Développement de nouvelles stratégies de prévention et de résistance aux infections opportunistes chez l'Omble de fontaine (Salvelinus fontinalis)

Les bactéries peuvent exploiter quasiment toutes les niches écologiques, dont les organismes multicellulaires. Les relations hôte-bactéries se classent sur une grande gamme d’interactions allant du mutualisme au parasitisme. Dans ce contexte, l’objectif théorique de mon doctorat est d’étudier les relations complexes existant entre un poisson, l’Omble de fontaine, et le cortège microbien qui l’accompagne. Cette espèce est la cible d’infections opportunistes par des bactéries pathogènes du genre Flavobacterium. L’objectif appliqué visait à développer une approche alternative aux antibiotiques pour prévenir et traiter les infections opportunistes. Le premier résultat du projet a mis en lumière qu’un stress hypoxique entraînait une diminution des bactéries à potentiel bénéfique provoquant une dysbiose, favorisant à son tour l’infection par les pathogènes. Nous avons donc ensuite isolé des bactéries issues du microbiome pour tester leurs effets antagonistes vis-à-vis des pathogènes F. columnare et F. psychophilum. Nous avons pu ainsi découvrir sept candidats potentiels in vitro et tester un candidat qui s’est montré efficace par compétition par interférence dans le traitement de la maladie de l’eau froide in vivo. Le dernier objectif de cette thèse consistait à tester la présence de régions géniques chez l’hôte permettant le recrutement des bactéries bénéfiques dans le microbiome. Nous avons donc analysé le microbiome cutané de 86 individus d’une famille d’hybrides de deuxième génération. Nous avons observé une forte variabilité interindividuelle et déterminé trois régions géniques impliquées dans la modulation de trois taxons bactériens dont Methylobacterium, qui est primordial dans le maintien de l’homéostasie du microbiome. Tous nos résultats appuient le rôle du microbionte cutané dans la protection contre les infections opportunistes.Bacteria can colonize every ecological niche including multicellular organisms, due to their fast growth and their biochemical abilities, . Host-bacteria relationships are complex and range from parasitism to mutualism. Under this framework, my theoretical objective is to study the relationship complexity between brook charr and its microbial partners. This fish species is targeted by opportunistic infections from bacterial pathogens belonging to the Flavobacterium genus. My applied objective focuse on the development of alternative strategies to prevent and treat these infections without antibiotics. The first result of this project highlight that hypoxic stress induce a diminution of the potentially beneficial bacteria leading to a dysbiosis, which in turn triggers opportunistic infections. Then, we isolated bacteria from the microbiome to test their antagonistic effects on two pathogens Flavobacterium columnare and F. psychrophilum. We identify seven potential candidates in vitro, one tested in vivo and being effective to prevent cold-water disease via interference competition. The last objective is to test the existence of host genetic regions associated with the recruitment capacity of beneficial genera in the microbiome. To this end, we analyze the skin microbiome of 86 progenies issued from a dihybrid cross. A strong inter-individual variability is observed and we identify three genetic regions involved in the recruitment of three bacterial genera including Methylobacterium, which is very important to maintain microbiome homeostasis. Overall, the results demonstrate the role of skin microbiota in brook charr resistance against opportunistic infections

High order numerical schemes for transport equations on bounded domains

This article is an account of the NABUCO project achieved during the summer camp CEMRACS 2019 devoted to geophysical fluids and gravity flows. The goal is to construct finite difference approximations of the transport equation with nonzero incoming boundary data that achieve the best possible convergence rate in the maximum norm. We construct, implement and analyze the so-called inverse Lax-Wendroff procedure at the incoming boundary. Optimal convergence rates are obtained by combining sharp stability estimates for extrapolation boundary conditions with numerical boundary layer expansions. We illustrate the results with the Lax-Wendroff and O3 schemes

Dental Biofilm and Saliva Microbiome and Its Interplay with Pediatric Allergies

Little is known about the interplay and contribution of oral microorganisms to allergic diseases, especially in children. The aim of the clinical study was to associate saliva and dental biofilm microbiome with allergic disease, in particular with allergic asthma. In a single-center study, allergic/asthmatic children (n = 15; AA-Chd; age 10.7 ± 2.9), atopic/allergic children (n = 16; AT/AL-Chd; 11.3 ± 2.9), and healthy controls (n = 15; CON-Chd; age 9.9 ± 2.2) were recruited. After removing adhering biofilms from teeth and collecting saliva, microbiome was analyzed by using a 16s-rRNA gene-based next-generation sequencing in these two mediums. Microbiome structure differed significantly between saliva and dental biofilms (β-diversity). Within the groups, the dental biofilm microbiome of AA-Chd and AT/AL-Chd showed a similar microbial fingerprint characterized by only a small number of taxa that were enriched or depleted (4) compared to the CON-Chd, while both diseased groups showed a stronger microbial shift compared to CON-Chd, revealing 14 taxa in AA-Chd and 15 taxa in AT/AL-Chd that were different. This could be the first note to the contribution of dental biofilm and its metabolic activity to allergic health or disease

Staphylococcus massiliensis isolated from human blood cultures, Germany, 2017-2020

Clinical and laboratory data on newly described staphylococcal species is rare, which hampers decision-making when such pathogens are detected in clinical specimens. Here, we describe Staphylococcus massiliensis detected in three patients at a university hospital in southwest Germany. We report the discrepancy of microbiological fndings between matrix-assisted laser desorption/ionization time-of-fight mass spectrometry, 16S-rRNA polymerase chain reaction, and whole-genome sequencing for all three isolates. Our fndings highlight the diagnostic pitfalls pertinent to novel and non-model organisms in daily microbiological practice, in whom the correct identifcation is dependent on database accuracy

Postoperative complications are associated with long-term changes in the gut microbiota following colorectal cancer surgery

Changes in the gut microbiome have already been associated with postoperative complications in major abdominal surgery. However, it is still unclear whether these changes are transient or a long-lasting effect. Therefore, the aim of this prospective clinical pilot study was to examine long-term changes in the gut microbiota and to correlate these changes with the clinical course of the patient. Methods: In total, stool samples of 62 newly diagnosed colorectal cancer patients undergoing primary tumor resection were analyzed by 16S-rDNA next-generation sequencing. Stool samples were collected preoperatively in order to determine the gut microbiome at baseline as well as at 6, 12, and 24 months thereafter to observe longitudinal changes. Postoperatively, the study patients were separated into two groups-patients who suffered from postoperative complications

Gut microbiome patterns correlate with higher postoperative complication rates after pancreatic surgery

Abstract Background Postoperative complications are of great relevance in daily clinical practice, and the gut microbiome might play an important role by preventing pathogens from crossing the intestinal barrier. The two aims of this prospective clinical pilot study were: (1) to examine changes in the gut microbiome following pancreatic surgery, and (2) to correlate these changes with the postoperative course of the patient. Results In total, 116 stool samples of 32 patients undergoing pancreatic surgery were analysed by 16S-rRNA gene next-generation sequencing. One sample per patient was collected preoperatively in order to determine the baseline gut microbiome without exposure to surgical stress and/or antibiotic use. At least two further samples were obtained within the first 10 days following the surgical procedure to observe longitudinal changes in the gut microbiome. Whenever complications occurred, further samples were examined. Based on the structure of the gut microbiome, the samples could be allocated into three different microbial communities (A, B and C). Community B showed an increase in Akkermansia, Enterobacteriaceae and Bacteroidales as well as a decrease in Lachnospiraceae, Prevotella and Bacteroides. Patients showing a microbial composition resembling community B at least once during the observation period were found to have a significantly higher risk for developing postoperative complications (B vs. A, odds ratio = 4.96, p < 0.01**; B vs. C, odds ratio = 2.89, p = 0.019*). Conclusions The structure of the gut microbiome is associated with the development of postoperative complications

Satellite and in situ sampling mismatches: Consequences for the estimation of satellite sea surface salinity uncertainties

Validation of satellite sea surface salinity (SSS) products is typically based on comparisons with in-situ measurements at a few meters’ depth, which are mostly done at a single location and time. The difference in term of spatio-temporal resolution between the in-situ near-surface salinity and the two-dimensional satellite SSS results in a sampling mismatch uncertainty. The Climate Change Initiative (CCI) project has merged SSS from three satellite missions. Using an optimal interpolation, weekly and monthly SSS and their uncertainties are estimated at a 50 km spatial resolution over the global ocean. Over the 2016–2018 period, the mean uncertainty on weekly CCI SSS is 0.13, whereas the standard deviation of weekly CCI minus in-situ Argo salinities is 0.24. Using SSS from a high-resolution model reanalysis, we estimate the expected uncertainty due to the CCI versus Argo sampling mismatch. Most of the largest spatial variability of the satellite minus Argo salinity is observed in regions with large estimated sampling mismatch. A quantitative validation is performed by considering the statistical distribution of the CCI minus Argo salinity normalized by the sampling and retrieval uncertainties. This quantity should follow a Gaussian distribution with a standard deviation of 1, if all uncertainty contributions are properly taken into account. We find that (1) the observed differences between Argo and CCI data in dynamical regions (river plumes, fronts) are mainly due to the sampling mismatch; (2) overall, the uncertainties are well estimated in CCI version 3, much improved compared to CCI version 2. There are a few dynamical regions where discrepancies remain and where the satellite SSS, their associated uncertainties and the sampling mismatch estimates should be further validated