Biology subjects

Koval, A.

Publications and source records attributed to Koval, A..

5 recordsLinked to original sources

bioRxiv2026

Accurate detection of tumor clonality and ongoing expansion mode from genomic data

Recent evidence shows that despite considerable effort, currently available algorithms for estimating intratumor heterogeneity (ITH) remain limited. We developed DECODE (Deciphering Cancer Origin from DNA Evolution), a novel mutation clustering method that incorporates the impact of sample-specific sequencing coverage and mutation calling biases. On synthetic data, DECODE outperformed existing methods across multiple clonality metrics and accurately detected and characterized the neutral tail in the site frequency spectrum (SFS), which encodes the tumors ongoing expansion mode. In acute myeloid leukemia, accounting for the neutral tail enabled DECODE to yield more parsimonious clonal decompositions that align more closely with known subclonal dynamics that drive relapse. Applied to data from The Cancer Genome Atlas, DECODE not only detected a neutral SFS tail in most samples across tumor types but also uncovered a clinically meaningful link between ITH and survival in low-grade glioma. By jointly inferring clonality and expansion mode, DECODE provides two complementary and prognostically relevant readouts of tumor evolution from single tumor genomic samples.

bioinformatics↗

bioRxiv2026

Defects in CD8+ T cell suppression by Foxp3-ΔE2 expressing regulatory T cells

AbstractRegulatory T cells (Tregs) prevent autoimmunity through suppressive functions largely programmed by the transcription factor FOXP3. Healthy humans express approximately equivalent levels of two major alternatively spliced isoforms of FOXP3: a full-length version containing all coding exons (FOXP3-FL) and a version lacking exon 2 (FOXP3-{Delta}E2). However, sole FOXP3-{Delta}E2 expression causes lethal IPEX syndrome, and the FOXP3-{Delta}E2 isoform is elevated in several autoimmune diseases. These observations strongly suggest defects in suppression by FOXP3-{Delta}E2 Tregs which we investigated here using Foxp3-{Delta}E2 mice. In an influenza virus infection model, Foxp3-{Delta}E2 mice had an increased magnitude of the CD8+ T cell response during acute and memory formation phases of infection. Transcriptomic and chromatin accessibility analyses of homeostatic Foxp3-{Delta}E2 Tregs revealed impaired Treg programming, including reduced expression of inhibitory molecules such as Il2ra and chemokine receptors. Decreased cell surface CD25 expression on Foxp3-{Delta}E2 Tregs was associated with reduced IL-2 responsiveness in Foxp3-{Delta}E2 Tregs and, reciprocally, increased IL-2 responsiveness in CD8+ T cells from Foxp3-{Delta}E2 mice. Additionally, altered chemokine receptor expression resulted in diminished localization of Foxp3-{Delta}E2 Tregs to the T cell zone of the inflamed lymph node. Thus, Treg programming by the Foxp3-{Delta}E2 isoform impairs suppressive function, resulting in failure to restrain CD8+ T cells and aberrant immune responses. One Sentence SummaryFoxp3-{Delta}E2 expressing regulatory T cells have altered cellular programming which impairs their IL-2 sink function and co-localization with conventional T cells during priming, enhancing CD8+ T cell responses.

immunology↗

bioRxiv2023

The DeMixSC deconvolution framework uses single-cell sequencing plus a small benchmark dataset for improved analysis of cell-type ratios in complex tissue samples

Bulk deconvolution with single-cell/nucleus RNA-seq data is critical for understanding heterogeneity in complex biological samples, yet the technological discrepancy across sequencing platforms limits deconvolution accuracy. To address this, we introduce an experimental design to match inter-platform biological signals, hence revealing the technological discrepancy, and then develop a deconvolution framework called DeMixSC using the better-matched, i.e., benchmark, data. Built upon a novel weighted nonnegative least-squares framework, DeMixSC identifies and adjusts genes with high technological discrepancy and aligns the benchmark data with large patient cohorts of matched-tissue-type for large-scale deconvolution. Our results using a benchmark dataset of healthy retinas suggest much-improved deconvolution accuracy. Further analysis of a cohort of 453 patients with age-related macular degeneration supports the broad applicability of DeMixSC. Our findings reveal the impact of technological discrepancy on deconvolution performance and underscore the importance of a well-matched dataset to resolve this challenge. The developed DeMixSC framework is generally applicable for deconvolving large cohorts of disease tissues, and potentially cancer.

bioinformatics↗

bioRxiv2023

Cis-regulatory polymorphism at fiz ecdysone oxidase contributes to polygenic adaptation to malnutrition in Drosophila

We investigate the contribution of a candidate gene, fiz (fezzik), to complex polygenic adaptation to juvenile malnutrition in Drosophila melanogaster. We show that experimental populations adapted during >250 generations of experimental evolution to a nutritionally poor larval diet (Selected populations) evolved several-fold lower fiz expression compared to unselected Control populations. This divergence in fiz expression is mediated by a cis-regulatory polymorphism. This polymorphism, which was originally present in a sample from a natural population in Switzerland, is distinct from a second cis-regulatory SNP previously identified in non-African D. melanogaster populations, implying that two independent cis-regulatory variants promoting high fiz expression segregate in non-African populations. Enzymatic analyses of Fiz protein expressed in E. coli demonstrate that it has ecdysone oxidase activity acting on both ecdysone and 20-hydroxyecdysone. Four of five fiz paralogs annotated to ecdysteroid metabolism also show reduced expression in Selected larvae, suggesting that malnutrition-driven selection favored general downregulation of ecdysone oxidases. Finally, as an independent test of the role of fiz in poor diet adaptation, we show that fiz knockdown by RNAi results in faster larval growth on the poor diet, but at the cost of greatly reduced survival. These results imply that downregulation of fiz in Selected populations was favored because of its role in suppressing growth in response to nutrient shortage. However, fiz downregulation is only adaptive in combination with other changes evolved by Selected populations, such as in nutrient acquisition and metabolism, which ensure that the organism can actually sustain the faster growth promoted by fiz downregulation.

evolutionary biology↗

bioRxiv2023

Ric8 proteins as the neomorphic partners of G alpha o in GNAO1 encephalopathies

GNAO1 mutated in pediatric encephalopathies encodes the major neuronal G-protein Go. Of >40 pathogenic mutations, most are single amino acid substitutions spreading across Go sequence. We perform extensive characterization of Go mutants showing abnormal GTP uptake and hydrolysis, and deficiencies to bind G{beta}{gamma} and RGS19. Plasma membrane localization of Go is decreased for a subset of mutations that leads to epileptic manifestations. Pathogenic mutants massively gain interaction with Ric8A/B proteins, delocalizing them from cytoplasm to Golgi. Being general G-subunit chaperones and binding multiple other proteins, Ric8A/B likely mediate the disease dominance when engaging in neomorphic interactions with pathogenic Go. As the strength of Go-Ric8B interactions correlates with disease severity, our study further identifies an efficient biomarker and predictor for clinical manifestations in GNAO1 encephalopathies. One-Sentence SummaryNeomorphic mutations in Go gain dominant interactions with Ric8A/B, correlating with severity in pediatric encephalopathies.

cell biology↗