Fat tissue, also known as white adipose tissue, specializes in storing excess calories. Much of this storage happens under the skin, but fat tissue can also build up inside the abdomen and surround organs, where it is known as ‘visceral’ fat. When visceral fat tissue is unhealthy, it may help diseases such as diabetes and heart disease to develop.

Unhealthy fat tissue contains enlarged fat cells, which may die from overwork. The stress this places on the surrounding tissue activates the immune system, causing inflammation and the build-up of collagen fibers around the cells (a condition known as fibrosis). Not all people develop this type of unhealthy fat tissue, but we do not yet understand why.

In many tissues, blood vessels serve as a home for several types of adult stem cells that help to rejuvenate the tissue following damage. To identify these cells, Hepler et al. analyzed the genes used by more than 3,000 cells living around the blood vessels in the visceral fat of adult mice. Recent work had already revealed that stem cells called adipocyte precursor cells live in this region. Hepler et al. now reveal the presence of a second group of cells, termed fibro-inflammatory progenitor cells (or FIPs for short).

To investigate the roles of each cell type in more detail, Hepler et al. developed a new technique to isolate the adipocyte precursor cells from other cell types. When grown in the right conditions in petri dishes, the adipocyte precursor cells were able to form new fat cells. They could also make new fat cells when transplanted into mice that lacked fat tissue. By contrast, the FIPs can suppress the activity of adipocyte precursor cells and activate immune cells. They may also help fibrosis to develop.

It is not yet clear whether FIPs are present in human fat tissue. But, if they are, understanding them in greater detail may suggest new ways to treat diabetes and heart disease in obese people.

White adipose tissue (WAT) represents the principle site for safe and efficient energy storage in mammals. WAT, as a whole, is considerably heterogeneous. WAT is composed of energy-storing adipocytes, various immune cell populations, vascular cells, adipocyte precursor cells (APCs), and largely uncharacterized stromal populations. The development and function of adipose tissue is highly dependent on critical interactions between adipocytes, APCs, immune cells, and endothelial cells (Han et al., 2011; Hong et al., 2015).

WAT has a unique and remarkable capacity to expand and contract in size in response to changes in demand for energy storage. In the context of positive energy balance (nutrient excess), WAT expands to meet the increased demand for energy storage, leading ultimately to the condition of obesity. The manner by which WAT expands is a critical determinant of metabolic health in obesity. It has long been appreciated that individuals who preferentially accumulate WAT in subcutaneous regions are at a relatively lower risk for developing insulin resistance when compared to equally obese individuals with central (visceral) adiposity (Kissebah et al., 1982; Krotkiewski et al., 1983). It is now widely believed that visceral and subcutaneous WAT depots represent fundamentally distinct types of WAT (Karastergiou et al., 2013; Lee et al., 2013; Macotela et al., 2012; Yamamoto et al., 2010). Indeed, visceral and subcutaneous WAT depots emanate from distinct developmental lineages (Chau et al., 2014).

Importantly, another clear determinant of metabolic health in obesity is manner in which individual WAT depots expand and ‘remodel’ (Hepler and Gupta, 2017; Lee et al., 2010). WAT ‘remodeling’ associated with obesity can be described as both quantitative and qualitative changes in adipocyte numbers and stromal-vascular cell composition. Pathological WAT expansion is characterized by the presence of enlarged adipocytes, excessive macrophage accumulation, and fibrosis (Divoux et al., 2010; Gustafson et al., 2009; Hardy et al., 2011; Klöting and Blüher, 2014; Sun et al., 2013). The prevailing hypothesis is that as ‘overworked’ fat cells reach their storage capacity, adipocyte death, inflammation, and fibrosis ensue (Hepler and Gupta, 2017; Sun et al., 2011). This is often associated with the deleterious accumulation of lipids in the liver, skeletal muscle, pancreas, and heart (termed ‘lipotoxicity’) (Unger and Scherer, 2010). Healthy WAT expansion occurs when adipose tissue expands through adipocyte hyperplasia (increase in adipocyte number through de novo differentiation) (Denis and Obin, 2013; Kim et al., 2014; Klöting et al., 2010). This is associated with a lower degree of chronic tissue inflammation and fibrosis. These adipose phenotypes of the ‘metabolically healthy’ obese tightly correlate with sustained insulin sensitivity in these patients. To date, the factors dictating a healthy vs. unhealthy WAT expansion in obesity remain poorly defined. In particular, the array of cell types within the adipose stromal-vascular compartment contributing to the remodeling of WAT in obesity has remained largely undefined.

