To the proteome and beyond: advances in single-cell omics profiling for plant systems

Single-cell proteomics differentiates Arabidopsis root cell types

Single-cell proteomics (SCP) is an emerging approach to resolve cellular heterogeneity within complex tissues of multi-cellular organisms. Here, we demonstrate the feasibility of SCP on plant samples using the model plant Arabidopsis thaliana. Specifically, we focused on examining isolated single cells from the cortex and endodermis, which are two adjacent root cell types derived from a common stem cell lineage. From 756 root cells, we identified 3763 proteins and 1118 proteins/cell. Ultimately, we focus on 3217 proteins quantified following stringent filtering. Of these, we identified 596 proteins whose expression is enriched in either the cortex or endodermis and are able to differentiate these closely related plant cell types. Collectivity, this study demonstrates that SCP can resolve neighboring cell types with distinct functions, thereby facilitating the identification of biomarkers and candidate proteins to enable functional genomics.

Identification of potential auxin response candidate genes for soybean rapid canopy coverage through comparative evolution and expression analysis

Introduction

Throughout domestication, crop plants have gone through strong genetic bottlenecks, dramatically reducing the genetic diversity in today's available germplasm. This has also reduced the diversity in traits necessary for breeders to develop improved varieties. Many strategies have been developed to improve both genetic and trait diversity in crops, from backcrossing with wild relatives, to chemical/radiation mutagenesis, to genetic engineering. However, even with recent advances in genetic engineering we still face the rate limiting step of identifying which genes and mutations we should target to generate diversity in specific traits.

Methods

Here, we apply a comparative evolutionary approach, pairing phylogenetic and expression analyses to identify potential candidate genes for diversifying soybean (Glycine max) canopy cover development via the nuclear auxin signaling gene families, while minimizing pleiotropic effects in other tissues. In soybean, rapid canopy cover development is correlated with yield and also suppresses weeds in organic cultivation.

Results and discussion

We identified genes most specifically expressed during early canopy development from the TIR1/AFB auxin receptor, Aux/IAA auxin co-receptor, and ARF auxin response factor gene families in soybean, using principal component analysis. We defined Arabidopsis thaliana and model legume species orthologs for each soybean gene in these families allowing us to speculate potential soybean phenotypes based on well-characterized mutants in these model species. In future work, we aim to connect genetic and functional diversity in these candidate genes with phenotypic diversity in planta allowing for improvements in soybean rapid canopy cover, yield, and weed suppression. Further development of this and similar algorithms for defining and quantifying tissue- and phenotype-specificity in gene expression may allow expansion of diversity in valuable phenotypes in important crops.

Chloroplast ATP synthase: From structure to engineering

F-type ATP synthases are extensively researched protein complexes because of their widespread and central role in energy metabolism. Progress in structural biology, proteomics, and molecular biology has also greatly advanced our understanding of the catalytic mechanism, post-translational modifications, and biogenesis of chloroplast ATP synthases. Given their critical role in light-driven ATP generation, tailoring the activity of chloroplast ATP synthases and modeling approaches can be applied to modulate photosynthesis. In the future, advances in genetic manipulation and protein design tools will significantly expand the scope for testing new strategies in engineering light-driven nanomotors.

Large language models in plant biology

Large language models (LLMs), such as ChatGPT, have taken the world by storm. However, LLMs are not limited to human language and can be used to analyze sequential data, such as DNA, protein, and gene expression. The resulting foundation models can be repurposed to identify the complex patterns within the data, resulting in powerful, multipurpose prediction tools able to predict the state of cellular systems. This review outlines the different types of LLMs and showcases their recent uses in biology. Since LLMs have not yet been embraced by the plant community, we also cover how these models can be deployed for the plant kingdom.

ggPlantmap: an open-source R package for the creation of informative and quantitative ggplot maps derived from plant images

