Biophysics education section and computational training discussion at VII Congress of Russian Biophysicists.

We present commentaries on the section "Biophysical education" of the VII Congress of Russian Biophysicists. Presentations are briefly introduced along with the current problems of biophysical education and the educational approach development. We discuss educational course on bioinformatics based on the integration of online databases and the usage of internet platforms for functional annotation of genes and proteins.

Bioinformatics tools for the sequence complexity estimates.

We review current methods and bioinformatics tools for the text complexity estimates (information and entropy measures). The search DNA regions with extreme statistical characteristics such as low complexity regions are important for biophysical models of chromosome function and gene transcription regulation in genome scale. We discuss the complexity profiling for segmentation and delineation of genome sequences, search for genome repeats and transposable elements, and applications to next-generation sequencing reads. We review the complexity methods and new applications fields: analysis of mutation hotspots loci, analysis of short sequencing reads with quality control, and alignment-free genome comparisons. The algorithms implementing various numerical measures of text complexity estimates including combinatorial and linguistic measures have been developed before genome sequencing era. The series of tools to estimate sequence complexity use compression approaches, mainly by modification of Lempel-Ziv compression. Most of the tools are available online providing large-scale service for whole genome analysis. Novel machine learning applications for classification of complete genome sequences also include sequence compression and complexity algorithms. We present comparison of the complexity methods on the different sequence sets, the applications for gene transcription regulatory regions analysis. Furthermore, we discuss approaches and application of sequence complexity for proteins. The complexity measures for amino acid sequences could be calculated by the same entropy and compression-based algorithms. But the functional and evolutionary roles of low complexity regions in protein have specific features differing from DNA. The tools for protein sequence complexity aimed for protein structural constraints. It was shown that low complexity regions in protein sequences are conservative in evolution and have important biological and structural functions. Finally, we summarize recent findings in large scale genome complexity comparison and applications for coronavirus genome analysis.

Medical Genetics, Genomics and Bioinformatics-2022.

The analysis of molecular mechanisms of disease progression challenges the development of bioinformatics tools and omics data integration [...].

AP-HP Health Data Space (AHDS) to the Test of the Covid-19 Pandemic.

Sharing observational and interventional health data within a common data space enables university hospitals to leverage such data for biomedical discovery and moving towards a learning health system. OBJECTIVE: To describe the AP-HP Health Data Space (AHDS) and the IT services supporting piloting, research, innovation and patient care. METHODS: Built on three pillars - governance and ethics, technology and valorization - the AHDS and its major component, the Clinical Data Warehouse (CDW) have been developed since 2015. RESULTS: The AP-HP CDW has been made available at scale to AP-HP both healthcare professionals and public or private partners in January 2017. Supported by an institutional secured and high-performance cloud and an ecosystem of tools, mostly open source, the AHDS integrates a large amount of massive healthcare data collected during care and research activities. As of December 2021, the AHDS operates the electronic data capture for almost +840 clinical trials sponsored by AP-HP, the CDW is enabling the processing of health data from more than 11 million patients and generated +200 secondary data marts from IRB authorized research projects. During the Covid-19 pandemic, AHDS has had to evolve quickly to support administrative professionals and caregivers heavily involved in the reorganization of both patient care and biomedical research. CONCLUSION: The AP-HP Data Space is a key facilitator for data-driven evidence generation and making the health system more efficient and personalized.

Statistical estimates of multiple transcription factors binding in the model plant genomes based on ChIP-seq data.

