Genome Sequence Database Research Articles

Exploring genetic diversity of hepatitis D virus full-length genome in Brazil: Discovery of a novel HDV-8 subgenotype beyond African borders

Hepatitis D virus (HDV) is currently classified into 8 genotypes (1 to 8) and several subgenotypes, with distinct distribution worldwide. However, due to the scarcity of complete genome sequences in databases, this classification is constantly being updated and tends to be regularly revisited in upcoming years as more sequence data becomes available. Aiming to increase knowledge about the genetic variability of HDV, this study presents the full-length genomes of 11 HDV samples collected in Brazil in endemic and non-endemic regions, including the first complete genomes of the genotypes 5 and 8 obtained outside Africa. We also determined the co-infecting HBV genotypes to investigate their prevalence among the HDV-infected individuals throughout the country. Whole genome sequencing confirmed our previous findings based on a partial fragment of the HDV genome, in which HDV subgenoypes 3c (9/11; 81.8 %), 5b (1/11; 9.1 %) and one HDV-8 sequence (1/11; 9.1 %) were detected. As previously observed, HDV-8 formed a distinct branch apart from subgenotypes 8a and 8b, a monophyletic clade representing a novel HDV-8 subgenotype, designated as 8c. Among HDV-3 samples, the main co-infecting HBV genotype found was HBV-F (4/8; 50 %), reflecting the higher incidence of this native South American genotype in the endemic Amazon Basin. Both samples infected with HDV-5 and HDV-8 were coinfected with HBV genotype E, also a genotype with African origin. Our findings based on complete genome sequence of HDV corroborated our results based on a partial region of the HDV genome of a novel HDV-8 subgenotype and reinforced the need to use full-length genomes to properly subdivide genotypes with very low intragroup genetic variability, such as HDV-3. The provision of these complete genomes is expected to contribute to the enrichment of sequence databases for future molecular and evolutionary investigations of HDV.

Characterization of mesothelin gene expression in dogs and overexpression in canine mesotheliomas.

Canine mesotheliomas are uncommon malignant tumors typically detected late. Minimally invasive diagnostic biomarkers would facilitate diagnosis at earlier stages, thereby improving clinical outcomes. We hypothesized that mesothelin could be used as a reliable diagnostic biomarker for canine mesotheliomas since it has been used as a cancer biomarker for human mesothelioma. We aimed to explore and characterize mesothelin gene expression in dogs and assess its use as a diagnostic biomarker for canine mesotheliomas. We quantified expressed canine mesothelin transcripts via reverse transcription polymerase chain reaction (RT-PCR) and sequenced them using ribonucleic acid (RNA) extracted from a canine mesothelioma cell line. After confirming mesothelin expression, we assessed its levels in major organ tissues and compared them with those in the mesothelioma tissues using quantitative PCR (qPCR). Mesothelin overexpression in mesotheliomas was detected, and we further compared its levels using qPCR between mesotheliomas and non-mesotheliomas using tumor tissues and clinical sample effusions, confirming its significance as a diagnostic biomarker for canine mesothelioma. Mesothelin complementary deoxyribonucleic acid (cDNA) was amplified via RT-PCR, yielding a single band of expected upon DNA electrophoresis. Sequence analyses confirmed it as a predicted canine mesothelin transcript from the genome sequence database. Comparative sequence analysis of the deduced amino acid sequence of the expressed canine mesothelin demonstrated molecular signature similarities with the human mesothelin. However, the pre-sequence of canine mesothelin lacks the mature megakaryocyte potentiating factor (MPF) portion, which is typically cleaved post-translationally with furin. Mesothelin expression was quantified via qPCR revealing low levels in the mesothelial and lung tissues, with negligible expression in the other major organs. Canine mesothelin exhibited significantly higher expression in the canine mesotheliomas than in the noncancerous tissues. Moreover, analysis of clinical samples using qPCR demonstrated markedly elevated mesothelin expression in canine mesotheliomas compared to non-mesothelioma cases. Canine mesothelin exhibits molecular and biological characteristics akin to human mesothelin. It could serve as a vital biomarker for diagnosing canine mesotheliomas, applicable to both tissue- and effusion-based samples.

