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Abstract Drug–drug interactions (DDI) are a critical concern in healthcare due to their potential to cause adverse effects and compromise patient safety. Supervised machine learning models for DDI prediction need to be optimized to learn abstract, transferable features, and generalize to larger chemical spaces, primarily due to the scarcity of high-quality labeled DDI data. Inspired by recent advances in computer vision, we present SMR–DDI, a self-supervised framework that leverages contrastive learning to embed drugs into a scaffold-based feature space. Molecular scaffolds represent the core structural motifs that drive pharmacological activities, making them valuable for learning informative representations. Specifically, we pre-trained SMR–DDI on a large-scale unlabeled molecular dataset. We generated augmented views for each molecule via SMILES enumeration and optimized the embedding process through contrastive loss minimization between views. This enables the model to capture relevant and robust molecular features while reducing noise. We then transfer the learned representations for the downstream prediction of DDI. Experiments show that the new feature space has comparable expressivity to state-of-the-art molecular representations and achieved competitive DDI prediction results while training on less data. Additional investigations also revealed that pre-training on more extensive and diverse unlabeled molecular datasets improved the model’s capability to embed molecules more effectively. Our results highlight contrastive learning as a promising approach for DDI prediction that can identify potentially hazardous drug combinations using only structural information.

Abstract Background Streptococcus pneumoniae is a gram-positive opportunistic pathogen, and infection risks of S. pneumoniae can be profoundly augmented by its acquired multidrug-resistance (MDR). The rapid development of MDR in S. pneumoniae was attributed to the international dissemination of a small number of multidrug-resistant “clones.” Clonal complex (CC) 271 is a prevalent MDR CC in the world and the most prevalent CC in China. However, the evolutionary trajectories of multidrug-resistant S. pneumoniae CC271 in China still are largely unknown. Methods We investigated a collection of 1312 S. pneumoniae isolates collected from 28 tertiary hospitals in China from 2007 to 2020. Recombination prediction and recombination-masked phylogenetic analysis were combined to determine the population structure and mode of evolution of CC271. Data from the Global Pneumococcal Sequencing program (GPS) were combined to understand the global distribution of clones identified in this study. Bayesian analysis were recruited to analysis the evolutionary dynamics of dominant clones within CC271 in China. Results The phylogenomic analysis resulted in the discovery of two globally distributed clones, ST271-A and ST271-B. ST271-A was a derivative of ST236 and an ancestor of ST271-B and ST320, refining the internal phylogenetic relationship of CC271. ST271-B was the most dominant clone in China, with higher β-lactam resistance especially for cephalosporins comparing to other MDR clones. Bayesian skyline plot showed a rapid expansion of 19F ST271-B from 1995 to 2000, which correlates with the widespread use of cephalosporins in the 1990s in China. 19A ST320, a vaccine-escape clone, is the second largest population in China. The Bayesian skyline plot showed that the 19A ST320 began to expand rapidly around 2001, which appeared to coincide with the prevalence of 19A after application of PCV7 in 2000 in the USA. We also observed frequent transmission of 19A ST320 between countries. It suggests that mass vaccination in some countries could affect the prevalence of clones in unvaccinated countries in the context of high-frequency international transmission. Conclusions Our results refined the internal phylogenetic relationship of CC271, showing that the 19F ST271-B and 19A ST320 evolved independently from ST271-A, with different histories and driving forces for their evolution and dissemination in China.

Nunavik Inuit gut microbiome retains a high intra-individual and lower inter-individual diversity, and is distinct from the gut microbiome of non-industrial and industrial populations

Abstract Identification of proteins is one of the most computationally intensive steps in genomics studies. It usually relies on aligners that do not accommodate rich information on proteins and require additional pipelining steps for protein identification. We introduce kAAmer, a protein database engine based on amino-acid k-mers that provides efficient identification of proteins while supporting the incorporation of flexible annotations on these proteins. Moreover, the database is built to be used as a microservice, to be hosted and queried remotely.

