Use of high-content analysis and machine learning to characterize complex microbial samples via morphological analysis
Autoři:
Jennifer Petitte aff001; Michael Doherty aff001; Jacob Ladd aff001; Cassandra L. Marin aff001; Samuel Siles aff001; Vanessa Michelou aff001; Amanda Damon aff001; Erin Quattrini Eckert aff001; Xiang Huang aff001; John W. Rice aff001
Působiště autorů:
Novozymes North America, Inc., Durham, North Carolina, United States of America
aff001
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0222528
Souhrn
High Content Analysis (HCA) has become a cornerstone of cellular analysis within the drug discovery industry. To expand the capabilities of HCA, we have applied the same analysis methods, validated in numerous mammalian cell models, to microbiology methodology. Image acquisition and analysis of various microbial samples, ranging from pure cultures to culture mixtures containing up to three different bacterial species, were quantified and identified using various machine learning processes. These HCA techniques allow for faster cell enumeration than standard agar-plating methods, identification of “viable but not plate culturable” microbe phenotype, classification of antibiotic treatment effects, and identification of individual microbial strains in mixed cultures. These methods greatly expand the utility of HCA methods and automate tedious and low-throughput standard microbiological methods.
Klíčová slova:
Antibiotics – Flow cytometry – Cell staining – Machine learning algorithms – Machine learning – DAPI staining – Protein synthesis – Image analysis
Zdroje
1. Jones LH, Bunnage ME. Applications of chemogenomic library screening in drug discovery. Nat Rev Drug Discov. Nature Publishing Group; 2017;16: 285–296. doi: 10.1038/nrd.2016.244 28104905
2. Dürr O, Murina E, Siegismund D, Tolkachev V, Steigele S, Sick B. Know When You Don’t Know: A Robust Deep Learning Approach in the Presence of Unknown Phenotypes. Assay Drug Dev Technol. Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA; 2018;16: 343–349. doi: 10.1089/adt.2018.859 30148665
3. Jordan MI, Mitchell TM. Machine learning: Trends, perspectives, and prospects. Science. American Association for the Advancement of Science; 2015;349: 255–60. doi: 10.1126/science.aaa8415 26185243
4. Grote M. Petri dish versus Winogradsky column: a longue durée perspective on purity and diversity in microbiology, 1880s–1980s. Hist Philos Life Sci. Springer International Publishing; 2018;40: 11. doi: 10.1007/s40656-017-0175-9 29188459
5. Stiefel P, Schmidt-Emrich S, Maniura-Weber K, Ren Q. Critical aspects of using bacterial cell viability assays with the fluorophores SYTO9 and propidium iodide. BMC Microbiol. BioMed Central; 2015;15: 36. doi: 10.1186/s12866-015-0376-x 25881030
6. Li M, Liu L, Xi N, Wang Y. Nanoscale monitoring of drug actions on cell membrane using atomic force microscopy. Acta Pharmacol Sin. Nature Publishing Group; 2015;36: 769–782. doi: 10.1038/aps.2015.28 26027658
7. Vives-Rego J, Lebaron P, Nebe-von Caron G. Current and future applications of flow cytometry in aquatic microbiology. FEMS Microbiol Rev. Oxford University Press; 2000;24: 429–448. doi: 10.1111/j.1574-6976.2000.tb00549.x 10978545
8. Moter A, Göbel UB. Fluorescence in situ hybridization (FISH) for direct visualization of microorganisms. J Microbiol Methods. Elsevier; 2000;41: 85–112. doi: 10.1016/S0167-7012(00)00152-4
9. Rohde A, Hammerl JA, Appel B, Dieckmann R, Al Dahouk S. FISHing for bacteria in food–A promising tool for the reliable detection of pathogenic bacteria? Food Microbiol. Academic Press; 2015;46: 395–407. doi: 10.1016/J.FM.2014.09.002 25475309
10. Wang Y, Huang WE, Cui L, Wagner M. Single cell stable isotope probing in microbiology using Raman microspectroscopy. Curr Opin Biotechnol. Elsevier Current Trends; 2016;41: 34–42. doi: 10.1016/J.COPBIO.2016.04.018 27149160
11. Koydemir HC, Gorocs Z, Tseng D, Cortazar B, Feng S, Chan RYL, et al. Rapid imaging, detection and quantification of Giardia lamblia cysts using mobile-phone based fluorescent microscopy and machine learning. Lab Chip. The Royal Society of Chemistry; 2015;15: 1284–1293. doi: 10.1039/C4LC01358A 25537426
12. Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R, Gordon JI. The Human Microbiome Project. Nature. 2007;449: 804–810. doi: 10.1038/nature06244 17943116
13. Gilbert JA, Jansson JK, Knight R. The Earth Microbiome project: successes and aspirations. BMC Biol. BioMed Central; 2014;12: 69. doi: 10.1186/s12915-014-0069-1 25184604
14. Berg G, Grube M, Schloter M, Smalla K. Unraveling the plant microbiome: looking back and future perspectives. Front Microbiol. Frontiers; 2014;5: 148. doi: 10.3389/fmicb.2014.00148 24926286
15. van der Heijden MGA, Hartmann M. Networking in the Plant Microbiome. PLOS Biol. Public Library of Science; 2016;14: e1002378. doi: 10.1371/journal.pbio.1002378 26871440
16. Berg G, Grube M, Schloter M, Smalla K. The plant microbiome and its importance for plant and human health. Front Microbiol. Frontiers; 2014;5: 1. doi: 10.3389/fmicb.2014.00491 25278934
17. Sorensen K, Brodbeck U. Assessment of coating-efficiency in ELISA plates by direct protein determination. J Immunol Methods. Elsevier; 1986;95: 291–293. doi: 10.1016/0022-1759(86)90419-9
18. Barros RC, Gelens E, Bulten E, Tuin A, de Jong MR, Kuijer R, et al. Self-assembled nanofiber coatings for controlling cell responses. J Biomed Mater Res Part A. 2017;105: 2252–2265. doi: 10.1002/jbm.a.36092 28513985
19. da Silva Domingues JF, Roest S, Wang Y, van der Mei HC, Libera M, van Kooten TG, et al. Macrophage phagocytic activity toward adhering staphylococci on cationic and patterned hydrogel coatings versus common biomaterials. Acta Biomater. Elsevier; 2015;18: 1–8. doi: 10.1016/J.ACTBIO.2015.02.028 25752975
20. Sincock SA, Robinson JP. Flow cytometric analysis of microorganisms. Methods Cell Biol. Academic Press; 2001;64: 511–537. doi: 10.1016/S0091-679X(01)64027-5
21. Sutton S. [Microbiology Topics. Accuracy of Plate Counts [Internet]. www.microbiol.org
22. Riss TL, Moravec RA, Niles AL, Duellman S, Benink HA, Worzella TJ, et al. Cell Viability Assays [Internet]. Assay Guidance Manual. Eli Lilly & Company and the National Center for Advancing Translational Sciences; 2004. http://www.ncbi.nlm.nih.gov/pubmed/23805433
23. Hein CD, Liu X-M, Wang D. Click chemistry, a powerful tool for pharmaceutical sciences. Pharm Res. NIH Public Access; 2008;25: 2216–30. doi: 10.1007/s11095-008-9616-1 18509602
24. Moellering RC. Vancomycin: A 50-Year Reassessment. Clin Infect Dis. Oxford University Press; 2006;42: S3–S4. doi: 10.1086/491708 16323117
25. Watanakunakorn C. Mode of action and in-vitro activity of vancomycin. J Antimicrob Chemother. 1984;14 Suppl D: 7–18. http://www.ncbi.nlm.nih.gov/pubmed/6440886
26. Brodersen DE, Clemons WM, Carter AP, Morgan-Warren RJ, Wimberly BT, Ramakrishnan V. The Structural Basis for the Action of the Antibiotics Tetracycline, Pactamycin, and Hygromycin B on the 30S Ribosomal Subunit. Cell. Cell Press; 2000;103: 1143–1154. doi: 10.1016/S0092-8674(00)00216-6
27. Zoffmann S, Vercruysse M, Benmansour F, Maunz A, Wolf L, Blum Marti R, et al. Machine learning-powered antibiotics phenotypic drug discovery. Sci Rep. Nature Publishing Group; 2019;9: 5013. doi: 10.1038/s41598-019-39387-9 30899034
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