As plant research generates an ever-growing volume of spatial quantitative data, the need for decentralized and user-friendly visualization tools to explore large and complex datasets becomes crucial. Existing resources, such as the Plant eFP (electronic Fluorescent Pictograph) viewer, have played a pivotal role on the communication of gene expression data across many plant species. However, although widely used by the plant research community, the Plant eFP viewer lacks open and user-friendly tools for the creation of customized expression maps independently. Plant biologists with less coding experience can often encounter challenges when attempting to explore ways to communicate their own spatial quantitative data. We present 'ggPlantmap' an open-source R package designed to address this challenge by providing an easy and user-friendly method for the creation of ggplot representative maps from plant images. ggPlantmap is built in R, one of the most used languages in biology, to empower plant scientists to create and customize eFP-like viewers tailored to their experimental data. Here, we provide an overview of the package and tutorials that are accessible even to users with minimal R programming experience. We hope that ggPlantmap can assist the plant science community, fostering innovation, and improving our understanding of plant development and function.

Integrated Review of Transcriptomic and Proteomic Studies to Understand Molecular Mechanisms of Rice's Response to Environmental Stresses

Rice (Oryza sativa L.) is grown nearly worldwide and is a staple food for more than half of the world's population. With the rise in extreme weather and climate events, there is an urgent need to decode the complex mechanisms of rice's response to environmental stress and to breed high-yield, high-quality and stress-resistant varieties. Over the past few decades, significant advancements in molecular biology have led to the widespread use of several omics methodologies to study all aspects of plant growth, development and environmental adaptation. Transcriptomics and proteomics have become the most popular techniques used to investigate plants' stress-responsive mechanisms despite the complexity of the underlying molecular landscapes. This review offers a comprehensive and current summary of how transcriptomics and proteomics together reveal the molecular details of rice's response to environmental stresses. It also provides a catalog of the current applications of omics in comprehending this imperative crop in relation to stress tolerance improvement and breeding. The evaluation of recent advances in CRISPR/Cas-based genome editing and the application of synthetic biology technologies highlights the possibility of expediting the development of rice cultivars that are resistant to stress and suited to various agroecological environments.

Streamlined spatial and environmental expression signatures characterize the minimalist duckweed Wolffia australiana

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light-dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquatic Wolffia australiana, to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and found Wolffia cells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis. Although these tissues share transcriptomic similarity with model plants, they display distinct adaptations that Wolffia has made for the aquatic environment. Within this broad classification, discrete subspecializations are evident, with select cells showing unique transcriptomic signatures associated with developmental maturation and specialized physiologies. Assessing this simplified biological system temporally at two key time-of-day (TOD) transitions, we identify additional TOD-responsive genes previously overlooked in whole-plant transcriptomic approaches and demonstrate that the core circadian clock machinery and its downstream responses can vary in cell-specific manners, even in this simplified system. Distinctions between cell types and their responses to submergence and/or TOD are driven by expression changes of unexpectedly few genes, characterizing Wolffia as a highly streamlined organism with the majority of genes dedicated to fundamental cellular processes. Wolffia provides a unique opportunity to apply reductionist biology to elucidate signaling functions at the organismal level, for which this work provides a powerful resource.

Breaking barriers: improving time and space resolution of arbuscular mycorrhizal symbiosis with single-cell sequencing approaches

The cell and molecular bases of arbuscular mycorrhizal (AM) symbiosis, a crucial plant-fungal interaction for nutrient acquisition, have been extensively investigated by coupling traditional RNA sequencing techniques of roots sampled in bulk, with methods to capture subsets of cells such as laser microdissection. These approaches have revealed central regulators of this complex relationship, yet the requisite level of detail to effectively untangle the intricacies of temporal and spatial development remains elusive.The recent adoption of single-cell RNA sequencing (scRNA-seq) techniques in plant research is revolutionizing our ability to dissect the intricate transcriptional profiles of plant-microbe interactions, offering unparalleled insights into the diversity and dynamics of individual cells during symbiosis. The isolation of plant cells is particularly challenging due to the presence of cell walls, leading plant researchers to widely adopt nuclei isolation methods. Despite the increased resolution that single-cell analyses offer, it also comes at the cost of spatial perspective, hence, it is necessary the integration of these approaches with spatial transcriptomics to obtain a comprehensive overview.To date, few single-cell studies on plant-microbe interactions have been published, most of which provide high-resolution cell atlases that will become crucial for fully deciphering symbiotic interactions and addressing future questions. In AM symbiosis research, key processes such as the mutual recognition of partners during arbuscule development within cortical cells, or arbuscule senescence and degeneration, remain poorly understood, and these advancements are expected to shed light on these processes and contribute to a deeper understanding of this plant-fungal interaction.

