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Schematic schedule of the CD133+ cell isolation process using the CliniMACS Prodigy® BM-133 system. Gray: manual steps (two operators); green: semi-automatic steps (one operator, dual control); blue: automatic steps. (PDF 1368 kb)

Schematic schedule of the CD133+ cell isolation process using the CliniMACS Prodigy® BM-133 system. Gray: manual steps (two operators); green: semi-automatic steps (one operator, dual control); blue: automatic steps. (PDF 1368 kb)

Phenotypic and morphologic characterization of non-target cell populations presented in the automatically generated cell product (CP). Non-target cell populations were subdivided into three fractions: CD45+/CD34− (region J) and CD45+/CD34low (region Q) (a); CD45+/CD34+/CD133− (region I) (b). CD45+/CD34-/low non-target cells were further analyzed concerning their CD133 expression (regions M and R, respectively). Size and granularity of all three fractions were evaluated: region K and T: smaller than target cell population; region O, S and P: same size/granularity than target cell population; region L: higher granularity than target cell population. (PDF 130 kb)

Uptake of acetylated low-density lipoprotein (acLDL) of colony-forming unit endothelial cell (CFU-EC) assay-derived cells. CFU-EC assay was performed and after 29 days incubation the uptake of acLDL (green) was examined by immunostaining in non-adherent cells. Nuclei were stained with Hoechst dye (blue). Pictures were taken using ELYRA PS.1 LSM 780 microscope (Carl Zeiss GmbH). Images of manually (a and b) and automatically (c and d) isolated cells. Scale bars: 100 μm (a and c) and 20 μm (b and d). (PDF 341 kb)

List of antibodies used for flow cytometry-based quality control of manually isolated CD133+ stem cells and for the characterization of stemness marker expression in the automatically generated cell product. (DOC 33Â kb)

Schematic representation of two different logistical procedures used for the manufacturing of stem cell products in cardiovascular regenerative medicine. Manual/semi-automatic systems require centralized GMP-compliant manufacturing by an external service provider (a). Entirely closed systems such as the automatic CliniMACS Prodigy® enable decentralized GMP-compliant manufacturing by an in-house facility (b). a Centralized GMP-compliant manufacturing by an external service provider: few specialized contractors are available for a distinct cell product because standardized high-level clean rooms (Class A in B) and sophisticated training are required for the manual or semi-automatic manufacturing. This results in higher costs of the therapy due to an increased logistical effort (e.g., long-distance transportation) and longer hospitalization of the patients as well as a possible loss of cell product quality (e.g., CliniMACS® Plus). b Decentralized GMP-compliant manufacturing by an in-house facility: cell products intended for clinical application can be manufactured on-site owing to reduced clean room requirements (Class A in D) and easier standardization of processes with minimized inter-individual variability due to automatic manufacturing. Lower logistical effort (in-house transport) and shorter hospitalization enables minimized costs plus a better and stable quality of the cell product (e.g., CliniMACS Prodigy®). (PDF 109 kb)

Phenotypic and morphologic characterization of non-target cell populations presented in the automatically generated cell product (CP). Non-target cell populations were subdivided into three fractions: CD45+/CD34− (region J) and CD45+/CD34low (region Q) (a); CD45+/CD34+/CD133− (region I) (b). CD45+/CD34-/low non-target cells were further analyzed concerning their CD133 expression (regions M and R, respectively). Size and granularity of all three fractions were evaluated: region K and T: smaller than target cell population; region O, S and P: same size/granularity than target cell population; region L: higher granularity than target cell population. (PDF 130 kb)

Overview of data obtained from manual cell isolation. Volumes of bone marrow (BM) samples were ascertained by visual control. Total numbers of viable CD133+ cells were determined using Neubauer hemocytometer. The frequencies of viable CD133+ cells were measured by flow cytometry in accordance with ISHAGE guidelines. (DOC 36Â kb)

