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A guideline for reporting experimental protocols in life sciences

Olga giraldo.

1 Ontology Engineering Group, Campus de Montegancedo, Boadilla del Monte, Universidad Politécnica de Madrid, Madrid, Spain

Alexander Garcia

2 Technische Universität Graz, Graz, Austria

Oscar Corcho

Associated data.

• Dryad 2017. [7 July 2017]. Dryad homepage. http://datadryad.org/
• Figshare 2017. [7 July 2017]. Figshare. http://figshare.com
• Giraldo O, Garcia A, Corcho O. 2018a. Corpus of protocols [Data set] Zenodo. [ CrossRef ]
• Giraldo O, Garcia A, Corcho O. 2018b. Guidelines for reporting experimental protocols [Data set] Zenodo. [ CrossRef ]
• Giraldo O, Garcia A, Corcho O. 2018c. Survey—reporting an experimental protocol [Data set] Zenodo. [ CrossRef ]
• Gómez FL, Alexander, Giraldo O. 2018. SMARTProtocols/SMARTProtocols.github.io: first release of SMARTProtocols.github.io. Zenodo. [ CrossRef ]

The following information was supplied regarding data availability:

Federico López Gómez, Alexander Garcia & Olga Giraldo. (2018, March 26). SMARTProtocols/SMARTProtocols.github.io: First release of SMARTProtocols.github.io (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.1207846 .

Olga Giraldo. (2018, March 22). oxgiraldo/SMART-Protocols: First release of SMART-Protocols repository (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.1205247 .

Olga Giraldo, Alexander Garcia, & Oscar Corcho. (2018). Survey - reporting an experimental protocol [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1204916 .

Olga Giraldo, Alexander Garcia, & Oscar Corcho. (2018). Guidelines for reporting experimental protocols [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1204887 .

Olga Giraldo, Alexander Garcia, & Oscar Corcho. (2018). Corpus of protocols [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1204838 .

Experimental protocols are key when planning, performing and publishing research in many disciplines, especially in relation to the reporting of materials and methods. However, they vary in their content, structure and associated data elements. This article presents a guideline for describing key content for reporting experimental protocols in the domain of life sciences, together with the methodology followed in order to develop such guideline. As part of our work, we propose a checklist that contains 17 data elements that we consider fundamental to facilitate the execution of the protocol. These data elements are formally described in the SMART Protocols ontology. By providing guidance for the key content to be reported, we aim (1) to make it easier for authors to report experimental protocols with necessary and sufficient information that allow others to reproduce an experiment, (2) to promote consistency across laboratories by delivering an adaptable set of data elements, and (3) to make it easier for reviewers and editors to measure the quality of submitted manuscripts against an established criteria. Our checklist focuses on the content, what should be included. Rather than advocating a specific format for protocols in life sciences, the checklist includes a full description of the key data elements that facilitate the execution of the protocol.

Introduction

Experimental protocols are fundamental information structures that support the description of the processes by means of which results are generated in experimental research ( Giraldo et al., 2017 ; Freedman, Venugopalan & Wisman, 2017 ). Experimental protocols, often as part of “Materials and Methods” in scientific publications, are central for reproducibility; they should include all the necessary information for obtaining consistent results ( Casadevall & Fang, 2010 ; Festing & Altman, 2002 ). Although protocols are an important component when reporting experimental activities, their descriptions are often incomplete and vary across publishers and laboratories. For instance, when reporting reagents and equipment, researchers sometimes include catalog numbers and experimental parameters; they may also refer to these items in a generic manner, e.g., “ Dextran sulfate, Sigma-Aldrich ” ( Karlgren et al., 2009 ). Having this information is important because reagents usually vary in terms of purity, yield, pH, hydration state, grade, and possibly additional biochemical or biophysical features. Similarly, experimental protocols often include ambiguities such as “ Store the samples at room temperature until sample digestion ” ( Brandenburg et al., 2002 ); but, how many Celsius degrees? What is the estimated time for digesting the sample? Having this information available not only saves time and effort, it also makes it easier for researchers to reproduce experimental results; adequate and comprehensive reporting facilitates reproducibility ( Freedman, Venugopalan & Wisman, 2017 ; Baker, 2016 ).

Several efforts focus on building data storage infrastructures, e.g., 3TU. Datacentrum ( 4TU, 2017 ), CSIRO Data Access Portal ( CSIRO, 2017 ), Dryad ( Dryad, 2017 ), figshare ( Figshare, 2017 ), Dataverse ( King, 2007 ) and Zenodo ( Zenodo, 2017 ). These data repositories make it possible to review the data and evaluate whether the analysis and conclusions drawn are accurate. However, they do little to validate the quality and accuracy of the data itself. Evaluating research implies being able to obtain similar, if not identical results. Journals and funders are now asking for datasets to be publicly available for reuse and validation. Fully meeting this goal requires datasets to be endowed with auxiliary data providing contextual information e.g., methods used to derive such data ( Assante et al., 2016 ; Simmhan, Plale & Gannon, 2005 ). If data must be public and available, shouldn’t methods be equally public and available?

Illustrating the problem of adequate reporting, Moher et al. (2015) have pointed out that fewer than 20% of highly-cited publications have adequate descriptions of study design and analytic methods. In a similar vein, Vasilevsky et al. (2013) showed that 54% of biomedical research resources such as model organisms, antibodies, knockdown reagents (morpholinos or RNAi), constructs, and cell lines are not uniquely identifiable in the biomedical literature, regardless of journal Impact Factor. Accurate and comprehensive documentation for experimental activities is critical for patenting, as well as in cases of scientific misconduct. Having data available is important; knowing how the data were produced is just as important. Part of the problem lies in the heterogeneity of reporting structures; these may vary across laboratories in the same domain. Despite this variability, we want to know which data elements are common and uncommon across protocols; we use these elements as the basis for suggesting our guideline for reporting protocols. We have analyzed over 500 published and non-published experimental protocols, as well as guidelines for authors from journals publishing protocols. From this analysis we have derived a practical adaptable checklist for reporting experimental protocols.

Efforts such as the Structured, Transparent, Accessible Reporting (STAR) initiative ( Marcus, 2016 ; Cell Press, 2017 ) address the problem of structure and standardization when reporting methods. In a similar manner, The Minimum Information about a Cellular Assay (MIACA) ( MIACA, 2017 ), The Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) ( Lee et al., 2008 ) and many other “minimal information” efforts deliver minimal data elements describing specific types of experiments. Soldatova et al. (2008) and Soldatova et al. (2014) proposes the EXACT ontology for representing experimental actions in experimental protocols; similarly, Giraldo et al. (2017) proposes the S e MA ntic R epresen T ation of Protocols ontology (henceforth SMART Protocols Ontology) an ontology for reporting experimental protocols and the corresponding workflows. These approaches are not minimal; they aim to be comprehensive in the description of the workflow, parameters, sample, instruments, reagents, hints, troubleshooting, and all the data elements that help to reproduce an experiment and describe experimental actions.

There are also complementary efforts addressing the problem of identifiers for reagents and equipment; for instance, the Resource Identification Initiative (RII) ( Force11, 2017 ), aims to help researchers sufficiently cite the key resources used to produce the scientific findings. In a similar vein, the Global Unique Device Identification Database (GUDID) ( NIH, 2018 ) has key device identification information for medical devices that have Unique Device Identifiers (UDI); the Antibody Registry ( Antibody Registry, 2018 ), gives researchers a way to universally identify antibodies used in their research, and also the Addgene web-application ( Addgene, 2018 ) makes it easy for researchers to identify plasmids. Having identifiers make it possible for researchers to be more accurate in their reporting by unequivocally pointing to the resource used or produced. The Resource Identification Portal ( RIP, 2018 ), makes it easier to navigate through available identifiers, researchers can search across all the sources from a single location.

In this paper, we present a guideline for reporting experimental protocols; we complement our guideline with a machine-processable checklist that helps researchers, reviewers and editors to measure the completeness of a protocol. Each data element in our guideline is represented in the SMART Protocols Ontology. This paper is organized as follows: we start by describing the materials and methods used to derive the resulting guidelines. In the “Results” section, we present examples indicating how to report each data element; a machine readable checklist in the JavaScript Object Notation (JSON) format is also presented in this section. We then discuss our work and present the conclusions.

Materials and Methods

We have analyzed: (i) guidelines for authors from journals publishing protocols ( Giraldo, Garcia & Corcho, 2018b ), (ii) our corpus of protocols ( Giraldo, Garcia & Corcho, 2018a ), (iii) a set of reporting structures proposed by minimal information projects available in the FairSharing catalog ( McQuilton et al., 2016 ), and (iv) relevant biomedical ontologies available in BioPortal ( Whetzel et al., 2011 ) and Ontobee ( Xiang et al., 2011 ). Our analysis was carried out by a domain expert, Olga Giraldo; she is an expert in text mining and biomedical ontologies with over ten years of experience in laboratory techniques. All the documents were read, and then data elements, subject areas, materials (e.g., sample, kits, solutions, reagents, etc.), and workflow information were identified. Resulting from this activity we established a baseline terminology, common and non common data elements, as well as patterns in the description of the workflows (e.g., information describing the steps and the order for the execution of the workflow).

Instructions for authors from analyzed journals

Publishers usually have instructions for prospective authors; these indications tell authors what to include, the information that should be provided, and how it should be reported in the manuscript. In Table 1 we present the list of guidelines that were analyzed.

Corpus of protocols

Our corpus includes 530 published and unpublished protocols. Unpublished protocols (75 in total) were collected from four laboratories located at the International Center for Tropical Agriculture (CIAT) ( CIAT, 2017 ). The published protocols (455 in total) were gathered from the repository “Nature Protocol Exchange” ( NPE, 2017 ) and from 11 journals, namely: BioTechniques, Cold Spring Harbor Protocols, Current Protocols, Genetics and Molecular Research ( GMR, 2017 ), JoVE, Plant Methods ( BioMed Central, 2017 ), Plos One ( PLOS ONE, 2017 ), Springer Protocols, MethodsX, Bio-Protocol and the Journal of Biological Methods. The analyzed protocols comprise areas such as cell biology, molecular biology, immunology, and virology. The number of protocols from each journal is presented in Table 2 .

Minimum information standards and ontologies

We analyzed minimum information standards from the FairSharing catalog, e.g., MIAPPE ( MIAPPE, 2017 ), MIARE ( MIARE, 2017 ) and MIQE ( Bustin et al., 2009 ). See Table 3 for the complete list of minimum information models that we analyzed.

We paid special attention to the recommendations indicating how to describe specimens, reagents, instruments, software and other entities participating in different types of experiments. Ontologies available at Bioportal and Ontobee were also considered; we focused on ontologies modeling domains, e.g., bioassays (BAO), protocols (EXACT), experiments and investigations (OBI). We also focused on those modeling specific entities, e.g., organisms (NCBI Taxon), anatomical parts (UBERON), reagents or chemical compounds (ERO, ChEBI), instruments (OBI, BAO, EFO). The list of analyzed ontologies is presented in Table 4 .

Methods for developing this guideline

Developing the guideline entailed a series of activities; these were organized in the following stages: (i) analysis of guidelines for authors, (ii) analysis of protocols, (iii) analysis of Minimum Information (MI) standards and ontologies, and (iv) evaluation of the data elements from our guideline. For a detailed representation of our workflow, see Fig. 1

Analyzing guidelines for authors

We manually reviewed instructions for authors from nine journals as presented in Table 1 . In this stage (step A in Fig. 1 ), we identified bibliographic data elements classified as “desirable information” in the analyzed guidelines. See Table 5 .

In addition, we identified the rhetorical elements. These have been categorized in the guidelines for authors as: (i) required information (R), must be submitted with the manuscript; (ii) desirable information (D), should be submitted if available; and (iii) optional (O) or extra information. See Table 6 for more details.

Analyzing the protocols

In 2014, we started by manually reviewing 175 published and unpublished protocols; these were from domains such as cell biology, biotechnology, virology, biochemistry and pathology. From this collection, 75 are unpublished protocols and thus not available in the dataset for this paper. These unpublished protocols were collected from four laboratories located at the CIAT. In 2015, our corpus grew to 530; we included 355 published protocols gathered from one repository and eleven journals as listed in Table 2 . Our corpus of published protocols is: (i) identifiable, i.e., each document has a Digital Object Identifier (DOI) and (ii) in disciplines and areas related to the expertise provided by our domain experts, e.g., virology, pathology, biochemistry, biotechnology, plant biotechnology, cell biology, molecular and developmental biology and microbiology. In this stage, step B in Fig. 1 , we analyzed the content of the protocols; theory vs. practice was our main concern. We manually verified if published protocols were following the guidelines; if not, what was missing , what additional information was included? We also reviewed common data elements in unpublished protocols.

Analyzing minimum information standards and ontologies

Biomedical sciences have an extensive body of work related to minimum information standards and reporting structures, e.g., those from the FairSharing initiative. We were interested in determining whether there was any relation to these resources. Our checklist includes the data elements that are common across these resources. We manually analyzed standards such as MIQE, used to describe qPCR assays; we also looked into MIACA, it provides guidelines to report cellular assays; ARRIVE, which provides detailed descriptions of experiments on animal models and MIAPPE, addressing the descriptions of experiments for plant phenotyping. See Table 3 for a complete list of the standards that we analyzed. Metadata, data, and reporting structures in biomedical documents are frequently related to ontological concepts. We also looked into relations between data elements and biomedical ontologies available in BioPortal and Ontobee. We focused on ontologies representing materials that are often found in protocols; for instance, organisms, anatomical parts (e.g., CLO, UBERON, NCBI Taxon), reagents or chemical compounds (e.g., ChEBI, ERO), and equipment (e.g., OBI, BAO, EFO). The complete list of the ontologies that we analyzed is presented in Table 4 .

Generating the first draft

The first draft is the main output from the initial analysis of instructions for authors, experimental protocols, MI standards and ontologies, see (step D in Fig. 1 ). The data elements were organized into four categories: bibliographic data elements such as title, authors; descriptive data elements such as purpose, application; data elements for materials, e.g., sample, reagents, equipment; and data elements for procedures, e.g., critical steps, Troubleshooting. The role of the authors, provenance and properties describing the sample (e.g., organism part, amount of the sample, etc.) were considered in this first draft. In addition properties like “name”, “manufacturer or vendor” and “identifier” were proposed to describe equipment, reagents and kits.

Evaluation of data elements by domain experts

This stage entailed three activities. The first activity was carried out at CIAT with the participation of 19 domain experts in areas such as virology, pathology, biochemistry, and plant biotechnology. The input of this activity was the checklist V. 0.1 (see step E in Fig. 1 ). This evaluation focused on “ What information is necessary and sufficient for reporting an experimental protocol? ”; the discussion also addressed data elements that were not initially part of guidelines for authors -e.g., consumables. The result of this activity was the version 0.2 of the checklist; domain experts suggested to use an online survey for further validation. This survey was designed to enrich and validate the checklist V. 0.2. We used a Google survey that was circulated over mailing lists; participants did not have to disclose their identity (see step F in Fig. 1 ). A final meeting was organized with those who participated in workshops, as well as in the survey (23 in total) to discuss the results of the online poll. The discussion focused on the question: Should the checklist include data elements not considered by the majority of participants? Participants were presented with use cases where infrequent data elements are relevant in their working areas. It was decided to include all infrequent data elements; domain experts concluded that this guideline was a comprehensive checklist a opposed to a minimal information. Also, after discussing infrequent data elements it was concluded that the importance of a data element should not bear a direct relation to its popularity. The analogy used was that of an editorial council; some data elements needed to be included regardless of the popularity as an editorial decision. The output of this activity was the checklist V. 1.0. The survey and its responses are available at ( Giraldo, Garcia & Corcho, 2018c ). This current version includes a new bibliographic element “license of the protocol”, as well as the property “equipment configuration” associated to the datum equipment. The properties: alternative, optional and parallel steps were added to describe the procedure. In addition, the datum “PCR primers” was removed from the checklist, it is specific and therefore should be the product of a community specialization as opposed to part of a generic guideline.

Our results are summarized in Table 7 ; it includes all the data elements resulting from the process illustrated in Fig. 1 . We have also implemented our checklist as an online tool that generates data in the JSON format and presents an indicator of completeness based on the checked data elements; the tool is available at https://smartprotocols.github.io/checklist1.0 ( Gómez, alexander & Giraldo, 2018 ). Below, we present a complete description of the data elements in our checklist. We have organized the data elements in four categories, namely: (i) bibliographic data elements, (ii) discourse data elements, (iii) data elements for materials, and iv) data elements for the procedure. Ours is a comprehensive checklist, the data elements must be reported whenever applicable.

Bibliographic data elements

From the guidelines for authors, the datum “author identifier” was not considered, nor was this data element found in the analyzed protocols. The “provenance” is proposed as “desirable information” in only two of the guidelines (Nature Protocols and Bio-protocols), as well as “updates of the protocol” (Cold Spring Harbor Protocols and Bio-protocols). A total of 72.5% (29) of the protocols available in our Bio-protocols collection and 61.5% (24) of the protocols available in our Nature Protocols Exchange collection reported the provenance ( Fig. 2 ). None of the protocols collected from Cold Spring Harbor Protocols or Bio-protocols had been updated–last checked December 2017.

NC, Not Considered in guidelines; D, Desirable information if this is available.

As a result of the workshops, domain experts exposed the importance of including these three data elements in our checklist. For instance, readers sometimes need to contact the authors to ask about specific information (quantity of the sample used, the storage conditions of a solution prepared in the lab, etc.); occasionally, the correspondent author does not respond because he/she has changed his/her email address, and searching for the full name could retrieve multiple results. By using author IDs, this situation could be resolved. The experts asserted that well-documented provenance helps them to know where the protocol comes from and whether it has changed. For example, domain experts expressed their interest in knowing where a particular protocol was published for the first time, who has reused it, how many research papers have used it, how many people have modified it, etc. In a similar way, domain experts also expressed the need for a version control system that could help them to know and understand how, where and why the protocol has changed. For example, researchers are interested in tracking changes in quantities, reagents, instruments, hints, etc. For a complete description of the bibliographic data elements proposed in our checklist, see below.

Title. The title should be informative, explicit, and concise (50 words or fewer). The use of ambiguous terminology and trivial adjectives or adverbs (e.g., novel, rapid, efficient, inexpensive, or their synonyms) should be avoided. The use of numerical values, abbreviations, acronyms, and trademarked or copyrighted product names is discouraged. This definition was adapted from BioTechniques ( Giraldo, Garcia & Corcho, 2018b ). In Table 8 , we present examples illustrating how to define the title.

