Biological processes in living cells are often carried out by gene networks in which signals and reactions are integrated at network hubs, which play fundamental roles for maintaining the cell physiology through interacting highly with other genes. Network hubs are responsivle for collecting signals from the upstream genes and then tune the cellular outputs in correspondent to the environmental cues. Hub genes are known to be evolutionary conserved and even slight perturbations of the sequences can lead to deleterious cell growth. Despite of the functional constraint, the sequences of the hub genes still change along the time. It is unclear to what extent the natural sequence variation actually contributes to functional divergence and to what extent network hubs are evolvable. Furthermore, to our knowledge no study has ever addressed how these alterations impact long-term evolution. We investigated these questions using a protein homeostasis central hub, heat shock protein (Hsp90) wich is essential under the normal condition for maintaining the normal cell growth. When native Hsp90 in Saccharomyces cerevisiae cells was replaced by the ortholog from hypersaline-tolerant Yarrowia lipolytica that diverged from S. cerevisiae about 270 million years ago, the cells exhibited improved growth in hypersaline environments but compromised growth in others, indicating functional divergence in Hsp90 between the two yeasts. Laboratory evolution shows that evolved Y. lipolytica-HSP90-carrying S. cerevisiae cells exhibit a wider range of phenotypic variation than cells carrying native HSC82. Identified beneficial mutations are involved in multiple pathways and are often pleiotropic. Our results show that cells adapt to a heterologous Hsp90 by modifying different sub-networks, facilitating the evolution of phenotypic diversity inaccessible to wild-type cells.

Acknowledgements i
Abstract iii
Introduction iv
List of Figures ix
List of Tables xii
Chapter 1: Y. lipolytica Hsp90 and its interactome are functionally diverged from the S. cerevisiae counterparts 1
Materials and Methods 2
Hsp90 physical interactome analysis 2
Construction of the HSP90 replacement lines 2
Cell fitness assays 5
Western blotting for measuring the abundance of Hsp90 6
V-src kinase assay 7
Results 8
Replacing HSP90 with the Yarrowia lipolytica ortholog increases salt tolerance of Saccharomyces cerevisiae cells 8
19% of the S. cerevisiae Hsp90 physical interactors are missing in Y. lipolytica 16
Chapter 2: Experimental evolution of the Y. lipolytica-HSP90-hosting S. cerevisiae cells and their phenotypes 20
Materials and Methods 21
Experimental evolution 21
Flow cytometry of DNA content 21
Hsp104 aggregation assay 22
Cell morphology assay 23
Results 23
Adaptation to the foreign Hsp90 in laboratory evolution experiments 23
Fitness improvement in the evolved clones is specific to Ylip-Hsp90 30
Individual evolved Ylip-HSP90 clones improve their cell phsiologies to varying degrees 33
Chapter 3: Ylip-HSP90 evolved clones exhibit high phenotypic diversity which can be recapitulated by single mutations 37
Materials and Methods 38
Cell fitness assays 38
Hierarchical clustering and PCA analysis 39
Calculation of Pearson Correlation distances 39
Whole genome sequencing analysis 40
F1 segregant analysis 41
Gene ontology enrichment and network analysis 42
CRISPR-Cas9-directed mutant reconstitution 43
Data access 44
Results 48
Independent Ylip-HSP90 clones evolved through different adaptive trajectories 48
Mutations in evolved Ylip-HSP90 clones are associated with various Hsp90-related functions 56
Segregant analysis identifies beneficial mutations with strong fitness effects 95
Individual mutations exert condition-specific effects 98
Chapter 4: Impact of hub mutations and its implication in organismal evolution 104
Genotype and phenotype 105
Hub and evolvability 105
A compromised hub leads to network evolution 107
Reference 111

Reference
1.Hartwell, L.H., et al., From molecular to modular cell biology. Nature, 1999. 402(6761 Suppl): p. C47-52.
2.Barabasi, A.L. and Z.N. Oltvai, Network biology: understanding the cell''s functional organization. Nat Rev Genet, 2004. 5(2): p. 101-13.