The growing appreciation for the casual link between adipose tissue distribution and remodeling with systemic metabolic health has sparked considerable interest in defining the adipocyte precursors giving rise to fat cells in adults and the mechanisms controlling their differentiation in vivo (Hepler et al., 2017). In male C57BL/6 mice, adipose tissues expand in diet-induced obesity in a depot-selective manner. The epididymal WAT depot expands through both adipocyte hypertrophy and adipocyte hyperplasia (Jeffery et al., 2015; Kim et al., 2014; Wang et al., 2013b). The inguinal subcutaneous WAT depot expands almost exclusively by adipocyte hypertrophy. We recently reported that visceral adipocytes emerging in association with HFD feeding originate, at least in part, from perivascular precursors expressing Pdgfrb (Vishvanath et al., 2016). Pdgfrb encodes the platelet-derived growth factor receptor β chain (PDGFRβ protein) and is a widely used marker of perivascular cells (Armulik et al., 2011). We previously employed a pulse-chase lineage tracing mouse model to track the fate of Pdgfrb-expressing cells in adipose tissue. Following HFD feeding, Pdgfrb-expressing cells give rise to white adipocytes within visceral WAT depots (Vishvanath et al., 2016). The ability of these precursors to undergo de novo adipogenesis in the setting of diet-induced obesity is critical for healthy visceral WAT expansion (Shao et al., 2018). Inducible genetic disruption of Pparg, the master regulatory gene of adipocyte differentiation, in Pdgfrb-expressing cells leads to a loss of de novo adipogenesis from Pdgfrb-expressing cells in the visceral WAT depot of diet-induced obese mice; this exacerbates the pathologic remodeling of this depot (i.e. increased inflammation and fibrosis). Driving de novo adipogenesis from Pdgfrb-expressing cells through transgenic Pparg expression leads to a healthy expansion of visceral WAT (lower inflammation and small adipocytes) (Shao et al., 2018). The highly adipogenic subpopulation of PDGFRβ+ cells in gonadal WAT (gWAT) is quantitatively enriched in the expression of Pparg, as well as its upstream regulatory factor, Zfp423 (Gupta et al., 2012; Tang et al., 2008; Vishvanath et al., 2016). PDGFRβ+ cells enriched in these adipogenic factors express several mural cell (pericyte/smooth muscle) markers and reside directly adjacent to the endothelium in WAT blood vessels (Gupta et al., 2012; Tang et al., 2008; Vishvanath et al., 2016). Using Zfp423 reporter mice (Zfp423^GFP BAC transgenic mice), we revealed that PDGFRβ+ cells expressing high levels of Zfp423 (GFP+ or Zfp423^High) represent highly committed preadipocytes while Zfp423^Low cells (GFP-) lacked significant adipogenic capacity, and exhibited significantly different global patterns of gene expression (Vishvanath et al., 2016). These observations suggested that the pool of PDGFRβ+ cells in visceral WAT is functionally heterogeneous, with cells possessing distinct cellular phenotypes.

In this study, we set out to explore the functional heterogeneity within Pdgfrb-expressing cells of visceral WAT from adult mice. Furthermore, our objective was to identify improved strategies to purify adipocyte precursor populations from these depots. Through single-cell RNA-sequencing, we identified functionally distinct subpopulations of Pdgfrb-expressing progenitor cells. We identified a unique population of cells that display fibrogenic and functional pro-inflammatory phenotypes, and lack inherent adipogenic capacity. These fibro-inflammatory progenitors (termed here as ‘FIPs’) can be purified by the use of commercially available antibodies (LY6C + PDGFRβ+). On the other hand, LY6C- CD9- PDGFRβ+ cells represent a distinct pool of highly adipogenic visceral adipocyte precursor cells (‘APCs’) that robustly differentiate spontaneously in vitro in growth media containing insulin. The frequency of these PDGFRβ+ subpopulations is highly regulated under physiological conditions. These data reveal the functional heterogeneity of perivascular progenitors within visceral WAT and provide insight into how the adipose stroma can control WAT remodeling. Moreover, the molecular profiles obtained for FIPs and APCs from visceral WAT, along with the strategies to isolate these cells, will facilitate the study of physiological WAT remodeling in vivo.

Visceral adipose tissue dysfunction in obesity is driven, at least in part, by chronic tissue inflammation, collagen deposition, and a loss of adipocyte precursor activity. WAT remodeling involves substantial qualitative and quantitative changes to the composition of the stromal compartment of the tissue; however, the functional heterogeneity of WAT stromal-vascular fraction has remained poorly defined and tools to isolate and study distinct subpopulations have been lacking. Here, we unveil functionally distinct PDGFRβ+ stromal cell subpopulations in visceral WAT (Figure 9). Importantly, we have developed strategies to prospectively isolate these distinct populations using commercially available antibodies.

Figure 9

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Functional analyses indicate that a relatively large subpopulation of PDGFRβ+ perivascular cells in visceral gonadal WAT exert fibrogenic and pro-inflammatory phenotypes. These cells, termed here as ‘FIPs,’ lack adipogenic capacity in vitro but instead exhibit a fibrogenic phenotype. FIPs are physiologically regulated; the frequency of these cells increases upon HFD feeding. Clement and colleagues previously reported that fibrogenic cells residing in WAT could be identified by the expression of CD9 and PDGFRα (Marcelin et al., 2017). Indeed, FIPs express CD9 and PDGFRα; however, both CD9 and PDGFRα are also expressed in at least a subpopulation of mesothelial cells isolated from visceral WAT. As such, the selection of FIPs on the basis of LY6c and PDGFRβ expression (LY6C+ PDGFRβ+) represents a strategy to prospectively and specifically isolate FIPs from mouse gonadal WAT. Importantly, our data reveal a number of previously unappreciated ways in which perivascular cells may impact WAT remodeling (Figure 9). The LY6C+ PDGFRβ+ cells described here have the capacity to inhibit adipocyte differentiation from APCs through the release of secreted factors. The presence of highly anti-adipogenic stromal cells within the total PDGFRβ+ population may explain the apparent lack of adipogenic capacity that crude/unpurified visceral PDGFRβ+ cultures possess vitro, despite the presence of APCs. It is notable that visceral adipose FIPs appear distinct from the recently identified Aregs of inguinal WAT. Stromal cell heterogeneity may be depot-specific, with different depots utilizing distinct cell types to control their function and plasticity. The exact identities of the secreted factors and mechanisms that mediate the anti-adipogenic activity of FIPs and Aregs are still unknown. Importantly, whether FIPs and Aregs act to suppress/restrain adipocyte hyperplasia under physiological settings in vivo needs to be further explored.

