Isobar(PTM): a software tool for the quantitative analysis of post-translationally modified proteins

Specialized replication mechanisms maintain genome stability at human centromeres

The high incidence of whole-arm chromosome aneuploidy and translocations in tumors suggests instability of centromeres, unique loci built on repetitive sequences and essential for chromosome separation. The causes behind this fragility and the mechanisms preserving centromere integrity remain elusive. We show that replication stress, hallmark of pre-cancerous lesions, promotes centromeric breakage in mitosis, due to spindle forces and endonuclease activities. Mechanistically, we unveil unique dynamics of the centromeric replisome distinct from the rest of the genome. Locus-specific proteomics identifies specialized DNA replication and repair proteins at centromeres, highlighting them as difficult-to-replicate regions. The translesion synthesis pathway, along with other factors, acts to sustain centromere replication and integrity. Prolonged stress causes centromeric alterations like ruptures and translocations, as observed in ovarian cancer models experiencing replication stress. This study provides unprecedented insights into centromere replication and integrity, proposing mechanistic insights into the origins of centromere alterations leading to abnormal cancerous karyotypes.

msqrob2PTM: Differential Abundance and Differential Usage Analysis of MS-Based Proteomics Data at the Posttranslational Modification and Peptidoform Level

In the era of open-modification search engines, more posttranslational modifications than ever can be detected by LC-MS/MS-based proteomics. This development can switch proteomics research into a higher gear, as PTMs are key in many cellular pathways important in cell proliferation, migration, metastasis, and aging. However, despite these advances in modification identification, statistical methods for PTM-level quantification and differential analysis have yet to catch up. This absence can partly be explained by statistical challenges inherent to the data, such as the confounding of PTM intensities with its parent protein abundance. Therefore, we have developed msqrob2PTM, a new workflow in the msqrob2 universe capable of differential abundance analysis at the PTM and at the peptidoform level. The latter is important for validating PTMs found as significantly differential. Indeed, as our method can deal with multiple PTMs per peptidoform, there is a possibility that significant PTMs stem from one significant peptidoform carrying another PTM, hinting that it might be the other PTM driving the perceived differential abundance. Our workflows can flag both differential peptidoform abundance (DPA) and differential peptidoform usage (DPU). This enables a distinction between direct assessment of differential abundance of peptidoforms (DPA) and differences in the relative usage of peptidoforms corrected for corresponding protein abundances (DPU). For DPA, we directly model the log2-transformed peptidoform intensities, while for DPU, we correct for parent protein abundance by an intermediate normalization step which calculates the log2-ratio of the peptidoform intensities to their summarized parent protein intensities. We demonstrated the utility and performance of msqrob2PTM by applying it to datasets with known ground truth, as well as to biological PTM-rich datasets. Our results show that msqrob2PTM is on par with, or surpassing the performance of, the current state-of-the-art methods. Moreover, msqrob2PTM is currently unique in providing output at the peptidoform level.

MSstatsPTM: Statistical Relative Quantification of Posttranslational Modifications in Bottom-Up Mass Spectrometry-Based Proteomics

Liquid chromatography coupled with bottom-up mass spectrometry (LC-MS/MS)-based proteomics is increasingly used to detect changes in posttranslational modifications (PTMs) in samples from different conditions. Analysis of data from such experiments faces numerous statistical challenges. These include the low abundance of modified proteoforms, the small number of observed peptides that span modification sites, and confounding between changes in the abundance of PTM and the overall changes in the protein abundance. Therefore, statistical approaches for detecting differential PTM abundance must integrate all the available information pertaining to a PTM site and consider all the relevant sources of confounding and variation. In this manuscript, we propose such a statistical framework, which is versatile, accurate, and leads to reproducible results. The framework requires an experimental design, which quantifies, for each sample, both peptides with PTMs and peptides from the same proteins with no modification sites. The proposed framework supports both label-free and tandem mass tag-based LC-MS/MS acquisitions. The statistical methodology separately summarizes the abundances of peptides with and without the modification sites, by fitting separate linear mixed effects models appropriate for the experimental design. Next, model-based inferences regarding the PTM and the protein-level abundances are combined to account for the confounding between these two sources. Evaluations on computer simulations, a spike-in experiment with known ground truth, and three biological experiments with different organisms, modification types, and data acquisition types demonstrate the improved fold change estimation and detection of differential PTM abundance, as compared to currently used approaches. The proposed framework is implemented in the free and open-source R/Bioconductor package MSstatsPTM.

