Phosphomatics: interactive interrogation of substrate-kinase networks in global phosphoproteomics datasets

Metabolic remodeling in hiPSC-derived myofibers carrying the m.3243A>G mutation

Mutations in mitochondrial DNA cause severe multisystem disease frequently associated with muscle weakness. The m.3243A>G mutation is the major cause of mitochondrial encephalomyopathy lactic acidosis and stroke-like episodes (MELAS). Experimental models that recapitulate the disease phenotype in vitro for disease modeling or drug screening are very limited. We have therefore generated hiPSC-derived muscle fibers with variable heteroplasmic mtDNA mutation load without significantly affecting muscle differentiation potential. The cells exhibit physiological characteristics of muscle fibers and show a well-organized myofibrillar structure. In cells carrying the m.3243A>G mutation, the mitochondrial membrane potential and oxygen consumption were reduced in relation to the mutant load. We have shown through proteomic, phosphoproteomic, and metabolomic analyses that the m.3243A>G mutation variably affects the cell phenotype in relation to the mutant load. This variation is reflected by an increase in the NADH/NAD+ ratio, which in turn influences key nutrient-sensing pathways in the myofibers. This model enables a detailed study of the impact of the mutation on cellular bioenergetics and on muscle physiology with the potential to provide a platform for drug screening.

Inferring kinase-phosphosite regulation from phosphoproteome-enriched cancer multi-omics datasets

Phosphorylation in eukaryotic cells plays a key role in regulating cell signaling and disease progression. Despite the ability to detect thousands of phosphosites in a single experiment using high-throughput technologies, the kinases responsible for regulating these sites are largely unidentified. To solve this, we collected the quantitative data at the transcriptional, protein, and phosphorylation levels of 10 159 samples from 23 tumor datasets and 15 adjacent normal tissue datasets. Our analysis aimed to uncover the potential impact and linkage of kinase-phosphosite (KPS) pairs through experimental evidence in publications and prediction tools commonly used. We discovered that both experimentally validated and tool-predicted KPS pairs were enriched in groups where there is a significant correlation between kinase expression/phosphorylation level and the phosphorylation level of phosphosite. This suggested that a quantitative correlation could infer the KPS interconnections. Furthermore, the Spearman's correlation coefficient for these pairs were notably higher in tumor samples, indicating that these regulatory interactions are particularly pronounced in tumors. Consequently, building on the KPS correlations of different datasets as predictive features, we have developed an innovative approach that employed an oversampling method combined with and XGBoost algorithm (SMOTE-XGBoost) to predict potential kinase-specific phosphorylation sites in proteins. Moreover, the computed correlations and predictions of kinase-phosphosite interconnections were integrated into the eKPI database (https://ekpi.omicsbio.info/). In summary, our study could provide helpful information and facilitate further research on the regulatory relationship between kinases and phosphosites.

Multilevel plasticity and altered glycosylation drive aggressiveness in hypoxic and glucose-deprived bladder cancer cells

Bladder tumors with aggressive characteristics often present microenvironmental niches marked by low oxygen levels (hypoxia) and limited glucose supply due to inadequate vascularization. The molecular mechanisms facilitating cellular adaptation to these stimuli remain largely elusive. Employing a multi-omics approach, we discovered that hypoxic and glucose-deprived cancer cells enter a quiescent state supported by mitophagy, fatty acid β-oxidation, and amino acid catabolism, concurrently enhancing their invasive capabilities. Reoxygenation and glucose restoration efficiently reversed cell quiescence without affecting cellular viability, highlighting significant molecular plasticity in adapting to microenvironmental challenges. Furthermore, cancer cells exhibited substantial perturbation of protein O-glycosylation, leading to simplified glycophenotypes with shorter glycosidic chains. Exploiting glycoengineered cell models, we established that immature glycosylation contributes to reduced cell proliferation and increased invasion. Our findings collectively indicate that hypoxia and glucose deprivation trigger cancer aggressiveness, reflecting an adaptive escape mechanism underpinned by altered metabolism and protein glycosylation, providing grounds for clinical intervention.