The development of high-throughput genomic sequencing coupled with chromatin immunoprecipitation technologies allows studying the binding sites of the protein transcription factors (TF) in the genome scale. The growth of data volume on the experimentally determined binding sites raises qualitatively new problems for the analysis of gene expression regulation, prediction of transcription factors target genes, and regulatory gene networks reconstruction. Genome regulation remains an insufficiently studied though plants have complex molecular regulatory mechanisms of gene expression and response to environmental stresses. It is important to develop new software tools for the analysis of the TF binding sites location and their clustering in the plant genomes, visualization, and the following statistical estimates. This study presents application of the analysis of multiple TF binding profiles in three evolutionarily distant model plant organisms. The construction and analysis of non-random ChIP-seq binding clusters of the different TFs in mammalian embryonic stem cells were discussed earlier using similar bioinformatics approaches. Such clusters of TF binding sites may indicate the gene regulatory regions, enhancers and gene transcription regulatory hubs. It can be used for analysis of the gene promoters as well as a background for transcription networks reconstruction. We discuss the statistical estimates of the TF binding sites clusters in the model plant genomes. The distributions of the number of different TFs per binding cluster follow same power law distribution for all the genomes studied. The binding clusters in Arabidopsis thaliana genome were discussed here in detail.

Glioblastoma gene network reconstruction and ontology analysis by online bioinformatics tools.

Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.

Initializing a hospital-wide data quality program. The AP-HP experience.

BACKGROUND AND OBJECTIVES: Data Quality (DQ) programs are recognized as a critical aspect of new-generation research platforms using electronic health record (EHR) data for building Learning Healthcare Systems. The AP-HP Clinical Data Repository aggregates EHR data from 37 hospitals to enable large-scale research and secondary data analysis. This paper describes the DQ program currently in place at AP-HP and the lessons learned from two DQ campaigns initiated in 2017. MATERIALS AND METHODS: As part of the AP-HP DQ program, two domains - patient identification (PI) and healthcare services (HS) - were selected for conducting DQ campaigns consisting of 5 phases: defining the scope, measuring, analyzing, improving and controlling DQ. Semi-automated DQ profiling was conducted in two data sets - the PI data set containing 8.8 M patients and the HS data set containing 13,099 consultation agendas and 2122 care units. Seventeen DQ measures were defined and DQ issues were classified using a unified DQ reporting framework. For each domain, actions plans were defined for improving and monitoring prioritized DQ issues. RESULTS: Eleven identified DQ issues (8 for the PI data set and 3 for the HS data set) were categorized into completeness (n = 6), conformance (n = 3) and plausibility (n = 2) DQ issues. DQ issues were caused by errors from data originators, ETL issues or limitations of the EHR data entry tool. The action plans included sixteen actions (9 for the PI domain and 7 for the HS domain). Though only partial implementation, the DQ campaigns already resulted in significant improvement of DQ measures. CONCLUSION: DQ assessments of hospital information systems are largely unpublished. The preliminary results of two DQ campaigns conducted at AP-HP illustrate the benefit of the engagement into a DQ program. The adoption of a unified DQ reporting framework enables the communication of DQ findings in a well-defined manner with a shared vocabulary. Dedicated tooling is needed to automate and extend the scope of the generic DQ program. Specific DQ checks will be additionally defined on a per-study basis to evaluate whether EHR data fits for specific uses.

Gene-Targeted Analysis of Clinically Diagnosed Long QT Russian Families.

Long QT syndrome (LQTS) has great genetic heterogeneity: more than 500 mutations have been described in several genes. Despite many advances, a genetic diagnosis still cannot be established in 25-30% of patients. The aim of the present study was to perform genetic evaluation in 9 Russian families with LQTS; here we report the results of 4 positive probands and their relatives (a total of 16 individuals). All subjects underwent clinical examination, 12-lead ECG, and Holter monitoring. Genetic analysis of the 14 genes mainly involved in LQTS was performed using a next-generation sequencing approach. We identified two new mutations (KCNQ1 gene) and 6 known mutations (AKAP9, ANK2, KCNE1 and KCNJ2 genes) in 4 out of 9 probands, some of which have already been described in association with LQTS. Segregation studies suggest a possible causative role for KCNQ1 p.(Leu342Pro), AKAP9 p.(Arg1609Lys), KCNE1 p.(Asp85Asn), and KCNJ2 p.(Arg82Gln) variations. Our study confirmed the high genetic heterogeneity of this disease and highlights the difficulties to reveal clear pathogenic genotypes also in large pedigrees. To the best of our knowledge, this is the first genetic study of LQTS patients from Russian families.

