Arabidopsis proteome and the mass spectral assay library

Integrated multi-omics and genetic analyses reveal molecular determinants underlying Arabidopsis snap33 mutant phenotype

The secretory pathway is essential for plant immunity, delivering diverse antimicrobial molecules into the extracellular space. Arabidopsis thaliana soluble N-ethylmaleimide-sensitive-factor attachment protein receptor SNAP33 is a key actor of this process. The snap33 mutant displays dwarfism and necrotic lesions, however the molecular determinants of its macroscopic phenotypes remain elusive. Here, we isolated several new snap33 mutants that exhibited constitutive cell death and H2O2 accumulation, further defining snap33 as an autoimmune mutant. We then carried out quantitative transcriptomic and proteomic analyses showing that numerous defense transcripts and proteins were up-regulated in the snap33 mutant, among which genes/proteins involved in defense hormone, pattern-triggered immunity, and nucleotide-binding domain leucine-rich-repeat receptor signaling. qRT-PCR analyses and hormone dosages supported these results. Furthermore, genetic analyses elucidated the diverse contributions of the main defense hormones and some nucleotide-binding domain leucine-rich-repeat receptor signaling actors in the establishment of the snap33 phenotype, emphasizing the preponderant role of salicylic acid over other defense phytohormones. Moreover, the accumulation of pattern-triggered immunity and nucleotide-binding domain leucine-rich-repeat receptor signaling proteins in the snap33 mutant was confirmed by immunoblotting analyses and further shown to be salicylic acid-dependent. Collectively, this study unveiled molecular determinants underlying the Arabidopsis snap33 mutant phenotype and brought new insights into autoimmunity signaling.

Florigen-producing cells express FPF1-LIKE PROTEIN 1 that accelerates flowering and stem growth in long days with sunlight red/far-red ratio in Arabidopsis

Seasonal changes in spring induce flowering by expressing the florigen, FLOWERING LOCUS T (FT), in Arabidopsis. FT is expressed in unique phloem companion cells with unknown characteristics. The question of which genes are co-expressed with FT and whether they have roles in flowering remains elusive. Through tissue-specific translatome analysis, we discovered that under long-day conditions with the natural sunlight red/far-red ratio, the FT-producing cells express a gene encoding FPF1-LIKE PROTEIN 1 (FLP1). The master FT regulator, CONSTANS (CO), controls FLP1 expression, suggesting FLP1's involvement in the photoperiod pathway. FLP1 promotes early flowering independently of FT, is active in the shoot apical meristem, and induces the expression of SEPALLATA 3 (SEP3), a key E-class homeotic gene. Unlike FT, FLP1 facilitates inflorescence stem elongation. Our cumulative evidence indicates that FLP1 may act as a mobile signal. Thus, FLP1 orchestrates floral initiation together with FT and promotes inflorescence stem elongation during reproductive transitions.

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.

DPHL v.2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins

A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v.1, a previous pan-human library built from 1,096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying of 10,943 proteins. Here, we generated DPHL v.2 from 1,608 DDA-MS data. The data included 586 DDA-MS data acquired from 18 tissue types, while 1,022 files were derived from DPHL v.1. DPHL v.2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v.2 to include semi-tryptic peptides and protein isoforms. DPHL v.2 was then applied to two colorectal cancer cohorts. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v.1. Our findings show that the increased human proteome coverage of DPHL v.2 provides larger pools of potential protein biomarkers.

Dry side of the core: a meta-analysis addressing the original nature of the ABA signalosome at the onset of seed imbibition

The timing of seedling emergence is a major agricultural and ecological fitness trait, and seed germination is controlled by a complex molecular network including phytohormone signalling. One such phytohormone, abscisic acid (ABA), controls a large array of stress and developmental processes, and researchers have long known it plays a crucial role in repressing germination. Although the main molecular components of the ABA signalling pathway have now been identified, the molecular mechanisms through which ABA elicits specific responses in distinct organs is still enigmatic. To address the fundamental characteristics of ABA signalling during germination, we performed a meta-analysis focusing on the Arabidopsis dry seed proteome as a reflexion basis. We combined cutting-edge proteome studies, comparative functional analyses, and protein interaction information with genetic and physiological data to redefine the singular composition and operation of the ABA core signalosome from the onset of seed imbibition. In addition, we performed a literature survey to integrate peripheral regulators present in seeds that directly regulate core component function. Although this may only be the tip of the iceberg, this extended model of ABA signalling in seeds already depicts a highly flexible system able to integrate a multitude of information to fine-tune the progression of germination.

Identification of novel interacts partners of ADAR1 enzyme mediating the oncogenic process in aggressive breast cancer

Triple-negative breast cancer (TNBC) subtype is characterized by aggressive clinical behavior and poor prognosis patient outcomes. Here, we show that ADAR1 is more abundantly expressed in infiltrating breast cancer (BC) tumors than in benign tumors. Further, ADAR1 protein expression is higher in aggressive BC cells (MDA-MB-231). Moreover, we identify a novel interacting partners proteins list with ADAR1 in MDA-MB-231, using immunoprecipitation assay and mass spectrometry. Using iLoop, a protein-protein interaction prediction server based on structural features, five proteins with high iloop scores were discovered: Histone H2A.V, Kynureninase (KYNU), 40S ribosomal protein SA, Complement C4-A, and Nebulin (ranged between 0.6 and 0.8). In silico analysis showed that invasive ductal carcinomas had the highest level of KYNU gene expression than the other classifications (p < 0.0001). Moreover, KYNU mRNA expression was shown to be considerably higher in TNBC patients (p < 0.0001) and associated with poor patient outcomes with a high-risk value. Importantly, we found an interaction between ADAR1 and KYNU in the more aggressive BC cells. Altogether, these results propose a new ADAR-KYNU interaction as potential therapeutic targeted therapy in aggressive BC.

MS Ana: Improving Sensitivity in Peptide Identification with Spectral Library Search

Spectral library search can enable more sensitive peptide identification in tandem mass spectrometry experiments. However, its drawbacks are the limited availability of high-quality libraries and the added difficulty of creating decoy spectra for result validation. We describe MS Ana, a new spectral library search engine that enables high sensitivity peptide identification using either curated or predicted spectral libraries as well as robust false discovery control through its own decoy library generation algorithm. MS Ana identifies on average 36% more spectrum matches and 4% more proteins than database search in a benchmark test on single-shot human cell-line data. Further, we demonstrate the quality of the result validation with tests on synthetic peptide pools and show the importance of library selection through a comparison of library search performance with different configurations of publicly available human spectral libraries.

Analysis of the Arabidopsis coilin mutant reveals a positive role of AtCOILIN in plant immunity

Biogenesis of ribonucleoproteins occurs in dynamic subnuclear compartments called Cajal bodies (CBs). COILIN is a critical scaffolding component essential for CB formation, composition, and activity. We recently showed that Arabidopsis (Arabidopsis thaliana) AtCOILIN is phosphorylated in response to bacterial elicitor treatment. Here, we further investigated the role of AtCOILIN in plant innate immunity. Atcoilin mutants are compromised in defense responses to bacterial pathogens. Besides confirming a role of AtCOILIN in alternative splicing (AS), Atcoilin showed differential expression of genes that are distinct from those of AS, including factors involved in RNA biogenesis, metabolism, plant immunity, and phytohormones. Atcoilin mutant plants have reduced levels of defense phytohormones. As expected, the mutant plants were more sensitive to the necrotrophic fungal pathogen Botrytis cinerea. Our findings reveal an important role for AtCOILIN in innate plant immunity.

Challenges and opportunities for proteomics and the improvement of bread wheat quality

Wheat remains a critical global food source, pressured by climate change and the need to maximize yield, improve processing and nutritional quality and ensure safety. An enormous amount of research has been conducted to understand gluten protein composition and structure in relation to end-use quality, yet progress has become stagnant. This is mainly due to the need and inability to biochemically characterize the intact functional glutenin polymer in order to correlate to quality, necessitating reduction to monomeric subunits and a loss of contextual information. While some individual gluten proteins might have a positive or negative influence on gluten quality, it is the sum total of these proteins, their relative and absolute expression, their sub-cellular trafficking, the amount and size of glutenin polymers, and ratios between gluten protein classes that define viscoelasticity of gluten. The sub-cellular trafficking of gluten proteins during seed maturation is still not completely clear and there is evidence of dual pathways and therefore different destinations for proteins, either constitutively or temporally. The trafficking of proteins is also unclear in endosperm cells as they undergo programmed cell death; Golgi disappear around 12 DPA but protein filling continues at least to 25 DPA. Modulation of the timing of cellular events will invariably affect protein deposition and therefore gluten strength and function. Existing and emerging proteomics technologies such as proteoform profiling and top-down proteomics offer new tools to study gluten protein composition as a whole system and identify compositional patterns that can modify gluten structure with improved functionality.

Comprehensive proteomic analysis to elucidate the anti-heat stress effects of nano-selenium in rainbow trout (Oncorhynchus mykiss)

Because of the continuous intensification of global warming, extreme climate fluctuations, and high-density farming, cold-water rainbow trout (Oncorhynchus mykiss) are exposed to conditions of heat stress, which has severely impacted their survival and yield. Nano-selenium (nano-Se) shows higher biological activity and lower toxicity and has emerged as an ideal and ecological Se formulation. Herein rainbow trout were fed either a basal diet (control group) or basal diet plus 5 mg/kg nano-Se (treatment group). Samples were collected before (18 °C for 9 days; CG18, Se18) and after (24 °C for 8 h; CG24, Se24) heat stress. The DIA/SWATH approach was then applied to compare changes at the proteome level. We found 223 and 269 differentially abundant proteins in the CG18-CG24 and Se18-Se24 groups, respectively, which mainly included apoptosis-, heat stress-, and lipid-related proteins. In comparison with the CG18-CG24 group, the Se18-Se24 group showed higher abundance of molecular chaperone, such as Hsp70, Hsp90a.1, Hspa8, Hsp30, DNAJA4, Dnajb1, Bag2 and Ahsa1; on nano-Se supplementation, the heat stress-induced decline in the abundance of the selenoprotein MsrB2 was partially restored. Furthermore, nano-Se supplementation downregulated the abundance of lipid-related (CYP51, EBP, DHCR7, DHCR24, and APOB) and pro-apoptotic (caspase-8 and Bad) proteins. Protein-protein interaction analyses suggested that nano-Se inhibits apoptosis by upregulating the expression of Hsp70, Hsp90a.1, Hspa8, and Dnajb1; further, Hsp70/Hspa8 and MsrB2 appear to play a synergistic role in antioxidant defense under heat stress. Overall, our findings provide novel insights into nano-Se-mediated tolerance of heat stress, demonstrating that nano-Se exerts its anti-heat stress effects in rainbow trout by promoting protein repair, enhancing recovery of antioxidant enzyme activity, and alleviating lipid metabolism and apoptosis.

Wiskott-Aldrich syndrome protein forms nuclear condensates and regulates alternative splicing

The diverse functions of WASP, the deficiency of which causes Wiskott-Aldrich syndrome (WAS), remain poorly defined. We generated three isogenic WAS models using patient induced pluripotent stem cells and genome editing. These models recapitulated WAS phenotypes and revealed that WASP deficiency causes an upregulation of numerous RNA splicing factors and widespread altered splicing. Loss of WASP binding to splicing factor gene promoters frequently leads to aberrant epigenetic activation. WASP interacts with dozens of nuclear speckle constituents and constrains SRSF2 mobility. Using an optogenetic system, we showed that WASP forms phase-separated condensates that encompasses SRSF2, nascent RNA and active Pol II. The role of WASP in gene body condensates is corroborated by ChIPseq and RIPseq. Together our data reveal that WASP is a nexus regulator of RNA splicing that controls the transcription of splicing factors epigenetically and the dynamics of the splicing machinery through liquid-liquid phase separation.

