Experimental Evolution of Metabolic Dependency in Bacteria

PLoS Genetics

Volumn 12, Issue 11, 2016, Pages

  D’Souza, Glen ^a,c   Kost, Christian ^a,b  

^a MAX PLANCK INSTITUTE FOR CHEMICAL ECOLOGY   (Germany)

^b UNIVERSITY OF OSNABRÜCK   (Germany)

^c SWISS FEDERAL INSTITUTE OF AQUATIC SCIENCE AND TECHNOLOGY   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; AUXOTROPHY; BACTERIAL GENETICS; BACTERIAL METABOLISM; BACTERIAL STRAIN; CELL DENSITY; CONTROLLED STUDY; ESCHERICHIA COLI; GENETIC VARIABILITY; GROWTH RATE; MOLECULAR EVOLUTION; MUTATIONAL ANALYSIS; NONHUMAN; REGULATOR GENE; STRUCTURAL GENE; BACTERIAL GENOME; DIRECTED MOLECULAR EVOLUTION; ENVIRONMENT; GENETIC DRIFT; GENETIC SELECTION; GENETICS; GENOTYPE; GENOTYPE ENVIRONMENT INTERACTION; METABOLISM; METABOLOMICS; REPRODUCTIVE FITNESS;

DIRECTED MOLECULAR EVOLUTION; ENVIRONMENT; ESCHERICHIA COLI; GENE-ENVIRONMENT INTERACTION; GENETIC DRIFT; GENETIC FITNESS; GENOME, BACTERIAL; GENOTYPE; METABOLIC NETWORKS AND PATHWAYS; METABOLOMICS; SELECTION, GENETIC;

EID: 85000869396     PISSN: 15537390     EISSN: 15537404     Source Type: Journal    
DOI: 10.1371/journal.pgen.1006364     Document Type: Article

References (75)

