Publications by authors named "John L Hartman"

25 Publications

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

J Biol Chem 2020 Nov 26. Epub 2020 Nov 26.

Biochemistry and Molecular Genetics, University of Virginia, United States.

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, , 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.
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http://dx.doi.org/10.1074/jbc.RA120.015402DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7949035PMC
November 2020

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

Geroscience 2020 10 5. Epub 2020 Oct 5.

Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA.

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.
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http://dx.doi.org/10.1007/s11357-020-00265-2DOI Listing
October 2020

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

Cancer Metab 2019 23;7. Epub 2019 Oct 23.

Department of Genetics, University of Alabama at Birmingham, Birmingham, AL USA.

Background: The influence of the Warburg phenomenon on chemotherapy response is unknown. mimics the Warburg effect, repressing respiration in the presence of adequate glucose. Yeast phenomic experiments were conducted to assess potential influences of Warburg metabolism on gene-drug interaction underlying the cellular response to doxorubicin. Homologous genes from yeast phenomic and cancer pharmacogenomics data were analyzed to infer evolutionary conservation of gene-drug interaction and predict therapeutic relevance.

Methods: Cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library were measured by quantitative high-throughput cell array phenotyping (Q-HTCP), treating with escalating doxorubicin concentrations under conditions of respiratory or glycolytic metabolism. Doxorubicin-gene interaction was quantified by departure of CPPs observed for the doxorubicin-treated mutant strain from that expected based on an interaction model. Recursive expectation-maximization clustering (REMc) and Gene Ontology (GO)-based analyses of interactions identified functional biological modules that differentially buffer or promote doxorubicin cytotoxicity with respect to Warburg metabolism. Yeast phenomic and cancer pharmacogenomics data were integrated to predict differential gene expression causally influencing doxorubicin anti-tumor efficacy.

Results: Yeast compromised for genes functioning in chromatin organization, and several other cellular processes are more resistant to doxorubicin under glycolytic conditions. Thus, the Warburg transition appears to alleviate requirements for cellular functions that buffer doxorubicin cytotoxicity in a respiratory context. We analyzed human homologs of yeast genes exhibiting gene-doxorubicin interaction in cancer pharmacogenomics data to predict causality for differential gene expression associated with doxorubicin cytotoxicity in cancer cells. This analysis suggested conserved cellular responses to doxorubicin due to influences of homologous recombination, sphingolipid homeostasis, telomere tethering at nuclear periphery, actin cortical patch localization, and other gene functions.

Conclusions: Warburg status alters the genetic network required for yeast to buffer doxorubicin toxicity. Integration of yeast phenomic and cancer pharmacogenomics data suggests evolutionary conservation of gene-drug interaction networks and provides a new experimental approach to model their influence on chemotherapy response. Thus, yeast phenomic models could aid the development of precision oncology algorithms to predict efficacious cytotoxic drugs for cancer, based on genetic and metabolic profiles of individual tumors.
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http://dx.doi.org/10.1186/s40170-019-0201-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806529PMC
October 2019

Slowing ribosome velocity restores folding and function of mutant CFTR.

J Clin Invest 2019 12;129(12):5236-5253

Emory University School of Medicine, Atlanta, Georgia, USA.

Cystic fibrosis (CF) is caused by mutations in the CF transmembrane conductance regulator (CFTR), with approximately 90% of patients harboring at least one copy of the disease-associated variant F508del. We utilized a yeast phenomic system to identify genetic modifiers of F508del-CFTR biogenesis, from which ribosomal protein L12 (RPL12/uL11) emerged as a molecular target. In the present study, we investigated mechanism(s) by which suppression of RPL12 rescues F508del protein synthesis and activity. Using ribosome profiling, we found that rates of translation initiation and elongation were markedly slowed by RPL12 silencing. However, proteolytic stability and patch-clamp assays revealed RPL12 depletion significantly increased F508del-CFTR steady-state expression, interdomain assembly, and baseline open-channel probability. We next evaluated whether Rpl12-corrected F508del-CFTR could be further enhanced with concomitant pharmacologic repair (e.g., using clinically approved modulators lumacaftor and tezacaftor) and demonstrated additivity of these treatments. Rpl12 knockdown also partially restored maturation of specific CFTR variants in addition to F508del, and WT Cftr biogenesis was enhanced in the pancreas, colon, and ileum of Rpl12 haplosufficient mice. Modulation of ribosome velocity therefore represents a robust method for understanding both CF pathogenesis and therapeutic response.
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http://dx.doi.org/10.1172/JCI124282DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6877332PMC
December 2019

A Humanized Yeast Phenomic Model of Deoxycytidine Kinase to Predict Genetic Buffering of Nucleoside Analog Cytotoxicity.

Genes (Basel) 2019 09 30;10(10). Epub 2019 Sep 30.

Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA .

Knowledge about synthetic lethality can be applied to enhance the efficacy of anticancer 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 antitumor efficacy. Human deoxycytidine kinase (dCK) was conditionally expressed in the 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-gene ontology (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.
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http://dx.doi.org/10.3390/genes10100770DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826991PMC
September 2019

Ribosomal Stalk Protein Silencing Partially Corrects the ΔF508-CFTR Functional Expression Defect.