Pleiotropy, a feature or a bug? Toward co-ordinating plant growth, development, and environmental responses through engineering plant hormone signaling

The advent of gene editing technologies such as CRISPR has simplified co-ordinating trait development. However, identifying candidate genes remains a challenge due to complex gene networks and pathways. These networks exhibit pleiotropy, complicating the determination of specific gene and pathway functions. In this review, we explore how systems biology and single-cell sequencing technologies can aid in identifying candidate genes for co-ordinating specifics of plant growth and development within specific temporal and tissue contexts. Exploring sequence-function space of these candidate genes and pathway modules with synthetic biology allows us to test hypotheses and define genotype-phenotype relationships through reductionist approaches. Collectively, these techniques hold the potential to advance breeding and genetic engineering strategies while also addressing genetic diversity issues critical for adaptation and trait development.

Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications

The recent technological and computational advances in mass spectrometry-based single-cell proteomics have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell remains challenging. To address some of those limitations, we present a dedicated sample preparation chip, the proteoCHIP EVO 96 that directly interfaces with the Evosep One. This, in combination with the Bruker timsTOF demonstrates double the identifications without manual sample handling and the newest generation timsTOF Ultra identifies up to 4000 with an average of 3500 protein groups per single HEK-293T without a carrier or match-between runs. Our workflow spans 4 orders of magnitude, identifies over 50 E3 ubiquitin-protein ligases, and profiles key regulatory proteins upon small molecule stimulation. This study demonstrates that the proteoCHIP EVO 96-based sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.

Opportunities and Challenges in Advancing Plant Research with Single-cell Omics

Plants possess diverse cell types and intricate regulatory mechanisms to adapt to the ever-changing environment of nature. Various strategies have been employed to study cell types and their developmental progressions, including single-cell sequencing methods which provide high-dimensional catalogs to address biological concerns. In recent years, single-cell sequencing technologies in transcriptomics, epigenomics, proteomics, metabolomics, and spatial transcriptomics have been increasingly used in plant science to reveal intricate biological relationships at the single-cell level. However, the application of single-cell technologies to plants is more limited due to the challenges posed by cell structure. This review outlines the advancements in single-cell omics technologies, their implications in plant systems, future research applications, and the challenges of single-cell omics in plant systems.

Plant genome information facilitates plant functional genomics

MAIN CONCLUSION

In this review, we give an overview of plant sequencing efforts and how this impacts plant functional genomics research. Plant genome sequence information greatly facilitates the studies of plant biology, functional genomics, evolution of genomes and genes, domestication processes, phylogenetic relationships, among many others. More than two decades of sequencing efforts have boosted the number of available sequenced plant genomes. The first plant genome, of Arabidopsis, was published in the year 2000 and currently, 4604 plant genomes from 1482 plant species have been published. Various large sequence initiatives are running, which are planning to produce tens of thousands of sequenced plant genomes in the near future. In this review, we give an overview on the status of sequenced plant genomes and on the use of genome information in different research areas.

Protein post-translational modifications in auxin signaling

Protein post-translational modifications (PTMs), such as ubiquitination, phosphorylation, and small ubiquitin-like modifier (SUMO)ylation, are crucial for regulating protein stability, activity, subcellular localization, and binding with cofactors. Such modifications remarkably increase the variety and complexity of proteomes, which are essential for regulating numerous cellular and physiological processes. The regulation of auxin signaling is finely tuned in time and space to guide various plant growth and development. Accumulating evidence indicates that PTMs play critical roles in auxin signaling regulations. Thus, a thorough and systematic review of the functions of PTMs in auxin signal transduction will improve our profound comprehension of the regulation mechanism of auxin signaling and auxin-mediated various processes. This review discusses the progress of protein ubiquitination, phosphorylation, histone acetylation and methylation, SUMOylation, and S-nitrosylation in the regulation of auxin signaling.

