Thermal proteome profiling in bacteria: probing protein state in vivo

On the Origin of Information Dynamics in Early Life

We hypothesize that predictable variations in environmental conditions caused by night/day cycles created opportunities and hazards that initiated information dynamics central to life's origin. Increased daytime temperatures accelerated key chemical reactions but also caused the separation of double-stranded polynucleotides, leading to hydrolysis, particularly of single-stranded RNA. Daytime solar UV radiation promoted the synthesis of organic molecules but caused broad damage to protocell macromolecules. We hypothesize that inter-related simultaneous adaptations to these hazards produced molecular dynamics necessary to store and use information. Self-replicating RNA heritably reduced the hydrolysis of single strands after separation during warmer daytime periods by promoting sequences that formed hairpin loops, generating precursors to transfer RNA (tRNA), and initiating tRNA-directed evolutionary dynamics. Protocell survival during daytime promoted sequences in self-replicating RNA within protocells that formed RNA-peptide hybrids capable of scavenging UV-induced free radicals or catalyzing melanin synthesis from tyrosine. The RNA-peptide hybrids are precursors to ribosomes and the triplet codes for RNA-directed protein synthesis. The protective effects of melanin production persist as melanosomes are found throughout the tree of life. Similarly, adaptations mitigating UV damage led to the replacement of Na+ by K+ as the dominant mobile cytoplasmic cation to promote diel vertical migration and selected for homochirality. We conclude that information dynamics emerged in early life through adaptations to predictably fluctuating opportunities and hazards during night/day cycles, and its legacy remains observable in extant life.

PEBP1 amplifies mitochondrial dysfunction-induced integrated stress response

Mitochondrial dysfunction is involved in numerous diseases and the aging process. The integrated stress response (ISR) serves as a critical adaptation mechanism to a variety of stresses, including those originating from mitochondria. By utilizing mass spectrometry-based cellular thermal shift assay (MS-CETSA), we uncovered that phosphatidylethanolamine-binding protein 1 (PEBP1), also known as Raf kinase inhibitory protein (RKIP), is thermally stabilized by stresses which induce mitochondrial ISR. Depletion of PEBP1 impaired mitochondrial ISR activation by reducing eukaryotic translation initiation factor 2α (eIF2α) phosphorylation and subsequent ISR gene expression, which was independent of PEBP1's role in inhibiting the RAF/MEK/ERK pathway. Consistently, overexpression of PEBP1 potentiated ISR activation by heme-regulated inhibitor (HRI) kinase, the principal eIF2α kinase in the mitochondrial ISR pathway. Real-time interaction analysis using luminescence complementation in live cells revealed an interaction between PEBP1 and eIF2α, which was disrupted by eIF2α S51 phosphorylation. These findings suggest a role for PEBP1 in amplifying mitochondrial stress signals, thereby facilitating an effective cellular response to mitochondrial dysfunction. Therefore, PEBP1 may be a potential therapeutic target for diseases associated with mitochondrial dysfunction.

Identifying Opportunity Targets in Gram-Negative Pathogens for Infectious Disease Mitigation

Antimicrobial drug resistance (AMR) is a pressing global human health challenge. Humans face one of their grandest challenges as climate change expands the habitat of vectors that bear human pathogens, incidences of nosocomial infections rise, and new antibiotics discovery lags. AMR is a multifaceted problem that requires a multidisciplinary and an "all-hands-on-deck" approach. As chemical microbiologists, we are well positioned to understand the complexities of AMR while seeing opportunities for tackling the challenge. In this Outlook, we focus on vulnerabilities of human pathogens and posit that they represent "opportunity targets" for which few modulatory ligands exist. We center our attention on proteins in Gram-negative organisms, which are recalcitrant to many antibiotics because of their external membrane barrier. Our hope is to highlight such targets and explore their potential as "druggable" proteins for infectious disease mitigation. We posit that success in this endeavor will introduce new classes of antibiotics that might alleviate some of the current pressing AMR concerns.

Studying Target-Engagement of Anti-Infectives by Solvent-Induced Protein Precipitation and Quantitative Mass Spectrometry

Antimicrobial resistance (AMR) poses a serious threat to global health. The rapid emergence of resistance contrasts with the slow pace of antimicrobial development, emphasizing the urgent need for innovative drug discovery approaches. This study addresses a critical bottleneck in early drug development by introducing integral solvent-induced protein precipitation (iSPP) to rapidly assess the target-engagement of lead compounds in extracts of pathogenic microorganisms under close-to-physiological conditions. iSPP measures the change in protein stability against solvent-induced precipitation in the presence of ligands. The iSPP method for bacteria builds upon established SPP procedures and features optimized denaturation gradients and minimized sample input amounts. The effectiveness of the iSPP workflow was initially demonstrated through a multidrug target-engagement study. Using quantitative mass spectrometry (LC-MS/MS), we successfully identified known drug targets of seven different antibiotics in cell extracts of four AMR-related pathogens: the three Gram-negative bacteria Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and the Gram-positive bacterium Staphylococcus aureus. The iSPP method was ultimately applied to demonstrate target-engagement of compounds derived from target-based drug discovery. We employed five small molecules targeting three enzymes in the 2-C-methyl-d-erythritol 4-phosphate (MEP) pathway─a promising focus for anti-infective drug development. The study showcases iSPP adaptability and efficiency in identifying anti-infective drug targets, advancing early-stage drug discovery against AMR.

