Biology subjects

Purohit, S.

Publications and source records attributed to Purohit, S..

3 recordsLinked to original sources

bioRxiv2026

Reelin coordinates neuronal positioning and Müller glia scaffold maturation during retinal development

Reelin is a secreted extracellular matrix protein that regulates neuronal migration and layer formation in the developing brain, yet its role in retinal development remains incompletely defined. Here, we investigated Reelin function in retinal lamination using wild-type and Reeler (Reln-/-) mice, combining stage-resolved RNA in situ hybridization, immunohistochemistry, and single-nucleus RNA sequencing. We show that Reln is dynamically expressed in ganglion cell layer and inner nuclear layer neurons during retinal development and persists in discrete adult neuronal populations. Loss of Reelin leads to widespread defects in retinal organization affecting both neurons and Muller glia. In Reln-/- retinas, Muller glia exhibit reduced Glul positive extensions, indicating impaired glial scaffold maturation. Early-born neuronal populations are also disrupted, with altered spatial organization markers associated with retinal ganglion cell differentiation within the ganglion cell layer at postnatal day 9. Horizontal cells are significantly reduced with dorsal-predominant vulnerability, while cone photoreceptors are generated in normal numbers but show incomplete positioning within the outer nuclear layer. Together, these findings identify Reelin as a key regulator of retinal lamination that coordinates neuronal positioning with Muller glia morphogenesis, extending its canonical role in brain development to the vertebrate retina.

developmental biology↗

bioRxiv2026

ChatGEM: An Agentic Architecture Enabling Interactive Simulation of Genome-Scale Metabolic Models

Genome-scale metabolic models (GEMs) are powerful tools for predicting cellular phenotypes and guiding microbial strain engineering, yet broad adoption remains challenging due to the computational expertise required. To overcome that, we present ChatGEM, an agentic platform that enables interactive GEM simulation through natural language. Built on the multi-agent ADEPT framework, ChatGEM integrates COBRApy within a retrieval-augmented generation (RAG) architecture that coordinates code generation and execution through specialized agents. Benchmarking across three tasks of increasing complexity showed that RAG-enabled code generation improved the mean overall performance score from 2.63 to 4.20 while reducing the execution time significantly starting from routine to complex tasks. Application of ChatGEM using an enzyme-constrained GEM (ecGEM) for four engineered Pseudomonas putida KT2440 strains identified the constitutive strain as the optimal chassis for succinate overproduction using a succinate leakage index - a prediction observed experimentally. Therefore, ChatGEM democratizes metabolic modeling by enabling researchers without computational expertise to perform sophisticated GEM-based analyses through natural language, and, hence, accelerating scientific discovery.

systems biology↗

bioRxiv2025

Sources of non-uniform coverage in short-read RNA-Seq data

The origin of several normal cellular functions and related abnormalities can be traced back to RNA splicing. As such, RNA splicing is currently the focus of a vast array of studies. To quantify the transcriptome, short-read RNA-Seq remains the standard assay. The primary technical artifact of RNA-Seq library prep, which severely interferes with analysis, is extreme non-uniformity in coverage across transcripts. This non-uniformity is present in both bulk and single-cell RNA-Seq and is observed even when the sample contains only full-length transcripts. This issue dramatically affects the accuracy of isoform-level quantification of multi-isoform genes. Understanding the sources of this non-uniformity is critical to developing improved protocols and analysis methods. Here, we explore eight potential sources of non-uniformity. We demonstrate that it cannot be explained by one factor alone. We performed targeted experiments to investigate the effect of fragment length, PCR ramp rate, and ribosomal depletion. We assessed existing data sets with varying sample quality, PCR cycle number, reverse transcriptase, and technical or biological replicates. We found evidence that interference of reverse transcription by secondary structure is unlikely to be the major contributing factor, that rRNA pull-down methods do not cause non-uniformity, that PCR ramp rate does not substantially impact non-uniformity, and that shorter fragments do not reduce non-uniformity. All these findings contradict prior publications or recommendations.

bioinformatics↗