Issues in the ambiguous tittle:

Author name and author identifier. The full name(s) of the author(s) is required together with an author ID, e.g., ORCID ( ORCID, 2017 ) or research ID ( ResearcherID, 2017 ). The role of each author is also required; depending on the domain, there may be several roles. It is important to use a simple word that describes who did what. Publishers, laboratories, and authors should enforce the use of an “author contribution section” to identify the role of each author. We have identified two roles that are common across our corpus of documents.

• • Creator of the protocol: This is the person or team responsible for the development or adaptation of a protocol.
• • Laboratory-validation scientist: Protocols should be validated in order to certify that the processes are clearly described; it must be possible for others to follow the described processes. If applicable, statistical validation should also be addressed. The validation may be procedural (related to the process) or statistical (related to the statistics). According to the Food and Drug Administration (FDA) ( FDA, 2017 ), validation is “ establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its predetermined specifications and quality attributes ” ( Das, 2011 ).

Updating the protocol. The peer-reviewed and non peer-reviewed repositories of protocols should encourage authors to submit updated versions of their protocols; these may be corrections, retractions, or other revisions. Extensive modifications to existing protocols could be published as adapted versions and should be linked to the original protocol. We recommended to promote the use of a version control system; in this paper we suggest to use the version control guidelines proposed by the National Institute of Health (NIH) ( NIH, 2017 ).

• • Document dates: Suitable for unpublished protocols. The date indicating when the protocol was generated should be in the first page and, whenever possible, incorporated into the header or footer of each page in the document.
• – Draft document version number: Suitable for unpublished protocols. The first draft of a document will be Version 0.1. Subsequent drafts will have an increase of “0.1” in the version number, e.g., 0.2, 0.3, 0.4, ... 0.9, 0.10, 0.11.
• – Final document version number and date: Suitable for unpublished and published protocols. The author (or investigator) will deem a protocol final after all reviewers have provided final comments and these have been addressed. The first final version of a document will be Version 1.0; the date when the document becomes final should also be included. Subsequent final documents will have an increase of “1.0” in the version number (1.0, 2.0, etc.).
• • Documenting substantive changes: Suitable for unpublished and published protocols. A list of changes from the previous drafts or final documents will be kept. The list will be cumulative and identify the changes from the preceding document versions so that the evolution of the document can be seen. The list of changes and consent/assent documents should be kept with the final protocol.

Provenance of the protocol. The provenance is used to indicate whether or not the protocol results from modifying a previous one. The provenance also indicates whether the protocol comes from a repository, e.g., Nature Protocols Exchange, protocols.io ( Teytelman et al., 2016 ), or a journal like JoVE, MethodsX, or Bio-Protocols. The former refers to adaptations of the protocol. The latter indicates where the protocol comes from. See Table 9 .

License of the protocol. The protocols should include a license. Whether as part of a publication or, just as an internal document, researchers share, adapt and reuse protocols. The terms of the license should facilitate and make clear the legal framework for these activities.

Data elements of the discourse

Here, we present the elements considered necessary to understand the suitability of a protocol. They are the “overall objective or purpose”, “applications”, “advantages,” and “limitations”. 100% of the analyzed guidelines for author suggest the inclusion of these four elements in the abstract or introduction section. However, one or more of these four elements were not reported. For example, “limitations” was reported in only 20% of the protocols from Genetic and Molecular Research and PLOS One, and in 40% of the protocols from Springer. See Fig. 3 .

Interestingly, 83% of the respondents considered the “limitations” to be a data element that is necessary when reporting a protocol. In the last meeting, participants considered that “limitations” represents an opportunity to make suggestions for further improvements. Another data element discussed was “advantages”; 43% of the respondents considered the “advantages” as a data element that is necessary to be reported in a protocol. In the last meeting, all participants agreed that “advantages” (where applicable) could help us to compare a protocol with other alternatives commonly used to achieve the same result. For a complete description of the discourse data elements proposed in our checklist, see below.

Overall objective or Purpose. The description of the objective should make it possible for readers to decide on the suitability of the protocol for their experimental problem. See Table 10 .

Application of the protocol. This information should indicate the range of techniques where the protocol could be applied. See Table 10 .

Advantage(s) of the protocol. Here, the advantages of a protocol compared to other alternatives should be discussed. See Table 10 . Where applicable, references should be made to alternative methods that are commonly used to achieve the same result.

Limitation(s) of the protocol. This datum includes a discussion of the limitations of the protocol. This should also indicate the situations in which the protocol could be unreliable or unsuccessful. See Table 10 .

Data elements for materials

From the analyzed guidelines for authors, the datum “sample description” was considered only in the Current Protocols guidelines. The “laboratory consumables or supplies” datum was not included in any of the analyzed guidelines. See Fig. 4 .

NC, Not Considered in guidelines; D, Desirable information if this is available; R, Required information.

Our Current Protocols collection includes documents about toxicology, microbiology, magnetic resonance imaging, cytometry, chemistry, cell biology, human genetics, neuroscience, immunology, pharmacology, protein, and biochemistry; for these protocols the input is a biological or biochemical sample. This collection also includes protocols in bioinformatics with data as the input. 100% of the protocols from our Current Protocols collection includes information about the input of the protocol (biological/biochemical sample or data). In addition, 87% of protocols from this collection include a list of materials or resources (reagents, equipment, consumables, software, etc.).

We also analyzed the protocols from our MethodsX collection. We found that despite the exclusion of the sample description in guidelines for authors, the authors included this information in their protocols. Unfortunately, these protocols do not include a list of materials. Only 29% of the protocols reported a partial list of materials. For example, the protocol published by Vingataramin & Frost (2015) , includes a list of recommended equipment but does not list any of the reagents, consumables, or other resources mentioned in the protocol instructions. See Fig. 5 .

Domain experts considered that the input of the protocol (biological/biochemical sample or data) needs an accurate description; the granularity of the description varies depending on the domain. If such description is not available then the reproducibility could be affected. In addition, domain experts strongly suggested to include consumables in the checklist. It was a general surprise not to find these data elements in the guidelines for authors that we analyzed. Domain experts shared with us bad experiences caused by the lack of information about the type of consumables. Some of the incidents that may arise from the lack of this information include: (i) cross contamination, when no information suggesting the use of filtered pipet tips is available; (ii) misuse of containers, when no information about the use of containers resistant to extreme temperatures and/or impacts is available; (iii) misuse of containers, when a container made of a specific material should be used, e.g., glass vs. plastic vs. metal. This is critical information; researchers need to know if reagents or solutions prepared in the laboratory require some specific type of containers in order to avoid unnecessary reactions altering the result of the assay. Presented below is the set of data elements related to materials or resources used for carrying out the execution of a protocol.

Sample. This is the role played by a biological substance; the sample is an experimental input to a protocol. The information required depends on the type of sample being described and the requirements from different communities. Here, we present the data elements for samples commonly used across the protocols and guidelines that we analyzed.

• Strain, genotype or line: This datum is about subspecies such as ecotype, cultivar, accession, or line. In the case of crosses or breeding results, pedigree information should also be provided.
• – whole organism Typical examples are multicellular animals, plants, and fungi; or unicellular microorganisms such as a protists, bacteria, and archaea.
• – organism part Typical examples of an organism part include a cell line, a tissue, an organ, corporal bodily fluids protoplasts, nucleic acids, proteins, etc.
• – organism/sample identifier This is the unique identifier assigned to an organism. The NCBI taxonomy id, also known as “taxid”, is commonly used to identify an organism; the Taxonomy Database is a curated classification and nomenclature for all organisms in the public sequence databases. Public identification systems, e.g., the Taxonomy Database, should be used when ever possible. Identifiers may be internal; for instance, laboratories often have their own coding system for generating identifiers. When reporting internal identifiers it is important to also state the source and the nature (private or pubic) of the identifier, e.g., A0928873874, barcode (CIAT-DAPA internal identifier) of a specimen or sample.
• Amount of Bio-Source: This datum is about mass (mg fresh weight or mg dry weight), number of cells, or other measurable bulk numbers (e.g., protein content).
• Developmental stage: This datum includes age and gender (if applicable) of the organism.
• Bio-source Supplier: This datum is defined as a person, company, laboratory or entity that offers a variety of biosamples or biospecimens.
• Growth substrates: This datum refers to an hydroponic system (type, supplier, nutrients, concentrations), soil (type, supplier), agar (type, supplier), and cell culture (media, volume, cell number per volume).
• Growth environment: This datum includes, but is not limited to, controlled environments such as greenhouse (details on accuracy of control of light, humidity, and temperature), housing conditions (light/dark cycle), and non-controlled environments such as the location of the field trial.
• Growth time: This datum refers to the growth time of the sample prior to the treatment.
• • Sample pre-treatment or sample preparation: This datum refers to collection, transport, storage, preparation (e.g., drying, sieving, grinding, etc.), and preservation of the sample.

Laboratory equipment. The laboratory equipment includes apparatus and instruments that are used in diagnostic, surgical, therapeutic, and experimental procedures. In this subsection, all necessary equipment should be listed; manufacturer name or vendor (including the homepage), catalog number (or model), and configuration of the equipment should be part of this data element. See Table 11 .

• • Laboratory equipment name: This datum refers to the name of the equipment as it is given by the manufacturer (e.g., FocalCheck fluorescence microscope test slide).
• • Manufacturer name: This datum is defined as a person, company, or entity that produces finished goods (e.g., Life Technologies, Zeiss).
• • Laboratory equipment ID (model or catalog number): This datum refers to an identifier provided by the manufacturer or vendor (e.g., {"type":"entrez-nucleotide","attrs":{"text":"F36909","term_id":"4822535","term_text":"F36909"}} F36909 —catalog number for FocalCheck fluorescence microscope test slide from Life Technologies).
• • Equipment configuration: This datum should explain the configuration of the equipment and the parameters that make it possible to carry out an operation, procedure, or task (e.g., the configuration of an inverted confocal microscope).

Laboratory consumables or supplies. The laboratory consumables include, amongst others, disposable pipettes, beakers, funnels, test tubes for accurate and precise measurement, disposable gloves, and face masks for safety in the laboratory. In this subsection, a list with all the consumables necessary to carry out the protocol should be presented with manufacturer name (including the homepage) and catalog number. See Table 12 .

• • Laboratory consumable name: This datum refers to the name of the laboratory consumable as it is given by the manufacturer e.g., Cryogenic Tube, sterile, 1.2 ml.
• • Manufacturer name: This datum is defined as a person, enterprise, or entity that produces finished goods (e.g., Nalgene, Thermo-scientific, Eppendorf, Falcon)
• • Laboratory consumable ID (catalog number): This datum refers to an identifier provided by the manufacturer or vendor; for instance, 5000-0012 (catalog number for Cryogenic Tube, sterile, 1.2 mL from Nalgene).

Recipe for solutions. A recipe for solutions is a set of instructions for preparing a particular solution, media, buffer, etc. The recipe for solutions should include the list of all necessary ingredients (chemical compounds, substance, etc.), initial and final concentrations, pH, storage conditions, cautions, and hints. Ready-to-use reagents do not need to be listed in this category; all purchased reagents that require modification (e.g., a dilution or addition of β -mercaptoethanol) should be listed. See Table 13 for more information.

• • Solution name: This is the name of the preparation that has at least 2 chemical substances, one of them playing the role of solvent and the other playing the role of solute. If applicable, the name should include the following information: concentration of the solution, final volume and final pH. For instance, Ammonium bicarbonate (NH4HCO3), 50 mM, 10 ml, pH 7.8.
• • Chemical compound name or reagent name: This is the name of a drug, solvent, chemical, etc.; for instance, agarose, dimethyl sulfoxide (DMSO), phenol, sodium hydroxide. If applicable, a measurable property, e.g., concentration, should be included.
• • Initial concentration of a chemical compound: This is the first measured concentration of a compound in a substance.
• • Final concentration of chemical compound: This is the last measured concentration of a compound in a substance.
• • Storage conditions: This datum includes, among others, shelf life (maximum storage time) and storage temperature for the solutions e.g., “Store the solution at room temperature”, “maximum storage time, 6 months”. Specify whether or not the solutions must be prepared fresh.
• • Cautions: Toxic or harmful chemical compounds should be identified by the word ‘CAUTION’ followed by a brief explanation of the hazard and the precautions that should be taken when handling e.g., “CAUTION: NaOH is a very strong base. Can seriously burn skin and eyes. Wear protective clothing when handling. Make in fume hood”.
• • Hints: The “hints” are commentaries or “tips” that help the researcher to correctly prepare the recipe e.g., “Add NaOH to water to avoid splashing”.

Reagents. A reagent is a substance used in a chemical reaction to detect, measure, examine, or produce other substances. List all the reagents used when performing the protocol, the vendor name (including homepage), and catalog number. Reagents that are purchased ready-to-use should be listed in this section. See Table 14 .

• • Reagent name: This datum refers to the name of the reagent or chemical compound. For instance, “Taq DNA Polymerase from Thermus aquaticus with 10X reaction buffer without MgCl2”.
• • Reagent vendor or manufacturer: This is the person, enterprise, or entity that produces chemical reagents e.g., Sigma-Aldrich.
• • Reagent ID (catalog number): This is an identifier provided by the manufacturer or vendor. For instance, D4545-250UN (catalog number for Taq DNA Polymerase from Thermus aquaticus with 10X reaction buffer without MgCl2 from Sigma-Aldrich).

Kits. A kit is a gear consisting of a set of articles or tools for a specific purpose. List all the kits used when carrying out the protocol, the vendor name (including homepage), and catalog number.

• • Kit name: This datum refers to the name of the kit as it is given by the manufacturer e.g., Spectrum Plant Total RNA Kit, sufficient for 50 purifications.
• • Kit vendor or manufacturer: This is the person, enterprise, or entity that produces the kit e.g., Sigma-Aldrich.
• • Kit ID (catalog number): This is an identifier provided by the manufacturer or vendor e.g., STRN50, catalog number for Spectrum ™ Plant Total RNA Kit, sufficient for 50 purifications.

Software. Software is composed of a series of instructions that can be interpreted or directly executed by a processing unit. In this subsection, please list software used in the experiment including the version, as well as where to obtain it.

• • Software name: This datum refers to the name of the software. For instance, “LightCycler 480 Software”.
• • Software version: A software version number is an attribute that represents the version of software e.g., Version 1.5.
• • Software availability: This datum should indicate where the software can be downloaded from. If possible, license information should also be included; for instance, https://github.com/MRCIE-U/ariesmqtl, GPL3.0.

Data elements for the procedure

All the analyzed guidelines include recommendations about how to document the instructions; for example, list the steps in numerical order, use active tense, organize the procedures in major stages, etc. However, information about documentation of alternative, optional, or parallel steps (where applicable) and alert messages such as critical steps, pause point, and execution time was infrequent (available in less than 40% of the guidelines). See Fig. 6 .

NC, Not Considered in guidelines; O, Optional information; D, Desirable information if this is available; R, Required information.

We chose a subset of protocols (12 from our Plant Methods collection, 7 from our Biotechniques collection, and five unpublished protocols from CIAT) to review which data elements about the procedure were documented. 100% of the protocols have steps organized in major stages. 100% of the unpublished protocols list the steps in numerical order, and nearly 60% of the protocols from Plant Methods and Biotechniques followed this recommendation. Alert messages were included in 67% of the Plant Methods protocols and in 14% of the Biotechniques protocols. Neither of the five unpublished protocols included alert messages. Troubleshooting was reported in just a few protocols; this datum was available in 8% of the Plant Methods protocols and in 14% of the Biotechniques protocols. See Fig. 7 .

In this stage, the discussion with domain experts started with the description of steps. In some protocols, the steps are poorly described; for instance, some of them include working temperatures, e.g., cold room, on ice, room temperature; but, what exactly do they mean? Steps involving centrifugation, incubation, washing, etc., should specify conditions, e.g., time, temperature, speed (rpm or g), number of washes, etc. For experts, alert messages and troubleshooting (where applicable) complement the description of steps and facilitate a correct execution. This opinion coincides with the results of the survey, where troubleshooting and alert messages such as critical steps, pause points, and timing were considered relevant by 83%–87% of the respondents. The set of data elements related to the procedure is presented below.

• • Recommendation 1. Whenever possible, list the steps in numerical order; use active tense. For example: “Pipette 20 ml of buffer A into the flask,” as opposed to “20 ml of buffer A are/were pipetted into the flask” ( Nature Protocols, 2012 ).
• • Recommendation 2. Whenever there are two or more alternatives, these should be numbered as sets of consecutive steps Wiley’s Current Protocols (2012) . For example: “Choose procedure A (steps 1–10) or procedure B (steps 11–20); then continue with step 21 . . .”. Optional steps or steps to be executed in parallel should also be included.
• • Recommendation 3. For techniques comprising a number of individual procedures, organize these in the exact order in which they should be executed ( Nature Protocols, 2012 ).
• – Frozen/deep-freeze temperature (−20 °C to −15 °C)
• – Refrigerator, cold room or cold temperature (2 °C to 8 °C)
• – Cool temperature (8 °C to 15 °C)
• – Room/Ambient temperature (15 °C to 25 °C)
• – Warm/Lukewarm temperature (30 °C to 40 °C)

For centrifugation steps, specify time, temperature, and speed (rpm or g). Always state whether to discard/keep the supernatant/pellet. For incubations, specify time, temperature, and type of incubator. For washes, specify conditions e.g., temperature, washing solution and volume, specific number of washes, etc.

Useful auxiliary information should be included in the form of “alert messages”. The goal is to remind or alert the user of a protocol with respect to issues that may arise when executing a step. These messages may cover special tips or hints for performing a step successfully, alternate ways to perform the step, warnings regarding hazardous materials or other safety conditions, time considerations. For instance, pause points, speed at which the step must be performed and storage information (temperature, maximum duration) ( Wiley’s Current Protocols, 2012 ).

• • Pause point: This datum is appropriate after steps in the protocol where the procedure can be stopped. i.e., when the experiment can be stopped and resumed at a later point in time. Any PAUSE POINTS should be indicated with a brief description of the options available. See Table 15 .
• • Timing: This datum is used to include the approximate time of execution of a step or set of steps. Timing could also be indicated at the beginning of the protocol. See Table 15 .
• • Hints: Provide any commentary, note, or hints that will help the researcher to correctly perform the protocol. See Table 15 .
• • Troubleshooting: This datum is used to list common problems, possible causes, and solutions/methods of correction. This can be submitted as a 3-column table or listed in the text. An example is presented in “Table 1.Troubleshooting table”, available at Rohland & Hofreiter (2007) .

