Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders

Autism spectrum disorder (ASD) comprises a large group of neurodevelopmental conditions featuring, over a wide range of severity and combinations, a core set of manifestations (restricted sociality, stereotyped behavior and language impairment) alongside various comorbidities. Common and rare variants in several hundreds of genes and regulatory regions have been implicated in the molecular pathogenesis of ASD along a range of causation evidence strength. Despite significant progress in elucidating the impact of few paradigmatic individual loci, such sheer complexity in the genetic architecture underlying ASD as a whole has hampered the identification of convergent actionable hubs hypothesized to relay between the vastness of risk alleles and the core phenotypes. In turn this has limited the development of strategies that can revert or ameliorate this condition, calling for a systems-level approach to probe the cross-talk of cooperating genes in terms of causal interaction networks in order to make convergences experimentally tractable and reveal their clinical actionability. As a first step in this direction, we have captured from the scientific literature information on the causal links between the genes whose variants have been associated with ASD and the whole human proteome. This information has been annotated in a computer readable format in the SIGNOR database and is made freely available in the resource website. To link this information to cell functions and phenotypes, we have developed graph algorithms that estimate the functional distance of any protein in the SIGNOR causal interactome to phenotypes and pathways. The main novelty of our approach resides in the possibility to explore the mechanistic links connecting the suggested gene-phenotype relations.

Inter and intra-tumor heterogeneity of paediatric type diffuse high-grade gliomas revealed by single-cell mass cytometry

Paediatric-type diffuse high-grade gliomas (PDHGG) are aggressive tumors affecting children and young adults, with no effective treatment. These highly heterogeneous malignancies arise in different sites of the Central Nervous System (CNS), carrying distinctive molecular alterations and clinical outcomes (inter-tumor heterogeneity). Moreover, deep cellular and molecular profiling studies highlighted the coexistence of genetically and phenotypically different subpopulations within the same tumor mass (intra-tumor heterogeneity). Despite the recent advances made in the field, the marked heterogeneity of PDHGGs still impedes the development of effective targeted therapies and the identification of suitable biomarkers. In order to fill the existing gap, we used mass cytometry to dissect PDHGG inter- and intra-heterogeneity. This is one of the most advanced technologies of the "-omics" era that, using antibodies conjugated to heavy metals, allows the simultaneous measurement of more than 40 markers at single-cell level. To this end, we analyzed eight PDHGG patient-derived cell lines from different locational and molecular subgroups. By using a panel of 15 antibodies, directly conjugated to metals or specifically customized to detect important histone variants, significant differences were highlighted in the expression of the considered antigens. The single-cell multiparametric approach realized has deepened our understanding of PDHGG, confirming a high degree of intra- and inter-tumoral heterogeneity and identifying some antigens that could represent useful biomarkers for the specific PDHGG locational or molecular subgroups.

SIGNOR 3.0, the SIGnaling network open resource 3.0: 2022 update

The SIGnaling Network Open Resource (SIGNOR 3.0, https://signor.uniroma2.it) is a public repository that captures causal information and represents it according to an 'activity-flow' model. SIGNOR provides freely-accessible static maps of causal interactions that can be tailored, pruned and refined to build dynamic and predictive models. Each signaling relationship is annotated with an effect (up/down-regulation) and with the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the regulation of the target entity. Since its latest release, SIGNOR has undergone a significant upgrade including: (i) a new website that offers an improved user experience and novel advanced search and graph tools; (ii) a significant content growth adding up to a total of approx. 33,000 manually-annotated causal relationships between more than 8900 biological entities; (iii) an increase in the number of manually annotated pathways, currently including pathways deregulated by SARS-CoV-2 infection or involved in neurodevelopment synaptic transmission and metabolism, among others; (iv) additional features such as new model to represent metabolic reactions and a new confidence score assigned to each interaction.

HGG-46. Inter and Intra-tumor Heterogeneity of Pediatric-type Diffuse High-Grade Glioma Revealed by High-Dimensional Single-Cell Proteomics

Paediatric-type diffuse high-grade gliomas (PDHGG) are aggressive brain tumors, affecting children and young adults, with no effective treatments. A main constraint to the development of effective treatment is associated with their highly heterogeneous nature. In order to further dissect their intra and inter tumor heterogeneity, we exploited the mass cytometry technology, an advanced -OMIC approach that, by using metal-tagged antibodies, allows the simultaneous measurement of more than 40 markers, at single-cell level. Here we characterized 8 primary cell lines derived from diffuse pediatric-type high-grade glioma H3-wildtype (DHGG-WT), Diffuse hemispheric glioma H3G34-mutant (DHG-G34) and Diffuse midline glioma H3K27-altered (DMG-K27) patients. The adopted antibody panel was set to recognize antigens expressed by brain and tumor cells, including H3K27M and H3.3G34R variants, and it highlighted important intra- and inter- tumor heterogeneity in the expression of the 16 considered markers. Of these, CD56, CD44, CD29 and NESTIN were more expressed in the hemispheric cell lines, while CD90 was more expressed in the pontine. Even if there was not always a concordance between CyTOF and mRNA expression data from cell lines and tumor samples (e.g. CD90 and GFAP), CyTOF data were in line with the immunohistochemistry analysis for GFAP, whose expression was significantly higher in H3.1K27 compared to H3.3K27. The UMAP analysis allowed us to identify 10 cell clusters, with very minimal overlap between hemispheric and pontine location subgroups and with a peculiar antigenic profile, whose abundance strongly varied according to the mutational subgroups. For example, while the G34 subgroup was enriched for cluster 9 (CD29/CD63/CD56/PDGRFa), the H3.1K27 was enriched for cluster 3 (H3K27M/CD90/CD63/CD56) and cluster 4 (H3K27M/CD63/CD90/CD56/GFAP). In conclusion, single-cell mass cytometry reveals a significant inter and intra-tumoral heterogeneity at protein level, dependent on the molecular alterations. This approach could contribute to the identification of new clinically relevant biomarkers for PDHGG.