PLoS Biol 2016 05 11;14(5):e1002462. Epub 2016 May 11.

Department of Physiology, McGill University, Montréal, Quebec, Canada.

The most common cystic fibrosis (CF) causing mutation, deletion of phenylalanine 508 (ΔF508 or Phe508del), results in functional expression defect of the CF transmembrane conductance regulator (CFTR) at the apical plasma membrane (PM) of secretory epithelia, which is attributed to the degradation of the misfolded channel at the endoplasmic reticulum (ER). Deletion of phenylalanine 670 (ΔF670) in the yeast oligomycin resistance 1 gene (YOR1, an ABC transporter) of Saccharomyces cerevisiae phenocopies the ΔF508-CFTR folding and trafficking defects. Genome-wide phenotypic (phenomic) analysis of the Yor1-ΔF670 biogenesis identified several modifier genes of mRNA processing and translation, which conferred oligomycin resistance to yeast. Silencing of orthologues of these candidate genes enhanced the ΔF508-CFTR functional expression at the apical PM in human CF bronchial epithelia. Although knockdown of RPL12, a component of the ribosomal stalk, attenuated the translational elongation rate, it increased the folding efficiency as well as the conformational stability of the ΔF508-CFTR, manifesting in 3-fold augmented PM density and function of the mutant. Combination of RPL12 knockdown with the corrector drug, VX-809 (lumacaftor) restored the mutant function to ~50% of the wild-type channel in primary CFTRΔF508/ΔF508 human bronchial epithelia. These results and the observation that silencing of other ribosomal stalk proteins partially rescue the loss-of-function phenotype of ΔF508-CFTR suggest that the ribosomal stalk modulates the folding efficiency of the mutant and is a potential therapeutic target for correction of the ΔF508-CFTR folding defect.
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http://dx.doi.org/10.1371/journal.pbio.1002462DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4864299PMC
May 2016

Gene-nutrient interaction markedly influences yeast chronological lifespan.

Exp Gerontol 2016 12 25;86:113-123. Epub 2016 Apr 25.

Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Alabama at Birmingham, Birmingham, AL 35294, USA; Comprehensive Center for Healthy Aging, University of Alabama at Birmingham, Birmingham, AL 35294, USA; Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA. Electronic address:

Purpose: Research into the genetic mechanisms of aging has expanded rapidly over the past two decades. This has in part been the result of the use of model organisms (particularly yeast, worms and flies) and high-throughput technologies, combined with a growing interest in aging research. Despite this progress, widespread consensus regarding the pathways that are fundamental to the modulation of cellular aging and lifespan for all organisms has been limited due to discrepancies between different studies. We have compared results from published genome-wide, chronological lifespan (CLS) screens of individual gene deletion strains in Saccharomyces cerevisiae in order to identify gene deletion strains with consistent influences on longevity as possible indicators of fundamental aging processes from this single-celled, eukaryotic model organism.

Methods: Three previous reports have described genetic modifiers of chronological aging in the budding yeast (S. cerevisiae) using the yeast gene deletion strain collection. We performed a comparison among the data sets using correlation and decile distribution analysis to describe concordance between screens and identify strains that consistently increased or decreased CLS. We used gene enrichment analysis in an effort to understand the biology underlying genes identified in multiple studies. We attempted to replicate the different experimental conditions employed by the screens to identify potential sources of variability in CLS worth further investigating.

Results: Among 3209 strains present in all three screens, nine deletions strains were in common in the longest-lived decile (2.80%) and thirteen were in common in the shortest-lived decile (4.05%) of all three screens. Similarly, pairwise overlap between screens was low. When the same comparison was extended to three deciles to include more mutants studied in common between the three screens, enrichment of cellular processes based on gene ontology analysis in the long-lived strains remained very limited. To test the hypothesis that different parental strain auxotrophic requirements or media formulations employed by the respective genome-wide screens might contribute to the lack of concordance, different CLS assay conditions were assessed in combination with strains having different ploidy and auxotrophic requirements (all relevant to differences in the way the three genome-wide CLS screens were performed). This limited but systematic analysis of CLS with respect to auxotrophy, ploidy, and media revealed several instances of gene-nutrient interaction.

Conclusions: There is surprisingly little overlap between the results of three independently performed genome-wide screens of CLS in S. cerevisiae. However, differences in strain genetic background (ploidy and specific auxotrophic requirements) were present, as well as different media and experimental conditions (e.g., aeration and pooled vs. individual culturing), which, along with stochastic effects such as genetic drift or selection of secondary mutations that suppress the loss of function from gene deletion, could in theory account for some of the lack of consensus between results. Considering the lack of overlap in CLS phenotypes among the set of genes reported by all three screens, and the results of a CLS experiment that systematically tested (incorporating extensive controls) for interactions between variables existing between the screens, we propose that discrepancies can be reconciled through deeper understanding of the influence of cell intrinsic factors such as auxotrophic requirements ploidy status, extrinsic factors such as media composition and aeration, as well as interactions that may occur between them, for example as a result of different pooling vs. individually aging cultures. Such factors may have a more significant impact on CLS outcomes than previously realized. Future studies that systematically account for these contextual factors, and can thus clarify the interactions between genetic and nutrient factors that alter CLS phenotypes, should aid more complete understanding of the underlying biology so that genetic principles of CLS in yeast can be extrapolated to differential cellular aging observed in animal models.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5079838PMC
http://dx.doi.org/10.1016/j.exger.2016.04.012DOI Listing
December 2016

Long-range coupling between the extracellular gates and the intracellular ATP binding domains of multidrug resistance protein pumps and cystic fibrosis transmembrane conductance regulator channels.

FASEB J 2016 Mar 25;30(3):1247-62. Epub 2015 Nov 25.

*Department of Cell, Developmental, and Integrative Biology, Department of Genetics, and Department of Neurobiology, Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham, Birmingham, Alabama, USA

The ABCC transporter subfamily includes pumps, the long and short multidrug resistance proteins (MRPs), and an ATP-gated anion channel, the cystic fibrosis transmembrane conductance regulator (CFTR). We show that despite their thermodynamic differences, these ABCC transporter subtypes use broadly similar mechanisms to couple their extracellular gates to the ATP occupancies of their cytosolic nucleotide binding domains. A conserved extracellular phenylalanine at this gate was a prime location for producing gain of function (GOF) mutants of a long MRP in yeast (Ycf1p cadmium transporter), a short yeast MRP (Yor1p oligomycin exporter), and human CFTR channels. Extracellular gate mutations rescued ATP binding mutants of the yeast MRPs and CFTR by increasing ATP sensitivity. Control ATPase-defective MRP mutants could not be rescued by this mechanism. A CFTR double mutant with an extracellular gate mutation plus a cytosolic GOF mutation was highly active (single-channel open probability >0.3) in the absence of ATP and protein kinase A, each normally required for CFTR activity. We conclude that all 3 ABCC transporter subtypes use similar mechanisms to couple their extracellular gates to ATP occupancy, and highly active CFTR channels that bypass defects in ATP binding or phosphorylation can be produced.
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http://dx.doi.org/10.1096/fj.15-278382DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4750415PMC
March 2016

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease.

Genes (Basel) 2015 Feb 6;6(1):24-45. Epub 2015 Feb 6.

Department of Statistics and Michael Smith Laboratories, University of British Columbia, 3182 Earth Sciences Building, 2207 Main Mall, Vancouver, BC V6T-1Z4, Canada.

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease.
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http://dx.doi.org/10.3390/genes6010024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4377832PMC
February 2015

Aging and energetics' 'Top 40' future research opportunities 2010-2013.

F1000Res 2014 12;3:219. Epub 2014 Sep 12.

Nutrition and Obesity Research Center, University of Alabama at Birmingham, Birmingham, USA ; Department of Biology, University of Alabama at Birmingham, Birmingham, USA ; Comprehensive Center for Healthy Aging, University of Alabama at Birmingham, Birmingham, USA ; UAB Center for Exercise Medicine, University of Alabama at Birmingham, Birmingham, USA.

Background: As part of a coordinated effort to expand our research activity at the interface of Aging and Energetics a team of investigators at The University of Alabama at Birmingham systematically assayed and catalogued the top research priorities identified in leading publications in that domain, believing the result would be useful to the scientific community at large.

Objective: To identify research priorities and opportunities in the domain of aging and energetics as advocated in the 40 most cited papers related to aging and energetics in the last 4 years.

Design: The investigators conducted a search for papers on aging and energetics in Scopus, ranked the resulting papers by number of times they were cited, and selected the ten most-cited papers in each of the four years that include 2010 to 2013, inclusive.

Results:   Ten research categories were identified from the 40 papers.  These included: (1) Calorie restriction (CR) longevity response, (2) role of mTOR (mechanistic target of Rapamycin) and related factors in lifespan extension, (3) nutrient effects beyond energy (especially resveratrol, omega-3 fatty acids, and selected amino acids), 4) autophagy and increased longevity and health, (5) aging-associated predictors of chronic disease, (6) use and effects of mesenchymal stem cells (MSCs), (7) telomeres relative to aging and energetics, (8) accretion and effects of body fat, (9) the aging heart,  and (10) mitochondria, reactive oxygen species, and cellular energetics.

Conclusion: The field is rich with exciting opportunities to build upon our existing knowledge about the relations among aspects of aging and aspects of energetics and to better understand the mechanisms which connect them.
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http://dx.doi.org/10.12688/f1000research.5212.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4197746PMC
October 2014

Phenomic assessment of genetic buffering by kinetic analysis of cell arrays.

