Ovine pedomics : the first study of the ovine foot 16S rRNA-based microbiome

We report the first study of the bacterial microbiome of ovine interdigital skin based on 16S rRNA by pyrosequencing and conventional cloning with Sanger-sequencing. Three flocks were selected, one a flock with no signs of footrot or interdigital dermatitis, a second flock with interdigital dermatitis alone and a third flock with both interdigital dermatitis and footrot. The sheep were classified as having either healthy interdigital skin (H), interdigital dermatitis (ID) or virulent footrot (VFR). The ovine interdigital skin bacterial community varied significantly by flock and clinical condition. The diversity and richness of operational taxonomic units was greater in tissue from sheep with ID than H or VFR affected sheep. Actinobacteria, Bacteriodetes, Firmicutes and Proteobacteria were the most abundant phyla comprising 25 genera. Peptostreptococcus, Corynebacterium and Staphylococcus were associated with H, ID and VFR respectively. Sequences of Dichelobacter nodosus, the causal agent of ovine footrot, were not amplified due to mismatches in the 16S rRNA universal forward primer (27F). A specific real time PCR assay was used to demonstrate the presence of D. nodosus which was detected in all samples including the flock with no signs of ID or VFR. Sheep with ID had significantly higher numbers of D. nodosus (104-109 cells/g tissue) than those with H or VFR feet

Application of Two-Part Statistics for Comparison of Sequence Variant Counts

Investigation of microbial communities, particularly human associated communities, is significantly enhanced by the vast amounts of sequence data produced by high throughput sequencing technologies. However, these data create high-dimensional complex data sets that consist of a large proportion of zeros, non-negative skewed counts, and frequently, limited number of samples. These features distinguish sequence data from other forms of high-dimensional data, and are not adequately addressed by statistical approaches in common use. Ultimately, medical studies may identify targeted interventions or treatments, but lack of analytic tools for feature selection and identification of taxa responsible for differences between groups, is hindering advancement. The objective of this paper is to examine the application of a two-part statistic to identify taxa that differ between two groups. The advantages of the two-part statistic over common statistical tests applied to sequence count datasets are discussed. Results from the t-test, the Wilcoxon test, and the two-part test are compared using sequence counts from microbial ecology studies in cystic fibrosis and from cenote samples. We show superior performance of the two-part statistic for analysis of sequence data. The improved performance in microbial ecology studies was independent of study type and sequence technology used

Comparative Analysis of Pyrosequencing and a Phylogenetic Microarray for Exploring Microbial Community Structures in the Human Distal Intestine

Background Variations in the composition of the human intestinal microbiota are linked to diverse health conditions. High-throughput molecular technologies have recently elucidated microbial community structure at much higher resolution than was previously possible. Here we compare two such methods, pyrosequencing and a phylogenetic array, and evaluate classifications based on two variable 16S rRNA gene regions. Methods and Findings Over 1.75 million amplicon sequences were generated from the V4 and V6 regions of 16S rRNA genes in bacterial DNA extracted from four fecal samples of elderly individuals. The phylotype richness, for individual samples, was 1,400–1,800 for V4 reads and 12,500 for V6 reads, and 5,200 unique phylotypes when combining V4 reads from all samples. The RDP-classifier was more efficient for the V4 than for the far less conserved and shorter V6 region, but differences in community structure also affected efficiency. Even when analyzing only 20% of the reads, the majority of the microbial diversity was captured in two samples tested. DNA from the four samples was hybridized against the Human Intestinal Tract (HIT) Chip, a phylogenetic microarray for community profiling. Comparison of clustering of genus counts from pyrosequencing and HITChip data revealed highly similar profiles. Furthermore, correlations of sequence abundance and hybridization signal intensities were very high for lower-order ranks, but lower at family-level, which was probably due to ambiguous taxonomic groupings. Conclusions The RDP-classifier consistently assigned most V4 sequences from human intestinal samples down to genus-level with good accuracy and speed. This is the deepest sequencing of single gastrointestinal samples reported to date, but microbial richness levels have still not leveled out. A majority of these diversities can also be captured with five times lower sampling-depth. HITChip hybridizations and resulting community profiles correlate well with pyrosequencing-based compositions, especially for lower-order ranks, indicating high robustness of both approaches. However, incompatible grouping schemes make exact comparison difficult

The commensal infant gut meta-mobilome as a potential reservoir for persistent multidrug resistance integrons

