In vitro fermentation test bed for evaluation of engineered probiotics in polymicrobial communities

Main Article Content

Steven Arcidiacono
Amy M. Ehrenworth Breedon
Michael S. Goodson
Laurel A. Doherty
Wanda Lyon
Grace Jimenez
Ida G. Pantoja-Feliciano
Jason W. Soares

Keywords

in vitro fermentation, synthetic biology, simplified polymicrobial communities, engineered probiotics

Abstract

In vitro fermentation systems offer significant opportunity for deconvoluting complex metabolic dynamics within polymicrobial communities, particularly those associated with the human gut microbiome. In vitro gut models have broad experimental capacity allowing rapid evaluation of multiple parameters, generating knowledge to inform design of subsequent in vivo studies. Here, our method describes an in vitro fermentation test bed to provide a physiologically-relevant assessment of engineered probiotics circuit design functions. Typically, engineered probiotics are evaluated under pristine, monoor co-culture conditions and transitioned directly into animal or human studies, commonly resulting in a loss of desired function when introduced to complex gut communities. Our method encompasses a systematic workflow entailing fermentation, molecular and functional characterization, and statistical analyses to validate an engineered probiotic’s persistence, plasmid stability and reporter response. To demonstrate the workflow, simplified polymicrobial communities of human gut microbial commensals were utilized to investigate the probiotic Escherichia coli Nissle 1917 engineered to produce a fluorescent reporter protein. Commensals were assembled with increasing complexity to produce a mock community based on nutrient utilization. The method assesses engineered probiotic persistence in a competitive growth environment, reporter production and function, effect of engineering on organism growth and influence on commensal composition. The in vitro test bed represents a new element within the Design-Build-Test-Learn paradigm, providing physiologically-relevant feedback for circuit re-design and experimental validation for transition of engineered probiotics to higher fidelity animal or human studies.


 

