Substitution of dietary monounsaturated fatty acids from olive oil for saturated fatty acids from lard increases low-density lipoprotein apolipoprotein B-100 fractional catabolic rate in subjects with dyslipidemia associated with insulin resistance: a randomized controlled trial.

BACKGROUND: The substitution of monounsaturated acids (MUFAs) for saturated fatty acids (SFAs) is recommended for cardiovascular disease prevention but its impact on lipoprotein metabolism in subjects with dyslipidemia associated with insulin resistance (IR) remains largely unknown. OBJECTIVES: This study aimed to evaluate the impact of substituting MUFAs for SFAs on the in vivo kinetics of apolipoprotein (apo)B-containing lipoproteins and on the plasma lipidomic profile in adults with IR-induced dyslipidemia. METHODS: Males and females with dyslipidemia associated with IR (n = 18) were recruited for this crossover double-blind randomized controlled trial. Subjects consumed, in random order, a diet rich in SFAs (SFAs: 13.4%E; MUFAs: 14.4%E) and a diet rich in MUFAs (SFAs: 7.1%E; MUFAs: 20.7%E) in fully controlled feeding conditions for periods of 4 wk each, separated by a 4-wk washout. At the end of each diet, fasting plasma samples were taken together with measurements of the in vivo kinetics of apoB-containing lipoproteins. RESULTS: Substituting MUFAs for SFAs had no impact on triglyceride-rich lipoprotein apoB-48 fractional catabolic rate (FCR) (Δ = -8.9%, P = 0.4) and production rate (Δ = 0.0%, P = 0.9), although it decreased very low-density lipoprotein apoB-100 pool size (PS) (Δ = -22.5%; P = 0.01). This substitution also reduced low-density lipoprotein cholesterol (LDL-C) (Δ = -7.0%; P = 0.01), non-high-density lipoprotein cholesterol (Δ = -2.5%; P = 0.04), and LDL apoB-100 PS (Δ = -6.0%; P = 0.05). These differences were partially attributed to an increase in LDL apoB-100 FCR (Δ = +1.6%; P = 0.05). The MUFA diet showed reduced sphingolipid concentrations and elevated glycerophospholipid levels compared with the SFA diet. CONCLUSIONS: This study demonstrated that substituting dietary MUFAs for SFAs decreases LDL-C levels and LDL PS by increasing LDL apoB-100 FCR and results in an overall improved plasma lipidomic profile in individuals with IR-induced lipidemia. TRIAL REGISTRATION: This trial was registered as clinicaltrials.gov as NCT03872349.

Mendelian Randomization Analysis Identifies Blood Tyrosine Levels as a Biomarker of Non-Alcoholic Fatty Liver Disease.

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.

Exploring polypharmacy with artificial intelligence: data analysis protocol.

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.

Machine learning analysis identifies genes differentiating triple negative breast cancers.

Triple negative breast cancer (TNBC) is one of the most aggressive form of breast cancer (BC) with the highest mortality due to high rate of relapse, resistance, and lack of an effective treatment. Various molecular approaches have been used to target TNBC but with little success. Here, using machine learning algorithms, we analyzed the available BC data from the Cancer Genome Atlas Network (TCGA) and have identified two potential genes, TBC1D9 (TBC1 domain family member 9) and MFGE8 (Milk Fat Globule-EGF Factor 8 Protein), that could successfully differentiate TNBC from non-TNBC, irrespective of their heterogeneity. TBC1D9 is under-expressed in TNBC as compared to non-TNBC patients, while MFGE8 is over-expressed. Overexpression of TBC1D9 has a better prognosis whereas overexpression of MFGE8 correlates with a poor prognosis. Protein-protein interaction analysis by affinity purification mass spectrometry (AP-MS) and proximity biotinylation (BioID) experiments identified a role for TBC1D9 in maintaining cellular integrity, whereas MFGE8 would be involved in various tumor survival processes. These promising genes could serve as biomarkers for TNBC and deserve further investigation as they have the potential to be developed as therapeutic targets for TNBC.

Criibacterium bergeronii gen. nov., sp. nov., a new member of the family Peptostreptococcaceae, isolated from human clinical samples.