Data Elements Represented in the SMART Protocols Ontology

The data elements proposed in our guideline are represented in the SMART Protocols Ontology. This ontology was developed to facilitate the semantic representation of experimental protocols. Our ontology reuses the Basic Formal Ontology (BFO) ( IFOMIS, 2018 ) and the Relation Ontology (RO) ( Smith et al., 2005 ) to characterize concepts. In addition, each term in the SMART Protocols ontology is represented with annotation properties imported from the OBI Minimal metadata. The classes and properties are represented by their respective labels to facilitate the readability; the prefix indicates the provenance for each term. Our ontology is organized in two modules. The document module represents the metadata necessary and sufficient for reporting a protocol. The workflow module represents the executable elements of a protocol to be carried out and maintained by humans. Figure 8 presents the hierarchical organization of data elements into the SMART Protocols Ontology.

In this paper, we have described 17 data elements that can be used to improve the reporting structure of protocols. Our work is based on the analysis of 530 published and non-published protocols, guidelines for authors, and suggested reporting structures. We examined guidelines for authors from journals that specialize in publishing experimental protocols, e.g., Bio-protocols, Cold Spring Harbor Protocols, MethodsX, Nature Protocols, and Plant Methods (Methodology). Although JoVE ( JoVE, 2017 ) is a video methods journal, its guidelines for authors were also considered. Online repositories were also studied; these resources deliver an innovative approach for the publication of protocols by offering platforms tailored for this kind of document. For instance, protocols.io ( protocols.io, 2018 ) structures the protocol by using specific data elements and treats the protocol as a social object, thus facilitating sharing. It also makes it possible to have version control over the document. Protocol Exchange from Nature Protocols is an open repository where users upload, organize, comment, and share their protocols. Our guideline has also benefited from the input from a group of researchers whose primary interest is having reproducible protocols. By analyzing reporting structures and guidelines for authors, we are contributing to the homogenization of data elements that should be reported as part of experimental protocols. Improving the reporting structure of experimental protocols will add the necessary layer of information that should accompany the data that is currently being deposited into data repositories.

Ours was an iterative development process; drafts were reviewed and analyzed, and then improved versions were produced. This made it easier for us to make effective use of the time that domain experts had available. Working with experimental protocols that were known by our group of domain experts helped us to engage them in the iterations. Also, for the domain experts who worked with us during the workshops, there was a pre-existing interest in standardizing their reporting structures. Reporting guidelines are not an accepted norm in biology ( MIBBI, 2017 ); however, experimental protocols are part of the daily activities for most biologists. They are familiar with these documents, the benefits of standardization are easy for them to understand. From our experience at CIAT, once researchers were presented with a standardized format that they could extend and manage with minimal overhead, they adopted it. The early engagement with domain experts in the development process eased the initial adoption; they were familiar with the outcome and aware of the advantages of implementing this practice. However, maintaining the use of the guideline requires more than just availability of the guideline; the long-term use of these instruments requires an institutional policy in data stewardship. Our approach builds upon previous experiences; in our case, the guidelines presented in this paper are a tool that was conceived by researchers as part of their reporting workflow, thus adding a minimal burden on their workload. As domain experts were working with the guideline, they were also gaining familiarity with the Minimum Information for Biological and Biomedical Investigations (MIBBI) ( MIBBI, 2017 ) that were applicable to their experiments. This made it possible for us to also discuss the relation between MIBBIs and the content in the experimental protocols.

The quality of the information reported in experimental protocols and methods is a general cause for concern. Poorly described methods generate poorly reproducible research. In a study conducted by Flórez-Vargas et al. (2014) in Trypanosoma experiments, they report that none of the investigated articles met all the criteria that should be reported in these kinds of experiments. The study reported by Kilkenny et al. (2009) has similar results leading to similar conclusions; key metadata elements are not always reported by researchers. The widespread availability of key metadata elements in ontologies, guidelines, minimal information models, and reporting structures was discussed. These were, from the onset, understood as reusable sources of information. Domain experts understand that they were building on previous experiences; having examples of use is helpful in understanding how to adapt or reuse from existing resources. This helps them to understand the rationale of each data element within the context of their own practice. For us, being able to consult previous experiences was also an advantage. Sharing protocols is a common practice amongst researchers from within the same laboratories or collaborating in the same experiments or projects. However, there are limitations in sharing protocols, not necessarily related to the lack of reporting standards. They are, for instance, related to patenting and intellectual property issues, as well as to giving away competitive advantages implicit in the method.

During our development process, we considered the SMART Protocols ontology ( Giraldo et al., 2017 ); it reuses terminology from OBI, IAO, EXACT, ChEBI, NCBI taxonomy, and other ontologies. Our metadata elements have been mapped to the SMART Protocols ontology; the metadata elements in our guideline could also be mapped to resources on the web such as PubChem ( Kim et al., 2016 ) ( Wang et al., 2017 ) and the Taxonomy database from UniProt ( UniProt, 2017 ). Our implementation of the checklist illustrates how it could be used as an online tool to generate a complement to the metadata that is usually available with published protocols. The content of the protocol does not need to be displayed; key metadata elements are made available together with the standard bibliographic metadata. Laboratories could adapt the online tool to their specific reporting structures. Having a checklist made it easier for the domain experts to validate their protocols. Machine validation is preferable, but such mechanisms require documents to be machine-processable beyond that which our domain experts were able to generate. Domain experts were using the guideline to implement simple Microsoft Word reporting templates. Our checklist does not include aspects inherent to each possible type of experiment such as those available in the MIBBIs; these are based on the minimal common denominator for specific experiments. Both approaches complement each other; where MIBBIs offer specificity, our guideline provides a context that is general enough for facilitating reproducibility and adequate reporting without interfering with records such as those commonly managed by Laboratory Information Management Systems.

In laboratories, experimental protocols are released and periodically undergo revisions until they are released again. These documents follow the publication model put forward by Carole Goble, “ Don’t publish, release ” with strict versioning, changes, and forks ( Goble, 2017 ). Experimental protocols are essentially executable workflows for which identifiers for equipment, reagents, and samples need to be resolved against the Web. The use of unique identifiers can’t be underestimated when supporting adequate reporting; identifiers remove ambiguity for key resources and make it possible for software agents to resolve and enrich these entities. The workflows in protocols are mostly followed by humans, but in the future, robots may be executing experiments ( Yachie, Consortium & Natsume, 2017 ); it makes sense to investigate other publication paradigms for these documents. The workflow nature of these documents is more suitable for a fully machine-processable or -actionable document. The workflows should be intelligible for humans and processable by machines; thus, facilitating the transition to fully automated laboratory paradigms. Entities and executable elements should be declared and characterized from the onset. The document should be “born semantic” and thus inter-operable with the larger web of data. In this way post-publication and linguistic processing activities, such as Named Entity Recognition and annotation, could be more focused.

Currently, when protocols are published, they are treated like any other scientific publication. Little attention is paid to the workflow nature implicit in this kind of document, or to the chain of provenance indicating where it comes from and how it has changed. The protocol is understood as a text-based narrative instead of a self-descriptive Findable Accessible Interoperable and Reusable (FAIR) ( Wilkinson et al., 2016 ) compliant document. There are differences across the examined publications, e.g., JoVE builds the narrative around video, whereas Bio-protocols, MethodsX, Nature Protocols, and Plant Methods primarily rely on a text-based narrative. The protocol is, however, a particular type of publication; it is slightly different from other scientific articles. An experimental protocol is a document that is kept “alive” after it has been published. The protocols are routinely used in laboratory activities, and researchers often improve and adapt them, for instance, by extending the type of samples that can be tested, reducing timing, minimizing the quantity of certain reagents without altering the results, adding new recipes, etc. The issues found in reporting methods probably stem, at least in part, from the current structure of scientific publishing, which is not adequate to effectively communicate complex experimental methods ( Flórez-Vargas et al., 2014 ).

Experimental research should be reproducible whenever possible. Having precise descriptions of the protocols is a step in that direction. Our work addresses the problem of adequate reporting for experimental protocols. It builds upon previous work, as well as over an exhaustive analysis of published and unpublished protocols and guidelines for authors. There is value in guidelines because they indicate how to report; having examples of use facilitate how to adapt them. The guideline we present in this paper can be adapted to address the needs of specific communities. Improving reporting structures requires collective efforts from authors, peer reviewers, editors, and funding bodies. There is no “one size that fits all.” The improvement will be incremental; as guidelines and minimal information models are presented, they will be evaluated, adapted, and re-deployed.

Authors should be aware of the importance of experimental protocols in the research life-cycle. Experimental protocols ought to be reused and modified, and derivative works are to be expected. This should be considered by authors before publishing their protocols; the terms of use and licenses are the choice of the publisher, but where to publish is the choice of the author. Terms of use and licenses forbidding “reuse”, “reproduce”, “modify”, or “make derivative works based upon” should be avoided. Such restrictions are an impediment to the ability of researchers to use the protocols in their most natural way, which is adapting and reusing them for different purposes –not to mention sharing, which is a common practice among researchers. Protocols represent concrete “know-how” in the biomedical domain. Similarly, publishers should adhere to the principle of encouraging authors to make protocols available, for instance, as preprints or in repositories for protocols or journals. Publishers should enforce the use of repository or journal publishing protocols. Publishers require or encourage data to be available; the same principle should be applied to protocols. Experimental protocols are essential when reproducing or replicating an experiment; data is not contextualized unless the protocols used to derive the data are available.

This work is related to the SMART Protocols project. Ultimately we want: (1) to enable authors to report experimental protocols with necessary and sufficient information that allows others to reproduce an experiment, (2) to ensure that every data item is resolvable against resources in the web of data, and (3) to make the protocols available in RDF, JSON, and HTML as web native objects. We are currently working on a publication platform based on linked data for experimental protocols. Our approach is simple, we consider that protocols should be born semantics and FAIR.

Acknowledgments

Special thanks to the research staff at CIAT; in particular, we want to express our gratitude to those who participated in the workshops, survey and discussions. We also want to thank Melissa Carrion for her useful comments and proof-reading. Finally, we would like to thank the editor and reviewers (Leonid Teytelman, Philippe Rocca-Serra and Tom Gillespie) for their valuable comments and suggestions to improve the manuscript.

Funding Statement

This work was supported by the EU project Datos4.0 (No. C161046002). Olga Giraldo has been funded by the I+D+i pre doctoral grant from the UPM, and the Predoctoral grant from the I+D+i program from the Universidad Politécnica de Madrid. Alexander Garcia has been funded by the KOPAR project, H2020-MSCA-IF-2014, Grant Agreement No. 655009. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Additional Information and Declarations

The authors declare there are no competing interests.

Olga Giraldo conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.

Alexander Garcia contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft, alexander supervised the research and was a constant springboard for discussion and ideas wrt the checklist and methods.

Oscar Corcho reviewed drafts of the paper, and approved the final draft.

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• TECHNOLOGY FEATURE
• 06 September 2021
• Correction 09 September 2021

Five keys to writing a reproducible lab protocol

• Monya Baker

You can also search for this author in PubMed   Google Scholar

Every laboratory scientist has a horror story. The five-minute step they didn’t know they needed, which ended up costing them five months — or five years. Maybe it was swirling the plate as crowded cells were split between culture dishes. Or maybe the published protocol said to wash your sample once and heat thrice but meant the opposite, so that following the printed instructions destroyed the sample.

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Nature 597 , 293-294 (2021)

doi: https://doi.org/10.1038/d41586-021-02428-3

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Correction 09 September 2021 : An earlier version of this Technology feature gave the wrong name for the Reproducibility Project: Cancer Biology.

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Experimental Design – Types, Methods, Guide

Table of Contents

Experimental Design

Experimental design is a process of planning and conducting scientific experiments to investigate a hypothesis or research question. It involves carefully designing an experiment that can test the hypothesis, and controlling for other variables that may influence the results.

Experimental design typically includes identifying the variables that will be manipulated or measured, defining the sample or population to be studied, selecting an appropriate method of sampling, choosing a method for data collection and analysis, and determining the appropriate statistical tests to use.

Types of Experimental Design

Here are the different types of experimental design:

Completely Randomized Design

In this design, participants are randomly assigned to one of two or more groups, and each group is exposed to a different treatment or condition.

Randomized Block Design

This design involves dividing participants into blocks based on a specific characteristic, such as age or gender, and then randomly assigning participants within each block to one of two or more treatment groups.

Factorial Design

In a factorial design, participants are randomly assigned to one of several groups, each of which receives a different combination of two or more independent variables.

Repeated Measures Design

In this design, each participant is exposed to all of the different treatments or conditions, either in a random order or in a predetermined order.

Crossover Design

This design involves randomly assigning participants to one of two or more treatment groups, with each group receiving one treatment during the first phase of the study and then switching to a different treatment during the second phase.

Split-plot Design

In this design, the researcher manipulates one or more variables at different levels and uses a randomized block design to control for other variables.

Nested Design

This design involves grouping participants within larger units, such as schools or households, and then randomly assigning these units to different treatment groups.

Laboratory Experiment

Laboratory experiments are conducted under controlled conditions, which allows for greater precision and accuracy. However, because laboratory conditions are not always representative of real-world conditions, the results of these experiments may not be generalizable to the population at large.

Field Experiment

Field experiments are conducted in naturalistic settings and allow for more realistic observations. However, because field experiments are not as controlled as laboratory experiments, they may be subject to more sources of error.

Experimental Design Methods

Experimental design methods refer to the techniques and procedures used to design and conduct experiments in scientific research. Here are some common experimental design methods:

Randomization

This involves randomly assigning participants to different groups or treatments to ensure that any observed differences between groups are due to the treatment and not to other factors.

Control Group

The use of a control group is an important experimental design method that involves having a group of participants that do not receive the treatment or intervention being studied. The control group is used as a baseline to compare the effects of the treatment group.

Blinding involves keeping participants, researchers, or both unaware of which treatment group participants are in, in order to reduce the risk of bias in the results.

Counterbalancing

This involves systematically varying the order in which participants receive treatments or interventions in order to control for order effects.

Replication

Replication involves conducting the same experiment with different samples or under different conditions to increase the reliability and validity of the results.

This experimental design method involves manipulating multiple independent variables simultaneously to investigate their combined effects on the dependent variable.

This involves dividing participants into subgroups or blocks based on specific characteristics, such as age or gender, in order to reduce the risk of confounding variables.

Data Collection Method

Experimental design data collection methods are techniques and procedures used to collect data in experimental research. Here are some common experimental design data collection methods:

Direct Observation

This method involves observing and recording the behavior or phenomenon of interest in real time. It may involve the use of structured or unstructured observation, and may be conducted in a laboratory or naturalistic setting.

Self-report Measures

Self-report measures involve asking participants to report their thoughts, feelings, or behaviors using questionnaires, surveys, or interviews. These measures may be administered in person or online.

Behavioral Measures

Behavioral measures involve measuring participants’ behavior directly, such as through reaction time tasks or performance tests. These measures may be administered using specialized equipment or software.

Physiological Measures

Physiological measures involve measuring participants’ physiological responses, such as heart rate, blood pressure, or brain activity, using specialized equipment. These measures may be invasive or non-invasive, and may be administered in a laboratory or clinical setting.

Archival Data

Archival data involves using existing records or data, such as medical records, administrative records, or historical documents, as a source of information. These data may be collected from public or private sources.

Computerized Measures

Computerized measures involve using software or computer programs to collect data on participants’ behavior or responses. These measures may include reaction time tasks, cognitive tests, or other types of computer-based assessments.

Video Recording

Video recording involves recording participants’ behavior or interactions using cameras or other recording equipment. This method can be used to capture detailed information about participants’ behavior or to analyze social interactions.

Data Analysis Method

Experimental design data analysis methods refer to the statistical techniques and procedures used to analyze data collected in experimental research. Here are some common experimental design data analysis methods:

Descriptive Statistics

Descriptive statistics are used to summarize and describe the data collected in the study. This includes measures such as mean, median, mode, range, and standard deviation.

Inferential Statistics

Inferential statistics are used to make inferences or generalizations about a larger population based on the data collected in the study. This includes hypothesis testing and estimation.

Analysis of Variance (ANOVA)

ANOVA is a statistical technique used to compare means across two or more groups in order to determine whether there are significant differences between the groups. There are several types of ANOVA, including one-way ANOVA, two-way ANOVA, and repeated measures ANOVA.

Regression Analysis

Regression analysis is used to model the relationship between two or more variables in order to determine the strength and direction of the relationship. There are several types of regression analysis, including linear regression, logistic regression, and multiple regression.

Factor Analysis

Factor analysis is used to identify underlying factors or dimensions in a set of variables. This can be used to reduce the complexity of the data and identify patterns in the data.

Structural Equation Modeling (SEM)

SEM is a statistical technique used to model complex relationships between variables. It can be used to test complex theories and models of causality.

Cluster Analysis

Cluster analysis is used to group similar cases or observations together based on similarities or differences in their characteristics.

Time Series Analysis

Time series analysis is used to analyze data collected over time in order to identify trends, patterns, or changes in the data.

Multilevel Modeling

Multilevel modeling is used to analyze data that is nested within multiple levels, such as students nested within schools or employees nested within companies.

Applications of Experimental Design 

Experimental design is a versatile research methodology that can be applied in many fields. Here are some applications of experimental design:

• Medical Research: Experimental design is commonly used to test new treatments or medications for various medical conditions. This includes clinical trials to evaluate the safety and effectiveness of new drugs or medical devices.
• Agriculture : Experimental design is used to test new crop varieties, fertilizers, and other agricultural practices. This includes randomized field trials to evaluate the effects of different treatments on crop yield, quality, and pest resistance.
• Environmental science: Experimental design is used to study the effects of environmental factors, such as pollution or climate change, on ecosystems and wildlife. This includes controlled experiments to study the effects of pollutants on plant growth or animal behavior.
• Psychology : Experimental design is used to study human behavior and cognitive processes. This includes experiments to test the effects of different interventions, such as therapy or medication, on mental health outcomes.
• Engineering : Experimental design is used to test new materials, designs, and manufacturing processes in engineering applications. This includes laboratory experiments to test the strength and durability of new materials, or field experiments to test the performance of new technologies.
• Education : Experimental design is used to evaluate the effectiveness of teaching methods, educational interventions, and programs. This includes randomized controlled trials to compare different teaching methods or evaluate the impact of educational programs on student outcomes.
• Marketing : Experimental design is used to test the effectiveness of marketing campaigns, pricing strategies, and product designs. This includes experiments to test the impact of different marketing messages or pricing schemes on consumer behavior.

