Polly Fordyce is an Associate Professor of Genetics and Bioengineering and fellow of the ChEM-H Institute at Stanford, where her laboratory focuses on developing and applying new microfluidic platforms for quantitative, high-throughput biophysics and biochemistry and single-cell genomics. She graduated from the University of Colorado at Boulder with undergraduate degrees in physics and biology before moving to Stanford University, where she earned a Ph.D. in physics for work with Professor Steve Block developing instrumentation and assays for single-molecule studies of kinesin motor proteins. For her postdoctoral research, she worked with Professor Joe DeRisi to develop a new microfluidic platform for understanding how transcription factors recognize and bind their DNA targets as well as a new technology for bead-based multiplexing. She is the recipient of a number of awards, including an NIH New Innovator Award, an NSF CAREER Award, the 2023 Eli Lilly Award in Biological Chemistry, and is a Chan Zuckerberg Biohub Investigator.
Investigator, Chan Zuckerberg Biohub (2017 - 2022)
Honors & Awards
Eli Lilly Award in Biological Chemistry, Eli Lilly Foundation (2023)
Young Investigator Award, Protein Society (2023)
Breakthrough Science Initiative Award, Ono Pharma Foundation (2019-2022)
Investigator, Chan Zuckerberg Biohub (2017-2022)
Alfred P. Sloan Foundation Research Fellow, Alfred P. Sloane Foundarion (2017-2019)
New Innovator Award (DP2), NIH (2016-2021)
Scialog Fellow, Gordon & Betty Moore Foundation (2016-2017)
Pathway to Independence Award (K99), NIH (2012-2014)
Helen Hay Whitney Postdoctoral Fellowship, Helen Hay Whitney Foundation (2008-2011)
G. J. Lieberman Fellow, Stanford University (2003-2004)
Graduate Research Fellow, National Science Foundation (2002-2005)
Boards, Advisory Committees, Professional Organizations
Scientific Advisory Board, Evozyne (2023 - Present)
Advisory Board Member, Cell Systems (2020 - Present)
Postdoctoral Fellow, University of California San Francisco, Biophysics (2014)
Ph.D., Stanford University, Physics (2007)
B.A., University of Colorado at Boulder, Physics, Biology (2000)
Polly Fordyce and Jamin Hein. "United States Patent 63/387,748 Microbeads with ratiometric lanthanide encoding for drug screening", Leland Stanford Junior University, Chan Zuckerberg Biohub, Dec 16, 2022
Polly Fordyce and Jamin Hein. "United States Patent 63/387,757 Kinase/phosphatase substrate analysis and compositions using spectrally encoded microbeads", Leland Stanford Junior University, Chan Zuckerberg Biohub, Dec 16, 2022
Polly Fordyce, Christina Curtis, Alex Sockell, and Wing Hing Wong. "United States Patent 63/378,229 Array platform for high-throughput organoid profiling", Leland Stanford Junior University, Chan Zuckerberg Biohub, Oct 3, 2022
Yinnian Feng, Adam White, Polly Fordyce, Xiang Zhao, and K. Christopher Garcia. "United States Patent 63/108,162 High-throughput force-dependent cellular response assay using spectrally encoded smart beads", Leland Stanford Junior University, Chan Zuckerberg Biohub, Oct 30, 2020
Yinnian Feng, Adam White, Jamin Hein, and Polly Fordyce. "United States Patent 63/037,804 Methods, devices, and compositions related to polymeric microbeads", Chan Zuckerberg Biohub, Jun 11, 2020
Kara Brower, Sandy Klemm, William Greenleaf, Polly Fordyce. "United States Patent 62/693,800 Method to perform high-throughput single cell genomic and phenotypic analyses", Chan Zuckerberg Biohub, Jul 1, 2019
Adam White, Huy Nguyen, Brian Yu, Tyler Shimko, Polly Fordyce, Nadya Andini, Sam Yang. "United States Patent 62/853,494 Method for multiplexed detection of nucleic acids using spectrally encoded beads", Chan Zuckerberg Biohub, May 28, 2019
Kara Brower, Alex Sockell, Adam White, Polly Fordyce. "United States Patent 62/853,627 Multi-parameter single-cell analysis using spectrally encoded microbeads", Chan Zuckerberg Biohub, May 28, 2019
Brian Baxter, Joe DeRisi, Polly Fordyce, Rachel Gerver, Rafael Gomez-Sjoberg, Kurt Thorn. "United States Patent 61/692,816. Spectrally encoded microbeads and methods and devices for making and using same", University of California San Francisco, Aug 23, 2013
Current Research and Scholarly Interests
Cellular function and organismal homeostasis are governed by molecular interactions. Protein-DNA binding interactions are essential for regulating gene transcription and translation, dense networks of protein-protein and protein-peptide interactions further regulate cellular function, and enzymes make possible all of the chemical transformations essential to metabolism and signaling. Our goal is to understand, and eventually engineer, these complex processes by building and testing biophysical models of how the molecules that drive these processes work. To do so, an essential first step is to obtain the necessary quantitative measurements of the fundamental kinetic and thermodynamic constants of these molecular interactions and catalytic processes—the “universal language” needed to describe and ultimately predict function. In our lab, we use microfluidics and extensive hardware automation to perform these quantitative measurements at an unprecedented scale via 3 main platforms:
1. Array-based multiplexing experiments (MITOMI and HT-MEK) employ microfluidic devices containing 1,568 valved reaction chambers aligned to printed DNA arrays. We are currently using these devices to better understand how transcription factors find and bind their genomic targets to regulate gene expression, as well as to understand how enzymes achieve their extraordinary catalytic efficiency and substrate specificity.
2. MRBLEs (Microspheres with Ratiometric Barcode Lanthanide Encoding) rely on spectral multiplexing to track analytes throughout an experiment. We can create microspheres containing > 1,000 distinct ratios of lanthanide nanophosphors that can be uniquely identified via imaging alone, and are now using these MRBLEs in a variety of downstream assays.
3. Dropception is a microfluidic platform for creating double emulsion (water-in-oil-in-water) droplets that can be sorted in high-throughput using standard flow cytometers (FACS machines). We recently demonstrated the ability to generate and sort double emulsion droplets without breakage, isolate individual rare droplets of interest in wells of a multiwell plate, and recover all encapsulated nucleic acids, enabling a wide range of novel single-cell multi-omic techniques.
- Microfluidic Device Laboratory
BIOE 301D, GENE 207 (Win)
Independent Studies (10)
- Bioengineering Problems and Experimental Investigation
BIOE 191 (Win, Spr)
- Directed Investigation
BIOE 392 (Aut, Win, Spr)
- Directed Reading in Biophysics
BIOPHYS 399 (Aut, Win, Spr, Sum)
- Directed Reading in Genetics
GENE 299 (Aut, Win, Spr)
- Directed Study
BIOE 391 (Aut, Spr)
- Graduate Research
BIOPHYS 300 (Aut, Win, Spr, Sum)
- Graduate Research
GENE 399 (Aut, Win, Spr, Sum)
- Medical Scholars Research
GENE 370 (Aut, Win, Spr)
- Supervised Study
GENE 260 (Aut, Win, Spr)
- Undergraduate Research
GENE 199 (Aut, Win, Spr)
- Bioengineering Problems and Experimental Investigation
- Prior Year Courses
Doctoral Dissertation Reader (AC)
Katie Antilla, Benjamin Doughty, Michaela Hinks, Ethan Li, Michael Montgomery, Omar Niagne, Carla Perez
Postdoctoral Faculty Sponsor
Karl Krauth, Byungjin Lee, Daniel Mokhtari
Doctoral Dissertation Advisor (AC)
Eliel Akinbami, Beatriz Atsavapranee, Min Sung Cho, Matt DeJong, Nicole DelRosso, Renee Hastings, Michael Hayes, Jessica Karaguesian, Micah Olivas, Jack Shanahan, Lexy Strom, Peter Suzuki, Daria Wonderlick
Doctoral Dissertation Co-Advisor (AC)
Amr Mohamed, Maya Sheth
Beatriz Atsavapranee, Manish Ayushman, Hyejin Lee, Hope Leng, Carolina Rios-Martinez, Cassandra Villicana
Short tandem repeats bind transcription factors to tune eukaryotic gene expression.
Science (New York, N.Y.)
2023; 381 (6664): eadd1250
Short tandem repeats (STRs) are enriched in eukaryotic cis-regulatory elements and alter gene expression, yet how they regulate transcription remains unknown. We found that STRs modulate transcription factor (TF)-DNA affinities and apparent on-rates by about 70-fold by directly binding TF DNA-binding domains, with energetic impacts exceeding many consensus motif mutations. STRs maximize the number of weakly preferred microstates near target sites, thereby increasing TF density, with impacts well predicted by statistical mechanics. Confirming that STRs also affect TF binding in cells, neural networks trained only on in vivo occupancies predicted effects identical to those observed in vitro. Approximately 90% of TFs preferentially bound STRs that need not resemble known motifs, providing a cis-regulatory mechanism to target TFs to genomic sites.
View details for DOI 10.1126/science.add1250
View details for PubMedID 37733848
Decoupling of catalysis and transition state analog binding from mutations throughout a phosphatase revealed by high-throughput enzymology.