A Resource to Infer Molecular Paths Linking Cancer Mutations to Perturbation of Cell Metabolism

Some inherited or somatically-acquired gene variants are observed significantly more frequently in the genome of cancer cells. Although many of these cannot be confidently classified as driver mutations, they may contribute to shaping a cell environment that favours cancer onset and development. Understanding how these gene variants causally affect cancer phenotypes may help developing strategies for reverting the disease phenotype. Here we focus on variants of genes whose products have the potential to modulate metabolism to support uncontrolled cell growth. Over recent months our team of expert curators has undertaken an effort to annotate in the database SIGNOR 1) metabolic pathways that are deregulated in cancer and 2) interactions connecting oncogenes and tumour suppressors to metabolic enzymes. In addition, we refined a recently developed graph analysis tool that permits users to infer causal paths leading from any human gene to modulation of metabolic pathways. The tool grounds on a human signed and directed network that connects ∼8400 biological entities such as proteins and protein complexes via causal relationships. The network, which is based on more than 30,000 published causal links, can be downloaded from the SIGNOR website. In addition, as SIGNOR stores information on drugs or other chemicals targeting the activity of many of the genes in the network, the identification of likely functional paths offers a rational framework for exploring new therapeutic strategies that revert the disease phenotype.

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.

The IntAct database: efficient access to fine-grained molecular interaction data

The IntAct molecular interaction database (https://www.ebi.ac.uk/intact) is a curated resource of molecular interactions, derived from the scientific literature and from direct data depositions. As of August 2021, IntAct provides more than one million binary interactions, curated by twelve global partners of the International Molecular Exchange consortium, for which the IntAct database provides a shared curation and dissemination platform. The IMEx curation policy has always emphasised a fine-grained data and curation model, aiming to capture the relevant experimental detail essential for the interpretation of the provided molecular interaction data. Here, we present recent curation focus and progress, as well as a completely redeveloped website which presents IntAct data in a much more user-friendly and detailed way.

Assembling Disease Networks From Causal Interaction Resources

The development of high-throughput high-content technologies and the increased ease in their application in clinical settings has raised the expectation of an important impact of these technologies on diagnosis and personalized therapy. Patient genomic and expression profiles yield lists of genes that are mutated or whose expression is modulated in specific disease conditions. The challenge remains of extracting from these lists functional information that may help to shed light on the mechanisms that are perturbed in the disease, thus setting a rational framework that may help clinical decisions. Network approaches are playing an increasing role in the organization and interpretation of patients' data. Biological networks are generated by connecting genes or gene products according to experimental evidence that demonstrates their interactions. Till recently most approaches have relied on networks based on physical interactions between proteins. Such networks miss an important piece of information as they lack details on the functional consequences of the interactions. Over the past few years, a number of resources have started collecting causal information of the type protein A activates/inactivates protein B, in a structured format. This information may be represented as signed directed graphs where physiological and pathological signaling can be conveniently inspected. In this review we will (i) present and compare these resources and discuss the different scope in comparison with pathway resources; (ii) compare resources that explicitly capture causality in terms of data content and proteome coverage (iii) review how causal-graphs can be used to extract disease-specific Boolean networks.

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.

Biofabricating murine and human myo-substitutes for rapid volumetric muscle loss restoration

The importance of skeletal muscle tissue is undoubted being the controller of several vital functions including respiration and all voluntary locomotion activities. However, its regenerative capability is limited and significant tissue loss often leads to a chronic pathologic condition known as volumetric muscle loss. Here, we propose a biofabrication approach to rapidly restore skeletal muscle mass, 3D histoarchitecture, and functionality. By recapitulating muscle anisotropic organization at the microscale level, we demonstrate to efficiently guide cell differentiation and myobundle formation both in vitro and in vivo. Of note, upon implantation, the biofabricated myo-substitutes support the formation of new blood vessels and neuromuscular junctions-pivotal aspects for cell survival and muscle contractile functionalities-together with an advanced muscle mass and force recovery. Altogether, these data represent a solid base for further testing the myo-substitutes in large animal size and a promising platform to be eventually translated into clinical scenarios.

SCA-1 micro-heterogeneity in the fate decision of dystrophic fibro/adipogenic progenitors

The term micro-heterogeneity refers to non-genetic cell to cell variability observed in a bell-shaped distribution of the expression of a trait within a population. The contribution of micro-heterogeneity to physiology and pathology remains largely uncharacterised. To address such an issue, we investigated the impact of heterogeneity in skeletal muscle fibro/adipogenic progenitors (FAPs) isolated from an animal model of Duchenne muscular dystrophy (DMD), the mdx mouse. FAPs play an essential role in muscle homoeostasis. However, in pathological conditions or ageing, they are the source of intramuscular infiltrations of fibrotic or adipose tissue. By applying a multiplex flow cytometry assay, we characterised and purified from mdx muscles two FAP cell states expressing different levels of SCA-1. The two cell states are morphologically identical and repopulate each other after several growth cycles. However, they differ in their in vitro behaviour. Cells expressing higher levels of SCA-1 (SCA1-High-FAPs) differentiate more readily into adipocytes while, when exposed to a fibrogenic stimulation, increase the expression of Col1a1 and Timp1 mRNA. A transcriptomic analysis confirmed the adipogenic propensity of SCA1-High-FAPs. In addition, SCA1-High-FAPs proliferate more extensively ex vivo and display more proliferating cells in dystrophic muscles in comparison to SCA1-Low-FAPs. Adipogenesis of both FAP cell states is inhibited in vitro by leucocytes from young dystrophic mice, while leucocytes isolated from aged dystrophic mice are less effective in limiting the adipogenesis of SCA1-High-FAPs suggesting a differential regulatory effect of the microenvironment on micro-heterogeneity. Our data suggest that FAP micro-heterogeneity is modulated in pathological conditions and that this heterogeneity in turn may impact on the behaviour of interstitial mesenchymal cells in genetic diseases.

Towards a unified open access dataset of molecular interactions

The International Molecular Exchange (IMEx) Consortium provides scientists with a single body of experimentally verified protein interactions curated in rich contextual detail to an internationally agreed standard. In this update to the work of the IMEx Consortium, we discuss how this initiative has been working in practice, how it has ensured database sustainability, and how it is meeting emerging annotation challenges through the introduction of new interactor types and data formats. Additionally, we provide examples of how IMEx data are being used by biomedical researchers and integrated in other bioinformatic tools and resources.

