Adriana San Miguel
Bio
My research program focuses on using engineering and systems approaches to understand fundamental biological processes in living organisms, particularly the model organism Caenorhabditis elegans. We apply tools that enable the acquisition of biological data in a high-throughput, quantitative fashion. With these high-content engineering approaches, we aim to understand 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. In addition, we apply genetic and molecular biology tools that enable performing genome-wide systematic studies. Current active areas of research include aging of neuronal connections, genetic screens for late-onset phenotypes, quantitative behavioral assays, and the spatio-temporal role of age-associated proteins at the whole organism level.
Education
B.S., Chemical Engineering, ITESM (2005)
Ph.D., Chemical Engineering, Georgia Tech (2011)
Publications
- Morphological hallmarks of dopaminergic neurodegeneration are associated with altered neuron function in Caenorhabditis elegans , NEUROTOXICOLOGY (2024)
- An unbiased, automated platform for scoring dopaminergic neurodegeneration in C. elegans , PLOS ONE (2023)
- An unbiased, automated platform for scoring dopaminergic neurodegeneration in C. elegans , Dryad (2023)
- An unbiased, automated platform for scoring dopaminergic neurodegeneration inC. elegans , (2023)
- Data for: Endogenous DAF-16 spatiotemporal activity quantitatively predicts lifespan extension induced by dietary restriction , Dryad (2023)
- Endogenous DAF-16 spatiotemporal activity quantitatively predicts lifespan extension induced by dietary restriction , COMMUNICATIONS BIOLOGY (2023)
- Laminin switches terminal differentiation fate of human trophoblast stem cells under chemically defined culture conditions , JOURNAL OF BIOLOGICAL CHEMISTRY (2023)
- Molecular Engineering of Cyclic Azobenzene-Peptide Hybrid Ligands for the Purification of Human Blood Factor VIII via Photo-Affinity Chromatography , ADVANCED FUNCTIONAL MATERIALS (2023)
- Morphological hallmarks of dopaminergic neurodegeneration are associated with altered neuron function inCaenorhabditis elegans , (2023)
- Programming Probiotics: Diet-responsive gene expression and colonization control in engineeredS. boulardii , (2023)
Grants
Environmental stressors can exert large impacts on an organism??????????????????s physiology, fitness, and longevity. As a result, animals have complex modes of integrating information to either adapt or escape from the encountered environmental stressors by altering behavior, metabolism, gene expression, etc. Such exposures can induce both systemic and localized effects. For instance, sensing of noxious environments through neuronal circuits elicit an escape behavior while also inducing changes in gene expression. Based on their direct output (behavior or gene expression), neuronal and gene expression circuits would appear to be independent and operate in different contexts and time-scales. However, neuronal circuits and genetic pathways could interact in both a cell-autonomous and non-autonomous fashion. How systemic (i.e. direct exposure throughout all tissues) and neuronal-driven responses interact to drive an organismal state that can defend against environmental stressors is not understood. A challenge to address this question is the lack of tools to test these responses separately. In addition, different types of exposures (oxidants, heavy metals, dietary conditions, heat, UV light, pathogens, etc) can drive the stress response, and are known to act through parallel genetic pathways (regulated by DAF-16 and SKN-1 in C. elegans). However, most work thus far focuses on studying exposure to single stressors at one time-point, and at one concentration. In contrast, environmental exposures consist of complex mixtures of compounds through long periods of time. How multiple stressors interact to drive the stress response in a time-dependent manner, and whether these interactions can be partly explained by parallel genetic pathways has yet to be explored, mainly due to the large experimental space that combinatorial exposures entails. The goal of the proposed work is to understand how oxidative stress is integrated and processed by an organism. In particular, we aim to answer two questions: 1. How are neuronal signals from sensing ROS-generating compounds integrated with whole-animal tissue responses? 2. Do different pro-oxidant compounds and other stressors (dietary restriction, heat stress, and pathogen exposure) exhibit interacting effects on the stress response? Our approach integrates microfluidics, C. elegans, in vivo fluorescence imaging, image analysis, experimental design, and statistical modeling.
