Proteome-wide Analysis of Protein Thermal Stability in the Model Higher Plant Arabidopsis thaliana

Self-assembled nanonization of fatty acid-conjugated vaccine antigen for enhanced thermal stability

The aim of this study was to evaluate the enhanced thermal stability and physicochemical properties of fattigated vaccine antigens. High molecular weight influenza hemagglutinin (Heg) was used as a model antigen because of low heat stability requiring cold chamber. Heg was conjugated with long-chain oleic acid (C18) and short-chain 3-decenoic acid (C10) to prepare fattigated Heg. Circular dichroism analysis revealed no significant changes in the three-dimensional structure post-conjugation. In the liquid state, the fattigated Heg was self-assembled into nanoparticles (NPs) due to its amphiphilic nature, with sizes of 136.27 ± 12.78 nm for oleic acid-conjugated Heg (HOC) and 88.73 ± 3.27 nm for 3-decenoic acid-conjugated Heg (HDC). Accelerated thermal stability studies at 60 °C for 7 days demonstrated that fattigated Heg exhibited higher thermal stability than Heg in various liquid or solid states. The longer-chained HOC showed better thermal stability than HDC in the liquid state, attributed to increased hydrophobic interactions during self-assembly. In bio-mimicking liquid states at 37 °C, HOC exhibited higher thermal stability than Heg. Furthermore, solid-state HOC with cryoprotectants (trehalose, mannitol, and Tween® 80) had significantly increased thermal stability due to reduced exposure of protein surface area via nanonization behavior. The current fattigation platform could be a promising strategy for developing thermostable nano vaccines of heat-labile vaccine antigens.

Unveiling the dynamic relationship of viruses and/or symbiotic bacteria with plant resilience in abiotic stress

In the ecosphere, plants interact with environmental biotic and abiotic partners, where unbalanced interactions can induce unfavourable stress conditions. Abiotic factors (temperature, water, and salt) are primarily required for plants healthy survival, and any change in their availability is reflected as a stress signal. In certain cases, the presence of infectious pathogens such as viruses, bacteria, fungi, protozoa, nematodes, and insects can also create stress conditions in plants, leading to the emergence of disease or deficiency symptoms. While these symptoms are often typical of abiotic or biotic stress, however, there are instances where they can intensify under specific conditions. Here, we primarily summarize the viral interactions with plants during abiotic stress to understand how these associations are linked together during viral pathogenesis. Secondly, focus is given to the beneficial effects of root-associated symbiotic bacteria in fulfilling the basic needs of plants during normal as well as abiotic stress conditions. The modulations of plant functional proteins, and their occurrence/cross-talk, with pathogen (virus) and symbiont (bacteria) molecules are also discussed. Furthermore, we have highlighted the biochemical and systematic adaptations that develop in plants due to bacterial symbiosis to encounter stress hallmarks. Lastly, directions are provided towards exploring potential rhizospheric bacteria to maintain plant-microbes ecosystem and manage abiotic stress in plants to achieve better trait health in the horticulture crops.

Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation

Cellular activities are carried out vastly by protein complexes but large repertoire of protein complexes remains functionally uncharacterized which necessitate new strategies to delineate their roles in various cellular processes and diseases. Thermal proximity co-aggregation (TPCA) is readily deployable to characterize protein complex dynamics in situ and at scale. We develop a version termed Slim-TPCA that uses fewer temperatures increasing throughputs by over 3X, with new scoring metrics and statistical evaluation that result in minimal compromise in coverage and detect more relevant complexes. Less samples are needed, batch effects are minimized while statistical evaluation cost is reduced by two orders of magnitude. We applied Slim-TPCA to profile K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated, in accordance with the expected downregulation of most cellular activities, that include 55S ribosome and respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. Protein complexes in protein transport and degradation are found increasingly assembled unveiling their involvement in metabolic reprogramming during glucose deprivation. In summary, Slim-TPCA is an efficient strategy for characterization of protein complexes at scale across cellular conditions, and is available as Python package at https://pypi.org/project/Slim-TPCA/ .