PTMNavigator: interactive visualization of differentially regulated post-translational modifications in cellular signaling pathways

Post-translational modifications (PTMs) play pivotal roles in regulating cellular signaling, fine-tuning protein function, and orchestrating complex biological processes. Despite their importance, the lack of comprehensive tools for studying PTMs from a pathway-centric perspective has limited our ability to understand how PTMs modulate cellular pathways on a molecular level. Here, we present PTMNavigator, a tool integrated into the ProteomicsDB platform that offers an interactive interface for researchers to overlay experimental PTM data with pathway diagrams. PTMNavigator provides ~3000 canonical pathways from manually curated databases, enabling users to modify and create custom diagrams tailored to their data. Additionally, PTMNavigator automatically runs kinase and pathway enrichment algorithms whose results are directly integrated into the visualization. This offers a comprehensive view of the intricate relationship between PTMs and signaling pathways. We demonstrate the utility of PTMNavigator by applying it to two phosphoproteomics datasets, showing how it can enhance pathway enrichment analysis, visualize how drug treatments result in a discernable flow of PTM-driven signaling, and aid in proposing extensions to existing pathways. By enhancing our understanding of cellular signaling dynamics and facilitating the discovery of PTM-pathway interactions, PTMNavigator advances our knowledge of PTM biology and its implications in health and disease.

Engineering cell-free systems by chemoproteomic-assisted phenotypic screening

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

Targeting the ribosome to treat multiple myeloma

The high rates of protein synthesis and processing render multiple myeloma (MM) cells vulnerable to perturbations in protein homeostasis. The induction of proteotoxic stress by targeting protein degradation with proteasome inhibitors (PIs) has revolutionized the treatment of MM. However, resistance to PIs is inevitable and represents an ongoing clinical challenge. Our first-in-human study of the selective inhibitor of RNA polymerase I transcription of ribosomal RNA genes, CX-5461, has demonstrated a potential signal for anti-tumor activity in three of six heavily pre-treated MM patients. Here, we show that CX-5461 has potent anti-myeloma activity in PI-resistant MM preclinical models in vitro and in vivo. In addition to inhibiting ribosome biogenesis, CX-5461 causes topoisomerase II trapping and replication-dependent DNA damage, leading to G2/M cell-cycle arrest and apoptotic cell death. Combining CX-5461 with PI does not further enhance the anti-myeloma activity of CX-5461 in vivo. In contrast, CX-5461 shows synergistic interaction with the histone deacetylase inhibitor panobinostat in both the Vk∗MYC and the 5T33-KaLwRij mouse models of MM by targeting ribosome biogenesis and protein synthesis through distinct mechanisms. Our findings thus provide strong evidence to facilitate the clinical development of targeting the ribosome to treat relapsed and refractory MM.

Temporal Quantitative Proteomic and Phosphoproteomic Profiling of SH-SY5Y and IMR-32 Neuroblastoma Cells during All-Trans-Retinoic Acid-Induced Neuronal Differentiation

The human neuroblastoma cell lines SH-SY5Y and IMR-32 can be differentiated into neuron-like phenotypes through treatment with all-trans-retinoic acid (ATRA). After differentiation, these cell lines are extensively utilized as in vitro models to study various aspects of neuronal cell biology. However, temporal and quantitative profiling of the proteome and phosphoproteome of SH-SY5Y and IMR-32 cells throughout ATRA-induced differentiation has been limited. Here, we performed relative quantification of the proteomes and phosphoproteomes of SH-SY5Y and IMR-32 cells at multiple time points during ATRA-induced differentiation. Relative quantification of proteins and phosphopeptides with subsequent gene ontology analysis revealed that several biological processes, including cytoskeleton organization, cell division, chaperone function and protein folding, and one-carbon metabolism, were associated with ATRA-induced differentiation in both cell lines. Furthermore, kinase-substrate enrichment analysis predicted altered activities of several kinases during differentiation. Among these, CDK5 exhibited increased activity, while CDK2 displayed reduced activity. The data presented serve as a valuable resource for investigating temporal protein and phosphoprotein abundance changes in SH-SY5Y and IMR-32 cells during ATRA-induced differentiation.

Phospho-Analyst: An Interactive, Easy-to-Use Web Platform To Analyze Quantitative Phosphoproteomics Data

Phosphoproteomics is nowadays the method of choice to comprehensively identify and quantify thousands of phosphorylated peptides and their associated proteins with the goal of interrogating changes in signal transduction pathways and other cellular processes. One of the most popular software suites to analyze phosphoproteomic data sets is MaxQuant, which converts mass spectrometric raw data into quantitative information on phosphopeptides and proteins. However, despite the increased utilization of phosphoproteomics in biomedical research, simple and user-friendly tools supporting downstream statistical analysis and interpretation of these highly complex outputs are still lacking. We have therefore developed Phospho-Analyst, which─similar to its sibling LFQ-Analyst─is an easy-to-use, interactive web application specifically designed to reproducibly perform differential expression analyses with "one click" and to visualize phosphoproteomic results in a meaningful and practical manner. Furthermore, if quantitative total proteomic information is available for the same samples, Phospho-Analyst automatically normalizes all phosphoproteomic results to underlying protein abundance levels, thereby ensuring that only genuine changes in phosphorylation events are considered. As such, Phospho-Analyst can not only be used by experienced proteomic veterans but also by researchers without any prior knowledge in (phospho)proteomics, statistics, or bioinformatics. Phospho-Analyst, including a detailed manual, is freely available at https://analyst-suites.org/apps/phospho-analyst/.

