Colonic microbiota is associated with inflammation and host epigenomic alterations in inflammatory bowel disease.

Studies of inflammatory bowel disease (IBD) have been inconclusive in relating microbiota with distribution of inflammation. We report microbiota, host transcriptomics, epigenomics and genetics from matched inflamed and non-inflamed colonic mucosa [50 Crohn's disease (CD); 80 ulcerative colitis (UC); 31 controls]. Changes in community-wide and within-patient microbiota are linked with inflammation, but we find no evidence for a distinct microbial diagnostic signature, probably due to heterogeneous host-microbe interactions, and show only marginal microbiota associations with habitual diet. Epithelial DNA methylation improves disease classification and is associated with both inflammation and microbiota composition. Microbiota sub-groups are driven by dominant Enterbacteriaceae and Bacteroides species, representative strains of which are pro-inflammatory in vitro, are also associated with immune-related epigenetic markers. In conclusion, inflamed and non-inflamed colonic segments in both CD and UC differ in microbiota composition and epigenetic profiles.

Bacterial communities in commercial aircraft high-efficiency particulate air (HEPA) filters assessed by PhyloChip analysis.

UNLABELLED: Air travel can rapidly transport infectious diseases globally. To facilitate the design of biosensors for infectious organisms in commercial aircraft, we characterized bacterial diversity in aircraft air. Samples from 61 aircraft high-efficiency particulate air (HEPA) filters were analyzed with a custom microarray of 16S rRNA gene sequences (PhyloChip), representing bacterial lineages. A total of 606 subfamilies from 41 phyla were detected. The most abundant bacterial subfamilies included bacteria associated with humans, especially skin, gastrointestinal and respiratory tracts, and with water and soil habitats. Operational taxonomic units that contain important human pathogens as well as their close, more benign relatives were detected. When compared to 43 samples of urban outdoor air, aircraft samples differed in composition, with higher relative abundance of Firmicutes and Gammaproteobacteria lineages in aircraft samples, and higher relative abundance of Actinobacteria and Betaproteobacteria lineages in outdoor air samples. In addition, aircraft and outdoor air samples differed in the incidence of taxa containing human pathogens. Overall, these results demonstrate that HEPA filter samples can be used to deeply characterize bacterial diversity in aircraft air and suggest that the presence of close relatives of certain pathogens must be taken into account in probe design for aircraft biosensors. PRACTICAL IMPLICATIONS: A biosensor that could be deployed in commercial aircraft would be required to function at an extremely low false alarm rate, making an understanding of microbial background important. This study reveals a diverse bacterial background present on aircraft, including bacteria closely related to pathogens of public health concern. Furthermore, this aircraft background is different from outdoor air, suggesting different probes may be needed to detect airborne contaminants to achieve minimal false alarm rates. This study also indicates that aircraft HEPA filters could be used with other molecular techniques to further characterize background bacteria and in investigations in the wake of a disease outbreak.

Loss of bacterial diversity during antibiotic treatment of intubated patients colonized with Pseudomonas aeruginosa.

Management of airway infections caused by Pseudomonas aeruginosa is a serious clinical challenge, but little is known about the microbial ecology of airway infections in intubated patients. We analyzed bacterial diversity in endotracheal aspirates obtained from intubated patients colonized by P. aeruginosa by using 16S rRNA clone libraries and microarrays (PhyloChip) to determine changes in bacterial community compositions during antibiotic treatment. Bacterial 16S rRNA genes were absent from aspirates obtained from patients briefly intubated for elective surgery but were detected by PCR in samples from all patients intubated for longer periods. Sequencing of 16S rRNA clone libraries demonstrated the presence of many orally, nasally, and gastrointestinally associated bacteria, including known pathogens, in the lungs of patients colonized with P. aeruginosa. PhyloChip analysis detected the same organisms and many additional bacterial groups present at low abundance that were not detected in clone libraries. For each patient, both culture-independent methods showed that bacterial diversity decreased following the administration of antibiotics, and communities became dominated by a pulmonary pathogen. P. aeruginosa became the dominant species in six of seven patients studied, despite treatment of five of these six with antibiotics to which it was sensitive in vitro. Our data demonstrate that the loss of bacterial diversity under antibiotic selection is highly associated with the development of pneumonia in ventilated patients colonized with P. aeruginosa. Interestingly, PhyloChip analysis demonstrated reciprocal changes in abundance between P. aeruginosa and the class Bacilli, suggesting that these groups may compete for a similar ecological niche and suggesting possible mechanisms through which the loss of microbial diversity may directly contribute to pathogen selection and persistence.

NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes.

