Comparison of the oxidative phosphorylation (OXPHOS) nuclear genes in the genomes of Drosophila melanogaster, Drosophila pseudoobscura and Anopheles gambiae

BACKGROUND: In eukaryotic cells, oxidative phosphorylation (OXPHOS) uses the products of both nuclear and mitochondrial genes to generate cellular ATP. Interspecies comparative analysis of these genes, which appear to be under strong functional constraints, may shed light on the evolutionary mechanisms that act on a set of genes correlated by function and subcellular localization of their products. RESULTS: We have identified and annotated the Drosophila melanogaster, D. pseudoobscura and Anopheles gambiae orthologs of 78 nuclear genes encoding mitochondrial proteins involved in oxidative phosphorylation by a comparative analysis of their genomic sequences and organization. We have also identified 47 genes in these three dipteran species each of which shares significant sequence homology with one of the above-mentioned OXPHOS orthologs, and which are likely to have originated by duplication during evolution. Gene structure and intron length are essentially conserved in the three species, although gain or loss of introns is common in A. gambiae. In most tissues of D. melanogaster and A. gambiae the expression level of the duplicate gene is much lower than that of the original gene, and in D. melanogaster at least, its expression is almost always strongly testis-biased, in contrast to the soma-biased expression of the parent gene. CONCLUSIONS: Quickly achieving an expression pattern different from the parent genes may be required for new OXPHOS gene duplicates to be maintained in the genome. This may be a general evolutionary mechanism for originating phenotypic changes that could lead to species differentiation

The joint NETTAB/Integrative Bioinformatics 2015 Meeting: aims, topics and outcomes

Romano P, Hofestädt R, Lange M, D'Elia D. The joint NETTAB/Integrative Bioinformatics 2015 Meeting: aims, topics and outcomes. BMC BIOINFORMATICS. 2017;18(S5): 101.The 15th International NETTAB workshop and the 11th Integrative Bioinformatics Symposium were held together in Bari, on October 14-16, 2016, as Joint NETTAB/IB 2015 Meeting. A special topic for the meeting was "Bioinformatics for ncRNA", but the traditional topics of both meetings series were also included in the event. About 60 scientific contributions were presented, including six keynote lectures, one special guest lecture, and many oral communications and posters. A " Two-Day Hands-on Tutorial" event was organised before the workshop. Selected full papers from some of the best works presented in Bari were submitted either to the Journal of Integrative Bioinformatics or to a purpose Call for a Supplement of BMC Bioinformatics. Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been either accepted for publication in this Supplement or published in the Journal of Integrative Bioinformatics, for a more complete presentation of the outcomes of the meeting

Isolation of a 25-kDa protein binding to a curved DNA upstream the origin of the L strand replication in the rat mitochondrial genome

The presence of a curved DNA sequence in the gene for the NADH-dehydrogenase subunit 2 of rat mitochondrial genome, upstream from the origin of the light strand replication have been demonstrated through theoretical analysis and experimental approaches. Gel retardation assays showed that this structure makes a complex with a protein component extracted from the mitochondrial matrix. The isolation and purification of this protein is reported. With a Sepharose CL-6B and magnetic DNA affinity chromatography a polypeptide was purified to homogeneity having 25-kDa mass as shown by gel electrophoresis. To functionally characterize this protein, its capability to bind to other sequences of the homologous or heterologous DNA and to specific riboprobes was also investigated. A role for this protein as a trans-acting agent required for the expression of the mammalian mitochondrial genome is suggested

MitoRes: a resource of nuclear-encoded mitochondrial genes and their products in Metazoa

BACKGROUND: Mitochondria are sub-cellular organelles that have a central role in energy production and in other metabolic pathways of all eukaryotic respiring cells. In the last few years, with more and more genomes being sequenced, a huge amount of data has been generated providing an unprecedented opportunity to use the comparative analysis approach in studies of evolution and functional genomics with the aim of shedding light on molecular mechanisms regulating mitochondrial biogenesis and metabolism. In this context, the problem of the optimal extraction of representative datasets of genomic and proteomic data assumes a crucial importance. Specialised resources for nuclear-encoded mitochondria-related proteins already exist; however, no mitochondrial database is currently available with the same features of MitoRes, which is an update of the MitoNuc database extensively modified in its structure, data sources and graphical interface. It contains data on nuclear-encoded mitochondria-related products for any metazoan species for which this type of data is available and also provides comprehensive sequence datasets (gene, transcript and protein) as well as useful tools for their extraction and export. DESCRIPTION: MitoRes consolidates information from publicly external sources and automatically annotates them into a relational database. Additionally, it also clusters proteins on the basis of their sequence similarity and interconnects them with genomic data. The search engine and sequence management tools allow the query/retrieval of the database content and the extraction and export of sequences (gene, transcript, protein) and related sub-sequences (intron, exon, UTR, CDS, signal peptide and gene flanking regions) ready to be used for in silico analysis. CONCLUSION: The tool we describe here has been developed to support lab scientists and bioinformaticians alike in the characterization of molecular features and evolution of mitochondrial targeting sequences. The way it provides for the retrieval and extraction of sequences allows the user to overcome the obstacles encountered in the integrative use of different bioinformatic resources and the completeness of the sequence collection allows intra- and interspecies comparison at different biological levels (gene, transcript and protein)

