, Les cellules de la muqueuse intestinale
, 2.1.1. Développement et maturation du tractus digestif et fonction de barrière intestinale
, Protection contre la colonisation par des pathogènes
, Maturation et mise en place du système immunitaire
, Les facteurs influençant la composition du microbiote intestinal
, La pratique d'une activité physique
Les processus cellulaires de maintien de l'homéostasie intestinale ,
, Les systèmes de réparation de l'ADN
La réparation par les systèmes BER ,
,
,
, La mort cellulaire par l'apoptose
,
27 II.5.1.1. Principales voies de signalisation impliquées dans la carcinogénèse colorectale, 5.1. Mécanismes moléculaires impliqués dans la carcinogénèse ,
, II.5.1.2. Les différents phénotypes de la carcinogénèse colorectale
, Evènements moléculaires associés aux maladies inflammatoires chroniques de l'intestin et rôle de l'inflammation dans le CCR
, Les maladies inflammatoires chroniques prédisposantes
, Rôle du microbiote intestinal dans la carcinogénèse colorectale, p.41
, 2.1 Les mécanismes d'action mis en jeu par le microbiote intestinal
64 III.4.1. Les marqueurs microbiens : détection et pronostique du CCR, Stratégies diagnostiques et thérapeutiques utilisant ,
, 2.2. L'autophagie médiée par les protéines chaperonnes
, La maturation de l'autophagosome et la fusion de l'autophagosome avec le lysosome
, 2.4. Régulation transcriptionnelle, post-transcriptionnelle et posttraductionnelle, 3.2. Les voies et les facteurs de régulation de l'autophagie
, 3.5.2. Les bactéries qui bloquent et échappent à la machinerie autophagique
,
, IV.5. Implication de l'autophagie dans les cancers
, La modulation de l'autophagie dans les cancers : stratégies thérapeutiques, p.96
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, AIEC infection triggers modification of gut microbiota composition in genetically predisposed mice, contributing to intestinal inflammation
Analysis at the genus level by weighted UniFrac and PCoA did not show any pattern of clustering in any of the 4 mouse groups: eif2ak4 +/+ + LF82, eif2ak4 ?/? + LF82, eif2ak4 +/+ + PBS, eif2ak4 ?/? + PBS at day 1 and 4 post-infection (Fig. S1). In contrast, after 14 and 21 days of infection, a clear pattern of clustering in eif2ak4 ?/? + LF82 group compared to the other groups (eif2ak4 +/+ + LF82, eif2ak4 +/+ + PBS and eif2ak4 ?/? + PBS) was observed (Fig. 3). In detail, at day 14 and 21 post-infection, two dimensional (2D) plotting of PCoA-1 versus PCoA-2 failed to show a pattern of clustering between eif2ak4 +/+ + PBS and eif2ak4 +/+ + LF82 groups (Fig. 3B,F), indicating that colonization by AIEC may not alter microbiota composition in wild type host. In contrast, AIEC LF82 colonization resulted in altered microbiota composition in eif2ak4 ?/? mice at days 14 and 21 post-AIEC administration. 2D plotting of PCoA-1 versus PCoA-2 showed a clear difference in the microbiota composition between eif2ak4 ?/? + PBS and eif2ak4 ?/? + LF82 groups at day 14 (Fig. 3C) and 21 (Fig. 3G) post-infection. Furthermore, 2D plotting of PCoA-1 versus PCoA-2 also showed a difference in the gut microbiota composition between eif2ak4 +/+ and eif2ak4 ?/? mice after 14 (Fig. 3D) or 21 (Fig. 3H) days of AIEC administration. Taxonomic analysis at the genus level showed that most of the differences observed in PCoA were explained by an increase in Turicibacter and Clostridium in eif2ak4 ?/? + LF82 group compared to the other groups at days 14 (Fig. 4A,B) and 21 (Fig. 4C,D) post-infection. These results show that neither Eif2ak4 gene deficiency nor AIEC colonization alone is sufficient to induce a modification in the gut microbiota composition. However, the combination of the genetic and infectious factors leads to a significant shift in the gut microbiota of the mice. Interestingly, this shift occurred at day 14 post-infection before the appearance of inflammation at day 21 post-infection, y microbiota composition analysis. Fecal samples collected over time from eif2ak4 +/+ and eif2ak4 ?/? mice that had been challenged with AIEC LF82 or PBS were subjected to Illumina sequencing of the 16S rRNA genes, vol.8, 2018. ,
