Combining Phosphoproteomics Datasets and Literature Information to Reveal the Functional Connections in a Cell Phosphorylation Network

Multiplexed Profiling of CDK Kinase Activities in Tumor Biopsies with Fluorescent Peptide Biosensors

Detection of disease biomarkers constitutes a major challenge for the development of personalized and predictive diagnostics as well as companion assays. Protein kinases (PKs) involved in the coordination of cell cycle progression and proliferation that are hyperactivated in human cancers constitute attractive pharmacological targets and relevant biomarkers. Although it is relatively straightforward to assess the relative abundance of PKs in a biological sample, there is not always a direct correlation with enzymatic activity, which is regulated by several posttranslational mechanisms. Studies of relative abundance therefore convey limited information, and the lack of selective, sensitive, and standardized tools together with the inherent complexity of biological samples makes it difficult to quantify PK activities in physio-pathological tissues. To address this challenge, we have developed a toolbox of fluorescent biosensors that report on CDK activities in a sensitive, selective, dose-dependent, and quantitative fashion, which we have implemented to profile CDK activity signatures in cancer cell lines and biopsies from human tumors. In this study, we report on a standardized and calibrated biosensing approach to quantify CDK1,2,4, and 6 activities simultaneously through a combination of four different biosensors in a panel of 40 lung adenocarcinoma and 40 follicular lymphoma samples. CDK activity profiling highlighted two major patterns which were further correlated with age, sex of patients, tumor size, grade, and genetic and immunohistochemical features of the biopsies. Multiplex CDKACT biosensing technology provides new and complementary information relative to current genetic and immunohistochemical characterization of tumor biopsies, which will be useful for diagnostic purposes, potentially guiding therapeutic decision. These fluorescent peptide biosensors offer promise for personalized diagnostics based on kinase activity profiling.

Shining Light on Protein Kinase Biomarkers with Fluorescent Peptide Biosensors

Protein kinases (PKs) are established gameplayers in biological signalling pathways, and a large body of evidence points to their dysregulation in diseases, in particular cancer, where rewiring of PK networks occurs frequently. Fluorescent biosensors constitute attractive tools for probing biomolecules and monitoring dynamic processes in complex samples. A wide variety of genetically encoded and synthetic biosensors have been tailored to report on PK activities over the last decade, enabling interrogation of their function and insight into their behaviour in physiopathological settings. These optical tools can further be used to highlight enzymatic alterations associated with the disease, thereby providing precious functional information which cannot be obtained through conventional genetic, transcriptomic or proteomic approaches. This review focuses on fluorescent peptide biosensors, recent developments and strategies that make them attractive tools to profile PK activities for biomedical and diagnostic purposes, as well as insights into the challenges and opportunities brought by this unique toolbox of chemical probes.

SIGNORApp: a Cytoscape 3 application to access SIGNOR data

SUMMARY

SIGNORApp is a Cytoscape 3 (3.8 and later) application that provides access to causal interactions annotated in the SIGNOR resource. The application builds networks that can be represented as weighted, signed, directed graphs, where nodes are interacting biological entities and edges represent causal interactions captured by expert curators from experiments reported in peer reviewed journals. Users can query the SIGNOR dataset with (i) single or multiple entity name(s) or identifier(s) and optionally they may require to include in the output network their interacting partners, (ii) browse pathways that are annotated in the SIGNOR resource and (iii) extract the entire causal interactome. The app offers two visualizations modes: one only displaying entity interactions and a second emphasizing the post-translational modifications occurring as a consequence of the interaction. In addition, users can click on nodes and edges to access entity and interaction annotations. Causal information is available for three model organisms: Homo sapiens, Mus musculus and Rattus norvegicus.

AVAILABILITY AND IMPLEMENTATION

SIGNORApp has been developed for Cytoscape 3 (3.8 and later) in the Java programming language. The latest source code and the plugin can be found at: https://github.com/SIGNORcysAPP/signor-app and https://apps.cytoscape.org/apps/signorapp, respectively.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Using Multilayer Heterogeneous Networks to Infer Functions of Phosphorylated Sites

Mass spectrometry-based quantitative phosphoproteomics has become an essential approach in the study of cellular processes such as signaling. Commonly used methods to analyze phosphoproteomics datasets depend on generic, gene-centric annotations such as Gene Ontology terms, which do not account for the function of a protein in a particular phosphorylation state. Analysis of phosphoproteomics data is hampered by a lack of phosphorylated site-specific annotations. We propose a method that combines shotgun phosphoproteomics data, protein-protein interactions, and functional annotations into a heterogeneous multilayer network. Phosphorylation sites are associated to potential functions using a random walk on the heterogeneous network (RWHN) algorithm. We validated our approach against a model of the MAPK/ERK pathway and functional annotations from PhosphoSitePlus and were able to associate differentially regulated sites on the same proteins to their previously described specific functions. We further tested the algorithm on three previously published datasets and were able to reproduce their experimentally validated conclusions and to associate phosphorylation sites with known functions based on their regulatory patterns. Our approach provides a refinement of commonly used analysis methods and accurately predicts context-specific functions for sites with similar phosphorylation profiles.

