C. elegans, systems engineering, and systems biology
The San Miguel Lab is dedicated to accelerating biological discoveries by incorporating engineering and systems approaches to answer elusive questions in different areas of biology. We focus on applying engineering tools to perform experiments unfeasible with traditional techniques. We use the nematode C. elegans as a model organism and we work in topics such as neuronal aging, synaptic plasticity, noise and stochasticity, genetic networks, and buffering, among others. We incorporate tools that enable large-scale high-content quantitative characterization of phenotypes at various scales: from the subcellular level all the way to whole-organism behavioral outputs. We use custom-built platforms for our experimental studies, which typically incorporate microfluidics, computer vision, statistical data analysis, and integrative automation and control.
Some of our current projects include:
Forward genetic screens for identifying genes that regulate decline with age – Daniel Midkiff
A worm population is mutagenized, and is grown for two generations before being age synchronized for Day 2 adults. Worms are sorted for high levels of PAB-1::tagRFP in the pharynx as potential mutants. Progeny of potential mutants are tested for aggregation levels to determine true mutants. Once true aggregation mutants are identified, they are then tested for reduced lifespan. Verified lifespan mutants will undergo whole-genome sequencing to determine genes which regulate lifespan and aggregation.
In Vivo Longitudinal Tracking of the C. elegans Aging Network – Javier Huayta
The activity of gene networks associated with life span and healthspan varies in space and time, and can be perturbed by changes in the environment. It is still unclear how the history of these perturbations, and the responses of aging-associated gene networks determines the healthspan and lifespan of the C. elegans nematode. The longitudinal in vivo tracking of these live perturbations can be achieved through quantitative imaging processing of endogenous gene network expression. To accomplish this goal, we will combine microfluidics, high-throughput image processing, and multi-labeled endogenous gene expression lines (generated through CRISPR/Cas9 system). A microfluidic device designed ad hoc for in vivo tracking of C. elegans populations will enable qualitative imaging of fluorescent gene expression related to reproduction, dietary restriction, heat shock, oxidative stress, etc. The data sets thus acquired will be used to relate environmental perturbations, longitudinal gene activity, and lifespan and healthspan. Quantitative mathematical models derived with this data will elucidate how this lifelong background determines lifespan and healthspan in C. elegans.
Alzheimer’s Disease in C. Elegans – James Lichty
We are trying to create and test a better Amyloid Beta/Alzheimer’s Disease model for C. elegans. Current models only express the amyloid beta protein intracellularly, but in humans, the protein is largely expressed extracellularly. To correct this, we are taking advantage of the fact that C. elegans has some of the machinery necessary for extracellular expression and using that to express the amyloid beta protein outside the cell. Once this model is completed, we will use it to study the progression of Alzheimer’s Disease.
We also want to understand the interactions between Alzheimer’s Disease and bacterial pathogens. There has been recent evidence to suggest that non-familial Alzheimer’s Disease may in part be driven by certain pathogens and our body’s immune response to them. To this end, we have identified several candidate pathogens, and will feed them to the organism C. elegans. We will then observe the organisms overall and neuronal health as it ages, looking for trademark signs of neurodegradation and disease.
Novel tools for longitudinal, high-resolution monitoring of the aging nervous system in C. elegans – Sahand Saberi
C. elegans as a model organism has been studied extensively throughout past years. However, conventional techniques used to study these nematodes is low-throughput, labor intensive, and in some cases unable to perform certain experiments such as lifelong imaging. In my project, I am implementing microfluidic devices to address the issues mentioned above. My project is focused on integrating microfluidic device that perform high-resolution, longitudinal imaging with cutting edge image processing techniques to increase the accuracy of the data analysis. I am trying to use various machine learning techniques including Convolutional Neuronal Networks to process the images acquired. Successful integration of these techniques will enable me to segment and process images with complex features and eventually track subtle phenotypes occurring to nematodes as they age. We are currently interested in implementing CNNs in detecting neuronal beading in PVD and track this process quantitatively as nematodes age.
Building Quantitative Statistical Models to stressors in C. elegans – Karthik Suresh Arulalan
In vivo monitoring of head injury cellular damage in Alzheimer’s disease – Rita Tejada
An important challenge in understanding the links between traumatic brain injury (TBI) and Alzheimer’s disease (AD) is a scarcity of experimental models that enable systematic studies of neuronal injury, while quantifying subsequent damage and its interaction with AD. To elucidate the fundamental mechanistic relationships between injury and AD, and the genetic pathways at play, capturing post-injury in vivo dynamic information of both neurological function and morphology at high-resolution would be necessary. The nematode C. elegans provides a unique experimental platform to perform quantitative analysis of injury, neurodegeneration, and neuronal function in AD models. Neuronal injury induced by controlled microfluidic devices will enable characterization of morphological and functional defects in an intact nervous system, in vivo. By incorporating a C. elegans AD model, with controlled injury and high-content platforms, this work will enable studies of injury and neurodegeneration.
Quantitative Analysis by Image Processing of Extravillous Cytotrophoblast in Human Embryonic Stem Cell-derived Trophoblast – Victoria Karakis
I utilize image analysis techniques to quantitatively asses the effects cytokines have on the differentiation and invasion of human embryonic stem cell-derived extravillous cytotrophoblast cells (EVTs). These cells are a major cell type in the human placenta and play a key role in remodeling uterine spiral arteries to ensure efficient blood flow and fetal nutrition during pregnancy. Improper invasion of these cells can result in life-threatening diseases for the mother and fetus, including pre-eclampsia, where the only known cure is pre-term birth. Therefore, in understanding what effects the invasion of these cells, we can begin to understand and develop therapeutics to combat placental disorders.
Novel High-Throughput Microfluidic Particle Filter Mimicking the Manta Ray’s Feeding Mechanism – Andrew Clark
Microparticle filtration plays an important role in many medical and biological systems. However, most current technologies of microparticle filtration are limited by low-throughput or clogging. Interestingly, the Manta Ray uses a non-clogging filter feeding mechanism where filter pores are larger than the particles being filtered. We intend to scale down this feeding mechanism to filter microparticles of various sizes.