2021 Posters

Here we recapitulate the full diversity of spinal cell types along both the rostrocaudal (R/C) and dorsoventral (D/V) axes with chemically defined, scalable protocols using human pluripotent stem cells (hPSCs). We first induce R/C patterning to generate neuromesodermal cells from a defined anatomical level, then instruct these cells to become early spinal progenitors. By providing appropriate D/V signaling, spinal progenitors can be sub-specified to generate tunable ratios of motor neurons (MNs) and locomotor interneurons (INs) from the ventral spinal cord, or TGF-β-dependent proprioceptive INs and TGF-β-independent sensory INs from the dorsal spinal cord. Cultures with over 95% neuronal yield can be generated in as little as 19 days, and these protocols can be used modularly to generate phenotypes from different anatomical levels. Single-cell RNA-sequencing reveals regionally specified neurons with discrete Hox gene profiles, representation of all major motor and somatosensory spinal cell types, and the presence of human-specific cell populations. We applied the computational alrogithm Arborteum to infer modules of coexpressed genes between subpopulations, facilitating the discovery of novel markers defining region-specific neuronal types. Altogether, this dataset enables characterization of the diversity of human spinal cells for the first time. We anticipate that access to these cells will advance a mechanistic understanding spinal development, expand the potential and accuracy of in vitro models, provide insight into novel therapeutic targets, and represent clinically relevant populations for cell transplantation.

To address which acetylation sites are functionally relevant, our lab has developed and validated an improved, complementary proteomics method to calculate global and site-specific acetylation stoichiometry. Using the acetylation stoichiometry analyses, the goal of this study is to understand acetylation dynamics in serum stimulated cells and to define the cellular mechanisms involved in regulating the unique responses and rapid changes in protein acetylation.

The mechanistic basis for Flavobacterium colonization of the rhizosphere and soil is poorly understood, but it seems likely that colonization of surfaces such as roots and soil particles is essential for the maintenance of Flavobacterium in the rhizosphere. Sand is a common and easily manipulated soil particle, making it ideal for studying surface colonization in the laboratory. To dissect the genetic determinants of surface colonization, we conducted a massively parallel mutant screen (InSeq) of F. johnsoniae in the presence and absence of sand. This high-throughput screen revealed 25 genes likely to be important for sand colonization, including genes predicted to be involved in cell membrane biogenesis; motility; transport of amino acids, nucleotides, or inorganic ions; and metabolism. Most of the genes identified by the InSeq screen are uncharacterized, encoding either hypothetical proteins or proteins of unknown function. We validated the involvement of seven genes in colonization by constructing in-frame deletions in genes fjoh_0651 (hypothetical protein), fjoh_1448 (exosortase family protein XrtF), fjoh_1449 (exosortase F system-associated protein), fjoh_2379 (LysM peptidoglycan-binding domain-containing protein), fjoh_1653 (SprA), fjoh_1555 (PorV) and fjoh_1556(PorU) and testing the resulting mutants’ ability to colonize sand and other substrates such as glass and polystyrene. Four mutants tested were affected in attachment to and persistence on all three substrates, indicating the importance of the targeted genes in general surface colonization. Our results provide insight into surface colonization by F. johnsoniae and form the basis for further study of F. johnsoniae survival on surfaces in the rhizosphere.

Our strategy combines state-of-the-art, label-free optical metabolic imaging (OMI) to measure the physiological, functional, and high-content morphological status of photoreceptors, with single cell transcriptomic profiling (scRNA-seq) and regulatory network-based methods to analyze single cell data. The inferred gene regulatory networks can be used to identify a small (~50) set of biomarkers for adverse events within functional cells. Proof-of-concept studies will focus on the retina, specifically on rod and cone photoreceptors (PR) within 3D optic vesicle (OV) organoids derived from human pluripotent stem cells (PSCs). Creation of this dataset and validation of this approach will leverage these bioengineering technologies toward the development of safer genome editing therapeutics. By tackling a 3D, heterogeneous organoid culture, our approach will extend to more complex cultures. Thus, the impact of this work could be broad, with the potential to advance the development of genome editors administered to any tissue.

However, if some abiotic systems do share features similar enough to biotic systems but different enough from other abiotic systems, it is highly likely that the mechanism underlying such features also governs systems on the path from non-life to life. With this rationale, we perform comparative analyses on realistic abiotic and biotic reaction networks with the focus on autocatalysis, which underlies propagation – a key feature of life. We propose the concept of and provide an algorithm to detect Seed-dependent Autocatalytic Cycle (SAC), which feeds on food chemicals to propagate but cannot emerge without being seeded by some non-food chemicals. We found that serial stochastic activation of SACs can result in incrementally complexifying autocatalytic networks, and that multiple seemingly different life-like features, including stochastic seeding, seed-induced autocatalysis, trophic hierarchy, interdependence, scaffolding, and adaptation, are all natural outcomes of the reaction networks organized by SACs. In addition, the SAC theory provides a candidate roadmap from a simple abiotic environment to life-like prebiotic systems and finally to primitive forms of life, by a prebiotic evolutionary mechanism not necessarily requiring linear polymers storing genetic information. This also inspires new insights into designing origin-of-life experiments aimed at detecting SACs in vitro.

We report for the first time that SIRT3 is dispensable for CR-dependent longevity, and unexpectedly, find that SIRT3 ablation further extends lifespan under CR compared to WT mice. We revealed that loss of SIRT3 resulted in attenuated succinate-dependent respiration but preserved palmitate-dependent respiration in heart and liver of aged CR-treated mice. We further report that KOCR mice were less able to maintain carbohydrate-derived energy production and displayed faster fuel switch to FAO during post-absorption period, leading to a longer fasting state relative to WTCR animals. Despite longer lifespan, altered fuel utilization in KOCR is associated with reduced exercise capacity and spontaneous activity. These results provide an example of the uncoupling of lifespan and aerobic fitness, and new insights into the role of SIRT3 in CR adaptation, fuel utilization, and aging.

State-of-the-art algorithms for HRMC, such as k-GROUSE, perform well if there is modest amount of missing data, but typically fail on instances with large amounts of missing data. We propose a novel mixed integer linear programming formulation for HRMC. The formulation is based on building a set of candidate subspaces and assigning points to selected subspaces. The structure is identical to the classical facility-location problem, with subspaces playing the role of facilities and data points that of customers. We propose a Benders’ decomposition approach for solving the linear programming relaxation of the formulation combined with a column-generation approach for identifying candidate subspaces. The pricing problem to identify a basis matrix is a highly-nonconvex unconstrained nonlinear program that we solve approximately via a gradient-descent method. The integer programming formulation, solved over the candidate subspaces identified by pricing, yields high-quality solutions to the problem. We perform a significant empirical study showing our approach is a significant improvement over state-of-the-art methods for the HRMC problem, especially in the high-missing-data regime.

– community events and co-sponsored seminars that bring together researchers and other partners around relevant data science topics
– regular trainings (including Carpentries workshops) around fundamental data science and computational skills

This collection supports national and state science standards, and creates opportunities for learners to develop their STEAM identity (“Who do I think I am, who can I be, where do I belong?” in context of Science, Technology, Engineering, Arts and Math). Meet the Lab collections integrate into the Discovery Building’s public engagement with science programs, particularly our field trip and summer camp programs.

WID labs involved in the project to date:
Ashton Lab – Nervous System Engineers
Handelsman Lab – Antibiotic Hunters
Schloss Lab – Visual Reasoning Lab – production in progress
Solis-Lemus Lab – production in progress