Proceedings of the National Academy of Sciences of the United States of America
2023; 120 (29): e2219074120
Using high-throughput microfluidic enzyme kinetics (HT-MEK), we measured over 9,000 inhibition curves detailing impacts of 1,004 single-site mutations throughout the alkaline phosphatase PafA on binding affinity for two transition state analogs (TSAs), vanadate and tungstate. As predicted by catalytic models invoking transition state complementary, mutations to active site and active-site-contacting residues had highly similar impacts on catalysis and TSA binding. Unexpectedly, most mutations to more distal residues that reduced catalysis had little or no impact on TSA binding and many even increased tungstate affinity. These disparate effects can be accounted for by a model in which distal mutations alter the enzyme's conformational landscape, increasing the occupancy of microstates that are catalytically less effective but better able to accommodate larger transition state analogs. In support of this ensemble model, glycine substitutions (rather than valine) were more likely to increase tungstate affinity (but not more likely to impact catalysis), presumably due to increased conformational flexibility that allows previously disfavored microstates to increase in occupancy. These results indicate that residues throughout an enzyme provide specificity for the transition state and discriminate against analogs that are larger only by tenths of an Angstrom. Thus, engineering enzymes that rival the most powerful natural enzymes will likely require consideration of distal residues that shape the enzyme's conformational landscape and fine-tune active-site residues. Biologically, the evolution of extensive communication between the active site and remote residues to aid catalysis may have provided the foundation for allostery to make it a highly evolvable trait.
View details for DOI 10.1073/pnas.2219074120
View details for PubMedID 37428919
De novo distillation of thermodynamic affinity from deep learning regulatory sequence models of in vivo protein-DNA binding.
bioRxiv : the preprint server for biology
Transcription factors (TF) are proteins that bind DNA in a sequence-specific manner to regulate gene transcription. Despite their unique intrinsic sequence preferences, in vivo genomic occupancy profiles of TFs differ across cellular contexts. Hence, deciphering the sequence determinants of TF binding, both intrinsic and context-specific, is essential to understand gene regulation and the impact of regulatory, non-coding genetic variation. Biophysical models trained on in vitro TF binding assays can estimate intrinsic affinity landscapes and predict occupancy based on TF concentration and affinity. However, these models cannot adequately explain context-specific, in vivo binding profiles. Conversely, deep learning models, trained on in vivo TF binding assays, effectively predict and explain genomic occupancy profiles as a function of complex regulatory sequence syntax, albeit without a clear biophysical interpretation. To reconcile these complementary models of in vitro and in vivo TF binding, we developed Affinity Distillation (AD), a method that extracts thermodynamic affinities de-novo from deep learning models of TF chromatin immunoprecipitation (ChIP) experiments by marginalizing away the influence of genomic sequence context. Applied to neural networks modeling diverse classes of yeast and mammalian TFs, AD predicts energetic impacts of sequence variation within and surrounding motifs on TF binding as measured by diverse in vitro assays with superior dynamic range and accuracy compared to motif-based methods. Furthermore, AD can accurately discern affinities of TF paralogs. Our results highlight thermodynamic affinity as a key determinant of in vivo binding, suggest that deep learning models of in vivo binding implicitly learn high-resolution affinity landscapes, and show that these affinities can be successfully distilled using AD. This new biophysical interpretation of deep learning models enables high-throughput in silico experiments to explore the influence of sequence context and variation on both intrinsic affinity and in vivo occupancy.
View details for DOI 10.1101/2023.05.11.540401
View details for PubMedID 37214836
Double emulsions as a high-throughput enrichment and isolation platform for slower-growing microbes.
2023; 3 (1): 47
Our understanding of in situ microbial physiology is primarily based on physiological characterization of fast-growing and readily-isolatable microbes. Microbial enrichments to obtain novel isolates with slower growth rates or physiologies adapted to low nutrient environments are plagued by intrinsic biases for fastest-growing species when using standard laboratory isolation protocols. New cultivation tools to minimize these biases and enrich for less well-studied taxa are needed. In this study, we developed a high-throughput bacterial enrichment platform based on single cell encapsulation and growth within double emulsions (GrowMiDE). We showed that GrowMiDE can cultivate many different microorganisms and enrich for underrepresented taxa that are never observed in traditional batch enrichments. For example, preventing dominance of the enrichment by fast-growing microbes due to nutrient privatization within the double emulsion droplets allowed cultivation of slower-growing Negativicutes and Methanobacteria from stool samples in rich media enrichment cultures. In competition experiments between growth rate and growth yield specialist strains, GrowMiDE enrichments prevented competition for shared nutrient pools and enriched for slower-growing but more efficient strains. Finally, we demonstrated the compatibility of GrowMiDE with commercial fluorescence-activated cell sorting (FACS) to obtain isolates from GrowMiDE enrichments. Together, GrowMiDE + DE-FACS is a promising new high-throughput enrichment platform that can be easily applied to diverse microbial enrichments or screens.
View details for DOI 10.1038/s43705-023-00241-9
View details for PubMedID 37160952
Large-scale mapping and mutagenesis of human transcriptional effector domains.
Human gene expression is regulated by more than 2,000 transcription factors and chromatin regulators1,2. Effector domains within these proteins can activate or repress transcription. However, for many of these regulators we do not know what type of effector domains they contain, their location in the protein, their activation and repression strengths, and the sequences that are necessary for their functions. Here, we systematically measure the effector activity of more than 100,000 protein fragments tiling across most chromatin regulators and transcription factors in human cells (2,047 proteins). By testing the effect they have when recruited at reporter genes, we annotate 374 activation domains and 715 repression domains, roughly 80% of which are new and have not been previously annotated3-5. Rational mutagenesis and deletion scans across all the effector domains reveal aromatic and/or leucine residues interspersed with acidic, proline, serine and/or glutamine residues are necessary for activation domain activity. Furthermore, most repression domain sequences contain sites for small ubiquitin-like modifier (SUMO)ylation, short interaction motifs for recruiting corepressors or are structured binding domains for recruiting other repressive proteins. We discover bifunctional domains that can both activate and repress, some of which dynamically split a cell population into high- and low-expression subpopulations. Our systematic annotation and characterization of effector domains provide a rich resource for understanding the function of human transcription factors and chromatin regulators, engineering compact tools for controlling gene expression and refining predictive models of effector domain function.
View details for DOI 10.1038/s41586-023-05906-y
View details for PubMedID 37020022
View details for PubMedCentralID 4494013
On the dependent recognition of some long zinc finger proteins.
Nucleic acids research
The human genome contains about 800 C2H2 zinc finger proteins (ZFPs), and most of them are composed of long arrays of zinc fingers. Standard ZFP recognition model asserts longer finger arrays should recognize longer DNA-binding sites. However, recent experimental efforts to identify in vivo ZFP binding sites contradict this assumption, with many exhibiting short motifs. Here we use ZFY, CTCF, ZIM3, and ZNF343 as examples to address three closely related questions: What are the reasons that impede current motif discovery methods? What are the functions of those seemingly unused fingers and how can we improve the motif discovery algorithms based on long ZFPs' biophysical properties? Using ZFY, we employed a variety of methods and find evidence for 'dependent recognition' where downstream fingers can recognize some previously undiscovered motifs only in the presence of an intact core site. For CTCF, high-throughput measurements revealed its upstream specificity profile depends on the strength of its core. Moreover, the binding strength of the upstream site modulates CTCF's sensitivity to different epigenetic modifications within the core, providing new insight into how the previously identified intellectual disability-causing and cancer-related mutant R567W disrupts upstream recognition and deregulates the epigenetic control by CTCF. Our results establish that, because of irregular motif structures, variable spacing and dependent recognition between sub-motifs, the specificities of long ZFPs are significantly underestimated, so we developed an algorithm, ModeMap, to infer the motifs and recognition models of ZIM3 and ZNF343, which facilitates high-confidence identification of specific binding sites, including repeats-derived elements. With revised concept, technique, and algorithm, we can discover the overlooked specificities and functions of those 'extra' fingers, and therefore decipher their broader roles in human biology and diseases.
View details for DOI 10.1093/nar/gkad207
View details for PubMedID 36951113
Microfluidic encapsulation of photosynthetic cyanobacteria in hydrogel microparticles augments oxygen delivery to rescue ischemic myocardium.
Journal of bioscience and bioengineering
Cardiovascular disease, primarily caused by coronary artery disease, is the leading cause of death in the United States. While standard clinical interventions have improved patient outcomes, mortality rates associated with eventual heart failure still represent a clinical challenge. Macrorevascularization techniques inadequately address the microvascular perfusion deficits that persist beyond primary and secondary interventions. In this work, we investigate a photosynthetic oxygen delivery system that rescues the myocardium following acute ischemia. Using a simple microfluidic system, we encapsulated Synechococcus elongatus into alginate hydrogel microparticles (HMPs), which photosynthetically deliver oxygen to ischemic tissue in the absence of blood flow. We demonstrate that HMPs improve the viability of S. elongatus during the injection process and allow for simple oxygen diffusion. Adult male Wistar rats (n = 45) underwent sham surgery, acute ischemia reperfusion surgery, or a chronic ischemia reperfusion surgery, followed by injection of phosphate buffered saline (PBS), S. elongatus suspended in PBS, HMPs, or S. elongatus encapsulated in HMPs. Treatment with S. elongatus-HMPs mitigated cellular apoptosis and improved left ventricular function. Thus, delivery of S. elongatus encapsulated in HMPs improves clinical translation by utilizing a minimally invasive delivery platform that improves S. elongatus viability and enhances the therapeutic benefit of a novel photosynthetic system for the treatment of myocardial ischemia.
