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Bacterial small RNAs in the Genus Rickettsia

Authors: Casey L. C. Schroeder; Hema P. Narra; Mark Rojas; Abha Sahni; Jignesh Patel; Kamil Khanipov; Thomas G. Wood; +2 Authors

Bacterial small RNAs in the Genus Rickettsia

Abstract

Rickettsia species are obligate intracellular Gram-negative pathogenic bacteria and the etiologic agents of diseases such as Rocky Mountain spotted fever (RMSF), Mediterranean spotted fever, epidemic typhus, and murine typhus. Genome sequencing revealed that R. prowazekii has ~25 % non-coding DNA, the majority of which is thought to be either "junk DNA" or pseudogenes resulting from genomic reduction. These characteristics also define other Rickettsia genomes. Bacterial small RNAs, whose biogenesis is predominantly attributed to either the intergenic regions (trans-acting) or to the antisense strand of an open reading frame (cis-acting), are now appreciated to be among the most important post-transcriptional regulators of bacterial virulence and growth. We hypothesize that intergenic regions in rickettsial species encode for small, non-coding RNAs (sRNAs) involved in the regulation of its transcriptome, leading to altered virulence and adaptation depending on the host niche.We employed a combination of bioinformatics and in vitro approaches to explore the presence of sRNAs in a number of species within Genus Rickettsia. Using the sRNA Identification Protocol using High-throughput Technology (SIPHT) web interface, we predicted over 1,700 small RNAs present in the intergenic regions of 16 different strains representing 13 rickettsial species. We further characterized novel sRNAs from typhus (R. prowazekii and R. typhi) and spotted fever (R. rickettsii and R. conorii) groups for their promoters and Rho-independent terminators using Bacterial Promoter Prediction Program (BPROM) and TransTermHP prediction algorithms, respectively. Strong σ70 promoters were predicted upstream of all novel small RNAs, indicating the potential for transcriptional activity. Next, we infected human microvascular endothelial cells (HMECs) with R. prowazekii for 3 h and 24 h and performed Next Generation Sequencing to experimentally validate the expression of 26 sRNA candidates predicted in R. prowazekii. Reverse transcriptase PCR was also used to further verify the expression of six putative novel sRNA candidates in R. prowazekii.Our results yield clear evidence for the expression of novel R. prowazekii sRNA candidates during infection of HMECs. This is the first description of novel small RNAs for a highly pathogenic species of Rickettsia, which should lead to new insights into rickettsial virulence and adaptation mechanisms.

Keywords

Base Sequence, Molecular Sequence Data, Chromosome Mapping, Computational Biology, High-Throughput Nucleotide Sequencing, Reproducibility of Results, Gene Expression Regulation, Bacterial, Genomics, RNA, Bacterial, Consensus Sequence, Genetics, Position-Specific Scoring Matrices, RNA, Small Untranslated, RNA Interference, Nucleotide Motifs, Rickettsia, Promoter Regions, Genetic, Genome, Bacterial, Biotechnology, Research Article

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
34
Top 10%
Average
Top 10%
Green
gold