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Caspase-8 is a cysteine protease that plays an essential role in apoptosis. Consistently with its canonical proapoptotic function, cancer cells may genetically or epigenetically downregulate its expression. Unexpectedly, Caspase-8 is often retained in cancer, suggesting the presence of alternative mechanisms that may be exploited by cancer cells to their own benefit. In this regard, we reported that Src tyrosine kinase, which is aberrantly activated in many tumors, promotes Caspase-8 phosphorylation on Tyrosine 380 (Y380) preventing its full activation. Here, we investigated the significance of Caspase-8 expression and of its phosphorylation on Y380 in glioblastoma, a brain tumor where both Caspase-8 expression and Src activity are often aberrantly upregulated. Transcriptomic analyses identified inflammatory response as a major target of Caspase-8, and in particular, NFκB signaling as one of the most affected pathways. More importantly, we could show that Src-dependent phosphorylation of Caspase-8 on Y380 drives the assembly of a multiprotein complex that triggers NFκB activation, thereby inducing the expression of inflammatory and pro-angiogenic factors. Remarkably, phosphorylation on Y380 sustains neoangiogenesis and resistance to radiotherapy. In summary, our work identifies a novel interplay between Src kinase and Caspase-8 that allows cancer cells to hijack Caspase-8 to sustain tumor growth.

The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies (CVs) for the proteomics community and other fields supported by mass spectrometry since its inception 20 years ago. Here we describe the general operation of the PSI, including its leadership, working groups, yearly workshops, and the document process by which proposals are thoroughly and publicly reviewed in order to be ratified as PSI standards. We briefly describe the current state of the many existing PSI standards, some of which remain the same as when originally developed, some of which have undergone subsequent revisions, and some of which have become obsolete. Then the set of proposals currently being developed are described, with an open call to the community for participation in the forging of the next generation of standards. Finally, we describe some synergies and collaborations with other organizations and look to the future in how the PSI will continue to promote the open sharing of data and thus accelerate the progress of the field of proteomics.

Collectively, rare genetic disorders affect a substantial portion of the world’s population. In most cases, those affected face difficulties in receiving a clinical diagnosis and genetic characterization. The understanding of the molecular mechanisms of these diseases and the development of therapeutic treatments for patients are also challenging. However, the application of recent advancements in genome sequencing/analysis technologies and computer-aided tools for predicting phenotype-genotype associations can bring significant benefits to this field. In this review, we highlight the most relevant online resources and computational tools for genome interpretation that can enhance the diagnosis, clinical management, and development of treatments for rare disorders. Our focus is on resources for interpreting single nucleotide variants. Additionally, we present use cases for interpreting genetic variants in clinical settings and review the limitations of these results and prediction tools. Finally, we have compiled a curated set of core resources and tools for analyzing rare disease genomes. Such resources and tools can be utilized to develop standardized protocols that will enhance the accuracy and effectiveness of rare disease diagnosis.

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.

Background Analyses of the genomic variation in the western Mediterranean population are being used to reveal its evolutionary history and to understand the molecular basis of particular diseases. Aim To observe β-thalassemic mutational spectrum in western Andalusia, Spain, in the context of the Mediterranean. In addition, associations between disease and neutral gene variants within the β-globin gene (HBB) were also evaluated. Subjects and methods This study included 63 unrelated individuals diagnosed with β-thalassemia. In addition, 97 unrelated, healthy subjects of the same territory were also analysed as proxies of the normal genetic background. Allele associations and population genetic structure analyses were performed using different methodologies. Results Data have revealed a rather restricted spectrum of β-thalassemia mutations in the analysed sample. Although the detected variants fit well with the Mediterranean pattern, certain singularities support a structure of some specific β-thalassemia alleles. The IVSI-1 (G > A) shows a strong regionalisation. The spatial correlogram revealed a typically narrow wave structure, presumably linked to genetic isolation and genetic drift. Conclusions The long history of endemic malaria in the study territory, the rather high consanguinity rates among its autochthonous population, and other demographic features have been used here to understand the western Andalusian β-thalassemia molecular portrait.

About one-quarter of the euchromatic portion of the male-specific region of the human Y chromosome consists of large duplicated sequences that are organized in eight palindromes (termed P1–P8), which undergo arm-to arm gene conversion, a proposed mechanism for maintaining their sequence integrity. Although the relevance of gene conversion in the evolution of palindromic sequences has been profoundly recognized, the dynamic of this mechanism is still nuanced. To shed light into the evolution of these genomic elements, we performed a high-depth (50×) targeted next-generation sequencing of the palindrome P6 in 157 subjects belonging to the most divergent evolutionary lineages of the Y chromosome. We found 118 new paralogous sequence variants, which were placed into the context of a robust Y chromosome phylogeny based on 7240 SNPs of the X-degenerate region. We mapped along the phylogeny 80 gene conversion events that shaped the diversity of P6 arms during recent human history. In contrast to previous studies, we demonstrated that arm-to-arm gene conversion, which occurs at a rate of 6.01 × 10 −6 conversions/base/year, is not biased toward the retention of the ancestral state of sequences. We also found a significantly lower mutation rate of the arms (6.18 × 10−10 mutations/base/year) compared with the spacer (9.16 × 10−10 mutations/base/year), a finding that may explain the observed higher inter-species conservation of arms, without invoking any bias of conversion. Finally, by formally testing the mutation/conversion balance in P6, we found that the arms of this palindrome reached a steady-state equilibrium between mutation and gene conversion.

Chemotherapy regimens and radiotherapy are common strategies to fight cancer. In women, these therapies may cause side effects such as premature ovarian insufficiency (POI) and infertility. Clinical strategies to protect the ovarian reserve from the lethal effect of cancer therapies needs better understanding of the mechanisms underlying iatrogenic loss of follicle reserve. Recent reports demonstrate a critical role for p53 and CHK2 in the oocyte response to different DNA stressors, which are commonly used to treat cancer. Here we review the molecular mechanisms underlying the DNA damage stress response (DDR) and discuss crosstalk between DDR and signaling pathways implicated in primordial follicle activation.

Forensic DNA phenotyping (FDP) provides the ability to predict the human external traits from unknown sample donors, directly from minute amounts of DNA found at the crime scene. We developed a MPS multiplex assay, with the aim of genotyping all 41 DNA markers included in the HIrisPlex-S system for simultaneous prediction of eye, hair and skin colours. Forensic samples such as blood, skeletal remains, touch DNA, saliva swab, artificially degraded samples together with individuals with known phenotypes and a set of 2800 M control DNA were sequenced on the Ion Torrent platform in order to evaluate the concordance testing results and the forensic suitability of the 41-plex MPS assay. The panel was evaluated by testing a different number of PCR cycles and the volume of reagents for library preparation. The study demonstrated that full and reliable profiles were obtained with 0.1–5 ng, even with high degraded DNA. The increment of the number of PCR cycles results in an improvement of correctly genotyping and phenotyping for samples with low amounts of degraded DNA but higher frequencies of artefacts were found. The high DNA degradation level did not influence the correct genotyping and phenotyping and the critical parameter affecting the result is the quantity of input DNA. Eye and hair colour was predicted in 92.60% of individuals and skin colour in 85.15% of individuals. The results suggest that this MPS assay is robust, highly sensitive and useful for human pigmentation prediction in the forensic genetic field.

Selective degradation of the endoplasmic reticulum (ER) via autophagy (ER-phagy) is initiated by ER-phagy receptors, which facilitate the incorporation of ER fragments into autophagosomes. FAM134 reticulon family proteins (FAM134A, FAM134B, and FAM134C) are ER-phagy receptors with structural similarities and nonredundant functions. Whether they respond differentially to the stimulation of ER-phagy is unknown. Here, we describe an activation mechanism unique to FAM134C during starvation. In fed conditions, FAM134C is phosphorylated by casein kinase 2 (CK2) at critical residues flanking the LIR domain. Phosphorylation of these residues negatively affects binding affinity to the autophagy proteins LC3. During starvation, mTORC1 inhibition limits FAM134C phosphorylation by CK2, hence promoting receptor activation and ER-phagy. Using a novel tool to study ER-phagy in vivo and FAM134C knockout mice, we demonstrated the physiological relevance of FAM134C phosphorylation during starvation-induced ER-phagy in liver lipid metabolism. These data provide a mechanistic insight into ER-phagy regulation and an example of autophagy selectivity during starvation. We thank G. Diez Roux and P. Ashley-Norman for critical reading of the manuscript. We thank the microscopy, MS, advanced histopathology, and FACS facilities at TIGEM Institute. We thank E. Nusco for helping us with AAV injections. Funding: This work was supported by European Research Council (ERC) (714551), Telethon intramural grants, and Associazione Italiana per la Ricerca sul Cancro (AIRC) (IG 2015 Id 17717) (to C.S.) and Telethon Foundation (TMPGCBX16TT), AFM Telethon (Trampoline Grant), and AIRC (MFAG-2020-24856) (to P.G.). G.D.L. is a recipient of AIRC fellowship “Francesco Alicino” (25407). V.L. acknowledges funding from the ERC (101001784), the Italian MIUR-PRIN 2017 (2017FJZZRC), and the Swiss National Supercomputing Center (CSCS) (project ID u8). The work of A.S. was supported by the German Research Foundation DFG (SFB1177/2 and WO210/20-2) and the Dr. Rolf M. Schwiete Stiftung (13/2017). A.E. is supported by the RETOS projects Programme of Spanish Ministry of Science, Innovation and Universities, Spanish State Research Agency (grants SAF2015-67538-R and PID2019-104012RB-I00), and the ERC (638891). A.B.P.-G. is a recipient of Ph.D. fellowship from MICIU/AEI (BES-2017-081381). A.R. is a recipient of Umberto Veronesi Foundation postdoctoral fellowship. Author contributions: G.D.L. and F.I. performed most of the experiments. F.I. and A.B.P.-G. performed in vivo experiments. M.M. performed mutagenesis experiments. S.A. and V.L. performed LC3-FAM134C binding analysis. C.P.Q.M. performed in vitro phosphorylation assays. L.C. analyzed CK2 substrate phosphorylation. F.S., A.P., C.C., and A.S. analyzed proteomic data. G.N. provided critical suggestions. A.R. performed proteomic experiments. A.E. supervised in vivo experiments. M.R., L.A.P., and O.M. supervised CK2 experiments. C.S. designed the study. P.G. and C.S. conceived and supervised the experiments. C.S., P.G., V.L., and M.R. wrote the paper. G.D.L. and F.I. prepared the figures. All the authors read the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Sí

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.

