Multiple post-translational modifications in hepatocyte nuclear factor 4α

Redox-active cysteine, a highly reactive sulfhydryl, is one of the major targets of ROS. Formation of disulfide bonds and other oxidative derivatives of cysteine including sulfenic, sulfinic, and sulfonic acids, regulates the biological function of various proteins. We identified novel low-abundant cysteine modifications in cellular GAPDH purified on 2-dimensional gel electrophoresis (2D-PAGE) by employing selectively excluded mass screening analysis for nano ultraperformance liquid chromatography-electrospray-quadrupole-time of flight tandem mass spectrometry, in conjunction with MODi and MODmap algorithm. We observed unexpected mass shifts (Δm=-16, -34, +64, +87, and +103 Da) at redox-active cysteine residue in cellular GAPDH purified on 2D-PAGE, in oxidized NDP kinase A, peroxiredoxin 6, and in various mitochondrial proteins. Mass differences of -16, -34, and +64 Da are presumed to reflect the conversion of cysteine to serine, dehydroalanine (DHA), and Cys-SO2-SH respectively. To determine the plausible pathways to the formation of these products, we prepared model compounds and examined the hydrolysis and hydration of thiosulfonate (Cys-S-SO2-Cys) either to DHA (Δm=-34 Da) or serine along with Cys-SO2-SH (Δm=+64 Da). We also detected acrylamide adducts of sulfenic and sulfinic acids (+87 and +103 Da). These findings suggest that oxidations take place at redox-active cysteine residues in cellular proteins, with the formation of thiosulfonate, Cys-SO2-SH, and DHA, and conversion of cysteine to serine, in addition to sulfenic, sulfinic and sulfonic acids of reactive cysteine.

While tandem mass spectrometry can detect post-translational modifications (PTM) at the proteome scale, reported PTM sites are often incomplete and include false positives. Computational approaches can complement these datasets by additional predictions, but most available tools use prediction models pre-trained for single PTM type by the developers and it remains a difficult task to perform large-scale batch prediction for multiple PTMs with flexible user control, including the choice of training data. We developed an R package called PTMscape which predicts PTM sites across the proteome based on a unified and comprehensive set of descriptors of the physico-chemical microenvironment of modified sites, with additional downstream analysis modules to test enrichment of individual or pairs of PTMs in protein domains. PTMscape is flexible in the ability to process any major modifications, such as phosphorylation and ubiquitination, while achieving the sensitivity and specificity comparable to single-PTM methods and outperforming other multi-PTM tools. Applying this framework, we expanded proteome-wide coverage of five major PTMs affecting different residues by prediction, especially for lysine and arginine modifications. Using a combination of experimentally acquired sites (PSP) and newly predicted sites, we discovered that the crosstalk among multiple PTMs occur more frequently than by random chance in key protein domains such as histone, protein kinase, and RNA recognition motifs, spanning various biological processes such as RNA processing, DNA damage response, signal transduction, and regulation of cell cycle. These results provide a proteome-scale analysis of crosstalk among major PTMs and can be easily extended to other types of PTM.

Posttranslational modifications (PTMs) regulate molecular structures and functions of proteins by covalently binding to amino acids. Hundreds of thousands of PTMs have been reported for the human proteome, with multiple PTMs known to affect tens of thousands of lysine (K) residues. Our molecular evolutionary analyses show that K residues with multiple PTMs exhibit greater conservation than those with a single PTM, but the difference is rather small. In contrast, short-term evolutionary trends revealed in an analysis of human population variation exhibited a much larger difference. Lysine residues with three PTMs show 1.8-fold enrichment of Mendelian disease-associated variants when compared with K residues with two PTMs, with the latter showing 1.7-fold enrichment of these variants when compared with the K residues with one PTM. Rare polymorphisms in humans show a similar trend, which suggests much greater negative selection against mutations of K residues with multiple PTMs within population. Conversely, common polymorphisms are overabundant at unmodified K residues and at K residues with fewer PTMs. The observed difference between inter- and intraspecies patterns of purifying selection on residues with PTMs suggests extensive species-specific drifting of PTM positions. These results suggest that the functionality of a protein is likely conserved, without necessarily conserving the PTM positions over evolutionary time.

