Functional annotation and distribution overview of RNA families in 27 Streptococcus agalactiae genomes

Background: Streptococcus agalactiae, also known as Group B Streptococcus (GBS), is a Gram-positive bacterium that colonizes the gastrointestinal and genitourinary tract of humans. This bacterium has also been isolated from various animals, such as fish and cattle. Non-coding RNAs (ncRNAs) can act as regulators of gene expression in bacteria, such as Streptococcus pneumoniae and Streptococcus pyogenes. However, little is known about the genomic distribution of ncRNAs and RNA families in S. agalactiae. Results: Comparative genome analysis of 27 S. agalactiae strains showed more than 5 thousand genomic regions identified and classified as Core, Exclusive, and Shared genome sequences. We identified 27 to 89 RNA families per genome distributed over these regions, from these, 25 were in Core regions while Shared and Exclusive regions showed variations amongst strains. We propose that the amount and type of ncRNA present in each genome can provide a pattern to contribute in the identification of the clonal types. Conclusions: The identification of RNA families provides an insight over ncRNAs, sRNAs and ribozymes function, that can be further explored as targets for antibiotic development or studied in gene regulation of cellular processes. RNA families could be considered as markers to determine infection capabilities of different strains. Lastly, pan-genome analysis of GBS including the full range of functional transcripts provides a broader approach in the understanding of this pathogen.Fil: Wolf, Ivan Rodrigo. Universidade Estadual de Londrina; BrasilFil: Paschoal, Alexandre Rossi. Universidade Federal do Paraná; BrasilFil: Quiroga, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Domingues, Douglas Silva. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: de Souza, Rogério Fernandes. Universidade Estadual de Londrina; BrasilFil: Pretto Giordano, Lucienne Garcia. Universidade Estadual de Londrina; BrasilFil: Vilas Boas, Laurival Antonio. Universidade Estadual de Londrina; Brasi

Identification of novel genes and proteoforms in Angiostrongylus costaricensis through a proteogenomic approach

RNA sequencing (RNA-Seq) and mass-spectrometry-based proteomics data are often integrated in proteogenomic studies to assist in the prediction of eukaryote genome features, such as genes, splicing, single-nucleotide (SNVs), and single-amino-acid variants (SAAVs). Most genomes of parasite nematodes are draft versions that lack transcript- and protein-level information and whose gene annotations rely only on computational predictions

High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research

Abstract\ud \ud \ud \ud Background\ud \ud The implication of post-transcriptional regulation by microRNAs in molecular mechanisms underlying cancer disease is well documented. However, their interference at the cellular level is not fully explored. Functional in vitro studies are fundamental for the comprehension of their role; nevertheless results are highly dependable on the adopted cellular model. Next generation small RNA transcriptomic sequencing data of a tumor cell line and keratinocytes derived from primary culture was generated in order to characterize the microRNA content of these systems, thus helping in their understanding. Both constitute cell models for functional studies of microRNAs in head and neck squamous cell carcinoma (HNSCC), a smoking-related cancer. Known microRNAs were quantified and analyzed in the context of gene regulation. New microRNAs were investigated using similarity and structural search, ab initio classification, and prediction of the location of mature microRNAs within would-be precursor sequences. Results were compared with small RNA transcriptomic sequences from HNSCC samples in order to access the applicability of these cell models for cancer phenotype comprehension and for novel molecule discovery.\ud \ud \ud \ud Results\ud \ud Ten miRNAs represented over 70% of the mature molecules present in each of the cell types. The most expressed molecules were miR-21, miR-24 and miR-205, Accordingly; miR-21 and miR-205 have been previously shown to play a role in epithelial cell biology. Although miR-21 has been implicated in cancer development, and evaluated as a biomarker in HNSCC progression, no significant expression differences were seen between cell types. We demonstrate that differentially expressed mature miRNAs target cell differentiation and apoptosis related biological processes, indicating that they might represent, with acceptable accuracy, the genetic context from which they derive. Most miRNAs identified in the cancer cell line and in keratinocytes were present in tumor samples and cancer-free samples, respectively, with miR-21, miR-24 and miR-205 still among the most prevalent molecules at all instances. Thirteen miRNA-like structures, containing reads identified by the deep sequencing, were predicted from putative miRNA precursor sequences. Strong evidences suggest that one of them could be a new miRNA. This molecule was mostly expressed in the tumor cell line and HNSCC samples indicating a possible biological function in cancer.\ud \ud \ud \ud Conclusions\ud \ud Critical biological features of cells must be fully understood before they can be chosen as models for functional studies. Expression levels of miRNAs relate to cell type and tissue context. This study provides insights on miRNA content of two cell models used for cancer research. Pathways commonly deregulated in HNSCC might be targeted by most expressed and also by differentially expressed miRNAs. Results indicate that the use of cell models for cancer research demands careful assessment of underlying molecular characteristics for proper data interpretation. Additionally, one new miRNA-like molecule with a potential role in cancer was identified in the cell lines and clinical samples.The authors acknowledge the contribution of GENCAPO (Brazilian Head and Neck Genome Project) for clinical samples and for clinical and pathological data collection (complete list of members and affiliations presented athttp://www.gencapo.famerp.br). This work was supported by FAPESP (grants 09/04166-5 and 10/51168-0) and by Hospital Israelita Albert Einstein

