Evaluation of two approaches for assessing the genetic similarity of virioplankton populations as defined by genome size.

Viral production estimates show that virioplankton communities turn over rapidly in aquatic ecosystems. Thus, it is likely that the genetic identity of viral populations comprising the virioplankton also change over temporal and spatial scales, reflecting shifts in viral-host interactions. However, there are few approaches that can provide data on the genotypic identity of viral populations at low cost and with the sample throughput necessary to assess dynamic changes in the virioplankton. This study examined two of these approaches-T4-like major capsid protein (g23) gene polymorphism and randomly amplified polymorphic DNA-PCR (RAPD-PCR) fingerprinting-to ask how well each technique could track differences in virioplankton populations over time and geographic location. Seasonal changes in overall virioplankton composition were apparent from pulsed-field gel electrophoresis (PFGE) analysis. T4-like phages containing similar g23 proteins were found within both small- and large-genome populations, including populations from different geographic locations and times. The surprising occurrence of T4-like g23 within small genomic groups (23 to 64 kb) indicated that the genome size range of T4-like phages may be broader than previously believed. In contrast, RAPD-PCR fingerprinting detected high genotypic similarity within PFGE bands from the same location, time, and genome size class without the requirement for DNA sequencing. Unlike g23 polymorphism, RAPD-PCR fingerprints showed a greater temporal than geographic variation. Thus, while polymorphism in a viral signature gene, such as g23, can be a powerful tool for inferring evolutionary relationships, the degree to which this approach can capture fine-scale variability within virioplankton populations is less clear.

The Diversity of Lipopolysaccharide (O) and Capsular Polysaccharide (K) Antigens of Invasive Klebsiella pneumoniae in a Multi-Country Collection.

Klebsiella pneumoniae is a common cause of sepsis and is particularly associated with healthcare-associated infections. New strategies are needed to prevent or treat infections due to the emergence of multi-drug resistant K. pneumoniae. The goal of this study was to determine the diversity and distribution of O (lipopolysaccharide) and K (capsular polysaccharide) antigens on a large (>500) global collection of K. pneumoniae strains isolated from blood to inform vaccine development efforts. A total of 645 K. pneumoniae isolates were collected from the blood of patients in 13 countries during 2005-2017. Antibiotic susceptibility was determined using the Kirby-Bauer disk diffusion method. O antigen types including the presence of modified O galactan types were determined by PCR. K types were determined by multiplex PCR and wzi capsular typing. Sequence types of isolates were determined by multilocus sequence typing (MLST) targeting seven housekeeping genes. Among 591 isolates tested for antimicrobial resistance, we observed that 19.3% of isolates were non-susceptible to carbapenems and 62.1% of isolates were multidrug resistant (from as low as 16% in Sweden to 94% in Pakistan). Among 645 isolates, four serotypes, O1, O2, O3, and O5, accounted for 90.1% of K. pneumoniae strains. Serotype O1 was associated with multidrug resistance. Fifty percent of 199 tested O1 and O2 strains were gmlABC-positive, indicating the presence of the modified polysaccharide subunit D-galactan III. The most common K type was K2 by both multiplex PCR and wzi capsular typing. Of 39 strains tested by MLST, 36 strains were assigned to 26 known sequence types of which ST14, ST25, and ST258 were the most common. Given the limited number of O antigen types, diverse K antigen types and the high multidrug resistance, we believe that an O antigen-based vaccine would offer an excellent prophylactic strategy to prevent K. pneumoniae invasive infection.

VIROME: a standard operating procedure for analysis of viral metagenome sequences.

One consistent finding among studies using shotgun metagenomics to analyze whole viral communities is that most viral sequences show no significant homology to known sequences. Thus, bioinformatic analyses based on sequence collections such as GenBank nr, which are largely comprised of sequences from known organisms, tend to ignore a majority of sequences within most shotgun viral metagenome libraries. Here we describe a bioinformatic pipeline, the Viral Informatics Resource for Metagenome Exploration (VIROME), that emphasizes the classification of viral metagenome sequences (predicted open-reading frames) based on homology search results against both known and environmental sequences. Functional and taxonomic information is derived from five annotated sequence databases which are linked to the UniRef 100 database. Environmental classifications are obtained from hits against a custom database, MetaGenomes On-Line, which contains 49 million predicted environmental peptides. Each predicted viral metagenomic ORF run through the VIROME pipeline is placed into one of seven ORF classes, thus, every sequence receives a meaningful annotation. Additionally, the pipeline includes quality control measures to remove contaminating and poor quality sequence and assesses the potential amount of cellular DNA contamination in a viral metagenome library by screening for rRNA genes. Access to the VIROME pipeline and analysis results are provided through a web-application interface that is dynamically linked to a relational back-end database. The VIROME web-application interface is designed to allow users flexibility in retrieving sequences (reads, ORFs, predicted peptides) and search results for focused secondary analyses.