Recipient Organization
PURDUE UNIVERSITY
(N/A)
WEST LAFAYETTE,IN 47907
Performing Department
Nutrition Science
Non Technical Summary
In the United States, colon cancer (CC) is the third most common cancer and the third leading cause of cancer death, and studies have established a positive association between obesity and CC risk. Given that approximately 40% of adults in the United States are obese, this association represents a significant public health issue. While the number of new CC cases and the CC mortality rate have been steadily declining for the past 20 years (largely due to the increased use of screening tests for adenomatous polyps in the colon), this trend could be reversed with the continuous rise in obesity rate. The incidence of early onset CC, defined as CC diagnosed prior to 50 years of age, has actually been increasing by approximately 2% each year since 1994. While epidemiologists are still working to define the common risk factors linking these patients, obesity and dietary factors appear to be playing an important role. Consequently, there is an urgent need for the development of evidence-based CC preventive nutritional guidance and dietary interventions for obese individuals, which will require greater understanding of the mechanisms mediating the obesity-CC link. There are currently no targeted CC preventive interventions for the obese population or biomarkers to assist in identifying which individuals within this population are at particularly high risk of CC development.The proposed study will examine the role of gut bacteria and colon inflammation in the obesity-CC link. Our focus on these factors is justified by findings from several previous studies. Researchers have shown that transplants of fecal material from non-obese mice fed a high-fat diet promote greater small intestine tumor growth in comparison to feces from low-fat diet-fed mice. This indicates that a high-fat diet induces changes in the gut bacteria that stimulate intestinal tumor development, though the independent effects of obesity-induced changes in the gut bacteria on CC growth remain unknown. Obesity is known to promote pro-inflammatory changes in the colon, and colon inflammation has been strongly linked to increased CC risk. Given that the development and function of the intestinal immune system is dependent on the presence of gut bacteria, it seems very likely that these bacteria play a role in mediating obesity's effects on colon inflammation and the subsequent promotion of CC. Our proposed studies will use mouse models to determine: 1) How obesity alone (independent of obesity-associated dietary factors) and obesity-associated dietary factors (independent of obesity) affect the composition and function of the gut bacteria as well as colon inflammation; 2) The independent effects of the obesity or diet-induced changes in gut bacteria on colon tumor growth and colon inflammation using fecal transplants. Statistical analyses will allow us to correlate specific bacteria and their metabolites with the colon inflammation and tumor outcomes to develop mechanistic hypotheses for future studies.In the immediate future, we will use this information, as well as the published literature on how various prebiotics affect the gut microbiota, to determine which prebiotic(s) to test for colon cancer preventive activity in the obese setting in our next preclinical study.Thus, data from this project will lay the foundation for a research program thataims to define the precise mechanisms by which obesity-induced shifts in gut bacteria and related changes in colon inflammation contribute to colon carcinogenesis. The ultimate goal of this research is to significantly reduce the incidence of obesity-associated CC by applying our data to developevidence-basedpreventivenutritional guidanceand prebiotic interventions, as well asscreening tools for the identification of particularly high-risk patients.The development of theseCC preventive interventionshas the potential to impact the health of millions of obese individuals.
Animal Health Component
(N/A)
Research Effort Categories
Basic
100%
Applied
(N/A)
Developmental
(N/A)
Goals / Objectives
The overarching goal of this project isto determine the independent effect of obesity-induced gut microbial dysbiosis on tumor growth in a mouse model of colon cancer. We hypothesize that obesity-induced gut microbial dysbiosis, independent of dietary factors, promotes colon tumor growth and stimulation of local inflammation in the colon. The objectives are:1. Define the effects of obesity and obesity-promoting diets on gut microbial composition, fecal metabolites, and local inflammation.2. Determine the independent effects of obesity-induced and obesity-promoting diet-induced changes in the gut microbiota on colon tumor growth and local inflammation.