Methods Mol Biol 2014 ;1205:187-208

Department of Genetics, University of Alabama at Birmingham, KAUL 702, Birmingham, AL, 35294, USA,

Quantitative high-throughput cell array phenotyping (Q-HTCP) is applied to the genomic collection of yeast gene deletion mutants for systematic, comprehensive assessment of the contribution of genes and gene combinations to any phenotype of interest (phenomic analysis). Interacting gene networks influence every phenotype. Genetic buffering refers to how gene interaction networks stabilize or destabilize a phenotype. Like genomics, phenomics varies in its resolution with there being a trade-off allocating a greater number of measurements per sample to enhance quantification of the phenotype vs. increasing the number of different samples by obtaining fewer measurements per sample. The Q-HTCP protocol we describe assesses 50,000-70,000 cultures per experiment by obtaining kinetic growth curves from time series imaging of agar cell arrays. This approach was developed for the yeast gene deletion strains, but it could be applied as well to other microbial mutant arrays grown on solid agar media. The methods we describe are for creation and maintenance of frozen stocks, liquid source array preparation, agar destination plate printing, image scanning, image analysis, curve fitting, and evaluation of gene interaction.
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http://dx.doi.org/10.1007/978-1-4939-1363-3_12DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4920064PMC
May 2015

Conserved allosteric hot spots in the transmembrane domains of cystic fibrosis transmembrane conductance regulator (CFTR) channels and multidrug resistance protein (MRP) pumps.

J Biol Chem 2014 Jul 29;289(29):19942-57. Epub 2014 May 29.

From the Departments of Cell, Developmental, and Integrative Biology, Neurobiology and the Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham, Birmingham Alabama 35294-0005

ATP-binding cassette (ABC) transporters are an ancient family of transmembrane proteins that utilize ATPase activity to move substrates across cell membranes. The ABCC subfamily of the ABC transporters includes active drug exporters (the multidrug resistance proteins (MRPs)) and a unique ATP-gated ion channel (cystic fibrosis transmembrane conductance regulator (CFTR)). The CFTR channel shares gating principles with conventional ligand-gated ion channels, but the allosteric network that couples ATP binding at its nucleotide binding domains (NBDs) with conformational changes in its transmembrane helices (TMs) is poorly defined. It is also unclear whether the mechanisms that govern CFTR gating are conserved with the thermodynamically distinct MRPs. Here we report a new class of gain of function (GOF) mutation of a conserved proline at the base of the pore-lining TM6. Multiple substitutions of this proline promoted ATP-free CFTR activity and activation by the weak agonist, 5'-adenylyl-β,γ-imidodiphosphate (AMP-PNP). TM6 proline mutations exhibited additive GOF effects when combined with a previously reported GOF mutation located in an outer collar of TMs that surrounds the pore-lining TMs. Each TM substitution allosterically rescued the ATP sensitivity of CFTR gating when introduced into an NBD mutant with defective ATP binding. Both classes of GOF mutations also rescued defective drug export by a yeast MRP (Yor1p) with ATP binding defects in its NBDs. We conclude that the conserved TM6 proline helps set the energy barrier to both CFTR channel opening and MRP-mediated drug efflux and that CFTR channels and MRP pumps utilize similar allosteric mechanisms for coupling conformational changes in their translocation pathways to ATP binding at their NBDs.
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http://dx.doi.org/10.1074/jbc.M114.562116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106314PMC
July 2014

The SWI/SNF chromatin remodeling complex influences transcription by RNA polymerase I in Saccharomyces cerevisiae.

PLoS One 2013 20;8(2):e56793. Epub 2013 Feb 20.

Department of Biochemistry and Molecular Genetics, University of Alabama at Birmingham, Birmingham, AL, USA.

SWI/SNF is a chromatin remodeling complex that affects transcription initiation and elongation by RNA polymerase II. Here we report that SWI/SNF also plays a role in transcription by RNA polymerase I (Pol I) in Saccharomyces cerevisiae. Deletion of the genes encoding the Snf6p or Snf5p subunits of SWI/SNF was lethal in combination with mutations that impair Pol I transcription initiation and elongation. SWI/SNF physically associated with ribosomal DNA (rDNA) within the coding region, with an apparent peak near the 5' end of the gene. In snf6Δ cells there was a ∼2.5-fold reduction in rRNA synthesis rate compared to WT, but there was no change in average polymerase occupancy per gene, the number of rDNA gene repeats, or the percentage of transcriptionally active rDNA genes. However, both ChIP and EM analyses showed a small but reproducible increase in Pol I density in a region near the 5' end of the gene. Based on these data, we conclude that SWI/SNF plays a positive role in Pol I transcription, potentially by modifying chromatin structure in the rDNA repeats. Our findings demonstrate that SWI/SNF influences the most robust transcription machinery in proliferating cells.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0056793PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3577654PMC
August 2013

A yeast phenomic model for the gene interaction network modulating CFTR-ΔF508 protein biogenesis.

Genome Med 2012 Dec 27;4(12):103. Epub 2012 Dec 27.

