High throughput discovery of functional protein modifications by Hotspot Thermal Profiling

Monitoring Functional Posttranslational Modifications Using a Data-Driven Proteome Informatic Pipeline

Posttranslational modifications (PTMs) are of significant interest in molecular biomedicine due to their crucial role in signal transduction across various cellular and organismal processes. Characterizing PTMs, distinguishing between functional and inert modifications, quantifying their occupancies, and understanding PTM crosstalk are challenging tasks in any biosystem. Studying each PTM often requires a specific, labor-intensive experimental design. Here, we present a PTM-centric proteome informatic pipeline for predicting relevant PTMs in mass spectrometry-based proteomics data without prior information. Once predicted, these in silico identified PTMs can be incorporated into a refined database search and compared to measured data. As a practical application, we demonstrate how this pipeline can be used to study glycoproteomics in oral squamous cell carcinoma based on the proteome profile of primary tumors. Subsequently, we experimentally identified cellular proteins that are differentially expressed in cells treated with multikinase inhibitors dasatinib and staurosporine using mass spectrometry-based proteomics. Computational enrichment analysis was then employed to determine the potential PTMs of differentially expressed proteins induced by both drugs. Finally, we conducted an additional round of database search with the predicted PTMs. Our pipeline successfully analyzed the enriched PTMs, and detected proteins not identified in the initial search. Our findings support the effectiveness of PTM-centric searching of MS data in proteomics based on computational enrichment analysis, and we propose integrating this approach into future proteomics search engines.

iMetAct: An integrated systematic inference of metabolic activity for dissecting tumor metabolic preference and tumor-immune microenvironment

Metabolic enzymes play a central role in cancer metabolic reprogramming, and their dysregulation creates vulnerabilities that can be exploited for therapy. However, accurately measuring metabolic enzyme activity in a high-throughput manner remains challenging due to the complex, multi-layered regulatory mechanisms involved. Here, we present iMetAct, a framework that integrates metabolic-transcription networks with an information propagation strategy to infer enzyme activity from gene expression data. iMetAct outperforms expression-based methods in predicting metabolite conversion rates by accounting for the effects of post-translational modifications. With iMetAct, we identify clinically significant subtypes of hepatocellular carcinoma with distinct metabolic preferences driven by dysregulated enzymes and metabolic regulators acting at both the transcriptional and non-transcriptional levels. Moreover, applying iMetAct to single-cell RNA sequencing data allows for the exploration of cancer cell metabolism and its interplay with immune regulation in the tumor microenvironment. An accompanying online platform further facilitates tumor metabolic analysis, patient stratification, and immune microenvironment characterization.

Aspirin inhibits proteasomal degradation and promotes α-synuclein aggregate clearance through K63 ubiquitination

Aspirin is a potent lysine acetylation inducer, but its impact on lysine ubiquitination and ubiquitination-directed protein degradation is unclear. Herein, we develop the reversed-pulsed-SILAC strategy to systematically profile protein degradome in response to aspirin. By integrating degradome, acetylome, and ubiquitinome analyses, we show that aspirin impairs proteasome activity to inhibit proteasomal degradation, rather than directly suppressing lysine ubiquitination. Interestingly, aspirin increases lysosomal degradation-implicated K63-linked ubiquitination. Accordingly, using the major pathological protein of Parkinson's disease (PD), α-synuclein (α-syn), as an example of protein aggregates, we find that aspirin is able to reduce α-syn in cultured cells, neurons, and PD model mice with rescued locomotor ability. We further reveal that the α-syn aggregate clearance induced by aspirin is K63-ubiquitination dependent in both cells and PD mice. These findings suggest two complementary mechanisms by which aspirin regulates the degradation of soluble and insoluble proteins, providing insights into its diverse pharmacological effects that can aid in future drug development efforts.

SEC-MX: an approach to systematically study the interplay between protein assembly states and phosphorylation

A protein's molecular interactions and post-translational modifications (PTMs), such as phosphorylation, can be co-dependent and reciprocally co-regulate each other. Although this interplay is central for many biological processes, a systematic method to simultaneously study assembly states and PTMs from the same sample is critically missing. Here, we introduce SEC-MX (Size Exclusion Chromatography fractions MultipleXed), a global quantitative method combining Size Exclusion Chromatography and PTM-enrichment for simultaneous characterization of PTMs and assembly states. SEC-MX enhances throughput, allows phosphopeptide enrichment, and facilitates quantitative differential comparisons between biological conditions. Conducting SEC-MX on HEK293 and HCT116 cells, we generate a proof-of-concept dataset, mapping thousands of phosphopeptides and their assembly states. Our analysis reveals intricate relationships between phosphorylation events and assembly states and generates testable hypotheses for follow-up studies. Overall, we establish SEC-MX as a valuable tool for exploring protein functions and regulation beyond abundance changes.

Genetic code expansion reveals site-specific lactylation in living cells reshapes protein functions

Protein lactylation is an emerging field. To advance the exploration of its biological functions, here we develop a comprehensive workflow that integrates proteomics to identify lactylated sites, genetic code expansion (GCE) for the expression of site-specifically lactylated proteins in living cells, and an integrated functional analysis (IFA) platform to evaluate their biological effects. Using a combined wet-and-dry-lab proteomics strategy, we identify a conserved lactylation at ALDOA-K147, which we hypothesize plays a significant biological role. Expression of this site-specifically lactylated ALDOA in mammalian cells reveals that this modification not only inhibits enzymatic activity but also induces gain-of-function effects. These effects reshaped ALDOA functionality by enhancing protein stability, promoting nuclear translocation, regulating adhesion-related gene expression, altering cell morphology and modulating ALDOA-interacting proteins. Our findings highlight the utility of the GCE-based workflow in establishing causal relationships between specific lactylation events and both target-specific and cell-wide changes, advancing our understanding of protein lactylation's functional impact.

Thermal proteome profiling reveals fructose-1,6-bisphosphate as a phosphate donor to activate phosphoglycerate mutase 1

Deep understanding of sugar metabolite-protein interactions should provide implications on sugar metabolic reprogramming in human physiopathology. Although tremendous efforts have been made for determining individual event, global profiling of such interactome remains challenging. Here we describe thermal proteome profiling of glycolytic metabolite fructose-1,6-bisphosphate (FBP)-interacting proteins. Our results reveal a chemical signaling role of FBP which acts as a phosphate donor to activate phosphoglycerate mutase 1 (PGAM1) and contribute an intrapathway feedback for glycolysis and cell proliferation. At molecular level, FBP donates either C1-O-phosphate or C6-O-phosphate to the catalytic histidine of PGAM1 to form 3-phosphate histidine (3-pHis) modification. Importantly, structure-activity relationship studies facilitate the discovery of PGAM1 orthostatic inhibitors which can potentially restrain cancer cell proliferation. Collectively we have profiled a spectrum of FBP interactome, and discovered a unique covalent signaling function of FBP that supports Warburg effect via histidine phosphorylation which inspires the development of pharmacological tools targeting sugar metabolism.

