Metagenomics of the effects of antibiotics on the human gut

The Pervasive Effects of an Antibiotic on the Human Gut Microbiota, as Revealed by Deep 16S rRNA Sequencing

Dethlefsen L, Huse S, Sogin ML, Relman DA
PLoS Biology Vol. 6, No. 11, e280 doi:10.1371/journal.pbio.0060280

A paper in PLOS Biology from the Relman lab investigates the effect of a treatment with the antibiotic ciprofloxacin on the bacteria in the intestine. They collected over 7,000 full-length 16S rDNA sequences (1100-1400 bp) by Sanger sequencing and over 900,000 reads (~250 bp) from 454 sequencing of the V3 and the V6 regions. 

There are many important results in this paper, but it is particularly relevant that 454 sequencing reveals more taxonomic variation with greater stability than traditional sequencing. In my own work, I have found that sequence variants that occur only once in the experiment cannot be used to differentiate samples. Deep sequencing reveals more taxa, and also reduces the frequency of singletons. A rare sequence variant (OTU) that occurs only once in the ~7000 full-length sequences occurs about 65 times in the 454 data set, providing more than enough "probability of detection" to be used for comparisons between samples. 

"This set of 7,208 sequences is among the largest datasets of full-length 16S rRNA sequences from the human microbiota (or any environment), the rarefaction curves for V6 and V3 tag pyrosequencing eventually rise higher and display more curvature toward the horizontal than the OTU0.01 curve. These features show that a single run of the [454] FLX sequencer targeting V6 or V3 tags from the human gut microbiota can reveal more taxa, and capture a larger proportion of the detectable taxa, than a more extensive effort directed toward full-length 16S rRNA clone sequencing."

CisGenome new software for Chip-Seq

CisGenome - just published in Nov. Nature Biotechnology.

An integrated software system for analyzing ChIP-chip and ChIP-seq data.
Ji H, Jiang H, Ma W, Johnson DS, Myers RM, Wong WH.
Nat Biotechnol. 2008 Nov;26(11):1293-300.

A full-function integrated bioinformatics suite for ChIP-chip and ChIP-Seq including peak-finding, FDR control for single samples, subtraction of control lane, visualization and annotation of peaks on known genomes, and Motif finding.  Functional GUI on Windows and Mac. Wow. 

Software website here:  CisGenome

http://www.biostat.jhsph.edu/~hji/cisgenome/index.htm

Abstract:

We present CisGenome, a software system for analyzing genome-wide chromatin immunoprecipitation (ChIP) data. CisGenome
is designed to meet all basic needs of ChIP data analyses, including visualization, data normalization, peak detection, false
discovery rate computation, gene-peak association, and sequence and motif analysis. In addition to implementing previously
published ChIP–microarray (ChIP-chip) analysis methods, the software contains statistical methods designed specifically
for ChlP sequencing (ChIP-seq) data obtained by coupling ChIP with massively parallel sequencing. The modular design of
CisGenome enables it to support interactive analyses through a graphic user interface as well as customized batch-mode
computation for advanced data mining. A built-in browser allows visualization of array images, signals, gene structure,
conservation, and DNA sequence and motif information. We demonstrate the use of these tools by a comparative analysis of
ChIP-chip and ChIP-seq data for the transcription factor NRSF/REST, a study of ChIP-seq analysis with or without a negative
control sample, and an analysis of a new motif in Nanog- and Sox2-binding regions.