Sam Jones, PhD, is a biomedical scientist turned science journalist based in Washington, DC. Over the years she has held a range of titles, including scientist, editor, and science video host, but today she is the executive producer & co-host of the science podcast Tiny Matters. She's also a freelance journalist and fact-checker—writing for outlets like The New York Times, Scientific American, Popular Science, and Nature—and an occasional freelancer for biotech companies, writing and editing case studies, website materials, and social media content. You can find her work at sjoneswriting.com.

Systems that evolve over time in dynamic and nonlinear ways range from robotics to systems biology. These systems may enter undesirable states (e.g. collision with obstacles, population levels of harmful bacteria, etc.). Reachability analysis allows us to analyze when and how systems will become unsafe, and how to apply inputs to the system to maintain safety and reach desired states.  I will discuss applications in various areas, and current plans to extend our work for analysis of multi-scale biological systems.

Proteases as molecular machines are known to drive a large array of fundamental processes in the body. While the presence of proteases can be probed with conventional techniques to measure genes and proteins, the ability to measure protease cleavage activity in living tissue is limited. Yet, we know proteases are regulated by a multitude of factors in their environment, including their concentration, spatial localization, availability of cofactors, and presence of regulators. In order to create a tool to measure proteases in the living tissue of the injured brain, we created a nanosensor that detects the protease calpain.

The treatment of antibiotic-resistant bacterial infections is an unmet therapeutic need, due to the rapid emergence of resistant strains and the low level of investment in new therapeutics. The use of nanoparticles to enhance activity of current therapeutics, and to enable new approaches based on nucleic acid therapeutics, will be described.  Our effort focuses on the use of porous silicon nanoparticles, and systems that deliver small molecule antibiotics or siRNA against inflammatory macrophages will be used as examples.  Attachment of functional peptides imparts specific targeting and cell penetration properties to the constructs that show improved gene silencing and therapeutic outcomes in vivo.

Shivani Shukla, Bioengineering (BENG) PhD Program, UC San Diego
Co-mentors: Zeinab Jahed and Lingyan Shi

Electrical signaling governs muscle contraction, brain function, and insulin secretion. While clinical EEG/ECG
techniques signify aberrant electrical activity during disease, it is unclear how single cell action potentials (APs)
are affected by disease or drugs. Gold standard electrophysiology tools such as patch clamp and extracellular
microelectrode arrays are insufficient tools for recording APs from many cells for hours, weeks, or months. The
goal of my project is to develop a higher throughput and tunable platform for obtaining electrophysiological
signals from single adherent cells with millisecond resolution. In this seminar, I will present our newly developed
platform which contains arrays of nanopillar (NP) electrodes made using maskless photolithography and a two-
step dry and wet etching technique. We optimized various surface functionalization techniques to improve
adhesion of diverse cell types on our platforms. We demonstrate electrical recording from electrogenic 2D cardiac
monolayers, 3D printed cardiomyocytes, neuron-like PC12 adherent cells, and bacterial biofilms, demonstrating
multi-scale, multi-kingdom electrophysiological capabilities using a single device. We observed intracellular
action potentials for several days in 2D monolayers and 3D-printed cardiomyocytes with altered waveforms,
indicating differences in cytoarchitecture for drug screening. 3D cultures grown on paired-electrode platforms
showed simultaneous APs and extracellular spiking within a 10 um distance, suggesting the possibility of
extrapolating APs from in vivo extracellular signals. In differentiated PC12 cells, intracellular APs were recorded
over several days for the first time, and morphologies of neurites atop nanopillars were characterized using
fluorescence microscopy and electron microscopy. Our platform was redesigned to house bacterial biofilms,
which show membrane potential oscillations in response to high potassium flow. Biofilm electrophysiology
directly influences antibiotic resistance and gut microbiome heterogeneity. The versatility of our nanopillar
electrode arrays to record electrical signals from cells with a range sizes from 2 um - 30 um in diameter offers a
powerful tool for understanding how single cell electrical activity affects function and disease.