Examples of Experimental Design 

Here are some examples of experimental design in different fields:

• Example in Medical research : A study that investigates the effectiveness of a new drug treatment for a particular condition. Patients are randomly assigned to either a treatment group or a control group, with the treatment group receiving the new drug and the control group receiving a placebo. The outcomes, such as improvement in symptoms or side effects, are measured and compared between the two groups.
• Example in Education research: A study that examines the impact of a new teaching method on student learning outcomes. Students are randomly assigned to either a group that receives the new teaching method or a group that receives the traditional teaching method. Student achievement is measured before and after the intervention, and the results are compared between the two groups.
• Example in Environmental science: A study that tests the effectiveness of a new method for reducing pollution in a river. Two sections of the river are selected, with one section treated with the new method and the other section left untreated. The water quality is measured before and after the intervention, and the results are compared between the two sections.
• Example in Marketing research: A study that investigates the impact of a new advertising campaign on consumer behavior. Participants are randomly assigned to either a group that is exposed to the new campaign or a group that is not. Their behavior, such as purchasing or product awareness, is measured and compared between the two groups.
• Example in Social psychology: A study that examines the effect of a new social intervention on reducing prejudice towards a marginalized group. Participants are randomly assigned to either a group that receives the intervention or a control group that does not. Their attitudes and behavior towards the marginalized group are measured before and after the intervention, and the results are compared between the two groups.

When to use Experimental Research Design 

Experimental research design should be used when a researcher wants to establish a cause-and-effect relationship between variables. It is particularly useful when studying the impact of an intervention or treatment on a particular outcome.

Here are some situations where experimental research design may be appropriate:

• When studying the effects of a new drug or medical treatment: Experimental research design is commonly used in medical research to test the effectiveness and safety of new drugs or medical treatments. By randomly assigning patients to treatment and control groups, researchers can determine whether the treatment is effective in improving health outcomes.
• When evaluating the effectiveness of an educational intervention: An experimental research design can be used to evaluate the impact of a new teaching method or educational program on student learning outcomes. By randomly assigning students to treatment and control groups, researchers can determine whether the intervention is effective in improving academic performance.
• When testing the effectiveness of a marketing campaign: An experimental research design can be used to test the effectiveness of different marketing messages or strategies. By randomly assigning participants to treatment and control groups, researchers can determine whether the marketing campaign is effective in changing consumer behavior.
• When studying the effects of an environmental intervention: Experimental research design can be used to study the impact of environmental interventions, such as pollution reduction programs or conservation efforts. By randomly assigning locations or areas to treatment and control groups, researchers can determine whether the intervention is effective in improving environmental outcomes.
• When testing the effects of a new technology: An experimental research design can be used to test the effectiveness and safety of new technologies or engineering designs. By randomly assigning participants or locations to treatment and control groups, researchers can determine whether the new technology is effective in achieving its intended purpose.

How to Conduct Experimental Research

Here are the steps to conduct Experimental Research:

• Identify a Research Question : Start by identifying a research question that you want to answer through the experiment. The question should be clear, specific, and testable.
• Develop a Hypothesis: Based on your research question, develop a hypothesis that predicts the relationship between the independent and dependent variables. The hypothesis should be clear and testable.
• Design the Experiment : Determine the type of experimental design you will use, such as a between-subjects design or a within-subjects design. Also, decide on the experimental conditions, such as the number of independent variables, the levels of the independent variable, and the dependent variable to be measured.
• Select Participants: Select the participants who will take part in the experiment. They should be representative of the population you are interested in studying.
• Randomly Assign Participants to Groups: If you are using a between-subjects design, randomly assign participants to groups to control for individual differences.
• Conduct the Experiment : Conduct the experiment by manipulating the independent variable(s) and measuring the dependent variable(s) across the different conditions.
• Analyze the Data: Analyze the data using appropriate statistical methods to determine if there is a significant effect of the independent variable(s) on the dependent variable(s).
• Draw Conclusions: Based on the data analysis, draw conclusions about the relationship between the independent and dependent variables. If the results support the hypothesis, then it is accepted. If the results do not support the hypothesis, then it is rejected.
• Communicate the Results: Finally, communicate the results of the experiment through a research report or presentation. Include the purpose of the study, the methods used, the results obtained, and the conclusions drawn.

Purpose of Experimental Design 

The purpose of experimental design is to control and manipulate one or more independent variables to determine their effect on a dependent variable. Experimental design allows researchers to systematically investigate causal relationships between variables, and to establish cause-and-effect relationships between the independent and dependent variables. Through experimental design, researchers can test hypotheses and make inferences about the population from which the sample was drawn.

Experimental design provides a structured approach to designing and conducting experiments, ensuring that the results are reliable and valid. By carefully controlling for extraneous variables that may affect the outcome of the study, experimental design allows researchers to isolate the effect of the independent variable(s) on the dependent variable(s), and to minimize the influence of other factors that may confound the results.

Experimental design also allows researchers to generalize their findings to the larger population from which the sample was drawn. By randomly selecting participants and using statistical techniques to analyze the data, researchers can make inferences about the larger population with a high degree of confidence.

Overall, the purpose of experimental design is to provide a rigorous, systematic, and scientific method for testing hypotheses and establishing cause-and-effect relationships between variables. Experimental design is a powerful tool for advancing scientific knowledge and informing evidence-based practice in various fields, including psychology, biology, medicine, engineering, and social sciences.

Advantages of Experimental Design 

Experimental design offers several advantages in research. Here are some of the main advantages:

• Control over extraneous variables: Experimental design allows researchers to control for extraneous variables that may affect the outcome of the study. By manipulating the independent variable and holding all other variables constant, researchers can isolate the effect of the independent variable on the dependent variable.
• Establishing causality: Experimental design allows researchers to establish causality by manipulating the independent variable and observing its effect on the dependent variable. This allows researchers to determine whether changes in the independent variable cause changes in the dependent variable.
• Replication : Experimental design allows researchers to replicate their experiments to ensure that the findings are consistent and reliable. Replication is important for establishing the validity and generalizability of the findings.
• Random assignment: Experimental design often involves randomly assigning participants to conditions. This helps to ensure that individual differences between participants are evenly distributed across conditions, which increases the internal validity of the study.
• Precision : Experimental design allows researchers to measure variables with precision, which can increase the accuracy and reliability of the data.
• Generalizability : If the study is well-designed, experimental design can increase the generalizability of the findings. By controlling for extraneous variables and using random assignment, researchers can increase the likelihood that the findings will apply to other populations and contexts.

Limitations of Experimental Design

Experimental design has some limitations that researchers should be aware of. Here are some of the main limitations:

• Artificiality : Experimental design often involves creating artificial situations that may not reflect real-world situations. This can limit the external validity of the findings, or the extent to which the findings can be generalized to real-world settings.
• Ethical concerns: Some experimental designs may raise ethical concerns, particularly if they involve manipulating variables that could cause harm to participants or if they involve deception.
• Participant bias : Participants in experimental studies may modify their behavior in response to the experiment, which can lead to participant bias.
• Limited generalizability: The conditions of the experiment may not reflect the complexities of real-world situations. As a result, the findings may not be applicable to all populations and contexts.
• Cost and time : Experimental design can be expensive and time-consuming, particularly if the experiment requires specialized equipment or if the sample size is large.
• Researcher bias : Researchers may unintentionally bias the results of the experiment if they have expectations or preferences for certain outcomes.
• Lack of feasibility : Experimental design may not be feasible in some cases, particularly if the research question involves variables that cannot be manipulated or controlled.

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• Knowledge Base

Methodology

• What Is a Controlled Experiment? | Definitions & Examples

What Is a Controlled Experiment? | Definitions & Examples

Published on April 19, 2021 by Pritha Bhandari . Revised on June 22, 2023.

In experiments , researchers manipulate independent variables to test their effects on dependent variables. In a controlled experiment , all variables other than the independent variable are controlled or held constant so they don’t influence the dependent variable.

Controlling variables can involve:

• holding variables at a constant or restricted level (e.g., keeping room temperature fixed).
• measuring variables to statistically control for them in your analyses.
• balancing variables across your experiment through randomization (e.g., using a random order of tasks).

Table of contents

Why does control matter in experiments, methods of control, problems with controlled experiments, other interesting articles, frequently asked questions about controlled experiments.

Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables. Strong validity also helps you avoid research biases , particularly ones related to issues with generalizability (like sampling bias and selection bias .)

• Your independent variable is the color used in advertising.
• Your dependent variable is the price that participants are willing to pay for a standard fast food meal.

Extraneous variables are factors that you’re not interested in studying, but that can still influence the dependent variable. For strong internal validity, you need to remove their effects from your experiment.

• Design and description of the meal,
• Study environment (e.g., temperature or lighting),
• Participant’s frequency of buying fast food,
• Participant’s familiarity with the specific fast food brand,
• Participant’s socioeconomic status.

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You can control some variables by standardizing your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., ad color) should be systematically changed between groups.

Other extraneous variables can be controlled through your sampling procedures . Ideally, you’ll select a sample that’s representative of your target population by using relevant inclusion and exclusion criteria (e.g., including participants from a specific income bracket, and not including participants with color blindness).

By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.

After gathering your participants, you’ll need to place them into groups to test different independent variable treatments. The types of groups and method of assigning participants to groups will help you implement control in your experiment.

Control groups

Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment (e.g., a placebo to control for a placebo effect ), and compare the outcome with your experimental treatment.

You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.

To test the effect of colors in advertising, each participant is placed in one of two groups:

• A control group that’s presented with red advertisements for a fast food meal.
• An experimental group that’s presented with green advertisements for the same fast food meal.

Random assignment

To avoid systematic differences and selection bias between the participants in your control and treatment groups, you should use random assignment .

This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .

Random assignment is a hallmark of a “true experiment”—it differentiates true experiments from quasi-experiments .

Masking (blinding)

Masking in experiments means hiding condition assignment from participants or researchers—or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs and is critical for avoiding several types of research bias .

Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses , leading to observer bias . In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses. These are called demand characteristics . If participants behave a particular way due to awareness of being observed (called a Hawthorne effect ), your results could be invalidated.

Using masking means that participants don’t know whether they’re in the control group or the experimental group. This helps you control biases from participants or researchers that could influence your study results.

You use an online survey form to present the advertisements to participants, and you leave the room while each participant completes the survey on the computer so that you can’t tell which condition each participant was in.

Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.

Difficult to control all variables

Especially in research with human participants, it’s impossible to hold all extraneous variables constant, because every individual has different experiences that may influence their perception, attitudes, or behaviors.

But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.

Risk of low external validity

Controlled experiments have disadvantages when it comes to external validity —the extent to which your results can be generalized to broad populations and settings.

The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.

There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritize control or generalizability in your experiment.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

• A control group that receives a standard treatment, a fake treatment, or no treatment.
• Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

• A testable hypothesis
• At least one independent variable that can be precisely manipulated
• At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

• How you will manipulate the variable(s)
• How you will control for any potential confounding variables
• How many subjects or samples will be included in the study
• How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

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Laboratory Manual For SCI103 Biology I at Roxbury Community College

9 photosynthesis.

In this lab, we will study the effect of light intensity and quality (wave length - color) on photosynthesis . As a measure of the rate of photosynthesis, we will monitor the rate of oxygen production. When plants that spend their life submerged in water release oxygen it forms bubbles, which we can count over a period of time to determine photosynthesis rate.

Photosynthesis is a process used by plants and other organisms to convert light energy into chemical energy that can later be released to fuel the organisms’ activities (energy transformation). This chemical energy is stored in carbohydrate molecules, such as sugars, which are synthesized from carbon dioxide and water - hence the name photosynthesis, from the Greek phōs, “light”, and synthesis, “putting together”. In most cases, oxygen is also released as a waste product. Most plants, most algae, and cyanobacteria perform photosynthesis; such organisms are called photoautotrophs. Photosynthesis is largely responsible for producing and maintaining the oxygen content of the Earth’s atmosphere, and supplies all of the organic compounds and most of the energy necessary for life on Earth.

Although photosynthesis is performed differently by different species, the process always begins when energy from light is absorbed by proteins called reaction centers that contain green chlorophyll pigments. In plants, these proteins are held inside organelles called chloroplasts, which are most abundant in leaf cells, while in bacteria they are embedded in the plasma membrane. In these light-dependent reactions, some energy is used to strip electrons from suitable substances, such as water, producing oxygen gas. The hydrogen freed by the splitting of water is used in the creation of two further compounds that act as an immediate energy storage means: reduced nicotinamide adenine dinucleotide phosphate (NADPH) and adenosine triphosphate (ATP), the “energy currency” of cells.

In plants, algae and cyanobacteria, long-term energy storage in the form of sugars is produced by a subsequent sequence of light-independent reactions called the Calvin cycle; some bacteria use different mechanisms, such as the reverse Krebs cycle, to achieve the same end. In the Calvin cycle, atmospheric carbon dioxide is incorporated into already existing organic carbon compounds, such as ribulose bisphosphate (RuBP). Using the ATP and NADPH produced by the light-dependent reactions, the resulting compounds are then reduced and removed to form further carbohydrates, such as glucose.

The first photosynthetic organisms probably evolved early in the evolutionary history of life and most likely used reducing agents such as hydrogen or hydrogen sulfide, rather than water, as sources of electrons. Cyanobacteria appeared later; the excess oxygen they produced contributed directly to the oxygenation of the Earth, which rendered the evolution of complex life possible. Today, the average rate of energy capture by photosynthesis globally is approximately 130 terawatts which is about three times the current power consumption of human civilization. Photosynthetic organisms also convert around 100-115 thousand million metric tons of carbon into biomass per year.

The main source of light on Earth is the Sun. Sunlight provides the energy that green plants use to create sugars mostly in the form of starches, which release energy into the living things that digest them. This process of photosynthesis provides virtually all the energy used by living things. The primary properties of visible light are intensity, propagation direction, frequency or wavelength spectrum, and polarization, while its speed in a vacuum, 299,792,458 meters per second, is one of the fundamental constants of nature. Visible light, as with all types of electromagnetic radiation (EMR), is experimentally found to always move at this speed in a vacuum.

9.1 Intensity of light

Light is electromagnetic radiation within a certain portion of the electromagnetic spectrum (Figure 9.1 ). The word usually refers to visible light, which is visible to the human eye and is responsible for the sense of sight. Visible light is usually defined as having wavelengths in the range of 400-700 nanometres (nm), or 400 × 10 -9 to 700 × 10 -9 m, between the infrared (with longer wavelengths) and the ultraviolet (with shorter wavelengths). This wavelength means a frequency range of roughly 430-750 terahertz (THz).

Figure 9.1: Spectrum of light. V, violet; B, blue; G, green Y, yellow; O, orange; R, red

In this experiment (Figure 9.2 ), we will study the effect of light intensity on the photosynthetic activity of Elodea canadensis . We will vary the light intensity by changing the distance between the light source and the plant. We will count the emerging oxygen bubbles as an indicator of the photosynthetic activity of the plant.

Figure 9.2: Setup for photosynthesis experiment.

9.1.1 Experimental procedures

Before you begin with the actual experiment, write down in your own words the hypothesis for this experiment:

• Obtain a cylindrical test tube.
• Fill test tube with 0.3% sodium bicarbonate.
• Select a fresh, crisp sprig of Elodea about 15 cm in length.
• While the plant is still submerged, cut 2-3 mm from its base.
• Place the sprig upside down into the test tube filled with sodium bicarbonate. The sodium bicarbonate will absorb anu toxic materials that are released by the plant during photosynthesis.
• Keeping the plant submerged, position a light source 10 cm away and adjust so the light shines directly on the plant.
• Place the test tube in a beaker of water as shown in Fig. 9.2 to prevent overheating the plant. 1. 1. Allow the system to stand 7-10 minutes, or until bubbles begin to appear regularly.
• Count the bubbles produced each minute for a 5-minute period and average them. Record your findings in the table.
• Move the light back 20 cm from the plant, wait 5 minutes, and repeat counting. Record your findings in Table 9.1 .
• Move the light back 40 cm from the plant and repeat counting the bubbles.
• When you have finished recording your data, calculate the average number of bubbles for each 5 minute period and enter the result into the table.

Do the data support or contradict your hypothesis?

Figure 9.3: Appearance of bubbles indicates active photosynthesis.

9.2 Color of light

In this experiment, we will study the effect of the color of light on the photosynthetic activity of Elodea canadensis . We will use filter to expose the plant to light of only a limited range of wavelengths. We will again count the emerging oxygen bubbles as an indicator of the photosynthetic activity of the plant.

9.2.1 Experimental procedures

• Empty the test tube that you used in the previous experiment.
• Fill the test tube with fress 0.3% sodium bicarbonate.
• Place the Elodea sprig into the test tube and submerge it completely in the bicarbonate.
• Place the red colored filter between the test tube and the heat shield beaker and allow it to sit for 5 minutes.
• Count bubbles for 5 minutes as in the previous experiment. Record your findings in Table 9.2 .
• Remove the color filter and expose the plant to white light. Count bubbles again for 5 minutes in 1 minute intervals. Record your findings in Table 9.2 .
• Place the green colored filter between the test tube and the heat shield beaker and allow it to sit for 5 minutes.
• Count bubbles for 5 minutes. Record your findings in Table 9.2 . Table: (#tab:color) Color of light.

9.3 Determination of the light absorption spectrum of dye solutions

In this experiment, we will use a spectrophotometer to measure the differential absorption of light of different wavelength by water stained with food dyes.

Figure 9.4: Spectrophotometer and cuvettes with dye solutions.

9.3.1 Experimental procedures

• Take six cuvettes.
• Fill one cuvette with water.
• Fill each of the remaining five cuvettes with one of the color solutions listed in Table 9.3 .
• Insert the cuvette with water into the slot marked “B”.
• Insert the other cuvettes into the slots marked 1 to 5 and write down which color is in which slot.
• Following the instructions posted on the spectrophotometer, program the machine to take absorption measurements at wavelengths between 380-740 nm in 20 nm steps.
• Once the measurements are completed, write down the absorption number for each dye and wavelength.
• Use a spreadsheet program to graph your results.
• Compare your curves with the data shown in Figure 9.6 .

Figure 9.5: Cuvettes placed in the spectrophotometer.

Figure 9.6: Normalized absorption of red, green and blue dye solutions. Compare these data with your own results.