One-Pot Time-Induced Proteome Integral Solubility Alteration Assay for Automated and Sensitive Drug-Target Identification

The proteome integral solubility alteration (PISA) assay is widely used for identifying drug targets, but it is labor-intensive and time-consuming and requires a substantial amount of biological sample. Aiming at enabling automation and greatly reducing the sample amount, we developed one-pot time-induced (OPTI)-PISA. Here, we demonstrate OPTI-PISA performance on identifying targets of multiple drugs in cell lysate and scaling down the sample amount to sub-microgram levels, making the PISA method suitable for NanoProteomics. OPTI-PISA can be implemented using only the standard equipment of a proteomics lab.

Characterizing protein-protein interactions with thermal proteome profiling

Thermal proteome profiling (TPP) is an innovative technique that uses the principle of protein thermal stability to identify potential protein interaction partners. Employing quantitative mass spectrometry, TPP measures protein stability across the proteome, offering a comprehensive snapshot of protein interactions in a single experiment. When studying protein-protein interactions (PPI), TPP leverages changes in apparent protein melting temperatures to identify transient and weak interactions that most traditional PPI detection methodologies struggle to measure. This review discusses current TPP methodologies, the challenges of interpreting the resulting complex datasets, and opportunities to deepen and improve PPI networks. By advancing our grasp of intricate protein interactions, TPP promises to illuminate the molecular basis of diseases and drive the discovery of novel therapeutic targets.

Mitochondria: great balls of fire

Recent experimental studies indicate that mitochondria in mammalian cells are maintained at temperatures of at least 50 °C. While acknowledging the limitations of current experimental methods and their interpretation, we here consider the ramifications of this finding for cellular functions and for evolution. We consider whether mitochondria as heat-producing organelles had a role in the origin of eukaryotes and in the emergence of homeotherms. The homeostatic responses of mitochondrial temperature to externally applied heat imply the existence of a molecular heat-sensing system in mitochondria. While current findings indicate high temperatures for the innermost compartments of mitochondria, those of the mitochondrial surface and of the immediately surrounding cytosol remain to be determined. We ask whether some aspects of mitochondrial dynamics and motility could reflect changes in the supply and demand for mitochondrial heat, and whether mitochondrial heat production could be a factor in diseases and immunity.

Physiological Effects of TolC-Dependent Multidrug Efflux Pumps in Escherichia coli: Impact on Motility and Growth Under Stress Conditions

Enterobacteriaceae possess eight TolC-dependent multidrug efflux pumps: AcrAB-TolC, AcrAD-TolC, AcrEF-TolC, MdtEF-TolC, MdtABC-TolC, EmrAB-TolC, EmrYK-TolC, and MacAB-TolC, which efflux bile salts, antibiotics, metabolites, or other compounds. However, our understanding of their physiological roles remains limited, especially for less-studied pumps like EmrYK-TolC. In this study, we tested the effects on swimming motility and growth under stress conditions of Escherichia coli mutants individually deleted for each inner-membrane transporter component of all eight TolC-dependent pumps, a mutant deleted for the AcrB-accessory protein AcrZ, and a mutant simultaneously deleted for all eight pumps (ΔtolC). We found that all mutants tested, except the ΔemrY and ΔacrZ mutants, displayed increased swimming motility. Additionally, the loss of each individual TolC-dependent pump or AcrZ did not reduce growth and sometimes even enhanced it compared to the parental strain under various growth conditions: temperature (LB at 25, 30, 37, and 42°C), pH (LB at pH 6.0, 7.4, and 9.0; and LB buffered to pH 6.0, 7.4, and 8.25), LB with limited air exchange, and nutritional stress (M9-glucose or M9-glycerol). In contrast, the ΔtolC mutant grew significantly slower than the parental strain under all conditions tested except in LB-TRIS pH 7.4 and LB with limited air exchange. Overall, these findings indicate that while individual TolC-dependent pumps are generally dispensable for growth under many stress conditions in the absence of antimicrobials, possibly due to their partially overlapping substrate profiles, TolC-dependent efflux is required for maximal growth under most conditions.

Link Between Individual Codon Frequencies and Protein Expression: Going Beyond Codon Adaptation Index

An important role of a particular synonymous codon composition of a gene in its expression level is well known. There are a number of algorithms optimizing codon usage of recombinant genes to maximize their expression in host cells. Nevertheless, the underlying mechanism remains unsolved and is of significant relevance. In the realm of modern biotechnology, directing protein production to a specific level is crucial for metabolic engineering, genome rewriting and a growing number of other applications. In this study, we propose two new simple statistical and empirical methods for predicting the protein expression level from the nucleotide sequence of the corresponding gene: Codon Expression Index Score (CEIS) and Codon Productivity Score (CPS). Both of these methods are based on the influence of each individual codon in the gene on the overall expression level of the encoded protein and the frequencies of isoacceptors in the species. Our predictions achieve a correlation level of up to r = 0.7 with experimentally measured quantitative proteome data of Escherichia coli, which is superior to any previously proposed methods. Our work helps understand how codons determine protein abundances. Based on these methods, it is possible to design proteins optimized for expression in a particular organism.

Streamlined analysis of drug targets by proteome integral solubility alteration indicates organ-specific engagement

Proteins are the primary targets of almost all small molecule drugs. However, even the most selectively designed drugs can potentially target several unknown proteins. Identification of potential drug targets can facilitate design of new drugs and repurposing of existing ones. Current state-of-the-art proteomics methodologies enable screening of thousands of proteins against a limited number of drug molecules. Here we report the development of a label-free quantitative proteomics approach that enables proteome-wide screening of small organic molecules in a scalable, reproducible, and rapid manner by streamlining the proteome integral solubility alteration (PISA) assay. We used rat organs ex-vivo to determine organ specific targets of medical drugs and enzyme inhibitors to identify drug targets for common drugs such as Ibuprofen. Finally, global drug profiling revealed overarching trends of how small molecules affect the proteome through either direct or indirect protein interactions.