Kristen Garcia, Bioengineering Ph.D. Program, UC San Diego

Co-Mentors: Daniela Valdez-Jasso, Bioengineering

Pulmonary arterial hypertension (PAH) is a life-threatening disease characterized by pulmonary vascular remodeling and is represented by the narrowing of blood vessels in the lungs. I am interested in gaining a deeper understanding of the remodeling process of the right ventricle (RV) from the cellular-level up to the organ-level in PAH, and to determine how estrogen or other sex-differences affects this process. PAH is four times more likely to affect females over males, specifically females between the ages of 30-60 years old. I am working with an animal model to look across the multiple scales of the heart. On the organ-level, I use cardiac magnetic resonance imaging (cMRI) and in vivo pressure-volume relationships to quantitatively analyze the systolic/diastolic function of the heart. Diffusion-tensor MRI imaging (DTI) is also used to get the geometry and fiber orientation of the organ as a whole. These two imaging techniques are used to create a biventricular mesh of the heart. Next, mechanical tests on the planar biaxial device are used to determine stress-strain measurements on the tissue level, which can help determine how the stiffness changes in relation to the progression of PAH. Using tissue engineering applications, the tissue is decellularized to look at the effect of the extracellular matrix on the stress-strain measurements, and mechanobiology of the cellular level is determined to conclude how cells change over disease stages. Combining the knowledge of all these experiments will allow for us to use and adapt a very useful three-dimensional model that can help predict how structural and functional changes in the RV lead to RV failure, and how this is affected by the sex of the animal. I am currently in the process of using cMRI and DTI data to determine the myofiber directions throughout the heart and looking into levels of estrogen and its relation to the hemodynamic data results. 

Andrew Nguyen, Mechanical and Aerospace Engineering Ph.D. Program, UC San Diego

Advisor: Professor Padmini Rangamani, Mechanical and Aerospace Engineering

Synaptic plasticity is important for learning and memory. With increasing evidence linking sleep states to changes in synaptic strength, an emerging view is that sleep promotes learning and memory, by facilitating experience-induced synaptic plasticity. Adenosine, a neuromodulator often associated with the regulation of sleep, and its receptors (A1R and A2AR) have been found to be responsible for the potentiation or inhibition of synaptic transmission in the context of calcium signaling in neurons. In my work, I hypothesize that the interactions between adenosine and various calcium-mediated signaling pathways, such as glutamate-mediated calcium signaling, will give rise to the modulation of synaptic plasticity in neurons. To investigate this hypothesis I have been developing a quantitative model of signaling crosstalk between adenosine receptors and Glutamate receptors (mGluR5) to capture the connection between the molecular machinery associated with circadian adenosine to the molecular machinery associated with synaptic plasticity.

The goal of our lab at the University of California, San Diego (called the Bio-Nano-Electronics or BioNE Lab) is to “Engineer nanoscale electronics for higher throughput cellular- and molecular-scale sensing, to accelerate scientific discoveries related to human health and disease”.  To design more intelligent nano-electronics we first carefully characterize the complex nano-bio interface. Next, we use this knowledge to design our nano-electronics to be higher throughput, accurate, sensitive, with minimal perturbations to the biological system. Finally, with confidence in our biological read-outs from these high-throughput tools, there is a need to develop algorithms that can “learn” from our big dataset to answer fundamental biological questions. In this seminar I will present our recent advances using the above approach to design a nanoscale platform for recording electrical signals in parallel from hundreds to thousands of cardiac cells for cardiotoxicity screening. I will also briefly discuss ongoing efforts in our lab to utilize our platform for neuronal and biofilm electrophysiology. 

Metaproteomics is a mass spectrometry method to unbiasedly analyze the proteins expressed by a community of organisms. Stool metaproteomics is an emerging technique for the analysis of microbial protein abundance in human feces. Up to half of the dry solids in stool are bacterial biomass, almost exclusively from the digestive tract, making stool ideal biomaterial to analyze gut microbial proteins, as well as host and dietary proteins and other biomolecules. A recent study from the Gonzalez Lab employed stool metaproteomics to study inflammatory bowel disease, revealing that Bacteroides spp. proteases are elevated in disease and colitis phenotypes can be rescued with protease inhibitor treatment. In this talk, I will be discussing recent advances in stool metaproteomics, including high-throughput workflows, database development, and bioinformatic pipelines. I will also describe how I am addressing persistent limitations in stool metaproteomics and how I am applying this methodology to uncover protein effectors in the gut-brain axis in health and disease. 

Heart failure remains a significant cause of morbidity, mortality, and medical costs. 2-deoxy-ATP (dATP), a novel heart failure therapeutic, has been shown to improve contractile function without impairing relaxation. Previous studies in our group have shown that elevated dATP increases the rate of crossbridge binding cycling and the rate of calcium transient decay. However, the precise molecular mechanisms of these effects and how therapeutic responses are achieved when dATP is only a small fraction of the total ATP pool are unknown. We used multiscale computational modeling to integrate a filament-scale model of acto-myosin interactions, whole myocyte model, organ scale model of biventricular mechanoenergetics, and whole body circulatory model to predict the effects of dATP on ventricular mechanics in normal and heart failure conditions. We discovered synergistic interactions between calcium dynamics and force development that leads to improvements in myocyte contractility and lusitropy. Simulations also predicted that increased transition out of the super-relaxed state of myosin with elevated dATP can explain the large increases in force observed at low percentages of dATP. We further showed that this effect likely depends on both nearest neighbor cooperativity and thick filament mechanosensing. We predicted improvements in ventricular function consistent with experimental data in both healthy and failing conditions, with no additional impairment of metabolic state. Ventricular function was improved to a greater degree in failure than in healthy conditions, due at least in part to improved energy efficiency with elevated dATP.

AMPAR, alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor, is a receptor concentrated at the postsynaptic density (PSD) of dendritic spines. AMPAR is often used as a readout for synaptic plasticity since increased AMPAR density at the PSD leads to a stronger synaptic response to a stimulus while decreased AMPAR density leads to a weaker response. Changes in AMPAR density during synaptic plasticity involve numerous complex signaling pathways, many of which have been studied both experimentally and computationally. However, there are still open questions regarding how the dynamics of several key components upstream of AMPAR, including CaMKII and phosphatase dynamics, influence the mechanisms and dynamics of AMPAR trafficking. Here we construct both a deterministic compartmental ordinary differential equations model and a deterministic reaction-diffusion model of the simplified signaling network underlying AMPAR dynamics during synaptic plasticity to probe how upstream kinase and phosphatase dynamics influence AMPAR dynamics and trafficking. We find that key signaling components and trafficking mechanisms act over different timescales to modulate AMPAR density at the PSD. In particular, AMPAR temporal dynamics show two timescales associated with endo/exocytosis and total available AMPAR sources, while there is a strong relationship between total AMPAR number at the PSD and the spine volume to surface area ratio.

The monitoring of intracranial pressure (ICP) fluctuations, which is needed in the context of a number of neurological diseases, requires the insertion of pressure sensors, an invasive procedure with considerable risk factors. ICP fluctuations drive the wave-like pulsatile motion  of  cerebrospinal  fluid  (CSF)  along  the  compliant  spinal  canal.  Systematically derived simplified models relating the ICP fluctuations with the resulting CSF flow rate can be useful in enabling indirect evaluations of the former from non-invasive magnetic resonance imaging (MRI) measurements of the latter. As a preliminary step in enabling these  predictive  efforts,  a  model  is  developed for  the  pulsating  viscous  motion of  CSF  in  the  spinal  canal,  assumed  to  be  a  linearly  elastic  compliant  tube  of  slowly varying section, with a Darcy pressure-loss term included to model the fluid resistance introduced  by  the  trabeculae,  which  are  thin  collagen-reinforced  columns  that  forma  weblike  structure  stretching  across  the  subarachnoid  space  (SSAS).  Use  of  Fourier-series  expansions  enables  predictions  of  CSF  flow  rate  for  realistic  anharmonic  ICP fluctuations. The flow rate predicted using a representative ICP waveform together with a realistic canal anatomy is seen to compare favorably with in-vivo phase-contrast MRI measurements at multiple sections along the spinal canal. The results indicate that the proposed model, involving a limited number of parameters, can serve as a basis for future quantitative analyses targeting predictions of ICP temporal fluctuations based on MRI measurements of spinal-canal anatomy and CSF flow rate.

Mounting evidence suggests cerebrovascular dysfunction plays an important mechanistic role in the development of Alzheimer’s disease (AD), and that cerebral white matter (WM) is especially vulnerable to the effects of microvascular dysfunction. Arterial Spin Labeling (ASL), a class of Magnetic Resonance Imaging (MRI) techniques, is a popular method for assessing cerebral hemodynamics due to its non-invasive nature. However, inaccurate ASL methodology has prevented the systematic characterization of WM microvascular health and hemodynamics, even across healthy aging, thus hindering our understanding of cerebrovascular contributions to AD development. My project investigates whether velocity-selective ASL (VSASL) is a more robust measure of WM cerebral blood flow (CBF) than conventional techniques and can better capture age-related change in CBF.

Mitochondrial transcription factor A (TFAM) plays important roles in mitochondrial DNA (mtDNA) compaction, transcription initiation, and regulation of processes like transcription and replication processivity. Possible modes of local regulation of TFAM function within the mitochondrial matrix include phosphorylation by protein kinase A (PKA) and non-enzymatic acetylation by acetyl-CoA. Here we present that DNA-bound TFAM is less susceptible to these modifications. We confirm that phosphorylated or acetylated TFAM compact circular double-stranded DNA just as well as unmodified TFAM and provide an in-depth analysis of acetylated sites on TFAM. We show that both modifications of TFAM increase the processivity of mitochondrial RNA polymerase during transcription through TFAM-imposed barriers on DNA, but that each version of modified TFAM retains its full activity in transcription initiation. We conclude that TFAM phosphorylation by PKA and non-enzymatic acetylation are unlikely to occur at the mtDNA and that modified free TFAM retains its vital functionalities like compaction and transcription initiation while allowing transcription processivity enhancement.