Abstract Background Microglia participate in the immune response upon central nervous system (CNS) infections. However, the role of these cells during herpes simplex encephalitis (HSE) has not been fully characterized. We sought to identify different microglia/microglia-like cells and describe the potential mechanisms and signaling pathways involved during HSE. Methods The transcriptional response of CD11b+ immune cells, including microglia/microglia-like cells, was investigated using single-cell RNA sequencing (scRNA-seq) on cells isolated from the ventral posterolateral nucleus (VPL)-enriched thalamic regions of C57BL/6 N mice intranasally infected with herpes simplex virus-1 (HSV-1) (6 × 105 PFUs/20 µl). We further performed scanning electronic microscopy (SEM) analysis in VPL regions on day 6 post-infection (p.i.) to provide insight into microglial functions. Results We describe a novel microglia-like transcriptional response associated with a rare cell population (7% of all analyzed cells), named “in transition” microglia/microglia-like cells in HSE. This new microglia-like transcriptional signature, found in the highly infected thalamic regions, was enriched in specific genes (Retnlg, Cxcr2, Il1f9) usually associated with neutrophils. Pathway analysis of this cell-type transcriptome showed increased NLRP3-inflammasome-mediated interleukin IL-1β production, promoting a pro-inflammatory response. These cells' increased expression of viral transcripts suggests that the distinct “in transition” transcriptome corresponds to the intrinsic antiviral immune signaling of HSV-1-infected microglia/microglia-like cells in the thalamus. In accordance with this phenotype, we observed several TMEM119+/IBA-I+ microglia/microglia-like cells immunostained for HSV-1 in highly infected regions. Conclusions A new microglia/microglia-like state may potentially shed light on how microglia could react to HSV-1 infection. Our observations suggest that infected microglia/microglia-like cells contribute to an exacerbated CNS inflammation. Further characterization of this transitory state of the microglia/microglia-like cell transcriptome may allow the development of novel immunomodulatory approaches to improve HSE outcomes by regulating the microglial immune response.

Abstract Background Deep learning methods are a proven commodity in many fields and endeavors. One of these endeavors is predicting the presence of adverse drug–drug interactions (DDIs). The models generated can predict, with reasonable accuracy, the phenotypes arising from the drug interactions using their molecular structures. Nevertheless, this task requires improvement to be truly useful. Given the complexity of the predictive task, an extensive benchmarking on structure-based models for DDIs prediction was performed to evaluate their drawbacks and advantages. Results We rigorously tested various structure-based models that predict drug interactions using different splitting strategies to simulate different real-world scenarios. In addition to the effects of different training and testing setups on the robustness and generalizability of the models, we then explore the contribution of traditional approaches such as multitask learning and data augmentation. Conclusion Structure-based models tend to generalize poorly to unseen drugs despite their ability to identify new DDIs among drugs seen during training accurately. Indeed, they efficiently propagate information between known drugs and could be valuable for discovering new DDIs in a database. However, these models will most probably fail when exposed to unknown drugs. While multitask learning does not help in our case to solve the problem, the use of data augmentation does at least mitigate it. Therefore, researchers must be cautious of the bias of the random evaluation scheme, especially if their goal is to discover new DDIs.

Abstract Herpes simplex virus 1 (HSV-1) is responsible for herpes simplex virus encephalitis (HSE), associated with a 70% mortality rate in the absence of treatment. Despite intravenous treatment with acyclovir, mortality remains significant, highlighting the need for new anti-herpetic agents. Herein, we describe a novel neurovirulent recombinant HSV-1 (rHSV-1), expressing the fluorescent tdTomato and Gaussia luciferase (Gluc) enzyme, generated by the Clustered regularly interspaced short palindromic repeats (CRISPR)—CRISPR-associated protein 9 (Cas9) (CRISPR-Cas9) system. The Gluc activity measured in the cell culture supernatant was correlated (P = 0.0001) with infectious particles, allowing in vitro monitoring of viral replication kinetics. A significant correlation was also found between brain viral titers and Gluc activity in plasma (R2 = 0.8510, P

