Jonathan Livny

Bacteriophage control of Shiga toxin 1 production and release by Escherichia coli

The stx genes of many Shiga toxin‐encoding Escherichia coli (STEC) strains are encoded by prophages of the λ bacteriophage family. In the genome of the Stx1‐encoding phage H‐19B, the stx1AB genes are found ≈ 1 kb downstream of the late phage promoter, pR′, but are known to be regulated by the associated iron‐regulated promoter, pStx1. Growth of H‐19B lysogens in low iron concentrations or in conditions that induce the prophage results in increased Stx1 production. Although the mechanism by which low iron concentration induces Stx1 production is well understood, the mechanisms by which phage induction enhances toxin production have not been extensively characterized. The studies reported here identify the factors that contribute to Stx1 production after induction of the H‐19B prophage. We found that replication of the phage genome, with the associated increase in stx1AB copy number, is the most quantitatively important mechanism by which H‐19B induction increases Stx1 production. Three promoters are shown to be involved in stx1AB transcription after phage induction, the iron‐regulated pStx1 and the phage‐regulated pR and pR′ promoters, the relative importance of which varies with environmental conditions. Late phage transcription initiating at the pR′ promoter, contrary to previous findings in the related Stx2‐encoding phage φ361, was found to be unnecessary for high‐level Stx1 production after phage induction. Finally, we present evidence that phage‐mediated lysis regulates the quantity of Stx1 produced by determining the duration of Stx1 accumulation and provides a mechanism for Stx1 release. By amplifying stx1AB copy number, regulating stx1AB transcription and allowing for Stx1 release, the biology of the Stx‐encoding phages contributes greatly to the production of Stx, the principal virulence factor of STEC.

High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs.

Background Diverse bacterial genomes encode numerous small non-coding RNAs (sRNAs) that regulate myriad biological processes. While bioinformatic algorithms have proven effective in identifying sRNA-encoding loci, the lack of tools and infrastructure with which to execute these computationally demanding algorithms has limited their utilization. Genome-wide predictions of sRNA-encoding genes have been conducted in less than 3% of all sequenced bacterial strains, leading to critical gaps in current annotations. The relative paucity of genome-wide sRNA prediction represents a critical gap in current annotations of bacterial genomes and has limited examination of larger issues in sRNA biology, such as sRNA evolution. Methodology/Principal Findings We have developed and deployed SIPHT, a high throughput computational tool that utilizes workflow management and distributed computing to effectively conduct kingdom-wide predictions and annotations of intergenic sRNA-encoding genes. Candidate sRNA-encoding loci are identified based on the presence of putative Rho-independent terminators downstream of conserved intergenic sequences, and each locus is annotated for several features, including conservation in other species, association with one of several transcription factor binding sites and homology to any of over 300 previously identified sRNAs and cis-regulatory RNA elements. Using SIPHT, we conducted searches for putative sRNA-encoding genes in all 932 bacterial replicons in the NCBI database. These searches yielded nearly 60% of previously confirmed sRNAs, hundreds of previously annotated cis-encoded regulatory RNA elements such as riboswitches, and over 45,000 novel candidate intergenic loci. Conclusions/Significance Candidate loci were identified across all branches of the bacterial evolutionary tree, suggesting a central and ubiquitous role for RNA-mediated regulation among bacterial species. Annotation of candidate loci by SIPHT provides clues into the potential biological function of thousands of previously confirmed and candidate regulatory RNAs and affords new insights into the evolution of bacterial riboregulation.

Experimental discovery of sRNAs in Vibrio cholerae by direct cloning, 5S/tRNA depletion and parallel sequencing

Direct cloning and parallel sequencing, an extremely powerful method for microRNA (miRNA) discovery, has not yet been applied to bacterial transcriptomes. Here we present sRNA-Seq, an unbiased method that allows for interrogation of the entire small, non-coding RNA (sRNA) repertoire in any prokaryotic or eukaryotic organism. This method includes a novel treatment that depletes total RNA fractions of highly abundant tRNAs and small subunit rRNA, thereby enriching the starting pool for sRNA transcripts with novel functionality. As a proof-of-principle, we applied sRNA-Seq to the human pathogen Vibrio cholerae. Our results provide information, at unprecedented depth, on the complexity of the sRNA component of a bacterial transcriptome. From 407 039 sequence reads, all 20 known V. cholerae sRNAs, 500 new, putative intergenic sRNAs and 127 putative antisense sRNAs were identified in a limited number of growth conditions examined. In addition, characterization of a subset of the newly identified transcripts led to the identification of a novel sRNA regulator of carbon metabolism. Collectively, these results strongly suggest that the number of sRNAs in bacteria has been greatly underestimated and that future efforts to analyze bacterial transcriptomes will benefit from direct cloning and parallel sequencing experiments aided by 5S/tRNA depletion.

