The current dramatic increase of antibiotic resistant bacteria has revitalised the interest in bacteriophages as alternative antibacterial treatment. Meanwhile, the development of bioinformatics methods for analysing genomic data places high-throughput approaches for phage characterization within reach. Here, we present HostPhinder, a tool aimed at predicting the bacterial host of phages by examining the phage genome sequence. Using a reference database of 2196 phages with known hosts, HostPhinder predicts the host species of a query phage as the host of the most genomically similar reference phages. As a measure of genomic similarity the number of co-occurring k-mers (DNA sequences of length k) is used. Using an independent evaluation set, HostPhinder was able to correctly predict host genus and species for 81% and 74% of the phages respectively, giving predictions for more phages than BLAST and significantly outperforming BLAST on phages for which both had predictions. HostPhinder predictions on phage draft genomes from the INTESTI phage cocktail corresponded well with the advertised targets of the cocktail. Our study indicates that for most phages genomic similarity correlates well with related bacterial hosts. HostPhinder is available as an interactive web service [1] and as a stand alone download from the Docker registry [2].

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder.

Phage therapy has regained interest in recent years due to the alarming spread of antibiotic resistance. Whilst phage cocktails are commonly sold in pharmacies in countries such as Georgia and Russia, this is not the case in western countries due to western regulatory agencies requiring a thorough characterization of the drug. Here, DNA sequencing of constituent biological entities constitutes a first step. The pyophage (PYO) cocktail is one of the main commercial products of the Georgian Eliava Institute of Bacteriophage, Microbiology and Virology and is used to cure skin infections. Since its first production in the 1930s, the composition of the cocktail has been periodically modified to add phages effective against emerging pathogenic strains. In this paper, we compared the composition of three PYO cocktails from 1997 (PYO97), 2000 (PYO2000) and 2014 (PYO2014). Based on next generation sequencing, de novo assembly and binning of contigs into draft genomes based on tetranucleotide distance, thirty and twenty-nine phage draft genomes were predicted in PYO97 and PYO2014, respectively. Of these, thirteen and fifteen shared high similarity to known phages. Eleven draft genomes were found to be common in the two cocktails. One of these showed no similarity to publicly available phage genomes. Representatives of phages targeting E. faecalis, E. faecium, E. coli, Proteus, P. aeruginosa and S. aureus were found in both cocktails. Finally, we estimated larger overlap of the PYO2000 cocktail to PYO97 compared to PYO2014. Using next generation sequencing and metagenomics analysis, we were able to characterize and compare the content of PYO cocktails separated by 17 years in time. Even though the cocktail composition is upgraded every six months, we found it to remain relatively stable over the years.

Exercising at different times of day elicits different effects on exercise performance and metabolic health. However, the specific signals driving the observed time-of-day specific effects of exercise have not been fully identified. r Exercise influences the skeletal muscle circadian clock, although the relative contribution of muscle contraction and extracellular signals is unknown. r Here, we show that contraction acutely increases the expression of the core circadian clock gene Period Circadian Regulator 2 (Per2) and phase-shifts Per2 rhythmicity in muscle cells. This contraction effect on core clock genes is mediated through a calcium-dependant mechanism; r The results obtained in the present study suggest that a proportion of the ability of exercise to entrain the skeletal muscle clock is driven directly by muscle contraction. Contraction interventions may be used to mimic some time-of-day specific effects of exercise on metabolism and muscle performance.

Accumulating evidence supports the existence of a tissue microbiota, which may regulate the physiological function of tissues in normal and pathological states. To gain insight into the regulation of tissue-borne bacteria in physiological conditions, we quantified and sequenced the 16S rRNA gene in aseptically collected skeletal muscle and blood samples from eight healthy male individuals subjected to six weeks of endurance training. Potential contamination bias was evaluated and the taxa profiles of each tissue were established. We detected bacterial DNA in skeletal muscle and blood, with background noise levels of detected bacterial DNA considerably lower in control versus tissue samples. In both muscle and blood, Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes were the most prominent phyla. Endurance training changed the content of resident bacterial DNA in skeletal muscle but not in blood, with Pseudomonas being less abundant, and both Staphylococcus and Acinetobacter being more abundant in muscle after exercise. Our results provide evidence that endurance training specifically remodels the bacterial DNA profile of skeletal muscle in healthy young men. Future investigations may shed light on the physiological impact, if any, of training-induced changes in bacterial DNA in skeletal muscle.

Probiotic cultures encounter oxidative conditions during manufacturing, yet protein abundance changes induced by such stress have not been characterized for some of the most common probiotics and starters. This comparative proteomics investigation focuses on the response by Lactobacillus acidophilus NCFM to H O simulating an oxidative environment. Bacterial growth was monitored by BioScreen and batch cultures were harvested at exponential phase for protein profiling of stress responses by 2D gel based comparative proteomics. Proteins identified in 19 of 21 spots changing in abundance due to H O were typically related to carbohydrate and energy metabolism, cysteine biosynthesis, and stress. In particular, increased cysteine synthase activity may accumulate a cysteine pool relevant for protein stability, enzyme catalysis, and the disulfide-reducing pathway. The stress response further included elevated abundance of biomolecules reducing damage such as enzymes from DNA repair pathways and metabolic enzymes with active site cysteine residues. By contrast, a protein-refolding chaperone showed reduced abundance, possibly reflecting severe oxidative protein destruction that was not overcome by refolding. The proteome analysis provides novel insight into resistance mechanisms in lactic acid bacteria against reactive oxygen species and constitutes a valuable starting point for improving industrial processes, food design, or strain engineering preserving microorganism viability.

Insulin action initiates a series of phosphorylation events regulating cellular differentiation, growth and metabolism. We have previously discovered, in a mass spectrometry-based phosphoproteomic study, that insulin/IGF-1 signalling induces phosphorylation of retinoid x receptor alpha (RXRα) at S22 in mouse brown pre-adipocytes. Here, we show that insulin induces the phosphorylation of RXRα at S22 in both brown precursor and mature adipocytes through a pathway involving ERK, downstream of IRS-1 and −2. We also found that RXRα S22 phosphorylation is promoted by insulin and upon re-feeding in brown adipose tissue in vivo, and that insulin-stimulated S22 phosphorylation of RXRα is dampened by dietinduced obesity. We used Rxra knockout cells re-expressing wild type (WT) or S22A nonphosphorylatable forms of RXRα to further characterize the role of S22 in brown adipocytes. Knockout of Rxra in brown pre-adipocytes resulted in decreased lipid accumulation and adipogenic gene expression during differentiation, and re-expression of RxraWT alleviated these effects. However, we observed no significant difference in cells re-expressing the RxraS22A mutant as compared with the cells reexpressing RxraWT. Furthermore, comparison of gene expression during adipogenesis in the WT and S22A re-expressing cells by RNA sequencing revealed similar transcriptomic profiles. Thus, our data propose a dispensable role for RXRα S22 phosphorylation in adipogenesis and transcription in differentiating brown pre-adipocytes.

In Santiago, Chile, rotavirus antigenic type G1P8 has been highly prevalent and G2P4 has circulated in cycles. Differences in epidemiology of rotavirus antigenic types worldwide may prove to be relevant in efficacy of rotavirus vaccines.