Representative ISHAGE-based gating strategy used for the quality control of the automatically generated cell product (CP). Debris was excluded from CD45+ cells (a). CD34+ cells were selected from viable CD45+ cells (b). Events with high expression of the CD45 marker were excluded from viable CD45+/CD34+cells (c). FSC/SSC backgate was employed to select viable CD45+/CD34+ hematopoietic progenitor cells (HPCs) with blast morphology (d). Viable CD45+/CD34+/CD133+ cells were selected (e). Events with high expression of the CD45 marker were excluded from viable CD45+/CD34+/CD133+ cells (f). FSC/SSC backgate was employed to select viable CD45+/CD34+/CD133+ HPCs with blast morphology (g). A control gate (‘Ly’, lymphocytes) was used during exclusion of mature CD45+ HSCs. Red: target cell population. Gray: dead cells. (PDF 374 kb)

Overview of data obtained from CliniMACS® Prodigy BM-133 System validation process (a) and product quality review (PQR) (b). Volumes of samples were ascertained by visual control (bone marrow (BM)) or by weighing (cell product (CP), non-target cell bag (NTCB), waste bag (WB)). Total numbers of viable CD45+ and CD133+ cells were calculated by multiplying absolute cell numbers per volume unit with corresponding volumes. The frequencies of viable CD133+ cells were measured by flow cytometry in accordance with ISHAGE guidelines. (DOC 42 kb)

Von Willebrand factor (vWF) expression of colony-forming unit endothelial cell (CFU-EC) assay-derived cells. CFU-EC assay was performed and after 29 days incubation the vWF expression (green) was examined by immunostaining in non-adherent cells. Nuclei were stained with Hoechst dye (blue). Pictures were taken using ELYRA PS.1 LSM 780 microscope (Carl Zeiss GmbH). Images of manually (a and b) and automatically (c and d) isolated cells. Scale bars: 100 μm (a and c) and 20 μm (b and d). (PDF 295 kb)

Determination of apoptotic and necrotic cells in the automatically generated cell product (CP) after storage. The percentage of viable, early-stage apoptotic, late-stage apoptotic and necrotic cells was analyzed by flow cytometric measurements using Annexin V Apoptosis Detection Kit. Samples of CP were taken at the respective storage time. All data are presented as a mean ± SEM. n = 3. *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001. (PDF 108 kb)

List of antibodies used for flow cytometry-based quality control of manually isolated CD133+ stem cells and for the characterization of stemness marker expression in the automatically generated cell product. (DOC 33Â kb)

Stemness marker expression of target and non-target cell fractions presented in the automatically generated cell product (CP). For phenotype characterization the expression of stemness markers (CD117, CD184, CD309, CD14) was evaluated in target cells (CD45+CD34+CD133+) (a) and non-target cells (CD45+CD34−CD133−, CD45+CD34lowCD133−, CD45+CD34+CD133−) (b) using flow cytometry. The respective analysis was made in accordance with ISHAGE guidelines. Data are presented as a mean ± SEM, n = 9. (DOC 37 kb)

Overview of data obtained from manual cell isolation. Volumes of bone marrow (BM) samples were ascertained by visual control. Total numbers of viable CD133+ cells were determined using Neubauer hemocytometer. The frequencies of viable CD133+ cells were measured by flow cytometry in accordance with ISHAGE guidelines. (DOC 36Â kb)

Overview of data obtained from CliniMACS® Prodigy BM-133 System validation process (a) and product quality review (PQR) (b). Volumes of samples were ascertained by visual control (bone marrow (BM)) or by weighing (cell product (CP), non-target cell bag (NTCB), waste bag (WB)). Total numbers of viable CD45+ and CD133+ cells were calculated by multiplying absolute cell numbers per volume unit with corresponding volumes. The frequencies of viable CD133+ cells were measured by flow cytometry in accordance with ISHAGE guidelines. (DOC 42 kb)

Representative ISHAGE-based gating strategy used for the quality control of the automatically generated cell product (CP). Debris was excluded from CD45+ cells (a). CD34+ cells were selected from viable CD45+ cells (b). Events with high expression of the CD45 marker were excluded from viable CD45+/CD34+cells (c). FSC/SSC backgate was employed to select viable CD45+/CD34+ hematopoietic progenitor cells (HPCs) with blast morphology (d). Viable CD45+/CD34+/CD133+ cells were selected (e). Events with high expression of the CD45 marker were excluded from viable CD45+/CD34+/CD133+ cells (f). FSC/SSC backgate was employed to select viable CD45+/CD34+/CD133+ HPCs with blast morphology (g). A control gate (‘Ly’, lymphocytes) was used during exclusion of mature CD45+ HSCs. Red: target cell population. Gray: dead cells. (PDF 374 kb)