PTMoreR-enabled cross-species PTM mapping and comparative phosphoproteomics across mammals

To support PTM proteomic analysis and annotation in different species, we developed PTMoreR, a user-friendly tool that considers the surrounding amino acid sequences of PTM sites during BLAST, enabling a motif-centric analysis across species. By controlling sequence window similarity, PTMoreR can map phosphoproteomic results between any two species, perform site-level functional enrichment analysis, and generate kinase-substrate networks. We demonstrate that the majority of real P-sites in mice can be inferred from experimentally derived human P-sites with PTMoreR mapping. Furthermore, the compositions of 129 mammalian phosphoproteomes can also be predicted using PTMoreR. The method also identifies cross-species phosphorylation events that occur on proteins with an increased tendency to respond to the environmental factors. Moreover, the classic kinase motifs can be extracted across mammalian species, offering an evolutionary angle for refining current motifs. PTMoreR supports PTM proteomics in non-human species and facilitates quantitative phosphoproteomic analysis.

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.

Protein Thermal Stability Changes Induced by the Global Methylation Inhibitor 3-Deazaneplanocin A (DZNep)

DZNep (3-deazaneplanocin A) is commonly used to reduce lysine methylation. DZNep inhibits S-adenosyl-l-homocysteine hydrolase (AHCY), preventing the conversion of S-adenosyl-l-homocysteine (SAH) into L-homocysteine. As a result, the SAM-to-SAH ratio decreases, an indicator of the methylation potential within a cell. Many studies have characterized the impact of DZNep on histone lysine methylation or in specific cell or disease contexts, but there has yet to be a study looking at the potential downstream impact of DZNep treatment on proteins other than histones. Recently, protein thermal stability has provided a new dimension for studying the mechanism of action of small-molecule inhibitors. In addition to ligand binding, post-translational modifications and protein-protein interactions impact thermal stability. Here, we sought to characterize the protein thermal stability changes induced by DZNep treatment in HEK293T cells using the Protein Integral Solubility Alteration (PISA) assay. DZNep treatment altered the thermal stability of 135 proteins, with over half previously reported to be methylated at lysine residues. In addition to thermal stability, we identify changes in transcript and protein abundance after DZNep treatment to distinguish between direct and indirect impacts on thermal stability. Nearly one-third of the proteins with altered thermal stability had no changes at the transcript or protein level. Of these thermally altered proteins, CDK6 had a stabilized methylated peptide, while its unmethylated counterpart was unaltered. Multiple methyltransferases were among the proteins with thermal stability alteration, including DNMT1, potentially due to changes in the SAM/SAH levels. This study systematically evaluates DZNep's impact on the transcriptome, the proteome, and the thermal stability of proteins.

Thermal Proteome Profiling Reveals Insight to Antiproliferative and Pro-Apoptotic Effects of Lagunamide A in the Modulation of DNA Damage Repair

Lagunamide A is a biologically active natural product with a yet unidentified molecular mode of action. Cellular studies revealed that lagunamide A is a potent inhibitor of cancer cell proliferation, promotes apoptosis and causes mitochondrial dysfunction. To decipher the cellular mechanism responsible for these effects, we utilized thermal protein profiling (TPP) and identified EYA3 as a stabilized protein in cells upon lagunamide A treatment. EYA3, involved in the DNA damage repair process, was functionally investigated via siRNA based knockdown studies and corresponding effects of lagunamide A on DNA repair were confirmed. Furthermore, we showed that lagunamide A sensitized tumor cells to treatment with the drug doxorubicin highlighting a putative therapeutic strategy.

Profiling Proteins and Phosphorylation Sites During T Cell Activation Using an Integrated Thermal Shift Assay

T cell activation is a complex biological process of naive cells maturing into effector cells. Proteomic and phospho-proteomic approaches have provided critical insights into this process, yet it is not always clear how changes in individual proteins or phosphorylation sites have functional significance. Here, we developed the Phosphorylation Integrated Thermal Shift Assay (PITSA) that combines the measurement of protein or phosphorylation site abundance and thermal stability into a single tandem mass tags experiment and apply this method to study T cell activation. We quantified the abundance and thermal stability of over 7500 proteins and 5000 phosphorylation sites and identified significant differences in chromatin-related, TCR signaling, DNA repair, and proliferative phosphoproteins. PITSA may be applied to a wide range of biological contexts to generate hypotheses as to which proteins or phosphorylation sites are functionally regulated in a given system as well as the mechanisms by which this regulation may occur.

[Recent advances in protein precipitation-based methods for drug-target screening]

Drug targets are biological macromolecules that bind drug molecules in vivo. Therefore, the system-wide identification of drug targets plays a vital role in fully understanding the mechanism of drug action, efficacy, and side effects. The unbiased screening of drug targets may accelerate the process of drug discovery and candidate screening. Mass spectrometry is a key tool for large-scale protein identification and accurate quantification owing to its high acquisition speed, resolution, and sensitivity. Mass spectrometry-based proteomics has been widely used for drug-target screening. It can systematically identify the protein-target landscape of a drug and elucidate drug-protein interactions. Commonly used drug-target characterization methods, such as labeling-based affinity enrichment, require the chemical derivatization of drug molecules, which is not only time-consuming but may also affect the affinity of the drug towards its targets. Furthermore, the spatial effects of the derivatization groups may block interactions between the drug and its targets. Considering the disadvantages of affinity-enrichment methods, strategies that do not require chemical derivatization have received widespread attention. Proteins may undergo denaturation, unfolding, and precipitation under different conditions such as high temperatures, extreme pH, denaturants, and mechanical stress. Binding to small-molecule drugs may alter the folding balance of target proteins. The conformational stability of target proteins can be stabilized by binding with drugs, and protein-drug complexes are more resistant than free proteins to the precipitation induced by different conditions. Based on this mechanism, various large-scale drug-target identification methods using protein precipitation have been developed by combining proteomics and mass spectrometry analysis, including thermal proteome profiling and solvent-, mechanical stress-, and pH-induced protein precipitation. These methods have been successfully applied to the characterization of small-molecule drug targets. In this review, we describe the protein precipitation-based methods used for the high-throughput discovery of drug targets and elucidation of the interactions between drugs and proteins in the past decade. We also summarize the characteristics of each method and discuss their application potential in drug-efficacy evaluation and drug discovery.

