AREA 1: Immunology
Immune responses and dysfunction are frequently local, specific to microenvironments, and governed by complex regulatory mechanisms. This means that systemic interventions can be toxic and/or ineffective. In this area, we are exploring how different local or systemic compartments evolve distinct immune functions. The underlying immunology of normal and disease biology provide us with a treasure trove of knowledge to be mined and manipulated by engineered systems and models. These also raise new fundamental questions that we explore in our work.
AREA 2: Technology
The complexity of the immune system requires advances in technology to answer new fundamental and applied questions. We pull diverse tools from drug delivery, sensors, engineered model systems, and tissue engineering, retooling them into new ways to interrogate and control immune function in vitro and in vivo. These technological advances span scales, looking at modeling and manipulating the heterogeneity of single cells to the outputs from sparse (2-5 cells) cell interactions to the functions of higher order systems including networks of cells, tissues, and organs. We design molecules to simply, rapidly control signals and delivery, as well as develop modular implants and scaffolds to manipulate disease states. The key goal of these technologies is to enable our other studies to be executed in a unique, innovative way.
AREA 3: Analytics
Rational approaches to engineering immunity require enhanced understanding (both qualitative and quantitative) of immune function, connecting molecules and cells to the outputs of systems. However, complex dynamic networks regulate immune activation and suppression in healthy and disease states. We use a number of integrative, multi-scale analytical approaches inspired by systems biology to develop more robust models of immune network function. Working with colleagues, we also use our expertise to reduce the complexity of analysis to make new methods easily adaptable to end-users, including researchers and clinicians.
Postdoctoral Immune Engineering
Massachusetts Institute of Technology (MIT)
- Systems Biology, Novel Assays
- The limitation of many studies to interrogating specific immune cell types and their singular contributions has directed his interest towards development of engineering tools for deconvolving network-level functions (bulk cell populations or cell-cell interactions) and single-cell heterogeneity. Using a nanowell-based immunoassay platform (Chris Love lab), Dr. Szeto co-developed a method for tracking/deconvolution of single-cell and sparse cell (2-5 cell) secretory behaviors from mixed sample inputs by fluorescent sample barcoding. These barcodes will be used to quantitatively interrogate cell-cell outcomes. He also co-developed a stochastic particle barcoding/reversible hydrogel encapsulation method for massively parallel single-cell tracking and recovery, connecting longitudinal secretory profiles in nanowells to single-cell identity. Using systems biology, Dr. Szeto co-developed and implemented a broadly applicable experimental/computational approach for multivariate modeling/analysis of stimulated immune cell populations. This method identified a novel defect in PBMCs from HIV-infected donors: impaired early IFNγ secretion by TLR stimulated NK cells, which reduced diversification of the secreted cytokine network. Dr. Szeto further applied these multivariate analytical techniques to single-cell RNA-seq data to define transcriptional signatures of cell cycle and cellular heterogeneity in activated clonal lineages of murine CD8+ T cells using a novel microfluidics device (Scott Manalis lab), and to find signatures of therapeutic efficacy using intratumoral/intranodal cytokine measurements in murine models of cancer immunotherapy. These tools/methods provide an integrative, multiscale suite for immunodiagnostics and defining mechanisms of function and disease dysregulation in complex immune networks.
PhD - Cellular & Molecular Medicine
Johns Hopkins University School of Medicine
- Areas of focus/keywords: HIV, SIV, T cell signaling, immunomodulation
- Inspired by the immunological concerns in the field of viral gene therapy, Dr. Szeto’s PhD focused on the mechanisms and efficacy of an immunomodulatory therapy. Specifically looking to treat HIV latency and immune hyperactivation in chronic HIV infected individuals, his work delineated the effects of the antibiotic minocycline as a host-targeted antiretroviral. Long used as an immunomodulatory to alleviate inflammation in rheumatoid arthritis, minocycline’s molecular mechanisms in CD4+ T cells and the potential intersection of these effects in HIV infection were poorly defined. First-author work determined that 1) minocycline attenuated primary HIV infection of activated human CD4+ T cells after the reverse transcription stage, 2) these anti-HIV effects extended to reactivation of HIV from a model of latency and patient latent reservoirs, and 3) that T cell activation and cell cycle progression were attenuated. In a subsequent publication, Dr. Szeto determined the molecular mechanism underlying these effects: minocycline inhibits the transcription factor NFAT1 via increased phosphorylation through reduced calcium flux and increased GSK3 activity. As a co-investigator, he helped discover that minocycline attenuates type I interferon antiviral responses in plasmacytoid dendritic cells in vitro and prevented some aspects of immunopathogenesis in SIV-infected macaques in vivo. These studies, along with others from his PhD group, provided rationale to utilize minocycline in multiple SIV macaque studies, anti-HIV clinical trials, and a model of HIV immunopathogenesis humanized mice.
Molecular Biology & Genetics, Computer Science
Undergraduate and High School work
- Areas of focus/keywords: gene therapy (dsAAV), molecular genetics, bioinformatics
- Dr. Szeto’s early career contributions focused on the application of his expertise in computer programming and engineering to help solve problems in software development and physics, molecular biology and bioinformatics, and viral vector design in gene therapy. At the Army Research Laboratory, he designed and implemented a new software tool in MATLAB to mathematically model the effects of atmospheric conditions on acoustic sensor data and enable battlefield analysis by non-experts. At NCI-Frederick, his work focused on cloning, sequencing, and using bioinformatics tools to identify novel, essential genes in a Drosophila P-element insertion screen by sequence homology. Finally, his work at the University of Pittsburgh focused on the determination of packaging size limits and insert size effects on the molecular virology of double-stranded adeno-associated virus in human and murine cells. This work with other studies in the lab guided development of dsAAV as a gene therapy vector in muscular dystrophy and chronic hepatitis B virus infection.