9.4 Chromatography

Chromatography is a laboratory technique for the separation of a mixture. The mixture is dissolved in a fluid called the mobile phase, which carries it through a structure holding another material called the stationary phase. The various constituents of the mixture travel at different speeds, causing them to separate. The separation is based on differential partitioning between the mobile and stationary phases. Subtle differences in a compound’s partition coefficient result in differential retention on the stationary phase and thus affect the separation. Chromatography may be preparative or analytical. The purpose of preparative chromatography is to separate the components of a mixture for later use and is thus a form of purification. Analytical chromatography is done normally with smaller amounts of material and is for establishing the presence or measuring the relative proportions of analytes in a mixture.

In this experiment, we separate a mixture of food dyes (a dark brown liquid). The mobile phase (separation buffer) is 1% NaCl in water, the stationary phase is chromatography paper.

9.4.1 Experimental procedures

• Obtain a small beaker.
• Add NaCl running buffer to the beaker until it reaches a height of about 5 mm.
• Obtain a strip of chromatography paper and put it down on the bench.
• Obtain the bottle containing the dark green food dye mixture.
• Obtain a glass capillary and insert the tip of the capillary into the food dye mixture liquid. A little bit of dye will ascend into the capillary.
• Remove the capillary and apply.
• Touch the left side of the chromatography paper about 1 cm above its lower end with the tip of the capillary. A little bit of green liquid will spread out on the paper. Lift the capillary and touch the paper again just to the right of the dye you just applied. Repeat this until you have a horizontal line of dye from the left to the right side of the paper.
• Place the chromatography paper into the beaker as shown below.
• Observe how the running buffer moves up the paper and separates the dye mixture into three components (red, yellow and blue.

Figure 9.7: Result of the Chromatography experiment.

9.5 Review Questions

• What is light?
• In your own words, describe the endproducts of photosynthesis.
• In your own words, describe what happens in photosynthesis.
• What is chlorophyll and what does it do?
• Where inside of plant cells does photosynthesis happen?
• What is chromatography and what is it used for?

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Biology archive

Course: biology archive   >   unit 1, the scientific method.

• Controlled experiments
• The scientific method and experimental design

Introduction

• Make an observation.
• Ask a question.
• Form a hypothesis , or testable explanation.
• Make a prediction based on the hypothesis.
• Test the prediction.
• Iterate: use the results to make new hypotheses or predictions.

Scientific method example: Failure to toast

1. make an observation., 2. ask a question., 3. propose a hypothesis., 4. make predictions., 5. test the predictions..

• If the toaster does toast, then the hypothesis is supported—likely correct.
• If the toaster doesn't toast, then the hypothesis is not supported—likely wrong.

Logical possibility

Practical possibility, building a body of evidence, 6. iterate..

• If the hypothesis was supported, we might do additional tests to confirm it, or revise it to be more specific. For instance, we might investigate why the outlet is broken.
• If the hypothesis was not supported, we would come up with a new hypothesis. For instance, the next hypothesis might be that there's a broken wire in the toaster.

Want to join the conversation?

• Upvote Button navigates to signup page
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• Flag Button navigates to signup page

Enhancement of tryptophan 2-monooxygenase thermostability by semi-rational enzyme engineering: a strategic design to minimize experimental investigation †

First published on 27th July 2024

Tryptophan 2-monooxygenase (TMO) is an FAD-bound flavoenzyme which catalyzes the oxidative decarboxylation of L -tryptophan to produce indole-3-acetamide (IAM) and carbon dioxide. The reaction of TMO is the first step of indole-3-acetic acid (IAA) biosynthesis. Although TMO is of interest for mechanistic studies and synthetic biology applications, the enzyme has low thermostability and soluble expression yield. Herein, we employed a combined approach of rational design using computational tools with site-saturation mutagenesis to screen for TMO variants with significantly improved thermostability properties and soluble protein expression. The engineered TMO variants, TMO-PWS and TMO-PWSNR, possess melting temperatures ( T m ) of 65 °C, 17 °C higher than that of the wild-type enzyme (TMO-WT). At 50 °C, the stabilities ( t 1/2 ) of TMO-PWS and TMO-PWSNR were 85-fold and 92.4-fold higher, while their soluble expression yields were 1.4-fold and 2.1-fold greater than TMO-WT, respectively. Remarkably, the kinetic parameters of these variants were similar to those of the wild-type enzymes, illustrating that they are promising candidates for future studies. Molecular dynamic simulations of the wild-type and thermostable TMO variants identified key interactions for enhancing these improvements in the biophysical properties of the TMO variants. The introduced mutations contributed to hydrogen bond formation and an increase in the regional hydrophobicity, thereby, strengthening the TMO structure.

Introduction

The overall catalytic reaction of TMO is similar to those of flavoenzyme oxidases in which the first half-reaction is a reductive half-reaction where a substrate is oxidized by an enzyme-bound FAD to form an imino acid intermediate, followed by the second half-reaction which is oxidation of the reduced FAD to generate H 2 O 2 which subsequently reacts with the imino acid to form IAM. Although the kinetics and crystal structures of wild-type TMO and several variants have been reported, 6–13 a full understanding of the TMO mechanisms regarding the intriguing oxygen insertion to generate IAM at the oxidative half-reaction remains elusive. 14 For previous site-directed mutagenesis studies, none of the variants have shown improvement in enzyme stability; only the variant generating a keto acid instead of an amide product was obtained. 12 Based on our own experience, we found that the amount of soluble TMO overexpressed in E. coli was low and the enzyme was not very stable at ambient temperature. 15 This has obstructed a thorough mechanistic investigation or enzyme engineering campaign of TMO for further investigation.

Therefore, we proposed to overcome this hurdle by obtaining TMO variants which are more thermostable and overexpress better than the wild-type enzyme while still maintaining effective catalytic efficiency for IAM production. Such stable variants can serve as a well-built template for future mechanistic investigations and facilitate additional engineering efforts toward obtaining TMOs suitable for future applications.

Engineering of target enzymes to improve their thermostability can be done using the combined approaches of computational prediction, mechanism-guided, and random mutagenesis. 16–19 Semi-rational enzyme engineering is advantageous for creating a small-size library that contains a high chance of success in obtaining the desired enzymes. 20 Several computational tools for predicting probable variants are available. The FireProt web server is a comprehensive protein predictor that can be used to propose single- or multiple-point mutations to create thermostable protein variants. 21,22 B-FITTER software can be used to analyze B -factor values of individual residues and probe the high flexibility region of the protein structure. 23,24 Disulfide by Design 2.0 (DbD) can be used to calculate probable regions for introducing disulfide pairs to strengthen the protein structures. 25 Protein Repair One-Stop Shop (PROSS) is another comprehensive protein predictor focusing on improving protein stability and solubility. 26 By applying these tools with mechanistic understanding and knowledge of regions to be avoided or focused, we have successfully obtained variants of flavin-dependent enzymes with improved thermostability. 27–29

Apart from focusing on protein stability, we were also interested in improving the yield of soluble TMO. Several studies have reported obstacles in the production of soluble L -amino acid oxidases (LAAOs) 30 including TMO in E. coli systems. Typically, TMO is overexpressed in a low amount using a conventional expression system. 7 Recently, it has been reported that recombinant expression of the TMO native sequence resulted in insoluble protein, and a SUMO soluble protein tag was required for soluble TMO expression. 2 In our case, we found that the co-expression of a pGro7 chaperone vector was required to facilitate soluble TMO folding. 15 Here, we proposed that the semi-engineering approach can be used to improve TMO solubility and thermostability in the same engineering campaign.

In this work, TMO from P. savastanoi was engineered to improve its thermostability and soluble expression yield using a semi-rational enzyme engineering approach. The overall rationale used for selecting candidate residues for mutation was based on structural analysis and computational predictions by FireProt, DbD, PROSS, and B-FITTER software. DbD was used to predict the positions for the incorporation of disulfide bridges through site-directed mutagenesis. FireProt, B-FITTER and PROSS were used to predict the hotspot regions for site-saturation mutagenesis to obtain variants of 20 amino acids at each position. Libraries were screened for variants with improved thermostability compared to the wild-type enzyme. Beneficial single-site and double-site mutations were later combined to obtain the TMO-PWS and TMO-PWSNR variants which have a maximum T m value of 65 °C. The variants were further tested for time-course thermal tolerance, steady-state kinetics, and their soluble expression yield. Finally, they were tested for their ability to produce IAM in bioconversion experiments. Molecular dynamics (MD) simulations were also carried out to elucidate the effects of the mutations. The overall workflow of our approach is summarized in Fig. 1 . This work is the first to report TMO variants with significant improvement in thermostability and expression yield while maintaining comparable catalytic properties as the wild-type enzyme.

Results and discussion

Computation prediction and rational selection of candidate residues for improving the thermostability of tmo.

FireProt is a comprehensive web server tool which can be used to predict thermostable variants based on energy calculations and evolutionary analysis. 21,22 The FireProt web-based software can be accessed via https://loschmidt.chemi.muni.cz/fireprotweb/. The PDB file structure of TMO was submitted to FireProt for the prediction of TMO thermostable variants using the default settings. The software provided 50 suggested variants for mutation including 26 energy variants and 31 evolution variants. Some variants were classified as both types and, thus, there were 50 predicted variants in total. We selected and ranked the candidates based on the following criteria. The positions located within 8 Å from the active site were excluded to avoid interference with TMO catalysis. We selected only the variants with mutations at positions which resulted in differences in the folding free energy relative to the wild-type enzyme (ΔΔ G fold ) as calculated by both FoldX and/or Rosetta of less than −1 kcal mol −1 . Among the 50 suggested candidates, 22 candidates were selected for further analysis. The selected candidates and all of the variants predicted from the FireProt analysis are shown in Table S1 (ESI † ).

B-FITTER software which can be downloaded from the website (https://www.kofo.mpg.de/en/research/biocatalysis) provides identification of residues with high B -factor values. B -factor or temperature factor reflects the diffusion of the atomic electron density of crystal structures. The high B -factor value region (high diffusion of atomic electron density) reflects the high flexibility. We thus used the B-FITTER software to rank the top 20 highest B -factor value residues from the whole protein structure. These high B -factor value residues are targets for performing mutations to strengthen the region. The mutations could be iterative to create the most thermostable variant. 24 We analyzed the TMO PDB structure using B-FITTER to obtain the analysis as shown in Table S2 (ESI † ) in which most of the residues are located on the protein surface. The predicted positions and their adjacent positions (±1 residues from the predicted residue) with high B -factor values were selected to be compared with the results from FireProt and PROSS for final selection.

PROSS is also a comprehensive tool for predicting mutations to increase protein stability and solubility. 26,31,32 The PROSS online website can be accessed through https://pross.weizmann.ac.il/step/pross-terms/. After the TMO structure was submitted to the PROSS website, we obtained the suggested designs containing different numbers of mutations as listed from Design 1 to Design 9 (Fig. S1, ESI † ). Design 9 comprises the largest number of mutations and was suggested to be avoided by the website. In this work, the suggested positions from Design 1 (containing the lowest number of mutations present in every design) were selected to be compared with the results from FireProt and B-FITTER for the final selection.

According to Fig. 2 , the candidate residues predicted by FireProt (22 positions), B-FITTER (20 positions), and PROSS (9 designs), which passed our selection criteria, were compared, and analyzed for their structural interactions. For residues from B-FITTER analysis, the adjacent residues (±1 residues from the predicted residues) were also included in the consideration. We manually inspected target candidates to determine whether they could promote additional interactions with nearby residues without perturbing the TMO active site and the overall folding. We also favored the residues located near areas on the surface to possibly improve protein expression upon performing site-saturation mutagenesis.

The residues, including S33, Q85, C204, A307, N331, and A473, predicted in common by more than one tool, were subjected to site-saturation mutagenesis for further screening. We also selected the T496 position which was suggested only by FireProt but it was favored by structural analysis because it has potential to promote local aromatic interactions. The list of selected positions is shown in Table 1 and Fig. 2 .

The selected variants were successfully constructed, verified by sequence analysis, and overexpressed using the same methods as for the wild-type enzyme as described in the experimental procedures section. However, it was found that all of the DbD variants were insoluble upon overexpression, as observed by a large protein band at 67 kDa upon SDS-PAGE analysis in the lane corresponding to the pellet samples ( Table 2 and Fig. S2, ESI † ). Moreover, the cell pellet of the DbD variants did not show any yellow color, unlike the overexpressed wild-type TMO cell pellet which shows a distinctive yellow color commonly found in many cells overexpressing FAD-bound proteins. Therefore, only the approaches described in the previous section and Fig. 2 were further used to improve the TMO stability.

Identification of thermostable variants from high-throughput screening

For the first round of screening, we selected the first group of candidate positions with high negative values based on FoldX energy calculations. Therefore, the site-saturation mutagenesis was carried out at the T496 and N331 residues independently using the TMO-WT as a template. The variant samples were incubated at 50 °C for one hour before being tested in the reaction setting as described above. The T496F (TMO-F) and N331P (TMO-P) variants were identified from the screening results as promising candidates. These variants were purified and investigated by thermal shift assays for T m values in comparison to the T m of TMO-WT of 48 °C. The TMO-F variant showed a slight improvement in the T m with a one-degree Celsius increase; however, the T m of TMO-P was increased by approximately 7 °C. Therefore, the TMO-P variant was used as a template for the second round of evolution at other positions.

For the second round of screening, positions 33, 85, 204, 307, and 473 were subjected to site-saturation mutagenesis in independent libraries. The libraries containing double mutations (N331P and another mutation from this round) were expected to have higher thermostability than the template. Thus, the incubation temperature for this round was increased to 55 °C for an hour. Some examples of screening data are shown in Fig. S3 (ESI † ). From the last round of the screening, five variants which were N331P/S33E (TMO-PE), N331P/S33R (TMO-PR), N331P/Q85G (TMO-PG), N331P/C204S (TMO-PS), N331P/A307N (TMO-PN), and N331P/A473W (TMO-PW) were identified. The mutations S33E (TMO-PE) and Q85G (TMO-PG) were excluded from the further characterizations since the TMO-PE and TMO-PG variants showed less improvement in T m as compared to the S33R mutation, and the Q85G mutation showed lower enzyme activities than that of the wild-type enzyme (Fig. S4, ESI † ). Based on T m values, S33R, C204S, A307N, and A473W were identified as beneficial mutations to increase TMO stability. Thus, we combined these mutations to create variants with triple mutations (TMO-PWS, TMO-PWR, and TMO-PWN) by site-directed mutagenesis. We also created the combined variant with all five positions mutated (TMO-PWSNR) which was expected to improve the thermostability of the enzyme further. The summary of improvement in T m values for all of the variants is shown in Fig. 4 .

The addition of the third mutation using the TMO-PW variant as the template resulted in equal values of T m for the TMO-PWN and TMO-PWR variants, whereas the TMO-PWS exhibited a slight improvement, showing a T m of 65 °C. The TMO-PWSNR variant also showed a T m value of 65 °C, similar to the TMO-PWS variant. Altogether, the data suggests that the addition of another mutation to double mutation variants resulted in the slightly higher melting temperature while the combined variant of TMO-PWSNR showed a similar level of thermostability compared to the TMO-PWS variant, giving a T m value of around 65 °C.

Improvement of the thermostability among TMO variants

Characterization of thermostable TMO variants

Interestingly, in addition to the improvement in thermostability, the soluble overexpression yield of TMO variants determined by the amount of purified enzyme (in mg) per culture volume (in liter) was increased by approximately 2.14-fold for TMO-PWSNR and 1.46-fold for TMO-PWS relative to the wild-type TMO ( Fig. 6A ).

Time-course of TMO-PWS and TMO-PWSNR thermal tolerance

Thermostable variants’ performance at high temperature

We carried out another set of bioconversion experiments using the same conditions to compare the IAM production after 45 min at 25, 30, 40, and 50 °C. The results in Fig. 8B indicated that both TMO-PWS and TMO-PWSNR variants could maintain the ability to produce IAM well at all temperatures, while the TMO-WT showed reduced levels of IAM produced at 40 °C and 50 °C. Altogether, the results in Fig. 8 highlight the potential of TMO-PWS and TMO-PWSNR in future biotechnology applications.

MD simulations to understand the improved thermostability of TMO variants

We further inspected specific interactions around mutated residues of TMO-PWS and TMO-PWSNR compared to TMO-WT. The results from the snapshot of the simulations after 100 ns at 400 K demonstrated that the mutated residues play a role in rigidifying the protein structural models as shown in Fig. 10 . The C204S mutation introduced the hydrogen bonds from the hydroxyl group of the S204 side chain to interact with the carbonyl oxygen of the adjacent residue, S205 (3.2 Å), and the side chain of N208 (2.8 Å). The replacement of the sulfhydryl group by the hydroxyl group in C204 also resulted in stronger interactions between a polar hydrogen of the hydroxyl group and a partially negative oxygen of the side chain of N208 and the carbonyl oxygen of S205. Based on the structural model, shorter distances between the N208 side chain and the carbonyl oxygen of S205 to the oxygen atom of the S204 hydroxyl group could be observed (Fig. S6, ESI † ).

The A307N mutation could possibly improve the thermostability of the enzyme by contributing to a more hydrophilic environment in the region. The mutated N307 could form a hydrogen bond with the side chain of E306 (1.8 Å), thus stabilizing the loop region where N307 is located.

The S33 position is located on the flexible loop. The S33R mutation, which possesses a longer side chain, could form a hydrogen bond with the carbonyl group of R59 (2.6 Å) located on the helix of another domain. The mutation might enhance the interactions between these two areas, possibly increasing the surface hydrophilicity, protein rigidity, and solubility.

The N331 and A473 positions are also located in the hydrophobic region. The N331P and A473W mutation could increase the hydrophobicity between local hydrophobic residues such as I337, V355, L360, L467, and P470. In addition, the A473W mutation could also introduce a bulky side chain around the entrance of the FAD binding region. The bulky side chain could minimize the access of water into the hydrophobic region, possibly strengthening the inner core hydrophobic interactions.

For the improvement in soluble protein expression, we speculate that the mutations in TMO-PWS and TMO-PWSNR may affect the overall charge of the exposed protein surface. For example, the change of interactions around the S33R and A307N mutations discussed above may play important roles in increasing the solubility of TMO, as significant improvements could be observed in the soluble yields of TMO-PWSNR as compared to TMO-PWS.

Comparison of the predicted results among the various computational tools used and the success of variants obtained from the experimental investigation

It was interesting to note that the S33P variant was predicted by both FireProt and PROSS programs because the replacement of serine with a proline substitution would be expected to strengthen the flexible loop region. However, the experimental data from the screening process ( Fig. 4 ) showed that the S33R mutation was the most thermostable one for this position. This may be due to the fact that S33R provides a longer side chain for creating interactions with residues from a different region.

