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      The intracellular sRNA transcriptome of Listeria monocytogenes during growth in macrophages

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          Abstract

          Small non-coding RNAs (sRNAs) are widespread effectors of post-transcriptional gene regulation in bacteria. Currently extensive information exists on the sRNAs of Listeria monocytogenes expressed during growth in extracellular environments. We used deep sequencing of cDNAs obtained from fractioned RNA (<500 nt) isolated from extracellularly growing bacteria and from L. monocytogenes infected macrophages to catalog the sRNA repertoire during intracellular bacterial growth. Here, we report on the discovery of 150 putative regulatory RNAs of which 71 have not been previously described. A total of 29 regulatory RNAs, including small non-coding antisense RNAs, are specifically expressed intracellularly. We validated highly expressed sRNAs by northern blotting and demonstrated by the construction and characterization of isogenic mutants of rli31, rli33-1 and rli50* for intracellular expressed sRNA candidates, that their expression is required for efficient growth of bacteria in macrophages. All three mutants were attenuated when assessed for growth in mouse and insect models of infection. Comparative genomic analysis revealed the presence of lineage specific sRNA candidates and the absence of sRNA loci in genomes of naturally occurring infection-attenuated bacteria, with additional loss in non-pathogenic listerial genomes. Our analyses reveal extensive sRNA expression as an important feature of bacterial regulation during intracellular growth.

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          Regulatory RNAs in bacteria.

          Bacteria possess numerous and diverse means of gene regulation using RNA molecules, including mRNA leaders that affect expression in cis, small RNAs that bind to proteins or base pair with target RNAs, and CRISPR RNAs that inhibit the uptake of foreign DNA. Although examples of RNA regulators have been known for decades in bacteria, we are only now coming to a full appreciation of their importance and prevalence. Here, we review the known mechanisms and roles of regulatory RNAs, highlight emerging themes, and discuss remaining questions.
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            A new generation of homology search tools based on probabilistic inference.

            Many theoretical advances have been made in applying probabilistic inference methods to improve the power of sequence homology searches, yet the BLAST suite of programs is still the workhorse for most of the field. The main reason for this is practical: BLAST's programs are about 100-fold faster than the fastest competing implementations of probabilistic inference methods. I describe recent work on the HMMER software suite for protein sequence analysis, which implements probabilistic inference using profile hidden Markov models. Our aim in HMMER3 is to achieve BLAST's speed while further improving the power of probabilistic inference based methods. HMMER3 implements a new probabilistic model of local sequence alignment and a new heuristic acceleration algorithm. Combined with efficient vector-parallel implementations on modern processors, these improvements synergize. HMMER3 uses more powerful log-odds likelihood scores (scores summed over alignment uncertainty, rather than scoring a single optimal alignment); it calculates accurate expectation values (E-values) for those scores without simulation using a generalization of Karlin/Altschul theory; it computes posterior distributions over the ensemble of possible alignments and returns posterior probabilities (confidences) in each aligned residue; and it does all this at an overall speed comparable to BLAST. The HMMER project aims to usher in a new generation of more powerful homology search tools based on probabilistic inference methods.
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              Comparative genomics of Listeria species.

              Listeria monocytogenes is a food-borne pathogen with a high mortality rate that has also emerged as a paradigm for intracellular parasitism. We present and compare the genome sequences of L. monocytogenes (2,944,528 base pairs) and a nonpathogenic species, L. innocua (3,011,209 base pairs). We found a large number of predicted genes encoding surface and secreted proteins, transporters, and transcriptional regulators, consistent with the ability of both species to adapt to diverse environments. The presence of 270 L. monocytogenes and 149 L. innocua strain-specific genes (clustered in 100 and 63 islets, respectively) suggests that virulence in Listeria results from multiple gene acquisition and deletion events.
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                Author and article information

                Journal
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                May 2011
                May 2011
                29 January 2011
                29 January 2011
                : 39
                : 10
                : 4235-4248
                Affiliations
                1Institute of Medical Microbiology, Justus-Liebig-University, Frankfurter Strasse 107, 2Institute of Phytopathology and Applied Zoology, Justus-Liebig-University, Heinrich-Buff-Ring 26-32, 35392 Giessen and 3Genedata Bioinformatik GmbH, Lena-Christ-Strasse 50, D-82152 Planegg-Martinsried, Germany
                Author notes
                *To whom correspondence should be addressed. Tel: +49 641 99 46400; Fax: +49 641 99 46409; Email: torsten.hain@ 123456mikrobio.med.uni-giessen.de
                Correspondence may also be addressed to Trinad Chakraborty. Tel: +49 641 99 41251; Fax: +49 641 99 41259; Email: trinad.chakraborty@ 123456mikrobio.med.uni-giessen.de

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

                Article
                gkr033
                10.1093/nar/gkr033
                3105390
                21278422
                b9dfbdfc-42a5-47c9-ade7-be091e4089c2
                © The Author(s) 2011. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 September 2010
                : 12 January 2011
                : 13 January 2011
                Page count
                Pages: 14
                Categories
                Genomics

                Genetics
                Genetics

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