Quantifying the notions of canalizing and master genes in a gene regulatory network-a Boolean network modeling perspective

Design of the Building Research in CRC prevention (BRIDGE-CRC) trial: a 6-month, parallel group Mediterranean diet and weight loss randomized controlled lifestyle intervention targeting the bile acid-gut microbiome axis to reduce colorectal cancer risk among African American/Black adults with obesity

BACKGROUND

Among all racial/ethnic groups, people who identify as African American/Blacks have the second highest colorectal cancer (CRC) incidence in the USA. This disparity may exist because African American/Blacks, compared to other racial/ethnic groups, have a higher prevalence of risk factors for CRC, including obesity, low fiber consumption, and higher intakes of fat and animal protein. One unexplored, underlying mechanism of this relationship is the bile acid-gut microbiome axis. High saturated fat, low fiber diets, and obesity lead to increases in tumor promoting secondary bile acids. Diets high in fiber, such as a Mediterranean diet, and intentional weight loss may reduce CRC risk by modulating the bile acid-gut microbiome axis. The purpose of this study is to test the impact of a Mediterranean diet alone, weight loss alone, or both, compared to typical diet controls on the bile acid-gut microbiome axis and CRC risk factors among African American/Blacks with obesity. Because weight loss or a Mediterranean diet alone can reduce CRC risk, we hypothesize that weight loss plus a Mediterranean diet will reduce CRC risk the most.

METHODS

This randomized controlled lifestyle intervention will randomize 192 African American/Blacks with obesity, aged 45-75 years to one of four arms: Mediterranean diet, weight loss, weight loss plus Mediterranean diet, or typical diet controls, for 6 months (48 per arm). Data will be collected at baseline, mid-study, and study end. Primary outcomes include total circulating and fecal bile acids, taurine-conjugated bile acids, and deoxycholic acid. Secondary outcomes include body weight, body composition, dietary change, physical activity, metabolic risk, circulating cytokines, gut microbial community structure and composition, fecal short-chain fatty acids, and expression levels of genes from exfoliated intestinal cells linked to carcinogenesis.

DISCUSSION

This study will be the first randomized controlled trial to examine the effects of a Mediterranean diet, weight loss, or both on bile acid metabolism, the gut microbiome, and intestinal epithelial genes associated with carcinogenesis. This approach to CRC risk reduction may be especially important among African American/Blacks given their higher risk factor profile and increased CRC incidence.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04753359 . Registered on 15 February 2021.

Network Classification Based on Reducibility With Respect to the Stability of Canalizing Power of Genes in a Gene Regulatory Network - A Boolean Network Modeling Perspective

A key objective of studying biological systems is to design therapeutic intervention strategies for beneficially altering cell dynamics. Derivation of control policies is hindered by the high-dimensional state spaces associated with gene regulatory networks. Hence, it is critical to reduce the network complexity and the paper aims to address this issue by focusing on the distribution of the canalizing power (CP) of the genes in the model. Canalizing genes enforce broad corrective actions on cellular processes and play a crucial role in producing optimal reactions to external stimuli. Therefore, it is critical to reduce the network while preserving the canalizing power of genes. We reduce Boolean networks with perturbation by removing genes with the smallest canalizing power consecutively, and evaluate the stability of canalizing power. A systematic empirical study demonstrates that there are two classes of networks, reducible and irreducible with respect to the preservation of canalizing power of the genes. Based on these observations, we introduce the definition of reducible networks and proceed with the problem of selecting the relevant network features that allow for discriminating networks from the two different classes. We demonstrate the efficacy of the selected features on synthetic and real gene regulatory networks.

Gut-host Crosstalk: Methodological and Computational Challenges

Understanding how health-promoting microbiota are established and their beneficial interactions with the host is of critical biomedical importance. The current high throughput data acquisition technologies allow for integrating components of the gut ecosystem. The richness of data types and large number of measured variables involved underscores the critical importance of the appropriate choice of analytical and computational methods that can be used to model this complex ecosystem. This review outlines currently used approaches to perform analyses of data obtained as a result of interrogation of the gut-microbiota ecosystem and the challenges associated with these methodological and computational efforts. The problem of large dimensionality versus small numbers of samples is explained with discussions of clustering, dimensionality reduction, and statistical testing. Predictive modeling and data integration specific to the gut ecosystem are also discussed.