Merging multi-omics with proteome integral solubility alteration unveils antibiotic mode of action

Antimicrobial resistance is responsible for an alarming number of deaths, estimated at 5 million per year. To combat priority pathogens, like Helicobacter pylori, the development of novel therapies is of utmost importance. Understanding the molecular alterations induced by medications is critical for the design of multi-targeting treatments capable of eradicating the infection and mitigating its pathogenicity. However, the application of bulk omics approaches for unraveling drug molecular mechanisms of action is limited by their inability to discriminate between target-specific modifications and off-target effects. This study introduces a multi-omics method to overcome the existing limitation. For the first time, the Proteome Integral Solubility Alteration (PISA) assay is utilized in bacteria in the PISA-Express format to link proteome solubility with different and potentially immediate responses to drug treatment, enabling us the resolution to understand target-specific modifications and off-target effects. This study introduces a comprehensive method for understanding drug mechanisms and optimizing the development of multi-targeting antimicrobial therapies.

Cellular thermal shift assay: an approach to identify and assess protein target engagement

INTRODUCTION

A comprehensive and global knowledge of protein target engagement is of vital importance for mechanistic studies and in drug development. Since its initial introduction, the cellular thermal shift assay (CETSA) has proven to be a reliable and flexible technique that can be widely applied to multiple contexts and has profound applications in facilitating the identification and assessment of protein target engagement.

AREAS COVERED

This review introduces the principle of CETSA, elaborates on western blot-based CETSA and MS-based thermal proteome profiling (TPP) as well as the major applications and prospects of these approaches.

EXPERT OPINION

CETSA primarily evaluates a given ligand binding to a particular target protein in cells and tissues with the protein thermal stabilities analyzed by western blot. When coupling mass spectrometry with CETSA, thermal proteome profiling allows simultaneous proteome-wide experiment that greatly increased the efficiency of target engagement evaluation, and serves as a promising strategy to identify protein targets and off-targets as well as protein-protein interactions to uncover the biological effects. The CETSA approaches have broad applications and potentials in drug development and clinical research.

In situ analysis of osmolyte mechanisms of proteome thermal stabilization

Organisms use organic molecules called osmolytes to adapt to environmental conditions. In vitro studies indicate that osmolytes thermally stabilize proteins, but mechanisms are controversial, and systematic studies within the cellular milieu are lacking. We analyzed Escherichia coli and human protein thermal stabilization by osmolytes in situ and across the proteome. Using structural proteomics, we probed osmolyte effects on protein thermal stability, structure and aggregation, revealing common mechanisms but also osmolyte- and protein-specific effects. All tested osmolytes (trimethylamine N-oxide, betaine, glycerol, proline, trehalose and glucose) stabilized many proteins, predominantly via a preferential exclusion mechanism, and caused an upward shift in temperatures at which most proteins aggregated. Thermal profiling of the human proteome provided evidence for intrinsic disorder in situ but also identified potential structure in predicted disordered regions. Our analysis provides mechanistic insight into osmolyte function within a complex biological matrix and sheds light on the in situ prevalence of intrinsically disordered regions.

Systematic identification of structure-specific protein-protein interactions

The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis-mass spectrometry (LiP-MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP-MS detects well-characterized PPIs, including antibody-target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson's disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.

Targeting bacterial nickel transport with aspergillomarasmine A suppresses virulence-associated Ni-dependent enzymes

Microbial Ni2+ homeostasis underpins the virulence of several clinical pathogens. Ni2+ is an essential cofactor in urease and [NiFe]-hydrogenases involved in colonization and persistence. Many microbes produce metallophores to sequester metals necessary for their metabolism and starve competing neighboring organisms. The fungal metallophore aspergillomarasmine A (AMA) shows narrow specificity for Zn2+, Ni2+, and Co2+. Here, we show that this specificity allows AMA to block the uptake of Ni2+ and attenuate bacterial Ni-dependent enzymes, offering a potential strategy for reducing virulence. Bacterial exposure to AMA perturbs H2 metabolism, ureolysis, struvite crystallization, and biofilm formation and shows efficacy in a Galleria mellonella animal infection model. The inhibition of Ni-dependent enzymes was aided by Zn2+, which complexes with AMA and competes with the native nickelophore for the uptake of Ni2+. Biochemical analyses demonstrated high-affinity binding of AMA-metal complexes to NikA, the periplasmic substrate-binding protein of the Ni2+ uptake system. Structural examination of NikA in complex with Ni-AMA revealed that the coordination geometry of Ni-AMA mimics the native ligand, Ni-(L-His)2, providing a structural basis for binding AMA-metal complexes. Structure-activity relationship studies of AMA identified regions of the molecule that improve NikA affinity and offer potential routes for further developing this compound as an anti-virulence agent.

Selective targeting of Plasmodium falciparum Hsp90 disrupts the 26S proteasome

The molecular chaperone heat shock protein 90 (Hsp90) has an essential but largely undefined role in maintaining proteostasis in Plasmodium falciparum, the most lethal malaria parasite. Herein, we identify BX-2819 and XL888 as potent P. falciparum (Pf)Hsp90 inhibitors. Derivatization of XL888's scaffold led to the development of Tropane 1, as a PfHsp90-selective binder with nanomolar affinity. Hsp90 inhibitors exhibit anti-Plasmodium activity against the liver, asexual blood, and early gametocyte life stages. Thermal proteome profiling was implemented to assess PfHsp90-dependent proteome stability, and the proteasome-the main site of cellular protein recycling-was enriched among proteins with perturbed stability upon PfHsp90 inhibition. Subsequent biochemical and cellular studies suggest that PfHsp90 directly promotes proteasome hydrolysis by chaperoning the active 26S complex. These findings expand our knowledge of the PfHsp90-dependent proteome and protein quality control mechanisms in these pathogenic parasites, as well as further characterize this chaperone as a potential antimalarial drug target.

Stability-based approaches in chemoproteomics

Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies.

Engineering cell-free systems by chemoproteomic-assisted phenotypic screening

Phenotypic screening is a valuable tool to both understand and engineer complex biological systems. We demonstrate the functionality of this approach in the development of cell-free protein synthesis (CFPS) technology. Phenotypic screening identified numerous compounds that enhanced protein production in yeast lysate CFPS reactions. Notably, many of these were competitive ATP kinase inhibitors, with the exploitation of their inherent substrate promiscuity redirecting ATP flux towards heterologous protein expression. Chemoproteomic-guided strain engineering partially phenocopied drug effects, with a 30% increase in protein yield observed upon deletion of the ATP-consuming SSA1 component of the HSP70 chaperone. Moreover, drug-mediated metabolic rewiring coupled with template optimization generated the highest protein yields in yeast CFPS to date using a hitherto less efficient, but more cost-effective glucose energy regeneration system. Our approach highlights the utility of target-agnostic phenotypic screening and target identification to deconvolute cell-lysate complexity, adding to the expanding repertoire of strategies for improving CFPS.

Decoding the Role of the Global Proteome Dynamics for Cellular Thermal Stability

Molecular mechanisms underlying the thermal response of cells remain elusive. On the basis of the recent result that the short-time diffusive dynamics of the Escherichia coli proteome is an excellent indicator of temperature-dependent bacterial metabolism and death, we used neutron scattering (NS) spectroscopy and molecular dynamics (MD) simulations to investigate the sub-nanosecond proteome mobility in psychro-, meso-, and hyperthermophilic bacteria over a wide temperature range. The magnitude of thermal fluctuations, measured by atomic mean square displacements, is similar among all studied bacteria at their respective thermal cell death. Global roto-translational motions turn out to be the main factor distinguishing the bacterial dynamical properties. We ascribe this behavior to the difference in the average proteome net charge, which becomes less negative for increasing bacterial thermal stability. We propose that the chemical-physical properties of the cytoplasm and the global dynamics of the resulting proteome are fine-tuned by evolution to uphold optimal thermal stability conditions.

Structure activity relationship and target prediction for ABX464 analogues in Caenorhabditis elegans

Global challenges with treatment failures and/or widespread resistance in parasitic worms against commercially available anthelmintics lend impetus to the development of new anthelmintics with novel mechanism(s) of action. The free-living nematode Caenorhabditis elegans is an important model organism used for drug discovery, including the screening and structure-activity investigation of new compounds, and target deconvolution. Previously, we conducted a whole-organism phenotypic screen of the 'Pandemic Response Box' (from Medicines for Malaria Venture, MMV) and identified a hit compound, called ABX464, with activity against C. elegans and a related, parasitic nematode, Haemonchus contortus. Here, we tested a series of 44 synthesized analogues to explore the pharmacophore of activity on C. elegans and revealed five compounds whose potency was similar or greater than that of ABX464, but which were not toxic to human hepatoma (HepG2) cells. Subsequently, we employed thermal proteome profiling (TPP), protein structure prediction and an in silico-docking algorithm to predict ABX464-target candidates. Taken together, the findings from this study contribute significantly to the early-stage drug discovery of a new nematocide based on ABX464. Future work is aimed at validating the ABX464-protein interactions identified here, and at assessing ABX464 and associated analogues against a panel of parasitic nematodes, towards developing a new anthelmintic with a mechanism of action that is distinct from any of the compounds currently-available commercially.

Systematic analysis of drug combinations against Gram-positive bacteria

Drug combinations can expand options for antibacterial therapies but have not been systematically tested in Gram-positive species. We profiled ~8,000 combinations of 65 antibacterial drugs against the model species Bacillus subtilis and two prominent pathogens, Staphylococcus aureus and Streptococcus pneumoniae. Thereby, we recapitulated previously known drug interactions, but also identified ten times more novel interactions in the pathogen S. aureus, including 150 synergies. We showed that two synergies were equally effective against multidrug-resistant S. aureus clinical isolates in vitro and in vivo. Interactions were largely species-specific and synergies were distinct from those of Gram-negative species, owing to cell surface and drug uptake differences. We also tested 2,728 combinations of 44 commonly prescribed non-antibiotic drugs with 62 drugs with antibacterial activity against S. aureus and identified numerous antagonisms that might compromise the efficacy of antimicrobial therapies. We identified even more synergies and showed that the anti-aggregant ticagrelor synergized with cationic antibiotics by modifying the surface charge of S. aureus. All data can be browsed in an interactive interface ( https://apps.embl.de/combact/ ).

The potential of cross-linking mass spectrometry in the development of protein-protein interaction modulators

Cross-linking mass spectrometry (XL-MS) can provide a wealth of information on endogenous protein-protein interaction (PPI) networks and protein binding interfaces. These features make XL-MS an attractive tool to support the development of PPI-targeting drugs. Though not yet widely used, applications of XL-MS to drug characterization are beginning to emerge. Here, we compare XL-MS to established structural proteomics methods in drug research, discuss the current state and remaining challenges of XL-MS technology, and provide a perspective on the future role XL-MS can play in drug development, with a particular emphasis on PPI modulators.

