Comparative Genomic Analysis of Bacterial Data in BV-BRC: An Example Exploring Antimicrobial Resistance.

As genomic and related data continue to expand, research biologists are often hampered by the computational hurdles required to analyze their data. The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Centers (BRC) to assist researchers with their analysis of genome sequence and other omics-related data. Recently, the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD), and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs merged to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) at https://www.bv-brc.org/ . The combined BV-BRC leverages the functionality of the original resources for bacterial and viral research communities with a unified data model, enhanced web-based visualization and analysis tools, and bioinformatics services. Here we demonstrate how antimicrobial resistance data can be analyzed in the new resource.

The chromosome-scale genome assembly for the West Nile vector Culex quinquefasciatus uncovers patterns of genome evolution in mosquitoes.

BACKGROUND: Understanding genome organization and evolution is important for species involved in transmission of human diseases, such as mosquitoes. Anophelinae and Culicinae subfamilies of mosquitoes show striking differences in genome sizes, sex chromosome arrangements, behavior, and ability to transmit pathogens. However, the genomic basis of these differences is not fully understood. METHODS: In this study, we used a combination of advanced genome technologies such as Oxford Nanopore Technology sequencing, Hi-C scaffolding, Bionano, and cytogenetic mapping to develop an improved chromosome-scale genome assembly for the West Nile vector Culex quinquefasciatus. RESULTS: We then used this assembly to annotate odorant receptors, odorant binding proteins, and transposable elements. A genomic region containing male-specific sequences on chromosome 1 and a polymorphic inversion on chromosome 3 were identified in the Cx. quinquefasciatus genome. In addition, the genome of Cx. quinquefasciatus was compared with the genomes of other mosquitoes such as malaria vectors An. coluzzi and An. albimanus, and the vector of arboviruses Ae. aegypti. Our work confirms significant expansion of the two chemosensory gene families in Cx. quinquefasciatus, as well as a significant increase and relocation of the transposable elements in both Cx. quinquefasciatus and Ae. aegypti relative to the Anophelines. Phylogenetic analysis clarifies the divergence time between the mosquito species. Our study provides new insights into chromosomal evolution in mosquitoes and finds that the X chromosome of Anophelinae and the sex-determining chromosome 1 of Culicinae have a significantly higher rate of evolution than autosomes. CONCLUSION: The improved Cx. quinquefasciatus genome assembly uncovered new details of mosquito genome evolution and has the potential to speed up the development of novel vector control strategies.

Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR.

The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Center (BRC) program to assist researchers with analyzing the growing body of genome sequence and other omics-related data. In this report, we describe the merger of the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD) and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) https://www.bv-brc.org/. The combined BV-BRC leverages the functionality of the bacterial and viral resources to provide a unified data model, enhanced web-based visualization and analysis tools, bioinformatics services, and a powerful suite of command line tools that benefit the bacterial and viral research communities.

Anopheles mosquitoes reveal new principles of 3D genome organization in insects.

Chromosomes are hierarchically folded within cell nuclei into territories, domains and subdomains, but the functional importance and evolutionary dynamics of these hierarchies are poorly defined. Here, we comprehensively profile genome organizations of five Anopheles mosquito species and show how different levels of chromatin architecture influence each other. Patterns observed on Hi-C maps are associated with known cytological structures, epigenetic profiles, and gene expression levels. Evolutionary analysis reveals conservation of chromatin architecture within synteny blocks for tens of millions of years and enrichment of synteny breakpoints in regions with increased genomic insulation. However, in-depth analysis shows a confounding effect of gene density on both insulation and distribution of synteny breakpoints, suggesting limited causal relationship between breakpoints and regions with increased genomic insulation. At the level of individual loci, we identify specific, extremely long-ranged looping interactions, conserved for ~100 million years. We demonstrate that the mechanisms underlying these looping contacts differ from previously described Polycomb-dependent interactions and clustering of active chromatin.

A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes.