Ring Finger Protein 11 acts on ligand-activated EGFR via the direct interaction with the UIM region of ANKRD13 protein family

RING finger protein 11 (RNF11) is an evolutionary conserved Really Interesting New Gene E3 ligase that is overexpressed in several human tumours. Although several reports have highlighted its involvement in crucial cellular processes, the mechanistic details underlying its function are still poorly understood. Utilizing stable isotope labelling by amino acids in culture (SILAC)-based proteomics analysis, we identified 51 proteins that co-immunoprecipitate with wild-type RNF11 and/or with its catalytically inactive mutant. We focused our attention on the interaction of RNF11 with Ankyrin repeat domain-containing protein 13 (ANKRD13)s family. Members of the ANKRD13 family contain ubiquitin-interacting motifs (UIM) that recognize the Lys-63-linked ubiquitin (Ub) chains appended to Epidermal growth factor receptor (EGFR) soon after ligand binding. We show that ANKRD13A, ANKRD13B and ANKRD13D form a complex with RNF11 in vivo and that the UIMs are required for complex formation. However, at odds with the conventional UIM binding mode, Ub modification of RNF11 is not required for the interaction with ANKRD13 proteins. We also show that the interaction between ANKRD13A and RNF11 is modulated by the EGF stimulus and that a complex formed by ANKRD13A, RNF11 and activated EGFR is transiently assembled in the early phases of receptor endocytosis. Moreover, loss of function of the E3 ligases Itchy E3 ubiquitin-protein ligase (ITCH) or RNF11, respectively, abrogates or increases the ubiquitination of endogenous ANKRD13A, affecting its ability to bind activated EGFR. We propose a model whereby the ANKRD13 proteins act as molecular scaffolds that promote the transient formation of a complex between the activated EGFR and the E3 ligases ITCH and RNF11. By regulating the ubiquitination status of ANKRD13A and consequently its endocytic adaptor function, RNF11 promotes sorting of the activated EGFR for lysosomal degradation.

The IMEx Coronavirus interactome: an evolving map of Coronaviridae-Host molecular interactions

The current Coronavirus Disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions enables studying fine-grained resolution of the mechanisms behind the virus biology and the human organism response. Here we present a curated dataset of physical molecular interactions, manually extracted by IMEx Consortium curators focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family. Currently, the dataset comprises over 2,200 binarized interactions extracted from 86 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website ( www.ebi.ac.uk/intact ), and will be continuously updated as research on COVID-19 progresses.

CausalTAB: the PSI-MITAB 2.8 updated format for signalling data representation and dissemination

MOTIVATION

Combining multiple layers of information underlying biological complexity into a structured framework represent a challenge in systems biology. A key task is the formalization of such information in models describing how biological entities interact to mediate the response to external and internal signals. Several databases with signalling information, focus on capturing, organizing and displaying signalling interactions by representing them as binary, causal relationships between biological entities. The curation efforts that build these individual databases demand a concerted effort to ensure interoperability among resources.

RESULTS

Aware of the enormous benefits of standardization efforts in the molecular interaction research field, representatives of the signalling network community agreed to extend the PSI-MI controlled vocabulary to include additional terms representing aspects of causal interactions. Here, we present a common standard for the representation and dissemination of signalling information: the PSI Causal Interaction tabular format (CausalTAB) which is an extension of the existing PSI-MI tab-delimited format, now designated PSI-MITAB 2.8. We define the new term 'causal interaction', and related child terms, which are children of the PSI-MI 'molecular interaction' term. The new vocabulary terms in this extended PSI-MI format will enable systems biologists to model large-scale signalling networks more precisely and with higher coverage than before.

AVAILABILITY AND IMPLEMENTATION

PSI-MITAB 2.8 format and the new reference implementation of PSICQUIC are available online (https://psicquic.github.io/ and https://psicquic.github.io/MITAB28Format.html).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Toward High-Dimensional Single-Cell Analysis of Graphene Oxide Biological Impact: Tracking on Immune Cells by Single-Cell Mass Cytometry

Considering the potential exposure to graphene, the most investigated nanomaterial, the assessment of the impact on human health has become an urgent need. The deep understanding of nanomaterial safety is today possible by high-throughput single-cell technologies. Single-cell mass cytometry (cytometry by time-of flight, CyTOF) shows an unparalleled ability to phenotypically and functionally profile complex cellular systems, in particular related to the immune system, as recently also proved for graphene impact. The next challenge is to track the graphene distribution at the single-cell level. Therefore, graphene oxide (GO) is functionalized with AgInS₂ nanocrystals (GO-In), allowing to trace GO immune-cell interactions via the indium (¹¹⁵ In) channel. Indium is specifically chosen to avoid overlaps with the commercial panels (>30 immune markers). As a proof of concept, the GO-In CyTOF tracking is performed at the single-cell level on blood immune subpopulations, showing the GO interaction with monocytes and B cells, therefore guiding future immune studies. The proposed approach can be applied not only to the immune safety assessment of the multitude of graphene physical and chemical parameters, but also for graphene applications in neuroscience. Moreover, this approach can be translated to other 2D emerging materials and will likely advance the understanding of their toxicology.

Janus effect of glucocorticoids on differentiation of muscle fibro/adipogenic progenitors

Muscle resident fibro-adipogenic progenitors (FAPs), support muscle regeneration by releasing cytokines that stimulate the differentiation of myogenic stem cells. However, in non-physiological contexts (myopathies, atrophy, aging) FAPs cause fibrotic and fat infiltrations that impair muscle function. We set out to perform a fluorescence microscopy-based screening to identify compounds that perturb the differentiation trajectories of these multipotent stem cells. From a primary screen of 1,120 FDA/EMA approved drugs, we identified 34 compounds as potential inhibitors of adipogenic differentiation of FAPs isolated from the murine model (mdx) of Duchenne muscular dystrophy (DMD). The hit list from this screen was surprisingly enriched with compounds from the glucocorticoid (GCs) chemical class, drugs that are known to promote adipogenesis in vitro and in vivo. To shed light on these data, three GCs identified in our screening efforts were characterized by different approaches. We found that like dexamethasone, budesonide inhibits adipogenesis induced by insulin in sub-confluent FAPs. However, both drugs have a pro-adipogenic impact when the adipogenic mix contains factors that increase the concentration of cAMP. Gene expression analysis demonstrated that treatment with glucocorticoids induces the transcription of Gilz/Tsc22d3, an inhibitor of the adipogenic master regulator PPARγ, only in anti-adipogenic conditions. Additionally, alongside their anti-adipogenic effect, GCs are shown to promote terminal differentiation of satellite cells. Both the anti-adipogenic and pro-myogenic effects are mediated by the glucocorticoid receptor and are not observed in the presence of receptor inhibitors. Steroid administration currently represents the standard treatment for DMD patients, the rationale being based on their anti-inflammatory effects. The findings presented here offer new insights on additional glucocorticoid effects on muscle stem cells that may affect muscle homeostasis and physiology.