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTQuantitative Proteomic Analysis of Histone ModificationsHe Huang†, Shu Lin‡, Benjamin A. Garcia‡, and Yingming Zhao*†View Author Information† Ben May Department of Cancer Research, The University of Chicago, Chicago, Illinois 60637, United States‡ Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States*Tel.: (773) 834-1561. Fax: (773) 702-3701. E-mail: [email protected]Cite this: Chem. Rev. 2015, 115, 6, 2376–2418Publication Date (Web):February 17, 2015Publication History Received2 September 2014Published online17 February 2015Published inissue 25 March 2015https://pubs.acs.org/doi/10.1021/cr500491uhttps://doi.org/10.1021/cr500491ureview-articleACS PublicationsCopyright © 2015 American Chemical SocietyRequest reuse permissionsArticle Views9003Altmetric-Citations286LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Ions,Mass spectrometry,Monomers,Peptides and proteins,Protein structure Get e-Alerts

Epithelial-mesenchymal transition (EMT) mediates intrinsic and acquired resistance to epidermal growth factor receptor (EGFR) inhibitors. This becomes a major hurdle in lung cancer treatment due to the lack of effective therapeutic strategies. We hypothesized that decoding the EMT signaling network could provide insights into the specific combinatorial logic associated with EMT signaling and identify new therapeutic strategies to combat EGFRi resistance. To test this hypothesis, we applied sequential enrichment of post-translational modifications (SEPTM) proteomics to analyze proteomes of expressed proteins and multiple post-translational modifications (PTM) including phosphorylation, ubiquitination, and acetylation in erlotinib sensitive cells (HCC4006) and matched erlotinib resistant cells after EMT (HCC4006ER). We conducted integrative informatics to characterize EMT associated proteins, PTMs, pathways, cross-talk among PTMs and signaling networks from our data. We used siRNA and small molecules to functionally interrogate our results by assaying cell viability and migration. We identified 6,641 proteins, 2,418 unique pSTY sites, 784 unique UbK-sites and 713 unique AcK-sites respectively. We found 377 proteins increased and 1377 proteins decreased (p<0.05, fold>2) in HCC4006ER cells compared to parent HCC4006 cells. We constructed an EMT signaling network, composed of 206 proteins with PTM changes including pSTY-sites (141 increase, 191 decrease), UbK-sites (29 increase, 32 decrease) and AcK-sites (14 increase, 46 decrease). Of 206 differentially modified proteins, 88 proteins are reported to be associated with EMT. Pathway analysis enriched 284 pathways from this EMT signaling network. We identified small molecule inhibitors associated with various pathways and tested for their effects on resistant cells. Inhibitors targeting 17 pathways and 3 major transcription factors were found to have effects on H4006ER viability, with inhibitors targeting DDR1, WNT and CDK signaling pathways demonstrating the most impact. Using RNAi, we found that that loss-of-function of 8 of 88 EMT-associated proteins (TAGLN2, STMN1, FYN, HNRNPA2B1, DDR1, INPPL1, OSMR and PRKAR2A) decreased HCC4006ER cell viability. Finally, integrative informatics revealed cross-talk among PTMs within EMT signaling network. From this analysis, we found that inhibiting GLI induced transcription sensitizes H4006ER cells to both EGFR inhibitor and Casein Kinase inhibitor. Collectively, SEPTM proteomics allows decoding the complex interplay in PTM modulation associated with EMT-mediated resistance. Our results suggest DDR1 as a potential actionable target for EMT driven resistance, which can serve as an example for combinatorial targeting of EMT proteins and signaling pathways as a strategy for overcoming EMT-mediated drug resistance. Citation Format: Guolin Zhang, Karen Ross, Bin Fang, Jun-Min Zhou, Paul A. Stewart, Emma Adhikari, Eric A. Welsh, Xuefeng Wang, John M. Koomen, Cathy H. Wu, Eric B. Haura. Post translational crosstalk networks identify strategies to overcome EMT-mediated resistance to EGFR inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1308.

