The Spatiotemporal Dynamics of Mycobacterial Infection

Host response to Mycobacterium tuberculosis (Mtb) is distinctive in the use of a spatial immunological response to limit the progression of infection. This results in the formation granulomas, aggregations of immune cells that isolate invading microbes, a hallmark of the adaptive immune response to Mtb infection. Traditional in vivo studies have investigated the mature granuloma, but relatively fewer studies investigate how these structures form during the early stages of infection nor how spatial organization impacts control, resolution, or dissemination of the bacterium. Research has shown that initial aggregation of macrophages during innate immune response influences the progression of disease and formation of granulomas during adaptive immunity. However, current experimental methods for studying cellular interactions during early stages of infection are ill adapted for concurrent spatial and temporal quantification of host-pathogen dynamics, which is necessary for a quantitative understanding of the innate spatial immune response to Mtb and to inform the development of accurate computational models of tuberculosis disease. To address this, we developed a three-dimensional (3D) ex vivo model of mycobacterium infected macrophages cultured in reconstituted basement membrane and characterized the structural impact of 3D structure on infection dynamics in comparison to standard two-dimensional (2D) infection models. We quantified temporal immune response using standard biological sampling methodologies and long-term time-lapse confocal imaging to quantify the early spatiotemporal dynamics of macrophage response to mycobacterium infection. Our studies using Mycobacterium smegmatis indicate that the 3D environment induces a shift in dynamics. In 3D we see significantly higher cellular velocities in infected conditions as compared to control non-infected conditions, whereas the converse occurs in 2D. This may impact computational models that utilize 2D assumptions. We developed a data analysis pipeline to quantify macrophage state with respect to infection and cellular microenvironment. Results show non-infected and non-active macrophages within infected environments present dynamics comparable to controls, while infected and activated macrophages exhibit comparable spatiotemporal dynamics in 2D and 3D. Using the more virulent Mycobacterium bovis BCG, we observe a greater distinction between control and infected conditions and preliminary evidence of a more distinct 3D immune response resulting in increased cell death and extracellular bacteria.Biomedical Engineering, Department o

Analysis of the Spatio-Temporal Dynamics of Infection

Spatio-temporal dynamics are vital in understanding the course of infection, particularly for infections that lead to the formation of granulomas such as Mycobacterium tuberculosis which significantly impact the course of infection. In in vitro studies, the observable data is gathered at the global environment level (a single well), but this lacks the correlation and relationship between an individual cell, its local neighborhood and its global environment. Traditional 2D models of infection allow for easily replication and rapid sampling but, devoid of an extracellular matrix (ECM) are unable to fully replicate the spatial dynamics of an in vivo system. In vivo models, while providing multi-cellular response and spatial dynamics do not allow the freedom of sampling granted in vitro. We aim to develop corresponding in vitro and in silico platforms to adequately capture and analyze the multidimensional nature of immune response to infection. By connecting the in vitro and in silico platforms with confocal imaging, we are able to observe, quantify, and correlate cellular behaviors on all levels and determine the characterizes that lead to different outcomes of infection.Biomedical Engineering, Department o

Vascularized Hepatocellular Carcinoma on a Chip to Control Chemoresistance through Cirrhosis, Inflammation and Metabolic Activity

Understanding the effects of inflammation and cirrhosis on the regulation of drug metabolism during the progression of hepatocellular carcinoma (HCC) is critical for developing patient‐specific treatment strategies. Herein, novel 3D vascularized HCC on chips (HCCoCs), composed of HCC, endothelial, stellate, and Kupffer cells tuned to mimic normal or cirrhotic liver stiffness, are created. HCC inflammation is controlled by tuning Kupffer macrophage numbers, and the impact of cytochrome P450‐3A4 (CYP3A4) is investigated by culturing HepG2 HCC cells transfected with CYP3A4 to upregulate expression from baseline. This model allows for the simulation of chemotherapeutic delivery methods such as intravenous injection and transcatheter arterial chemoembolization (TACE). It is shown that upregulation of metabolic activity, incorporation of cirrhosis and inflammation, increases vascular permeability due to upregulated inflammatory cytokines leading to significant variability in chemotherapeutic treatment efficacy. Specifically, it is shown that further modulation of CYP3A4 activity of HCC cells by TACE delivery of doxorubicin provides an additional improvement to treatment response and reduces chemotherapy‐associated endothelial porosity increase. The HCCoCs are shown to have utility in uncovering the impact of the tumor microenvironment during cancer progression on vascular properties, tumor response to therapeutics, and drug delivery strategies

Combining Chemistry and Engineering for Hepatocellular Carcinoma: Nano-Scale and Smaller Therapies

Primary liver cancer, or hepatocellular carcinoma (HCC), is a major worldwide cause of death from carcinoma. Most patients are not candidates for surgery and medical therapies, including new immunotherapies, have not shown major improvements since the modest benefit seen with the introduction of sorafenib over a decade ago. Locoregional therapies for intermediate stage disease are not curative but provide some benefit. However, upon close scrutiny, there is still residual disease in most cases. We review the current status for treatment of intermediate stage disease, summarize the literature on correlative histopathology, and discuss emerging methods at micro-, nano-, and pico-scales to improve therapy. These include transarterial hyperthermia methods and thermoembolization, along with microfluidics model systems and new applications of mass spectrometry imaging for label-free analysis of pharmacokinetics and pharmacodynamics

Molecular, Metabolic, and Subcellular Mapping of the Tumor Immune Microenvironment via 3D Targeted and Non-Targeted Multiplex Multi-Omics Analyses

Most platforms used for the molecular reconstruction of the tumor–immune microenvironment (TIME) of a solid tumor fail to explore the spatial context of the three-dimensional (3D) space of the tumor at a single-cell resolution, and thus lack information about cell–cell or cell–extracellular matrix (ECM) interactions. To address this issue, a pipeline which integrated multiplex spatially resolved multi-omics platforms was developed to identify crosstalk signaling networks among various cell types and the ECM in the 3D TIME of two FFPE (formalin-fixed paraffin embedded) gynecologic tumor samples. These platforms include non-targeted mass spectrometry imaging (glycans, metabolites, and peptides) and Stereo-seq (spatial transcriptomics) and targeted seqIF (IHC proteomics). The spatially resolved imaging data in a two- and three-dimensional space demonstrated various cellular neighborhoods in both samples. The collection of spatially resolved analytes in a voxel (3D pixel) across serial sections of the tissue was also demonstrated. Data collected from this analytical pipeline were used to construct spatial 3D maps with single-cell resolution, which revealed cell identity, activation, and energized status. These maps will provide not only insights into the molecular basis of spatial cell heterogeneity in the TIME, but also novel predictive biomarkers and therapeutic targets, which can improve patient survival rates