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SPECIALTY GRAND CHALLENGE article

Plant biology research: what is next.

$\nAnna N. Stepanova$

Department of Plant and Microbial Biology, Program in Genetics, North Carolina State University, Raleigh, NC, United States

Plant biology is a key area of science that bears major weight in the mankind's ongoing and future efforts to combat the consequences of global warming, climate change, pollution, and population growth. An in-depth understanding of plant physiology is paramount to our ability to optimize current agricultural practices, to develop new crop varieties, or to implement biotechnological innovations in agriculture. The next-generation cultivars would have to withstand environmental contamination and a wider range of growth temperatures, soil nutrients and moisture levels and effectively deal with growing pathogen pressures to continue to yield well in even suboptimal conditions.

What are the next big questions in plant physiology, and plant biology in general, and what avenues of research should we be investigating and training students in for the next decade? As a plant scientist surrounded by like-minded individuals, I hear a lot of ideas that over time turn into buzz words, such as plant resilience, genotype-to-phenotype, data science, systems biology, biosensing, synthetic biology, neural networks, robustness, interdisciplinary training, new tool development, modeling, etc. What does it all mean and what are the main challenges that we should all be working on solving? Herein, I present my personal perspective on what the immediate questions and the biggest longer-term issues in plant science are. I suggest some themes and directions for future research in plant biology, some relatively obvious and some potentially unique, having been shaped by my own professional interests, experiences and the background in plant molecular genetics and physiology.

Integration, Packaging, Visualization and Interpretation of Existing OMICS and Genetic Data

For the past three decades, a lot of emphasis has been made on a small set of plant model organisms, primarily on Arabidopsis. There is no other plant on earth we know as much about as we do about this mustard weed. One clear need in the area of plant sciences is to make sense of the vast amount of descriptive phenotypic data that have been generated for this species and a handful of others—the transcriptome, metabolome, proteome, phenome, interactome, etc.—and the amazing genetic resources that have been built: mutants, transgenic lines and natural accession germplasm collections, tools and protocols, genomic sequences and other resources ( Koorneef and Meinke, 2010 ). Now, how do we organize these data into a series of integrated, comprehensive, user-friendly, cross-communicating databases that are easily accessible, searchable, trackable, and visual, with data that are downloadable and compatible with comparative analyses? How do we display the available data at a variety of scales, from the subcellular to the organismal and population level—think Google Earth but for an ecosystem or an agricultural field that allows you to zoom in and out to see the overview and the closeup—perhaps, by integrating and expanding existing initiative likes Plant Cell Atlas and ePlant ( Waese et al., 2017 ; Rhee et al., 2019 )? With the genome sequences of these select organisms in hand, often of multiple accessions of each, what can we learn about the genotype-to-phenotype relations? How can we use that knowledge to extrapolate the rules or patterns we discover in model organisms to species for which we have no experimental data beyond possibly a draft-quality genomic sequence and a few fragmentary phenotypic datasets? In other words, can the data obtained in reference organisms be leveraged to infer useful information relevant to a wide range of species of agricultural, ecological or, perhaps, ethnobotanical importance? Let's look into some examples of that.

Translational Research: Moving Foundational Discoveries From Models to Crops

It comes as no surprise that for the past 10–20 years the emphasis has been gradually shifting from Arabidopsis to non-model organisms, including crops and rare plant species. The key reason for that is the pressing need to move fast on crop improvement and plant conservation in light of the worlds' fast-growing population, climate change, pollution, habitat and agricultural land loss, and ever-increasing pathogen pressures. This shift of research focus is also steered by changing governmental policies and funders' priorities. To make the transition to studying crops and other non-models as smooth as possible, robust computational pipelines are needed that produce high-quality genome assemblies from combinations of short- and long-read sequences. In this regard, tackling the much more complex genomes of polyploid species presents an even greater challenge. With the genome sequences and high-quality assembles on hand, orthologous genes that have previously been studied only in reference organisms need to be tested for function in candidate processes in the non-model species of interest to determine what aspects of their function are conserved and what features are divergent. The key bottleneck in this process is, of course, the recalcitrance of many non-models to genetic transformation and plant regeneration ( Anjanappa and Gruissem, 2021 ). Thus, a major effort would need to be invested into new method development to improve the plant in vitro culturing, genetic transformation and regeneration pipelines, with the ectopic activation of morphogenesis genes like BABY BOOM, WUSCHEL, LEAFY COTYLEDON1 and 2 , and several others holding major promise for boosting the regeneration efficiency of otherwise recalcitrant plant species and cultivars ( Gordon-Kamm et al., 2019 ). Further optimization of genome editing technologies, including classical gene disruption through indels as well as more targeted gene edits via base- and prime-editing or homologous-recombination-based methods, should enable highly tailored manipulation of genes of interest. The foundational knowledge gained in both model and non-model organisms can then be leveraged by applied plant biologists and environmentalists in crop improvement and plant conservation.

Interpreting the Code

One aspect of experimental research we have become good at over the past 10 years is genome and transcriptome sequencing. The current challenge is to learn to infer what the sequence tells us about what a gene does and how it is regulated based on the code alone. Can we look at gene's genomic sequence and infer not only the gene function, but also the different levels of gene regulation, all from just the sequence without any additional experimentation? To elaborate on that distinction between function and regulation, we can already infer the likely function of an orthologous gene in a crop (previously studied in another species) based on the degree of conservation of its genomic sequence, and deduce, for instance, an enzymatic reaction a protein may catalyze, or a DNA element a transcription factor may bind, or a specific ion the channel may transport, or an array of ligands or other molecules a protein may interact with. What we cannot yet reliably do is to predict based on the gene sequence alone when and where the gene is transcribed and what environmental or developmental stimuli alter its expression, how stable its transcript is, what splicing patterns the transcript has in specific cell types or conditions, or what factors dictate these patterns, or how well the transcript is translated, how the protein folds, where in the cell the protein is targeted, what its half-life is, and so on. Can we someday look at the gene sequence and predict whether the gene is essential or what organ or tissues will be affected in the loss- or gain-of-function mutant, and what phenotype the mutant will show, all without having to run an experiment? Once we learn to do that for a diploid model plant, can the knowledge be translated to polyploids that may have a greater level of gene redundancy and potentially more cases of neofunctionalization? How do we gain that extraordinary power?