Functional annotation of proteins for signaling network inference in non-model species

Molecular biology aims to understand cellular responses and regulatory dynamics in complex biological systems. However, these studies remain challenging in non-model species due to poor functional annotation of regulatory proteins. To overcome this limitation, we develop a multi-layer neural network that determines protein functionality directly from the protein sequence. We annotate kinases and phosphatases in Glycine max. We use the functional annotations from our neural network, Bayesian inference principles, and high resolution phosphoproteomics to infer phosphorylation signaling cascades in soybean exposed to cold, and identify Glyma.10G173000 (TOI5) and Glyma.19G007300 (TOT3) as key temperature regulators. Importantly, the signaling cascade inference does not rely upon known kinase motifs or interaction data, enabling de novo identification of kinase-substrate interactions. Conclusively, our neural network shows generalization and scalability, as such we extend our predictions to Oryza sativa, Zea mays, Sorghum bicolor, and Triticum aestivum. Taken together, we develop a signaling inference approach for non-model species leveraging our predicted kinases and phosphatases.

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.

Endometrial small extracellular vesicles regulate human trophectodermal cell invasion by reprogramming the phosphoproteome landscape

A series of cyclical events within the uterus are crucial for pregnancy establishment. These include endometrial regeneration following menses, under the influence of estrogen (proliferative phase), then endometrial differentiation driven by estrogen/progesterone (secretory phase), to provide a microenvironment enabling attachment of embryo (as a hatched blastocyst) to the endometrial epithelium. This is followed by invasion of trophectodermal cells (the outer layer of the blastocyst) into the endometrium tissue to facilitate intrauterine development. Small extracellular vesicles (sEVs) released by endometrial epithelial cells during the secretory phase have been shown to facilitate trophoblast invasion; however, the molecular mechanisms that underline this process remain poorly understood. Here, we show that density gradient purified sEVs (1.06-1.11 g/ml, Alix⁺ and TSG101⁺, ∼180 nm) from human endometrial epithelial cells (hormonally primed with estrogen and progesterone vs. estrogen alone) are readily internalized by a human trophectodermal stem cell line and promote their invasion into Matrigel matrix. Mass spectrometry-based proteome analysis revealed that sEVs reprogrammed trophectoderm cell proteome and their cell surface proteome (surfaceome) to support this invasive phenotype through upregulation of pro-invasive regulators associated with focal adhesions (NRP1, PTPRK, ROCK2, TEK), embryo implantation (FBLN1, NIBAN2, BSG), and kinase receptors (EPHB4/B2, ERBB2, STRAP). Kinase substrate prediction highlighted a central role of MAPK3 as an upstream kinase regulating target cell proteome reprogramming. Phosphoproteome analysis pinpointed upregulation of MAPK3 T204/T202 phosphosites in hTSCs following sEV delivery, and that their pharmacological inhibition significantly abrogated invasion. This study provides novel molecular insights into endometrial sEVs orchestrating trophoblast invasion, highlighting the microenvironmental regulation of hTSCs during embryo implantation.

Oestrogen Activates the MAP3K1 Cascade and β-Catenin to Promote Granulosa-like Cell Fate in a Human Testis-Derived Cell Line

Sex determination triggers the differentiation of the bi-potential gonad into either an ovary or testis. In non-mammalian vertebrates, the presence or absence of oestrogen dictates gonad differentiation, while in mammals, this mechanism has been supplanted by the testis-determining gene SRY. Exogenous oestrogen can override this genetic trigger to shift somatic cell fate in the gonad towards ovarian developmental pathways by limiting the bioavailability of the key testis factor SOX9 within somatic cells. Our previous work has implicated the MAPK pathway in mediating the rapid cellular response to oestrogen. We performed proteomic and phosphoproteomic analyses to investigate the precise mechanism through which oestrogen impacts these pathways to activate β-catenin-a factor essential for ovarian development. We show that oestrogen can activate β-catenin within 30 min, concomitant with the cytoplasmic retention of SOX9. This occurs through changes to the MAP3K1 cascade, suggesting this pathway is a mechanism through which oestrogen influences gonad somatic cell fate. We demonstrate that oestrogen can promote the shift from SOX9 pro-testis activity to β-catenin pro-ovary activity through activation of MAP3K1. Our findings define a previously unknown mechanism through which oestrogen can promote a switch in gonad somatic cell fate and provided novel insights into the impacts of exogenous oestrogen exposure on the testis.