
Rebekah Drezek
· Professor of BioengineeringRice University · Bioengineering
Active 1997–2024
About
Rebekah Drezek is a Professor of Bioengineering and Associate Chair of Bioengineering at Rice University. Her research develops optical molecular imaging technologies for the in vivo assessment of tissue pathology and the quantitative analysis of nanoparticle uptake and interaction within cellular environments. Her work emphasizes the design, prototyping, and clinical testing of optical tools and nanomaterials that detect, diagnose, and treat cancer. She has translated nanoscale tools such as gold nanoparticles and quantum dot probes for targeted molecular imaging and tumor margin assessment, and developed photothermal nanoparticles aimed at targeting and eliminating cancer. Drezek collaborates on NIH-funded projects investigating gold nanoparticle-based delivery of cancer vaccines and adjuvants, and has served as principal investigator on projects developing high-resolution optical imaging approaches and nanoengineered imaging agents for breast cancer applications. Her research is interdisciplinary, involving collaborations with clinicians, molecular biologists, and biochemists within Rice and the Texas Medical Center, with a focus on leveraging emerging photonics technologies for minimally invasive, real-time disease detection and diagnosis. Drezek has published extensively, holds four patents, and has received numerous awards including the MIT Top Young Innovators Award, the AAMI Career Achievement Award, the Beckman Young Investigator Award, and the Adolph Lomb Medal from the Optical Society.
Research topics
- Computer Science
- Mathematics
- Biology
- Computational biology
- Statistics
- Materials science
- Cancer research
- Genetics
- Algorithm
- Bioinformatics
- Chemistry
- Nanotechnology
- Biological system
- Chromatography
Selected publications
Simulation-guided tunable DNA probe design for mismatch tolerant hybridization
PLoS ONE · 2024-08-22 · 2 citations
articleOpen accessSenior authorCorrespondingThe ability to both sensitively and specifically assess the sequence composition of a nucleic acid strand is an ever-growing field. Designing a detection scheme that can perform this function when the sequence of the target being detected deviates significantly from the canonical sequence however is difficult in part because probe/primer design is based on established Watson-Crick base-pairing rules. We present here a robust and tunable toehold-based exchange probe that can detect a sequence with a variable number of SNPs of unknown identity by inserting a series of controlled, sequential mismatches into the protector seal of the toehold probe, in an effort to make the protector seal "sloppy". We show that the mismatch-tolerant system follows predicted behavior closely even with targets containing up to four mismatches that thermodynamically deviate from the canonical sequence by up to 15 kcal/mole. The system also performs faithfully regardless of the global mismatch position on either the protector seal or target. Lastly, we demonstrate the generalizability of the approach by testing the increasingly mismatch-tolerant protectors on HIV clinical samples to show that the system is capable of resolving multiple, iteratively mutated sequences derived from numerous HIV sub-populations with remarkable precision.
Expanded Multiplexing on Sensor-Constrained Microfluidic Partitioning Systems
Analytical Chemistry · 2023 · 2 citations
Senior authorCorresponding- Computer Science
- Biological system
- Computational biology
Microfluidics can split samples into thousands or millions of partitions, such as droplets or nanowells. Partitions capture analytes according to a Poisson distribution, and in diagnostics, the analyte concentration is commonly inferred with a closed-form solution via maximum likelihood estimation (MLE). Here, we present a new scalable approach to multiplexing analytes. We generalize MLE with microfluidic partitioning and extend our previously developed Sparse Poisson Recovery (SPoRe) inference algorithm. We also present the first in vitro demonstration of SPoRe with droplet digital PCR (ddPCR) toward infection diagnostics. Digital PCR is intrinsically highly sensitive, and SPoRe helps expand its multiplexing capacity by circumventing its channel limitations. We broadly amplify bacteria with 16S ddPCR and assign barcodes to nine pathogen genera by using five nonspecific probes. Given our two-channel ddPCR system, we measured two probes at a time in multiple groups of droplets. Although individual droplets are ambiguous in their bacterial contents, we recover the concentrations of bacteria in the sample from the pooled data. We achieve stable quantification down to approximately 200 total copies of the 16S gene per sample, enabling a suite of clinical applications given a robust upstream microbial DNA extraction procedure. We develop a new theory that generalizes the application of this framework to many realistic sensing modalities, and we prove scaling rules for system design to achieve further expanded multiplexing. The core principles demonstrated here could impact many biosensing applications with microfluidic partitioning.