One of the critical components of the inferring-the-function or genotype-to-phenotype challenge will involve machine learning and neural network models, with the size and quality of the training datasets presenting as the likely bottleneck that would determine the accuracy of neural networks' predictions ( Ching et al., 2018 ). While the role of computational biologists in this endeavor would be to develop new algorithms or adapt existing pipelines and test the models, the irreplaceable function of experimental plant biologists in this effort will be to generate the most complete and robust datasets for model training. This inevitably brings us to the next big theme, data quality.

Data Quality: Standardization, Reliability, Robustness and Tracking

As experimental scientists, most if not all of us have had the negative experience of not being able to reproduce an important result (sometimes even our own) or confirm the identity of a material someone has shared with us (e.g., a strain, a plasmid, or a seed stock from a colleague or another lab). Issues with biological variation (e.g., differences in germination between seed batches), small sample size (due to prohibitive cost, time or material constraints, or other limitations), human error (suboptimal labeling nomenclature, poor tracking, inadequate record keeping, substandard experimental design, miscalculation, personnel changes, or outright sloppiness) or malfunctioning instrumentation (in many cases, due to the lack of funding or time to upkeep or upgrade the equipment) can all contribute to the limited reproducibility of experimental data or sample mix-up. Rarely is the wrongdoing intentional, but the consequences of these errors can be enormous. What can we do to minimize mistakes, standardize internal lab protocols and record keeping, and ultimately improve the reproducibility of published data? I would support a universal funder's mandate for detailed electronic note keeping (much like private companies require), automatic data backups and regular equipment upgrades, meticulous planning before an experiment is run (including developing a comprehensive sample labeling nomenclature, beyond the common 1, 2, 3), inclusion of universal controls (e.g., Arabidopsis Columbia accession included in every Arabidopsis experiment irrespective of what other germplasm is being tested), extensive sample replication, validation of the results at multiple steps in the process (like Sanger sequencing of construct intermediates), and other common-sense but often time-consuming practices (such as regrowing all genotypes side by side and using fresh seed stocks in an experiment to minimize seed batch effects, or resequencing every construct before donating it to the stock center or sharing it with others).

A different yet related constraint we often encounter in plant sciences is the inability to track and/or obtain the materials or datasets reported by other research groups or oftentimes even by prior members of one's own lab. To ensure the long-term availability and unrestricted access to published constructs, germplasm, omics datasets and other resources generated by the public sector, funding agencies should make it mandatory for all materials and data to be deposited in relevant stock centers, sequence repositories, etc. immediately upon publication. I often wonder whether this practice could be encouraged if one's scientific productivity and impact were to be evaluated not only by the number of papers published, but also by the number of stocks or datasets deposited and their usage by the community (e.g., the frequency of stock orders or data downloads). Publishers, on the other hand, should fully enforce the old rules that all submitted manuscripts must adhere to the established guidelines for proper scientific nomenclature (e.g., gene accession numbers, mutant names, or chemical structures) and include community access codes (e.g., gene identifiers, mutant stock numbers, Genbank accession codes, etc.) and detailed annotations for all materials and data utilized or generated in a study, with the compliance being a prerequisite for publication. These simple steps would reduce ambiguities, facilitate resource tracking, and make published materials and datasets universally available.

The extra effort invested into careful experiment planning, execution, record keeping, and making published materials and datasets trackable and accessible will undoubtedly lead to fewer but higher-quality research papers being published and ultimately save time and resources down the road. Of course, an external mandate for greater rigor and accountability would also mean the need for funding agencies to financially support the extra effort and develop ways to monitor the labs' adherence to the new stricter rigor and dissemination practices, but it is commonsense that in the long run it is cheaper to do the experiment right the first time around than waste years trying to reproduce or follow up on erroneous data or remaking the resource that has been generated previously.

Synthetic Biology

An exciting and highly promising area of sciences that plant biologists are starting to embrace more widely is synthetic biology. First, what is synthetic biology? To a plant biologist, it is a useful extension of classical molecular genetics that integrates basic engineering principles and aims to rebuild biology from the ground up. Traditionally, classically trained biologists approach learning about nature from top to bottom, much like a curious child trying to break a toy apart to see what it is made of. Synthetic biologists, vice versa, try to rebuild a functional system from its pieces to understand what its minimal required components are. In plant biology, we are still very far from being able to rebuild entire plants or plant cells from scratch, but we can reconstitute the pathways, e.g., those that we have previously studied in their native context, in a heterologous host cell, aka the chassis, or introduce simple gene regulatory circuits we have artificially built. Why would we want to do that? For one, to see if we can recreate the native behavior to ensure that we fully understand the pathway or the mechanism of regulation. In addition, this can be a useful endeavor from a practical perspective, as is the case in metabolic engineering, where a native or semi-synthetic biosynthetic pathway is expressed in a heterologous host (an intact plant or a cell suspension) to produce a valuable metabolite ( Lu et al., 2016 ; Birchfield and McIntosh, 2020 ), or in biosensing, where a synthetic genetic construct is introduced to turn the host into a bio-detector for a particular stimulus or ligand of interest, e.g., a metabolite ( Garagounis et al., 2021 ).