View details for DOI 10.1016/j.jbiosc.2023.03.001
View details for PubMedID 36966053
High-throughput, quantitative measurements reveal the biophysical mechanisms by which transcription factor mutations drive disease
CELL PRESS. 2023: 171A
View details for Web of Science ID 000989629700835
High throughput measurements of direct activation domain-coactivator interactions
CELL PRESS. 2023: 68A
View details for Web of Science ID 000989629700339
- Alleviating Cell Lysate-Induced Inhibition to Enable RT-PCR from Single Cells in Picoliter-Volume Double Emulsion Droplets ANALYTICAL CHEMISTRY 2023; 95 (2): 935-945
Metasurface optofluidics for dynamic control of light fields.
The ability to manipulate light and liquids on integrated optofluidics chips has spurred a myriad of important developments in biology, medicine, chemistry and display technologies. Here we show how the convergence of optofluidics and metasurface optics can lead to conceptually new platforms for the dynamic control of light fields. We first demonstrate metasurface building blocks that display an extreme sensitivity in their scattering properties to their dielectric environment. These blocks are then used to create metasurface-based flat optics inside microfluidic channels where liquids with different refractive indices can be directed to manipulate their optical behaviour. We demonstrate the intensity and spectral tuning of metasurface colour pixels as well as on-demand optical elements. We finally demonstrate automated control in an integrated meta-optofluidic platform to open up new display functions. Combined with large-scale microfluidic integration, our dynamic-metasurface flat-optics platform could open up the possibility of dynamic display, imaging, holography and sensing applications.
View details for DOI 10.1038/s41565-022-01197-y
View details for PubMedID 36163507
- BATTLES: high-throughput screening of antigen recognition under force NATURE METHODS 2022
A bead-based method for high-throughput mapping of the sequence- and force-dependence of T cell activation.
Adaptive immunity relies on T lymphocytes that use alphabeta T cell receptors (TCRs) to discriminate among peptides presented by major histocompatibility complex molecules (pMHCs). Identifying pMHCs capable of inducing robust T cell responses will not only enable a deeper understanding of the mechanisms governing immune responses but could also have broad applications in diagnosis and treatment. T cell recognition of sparse antigenic pMHCs in vivo relies on biomechanical forces. However, in vitro screening methods test potential pMHCs without force and often at high (nonphysiological) pMHC densities and thus fail to predict potent agonists in vivo. Here, we present a technology termed BATTLES (biomechanically assisted T cell triggering for large-scale exogenous-pMHC screening) that uses biomechanical force to initiate T cell triggering for peptides and cells in parallel. BATTLES displays candidate pMHCs on spectrally encoded beads composed of a thermo-responsive polymer capable of applying shear loads to T cells, facilitating exploration of the force- and sequence-dependent landscape of T cell responses. BATTLES can be used to explore basic T cell mechanobiology and T cell-based immunotherapies.
View details for DOI 10.1038/s41592-022-01592-2
View details for PubMedID 36064771
Machine learning for microfluidic design and control.
Lab on a chip
Microfluidics has developed into a mature field with applications across science and engineering, having particular commercial success in molecular diagnostics, next-generation sequencing, and bench-top analysis. Despite its ubiquity, the complexity of designing and controlling custom microfluidic devices present major barriers to adoption, requiring intuitive knowledge gained from years of experience. If these barriers were overcome, microfluidics could miniaturize biological and chemical research for non-experts through fully-automated platform development and operation. The intuition of microfluidic experts can be captured through machine learning, where complex statistical models are trained for pattern recognition and subsequently used for event prediction. Integration of machine learning with microfluidics could significantly expand its adoption and impact. Here, we present the current state of machine learning for the design and control of microfluidic devices, its possible applications, and current limitations.
View details for DOI 10.1039/d2lc00254j
View details for PubMedID 35904162
Systematic characterization of effect of flow rates and buffer compositions on double emulsion droplet volumes and stability.
Lab on a chip
Double emulsion droplets (DEs) are water/oil/water droplets that can be sorted via fluorescence-activated cell sorting (FACS), allowing for new opportunities in high-throughput cellular analysis, enzymatic screening, and synthetic biology. These applications require stable, uniform droplets with predictable microreactor volumes. However, predicting DE droplet size, shell thickness, and stability as a function of flow rate has remained challenging for monodisperse single core droplets and those containing biologically-relevant buffers, which influence bulk and interfacial properties. As a result, developing novel DE-based bioassays has typically required extensive initial optimization of flow rates to find conditions that produce stable droplets of the desired size and shell thickness. To address this challenge, we conducted systematic size parameterization quantifying how differences in flow rates and buffer properties (viscosity and interfacial tension at water/oil interfaces) alter droplet size and stability, across 6 inner aqueous buffers used across applications such as cellular lysis, microbial growth, and drug delivery, quantifying the size and shell thickness of >22000 droplets overall. We restricted our study to stable single core droplets generated in a 2-step dripping-dripping formation regime in a straightforward PDMS device. Using data from 138 unique conditions (flow rates and buffer composition), we also demonstrated that a recent physically-derived size law of Wang et al. can accurately predict double emulsion shell thickness for >95% of observations. Finally, we validated the utility of this size law by using it to accurately predict droplet sizes for a novel bioassay that requires encapsulating growth media for bacteria in droplets. This work has the potential to enable new screening-based biological applications by simplifying novel DE bioassay development.
View details for DOI 10.1039/d2lc00229a
View details for PubMedID 35593127
Tuning T cell receptor sensitivity through catch bond engineering.
Science (New York, N.Y.)
2022; 376 (6589): eabl5282
Adoptive cell therapy using engineered T cell receptors (TCRs) is a promising approach for targeting cancer antigens, but tumor-reactive TCRs are often weakly responsive to their target ligands, peptide-major histocompatibility complexes (pMHCs). Affinity-matured TCRs can enhance the efficacy of TCR-T cell therapy but can also cross-react with off-target antigens, resulting in organ immunopathology. We developed an alternative strategy to isolate TCR mutants that exhibited high activation signals coupled with low-affinity pMHC binding through the acquisition of catch bonds. Engineered analogs of a tumor antigen MAGE-A3-specific TCR maintained physiological affinities while exhibiting enhanced target killing potency and undetectable cross-reactivity, compared with a high-affinity clinically tested TCR that exhibited lethal cross-reactivity with a cardiac antigen. Catch bond engineering is a biophysically based strategy to tune high-sensitivity TCRs for T cell therapy with reduced potential for adverse cross-reactivity.
View details for DOI 10.1126/science.abl5282
View details for PubMedID 35389803
uPIC-M: Efficient and Scalable Preparation of Clonal Single Mutant Libraries for High-Throughput Protein Biochemistry.
2021; 6 (45): 30542-30554
New high-throughput biochemistry techniques complement selection-based approaches and provide quantitative kinetic and thermodynamic data for thousands of protein variants in parallel. With these advances, library generation rather than data collection has become rate-limiting. Unlike pooled selection approaches, high-throughput biochemistry requires mutant libraries in which individual sequences are rationally designed, efficiently recovered, sequence-validated, and separated from one another, but current strategies are unable to produce these libraries at the needed scale and specificity at reasonable cost. Here, we present a scalable, rapid, and inexpensive approach for creating User-designed Physically Isolated Clonal-Mutant (uPIC-M) libraries that utilizes recent advances in oligo synthesis, high-throughput sample preparation, and next-generation sequencing. To demonstrate uPIC-M, we created a scanning mutant library of SpAP, a 541 amino acid alkaline phosphatase, and recovered 94% of desired mutants in a single iteration. uPIC-M uses commonly available equipment and freely downloadable custom software and can produce a 5000 mutant library at 1/3 the cost and 1/5 the time of traditional techniques.
View details for DOI 10.1021/acsomega.1c04180
View details for PubMedID 34805683
MRBLE-pep Measurements Reveal Accurate Binding Affinities for B56, a PP2A Regulatory Subunit.
ACS measurement science Au
2021; 1 (2): 56-64
Signal transduction pathways rely on dynamic interactions between protein globular domains and short linear motifs (SLiMs). The weak affinities of these interactions are essential to allow fast rewiring of signaling pathways and downstream responses but also pose technical challenges for interaction detection and measurement. We recently developed a technique (MRBLE-pep) that leverages spectrally encoded hydrogel beads to measure binding affinities between a single protein of interest and 48 different peptide sequences in a single small volume. In prior work, we applied it to map the binding specificity landscape between calcineurin and the PxIxIT SLiM (Nguyen, H. Q. et al. Elife 2019, 8). Here, using peptide sequences known to bind the PP2A regulatory subunit B56alpha, we systematically compare affinities measured by MRBLE-pep or isothermal calorimetry (ITC) and confirm that MRBLE-pep accurately quantifies relative affinity over a wide dynamic range while using a fraction of the material required for traditional methods such as ITC.