It is now known that a relationship exists between Traumatic Brain Injury (TBI) and the risk for Alzheimer??????????????????s Disease (AD). Given that a large portion of the population, particularly veterans and former athletes, have suffered traumatic brain injuries, understanding how TBI and AD are correlated is of utmost importance to identify efficient prevention and treatment strategies. However, understanding how TBI increases the risk of AD is a significant challenge, since identifying changes in form and function of the brain and neurons upon injury and the effect of those changes on risk of AD is unfeasible in humans, and technically very difficult in mammalian model organisms. The work presented here will be focused on understanding how different patterns of injury result in adverse effects in the form and function of neurons, and how these changes might accelerate the onset or progression of AD. Our work is based on using a well-known model organism: C. elegans, a small nematode that has been fundamental in our current knowledge of neuroscience and aging. We will develop controllable micro-devices capable of inducing injury in C. elegans?????????????????? neurons in the presence and absence of amyloid-beta, a peptide at the root of Alzheimer??????????????????s Disease pathology. We will characterize how different patterns of injury result in changes in neuronal shape and integrity, and the combined effects of injury and amyloid-beta peptides. In addition, using this platform, we will search for genes that affect the process upon which the presence of amyloid-beta potentiates the adverse effects of brain injury. The proposed work will provide a tool to perform experiments in a high-throughput fashion, and thus enable testing a large number of injury patterns to identify the most significant, as well as determining the most relevant genes involved in this process. The results from this study will be fundamental in understanding the biological processes affected in TBI and AD, and will be fundamental for identifying potential treatment and prevention strategies.
Spatial regulation of gene expression is of paramount importance in animal development, with improper regulation resulting in defects in development and disease states in adults. At the DNA level, gene regulation can be achieved by transcription factors binding to their cognate sequences, which are often clustered together. These clusters, or enhancers, have been identified through a combination of labori-ous experimental work, computational methods, or genome-wide experimental methods. However, the relationship between enhancer sequence, transcription factor concentration(s), and spatially well-defined gene expression domains has not been clearly identified. One barrier to discerning this rela-tionship is the lack of high-throughput methods in a genetically tractable model animal. The overall objective of this proposal is to construct an input-output map that relates a wide variety of enhancer sequences to quantitative measurements of gene expression domains. To do this, we will perform high-throughput measurements of gene expression, in whole Drosophila embryos, driven by enhancers of varying sequence. We will design a Rapidly Evolving Enhancer DNA (REED) construct, which is a novel iteration of a method in yeast that uses cycles of reverse transcription to rapidly evolve a DNA locus. Our extension will improve efficiency by using recombinase-based integration, which will allow us to translate the method to animals. We will rapidly evolve a short segment of the fly genome that will act as an enhancer for a reporter construct. We will use a microfluidic-based array to image gene expression patterns at a rate of roughly 100 embryos per hour. The REED construct in animals is a novel method. While some cases exist of separate components of the proposed cassette, they have not been used together to rapidly evolve DNA sequence in ani-mals. The proposed work is high reward, as it will lead to a deeper understanding of one of the grand challenges of regulation of gene expression. Furthermore, high throughput evolution methods exist in unicellular organisms; however, such methods have yet to be pioneered in a multicellular animal. In that regard, our proposed work has the potential to impact many areas of animal biology. Furthermore, the development of a controllable microfluidic array to image and sort Drosophila embryos has wide applicability. While some microfluidic devices for imaging Drosophila embryos exist, our proposed de-vice will be able to sort the embryos depending on the imaging results. Furthermore, existing devices are designed to measure the dorsal-ventral axis, while ours will have the capability to image either ax-is.
We propose to establish a microfluidics-enabled in vitro system to quantitatively interrogate the effects of external stimuli (BPA, oxygen concentration/gradient) and intercellular commu-nication (trophoblast-macrophage interactions) on trophoblast differentiation and invasion in 3D cultures.
Although a multitude of pathways are known to affect longevity, how the interactions between all the players is regulated in a spatiotemporal manner, and how these interactions change through life and upon specific perturbations is far from understood. Given that longevity is a downstream integrative phenotype, it is difficult to fully describe the regulation of lifespan without a systems approach, with the fundamental premise that biomolecular entities dynamically interact and act in concert within and between cells and tissues. The overall goal of this proposal is to quantitatively determine how the spatiotemporal interplay of key aging regulators in response to environmental inputs drive longevity in C. elegans. To answer this question, we apply high throughput combinatorial stimuli and live imaging platforms, along with data-driven mathematical algorithms. We will develop models that reveal interactions between aging regulators in a spatiotemporal manner. This pipeline will enable quantitative longitudinal, and non-destructive acquisition of lifespan and healthspan, as well as live monitoring of protein abundance of key nodes in the aging network. Moreover, we will use these tools to understand gene x environment interactions, and to identify the optimal environmental conditions that can maximize lifespan. Finally, we will use these platforms and the developed predictive models to elucidate how the network state can be affected by temporal gene silencing. The work performed will be the grounding work to correlate molecular spatiotemporal dynamics of large-scale aging-associated networks with lifespan, thus opening new avenues in aging research.
