Brucella-driven host N-glycome remodeling controls infection.

Many powerful methods have been employed to elucidate the global transcriptomic, proteomic, or metabolic responses to pathogen-infected host cells. However, the host glycome responses to bacterial infection remain largely unexplored, and hence, our understanding of the molecular mechanisms by which bacterial pathogens manipulate the host glycome to favor infection remains incomplete. Here, we address this gap by performing a systematic analysis of the host glycome during infection by the bacterial pathogen Brucella spp. that cause brucellosis. We discover, surprisingly, that a Brucella effector protein (EP) Rhg1 induces global reprogramming of the host cell N-glycome by interacting with components of the oligosaccharide transferase complex that controls N-linked protein glycosylation, and Rhg1 regulates Brucella replication and tissue colonization in a mouse model of brucellosis, demonstrating that Brucella exploits the EP Rhg1 to reprogram the host N-glycome and promote bacterial intracellular parasitism, thereby providing a paradigm for bacterial control of host cell infection.

KaruBioNet: a network and discussion group for a better collaboration and structuring of bioinformatics in Guadeloupe (French West Indies).

Summary: Sequencing and other biological data are now more frequently available and at a lower price. Mutual tools and strategies are needed to analyze the huge amount of heterogeneous data generated by several research teams and devices. Bioinformatics represents a growing field in the scientific community globally. This multidisciplinary field provides a great amount of tools and methods that can be used to conduct scientific studies in a more strategic way. Coordinated actions and collaborations are needed to find more innovative and accurate methods for a better understanding of real-life data. A wide variety of organizations are contributing to KaruBioNet in Guadeloupe (French West Indies), a Caribbean archipelago. The purpose of this group is to foster collaboration and mutual aid among people from different disciplines using a 'one health' approach, for a better comprehension and surveillance of humans, plants or animals' health and diseases. The KaruBioNet network particularly aims to help researchers in their studies related to 'omics' data, but also more general aspects concerning biological data analysis. This transdisciplinary network is a platform for discussion, sharing, training and support between scientists interested in bioinformatics and related fields. Starting from a little archipelago in the Caribbean, we envision to facilitate exchange between other Caribbean partners in the future, knowing that the Caribbean is a region with non-negligible biodiversity which should be preserved and protected. Joining forces with other Caribbean countries or territories would strengthen scientific collaborative impact in the region. Information related to this network can be found at: http://www.pasteur-guadeloupe.fr/karubionet.html. Furthermore, a dedicated 'Galaxy KaruBioNet' platform is available at: http://calamar.univ-ag.fr/c3i/galaxy_karubionet.html. Availability and implementation Information about KaruBioNet is availabe at: http://www.pasteur-guadeloupe.fr/karubionet.html. Contact: dcouvin@pasteur-guadeloupe.fr. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

The super repertoire of type IV effectors in the pangenome of Ehrlichia spp. provides insights into host-specificity and pathogenesis.

The identification of bacterial effectors is essential to understand how obligatory intracellular bacteria such as Ehrlichia spp. manipulate the host cell for survival and replication. Infection of mammals-including humans-by the intracellular pathogenic bacteria Ehrlichia spp. depends largely on the injection of virulence proteins that hijack host cell processes. Several hypothetical virulence proteins have been identified in Ehrlichia spp., but one so far has been experimentally shown to translocate into host cells via the type IV secretion system. However, the current challenge is to identify most of the type IV effectors (T4Es) to fully understand their role in Ehrlichia spp. virulence and host adaptation. Here, we predict the T4E repertoires of four sequenced Ehrlichia spp. and four other Anaplasmataceae as comparative models (pathogenic Anaplasma spp. and Wolbachia endosymbiont) using previously developed S4TE 2.0 software. This analysis identified 579 predicted T4Es (228 pT4Es for Ehrlichia spp. only). The effector repertoires of Ehrlichia spp. overlapped, thereby defining a conserved core effectome of 92 predicted effectors shared by all strains. In addition, 69 species-specific T4Es were predicted with non-canonical GC% mostly in gene sparse regions of the genomes and we observed a bias in pT4Es according to host-specificity. We also identified new protein domain combinations, suggesting novel effector functions. This work presenting the predicted effector collection of Ehrlichia spp. can serve as a guide for future functional characterisation of effectors and design of alternative control strategies against these bacteria.

Searching algorithm for Type IV effector proteins (S4TE) 2.0: Improved tools for Type IV effector prediction, analysis and comparison in proteobacteria.

Bacterial pathogens have evolved numerous strategies to corrupt, hijack or mimic cellular processes in order to survive and proliferate. Among those strategies, Type IV effectors (T4Es) are proteins secreted by pathogenic bacteria to manipulate host cell processes during infection. They are delivered into eukaryotic cells in an ATP-dependent manner via the type IV secretion system, a specialized multiprotein complex. T4Es contain a wide spectrum of features including eukaryotic-like domains, localization signals or a C-terminal translocation signal. A combination of these features enables prediction of T4Es in a given bacterial genome. In this study, we developed a web-based comprehensive suite of tools with a user-friendly graphical interface. This version 2.0 of S4TE (Searching Algorithm for Type IV Effector Proteins; http://sate.cirad.fr) enables accurate prediction and comparison of T4Es. Search parameters and threshold can be customized by the user to work with any genome sequence, whether publicly available or not. Applications range from characterizing effector features and identifying potential T4Es to analyzing the effectors based on the genome G+C composition and local gene density. S4TE 2.0 allows the comparison of putative T4E repertoires of up to four bacterial strains at the same time. The software identifies T4E orthologs among strains and provides a Venn diagram and lists of genes for each intersection. New interactive features offer the best visualization of the location of candidate T4Es and hyperlinks to NCBI and Pfam databases. S4TE 2.0 is designed to evolve rapidly with the publication of new experimentally validated T4Es, which will reinforce the predictive power of the algorithm. The computational methodology can be used to identify a wide spectrum of candidate bacterial effectors that lack sequence conservation but have similar amino acid characteristics. This approach will provide very valuable information about bacterial host-specificity and virulence factors and help identify host targets for the development of new anti-bacterial molecules.

