State of the art
Genomic and Metagenomic Approaches for Predictive Surveillance of Emerging Pathogens and Antibiotic Resistance
Kimberley V. Sukhum,
Luke Diorio-Toth,
Gautam Dantas,
Kimberley V. Sukhum
The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
These authors contributed equally to this work.Search for more papers by this authorLuke Diorio-Toth
The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
These authors contributed equally to this work.Search for more papers by this authorCorresponding Author
Gautam Dantas
The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
Department of Molecular Microbiology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Correspondence: Gautam Dantas ([email protected])Search for more papers by this author
Kimberley V. Sukhum,
Luke Diorio-Toth,
Gautam Dantas,
Kimberley V. Sukhum
The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
These authors contributed equally to this work.Search for more papers by this authorLuke Diorio-Toth
The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
These authors contributed equally to this work.Search for more papers by this authorCorresponding Author
Gautam Dantas
The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
Department of Molecular Microbiology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Correspondence: Gautam Dantas ([email protected])Search for more papers by this authorAbstract
Antibiotic-resistant organisms (AROs) are a major concern to public health worldwide. While antibiotics have been naturally produced by environmental bacteria for millions of years, modern widespread use of antibiotics has enriched resistance mechanisms in human-impacted bacterial environments. Antibiotic resistance genes (ARGs) continue to emerge and spread rapidly. To combat the global threat of antibiotic resistance, researchers must develop methods to rapidly characterize AROs and ARGs, monitor their spread across space and time, and identify novel ARGs and resistance pathways. We review how high-throughput sequencing-based methods can be combined with classic culture-based assays to characterize, monitor, and track AROs and ARGs. Then, we evaluate genomic and metagenomic methods for identifying ARGs and biosynthetic pathways for novel antibiotics from genomic data sets. Together, these genomic analyses can improve surveillance and prediction of emerging resistance threats and accelerate the development of new antibiotic therapies to combat resistance.
Conflict of Interest
The authors declared no competing interests for this work.
References
- 1Aminov, R.I. A brief history of the antibiotic era: lessons learned and challenges for the future. Front. Microbiol. 1, 134 (2010).
- 2Brown, E.D. & Wright, G.D. Antibacterial drug discovery in the resistance era. Nature 529, 336–343 (2016).
- 3Adu-Oppong, B., Gasparrini, A.J. & Dantas, G. Genomic and functional techniques to mine the microbiome for novel antimicrobials and antimicrobial resistance genes. Ann. N. Y. Acad. Sci. 1388, 42–58 (2017).
- 4Cassini, A. et al. Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis. Lancet Infect. Dis. 19, 56–66 (2019).
- 5Crofts, T.S., Gasparrini, A.J. & Dantas, G. Next-generation approaches to understand and combat the antibiotic resistome. Nat. Rev. Microbiol. 15, 422–434 (2017).
- 6D'Costa, V.M. et al. Antibiotic resistance is ancient. Nature 477, 457–461 (2011).
- 7Bhullar, K. et al. Antibiotic resistance is prevalent in an isolated cave microbiome. PLoS ONE 7, e34953 (2012).
- 8Clemente, J.C. et al. The microbiome of uncontacted Amerindians. Sci. Adv. 1, e1500183 (2015).
- 9Knapp, C.W., Dolfing, J., Ehlert, P.A. & Graham, D.W. Evidence of increasing antibiotic resistance gene abundances in archived soils since 1940. Environ. Sci. Technol. 44, 580–587 (2010).
- 10Forsberg, K.J., Reyes, A., Wang, B., Selleck, E.M., Sommer, M.O. & Dantas, G. The shared antibiotic resistome of soil bacteria and human pathogens. Science 337, 1107–1111 (2012).
- 11Poirel, L., Rodriguez-Martinez, J.M., Mammeri, H., Liard, A. & Nordmann, P. Origin of plasmid-mediated quinolone resistance determinant QnrA. Antimicrob. Agents Chemother. 49, 3523–3525 (2005).
- 12Wang, R. et al. The global distribution and spread of the mobilized colistin resistance gene mcr-1. Nat. Commun. 9, 1179 (2018).
- 13Liu, Y.Y. et al. Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study. Lancet Infect. Dis. 16, 161–168 (2016).
