Novel interferon-sensitive genes unveiled by correlation-driven gene selection and systems biology

Interferons (IFNs) are key cytokines involved in alerting the immune system to viral infection. After IFN stimulation, cellular transcriptional profile critically changes, leading to the expression of several IFN stimulated genes (ISGs) that exert a wide variety of antiviral activities. Despite many ISGs have been already identified, a comprehensive network of coding and non-coding genes with a central role in IFN-response still needs to be elucidated. We performed a global RNA-Seq transcriptome profile of the HCV permissive human hepatoma cell line Huh7.5 and its parental cell line Huh7, upon IFN treatment, to define a network of genes whose coordinated modulation plays a central role in IFN-response. Our study adds molecular actors, coding and non-coding genes, to the complex molecular network underlying IFN-response and shows how systems biology approaches, such as correlation networks, network's topology and gene ontology analyses can be leveraged to this aim.

The coding and long noncoding single-cell atlas of the developing human fetal striatum

Deciphering how the human striatum develops is necessary for understanding the diseases that affect this region. To decode the transcriptional modules that regulate this structure during development, we compiled a catalog of 1116 long intergenic noncoding RNAs (lincRNAs) identified de novo and then profiled 96,789 single cells from the early human fetal striatum. We found that D1 and D2 medium spiny neurons (D1- and D2-MSNs) arise from a common progenitor and that lineage commitment is established during the postmitotic transition, across a pre-MSN phase that exhibits a continuous spectrum of fate determinants. We then uncovered cell type-specific gene regulatory networks that we validated through in silico perturbation. Finally, we identified human-specific lincRNAs that contribute to the phylogenetic divergence of this structure in humans. This work delineates the cellular hierarchies governing MSN lineage commitment.

A Simplified Amino Acidic Alphabet to Unveil the T-Cells Receptors Antigens: A Computational Perspective

The exposure to pathogens triggers the activation of adaptive immune responses through antigens bound to surface receptors of antigen presenting cells (APCs). T cell receptors (TCR) are responsible for initiating the immune response through their physical direct interaction with antigen-bound receptors on the APCs surface. The study of T cell interactions with antigens is considered of crucial importance for the comprehension of the role of immune responses in cancer growth and for the subsequent design of immunomodulating anticancer drugs. RNA sequencing experiments performed on T cells represented a major breakthrough for this branch of experimental molecular biology. Apart from the gene expression levels, the hypervariable CDR3α/β sequences of the TCR loops can now be easily determined and modelled in the three dimensions, being the portions of TCR mainly responsible for the interaction with APC receptors. The most direct experimental method for the investigation of antigens would be based on peptide libraries, but their huge combinatorial nature, size, cost, and the difficulty of experimental fine tuning makes this approach complicated time consuming, and costly. We have implemented in silico methodology with the aim of moving from CDR3α/β sequences to a library of potentially antigenic peptides that can be used in immunologically oriented experiments to study T cells’ reactivity. To reduce the size of the library, we have verified the reproducibility of experimental benchmarks using the permutation of only six residues that can be considered representative of all ensembles of 20 natural amino acids. Such a simplified alphabet is able to correctly find the poses and chemical nature of original antigens within a small subset of ligands of potential interest. The newly generated library would have the advantage of leading to potentially antigenic ligands that would contribute to a better understanding of the chemical nature of TCR-antigen interactions. This step is crucial in the design of immunomodulators targeted towards T-cells response as well as in understanding the first principles of an immune response in several diseases, from cancer to autoimmune disorders.

