WO2007038564A2 - Global transcription machinery engineering - Google Patents

Abstract

The invention relates to global transcription machinery engineering to produce altered cells having improved phenotypes.

Description

GLOBAL TRANSCRIPTION MACHINERY ENGINEERING

Related Applications

This application is a continuation-in-part of U.S. application serial number 11/238096, filed September 28, 2005, and claims the benefit under 35 U.S.C. § 119(e) of U.S. provisional application serial number 60/748315, filed December 7, 2005, the entire disclosures of which are incorporated herein by reference.

Field of the Invention The invention relates to global transcription machinery engineering to produce altered cells having improved phenotypes.

Background of the Invention

It is now generally accepted that many important cellular phenotypes, from disease states to metabolite overproduction, are affected by many genes. Yet, most cell and metabolic engineering approaches rely almost exclusively on the deletion or over-expression of single genes due to experimental limitations in vector construction and transformation efficiencies. These limitations preclude the simultaneous exploration of multiple gene modifications and confine gene modification searches to restricted sequential approaches where a single gene is modified at a time.

U.S. patent 5,686,283 described the use of a sigma factor encoded by rpoS to activate the expression of other bacterial genes that are latent or expressed at low levels in bacterial cells. This patent did not, however, describe mutating the sigma factor in order to change globally the transcription of genes. U.S. patent 5,200,341 provides a mutated rpoH gene identified as a suppressor of a temperature sensitive rpoD gene by selection of temperature-resistant mutants of a bacterial strain having the temperature sensitive rpoD gene. No mutagenesis of the bacteria was undertaken, nor was the suppressor strain selected for a phenotype other than temperature resistance. When the mutant rpoH gene is added to other bacteria that are modified to express heterologous proteins, the heterologous proteins are accumulated at increased levels in the bacteria.

U.S. patent 6,156,532 describes microorganisms that are modified by introduction of a gene coding for a heat shock protein and a gene coding for a sigma factor (rpoH) that specifically functions for the heat shock protein gene to enhance expression amount of the heat shock protein in cells. The modified microorganisms are useful for producing fermentative products such as amino acids. The sigma factor used in the microorganisms was not mutated. Directed evolution has been applied to microorganisms by shuffling of bacterial genomes for antibiotic (tylosin) production by Streptomyces (Zhang et al, Nature, 415, 644- 646 (2002)) and acid tolerance of Lactobacillus (Patnaik et al., Nature Biotech. 20, 707-712 (2002)). These methods did not target mutations in any specific gene or genes, but instead non-recombinantly shuffled the genomes of strains having a desired phenotype using protoplast fusion, followed by selection of strains having improvements in the desired phenotype.

Summary of the Invention

The invention utilizes global transcription machinery engineering to produce altered cells having improved phenotypes. In particular, the invention is demonstrated through the generation of mutated bacterial sigma factors with varying preferences for promoters on a genome-wide level. The cells resulting from introduction of the mutated sigma factors have rapid and marked improvements in phenotypes, such as tolerance of deleterious culture conditions or improved production of metabolites. The introduction of mutant transcription machinery into a cell, combined with methods and concepts of directed evolution, allows one to explore a vastly expanded search space in a high throughput manner by evaluating multiple, simultaneous gene alterations in order to improve complex cellular phenotypes.

Directed evolution through iterative rounds of mutagenesis and selection has been successful in broadening properties of antibodies and enzymes (W. P. Stemmer, Nature 370, 389-91 (1994)). These concepts have been recently extended and applied to non-coding, functional regions of DNA in the search for libraries of promoter activity spanning a broad dynamic range of strength as measured by different metrics (H. Alper, C. Fischer, E. Nevoigt, G. Stephanopoulos, Proc Natl Acad Sd USA 102, 12678-12683 (2005)). However, no evolution-inspired approaches have been directed towards the systematic modification of the global transcription machinery as a means of improving cellular phenotype. Yet, detailed biochemical studies suggest that both the transcription rate and in vitro preference for a given promoter sequence can be altered by modifying key residues on bacterial sigma factors (D. A. Siegele, J. C. Hu, W. A. Walter, C. A. Gross, J MoI Biol 206, 591-603 (1989); T. Gardella, H. Moyle, M. M. Susskind, JMoI Biol 206, 579-590 (1989)). Such modified transcription machinery units offer the unique opportunity to introduce simultaneous global transcription- level alterations that have the potential to impact cellular properties in a very profound way. According to one aspect of the invention, methods for altering the phenotype of a cell are provided. The methods include mutating a nucleic acid encoding global transcription machinery and, optionally, its promoter, expressing the nucleic acid in a cell to provide an altered cell that includes mutated global transcription machinery, and culturing the altered cell, hi some embodiments, the methods also include determining the phenotype of the altered cell or comparing the phenotype of the altered cell with the phenotype of the cell prior to alteration. In further embodiments, the methods also include repeating the mutation of the nucleic acid to produce a n^th generation altered cell. In still other embodiments, the methods also include determining the phenotype of the n^th generation altered cell or comparing the phenotype of the n^th generation altered cell with the phenotype of any prior generation altered cell or of the cell prior to alteration. In preferred embodiments, the step of repeating the mutation of the global transcription machinery includes isolating a nucleic acid encoding the mutated global transcription machinery and optionally, its promoter, from the altered cell, mutating the nucleic acid, and introducing the mutated nucleic acid into another cell.

