Jonathan Monk, Ph.D.

Publications

94 publications

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2026

  1. Investigating Azithromycin Activity Against ESBL-Producing Escherichia coli Under Physiologically Relevant Conditions

    Jung, Dahesh, Bjånes, Monk, Chavarria, Correa, Hoffman, Gage, Nizet, Kumaraswamy

    The Journal of Infectious Diseases

  2. Structure of the Enterobacter pan-genome is revealed using machine learning

    Burrows, Li, Monk, Chauhan, Palsson

    Microbiology Spectrum

2025

  1. A metabolic atlas of the Klebsiella pneumoniae species complex reveals lineage-specific metabolism and capacity for intra-species co-operation

    Vezina, Cooper, Barlow, Rethoret-Pasty, Brisse, Monk, Holt, Wyres

    PLOS Biology

  2. Colistin exerts potent activity against mcr+ Enterobacteriaceae via synergistic interactions with the host defense

    Kumaraswamy, Riestra, Flores, Dahesh, Askarian, Uchiyama, Monk, Jung, Bondsäter, Nilsson, Chang, Bulitta, Lang, Kousha, Bjånes, Chavarria, Clark, Seo, Sakoulas, Nizet

    Journal of Clinical Investigation

  3. Decomposition of the pangenome matrix reveals a structure in gene distribution in the Escherichia coli species

    Chauhan, Ardalani, Hyun, Monk, Phaneuf, Palsson

    mSphere

  4. Interpreting roles of mutations associated with the emergence of S. aureus USA300 strains using transcriptional regulatory network reconstruction

    Poudel, Hyun, Hefner, Monk, Nizet, Palsson

    eLife

  5. Multi-strain Analysis of Pseudomonas putida Reveals the Metabolic and Genetic Diversity of the Species

    Mueller, Krishnan, Wei, Hefner, Monk, Verkler, Tibocha-Bonilla, Ayala, Palsson, Feist, Niu

  6. PMkbase (version 1.0): an interactive web-based tool for tracking bacterial metabolic traits using phenotype microarrays made interoperable with sequence information and visualizing/processing PM data

    Krishnan, Hefner, Szubin, Monk, Pride, Palsson

    Microbiology Spectrum

  7. Rare metabolic gene essentiality is a determinant of microniche adaptation in Eschherichia coli

    Ardalani, Phaneuf, Krishnan, Chauhan, Pride, Zielinski, Monk, Nielsen, Palsson

    PLOS Pathogens

2024

  1. A validated pangenome-scale metabolic model for the Klebsiella pneumoniae species complex

    Cooper, Vezina, Hawkey, Passet, López-Fernández, Monk, Brisse, Holt, Wyres

    Microbial Genomics

  2. CyuR is a dual regulator for L-cysteine dependent antimicrobial resistance in Escherichia coli

    Rodionova, Lim, Gao, Rodionov, Hutchison, Szubin, Dalldorf, Monk, Palsson

    Communications Biology

2023

  1. Bactabolize: A tool for high-throughput generation of bacterial strain-specific metabolic models

    Vezina, Watts, Hawkey, Cooper, Judd, Jenney, Monk, Holt, Wyres

  2. Comprehensive whole genome sequencing with hybrid assembly of multi-drug resistant Candida albicans isolate causing cerebral abscess

    Kumaraswamy, Coady, Szubin, Martin, Palsson, Nizet, Monk

    Current Research in Microbial Sciences

  3. Global pathogenomic analysis identifies known and novel genetic antimicrobial resistance determinants in twelve species

    Hyun, Monk, Szubin, Hefner, Palsson

  4. Historical biomonitoring of pollution trends in the North Pacific using archived samples from the Continuous Plankton Recorder Survey

    Li, Naviaux, Lingampelly, Wang, Monk, Taylor, Ostle, Batten, Naviaux

    Science of The Total Environment

  5. Metabolic features of treatment-refractory major depressive disorder with suicidal ideation

    Pan, Naviaux, Wang, Li, Monk, Lingampelly, Segreti, Bloom, Vockley, Tarnopolsky, Finegold, Peters, Naviaux

