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.

Novel isoforms of influenza virus PA-X and PB1-F2 indicated by automatic annotation.

The influenza A virus genome contains 8 gene segments encoding 10 commonly recognized proteins. Additional protein products have been identified, including PB1-F2 and PA-X. We report the in-silico identification of novel isoforms of PB1-F2 and PA-X in influenza virus genomes sequenced from avian samples. The isoform observed in PA-X includes a mutated stop codon that should extend the protein product by 8 amino acids. The isoform observed in PB1-F2 includes two nonsense mutations that should truncate the N-terminal region of the protein product and remove the entire mitochondrial targeting domain. Both isoforms were uncovered during automatic annotation of CEIRS sequence data. Nominally termed PA-X8 and PB1-F2-Cterm, both predicted isoforms were subsequently found in other annotated influenza genomes previously deposited in GenBank. Both isoforms were noticed due to discrepant annotations output by two annotation engines, indicating a benefit of incorporating multiple algorithms during gene annotation.

Author Correction: Microbiome disturbance and resilience dynamics of the upper respiratory tract during influenza A virus infection.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Microbiome disturbance and resilience dynamics of the upper respiratory tract during influenza A virus infection.

Infection with influenza can be aggravated by bacterial co-infections, which often results in disease exacerbation. The effects of influenza infection on the upper respiratory tract (URT) microbiome are largely unknown. Here, we report a longitudinal study to assess the temporal dynamics of the URT microbiomes of uninfected and influenza virus-infected humans and ferrets. Uninfected human patients and ferret URT microbiomes have stable healthy ecostate communities both within and between individuals. In contrast, infected patients and ferrets exhibit large changes in bacterial community composition over time and between individuals. The unhealthy ecostates of infected individuals progress towards the healthy ecostate, coinciding with viral clearance and recovery. Pseudomonadales associate statistically with the disturbed microbiomes of infected individuals. The dynamic and resilient microbiome during influenza virus infection in multiple hosts provides a compelling rationale for the maintenance of the microbiome homeostasis as a potential therapeutic target to prevent IAV associated bacterial co-infections.

ARGONAUT II Study of the In Vitro Activity of Plazomicin against Carbapenemase-Producing Klebsiella pneumoniae.

Plazomicin was tested against 697 recently acquired carbapenem-resistant Klebsiella pneumoniae isolates from the Great Lakes region of the United States. Plazomicin MIC50 and MIC90 values were 0.25 and 1 mg/liter, respectively; 680 isolates (97.6%) were susceptible (MICs of ≤2 mg/liter), 9 (1.3%) intermediate (MICs of 4 mg/liter), and 8 (1.1%) resistant (MICs of >32 mg/liter). Resistance was associated with rmtF-, rmtB-, or armA-encoded 16S rRNA methyltransferases in all except 1 isolate.

Annotated Genome Sequence of Aspergillus tanneri NIH1004.

The annotated genome of Aspergillus tanneri, a recently discovered drug-resistant pathogen, was determined by employing the Oxford Nanopore MinION platform and the Funannotate pipeline. The genome size and the number of protein-coding genes are notably larger than those of the most common etiological agent of aspergillosis, Aspergillus fumigatus.

Ceftazidime-Avibactam in Combination With Fosfomycin: A Novel Therapeutic Strategy Against Multidrug-Resistant Pseudomonas aeruginosa.

Previously, by targeting penicillin-binding protein 3, Pseudomonas-derived cephalosporinase (PDC), and MurA with ceftazidime-avibactam-fosfomycin, antimicrobial susceptibility was restored among multidrug-resistant (MDR) Pseudomonas aeruginosa. Herein, ceftazidime-avibactam-fosfomycin combination therapy against MDR P. aeruginosa clinical isolate CL232 was further evaluated. Checkerboard susceptibility analysis revealed synergy between ceftazidime-avibactam and fosfomycin. Accordingly, the resistance elements present and expressed in P. aeruginosa were analyzed using whole-genome sequencing and transcriptome profiling. Mutations in genes that are known to contribute to ß-lactam resistance were identified. Moreover, expression of blaPDC, the mexAB-oprM efflux pump, and murA were upregulated. When fosfomycin was administered alone, the frequency of mutations conferring resistance was high; however, coadministration of fosfomycin with ceftazidime-avibactam yielded a lower frequency of resistance mutations. In a murine infection model using a high bacterial burden, ceftazidime-avibactam-fosfomycin significantly reduced the P. aeruginosa colony-forming units (CFUs), by approximately 2 and 5 logs, compared with stasis and in the vehicle-treated control, respectively. Administration of ceftazidime-avibactam and fosfomycin separately significantly increased CFUs, by approximately 3 logs and 1 log, respectively, compared with the number at stasis, and only reduced CFUs by approximately 1 log and 2 logs, respectively, compared with the number in the vehicle-treated control. Thus, the combination of ceftazidime-avibactam-fosfomycin was superior to either drug alone. By employing a "mechanism-based approach" to combination chemotherapy, we show that ceftazidime-avibactam-fosfomycin has the potential to offer infected patients with high bacterial burdens a therapeutic hope against infection with MDR P. aeruginosa that lack metallo-ß-lactamases.

OMeta: an ontology-based, data-driven metadata tracking system.

BACKGROUND: The development of high-throughput sequencing and analysis has accelerated multi-omics studies of thousands of microbial species, metagenomes, and infectious disease pathogens. Omics studies are enabling genotype-phenotype association studies which identify genetic determinants of pathogen virulence and drug resistance, as well as phylogenetic studies designed to track the origin and spread of disease outbreaks. These omics studies are complex and often employ multiple assay technologies including genomics, metagenomics, transcriptomics, proteomics, and metabolomics. To maximize the impact of omics studies, it is essential that data be accompanied by detailed contextual metadata (e.g., specimen, spatial-temporal, phenotypic characteristics) in clear, organized, and consistent formats. Over the years, many metadata standards developed by various metadata standards initiatives have arisen; the Genomic Standards Consortium's minimal information standards (MIxS), the GSCID/BRC Project and Sample Application Standard. Some tools exist for tracking metadata, but they do not provide event based capabilities to configure, collect, validate, and distribute metadata. To address this gap in the scientific community, an event based data-driven application, OMeta, was created that allows users to quickly configure, collect, validate, distribute, and integrate metadata. RESULTS: A data-driven web application, OMeta, has been developed for use by researchers consisting of a browser-based interface, a command-line interface (CLI), and server-side components that provide an intuitive platform for configuring, capturing, viewing, and sharing metadata. Project and sample metadata can be set based on existing standards or based on projects goals. Recorded information includes details on the biological samples, procedures, protocols, and experimental technologies, etc. This information can be organized based on events, including sample collection, sample quantification, sequencing assay, and analysis results. OMeta enables configuration in various presentation types: checkbox, file, drop-box, ontology, and fields can be configured to use the National Center for Biomedical Ontology (NCBO), a biomedical ontology server. Furthermore, OMeta maintains a complete audit trail of all changes made by users and allows metadata export in comma separated value (CSV) format for convenient deposition of data into public databases. CONCLUSIONS: We present, OMeta, a web-based software application that is built on data-driven principles for configuring and customizing data standards, capturing, curating, and sharing metadata.

Sequence heterogeneity of the PenA carbapenemase in clinical isolates of Burkholderia multivorans.

Multidrug-resistant gram-negative pathogens are a significant health threat. Burkholderia spp. encompass a complex subset of gram-negative bacteria with a wide range of biological functions that include human, animal, and plant pathogens. The treatment of infections caused by Burkholderia spp. is problematic due to their inherent resistance to multiple antibiotics. The major ß-lactam resistance determinant expressed in Burkholderia spp. is a class A ß-lactamase of the PenA family. In this study, significant amino acid sequence heterogeneity was discovered in PenA (37 novel variants) within a panel of 48 different strains of Burkholderia multivorans isolated from individuals with cystic fibrosis. Phylogenetic analysis distributed the 37 variants into 5 groups based on their primary amino acid sequences. Amino acid substitutions were present throughout the entire ß-lactamase and did not congregate to specific regions of the protein. The PenA variants possessed 5 to 17 single amino acid changes. The N189S and S286I substitutions were most prevalent and found in all variants. Due to the sequence heterogeneity in PenA, a highly conserved peptide (18 amino acids) within PenA was chosen as the antigen for polyclonal antibody production in order to measure expression of PenA within the 48 clinical isolates of B. multivorans. Characterization of the anti-PenA peptide antibody, using immunoblotting approaches, exposed several unique features of this antibody (i.e., detected <500 pg of purified PenA, all 37 PenA variants in B. multivorans, and Pen-like ß-lactamases from other species within the Burkholderia cepacia complex). The significant sequence heterogeneity found in PenA may have occurred due to selective pressure (e.g., exposure to antimicrobial therapy) within the host. The contribution of these changes warrants further investigation.