FIPs also exert a functional pro-inflammatory phenotype in response to pro-inflammatory stimuli. It is notable that the frequency of FIPs increases following the onset of HFD feeding. This raises an intriguing hypothesis for future studies that perivascular stromal cells can modulate local tissue inflammation. This notion is in line with recent studies indicating that vascular mural cells can serve as ‘gatekeepers’ of inflammation in the lung (Hung et al., 2017). On the other hand, one may expect that the increased frequency of FIPs would also completely blunt the differentiation of APCs in this depot. This is clearly not the case as gonadal WAT in mice is able to expand through adipocyte hyperplasia in the setting of diet-induced obesity. One possibility is that the anti-adipogenic activity of FIPs (rather than the frequency per se) is diminished by local signals in an attempt to facilitate adipogenesis within the depot. Another possibility lies in the spatial distribution of activated FIPs and APCs; their proximity to one another may influence their activity. The identification of these populations from the MuralChaser mice essentially places them within the perivascular compartment of adipose tissue; however, where APCs and FIPs are localized and become activated within the tissue is still unknown. Clearly, additional studies of these cells will be needed in order to determine their precise contribution to WAT inflammation and health in various settings in vivo. Furthermore, it is certainly plausible that FIPs contribute to WAT remodeling beyond fibrosis, inflammation, and adipogenesis.

The ability to isolate functionally distinct subpopulations of mural cells affords the possibility of identifying factors regulating these diverse mural cell phenotypes. Our gene expression analysis revealed the enrichment in mRNA levels of Nr4a family members in FIPs. Several studies have implicated NR4A nuclear receptors as modulators of inflammatory signaling; the precise impact of NR4A members on inflammation appears context/cell type specific. In some studies, NR4A family members are observed as being pro-inflammatory (Pei et al., 2006). In other settings, NR4A expression is induced in response to pro-inflammatory stimuli but acts as a molecular brake on inflammatory signaling. Our gain- and loss of function studies suggest that FIPs activate Nr4a family members in response to pro-inflammatory stimuli to serve as a transcriptional brake on inflammatory cytokine gene expression. This counter-regulatory response may be a mechanism to limit cellular oxidative stress and apoptosis driven by inflammatory signaling (Rodríguez-Calvo et al., 2017). Chao et al. previously demonstrated that NR4A family members are potent regulators of adipocyte differentiation (Chao et al., 2008). Thus, NR4A members may play multiple roles in controlling of the fate and function of adipose perivascular cells. Additional studies involving the genetic manipulation of Nr4a family members in PDGFRβ+ cells in vivo will be needed to elucidate the exact requirements of NR4A members in WAT remodeling in vivo. Importantly, the ability to isolate FIPs and APCs affords the possibility of employing several different types of genomic approaches in an effort to reveal novel molecular mechanisms controlling adipose tissue inflammation, fibrosis, and adipogenesis.

As described above, there has been tremendous interest in elucidating the identity of adipocyte precursors in adult adipose tissue. Pioneering studies from Friedman and colleagues led to a now widely-used strategy to prospectively isolate adipocyte progenitor cells from freshly isolated WAT (Rodeheffer et al., 2008). APCs have been isolated on the basis of CD29, SCA-1, and CD34 expression (CD29+ CD34+ SCA-1+ CD31- CD45-). These markers have proven to be quite useful for the selection of APCs from inguinal WAT and other WAT depots; however, a notable observation made here is that SCA-1 expression is in fact enriched in FIPs rather than APCs of the gonadal WAT depot. As such, the selection of cells on the basis of SCA-1 expression from this particular WAT depot yields a functionally heterogeneous population that likely includes FIPs, and perhaps even enriches for these cells. This may explain, at least in part, the notable lack of adipogenic potential that isolated gonadal CD34+ SCA-1+ cells possess in vitro (Church et al., 2014). Our prior work pointed to Zfp423 as a marker of committed preadipocytes; however, our scRNA-seq data reveal that Zfp423 expression is not confined exclusively to the APC subpopulation of PDGFRβ+ cells; Pdgfrb-expressing MLCs and FIPs also express Zfp423. Nevertheless, the selection of GFP^High PDGFRβ+ cells from gWAT of Zfp423^GFP reporter mice enriches for committed APCs, perhaps reflecting increased promoter/transgene activity in these cells.

Recent scRNA-seq analyses from Granneman and colleagues provide a cellular atlas of putative adipocyte precursor populations in adipose tissue (Burl et al., 2018). Their analyses included all non-hematopoetic, non-endothelial cells of the isolated adipose stromal-vascular fraction. The strength of their approach is that it allows for one to capture both perivascular (PDGFRβ+) and non-perivascular precursor populations. Our approach will identify precursor populations that express Pdgfrb/rtTA at the time of the pulse labeling. Pdgfrb expression declines as cell undergo differentiation into adipocytes. This means that cells even further committed to the adipocyte lineage (i.e. no longer express Pdgfrb) may not be captured through our analysis. Moreover, putative stem cell populations not yet expressing Pdgfrb may also be present and not captured (e.g. Pref1^rtTA targeted cells [Hudak et al., 2014]). Nevertheless, it is notable that most of the adipocyte precursor populations represented in the study by Burl et al. were indeed captured in our analysis. One cannot rule out the existence of additional adipocyte progenitor populations in any particular adipose depot; however, the congruency of the two independent studies suggests the MuralChaser model can identify and target the major APC populations residing within visceral WAT of mice. Moreover, the selection of LY6C- PDGFRβ+ cells from gWAT using commercially available antibodies represents a refined and convenient strategy to isolate visceral adipocyte precursors from wild type mice or genetic mouse models of interest.