Plant Proteome Dynamics

Proteins are intimately involved in executing and controlling virtually all cellular processes. To understand the molecular mechanisms that underlie plant phenotypes, it is essential to investigate protein expression, interactions, and modifications, to name a few. The proteome is highly dynamic in time and space, and a plethora of protein modifications, protein interactions, and network constellations are at play under specific conditions and developmental stages. Analysis of proteomes aims to characterize the entire protein complement of a particular cell type, tissue, or organism-a challenging task, given the dynamic nature of the proteome. Modern mass spectrometry-based proteomics technology can be used to address this complexity at a system-wide scale by the global identification and quantification of thousands of proteins. In this review, we present current methods and technologies employed in mass spectrometry-based proteomics and provide examples of dynamic changes in the plant proteome elucidated by proteomic approaches.

Proteomic Analysis Dissects Molecular Mechanisms Underlying Plant Responses to Phosphorus Deficiency

Phosphorus (P) is an essential nutrient for plant growth. In recent decades, the application of phosphate (Pi) fertilizers has contributed to significant increases in crop yields all over the world. However, low efficiency of P utilization in crops leads to intensive application of Pi fertilizers, which consequently stimulates environmental pollution and exhaustion of P mineral resources. Therefore, in order to strengthen the sustainable development of agriculture, understandings of molecular mechanisms underlying P efficiency in plants are required to develop cultivars with high P utilization efficiency. Recently, a plant Pi-signaling network was established through forward and reverse genetic analysis, with the aid of the application of genomics, transcriptomics, proteomics, metabolomics, and ionomics. Among these, proteomics provides a powerful tool to investigate mechanisms underlying plant responses to Pi availability at the protein level. In this review, we summarize the recent progress of proteomic analysis in the identification of differential proteins that play roles in Pi acquisition, translocation, assimilation, and reutilization in plants. These findings could provide insights into molecular mechanisms underlying Pi acquisition and utilization efficiency, and offer new strategies in genetically engineering cultivars with high P utilization efficiency.

SARS-CoV-2 genomes from Saudi Arabia implicate nucleocapsid mutations in host response and increased viral load

Monitoring SARS-CoV-2 spread and evolution through genome sequencing is essential in handling the COVID-19 pandemic. Here, we sequenced 892 SARS-CoV-2 genomes collected from patients in Saudi Arabia from March to August 2020. We show that two consecutive mutations (R203K/G204R) in the nucleocapsid (N) protein are associated with higher viral loads in COVID-19 patients. Our comparative biochemical analysis reveals that the mutant N protein displays enhanced viral RNA binding and differential interaction with key host proteins. We found increased interaction of GSK3A kinase simultaneously with hyper-phosphorylation of the adjacent serine site (S206) in the mutant N protein. Furthermore, the host cell transcriptome analysis suggests that the mutant N protein produces dysregulated interferon response genes. Here, we provide crucial information in linking the R203K/G204R mutations in the N protein to modulations of host-virus interactions and underline the potential of the nucleocapsid protein as a drug target during infection.

A comparative study of data-dependent acquisition and data-independent acquisition in proteomics analysis of clinical lung cancer tissues constrained by blood contamination

Proteomics analysis is often troubled by high-abundance proteins in samples such as plasma. However, many surgical tissue samples inevitably have got contaminated with blood before cryopreservation. Selection of an appropriate method to minimize the effect of high-abundance proteins is important for proteomics analysis of blood contaminated tissues. Here, we investigated and compared the abilities of data-independent acquisition (DIA) and data-dependent acquisition (DDA) strategies for the proteomics analysis of blood contaminated clinical tissue samples. Twelve pairs of carcinoma and para-carcinoma tissue samples from lung cancer patients were used for proteomics assays separately by DIA and DDA, and the blood contamination level in samples was evaluated by contamination index (CI). Compared with the DDA strategy, DIA in whole exhibited much better analytical capabilities in proteomics analysis of these samples with more identified protein groups and a higher discovery of differential proteins. With CI value increasing, whether DIA or DDA showed decreasing analysis ability. However, for samples with high CI values, the DIA strategy still shows acceptable analytical capability and indicates better blood pollution resistance than the DDA strategy. Our results implied that for clinical tissue samples, particularly for those contaminated with blood, DIA strategy should be a preferred method in proteomics studies.