Background: The overall influence of gene interaction in human disease is unknown. In cystic fibrosis (CF) a single allele of the cystic fibrosis transmembrane conductance regulator (CFTR-[increment]F508) accounts for most of the disease. In cell models, CFTR-[increment]F508 exhibits defective protein biogenesis and degradation rather than proper trafficking to the plasma membrane where CFTR normally functions. Numerous genes function in the biogenesis of CFTR and influence the fate of CFTR-[increment]F508. However it is not known whether genetic variation in such genes contributes to disease severity in patients. Nor is there an easy way to study how numerous gene interactions involving CFTR-[increment]F would manifest phenotypically.

Methods: To gain insight into the function and evolutionary conservation of a gene interaction network that regulates biogenesis of a misfolded ABC-transporter, we employed yeast genetics to develop a "phenomic" model, in which the CFTR-[increment]F508-equivalent residue of a yeast homolog is mutated (Yor1-[increment]F670), and where the genome is scanned quantitatively for interaction. We first confirmed that Yor1-[increment]F undergoes protein misfolding and has reduced half-life, analogous to CFTR-[increment]F. Gene interaction was then assessed quantitatively by growth curves for all ~5000 double mutants, based on alteration in the dose response to growth inhibition by oligomycin, a toxin extruded from the cell at the plasma membrane by Yor1.

Results: From a comparative genomic perspective, yeast gene interaction influencing Yor1-[increment]F biogenesis was representative of human homologs previously found to modulate processing of CFTR-[increment]F in mammalian cells. Additional evolutionarily conserved pathways were implicated by the study, and a [increment]F-specific pro-biogenesis function of the recently discovered ER Membrane Complex (EMC) was evident from the yeast screen. This novel function was validated biochemically by siRNA of an EMC ortholog in a human cell line expressing CFTR-[increment]F508. The precision and accuracy of quantitative high throughput cell array phenotyping (Q-HTCP), which captures tens of thousands of growth curves simultaneously, provided powerful resolution to measure gene interaction on a phenomic scale, based on discrete cell proliferation parameters.

Conclusion: We propose phenomic analysis of Yor1-[increment]F as a model for investigating gene interaction networks that can modulate cystic fibrosis disease severity. Although the clinical relevance of the Yor1-[increment]F gene interaction network for cystic fibrosis remains to be defined, the model appears to be informative with respect to human cell models of CFTR-[increment]F. Moreover, the general strategy of yeast phenomics can be employed in a systematic manner to model gene interaction for other diseases relating to pathologies that result from protein misfolding or potentially any disease involving evolutionarily conserved genetic pathways.
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http://dx.doi.org/10.1186/gm404DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3906889PMC
December 2012

A screen to identify small molecule inhibitors of protein-protein interactions in mycobacteria.

Assay Drug Dev Technol 2011 Jun 31;9(3):299-310. Epub 2011 Jan 31.

The Department of Microbiology, University of Alabama at Birmingham, USA.

Despite extensive efforts in tuberculosis (TB) drug research, very few novel inhibitors have been discovered. This issue emphasizes the need for innovative methods to discover new anti-TB drugs. In this study, we established a new high-throughput screen (HTS) platform technology that differs from traditional TB drug screens because it utilizes Mycobacterial-Protein Fragment Complementation (M-PFC) to identify small molecule inhibitors of protein-protein interactions in mycobacteria. Several examples of protein-protein interactions were tested with M-PFC to highlight the diversity of selectable drug targets that could be used for screening. These included interactions of essential regulators (IdeR dimerization), enzymatic complexes (LeuCD), secretory antigens (Cfp10-Esat6), and signaling pathways (DevR dimerization). The feasibility of M-PFC in a HTS platform setting was tested by performing a proof-of-concept quantitative HTS of 3,600 small molecule compounds on DevR-DevR interaction, which was chosen because of its strong implications in Mycobacterium tuberculosis persistence and the need for effective drugs against latent TB. The calculated Z'-factor was consistently ≥0.8, indicating a robust and reproducible assay. Completion of the proof-of-concept screen allowed for the identification of advantages and disadvantages in the current assay design, where improvements made will further pioneer M-PFC-based applications in a large-scale HTS format.
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http://dx.doi.org/10.1089/adt.2010.0326DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3102257PMC
June 2011

Global analysis of phase locking in gene expression during cell cycle: the potential in network modeling.

BMC Syst Biol 2010 Dec 3;4:167. Epub 2010 Dec 3.

Department of Physics, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA.

Background: In nonlinear dynamic systems, synchrony through oscillation and frequency modulation is a general control strategy to coordinate multiple modules in response to external signals. Conversely, the synchrony information can be utilized to infer interaction. Increasing evidence suggests that frequency modulation is also common in transcription regulation.

Results: In this study, we investigate the potential of phase locking analysis, a technique to study the synchrony patterns, in the transcription network modeling of time course gene expression data. Using the yeast cell cycle data, we show that significant phase locking exists between transcription factors and their targets, between gene pairs with prior evidence of physical or genetic interactions, and among cell cycle genes. When compared with simple correlation we found that the phase locking metric can identify gene pairs that interact with each other more efficiently. In addition, it can automatically address issues of arbitrary time lags or different dynamic time scales in different genes, without the need for alignment. Interestingly, many of the phase locked gene pairs exhibit higher order than 1:1 locking, and significant phase lags with respect to each other. Based on these findings we propose a new phase locking metric for network reconstruction using time course gene expression data. We show that it is efficient at identifying network modules of focused biological themes that are important to cell cycle regulation.