Protein acetylation, one of many types of post-translational modifications (PTMs), is involved in a variety of biological and cellular processes. In the present study, we applied both CsCl density gradient (CDG) centrifugation-based protein fractionation and a dimethyl-labeling-based 4C quantitative PTM proteomics workflow in the study of dynamic acetylproteomic changes in Arabidopsis. This workflow integrates the dimethyl chemical labeling with chromatography-based acetylpeptide separation and enrichment followed by mass spectrometry (MS) analysis, the extracted ion chromatogram (XIC) quantitation-based computational analysis of mass spectrometry data to measure dynamic changes of acetylpeptide level using an in-house software program, named Stable isotope-based Quantitation-Dimethyl labeling (SQUA-D), and finally the confirmation of ethylene hormone-regulated acetylation using immunoblot analysis. Eventually, using this proteomic approach, 7456 unambiguous acetylation sites were found from 2638 different acetylproteins, and 5250 acetylation sites, including 5233 sites on lysine side chain and 17 sites on protein N termini, were identified repetitively. Out of these repetitively discovered acetylation sites, 4228 sites on lysine side chain (i.e. 80.5%) are novel. These acetylproteins are exemplified by the histone superfamily, ribosomal and heat shock proteins, and proteins related to stress/stimulus responses and energy metabolism. The novel acetylproteins enriched by the CDG centrifugation fractionation contain many cellular trafficking proteins, membrane-bound receptors, and receptor-like kinases, which are mostly involved in brassinosteroid, light, gravity, and development signaling. In addition, we identified 12 highly conserved acetylation site motifs within histones, P-glycoproteins, actin depolymerizing factors, ATPases, transcription factors, and receptor-like kinases. Using SQUA-D software, we have quantified 33 ethylene hormone-enhanced and 31 hormone-suppressed acetylpeptide groups or called unique PTM peptide arrays (UPAs) that share the identical unique PTM site pattern (UPSP). This CDG centrifugation protein fractionation in combination with dimethyl labeling-based quantitative PTM proteomics, and SQUA-D may be applied in the quantitation of any PTM proteins in any model eukaryotes and agricultural crops as well as tissue samples of animals and human beings.

Post-translational modifications (PTMs) play very important roles in various cell signaling pathways and biological process. Due to PTMs' extremely important roles, many major PTMs have been studied, while the functional and mechanical characterization of major PTMs is well documented in several databases. However, most currently available databases mainly focus on protein sequences, while the real 3D structures of PTMs have been largely ignored. Therefore, studies of PTMs 3D structural signatures have been severely limited by the deficiency of the data. Here, we develop PRISMOID, a novel publicly available and free 3D structure database for a wide range of PTMs. PRISMOID represents an up-to-date and interactive online knowledge base with specific focus on 3D structural contexts of PTMs sites and mutations that occur on PTMs and in the close proximity of PTM sites with functional impact. The first version of PRISMOID encompasses 17145 non-redundant modification sites on 3919 related protein 3D structure entries pertaining to 37 different types of PTMs. Our entry web page is organized in a comprehensive manner, including detailed PTM annotation on the 3D structure and biological information in terms of mutations affecting PTMs, secondary structure features and per-residue solvent accessibility features of PTM sites, domain context, predicted natively disordered regions and sequence alignments. In addition, high-definition JavaScript packages are employed to enhance information visualization in PRISMOID. PRISMOID equips a variety of interactive and customizable search options and data browsing functions; these capabilities allow users to access data via keyword, ID and advanced options combination search in an efficient and user-friendly way. A download page is also provided to enable users to download the SQL file, computational structural features and PTM sites' data. We anticipate PRISMOID will swiftly become an invaluable online resource, assisting both biologists and bioinformaticians to conduct experiments and develop applications supporting discovery efforts in the sequence-structural-functional relationship of PTMs and providing important insight into mutations and PTM sites interaction mechanisms. The PRISMOID database is freely accessible at http://prismoid.erc.monash.edu/. The database and web interface are implemented in MySQL, JSP, JavaScript and HTML with all major browsers supported.