    Translational Psychiatry

  6. Metabolomic and exposomic biomarkers of risk of future neurodevelopmental delay in human milk

    Li, Bertrand, Naviaux, Monk, Wells, Wang, Lingampelly, Naviaux, Chambers

    Pediatric Research

  7. Rev1 deficiency induces a metabolic shift in MEFs that can be manipulated by the NAD+ precursor nicotinamide riboside

    Anugula, Li, Li, Hendriksen, Christensen, Wang, Monk, de Wind, Bohr, Desler, Naviaux, Rasmussen

    Heliyon

  8. Whole-genome sequences from wild-type and laboratory-evolved strains define the alleleome and establish its hallmarks

    Catoiu, Phaneuf, Monk, Palsson

    Proceedings of the National Academy of Sciences

2022

  1. A curated collection of Klebsiella metabolic models reveals variable substrate usage and gene essentiality

    Hawkey, Vezina, Monk, Judd, Harshegyi, López-Fernández, Rodrigues, Brisse, Holt, Wyres

    Genome Research

  2. Cerebrospinal fluid and plasma metabolomics of acute endurance exercise

    Li, Schön, Naviaux, Monk, Alchus‐Laiferová, Wang, Straka, Matejička, Valkovič, Ukropec, Tarnopolsky, Naviaux, Ukropcová

    The FASEB Journal

  3. Comparative pangenomics: analysis of 12 microbial pathogen pangenomes reveals conserved global structures of genetic and functional diversity

    Hyun, Monk, Palsson

    BMC Genomics

  4. Estimated Roles of the Carrier and the Bacterial Strain When Methicillin-Resistant Staphylococcus aureus Decolonization Fails: a Case-Control Study

    Holm, Jørgensen, Bagge, Worning, Pedersen, Westh, Monk, Bartels

    Microbiology Spectrum

  5. Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes

    Kavvas, Long, Sastry, Poudel, Antoniewicz, Ding, Mohamed, Szubin, Monk, Feist, Palsson

    mSystems

  6. Genome-scale metabolic network reconstructions of diverse Escherichia strains reveal strain-specific adaptations

    Monk

    Philosophical Transactions of the Royal Society B

  7. High-quality genome-scale metabolic network reconstruction of probiotic bacterium Escherichia coli Nissle 1917

    van ‘t Hof, Mohite, Monk, Weber, Palsson, Sommer

    BMC Bioinformatics

  8. Mathematical models to study the biology of pathogens and the infectious diseases they cause

    Xavier, Monk, Poudel, Norsigian, Sastry, Liao, Bento, Suchard, Arrieta-Ortiz, Peterson, Baliga, Stoeger, Ruffin, Richardson, Gao, Horvath, Haag, Wu, Savidge, Yeaman

    iScience

  9. Pangenome analysis of Enterobacteria reveals richness of secondary metabolite gene clusters and their associated gene sets

    Mohite, Lloyd, Monk, Weber, Palsson

    Synthetic and Systems Biotechnology

  10. Systems biology approach to functionally assess the Clostridioides difficile pangenome reveals genetic diversity with discriminatory power

    Norsigian, Danhof, Brand, Midani, Broddrick, Savidge, Britton, Palsson, Spinler, Monk

    Proceedings of the National Academy of Sciences

  11. Transmission of Klebsiella strains and plasmids within and between grey‐headed flying fox colonies

    Vezina, Judd, McDougall, Boardman, Power, Hawkey, Brisse, Monk, Holt, Wyres

    Environmental Microbiology

2021

  1. A Systems Approach Discovers the Role and Characteristics of Seven LysR Type Transcription Factors in Escherichia Coli

    Rodionova, Palsson, Gao, Wong, Szubin, Lim, Rodionov, Zhang, Saier

  2. Experimentally Validated Reconstruction and Analysis of a Genome-Scale Metabolic Model of an Anaerobic Neocallimastigomycota Fungus

