Maternal immune factors involved in the prevention or facilitation of neonatal bacterial infections.

Newborns, whether born prematurely or at term, have a fully formed but naive immune system that must adapt to the extra-uterine environment to prevent infections. Maternal immunity, transmitted through the placenta and breast milk, protects newborns against infections, primarily via immunoglobulins (IgG and IgA) and certain maternal immune cells also known as microchimeric cells. Recently, it also appeared that the maternal gut microbiota played a vital role in neonatal immune maturation via microbial compounds impacting immune development and the establishment of immune tolerance. In this context, maternal vaccination is a powerful tool to enhance even more maternal and neonatal health. It involves the transfer of vaccine-induced antibodies to protect both mother and child from infectious diseases. In this work we review the state of the art on maternal immune factors involved in the prevention of neonatal bacterial infections, with particular emphasis on the role of maternal vaccination in protecting neonates against bacterial disease.

Gut microbiota in SLE: from animal models to clinical evidence and pharmacological perspectives.

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.

Gut microbiota in systemic lupus erythematosus patients and lupus mouse model: a cross species comparative analysis for biomarker discovery.

An increasing number of studies have provided strong evidence that gut microbiota interact with the immune system and stimulate various mechanisms involved in the pathogenesis of auto-immune diseases such as Systemic Lupus Erythematosus (SLE). Indeed, gut microbiota could be a source of diagnostic and prognostic biomarkers but also hold the promise to discover novel therapeutic strategies. Thus far, specific SLE microbial signatures have not yet been clearly identified with alteration patterns that may vary between human and animal studies. In this study, a comparative analysis of a clinically well-characterized cohort of adult patients with SLE showed reduced biodiversity, a lower Firmicutes/Bacteroidetes (F/B) ratio, and six differentially abundant taxa compared with healthy controls. An unsupervised clustering of patients with SLE patients identified a subgroup of patients with a stronger alteration of their gut microbiota. Interestingly, this clustering was strongly correlated with the disease activity assessed with the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score (p = 0.03, odd ratio = 15) and the identification of specific alterations involving the F/B ratio and some different taxa. Then, the gut microbiota of pristane-induced lupus and control mice were analyzed for comparison with our human data. Among the six differentially abundant taxa of the human disease signature, five were common with our murine model. Finally, an exhaustive cross-species comparison between our data and previous human and murine SLE studies revealed a core-set of gut microbiome species that might constitute biomarker panels relevant for future validation studies.

Human Stool Preservation Impacts Taxonomic Profiles in 16S Metagenomics Studies.

Microbiotas play critical roles in human health, yet in most cases scientists lack standardized and reproducible methods from collection and preservation of samples, as well as the choice of omic analysis, up to the data processing. To date, stool sample preservation remains a source of technological bias in metagenomic sequencing, despite newly developed storage solutions. Here, we conducted a comparative study of 10 storage methods for human stool over a 14-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 thus highlighting that some solutions are more performant in preserving the true gut microbial community. Furthermore, our results showed that the bias associated with the stabilizers can be linked to the phenotypical traits of the bacterial populations present in the studied samples. Although newly developed storage solutions have improved our capacity to stabilize stool microbial content over time, they are nevertheless not devoid of biases hence requiring the implantation of standard operating procedures. Acknowledging the biases and limitations of the implemented method is key to better interpret and support true associated microbiome patterns that will then lead us towards personalized medicine, in which the microbiota profile could constitute a reliable tool for clinical practice.