OligoMinerApp: a web-server application for the design of genome-scale oligonucleotide in situ hybridization probes through the flexible OligoMiner environment

Fluorescence in situ hybridization (FISH) is a powerful single-cell technique that harnesses nucleic acid base pairing to detect the abundance and positioning of cellular RNA and DNA molecules in fixed samples. Recent technology development has paved the way to the construction of FISH probes entirely from synthetic oligonucleotides (oligos), allowing the optimization of thermodynamic properties together with the opportunity to design probes against any sequenced genome. However, comparatively little progress has been made in the development of computational tools to facilitate the oligos design, and even less has been done to extend their accessibility. OligoMiner is an open-source and modular pipeline written in Python that introduces a novel method of assessing probe specificity that employs supervised machine learning to predict probe binding specificity from genome-scale sequence alignment information. However, its use is restricted to only those people who are confident with command line interfaces because it lacks a Graphical User Interface (GUI), potentially cutting out many researchers from this technology. Here, we present OligoMinerApp (http://oligominerapp.org), a web-based application that aims to extend the OligoMiner framework through the implementation of a smart and easy-to-use GUI and the introduction of new functionalities specially designed to make effective probe mining available to everyone.

BioHackathon 2015: Semantics of data for life sciences and reproducible research

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

Transcriptional Landscape of Human Tissue Lymphocytes Unveils Uniqueness of Tumor-Infiltrating T Regulatory Cells

Tumor-infiltrating regulatory T lymphocytes (Treg) can suppress effector T cells specific for tumor antigens. Deeper molecular definitions of tumor-infiltrating-lymphocytes could thus offer therapeutic opportunities. Transcriptomes of T helper 1 (Th1), Th17, and Treg cells infiltrating colorectal or non-small-cell lung cancers were compared to transcriptomes of the same subsets from normal tissues and validated at the single-cell level. We found that tumor-infiltrating Treg cells were highly suppressive, upregulated several immune-checkpoints, and expressed on the cell surfaces specific signature molecules such as interleukin-1 receptor 2 (IL1R2), programmed death (PD)-1 Ligand1, PD-1 Ligand2, and CCR8 chemokine, which were not previously described on Treg cells. Remarkably, high expression in whole-tumor samples of Treg cell signature genes, such as LAYN, MAGEH1, or CCR8, correlated with poor prognosis. Our findings provide insights into the molecular identity and functions of human tumor-infiltrating Treg cells and define potential targets for tumor immunotherapy.

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Transcriptome analysis performed on tumor-resident CD4⁺ Th1, Th17, and Treg cells

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Tumor-infiltrating Treg cells are defined by the expression of signature genes

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Treg-specific signature genes correlate with patients’ survival in both CRC and NSCLC

Next-Generation Sequencing Analysis of Long Noncoding RNAs in CD4+ T Cell Differentiation

Next-generation sequencing approaches, in particular RNA-seq, provide a genome-wide expression profiling allowing the identification of novel and rare transcripts such as long noncoding RNAs (lncRNA). Many RNA-seq studies have now been performed aimed at the characterization of lncRNAs and their possible involvement in cell development and differentiation in different organisms, cell types, and tissues. The adaptive immune system is an extraordinary context for the study of the role of lncRNAs in differentiation. Indeed lncRNAs seem to be key drivers in governing flexibility and plasticity of both CD8⁺ and CD4⁺ T cell, together with lineage-specific transcription factors and cytokines, acting as fine-tuners of fate choices in T cell differentiation.We describe here a pipeline for the identification of lncRNAs starting from RNA-Seq raw data.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

Background

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples.

Description

We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations.

Conclusions

Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.

Analysis RNA-seq and Noncoding RNA

RNA-Seq is an approach to transcriptome profiling that uses deep-sequencing technologies to detect and accurately quantify RNA molecules originating from a genome at a given moment in time. In recent years, the advent of RNA-Seq has facilitated genome-wide expression profiling, including the identification of novel and rare transcripts like noncoding RNAs and novel alternative splicing isoforms.Here, we describe the analytical steps required for the identification and characterization of noncoding RNAs starting from RNA-Seq raw samples, with a particular emphasis on long noncoding RNAs (lncRNAs).