Despite the accumulating knowledge on the development and establishment of the gut microbiota, its role as a reservoir for multidrug resistance is not well understood. This study investigated the prevalence and persistence patterns of an integrase gene (int1), used as a proxy for integrons (which often carry multiple antimicrobial resistance genes), in the fecal microbiota of 147 mothers and their children sampled longitudinally from birth to 2 years. The study showed the int1 gene was detected in 15% of the study population, and apparently more persistent than the microbial community structure itself. We found int1 to be persistent throughout the first two years of life, as well as between mothers and their 2-year-old children. Metagenome sequencing revealed integrons in the gut meta-mobilome that were associated with plasmids and multidrug resistance. In conclusion, the persistent nature of integrons in the infant gut microbiota makes it a potential reservoir of mobile multidrug resistance

Triggers of acute attacks of gout, does age of gout onset matter?: a primary care based cross-sectional study

Objectives To determine the proportion of people with gout who self-report triggers of acute attacks; identify the commonly reported triggers, and examine the disease and demographic features associated with self-reporting any trigger(s) of acute attacks of gout. Methods Individuals with gout were asked to fill a questionnaire enquiring about triggers that precipitated their acute gout attacks. Binary logistic regression was used to compute odds ratio (OR) and 95% confidence intervals (CI) to examine the association between having ≥1 self-reported trigger of acute gout and disease and demographic risk factors and to adjust for covariates. All statistical analyses were performed using STATA. Results 550 participants returned completed questionnaires. 206 (37.5%) reported at least one trigger of acute attacks, and less than 5% reported >2 triggers. Only 28.73% participants reported that their most recent gout attack was triggered by dietary or lifestyle risk factors. The most frequently self-reported triggers were alcohol intake (14.18%), red-meat or sea-food consumption (6%), dehydration (4.91%), injury or excess activity (4.91%), and excessively warm or cold weather (4.36% and 5.45%). Patients who had onset of gout before the age of 50 years were significantly more likely to identify a trigger for precipitating their acute gout attacks (aOR (95%CI) 1.73 (1.12–2.68) after adjusting for covariates. Conclusion Most people with gout do not identify any triggers for acute attacks, and identifiable triggers are more common in those with young onset gout. Less than 20% people self-reported acute gout attacks from conventionally accepted triggers of gout e.g. alcohol, red-meat intake, while c.5% reported novel triggers such as dehydration, injury or physical activity, and weather extremes

Characterisation of Gut Microbiota in Ossabaw and Göttingen Minipigs as Models of Obesity and Metabolic Syndrome

Recent evidence suggests that the gut microbiota is an important contributing factor to obesity and obesity related metabolic disorders, known as the metabolic syndrome. The aim of this study was to characterise the intestinal microbiota in two pig models of obesity namely Göttingen minipigs and the Ossabaw minipigs.The cecal, ileal and colonic microbiota from lean and obese Osabaw and Göttingen minipigs were investigated by Illumina-based sequencing and by high throughput qPCR, targeting the 16S rRNA gene in different phylogenetic groups of bacteria. The weight gain through the study was significant in obese Göttingen and Ossabaw minipigs. The lean Göttingen minipigs' cecal microbiota contained significantly higher abundance of Firmicutes (P<0.006), Akkermensia (P<0.01) and Methanovibribacter (P<0.01) than obese Göttingen minipigs. The obese Göttingen cecum had higher abundances of the phyla Spirochaetes (P<0.03), Tenericutes (P<0.004), Verrucomicrobia (P<0.005) and the genus Bacteroides (P<0.001) compared to lean minipigs. The relative proportion of Clostridium cluster XIV was 7.6-fold higher in cecal microbiota of obese Göttingen minipigs as compared to lean. Obese Ossabaw minipigs had a higher abundance of Firmicutes in terminal ileum and lower abundance of Bacteroidetes in colon than lean Ossabaw minipigs (P<0.01). Obese Ossabaws had significantly lower abundances of the genera Prevotella and Lactobacillus and higher abundance of Clostridium in their colon than the lean Ossabaws. Overall, the Göttingen and Ossabaw minipigs displayed different microbial communities in response to diet-induced obesity in the different sections of their intestine.Obesity-related changes in the composition of the gut microbiota were found in lean versus obese Göttingen and Ossabaw minipigs. In both pig models diet seems to be the defining factor that shapes the gut microbiota as observed by changes in different bacteria divisions between lean and obese minipigs

XplorSeq: A software environment for integrated management and phylogenetic analysis of metagenomic sequence data