Bioinformatics in RNomics: Computational characterization of non-coding RNAs

A visao sobre o dogma central da biologia molecular passou por aperfeicoamentos na virada deste seculo. Muito se deve ao interesse por pesquisas feitas para compreensao do que ate entao eram regioes do genoma conhecidas como DNA Lixo. Neste contexto, projetos de transcriptoma, avancos em tecnologias de sequenciamento, bem como analises em bioinformatica, contribuiram para elucidar o que estava sendo transcrito. Tais regioes foram denominadas como RNAs nao-codificadores ou non-coding RNA (ncRNA) que eram transcritas, mas nao traduzidas em proteinas. Apesar da quantidade de metodos para o estudo in silico dos ncRNAs, existem lacunas a serem preenchidas nas pesquisas desta molecula, tais como: metodos de anotacao em geral, caracterizacao de novas classes e mecanismos alternativos de busca por similaridade de sequencia primaria. Alem disso, nao se havia uma ferramenta que reunisse num unico local as informacoes dos bancos de dados publicos de ncRNA disponiveis. Neste trabalho, buscou-se preencher tais lacunas, contribuindo para o desenvolvimento de metodos computacionais nas pesquisas em ncRNAs. Foram utilizados os genomas de Hymenoptera e Diptera como sistema biologico para aplicar e testar os metodos desenvolvidos.The classical vision of the central dogma of molecular biology was not changes dramatic until the end of the 20th century. At this time the scientific communities were interesting to understand what have in the regions of the genome known as \"Junk DNA\". Transcriptome projects together with sequencing Technologies anda bioinformatics analysis help to elucidate that this transcripts were regions that do not coding proteins and maybe has function. These transcripts are called non-coding RNA (ncRNA). Although there are a lot of computational approaches to the in silico research of ncRNA, there is a gap of research about this molecule such: approaches to the general annotation of ncRNA; identification of new classes of ncRNA; and alternatives search mechanisms of ncRNA. Besides that, there are not any central repository of public non-coding RNA databases that could help search for the information about it. In this report, we fill this gap. We tried to contributing to the development of computational methods in research on ncRNAs. We also used the Hymenoptera and Diptera genomes as a biological system to apply and test our developed approaches

Small RNAs in metastatic and non-metastatic oral squamous cell carcinoma

Abstract\ud \ud Background\ud Small non-coding regulatory RNAs control cellular functions at the transcriptional and post-transcriptional levels. Oral squamous cell carcinoma is among the leading cancers in the world and the presence of cervical lymph node metastases is currently its strongest prognostic factor. In this work we aimed at finding small RNAs expressed in oral squamous cell carcinoma that could be associated with the presence of lymph node metastasis.\ud \ud \ud Methods\ud Small RNA libraries from metastatic and non-metastatic oral squamous cell carcinomas were sequenced for the identification and quantification of known small RNAs. Selected markers were validated in plasma samples. Additionally, we used in silico analysis to investigate possible new molecules, not previously described, involved in the metastatic process.\ud \ud \ud Results\ud Global expression patterns were not associated with cervical metastases. MiR-21, miR-203 and miR-205 were highly expressed throughout samples, in agreement with their role in epithelial cell biology, but disagreeing with studies correlating these molecules with cancer invasion. Eighteen microRNAs, but no other small RNA class, varied consistently between metastatic and non-metastatic samples. Nine of these microRNAs had been previously detected in human plasma, eight of which presented consistent results between tissue and plasma samples. MiR-31 and miR-130b, known to inhibit several steps in the metastatic process, were over-expressed in non-metastatic samples and the expression of miR-130b was confirmed in plasma of patients showing no metastasis. MiR-181 and miR-296 were detected in metastatic tumors and the expression of miR-296 was confirmed in plasma of patients presenting metastasis. A novel microRNA-like molecule was also associated with non-metastatic samples, potentially targeting cell-signaling mechanisms.\ud \ud \ud Conclusions\ud We corroborate literature data on the role of small RNAs in cancer metastasis and suggest the detection of microRNAs as a tool that may assist in the evaluation of oral squamous cell carcinoma metastatic potential.The authors acknowledge the contribution of GENCAPO (Brazilian Head and\ud Neck Genome Project) for clinical samples and for clinical and pathological\ud Severino et al. BMC Medical Genomics (2015) 8:31 Page 13 of 15\ud data collection and analysis (complete list of members and affiliations\ud presented at http://www.gencapo.famerp.br) and the technical expertise and\ud accessibility of Dr. Susan Ienne da Silva Vançan and of Dr. Tiago Antonio de\ud Souza at CEFAP-USP during small RNA sequencing. This work was supported\ud by FAPESP (grant 10/51168-0) and by Hospital Israelita Albert Einstein