Metabolic reprogramming of fibro/adipogenic progenitors facilitates muscle regeneration

High-fat diet ameliorates muscle dystrophic phenotype by promoting the FAP-dependent myogenesis of satellite cells.

In Duchenne muscular dystrophy (DMD), the absence of the dystrophin protein causes a variety of poorly understood secondary effects. Notably, muscle fibers of dystrophic individuals are characterized by mitochondrial dysfunctions, as revealed by a reduced ATP production rate and by defective oxidative phosphorylation. Here, we show that in a mouse model of DMD (mdx), fibro/adipogenic progenitors (FAPs) are characterized by a dysfunctional mitochondrial metabolism which correlates with increased adipogenic potential. Using high-sensitivity mass spectrometry–based proteomics, we report that a short-term high-fat diet (HFD) reprograms dystrophic FAP metabolism in vivo. By combining our proteomic dataset with a literature-derived signaling network, we revealed that HFD modulates the β-catenin–follistatin axis. These changes are accompanied by significant amelioration of the histological phenotype in dystrophic mice. Transplantation of purified FAPs from HFD-fed mice into the muscles of dystrophic recipients demonstrates that modulation of FAP metabolism can be functional to ameliorate the dystrophic phenotype. Our study supports metabolic reprogramming of muscle interstitial progenitor cells as a novel approach to alleviate some of the adverse outcomes of DMD.

SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 update

The SIGnaling Network Open Resource 2.0 (SIGNOR 2.0) is a public repository that stores signaling information as binary causal relationships between biological entities. The captured information is represented graphically as a signed directed graph. Each signaling relationship is associated to an effect (up/down-regulation) and to the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the up/down-regulation of the target entity. Since its first release, SIGNOR has undergone a significant content increase and the number of annotated causal interactions have almost doubled. SIGNOR 2.0 now stores almost 23 000 manually-annotated causal relationships between proteins and other biologically relevant entities: chemicals, phenotypes, complexes, etc. We describe here significant changes in curation policy and a new confidence score, which is assigned to each interaction. We have also improved the compliance to the FAIR data principles by providing (i) SIGNOR stable identifiers, (ii) programmatic access through REST APIs, (iii) bioschemas and (iv) downloadable data in standard-compliant formats, such as PSI-MI CausalTAB and GMT. The data are freely accessible and downloadable at https://signor.uniroma2.it/.

CancerGeneNet: linking driver genes to cancer hallmarks

CancerGeneNet (https://signor.uniroma2.it/CancerGeneNet/) is a resource that links genes that are frequently mutated in cancers to cancer phenotypes. The resource takes advantage of a curation effort aimed at embedding a large fraction of the gene products that are found altered in cancer cells into a network of causal protein relationships. Graph algorithms, in turn, allow to infer likely paths of causal interactions linking cancer associated genes to cancer phenotypes thus offering a rational framework for the design of strategies to revert disease phenotypes. CancerGeneNet bridges two interaction layers by connecting proteins whose activities are affected by cancer drivers to proteins that impact on the 'hallmarks of cancer'. In addition, CancerGeneNet annotates curated pathways that are relevant to rationalize the pathological consequences of cancer driver mutations in selected common cancers and 'MiniPathways' illustrating regulatory circuits that are frequently altered in different cancers.

The IMEx coronavirus interactome: an evolving map of Coronaviridae-host molecular interactions

The current coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions can provide fine-grained resolution of the mechanisms behind the virus biology and the human organism response. We present a curated dataset of physical molecular interactions focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family that has been manually extracted by International Molecular Exchange (IMEx) Consortium curators. Currently, the dataset comprises over 4400 binarized interactions extracted from 151 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (https://www.ebi.ac.uk/intact) and will be continuously updated as research on COVID-19 progresses.

HiPPO and PANDA: Two Bioinformatics Tools to Support Analysis of Mass Cytometry Data

High-dimensional mass cytometry (Cytometry by Time-Of-Flight; CyTOF) is a multiparametric single-cell approach that allows for more than 40 parameters to be evaluated simultaneously, opening the possibility to dissect cellular heterogeneity and elucidate functional interactions between different cell types. However, the complexity of these data makes analysis and interpretation daunting. We created High-throughput Population Profiler (HiPPO), a tool that reduces the complexity of the CyTOF data and allows homogeneous clusters of cells to be visualized in an intuitive manner. Each subpopulation is mapped to the Population Analysis Database (PANDA), an open-source, manually curated database containing protein expression profiles for selected markers of primary cells, allowing for cell type abundance in the analyzed samples to be monitored. Custom cell definitions can be submitted for targeted identifications. All cell clusters, regardless of their annotation status, are available for further analyses. HiPPO also conducts nonparametric tests to determine whether differences in protein expression levels between conditions are significant. HiPPO strikes a balance between diagnostic power and computational burden. Its minimal computational footprint allows for subpopulations in a heterogeneous sample to be identified and quantified quickly.

SPV: a JavaScript Signaling Pathway Visualizer

Summary

The visualization of molecular interactions annotated in web resources is useful to offer to users such information in a clear intuitive layout. These interactions are frequently represented as binary interactions that are laid out in free space where, different entities, cellular compartments and interaction types are hardly distinguishable. Signaling Pathway Visualizer is a free open source JavaScript library, which offers a series of pre-defined elements, compartments and interaction types meant to facilitate the representation of signaling pathways consisting of causal interactions without neglecting simple protein–protein interaction networks.

Availability and implementation

Freely available under Apache version 2 license; Source code: https://github.com/Sinnefa/SPV_Signaling_Pathway_Visualizer_v1.0. Language: JavaScript; Web technology: Scalable Vector Graphics; Libraries: D3.js.

