Patrick Ng

Low‐diversity bacterial community in the gut of the fruitfly Drosophila melanogaster

The bacteria in the fruitfly Drosophila melanogaster of different life stages was quantified by 454 pyrosequencing of 16S rRNA gene amplicons. The sequence reads were dominated by 5 operational taxonomic units (OTUs) at ≤ 97% sequence identity that could be assigned to Acetobacter pomorum, A. tropicalis, Lactobacillus brevis, L. fructivorans and L. plantarum. The saturated rarefaction curves and species richness indices indicated that the sampling (85,000-159,000 reads per sample) was comprehensive. Parallel diagnostic PCR assays revealed only minor variation in the complement of the five bacterial species across individual insects and three D. melanogaster strains. Other gut-associated bacteria included 6 OTUs with low %ID to previously reported sequences, raising the possibility that they represent novel taxa within the genera Acetobacter and Lactobacillus. A developmental change in the most abundant species, from L. fructivorans in young adults to A. pomorum in aged adults was identified; changes in gut oxygen tension or immune system function might account for this effect. Host immune responses and disturbance may also contribute to the low bacterial diversity in the Drosophila gut habitat.

Apples to apples

MOTIVATION Effective algorithms for finding relatively weak motifs are an important practical necessity while scanning long DNA sequences for regulatory elements. The success of such an algorithm hinges on the ability of its scoring function combined with a significance analysis test to discern real motifs from random noise. RESULTS In the first half of the paper we show that the paradigm of relying on entropy scores and their E-values can lead to undesirable results when searching for weak motifs and we offer alternate approaches to analyzing the significance of motifs. In the second half of the paper we reintroduce a scoring function and present a motif-finder that optimizes it that are more effective in finding relatively weak motifs than other tools. AVAILABILITY The GibbsILR motif finder is available at http://www.cs.cornell.edu/~keich.

GIMSAN: a Gibbs motif finder with significance analysis

UNLABELLED We present GIMSAN (GIbbsMarkov with Significance ANalysis): a novel tool for de novo motif finding. GIMSAN combines GibbsMarkov, our variant of the Gibbs Sampler, described here for the first time, with our recently introduced significance analysis. AVAILABILITY GIMSAN is currently available as a web application and a stand-alone application on Unix and PBS (Portable Batch System) cluster through links from http://www.cs.cornell.edu/~keich.

REFINING MOTIF FINDERS WITH E-VALUE CALCULATIONS

Motif finders are an important tool for searching for regulatory elements in DNA. Popular existing programs optimize the entropy score to efficiently search for motifs. While E-values are commonly used for assigning significance to the optimal reported motifs they are not directly optimized for. This raises the question whether optimizing for E-values instead of entropy could improve the finders’ ability to detect weak motifs. We first present an efficient algorithm to accurately compute multiple E-values which changes the nature of the above question from a hypothetical to a practical one. Incorporating this method into CONSENSUSand Gibbs-based finders we then demonstrate on synthetic data that the answer to our question is positive. In particular, E-value based optimizations show significant improvement over existing tools for finding motifs of unknown width.

16SpeB: Towards defining bacterial species boundaries by intra-species gene sequence identity

Summary 16SpeB (16S rRNA-based Species Boundary) is a package of Perl programs that evaluates total sequence variation of a bacterial species at the levels of the whole 16S rRNA sequences or single hypervariable (V) regions, using publicly-available sequences. The 16SpeB pipelines filter sequences from duplicated strains and of low quality, extracts a V region of interest using general primer sequences, and calculates sequence percentage identity (%ID) through all possible pairwise alignments. Results The minimum %ID of 16S rRNA gene sequences for 15 clinically-important bacterial species, as determined by 16SpeB, ranged from 82.6% to 99.8%. The relationship between minimum %ID of V2/V6 regions and full-gene sequences varied among species, indicating that %ID species limits should be resolved independently for each region of the 16S rRNA gene and bacterial species. Availability 16SpeB and user manual are freely available for download from: https://github.com/pnpnpn/16SpeB. A video tutorial is available at: https://youtu.be/Vd6YmMhyBiA Contact cw442@cornell.edu Supplementary information Supplementary data are available at Bioinformatics online.