Sequence-Based Protein Design: A Review of Using Statistical Models to Characterize Coevolutionary Traits for Developing Hybrid Proteins as Genetic Sensors.

Statistical analyses of homologous protein sequences can identify amino acid residue positions that co-evolve to generate family members with different properties. Based on the hypothesis that the coevolution of residue positions is necessary for maintaining protein structure, coevolutionary traits revealed by statistical models provide insight into residue-residue interactions that are important for understanding protein mechanisms at the molecular level. With the rapid expansion of genome sequencing databases that facilitate statistical analyses, this sequence-based approach has been used to study a broad range of protein families. An emerging application of this approach is to design hybrid transcriptional regulators as modular genetic sensors for novel wiring between input signals and genetic elements to control outputs. Among many allosterically regulated regulator families, the members contain structurally conserved and functionally independent protein domains, including a DNA-binding module (DBM) for interacting with a specific genetic element and a ligand-binding module (LBM) for sensing an input signal. By hybridizing a DBM and an LBM from two different family members, a hybrid regulator can be created with a new combination of signal-detection and DNA-recognition properties not present in natural systems. In this review, we present recent advances in the development of hybrid regulators and their applications in cellular engineering, especially focusing on the use of statistical analyses for characterizing DBM-LBM interactions and hybrid regulator design. Based on these studies, we then discuss the current limitations and potential directions for enhancing the impact of this sequence-based design approach.

BA.5 sub-lineages associated with higher severity of COVID-19 infection: A cross-sectional study in Indonesia

ObjectivesWe aimed to compare the clinical severity and outcome among laboratory-confirmed Omicron variant cases admitted between January and December 2022. MethodsThis is a cross-sectional study conducted in Hasan Sadikin General Hospital between January and December 2022. We enrolled patients aged ≥18 years with laboratory-confirmed Omicron infection. Data were collected from clinical records and a whole genome sequencing database. We compared the risk of severe symptoms and mortality using a logistic regression analysis adjusted for sex, age, comorbidities, and vaccination status. ResultsWe enrolled 255 patients and the main sub-lineages were BA.1 (16.1%), BA.2 (11.4%), BA.5 (35.7%), XBB (22.7%), and BQ.1 (14.1%). Compared with BA.1/BA.2, BA.5 sub-lineages were associated with severe symptoms (adjusted odds ratio of 2.9, 95% confidence interval 1.1-8.2, P <0.05). The highest risk of severe symptoms and mortality was linked with a high number of comorbidities (adjusted odds ratio of 7.8, 95% confidence interval 1.7-22.4, P <0.05). Booster vaccination was protective of severity and mortality. ConclusionsDisease severity was associated with BA.5 sub-lineages and multiple comorbidities. Good management is particularly important for people with comorbidities. Furthermore, booster vaccination is also required to reduce severity and mortality.

A review on recent taxonomic updates of gut bacteria associated with social bees, with a curated genomic reference database.

Honeybees and bumblebees play a crucial role as essential pollinators. The special gut microbiome of social bees is a key factor in determining the overall fitness and health of the host. Although bees harbor relatively simple microbial communities at the genus level, recent studies have unveiled significant genetic divergence and variations in gene content within each bacterial genus. However, a comprehensive and refined genomics-based taxonomic database specific to social bee gut microbiomes remains lacking. Here, we first provided an overview of the current knowledge on the distribution and function of social bee gut bacteria, as well as the factors that influence the gut population dynamics. We then consolidated all available genomes of the gut bacteria of social bees and refined the species-level taxonomy, by constructing a maximum-likelihood core genome phylogeny and calculating genome-wide pairwise average nucleotide identity. On the basis of the refined species taxonomy, we constructed a curated genomic reference database, named the bee gut microbe genome sequence database (BGM-GDb). To evaluate the species-profiling performance of the curated BGM-GDb, we retrieved a series of bee gut metagenomic data and inferred the species-level composition using metagenomic intra-species diversity analysis system (MIDAS), and then compared the results with those obtained from a prebuilt MIDAS database. We found that compared with the default database, the BGM-GDb excelled in aligned read counts and bacterial richness. Overall, this high-resolution and precise genomic reference database will facilitate research in understanding the gut community structure of social bees.

