Simple Methodology to Score Micropattern Quality and Effectiveness

Micropatterns (MPs) are widely used as a powerful tool to control cell morphology and phenotype. However, methods for determining the effectiveness of how well cells are controlled by the shape of MPs have been inconsistently used and studies rarely report on this topic, indicating lack of standardization. We introduce an evaluation score that quantitatively assesses the MP fabrication quality and effectiveness, which can be broadly used in conjunction with all currently available MP design types. This score uses four simple and quick steps: (i) scoring MP and (ii) background fabrication quality, (iii) defining the type(s) of MP of interest, and (iv) assigning so-called efficiency descriptors describing cell behavior. These steps are based on visual inspection and quick categorization of various aspects of MP fabrication quality and cell behavior, presented in illustrations and microscopy image examples intended to serve as a reference "atlas." To illustrate the advantage of using this score, we determined differences in cell morphology and F-actin intensity between scored versus nonscored cells. These measurements, which could be different in other studies, were chosen because both are understood as markers of cell phenotype and function. We combined intensity-calibrated immunofluorescence microscopy and image-based single cell protein analysis. Most important, significant differences in cell morphology and cytoskeletal protein content between scored versus nonscored cells were noted: the unconditional inclusion of all experimental read-outs (i.e., all MP data regardless of MP quality and effectiveness) into the final results significantly misjudged the experimental readouts versus only including experimental read-outs of quality-controlled and effective MPs, identified by scoring. Specifically, nonscoring underestimated the F-actin intensity per cell and quantitative cellular morphometric descriptors circularity and solidity and overestimated aspect ratio. Scoring improved the precision of cellular readouts, advocating the use of a MP quality and efficiency score as a quantitative decision-supporting tool in deciding whether or not particular MPs should be used for experiments, saving time and money. This simple scoring methodology can be used for improving MP fabrication, comparing results across studies, benefiting basic science studies and potential future clinical use of MPs by introducing standardization.

Authors

Institutions

Publication Details

Journal
Tissue Engineering Part C Methods
Published
2024-08-30
DOI
https://doi.org/10.1089/ten.tec.2024.0141
Citations
1
Primary Topic
Microfluidic and Bio-sensing Technologies
Type
article
Field-Weighted Citation Impact
0.18
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simple Methodology to Score Micropattern Quality and Effectiveness

Mischa Selig, Melanie L. Hart, Bernd Rolauffs, Hui Che et al.
1 citations
Tissue Engineering Part C Methods
Microfluidic and Bio-sensing Technologies
0.18
article

Simple Methodology to Score Micropattern Quality and Effectiveness

Mischa Selig, Melanie L. Hart, Bernd Rolauffs, Hui Che, Jasmin Lauer
article en
1 citations

Abstract

Micropatterns (MPs) are widely used as a powerful tool to control cell morphology and phenotype. However, methods for determining the effectiveness of how well cells are controlled by the shape of MPs have been inconsistently used and studies rarely report on this topic, indicating lack of standardization. We introduce an evaluation score that quantitatively assesses the MP fabrication quality and effectiveness, which can be broadly used in conjunction with all currently available MP design types. This score uses four simple and quick steps: (i) scoring MP and (ii) background fabrication quality, (iii) defining the type(s) of MP of interest, and (iv) assigning so-called efficiency descriptors describing cell behavior. These steps are based on visual inspection and quick categorization of various aspects of MP fabrication quality and cell behavior, presented in illustrations and microscopy image examples intended to serve as a reference "atlas." To illustrate the advantage of using this score, we determined differences in cell morphology and F-actin intensity between scored versus nonscored cells. These measurements, which could be different in other studies, were chosen because both are understood as markers of cell phenotype and function. We combined intensity-calibrated immunofluorescence microscopy and image-based single cell protein analysis. Most important, significant differences in cell morphology and cytoskeletal protein content between scored versus nonscored cells were noted: the unconditional inclusion of all experimental read-outs (i.e., all MP data regardless of MP quality and effectiveness) into the final results significantly misjudged the experimental readouts versus only including experimental read-outs of quality-controlled and effective MPs, identified by scoring. Specifically, nonscoring underestimated the F-actin intensity per cell and quantitative cellular morphometric descriptors circularity and solidity and overestimated aspect ratio. Scoring improved the precision of cellular readouts, advocating the use of a MP quality and efficiency score as a quantitative decision-supporting tool in deciding whether or not particular MPs should be used for experiments, saving time and money. This simple scoring methodology can be used for improving MP fabrication, comparing results across studies, benefiting basic science studies and potential future clinical use of MPs by introducing standardization.

Tissue Engineering Part C MethodsVol. 30(11)
University of Freiburg (DE), Suzhou Municipal Hospital (CN), Nanjing Medical University (CN)
Openalex Percentile: Top 53%
Microfluidic and Bio-sensing Technologies
0.18
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.