The human MSY ampliconic region is mainly composed of large duplicated sequences that are organized in eight palindromes (termed P1–P8), and may undergo arm-to-arm gene conversion. Although the importance of these elements is widely recognized, their evolutionary dynamics are still nuanced. Here, we focused on the P8 palindrome, which shows a complex evolutionary history, being involved in intra- and inter-chromosomal gene conversion. To disclose its evolutionary complexity, we performed a high-depth (50×) targeted next-generation sequencing of this element in 157 subjects belonging to the most divergent lineages of the Y chromosome tree. We found a total of 72 polymorphic paralogous sequence variants that have been exploited to identify 41 Y-Y gene conversion events that occurred during recent human history. Through our analysis, we were able to categorize P8 arms into three portions, whose molecular diversity was modelled by different evolutionary forces. Notably, the outer region of the palindrome is not involved in any gene conversion event and evolves exclusively through the action of mutational pressure. The inner region is affected by Y-Y gene conversion occurring at a rate of 1.52 × 10−5 conversions/base/year, with no bias towards the retention of the ancestral state of the sequence. In this portion, GC-biased gene conversion is counterbalanced by a mutational bias towards AT bases. Finally, the middle region of the arms, in addition to intra-chromosomal gene conversion, is involved in X-to-Y gene conversion (at a rate of 6.013 × 10−8 conversions/base/year) thus being a major force in the evolution of the VCY/VCX gene 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.

Objectives The 3' regulatory region of the immunoglobulin heavy chain gene (IGH) includes the HS1.2 enhancer displaying length polymorphism with four known variants. The goal of the research was to provide an overview of this variability and of its evolutionary significance across human populations. Materials and methods We compiled published and original data on HS1.2 polymorphism in 3,100 subjects from 26 human populations. Moreover, we imputed the haplotypic arrangement of the HS1.2 region in the 1000 Genomes Project (1KGP). In this dataset, imputation could also be obtained for the G1m-G3m allotype by virtue of the precise correspondence between serological types and amino acid (and DNA) substitutions in IGHG1 and IGHG3. Results HS1.2 variant frequencies displayed similar patterns of continental partitioning as those reported in the literature for the physically neighboring IGHG1-IGHG3 system. The 1KGP data revealed that linkage disequilibrium (LD) can explain the spread of joint HS1.2-IGHG1-IGHG3 associations across continents and within continental populations, with stronger LD out of Africa and the features of an evolutionarily stable genomic block with differential expression in lymphoblastoid cell lines. Discussion Strong population structuring involves at least the entire 70 kb genomic region here considered, due to the tight LD which maintained HS1.2, IGHG1, and IGHG3 in nonrandom arrangements. This might be key to better understand the evolutionary path of the entire genomic region driven by immune response capabilities, during the formation of continental gene pools.