Quantitative Time-Course Analysis of Osmotic and Salt Stress in Arabidopsis thaliana Using Short Gradient Multi-CV FAIMSpro BoxCar DIA

A major limitation when undertaking quantitative proteomic time-course experimentation is the tradeoff between depth-of-analysis and speed-of-analysis. In high complexity and high dynamic range sample types, such as plant extracts, balance between resolution and time is especially apparent. To address this, we evaluate multiple compensation voltage (CV) high field asymmetric waveform ion mobility spectrometry (FAIMSpro) settings using the latest label-free single-shot Orbitrap-based DIA acquisition workflows for their ability to deeply quantify the Arabidopsis thaliana seedling proteome. Using a BoxCarDIA acquisition workflow with a -30 -50 -70 CV FAIMSpro setting, we were able to consistently quantify >5000 Arabidopsis seedling proteins over a 21-min gradient, facilitating the analysis of ∼42 samples per day. Utilizing this acquisition approach, we then quantified proteome-level changes occurring in Arabidopsis seedling shoots and roots over 24 h of salt and osmotic stress, to identify early and late stress response proteins and reveal stress response overlaps. Here, we successfully quantify >6400 shoot and >8500 root protein groups, respectively, quantifying nearly ∼9700 unique protein groups in total across the study. Collectively, we pioneer a short gradient, multi-CV FAIMSpro BoxCarDIA acquisition workflow that represents an exciting new analysis approach for undertaking quantitative proteomic time-course experimentation in plants.

Systematic thermal analysis of the Arabidopsis proteome: Thermal tolerance, organization, and evolution

Understanding the thermal stability of the plant proteome in the context of the native cellular environment would aid the design of crops with high thermal tolerance, but only limited such data are available. Here, we applied quantitative mass spectrometry to profile the thermal stability of the Arabidopsis proteome and identify thermo-sensitive and thermo-resilient protein networks in Arabidopsis, providing a basis for understanding heat-induced damage. We also show that the similarities of the protein-melting curves can be used as a proxy to evaluate system-wide protein-protein interactions in non-engineered plants and enable the identification of transient interactions exhibited by metabolons in the context of the cellular environment. Finally, we report a systematic comparison of the thermal stability of paralogs in Arabidopsis to aid the investigation and understanding of gene duplication and protein evolution. Taken together, our results could have broad implications for the fields of plant thermal tolerance, plant protein assemblies, and evolution.

Protein interactome of 3',5'-cAMP reveals its role in regulating the actin cytoskeleton

Identification of protein interactors is ideally suited for the functional characterization of small molecules. 3',5'-cAMP is an evolutionary ancient signaling metabolite largely uncharacterized in plants. To tap into the physiological roles of 3',5'-cAMP, we used a chemo-proteomics approach, thermal proteome profiling (TPP), for the unbiased identification of 3',5'-cAMP protein targets. TPP measures shifts in the protein thermal stability upon ligand binding. Comprehensive proteomics analysis yielded a list of 51 proteins significantly altered in their thermal stability upon incubation with 3',5'-cAMP. The list contained metabolic enzymes, ribosomal subunits, translation initiation factors, and proteins associated with the regulation of plant growth such as CELL DIVISION CYCLE 48. To functionally validate obtained results, we focused on the role of 3',5'-cAMP in regulating the actin cytoskeleton suggested by the presence of actin among the 51 identified proteins. 3',5'-cAMP supplementation affected actin organization by inducing actin-bundling. Consistent with these results, the increase in 3',5'-cAMP levels, obtained either by feeding or by chemical modulation of 3',5'-cAMP metabolism, was sufficient to partially rescue the short hypocotyl phenotype of the actin2 actin7 mutant, severely compromised in actin level. The observed rescue was specific to 3',5'-cAMP, as demonstrated using a positional isomer 2',3'-cAMP, and true for the nanomolar 3',5'-cAMP concentrations reported for plant cells. In vitro characterization of the 3',5'-cAMP-actin pairing argues against a direct interaction between actin and 3',5'-cAMP. Alternative mechanisms by which 3',5'-cAMP would affect actin dynamics, such as by interfering with calcium signaling, are discussed. In summary, our work provides a specific resource, 3',5'-cAMP interactome, as well as functional insight into 3',5'-cAMP-mediated regulation in plants.

When drought meets heat - a plant omics perspective

Changes in weather patterns with emerging drought risks and rising global temperature are widespread and negatively affect crop growth and productivity. In nature, plants are simultaneously exposed to multiple biotic and abiotic stresses, but most studies focus on individual stress conditions. However, the simultaneous occurrence of different stresses impacts plant growth and development differently than a single stress. Plants sense the different stress combinations in the same or in different tissues, which could induce specific systemic signalling and acclimation responses; impacting different stress-responsive transcripts, protein abundance and modifications, and metabolites. This mini-review focuses on the combination of drought and heat, two abiotic stress conditions that often occur together. Recent omics studies indicate common or independent regulators involved in heat or drought stress responses. Here, we summarize the current research results, highlight gaps in our knowledge, and flag potential future focus areas.