A rod-shaped, motile anaerobic bacterium, designated CCRI-22567T, was isolated from a vaginal sample of a woman diagnosed with bacterial vaginosis and subjected to a polyphasic taxonomic study. The novel strain was capable of growth at 30-42 °C (optimum, 42 °C), at pH 5.5-8.5 (optimum, pH 7.0-7.5) and in the presence of 0-1.5 % (w/v) NaCl (optimally at 0.5 % NaCl). The phylogenetic trees based on 16S rRNA gene sequences showed that strain CCRI-22567T forms a distinct evolutionary lineage independent of other taxa in the family Peptostreptococcaceae. Strain CCRI-22567T exhibited 90.1 % 16S rRNA gene sequence similarity to Peptoanaerobacter stomatis ACC19aT and 89.7 % to Eubacterium yurii subsp. schtitka ATCC 43716. The three closest organisms with an available whole genome were compared to strain CCRI-22567T for genomic relatedness assessment. The genomic average nucleotide identities (OrthoANIu) obtained with Peptoanaerobacter stomatis ACC19aT, Eubacterium yurii subsp. margaretiae ATCC 43715 and Filifactor alocis ATCC 35896T were 71.8, 70.3 and 69.6 %, respectively. Strain CCRI-22567T contained C18 : 1 ω9c and C18 : 1 ω9c DMA as the major fatty acids. The DNA G+C content of strain CCRI-22567T based on its genome sequence was 33.8 mol%. On the basis of the phylogenetic, chemotaxonomic and other phenotypic properties, strain CCRI-22567T is considered to represent a new genus and species within the family Peptostreptococcaceae, for which the name Criibacterium bergeronii gen. nov., sp. nov., is proposed. The type strain of Criibacterium bergeronii is CCRI-22567T (=LMG 31278T=DSM 107614T=CCUG 72594T).

Human viral pathogens are pervasive in wastewater treatment center aerosols.

Wastewater treatment center (WTC) workers may be vulnerable to diseases caused by viruses, such as the common cold, influenza and gastro-intestinal infections. Although there is a substantial body of literature characterizing the microbial community found in wastewater, only a few studies have characterized the viral component of WTC aerosols, despite the fact that most diseases affecting WTC workers are of viral origin and that some of these viruses are transmitted through the air. In this study, we evaluated in four WTCs the presence of 11 viral pathogens of particular concern in this milieu and used a metagenomic approach to characterize the total viral community in the air of one of those WTCs. The presence of viruses in aerosols in different locations of individual WTCs was evaluated and the results obtained with four commonly used air samplers were compared. We detected four of the eleven viruses tested, including human adenovirus (hAdV), rotavirus, hepatitis A virus (HAV) and Herpes Simplex virus type 1 (HSV1). The results of the metagenomic assay uncovered very few viral RNA sequences in WTC aerosols, however sequences from human DNA viruses were in much greater relative abundance.

Global Mapping of the Macrophage-HIV-1 Transcriptome Reveals that Productive Infection Induces Remodeling of Host Cell DNA and Chromatin.

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.

Machine learning assisted design of highly active peptides for drug discovery.

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/.

MHC-NP: predicting peptides naturally processed by the MHC.

We present MHC-NP, a tool for predicting peptides naturally processed by the MHC pathway. The method was part of the 2nd Machine Learning Competition in Immunology and yielded state-of-the-art accuracy for the prediction of peptides eluted from human HLA-A*02:01, HLA-B*07:02, HLA-B*35:01, HLA-B*44:03, HLA-B*53:01, HLA-B*57:01 and mouse H2-D(b) and H2-K(b) MHC molecules. We briefly explain the theory and motivations that have led to developing this tool. General applicability in the field of immunology and specifically epitope-based vaccine are expected. Our tool is freely available online and hosted by the Immune Epitope Database at http://tools.immuneepitope.org/mhcnp/.

Nasopharyngeal carriage of individual Streptococcus pneumoniae serotypes during pediatric radiologically confirmed community acquired pneumonia following PCV7 introduction in Switzerland.