CLAVATA signaling in plant-environment interactions

Plants must rapidly and dynamically adapt to changes in their environment. Upon sensing environmental signals, plants convert them into cellular signals, which elicit physiological or developmental changes that allow them to respond to various abiotic and biotic cues. Because plants can be simultaneously exposed to multiple environmental cues, signal integration between plant cells, tissues, and organs is necessary to induce specific responses. Recently, CLAVATA3/EMBRYO SURROUNDING REGION-related (CLE) peptides and their cognate CLAVATA-type receptors received increased attention for their roles in plant-environment interactions. CLE peptides are mobile signaling molecules, many of which are induced by a variety of biotic and abiotic stimuli. Secreted CLE peptides are perceived by receptor complexes on the surface of their target cells, which often include the leucine-rich repeat receptor-like kinase CLAVATA1. Receptor activation then results in cell-type and/or environment-specific responses. This review summarizes our current understanding of the diverse roles of environment-regulated CLE peptides in modulating plant responses to environmental cues. We highlight how CLE signals regulate plant physiology by fine-tuning plant-microbe interactions, nutrient homeostasis, and carbon allocation. Finally, we describe the role of CLAVATA receptors in the perception of environment-induced CLE signals and discuss how diverse CLE-CLAVATA signaling modules may integrate environmental signals with plant physiology and development.

Growth regulation by apyrases: Insights from altering their expression level in different organisms

Apyrase (APY) enzymes are nucleoside triphosphate (NTP) diphosphohydrolases that can remove the terminal phosphate from NTPs and nucleoside diphosphates but not from nucleoside monophosphates. They have conserved structures and functions in yeast, plants, and animals. Among the most studied APYs in plants are those in Arabidopsis (Arabidopsis thaliana; AtAPYs) and pea (Pisum sativum; PsAPYs), both of which have been shown to play major roles in regulating plant growth and development. Valuable insights on their functional roles have been gained by transgenically altering their transcript abundance, either by constitutively expressing or suppressing APY genes. This review focuses on recent studies that have provided insights on the mechanisms by which APY activity promotes growth in different organisms. Most of these studies have used transgenic lines that constitutively expressed APY in multiple different plants and in yeast. As APY enzymatic activity can also be changed post-translationally by chemical blockage, this review also briefly covers studies that used inhibitors to suppress APY activity in plants and fungi. It concludes by summarizing some of the main unanswered questions about how APYs regulate plant growth and proposes approaches to answering them.

Special Issue "State-of-the-Art Molecular Plant Sciences in Japan"

Food shortages are one of the most serious problems caused by global warming and population growth in this century [...].

Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications

Mass spectrometry (MS)-based single-cell proteomics (SCP) has gained massive attention as a viable complement to other single cell approaches. The rapid technological and computational advances in the field have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell at reasonable proteome depth to characterize biological phenomena remains a challenge. To address some of those limitations we present a combination of fully automated single cell sample preparation utilizing a dedicated chip within the picolitre dispensing robot, the cellenONE. The proteoCHIP EVO 96 can be directly interfaced with the Evosep One chromatographic system for in-line desalting and highly reproducible separation with a throughput of 80 samples per day. This, in combination with the Bruker timsTOF MS instruments, demonstrates double the identifications without manual sample handling. Moreover, relative to standard high-performance liquid chromatography, the Evosep One separation provides further 2-fold improvement in protein identifications. The implementation of the newest generation timsTOF Ultra with our proteoCHIP EVO 96-based sample preparation workflow reproducibly identifies up to 4,000 proteins per single HEK-293T without a carrier or match-between runs. Our current SCP depth spans over 4 orders of magnitude and identifies over 50 biologically relevant ubiquitin ligases. We complement our highly reproducible single-cell proteomics workflow to profile hundreds of lipopolysaccharide (LPS)-perturbed THP-1 cells and identified key regulatory proteins involved in interleukin and interferon signaling. This study demonstrates that the proteoCHIP EVO 96-based SCP sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.

