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Background
Prokaryotes have relatively small genomes, densely-packed with protein-encoding sequences. RNA sequencing has, however, revealed surprisingly complex transcriptomes and here we report the transcripts present in the model hyperthermophilic Archaeon, Thermococcus kodakarensis, under different physiological conditions.
Results
Sequencing cDNA libraries, generated from RNA isolated from cells under different growth and metabolic conditions has identified >2,700 sites of transcription initiation, established a genome-wide map of transcripts, and consensus sequences for transcription initiation and post-transcription regulatory elements. The primary transcription start sites (TSS) upstream of 1,254 annotated genes, plus 644 primary TSS and their promoters within genes, are identified. Most mRNAs have a 5'-untranslated region (5'-UTR) 10 to 50 nt long (median = 16 nt), but ~20% have 5'-UTRs from 50 to 300 nt long and ~14% are leaderless. Approximately 50% of mRNAs contain a consensus ribosome binding sequence. The results identify TSS for 1,018 antisense transcripts, most with sequences complementary to either the 5'- or 3'-region of a sense mRNA, and confirm the presence of transcripts from all three CRISPR loci, the RNase P and 7S RNAs, all tRNAs and rRNAs and 69 predicted snoRNAs. Two putative riboswitch RNAs were present in growing but not in stationary phase cells. The procedure used is designed to identify TSS but, assuming that the number of cDNA reads correlates with transcript abundance, the results also provide a semi-quantitative documentation of the differences in T. kodakarensis genome expression under different growth conditions and confirm previous observations of substrate-dependent specific gene expression. Many previously unanticipated small RNAs have been identified, some with relative low GC contents (≤50%) and sequences that do not fold readily into base-paired secondary structures, contrary to the classical expectations for non-coding RNAs in a hyperthermophile.
Conclusion
The results identify >2,700 TSS, including almost all of the primary sites of transcription initiation upstream of annotated genes, plus many secondary sites, sites within genes and sites resulting in antisense transcripts. The T. kodakarensis genome is small (~2.1 Mbp) and tightly packed with protein-encoding genes, but the transcriptomes established also contain many non-coding RNAs and predict extensive RNA-based regulation in this model Archaeon.
Background: RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems.
Results: We present RNASEG, an algorithm for the prediction of transcriptional units based on dRNA-seq data. A key feature of the algorithm is that, based on the data, it distinguishes between transcribed and un-transcribed genomic segments. Furthermore, the program provides many different predictions in a single run, which can be used to infer the significance of transcriptional units in a consensus procedure. We show the performance of our method based on a well-studied dRNA-seq data set for Helicobacter pylori.
Conclusions: With our algorithm it is possible to identify operons and 5'- and 3'-UTRs in an automated fashion. This alleviates the need for labour intensive manual inspection and enables large-scale studies in the area of comparative transcriptomics.
Background:
The interaction of eukaryotic host and prokaryotic pathogen cells is linked to specific changes in the cellular proteome, and consequently to infection-related gene expression patterns of the involved cells. To simultaneously assess the transcriptomes of both organisms during their interaction we developed dual 3'Seq, a tag-based sequencing protocol that allows for exact quantification of differentially expressed transcripts in interacting pro-and eukaryotic cells without prior fixation or physical disruption of the interaction.
Results:
Human epithelial cells were infected with Salmonella enterica Typhimurium as a model system for invasion of the intestinal epithelium, and the transcriptional response of the infected host cells together with the differential expression of invading and intracellular pathogen cells was determined by dual 3'Seq coupled with the next-generation sequencing-based transcriptome profiling technique deepSuperSAGE (deep Serial Analysis of Gene Expression). Annotation to reference transcriptomes comprising the operon structure of the employed S. enterica Typhimurium strain allowed for in silico separation of the interacting cells including quantification of polycistronic RNAs. Eighty-nine percent of the known loci are found to be transcribed in prokaryotic cells prior or subsequent to infection of the host, while 75% of all protein-coding loci are represented in the polyadenylated transcriptomes of human host cells.
Conclusions:
Dual 3'Seq was alternatively coupled to MACE (Massive Analysis of cDNA ends) to assess the advantages and drawbacks of a library preparation procedure that allows for sequencing of longer fragments. Additionally, the identified expression patterns of both organisms were validated by qRT-PCR using three independent biological replicates, which confirmed that RELB along with NFKB1 and NFKB2 are involved in the initial immune response of epithelial cells after infection with S. enterica Typhimurium.
The primary transcriptome of Neisseria meningitidis and its interaction with the RNA chaperone Hfq
(2017)
Neisseria meningitidis is a human commensal that can also cause life-threatening meningitis and septicemia. Despite growing evidence for RNA-based regulation in meningococci, their transcriptome structure and output of regulatory small RNAs (sRNAs) are incompletely understood. Using dRNA-seq, we have mapped at single-nucleotide resolution the primary transcriptome of N. meningitidis strain 8013. Annotation of 1625 transcriptional start sites defines transcription units for most protein-coding genes but also reveals a paucity of classical σ70-type promoters, suggesting the existence of activators that compensate for the lack of −35 consensus sequences in N. meningitidis. The transcriptome maps also reveal 65 candidate sRNAs, a third of which were validated by northern blot analysis. Immunoprecipitation with the RNA chaperone Hfq drafts an unexpectedly large post-transcriptional regulatory network in this organism, comprising 23 sRNAs and hundreds of potential mRNA targets. Based on this data, using a newly developed gfp reporter system we validate an Hfq-dependent mRNA repression of the putative colonization factor PrpB by the two trans-acting sRNAs RcoF1/2. Our genome-wide RNA compendium will allow for a better understanding of meningococcal transcriptome organization and riboregulation with implications for colonization of the human nasopharynx.
FinO-domain proteins are a widespread family of bacterial RNA-binding proteins with regulatory functions. Their target spectrum ranges from a single RNA pair, in the case of plasmid-encoded FinO, to global RNA regulons, as with enterobacterial ProQ. To assess whether the FinO domain itself is intrinsically selective or promiscuous, we determine in vivo targets of Neisseria meningitidis, which consists of solely a FinO domain. UV-CLIP-seq identifies associations with 16 small non-coding sRNAs and 166 mRNAs. Meningococcal ProQ predominantly binds to highly structured regions and generally acts to stabilize its RNA targets. Loss of ProQ alters transcript levels of >250 genes, demonstrating that this minimal ProQ protein impacts gene expression globally. Phenotypic analyses indicate that ProQ promotes oxidative stress resistance and DNA damage repair. We conclude that FinO domain proteins recognize some abundant type of RNA shape and evolve RNA binding selectivity through acquisition of additional regions that constrain target recognition. FinO-domain proteins are bacterial RNA-binding proteins with a wide range of target specificities. Here, the authors employ UV CLIP-seq and show that minimal ProQ protein of Neisseria meningitidis binds to various small non-coding RNAs and mRNAs involved in virulence.