BACKGROUND: Community-acquired pneumonia (CAP) is a serious cause of morbidity among children in developed countries. The real impact of 7-valent pneumococcal conjugate vaccine (PCV7) on pneumococcal pneumonia is difficult to assess accurately. METHODS: Children aged ≤16 years with clinical and radiological pneumonia were enrolled in a multicenter prospective study. Children aged ≤16 years admitted for a minor elective surgery was recruited as controls. Nasopharyngeal samples for PCR serotyping of S. pneumoniae were obtained in both groups. Informations on age, gender, PCV7 vaccination status, day care/school attendance, siblings, tobacco exposure were collected. RESULTS: In children with CAP (n=236), 54% of the nasopharyngeal swabs were PCR-positive for S. pneumoniae compared to 32% in controls (n=105) (p=0.003). Serotype 19A was the most common pneumococcal serotype carried in children with CAP (13%) and in controls (15%). Most common serotypes were non-vaccine types (39.4% for CAP and 47.1% for controls) and serotypes included only in PCV13 (32.3% for CAP and 23.5% for controls). There was no significant difference in vaccine serotype distribution between the two groups. In fully vaccinated children with CAP, the proportion of serotypes carried only in PCV13 was higher (51.4%) than in partially vaccinated or non vaccinated children (27.6% and 28.6% respectively, p=0.037). CONCLUSIONS: Two to 4 years following introduction of PCV7, predominant S. pneumoniae serotypes carried in children with CAP were non PCV7 serotypes, and the 6 new serotypes included in PCV13 accounted for 51.4% of carried serotypes in fully vaccinated children.

Correlation between Clostridium difficile bacterial load, commercial real-time PCR cycle thresholds, and results of diagnostic tests based on enzyme immunoassay and cell culture cytotoxicity assay.

The impact of Clostridium difficile fecal loads on diagnostic test results is poorly understood, but it may have clinical importance. In this study, we investigated the relationship between C. difficile fecal load and the results of four assays: a glutamate dehydrogenase (GDH) enzyme immunoassay (EIA), a toxin A/B antigen EIA (ToxAB), a cell culture cytotoxicity assay (CCA), and PCR targeting the tcdB gene. We also compared the PCR cycle threshold (CT) with the results of quantitative culture using Spearman's rank correlation coefficient. Finally, we sequenced the genomes of 24 strains with different detection profiles. A total of 203 clinical samples harboring toxigenic C. difficile were analyzed and sorted into one of four groups: 17 PCR(+) (group 1), 37 PCR(+) GDH(+) (group 2), 24 PCR(+) GDH(+) CCA(+) (group 3), and 125 PCR(+) GDH(+) ToxAB(+) (group 4). The overall median fecal load in log10 CFU/g was 6.67 (interquartile range [IQR], 5.57 to 7.54). The median fecal bacterial load of groups 1, 2, 3, and 4 were 4.15 (IQR, 3.00 to 4.98), 5.74 (IQR, 4.75 to 6.16), 6.20 (IQR, 5.23 to 6.80), and 7.08 (IQR, 6.35 to 7.83), respectively. Group 1 samples had lower fecal loads than those from each of the other groups (P < 0.001). Group 2 samples had lower fecal loads than those from groups 3 and 4 (P < 0.001). There was a significant correlation between PCR CT and fecal loads (ρ = -0.697; P < 0.001). NAP1 strains were associated with the detection of toxins by EIA or CCA (P = 0.041). This study demonstrates an association between C. difficile fecal load and the results of routinely used diagnostic tests.

Gene expression modulation and the molecular mechanisms involved in Nelfinavir resistance in Leishmania donovani axenic amastigotes.

Drug resistance is a major public health challenge in leishmaniasis chemotherapy, particularly in the case of emerging Leishmania/HIV-1 co-infections. We have delineated the mechanism of cell death induced by the HIV-1 protease inhibitor, Nelfinavir, in the Leishmania parasite. In order to further study Nelfinavir-Leishmania interactions, we selected Nelfinavir-resistant axenic amastigotes in vitro and characterized them. RNA expression profiling analyses and comparative genomic hybridizations of closely related Leishmania species were used as a screening tool to compare Nelfinavir-resistant and -sensitive parasites in order to identify candidate genes involved in drug resistance. Microarray analyses of Nelfinavir-resistant and -sensitive Leishmania amastigotes suggest that parasites regulate mRNA levels either by modulating gene copy numbers through chromosome aneuploidy, or gene deletion/duplication by homologous recombination. Interestingly, supernumerary chromosomes 6 and 11 in the resistant parasites lead to upregulation of the ABC class of transporters. Transporter assays using radiolabelled Nelfinavir suggest a greater drug accumulation in the resistant parasites and in a time-dependent manner. Furthermore, high-resolution electron microscopy and measurements of intracellular polyphosphate levels showed an increased number of cytoplasmic vesicular compartments known as acidocalcisomes in Nelfinavir-resistant parasites. Together these results suggest that Nelfinavir is rapidly and dramatically sequestered in drug-induced intracellular vesicles.

