| Literature DB >> 22128816 |
Qiang Shi1, Laura A Cox, Vida Hodara, Xing Li Wang, John L VandeBerg.
Abstract
To determine in the baboon model the identities and functional characteristics of endothelial progenitor cells (EPCs) mobilized in response to artery ligation, we collected peripheral blood mononuclear cells (PBMNCs) before and 3 days after a segment of femoral artery was removed. Our goal was to find EPC subpopulations with highly regenerative capacity. We identified 12 subpopulations of putative EPCs that were altered >1.75-fold; two subpopulations (CD146+/CD54-/CD45- at 6.63-fold, and CD146+/UEA-1-/CD45- at 12.21-fold) were dramatically elevated. To investigate the regenerative capacity of putative EPCs, we devised a new assay that maximally resembled their in vivo scenario, we purified CD34+ and CD146+ cells and co-cultured them with basal and mobilized PBMNCs; both cell types took up Dil-LDL, but purified CD146+ cells exhibited accelerated differentiation by increasing expression of CD31 and CD144, and by exhibiting more active cord-like structure formation by comparison to the CD34+ subpopulation in a co-culture with mobilized PBMNCs. We demonstrate that ischaemia due to vascular ligation mobilizes multiple types of cells with distinct roles. Baboon CD146+ cells exhibit higher reparative capacity than CD34+ cells, and thus are a potential source for therapeutic application.Entities:
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Year: 2012 PMID: 22128816 PMCID: PMC3433842 DOI: 10.1111/j.1582-4934.2011.01501.x
Source DB: PubMed Journal: J Cell Mol Med ISSN: 1582-1838 Impact factor: 5.310
Antibodies used for flow cytometry and for immunofluorescence
| Antibodies with conjugate | Vendor and catalogue no. | Clone | Volume/106 cells or dilutions used |
|---|---|---|---|
| CD34-PE | BD Biosciences #550619 | 563 | 10 μl |
| CD31-FITC | BD Biosciences #557508 | WM59 | 5 μl |
| CD117-APC | BD Biosciences #550412 | YB5.B8 | 5 μl |
| CD45-PerCP | BD Biosciences #558411 | DO58-1283 | 5 μl |
| CD146-PE | R&D Systems FAB932P | 12808 | 10 μl |
| CD54-APC | BD Biosciences #559771 | HA58 | 10 μl |
| CXCR4-APC | BioLegend #306510 | 12G5 | 5 μl |
| CD181-FITC | BioLegend #320605 | 8F1 | 5 μl |
| UEA-1-FITC | Sigma #9006 | 3 μl | |
| CD195-APC | BD Biosciences #550856 | 3A9 | 5 μl |
| VEGFR3-PE | R&D Systems #FAB3492P | 54733 | 5 μl |
| CD14-FITC | Beckman-Coulter #6603511 | MY4 | 5 μl |
| CD144 (VE-Cadherin) | Cell Signaling #2500 | Rabbit IgG | 1:400 |
| CD62E-FITC | R&D Systems #BBA21 | BB1G-E5 | 1:50 |
| Anti-rabbit with Texas Red | Santa Cruz #sc-2780 | Goat IgG | 1:400 |
Quantification of responsive cells due to ischaemic treatment (cells/μl)
| Number of positive cells/μl | Fold change | |||
|---|---|---|---|---|
| Day 0 | Day 3 | (Day 3/0) | ||
| CD34+/CD31+/CD45– | 32.91 ± 25.80 | 56.04 ± 80.74 | 0.49 | |
| CD34+/CD195+/CD45– | 77.73 ± 125.83 | 23.48 ± 35.33 | 0.15 | |
| CD34+/CXCR4+/CD45– | 16.21 ± 24.62 | 14.20 ± 16.41 | 0.87 | 0.81 |
| CD34+/CD14+ | 62.56 ± 63.90 | 49.34 ± 47.34 | 0.78 | 0.14 |
| CD34+/CD14+/CD45– | 34.69 ± 44.21 | 147.7 ± 281.9 | 0.31 | |
| CD117+/CD45– | 22.94 ± 26.57 | 47.17 ± 35.34 | 0.20 | |
| CD117+/CD31+/CD45– | 8.04 ± 7.03 | 37.03 ± 43.40 | 0.10 | |
| CD117+/CD34+/CD45+ | 0.34 ± 0.53 | 0.56 ± 0.58 | 0.23 | |
| CD117+/CD34+/CD45– | 14.64 ± 22.01 | 36.35 ± 30.47 | 0.20 | |
| CD146+/CD54–/CD45– | 48.22 ± 34.19 | 319.85 ± 220.75 | 0.009* | |
| CD146+/UEA-1+/CD45– | 8.89 ± 16.64 | 108.6 ± 171.5 | 0.14 | |
| CD146+/CD54+/CD45– | 10.51 ± 14.55 | 10.04 ± 13.28 | 0.95 | 0.93 |
| CD54+/UEA-1+/CD45– | 10.12 ± 15.71 | 15.76 ± 32.89 | 0.69 | |
| VEGFR3+/CD181+/CD45– | 16.33 ± 18.31 | 42.95 ± 53.14 | 0.20 | |
| VEGFR3+/CD45– | 58.24 ± 38.69 | 109.85 ± 58.65 | 0.03* | |
| VEGFR3+/CXCR4+ | 2.48 ± 1.32 | 2.59 ± 1.91 | 1.04 | 0.58 |
| VEGFR3+/CXCR4+/CD45– | 32.59 ± 37.75 | 60.38 ± 46.22 | 0.03* | |
| CXCR4+/CD14+/CD45– | 30.47 ± 51.85 | 63.48 ± 154.28 | 0.66 | |
| CXCR4+/CD181+/CD45– | 11.08 ± 12.48 | 56.88 ± 118.37 | 0.35 | |
Measures are mean ± S.D., n= 8, *P < 0.05 t-test, mobilized (Day 3) versus basal (Day 0) measures. Values in bold represent >1.75 criteria.
Ontology analysis of molecular and cellular components up-regulated at 3 days compared with 0 day
| Annotation | Gene set | z-score |
|---|---|---|
| Angiogenesis-mediated signalling pathway | ||
| Regulation of BMP signalling pathway | 26 | 5.97 |
| Transmembrane receptor protein serine/threonine kinase signalling pathway | 139 | 4.95 |
| BMP signalling pathway | 60 | 3.8 |
| Regulation of transforming growth factor β receptor signalling pathway | 68 | 3.54 |
| Transforming growth factor β receptor signalling pathway | 114 | 2.6 |
| Cytokine related | ||
| Cytokine biosynthetic process | 83 | 3.15 |
| Cytokine metabolic process | 84 | 3.13 |
| Enzyme-linked receptor protein signalling pathway | 416 | 2.45 |
| Cell response to stress | ||
| Nucleus organization | 48 | 4.3 |
| Positive regulation of cellular process | 1664 | 3.51 |
| Positive regulation of biological process | 1832 | 3.24 |
| Positive regulation of cell communication | 298 | 3.1 |
| Intracellular signalling cascade | 1501 | 2.96 |
| Cellular component disassembly | 116 | 2.57 |
| Cell communication | 3954 | 2.33 |
| Cellular response to stimulus | 979 | 2.07 |
| Defence response | 628 | 1.73 |
| Inflammatory reactions | ||
| Inflammatory response | 349 | 2.78 |
| Regulation of immune system process | 357 | 2.74 |
| Viral reproduction | 82 | 3.17 |
| Regulation of immune system process | 357 | 2.74 |
| Leukocyte-mediated immunity | 126 | 2.44 |
| Immune system process | 1013 | 2 |
| Cell differentiation | ||
| Erythrocyte differentiation | 57 | 3.91 |
| Osteoblast differentiation | 3.6 | 3.58 |
| Positive regulation of developmental process | 641 | 2.96 |
| Gonad development | 103 | 2.77 |
| Myeloid cell differentiation | 140 | 2.27 |
| Muscle tissue development | 168 | 2.01 |
| Cell or tissue repair | ||
| DNA repair | 278 | 3.25 |
| Cellular response to DNA damage stimulus | 325 | 2.93 |
| Response to DNA damage stimulus | 359 | 2.73 |
| Homeostasis of number of cells | 112 | 2.63 |
| Multicellular organism reproduction | 121 | 2.5 |
| Reproductive process in a multicellular organism | 121 | 2.5 |
| Positive regulation of apoptosis | 416 | 2.45 |
| Positive regulation of programmed cell death | 419 | 2.44 |
| Positive regulation of cell death | 421 | 2.43 |
| Cellular protein metabolic process | 2492 | 2.39 |
| Positive regulation of protein kinase cascade | 160 | 2.08 |
| Cellular biopolymer metabolic process | 5649 | 1.74 |
| Cellular macromolecule metabolic process | 5763 | 1.68 |
| Cellular biopolymer catabolic process | 691 | 1.58 |
| Biopolymer metabolic process | 6067 | 15 |
z-score, calculated in GeneSifter, detailed formula is presented in Materials and methods section.