Public health vaccination recommendations for COVID-19 primary series and boosters in previously infected individuals differ worldwide. As infection with SARS-CoV-2 is often asymptomatic, it remains to be determined if vaccine immunogenicity is comparable in all previously infected subjects. This study presents detailed immunological evidence to clarify the requirements for one- or two-dose primary vaccination series for naturally primed individuals. The main objective was to evaluate the immune response to COVID-19 mRNA vaccination to establish the most appropriate vaccination regimen to induce robust immune responses in individuals with prior SARS-CoV-2 infection. The main outcome measure was a functional immunity score (zero to three) before and after vaccination, based on anti-RBD IgG levels, serum capacity to neutralize live virus and IFN-γ secretion capacity in response to SARS-CoV-2 peptide pools. One point was attributed for each of these three functional assays with response above the positivity threshold. The immunity score was compared based on subjects’ symptoms at diagnosis and/or serostatus prior to vaccination. None of the naïve participants (n=14) showed a maximal immunity score of three following one dose of vaccine compared to 84% of the previously infected participants (n=55). All recovered individuals who did not have an immunity score of three were seronegative prior to vaccination, and 67% had not reported symptoms resulting from their initial infection. Following one dose of vaccine, their immune responses were comparable to naïve individuals, with significantly weaker responses than individuals who were symptomatic during infection. These results indicate that the absence of symptoms during initial infection and negative serostatus prior to vaccination predict the strength of immune responses to COVID-19 mRNA vaccine. Altogether, these findings highlight the importance of administering the complete two-dose primary regimen and following boosters of mRNA vaccines to individuals who experienced asymptomatic SARS-CoV-2 infection.

Abstract Background Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication combinations and sequences of use makes it complicated for traditional statistical methods to predict which therapy is genuinely associated with health outcomes. The project aims to use artificial intelligence (AI) to determine the quality of polypharmacy among older adults with chronic diseases in the province of Québec, Canada. Methods We will use data from the Quebec Integrated Chronic Disease Surveillance System (QICDSS). QICDSS contains information about prescribed medications in older adults in Quebec collected over 20 years. It also includes diagnostic codes and procedures, and sociodemographic data linked through a unique identification number for each individual. Our research will be structured around three interconnected research axes: AI, Health, and Law&Ethics. The AI research axis will develop algorithms for finding frequent patterns of medication use that correlate with health events, considering data locality and temporality (explainable AI or XAI). The Health research axis will translate these patterns into polypharmacy indicators relevant to public health surveillance and clinicians. The Law&Ethics axis will assess the social acceptability of the algorithms developed using AI tools and the indicators developed by the Heath axis and will ensure that the developed indicators neither discriminate against any population group nor increase the disparities already present in the use of medications. Discussion The multi-disciplinary research team consists of specialists in AI, health data, statistics, pharmacy, public health, law, and ethics, which will allow investigation of polypharmacy from different points of view and will contribute to a deeper understanding of the clinical, social, and ethical issues surrounding polypharmacy and its surveillance, as well as the use of AI for health record data. The project results will be disseminated to the scientific community, healthcare professionals, and public health decision-makers in peer-reviewed publications, scientific meetings, and reports. The diffusion of the results will ensure the confidentiality of individual data.

Abstract Background Low-abundance microorganisms of the gut microbiome are often referred to as a reservoir for antibiotic resistance genes. Unfortunately, these less-abundant bacteria can be overlooked by deep shotgun sequencing. In addition, it is a challenge to associate the presence of resistance genes with their risk of acquisition by pathogens. In this study, we used liquid culture enrichment of stools to assemble the genome of lower-abundance bacteria from fecal samples. We then investigated the gene content recovered from these culture-enriched and culture-independent metagenomes in relation with their taxonomic origin, specifically antibiotic resistance genes. We finally used a pangenome approach to associate resistance genes with the core or accessory genome of Enterobacteriaceae and inferred their propensity to horizontal gene transfer. Results Using culture-enrichment approaches with stools allowed assembly of 187 bacterial species with an assembly size greater than 1 million nucleotides. Of these, 67 were found only in culture-enriched conditions, and 22 only in culture-independent microbiomes. These assembled metagenomes allowed the evaluation of the gene content of specific subcommunities of the gut microbiome. We observed that differentially distributed metabolic enzymes were associated with specific culture conditions and, for the most part, with specific taxa. Gene content differences between microbiomes, for example, antibiotic resistance, were for the most part not associated with metabolic enzymes, but with other functions. We used a pangenome approach to determine if the resistance genes found in Enterobacteriaceae, specifically E. cloacae or E. coli, were part of the core genome or of the accessory genome of this species. In our healthy volunteer cohort, we found that E. cloacae contigs harbored resistance genes that were part of the core genome of the species, while E. coli had a large accessory resistome proximal to mobile elements. Conclusion Liquid culture of stools contributed to an improved functional and comparative genomics study of less-abundant gut bacteria, specifically those associated with antibiotic resistance. Defining whether a gene is part of the core genome of a species helped in interpreting the genomes recovered from culture-independent or culture-enriched microbiomes.