Single-cell transcriptomics has become very useful in revealing molecular heterogeneity amongst seemingly homogenous populations of cells. The challenge, however, is to determine whether molecularly distinct populations of cells represent distinct ‘cell types,’ or rather ‘cell states’ which are influenced by their local microenvironment. Here, we reveal molecular heterogeneity amongst PDGFRβ+ cells within visceral white adipose tissue and begin to define the functional differences between the identified subpopulations. Our functional analyses suggest that the properties of visceral FIPs are at least somewhat stable; FIPs are quite limited in adipogenic potential in vitro and upon transplantation. They do not readily activate Pparg expression under the conditions examined. The phenotype of visceral APCs may be less stable. Visceral APCs have the potential to adopt characteristics of FIPs. In vitro and in vivo following HFD, APCs can activate the expression of pro-inflammatory cytokines. A caveat to most of our functional studies is that the cells are studied outside their native microenvironment. Under some physiological conditions, it is certainly plausible that multiple PDGFRβ+ subpopulations give rise in vivo to adipocytes; such adipocytes might even possess unique functional characteristics. Our prior lineage-tracing studies using the MuralChaser model clearly established that adipocytes emerge from Pdgfrb-expressing cells; efforts to define the relative contribution of individual mural cell subpopulations will require more precise lineage-tracing approaches with more specific Cre drivers. Moreover, our current studies cannot exclude the possibility that even further heterogeneity exists amongst PDGFRβ+ cells or within the identified subpopulations. Deeper sequencing, refined analyses, and further functional studies may unveil even more heterogeneity than appreciated.

It is noteworthy that Pdgfrb is expressed in a subset of WAT associated mesothelial cells and that Pdgfrb-expressing mesothelial cells express Pparg and some level of Zfp423. As described above, several lines of evidence point to a lineage relationship between embryonic mesothelial cells, APCs, and perivascular stromal cells within the visceral compartment (Chau et al., 2014; Rinkevich et al., 2012). PDGFRβ+ MLCs did not exhibit robust adipogenic potential under the culture conditions utilized here, despite their expression of Pparg isoform two and Zfp423. Additional signals may be needed in order to drive adipocyte differentiation from these cells. Alternatively, this subpopulation of mesothelial cells may represent developmental intermediates between mesothelial cells and perivascular progenitors. Further insight into the functional significance of these various stromal subpopulations, their developmental origins, and their cellular plasticity will require additional genetic tools to manipulate individual populations selectively in vivo. Nevertheless, the molecular profiles obtained for FIPs and APCs from visceral WAT, along with the strategies to isolate these cells, will facilitate the study of physiological visceral WAT remodeling in vivo. Ultimately, unraveling the cellular and molecular determinants of WAT expansion and remodeling may lead to strategies to improve adipose tissue function and defend against metabolic disease.

Sequencing data have been deposited to GEO under accession codes GSE111588.

1. 1. Gupta RK
   2. Hepler C

   (2018) Single cell RNA-sequencing of visceral adipose tissue Pdgfrβ+ cells

   Publicly available at the NCBI Gene Expression Omnibus (accession no. GSE111588).

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111588

1. 1. Ambrosi TH
   2. Scialdone A
   3. Graja A
   4. Gohlke S
   5. Jank AM
   6. Bocian C
   7. Woelk L
   8. Fan H
   9. Logan DW
   10. Schürmann A
   11. Saraiva LR
   12. Schulz TJ

   (2017) Adipocyte accumulation in the bone marrow during obesity and aging impairs stem Cell-Based hematopoietic and bone regeneration

   Cell Stem Cell 20:771–784.

   https://doi.org/10.1016/j.stem.2017.02.009

   • PubMed
   • Google Scholar
2. 1. Armulik A
   2. Genové G
   3. Betsholtz C

   (2011) Pericytes: developmental, physiological, and pathological perspectives, problems, and promises

   Developmental Cell 21:193–215.

   https://doi.org/10.1016/j.devcel.2011.07.001

   • PubMed
   • Google Scholar
3. 1. Berry R
   2. Rodeheffer MS

   (2013) Characterization of the adipocyte cellular lineage in vivo

   Nature Cell Biology 15:302–308.

   https://doi.org/10.1038/ncb2696

   • PubMed
   • Google Scholar
4. 1. Burl RB
   2. Ramseyer VD
   3. Rondini EA
   4. Pique-Regi R
   5. Lee YH
   6. Granneman JG

   (2018) Deconstructing adipogenesis induced by β3-Adrenergic receptor activation with Single-Cell expression profiling

   Cell Metabolism 28:300–309.