Hsp70-Bag3 interactions regulate cancer-related signaling networks.

Bag3, a nucleotide exchange factor of the heat shock protein Hsp70, has been implicated in cell signaling. Here, we report that Bag3 interacts with the SH3 domain of Src, thereby mediating the effects of Hsp70 on Src signaling. Using several complementary approaches, we established that the Hsp70-Bag3 module is a broad-acting regulator of cancer cell signaling by modulating the activity of the transcription factors NF-κB, FoxM1, Hif1α, the translation regulator HuR, and the cell-cycle regulators p21 and survivin. We also identified a small-molecule inhibitor, YM-1, that disrupts the Hsp70-Bag3 interaction. YM-1 mirrored the effects of Hsp70 depletion on these signaling pathways, and in vivo administration of this drug was sufficient to suppress tumor growth in mice. Overall, our results defined Bag3 as a critical factor in Hsp70-modulated signaling and offered a preclinical proof-of-concept that the Hsp70-Bag3 complex may offer an appealing anticancer target.

Computer and statistical analysis of transcription factor binding and chromatin modifications by ChIP-seq data in embryonic stem cell.

Advances in high throughput sequencing technology have enabled the identification of transcription factor (TF) binding sites in genome scale. TF binding studies are important for medical applications and stem cell research. Somatic cells can be reprogrammed to a pluripotent state by the combined introduction of factors such as Oct4, Sox2, c-Myc, Klf4. These reprogrammed cells share many characteristics with embryonic stem cells (ESCs) and are known as induced pluripotent stem cells (iPSCs). The signaling requirements for maintenance of human and murine embryonic stem cells (ESCs) differ considerably. Genome wide ChIP-seq TF binding maps in mouse stem cells include Oct4, Sox2, Nanog, Tbx3, Smad2 as well as group of other factors. ChIP-seq allows study of new candidate transcription factors for reprogramming. It was shown that Nr5a2 could replace Oct4 for reprogramming. Epigenetic modifications play important role in regulation of gene expression adding additional complexity to transcription network functioning. We have studied associations between different histone modification using published data together with RNA Pol II sites. We found strong associations between activation marks and TF binding sites and present it qualitatively. To meet issues of statistical analysis of genome ChIP-sequencing maps we developed computer program to filter out noise signals and find significant association between binding site affinity and number of sequence reads. The data provide new insights into the function of chromatin organization and regulation in stem cells.

An Epstein-Barr virus encoded inhibitor of Colony Stimulating Factor-1 signaling is an important determinant for acute and persistent EBV infection.

Acute Epstein-Barr virus (EBV) infection is the most common cause of Infectious Mononucleosis. Nearly all adult humans harbor life-long, persistent EBV infection which can lead to development of cancers including Hodgkin Lymphoma, Burkitt Lymphoma, nasopharyngeal carcinoma, gastric carcinoma, and lymphomas in immunosuppressed patients. BARF1 is an EBV replication-associated, secreted protein that blocks Colony Stimulating Factor 1 (CSF-1) signaling, an innate immunity pathway not targeted by any other virus species. To evaluate effects of BARF1 in acute and persistent infection, we mutated the BARF1 homologue in the EBV-related herpesvirus, or lymphocryptovirus (LCV), naturally infecting rhesus macaques to create a recombinant rhLCV incapable of blocking CSF-1 (ΔrhBARF1). Rhesus macaques orally challenged with ΔrhBARF1 had decreased viral load indicating that CSF-1 is important for acute virus infection. Surprisingly, ΔrhBARF1 was also associated with dramatically lower virus setpoints during persistent infection. Normal acute viral load and normal viral setpoints during persistent rhLCV infection could be restored by Simian/Human Immunodeficiency Virus-induced immunosuppression prior to oral inoculation with ΔrhBARF1 or infection of immunocompetent animals with a recombinant rhLCV where the rhBARF1 was repaired. These results indicate that BARF1 blockade of CSF-1 signaling is an important immune evasion strategy for efficient acute EBV infection and a significant determinant for virus setpoint during persistent EBV infection.