Computational Optimization of Spectral Library Size Improves DIA-MS Proteome Coverage and Applications to 15 Tumors

Efficient peptide and protein identifications from data-independent acquisition mass spectrometric (DIA-MS) data typically rely on a project-specific spectral library with a suitable size. Here, we describe subLib, a computational strategy for optimizing the spectral library for a specific DIA data set based on a comprehensive spectral library, requiring the preliminary analysis of the DIA data set. Compared with the pan-human library strategy, subLib achieved a 41.2% increase in peptide precursor identifications and a 35.6% increase in protein group identifications in a test data set of six colorectal tumor samples. We also applied this strategy to 389 carcinoma samples from 15 tumor data sets: up to a 39.2% increase in peptide precursor identifications and a 19.0% increase in protein group identifications were observed. Our strategy for spectral library size optimization thus successfully proved to deepen the proteome coverages of DIA-MS data.

The Arabidopsis PeptideAtlas: Harnessing worldwide proteomics data to create a comprehensive community proteomics resource

We developed a resource, the Arabidopsis PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/), to solve central questions about the Arabidopsis thaliana proteome, such as the significance of protein splice forms and post-translational modifications (PTMs), or simply to obtain reliable information about specific proteins. PeptideAtlas is based on published mass spectrometry (MS) data collected through ProteomeXchange and reanalyzed through a uniform processing and metadata annotation pipeline. All matched MS-derived peptide data are linked to spectral, technical, and biological metadata. Nearly 40 million out of ∼143 million MS/MS (tandem MS) spectra were matched to the reference genome Araport11, identifying ∼0.5 million unique peptides and 17,858 uniquely identified proteins (only isoform per gene) at the highest confidence level (false discovery rate 0.0004; 2 non-nested peptides ≥9 amino acid each), assigned canonical proteins, and 3,543 lower-confidence proteins. Physicochemical protein properties were evaluated for targeted identification of unobserved proteins. Additional proteins and isoforms currently not in Araport11 were identified that were generated from pseudogenes, alternative start, stops, and/or splice variants, and small Open Reading Frames; these features should be considered when updating the Arabidopsis genome. Phosphorylation can be inspected through a sophisticated PTM viewer. PeptideAtlas is integrated with community resources including TAIR, tracks in JBrowse, PPDB, and UniProtKB. Subsequent PeptideAtlas builds will incorporate millions more MS/MS data.

Deep representation features from DreamDIAXMBD improve the analysis of data-independent acquisition proteomics

We developed DreamDIA^XMBD (denoted as DreamDIA), a software suite based on a deep representation model for data-independent acquisition (DIA) data analysis. DreamDIA adopts a data-driven strategy to capture comprehensive information from elution patterns of peptides in DIA data and achieves considerable improvements on both identification and quantification performance compared with other state-of-the-art methods such as OpenSWATH, Skyline and DIA-NN. Specifically, in contrast to existing methods which use only 6 to 10 selected fragment ions from spectral libraries, DreamDIA extracts additional features from hundreds of theoretical elution profiles originated from different ions of each precursor using a deep representation network. To achieve higher coverage of target peptides without sacrificing specificity, the extracted features are further processed by nonlinear discriminative models under the framework of positive-unlabeled learning with decoy peptides as affirmative negative controls. DreamDIA is publicly available at https://github.com/xmuyulab/DreamDIA-XMBD for high coverage and accuracy DIA data analysis.

Family-wide evaluation of RAPID ALKALINIZATION FACTOR peptides

Plant peptide hormones are important players that control various aspects of the lives of plants. RAPID ALKALINIZATION FACTOR (RALF) peptides have recently emerged as important players in multiple physiological processes. Numerous studies have increased our understanding of the evolutionary processes that shaped the RALF family of peptides. Nevertheless, to date, there is no comprehensive, family-wide functional study on RALF peptides. Here, we analyzed the phylogeny of the proposed multigenic RALF peptide family in the model plant Arabidopsis (Arabidopsis thaliana), ecotype Col-0, and tested a variety of physiological responses triggered by RALFs. Our phylogenetic analysis reveals that two of the previously proposed RALF peptides are not genuine RALF peptides, which leads us to propose a revision to the consensus AtRALF peptide family annotation. We show that the majority of AtRALF peptides, when applied exogenously as synthetic peptides, induce seedling or root growth inhibition and modulate reactive oxygen species (ROS) production in Arabidopsis. Moreover, our findings suggest that alkalinization and growth inhibition are, generally, coupled characteristics of RALF peptides. Additionally, we show that for the majority of the peptides, these responses are genetically dependent on FERONIA, suggesting a pivotal role for this receptor kinase in the perception of multiple RALF peptides.