I propose a Bayesian parameter estimation framework to facilitate model calibration and uncertainty analysis for predictive models of biological systems. Many of these models are nonlinear differential equations that characterize the dynamics of the relevant biochemical species. System biologists need to estimate many free parameters from sparse and noisy experimental data to calibrate these models. Despite the uncertainties associated with this data, systems biologists directly fit the free parameters, typically ignoring any uncertainty altogether. My work moves past this traditional model-fitting paradigm by adapting an approximate marginal Markov chain Monte Carlo (MCMC) method for Bayesian parameter estimation. I find that this method can recover the posterior parameter distribution from experimental data for a well-known biological system, the mitogen-activated protein kinase (MAPK) signaling pathway. This work introduces a new modeling paradigm that bridges the gap between standard systems biology modeling practices and rigorous uncertainty quantification.

AMP-Kinase (AMPK) is the master sensor for the organism’s metabolism and energy, and has many diseases linked to both its activation and inhibition, including cancer, gastrointestinal, heart, and even neurodegenerative diseases. My main research project involves designing and synthesizing potent activators selective for α1β1γ1 and α2β1γ1 isoforms. The gene encoding the β1 subunit of AMPK, PRKAB1, was first discovered as a viable drug target for inflammatory bowel disease (IBD) by our collaborators, the Ghosh lab (UCSD School of Medicine). Using Boolean implication networks to analyze gene clusters, the continuum states of IBD-related diseases were more easily differentiated between disease and health states of patients. Recent efforts in medicinal chemistry in collaboration with the Ghosh lab has opened up some exciting new opportunities in drug design to target proteins such as APMK. Using in silico docking experiments, along with previously published ligand-protein pair co-crystal structures as references, we were able to create a robust model for predicting the binding affinity and selectivity for novel β1 selective agonists. I have established the chemistry and methodology for synthesizing these agonists, and intend to both synthesize and test (in vitro) these novel β1 selective agonists designed in silico.

Dilated and hypertrophic cardiomyopathies (DCM and HCM) affect 1 in 500 Americans. Current treatments only slow disease progression without treating underlying mechanisms; therefore, novel therapeutics are needed to treat HCM and DCM. 2’-deoxy-adeninetripohsphate is a naturally occurring myosin activator, and proposed heart failure and DCM therapeutic. In this work, I use molecular simulations to understand the mechanism by which dATP increase cardiac contractile force and function. Specifically, I have used molecular dynamics simulations to build Markov models of protein kinetics, that can be used with Brownian dynamics simulations to understand actin-myosin kinetics. Through this work, have shown that dATP functions by increasing the association rate of myosin to actin in the pre-powerstroke state. The DCM mutations A223T and S532P found cardiac myosin heavy chain were also modeled with this framework and found to have diverging effects on the association rate of myosin to actin. Specifically, dATP, S532P and A223T have 5.3-, 3.0-, and 0.56-time fold changes to the association rate respectively. These simulations help to predict organ level function, and lead to improved mechanistic understandings of actin-myosin interactions.

Pulmonary arterial hypertension (PAH) is a life-threatening progressive disease that is  characterized by pulmonary vascular remodeling and is represented by narrowing of blood  vessels in the lungs. PAH effects females four times more likely than males, specifically females  between the ages of 30-60 years old, leading to an interesting paradox known as the estrogen  puzzle. Past research has resulted in contradicting conclusions; some of which show a  protective effect of estrogen on PAH versus others showing a disease promoting effect. It is  known that right ventricular (RV) function and morphology are important indicators of the  severity of PAH. I am interested in determining the role that estrogen plays on the right  ventricle during the progression of PAH. I hypothesize that estrogen plays a major role in the  remodeling of the RV leading to an overall protective effect against right heart failure. I aim to  quantify the hemodynamics of the right ventricle throughout the progression of PAH using a rat  model and to identify the sex dependent effects of estrogen in the remodeling and mechanics  of the RV. After the induction of PAH using a Sugen-Hypoxia protocol, terminal procedures are  conducted, in which in vivo blood pressure-volume relationships are measured, with the goal of  investigating changes due to pressure overload. I am currently focusing on these pressure volume loops for each subset of animals with the goal of finding patterns to describe the  differences in the hearts function for males, non-ovariectomized females, and ovariectomized  females. I am looking at the PV loop as a whole, the slope of the isovolumic contraction and  relaxation phases, and am attempting to determine if we can expect to see a specific range of  values for the PV curves for a given group. My future plans are to dive more into the estrogen  component of RV remodeling in PAH and relate estrogen levels to PV loops and overall heart  function.