TY - JOUR
T1 - An algorithm-based topographical biomaterials library to instruct cell fate
AU - Unadkat, Hemant V.
AU - Hulsman, Marc
AU - Cornelissen, Kamiel
AU - Papenburg, Bernke J.
AU - Truckenmul̈ler, Roman K.
AU - Post, Gerhard F.
AU - Uetz, Marc
AU - Reinders, Marcel J.T.
AU - Stamatialis, Dimitrios
AU - Van Blitterswijk, Clemens A.
AU - De Boer, Jan
PY - 2011/10/4
Y1 - 2011/10/4
N2 - It is increasingly recognized that material surface topography is able to evoke specific cellular responses, endowing materials with instructive properties that were formerly reserved for growth factors. This opens the window to improve upon, in a cost-effective manner, biological performance of any surface used in the human body. Unfortunately, the interplay between surface topographies and cell behavior is complex and still incompletely understood. Rational approaches to search for bioactive surfaces will therefore omit previously unperceived interactions. Hence, in the present study, we use mathematical algorithms to design nonbiased, random surface features and produce chips of poly(lactic acid) with 2,176 different topographies. With human mesenchymal stromal cells (hMSCs) grown on the chips and using high-content imaging, we reveal unique, formerly unknown, surface topographies that are able to induce MSC proliferation or osteogenic differentiation. Moreover, we correlate parameters of the mathematical algorithms to cellular responses, which yield novel design criteria for these particular parameters. In conclusion, we demonstrate that randomized libraries of surface topographies can be broadly applied to unravel the interplay between cells and surface topography and to find improved material surfaces.
AB - It is increasingly recognized that material surface topography is able to evoke specific cellular responses, endowing materials with instructive properties that were formerly reserved for growth factors. This opens the window to improve upon, in a cost-effective manner, biological performance of any surface used in the human body. Unfortunately, the interplay between surface topographies and cell behavior is complex and still incompletely understood. Rational approaches to search for bioactive surfaces will therefore omit previously unperceived interactions. Hence, in the present study, we use mathematical algorithms to design nonbiased, random surface features and produce chips of poly(lactic acid) with 2,176 different topographies. With human mesenchymal stromal cells (hMSCs) grown on the chips and using high-content imaging, we reveal unique, formerly unknown, surface topographies that are able to induce MSC proliferation or osteogenic differentiation. Moreover, we correlate parameters of the mathematical algorithms to cellular responses, which yield novel design criteria for these particular parameters. In conclusion, we demonstrate that randomized libraries of surface topographies can be broadly applied to unravel the interplay between cells and surface topography and to find improved material surfaces.
KW - High-throughput screening
KW - Mesenchymal stromal cells
KW - Microfabrication
UR - http://www.scopus.com/inward/record.url?scp=80053644469&partnerID=8YFLogxK
U2 - 10.1073/pnas.1109861108
DO - 10.1073/pnas.1109861108
M3 - Article
C2 - 21949368
AN - SCOPUS:80053644469
VL - 108
SP - 16565
EP - 16570
JO - Proceedings of the National Academy of Sciences of the United States of America (PNAS)
JF - Proceedings of the National Academy of Sciences of the United States of America (PNAS)
SN - 0027-8424
IS - 40
ER -