Fatma Z. Guerfali

MicroRNA Expression Profile in Human Macrophages in Response to Leishmania major Infection

Background Leishmania (L.) are intracellular protozoan parasites able to survive and replicate in the hostile phagolysosomal environment of infected macrophages. They cause leishmaniasis, a heterogeneous group of worldwide-distributed affections, representing a paradigm of neglected diseases that are mainly embedded in impoverished populations. To establish successful infection and ensure their own survival, Leishmania have developed sophisticated strategies to subvert the host macrophage responses. Despite a wealth of gained crucial information, these strategies still remain poorly understood. MicroRNAs (miRNAs), an evolutionarily conserved class of endogenous 22-nucleotide non-coding RNAs, are described to participate in the regulation of almost every cellular process investigated so far. They regulate the expression of target genes both at the levels of mRNA stability and translation; changes in their expression have a profound effect on their target transcripts. Methodology/Principal Findings We report in this study a comprehensive analysis of miRNA expression profiles in L. major-infected human primary macrophages of three healthy donors assessed at different time-points post-infection (three to 24 h). We show that expression of 64 out of 365 analyzed miRNAs was consistently deregulated upon infection with the same trends in all donors. Among these, several are known to be induced by TLR-dependent responses. GO enrichment analysis of experimentally validated miRNA-targeted genes revealed that several pathways and molecular functions were disturbed upon parasite infection. Finally, following parasite infection, miR-210 abundance was enhanced in HIF-1α-dependent manner, though it did not contribute to inhibiting anti-apoptotic pathways through pro-apoptotic caspase-3 regulation. Conclusions/Significance Our data suggest that alteration in miRNA levels likely plays an important role in regulating macrophage functions following L. major infection. These results could contribute to better understanding of the dynamics of gene expression in host cells during leishmaniasis.

Application of Multi-SOM clustering approach to macrophage gene expression analysis

The production of increasingly reliable and accessible gene expression data has stimulated the development of computational tools to interpret such data and to organize them efficiently. The clustering techniques are largely recognized as useful exploratory tools for gene expression data analysis. Genes that show similar expression patterns over a wide range of experimental conditions can be clustered together. This relies on the hypothesis that genes that belong to the same cluster are coregulated and involved in related functions. Nevertheless, clustering algorithms still show limits, particularly for the estimation of the number of clusters and the interpretation of hierarchical dendrogram, which may significantly influence the outputs of the analysis process. We propose here a multi level SOM based clustering algorithm named Multi-SOM. Through the use of clustering validity indices, Multi-SOM overcomes the problem of the estimation of clusters number. To test the validity of the proposed clustering algorithm, we first tested it on supervised training data sets. Results were evaluated by computing the number of misclassified samples. We have then used Multi-SOM for the analysis of macrophage gene expression data generated in vitro from the same individual blood infected with 5 different pathogens. This analysis led to the identification of sets of tightly coregulated genes across different pathogens. Gene Ontology tools were then used to estimate the biological significance of the clustering, which showed that the obtained clusters are coherent and biologically significant.

An in silico immunological approach for prediction of CD8+ T cell epitopes of Leishmania major proteins in susceptible BALB/c and resistant C57BL/6 murine models of infection

It is well established that MHC class II restricted-CD4 T cells are dominant during the development of immunity against Leishmania (L) in the C57BL/6-resistant mouse strain. However and in agreement with a number of previous observations indicating that specific CD8 T cells are primed during natural infection or vaccination in humans, a great deal of evidence obtained recently with the susceptible BALB/c murine model of infection by Leishmania major indicates that CD8 T cells participate in both pathogenesis and immunity to cutaneous leishmaniasis. Our goal herein was to identify in silico all parasitic peptides present in the whole L. major predicted proteome, using several public computational systems for the prediction of peptide binding to all MHC (histocompatibility complex-2) molecules in BALB/c and C57BL/6 mice (Syfpeithi, Rankpep, PRED(BALB/c) and Bimas). Peptides that were predicted to bind to different H2 molecules were then analysed for their homology with any of the murine proteins annotated so far, using the BLAST algorithm. Sets of selected peptides for each H2 molecule were defined by different prediction systems and compared to each other. Surprisingly, the results showed that a higher number of L. major peptides were predicted to bind H2 BALB/c molecules and very few or none to bind H2 C57BL/6 molecules. Our finding illustrates how a hybrid immuno-computational approach may be useful for biologists to target an in silico set of selected proteins to define potential candidate antigens for experimental vaccination with greater accuracy as well as a reduced number of T cell antigens.

EuPathDomains: The divergent domain database for eukaryotic pathogens

Eukaryotic pathogens (e.g. Plasmodium, Leishmania, Trypanosomes, etc.) are a major source of morbidity and mortality worldwide. In Africa, one of the most impacted continents, they cause millions of deaths and constitute an immense economic burden. While the genome sequence of several of these organisms is now available, the biological functions of more than half of their proteins are still unknown. This is a serious issue for bringing to the foreground the expected new therapeutic targets. In this context, the identification of protein domains is a key step to improve the functional annotation of the proteins. However, several domains are missed in eukaryotic pathogens because of the high phylogenetic distance of these organisms from the classical eukaryote models. We recently proposed a method, co-occurrence domain detection (CODD), that improves the sensitivity of Pfam domain detection by exploiting the tendency of domains to appear preferentially with a few other favorite domains in a protein. In this paper, we present EuPathDomains (http://www.atgc-montpellier.fr/EuPathDomains/), an extended database of protein domains belonging to ten major eukaryotic human pathogens. EuPathDomains gathers known and new domains detected by CODD, along with the associated confidence measurements and the GO annotations that can be deduced from the new domains. This database significantly extends the Pfam domain coverage of all selected genomes, by proposing new occurrences of domains as well as new domain families that have never been reported before. For example, with a false discovery rate lower than 20%, EuPathDomains increases the number of detected domains by 13% in Toxoplasma gondii genome and up to 28% in Cryptospordium parvum, and the total number of domain families by 10% in Plasmodium falciparum and up to 16% in C. parvum genome. The database can be queried by protein names, domain identifiers, Pfam or Interpro identifiers, or organisms, and should become a valuable resource to decipher the protein functions of eukaryotic pathogens.

Genetic micro-heterogeneity of Leishmania major in emerging foci of zoonotic cutaneous leishmaniasis in Tunisia.

Tunisia is endemic for zoonotic cutaneous leishmaniasis (ZCL), a parasitic disease caused by Leishmania (L.) major. ZCL displays a wide clinical polymorphism, with severe forms present more frequently in emerging foci where naive populations are dominant. In this study, we applied the multi-locus microsatellite typing (MLMT) using ten highly informative and discriminative markers to investigate the genetic structure of 35 Tunisian Leishmania (L.) major isolates collected from patients living in five different foci of Central Tunisia (two old and three emerging foci). Phylogenetic reconstructions based on genetic distances showed that nine of the ten tested loci were homogeneous in all isolates with homozygous alleles, whereas one locus (71AT) had a 58/64-bp bi-allelic profile with an allele linked to emerging foci. Promastigote-stage parasites with the 58-bp allele tend to be more resistant to in vitro complement lysis. These results, which stress the geographical dependence of the genetic micro-heterogeneity, may improve our understanding of the ZCL epidemiology and clinical outcome.

Identification of divergent protein domains by combining HMM-HMM comparisons and co-occurrence detection.

Identification of protein domains is a key step for understanding protein function. Hidden Markov Models (HMMs) have proved to be a powerful tool for this task. The Pfam database notably provides a large collection of HMMs which are widely used for the annotation of proteins in sequenced organisms. This is done via sequence/HMM comparisons. However, this approach may lack sensitivity when searching for domains in divergent species. Recently, methods for HMM/HMM comparisons have been proposed and proved to be more sensitive than sequence/HMM approaches in certain cases. However, these approaches are usually not used for protein domain discovery at a genome scale, and the benefit that could be expected from their utilization for this problem has not been investigated. Using proteins of P. falciparum and L. major as examples, we investigate the extent to which HMM/HMM comparisons can identify new domain occurrences not already identified by sequence/HMM approaches. We show that although HMM/HMM comparisons are much more sensitive than sequence/HMM comparisons, they are not sufficiently accurate to be used as a standalone complement of sequence/HMM approaches at the genome scale. Hence, we propose to use domain co-occurrence — the general domain tendency to preferentially appear along with some favorite domains in the proteins — to improve the accuracy of the approach. We show that the combination of HMM/HMM comparisons and co-occurrence domain detection boosts protein annotations. At an estimated False Discovery Rate of 5%, it revealed 901 and 1098 new domains in Plasmodium and Leishmania proteins, respectively. Manual inspection of part of these predictions shows that it contains several domain families that were missing in the two organisms. All new domain occurrences have been integrated in the EuPathDomains database, along with the GO annotations that can be deduced.

In silico prediction of protein-protein interactions in human macrophages

BackgroundProtein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages.ResultsWe integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection.ConclusionOur work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.

Comparative genomics of Tunisian Leishmania major isolates causing human cutaneous leishmaniasis with contrasting clinical severity.

