Biology subjects

Wollman, R.

Publications and source records attributed to Wollman, R..

3 recordsLinked to original sources

bioRxiv2019

Loci specific epigenetic drug sensitivity

Therapeutic targeting of epigenetic modulators offers a novel approach to the treatment of several diseases including cancer, heart diseases and AIDS. The cellular consequences of chemical compounds that target epigenetic regulators (epi-drugs) are complex. Epi-drugs affect global cellular phenotypes and cause local changes to gene expression due to alteration of a gene chromatin environment. Despite increasing use in the clinic, the mechanisms responsible for cellular changes are unclear. Specifically, to what degree the effects are a result of cell-wide changes or disease related locus specific effects is unknown. Here we developed a platform to systematically and simultaneously investigate the sensitivity of epi-drugs at hundreds of genomic locations by combining DNA barcoding, unique split-pool encoding and single cell expression measurements. Internal controls are used to isolate locus specific effects separately from any global consequences these drugs have. Using this platform we discovered wide-spread loci specific sensitivities to epi-drugs for three distinct epi-drugs that target histone deacetylase, DNA methylation and bromodomain proteins. By leveraging ENCODE data on chromatin modification, we identified features of chromatin environments that are most likely to be affected by epi-drugs. The measurements of loci specific epi-drugs sensitivities will pave the way to the development of targeted therapy for personalized medicine.

genomics↗

bioRxiv2019

Mammalian gene expression variability is explained by underlying cell state

Gene expression variability in mammalian systems plays an important role in physiological and pathophysiological conditions. This variability can come from differential regulation related to cell state (extrinsic) and allele-specific transcriptional bursting (intrinsic). Yet, the relative contribution of these two distinct sources is unknown. Here we exploit the qualitative difference in the patterns of covariance between these two sources to quantify their relative contributions to expression variance in mammalian cells. Using multiplexed error robust RNA fluorescent in situ hybridization (MERFISH) we measured the multivariate gene expression distribution of 150 genes related to Ca2+ signaling coupled with the dynamic Ca2+ response of live cells to ATP. We show that after controlling for cellular phenotypic states such as size, cell cycle stage, and Ca2+ response to ATP, the remaining variability is effectively at the Poisson limit for most genes. These findings demonstrate that the majority of expression variability results from cell state differences and that the contribution of transcriptional bursting is relatively minimal.

systems biology↗

bioRxiv2019

Optimal decoding of NFkB signaling dynamics

The encoder/decoder paradigm suggests that signaling networks transform information about the extracellular environment into specific signaling patterns that are then read by downstream effectors to control cellular behavior. Previous work used information theoretical tools to analyze the fidelity of encoding using dynamic signaling patterns. However, as the overall fidelity depends on both encoding and decoding, it is important to consider information loss during signal decoding. Here we used NFkB signaling as a model to understand the accuracy of signal decoding. Using a detailed mathematical model we simulated realistic NFkB signaling patterns with different degrees of variability. The NFkB patterns were used as an input to a simple gene expression model. Analysis of information transmission between ligand and NFkB and ligand and gene expression allow us to determine information loss in both encoding and decoding steps. Information loss could occur due to biochemical noise or due to lack of specificity in decoding response. We found that noise free decoding has very little information loss suggesting that decoding through gene expression can preserve specificity in NFkB patterns. As expected, information transmission through a noisy decoder suffers from information loss. Interestingly, this effect can be mitigated by a specific choice of decoding parameters that can substantially reduce information loss due to biochemical noise during signal decoding. Overall our results show that optimal decoding of dynamic patterns can preserve ligand specificity to maximize the accuracy of cellular response to environmental cues.\n\nSynopsisThe fidelity of signal transduction depends on the accurate encoding of ligand information in specific signaling patterns and the reliable decoding of these patterns by downstream gene expression machinery. We present an analysis of the accuracy of decoding processes in the case of the transcription factor NFkB. We show that noiseless decoding can preserve ligand identity with minimal information loss. Noisy decoding does result in information loss, an effect that can be largely mitigated by choice of optimal decoding parameter values. O_LIDecoding of dynamic signaling patterns by a simple gene model can preserve most of the information about ligand identity.\nC_LIO_LINoisy decoding will result in information loss, but this effect can be mitigated by the optimal choice of decoding parameters.\nC_LIO_LIImprovement in decoding is a result of decreased variability in gene expression patterns.\nC_LI

systems biology↗