CETSA and thermal proteome profiling strategies for target identification and drug discovery of natural products

BACKGROUND

Monitoring target engagement at various stages of drug development is essential for natural product (NP)-based drug discovery and development. The cellular thermal shift assay (CETSA) developed in 2013 is a novel, broadly applicable, label-free biophysical assay based on the principle of ligand-induced thermal stabilization of target proteins, which enables direct assessment of drug-target engagement in physiologically relevant contexts, including intact cells, cell lysates and tissues. This review aims to provide an overview of the work principles of CETSA and its derivative strategies and their recent progress in protein target validation, target identification and drug lead discovery of NPs.

METHODS

A literature-based survey was conducted using the Web of Science and PubMed databases. The required information was reviewed and discussed to highlight the important role of CETSA-derived strategies in NP studies.

RESULTS

After nearly ten years of upgrading and evolution, CETSA has been mainly developed into three formats: classic Western blotting (WB)-CETSA for target validation, thermal proteome profiling (TPP, also known as MS-CETSA) for unbiased proteome-wide target identification, and high-throughput (HT)-CETSA for drug hit discovery and lead optimization. Importantly, the application possibilities of a variety of TPP approaches for the target discovery of bioactive NPs are highlighted and discussed, including TPP-temperature range (TPP-TR), TPP-compound concentration range (TPP-CCR), two-dimensional TPP (2D-TPP), cell surface-TPP (CS-TPP), simplified TPP (STPP), thermal stability shift-based fluorescence difference in 2D gel electrophoresis (TS-FITGE) and precipitate supported TPP (PSTPP). In addition, the key advantages, limitations and future outlook of CETSA strategies for NP studies are discussed.

CONCLUSION

The accumulation of CETSA-based data can significantly accelerate the elucidation of the mechanism of action and drug lead discovery of NPs, and provide strong evidence for NP treatment against certain diseases. The CETSA strategy will certainly bring a great return far beyond the initial investment and open up more possibilities for future NP-based drug research and development.

DeepSTABp: A Deep Learning Approach for the Prediction of Thermal Protein Stability

Proteins are essential macromolecules that carry out a plethora of biological functions. The thermal stability of proteins is an important property that affects their function and determines their suitability for various applications. However, current experimental approaches, primarily thermal proteome profiling, are expensive, labor-intensive, and have limited proteome and species coverage. To close the gap between available experimental data and sequence information, a novel protein thermal stability predictor called DeepSTABp has been developed. DeepSTABp uses a transformer-based protein language model for sequence embedding and state-of-the-art feature extraction in combination with other deep learning techniques for end-to-end protein melting temperature prediction. DeepSTABp can predict the thermal stability of a wide range of proteins, making it a powerful and efficient tool for large-scale prediction. The model captures the structural and biological properties that impact protein stability, and it allows for the identification of the structural features that contribute to protein stability. DeepSTABp is available to the public via a user-friendly web interface, making it accessible to researchers in various fields.

Mass spectrometric exploration of phytohormone profiles and signaling networks

Phytohormones have crucial roles in plant growth, development, and acclimation to environmental stress; however, measuring phytohormone levels and unraveling their complex signaling networks and interactions remains challenging. Mass spectrometry (MS) has revolutionized the study of complex biological systems, enabling the comprehensive identification and quantification of phytohormones and their related targets. Here, we review recent advances in MS technologies and highlight studies that have used MS to discover and analyze phytohormone-mediated molecular events. In particular, we focus on the application of MS for profiling phytohormones, elucidating phosphorylation signaling, and mapping protein interactions in plants.

Cellular Thermal Shift Assay for the Detection of Small Molecule-Target Interactions in Arabidopsis Cells

Chemical genetics takes advantage of small molecule-protein interactions to explore various biological processes. Although an attractive alternative to classical genetics in plants, the identification of small-molecule targets remains a challenge and limits the broad use of the compounds. The cellular thermal shift assay (CETSA), based on the principle that binding of small molecules could affect the thermal stability of proteins, has been applied for target validation in plant cells. Combined with high-resolution mass spectrometry, CETSA can detect small-molecule targets by monitoring the changes in the protein thermal stability caused by the interactions with small molecules at the proteome level. Here we describe the small-molecule target validation as well as the target identification with mass spectrometry by means of CETSA.

Plant-specific HDT family histone deacetylases are nucleoplasmins

Histone acetyltransferase (HAT)- and histone deacetylase (HDAC)-mediated histone acetylation and deacetylation regulate nucleosome dynamics and gene expression. HDACs are classified into different families, with HD-tuins or HDTs being specific to plants. HDTs show some sequence similarity to nucleoplasmins, the histone chaperones that aid in binding, storing, and loading H2A/H2B dimers to assemble nucleosomes. Here, we solved the crystal structure of the N-terminal domain (NTD) of all four HDTs (HDT1, HDT2, HDT3, and HDT4) from Arabidopsis (Arabidopsis thaliana). The NTDs form a nucleoplasmin fold, exist as pentamers in solution, and are resistant to protease treatment, high temperature, salt, and urea conditions. Structurally, HDTs do not form a decamer, unlike certain classical nucleoplasmins. The HDT-NTD requires an additional A2 acidic tract C-terminal to the nucleoplasmin domain for interaction with histone H3/H4 and H2A/H2B oligomers. We also report the in-solution structures of HDT2 pentamers in complex with histone oligomers. Our study provides a detailed structural and in vitro functional characterization of HDTs, revealing them to be nucleoplasmin family histone chaperones. The experimental confirmation that HDTs are nucleoplasmins may spark new interest in this enigmatic family of proteins.