3.Eisenberg, D., et al., Protein function in the post-genomic era. Nature, 2000. 405(6788): p. 823-6.
4.Proulx, S.R., D.E. Promislow, and P.C. Phillips, Network thinking in ecology and evolution. Trends Ecol Evol, 2005. 20(6): p. 345-53.
5.Jeong, H., et al., Lethality and centrality in protein networks. Nature, 2001. 411(6833): p. 41-2.
6.Batada, N.N., L.D. Hurst, and M. Tyers, Evolutionary and physiological importance of hub proteins. PLoS Comput Biol, 2006. 2(7): p. e88.
7.Levy, S.F. and M.L. Siegal, Network hubs buffer environmental variation in Saccharomyces cerevisiae. PLoS Biol, 2008. 6(11): p. e264.
8.Powers, E.T. and W.E. Balch, Diversity in the origins of proteostasis networks--a driver for protein function in evolution. Nat Rev Mol Cell Biol, 2013. 14(4): p. 237-48.
9.Borkovich, K.A., et al., hsp82 is an essential protein that is required in higher concentrations for growth of cells at higher temperatures. Mol Cell Biol, 1989. 9(9): p. 3919-30.
10.Aligue, R., H. Akhavan-Niak, and P. Russell, A role for Hsp90 in cell cycle control: Wee1 tyrosine kinase activity requires interaction with Hsp90. EMBO J, 1994. 13(24): p. 6099-106.
11.Cutforth, T. and G.M. Rubin, Mutations in Hsp83 and Cdc37 Impair Signaling by the Sevenless Receptor Tyrosine Kinase in Drosophila. Cell, 1994. 77(7): p. 1027-1036.
12.Birnby, D.A., et al., A transmembrane guanylyl cyclase (DAF-11) and Hsp90 (DAF-21) regulate a common set of chemosensory behaviors in Caenorhabditis elegans. Genetics, 2000. 155(1): p. 85-104.
13.Devaney, E., et al., Hsp90 is essential in the filarial nematode Brugia pahangi. International Journal for Parasitology, 2005. 35(6): p. 627-636.
14.McClellan, A.J., et al., Diverse cellular functions of the Hsp90 molecular chaperone uncovered using systems approaches. Cell, 2007. 131(1): p. 121-35.
15.Zhao, R., et al., Navigating the chaperone network: an integrative map of physical and genetic interactions mediated by the hsp90 chaperone. Cell, 2005. 120(5): p. 715-27.
16.Taipale, M., D.F. Jarosz, and S. Lindquist, HSP90 at the hub of protein homeostasis: emerging mechanistic insights. Nat Rev Mol Cell Biol, 2010. 11(7): p. 515-28.
17.Gopinath, R.K., et al., The Hsp90-dependent proteome is conserved and enriched for hub proteins with high levels of protein-protein connectivity. Genome Biol Evol, 2014. 6(10): p. 2851-65.
18.Makhnevych, T. and W.A. Houry, The role of Hsp90 in protein complex assembly. Biochim Biophys Acta, 2012. 1823(3): p. 674-82.
19.Chiosis, G., C.A. Dickey, and J.L. Johnson, A global view of Hsp90 functions. Nat Struct Mol Biol, 2013. 20(1): p. 1-4.
20.Kim, T.S., et al., Interaction of Hsp90 with ribosomal proteins protects from ubiquitination and proteasome-dependent degradation. Mol Biol Cell, 2006. 17(2): p. 824-33.
21.Pearl, L.H. and C. Prodromou, Structure and mechanism of the Hsp90 molecular chaperone machinery. Annu Rev Biochem, 2006. 75: p. 271-94.
22.Rohl, A., J. Rohrberg, and J. Buchner, The chaperone Hsp90: changing partners for demanding clients. Trends Biochem Sci, 2013. 38(5): p. 253-62.
23.Citri, A., et al., Hsp90 recognizes a common surface on client kinases. J Biol Chem, 2006. 281(20): p. 14361-9.
24.Xu, W., et al., Surface charge and hydrophobicity determine ErbB2 binding to the Hsp90 chaperone complex. Nat Struct Mol Biol, 2005. 12(2): p. 120-6.