In certain embodiments, the cell is a prokaryotic cell, preferably a bacterial cell or an archaeal cell. In such embodiments, the global transcription machinery preferably is a sigma factor or an anti-sigma factor. Nucleic acid molecules encoding the sigma factors include rpoD (σ⁷⁰) genes, rpoF (σ²⁸) genes, rpoS (σ³⁸) genes, rpoH(σⁿ) genes, rpoN(σ⁵⁴) genes, rpoE (σ²⁴) genes and fed (σ¹⁹) genes. The sigma factor or anti-sigma factor can be expressed from an expression vector. In other embodiments, the cell is a eukaryotic cell. Preferred eukaryotic cells include yeast cells, mammalian cells, plant cells, insect cells, stem cells and fungus cells. In certain embodiments, one or more of the eukaryotic cells are contained in, or form, a multicellular organism. In some embodiments, the nucleic acid is expressed in the cell from a tissue- specific promoter, a cell-specific promoter, or an organelle-specific promoter. In still other eukaryotic embodiments, the global transcription machinery binds to an

RNA polymerase I, an RNA polymerase II or an RNA polymerase III, or a promoter of an RNA polymerase I, an RNA polymerase II or an RNA polymerase III. Preferred global transcription machinery includes TFIID or a subunit thereof, such as TATA-binding protein - A -

(TBP) or a TBP-associated factor (TAF), such as TAF25. Nucleic acid molecules encoding the global transcription machinery include GALl 1 genes, SIN4 genes, RGRl genes, HRSl genes, PAFl genes, MED2 genes, SNF6 genes, SNF2 genes and SWIl genes. The global transcription machinery, in other embodiments, is a nucleic acid methyltransferase, a histone methyltransferase, a histone acetylase or a histone deacetylase. The global transcription machinery is expressed from an expression vector in certain embodiments.

The nucleic acid in some embodiments is a nucleic acid of an organelle of the eukaryotic cell, preferably a mitochondrion or a chloroplast. The nucleic acid optionally is part of an expression vector. The nucleic acid in certain embodiments is a member of a collection (e.g., a library) of nucleic acids. Thus the methods of the invention include, in some embodiments, introducing the collection into the cell.

In further embodiments, the step of expressing the nucleic acid includes integrating the nucleic acid into the genome or replacing a nucleic acid that encodes the endogenous global transcription machinery.

The mutation of the nucleic acid, in certain embodiments, includes directed evolution of the nucleic acid, such as mutation by error prone PCR or mutation by gene shuffling. In other embodiments, the mutation of the nucleic acid includes synthesizing the nucleic acid with one or more mutations. Nucleic acid mutations in the invention can include one or more point mutations, and/or one or more truncations and/or deletions.

In some embodiments of the invention, a promoter binding region of the global transcription machinery is not disrupted or removed by the one or more truncations or deletions. In other embodiments, the mutated global transcription machinery exhibits increased transcription of genes relative to the unmutated global transcription machinery, decreased transcription of genes relative to the unmutated global transcription machinery, increased repression of gene transcription relative to the unmutated global transcription machinery, and/or decreased repression of gene transcription relative to the unmutated global transcription machinery. In still other embodiments, the methods also include selecting the altered cell for a predetermined phenotype. Preferably, the step of selecting includes culturing the altered cell under selective conditions and/or high-throughput assays of individual cells for the phenotype. A wide variety of phenotypes can be selected in accordance with the invention. In some preferred embodiments, the phenotype is increased tolerance of deleterious culture conditions. Such phenotypes include: solvent tolerance or hazardous waste tolerance, e.g., ethanol, hexane or cyclohexane; tolerance of industrial media; tolerance of high sugar concentration; tolerance of high salt concentration; tolerance of high temperatures; tolerance of extreme pH; tolerance of surfactants, tolerance of osmotic stress and tolerance of a plurality of deleterious conditions.

In other preferred embodiments, the phenotype is increased metabolite production. Metabolites include lycopene, ethanol, polyhydroxybutyrate (PHB), and therapeutic proteins, such as an antibody or an antibody fragment.

In still other preferred embodiments, the phenotype is tolerance to a toxic substrate, metabolic intermediate or product. Toxic metabolites include organic solvents, acetate, para- hydroxybenzoic acid (pHBA) and overexpressed proteins.

Additional phenotypes include antibiotic resistance and increased resistance to apoptosis.

In some embodiments, the cell is contained in a multicellular organism. In such embodiments, preferred phenotypes include one or more growth characteristics, generation time, resistance to one or more pests or diseases, production of fruit or other parts of a plant, one or more developmental changes, one or more lifespan alterations, gain or loss of function and/or increased robustness.

The cell used in the methods can be optimized for the phenotype prior to mutating the global transcription machinery.

The methods of the invention, in certain embodiments, also include identifying the changes in gene expression in the altered cell. The changes in gene expression preferably are determined using a nucleic acid microarray.

According to another aspect of the invention, methods for altering the phenotype of a cell are provided. The methods include altering the expression of one or more gene products in a first cell that are identified by detecting changes in gene expression in a second cell, wherein the changes in gene expression in the second cell are produced by mutating global transcription machinery of the second cell.

In some embodiments, altering the expression of the one or more gene products in the first cell includes increasing expression of one or more gene products that were increased in the second cell. In some preferred embodiments, the expression of the one or more gene products is increased by introducing into the first cell one or more expression vectors that express the one or more gene products, or by increasing the transcription of one or more endogenous genes that encode the one or more gene products. In the latter embodiments, increasing the transcription of the one or more endogenous genes includes mutating a transcriptional control (e.g., promoter/enhancer) sequence of the one or more genes.

In other embodiments, altering the expression of the one or more gene products in the first cell includes decreasing expression of one or more gene products that were decreased in the altered cell. Preferably, the expression of the one or more gene products is decreased by introducing into the first cell nucleic acid molecules that reduce the expression of the one or more gene products, such as nucleic acid molecules that are, or express, siKNA molecules, hi other embodiments, the expression of the one or more gene products is decreased by mutating one or more genes that encode the one or more gene products or a transcriptional control (e.g., promoter/enhancer) sequence of the one or more genes.

The changes in gene expression in the second cell preferably are determined using a nucleic acid microarray.

In other embodiments, the changes in gene expression in the second cell are used to construct a model of a gene or protein network, and the model is used to select which of the one or more gene products in the network to alter.

The global transcription machinery in some embodiments includes more than one nucleic acid and/or polypeptide or is encoded by more than one nucleic acid.

Also provided according to the invention are cells produced by the foregoing methods.

According to another aspect of the invention, methods for altering the production of a metabolite are provided. The methods include mutating, according to any of the foregoing methods, global transcription machinery of a cell that produces a selected metabolite to produce an altered cell, and isolating altered cells that produce increased or decreased amounts of the selected metabolite. In some embodiments, the methods also include culturing the isolated cells, and recovering the metabolite from the cells or the cell culture. Preferred metabolites include lycopene, ethanol, polyhydroxybutyrate (PHB) and therapeutic proteins, such as recombinant proteins, antibodies or antibody fragments.

In some embodiments the cells are prokaryotic cells, including bacterial cells or archaeal cells. In other embodiments, the cells are eukaryotic cells, including yeast cells, mammalian cells, plant cells, insect cells, stem cells and fungus cells. The global transcription machinery in certain of the latter embodiments is encoded by nucleic acid of an organelle of the eukaryotic cell, preferably a mitochondrion or a chloroplast.

According to another aspect of the invention, collections (e.g., a library) including a plurality of different nucleic acid molecule species are provided, in which it is preferred that each nucleic acid molecule species encodes global transcription machinery comprising different mutation(s). In some preferred embodiments, the global transcription machinery is a sigma factor or an anti-sigma factor. Preferably the nucleic acid encoding the sigma factor is a rpoD (σ⁷⁰) gene, a rpoF (σ²⁸) gene, a rpoS (σ³⁸) gene, a rpoH (σ³²) gene, a rpoN (σ⁵⁴) gene, a rpoE (σ²⁴) gene or a feel (σ¹⁹) gene. In other preferred embodiments, the global transcription machinery binds to an RNA polymerase I, an RNA polymerase II or an RNA polymerase III, or a promoter of an RNA polymerase I, an RNA polymerase II or an RNA polymerase III. Preferably the global transcription machinery is TFIID or a subunit thereof, such as a TATA-binding protein (TBP) or a TBP-associated factor (TAF), such as TAF25. In other embodiments, the global transcription machinery is a nucleic acid methyltransferase, a histone methyltransferase, a histone acetylase or a histone deacetylase.

In certain embodiments, the nucleic acid molecule species are contained in expression vectors, preferably expressed from a tissue-specific promoter, a cell-specific promoter, or an organelle-specific promoter. The expression vectors preferably contain a plurality of different nucleic acid molecule species, wherein each nucleic acid molecule species encodes different global transcription machinery.

In other embodiments, the global transcription machinery is mutated by directed evolution, which preferably is performed using error prone PCR and/or using gene shuffling. Preferred mutation(s) in the global transcription machinery is/are one or more point mutations and/or one or more truncations and/or deletions. In some embodiments, the truncation does not include the promoter binding region of the global transcription machinery.

In still other embodiments, the global transcription machinery of a cell is mutated according to any of the foregoing methods.

In a further aspect of the invention, collections (e.g., a library) of cells is provide that includes the foregoing collections of nucleic acid molecules. In some embodiments, the collection includes a plurality of cells, each of the plurality of cells comprising one or more of the nucleic acid molecules. The cells preferably are prokaryotic cells, such as bacterial cells or archaeal cells or eukaryotic cells, such as yeast cells, mammalian cells, plant cells, insect cells, stem cells or fungus cells. In other embodiments, the nucleic acid molecules are integrated into the genome of the cells or replace nucleic acids that encode the endogenous global transcription machinery.

According to still another aspect of the invention, nucleic acids encoding global transcription machinery produced by a plurality of rounds of mutation are provided. The ' plurality of rounds of mutation preferably include directed evolution, such as that performed by mutation by error prone PCR and/or mutation by gene shuffling.

In some embodiments , the nucleic acid encodes a plurality of different global transcription machinery species. The nucleic acid preferably encodes a plurality of different versions of the same type of global transcription machinery species. Also provided according to the invention is global transcription machinery encoded by the foregoing nucleic acids.

In another aspect of the invention, truncated sigma factor proteins are provided that include (carboxy-terminal) region 4.

According to a further aspect of the invention, methods for bioremediation of a selected waste product are provided. The methods include mutating, according to any of the foregoing methods, global transcription machinery of a cell to produce an altered cell, isolating altered cells that metabolize an increased amount of the selected waste product relative to unaltered cells, culturing the isolated cells, and exposing the altered cells to the selected waste product, thereby providing bioremediation of the selected waste product.

These and other aspects of the invention, as well as various embodiments thereof, will become more apparent in reference to the drawings and detailed description of the invention.

Brief Description of the Drawings

Figure 1 depicts the basic methodology of global transcription machinery engineering. By introducing altered global transcription machinery into a cell, the transcriptome is altered and the expression level of genes changes in a global manner. In this study, the bacterial sigma factor 70 (encoded by rpoD) was subjected to error-prone PCR to generate various mutants. The mutants were then cloned into a low-copy expression vector, during which the possibility arose for a truncated form of the sigma factor due to the presence of a nearly complete internal restriction enzyme site. The vectors were then transformed into E. coli and screened based on the desired phenotype. Isolated mutants can then be subjected to subsequent rounds of mutagenesis and selection to further improve phenotypes.

Figure 2 shows the isolation of ethanol tolerant sigma factor mutants. Strains were isolated containing mutant sigma factors which increased the tolerance to ethanol. Fig. 2A: The overall enhancement of phenotype through the various round of directed evolution of the mutant factor. Overall enhancement (y-axis) is assessed by talcing the summation of the fold reduction of doubling time for the mutant over the control at 0, 20, 40, 50, 60, 70 and 80 g/L of ethanol. By the third round, the improvement in growth rate seems to be small and incremental. Fig. 2B: The location of mutations on the σ⁷⁰ protein are indicated in relation to previously identified critical functional regions. The second round mutagenesis resulted in the identification of a truncated factor containing only one of the two prior mutations in that region. Fig. 2C: Growth curves are presented for the Round 3 mutant (Red) and control (Blue) strains. The round 3 mutant has significantly improved growth rates at all tested ethanol concentrations. Fig. 2D: Amino acid sequence alignments of the ethanol tolerant mutant sigma factors (Native, SEQ ID NO: 17; Round 1, SEQ ID NO: 18; Round 2, SEQ ID NO: 19; Round 3, SEQ ID NO:20).

Figure 3 shows sequence analysis of sigma factors for additional phenotypes. Fig. 3 A: The location of the mutations in the acetate and pHBA mutants of the σ⁷⁰ protein area indicated in relation to previously identified critical functional regions. The vast majority of the acetate mutants were full-length sigma factors. The identified mutant for pHBA was a truncated factor which is expected to act as an inhibitor to specific gene transcription. Fig. 3B: Amino acid sequence alignments of the acetate tolerant mutant sigma factors (Native, SEQ ID NO: 17; AcI, SEQ ID NO:21; Ac2, SEQ ID NO:22; Ac3, SEQ ID NO:23; Ac4, SEQ ID NO:24; Ac5, SEQ ID NO:25). Fig. 3C: Amino acid sequence alignments of the pHBA tolerant mutant sigma factors (Native, SEQ ID NO: 17; pHBAl, SEQ ID NO:26).

Figure 4 depicts cell densities of cultures of isolated strains with hexane tolerant sigma factor mutants. Fig. 4 also shows the sequences of the best hexane-tolerant mutants, Hex-12 and Hex-18. Figure 5 shows cell densities of cultures of isolated strains with cyclohexane tolerant sigma factor mutants.

Figure 6 depicts cell densities of cultures of isolated strains of antibiotic resistant sigma factor mutants at increasing concentrations of nalidixic acid.

Figures 7A - 7D show the results of culturing and assaying selected strains for lycopene production at 15 and 24 hours, along with the sequence of the sigma factor mutant from the best strain. Figure 8 is a dot plot that depicts the maximum fold increase in lycopene production achieved over the control during the fermentation. The size of the circle is proportional to the fold increase.

Figure 9 illustrates the lycopene content after 15 hours for several strains of interest. This figure compares the improvement provided by global transcription machinery engineering to traditional methods of strain improvement by sequential gene knockouts. In this example, the method of global transcription machinery engineering was more potent in increasing the phenotype than a series of multiple gene knockouts. Furthermore, improvements were achieved in pre-engineered strains. Figure 10 shows strains selected for increased exponential phase PHB in a glucose- minimal media. Fig. 7A presents the results for various strains (bars in red and yellow represent controls) obtained using sigma factor engineering. Fig. 7B presents the results of selected strains from a random knockout library created using transposon mutagenesis.

Figure 11 depicts cell densities of cultures of isolated strains of SDS-tolerant sigma factor mutants at increasing concentrations of SDS, along with the sequence of the sigma factor mutant from the best strain.

Figure 12 shows a growth analysis of LiCl gTME mutants in yeast. Strains harboring mutant Tq/25 or Sptl5 were isolated with through serial subculturing in elevated levels of LiCl in a synthetic minimal medium. The growth yield (as measured by OD600) is shown for mutant and control strains after 16 hours. The Tq/25 outperformed the control at lower concentrations of LiCl, while the SptlS mutant was more effective at higher concentrations. Figure 13 depicts sequence analysis of LiCl gTME mutants in yeast. Mutations are shown mapped onto a schematic showing critical functional components of the respective factor. Each mutant was seen to possess only a single amino acid substitution. Figure 14 shows a growth analysis of glucose gTME mutants in yeast. Strains harboring mutant Tq/25 or Sptl 5 were isolated with through serial subculturing in elevated levels of glucose in a synthetic minimal medium. Here, both proteins show an improvement across a similar range of concentrations, with the SPTl 5 protein giving the largest improvement. Figure 15 depicts sequence analysis of glucose gTME mutants in yeast. Mutations are shown mapped onto a schematic showing critical functional components of the respective factor. Each mutant was seen to possess only a single amino acid substitution, however several other SPTl 5 proteins were isolated, some possessing many mutations. Figure 16 shows a growth analysis of ethanol-glucose gTME mutants in yeast. Strains harboring mutant Taf25 or Sptl5 were isolated with through serial subculturing in elevated levels of ethanol and glucose in a synthetic minimal medium and assayed for growth at 20 hours. Here, the SPT 15 protein far exceeded the impact of the TAF25 mutant. Figure 17 depicts sequence analysis of ethanol-glucose gTME mutants in yeast.

Mutations are shown mapped onto a schematic showing critical functional components of the respective factor. Each mutant was seen to possess several single amino acid substitutions in critical regions for DNA or protein contacts.

Detailed Description of the Invention

Global transcription machinery is responsible for controlling the transcriptome in all cellular systems (prokaryotic and eukaryotic). In bacterial systems, the sigma factors play a critical role in orchestrating global transcription by focusing the promoter preferences of the RNA polymerase holoenzyme (R. R. Burgess, L. Anthony, Curr. Opin. Microbiol 4, 126-131 (2001)). Escherichia coli contains six alternative sigma factors and one principal factor, σ⁷⁰, encoded by the gene rpoD. On the protein level, regions of residues have been analyzed for contacts with promoter sites and the holoenzyme (J. T. Owens et al., PNAS 95, 6021-6026 (1998)). Crystal structure analysis and site specific mutagenesis of σ⁷⁰ in E. coli and other bacteria, have demonstrated the ability to alter the in vitro promoter preference of the RNA polymerase holoenzyme evidenced by increased or decreased transcription of a reporter gene (A. Malhotra, E. Severinova, S. A. Darst, Cell 87, 127-36 (1996)). This invention exploits the ability to generate mutant sigma factors with varying preferences for promoters on a genome-wide level.

Traditional strain improvement paradigms rely predominantly on making sequential, single-gene modifications and often fail to reach the global maxima. The reason is that metabolic landscapes are complex (H. Alper, K. Miyaoku, G. Stephanopoulos, Nat Biotechnol 23, 612-616 (2005); H. Alper, Y.-S. Jin, J. F. Moxley, G. Stephanopoulos, Metab Eng 7, 155-164 (2005)) and incremental or greedy search algorithms fail to uncover synthetic mutants that are beneficial only when all mutations are simultaneously introduced. Protein engineering on the other hand can quickly improve fitness, through randomized mutagenesis and selection for enhanced antibody affinity, enzyme specificity, or catalytic activity (E. T. Boder, K. S. Midelfort, K. D. Wittrup, Proc Natl Acad Sci USA 91, 10701-5 (2000); A. Glieder, E. T. Farinas, F. H. Arnold, Nat Biotechnol 20, 1135-9 (2002); N. Varadarajan, J. Gam, M. J. Olsen, G. Georgiou, B. L. Iverson, Proc Natl Acad Sci USA 102, 6855-60 (2005)). An important reason for the drastic enhancement obtained in these examples is the ability of these methods to probe a significant subset of the huge amino acid combinatorial space by evaluating many simultaneous mutations. Using the invention, we exploit the global regulatory functions of the σ⁷⁰ sigma factor to similarly introduce multiple simultaneous gene expression changes and thus facilitate whole-cell engineering by selecting mutants responsible for improved cellular phenotype.

The invention provides methods for altering the phenotype of a cell. In the methods include mutating a nucleic acid encoding a global transcription machinery protein and, optionally, its promoter, expressing the nucleic acid in a cell to provide an altered cell that includes a mutated global transcription machinery protein, and culturing the altered cell. As used herein, "global transcription machinery" is one or more molecules that modulates the transcription of a plurality of genes. The global transcription machinery can be proteins that affect gene transcription by interacting with and modulating the activity of a RNA polymerase molecule. The global transcription machinery also can be proteins that alter the ability of the genome of a cell to be transcribed (e.g., methyltransferases, histone methyltransferases, histone acetylases and deacetylases). Further, global transcription machinery can be molecules other than proteins (e.g., micro RNAs) that alter transcription of a plurality of genes. Global transcription machinery useful in accordance with the invention include bacterial sigma factors and anti-sigma factors. Exemplary genes that encode sigma factors include rpoD, encoding σ⁷⁰; rpoF, encoding σ²⁸; rpoS, encoding σ³⁸; rpoH, encoding σ³²; rpoN, encoding σ⁵⁴; rpoE, encoding σ²⁴; sad fed, encoding σ¹⁹. Anti-sigma factors bind to the sigma factors and control their availability and consequently transcription. In E. coli, anti-sigma factors are encoded by rsd (for sigma factor 70) or flgM, among others. The anti- sigma factors can be mutated to control their impact in transcription for normal cells. In addition, novel pairings of mutant sigma factors with mutant anti-sigma factors can be created to create further control of transcription in cells. For example, the anti-sigma factor can be expressed using an inducible promoter, which allows for tunable control of the phenotype imparted by the mutant sigma factor.