Myo-REG: A Portal for Signaling Interactions in Muscle Regeneration

Muscle regeneration is a complex process governed by the interplay between several muscle-resident mononuclear cell populations. Following acute or chronic damage these cell populations are activated, communicate via cell-cell interactions and/or paracrine signals, influencing fate decisions via the activation or repression of internal signaling cascades. These are highly dynamic processes, occurring with distinct temporal and spatial kinetics. The main challenge toward a system level description of the muscle regeneration process is the integration of this plethora of inter- and intra-cellular interactions. We integrated the information on muscle regeneration in a web portal. The scientific content annotated in this portal is organized into two information layers representing relationships between different cell types and intracellular signaling-interactions, respectively. The annotation of the pathways governing the response of each cell type to a variety of stimuli/perturbations occurring during muscle regeneration takes advantage of the information stored in the SIGNOR database. Additional curation efforts have been carried out to increase the coverage of molecular interactions underlying muscle regeneration and to annotate cell-cell interactions. To facilitate the access to information on cell and molecular interactions in the context of muscle regeneration, we have developed Myo-REG, a web portal that captures and integrates published information on skeletal muscle regeneration. The muscle-centered resource we provide is one of a kind in the myology field. A friendly interface allows users to explore, approximately 100 cell interactions or to analyze intracellular pathways related to muscle regeneration. Finally, we discuss how data can be extracted from this portal to support in silico modeling experiments.

DISNOR: a disease network open resource

DISNOR is a new resource that aims at exploiting the explosion of data on the identification of disease-associated genes to assemble inferred disease pathways. This may help dissecting the signaling events whose disruption causes the pathological phenotypes and may contribute to build a platform for precision medicine. To this end we combine the gene-disease association (GDA) data annotated in the DisGeNET resource with a new curation effort aimed at populating the SIGNOR database with causal interactions related to disease genes with the highest possible coverage. DISNOR can be freely accessed at http://DISNOR.uniroma2.it/ where >3700 disease-networks, linking ∼2600 disease genes, can be explored. For each disease curated in DisGeNET, DISNOR links disease genes by manually annotated causal relationships and offers an intuitive visualization of the inferred ‘patho-pathways’ at different complexity levels. User-defined gene lists are also accepted in the query pipeline. In addition, for each list of query genes—either annotated in DisGeNET or user-defined—DISNOR performs a gene set enrichment analysis on KEGG-defined pathways or on the lists of proteins associated with the inferred disease pathways. This function offers additional information on disease-associated cellular pathways and disease similarity.

Lowe syndrome-linked endocytic adaptors direct membrane cycling kinetics with OCRL in Dictyostelium discoideum

Mutations of the inositol 5-phosphatase OCRL cause Lowe syndrome (LS), characterized by congenital cataract, low IQ, and defective kidney proximal tubule resorption. A key subset of LS mutants abolishes OCRL’s interactions with endocytic adaptors containing F&H peptide motifs. Converging unbiased methods examining human peptides and the unicellular phagocytic organism Dictyostelium discoideum reveal that, like OCRL, the Dictyostelium OCRL orthologue Dd5P4 binds two proteins closely related to the F&H proteins APPL1 and Ses1/2 (also referred to as IPIP27A/B). In addition, a novel conserved F&H interactor was identified, GxcU (in Dictyostelium) and the Cdc42-GEF FGD1-related F-actin binding protein (Frabin) (in human cells). Examining these proteins in D. discoideum, we find that, like OCRL, Dd5P4 acts at well-conserved and physically distinct endocytic stations. Dd5P4 functions in coordination with F&H proteins to control membrane deformation at multiple stages of endocytosis and suppresses GxcU-mediated activity during fluid-phase micropinocytosis. We also reveal that OCRL/Dd5P4 acts at the contractile vacuole, an exocytic osmoregulatory organelle. We propose F&H peptide-containing proteins may be key modifiers of LS phenotypes.

CoCUN, a Novel Ubiquitin Binding Domain Identified in N4BP1

Ubiquitin binding domains (UBDs) are modular elements that bind non-covalently to ubiquitin and act as downstream effectors and amplifiers of the ubiquitination signal. With few exceptions, UBDs recognize the hydrophobic path centered on Ile44, including residues Leu8, Ile44, His68, and Val70. A variety of different orientations, which can be attributed to specific contacts between each UBD and surface residues surrounding the hydrophobic patch, specify how each class of UBD specifically contacts ubiquitin. Here, we describe the structural model of a novel ubiquitin-binding domain that we identified in NEDD4 binding protein 1 (N4BP1). By performing protein sequence analysis, mutagenesis, and nuclear magnetic resonance (NMR) spectroscopy of the ¹⁵N isotopically labeled protein, we demonstrate that a Phe-Pro motif in N4BP1 recognizes the canonical hydrophobic patch of ubiquitin. This recognition mode resembles the molecular mechanism evolved in the coupling of ubiquitin conjugation to endoplasmic-reticulum (ER) degradation (CUE) domain family, where an invariant proline, usually following a phenylalanine, is required for ubiquitin binding. Interestingly, this novel UBD, which is not evolutionary related to CUE domains, shares a 40% identity and 47% similarity with cullin binding domain associating with NEDD8 (CUBAN), a protein module that also recognizes the ubiquitin-like NEDD8. Based on these features, we dubbed the region spanning the C-terminal 50 residues of N4BP1 the CoCUN domain, for Cousin of CUBAN. By performing circular dichroism and ¹⁵N NMR chemical shift perturbation of N4BP1 in complex with ubiquitin, we demonstrate that the CoCUN domain lacks the NEDD8 binding properties observed in CUBAN. We also show that, in addition to mediating the interaction with ubiquitin and ubiquitinated substrates, both CUBAN and CoCUN are poly-ubiquitinated in cells. The structural and the functional characterization of this novel UBD can contribute to a deeper understanding of the molecular mechanisms governing N4BP1 function, providing at the same time a valuable tool for clarifying how the discrimination between ubiquitin and the highly related NEDD8 is achieved.

Fibro-adipogenic progenitors of dystrophic mice are insensitive to NOTCH regulation of adipogenesis

Fibro-adipogenic progenitors (FAPs) promote satellite cell differentiation in adult skeletal muscle regeneration. However, in pathological conditions, FAPs are responsible for fibrosis and fatty infiltrations. Here we show that the NOTCH pathway negatively modulates FAP differentiation both in vitro and in vivo. However, FAPs isolated from young dystrophin-deficient mdx mice are insensitive to this control mechanism. An unbiased mass spectrometry-based proteomic analysis of FAPs from muscles of wild-type and mdx mice suggested that the synergistic cooperation between NOTCH and inflammatory signals controls FAP differentiation. Remarkably, we demonstrated that factors released by hematopoietic cells restore the sensitivity to NOTCH adipogenic inhibition in mdx FAPs. These results offer a basis for rationalizing pathological ectopic fat infiltrations in skeletal muscle and may suggest new therapeutic strategies to mitigate the detrimental effects of fat depositions in muscles of dystrophic patients.