Extreme Compressed Sensing of Poisson Rates From Multiple Measurements
IEEE Transactions on Signal Processing · 2022 · 5 citations
- Computer Science
- Computer Science
- Algorithm
Compressed sensing (CS) is a signal processing technique that enables the efficient recovery of a sparse high-dimensional signal from low-dimensional measurements. In the multiple measurement vector (MMV) framework, a set of signals with the same support must be recovered from their corresponding measurements. Here, we present the first exploration of the MMV problem where signals are independently drawn from a sparse, multivariate Poisson distribution. We are primarily motivated by a suite of biosensing applications of microfluidics where analytes (such as whole cells or biomarkers) are captured in small volume partitions according to a Poisson distribution. We recover the sparse parameter vector of Poisson rates through maximum likelihood estimation with our novel Sparse Poisson Recovery (SPoRe) algorithm. SPoRe uses batch stochastic gradient ascent enabled by Monte Carlo approximations of otherwise intractable gradients. By uniquely leveraging the Poisson structure, SPoRe substantially outperforms a comprehensive set of existing and custom baseline CS algorithms. Notably, SPoRe can exhibit high performance even with one-dimensional measurements and high noise levels. This resource efficiency is not only unprecedented in the field of CS but is also particularly potent for applications in microfluidics in which the number of resolvable measurements per partition is often severely limited. We prove the identifiability property of the Poisson model under such lax conditions, analytically develop insights into system performance, and confirm these insights in simulated experiments. Our findings encourage a new approach to biosensing and are generalizable to other applications featuring spatial and temporal Poisson signals.
Expanded Multiplexing on Sensor-Constrained Microfluidic Partitioning Systems
bioRxiv (Cold Spring Harbor Laboratory) · 2022-12-23
preprintOpen accessSenior authorCorrespondingAbstract Microfluidics can split samples into thousands or millions of partitions such as droplets or nanowells. Partitions capture analytes according to a Poisson distribution, and in diagnostics, the analyte concentration is commonly calculated with a closed-form solution via maximum likelihood estimation (MLE). Here, we present a generalization of MLE with microfluidics, an extension of our previously developed Sparse Poisson Recovery (SPoRe) algorithm, and an in vitro demonstration with droplet digital PCR (ddPCR) of the new capabilities that SPoRe enables. Many applications such as infection diagnostics require sensitive detection and broad-range multiplexing. Digital PCR coupled with conventional target-specific sensors yields the former but is constrained in multiplexing by the number of available measurement channels (e.g., fluorescence). In our demonstration, we circumvent these limitations by broadly amplifying bacteria with 16S ddPCR and assigning barcodes to nine pathogen genera using only five nonspecific probes. Moreover, we measure only two probes at a time in multiple groups of droplets given our two-channel ddPCR system. Although individual droplets are ambiguous in their bacterial content, our results show that the concentrations of bacteria in the sample can be uniquely recovered given the pooled distribution of partition measurements from all groups. We ultimately achieve stable quantification down to approximately 200 total copies of the 16S gene per sample, enabling a suite of clinical applications given a robust upstream microbial DNA extraction procedure. We develop new theory that generalizes the application of this framework to a broad class of realistic sensors and applications, and we prove scaling rules for system design to achieve further expanded multiplexing. This flexibility means that the core principles and capabilities demonstrated here can generalize to most biosensing applications with microfluidic partitioning.