Rewiring of the protein-protein-metabolite interactome during the diauxic shift in yeast

In budding yeast Saccharomyces cerevisiae, the switch from aerobic fermentation to respiratory growth is separated by a period of growth arrest, known as the diauxic shift, accompanied by a significant metabolic rewiring, including the derepression of gluconeogenesis and the establishment of mitochondrial respiration. Previous studies reported hundreds of proteins and tens of metabolites accumulating differentially across the diauxic shift transition. To assess the differences in the protein-protein (PPIs) and protein-metabolite interactions (PMIs) yeast samples harvested in the glucose-utilizing, fermentative phase, ethanol-utilizing and early stationary respiratory phases were analysed using isothermal shift assay (iTSA) and a co-fractionation mass spectrometry approach, PROMIS. Whereas iTSA monitors changes in protein stability and is informative towards protein interaction status, PROMIS uses co-elution to delineate putative PPIs and PMIs. The resulting dataset comprises 1627 proteins and 247 metabolites, hundreds of proteins and tens of metabolites characterized by differential thermal stability and/or fractionation profile, constituting a novel resource to be mined for the regulatory PPIs and PMIs. The examples discussed here include (i) dissociation of the core and regulatory particle of the proteasome in the early stationary phase, (ii) the differential binding of a co-factor pyridoxal phosphate to the enzymes of amino acid metabolism and (iii) the putative, phase-specific interactions between proline-containing dipeptides and enzymes of central carbon metabolism.

Recent advances in isobaric labeling and applications in quantitative proteomics

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.

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.

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.

Mass spectrometry-based technologies for probing the 3D world of plant proteins

Over the past two decades, mass spectrometric (MS)-based proteomics technologies have facilitated the study of signaling pathways throughout biology. Nowhere is this needed more than in plants, where an evolutionary history of genome duplications has resulted in large gene families involved in posttranslational modifications and regulatory pathways. For example, at least 5% of the Arabidopsis thaliana genome (ca. 1,200 genes) encodes protein kinases and protein phosphatases that regulate nearly all aspects of plant growth and development. MS-based technologies that quantify covalent changes in the side-chain of amino acids are critically important, but they only address one piece of the puzzle. A more crucially important mechanistic question is how noncovalent interactions-which are more difficult to study-dynamically regulate the proteome's 3D structure. The advent of improvements in protein 3D technologies such as cryo-electron microscopy, nuclear magnetic resonance, and X-ray crystallography has allowed considerable progress to be made at this level, but these methods are typically limited to analyzing proteins, which can be expressed and purified in milligram quantities. Newly emerging MS-based technologies have recently been developed for studying the 3D structure of proteins. Importantly, these methods do not require protein samples to be purified and require smaller amounts of sample, opening the wider proteome for structural analysis in complex mixtures, crude lysates, and even in intact cells. These MS-based methods include covalent labeling, crosslinking, thermal proteome profiling, and limited proteolysis, all of which can be leveraged by established MS workflows, as well as newly emerging methods capable of analyzing intact macromolecules and the complexes they form. In this review, we discuss these recent innovations in MS-based "structural" proteomics to provide readers with an understanding of the opportunities they offer and the remaining challenges for understanding the molecular underpinnings of plant structure and function.

Proteome-wide cellular thermal shift assay reveals unexpected cross-talk between brassinosteroid and auxin signaling

Chemical genetics, which investigates biological processes using small molecules, is gaining interest in plant research. However, a major challenge is to uncover the mode of action of the small molecules. Here, we applied the cellular thermal shift assay coupled with mass spectrometry (CETSA MS) to intact Arabidopsis cells and showed that bikinin, the plant-specific glycogen synthase kinase 3 (GSK3) inhibitor, changed the thermal stability of some of its direct targets and putative GSK3-interacting proteins. In combination with phosphoproteomics, we also revealed that GSK3s phosphorylated the auxin carrier PIN-FORMED1 and regulated its polarity that is required for the vascular patterning in the leaf.

