Biology subjects

Hartman, J. L.

Publications and source records attributed to Hartman, J. L..

6 recordsLinked to original sources

bioRxiv2026

Temozolomide Induces Aberrant RNA Alkylation and Widespread Translational Repression

Temozolomide (TMZ) is a frontline alkylating chemotherapy, yet its direct impact on RNA modification and global translation dynamics remains poorly understood. Here, we demonstrate that TMZ induces pervasive RNA alkylation causing severe translational impairment. TMZ directly deposits aberrant methyl groups onto single-stranded mRNA in vitro, creating physical lesions that lower translational efficiency. In glioblastoma cells, acute TMZ exposure triggers a rapid, widespread accumulation of m7G on cellular RNAs, leading to the significant attenuation of global protein synthesis. Nanopore direct RNA sequencing identified distinct guanine-specific error signatures and sequence context preferences associated with TMZ-induced damage. Using a quantitative yeast spike-in ribosome profiling strategy, we mapped this translational repression at transcript-level, revealing a global downregulation of translational efficiency. This widespread repression disproportionately targets highly interconnected networks essential for cellular proliferation, specifically chromosome organization. We show that the severity of this translational repression is driven by a transcript's coding guanine density, stability and translation initiation speed. Together, our findings suggest that TMZ-induced alkylation targets stable, highly translated, guanine-rich transcripts. This establishes aberrant RNA methylation and subsequent translational arrest as a potential mechanism of temozolomide cytotoxicity.

biochemistry↗

bioRxiv2020

A cell non-autonomous mechanism of yeast chronological aging regulated by caloric restriction and one-carbon metabolism

Caloric restriction (CR) improves healthspan and lifespan of organisms ranging from yeast to mammals. Understanding the mechanisms involved will uncover future interventions for aging associated diseases. In budding yeast, Saccharomyces cerevisiae, CR is commonly defined by reduced glucose in the growth medium, which extends both replicative and chronological lifespan (CLS). We found that conditioned media collected from stationary phase CR cultures extended CLS when supplemented into non-restricted (NR) cultures, suggesting a potential cell non-autonomous mechanism of CR-induced lifespan regulation. Chromatography and untargeted metabolomics of the conditioned media, as well as transcriptional responses associated with the longevity effect, pointed to specific amino acids enriched in the CR conditioned media (CRCM) as functional molecules, with L-serine being a particularly strong candidate. Indeed, supplementing L-serine into NR cultures extended CLS through a mechanism dependent on the one-carbon metabolism pathway, thus implicating this conserved and central metabolic hub in lifespan regulation.

cell biology↗

bioRxiv2020

High-resolution yeast quiescence profiling in human-like media reveals interacting influences of auxotrophy and nutrient availability

Yeast cells survive in stationary phase culture by entering quiescence, which is measured by colony forming capacity upon nutrient re-exposure. Yeast chronological lifespan (CLS) studies, employing the comprehensive collection of gene knockout strains, have correlated weakly between independent laboratories, which is hypothesized to reflect differential interaction between the deleted genes, auxotrophy, media composition and other assay conditions influencing quiescence. This hypothesis was investigated by high-throughput quiescence profiling of the parental prototrophic strain, from which the gene deletion strain libraries were constructed, and all possible auxotrophic allele combinations in that background. Defined media resembling human cell culture media promoted long-term quiescence, and was used to assess effects of glucose, ammonium sulfate, auxotrophic nutrient availability, Target of Rapamycin signaling, and replication stress. Frequent, high-replicate measurements of colony forming capacity from cultures aged past 60 days provided profiles of quiescence phenomena such as gasping and hormesis. Media acidification was assayed in parallel to assess correlation. Influences of leucine, methionine, glucose, and ammonium sulfate metabolism were clarified, and a role for lysine metabolism newly characterized, while histidine and uracil perturbations had less impact. Interactions occurred between glucose, ammonium sulfate, auxotrophy, auxotrophic nutrient limitation, aeration, TOR signaling, and/or replication stress. Weak correlation existed between media acidification and maintenance of quiescence. In summary, experimental factors, uncontrolled across previous genome-wide yeast CLS studies, influence quiescence and interact extensively, revealing quiescence as a complex metabolic and developmental process that should be studied in a prototrophic context, omitting ammonium sulfate from defined media, and employing highly replicable protocols.

genetics↗

bioRxiv2019

A High-Throughput Extraction and Analysis Method for Steroidal Glycoalkaloids in Tomato