Interaction Network Provides Clues on the Role of BCAR1 in Cellular Response to Changes in Gravity

When culturing cells in space or under altered gravity conditions on Earth to investigate the impact of gravity, their adhesion and organoid formation capabilities change. In search of a target where the alteration of gravity force could have this impact, we investigated p130cas/BCAR1 and its interactions more thoroughly, particularly as its activity is sensitive to applied forces. This protein is well characterized regarding its role in growth stimulation and adhesion processes. To better understand BCAR1′s force-dependent scaffolding of other proteins, we studied its interactions with proteins we had detected by proteome analyses of MCF-7 breast cancer and FTC-133 thyroid cancer cells, which are both sensitive to exposure to microgravity and express BCAR1. Using linked open data resources and our experiments, we collected comprehensive information to establish a semantic knowledgebase and analyzed identified proteins belonging to signaling pathways and their networks. The results show that the force-dependent phosphorylation and scaffolding of BCAR1 influence the structure, function, and degradation of intracellular proteins as well as the growth, adhesion and apoptosis of cells similarly to exposure of whole cells to altered gravity. As BCAR1 evidently plays a significant role in cell responses to gravity changes, this study reveals a clear path to future research performing phosphorylation experiments on BCAR1.

Omics-based molecular analyses of adhesion by aquatic invertebrates

Many aquatic invertebrates are associated with surfaces, using adhesives to attach to the substratum for locomotion, prey capture, reproduction, building or defence. Their intriguing and sophisticated biological glues have been the focus of study for decades. In all but a couple of specific taxa, however, the precise mechanisms by which the bioadhesives stick to surfaces underwater and (in many cases) harden have proved to be elusive. Since the bulk components are known to be based on proteins in most organisms, the opportunities provided by advancing 'omics technologies have revolutionised bioadhesion research. Time-consuming isolation and analysis of single molecules has been either replaced or augmented by the generation of massive data sets that describe the organism's translated genes and proteins. While these new approaches have provided resources and opportunities that have enabled physiological insights and taxonomic comparisons that were not previously possible, they do not provide the complete picture and continued multi-disciplinarity is essential. This review covers the various ways in which 'omics have contributed to our understanding of adhesion by aquatic invertebrates, with new data to illustrate key points. The associated challenges are highlighted and priorities are suggested for future research.

The Greatwall kinase safeguards the genome integrity by affecting the kinome activity in mitosis

Progression through mitosis is balanced by the timely regulation of phosphorylation and dephosphorylation events ensuring the correct segregation of chromosomes before cytokinesis. This balance is regulated by the opposing actions of CDK1 and PP2A, as well as the Greatwall kinase/MASTL. MASTL is commonly overexpressed in cancer, which makes it a potential therapeutic anticancer target. Loss of Mastl induces multiple chromosomal errors that lead to the accumulation of micronuclei and multilobulated cells in mitosis. Our analyses revealed that loss of Mastl leads to chromosome breaks and abnormalities impairing correct segregation. Phospho-proteomic data for Mastl knockout cells revealed alterations in proteins implicated in multiple processes during mitosis including double-strand DNA damage repair. In silico prediction of the kinases with affected activity unveiled NEK2 to be regulated in the absence of Mastl. We uncovered that, RAD51AP1, involved in regulation of homologous recombination, is phosphorylated by NEK2 and CDK1 but also efficiently dephosphorylated by PP2A/B55. Our results suggest that MastlKO disturbs the equilibrium of the mitotic phosphoproteome that leads to the disruption of DNA damage repair and triggers an accumulation of chromosome breaks even in noncancerous cells.