Computational annotation of UTR cis-regulatory modules through Frequent Pattern Mining

<p>Abstract</p> <p>Background</p> <p>Many studies report about detection and functional characterization of cis-regulatory motifs in untranslated regions (UTRs) of mRNAs but little is known about the nature and functional role of their distribution. To address this issue we have developed a computational approach based on the use of data mining techniques. The idea is that of mining frequent combinations of translation regulatory motifs, since their significant co-occurrences could reveal functional relationships important for the post-transcriptional control of gene expression. The experimentation has been focused on targeted mitochondrial transcripts to elucidate the role of translational control in mitochondrial biogenesis and function.</p> <p>Results</p> <p>The analysis is based on a two-stepped procedure using a sequential pattern mining algorithm. The first step searches for frequent patterns (FPs) of motifs without taking into account their spatial displacement. In the second step, frequent sequential patterns (FSPs) of spaced motifs are generated by taking into account the conservation of spacers between each ordered pair of co-occurring motifs. The algorithm makes no assumption on the relation among motifs and on the number of motifs involved in a pattern. Different FSPs can be found depending on different combinations of two parameters, i.e. the threshold of the minimum percentage of sequences supporting the pattern, and the granularity of spacer discretization. Results can be retrieved at the UTRminer web site: <url>http://utrminer.ba.itb.cnr.it/</url>. The discovered FPs of motifs amount to 216 in the overall dataset and to 140 in the human subset. For each FP, the system provides information on the discovered FSPs, if any. A variety of search options help users in browsing the web resource. The list of sequence IDs supporting each pattern can be used for the retrieval of information from the UTRminer database.</p> <p>Conclusion</p> <p>Computational prediction of structural properties of regulatory sequences is not trivial. The presented data mining approach is able to overcome some limits observed in other competitive tools. Preliminary results on UTR sequences from nuclear transcripts targeting mitochondria are promising and lead us to be confident on the effectiveness of the approach for future developments.</p

The 20th anniversary of EMBnet: 20 years of bioinformatics for the Life Sciences community

The EMBnet Conference 2008, focusing on 'Leading Applications and Technologies in Bioinformatics', was organized by the European Molecular Biology network (EMBnet) to celebrate its 20th anniversary. Since its foundation in 1988, EMBnet has been working to promote collaborative development of bioinformatics services and tools to serve the European community of molecular biology laboratories. This conference was the first meeting organized by the network that was open to the international scientific community outside EMBnet. The conference covered a broad range of research topics in bioinformatics with a main focus on new achievements and trends in emerging technologies supporting genomics, transcriptomics and proteomics analyses such as high-throughput sequencing and data managing, text and data-mining, ontologies and Grid technologies. Papers selected for publication, in this supplement to BMC Bioinformatics, cover a broad range of the topics treated, providing also an overview of the main bioinformatics research fields that the EMBnet community is involved in

Gene expression signature induced by grape intake in healthy subjects reveals wide-spread beneficial effects on peripheral blood mononuclear cells

Abstract Using a transcriptomic approach, we performed a pilot study in healthy subjects to evaluate the changes in gene expression induced by grape consumption. Blood from twenty subjects was collected at baseline (T0), after 21 days of grape-rich diet (T1) and after one-month washout (T2). Gene expression profiling of peripheral blood mononuclear cells from six subjects identified 930 differentially expressed transcripts. Gene functional analysis revealed changes (at T1 and/or T2) suggestive of antithrombotic and anti-inflammatory effects, confirming and extending previous finding on the same subjects. Moreover, we observed several other favourable changes in the transcription of genes involved in crucial processes such as immune response, DNA and protein repair, autophagy and mitochondrial biogenesis. Finally, we detected significant changes in many long non-coding RNAs genes, whose regulatory functions are being increasingly appreciated. Altogether, our data suggest that a grape diet may exert its beneficial effects by targeting different strategic pathways

The need for standardisation in life science research - an approach to excellence and trust

Today, academic researchers benefit from the changes driven by digital technologies and the enormous growth of knowledge and data, on globalisation, enlargement of the scientific community, and the linkage between different scientific communities and the society. To fully benefit from this development, however, information needs to be shared openly and transparently. Digitalisation plays a major role here because it permeates all areas of business, science and society and is one of the key drivers for innovation and international cooperation. To address the resulting opportunities, the EU promotes the development and use of collaborative ways to produce and share knowledge and data as early as possible in the research process, but also to appropriately secure results with the European strategy for Open Science (OS). It is now widely recognised that making research results more accessible to all societal actors contributes to more effective and efficient science; it also serves as a boost for innovation in the public and private sectors. However for research data to be findable, accessible, interoperable and reusable the use of standards is essential. At the metadata level, considerable efforts in standardisation have already been made (e.g. Data Management Plan and FAIR Principle etc.), whereas in context with the raw data these fundamental efforts are still fragmented and in some cases completely missing. The CHARME consortium, funded by the European Cooperation in Science and Technology (COST) Agency, has identified needs and gaps in the field of standardisation in the life sciences and also discussed potential hurdles for implementation of standards in current practice. Here, the authors suggest four measures in response to current challenges to ensure a high quality of life science research data and their re-usability for research and innovation

Advancing microbiome research with machine learning : key findings from the ML4Microbiome COST action

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions

The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies