Volume 22, Issue 3, Pages (September 2015)

Slides:



Advertisements
Similar presentations
Volume 6, Issue 4, Pages (April 2017)
Advertisements

Analysis of Positive Selection at Single Nucleotide Polymorphisms Associated with Body Mass Index Does Not Support the “Thrifty Gene” Hypothesis  Guanlin.
Alternative Computational Analysis Shows No Evidence for Nucleosome Enrichment at Repetitive Sequences in Mammalian Spermatozoa  Hélène Royo, Michael Beda.
Temporal Processing and Adaptation in the Songbird Auditory Forebrain
Volume 10, Issue 4, Pages (October 2009)
Volume 26, Issue 16, Pages (August 2016)
Volume 86, Issue 3, Pages (May 2015)
Volume 21, Issue 1, Pages (January 2017)
Jacob Andrade, Shundi Ge, Goar Symbatyan, Michael S. Rosol, Arthur J
Araceli Ramirez-Cardenas, Maria Moskaleva, Andreas Nieder 
Mark S. Blumberg, Cassandra M. Coleman, Ashlynn I. Gerth, Bob McMurray 
Decoding Wakefulness Levels from Typical fMRI Resting-State Data Reveals Reliable Drifts between Wakefulness and Sleep  Enzo Tagliazucchi, Helmut Laufs 
Volume 26, Issue 2, Pages e3 (August 2017)
Frontal Cortex and the Discovery of Abstract Action Rules
Volume 24, Issue 1, Pages (July 2016)
Volume 89, Issue 6, Pages (March 2016)
Jacob Andrade, Shundi Ge, Goar Symbatyan, Michael S. Rosol, Arthur J
Volume 66, Issue 6, Pages (June 2010)
Onset of thymic recovery and plateau of thymic output are differentially regulated after stem cell transplantation in children  Matthias Eyrich, Gernot.
Volume 87, Issue 1, Pages (July 2015)
Volume 20, Issue 6, Pages (December 2014)
Volume 4, Issue 1, Pages (January 2015)
Michael L. Morgan, Gregory C. DeAngelis, Dora E. Angelaki  Neuron 
Volume 14, Issue 2, Pages (February 2014)
Thiazolidinediones Regulate Adipose Lineage Dynamics
Volume 55, Issue 3, Pages (August 2007)
Feature- and Order-Based Timing Representations in the Frontal Cortex
Volume 96, Issue 4, Pages e5 (November 2017)
Volume 19, Issue 6, Pages (June 2014)
Hedging Your Bets by Learning Reward Correlations in the Human Brain
Volume 123, Issue 6, Pages (December 2005)
Volume 11, Issue 5, Pages (May 2015)
The Age of Olfactory Bulb Neurons in Humans
Volume 23, Issue 10, Pages (October 2016)
Volume 3, Issue 1, Pages (July 2016)
The Generality of Parietal Involvement in Visual Attention
Cristina Márquez, Scott M. Rennie, Diana F. Costa, Marta A. Moita 
Jianing Yu, David Ferster  Neuron 
Adaptation Disrupts Motion Integration in the Primate Dorsal Stream
Hippocampal “Time Cells”: Time versus Path Integration
Peter A. Savage, Mark M. Davis  Immunity 
BOLD fMRI Correlation Reflects Frequency-Specific Neuronal Correlation
Sharon C. Furtak, Omar J. Ahmed, Rebecca D. Burwell  Neuron 
Ryo Sasaki, Takanori Uka  Neuron  Volume 62, Issue 1, Pages (April 2009)
Analysis of Positive Selection at Single Nucleotide Polymorphisms Associated with Body Mass Index Does Not Support the “Thrifty Gene” Hypothesis  Guanlin.
Volume 37, Issue 6, Pages (March 2010)
Dynamics of Blood-Borne CD8 Memory T Cell Migration In Vivo
Volume 24, Issue 7, Pages (August 2018)
Volume 86, Issue 3, Pages (May 2015)
Temporal Processing and Adaptation in the Songbird Auditory Forebrain
Volume 11, Issue 3, Pages (September 1999)
Weighing in on Adipocyte Precursors
Volume 66, Issue 3, Pages (September 2004)
Mark S. Blumberg, Cassandra M. Coleman, Ashlynn I. Gerth, Bob McMurray 
Local and Global Contrast Adaptation in Retinal Ganglion Cells
Timing, Timing, Timing: Fast Decoding of Object Information from Intracranial Field Potentials in Human Visual Cortex  Hesheng Liu, Yigal Agam, Joseph.
Timescales of Inference in Visual Adaptation
Daniel E. Winkowski, Eric I. Knudsen  Neuron 
Kevin G. Haworth, Christina Ironside, Zachary K. Norgaard, Willimark M
Identification of White Adipocyte Progenitor Cells In Vivo
Volume 53, Issue 6, Pages (March 2014)
Volume 20, Issue 7, Pages (August 2017)
Encoding of Stimulus Probability in Macaque Inferior Temporal Cortex
Bálint Lasztóczi, Thomas Klausberger  Neuron 
Environmental Consistency Determines the Rate of Motor Adaptation
Below Thermoneutrality, Changes in Activity Do Not Drive Changes in Total Daily Energy Expenditure between Groups of Mice  Sam Virtue, Patrick Even, Antonio.
Volume 2, Issue 3, Pages (March 2008)
Equivalent Parental Contribution to Early Plant Zygotic Development
Volume 26, Issue 16, Pages (August 2016)
Mutational Analysis of Ionizing Radiation Induced Neoplasms
Presentation transcript:

Volume 22, Issue 3, Pages 408-417 (September 2015) Transplanted Bone Marrow-Derived Cells Contribute to Human Adipogenesis  Mikael Rydén, Mehmet Uzunel, Joanna L. Hård, Erik Borgström, Jeff E. Mold, Erik Arner, Niklas Mejhert, Daniel P. Andersson, Yvonne Widlund, Moustapha Hassan, Christina V. Jones, Kirsty L. Spalding, Britt-Marie Svahn, Afshin Ahmadian, Jonas Frisén, Samuel Bernard, Jonas Mattsson, Peter Arner  Cell Metabolism  Volume 22, Issue 3, Pages 408-417 (September 2015) DOI: 10.1016/j.cmet.2015.06.011 Copyright © 2015 Elsevier Inc. Terms and Conditions

Cell Metabolism 2015 22, 408-417DOI: (10.1016/j.cmet.2015.06.011) Copyright © 2015 Elsevier Inc. Terms and Conditions

Figure 1 Selection Process of Individuals Included in the Study Details on the inclusion criteria are described in the Experimental Procedures. Cell Metabolism 2015 22, 408-417DOI: (10.1016/j.cmet.2015.06.011) Copyright © 2015 Elsevier Inc. Terms and Conditions

Figure 2 Contribution of Bone Marrow to the Mature Adipocyte Population and Influence of Body Weight (A) The proportion of donor cells in recipient adipose tissue and isolated fat cells was determined by two independent methods, as described in detail in the Experimental Procedures. The quantitative results were based on the mean value of at least two different polymorphic markers. The percentage of donor-derived cells was considerable in adipose tissue pieces, presumably due to leukocytes present in the capillaries. The donor cell fraction in isolated adipocytes was clearly detectable, although significantly lower (by paired t test). (B) The proportion of donor cells in isolated adipocytes from each subject was related to time since transplantation by linear regression analysis. The regression line for the whole cohort is shown. When dividing the subjects into obese (n = 11, white circles) and non-obese (n = 54, black circles), the regression lines differed significantly (F = 13.3, p = 0.0006 by ANCOVA), but there was no interaction between obesity status and time since transplantation (F = 1.2, p = 0.28). (C) The ratio of donor cells was significantly higher in the obese group compared with non-obese subjects as calculated by unpaired t test. See also Figures S1 and S2 and Table S1. Error bars in (A) and (C) are SEM. Cell Metabolism 2015 22, 408-417DOI: (10.1016/j.cmet.2015.06.011) Copyright © 2015 Elsevier Inc. Terms and Conditions