These results were consistent with the results obtained with eif2ak4 +/+ and eif2ak4 ?/? mice, indicating that AIEC colonization triggers a chronic inflammation response in a genetically predisposed host deficient in Eif2ak4 gene. Finally, microbiota composition analysis using fecal samples from Tg/eif2ak4 +/+ and Tg/eif2ak4 ?/? mice before any treatment (day 0) by weighted UniFrac and PCoA did not show any pattern of clustering between the two genotypes (Fig. S2), vol.8, 2018. ,
, Taxonomic analyses at the genus level were consistent with those performed with eif2ak4 +/+ and eif2ak4 ?/? mice as most of the differences observed in PCoA were explained by an increase in Turicibacter and Clostridium in Tg/eif2ak4 ?/? + LF82 group compared to the other groups (Fig. 7A-D). Nevertheless, we observed an increase of Escherichia in Tg/eif2ak4 ?/? + LF82 group compared to the other groups at day 21 post-infection (Fig. 7E), and this was not observed for eif2ak4 ?/? + LF82 mice). In addition, we determined AIEC LF82 colonization by quantifying pMT gene expression by qPCR at day 14 and 21 post-infection in both Tg/eif2ak4 ?/? and Tg/eif2ak4 +/+ groups. LF82-specific pMT gene expression level was increased in Tg/eif2ak4 ?/? compared to Tg/eif2ak4 +/+ mice at day 14 and 21 post-infection, although no significant difference was detected at day 1 post-infection (Fig. 7F). In addition, in Tg/eif2ak4 ?/? + LF82 mice, pMT gene expression level was increased at day 21 compared to day 14 post-infection, and this was not observed for Tg/eif2ak4 +/+ mice (Fig. 7F). This suggests that LF82 bacteria can persist in the gastrointestinal tract of Tg/eif2ak4 ?/? mice and expanse their colonization at later time. These results, which were consistent with those obtained with non-transgenic mice, As it was shown for eif2ak4 ?/? mice, AIEC colonization also induced a change in the microbiota composition in Tg/eif2ak4 ?/? mice. These changes were readily apparent by 14 and 21 days post-infection, as 2D plotting of PCoA-1 versus PCoA-2 showed a shift in the gut microbiota composition of Tg/eif2ak4 ?/? mice compared to the other groups (Fig. 6C,G)
, Tg/eif2ak4 +/+ and Tg/eif2ak4 ?/? mice were challenged by oral gavage for 3 days (once per day) with PBS or with 10 9 CFU of the AIEC LF82 strain or the non-pathogenic E. coli K12 MG1655 strain (N = 5 mice per group). (A) The number of AIEC LF82 bacteria was determined in the feces collected every day post-infection by platting on LB media containing selective antibiotics. (B) Fecal lcn-2 levels were measured by ELISA. Means were shown as lines, Colonization of CEABAC10 transgenic (Tg) mice deficient in Eif2ak4 gene with AIEC triggers chronic gut inflammation
Colonization of CEABC10 transgenic (Tg) mice deficient in Eif2ak4 gene with AIEC LF82 results in modification of the gut microbiota composition at days 14 and 21 post-infection. Tg/eif2ak4 +/+ and Tg/eif2ak4 ?/? mice were challenged by oral gavage for 3 days (once per day) with PBS (N = 6 mice per group) or with 10 9 CFU of the AIEC LF82 strain (N = 6 mice per group). Feces were collected at days 14 (A-D) and 21 (E-H) post-infection for the analysis of the bacterial microbiota composition based on Illumina sequencing of the 16S rRNA gene. (A-H) Mouse fecal bacterial communities were clustered using PCoA of the weighted UniFrac distance matrix. PCoA-1 and PCoA-2 were plotted, vol.8, 2018. ,
,
F) Comparison between mouse groups: Tg/eif2ak4 +/+ + PBS and Tg/eif2ak4 +/+ + LF82. (C,G) Comparison between mouse groups: Tg/eif2ak4 ?/? + PBS and Tg/eif2ak4 ?/? + LF82. (D,H) Comparison between mouse groups: Tg/eif2ak4 +/+ + LF82 and Tg/eif2ak4 ?/? + LF82. Materials and Methods Mice. eif2ak4 ?/? mice 51 were kindly provided by ,