Antimicrobial resistance (AMR) is a major global health threat that affects millions of people each year. Funding agencies worldwide and the global research community have expended considerable capital and effort tracking the evolution and spread of AMR by isolating and sequencing bacterial strains and performing antimicrobial susceptibility testing (AST). For the last several years, we have been capturing these efforts by curating data from the literature and data resources and building a set of assembled bacterial genome sequences that are paired with laboratory-derived AST data. This collection currently contains AST data for over 67 000 genomes encompassing approximately 40 genera and over 100 species. In this paper, we describe the characteristics of this collection, highlighting areas where sampling is comparatively deep or shallow, and showing areas where attention is needed from the research community to improve sampling and tracking efforts. In addition to using the data to track the evolution and spread of AMR, it also serves as a useful starting point for building machine learning models for predicting AMR phenotypes. We demonstrate this by describing two machine learning models that are built from the entire dataset to show where the predictive power is comparatively high or low. This AMR metadata collection is freely available and maintained on the Bacterial and Viral Bioinformatics Center (BV-BRC) FTP site ftp://ftp.bvbrc.org/RELEASE_NOTES/PATRIC_genomes_AMR.txt.

The Beginning of the End: A Chromosomal Assembly of the New World Malaria Mosquito Ends with a Novel Telomere.

Chromosome level assemblies are accumulating in various taxonomic groups including mosquitoes. However, even in the few reference-quality mosquito assemblies, a significant portion of the heterochromatic regions including telomeres remain unresolved. Here we produce a de novo assembly of the New World malaria mosquito, Anopheles albimanus by integrating Oxford Nanopore sequencing, Illumina, Hi-C and optical mapping. This 172.6 Mbps female assembly, which we call AalbS3, is obtained by scaffolding polished large contigs (contig N50 = 13.7 Mbps) into three chromosomes. All chromosome arms end with telomeric repeats, which is the first in mosquito assemblies and represents a significant step toward the completion of a genome assembly. These telomeres consist of tandem repeats of a novel 30-32 bp Telomeric Repeat Unit (TRU) and are confirmed by analyzing the termini of long reads and through both chromosomal in situ hybridization and a Bal31 sensitivity assay. The AalbS3 assembly included previously uncharacterized centromeric and rDNA clusters and more than doubled the content of transposable elements and other repetitive sequences. This telomere-to-telomere assembly, although still containing gaps, represents a significant step toward resolving biologically important but previously hidden genomic components. The comparison of different scaffolding methods will also inform future efforts to obtain reference-quality genomes for other mosquito species.

Nix alone is sufficient to convert female Aedes aegypti into fertile males and myo-sex is needed for male flight.

A dominant male-determining locus (M-locus) establishes the male sex (M/m) in the yellow fever mosquito, Aedes aegyptiNix, a gene in the M-locus, was shown to be a male-determining factor (M factor) as somatic knockout of Nix led to feminized males (M/m) while transient expression of Nix resulted in partially masculinized females (m/m), with male reproductive organs but retained female antennae. It was not clear whether any of the other 29 genes in the 1.3-Mb M-locus are also needed for complete sex-conversion. Here, we report the generation of multiple transgenic lines that express Nix under the control of its own promoter. Genetic and molecular analyses of these lines provided insights unattainable from previous transient experiments. We show that the Nix transgene alone, in the absence of the M-locus, was sufficient to convert females into males with all male-specific sexually dimorphic features and male-like gene expression. The converted m/m males are flightless, unable to perform the nuptial flight required for mating. However, they were able to father sex-converted progeny when presented with cold-anesthetized wild-type females. We show that myo-sex, a myosin heavy-chain gene also in the M-locus, was required for male flight as knockout of myo-sex rendered wild-type males flightless. We also show that Nix-mediated female-to-male conversion was 100% penetrant and stable over many generations. Therefore, Nix has great potential for developing mosquito control strategies to reduce vector populations by female-to-male sex conversion, or to aid in a sterile insect technique that requires releasing only non-biting males.

Evaluating the impact of international airline suspensions on the early global spread of COVID-19.

Global airline networks play a key role in the global importation of emerging infectious diseases. Detailed information on air traffic between international airports has been demonstrated to be useful in retrospectively validating and prospectively predicting case emergence in other countries. In this paper, we use a well-established metric known as effective distance on the global air traffic data from IATA to quantify risk of emergence for different countries as a consequence of direct importation from China, and compare it against arrival times for the first 24 countries. Using this model trained on official first reports from WHO, we estimate time of arrival (ToA) for all other countries. We then incorporate data on airline suspensions to recompute the effective distance and assess the effect of such cancellations in delaying the estimated arrival time for all other countries. Finally we use the infectious disease vulnerability indices to explain some of the estimated reporting delays.