miRiadne: a web tool for consistent integration of miRNA nomenclature

The miRBase is the official miRNA repository which keeps the annotation updated on newly discovered miRNAs: it is also used as a reference for the design of miRNA profiling platforms. Nomenclature ambiguities generated by loosely updated platforms and design errors lead to incompatibilities among platforms, even from the same vendor. Published miRNA lists are thus generated with different profiling platforms that refer to diverse and not updated annotations. This greatly compromises searches, comparisons and analyses that rely on miRNA names only without taking into account the mature sequences, which is particularly critic when such analyses are carried over automatically. In this paper we introduce miRiadne, a web tool to harmonize miRNA nomenclature, which takes into account the original miRBase versions from 10 up to 21, and annotations of 40 common profiling platforms from nine brands that we manually curated. miRiadne uses the miRNA mature sequence to link miRBase versions and/or platforms to prevent nomenclature ambiguities. miRiadne was designed to simplify and support biologists and bioinformaticians in re-annotating their own miRNA lists and/or data sets. As Ariadne helped Theseus in escaping the mythological maze, miRiadne will help the miRNA researcher in escaping the nomenclature maze. miRiadne is freely accessible from the URL http://www.miriadne.org.

Community-driven development for computational biology at Sprints, Hackathons and Codefests

Background

Computational biology comprises a wide range of technologies and approaches. Multiple technologies can be combined to create more powerful workflows if the individuals contributing the data or providing tools for its interpretation can find mutual understanding and consensus. Much conversation and joint investigation are required in order to identify and implement the best approaches.

Traditionally, scientific conferences feature talks presenting novel technologies or insights, followed up by informal discussions during coffee breaks. In multi-institution collaborations, in order to reach agreement on implementation details or to transfer deeper insights in a technology and practical skills, a representative of one group typically visits the other. However, this does not scale well when the number of technologies or research groups is large.

Conferences have responded to this issue by introducing Birds-of-a-Feather (BoF) sessions, which offer an opportunity for individuals with common interests to intensify their interaction. However, parallel BoF sessions often make it hard for participants to join multiple BoFs and find common ground between the different technologies, and BoFs are generally too short to allow time for participants to program together.

Results

This report summarises our experience with computational biology Codefests, Hackathons and Sprints, which are interactive developer meetings. They are structured to reduce the limitations of traditional scientific meetings described above by strengthening the interaction among peers and letting the participants determine the schedule and topics. These meetings are commonly run as loosely scheduled "unconferences" (self-organized identification of participants and topics for meetings) over at least two days, with early introductory talks to welcome and organize contributors, followed by intensive collaborative coding sessions. We summarise some prominent achievements of those meetings and describe differences in how these are organised, how their audience is addressed, and their outreach to their respective communities.

Conclusions

Hackathons, Codefests and Sprints share a stimulating atmosphere that encourages participants to jointly brainstorm and tackle problems of shared interest in a self-driven proactive environment, as well as providing an opportunity for new participants to get involved in collaborative projects.

Role of microRNAs and long-non-coding RNAs in CD4(+) T-cell differentiation

CD4(+) T lymphocytes orchestrate adaptive immune responses by differentiating into various subsets of effector T cells such as T-helper 1 (Th1), Th2, Th17, and regulatory T cells. These subsets have been generally described by master transcription factors that dictate the expression of cytokines and receptors, which ultimately define lymphocyte effector functions. However, the view of T-lymphocyte subsets as stable and terminally differentiated lineages has been challenged by increasing evidence of functional plasticity within CD4(+) T-cell subsets, which implies flexible programming of effector functions depending on time and space of T-cell activation. An outstanding question with broad basic and traslational implications relates to the mechanisms, besides transcriptional regulation, which define the plasticity of effector functions. In this study, we discuss the emerging role of regulatory non-coding RNAs in T-cell differentiation and plasticity. Not only microRNAs have been proven to be important for CD4(+) T-cell differentiation, but it is also likely that the overall T-cell functioning is the result of a multilayered network composed by coding RNAs as well as by short and long non-coding RNAs. The integrated study of all the nodes of this network will provide a comprehensive view of the molecular mechanisms underlying T-cell functions in health and disease.