Simulation-guided sloppy DNA probe design for mismatch tolerant hybridization
bioRxiv (Cold Spring Harbor Laboratory) · 2022-12-21
preprintOpen accessSenior authorAbstract The ability to both sensitively and specifically assess the sequence composition of a nucleic acid strand is an ever-growing field. Designing a detection scheme that can perform this function when the sequence of the target being detected deviates significantly from the canonical sequence however is difficult in part because probe/primer design is based on established Watson-Crick base-pairing rules. We present here a robust and tunable toehold-based exchange probe that can detect a sequence with a variable number of SNPs of unknown identity by inserting a series of controlled, sequential mismatches into the protector seal of the toehold probe, in an effort to make the protector seal “sloppy”. We show that the mismatch tolerant system follows predicted behavior closely even with targets containing up to four mismatches and thermodynamically deviating from the canonical sequence by up to 15 kcal/mole. The system also performs faithfully regardless of the global mismatch position on either the protector seal or target. Lastly, we demonstrate the generalizability of the approach by testing the increasingly sloppy protectors on HIV clinical samples and show that the system is capable of resolving multiple, iteratively mutated sequences derived from numerous HIV sub-populations with remarkable precision.
bioRxiv (Cold Spring Harbor Laboratory) · 2020-04-24
preprintOpen accessSenior authorAbstract Cancer has proven to be an extremely difficult challenge to treat. Several fundamental issues currently underlie cancer treatment including differentiating self from non-self, functional coupling of the recognition and therapeutic components of various therapies, and the propensity of cancerous cells to develop resistance to common treatment modalities via evolutionary pressure. Given these limitations, there is an increasing need to develop an all-encompassing therapeutic that can uniquely target malignant cells, decouple recognition from treatment, and overcome evolutionarily driven cancer resistance. We describe herein, a new class of programmable self-assembling dsRNA-based cancer therapeutics, that uniquely targets aberrant genetic sequences, and in a functionally decoupled manner, undergoes oncogenic RNA activated displacement (ORAD), initiating a therapeutic cascade that induces apoptosis and immune activation. As a proof-of-concept, we show that RNA strands targeting the EWS/Fli1 fusion gene in Ewing Sarcoma cells that are end-blocked with phosphorothioate bonds and additionally sealed with a 2’-U modified DNA protector can be used to induce specific and potent killing of cells containing the target oncogenic sequence, but not wildtype.
Molecular Therapy — Oncolytics · 2020 · 2 citations
Senior authorCorresponding- Cancer research
- Biology
- Computational biology
Cancer has proven to be an extremely difficult challenge to treat. Several fundamental issues currently underlie cancer treatment, including differentiating self from nonself, functional coupling of the recognition and therapeutic components of various therapies, and the propensity of cancerous cells to develop resistance to common treatment modalities via evolutionary pressure. Given these limitations, there is an increasing need to develop an all-encompassing therapeutic that can uniquely target malignant cells, decouple recognition from treatment, and overcome evolutionarily driven cancer resistance. We describe herein a new class of programmable self-assembling double-stranded RNA (dsRNA)-based cancer therapeutics that uniquely targets aberrant genetic sequences and in a functionally decoupled manner, undergoes oncogenic RNA-activated displacement (ORAD), initiating a therapeutic cascade that induces apoptosis and immune activation. As a proof of concept, we show that RNA strands targeting the EWS/Fli1 fusion gene in Ewing sarcoma cells that are end blocked with phosphorothioate bonds and additionally sealed with a 2'-deoxyuridine (2'-U)-modified DNA protector can be used to induce specific and potent killing of cells containing the target oncogenic sequence but not wild type.