Microbiologists conducting surveys of bacterial and archaeal diversity often require comparative alignments of thousands of 16S rRNA genes collected from a sample. The computational resources and bioinformatics expertise required to construct such an alignment has inhibited high-throughput analysis. It was hypothesized that an online tool could be developed to efficiently align thousands of 16S rRNA genes via the NAST (Nearest Alignment Space Termination) algorithm for creating multiple sequence alignments (MSA). The tool was implemented with a web-interface at http://greengenes.lbl.gov/NAST. Each user-submitted sequence is compared with Greengenes' 'Core Set', comprising approximately 10,000 aligned non-chimeric sequences representative of the currently recognized diversity among bacteria and archaea. User sequences are oriented and paired with their closest match in the Core Set to serve as a template for inserting gap characters. Non-16S data (sequence from vector or surrounding genomic regions) are conveniently removed in the returned alignment. From the resulting MSA, distance matrices can be calculated for diversity estimates and organisms can be classified by taxonomy. The ability to align and categorize large sequence sets using a simple interface has enabled researchers with various experience levels to obtain bacterial and archaeal community profiles.

Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB.

A 16S rRNA gene database (http://greengenes.lbl.gov) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. It was found that there is incongruent taxonomic nomenclature among curators even at the phylum level. Putative chimeras were identified in 3% of environmental sequences and in 0.2% of records derived from isolates. Environmental sequences were classified into 100 phylum-level lineages in the Archaea and Bacteria.

Comprehensive aligned sequence construction for automated design of effective probes (CASCADE-P) using 16S rDNA.

MOTIVATION: Prokaryotic organisms have been identified utilizing the sequence variation of the 16S rRNA gene. Variations steer the design of DNA probes for the detection of taxonomic groups or specific organisms. The long-term goal of our project is to create probe arrays capable of identifying 16S rDNA sequences in unknown samples. This necessitated the authentication, categorization and alignment of the >75 000 publicly available '16S' sequences. Preferably, the entire process should be computationally administrated so the aligned collection could periodically absorb 16S rDNA sequences from the public records. A complete multiple sequence alignment would provide a foundation for computational probe selection and facilitates microbial taxonomy and phylogeny. RESULTS: Here we report the alignment and similarity clustering of 62 662 16S rDNA sequences and an approach for designing effective probes for each cluster. A novel alignment compression algorithm, NAST (Nearest Alignment Space Termination), was designed to produce the uniform multiple sequence alignment referred to as the prokMSA. From the prokMSA, 9020 Operational Taxonomic Units (OTUs) were found based on transitive sequence similarities. An automated approach to probe design was straightforward using the prokMSA clustered into OTUs. As a test case, multiple probes were computationally picked for each of the 27 OTUs that were identified within the Staphylococcus Group. The probes were incorporated into a customized microarray and were able to correctly categorize Staphylococcus aureus and Bacillus anthracis into their correct OTUs. Although a successful probe picking strategy is outlined, the main focus of creating the prokMSA was to provide a comprehensive, categorized, updateable 16S rDNA collection useful as a foundation for any probe selection algorithm.

Sequence-specific identification of 18 pathogenic microorganisms using microarray technology.

We have developed a Multi-Pathogen Identification (MPID) microarray for high confidence identification of eighteen pathogenic prokaryotes, eukaryotes and viruses. Analysis of amplified products from pathogen genomic DNA using microarray hybridization allows for highly specific and sensitive detection, and allows the discrimination between true amplification products and false positive amplification products that might be derived from primers annealing to non-target sequences. Species-specific primer sets were used to amplify multiple diagnostic regions unique to each individual pathogen. Amplified products were washed over the surface of the microarray, and labelled with phycoerythrin-streptavidin for fluorescence detection. A series of overlapping 20-mer oligonucleotide probes hybridize to the entire diagnostic region, while parallel hybridizations on the same surface allow simultaneous screening for all organisms. Comparison to probes that differ by a single mismatch at the central position reduced the contribution of non-specific hybridization. Samples containing individual pathogens were analyzed in separate experiments and the corresponding species-specific diagnostic regions were identified by fluorescence among their highly redundant probe sets. On average, 91% of the 53 660 pathogen probes on the MPID microarray performed as predicted. The limit of detection was found to be as little as 10 fg of B. anthracis DNA in samples that were amplified with six diagnostic primer-pairs. In contrast, PCR products were not observed at this concentration when identical samples were prepared and visualized by agarose gel electrophoresis.

Development of a high-volume aerosol collection system for the identification of air-borne micro-organisms.

AIMS: A high-volume aerosol collector was developed to efficiently capture airborne bacteria in order to assess levels of diversity in the air. METHODS AND RESULTS: Particulate matter was collected on a device designed to filter 1.4 x 10(6) litres of air in a 24 h period on a 1-microm pore size polyester membrane. Methods were optimized for extraction of genomic DNA from the air filter concentrate. Preparation times of 90 s with 0.5-0. 05 mm diameter zirconia/silica beads yielded the highest concentration genomic DNA that was able to support PCR. A 24-h air sample was taken in Salt Lake City, Utah and the microbial composition was determined by the amplification and sequence analysis of 16S ribosomal DNA fragments. CONCLUSIONS: Sequence analysis revealed a large diversity in the type of microbial species present including clones matching the sequence of Clostridium botulinum. The primary components of the aerosol sample included many different spore-forming bacteria as well as more fragile members of the Proteobacteria division. SIGNIFICANCE AND IMPACT OF STUDY: The high-volume air collection and genomic DNA recovery system allows for the rapid detection of both cultivable as well as culture-resistant organisms in the environment.