Narrow Precursor Mass Range for DIA-MS Enhances Protein Identification and Quantification in Arabidopsis

Data independent acquisition-mass spectrometry (DIA-MS) is becoming widely utilised for robust and accurate quantification of samples in quantitative proteomics. Here, we describe the systematic evaluation of the effects of DIA precursor mass range on total protein identification and quantification. We show that a narrow mass range of precursors (~250 m/z) for DIA-MS enables a higher number of protein identifications. Subsequent application of DIA with narrow precursor range (from 400 to 650 m/z) on an Arabidopsis sample with spike-in known proteins identified 34.7% more proteins than in conventional DIA (cDIA) with a wide precursor range of 400-1200 m/z. When combining several DIA-MS analyses with narrow precursor ranges (i.e., 400-650, 650-900 and 900-1200 m/z), we were able to quantify 10,099 protein groups with a median coefficient of variation of <6%. These findings represent a 54.7% increase in the number of proteins quantified than with cDIA analysis. This is particularly important for low abundance proteins, as exemplified by the six-protein mix spike-in. In cDIA only five out of the six-protein mix were quantified while our approach allowed accurate quantitation of all six proteins.

Malat-1-PRC2-EZH1 interaction supports adaptive oxidative stress dependent epigenome remodeling in skeletal myotubes

PRC2-mediated epigenetic function involves the interaction with long non-coding RNAs (lncRNAs). Although the identity of some of these RNAs has been elucidated in the context of developmental programs, their counterparts in postmitotic adult tissue homeostasis remain uncharacterized. To this aim, we used terminally differentiated postmitotic skeletal muscle cells in which oxidative stress induces the dynamic activation of PRC2-Ezh1 through Embryonic Ectoderm Develpment (EED) shuttling to the nucleus. We identify lncRNA Malat-1 as a necessary partner for PRC2-Ezh1-dependent response to oxidative stress. We show that in this pathway, PRC2-EZH1 dynamic assembly, and in turn stress induced skeletal muscle targeted genes repression, depends specifically on Malat-1. Our study reports about PRC2-RNA interactions in the physiological context of adaptive oxidative stress response and identifies the first lncRNA involved in PRC2-Ezh1 function.

Three-in-One Simultaneous Extraction of Proteins, Metabolites and Lipids for Multi-Omics

Elucidation of complex molecular networks requires integrative analysis of molecular features and changes at different levels of information flow and regulation. Accordingly, high throughput functional genomics tools such as transcriptomics, proteomics, metabolomics, and lipidomics have emerged to provide system-wide investigations. Unfortunately, analysis of different types of biomolecules requires specific sample extraction procedures in combination with specific analytical instrumentation. The most efficient extraction protocols often only cover a restricted type of biomolecules due to their different physicochemical properties. Therefore, several sets/aliquots of samples are needed for extracting different molecules. Here we adapted a biphasic fractionation method to extract proteins, metabolites, and lipids from the same sample (3-in-1) for liquid chromatography-tandem mass spectrometry (LC-MS/MS) multi-omics. To demonstrate utility of the improved method, we used bacteria-primed Arabidopsis leaves to generate multi-omics datasets from the same sample. In total, we were able to analyze 1849 proteins, 1967 metabolites, and 424 lipid species in single samples. The molecules cover a wide range of biological and molecular processes, and allow quantitative analyses of different molecules and pathways. Our results have shown the clear advantages of the multi-omics method, including sample conservation, high reproducibility, and tight correlation between different types of biomolecules.

