Genome Sequence of Pseudomonas Phage UMP151, Isolated from the Female Bladder Microbiota

A temperate bacteriophage, designated UMP151, was isolated from a Pseudomonas aeruginosa strain from a catheterized urine sample of a woman with overactive bladder (OAB) symptoms. The 41,303-bp genome sequence of Pseudomonas phage UMP151 exhibits sequence similarity to prophage and lytic phage sequences isolated from other areas of the human body

Draft Genome Assemblies of 4 Lactobacillus jensenii and 3 Lactobacillus mulieris Strains from the Urinary Tract

Lactobacilli are dominant members of the healthy female bladder microbiota. Here, we report the draft genome sequences of 4 Lactobacillus jensenii and 3 Lactobacillus mulieris strains isolated from catheterized urine samples

Mechanisms Responsible for a ΦX174 Mutant\u27s Ability To Infect Escherichia coli by Phosphorylation

The ability for a virus to expand its host range is dependent upon a successful mode of viral entry. As such, the host range of the well-studied ΦX174 bacteriophage is dictated by the presence of a particular lipopolysaccharide (LPS) on the bacterial surface. The mutant ΦX174 strain JACS-K, unlike its ancestor, is capable of infecting both its native host Escherichia coli C and E. coli K-12, which does not have the necessary LPS. The conversion of an alanine to a very reactive threonine on its virion surface was found to be responsible for the strain\u27s expanded host range

HAsh-MaP-ERadicator: Filtering Non-Target Sequences from Next Generation Sequencing Reads

Contemporary DNA sequencing technologies are continuously increasing throughput at ever decreasing costs. Moreover, due to recent advances in sequencing technology new platforms are emerging. As such computational challenges persist. The average read length possible has taken a giant leap forward with the PacBio and Nanopore solutions. Regardless of the platform used, impurities within the DNA preparation of the sample - be it from unintentional contaminants or pervasive symbiots - remains an issue. We have developed a new tool, HAsh-MaP-ERadicator (HAMPER), for the detection and removal of non-target, contaminating DNA sequences. Integrating hash-based and mapping-based strategies, HAMPER is both memory and time efficient while maintaining a high level of sensitivity. Moreover, HAMPER was designed for flexibility: reads of any size can be efficiently examined and the user can set parameters specific for the analysis of reads produced by a particular sequencer. To evaluate our method, mock sequencing runs were generated including various contaminating species and with variable rates of mutation revealing a high level of sensitivity and specificity. Reads that are not of interest can quickly be removed using HAMPER thus improving downstream analyses

UPΦ phages, a new group of filamentous phages found in several members of Enterobacteriales

Filamentous phages establish chronic infections in their bacterial hosts, and new phages are secreted by infected bacteria for multiple generations, typically without causing host death. Often, these viruses integrate in their host’s genome by co-opting the host’s XerCD recombinase system. In several cases, these viruses also encode genes that increase bacterial virulence in plants and animals. Here, we describe a new filamentous phage, UPϕ901, which we originally found integrated in a clinical isolate of Escherichia coli from urine. UPϕ901 and closely related phages can be found in published genomes of over 200 other bacteria, including strains of Citrobacter koseri, Salmonella enterica, Yersinia enterocolitica, and Klebsiella pneumoniae. Its closest relatives are consistently found in urine or in the blood and feces of patients with urinary tract infections. More distant relatives can be found in isolates from other environments, including sewage, water, soil, and contaminated food. Each of these phages, which we collectively call ‘UPϕ viruses’, also harbors two or more novel genes of unknown function

virMine 2.0: Identifying Viral Sequences in Microbial Communities

Here, we present virMine 2.0, the next generation of the virMine software tool. virMine 2.0 uses an exclusion technique to remove nonviral data from sequencing reads and scores the remaining data based on relatedness to viral elements, eliminating the sole dependency on homology identification

Bacteriophages VS Pseudomonas aeruginosa Biofilms

P. aeruginosa biofilms are difficult to treat due to the thick extracellular matrix and acquired antibiotic resistance. The bacteriophage (virus that infects bacterial cells) can destroy and prevent further growth of the bacterial biofilms. The goal of this project has been to treat biofilms with phages and check for antibiotic resistance