The insertion site of the internal tandem duplications (ITDs) in the FLT3 gene affects the sensitivity to tyrosine kinase inhibitors (TKIs) therapy in acute myeloid leukemia (AML). Patients with the ITD in the tyrosine kinase domain lack effective therapeutic options. Here, to identify genotype-driven strategies increasing the TKI therapy efficacy, we developed SignalingProfiler, a strategy supporting the integration of high-sensitive mass spectrometry-based (phospho)proteomics, RNA sequencing datasets with literature-derived signaling networks. The approach generated FLT3-ITD genotype-specific predictive models and revealed a conserved role of the WEE1-CDK1 axis in TKIs resistance. Remarkably, pharmacological inhibition of the WEE1 kinase synergizes and strengthens the pro-apoptotic effect of TKIs therapy in cell lines and patient-derived primary blasts. Finally, we propose a new molecular mechanism of TKIs resistance in AML and suggest the combination of WEE1 inhibitor and TKI as a therapeutic option to improve patients clinical outcome.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes. We acknowledge the support of the developers of PhenoTips, which was used in the past by RD-Connect and NeurOmics as the primary tool to collate phenotypic data. We would also like to thank the leaders and members of the Instituto Nacional de Bioinformática (INB) and ELIXIR for their support and collaboration throughout the years. RD-Connect (RD-Connect, an integrated platform connecting registries, biobanks, and clinical bioinformatics) received funding from the Seventh Framework (FP7) Programme of the European Union under grant agreement No 305444. Data were analyzed using the RD-Connect GPAP, which received funding from EU projects Solve-RD, EJP-RD (grant numbers H2020 779257, H2020 825575), Instituto de Salud Carlos III (Grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática, INB), ELIXIR-EXCELERATE (Grant number EU H2020 #676559) and ELIXIR Implementation Studies (Remote real-time visualization of human rare disease genomics data (RD-Connect) stored at the EGA ELIXIR. 2017-2018; ELIXIR IT-2017-INTEGRATION, Rare Disease Infrastructure ELIXIR, 2019-2020 and the Beacon ELIXIR, 2019-2021). The RD-Connect GPAP has leveraged developments funded through project VEIS (001-P-001647 co-financed by the European Regional Development Fund of the European Union in the framework of the Operational Program FEDER of Catalonia 2014-2020 with the support of the Secretaria d'Universitats i Recerca del Departament d'Empresa i Coneixement de la Generalitat de Catalunya) and URD-Cat (PERIS SLT002/16/00174, Departament de Salut, Generalitat de Catalunya). The research leading to these results has received funding from Consequitur (Newton Fund UK/Turkey, MR/N027302/1), BBMRI-LPC (EU FP7 #313010), NeurOmics (EU FP7 #305121), the Economic Development Department of the Navarra Government (Grant number 001114112017), the European Reference Network for Rare Neurological Diseases (Project ID number 739510) and NIH, National Institute of Child Health and Human Development (1R01HD103805-01). We acknowledge the support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Program/Generalitat de Catalunya. We also acknowledge the support of the Generalitat de Catalunya through Departament de Salut and Departament d'Empresa i Coneixement and Co-financing by the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) with funds from the European Regional Development Fund (ERDF) corresponding to the 2014-2020 Smart Growth Operating Program. HL receives support from the Canadian Institutes of Health Research (Foundation Grant FDN-167281), the Canadian Institutes of Health Research and Muscular Dystrophy Canada (Network Catalyst Grant for NMD4C), the Canada Foundation for Innovation (CFI-JELF 38412), and the Canada Research Chairs program (Canada Research Chair in Neuromuscular Genomics and Health, 950-232279).

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.

Kinship recognition between anonymous DNA samples is becoming a relevant issue in forensics, more so with the increasing number of DNA profiles in databanks. Also, NGS-based genotyping is being increasingly used in routine personal identification, to simultaneously type large numbers of markers of different kind. In the present work, we explored computationally and experimentally the performance of the ForenSeq™ DNA Signature Prep Kit in identifying the true relationship between two anonymous samples, distinguishing it from other possible relationships. We analyzed with Familias R series of 10,000 pairs with 9 different simulated relationships, corresponding to different degrees of autosomal sharing. For each pair we obtained likelihood ratios for five kinship hypotheses vs. unrelatedness, and used their ranking to identify the preferred relationship. We also typed 21 subjects from two pedigrees, representing from parent-child to 4th cousins relationships. As expected, the power for identifying the true relationship decays in the order of autosomal sharing. Parent-child and full siblings can be robustly identified against other relationships. For half-siblings the chance of reaching a significant conclusion is already small. For more distant relationships the proportion of cases correctly and significantly identified is 10% or less. Bidirectional errors in kinship attribution include the suggestion of relatedness when this does not exist (10–50%), and the suggestion of independence in pairs of individuals more than 4 generations apart (25–60%). The real cases revealed a relevant effect of genotype miscalling at some loci, which could only be partly avoided by modulating the analysis parameters. In conclusion, with the exception of first degree relatives, the kit can be useful to inform additional investigations, but does not usually provide probatory results.

Cancer cells frequently exhibit dysregulation of the DNA damage response (DDR), genomic instability, and altered RNA metabolism. Recent genome-wide studies have strongly suggested an interaction between the pathways involved in the cellular response to DDR and in the regulation of RNA metabolism, but the molecular mechanism(s) involved in this crosstalk are largely unknown. Herein, we found that activation of the DDR kinase ATM promotes its interaction with Sam68, leading to phosphorylation of this multifunctional RNA binding protein (RBP) on three residues: threonine 61, serine 388 and serine 390. Moreover, we demonstrate that ATM-dependent phosphorylation of threonine 61 promotes the function of Sam68 in the DDR pathway and enhances its RNA processing activity. Importantly, ATM-mediated phosphorylation of Sam68 in prostate cancer cells modulates alternative polyadenylation of transcripts that are targets of Sam68, supporting the notion that the ATM–Sam68 axis exerts a multifaceted role in the response to DNA damage. Thus, our work validates Sam68 as an ATM kinase substrate and uncovers an unexpected bidirectional interplay between ATM and Sam68, which couples the DDR pathway to modulation of RNA metabolism in response to genotoxic stress.