Proteogenomics-based functional genome research: approaches, applications, and perspectives in plants

Proteogenomics (PG) integrates the proteome with the genome and transcriptome to refine gene models and annotation. Coupled with single-cell (SC) assays, PG effectively distinguishes heterogeneity among cell groups. Affiliating spatial information to PG reveals the high-resolution circuitry within SC atlases. Additionally, PG can investigate dynamic changes in protein-coding genes in plants across growth and development as well as stress and external stimulation, significantly contributing to the functional genome. Here we summarize existing PG research in plants and introduce the technical features of various methods. Combining PG with other omics, such as metabolomics and peptidomics, can offer even deeper insights into gene functions. We argue that the application of PG will represent an important font of foundational knowledge for plants.

UV-B responses in the spotlight: Dynamic photoreceptor interplay and cell-type specificity

Plants are constantly exposed to a multitude of external signals, including light. The information contained within the full spectrum of light is perceived by a battery of photoreceptors, each with specific and shared signalling outputs. Recently, it has become clear that UV-B radiation is a vital component of the electromagnetic spectrum, guiding growth and being crucial for plant fitness. However, given the large overlap between UV-B specific signalling pathways and other photoreceptors, understanding how plants can distinguish UV-B specific signals from other light components deserves more scrutiny. With recent evidence, we propose that UV-B signalling and other light signalling pathways occur within distinct tissues and cell-types and that the contribution of each pathway depends on the type of response and the developmental stage of the plant. Elucidating the precise site(s) of action of each molecular player within these signalling pathways is key to fully understand how plants are able to orchestrate coordinated responses to light within the whole plant body. Focusing our efforts on the molecular study of light signal interactions to understand plant growth in natural environments in a cell-type specific manner will be a next step in the field of photobiology.

Defining Mechanisms of C3 to CAM Photosynthesis Transition toward Enhancing Crop Stress Resilience

Global climate change and population growth are persistently posing threats to natural resources (e.g., freshwater) and agricultural production. Crassulacean acid metabolism (CAM) evolved from C3 photosynthesis as an adaptive form of photosynthesis in hot and arid regions. It features the nocturnal opening of stomata for CO2 assimilation, diurnal closure of stomata for water conservation, and high water-use efficiency. To cope with global climate challenges, the CAM mechanism has attracted renewed attention. Facultative CAM is a specialized form of CAM that normally employs C3 or C4 photosynthesis but can shift to CAM under stress conditions. It not only serves as a model for studying the molecular mechanisms underlying the CAM evolution, but also provides a plausible solution for creating stress-resilient crops with facultative CAM traits. This review mainly discusses the recent research effort in defining the C3 to CAM transition of facultative CAM plants, and highlights challenges and future directions in this important research area with great application potential.

Understanding plant pathogen interactions using spatial and single-cell technologies

Plants are in contact with diverse pathogens and microorganisms. Intense investigation over the last 30 years has resulted in the identification of multiple immune receptors in model and crop species as well as signaling overlap in surface-localized and intracellular immune receptors. However, scientists still have a limited understanding of how plants respond to diverse pathogens with spatial and cellular resolution. Recent advancements in single-cell, single-nucleus and spatial technologies can now be applied to plant-pathogen interactions. Here, we outline the current state of these technologies and highlight outstanding biological questions that can be addressed in the future.

A method for analyzing programmed cell death in xylem development by flow cytometry

Programmed cell death (PCD) is a genetically regulated developmental process leading to the death of specific types of plant cells, which plays important roles in plant development and growth such as wood formation. However, an efficient method needs to be established to study PCD in woody plants. Flow cytometry is widely utilized to evaluate apoptosis in mammalian cells, while it is rarely used to detect PCD in plants, especially in woody plants. Here, we reported that the xylem cell protoplasts from poplar stem were stained with a combination of fluorescein annexin V-FITC and propidium iodide (PI) and then sorted by flow cytometry. As expected, living cells (annexin V-FITC negative/PI negative), early PCD cells (annexin V-FITC positive/PI negative), and late PCD cells (annexin V-FITC positive/PI positive) could be finely distinguished through this method and then subjected for quantitative analysis. The expression of cell-type- and developmental stages-specific marker genes was consistent with the cell morphological observation. Therefore, the newly developed fluorescence-activated cell sorting (FACS) method can be used to study PCD in woody plants, which will be beneficial for studying the molecular mechanisms of wood formation.

Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics

Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth of protein quantification, especially for proteins and modifications of biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus increasing proteome depth. These strategies increased the sensitivity, data completeness and proteome coverage over twofold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport, similarly across both treatment conditions. This covariation is coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at http://scp.slavovlab.net/pSCoPE .

Charting plant gene functions in the multi-omics and single-cell era

Despite the increased access to high-quality plant genome sequences, the set of genes with a known function remains far from complete. With the advent of novel bulk and single-cell omics profiling methods, we are entering a new era where advanced and highly integrative functional annotation strategies are being developed to elucidate the functions of all plant genes. Here, we review different multi-omics approaches to improve functional and regulatory gene characterization and highlight the power of machine learning and network biology to fully exploit the complementary information embedded in different omics layers. Finally, we discuss the potential of emerging single-cell methods and algorithms to further increase the resolution, allowing generation of functional insights about plant biology.

From prediction to function: Current practices and challenges towards the functional characterization of type III effectors

The type III secretion system (T3SS) is a well-studied pathogenicity determinant of many bacteria through which effectors (T3Es) are translocated into the host cell, where they exercise a wide range of functions to deceive the host cell's immunity and to establish a niche. Here we look at the different approaches that are used to functionally characterize a T3E. Such approaches include host localization studies, virulence screenings, biochemical activity assays, and large-scale omics, such as transcriptomics, interactomics, and metabolomics, among others. By means of the phytopathogenic Ralstonia solanacearum species complex (RSSC) as a case study, the current advances of these methods will be explored, alongside the progress made in understanding effector biology. Data obtained by such complementary methods provide crucial information to comprehend the entire function of the effectome and will eventually lead to a better understanding of the phytopathogen, opening opportunities to tackle it.

From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology

The selection of plant genotypes with improved productivity and tolerance to environmental constraints has always been a major concern in plant breeding. Classical approaches based on the generation of variability and selection of better phenotypes from large variant collections have improved their efficacy and processivity due to the implementation of molecular biology techniques, particularly genomics, Next Generation Sequencing and other omics such as proteomics and metabolomics. In this regard, the identification of interesting variants before they develop the phenotype trait of interest with molecular markers has advanced the breeding process of new varieties. Moreover, the correlation of phenotype or biochemical traits with gene expression or protein abundance has boosted the identification of potential new regulators of the traits of interest, using a relatively low number of variants. These important breakthrough technologies, built on top of classical approaches, will be improved in the future by including the spatial variable, allowing the identification of gene(s) involved in key processes at the tissue and cell levels.

Proteomics research in forest trees: A 2012-2022 update

This review is a compilation of proteomic studies on forest tree species published in the last decade (2012-2022), mostly focused on the most investigated species, including Eucalyptus, Pinus, and Quercus. Improvements in equipment, platforms, and methods in addition to the increasing availability of genomic data have favored the biological knowledge of these species at the molecular, organismal, and community levels. Integration of proteomics with physiological, biochemical and other large-scale omics in the direction of the Systems Biology, will provide a comprehensive understanding of different biological processes, from growth and development to responses to biotic and abiotic stresses. As main issue we envisage that proteomics in long-living plants will thrive light on the plant responses and resilience to global climate change, contributing to climate mitigation strategies and molecular breeding programs. Proteomics not only will provide a molecular knowledge of the mechanisms of resilience to either biotic or abiotic stresses, but also will allow the identification on key gene products and its interaction. Proteomics research has also a translational character being applied to the characterization of the variability and biodiversity, as well as to wood and non-wood derived products, traceability, allergen and bioactive peptides identification, among others. Even thought, the full potential of proteomics is far from being fully exploited in forest tree research, with PTMs and interactomics being reserved to plant model systems. The most outstanding achievements in forest tree proteomics in the last decade as well as prospects are discussed.

Plant synthetic biology innovations for biofuels and bioproducts

Plant-based biosynthesis of fuels, chemicals, and materials promotes environmental sustainability, which includes decreases in greenhouse gas emissions, water pollution, and loss of biodiversity. Advances in plant synthetic biology (synbio) should improve precision and efficacy of genetic engineering for sustainability. Applicable synbio innovations include genome editing, gene circuit design, synthetic promoter development, gene stacking technologies, and the design of environmental sensors. Moreover, recent advancements in developing spatially resolved and single-cell omics contribute to the discovery and characterization of cell-type-specific mechanisms and spatiotemporal gene regulations in distinct plant tissues for the expression of cell- and tissue-specific genes, resulting in improved bioproduction. This review highlights recent plant synbio progress and new single-cell molecular profiling towards sustainable biofuel and biomaterial production.

Does filter-aided sample preparation provide sufficient method linearity for quantitative plant shotgun proteomics?

Due to its outstanding throughput and analytical resolution, gel-free LC-based shotgun proteomics represents the gold standard of proteome analysis. Thereby, the efficiency of sample preparation dramatically affects the correctness and reliability of protein quantification. Thus, the steps of protein isolation, solubilization, and proteolysis represent the principal bottleneck of shotgun proteomics. The desired performance of the sample preparation protocols can be achieved by the application of detergents. However, these compounds ultimately compromise reverse-phase chromatographic separation and disrupt electrospray ionization. Filter-aided sample preparation (FASP) represents an elegant approach to overcome these limitations. Although this method is comprehensively validated for cell proteomics, its applicability to plants and compatibility with plant-specific protein isolation protocols remain to be confirmed. Thereby, the most important gap is the absence of the data on the linearity of underlying protein quantification methods for plant matrices. To fill this gap, we address here the potential of FASP in combination with two protein isolation protocols for quantitative analysis of pea (Pisum sativum) seed and Arabidopsis thaliana leaf proteomes by the shotgun approach. For this aim, in comprehensive spiking experiments with bovine serum albumin (BSA), we evaluated the linear dynamic range (LDR) of protein quantification in the presence of plant matrices. Furthermore, we addressed the interference of two different plant matrices in quantitative experiments, accomplished with two alternative sample preparation workflows in comparison to conventional FASP-based digestion of cell lysates, considered here as a reference. The spiking experiments revealed high sensitivities (LODs of up to 4 fmol) for spiked BSA and LDRs of at least 0.6 × 10². Thereby, phenol extraction yielded slightly better recoveries, whereas the detergent-based method showed better linearity. Thus, our results indicate the very good applicability of FASP to quantitative plant proteomics with only limited impact of the protein isolation technique on the method's overall performance.

Cotton proteomics: Dissecting the stress response mechanisms in cotton

The natural environment of plants comprises a complex set of biotic and abiotic stresses, and plant responses to these stresses are complex as well. Plant proteomics approaches have significantly revealed dynamic changes in plant proteome responses to stress and developmental processes. Thus, we reviewed the recent advances in cotton proteomics research under changing environmental conditions, considering the progress and challenging factors. Finally, we highlight how single-cell proteomics is revolutionizing plant research at the proteomics level. We envision that future cotton proteomics research at the single-cell level will provide a more complete understanding of cotton's response to stresses.

