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

T4SEpp: A pipeline integrating protein language models to predict bacterial type IV secreted effectors

Many pathogenic bacteria use type IV secretion systems (T4SSs) to deliver effectors (T4SEs) into the cytoplasm of eukaryotic cells, causing diseases. The identification of effectors is a crucial step in understanding the mechanisms of bacterial pathogenicity, but this remains a major challenge. In this study, we used the full-length embedding features generated by six pre-trained protein language models to train classifiers predicting T4SEs and compared their performance. We integrated three modules into a model called T4SEpp. The first module searched for full-length homologs of known T4SEs, signal sequences, and effector domains; the second module fine-tuned a machine learning model using data for a signal sequence feature; and the third module used the three best-performing pre-trained protein language models. T4SEpp outperformed other state-of-the-art (SOTA) software tools, achieving ∼0.98 accuracy at a high specificity of ∼0.99, based on the assessment of an independent validation dataset. T4SEpp predicted 13 T4SEs from Helicobacter pylori, including the well-known CagA and 12 other potential ones, among which eleven could potentially interact with human proteins. This suggests that these potential T4SEs may be associated with the pathogenicity of H. pylori. Overall, T4SEpp provides a better solution to assist in the identification of bacterial T4SEs and facilitates studies of bacterial pathogenicity. T4SEpp is freely accessible at https://bis.zju.edu.cn/T4SEpp.

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.

T4SEfinder: a bioinformatics tool for genome-scale prediction of bacterial type IV secreted effectors using pre-trained protein language model

Bacterial type IV secretion systems (T4SSs) are versatile and membrane-spanning apparatuses, which mediate both genetic exchange and delivery of effector proteins to target eukaryotic cells. The secreted effectors (T4SEs) can affect gene expression and signal transduction of the host cells. As such, they often function as virulence factors and play an important role in bacterial pathogenesis. Nowadays, T4SE prediction tools have utilized various machine learning algorithms, but the accuracy and speed of these tools remain to be improved. In this study, we apply a sequence embedding strategy from a pre-trained language model of protein sequences (TAPE) to the classification task of T4SEs. The training dataset is mainly derived from our updated type IV secretion system database SecReT4 with newly experimentally verified T4SEs. An online web server termed T4SEfinder is developed using TAPE and a multi-layer perceptron (MLP) for T4SE prediction after a comprehensive performance comparison with several candidate models, which achieves a slightly higher level of accuracy than the existing prediction tools. It only takes about 3 minutes to make a classification for 5000 protein sequences by T4SEfinder so that the computational speed is qualified for whole genome-scale T4SEs detection in pathogenic bacteria. T4SEfinder might contribute to meet the increasing demands of re-annotating secretion systems and effector proteins in sequenced bacterial genomes. T4SEfinder is freely accessible at https://tool2-mml.sjtu.edu.cn/T4SEfinder_TAPE/.

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.

A fundamental step for the survival and replication of intravacuolar bacterial pathogens is the establishment of a replicative niche inside host cells by the secretion of bacterial effector proteins in the cytoplasm of the infected cells. These effectors manipulate host signaling pathways, thus allowing to escape the host degradative pathway and uptake nutrients required for intracellular replication of bacteria. In this study, we used S4TE2.0 software for high-throughput computational prediction of bacterial type IV effectors in zoonotic bacteria of the Anaplasmataceae family. The analysis of protein architecture of effectors helped us to identify the cellular pathways targeted during the infection process. The demonstration that effectors are modular components with a broad variety of protein architectures nicely explains their pleotropic mode of action and enlightens their function. We showed that bacterial adaptation to a given host during evolution requires a minimal repertoire of candidate effectors although further experimental determination is needed. T4Es are of increasing interest for basic research, including comprehension of hijacked cellular pathways, manipulated innate immunity, and application for therapeutics. Indeed pathogenomics-driven studies, especially on genetically intractable intracellular bacteria such as Anaplasmataceae, have now a substantial impact for the development of host-targeted antimicrobials, as an alternative to antibiotics.

Effectors of the Stenotrophomonas maltophilia Type IV Secretion System Mediate Killing of Clinical Isolates of Pseudomonas aeruginosa

Previously, we documented that Stenotrophomonas maltophilia encodes a type IV secretion system (T4SS) that allows the organism to kill, in contact-dependent fashion, heterologous bacteria, including wild-type Pseudomonas aeruginosa. Bioinformatic screens based largely on the presence of both a C-terminal consensus sequence and an adjacent gene encoding a cognate immunity protein identified 13 potential antibacterial effectors, most of which were highly conserved among sequenced strains of S. maltophilia. The immunity proteins of two of these proved especially capable of protecting P. aeruginosa and Escherichia coli against attack from the Stenotrophomonas T4SS. In turn, S. maltophilia mutants lacking the putative effectors RS14245 and RS14255 were impaired for killing not only laboratory E. coli but clinical isolates of P. aeruginosa, including ones isolated from the lungs of cystic fibrosis patients. That complemented mutants behaved as wild type did confirmed that RS14245 and RS14255 are required for the bactericidal activity of the S. maltophilia T4SS. Moreover, a mutant lacking both of these proteins was as impaired as a mutant lacking the T4SS apparatus, indicating that RS14245 and RS14255 account for (nearly) all of the bactericidal effects seen. Utilizing an interbacterial protein translocation assay, we determined that RS14245 and RS14255 are bona fide substrates of the T4SS, a result confirmed by examination of mutants lacking both the T4SS and the individual effectors. Delivery of the cloned 14245 protein (alone) into the periplasm resulted in the killing of target bacteria, indicating that this effector, a putative lipase, is both necessary and sufficient for bactericidal activity.