Studying multiple post-translational modifications (PTMs) of proteins is a crucial step to understand PTM crosstalk and gain more holistic insights into protein function. Despite the importance of multi-PTM enrichment studies, few studies investigate more than one PTM at a time, due partially to the expenses, time, and large protein quantities required to perform multiple global proteomic analysis of PTMs. The "one-pot" affinity enrichment detailed in this protocol overcomes these barriers by permitting the simultaneous identification and quantification of peptides with lysine residues containing acetylation and succinylation PTMs with low amounts of sample input. The protocol involves preparation of protein lysate from mouse livers of SIRT5 knockout mice, performance of trypsin digestion, enrichment for PTMs, and performance of mass spectrometric analysis using a data-independent acquisition (DIA) workflow. Because this workflow allows for the enrichment of two PTMs from the same sample simultaneously, it provides a practical tool to study PTM crosstalk without requiring large amounts of samples, and it greatly reduces the time required for sample preparation, data acquisition, and analysis. The DIA component of the workflow provides comprehensive PTM-specific information. This is particularly important when studying PTM site localization, as DIA provides comprehensive sets of fragment ions that can be computationally deciphered to differentiate between different PTM localization isoforms.

Most naturally occurring mammalian cancers and immortalized tissue culture cell lines share a common characteristic, the overexpression of full-length HMGA1 (high mobility group A1) proteins. The HMGA1 protooncogene codes for two closely related isoform proteins, HMGA1a and HMGA1b, and causes cancerous cellular transformation when overexpressed in either transgenic mice or "normal" cultured cell lines. Previous work has suggested that the in vivo types and patterns of the HMGA1 post-translational modifications (PTMs) differ between normal and malignant cells. The present study focuses on the important question of whether HMGA1a and HMGA1b proteins isolated from the same cell type have identical or different PTM patterns and also whether these isoform patterns differ between non-malignant and malignant cells. Two independent mass spectrometry methods were used to identify the types of PTMs found on specific amino acid residues on the endogenous HMGA1a and HMGA1b proteins isolated from a non-metastatic human mammary epithelial cell line, MCF-7, and a malignant metastatic cell line derived from MCF-7 cells that overexpressed the transgenic HMGA1a protein. Although some of the PTMs were the same on both the HMGA1a and HMGA1b proteins isolated from a given cell type, many other modifications were present on one but not the other isoform. Furthermore, we demonstrate that both HMGA1 isoforms are di-methylated on arginine and lysine residues. Most importantly, however, the PTM patterns on the endogenous HMGA1a and HMGA1b proteins isolated from non-metastatic and metastatic cells were consistently different, suggesting that the isoforms likely exhibit differences in their biological functions/activities in these cell types.

Maturity-onset diabetes of the young (MODY) is a genetically heterogeneous monogenic form of diabetes characterized by onset of diabetes below 25 years of age, autosomal dominant mode of inheritance and primary defect in insulin secretion. Mutations in the gene (HNF1A) encoding transcription factor hepatocyte nuclear factor 1A (HNF-1A) results in one of the most common forms of MODY (MODY3). HNF-1A is mainly enriched in pancreatic β-cells and hepatocytes and important for organ development and normal pancreatic function. We here report on the functional interrogation of eight missense HNF1A mutations associated with MODY3 in South Indian subjects, and the contributing effect of common variant (S487N) within HNF1A. Of the eight mutations, three mutations (p.R171G, p.G245R and p.R263H), in particular, affected HNF-1A function in transfected HeLa cells by reducing both transcriptional activity and nuclear localization, possibly due to disruption of the integrity of the three dimensional structure. The common variant p.S487N contributed further to the loss-of-function of p.R271Q (p.R271Q+p.S487N double mutant), in vitro, on both activity and localization. Our data on the first functional study of HNF1A mutations in South India subjects confers that the defect of the HNF-1A mutant proteins are responsible for MODY3 diabetes in these patients.