Zoonotic cutaneous leishmaniasis caused by Leishmania (L.) major parasites affects urban and suburban areas in the center and south of Tunisia where the disease is endemo-epidemic. Several cases were reported in human patients for which infection due to L. major induced lesions with a broad range of severity. However, very little is known about the mechanisms underlying this diversity. Our hypothesis is that parasite genomic variability could, in addition to the host immunological background, contribute to the intra-species clinical variability observed in patients and explain the lesion size differences observed in the experimental model. Based on several epidemiological, in vivo and in vitro experiments, we focused on two clinical isolates showing contrasted severity in patients and BALB/c experimental mice model. We used DNA-seq as a high-throughput technology to facilitate the identification of genetic variants with discriminating potential between both isolates. Our results demonstrate that various levels of heterogeneity could be found between both L. major isolates in terms of chromosome or gene copy number variation (CNV), and that the intra-species divergence could surprisingly be related to single nucleotide polymorphisms (SNPs) and Insertion/Deletion (InDels) events. Interestingly, we particularly focused here on genes affected by both types of variants and correlated them with the observed gene CNV. Whether these differences are sufficient to explain the severity in patients is obviously still open to debate, but we do believe that additional layers of -omic information is needed to complement the genomic screen in order to draw a more complete map of severity determinants.

Comparative analysis of macrophage transcriptome of four mice strains after L. Major infection

Leishmaniasis is a parasitic disease caused by a protozoan parasite of the genus Leishmania (L.), using the macrophage as the main host cell where it can survive and replicate. The infection outcome depends on the balance between the ability of the host to activate the macrophage microbocidal mechanisms to kill the parasite, and the pathogen’s ability to suppress the host immune response and survive in the harsh environment of phagolysosomes. This ability to circumvent the host immune response may be the result of pressure exerted by the parasite on macrophage gene expression in a way that promotes their survival and multiplication. In this study, we compared the expression kinetics of 82 Bone-Marrow-Derived Macropahge (BMDM) gene transcripts, from susceptible (BALB/c and PWK) and resistant (C57BL/6 and MBT) mice strains, following in vitro infection with L. major parasites, the causative agent of human zoonotic cutaneous leishmaniasis. These genes belong to several functional families e.g., IFN? pathway, TLRs, chemokines, nitric oxid production pathway or involved in various metabolic pathways. Our results showed a clear contrast between the different profiles according to the infection stage (early vs. middle or late) in the four mice strains: regardless to targeted transcripts, the BMDM gene expression profile reflects, at early stages (3h post-infection), the genetic mice background and their susceptibility to Leishmania infection; whereas there is no such correlation at later stages. Indeed, and independently of the gene function, macrophages of susceptible BALB/c and PWK mice showed a general inhibited expression profile while the resistant C57BL/6 and MBT mice expression profile levels are higher compared to non-infected BMDM. Strikingly, this observation was not seen at later times of infection (24h and 72h post-infection) and the expression level depends on each transcript; a direct relationship between the mouse background and the level of expression of a given gene being less obvious. Whether, this early strain-specific effect of parasites on BMDM is due to a general phenomenon that may be encountered with any phagocytosed particle or specific to L. major will be discussed. This study provides a strong argument that susceptibility versus resistance to Leishmania infection of mice with different genetic backgrounds, would be partly due to the innate immunity. These results indicate that these differences in activation of innate immunity illustrate, at least in part, the differences in clinical expression of experimental leishmaniasis in the four mice strains.

Role of Human Macrophage Polarization in Inflammation during Infectious Diseases

Experimental models have often been at the origin of immunological paradigms such as the M1/M2 dichotomy following macrophage polarization. However, this clear dichotomy in animal models is not as obvious in humans, and the separating line between M1-like and M2-like macrophages is rather represented by a continuum, where boundaries are still unclear. Indeed, human infectious diseases, are characterized by either a back and forth or often a mixed profile between the pro-inflammatory microenvironment (dominated by interleukin (IL)-1β, IL-6, IL-12, IL-23 and Tumor Necrosis Factor (TNF)-α cytokines) and tissue injury driven by classically activated macrophages (M1-like) and wound healing driven by alternatively activated macrophages (M2-like) in an anti-inflammatory environment (dominated by IL-10, Transforming growth factor (TGF)-β, chemokine ligand (CCL)1, CCL2, CCL17, CCL18, and CCL22). This review brews the complexity of the situation during infectious diseases by stressing on this continuum between M1-like and M2-like extremes. We first discuss the basic biology of macrophage polarization, function, and role in the inflammatory process and its resolution. Secondly, we discuss the relevance of the macrophage polarization continuum during infectious and neglected diseases, and the possibility to interfere with such activation states as a promising therapeutic strategy in the treatment of such diseases.