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Scher, Y.

Publications and source records attributed to Scher, Y..

3 recordsLinked to original sources

Leveraging Twin Information for Inference of Gene Regulatory Networks

Gene regulatory networks (GRNs) underlie maintenance of cellular phenotypes and responses to stimuli. Modern single-cell profiling methods offer high-throughput datasets to infer GRNs en masse but do not capture dynamic information. Cell-state heterogeneity further confounds correlation-based inference approaches. We addressed these challenges with TwINFER, a conceptual framework leveraging information from recently divided sister cells, or "twins," identifiable via recently developed barcoding techniques. We show that twin information discriminates regulatory from non-regulatory correlations and resolves interaction direction and type (activation/repression). We performed a diverse set of simulations, covering common network motifs and large-scale networks, where TwINFER outperforms state-of-the-art inference capabilities. Crucially, TwINFER resolved the commonly observed false positives in fan-out and feed-forward loop motifs where most methods perform poorly. Lastly, we applied TwINFER to a lineage-barcoded hematopoiesis dataset which refined the network inference, flagged multi-state genes, and determined causal relations. Our work exploits cellular twins as untapped information, readily complementing existing inference approaches.

systems biology↗

Measurements and simulations of transmembrane water exchange by diffusion NMR methods: From yeast cells to optic nerve ex vivo

Non-invasive measurement of exchange is paramount in different fields, ranging from material to biological sciences. Unaccounted exchange may even blur micro-structural or other characteristics of multi compartmental systems studied by MR methods. Despite the growing interest in diffusion-exchange studies of complex systems, comparative studies remain scarce. Most existing investigations have applied different diffusion MR methods to different biological samples under varying experimental conditions, making direct comparisons difficult. Moreover, the lack of a gold standard for exchange rate measurements further complicates efforts to validate and interpret results. To address these challenges, we employed two diffusion NMR-based methods--the constant-gradient pulsed field gradient (CG-PFG) and the recently introduced filter-exchange NMR spectroscopy (FEXSY)--to investigate apparent water exchange in yeast cells and optic nerves, both before and after fixation. We first evaluated the effect of the q-values on the extracted indices and then evaluated the repeatability and reproducibility of the measurements. The CG-PFG and FEXSY experiments were collected on the same sample to allow comparison of the results. The intracellular mean residence times (MRTs) ({tau}i) extracted from the log-linear fit of the CG-PFG NMR experiments were found to be 554 {+/-} 6 ms and 337 {+/-} 10 ms for yeast cells before and after fixation, respectively. The respective{tau} i values extracted from the FEXSY experiments before and after fixation were found to be 368 {+/-} 14 ms and 146 {+/-} 24 ms, respectively. Despite the difference in absolute values of MRTs, the same qualitative behavior is observed in the two methodologies, and both could be analyzed using the bi-compartmental Karger model. The same methodologies were then used to study exchange in the more complex porcine optic nerves. There, the bi-compartmental Karger model analysis is shown to be inadequate. Extensive Monte Carlo simulations are used to narrow down on the most possible explanation, suggesting that optic nerves are multi-compartmental systems where not all spins are free to undergo exchange. Supporting theoretical calculations point to the existence of at least one additional non-exchanging restricted compartment. Thus, a tri-compartmental model is derived and used to analyze the data. The new model fits the data significantly better and results in dramatically different exchange rates when used on white matter (WM) data: CG-PFG experiments were found to be 730 {+/-} 40 ms and 803 {+/-} 16 ms for optic nerves before and after fixation, respectively. The respective{tau} i values extracted from the FEXSY experiments before and after fixation were found to be 530 {+/-} 125 ms and 387 {+/-} 104 ms, respectively. These values are considerably lower than the values previously reported. Finally, we use simulations to show that the quantitative discrepancy between CG-PFG and FEXSY can be attributed, at least partially, to the difference in T2 values between the intra- and extracellular compartments. We thus encourage the pairing of exchange and spin-spin relaxation measurements in future studies. We end with a discussion on the current state of the diffusion-exchange, and in an attempt to put a spotlight on essential corner stones that are still missing despite the great advance of recent years: experimental standardization, method comparison, and adequate modeling.

neuroscience↗

Optical Genome and Epigenome Mapping of Clear Cell Renal Cell Carcinoma

Cancer cells display complex genomic aberrations that include large-scale genetic rearrangements and epigenetic modulation that are not easily characterized by short-read sequencing. We present a method for simultaneous profiling of long-range genetic/epigenetic changes in matched cancer samples. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer. Most ccRCC cases demonstrate somatic genomic alterations involving the short arm of chromosome 3 (3p), most often targeting the von Hippel-Lindau (VHL) gene. Aiming to identify somatic alterations that characterize early stage ccRCC, we performed comprehensive genetic, cytogenetic and epigenetic analyses comparing ccRCC tumor to adjacent non-tumorous tissue. Optical genome mapping identified genomic aberrations such as structural and copy number variations, complementing exome-sequencing results. Single-molecule methylome and hydroxymethylome mapping revealed multiple differential regions, some of them known to be associated with ccRCC pathogenesis. Among them, metabolic pathways were significantly enriched. Moreover, significant global epigenetic differences were detected between the tumor and the adjacent non-tumorous tissue, and a correlation between epigenetic signals and gene expression was found. This is the first reported comparison of a human tumor and a matched tissue by optical genome/epigenome mapping, revealing well-established and novel somatic aberrations.

genomics↗