RIPS (rapid intuitive pathogen surveillance): a tool for surveillance of genome sequence data from foodborne bacterial pathogens.

Monitoring data submitted to the National Center for Biotechnology Information's Pathogen Detection whole-genome sequence database, which includes the foodborne bacterial pathogens Listeria monocytogenes, Salmonella enterica, and Escherichia coli, has proven effective for detecting emerging outbreaks. As part of the submission process, new sequence data are typed using a whole-genome multi-locus sequence typing scheme and clustered with sequences already in the database. Publicly available text files contain the results of these analyses. However, contextualizing and interpreting this information is complex. We present the Rapid Intuitive Pathogen Surveillance (RIPS) tool, which shows the results of the NCBI Rapid Reports, along with appropriate metadata, in a graphical, interactive dashboard. RIPS makes the information in the Rapid Reports useful for real-time surveillance of genome sequence databases.

Characterisation of the COVID-19 epidemic process in Moscow and search for possible determinants of the trends of the observed changes

Background. Constant assessment of the dynamics of the main characteristics of the epidemic process is the basic function of epidemiological surveillance of infectious diseases. The search for factors that determine changes in the characteristics of the epidemic process makes it possible to develop timely management decisions and reduce the risk of an increase in the scale of the pandemic. Moscow is the main centre of attraction for the population of other Russian regions with the most complex structure of social links and the highest population density.&#x0D; The purpose of the study is to identify factors that potentially determine the trends of observed changes using a molecular epidemiological analysis of the main characteristics of the epidemic process of a new coronavirus infection (COVID-19).&#x0D; Materials and methods. For the analysis, the data of Russian national genome sequence database of SARS-CoV-2 virus (VGARus) were combined with information on morbidity and mortality presented at the official internet resources стопкоронавирус.рф and Yandex DataLens, the dynamics of vaccination, COVID-19 disease incidence and hospitalization from the portal Gogov.ru. A multicentre retrospective observational epidemiological study was conducted to examine the sex and age structure of hospitalised patients. Anonymized case histories of patients with COVID-19 collected at different follow-up periods in the institutions of Moscow (41,561 cases) served as a source of data for the sex and age structure analysis.&#x0D; Results. We identified 11 periods with significantly different complex epidemiological characteristics. A decrease in the incidence among young people of working age during the period of restrictive measures was revealed. In 3 out of 11 worsening of the epidemic situation coincided with the beginning of the circulation of a new genetic variant of the pathogen COVID-19 (variants Wuhan, Delta, Omicron). A decrease in the incidence in the summer period was noted, regardless of the circulating genetic variants.&#x0D; Conclusion. A significant part of the observed dynamics of the characteristics of the epidemic process in Moscow can be explained by the properties of the pathogen, seasonality and dynamics of magnitude of the herd immunity. The influence of the dynamics of the herd immunity indicators on the course of the epidemic process is to be studied further.

Search of a genomic sequence database for potential novel blood group antigens: Investigation into why some amino acid substitutions are not immunogenic.