Persistent infection drives the development of CD8+ T cells specific for late lytic infection antigens in lymphocryptovirus-infected macaques and Epstein-Barr virus-infected humans.

We examined the CD8(+) T cell repertoire against lytic infection antigens in rhesus macaques persistently infected with the Epstein-Barr virus (EBV)-related lymphocryptovirus (rhLCV). CD8(+) T cells specific for late (L) antigens were detected at rates comparable to those for early antigens and were associated with increasing duration of infection. L antigen-specific CD8(+) T cells were also readily detected in adult, EBV-positive humans. Thus, viral major histocompatibility complex class I (MHCI) immune evasion genes expressed during lytic LCV infection do not prevent L-specific CD8(+) T cell development over time during persistent infection.

Antibodies to lytic infection proteins in lymphocryptovirus-infected rhesus macaques: a model for humoral immune responses to epstein-barr virus infection.

Humoral immune responses to rhesus lymphocryptovirus (rhLCV) lytic infection proteins were evaluated in the rhesus macaque animal model for Epstein-Barr virus (EBV) infection. We found a hierarchy of humoral responses to 14 rhLCV lytic infection proteins in naturally infected rhesus macaques, with (i) widespread and robust responses to four glycoproteins expressed as late proteins, (ii) frequent but less robust responses to a subset of early proteins, and (iii) low-level responses to immediate-early proteins. This hierarchy of humoral responses was similar to that reported for EBV-infected humans, with the notable exception of the response to rhBARF1. Serum antibodies to rhBARF1 were frequently detected in healthy rhLCV-infected macaques, but in humans, anti-BARF1 antibodies have been reported primarily in patients with EBV-positive nasopharyngeal carcinoma (NPC). The macaque data accurately predicted that serum antibodies against BARF1 are a normal response to EBV infection when human serum samples are analyzed. The rhesus macaque animal provides a unique perspective on humoral responses to EBV infection in humans and can be a valuable model for EBV vaccine development.

Cloning of the Epstein-Barr virus-related rhesus lymphocryptovirus as a bacterial artificial chromosome: a loss-of-function mutation of the rhBARF1 immune evasion gene.

Rhesus macaques are naturally infected with a gammaherpesvirus which is in the same lymphocryptovirus (LCV) genus as and closely related to Epstein-Barr virus (EBV). The rhesus macaque LCV (rhLCV) contains a repertoire of genes identical to that of EBV, and experimental rhLCV infection of naive rhesus macaques accurately models acute and persistent EBV infection of humans. We cloned the LCL8664 rhLCV strain as a bacterial artificial chromosome to create recombinant rhLCV for investigation in this animal model system. A recombinant rhLCV (clone 16 rhLCV) carrying a mutation in the putative immune evasion gene rhBARF1 was created along with a rescued wild-type (rWT) rhLCV in which the rhBARF1 open reading frame (ORF) was repaired. The rWT rhLCV molecular clone demonstrated viral replication and B-cell immortalization properties comparable to those of the naturally derived LCL8664 rhLCV. Qualitatively, clone 16 rhLCV carrying a mutated rhBARF1 was competent for viral replication and B-cell immortalization, but quantitative assays showed that clone 16 rhLCV immortalized B cells less efficiently than LCL8664 and rWT rhLCV. Functional studies showed that rhBARF1 could block CSF-1 cytokine signaling as well as EBV BARF1, whereas the truncated rhBARF1 from clone 16 rhLCV was a loss-of-function mutant. These recombinant rhLCV can be used in the rhesus macaque animal model system to better understand how a putative viral immune evasion gene contributes to the pathogenesis of acute and persistent EBV infection. The development of a genetic system for making recombinant rhLCV constitutes a major advance in the study of EBV pathogenesis in the rhesus macaque animal model.