View details for DOI 10.1021/acsmeasuresciau.1c00008
View details for PubMedID 35128539
- Revealing enzyme functional architecture via high-throughput microfluidic enzyme kinetics SCIENCE 2021; 373 (6553): 411-+
Fundamentals to function: Quantitative and scalable approaches for measuring protein stability.
2021; 12 (6): 547-560
Folding a linear chain of amino acids into a three-dimensional protein is a complex physical process that ultimately confers an impressive range of diverse functions. Although recent advances have driven significant progress in predicting three-dimensional protein structures from sequence, proteins are not static molecules. Rather, they exist as complex conformational ensembles defined by energy landscapes spanning the space of sequence and conditions. Quantitatively mapping the physical parameters that dictate these landscapes and protein stability is therefore critical to develop models that are capable of predicting how mutations alter function of proteins in disease and informing the design of proteins with desired functions. Here, we review the approaches that are used to quantify protein stability at a variety of scales, from returning multiple thermodynamic and kinetic measurements for a single protein sequence to yielding indirect insights into folding across a vast sequence space. The physical parameters derived from these approaches will provide a foundation for models that extend beyond the structural prediction to capture the complexity of conformational ensembles and, ultimately, their function.
View details for DOI 10.1016/j.cels.2021.05.009
View details for PubMedID 34139165
Double Emulsion Picoreactors for High-Throughput Single-Cell Encapsulation and Phenotyping via FACS.
In the past five years, droplet microfluidic techniques have unlocked new opportunities for the high-throughput genome-wide analysis of single cells, transforming our understanding of cellular diversity and function. However, the field lacks an accessible method to screen and sort droplets based on cellular phenotype upstream of genetic analysis, particularly for large and complex cells. To meet this need, we developed Dropception, a robust, easy-to-use workflow for precise single-cell encapsulation into picoliter-scale double emulsion droplets compatible with high-throughput screening via fluorescence-activated cell sorting (FACS). We demonstrate the capabilities of this method by encapsulating five standardized mammalian cell lines of varying sizes and morphologies as well as a heterogeneous cell mixture of a whole dissociated flatworm (5-25 mum in diameter) within highly monodisperse double emulsions (35 mum in diameter). We optimize for preferential encapsulation of single cells with extremely low multiple-cell loading events (<2% of cell-containing droplets), thereby allowing direct linkage of cellular phenotype to genotype. Across all cell lines, cell loading efficiency approaches the theoretical limit with no observable bias by cell size. FACS measurements reveal the ability to discriminate empty droplets from those containing cells with good agreement to single-cell occupancies quantified via microscopy, establishing robust droplet screening at single-cell resolution. High-throughput FACS screening of cellular picoreactors has the potential to shift the landscape of single-cell droplet microfluidics by expanding the repertoire of current nucleic acid droplet assays to include functional phenotyping.
View details for DOI 10.1021/acs.analchem.0c02499
View details for PubMedID 32900183
Protocol for Peptide Synthesis on Spectrally Encoded Beads for MRBLE-pep Assays.
2020; 10 (13): e3669
Every living cell relies on signal transduction pathways comprised of protein-protein interactions (PPIs). In many cases, these PPIs are between a folded protein domain and a short linear motif (SLiM) within an unstructured region of a protein. As a result of this small interaction interface (3-10 amino acids), the affinities of SLiM-mediated interactions are typically weak (Kds of ~1-10 µM), allowing physiologically relevant changes in cellular concentrations of either protein partner to dictate changes in occupancy and thereby transmit cellular signals. However, these weak affinities also render detection and quantitative measurement of these interactions challenging and labor intensive. To address this, we recently developed MRBLE-pep, a technology that employs peptide libraries synthesized on spectrally encoded hydrogel beads to allow multiplexed affinity measurements between a protein and many different peptides in parallel. This approach dramatically reduces both the amount of protein and peptide as well as the time required to measure protein-peptide affinities compared to traditional methods. Here, we provide a detailed protocol describing how to: (1) functionalize polyethylene glycol diacrylate (PEG-DA) MRBLE beads with free amine groups, (2) synthesize peptide libraries on functionalized MRBLEs, (3) validate synthesized peptide sequences via MALDI mass spectrometry and quantify evenness of peptide coverage on MRBLEs, (4) use MRBLE-bound peptide libraries in multiplexed protein binding assays, and (5) analyze binding data to determine binding affinities. We anticipate that this protocol should prove useful for other researchers seeking to use MRBLE-pep in their own laboratories as well as for researchers broadly interested in solid-phase peptide synthesis and protein-protein binding assay development.
View details for DOI 10.21769/BioProtoc.3669
View details for PubMedID 33659339
View details for PubMedCentralID PMC7842318
- Protocol for Peptide Synthesis on Spectrally Encoded Beads for MRBLE-pep Assays BIO-PROTOCOL 2020; 10 (13)
Double emulsion flow cytometry with high-throughput single droplet isolation and nucleic acid recovery.
Lab on a chip
Droplet microfluidics has made large impacts in diverse areas such as enzyme evolution, chemical product screening, polymer engineering, and single-cell analysis. However, while droplet reactions have become increasingly sophisticated, phenotyping droplets by a fluorescent signal and sorting them to isolate individual variants-of-interest at high-throughput remains challenging. Here, we present sdDE-FACS (s[combining low line]ingle d[combining low line]roplet D[combining low line]ouble E[combining low line]mulsion-FACS), a new method that uses a standard flow cytometer to phenotype, select, and isolate individual double emulsion droplets of interest. Using a 130 mum nozzle at high sort frequency (12-14 kHz), we demonstrate detection of droplet fluorescence signals with a dynamic range spanning 5 orders of magnitude and robust post-sort recovery of intact double emulsion (DE) droplets using 2 commercially-available FACS instruments. We report the first demonstration of single double emulsion droplet isolation with post-sort recovery efficiencies >70%, equivalent to the capabilities of single-cell FACS. Finally, we establish complete downstream recovery of nucleic acids from single, sorted double emulsion droplets via qPCR with little to no cross-contamination. sdDE-FACS marries the full power of droplet microfluidics with flow cytometry to enable a variety of new droplet assays, including rare variant isolation and multiparameter single-cell analysis.
View details for DOI 10.1039/d0lc00261e
View details for PubMedID 32417874
- Leveraging Microfluidics for High-Throughput Studies of Transcription Factor/DNA Binding WILEY. 2020
A High-Throughput Assay Platform for Next-Generation Mechanistic Enzymology and Applications
CELL PRESS. 2020: 535A
View details for Web of Science ID 000513023203420
A High-Throughput Platform Characterizes Functional Effects of Transcription Factor Mutations
CELL PRESS. 2020: 74A–75A
View details for Web of Science ID 000513023200373
High-Throughput Affinity Measurements of Transcription Factor and DNA Mutations Reveal Affinity and Specificity Determinants.
Transcription factors (TFs) bind regulatory DNA to control gene expression, and mutations to either TFs or DNA can alter binding affinities to rewire regulatory networks and drive phenotypic variation. While studies have profiled energetic effects of DNA mutations extensively, we lack similar information for TF variants. Here, we present STAMMP (simultaneous transcription factor affinity measurements via microfluidic protein arrays), a high-throughput microfluidic platform enabling quantitative characterization of hundreds of TF variants simultaneously. Measured affinities for ∼210 mutants of a model yeast TF (Pho4) interacting with 9 oligonucleotides (>1,800 Kds) reveal that many combinations of mutations to poorly conserved TF residues and nucleotides flanking the core binding site alter but preserve physiological binding, providing a mechanism by which combinations of mutations in cis and trans could modulate TF binding to tune occupancies during evolution. Moreover, biochemical double-mutant cycles across the TF-DNA interface reveal molecular mechanisms driving recognition, linking sequence to function. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.
View details for DOI 10.1016/j.cels.2020.11.012
View details for PubMedID 33340452
DeCoDe: degenerate codon design for complete protein-coding DNA libraries.
Bioinformatics (Oxford, England)
High-throughput protein screening is a critical technique for dissecting and designing protein function. Libraries for these assays can be created through a number of means, including targeted or random mutagenesis of a template protein sequence or direct DNA synthesis. However, mutagenic library construction methods often yield vastly more non-functional than functional variants and, despite advances in large-scale DNA synthesis, individual synthesis of each desired DNA template is often prohibitively expensive. Consequently, many protein screening libraries rely on the use of degenerate codons (DCs), mixtures of DNA bases incorporated at specific positions during DNA synthesis, to generate highly diverse protein variant pools from only a few low-cost synthesis reactions. However, selecting DCs for sets of sequences that covary at multiple positions dramatically increases the difficulty of designing a DC library and leads to the creation of many undesired variants that can quickly outstrip screening capacity.We introduce a novel algorithm for total DC library optimization, DeCoDe, based on integer linear programming. DeCoDe significantly outperforms state-of-the-art DC optimization algorithms and scales well to more than a hundred proteins sharing complex patterns of covariation (e.g., the lab-derived avGFP lineage). Moreover, DeCoDe is, to our knowledge, the first DC design algorithm with the capability to encode mixed-length protein libraries. We anticipate DeCoDe to be broadly useful for a variety of library generation problems, ranging from protein engineering attempts that leverage mutual information to the reconstruction of ancestral protein states.github.com/OrensteinLab/DeCoDe.Supplementary data are available at Bioinformatics online.