   https://doi.org/10.1016/j.cmet.2018.05.025

   • PubMed
   • Google Scholar
5. 1. Carrière A
   2. Jeanson Y
   3. Côté JA
   4. Dromard C
   5. Galinier A
   6. Menzel S
   7. Barreau C
   8. Dupuis-Coronas S
   9. Arnaud E
   10. Girousse A
   11. Cuminetti V
   12. Paupert J
   13. Cousin B
   14. Sengenes C
   15. Koch-Nolte F
   16. Tchernof A
   17. Casteilla L

   (2017) Identification of the ectoenzyme CD38 as a marker of committed preadipocytes

   International Journal of Obesity 41:1539–1546.

   https://doi.org/10.1038/ijo.2017.140

   • PubMed
   • Google Scholar
6. 1. Chao LC
   2. Bensinger SJ
   3. Villanueva CJ
   4. Wroblewski K
   5. Tontonoz P

   (2008) Inhibition of adipocyte differentiation by Nur77, Nurr1, and Nor1

   Molecular Endocrinology 22:2596–2608.

   https://doi.org/10.1210/me.2008-0161

   • PubMed
   • Google Scholar
7. 1. Chau YY
   2. Bandiera R
   3. Serrels A
   4. Martínez-Estrada OM
   5. Qing W
   6. Lee M
   7. Slight J
   8. Thornburn A
   9. Berry R
   10. McHaffie S
   11. Stimson RH
   12. Walker BR
   13. Chapuli RM
   14. Schedl A
   15. Hastie N

   (2014) Visceral and subcutaneous fat have different origins and evidence supports a mesothelial source

   Nature Cell Biology 16:367–375.

   https://doi.org/10.1038/ncb2922

   • PubMed
   • Google Scholar
8. 1. Church CD
   2. Berry R
   3. Rodeheffer MS

   (2014) Isolation and study of adipocyte precursors

   Methods in Enzymology 537:31–46.

   https://doi.org/10.1016/B978-0-12-411619-1.00003-3

   • PubMed
   • Google Scholar
9. 1. Darimont C
   2. Avanti O
   3. Blancher F
   4. Wagniere S
   5. Mansourian R
   6. Zbinden I
   7. Leone-Vautravers P
   8. Fuerholz A
   9. Giusti V
   10. Macé K

   (2008) Contribution of mesothelial cells in the expression of inflammatory-related factors in omental adipose tissue of obese subjects

   International Journal of Obesity 32:112–120.

   https://doi.org/10.1038/sj.ijo.0803688

   • PubMed
   • Google Scholar
10. 1. Denis GV
    2. Obin MS

    (2013) 'Metabolically healthy obesity': origins and implications

    Molecular Aspects of Medicine 34:59–70.

    https://doi.org/10.1016/j.mam.2012.10.004

    • PubMed
    • Google Scholar
11. 1. Divoux A
    2. Tordjman J
    3. Lacasa D
    4. Veyrie N
    5. Hugol D
    6. Aissat A
    7. Basdevant A
    8. Guerre-Millo M
    9. Poitou C
    10. Zucker JD
    11. Bedossa P
    12. Clément K

    (2010) Fibrosis in human adipose tissue: composition, distribution, and link with lipid metabolism and fat mass loss

    Diabetes 59:2817–2825.

    https://doi.org/10.2337/db10-0585

    • PubMed
    • Google Scholar
12. 1. Gupta RK
    2. Mepani RJ
    3. Kleiner S
    4. Lo JC
    5. Khandekar MJ
    6. Cohen P
    7. Frontini A
    8. Bhowmick DC
    9. Ye L
    10. Cinti S
    11. Spiegelman BM

    (2012) Zfp423 expression identifies committed preadipocytes and localizes to adipose endothelial and perivascular cells

    Cell Metabolism 15:230–239.

    https://doi.org/10.1016/j.cmet.2012.01.010

    • PubMed
    • Google Scholar
13. 1. Gupta OT
    2. Gupta RK

    (2015) Visceral adipose tissue mesothelial cells: living on the edge or just taking up space?

    Trends in Endocrinology & Metabolism 26:515–523.

    https://doi.org/10.1016/j.tem.2015.07.003

    • PubMed
    • Google Scholar
14. 1. Gustafson B
    2. Gogg S
    3. Hedjazifar S
    4. Jenndahl L
    5. Hammarstedt A
    6. Smith U

    (2009) Inflammation and impaired adipogenesis in hypertrophic obesity in man

    American Journal of Physiology-Endocrinology and Metabolism 297:E999–E1003.

    https://doi.org/10.1152/ajpendo.00377.2009

    • PubMed
    • Google Scholar
15. 1. Han J
    2. Lee JE
    3. Jin J
    4. Lim JS
    5. Oh N
    6. Kim K
    7. Chang SI
    8. Shibuya M
    9. Kim H
    10. Koh GY

    (2011) The spatiotemporal development of adipose tissue

    Development 138:5027–5037.

    https://doi.org/10.1242/dev.067686

    • PubMed
    • Google Scholar
16. 1. Hardy OT
    2. Perugini RA
    3. Nicoloro SM
    4. Gallagher-Dorval K
    5. Puri V
    6. Straubhaar J
    7. Czech MP

    (2011) Body mass index-independent inflammation in omental adipose tissue associated with insulin resistance in morbid obesity

    Surgery for Obesity and Related Diseases 7:60–67.

    https://doi.org/10.1016/j.soard.2010.05.013

    • PubMed
    • Google Scholar
17. 1. Hepler C
    2. Gupta RK

    (2017) The expanding problem of adipose depot remodeling and postnatal adipocyte progenitor recruitment

    Molecular and Cellular Endocrinology 445:95–108.

    https://doi.org/10.1016/j.mce.2016.10.011

    • PubMed
    • Google Scholar
18. 1. Hepler C
    2. Vishvanath L
    3. Gupta RK

    (2017) Sorting out adipocyte precursors and their role in physiology and disease

    Genes & Development 31:127–140.

    https://doi.org/10.1101/gad.293704.116

    • PubMed
    • Google Scholar
19. 1. Hill AA
    2. Reid Bolus W
    3. Hasty AH

    (2014) A decade of progress in adipose tissue macrophage biology

    Immunological Reviews 262:134–152.

    https://doi.org/10.1111/imr.12216

    • PubMed
    • Google Scholar
20. 1. Hong KY
    2. Bae H
    3. Park I
    4. Park DY
    5. Kim KH
    6. Kubota Y
    7. Cho ES
    8. Kim H
    9. Adams RH
    10. Yoo OJ
    11. Koh GY

    (2015) Perilipin+ embryonic preadipocytes actively proliferate along growing vasculatures for adipose expansion

    Development 142:2623–2632.

    https://doi.org/10.1242/dev.125336

    • PubMed
    • Google Scholar
21. 1. Hudak CS
    2. Gulyaeva O
    3. Wang Y
    4. Park SM
    5. Lee L
    6. Kang C
    7. Sul HS

    (2014) Pref-1 marks very early mesenchymal precursors required for adipose tissue development and expansion

    Cell Reports 8:678–687.

    https://doi.org/10.1016/j.celrep.2014.06.060

    • PubMed
    • Google Scholar
22. 1. Hung CF
    2. Mittelsteadt KL
    3. Brauer R
    4. McKinney BL
    5. Hallstrand TS
    6. Parks WC
    7. Chen P
    8. Schnapp LM
    9. Liles WC
    10. Duffield JS
    11. Altemeier WA

    (2017) Lung pericyte-like cells are functional interstitial immune sentinel cells

    American Journal of Physiology-Lung Cellular and Molecular Physiology 312:L556–L567.

    https://doi.org/10.1152/ajplung.00349.2016

    • PubMed
    • Google Scholar
23. 1. Jeffery E
    2. Church CD
    3. Holtrup B
    4. Colman L
    5. Rodeheffer MS

    (2015) Rapid depot-specific activation of adipocyte precursor cells at the onset of obesity

    Nature Cell Biology 17:376–385.

    https://doi.org/10.1038/ncb3122

    • PubMed
    • Google Scholar
24. 1. Karastergiou K
    2. Fried SK
    3. Xie H
    4. Lee MJ
    5. Divoux A
    6. Rosencrantz MA
    7. Chang RJ
    8. Smith SR

    (2013) Distinct developmental signatures of human abdominal and gluteal subcutaneous adipose tissue depots

    The Journal of Clinical Endocrinology & Metabolism 98:362–371.

    https://doi.org/10.1210/jc.2012-2953

    • PubMed
    • Google Scholar
25. 1. Kim SM
    2. Lun M
    3. Wang M
    4. Senyo SE
    5. Guillermier C
    6. Patwari P
    7. Steinhauser ML

    (2014) Loss of white adipose hyperplastic potential is associated with enhanced susceptibility to insulin resistance

    Cell Metabolism 20:1049–1058.

    https://doi.org/10.1016/j.cmet.2014.10.010

    • PubMed
    • Google Scholar
26. 1. Kissebah AH
    2. Vydelingum N
    3. Murray R
    4. Evans DJ
    5. Hartz AJ
    6. Kalkhoff RK
    7. Adams PW

    (1982) Relation of body fat distribution to metabolic complications of obesity

    The Journal of Clinical Endocrinology & Metabolism 54:254–260.

    https://doi.org/10.1210/jcem-54-2-254

    • PubMed
    • Google Scholar
27. 1. Klöting N
    2. Fasshauer M
    3. Dietrich A
    4. Kovacs P
    5. Schön MR
    6. Kern M
    7. Stumvoll M
    8. Blüher M

    (2010) Insulin-sensitive obesity

    American Journal of Physiology-Endocrinology and Metabolism 299:E506–E515.

    https://doi.org/10.1152/ajpendo.00586.2009

    • PubMed
    • Google Scholar
28. 1. Klöting N
    2. Blüher M

    (2014) Adipocyte dysfunction, inflammation and metabolic syndrome

    Reviews in Endocrine and Metabolic Disorders 15:277–287.

    https://doi.org/10.1007/s11154-014-9301-0

    • PubMed
    • Google Scholar
29. 1. Krotkiewski M
    2. Björntorp P
    3. Sjöström L
    4. Smith U

    (1983) Impact of obesity on metabolism in men and women. Importance of regional adipose tissue distribution

    Journal of Clinical Investigation 72:1150–1162.

    https://doi.org/10.1172/JCI111040

    • PubMed
    • Google Scholar
30. 1. Lee MJ
    2. Wu Y
    3. Fried SK

    (2010) Adipose tissue remodeling in pathophysiology of obesity

    Current Opinion in Clinical Nutrition and Metabolic Care 13:371–376.

    https://doi.org/10.1097/MCO.0b013e32833aabef

    • PubMed
    • Google Scholar
31. 1. Lee YH
    2. Petkova AP
    3. Mottillo EP
    4. Granneman JG