25.Rutherford, S.L. and S. Lindquist, Hsp90 as a capacitor for morphological evolution. Nature, 1998. 396(6709): p. 336-342.
26.Queitsch, C., T.A. Sangster, and S. Lindquist, Hsp90 as a capacitor of phenotypic variation. Nature, 2002. 417(6889): p. 618-24.
27.Rohner, N., et al., Cryptic variation in morphological evolution: HSP90 as a capacitor for loss of eyes in cavefish. Science, 2013. 342(6164): p. 1372-5.
28.Hsieh, Y.Y., P.H. Hung, and J.Y. Leu, Hsp90 regulates nongenetic variation in response to environmental stress. Mol Cell, 2013. 50(1): p. 82-92.
29.Jarosz, D.F., M. Taipale, and S. Lindquist, Protein homeostasis and the phenotypic manifestation of genetic diversity: principles and mechanisms. Annu Rev Genet, 2010. 44: p. 189-216.
30.Breitkreutz, A., et al., A global protein kinase and phosphatase interaction network in yeast. Science, 2010. 328(5981): p. 1043-6.
31.Hughes, T.R., et al., Functional discovery via a compendium of expression profiles. Cell, 2000. 102(1): p. 109-26.
32.Mnaimneh, S., et al., Exploration of essential gene functions via titratable promoter alleles. Cell, 2004. 118(1): p. 31-44.
33.Kushnirov, V.V., Rapid and reliable protein extraction from yeast. Yeast, 2000. 16(9): p. 857-60.
34.Wayne, N. and D.N. Bolon, Dimerization of Hsp90 is required for in vivo function: Design and analysis of monomers and dimers. Journal of Biological Chemistry, 2007. 282(48): p. 35386-35395.
35.Galagan, J.E., et al., Genomics of the fungal kingdom: insights into eukaryotic biology. Genome Res, 2005. 15(12): p. 1620-31.
36.Taylor, J.W. and M.L. Berbee, Dating divergences in the Fungal Tree of Life: review and new analyses. Mycologia, 2006. 98(6): p. 838-49.
37.Xu, Y. and S. Lindquist, Heat-shock protein hsp90 governs the activity of pp60v-src kinase. Proc Natl Acad Sci U S A, 1993. 90(15): p. 7074-8.
38.Praphailong, W. and G.H. Fleet, The effect of pH, sodium chloride, sucrose, sorbate and benzoate on the growth of food spoilage yeasts. Food Microbiology, 1997. 14(5): p. 459-468.
39.Duquesne, S., et al., The yeast Yarrowia lipolytica as a generic tool for molecular evolution of enzymes. Methods Mol Biol, 2012. 861: p. 301-12.
40.Imai, J. and I. Yahara, Role of HSP90 in salt stress tolerance via stabilization and regulation of calcineurin. Mol Cell Biol, 2000. 20(24): p. 9262-70.
41.Kao, K.C. and G. Sherlock, Molecular characterization of clonal interference during adaptive evolution in asexual populations of Saccharomyces cerevisiae. Nat Genet, 2008. 40(12): p. 1499-504.
42.Lenski, R.E., et al., Long-Term Experimental Evolution in Escherichia-Coli .1. Adaptation and Divergence during 2,000 Generations. American Naturalist, 1991. 138(6): p. 1315-1341.
43.Lee, S., W.A. Lim, and K.S. Thorn, Improved blue, green, and red fluorescent protein tagging vectors for S. cerevisiae. PLoS One, 2013. 8(7): p. e67902.
44.Ohya, Y., et al., High-dimensional and large-scale phenotyping of yeast mutants. Proc Natl Acad Sci U S A, 2005. 102(52): p. 19015-20.
45.Gerstein, A.C., et al., Genomic convergence toward diploidy in Saccharomyces cerevisiae. PLoS Genet, 2006. 2(9): p. e145.
46.Oromendia, A.B., S.E. Dodgson, and A. Amon, Aneuploidy causes proteotoxic stress in yeast. Genes Dev, 2012. 26(24): p. 2696-708.