Identification of Putative Early Atherosclerosis Biomarkers by Unsupervised Deconvolution of Heterogeneous Vascular Proteomes.

Coronary artery disease remains a leading cause of death in industrialized nations, and early detection of disease is a critical intervention target to effectively treat patients and manage risk. Proteomic analysis of mixed tissue homogenates may obscure subtle protein changes that occur uniquely in underlying tissue subtypes. The unsupervised 'convex analysis of mixtures' (CAM) tool has previously been shown to effectively segregate cellular subtypes from mixed expression data. In this study, we hypothesized that CAM would identify proteomic information specifically informative to early atherosclerosis lesion involvement that could lead to potential markers of early disease detection. We quantified the proteome of 99 paired abdominal aorta (AA) and left anterior descending coronary artery (LAD) specimens (N = 198 specimens total) acquired during autopsy of young adults free of diagnosed cardiac disease. The CAM tool was then used to segregate protein subsets uniquely associated with different underlying tissue types, yielding markers of normal and fibrous plaque (FP) tissues in LAD and AA (N = 62 lesions markers). CAM-derived FP marker expression was validated against pathologist estimated luminal surface involvement of FP, as well as in an orthogonal cohort of "pure" fibrous plaque, fatty streak, and normal vascular specimens. A targeted mass spectrometry (MS) assay quantified 39 of 62 CAM-FP markers in plasma from women with angiographically verified coronary artery disease (CAD, N = 46) or free from apparent CAD (control, N = 40). Elastic net variable selection with logistic regression reduced this list to 10 proteins capable of classifying CAD status in this cohort with <6% misclassification error, and a mean area under the receiver operating characteristic curve of 0.992 (confidence interval 0.968-0.998) after cross validation. The proteomics-CAM workflow identified lesion-specific molecular biomarker candidates by distilling the most representative molecules from heterogeneous tissue types.

The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities.

The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.

Revisiting the ß-Lactams for Tuberculosis Therapy with a Compound-Compound Synthetic Lethality Approach.

The suboptimal effectiveness of ß-lactam antibiotics against Mycobacterium tuberculosis has hindered the utility of this compound class for tuberculosis treatment. However, the results of treatment with a second-line regimen containing meropenem plus a ß-lactamase inhibitor were found to be encouraging in a case study of extensively drug-resistant tuberculosis (M. C. Payen, S. De Wit, C. Martin, R. Sergysels, et al., Int J Tuberc Lung Dis 16:558-560, 2012, https://doi.org/10.5588/ijtld.11.0414). We hypothesized that the innate resistance of M. tuberculosis to ß-lactams is mediated in part by noncanonical accessory proteins that are not considered the classic targets of ß-lactams and that small-molecule inhibitors of those accessory targets might sensitize M. tuberculosis to ß-lactams. In this study, we screened an NIH small-molecule library for the ability to sensitize M. tuberculosis to meropenem. We identified six hit compounds, belonging to either the N-arylindole or benzothiophene chemotype. Verification studies confirmed the synthetic lethality phenotype for three of the N-arylindoles and one benzothiophene derivative. The latter was demonstrated to be partially bioavailable via oral administration in mice. Structure-activity relationship studies of both structural classes identified analogs with potent antitubercular activity, alone or in combination with meropenem. Transcriptional profiling revealed that oxidoreductases, MmpL family proteins, and a 27-kDa benzoquinone methyltransferase could be the targets of the N-arylindole potentiator. In conclusion, our compound-compound synthetic lethality screening revealed novel small molecules that were capable of potentiating the action of meropenem, presumably via inhibition of the innate resistance conferred by ß-lactam accessory proteins. ß-Lactam compound-compound synthetic lethality may be an alternative approach for drug-resistant tuberculosis.

Guy1, a Y-linked embryonic signal, regulates dosage compensation in Anopheles stephensi by increasing X gene expression.

