Name
Abstract | ||
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Understanding the fundamental characteristics of microbial communities could have far reaching implications for human health and applied biotechnology. Despite this, much is still unknown regarding the genetic basis and evolutionary strategies underlying the formation of viable synthetic communities. By pairing auxotrophic mutants in co-culture, it has been demonstrated that viable nascent E. coli communities can be established where the mutant strains are metabolically coupled. A novel algorithm, OptAux, was constructed to design 61 unique multi-knockout E. coli auxotrophic strains that require significant metabolite uptake to grow. These predicted knockouts included a diverse set of novel non-specific auxotrophs that result from inhibition of major biosynthetic subsystems. Three OptAux predicted non-specific auxotrophic strainswith diverse metabolic deficiencieswere co-cultured with an L-histidine auxotroph and optimized via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community growth rates and provided insight into mechanisms for adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents new insight into the genetic strategies underlying viable nascent community formation and a cutting-edge computational method to elucidate metabolic changes that empower the creation of cooperative communities. Author summary Many basic characteristics underlying the establishment of cooperative growth in bacterial communities have not been studied in detail. The presented work sought to understand the adaptation of syntrophic communities by first employing a new computational method to generate a comprehensive catalog of E. coli auxotrophic mutants. Many of the knockouts in the catalog had the predicted effect of disabling a major biosynthetic process. As a result, these strains were predicted to be capable of growing when supplemented with many different individual metabolites (i.e., a non-specific auxotroph), but the strains would require a high amount of metabolic cooperation to grow in community. Three such non-specific auxotroph mutants from this catalog were co-cultured with a proven auxotrophic partner in vivo and evolved via adaptive laboratory evolution. In order to successfully grow, each strain in co-culture had to evolve under a pressure to grow cooperatively in its new niche. The non-specific auxotrophs further had to adapt to significant homeostatic changes in cell's metabolic state caused by knockouts in metabolic genes. The genomes of the successfully growing communities were sequenced, thus providing unique insights into the genetic changes accompanying the formation and optimization of the viable communities. A computational model was further developed to predict how finite protein availability, a fundamental constraint on cell metabolism, could impact the composition of the community (i.e., the relative abundances of each community member). |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1371/journal.pcbi.1006213 | PLOS COMPUTATIONAL BIOLOGY |
DocType | Volume | Issue |
Journal | 15 | 3 |
ISSN | Citations | PageRank |
1553-734X | 0 | 0.34 |
References | Authors | |
13 | 14 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Colton J Lloyd | 1 | 5 | 2.51 |
| Zachary A. King | 2 | 60 | 4.97 |
| Troy E Sandberg | 3 | 0 | 0.68 |
| Ying Hefner | 4 | 0 | 0.68 |
| Connor A Olson | 5 | 0 | 0.68 |
| Patrick V Phaneuf | 6 | 2 | 1.38 |
| Edward J. O'Brien | 7 | 10 | 1.32 |
| Jon G Sanders | 8 | 0 | 0.34 |
| Rodolfo A Salido | 9 | 0 | 0.34 |
| Karenina Sanders | 10 | 0 | 0.34 |
| Caitriona Brennan | 11 | 0 | 0.34 |
| Gregory Humphrey | 12 | 0 | 0.34 |
| Rob Knight | 13 | 366 | 26.19 |
| Adam M Feist | 14 | 27 | 3.15 |