Digital Insights Into Nucleotide Metabolism and Antibiotic Treatment Failure

Nucleotide metabolism plays a central role in bacterial physiology, producing the nucleic acids necessary for DNA replication and RNA transcription. Recent studies demonstrate that nucleotide metabolism also proactively contributes to antibiotic-induced lethality in bacterial pathogens and that disruptions to nucleotide metabolism contributes to antibiotic treatment failure in the clinic. As antimicrobial resistance continues to grow unchecked, new approaches are needed to study the molecular mechanisms responsible for antibiotic efficacy. Here we review emerging technologies poised to transform understanding into why antibiotics may fail in the clinic. We discuss how these technologies led to the discovery that nucleotide metabolism regulates antibiotic drug responses and why these are relevant to human infections. We highlight opportunities for how studies into nucleotide metabolism may enhance understanding of antibiotic failure mechanisms.

[1]  M. Díaz-Muñoz,et al.  Purinergic Signaling in the Hallmarks of Cancer , 2020, Cells.

[2]  Jason H. Yang,et al.  A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action , 2019, Cell.

[3]  J. Collins,et al.  A multiplexable assay for screening antibiotic lethality against drug-tolerant bacteria , 2019, Nature Methods.

[4]  Arunima Chaudhuri,et al.  Cell Biology by the Numbers , 2016, The Yale Journal of Biology and Medicine.

[5]  M. Vulić,et al.  Role of Global Regulators and Nucleotide Metabolism in Antibiotic Tolerance in Escherichia coli , 2008, Antimicrobial Agents and Chemotherapy.

[6]  James H. Bullard,et al.  Origins of the E. coli strain causing an outbreak of hemolytic-uremic syndrome in Germany. , 2011, The New England journal of medicine.

[7]  T. Bollenbach,et al.  Highly parallel lab evolution reveals that epistasis can curb the evolution of antibiotic resistance , 2020, Nature Communications.

[8]  Blake W Buchan,et al.  Emerging Technologies for the Clinical Microbiology Laboratory , 2014, Clinical Microbiology Reviews.

[9]  Bernhard O. Palsson,et al.  A biochemically-interpretable machine learning classifier for microbial GWAS , 2020, Nature Communications.

[10]  Jason H. Yang,et al.  Antibiotic-Induced Changes to the Host Metabolic Environment Inhibit Drug Efficacy and Alter Immune Function. , 2017, Cell host & microbe.

[11]  Miguel Vicente,et al.  The enemy within us: lessons from the 2011 European Escherichia coli O104:H4 outbreak , 2012, EMBO molecular medicine.

[12]  Jonathan M Stokes,et al.  Clinically relevant mutations in core metabolic genes confer antibiotic resistance , 2021, Science.

[13]  Adam M. Feist,et al.  iML1515, a knowledgebase that computes Escherichia coli traits , 2017, Nature Biotechnology.

[14]  Valentina Ferrari,et al.  Nucleoside Derived Antibiotics to Fight Microbial Drug Resistance: New Utilities for an Established Class of Drugs? , 2016, Journal of medicinal chemistry.

[15]  Jason H. Yang,et al.  Carbon Sources Tune Antibiotic Susceptibility in Pseudomonas aeruginosa via Tricarboxylic Acid Cycle Control. , 2017, Cell chemical biology.

[16]  S. Levy,et al.  Plasmid-determined tetracycline resistance involves new transport systems for tetracycline , 1978, Nature.

[17]  Andrew C. Pawlowski,et al.  The Comprehensive Antibiotic Resistance Database , 2013, Antimicrobial Agents and Chemotherapy.

[18]  Ahmad S. Khalil,et al.  Antibiotic efficacy is linked to bacterial cellular respiration. , 2015, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Xilin Zhao,et al.  Post-stress bacterial cell death mediated by reactive oxygen species , 2019, Proceedings of the National Academy of Sciences.

[20]  B. Conlon,et al.  Antibiotic efficacy in the complex infection environment. , 2018, Current opinion in microbiology.

[21]  Jonathan M Stokes,et al.  Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate , 2019, Nature Microbiology.

[22]  J. Linden,et al.  Purinergic regulation of the immune system , 2016, Nature Reviews Immunology.

[23]  Bernhard O Palsson,et al.  Machine learning with random subspace ensembles identifies antimicrobial resistance determinants from pan-genomes of three pathogens , 2020, PLoS Comput. Biol..

[24]  Liang Li,et al.  Role of Purine Biosynthesis in Persistent Methicillin-Resistant Staphylococcus aureus Infection , 2018, The Journal of infectious diseases.

[25]  D. E. Atkinson,et al.  Adenine nucleotide concentrations and turnover rates. Their correlation with biological activity in bacteria and yeast. , 1977, Advances in microbial physiology.