1. Puigbò P, Lobkovsky A, Kristensen D, Wolf Y, Koonin E, Genomes in turmoil: Quantification of genome dynamics in prokaryote supergenomes. BMC Biol. 2014; 12:1–19.
2. Martínez-Cano DJ, Reyes-Prieto M, Martínez-Romero E, Partida-Martínez LP, Latorre A, Moya A, et al. Evolution of small prokaryotic genomes. Front Microbiol. 2014; 5: 742. doi: 10.3389/fmicb.2014.0074225610432
3. Bolotin E, Hershberg R, Gene loss dominates as a source of genetic variation within clonal pathogenic bacterial species. Genome Biol Evol. 2015; 7: 2173–2187. doi: 10.1093/gbe/evv13526163675
4. Wernegreen JJ, Endosymbiont evolution: predictions from theory and surprises from genomes. Ann NY Acad Sci. 2015; 1360:16–35. doi: 10.1111/nyas.1274025866055
5. Nakabachi A, Yamashita A, Toh H, Ishikawa H, Dunbar HE, et al. The 160-kilobase genome of the bacterial endosymbiont Carsonella. Science. 2006; 314: 267. doi: 10.1126/science.113419617038615
6. Moran NA, Microbial minimalism: Genome reduction in bacterial pathogens. Cell. 2002; 108: 583–586. 11893328
7. D'Souza G, Waschina S, Kaleta C, Kost C, Plasticity and epistasis strongly affect bacterial fitness after losing multiple metabolic genes. Evolution. 2015; 69: 1244–1254. doi: 10.1111/evo.1264025765095
8. D'Souza G, Waschina S, Pande S, Bohl K, Kaleta C, Kost C, Less is more: Selective advantages can explain the prevalent loss of biosynthetic genes in bacteria. Evolution. 2014; 68: 2559–2570. doi: 10.1111/evo.1246824910088
9. Mee MT, Collins JJ, Church GM, Wang HH, Syntrophic exchange in synthetic microbial communities. Proc Natl Acad Sci USA. 2014; 111: E2149–E2156. doi: 10.1073/pnas.140564111124778240
10. Monk JM, Charusanti P, Aziz RK, Lerman JA, Premyodhin N, Orth JD, et al. Genome-scale metabolic reconstructions of multiple Escherichia coli strains highlight strain-specific adaptations to nutritional environments. Proc Natl Acad Sci USA. 2013; 110: 20338–20343. doi: 10.1073/pnas.130779711024277855
11. Ensminger AW, Yassin Y, Miron A, Isberg RR, Experimental evolution of Legionella pneumophila in mouse macrophages leads to strains with altered determinants of environmental survival. Plos Pathog. 2012; 8(5):e1002731. doi: 10.1371/journal.ppat.100273122693450
12. Ochman H, Moran NA, Genes lost and genes found: Evolution of bacterial pathogenesis and symbiosis. Science. 2001; 292: 1096–1099. 11352062
13. McCutcheon JP, Moran NA, Parallel genomic evolution and metabolic interdependence in an ancient symbiosis. Proc Natl Acad Sci USA. 2007; 104:19392–19397. doi: 10.1073/pnas.070885510418048332
14. McCutcheon JP, Moran NA, Extreme genome reduction in symbiotic bacteria. Nat Rev Microbiol. 2012; 10: 13–26.
15. Luo H, Csűros M, Hughes AL, Moran MA, Evolution of divergent life history strategies in marine alphaproteobacteria. mBio. 2013; 4(4): e00373–13. doi: 10.1128/mBio.00373-1323839216
16. Grote J, Thrash JC, Huggett MJ, Landry ZC, Carini P, Giovannoni SJ, et al. Streamlining and core genome conservation among highly divergent members of the SAR11 clade. mBio. 2012; 3(5):e00252–12. doi: 10.1128/mBio.00252-1222991429
17. Kuo CH, Moran NA, Ochman H, The consequences of genetic drift for bacterial genome complexity. Genome Res. 2009; 19: 1450–1454. doi: 10.1101/gr.091785.10919502381
18. Batut B, Knibbe C, Marais G, Daubin V, Reductive genome evolution at both ends of the bacterial population size spectrum. Nat Rev Microbiol. 2014; 12: 841–850. doi: 10.1038/nrmicro333125220308
19. Mira A, Ochman H, Moran NA, Deletional bias and the evolution of bacterial genomes. Trends Genet. 2001; 17: 589–596. 11585665
20. Moran NA, Accelerated evolution and Muller's rachet in endosymbiotic bacteria. Proc Natl Acad Sci USA. 1996; 93: 2873–2878. 8610134
21. Nilsson AI, Koskiniemi S, Eriksson S, Kugelberg E, Hinton JCD, Andersson DI, Bacterial genome size reduction by experimental evolution. Proc Natl Acad Sci USA. 2005; 102: 12112–12116. doi: 10.1073/pnas.050365410216099836
22. Dykhuizen D, Selection for tryptophan auxotrophs of Escherichia coli in glucose-limited chemostats as a test of energy-conservation hypothesis of evolution. Evolution. 1978; 32: 125–150.
23. Zamenhof S, Eichhorn HH, Study of microbial evolution through loss of biosynthetic functions- Establishment of defective mutants. Nature. 1967; 216: 456–458. 4964402
24. Giovannoni SJ, Cameron Thrash J, Temperton B, Implications of streamlining theory for microbial ecology. ISME J. 2014; 8: 1553–1565. doi: 10.1038/ismej.2014.6024739623
25. Lang GI, Rice DP, Hickman MJ, Sodergren E, Weinstock GM, et al. Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature. 2013; 500: 571–574. doi: 10.1038/nature1234423873039