Ontology analysis of molecular and cellular components down-regulated at 3 days compared with 0 days
| Annotation | Gene set | z-score |
|---|---|---|
| Signalling pathways | ||
| Positive regulation of stress-activated protein kinase signalling pathway | 20 | 4.12 |
| JNK cascade | 90 | 2.91 |
| Stress-activated protein kinase signalling pathway | 98 | 2.64 |
| Negative regulation of transforming growth factor β receptor signalling pathway | 32 | 2.86 |
| Regulation of stress-activated protein kinase Signalling pathway | 66 | 2.58 |
| Positive regulation of MAPKKK cascade | 45 | 2.05 |
| Cell metabolic process | ||
| Primary metabolic process | 7305 | 3.28 |
| Protein modification process | 1498 | 3.26 |
| mRNA processing | 322 | 3.17 |
| Protein amino acid dephosphorylation | 132 | 3.17 |
| Metabolic process | 8049 | 3.13 |
| Cellular macromolecule metabolic process | 5763 | 3.13 |
| Negative regulation of translation | 29 | 3.11 |
| DNA catabolic process | 55 | 3.1 |
| Nucleobase, nucleoside, nucleotide and nucleic acid metabolic process | 4103 | 2.95 |
| Cellular activity regulations | ||
| Cellular metabolic process | 7158 | 2.8 |
| Protein ubiquitination | 129 | 2.77 |
| Cellular biopolymer catabolic process | 691 | 2.31 |
| Negative regulation of cell communication | 233 | 2.25 |
| Regulation of cell communication | 927 | 2.02 |
| Regulation of macromolecule biosynthetic process | 2645 | 2.01 |
| Regulation of kinase activity | 339 | 2 |
| Enzyme-linked receptor protein signalling pathway | 416 | 1.65 |
z-score, calculated in GeneSifter, detailed formula is presented in Materials and methods section.
Fig 1Effects of basal and mobilized PBMCs on endothelial proliferation and migration. Wounded ECs were cultured under medium without (A) and with (B) endothelial growth factor supplements for 24 hrs, as negative and positive controls. When mobilized PBMNCs were co-cultured for 24 hrs with the wounded EC layer in the absence of endothelial growth factors, wound healing was accelerated as evidenced by more rapid endothelial proliferation and migration (C) by comparison with basal PBMNCs (D). Significant differences (P < 0.05) existed in the width of the wound after the healing process for wounds treated with mobilized cells (light grey) versus basal cells (dark grey) versus negative control (black) as shown in (E). Original magnification, χ200.
Fig 2Microscopic assessment of CD34+ and CD146+ EPC differentiation. Microscopic characteristics of enriched CD34+ (A–C) and CD146+ (D–F) EPCs co-cultured with basal PBMNCs (A and D) and mobilized PBMNCs (B and C, E and F). Co-culture with mobilized PBMNCs increased the cell number (B and E). More endothelial-like cells with cobblestone shape grew when co-cultured with mobilized PBMNCs (E and F), while more star-like cells dominated when CD34+ cells were co-cultured with basal PBMNCs (B and C). Original magnification: χ200 (A and B, D and E); original magnification: χ400 (C, F).
Late-outgtowth colony formation unit of enriched CD34+ and CD146+ cells co-cultured with basal and mobilized PBMNCs
| CD34+ (colony units/103 cells seeded) | CD146+ (colony units/103 cells seeded) | |
|---|---|---|
| Basal PBMNCs | ||
| Mean ± SD | 1.33 ± 0.74 | 2.00 ± 1.00 |
| Range | 0–2 | 1–4 |
| | 6 | 6 |
| Mobilized PBMNCs | ||
| Mean ± SD | 2.66 ± 1.06 | 5.16 ± 1.06 |
| Range | 1–4 | 4–7 |
| | 6 | 6 |
P < 0.05 mobilized PBMNCs versus basal PBMNCs;
P < 0.05 mobilized CD146+ cells versus mobilized CD34+ cells.
Fig 3Effects of mobilized PBMNCs on CD34+ and CD146+ cell differentiation. CD34+ (A–C) and CD146+ (D–F) positive cells were seeded on cover slips and cultured for 3 weeks after which their endothelial specific antigen expression was examined. Green: CD31 (A and D), CD144 (B and E), CD62E (C and F); red: Dil-LDL; blue: DAPI. (A–F) Original magnification, χ600. CD34 (G–I) and CD146 (J–L) positive selected cells were seeded on Matrigel for the tube formation test. After 4 hrs (G, J), 18 hrs (H, K) and 96 hrs (I, L), images were taken using an inverted microscope at 200χ. CD146+ progenitor cells formed longer tubes (length) and more interconnections (branching) than CD34 progenitor cells under the same culture conditions. M: mean ± S.D. of the length and branching number (sum of the numbers under each of three random low power fields) for the two cell types, respectively; n= 3, *P < 0.05 between two groups.
Fig 4Mechanism of ischaemia mobilized cellular components and their interrelationship in neovascularization using baboon femoral artery ligation. After animals were treated, ischaemia was introduced and led to multiple signalling pathway activations, resulting in progenitor mobilizations. Mobilized progenitor cells included haematopoietic stem cells as well as vascular/endothelial stem cells in order to resume local circulation. Several types of endothelial progenitor cells with distinct functionalities might cooperate and orchestrate to provide neovascular blocks (CD146+ subpopulation) as well as proangiogenic environments (CD34+ subpopulation) for progenitor cells to home and grow. The solid lines mean well-accepted mechanisms; the dashed lines mean alternative proposed pathways.