CRISPRi screen for enhancing heterologous α-amylase yield in Bacillus subtilis.

Yield improvements in cell factories can potentially be obtained by fine-tuning the regulatory mechanisms for gene candidates. In pursuit of such candidates, we performed RNA-sequencing of two α-amylase producing Bacillus strains and predict hundreds of putative novel non-coding transcribed regions. Surprisingly, we found among hundreds of non-coding and structured RNA candidates that non-coding genomic regions are proportionally undergoing the highest changes in expression during fermentation. Since these classes of RNA are also understudied, we targeted the corresponding genomic regions with CRIPSRi knockdown to test for any potential impact on the yield. From differentially expression analysis, we selected 53 non-coding candidates. Although CRISPRi knockdowns target both the sense and the antisense strand, the CRISPRi experiment cannot link causes for yield changes to the sense or antisense disruption. Nevertheless, we observed on several instances with strong changes in enzyme yield. The knockdown targeting the genomic region for a putative antisense RNA of the 3' UTR of the skfA-skfH operon led to a 21% increase in yield. In contrast, the knockdown targeting the genomic regions of putative antisense RNAs of the cytochrome c oxidase subunit 1 (ctaD), the sigma factor sigH, and the uncharacterized gene yhfT decreased yields by 31 to 43%.

BSGatlas: a unified Bacillus subtilis genome and transcriptome annotation atlas with enhanced information access.

A large part of our current understanding of gene regulation in Gram-positive bacteria is based on Bacillus subtilis, as it is one of the most well studied bacterial model systems. The rapid growth in data concerning its molecular and genomic biology is distributed across multiple annotation resources. Consequently, the interpretation of data from further B. subtilis experiments becomes increasingly challenging in both low- and large-scale analyses. Additionally, B. subtilis annotation of structured RNA and non-coding RNA (ncRNA), as well as the operon structure, is still lagging behind the annotation of the coding sequences. To address these challenges, we created the B. subtilis genome atlas, BSGatlas, which integrates and unifies multiple existing annotation resources. Compared to any of the individual resources, the BSGatlas contains twice as many ncRNAs, while improving the positional annotation for 70 % of the ncRNAs. Furthermore, we combined known transcription start and termination sites with lists of known co-transcribed gene sets to create a comprehensive transcript map. The combination with transcription start/termination site annotations resulted in 717 new sets of co-transcribed genes and 5335 untranslated regions (UTRs). In comparison to existing resources, the number of 5' and 3' UTRs increased nearly fivefold, and the number of internal UTRs doubled. The transcript map is organized in 2266 operons, which provides transcriptional annotation for 92 % of all genes in the genome compared to the at most 82 % by previous resources. We predicted an off-target-aware genome-wide library of CRISPR-Cas9 guide RNAs, which we also linked to polycistronic operons. We provide the BSGatlas in multiple forms: as a website (https://rth.dk/resources/bsgatlas/), an annotation hub for display in the UCSC genome browser, supplementary tables and standardized GFF3 format, which can be used in large scale -omics studies. By complementing existing resources, the BSGatlas supports analyses of the B. subtilis genome and its molecular biology with respect to not only non-coding genes but also genome-wide transcriptional relationships of all genes.

Detection of internal N7-methylguanosine (m7G) RNA modifications by mutational profiling sequencing.

Methylation of guanosine on position N7 (m7G) on internal RNA positions has been found in all domains of life and have been implicated in human disease. Here, we present m7G Mutational Profiling sequencing (m7G-MaP-seq), which allows high throughput detection of m7G modifications at nucleotide resolution. In our method, m7G modified positions are converted to abasic sites by reduction with sodium borohydride, directly recorded as cDNA mutations through reverse transcription and sequenced. We detect positions with increased mutation rates in the reduced and control samples taking the possibility of sequencing/alignment error into account and use replicates to calculate statistical significance based on log likelihood ratio tests. We show that m7G-MaP-seq efficiently detects known m7G modifications in rRNA with mutational rates up to 25% and we map a previously uncharacterised evolutionarily conserved rRNA modification at position 1581 in Arabidopsis thaliana SSU rRNA. Furthermore, we identify m7G modifications in budding yeast, human and arabidopsis tRNAs and demonstrate that m7G modification occurs before tRNA splicing. We do not find any evidence for internal m7G modifications being present in other small RNA, such as miRNA, snoRNA and sRNA, including human Let-7e. Likewise, high sequencing depth m7G-MaP-seq analysis of mRNA from E. coli or yeast cells did not identify any internal m7G modifications.

Excess primer degradation by Exo I improves the preparation of 3' cDNA ligation-based sequencing libraries.

RNA sequencing library construction using single-stranded ligation of a DNA adapter to 3' ends of cDNAs often produces primer-adapter byproducts, which compete with cDNA-adapter ligation products during library amplification and, therefore, reduces the number of informative sequencing reads. We find that Escherichia coli Exo I digestion efficiently and selectively removes surplus reverse transcription primer and thereby reduces the primer-adapter product contamination in 3' cDNA ligation-based sequencing libraries, including small RNA libraries, which are typically similar in size to the primer-adapter products. We further demonstrate that Exo I treatment does not lead to trimming of the cDNA 3' end when duplexed with the RNA template. Exo I digestion is easy to perform and implement in other protocols and could facilitate a more widespread use of 3' cDNA ligation for sequencing-based applications.

RNA-Seq for Bacterial Gene Expression.

RNA sequencing (RNA-seq) has become the preferred method for global quantification of bacterial gene expression. With the continued improvements in sequencing technology and data analysis tools, the most labor-intensive and expensive part of an RNA-seq experiment is the preparation of sequencing libraries, which is also essential for the quality of the data obtained. Here, we present a straightforward and inexpensive basic protocol for preparation of strand-specific RNA-seq libraries from bacterial RNA as well as a computational pipeline for the data analysis of sequencing reads. The protocol is based on the Illumina platform and allows easy multiplexing of samples and the removal of sequencing reads that are PCR duplicates. © 2018 by John Wiley & Sons, Inc.

SHAPE Selection (SHAPES) enrich for RNA structure signal in SHAPE sequencing-based probing data.

Selective 2' Hydroxyl Acylation analyzed by Primer Extension (SHAPE) is an accurate method for probing of RNA secondary structure. In existing SHAPE methods, the SHAPE probing signal is normalized to a no-reagent control to correct for the background caused by premature termination of the reverse transcriptase. Here, we introduce a SHAPE Selection (SHAPES) reagent, N-propanone isatoic anhydride (NPIA), which retains the ability of SHAPE reagents to accurately probe RNA structure, but also allows covalent coupling between the SHAPES reagent and a biotin molecule. We demonstrate that SHAPES-based selection of cDNA-RNA hybrids on streptavidin beads effectively removes the large majority of background signal present in SHAPE probing data and that sequencing-based SHAPES data contain the same amount of RNA structure data as regular sequencing-based SHAPE data obtained through normalization to a no-reagent control. Moreover, the selection efficiently enriches for probed RNAs, suggesting that the SHAPES strategy will be useful for applications with high-background and low-probing signal such as in vivo RNA structure probing.