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 ◽  
...  

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...

2021 ◽  
Author(s):  
Diana Wu ◽  
Chelsea Gordon ◽  
John Shin ◽  
Michael Eisenstein ◽  
Hyongsok Tom Soh

Although antibodies are a powerful tool for molecular biology and clinical diagnostics, there are many emerging applications for which nucleic acid-based aptamers can be advantageous. However, generating high-quality aptamers with sufficient affinity and specificity for biomedical applications is a challenging feat for most research laboratories. In this Account, we describe four techniques developed in our lab to accelerate the discovery of high quality aptamer reagents that can achieve robust binding even for challenging molecular targets. The first method is particle display, in which we convert solution-phase aptamers into aptamer particles that can be screened via fluorescence-activated cell sorting (FACS) to quantitatively isolate individual aptamer particles based on their affinity. This enables the efficient isolation of high-affinity aptamers in fewer selection rounds than conventional methods, thereby minimizing selection biases and reducing the emergence of artifacts in the final aptamer pool. We subsequently developed the multi-parametric particle display (MPPD) method, which employs two-color FACS to isolate aptamer particles based on both affinity and specificity, yielding aptamers that exhibit excellent target binding even in complex matrices like serum. The third method is a click chemistry-based particle display (click-PD) that enables the generation and high-throughput screening of non-nattural aptamers with a wide range of base modifications. We have shown that these base-modified aptamers can achieve robust affinity and specificity for targets that have proven challenging or inaccessible with natural nucleotide-based aptamer libraries. Lastly, we describe the non-natural aptamer array (N2A2) platform, in which a modified benchtop sequencing instrument is used to characterize base-modified aptamers in a massively parallel fashion, enabling the efficient identification of molecules with excellent affinity and specificity for their targets. This system first generates aptamer clusters on the flow-cell surface that incorporate alkyne-modified nucleobases, and then performs a click reaction to couple those nucleobases to an azide-modified chemical moiety. This yields a sequence-defined array of tens of millions of base-modified sequences, which can then be characterized in a high-throughput fashion. Collectively, we believe that these advancements are helping to make aptamer technology more accessible, efficient, and robust, thereby enabling the use of these affinity reagents for a wider range of molecular recognition and detection-based applications.


Author(s):  
Haomin Chen ◽  
Lee Loong Wong ◽  
Stefan Adams

The identification of materials for advanced energy-storage systems is still mostly based on experimental trial and error. Increasingly, computational tools are sought to accelerate materials discovery by computational predictions. Here are introduced a set of computationally inexpensive software tools that exploit the bond-valence-based empirical force field previously developed by the authors to enable high-throughput computational screening of experimental or simulated crystal-structure models of battery materials predicting a variety of properties of technological relevance, including a structure plausibility check, surface energies, an inventory of equilibrium and interstitial sites, the topology of ion-migration paths in between those sites, the respective migration barriers and the site-specific attempt frequencies. All of these can be predicted from CIF files of structure models at a minute fraction of the computational cost of density functional theory (DFT) simulations, and with the added advantage that all the relevant pathway segments are analysed instead of arbitrarily predetermined paths. The capabilities and limitations of the approach are evaluated for a wide range of ion-conducting solids. An integrated simple kinetic Monte Carlo simulation provides rough (but less reliable) predictions of the absolute conductivity at a given temperature. The automated adaptation of the force field to the composition and charge distribution in the simulated material allows for a high transferability of the force field within a wide range of Lewis acid–Lewis base-type ionic inorganic compounds as necessary for high-throughput screening. While the transferability and precision will not reach the same levels as in DFT simulations, the fact that the computational cost is several orders of magnitude lower allows the application of the approach not only to pre-screen databases of simple structure prototypes but also to structure models of complex disordered or amorphous phases, and provides a path to expand the analysis to charge transfer across interfaces that would be difficult to cover by ab initio methods.


Lab on a Chip ◽  
2010 ◽  
Vol 10 (2) ◽  
pp. 227-234 ◽  
Author(s):  
Christopher Moraes ◽  
Jan-Hung Chen ◽  
Yu Sun ◽  
Craig A. Simmons

2018 ◽  
Author(s):  
Andrew Tarzia ◽  
Masahide Takahashi ◽  
Paolo Falcaro ◽  
Aaron Thornton ◽  
Christian Doonan ◽  
...  

The ability to align porous metal–organic frameworks (MOFs) on substrate surfaces on a macroscopic scale is a vital step towards integrating MOFs into functional devices. But macroscale surface alignment of MOF crystals has only been demonstrated in a few cases. To accelerate the materials discovery process, we have developed a high-throughput computational screening algorithm to identify MOFs that are likely to undergo macroscale aligned heterepitaxial growth on a substrate. Screening of thousands of MOF structures by this process can be achieved in a few days on a desktop workstation. The algorithm filters MOFs based on surface chemical compatibility, lattice matching with the substrate, and interfacial bonding. Our method uses a simple new computationally efficient measure of the interfacial energy that considers both bond and defect formation at the interface. Furthermore, we show that this novel descriptor is a better predictor of aligned heteroepitaxial growth than other established interface descriptors, by testing our screening algorithm on a sample set of copper MOFs that have been grown heteroepitaxially on a copper hydroxide surface. Application of the screening process to several MOF databases reveals that the top candidates for aligned growth on copper hydroxide comprise mostly MOFs with rectangular lattice symmetry in the plane of the substrate. This result indicates a substrate-directing effect that could be exploited in targeted synthetic strategies. We also identify that MOFs likely to form aligned heterostructures have broad distributions of in-plane pore sizes and anisotropies. Accordingly, this suggests that aligned MOF thin films with a wide range of properties may be experimentally accessible.


