Metatranscriptomic analysis reveals active bacterial communities in diabetic foot infections

Despite the extended view of the composition of diabetic foot infections (DFIs), little is known about which transcriptionally active bacterial communities are pertinent to infection, and if any differences are associated with increased infection severity. We applied a RNA sequencing approach to analyze the composition, function, and pathogenicity of the active bacterial communities in DFIs. Taxonomic profiling of bacterial transcripts revealed the presence of 14 bacterial phyla in DFIs. The abundance of the Spiroplasma, Vibrio, and Mycoplasma were significantly different in different infection severities (P < 0.05). Mild and severe stages of infections were dominated by Staphylococcus aureus and Porphyromonas asaccharolytica, respectively. A total of 132 metabolic pathways were identified of which ribosome and thiamin being among the most highly transcribed pathways. Moreover, a total of 131 antibiotic resistance genes, primarily involved in the multidrug efflux pumps/exporters, were identified. Furthermore, iron acquisition systems (synthesize and regulation of siderophores) and pathways involved in the synthesis and regulation of cell-surface components associated with adhesion, colonization, and movement of bacterial cells were the most common virulence factors. These virulence factors may help bacteria compete for scares resources and survive the host wound proteases. Characterization of transcriptionally active bacterial communities can help to provide an understanding of the role of key pathogens in the development of DFIs. Such information can be clinically useful allowing replacement of DFIs empirical therapy with targeted treatment

Impact of Experimental Hookworm Infection on the Human Gut Microbiota

The interactions between gastrointestinal parasitic helminths and commensal bacteria are likely to play a pivotal role in the establishment of host-parasite cross-talk, ultimately shaping the development of the intestinal immune system. However, little information is available on the impact of infections by gastrointestinal helminths on the bacterial communities inhabiting the human gut. We used 16S rRNA gene amplification and pyrosequencing to characterize, for the first time to our knowledge, the differences in composition and relative abundance of fecal microbial communities in human subjects prior to and following experimental infection with the blood-feeding intestinal hookworm, Necator americanus. Our data show that, although hookworm infection leads to a minor increase in microbial species richness, no detectable effect is observed on community structure, diversity or relative abundance of individual bacterial species

Experimental hookworm infection and escalating gluten challenges are associated with increased microbial richness in celiac subjects.

The intestinal microbiota plays a critical role in the development of the immune system. Recent investigations have highlighted the potential of helminth therapy for treating a range of inflammatory disorders, including celiac disease (CeD); however, the mechanisms by which helminths modulate the immune response of the human host and ameliorate CeD pathology are unknown. In this study, we investigated the potential role of alterations in the human gut microbiota in helminth-mediated suppression of an inflammatory disease. We assessed the qualitative and quantitative changes in the microbiota of human volunteers with CeD prior to and following infection with human hookworms, and following challenge with escalating doses of dietary gluten. Experimental hookworm infection of the trial subjects resulted in maintenance of the composition of the intestinal flora, even after a moderate gluten challenge. Notably, we observed a significant increase in microbial species richness over the course of the trial, which could represent a potential mechanism by which hookworms can regulate gluten-induced inflammation and maintain intestinal immune homeostasis.This work was supported by grants 1052938 to C.C., 613718 to P.G., and 1037304 and 1020114 to A.L. from the National Health and Medical Research Council of Australia (NHMRC), and from James Cook University (FMHMS 2013 grants round) and the Isaac Newton Trust / Wellcome Trust ISSF / University of Cambridge Joint Research Grants Scheme to C.C.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/srep1379

Detailed analysis of metagenome datasets obtained from biogas-producing microbial communities residing in biogas reactors does not indicate the presence of putative pathogenic microorganisms

Background: In recent years biogas plants in Germany have been supposed to be involved in amplification and dissemination of pathogenic bacteria causing severe infections in humans and animals. In particular, biogas plants are discussed to contribute to the spreading of Escherichia coli infections in humans or chronic botulism in cattle caused by Clostridium botulinum. Metagenome datasets of microbial communities from an agricultural biogas plant as well as from anaerobic lab-scale digesters operating at different temperatures and conditions were analyzed for the presence of putative pathogenic bacteria and virulence determinants by various bioinformatic approaches. Results: All datasets featured a low abundance of reads that were taxonomically assigned to the genus Escherichia or further selected genera comprising pathogenic species. Higher numbers of reads were taxonomically assigned to the genus Clostridium. However, only very few sequences were predicted to originate from pathogenic clostridial species. Moreover, mapping of metagenome reads to complete genome sequences of selected pathogenic bacteria revealed that not the pathogenic species itself, but only species that are more or less related to pathogenic ones are present in the fermentation samples analyzed. Likewise, known virulence determinants could hardly be detected. Only a marginal number of reads showed similarity to sequences described in the Microbial Virulence Database MvirDB such as those encoding protein toxins, virulence proteins or antibiotic resistance determinants. Conclusions: Findings of this first study of metagenomic sequence reads of biogas producing microbial communities suggest that the risk of dissemination of pathogenic bacteria by application of digestates from biogas fermentations as fertilizers is low, because obtained results do not indicate the presence of putative pathogenic microorganisms in the samples analyzed