[26]  Jonathan M Stokes,et al.  Bacterial Metabolism and Antibiotic Efficacy , 2019, Cell metabolism.

[27]  Melis N. Anahtar,et al.  Applications of Machine Learning to the Problem of Antimicrobial Resistance: an Emerging Model for Translational Research , 2021, Journal of clinical microbiology.

[28]  M. Laub,et al.  ppGpp Coordinates Nucleotide and Amino-Acid Synthesis in E. coli During Starvation. , 2020, Molecular cell.

[29]  E. Brown,et al.  Metabolic suppression identifies new antibacterial inhibitors under nutrient limitation , 2013, Nature chemical biology.

[30]  A. Vázquez-Torres,et al.  Salmonella Reprograms Nucleotide Metabolism in Its Adaptation to Nitrosative Stress , 2018, mBio.

[31]  E. Brown,et al.  Antibacterial drug discovery in the resistance era , 2016, Nature.

[32]  Saloni R. Jain,et al.  Bactericidal Antibiotics Induce Toxic Metabolic Perturbations that Lead to Cellular Damage. , 2015, Cell reports.

[33]  Tanel Tenson,et al.  Recent functional insights into the role of (p)ppGpp in bacterial physiology , 2015, Nature Reviews Microbiology.

[34]  Benjamin J. Raphael,et al.  Visible Machine Learning for Biomedicine , 2018, Cell.

[35]  Jason H. Yang,et al.  Lethality of MalE-LacZ hybrid protein shares mechanistic attributes with oxidative component of antibiotic lethality , 2017, Proceedings of the National Academy of Sciences.

[36]  N. Reinsch,et al.  On the Road to Maturity , 1997 .

[37]  C. Sassetti,et al.  Metabolic Regulation of Mycobacterial Growth and Antibiotic Sensitivity , 2011, PLoS biology.

[38]  Jinming Li,et al.  mNGS in clinical microbiology laboratories: on the road to maturity , 2019, Critical reviews in microbiology.

[39]  M. Maiden,et al.  Horizontal genetic exchange, evolution, and spread of antibiotic resistance in bacteria. , 1998, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[40]  D. Clayton,et al.  Purine Biosynthesis Metabolically Constrains Intracellular Survival of Uropathogenic Escherichia coli , 2016, Infection and Immunity.

[41]  Jason H. Yang,et al.  Antibiotic efficacy-context matters. , 2017, Current opinion in microbiology.

[42]  B. Spira,et al.  Diversity in E. coli (p)ppGpp Levels and Its Consequences , 2020, Frontiers in Microbiology.

[43]  Ofer Fridman,et al.  Distinguishing between resistance, tolerance and persistence to antibiotic treatment , 2016, Nature Reviews Microbiology.

[44]  E. Pålsson-McDermott,et al.  Targeting immunometabolism as an anti-inflammatory strategy , 2020, Cell Research.

[45]  D. Andersson,et al.  Evolutionary Trajectories to Antibiotic Resistance. , 2017, Annual review of microbiology.

[46]  Emma J. Chory,et al.  A Deep Learning Approach to Antibiotic Discovery , 2020, Cell.

[47]  B. Kégl,et al.  Genome-wide analysis captures the determinants of the antibiotic cross-resistance interaction network , 2014, Nature Communications.

[48]  M. Webber,et al.  Molecular mechanisms of antibiotic resistance , 2014, Nature Reviews Microbiology.

[49]  Jamey D. Young,et al.  Host nutrient milieu drives an essential role for aspartate biosynthesis during invasive Staphylococcus aureus infection , 2020, Proceedings of the National Academy of Sciences.

[50]  D. Sherman,et al.  ODELAM, rapid sequence-independent detection of drug resistance in isolates of Mycobacterium tuberculosis , 2020, eLife.

[51]  E. Driggers,et al.  The Untapped Opportunity and Challenge of Immunometabolism: A New Paradigm for Drug Discovery. , 2019, Cell metabolism.

[52]  R. Corrigan,et al.  The stringent response and physiological roles of (pp)pGpp in bacteria , 2020, Nature Reviews Microbiology.

[53]  M. Laub,et al.  Affinity-based capture and identification of protein effectors of the growth regulator ppGpp , 2018, Nature Chemical Biology.

[54]  A. L. Koch,et al.  The purine metabolism of Escherichia coli. , 1952, Journal of Biological Chemistry.

[55]  U. Sauer,et al.  Nontargeted Metabolomics Reveals the Multilevel Response to Antibiotic Perturbations. , 2017, Cell reports.

[56]  Guo-Ping Zhao,et al.  Oxidation of dCTP contributes to antibiotic lethality in stationary-phase mycobacteria , 2018, Proceedings of the National Academy of Sciences.

[57]  Daniel J. Wilson,et al.  Transforming clinical microbiology with bacterial genome sequencing , 2012, Nature Reviews Genetics.

