Project description:Pancreatic cancer is the 3rd most prevalent cause of cancer related deaths in United states alone, with over 55000 patients being diagnosed in 2019 alone and nearly as many succumbing to it. Late detection, lack of effective therapy and poor understanding of pancreatic cancer systemically contributes to its poor survival statistics. Obesity and high caloric intake linked co-morbidities like type 2 diabetes (T2D) have been attributed as being risk factors for a number of cancers including pancreatic cancer. Studies on gut microbiome has shown that lifestyle factors as well as diet has a huge effect on the microbial flora of the gut. Further, modulation of gut microbiome has been seen to contribute to effects of intensive insulin therapy in mice on high fat diet. In another study, abnormal gut microbiota was reported to contribute to development of diabetes in Db/Db mice. Recent studies indicate that microbiome and microbial dysbiosis plays a role in not only the onset of disease but also in its outcome. In colorectal cancer, Fusobacterium has been reported to promote therapy resistance. Certain intra-tumoral bacteria have also been shown to elicit chemo-resistance by metabolizing anti-cancerous agents. In pancreatic cancer, studies on altered gut microbiome have been relatively recent. Microbial dysbiosis has been observed to be associated with pancreatic tumor progression. Modulation of microbiome has been shown to affect response to anti-PD1 therapy in this disease as well. However, most of the studies in pancreatic cancer and microbiome have remained focused om immune modulation. In the current study, we observed that in a T2D mouse model, the microbiome changed significantly as the hyperglycemia developed in these animals. Our results further showed that, tumors implanted in the T2D mice responded poorly to Gemcitabine/Paclitaxel (Gem/Pac) standard of care compared to those in the control group. A metabolomic reconstruction of the WGS of the gut microbiota further revealed that an enrichment of bacterial population involved in drug metabolism in the T2D group.
Project description:Aging is associated with declining immunity and inflammation as well as alterations in the gut microbiome with a decrease of beneficial microbes and increase in pathogenic ones. The aim of this study was to investigate aging associated gut microbiome in relation to immunologic and metabolic profile in a non-human primate (NHP) model. 12 old (age>18 years) and 4 young (age 3-6 years) Rhesus macaques were included in this study. Immune cell subsets were characterized in PBMC by flow cytometry and plasma cytokines levels were determined by bead based multiplex cytokine analysis. Stool samples were collected by ileal loop and investigated for microbiome analysis by shotgun metagenomics. Serum, gut microbial lysate and microbe-free fecal extract were subjected to metabolomic analysis by mass-spectrometry. Our results showed that the old animals exhibited higher inflammatory biomarkers in plasma and lower CD4 T cells with altered distribution of naïve and memory T cell maturation subsets. The gut microbiome in old animals had higher abundance of Archaeal and Proteobacterial species and lower Firmicutes than the young. Significant enrichment of metabolites that contribute to inflammatory and cytotoxic pathways was observed in serum and feces of old animals compared to the young. We conclude that aging NHP undergo immunosenescence and age associated alterations in the gut microbiome that has a distinct metabolic profile.
Project description:We used a DNA microarray chip covering 369 resistance types to investigate the relation of antibiotic resistance gene diversity with humans’ age. Metagenomic DNA from fecal samples of 123 healthy volunteers of four different age groups, i.e. pre-school Children (CH), School Children (SC), High School Students (HSS) and Adults (AD) were used for hybridization. The results showed that 80 different gene types were recovered from the 123 individuals gut microbiota, among which 25 were present in CH, 37 in SC, 58 in HSS and 72 in AD. Further analysis indicated that antibiotic resistance genes in groups of CH, SC and AD can be independently clustered, and those ones in group HSS are more divergent. The detailed analysis of antibiotic resistance genes in human gut is further described in the paper DNA microarray analysis reveals the antibiotic resistance gene diversity in human gut microbiota is age-related submitted to Sentific Reports
Project description:HuMiChip was used to analyze human oral and gut microbiomes, showing significantly different functional gene profiles between oral and gut microbiome. The results were used to demonstarte the usefulness of applying HuMiChip to human microbiome studies.
Project description:This study demonstrates the usefulness of the API by generating a baseline gut microbiota profile of a healthy population and estimating reference intervals for the functional abundance of manually selected KEGG pathways. API facilitates microbiome research by providing dynamic and customizable tools for estimating reference intervals for gut microbiota functional abundances. Through the API, researchers can rapidly generate gut microbiota functional profiles of healthy populations to use as a baseline for comparison. The API also allows users to manually select specific KEGG pathways and estimate reference intervals for the functional abundance of those pathways. By generating these customized reference intervals, researchers can better understand the expected range of gut microbiota functions in healthy individuals. API enables microbiome studies to go beyond simple taxonomic profiling and delve deeper into the functional potential of gut microbiome communities. In summary, API represents a valuable tool for microbiome researchers that enhances the ability to elucidate connections between gut microbial functions and human health.