47.Trotter, E.W., et al., Protein misfolding and temperature up-shift cause G1 arrest via a common mechanism dependent on heat shock factor in Saccharomycescerevisiae. Proc Natl Acad Sci U S A, 2001. 98(13): p. 7313-8.
48.Trotter, E.W., et al., Misfolded proteins are competent to mediate a subset of the responses to heat shock in Saccharomyces cerevisiae. J Biol Chem, 2002. 277(47): p. 44817-25.
49.Obrig, T.G., et al., Mechanism by Which Cycloheximide and Related Glutarimide Antibiotics Inhibit Peptide Synthesis on Reticulocyte Ribosomes. Journal of Biological Chemistry, 1971. 246(1): p. 174-&.
50.Lippincott-Schwartz, J., et al., Brefeldin A''s effects on endosomes, lysosomes, and the TGN suggest a general mechanism for regulating organelle structure and membrane traffic. Cell, 1991. 67(3): p. 601-16.
51.Samali, A., et al., Methods for monitoring endoplasmic reticulum stress and the unfolded protein response. Int J Cell Biol, 2010. 2010: p. 830307.
52.Piper, P.W., The heat shock and ethanol stress responses of yeast exhibit extensive similarity and functional overlap. FEMS Microbiol Lett, 1995. 134(2-3): p. 121-7.
53.Grimminger, V., et al., The prion curing agent guanidinium chloride specifically inhibits ATP hydrolysis by Hsp104. J Biol Chem, 2004. 279(9): p. 7378-83.
54.Gaczynska, M. and P.A. Osmulski, Small-molecule inhibitors of proteasome activity. Methods Mol Biol, 2005. 301: p. 3-22.
55.Liu, C., et al., Proteasome inhibition in wild-type yeast Saccharomyces cerevisiae cells. Biotechniques, 2007. 42(2): p. 158, 160, 162.
56.Team, R.C., R: A language and environment for statistical computing. . 2017, R Foundation for Statistical Computing: Vienna, Austria.
57.Warnes, G.R., et al., gplots: Various R Programming Tools for Plotting Data. 2016.
58.Kassambara, A. and F. Mundt, factoextra: Extract and Visualize the Results of Multivariate Data Analyses. . 2017.
59.Hsu, P.C., C.Y. Yang, and C.Y. Lan, Candida albicans Hap43 Is a Repressor Induced under Low-Iron Conditions and Is Essential for Iron-Responsive Transcriptional Regulation and Virulence. Eukaryotic Cell, 2011. 10(2): p. 207-225.
60.Thorvaldsdottir, H., J.T. Robinson, and J.P. Mesirov, Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Briefings in Bioinformatics, 2013. 14(2): p. 178-192.
61.Li, H., et al., The Sequence Alignment/Map format and SAMtools. Bioinformatics, 2009. 25(16): p. 2078-9.
62.Takagi, H., et al., QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. Plant J, 2013. 74(1): p. 174-83.
63.Benjamini, Y. and Y. Hochberg, Controlling the False Discovery Rate - a Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B-Methodological, 1995. 57(1): p. 289-300.
64.Su, G., et al., Biological network exploration with Cytoscape 3. Curr Protoc Bioinformatics, 2014. 47: p. 8 13 1-24.
65.DiCarlo, J.E., et al., Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems. Nucleic Acids Research, 2013. 41(7): p. 4336-4343.
66.Horwitz, A.A., et al., Efficient Multiplexed Integration of Synergistic Alleles and Metabolic Pathways in Yeasts via CRISPR-Cas. Cell Syst, 2015. 1(1): p. 88-96.
67.Slaymaker, I.M., et al., Rationally engineered Cas9 nucleases with improved specificity. Science, 2016. 351(6268): p. 84-8.
68.Hirotsu, N., et al., Protocol: a simple gel-free method for SNP genotyping using allele-specific primers in rice and other plant species. Plant Methods, 2010. 6.
69.Lang, G.I. and A.W. Murray, Estimating the per-base-pair mutation rate in the yeast Saccharomyces cerevisiae. Genetics, 2008. 178(1): p. 67-82.