Proteomics and plant biology: contributions to date and a look towards the next decade

INTRODUCTION

This review presents the view of the author, that is opinionable and even speculative, on the field of proteomics, its application to plant biology knowledge, and translation to biotechnology. Written in a more academic than scientific style, it is based on past original and review articles by the author´s group, and those published by leading scientists in the last two years.

AREAS COVERED

Starting with a general definition and references to historical milestones, it covers sections devoted to the different platforms employed, the plant biology discourse in the protein language, challenges and future prospects, ending with the author opinion.

EXPERT OPINION

In 25 years, five proteomics platform generations have appeared. We are now moving from proteomics to Systems Biology. While feasible with model organisms, proteomics of orphan species remains challenging. Proteomics, even in its simplest approach, sheds light on plant biological processes, central dogma, and molecular bases of phenotypes of interest, and it can be translated to areas such as food traceability and allergen detection. Proteomics should be validated and optimized to each experimental system, objectives, and hypothesis. It has limitations, artifacts, and biases. We should not blindly accept proteomics data and just create a list of proteins, networks, and avoid speculative biological interpretations. From the hundred to thousand proteins identified and quantified, it is important to obtain a focus and validate some of them, otherwise it is merely. We are starting to have the protein pieces, so let, from now, build the proteomics and biological puzzle.

Estimating the number of protein molecules in a plant cell: protein and amino acid homeostasis during drought

During drought stress, cellular proteostasis on the one hand and amino acid homeostasis on the other hand are severely challenged, because the decrease in photosynthesis induces massive proteolysis, leading to drastic changes in both the proteome and the free amino acid pool. Thus, we selected progressive drought stress in Arabidopsis (Arabidopsis thaliana) as a model to investigate on a quantitative level the balance between protein and free amino acid homeostasis. We analyzed the mass composition of the leaf proteome based on proteomics datasets, and estimated how many protein molecules are present in a plant cell and its subcellular compartments. In addition, we calculated stress-induced changes in the distribution of individual amino acids between the free and protein-bound pools. Under control conditions, an average Arabidopsis mesophyll cell contains about 25 billion protein molecules, of which 80% are localized in chloroplasts. Severe water deficiency leads to degradation of more than 40% of the leaf protein mass, and thus causes a drastic shift in distribution toward the free amino acid pool. Stress-induced proteolysis of just half of the 340 million RubisCO hexadecamers present in the chloroplasts of a single mesophyll cell doubles the cellular content of free amino acids. A major fraction of the amino acids released from proteins is channeled into synthesis of proline, which is a compatible osmolyte. Complete oxidation of the remaining fraction as an alternative respiratory substrate can fully compensate for the lack of photosynthesis-derived carbohydrates for several hours.

New insight into the rapid growth of the Mikania micrantha stem based on DIA proteomic and RNA-Seq analysis

Mikania micrantha is one of the world's most invasive plants, which causes severe damage to natural ecosystems and agroforestry systems due to its rapid stem growth. This work investigated the proteomic and transcriptomic profiles of M. micrantha in different stem tissues (pre-internode, post-internode, and internode), as well as in adventitious roots and primary roots with the final goal of elucidating differentially expressed genes and proteins responsible for the rapid growth of stem. The objective was approached by using DIA-based proteomic and RNA-Seq technologies. More than seven giga-transcriptome clean reads were sequenced, and 5196 protein species were identified. Differentially expressed genes identified in all stem tissues were significantly enriched in photosynthesis and carbon fixation, suggesting that the stem possesses a strong photosynthetic capacity in order to maintain the energy supply for this species. Analysis of differentially expressed proteins showed that proteins related to photosystem I/II and the cytochrome b6/f complex, such as D1, D2, and cp43, were also highly accumulated in the adventitious roots, corroborating the transcriptome analysis results. These results provided basic proteomic and transcriptional expression information about the M. micrantha stem and adventitious root, thereby improving our understanding of the molecular mechanism underlying rapid growth in this species. SIGNIFICANCE: This is the first study to investigate the proteomic and transcriptomic profiles of Mikania micrantha, a highly invasive plant, in different stem tissues (pre-internode, post-internode, and internode), as well as in adventitious and primary roots, using the latest DIA-based (data-independent acquisition mode) proteomic and RNA-Seq technologies. A comprehensive study was carried out, and differentially expressed genes and differentially expressed proteins identified in the pre-internode, post-internode, and internode tissues were significantly enriched during photosynthesis and carbon fixation, suggesting that the M. micrantha stem possesses a strong photosynthetic capacity that allows the plant to maintain a high energy supply. Enriched plant hormone signal transduction pathway analysis revealed an interaction between auxin and other phytohormones involved in adventitious root development. The study provided basic data on the molecular mechanism of M. micrantha vegetative propagation and the rapid growth of its stem. The novel scientific content of this study successfully builds upon the limited information currently available on the subject, therefore warranting publication.

