Genomic and ecogenomic characterisation of Proteus mirabilis bacteriophage

Proteus mirabilis often complicates the care of catheterized patients through the formation of crystalline biofilms which block urine flow. Bacteriophage therapy has been highlighted as a promising approach to control this problem, but relatively few phages infecting P. mirabilis have been characterized. Here we characterize five phages capable of infecting P. mirabilis, including those shown to reduce biofilm formation, and provide insights regarding the wider ecological and evolutionary relationships of these phages. Transmission electron microscopy (TEM) imaging of phages vB_PmiP_RS1pmA, vB_PmiP_RS1pmB, vB_PmiP_RS3pmA, and vB_PmiP_RS8pmA showed that all share morphologies characteristic of the Podoviridae family. The genome sequences of vB_PmiP_RS1pmA, vB_PmiP_RS1pmB, and vB_PmiP_RS3pmA showed these are species of the same phage differing only by point mutations, and are closely related to vB_PmiP_RS8pmA. Podophages characterized in this study were also found to share similarity in genome architecture and composition to other previously described P. mirabilis podophages (PM16 and PM75). In contrast, vB_PimP_RS51pmB showed morphology characteristic of the Myoviridae family, with no notable similarity to other phage genomes examined. Ecogenomic profiling of all phages revealed no association with human urinary tract viromes, but sequences similar to vB_PimP_RS51pmB were found within human gut, and human oral microbiomes. Investigation of wider host-phage evolutionary relationships through tetranucleotide profiling of phage genomes and bacterial chromosomes, indicated vB_PimP_RS51pmB has a relatively recent association with Morganella morganii and other non-Proteus members of the Morganellaceae family. Subsequent host range assays confirmed vB_PimP_RS51pmB can infect M. morganii

Comparative (Meta)genomic Analysis and Ecological Profiling of Human Gut-Specific Bacteriophage φB124-14

Bacteriophage associated with the human gut microbiome are likely to have an important impact on community structure and function, and provide a wealth of biotechnological opportunities. Despite this, knowledge of the ecology and composition of bacteriophage in the gut bacterial community remains poor, with few well characterized gut-associated phage genomes currently available. Here we describe the identification and in-depth (meta)genomic, proteomic, and ecological analysis of a human gut-specific bacteriophage (designated φB124-14). In doing so we illuminate a fraction of the biological dark matter extant in this ecosystem and its surrounding eco-genomic landscape, identifying a novel and uncharted bacteriophage gene-space in this community. φB124-14 infects only a subset of closely related gut-associated Bacteroides fragilis strains, and the circular genome encodes functions previously found to be rare in viral genomes and human gut viral metagenome sequences, including those which potentially confer advantages upon phage and/or host bacteria. Comparative genomic analyses revealed φB124-14 is most closely related to φB40-8, the only other publically available Bacteroides sp. phage genome, whilst comparative metagenomic analysis of both phage failed to identify any homologous sequences in 136 non-human gut metagenomic datasets searched, supporting the human gut-specific nature of this phage. Moreover, a potential geographic variation in the carriage of these and related phage was revealed by analysis of their distribution and prevalence within 151 human gut microbiomes and viromes from Europe, America and Japan. Finally, ecological profiling of φB124-14 and φB40-8, using both gene-centric alignment-driven phylogenetic analyses, as well as alignment-free gene-independent approaches was undertaken. This not only verified the human gut-specific nature of both phage, but also indicated that these phage populate a distinct and unexplored ecological landscape within the human gut microbiome

Models of Models: A Translational Route for Cancer Treatment and Drug Development

Every patient and every disease is different. Each patient therefore requires a personalized treatment approach. For technical reasons, a personalized approach is feasible for treatment strategies such as surgery, but not for drug-based therapy or drug development. The development of individual mechanistic models of the disease process in every patient offers the possibility of attaining truly personalized drug-based therapy and prevention. The concept of virtual clinical trials and the integrated use of in silico, in vitro, and in vivo models in preclinical development could lead to significant gains in efficiency and order of magnitude increases in the cost effectiveness of drug development and approval. We have developed mechanistic computational models of large-scale cellular signal transduction networks for prediction of drug effects and functional responses, based on patient-specific multi-level omics profiles. However, a major barrier to the use of such models in a clinical and developmental context is the reliability of predictions. Here we detail how the approach of using “models of models” has the potential to impact cancer treatment and drug development. We describe the iterative refinement process that leverages the flexibility of experimental systems to generate highly dimensional data, which can be used to train and validate computational model parameters and improve model predictions. In this way, highly optimized computational models with robust predictive capacity can be generated. Such models open up a number of opportunities for cancer drug treatment and development, from enhancing the design of experimental studies, reducing costs, and improving animal welfare, to increasing the translational value of results generated

Resolution of habitat-associated ecogenomic signatures in bacteriophage genomes and application to microbial source tracking

Just as the expansion in genome sequencing has revealed and permitted the exploitation of phylogenetic signals embedded in bacterial genomes, the application of metagenomics has begun to provide similar insights at the ecosystem-level for microbial communities. However, little is known regarding this aspect of bacteriophage associated with microbial ecosystems, and if phage encode discernible habitat-associated signals diagnostic of underlying microbiomes. Here we demonstrate that individual phage can encode clear habitat-related “ecogenomic signatures”, based on relative representation of phage encoded gene homologues in metagenomic datasets. Furthermore, we show the  ecogenomic signature encoded by the gut-associated ɸB124-14 can be used to segregate metagenomes according to environmental origin, and distinguish “contaminated” environmental metagenomes (subject to simulated in silico human faecal pollution) from uncontaminated datasets. This indicates phage encoded ecological signals likely possess sufficient discriminatory power for use in biotechnological applications, such as development of microbial source tracking tools for monitoring water quality

Identification of aminoglycoside and β-lactam resistance genes from within an infant gut functional metagenomic library.

The infant gut microbiota develops rapidly during the first 2 years of life, acquiring microorganisms from diverse sources. During this time, significant opportunities exist for the infant to acquire antibiotic resistant bacteria, which can become established and constitute the infant gut resistome. With increased antibiotic resistance limiting our ability to treat bacterial infections, investigations into resistance reservoirs are highly pertinent. This study aimed to explore the nascent resistome in antibiotically-naïve infant gut microbiomes, using a combination of metagenomic approaches. Faecal samples from 22 six-month-old infants without previous antibiotic exposure were used to construct a pooled metagenomic library, which was functionally screened for ampicillin and gentamicin resistance. Our library of ∼220Mb contained 0.45 ampicillin resistant hits/Mb and 0.059 gentamicin resistant hits/Mb. PCR-based analysis of fosmid clones and uncloned metagenomic DNA, revealed a diverse and abundant aminoglycoside and β-lactam resistance reservoir within the infant gut, with resistance determinants exhibiting homology to those found in common gut inhabitants, including Escherichia coli, Enterococcus sp., and Clostridium difficile, as well as to genes from cryptic environmental bacteria. Notably, the genes identified differed from those revealed when a sequence-driven PCR-based screen of metagenomic DNA was employed. Carriage of these antibiotic resistance determinants conferred substantial, but varied (2-512x), increases in antibiotic resistance to their bacterial host. These data provide insights into the infant gut resistome, revealing the presence of a varied aminoglycoside and β-lactam resistance reservoir even in the absence of selective pressure, confirming the infant resistome establishes early in life, perhaps even at birth