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Mistry, B. A.

Publications and source records attributed to Mistry, B. A..

2 recordsLinked to original sources

Xist-seeded nucleation sites form local concentration gradients of silencing proteins to inactivate the X-chromosome

The long non-coding RNA Xist exploits numerous effector proteins to progressively induce gene silencing across the X chromosome and form the inactive X (Xi)-compartment. The mechanism underlying formation of the chromosome-wide Xi-compartment is poorly understood. Here, we find that formation of the Xi-compartment is induced by [~]50 locally confined granules, where two Xist RNA molecules nucleate supra-molecular complexes (SMCs) of interacting proteins. Xist-SMCs are transient structures that concentrate rapidly recycling proteins in the X by increasing protein binding affinity. We find that gene silencing originates at Xist-SMCs and propagates across the entire chromosome over time, achieved by Polycomb-mediated coalescence of chromatin regions and aggregation, via its intrinsically disordered domains, of the critical silencing factor SPEN. Our results suggest a new model for X chromosome inactivation, in which Xist RNA induces macromolecular crowding of heterochromatinizing proteins near distinct sites which ultimately increases their density throughout the chromosome. This mechanism enables deterministic gene silencing without the need for Xist ribonucleoprotein complex-chromatin interactions at each target gene.

cell biology↗

The Effects of Statistical Multiplicity of Infection on Virus Quantification and Infectivity Assays

Many biological assays are employed in virology to quantify parameters of interest. Two such classes of assays, virus quantification assays (VQA) and infectivity assays (IA), aim to estimate the number of viruses present in a solution, and the ability of a viral strain to successfully infect a host cell, respectively. VQAs operate at extremely dilute concentrations and results can be subject to stochastic variability in virus-cell interactions. At the other extreme, high viral particle concentrations are used in IAs, resulting in large numbers of viruses infecting each cell, enough for measurable change in total transcription activity. Furthermore, host cells can be infected at any concentration regime by multiple particles, resulting in a statistical multiplicity of infection (SMOI) and yielding potentially significant variability in the assay signal and parameter estimates. We develop probabilistic models for SMOI at low and high viral particle concentration limits and apply them to the plaque (VQA), endpoint dilution (VQA), and luciferase reporter (IA) assays. A web-based tool implementing our models and analysis is also developed and presented. We test our proposed new methods for inferring experimental parameters from data using numerical simulations and show improvement on existing procedures in all limits.

biophysics↗