Microfabricated arrays for high-throughput screening of cellular response to cyclic substrate deformation

Lab on a Chip ◽  
2010 ◽  
Vol 10 (2) ◽  
pp. 227-234 ◽  
Author(s):  
Christopher Moraes ◽  
Jan-Hung Chen ◽  
Yu Sun ◽  
Craig A. Simmons
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Cellular Response ◽  
Microfabricated Arrays

Rapid generation of Hybrid Biochemical/Mechanical Cues in Heterogeneous Droplets for High-Throughput Screening of Cellular Response

Lab on a Chip ◽  
2021 ◽  
Author(s):  
Xing Zhao ◽  
Gaozhi Ou ◽  
Mengcheng Lei ◽  
Yang Zhang ◽  
Lina Li ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
High Throughput ◽  
High Throughput Screening ◽  
Cellular Response ◽  
Wide Range ◽  
Rapid Generation ◽  
P Cells

Cells in native microenvironment are subjected to varying combinations of biochemical cues and mechanical cues in a wide range. Despite many signaling pathways have been found to be responsive for...

Automated high-throughput screening of carbon nanotube-based bio-nanocomposites for bone cement applications

2011 ◽  
Vol 83 (11) ◽  
pp. 2063-2069 ◽  
Author(s):  
Paula P. Gonçalves ◽  
Manoj K. Singh ◽  
Virgília S. Silva ◽  
Filipa Marques ◽  
Ana Marques ◽  
...  
Keyword(s):  
High Throughput ◽  
Cell Morphology ◽  
High Throughput Screening ◽  
Trypan Blue ◽  
Cellular Response ◽  
Mg63 Cell ◽  
Cell Diameter ◽  
Blue Dye ◽  
Bioactive Materials ◽  
Average Cell

In this work we demonstrate the potential of using an automated cell viability analyzer for developing high-throughput screening of orthopedic bioactive materials. We used a biomaterial of carbon nanotubes (CNTs)-based composite integrated with hydroxyapatite/polymethyl methacrylate (HA/PMMA) with controlled physical and chemical properties to evaluate the usefulness of morphometric analysis in conjunction with trypan blue dye exclusion assays in MG63 cell cultures. The MG63 cell line, derived from human bone osteo-sarcoma, is often used as a model for studying osteoblast-like cellular response to bioactive materials for orthopedic surgery. The viability analyzer, Vi-CELLTM XR, Beckman Coulter, was used with trypan blue dye exclusion method in cell suspensions obtained after trypsinization along with determining the distribution plots of cell diameter and circularity, which are critical cellular characteristics. In addition, the activity of alkaline phosphatase (ALP), a typical representation of osteogenic activity of osteoblasts, was also measured spectro-photometrically using p-nitrophenol phosphate as the substrate. Comparative analysis of the frequency histogram of average cell diameter and circularity allowed for the analyses of significant alterations in cell morphology not only over time in control cultures (spherical vs. a flat morphology) but also with respect to PMMA and HA nanocomposites. After cell exposure to HA/PMMA/CNTs, a shift toward loss of cell circularity was observed. The appearances of more differentiated morphologic features were well correlated with the increase of secreted ALP activity. In conclusion, the evaluation of material-induced changes of cell morphology could represent a valuable prescreening test for bioactive properties.

scholarly journals Deep2Full: Predictive model for complementing phenotypic outcomes in a deep mutational scan using protein sequence and structure information

2017 ◽  
Author(s):  
C. K. Sruthi ◽  
Meher K. Prakash
Keyword(s):  
Amino Acid ◽  
High Throughput ◽  
High Throughput Screening ◽  
Cellular Response ◽  
Computational Models ◽  
Single Point ◽  
Drug Concentrations ◽  
Scan Data ◽  
The Impact ◽  
Bio Engineering

AbstractLarge scale mutagenesis experiments are becoming possible owing to the advancement in the sequencing technologies and high throughput screening. Deep mutational scans perform exhaustive single-point muta-tions on a protein and probe their phenotypic effects. Performing a full scan with site-directed mutations of all the amino acid residues in a protein may not be practical, and may not even be required, especially if predictive computational models can be developed. Computational models are however naive to cellular response in the myriads of assay-conditions. In order to develop the realistic paradigm of assay context-aware predictive hybrid models, we combine minimal deep mutational studies with computational models and pre-dict the phenotypic outcomes quantitatively. Structural, sequence and co-evolutionary information along with partial deep mutational scan data was included to capture the phenotypic relevance of the mutations to the specific screening criterion. The model reliably predicts the fitness outcomes of hundreds of randomly selected amino acid mutations in β-lactamase, when the phenotypic fitness data from as few as 15% of the full mutation is available. Interestingly, the predictive capabilities are better with a random set of mutations rather than with a systematic substitution of all amino acids to alanine, asparagine and histidine (ANH). The model can potentially be extended for predicting the phenotypic outcomes at other concentrations of the stressor by carefully analyzing the dose-response curves of a representative set of mutations.Author SummaryMutations are the minor changes in protein sequences, with incommensurately high consequences for their function. Many severe diseases can occur with simple single point mutations. An interesting way of studying these mutations is not to isolate the protein from its natural conditions, but rather study how the fitness of the cell improves or decreases in response to these mutations. Whether it is for understanding disease biology or for bio-engineering applications it is important to quantify the impact of mutations on the cellular fitness. An experimental paradigm has evolved which has improved the ability to sample several hundred thousands of mutation-fitness relations using high throughput screening. However, since these are very specialized experiments, the question is if the number of such experiments required can be minimized, by using computer models to complement the rest of the fitness predictions. In this work we introduce this new paradigm which uses computer model trained on a partial deep mutation scan data, to predict the fitness variations in a full mutations scan that could also be repeated under multiple experimental conditions like drug concentrations.

High-throughput screening program for botanical extracts

Planta Medica ◽  
2012 ◽  
Vol 78 (11) ◽  
Author(s):  
L Hingorani ◽  
NP Seeram ◽  
B Ebersole
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Screening Program ◽  
Botanical Extracts

High throughput screening of microbial biodiversity for the discovery of novel cosmeceutical agents

Planta Medica ◽  
2015 ◽  
Vol 81 (16) ◽  
Author(s):  
K Georgousaki ◽  
N DePedro ◽  
AM Chinchilla ◽  
N Aliagiannis ◽  
F Vicente ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Microbial Biodiversity

High throughput screening to investigate Brazilian Cerrado biome plant extract bank chemical diversity

Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381
Author(s):  
LS Espindola ◽  
RG Dusi ◽  
KR Gustafson ◽  
J McMahon ◽  
JA Beutler
Keyword(s):  
High Throughput ◽  
Plant Extract ◽  
High Throughput Screening ◽  
Chemical Diversity ◽  
Brazilian Cerrado ◽  
Cerrado Biome

High-throughput screening revealed a clinically relevant drug to induce sperm motility

2014 ◽  
Author(s):  
Clair Cochrane ◽  
Halil Ruso ◽  
Anthony Hope ◽  
Rosemary G Clarke ◽  
Christopher Barratt ◽  
...  
Keyword(s):  
Sperm Motility ◽  
High Throughput ◽  
High Throughput Screening
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