2018-03-01
preprintOpen accessSenior authorCell quantification assays are essential components of most biological and clinical labs. However, many currently available quantification assays, including flow cytometry and commercial cell counting systems, suffer from unique drawbacks that limit their overall efficacy. In order to address the shortcomings of traditional quantification assays, we have designed a robust, low-cost, automated optical cell cytometer that quantifies individual cells in a multiwell plate using tools readily available in most labs. Plating and subsequent quantification of various dilution series using the automated optical cytometer demonstrates the single-cell sensitivity, near-perfect R 2 accuracy, and greater than 5-log dynamic range of our system. Further, the optical cytometer is capable of obtaining absolute counts of multiple cell types in one well as part of a co-culture setup. To demonstrate this ability, we recreated an experiment that assesses the tumoricidal properties of primed macrophages on co-cultured tumor cells as a proof-of-principle test. The results of the experiment reveal that primed macrophages display enhanced cytotoxicity towards tumor cells while simultaneously losing the ability to proliferate, an example of a dynamic interplay between two cell populations that our optical cytometer is successfully able to elucidate.
PeerJ · 2018-06-05 · 5 citations
articleOpen accessSenior authorCell quantification assays are essential components of most biological and clinical labs. However, many currently available quantification assays, including flow cytometry and commercial cell counting systems, suffer from unique drawbacks that limit their overall efficacy. In order to address the shortcomings of traditional quantification assays, we have designed a robust, low-cost, automated microscopy-based cytometer that quantifies individual cells in a multiwell plate using tools readily available in most labs. Plating and subsequent quantification of various dilution series using the automated microscopy-based cytometer demonstrates the single-cell sensitivity, near-perfect R 2 accuracy, and greater than 5-log dynamic range of our system. Further, the microscopy-based cytometer is capable of obtaining absolute counts of multiple cell types in one well as part of a co-culture setup. To demonstrate this ability, we recreated an experiment that assesses the tumoricidal properties of primed macrophages on co-cultured tumor cells as a proof-of-principle test. The results of the experiment reveal that primed macrophages display enhanced cytotoxicity toward tumor cells while simultaneously losing the ability to proliferate, an example of a dynamic interplay between two cell populations that our microscopy-based cytometer is successfully able to elucidate.
2018-06-05
peer-reviewOpen accessCell quantification assays are essential components of most biological and clinical labs.However, many currently available quantification assays, including flow cytometry and commercial cell counting systems, suffer from unique drawbacks that limit their overall efficacy.In order to address the shortcomings of traditional quantification assays, we have designed a robust, low-cost, automated optical cell cytometer that quantifies individual cells in a multiwell plate using tools readily available in most labs.Plating and subsequent quantification of various dilution series using the automated microscopy-based cytometer demonstrates the single-cell sensitivity, near-perfect R 2 accuracy, and greater than 5-log dynamic range of our system.Further, the microscopy-based cytometer is capable of obtaining absolute counts of multiple cell types in one well as part of a co-culture setup.To demonstrate this ability, we recreated an experiment that assesses the tumoricidal properties of primed macrophages on co-cultured tumor cells as a proof-of-principle test.The results of the experiment reveal that primed macrophages display enhanced cytotoxicity towards tumor cells while simultaneously losing the ability to proliferate, an example of a dynamic interplay between two cell populations that our microscopy-based cytometer is successfully able to elucidate.
Recent grants
NIH · $1.6M · 2015
Nonspecific DNA Sensors for Scalable Pathogen Diagnostics
NSF · $260k · 2020–2023
NIH · $3.0M · 2012
Frequent coauthors
- 27 shared
Jennifer L. West
Duke University
- 27 shared
Emmanuel Chang
Tennessee Retina
- 25 shared
Rebecca Richards‐Kortum
Rice University
- 23 shared
Naomi J. Halas
Rice University
- 21 shared
Aaron E. Foster
Medpace (United States)
- 21 shared
Ming‐Qiang Zhu
Wuhan National Laboratory for Optoelectronics
- 19 shared
Anant Agrawal
United States Food and Drug Administration
- 17 shared
Lissett R. Bickford
Children's Cancer Therapy Development Institute
Labs
Awards & honors
- MIT TR100 Technology Reviews’ selection of 100 Top Young Inn…
- Association for the Advancement of Medical Instrumentation (…
- Beckman Young Investigator Award (2005)
- U.S. Department of Defense Era of Hope Scholar (2007)
- American Society for Photobiology Research Award (2008)
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