Efficient and robust RNA-seq process for cultured bacteria and complex community transcriptomes.

We have developed a process for transcriptome analysis of bacterial communities that accommodates both intact and fragmented starting RNA and combines efficient rRNA removal with strand-specific RNA-seq. We applied this approach to an RNA mixture derived from three diverse cultured bacterial species and to RNA isolated from clinical stool samples. The resulting expression profiles were highly reproducible, enriched up to 40-fold for non-rRNA transcripts, and correlated well with profiles representing undepleted total RNA.

Nucleic acid detection with CRISPR-Cas13a/C2c2

Sensitive and specific CRISPR diagnostics Methods are needed that can easily detect nucleic acids that signal the presence of pathogens, even at very low levels. Gootenberg et al. combined the allele-specific sensing ability of CRISPR-Cas13a with recombinase polymerase amplification methods to detect specific RNA and DNA sequences. The method successfully detected attomolar levels of Zika virus, as well as the presence of pathogenic bacteria. It could also be used to perform human genotyping from cell-free DNA. Science, this issue p. 438 An ortholog of CRISPR-Cas13a/C2c2 can be used as a highly sensitive detector of specific RNA and DNA sequences. Rapid, inexpensive, and sensitive nucleic acid detection may aid point-of-care pathogen detection, genotyping, and disease monitoring. The RNA-guided, RNA-targeting clustered regularly interspaced short palindromic repeats (CRISPR) effector Cas13a (previously known as C2c2) exhibits a “collateral effect” of promiscuous ribonuclease activity upon target recognition. We combine the collateral effect of Cas13a with isothermal amplification to establish a CRISPR-based diagnostic (CRISPR-Dx), providing rapid DNA or RNA detection with attomolar sensitivity and single-base mismatch specificity. We use this Cas13a-based molecular detection platform, termed Specific High-Sensitivity Enzymatic Reporter UnLOCKing (SHERLOCK), to detect specific strains of Zika and Dengue virus, distinguish pathogenic bacteria, genotype human DNA, and identify mutations in cell-free tumor DNA. Furthermore, SHERLOCK reaction reagents can be lyophilized for cold-chain independence and long-term storage and be readily reconstituted on paper for field applications.

How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?

BackgroundHigh-throughput sequencing of cDNA libraries (RNA-Seq) has proven to be a highly effective approach for studying bacterial transcriptomes. A central challenge in designing RNA-Seq-based experiments is estimating a priori the number of reads per sample needed to detect and quantify thousands of individual transcripts with a large dynamic range of abundance.ResultsWe have conducted a systematic examination of how changes in the number of RNA-Seq reads per sample influences both profiling of a single bacterial transcriptome and the comparison of gene expression among samples. Our findings suggest that the number of reads typically produced in a single lane of the Illumina HiSeq sequencer far exceeds the number needed to saturate the annotated transcriptomes of diverse bacteria growing in monoculture. Moreover, as sequencing depth increases, so too does the detection of cDNAs that likely correspond to spurious transcripts or genomic DNA contamination. Finally, even when dozens of barcoded individual cDNA libraries are sequenced in a single lane, the vast majority of transcripts in each sample can be detected and numerous genes differentially expressed between samples can be identified.ConclusionsOur analysis provides a guide for the many researchers seeking to determine the appropriate sequencing depth for RNA-Seq-based studies of diverse bacterial species.

Distribution of Centromere-Like parS Sites in Bacteria: Insights from Comparative Genomics

Partitioning of low-copy-number plasmids to daughter cells often depends on ParA and ParB proteins acting on centromere-like parS sites. Similar chromosome-encoded par loci likely also contribute to chromosome segregation. Here, we used bioinformatic approaches to search for chromosomal parS sites in 400 prokaryotic genomes. Although the consensus sequence matrix used to search for parS sites was derived from two gram-positive species, putative parS sites were identified on the chromosomes of 69% of strains from all branches of bacteria. Strains that were not found to contain parS sites clustered among relatively few branches of the prokaryotic evolutionary tree. In the vast majority of cases, parS sites were identified in origin-proximal regions of chromosomes. The widespread conservation of parS sites across diverse bacteria suggests that par loci evolved very early in the evolution of bacterial chromosomes and that the absence of parS, parA, and/or parB in certain strains likely reflects the loss of one of more of these loci much later in evolution. Moreover, the highly conserved origin-proximal position of parS suggests par loci are primarily devoted to regulating processes that involve the origin region of bacterial chromosomes. In species containing multiple chromosomes, the parS sites found on secondary chromosomes diverge significantly from those found on their primary chromosomes, suggesting that chromosome segregation of multipartite genomes requires distinct replicon-specific par loci. Furthermore, parS sites on secondary chromosomes are not well conserved among different species, suggesting that the evolutionary histories of secondary chromosomes are more diverse than those of primary chromosomes.