Biostatistical prediction of genes essential for growth of Anaplasma phagocytophilum in a human promyelocytic cell line using a random transposon mutant library

Anaplasma phagocytophilum (Ap), agent of human anaplasmosis, is an intracellular bacterium that causes the second most common tick-borne illness in North America. To address the lack of a genetic system for these pathogens, we used random Himar1 transposon mutagenesis to generate a library of Ap mutants capable of replicating in human promyelocytes (HL-60 cells). Illumina sequencing identified 1195 non-randomly distributed insertions. As the density of mutants was non-saturating, genes without insertions were either essential for Ap, or spared randomly. To resolve this question, we applied a biostatistical method for prediction of essential genes. Since the chances that a transposon was inserted into genomic TA dinucleotide sites should be the same for all loci, we used a Markov chain Monte Carlo model to estimate the probability that a non-mutated gene was essential for Ap. Predicted essential genes included those coding for structural ribosomal proteins, enzymes involved in metabolism, components of the type IV secretion system, antioxidant defense molecules and hypothetical proteins. We have used an in silico post-genomic approach to predict genes with high probability of being essential for replication of Ap in HL-60 cells. These results will help target genes to investigate their role in the pathogenesis of human anaplasmosis.

iT4SE-EP: Accurate Identification of Bacterial Type IV Secreted Effectors by Exploring Evolutionary Features from Two PSI-BLAST Profiles

Many gram-negative bacteria use type IV secretion systems to deliver effector molecules to a wide range of target cells. These substrate proteins, which are called type IV secreted effectors (T4SE), manipulate host cell processes during infection, often resulting in severe diseases or even death of the host. Therefore, identification of putative T4SEs has become a very active research topic in bioinformatics due to its vital roles in understanding host-pathogen interactions. PSI-BLAST profiles have been experimentally validated to provide important and discriminatory evolutionary information for various protein classification tasks. In the present study, an accurate computational predictor termed iT4SE-EP was developed for identifying T4SEs by extracting evolutionary features from the position-specific scoring matrix and the position-specific frequency matrix profiles. First, four types of encoding strategies were designed to transform protein sequences into fixed-length feature vectors based on the two profiles. Then, the feature selection technique based on the random forest algorithm was utilized to reduce redundant or irrelevant features without much loss of information. Finally, the optimal features were input into a support vector machine classifier to carry out the prediction of T4SEs. Our experimental results demonstrated that iT4SE-EP outperformed most of existing methods based on the independent dataset test.

Computational prediction of secreted proteins in gram-negative bacteria

Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction.

T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm

Type IV secreted effectors (T4SEs) can be translocated into the cytosol of host cells via type IV secretion system (T4SS) and cause diseases. However, experimental approaches to identify T4SEs are time- and resource-consuming, and the existing computational tools based on machine learning techniques have some obvious limitations such as the lack of interpretability in the prediction models. In this study, we proposed a new model, T4SE-XGB, which uses the eXtreme gradient boosting (XGBoost) algorithm for accurate identification of type IV effectors based on optimal features based on protein sequences. After trying 20 different types of features, the best performance was achieved when all features were fed into XGBoost by the 5-fold cross validation in comparison with other machine learning methods. Then, the ReliefF algorithm was adopted to get the optimal feature set on our dataset, which further improved the model performance. T4SE-XGB exhibited highest predictive performance on the independent test set and outperformed other published prediction tools. Furthermore, the SHAP method was used to interpret the contribution of features to model predictions. The identification of key features can contribute to improved understanding of multifactorial contributors to host-pathogen interactions and bacterial pathogenesis. In addition to type IV effector prediction, we believe that the proposed framework can provide instructive guidance for similar studies to construct prediction methods on related biological problems. The data and source code of this study can be freely accessed at https://github.com/CT001002/T4SE-XGB.

Subcellular Location of Piscirickettsia salmonis Heat Shock Protein 60 (Hsp60) Chaperone by Using Immunogold Labeling and Proteomic Analysis

Piscirickettsia salmonis is the causative bacterial agent of piscirickettsiosis, a systemic fish disease that significantly impacts the Chilean salmon industry. This bacterium possesses a type IV secretion system (T4SS), several proteins of the type III secretion system (T3SS), and a single heat shock protein 60 (Hsp60/GroEL). It has been suggested that due to its high antigenicity, the P. salmonis Hsp60 could be surface-exposed, translocated across the membrane, and (or) secreted into the extracellular matrix. This study tests the hypothesis that P. salmonis Hsp60 could be located on the bacterial surface. Immunogold electron microscopy and proteomic analyses suggested that although P. salmonis Hsp60 was predominantly associated with the bacterial cell cytoplasm, Hsp60-positive spots also exist on the bacterial cell envelope. IgY antibodies against P. salmonis Hsp60 protected SHK-1 cells against infection. Several bioinformatics approaches were used to assess Hsp60 translocation by the T4SS, T3SS, and T6SS, with negative results. These data support the hypothesis that small amounts of Hsp60 must reach the bacterial cell surface in a manner probably not mediated by currently characterized secretion systems, and that they remain biologically active during P. salmonis infection, possibly mediating adherence and (or) invasion.