We do not fully comprehend what we cannot ourselves recreate. We may know, for example, that a gene is induced, for example, by heat stress, but that observation does not tell us anything about the developmental regulation of that gene, or what other biotic or abiotic factors control this gene's expression. An illustrative example of how limited our current knowledge is and how synthetic biology can help us to bypass the lack of comprehensive understanding is to try the following mental exercise. How would one go about conferring a desired pattern of expression to a gene of interest, so that the gene is transcribed, for example, only in a flower, in the anthers at a particular stage of flower development, and only in response to heat stress? If we are talking about a model organism, we can scavenge available transcriptomic data in hopes of finding a native gene with such a pattern, but chances are that most anther-enriched genes will be expressed elsewhere and/or will be regulated by stimuli other than the heat stress. With the vast amount of transcriptomic data and limited ChIP-seq, DAP-seq and chromatin availability data (ATAC-seq, DNase-seq, etc.), we still have no reliable ways to infer transcription patterns of a native gene across all tissues and conditions. A combination of bioinformatic analysis (to identify putative transcription factor binding sites based on sequence conservation) ( Zemlyanskaya et al., 2021 ), classical transgene promoter bashing (that involves building a series of transgenes with chunks of the promoter deleted or replaced in an effort to characterize the effect of these targeted DNA modifications on the expression of a reporter gene in a systematic manner) ( Andersson and Sandelin, 2020 ), and/or more recently, in planta promoter bashing via genome editing (i.e., generating targeted promoter modifications directly in the native genomic context) ( Pandiarajan and Grover, 2018 ) are often relied upon to identify regulatory cis -elements in the promoters of interest. However, these approaches will not be enough to identify the full array of the DNA cis -elements that dictate the spatiotemporal regulation of a gene of interest, but these strategies may be helpful at pinpointing some candidate cis -elements and experimentally validating which elements are required.

If a particular DNA element is experimentally shown to be necessary, let's say, for heat stress upregulation, the next step is to test if the element is sufficient. This could be done by building a tandem of these elements, making a synthetic proximal promoter and placing it upstream of a well-characterized core promoter like that of 35S to drive a reporter ( Ali and Kim, 2019 ). In the best-case scenario, if we are successful with finding an element that can confer heat-inducible expression to the reporter, we have no easy way of restricting this heat-activated expression to just the anthers, let alone at a specific stage of anther development. Even if we had another DNA element at hand that confers tissue-specific expression (in this example, in anthers), we have no straightforward way of implementing what computer scientists would view as the Boolean AND logic—to combine these DNA elements (e.g., in a single proximal promoter) in a manner that the transcription of the gene will now only be triggered specifically in anthers in response to heat, but not in any other conditions or tissues. Synthetic biology makes the implementation of that AND logic (and other types of Boolean logic gates) possible, e.g., through the use of heterodimeric transcription factors, with one monomer active in anthers (through the use of an anther-specific promoter) and another monomer expressed only in response to heat stress (through the use of a heat-regulated promoter) ( Figure 1 ). In this scenario, the full heterodimeric transcription factor would only be reconstituted in the anthers of heat-treated plants and will activate its target genes only in those flower tissues specifically under heat stress.

Figure 1 . An example of a hypothetical genetic Boolean logic AND gate. AB is a heterodimeric transcription factor. If subunit A is expressed in anthers and subunit B is inducible by heat, the full transcription factor is reconstituted only in heat-stressed anthers. The AND logic restricts the expression of the output gene of interest specifically to the tissues and conditions where/when both A and B are-co-expressed.

Thus, synthetic biology enables us to build genetic devices capable of controlling specific processes of interest despite the lack of the full mechanistic understanding of all the moving parts in those processes. In the near future, more and more plant biologists will adopt synthetic biology as a powerful way to bypass some of the technical bottlenecks in plant sciences. Who knows, someday futuristic concepts of a minimal plant genome and a minimal plant cell ( Yang et al., 2020 ) may even become a reality. How soon will we have a thorough enough understanding of plant molecular genetics and physiology, so that we can determine the minimal set of genes to make a functional plant that can stay alive in a single stable (optimal) environment? What would we need to add to the minimal system to make the plant now capable of responding to stress and thriving in less-than-optimal conditions? Although one would agree that we have a very long way before we can get there, it is not too early to start thinking about those more ambitious projects, while working on still very difficult but more achievable shorter-term goals where synthetic biology will play a central role, such as developing nitrogen-fixing cereal crops ( Bloch et al., 2020 ) or C4 rice ( Ermakova et al., 2020 ).

Other Directions and Concluding Remarks

Several other areas relevant to plant sciences will have paramount importance to our ability to propel plant biology research forward. Advanced automated high-throughput imaging and phenotyping will provide a more systematic, robust way to collect reliable morphometric data on a diversity of plant species in the lab, the greenhouse, and the field. New computational tool development and the implementation of novel experimental methods, along with the optimization and streamlining of existing tools and protocols, will remain the main driver of research progress, with single-cell omics approaches likely taking center stage for the next few years. Data science will play an even more predominant role given the vast amount of new data being generated and the need to handle and make sense of all that information. Systems-level approaches, mathematical modeling and machine learning will become a more integral part of plant biology research, enabling scientists to systematize and prioritize complex data and provide plant researchers with experimentally testable predictions.

If we want to see the breakthroughs we are making at the bench or in the field implemented in real-life products, we also need to work on shifting the public perception of biotechnologies. Critical steps toward rebuilding public trust in science include a greater understanding of the societal impacts of proposed innovations through collaboration with social scientists, the engagement of researchers with the science policy making process, and the active participation of all scientists (students, postdocs, technicians, faculty, industry professionals, etc.) in community outreach programs to make our work—and its implications—accessible to the general public. Lastly, one essential factor that would make the scientific advancements sustainable in the long run is a generous investment into the robust, trans-disciplinary training of the next generation of plant scientists. Our ability to create a welcoming environment for trainees from all backgrounds and paths of life would allow these students and postdocs to feel that their research team is their second family. Today's trainees are the ones who will be solving the world's pressing issues for years to come. Our ability to provide young scientists with the solid knowledge base and diverse skills would ensure that they are well equipped to take on the next big challenge.

Looking ahead, fundamental research on model organisms, applied work on crops, and conservation studies on rare plants will all continue to be of vital importance to modern plant biology. High-throughput inquiries and gene-specific projects done by mega-groups and small labs in state-of-the-art facilities or traditional field labs will all remain indispensable to the progress of plant sciences. In the end, addressing pressing societal issues like feeding the world's growing population and mitigating climate change ultimately rests on our ability as scientists to come together and harness the power of plants. Plant biology research is positioned to play a central role in this critical endeavor. It is an exciting and urgent time to be—or become—a plant scientist.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

The work in the Stepanova lab is supported by the National Science Foundation grants NSF 1750006, NSF 1444561, NSF 1940829.

Conflict of Interest

The author declares 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.

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Keywords: plant biology, plant physiology, synthetic biology, translational research, data reproducibility

Citation: Stepanova AN (2021) Plant Biology Research: What Is Next? Front. Plant Sci. 12:749104. doi: 10.3389/fpls.2021.749104

Received: 05 August 2021; Accepted: 06 September 2021; Published: 30 September 2021.

Edited and reviewed by: Joshua L. Heazlewood , The University of Melbourne, Australia

Copyright © 2021 Stepanova. 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: Anna N. Stepanova, atstepan@ncsu.edu

Disclaimer: 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.

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Article Contents

Decoding of life: genome analyses and functional characterization, kiss and ride: molecular interactions, femto is no limit: the content of plant tissues, seeing is believing: microscopy as an indispensable technique for studying plants, rewrite ‘whatever’: gene editing, conclusions, acknowledgements, conflict of interest, methods in plant science.

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Martin Janda, Methods in plant science, Journal of Experimental Botany , Volume 75, Issue 17, 11 September 2024, Pages 5163–5168, https://doi.org/10.1093/jxb/erae328

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The development of new techniques and technical advances in existing methods are the driving force in any area of research, including experimental botany. Improving our knowledge about the mechanisms of how the ‘world works’ is a necessary first step in creating a new technology. On the other hand, very often, it needs an advance in methods in order to make a new scientific discovery. Research in plant biology is no exception to this, and it often paves the way for the development of new methods or approaches that can have applications across wider subject areas.

The idea to put together this special issue came via the support of the Journal of Experimental Botany for the conference ‘Methods in Plant Sciences 2023’, held in Srní, Czech Republic. The meeting brought together more than 200 plant biologists and focused exclusively on techniques applicable to plant sciences. Several participants of the conference accepted the offer to write reviews about methodology approaches within their fields of expertise, and they represent the core of this issue, whilst other contributors have provided original reseach papers and also additional reviews. The result is that the papers cover a wide range of methods and approaches, from molecular dynamics through -omics and microscopy to monitoring plant–herbivore interactions. The articles can broadly be divided into two categories, namely texts focusing on a single methodological approach, its potential applications, and associated pitfalls, and those focusing on complex biological phenomena that require multiple methodological approaches in order to be properly characterized and understood.

In early studies, the variety of available methods was limited, and often only one technique was used. Thus, the findings were burdened by assumptions and potential shortcomings in the method. For example, in 1671, Grew and Malpigni used a recently developed microscope to describe pollen grains ( Manten, 1969 ): nowadays, basic research in experimental plant biology is not satisfied just with mere description but is focused on gaining an in-depth understanding of the underlying mechanism. In such studies, using one approach is insufficient, and scientists need to integrate multiple available methods—and sometimes improving them—to push our knowledge further. I am convinced that the papers in this special issue provide insightful information about recent advances in a wide spectrum of plant methods and will be useful for a broad audience.

Knowledge of hereditary information is one of the fundamental building blocks in understanding how organisms work, and plant science has benefited greatly in recent years from advances in sequencing technologies. The first plant genome to be fully sequenced was published in 2000, the same year as the first human genome, and it was that of the flowering plant Arabidopsis thaliana ( The Arabidopsis Genome Initiative, 2000 ). The Arabidopsis genome project took approximately 10 years from its beginnings and cost around 100 million USD; nowadays, it costs under 1000 USD to obtain a high-quality Arabidopsis genome, and the results are available within a week ( Li and Harkess, 2018 ). Thus, it is not surprising that more than a thousand Arabidopsis ecotypes have been sequenced ( 1001 Genomes Consortium, 2016 ), and projects aiming at sequencing tens of thousands of plants have become realistic ( https://db.cngb.org/10kp/ ).

Among other uses, such large datasets form the basis of so-called genome-wide association studies (GWAS). GWAS are capable of providing information on the functional involvement of genes within the studied biological process ( Nordborg and Weigel, 2008 ). To perform GWAS effectively, in addition to the availability of a high-throughput screening method, such as seedling growth analysis, it is also necessary to use the best possible algorithm to search for mutations within the collection. In this issue, John et al . (2024) present technical improvements regarding the approach to analysing sequence data using a permutational GWAS method.

Hereditary information is not just stored in the plant cell nucleus, with DNA also being found in mitochondria and plastids. The development of techniques known collectively as next-generation sequencing has in particular made it possible to analyse DNA sequences from these organelles. In their review, Štorchová and Krüger (2024) focus on the analysis of mitochondrial genomes in plants, describing the bottlenecks that stand in the way of obtaining hereditary information from them while highlighting that different next-generation sequencing techniques do not all provide the same results, and that using a combination of them appears to be the most efficient way to obtain high-quality and reliable mitochondrial DNA sequences. Hereditary information and its expression in mitochondria is also the subject of a review in this issue by Kwasniak-Owczarek and Janska (2024) . The authors focus on the translation of genes encoded in semi-autonomous organelles, pointing out that translation is a fundamental regulatory element in the expression of these genes. They also describe techniques that have not yet been applied to plants.

The development of the polymerase chain reaction (PCR) method, for which Kary Mullis was awarded the Nobel Prize in 1993, enabled gene transcription analysis and was a milestone for studying the involvement influence of individual genes on events in living organisms. Normally, samples prepared for transcriptomic analysis consist of the genetic information of many plant cells and cell types. For example, researchers collect RNA from the whole or at least part of the leaf. However, in recent years, attention has been turned to being able to analyse transcription in single cells ( Tang et al. , 2009 ). This technological advance has led to the expansion of analyses at the single-cell level beyond transcriptomics, and techniques are now also being developed for other ‘-omics’ ( Bennett et al ., 2023 ). In this special issue, Tenorio Berrío and Dubois (2024) discuss the potential of single-cell transcriptomics in the context of plant stress responses. Data from single-cell studies, which can discern spatial patterns of cell responses within whole organs, are likely to provide an explanation for the events where homogenizing of the ‘whole leaf’ is too low-resolution, such as transcriptomic patterns within the leaf as a response to the pathogens.

Genome analysis does not end with the knowledge of the nucleotide sequence. The mixture of DNA and proteins that form the chromosomes is folded into a higher structure—chromatin—and its 3D structure has a very significant influence on the subsequent manifestation of hereditary information. Our current knowledge is summarized by Šimková et al. (2024) , and they consider the possibilities and limitations of different approaches to analyse genome-folding into a 3D architecture. They give particular focus on describing proximity ligation Hi-C methods. Detailed knowledge of the chromatin structure of individual chromosomes leads us to the goal of studying the functional wiring of individual chromosomes. In this context, sex chromosomes are an interesting research target, and this topic is reviewed by Hobza et al. (2024) .

Gene expression ends with the creation of the desired molecules, such as enzymes. Enzymes are essential components of metabolic processes that generate further compounds. All the molecules produced are transported to the site of their function, whether as enzymes, structural components, or energy sources. Molecules do not exist in a vacuum and are constantly interacting with other molecules. In this special issue, three reviews examine methods used to study the interactions of specific types of molecules: Cuadrado and van Damme (2024) focus on advances in protein–protein interactions, whilst Neubergerová and Pleskot (2024) and Škrabálková et al. (2024) focus on interactions between proteins and lipids, with each paper looking at the subject from a different perspective. The usage and power of molecular dynamics are described by Neubergerová and Pleskot, and biochemical, ‘wet’ molecular biology and microscopic approaches are presented by Škrabálková et al .

The molecules that influence most physiological phenotypes in plants are phytohormones, also referred to in the past as plant growth regulators. Perhaps surprisingly, phytohormones are also involved in the regulation of epigenetic events in plants: by their interactions with receptors or binding proteins, they are able to cause epigenetic changes. These interactions, their mechanisms of action, and the methods used to study the links between phytohormones and epigenetic regulation are discussed by Rudolf et al . (2024) .

Plants are ingenious chemical engineers. As such, they are able to synthesize a plethora of molecules, and they serve as a source of inspiration for organic chemists. In this special issue, Ćavar Zeljković et al. (2024) present an improved protocol for determining nitrogen-related metabolites, which include amino acids together with biogenic amines and their acetylated and methylated derivates. The method that they present enables the determination of the concentration of a total of 74 metabolites, some of the which have a limit of detection in the lower units of femtomoles per injection. The authors demonstrate the functionality of the protocol in the model dicot plant Arabidopsis thaliana , as well as in a variety of crop species: Solanum lycopersicum and Nicotiana tabacum (C 3 dicots), Zea mays (C 4 monocot) and Hordeum vulgare and Triticum aesetivum (C 3 monocots).

Petrik et al. (2024) focus on the analysis of phytohormones. A detailed knowledge of phytohormone concentrations in different parts of the plant and under different growing and stress conditions is needed to understand their effects. Phytohormones represent diverse types of molecules, and Petrik et al. refer to the art of their analysis as ‘hormonomics’, thereby placing it alongside traditional ‘-omics’ such as transcriptomics, proteomics, and metabolomics. They highlight the boom in phytohormonal analyses as evidenced by the large increase in publications focusing on their determination in recent years. Phytohormones can be analysed by targeted or non-targeted approaches and, in combination with microscopic techniques, it is now becoming possible to consider the analysis of their concentrations not only at organ-level resolution, but to approximate their concentrations at the cellular and even subcellular levels as well ( Petrik et al ., 2024 ), thus approaching that of single-cell transcriptomics as noted above. It is expected that using parallel reaction monitoring for high-resolution mass spectrometry, a sensitivity at 50 amol can be achieved, which makes the future use of this approach in ‘hormonics’ look promising.

Microscopy is a technique without which it is hard to imagine plant research. Its use in plants dates back to 1665 when Robert Hooke published the book Micrographia . From this early origin, the technique expanded massively, and today it is divided into many branches, such as bright-field, fluorescence, confocal, and electron microscopy. Each has its distinct limits in resolution and its own (dis)advantages. This special issue includes two original research articles that use microscopy as their main method. Daněk et al . (2024) improve the analysis and quantification of autophagosomes in a 3D perspective by critically evaluating the limitations of previously used techniques and comparing them with the modified approach that they present. Narasimhan et al. (2024) present a tool box for analysing the binding of peptides to their receptors, for which they have developed genetic tools to use at good spatiotemporal resolution in vivo . In addition, a review by Müller-Schüssele (2024) describes the creation of biosensors for the determination of redox dynamics that are analysed using microscopy..

