微生物学

Gene transcription in bacteria often starts some nucleotides upstream of the start codon. Identifying the specific Transcriptional Start Site (TSS) is essential for genetic manipulation, as in many cases upstream of the start codon there are sequence elements that are involved in gene expression regulation. Taken into account the classical gene structure, we are able to identify two kinds of transcriptional start site: primary and secondary. A primary transcriptional start site is located some nucleotides upstream of the translational start site, while a secondary transcriptional start site is located within the gene encoding sequence.

Here, we present a step by step protocol for genome-wide transcriptional start sites determination by differential RNA-sequencing (dRNA-seq) using the enteric pathogen Shigella flexneri serotype 5a strain M90T as model. However, this method can be employed in any other bacterial species of choice. In the first steps, total RNA is purified from bacterial cultures using the hot phenol method. Ribosomal RNA (rRNA) is specifically depleted via hybridization probes using a commercial kit. A 5′-monophosphate-dependent exonuclease (TEX)-treated RNA library enriched in primary transcripts is then prepared for comparison with a library that has not undergone TEX-treatment, followed by ligation of an RNA linker adaptor of known sequence allowing the determination of TSS with single nucleotide precision. Finally, the RNA is processed for Illumina sequencing library preparation and sequenced as purchased service. TSS are identified by in-house bioinformatic analysis.

Our protocol is cost-effective as it minimizes the use of commercial kits and employs freely available software.

Next generation high-throughput sequencing has enabled sensitive and unambiguous analysis of RNA populations in cells. Here, we describe a method for isolation and strand-specific sequencing of small RNA pools from bacteria that can be multiplexed to accommodate multiple biological samples in a single experiment. Small RNAs are isolated by polyacrylamide gel electrophoresis and treated with T4 polynucleotide kinase. This allows for 3’ adapter ligation to CRISPR RNAs, which don’t have pre-existing 3’-OH ends. Pre-adenylated adapters are then ligated using T4 RNA ligase 1 in the absence of ATP and with a high concentration of polyethylene glycol (PEG). The 3’ capture step enables precise determination of the 3’ ends of diverse RNA molecules. Additionally, a random hexamer in the ligated adapter helps control for potential downstream amplification bias. Following reverse-transcription, the cDNA product is circularized and libraries are prepared by PCR. We show that the amplified library need not be visible by gel electrophoresis for efficient sequencing of the desired product. Using this method, we routinely prepare RNA sequencing libraries from minute amounts of purified small RNA. This protocol is tailored to assay for CRISPR RNA biogenesis in bacteria through sequencing of mature CRISPR RNAs, but can be used to sequence diverse classes of small RNAs. We also provide a fully worked example of our data processing pipeline, with instructions for running the provided scripts.

Analysis of hypervariable regions (HVR) using pyrosequencing techniques is hampered by the ability of error correction algorithms to account for the heterogeneity of the variants present. Analysis of between-sample fluctuations to virome sub-populations, and detection of low frequency variants, are unreliable through the application of arbitrary frequency cut offs. Cumulatively this leads to an underestimation of genetic diversity. In the following technique we describe the analysis of Hepatitis C virus (HCV) HVR1 which includes the E1/E2 glycoprotein gene junction. This procedure describes the evolution of HCV in a treatment naïve environment, from 10 samples collected over 10 years, using ultradeep pyrosequencing (UDPS) performed on the Roche GS FLX titanium platform (Palmer et al., 2014). Initial clonal analysis of serum samples was used to inform downstream error correction algorithms that allowed for a greater sequence depth to be reached. PCR amplification of this region has been tested for HCV genotypes 1, 2, 3 and 4.