[Identification of the binding proteins of organic acid metabolites by matrix thermal shift assay]

Organic acid metabolites exhibit acidic properties. These metabolites serve as intermediates in major carbon metabolic pathways and are involved in several biochemical pathways, including the tricarboxylic acid (TCA) cycle and glycolysis. They also regulate cellular activity and play crucial roles in epigenetics, tumorigenesis, and cellular signal transduction. Knowledge of the binding proteins of organic acid metabolites is crucial for understanding their biological functions. However, identifying the binding proteins of these metabolites has long been a challenging task owing to the transient and weak nature of their interactions. Moreover, traditional methods are unsuitable for the structural modification of the ligands of organic acid metabolites because these metabolites have simple and similar structures. Even minor structural modifications can significantly affect protein interactions. Thermal proteome profiling (TPP) provides a promising avenue for identifying binding proteins without the need for structural modifications. This approach has been successfully applied to the identification of the binding proteins of several metabolites. In this study, we investigated the binding proteins of two TCA cycle intermediates, i.e., succinate and fumarate, and lactate, an end-product of glycolysis, using the matrix thermal shift assay (mTSA) technique. This technique involves combining single-temperature (52 ℃) TPP and dose-response curve analysis to identify ligand-binding proteins with high levels of confidence and determine the binding affinity between ligands and proteins. To this end, HeLa cells were lysed, followed by protein desalting to remove endogenous metabolites from the cell lysates. The desalted cell lysates were treated with fumarate or succinate at final concentrations of 0.004, 0.04, 0.4, and 2 mmol/L in the experimental groups or 2 mmol/L sodium chloride in the control group. Considering that the cellular concentration of lactate can be as high as 2-30 mmol/L, we then applied lactate at final concentrations of 0.2, 1, 5, 10, and 25 mmol/L in the experimental groups or 25 mmol/L sodium chloride in the control group. Using high-sensitivity mass spectrometry coupled with data-independent acquisition (DIA) quantification, we quantified 5870, 5744, and 5816 proteins in succinate, fumarate, and lactate mTSA experiments, respectively. By setting stringent cut-off values (i.e., significance of changes in protein thermal stability (p-value)<0.001 and quality of the dose-response curve fitting (square of Pearson's correlation coefficient, R2)>0.95), multiple binding proteins for these organic acid metabolites from background proteins were confidently determined. Several known binding proteins were identified, notably fumarate hydratase (FH) as a binding protein for fumarate, and α-ketoglutarate-dependent dioxygenase (FTO) as a binding protein for both fumarate and succinate. Additionally, the affinity data for the interactions between these metabolites and their binding proteins were obtained, which closely matched those reported in the literature. Interestingly, ornithine aminotransferase (OAT), which is involved in amino acid biosynthesis, and 3-mercaptopyruvate sulfurtransferase (MPST), which acts as an antioxidant in cells, were identified as lactate-binding proteins. Subsequently, an orthogonal assay technique developed in our laboratory, the solvent-induced precipitation (SIP) technique, was used to validate the mTSA results. SIP identified OAT as the top target candidate, validating the mTSA-based finding that OAT is a novel lactate-binding protein. Although MPST was not identified as a lactate-binding protein by SIP, statistical analysis of MPST in the mTSA experiments with 10 or 25 mmol/L lactate revealed that MPST is a lactate-binding protein with a high level of confidence. Peptide-level empirical Bayes t-tests combined with Fisher's exact test also supported the conclusion that MPST is a lactate-binding protein. Lactate is structurally similar to pyruvate, the known binding protein of MPST. Therefore, assuming that lactate could potentially occupy the binding site of pyruvate on MPST. Overall, the novel binding proteins identified for lactate suggest their potential involvement in amino acid synthesis and redox balance regulation.

Discovery of metal-binding proteins by thermal proteome profiling

Metal-binding proteins (MBPs) have various and important biological roles in all living species and many human diseases are intricately linked to dysfunctional MBPs. Here, we report a chemoproteomic method named 'metal extraction-triggered agitation logged by thermal proteome profiling' (METAL-TPP) to globally profile MBPs in proteomes. The method involves the extraction of metals from MBPs using chelators and monitoring the resulting protein stability changes through thermal proteome profiling. Applying METAL-TPP to the human proteome with a broad-spectrum chelator, EDTA, revealed a group of proteins with reduced thermal stability that contained both previously known MBPs and currently unannotated MBP candidates. Biochemical characterization of one potential target, glutamine-fructose-6-phosphate transaminase 2 (GFPT2), showed that zinc bound the protein, inhibited its enzymatic activity and modulated the hexosamine biosynthesis pathway. METAL-TPP profiling with another chelator, TPEN, uncovered additional MBPs in proteomes. Collectively, this study developed a robust tool for proteomic discovery of MBPs and provides a rich resource for functional studies of metals in cell biology.

PTransIPs: Identification of Phosphorylation Sites Enhanced by Protein PLM Embeddings

Phosphorylation is pivotal in numerous fundamental cellular processes and plays a significant role in the onset and progression of various diseases. The accurate identification of these phosphorylation sites is crucial for unraveling the molecular mechanisms within cells and during viral infections, potentially leading to the discovery of novel therapeutic targets. In this study, we develop PTransIPs, a new deep learning framework for the identification of phosphorylation sites. Independent testing results demonstrate that PTransIPs outperforms existing state-of-the-art (SOTA) methods, achieving AUCs of 0.9232 and 0.9660 for the identification of phosphorylated S/T and Y sites, respectively. PTransIPs contributes from three aspects. 1) PTransIPs is the first to apply protein pre-trained language model (PLM) embeddings to this task. It utilizes ProtTrans and EMBER2 to extract sequence and structure embeddings, respectively, as additional inputs into the model, effectively addressing issues of dataset size and overfitting, thus enhancing model performance; 2) PTransIPs is based on Transformer architecture, optimized through the integration of convolutional neural networks and TIM loss function, providing practical insights for model design and training; 3) The encoding of amino acids in PTransIPs enables it to serve as a universal framework for other peptide bioactivity tasks, with its excellent performance shown in extended experiments of this paper.

IB-DNQ and Rucaparib dual treatment alters cell cycle regulation and DNA repair in triple negative breast cancer cells

Background

Triple negative breast cancer (TNBC), characterized by the lack of three canonical receptors, is unresponsive to commonly used hormonal therapies. One potential TNBC-specific therapeutic target is NQO1, as it is highly expressed in many TNBC patients and lowly expressed in non-cancer tissues. DNA damage induced by NQO1 bioactivatable drugs in combination with Rucaparib-mediated inhibition of PARP1-dependent DNA repair synergistically induces cell death.

Methods

To gain a better understanding of the mechanisms behind this synergistic effect, we used global proteomics, phosphoproteomics, and thermal proteome profiling to analyze changes in protein abundance, phosphorylation and protein thermal stability.

Results

Very few protein abundance changes resulted from single or dual agent treatment; however, protein phosphorylation and thermal stability were impacted. Histone H2AX was among several proteins identified to have increased phosphorylation when cells were treated with the combination of IB-DNQ and Rucaparib, validating that the drugs induced persistent DNA damage. Thermal proteome profiling revealed destabilization of H2AX following combination treatment, potentially a result of the increase in phosphorylation. Kinase substrate enrichment analysis predicted altered activity for kinases involved in DNA repair and cell cycle following dual agent treatment. Further biophysical analysis of these two processes revealed alterations in SWI/SNF complex association and tubulin / p53 interactions.

Conclusions

Our findings that the drugs target DNA repair and cell cycle regulation, canonical cancer treatment targets, in a way that is dependent on increased expression of a protein selectively found to be upregulated in cancers without impacting protein abundance illustrate that multi-omics methodologies are important to gain a deeper understanding of the mechanisms behind treatment induced cancer cell death.

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.

The role of N-terminal phosphorylation of DGK-θ

Diacylglycerol kinases (DGKs) are lipid kinases that mediate the phosphorylation of diacylglycerol (DAG) leading to the production of phosphatidic acid (PtdOH). To examine the role of phosphorylation on DGK-θ, we first identified the phosphorylated sites on endogenous DGK-θ from mouse brain and found four sites: S15, S17, which we refer to phosphomotif-1 sites, and S22 and S26 which we refer to as phosphomotif-2 sites. This study focused on the role of these phosphorylated sites on enzyme activity, membrane binding, thermal stability, and cellular half-life of DGK-θ. After generating a construct devoid of all non-catalytic phosphorylation sites (4A), we also generated other constructs to mimic phosphorylation of these residues by mutating them to glutamate (E). Our data demonstrate that an increase in membrane affinity requires the phosphorylation of all four endogenous sites as the phosphomimetic 4E but not other phosphomimietics. Furthermore, 4E also shows an increase in basal activity as well as an increase in the Syt1-induced activity compared to 4A. It is noteworthy that these phosphorylations had no effect on the thermal stability or cellular half-life of this enzyme. Interestingly, when only one phosphorylation domain (phosphomotif-1 or phosphomotif-2) contained phosphomimetics (S15E/S17E or S22E/S26E), the basal activity was also increased but membrane binding affinity was not increased. Furthermore, when only one residue in each domain mimicked an endogenous phosphorylated serine (S15E/S22E or S17E/S26E), the Syt1-induced activity as well as membrane binding affinity decreased relative to 4A. These results indicate that these endogenous phosphorylation sites contribute differentially to membrane binding and enzymatic activity.

Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach

The worldwide appearance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated significant concern and posed a considerable challenge to global health. Phosphorylation is a common post-translational modification that affects many vital cellular functions and is closely associated with SARS-CoV-2 infection. Precise identification of phosphorylation sites could provide more in-depth insight into the processes underlying SARS-CoV-2 infection and help alleviate the continuing COVID-19 crisis. Currently, available computational tools for predicting these sites lack accuracy and effectiveness. In this study, we designed an innovative meta-learning model, Meta-Learning for Serine/Threonine Phosphorylation (MeL-STPhos), to precisely identify protein phosphorylation sites. We initially performed a comprehensive assessment of 29 unique sequence-derived features, establishing prediction models for each using 14 renowned machine learning methods, ranging from traditional classifiers to advanced deep learning algorithms. We then selected the most effective model for each feature by integrating the predicted values. Rigorous feature selection strategies were employed to identify the optimal base models and classifier(s) for each cell-specific dataset. To the best of our knowledge, this is the first study to report two cell-specific models and a generic model for phosphorylation site prediction by utilizing an extensive range of sequence-derived features and machine learning algorithms. Extensive cross-validation and independent testing revealed that MeL-STPhos surpasses existing state-of-the-art tools for phosphorylation site prediction. We also developed a publicly accessible platform at https://balalab-skku.org/MeL-STPhos. We believe that MeL-STPhos will serve as a valuable tool for accelerating the discovery of serine/threonine phosphorylation sites and elucidating their role in post-translational regulation.

Homologous Pairs of Low and High Temperature Originating Proteins Spanning the Known Prokaryotic Universe

Stability of proteins at high temperature has been a topic of interest for many years, as this attribute is favourable for applications ranging from therapeutics to industrial chemical manufacturing. Our current understanding and methods for designing high-temperature stability into target proteins are inadequate. To drive innovation in this space, we have curated a large dataset, learn2thermDB, of protein-temperature examples, totalling 24 million instances, and paired proteins across temperatures based on homology, yielding 69 million protein pairs - orders of magnitude larger than the current largest. This important step of pairing allows for study of high-temperature stability in a sequence-dependent manner in the big data era. The data pipeline is parameterized and open, allowing it to be tuned by downstream users. We further show that the data contains signal for deep learning. This data offers a new doorway towards thermal stability design models.

Scaled-Down Thermal Profiling and Coaggregation Analysis of the Proteome for Drug Target and Protein Interaction Analysis

Thermal proteome profiling (TPP), an experimental technique combining the cellular thermal shift assay (CETSA) with quantitative protein mass spectrometry (MS), identifies interactions of drugs and chemicals with endogenous proteins. Thermal proximity coaggregation (TPCA) profiling extended TPP to study the intracellular dynamics of protein complexes. In TPP and TPCA, samples are subjected to multiple denaturing temperatures, each requiring over 100 μg of proteins, which restricts their applications for rare cells and precious clinical samples. We developed a workflow termed STASIS (scaled-down thermal profiling and coaggregation analysis with SISPROT) that scales down the required protein to as low as 1 μg per temperature. This is achieved by heating and centrifugation using the same PCR tube, processing samples with the SISPROT technology (simple and integrated spintip-based proteomics technology), and tip-based manual fractionation of TMT-labeled peptides. We evaluate the STASIS workflow with starting protein quantities of 10, 5, and 1 μg per temperature prior to heating, identifying between 4000 and 5000 proteins with 6 h of acquisition time. Importantly, we observed a high correlation in the Tm of proteins with minimal difference in TPCA performance for predicting protein complexes. Moreover, STASIS could identify the targets of methotrexate and panobinostat with high precision with 1 μg of proteins per temperature. In conclusion, STASIS is a robust cost-effective technique for target deconvolution and extended TPCA to rare primary cells and precious clinical samples for the analysis of protein complexes.