We previously showed that Guy1, a primary signal expressed from the Y chromosome, is a strong candidate for a male-determining factor that confers female-specific lethality in Anopheles stephensi (Criscione et al., 2016). Here, we present evidence that Guy1 increases X gene expression in Guy1-transgenic females from two independent lines, providing a mechanism underlying the Guy1-conferred female lethality. The median level gene expression (MGE) of X-linked genes is significantly higher than autosomal genes in Guy1-transgenic females while there is no significant difference in MGE between X and autosomal genes in wild-type females. Furthermore, Guy1 significantly upregulates at least 40% of the 996 genes across the X chromosome in transgenic females. Guy1-conferred female-specific lethality is remarkably stable and completely penetrant. These findings indicate that Guy1 regulates dosage compensation in An. stephensi and components of dosage compensation may be explored to develop novel strategies to control mosquito-borne diseases.

PATRIC as a unique resource for studying antimicrobial resistance.

The Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org) is designed to provide researchers with the tools and services that they need to perform genomic and other 'omic' data analyses. In response to mounting concern over antimicrobial resistance (AMR), the PATRIC team has been developing new tools that help researchers understand AMR and its genetic determinants. To support comparative analyses, we have added AMR phenotype data to over 15 000 genomes in the PATRIC database, often assembling genomes from reads in public archives and collecting their associated AMR panel data from the literature to augment the collection. We have also been using this collection of AMR metadata to build machine learning-based classifiers that can predict the AMR phenotypes and the genomic regions associated with resistance for genomes being submitted to the annotation service. Likewise, we have undertaken a large AMR protein annotation effort by manually curating data from the literature and public repositories. This collection of 7370 AMR reference proteins, which contains many protein annotations (functional roles) that are unique to PATRIC and RAST, has been manually curated so that it projects stably across genomes. The collection currently projects to 1 610 744 proteins in the PATRIC database. Finally, the PATRIC Web site has been expanded to enable AMR-based custom page views so that researchers can easily explore AMR data and design experiments based on whole genomes or individual genes.

Proteomic Architecture of Human Coronary and Aortic Atherosclerosis.

BACKGOUND: The inability to detect premature atherosclerosis significantly hinders implementation of personalized therapy to prevent coronary heart disease. A comprehensive understanding of arterial protein networks and how they change in early atherosclerosis could identify new biomarkers for disease detection and improved therapeutic targets. METHODS: Here we describe the human arterial proteome and proteomic features strongly associated with early atherosclerosis based on mass spectrometry analysis of coronary artery and aortic specimens from 100 autopsied young adults (200 arterial specimens). Convex analysis of mixtures, differential dependent network modeling, and bioinformatic analyses defined the composition, network rewiring, and likely regulatory features of the protein networks associated with early atherosclerosis and how they vary across 2 anatomic distributions. RESULTS: The data document significant differences in mitochondrial protein abundance between coronary and aortic samples (coronary>>aortic), and between atherosclerotic and normal tissues (atherosclerotic<

Assembly, Annotation, and Comparative Genomics in PATRIC, the All Bacterial Bioinformatics Resource Center.

In the "big data" era, research biologists are faced with analyzing new types that usually require some level of computational expertise. A number of programs and pipelines exist, but acquiring the expertise to run them, and then understanding the output can be a challenge.The Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org ) has created an end-to-end analysis platform that allows researchers to take their raw reads, assemble a genome, annotate it, and then use a suite of user-friendly tools to compare it to any public data that is available in the repository. With close to 113,000 bacterial and more than 1000 archaeal genomes, PATRIC creates a unique research experience with "virtual integration" of private and public data. PATRIC contains many diverse tools and functionalities to explore both genome-scale and gene expression data, but the main focus of this chapter is on assembly, annotation, and the downstream comparative analysis functionality that is freely available in the resource.

Whole Exome Sequencing to Identify Genetic Variants Associated with Raised Atherosclerotic Lesions in Young Persons.

We investigated the influence of genetic variants on atherosclerosis using whole exome sequencing in cases and controls from the autopsy study "Pathobiological Determinants of Atherosclerosis in Youth (PDAY)". We identified a PDAY case group with the highest total amounts of raised lesions (n = 359) for comparisons with a control group with no detectable raised lesions (n = 626). In addition to the standard exome capture, we included genome-wide proximal promoter regions that contain sequences that regulate gene expression. Our statistical analyses included single variant analysis for common variants (MAF > 0.01) and rare variant analysis for low frequency and rare variants (MAF < 0.05). In addition, we investigated known CAD genes previously identified by meta-analysis of GWAS studies. We did not identify individual common variants that reached exome-wide significance using single variant analysis. In analysis limited to 60 CAD genes, we detected strong associations with COL4A2/COL4A1 that also previously showed associations with myocardial infarction and arterial stiffness, as well as coronary artery calcification. Likewise, rare variant analysis did not identify genes that reached exome-wide significance. Among the 60 CAD genes, the strongest association was with NBEAL1 that was also identified in gene-based analysis of whole exome sequencing for early onset myocardial infarction.

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center.

The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org). Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by 'virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics.

Bioinformatic Analysis of Coronary Disease Associated SNPs and Genes to Identify Proteins Potentially Involved in the Pathogenesis of Atherosclerosis.

Factors that contribute to the onset of atherosclerosis may be elucidated by bioinformatic techniques applied to multiple sources of genomic and proteomic data. The results of genome wide association studies, such as the CardioGramPlusC4D study, expression data, such as that available from expression quantitative trait loci (eQTL) databases, along with protein interaction and pathway data available in Ingenuity Pathway Analysis (IPA), constitute a substantial set of data amenable to bioinformatics analysis. This study used bioinformatic analyses of recent genome wide association data to identify a seed set of genes likely associated with atherosclerosis. The set was expanded to include protein interaction candidates to create a network of proteins possibly influencing the onset and progression of atherosclerosis. Local average connectivity (LAC), eigenvector centrality, and betweenness metrics were calculated for the interaction network to identify top gene and protein candidates for a better understanding of the atherosclerotic disease process. The top ranking genes included some known to be involved with cardiovascular disease (APOA1, APOA5, APOB, APOC1, APOC2, APOE, CDKN1A, CXCL12, SCARB1, SMARCA4 and TERT), and others that are less obvious and require further investigation (TP53, MYC, PPARG, YWHAQ, RB1, AR, ESR1, EGFR, UBC and YWHAZ). Collectively these data help define a more focused set of genes that likely play a pivotal role in the pathogenesis of atherosclerosis and are therefore natural targets for novel therapeutic interventions.

Mapping the Regulatory Network for Salmonella enterica Serovar Typhimurium Invasion.

UNLABELLED: Salmonella enterica pathogenicity island 1 (SPI-1) encodes proteins required for invasion of gut epithelial cells. The timing of invasion is tightly controlled by a complex regulatory network. The transcription factor (TF) HilD is the master regulator of this process and senses environmental signals associated with invasion. HilD activates transcription of genes within and outside SPI-1, including six other TFs. Thus, the transcriptional program associated with host cell invasion is controlled by at least 7 TFs. However, very few of the regulatory targets are known for these TFs, and the extent of the regulatory network is unclear. In this study, we used complementary genomic approaches to map the direct regulatory targets of all 7 TFs. Our data reveal a highly complex and interconnected network that includes many previously undescribed regulatory targets. Moreover, the network extends well beyond the 7 TFs, due to the inclusion of many additional TFs and noncoding RNAs. By comparing gene expression profiles of regulatory targets for the 7 TFs, we identified many uncharacterized genes that are likely to play direct roles in invasion. We also uncovered cross talk between SPI-1 regulation and other regulatory pathways, which, in turn, identified gene clusters that likely share related functions. Our data are freely available through an intuitive online browser and represent a valuable resource for the bacterial research community. IMPORTANCE: Invasion of epithelial cells is an early step during infection by Salmonella enterica and requires secretion of specific proteins into host cells via a type III secretion system (T3SS). Most T3SS-associated proteins required for invasion are encoded in a horizontally acquired genomic locus known as Salmonella pathogenicity island 1 (SPI-1). Multiple regulators respond to environmental signals to ensure appropriate timing of SPI-1 gene expression. In particular, there are seven transcription regulators that are known to be involved in coordinating expression of SPI-1 genes. We have used complementary genome-scale approaches to map the gene targets of these seven regulators. Our data reveal a highly complex and interconnected regulatory network that includes many previously undescribed target genes. Moreover, our data functionally implicate many uncharacterized genes in the invasion process and reveal cross talk between SPI-1 regulation and other regulatory pathways. All datasets are freely available through an intuitive online browser.

Antimicrobial Resistance Prediction in PATRIC and RAST.

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88-99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71-88%. This set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.