Rephine.r: A pipeline for correcting gene calls and clusters to improve phage pangenomes and phylogenies

Background. A pangenome is the collection of all genes found in a set of related genomes. For microbes, these genomes are often different strains of the same species, and the pangenome offers a means to compare gene content variation with differences in phenotypes, ecology, and phylogenetic relatedness. Though most frequently applied to bacteria, there is growing interest in adapting pangenome analysis to bacteriophages. However, working with phage genomes presents new challenges. First, most phage families are under-sampled, and homologous genes in related viruses can be difficult to identify. Second, homing endonucleases and intron-like sequences may be present, resulting in fragmented gene calls. Each of these issues can reduce the accuracy of standard pangenome analysis tools. Methods. We developed an R pipeline called Rephine.r that takes as input the gene clusters produced by an initial pangenomics workflow. Rephine.r then proceeds in two primary steps. First, it identifies three common causes of fragmented gene calls: (1) indels creating early stop codons and new start codons; (2) interruption by a selfish genetic element; and (3) splitting at the ends of the reported genome. Fragmented genes are then fused to create new sequence alignments. In tandem, Rephine.r searches for distant homologs separated into different gene families using Hidden Markov Models. Significant hits are used to merge families into larger clusters. A final round of fragment identification is then run, and results may be used to infer single-copy core genomes and phylogenetic trees. Results. We applied Rephine.r to three well-studied phage groups: the Tevenvirinae (e.g., T4), the Studiervirinae (e.g., T7), and the Pbunaviruses (e.g., PB1). In each case, Rephine.r recovered additional members of the single-copy core genome and increased the overall bootstrap support of the phylogeny. The Rephine.r pipeline is provided through GitHub (https://www.github.com/coevoeco/Rephine.r) as a single script for automated analysis and with utility functions to assist in building single-copy core genomes and predicting the sources of fragmented genes

Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution

Bacteriophages are the most abundant and diverse biological entities on the planet, and new phage genomes are being discovered at a rapid pace. As more phage genomes are published, new methods are needed for placing these genomes in an ecological and evolutionary context. Phages are difficult to study by phylogenetic methods, because they exchange genes regularly, and no single gene is conserved across all phages. Here, we demonstrate how gene-level networks can provide a high-resolution view of phage genetic diversity and offer a novel perspective on virus ecology. We focus our analyses on virus host range and show how network topology corresponds to host relatedness, how to find groups of genes with the strongest host-specific signatures, and how this perspective can complement phage host prediction tools. We discuss extensions of gene network analysis to predicting the emergence of phages on new hosts, as well as applications to features of phage biology beyond host range

Diversity of Pseudomonas aeruginosa Temperate Phages

Modern sequencing technologies have provided insight into the genetic diversity of numerous species, including the human pathogen Pseudomonas aeruginosa. Bacterial genomes often harbor bacteriophage genomes (prophages), which can account for upwards of 20% of the genome. Prior studies have found P. aeruginosa prophages that contribute to their host’s pathogenicity and fitness. These advantages come in many different forms, including the production of toxins, promotion of biofilm formation, and displacement of other P. aeruginosa strains. While several different genera and species of P. aeruginosa prophages have been studied, there has not been a comprehensive study of the overall diversity of P. aeruginosa-infecting prophages. Here, we present the results of just such an analysis. A total of 6,852 high-confidence prophages were identified from 5,383 P. aeruginosa genomes from strains isolated from the human body and other environments. In total, 3,201 unique prophage sequences were identified. While 53.1% of these prophage sequences displayed sequence similarity to publicly available phage genomes, novel and highly mosaic prophages were discovered. Among these prophages, there is extensive diversity, including diversity within the functionally conserved integrase and C repressor coding regions, two genes responsible for prophage entering and persisting through the lysogenic life cycle. Analysis of integrase, C repressor, and terminase coding regions revealed extensive reassortment among P. aeruginosa prophages. This catalog of P. aeruginosa prophages provides a resource for future studies into the evolution of the species