Obtaining Functional Proteomics Insights From Thermal Proteome Profiling Through Optimized Melt Shift Calculation and Statistical Analysis With InflectSSP

Thermal proteome profiling (TPP) is an invaluable tool for functional proteomics studies that has been shown to discover changes associated with protein-ligand, protein-protein, and protein-RNA interaction dynamics along with changes in protein stability resulting from cellular signaling. The increasing number of reports employing this assay has not been met concomitantly with new approaches leading to advancements in the quality and sensitivity of the corresponding data analysis. The gap between data acquisition and data analysis tools is important to fill as TPP findings have reported subtle melt shift changes related to signaling events such as protein posttranslational modifications. In this study, we have improved the Inflect data analysis pipeline (now referred to as InflectSSP, available at https://CRAN.R-project.org/package=InflectSSP) to increase the sensitivity of detection for both large and subtle changes in the proteome as measured by TPP. Specifically, InflectSSP now has integrated statistical and bioinformatic functions to improve objective functional proteomics findings from the quantitative results obtained from TPP studies through increasing both the sensitivity and specificity of the data analysis pipeline. InflectSSP incorporates calculation of a "melt coefficient" into the pipeline with production of average melt curves for biological replicate studies to aid in identification of proteins with significant melts. To benchmark InflectSSP, we have reanalyzed two previously reported datasets to demonstrate the performance of our publicly available R-based program for TPP data analysis. We report new findings following temporal treatment of human cells with the small molecule thapsigargin that induces the unfolded protein response as a consequence of inhibition of sarcoplasmic/endoplasmic reticulum calcium ATPase 2A. InflectSSP analysis of our unfolded protein response study revealed highly reproducible and statistically significant target engagement over a time course of treatment while simultaneously providing new insights into the possible mechanisms of action of the small molecule thapsigargin.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.

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.

IPs-GRUAtt: An attention-based bidirectional gated recurrent unit network for predicting phosphorylation sites of SARS-CoV-2 infection

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has generated tremendous concern and poses a serious threat to international public health. Phosphorylation is a common post-translational modification affecting many essential cellular processes and is inextricably linked to SARS-CoV-2 infection. Hence, accurate identification of phosphorylation sites will be helpful to understand the mechanisms of SARS-CoV-2 infection and mitigate the ongoing COVID-19 pandemic. In the present study, an attention-based bidirectional gated recurrent unit network, called IPs-GRUAtt, was proposed to identify phosphorylation sites in SARS-CoV-2-infected host cells. Comparative results demonstrated that IPs-GRUAtt surpassed both state-of-the-art machine-learning methods and existing models for identifying phosphorylation sites. Moreover, the attention mechanism made IPs-GRUAtt able to extract the key features from protein sequences. These results demonstrated that the IPs-GRUAtt is a powerful tool for identifying phosphorylation sites. For facilitating its academic use, a freely available online web server for IPs-GRUAtt is provided at http://cbcb.cdutcm.edu.cn/phosphory/.

Decoding protein methylation function with thermal stability analysis

Protein methylation is an important modification beyond epigenetics. However, systems analyses of protein methylation lag behind compared to other modifications. Recently, thermal stability analyses have been developed which provide a proxy of a protein functional status. Here, we show that molecular and functional events closely linked to protein methylation can be revealed by the analysis of thermal stability. Using mouse embryonic stem cells as a model, we show that Prmt5 regulates mRNA binding proteins that are enriched in intrinsically disordered regions and involved in liquid-liquid phase separation mechanisms, including the formation of stress granules. Moreover, we reveal a non-canonical function of Ezh2 in mitotic chromosomes and the perichromosomal layer, and identify Mki67 as a putative Ezh2 substrate. Our approach provides an opportunity to systematically explore protein methylation function and represents a rich resource for understanding its role in pluripotency.

Liquid Biopsy Snapshots of Key Phosphoproteomic Pathways in Lung Cancer Patients for Diagnosis and Therapy Monitoring

Phosphorylation is a post-translational modification in proteins that changes protein conformation and activity for regulating signal transduction pathways. This mechanism is frequently impaired in lung cancer, resulting in permanently active constitutive phosphorylation to initiate tumor growth and/or reactivate pathways in response to therapy. We developed a multiplexed phosphoprotein analyzer chip (MPAC) that enables rapid (detection time: 5 min) and sensitive (LOD: 2 pg/μL) detection of protein phosphorylation and presents phosphoproteomic profiling of major phosphorylation pathways in lung cancer. We monitored phosphorylated receptors and downstream proteins involved in mitogen-activated protein kinase (MAPK) and PI3K/AKT/mTOR pathways in lung cancer cell line models and patient-derived extracellular vesicles (EV). Using kinase inhibitor drugs in cell line models, we found that the drug can inhibit the phosphorylation and/or activation of the kinase pathway. We then generated a phosphorylation heatmap by EV phosphoproteomic profiling of plasma samples isolated from 36 lung cancer patients and 8 noncancer individuals. The heatmap showed a clear difference between the noncancer and cancer samples and identify the specific proteins that are activated in the cancer samples. Our data also showed that MPAC could monitor immunotherapy responses by assessment of the phosphorylation states of the proteins, particularly for PD-L1. Finally, with a longitudinal study, we found that the phosphorylation levels of the proteins were indicative of a positive response to therapy. We believe that this study will lead to personalized treatment by providing a better understanding of the active and resistant pathways and will provide a tool for selecting combined and targeted therapies for precision medicine.

Orchestration of Mitochondrial Function and Remodeling by Post-Translational Modifications Provide Insight into Mechanisms of Viral Infection

The regulation of mitochondria structure and function is at the core of numerous viral infections. Acting in support of the host or of virus replication, mitochondria regulation facilitates control of energy metabolism, apoptosis, and immune signaling. Accumulating studies have pointed to post-translational modification (PTM) of mitochondrial proteins as a critical component of such regulatory mechanisms. Mitochondrial PTMs have been implicated in the pathology of several diseases and emerging evidence is starting to highlight essential roles in the context of viral infections. Here, we provide an overview of the growing arsenal of PTMs decorating mitochondrial proteins and their possible contribution to the infection-induced modulation of bioenergetics, apoptosis, and immune responses. We further consider links between PTM changes and mitochondrial structure remodeling, as well as the enzymatic and non-enzymatic mechanisms underlying mitochondrial PTM regulation. Finally, we highlight some of the methods, including mass spectrometry-based analyses, available for the identification, prioritization, and mechanistic interrogation of PTMs.