Figure 3 Mathematical Modeling of BM Contribution to Human Adipogenesis (A) Adipocyte death is matched by integration of newly produced adipocytes in the WAT. Under steady state, the turnover rate r, i.e., the rate at which adipocytes are replaced per year, is constant. BM/PBSC transplant-derived cells contribute PTx cells/year to WAT, out of a total of P new cells/year. The presence of BM/PBSC transplant-derived adipocytes in the WAT reflects the balance between integration of new cells in the tissue and physiological turnover. (B) The proportion f of transplant-derived cells in WAT increases from zero, at the time of transplantation, to reach an equilibrium p = PTx/P, after a time determined by the inverse of the turnover rate (1/r, in years). Pre-transplantation BM-derived adipocytes will be gradually replaced by transplant-derived adipocytes. Under steady-state assumption, the proportion of transplant-derived adipocytes at time t after transplantation is:f(t)=p[1−e−rt] Therefore, the contribution of transplant-derived cells to adipogenesis is given by the observed proportion of cells in WAT corrected by a factor depending on the time elapsed since transplantation:p=f(t)1−e−rt See also Supplemental Experimental Procedures for more details. Cell Metabolism 2015 22, 408-417DOI: (10.1016/j.cmet.2015.06.011) Copyright © 2015 Elsevier Inc. Terms and Conditions

Figure 4 Contribution of Bone Marrow to the Mature Adipocyte Population and Influence of Body Weight (A) The contribution of donor cells to the adipocyte population under steady-state conditions (donor cell production rate) was determined using the mathematical model described in Figure 3. This ratio was strongly influenced by BMI, with a proportional increase in donor adipocytes in individuals of higher weight classes as determined by analysis of variance (p = 0.004). Results from post hoc tests are indicated by brackets (∗p < 0.05, ∗∗p < 0.01), and the number of subjects in each weight class is indicated. (B) There was a statistically significant relationship between BMI and donor cell production rate as determined by linear regression analysis (n = 65). (C) The donor cell production rate was higher in subjects who had received PBSC compared with BM (by unpaired t test). Error bars in panels are SEM. Regression coefficients and p values are indicated. See also Figures S3A–S3G. Cell Metabolism 2015 22, 408-417DOI: (10.1016/j.cmet.2015.06.011) Copyright © 2015 Elsevier Inc. Terms and Conditions

Figure 5 Laser Capture Microdissection, Exome Sequencing, and Whole-Genome Sequencing of Single Adipocytes Isolated from Study Subject 1 (A) Representative photomicrographs of individual mature fat cells isolated from study subject 1 prior to capture. Triglycerides were stained with BODIPY and nuclei with Hoescht. Cells were isolated using laser capture microdissection, their genomes amplified using whole-genome amplification, and exomes and genomes were sequenced in order to determine their genotypes. The individual cells are cell #2, cell #10, and cell #16, and their corresponding genotypes, determined by exome and whole-genome sequencing, are shown in (B) and (C), respectively. Scale bar is 100 μm. (B) Exome-wide distribution of donor- and recipient-specific homozygous SNPs in single adipocytes isolated from study subject 1. Only samples with five or more variants passing the filters were included. Each row represents a sample, and each column represents a SNP position; the top two rows represent donor (pink) and recipient (blue) whole-blood gDNA while the rows below represent analyses of gDNA from single cells. All homozygous SNPs that differ between the donor and recipient and from which at least one single cell displays a signal above the defined threshold are depicted. Each detected SNP in the single cells has been assigned a color depending on whether the genotype at that position corresponds to the donor (pink), the recipient (blue), or both (yellow). Positions where no signals above the defined thresholds were detected are depicted in gray. Out of 27 analyzed cells from this subject, cell #10 displayed mixed genotypes, cell #16 displayed donor-specific genotypes, and the remaining cells, represented here by cell #2, displayed recipient-specific genotypes. Further descriptions are found in the Supplemental Information and Figures S4 and S5. (C) The classification of cell origin of cell #2, cell #10, and cell #16 determined by exome sequencing was confirmed by whole-genome sequencing. Circle plots detail the number of detected donor, recipient, and mixed variants across the entire genome identified in these three cells. Cell Metabolism 2015 22, 408-417DOI: (10.1016/j.cmet.2015.06.011) Copyright © 2015 Elsevier Inc. Terms and Conditions