Zinc Finger-Homeodomain and Mini Zinc Finger proteins are key players in plant growth and responses to environmental stresses

The ZINC FINGER-HOMEODOMAIN (ZHD) protein family is a plant-specific family of transcription factors containing two conserved motifs: a non-canonical C5H3 zinc finger domain (ZF) and a DNA-binding homeodomain (HD). The MINI ZINC FINGER (MIF) proteins belong to this family, but were possibly derived from the ZHDs by losing the HD. Information regarding the function of ZHD and MIF proteins is scarce. However, different studies have shown that ZHD/MIF proteins play important roles not only in plant growth and development, but also in response to environmental stresses, including drought and pathogen attack. Here we review recent advances relative to ZHD/MIF functions in multiple species, to provide new insights into the diverse roles of these transcription factors in plants. Their mechanism of action in relation to their ability to interact with other proteins and DNA is also discussed. We then propose directions for future studies to understand better their important roles and pinpoint strategies for potential applications in crop improvement.

Recent advances in proteomics and metabolomics in plants

Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.

Advances in LC-MS/MS usher in the era of single-cell proteomics

As a new realm of single-cell studies becomes more accessible, innovative developments in one well-established technique are driving the field towards full-coverage proteomic profiles of single cells.

Multi-Omics Techniques for Soybean Molecular Breeding

Soybean is a major crop that provides essential protein and oil for food and feed. Since its origin in China over 5000 years ago, soybean has spread throughout the world, becoming the second most important vegetable oil crop and the primary source of plant protein for global consumption. From early domestication and artificial selection through hybridization and ultimately molecular breeding, the history of soybean breeding parallels major advances in plant science throughout the centuries. Now, rapid progress in plant omics is ushering in a new era of precision design breeding, exemplified by the engineering of elite soybean varieties with specific oil compositions to meet various end-use targets. The assembly of soybean reference genomes, made possible by the development of genome sequencing technology and bioinformatics over the past 20 years, was a great step forward in soybean research. It facilitated advances in soybean transcriptomics, proteomics, metabolomics, and phenomics, all of which paved the way for an integrated approach to molecular breeding in soybean. In this review, we summarize the latest progress in omics research, highlight novel findings made possible by omics techniques, note current drawbacks and areas for further research, and suggest that an efficient multi-omics approach may accelerate soybean breeding in the future. This review will be of interest not only to soybean breeders but also to researchers interested in the use of cutting-edge omics technologies for crop research and improvement.

Applications of cell- and tissue-specific 'omics to improve plant productivity

The individual tissues and cell types of plants each have characteristic properties that contribute to the function of the plant as a whole. These are reflected by unique patterns of gene expression, protein and metabolite content, which enable cell-type-specific patterns of growth, development and physiology. Gene regulatory networks act within the cell types to govern the production and activity of these components. For the broader organism to grow and reproduce successfully, cell-type-specific activity must also function within the context of surrounding cell types, which is achieved by coordination of signalling pathways. We can investigate how gene regulatory networks are constructed and function using integrative 'omics technologies. Historically such experiments in plant biological research have been performed at the bulk tissue level, to organ resolution at best. In this review, we describe recent advances in cell- and tissue-specific 'omics technologies that allow investigation at much improved resolution. We discuss the advantages of these approaches for fundamental and translational plant biology, illustrated through the examples of specialised metabolism in medicinal plants and seed germination. We also discuss the challenges that must be overcome for such approaches to be adopted widely by the community.

Scaling Up Single-Cell Proteomics

Single-cell tandem MS has enabled analyzing hundreds of single cells per day and quantifying thousands of proteins across the cells. The broad dissemination of these capabilities can empower the dissection of pathophysiological mechanisms in heterogeneous tissues. Key requirements for achieving this goal include robust protocols performed on widely accessible hardware, robust quality controls, community standards, and automated data analysis pipelines that can pinpoint analytical problems and facilitate their timely resolution. Toward meeting these requirements, this perspective outlines both existing resources and outstanding opportunities, such as parallelization, for catalyzing the wide dissemination of quantitative single-cell proteomics analysis that can be scaled up to tens of thousands of single cells. Indeed, simultaneous parallelization of the analysis of peptides and single cells is a promising approach for multiplicative increase in the speed of performing deep and quantitative single-cell proteomics. The community is ready to begin a virtuous cycle of increased adoption fueling the development of more technology and resources for single-cell proteomics that in turn drive broader adoption, scientific discoveries, and clinical applications.