Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. Using multiple tissues from a single donor enabled identification of the clonal distribution of T cells between tissues, identification of the tissue-specific mutation rate in B cells, and analysis of the cell cycle state and proliferative potential of shared cell types across tissues. Cell type–specific RNA splicing was discovered and analyzed across tissues within an individual.

Single cell RNA sequencing (scRNA-seq) enables detailed examination of a cell's underlying regulatory networks and the molecular factors contributing to its identity. We developed scRFE (single-cell identity definition using random forests and recursive feature elimination, pronounced 'surf') with the goal of easily generating interpretable gene lists that can accurately distinguish observations (single-cells) by their features(genes) given a class of interest. scRFE is an algorithm implemented as a Python package that combines the classical random forest method with recursive feature elimination and cross validation to find the features necessary and sufficient to classify cells in a single-cell RNA-seq dataset by ranking feature importance. The package is compatible with Scanpy, enabling a seamless integration into any single-cell data analysis workflow that aims at identifying minimal transcriptional programs relevant to describing metadata features of the dataset. We applied scRFE to the Tabula Muris Senis and reproduced commonly known aging patterns and transcription factor reprogramming protocols, highlighting the biological value of scRFE's learned features.

There are approximately 415 million people with Diabetes Mellitus worldwide and there exists a growing need for an ultrastable, heat resistant formulation of rapid‐acting insulin to treat the millions of people who live in developing countries where temperatures routinely exceed 45ºC. The heat resistance and stability of insulin is especially crucial due to the fact that insulin degrades ten times faster for every 10°C increase in temperature above 25°C. Several rapid‐acting insulin analogs have been created, though most do not last longer than 30 days and are reliant on the expensive cold chain delivery system of insulin analogs. This is due to chemical and physical degradation by way of deamidation, transamidation and cross‐beta assembly of linear polymers, or fibrillation. Rapid‐acting analogs must also combat the formation of the inactive hexameric formulation of insulin due to the presence of zinc and an excess of hydrogen ions. A single‐chain insulin analog has been created called SCI‐57 which consists of a glycine rich peptide (6 residues in length) that connects the A and B chains of the insulin analog. Adding a peptide tether will restrict splaying of the A and B chains, thus decreasing the risk of fibrillation even under high temperatures. To ensure that the analog is rapid‐acting and will not form storage hexamers, SCI‐57 has replaced ThrA8 with His to omit an unfavorable beta‐branched amino acid and HisB10 with Asp to create a more favorable relationship with the electrostatic dipole of the B‐chain alpha helix. Replacing HisB10 with Asp also blocks zinc binding, furthermore ensuring that the analog in its active, monomeric state. Both of these actions triple the activity of two‐chain analogs which will also benefit SCI‐57 by allowing it to bind quickly to the insulin receptor. Furthermore, SCI‐57 is much more resistant to fibrillation under high temperatures than previous analogs and maintains insulin receptor affinity as well as efficiency. The Nueva School MSOE Center for Biomolecular Modeling MAPS Team used 3‐D modeling and printing technology to examine structure‐function relationships of SCI‐57.Primary Citation:Hua, Qing‐xin, et al. “Design of an Active Ultrastable Single‐Chain Insulin Analog: SYNTHESIS, STRUCTURE, AND THERAPEUTIC IMPLICATIONS.” The Journal of Biological Chemistry, American Society for Biochemistry and Molecular Biology, 23 May 2008This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Major Depressive Disorder (MDD) is the leading cause of disability worldwide. One of MDD's most troubling symptoms is the loss of reward firing, or anhedonia. Current publications indicate that MTCH‐2, a gene associated with mitochondrial transport, is related to a decrease in firing rates in the hippocampus of mice. Additionally, a GWAS reported a link between MTCH‐2 and neuroticism in humans. Consequently, we hypothesize that a MTCH‐2 related decrease in firing rates in the nucleus accumbens could potentially play a role in the development of depressive symptoms.The C. Elegans MTCH‐1 protein shows a 87% homology to the human MTCH‐2 protein. Here, we examine the relationship between the MTCH‐1 gene and C. Elegans reward firing. Because C. Elegans reward firing levels have been associated with changes in speed change fluidity in past studies, we measure C. Elegans motility as a proxy for reward firing. In this study, we compare motility and gene expression in MTCH‐1 deficient worms and wt worms and further examine MTCH‐1 knockdown to control motility. Together, these data points may indicate a role of MTCH‐2 in depression.Support or Funding InformationThe Nueva SchoolThis abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.