A microscope is not always necessary to prove that ‘seeing is believing’. Sotta and Fujiwara (2024) describe the development of a new, inexpensive, and reliable high-throughput method for monitoring herbivore insect feeding in Arabidopsis, which ultilizes a scanner and custom-built macro software for the free ImageJ and R packages.

Good quality visualization contributes to a better understanding of the processes taking place in plants, and Jo and Kajala (2024) introduce a new open-source ggPlantmap programme for visualization of experimental data, in a similar fashion to that provided by ePlant ( Waese et al. , 2017 ).

Since the description of the revolutionary gene-editing technology using CRISPR/Cas9 ( Jinek et al ., 2012 ), researchers in nearly all fields of biology have harnessed its possibility of creating desired mutant organisms. In plants, the technology is being used and improved extensively. The database created by the EU-SAGE initiative, which aims to open the European Union to the use of new genomic techniques in agriculture, contains more than 800 studies that have already utilized CRISPR to create genome-edited crop plants ( https://www.eu-sage.eu/genome-search ).

In this special issue, Přibylová and Fischer (2024) have written a detailed ‘cookbook’ for planning and performing gene editing using CRISPR. The authors highlight details that are not easy (or are indeed impossible) to obtain from original research articles, such as the effect of the chromatin state on CRISPR/Cas9 activity. In another paper, Vats et al . (2024) discuss prime editing in plants, noting its advantages and, at the same time, the challenges that need to be overcome to use this technique effectively, such as the fact that prime editing works with very low efficiency in dicots.

CRISPR/Cas9 has opened up unexpected possibilities for transcribing genomes and made it possible to think about editing in virtually all plants. As a result, the current bottleneck in research is no longer editing itself but determining the most efficient and reliable transformation process for the plant chosen for gene editing.

From the very beginning, plant research has benefited from the most advanced methodological approaches that have been available and, in turn, it has often been part of their evolution, such as the birth of genetics ( Mendel, 1865 ) or gene silencing ( Baulcombe, 2002 ). It is rather like the ‘chicken-and-egg’ question: which came first, knowledge or method? One cannot be without the other. In the past, one available method (e.g. microscopy) and excellent observational talent were often enough to make significant scientific progress: such a situation is perhaps not imaginable today even in basic research. Now, significant advances in knowledge require a detailed description of the mechanisms of how the plant works, and this in turn requires a combination of the multiple, often state-of-the-art, methods that are available, many of which have only been developed just recently.

I am confident that the collection of articles assembled in this special issue will help a broad range of our colleagues obtain a good overview and better understanding of the techniques now available in plant biology. As an example, the fictional case study in Box 1 summarizes the possibilities of the methods and approaches presented in this issue to deal with a complex, long-term scientific goal.

This virtual case study examines the effects of herbivore-associated molecular patterns on plants, and serves to highlight the application of methods considered in this special issue. All the ‘results’ referred to and the associated discussion are fictitious.

(A) We have identified a novel peptide from larvae that can be used to treat plants and trigger their resistance. We monitored the damage caused by larvae to the plant using the methodology presented by Sotta and Fujiwara (2024) , [1] , which provides a very cheap and high-throughput approach. In addition to protection against larvae, we also observed a triggered immune response after the peptide treatment. This prompted us to ask what the molecular mechanism was, and we assumed that there must be a plant receptor recognizing the peptide. (B) Due to the availability of a collection of sequenced ecotypes of our plant, we were able to perform a genome-wide association study (GWAS) analysis and obtained a candidate gene for the receptor ( John et al ., 2024 ) [2] . The structure of the receptor revealed its localization on the plasma membrane. (C) We analysed the binding of the peptide to its receptor using the techniques described by Cuadrado and van Damme (2024) and Narasimhan et al . (2024) , [3,4] . We next characterized the receptor complex and the interaction between the two proteins. So far, we have not been able to perform prime editing on our plant to confirm the direct site of the peptide binding to the receptor ( Vats et al ., 2024 ) [5] . Using molecular dynamics, we have predicted the local composition of the plasma membrane around the receptor in the absence and presence of the peptide ( Neubergerová and Pleskot, 2024 ) [6] . A combination of molecular biology, biochemistry, and microscopy techniques confirmed the results obtained using molecular dynamics ( Škrabálková et al ., 2024 ) [7] . Using the approach described by Daňek et al. (2024) , [8] , we were able to demonstrate that the binding of the peptide to the receptor does not lead to autophagy. We performed a detailed single-cell transcriptomic analysis, as described by Tenorio Berrío and Dubois (2024) , [9] , and the results showed a clear similarity to typical biotic stress transcriptomic responses. Utilizing complex methods described by Rudolf et al . (2024) , [10] , we did not find any influence of the peptide treatment on the plant epigenetic landscape. One of the typical responses to biotic stress is changes in redox, which we analysed using the biosensors described by Müller-Schüssele (2024) , [11] . Another typical stress response is a change in the concentration of phytohormones, and we used the state-of-the-art methods described by Petrik et al . (2024) , [12] to examine these at a detailed level. Unsurprisingly, we found significant changes in the jasmonic and salicylic acid levels in distinct parts of the leaf. An intriguing observation from our transcriptomic analysis was that there might be changes in the abundance of nitrogen-related compounds. Using the techniques described by Ćavar Zeljković et al . (2024) , [13] , we were able to analyse these changes and identify altered concentrations in particular nitrogen-related compounds. We visualized the results obtained in (C) using the ggPlantap package ( Jo and Kajala, 2024 ) [14] . We have found that plants from other families, for example, sunflowers, do not respond well to the peptide. Focusing on sunflower, we determined that the homolog receptor protein contains a number of structural differences, effectively abolishing its interaction with the aphid peptide. (D) Therefore, we decided to edit the receptor gene in sunflower to make its sequence identical to that of our original model plant. For this, we utilized the CRISPR/Cas9 approach, as described in detail by Přibylová and Fischer (2024) [15] . As predicted, our genetic modification led to decreased damage caused by the larvae in sunflowers. Created with BioRender.com.

Many thanks to all the people who contributed to the success of the conference ‘Methods in Plant Sciences 2023’ in Srní, Czech Republic, and to all the authors who have contributed to this special issue, on whose work this editorial is based. I would like to thank Dr Štěpán Jeřábek of Columbia University (NY, USA) for help with editing the final draft of this text. Last but not least, I would like to thank the editorial office of the Journal of Experimental Botany for all their help and patience with the special issue.

The author declares that he has no conflict of interest in relation to this work.

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New research on plant stem cells shines light on how plants grow stronger

by Anna Zarra Aldrich, University of Connecticut

Stem cell research is a hot topic. With applications for a host of human medical advancements, researchers have been working with animal and human stem cells for years.

But animals aren't the only ones with stem cells.

Huanzhong Wang, professor of plant molecular biology in the College of Agriculture, Health and Natural Resources (CAHNR), wants people to know that plants have stem cells too. Just like in the medical world, plant stem cells could support human growth and development when used to improve the food supply.

"It's not just humans and animals," Wang says. "Plants have stem cells too, and we should be paying attention to them."

In their roots, shoots, and vasculature, stem cells control cell division and differentiation for plants. Plant stem cells play a vital role in growth and development.

"Plants can grow for many, many years because different types of stem cells basically ensure they can grow up in the air and deep into the ground," Wang says. "To grow a thicker stem or trunk, they need another type of stem cell."

Plant stem cells have largely been overlooked because they don't have applications for human biomedical research. But that doesn't make them any less fascinating. And Wang has demonstrated that better understanding how these cells work can support a more resilient food supply.

Wang's lab has been working with plant stem cells for years trying to understand how they control their stem cells, specifically the stem cells that give rise to vascular bundles—the structures that carry water and other nutrients throughout the plant.

Recently the group published a paper in New Phytologist that sheds light on this question. Wang's lab discovered a transcription factor gene called HVA that controls cell division in vascular stem cells.

When this gene is overexpressed, the researchers observed an increase in the number of vascular bundles and overall stem cell activity.

The researchers compared plants with no overexpression of HVA gene, those with one copy of overexpressed HVA gene and one regular gene, and finally plants with two copies of overexpressed HVA genes.

In the group with no overexpression, the plants had five to eight vascular bundles. In the plants with one copy of the overexpressed HVA gene, they had more than 20 bundles, and with two copies of overexpressed HVA genes they had more than 50.

Aside from advancing science's understanding of how plants work, Wang's findings have important implications for agriculture.

Plants with more vascular bundles are stronger and more resistant to wind. This knowledge could be used to intentionally generate sturdier cultivars with the overexpression mutation.

This is especially relevant for tall, slender crops like corn, the biggest crop in the U.S.

"When plants grow taller, there is a risk that they could topple over," Wang says. "Having more vascular bundles ensures the plant can stand still and resist those conditions."

Even though Wang's lab conducted the study using a model organism in the mustard family, the HVA gene is found in other plants as well, making this research broadly applicable.

HVA is one of hundreds of transcription factors in a large family in the plant's genome. Wang is interested in discovering what some of the other genes in this family do.

"We are interested in studying other closely related genes to find out their function," Wang says. "It will be interesting to study further how this gene family affects vascular development.

Journal information: New Phytologist

Provided by University of Connecticut

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Plant-based products originating from serbia that affect p-glycoprotein activity.

1. Drug Resistance in Cancer Therapy

1.1. p-gp role and regulation in cellular physiology, 1.2. p-gp role in cancer therapy and efforts to overcome multidrug resistance, 2. modulation of p-gp activity by natural product drugs, 2.1. sesquiterpenoids, 2.1.1. genus artemisia, 2.1.2. genus curcuma, 2.1.3. genus ferula, 2.1.4. genus inula, 2.1.5. genus petasites, 2.1.6. genus celastrus, 2.2. diterpenoids, 2.2.1. genus salvia, 2.2.2. genus euphorbia, e. nicaeensis all., e. dendroides l., e. esula l., e. helioscopia l., e. sororia a. schrenk, e. glomerulans prokh., 2.3. chalcones, 2.3.1. genus piper, 2.3.2. genus helichrysum, 2.3.3. genus glycyrrhiza, 2.3.4. genus cullen, 2.3.5. genus artemisia, 2.3.6. genus humulus, 2.4. riccardins, 2.5. diarylheptanoids, 2.5.1. genus alnus, 2.5.2. genus curcuma.

Classes of Natural Products	P-gp Inhibitors and MDR Modulators	Derivatives	Additional Biological Activities *	Origin
sesquiterpenoids	]	] ]	] ] /M cell cycle arrest and apoptosis [ ]	Genus Artemisia
	]	]	]	Genus Artemisia
	] ] , ]		] ] ] ] ] ] ]	Genus Curcuma
	] ] ] ]			Genus Ferula
	, ] ] ]		] ]	Genus Inula
	] ]		] ] ] ]	Genus Petasites
	]			Genus Celastrus
diterpenoids	, ]	] ]pyrimidines [ ]	, ] ] , ]	Genus Salvia
diterpenoids	] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ]	] ]		Genus Euphorbia
chalcones	] ]		] ]	Genus Piper
	] ]		] ] ]	Genus Helichrysum
	]		] ]	Genus Glycyrrhiza
	]		] ] ] ] ] ]	Genus Cullen
	]		] ]	Genus Artemisia
	]		] ]	Genus Humulus
riccardins	] ]		] ] ] ] ]	Genera Lunularia, Monoclea, Dumortiera, Plagiochila, and Primula
diarylheptanoids	] -methylhirsutanonol [ ]		]	Genus Alnus
diarylheptanoids	] ]		, ] , ] , ] , ] , ]	Genus Curcuma