    (2012) In vivo identification of bipotential adipocyte progenitors recruited by β3-adrenoceptor activation and high-fat feeding

    Cell Metabolism 15:480–491.

    https://doi.org/10.1016/j.cmet.2012.03.009

    • PubMed
    • Google Scholar
32. 1. Lee MJ
    2. Wu Y
    3. Fried SK

    (2013) Adipose tissue heterogeneity: implication of depot differences in adipose tissue for obesity complications

    Molecular Aspects of Medicine 34:1–11.

    https://doi.org/10.1016/j.mam.2012.10.001

    • PubMed
    • Google Scholar
33. 1. Macotela Y
    2. Emanuelli B
    3. Mori MA
    4. Gesta S
    5. Schulz TJ
    6. Tseng YH
    7. Kahn CR

    (2012) Intrinsic differences in adipocyte precursor cells from different white fat depots

    Diabetes 61:1691–1699.

    https://doi.org/10.2337/db11-1753

    • PubMed
    • Google Scholar
34. 1. Marcelin G
    2. Ferreira A
    3. Liu Y
    4. Atlan M
    5. Aron-Wisnewsky J
    6. Pelloux V
    7. Botbol Y
    8. Ambrosini M
    9. Fradet M
    10. Rouault C
    11. Hénégar C
    12. Hulot JS
    13. Poitou C
    14. Torcivia A
    15. Nail-Barthelemy R
    16. Bichet JC
    17. Gautier EL
    18. Clément K

    (2017) A PDGFRα-Mediated Switch toward CD9^high Adipocyte Progenitors Controls Obesity-Induced Adipose Tissue Fibrosis

    Cell Metabolism 25:673–685.

    https://doi.org/10.1016/j.cmet.2017.01.010

    • PubMed
    • Google Scholar
35. 1. Mutsaers SE
    2. Birnie K
    3. Lansley S
    4. Herrick SE
    5. Lim CB
    6. Prêle CM

    (2015) Mesothelial cells in tissue repair and fibrosis

    Frontiers in Pharmacology 6:113.

    https://doi.org/10.3389/fphar.2015.00113

    • PubMed
    • Google Scholar
36. 1. Pei L
    2. Castrillo A
    3. Tontonoz P

    (2006) Regulation of macrophage inflammatory gene expression by the orphan nuclear receptor Nur77

    Molecular Endocrinology 20:786–794.

    https://doi.org/10.1210/me.2005-0331

    • PubMed
    • Google Scholar
37. 1. Rinkevich Y
    2. Mori T
    3. Sahoo D
    4. Xu PX
    5. Bermingham JR
    6. Weissman IL

    (2012) Identification and prospective isolation of a mesothelial precursor lineage giving rise to smooth muscle cells and fibroblasts for mammalian internal organs, and their vasculature

    Nature Cell Biology 14:1251–1260.

    https://doi.org/10.1038/ncb2610

    • PubMed
    • Google Scholar
38. 1. Rodeheffer MS
    2. Birsoy K
    3. Friedman JM

    (2008) Identification of white adipocyte progenitor cells in vivo

    Cell 135:240–249.

    https://doi.org/10.1016/j.cell.2008.09.036

    • PubMed
    • Google Scholar
39. 1. Rodríguez-Calvo R
    2. Tajes M
    3. Vázquez-Carrera M

    (2017) The NR4A subfamily of nuclear receptors: potential new therapeutic targets for the treatment of inflammatory diseases

    Expert Opinion on Therapeutic Targets 21:291–304.

    https://doi.org/10.1080/14728222.2017.1279146

    • PubMed
    • Google Scholar
40. 1. Schwalie PC
    2. Dong H
    3. Zachara M
    4. Russeil J
    5. Alpern D
    6. Akchiche N
    7. Caprara C
    8. Sun W
    9. Schlaudraff KU
    10. Soldati G
    11. Wolfrum C
    12. Deplancke B

    (2018) A stromal cell population that inhibits adipogenesis in mammalian fat depots

    Nature 559:103–108.

    https://doi.org/10.1038/s41586-018-0226-8

    • PubMed
    • Google Scholar
41. 1. Shan B
    2. Wang X
    3. Wu Y
    4. Xu C
    5. Xia Z
    6. Dai J
    7. Shao M
    8. Zhao F
    9. He S
    10. Yang L
    11. Zhang M
    12. Nan F
    13. Li J
    14. Liu J
    15. Liu J
    16. Jia W
    17. Qiu Y
    18. Song B
    19. Han JJ
    20. Rui L
    21. Duan SZ
    22. Liu Y

    (2017) The metabolic ER stress sensor IRE1α suppresses alternative activation of macrophages and impairs energy expenditure in obesity

    Nature Immunology 18:519–529.

    https://doi.org/10.1038/ni.3709

    • PubMed
    • Google Scholar
42. 1. Shao M
    2. Ishibashi J
    3. Kusminski CM
    4. Wang QA
    5. Hepler C
    6. Vishvanath L
    7. MacPherson KA
    8. Spurgin SB
    9. Sun K
    10. Holland WL
    11. Seale P
    12. Gupta RK

    (2016) Zfp423 maintains white adipocyte identity through suppression of the beige cell thermogenic gene program

    Cell Metabolism 23:1167–1184.

    https://doi.org/10.1016/j.cmet.2016.04.023

    • PubMed
    • Google Scholar
43. 1. Shao M
    2. Vishvanath L
    3. Busbuso NC
    4. Hepler C
    5. Shan B
    6. Sharma AX
    7. Chen S
    8. Yu X
    9. An YA
    10. Zhu Y
    11. Holland WL
    12. Gupta RK