Bottom-up mass spectrometry-based proteomics studies changes in protein abundance and structure across conditions. Since the currency of these experiments are peptides, i.e. subsets of protein sequences that carry the quantitative information, conclusions at a different level must be computationally inferred. The inference is particularly challenging in situations where the peptides are shared by multiple proteins or post-translational modifications. While many approaches infer the underlying abundances from unique peptides, there is a need to distinguish the quantitative patterns when peptides are shared. We propose a statistical approach for estimating protein abundances, as well as site occupancies of post-translational modifications, based on quantitative information from shared peptides. The approach treats the quantitative patterns of shared peptides as convex combinations of abundances of individual proteins or modification sites, and estimates the abundance of each source in a sample together with the weights of the combination. In simulation-based evaluations, the proposed approach improved the precision of estimated fold changes between conditions. We further demonstrated the practical utility of the approach in experiments with diverse biological objectives, ranging from protein degradation and thermal proteome stability, to changes in protein post-translational modifications. The approach is implemented in an open-source R package MSstatsWeightedSummary. The package is currently available at https://github.com/Vitek-Lab/MSstatsWeightedSummary (doi: 10.5281/zenodo.14662989). Code required to reproduce the results presented in this article can be found in a repository https://github.com/mstaniak/MWS_reproduction (doi: 10.5281/zenodo.14656053).

The increasing dynamic functions of post-translational modifications (PTMs) within protein molecules present outstanding challenges for plant biology even at this present day. Protein PTMs are among the first and fastest plant responses to changes in the environment, indicating that the mechanisms and dynamics of PTMs are an essential area of plant biology. Besides being key players in signaling, PTMs play vital roles in gene expression, gene, and protein localization, protein stability and interactions, as well as enzyme kinetics. In this review, we take a broader but concise approach to capture the current state of events in the field of plant PTMs. We discuss protein modifications including citrullination, glycosylation, phosphorylation, oxidation and disulfide bridges, N-terminal, SUMOylation, and ubiquitination. Further, we outline the complexity of studying PTMs in relation to compartmentalization and function. We conclude by challenging the proteomics community to engage in holistic approaches towards identification and characterizing multiple PTMs on the same protein, their interaction, and mechanism of regulation to bring a deeper understanding of protein function and regulation in plants.

PTMcosmos is a comprehensive database with an interactive web portal designed to catalog and visualize post-translational modifications (PTMs) in humans. It contains 469,183 experimentally-validated PTM sites and their supporting evidence from UniProt Knowledge Base, PhosphoSitePlus, and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). PTMcosmos summarizes the entire spectrum of CPTAC proteomics data on human cancer patients, including protein and PTM peptide abundance data from 10 different cancer types. Additionally, PTMcosmos contains cancer somatic mutations from The Cancer Genome Atlas (TCGA), thus allowing for the collective integration and analysis of different data types. In PTMcosmos, we have built an ensemble of interactive visualization tools that allow researchers to investigate altered PTM functions due to genetic alterations in close proximity. The database is live at https://ptmcosmos.wustl.edu. We used PTMcosmos to investigate PTM regulation across cancer types. First, we examined the differential abundance of the PTM sites of cancer driver genes, focusing primarily on phosphorylation of the tumor suppressor retinoblastoma protein (encoded by RB1) and acetylation of the histone acetyltransferase E1A Binding Protein P300 (EP300) across cancer types. We analyzed the association between these PTM events and downstream targets, as well as with tumor subtypes, significantly mutated gene (SMG) mutation status, and clinical features. Second, we investigated the association of the protein abundance of cancer driver genes with ubiquitylsites in lung squamous cell carcinoma (LSCC) to nominate potentially novel modes of regulation of these proteins’ activities. We further analyzed the tumor subtype specificity and tumor-normal abundance changes of these ubiquitylsites and their corresponding substrate proteins, identifying several EGFR ubiquitylsites which may regulate EGFR abundance in LSCC. Finally, we identified the linear and spatial clustering of mutations and PTM sites, identifying multiple mutation-PTM clusters in cancer related genes, including TP53, PIK3CA, CTNNB1, EGFR, and IDH1. We envision that PTMcosmos will serve both the CPTAC consortium and the wider research community to better understand the role of PTMs in cancer. Citation Format: Liang-Bo Wang, Akshay Govindan, Song Cao, Li Ding. PTMcosmos: A web portal of post-translational modifications and proteogenomic resources in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5027.