For C204 and A307 positions, different amino acids were predicted between the two software programs. C204Y and C204V were suggested by FireProt and PROSS, respectively, while we obtained C204S as the most thermostable variant. Based on the analysis shown in Fig. 10 , the serine residue may provide better hydrogen bond interactions with the residues, S205 and N208. We did not detect C204Y and C204V variants as thermostable enzymes. This might be due to nonproper alignment of these residues for hydrogen bond formation (Fig. S7, ESI † ). For the variant A307N obtained from experimental screening, it was different from the predicted results from FireProt as A307S and PROSS as A307G. This may be due to the hydrogen bond formation between the A307N and the residue E306 ( Fig. 10 ).

Conclusions

Experimental procedures, materials and analytical instruments, construction of plasmid, genes, and enzyme variants, protein expression and purification of wild-type and tmo variants, selection of candidate residues by computational prediction, structural analysis, and rational selection, construction of tmo variants for screening, high-throughput screening of thermostable variants, product analysis, determination of tmo melting temperatures ( t m ) using thermal shift assays, measuring tmo activities after heat treatment, steady-state kinetics of tmo variants, bioconversion of tmo variants, md simulations, author contributions, data availability, conflicts of interest, acknowledgements.

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From large labs to small teams, mentorship thrives

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Each year, new MIT graduate students are tasked with the momentous decision of choosing a research group that will serve as their home for the next several years. Among many questions they face: join an established research effort, or work with a new faculty member in a growing group?

Professors Cynthia Breazeal, leading a group of over 30 students, and Ming Guo, with a lab of fewer than 10, demonstrate that excellent mentorship can thrive in a research group of any size.

Cynthia Breazeal: Flexible leadership

Cynthia Breazeal is a professor of media arts and sciences at MIT, where she founded and directs the Personal Robots group at the MIT Media Lab. She is also the MIT dean for digital learning, leading MIT Open Learning’s business and research and engagement units. Breazeal is a pioneer of social robotics and human-robot interaction, and her research group investigates social robots applied to education, pediatrics, health and wellness, and aging.

Breazeal’s focus on taking multidisciplinary approaches to her research has resulted in an inclusive and supportive lab environment. Moreover, she does not shy away from taking students with unconventional backgrounds.

One nominator joined Breazeal's lab as a design researcher without a computer science background. However, Breazeal recognized the value of their work within the context of her lab’s research directions. “I was a bit of an oddball in the group”, the nominator modestly recounts, “but had joined to help make the work in the group more human-centered.”

Throughout the student's academic journey, Breazeal offered unwavering support, whether by connecting them with experts to solve specific problems or guiding them through the academic job search process.

Over the Covid-19 pandemic, Breazeal prioritized gathering student feedback through a survey about how she could best support her research group. In response to this input, Breazeal established the Senior Research Team (SRT) within her group.

The SRT includes PhD holders such as postdocs and research scientists who provide personalized mentorship to one or two graduate students per semester. The SRT members serve as dedicated advocates and points of contact, with weekly check-ins to address questions within the lab. Additionally, SRT members meet by themselves weekly to discuss student concerns and bring up urgent issues with Breazeal directly. Lastly, students can sign up for meetings with Breazeal and participate in paper review sessions with her and co-authors.

In the nominator’s opinion, this new system was implemented because Breazeal cares about her students and her lab culture. With over 30 members in her group, Breazeal cannot provide hands-on support for everyone daily, but she still deeply cares about each person's experience in the lab. The nominator shared that Breazeal “understands as she progresses in her career, she needs to make sure that she is changing and creating new systems for her research group to continue to operate smoothly.”

Ming Guo: Emphasizing learning over achievement

Ming Guo is an associate professor in the Department of Mechanical Engineering. Guo’s group works at the interface of mechanics, physics, and cell biology, seeking to understand how physical properties and biological function affect each other in cellular systems.

A key aspect of Guo’s mentorship style is his ability to foster an environment where students feel comfortable expressing their difficulties. He actively shows empathy for his students’ lives outside of the lab, often reaching out to provide support during challenging times. When one nominator found themselves faced with significant personal difficulties, Guo made a point to check in regularly, ensuring the student had a support network of friends and labmates.

Guo champions his students both academically and personally. For instance, when a collaborating lab placed unrealistic expectations on a student’s experimental output, Guo openly praised the student’s efforts and achievements in a joint meeting, alleviating pressure and highlighting the student’s hard work.

In addition, Guo encourages vulnerable conversations about issues affecting students, such as political developments and racial inequities. During the graduate student unionization process, he fostered open discussion, showing genuine interest in understanding the challenges faced by graduate students and using these insights to better support them.

In Guo’s research group, learning and development are prioritized over achievements and goals. When students encounter challenges in their research, Guo helps them maintain perspective by validating their struggles and recognizing the skills they acquire through difficult experiments. By celebrating their progress and emphasizing the importance of the learning process, he ensures that students understand the value of their experiences beyond outcomes. This approach not only boosts their confidence, but also fosters a deeper appreciation for the scientific process and their own development as researchers.

Guo says that he feels most energized and happy when he talks to students. He looks forward to the new ideas that they present. One nominator commented on how much Guo enjoys giving feedback at group meetings: “Sometimes he isn’t convinced in the beginning, but he has cultivated our lab atmosphere to be conducive to extended discussion.”

The nominator continues, “When things do work and become really interesting, he is extremely excited with us and pushes us to share our own ideas with the wider research community.” 

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ORIGINAL RESEARCH article

Vermicompost application enhances soil health and plant physiological and antioxidant defense to conferring heavy metals tolerance in fragrant rice.

• 1 State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, South China Agricultural University, Guangzhou, China
• 2 Department of Agriculture, The University of Swabi, Swabi, Pakistan
• 3 Key Laboratory of Crop Cultivation and Physiology, College of Agriculture, Guangxi University, Nanning, China
• 4 College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
• 5 Centre of Excellence in Biotechnology Research, King Saud University, Riyadh, Saudi Arabia
• 6 Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia
• 7 Department of Agronomy, Faculty of Agriculture, Kafrelsheikh University, Kafrelsheikh, Egypt
• 8 CFAES Rattan Lal Center for Carbon Management and Sequestration, The Ohio State University, Columbus, OH, United States

Cadmium (Cd) contamination in agricultural soils and its accumulation in plant organs have become a global issue due to its harmful effects on human health. The in-situ stabilizing technique, which involves using organic amendments, is commonly employed for removing Cd from agricultural soils. Thus, the current study investigated the effect of vermicompost (VC) on soil properties and plant physio-biochemical attributes, leaf ultrastructure analysis, antioxidant defense mechanisms, and grain yields of two different fragrant rice cultivars, Xiangyaxiangzhan (XGZ) and Meixiangzhan-2 (MXZ-2), under Cd-stress conditions. The results showed that Cd toxicity deteriorates soil quality, the plant’s photosynthetic apparatus, and the plant’s antioxidant defense mechanism. Moreover, under Cd stress, both cultivars produced significantly lower ( p  < 0.05) rice grain yields compared to non-Cd stress conditions. However, the VC application alleviated the Cd toxicity and improved soil qualitative traits, such as soil organic carbon, available nitrogen, total nitrogen, phosphorus, and potassium. Similarly, VC amendments improved leaf physiological activity, photosynthetic apparatus function, antioxidant enzyme activities and its related gene expression under Cd stress These enhancements led to increased grain yields of both fragrant under Cd toxicity. The addition of VC mitigated the adverse effects of Cd on the leaf chloroplast structure by reducing Cd uptake and accumulation in tissues. This helped prevent Cd-induced peroxidation damage to leaf membrane lipids by increasing the activities of antioxidant enzymes such as ascorbate peroxidase (APX), catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD). On average across the growth stages, the Pos-Cd + VC3 treatment increased SOD, APX, CAT, and POD activities by122.2 and 112.5%, 118.6, and 120.6%, 44.6 and 40.6%, and 38.6 and 33.2% in MXZ-2 and XGZ, respectively, compared to the plants treated with Pos-Cd treated alone. Enhancements in leaf physiological activity and plant antioxidant enzyme activity strengthen the plant’s antioxidant defense mechanism against Cd toxicity. In addition, correlation analysis showed a strong relationship between the leaf net photosynthetic rate and soil chemical attributes, suggesting that improved soil fertility enhances leaf physiological activity and boosts rice grain yields. Of the treatments, Pos-Cd + VC3 proved to be the most effective treatment in terms of enhancing soil health and achieving high fragrant rice yields. Thus, the outcomes of this study show that the addition of VC in Cd-contaminated soils could be useful for sustainable rice production and safe utilization of Cd-polluted soil.

Graphical Abstract .

1 Introduction

Heavy metals, especially Cd, pose significant hazards due to their high toxicity and propensity for substantial uptake and accumulation in cereal grains ( Singh et al., 2020 ). The Cd accumulation in arable soil is caused by industrial processes such as waste discharge, fertilization, mining, and smelting ( Islam et al., 2017 ; Tang et al., 2019 ; Seleiman et al., 2020 ). Cd is more soluble and mobile than other metals, making it easily absorbed by plants, translocated within them, and deposited in various plant parts ( Chen Q. et al., 2018 ; Chen Y. et al., 2018 ; Adil et al., 2020 ). Furthermore, Cd is commonly non-recyclable and difficult to remove from the soil, and it can migrate to cereal grains via the soil–plant-food cycle, thereby posing health hazards to humans ( Rizwan et al., 2016 ; Seleiman et al., 2020 ). The Cd inputs and availability in soil adversely affect soil microbial biodiversity and its associated ecosystem function ( Xue et al., 2017 ; Haider et al., 2021 ; Iqbal et al., 2024a ). Cadmium garnered a lot of attention in arable soil because of its toxicity, availability, and persistence in living organisms ( Rizwan et al., 2016 ; Huang et al., 2019 ).

Additionally, high Cd levels in arable fields may affect soil health, physiochemical characteristics, and plant metabolism, resulting in lower crop growth and reduced productivity ( Mitra et al., 2018 ; Iqbal et al., 2023a ). Cd also inhibits plant photosynthesis and reduces plant uptake of essential mineral nutrients, resulting in a decrease in agricultural output ( Tran and Popova, 2013 ; Chen Q. et al., 2018 ; Chen Y. et al., 2018 ). In addition, Cd toxicity in plants can produce physiological, biochemical, and physical changes, including reduction in root growth, stomatal density, and chlorosis ( Bari et al., 2019 ; Huybrechts et al., 2020 ). The plant photosynthetic apparatus is often more vulnerable to Cd-induced damage. Plant chlorophyll is essential for photosynthesis, and any decrease in plant chlorophyll production due to Cd toxicity declines the photosynthesis process ( Li et al., 2010 ; Parmar et al., 2013 ). Cd stress affects mitochondrial function in plants by affecting redox control and promoting the generation of additional reactive oxygen species (ROS), that damage membrane lipids and alter overall metabolic activity ( Chen Q. et al., 2018 ; Chen Y. et al., 2018 ; Huybrechts et al., 2020 ). The ROS generated under stress is responsible for cellular oxidative injury and genotoxicity ( Gallego et al., 2012 ; Khan et al., 2022 ). As a result, Cd, one of the most harmful contaminants, demands special attention to regulate its mobility in arable soils.

Rice is an important cereal crop for about 3.5 billion people worldwide ( Dabral et al., 2019 ). Rice is a key ingredient and staple diet for Chinese people ( Chauhan et al., 2017 ). The majority of Cd in the food channel could come from agricultural products, and Cd in soil plants accumulates up by roots and finally enters the food, posing health concerns to the human immunological, neurological, and reproductive organs ( Parmar et al., 2013 ; Adil et al., 2020 ). In situ stabilization technique, using organic additions such as cattle fertilizer, biochar, and compost, is an environmentally friendly approach to preventing Cd ( Hamid et al., 2020 ; Ullah et al., 2020 ; Yuan et al., 2022 ; Ali et al., 2022a , b , c ; Iqbal et al., 2024b ). However, these techniques are ineffective and problematic because of the accompanying costs and additional pollutants ( Shaheen and Rinklebe, 2015 ; Pramanik et al., 2018 ). In addition, according to Igalavithana et al. (2017) the use of these organic fertilizers alone might enhance the risk of arsenic pollution; for instance, applying wood bark organic biochar increases exchangeable arsenic in soil by 84.5%.

Vermicompost (VC), is the product of the decomposition process using species of worms, usually white worms, red wigglers, and other earthworms to create a mixture of decomposing vegetables, food waste and vermicas ( Charan et al., 2024 ). The VC, a nutrient-rich fertilizer, is turning more common for heavy metal-contaminated arable soil rehabilitation ( Wang et al., 2018 ; Zhang et al., 2020 ). Alam et al. (2020) found that VC is more beneficial and effective than wasted mushroom and organic fertilizer for reducing Cd and other metals accumulation and uptake in plants. Earthworms can accumulate various heavy metals such as Cd, Pb, Hg, and Zn, and store it in benign forms in the chloragogenous tissues ( Song et al., 2015 ). The peak absorption rate of 170.65 mg/g of Cd 2+ on VC indicates that VC is a possible in situ sorbent for Cd-polluted soil ( Zhu et al., 2017 ). Moreover, VC treatment may affect soil physical and biochemical parameters and alter the chemical composition of Cd in soils, reducing Cd bioavailability in soils by adsorption, immobilization, and precipitation ( Bradham et al., 2018 ; Cambier et al., 2019 ). After soil application, VC provides polysaccharides, the release of mucus from earthworms and microorganisms, and improves soil physical structure, i.e., aeration, porosity, aggregate stability, and drainage, all of which are beneficial to crop root growth, as well as nutrient uptake by plants ( Lim et al., 2015 ; Hussain et al., 2021 ). VC is a rich source of plant micronutrients and macronutrients, hence adding VC improved the mineral elements in soils, resulting in increased plant growth and production ( Maji et al., 2017 ; Dubey et al., 2020 ; Goswami et al., 2024 ). However, limited studies have evaluated VC’s effects on paddy soil properties, fragrant rice Cd uptake, plant physiological and antioxidant defense function, and rice production under Cd toxicity.

Given previous consideration, this research investigated the application of VC as a soil conditioner, which is a potential remediation technique in Cd-polluted fields. We used aromatic rice cultivars MXZ-2 and XGZ, which are popular in southern China due to their pleasant flavor ( Luo H. et al., 2020 ; Luo Y. et al., 2020 ; Zhang et al., 2022 ). Rice, a semi-aquatic tropical plant grown on marshy lands, is very susceptible to Cd uptake and accumulation in organs ( Wu et al., 2014 ). The presence of Cd in arable soil is common, particularly in China, it can be absorbed by rice plants. This metal accumulates in the grains, posing a significant threat to both the quality and nutritional value of rice. This contamination adversely affects human health and crop production ( Zeng et al., 2019 ; Adil et al., 2024 ). High concentrations of Cd in rice grains not only alter their taste and texture but also diminish their nutritional content ( Bin Rahman and Zhang, 2023 ). Consumption of Cd-contaminated rice grains can lead to health issues such as kidney damage, skeletal abnormalities, and potentially cancer ( Song et al., 2015 ). Therefore, addressing Cd toxicity in rice cultivation is crucial for ensuring the food safety and nutritional security of communities globally. In this study, we applied VC as a composite material in Cd-contaminated soil to counteract the negative impacts of Cd on soil fertility, plant physiological and biochemical attributes, and grain yield. To the best of our knowledge, there is a lake of knowledge regarding the measured variables in this study in the context of soil and fragrant rice crops relative to different VC amendments under Cd toxicity conditions. The main objectives of the study were: (1) to investigate the impacts of VC on soil environmental parameters and soil fertility (2) to assess the role of VC in plant physiology, especially its impact on photosynthetic performance and leaf ultrastructure (i.e., chloroplast, cell wall, and vacuole), and biochemical attributes (3) to explore the effect of VC application on fragrant-rice yield and the role of soil fertility in plant physiological and biochemical activity. The present work hypothesized that applying VC can improve soil health which in turn increases plant physiological activity and antioxidant defense systems under Cd toxicity. This work will produce a conceptual framework for safe and sustainable crop production in Cd-contaminated soils.

2 Materials and methods

2.1 experimental place and basic soil qualities.

A pot study was carried out at the South China Agriculture University Research Station. The soil of the experimental site (0–15 cm) is slightly acidic, with a pH of 5.88. Furthermore, the soil has 23.75 g kg −1 organic matter, 1.18 g kg −1 TN, 145.40 mg kg −1 available N, and 0.98 g kg −1 phosphorus. Supplementary Table S1 also includes details about the soil’s qualities.

2.2 Experimental details

In the present research, we used two different fragrant rice varieties, MXZ-2 and XGZ, which respond differently to Cd-stress conditions ( Imran et al., 2020 ). Both cultivars were obtained from the College of Agriculture, South China Agriculture University. The experiment was conducted in complete block design in the early season of 2023 (March–July). The soil was obtained to a depth of 15 cm from the paddy field and then placed into plastic pots. Further, it was ensured that all pots contained the same size and weight of soil to minimize experimental error. The recommended dose of VC was applied 1 week ago from seedling transplantation. The applied VC was manufactured by Hubei Tianhenjia Biological Environmental Protection Technology Co., Ltd., Wuxue City, Hubei Province, China; it consisted of 34.90% organic matter, 1.48% TN, 2.76% P 2 O 2 , and 1.00% K 2 O, and had a pH of 7.6. Three VC rates, such as VC1 = 0 t ha −1 , VC2 = 3 t ha −1 , and VC3 = 6 t ha -1, and two doses of Cd (Cd, 0 and 50 mg Cd kg −1 ) were tested. The study included six treatments: (1) Neg-Cd + VC1 = 0 mg Cd + 0 t ha −1 VC, (2) Neg-Cd + VC2 = 0 mg Cd + 3 t ha −1 VC, (3) Neg-Cd + VC3 = 0 mg Cd + 6 t ha −1 VC, (4) Pos-Cd + VC1 = 50 mg Cd + 0 t ha −1 VC, (5) Pos-Cd + VC2 = 50 mg Cd + 3 t ha −1 VC, and (6) Pos-Cd + VC3 = 50 mg Cd + 6 t ha −1 VC. The seeds of the fragrant rice cultivars were used as a test crop and cultivated in a plastic pot, with each pot containing three hills. The seedlings were transplanted into pots in mid-March, and the rice crops were harvested in mid-July. The NPK dose was 300:150:300 (kg ha −1 ) 1.80 g of N was used as urea, 0.90 g of P 2 O 2 as superphosphate, and 2.20 g of potassium chloride. Uniform flooding irrigation was maintained from the planting of seedlings to physiological maturity to establish anaerobic conditions in the pots. Usual farming practices, such as insecticide and pesticide application, were applied in all treatments.