Conclusions: Our result demonstrates the potential of phase locking analysis in transcription network modeling. It also suggests the importance of understanding the dynamics underlying the gene expression patterns.
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http://dx.doi.org/10.1186/1752-0509-4-167DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3017040PMC
December 2010

Recursive expectation-maximization clustering: a method for identifying buffering mechanisms composed of phenomic modules.

Chaos 2010 Jun;20(2):026103

Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA.

Interactions between genetic and/or environmental factors are ubiquitous, affecting the phenotypes of organisms in complex ways. Knowledge about such interactions is becoming rate-limiting for our understanding of human disease and other biological phenomena. Phenomics refers to the integrative analysis of how all genes contribute to phenotype variation, entailing genome and organism level information. A systems biology view of gene interactions is critical for phenomics. Unfortunately the problem is intractable in humans; however, it can be addressed in simpler genetic model systems. Our research group has focused on the concept of genetic buffering of phenotypic variation, in studies employing the single-cell eukaryotic organism, S. cerevisiae. We have developed a methodology, quantitative high throughput cellular phenotyping (Q-HTCP), for high-resolution measurements of gene-gene and gene-environment interactions on a genome-wide scale. Q-HTCP is being applied to the complete set of S. cerevisiae gene deletion strains, a unique resource for systematically mapping gene interactions. Genetic buffering is the idea that comprehensive and quantitative knowledge about how genes interact with respect to phenotypes will lead to an appreciation of how genes and pathways are functionally connected at a systems level to maintain homeostasis. However, extracting biologically useful information from Q-HTCP data is challenging, due to the multidimensional and nonlinear nature of gene interactions, together with a relative lack of prior biological information. Here we describe a new approach for mining quantitative genetic interaction data called recursive expectation-maximization clustering (REMc). We developed REMc to help discover phenomic modules, defined as sets of genes with similar patterns of interaction across a series of genetic or environmental perturbations. Such modules are reflective of buffering mechanisms, i.e., genes that play a related role in the maintenance of physiological homeostasis. To develop the method, 297 gene deletion strains were selected based on gene-drug interactions with hydroxyurea, an inhibitor of ribonucleotide reductase enzyme activity, which is critical for DNA synthesis. To partition the gene functions, these 297 deletion strains were challenged with growth inhibitory drugs known to target different genes and cellular pathways. Q-HTCP-derived growth curves were used to quantify all gene interactions, and the data were used to test the performance of REMc. Fundamental advantages of REMc include objective assessment of total number of clusters and assignment to each cluster a log-likelihood value, which can be considered an indicator of statistical quality of clusters. To assess the biological quality of clusters, we developed a method called gene ontology information divergence z-score (GOid_z). GOid_z summarizes total enrichment of GO attributes within individual clusters. Using these and other criteria, we compared the performance of REMc to hierarchical and K-means clustering. The main conclusion is that REMc provides distinct efficiencies for mining Q-HTCP data. It facilitates identification of phenomic modules, which contribute to buffering mechanisms that underlie cellular homeostasis and the regulation of phenotypic expression.
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http://dx.doi.org/10.1063/1.3455188DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909310PMC
June 2010

Genomewide analysis reveals novel pathways affecting endoplasmic reticulum homeostasis, protein modification and quality control.

Genetics 2009 Jul 11;182(3):757-69. Epub 2009 May 11.

Department of Biological Sciences, Columbia University, New York, New York 10027, USA.

To gain new mechanistic insight into ER homeostasis and the biogenesis of secretory proteins, we screened a genomewide collection of yeast mutants for defective intracellular retention of the ER chaperone, Kar2p. We identified 87 Kar2p-secreting strains, including a number of known components in secretory protein modification and sorting. Further characterization of the 73 nonessential Kar2p retention mutants revealed roles for a number of novel gene products in protein glycosylation, GPI-anchor attachment, ER quality control, and retrieval of escaped ER residents. A subset of these mutants, required for ER retrieval, included the GET complex and two novel proteins that likely function similarly in membrane insertion of tail-anchored proteins. Finally, the variant histone, Htz1p, and its acetylation state seem to play an important role in maintaining ER retrieval pathways, suggesting a surprising link between chromatin remodeling and ER homeostasis.
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http://dx.doi.org/10.1534/genetics.109.101105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2710157PMC
July 2009

Stringent mating-type-regulated auxotrophy increases the accuracy of systematic genetic interaction screens with Saccharomyces cerevisiae mutant arrays.

Genetics 2009 Jan 28;181(1):289-300. Epub 2008 Oct 28.

Department of Genetics, University of Alabama, Birmingham, Alabama 35294, USA.