Proteomic discovery of chemical probes that perturb protein complexes in human cells

Most human proteins lack chemical probes, and several large-scale and generalizable small-molecule binding assays have been introduced to address this problem. How compounds discovered in such "binding-first" assays affect protein function, nonetheless, often remains unclear. Here, we describe a "function-first" proteomic strategy that uses size exclusion chromatography (SEC) to assess the global impact of electrophilic compounds on protein complexes in human cells. Integrating the SEC data with cysteine-directed activity-based protein profiling identifies changes in protein-protein interactions that are caused by site-specific liganding events, including the stereoselective engagement of cysteines in PSME1 and SF3B1 that disrupt the PA28 proteasome regulatory complex and stabilize a dynamic state of the spliceosome, respectively. Our findings thus show how multidimensional proteomic analysis of focused libraries of electrophilic compounds can expedite the discovery of chemical probes with site-specific functional effects on protein complexes in human cells.

A basic phosphoproteomic-DIA workflow integrating precise quantification of phosphosites in systems biology

Phosphorylation is one of the most important post-translational modifications (PTMs) of proteins, governing critical protein functions. Most human proteins have been shown to undergo phosphorylation, and phosphoproteomic studies have been widely applied due to recent advancements in high-resolution mass spectrometry technology. Although the experimental workflow for phosphoproteomics has been well-established, it would be useful to optimize and summarize a detailed, feasible protocol that combines phosphoproteomics and data-independent acquisition (DIA), along with follow-up data analysis procedures due to the recent instrumental and bioinformatic advances in measuring and understanding tens of thousands of site-specific phosphorylation events in a single experiment. Here, we describe an optimized Phos-DIA protocol, from sample preparation to bioinformatic analysis, along with practical considerations and experimental configurations for each step. The protocol is designed to be robust and applicable for both small-scale phosphoproteomic analysis and large-scale quantification of hundreds of samples for studies in systems biology and systems medicine.

Investigation of cellular response to the HSP90 inhibition in human cells through thermal proteome profiling

Heat shock proteins are chaperones and they are responsible for protein folding in cells. HSP90 is one of the most important chaperones in human cells, and its inhibition is promising for cancer therapy. However, despite the development of multiple HSP90 inhibitors, none of them has been approved for disease treatment due to unexpected cellular toxicity and side-effects. Hence, a more comprehensive investigation of cellular response to HSP90 inhibitors can aid in a better understanding of the molecular mechanisms of the cytotoxicity and side effects of these inhibitors. The thermal stability shifts of proteins, which represent protein structure and interaction alterations, can provide valuable information complementary to the results obtained from commonly used abundance-based proteomics analysis. Here, we systematically investigated cell response to different HSP90 inhibitors through global quantification of protein thermal stability changes using thermal proteome profiling, together with measurement of protein abundance changes. Besides the targets and potential off-targets of the drugs, proteins with significant thermal stability changes under the HSP90 inhibition are found to be involved in cell stress responses and the translation process. Moreover, proteins with thermal stability shifts under the inhibition are upstream of those with altered expression. These findings indicate that the HSP90 inhibition perturbs cell transcription and translation processes. The current study provides a different perspective for achieving a better understanding of cellular response to the chaperone inhibition.

LKB1-Dependent Regulation of TPI1 Creates a Divergent Metabolic Liability between Human and Mouse Lung Adenocarcinoma

KRAS is the most frequently mutated oncogene in human lung adenocarcinomas (hLUAD), and activating mutations frequently co-occur with loss-of-function mutations in TP53 or STK11/LKB1. However, mutation of all three genes is rarely observed in hLUAD, even though engineered comutation is highly aggressive in mouse lung adenocarcinoma (mLUAD). Here, we provide a mechanistic explanation for this difference by uncovering an evolutionary divergence in the regulation of triosephosphate isomerase (TPI1). In hLUAD, TPI1 activity is regulated via phosphorylation at Ser21 by the salt inducible kinases (SIK) in an LKB1-dependent manner, modulating flux between the completion of glycolysis and production of glycerol lipids. In mice, Ser21 of TPI1 is a Cys residue that can be oxidized to alter TPI1 activity without a need for SIKs or LKB1. Our findings suggest this metabolic flexibility is critical in rapidly growing cells with KRAS and TP53 mutations, explaining why the loss of LKB1 creates a liability in these tumors.

SIGNIFICANCE

Utilizing phosphoproteomics and metabolomics in genetically engineered human cell lines and genetically engineered mouse models (GEMM), we uncover an evolutionary divergence in metabolic regulation within a clinically relevant genotype of human LUAD with therapeutic implications. Our data provide a cautionary example of the limits of GEMMs as tools to study human diseases such as cancers. This article is highlighted in the In This Issue feature, p. 799.

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.

Recent advances in kinase signaling network profiling by mass spectrometry

Mass spectrometry-based phosphoproteomics is currently the leading methodology for the study of global kinase signaling. The scientific community is continuously releasing technological improvements for sensitive and fast identification of phosphopeptides, and their accurate quantification. To interpret large-scale phosphoproteomics data, numerous bioinformatic resources are available that help understanding kinase network functional role in biological systems upon perturbation. Some of these resources are databases of phosphorylation sites, protein kinases and phosphatases; others are bioinformatic algorithms to infer kinase activity, predict phosphosite functional relevance and visualize kinase signaling networks. In this review, we present the latest experimental and bioinformatic tools to profile protein kinase signaling networks and provide examples of their application in biomedicine.

Computational systems approach towards phosphoproteomics and their downstream regulation

Protein phosphorylation plays an essential role in modulating cell signalling and its downstream transcriptional and translational regulations. Until recently, protein phosphorylation has been studied mostly using low-throughput biochemical assays. The advancement of mass spectrometry (MS)-based phosphoproteomics transformed the field by enabling measurement of proteome-wide phosphorylation events, where tens of thousands of phosphosites are routinely identified and quantified in an experiment. This has brought a significant challenge in analysing large-scale phosphoproteomic data, making computational methods and systems approaches integral parts of phosphoproteomics. Previous works have primarily focused on reviewing the experimental techniques in MS-based phosphoproteomics, yet a systematic survey of the computational landscape in this field is still missing. Here, we review computational methods and tools, and systems approaches that have been developed for phosphoproteomics data analysis. We categorise them into four aspects including data processing, functional analysis, phosphoproteome annotation and their integration with other omics, and in each aspect, we discuss the key methods and example studies. Lastly, we highlight some of the potential research directions on which future work would make a significant contribution to this fast-growing field. We hope this review provides a useful snapshot of the field of computational systems phosphoproteomics and stimulates new research that drives future development.