Polypeptide blood group antigens are typically identified through investigation of the antibodies they induce. Human genome sequence databases are a new tool to identify AA substitutions that potentially create blood group antigens. The Erythrogene genomic sequence database was searched for missense mutations not known to be blood group antigens in the extracellular domains of selected RBC proteins in European populations. Any mutations found with prevalence of 1%-90% and not known to have induced antibodies in transfusion practice were analyzed using protein structural analysis and epitope prediction programs to determine why they apparently lack immunogenicity. Thirteen missense mutations not known to create blood group antigens were identified in the extracellular domains of Kell, BCAM, and RhD proteins, but not in RhCE, Urea Transporter 1 (Kidd), Atypical Chemokine Receptor 1 (Duffy), glycophorin A or glycophorin B. While 11 of the 13 mutations had low prevalence (<1%), a Kell Ser726Pro substitution and a BCAM Val196Ile substitution had predicted phenotype prevalences of 43.2% and 5.7%, respectively. Ser726Pro had multiple properties of a linear B-cell epitope, but possible suboptimal protein location for B-cell receptor binding and limited T-cell epitope possibilities. Val196Ile was not predicted to be in a linear B-cell epitope. Multiple potential new blood group antigens of low prevalence were identified. Whether they are antigenic remains to be determined. Two higher prevalence variants in Kell and BCAM are unlikely antigens, otherwise their antibodies presumably would already have been identified. Possible reasons for their poor immunogenicity were identified.

MetaNovo: An open-source pipeline for probabilistic peptide discovery in complex metaproteomic datasets.

Microbiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focused search sequence databases based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing only targets the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. Here we describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored sequence databases for target-decoy searches directly at the proteome level, enabling metaproteomic analyses without prior expectation of sample composition or metagenomic data generation and compatible with standard downstream analysis pipelines. We compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome sequence database-but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic sequence database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying an experimental sample contaminant without prior expectation. By estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence databases to search. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic sequence database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself.

Host range of strand-biased circularizing integrative elements: a new class of mobile DNA elements nesting in Gammaproteobacteria

BackgroundThe strand-biased circularizing integrative elements (SEs) are putatively non-mobilizable integrative elements for transmitting antimicrobial resistance genes. The transposition mode and the prevalence of SEs in prokaryotes remain vague.ResultsTo corroborate the transposition mode and the prevalence of SEs, hypothetical transposition intermediates of an SE were searched for in genomic DNA fractions of an SE host. Then, the SE core genes were defined based on gene knockout experiments, and the synteny blocks of their distant homologs were searched for in the RefSeq complete genome sequence database using PSI-BLAST. A genomic DNA fractionation experiment revealed that SE copies are present in a double-stranded nicked circular form in vivo. Operonic structure of three conserved coding sequences (intA, tfp, intB) and srap located at the left end of SEs were identified as essential for attL × attR recombination. The synteny blocks of tfp and srap homologs were detected in 3.6% of the replicons of Gammaproteobacteria but not in other taxa, implying that SE movement is host-dependent. SEs have been discovered most frequently in the orders Vibrionales (19% of replicons), Pseudomonadales (18%), Alteromonadales (17%), and Aeromonadales (12%). Genomic comparisons revealed 35 new SE members with identifiable termini. SEs are present at 1 to 2 copies per replicon and have a median length of 15.7 kb. Three newly identified SE members carry antimicrobial resistance genes, like tmexCD-toprJ, mcr-9, and blaGMA-1. Further experiments validated that three new SE members possess the strand-biased attL × attR recombination activity.ConclusionsThis study suggested that transposition intermediates of SEs are double-stranded circular DNA. The main hosts of SEs are a subset of free-living Gammaproteobacteria; this represents a rather narrow host range compared to those of mobile DNA element groups discovered to date. As the host range, genetic organization, and movements are unique among the mobile DNA elements, SEs provide a new model system for host-mobile DNA element coevolution studies.

The distribution and characteristic of two transposable elements in the genome of Cydia pomonella granulovirus and codling moth