Antimicrobial resistance (AMR) is continuing to grow across the world. Though often thought of as a mostly public health issue, AMR is also a major agricultural and environmental problem. As such, many researchers refer to it as the preeminent One Health issue. Aerial transport of antimicrobial-resistant bacteria via bioaerosols is still poorly understood. Recent work has highlighted the presence of antibiotic resistance genes in bioaerosols. Emissions of AMR bacteria and genes have been detected from various sources, including wastewater treatment plants, hospitals, and agricultural practices; however, their impacts on the broader environment are poorly understood. Contextualizing the roles of bioaerosols in the dissemination of AMR necessitates a multidisciplinary approach. Environmental factors, industrial and medical practices, as well as ecological principles influence the aerial dissemination of resistant bacteria. This article introduces an ongoing project assessing the presence and fate of AMR in bioaerosols across Canada. Its various sub-studies include the assessment of the emissions of antibiotic resistance genes from many agricultural practices, their long-distance transport, new integrative methods of assessment, and the creation of dissemination models over short and long distances. Results from sub-studies are beginning to be published. Consequently, this paper explains the background behind the development of the various sub-studies and highlight their shared aspects.

Non-alcoholic fatty liver disease (NAFLD) is a complex disease associated with premature mortality. Its diagnosis is challenging, and the identification of biomarkers causally influenced by NAFLD may be clinically useful. We aimed at identifying blood metabolites causally impacted by NAFLD using two-sample Mendelian randomization (MR) with validation in a population-based biobank. Our instrument for genetically predicted NAFLD included all independent genetic variants from a recent genome-wide association study. The outcomes included 123 blood metabolites from 24,925 individuals. After correction for multiple testing, a positive effect of NAFLD on plasma tyrosine levels but not on other metabolites was identified. This association was consistent across MR methods and was robust to outliers and pleiotropy. In observational analyses performed in the Estonian Biobank (10,809 individuals including 359 patients with NAFLD), after multivariable adjustment, tyrosine levels were positively associated with the presence of NAFLD (odds ratio per 1 SD increment = 1.23 [95% confidence interval = 1.12–1.36], p = 2.19 × 10−5). In a small proof-of-concept study on bariatric surgery patients, blood tyrosine levels were higher in patients with NAFLD than without. This study revealed a potentially causal effect of NAFLD on blood tyrosine levels, suggesting it may represent a new biomarker of NAFLD.

The yeast Geotrichum candidum (teleomorph Galactomyces candidus) is inoculated onto mold- and smear-ripened cheeses and plays several roles during cheese ripening. Its ability to metabolize proteins, lipids, and organic acids enables its growth on the cheese surface and promotes the development of organoleptic properties. Recent multilocus sequence typing (MLST) and phylogenetic analyses of G. candidum isolates revealed substantial genetic diversity, which may explain its strain-dependant technological capabilities. Here, we aimed to shed light on the phenotypic and genetic diversity among eight G. candidum and three Galactomyces spp. strains of environmental and dairy origin. Phenotypic tests such as carbon assimilation profiles, the ability to grow at 35°C and morphological traits on agar plates allowed us to discriminate G. candidum from Galactomyces spp. The genomes of these isolates were sequenced and assembled; whole genome comparison clustered the G. candidum strains into three subgroups and provided a reliable reference for MLST scheme optimization. Using the whole genome sequence as a reference, we optimized an MLST scheme using six loci that were proposed in two previous MLST schemes. This new MLST scheme allowed us to identify 15 sequence types (STs) out of 41 strains and revealed three major complexes named GeoA, GeoB, and GeoC. The population structure of these 41 strains was evaluated with STRUCTURE and a NeighborNet analysis of the combined six loci, which revealed recombination events between and within the complexes. These results hint that the allele variation conferring the different STs arose from recombination events. Recombination occurred for the six housekeeping genes studied, but most likely occurred throughout the genome. These recombination events may have induced an adaptive divergence between the wild strains and the cheesemaking strains, as observed for other cheese ripening fungi. Further comparative genomic studies are needed to confirm this phenomenon in G. candidum. In conclusion, the draft assembly of 11 G. candidum/Galactomyces spp. genomes allowed us to optimize a genotyping MLST scheme and, combined with the assessment of their ability to grow under different conditions, provides a reliable tool to cluster and eventually improves the selection of G. candidum strains.

Carbapenemase-producing Enterobacterales, including KPC-2 producers, have become a major clinical problem. During an outbreak in Quebec City, Canada, KPC-2-producing Klebsiella michiganensis and Citrobacter farmeri were isolated from a patient six weeks apart. We determined their complete genome sequences. Both isolates carried nearly identical IncN2 plasmids with blaKPC-2 on a Tn4401b element. Both strains also carried IncP1 plasmids, but that of C. farmeri did not carry a Beta-lactamase gene, whereas that of K. michiganensis carried a second copy of blaKPC-2 on Tn4401b. These results suggest recent plasmid transfer between the two species and a recent transposition event.

Abstract It has been proposed that macrophages could serve as long-lived compartments for HIV-1 infection under in vivo situations because these cells are resistant to the virus-mediated cytopathic effect, produce progeny virus over extended periods of time and are localized in tissues that are often less accessible by treatment. Comprehensive experimental studies are thus needed to characterize the HIV-1-induced modulation of host genes in these myeloid lineage cells. To shed light on this important issue, we performed comparative analyses of mRNA expression levels of host genes in uninfected bystander and HIV-1-infected human macrophages using an infectious reporter virus construct coupled with a large-scale RNA sequencing approach. We observed a rapid differential expression of several host factors in the productively infected macrophage population including genes regulating DNA replication factors and chromatin remodeling. A siRNA-mediated screening study to functionally identify host determinants involved in HIV-1 biology has provided new information on the virus molecular regulation in macrophages.

One of the most critical but still poorly understood aspects of eukaryotic cell proliferation is the basis for commitment to cell division in late G1 phase, called Start in yeast and the Restriction Point in metazoans. In all species, a critical cell size threshold coordinates cell growth with cell division and thereby establishes a homeostatic cell size. While a comprehensive survey of cell size genetic determinism has been performed in the saprophytic yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe, very little is known in pathogenic fungi. As a number of critical Start regulators are haploinsufficient for cell size, we applied a quantitative analysis of the size phenome, using elutriation-barcode sequencing methodology, to 5639 barcoded heterozygous deletion strains of the opportunistic yeast Candida albicans. Our screen identified conserved known regulators and biological processes required to maintain size homeostasis in the opportunistic yeast C. albicans. We also identified novel C. albicans-specific size genes and provided a conceptual framework for future mechanistic studies. Interestingly, some of the size genes identified were required for fungal pathogenicity suggesting that cell size homeostasis may be elemental to C. albicans fitness or virulence inside the host.

The lactococcal virulent phage p2 is a model for studying the Skunavirus genus, the most prevalent group of phages causing milk fermentation failures in cheese factories worldwide. This siphophage infects Lactococcus lactis MG1363, a model strain used to study Gram-positive lactic acid bacteria. The structural proteins of phage p2 have been thoroughly described, while most of its non-structural proteins remain uncharacterized. Here, we developed an integrative approach, making use of structural biology, genomics, physiology, and proteomics to provide insights into the function of ORF47, the most conserved non-structural protein of unknown function among the Skunavirus genus. This small phage protein, which is composed of three α-helices, was found to have a major impact on the bacterial proteome during phage infection and to significantly reduce the emergence of bacteriophage-insensitive mutants.

To assess molecular evolution of the respiratory syncytial virus (RSV) fusion gene, we analyzed RSV-positive specimens from 123 children in Canada who did or did not receive RSV immunoprophylaxis (palivizumab) during 2006–2010. Resistance-conferring mutations within the palivizumab binding site occurred in 8.7% of palivizumab recipients and none of the nonrecipients.

The St. Lawrence hydrographic system includes freshwater, brackish, and marine habitats, and is the largest waterway in North America by volume. The food-webs in these habitats are ultimately dependent on phytoplankton. Viral lysis is believed to be responsible for a major part of phytoplankton mortality. To better understand their role, we characterized the diversity and distribution of two viral taxa infecting phytoplankton: the picornaviruses and phycodnaviruses. Our study focused on the estuary transition zone, which is an important nursery for invertebrates and fishes. Both viral taxa were investigated by PCR amplification of conserved molecular markers and next-generation sequencing at six sites, ranging from freshwater to marine. Our results revealed few shared viral phylotypes between saltwater and freshwater sites. Salinity appeared to be the primary determinant of viral community composition. Moreover, our analysis indicated that the viruses identified in this region of the St. Lawrence diverge from classified viruses and homologous published environmental virotypes. These results suggest that DNA and RNA viruses infecting phytoplankton are likely active in the estuary transition zone, and that this region harbors its own unique viral assemblages.

The discovery of peptides possessing high biological activity is very challenging due to the enormous diversity for which only a minority have the desired properties. To lower cost and reduce the time to obtain promising peptides, machine learning approaches can greatly assist in the process and even partly replace expensive laboratory experiments by learning a predictor with existing data or with a smaller amount of data generation. Unfortunately, once the model is learned, selecting peptides having the greatest predicted bioactivity often requires a prohibitive amount of computational time. For this combinatorial problem, heuristics and stochastic optimization methods are not guaranteed to find adequate solutions. We focused on recent advances in kernel methods and machine learning to learn a predictive model with proven success. For this type of model, we propose an efficient algorithm based on graph theory, that is guaranteed to find the peptides for which the model predicts maximal bioactivity. We also present a second algorithm capable of sorting the peptides of maximal bioactivity. Extensive analyses demonstrate how these algorithms can be part of an iterative combinatorial chemistry procedure to speed up the discovery and the validation of peptide leads. Moreover, the proposed approach does not require the use of known ligands for the target protein since it can leverage recent multi-target machine learning predictors where ligands for similar targets can serve as initial training data. Finally, we validated the proposed approach in vitro with the discovery of new cationic antimicrobial peptides. Source code freely available at http://graal.ift.ulaval.ca/peptide-design/.

Gene amplification of specific loci has been described in all kingdoms of life. In the protozoan parasite Leishmania, the product of amplification is usually part of extrachromosomal circular or linear amplicons that are formed at the level of direct or inverted repeated sequences. A bioinformatics screen revealed that repeated sequences are widely distributed in the Leishmania genome and the repeats are chromosome-specific, conserved among species, and generally present in low copy number. Using sensitive PCR assays, we provide evidence that the Leishmania genome is continuously being rearranged at the level of these repeated sequences, which serve as a functional platform for constitutive and stochastic amplification (and deletion) of genomic segments in the population. This process is adaptive as the copy number of advantageous extrachromosomal circular or linear elements increases upon selective pressure and is reversible when selection is removed. We also provide mechanistic insights on the formation of circular and linear amplicons through RAD51 recombinase-dependent and -independent mechanisms, respectively. The whole genome of Leishmania is thus stochastically rearranged at the level of repeated sequences, and the selection of parasite subpopulations with changes in the copy number of specific loci is used as a strategy to respond to a changing environment.

During the summer of 2012, a major Legionella pneumophila serogroup 1 outbreak occurred in Quebec City, Canada, which caused 182 declared cases of Legionnaire's disease and included 13 fatalities. Legionella pneumophila serogroup 1 isolates from 23 patients as well as from 32 cooling towers located in the vicinity of the outbreak were recovered for analysis. In addition, 6 isolates from the 1996 Quebec City outbreak and 4 isolates from patients unrelated to both outbreaks were added to allow comparison. We characterized the isolates using pulsed-field gel electrophoresis, sequence-based typing, and whole genome sequencing. The comparison of patients-isolated strains to cooling tower isolates allowed the identification of the tower that was the source of the outbreak. Legionella pneumophila strain Quebec 2012 was identified as a ST-62 by sequence-based typing methodology. Two new Legionellaceae plasmids were found only in the epidemic strain. The LVH type IV secretion system was found in the 2012 outbreak isolates but not in the ones from the 1996 outbreak and only in half of the contemporary human isolates. The epidemic strains replicated more efficiently and were more cytotoxic to human macrophages than the environmental strains tested. At least four Icm/Dot effectors in the epidemic strains were absent in the environmental strains suggesting that some effectors could impact the intracellular replication in human macrophages. Sequence-based typing and pulsed-field gel electrophoresis combined with whole genome sequencing allowed the identification and the analysis of the causative strain including its likely environmental source.

Team1 (vB_SauM_Team1) is a polyvalent staphylococcal phage belonging to the Myoviridae family. Phage Team1 was propagated on a Staphylococcus aureus strain and a non-pathogenic Staphylococcus xylosus strain used in industrial meat fermentation. The two Team1 preparations were compared with respect to their microbiological and genomic properties. The burst sizes, latent periods, and host ranges of the two derivatives were identical as were their genome sequences. Phage Team1 has 140,903 bp of double stranded DNA encoding for 217 open reading frames and 4 tRNAs. Comparative genomic analysis revealed similarities to staphylococcal phages ISP (97%) and G1 (97%). The host range of Team1 was compared to the well-known polyvalent staphylococcal phages phi812 and K using a panel of 57 S. aureus strains collected from various sources. These bacterial strains were found to represent 18 sequence types (MLST) and 14 clonal complexes (eBURST). Altogether, the three phages propagated on S. xylosus lysed 52 out of 57 distinct strains of S. aureus. The identification of phage-insensitive strains underlines the importance of designing phage cocktails with broadly varying and overlapping host ranges. Taken altogether, our study suggests that some staphylococcal phages can be propagated on food-grade bacteria for biocontrol and safety purposes.

The human protozoan parasites Leishmania are prototrophic for pyrimidines with the ability of both de novo biosynthesis and uptake of pyrimidines.Five independent L. infantum mutants were selected for resistance to the pyrimidine analogue 5-fluorouracil (5-FU) in the hope to better understand the metabolism of pyrimidine in Leishmania. Analysis of the 5-FU mutants by comparative genomic hybridization and whole genome sequencing revealed in selected mutants the amplification of DHFR-TS and a deletion of part of chromosome 10. Point mutations in uracil phosphorybosyl transferase (UPRT), thymidine kinase (TK) and uridine phosphorylase (UP) were also observed in three individual resistant mutants. Transfection experiments confirmed that these point mutations were responsible for 5-FU resistance. Transport studies revealed that one resistant mutant was defective for uracil and 5-FU import.This study provided further insights in pyrimidine metabolism in Leishmania and confirmed that multiple mutations can co-exist and lead to resistance in Leishmania.

Streptococcus pneumoniae serotype epidemiology is essential since serotype replacement is a concern when introducing new polysaccharide-conjugate vaccines. A novel PCR-based automated microarray assay was developed to assist in the tracking of the serotypes. Autolysin, pneumolysin and eight genes located in the capsular operon were amplified using multiplex PCR. This step was followed by a tagged fluorescent primer extension step targeting serotype-specific polymorphisms. The tagged primers were then hybridized to a microarray. Results were exported to an expert system to identify capsular serotypes. The assay was validated on 166 cultured S. pneumoniae samples from 63 different serotypes as determined by the Quellung method. We show that typing only 12 polymorphisms located in the capsular operon allows the identification at the serotype level of 22 serotypes and the assignation of 24 other serotypes to a subgroup of serotypes. Overall, 126 samples (75.9%) were correctly serotyped, 14 were assigned to a member of the same serogroup, 8 rare serotypes were erroneously serotyped, and 18 gave negative serotyping results. Most of the discrepancies involved rare serotypes or serotypes that are difficult to discriminate using a DNA-based approach, for example 6A and 6B. The assay was also tested on clinical specimens including 43 cerebrospinal fluid samples from patients with meningitis and 59 nasopharyngeal aspirates from bacterial pneumonia patients. Overall, 89% of specimens positive for pneumolysin were serotyped, demonstrating that this method does not require culture to serotype clinical specimens. The assay showed no cross-reactivity for 24 relevant bacterial species found in these types of samples. The limit of detection for serotyping and S. pneumoniae detection was 100 genome equivalent per reaction. This automated assay is amenable to clinical testing and does not require any culturing of the samples. The assay will be useful for the evaluation of serotype prevalence changes after new conjugate vaccines introduction.

Miltefosine (MF) is the first oral compound used in the chemotherapy against leishmaniasis. Since the mechanism of action of this drug and the targets of MF in Leishmania are unclear, we generated in a step-by-step manner Leishmania major promastigote mutants highly resistant to MF. Two of the mutants were submitted to a short-read whole genome sequencing for identifying potential genes associated with MF resistance.Analysis of the genome assemblies revealed several independent point mutations in a P-type ATPase involved in phospholipid translocation. Mutations in two other proteins-pyridoxal kinase and α-adaptin like protein-were also observed in independent mutants. The role of these proteins in the MF resistance was evaluated by gene transfection and gene disruption and both the P-type ATPase and pyridoxal kinase were implicated in MF susceptibility. The study also highlighted that resistance can be highly heterogeneous at the population level with individual clones derived from this population differing both in terms of genotypes but also susceptibility phenotypes.Whole genome sequencing was used to pinpoint known and new resistance markers associated with MF resistance in the protozoan parasite Leishmania. The study also demonstrated the polyclonal nature of a resistant population with individual cells with varying susceptibilities and genotypes.

Subversion or exacerbation of antigen-presenting cells (APC) death modulates host/pathogen equilibrium. We demonstrated during in vitro differentiation of monocyte-derived macrophages and monocyte-derived dendritic cells (DCs) that HIV sensitizes the cells to undergo apoptosis in response to TRAIL and FasL, respectively. In addition, we found that HIV-1 increased the levels of pro-apoptotic Bax and Bak molecules and decreased the levels of anti-apoptotic Mcl-1 and FLIP proteins. To assess the relevance of these observations in the context of an experimental model of HIV infection, we investigated the death of APC during pathogenic SIV-infection in rhesus macaques (RMs). We demonstrated increased apoptosis, during the acute phase, of both peripheral blood DCs and monocytes (CD14(+)) from SIV(+)RMs, associated with a dysregulation in the balance of pro- and anti-apoptotic molecules. Caspase-inhibitor and death receptors antagonists prevented apoptosis of APCs from SIV(+)RMs. Furthermore, increased levels of FasL in the sera of pathogenic SIV(+)RMs were detected, compared to non-pathogenic SIV infection of African green monkey. We suggest that inappropriate apoptosis of antigen-presenting cells may contribute to dysregulation of cellular immunity early in the process of HIV/SIV infection.

BACKGROUND: Drug resistance is a major problem in leishmaniasis chemotherapy. RNA expression profiling using DNA microarrays is a suitable approach to study simultaneous events leading to a drug-resistance phenotype. Genomic analysis has been performed primarily with Old World Leishmania species and here we investigate molecular alterations in antimony resistance in the New World species L. amazonensis. METHODS/PRINCIPAL FINDINGS: We selected populations of L. amazonensis promastigotes for resistance to antimony by step-wise drug pressure. Gene expression of highly resistant mutants was studied using DNA microarrays. RNA expression profiling of antimony-resistant L. amazonensis revealed the overexpression of genes involved in drug resistance including the ABC transporter MRPA and several genes related to thiol metabolism. The MRPA overexpression was validated by quantitative real-time RT-PCR and further analysis revealed that this increased expression was correlated to gene amplification as part of extrachromosomal linear amplicons in some mutants and as part of supernumerary chromosomes in other mutants. The expression of several other genes encoding hypothetical proteins but also nucleobase and glucose transporter encoding genes were found to be modulated. CONCLUSIONS/SIGNIFICANCE: Mechanisms classically found in Old World antimony resistant Leishmania were also highlighted in New World antimony-resistant L. amazonensis. These studies were useful to the identification of resistance molecular markers.

The innate immune system recognizes virus infection and evokes antiviral responses which include producing type I interferons (IFNs). The induction of IFN provides a crucial mechanism of antiviral defense by upregulating interferon-stimulated genes (ISGs) that restrict viral replication. ISGs inhibit the replication of many viruses by acting at different steps of their viral cycle. Specifically, IFN treatment prior to in vitro human immunodeficiency virus (HIV) infection stops or significantly delays HIV-1 production indicating that potent inhibitory factors are generated. We report that HIV-1 infection of primary human macrophages decreases tumor necrosis factor receptor-associated factor 6 (TRAF6) and virus-induced signaling adaptor (VISA) expression, which are both components of the IFN signaling pathway controlling viral replication. Knocking down the expression of TRAF6 in macrophages increased HIV-1 replication and augmented the expression of IRF7 but not IRF3. Suppressing VISA had no impact on viral replication. Overexpression of IRF7 resulted in enhanced viral replication while knocking down IRF7 expression in macrophages significantly reduced viral output. These findings are the first demonstration that TRAF6 can regulate HIV-1 production and furthermore that expression of IRF7 promotes HIV-1 replication.