Characterizing spontaneous induction of Stx encoding phages using a selectable reporter system

Shiga toxin (Stx) genes in Stx producing Escherichia coli (STEC) are encoded in prophages of the λ family, such as H‐19B. The subpopulation of STEC lysogens with induced prophages has been postulated to contribute significantly to Stx production and release. To study induced STEC, we developed a selectable in vivo expression technology, SIVET, a reporter system adapted from the RIVET system. The SIVET lysogen has a defective H‐19B prophage encoding the TnpR resolvase gene downstream of the phage PR promoter and a cat gene with an inserted tet gene flanked by targets for the TnpR resolvase. Expression of resolvase results in excision of tet, restoring a functional cat gene; induced lysogens survive and are chloramphenicol resistant. Using SIVET we show that: (i) approximately 0.005% of the H‐19B lysogens are spontaneously induced per generation during growth in LB. (ii) Variations in cellular physiology (e.g. RecA protein) rather than in levels of expressed repressor explain why members of a lysogen population are spontaneously induced. (iii) A greater fraction of lysogens with stx encoding prophages are induced compared to lysogens with non‐Stx encoding prophages, suggesting increased sensitivity to inducing signal(s) has been selected in Stx encoding prophages. (iv) Only a small fraction of the lysogens in a culture spontaneously induce and when the lysogen carries two lambdoid prophages with different repressor/operators, 933W and H‐19B, usually both prophages in the same cell are induced.

sRNAPredict: an integrative computational approach to identify sRNAs in bacterial genomes

Small non-coding bacterial RNAs (sRNAs) play important regulatory roles in a variety of cellular processes. Nearly all known sRNAs have been identified in Escherichia coli and most of these are not conserved in the majority of other bacterial species. Many of the E.coli sRNAs were initially predicted through bioinformatic approaches based on their common features, namely that they are encoded between annotated open reading frames and are flanked by predictable transcription signals. Because promoter consensus sequences are undetermined for most species, the successful use of bioinformatics to identify sRNAs in bacteria other than E.coli has been limited. We have created a program, sRNAPredict, which uses coordinate-based algorithms to integrate the respective positions of individual predictive features of sRNAs and rapidly identify putative intergenic sRNAs. Relying only on sequence conservation and predicted Rho-independent terminators, sRNAPredict was used to search for sRNAs in Vibrio cholerae. This search identified 9 of the 10 known or putative V.cholerae sRNAs and 32 candidates for novel sRNAs. Small transcripts for 6 out of 9 candidate sRNAs were observed by Northern analysis. Our findings suggest that sRNAPredict can be used to efficiently identify novel sRNAs even in bacteria for which promoter consensus sequences are not available.

High-resolution definition of the Vibrio cholerae essential gene set with hidden Markov model–based analyses of transposon-insertion sequencing data

The coupling of high-density transposon mutagenesis to high-throughput DNA sequencing (transposon-insertion sequencing) enables simultaneous and genome-wide assessment of the contributions of individual loci to bacterial growth and survival. We have refined analysis of transposon-insertion sequencing data by normalizing for the effect of DNA replication on sequencing output and using a hidden Markov model (HMM)-based filter to exploit heretofore unappreciated information inherent in all transposon-insertion sequencing data sets. The HMM can smooth variations in read abundance and thereby reduce the effects of read noise, as well as permit fine scale mapping that is independent of genomic annotation and enable classification of loci into several functional categories (e.g. essential, domain essential or ‘sick’). We generated a high-resolution map of genomic loci (encompassing both intra- and intergenic sequences) that are required or beneficial for in vitro growth of the cholera pathogen, Vibrio cholerae. This work uncovered new metabolic and physiologic requirements for V. cholerae survival, and by combining transposon-insertion sequencing and transcriptomic data sets, we also identified several novel noncoding RNA species that contribute to V. cholerae growth. Our findings suggest that HMM-based approaches will enhance extraction of biological meaning from transposon-insertion sequencing genomic data.