The Ruby UCSC API: accessing the UCSC genome database using Ruby

Background

The University of California, Santa Cruz (UCSC) genome database is among the most used sources of genomic annotation in human and other organisms. The database offers an excellent web-based graphical user interface (the UCSC genome browser) and several means for programmatic queries. A simple application programming interface (API) in a scripting language aimed at the biologist was however not yet available. Here, we present the Ruby UCSC API, a library to access the UCSC genome database using Ruby.

Results

The API is designed as a BioRuby plug-in and built on the ActiveRecord 3 framework for the object-relational mapping, making writing SQL statements unnecessary. The current version of the API supports databases of all organisms in the UCSC genome database including human, mammals, vertebrates, deuterostomes, insects, nematodes, and yeast.

The API uses the bin index—if available—when querying for genomic intervals. The API also supports genomic sequence queries using locally downloaded *.2bit files that are not stored in the official MySQL database. The API is implemented in pure Ruby and is therefore available in different environments and with different Ruby interpreters (including JRuby).

Conclusions

Assisted by the straightforward object-oriented design of Ruby and ActiveRecord, the Ruby UCSC API will facilitate biologists to query the UCSC genome database programmatically. The API is available through the RubyGem system. Source code and documentation are available at https://github.com/misshie/bioruby-ucsc-api/ under the Ruby license. Feedback and help is provided via the website at http://rubyucscapi.userecho.com/.

Biogem: an effective tool-based approach for scaling up open source software development in bioinformatics

SUMMARY

Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices. Biogem, with its targeted modular and decentralized approach, software generator, tools and tight web integration, is an improved general model for scaling up collaborative open source software development in bioinformatics.

AVAILABILITY

Biogem and modules are free and are OSS. Biogem runs on all systems that support recent versions of Ruby, including Linux, Mac OS X and Windows. Further information at http://www.biogems.info. A tutorial is available at http://www.biogems.info/howto.html

CONTACT

bonnal@ingm.org.

Complete genome sequence of a serotype 11A, ST62 Streptococcus pneumoniae invasive isolate

Background

Streptococcus pneumoniae is an important human pathogen representing a major cause of morbidity and mortality worldwide. We sequenced the genome of a serotype 11A, ST62 S. pneumoniae invasive isolate (AP200), that was erythromycin-resistant due to the presence of the erm(TR) determinant, and carried out analysis of the genome organization and comparison with other pneumococcal genomes.

Results

The genome sequence of S. pneumoniae AP200 is 2,130,580 base pair in length. The genome carries 2216 coding sequences (CDS), 56 tRNA, and 12 rRNA genes. Of the CDSs, 72.9% have a predicted biological known function. AP200 contains the pilus islet 2 and, although its phenotype corresponds to serotype 11A, it contains an 11D capsular locus. Chromosomal rearrangements resulting from a large inversion across the replication axis, and horizontal gene transfer events were observed. The chromosomal inversion is likely implicated in the rebalance of the chromosomal architecture affected by the insertions of two large exogenous elements, the erm(TR)-carrying Tn1806 and a functional prophage designated ϕSpn_200. Tn1806 is 52,457 bp in size and comprises 49 ORFs. Comparative analysis of Tn1806 revealed the presence of a similar genetic element or part of it in related species such as Streptococcus pyogenes and also in the anaerobic species Finegoldia magna, Anaerococcus prevotii and Clostridium difficile. The genome of ϕSpn_200 is 35,989 bp in size and is organized in 47 ORFs grouped into five functional modules. Prophages similar to ϕSpn_200 were found in pneumococci and in other streptococcal species, showing a high degree of exchange of functional modules. ϕSpn_200 viral particles have morphologic characteristics typical of the Siphoviridae family and are capable of infecting a pneumococcal recipient strain.

Conclusions

The sequence of S. pneumoniae AP200 chromosome revealed a dynamic genome, characterized by chromosomal rearrangements and horizontal gene transfers. The overall diversity of AP200 is driven mainly by the presence of the exogenous elements Tn1806 and ϕSpn_200 that show large gene exchanges with other genetic elements of different bacterial species. These genetic elements likely provide AP200 with additional genes, such as those conferring antibiotic-resistance, promoting its adaptation to the environment.