- 14Forsberg, K.J. et al. Bacterial phylogeny structures soil resistomes across habitats. Nature 509, 612–616 (2014).
- 15Finley, R.L. et al. The scourge of antibiotic resistance: the important role of the environment. Clin. Infect. Dis. 57, 704–710 (2013).
- 16Douglas, A.P. et al. Utilizing genomic analyses to investigate the first outbreak of vanA vancomycin-resistant Enterococcus in Australia with emergence of daptomycin non-susceptibility. J. Med. Microbiol. 68, 303–308 (2019).
- 17Johnson, R.C. et al. Investigation of a cluster of sphingomonas koreensis infections. N. Engl. J. Med. 379, 2529–2539 (2018).
- 18Katz, M., Hover, B.M. & Brady, S.F. Culture-independent discovery of natural products from soil metagenomes. J. Ind. Microbiol. Biotechnol. 43, 129–141 (2016).
- 19Cohen, L.J., Han, S., Huang, Y.H. & Brady, S.F. Identification of the colicin V bacteriocin gene cluster by functional screening of a human microbiome metagenomic library. ACS Infect. Dis. 4, 27–32 (2018).
- 20Wieser, A., Schneider, L., Jung, J. & Schubert, S. MALDI-TOF MS in microbiological diagnostics-identification of microorganisms and beyond (mini review). Appl. Microbiol. Biotechnol. 93, 965–974 (2012).
- 21Jorgensen, J.H. & Ferraro, M.J. Antimicrobial susceptibility testing: a review of general principles and contemporary practices. Clin. Infect. Dis. 49, 1749–1755 (2009).
- 22Didelot, X., Bowden, R., Wilson, D.J., Peto, T.E.A. & Crook, D.W. Transforming clinical microbiology with bacterial genome sequencing. Nat. Rev. Genet. 13, 601–612 (2012).
- 23Köser, C.U. et al. Routine use of microbial whole genome sequencing in diagnostic and public health microbiology. PLoS Pathog. 8, e1002824 (2012).
- 24Potter, R.F. et al. Population structure, antibiotic resistance, and uropathogenicity of Klebsiella variicola. MBio 9, e02481-18 (2018).
- 25Hu, Z. et al. Metagenomic next-generation sequencing as a diagnostic tool for toxoplasmic encephalitis. Ann. Clin. Microbiol. Antimicrob. 17, 45 (2018).
- 26Rodrigues, C., Passet, V., Rakotondrasoa, A. & Brisse, S. Identification of Klebsiella pneumoniae, Klebsiella quasipneumoniae, Klebsiella variicola and related phylogroups by MALDI-TOF mass spectrometry. Front. Microbiol. 9, 3000 (2018).
- 27Lu, Y., Feng, Y., McNally, A. & Zong, Z. Occurrence of colistin-resistant hypervirulent Klebsiella variicola. J. Antimicrob. Chemother. 73, 3001–3004 (2018).
- 28Maatallah, M. et al. Klebsiella variicola is a frequent cause of bloodstream infection in the stockholm area, and associated with higher mortality compared to K. pneumoniae. PLoS ONE 9, e113539 (2014).
- 29Decraene, V. et al. A large, refractory nosocomial outbreak of Klebsiella pneumoniae carbapenemase-producing Escherichia coli demonstrates carbapenemase gene outbreaks involving sink sites require novel approaches to infection control. Antimicrob. Agents Chemother. 62, e01689-18 (2018).
- 30Boolchandani, M., D'Souza, A. & Dantas, G. Sequencing-based methods and resources to study antimicrobial resistance. Nat. Rev. Genet. 20, 356–370 (2019).
- 31 American Academy of Microbiology. Applications of Clinical Microbial Next-Generation Sequencing: Report on an American Academy of Microbiology colloquium held in Washington, DC, in April 2015 (American Society for Microbiology, Washington, DC, 2016).
- 32Quainoo, S. et al. Whole-genome sequencing of bacterial pathogens: the future of nosocomial outbreak analysis. Clin. Microbiol. Rev. 30, 1015–1063 (2017).
- 33Truong, D.T. et al. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat. Methods 12, 902–903 (2015).
- 34Abubucker, S. et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput. Biol. 8, e1002358 (2012).
- 35Kaminski, J., Gibson, M.K., Franzosa, E.A., Segata, N., Dantas, G. & Huttenhower, C. High-specificity targeted functional profiling in microbial communities with ShortBRED. PLoS Comput. Biol. 11, e1004557 (2015).
- 36Guo, L.Y. et al. Detection of pediatric bacterial meningitis pathogens from cerebrospinal fluid by next-generation sequencing technology. J. Infect. 78, 323–337 (2019).
- 37Boucher, A. et al. Epidemiology of infectious encephalitis causes in 2016. Med. Mal. Infect. 47, 221–235 (2017).
- 38Shao, L., Ling, Z., Chen, D., Liu, Y., Yang, F. & Li, L. Disorganized gut microbiome contributed to liver cirrhosis progression: a meta-omics-based study. Front. Microbiol. 9, 3166 (2018).
- 39Opota, O., Jaton, K. & Greub, G. Microbial diagnosis of bloodstream infection: towards molecular diagnosis directly from blood. Clin. Microbiol. Infect. 21, 323–331 (2015).
- 40Marotz, C.A., Sanders, J.G., Zuniga, C., Zaramela, L.S., Knight, R. & Zengler, K. Improving saliva shotgun metagenomics by chemical host DNA depletion. Microbiome 6, 42 (2018).
- 41Johnson, A.P. & Woodford, N. Global spread of antibiotic resistance: the example of New Delhi metallo-beta-lactamase (NDM)-mediated carbapenem resistance. J. Med. Microbiol. 62, 499–513 (2013).
- 42Walsh, T.R., Weeks, J., Livermore, D.M. & Toleman, M.A. Dissemination of NDM-1 positive bacteria in the New Delhi environment and its implications for human health: an environmental point prevalence study. Lancet Infect. Dis. 11, 355–362 (2011).
- 43Ng, C. et al. Characterization of metagenomes in urban aquatic compartments reveals high prevalence of clinically relevant antibiotic resistance genes in wastewaters. Front. Microbiol. 8, 2200 (2017).
- 44Lax, S. et al. Longitudinal analysis of microbial interaction between humans and the indoor environment. Science 345, 1048–1052 (2014).
- 45Lax, S. & Gilbert, J.A. Hospital-associated microbiota and implications for nosocomial infections. Trends Mol. Med. 21, 427–432 (2015).
- 46Vaz-Moreira, I., Nunes, O.C. & Manaia, C.M. Diversity and antibiotic resistance in Pseudomonas spp. from drinking water. Sci. Total Environ. 426, 366–374 (2012).
- 47Wen, X. et al. Occurrence and contamination profiles of antibiotic resistance genes from swine manure to receiving environments in Guangdong Province southern China. Ecotoxicol. Environ. Saf. 173, 96–102 (2019).
- 48Vaz-Moreira, I., Nunes, O.C. & Manaia, C.M. Bacterial diversity and antibiotic resistance in water habitats: searching the links with the human microbiome. FEMS Microbiol. Rev. 38, 761–778 (2014).
- 49Ruiz-Fons, F. A review of the current status of relevant zoonotic pathogens in wild swine (Sus scrofa) populations: changes modulating the risk of transmission to humans. Transbound. Emerg. Dis. 64, 68–88 (2017).
- 50Richard, M. et al. Factors determining human-to-human transmissibility of zoonotic pathogens via contact. Curr. Opin. Virol. 22, 7–12 (2017).
- 51Zhu, Y.G. et al. Diverse and abundant antibiotic resistance genes in Chinese swine farms. Proc. Natl Acad. Sci. USA 110, 3435–3440 (2013).
- 52Xie, W.Y., Yang, X.P., Li, Q., Wu, L.H., Shen, Q.R. & Zhao, F.J. Changes in antibiotic concentrations and antibiotic resistome during commercial composting of animal manures. Environ. Pollut. 219, 182–190 (2016).
- 53Ruan, Z. et al. Emergence of a ST2570 Klebsiella pneumoniae isolate carrying mcr-1 and blaCTX-M-14 recovered from a bloodstream infection in China. Clin. Microbiol. Infect. 25, 916–918 (2019).
- 54Reddy, B. & Dubey, S.K. River Ganges water as reservoir of microbes with antibiotic and metal ion resistance genes: high throughput metagenomic approach. Environ. Pollut. 246, 443–451 (2019).
- 55Fernandes, T., Vaz-Moreira, I. & Manaia, C.M. Neighbor urban wastewater treatment plants display distinct profiles of bacterial community and antibiotic resistance genes. Environ. Sci. Pollut. Res. Int. 26, 11269–11278 (2019).
- 56Guo, J., Li, J., Chen, H., Bond, P.L. & Yuan, Z. Metagenomic analysis reveals wastewater treatment plants as hotspots of antibiotic resistance genes and mobile genetic elements. Water Res. 123, 468–478 (2017).
- 57Czekalski, N. et al. Inactivation of antibiotic resistant bacteria and resistance genes by ozone: from laboratory experiments to full-scale wastewater treatment. Environ. Sci. Technol. 50, 11862–11871 (2016).
- 58Amos, G.C., Zhang, L., Hawkey, P.M., Gaze, W.H. & Wellington, E.M. Functional metagenomic analysis reveals rivers are a reservoir for diverse antibiotic resistance genes. Vet. Microbiol. 171, 441–447 (2014).
- 59Chen, H., Bai, X., Jing, L., Chen, R. & Teng, Y. Characterization of antibiotic resistance genes in the sediments of an urban river revealed by comparative metagenomics analysis. Sci. Total Environ. 653, 1513–1521 (2019).
- 60Ma, L. et al. Catalogue of antibiotic resistome and host-tracking in drinking water deciphered by a large scale survey. Microbiome 5, 154 (2017).
- 61Hover, B.M. et al. Culture-independent discovery of the malacidins as calcium-dependent antibiotics with activity against multidrug-resistant gram-positive pathogens. Nat. Microbiol. 3, 415–422 (2018).
- 62Pehrsson, E.C. et al. Interconnected microbiomes and resistomes in low-income human habitats. Nature 533, 212–216 (2016).
- 63Gibson, M.K. et al. Developmental dynamics of the preterm infant gut microbiota and antibiotic resistome. Nat. Microbiol. 1, 16024 (2016).
- 64Liu, B. & Pop, M. ARDB–antibiotic resistance genes database. Nucleic Acids Res. 37, D443–D447 (2009).
- 65Jia, B. et al. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res. 45, D566–D573 (2017).
- 66Bush, K. & Jacoby, G.A. Updated functional classification of beta-lactamases. Antimicrob. Agents Chemother. 54, 969–976 (2010).
- 67Thai, Q.K., Bös, F. & Pleiss, J. The Lactamase engineering database: a critical survey of TEM sequences in public databases. BMC Genom. 10, 390 (2009).
- 68Zankari, E. et al. Genotyping using whole-genome sequencing is a realistic alternative to surveillance based on phenotypic antimicrobial susceptibility testing. J. Antimicrob. Chemother. 68, 771–777 (2013).
- 69Langmead, B. & Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
- 70Lin, Y., Li, J., Shen, H., Zhang, L., Papasian, C.J. & Deng, H.W. Comparative studies of de novo assembly tools for next-generation sequencing technologies. Bioinformatics 27, 2031–2037 (2011).
- 71Gibson, M.K., Forsberg, K.J. & Dantas, G. Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology. ISME J. 9, 207–216 (2015).
- 72Bocanegra-Ibarias, P. et al. Molecular and microbiological report of a hospital outbreak of NDM-1-carrying Enterobacteriaceae in Mexico. PLoS ONE 12, e0179651 (2017).
- 73Eid, J. et al. Real-time DNA sequencing from single polymerase molecules. Science 323, 133–138 (2009).
- 74Clarke, J., Wu, H.C., Jayasinghe, L., Patel, A., Reid, S. & Bayley, H. Continuous base identification for single-molecule nanopore DNA sequencing. Nat. Nanotechnol. 4, 265–270 (2009).
- 75Liao, Y.C., Lin, S.H. & Lin, H.H. Completing bacterial genome assemblies: strategy and performance comparisons. Sci. Rep. 5, 8747 (2015).
- 76Břinda, K. et al. Lineage calling can identify antibiotic resistant clones within minutes. bioRxiv (2018). https://doi.org/10.1101/403204
- 77Bradley, P. et al. Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis. Nat. Commun. 6, 10063 (2015).
- 78Ghurye, J.S., Cepeda-Espinoza, V. & Pop, M. Metagenomic assembly: overview, challenges and applications. Yale J. Biol. Med. 89, 353–362 (2016).
- 79van der Walt, A.J., van Goethem, M.W., Ramond, J.B., Makhalanyane, T.P., Reva, O. & Cowan, D.A. Assembling metagenomes, one community at a time. BMC Genom. 18, 521 (2017).
- 80Beaulaurier, J. et al. Metagenomic binning and association of plasmids with bacterial host genomes using DNA methylation. Nat. Biotechnol. 36, 61–69 (2018).
- 81Altschul, S.F., Gish, W., Miller, W., Myers, E.W. & Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).
- 82Zankari, E. et al. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 67, 2640–2644 (2012).
- 83Eddy, S.R. Profile hidden Markov models. Bioinformatics 14, 755–763 (1998).
- 84Blin, K. et al. antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification. Nucleic Acids Res. 45, W36–W41 (2017).
- 85Donia, M.S. et al. A systematic analysis of biosynthetic gene clusters in the human microbiome reveals a common family of antibiotics. Cell 158, 1402–1414 (2014).
- 86Rondon, M.R. et al. Cloning the soil metagenome: a strategy for accessing the genetic and functional diversity of uncultured microorganisms. Appl. Environ. Microbiol. 66, 2541–2547 (2000).
- 87Pehrsson, E.C., Forsberg, K.J., Gibson, M.K., Ahmadi, S. & Dantas, G. Novel resistance functions uncovered using functional metagenomic investigations of resistance reservoirs. Front. Microbiol. 4, 145 (2013).
- 88Moore, A.M. et al. Pediatric fecal microbiota harbor diverse and novel antibiotic resistance genes. PLoS ONE 8, e78822 (2013).
- 89Forsberg, K.J., Patel, S., Wencewicz, T.A. & Dantas, G. The tetracycline destructases: a novel family of tetracycline-inactivating enzymes. Chem. Biol. 22, 888–897 (2015).
- 90Park, J. et al. Plasticity, dynamics, and inhibition of emerging tetracycline resistance enzymes. Nat. Chem. Biol. 13, 730–736 (2017).
- 91Drawz, S.M. & Bonomo, R.A. Three decades of beta-lactamase inhibitors. Clin. Microbiol. Rev. 23, 160–201 (2010).
- 92Markley, J.L. et al. Semisynthetic analogues of anhydrotetracycline as inhibitors of tetracycline destructase enzymes. ACS Infect. Dis. 5, 618–633 (2019).
- 93Leski, T.A. et al. Multidrug-resistant tet(X)-containing hospital isolates in Sierra Leone. Int. J. Antimicrob. Agents 42, 83–86 (2013).
- 94Zhanel, G.G. et al. Review of eravacycline, a novel fluorocycline antibacterial agent. Drugs 76, 567–588 (2016).
- 95Tanaka, S.K., Steenbergen, J. & Villano, S. Discovery, pharmacology, and clinical profile of omadacycline, a novel aminomethylcycline antibiotic. Bioorg. Med. Chem. 24, 6409–6419 (2016).
- 96Martinez, A. et al. Genetically modified bacterial strains and novel bacterial artificial chromosome shuttle vectors for constructing environmental libraries and detecting heterologous natural products in multiple expression hosts. Appl. Environ. Microbiol. 70, 2452–2463 (2004).
- 97Craig, J.W., Chang, F.Y., Kim, J.H., Obiajulu, S.C. & Brady, S.F. Expanding small-molecule functional metagenomics through parallel screening of broad-host-range cosmid environmental DNA libraries in diverse proteobacteria. Appl. Environ. Microbiol. 76, 1633–1641 (2010).
- 98Fowler, D.M. & Fields, S. Deep mutational scanning: a new style of protein science. Nat. Methods 11, 801–807 (2014).
- 99Fowler, D.M., Stephany, J.J. & Fields, S. Measuring the activity of protein variants on a large scale using deep mutational scanning. Nat. Protoc. 9, 2267–2284 (2014).
- 100Sun, Z., Hu, L., Sankaran, B., Prasad, B.V.V. & Palzkill, T. Differential active site requirements for NDM-1 beta-lactamase hydrolysis of carbapenem versus penicillin and cephalosporin antibiotics. Nat. Commun. 9, 4524 (2018).