The improper use of antibiotics by humans may promote the dissemination of resistance in wildlife. The persistence and spread of acquired antibiotic resistance and human-associated bacteria in the environment, while representing a threat to wildlife, can also be exploited as a tool to monitor the extent of human impact, particularly on endangered animal species. Hence, we investigated both the associated enterobacterial species and the presence of acquired resistance traits in the cloacal microbiota of the critically endangered lesser Antillean iguana (Iguana delicatissima), by comparing two separate populations living in similar climatic conditions but exposed to different anthropic pressures. A combination of techniques, including direct plating, DNA sequencing and antimicrobial susceptibility testing allowed us to characterize the dominant enterobacterial populations, the antibiotic resistant strains and their profiles. A higher frequency of Escherichia coli was found in the samples from the more anthropized site, where multi-drug resistant strains were also isolated. These results confirm how human-associated bacteria as well as their antibiotic-resistance determinants may be transferred to wildlife, which, in turn, may act as a reservoir of antibiotic resistance.

PubMed: 31209238, The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells. © 2019, The Author(s)., National Institute for Health Research, NIHR Wellcome Trust, WT: 102696, 206194 Magyar Tudományos Akadémia, MTA Bayer 668858 PrECISE AstraZeneca, We thank the Genomics of Drug Sensitivity in Cancer and COSMIC teams at the Wellcome Trust Sanger Institute for help with the preparation of the molecular data, Denes Turei for help with Omnipath, and Katjusa Koler for help with matching drug names across combination screens. We thank AstraZeneca for funding and provision of data to the DREAM Consortium to run the challenge, and funding from the European Union Horizon 2020 research (under grant agreement No 668858 PrECISE to J.S.R.), the Joint Research Center for Computational Biomedicine (which is partially funded by Bayer AG) to J.S.R., National Institute for Health Research (NIHR) Sheffield Biomedical Research Center, Premium Postdoctoral Fellowship Program of the Hungarian Academy of Sciences. M.G lab is supported by Wellcome Trust (102696 and 206194)., Competing interests: K.C.B., Z.G., G.Y.D., E.K.Y.T., S.F., and J.R.D. are AstraZeneca employees. K.C.B., Z.G., E.K.Y.T., S.F., and J.R.D. are AstraZeneca shareholders. Y.G. receives personal compensation from Eli Lilly and Company, is a shareholder of Cleerly, Inc., and Ann Arbor Algorithms, Inc. M.G. receives research funding from AstraZeneca and has performed consultancy for Sanofi. The remaining authors declare no competing interests.

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.

The geography of southern Iberia and an abundant archaeological record of human occupation are ideal conditions for a full understanding of scenarios of genetic history in the area. Recent advances in the phylogeography of Y-chromosome lineages offer the opportunity to set upper bounds for the appearance of different genetic components.To provide a global knowledge on the Y haplogroups observed in Andalusia with their Y microsatellite variation. Preferential attention is given to the vehement debate about the age, origin and expansion of R1b-M269 clade and sub-lineages.Four hundred and fourteen male DNA samples from western and eastern autochthonous Andalusians were genotyped for a set of Y-SNPs and Y-STRs. Gene diversity, potential population genetic structures and coalescent times were assessed.Most of the analysed samples belong to the European haplogroup R1b1a1a2-M269, whereas haplogroups E, J, I, G and T show lower frequencies. A phylogenetic dissection of the R1b-M269 was performed and younger time frames than those previously reported in the literature were obtained for its sub-lineages.The particular Andalusian R1b-M269 assemblage confirms the shallow topology of the clade. Moreover, the sharing of lineages with the rest of Europe indicates the impact in Iberia of an amount of pre-existing diversity, with the possible exception of R1b-DF27. Lineages such as J2-M172 and G-M201 highlight the importance of maritime travels of early farmers who reached the Iberian Peninsula.

Repurposing of drugs for new therapeutic use has received considerable attention for its potential to reduce time and cost of drug development. Here we present a new strategy to identify chemicals that are likely to induce differentiation of leukemic cells. As Acute Myeloid Leukemia (AML) is the result of a block in myeloid differentiation, finding new drugs that are capable of inducing blast terminal maturation is considered a valuable strategy. We used data from the Connectivity Map (CMap) to identify drugs that could be repositioned for their potential to activate transcription factors that mediate myeloid differentiation. Compounds promoting the activation of transcription factors that play a positive role in myeloid differentiation were considered candidate pro-differentiation drugs. This approach yielded a list of chemicals ranked according to the potential to activate transcription factors that induce differentiation of leukemic progenitor cells. Drugs that are already used in differentiation therapy, such as for instance all-trans retinoic acid (ATRA) are in the top positions of this ranked list. To validate our strategy, we tested thein vitrodifferentiation potential of 22 candidate compounds using the HL-60 human cell line as a myeloid differentiation model. Ten out of 22 compounds, ranking high in the inferred list, were confirmed to induce significant differentiation of HL-60. Some of these compounds are known to trigger the DNA damage response, thus identifying this process as a target to modulate myeloid differentiation. These results underscore the potential of our approach to accelerate the drug discovery process. The method that we have developed is highly versatile and it can be adapted to different drug repurposing projects.

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.

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various steps in the knowledge management process that focuses on understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to standardize and update existing knowledge management workflows and involve end-users in the process of designing the Gene Regulation Knowledge Commons (GRKC). Here the GREEKC consortium describes its main achievements in improving this GRKC. info:eu-repo/semantics/publishedVersion

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.