Characterization of the AmpC ß-Lactamase from Burkholderia multivorans.

Burkholderia multivorans is a member of the Burkholderia cepacia complex, a group of >20 related species of nosocomial pathogens that commonly infect individuals suffering from cystic fibrosis. ß-Lactam antibiotics are recommended as therapy for infections due to Bmultivorans, which possesses two ß-lactamase genes, blapenA and blaAmpC PenA is a carbapenemase with a substrate profile similar to that of the Klebsiella pneumoniae carbapenemase (KPC); in addition, expression of PenA is inducible by ß-lactams in Bmultivorans Here, we characterize AmpC from Bmultivorans ATCC 17616. AmpC possesses only 38 to 46% protein identity with non-Burkholderia AmpC proteins (e.g., PDC-1 and CMY-2). Among 49 clinical isolates of Bmultivorans, we identified 27 different AmpC variants. Some variants possessed single amino acid substitutions within critical active-site motifs (Ω loop and R2 loop). Purified AmpC1 demonstrated minimal measurable catalytic activity toward ß-lactams (i.e., nitrocefin and cephalothin). Moreover, avibactam was a poor inhibitor of AmpC1 (Kiapp > 600 µM), and acyl-enzyme complex formation with AmpC1 was slow, likely due to lack of productive interactions with active-site residues. Interestingly, immunoblotting using a polyclonal anti-AmpC antibody revealed that protein expression of AmpC1 was inducible in Bmultivorans ATCC 17616 after growth in subinhibitory concentrations of imipenem (1 µg/ml). AmpC is a unique inducible class C cephalosporinase that may play an ancillary role in Bmultivorans compared to PenA, which is the dominant ß-lactamase in Bmultivorans ATCC 17616.

NeatFreq: reference-free data reduction and coverage normalization for De Novo sequence assembly.

BACKGROUND: Deep shotgun sequencing on next generation sequencing (NGS) platforms has contributed significant amounts of data to enrich our understanding of genomes, transcriptomes, amplified single-cell genomes, and metagenomes. However, deep coverage variations in short-read data sets and high sequencing error rates of modern sequencers present new computational challenges in data interpretation, including mapping and de novo assembly. New lab techniques such as multiple displacement amplification (MDA) of single cells and sequence independent single primer amplification (SISPA) allow for sequencing of organisms that cannot be cultured, but generate highly variable coverage due to amplification biases. RESULTS: Here we introduce NeatFreq, a software tool that reduces a data set to more uniform coverage by clustering and selecting from reads binned by their median kmer frequency (RMKF) and uniqueness. Previous algorithms normalize read coverage based on RMKF, but do not include methods for the preferred selection of (1) extremely low coverage regions produced by extremely variable sequencing of random-primed products and (2) 2-sided paired-end sequences. The algorithm increases the incorporation of the most unique, lowest coverage, segments of a genome using an error-corrected data set. NeatFreq was applied to bacterial, viral plaque, and single-cell sequencing data. The algorithm showed an increase in the rate at which the most unique reads in a genome were included in the assembled consensus while also reducing the count of duplicative and erroneous contigs (strings of high confidence overlaps) in the deliverable consensus. The results obtained from conventional Overlap-Layout-Consensus (OLC) were compared to simulated multi-de Bruijn graph assembly alternatives trained for variable coverage input using sequence before and after normalization of coverage. Coverage reduction was shown to increase processing speed and reduce memory requirements when using conventional bacterial assembly algorithms. CONCLUSIONS: The normalization of deep coverage spikes, which would otherwise inhibit consensus resolution, enables High Throughput Sequencing (HTS) assembly projects to consistently run to completion with existing assembly software. The NeatFreq software package is free, open source and available at https://github.com/bioh4x/NeatFreq .

Standardized metadata for human pathogen/vector genomic sequences.

High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium's minimal information (MIxS) and NCBI's BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant.

Draft Genome Sequences of Burkholderia cenocepacia ET12 Lineage Strains K56-2 and BC7.

The Burkholderia cepacia complex (BCC) is a group of closely related bacteria that are responsible for respiratory infections in immunocompromised humans, most notably those with cystic fibrosis (CF). We report the genome sequences for Burkholderia cenocepacia ET12 lineage CF isolates K56-2 and BC7.