Biology subjects

Suresh, I.

Publications and source records attributed to Suresh, I..

5 recordsLinked to original sources

bioRxiv2026

A high aneuploidy supply rate underlies parallel evolution of fluconazole resistance in Saccharomyces cerevisiae

Copy number variants (CNVs) of ERG11 play a major role in acquisition of resistance to the commonly used azole family of antifungal drugs in many pathogenic yeast species. However, the conditions in which these CNVs arise, and the factors that underlie their emergence and selection in evolving populations, remain poorly understood. Here, we studied the dynamics of de novo CNVs at the ERG11 locus in Saccharomyces cerevisiae to determine the effect of different drug concentrations and temperatures on CNV formation and selection. We found that ERG11 CNVs emerge reproducibly at fluconazole concentrations around the IC50. With increases in temperature, CNVs emerged more rapidly and had a higher tendency towards fixation. Evolved ERG11 CNV strains provided a significant growth advantage across a narrow range of fluconazole concentrations near the IC50 of the wildtype strain. Whole genome sequencing of 35 independent evolved lineages revealed that all ERG11 CNVs are aneuploidies of chromosome VIII. Relocation of ERG11 to chromosome XI also results exclusively in selection for chromosome XI aneuploids. We show that fluconazole does not increase the frequency at which aneuploids are generated. Therefore, we conclude that a high spontaneous rate of aneuploidy formation underlies recurrent acquisition of resistance to fluconazole in a temperature and drug concentration dependent manner. Author SummaryCopy number variations (CNV), defined as duplications or deletions of genomic regions, are pervasive throughout all forms of life. Although CNVs can provide a route toward rapid adaptation, they can also be associated with high fitness costs. In pathogenic yeast species, CNVs with diverse genetic structures are known to play a role in antifungal drug resistance. However, the conditions that favor CNV formation and selection are unclear. We applied a fluorescent CNV reporter system to track newly formed CNVs and found that they arise reproducibly at a narrow range of drug concentrations, and that increases in temperature generally lead to more rapid emergence of CNVs. DNA sequencing revealed that the evolved CNVs contained duplications of the entire chromosome, rather than just the region surrounding the gene under selection. Thus, aneuploidy - gain or loss of an entire chromosome - is a mechanism for rapid evolution of drug resistance, potentially without the fitness costs thought to be associated with this mechanism.

evolutionary biology↗

bioRxiv2025

A Conserved Metabolic Network Regulates Titan Cell Formation in Cryptococcus neoformans

Cryptococcus neoformans is an opportunistic fungal pathogen that causes pulmonary infections and life-threatening meningoencephalitis in immunocompromised individuals. In addition to the polysaccharide capsule and melanin, titan cell formation is a key virulence trait that promotes immune evasion and disease progression. Despite the established role of titan cells in C. neoformans pathogenesis, the molecular mechanisms governing their formation remain poorly understood. Here, we demonstrate that glycolysis is critical for titan cell formation in C. neoformans. Pharmacological inhibition or genetic disruption of glycolysis significantly impaired titanization, whereas exogenous cAMP add-back restored the defect. To elucidate the underlying mechanism, we performed comparative RNA-seq analyses of wild- type, hxk2{Delta}, and hxk2{Delta} supplemented with cAMP under titan cell inducing conditions. Transcriptomic analyses revealed significant downregulation of a large subset of calcineurin- responsive genes in the hxk2{Delta} mutant, many of which were restored upon cAMP supplementation. Consistent with these findings, pharmacological inhibition of calcineurin using FK506 or cyclosporin A markedly reduced titan cell formation, establishing an essential role for calcineurin signaling in this morphological transition. Furthermore, supplementation with CaCl2 rescued the titanization defect of the hxk2{Delta} mutant, whereas chelation of extracellular calcium with EGTA significantly inhibited titanization in wild-type cells. Using the calcium-sensitive dye, we found that intracellular calcium levels were substantially reduced in the hxk2{Delta} mutant and were restored by CaCl2 or cAMP supplementation. Collectively, our findings uncover a previously unrecognized glycolysis-calcineurin regulatory axis that governs titan cell formation and establishes a direct mechanistic link between central carbon metabolism, calcium homeostasis and fungal morphogenesis. SummaryTitan cell formation is a critical virulence trait that promotes immune evasion and disease progression of Cryptococcus neoformans. However, the mechanisms governing this morphological transition remain poorly understood. Here, we demonstrate that glycolysis is essential for titan cell formation and uncover a previously unrecognized link between glycolysis, calcium homeostasis, and calcineurin signaling. Comparative transcriptomics, pharmacological perturbation, calcium rescue experiments, and intracellular calcium measurements reveal that disruption of glycolysis attenuates calcineurin signaling by reducing intracellular calcium levels, thereby impairing titanization. These findings establish a novel glycolysis-calcineurin regulatory axis controlling fungal morphogenesis in C. neoformans.