Project description:Age-dependent changes of the gut-associated microbiome have been linked to increased frailty and systemic inflammation. This study found that age-associated changes of the gut microbiome of BALB/c and C57BL/6 mice could be reverted by co-housing of aged (22 months old) and adult (3 months old) mice for 30-40 days or faecal microbiota transplantation (FMT) from adult into aged mice. This was demonstrated using high-throughput sequencing of the V3-V4 hypervariable region of bacterial 16S rRNA gene isolated from faecal pellets collected from 3-4 months old adult and 22-23 months old aged mice before and after co-housing or FMT.
Project description:We used a DNA microarray chip covering 369 resistance types to investigate the relation of antibiotic resistance gene diversity with humansM-bM-^@M-^Y age. Metagenomic DNA from fecal samples of 123 healthy volunteers of four different age groups, i.e. pre-school Children (CH), School Children (SC), High School Students (HSS) and Adults (AD) were used for hybridization. The results showed that 80 different gene types were recovered from the 123 individuals gut microbiota, among which 25 were present in CH, 37 in SC, 58 in HSS and 72 in AD. Further analysis indicated that antibiotic resistance genes in groups of CH, SC and AD can be independently clustered, and those ones in group HSS are more divergent. The detailed analysis of antibiotic resistance genes in human gut is further described in the paper DNA microarray analysis reveals the antibiotic resistance gene diversity in human gut microbiota is age-related submitted to Sentific Reports The antibiotic resistance gene microarray is custom-designed (Roche NimbleGen), based on a single chip containing 3 internal replicated probe sets of 12 probes per resistance gene, covering the whole 315K 12-plex platform spots.
Project description:Cocaine use disorder represents a public health crisis with no FDA-approved medications for its treatment. A growing body of research has detailed the important connections between the brain and the resident population of bacteria in the gut, the gut microbiome in psychiatric disease models. Acute depletion of gut bacteria results in enhanced reward in a mouse cocaine place preference model, and repletion of bacterially-derived short-chain fatty acid (SCFA) metabolites reverses this effect. However, the role of the gut microbiome and its metabolites in modulating cocaine-seeking behavior after prolonged abstinence is unknown. Given that relapse prevention is the most clinically challenging issue in treating substance use disorders, studies examining the effects of microbiome manipulations in relapse-relevant models are critical. Here, Sprague-Dawley rats received either untreated water or antibiotics to deplete the gut microbiome and its metabolites. Rats were trained to self-administer cocaine and subjected to either within-session threshold testing to evaluate motivation for cocaine or 21 days of abstinence followed by a cue-induced cocaine-seeking task to model relapse behavior. Microbiome depletion did not affect cocaine acquisition on an FR1 schedule. However, microbiome-depleted subjects exhibited significantly enhanced motivation for low dose cocaine on a within-session threshold task. Similarly, microbiome depletion increased cue-induced cocaine-seeking following prolonged abstinence. In the absence of a normal microbiome, repletion of bacterially-derived SCFA metabolites reversed the behavioral and transcriptional changes associated with microbiome depletion. These findings suggest that gut bacteria, via their metabolites, are key regulators of drug-seeking behaviors, positioning the microbiome as a potential translational research target.
Project description:Pancreatic cancer is among the deadliest cancers that affects almost 54,000 patients in United States alone, with 90% of them succumbing to the disease. Lack of early detection is considered to be the foremost reason for such dismal survival rates. Our study shows that resident gut microbiota is altered at the early stages of tumorigenesis much before development of observable tumors in a spontaneous, genetically engineered mouse model for pancreatic cancer. In the current study, we analyzed the microbiome of in a genetic mouse model for PDAC (KRASG12DTP53R172HPdxCre or KPC) and age-matched controls using WGS at very early time points of tumorigenesis. During these time points, the KPC mice do not show any detectable tumors in their pancreas. Our results show that at these early time points, the histological changes in the pancreas correspond to a significant change in certain gut microbial population. Our predictive metabolomic analysis on the identified bacterial species reveal that the primary microbial metabolites involved in progression and development of PDAC tumors are involved in polyamine metabolism.