D-amino acids signal a stress-dependent run-away response in Vibrio cholerae

To explore favourable niches while avoiding threats, many bacteria use a chemotaxis navigation system. Despite decades of studies on chemotaxis, most signals and sensory proteins are still unknown. Many bacterial species release D-amino acids to the environment; however, their function remains largely unrecognized. Here we reveal that D-arginine and D-lysine are chemotactic repellent signals for the cholera pathogen Vibrio cholerae. These D-amino acids are sensed by a single chemoreceptor MCPDRK co-transcribed with the racemase enzyme that synthesizes them under the control of the stress-response sigma factor RpoS. Structural characterization of this chemoreceptor bound to either D-arginine or D-lysine allowed us to pinpoint the residues defining its specificity. Interestingly, the specificity for these D-amino acids appears to be restricted to those MCPDRK orthologues transcriptionally linked to the racemase. Our results suggest that D-amino acids can shape the biodiversity and structure of complex microbial communities under adverse conditions.

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics

Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.

Quantitative approaches to study phenotypic effects of large-scale genetic perturbations

How microbes interact with their environment and how the complex interplay of their genes enables them to survive and thrive under stress is a fundamental question in microbial system biology, which is also important from a public health perspective. Large-scale studies of gene-gene, gene-drug, and drug-drug interactions have proven to be powerful tools for elucidating gene function and functional modules in the cell. Approaches that systematically quantify phenotypes in libraries of microbial strains with genome-wide genetic perturbations are crucial for progress in this area. Here, we review recent advances in this field, and point out applications to the study of gene-drug interactions. We highlight newly developed techniques for the rapid generation of genome-wide mutant libraries and the high-throughput measurement of more complex phenotypes and other observables, such as cell morphology or thermal stability of the proteome.

Thermal unfolding methods in drug discovery

Thermal unfolding methods, applied in both isolated protein and cell-based settings, are increasingly used to identify and characterize hits during early drug discovery. Technical developments over recent years have facilitated their application in high-throughput approaches, and they now are used more frequently for primary screening. Widespread access to instrumentation and automation, the ability to miniaturize, as well as the capability and capacity to generate the appropriate scale and quality of protein and cell reagents have all played a part in these advances. As the nature of drug targets and approaches to their modulation have evolved, these methods have broadened our ability to provide useful chemical start points. Target proteins without catalytic function, or those that may be difficult to express and purify, are amenable to these methods. Here, we provide a review of the applications of thermal unfolding methods applied in hit finding during early drug discovery.

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.

Targeting the human gut microbiome with small-molecule inhibitors

The human gut microbiome is a complex microbial community that is strongly linked to both host health and disease. However, the detailed molecular mechanisms underlying the effects of these microorganisms on host biology remain largely uncharacterized. The development of non-lethal, small-molecule inhibitors that target specific gut microbial activities enables a powerful but underutilized approach to studying the gut microbiome and a promising therapeutic strategy. In this Review, we will discuss the challenges of studying this microbial community, the historic use of small-molecule inhibitors in microbial ecology, and recent applications of this strategy. We also discuss the evidence suggesting that host-targeted drugs can affect the growth and metabolism of gut microbes. Finally, we address the issues of developing and implementing microbiome-targeted small-molecule inhibitors and define important future directions for this research.

Whole-genome sequencing analysis of two heat-evolved Escherichia coli strains

BACKGROUND

High temperatures cause a suite of problems for cells, including protein unfolding and aggregation; increased membrane fluidity; and changes in DNA supercoiling, RNA stability, transcription and translation. Consequently, enhanced thermotolerance can evolve through an unknown number of genetic mechanisms even in the simple model bacterium Escherichia coli. To date, each E. coli study exploring this question resulted in a different set of mutations. To understand the changes that can arise when an organism evolves to grow at higher temperatures, we sequenced and analyzed two previously described E. coli strains, BM28 and BM28 ΔlysU, that have been laboratory adapted to the highest E. coli growth temperature reported to date.

RESULTS

We found three large deletions in the BM28 and BM28 ΔlysU strains of 123, 15 and 8.5 kb in length and an expansion of IS10 elements. We found that BM28 and BM28 ΔlysU have considerably different genomes, suggesting that the BM28 culture that gave rise to BM28 and BM28 ΔlysU was a mixed population of genetically different cells. Consistent with published findings of high GroESL expression in BM28, we found that BM28 inexplicitly carries the groESL bearing plasmid pOF39 that was maintained simply by high-temperature selection pressure. We identified over 200 smaller insertions, deletions, single nucleotide polymorphisms and other mutations, including changes in master regulators such as the RNA polymerase and the transcriptional termination factor Rho. Importantly, this genome analysis demonstrates that the commonly cited findings that LysU plays a crucial role in thermotolerance and that GroESL hyper-expression is brought about by chromosomal mutations are based on a previous misinterpretation of the genotype of BM28.

CONCLUSIONS

This whole-genome sequencing study describes genetically distinct mechanisms of thermotolerance evolution from those found in other heat-evolved E. coli strains. Studying adaptive laboratory evolution to heat in simple model organisms is important in the context of climate change. It is important to better understand genetic mechanisms of enhancing thermotolerance in bacteria and other organisms, both in terms of optimizing laboratory evolution methods for various organisms and in terms of potential genetic engineering of organisms most at risk or most important to our societies and ecosystems.

Reversible protein assemblies in the proteostasis network in health and disease

While proteins populating their native conformations constitute the functional entities of cells, protein aggregates are traditionally associated with cellular dysfunction, stress and disease. During recent years, it has become clear that large aggregate-like protein condensates formed via liquid-liquid phase separation age into more solid aggregate-like particles that harbor misfolded proteins and are decorated by protein quality control factors. The constituent proteins of the condensates/aggregates are disentangled by protein disaggregation systems mainly based on Hsp70 and AAA ATPase Hsp100 chaperones prior to their handover to refolding and degradation systems. Here, we discuss the functional roles that condensate formation/aggregation and disaggregation play in protein quality control to maintain proteostasis and why it matters for understanding health and disease.