microbiology↗

bioRxiv2025

Segmental copy number amplifications are stable in the absence of selection

Copy number variants (CNVs) are DNA duplications and deletions that cause genetic variation, underlying rapid adaptive evolution. CNVs often confer selective advantages, but can also incur fitness costs. Evolution of Saccharomyces cerevisiae in nutrient-limited chemostats recurrently selects for amplifications of nutrient transporter genes. However, their fate upon return to a non-selective environment remains unknown. To investigate CNV fitness and stability upon removing the original selection pressure, we studied 15 CNV lineages (11 segmental, 4 whole-chromosomal amplifications) selected in nitrogen-limited chemostats. CNV stability was monitored using fluorescent reporters during propagation in nutrient-rich batch cultures for 110-220 generations. All aneuploid lineages showed rapid CNV loss and reversion to a single-copy genotype, whereas segmental amplifications were remarkably stable- one of 11 strains reverted. Pairwise fitness competitions in rich media revealed strong fitness defects associated solely with CNVs that reverted; reversion led to increased fitness. Using simulation-based inference to estimate reversion rates and fitness effects, we determined negative selection as the primary driver of CNV loss. Whole-genome sequencing revealed that reversion of aneuploids and a segmental amplification left no evidence of prior CNV existence, rendering revertant genomes indistinguishable from the single-copy ancestor. Detailed characterization of a partial revertant identified chromosomal translocation, suggesting that extant CNVs can undergo structural diversification. Our findings provide novel evidence that most segmental CNVs adapted to nitrogen limitation are stable upon removal of selection, but costly gene amplifications are readily reversible. Together, these highlight the importance of CNVs in both long-term genome evolution and rapid, reversible adaptation to transient selection.

evolutionary biology↗

bioRxiv2024

DNA replication errors are a major source of adaptive gene amplification

Copy number variants (CNVs)--gains and losses of genomic sequences--are an important source of genetic variation underlying rapid adaptation and genome evolution. However, despite their central role in evolution little is known about the factors that contribute to the structure, size, formation rate, and fitness effects of adaptive CNVs. Local genomic sequences are likely to be an important determinant of these properties. Whereas it is known that point mutation rates vary with genomic location and local DNA sequence features, the role of genome architecture in the formation, selection, and the resulting evolutionary dynamics of CNVs is poorly understood. Previously, we have found that the GAP1 gene in Saccharomyces cerevisiae undergoes frequent and repeated amplification and selection under long-term experimental evolution in glutamine-limiting conditions. The GAP1 gene has a unique genomic architecture consisting of two flanking long terminal repeats (LTRs) and a proximate origin of DNA replication (autonomously replicating sequence, ARS), which are likely to promote rapid GAP1 CNV formation. To test the role of these genomic elements on CNV-mediated adaptive evolution, we performed experimental evolution in glutamine-limited chemostats using engineered strains lacking either the adjacent LTRs, ARS, or all elements. Using a CNV reporter system and neural network simulation-based inference (nnSBI) we quantified the formation rate and fitness effect of CNVs for each strain. We find that although GAP1 CNVs repeatedly form and sweep to high frequency in strains with modified genome architecture, removal of local DNA elements significantly impacts the rate and fitness effect of CNVs and the rate of adaptation. We performed genome sequence analysis to define the molecular mechanisms of CNV formation for 177 CNV lineages. We find that across all four strain backgrounds, between 26% and 80% of all GAP1 CNVs are mediated by Origin Dependent Inverted Repeat Amplification (ODIRA) which results from template switching between the leading and lagging strand during DNA synthesis. In the absence of the local ARS, a distal ARS can mediate CNV formation via ODIRA. In the absence of local LTRs, homologous recombination mechanisms still mediate gene amplification following de novo insertion of retrotransposon elements at the locus. Our study demonstrates the remarkable plasticity of the genome and reveals that template switching during DNA replication is a frequent source of adaptive CNVs.

evolutionary biology↗

bioRxiv2023

Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression

Cells respond to environmental and developmental stimuli by remodeling their transcriptomes through regulation of both mRNA transcription and mRNA decay. A central goal of biology is identifying the global set of regulatory relationships between factors that control mRNA production and degradation and their target transcripts and construct a predictive model of gene expression. Regulatory relationships are typically identified using transcriptome measurements and causal inference algorithms. RNA kinetic parameters are determined experimentally by employing run-on or metabolic labeling (e.g. 4-thiouracil) methods that allow transcription and decay rates to be separately measured. Here, we develop a deep learning model, trained with single-cell RNA-seq data, that both infers causal regulatory relationships and estimates RNA kinetic parameters. The resulting in silico model predicts future gene expression states and can be perturbed to simulate the effect of transcription factor changes. We acquired model training data by sequencing the transcriptomes of 175,000 individual Saccharomyces cerevisiae cells that were subject to an external perturbation and continuously sampled over a one hour period. The rate of change for each transcript was calculated on a per-cell basis to estimate RNA velocity. We then trained a deep learning model with transcriptome and RNA velocity data to calculate time-dependent estimates of mRNA production and decay rates. By separating RNA velocity into transcription and decay rates, we show that rapamycin treatment causes existing ribosomal protein transcripts to be rapidly destabilized, while production of new transcripts gradually slows over the course of an hour. The neural network framework we present is designed to explicitly model causal regulatory relationships between transcription factors and their genes, and shows superior performance to existing models on the basis of recovery of known regulatory relationships. We validated the predictive power of the model by perturbing transcription factors in silico and comparing transcriptome-wide effects with experimental data. Our study represents the first step in constructing a complete, predictive, biophysical model of gene expression regulation.

systems biology↗