26. Dufresne A, Garczarek L, Partensky F, Accelerated evolution associated with genome reduction in a free-living prokaryote. Genome Biol. 2005; 6(2): R14. doi: 10.1186/gb-2005-6-2-r1415693943
27. Koskiniemi S, Sun S, Berg OG, Andersson DI, Selection-driven gene loss in bacteria. PLoS Genet. 2012; 8(6): e1002787. doi: 10.1371/journal.pgen.100278722761588
28. Lee MC, Marx CJ, Repeated, selection-driven genome reduction of accessory genes in experimental populations. PLoS Genet. 2012; 8: e1002651. doi: 10.1371/journal.pgen.100265122589730
29. De Visser JAGM, Rozen DE, Limits to adaptation in asexual populations. J. Evol. Bio. 2005; 18: 779–788.
30. Pande S, Merker H, Bohl K, Reichelt M, Schuster S, de Figueiredo LF, et al. Fitness and stability of obligate cross-feeding interactions that emerge upon gene loss in bacteria. ISME J. 2014; 8: 953–962. doi: 10.1038/ismej.2013.21124285359
31. Conrad TM, Frazier M, Joyce AR, Cho B-K, Knight EM, Lewis NE, et al. RNA polymerase mutants found through adaptive evolution reprogram Escherichia coli for optimal growth in minimal media. Proc Natl Acad Sci USA. 2010; 107: 20500–20505. doi: 10.1073/pnas.091125310721057108
32. Nishino K, Honda T, Yamaguchi A, Genome-wide analyses of Escherichia coli gene expression responsive to the BaeSR two-component regulatory system. J Bacteriol. 2005; 187: 1763–1772. doi: 10.1128/JB.187.5.1763-1772.200515716448
33. Williams MD, Ouyang TX, Flickinger MC, Starvation-induced expression of SspA and SspB: the effects of a null mutation in sspA on Escherichia coli protein synthesis and survival during growth and prolonged starvation. Mol Microbiol. 1994; 11: 1029–1043. 8022275
34. Deutch AH, Rushlow KE, Smith CJ, Analysis of the Escherichia coli proBA locus by DNA and protein sequencing. Nucleic Acids Res. 1984; 12: 6337–6355. 6089111
35. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP, Predicting the functional effect of amino acid substitutions and indels. PLoS One. 2012; 7:e46688. doi: 10.1371/journal.pone.004668823056405
36. Waschina S, D'Souza G, Kost C, Kaleta C, Metabolic network architecture and carbon source determine metabolite production costs. FEBS J. 2016; 283: 2149–2163. doi: 10.1111/febs.1372727029764
37. Hottes AK, Freddolino PL, Khare A, Donnell ZN, Liu JC, et al. Bacterial adaptation through loss of function. PLoS Genet. 2013; 9(7): e1003617. doi: 10.1371/journal.pgen.100361723874220
38. Fujita AI, Abe T, Amino acid concentration and distribution of lysozyme and protease activities in the guts of higher termites. Physiol Entomol. 2002; 27: 76–78.
39. Werdin-Pfisterer NR, Kielland K, Boone RD, Buried organic horizons represent amino acid reservoirs in boreal forest soils. Soil Biol Biochem. 2012; 55: 122–131.
40. Boles BR, Thoendel M, Singh PK, Self-generated diversity produces "insurance effects" in biofilm communities. Proc Natl Acad Sci USA. 2004; 101: 16630–16635. doi: 10.1073/pnas.040746010115546998
41. Giraud A, Matic I, Tenaillon O, Clara A, Radman M, Fons M, et al. Costs and benefits of high mutation rates: Adaptive evolution of bacteria in the mouse gut. Science. 2001; 291: 2606–2608. doi: 10.1126/science.105642111283373
42. Bolotin A, Quinquis B, Renault P, Sorokin A, Ehrlich SD, Kulakauskas S, et al. Complete sequence and comparative genome analysis of the dairy bacterium Streptococcus thermophilus. Nature Biotechnol. 2004; 22: 1554–1558.
43. Giovannoni SJ, Trip J, Givan S, Podar M, Vergin K, Baptista D, Genome streamlining in a cosmopolitan oceanic bacterium. Science. 2005;309: 1242–1245doi: 10.1126/science.111405716109880
44. Thomas SR, Ray A, Hodson ME, Pitt TL, Increased sputum amino acid concentrations andauxotrophy of Pseudomonas aeruginosa in severe cystic fibrosis lung disease. Thorax. 2000; 55: 795–797. doi: 10.1136/thorax.55.9.79510950901
45. Barth AL, Pitt TL, The high amino-acid content of sputum from cystic fibrosis patients promotes growth of auxotrophic Pseudomonas aeruginosa. J Med Microbiol. 1996; 45: 110–119. doi: 10.1099/00222615-45-2-1108683546
46. Morris JJ, Lenski RE, Zinser ER, The black queen hypothesis: Evolution of dependencies through adaptive gene loss. mBio. 2012; 3: e00036–12. doi: 10.1128/mBio.00036-1222448042
47. Morris JJ, Papoulis SE, Lenski RE, Coexistence of evolving bacteria stabilized by a shared black queen function. Evolution. 2014: 68: 2960–2971. doi: 10.1111/evo.1248524989794
48. Morris JJ, Black Queen evolution: the role of leakiness in structuring microbial communities. Trends Genet. 2015: 31, 475–482. doi: 10.1016/j.tig.2015.05.00426078099
