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Background Shallow shotgun metagenomics (SSM) has been recently suggested as a promising strategy to study human microbiota, providing nearly identical taxonomic profiles to deep shotgun metagenomics but at a sequencing cost as low as that of metabarcoding. To help clinical researchers determine whether shallow sequencing is appropriate for their projects, it is crucial to ascertain the accuracy of the information it provides, compared to deep sequencing. Here, we design a mapping-based workflow to build taxonomic profiles from SSM data and assess its accuracy at varying sequencing depths at both sample and cohort levels using extensive simulations and several public data sets. Results To identify genuinely present species and spuriously identified ones, we propose a novel data-driven filtering method based on machine learning techniques that largely outperforms basic filtering strategies based on pre defined thresholds, resulting in reliable taxonomic profiles at different sequencing depths, ranging from 50K to 10M reads/samples. Up to 90% of species with relative abundances higher than 4.10−4 were recovered correctly at 500K reads/sample showing that only information about rare taxa is lost at shallow depths. Furthermore, our results clearly show that SSM is able to correctly recover relevant biological signal from the confidently identified taxa, such as differences between groups of patients and diagnosis-like classification. Conclusions This study confirms that SSM is suitable for clinical research on human gut microbiota. We recommend that researchers should consider moving from 16S to SSM to limit biases in taxonomic profiles, or moving from deep to shallow sequencing, when functional analyses are not the main focus, to reduce costs and be able to include more patients in research projects.

Due to the role of macrophages in glomerular inflammation, macrophage surface molecules such as CD163 and CD11b represent attractive biomarkers for monitoring Lupus Nephritis (LN). We hypothesize that their urinary levels may reflect kidney disease activity. Here, we first analyzed the levels of urinary soluble CD163 (U-sCD163) and CD11b (U-sCD11b) in a cohort of 40 patients with LN including 23 with active disease. U-sCD163 levels were significantly elevated in active LN and correlated with the renal activity score, in contrast to U-sCD11b. Then, we developed the pristane induced LN mouse model to analyze, in a longitudinal way, the evolution of U-sCD163 levels according to the glomerular inflammation progression and response to treatment. We showed an increase of U-sCD163 levels associated with glomerular immune-complex deposits on mouse kidney biopsies at an early stage of the disease and a correlation with inflammatory markers including interferon-α, C-reactive protein and tumor necrosis factor-α. In addition, we showed that U-sCD163 levels decreased following efficient hydroxychloroquine treatment. Altogether our results led us to conclude that U-sCD163 represent a non-invasive biomarker for LN reflecting glomerular inflammation. Although prospective study in patients with LN, active or not, are necessary, U-sCD163 could be proposed to monitor response to treatment.

International audience; Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease driven by complex interactions between genetics and environmental factors. SLE is characterised by breaking self-immune tolerance and autoantibody production that triggers inflammation and damage of multiple organs. Given the highly heterogeneous nature of SLE, the treatments currently used are still not satisfactory with considerable side effects, and the development of new therapies is a major health issue for better patient management. In this context, mouse models significantly contribute to our knowledge of the pathogenesis of SLE and are an invaluable tool for testing novel therapeutic targets. Here, we discuss the role of the most used SLE mouse models and their contribution to therapeutic improvement. Considering the complexity of developing targeted therapies for SLE, adjuvant therapies are also increasingly proposed. Indeed, murine and human studies have recently revealed that gut microbiota is a potential target and holds great promises for successful new SLE therapies. However, the mechanisms of gut microbiota dysbiosis in SLE remain unclear to date. In this review, we propose an inventory of existing studies investigating the relationship between gut microbiota dysbiosis and SLE to establish microbiome signature that may serve as a potential biomarker of the disease and its severity as well as a new potential therapy target. This approach may open new possibilities for early diagnosis, prevention and therapeutic perspectives of SLE based on gut microbiome.

Breath testing has become a widely used tool to diagnose small intestinal bacterial overgrowths (SIBO) and intestinal methanogen overgrowths (IMO) in clinical settings. Due to the heterogeneity in clinical manifestations and lack of standardization among centers performing breath testing, SIBO and IMO can be easily overlooked by the clinician.We studied the prevalence and symptoms of SIBO/IMO in French patients referred for breath testing after seeking medical advice.Breath test data and symptoms of 331 patients were assessed for SIBO/IMO using the H2/CH4 lactulose breath test (LBT). Wilcoxon test or χ2 test were used to compare patients with SIBO/IMO to patients without SIBO/IMO. LBT positive patients (H2+, CH4+, and CH4+/H2+) were compared using Kruskal-Wallis test for continuous data or χ2 test for categorical data.Among the 186 (68.1%) patients tested positive for an overgrowth with respectively 40.3%, 47.3%, 12.4% for H2+, CH4+ and CH4+/H2+, presence of diarrhea was significantly increased in hydrogen type overgrowths (p0.001). No significant difference according to age, gender and symptoms was associated with a positive test except for joint pain that was less prevalent among LBT positive patients (p=0.038). In 86.5% of IMOs, positivity with CH4 values ≥10ppm could be identified at baseline.There are little discriminating symptoms that can help the clinician to identify patients likely to have a SIBO/IMO. However, SIBO/IMOs remain a common disorder widely underdiagnosed that need further studies to better apprehend functional bowel disorders.

