Weight, habitual fibre intake, and microbiome composition predict tolerance to fructan supplementation.

Fructans are commonly used as dietary fibre supplements for their ability to promote the growth of beneficial gut microbes. However, fructan consumption has been associated with various dosage-dependent side effects. We characterised side effects in an exploratory analysis of a randomised trial in healthy adults (n = 40) who consumed 18 g/day inulin or placebo. We found that individuals weighing more or habitually consuming higher fibre exhibited the best tolerance. Furthermore, we identified associations between gut microbiome composition and host tolerance. Specifically, higher levels of Christensenellaceae R-7 group were associated with gastrointestinal discomfort, and a machine-learning-based approach successfully predicted high levels of flatulence, with [Ruminococcus] torques group and (Oscillospiraceae) UCG-002 sp. identified as key predictive taxa. These data reveal trends that can help guide personalised recommendations for initial inulin dosage. Our results support prior ecological findings indicating that fibre supplementation has the greatest impact on individuals whose baseline fibre intake is lowest.

Gaining Wings to FLY: Using Drosophila Oogenesis as an Entry Point for Citizen Scientists in Laboratory Research.

Citizen science is a productive approach to include non-scientists in research efforts that impact particular issues or communities. In most cases, scientists at advanced career stages design high-quality, exciting projects that enable citizen contribution, a crowdsourcing process that drives discovery forward and engages communities. The challenges of having citizens design their own research with no or limited training and providing access to laboratory tools, reagents, and supplies have limited citizen science efforts. This leaves the incredible life experiences and immersion of citizens in communities that experience health disparities out of the research equation, thus hampering efforts to address community health needs with a full picture of the challenges that must be addressed. Here, we present a robust and reproducible approach that engages participants from Grade 5 through adult in research focused on defining how diet impacts disease signaling. We leverage the powerful genetics, cell biology, and biochemistry of Drosophila oogenesis to define how nutrients impact phenotypes associated with genetic mutants that are implicated in cancer and diabetes. Participants lead the project design and execution, flipping the top-down hierarchy of the prevailing scientific culture to co-create research projects and infuse the research with cultural and community relevance.

Quantifying cumulative phenotypic and genomic evidence for procedural generation of metabolic network reconstructions.

Genome-scale metabolic network reconstructions (GENREs) are valuable tools for understanding microbial metabolism. The process of automatically generating GENREs includes identifying metabolic reactions supported by sufficient genomic evidence to generate a draft metabolic network. The draft GENRE is then gapfilled with additional reactions in order to recapitulate specific growth phenotypes as indicated with associated experimental data. Previous methods have implemented absolute mapping thresholds for the reactions automatically included in draft GENREs; however, there is growing evidence that integrating annotation evidence in a continuous form can improve model accuracy. There is a need for flexibility in the structure of GENREs to better account for uncertainty in biological data, unknown regulatory mechanisms, and context-specificity associated with data inputs. To address this issue, we present a novel method that provides a framework for quantifying combined genomic, biochemical, and phenotypic evidence for each biochemical reaction during automated GENRE construction. Our method, Constraint-based Analysis Yielding reaction Usage across metabolic Networks (CANYUNs), generates accurate GENREs with a quantitative metric for the cumulative evidence for each reaction included in the network. The structuring of CANYUNs allows for the simultaneous integration of three data inputs while maintaining all supporting evidence for biochemical reactions that may be active in an organism. CANYUNs is designed to maximize the utility of experimental and annotation datasets and to ultimately assist in the curation of the reference datasets used for the automatic construction of metabolic networks. We validated CANYUNs by generating an E. coli K-12 model and compared it to the manually curated reconstruction iML1515. Finally, we demonstrated the use of CANYUNs to build a model by generating an E. coli Nissle CANYUNs model using novel phenotypic data that we collected. This method may address key challenges for the procedural construction of metabolic networks by leveraging uncertainty and redundancy in biological data.

Novel tools for genetic manipulation of follicle stem cells in the Drosophila ovary reveal an integrin-dependent transition from quiescence to proliferation.

In many tissues, the presence of stem cells is inferred by the capacity of the tissue to maintain homeostasis and undergo repair after injury. Isolation of self-renewing cells with the ability to generate the full array of cells within a given tissue strongly supports this idea, but the identification and genetic manipulation of individual stem cells within their niche remain a challenge. Here we present novel methods for marking and genetically altering epithelial follicle stem cells (FSCs) within the Drosophila ovary. Using these new tools, we define a sequential multistep process that comprises transitioning of FSCs from quiescence to proliferation. We further demonstrate that integrins are cell-autonomously required within FSCs to provide directional signals that are necessary at each step of this process. These methods may be used to define precise roles for specific genes in the sequential events that occur during FSC division after a period of quiescence.