Baculoviruses are capable to acquire insect host transposable elements (TEs) in their genomes and are hypothesized as possible vectors of insect transposons between Lepidopteran species. Here, we investigated the host origin of two TEs, namely the Tc1/mariner-like element TCp3.2 and a 0.7 kbp insertion sequence (IS07), found in the genome of different isolates of Cydia pomonella granulovirus (CpGV), a member of the Betabaculovirus genus. The sequences of both TEs were searched for in the full genome sequence database of codling moth (CM, Cydia pomonella L.). A total of eleven TCp3.2 TE copies and 76 copies of the IS07 fragments were identified in the CM genome. These TEs were distributed over the 22 autosomes and the Z chromosome (chr1) of CM, except chr6, chr12, chr16, chr23, chr27 and the W chromosome (chr29). TCp3.2 copies with two transposase genes in opposite direction, representing a novel feature, were identified on chr10 and chr18. The TCp3.2 transposase was characterized by DD41D motif of classic Tc1/mariner transposons, consisting of DNA-binding domain, catalytic domain and nuclear localization signal (NLS). Transcription analyses of uninfected and CpGV-infected CM larvae suggested a doubling of the TCp3.2 transposase transcription rate in virus infected larvae. Furthermore, IS07 insertion into the CpGV genome apparently added new transcription initiation sites to the viral genome. The global analysis of the distribution of two TEs in the genome of CM addressed the influx of mobile TEs from CM to CpGV, a genetic process that contributes to the population diversity of baculoviruses.

Qualitative Bioinformatics: Towards a Public Understanding of Neurodegenerative Disease Research through BioArt, Data-Art, Hands-on BioMedia Workshops, Immersive Environments, and Artists in Labs.

Neurodegenerative disease (ND) research is producing new pharmaceutical compounds for chronic diseases utilizing bioinformatics. Algorithmic data mining of high-throughput omics systems is conjoined with the study of the in vitro dynamics of protein folding through visualization techniques, i.e., Bio-AFM. Novel models of disease pathway diagrams are being produced and the processes are in place to enhance the validation of these models. From bench work to BLAST to bedside, globally standardized research is led by collaborative clusters, working on cloud-based platforms, with crowd sourced human cohort collections, pairing pure, curiosity-based neurological research with deep learning data analysis techniques. ND research is leading the way towards clinical applications for preventing, curing, or ameliorating major diseases of neurological dysfunction, such as Alzheimer's disease (AD) and Parkinson's disease (PD).Most of this is too complex for the average citizen to comprehend. Can bioart and data-art contribute to the public understanding of genome sequencing and bioinformatics databases in the context of ND research? Informal studies towards demystifying bioinformatics through creative practices have been tested, revealing significant qualitative benefits for public well-being while introducing bioinformatics databases, for instance, previous projects: the VASTAL Bioinformatics and Literary Studies: (De)Mystified Genetic Code Lab, held at the Waag in Amsterdam, NL, 2009 and more recently the Creative Germline Constructs Bank (CGCB) of the transgenic human Genome Alternatives Project (thGAP), held at Hackteria ZET, Zurich, Switzerland, 2021.For the Hub of Art Laboratories (HAL), of the Department of Audio & Visual Arts (AVArts), Ionian University in Corfu, Greece, the animation node is challenged to create audiovisual, immersive, and interactive environments that highlight natural processes and phenomena of the microcosm and macrocosm through nature/data interface experimentation. It is the intention of the node's researchers to expand these notions to be inclusive of the processes of the biotechnological and bioinformatics interrogation of human disease as a part of local clades and global nature. In our productions, we would like to emphasize: cryogenic storage, genome analysis, bioinformatic database management, biomarkers for polygenic abnormalities, genotyping/phenotyping, gene expression patterns over time, AI reading of cloud-based research, experiencial DNA/RNA synthesis, the development of novel DNA, RNA and protein-based therapeutic agents for biomedical applications and CRISPR construct design for model organisms. It is the HAL animation node's goal to design and explore bioart-based, hands-on public workshops that mix bioinformatics and data-art with in-depth knowledge of the scientific community around ND research bodies.To develop these labs, dedicated artistic research is required to be undertaken through laboratory immersion, interactions with scientists, and hands-on experience in the lab. Artists must experience scientific processes through residencies in labs to learn both how to convey the techniques and the social implications of novel methodologies. Artists developing bioart workshops that can introduce non-specialists to a dizzying array of research methodologies need to know what they are talking about. It takes experience and dedication to convey simplified versions of real-time biosensor data, automated histology, clinical databases of medical case studies (anonymized clients), real-time PCR, novel diagnostic biomarker development, etc. As qualitative researchers, artists in labs ensure creative yet informed art and science (SciArt) outcomes able to stimulate public debate through unorthodox education and accurate playfulness. Obviously, the immersive experience of lab research provides an artist's projects with both nuance and knowledge. How can artists in labs also add to the scientific potentials of a laboratory's research goals?