Project Methods
Objective 1:Define the effects of obesity and obesity-promoting diets on gut microbial composition, fecal metabolites, and local inflammation.Experimental design:Starting at 6 weeks of age, 16 male ob/ob mice, which develop severe obesity due to hyperphagia (van der Kroon et al., 1981), will be fed a low-fat diet (LFD, 10% kcal from fat)ad libitum. Six-week old male wild-type C57BL/6 mice will be randomized to 5 groups (n=16/grp): 1) LFDad libitumto maintain a normal weight, 2) high-fat diet (HFD, 60% kcal from fat) or 3) western diet (WD, 40% kcal from fat, 30% kcal from sugar)ad libitumto induce obesity, and 4) Pair-fed HFD or 5) Pair-fed WD. The pair-fed mice will receive a daily HFD or WD pellet equal to the average daily kcal intake of group 1 to prevent them from gaining excess weight. Both high-fat and western diet-induced models of obesity are included because while the former is most commonly used, the latter more closely aligns with the average macronutrient consumption in westernized countries (Pinheiro-Castro et al., 2019). Body fat percentage will be determined in all mice by echoMRI immediately prior to euthanization after 15 weeks on diet. The cecal material from each mouse will be collected under anaerobic conditions, mixed with an anaerobic PBS/glycerol mixture and frozen at -80°C in 10 aliquots/mouse for use in the Objective 2 fecal microbial transplants.Inflammation:Expression of several pro- and anti-inflammatory cytokines in the proximal and distal colons of half the mice in each group will be assessed by quantitative RT-PCR. Paraffin-embedded colon tissue from the other half will be stained via IHC for immune cell markers: CD8+ T cells, Foxp3+ regulatory T cells, T-bet+ T cells, and F4/80+ macrophages, which have all been previously shown to be modulated by obesity in mice or humans (Luck et al., 2015; Pendyala et al., 2011).Gut microbiota characterization:DNA isolated from fecal pellets collected at baseline and in the final study week will be used for Illumina 16S V4 rRNA gene library construction, performed under the supervision of collaborator Dr. Tzu-Wen Cross, and 16S amplicon sequencing via Illumina Next Generation MiSeq. Dr. Cross will also assist with analysis of the raw sequencing data via QIIME 2. Collaborator Dr. Nadia Lanman (Purdue Collaborative Core for Cancer Bioinformatics) will then use the R package Phyloseq to perform a taxa diversity analysis across samples and conditions and DESeq2 to identify statistically significant differences in abundance of taxa between treatments.Fecal metabolite characterization:Fecal samples collected in the last week of study will also be subjected to non-targeted metabolomic analysis to further define the functional profile of each group's gut microbiota and specifically assess the impact of obesity and/or obesity-promoting diets on the production of inflammation-promoting fecal metabolites. Samples will be submitted to Metabolon for processing and quantification of >1000 metabolites via ultra-high-performance liquid chromatography/tandem accurate mass spectrometry. Metabolon will then link differences in metabolites between the groups to biochemical pathways, enabling differences in functional profiles to be determined.Statistical analyses:To evaluate differences between groups in body weight and inflammation markers, one-way analysis of variance (ANOVA) using Tukey's Multiple Comparisons Test comparison will be performed on GraphPad Prism software. AdjustedP<0.05 will be considered significant.Statistical dependence between measures of colon inflammation/immune cell markers, specific gut microbial taxa, and fecal metabolites of interest (particularly those linked to inflammation) will be determined by Dr. Lanman. Multiple linear regression analysis will be performed using the R statistical language to identify associations between these variables. Correlations analysis will be performed using Spearman correlation coefficients. The sample size (n=16 mice/group) will provide a 1:1 ratio of fecal donor:recipient mice, based on the power analysis for Objective 2.Objective 2: Determine the independent effects of obesity-induced and obesity-promoting diet-induced changes in the gut microbiota on colon tumor growth and local inflammation.Experimental Design:Nine-week-old male wild-type FVB/N mice (n=112) will receive a 14-day antibiotic cocktail treatment (1.0 mg/ml ampicillin, 5 mg/ml vancomycin, 5 mg/ml neomycin, 10 mg/ml metronidazole; 10 ml/kg/day via oral gavage every 12 hours) to knock-down the gut microbiota (Reikvam et al., 2011). Sixteen additional mice will receive a 14-day vehicle oral gavage (control group 1). Next, 96 of the 112 antibiotic-treated mice will be randomized to receive a fecal microbial transplant (FMT) via oral gavage from the 6 donor mouse groups in Objective 1, with a 1:1 donor:recipient mouse ratio (n=16/group). The other 16 antibiotic-treated mice (and control group 1) will receive a FMT vehicle oral gavage (control group 2). At 12 weeks of age (after the 1st FMT), all mice will begin 5 weeks of azoxymethane (AOM, 10 mg/kg i.p.), a chemical carcinogen that induces colon tumors. The AOM model was chosen because it closely mirrors the pathogenesis and molecular profile of human sporadic colon cancer (Chen & Huang, 2009). All mice will be fed the LFDad libitumthroughout study and receive a FMT (or vehicle) every 3 weeks to maintain colonization until euthanization at 15 weeks after the final AOM injection. C57BL/6 mice cannot be used here because they are insensitive to AOM, developing only aberrant crypt foci in response to the carcinogen (Zeng et al., 2018) while FVB/N mice develop tumors (Olivo-Marston et al., 2014). Conversely, C57BL/6 mice must be used in Objective 1 because while both FVB/N and C57BL/6 mice develop obesity in response to a HFD (Montgomery et al., 2013), ob/ob mice are only commercially available on a C57BL/6 background and thus all Objective 1 mice must be on this background.Tumor assessment, body composition, inflammation:Tumors will be enumerated and 2 dimensions of each measured using digital calipers. The same endpoint assessments for body composition and inflammation will be performed as described for Objective 1, with the inflammatory cytokines assessed only in non-tumor bearing colon tissue.Gut microbiota and fecal metabolite characterization:Fecal pellets collectedat baseline, 1-week after the 1st FMT/prior to AOM initiation (to determine the success of the first FMT), after the 2nd FMT/during the AOM regimen (to determine the impact of AOM on the transplanted microbiota), and at euthanization will be used for sequencing and analysis as described for Objective 1. Dr. Cross will again assist with library construction and QIIME 2 analysis. Metabolomic analysis will also be performed on endpoint samples as described in Objective 1.Statistical analyses:The same statistical tests and software described for Objective 1 will be used for Objective 2. Dr. Lanman will again assist with correlative analyses, though here will determine whether there are correlations between specific gut microbial taxa, fecal metabolites of interest, colon inflammation/immune cell markers, and tumor outcomes. Collaborator Dr. Scott Bultman assisted with study design and will assist with interpretation of this correlative data. The sample size (n=16 mice/group) was calculated to be sufficient to detect a 100% difference in the primary outcome of tumor multiplicity with 80% power (P=0.05).