Abstract

Forsomethingascomplexandmultifacetedasbacterialantibioticresistance(AR),ourdrugevaluation paradigmisstrikinglynarrowandhomogenous:MIC/MBCtestinginstandardizedbacteriologicmedia.We haveshownthatthisdrugevaluationparadigmisinadequate,evenmisleading,aschangesinthemedia conditionsoftheprocedureleadtodramaticallydifferentresults.Amoreholisticdefinitionofantibiotictherapy thatcentersonunderstandingantibioticactivityinsynergywithhostinnateimmunefactorssuchascationic antimicrobialpeptides(AMPs),serumandphagocyticcells(e.g.neutrophils)revealstherapeuticoptions unrecognizedinstandardtesting.TheproposedU01programrepresentsagroundbreakingapproachtouse systemsbiologyapproachesandinformmoreeffectiveantibioticutilizationinthecontextofhostinnate immunity.Weproposeto:1)buildaniterativesystemsbiologyworkflowthatintegratesmultipleexperimental andcomputationalapproachestogiveacomprehensiveassessmentofAR?and2)applythisworkflowtohigh prioritypathogenstosystematicallyelucidateARmechanismsandtheirconditiondependency.Theiterative workflowincludes:(i)omicsandphysiologicaldatageneration.Clinicallyisolatedstrainsoftheselected pathogenswillbegrownunderconventionaltesting(bacteriologicmedia)andmorephysiologicconditions (tissueculturemedia,serum,andinpresenceofAMPsandneutrophils)toprobeforadvantageousgainof activity.Theomicsdatatypescollectedare:DNAresequencing,RNAseq,andmetabolomics.(ii) Bioinformaticsanddatamodelinganalysisinvolvesthreeapproaches:bigdataanalysisfordataset dimensionalityandcoarsegrainedvariabledependenciesassessment,genomescalemodelingfor mechanisticelucidationandanalysis,andmachinelearningthatusesARrelatedmetadatatoclassifythe overallbiologicalfunctions.ThisanalysiswillleadtounderstandingofARmechanisms.(iii)Multiscale validationfromanimalmodels,tolaboratoryevolution,tocytology,togeneexpressionalteration,tostructural proteinanalysisofputativetargets.Thevalidationthusrangesfromhostbehaviortoatomisticdetailof ligandtargetinteractions.Theiterativeloopthencloses,comparingcomputationalpredictiontoexperimental outcomes.Falsenegativeandfalsepositivepredictionsarethenalgorithmicallyanalyzedbyahypothesis generatingfamilyofalgorithmsthatthenmakessuggestionsaboutwhatconditionstouseinthenextiteration oftheloop.Thepathogensthatwewillfocusonaremethicillinresistant?Staphylococcusaureus?(MRSA),the carbapenemresistantEnterobacteriaceae(CRE)Klebsiella?pneumoniae?and?Acinetobacterbaumannii,?and Pseudomonasaeruginosa?.Theteamofinvestigatorshasmadethefoundationalobservationsandledthe developmentofthetechnologiesonwhichtheiterativeworkflowisbased.Amultiandgenomescalemethods ofsystemsbiologyfulfillsrequirementsofRFAAI14064towhichitresponds.

Public Health Relevance

Thecurrentevaluationofantibioticdrugcandidatesindrugdiscoveryandinclinicalmedicineisconductedin laboratorymediathatignorestheactualphysiologicconditionsinthehostandthehostimmunesystem.We havediscoveredpotentantimicrobialactivitiesofexistingantibioticsagainsthighly?drugresistantsuperbugs? thatarecurrentlyignoredbutrevealedinsynergywiththehumanimmunesystem.Thisprogramproposesa holisticandcomprehensivesystemsbiologyapproachtosystematicallydiscovernoveltreatmentopportunities andunderlyingmechanismsusinganoveliterativedatageneration,analysis,andmodelingworkflow.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01AI124316-01
Application #
9108693
Study Section
Special Emphasis Panel (ZAI1-EC-M (J1))
Program Officer
Dugan, Vivien G
Project Start
2016-03-15
Project End
2021-02-28
Budget Start
2016-03-15
Budget End
2017-02-28
Support Year
1
Fiscal Year
2016
Total Cost
$1,989,374
Indirect Cost
$615,465

  Institution

Name
University of California San Diego
Department
Pediatrics
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093

  Publications

Norsigian, Charles J; Kavvas, Erol; Seif, Yara et al. (2018) iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE. Front Genet 9:121
Kumaraswamy, Monika; Do, Carter; Sakoulas, George et al. (2018) Listeria monocytogenes endocarditis: case report, review of the literature, and laboratory evaluation of potential novel antibiotic synergies. Int J Antimicrob Agents 51:468-478
Askarian, Fatemeh; Wagner, Theresa; Johannessen, Mona et al. (2018) Staphylococcus aureus modulation of innate immune responses through Toll-like (TLR), (NOD)-like (NLR) and C-type lectin (CLR) receptors. FEMS Microbiol Rev 42:656-671
Askarian, Fatemeh; Lapek Jr, John D; Dongre, Mitesh et al. (2018) Staphylococcus aureus Membrane-Derived Vesicles Promote Bacterial Virulence and Confer Protective Immunity in Murine Infection Models. Front Microbiol 9:262
Quinn, Robert A; Comstock, William; Zhang, Tianyu et al. (2018) Niche partitioning of a pathogenic microbiome driven by chemical gradients. Sci Adv 4:eaau1908
Kavvas, Erol S; Seif, Yara; Yurkovich, James T et al. (2018) Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions. BMC Syst Biol 12:25
Fang, Xin; Monk, Jonathan M; Nurk, Sergey et al. (2018) Metagenomics-Based, Strain-Level Analysis of Escherichia coli From a Time-Series of Microbiome Samples From a Crohn's Disease Patient. Front Microbiol 9:2559
Kavvas, Erol S; Catoiu, Edward; Mih, Nathan et al. (2018) Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance. Nat Commun 9:4306
Choudhary, Kumari S; Mih, Nathan; Monk, Jonathan et al. (2018) The Staphylococcus aureus Two-Component System AgrAC Displays Four Distinct Genomic Arrangements That Delineate Genomic Virulence Factor Signatures. Front Microbiol 9:1082
Fang, Xin; Monk, Jonathan M; Mih, Nathan et al. (2018) Escherichia coli B2 strains prevalent in inflammatory bowel disease patients have distinct metabolic capabilities that enable colonization of intestinal mucosa. BMC Syst Biol 12:66

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