Measuring pathway database coverage of the phosphoproteome

Protein phosphorylation is one of the best known post-translational mechanisms playing a key role in the regulation of cellular processes. Over 100,000 distinct phosphorylation sites have been discovered through constant improvement of mass spectrometry based phosphoproteomics in the last decade. However, data saturation is occurring and the bottleneck of assigning biologically relevant functionality to phosphosites needs to be addressed. There has been finite success in using data-driven approaches to reveal phosphosite functionality due to a range of limitations. The alternate, more suitable approach is making use of prior knowledge from literature-derived databases. Here, we analysed seven widely used databases to shed light on their suitability to provide functional insights into phosphoproteomics data. We first determined the global coverage of each database at both the protein and phosphosite level. We also determined how consistent each database was in its phosphorylation annotations compared to a global standard. Finally, we looked in detail at the coverage of each database over six experimental datasets. Our analysis highlights the relative strengths and weaknesses of each database, providing a guide in how each can be best used to identify biological mechanisms in phosphoproteomic data.

Combining Mass Spectrometry-Based Phosphoproteomics with a Network-Based Approach to Reveal FLT3-Dependent Mechanisms of Chemoresistance

FLT3 mutations are the most frequently identified genetic alterations in acute myeloid leukemia (AML) and are associated with poor clinical outcome, relapse and chemotherapeutic resistance. Elucidating the molecular mechanisms underlying FLT3-dependent pathogenesis and drug resistance is a crucial goal of biomedical research. Given the complexity and intricacy of protein signaling networks, deciphering the molecular basis of FLT3-driven drug resistance requires a systems approach. Here we discuss how the recent advances in mass spectrometry (MS)-based (phospho) proteomics and multiparametric analysis accompanied by emerging computational approaches offer a platform to obtain and systematically analyze cell-specific signaling networks and to identify new potential therapeutic targets.

A metal oxide affinity probe derived from MIL-125 for selective enrichment of endogenous phosphopeptides

Highly effective enrichment of endogenous phosphopeptides from complex biological samples is an essential and crucial theme in the analysis of phosphopeptidomics. Herein, an ordered mesoporous TiO₂/C composite (denoted as Ti-MCM) was prepared by the pyrolysis of MIL-125 under a N₂ atmosphere. The obtained Ti-MCM possesses a high specific surface area (165 m² g^-1), a uniform pore size (3.75 nm), and a large amount of Ti (46%). By utilizing the selective chelation between Ti-MCM and phosphopeptides, 25 phosphopeptides were detected in α-casein digest after enrichment. The material shows good selectivity even in the presence of 2000-fold excess of interference peptides. It was also used to enrich endogenous phosphopeptides from the complex samples of human serum and saliva and showed a good performance.

A Resource for the Network Representation of Cell Perturbations Caused by SARS-CoV-2 Infection

The coronavirus disease 2019 (COVID-19) pandemic has caused more than 2.3 million casualties worldwide and the lack of effective treatments is a major health concern. The development of targeted drugs is held back due to a limited understanding of the molecular mechanisms underlying the perturbation of cell physiology observed after viral infection. Recently, several approaches, aimed at identifying cellular proteins that may contribute to COVID-19 pathology, have been reported. Albeit valuable, this information offers limited mechanistic insight as these efforts have produced long lists of cellular proteins, the majority of which are not annotated to any cellular pathway. We have embarked in a project aimed at bridging this mechanistic gap by developing a new bioinformatic approach to estimate the functional distance between a subset of proteins and a list of pathways. A comprehensive literature search allowed us to annotate, in the SIGNOR 2.0 resource, causal information underlying the main molecular mechanisms through which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and related coronaviruses affect the host-cell physiology. Next, we developed a new strategy that enabled us to link SARS-CoV-2 interacting proteins to cellular phenotypes via paths of causal relationships. Remarkably, the extensive information about inhibitors of signaling proteins annotated in SIGNOR 2.0 makes it possible to formulate new potential therapeutic strategies. The proposed approach, which is generally applicable, generated a literature-based causal network that can be used as a framework to formulate informed mechanistic hypotheses on COVID-19 etiology and pathology.