Reshaping of the Arabidopsis thaliana Proteome Landscape and Co-regulation of Proteins in Development and Immunity

Proteome remodeling is a fundamental adaptive response, and proteins in complexes and functionally related proteins are often co-expressed. Using a deep sampling strategy we define core proteomes of Arabidopsis thaliana tissues with around 10 000 proteins per tissue, and absolutely quantify (copy numbers per cell) nearly 16 000 proteins throughout the plant lifecycle. A proteome-wide survey of global post-translational modification revealed amino acid exchanges pointing to potential conservation of translational infidelity in eukaryotes. Correlation analysis of protein abundance uncovered potentially new tissue- and age-specific roles of entire signaling modules regulating transcription in photosynthesis, seed development, and senescence and abscission. Among others, the data suggest a potential function of RD26 and other NAC transcription factors in seed development related to desiccation tolerance as well as a possible function of cysteine-rich receptor-like kinases (CRKs) as ROS sensors in senescence. All of the components of ribosome biogenesis factor (RBF) complexes were found to be co-expressed in a tissue- and age-specific manner, indicating functional promiscuity in the assembly of these less-studied protein complexes in Arabidopsis.Furthermore, we characterized detailed proteome remodeling in basal immunity by treating Arabidopsis seeldings with flg22. Through simultaneously monitoring phytohormone and transcript changes upon flg22 treatment, we obtained strong evidence of suppression of jasmonate (JA) and JA-isoleucine (JA-Ile) levels by deconjugation and hydroxylation by IAA-ALA RESISTANT3 (IAR3) and JASMONATE-INDUCED OXYGENASE 2 (JOX2), respectively, under the control of JASMONATE INSENSITIVE 1 (MYC2), suggesting an unrecognized role of a new JA regulatory switch in pattern-triggered immunity. Taken together, the datasets generated in this study present extensive coverage of the Arabidopsis proteome in various biological scenarios, providing a rich resource available to the whole plant science community.

Probing SWATH-MS as a tool for proteome level quantification in a nonmodel fish

Quantitative proteomics via mass spectrometry can provide valuable insight into molecular and phenotypic characteristics of a living system. Recent mass spectrometry developments include data‐independent acquisition (SWATH/DIA‐MS), an accurate, sensitive and reproducible method for analysing the whole proteome. The main requirement for this method is the creation of a comprehensive spectral library. New technologies have emerged producing larger and more accurate species‐specific libraries leading to a progressive collection of proteome references for multiple molecular model species. Here, for the first time, we set out to compare different spectral library constructions using multiple tissues from a coral reef fish to demonstrate its value and feasibility for nonmodel organisms. We created a large spectral library composed of 12,553 protein groups from liver and brain tissues. Via identification of differentially expressed proteins under fish exposure to elevated pCO₂ and temperature, we validated the application and usefulness of these different spectral libraries. Successful identification of significant differentially expressed proteins from different environmental exposures occurred using the library with a combination of data‐independent and data‐dependent acquisition methods as well as both tissue types. Further analysis revealed expected patterns of significantly up‐regulated heat shock proteins in a dual condition of ocean warming and acidification indicating the biological accuracy and relevance of the method. This study provides the first reference spectral library for a nonmodel organism. It represents a useful guide for future building of accurate spectral library references in nonmodel organisms allowing the discovery of ecologically relevant changes in the proteome.