University of Massachusetts Amherst

Search Google Appliance


Graduate Seminar (G.R.A.S.S.) – Sualyneth Galarza (Peyton) and Poonam Phalak (Henson)


Tuesday, November 28, 2017 - 11:30am


LGRT 201


Sualyneth Galarza – Shelly Peyton Lab

A Brain ECM Mimicking Hydrogel
Sualyneth Galarza and Shelly R. Peyton

Metastasis, the spread of cancer cells from the primary tumor to secondary sites, accounts for 90% of cancer-related deaths. To date, intrinsic efforts have been focused on understanding the genetic and extracellular mechanisms that mediate metastasis. The extracellular matrix (ECM) has been shown to promote metastasis by modulating behavioral aspects of cancer cells. However, how individual components in the ECM regulate the formation of a metastatic lesion remain unknown. The current lack of appropriate model systems is one potential limiting factor in uncovering these molecular mechanisms. Animal models, such as rodents, offer a native and complex physiology, but they are expensive, time-consuming, and difficult to control and manipulate. In vitro models, in comparison, are inexpensive and easy to assemble. Within the context of the brain, cell culture platforms derived from tissue, such as collagen hydrogels, cortical slices, decellularized tissues, and cerebral organoids mimic some aspects of the brain architecture but do not readily allow investigators to identify individual driving forces from the ECM responsible for changes in observed cell behaviors. Synthetic hydrogels, in contrast, have the potential to provide tight control over finite variables like stiffness and bioactive ligand density, and they are highly reproducible. However, current hydrogel systems tend to oversimplify the native ECM and neglect many of the complex arrays of proteins in real tissue. To augment these in vitro efforts, we have designed a brain tissue mimicking hydrogel that captures a brain-specific ECM signature, alongside the appropriate brain viscoelasticity. In this platform, we aim to study the role of the brain ECM remodeling in breast cancer brain metastasis. We foresee this model providing an avenue to target specific tissue features and being used to quantify cell-cell and cell-matrix phenotypes across multiple brain disease models and applications throughout tissue engineering.


Poonam Phalak – Michael Henson Lab

In silico metabolic modeling of Pseudomonas aeruginosa-Staphylococcus aureus multispecies biofilms
Poonam Phalak and Michael A. Henson

Pseudomonas aeruginosa and Staphylococcus aureus are the two bacteria most commonly isolated from various infections like chronic wounds and cystic fibrosis (CF). Individuals co-infected with these two bacteria are more prone to exacerbations and hospitalization than patients infected with either bacterium alone; thus, such coinfections contribute to worse clinical outcomes in this patient population. The spatial organization of biofilm consortia cause bacteria to exhibit phenotypes distinct from planktonic growth and often render the application of antibacterial compounds ineffective. We developed spatiotemporal models to investigate the multispecies metabolism of a biofilm consortium comprised of two common chronic wound/CF isolates: the aerobe Pseudomonas aeruginosa and the facultative anaerobe Staphylococcus aureus. By combining genome-scale metabolic reconstructions with partial differential equations for metabolite diffusion, the models were able to provide both temporal and spatial predictions with genome-scale resolution. The multispecies biofilm metabolic model was used to investigate the hypothesis that P. aeruginosa can exert its influence on S. aureus at a distance via secreted factors. Simulations were performed by supplying nutrients at either top or bottom of the biofilm to mimic the in vivo chronic wound/CF environments. P. aeruginosa was forced to secrete HQNO/pyocyanin, which diffused through the biofilm and inhibited S. aureus growth. Lactate synthesized by S. aureus was modeled to be the preferred carbon source for P. aeruginosa, as has been shown experimentally.

The models were used to analyze the metabolic differences between single species and two species biofilms and to investigate the tendency of the two bacteria to spatially partition in the multispecies biofilm as observed experimentally. The multispecies biofilm model also demonstrated experimentally observed behavior, including dominance of P. aeruginosa, upregulation of S. aureus fermentative metabolism and enhanced P. aeruginosa growth due to lactate cross feeding.



Follow UMass Chemical Engineering: