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1.  Advantages of mixing bioinformatics and visualization approaches for analyzing sRNA-mediated regulatory bacterial networks 
Briefings in Bioinformatics  2014;16(5):795-805.
The revolution in high-throughput sequencing technologies has enabled the acquisition of gigabytes of RNA sequences in many different conditions and has highlighted an unexpected number of small RNAs (sRNAs) in bacteria. Ongoing exploitation of these data enables numerous applications for investigating bacterial transacting sRNA-mediated regulation networks. Focusing on sRNAs that regulate mRNA translation in trans, recent works have noted several sRNA-based regulatory pathways that are essential for key cellular processes. Although the number of known bacterial sRNAs is increasing, the experimental validation of their interactions with mRNA targets remains challenging and involves expensive and time-consuming experimental strategies. Hence, bioinformatics is crucial for selecting and prioritizing candidates before designing any experimental work. However, current software for target prediction produces a prohibitive number of candidates because of the lack of biological knowledge regarding the rules governing sRNA–mRNA interactions. Therefore, there is a real need to develop new approaches to help biologists focus on the most promising predicted sRNA–mRNA interactions. In this perspective, this review aims at presenting the advantages of mixing bioinformatics and visualization approaches for analyzing predicted sRNA-mediated regulatory bacterial networks.
doi:10.1093/bib/bbu045
PMCID: PMC4570199  PMID: 25477348
bacterial small RNAs; regulatory network; enrichment methods; visualization software
2.  Draft Genome Sequences of Mycoplasma auris and Mycoplasma yeatsii, Two Species of the Ear Canal of Caprinae 
Genome Announcements  2013;1(3):e00280-13.
We report here the draft genome sequences of Mycoplasma auris and Mycoplasma yeatsii, two species commonly isolated from the external ear canal of Caprinae.
doi:10.1128/genomeA.00280-13
PMCID: PMC3707572  PMID: 23766401
3.  Draft Genome Sequences of Mycoplasma alkalescens, Mycoplasma arginini, and Mycoplasma bovigenitalium, Three Species with Equivocal Pathogenic Status for Cattle 
Genome Announcements  2013;1(3):e00348-13.
We report here the draft genome sequences of Mycoplasma alkalescens, Mycoplasma arginini, and Mycoplasma bovigenitalium. These three species are regularly isolated from bovine clinical specimens, although their role in disease is unclear.
doi:10.1128/genomeA.00348-13
PMCID: PMC3707579  PMID: 23766408
4.  Complete Genome Sequence of Mycoplasma putrefaciens Strain 9231, One of the Agents of Contagious Agalactia in Goats 
Genome Announcements  2013;1(3):e00354-13.
Mycoplasma putrefaciens is one of the etiologic agents of contagious agalactia in goats. We report herein the complete genome sequence of Mycoplasma putrefaciens strain 9231.
doi:10.1128/genomeA.00354-13
PMCID: PMC3707581  PMID: 23766410
5.  Emergence of Atypical Mycoplasma agalactiae Strains Harboring a New Prophage and Associated with an Alpine Wild Ungulate Mortality Episode 
Applied and Environmental Microbiology  2012;78(13):4659-4668.
The bacterium Mycoplasma agalactiae is responsible for contagious agalactia (CA) in small domestic ruminants, a syndrome listed by the World Organization for Animal Health and responsible for severe damage to the dairy industry. Recently, we frequently isolated this pathogen from lung lesions of ibexes during a mortality episode in the French Alps. This situation was unusual in terms of host specificity and tissue tropism, raising the question of M. agalactiae emergence in wildlife. To address this issue, the ibex isolates were characterized using a combination of approaches that included antigenic profiles, molecular typing, optical mapping, and whole-genome sequencing. Genome analyses showed the presence of a new, large prophage containing 35 coding sequences (CDS) that was detected in most but not all ibex strains and has a homolog in Mycoplasma conjunctivae, a species causing keratoconjunctivitis in wild ungulates. This and the presence in all strains of large integrated conjugative elements suggested highly dynamic genomes. Nevertheless, M. agalactiae strains circulating in the ibex population were shown to be highly related, most likely originating from a single parental clone that has also spread to another wild ungulate species of the same geographical area, the chamois. These strains clearly differ from strains described in Europe so far, including those found nearby, before CA eradication a few years ago. While M. agalactiae pathogenicity in ibexes remains unclear, our data showed the emergence of atypical strains in Alpine wild ungulates, raising the question of a role for the wild fauna as a potential reservoir of pathogenic mycoplasmas.
doi:10.1128/AEM.00332-12
PMCID: PMC3370481  PMID: 22522685
6.  Flux Analysis of the Trypanosoma brucei Glycolysis Based on a Multiobjective-Criteria Bioinformatic Approach 
Advances in Bioinformatics  2012;2012:159423.
Trypanosoma brucei is a protozoan parasite of major of interest in discovering new genes for drug targets. This parasite alternates its life cycle between the mammal host(s) (bloodstream form) and the insect vector (procyclic form), with two divergent glucose metabolism amenable to in vitro culture. While the metabolic network of the bloodstream forms has been well characterized, the flux distribution between the different branches of the glucose metabolic network in the procyclic form has not been addressed so far. We present a computational analysis (called Metaboflux) that exploits the metabolic topology of the procyclic form, and allows the incorporation of multipurpose experimental data to increase the biological relevance of the model. The alternatives resulting from the structural complexity of networks are formulated as an optimization problem solved by a metaheuristic where experimental data are modeled in a multiobjective function. Our results show that the current metabolic model is in agreement with experimental data and confirms the observed high metabolic flexibility of glucose metabolism. In addition, Metaboflux offers a rational explanation for the high flexibility in the ratio between final products from glucose metabolism, thsat is, flux redistribution through the malic enzyme steps.
doi:10.1155/2012/159423
PMCID: PMC3477527  PMID: 23097667
7.  A novel substitution matrix fitted to the compositional bias in Mollicutes improves the prediction of homologous relationships 
BMC Bioinformatics  2011;12:457.
Background
Substitution matrices are key parameters for the alignment of two protein sequences, and consequently for most comparative genomics studies. The composition of biological sequences can vary importantly between species and groups of species, and classical matrices such as those in the BLOSUM series fail to accurately estimate alignment scores and statistical significance with sequences sharing marked compositional biases.
Results
We present a general and simple methodology to build matrices that are especially fitted to the compositional bias of proteins. Our approach is inspired from the one used to build the BLOSUM matrices and is based on learning substitution and amino acid frequencies on real sequences with the corresponding compositional bias. We applied it to the large scale comparison of Mollicute AT-rich genomes. The new matrix, MOLLI60, was used to predict pairwise orthology relationships, as well as homolog families among 24 Mollicute genomes. We show that this new matrix enables to better discriminate between true and false orthologs and improves the clustering of homologous proteins, with respect to the use of the classical matrix BLOSUM62.
Conclusions
We show in this paper that well-fitted matrices can improve the predictions of orthologous and homologous relationships among proteins with a similar compositional bias. With the ever-increasing number of sequenced genomes, our approach could prove valuable in numerous comparative studies focusing on atypical genomes.
doi:10.1186/1471-2105-12-457
PMCID: PMC3248887  PMID: 22115330

Results 1-7 (7)