2.3 Sampling and analysis

2.3.1 soil chemical attributes.

A core sampler was used to gather soil samples at a depth of 15 cm before to seedlings and after harvest. The samples were then separated into two separate portions, one half for soil nutritional evaluations and the other for molecular analysis and stored at −80°C. Soil organic C (SOC) was examined using the K 2 Cr 2 O 7 -H 2 SO 4 oxidation method posted by Wang et al. (2003) . Furthermore, the Ohyama (1991) approach was employed for TN. The TN was determined using Jackson’s (1956) micro-Kjeldahl technique. Finally, Lu’s (2000) techniques evaluated soil pH, AN, TP, and TK.

2.3.2 Rice grain yield and leaf physiological attributes

At maturity, rice plants from the pot were picked to examine grain yield adjusted to 14% moisture content. Moreover, at the tillering and heading stages, several gaseous exchange parameters were examined, including transpiration rate (Tr), net photosynthetic rate (Pn), intercellular CO 2 concentration (Ci), and stomatal conductance (gs). On a sunny day, a transportable photosynthesis machine (Li-6800, Li-COR USA) was utilized to measure photosynthesis.

Fresh leaf samples (size 1 mm 2 ) were chosen for transmission electron microscope (TEM) analysis. Small slices of leaves, about 1–3 mm, were fixed in 4% glutaraldehyde (v/v) in 0.2 mol/L PBS (sodium phosphate buffer, pH 7.2) for 6–8 h, then in 1% OsO4 for 1 h, and finally in 0.2 mol/L PBS (pH 7.2) for 1–2 h. Dehydration was performed in a graded ethanol series (50, 60, 70, 80, 90, and 100%), followed by acetone, before samples were filtered and embedded in Spurr’s resin. Finally, ultra-thin sections (80 nm) were produced and placed on copper grids for TEM imaging ( Roland and Vian, 1991 ).

2.3.3 Antioxidant enzyme activities

The antioxidant enzymes, such as superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX) activities in fresh leaves were determined by using previously described by Wu et al. (2003) . Briefly, fresh rice leaves were homogenized using sodium phosphate buffer (50 mM, pH 7.5). The homogenized sample was centrifuged at 12,000 rpm for 10 min at 4°C. The supernatant was then collected and used for subsequent assays. In the enzyme extract, the measurement of the activity of SOD was done using the enzyme solution containing methionine (750 mM), NBT (5.2 mM), EDTA (0.1 mM) and PBS (50 mM). The enzymatic activities of SOD, POD, CAT, and APX were measured as previously reported procedures ( Jiang and Zhang, 2001 ).

2.3.4 Total RNA extraction and qRT-PCR analysis

Total RNA was isolated from the samples using TRIzol reagent (Invitrogen, Carlsbad, California, United States). The qRT-PCR was then evaluated using the Pfafflfl (2001) technique, as previously reported. Rice ACTIN (Os03g50885) was utilized as a reference gene for relative quantification. Supplementary Table S1 provides information about nucleotide sequences and specific annealing temperatures. Three biological repetitions were employed, and expressions were calculated by normalizing the Ct value for every gene compared to the ACTIN value. Quantification was done using the 2 −∆∆Ct approach, as indicated in the previous study ( Pfafflfl, 2001 ).

2.3.5 Measurements of MDA and H 2 O 2

Leaf malondialdehyde (MDA) content during the vegetative and reproductive was measured by the previously reported method ( Velikova et al., 2000 ). To measure MDA contents, fresh rice leaves were sampled and immediately homogenized in 0.1% (w/v) cold TCA, and the homogenate was centrifuged at 12,000 g for 20 min at 4°C. The reaction mixture contained 0.5 mL of supernatant, and 2.5 mL of 0.5% thiobarbituric acid (TBA) solution (dissolved in 20% TCA). The reaction mixture was boiled for 30 min, and then rapidly cooled and centrifuged for 5 min at 12,000 × g. The difference between the absorbance values at 532 and 600 nm with an extinction coefficient of 155 mM cm 1 was applied to calculate the MDA contents. In addition, hydrogen peroxide (H 2 O 2 ) was investigated from the fresh samples by the technique recommended earlier ( Bates et al., 1973 ). Fresh leaf samples (0.2 g) were crushed in liquid nitrogen and homogenized with 1 mL of 0.1% trichloroacetic acid (TCA) and centrifuged at 12,000 g for 20 min (4°C) for the measurement of hydrogen peroxide (H 2 O 2 ). The reaction mixture was comprised of 0.5 mL of potassium phosphate buffer (pH 6.8, 100 mM), 1 mL potassium iodide (1 M), and 0.5 mL supernatant. The H 2 O 2 contents were measured by spectrophotometer (UV–VIS 2550, Shimadzu, Japan) at 390 nm.

2.3.6 Assessment of proline and protein level

As stated in earlier studies, the amount of proline in fresh leaves was determined using Bradford’s (1976) technique The solution was purified with 5 mL of toluene, and the absorption of red chromophore in the methanol component was obtained at the 520 nm range. Fresh leaves (0.1 g) were standardized in 50 mM sodium phosphate buffer (1 mM EDTA-Na2, 2% polyvinyl pyrrolidine-40) and spun at 10,000 × g for 15 min at 4°C and finally, the reaction solution was scanned at 595 nm for final protein content.

2.3.7 Determination of plant cd content

The dried samples were grinded and processed at a 4:1 (v/v) ratio in HNO 3 and HClO 4 before being diluted up to 25 mL. Then, Cd levels in rice organs were subsequently analyzed with a flame atomic absorption spectrometer as earlier advised by Cao et al. (2014) .

2.4 Statistical analysis

The results collected on soil chemical attributes and fragrant rice physiological, biochemical attributes and grain yield were analyzed using relevant ANOVA procedures for completely randomized design, using Statistix 8.1 software (Analytical Software). Before analysis, results were normalized using the arcsine function. Tukey’s post-hoc test was conducted to compare multiple means for variables with significant influence from experimental factors.

3.1 Effect of VC on soil fertility

The addition of VC considerably enhanced soil chemical characteristics, including SOC, pH, AN, TN, TP, and TK as compared to sole Cd-stressed soil: Pos-Cd + VC1 ( Table 1 ). The application mitigated the adverse effects of Cd on soil health, and the effect was most pronounced in all evaluated parameters at high VC amendments. Off the treatments, the non-Cd stressed soil (Neg-Cd + VC3) had higher values for soil qualitative features (i.e., pH, TN, AN, and SOC), while the solo Pos-Cd soil had the lowest values. Related to Pos-Cd + VC1, Pos-Cd + VC3 enhanced soil SOC, pH, TN, and AN by 5.78, 43.13, 178.54, and 11.38%, respectively, in Cd-contaminated soil. Likewise, low VC input increased each examined variable, although not as much as compared to VC amendments under Cd toxicity.

Table 1 . The impact of vermicompost on soil chemical composition in Cd contaminated soil.

3.2 Effect of VC on leaf gas exchange attributes and grain yield

Fragrant rice verities, XGZ and MXZ-2, showed substantial variations in photosynthesis rate with VC application in a Cd stress condition ( Figures 1 , 2 ). In Cd-contaminated soil, the VC treatment improved leaf photosynthetic characteristics such as Pn , Tr, gs, and Ci. In addition, the treatments followed a similar pattern across both development phases. Pos-Cd + VC3 enhanced Pn and Tr by 60.66 and 42.44%, correspondingly, in MXZ-2 and 66.40 and 42.44% in the XGZ, as related compared to the High VC treatment: Pos-Cd + VC3, as shown in Figure 1 . Similarly, low-VC-treated pots considerably boosted leaf physiological activity over Cd-stressed plants.

Figure 1 . Effect of vermicompost application on net photosynthetic rate (A,B) and transpiration rate (C,D) of rice MXZ-2 and XGZ at different growth periods under Cd toxicity. Tukey analyses were performed to compare the means of the treatments, and the findings were interpreted using a simple test based on the Tukey HSD test at ( p < 0.05). Error bars are standard errors of the mean. At p  < 0.05, bars with different letters show significant ( p < 0.05) differences among the treatments. ** and * indicate significance level at 1% and 5%, correspondingly. See Table 1 for treatment combination details.

Figure 2 . Effect of vermicompost application on leaf stomatal conductance (A,B) and intercellular CO2 concentration (C,D) of rice cultivars, i.e., MXZ-2 and XGZ at different growth periods under Cd toxicity. Tukey analyses were performed to relate the means of the treatments, and the findings were interpreted based on the Tukey HSD test at ( p < 0.05). At p  < 0.05, bars with distinct letters show significant differences among treatments. ** and * indicate significance level at 1% and 5%, respectively. See Table 1 for treatment combination details.

Across the growth, differences in gs and Ci were also substantially higher compared with Cd-stressed plants ( Figures 2A – D ). Across the growth stages, the Pos-Cd + VC3 enhanced gs and Ci by 60.64 and 15.30%, correspondingly, in MXZ-2 and 56.45 and 15.80%, in XGZ cultivars under Cd toxicity. Similarly, low VC-treated plants significantly ( p  < 0.05) increased gs and Ci than only Cd-stressed plants. Furthermore, findings showed that XGZ was more resilient to Cd stress than the MXZ-2 cultivar.

3.3 Leaf ultrastructure analysis under Cd toxicity

Plant growth and development depend primarily on cell elongation and division. In the present study, the plant physiological, biochemical, and yield improved with the addition of VC amendments. Thus, Pos-Cd + VC1, Pos-Cd + VC3, and Neg-Cd + VC3 treated plants were selected for leaf ultrastructure (TEM) analysis and analyzed the changes in the ultrastructure cells of fragrant rice leaves ( Figure 3 ). The leaf ultrastructure analysis showed that the Cd toxicity damages the shape and size of the cell relative to High VC-treated plants: Pos-Cd + VC3 and Neg-Cd + VC3. Under no Cd stress conditions (no Cd) supplemented with vermicomposting (Neg-Cd + VC3), chloroplasts in XGZ and MXZ-2 exhibited well-organized grana and stroma lamellae, developing complete thylakoid membrane systems. However, under Cd stress (Pos-Cd + VC1), chloroplast morphology changed gradually from oblong round to expanding spindle-like shapes, with severe deformities observed in MGZ-2 such as irregular shapes with distorted plastids and dissolution of grana lamellae. In contrast, the changes in chloroplasts (thylakoid and grana lamellae) were less severe in XGZ under Cd stress. Following vermicomposting under Cd stress (Pos-Cd + VC3), chloroplasts and thylakoid membranes in MXZ-2 partially recovered, while chloroplast structures in XGZ resembled those in plants under Neg-Cd + VC3 conditions. Resultantly, vermicomposting application eased the negative effects of Cd on chloroplast structure in both varieties (XGZ and MXZ-2) of fragrant rice.

Figure 3 . Effect of VC application on leaf ultrastructure analysis of rice cultivars such as Xiangyaxiangzhan and Meixiangzhan-2 under Cd toxicity. CW, cell wall; Ch, chloroplast; V, Vacuole. See Table 1 for treatment combination details.

3.4 Effect of VC application on enzyme activity

Antioxidant-related enzyme activities were investigated to determine the role of VC additions in mitigating Cd-induced oxidative stress in both varieties ( Figures 4 , 5 ). The findings demonstrated that Cd stress significantly reduced the antioxidant enzyme activity of rice cultivars than non-Cd stressed plants. Leaf antioxidants enzyme production changed substantially across cultivars, with XGZ exhibiting a slighter drop, indicating that it is more resistant to the Cd stress. Surprisingly VC application reduced Cd toxicity under High VC treatments while increasing antioxidant enzyme activities in leaves under Cd pollution. Across the development phases, the treatments followed a similar pattern. Averaged throughout development stages, Pos-CD + VC3 treatment substantially increased SOD (122.55 and 114.46%), POD (38.65 and 36.23%), CAT (42.46 and 45.66%), and APX (112.22 and 126.45%) activities in MXZ-2 and XGZ rice, respectively, related to Pos-Cd treated plants alone. Similarly, low VC-treated pots had significantly higher antioxidant enzyme activity than Cd-stressed plants.

Figure 4 . Effect of vermicompost application on the activity of superoxide dismutase (A,B) peroxidase (C,D) enzymes in the leaves of rice cultivars, i.e., MXZ-2 and XGZ at different growth periods under Cd toxicity conditions. Tukey analyses were performed to relate the means of the treatments, and the findings were interpreted based on the Tukey HSD test at ( p < 0.05). Error bars are standard errors of the mean. At p  < 0.05, bars with distinct letters show significant differences among the treatments. ** and * indicate significance level at 1% and 5%, respectively. See Table 1 for treatment combination details.

Figure 5 . Effect of vermicompost application on the activity of catalase (A,B) and ascorbate peroxidase (C,D) enzymes of rice cultivars, i.e., MXZ-2 and XGZ at different growth periods. Tukey analyses were performed to relate the means of the treatments, and the findings were interpreted using a simple test based on the Tukey HSD test at ( p < 0.05). Error bars are standard errors of the mean. At p  < 0.05, bars with different letters show significant differences among the treatments. ** and * indicate significance at 1% and 5%, respectively. See Table 1 for treatment combination details.

3.5 Effect of VC application on the antioxidant genes expression pattern

In the current study, the expression patterns of antioxidant-related genes of both fragrant rice cultivars are shown in Figures 6 , 7 . The gene expression levels were altered by various VC treatments under Cd intoxication. In both cultivars, Cd-stressed plants had considerably lower expression patterns of genes (such as OsPOD, OsSOD, OsCAT , and OsAPX ) than Neg-Cd plants. However, High-VC treatment reduced Cd toxicity in plants and elevated the pattern of genes related to the plant defense system. Pos-Cd + VC3 substantially enhanced transcript levels OsPOD (82.36 and 920.28%), OsSOD (88.68 and 68.65%), OsCAT (122.55 and 145.85%), and OsAPX (97.34 and 85.75%) in MXZ-2 and XGZ, relative to Pos-CD + VC1, averaged throughout development stages. Similarly, the other VC-treated plants showed significant increases in the transcription level of antioxidant-related genes.

Figure 6 . Effect of VC application on the relative expression of OsSOD (A,B) and OsPOD (C,D) of rice cultivars, i.e., MXZ-2 and XGZ at different growth stages. Tukey analyses were performed to relate the means of the treatments, and the findings were interpreted using a simple test based on the Tukey HSD test at ( p < 0.05). Error bars are standard errors of the mean of the treatments. At p  < 0.05, bars with distinct letter show significant differences among the treatments. ** and * indicate significance at 1% and 5%, respectively. See Table 1 for treatment combinations details.

Figure 7 . Effect of VC application on the relative expression of OsCAT (A,B) and OsAPX (C,D) of rice cultivars, i.e., MXZ-2 and XGZ at different growth periods. Tukey tests were performed to relate the means of the treatments, and the findings were interpreted using a simple test based on the Tukey HSD test at ( p < 0.05). Error bars are standard errors of the mean. At p  < 0.05, bars with distinct letter show significant ( p  < 0.05) differences among the treatments. ** and * indicate significance at 1% and 5%, respectively. See Table 1 for details treatment combinations.

3.6 Effect of VC application on protein and proline level

Soluble protein and proline production were significantly different with the use of VC under Cd toxicity ( Table 2 ). Both cultivars had significant variations in protein and proline content. The results showed that the Cd toxicity significantly enhanced proline levels in both stages when compared to Neg-Cd experienced plants. However, the VC modifications reduced Cd stress and lowered proline synthesis. Proline production followed a consistent pattern across development stages, and when Pos-Cd + VC3 was applied, leaf proline concentration dropped by 65.44 and 55.44% in XGZ and MXZ-2 cultivars, correspondingly, compared to Pos-Cd plants. Likewise, lesser VC addition significantly reduced proline content when compared to Cd-stressed plants. In compared to proline, the Pos-Cd plants significantly reduced the soluble protein concentration. Soluble protein levels increased linearly from the vegetative to reproductive development phases. In comparison to Pos-Cd + VC1, Pos-Cd + VC3 treated pots increased leaf total protein content by 36.22 and 42.88% in XGZ and MXZ-2 cultivars, respectively ( Table 2 ). Additionally, the results revealed that MXZ-2 had lower proline content and soluble protein than XGZ, suggesting that MXZ-2 is more vulnerable to stress conditions.

Table 2 . Effect of VC application on proline and soluble protein content of different rice cultivars under Cd toxicity.

3.7 Influence of VC application on MDA and H 2 O 2 contents under toxicity

The current findings showed that VC treatment considerably reduced the concentrations of MDA and H 2 O 2 in both varieties under Cd conditions ( Table 3 ). XGZ and MXZ-2 showed substantial ( p  < 0.05) variations for leaf MDA and H 2 O 2 levels. In contrast, solo Cd-stressed plants significantly elevated MDA and H 2 O 2 levels in both rice cultivars’ leaves. Sole Cd-stressed treatment (Pos-Cd + VC1) substantially raised the level of MDA by 68.42 and 82.66% and H 2 O 2 by 72.66 and 82.34%, respectively, in XGZ and MXZ-2 cultivars ( Table 3 ). Moreover, the outcomes revealed that the concentrations MDA and of H 2 O 2 in MXZ-2 were greater than in XGZ, showing that the XGZ cultivar is more resistant to Cd pollution compared to MXZ.

Table 3 . Effect of VC application on H 2 O 2 and MDA content of different fragrant rice cultivars (i.e., MXZ-2 and XGZ) under Cd toxicity.