Changes in duodenal tissue-associated microbiota following hookworm infection and consecutive gluten challenges in humans with coeliac disease

A reduced diversity of the gastrointestinal commensal microbiota is associated with the development of several inflammatory diseases. Recent reports in humans and animal models have demonstrated the beneficial therapeutic effects of infections by parasitic worms (helminths) in some inflammatory disorders, such as inflammatory bowel disease (IBD) and coeliac disease (CeD). Interestingly, these studies have described how helminths may alter the intestinal microbiota, potentially representing a mechanism by which they regulate inflammation. However, for practical reasons, these reports have primarily analysed the faecal microbiota. In the present investigation, we have assessed, for the first time, the changes in the microbiota at the site of infection by a parasitic helminth (hookworm) and gluten-dependent inflammation in humans with CeD using biopsy tissue from the duodenum. Hookworm infection and gluten exposure were associated with an increased abundance of species within the Bacteroides phylum, as well as increases in the richness and diversity of the tissue-resident microbiota within the intestine, results that are consistent with previous reports using other helminth species in humans and animal models. Hence, this may represent a mechanism by which parasitic helminths may restore intestinal immune homeostasis and exert a therapeutic benefit in CeD, and potentially other inflammatory disorders

Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) web-server

Genomics Data Miner (GMine) is a user-friendly online software that allows non-experts to mine, cluster and compare multidimensional biomolecular datasets. Various powerful visualization techniques are provided, generating high quality figures that can be directly incorporated into scientific publications. Robust and comprehensive analyses are provided via a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering and multivariable regression. The software has a focus on multivariate techniques, which can attribute variance in the measurements to multiple explanatory variables and confounders. Various normalization methods are provided. Extensive help pages and a tutorial are available via a wiki server. Using GMine we reanalyzed proteome microarray data of host antibody response against Plasmodium falciparum. Our results support the hypothesis that immunity to malaria is a higher-order phenomenon related to a pattern of responses and not attributable to any single antigen. We also analyzed gene expression across resting and activated T cells, identifying many immune-related genes with differential expression. This highlights both the plasticity of T cells and the operation of a hardwired activation program. These application examples demonstrate that GMine facilitates an accurate and in-depth analysis of complex molecular datasets, including genomics, transcriptomics and proteomics data

Comparative metagenomics of biogas-producing microbial communities from production-scale biogas plants operating under wet or dry fermentation conditions

Stolze Y, Zakrzewski M, Maus I, et al. Comparative metagenomics of biogas-producing microbial communities from production-scale biogas plants operating under wet or dry fermentation conditions. Biotechnology for Biofuels. 2015;8(1): 14.Background Decomposition of biomass for biogas production can be practiced under wet and dry fermentation conditions. In contrast to the dry fermentation technology, wet fermentation is characterized by a high liquid content and a relatively low total solid content. In this study, the composition and functional potential of a biogas-producing microbial community in an agricultural biogas reactor operating under wet fermentation conditions was analyzed by a metagenomic approach applying 454-pyrosequencing. The obtained metagenomic dataset and corresponding 16S rRNA gene amplicon sequences were compared to the previously sequenced comparable metagenome from a dry fermentation process, meeting explicitly identical boundary conditions regarding sample and community DNA preparation, sequencing technology, processing of sequence reads and data analyses by bioinformatics tools. Results High-throughput metagenome sequencing of community DNA from the wet fermentation process applying the pyrosequencing approach resulted in 1,532,780 reads, with an average read length of 397 bp, accounting for approximately 594 million bases of sequence information in total. Taxonomic comparison of the communities from wet and dry fermentation revealed similar microbial profiles with Bacteria being the predominant superkingdom, while the superkingdom Archaea was less abundant. In both biogas plants, the bacterial phyla Firmicutes, Bacteroidetes, Spirochaetes and Proteobacteria were identified with descending frequencies. Within the archaeal superkingdom, the phylum Euryarchaeota was most abundant with the dominant class Methanomicrobia. Functional profiles of the communities revealed that environmental gene tags representing methanogenesis enzymes were present in both biogas plants in comparable frequencies. 16S rRNA gene amplicon high-throughput sequencing disclosed differences in the sub-communities comprising methanogenic Archaea between both processes. Fragment recruitments of metagenomic reads to the reference genome of the archaeon Methanoculleus bourgensis MS2T revealed that dominant methanogens within the dry fermentation process were highly related to the reference. Conclusions Although process parameters, substrates and technology differ between the wet and dry biogas fermentations analyzed in this study, community profiles are very similar at least at higher taxonomic ranks, illustrating that core community taxa perform key functions in biomass decomposition and methane synthesis. Regarding methanogenesis, Archaea highly related to the type strain M. bourgensis MS2T dominate the dry fermentation process, suggesting the adaptation of members belonging to this species to specific fermentation process parameters

The coral core microbiome identifies rare bacterial taxa as ubiquitous endosymbionts

© 2015 International Society for Microbial Ecology All rights reserved. Despite being one of the simplest metazoans, corals harbor some of the most highly diverse and abundant microbial communities. Differentiating core, symbiotic bacteria from this diverse hostassociated consortium is essential for characterizing the functional contributions of bacteria but has not been possible yet. Here we characterize the coral core microbiome and demonstrate clear phylogenetic and functional divisions between the micro-scale, niche habitats within the coral host. In doing so, we discover seven distinct bacterial phylotypes that are universal to the core microbiome of coral species, separated by thousands of kilometres of oceans. The two most abundant phylotypes are co-localized specifically with the corals' endosymbiotic algae and symbiont-containing host cells. These bacterial symbioses likely facilitate the success of the dinoflagellate endosymbiosis with corals in diverse environmental regimes

EDGAR: A software framework for the comparative analysis of prokaryotic genomes

Blom J, Albaum S, Doppmeier D, et al. EDGAR: a software framework for the comparative analysis of prokaryotic genomes. BMC Bioinformatics. 2009;10(1): 154.Background:The introduction of next generation sequencing approaches has caused a rapid increase in the number of completely sequenced genomes. As one result of this development, it is now feasible to analyze large groups of related genomes in a comparative approach. A main task in comparative genomics is the identification of orthologous genes in different genomes and the classification of genes as core genes or singletons. Results: To support these studies EDGAR – ''Efficient Database framework for comparative Genome Analyses using BLAST score Ratios'' – was developed. EDGAR is designed to automatically perform genome comparisons in a high throughput approach. Comparative analyses for 582 genomes across 75 genus groups taken from the NCBI genomes database were conducted with the software and the results were integrated into an underlying database. To demonstrate a specific application case, we analyzed ten genomes of the bacterial genus Xanthomonas, for which phylogenetic studies were awkward due to divergent taxonomic systems. The resultant phylogeny EDGAR provided was consistent with outcomes from traditional approaches performed recently and moreover, it was possible to root each strain with unprecedented accuracy. Conclusion: EDGAR provides novel analysis features and significantly simplifies the comparative analysis of related genomes. The software supports a quick survey of evolutionary relationships and simplifies the process of obtaining new biological insights into the differential gene content of kindred genomes. Visualization features, like synteny plots or Venn diagrams, are offered to the scientific community through a web-based and therefore platform independent user interface http://edgar.cebitec.uni-bielefeld.de webcite, where the precomputed data sets can be browsed

Bioinformatic Analysis Reveals High Diversity of Bacterial Genes for Laccase-Like Enzymes

Fungal laccases have been used in various fields ranging from processes in wood and paper industries to environmental applications. Although a few bacterial laccases have been characterized in recent years, prokaryotes have largely been neglected as a source of novel enzymes, in part due to the lack of knowledge about the diversity and distribution of laccases within Bacteria. In this work genes for laccase-like enzymes were searched for in over 2,200 complete and draft bacterial genomes and four metagenomic datasets, using the custom profile Hidden Markov Models for two- and three- domain laccases. More than 1,200 putative genes for laccase-like enzymes were retrieved from chromosomes and plasmids of diverse bacteria. In 76% of the genes, signal peptides were predicted, indicating that these bacterial laccases may be exported from the cytoplasm, which contrasts with the current belief. Moreover, several examples of putatively horizontally transferred bacterial laccase genes were described. Many metagenomic sequences encoding fragments of laccase-like enzymes could not be phylogenetically assigned, indicating considerable novelty. Laccase-like genes were also found in anaerobic bacteria, autotrophs and alkaliphiles, thus opening new hypotheses regarding their ecological functions. Bacteria identified as carrying laccase genes represent potential sources for future biotechnological applications