Overexpression of RACGAP1 by E2F1 Promotes Neuroendocrine Differentiation of Prostate Cancer by Stabilizing EZH2 Expression.

Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer. It is characterized by the loss of androgen receptor (AR) signaling in neuroendocrine transdifferentiation, and finally, resistance to AR-targeted therapy. With the application of a new generation of potent AR inhibitors, the incidence of NEPC is gradually increasing. The molecular mechanism of neuroendocrine differentiation (NED) after androgen deprivation therapy (ADT) remains largely unclear. In this study, using NEPC-related genome sequencing database analyses, we screened RACGAP1, a common differentially expressed gene. We investigated RACGAP1 expression in clinical prostate cancer specimens by IHC. Regulated pathways were examined by Western blotting, qRT-PCR, luciferase reporter, chromatin immunoprecipitation, and immunoprecipitation assays. The corresponding function of RACGAP1 in prostate cancer was analyzed by CCK-8 and Transwell assays. The changes of neuroendocrine markers and AR expression in C4-2-R and C4-2B-R cells were detected in vitro. We confirmed that RACGAP1 contributed to NE transdifferentiation of prostate cancer. Patients with high tumor RACGAP1 expression had shorter relapse-free survival time. The expression of RACGAP1 was induced by E2F1. RACGAP1 promoted neuroendocrine transdifferentiation of prostate cancer by stabilizing EZH2 expression in the ubiquitin-proteasome pathway. Moreover, overexpression of RACGAP1 promoted enzalutamide resistance of castration-resistant prostate cancer (CRPC) cells. Our results showed that the upregulation of RACGAP1 by E2F1 increased EZH2 expression, which drove NEPC progression. This study explored the molecular mechanism of NED and may provide novel methods and ideas for targeted therapy of NEPC.

Biallelic TLR4 deficiency in humans

Toll-like receptors (TLRs) mediate functions for host defense and inflammatory responses. TLR4 recognizes LPS, a component of gram-negative bacteria as well as host-derived endogenous ligands such as S100A8 and S100A9 proteins. We sought to report phenotype and cellular function of individuals with complete TLR4 deficiency. We performed genome sequencing and investigated exome and genome sequencing databases. Cellular responses were studied on primary monocytes, macrophages, and neutrophils, as well as cell lines using flow cytometry, reporter, and cytokine assays. We identified 2 individuals in a family of Qatari origin carrying a homozygous stop codon variant p.Q188X in TLR4 presenting with a variable phenotype (asymptomatic and inflammatory bowel disease consistent with severe perianal Crohn disease). Athird individual with homozygous p.Y794X was identified in a population database. In contrast to hypomorphic polymorphisms p.D299G and p.T399I, the variants p.Q188X and p.Y794X completely abrogated LPS-induced cytokine responses whereas TLR2 response was normal. TLR4 deficiency causes a neutrophil CD62L shedding defect, whereas antimicrobial activity toward intracellular Salmonella was intact. Biallelic TLR4 deficiency in humans causes an inborn error of immunity in responding to LPS. This complements the spectrum of known primary immunodeficiencies, in particular myeloid differentiation primary response 88 (MYD88) or the IL-1 receptor-associated kinase 4 (IRAK4) deficiency that are downstream of TLR4 and TLR2 signaling.

A Timeframe for SARS-CoV-2 Genomes: A Proof of Concept for Postmortem Interval Estimations.

