Besides beige adipogenesis increasing the progenitor pool

Besides beige adipogenesis, increasing the progenitor pool in adipose tissues through angiogenesis has another advantage. It is known that PDGFRα+ progenitor Tunicamycin are the source of both beige and white adipocytes (Lee et al., 2012; Lee et al., 2013; Lee et al., 2015). Thus, enhancing PDGFRα+ progenitor cell pool will not only increase beige but also white adipogenesis, as shown by the increased expression of white preadipose genes in MVA WAT of this study. Adipose tissue is the organ to store fat, and an insufficient number of adipocytes leads to adipocyte hypertrophy, hypoxia and inflammation, a key cause of metabolic dysfunction (Rosen and Spiegelman, 2014). Thus, adipocyte hyperplasia has protective effects on metabolic dysfunction induced by excessive energy intake. Consistently, there is one subgroup of people who are metabolically health despite being obese, while others exhibit severe metabolic syndromes (Denis and Obin, 2013). People who are called “metabolically healthy obese” (MHO) tend to have smaller adipocytes (Kloting et al., 2010) and higher mitochondrial transcription (Naukkarinen et al., 2014). These individuals have reduced visceral adiposity, reduced inflammation, improved glucose and lipid homeostasis when compared to other equally obese unhealthy subjects (Denis and Obin, 2013). Based on our discovery, maternal vitamin A or RA supplementation increases the progenitor pool in offspring, which reduces average adipocyte sizes and increases adipocyte hyperplasia, improving overall metabolic health of offspring. In conclusion, offspring adipose tissue health is substantially improved due to maternal vitamin A or RA supplementation. Maternal vitamin A promotes vascular system development, which consequently increases the population of PDGFRα+ adipose progenitor cells. In addition, maternal vitamin A supplementation strongly upregulates beige adipogenesis of PDGFRα+ progenitor cells. In combination, maternal vitamin A treated offspring have increased beige adipogenesis and smaller adipocyte sizes, which protect offspring against diet-induced obesity and metabolic dysfunction. The following are the supplementary data related to this article.
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Introduction Urine is a commonly used biological fluid for discovery of disease markers, diagnostics, and health status monitoring. Urine presents several distinct advantages over blood. For example, its sampling is truly non-invasive, therefore can be repeated frequently; the urine proteome is also simpler than the plasma proteome and more amenable to proteomic analysis (An and Gao, 2015; Shao et al., 2011b). Proteins in urine originate from glomerular filtration of plasma and secretion of urogenital system (Pisitkun et al., 2004, 2006; Sun et al., 2005; Wang et al., 2006) and changes in urinary protein composition can reflect physiological and pathological status of the human body (Decramer et al., 2008; Wu and Gao, 2015). Much effort has been made to characterize protein composition of urine using mass spectrometry (MS) during the last decade (Adachi et al., 2006; Kentsis et al., 2009; Khristenko et al., 2016; Marimuthu et al., 2011; Nagaraj and Mann, 2011; Sun et al., 2009; Thongboonkerd et al., 2002). Databases, such as Max-Planck Unified Proteome database (http://mapuproteome.com/) (Zhang et al., 2007), the Human Kidney and Urine Proteome Project (http://www.hkupp.org/) (Yamamoto et al., 2008), the Human Urinary Proteome Database (http://mosaiques-diagnostics.de/diapatpcms/mosaiquescms/front_content.php?idcat=257) (Coon et al., 2008), Urinary Protein Biomarker (UPB) database (http://www.mybiosoftware.com/upb-20130710-urine-protein-biomarker-database.html) (Shao et al., 2011a), and Urine Proteomics.org (http://urineproteomics.org/databases.html) (Kentsis et al., 2009), documented lists of urinary proteins, providing convenient resources for keeping track of published urine proteomes. However, none of these databases provided quantitative information about the urine proteins.