The Aguilar group is focused understanding transcriptional and epigenetic mechanisms of skeletal muscle stem cells in diverse contexts such as regeneration after injury and aging. We focus on this area because there are little to no therapies for skeletal muscle after injury or aging. We use various types of in-vivo and in-vitro models in combination with genomic assays and high-throughput sequencing to study these molecular mechanisms.
Our laboratory focuses on (1) the biology of cancer metastasis, especially bone metastasis, including the role of the host microenvironment; and (2) mechanisms of chemoresistance. We explore for genes that regulate metastasis and the interaction between the host microenvironment and cancer cells. We are performing single cell multiomics and spatial analysis to enable us to identify rare cell populations and promote precision medicine. Our research methodology uses a combination of molecular, cellular, and animal studies. The majority of our work is highly translational to provide clinical relevance to our work. In terms of data science, we collaborate on applications of both established and novel methodologies to analyze high dimensional; deconvolution of high dimensional data into a cellular and tissue context; spatial mapping of multiomic data; and heterogenous data integration.
Obesity promotes type 2 diabetes (T2D) the 3rd leading cause of death in the United States and accounts for $237 billion healthcare cost. T2D and obesity promote infections that cause sepsis, the leading cause of mortality in the intensive care unit following traumatic injury. Despite advances in supportive care, sepsis mortality remains 25% and escalates over time. Survival from sepsis depends on emergency myelopoiesis of macrophages (MΦ) to clear bacteria and deescalate inflammation. Resolving inflammation requires MΦ polarization from pro-inflammatory M1 to anti-inflammatory MΦ states. The MΦ ability to polarize depends on the intrinsic plasticity inherited from hematopoietic stem and progenitor cells (HSPCs) during emergency myelopoiesis. Our published data in trauma and sepsis in mice and humans demonstrates that obesity and T2D alter HSPC myelopoiesis, inhibit MΦ plasticity and prevent M1Φ polarization to other functional MΦ states. However, the impact of altered MΦ myelopoiesis and restricted M1Φ polarity on sepsis pathogenesis is unknown. A critical need exists to understand the mechanisms by which obesity and T2D alter myelopoiesis, inhibit MΦ plasticity and prevent MΦ polarity to promote bacterial sepsis mortality. We hypothesize that obesity and T2D prime HSPC myelopoiesis to produce dysfunctional M1Φs incapable of bacterial clearance, and effective polarization which hinder inflammation resolution during sepsis and cause mortality. We will test the hypothesis with the following aims that, when completed, will fill the current knowledge void and improve sepsis survival. In Aim 1 we will determine the mechanisms in T2D and obesity that alter myelopoiesis in bacterial sepsis. The findings will reveal how obesity and T2D prime HSPCs and alter myelopoiesis to prevent MΦ polarity in mice and humans with sepsis. In Aim 2 we will identify the functional consequences of obese, T2D M1Φs unable to polarize to other activation states during bacterial sepsis. We will explore how restricted MΦ polarity effects immune cell responses and cytokine production to define how T2D and obesity impede inflammation resolution. The data generated will identify new pathways that promote aberrant myeloid production, restricted MΦ plasticity and prevent inflammation resolution during bacterial sepsis. Novel targeted therapies can then be developed for clinical implementation for bacterial eradication, wound healing and survival from sepsis in obesity and T2D.
Study of Pandemic Publishing: How Scholarly Literature is Affected by COVID-19 Pandemic
This project addresses the quality of recently published COVID-19 publications. With the COVID-19 pandemic, researchers publish a lot their research as preprints. And while preprints are an important development in scholarly publishing, they are works in progress that need further refinement to become a more rigorous final product. Scholarly publishers are also taking initiatives to accelerate publication process, for example, by asking reviewers to curtail requests for additional experiments upon revisions. Sacrificing rigor for haste inevitably increases the likelihood of article correction and retraction, leading to spread of false information within supposedly trustworthy sources that have a peer-reviewing process in place to ensure proper verification. I study the quality of COVID-19 related scholarly works by using CADRE’s datasets to identify signs of incoherency, irreproducibility, and haste.
Applications of computational tools for molecular modeling (Discovery Studio, ICM-Pro, MOE, and YASARA) and data science (ADMET Predictor, KNIME, Origin Pro, Prism, Python, and R) to computational toxicology, drug discovery, homology modeling, molecular dynamics, and protein structure/function prediction. Current special interests include therapeutics for neurodegenerative disorders (Alzheimer’s, Parkinson’s, and motor neuron diseases) and infectious diseases (COVID-19).
3D alignment of acetylcholinesterase (AChE) from mouse (magenta) and electric eel (gray) showing the amino acid residues of the catalytic triad.
My work falls into three general application areas. I am an applied (accredited) biostatistician with a strong team science motivation and I collaborate with scientists in primarily the biomedical sciences, contributing expertise in experimental design, statistical analysis/modeling, and data visualization. I have held faculty appointments in Schools of Medicine and Nursing, and also worked as a senior scientist in the Human Research Program at the NASA Johnson Space Center. I currently direct an Applied Biostatistics Laboratory and Data Management Core within the UM School of Nursing, and maintain several collaborative research programs within the School, at NASA, and with collaborators elsewhere.
Synthetic polymers have been used as a molecular platform to develop host-defense antimicrobial peptide (AMP) mimics toward the development of “polymer antibiotics” which are effective in killing drug-resistant bacteria. Our research has been centered on the AMP-mimetic design and chemical optimization strategies as well as the biological and biophysical implications of AMP mimicry by synthetic polymers. The AMP-mimetic polymers showed broad-spectrum activity, rapid bactericidal activity, and low propensity for resistance development in bacteria, which represent the hallmarks of AMPs. The polymers form amphipathic conformations capable of membrane disruption upon binding to bacterial membrane, which recapitulates the folding of alpha-helical AMPs. We propose a new perception that AMP-mimetic polymers are an inherently bioactive platform as whole molecules, which mimic more than the side chain functionalities of AMPs. The chemical and structural diversity of polymers will expand the possibilities for new antimicrobial materials including macromolecules and molecular assemblies with tailored activity. This type of synthetic polymers is cost-effective, suitable for large-scale production, and tunable for diverse applications, providing great potential for the development of versatile platforms that can be used as direct therapeutics or attached on surfaces.
Shobita Parthasarathy studies the governance of emerging science and technology as well as the politics of evidence and expertise in policymaking, in comparative and international perspective. She has a long-standing interest in the use and regulation of genomic and genetic data. Her first two books, Building Genetic Medicine: Breast Cancer, Technology, and the Comparative Politics of Health Care (MIT Press, 2007) and Patent Politics: Life Forms, Markets, and the Public Interest in the United States and Europe, (University of Chicago Press, 2017) cover these themes. Using comparative and qualitative interpretive research methods, she studies the the ethics, politics, and economics of data collection and interpretation. This includes concerns about consent and intellectual property in genomic databases, the social implications of commodifying data, the use of personal data in determining access to social services and health care, and the use of data for social justice and public good.
Her current research focuses on the politics of inclusive innovation in international development, with a focus in India. She is interested in how political culture and ideology shape what counts as inclusive “innovation”, and in the implications for social and political order—particularly the “empowerment” of poor girls and women.