Diffusive Dynamics of Bacterial Proteome as a Proxy of Cell Death

Temperature variations have a big impact on bacterial metabolism and death, yet an exhaustive molecular picture of these processes is still missing. For instance, whether thermal death is determined by the deterioration of the whole or a specific part of the proteome is hotly debated. Here, by monitoring the proteome dynamics of E. coli, we clearly show that only a minor fraction of the proteome unfolds at the cell death. First, we prove that the dynamical state of the E. coli proteome is an excellent proxy for temperature-dependent bacterial metabolism and death. The proteome diffusive dynamics peaks at about the bacterial optimal growth temperature, then a dramatic dynamical slowdown is observed that starts just below the cell's death temperature. Next, we show that this slowdown is caused by the unfolding of just a small fraction of proteins that establish an entangling interprotein network, dominated by hydrophobic interactions, across the cytoplasm. Finally, the deduced progress of the proteome unfolding and its diffusive dynamics are both key to correctly reproduce the E. coli growth rate.

Mass spectrometric insights into protein aggregation

Protein aggregation is now recognized as a generic and significant component of the protein energy landscape. Occurring through a complex and dynamic pathway of structural interconversion, the assembly of misfolded proteins to form soluble oligomers and insoluble aggregates remains a challenging topic of study, both in vitro and in vivo. Since the etiology of numerous human diseases has been associated with protein aggregation, and it has become a field of increasing importance in the biopharmaceutical industry, the biophysical characterization of protein misfolded states and their aggregation mechanisms continues to receive increased attention. Mass spectrometry (MS) has firmly established itself as a powerful analytical tool capable of both detection and characterization of proteins at all levels of structure. Given inherent advantages of biological MS, including high sensitivity, rapid timescales of analysis, and the ability to distinguish individual components from complex mixtures with unrivalled specificity, it has found widespread use in the study of protein aggregation, importantly, where traditional structural biology approaches are often not amenable. The present review aims to provide a brief overview of selected MS-based approaches that can provide a range of biophysical descriptors associated with protein conformation and the aggregation pathway. Recent examples highlight where this technology has provided unique structural and mechanistic understanding of protein aggregation.

Elucidating Protein-Ligand Interactions in Cell Lysates Using High-Throughput Hydrogen-Deuterium Exchange Mass Spectrometry with Integrated Protein Thermal Depletion

Hydrogen-deuterium exchange coupled with mass spectrometry (HDX-MS) is a powerful technique for the characterization of protein-ligand interactions. Currently, there is a growing need for breakthroughs in the application of HDX-MS analysis to protein-ligand interactions in highly complex biological samples such as cell lysates. However, HDX-MS analysis in such systems suffers from extreme spectral complexity as a result of high sample complexity and limited LC separation power due to the traditional use of short LC gradients. Here, we introduced protein thermal depletion (PTD) to reduce protein complexity in E. coli cell lysate for our subzero-temperature long gradient UPLC-HDX-MS platform (PTD-HDX-MS) to facilitate high-throughput analysis of protein-ligand interactions in cell lysates. We spiked bovine carbonic anhydrase II (CaII) and its inhibitor acetazolamide (AZM) into E. coli cell lysate as a model system in our study. We demonstrated that PTD at 60 °C greatly reduces protein complexity in cell lysates, while the AZM-targeted CaII complex remains in solution due to improved thermal stability upon binding. Using both PTD to reduce sample complexity and subzero-temperature long gradient UPLC to boost LC separation power, we successfully elucidated the interaction sites between AZM and CaII in E. coli cell lysate from the high-throughput HDX-MS analysis of thousands of deuterated peptides from hundreds of proteins. Our results highlight the great promise of the PTD-HDX-MS platform for the identification of ligand targets and characterization of protein-ligand interactions in highly complex biological samples such as cell lysates.

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.

Protein-Peptide Turnover Profiling reveals the order of PTM addition and removal during protein maturation

Post-translational modifications (PTMs) regulate various aspects of protein function, including degradation. Mass spectrometric methods relying on pulsed metabolic labeling are popular to quantify turnover rates on a proteome-wide scale. Such data have traditionally been interpreted in the context of protein proteolytic stability. Here, we combine theoretical kinetic modeling with experimental pulsed stable isotope labeling of amino acids in cell culture (pSILAC) for the study of protein phosphorylation. We demonstrate that metabolic labeling combined with PTM-specific enrichment does not measure effects of PTMs on protein stability. Rather, it reveals the relative order of PTM addition and removal along a protein's lifetime-a fundamentally different metric. This is due to interconversion of the measured proteoform species. Using this framework, we identify temporal phosphorylation sites on cell cycle-specific factors and protein complex assembly intermediates. Our results thus allow tying PTMs to the age of the modified proteins.

Thermal proteome profiling: Insights into protein modifications, associations, and functions

Tracking proteins' biophysical characteristics on a proteome-wide scale can provide valuable information on their functions and interactions. Thermal proteome profiling (TPP) is a multiplexed quantitative proteomics approach that measures changes in protein thermal stability-a key biophysical property-across different cellular states. Developed in 2014, as a target-deconvolution assay for drugs and other small molecules, TPP has since evolved to a system-level biochemical omics technique providing insights into context-dependent changes in protein states. In this review, we summarise key advances in the experimental and data analysis pipeline that have aided this transformation and discuss the recent developments and applications of TPP.