Global transcription machinery also includes polypeptides that bind to and modulate the activity of eukaryotic RNA polymerases, such as RNA polymerase I, RNA polymerase II or RNA polymerase III, or a promoter of RNA polymerase I, RNA polymerase II or RNA polymerase III. Examples of such eukaryotic global transcription machinery are TFIID or a subunit thereof, such as TATA-binding protein (TBP) or a TBP-associated factor (TAP) such as TAF25, and elongation factors. Further examples from yeast include GALl 1, SIN4, RGRl, HRSl, PAFl, MED2, SNF6, SNF2, and SWIl. Global transcription machinery also includes polypeptides that alter the ability of chromosomal DNA to be transcribed, such as nucleic acid methyltransferases (e.g., DamMT, DNMTl, Dnmt3a); histone methyltransferases (e.g., Setl, MLLl); histone acetylases (e.g., PCAF, GCN5, Sas2p and other MYST-type histone acetylases, TIP60); and histone deacetylases (e.g., HDACl, HDAl, HDAC2, HDAC3, RPD3, HDAC8, Sir2p), as well as associated factors (e.g., HDACs are associated with mSin3A, Mi-2/NRD, CoREST/kiaa0071, N-CoR and SMRT).

Still other global transcription machinery is encoded by nucleic acid molecules of an organelle of a eukaryotic cell, such as a mitochondrion or a chloroplast. m many instances, the process of mutating the global transcription machinery will include iteratively making a plurality of mutations of the global transcription machinery, but it need not, as even a single mutation of the global transcription machinery can result in dramatic alteration of phenotype, as is demonstrated herein.

While the methods of the invention typically are carried out by mutating the global transcription machinery followed by introducing the mutated global transcription machinery into a cell to create an altered cell, it is also possible to mutate endogenous global transcription machinery genes, e.g., by replacement with mutant global transcription machinery or by in situ mutation of the endogenous global transcription machinery. As used herein, "endogenous" means native to the cell; in the case of mutating global transcription machinery, endogenous refers to the gene or genes of the global transcription machinery that are in the cell. In contrast, the more typical methodology includes mutation of a global transcription machinery gene or genes outside of the cell, followed by introduction of the mutated gene(s) into the cell.

The global transcription machinery genes can be of the same species or different species as the cell into which they are introduced. For example, as shown herein, E. coli sigma factor 70 was mutated and introduced into E. coli to alter the phenotype of the E coli cells. Other global transcription machinery of E. coli also could be used in the same fashion. Similarly, global transcription machinery of a particular yeast species, e.g., S. cerevisiae or S. pombe, could be mutated and introduced into the same yeast species. Likewise, global transcription machinery of a nematode species, e.g., C. elegans, or a mammalian species, e.g., M. musculus, R. norvegicus or H. sapiens, can be mutated and introduced into the same species in a manner similar to the specific examples provided herein, using standard recombinant genetic techniques. Alternatively, global transcription machinery from different species can be utilized to provide additional variation in the transcriptional control of genes. For example, global transcription machinery of a Streptomyces bacterium could be mutated and introduced into E. coli. The different global transcription machinery also could be sourced from different kingdoms or phyla of organisms. Depending on the method of mutation used, same and different global transcription machinery can be combined for use in the methods of the invention, e.g., by gene shuffling.

Optionally, the transcriptional control sequences of global transcription machinery can be mutated, rather than the coding sequence itself. Transcriptional control sequences include promoter and enhancer sequences. The mutated promoter and/or enhancer sequences, linked to the global transcription machinery coding sequence, can then be introduced into the cell.

After the mutant global transcription machinery is introduced into the cell to make an altered cell, then the phenotype of the altered cell is determined/assayed. This can be done by selecting altered cells for the presence (or absence) of a particular phenotype. Examples of phenotypes are described in greater detail below. The phenotype also can be determined by comparing the phenotype of the altered cell with the phenotype of the cell prior to alteration.

In preferred embodiments, the mutation of the global transcription machinery and introduction of the mutated global transcription machinery are repeated one or more times to produce an "n^th generation" altered cell, where "n" is the number of iterations of the mutation and introduction of the global transcription machinery. For example, repeating the mutation and introduction of the global transcription machinery once (after the initial mutation and introduction of the global transcription machinery) results in a second generation altered cell. The next iteration results in a third generation altered cell, and so on. The phenotypes of the cells containing iteratively mutated global transcription machinery then are determined (or compared with a cell containing non-mutated global transcription machinery or a previous iteration of the mutant global transcription machinery) as described elsewhere herein.

The process of iteratively mutating the global transcription machinery allows for improvement of phenotype over sequential mutation steps, each of which may result in multiple mutations of the global transcription machinery. It is also possible that the iterative mutation may result in mutations of particular amino acid residues "appearing" and "disappearing" in the global transcription machinery over the iterative process. Examples of such mutations are provided in the working examples. In a typical use of the methodology, the global transcription machinery is subjected to directed evolution by mutating a nucleic acid molecule that encodes the global transcription machinery. A preferred method to mutate the nucleic acid molecule is to subject the coding sequence to mutagenesis, and then to insert the nucleic acid molecule into a vector (e.g., a plasmid). This process may be inverted if desired, i.e., first insert the nucleic acid molecule into a vector, and then subject the sequence to mutagenesis, although it is preferred to mutate the coding sequence prior to inserting it in a vector.

When the directed evolution of the global transcription machinery is repeated, i.e., in the iterative processes of the invention, a preferred method includes the isolation of a nucleic acid encoding the mutated global transcription machinery and optionally, its promoter, from the altered cell. The isolated nucleic acid molecule is then mutated (producing a nucleic acid encoding a second generation mutated global transcription machinery), and subsequently introduced into another cell.