Reconstructing kinase network topologies from phosphoproteomics data reveals cancer-associated rewiring

Understanding how oncogenic mutations rewire regulatory-protein networks is important for rationalizing the mechanisms of oncogenesis and for individualizing anticancer treatments. We report a chemical phosphoproteomics method to elucidate the topology of kinase-signaling networks in mammalian cells. We identified >6,000 protein phosphorylation sites that can be used to infer >1,500 kinase-kinase interactions and devised algorithms that can reconstruct kinase network topologies from these phosphoproteomics data. Application of our methods to primary acute myeloid leukemia and breast cancer tumors quantified the relationship between kinase expression and activity, and enabled the identification of hitherto unknown kinase network topologies associated with drug-resistant phenotypes or specific genetic mutations. Using orthogonal methods we validated that PIK3CA wild-type cells adopt MAPK-dependent circuitries in breast cancer cells and that the kinase TTK is important in acute myeloid leukemia. Our phosphoproteomic signatures of network circuitry can identify kinase topologies associated with both phenotypes and genotypes of cancer cells.

Proteomics of Long-Lived Mammals

Mammalian species differ up to 100-fold in their aging rates and maximum lifespans. Long-lived mammals appear to possess traits that extend lifespan and healthspan. Genomic analyses have not revealed a single pro-longevity function that would account for all longevity effects. In contrast, it appears that pro-longevity mechanisms may be complex traits afforded by connections between metabolism and protein functions that are impossible to predict by genomic approaches alone. Thus, metabolomics and proteomics studies will be required to understand the mechanisms of longevity. Several examples are reviewed that demonstrate the naked mole rat (NMR) shows unique proteomic signatures that contribute to longevity by overcoming several hallmarks of aging. SIRT6 is also discussed as an example of a protein that evolves enhanced enzymatic function in long-lived species. Finally, it is shown that several longevity-related proteins such as Cip1/p21, FOXO3, TOP2A, AKT1, RICTOR, INSR, and SIRT6 harbor posttranslational modification (PTM) sites that preferentially appear in either short- or long-lived species and provide examples of crosstalk between PTM sites. Prospects of enhancing lifespan and healthspan of humans by altering metabolism and proteoforms with drugs that mimic changes observed in long-lived species are discussed.

Proteomic Analysis Reveals Anti-Fibrotic Effects of Blue Light Photobiomodulation on Fibroblasts

BACKGROUND AND OBJECTIVES

This study was aimed at determining the effects of blue light photobiomodulation on primary adult mouse dermal fibroblasts (AMDFs) and the associated signaling pathways.

STUDY DESIGN/MATERIALS AND METHODS

Cultured AMDFs from adult C57BL/6 mice were irradiated by blue light from a light-emitting diode (wavelength = 463 ± 50 nm; irradiance = 5 mW/cm² ; energy density = 4-8 J/cm² ). The cells were analyzed using mass spectrometry for proteomics/phosphoproteomics, AlamarBlue assay for mitochondrial activity, time-lapse video for cell migration, quantitative polymerase chain reaction for gene expression, and immunofluorescence for protein expression.

RESULTS

Proteomic/phosphoproteomic analysis showed inhibition of extracellular signal-regulated kinases/mammalian target of rapamycin and casein kinase 2 pathways, cell motility-related networks, and multiple metabolic processes, including carbon metabolism, biosynthesis of amino acid, glycolysis/gluconeogenesis, and the pentose phosphate pathway. Functional analysis demonstrated inhibition of mitochondrial activities, cell migration, and mitosis. Expression of growth promoting insulin-like growth factor 1 and fibrosis-related genes, including transforming growth factor β1 (TGFβ1) and collagen type 1 ɑ2 chain diminished. Protein expression of α-smooth muscle actin, an important regulator of myofibroblast functions, was also suppressed.

CONCLUSIONS

Low-level blue light exerted suppressive effects on AMDFs, including suppression of mitochondrial activity, metabolism, cell motility, proliferation, TGFβ1 levels, and collagen I production. Low-level blue light can be a potential treatment for the prevention and reduction of tissue fibrosis, such as hypertrophic scar and keloids. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

Fshb Knockout Mouse Model, Two Decades Later and Into the Future

In 1997, nearly 20 years ago, we reported the phenotypes of follicle-stimulating hormone (FSH) β (Fshb) null mice. Since then, these mice have been useful for various physiological and genetic studies in reproductive and skeletal biology. In a 2009 review titled "FSHβ Knockout Mouse Model: A Decade Ago and Into the Future," I summarized the need for and what led to the development of an FSH-deficient mouse model and its applications, including delineation of the emerging extragonadal roles of FSH in bone cells by using this genetic model. These studies opened up exciting avenues of research on osteoporosis and now extend into those on adiposity in postmenopausal women. Here, I summarize the progress made with this mouse model since 2009 with regard to FSH rerouting in vivo, deciphering the role of N-glycosylation on FSHβ, roles of FSH in somatic-germ cell interactions in gonads, and provide a road map that is anticipated to emerge in the near future. Undoubtedly, the next 10 years should be an even more exciting time to explore the fertile area of FSH biology and its implications for basic and clinical reproductive physiology research.