Maternal obesity alters offspring liver and skeletal muscle metabolism in early post-puberty despite maintaining a normal post-weaning dietary lifestyle.

Maternal obesity (MO) during pregnancy is linked to increased and premature risk of age-related metabolic diseases in the offspring. However, the underlying molecular mechanisms still remain not fully understood. Using a well-established nonhuman primate model of MO, we analyzed tissue biopsies and plasma samples obtained from post-pubertal offspring (3-6.5 y) of MO mothers (n = 19) and from control animals born to mothers fed a standard diet (CON, n = 13). All offspring ate a healthy chow diet after weaning. Using untargeted gas chromatography-mass spectrometry metabolomics analysis, we quantified a total of 351 liver, 316 skeletal muscle, and 423 plasma metabolites. We identified 58 metabolites significantly altered in the liver and 46 in the skeletal muscle of MO offspring, with 8 metabolites shared between both tissues. Several metabolites were changed in opposite directions in males and females in both liver and skeletal muscle. Several tissue-specific and 4 shared metabolic pathways were identified from these dysregulated metabolites. Interestingly, none of the tissue-specific metabolic changes were reflected in plasma. Overall, our study describes characteristic metabolic perturbations in the liver and skeletal muscle in MO offspring, indicating that metabolic programming in utero persists postnatally, and revealing potential novel mechanisms that may contribute to age-related metabolic diseases later in life.

Adaptation of Hybridization Capture of Chromatin-associated Proteins for Proteomics to Mammalian Cells.

The hybridization capture of chromatin-associated proteins for proteomics (HyCCAPP) technology was initially developed to uncover novel DNA-protein interactions in yeast. It allows analysis of a target region of interest without the need for prior knowledge about likely proteins bound to the target region. This, in theory, allows HyCCAPP to be used to analyze any genomic region of interest, and it provides sufficient flexibility to work in different cell systems. This method is not meant to study binding sites of known transcription factors, a task better suited for Chromatin Immunoprecipitation (ChIP) and ChIP-like methods. The strength of HyCCAPP lies in its ability to explore DNA regions for which there is limited or no knowledge about the proteins bound to it. It can also be a convenient method to avoid biases (present in ChIP-like methods) introduced by protein-based chromatin enrichment using antibodies. Potentially, HyCCAPP can be a powerful tool to uncover truly novel DNA-protein interactions. To date, the technology has been predominantly applied to yeast cells or to high copy repeat sequences in mammalian cells. In order to become the powerful tool we envision, HyCCAPP approaches need to be optimized to efficiently capture single-copy loci in mammalian cells. Here, we present our adaptation of the initial yeast HyCCAPP capture protocol to human cell lines, and show that single-copy chromatin regions can be efficiently isolated with this modified protocol.

HyCCAPP as a tool to characterize promoter DNA-protein interactions in Saccharomyces cerevisiae.

Currently available methods for interrogating DNA-protein interactions at individual genomic loci have significant limitations, and make it difficult to work with unmodified cells or examine single-copy regions without specific antibodies. In this study, we describe a physiological application of the Hybridization Capture of Chromatin-Associated Proteins for Proteomics (HyCCAPP) methodology we have developed. Both novel and known locus-specific DNA-protein interactions were identified at the ENO2 and GAL1 promoter regions of Saccharomyces cerevisiae, and revealed subgroups of proteins present in significantly different levels at the loci in cells grown on glucose versus galactose as the carbon source. Results were validated using chromatin immunoprecipitation. Overall, our analysis demonstrates that HyCCAPP is an effective and flexible technology that does not require specific antibodies nor prior knowledge of locally occurring DNA-protein interactions and can now be used to identify changes in protein interactions at target regions in the genome in response to physiological challenges.