Meta-Analysis of Aedes aegypti Expression Datasets: Comparing Virus Infection and Blood-Fed Transcriptomes to Identify Markers of Virus Presence

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2018-02-16T17:49:21Z No. of bitstreams: 1 Fukutani KF Meta - Analysis of Aedes aegypti Expression Datasets .........pdf: 4409165 bytes, checksum: 8196abb5c066bf1d7354ad6860a023d6 (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2018-02-16T18:06:45Z (GMT) No. of bitstreams: 1 Fukutani KF Meta - Analysis of Aedes aegypti Expression Datasets .........pdf: 4409165 bytes, checksum: 8196abb5c066bf1d7354ad6860a023d6 (MD5)Made available in DSpace on 2018-02-16T18:06:45Z (GMT). No. of bitstreams: 1 Fukutani KF Meta - Analysis of Aedes aegypti Expression Datasets .........pdf: 4409165 bytes, checksum: 8196abb5c066bf1d7354ad6860a023d6 (MD5) Previous issue date: 2017Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB process no. JCB0004/2013). KF was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP no. 2017/03491-6). AP acknowledges financial support from CNPq—Grant Edital Universal MCTI/CNPQ/Universal14/2014 (Process No.: 454505/2014-0).Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Pós-Graduação em Biotecnologia em Saúde e Medicina de Investigação. Salvador, BA, BrasilFederal University of Technology. Cornélio Procópio, PR, BrazilUniversity of Uberlândia. Patos de Minas, MG, BrazilFundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / Federal University of Bahia. School of Medicine. Post-Graduation Program in Health Sciences.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / Federal University of Bahia. School of Medicine. Post-Graduation Program in Health Sciences.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Pós-Graduação em Biotecnologia em Saúde e Medicina de Investigação. Salvador, BA, Brasil / Universidade Estadual de Feira de Santana. Programa de Pós-Graduação em Computação Aplicada. Feira de Santana, BA, BrasilThe mosquitoAedes aegypti(L.) is vector of several arboviruses including dengue, yellow fever, chikungunya, and more recently zika. Previous transcriptomic studies have been performed to elucidate altered pathways in response to viral infection. However, the intrinsic coupling between alimentation and infection were unappreciated in these studies. Feeding is required for the initial mosquito contact with the virus and these events are highly dependent. Addressing this relationship, we reinterrogated datasets of virus-infected mosquitoes with two different diet schemes (fed and unfed mosquitoes), evaluating the metabolic cross-talk during both processes. We constructed coexpression networks with the differentially expressed genes of these comparison: virus-infected versus blood-fed mosquitoes and virus-infected versus unfed mosquitoes. Our analysis identified one module with 110 genes that correlated with infection status (representing ~0.7% of theA. aegyptigenome). Furthermore, we performed a machine-learning approach and summarized the infection status using only four genes (AAEL012128, AAEL014210, AAEL002477, and AAEL005350). While three of the four genes were annotated as hypothetical proteins, AAEL012128 gene is a membrane amino acid transporter correlated with viral envelope binding. This gene alone is able to discriminate all infected samples and thus should have a key role to discriminate viral infection in theA. aegyptimosquito. Moreover, validation using external datasets found this gene as differentially expressed in four transcriptomic experiments. Therefore, these genes may serve as a proxy of viral infection in the mosquito and the others 106 identified genes provides a framework to future studies

Identification of Novel Genes and Proteoforms in Angiostrongylus costaricensis through a Proteogenomic Approach

RNA sequencing (RNA-Seq) and mass-spectrometry-based proteomics data are often integrated in proteogenomic studies to assist in the prediction of eukaryote genome features, such as genes, splicing, single-nucleotide (SNVs), and single-amino-acid variants (SAAVs). Most genomes of parasite nematodes are draft versions that lack transcript- and protein-level information and whose gene annotations rely only on computational predictions. Angiostrongylus costaricensis is a roundworm species that causes an intestinal inflammatory disease, known as abdominal angiostrongyliasis (AA). Currently, there is no drug available that acts directly on this parasite, mostly due to the sparse understanding of its molecular characteristics. The available genome of A. costaricensis, specific to the Costa Rica strain, is a draft version that is not supported by transcript- or protein-level evidence. This study used RNA-Seq and MS/MS data to perform an in-depth annotation of the A. costaricensis genome. Our prediction improved the reference annotation with (a) novel coding and non-coding genes; (b) pieces of evidence of alternative splicing generating new proteoforms; and (c) a list of SNVs between the Brazilian (Crissiumal) and the Costa Rica strain. To the best of our knowledge, this is the first time that a multi-omics approach has been used to improve the genome annotation of A. costaricensis. We hope this improved genome annotation can assist in the future development of drugs, kits, and vaccines to treat, diagnose, and prevent AA caused by either the Brazil strain (Crissiumal) or the Costa Rica strain

Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall

<div><p>The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV) was published, providing new data to investigate whether this “infection” gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.</p></div