Despite the growing interest in using chemical genetics in plant research, small molecule target identification remains a major challenge. The cellular thermal shift assay coupled with high-resolution mass spectrometry (CETSA MS) that monitors changes in the thermal stability of proteins caused by their interactions with small molecules, other proteins, or posttranslational modifications, allows the discovery of drug targets or the study of protein–metabolite and protein–protein interactions mainly in mammalian cells. To showcase the applicability of this method in plants, we applied CETSA MS to intact Arabidopsis thaliana cells and identified the thermal proteome of the plant-specific glycogen synthase kinase 3 (GSK3) inhibitor, bikinin. A comparison between the thermal and the phosphoproteomes of bikinin revealed the auxin efflux carrier PIN-FORMED1 (PIN1) as a substrate of the Arabidopsis GSK3s that negatively regulate the brassinosteroid signaling. We established that PIN1 phosphorylation by the GSK3s is essential for maintaining its intracellular polarity that is required for auxin-mediated regulation of vascular patterning in the leaf, thus revealing cross-talk between brassinosteroid and auxin signaling.

Thermal Proteome Profiling to Identify Protein-ligand Interactions in the Apicomplexan Parasite Toxoplasma gondii

Toxoplasma gondii is a single-celled eukaryotic parasite that chronically infects a quarter of the global population. In recent years, phenotypic screens have identified compounds that block parasite replication. Unraveling the pathways and molecular mechanisms perturbed by such compounds requires target deconvolution. In parasites, such deconvolution has been achieved via chemogenomic approaches-for example, directed evolution followed by whole-genome sequencing or genome-wide knockout screens. As a proteomic alternative that directly probes the physical interaction between compound and protein, thermal proteome profiling (TPP), also known as the cellular thermal shift assay (CETSA), recently emerged as a method to identify small molecule-target interactions in living cells and cell extracts in a variety of organisms, including unicellular eukaryotic pathogens. Ligand binding induces a thermal stability shift-stabilizing or destabilizing proteins that change conformationally in response to the ligand-that can be measured by mass spectrometry (MS). Cells are incubated with different concentrations of ligand and heated, causing thermal denaturation of proteins. The soluble protein is extracted and quantified with multiplexed, quantitative MS, resulting in thousands of thermal denaturation profiles. Proteins engaging the ligand can be identified by their compound-dependent thermal shift. The protocol provided here can be used to identify ligand-target interactions and assess the impact of environmental or genetic perturbations on the thermal stability of the proteome in T. gondii and other eukaryotic pathogens. Graphic abstract: Thermal proteome profiling for target identification in the apicomplexan parasite T. gondii.

Drug Target Identification in Tissues by Thermal Proteome Profiling

Drug target deconvolution can accelerate the drug discovery process by identifying a drug's targets (facilitating medicinal chemistry efforts) and off-targets (anticipating toxicity effects or adverse drug reactions). Multiple mass spectrometry-based approaches have been developed for this purpose, but thermal proteome profiling (TPP) remains to date the only one that does not require compound modification and can be used to identify intracellular targets in living cells. TPP is based on the principle that the thermal stability of a protein can be affected by its interactions. Recent developments of this approach have expanded its applications beyond drugs and cell cultures to studying protein-drug interactions and biological phenomena in tissues. These developments open up the possibility of studying drug treatment or mechanisms of disease in a holistic fashion, which can result in the design of better drugs and lead to a better understanding of fundamental biology. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The thermal proteome stability profile of Trypanosoma cruzi in epimastigote and trypomastigote life stages

Trypanosoma cruzi is a flagellate protozoa being the etiological agent of Chagas disease, a neglected tropical disease, which still poses a public health problem worldwide. The intricate molecular changes during T. cruzi-host interaction have been explored using different largescale omics techniques. However, protein stability is largely unknown. Thermal proteome profiling (TPP) methodology has the potential to characterize proteome-wide stability highlighting key proteins during T. cruzi infection and life stage transition from the invertebrate to the mammalian host. In the present work, T. cruzi epimastigotes and trypomastigotes cell lysates were subjected to TPP workflow and analyzed by quantitative large-scale mass spectrometry-based proteomics to fit a melting profile for each protein. A total of 2884 proteins were identified and associated to 1741 melting curves being 1370 in trypomastigotes (Tm_AVG 53.53 °C) and 1279 in epimastigotes (Tm_AVG 50.89 °C). A total of 453 proteins were identified with statistically different melting profiles between the two life stages. Proteins associated to pathogenesis and intracellular transport had regulated melting temperatures. Membrane and glycosylated proteins had a higher average Tm in trypomastigotes compared to epimastigotes. This study represents the first large-scale comparison of parasite protein stability between life stages. SIGNIFICANCE: Trypanosoma cruzi, a unicellular flagellate parasite, is the etiological agent of Chagas disease, endemic in South America and affecting more that 7 million people worldwide. There is an intense research to identify novel chemotherapeutic and diagnostic targets of Chagas disease. Proteomic approaches have helped in elucidating the quantitative proteome and PTMs changes of T. cruzi during life cycle transition and upon different biotic and abiotic stimuli. However, a comprehensive knowledge of the protein-protein interaction and protein conformation is still missing. In order to fill this gap, this manuscript elucidates the T. cruzi Y strain proteome-wide thermal stability map in the epimastigote and trypomastigote life stages. Comparison between life stages showed a higher average melting temperature stability for trypomastigotes than epimastigotes indicating a host temperature adaptation. Both presented a selective thermal stability shift for cellular compartments, molecular functions and biological processes based on the T. cruzi life stage. Membrane and glycosylated proteins presented a higher thermal stability in trypomastigotes when compared to the epimastigotes.