Tg/eif2ak4 ?/? mice were administered orally by gavage during three days (once per day) with either 10 9 of ampicillin-erythromycin-resistant AIEC LF82 strain isolated from a CD patient 14 or the rifampicin-resistant non-pathogenic E. coli K12 MG1655 strain. Bacterial persistence in the gut was evaluated every day post-infection. For this, fresh fecal samples (100-200 mg) were homogenized in PBS. After serial dilutions, fecal samples were plated on LB agar plates containing 50 µg/ml ampicillin and 20 µg/ml erythromycin (Euromedex, E002) to isolate LF82 bacteria, or containing 300 µg/ml rifampicin (Euromedex, 1059-B) to isolate E. coli K12 bacteria, and were incubated overnight at 37 °C ,
, Quantification of fecal lipocalin-2. The levels of the inflammatory marker lcn-2 were measured in feces by enzyme-linked immunosorbent assays (ELISA) as previously described 41 . For this, frozen fecal samples were reconstituted in PBS containing 0.1% Tween 20 (Euromedex, 2001-A) and were disrupted to obtain a homogenous fecal suspension. These samples were then centrifuged for 10 minutes at 12,000 rpm at 4 °C. Clear supernatants were collected and stored at ?80 °C until analysis. Lcn-2 levels in the supernatants were measured using a mouse Duoset Lcn-2 ELISA kit
Germany) following manufacturer's instructions. DNA samples were used for 16S rRNA gene sequencing using the Illumina technology as previously described 41 . Briefly, the 16S rRNA gene V4 variable region PCR primers F515/R806 52 with barcode on the forward primer were used in a PCR using the HotStartTaq Plus Master Mix Kit (Qiagen, USA) under the following conditions: 94 °C for 3 minutes, followed by 28 cycles of 94 °C for 30 seconds, 53 °C for 40 seconds and 72 °C for 1 minute, after which a final elongation step at 72 °C for 5 minutes was performed. After amplification, PCR products were checked in 2% agarose gel to determine the success of amplification and the relative intensity of bands. All samples were pooled together in equal proportions based on their molecular weight and DNA concentrations, Microbiota composition analysis by Illumina Sequencing. DNA was extracted from frozen mouse fecal samples using NucleoSpin ® Soil ,
Final OTUs were taxonomically classified using BLASTn against a curated database derived from GreenGenes 53 , RDPII and NCBI, -y (97% similarity), vol.8, 2018. ,
, Each qPCR reaction mixture consisted of iQ SYBR Green Supermix (Biorad), 0.25 µM of each primer and 10 ng of extracted DNA. To detect AIEC LF82, primers binding to the LF82-specific pMT gene (forward 5?-CCATTCATGCAGCAGCTCTTT-3? and reverse 5?-ATCGGACAACATTAGCGGTGT-3?) were used 37 . A region of the 16S rRNA gene of all bacteria was amplified using the universal primers (Forward: 5?-ACTCCTACGGGAGGCAG-3? and reverse 5?-GACTACCAGGGTATCTAATCC-3?) 54 . Amplification programs included an initial denaturation at 95 °C for 10 min followed by 40 cycles consisting of denaturation at 95 °C for 30 sec, Singletons and any OTUs present in all samples <0.1% were removed before further analyses
, Data were normalized to total bacterial. Fold-induction was calculated using the ??Ct method as follows: ??Ct = (Ct pMT ? Ct total bacteria ) group 2 ? (Ct pMT ? Ct total bacteria ) group 1 , and the final data were derived from 2 ???Ct . Ethical statement. Animal protocols were carried out in strict accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals of the Université Clermont-Auvergne
, Statistical analysis was performed using one-way ANOVA test followed by Bonferroni's post-hoc comparisons with GraphPad Prism version 5.01 software (GraphPad Software, Statistical analysis. For bacterial CFUs, lcn-2 levels and relative abundance of bacterial genus data, values were expressed as means ± SEM
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