Learning deep representations of enzyme thermal adaptation

Temperature is a fundamental environmental factor that shapes the evolution of organisms. Learning thermal determinants of protein sequences in evolution thus has profound significance for basic biology, drug discovery, and protein engineering. Here, we use a data set of over 3 million BRENDA enzymes labeled with optimal growth temperatures (OGTs) of their source organisms to train a deep neural network model (DeepET). The protein-temperature representations learned by DeepET provide a temperature-related statistical summary of protein sequences and capture structural properties that affect thermal stability. For prediction of enzyme optimal catalytic temperatures and protein melting temperatures via a transfer learning approach, our DeepET model outperforms classical regression models trained on rationally designed features and other deep-learning-based representations. DeepET thus holds promise for understanding enzyme thermal adaptation and guiding the engineering of thermostable enzymes.

Network analysis of genome-wide association studies for drug target prioritisation

Over the past decades, genome-wide association studies (GWAS) have led to a dramatic expansion of genetic variants implicated with human traits and diseases. These advances are expected to result in new drug targets but the identification of causal genes and the cell biology underlying human diseases from GWAS remains challenging. Here, we review protein interaction network-based methods to analyse GWAS data. These approaches can rank candidate drug targets at GWAS-associated loci or among interactors of disease genes without direct genetic support. These methods identify the cell biology affected in common across diseases, offering opportunities for drug repurposing, as well as be combined with expression data to identify focal tissues and cell types. Going forward, we expect that these methods will further improve from advances in the characterisation of context specific interaction networks and the joint analysis of rare and common genetic signals.

Molecular Information Theory Meets Protein Folding

We propose an application of molecular information theory to analyze the folding of single domain proteins. We analyze results from various areas of protein science, such as sequence-based potentials, reduced amino acid alphabets, backbone configurational entropy, secondary structure content, residue burial layers, and mutational studies of protein stability changes. We found that the average information contained in the sequences of evolved proteins is very close to the average information needed to specify a fold ∼2.2 ± 0.3 bits/(site·operation). The effective alphabet size in evolved proteins equals the effective number of conformations of a residue in the compact unfolded state at around 5. We calculated an energy-to-information conversion efficiency upon folding of around 50%, lower than the theoretical limit of 70%, but much higher than human-built macroscopic machines. We propose a simple mapping between molecular information theory and energy landscape theory and explore the connections between sequence evolution, configurational entropy, and the energetics of protein folding.

Highly effective identification of drug targets at the proteome level by pH-dependent protein precipitation

Fully understanding the target spaces of drugs is essential for investigating the mechanism of drug action and side effects, as well as for drug discovery and repurposing. In this study, we present an energetics-based approach, termed pH-dependent protein precipitation (pHDPP), to probe the ligand-induced protein stability shift for proteome-wide drug target identification. We demonstrate that pHDPP works for a diverse array of ligands, including a folate derivative, an ATP analog, a CDK inhibitor and an immunosuppressant, enabling highly specific identification of target proteins from total cell lysates. This approach is compared to thermal and solvent-induced denaturation approaches with a pan-kinase inhibitor as the model drug, demonstrating its high sensitivity and high complementarity to other approaches. Dihydroartemisinin (DHA), a dominant derivative of artemisinin to treat malaria, is known to have an extraordinary effect on the treatment of various cancers. However, the anti-tumor mechanisms remain unknown. pHDPP was applied to reveal the target space of DHA and 45 potential target proteins were identified. Pathway analysis indicated that these target proteins were mainly involved in metabolism and apoptosis pathways. Two cancer-related target proteins, ALDH7A1 and HMGB1, were validated by structural simulation and AI-based target prediction methods. And they were further validated to have strong affinity to DHA by using cellular thermal shift assay (CETSA). In summary, pHDPP is a powerful tool to construct the target protein space to reveal the mechanism of drug action and would have broad application in drug discovery studies.

Integrated changes in thermal stability and proteome abundance during altered nutrient states in Escherichia coli and human cells

Altered thermal solubility measurement techniques are emerging as powerful tools to assess ligand binding, post-translational modification, protein-protein interactions, and many other cellular processes that affect protein state under various cellular conditions. Thermal solubility or stability profiling techniques are enabled on a global proteomic scale by employing isobaric tagging reagents that facilitate multiplexing capacity required to measure changes in the proteome across thermal gradients. Key among these is thermal proteomic profiling (TPP), which requires 8-10 isobaric tags per gradient and generation of multiple proteomic datasets to measure different replicates and conditions. Furthermore, using TPP to measure protein thermal stability state across different conditions may also require measurements of differential protein abundance. Here, we use the proteome integral stability alteration (PISA) assay, a higher throughput version of TPP, to measure global changes in protein thermal stability normalized to their protein abundance. We explore the use of this approach to determine changes in protein state between logarithmic and stationary phase Escherichia coli as well as glucose-starved human Hek293T cells. We observed protein intensity-corrected PISA changes in 290 and 350 proteins due to stationary phase transition in E. coli and glucose starvation, respectively. These data reveal several examples of proteins that were not previously associated with nutrient states by abundance alone. These include E. coli proteins such as putative acyl-CoA dehydrogenase (aidB) and chaperedoxin (cnoX) as well as human RAB vesicle trafficking proteins and many others which may indicate their involvement in metabolic diseases such as cancer.