3. Novel Perspectives with Naturally Derived P-Glycoprotein Inhibitors

Author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Dinić, J.; Podolski-Renić, A.; Novaković, M.; Li, L.; Opsenica, I.; Pešić, M. Plant-Based Products Originating from Serbia That Affect P-glycoprotein Activity. Molecules 2024 , 29 , 4308. https://doi.org/10.3390/molecules29184308

Dinić J, Podolski-Renić A, Novaković M, Li L, Opsenica I, Pešić M. Plant-Based Products Originating from Serbia That Affect P-glycoprotein Activity. Molecules . 2024; 29(18):4308. https://doi.org/10.3390/molecules29184308

Dinić, Jelena, Ana Podolski-Renić, Miroslav Novaković, Liang Li, Igor Opsenica, and Milica Pešić. 2024. "Plant-Based Products Originating from Serbia That Affect P-glycoprotein Activity" Molecules 29, no. 18: 4308. https://doi.org/10.3390/molecules29184308

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Groundbreaking Study: Plant-Based Proteins Could Be the Key to Longer Life

Recent research reveals that plants have all essential amino acids , debunking a longstanding misconception.

A New England Journal of Medicine letter to the editor by Neal D. Barnard, MD, published on August 1, 2024, highlights the significant health benefits of plant-based proteins over animal-based ones. Contrary to the widespread misconception, Dr. Barnard’s findings reveal that plants provide all essential amino acids—the fundamental components of proteins. Of these, nine are essential, meaning the human body cannot synthesize them on its own; however, they are all present in plant sources.

“In addition, plant-based proteins are associated with reduced mortality compared with animal proteins,” says Dr. Barnard, president of the Physicians Committee for Responsible Medicine, a nonprofit public health advocacy organization, and adjunct professor of medicine at the George Washington University School of Medicine and Health Sciences in Washington, D.C. “A major Harvard study showed that when plant-based proteins are consumed instead of protein from beef, poultry, fish, dairy products, or eggs, mortality is reduced.”

Nutritional Considerations in Plant-Based Eating

People drawing their nutrition from plant-based diets enjoy a reduced risk of diabetes, obesity, heart disease, and cancer. Even so, people on any diet should pay attention to their need for vitamin B12 and other nutrients.

The letter was published in response to a New England Journal of Medicine article introducing a new series on nutrition. “Many people are now shifting to plant-based diets, and their nutrition improves in the process,” Dr. Barnard says.

Reference: “Guidance on Energy and Macronutrients across the Life Span” by Steven B. Heymsfield and Sue A. Shapses, 10 April 2024, New England Journal of Medicine . DOI: 10.1056/NEJMra2214275

Meat vs. plant: new research reveals a clear winner for muscle growth, scientists shed new light on the protein diet paradox, animal vs. plant protein: new research suggests that these protein sources are not nutritionally equivalent, a new way to lose weight could change your metabolism, researchers find that eating just a little more protein can enhance your health, humans absorb less protein from plant-based meat than normal meat, higher protein intake does not increase lean body mass in older men, a low-glycemic diet is more effective at burning calories, researchers find possible link between diet soda and vascular risks.

Not this… AGAIN! Plant based proteins doesn’t mean that processed, vegan crap…. think legumes and the like. Skip the veggie burger for dal soup.

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Boar’s Head closing Virginia plant linked to deadly listeria outbreak

An aerial view of the Boar’s Head processing plant that was tied to a deadly food poisoning outbreak Thursday Aug. 29, 2024, in Jarratt, Va. (AP Photo/Steve Helber)

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Boar’s Head said Friday it’s closing the Virginia plant tied to a deadly listeria outbreak .

The Sarasota, Florida-based company said it will also permanently discontinue production of liverwurst, the product that was linked to the deaths of at least nine people and hospitalizations of about 50 others in 18 states.

Boar’s Head expressed regret and deep apologies for the outbreak in a statement on its website.

Boar’s Head said an internal investigation at its Jarratt, Virginia, plant found that the contamination was the result of a specific production process. The process only existed at the Jarratt plant and was only used for liverwurst, the company said.

The Jarratt plant hasn’t been operational since late July, when Boar’s Head recalled more than 7 million pounds of deli meats and other products after tests confirmed listeria bacteria in its products was making people sick.

Listeria infections are caused by a hardy type of bacteria that can survive and even thrive during refrigeration. An estimated 1,600 people get listeria food poisoning each year and about 260 die, according to the U.S. Centers for Disease Control. Infections can be hard to pinpoint because symptoms may occur up to 10 weeks after eating contaminated food.

The Jarratt plant had a troubled history . Government inspectors found 69 instances of “noncompliance” at the facility over the last year, including instances of mold, insects, liquid dripping from ceilings and meat and fat residue on walls, floors and equipment.

Boar’s Head said “hundreds” of employees will be impacted by the closure.

“We do not take lightly our responsibility as one of the area’s largest employers,” the company said. “But, under these circumstances, we feel that a plant closure is the most prudent course.”

The company said it is appointing a new chief food safety officer who will report to its president. It is also establishing a safety council comprised of independent experts, including Mindy Brashears, a former food safety chief at the U.S. Department of Agriculture, and Frank Yiannas, a former deputy commissioner for food policy at the U.S. Food and Drug Administration.

“This is a dark moment in our company’s history, but we intend to use this as an opportunity to enhance food safety programs not just for our company, but for the entire industry,” the company said.

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