Biosensor Design for Dynamic Single Cell Analysis. SBL has made significant contributions to biosensing in live single cells for dynamic multigene analysis. For instance, we have established GNR-LNA biosensors for mapping dynamic gene expression profiles in photothermally stimulated lung tissues, mechanically damaged mouse cornea, Nrf2 mediated chemoresistance in KRASG12D mouse lung tumors, and patient-derived tumor organoids (ACS Nano 2014 Link; Advanced Materials 2015 Link). In addition, we have demonstrated multiplex detection of both mRNA and protein in the same cell by incorporating molecular aptamers into the biosensor design (Biomaterials 2018 Link). These single cell biosensors have been applied to rapidly identify bacterial species at the single cell level (Nanomedicine: NBM 2019 Link) and to monitor the reprogramming of epigenetically primed iPSCs (Nature Materials 2022 Link).

GNR-LNA biosensors

Bioinspired microfluidics for 3D tissue modeling and disease diagnostics. SBL has pioneered microfluidic devices and single cell manipulation techniques for medical diagnostics and tissue modeling. For instance, we confine pathogens from raw or enriched patient samples in microchannels to determine the bacterial antibiotic resistance profiles at the single cell level (PNAS 2019 Link). Their growth rates and antibiotic resistance profiles can be determined at the single cell level in as few as 30 min. We have also developed bioinspired microfluidic systems for the metabolic evaluation of urinary stone disease at the point of care (Science Advances 2020 Link). Our technologies are being adopted in various clinical studies and product development pipelines worldwide, in partnership with clinical and industrial partners (Nature Sustainability 2019 Link).

Single cell AST device

Data science and artificial intelligence. SBL is engaged in data science and computational techniques (PLoS Computational Biology 2016 Link). For instance, we establish an artificial intelligence (AI)-guided experimental strategy for screening potent antiviral drug combinations and immunomodulation cocktails (PNAS 2008 Link). The AI-guided method reduces the one million possible cases in the search space into as few as ten iterations, which dramatically reduces the time and cost of the optimization process. Similarly, we have demonstrated a metamodel antimicrobial cocktail optimization (MACO) scheme to identify synergistic antibiotic cocktails that reduce the minimum inhibitory concentration 40-fold (PLoS ONE 2010 Link). We are actively working on machine learning and bioinformatic techniques for modeling complex biomedical processes and medical diagnostics. 

3D image analysis

Infectious diseases and antimicrobial resistance. Rapid detection of pathogenic agents is critical toward the judicious management of infectious diseases, such as urinary tract infection and sepsis, especially in emergency situations and high-risk areas such as hospitals, airports, rural clinics, and temporary clinics established in response to disasters (Nature Biomedical Engineering 2020 Link).  In settings where highly infectious pathogens are suspected, point-of-care detection will lead to the timely initiation of appropriate treatments, which will reduce the infected individuals’ morbidity and mortality, as well as address public health concerns by efficient triaging of the uninfected from the infected. Within this context, we design and implement microfluidic, rapid diagnostic systems to address the unmet critical need for rapid pathogen identification and antimicrobial susceptibility testing (PNAS 2019 Link). 

Single cell pathogen identification

Collective cancer invasion and leader cell formation. Collective cancer invasion is increasingly recognized as a predominant mechanism in the metastatic cascade. At the onset of collective cell migration, a subset of cells within an initially homogenous population acquires a distinct “leader” phenotype (Nature Reviews Cancer, 2020 Link). However, the molecular mechanisms driving the formation of invasive leader cells, as well as the signaling network regulating their density during collective cancer invasion, remain to be determined.  Using dynamic single cell gene expression analysis and computational modeling, we have shown that the leader cell identity is dynamically regulated by Dll4-Notch1 signaling and intercellular tension (Nature Communications 2015 Link). Furthermore, we have elucidated the relationship between Nrf2, hybrid epithelial-mesenchymal transition, and Notch1-Dll4 signaling in the regulation of collective cancer invasion (PNAS, 2023 Link).

Bladder tumor organoids

Microbiota and immunotherapy. Microbiota contribute fundamentally to human health, and the imbalance of microbiota (dysbiosis) is associated with various medical conditions. Patients in the hospital (e.g., ICU) are certain to experience disturbances of the microbiota due to underlying diagnosis at admission and unintended consequences of medical treatment. Furthermore, the microbiota is increasingly recognized as a critical component in cancer and cancer therapy (e.g., immunotherapy). Understanding the microbiota in various medical conditions could open new opportunities for disease diagnostics, prognosis, and treatment (Nature Reviews Bioengineering; SLAS Technology 2019 Link). 

Single cell analysis