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Our research centers on development of medical devices that can benefit clinical practice.

Advanced pathogen diagnosis combating for antimicrobial resistance

Traditional pathogen diagnostics require lengthy culture-based procedures, typically 3-5 days, delaying prompt delivery of diagnostic results and treatment strategies and consequently resulting in antimicrobial resistance (Nat. Rev. Methods Primers, 2023; Nat. Biomed. Eng., 2020). In response, we develop biomedical devices and methods for rapid pathogen diagnostics, which are capable of detecting cell replication (PNAS, 2019; Lab chip, 2022) and nucleic acids (Lab chip, 2021; Nanomedicine, 2019; Lab chip, 2018) in single bacterial cells. This single-cell detection facilitates diagnosis in a timely manner; for example, a few cell cycles are sufficient to reveal replication differences in an individual bacterium and thus its antibiotic resistance. Moreover, we integrate AI-driven analytical tools with single-cell detection toward a more automated, accessible diagnostic workflow (Adv. Sci., 20026). We envision translating our diagnostic systems into clinical practice.

 

Single-cell pathogen identification and AST by cell physical features and replication in microchannels

Single-cell AST by cell growth in a microwell

AI algorithm for automated single-cell recognition & quantification

Digital-PCR for single-cell pathogen detection

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Biosensor design for pathogen detection

References:
 

  1. Hui Li#, Kuangwen Hsieh#, Pak Kin Wong, Kathleen E Mach, Joseph C Liao, Tza-Huei Wang. Single-cell pathogen diagnostics for combating antibiotic resistance, Nature Reviews Methods Primers, 3, 6 (2023). https://doi.org/10.1038/s43586-022-00190-y. (#Co-first authors)

  2. Hui Li, Peter Torab, Kathleen E. Mach, Christine Surrette, Matthew R. England, David W. Craft, Neal J. Thomas, Joseph C. Liao, Chris Puleo, and Pak Kin Wong. Adaptable Microfluidic System for Single Cell Pathogen Classification and Antimicrobial Susceptibility Testing. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 116 (21) 10270-10279, 2019.

  3. Hui Li, Peter Torab, and Pak Kin Wong. Detection of bacterial infection via a fidget spinner, Nature Biomedical Engineering, 4, 577–578, 2020.

  4. Sabita Khadka, Bushra Raahat, Spyros Tragoudas*, and Hui Li*, Artificial Intelligence-Empowered Single-Cell Phenotyping for Rapid, Automated Pathogen Diagnostics. Advanced Science (2026): e77334. https://doi.org/10.1002/advs.77334. 

  5. Hui Li, Yi Lu, and Pak Kin Wong, Diffusion–reaction kinetics of microfluidic amperometric biosensors. Lab on a Chip, doi:10.1039/C8LC00794B (2018).

  6. Jiumei Hu, Liben Chen, Pengfei Zhang, Kuangwen Hsieh, Hui Li, and Tza-Huei Wang, A vacuum-driven microfluidic array for multi-step sample digitalization, Lab on a Chip, doi.org/10.1039/D1LC00636C, 2021.

​Bioinspired ultra-repellent SLIPS technique for biomedical applications

We investigate biomedical applications of a bioinspired ultra-repellent SLIPS technique – Slippery Liquid-infused Porous Surface – a dynamic, molecularly smooth surface created by locking lubricating liquids in micro/nanostructured substrates (Sci. Adv., 2020; Nat. Sustain., 2019). It has been engineered on SLIPS-LAB, a medical system, for timely measurement of urinary stone analytes to facilitate management of high-risk stone formers. By incorporating the outperforming smoothness for minimizing friction in liquid handling, with microfluidics, precise manufacturing, and biochemistry, SLIPS-LAB enables point-of-care evaluation of urinary stone disease (Sci. Adv., 2020). Moreover, we have been working to use SLIPS for anti-fouling and anti-infection purposes.

Ultra-repellency enables SLIPS-LAB for point-of-care diagnosis of urinary stone disease and allows great potentials

Ultra-repellent LESS coating facilates anti-sticky and anti-fouling on surfaces

References:
 

  1. Hui Li, Eugene Shkolyar, Jing Wang, Alan C. Pao, Simon Conti, Joseph C. Liao, Tak Sing Wong, and Pak Kin Wong. SLIPS-LAB – A Bioinspired Bioanalysis System for Metabolic Evaluation of Urinary Stone Disease, Science Advances, 6 (21), eaba8535, 2020.

  2. Jing Wang, Lin Wang, Nan Sun, Ross Tierney, Hui Li, Margo Corsetti, Leon Williams, Pak Kin Wong, and Tak-Sing Wong, Viscoelastic solid-repellent coatings for extreme water saving and global sanitation, Nature Sustainability, 2, 1097–1105, 2019.

Microfluidic devices for drug screening

Drug screening aims to determine targets of interest among numerous potential candidates. This is typically performed using microtiter plates, which is limited for high throughput screening due to the large reagent consumptions in each assay and/or the difficulty of performing multistep biochemical assays (Trends Biotechnol., 2022). To response, we have developed microfluidic devices to address these issues, such as an automation combinatorial nanodroplet system for high throughput screening of antibiotic combinations (Lab chip, 2022), a microwell device to screen contraceptive agents (Small, 2019), and a prototype oligonucleotide synthesizer for in-house oligonucleotide synthesis and thereof drug screening for siRNA (Sci. Rep., 2019). We aim to explore the screening for anticancer drugs.

Nanodroplet system for high-throughput screening of antibiotic combinations

Automation microwell sytem  for screening nonhormonal contraceptive agents

Inkjet printer and microwell array for in-house oligo synthesis and screening

References:
 

  1. Hui Li, Pengfei Zhang, Kuangwen Hsieh, and Jeff Tza-Huei Wang, Combinatorial nanodroplet platform for screening antibiotic combinations, Lab on a Chip, doi.org/10.1039/D1LC00865J, 2022.

  2. Hui Li, Tyler Garner, Francisco Diaz, and Pak Kin Wong. A Multiwell Microfluidic Device for Analyzing and Screening Non-Hormonal Contraceptive Agents, Small, 15, 1901910, 2019.

  3. Hui Li#, Ye Huang#, Zewen Wei, Wei Wang, Zhenjun Yang, Zicai Liang, and Zhihong Li. An oligonucleotide synthesizer based on a microreactor chip and an inkjet printer, Scientific Report, 9, 5058, 2019. (*Co-first authors)

  4. Fangchi Shao, Pei-Wei Lee, Hui Li, Kuangwen Hsieh and Tza-Huei Wang, Emerging Platforms for High-Throughput Enzymatic Bioassays, Trends in Biotechnology, 2022.

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Copyright by Li Group. All rights reserved.

School of Electrical, Computer, and Biomedical Engineering, Southern Illinois University

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