March 29th CTE Seminar

Student Speakers

Title: Agroseek: Computational tools for analyzing and predicting patterns of antibiotic resistance genes based on metagenomic data

Presenter: Xiao Liang

Research group: Computational Biology and Bioinformatics

Antibiotic resistance genes (ARGs) play an important role in antibiotic resistent bacteria and can pose a threat to human health. However, it is still unclear how different agricutural practices can affect the spread of ARGs. In this project, we attempt to inspect the spread of ARGs in the agricultural chain from stage to stage computationally. We will analyze not only the metagenomics data sequenced from different stages, but also the metadata associated with them such as physico-chemical factors and management practices. We aim at building interpretive and predictive computational tools to identify the critical control points that influence the spread of ARGs and find shared patterns given certain combinations of practices. Also we construct a database to manage and store the data. Using the database, the data and analysis results from different projects and stages will be easy to retrieve and compared each other with. In this talk, I will discuss the potentialities and challenges in metagenomic analysis, primarily in the context of staged argricultural chain. Also I will talk about the current solutions and plans we propose for our project.

Title: Electrical properties of tissue: how they change during electroporation and their use in treatment planning

Presenter: Natalie White

Research group:  Bioelectromechanical Systems Laboratory

Irreversible electroporation (IRE) is a cancer treatment that uses high voltage, short pulses to locally ablate tumor tissue. Currently in use for the treatment of pancreatic, liver, and kidney tumors, obtaining maximum tumor treatment while limiting damage to healthy tissue and vasculature is heavily dependent on treatment parameters. Because IRE involves the direct insertion of electrodes into the target treatment area, parameters such as electrode spacing, electrode exposure, number of pulses, applied voltage, and patient anatomy all affect the expected ablation zone. A critical piece of information needed to determine optimal treatment, whether in a pre-treatment computational model or in real-time during IRE itself, is the electrical properties of the target tissue. These properties are dependent on tissue type and change depending on the strength of the applied electric field, making their quantification challenging. One simple method for characterizing tissue ex vivo is the parallel-plate method, which allows us to measure tissue resistance and calculate conductivity easily. Another method is electrical impedance spectroscopy, which provides additional information about frequency-dependent properties of the tissue. Frequency-dependent properties are also captured in electrical circuit models such as the Cole-Cole model. These models are needed in order to quantify the behavior of tissue when exposed to a pulsed electric field, which is crucial information needed to create a personalized IRE treatment plan for a given patient.