In this work, we will develop mathematical models that represent the fundamental rules that describe heterogeneity, buffering, and determination of lifespan in C. elegans. We will characterize the lifelong spatiotemporal activity of genes that regulate key aging pathways under a variety of environmental conditions, and identify the rules that link this information to longevity. We aim to define how lifelong activity of evolutionary conserved longevity and stress pathways is cumulatively integrated to determine lifespan as an emergent property of the system. Experimental tools that enable simultaneous quantitative analysis of in vivo gene activity and combinatorial environmental perturbations will be developed. These tools hinge on microfluidics, computer vision, automation, and new reporter strains to track gene activity under endogenous regulatory control. Large data sets will be used to derive data-driven mathematical models that describe the stochastic dynamics of gene activity and its downstream outcome: lifespan. Novel statistical techniques will be combined with mathematical models to infer phenotypic heterogeneity and robustness within populations. By performing longitudinal analysis at the single-individual level, we will extract the necessary information to describe the relationship between stochasticity in gene activity patterns and longevity. We will use this information to understand how and whether heterogeneity in gene activity is transferred to lifespan heterogeneity. For instance, we will determine whether lifespan variability amongst a population can be explained by variations in aging pathway activity, or whether lifespan is an inherently stochastic process.
The overall goal of this proposal is to define the regulators of synaptic strength through morphological descriptors of synaptic sites in C. elegans. In this work, I propose to test the central hypothesis that synaptic morphology is correlated with aging, and is indirectly affected by environmental cues through activity-dependent mechanisms. This work will be performed in a three-year independent research phase (R00), and continues work performed in the mentored K99 phase of this grant. The goal of this independent phase is to quantify the aging-induced morphological changes that occur in synapses, their correlated functional and behavioral outputs, and the role that neuronal activity patterns play on aging-induced synaptic changes. In order to accomplish this goal, a high-throughput integrative synaptic morphology and function characterization pipeline developed will be applied. This work will be based on: (1) establishing the morphological and functional changes that occur at synaptic sites throughout an animal??????????????????s lifespan, (2) the relationship between age-related neuronal decline, stress response and longevity genetic pathways, and (3) determining whether controlled lifelong patterns of neuronal activity has an effect on synaptic morphology and, more importantly, on aging-induced neuronal decline. The proposed work here is innovative since it will enable otherwise unfeasible in vivo studies of synaptic morphology at a large scale and is projected to facilitate morphological studies of neural connections as well as genetic and drug screens, shedding light on genetic pathways involved in neural function and treatments to alleviate and prevent neuronal decline.
The identification of drugs that can treat Amyotrophic Lateral Sclerosis is a challenging problem. In order to better identify putative drug candidates, and their optimal combinations, this proposal will focus on high-throughput screening of drug libraries in an animal model for ALS, particularly Caenorhabditis elegans. This proposal will take an integrative approach, where the changes effected by drugs on the ALS animal model will be assessed from a several perspectives: cellular anatomy, electrophysiology and behavior. This integrative approach should aid in better identifying true putative drug candidates, given that the effects of drugs on ALS should act at all levels. This proposal will focus on developing a phenotyping and drug screening platform that will be: high-throughput (HT) to screen large chemical libraries, high-dimensional, HD, (to incorporate all aspects of an ALS phenotype), and quantitative, to avoid missing drug candidates that might require higher concentrations for a full phenotype rescue. This platform will be developed by incorporating microfabrication technology and automated image analysis, and will be able to screen over a hundred animals per hour. Thus, our HT-HD phenotyping platform combined with C. elegans models for ALS will allow researchers to comprehensively test very large chemical libraries in vivo and select from this group only the most promising drugs and drug combinations for labor intensive mammalian testing.