View details for DOI 10.1093/bioinformatics/btaa162
View details for PubMedID 32176271
MRBLES 2.0: High-throughput generation of chemically functionalized spectrally and magnetically encoded hydrogel beads using a simple single-layer microfluidic device.
Microsystems & nanoengineering
2020; 6: 109
The widespread adoption of bead-based multiplexed bioassays requires the ability to easily synthesize encoded microspheres and conjugate analytes of interest to their surface. Here, we present a simple method (MRBLEs 2.0) for the efficient high-throughput generation of microspheres with ratiometric barcode lanthanide encoding (MRBLEs) that bear functional groups for downstream surface bioconjugation. Bead production in MRBLEs 2.0 relies on the manual mixing of lanthanide/polymer mixtures (each of which comprises a unique spectral code) followed by droplet generation using single-layer, parallel flow-focusing devices and the off-chip batch polymerization of droplets into beads. To streamline downstream analyte coupling, MRBLEs 2.0 crosslinks copolymers bearing functional groups on the bead surface during bead generation. Using the MRBLEs 2.0 pipeline, we generate monodisperse MRBLEs containing 48 distinct well-resolved spectral codes with high throughput (>150,000/min and can be boosted to 450,000/min). We further demonstrate the efficient conjugation of oligonucleotides and entire proteins to carboxyl MRBLEs and of biotin to amino MRBLEs. Finally, we show that MRBLEs can also be magnetized via the simultaneous incorporation of magnetic nanoparticles with only a minor decrease in the potential code space. With the advantages of dramatically simplified device fabrication, elimination of the need for custom-made equipment, and the ability to produce spectrally and magnetically encoded beads with direct surface functionalization with high throughput, MRBLEs 2.0 can be directly applied by many labs towards a wide variety of downstream assays, from basic biology to diagnostics and other translational research.
View details for DOI 10.1038/s41378-020-00220-3
View details for PubMedID 33299601
Quantitative mapping of protein-peptide affinity landscapes using spectrally encoded beads.
Transient, regulated binding of globular protein domains to Short Linear Motifs (SLiMs) in disordered regions of other proteins drives cellular signaling. Mapping the energy landscapes of these interactions is essential for deciphering and perturbing signaling networks but is challenging due to their weak affinities. We present a powerful technology (MRBLE-pep) that simultaneously quantifies protein binding to a library of peptides directly synthesized on beads containing unique spectral codes. Using MRBLE-pep, we systematically probe binding of human calcineurin (CN), a conserved protein phosphatase essential for the immune response and target of immunosuppressants, to the PxIxIT SLiM. We discover that flanking residues and post-translational modifications critically contribute to PxIxIT-CN affinity and identify CN-binding peptides based on multiple scaffolds with a wide range of affinities. The quantitative biophysical data provided by this approach will improve computational modeling efforts, elucidate a broad range of weak protein-SLiM interactions, and revolutionize our understanding of signaling networks.
View details for DOI 10.7554/eLife.40499
View details for PubMedID 31282865
Live imaging of Aiptasia larvae, a model system for coral and anemone bleaching, using a simple microfluidic device.
2019; 9 (1): 9275
Coral reefs, and their associated diverse ecosystems, are of enormous ecological importance. In recent years, coral health has been severely impacted by environmental stressors brought on by human activity and climate change, threatening the extinction of several major reef ecosystems. Reef damage is mediated by a process called 'coral bleaching' where corals, sea anemones, and other cnidarians lose their photosynthetic algal symbionts (family Symbiodiniaceae) upon stress induction, resulting in drastically decreased host energy harvest and, ultimately, coral death. The mechanism by which this critical cnidarian-algal symbiosis is lost remains poorly understood. The larvae of the sea anemone, Exaiptasia pallida (commonly referred to as 'Aiptasia') are an attractive model organism to study this process, but they are large (100 mm in length, 75 mm in diameter), deformable, and highly motile, complicating long-term imaging and limiting study of this critical endosymbiotic relationship in live organisms. Here, we report 'Traptasia', a simple microfluidic device with multiple traps designed to isolate and image individual, live larvae of Aiptasia and their algal symbionts over extended time courses. Using a trap design parameterized via fluid flow simulations and polymer bead loading tests, we trapped Aiptasia larvae containing algal symbionts and demonstrated stable imaging for >10 hours. We visualized algae within Aiptasia larvae and observed algal expulsion under an environmental stressor. To our knowledge, this device is the first to enable time-lapsed, high-throughput live imaging of cnidarian larvae and their algal symbionts and, in further implementation, could provide important insights into the cellular mechanisms of cnidarian bleaching under different environmental stressors. The 'Traptasia' device is simple to use, requires minimal external equipment and no specialized training to operate, and can easily be adapted using the trap optimization data presented here to study a variety of large, motile organisms.
View details for DOI 10.1038/s41598-019-45167-2
View details for PubMedID 31239506
- An open-source software analysis package for Microspheres with Ratiometric Barcode Lanthanide Encoding (MRBLEs) PLOS ONE 2019; 14 (3)
- A Microfluidics-Based Assay for Mapping Connectivity in Highly Proficient Enzymes Reveals Functional Modularity CELL PRESS. 2019: 66A
- A High-Throughput Platform for Probing Mechanisms of Transcription Factor-DNA Binding CELL PRESS. 2019: 502A
- Deep Learning Models Explore the Structural Effects of Transcription Factor-DNA Complexes on Binding Specificity CELL PRESS. 2019: 503A
- Bringing Enzymology into the Genomic Era: Developing and Deploying New Tools to Quantitatively Map Functional Connections Throughout an Enzyme CELL PRESS. 2019: 23A
An open-source software analysis package for Microspheres with Ratiometric Barcode Lanthanide Encoding (MRBLEs).
2019; 14 (3): e0203725
Multiplexed bioassays, in which multiple analytes of interest are probed in parallel within a single small volume, have greatly accelerated the pace of biological discovery. Bead-based multiplexed bioassays have many technical advantages, including near solution-phase kinetics, small sample volume requirements, many within-assay replicates to reduce measurement error, and, for some bead materials, the ability to synthesize analytes directly on beads via solid-phase synthesis. To allow bead-based multiplexing, analytes can be synthesized on spectrally encoded beads with a 1:1 linkage between analyte identity and embedded codes. Bead-bound analyte libraries can then be pooled and incubated with a fluorescently-labeled macromolecule of interest, allowing downstream quantification of interactions between the macromolecule and all analytes simultaneously via imaging alone. Extracting quantitative binding data from these images poses several computational image processing challenges, requiring the ability to identify all beads in each image, quantify bound fluorescent material associated with each bead, and determine their embedded spectral code to reveal analyte identities. Here, we present a novel open-source Python software package (the mrbles analysis package) that provides the necessary tools to: (1) find encoded beads in a bright-field microscopy image; (2) quantify bound fluorescent material associated with bead perimeters; (3) identify embedded ratiometric spectral codes within beads; and (4) return data aggregated by embedded code and for each individual bead. We demonstrate the utility of this package by applying it towards analyzing data generated via multiplexed measurement of calcineurin protein binding to MRBLEs (Microspheres with Ratiometric Barcode Lanthanide Encoding) containing known and mutant binding peptide motifs. We anticipate that this flexible package should be applicable to a wide variety of assays, including simple bead or droplet finding analysis, quantification of binding to non-encoded beads, and analysis of multiplexed assays that use ratiometric, spectrally encoded beads.
View details for PubMedID 30901328
micrIO: an open-source autosampler and fraction collector for automated microfluidic input-output.
Lab on a chip
Microfluidic devices are an enabling technology for many labs, facilitating a wide range of applications spanning high-throughput encapsulation, molecular separations, and long-term cell culture. In many cases, however, their utility is limited by a 'world-to-chip' barrier that makes it difficult to serially interface samples with these devices. As a result, many researchers are forced to rely on low-throughput, manual approaches for managing device input and output (IO) of samples, reagents, and effluent. Here, we present a hardware-software platform for automated microfluidic IO (micrIO). The platform, which is uniquely compatible with positive-pressure microfluidics, comprises an 'AutoSipper' for input and a 'Fraction Collector' for output. To facilitate widespread adoption, both are open-source builds constructed from components that are readily purchased online or fabricated from included design files. The software control library, written in Python, allows the platform to be integrated with existing experimental setups and to coordinate IO with other functions such as valve actuation and assay imaging. We demonstrate these capabilities by coupling both the AutoSipper and Fraction Collector to two microfluidic devices: a simple, valved inlet manifold and a microfluidic droplet generator that produces beads with distinct spectral codes. Analysis of the collected materials in each case establishes the ability of the platform to draw from and output to specific wells of multiwell plates with negligible cross-contamination between samples.
