16 research outputs found
Mice with a Targeted Deletion of the Type 2 Deiodinase Are Insulin Resistant and Susceptible to Diet Induced Obesity
The type 2 iodothyronine deiodinase (D2) converts the pro-hormone thyroxine into T3 within target tissues. D2 is essential for a full thermogenic response of brown adipose tissue (BAT), and mice with a disrupted Dio2 gene (D2KO) have an impaired response to cold. BAT is also activated by overfeeding.After 6-weeks of HFD feeding D2KO mice gained 5.6% more body weight and had 28% more adipose tissue. Oxygen consumption (V0(2)) was not different between genotypes, but D2KO mice had an increased respiratory exchange ratio (RER), suggesting preferential use of carbohydrates. Consistent with this, serum free fatty acids and β-hydroxybutyrate were lower in D2KO mice on a HFD, while hepatic triglycerides were increased and glycogen content decreased. Neither genotype showed glucose intolerance, but D2KO mice had significantly higher insulin levels during GTT independent of diet. Accordingly, during ITT testing D2KO mice had a significantly reduced glucose uptake, consistent with insulin resistance. Gene expression levels in liver, muscle, and brown and white adipose tissue showed no differences that could account for the increased weight gain in D2KO mice. However, D2KO mice have higher PEPCK mRNA in liver suggesting increased gluconeogenesis, which could also contribute to their apparent insulin resistance.We conclude that the loss of the Dio2 gene has significant metabolic consequences. D2KO mice gain more weight on a HFD, suggesting a role for D2 in protection from diet-induced obesity. Further, D2KO mice appear to have a greater reliance on carbohydrates as a fuel source, and limited ability to mobilize and to burn fat. This results in increased fat storage in adipose tissue, hepatic steatosis, and depletion of liver glycogen in spite of increased gluconeogenesis. D2KO mice are also less responsive to insulin, independent of diet-induced obesity
Real-Time Monitoring of Tumorigenesis, Dissemination, & Drug Response in a Preclinical Model of Lymphangioleiomyomatosis/Tuberous Sclerosis Complex
Background: TSC2-deficient cells can proliferate in the lungs, kidneys, and other organs causing devastating progressive multisystem disorders such as lymphangioleiomyomatosis (LAM) and tuberous sclerosis complex (TSC). Preclinical models utilizing LAM patient-derived cells have been difficult to establish. We developed a novel animal model system to study the molecular mechanisms of TSC/LAM pathogenesis and tumorigenesis and provide a platform for drug testing. Methods and Findings: TSC2-deficient human cells, derived from the angiomyolipoma of a LAM patient, were engineered to co-express both sodium-iodide symporter (NIS) and green fluorescent protein (GFP). Cells were inoculated intraparenchymally, intravenously, or intratracheally into athymic NCr nu/nu mice and cells were tracked and quantified using single photon emission computed tomography (SPECT) and computed tomography (CT). Surprisingly, TSC2-deficient cells administered intratracheally resulted in rapid dissemination to lymph node basins throughout the body, and histopathological changes in the lung consistent with LAM. Estrogen was found to be permissive for tumor growth and dissemination. Rapamycin inhibited tumor growth, but tumors regrew after the drug treatment was withdrawn. Conclusions: We generated homogeneous NIS/GFP co-expressing TSC2-deficient, patient-derived cells that can proliferate and migrate in vivo after intratracheal instillation. Although the animal model we describe has some limitations, we demonstrate that systemic tumors formed from TSC2-deficient cells can be monitored and quantified noninvasively over time using SPECT/CT, thus providing a much needed model system for in vivo drug testing and mechanistic studies of TSC2-deficient cells and their related clinical syndromes
Structure, function and diversity of the healthy human microbiome
Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in
part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273
to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander;
U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.;
U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.;
R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.;
R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to
D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and
R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.;
R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was
supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves
and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang,
F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J.
V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.);
DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research;
U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and
R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and
D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research
Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF
DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US
Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL
Laboratory-Directed Research and Development grant 20100034DR and the US
Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research
Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career
Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe
J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by
the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial
Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of
Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis
of the HMPdata was performed using National Energy Research Scientific Computing
resources, the BluBioU Computational Resource at Rice University
A framework for human microbiome research
A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies
High-Resolution Computed Tomography of Single Breast Cancer Microcalcifications in Vivo
Microcalcification is a hallmark of breast cancer and a key diagnostic feature for mammography. We recently described the first robust animal model of breast cancer microcalcification. In this study, we hypothesized that high-resolution computed tomography (CT) could potentially detect the genesis of a single microcalcification in vivo and quantify its growth over time. Using a commercial CT scanner, we systematically optimized acquisition and reconstruction parameters. Two ray-tracing image reconstruction algorithms were tested: a voxel-driven “fast” cone beam algorithm (FCBA) and a detector-driven “exact” cone beam algorithm (ECBA). By optimizing acquisition and reconstruction parameters, we were able to achieve a resolution of 104 μm full width at half-maximum (FWHM). At an optimal detector sampling frequency, the ECBA provided a 28 μm (21%) FWHM improvement in resolution over the FCBA. In vitro, we were able to image a single 300 μm X 100 μm hydroxyapatite crystal. In a syngeneic rat model of breast cancer, we were able to detect the genesis of a single microcalcification in vivo and follow its growth longitudinally over weeks. Taken together, this study provides an in vivo “gold standard” for the development of calcification-specific contrast agents and a model system for studying the mechanism of breast cancer microcalcification
Differential response to radiation treatment in molecular subtypes of diffuse large B-Cell lymphoma (DLBCL).
Lymph node metastasis and invasion by TSC2-deficient cells.
<p>A. Normal lymph node (LN; top row) and lymph node identified by GFP and NIS expression (bottom row) 4 weeks after intratracheal administration of 621-327 cells. Left column shows <i>in vivo</i> color video image. Right columns show same nodes <i>ex vivo</i> after resection, placement on black paper, and imaging using color video, GFP fluorescence, and SPECT/CT, respectively. Scale bars = 1 mm. B. Hematoxylin and eosin (H&E) staining of frozen sections from normal (top row) and tumor-infiltrated (bottom row) lymph nodes 2 weeks after intratracheal administration of 621-327 cells. Dotted rectangle inset  =  higher magnification. Consecutive tissue sections were also stained with anti-GFP antibody. Scale bars = 50 µm. C. H&E staining of paraffin-embedded, tumor-infiltrated lymph nodes at 15 weeks post-administration of 621-327 cells. Dotted rectangle inset  =  higher magnification. Scale bars = 50 µm.</p
The effect of sex and exogenous estrogen on TSC2-deficient tumor growth.
<p>Female (left) or male (right) mice were implanted with 0.18 mg 17ß-estradiol pellets or control placebo pellets subcutaneously. Ten days later, 621-327 cells were administered intratracheally and tumors quantified every other week by SPECT/CT. Shown are the results after 4 weeks of hormone treatment. T  =  thyroid; S  =  stomach; B  =  bladder. Arrows indicate tumors. Scale bars  = 1 cm. +/−  = 0.3–1.4; +  = 1.5 - 2.5; ++  = 2.6–3.7; +++  =  ≥3.8%ID/mm<sup>3</sup> (×10<sup>−5</sup>).</p
Quantitation of LAM/TSC tumor response to drug treatment.
<p>A. Typical SPECT/CT images of mice treated with rapamycin or vehicle for 4 weeks (i.e., 6 weeks after intratracheal administration of 621-327 cells). T  =  thyroid; S  =  stomach; B  =  bladder. Arrows indicate tumors. Scale bars = 1 cm. B.<sup> 99m</sup>Tc-pertechnetate uptake in LAM/TSC tumors before, during, and after treatment with rapamycin or vehicle control. 621-327 cells were administered intratracheally at time = 0. Rapamycin treatment was during weeks 2 to 6. Mice were followed an additional 2 weeks off drug.</p
Generation and characterization of <i>in vivo</i> trackable TSC2-deficient cells.
<p>A. Expression cassettes of adenoviral (Ad-NIS/GFP) and retroviral (Retro-NIS/GFP) vectors. CMV  =  cytomegalovirus promoter, NIS  =  sodium-iodide symporter, LITR  =  left-handed inverted terminal repeat, RITR  =  right-handed inverted terminal repeat, GFP  =  green fluorescent protein, ΔE1, ΔE3 =  E1 and E3 deletions of adenovirus type 5 (Ad5) backbone sequence, 5′ LTR = 5′ long terminal repeat, φ signal  =  virus packing signal, IRES  =  internal ribosome entry site, 3′ LTR  = 3′ long terminal repeat. B. <i>In vitro</i> uptake of <sup>99m</sup>Tc-pertechnetate and GFP fluorescence in stable Retro-NIS−/GFP-expressing 621-327 cells (top row) and control 621-101 cells (bottom row). Scale bar = 6 mm. C. Immunofluorescent detection of GFP, NIS, and tuberin in TSC2-deficient 621-327 cells (top row), control 621-101 cells (middle row), and HeLa cells (bottom row). GFP fluorescence (2nd column), staining with primary anti-NIS specific antibody (3rd column) or anti-tuberin antibody (right column) with secondary Cy3 antibody conjugates is shown along with phase contrast (left column). Scale bar = 50 µm. D. Western blot analysis of TSC2-expressing HEK293T control cells, and TSC2-deficient 621-101 cells and 621-327 cells, using antibodies to key signaling proteins, NIS, and GFP. A beta actin loading control is also shown, as are long exposure times (long exp.) for tuberin and hamartin.</p