<p>Abstract</p> <p>Background</p> <p>Advances in automated DNA sequencing technology have accelerated the generation of metagenomic DNA sequences, especially environmental ribosomal RNA gene (rDNA) sequences. As the scale of rDNA-based studies of microbial ecology has expanded, need has arisen for software that is capable of managing, annotating, and analyzing the plethora of diverse data accumulated in these projects.</p> <p>Results</p> <p>XplorSeq is a software package that facilitates the compilation, management and phylogenetic analysis of DNA sequences. XplorSeq was developed for, but is not limited to, high-throughput analysis of environmental rRNA gene sequences. XplorSeq integrates and extends several commonly used UNIX-based analysis tools by use of a Macintosh OS-X-based graphical user interface (GUI). Through this GUI, users may perform basic sequence import and assembly steps (base-calling, vector/primer trimming, contig assembly), perform BLAST (Basic Local Alignment and Search Tool; <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr><abbr bid="B3">3</abbr></abbrgrp>) searches of NCBI and local databases, create multiple sequence alignments, build phylogenetic trees, assemble Operational Taxonomic Units, estimate biodiversity indices, and summarize data in a variety of formats. Furthermore, sequences may be annotated with user-specified meta-data, which then can be used to sort data and organize analyses and reports. A document-based architecture permits parallel analysis of sequence data from multiple clones or amplicons, with sequences and other data stored in a single file.</p> <p>Conclusion</p> <p>XplorSeq should benefit researchers who are engaged in analyses of environmental sequence data, especially those with little experience using bioinformatics software. Although XplorSeq was developed for management of rDNA sequence data, it can be applied to most any sequencing project. The application is available free of charge for non-commercial use at <url>http://vent.colorado.edu/phyloware</url>.</p

Limited congruence exhibited across microbial, meiofaunal and macrofaunal benthic assemblages in a heterogeneous coastal environment

One of the most common approaches for investigating the ecology of spatially complex environments is to examine a single biotic assemblage present, such as macroinvertebrates. Underlying this approach are assumptions that sampled and unsampled taxa respond similarly to environmental gradients and exhibit congruence across different sites. These assumptions were tested for five benthic groups of various sizes (archaea, bacteria, microbial eukaryotes/protists, meiofauna and macrofauna) in Plymouth Sound, a harbour with many different pollution sources. Sediments varied in granulometry, hydrocarbon and trace metal concentrations. Following variable reduction, canonical correspondence analysis did not identify any associations between sediment characteristics and assemblage composition of archaea or macrofauna. In contrast, variation in bacteria was associated with granulometry, trace metal variations and bioturbation (e.g. community bioturbation potential). Protists varied with granulometry, hydrocarbon and trace metal predictors. Meiofaunal variation was associated with hydrocarbon and bioturbation predictors. Taxon turnover between sites varied with only three out of 10 group pairs showing congruence (meiofauna-protists, meiofauna-macrofauna and protists-macrofauna). While our results support using eukaryotic taxa as proxies for others, the lack of congruence suggests caution should be applied to inferring wider indicator or functional interpretations from studies of a single biotic assemblage

AxPcoords & parallel AxParafit: statistical co-phylogenetic analyses on thousands of taxa

Background Current tools for Co-phylogenetic analyses are not able to cope with the continuous accumulation of phylogenetic data. The sophisticated statistical test for host-parasite co-phylogenetic analyses implemented in Parafit does not allow it to handle large datasets in reasonable times. The Parafit and DistPCoA programs are the by far most compute-intensive components of the Parafit analysis pipeline. We present AxParafit and AxPcoords (Ax stands for Accelerated) which are highly optimized versions of Parafit and DistPCoA respectively. Results Both programs have been entirely re-written in C. Via optimization of the algorithm and the C code as well as integration of highly tuned BLAS and LAPACK methods AxParafit runs 5–61 times faster than Parafit with a lower memory footprint (up to 35% reduction) while the performance benefit increases with growing dataset size. The MPI-based parallel implementation of AxParafit shows good scalability on up to 128 processors, even on medium-sized datasets. The parallel analysis with AxParafit on 128 CPUs for a medium-sized dataset with an 512 by 512 association matrix is more than 1,200/128 times faster per processor than the sequential Parafit run. AxPcoords is 8–26 times faster than DistPCoA and numerically stable on large datasets. We outline the substantial benefits of using parallel AxParafit by example of a large-scale empirical study on smut fungi and their host plants. To the best of our knowledge, this study represents the largest co-phylogenetic analysis to date. Conclusion The highly efficient AxPcoords and AxParafit programs allow for large-scale co-phylogenetic analyses on several thousands of taxa for the first time. In addition, AxParafit and AxPcoords have been integrated into the easy-to-use CopyCat tool