Hyper-variability in Circulating Insulin Levels and Physiological Outcomes to High Fat Feeding in Male Ins1-/-:Ins2+/- Mice in a Specific Pathogen-free Facility


This paper from Jim Johnson’s group (@JimJohnsonSci) was posted to bioRxiv at http://dx.doi.org/10.1101/031799.

Abstract: Insulin is an essential hormone with key roles in energy homeostasis and body composition. Mice and rats, unlike other mammals, have two insulin genes: the rodent-specific Ins1 gene and the ancestral Ins2 gene. The relationships between insulin gene dosage and obesity has previously been explored in male and female Ins2-/- mice with full or reduced Ins1 dosage, as well as in female Ins1-/- mice with full or partial Ins2 dosage. We report herein unexpected hyper-variability in circulating insulin and physiological responses to high fat feeding in male Ins1-/-:Ins2+/- mice. Two large cohorts of Ins1-/-:Ins2+/- mice and their Ins1-/-:Ins2+/+ littermates were fed chow diet or high fat diet (HFD) from weaning and housed in specific pathogen-free (SPF) conditions. Cohort A and cohort B were studied one year apart. Contrary to female mice from the same litters, inactivating one Ins2 allele on the complete Ins1-null background did not cause a consistent reduction of circulating insulin in male mice. In cohort A, HFD-fed males showed an equivalent degree of insulin hypersecretion and weight gain, regardless of Ins2 dosage. In cohort B, Ins1-/-:Ins2+/- males showed decreased insulin levels and body mass, compared to Ins1-/-:Ins2+/+ littermates. While experimental conditions were held consistent between cohorts, we found that HFD-fed Ins1-/-:Ins2+/- mice with lower insulin levels had increased corticosterone. Collectively, these observations highlight the hyper-variability and range of phenotypic characteristics modulated by Ins2 gene dosage, specifically in male mice.


Limits of aerobic metabolism in cancer cells

From Alexei Vazquez at the University of Glasgow is this paper posted on BioRxiv:

Cancer cells exhibit high rates of aerobic glycolysis and glutaminolysis. Aerobic glycolysis can provide energy and glutaminolysis can provide carbon for anaplerosis and reductive carboxylation to citrate. However, all these metabolic requirements could be in principle satisfied from glucose. Energy can be generated from oxidative phosphorylation (OxPhos) of glucose, anaplerosis can be accomplished using pyruvate carboxylate and citrate can be derived from glucose. Here we investigate why cancer cells do not satisfy their metabolic demands using aerobic biosynthesis from glucose. Based on the typical composition of a mammalian cell we quantify the energy demand and the OxPhos burden of cell biosynthesis from glucose. Our calculation demonstrates that aerobic growth from glucose is feasible up to a minimum doubling time that is proportional to the OxPhos burden and inversely proportional to the mitochondria OxPhos capacity. To grow faster cancer cells must activate aerobic glycolysis for energy generation and uncouple NADH generation from biosynthesis. To uncouple biosynthesis from NADH generation cancer cells can synthesize lipids from carbon sources that do not produce NADH in their catabolism, including acetate and the amino acids glutamate, glutamine, phenylalanine and tyrosine. Finally, we show that cancer cell lines commonly used in cancer research have an OxPhos capacity that is insufficient to support aerobic biosynthesis from glucose. We conclude that selection for high rate of biosynthesis implies a selection for aerobic glycolysis and uncoupling biosynthesis from NADH generation. Any defect or perturbation reducing the OxPhos capacity will exacerbate this selection.

Mitochondrial DNA Copy Number Variation Across Human Cancers

Published recently on BioRxiv from Chris Sander’s lab (this is the abstract):

In cancer, mitochondrial dysfunction, through mutations, deletions, and changes in copy number of mitochondrial DNA (mtDNA), contributes to the malignant transformation and progression of tumors. Here, we report the first large-scale survey of mtDNA copy number variation across 21 distinct solid tumor types, examining over 13,000 tissue samples profiled with next-generation sequencing methods. We find a tendency for cancers, especially of the bladder and kidney, to be significantly depleted of mtDNA, relative to matched normal tissue. We show that mtDNA copy number is correlated to the expression of mitochondrially-localized metabolic pathways, suggesting that mtDNA copy number variation reflect gross changes in mitochondrial metabolic activity. Finally, we identify a subset of tumor-type-specific somatic alterations, including IDH1 and NF1 mutations in gliomas, whose incidence is strongly correlated to mtDNA copy number. Our findings suggest that modulation of mtDNA copy number may play a role in the pathology of cancer.

Genetic Basis of Transcriptome Diversity in Drosophila melanogaster

This preprint from Trudy Mackay‘s group at NC State uses a recombinant inbred series of flies known as the Drosophila Genome Reference Panel (DGRP) to evaluate how genetic variation affects transcription.  To do this they extracted RNA from whole flies, pooled from males and females of each of the 192 recombinant inbred fly lines.  They fit the transcriptome data for each gene to a linear mixed effects model that included gender as the dependent variable and the RI line as a random effect.  They then calculated broad (based on the random effects term) and narrow sense (by incorporating a genetic covariance matrix) heritability for each transcript.


They found several interesting things.  First, with respect to sex they found that of the 18,140 transcripts tested, 7626 of these genes showed significant variability across the panel.  The broad sense heritability of genes ranged from 0.034-0.946 across the panel.

They then incorporated additive genetic variance into their model to compare narrow sense and broad sense heritability, and surprisingly found that this simple additive model explained most of the broad sense heritability (for a good explanation of the difference between the two see here, here and here).  What this suggests is that in their model, additive genetic effects explains most of the phenotypic variance of the transcripts.  They also modelled the within-transcript variance in expression, and found that unlike mean expression, the variance in expression was often modified by trans-eQTLs.  Supporting this, they found that nearly 50% of genes had a nearby cis-eQTL, mostly clustered around the 5′ transcriptional start site.  This is consistent with the idea that genetic drivers of transcriptional variation are near the upstream transcriptional regulatory modules of a gene.  The most surprising thing they saw (to me at least) was that most genetic expression variance was sex-specific, with only 185 eQTLs affecting expression in both sexes, out of 941 (male) and 1139 (female) cis-eQTL’s identified.  This is much higher than the rates identified by others in humans (12-17% in this paper).  Certainly this suggests that incorporating sex as a factor in GWA studies is extremely important.

In sum, this paper along with the previous work by Leonid Kruglyak’s group showing most heritability can be explained by additive genetic effects (see here in yeast) adds an important element to our understanding of how genetic variation can affect heritability.

Hat tip to Haldane’s Sieve who mentioned the paper here

Wen Huang, Mary Anna Carbone, Michael Magwire, Jason Peiffer, Richard Lyman, Eric Stone, Robert Anholt, & Trudy Mackay (2015). Genetic Basis of Transcriptome Diversity in Drosophila melanogaster bioRxiv : 10.1101/018325