Biology subjects

Hassan, A. Z.

Publications and source records attributed to Hassan, A. Z..

7 recordsLinked to original sources

bioRxiv2026

Expanding TheCellMap.org to visualize a genome-scale genetic interaction network for a human cell line

Genetic interaction networks map functional connections between genes and their corresponding pathways and complexes. We previously developed TheCellMap.org as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) analysis in the budding yeast, Saccharomyces cerevisiae. We have expanded TheCellMap.org to include ~89,000 quantitative genetic interactions identified from genome-scale CRISPR-based analysis of ~4 million human gene pairs in the haploid cell line, HAP1. TheCellMap.org enables users to readily access, visualize and explore human HAP1 genetic interactions, as well as to extract and reorganize sub-networks, applying data-driven network layouts in an intuitive and interactive manner.

systems biology↗

bioRxiv2025

A global genetic interaction map of a human cell reveals conserved principles of genetic networks

We generated a genome-scale, genetic interaction network from the analysis of more than 4 million double mutants in the haploid human cell line, HAP1. The network maps [~]90,000 genetic interactions, including thousands of extreme synthetic lethal and genetic suppression interactions. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes, pathways, biological processes, and cellular compartments. Comparative analyses showed that general principles of genetic networks are conserved from yeast to human cells. A genetic interaction network mapped in a single genetic background complements the DepMap gene co-essentiality network, recapitulating many of the same biological connections and also capturing unique functional information to reveal roles of uncharacterized genes and molecular determinants of specific cancer cell line genetic dependencies.

systems biology↗

bioRxiv2025

Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens

Genetic interaction (GI) networks in model organisms have revealed how combinations of genome variants can impact phenotypes. To advance efforts toward a reference human GI network, we developed the quantitative Genetic Interaction (qGI) score, a method for precise GI measurement from genome-wide CRISPR-Cas9 screens in different query mutants constructed in a single human cell line. We found surprising prevalent systematic variation unrelated to GIs in CRISPR screen data, including both genomically linked effects and functionally coherent covariation. Leveraging [~]40 control screens in wild-type cells and half a billion differential fitness effect measurements, we developed a pipeline for CRISPR screen data processing and normalization to correct these artifacts and measure accurate, quantitative GIs. We also comprehensively characterized GI reproducibility by characterizing 4 - 5 biological replicates for [~]125,000 unique gene pairs. The qGI framework enables systematic identification of human GIs and provides broadly applicable strategies for analyzing context-specific CRISPR screen data.

bioinformatics↗

bioRxiv2024

Inhibition of the RNA Regulator HuR mitigates spinal cord injury by potently suppressing post-injury neuroinflammation

BackgroundNeuroinflammation plays a significant role in promoting secondary tissue injury after spinal cord trauma. Within minutes after spinal cord injury (SCI), microglia and astrocytes become activated and produce inflammatory mediators such as TNF-, IL-6, iNOS and COX-2 which induce tissue injury through cytotoxicity, vascular hyperpermeability, and secondary ischemia. The inflammatory cascade is amplified by chemokines such as CCL2 and CXCL1 that promote recruitment of peripheral inflammatory cells into the injured spinal cord. HuR is a key post-transcriptional RNA regulator that controls glial expression of many pro-inflammatory factors by binding to adenylate- and uridylate-rich elements in 3 untranslated regions of the mRNA. SRI-42127 is a small molecule inhibitor that blocks HuR nucleocytoplasmic translocation, a process critical for its regulatory function. The goal of this study was to assess the potential of SRI-42127 for suppressing neuroinflammation after SCI and improving functional outcome. MethodsAdult female mice underwent a contusion injury at the T10 level. SRI-42127 or vehicle was administered intraperitoneally starting 1 h after injury and up to 5 days. Locomotor function was assessed by open field testing, balance beam and rotarod. Immunohistochemistry was used to assess lesion size, neuronal loss, myelin sparing, microglial activation and HuR localization. Molecular analyses of spinal cord and peripheral tissues for expression of inflammatory mediators included qPCR, immunohistochemistry, ELISA, or western blot. Post-SCI pain was assessed by the mouse grimace scale. ResultsSRI-42127 significantly attenuated loss of locomotor function and post-SCI pain. Histologic correlates to these beneficial effects included reduced lesion size, neuronal loss, and an increase in myelin sparing. There was reduced microglial activation at the epicenter with concomitant attenuation of HuR nucleocytoplasmic translocation. Molecular analysis revealed a striking reduction of pro-inflammatory mediators at the epicenter including IL-6, MMP-12, IL-1{beta}, TNF-, iNOS, COX-2, and chemokines CCL2, CXCL1, and CXCL2. Suppression of inflammatory responses extended peripherally including serum, liver, and spleen. ConclusionTargeting HuR after SCI is a viable therapeutic approach for suppressing neuroinflammatory responses after tissue injury and improving functional outcome.