View details for DOI 10.1039/c9lc00512a
View details for PubMedID 31701110
Satb1 integrates DNA binding site geometry and torsional stress to differentially target nucleosome-dense regions.
2019; 10 (1): 3221
The Satb1 genome organizer regulates multiple cellular and developmental processes. It is not yet clear how Satb1 selects different sets of targets throughout the genome. Here we have used live-cell single molecule imaging and deep sequencing to assess determinants of Satb1 binding-site selectivity. We have found that Satb1 preferentially targets nucleosome-dense regions and can directly bind consensus motifs within nucleosomes. Some genomic regions harbor multiple, regularly spaced Satb1 binding motifs (typical separation ~1 turn of the DNA helix) characterized by highly cooperative binding. The Satb1 homeodomain is dispensable for high affinity binding but is essential for specificity. Finally, we find that Satb1-DNA interactions are mechanosensitive. Increasing negative torsional stress in DNA enhances Satb1 binding and Satb1 stabilizes base unpairing regions against melting by molecular machines. The ability of Satb1 to control diverse biological programs may reflect its ability to combinatorially use multiple site selection criteria.
View details for DOI 10.1038/s41467-019-11118-8
View details for PubMedID 31324780
Diversification of DNA binding specificities enabled SREBP transcription regulators to expand the repertoire of cellular functions that they govern in fungi.
2018; 14 (12): e1007884
The Sterol Regulatory Element Binding Proteins (SREBPs) are basic-helix-loop-helix transcription regulators that control the expression of sterol biosynthesis genes in higher eukaryotes and some fungi. Surprisingly, SREBPs do not regulate sterol biosynthesis in the ascomycete yeasts (Saccharomycotina) as this role was handed off to an unrelated transcription regulator in this clade. The SREBPs, nonetheless, expanded in fungi such as the ascomycete yeasts Candida spp., raising questions about their role and evolution in these organisms. Here we report that the fungal SREBPs diversified their DNA binding preferences concomitantly with an expansion in function. We establish that several branches of fungal SREBPs preferentially bind non-palindromic DNA sequences, in contrast to the palindromic DNA motifs recognized by most basic-helix-loop-helix proteins (including SREBPs) in higher eukaryotes. Reconstruction and biochemical characterization of the likely ancestor protein suggest that an intrinsic DNA binding promiscuity in the family was resolved by alternative mechanisms in different branches of fungal SREBPs. Furthermore, we show that two SREBPs in the human commensal yeast Candida albicans drive a transcriptional cascade that inhibits a morphological switch under anaerobic conditions. Preventing this morphological transition enhances C. albicans colonization of the mammalian intestine, the fungus' natural niche. Thus, our results illustrate how diversification in DNA binding preferences enabled the functional expansion of a family of eukaryotic transcription regulators.
View details for PubMedID 30596634
High-throughput chromatin accessibility profiling at single-cell resolution.
2018; 9 (1): 3647
Here we develop a high-throughput single-cell ATAC-seq (assay for transposition of accessible chromatin) method to measure physical access to DNA in whole cells. Our approach integrates fluorescence imaging and addressable reagent deposition across a massively parallel (5184) nano-well array, yielding a nearly 20-fold improvement in throughput (up to ~1800 cells/chip, 4-5h on-chip processing time) and library preparationcost (~81 per cell) compared to prior microfluidic implementations. We apply this method to measure regulatory variation in peripheral blood mononuclear cells (PBMCs) and show robust, de novo clustering of single cells by hematopoietic cell type.
View details for PubMedID 30194434
Discovering epistatic feature interactions from neural network models of regulatory DNA sequences.
Bioinformatics (Oxford, England)
2018; 34 (17): i629-i637
Transcription factors bind regulatory DNA sequences in a combinatorial manner to modulate gene expression. Deep neural networks (DNNs) can learn the cis-regulatory grammars encoded in regulatory DNA sequences associated with transcription factor binding and chromatin accessibility. Several feature attribution methods have been developed for estimating the predictive importance of individual features (nucleotides or motifs) in any input DNA sequence to its associated output prediction from a DNN model. However, these methods do not reveal higher-order feature interactions encoded by the models.We present a new method called Deep Feature Interaction Maps (DFIM) to efficiently estimate interactions between all pairs of features in any input DNA sequence. DFIM accurately identifies ground truth motif interactions embedded in simulated regulatory DNA sequences. DFIM identifies synergistic interactions between GATA1 and TAL1 motifs from in vivo TF binding models. DFIM reveals epistatic interactions involving nucleotides flanking the core motif of the Cbf1 TF in yeast from in vitro TF binding models. We also apply DFIM to regulatory sequence models of in vivo chromatin accessibility to reveal interactions between regulatory genetic variants and proximal motifs of target TFs as validated by TF binding quantitative trait loci. Our approach makes significant strides in improving the interpretability of deep learning models for genomics.Code is available at: https://github.com/kundajelab/dfim.Supplementary data are available at Bioinformatics online.
View details for DOI 10.1093/bioinformatics/bty575
View details for PubMedID 30423062
View details for PubMedCentralID PMC6129272
- Discovering epistatic feature interactions from neural network models of regulatory DNA sequences OXFORD UNIV PRESS. 2018: 629–37
Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2018; 115 (16): E3702–E3711
Transcription factors (TFs) are primary regulators of gene expression in cells, where they bind specific genomic target sites to control transcription. Quantitative measurements of TF-DNA binding energies can improve the accuracy of predictions of TF occupancy and downstream gene expression in vivo and shed light on how transcriptional networks are rewired throughout evolution. Here, we present a sequencing-based TF binding assay and analysis pipeline (BET-seq, for Binding Energy Topography by sequencing) capable of providing quantitative estimates of binding energies for more than one million DNA sequences in parallel at high energetic resolution. Using this platform, we measured the binding energies associated with all possible combinations of 10 nucleotides flanking the known consensus DNA target interacting with two model yeast TFs, Pho4 and Cbf1. A large fraction of these flanking mutations change overall binding energies by an amount equal to or greater than consensus site mutations, suggesting that current definitions of TF binding sites may be too restrictive. By systematically comparing estimates of binding energies output by deep neural networks (NNs) and biophysical models trained on these data, we establish that dinucleotide (DN) specificities are sufficient to explain essentially all variance in observed binding behavior, with Cbf1 binding exhibiting significantly more nonadditivity than Pho4. NN-derived binding energies agree with orthogonal biochemical measurements and reveal that dynamically occupied sites in vivo are both energetically and mutationally distant from the highest affinity sites.
View details for PubMedID 29588420
An Open-Source, Programmable Pneumatic Setup for Operation and Automated Control of Single- and Multi-Layer Microfluidic Devices.
2018; 3: 117–34
Microfluidic technologies have been used across diverse disciplines (e.g. high-throughput biological measurement, fluid physics, laboratory fluid manipulation) but widespread adoption has been limited in part due to the lack of openly disseminated resources that enable non-specialist labs to make and operate their own devices. Here, we report the open-source build of a pneumatic setup capable of operating both single and multilayer (Quake-style) microfluidic devices with programmable scripting automation. This setup can operate both simple and complex devices with 48 device valve control inputs and 18 sample inputs, with modular design for easy expansion, at a fraction of the cost of similar commercial solutions. We present a detailed step-by-step guide to building the pneumatic instrumentation, as well as instructions for custom device operation using our software, Geppetto, through an easy-to-use GUI for live on-chip valve actuation and a scripting system for experiment automation. We show robust valve actuation with near real-time software feedback and demonstrate use of the setup for high-throughput biochemical measurements on-chip. This open-source setup will enable specialists and novices alike to run microfluidic devices easily in their own laboratories.
View details for PubMedID 30221210
BET-seq: Binding energy topographies revealed by microfluidics and high-throughput sequencing.
Methods in cell biology
2018; 148: 229–50
Biophysical models of transcriptional regulation rely on energetic measurements of the binding affinities between transcription factors (TFs) and target DNA binding sites. Historically, assays capable of measuring TF-DNA binding affinities have been relatively low-throughput (measuring ~103 sequences in parallel) and have required significant specialized equipment, limiting their use to a handful of laboratories. Recently, we developed an experimental assay and analysis pipeline that allows measurement of binding energies between a single TF and up to 106 DNA species in a single experiment (Binding Energy Topography by sequencing, or BET-seq) (Le et al., 2018). BET-seq employs the Mechanically Induced Trapping of Molecular Interactions (MITOMI) platform to purify DNA bound to a TF at equilibrium followed by high coverage sequencing to reveal relative differences in binding energy for each sequence. While we have previously used BET-seq to refine the binding affinity landscapes surrounding high-affinity DNA consensus target sites, we anticipate this technique will be applied in future work toward measuring a wide variety of TF-DNA landscapes. Here, we provide detailed instructions and general considerations for DNA library design, performing BET-seq assays, and analyzing the resulting data.
View details for PubMedID 30473071
Optimized Sequence Library Design for Efficient In Vitro Interaction Mapping.