70.Kvitek, D.J. and G. Sherlock, Reciprocal sign epistasis between frequently experimentally evolved adaptive mutations causes a rugged fitness landscape. PLoS Genet, 2011. 7(4): p. e1002056.
71.Leach, M.D., et al., Fungal Hsp90: a biological transistor that tunes cellular outputs to thermal inputs. Nature Reviews Microbiology, 2012. 10(10): p. 693-704.
72.Stark, C., et al., BioGRID: a general repository for interaction datasets. Nucleic Acids Res, 2006. 34(Database issue): p. D535-9.
73.Raman, K. and A. Wagner, Evolvability and robustness in a complex signalling circuit. Mol Biosyst, 2011. 7(4): p. 1081-92.
74.Kirschner, M. and J. Gerhart, Evolvability. Proc Natl Acad Sci U S A, 1998. 95(15): p. 8420-7.
75.Ronshaugen, M., N. McGinnis, and W. McGinnis, Hox protein mutation and macroevolution of the insect body plan. Nature, 2002. 415(6874): p. 914-7.
76.Rebeiz, M., N.H. Patel, and V.F. Hinman, Unraveling the Tangled Skein: The Evolution of Transcriptional Regulatory Networks in Development. Annu Rev Genomics Hum Genet, 2015. 16: p. 103-31.
77.Lynch, V.J. and G.P. Wagner, Resurrecting the role of transcription factor change in developmental evolution. Evolution, 2008. 62(9): p. 2131-54.
78.Maheshwari, S. and D.A. Barbash, The genetics of hybrid incompatibilities. Annu Rev Genet, 2011. 45: p. 331-55.
79.Genest, O., et al., Uncovering a Region of Heat Shock Protein 90 Important for Client Binding in E. coli and Chaperone Function in Yeast. Molecular Cell, 2013. 49(3): p. 464-473.
80.Rajon, E. and J. Masel, Compensatory evolution and the origins of innovations. Genetics, 2013. 193(4): p. 1209-20.
81.Huang, J.L., Horizontal gene transfer in eukaryotes: The weak-link model. Bioessays, 2013. 35(10): p. 868-875.
82.Husnik, F. and J.P. McCutcheon, Functional horizontal gene transfer from bacteria to eukaryotes. Nature Reviews Microbiology, 2018. 16(2): p. 67-79.
83.Bergman, A. and M.L. Siegal, Evolutionary capacitance as a general feature of complex gene networks. Nature, 2003. 424(6948): p. 549-552.
84.Ferrer, M., et al., Chaperonins govern growth of Escherichia coli at low temperatures. Nature Biotechnology, 2003. 21(11): p. 1266-1267.
85.Lind, P.A., et al., Compensatory gene amplification restores fitness after inter-species gene replacements. Mol Microbiol, 2010. 75(5): p. 1078-89.
86.Kacar, B., et al., Functional Constraints on Replacing an Essential Gene with Its Ancient and Modern Homologs. MBio, 2017. 8(4).
87.Kacar, B., et al., Experimental Evolution of Escherichia coli Harboring an Ancient Translation Protein. J Mol Evol, 2017. 84(2-3): p. 69-84.
88.Pavlicev, M. and G.P. Wagner, A model of developmental evolution: selection, pleiotropy and compensation. Trends Ecol Evol, 2012. 27(6): p. 316-22.
89.Dalal, C.K. and A.D. Johnson, How transcription circuits explore alternative architectures while maintaining overall circuit output. Genes & Development, 2017. 31(14): p. 1397-1405.
90.Wagner, G.P. and V.J. Lynch, The gene regulatory logic of transcription factor evolution. Trends Ecol Evol, 2008. 23(7): p. 377-85.
91.Lenski, R.E., et al., The evolutionary origin of complex features. Nature, 2003. 423(6936): p. 139-44.
92.Covert, A.W., 3rd, et al., Experiments on the role of deleterious mutations as stepping stones in adaptive evolution. Proc Natl Acad Sci U S A, 2013. 110(34): p. E3171-8.