[58]  John L. Johnson,et al.  Bacterial Factors That Predict Relapse after Tuberculosis Therapy , 2018, The New England journal of medicine.

[59]  Irine Ronin,et al.  Effect of tolerance on the evolution of antibiotic resistance under drug combinations , 2020, Science.

[60]  James J Foti,et al.  Oxidation of the Guanine Nucleotide Pool Underlies Cell Death by Bactericidal Antibiotics , 2012, Science.

[61]  Kenneth P Smith,et al.  Image analysis and artificial intelligence in infectious disease diagnostics. , 2020, Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases.

[62]  Liping Li,et al.  Contribution of Reactive Oxygen Species to Thymineless Death in Escherichia coli , 2017, Nature Microbiology.

[63]  A. Mankin,et al.  Nucleotide Biosynthesis Is Critical for Growth of Bacteria in Human Blood , 2008, PLoS pathogens.

[64]  Ahmad S Khalil,et al.  Antibiotics induce redox-related physiological alterations as part of their lethality. , 2014, Proceedings of the National Academy of Sciences of the United States of America.

[65]  Kai Zhou,et al.  Application of next generation sequencing in clinical microbiology and infection prevention. , 2017, Journal of biotechnology.

[66]  J. Adkins,et al.  Stochastic Variation in Expression of the Tricarboxylic Acid Cycle Produces Persister Cells , 2019, mBio.

[67]  Jonathan M. Monk Predicting Antimicrobial Resistance and Associated Genomic Features from Whole-Genome Sequencing , 2018, Journal of Clinical Microbiology.

[68]  J. Collins,et al.  Predictive biology: modelling, understanding and harnessing microbial complexity , 2020, Nature Reviews Microbiology.

[69]  Amy K. Cain,et al.  A decade of advances in transposon-insertion sequencing , 2020, Nature Reviews Genetics.

[70]  C. Nathan,et al.  Biology of antimicrobial resistance and approaches to combat it , 2020, Science Translational Medicine.

[71]  Eric D. Kelsic,et al.  Spatiotemporal microbial evolution on antibiotic landscapes , 2016, Science.

[72]  J. Collins,et al.  A Common Mechanism of Cellular Death Induced by Bactericidal Antibiotics , 2007, Cell.

[73]  B. Zhao,et al.  Clinically prevalent mutations in Mycobacterium tuberculosis alter propionate metabolism and mediate multidrug tolerance , 2018, Nature Microbiology.

[74]  J. Gots,et al.  The purine and pyrimidine metabolism of normal and phage-infected Escherichia coli. , 1953, The Journal of biological chemistry.

[75]  Trevor Bedford,et al.  Nextstrain: real-time tracking of pathogen evolution , 2017, bioRxiv.

[76]  Edward J. O'Brien,et al.  Using Genome-scale Models to Predict Biological Capabilities , 2015, Cell.

[77]  Xilin Zhao,et al.  Reactive oxygen species and the bacterial response to lethal stress. , 2014, Current opinion in microbiology.

[78]  Sang-Nae Cho,et al.  Transient drug-tolerance and permanent drug-resistance rely on the trehalose-catalytic shift in Mycobacterium tuberculosis , 2019, Nature Communications.

[79]  Yuan Liu,et al.  Thymine Sensitizes Gram-Negative Pathogens to Antibiotic Killing , 2021, Frontiers in Microbiology.

[80]  Hannah R. Meredith,et al.  Applying ecological resistance and resilience to dissect bacterial antibiotic responses , 2018, Science Advances.

[81]  Shaohua Zhao,et al.  Using machine learning to predict antimicrobial minimum inhibitory concentrations and associated genomic features for nontyphoidal Salmonella , 2018, bioRxiv.

[82]  Saloni R. Jain,et al.  Understanding and Sensitizing Density-Dependent Persistence to Quinolone Antibiotics. , 2017, Molecular cell.

[83]  Stephanie M. Amato,et al.  Metabolic control of persister formation in Escherichia coli. , 2013, Molecular cell.

[84]  K. Lewis,et al.  ATP-Dependent Persister Formation in Escherichia coli , 2017, mBio.

[85]  C. Walsh,et al.  Eight Kinetically Stable but Thermodynamically Activated Molecules that Power Cell Metabolism. , 2017, Chemical reviews.

[86]  I. Chopra,et al.  Plasmid-mediated tetracycline resistance in Escherichia coli involves increased efflux of the antibiotic. , 1980, Biochemical and biophysical research communications.

[87]  W. Shi,et al.  Genetic Screen Reveals the Role of Purine Metabolism in Staphylococcus aureus Persistence to Rifampicin , 2015, Antibiotics.

[88]  U. Sauer,et al.  High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds , 2018, Science Translational Medicine.