Establishing the timeframe when a particular virus was circulating in a population could be useful in several areas of biomedical research, including microbiology and legal medicine. Using simulations, we demonstrate that the circulation timeframe of an unknown SARS-CoV-2 genome in a population (hereafter, estimated time of a queried genome [QG]; tE-QG) can be easily predicted using a phylogenetic model based on a robust reference genome database of the virus, and information on their sampling dates. We evaluate several phylogeny-based approaches, including modeling evolutionary (substitution) rates of the SARS-CoV-2 genome (~10-3 substitutions/nucleotide/year) and the mutational (substitutions) differences separating the QGs from the reference genomes (RGs) in the database. Owing to the mutational characteristics of the virus, the present Viral Molecular Clock Dating (VMCD) method covers timeframes going backwards from about a month in the past. The method has very low errors associated to the tE-QG estimates and narrow intervals of tE-QG, both ranging from a few days to a few weeks regardless of the mathematical model used. The SARS-CoV-2 model represents a proof of concept that can be extrapolated to any other microorganism, provided that a robust genome sequence database is available. Besides obvious applications in epidemiology and microbiology investigations, there are several contexts in forensic casework where estimating tE-QG could be useful, including estimation of the postmortem intervals (PMI) and the dating of samples stored in hospital settings.

Fecal carriage and clonal dissemination of blaNDM-1 carrying Klebsiella pneumoniae sequence type 147 at an intensive care unit in Lao PDR

ObjectivesCarbapenemase-producing Enterobacterales (CPE) are high priority targets of global antimicrobial surveillance. Herein, we determined the colonization rate of CPE on admission to intensive care units in Vientiane, Lao PDR in August-September 2019.MethodsData regarding clinical conditions, infection control, and antibiotic usage were collected during admission. Rectal swab samples (n = 137) collected during admission were inoculated to selective chromogenic agars, followed by confirmatory tests for extended-spectrum beta-lactamases and carbapenemases. All CPE isolates were sequenced on Illumina (HiSeq2500), reads assembled using SPAdes 3.13, and the draft genomes used to query a database (https://www.genomicepidemiology.org) for resistome, plasmid replicons, and sequence types (ST). Optical DNA mapping (ODM) was used to characterize plasmids and to determine location of resistance genes. Minimum spanning tree was generated using the Bacterial Isolate Genome Sequence database (BIGSdb) and annotated using iTOL.ResultFrom 47 Enterobacterales isolated on selective agars, K. pneumoniae (25/47) and E. coli (12/47) were the most prevalent species, followed by K aerogenes (2/47), K. variicola (1/47), and K. oxytoca (1/47). The overall prevalence of ESBLs was 51.0%; E. coli 83.3% (10/12) and Klebsiella spp. 41.3% (12/29). Twenty percent of the K. pneumoniae (5/25) isolates were carbapenem-resistant, and 4/5 contained the blaNDM-1 gene. All blaNDM-1 isolates belonged to ST147 and were indistinguishable with cgMLST. ODM showed that the blaNDM-1 gene was located on identical plasmids in all isolates.ConclusionThe prevalence of ESBL-producing Enterobacterales was high, while carbapenemases were less common. However, the detection of clonal dissemination of blaNDM-1-producing K. pneumoniae isolates in one of the intensive care units calls for vigilance. Stringent infection prevention and antimicrobial stewardship strategies are highly important measures.

COLLECTION OF MICROORGANISMS – BIORESOURCES AND DATABASE

The Republican Collection of Microorganisms (RCM) is a depository of industrial microorganisms intended for research and analytical work, for the organization of biotechnological production.The Biobank of industrial microorganisms of the RCM stores more than 700 strains from various taxonomic groups (bacteria, actinomycetes, yeast, mycelial fungi). In Kazakhstan, there is no single annotated database (DB) of collectible strains of industrial microorganisms, including information about their- and genotypic characteristics.In this regard, the VRCM is working on the creation of a database, containing the genetic characteristics of deposited strains of industrial microorganisms.To compare genomes, the BLAST+ software package (Basic Local Alignment Search Tool) is used according to the instructions of the National Center for Biotechnology Information (NCBI).The creation of a database of genomic sequences of microorganisms based on the BLAST computer program (nucleotide group) and the storage of information in the Biobank of industrial microorganisms of the RCM will contribute to improving the quality of service function and safety of collection cultures.

Systematic Functional Annotation Workflow for Insects.

