Next generation microfluidic platforms for high-throughput protein biochemistry

Maerkl, Sebastian J.

doi:10.1016/j.copbio.2010.08.010

Cited by 27 publications

(17 citation statements)

References 37 publications

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“…MITOMI is a versatile platform capable of measuring a broad range of biomolecular interactions, including proteinprotein (27), protein-DNA (17,28), protein-RNA (29), and protein-small molecule (29). The integrated nature of the approach allows for the large-scale on-chip synthesis, purification, and characterization of proteins (30,31). A recent study by Bates and Quake showed that MITOMI could be adapted to enable the measurement of binding kinetics of a single antibody-antigen interaction (22).…”

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confidence: 99%

Massively parallel measurements of molecular interaction kinetics on a microfluidic platform

Geertz

Shore

Maerkl

2012

Proc. Natl. Acad. Sci. U.S.A.

103

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Quantitative biology requires quantitative data. No high-throughput technologies exist capable of obtaining several hundred independent kinetic binding measurements in a single experiment. We present an integrated microfluidic device (k-MITOMI) for the simultaneous kinetic characterization of 768 biomolecular interactions. We applied k-MITOMI to the kinetic analysis of transcription factor (TF)-DNA interactions, measuring the detailed kinetic landscapes of the mouse TF Zif268, and the yeast TFs Tye7p, Yox1p, and Tbf1p. We demonstrated the integrated nature of k-MITOMI by expressing, purifying, and characterizing 27 additional yeast transcription factors in parallel on a single device. Overall, we obtained 2,388 association and dissociation curves of 223 unique molecular interactions with equilibrium dissociation constants ranging from 2 × 10 −6 M to 2 × 10 −9 M, and dissociation rate constants of approximately 6 s −1 to 8.5 × 10 −3 s −1 . Association rate constants were uniform across 3 TF families, ranging from 3.7 × 10 6 M −1 s −1 to 9.6 × 10 7 M −1 s −1 , and are well below the diffusion limit. We expect that k-MITOMI will contribute to our quantitative understanding of biological systems and accelerate the development and characterization of engineered systems.biochemistry | biophysics | systems biology S ystems and synthetic biology, as well as the computational models and engineering-based approaches they employ, rely heavily on quantitative data (1, 2). Thus far, efforts in systems biology have mainly focused on cataloging and mapping genomes and proteomes. Genome sequencing and gene expression analysis have provided insight into genome architecture (3-6), and functional genomics approaches, including high-throughput protein-based methods (7-15), mapped network topologies.Although the number of known protein-protein and protein-DNA interactions is already substantial, the information describing such networks is predominantly qualitative and binary in nature. It is also becoming clear that network topologies alone are not sufficient to model complex biological processes. Precise quantitative information describing every interaction in a network would be tremendously valuable (2), yet binding affinities are known for only a small fraction of interactions (16, 17) and kinetic information hardly exists at all. This dearth of quantitative interaction data is due to a lack of high-throughput technologies capable of measuring kinetic rates of biomolecular interactions. Current methods used for kinetic rate measurements are generally based on surface plasmon resonance (SPR) (18) such as BioRad's ProteOn XPR36 6 × 6 array system, which measures 36 interactions in a single run. SPR-based measurements have been integrated with microfluidic devices (19, 20) to achieve higher degrees of parallelization (21). Yet proof of concept demonstrations have made use of only a small fraction of the proposed throughput and often restrict their measurements to protein-antibody interactions with high affinities and long half-lives...

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mentioning

confidence: 99%

Massively parallel measurements of molecular interaction kinetics on a microfluidic platform

Geertz

Shore

Maerkl

2012

Proc. Natl. Acad. Sci. U.S.A.

103

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“…Another field of application of mLSI is protein synthesis and characterization. In addition to high throughput, when married to DNA-to-protein arrays, mLSI has enabled multiplexed protein expression and utilization of advanced detection technologies, as summarized in the recent review by Maerkl on protein biochemistry [61].…”

Section: Biological and Chemical Applicationsmentioning

confidence: 99%

Recent developments in microfluidic large scale integration

Araci

Brisk

2014

Current Opinion in Biotechnology

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In 2002, Thorsen et al. integrated thousands of micromechanical valves on a single microfluidic chip and demonstrated that the control of the fluidic networks can be simplified through multiplexors [1]. This enabled realization of highly parallel and automated fluidic processes with substantial sample economy advantage. Moreover, the fabrication of these devices by multilayer soft lithography was easy and reliable hence contributed to the power of the technology; microfluidic large scale integration (mLSI). Since then, mLSI has found use in wide variety of applications in biology and chemistry. In the meantime, efforts to improve the technology have been ongoing. These efforts mostly focus on; novel materials, components, micromechanical valve actuation methods, and chip architectures for mLSI. In this review, these technological advances are discussed and, recent examples of the mLSI applications are summarized. Recent advancements in microfluidic technologies have created new opportunities in the fields of biology and chemistry through miniaturization and automation of common processes, including mixing, metering, trapping, reaction, filtering, and separation, among others. Microfluidic large scale integration (mLSI) enables the fabrication of microfluidic chips containing hundreds or more of these functions using well-established lithography techniques, similar in principle to electronic LSI in the semiconductor industry [1]. Small feature dimensions, abundant spatial parallelism, and control over fluid flow provide mLSI technology with advantages such as high throughput, precise metering, automation and low reagent consumption. The implications of mLSI technology can especially be seen in recent advances in single cell, genomic, and protein analysis.

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“…This transformation has been driven in part by development of new technologies for high-throughput data acquisition that now make it possible to sequence genomes (Metzker, 2009), and to measure RNA (Wang et al, 2009) and protein (Maerkl, 2011) expression levels with ever increasing accuracy and lower cost. These extraordinary achievements have contributed to advances in genetic medicine (Amberger et al, 2009) and the discovery of gene and protein signatures of disease (Wood et al, 2007; Hanash and Taguchi, 2010; Addona et al, 2011; Cancer Genome Atlas Research Network, 2011; Heidecker et al, 2011; Majewski and Bernards, 2011).…”

Section: Overviewmentioning

confidence: 99%

Grand Challenges in Computational Physiology and Medicine

Winslow¹

2011

Front. Physio.

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Next generation microfluidic platforms for high-throughput protein biochemistry

Cited by 27 publications

References 37 publications

Massively parallel measurements of molecular interaction kinetics on a microfluidic platform

Massively parallel measurements of molecular interaction kinetics on a microfluidic platform

Recent developments in microfluidic large scale integration

Grand Challenges in Computational Physiology and Medicine

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