Non-invasive genomics of respiratory pathogens infecting wild great apes using hybridisation capture.

Human respiratory pathogens have repeatedly caused lethal outbreaks in wild great apes across Africa, leading to population declines. Nonetheless, our knowledge of potential genomic changes associated with pathogen introduction and spread at the human-great ape interface remains sparse. Here, we made use of target enrichment coupled with next generation sequencing to non-invasively investigate five outbreaks of human-introduced respiratory disease in wild chimpanzees living in Taï National Park, Ivory Coast. By retrieving 34 complete viral genomes and three distinct constellations of pneumococcal virulence factors, we provide genomic insights into these spillover events and describe a framework for non-invasive genomic surveillance in wildlife.

Yaws Disease Caused by Treponema pallidum subspecies pertenue in Wild Chimpanzee, Guinea, 2019.

Yaws-like lesions are widely reported in wild African great apes, yet the causative agent has not been confirmed in affected animals. We describe yaws-like lesions in a wild chimpanzee in Guinea for which we demonstrate infection with Treponema pallidum subsp. pertenue. Assessing the conservation implications of this pathogen requires further research.

Monkeypox virus emergence in wild chimpanzees reveals distinct clinical outcomes and viral diversity.

Monkeypox is a viral zoonotic disease on the rise across endemic habitats. Despite the growing importance of monkeypox virus, our knowledge on its host spectrum and sylvatic maintenance is limited. Here, we describe the recent repeated emergence of monkeypox virus in a wild, human-habituated western chimpanzee (Pan troglodytes verus, hereafter chimpanzee) population from Taï National Park, Ivory Coast. Through daily monitoring, we show that further to causing its typical exanthematous syndrome, monkeypox can present itself as a severe respiratory disease without a diffuse rash. By analysing 949 non-invasively collected samples, we identify the circulation of at least two distinct monkeypox virus lineages and document the shedding of infectious particles in faeces and flies, suggesting that they could mediate indirect transmission. We also show that the carnivorous component of the Taï chimpanzees' diet, mainly consisting of the sympatric monkeys they regularly hunt, did not change nor shift towards rodent consumption (the presumed reservoir) before the outbreaks, suggesting that the sudden emergence of monkeypox virus in this population is probably due to changes in the ecology of the virus itself. Using long-term mortality surveillance data from Taï National Park, we provide evidence of little to no prior viral activity over at least two decades. We conclude that great ape sentinel systems devoted to the longitudinal collection of behavioural and health data can help clarify the epidemiology and clinical presentation of zoonotic pathogens.

Novel DNA Methylation Sites Influence GPR15 Expression in Relation to Smoking.

Smoking is a major risk factor for cardiovascular diseases and has been implicated in the regulation of the G protein-coupled receptor 15 (GPR15) by affecting CpG methylation. The G protein-coupled receptor 15 is involved in angiogenesis and inflammation. An effect on GPR15 gene regulation has been shown for the CpG site CpG3.98251294. We aimed to analyze the effect of smoking on GPR15 expression and methylation sites spanning the GPR15 locus. DNA methylation of nine GPR15 CpG sites was measured in leukocytes from 1291 population-based individuals using the EpiTYPER. Monocytic GPR15 expression was measured by qPCR at baseline and five-years follow up. GPR15 gene expression was upregulated in smokers (beta (ß) = -2.699, p-value (p) = 1.02 × 10-77) and strongly correlated with smoking exposure (ß = -0.063, p = 2.95 × 10-34). Smoking cessation within five years reduced GPR15 expression about 19% (p = 9.65 × 10-5) with decreasing GPR15 expression over time (ß = 0.031, p = 3.81 × 10-6). Additionally, three novel CpG sites within GPR15 affected by smoking were identified. For CpG3.98251047, DNA methylation increased steadily after smoking cessation (ß = 0.123, p = 1.67 × 10-3) and strongly correlated with changes in GPR15 expression (ß = 0.036, p = 4.86 × 10-5). Three novel GPR15 CpG sites were identified in relation to smoking and GPR15 expression. Our results provide novel insights in the regulation of GPR15, which possibly linked smoking to inflammation and disease progression.

Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data.

Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data.