2017; 5 (3): 230-236.e5
Sequence libraries that cover all k-mers enable universal, unbiased measurements of binding to both oligonucleotides and peptides. While the number of k-mers grows exponentially in k, space on all experimental platforms is limited. Here, we shrink k-mer library sizes by using joker characters, which represent all characters in the alphabet simultaneously. We present the JokerCAKE (joker covering all k-mers) algorithm for generating a short sequence such that each k-mer appears at least p times with at most one joker character per k-mer. By running our algorithm on a range of parameters and alphabets, we show that JokerCAKE produces near-optimal sequences. Moreover, through comparison with data from hundreds of DNA-protein binding experiments and with new experimental results for both standard and JokerCAKE libraries, we establish that accurate binding scores can be inferred for high-affinity k-mers using JokerCAKE libraries. JokerCAKE libraries allow researchers to search a significantly larger sequence space using the same number of experimental measurements and at the same cost.
View details for DOI 10.1016/j.cels.2017.07.006
View details for PubMedID 28957657
View details for PubMedCentralID PMC5661997
- Programmable Microfluidic Synthesis of Over One Thousand Uniquely Identifiable Spectral Codes ADVANCED OPTICAL MATERIALS 2017; 5 (3)
Multi-step Variable Height Photolithography for Valved Multilayer Microfluidic Devices.
Journal of visualized experiments : JoVE
Microfluidic systems have enabled powerful new approaches to high-throughput biochemical and biological analysis. However, there remains a barrier to entry for non-specialists who would benefit greatly from the ability to develop their own microfluidic devices to address research questions. Particularly lacking has been the open dissemination of protocols related to photolithography, a key step in the development of a replica mold for the manufacture of polydimethylsiloxane (PDMS) devices. While the fabrication of single height silicon masters has been explored extensively in literature, fabrication steps for more complicated photolithography features necessary for many interesting device functionalities (such as feature rounding to make valve structures, multi-height single-mold patterning, or high aspect ratio definition) are often not explicitly outlined. Here, we provide a complete protocol for making multilayer microfluidic devices with valves and complex multi-height geometries, tunable for any application. These fabrication procedures are presented in the context of a microfluidic hydrogel bead synthesizer and demonstrate the production of droplets containing polyethylene glycol (PEG diacrylate) and a photoinitiator that can be polymerized into solid beads. This protocol and accompanying discussion provide a foundation of design principles and fabrication methods that enables development of a wide variety of microfluidic devices. The details included here should allow non-specialists to design and fabricate novel devices, thereby bringing a host of recently developed technologies to their most exciting applications in biological laboratories.
View details for DOI 10.3791/55276
View details for PubMedID 28190039
Joker de Bruijn: Sequence Libraries to Cover All k-mers Using Joker Characters
SPRINGER-VERLAG BERLIN. 2017: 389–90
View details for PubMedID 29707702
How duplicated transcription regulators can diversify to govern the expression of nonoverlapping sets of genes
GENES & DEVELOPMENT
2014; 28 (12): 1272-1277
The duplication of transcription regulators can elicit major regulatory network rearrangements over evolutionary timescales. However, few examples of duplications resulting in gene network expansions are understood in molecular detail. Here we show that four Candida albicans transcription regulators that arose by successive duplications have differentiated from one another by acquiring different intrinsic DNA-binding specificities, different preferences for half-site spacing, and different associations with cofactors. The combination of these three mechanisms resulted in each of the four regulators controlling a distinct set of target genes, which likely contributed to the adaption of this fungus to its human host. Our results illustrate how successive duplications and diversification of an ancestral transcription regulator can underlie major changes in an organism's regulatory circuitry.
View details for DOI 10.1101/gad.242271.114
View details for Web of Science ID 000337991000002
View details for PubMedID 24874988
Structure of the transcriptional network controlling white-opaque switching in Candida albicans
2013; 90 (1): 22-35
The human fungal pathogen Candida albicans can switch between two phenotypic cell types, termed 'white' and 'opaque'. Both cell types are heritable for many generations, and the switch between the two types occurs epigenetically, that is, without a change in the primary DNA sequence of the genome. Previous work identified six key transcriptional regulators important for white-opaque switching: Wor1, Wor2, Wor3, Czf1, Efg1, and Ahr1. In this work, we describe the structure of the transcriptional network that specifies the white and opaque cell types and governs the ability to switch between them. In particular, we use a combination of genome-wide chromatin immunoprecipitation, gene expression profiling, and microfluidics-based DNA binding experiments to determine the direct and indirect regulatory interactions that form the switch network. The six regulators are arranged together in a complex, interlocking network with many seemingly redundant and overlapping connections. We propose that the structure (or topology) of this network is responsible for the epigenetic maintenance of the white and opaque states, the switching between them, and the specialized properties of each state.
View details for DOI 10.1111/mmi.12329
View details for Web of Science ID 000324950600003
View details for PubMedID 23855748
Microfluidic affinity and ChIP-seq analyses converge on a conserved FOXP2-binding motif in chimp and human, which enables the detection of evolutionarily novel targets
NUCLEIC ACIDS RESEARCH
2013; 41 (12): 5991-6004
The transcription factor forkhead box P2 (FOXP2) is believed to be important in the evolution of human speech. A mutation in its DNA-binding domain causes severe speech impairment. Humans have acquired two coding changes relative to the conserved mammalian sequence. Despite intense interest in FOXP2, it has remained an open question whether the human protein's DNA-binding specificity and chromatin localization are conserved. Previous in vitro and ChIP-chip studies have provided conflicting consensus sequences for the FOXP2-binding site. Using MITOMI 2.0 microfluidic affinity assays, we describe the binding site of FOXP2 and its affinity profile in base-specific detail for all substitutions of the strongest binding site. We find that human and chimp FOXP2 have similar binding sites that are distinct from previously suggested consensus binding sites. Additionally, through analysis of FOXP2 ChIP-seq data from cultured neurons, we find strong overrepresentation of a motif that matches our in vitro results and identifies a set of genes with FOXP2 binding sites. The FOXP2-binding sites tend to be conserved, yet we identified 38 instances of evolutionarily novel sites in humans. Combined, these data present a comprehensive portrait of FOXP2's-binding properties and imply that although its sequence specificity has been conserved, some of its genomic binding sites are newly evolved.
View details for DOI 10.1093/nar/gkt259
View details for Web of Science ID 000321057100012
View details for PubMedID 23625967
Identification and characterization of a previously undescribed family of sequence-specific DNA-binding domains
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2013; 110 (19): 7660-7665
Sequence-specific DNA-binding proteins are among the most important classes of gene regulatory proteins, controlling changes in transcription that underlie many aspects of biology. In this work, we identify a transcriptional regulator from the human fungal pathogen Candida albicans that binds DNA specifically but has no detectable homology with any previously described DNA- or RNA-binding protein. This protein, named White-Opaque Regulator 3 (Wor3), regulates white-opaque switching, the ability of C. albicans to switch between two heritable cell types. We demonstrate that ectopic overexpression of WOR3 results in mass conversion of white cells to opaque cells and that deletion of WOR3 affects the stability of opaque cells at physiological temperatures. Genome-wide chromatin immunoprecipitation of Wor3 and gene expression profiling of a wor3 deletion mutant strain indicate that Wor3 is highly integrated into the previously described circuit regulating white-opaque switching and that it controls a subset of the opaque transcriptional program. We show by biochemical, genetic, and microfluidic experiments that Wor3 binds directly to DNA in a sequence-specific manner, and we identify the set of cis-regulatory sequences recognized by Wor3. Bioinformatic analyses indicate that the Wor3 family arose more recently in evolutionary time than most previously described DNA-binding domains; it is restricted to a small number of fungi that include the major fungal pathogens of humans. These observations show that new families of sequence-specific DNA-binding proteins may be restricted to small clades and suggest that current annotations--which rely on deep conservation--underestimate the fraction of genes coding for transcriptional regulators.
View details for DOI 10.1073/pnas.1221734110
View details for Web of Science ID 000319327700041
View details for PubMedID 23610392
Programmable microfluidic synthesis of spectrally encoded microspheres
LAB ON A CHIP
2012; 12 (22): 4716-4723
Spectrally encoded fluorescent beads are an attractive platform for assay miniaturization and multiplexing in the biological sciences. Here, we synthesize hydrophilic PEG-acrylate polymer beads encoded with lanthanide nanophosphors using a fully automated microfluidic synthesis device. These beads are encoded by including varying amounts of two lanthanide nanophosphors relative to a third reference nanophosphor to generate 24 distinct ratios. These codes differ by less than 3% from their target values and can be distinguished from each other with an error rate of <0.1%. The encoded bead synthesis strategy we have used is readily extensible to larger numbers of codes, potentially up to millions, providing a new platform technology for assay multiplexing.