CUBAN, a Case Study of Selective Binding: Structural Details of the Discrimination between Ubiquitin and NEDD8

The newly identified CUBAN (Cullin binding domain associating with NEDD8) domain recognizes both ubiquitin and the ubiquitin-like NEDD8. Despite the high similarity between the two molecules, CUBAN shows a clear preference for NEDD8, free and conjugated to cullins. We previously characterized the domain structure, both alone and in complex with NEDD8. The results here reported are addressed to investigate the determinants that drive the selective binding of CUBAN towards NEDD8 and ubiquitin. The ¹⁵N HSQC NMR perturbation pattern of the labeled CUBAN domain, when combined with either NEDD8 or ubiquitin, shows a clear involvement of hydrophobic residues that characterize the early stages of these interactions. After a slow conformational selection step, hydrophobic and then neutral and polar interactions take place, which drive the correct orientation of the CUBAN domain, leading to differences in the recognition scheme of NEDD8 and ubiquitin. As a result, a cascade of induced fit steps seems to determine the structural preference shown for NEDD8 and therefore the basis of the selectivity of the CUBAN domain. Finally, molecular dynamics analysis was performed to determine by fluctuations the internal flexibility of the CUBAN/NEDD8 complex. We consider that our results, based on a structural investigation mainly focused on the early stages of the recognition, provide a fruitful opportunity to report the different behavior of the same protein with two highly similar binding partners.

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

Protein phosphorylation modulates many biological processes. However, the characterization of the complex regulatory circuits underlying cell response to external and internal stimuli is still limited by our inability to describe the phosphorylation network on a global scale. Modern MS-based phosphoproteomics allows monitoring tens of thousands of phosphorylation sites in multiple conditions, making the approach ideal to explore signaling pathways mediated by phosphorylation. Here, we review recent advances in phosphoproteomics and discuss some of the computational approaches developed to facilitate extraction of signaling information from these datasets. Finally, this review focuses on approaches that integrate prior literature information with unbiased phosphoproteomics experiments.

Selectivity of the CUBAN domain in the recognition of ubiquitin and NEDD8

Among the members of the ubiquitin-like (Ubl) protein family, neural precursor cell expressed developmentally down-regulated protein 8 (NEDD8) is the closest in sequence to ubiquitin (57% identity). The two modification mechanisms and their functions, however, are highly distinct and the two Ubls are not interchangeable. A complex network of interactions between modifying enzymes and adaptors, most of which are specific while others are promiscuous, ensures selectivity. Many domains that bind the ubiquitin hydrophobic patch also bind NEDD8 while no domain that specifically binds NEDD8 has yet been described. Here, we report an unbiased selection of domains that bind ubiquitin and/or NEDD8 and we characterize their specificity/promiscuity. Many ubiquitin-binding domains bind ubiquitin preferentially and, to a lesser extent, NEDD8. In a few cases, the affinity of these domains for NEDD8 can be increased by substituting the alanine at position 72 with arginine, as in ubiquitin. We have also identified a unique domain, mapping to the carboxyl end of the protein KHNYN, which has a stark preference for NEDD8. Given its ability to bind neddylated cullins, we have named this domain CUBAN (Cullin-Binding domain Associating with NEDD8). We present here the solution structure of the CUBAN domain both in the isolated form and in complex with NEDD8. The results contribute to the understanding of the discrimination mechanism between ubiquitin and the Ubl. They also provide new insights on the biological role of a ill-defined protein, whose function is hitherto only predicted.

Gene Regulatory Network Modeling of Macrophage Differentiation Corroborates the Continuum Hypothesis of Polarization States

Macrophages derived from monocyte precursors undergo specific polarization processes which are influenced by the local tissue environment: classically activated (M1) macrophages, with a pro-inflammatory activity and a role of effector cells in Th1 cellular immune responses, and alternatively activated (M2) macrophages, with anti-inflammatory functions and involved in immunosuppression and tissue repair. At least three different subsets of M2 macrophages, namely, M2a, M2b, and M2c, are characterized in the literature based on their eliciting signals. The activation and polarization of macrophages is achieved through many, often intertwined, signaling pathways. To describe the logical relationships among the genes involved in macrophage polarization, we used a computational modeling methodology, namely, logical (Boolean) modeling of gene regulation. We integrated experimental data and knowledge available in the literature to construct a logical network model for the gene regulation driving macrophage polarization to the M1, M2a, M2b, and M2c phenotypes. Using the software GINsim and BoolNet, we analyzed the network dynamics under different conditions and perturbations to understand how they affect cell polarization. Dynamic simulations of the network model, enacting the most relevant biological conditions, showed coherence with the observed behavior of in vivo macrophages. The model could correctly reproduce the polarization toward the four main phenotypes as well as to several hybrid phenotypes, which are known to be experimentally associated to physiological and pathological conditions. We surmise that shifts among different phenotypes in the model mimic the hypothetical continuum of macrophage polarization, with M1 and M2 being the extremes of an uninterrupted sequence of states. Furthermore, model simulations suggest that anti-inflammatory macrophages are resilient to shift back to the pro-inflammatory phenotype.

Group I Paks support muscle regeneration and counteract cancer-associated muscle atrophy

BACKGROUND

Skeletal muscle is characterized by an efficient regeneration potential that is often impaired during myopathies. Understanding the molecular players involved in muscle homeostasis and regeneration could help to find new therapies against muscle degenerative disorders. Previous studies revealed that the Ser/Thr kinase p21 protein-activated kinase 1 (Pak1) was specifically down-regulated in the atrophying gastrocnemius of Yoshida hepatoma-bearing rats. In this study, we evaluated the role of group I Paks during cancer-related atrophy and muscle regeneration.

METHODS

We examined Pak1 expression levels in the mouse Tibialis Anterior muscles during cancer cachexia induced by grafting colon adenocarcinoma C26 cells and in vitro by dexamethasone treatment. We investigated whether the overexpression of Pak1 counteracts muscle wasting in C26-bearing mice and in vitro also during interleukin-6 (IL6)-induced or dexamethasone-induced C2C12 atrophy. Moreover, we analysed the involvement of group I Paks on myogenic differentiation in vivo and in vitro using the group I chemical inhibitor IPA-3.

RESULTS

We found that Pak1 expression levels are reduced during cancer-induced cachexia in the Tibialis Anterior muscles of colon adenocarcinoma C26-bearing mice and in vitro during dexamethasone-induced myotube atrophy. Electroporation of muscles of C26-bearing mice with plasmids directing the synthesis of PAK1 preserves fiber size in cachectic muscles by restraining the expression of atrogin-1 and MuRF1 and possibly by inducing myogenin expression. Consistently, the overexpression of PAK1 reduces the dexamethasone-induced expression of MuRF1 in myotubes and increases the phospho-FOXO3/FOXO3 ratio. Interestingly, the ectopic expression of PAK1 counteracts atrophy in vitro by restraining the IL6-Stat3 signalling pathway measured in luciferase-based assays and by reducing rates of protein degradation in atrophying myotubes exposed to IL6. On the other hand, we observed that the inhibition of group I Paks has no effect on myotube atrophy in vitro and is associated with impaired muscle regeneration in vivo and in vitro. In fact, we found that mice treated with the group I inhibitor IPA-3 display a delayed recovery from cardiotoxin-induced muscle injury. This is consistent with in vitro experiments showing that IPA-3 impairs myogenin expression and myotube formation in vessel-associated myogenic progenitors, C2C12 myoblasts, and satellite cells. Finally, we observed that IPA-3 reduces p38α/β phosphorylation that is required to proceed through various stages of satellite cells differentiation: activation, asymmetric division, and ultimately myotube formation.

CONCLUSIONS

Our data provide novel evidence that is consistent with group I Paks playing a central role in the regulation of muscle homeostasis, atrophy and myogenesis.

Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions

BACKGROUND

Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes.

RESULTS

The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal.

CONCLUSIONS

PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download.

Regulation of myoblast differentiation by metabolic perturbations induced by metformin

The metabolic perturbation caused by calorie restriction enhances muscle repair by playing a critical role in regulating satellite cell availability and activity in the muscles of young and old mice. To clarify the underlying mechanisms we asked whether myoblast replication and differentiation are affected by metformin, a calorie restriction-mimicking drug. C2C12, a mouse myoblast cell line, readily differentiate in vitro and fuse to form myotubes. However, when incubated with metformin, C2C12 slow their replication and do not differentiate. Interestingly, lower doses of metformin promote myogenic differentiation. We observe that metformin treatment modulates the expression of cyclins and cyclin inhibitors thereby inducing a cell cycle perturbation that causes a delay in the G2/M transition. The effect of metformin treatment is reversible since after drug withdrawal, myoblasts can re-enter the cell cycle and/or differentiate, depending on culture conditions. Myoblasts cultured under metformin treatment fail to up-regulate MyoD and p21cip1, a key step in cell cycle exit and terminal differentiation. Although the details of the molecular mechanisms underlying the effect of the drug on myoblasts still need to be clarified, we propose that metformin negatively affects myogenic differentiation by inhibiting irreversible exit from the cell cycle through reduction of MyoD and p21cip1 levels.

SIGNOR: A Database of Causal Relationships Between Biological Entities-A Short Guide to Searching and Browsing

SIGNOR (http://signor.uniroma2.it), the SIGnaling Network Open Resource, is a database designed to store experimentally validated causal interactions, i.e., interactions where a source entity has a regulatory effect (up-regulation, down-regulation, etc.) on a second target entity. SIGNOR acts both as a source of signaling information and a support for data analysis, modeling, and prediction. A user-friendly interface features the ability to search entries for any given protein or group of proteins and to display their interactions graphically in a network view. At the time of writing, SIGNOR stores approximately 16,000 manually curated interactions connecting more than 4,000 biological entities (proteins, chemicals, protein complexes, etc.) that play a role in signal transduction. SIGNOR also offers a collection of 37 signaling pathways. SIGNOR can be queried by three search tools: "single-entity" search, "multiple-entity" search, and "pathway" search. This manuscript describes two basic protocols detailing how to navigate and search the SIGNOR database and how to download the annotated dataset for local use. Finally, the support protocol reviews the utilities of the graphic visualizer. © 2017 by John Wiley & Sons, Inc.

Both Intrinsic Substrate Preference and Network Context Contribute to Substrate Selection of Classical Tyrosine Phosphatases

Reversible tyrosine phosphorylation is a widespread post-translational modification mechanism underlying cell physiology. Thus, understanding the mechanisms responsible for substrate selection by kinases and phosphatases is central to our ability to model signal transduction at a system level. Classical protein-tyrosine phosphatases can exhibit substrate specificity in vivo by combining intrinsic enzymatic specificity with the network of protein-protein interactions, which positions the enzymes in close proximity to their substrates. Here we use a high throughput approach, based on high density phosphopeptide chips, to determine the in vitro substrate preference of 16 members of the protein-tyrosine phosphatase family. This approach helped identify one residue in the substrate binding pocket of the phosphatase domain that confers specificity for phosphopeptides in a specific sequence context. We also present a Bayesian model that combines intrinsic enzymatic specificity and interaction information in the context of the human protein interaction network to infer new phosphatase substrates at the proteome level.

Profiling Phosphopeptide-Binding Domain Recognition Specificity Using Peptide Microarrays

Cellular organization and response to internal and external stimuli are mediated by an intricate web of protein interactions. Some of these interactions are regulated by covalent posttranslational modifications such as phosphorylation and acetylation. These modifications can change the chemical nature of the interaction interfaces and modulate the binding affinity of the interacting partners. In signal transduction, the most frequent modification is reversible phosphorylation of tyrosine, serine or threonine residues. Protein phosphorylation may modulate the activity of enzymes by modifying their conformation, or regulate the formation of complexes by creating docking sites to recruit downstream effectors. Families of modular domains, such as SH2, PTB, and 14-3-3, act as "readers" of the modification event. Specificity between closely related domains of the same family is mediated by the chemical properties of the domain binding surface that, aside from offering a hydrophilic pocket for the phosphorylated residue, shows preference for specific sequences. Although the protein structure and the cell context are also important to ensure specificity, the amino acid sequence flanking the phosphorylation site defines the accuracy of the recognition process, and it is therefore essential to define the binding specificity of phosphopeptide binding domains in order to understand and to infer the interaction web mediated by phosphopeptides. Methods commonly used to discover new interactions (such as yeast two hybrid and phage display) are not suited to study interactions with phosphorylated proteins. On the other hand, peptide arrays are a powerful approach to precisely identify the binding preference of phosphopeptide recognition domains. Here we describe a detailed protocol to assemble arrays of hundreds to thousands phospho-peptides and to screen them with any modular domain of interest.

