Biology subjects

Kuzmin, E.

Publications and source records attributed to Kuzmin, E..

5 recordsLinked to original sources

bioRxiv2025

Integrated Metabolic Complex Genetic Interaction 1 Network of Chromosome 4p Loss in Basal Breast Cancer

Basal breast cancer subtype is enriched for triple-negative breast cancer (TNBC) and exhibits a recurrent large chromosomal deletion in chromosome 4p (chr4p). Chr4p loss is associated with poor survival, evolves early in tumorigenesis and confers on cells a proliferative state. Here, we map the integrated metabolic complex genetic interaction network of chr4p in basal breast cancer to identify targetable vulnerabilities. Differential gene expression analysis of patient derived xenografts and cancer cell models revealed that chr4p loss is associated with changes in cellular energetics and reduction/oxidation balance. Analysis of DepMap pooled genome-wide CRISPR-Cas9 screens identified complex genetic interactions specific to chr4p deletion in basal breast cancer cell models. Functional assays revealed that chr4p loss is associated with disrupted mitochondrial respiratory function and reduced glycolytic capacity, suggesting metabolic rewiring. Increased reactive oxygen species and lipid peroxidation compromised antioxidant defense mechanisms. Ultimately, this study sheds light on targeted therapies for basal breast cancer harboring large chromosomal deletions.

genomics↗

bioRxiv2025

PARPAL: PARalog Protein Redistribution using Abundance and Localization in Yeast Database

Whole-genome duplication (WGD) events are common across various organisms however the retention and evolution of WGD paralogs is not fully understood. Quantitative measure of protein redistribution in response to the deletion of their WGD paralog provides insight into sources of gene retention. Here, we describe PARPAL (PARalog Protein Retribution using Abundance and Localization in Yeast), a web database that houses results of high-content screening and deep learning neural network analysis of the redistribution of 164 proteins reflecting how their subcellular localization and protein abundance change in response to their paralog deletion. We interrogated a total of 82 paralog pairs in two genetic backgrounds for a total of [~]3,500 micrographs of [~]460,000 cells. PARPAL also links to other studies on trigenic interactions, protein-protein interactions and protein abundance. PARPAL is available at https://parpal.c3g-app.sd4h.ca and is a valuable resource for the yeast community interested in understanding the retention and evolution of paralogs and can help researchers to investigate protein dynamics of paralogs in other organisms.

systems biology↗

bioRxiv2023

Single-cell imaging of protein dynamics of paralogs reveals mechanisms of gene retention

Gene duplication is common across the tree of life, including yeast and humans, and contributes to genomic robustness. In this study, we examined changes in the subcellular localization and abundance of proteins in response to the deletion of their paralogs originating from the whole-genome duplication event, which is a largely unexplored mechanism of functional divergence. We performed a systematic single-cell imaging analysis of protein dynamics and screened subcellular redistribution of proteins, capturing their localization and abundance changes, providing insight into forces determining paralog retention. Paralogs showed dependency, whereby proteins required their paralog to maintain their native abundance or localization, more often than compensation. Network feature analysis suggested the importance of functional redundancy and rewiring of protein and genetic interactions underlying redistribution response of paralogs. Translation of non-canonical protein isoform emerged as a novel compensatory mechanism. This study provides new insights into paralog retention and evolutionary forces that shape genomes.

systems biology↗

bioRxiv2023

Evolution of chromosome arm aberrations in breast cancer through genetic network rewiring

The basal breast cancer subtype is enriched for triple-negative breast cancer (TNBC) and displays consistent large chromosomal deletions. Here, we characterize the evolution and maintenance of chromosome 4p (chr4p) loss in basal breast cancer. TCGA data analysis showed recurrent deletion of chr4p in basal breast cancer. Phylogenetic analysis of a unique panel of 23 primary tumor/patient-derived xenograft basal breast cancers revealed early evolution of chr4p deletion. Mechanistically we show that Chr4p loss is associated with enhanced proliferation. Gene function studies identified an unknown gene, C4orf19, within chr4p, which suppressed proliferation when overexpressed and is a novel member of a PDCD10-GCKIII kinase module, we name as PGCA1. Genome-wide pooled overexpression screens using a barcoded library of human open reading frames, identified chromosomal regions, including chr4p, that suppress proliferation when overexpressed in a context-dependent manner implicating network interactions. Together this sheds light on the early emergence of complex aneuploid karyotypes involving chr4p and adaptive landscapes shaping breast cancer genomes.

genomics↗

bioRxiv2021

Correspondence between gene expression and neurotransmitter receptor and transporter density in the human brain

Neurotransmitter receptors modulate the signaling between neurons. Thus, neurotransmitter receptors and transporters play a key role in shaping brain function. Due to the lack of comprehensive neurotransmitter receptor/transporter density datasets, microarray gene expression is often used as a proxy for receptor densities. In the present report, we comprehensively test the expression-density association for a total of 27 neurotransmitter receptors, receptor binding-sites, and transporters across 9 different neurotransmitter systems, using both PET and autoradiography imaging modalities. We find poor spatial correspondences between gene expression and density for all neurotransmitter receptors and transporters except four single-protein metabotropic receptors (5-HT1A, D2, CB1, and MOR). These expression-density associations are related to population variance and change across different classes of laminar differentiation. Altogether, we recommend using direct measures of receptor and transporter density when relating neurotransmitter systems to brain structure and function.

neuroscience↗