Characterization of the Heat-Stable Proteome during Seed Germination in Arabidopsis with Special Focus on LEA Proteins

During seed germination, desiccation tolerance is lost in the radicle with progressing radicle protrusion and seedling establishment. This process is accompanied by comprehensive changes in the metabolome and proteome. Germination of Arabidopsis seeds was investigated over 72 h with special focus on the heat-stable proteome including late embryogenesis abundant (LEA) proteins together with changes in primary metabolites. Six metabolites in dry seeds known to be important for seed longevity decreased during germination and seedling establishment, while all other metabolites increased simultaneously with activation of growth and development. Thermo-stable proteins were associated with a multitude of biological processes. In the heat-stable proteome, a relatively similar proportion of fully ordered and fully intrinsically disordered proteins (IDP) was discovered. Highly disordered proteins were found to be associated with functional categories development, protein, RNA and stress. As expected, the majority of LEA proteins decreased during germination and seedling establishment. However, four germination-specific dehydrins were identified, not present in dry seeds. A network analysis of proteins, metabolites and amino acids generated during the course of germination revealed a highly connected LEA protein network.

Recent progress in mass spectrometry-based strategies for elucidating protein-protein interactions

Protein-protein interactions are fundamental to various aspects of cell biology with many protein complexes participating in numerous fundamental biological processes such as transcription, translation and cell cycle. MS-based proteomics techniques are routinely applied for characterising the interactome, such as affinity purification coupled to mass spectrometry that has been used to selectively enrich and identify interacting partners of a bait protein. In recent years, many orthogonal MS-based techniques and approaches have surfaced including proximity-dependent labelling of neighbouring proteins, chemical cross-linking of two interacting proteins, as well as inferring PPIs from the co-behaviour of proteins such as the co-fractionating profiles and the thermal solubility profiles of proteins. This review discusses the underlying principles, advantages, limitations and experimental considerations of these emerging techniques. In addition, a brief account on how MS-based techniques are used to investigate the structural and functional properties of protein complexes, including their topology, stoichiometry, copy number and dynamics, are discussed.

Thermal Analysis of a Mixture of Ribosomal Proteins by vT-ESI-MS: Toward a Parallel Approach for Characterizing the Stabilitome

The thermal stabilities of endogenous, intact proteins and protein assemblies in complex mixtures were characterized in parallel by means of variable-temperature electrospray ionization coupled to mass spectrometry (vT-ESI-MS). The method is demonstrated by directly measuring the melting transitions of seven proteins from a mixture of proteins derived from ribosomes. A proof-of-concept measurement of a fraction of an Escherichia coli lysate is provided to extend this approach to characterize the thermal stability of a proteome. As the solution temperature is increased, proteins and protein complexes undergo structural and organizational transitions; for each species, the folded ↔ unfolded and assembled ↔ disassembled populations are monitored based on changes in vT-ESI-MS charge state distributions and masses. The robustness of the approach illustrates a step toward the proteome-wide characterization of thermal stabilities and structural transitions-the stabilitome.

Mapping the plant proteome: tools for surveying coordinating pathways

Plants rapidly respond to environmental fluctuations through coordinated, multi-scalar regulation, enabling complex reactions despite their inherently sessile nature. In particular, protein post-translational signaling and protein-protein interactions combine to manipulate cellular responses and regulate plant homeostasis with precise temporal and spatial control. Understanding these proteomic networks are essential to addressing ongoing global crises, including those of food security, rising global temperatures, and the need for renewable materials and fuels. Technological advances in mass spectrometry-based proteomics are enabling investigations of unprecedented depth, and are increasingly being optimized for and applied to plant systems. This review highlights recent advances in plant proteomics, with an emphasis on spatially and temporally resolved analysis of post-translational modifications and protein interactions. It also details the necessity for generation of a comprehensive plant cell atlas while highlighting recent accomplishments within the field.

