ExtraTrain: a database of Extragenic regions and Transcriptional information in prokaryotic organisms.

BACKGROUND: Transcriptional regulation processes are the principal mechanisms of adaptation in prokaryotes. In these processes, the regulatory proteins and the regulatory DNA signals located in extragenic regions are the key elements involved. As all extragenic spaces are putative regulatory regions, ExtraTrain covers all extragenic regions of available genomes and regulatory proteins from bacteria and archaea included in the UniProt database. DESCRIPTION: ExtraTrain provides integrated and easily manageable information for 679816 extragenic regions and for the genes delimiting each of them. In addition ExtraTrain supplies a tool to explore extragenic regions, named Palinsight, oriented to detect and search palindromic patterns. This interactive visual tool is totally integrated in the database, allowing the search for regulatory signals in user defined sets of extragenic regions. The 26046 regulatory proteins included in ExtraTrain belong to the families AraC/XylS, ArsR, AsnC, Cold shock domain, CRP-FNR, DeoR, GntR, IclR, LacI, LuxR, LysR, MarR, MerR, NtrC/Fis, OmpR and TetR. The database follows the InterPro criteria to define these families. The information about regulators includes manually curated sets of references specifically associated to regulator entries. In order to achieve a sustainable and maintainable knowledge database ExtraTrain is a platform open to the contribution of knowledge by the scientific community providing a system for the incorporation of textual knowledge. CONCLUSION: ExtraTrain is a new database for exploring Extragenic regions and Transcriptional information in bacteria and archaea. ExtraTrain database is available at http://www.era7.com/ExtraTrain/.

Gene calling and bacterial genome annotation with BG7.

New massive sequencing technologies are providing many bacterial genome sequences from diverse taxa but a refined annotation of these genomes is crucial for obtaining scientific findings and new knowledge. Thus, bacterial genome annotation has emerged as a key point to investigate in bacteria. Any efficient tool designed specifically to annotate bacterial genomes sequenced with massively parallel technologies has to consider the specific features of bacterial genomes (absence of introns and scarcity of nonprotein-coding sequence) and of next-generation sequencing (NGS) technologies (presence of errors and not perfectly assembled genomes). These features make it convenient to focus on coding regions and, hence, on protein sequences that are the elements directly related with biological functions. In this chapter we describe how to annotate bacterial genomes with BG7, an open-source tool based on a protein-centered gene calling/annotation paradigm. BG7 is specifically designed for the annotation of bacterial genomes sequenced with NGS. This tool is sequence error tolerant maintaining their capabilities for the annotation of highly fragmented genomes or for annotating mixed sequences coming from several genomes (as those obtained through metagenomics samples). BG7 has been designed with scalability as a requirement, with a computing infrastructure completely based on cloud computing (Amazon Web Services).

Metagenomic Analysis of Milk of Healthy and Mastitis-Suffering Women.

BACKGROUND: Some studies have been conducted to assess the composition of the bacterial communities inhabiting human milk, but they did not evaluate the presence of other microorganisms, such as fungi, archaea, protozoa, or viruses. OBJECTIVE: This study aimed to compare the metagenome of human milk samples provided by healthy and mastitis-suffering women. METHODS: DNA was isolated from human milk samples collected from 10 healthy women and 10 women with symptoms of lactational mastitis. Shotgun libraries from total extracted DNA were constructed and the libraries were sequenced by 454 pyrosequencing. RESULTS: The amount of human DNA sequences was ≥ 90% in all the samples. Among the bacterial sequences, the predominant phyla were Proteobacteria, Firmicutes, and Bacteroidetes. The healthy core microbiome included the genera Staphylococcus, Streptococcus, Bacteroides, Faecalibacterium, Ruminococcus, Lactobacillus, and Propionibacterium. At the species level, a high degree of inter-individual variability was observed among healthy women. In contrast, Staphylococcus aureus clearly dominated the microbiome in the samples from the women with acute mastitis whereas high increases in Staphylococcus epidermidis-related reads were observed in the milk of those suffering from subacute mastitis. Fungal and protozoa-related reads were identified in most of the samples, whereas Archaea reads were absent in samples from women with mastitis. Some viral-related sequence reads were also detected. CONCLUSION: Human milk contains a complex microbial metagenome constituted by the genomes of bacteria, archaea, viruses, fungi, and protozoa. In mastitis cases, the milk microbiome reflects a loss of bacterial diversity and a high increase of the sequences related to the presumptive etiological agents.

Important biological information uncovered in previously unaligned reads from chromatin immunoprecipitation experiments (ChIP-Seq).

Establishing the architecture of gene regulatory networks (GRNs) relies on chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-Seq) methods that provide genome-wide transcription factor binding sites (TFBSs). ChIP-Seq furnishes millions of short reads that, after alignment, describe the genome-wide binding sites of a particular TF. However, in all organisms investigated an average of 40% of reads fail to align to the corresponding genome, with some datasets having as much as 80% of reads failing to align. We describe here the provenance of previously unaligned reads in ChIP-Seq experiments from animals and plants. We show that a substantial portion corresponds to sequences of bacterial and metazoan origin, irrespective of the ChIP-Seq chromatin source. Unforeseen was the finding that 30%-40% of unaligned reads were actually alignable. To validate these observations, we investigated the characteristics of the previously unaligned reads corresponding to TAL1, a human TF involved in lineage specification of hemopoietic cells. We show that, while unmapped ChIP-Seq read datasets contain foreign DNA sequences, additional TFBSs can be identified from the previously unaligned ChIP-Seq reads. Our results indicate that the re-evaluation of previously unaligned reads from ChIP-Seq experiments will significantly contribute to TF target identification and determination of emerging properties of GRNs.

BG7: a new approach for bacterial genome annotation designed for next generation sequencing data.

BG7 is a new system for de novo bacterial, archaeal and viral genome annotation based on a new approach specifically designed for annotating genomes sequenced with next generation sequencing technologies. The system is versatile and able to annotate genes even in the step of preliminary assembly of the genome. It is especially efficient detecting unexpected genes horizontally acquired from bacterial or archaeal distant genomes, phages, plasmids, and mobile elements. From the initial phases of the gene annotation process, BG7 exploits the massive availability of annotated protein sequences in databases. BG7 predicts ORFs and infers their function based on protein similarity with a wide set of reference proteins, integrating ORF prediction and functional annotation phases in just one step. BG7 is especially tolerant to sequencing errors in start and stop codons, to frameshifts, and to assembly or scaffolding errors. The system is also tolerant to the high level of gene fragmentation which is frequently found in not fully assembled genomes. BG7 current version - which is developed in Java, takes advantage of Amazon Web Services (AWS) cloud computing features, but it can also be run locally in any operating system. BG7 is a fast, automated and scalable system that can cope with the challenge of analyzing the huge amount of genomes that are being sequenced with NGS technologies. Its capabilities and efficiency were demonstrated in the 2011 EHEC Germany outbreak in which BG7 was used to get the first annotations right the next day after the first entero-hemorrhagic E. coli genome sequences were made publicly available. The suitability of BG7 for genome annotation has been proved for Illumina, 454, Ion Torrent, and PacBio sequencing technologies. Besides, thanks to its plasticity, our system could be very easily adapted to work with new technologies in the future.