    Wilken, Monk, Leggieri, Lawson, Lankiewicz, Seppälä, Daum, Jenkins, Lipzen, Mondo, Barry, Grigoriev, Henske, Theodorou, Palsson, Petzold, O’Malley

    mSystems

  3. Genome‐scale metabolic modeling reveals key features of a minimal gene set

    Lachance, Matteau, Brodeur, Lloyd, Mih, King, Knight, Feist, Monk, Palsson, Jacques, Rodrigue

    Molecular Systems Biology

  4. Identifying the effect of vancomycin on health care–associated methicillin-resistant Staphylococcus aureus strains using bacteriological and physiological media

    Rajput, Poudel, Tsunemoto, Meehan, Szubin, Olson, Seif, Lamsa, Dillon, Vrbanac, Sugie, Dahesh, Monk, Dorrestein, Knight, Pogliano, Nizet, Feist, Palsson

    GigaScience

  5. Metabolic and behavioral features of acute hyperpurinergia and the maternal immune activation mouse model of autism spectrum disorder

    Zolkipli-Cunningham, Naviaux, Nakayama, Hirsch, Monk, Li, Wang, Le, Meinardi, Blake, Naviaux

    PLOS ONE

  6. Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence

    Mocking, Naviaux, Li, Wang, Monk, Bright, Figueroa, Schene, Ruhé, Assies, Naviaux

    Translational Psychiatry

  7. Rapid resistance development to three antistaphylococcal therapies in antibiotic-tolerant staphylococcus aureus bacteremia

    Miller, Monk, Szubin, Berti

    PLOS ONE

2020

  1. A biochemically-interpretable machine learning classifier for microbial GWAS

    Kavvas, Yang, Monk, Heckmann, Palsson

    Nature Communications

  2. A workflow for generating multi-strain genome-scale metabolic models of prokaryotes

    Norsigian, Fang, Seif, Monk, Palsson

    Nature Protocols

  3. Adaptations of Escherichia coli strains to oxidative stress are reflected in properties of their structural proteomes

    Mih, Monk, Fang, Catoiu, Heckmann, Yang, Palsson

    BMC Bioinformatics

  4. Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

    Lloyd, Monk, Yang, Ebrahim, Palsson

  5. Genome-Scale Metabolic Model of Xanthomonas phaseoli pv. manihotis: An Approach to Elucidate Pathogenicity at the Metabolic Level

    Botero, Monk, Rodríguez Cubillos, Rodríguez Cubillos, Restrepo, Bernal-Galeano, Reyes, González Barrios, Palsson, Restrepo, Bernal

    Frontiers in Genetics

  6. High-Quality Genome-Scale Models From Error-Prone, Long-Read Assemblies

    Broddrick, Szubin, Norsigian, Monk, Palsson, Parenteau

    Frontiers in Microbiology

  7. High‐quality genome‐scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities

    Nogales, Mueller, Gudmundsson, Canalejo, Duque, Monk, Feist, Ramos, Niu, Palsson

    Environmental Microbiology

  8. Impact of insertion sequences on convergent evolution of Shigella species

    Hawkey, Monk, Billman-Jacobe, Palsson, Holt

    PLOS Genetics

  9. Improved Dried Blood Spot-Based Metabolomics: A Targeted, Broad-Spectrum, Single-Injection Method

    Li, Naviaux, Monk, Wang, Naviaux

    Metabolites

  10. MEMOTE for standardized genome-scale metabolic model testing

    Lieven, Beber, Olivier, Bergmann, Ataman, Babaei, Bartell, Blank, Chauhan, Correia, Diener, Dräger, Ebert, Edirisinghe, Faria, Feist, Fengos, Fleming, García-Jiménez, Hatzimanikatis, van Helvoirt, Henry, Hermjakob, Herrgård, Kaafarani, Kim, King, Klamt, Klipp, Koehorst, König, Lakshmanan, Lee, Lee, Lee, Lewis, Liu, Ma, Machado, Mahadevan, Maia, Mardinoglu, Medlock, Monk, Nielsen, Nielsen, Nogales, Nookaew, Palsson, Papin, Patil, Poolman, Price, Resendis-Antonio, Richelle, Rocha, Sánchez, Schaap, Malik Sheriff, Shoaie, Sonnenschein, Teusink, Vilaça, Vik, Wodke, Xavier, Yuan, Zakhartsev, Zhang

    Nature Biotechnology

  11. Machine learning with random subspace ensembles identifies antimicrobial resistance determinants from pan-genomes of three pathogens

    Hyun, Kavvas, Monk, Palsson

    PLOS Computational Biology

  12. Machine learning with random subspace ensembles identifies antimicrobial resistance determinants from pan-genomes of three pathogens

    Hyun, Kavvas, Monk, Palsson

    PLOS Computational Biology

  13. Metabolic and Behavioral Features of Acute Hyperpurinergia and the Connection to Autism Spectrum Disorder

    Zolkipli-Cunningham, Naviaux, Nakayama, Hirsch, Monk, Li, Wang, Le, Meinardi, Blake, Naviaux

  14. Pangenome analytics reveal two-component systems as conserved targets in ESKAPEE pathogens

    Rajput, Seif, Choudhary, Dalldorf, Poudel, Monk, Palsson

  15. Reconstruction and Validation of a Genome-Scale Metabolic Model of Streptococcus oralis (iCJ415), a Human Commensal and Opportunistic Pathogen

    Jensen, Norsigian, Fang, Nielsen, Christensen, Palsson, Monk

    Frontiers in Genetics

  16. Systems biology analysis of the Clostridioides difficile core-genome contextualizes microenvironmental evolutionary pressures leading to genotypic and phenotypic divergence

    Norsigian, Danhof, Brand, Oezguen, Midani, Palsson, Savidge, Britton, Spinler, Monk

    npj Systems Biology and Applications

2019

  1. 596. Distinct, Segregated Daptomycin-Susceptible and Daptomycin-Nonsusceptible Staphylococcus aureus Populations Associated with Tricuspid-Valve Infective Endocarditis

    Miller, Dey, Smolenski, Kulkarni, Sakoulas, Monk, Szubin, David. Berti

    Open Forum Infectious Diseases

  2. A computational knowledge-base elucidates the response of Staphylococcus aureus to different media types

    Seif, Monk, Mih, Tsunemoto, Poudel, Zuniga, Broddrick, Zengler, Palsson

    PLOS Computational Biology

  3. BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data

    Lachance, Lloyd, Monk, Yang, Sastry, Seif, Palsson, Rodrigue, Feist, King, Jacques

    PLOS Computational Biology

  4. Cellular responses to reactive oxygen species are predicted from molecular mechanisms

    Yang, Mih, Anand, Park, Tan, Yurkovich, Monk, Lloyd, Sandberg, Seo, Kim, Sastry, Phaneuf, Gao, Broddrick, Chen, Heckmann, Szubin, Hefner, Feist, Palsson

    Proceedings of the National Academy of Sciences

  5. Characterization of CA-MRSA TCH1516 exposed to nafcillin in bacteriological and physiological media

    Poudel, Tsunemoto, Meehan, Szubin, Olson, Lamsa, Seif, Dillon, Vrbanac, Sugie, Dahesh, Monk, Dorrestein, Pogliano, Knight, Nizet, Palsson, Feist

    Scientific Data

  6. Comparative Genome-Scale Metabolic Modeling of Metallo-Beta-Lactamase–Producing Multidrug-Resistant Klebsiella pneumoniae Clinical Isolates

    Norsigian, Attia, Szubin, Yassin, Palsson, Aziz, Monk

    Frontiers in Cellular and Infection Microbiology

  7. Metabolic features of Gulf War illness

    Naviaux, Naviaux, Li, Wang, Monk, Bright, Koslik, Ritchie, Golomb

    PLOS ONE

  8. Profiling the effect of nafcillin on HA-MRSA D712 using bacteriological and physiological media

    Rajput, Poudel, Tsunemoto, Meehan, Szubin, Olson, Lamsa, Seif, Dillon, Vrbanac, Sugie, Dahesh, Monk, Dorrestein, Knight, Nizet, Palsson, Feist, Pogliano

    Scientific Data

  9. Reduced Production of Bacterial Membrane Vesicles Predicts Mortality in ST45/USA600 Methicillin-Resistant Staphylococcus aureus Bacteremia

    Dey, Gudipati, Giuliano, Zervos, Monk, Szubin, Jorgensen, Sakoulas, Berti

    Antibiotics

  10. SMAD3 directly regulates cell cycle genes to maintain arrest in granulosa cells of mouse primordial follicles

    Granados-Aparici, Hardy, Franks, Sharum, Waite, Fenwick

    Scientific reports

  11. Strain-Specific Metabolic Requirements Revealed by a Defined Minimal Medium for Systems Analyses of Staphylococcus aureus

    Machado, Weng, Dillon, Seif, Holland, Pekar, Monk, Nizet, Palsson, Feist

    Applied and Environmental Microbiology

  12. Systems Biology and Pangenome of Salmonella O-Antigens

    Seif, Monk, Machado, Kavvas, Palsson

    mBio

  13. Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection

    Yan, Estanbouli, Liao, Kim, Monk, Rahman, Kamboj, Palsson, Qiu, Xavier

    PLOS Computational Biology

  14. Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal Salmonella

    Nguyen, Long, McDermott, Olsen, Olson, Stevens, Tyson, Zhao, Davis

    Journal of Clinical Microbiology

2018

  1. Escherichia coli B2 strains prevalent in inflammatory bowel disease patients have distinct metabolic capabilities that enable colonization of intestinal mucosa

    Fang, Monk, Mih, Du, Sastry, Kavvas, Seif, Smarr, Palsson

    BMC Systems Biology

  2. Gapless, Unambiguous Genome Sequence for Escherichia coli C, a Workhorse of Industrial Biology

    Pekar, Phaneuf, Szubin, Palsson, Feist, Monk

    Microbiology Resource Announcements

  3. Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits

    Seif, Kavvas, Lachance, Yurkovich, Nuccio, Fang, Catoiu, Raffatellu, Palsson, Monk

    Nature Communications

  4. Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

    Kavvas, Catoiu, Mih, Yurkovich, Seif, Dillon, Heckmann, Anand, Yang, Nizet, Monk, Palsson

    Nature Communications

  5. Metagenomics-Based, Strain-Level Analysis of Escherichia coli From a Time-Series of Microbiome Samples From a Crohn's Disease Patient

    Fang, Monk, Nurk, Akseshina, Zhu, Gemmell, Gianetto-Hill, Leung, Szubin, Sanders, Beck, Li, Sandborn, Gray-Owen, Knight, Allen-Vercoe, Palsson, Smarr

    Frontiers in Microbiology

  6. The Staphylococcus aureus Two-Component System AgrAC Displays Four Distinct Genomic Arrangements That Delineate Genomic Virulence Factor Signatures

    Choudhary, Mih, Monk, Kavvas, Yurkovich, Sakoulas, Palsson

    Frontiers in Microbiology

  7. Thermodynamic favorability and pathway yield as evolutionary tradeoffs in biosynthetic pathway choice

    Du, Zielinski, Monk, Palsson

    Proceedings of the National Academy of Sciences

  8. Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

    Kavvas, Seif, Yurkovich, Norsigian, Poudel, Greenwald, Ghatak, Palsson, Monk

    BMC Systems Biology

  9. iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE

    Norsigian, Kavvas, Seif, Palsson, Monk

    Frontiers in Genetics

2017

  1. Machine learning in computational biology to accelerate high-throughput protein expression

    Sastry, Monk, Tegel, Uhlen, Palsson, Rockberg, Brunk

    Bioinformatics

  2. The aldehyde dehydrogenase, AldA, is essential for L-1,2-propanediol utilization in laboratory-evolved Escherichia coli

    Aziz, Monk, Andrews, Nhan, Khaw, Wong, Palsson, Charusanti

    Microbiological Research

  3. iML1515, a knowledgebase that computes Escherichia coli traits

    Monk, Lloyd, Brunk, Mih, Sastry, King, Takeuchi, Nomura, Zhang, Mori, Feist, Palsson

    Nature Biotechnology

  4. ssbio: A Python Framework for Structural Systems Biology

    Mih, Brunk, Chen, Catoiu, Sastry, Kavvas, Monk, Zhang, Palsson

2016

  1. Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

    Brunk, George, Alonso-Gutierrez, Thompson, Baidoo, Wang, Petzold, McCloskey, Monk, Yang, O’Brien, Batth, Martin, Feist, Adams, Keasling, Palsson, Lee

    Cell Systems

  2. Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity

    Bosi, Monk, Aziz, Fondi, Nizet, Palsson

    Proceedings of the National Academy of Sciences

  3. Multi-omics Quantification of Species Variation of Escherichia coli Links Molecular Features with Strain Phenotypes

    Monk, Koza, Campodonico, Machado, Seoane, Palsson, Herrgård, Feist

    Cell Systems

  4. Systems biology of the structural proteome

    Brunk, Mih, Monk, Zhang, O’Brien, Bliven, Chen, Chang, Bourne, Palsson

    BMC Systems Biology

  5. What Makes a Bacterial Species Pathogenic?:Comparative Genomic Analysis of the Genus Leptospira

    Fouts, Matthias, Adhikarla, Adler, Amorim-Santos, Berg, Bulach, Buschiazzo, Chang, Galloway, Haake, Haft, Hartskeerl, Ko, Levett, Matsunaga, Mechaly, Monk, Nascimento, Nelson, Palsson, Peacock, Picardeau, Ricaldi, Thaipandungpanit, Wunder, Yang, Zhang, Vinetz

    PLOS Neglected Tropical Diseases

2015

  1. Model-driven discovery of synergistic inhibitors against E. coli and S. enterica serovar Typhimurium targeting a novel synthetic lethal pair, aldA and prpC

    Aziz, Khaw, Monk, Brunk, Lewis, Loh, Mishra, Nagle, Satyanarayana, Dhakshinamoorthy, Luche, Kitchen, Andrews, Palsson, Charusanti

    Frontiers in Microbiology

  2. Model-driven discovery of underground metabolic functions in Escherichia coli

    Guzmán, Utrilla, Nurk, Brunk, Monk, Ebrahim, Palsson, Feist

    Proceedings of the National Academy of Sciences

  3. Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data

    Yang, Tan, O’Brien, Monk, Kim, Li, Charusanti, Ebrahim, Lloyd, Yurkovich, Du, Dräger, Thomas, Sun, Saunders, Palsson

    Proceedings of the National Academy of Sciences

  4. Using Genome-scale Models to Predict Biological Capabilities

    O’Brien, Monk, Palsson

    Cell

2014

  1. Constraint-based models predict metabolic and associated cellular functions

    Bordbar, Monk, King, Palsson

    Nature Reviews Genetics

  2. Optimizing genome-scale network reconstructions

    Monk, Nogales, Palsson

    Nature Biotechnology

  3. Predicting microbial growth

    Monk, Palsson

    Science

2013

  1. Genome-scale metabolic reconstructions of multiple Escherichia coli strains highlight strain-specific adaptations to nutritional environments

    Monk, Charusanti, Aziz, Lerman, Premyodhin, Orth, Feist, Palsson

    Proceedings of the National Academy of Sciences

2011

  1. Wdr5 Mediates Self-Renewal and Reprogramming via the Embryonic Stem Cell Core Transcriptional Network

    Ang, Tsai, Lee, Monk, Su, Ratnakumar, Ding, Ge, Darr, Chang, Wang, Rendl, Bernstein, Schaniel, Lemischka

    Cell