Evaluation of Algorithm Performance in ChIP-Seq Peak Detection

Next-generation DNA sequencing coupled with chromatin immunoprecipitation (ChIP-seq) is revolutionizing our ability to interrogate whole genome protein-DNA interactions. Identification of protein binding sites from ChIP-seq data has required novel computational tools, distinct from those used for the analysis of ChIP-Chip experiments. The growing popularity of ChIP-seq spurred the development of many different analytical programs (at last count, we noted 31 open source methods), each with some purported advantage. Given that the literature is dense and empirical benchmarking challenging, selecting an appropriate method for ChIP-seq analysis has become a daunting task. Herein we compare the performance of eleven different peak calling programs on common empirical, transcription factor datasets and measure their sensitivity, accuracy and usability. Our analysis provides an unbiased critical assessment of available technologies, and should assist researchers in choosing a suitable tool for handling ChIP-seq data

Primer selection impacts specific population abundances but not community dynamics in a monthly time-series 16S rRNA gene amplicon analysis of coastal marine bacterioplankton.

Primers targeting the 16S small subunit ribosomal RNA marker gene, used to characterize bacterial and archaeal communities, have recently been re-evaluated for marine planktonic habitats. To investigate whether primer selection affects the ecological interpretation of bacterioplankton populations and community dynamics, amplicon sequencing with four primer sets targeting several hypervariable regions of the 16S rRNA gene was conducted on both mock communities constructed from cloned 16S rRNA genes and a time-series of DNA samples from the temperate coastal Santa Barbara Channel. Ecological interpretations of community structure (delineation of depth and seasonality, correlations with environmental factors) were similar across primer sets, while population dynamics varied. We observed substantial differences in relative abundances of taxa known to be poorly resolved by some primer sets, such as Thaumarchaeota and SAR11, and unexpected taxa including Roseobacter clades. Though the magnitude of relative abundances of common OTUs differed between primer sets, the relative abundances of the OTUs were nonetheless strongly correlated. We do not endorse one primer set but rather enumerate strengths and weaknesses to facilitate selection appropriate to a system or experimental goal. While 16S rRNA gene primer bias suggests caution in assessing quantitative population dynamics, community dynamics appear robust across studies using different primers

A Monte Carlo-based framework enhances the discovery and interpretation of regulatory sequence motifs

Abstract Background Discovery of functionally significant short, statistically overrepresented subsequence patterns (motifs) in a set of sequences is a challenging problem in bioinformatics. Oftentimes, not all sequences in the set contain a motif. These non-motif-containing sequences complicate the algorithmic discovery of motifs. Filtering the non-motif-containing sequences from the larger set of sequences while simultaneously determining the identity of the motif is, therefore, desirable and a non-trivial problem in motif discovery research. Results We describe MotifCatcher, a framework that extends the sensitivity of existing motif-finding tools by employing random sampling to effectively remove non-motif-containing sequences from the motif search. We developed two implementations of our algorithm; each built around a commonly used motif-finding tool, and applied our algorithm to three diverse chromatin immunoprecipitation (ChIP) data sets. In each case, the motif finder with the MotifCatcher extension demonstrated improved sensitivity over the motif finder alone. Our approach organizes candidate functionally significant discovered motifs into a tree, which allowed us to make additional insights. In all cases, we were able to support our findings with experimental work from the literature. Conclusions Our framework demonstrates that additional processing at the sequence entry level can significantly improve the performance of existing motif-finding tools. For each biological data set tested, we were able to propose novel biological hypotheses supported by experimental work from the literature. Specifically, in Escherichia coli, we suggested binding site motifs for 6 non-traditional LexA protein binding sites; in Saccharomyces cerevisiae, we hypothesize 2 disparate mechanisms for novel binding sites of the Cse4p protein; and in Halobacterium sp. NRC-1, we discoverd subtle differences in a general transcription factor (GTF) binding site motif across several data sets. We suggest that small differences in our discovered motif could confer specificity for one or more homologous GTF proteins. We offer a free implementation of the MotifCatcher software package at http://www.bme.ucdavis.edu/facciotti/resources_data/software/ .http://deepblue.lib.umich.edu/bitstream/2027.42/112965/1/12859_2012_Article_5570.pd

Microscale sulfur cycling in the phototrophic pink berry consortia of the Sippewissett Salt Marsh

Microbial metabolism is the engine that drives global biogeochemical cycles, yet many key transformations are carried out by microbial consortia over short spatiotemporal scales that elude detection by traditional analytical approaches. We investigate syntrophic sulfur cycling in the ‘pink berry’ consortia of the Sippewissett Salt Marsh through an integrative study at the microbial scale. The pink berries are macroscopic, photosynthetic microbial aggregates composed primarily of two closely associated species: sulfide-oxidizing purple sulfur bacteria (PB-PSB1) and sulfate-reducing bacteria (PB-SRB1). Using metagenomic sequencing and 34S-enriched sulfate stable isotope probing coupled with nanoSIMS, we demonstrate interspecies transfer of reduced sulfur metabolites from PB-SRB1 to PB-PSB1. The pink berries catalyse net sulfide oxidation and maintain internal sulfide concentrations of 0–500 μm. Sulfide within the berries, captured on silver wires and analysed using secondary ion mass spectrometer, increased in abundance towards the berry interior, while δ34S-sulfide decreased from 6‰ to −31‰ from the exterior to interior of the berry. These values correspond to sulfate–sulfide isotopic fractionations (15–53‰) consistent with either sulfate reduction or a mixture of reductive and oxidative metabolisms. Together this combined metagenomic and high-resolution isotopic analysis demonstrates active sulfur cycling at the microscale within well-structured macroscopic consortia consisting of sulfide-oxidizing anoxygenic phototrophs and sulfate-reducing bacteria

A workflow for genome-wide mapping of archaeal transcription factors with ChIP-seq

Deciphering the structure of gene regulatory networks across the tree of life remains one of the major challenges in postgenomic biology. We present a novel ChIP-seq workflow for the archaea using the model organism Halobacterium salinarum sp. NRC-1 and demonstrate its application for mapping the genome-wide binding sites of natively expressed transcription factors. This end-to-end pipeline is the first protocol for ChIP-seq in archaea, with methods and tools for each stage from gene tagging to data analysis and biological discovery. Genome-wide binding sites for transcription factors with many binding sites (TfbD) are identified with sensitivity, while retaining specificity in the identification the smaller regulons (bacteriorhodopsin-activator protein). Chromosomal tagging of target proteins with a compact epitope facilitates a standardized and cost-effective workflow that is compatible with high-throughput immunoprecipitation of natively expressed transcription factors. The Pique package, an open-source bioinformatics method, is presented for identification of binding events. Relative to ChIP-Chip and qPCR, this workflow offers a robust catalog of protein–DNA binding events with improved spatial resolution and significantly decreased cost. While this study focuses on the application of ChIP-seq in H. salinarum sp. NRC-1, our workflow can also be adapted for use in other archaea and bacteria with basic genetic tools

Microscale sulfur cycling in the phototrophic pink berry consortia of the Sippewissett Salt Marsh

Microbial metabolism is the engine that drives global biogeochemical cycles, yet many key transformations are carried out by microbial consortia over short spatiotemporal scales that elude detection by traditional analytical approaches. We investigate syntrophic sulfur cycling in the ‘pink berry’ consortia of the Sippewissett Salt Marsh through an integrative study at the microbial scale. The pink berries are macroscopic, photosynthetic microbial aggregates composed primarily of two closely associated species: sulfide-oxidizing purple sulfur bacteria (PB-PSB1) and sulfate-reducing bacteria (PB-SRB1). Using metagenomic sequencing and 34S-enriched sulfate stable isotope probing coupled with nanoSIMS, we demonstrate interspecies transfer of reduced sulfur metabolites from PB-SRB1 to PB-PSB1. The pink berries catalyse net sulfide oxidation and maintain internal sulfide concentrations of 0–500 μm. Sulfide within the berries, captured on silver wires and analysed using secondary ion mass spectrometer, increased in abundance towards the berry interior, while δ34S-sulfide decreased from 6‰ to −31‰ from the exterior to interior of the berry. These values correspond to sulfate–sulfide isotopic fractionations (15–53‰) consistent with either sulfate reduction or a mixture of reductive and oxidative metabolisms. Together this combined metagenomic and high-resolution isotopic analysis demonstrates active sulfur cycling at the microscale within well-structured macroscopic consortia consisting of sulfide-oxidizing anoxygenic phototrophs and sulfate-reducing bacteria