Background: Microbiotas play critical roles in human health, yet in most cases scientists lack standardized and reproducible methods. To date, stool sample preservation remains a source of technological bias in metagenomic sequencing, despite newly developed storage solutions. Studying those biases will help in identifying the appropriate stool preservation approach to promote the implementation of standard operating procedure and improve comparability across multiple microbiome studies. Results: Here, we conducted a comparative study of 10 storage methods for human stool over a 15-day period of storage at fluctuating temperatures. We first compared the performance of each stabilizer with observed bacterial composition variation within the same specimen. Then, we identified the nature of the observed variations to determine which bacterial populations were more impacted by the stabilizer. We found that DNA stabilizers display various stabilizing efficacies and affect the recovered bacterial profiles. Furthermore, our results showed that the bias associated with the stabilizers can be linked to the phenotypical characteristics of the bacterial populations present in the studied samples. Conclusions: Although newly developed storage solutions have improved our capacity to stabilize stool microbial content over time, they are nevertheless not devoid of biases. We therefore recommend considering the nature of these technological biases before claiming whether some microbes are beneficial or even deleterious to human health.

Background Recent data have suggested that failure to achieve sustained virological response with direct-acting antiviral therapy is usually due to relapse and is primarily associated with the emergence of resistance-associated substitutions. The aim of this study was to investigate the prevalence and characterization of non-structural-5A resistance-associated substitutions in patients infected with HCV genotypes 1, 3 and 4 treated by direct-acting antiviral therapy, including anti-non-structural-5A, and to characterize the pre-existing resistance-associated substitutions in subjects treated with anti-non-structural-5A inhibitors. Methods From January 2014 to March 2016, 2,995 patients infected with HCV genotypes 1, 3 and 4 were exposed to non-structural-5A inhibitors. Sequencing results at the time of virological failure were available for 61 patients; sequencing at baseline was available for 35 of these patients. Results Among the 35 patients with sequencing results available at baseline, 15 had no resistance-associated substitution, 16 had only one resistance-associated substitution, and 4 had more than one resistance-associated substitution. Resistance-associated substitutions were harbored in 57% of the sequences in the non-structural-5A region. Among the 61 patients sequenced at virological failure, 50 (82%) patients presented at least one resistance-associated substitutions inducing a high level of resistance to non-structural-5A inhibitors (>10-fold resistance). Conclusions This pooled analysis suggests that non-structural-5A resistance-associated substitutions screening should be recommended when considering retreatment with a non-structural-5A inhibitor regimen in patients who have previously experienced failed non-structural-5A treatment.

Background & AimLiver fibrosis screening in primary care population is a major public health issue. The FIB-4 index is a simple non-invasive fibrosis test combining age, transaminases, platelets count, developed for the diagnosis of advanced fibrosis. The aim of our study was to evaluate the interest of liver fibrosis screening using systematic calculation of FIB-4 in routine blood analysis.MethodsBetween December 2018 and May 2019, we conducted a prospective screening of liver fibrosis in 134 158 patients during a medical check-up including routine blood analysis. Among these patients, 29 707 had transaminases and platelets counts available and benefited from an automatic calculation of FIB-4. Results were obtained from 21 French clinical laboratories in the Bouches du Rhône region.ResultsAmong the 29 707 patients, 2160 (7.3%) had significant fibrosis (FIB-4>2.67). Individual investigation of patients with FIB-4>2.67 allowed to screen 1267 (1267/2160: 59%) patients who were not managed for any liver disease.ConclusionsThis work demonstrates the interest of FIB-4 for the screening of liver fibrosis in primary care population. Our study strongly supports this easy-to-implement strategy using a simple Fib-4 measure resulting from the use of available routine test results.FundingThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Clinical Registering NumberMR-0314071019 (INDS: French National Institute for Medical Data)

Replication of the hepatitis C virus (HCV) is an error-prone process. This high error rate results in the emergence of viral populations (quasispecies) within hosts and contributes to interhost variability. Numerous studies have demonstrated that both viral and host factors contribute to this viral diversity, which can ultimately affect disease outcome. As the host’s immune response is an important correlate of infection outcome for HCV, many of these viral variations are strongly influenced by T-cell immune pressure and accordingly constitute an efficient strategy to subvert such pressures (viral adaptations). This paper will review the data on viral diversity observed between and within hosts infected with HCV from the acute to the chronic stage of infection and will focus on viral adaptation to the host’s T-cell immune response.

Genetic and cellular studies have shown that the host's innate and adaptive immune responses are an important correlate of viral infection outcome. The features of the host's immune response (host resistance) reflect the coevolution between hosts and pathogens that has occurred over millennia, and that has also resulted in a number of strategies developed by viruses to improve fitness and survival within the host (viral adaptation). In this review, we discuss viral adaptation to host immune pressure via protein-protein interactions and sequence-specific mutations. Specifically, we will present the "state of play" on viral escape mutations to host T-cell responses in the context of the hepatitis C virus, and their influence on infection outcome.