Type I Interferon Signaling Disrupts the Hepatic Urea Cycle and Alters Systemic Metabolism to Suppress T Cell Function

Infections induce complex host responses linked to antiviral defense, inflammation, and tissue damage and repair. We hypothesized that the liver, as a central metabolic hub, may orchestrate systemic metabolic changes during infection. We infected mice with chronic lymphocytic choriomeningitis virus (LCMV), performed RNA sequencing and proteomics of liver tissue, and integrated these data with serum metabolomics at different infection phases. Widespread reprogramming of liver metabolism occurred early after infection, correlating with type I interferon (IFN-I) responses. Viral infection induced metabolic alterations of the liver that depended on the interferon alpha/beta receptor (IFNAR1). Hepatocyte-intrinsic IFNAR1 repressed the transcription of metabolic genes, including Otc and Ass1, which encode urea cycle enzymes. This led to decreased arginine and increased ornithine concentrations in the circulation, resulting in suppressed virus-specific CD8+ T cell responses and ameliorated liver pathology. These findings establish IFN-I-induced modulation of hepatic metabolism and the urea cycle as an endogenous mechanism of immunoregulation. VIDEO ABSTRACT.

Modulation of muscle protein synthesis by amino acids: what consequences for the secretome? A preliminary in vitro study

The modulation by amino acids of muscle secretome is largely unknown. In this study, we investigate the effect of hyperaminoacidemia or specific amino acids (citrulline or leucine) on protein synthesis and secretome in myotubes. All conditions stimulate muscle protein synthesis, and secretome is differently modulated depending of the amino acids considered. In conclusion, the activation of protein synthesis by amino acids induces different modulations of the muscle secretome, proposing a new role of amino acids in the regulation of muscle function.

Semantic Analysis of Posttranslational Modification of Proteins Accumulated in Thyroid Cancer Cells Exposed to Simulated Microgravity

When monolayers of tissue cancer cells of various origins are exposed to real or simulated microgravity, many cells leave the monolayer and assemble to three-dimensional (3D) aggregates (spheroids). In order to define the cellular machinery leading to this change in growth behavior of FTC-133 human thyroid cancer cells and MCF-7 breast cancer cells, we recently performed proteome analyses on these cell lines and determined the proteins’ accumulation in monolayer cells grown under 1g-conditions as well as in the cells of spheroids assembled under simulated microgravity during three and 14 days, respectively. At that time, an influence of the increment or decrement of some of the more than 5000 proteins detected in each cell line was investigated. In this study, we focused on posttranslational modifications (PTMs) of proteins. For this purpose, we selected candidates from the list of the proteins detected in the two preceding proteome analyses, which showed significant accumulation in spheroid cells as compared to 1g monolayer cells. Then we searched for those PTMs of the selected proteins, which according to the literature have already been determined experimentally. Using the Semantic Protocol and RDF Query Language (SPARQL), various databases were examined. Most efficient was the search in the latest version of the dbPTM database. In total, we found 72 different classes of PTMs comprising mainly phosphorylation, glycosylation, ubiquitination and acetylation. Most interestingly, in 35 of the 69 proteins, N6 residues of lysine are modifiable.

Human tissue engineering allows the identification of active miRNA regulators of glioblastoma aggressiveness

Glioblastoma multiforme (GBM) is among the most aggressive cancers associated with massive infiltration of peritumoral parenchyma by migrating tumor cells. The infiltrative nature of GBM cells, the intratumoral heterogeneity concomitant with redundant signaling pathways likely underlie the inability of conventional and targeted therapies to achieve long-term remissions. In this respect, microRNAs (miRNAs), which are endogenous small non-coding RNAs that play a role in cancer aggressiveness, emerge as possible relevant prognostic biomarkers or therapeutic targets for treatment of malignant gliomas. We previously described a tissue model of GBM developing into a stem cell-derived human Engineered Neural Tissue (ENT) that allows the study of tumor/host tissue interaction. Combined with high throughput sequencing analysis, we took advantage of this human and integrated tissue model to understand miRNAs regulation. Three miRNAs (miR-340, -494 and -1293) active on cell proliferation, adhesion to extracellular matrix and tumor cell invasion were identified in GBM cells developing within ENT, and also confirmed in GBM biopsies. The components of miRNAs regulatory network at the transcriptional and the protein level have been also revealed by whole transcriptome analysis and Tandem Mass Tag in transfected GBM cells. Notably, miR-340 has a clinical relevance and modulates the expression of miR-494 and -1293, emphasizing its biological significance. Altogether, these findings demonstrate that human tissue engineering modeling GBM development in neural host tissue is a suitable tool to identify active miRNAs. Collectively, our study identified miR-340 as a strong modulator of GBM aggressiveness which may constitute a therapeutic target for treatment of malignant gliomas.