Activation of the Pro-Oxidant PKCβII-p66Shc Signaling Pathway Contributes to Pericyte Dysfunction in Skeletal Muscles of Patients With Diabetes With Critical Limb Ischemia

Critical limb ischemia (CLI), foot ulcers, former amputation, and impaired regeneration are independent risk factors for limb amputation in subjects with diabetes. The present work investigates whether and by which mechanism diabetes negatively impacts on functional properties of muscular pericytes (MPs), which are resident stem cells committed to reparative angiomyogenesis. We obtained muscle biopsy samples from patients with diabetes who were undergoing major limb amputation and control subjects. Diabetic muscles collected at the rim of normal tissue surrounding the plane of dissection showed myofiber degeneration, fat deposition, and reduction of MP vascular coverage. Diabetic MPs (D-MPs) display ultrastructural alterations, a differentiation bias toward adipogenesis at the detriment of myogenesis and an inhibitory activity on angiogenesis. Furthermore, they have an imbalanced redox state, with downregulation of the antioxidant enzymes superoxide dismutase 1 and catalase, and activation of the pro-oxidant protein kinase C isoform β-II (PKCβII)-dependent p66^Shc signaling pathway. A reactive oxygen species scavenger or, even more effectively, clinically approved PKCβII inhibitors restore D-MP angiomyogenic activity. Inhibition of the PKCβII-dependent p66^Shc signaling pathway could represent a novel therapeutic approach for the promotion of muscle repair in individuals with diabetes.

The cell-autonomous mechanisms underlying the activity of metformin as an anticancer drug

The biguanide drug metformin profoundly affects cell metabolism, causing an impairment of the cell energy balance and triggering a plethora of pleiotropic effects that vary depending on the cellular or environmental context. Interestingly, a decade ago, it was observed that metformin-treated diabetic patients have a significantly lower cancer risk. Although a variety of in vivo and in vitro observations emphasising the role of metformin as anticancer drug have been reported, the underlying mechanisms are still poorly understood. Here, we discuss our current understanding of the molecular mechanisms that are perturbed by metformin treatment and that might be relevant to understand its antitumour activities. We focus on the cell-autonomous mechanisms modulating growth and death of cancer cells.

Deep Proteomics of Breast Cancer Cells Reveals that Metformin Rewires Signaling Networks Away from a Pro-growth State

Metformin is the most frequently prescribed drug for type 2 diabetes. In addition to its hypoglycemic effects, metformin also lowers cancer incidence. This anti-cancer activity is incompletely understood. Here, we profiled the metformin-dependent changes in the proteome and phosphoproteome of breast cancer cells using high-resolution mass spectrometry. In total, we quantified changes of 7,875 proteins and 15,813 phosphosites after metformin changes. To interpret these datasets, we developed a generally applicable strategy that overlays metformin-dependent changes in the proteome and phosphoproteome onto a literature-derived network. This approach suggested that metformin treatment makes cancer cells more sensitive to apoptotic stimuli and less sensitive to pro-growth stimuli. These hypotheses were tested in vivo; as a proof-of-principle, we demonstrated that metformin inhibits the p70S6K-rpS6 axis in a PP2A-phosphatase dependent manner. In conclusion, analysis of deep proteomics reveals both detailed and global mechanisms that contribute to the anti-cancer activity of metformin.

Tools and data services registry: a community effort to document bioinformatics resources

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.

Here we present a community-driven curation effort, supported by ELIXIR—the European infrastructure for biological information—that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.

As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.

SIGNOR: a database of causal relationships between biological entities

Assembly of large biochemical networks can be achieved by confronting new cell-specific experimental data with an interaction subspace constrained by prior literature evidence. The SIGnaling Network Open Resource, SIGNOR (available on line at http://signor.uniroma2.it), was developed to support such a strategy by providing a scaffold of prior experimental evidence of causal relationships between biological entities. The core of SIGNOR is a collection of approximately 12,000 manually-annotated causal relationships between over 2800 human proteins participating in signal transduction. Other entities annotated in SIGNOR are complexes, chemicals, phenotypes and stimuli. The information captured in SIGNOR can be represented as a signed directed graph illustrating the activation/inactivation relationships between signalling entities. Each entry is associated to the post-translational modifications that cause the activation/inactivation of the target proteins. More than 4900 modified residues causing a change in protein concentration or activity have been curated and linked to the modifying enzymes (about 351 human kinases and 94 phosphatases). Additional modifications such as ubiquitinations, sumoylations, acetylations and their effect on the modified target proteins are also annotated. This wealth of structured information can support experimental approaches based on multi-parametric analysis of cell systems after physiological or pathological perturbations and to assemble large logic models.

Alterations in the phosphoproteomic profile of cells expressing a non-functional form of the SHP2 phosphatase

The phosphatase SHP-2 plays an essential role in growth factor signaling and mutations in its locus is the cause of congenital and acquired pathologies. Mutations of SHP-2 are known to affect the activation of the RAS pathway. Gain-of-function mutations cause the Noonan syndrome, the most common non-chromosomal congenital disorder. In order to obtain a holistic picture of the intricate regulatory mechanisms underlying SHP-2 physiology and pathology, we set out to characterize perturbations of the cell phosphorylation profile caused by an altered localization of SHP-2. To describe the proteins whose activity may be directly or indirectly modulated by SHP-2 activity, we identified tyrosine peptides that are differentially phosphorylated in wild type SHP-2 cells and isogenic cells expressing a non-functional SHP-2 variant that cannot dephosphorylate the physiological substrates due to a defect in cellular localization upon growth factor stimulation. By an iTRAQ based strategy coupled to mass spectrometry, we have identified 63 phosphorylated tyrosine residues in 53 different proteins whose phosphorylation is affected by SHP-2 activity. Some of these confirm already established regulatory mechanisms while many others suggest new possible signaling routes that may contribute to the modulation of the ERK and p38 pathways by SHP-2. Interestingly many new proteins that we found to be regulated by SHP-2 activity are implicated in the formation and regulation of focal adhesions.