A genomic collection of haploid Saccharomyces cerevisiae deletion strains provides a unique resource for systematic analysis of gene interactions. Double-mutant haploid strains can be constructed by the synthetic genetic array (SGA) method, wherein a query mutation is introduced by mating to mutant arrays, selection of diploid double mutants, induction of meiosis, and selection of recombinant haploid double-mutant progeny. The mechanism of haploid selection is mating-type-regulated auxotrophy (MRA), by which prototrophy is restricted to a particular haploid genotype generated only as a result of meiosis. MRA escape leads to false-negative genetic interaction results because postmeiotic haploids that are supposed to be under negative selection instead proliferate and mate, forming diploids that are heterozygous at interacting loci, masking phenotypes that would be observed in a pure haploid double-mutant culture. This work identified factors that reduce MRA escape, including insertion of terminator and repressor sequences upstream of the MRA cassette, deletion of silent mating-type loci, and utilization of alpha-type instead of a-type MRA. Modifications engineered to reduce haploid MRA escape reduced false negative results in SGA-type analysis, resulting in >95% sensitivity for detecting gene-gene interactions.
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http://dx.doi.org/10.1534/genetics.108.092981DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2621176PMC
January 2009

Defining genetic interaction.

Proc Natl Acad Sci U S A 2008 Mar 27;105(9):3461-6. Epub 2008 Feb 27.

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, Boston, MA 02115, USA.

Sometimes mutations in two genes produce a phenotype that is surprising in light of each mutation's individual effects. This phenomenon, which defines genetic interaction, can reveal functional relationships between genes and pathways. For example, double mutants with surprisingly slow growth define synergistic interactions that can identify compensatory pathways or protein complexes. Recent studies have used four mathematically distinct definitions of genetic interaction (here termed Product, Additive, Log, and Min). Whether this choice holds practical consequences has not been clear, because the definitions yield identical results under some conditions. Here, we show that the choice among alternative definitions can have profound consequences. Although 52% of known synergistic genetic interactions in Saccharomyces cerevisiae were inferred according to the Min definition, we find that both Product and Log definitions (shown here to be practically equivalent) are better than Min for identifying functional relationships. Additionally, we show that the Additive and Log definitions, each commonly used in population genetics, lead to differing conclusions related to the selective advantages of sexual reproduction.
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http://dx.doi.org/10.1073/pnas.0712255105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2265146PMC
March 2008

Buffering of deoxyribonucleotide pool homeostasis by threonine metabolism.

Authors:
John L Hartman

Proc Natl Acad Sci U S A 2007 Jul 2;104(28):11700-5. Epub 2007 Jul 2.

Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA.

Synergistically interacting gene mutations reveal buffering relationships that provide growth homeostasis through their compensation of one another. This analysis in Saccharomyces cerevisiae revealed genetic modules involved in tricarboxylic acid cycle regulation (RTG1, RTG2, RTG3), threonine biosynthesis (HOM3, HOM2, HOM6, THR1, THR4), amino acid permease trafficking (LST4, LST7), and threonine catabolism (GLY1). These modules contribute to a molecular circuit that regulates threonine metabolism and buffers deficiency in deoxyribonucleotide biosynthesis. Phenotypic, genetic, and biochemical evidence for this buffering circuit was obtained through analysis of deletion mutants, titratable alleles of ribonucleotide reductase genes, and measurements of intracellular deoxyribonucleotide pool concentrations. This circuit provides experimental evidence, in eukaryotes, for the presence of a high-flux backbone of metabolism, which was previously predicted from in silico modeling of global metabolism in bacteria. This part of the high-flux backbone appears to buffer deficiency in ribonucleotide reductase by enabling a compensatory increase in de novo purine biosynthesis that provides additional rate-limiting substrates for dNTP production and DNA synthesis. Hypotheses regarding unexpected connections between these metabolic pathways were facilitated by genome-wide but also highly quantitative phenotypic assessment of interactions. Validation of these hypotheses substantiates the added benefit of quantitative phenotyping for identifying subtleties in gene interaction networks that modulate cellular phenotypes.
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http://dx.doi.org/10.1073/pnas.0705212104DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1913885PMC
July 2007

High throughput drug screening for human immunodeficiency virus type 1 reactivating compounds.

Assay Drug Dev Technol 2007 Apr;5(2):181-89

Department of Medicine, The University of Alabama at Birmingham, Birmingham, AL 35294, USA.

The ability of human immunodeficiency virus type 1 (HIV-1) to persist in a latent stage in memory T cells in the presence of antiretroviral therapy poses a major obstacle to the development of an HIV-1 therapy with curative intent. As latently infected cells are phenotypically not distinguishable from uninfected cells, therapeutic reactivation of the latent infection, followed by the death of the host cell induced by viral cytopathicity, is considered the only means to eliminate this viral reservoir. To identify compounds with the potential to reactivate latent HIV-1, we have developed a series of latently HIV-1-infected reporter cell lines that allow for high throughput drug screening (HTS) in a 384-well plate-based format. The latent reporter cell lines use enhanced green fluorescence protein (eGFP) as a direct and quantitative marker of HIV-1 expression. To aid identification of specific compounds, the cells are engineered to constitutively express a second, red fluorescent protein that has no spectral overlap with eGFP, which allows for the simultaneous quantification of cell viability (inversely correlated to compound toxicity). Thus, these reporters enable prioritization of compounds most likely to have a favorable therapeutic window. The high dynamic signal range and the excellent reproducibility of the primary screening assay result in a Z' -factor of 0.89, which characterizes the HTS system as very robust. The assay has been implemented for automated drug screening, and we here discuss the advantages and limitations of the HTS system based on the data obtained for 1,600 compounds during a limited proof-of-concept drug screen.
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http://dx.doi.org/10.1089/adt.2006.040DOI Listing
April 2007

Accurate, precise modeling of cell proliferation kinetics from time-lapse imaging and automated image analysis of agar yeast culture arrays.