Quantitation of protein post-translational modifications using isobaric tandem mass tags

Post-translational modifications (PTMs) of proteins are known to modulate many cellular processes and their qualitative and quantitative evaluation is fundamental for understanding the mechanisms of biological events. Over the past decade, improvements in sample preparation techniques and enrichment strategies, the development of quantitative labeling strategies, the launch of a new generation of mass spectrometers and the creation of bioinformatics tools for the interrogation of ever larger datasets has established MS-based quantitative proteomics as a powerful workflow for global proteomics, PTM analysis and the elucidation of key biological mechanisms. With the advantage of their multiplexing capacity and the flexibility of an ever-growing family of different peptide-reactive groups, isobaric tandem mass tags facilitate quantitative proteomics and PTM experiments and enable higher sample throughput. In this review, we focus on the technical concept and utility of the isobaric tandem mass tag labeling approach to PTM analysis, including phosphorylation, glycosylation and S-nitrosylation.

Computational and statistical methods for high-throughput analysis of post-translational modifications of proteins

The investigation of post-translational modifications (PTMs) represents one of the main research focuses for the study of protein function and cell signaling. Mass spectrometry instrumentation with increasing sensitivity improved protocols for PTM enrichment and recently established pipelines for high-throughput experiments allow large-scale identification and quantification of several PTM types. This review addresses the concurrently emerging challenges for the computational analysis of the resulting data and presents PTM-centered approaches for spectra identification, statistical analysis, multivariate analysis and data interpretation. We furthermore discuss the potential of future developments that will help to gain deep insight into the PTM-ome and its biological role in cells. This article is part of a Special Issue entitled: Computational Proteomics.

Human cytomegalovirus pUL97 kinase induces global changes in the infected cell phosphoproteome

Replication of human cytomegalovirus (HCMV) is regulated in part by cellular kinases and the single viral Ser/Thr kinase, pUL97. The virus-coded kinase augments the replication of HCMV by enabling nuclear egress and altering cell cycle progression. These roles are accomplished through direct phosphorylation of nuclear lamins and the retinoblastoma protein, respectively. In an effort to identify additional pUL97 substrates, we analyzed the phosphoproteome of SILAC-labeled human fibroblasts during infection with either wild-type HCMV or a pUL97 kinase-dead mutant virus. Phosphopeptides were enriched over a titanium dioxide matrix and analyzed by high-resolution MS. We identified 157 unambiguous phosphosites from 106 cellular and 17 viral proteins whose phosphorylation required UL97. Analysis of peptides containing these sites allowed the identification of several candidate pUL97 phosphorylation motifs, including a completely novel phosphorylation motif, LxSP. Substrates harboring the LxSP motif were enriched in nucleocytoplasmic transport functions, including a number of components of the nuclear pore complex. These results extend the known functions of pUL97 and suggest that modulation of nuclear pore function may be important during HCMV replication.

Global analysis of muscle-specific kinase signaling by quantitative phosphoproteomics

The development of the neuromuscular synapse depends on signaling processes that involve protein phosphorylation as a crucial regulatory event. Muscle-specific kinase (MuSK) is the key signaling molecule at the neuromuscular synapse whose activity is required for the formation of a mature and functional synapse. However, the signaling cascade downstream of MuSK and the regulation of the different components are still poorly understood. In this study we used a quantitative phosphoproteomics approach to study the phosphorylation events and their temporal regulation downstream of MuSK. We identified a total of 10,183 phosphopeptides, of which 203 were significantly up- or down-regulated. Regulated phosphopeptides were classified into four different clusters according to their temporal profiles. Within these clusters we found an overrepresentation of specific protein classes associated with different cellular functions. In particular, we found an enrichment of regulated phosphoproteins involved in posttranscriptional mechanisms and in cytoskeletal organization. These findings provide novel insights into the complex signaling network downstream of MuSK and form the basis for future mechanistic studies.