Ironing out the details: Untangling dietary iron and genetic background in diabetes

The search for genetic risk factors in type-II diabetes has been hindered by a failure to consider dietary variables. Dietary nutrients impact metabolic disease risk and severity and are essential to maintaining metabolic health. Genetic variation between individuals confers differences in metabolism, which directly impacts response to diet. Most studies attempting to identify genetic risk factors in disease fail to incorporate dietary components, and thus are ill-equipped to capture the breadth of the genome’s impact on metabolism. Understanding how genetic background interacts with nutrients holds the key to predicting and preventing metabolic diseases through the implementation of personalized nutrition. Dysregulation of iron homeostasis is associated with type-II diabetes, but the link between dietary iron and metabolic dysfunction is poorly defined. High iron burden in adipose tissue induces insulin resistance, but the mechanisms underlying adipose iron accumulation remain unknown. Hepcidin controls dietary iron absorption and distribution in metabolic tissues, but it is unknown whether genetic variation influencing hepcidin expression modifies susceptibility to dietary iron-induced insulin resistance. This review highlights discoveries concerning the axis of iron homeostasis and adipose function and suggests that genetic variation underlying dietary iron metabolism is an understudied component of metabolic disease

Integrated transcriptomics contrasts fatty acid metabolism with hypoxia response in β-cell subpopulations associated with glycemic control

BACKGROUND: Understanding how heterogeneous β-cell function impacts diabetes is imperative for therapy development. Standard single-cell RNA sequencing analysis illuminates some factors driving heterogeneity, but new strategies are required to enhance information capture. RESULTS: We integrate pancreatic islet single-cell and bulk RNA sequencing data to identify β-cell subpopulations based on gene expression and characterize genetic networks associated with β-cell function in obese SM/J mice. We identify β-cell subpopulations associated with basal insulin secretion, hypoxia response, cell polarity, and stress response. Network analysis associates fatty acid metabolism and basal insulin secretion with hyperglycemic-obesity, while expression of Pdyn and hypoxia response is associated with normoglycemic-obesity. CONCLUSIONS: By integrating single-cell and bulk islet transcriptomes, our study explores β-cell heterogeneity and identifies novel subpopulations and genetic pathways associated with β-cell function in obesity

A Closer Look at Dietary Supplements: An Exercise in Experiential Learning

undergraduate poster presentatio

ANTIGEN-SPECIFIC T-CELL FACTOR IN CELL COOPERATION: PHYSICAL PROPERTIES AND MAPPING IN THE LEFT-HAND (K) HALF OF H-2

Mouse thymus cells, educated to poly(tyrosyl,glutamyl)-polyDLalanyl--polylysyl [(T,G)-A--L], release an antigen-specific factor on brief culture in vitro. The factor cooperates with bone marrow cells in the antibody response to (T,G)-A--L in irradiated recipients. Its mol wt determined from Sephadex G100 chromatography is in the region of 50,000. The factor is removed by specific antigen-coated columns, but not by anti-immunoglobulin (anti-Fab, anti-µ, anti-Fv) adsorbents. The factor is removed by alloantisera directed against the H-2 haplotype of the strain in which it is produced. Moreover, only antisera with specificity for the K side of H-2 were successful in removing the factor activity

Brown adipose expansion and remission of glycemic dysfunction in obese SM/J mice

We leverage the SM/J mouse to understand glycemic control in obesity. High-fat-fed SM/J mice initially develop poor glucose homeostasis relative to controls. Strikingly, their glycemic dysfunction resolves by 30 weeks of age despite persistent obesity. The mice dramatically expand their brown adipose depots as they resolve glycemic dysfunction. This occurs naturally and spontaneously on a high-fat diet, with no temperature or genetic manipulation. Removal of the brown adipose depot impairs insulin sensitivity, indicating that the expanded tissue is functioning as an insulin-stimulated glucose sink. We describe morphological, physiological, and transcriptomic changes that occur during the brown adipose expansion and remission of glycemic dysfunction, and focus on Sfrp1 (secreted frizzled-related protein 1) as a compelling candidate that may underlie this phenomenon. Understanding how the expanded brown adipose contributes to glycemic control in SM/J mice will open the door for innovative therapies aimed at improving metabolic complications in obesity

Spontaneous restoration of functional β-cell mass in obese SM/J mice

Maintenance of functional β-cell mass is critical to preventing diabetes, but the physiological mechanisms that cause β-cell populations to thrive or fail in the context of obesity are unknown. High fat-fed SM/J mice spontaneously transition from hyperglycemic-obese to normoglycemic-obese with age, providing a unique opportunity to study β-cell adaptation. Here, we characterize insulin homeostasis, islet morphology, and β-cell function during SM/J\u27s diabetic remission. As they resolve hyperglycemia, obese SM/J mice dramatically increase circulating and pancreatic insulin levels while improving insulin sensitivity. Immunostaining of pancreatic sections reveals that obese SM/J mice selectively increase β-cell mass but not α-cell mass. Obese SM/J mice do not show elevated β-cell mitotic index, but rather elevated α-cell mitotic index. Functional assessment of isolated islets reveals that obese SM/J mice increase glucose-stimulated insulin secretion, decrease basal insulin secretion, and increase islet insulin content. These results establish that β-cell mass expansion and improved β-cell function underlie the resolution of hyperglycemia, indicating that obese SM/J mice are a valuable tool for exploring how functional β-cell mass can be recovered in the context of obesity

Using whole-genome sequences of the LG/J and SM/J inbred mouse strains to prioritize quantitative trait genes and nucleotides

Background The laboratory mouse is the most commonly used model for studying variation in complex traits relevant to human disease. Here we present the whole-genome sequences of two inbred strains, LG/J and SM/J, which are frequently used to study variation in complex traits as diverse as aging, bone-growth, adiposity, maternal behavior, and methamphetamine sensitivity. Results We identified small nucleotide variants (SNVs) and structural variants (SVs) in the LG/J and SM/J strains relative to the reference genome and discovered novel variants in these two strains by comparing their sequences to other mouse genomes. We find that 39% of the LG/J and SM/J genomes are identical-by-descent (IBD). We characterized amino-acid changing mutations using three algorithms: LRT, PolyPhen-2 and SIFT. We also identified polymorphisms between LG/J and SM/J that fall in regulatory regions and highly informative transcription factor binding sites (TFBS). We intersected these functional predictions with quantitative trait loci (QTL) mapped in advanced intercrosses of these two strains. We find that QTL are both over-represented in non-IBD regions and highly enriched for variants predicted to have a functional impact. Variants in QTL associated with metabolic (231 QTL identified in an F16 generation) and developmental (41 QTL identified in an F34generation) traits were interrogated and we highlight candidate quantitative trait genes (QTG) and nucleotides (QTN) in a QTL on chr13 associated with variation in basal glucose levels and in a QTL on chr6 associated with variation in tibia length. Conclusions We show how integrating genomic sequence with QTL reduces the QTL search space and helps researchers prioritize candidate genes and nucleotides for experimental follow-up. Additionally, given the LG/J and SM/J phylogenetic context among inbred strains, these data contribute important information to the genomic landscape of the laboratory mouse