Corrigendum: Comparative Genomics of the Zoonotic Pathogen Ehrlichia chaffeensis Reveals Candidate Type IV Effectors and Putative Host Cell Targets.

[This corrects the article on p. 204 in vol. 6, PMID: 28180111.].

Interactions "Candidatus Liberibacter solanacearum"-Bactericera cockerelli: Haplotype Effect on Vector Fitness and Gene Expression Analyses.

"Candidatus Liberibacter solanacearum" (Lso) has emerged as a serious threat world-wide. Five Lso haplotypes have been identified so far. Haplotypes A and B are present in the Americas and/or New Zealand, where they are vectored to solanaceous plants by the potato psyllid, Bactericera cockerelli (Sulc) (Hemiptera: Triozidae). The fastidious nature of these pathogens has hindered the study of the interactions with their eukaryotic hosts (vector and plant). To understand the strategies used by these pathogens to infect their vector, the effects of each Lso haplotype (A or B) on psyllid fitness was investigated, and genome-wide transcriptomic and RT-qPCR analyses were performed to evaluate Lso gene expression in association with its vector. Results showed that psyllids infected with haplotype B had significantly lower percentage of nymphal survival compared to psyllids infected with haplotype A. Although overall gene expression across Lso genome was similar between the two Lso haplotypes, differences in the expression of key candidate genes were found. Among the 16 putative type IV effector genes tested, four of them were differentially expressed between Lso haplotypes, while no differences in gene expression were measured by qPCR or transcriptomic analysis for the rest of the genes. This study provides new information regarding the pathogenesis of Lso haplotypes in their insect vector.

Comparative Genomics of the Zoonotic Pathogen Ehrlichia chaffeensis Reveals Candidate Type IV Effectors and Putative Host Cell Targets.

During infection, some intracellular pathogenic bacteria use a dedicated multiprotein complex known as the type IV secretion system to deliver type IV effector (T4E) proteins inside the host cell. These T4Es allow the bacteria to evade host defenses and to subvert host cell processes to their own advantage. Ehrlichia chaffeensis is a tick-transmitted obligate intracellular pathogenic bacterium, which causes human monocytic ehrlichiosis. Using comparative whole genome analysis, we identified the relationship between eight available E. chaffeensis genomes isolated from humans and show that these genomes are highly conserved. We identified the candidate core type IV effectome of E. chaffeensis and some conserved intracellular adaptive strategies. We assigned the West Paces strain to genetic group II and predicted the repertoires of T4Es encoded by E. chaffeensis genomes, as well as some putative host cell targets. We demonstrated that predicted T4Es are preferentially distributed in gene sparse regions of the genome. In addition to the identification of the two known type IV effectors of Anaplasmataceae, we identified two novel candidates T4Es, ECHLIB_RS02720 and ECHLIB_RS04640, which are not present in all E. chaffeensis strains and could explain some variations in inter-strain virulence. We also identified another novel candidate T4E, ECHLIB_RS02720, a hypothetical protein exhibiting EPIYA, and NLS domains as well as a classical type IV secretion signal, suggesting an important role inside the host cell. Overall, our results agree with current knowledge of Ehrlichia molecular pathogenesis, and reveal novel candidate T4Es that require experimental validation. This work demonstrates that comparative effectomics enables identification of important host pathways targeted by the bacterial pathogen. Our study, which focuses on the type IV effector repertoires among several strains of E. chaffeensis species, is an original approach and provides rational putative targets for the design of alternative therapeutics against intracellular pathogens. The collection of putative effectors of E. chaffeensis described in our paper could serve as a roadmap for future studies of the function and evolution of effectors.

Searching algorithm for type IV secretion system effectors 1.0: a tool for predicting type IV effectors and exploring their genomic context.

Type IV effectors (T4Es) are proteins produced by pathogenic bacteria to manipulate host cell gene expression and processes, divert the cell machinery for their own profit and circumvent the immune responses. T4Es have been characterized for some bacteria but many remain to be discovered. To help biologists identify putative T4Es from the complete genome of α- and γ-proteobacteria, we developed a Perl-based command line bioinformatics tool called S4TE (searching algorithm for type-IV secretion system effectors). The tool predicts and ranks T4E candidates by using a combination of 13 sequence characteristics, including homology to known effectors, homology to eukaryotic domains, presence of subcellular localization signals or secretion signals, etc. S4TE software is modular, and specific motif searches are run independently before ultimate combination of the outputs to generate a score and sort the strongest T4Es candidates. The user keeps the possibility to adjust various searching parameters such as the weight of each module, the selection threshold or the input databases. The algorithm also provides a GC% and local gene density analysis, which strengthen the selection of T4E candidates. S4TE is a unique predicting tool for T4Es, finding its utility upstream from experimental biology.