49. Benomar S, Ranava D, Cárdenas ML, Trably E, Rafrafi Y, Ducret A, et al. Nutritional stress induces exchange of cell material and energetic coupling between bacterial species. Nat Commun. 2015: 6, 6283. doi: 10.1038/ncomms728325704114
50. Pande S, Shitut S, Freund L, Westermann M, Bertels F, Colesie C, et al. Metabolic crossfeeding via intercellular nanotubes among bacteria. Nat Commun. 2015: 6, 6238. doi: 10.1038/ncomms723825703793
51. Kaleta C, Schäuble S, Rinas U, Schuster S, Metabolic costs of amino acid and protein production in Escherichia coli. Biotechnology J. 2013: 8, 1105–1114.
52. Lang GI, Desai MM, The spectrum of adaptive mutations in experimental evolution. Genomics. 2014; 104: 412–416. doi: 10.1016/j.ygeno.2014.09.01125269377
53. Garcia SL, McMahon KD, Martinez-Garcia M, Srivastava A, Sczyrba A, Stepanauskas R, et al. Metabolic potential of a single cell belonging to one of the most abundant lineages in freshwater bacterioplankton. ISME J. 2013: 7, 137–147. doi: 10.1038/ismej.2012.8622810059
54. Moran NA, McCutcheon JP, Nakabachi A, Genomics and evolution of heritable bacterial symbionts. Annu Rev Genet. 2008: 42, 165–190. doi: 10.1146/annurev.genet.41.110306.13011918983256
55. Moran NA, Plague GR, Genomic changes following host restriction in bacteria. Curr Opin Genet Dev. 2004: 14, 627–633. doi: 10.1016/j.gde.2004.09.00315531157
56. McCutcheon JP, Moran NA, Functional convergence in reduced genomes of bacterial symbionts spanning 200 My of evolution. Genome Biol Evol. 2010: 2, 708–718. doi: 10.1093/gbe/evq05520829280
57. McCutcheon JP, von Dohlen CD, An interdependent metabolic patchwork in the nested symbiosis of mealybugs. Curr Biol. 2011: 21, 1366–1372. doi: 10.1016/j.cub.2011.06.05121835622
58. Kaltenpoth M, Goettler W, Koehler S, Strohm E, Life cycle and population dynamics of a protective insect symbiont reveal severe bottlenecks during vertical transmission. Evol Eco. 2010; 24: 463–477.
59. Hosokawa T, Kikuchi Y, Fukatsu T, How many symbionts are provided by mothers, acquired by offspring, and needed for successful vertical transmission in an obligate insect-bacterium mutualism?Mol Ecol. 2007; 16: 5316–5325. doi: 10.1111/j.1365-294X.2007.03592.x18028305
60. Hugenholtz P, Goebel BM, Pace NR, Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity. J Bacteriol. 1998: 180, 4765–4774. 9733676
61. Amann RI, Ludwig W, Schleifer KH, Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev. 1995: 59, 143–169. 7535888
62. Lenski RE, Rose MR, Simpson SC, Tadler SC, Long-term experimental evolution in Escherichia coli. 1. Adaptation and divergence during 2,000 generations. Am Nat. 1991: 138, 1315–1341.
63. Vanstockem M, Michiels K, Vanderleyden J, Vangool AP, Transposon mutagenesis of Azospirillum brasilense and Azospirillum lipoferum—Physical analysis of Tn5 and Tn5-Mob insertion mutants. Appl Environ Microbiol. 1987: 53, 410–415. 16347289
64. Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y, Baba M, et al. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol Syst Biol. 2006: 2.
65. Bertels F, Merker H, Kost C, Design and characterization of auxotrophy-based amino acid biosensors. Plos One. 2012: 7.
66. Dykhuizen DE, Experimental studies of natural selection in bacteria. Annu Rev Ecol Evol Syst. 1990: 21, 373–398.
67. Grenier F, Matteau D, Baby V, Rodrigue S, Complete genome sequence of Escherichia coli BW25113. Genome Announc. 2014: 2.
68. Barrick JE, Yu DS, Yoon SH, Jeong H, Oh TK, Schneider D, et al. Genome evolution and adaptation in a long-term experiment with Escherichia coli. Nature. 2009: 461, 1243–1274. doi: 10.1038/nature0848019838166
69. Deatherage DE, Barrick JE, Identification of mutations in laboratory evolved microbes from next-generation sequencing data using breseq. Methods Mol Biol. 2014: 1151, 165–188. doi: 10.1007/978-1-4939-0554-6_1224838886
70. Reisch CR, Prather KLJ, The no-SCAR (Scarless Cas9 Assisted Recombineering) system for genome editing in Escherichia coli. Sci Rep. 2015: 5: 15096. doi: 10.1038/srep1509626463009
71. Howell D, Statistical Methods for Psychology. 8th edn. Cengage Learning. 2012.
72. Andrade JM, Estévez-Pérez MG, Statistical comparison of the slopes of two regression lines: A tutorial. Anal Chim Acta. 2014: 838, 1–12. doi: 10.1016/j.aca.2014.04.05725064237
73. Zar JH, Biostatistical Analysis. 4th eds. Pearson Education India. 1999.
74. Benjamini Y, Krieger AM, Yekutieli D, Adaptive linear step-up procedures that control the false discovery rate. Biometrika. 2006: 93, 491–507.
75. Keseler I, Collado-Vides J, Santos-Zavaleta A, Peralta-Gil M, Gama-Castro S, EcoCyc: a comprehensive database of Escherichia coli biology. Nucleic Acids Res. 2011: 39: D583—D590. doi: 10.1093/nar/gkq114321097882