Learning a peptide-protein binding affinity predictor with kernel ridge regression.

BACKGROUND: The cellular function of a vast majority of proteins is performed through physical interactions with other biomolecules, which, most of the time, are other proteins. Peptides represent templates of choice for mimicking a secondary structure in order to modulate protein-protein interaction. They are thus an interesting class of therapeutics since they also display strong activity, high selectivity, low toxicity and few drug-drug interactions. Furthermore, predicting peptides that would bind to a specific MHC alleles would be of tremendous benefit to improve vaccine based therapy and possibly generate antibodies with greater affinity. Modern computational methods have the potential to accelerate and lower the cost of drug and vaccine discovery by selecting potential compounds for testing in silico prior to biological validation. RESULTS: We propose a specialized string kernel for small bio-molecules, peptides and pseudo-sequences of binding interfaces. The kernel incorporates physico-chemical properties of amino acids and elegantly generalizes eight kernels, comprised of the Oligo, the Weighted Degree, the Blended Spectrum, and the Radial Basis Function. We provide a low complexity dynamic programming algorithm for the exact computation of the kernel and a linear time algorithm for it's approximation. Combined with kernel ridge regression and SupCK, a novel binding pocket kernel, the proposed kernel yields biologically relevant and good prediction accuracy on the PepX database. For the first time, a machine learning predictor is capable of predicting the binding affinity of any peptide to any protein with reasonable accuracy. The method was also applied to both single-target and pan-specific Major Histocompatibility Complex class II benchmark datasets and three Quantitative Structure Affinity Model benchmark datasets. CONCLUSION: On all benchmarks, our method significantly (p-value ≤ 0.057) outperforms the current state-of-the-art methods at predicting peptide-protein binding affinities. The proposed approach is flexible and can be applied to predict any quantitative biological activity. Moreover, generating reliable peptide-protein binding affinities will also improve system biology modelling of interaction pathways. Lastly, the method should be of value to a large segment of the research community with the potential to accelerate the discovery of peptide-based drugs and facilitate vaccine development. The proposed kernel is freely available at http://graal.ift.ulaval.ca/downloads/gs-kernel/.

Telomeric gene deletion and intrachromosomal amplification in antimony-resistant Leishmania.

Antimonials are still the mainstay of treatment against leishmaniasis but drug resistance is increasing. We carried out short read next-generation sequencing (NGS) and comparative genomic hybridization (CGH) of three independent Leishmania major antimony-resistant mutants. Copy number variations were consistently detected with both NGS and CGH. A major attribute of antimony resistance was a novel terminal deletion of variable length (67 kb to 204 kb) of the polyploid chromosome 31 in the three mutants. Terminal deletions in two mutants occurred at the level of inverted repeated sequences. The AQP1 gene coding for an aquaglyceroporin was part of the deleted region and its transfection into resistant mutants reverted resistance to SbIII. We also highlighted an intrachromosomal amplification of a subtelomeric locus on chromosome 34 in one mutant. This region encoded for ascorbate-dependent peroxidase (APX) and glucose-6-phosphate dehydrogenase (G6PDH). Overexpression of these genes in revertant backgrounds demonstrated resistance to SbIII and protection from reactive oxygen species (ROS). Generation of a G6PDH null mutant in one revertant exhibited SbIII sensitivity and a decreased protection of ROS. Our genomic analyses and functional validation highlighted novel genomic rearrangements, functionally important resistant loci and the implication of new genes in antimony resistance in Leishmania.

Simian immunodeficiency virus infects follicular helper CD4 T cells in lymphoid tissues during pathogenic infection of pigtail macaques.