Multi-comparative Thermal Proteome Profiling Uncovers New O-GlcNAc Proteins in a System-wide Method

Among diverse protein post-translational modifications, O-GlcNAcylation, a simple but essential monosaccharide modification, plays crucial roles in cellular processes and is closely related to various diseases. Despite its ubiquity in cells, properties of low stoichiometry and reversibility are hard nuts to crack in system-wide research of O-GlcNAc. Herein, we developed a novel method employing multi-comparative thermal proteome profiling for O-GlcNAc transferase (OGT) substrate discovery. Melting curves of proteins under different treatments were profiled and compared with high reproducibility and consistency. Consequently, proteins with significantly shifted stabilities caused by OGT and uridine-5'-diphosphate N-acetylglucosamine were screened out from which new O-GlcNAcylated proteins were uncovered.

Coordinate-Dependent Drift-Diffusion Reveals the Kinetic Intermediate Traps of Top7-Based Proteins

The computer-designed Top7 served as a scaffold to produce immunoreactive proteins by grafting of the 2F5 HIV-1 antibody epitope (Top7-2F5) followed by biotinylation (Top7-2F5-biotin). The resulting nonimmunoglobulin affinity proteins were effective in inducing and detecting the HIV-1 antibody. However, the grafted Top7-2F5 design led to protein aggregation, as opposed to the soluble biotinylated Top7-2F5-biotin. The structure-based model predicted that the thermodynamic cooperativity of Top7 increases after grafting and biotin-labeling, reducing their intermediate state populations. In this work, the folding kinetic traps that might contribute to the aggregation propensity are investigated by the diffusion theory. Since the engineered proteins have similar sequence and structural homology, they served as protein models to study the kinetic intermediate traps that were uncovered by characterizing the position-dependent drift-velocity (v(Q)) and the diffusion (D(Q)) coefficients. These coordinate-dependent coefficients were taken into account to obtain the folding and transition path times over the free energy transition states containing the intermediate kinetic traps. This analysis may be useful to predict the aggregated kinetic traps of scaffold-epitope proteins that might compose novel diagnostic and therapeutic platforms.

Identification of 3-Phenylquinoline Derivative PQ1 as an Antagonist of p53 Transcriptional Activity

Transcription factor p53 regulates cellular responses to environmental perturbations via the transcriptional activation of downstream target genes. Inappropriate p53 activation can trigger abnormal cellular responses, therefore leading to acute or chronic tissue damage, human developmental syndromes, and neurodegenerative diseases. Antagonists of p53 transcriptional activity provide prospective therapeutic applications and molecular probes. In this article, we identified five 3-phenylquinoline derivatives as potential p53 inhibitors through screening a chemical library consisting of 120 compounds, in which PQ1 was the most active compound. PQ1 had no effect on p53 protein levels and decreased the expression of p53 target gene p21. PQ1 thermally stabilizes the wild-type p53 protein. Further, transcriptomics confirmed that PQ1 exposure generated a similar regulatory effect to transcription profiles with a reported p53 transcriptional inhibitor pifithrin-α. However, compared to pifithrin-α, PQ1 increased the sensitivity of SW480 cells to 5FU. Taken together, PQ1 was a novel antagonist of p53 transcriptional activity. We propose that PQ1 could be developed as a chemical tool to pinpoint the physiological functions of p53 and a novel lead compound for targeting dysfunctional p53 activation.

Revving an Engine of Human Metabolism: Activity Enhancement of Triosephosphate Isomerase via Hemi-Phosphorylation

Triosephosphate isomerase (TPI) performs the 5th step in glycolysis, operates near the limit of diffusion, and is involved in "moonlighting" functions. Its dimer was found singly phosphorylated at Ser20 (pSer20) in human cells, with this post-translational modification (PTM) showing context-dependent stoichiometry and loss under oxidative stress. We generated synthetic pSer20 proteoforms using cell-free protein synthesis that showed enhanced TPI activity by 4-fold relative to unmodified TPI. Molecular dynamics simulations show that the phosphorylation enables a channel to form that shuttles substrate into the active site. Refolding, kinetic, and crystallographic analyses of point mutants including S20E/G/Q indicate that hetero-dimerization and subunit asymmetry are key features of TPI. Moreover, characterization of an endogenous human TPI tetramer also implicates tetramerization in enzymatic regulation. S20 is highly conserved across eukaryotic TPI, yet most prokaryotes contain E/D at this site, suggesting that phosphorylation of human TPI evolved a new switch to optionally boost an already fast enzyme. Overall, complete characterization of TPI shows how endogenous proteoform discovery can prioritize functional versus bystander PTMs.

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.

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.

Proteotype coevolution and quantitative diversity across 11 mammalian species

Evolutionary profiling has been largely limited to the nucleotide level. Using consistent proteomic methods, we quantified proteomic and phosphoproteomic layers in fibroblasts from 11 common mammalian species, with transcriptomes as reference. Covariation analysis indicates that transcript and protein expression levels and variabilities across mammals remarkably follow functional role, with extracellular matrix-associated expression being the most variable, demonstrating strong transcriptome-proteome coevolution. The biological variability of gene expression is universal at both interindividual and interspecies scales but to a different extent. RNA metabolic processes particularly show higher interspecies versus interindividual variation. Our results further indicate that while the ubiquitin-proteasome system is strongly conserved in mammals, lysosome-mediated protein degradation exhibits remarkable variation between mammalian lineages. In addition, the phosphosite profiles reveal a phosphorylation coevolution network independent of protein abundance.

Cyclic immonium ion of lactyllysine reveals widespread lactylation in the human proteome

Lactylation was initially discovered on human histones. Given its nascence, its occurrence on nonhistone proteins and downstream functional consequences remain elusive. Here we report a cyclic immonium ion of lactyllysine formed during tandem mass spectrometry that enables confident protein lactylation assignment. We validated the sensitivity and specificity of this ion for lactylation through affinity-enriched lactylproteome analysis and large-scale informatic assessment of nonlactylated spectral libraries. With this diagnostic ion-based strategy, we confidently determined new lactylation, unveiling a wide landscape beyond histones from not only the enriched lactylproteome but also existing unenriched human proteome resources. Specifically, by mining the public human Meltome Atlas, we found that lactylation is common on glycolytic enzymes and conserved on ALDOA. We also discovered prevalent lactylation on DHRS7 in the draft of the human tissue proteome. We partially demonstrated the functional importance of lactylation: site-specific engineering of lactylation into ALDOA caused enzyme inhibition, suggesting a lactylation-dependent feedback loop in glycolysis.

Biotin-painted proteins have thermodynamic stability switched by kinetic folding routes

Biotin-labeled proteins are widely used as tools to study protein-protein interactions and proximity in living cells. Proteomic methods broadly employ proximity-labeling technologies based on protein biotinylation in order to investigate the transient encounters of biomolecules in subcellular compartments. Biotinylation is a post-translation modification in which the biotin molecule is attached to lysine or tyrosine residues. So far, biotin-based technologies proved to be effective instruments as affinity and proximity tags. However, the influence of biotinylation on aspects such as folding, binding, mobility, thermodynamic stability, and kinetics needs to be investigated. Here, we selected two proteins [biotin carboxyl carrier protein (BCCP) and FKBP3] to test the influence of biotinylation on thermodynamic and kinetic properties. Apo (without biotin) and holo (biotinylated) protein structures were used separately to generate all-atom structure-based model simulations in a wide range of temperatures. Holo BCCP contains one biotinylation site, and FKBP3 was modeled with up to 23 biotinylated lysines. The two proteins had their estimated thermodynamic stability changed by altering their energy landscape. In all cases, after comparison between the apo and holo simulations, differences were observed on the free-energy profiles and folding routes. Energetic barriers were altered with the density of states clearly showing changes in the transition state. This study suggests that analysis of large-scale datasets of biotinylation-based proximity experiments might consider possible alterations in thermostability and folding mechanisms imposed by the attached biotins.

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).

Force-dependent intercellular adhesion strengthening underlies asymmetric adherens junction contraction

Tissue morphogenesis arises from the culmination of changes in cell-cell junction length. Mechanochemical signaling in the form of RhoA underlies these ratcheted contractions, which occur asymmetrically. The underlying mechanisms of asymmetry remain unknown. We use optogenetically controlled RhoA in model epithelia together with biophysical modeling to uncover the mechanism lending to asymmetric vertex motion. Using optogenetic and pharmacological approaches, we find that both local and global RhoA activation can drive asymmetric junction contraction in the absence of tissue-scale patterning. We find that standard vertex models with homogeneous junction properties are insufficient to recapitulate the observed junction dynamics. Furthermore, these experiments reveal a local coupling of RhoA activation with E-cadherin accumulation. This motivates a coupling of RhoA-mediated increases in tension and E-cadherin-mediated adhesion strengthening. We then demonstrate that incorporating this force-sensitive adhesion strengthening into a continuum model is successful in capturing the observed junction dynamics. Thus, we find that a force-dependent intercellular "clutch" at tricellular vertices stabilizes vertex motion under increasing tension and is sufficient to generate asymmetries in junction contraction.

Analysis of human Tribbles 2 (TRIB2) pseudokinase

Human Tribbles 2 (TRIB2) is a cancer-associated pseudokinase with a broad human protein interactome, including the well-studied AKT, C/EBPα and MAPK modules. Several lines of evidence indicate that human TRIB2 promotes cell survival and drug-resistance in solid tumors and blood cancers and is therefore of interest as a potential therapeutic target, although its physiological functions remain relatively poorly understood. The unique TRIB2 pseudokinase domain lacks the canonical 'DFG' motif, and subsequently possesses very low affinity for ATP in both the presence and absence of metal ions. However, TRIB2 also contains a unique cysteine-rich αC-helix, which interacts with a conserved peptide motif in its own carboxyl-terminal tail. This regulatory flanking region drives regulated interactions with distinct E3 ubiquitin ligases that serve to control the stability and turnover of TRIB2 client proteins. TRIB2 is also a low-affinity target of several known small-molecule protein kinase inhibitors, which were originally identified using purified recombinant TRIB2 proteins and a thermal shift assay. In this chapter, we discuss laboratory-based procedures for purification, stabilization and analysis of human TRIB2, including screening procedures that can be used for the identification of both reversible and covalent small molecule ligands.

PACTS-Assisted Thermal Proteome Profiling for Use in Identifying Peptide-Interacting Proteins

Bioactive peptides play important roles in various biological processes. However, the traditional methods for profiling the peptide-interacting proteins require modifications to the peptide molecules, often leading to false identifications. We found that the interaction between peptide ligands and protein receptors induced significant changes in the abundance of the interacting proteins, which is a signature indicating the interaction and providing complementary information for use in the classical thermal proteome profiling (TPP) technique. Herein, we developed a novel Peptide-ligand-induced Abundance Change of proTeinS (PACTS)-assisted TPP strategy for the identification of peptide-interacting proteins based on the peptide-ligand-induced change in protein abundance. The utility and efficacy of this approach were demonstrated by the identification of the interaction of the protein 3-phosphoinositide-dependent protein kinase 1 (PDPK1) and PDPK1-interacting fragment (PIF) pair and by large-scale profiling of the interacting proteins of PIF. The PACTS-assisted TPP approach was applied to describe the interactome of amyloid beta (Aβ) 1-42 in THP-1 cells and resulted in the identification of 103 interacting proteins. Validation experiments indicated that Aβ1-42 interacted directly with fatty acid synthase and inhibited its enzymatic activity, providing insights into fatty acid metabolic disorders in Alzheimer's disease (AD). Overall, PACTS-assisted TPP is an efficient approach, and the newly identified Aβ-interacting proteins provide rich resources for the research on AD.

Improved Stability of Human CGI-58 Induced by Phosphomimetic S237E Mutation

In lipolysis, the activating function of CGI-58 is regulated by its interaction with perilipin 1 (PLIN1) localized on the lipid droplet (LD), and its release is controlled by phosphorylation. Once lipolysis is stimulated by catecholamines, protein kinase A (PKA)-mediated phosphorylation enables the dissociation of the CGI-58/PLIN1 complex, thereby recruiting adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL) to initiate fatty acid release. It has been shown that mouse CGI-58 mutant S239E, which mimics the phosphorylation of this residue, is able to dissociate from the CGI-58/PLIN1 complex and activate ATGL. Here, we analyze the stabilizing effect on human CGI-58 of a triple tryptophan to alanine mutant (3WA) on the LD-binding motif, as well as a quadruple mutant in which the phosphomimetic S237E substitution was introduced to the 3WA construct (3WA/S237E). We found that tryptophan residues promote wild-type (WT) protein aggregation in solution since their substitution for alanine residues favors the presence of the monomer. Our experimental data showed increased thermal stability and solubility of 3WA/S237E protein compared to the 3WA mutant. Moreover, the 3WA/S237E protein showed proper folding and a functional binding site for oleoyl-CoA. The analysis of a bioinformatic three-dimensional (3D) model suggests an intramolecular interaction between the phosphomimetic glutamic acid and a residue of the α/β hydrolase core. This could explain the increased solubility and stability observed in the 3WA/S237E mutant and evidences the possible role of serine 237 phosphorylation.