Transgenic Testing Does Not Support a Role for Additional Candidate Genes in Wolbachia Male Killing or Cytoplasmic Incompatibility

Wolbachia are widespread bacterial endosymbionts that manipulate the reproduction of diverse arthropods to spread through a population and can substantially shape host evolution. Recently, reports identified three prophage WO genes (wmk, cifA, and cifB) that transgenically recapitulate many aspects of reproductive manipulation in Drosophila melanogaster. Here, we transgenically tested 10 additional gene candidates for CI and/or male killing in flies. The results yield no evidence for the involvement of these gene candidates in reproductive parasitism, bolstering the evidence for identification of the cif and wmk genes as the major factors involved in their phenotypes. In addition, evidence supports new hypotheses for prediction of male-killing phenotypes or lack thereof based on wmk transcript length and copy number. These experiments inform efforts to understand the full basis of reproductive parasitism for basic and applied purposes and lay the foundation for future work on the function of an interesting group of Wolbachia and phage WO genes.

Endosymbiotic bacteria in the genus Wolbachia remarkably infect nearly half of all arthropod species. They spread in part because of manipulations of host sexual reproduction that enhance the maternal transmission of the bacteria, including male killing (death of infected males) and unidirectional cytoplasmic incompatibility (CI; death of offspring from infected fathers and uninfected mothers). Recent discoveries identified several genes in prophage WO of Wolbachia (wmk, cifA, and cifB) that fully or partially recapitulate male killing or CI when transgenically expressed in Drosophila melanogaster. However, it is not yet fully resolved if other gene candidates contribute to these phenotypes. Here, we transgenically tested 10 additional gene candidates for their involvement in male killing and/or CI. The results show that despite sequence and protein architecture similarities or comparative associations with reproductive parasitism, transgenic expression of the candidates does not recapitulate male killing or CI. Sequence analysis across Wmk and its closest relatives reveals amino acids that may be important to its function. In addition, evidence is presented to propose new hypotheses regarding the relationship between wmk transcript length and its ability to kill a given host, as well as copy number of wmk homologs within a bacterial strain, which may be predictive of host resistance. Together, these analyses continue to build the evidence for identification of wmk, cifA, and cifB as the major genes that have thus far been shown to cause reproductive parasitism in Wolbachia, and the transgenic resources provide a basis for further functional study of phage WO genes.

IMPORTANCEWolbachia are widespread bacterial endosymbionts that manipulate the reproduction of diverse arthropods to spread through a population and can substantially shape host evolution. Recently, reports identified three prophage WO genes (wmk, cifA, and cifB) that transgenically recapitulate many aspects of reproductive manipulation in Drosophila melanogaster. Here, we transgenically tested 10 additional gene candidates for CI and/or male killing in flies. The results yield no evidence for the involvement of these gene candidates in reproductive parasitism, bolstering the evidence for identification of the cif and wmk genes as the major factors involved in their phenotypes. In addition, evidence supports new hypotheses for prediction of male-killing phenotypes or lack thereof based on wmk transcript length and copy number. These experiments inform efforts to understand the full basis of reproductive parasitism for basic and applied purposes and lay the foundation for future work on the function of an interesting group of Wolbachia and phage WO genes.

Stenotrophomonas maltophilia Encodes a VirB/VirD4 Type IV Secretion System That Modulates Apoptosis in Human Cells and Promotes Competition against Heterologous Bacteria, Including Pseudomonas aeruginosa

Stenotrophomonas maltophilia is an emerging opportunistic and nosocomial pathogen. S. maltophilia is also a risk factor for lung exacerbations in cystic fibrosis patients. S. maltophilia attaches to various mammalian cells, and we recently documented that the bacterium encodes a type II secretion system which triggers detachment-induced apoptosis in lung epithelial cells. We have now confirmed that S. maltophilia also encodes a type IVA secretion system (VirB/VirD4 [VirB/D4] T4SS) that is highly conserved among S. maltophilia strains and, looking beyond the Stenotrophomonas genus, is most similar to the T4SS of Xanthomonas To define the role(s) of this T4SS, we constructed a mutant of strain K279a that is devoid of secretion activity due to loss of the VirB10 component. The mutant induced a higher level of apoptosis upon infection of human lung epithelial cells, indicating that a T4SS effector(s) has antiapoptotic activity. However, when we infected human macrophages, the mutant triggered a lower level of apoptosis, implying that the T4SS also elaborates a proapoptotic factor(s). Moreover, when we cocultured K279a with strains of Pseudomonas aeruginosa, the T4SS promoted the growth of S. maltophilia and reduced the numbers of heterologous bacteria, signaling that another effector(s) has antibacterial activity. In all cases, the effect of the T4SS required S. maltophilia contact with its target. Thus, S. maltophilia VirB/D4 T4SS appears to secrete multiple effectors capable of modulating death pathways. That a T4SS can have anti- and prokilling effects on different targets, including both human and bacterial cells, has, to our knowledge, not been seen before.

An account of in silico identification tools of secreted effector proteins in bacteria and future challenges

Bacterial pathogens secrete numerous effector proteins via six secretion systems, type I to type VI secretion systems, to adapt to new environments or to promote virulence by bacterium-host interactions. Many computational approaches have been used in the identification of effector proteins before the subsequent experimental verification because they tolerate laborious biological procedures and are genome scale, automated and highly efficient. Prevalent examples include machine learning methods and statistical techniques. In this article, we summarize the computational progress toward predicting secreted effector proteins in bacteria, with an opening of an introduction of features that are used to discriminate effectors from non-effectors. The mechanism, contribution and deficiency of previous developed detection tools are presented, which are further benchmarked based on a curated testing data set. According to the results of benchmarking, potential improvements of the prediction performance are discussed, which include (1) more informative features for discriminating the effectors from non-effectors; (2) the construction of comprehensive training data set of the machine learning algorithms; (3) the advancement of reliable prediction methods and (4) a better interpretation of the mechanisms behind the molecular processes. The future of in silico identification of bacterial secreted effectors includes both opportunities and challenges.