The isolated nucleic acid molecule when mutated, forms a collection of mutated nucleic acid molecules that have different mutations or sets of mutations. For example, the nucleic acid molecule when mutated randomly can have set of mutations that includes mutations at one or more positions along the length of the nucleic acid molecule. Thus, a first member of the set may have one mutation at nucleotide nl (wherein nx represents a number of the nucleotide sequence of the nucleic acid molecule, with x being the position of the nucleotide from the first to the last nucleotide of the molecule). A second member of the set may have one mutation at nucleotide n2. A third member of the set may have two mutations at nucleotides nl and n3. A fourth member of the set may have two mutations at positions n4 and n5. A fifth member of the set may have three mutations: two point mutations at nucleotides n4 and n5, and a deletion of nucleotides n6-n7. A sixth member of the set may have point mutations at nucleotides nl, n5 and n8, and a truncation of the 3' terminal nucleotides. A seventh member of the set may have nucleotides n9-nlθ switched with nucleotides nll-nl2. Various other combinations can be readily envisioned by one of ordinary skill in the art, including combinations of random and directed mutations. The collection of nucleic acid molecules can be a library of nucleic acids, such as a number of different mutated nucleic acid molecules inserted in a vector. Such a library can be stored, replicated, aliquotted and/or introduced into cells to produce altered cells in accordance with standard methods of molecular biology. Mutation of the global transcription machinery for directed evolution preferably is random. However, it also is possible to limit the randomness of the mutations introduced into the global transcription machinery, to make a non-random or partially random mutation to the global transcription machinery, or some combination of these mutations. For example, for a partially random mutation, the mutation(s) may be confined to a certain portion of the nucleic acid molecule encoding the global transcription machinery.

The method of mutation can be selected based on the type of mutations that are desired. For example, for random mutations, methods such as error-prone PCR amplification of the nucleic acid molecule can be used. Site-directed mutagenesis can be used to introduce specific mutations at specific nucleotides of the nucleic acid molecule. Synthesis of the nucleic acid molecules can be used to introduce specific mutations and/or random mutations, the latter at one or more specific nucleotides, or across the entire length of the nucleic acid molecule. Methods for synthesis of nucleic acids are well known in the art (e.g., Tian et al., Nature 432: 1050-1053 (2004)).

DNA shuffling (also known as gene shuffling) can be used to introduce still other mutations by switching segments of nucleic acid molecules. See, e.g., US patent 6,518,065, related patents, and references cited therein. The nucleic acid molecules used as the source material to be shuffled can be nucleic acid molecule(s) that encode(s) a single type of global transcription machinery (e.g., σ⁷⁰), or more than one type of global transcription machinery. For example, nucleic acid molecules encoding different global transcription machinery, such as different sigma factors of a single species (e.g., σ⁷⁰ and σ²⁸ of E. coli), or sigma factors from different species can be shuffled. Likewise, nucleic acid molecules encoding different types of global transcription machinery, e.g., sigma factor 70 and TFIID, can be shuffled.

A variety of other methods of mutating nucleic acid molecules, in a random or non- random fashion, are well known to one of ordinary skill in the art. One or more different methods can be used combinatorially to make mutations in nucleic acid molecules encoding global transcription machinery. In this aspect, "combinatorially" means that different types of mutations are combined in a single nucleic acid molecule, and assorted in a set of nucleic acid molecules. Different types of mutations include point mutations, truncations of nucleotides, deletions of nucleotides, additions of nucleotides, substitutions of nucleotides, and shuffling (e.g., re-assortment) of segments of nucleotides. Thus, any single nucleic acid molecule can have one or more types of mutations, and these can be randomly or non- randomly assorted in a set of nucleic acid molecules. For example, a set of nucleic acid molecules can have a mutation common to each nucleic acid molecule in the set, and a variable number of mutations that are not common to each nucleic acid molecule in the set. The common mutation, for example, may be one that is found to be advantageous to a desired altered phenotype of the cell.

Preferably a promoter binding region of the global transcription machinery is not disrupted or removed by the one or more truncations or deletions.

The mutated global transcription machinery can exhibit increased or decreased transcription of genes relative to the unmutated global transcription machinery. In addition, the mutated global transcription machinery can exhibit increased or decreased repression of transcription of genes relative to the unmutated global transcription machinery. As used herein, a "vector" may be any of a number of nucleic acids into which a desired sequence may be inserted by restriction and ligation for transport between different genetic environments or for expression in a host cell. Vectors are typically composed of DNA although RNA vectors are also available. Vectors include, but are not limited to: plasmids, phagemids, virus genomes and artificial chromosomes. A cloning vector is one which is able to replicate autonomously or integrated in the genome in a host cell, and which is further characterized by one or more endonuclease restriction sites at which the vector may be cut in a determinable fashion and into which a desired DNA sequence may be ligated such that the new recombinant vector retains its ability to replicate in the host cell. In the case of plasmids, replication of the desired sequence may occur many times as the plasmid increases in copy number within the host bacterium or just a single time per host before the host reproduces by mitosis. In the case of phage, replication may occur actively during a lytic phase or passively during a lysogenic phase.

