Feasibility of an In-Situ Microbial Decontamination of an Ice-Melting Probe

Autonomous robotic systems for penetrating thick ice shells with simultaneous collecting of scientific data are very promising devices in both terrestrial (glacier, climate research) and extra-terrestrial applications. Technical challenges in development of such systems are numerous and include 3D-navigation, an appropriate energy source, motion control, etc. Not less important is the problem of forward contamination of the pristine glacial environments with microorganisms and biomolecules from the surface of the probe. This study was devoted to establishing a laboratory model for microbial contamination of a newlyconstructed ice-melting probe called IceMole and to analyse the viability and amount of the contaminating microorganisms as a function of distance. The used bacterial strains were Bacillus subtilis (ATCC 6051) and Escherichia coli (ATCC 11775). The main objective was development of an efficient and reliable in-situ decontamination method of the melting probe. Therefore, several chemical substances were tested in respect of their efficacy to eliminate bacteria on the surface of the melting probe at low temperature (0 - 5 °C) and at continuous dilution by melted water. Our study has shown that at least 99.9% decontamination of the IceMole can be successfully achieved by the injection of 30% (v/v) hydrogen peroxide and 3% (v/v) sodium hypochlorite into the drilling site. We were able to reproduce this result in both time-dependent and depth-dependent experiments. The sufficient amount of 30% (v/v) H2O2 or 3% (v/v) NaClO has been found to be approximately 18 L per cm² of the probe’s surface

Mining microbial metatranscriptomes for expression of antibiotic resistance genes under natural conditions

Antibiotic resistance genes are found in a broad range of ecological niches associated with complex microbiota. Here we investigated if resistance genes are not only present, but also transcribed under natural conditions. Furthermore, we examined the potential for antibiotic production by assessing the expression of associated secondary metabolite biosynthesis gene clusters. Metatranscriptome datasets from intestinal microbiota of four human adults, one human infant, 15 mice and six pigs, of which only the latter have received antibiotics prior to the study, as well as from sea bacterioplankton, a marine sponge, forest soil and sub-seafloor sediment, were investigated. We found that resistance genes are expressed in all studied ecological niches, albeit with niche-specific differences in relative expression levels and diversity of transcripts. For example, in mice and human infant microbiota predominantly tetracycline resistance genes were expressed while in human adult microbiota the spectrum of expressed genes was more diverse, and also included beta-lactam, aminoglycoside and macrolide resistance genes. Resistance gene expression could result from the presence of natural antibiotics in the environment, although we could not link it to expression of corresponding secondary metabolites biosynthesis clusters. Alternatively, resistance gene expression could be constitutive, or these genes serve alternative roles besides antibiotic resistance.Peer reviewe

A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets

Contains fulltext : 119246.pdf (publisher's version ) (Open Access)BACKGROUND: Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretation of which requires a reliable bioinformatic pipeline. In this study, we focus on the development of such a metatranscriptome pipeline, which we validate using Illumina RNA-seq datasets derived from the small intestine microbiota of two individuals with an ileostomy. RESULTS: The metatranscriptome pipeline developed here enabled effective removal of rRNA derived sequences, followed by confident assignment of the predicted function and taxonomic origin of the mRNA reads. Phylogenetic analysis of the small intestine metatranscriptome datasets revealed a strong similarity with the community composition profiles obtained from 16S rDNA and rRNA pyrosequencing, indicating considerable congruency between community composition (rDNA), and the taxonomic distribution of overall (rRNA) and specific (mRNA) activity among its microbial members. Reproducibility of the metatranscriptome sequencing approach was established by independent duplicate experiments. In addition, comparison of metatranscriptome analysis employing single- or paired-end sequencing methods indicated that the latter approach does not provide improved functional or phylogenetic insights. Metatranscriptome functional-mapping allowed the analysis of global, and genus specific activity of the microbiota, and illustrated the potential of these approaches to unravel syntrophic interactions in microbial ecosystems. CONCLUSIONS: A reliable pipeline for metatransciptome data analysis was developed and evaluated using RNA-seq datasets obtained for the human small intestine microbiota. The set-up of the pipeline is very generic and can be applied for (bacterial) metatranscriptome analysis in any chosen niche