2018 ◽  
Author(s):  
Andrew Tarzia ◽  
Masahide Takahashi ◽  
Paolo Falcaro ◽  
Aaron Thornton ◽  
Christian Doonan ◽  
...  

The ability to align porous metal–organic frameworks (MOFs) on substrate surfaces on a macroscopic scale is a vital step towards integrating MOFs into functional devices. But macroscale surface alignment of MOF crystals has only been demonstrated in a few cases. To accelerate the materials discovery process, we have developed a high-throughput computational screening algorithm to identify MOFs that are likely to undergo macroscale aligned heterepitaxial growth on a substrate. Screening of thousands of MOF structures by this process can be achieved in a few days on a desktop workstation. The algorithm filters MOFs based on surface chemical compatibility, lattice matching with the substrate, and interfacial bonding. Our method uses a simple new computationally efficient measure of the interfacial energy that considers both bond and defect formation at the interface. Furthermore, we show that this novel descriptor is a better predictor of aligned heteroepitaxial growth than other established interface descriptors, by testing our screening algorithm on a sample set of copper MOFs that have been grown heteroepitaxially on a copper hydroxide surface. Application of the screening process to several MOF databases reveals that the top candidates for aligned growth on copper hydroxide comprise mostly MOFs with rectangular lattice symmetry in the plane of the substrate. This result indicates a substrate-directing effect that could be exploited in targeted synthetic strategies. We also identify that MOFs likely to form aligned heterostructures have broad distributions of in-plane pore sizes and anisotropies. Accordingly, this suggests that aligned MOF thin films with a wide range of properties may be experimentally accessible.


2021 ◽  
Author(s):  
Hassan Aljama ◽  
Martin Head-Gordon ◽  
Alexis Bell

Abstract Cation exchanged-zeolites are functional materials with a wide range of applications from catalysis to sorbents. They present a challenge for computational studies using density functional theory due to the numerous possible active sites. From Al configuration, to placement of extra framework cation(s), to potentially different oxidation states of the cation, accounting for all these possibilities is not trivial. To make the number of calculations more tractable, most studies focus on a few active sites. We attempt to go beyond these limitations by implementing a workflow for a high throughput screening, designed to systematize the problem and exhaustively search for feasible active sites. We use Pd-exchanged CHA and BEA to illustrate the approach. After conducting thousands of individual calculations, we identify the sites most favorable for the Pd cation and discuss the results in detail. The high throughput screening identifies many energetically favorable sites that are non-trivial. Lastly, we employ these results to examine NO adsorption in Pd-exchanged CHA, which is a promising passive NOx adsorbent (PNA) during the cold start of automobiles. The results shed light on critical active sites for NOx capture that were not previously studied.


2020 ◽  
Vol 26 (1) ◽  
pp. 140-150
Author(s):  
Ann M. Decker ◽  
Kelly M. Mathews ◽  
Bruce E. Blough ◽  
Brian P. Gilmour

The human trace amine-associated receptor 1 (hTAAR1) is a G protein-coupled receptor (GPCR) that is widely expressed in monoaminergic nuclei in the central nervous system and has therapeutic potential for multiple diseases, including drug addiction and schizophrenia. Thus, identification of novel hTAAR1 ligands is critical to advancing our knowledge of hTAAR1 function and to the development of therapeutics for a wide range of diseases. Herein we describe the development of a robust, 3-addition high-throughput screening (HTS) calcium mobilization assay using stable CHO-Gαq16-hTAAR1 cells, which functionally couple hTAAR1 to the promiscuous Gαq16 protein and thus allow signal transduction to occur through mobilization of internal calcium. Our previously established 96-well hTAAR1 assay was first miniaturized to the 384-well format and optimized to provide an assay with a Z′ factor of 0.84, which is indicative of a robust HTS assay. Using the 3-addition protocol, 22,000 compounds were screened and yielded a ~1% agonist hit rate and a ~0.2% antagonist hit rate. Of the antagonist hits, two confirmed hits are the most potent hTAAR1 antagonists identified to date (IC50 = 206 and 281 nM). While scientists have been studying hTAAR1 for years, the lack of suitable hTAAR1 antagonists has been a major roadblock for studying the basic pharmacology of hTAAR1. Thus, these new ligands will serve as valuable tools to study hTAAR1-mediated signaling mechanisms, therapeutic potential, and in vivo functions.


2000 ◽  
Vol 5 (4) ◽  
pp. 239-247 ◽  
Author(s):  
Anthony C. Chiulli ◽  
Karen Trompeter ◽  
Michelle Palmer

The second messenger 3′, 5′-cyclic AMP (cAMP) is a highly regulated molecule that is governed by G protein-coupled receptor activation and other cellular processes. Measurement of cAMP levels in cells is widely used as an indicator of receptor function in drug discovery applications. We have developed a nonradioactive ELISA for the accurate quantitation of cAMP levels produced in cell-based assays. This novel competitive assay utilizes chemiluminescent detection that affords both a sensitivity and a dynamic assay range that have not been previously reported with any other assay methodologies. The assay has been automated in 96- and 384-well formats, providing assay data that are equivalent to, if not better than, data generated by hand. This report demonstrates the application of this novel assay technology to the functional analysis of a specific G protein-coupled receptor, neuropeptide receptor Y1, on SK-N-MC cells. Our data indicate the feasibility of utilizing this assay methodology for monitoring cAMP levels in a wide range of functional cell-based assays for high throughput screening.


Sign in / Sign up

Export Citation Format

Share Document