Inflect: Optimizing Computational Workflows for Thermal Proteome Profiling Data Analysis

The CETSA and Thermal Proteome Profiling (TPP) analytical methods are invaluable for the study of protein-ligand interactions and protein stability in a cellular context. These tools have increasingly been leveraged in work ranging from understanding signaling paradigms to drug discovery. Consequently, there is an important need to optimize the data analysis pipeline that is used to calculate protein melt temperatures (Tm) and relative melt shifts from proteomics abundance data. Here, we report a user-friendly analysis of the melt shift calculation workflow where we describe the impact of each individual calculation step on the final output list of stabilized and destabilized proteins. This report also includes a description of how key steps in the analysis workflow quantitatively impact the list of stabilized/destabilized proteins from an experiment. We applied our findings to develop a more optimized analysis workflow that illustrates the dramatic sensitivity of chosen calculation steps on the final list of reported proteins of interest in a study and have made the R based program Inflect available for research community use through the CRAN repository [McCracken, N. Inflect: Melt Curve Fitting and Melt Shift Analysis. R package version 1.0.3, 2021]. The Inflect outputs include melt curves for each protein which passes filtering criteria in addition to a data matrix which is directly compatible with downstream packages such as UpsetR for replicate comparisons and identification of biologically relevant changes. Overall, this work provides an essential resource for scientists as they analyze data from TPP and CETSA experiments and implement their own analysis pipelines geared toward specific applications.

Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post‐translational turnover, we devised a strategy combining pulse stable isotope‐labeled amino acids in cells (pSILAC), data‐independent acquisition mass spectrometry (DIA‐MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome‐wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.

The Relationship between the Misfolding Avoidance Hypothesis and Protein Evolutionary Rates in the Light of Empirical Evidence

For more than a decade, the misfolding avoidance hypothesis (MAH) and related theories have dominated evolutionary discussions aimed at explaining the variance of the molecular clock across cellular proteins. In this study, we use various experimental data to further investigate the consistency of the MAH predictions with empirical evidence. We also critically discuss experimental results that motivated the MAH development and that are often viewed as evidence of its major contribution to the variability of protein evolutionary rates. We demonstrate, in Escherichia coli and Homo sapiens, the lack of a substantial negative correlation between protein evolutionary rates and Gibbs free energies of unfolding, a direct measure of protein stability. We then analyze multiple new genome-scale data sets characterizing protein aggregation and interaction propensities, the properties that are likely optimized in evolution to alleviate deleterious effects associated with toxic protein misfolding and misinteractions. Our results demonstrate that the propensity of proteins to aggregate, the fraction of charged amino acids, and protein stickiness do correlate with protein abundances. Nevertheless, across multiple organisms and various data sets we do not observe substantial correlations between proteins’ aggregation- and stability-related properties and evolutionary rates. Therefore, diverse empirical data support the conclusion that the MAH and similar hypotheses do not play a major role in mediating a strong negative correlation between protein expression and the molecular clock, and thus in explaining the variability of evolutionary rates across cellular proteins.

Fight hard or die trying: when plants face pathogens under heat stress

In their natural environment, plants are exposed to biotic or abiotic stresses that occur sequentially or simultaneously. Plant responses to these stresses have been studied widely and have been well characterised in simplified systems involving single plant species facing individual stress. Temperature elevation is a major abiotic driver of climate change and scenarios have predicted an increase in the number and severity of epidemics. In this context, here we review the available data on the effect of heat stress on plant-pathogen interactions. Considering 45 studies performed on model or crop species, we discuss the possible implications of the optimum growth temperature of plant hosts and pathogens, mode of stress application and temperature variation on resistance modulations. Alarmingly, most identified resistances are altered under temperature elevation, regardless of the plant and pathogen species. Therefore, we have listed current knowledge on heat-dependent plant immune mechanisms and pathogen thermosensory processes, mainly studied in animals and human pathogens, that could help to understand the outcome of plant-pathogen interactions under elevated temperatures. Based on a general overview of the mechanisms involved in plant responses to pathogens, and integrating multiple interactions with the biotic environment, we provide recommendations to optimise plant disease resistance under heat stress and to identify thermotolerant resistance mechanisms.