View details for DOI 10.1039/c2lc40699c
View details for Web of Science ID 000310865200017
View details for PubMedID 23042484
Basic leucine zipper transcription factor Hac1 binds DNA in two distinct modes as revealed by microfluidic analyses
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2012; 109 (45): E3084-E3093
A quantitative understanding of how transcription factors interact with genomic target sites is crucial for reconstructing transcriptional networks in vivo. Here, we use Hac1, a well-characterized basic leucine zipper (bZIP) transcription factor involved in the unfolded protein response (UPR) as a model to investigate interactions between bZIP transcription factors and their target sites. During the UPR, the accumulation of unfolded proteins leads to unconventional splicing and subsequent translation of HAC1 mRNA, followed by transcription of UPR target genes. Initial candidate-based approaches identified a canonical cis-acting unfolded protein response element (UPRE-1) within target gene promoters; however, subsequent studies identified a large set of Hac1 target genes lacking this UPRE-1 and containing a different motif (UPRE-2). Using a combination of unbiased and directed microfluidic DNA binding assays, we established that Hac1 binds in two distinct modes: (i) to short (6-7 bp) UPRE-2-like motifs and (ii) to significantly longer (11-13 bp) extended UPRE-1-like motifs. Using a genetic screen, we demonstrate that a region of extended homology N-terminal to the basic DNA binding domain is required for this dual site recognition. These results establish Hac1 as the first bZIP transcription factor known to adopt more than one binding mode and unify previously conflicting and discrepant observations of Hac1 function into a cohesive model of UPR target gene activation. Our results also suggest that even structurally simple transcription factors can recognize multiple divergent target sites of very different lengths, potentially enriching their downstream target repertoire.
View details for DOI 10.1073/pnas.1212457109
View details for Web of Science ID 000311156700009
View details for PubMedID 23054834
View details for PubMedCentralID PMC3494901
Systematic characterization of feature dimensions and closing pressures for microfluidic valves produced via photoresist reflow
LAB ON A CHIP
2012; 12 (21): 4287-4295
Multilayer soft lithography (MSL) provides a convenient and low-cost method for fabricating poly(dimethyl siloxane) (PDMS) microfluidic devices with on-chip valves for automated and precise control of fluid flow. MSL casting molds for flow channels typically incorporate small patches of rounded positive photoresist at valve locations to achieve the rounded cross-sectional profile required for these valves to function properly. Despite the importance of these rounded features for device performance, a comprehensive characterization of how the rounding process affects feature dimensions and closing pressures has been lacking. Here, we measure valve dimensions both before and after rounding and closing pressures for 120 different valve widths and lengths at post-rounding heights between 15 and 84 μm, for a total of 1200 different geometries spanning a wide range of useful sizes. We find that valve height and width after rounding depend strongly on valve aspect ratios, with these effects becoming more pronounced for taller and narrower features. Based on the measured data, we provide a simple fitted model and an online tool for estimating the pre-rounding dimensions needed to achieve desired post-rounding dimensions. We also find that valve closing pressures are well explained by modelling valve membranes in a manner analogous to a suspension bridge, shedding new light on device physics and providing a practical model for estimating closing pressures during device design.
View details for DOI 10.1039/c2lc40414a
View details for Web of Science ID 000310916100012
View details for PubMedID 22930180
De novo identification and biophysical characterization of transcription-factor binding sites with microfluidic affinity analysis
2010; 28 (9): 970-976
Gene expression is regulated in part by protein transcription factors that bind target regulatory DNA sequences. Predicting DNA binding sites and affinities from transcription factor sequence or structure is difficult; therefore, experimental data are required to link transcription factors to target sequences. We present a microfluidics-based approach for de novo discovery and quantitative biophysical characterization of DNA target sequences. We validated our technique by measuring sequence preferences for 28 Saccharomyces cerevisiae transcription factors with a variety of DNA-binding domains, including several that have proven difficult to study by other techniques. For each transcription factor, we measured relative binding affinities to oligonucleotides covering all possible 8-bp DNA sequences to create a comprehensive map of sequence preferences; for four transcription factors, we also determined absolute affinities. We expect that these data and future use of this technique will provide information essential for understanding transcription factor specificity, improving identification of regulatory sites and reconstructing regulatory interactions.
View details for DOI 10.1038/nbt.1675
View details for Web of Science ID 000281719100024
View details for PubMedID 20802496
View details for PubMedCentralID PMC2937095
Individual dimers of the mitotic kinesin motor Eg5 step processively and support substantial loads in vitro
NATURE CELL BIOLOGY
2006; 8 (5): 470-U89
Eg5, a member of the kinesin superfamily of microtubule-based motors, is essential for bipolar spindle assembly and maintenance during mitosis, yet little is known about the mechanisms by which it accomplishes these tasks. Here, we used an automated optical trapping apparatus in conjunction with a novel motility assay that employed chemically modified surfaces to probe the mechanochemistry of Eg5. Individual dimers, formed by a recombinant human construct Eg5-513-5His, stepped processively along microtubules in 8-nm increments, with short run lengths averaging approximately eight steps. By varying the applied load (with a force clamp) and the ATP concentration, we found that the velocity of Eg5 was slower and less sensitive to external load than that of conventional kinesin, possibly reflecting the distinct demands of spindle assembly as compared with vesicle transport. The Eg5-513-5His velocity data were described by a minimal, three-state model where a force-dependent transition follows nucleotide binding.
View details for DOI 10.1038/ncb1394
View details for Web of Science ID 000237299400010
View details for PubMedID 16604065
View details for PubMedCentralID PMC1523314
Eg5 steps it up!
Understanding how molecular motors generate force and move microtubules in mitosis is essential to understanding the physical mechanism of cell division. Recent measurements have shown that one mitotic kinesin superfamily member, Eg5, is mechanically processive and capable of crosslinking and sliding microtubules in vitro. In this review, we highlight recent work that explores how Eg5 functions under load, with an emphasis on the nanomechanical properties of single enzymes.
View details for DOI 10.1186/1747-1028-1-31
View details for Web of Science ID 000207723600031
View details for PubMedID 17173688
View details for PubMedCentralID PMC1716758
Simultaneous, coincident optical trapping and single-molecule fluorescence
2004; 1 (2): 133-139
We constructed a microscope-based instrument capable of simultaneous, spatially coincident optical trapping and single-molecule fluorescence. The capabilities of this apparatus were demonstrated by studying the force-induced strand separation of a dye-labeled, 15-base-pair region of double-stranded DNA (dsDNA), with force applied either parallel ('unzipping' mode) or perpendicular ('shearing' mode) to the long axis of the region. Mechanical transitions corresponding to DNA hybrid rupture occurred simultaneously with discontinuous changes in the fluorescence emission. The rupture force was strongly dependent on the direction of applied force, indicating the existence of distinct unbinding pathways for the two force-loading modes. From the rupture force histograms, we determined the distance to the thermodynamic transition state and the thermal off rates in the absence of load for both processes.
View details for DOI 10.1038/NMETH714
View details for Web of Science ID 000226753800017
View details for PubMedID 15782176
View details for PubMedCentralID PMC1483847
Stepping and stretching - How kinesin uses internal strain to walk processively
JOURNAL OF BIOLOGICAL CHEMISTRY
2003; 278 (20): 18550-18556
The ability of kinesin to travel long distances on its microtubule track without dissociating has led to a variety of models to explain how this remarkable degree of processivity is maintained. All of these require that the two motor domains remain enzymatically "out of phase," a behavior that would ensure that, at any given time, one motor is strongly attached to the microtubule. The maintenance of this coordination over many mechanochemical cycles has never been explained, because key steps in the cycle could not be directly observed. We have addressed this issue by applying several novel spectroscopic approaches to monitor motor dissociation, phosphate release, and nucleotide binding during processive movement by a dimeric kinesin construct. Our data argue that the major effect of the internal strain generated when both motor domains of kinesin bind the microtubule is to block ATP from binding to the leading motor. This effect guarantees the two motor domains remain out of phase for many mechanochemical cycles and provides an efficient and adaptable mechanism for the maintenance of processive movement.
View details for DOI 10.1074/jbc.M300849200
View details for Web of Science ID 000182838300126
View details for PubMedID 12626516
View details for PubMedCentralID PMC1533991
Combined optical trapping and single-molecule fluorescence.
Journal of biology
2003; 2 (1): 6-?
Two of the mainstay techniques in single-molecule research are optical trapping and single-molecule fluorescence. Previous attempts to combine these techniques in a single experiment - and on a single macromolecule of interest - have met with little success, because the light intensity within an optical trap is more than ten orders of magnitude greater than the light emitted by a single fluorophore. Instead, the two techniques have been employed sequentially, or spatially separated by distances of several micrometers within the sample, imposing experimental restrictions that limit the utility of the combined method. Here, we report the development of an instrument capable of true, simultaneous, spatially coincident optical trapping and single-molecule fluorescence.We demonstrate the capability of the apparatus by studying force-induced strand separation of a rhodamine-labeled, 15 base-pair segment of double-stranded DNA, with force applied perpendicular to the axis of the DNA molecule. As expected, we observed abrupt mechanical transitions corresponding to the unzipping of DNA at a critical force. Transitions occurred concomitant with changes in the fluorescence of dyes attached at the duplex ends, which became unquenched upon strand separation.Through careful optical design, the use of high-performance spectral notch filters, a judicious choice of fluorophores, and the rapid acquisition of data gained by computer-automating the experiment, it is possible to perform combined optical trapping and single-molecule fluorescence. This opens the door to many types of experiment that employ optical traps to supply controlled external loads while fluorescent molecules report concurrent information about macromolecular structure.
View details for PubMedID 12733997