Prediction of T4SS Effector Proteins for Anaplasma phagocytophilum Using OPT4e, A New Software Tool

Type IV secretion systems (T4SS) are used by a number of bacterial pathogens to attack the host cell. The complex protein structure of the T4SS is used to directly translocate effector proteins into host cells, often causing fatal diseases in humans and animals. Identification of effector proteins is the first step in understanding how they function to cause virulence and pathogenicity. Accurate prediction of effector proteins via a machine learning approach can assist in the process of their identification. The main goal of this study is to predict a set of candidate effectors for the tick-borne pathogen Anaplasma phagocytophilum, the causative agent of anaplasmosis in humans. To our knowledge, we present the first computational study for effector prediction with a focus on A. phagocytophilum. In a previous study, we systematically selected a set of optimal features from more than 1,000 possible protein characteristics for predicting T4SS effector candidates. This was followed by a study of the features using the proteome of Legionella pneumophila strain Philadelphia deduced from its complete genome. In this manuscript we introduce the OPT4e software package for Optimal-features Predictor for T4SS Effector proteins. An earlier version of OPT4e was verified using cross-validation tests, accuracy tests, and comparison with previous results for L. pneumophila. We use OPT4e to predict candidate effectors from the proteomes of A. phagocytophilum strains HZ and HGE-1 and predict 48 and 46 candidates, respectively, with 16 and 18 deemed most probable as effectors. These latter include the three known validated effectors for A. phagocytophilum.

Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches

In the course of infecting their hosts, pathogenic bacteria secrete numerous effectors, namely, bacterial proteins that pervert host cell biology. Many Gram-negative bacteria, including context-dependent human pathogens, use a type IV secretion system (T4SS) to translocate effectors directly into the cytosol of host cells. Various type IV secreted effectors (T4SEs) have been experimentally validated to play crucial roles in virulence by manipulating host cell gene expression and other processes. Consequently, the identification of novel effector proteins is an important step in increasing our understanding of host-pathogen interactions and bacterial pathogenesis. Here, we train and compare six machine learning models, namely, Naïve Bayes (NB), K-nearest neighbor (KNN), logistic regression (LR), random forest (RF), support vector machines (SVMs) and multilayer perceptron (MLP), for the identification of T4SEs using 10 types of selected features and 5-fold cross-validation. Our study shows that: (1) including different but complementary features generally enhance the predictive performance of T4SEs; (2) ensemble models, obtained by integrating individual single-feature models, exhibit a significantly improved predictive performance and (3) the 'majority voting strategy' led to a more stable and accurate classification performance when applied to predicting an ensemble learning model with distinct single features. We further developed a new method to effectively predict T4SEs, Bastion4 (Bacterial secretion effector predictor for T4SS), and we show our ensemble classifier clearly outperforms two recent prediction tools. In summary, we developed a state-of-the-art T4SE predictor by conducting a comprehensive performance evaluation of different machine learning algorithms along with a detailed analysis of single- and multi-feature selections.

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.

Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila

Type IV secretion systems exist in a number of bacterial pathogens and are used to secrete effector proteins directly into host cells in order to change their environment making the environment hospitable for the bacteria. In recent years, several machine learning algorithms have been developed to predict effector proteins, potentially facilitating experimental verification. However, inconsistencies exist between their results. Previously we analysed the disparate sets of predictive features used in these algorithms to determine an optimal set of 370 features for effector prediction. This study focuses on the best way to use these optimal features by designing three machine learning classifiers, comparing our results with those of others, and obtaining de novo results. We chose the pathogen Legionella pneumophila strain Philadelphia-1, a cause of Legionnaires’ disease, because it has many validated effector proteins and others have developed machine learning prediction tools for it. While all of our models give good results indicating that our optimal features are quite robust, Model 1, which uses all 370 features with a support vector machine, has slightly better accuracy. Moreover, Model 1 predicted 472 effector proteins that are deemed highly probable to be effectors and include 94% of known effectors. Although the results of our three models agree well with those of other researchers, their models only predicted 126 and 311 candidate effectors.

Tiny architects: biogenesis of intracellular replicative niches by bacterial pathogens

Co-evolution of bacterial pathogens with their hosts led to the emergence of a stunning variety of strategies aiming at the evasion of host defences, colonisation of host cells and tissues and, ultimately, the establishment of a successful infection. Pathogenic bacteria are typically classified as extracellular and intracellular; however, intracellular lifestyle comes in many different flavours: some microbes rapidly escape to the cytosol whereas other microbes remain within vacuolar compartments and harness membrane trafficking pathways to generate their host-derived, pathogen-specific replicative niche. Here we review the current knowledge on a variety of vacuolar lifestyles, the effector proteins used by bacteria as tools to take control of the host cell and the main membrane trafficking signalling pathways targeted by vacuolar pathogens as source of membranes and nutrients. Finally, we will also discuss how host cells have developed countermeasures to sense the biogenesis of the aberrant organelles harbouring bacteria. Understanding the dialogue between bacterial and eukaryotic proteins is the key to unravel the molecular mechanisms of infection and in turn, this may lead to the identification of new targets for the development of new antimicrobials.