BMC Syst Biol 2007 Jan 8;1. Epub 2007 Jan 8.

Department of Genetics, University of Alabama School of Medicine, Birmingham, Alabama 35294, USA.

Background: Genome-wide mutant strain collections have increased demand for high throughput cellular phenotyping (HTCP). For example, investigators use HTCP to investigate interactions between gene deletion mutations and additional chemical or genetic perturbations by assessing differences in cell proliferation among the collection of 5000 S. cerevisiae gene deletion strains. Such studies have thus far been predominantly qualitative, using agar cell arrays to subjectively score growth differences. Quantitative systems level analysis of gene interactions would be enabled by more precise HTCP methods, such as kinetic analysis of cell proliferation in liquid culture by optical density. However, requirements for processing liquid cultures make them relatively cumbersome and low throughput compared to agar. To improve HTCP performance and advance capabilities for quantifying interactions, YeastXtract software was developed for automated analysis of cell array images.

Results: YeastXtract software was developed for kinetic growth curve analysis of spotted agar cultures. The accuracy and precision for image analysis of agar culture arrays was comparable to OD measurements of liquid cultures. Using YeastXtract, image intensity vs. biomass of spot cultures was linearly correlated over two orders of magnitude. Thus cell proliferation could be measured over about seven generations, including four to five generations of relatively constant exponential phase growth. Spot area normalization reduced the variation in measurements of total growth efficiency. A growth model, based on the logistic function, increased precision and accuracy of maximum specific rate measurements, compared to empirical methods. The logistic function model was also more robust against data sparseness, meaning that less data was required to obtain accurate, precise, quantitative growth phenotypes.

Conclusion: Microbial cultures spotted onto agar media are widely used for genotype-phenotype analysis, however quantitative HTCP methods capable of measuring kinetic growth rates have not been available previously. YeastXtract provides objective, automated, quantitative, image analysis of agar cell culture arrays. Fitting the resulting data to a logistic equation-based growth model yields robust, accurate growth rate information. These methods allow the incorporation of imaging and automated image analysis of cell arrays, grown on solid agar media, into HTCP-driven experimental approaches, such as global, quantitative analysis of gene interaction networks.
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http://dx.doi.org/10.1186/1752-0509-1-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1847469PMC
January 2007

The case for strategic international alliances to harness nutritional genomics for public and personal health.

Br J Nutr 2005 Nov;94(5):623-32

Center of Excellence in Nutritional Genomics, University of California, Davis, CA 95616, USA.

Nutrigenomics is the study of how constituents of the diet interact with genes, and their products, to alter phenotype and, conversely, how genes and their products metabolise these constituents into nutrients, antinutrients, and bioactive compounds. Results from molecular and genetic epidemiological studies indicate that dietary unbalance can alter gene-nutrient interactions in ways that increase the risk of developing chronic disease. The interplay of human genetic variation and environmental factors will make identifying causative genes and nutrients a formidable, but not intractable, challenge. We provide specific recommendations for how to best meet this challenge and discuss the need for new methodologies and the use of comprehensive analyses of nutrient-genotype interactions involving large and diverse populations. The objective of the present paper is to stimulate discourse and collaboration among nutrigenomic researchers and stakeholders, a process that will lead to an increase in global health and wellness by reducing health disparities in developed and developing countries.
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http://dx.doi.org/10.1079/bjn20051585DOI Listing
November 2005

Systematic quantification of gene interactions by phenotypic array analysis.

Genome Biol 2004 29;5(7):R49. Epub 2004 Jun 29.

Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA.

A phenotypic array method, developed for quantifying cell growth, was applied to the haploid and homozygous diploid yeast deletion strain sets. A growth index was developed to screen for non-additive interacting effects between gene deletion and induced perturbations. From a genome screen for hydroxyurea (HU) chemical-genetic interactions, 298 haploid deletion strains were selected for further analysis. The strength of interactions was quantified using a wide range of HU concentrations affecting reference strain growth. The selectivity of interaction was determined by comparison with drugs targeting other cellular processes. Bio-modules were defined as gene clusters with shared strength and selectivity of interaction profiles. The functions and connectivity of modules involved in processes such as DNA repair, protein secretion and metabolic control were inferred from their respective gene composition. The work provides an example of, and a general experimental framework for, quantitative analysis of gene interaction networks that buffer cell growth.
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http://dx.doi.org/10.1186/gb-2004-5-7-r49DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC463315PMC
October 2004