3.8 Influence of VC amendments on Cd uptake in plant different organs and rice grain yield

The accumulation of Cd in several organs (root, stem + leaves, and grains) of both rice varieties is significantly ( p  < 0.05) higher in Cd stress plants ( Table 4 ). However, the use of VC reduced Cd-related toxicity and significantly lowered Cd uptake in rice different organs. The Cd content in roots was higher than shoots and grains. Off the treatments, Neg-Cd + VC3 had the minimum Cd accumulation rice plant organs, whereas Pos-Cd + VC1 had the greatest levels. The use of VC significantly lowered Cd concentrations in roots, leaves, stems, and grain. Relative to Pos-Cd, the High VC (Pos-Cd + VC3) decreased the uptake of Cd in the MXZ-2 rice cultivar by 35.66, 46.65, and 73.55% in roots, shoots, and grains, respectively. Similarly, relative to Pos-Cd, the High-VC3 treatment reduced Cd absorption in XGZ cultivar by 33.45, 43.88, and 70.66% in roots, shoots, and grains, correspondingly. The data demonstrated that a high VC dosage significantly decreased Cd uptake in rice plants. Furthermore, the results showed that MXZ-2 accumulated more Cd than XGZ, implying that the aromatic rice XGZ is more resistant to Cd contamination soil than MXZ-2.

Table 4 . The effect of VC uses on Cd accumulation in aromatic rice varieties in various organs and grain yield under Cd stress.

Additionally, the Cd stress reduced the fragrant rice yield and productivity. However, the VC application improved the rice yield and productivity; off the treatment, Neg-Cd + VC3 resulted in a higher rice grain yield. In addition, Pos-Cd + VC3 enhanced grain yield by 40.2% in MXZ-2 and 41.40% in the XGZ cultivar as compared to Pos-Cd + VC1 ( Table 4 ). Similarly, low-VC-treated pots considerably improved the rice grain yield under Cd toxicity.

3.9 Relationship between soil properties, leaf net photosynthetic rate and antioxidant enzyme activity

A linear regression analysis were conducted to assess the role of soil quality in improving plant physiological activity and antioxidant defense system in the present study ( Figure 8 ). A positive correlation was noted between the soil chemical traits, such as SOC and TN content with leaf net photosynthetic rate ( Figures 8A , B ). Furthermore, the correlation analysis showed that the SOC and TN were highly positively correlated with the net photosynthetic rate ( R 2  = 0.63*; Figure 8A ) and ( R 2  = 0.60*; Figure 8B ), respectively. The regression analysis exhibited that the improvements in leaf physiological activity are directly associated with soil quality, suggesting that higher soil health results in higher plant physiological activity. In addition, the correlation study among net photosynthetic levels and antioxidant enzyme activity also showed a highly positive correlation ( Figure 9 ). The analysis showed that the photosynthetic rate was highly strongly correlated with the antioxidant enzyme activity (i.e., SOD; R 2  = 0.84**; Figure 9A , POD; R 2  = 0.92**; Figure 9B , CAT; R 2  = 0.90**; Figure 9C , and APX; R 2  = 0.80**; Figure 9D ). These analyses displayed that the improvement in leaf physiological activity is directly related to plant antioxidant defense systems. Thus, the improvements in plant antioxidant systems and physiological performance are related to soil health and fertility.

Figure 8 . Linear regression analysis between soil organic carbon (SOC) and total nitrogen (TN) with leaf net photosynthetic rate ( Pn ) under VC application in a Cd-contaminated soil ( n  = 6). * P < 0.05.

Figure 9 . Linear regression analysis of leaf net photosynthetic rate ( Pn ) with antioxidant enzyme activity [i.e., SOD (A) , POD (B) , CAT (C) , and APX (D) ] under the application in a Cd-contaminated soil ( n  = 6). ** P < 0.01.

4 Discussion

The physio-biochemical and antioxidant defense systems of plants are all disrupted by heavy metal pollution, particularly Cd toxicity. This results in significant yield reductions and losses in yield production and quality, which act as a serious risk to human health via the food chain ( Liang et al., 2017 ). In situ stabilization, which involves immobilizing Cd through the application of organic fertilizers such as cattle dung, vermicompost, and biochar, is an effective and environmentally benign method recently ( Ali et al., 2020 ; Hamid et al., 2020 ). In the present investigation, we examined how VC amendments affected the chemical properties of the paddy soil, the physio-biochemical features of the plants, the antioxidant defense systems, and the leaf ultrastructure of fragrant rice grown in soil contaminated with Cd.

4.1 Soil properties

According to Table 1 of this investigation, the use of VC greatly improved the soil qualitative characteristics under Cd toxicity. We noted that VC biodegrades improve soil quality and slowly release of plant-required nutrients throughout plant growth. The higher pH values were noted under VC amendments addition as compared to non-VC treated soil. According to Ni et al. (2018) , nitrification generates H + and lowers soil pH when synthetic N fertilizer is used only. The acidic characteristics of synthetic N may cooperate in reducing soil pH ( Iqbal et al., 2019 ; Adekiya et al., 2020 ). On the other hand, soil acidity was greatly decreased by adding organic N additions ( Iqbal et al., 2021a , b , 2023b ). Likewise, in this study, the addition of VC significantly enhanced the pH of the soil ( Table 1 ). This could be explained by the fact that the hydroxyl ions (OH − ) from a-charged functional group in organic additions and the hydrolysis of CaCO 3 produce hydroxyl ions (OH − ) that interact with H + ions to increase the pH of the soil. These hydroxyl ions include phenolic, hydroxyl, and carboxyl groups ( Gul et al., 2015 ). Most growing plants would benefit from the pH of the soil being adjusted by the VC to a roughly neutral level ( Fernández-Bayo et al., 2009 ).

Additionally, the addition of VC significantly improved the soil nutrient status in the present study. The possible explanation for this is the fact that the organic compost has a high ratio of organic matter and other essential plant nutrients ( Tejada et al., 2010 ; Iqbal et al., 2023a , b ). According to Liang et al. (2017) , heavy metals typically do not melt or migrate readily in high-pH soil. Thus, it is possible that the higher soil pH caused by the application of VC fertilizer played an important role in slowing Cd migration in the soil in this experiment. Furthermore, the addition of VC improved soil nutrient availability, leading to greater plant growth and productivity in the current study ( Table 1 ). The application of VC facilitates the secretion of mucus by earthworms, polysaccharides, and microorganisms, all of which improve the soil’s physical structure, which is important for plant root growth and nutrient uptake ( Lim et al., 2015 ). In conclusion, vermicomposting enriches the soil with beneficial microbes, enzymes, and humic acids, hence improving soil structure and water retention capacity ( Iqbal et al., 2023a ). This increases nutrient availability to plants, allowing stronger root development and better nutrient uptake ( Iqbal et al., 2024b ). Furthermore, the VC addition enhances soil biodiversity by promoting the beneficial microbes which in turn enhances plant growth directly by production of plant growth-regulating hormones and enzymes and indirectly by controlling plant pathogens, nematodes, and other pests, thereby enhancing plant health and minimizing yield loss ( Pathma and Sakthivel, 2012 ). Interestingly, its slow release of nutrients provides long-term fertility, decreasing the demand for artificial fertilizers and minimizing environmental effects ( Pathma and Sakthivel, 2012 ). Overall, the use of VC improves soil fertility while also encouraging sustainable farming practices by promoting long-term soil health and productivity.

4.2 Leaf physiological and plant biochemical attributes

Photosynthesis is the main element of plant physiological activity and productivity by enhancing crop growth and biomass accumulation ( Khan et al., 2017 ; Iqbal et al., 2020 ; Ali et al., 2021 ). In the present study, the VC enhanced the plant photosynthetic efficiency, including, Tr, g s , and Ci, in VC-treated plants as compared to non-VC-treated plants under Cd stress ( Figures 1 , 2 ). The enhancement in leaf photosynthetic activity induced under VC application could be primarily attributed to the improved soil fertility ( Table 1 ), faster release of soil nutrients from VC in the early growth stages and gradual and slow release of crop-related nutrients from VC throughout the crop period ( Yang et al., 2015 ; Luo H. et al., 2020 ; Luo Y. et al., 2020 ; Iqbal et al., 2022 ). Photosynthesis experienced a strong reaction to water and soil health ( Makoto and Koike, 2007 ). A sufficient supply of water and nutrients will decrease the number of water-soluble nutrients and the stress-inducing root-sourced signal (ABA), which will open the stomata on leaves and increase their water potential and physiological activity ( Daszkowska-Golec and Szarejko, 2013 ). In addition, the linear regression analysis in the present study also showed a highly positive relation between soil chemical traits and leaf photosynthetic activity ( Figure 8 ). Aslam et al. (2020) , reported that the application of VC improves the plant’s morphological and physiological attributes.

The VC addition enhances crop growth, yield, and quality due to its plant growth-promoting characteristics. VC stimulates plant emergence because of the availability of essential plant nutrients ( Iqbal et al., 2024a , b ). According to Khan et al. (2021) , antioxidants can lessen oxidative damage and reactive oxidative stress in plants, which is important for plant defense systems. Under the Cd stress condition, the plant’s physiological and biochemical attributes significantly ( p  < 0.05) reduced in the current study ( Figures 4 , 5 ). Furthermore, the Cd toxicity damaged leaf ultrastructure components such as cell wall, chloroplast, and vacuoles ( Figure 3 ). However, the VC addition counteracted the Cd toxicity and healed the plant’s oxidative damage, which may be linked to an increase in the activity of antioxidant enzymes and the expression of genes encoding antioxidants ( Figures 4 – 7 ). According to earlier research, SOD, POD, CAT, and APX protected plants against oxidative plant damage by acting as antioxidant enzymes ( Hasanuzzaman et al., 2020 ; Moustafa-Farag et al., 2020 ). In this study, we also found that pots containing Cd had lower SOD activity. This could be the case as SOD, which reduces reactive oxidative stress and transforms hazardous O2 into less toxic H 2 O 2 , is the antioxidant system’s first line of defense ( Anjum et al., 2011 ). Similarly, a similar pattern was observed in the activity of CAT, which protects plant cells by turning O 2 into the less toxic H 2 O 2 , thereby reducing oxidative stress ( Sanchez-Casas and Klessig, 1994 ; Iqbal et al., 2023a , b ). The procedure involved in eliminating O 2 and the increased formation of H 2 O 2 and MDA in the current investigation may be the cause of the significant decline in antioxidant enzyme activity under Cd stress ( Table 3 ). On the other hand, both aromatic rice varieties’ antioxidant enzyme activity was enhanced by VC addition, which may have been a major factor in improving plant growth and antioxidant defense system. Moreover, the results of the linear regression analysis demonstrated that increased leaf physiological activity enhanced the antioxidant defense system and leaf ultrastructure, including the cell wall, chloroplast, and vacuole ( Figures 3 – 5 ). Additionally, the expression level of antioxidants encoding genes is strongly elevated in plants treated with VC ( Figures 6 , 7 ). According to Gao et al. (2013) , VC enhances the activity of antioxidant enzymes and so helps in the production of crops by shielding the leaf chloroplast structure from reactive O 2 .

Plant cytoplasm contains a substance called proline, which regulates osmotic pressure by altering the water potential of cells ( Muneer et al., 2011 ). In this study, under Cd-stress situations, leaf proline content was boosted significantly ( Table 2 ). Plant proline levels are elevated by heavy metal stress, especially Cd toxicity because stressed plants are more resilient ( Bauddh and Singh, 2012 ). Plant protein degradation may be linked to an increase in proline content and plant damage may be reflected in an increase in proline levels in plant tissue ( Palma et al., 2002 ). Our results are consistent with Elmer and White (2018) and Cao et al. (2014) who reported that the increased protease activity caused protein deficiency under Cd stress conditions. Similar findings were stated by other researchers that the production of soluble protein is significantly affected by stress conditions, particularly by Cd stress ( Palma et al., 2002 ; Cao et al., 2014 ). However, the VC application alleviated the adverse effect of Cd on plants and greatly increased the protein content in the leaves of rice in the present study ( Table 2 ). According to our findings, adding VC amendments to the soil improved its fertility, which in turn improved the physiological and biochemical processes of the plant by facilitating the uptake and accumulation of vital nutrients. Moreover, the VC application lowered the leaf proline content and strengthened plant defense systems due to improved plant physiological activity, indicating a moderating effect in preserving plant osmotic balance under Cd-contaminated soil ( Table 2 ). The results of the linear regression analysis also demonstrated a strong and positive correlation between plant antioxidant defense systems and the leaf net photosynthetic rate ( Figure 9 ).

The present research demonstrated that increased MDA and H 2 O 2 generation were indicative of enhanced oxidative damage and leaf ultrastructure in the plant under Cd stress ( Table 3 ). However, by lowering Cd uptake and aggregation in rice organs, VC treatments lessened the harmful effects of Cd ( Table 4 ). Adding VC to soils not only gives plants vital nutrients for growth but also acts as a soil additive by causing heavy metals in the soil to become more complex, soluble, and precipitated. The VC reduces the mobility and uptake of Cd in plants ( Huang et al., 2018 ). Therefore, by enhancing plant growth and antioxidant defense systems, the VC significantly decreased MDA and H 2 O 2 in rice leaf organs. This suggests that the VC application lessened intracellular membrane disruptions caused by Cd throughout plant growth and development.

4.3 Cd accumulation in rice plant’s different organs and grain yield

In the current study, the use of VC dramatically decreased the absorption and content of Cd in rice in organs, including the roots, shoots, and grains ( Table 4 ). The organic VC treatment, which reduced the accessibility and mobility of Cd in arable soil, is mostly responsible for this behavior. By enhancing the complexation and precipitation of metals in farming soil, VC addition can serve as a soil additive, giving plants nutrients and organic matter while simultaneously reducing their mobility and availability of heavy metals ( Deng et al., 2017 ). However, VC amendments, because of its vast surface area, high cation exchange capacity, and richness in active functional groups, VC may be considered a promising treatment for stabilizing heavy metals in soil ( Wang et al., 2018 ; Ding et al., 2021 ). When compared to soils that have not been treated with VC, the possibility of Cd absorption and uptake n in plant roots is therefore much decreased. Additionally, Wan et al. (2020) noted that supplying more organic fertilizers significantly decreased the amount of Cd in rice grain, ranging from 7.8 to 79.3%. In a similar vein, Tang et al. (2015) discovered that adding organic amendments decreased the amount of metal in B. chinezsis plant roots and shoots growing in acidic soil.

In the present study, the addition of VC significantly increased fragrant rice yields in Cd-stressed soil ( Table 4 ). Improvements in crop production and quality are closely associated with enhancements in soil physiochemical and biological properties ( Iqbal et al., 2021a , b ). Organic fertilizers enhance soil health and fertility, which increases plant growth, crop yield, and yield elements ( Ali et al., 2020 ; Iqbal et al., 2022 ). In this study, increased soil nutritional values were found in VC-treated soil ( Table 1 ), which improved aromatic rice growth, physiological activity, and yield by giving the necessary nutrients across the growing period. This was supported by linear regression, which revealed that soil chemical features were highly positively related to leaf physiological traits ( Figure 8 ). Iqbal et al. (2022) found that differences in yield are positively linked with soil biochemical state. Thus, variations in rice yield and yield components are largely dependent on soil health and nutrition.

5 Conclusion

This study aimed to determine how VC application reduced the adverse impacts of Cd toxicity on soil health and fragrant rice growth and grain yield. The results showed that the soil quality and physiological and metabolic efficiency of the fragrant rice cultivars were adversely affected by Cd toxicity. Moreover, under Cd stress, there was an increase in proline, MDA, and H 2 O 2 production, as well as Cd uptake and accumulation in rice organs, particularly in the roots and leaves. However, the VC application alleviated the Cd toxicity on soil health and plant physiological and biochemical attributes. The application of VC simultaneously immobilized Cd in paddy soil and enhanced the chemical characteristics of the soil due to its vast surface area, high cation exchange capacity, and richness in active functional groups and nutrients. Our findings concluded that the addition of VC enhances plant growth and production by promoting soil fertility which in turn enhances plant nutrient uptake and reduces Cd toxicity. Overall, the use of VC improves soil fertility while also encouraging sustainable farming practices by decreasing the demand for synthetic fertilizers and promoting long-term soil health and crop productivity.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary material , further inquiries can be directed to the corresponding authors.

Author contributions

AI: Conceptualization, Methodology, Project administration, Supervision, Visualization, Data curation, Formal analysis, Investigation, Software, Writing – original draft. RK: Methodology, Formal analysis, Software, Validation, Visualization, Writing - review & editing. QH: Formal analysis, Methodology, Software, Validation, Writing – review & editing, Conceptualization, Data curation, Investigation, Visualization. MI: Methodology, Formal analysis, Software, Validation, Visualization, Resources, Writing - review & editing. ZM: Conceptualization, Data curation, Investigation, Methodology, Software, Writing – review & editing, Project administration, Resources, Supervision. TH: Data curation, Formal analysis, Methodology, Software, Supervision, Visualization, Writing – review & editing, Project administration, Resources. MA: Conceptualization, Formal analysis, Methodology, Software, Supervision, Writing – review & editing, Data curation, Visualization. IA: Formal analysis, Funding acquisition, Methodology, Resources, Software, Supervision, Validation, Writing – review & editing. HR: Funding acquisition, Methodology, Supervision, Writing – review & editing, Conceptualization, Formal analysis, Project administration, Software. MS: Conceptualization, Methodology, Project administration, Supervision, Validation, Writing – review & editing, Formal analysis, Funding acquisition, Resources, Software, Visualization. AE: Writing – review & editing, Funding acquisition, Methodology, Resources, Supervision, Validation. RL: Conceptualization, Methodology, Project administration, Supervision, Validation, Writing – review & editing. XT: Writing – review & editing.

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Our work was supported by the Guangzhou Science and Technology Project (202103000075) and the Talent Introduction and Research Program of South China Agriculture University (41000-222106).

Acknowledgments

The authors extended their appreciation to the Researcher Supporting Project Number (RSPD2024R745), King Saud University, Riyadh, Saudi Arabia. In addition, we want to thank our South China Agriculture University Research Station collaborators for their research assistance.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fsufs.2024.1418554/full#supplementary-material

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Keywords: antioxidant-encoding genes, cadmium toxicity, fragrant rice, leaf physiological activity, soil fertility, vermicompost

Citation: Iqbal A, Khan R, Hussain Q, Imran M, Mo Z, Hua T, Adnan M, Abid I, Rizwana H, Soliman Elshikh M, El Sabagh A, Lal R and Tang X (2024) Vermicompost application enhances soil health and plant physiological and antioxidant defense to conferring heavy metals tolerance in fragrant rice. Front. Sustain. Food Syst . 8:1418554. doi: 10.3389/fsufs.2024.1418554

Received: 16 April 2024; Accepted: 24 July 2024; Published: 07 August 2024.

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Copyright © 2024 Iqbal, Khan, Hussain, Imran, Mo, Hua, Adnan, Abid, Rizwana, Soliman Elshikh, El Sabagh, Lal and Tang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Anas Iqbal, [email protected] ; Xiangru Tang, [email protected]

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