STEP SEQ IP HOW TO

STEP SEQ IP HOW TO

Several methods and review articles describe in detail how to perform ChIP-chip and ChIP-seq experiments, and we encourage readers to also review these publications.

Aspects of the ChIP-seq method and resulting data analysis will be described in detail throughout this review ( Figure 1). We encourage those interested in performing ChIP-seq experiments or variations on ChIP-seq to review other studies if they want a broader sense of the experimental and analytical variables.Дў.1 General Overview of ChIP-seq ProcedureД¬hIP-seq reports on the DNA sequences that can be cross-linked by formaldehyde to a given transcription factor in actively growing cells and then enriched relative to genomic DNA when the DNA-protein complexes are precipitated by use of an antibody specific to the transcription factor. ChIP-exo has shown promise in the few bacterial studies where it has been used but the analysis of ChIP-exo data has its own unique issues including sample preparation and data analysis. It is beyond the scope of this review to provide a comprehensive description of known variations of ChIP-seq analysis, including the higher resolution variant, ChIP-exo. It is important to note that analysis of ChIP-seq data in bacteria is an evolving pipeline and as such, new approaches and algorithms are being introduced frequently.

We offer a general overview of each step and highlight specific analyses that have aided our work. Here, we provide an overview to using ChIP-seq to identify bacterial regulons, from sample preparation, data generation, data visualization, data analysis, and downstream bioinformatic and computational analyses. A subset of these studies also correlated occupancy data with expression data to investigate the regulons of certain TFs, and we predict the desire to use these assays to study other TFs will increase as the costs of the performing ChIP-seq decrease. While many of the studies have focused on TFs in Escherichia coli, recent studies have examined transcription factors in many diverse bacterial species, such as Vibrio cholerae, Vibrio harveyi, Rhodobacter sphaeroides, Salmonella enterica, Mycobacterium tuberculosis, and Caulobacter crescentus. While it is possible to characterize binding to these regions using in vitro assays, recent advances in genome wide analysis, make identification of these binding sites possible in vivo, allowing identification of binding events under the same growth conditions that RNA levels were determined.Д¬hromatin immunoprecipitation (ChIP) followed by microarray analysis (ChIP-chip) or, more recently, high-throughput sequencing (ChIP-seq), which has a much higher resolution and signal-to-noise ratio than ChIP-chip, has been used to map genome-wide binding of many bacterial TFs. This requires identification of TF binding within the appropriate promoter region. However, whole-genome expression analyses cannot reveal whether the influence of the TF on RNA levels is direct or indirect. By comparing RNA profiles of strains lacking the transcription factor to their parent strain, using either microarray technology or high-throughput sequencing technology, candidate genes controlled by a transcription factor can be identified. Identifying all the genes directly regulated by a transcription factor can be challenging particularly for those that regulate a large number of genes and whose DNA binding sites might be less conserved and thus difficult to identify using bioinformatic approaches. Transcriptional regulation of gene expression by transcription factors (TFs) is a common mechanism of regulation in bacteria.

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