Mutational analysis of gene function in the Anaplasmataceae: Challenges and perspectives

Mutational analysis is an efficient approach to identifying microbial gene function. Until recently, lack of an effective tool for Anaplasmataceae yielding reproducible results has created an obstacle to functional genomics, because surrogate systems, e.g., ectopic gene expression and analysis in E. coli, may not provide accurate answers. We chose to focus on a method for high-throughput generation of mutants via random mutagenesis as opposed to targeted gene inactivation. In our search for a suitable mutagenesis tool, we considered attributes of the Himar1 transposase system, i.e., random insertion into AT dinucleotide sites, which are abundant in Anaplasmataceae, and lack of requirement for specific host factors. We chose the Anaplasma marginale tr promoter, and the clinically irrelevant antibiotic spectinomycin for selection, and in addition successfully implemented non-antibiotic selection using an herbicide resistance gene. These constructs function reasonably well in Anaplasma phagocytophilum harvested from human promyelocyte HL-60 cells or Ixodes scapularis tick cells. We describe protocols developed in our laboratory, and discuss what likely makes them successful. What makes Anaplasmataceae electroporation competent is unknown and manipulating electroporation conditions has not improved mutational efficiency. A concerted effort is needed to resolve remaining problems that are inherent to the obligate intracellular bacteria. Finally, using this approach, we describe the discovery and characterization of a putative secreted effector necessary for Ap survival in HL-60 cells.

Quantitative Yeast Genetic Interaction Profiling of Bacterial Effector Proteins Uncovers a Role for the Human Retromer in Salmonella Infection

Intracellular bacterial pathogens secrete a repertoire of effector proteins into host cells that are required to hijack cellular pathways and cause disease. Despite decades of research, the molecular functions of most bacterial effectors remain unclear. To address this gap, we generated quantitative genetic interaction profiles between 36 validated and putative effectors from three evolutionarily divergent human bacterial pathogens and 4,190 yeast deletion strains. Correlating effector-generated profiles with those of yeast mutants, we recapitulated known biology for several effectors with remarkable specificity and predicted previously unknown functions for others. Biochemical and functional validation in human cells revealed a role for an uncharacterized component of the Salmonella SPI-2 translocon, SseC, in regulating maintenance of the Salmonella vacuole through interactions with components of the host retromer complex. These results exhibit the power of genetic interaction profiling to discover and dissect complex biology at the host-pathogen interface.

Comparative Transcriptome Profiling of Virulent and Attenuated Ehrlichia ruminantium Strains Highlighted Strong Regulation of map1- and Metabolism Related Genes

The obligate intracellular pathogenic bacterium, Ehrlichia ruminantium, is the causal agent of heartwater, a fatal disease in ruminants transmitted by Amblyomma ticks. So far, three strains have been attenuated by successive passages in mammalian cells. The attenuated strains have improved capacity for growth in vitro, whereas they induced limited clinical signs in vivo and conferred strong protection against homologous challenge. However, the mechanisms of pathogenesis and attenuation remain unknown. In order to improve knowledge of E. ruminantium pathogenesis, we performed a comparative transcriptomic analysis of two distant strains of E. ruminantium, Gardel and Senegal, and their corresponding attenuated strains. Overall, our results showed an upregulation of gene expression encoding for the metabolism pathway in the attenuated strains compared to the virulent strains, which can probably be associated with higher in vitro replicative activity and a better fitness to the host cells. We also observed a significant differential expression of membrane protein-encoding genes between the virulent and attenuated strains. A major downregulation of map1-related genes was observed for the two attenuated strains, whereas upregulation of genes encoding for hypothetical membrane proteins was observed for the four strains. Moreover, CDS_05140, which encodes for a putative porin, displays the highest gene expression in both attenuated strains. For the attenuated strains, the significant downregulation of map1-related gene expression and upregulation of genes encoding other membrane proteins could be important in the implementation of efficient immune responses after vaccination with attenuated vaccines. Moreover, this study revealed an upregulation of gene expression for 8 genes encoding components of Type IV secretion system and 3 potential effectors, mainly in the virulent Gardel strain. Our transcriptomic study, supported by previous proteomic studies, provides and also confirms new information regarding the characterization of genes involved in E. ruminantium virulence and attenuation mechanisms.

An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach

Type IV secretion systems (T4SS) are multi-protein complexes in a number of bacterial pathogens that can translocate proteins and DNA to the host. Most T4SSs function in conjugation and translocate DNA; however, approximately 13% function to secrete proteins, delivering effector proteins into the cytosol of eukaryotic host cells. Upon entry, these effectors manipulate the host cell’s machinery for their own benefit, which can result in serious illness or death of the host. For this reason recognition of T4SS effectors has become an important subject. Much previous work has focused on verifying effectors experimentally, a costly endeavor in terms of money, time, and effort. Having good predictions for effectors will help to focus experimental validations and decrease testing costs. In recent years, several scoring and machine learning-based methods have been suggested for the purpose of predicting T4SS effector proteins. These methods have used different sets of features for prediction, and their predictions have been inconsistent. In this paper, an optimal set of features is presented for predicting T4SS effector proteins using a statistical approach. A thorough literature search was performed to find features that have been proposed. Feature values were calculated for datasets of known effectors and non-effectors for T4SS-containing pathogens for four genera with a sufficient number of known effectors, Legionella pneumophila, Coxiella burnetii, Brucella spp, and Bartonella spp. The features were ranked, and less important features were filtered out. Correlations between remaining features were removed, and dimensional reduction was accomplished using principal component analysis and factor analysis. Finally, the optimal features for each pathogen were chosen by building logistic regression models and evaluating each model. The results based on evaluation of our logistic regression models confirm the effectiveness of our four optimal sets of features, and based on these an optimal set of features is proposed for all T4SS effector proteins.

