Biology subjects

Tanes, C.

Publications and source records attributed to Tanes, C..

5 recordsLinked to original sources

bioRxiv2025

Colibactin-producing E. coli promote carcinogenesis of gastroesophageal adenocarcinoma and simultaneously induce autophagy and differentiation

Background & AimsGastroesophageal adenocarcinoma (GEAC) is a malignancy of the gastroesophageal junction (GEJ) and is associated with reflux of gastroduodenal contents and Barretts Esophagus (BE). A shift towards gram-negative bacteria in the microbiota of the GEJ additionally promotes inflammation and likely carcinogenesis. Enterobacteriaceae are enriched in advanced stages of GEAC development, and members of this family can produce colibactin, a genotoxin implicated in DNA damage and tumor progression. We aimed to validate these observations and investigate the effect of E. coli with or without colibactin production on GEAC-carcinogenesis. MethodsBacteria were profiled in human biopsies with imaging and 16S rRNA gene sequencing. Organoids of our L2-IL1B mouse model of GEAC were exposed to E. coli with colibactin (CoPEC) and without colibactin production (noCoPEC) via organoid microinjection. The phenotypic and transcriptomic changes in the organoids after the coculture with E. coli were evaluated via histology and single-cell RNA sequencing. ResultsIn human specimens, we observed an infiltration of bacteria in GEJ-tissue upon tumor formation and detected Enterobacteriaceae in one third of BE-patients. CoPEC-injected organoids exhibited high rates of proliferation and DNA damage, and an upregulation of cancer-associated genes and pathways. Furthermore, genes and pathways associated with immune activation, defense mechanisms, metabolic reprogramming, autophagy and differentiation were upregulated in CoPEC-injected organoids. ConclusionIn addition to the enrichment of Enterobacteriaceae in the GEJ-tissue of patients at late stages of GEAC, we show that the exposure of colibactin-producing E. coli to murine BE-organoids promotes genetic instability and proliferation, and the activation of cancer-associated pathways, while also activating autophagy and enhancing intercellular homeostasis. This indicates that colibactin-producing E. coli have a dual effect on early stages of GEAC-carcinogenesis. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/687579v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1281a14org.highwire.dtl.DTLVardef@1c83c91org.highwire.dtl.DTLVardef@10088d2org.highwire.dtl.DTLVardef@1698a2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Concomitant suppression of COX-1 and COX-2 is insufficient to induce enteropathy associated with chronic NSAID use

Nonsteroidal anti-inflammatory drugs (NSAIDs) are the most widely used medications for the management of chronic pain; however, they are associated with numerous gastrointestinal (GI) adverse events. Although many mechanisms have been suggested, NSAID-induced enteropathy has been thought to be primarily due to inhibition of both cyclooxygenases (COX) -1 and -2, which results in suppression of prostaglandin synthesis. Yet surprisingly, we found that concomitant postnatal deletion of Cox-1 and -2 over 10 months failed to cause intestinal injury in mice unless they were treated with naproxen or its structural analog, phenylpropionic acid, which is not a COX inhibitor. Cox double knockout mice exhibit a distinct gut microbiome composition and cohousing them with controls rescues their dysbiosis and delays the onset of NSAID-induced GI bleeding. In both the UK Biobank and All of Us human cohorts, coadministration of antibiotics with NSAIDs is associated with an increased frequency of GI bleeding. These results show that prostaglandin suppression plays a trivial role in NSAID-induced enteropathy. However, Cox deletion causes dysbiosis of the gut microbiome that amplifies the enteropathic response to NSAIDs.

pharmacology and toxicology↗

bioRxiv2023

Interactions between the gut microbiome, dietary restriction, and aging in genetically diverse mice

The intestinal microbiome changes with age, but the causes and consequences of microbiome aging remain unclear. Furthermore, the gut microbiome has been proposed to mediate the benefit of lifespan- extending interventions such as dietary restriction, but this hypothesis warrants further exploration. Here, by analyzing 2997 metagenomes collected longitudinally from 913 deeply phenotyped, genetically diverse mice, we provide new insights into the interplay between the microbiome, aging, dietary restriction, host genetics, and a wide range of health parameters. First, we find that microbiome uniqueness increases with age across datasets and species. Moreover, age-associated changes are better explained by cumulative exposure to stochastic events (neutral theory) than by the influence of an aging host (selection theory). Second, we unexpectedly find that the majority of microbiome features are significantly heritable and that the amount of variation explained by host genetics is as large as that of aging and dietary restriction. Third, we find that the intensity of dietary restriction parallels the extent of microbiome changes and that dietary restriction does not rejuvenate the microbiome. Lastly, we find that the microbiome is significantly associated with multiple health parameters -- including body composition, immune parameters, and frailty -- but not with lifespan. In summary, this large and multifaceted study sheds light on the factors influencing the microbiome and aspects of host physiology modulated by the microbiome.

microbiology↗

bioRxiv2023

Colonization and Dissemination of Klebsiella pneumoniae is Dependent on Dietary Carbohydrates

Dysbiosis of the gut microbiota is increasingly appreciated as both a consequence and precipitant of human disease. The outgrowth of the bacterial family Enterobacteriaceae is a common feature of dysbiosis, including the human pathogen Klebsiella pneumoniae. Dietary interventions have proven efficacious in the resolution of dysbiosis, though the specific dietary components involved remain poorly defined. Based on a previous human diet study, we hypothesized that dietary nutrients serve as a key resource for the growth of bacteria found in dysbiosis. Through human sample testing, and ex-vivo, and in vivo modeling, we find that nitrogen is not a limiting resource for the growth of Enterobacteriaceae in the gut, contrary to previous studies. Instead, we identify dietary simple carbohydrates as critical in colonization of K. pneumoniae. We additionally find that dietary fiber is necessary for colonization resistance against K. pneumoniae, mediated by recovery of the commensal microbiota, and protecting the host against dissemination from the gut microbiota during colitis. Targeted dietary therapies based on these findings may offer a therapeutic strategy in susceptible patients with dysbiosis.

microbiology↗

bioRxiv2023

A quantitative approach to measure and predict microbiome response to antibiotics

BackgroundAlthough antibiotics induce sizable perturbations in the human microbiome, we lack a systematic and quantitative method to measure and predict the microbiomes response to specific antibiotics. Here, we introduce such a method, which takes the form of a Microbiome Response Index (MiRIx) for each antibiotic. Antibiotic-specific MiRIx values quantify the overall susceptibility of the microbiota to an antibiotic, based on databases of bacterial phenotypes and published data on intrinsic antibiotic susceptibility. ResultsWe applied our approach to five published microbiome studies that carried out antibiotic interventions with vancomycin, metronidazole, ciprofloxacin, amoxicillin, and doxycycline. We show how MiRIx can be used in conjunction with existing microbiome analytical approaches to gain a deeper understanding of the microbiome response to antibiotics. Finally, we generate antibiotic response predictions for the oral, skin, and gut microbiome in healthy humans. ConclusionsOur approach is implemented as open-source software and is readily applied to microbiome data sets generated by 16S rRNA marker gene sequencing or shotgun metagenomics.

bioinformatics↗