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.

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.

The denitrosylase S‐nitrosoglutathione reductase (GSNOR) has been suggested to sustain mitochondrial removal by autophagy (mitophagy), functionally linking S‐nitrosylation to cell senescence and aging. In this study, we provide evidence that GSNOR is induced at the translational level in response to hydrogen peroxide and mitochondrial ROS. The use of selective pharmacological inhibitors and siRNA demonstrates that GSNOR induction is an event downstream of the redox‐mediated activation of ATM, which in turn phosphorylates and activates CHK2 and p53 as intermediate players of this signaling cascade. The modulation of ATM/GSNOR axis, or the expression of a redox‐insensitive ATM mutant influences cell sensitivity to nitrosative and oxidative stress, impairs mitophagy and affects cell survival. Remarkably, this interplay modulates T‐cell activation, supporting the conclusion that GSNOR is a key molecular effector of the antioxidant function of ATM and providing new clues to comprehend the pleiotropic effects of ATM in the context of immune function., Hydrogen peroxide and pro‐oxidant conditions activate ATM via oxidation of Cys2991. The resulting phospho‐signal activates CHK2 and p53 and culminates in enhanced translation of the denitrosylase GSNOR to sustain mitophagy and protect the cells against oxidative stress.

Cancer treatments can often adversely affect the quality of life of young women. One of the most relevant negative impacts is the loss of fertility. Cyclophosphamide is one of the most detrimental chemotherapeutic drugs for the ovary. Cyclophosphamide may induce the destruction of dormant follicles while promoting follicle activation and growth. Herein, we demonstrate the in vivo protective effect of the allosteric Bcr-Abl tyrosine kinase inhibitor Asciminib on signaling pathways activated by cyclophosphamide in mouse ovaries. We also provide evidence that Asciminib does not interfere with the cytotoxic effect of cyclophosphamide in Michigan Cancer Foundation (MCF)7 breast cancer cells. Our data indicate that concomitant administration of Asciminib mitigates the cyclophosphamide-induced ovarian reserve loss without affecting the anticancer potential of cyclophosphamide. Taken together, these observations are relevant for the development of effective ferto-protective adjuvants to preserve the ovarian reserve from the damaging effects of cancer therapies.

Contains fulltext : 232394.pdf (Publisher’s version ) (Closed access) We evaluated the association between germline genetic variants located within the 3'-untranlsated region (polymorphic 3'UTR, ie, p3UTR) of candidate genes involved in multiple myeloma (MM). We performed a case-control study within the International Multiple Myeloma rESEarch (IMMEnSE) consortium, consisting of 3056 MM patients and 1960 controls recruited from eight countries. We selected p3UTR of six genes known to act in different pathways relevant in MM pathogenesis, namely KRAS (rs12587 and rs7973623), VEGFA (rs10434), SPP1 (rs1126772), IRF4 (rs12211228) and IL10 (rs3024496). We found that IL10-rs3024496 was associated with increased risk of developing MM and with a worse overall survival of MM patients. The variant allele was assayed in a vector expressing eGFP chimerized with the IL10 3'-UTR and it was found functionally active following transfection in human myeloma cells. In this experiment, the A-allele caused a lower expression of the reporter gene and this was also in agreement with the in vivo expression of mRNA measured in whole blood as reported in the GTEx portal. Overall, these data are suggestive of an effect of the IL10-rs3024496 SNP on the regulation of IL10 mRNA expression and it could have clinical implications for better characterization of MM patients in terms of prognosis.

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., The IMEx consortium provides one of the largest resources of curated, experimentally verified molecular interaction data. Here, the authors review how IMEx evolved into a fundamental resource for life scientists and describe how IMEx data can support biomedical research.

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.

Increasing evidence suggests a strong interplay between autophagy and genomic stability. Recently, several papers have demonstrated a molecular connection between the DNA Damage Response (DDR) and autophagy and have explored how this link influences cell fate and the choice between apoptosis and senescence in response to different stimuli. The aberrant deregulation of this interplay is linked to the development of pathologies, including cancer and neurodegeneration. Ataxia-telangiectasia mutated kinase (ATM) is the product of a gene that is lost in Ataxia-Telangiectasia (A-T), a rare genetic disorder characterized by ataxia and cerebellar neurodegeneration, defects in the immune response, higher incidence of lymphoma development, and premature aging. Importantly, ATM kinase plays a central role in the DDR, and it can finely tune the balance between senescence and apoptosis: activated ATM promotes autophagy and in particular sustains the lysosomal-mitochondrial axis, which in turn promotes senescence and inhibits apoptosis. Therefore, ATM is the key factor that enables cells to escape apoptosis by entering senescence through modulation of autophagy. Importantly, unlike apoptotic cells, senescent cells are viable and have the ability to secrete proinflammatory and mitogenic factors, thus influencing the cellular environment. In this review we aim to summarize recent advances in the understanding of molecular mechanisms linking DDR and autophagy to senescence, pointing out the role of ATM kinase in these cellular responses. The significance of this regulation in the pathogenesis of Ataxia-Telangiectasia will be discussed.