Simple SummaryThe functions of all genes encoded in the genome should be studied for genome editing. Genome editing technology can speed up insect research for the functional analysis of genes. Our knowledge about the functional information of genes is still incomplete currently, while the genome sequencing of an organism can be completed. The functional information has been annotated based solely on the information that has been obtained from the results of previous biological research. However, this information will be important in determining the target genes for genome editing. In particular, it is very important that this information is in machine-readable form because computer programs mainly parse this information for the understanding of biological systems. In this paper, we describe a workflow-based method for annotating gene functions in insects that makes use of transcribed sequence information as well as reference genome and protein sequence databases. Using the developed workflow, we annotated the functional information of the Japanese stick insect and silkworm, including gene expression as well as sequence analysis. The functional annotation information obtained by the workflow will greatly expand the possibilities of entomological research using genome editing.Next-generation sequencing has revolutionized entomological study, rendering it possible to analyze the genomes and transcriptomes of non-model insects. However, use of this technology is often limited to obtaining the nucleotide sequences of target or related genes, with many of the acquired sequences remaining unused because other available sequences are not sufficiently annotated. To address this issue, we have developed a functional annotation workflow for transcriptome-sequenced insects to determine transcript descriptions, which represents a significant improvement over the previous method (functional annotation pipeline for insects). The developed workflow attempts to annotate not only the protein sequences obtained from transcriptome analysis but also the ncRNA sequences obtained simultaneously. In addition, the workflow integrates the expression-level information obtained from transcriptome sequencing for application as functional annotation information. Using the workflow, functional annotation was performed on the sequences obtained from transcriptome sequencing of the stick insect (Entoria okinawaensis) and silkworm (Bombyx mori), yielding richer functional annotation information than that obtained in our previous study. The improved workflow allows the more comprehensive exploitation of transcriptome data and is applicable to other insects because the workflow has been openly developed on GitHub.

Prediction of Pasteurella multocida serotypes based on whole genomic sequences

The serotypes of Pasteurella multocida were predicted based on whole genomic sequences (WGS) with specific genes of the capsular and liposaccharide (LPS) outer core polysaccharide regions as targets. A total of 56 strains were whole genomic sequenced and in addition all assembled genomes from NCBI were included for comparison. BIGSdb (Bacterial Isolate Genome Sequence Database) was installed on a Linux server and targets for capsular types A, B, D, E and F were defined as gene sequences of hyaD, bcbD, dcbF, ecbJ and fcbD, respectively and targets for LPS groups 1, 2, 3, 4, 5, 6, 7 and 8 were defined as gene sequences of pcgB, nctA, gatF, latB, rmlA, nctB, ppgB and natG, respectively. The serotypes of P. multocida were predicted from WGS by designating the capsular type and LPS group as well as subtype alleles to isolates. Comparisons between WGS predictions of capsular types and classical phenotypic typing showed correspondence in 87 % of cases whereas comparisons of WGS predictions of LPS groups to phenotypic typing corresponded for 82 % of the strains. In total 93 % and 94 % of the strains available with WGS could be capsular and LPS group typed, respectively. The server is free to access from https://ivsmlst.sund.ku.dk.

The TNNT2:c.95-108G>A variant is common in Maine Coons and shows no association with hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a common and potentially fatal heart disease in many cat breeds. An intronic variant in TNNT2, c.95-108G>A, was recently reported as the cause of HCM in the Maine Coon. The aim of this study was to determine this variant's allele frequency in different populations and its possible association with HCM. Based on 160 Maine Coon samples collected in Belgium, Italy, Sweden and the USA, the variant's allele frequency was estimated to be 0.32. Analysis of the 99 Lives feline whole genome sequencing database showed that the TNNT2 variant also occurs in other breeds, as well as mixed-breed cats. Comparison of 31 affected and 58 healthy cats did not reveal significantly increased odds for HCM in homozygotes. Based on the combined evidence and in agreement with the standards and guidelines for the interpretation of sequence variants, this variant is currently classified as a variant of unknown significance and should not be used for breeding decisions regarding HCM.