TXTGate: profiling gene groups with text-based information

We implemented a framework called TXTGate that combines literature indices of selected public biological resources in a flexible text-mining system designed towards the analysis of groups of genes. By means of tailored vocabularies, term- as well as gene-centric views are offered on selected textual fields and MEDLINE abstracts used in LocusLink and the Saccharomyces Genome Database. Subclustering and links to external resources allow for in-depth analysis of the resulting term profiles

ARACINs, Brassicaceae-specific peptides exhibiting antifungal activities against necrotrophic pathogens in Arabidopsis

Plants have developed a variety of mechanisms to cope with abiotic and biotic stresses. In a previous subcellular localization study of hydrogen peroxide-responsive proteins, two peptides with an unknown function (designated ARACIN1 and ARACIN2) have been identified. These peptides are structurally very similar but are transcriptionally differentially regulated during abiotic stresses during Botrytis cinerea infection or after benzothiadiazole and methyl jasmonate treatments. In Arabidopsis (Arabidopsis thaliana), these paralogous genes are positioned in tandem within a cluster of pathogen defense-related genes. Both ARACINs are small, cationic, and hydrophobic peptides, known characteristics for antimicrobial peptides. Their genes are expressed in peripheral cell layers prone to pathogen entry and are lineage specific to the Brassicaceae family. In vitro bioassays demonstrated that both ARACIN peptides have a direct antifungal effect against the agronomically and economically important necrotrophic fungi B. cinerea, Alternaria brassicicola, Fusarium graminearum, and Sclerotinia sclerotiorum and yeast (Saccharomyces cerevisiae). In addition, transgenic Arabidopsis plants that ectopically express ARACIN1 are protected better against infections with both B. cinerea and A. brassicicola. Therefore, we can conclude that both ARACINs act as antimicrobial peptides

Technology Training Propelling Long Lasting Skills

<p>With a modular format and hands-on approach, we offered more then 20 different courses in a variety of topics between 2021and 2023. To offer specialized training in the most up-to-date tools and methods, we engaged with approximately 25 contributors affiliated with the universities, VIB and ELIXIR. We focus mainly in hands-on session aiming for the best expirence for the participants.</p&gt

Bioinformatics: Organisms from Venus, Technology from Jupiter, Algorithms from Mars

In this paper, we discuss datasets that are being generated by microarray technology, which makes it possible to measure in parallel the activity or expression of thousands of genes simultaneously. We discuss the basics of the technology, how to preprocess the data, and how classical and newly developed algorithms can be used to generate insight in the biological processes that have generated the data. Algorithms we discuss are Principal Component Analysis, clustering techniques such as hierarchical clustering and Adaptive Quality Based Clustering and statistical sampling methods, such as Monte Carlo Markov Chains and Gibbs sampling. We illustrate these algorithms with several real-life cases from diagnostics and class discovery in leukemia, functional genomics research on the mitotic cell cycle of yeast, and motif detection in Arabidopsis thaliana using DNA background models. We also discuss some bioinformatics software platforms. In the final part of the manuscript, we present some future perspectives on the development of bioinformatics, including some visionary discussions on technology, algorithms, systems biology and computational biomedicine

Annotation of the pRhico plasmid of Azospirillum brasilense reveals its role in determining the outer surface composition

The plant growth-promoting soil bacterium Azospirillum brasilense enhances growth of economically important crops, such as wheat, corn and rice. In order to improve plant growth, a close bacterial association with the plant roots is needed. Genes encoded on a 90-MDa plasmid, denoted pRhico plasmid, present in A. brasilense Sp7, play an important role in plant root interaction. Sequencing, annotation and in silico analysis of this 90-MDa plasmid revealed the presence of a large collection of genes encoding enzymes involved in surface polysaccharide biosynthesis. Analysis of the 90-MDa plasmid genome provided evidence for its essential role in the viability of the bacterial cell

Systematic review and meta-analysis of genome-wide pooled CRISPR screens to identify host factors involved in influenza A virus infection

The host-virus interactome is increasingly recognized as an important research field to discover new therapeutic targets to treat influenza. Multiple pooled genome-wide CRISPR-Cas screens have been reported to identify new pro- and antiviral host factors of the influenza A virus. However, at present, a comprehensive summary of the results is lacking. We performed a systematic review of all reported CRISPR studies in this field in combination with a meta-analysis using the algorithm of meta-analysis by information content (MAIC). Two ranked gene lists were generated based on evidence in 15 proviral and 4 antiviral screens. Enriched pathways in the proviral MAIC results were compared to those of a prior array-based RNA interference (RNAi) meta-analysis. The top 50 proviral MAIC list contained genes whose role requires further elucidation, such as the endosomal ion channel TPCN1 and the kinase WEE1. Moreover, MAIC indicated that ALYREF, a component of the transcription export complex, has antiviral properties, whereas former knockdown experiments attributed a proviral role to this host factor. CRISPR-Cas-pooled screens displayed a bias toward early-replication events, whereas the prior RNAi meta-analysis covered early and late-stage events. RNAi screens led to the identification of a larger fraction of essential genes than CRISPR screens. In summary, the MAIC algorithm points toward the importance of several less well-known pathways in host-influenza virus interactions that merit further investigation. The results from this meta-analysis of CRISPR screens in influenza A virus infection may help guide future research efforts to develop host-directed anti-influenza drugs.ImportanceViruses rely on host factors for their replication, whereas the host cell has evolved virus restriction factors. These factors represent potential targets for host-oriented antiviral therapies. Multiple pooled genome-wide CRISPR-Cas screens have been reported to identify pro- and antiviral host factors in the context of influenza virus infection. We performed a comprehensive analysis of the outcome of these screens based on the publicly available gene lists, using the recently developed algorithm meta-analysis by information content (MAIC). MAIC allows the systematic integration of ranked and unranked gene lists into a final ranked gene list. This approach highlighted poorly characterized host factors and pathways with evidence from multiple screens, such as the vesicle docking and lipid metabolism pathways, which merit further exploration