Premature neonatal gut microbial community patterns supporting an epithelial TLR-mediated pathway for necrotizing enterocolitis.

BACKGROUND: Necrotising enterocolitis (NEC) is a devastating bowel disease, primarily affecting premature infants, with a poorly understood aetiology. Prior studies have found associations in different cases with an overabundance of particular elements of the faecal microbiota (in particular Enterobacteriaceae or Clostridium perfringens), but there has been no explanation for the different results found in different cohorts. Immunological studies have indicated that stimulation of the TLR4 receptor is involved in development of NEC, with TLR4 signalling being antagonised by the activated TLR9 receptor. We speculated that differential stimulation of these two components of the signalling pathway by different microbiota might explain the dichotomous findings of microbiota-centered NEC studies. Here we used shotgun metagenomic sequencing and qPCR to characterise the faecal microbiota community of infants prior to NEC onset and in a set of matched controls. Bayesian regression was used to segregate cases from control samples using both microbial and clinical data. RESULTS: We found that the infants suffering from NEC fell into two groups based on their microbiota; one with low levels of CpG DNA in bacterial genomes and the other with high abundances of organisms expressing LPS. The identification of these characteristic communities was reproduced using an external metagenomic validation dataset. We propose that these two patterns represent the stimulation of a common pathway at extremes; the LPS-enriched microbiome suggesting overstimulation of TLR4, whilst a microbial community with low levels of CpG DNA suggests reduction of the counterbalance to TLR4 overstimulation. CONCLUSIONS: The identified microbial community patterns support the concept of NEC resulting from TLR-mediated pathways. Identification of these signals suggests characteristics of the gastrointestinal microbial community to be avoided to prevent NEC. Potential pre- or pro-biotic treatments may be designed to optimise TLR signalling.

EchoBASE: an integrated post-genomic database for Escherichia coli.

EchoBASE (http://www.ecoli-york.org) is a relational database designed to contain and manipulate information from post-genomic experiments using the model bacterium Escherichia coli K-12. Its aim is to collate information from a wide range of sources to provide clues to the functions of the approximately 1500 gene products that have no confirmed cellular function. The database is built on an enhanced annotation of the updated genome sequence of strain MG1655 and the association of experimental data with the E.coli genes and their products. Experiments that can be held within EchoBASE include proteomics studies, microarray data, protein-protein interaction data, structural data and bioinformatics studies. EchoBASE also contains annotated information on 'orphan' enzyme activities from this microbe to aid characterization of the proteins that catalyse these elusive biochemical reactions.

Parallel Evolution in Streptococcus pneumoniae Biofilms.

Streptococcus pneumoniae is a commensal human pathogen and the causative agent of various invasive and noninvasive diseases. Carriage of the pneumococcus in the nasopharynx is thought to be mediated by biofilm formation, an environment where isogenic populations frequently give rise to morphological colony variants, including small colony variant (SCV) phenotypes. We employed metabolic characterization and whole-genome sequencing of biofilm-derived S. pneumoniae serotype 22F pneumococcal SCVs to investigate diversification during biofilm formation. Phenotypic profiling revealed that SCVs exhibit reduced growth rates, reduced capsule expression, altered metabolic profiles, and increased biofilm formation compared to the ancestral strain. Whole-genome sequencing of 12 SCVs from independent biofilm experiments revealed that all SCVs studied had mutations within the DNA-directed RNA polymerase delta subunit (RpoE). Mutations included four large-scale deletions ranging from 51 to 264 bp, one insertion resulting in a coding frameshift, and seven nonsense single-nucleotide substitutions that result in a truncated gene product. This work links mutations in the rpoE gene to SCV formation and enhanced biofilm development in S. pneumoniae and therefore may have important implications for colonization, carriage, and persistence of the organism. Furthermore, recurrent mutation of the pneumococcal rpoE gene presents an unprecedented level of parallel evolution in pneumococcal biofilm development.

Challenges of the Unknown: Clinical Application of Microbial Metagenomics.

Availability of fast, high throughput and low cost whole genome sequencing holds great promise within public health microbiology, with applications ranging from outbreak detection and tracking transmission events to understanding the role played by microbial communities in health and disease. Within clinical metagenomics, identifying microorganisms from a complex and host enriched background remains a central computational challenge. As proof of principle, we sequenced two metagenomic samples, a known viral mixture of 25 human pathogens and an unknown complex biological model using benchtop technology. The datasets were then analysed using a bioinformatic pipeline developed around recent fast classification methods. A targeted approach was able to detect 20 of the viruses against a background of host contamination from multiple sources and bacterial contamination. An alternative untargeted identification method was highly correlated with these classifications, and over 1,600 species were identified when applied to the complex biological model, including several species captured at over 50% genome coverage. In summary, this study demonstrates the great potential of applying metagenomics within the clinical laboratory setting and that this can be achieved using infrastructure available to nondedicated sequencing centres.

Developing an integrated proteo-genomic approach for the characterisation of biomarkers for the identification of Bacillus anthracis.

Bacillus anthracis is the causative agent of anthrax, an acute and often fatal disease in humans. Due to the high genomic relatedness within the Bacillus cereus group of species it is a challenge to identify B. anthracis consistently. Alternative strategies such as proteomics coupled with mass spectrometry (MS) provide a powerful approach for biomarker discovery. However, validating and evaluating these markers, particularly for genetically homogeneous species such as B. anthracis are challenging. The objective of this study is to develop a robust biomarker discovery and validation pipeline, using proteomic methodology combined with in silico and molecular approaches, to determine a biomarker list, using B. anthracis as a model. In this exploratory study we profiled the proteome of B. anthracis and genetically related species using GeLC-Liquid Chromatography MS/MS (GeLC-LC MS/MS), identifying peptides that could be used to detect B. anthracis. Peptides were filtered to remove low quality identifications. Using comparative bioinformatic approaches, matching and searching against genomic sequence data a shortlist of peptide biomarkers was determined and validated using DNA sequencing, against a panel of closely related strains, to determine marker specificity. Further validation was performed using MS quantitation methods to assess sensitivity and specificity. A biomarker discovery pipeline was successfully developed in this study, comprising four distinct stages: proteome profiling, comparative bioinformatic validation, DNA sequencing and MS validation. Using the pipeline, 5379 peptides specific for Bacillus species and 36 peptides specific for B. anthracis were identified and validated. The 36 peptides, representing 30 proteins were derived from over 15 different clusters of orthologous group categories, including proteins involved in transcription, energy production/conservation as well as multifunctional proteins. We demonstrated that the peptide biomarkers identified in this study could be detected in a complex background, in which 0.1 µg of protein extract from B. anthracis was spiked into 9.90 µg of B. cereus protein extracts. The integration of both stable non-redundant peptides with molecular methodology for marker discovery and validation, improves the robustness of identifying and characterising candidate biomarkers for the identification of bacteria such as B. anthracis.

Performance comparison of benchtop high-throughput sequencing platforms.

Three benchtop high-throughput sequencing instruments are now available. The 454 GS Junior (Roche), MiSeq (Illumina) and Ion Torrent PGM (Life Technologies) are laser-printer sized and offer modest set-up and running costs. Each instrument can generate data required for a draft bacterial genome sequence in days, making them attractive for identifying and characterizing pathogens in the clinical setting. We compared the performance of these instruments by sequencing an isolate of Escherichia coli O104:H4, which caused an outbreak of food poisoning in Germany in 2011. The MiSeq had the highest throughput per run (1.6 Gb/run, 60 Mb/h) and lowest error rates. The 454 GS Junior generated the longest reads (up to 600 bases) and most contiguous assemblies but had the lowest throughput (70 Mb/run, 9 Mb/h). Run in 100-bp mode, the Ion Torrent PGM had the highest throughput (80­100 Mb/h). Unlike the MiSeq, the Ion Torrent PGM and 454 GS Junior both produced homopolymer-associated indel errors (1.5 and 0.38 errors per 100 bases, respectively).