Tomato steroidal glycoalkaloids (tSGAs) are a class of cholesterol-derived metabolites uniquely produced by the tomato clade. These compounds provide protection against biotic stress due to their fungicidal and insecticidal properties. Although commonly reported as being anti-nutritional, both in vitro as well as pre-clinical animal studies have indicated that some tSGAs may have a beneficial impact on human health. However, the paucity of quantitative extraction and analysis methods presents a major obstacle for determining the biological and nutritional functions of tSGAs. To address this problem, we developed and validated the first comprehensive extraction and UHPLC-MS/MS quantification method for tSGAs. Our extraction method allows for up to 16 samples to be extracted simultaneously in 20 minutes with 93.0 {+/-} 6.8% and 100.8 {+/-} 13.1% recovery rates for tomatidine and alpha-tomatine, respectively. Our ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method was able to chromatographically separate analytes derived from 16 tSGAs representing 9 different tSGA masses, as well as two internal standards, in 13 minutes. Tomato steroidal glycoalkaloids that did not have available standards were annotated using high resolution mass spectrometry as well as product ion scans that provided fragmentation data. Lastly, we utilized our method to survey a variety of commonly consumed tomato-based products. Total tSGA concentrations ranged from 0.7 to 3.4 mg/serving and represent some of the first reported tSGA concentrations in tomato-based products. Our validation studies indicate that our method is sensitive, robust, and able to be used for a variety of applications where concentrations of biologically relevant tSGAs need to be quantified.

plant biology↗

bioRxiv2019

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

Knowledge about synthetic lethality can be applied to enhance the efficacy of anti-cancer therapies in individual patients harboring genetic alterations in their cancer that specifically render it vulnerable. We investigated the potential for high-resolution phenomic analysis in yeast to predict such genetic vulnerabilities by systematic, comprehensive, and quantitative assessment of drug-gene interaction for gemcitabine and cytarabine, substrates of deoxycytidine kinase that have similar molecular structures yet distinct anti-tumor efficacy. Human deoxycytidine kinase (dCK) was conditionally expressed in the S. cerevisiae genomic library of knockout and knockdown (YKO/KD) strains, to globally and quantitatively characterize differential drug-gene interaction for gemcitabine and cytarabine. Pathway enrichment analysis revealed that autophagy, histone modification, chromatin remodeling, and apoptosis-related processes influence gemcitabine specifically, while drug-gene interaction specific to cytarabine was less enriched in Gene Ontology. Processes having influence over both drugs were DNA repair and integrity checkpoints and vesicle transport and fusion. Non-GO-enriched genes were also informative. Yeast phenomic and cancer cell line pharmacogenomics data were integrated to identify yeast-human homologs with correlated differential gene expression and drug-efficacy, thus providing a unique resource to predict whether differential gene expression observed in cancer genetic profiles are causal in tumor-specific responses to cytotoxic agents.

systems biology↗

bioRxiv2019

A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

BackgroundSaccharomyces cerevisiae represses respiration in the presence of adequate glucose, mimicking the Warburg effect, termed aerobic glycolysis. We conducted yeast phenomic experiments to characterize differential doxorubicin-gene interaction, in the context of respiration vs. glycolysis. The resulting systems level biology about doxorubicin cytotoxicity, including the influence of the Warburg effect, was integrated with cancer pharmacogenomics data to identify potentially causal correlations between differential gene expression and anti-cancer efficacy.\n\nMethodsQuantitative high-throughput cell array phenotyping (Q-HTCP) was used to measure cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library, treated with escalating doxorubicin concentrations in fermentable and non-fermentable media. Doxorubicin-gene interaction was quantified by departure of the observed and expected phenotypes for the doxorubicin-treated mutant strain, with respect to phenotypes for the untreated mutant strain and both the treated and untreated reference strain. Recursive expectation-maximization clustering (REMc) and Gene Ontology-based analyses of interactions were used to identify functional biological modules that buffer doxorubicin cytotoxicity, and to characterize their Warburg-dependence. Yeast phenomic data was applied to cancer cell line pharmacogenomics data to predict differential gene expression that causally influences the anti-tumor efficacy, and potentially the anthracycline-associated host toxicity, of doxorubicin.\n\nResultsDoxorubicin cytotoxicity was greater with respiration, suggesting the Warburg effect can influence therapeutic efficacy. Accordingly, doxorubicin drug-gene interaction was more extensive with respiration, including increased buffering by cellular processes related to chromatin organization, protein folding and modification, translation reinitiation, spermine metabolism, and fatty acid beta-oxidation. Pathway enrichment was less notable for glycolysis-specific buffering. Cellular processes exerting influence relatively independently, with respect to Warburg status, included homologous recombination, sphingolipid homeostasis, telomere tethering at nuclear periphery, and actin cortical patch localization. Causality for differential gene expression associated with doxorubicin cytotoxicity in tumor cells was predicted within the biological context of the phenomic model.\n\nConclusionsWarburg status influences the genetic requirements to buffer doxorubicin toxicity. Yeast phenomics provides an experimental platform to model the complexity of gene interaction networks that influence human disease phenotypes, as in this example of chemotherapy response. High-resolution, systems level yeast phenotyping is useful to predict the biological influence of functional variation on disease, offering the potential to fundamentally advance precision medicine.

systems biology↗