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References

1. Bober JR, Beisei CL, Nair NU (2018) Synthetic biology approaches to engineer probiotics and members of the human microbiota for biomedical applications. Ann Rev Biomed Eng 20: 277-300. doi: 10.1146/annurev-bioeng-062117-121019.
PMID: 29528686
2. Naydich AD, Nangle SN, Bues JJ, Trivedi D, Nissar N, et al. (2019) Synthetic gene circuits enable systems-level biosensor trigger discovery at the hostmicrobe interface. MSystems 4: e00125-19. doi: 10.1128/mSystems.00125-19. PMID: 31186335
3. Daeffler KN, Galley JD, Sheth RU, Ortiz-Velez LC, Bibb CO, et al. (2017) Engineering bacterial thiosulfate and tetrathionate sensors for detecting gut inflammation. Mol Syst Biol 13: 923. doi: 10.15252/msb.20167416. PMID: 28373240
4. Archer EJ, Robinson AB, Süel GM (2012) Engineered E. coli that detect and respond to gut inflammation through nitric oxide sensing. ACS Synth Biol 1: 451-457. doi: 10.1021/sb3000595. PMID: 23656184
5. Harbaugh SV, Goodson MS, Dillon K, Zabarnick S, Kelley-Loughnane N (2017) Riboswitch-based reversible dual color sensor. ACS Synth Biol 6: 766-781. doi: 10.1021/acssynbio.6b00199. PMID: 28121427
6. Dou J, Bennett MR (2018) Synthetic biology and the gut microbiome. Biotechnol J 13: 1700159. doi: 10.1002/biot.201700159. PMID: 28976641
7. Certain LK, Way JC, Pezone MJ, Collins JJ (2017) Using engineered bacteria to characterize infection dynamics and antibiotic effects in vivo. Cell Host Microbe 22: 263-268. doi: 10.1016/j.chom.2017.08.001. PMID: 28867388
8. Mimee M, Citorik RJ, Lu TK (2016) Microbiome therapeutics - advances and challenges. Adv Drug Deliv Rev 105: 44-54. doi: 10.1016/j.addr.2016.04.032. PMID: 27158095
9. Smith MW, Neidhardt FC (1983) Proteins induced by anaerobiosis in Escherichia coli. J Bacteriol 154: 336-343. doi: 10.1128/JB.154.1.336-343.1983. PMID: 6339476
10. Covert MW, Knight EM, Reed JL, Herrgard MJ, Palsson BO (2004) Integrating high-throughput and computational data elucidates bacterial networks. Nature 429: 92-96. doi: 10.1038/nature02456. PMID: 15129285
11. Guzman-Rodriguez M, McDonald JA, Hyde R, Allen-Vercoe E, Claud EC, et al. (2018) Using bioreactors to study the effects of drugs on the human microbiota. Methods 149: 31-41. doi: 10.1016/j.ymeth.2018.08.003. PMID: 30102990
12. Macfarlane GT, Macfarlane S, Gibson GR (1998) Validation of a three-stage compound continuous culture system for investigating the effect of retention time on the ecology and metabolism of bacteria in the human colon. Microb
Ecol 35: 180-187. doi: 10.1007/s002489900072. PMID: 9541554
13. Newton DF, Macfarlane S, Macfarlane GT (2013) Effects of antibiotics on bacterial species composition and metabolic activities in chemostats containing defined populations of human gut microorganisms. Antimicrob Agents Chemother
57: 2016-2025. doi: 10.1128/AAC.00079-13. PMID: 23403424
14. Wagner RD, Johnson SJ, Cerniglia CE (2008) In vitro model of colonization resistance by the enteric microbiota: effects of antimicrobial agents used in food-producing animals. Antimicrob Agents Chemother 52: 1230-1237. doi: 10.1128/AAC.00852-07. PMID: 18227184
15. Goodman AL, McNulty NP, Zhao Y, Leip D, Mitra RD, et al. (2009) Identifying genetic determinants needed to establish a human gut symbiont in its habitat. Cell Host & Microbe 6: 279-89. doi: 10.1016/j.chom.2009.08.003. PMID: 19748469
16. Yen S, McDonald JA, Schroeter K, Oliphant K, Sokolenko S, et al. (2015) Metabolomic analysis of human fecal microbiota: a comparison of feces-derived communities and defined mixed communities. J Proteome Res 14: 1472-82.
doi: 10.1021/pr5011247. PMID: 25670064
17. Pantoja-Feliciano IG, Soares JW, Doherty LA, Karl JP, McClung HL, et al. (2109) Acute stressor alters inter-species microbial competition for resistant starch-supplemented medium. Gut microbes 10: 439-446. doi: 10.1080/19490976.2018.1554962. PMID: 31309868
18. Protocols Online. Bacteroides fragilis growth conditions. Cited on June 26, 2009. Available from: http://www.protocol-online.org/biology-forums-2/posts/8839.html
19. Eley A, Greenwood D, O'Grady F (1985) Comparative growth of Bacteroides species in various anaerobic culture media. J Med Microbiol 19: 195-201. doi: 10.1099/00222615-19-2-195. PMID: 3981610
20. QIAGEN, Inc. QIAamp DNA Mini and Blood Mini Handbook, 5th Ed. (2016) Appendix D; Isolation of genomic DNA from Bacteria. QIAGEN, Inc. p. 56. Available from https://www.qiagen.com/us/resources/resourcedetail?id=62a200d6-faf4-469b-b50f-2b59cf738962&lang=en
21. The Huttenhower Lab. KneadData. Available from http://huttenhower.sph. Harvard.edu/kneaddata
22. The Huttenhower Lab. HUMAnN2.0. Available from http://huttenhower.sph. Harvard.edu/humann2
23. Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, et al. (2012) Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Meth 9: 811-814. doi: 10.1038/nmeth.2066. PMID: 22688413
24. Truong DT, Franzosa EA, Tickle TL, Scholz M, Weingart G, Pasolli E, et al. (2015) MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat Meth 12: 902-903. PMID: 26418763
25. Suzek BE, Wang Y, Huang H, McGarvey PB, Wu CH (2015) UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches. Bioinformatics 31: 926-932. doi: 10.1093/bioinformatics/btu739.
PMID: 25398609
26. Friendly M, Monette G, Fox J (2013) Elliptical insights: understanding statistical methods through elliptical geometry. Statistical Science 28: 1-39. doi: 10.1214/12-STS402