Functional Intestinal Metagenomics (Chapter 18)

The premiere two-volume reference on revelations from studying complex microbial communities in many distinct habitats Metagenomics is an emerging field that has changed the way microbiologists study microorganisms. It involves the genomic analysis of microorganisms by extraction and cloning of DNA from a group of microorganisms, or the direct use of the purified DNA or RNA for sequencing, which allows scientists to bypass the usual protocol of isolating and culturing individual microbial species. This method is now used in laboratories across the globe to study microorganism diversity and for isolating novel medical and industrial compounds. Handbook of Molecular Microbial Ecology is the first comprehensive two-volume reference to cover unculturable microorganisms in a large variety of habitats, which could not previously have been analyzed without metagenomic methodology. It features review articles as well as a large number of case studies, based largely on original publications and written by international experts. This second volume, Metagenomics in Different Habitats, covers such topics as: •Viral genomes •Metagenomics studies in a variety of habitats, including marine environments and lakes, soil, and human and animal digestive tracts •Other habitats, including those involving microbiome diversity in human saliva and functional intestinal metagenomics; diversity of archaea in terrestrial hot springs; and microbial communities living at the surface of building stones •Biodegradation •Biocatalysts and natural products A special feature of this book is the highlighting of the databases and computer programs used in each study; they are listed along with their sites in order to facilitate the computer-assisted analysis of the vast amount of data generated by metagenomic studies. Such studies in a variety of habitats are described here, which present a large number of different system-dependent approaches in greatly differing habitats. Handbook of Molecular Microbial Ecology II is an invaluable reference for researchers in metagenomics, microbial ecology, microbiology, and environmental microbiology; those working on the Human Microbiome Project; microbial geneticists; and professionals in molecular microbiology and bioinformatics

Comparative analysis of Lactobacillus plantarum WCFS1 transcriptomes by using DNA microarray and next-generation sequencing technologies.

Item does not contain fulltextRNA sequencing is starting to compete with the use of DNA microarrays for transcription analysis in eukaryotes as well as in prokaryotes. The application of RNA sequencing in prokaryotes requires additional steps in the RNA preparation procedure to increase the relative abundance of mRNA and cannot employ the poly(T)-primed approach in cDNA synthesis. In this study, we aimed to validate the use of RNA sequencing (direct cDNA sequencing and 3'-untranslated region [UTR] sequencing) using Lactobacillus plantarum WCFS1 as a model organism, employing its established microarray platform as a reference. A limited effect of mRNA enrichment on genome-wide transcript quantification was observed, and comparative transcriptome analyses were performed for L. plantarum WCFS1 grown in two different laboratory media. Microarray analyses and both RNA sequencing methods resulted in similar depths of analysis and generated similar fold-change ratios of differentially expressed genes. The highest overall correlation was found between microarray and direct cDNA sequencing-derived transcriptomes, while the 3'-UTR sequencing-derived transcriptome appeared to deviate the most. Overall, a high similarity between patterns of transcript abundance and fold-change levels of differentially expressed genes was detected by all three methods, indicating that the biological conclusions drawn from the transcriptome data were consistent among the three technologies.01 juni 201

Sequencing the bacterial metatranscriptome associated with the marine sponge Crambe crambe

Crambe crambe was sampled from the Western Mediterranean and immediately presserved in RNA later. Total RNA was extracted en rRNA and eukaryotic mRNA were removed and the remaining bacterial mRNA (and unremoved rRNAs and eukaryotic mRNAs) were sequenced with the Illumina HiSeq using paired end sequencing

Sequencing the bacterial metatranscriptome associated with the marine sponge Crambe crambe

Crambe crambe was sampled from the Western Mediterranean and immediately presserved in RNA later. Total RNA was extracted en rRNA and eukaryotic mRNA were removed and the remaining bacterial mRNA (and unremoved rRNAs and eukaryotic mRNAs) were sequenced with the Illumina HiSeq using paired end sequencing

Mining microbial metatranscriptomes for expression of antibiotic resistance genes under natural conditions

We use a novel approach (an analysis of metatranscriptomics data) to study antibiotic resistance, a topic that poses major health care concerns. We investigate resistance gene expression in microbial communities in a diverse range of environments