The Toolbox for Uncovering the Functions of Legionella Dot/Icm Type IVb Secretion System Effectors: Current State and Future Directions

The defective in organelle trafficking/intracellular multiplication (Dot/Icm) Type IVb secretion system (T4SS) is the essential virulence factor for the intracellular life style and pathogenicity of Legionella species. Screens demonstrated that an individual L. pneumophila strain can use the Dot/Icm T4SS to translocate an unprecedented number of more than 300 proteins into host cells, where these, so called Icm/Dot-translocated substrates (IDTS) or effectors, manipulate host cell functions to the benefit of the bacteria. Bioinformatic analysis of the pan-genus genome predicts at least 608 orthologous groups of putative effectors. Deciphering the function of these effectors is key to understanding Legionella pathogenesis; however, the analysis is challenging. Substantial functional redundancy renders classical, phenotypic screening of single gene deletion mutants mostly ineffective. Here, I review experimental approaches that were successfully used to identify, validate and functionally characterize T4SS effectors and highlight new methods, which promise to facilitate unlocking the secrets of Legionella's extraordinary weapons arsenal.

Tracking Proteins Secreted by Bacteria: What's in the Toolbox?

Bacteria have acquired multiple systems to expose proteins on their surface, release them in the extracellular environment or even inject them into a neighboring cell. Protein secretion has a high adaptive value and secreted proteins are implicated in many functions, which are often essential for bacterial fitness. Several secreted proteins or secretion machineries have been extensively studied as potential drug targets. It is therefore important to identify the secretion substrates, to understand how they are specifically recognized by the secretion machineries, and how transport through these machineries occurs. The purpose of this review is to provide an overview of the biochemical, genetic and imaging tools that have been developed to evaluate protein secretion in a qualitative or quantitative manner. After a brief overview of the different tools available, we will illustrate their advantages and limitations through a discussion of some of the current open questions related to protein secretion. We will start with the question of the identification of secreted proteins, which for many bacteria remains a critical initial step toward a better understanding of their interactions with the environment. We will then illustrate our toolbox by reporting how these tools have been applied to better understand how substrates are recognized by their cognate machinery, and how secretion proceeds. Finally, we will highlight recent approaches that aim at investigating secretion in real time, and in complex environments such as a tissue or an organism.

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.

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 (Šulc) (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 Proteomic Profiling of Ehrlichia ruminantium Pathogenic Strain and Its High-Passaged Attenuated Strain Reveals Virulence and Attenuation-Associated Proteins

The obligate intracellular bacterium Ehrlichia ruminantium (ER) causes heartwater, a fatal tick-borne disease in livestock. In the field, ER strains present different levels of virulence, limiting vaccine efficacy, for which the molecular basis remains unknown. Moreover, there are no genetic tools currently available for ER manipulation, thus limiting the knowledge of the genes/proteins that are essential for ER pathogenesis and biology. As such, to identify proteins and/or mechanisms involved in ER virulence, we performed the first exhaustive comparative proteomic analysis between a virulent strain (ERGvir) and its high-passaged attenuated strain (ERGatt). Despite their different behaviors in vivo and in vitro, our results from 1DE-nanoLC-MS/MS showed that ERGvir and ERGatt share 80% of their proteins; this core proteome includes chaperones, proteins involved in metabolism, protein-DNA-RNA biosynthesis and processing, and bacterial effectors. Conventional 2DE revealed that 85% of the identified proteins are proteoforms, suggesting that post-translational modifications (namely glycosylation) are important in ER biology. Strain-specific proteins were also identified: while ERGatt has an increased number and overexpression of proteins involved in cell division, metabolism, transport and protein processing, ERGvir shows an overexpression of proteins and proteoforms (DIGE experiments) involved in pathogenesis such as Lpd, AnkA, VirB9 and B10, providing molecular evidence for its increased virulence in vivo and in vitro. Overall, our work reveals that ERGvir and ERGatt proteomes are streamlined to fulfill their biological function (maximum virulence for ERGvir and replicative capacity for ERGatt), and we provide both pioneering data and novel insights into the pathogenesis of this obligate intracellular bacterium.

Ehrlichia's molecular tricks to manipulate their host cells

Ehrlichia is a large genus of obligate intracellular Gram-negative bacteria transmitted by ticks that cause several emerging infectious diseases in humans and are pathogenic on rodents, ruminants, and dogs. Ehrlichia spp. invade and replicate either in endothelial cells, white blood cells, or within midgut cells and salivary glands of their vector ticks. In this review, we discuss the insights that functional studies are providing on how this group of bacteria exploits their host by subverting host innate immunity and hijacking cellular processes.

Targeting of host organelles by pathogenic bacteria: a sophisticated subversion strategy

Many bacterial pathogens have evolved the ability to subvert and exploit host functions in order to enter and replicate in eukaryotic cells. For example, bacteria have developed specific mechanisms to target eukaryotic organelles such as the nucleus, the mitochondria, the endoplasmic reticulum and the Golgi apparatus. In this Review, we highlight the most recent advances in our understanding of the mechanisms that bacterial pathogens use to target these organelles. We also discuss how these strategies allow bacteria to manipulate host functions and to ultimately enable bacterial infection.

Computational prediction of secretion systems and secretomes of Brucella: identification of novel type IV effectors and their interaction with the host

Brucella spp. are facultative intracellular pathogens that cause brucellosis in various mammals including humans. Brucella survive inside the host cells by forming vacuoles and subverting host defence systems. This study was aimed to predict the secretion systems and the secretomes of Brucella spp. from 39 complete genome sequences available in the databases. Furthermore, an attempt was made to identify the type IV secretion effectors and their interactions with host proteins. We predicted the secretion systems of Brucella by the KEGG pathway and SecReT4. Brucella secretomes and type IV effectors (T4SEs) were predicted through genome-wide screening using JVirGel and S4TE, respectively. Protein-protein interactions of Brucella T4SEs with their hosts were analyzed by HPIDB 2.0. Genes coding for Sec and Tat pathways of secretion and type I (T1SS), type IV (T4SS) and type V (T5SS) secretion systems were identified and they are conserved in all the species of Brucella. In addition to the well-known VirB operon coding for the type IV secretion system (T4SS), we have identified the presence of additional genes showing homology with T4SS of other organisms. On the whole, 10.26 to 14.94% of total proteomes were found to be either secreted (secretome) or membrane associated (membrane proteome). Approximately, 1.7 to 3.0% of total proteomes were identified as type IV secretion effectors (T4SEs). Prediction of protein-protein interactions showed 29 and 36 host-pathogen specific interactions between Bos taurus (cattle)-B. abortus and Ovis aries (sheep)-B. melitensis, respectively. Functional characterization of the predicted T4SEs and their interactions with their respective hosts may reveal the secrets of host specificity of Brucella.

Common protein sequence signatures associate with Sclerotinia borealis lifestyle and secretion in fungal pathogens of the Sclerotiniaceae

Fungal plant pathogens produce secreted proteins adapted to function outside fungal cells to facilitate colonization of their hosts. In many cases such as for fungi from the Sclerotiniaceae family the repertoire and function of secreted proteins remains elusive. In the Sclerotiniaceae, whereas Sclerotinia sclerotiorum and Botrytis cinerea are cosmopolitan broad host-range plant pathogens, Sclerotinia borealis has a psychrophilic lifestyle with a low optimal growth temperature, a narrow host range and geographic distribution. To spread successfully, S. borealis must synthesize proteins adapted to function in its specific environment. The search for signatures of adaptation to S. borealis lifestyle may therefore help revealing proteins critical for colonization of the environment by Sclerotiniaceae fungi. Here, we analyzed amino acids usage and intrinsic protein disorder in alignments of groups of orthologous proteins from the three Sclerotiniaceae species. We found that enrichment in Thr, depletion in Glu and Lys, and low disorder frequency in hot loops are significantly associated with S. borealis proteins. We designed an index to report bias in these properties and found that high index proteins were enriched among secreted proteins in the three Sclerotiniaceae fungi. High index proteins were also enriched in function associated with plant colonization in S. borealis, and in in planta-induced genes in S. sclerotiorum. We highlight a novel putative antifreeze protein and a novel putative lytic polysaccharide monooxygenase identified through our pipeline as candidate proteins involved in colonization of the environment. Our findings suggest that similar protein signatures associate with S. borealis lifestyle and with secretion in the Sclerotiniaceae. These signatures may be useful for identifying proteins of interest as targets for the management of plant diseases.

Identification and Characterization of Anaplasma phagocytophilum Proteins Involved in Infection of the Tick Vector, Ixodes scapularis

Anaplasma phagocytophilum is an emerging zoonotic pathogen transmitted by Ixodes scapularis that causes human granulocytic anaplasmosis. Here, a high throughput quantitative proteomics approach was used to characterize A. phagocytophilum proteome during rickettsial multiplication and identify proteins involved in infection of the tick vector, I. scapularis. The first step in this research was focused on tick cells infected with A. phagocytophilum and sampled at two time points containing 10–15% and 65–71% infected cells, respectively to identify key bacterial proteins over-represented in high percentage infected cells. The second step was focused on adult female tick guts and salivary glands infected with A. phagocytophilum to compare in vitro results with those occurring during bacterial infection in vivo. The results showed differences in the proteome of A. phagocytophilum in infected ticks with higher impact on protein synthesis and processing than on bacterial replication in tick salivary glands. These results correlated well with the developmental cycle of A. phagocytophilum, in which cells convert from an intracellular reticulated, replicative form to the nondividing infectious dense-core form. The analysis of A. phagocytophilum differentially represented proteins identified stress response (GroEL, HSP70) and surface (MSP4) proteins that were over-represented in high percentage infected tick cells and salivary glands when compared to low percentage infected cells and guts, respectively. The results demonstrated that MSP4, GroEL and HSP70 interact and bind to tick cells, thus playing a role in rickettsia-tick interactions. The most important finding of these studies is the increase in the level of certain bacterial stress response and surface proteins in A. phagocytophilum-infected tick cells and salivary glands with functional implication in tick-pathogen interactions. These results gave a new dimension to the role of these stress response and surface proteins during A. phagocytophilum infection in ticks. Characterization of Anaplasma proteome contributes information on host-pathogen interactions and provides targets for development of novel control strategies for pathogen infection and transmission.

ESCCAR international congress on Rickettsia and other intracellular bacteria

The European Society for the study of Chlamydia, Coxiella, Anaplasma and Rickettsia (ESCCAR) held his triennial international meeting in Lausanne. This meeting gathered 165 scientists from 28 countries and all 5 continents, allowing efficient networking and major scientific exchanges. Topics covered include molecular and cellular microbiology, genomics, as well as epidemiology, veterinary and human medicine. Several breakthroughs have been revealed at the meeting, such as (i) the presence of CRISPR (the "prokaryotic immune system") in chlamydiae, (ii) an Anaplasma effector involved in host chromatin remodelling, (iii) the polarity of the type III secretion system of chlamydiae during the entry process revealed by cryo-electron tomography. Moreover, the ESCCAR meeting was a unique opportunity to be exposed to cutting-edge science and to listen to comprehensive talks on current hot topics.

Proteomic profiling of the outer membrane fraction of the obligate intracellular bacterial pathogen Ehrlichia ruminantium

The outer membrane proteins (OMPs) of Gram-negative bacteria play a crucial role in virulence and pathogenesis. Identification of these proteins represents an important goal for bacterial proteomics, because it aids in vaccine development. Here, we have developed such an approach for Ehrlichia ruminantium, the obligate intracellular bacterium that causes heartwater. A preliminary whole proteome analysis of elementary bodies, the extracellular infectious form of the bacterium, had been performed previously, but information is limited about OMPs in this organism and about their role in the protective immune response. Identification of OMPs is also essential for understanding Ehrlichia's OM architecture, and how the bacterium interacts with the host cell environment. First, we developed an OMP extraction method using the ionic detergent sarkosyl, which enriched the OM fraction. Second, proteins were separated via one-dimensional electrophoresis, and digested peptides were analyzed via nano-liquid chromatographic separation coupled with mass spectrometry (LC-MALDI-TOF/TOF). Of 46 unique proteins identified in the OM fraction, 18 (39%) were OMPs, including 8 proteins involved in cell structure and biogenesis, 4 in transport/virulence, 1 porin, and 5 proteins of unknown function. These experimental data were compared to the predicted subcellular localization of the entire E. ruminantium proteome, using three different algorithms. This work represents the most complete proteome characterization of the OM fraction in Ehrlichia spp. The study indicates that suitable subcellular fractionation experiments combined with straightforward computational analysis approaches are powerful for determining the predominant subcellular localization of the experimentally observed proteins. We identified proteins potentially involved in E. ruminantium pathogenesis, which are good novel targets for candidate vaccines. Thus, combining bioinformatics and proteomics, we discovered new OMPs for E. ruminantium that are valuable data for those investigating new vaccines against this organism. In summary, we provide both pioneering data and novel insights into the pathogenesis of this obligate intracellular bacterium.

Common protein sequence signatures associate with Sclerotinia borealis lifestyle and secretion in fungal pathogens of the Sclerotiniaceae

Fungal plant pathogens produce secreted proteins adapted to function outside fungal cells to facilitate colonization of their hosts. In many cases such as for fungi from the Sclerotiniaceae family the repertoire and function of secreted proteins remains elusive. In the Sclerotiniaceae, whereas Sclerotinia sclerotiorum and Botrytis cinerea are cosmopolitan broad host-range plant pathogens, Sclerotinia borealis has a psychrophilic lifestyle with a low optimal growth temperature, a narrow host range and geographic distribution. To spread successfully, S. borealis must synthesize proteins adapted to function in its specific environment. The search for signatures of adaptation to S. borealis lifestyle may therefore help revealing proteins critical for colonization of the environment by Sclerotiniaceae fungi. Here, we analyzed amino acids usage and intrinsic protein disorder in alignments of groups of orthologous proteins from the three Sclerotiniaceae species. We found that enrichment in Thr, depletion in Glu and Lys, and low disorder frequency in hot loops are significantly associated with S. borealis proteins. We designed an index to report bias in these properties and found that high index proteins were enriched among secreted proteins in the three Sclerotiniaceae fungi. High index proteins were also enriched in function associated with plant colonization in S. borealis, and in in planta-induced genes in S. sclerotiorum. We highlight a novel putative antifreeze protein and a novel putative lytic polysaccharide monooxygenase identified through our pipeline as candidate proteins involved in colonization of the environment. Our findings suggest that similar protein signatures associate with S. borealis lifestyle and with secretion in the Sclerotiniaceae. These signatures may be useful for identifying proteins of interest as targets for the management of plant diseases.

Understanding Anaplasmataceae pathogenesis using "Omics" approaches

This paper examines how "Omics" approaches improve our understanding of Anaplasmataceae pathogenesis, through a global and integrative strategy to identify genes and proteins involved in biochemical pathways key for pathogen-host-vector interactions. The Anaplasmataceae family comprises obligate intracellular bacteria mainly transmitted by arthropods. These bacteria are responsible for major human and animal endemic and emerging infectious diseases with important economic and public health impacts. In order to improve disease control strategies, it is essential to better understand their pathogenesis. Our work focused on four Anaplasmataceae, which cause important animal, human and zoonotic diseases: Anaplasma marginale, A. phagocytophilum, Ehrlichia chaffeensis, and E. ruminantium. Wolbachia spp. an endosymbiont of arthropods was also included in this review as a model of a non-pathogenic Anaplasmataceae. A gap analysis on "Omics" approaches on Anaplasmataceae was performed, which highlighted a lack of studies on the genes and proteins involved in the infection of hosts and vectors. Furthermore, most of the studies have been done on the pathogen itself, mainly on infectious free-living forms and rarely on intracellular forms. In order to perform a transcriptomic analysis of the intracellular stage of development, researchers developed methods to enrich bacterial transcripts from infected cells. These methods are described in this paper. Bacterial genes encoding outer membrane proteins, post-translational modifications, eukaryotic repeated motif proteins, proteins involved in osmotic and oxidative stress and hypothetical proteins have been identified to play a key role in Anaplasmataceae pathogenesis. Further investigations on the function of these outer membrane proteins and hypothetical proteins will be essential to confirm their role in the pathogenesis. Our work underlines the need for further studies in this domain and on host and vector responses to infection.