Stemness marker expression of target and non-target cell fractions presented in the automatically generated cell product (CP). For phenotype characterization the expression of stemness markers (CD117, CD184, CD309, CD14) was evaluated in target cells (CD45+CD34+CD133+) (a) and non-target cells (CD45+CD34−CD133−, CD45+CD34lowCD133−, CD45+CD34+CD133−) (b) using flow cytometry. The respective analysis was made in accordance with ISHAGE guidelines. Data are presented as a mean ± SEM, n = 9. (DOC 37 kb)

Determination of apoptotic and necrotic cells in the automatically generated cell product (CP) after storage. The percentage of viable, early-stage apoptotic, late-stage apoptotic and necrotic cells was analyzed by flow cytometric measurements using Annexin V Apoptosis Detection Kit. Samples of CP were taken at the respective storage time. All data are presented as a mean ± SEM. n = 3. *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001. (PDF 108 kb)

At present, intensive investigation aims at the creation of optimal valvular prostheses. We introduced and tested the applicability and functionality of two advanced cell-plus-matrix seeding technologies, spray-assisted bioprocessing (SaBP) and laser-assisted bioprocessing (LaBP), for autologous tissue engineering (TE) of bioresorbable artificial grafts. For SaBP, human mesenchymal stem cells (HMSCs), umbilical cord vein endothelial cells (HUVECs) and fibrin were simultaneously spray-administered on poly(?-caprolactone) (PCL) substrates. For LaBP, HUVECs and HMSCs were separately laser-printed in stripes, followed by fibrin sealing. Three-leaflet valves were manufactured following TE of electrospun PCL tissue equivalents. Grafts were monitored in vitro under static and dynamic conditions in bioreactors. SaBP and LaBP resulted in TE of grafts with homogeneous cell distribution and accurate cell pattern, respectively. The engineered valves demonstrated immediate sufficient performance, complete cell coating, proliferation, engraftment, HUVEC-mediated invasion, HMSC differentiation and extracellular matrix deposition. SaBP revealed higher efficiency, with at least 12-fold shorter processing time than the applied LaBP set-up. LaBP realized coating with higher cell density and minimal cell-scaffold distance. Fibrin and PCL stability remain issues for improvement. The introduced TE technologies resulted in complete valvular cell-plus-matrix coating, excellent engraftment and HMSCs differentiation. SaBP might have potential for intraoperative table-side TE considering the procedural duration and ease of implementation. LaBP might accelerate engraftment with precise patterns.

Myocardial infarction (MI) is a major condition causing heart failure (HF). After MI, the renin angiotensin system (RAS) and its signalling octapeptide angiotensin II (Ang II) interferes with cardiac injury/repair via the AT1 and AT2 receptors (AT1R, AT2R). Our study aimed at deciphering the mechanisms underlying the link between RAS and cellular components of the immune response relying on a rodent model of HF as well as HF patients. Flow cytometric analyses showed an increase in the expression of CD4+ AT2R+ cells in the rat heart and spleen post-infarction, but a reduction in the peripheral blood. The latter was also observed in HF patients. The frequency of rat CD4+ AT2R+ T cells in circulating blood, post-infarcted heart and spleen represented 3.8 ± 0.4%, 23.2 ± 2.7% and 22.6 ± 2.6% of the CD4+ cells. CD4+ AT2R+ T cells within blood CD4+ T cells were reduced from 2.6 ± 0.2% in healthy controls to 1.7 ± 0.4% in patients. Moreover, we characterized CD4+ AT2R+ T cells which expressed regulatory FoxP3, secreted interleukin-10 and other inflammatory- related cytokines. Furthermore, intramyocardial injection of MI-induced splenic CD4+ AT2R+ T cells into recipient rats with MI led to reduced infarct size and improved cardiac performance. We defined CD4+ AT2R+ cells as a T cell subset improving heart function post-MI corresponding with reduced infarction size in a rat MI-model. Our results indicate CD4+ AT2R+ cells as a promising population for regenerative therapy, via myocardial transplantation, pharmacological AT2R activation or a combination thereof.