neuroscience↗

bioRxiv2024

The PRC2.1 Subcomplex Opposes G1 Progression through Regulation of CCND1 and CCND2

Progression through the G1 phase of the cell cycle is the most highly regulated step in cellular division. We employed a chemogenetic approach to discover novel cellular networks that regulate cell cycle progression. This approach uncovered functional clusters of genes that altered sensitivity of cells to inhibitors of the G1/S transition. Mutation of components of the Polycomb Repressor Complex 2 rescued proliferation inhibition caused by the CDK4/6 inhibitor palbociclib, but not to inhibitors of S phase or mitosis. In addition to its core catalytic subunits, mutation of the PRC2.1 accessory protein MTF2, but not the PRC2.2 protein JARID2, rendered cells resistant to palbociclib treatment. We found that PRC2.1 (MTF2), but not PRC2.2 (JARID2), was critical for promoting H3K27me3 deposition at CpG islands genome-wide and in promoters. This included the CpG islands in the promoter of the CDK4/6 cyclins CCND1 and CCND2, and loss of MTF2 lead to upregulation of both CCND1 and CCND2. Our results demonstrate a role for PRC2.1, but not PRC2.2, in antagonizing G1 progression in a diversity of cell linages, including CML, breast cancer and immortalized cell lines.

molecular biology↗

bioRxiv2023

A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds

Current approaches to define chemical-genetic interactions (CGIs) in human cell lines are resource-intensive. We designed a scalable chemical-genetic screen platform by generating a DNA damage response (DDR)-focused custom sgRNA library. We performed five proof-of-principle compound screens and found that the compounds known modes-of-action (MoA) were enriched among the compounds CGIs. These scalable screens recapitulated expected CGIs at a comparable signal-to-noise ratio (SNR) relative to genome-wide screens. Furthermore, time-resolved CGIs, captured by sequencing screens at various time points, suggested an unexpected, late time point interstrand-crosslinking (ICL) repair pathway response to camptothecin-induced DNA damage. Our approach can facilitate screening compounds at scale and produce biologically informative CGI profiles.

systems biology↗

bioRxiv2023

Dimensionality reduction methods for extracting functional networks from large-scale CRISPR screens

CRISPR-Cas9 screens facilitate the discovery of gene functional relationships and phenotype-specific dependencies. The Cancer Dependency Map (DepMap) is the largest compendium of whole-genome CRISPR screens aimed at identifying cancer-specific genetic dependencies across human cell lines. A mitochondria-associated bias has been previously reported to mask signals for genes involved in other functions, and thus, methods for normalizing this dominant signal to improve co-essentiality networks are of interest. In this study, we explore three unsupervised dimensionality reduction methods - autoencoders, robust, and classical principal component analyses (PCA) - for normalizing the DepMap to improve functional networks extracted from these data. We propose a novel "onion" normalization technique to combine several normalized data layers into a single network. Benchmarking analyses reveal that robust PCA combined with onion normalization outperforms existing methods for normalizing the DepMap. Our work demonstrates the value of removing low-dimensional signals from the DepMap before constructing functional gene networks and provides generalizable dimensionality reduction-based normalization tools.

bioinformatics↗