Background: The compilation of a list of genetic modifiers in Alzheimer’s disease (AD) is an open research field. The GABAergic system is affected in several neurological disorders but its role in AD is largely understudied. Objective/Methods: As an explorative study, we considered variants in genes of GABA catabolism (ABAT, ALDH5A1, AKR7A2), and APOE in 300 Italian patients and 299 controls. We introduce a recent multivariate method to take into account the individual APOE genotype, thus controlling for the effect of the discrepant allele distributions in cases versus controls. We add a genotype-phenotype analysis based on age at onset and the Mini-Mental State Evaluation score. Results: On the background of strongly divergent APOE allele distributions in AD versus controls, two genotypic interactions that represented a subtle but significant peculiarity of the AD cohort emerged. The first is between ABAT and APOE, and the second between some ALDH5A1 genotypes and APOE. Decreased SSADH activity is predicted in AD carriers of APOE ɛ4, representing an additional suggestion for increased oxidative damage. Conclusion: We identified a difference between AD and controls, not in a shift of the allele frequencies at genes of the GABA catabolism pathway, but rather in gene interactions peculiar of the AD cohort. The emerging view is that of a multifactorial contribution to the disease, with a main risk factor (APOE), and additional contributions by the variants here considered. We consider genes of the GABA degradation pathway good candidates as modifiers of AD, contributing to energy impairment in AD brain.

Lysosomal degradation of the endoplasmic reticulum (ER) via autophagy (ER‐phagy) is emerging as a critical regulator of cell homeostasis and function. The recent identification of ER‐phagy receptors has shed light on the molecular mechanisms underlining this process. However, the signaling pathways regulating ER‐phagy in response to cellular needs are still largely unknown. We found that the nutrient responsive transcription factors TFEB and TFE3—master regulators of lysosomal biogenesis and autophagy—control ER‐phagy by inducing the expression of the ER‐phagy receptor FAM134B. The TFEB/TFE3‐FAM134B axis promotes ER‐phagy activation upon prolonged starvation. In addition, this pathway is activated in chondrocytes by FGF signaling, a critical regulator of skeletal growth. FGF signaling induces JNK‐dependent proteasomal degradation of the insulin receptor substrate 1 (IRS1), which in turn inhibits the PI3K‐PKB/Akt‐mTORC1 pathway and promotes TFEB/TFE3 nuclear translocation and enhances FAM134B transcription. Notably, FAM134B is required for protein secretion in chondrocytes, and cartilage growth and bone mineralization in medaka fish. This study identifies a new signaling pathway that allows ER‐phagy to respond to both metabolic and developmental cues., Nuclear translocation of TFEB/TFE3 transcription factors and expression of FAM134B downstream of FGF18 signalling induce ER‐phagy in chondrocytes to promote bone development.

The interstitial space surrounding the skeletal muscle fibers is populated by a variety of mononuclear cell types. Upon acute or chronic insult, these cell populations become activated and initiate finely-orchestrated crosstalk that promotes myofiber repair and regeneration. Mass cytometry is a powerful and highly multiplexed technique for profiling single-cells. Herein, it was used to dissect the dynamics of cell populations in the skeletal muscle in physiological and pathological conditions. Here, we characterized an antibody panel that could be used to identify most of the cell populations in the muscle interstitial space. By exploiting the mass cytometry resolution, we provided a comprehensive picture of the dynamics of the major cell populations that sensed and responded to acute damage in wild type mice and in a mouse model of Duchenne muscular dystrophy. In addition, we revealed the intrinsic heterogeneity of many of these cell populations.

Glioblastoma multiforme (GBM) is a severe brain tumor whose ability to mutate and adapt to therapies is at the base for the extremely poor survival rate of patients. Despite multiple efforts to develop alternative forms of treatment, advances have been disappointing and GBM remains an arduous tumor to treat. One of the leading causes for its strong resistance is the innate upregulation of DNA repair mechanisms. Since standard therapy consists of a combinatory use of ionizing radiation and alkylating drugs, which both damage DNA, targeting the DNA damage response (DDR) is proving to be a beneficial strategy to sensitize tumor cells to treatment. In this review, we will discuss how recent progress in the availability of the DDR kinase inhibitors will be key for future therapy development. Further, we will examine the principal existing DDR inhibitors, with special focus on those currently in use for GBM clinical trials.