T follicular helper (Tfh) cells are a specialized subset of memory CD4(+) T cells that are found exclusively within the germinal centers of secondary lymphoid tissues and are important for adaptive antibody responses and B cell memory. Tfh cells do not express CCR5, the primary entry coreceptor for both human immunodeficiency virus type 1 (HIV-1) and simian immunodeficiency virus (SIV), and therefore, we hypothesized that these cells would avoid infection. We studied lymph nodes and spleens from pigtail macaques infected with pathogenic strain SIVmac239 or SIVmac251, to investigate the susceptibility of Tfh cells to SIV infection. Pigtail macaque PD-1(high) CD127(low) memory CD4(+) T cells have a phenotype comparable to that of human Tfh cells, expressing high levels of CXCR5, interleukin-21 (IL-21), Bcl-6, and inducible T cell costimulator (ICOS). As judged by either proviral DNA or cell-associated viral RNA measurements, macaque Tfh cells were infected with SIV at levels comparable to those in other CD4(+) memory T cells. Infection of macaque Tfh cells was evident within weeks of inoculation, yet we confirmed that Tfh cells do not express CCR5 or either of the well-known alternative SIV coreceptors, CXCR6 and GPR15. Mutations in the SIV envelope gp120 region occurred in chronically infected macaques but were uniform across each T cell subset investigated, indicating that the viruses used the same coreceptors to enter different cell subsets. Early infection of Tfh cells represents an unexpected focus of viral infection. Infection of Tfh cells does not interrupt antibody production but may be a factor that limits the quality of antibody responses and has implications for assessing the size of the viral reservoir.

HIV downregulates interferon-stimulated genes in primary macrophages.

HIV is able to outpace the innate immune response, including that mediated by interferon (IFN), to establish a productive infection. Primary macrophages, however, may be protected from HIV infection by treatment with type I IFN before virus exposure. The ability of HIV to modulate the type I IFN-mediated innate immune response when it encounters a cell that has already been exposed to IFN remains poorly defined. The optimal pretreatment time (12 h) and the most potent HIV-inhibitors (e.g., IFN-α2 and -ω) were identified to investigate the ability of HIV to modulate an established type I IFN response. Gene expression at the level of the entire transcriptome was then compared between primary macrophages treated with type I IFNs, as opposed to treated with IFNs and then infected with HIV. Although HIV was not able to establish a robust infection, the virus was able to downregulate a number of IFN-stimulated genes (ISGs) with a fold change greater than 1.5 (i.e., AXL, IFI27, IFI44, IFI44L, ISG15, OAS1, OAS3, and XAF1). The downregulation of OAS1 by the presence of HIV was confirmed by real-time quantitative polymerase chain reaction. In conclusion, even though HIV replication is significantly inhibited by IFN pretreatment, the virus is able to downregulate the transcription of known antiviral ISGs (e.g., IFI44, ISG15, and OAS1).

Building an HIV data mashup using Bio2RDF.

We present an update to the Bio2RDF Linked Data Network, which now comprises ∼30 billion statements across 30 data sets. Significant changes to the framework include the accommodation of global mirrors, offline data processing and new search and integration services. The utility of this new network of knowledge is illustrated through a Bio2RDF-based mashup with microarray gene expression results and interaction data obtained from the HIV-1, Human Protein Interaction Database (HHPID) with respect to the infection of human macrophages with the human immunodeficiency virus type 1 (HIV-1).

Molecular evolution of respiratory syncytial virus fusion gene, Canada, 2006-2010.

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.

Genome sequencing of the lizard parasite Leishmania tarentolae reveals loss of genes associated to the intracellular stage of human pathogenic species.

The Leishmania tarentolae Parrot-TarII strain genome sequence was resolved to an average 16-fold mean coverage by next-generation DNA sequencing technologies. This is the first non-pathogenic to humans kinetoplastid protozoan genome to be described thus providing an opportunity for comparison with the completed genomes of pathogenic Leishmania species. A high synteny was observed between all sequenced Leishmania species. A limited number of chromosomal regions diverged between L. tarentolae and L. infantum, while remaining syntenic to L. major. Globally, >90% of the L. tarentolae gene content was shared with the other Leishmania species. We identified 95 predicted coding sequences unique to L. tarentolae and 250 genes that were absent from L. tarentolae. Interestingly, many of the latter genes were expressed in the intracellular amastigote stage of pathogenic species. In addition, genes coding for products involved in antioxidant defence or participating in vesicular-mediated protein transport were underrepresented in L. tarentolae. In contrast to other Leishmania genomes, two gene families were expanded in L. tarentolae, namely the zinc metallo-peptidase surface glycoprotein GP63 and the promastigote surface antigen PSA31C. Overall, L. tarentolae's gene content appears better adapted to the promastigote insect stage rather than the amastigote mammalian stage.

TRAF6 and IRF7 control HIV replication in macrophages.

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.