    (2018) De novo adipocyte differentiation from Pdgfrβ⁺ preadipocytes protects against pathologic visceral adipose expansion in obesity

    Nature Communications 9:890.

    https://doi.org/10.1038/s41467-018-03196-x

    • PubMed
    • Google Scholar
44. 1. Sun K
    2. Kusminski CM
    3. Scherer PE

    (2011) Adipose tissue remodeling and obesity

    Journal of Clinical Investigation 121:2094–2101.

    https://doi.org/10.1172/JCI45887

    • PubMed
    • Google Scholar
45. 1. Sun K
    2. Tordjman J
    3. Clément K
    4. Scherer PE

    (2013) Fibrosis and adipose tissue dysfunction

    Cell Metabolism 18:470–477.

    https://doi.org/10.1016/j.cmet.2013.06.016

    • PubMed
    • Google Scholar
46. 1. Tang W
    2. Zeve D
    3. Suh JM
    4. Bosnakovski D
    5. Kyba M
    6. Hammer RE
    7. Tallquist MD
    8. Graff JM

    (2008) White fat progenitor cells reside in the adipose vasculature

    Science 322:583–586.

    https://doi.org/10.1126/science.1156232

    • PubMed
    • Google Scholar
47. 1. Unger RH
    2. Scherer PE

    (2010) Gluttony, sloth and the metabolic syndrome: a roadmap to lipotoxicity

    Trends in Endocrinology & Metabolism 21:345–352.

    https://doi.org/10.1016/j.tem.2010.01.009

    • PubMed
    • Google Scholar
48. 1. Vishvanath L
    2. MacPherson KA
    3. Hepler C
    4. Wang QA
    5. Shao M
    6. Spurgin SB
    7. Wang MY
    8. Kusminski CM
    9. Morley TS
    10. Gupta RK

    (2016) Pdgfrβ+ Mural Preadipocytes Contribute to Adipocyte Hyperplasia Induced by High-Fat-Diet Feeding and Prolonged Cold Exposure in Adult Mice

    Cell Metabolism 23:350–359.

    https://doi.org/10.1016/j.cmet.2015.10.018

    • PubMed
    • Google Scholar
49. 1. Wang F
    2. Mullican SE
    3. DiSpirito JR
    4. Peed LC
    5. Lazar MA

    (2013a) Lipoatrophy and severe metabolic disturbance in mice with fat-specific deletion of PPARγ

    PNAS 110:18656–18661.

    https://doi.org/10.1073/pnas.1314863110

    • PubMed
    • Google Scholar
50. 1. Wang QA
    2. Tao C
    3. Gupta RK
    4. Scherer PE

    (2013b) Tracking adipogenesis during white adipose tissue development, expansion and regeneration

    Nature Medicine 19:1338–1344.

    https://doi.org/10.1038/nm.3324

    • PubMed
    • Google Scholar
51. 1. Xu H
    2. Barnes GT
    3. Yang Q
    4. Tan G
    5. Yang D
    6. Chou CJ
    7. Sole J
    8. Nichols A
    9. Ross JS
    10. Tartaglia LA
    11. Chen H

    (2003) Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance

    Journal of Clinical Investigation 112:1821–1830.

    https://doi.org/10.1172/JCI200319451

    • PubMed
    • Google Scholar
52. 1. Yamamoto Y
    2. Gesta S
    3. Lee KY
    4. Tran TT
    5. Saadatirad P
    6. Kahn CR

    (2010) Adipose depots possess unique developmental gene signatures

    Obesity 18:872–878.

    https://doi.org/10.1038/oby.2009.512

    • PubMed
    • Google Scholar

Author details

1. Chelsea Hepler

   Touchstone Diabetes Center, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9938-382X

2. Bo Shan

   Touchstone Diabetes Center, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

3. Qianbin Zhang

   Touchstone Diabetes Center, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Formal analysis, Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

4. Gervaise H Henry

   Department of Urology, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Resources, Formal analysis, Investigation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7772-9578

5. Mengle Shao

   Touchstone Diabetes Center, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Formal analysis, Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5488-9904

6. Lavanya Vishvanath

   Touchstone Diabetes Center, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Resources, Formal analysis, Investigation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

7. Alexandra L Ghaben

   Touchstone Diabetes Center, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Resources, Investigation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7377-7820

8. Angela B Mobley

   Department of Immunology, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Resources, Formal analysis, Supervision, Investigation, Methodology

   Competing interests

   No competing interests declared

9. Douglas Strand

   Department of Urology, University of Texas Southwestern Medical Center, Dallas, United States

   Contribution

   Resources, Formal analysis, Supervision, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0746-927X

10. Gary C Hon

    Cecil H. and Ida Green Center for Reproductive Biology Sciences, Division of Basic Reproductive Biology Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, United States

    Contribution

    Resources, Formal analysis, Supervision, Investigation, Methodology, Writing—review and editing

    Competing interests

    No competing interests declared

11. Rana K Gupta

    Touchstone Diabetes Center, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, United States

    Contribution

    Conceptualization, Formal analysis, Supervision, Funding acquisition, Investigation, Writing—original draft, Project administration, Writing—review and editing

    For correspondence

    Rana.Gupta@UTSouthwestern.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-9001-4531

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