Thermal Proteome Profiling and Meltome Analysis of a Thermophilic Bacterial Strain, Geobacillus thermoleovorans ARTRW1: Toward Industrial Applications

Thermophilic microorganisms that thrive in extreme environments are of great importance because they express heat-resistant enzymes with the potential to serve as biocatalysts in industrial applications. Thermal proteome profiling (TPP) is a multiplexed quantitative mass spectrometry method for analyses of structural information and melting behavior of thousands of proteins, simultaneously determining the thermal denaturation profiles of each protein. We report, in this study, TPP applied to a thermophilic bacterial proteome, a recently isolated strain of Geobacillus thermoleovorans named as ARTRW1. The proteome was investigated in terms of thermostable enzymes that are relevant to industrial applications. In this study, we present the thermostability profiles of its 868 proteins. The majority of G. thermoleovorans proteome was observed to melt between 62.5°C and 72°C, with melting point (T_m) mean value of 68.1°C ± 6.6°C. Unfolding characteristics of several enzymes, including amylase, protease, and lipase, were demonstrated which are highly informative in terms of their applicability to specific industrial processes. A significant correlation was observed between protein melting temperature and the structural features such as molecular weight and abundance, whereas correlations were modest or weak in relation to the α-helix structure percentages. Taken together, we demonstrated a system-wide melting profile analysis of a thermal proteome and listed proteins with elevated T_m values that are highly promising for applications in medicine, food engineering, and cosmetics in particular. The extracted T_m values were found similar to those obtained by biophysical methods applied to purified proteins. TPP analysis has significant industrial and biomedical potentials to accelerate thermophilic enzyme research and innovation.

Target identification and validation of natural products with label-free methodology: A critical review from 2005 to 2020

Natural products (NPs) have been an important source of therapeutic drugs in clinic use and contributed many chemical probes for research. The usefulness of NPs is however often marred by the incomplete understanding of their direct cellular targets. A number of experimental methods for drug target identification have been developed over the years. One class of methods, termed "label-free" methodology, exploits the energetic and biophysical features accompanying the association of macromolecules with drugs and other compounds in their native forms. Herein we review the working principles, assay implementations, and key applications of the most important approaches, and also give examples where they have been applied to NPs. We also assess the key advantages and limitations of each method. Furthermore, we address when and how the label-free methodology can be particularly useful considering some of the unique features of NP chemistry and bioactivation.

Thermal proteome profiling for interrogating protein interactions

Thermal proteome profiling (TPP) is based on the principle that, when subjected to heat, proteins denature and become insoluble. Proteins can change their thermal stability upon interactions with small molecules (such as drugs or metabolites), nucleic acids or other proteins, or upon post-translational modifications. TPP uses multiplexed quantitative mass spectrometry-based proteomics to monitor the melting profile of thousands of expressed proteins. Importantly, this approach can be performed in vitro, in situ, or in vivo. It has been successfully applied to identify targets and off-targets of drugs, or to study protein-metabolite and protein-protein interactions. Therefore, TPP provides a unique insight into protein state and interactions in their native context and at a proteome-wide level, allowing to study basic biological processes and their underlying mechanisms.

Temporal dynamics of protein complex formation and dissociation during human cytomegalovirus infection

The co-evolution and co-existence of viral pathogens with their hosts for millions of years is reflected in dynamic virus-host protein-protein interactions (PPIs) that are intrinsic to the spread of infections. Here, we investigate the system-wide dynamics of protein complexes throughout infection with the herpesvirus, human cytomegalovirus (HCMV). Integrating thermal shift assays and mass spectrometry quantification with virology and microscopy, we monitor the temporal formation and dissociation of hundreds of functional protein complexes and the dynamics of host-host, virus-host, and virus-virus PPIs. We establish pro-viral roles for cellular protein complexes and translocating proteins. We show the HCMV receptor integrin beta 1 dissociates from extracellular matrix proteins, becoming internalized with CD63, which is necessary for virus production. Moreover, this approach facilitates characterization of essential viral proteins, such as pUL52. This study of temporal protein complex dynamics provides insights into mechanisms of HCMV infection and a resource for biological and therapeutic studies.

Here, Hashimoto et al. apply mass spectrometry-based thermal proximity coaggregation to characterize the temporal dynamics of virus-host protein-protein interactions during human cytomegalovirus (HCMV) infection, uncovering proviral functions including the internalization of the HCMV receptor integrin beta 1 with CD63.

Emerging strategies for the identification of protein-metabolite interactions

Interactions between biological molecules enable life. The significance of a cell-wide understanding of molecular complexes is thus obvious. In comparison to protein-protein interactions, protein-metabolite interactions remain under-studied. However, this has been gradually changing due to technological progress. Here, we focus on the interactions between ligands and receptors, the triggers of signalling events. While the number of small molecules with proven or proposed signalling roles is rapidly growing, most of their protein receptors remain unknown. Conversely, there are numerous signalling proteins with predicted ligand-binding domains for which the identities of the metabolite counterparts remain elusive. Here, we discuss the current biochemical strategies for identifying protein-metabolite interactions and how they can be used to characterize known metabolite regulators and identify novel ones.