Succinate semialdehyde dehydrogenase (SSADH) is a mitochondrial enzyme, encoded by ALDH5A1, mainly involved in &gamma, aminobutyric acid (GABA) catabolism and energy supply of neuronal cells, possibly contributing to antioxidant defense. This study aimed to further investigate the antioxidant role of SSADH, and to verify if common SNPs of ALDH5A1 may affect SSADH activity, stability, and mitochondrial function. In this study, we used U87 glioblastoma cells as they represent a glial cell line. These cells were transiently transfected with a cDNA construct simultaneously harboring three SNPs encoding for a triple mutant (TM) SSADH protein (p.G36R/p.H180Y/p.P182L) or with wild type (WT) cDNA. SSADH activity and protein level were measured. Cell viability, lipid peroxidation, mitochondrial morphology, membrane potential (&Delta, &Psi, ), and protein markers of mitochondrial stress were evaluated upon Paraquat treatment, in TM and WT transfected cells. TM transfected cells show lower SSADH protein content and activity, fragmented mitochondria, higher levels of peroxidized lipids, and altered &Delta, than WT transfected cells. Upon Paraquat treatment, TM cells show higher cell death, lipid peroxidation, 4-HNE protein adducts, and lower &Delta, than WT transfected cells. These results reinforce the hypothesis that SSADH contributes to cellular antioxidant defense, furthermore, common SNPs may produce unstable, less active SSADH, which could per se negatively affect mitochondrial function and, under oxidative stress conditions, fail to protect mitochondria.

Glioblastoma multiforme (GBM) is one of the most recalcitrant brain tumors characterized by a tumor microenvironment (TME) that strongly supports GBM growth, aggressiveness, invasiveness, and resistance to therapy. Importantly, a common feature of GBM is the aberrant activation of receptor tyrosine kinases (RTKs) and of their downstream signaling cascade, including the non-receptor tyrosine kinase SRC. SRC is a central downstream intermediate of many RTKs, which triggers the phosphorylation of many substrates, therefore, promoting the regulation of a wide range of different pathways involved in cell survival, adhesion, proliferation, motility, and angiogenesis. In addition to the aforementioned pathways, SRC constitutive activity promotes and sustains inflammation and metabolic reprogramming concurring with TME development, therefore, actively sustaining tumor growth. Here, we aim to provide an updated picture of the molecular pathways that link SRC to these events in GBM. In addition, SRC targeting strategies are discussed in order to highlight strengths and weaknesses of SRC inhibitors in GBM management, focusing our attention on their potentialities in combination with conventional therapeutic approaches (i.e., temozolomide) to ameliorate therapy effectiveness.

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.

Blastocystis spp. is a common single-celled intestinal symbiont, comprising several genetic subtypes (ST) and transmissible by animal-to-animal, human-to-human, animal-to-human and, possibly, human-to-animal routes. This work was designed to explore the presence of Blastocystis in sympatric domestic and wild suids and their ability to carry zoonotic STs, in a condition of widespread opportunity to come in contact with the microorganism through their shared water and food resources, and other carriers. We sampled 42 and 37 stool samples from wild boars and domestic pigs, respectively. STs were first identified by PCR followed by Sanger sequencing. Sequences represented in double-band PCR products or in Sanger chromatograms displaying multiple peaks, were resolved by next generation sequencing (NGS). Twenty-six (61.9%) wild boar and 26 (70.2%) pig samples were PCR-positive, respectively. ST3, ST5 and ST15 were found in 3.8%, 38.4% and 80.8% of the positive wild boars and 11.5%, 88.5%, 11.5% of the positive pigs, respectively. ST1 was found only in pigs (3.8%). STs 5 and 15 were common in both groups of animals, but in reversed proportions, suggesting preferential colonization. We found significantly different ST distributions among wild boars and domestic pigs. This might indicate that lifestyle differences between the two populations influence their risk for contracting certain subtypes, or that ST5 and ST15 can colonize preferentially wild or domestic animals. Based on the STs described here, wild boars and domestic pigs can act as reservoirs with zoonotic potential. The ability of suids to carry zoonotic STs appears to be higher when using NGS than Sanger sequencing, and resolution of complex sequencing profiles is imperative before excluding the presence of STs of human concern.

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.

Epidermal Growth Factor receptor (EGFR) is a tyrosine kinase receptor widely expressed on the surface of numerous cell types, which activates several downstream signalling pathways involved in cell proliferation, migration and survival. EGFR alterations, such as overexpression or mutations, have been frequently observed in several cancers, including glioblastoma (GBM), and are associated to uncontrolled cell proliferation. Here we show that the inhibition of mammalian target of Rapamycin (mTOR) mediates EGFR delivery to lysosomes for degradation in GBM cells, independently of autophagy activation. Coherently with EGFR internalisation and degradation, mTOR blockade negatively affects the mitogen activated protein/extracellular signal-regulated kinase (MAPK)/ERK pathway. Furthermore, we provide evidence that Src kinase activation is required for EGFR internaliation upon mTOR inhibition. Our results further support the hypothesis that mTOR targeting may represent an effective therapeutic strategy in GBM management, as its inhibition results in EGFR degradation and in proliferative signal alteration.

The Molecular INTeractions Database (MINT) is a public database designed to store information about protein interactions. Protein interactions are extracted from scientific literature and annotated in the database by expert curators. Currently (October 2019), MINT contains information on more than 26,000 proteins and more than 131,600 interactions in over 30 model organisms. This article provides protocols for searching MINT over the Internet, using the new MINT Web Page. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Searching MINT over the internet Alternate Protocol: MINT visualizer Basic Protocol 2: Submitting interaction data.