BME Graduate Student Seminar (ZOOM): Jeremy Lombardo and Erik Gonzalez-Leon

Jeremy Lombardo: Microfluidic tissue processing platform for single cell analysis

Abstract: Tissues are highly complex ecosystems, composed of heterogenous cell populations that vary in gene expression and function due to epigenetic and genetic distinctions, stochastic events and microenvironmental factors. In the context of cancer, characterizing intratumor heterogeneity has been crucial in understanding cancer progression, metastasis and the development of drug resistance. In order to capture this significant cellular heterogeneity, high throughput single cell analysis methods like flow cytometry, mass cytometry and single cell RNA sequencing must be employed. These analysis methods, however, require that tissues first be dissociated into cellular suspensions, and this process currently represents a major bottleneck hindering these efforts. Conventional protocols for dissociating tissues are inefficient and antiquated, relying on many manual intensive, time-consuming and highly user-variable steps for mincing, digesting, disaggregating and filtering tissue specimens. Advances in microfabricated technologies, however, hold exciting potential in their ability to carry out many standard laboratory procedures, such as tissue dissociation, on-chip by offering high throughput, precise sample manipulation. Here, we present a microfluidic platform consisting of three different tissue-processing technologies that significantly improves the breakdown of diverse tissue types into high quality cell suspensions that are ready for downstream single cell analysis. Using our platform, we optimize dissociation of murine kidney, tumor, liver and heart tissues, and investigate the dissociation kinetics of cell types within these tissues. For difficult to digest tissues such as kidney and tumor, microfluidic processing can reduce protocols from an hour to 15 minutes. Alternatively, at longer processing times the device platform produces >two-fold more epithelial cells and leukocytes, and >five-fold more endothelial cells. This system can significantly shorten processing time or enhance single cell recovery, and in some cases accomplish both, while doing so in an automatable and reliable fashion. In future work, we envision incorporating cell sorting and analysis capabilities on-chip to achieve full point-of-care single cell diagnostic platforms. 

Erik Gonzalez-Leon: Enhancing mechanical and biochemical properties of self-assembled neomenisci through a novel combination of bioactive stimuli

Abstract: Knee meniscus fibrocartilage injury is frequent and represents the most common set of procedures practiced by orthopedic surgeons, resulting in over 1 million surgeries annually in the United States and Europe. Tissue engineering has been proposed as a novel solution for meniscus repair and replacement due to its near-avascularity and intrinsic lack of healing. Here, we describe a novel approach to enhance both extracellular matrix content and organization to augment mechanical properties of engineered neomenisci. A self-assembling process is utilized to synthesize fibrocartilage, which does not require exogenous scaffolds and relies on cell-to-cell interaction in order to form engineered constructs. Lysophosphatidic acid (LPA), in addition to the TCL cocktail (TGF-b1, chondroitinase ABC, lysyl oxidase-like protein II), was added to engineered neomenisci during culture and resulted in increased tensile properties and extracellular matrix content. In addition, TCL + LPA treatment induced mechanical anisotropy, a property crucial to the function of the native knee meniscus. This study utilizes a novel combination of several bioactive stimuli for use in tissue engineering studies, and provides a promising path toward achieving neomenisci mechanical properties akin to native tissue.