Bacterial retrons encode phage-defending tripartite toxin-antitoxin systems

Retrons are prokaryotic genetic retroelements encoding a reverse transcriptase that produces multi-copy single-stranded DNA1 (msDNA). Despite decades of research on the biosynthesis of msDNA2, the function and physiological roles of retrons have remained unknown. Here we show that Retron-Sen2 of Salmonella enterica serovar Typhimurium encodes an accessory toxin protein, STM14_4640, which we renamed as RcaT. RcaT is neutralized by the reverse transcriptase-msDNA antitoxin complex, and becomes active upon perturbation of msDNA biosynthesis. The reverse transcriptase is required for binding to RcaT, and the msDNA is required for the antitoxin activity. The highly prevalent RcaT-containing retron family constitutes a new type of tripartite DNA-containing toxin-antitoxin system. To understand the physiological roles of such toxin-antitoxin systems, we developed toxin activation-inhibition conjugation (TAC-TIC), a high-throughput reverse genetics approach that identifies the molecular triggers and blockers of toxin-antitoxin systems. By applying TAC-TIC to Retron-Sen2, we identified multiple trigger and blocker proteins of phage origin. We demonstrate that phage-related triggers directly modify the msDNA, thereby activating RcaT and inhibiting bacterial growth. By contrast, prophage proteins circumvent retrons by directly blocking RcaT. Consistently, retron toxin-antitoxin systems act as abortive infection anti-phage defence systems, in line with recent reports3,4. Thus, RcaT retrons are tripartite DNA-regulated toxin-antitoxin systems, which use the reverse transcriptase-msDNA complex both as an antitoxin and as a sensor of phage protein activities.

Expanding the search for small-molecule antibacterials by multidimensional profiling

New techniques for systematic profiling of small-molecule effects can enhance traditional growth inhibition screens for antibiotic discovery and change how we search for new antibacterial agents. Computational models that integrate physicochemical compound properties with their phenotypic and molecular downstream effects can not only predict efficacy of molecules yet to be tested, but also reveal unprecedented insights on compound modes of action (MoAs). The unbiased characterization of compounds that themselves are not growth inhibitory but exhibit diverse MoAs, can expand antibacterial strategies beyond direct inhibition of core essential functions. Early and systematic functional annotation of compound libraries thus paves the way to new models in the selection of lead antimicrobial compounds. In this Review, we discuss how multidimensional small-molecule profiling and the ever-increasing computing power are accelerating the discovery of unconventional antibacterials capable of bypassing resistance and exploiting synergies with established antibacterial treatments and with protective host mechanisms.

Integrated genomics and chemical biology herald an era of sophisticated antibacterial discovery, from defining essential genes to target elucidation

The golden age of antibiotic discovery in the 1940s-1960s saw the development and deployment of many different classes of antibiotics, revolutionizing the field of medicine. Since that time, our ability to discover antibiotics of novel structural classes or mechanisms has not kept pace with the ever-growing threat of antibiotic resistance. Recently, advances at the intersection of genomics and chemical biology have enabled efforts to better define the vulnerabilities of essential gene targets, to develop sophisticated whole-cell chemical screening methods that reveal target biology early, and to elucidate small molecule targets and modes of action more effectively. These new technologies have the potential to expand the chemical diversity of antibiotic candidates, as well as the breadth of targets. We illustrate how the latest tools of genomics and chemical biology are being integrated to better understand pathogen vulnerabilities and antibiotic mechanisms in order to inform a new era of antibiotic discovery.

Small Molecule Arranged Thermal Proximity Coaggregation (smarTPCA)-A Novel Approach to Characterize Protein-Protein Interactions in Living Cells by Similar Isothermal Dose-Responses

Chemical biology and the application of small molecules has proven to be a potent perturbation strategy, especially for the functional elucidation of proteins, their networks, and regulators. In recent years, the cellular thermal shift assay (CETSA) and its proteome-wide extension, thermal proteome profiling (TPP), have proven to be effective tools for identifying interactions of small molecules with their target proteins, as well as off-targets in living cells. Here, we asked the question whether isothermal dose-response (ITDR) CETSA can be exploited to characterize secondary effects downstream of the primary binding event, such as changes in post-translational modifications or protein-protein interactions (PPI). By applying ITDR-CETSA to MAPK14 kinase inhibitor treatment of living HL-60 cells, we found similar dose-responses for the direct inhibitor target and its known interaction partners MAPKAPK2 and MAPKAPK3. Extension of the dose-response similarity comparison to the proteome wide level using TPP with compound concentration range (TPP-CCR) revealed not only the known MAPK14 interaction partners MAPKAPK2 and MAPKAPK3, but also the potentially new intracellular interaction partner MYLK. We are confident that dose-dependent small molecule treatment in combination with ITDR-CETSA or TPP-CCR similarity assessment will not only allow discrimination between primary and secondary effects, but will also provide a novel method to study PPI in living cells without perturbation by protein modification, which we named "small molecule arranged thermal proximity coaggregation" (smarTPCA).

Elucidating the Mechanisms of Action of Antimicrobial Agents

Despite the ever-growing antibiotic resistance crisis, the rate at which new antimicrobials are being discovered and approved for human use has rapidly declined over the past 75 years. A barrier for advancing newly identified antibiotics beyond discovery is elucidating their mechanism(s) of action.

The Fe-S proteome of Escherichia coli: prediction, function and fate

Iron-sulfur (Fe-S) clusters are inorganic ubiquitous and ancient cofactors. Fe-S bound proteins contribute to most cellular processes, including DNA replication and integrity, genetic expression and regulation, metabolism, biosynthesis and most bioenergetics systems. Also, Fe-S proteins hold a great biotechnological potential in metabolite and chemical production, including antibiotics. From classic biophysics and spectroscopy methodologies to recent development in bioinformatics, including structural modeling and chemoproteomics, our capacity to predict and identify Fe-S proteins has spectacularly increased over the recent years. Here, these developments are presented and collectively used to update the composition of Escherichia coli Fe-S proteome, for which we predict 181 occurrences, i.e. 40 more candidates than in our last catalog (Py and Barras, 2010), and equivalent to 4% of its total proteome. Besides, Fe-S clusters can be targeted by redox active compounds or reactive oxygen and nitrosative species, and even be destabilized by contaminant metals. Accordingly, we discuss how cells handle damaged Fe-S proteins, i.e. degradation, recycling or repair.

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.