Biology subjects

Young, C. L.

Publications and source records attributed to Young, C. L..

4 recordsLinked to original sources

bioRxiv2024

Comparative evaluation of cell-based assay technologies for scoring drug-induced condensation of SARS-CoV-2 nucleocapsid protein

Protein-nucleic acid phase separation has been implicated in many diseases such as viral infections, neurodegeneration, and cancer. There is great interest in identifying condensate modulators (CMODs), which are small molecules that alter the dynamics and functions of phase-separated condensates, as a potential therapeutic modality. Most CMODs were identified in cellular high-content screens (HCS) where micron-scale condensates were characterized by fluorescence microscopy. These approaches lack information on protein dynamics, are limited by microscope resolution, and are insensitive to subtle condensation phenotypes missed by overfit analysis pipelines. Here, we evaluate two alternative cell-based assays: high-throughput single molecule tracking (htSMT) and proximity-based condensate biosensors using NanoBIT (split luciferase) and NanoBRET (bioluminescence resonance energy transfer) technologies. We applied these methods to evaluate condensation of the SARS-CoV-2 nucleocapsid (N) protein under GSK3 inhibitor treatment, which we had previously identified in our HCS campaign to induce condensation with well-defined structure-activity relationships (SAR). Using htSMT, we observed robust changes in N protein diffusion as early as 3 hours post GSK3 inhibition. Proximity-based N biosensors also reliably reported on condensation, enabling the rapid assaying of large compound libraries with a readout independent of imaging. Both htSMT and proximity-based biosensors performed well in a screening format and provided information on CMOD activity that was complementary to HCS. We expect that this expanded toolkit for interrogating phase-separated proteins will accelerate the identification of CMODs for important therapeutic targets.

molecular biology↗

bioRxiv2023

Rising daptomycin resistance in Enterococcus faecium across a hospital system occurred via rampant recurrent evolution and occasional transmission between patients.

The rise of antibiotic resistance in a population involves two distinct processes: the origin of resistance and its spread. Here we study the contribution of both processes to the increase in daptomycin resistance in Enterococcus faecium in a hospital system. This case-control genomic study includes whole-genome sequencing of 82 isolates obtained from 24 case patients with clinically determined daptomycin-resistance and 24 controls. Among the case patients, the first isolate was resistant in 15 patients (R patients) while in the remaining nine the first isolate was susceptible but was followed by one or more resistant isolates (SR patients). Mutations in a set of candidate daptomycin resistance genes were compared within and between all patients. Additionally, among closely related isolates, mutations were identified across the entire assembled genome. Daptomycin resistance evolved separately multiple times and there was no phylogenetic clustering of the R or the SR groups. Six of the nine SR pairs gained mutations in previously identified candidate loci for daptomycin resistance, with the major cardiolipin synthase (clsA) being mutated most frequently. The hospital-wide increases in daptomycin resistance in E. faecium was the result of recurrent evolution taking multiple evolutionary pathways and occasional transmission of resistant isolates between patients. ImportanceAntimicrobial resistance in healthcare settings presents an important challenge, because infections with resistant organisms are associated with higher cost, longer hospital stays and worse outcomes for patients. However, it can be difficult to identify the factors driving the increase in resistance, specifically the relative contribution of resistance arising anew through mutation versus the transmission of resistant organisms from patient to patient. We study a hospital where resistance to daptomycin was increasing among Enterococcus faecium, an important hospital pathogen. We find the increase in resistance was the results of resistance arising many times independently. We also identify occasional transmission of daptomycin resistant organisms. Thus, control of daptomycin resistance in E. faecium may require interventions that both slow the emergence of resistance within patients and slow its spread. This work sheds light on the complex population dynamics leading to antibiotic resistance in hospitals.

evolutionary biology↗

bioRxiv2022

The molecular architecture of cell cycle arrest

The cellular decision governing the transition between proliferative and arrested states is crucial to the development and function of every tissue. While the molecular mechanisms that regulate the proliferative cell cycle are well established, we know comparatively little about what happens to cells as they diverge into cell cycle arrest. We performed hyperplexed imaging of 49 cell cycle effectors to obtain a map of the molecular architecture that governs cell cycle exit and progression into reversible ("quiescent") and irreversible ("senescent") arrest states. Using this map, we found multiple points of divergence from the proliferative cell cycle; identified stress-specific states of arrest; and resolved the molecular mechanisms governing these fate decisions, which we validated by single-cell, time-lapse imaging. Notably, we found that cells can exit into senescence from either G1 or G2; however, both subpopulations converge onto a single senescent state with a G1-like molecular signature. Cells can escape from this "irreversible" arrest state through the upregulation of G1 cyclins. This comprehensive map provides a first glimpse of the overall organization of cell proliferation and arrest.

cell biology↗

bioRxiv2021

The structure of the human cell cycle

The human cell cycle is conventionally depicted as a five-phase model consisting of four proliferative phases (G1, S, G2, M) and a single state of arrest (G0). However, recent studies show that individual cells can take different paths through the cell cycle and exit into distinct arrest states, thus necessitating an update to the canonical model. We combined time lapse microscopy, highly multiplexed single cell imaging and manifold learning to determine the underlying "structure" of the human cell cycle under multiple growth and arrest conditions. By visualizing the cell cycle as a complete biological process, we identified multiple points of divergence from the proliferative cell cycle into distinct states of arrest, revealing multiple mechanisms of cell cycle exit and re-entry and the molecular routes to senescence, endoreduplication and polyploidy. These findings enable the visualization and comparison of alternative cell cycles in development and disease. One-sentence summaryA systems-level view of single-cell states reveals the underlying architecture of the human cell cycle

cell biology↗