Post-translational modification (PTM) sites have become popular for predictor development. However, with the exception of phosphorylation and a handful of other examples, PTMs suffer from a limited number of available training examples and sparsity in protein sequences. Here, proline hydroxylation is taken as an example to compare different methods and evaluate their performance on new experimentally determined sites. As a guide for effective experimental design, predictors require both high specificity and sensitivity. However, the self-reported performance may often not be indicative of prediction quality and detection of new sites is not guaranteed. We have benchmarked seven published hydroxylation site predictors on two newly constructed independent datasets. The self-reported performance is found to widely overestimate the real accuracy measured on independent datasets. No predictor performs better than random on new examples, indicating the refined models do not sufficiently generalize to detect new sites. The number of false positives is high and precision low, in particular for non-collagen proteins whose motifs are not conserved. As hydroxylation site predictors do not generalize for new data, caution is advised when using PTM predictors in the absence of independent evaluations, in particular for highly specific sites involved in signalling.

BackgroundHepatocyte nuclear factor-4α (HNF4α; NR2A1) is an orphan member of the nuclear receptor superfamily involved in various processes that could influence endoderm development, glucose and lipid metabolism. A loss-of-function mutation in human HNF4α causes one form of diabetes mellitus called maturity-onset diabetes of the young type 1 (MODY1) which is characterized in part by a diminished insulin secretory response to glucose. The expression of HNF4α in a variety of tissues has been examined predominantly at the mRNA level, and there is little information regarding the cellular localization of the endogenous HNF4α protein, due, in part, to the limited availability of human HNF4α-specific antibodies.ResultsMonoclonal antibodies have been produced using baculovirus particles displaying gp64-HNF4α fusion proteins as the immunizing agent. The mouse anti-human HNF4α monoclonal antibody (K9218) generated against human HNF4α1/α2/α3 amino acids 3–49 was shown to recognize not only the transfected and expressed P1 promoter-driven HNF4α proteins, but also endogenous proteins. Western blot analysis with whole cell extracts from Hep G2, Huh7 and Caco-2 showed the expression of HNF4α protein, but HEK293 showed no expression of HNF4α protein. Nuclear-specific localization of the HNF4α protein was observed in the hepatocytes of liver cells, proximal tubular epithelial cells of kidney, and mucosal epithelial cells of small intestine and colon, but no HNF4α protein was detected in the stomach, pancreas, glomerulus, and distal and collecting tubular epithelial cells of kidney. The same tissue distribution of HNF4α protein was observed in humans and rats. Electron microscopic immunohistochemistry showed a chromatin-like localization of HNF4α in the liver and kidney. As in the immunohistochemical investigation using K9218, HNF4α mRNA was found to be localized primarily to liver, kidney, small intestine and colon by RT-PCR and GeneChip analysis.ConclusionThese results suggest that this method has the potential to produce valuable antibodies without the need for a protein purification step. Immunohistochemical studies indicate the tissue and subcellular specific localization of HNF4α and demonstrate the utility of K9218 for the detection of P1 promoter-driven HNF4α isoforms in humans and in several other mammalian species.