An expression vector is one into which a desired DNA sequence may be inserted by restriction and ligation such that it is operably joined to regulatory sequences and may be expressed as an RNA transcript. Vectors may further contain one or more marker sequences suitable for use in the identification of cells which have or have not been transformed or transfected with the vector. Markers include, for example, genes encoding proteins which increase or decrease either resistance or sensitivity to antibiotics or other compounds, genes which encode enzymes whose activities are detectable by standard assays known in the art (e.g., β-galactosidase, luciferase or alkaline phosphatase), and genes which visibly affect the phenotype of transformed or transfected cells, hosts, colonies or plaques (e.g., green fluorescent protein). Preferred vectors are those capable of autonomous replication and expression of the structural gene products present in the DNA segments to which they are operably joined.

As used herein, a coding sequence and regulatory sequences are said to be "operably" joined when they are covalently linked in such a way as to place the expression or transcription of the coding sequence under the influence or control of the regulatory sequences. If it is desired that the coding sequences be translated into a functional protein, two DNA sequences are said to be operably joined if induction of a promoter in the 5' regulatory sequences results in the transcription of the coding sequence and if the nature of the linkage between the two DNA sequences does not (1) result in the introduction of a frame-shift mutation, (2) interfere with the ability of the promoter region to direct the transcription of the coding sequences, or (3) interfere with the ability of the corresponding RNA transcript to be translated into a protein. Thus, a promoter region would be operably joined to a coding sequence if the promoter region were capable of effecting transcription of that DNA sequence such that the resulting transcript might be translated into the desired protein or polypeptide. The precise nature of the regulatory sequences needed for gene expression may vary between species or cell types, but shall in general include, as necessary, 5' non-transcribed and 5' non-translated sequences involved with the initiation of transcription and translation respectively, such as a TATA box, capping sequence, CAAT sequence, and the like. In particular, such 5' non-transcribed regulatory sequences will include a promoter region which includes a promoter sequence for transcriptional control of the operably joined gene.

Regulatory sequences may also include enhancer sequences or upstream activator sequences as desired. The vectors of the invention may optionally include 5' leader or signal sequences. The choice and design of an appropriate vector is within the ability and discretion of one of ordinary skill in the art. Expression vectors containing all the necessary elements for expression are commercially available and known to those skilled in the art. See, e.g., Sambrook et al., Molecular Cloning: A Laboratory Manual, Second Edition, Cold Spring Harbor Laboratory Press, 1989. Cells are genetically engineered by the introduction into the cells of heterologous DNA (RNA) encoding a CT antigen polypeptide or fragment or variant thereof. That heterologous DNA (RNA) is placed under operable control of transcriptional elements to permit the expression of the heterologous DNA in the host cell.

Preferred systems for mRNA expression in mammalian cells are those such as pRc/CMV or pcDNA3.1 (available from Invitrogen, Carlsbad, CA) that contain a selectable marker such as a gene that confers G418 resistance (which facilitates the selection of stably transfected cell lines) and the human cytomegalovirus (CMV) enhancer-promoter sequences. Additionally, suitable for expression in primate or canine cell lines is the pCEP4 vector (Invitrogen), which contains an Epstein Barr Virus (EBV) origin of replication, facilitating the maintenance of plasmid as a multicopy extrachromosomal element.

When the nucleic acid molecule that encodes mutated global transcription machinery is expressed in a cell, a variety of transcription control sequences (e.g., promoter/enhancer sequences) can be used to direct expression of the global transcription machinery. The promoter can be a native promoter, i.e., the promoter of the global transcription machinery gene, which provides normal regulation of expression of the global transcription machinery. The promoter also can be one that is ubiquitously expressed, such as beta-actin, ubiquitin B, phage promoters or the cytomegalovirus promoter. A promoter useful in the invention also can be one that does not ubiquitously express the global transcription machinery. For example, the global transcription machinery can be expressed in a cell using a tissue-specific promoter, a cell-specific promoter, or an organelle-specific promoter. A variety of conditional promoters also can be used, such as promoters controlled by the presence or absence of a molecule, such as the tetracycline-responsive promoter (M. Gossen and H. Bujard, Proc. Natl Acad. ScL USA, 89, 5547-5551 (1992)).

A nucleic acid molecule that encodes mutated global transcription machinery can be introduced into a cell or cells using methods and techniques that are standard in the art. For example, nucleic acid molecules can be introduced by various transfection methods, transduction, electroporation, particle bombardment, injection (including microinjection of cells and injection into multicellular organisms), lipofection, yeast spheroplast/cell fusion for YACs (yeast artificial chromosomes), Agrobacterium-mediated transformation for plant cells, etc..

Expressing the nucleic acid molecule encoding mutated global transcription machinery also may be accomplished by integrating the nucleic acid molecule into the genome or by replacing a nucleic acid sequence that encodes the endogenous global transcription machinery.

By mutating global transcription machinery, novel compositions are provided, including nucleic acid molecules encoding global transcription machinery produced by a plurality of rounds of mutation. The plurality of rounds of mutation can include directed evolution, in which each round of mutation is followed by a selection process to select the mutated global transcription machinery that confer a desired phenotype. The methods of mutation and selection of the mutated global transcription machinery are as described elsewhere herein. Global transcription machinery produced by these nucleic acid molecules also are provided.

In certain cases, it has been found that mutated global transcription machinery are truncated forms of the unmutated global transcription machinery. In particular, for sigma factor 70, it has been found that an amino-terminal truncation of σ⁷⁰ that leaves only the carboxyl-terminus of the σ⁷⁰ protein confers advantageous phenotypes to bacteria in which it is introduced. Thus, fragments of global transcription machinery are provided, particularly fragments that retain the promoter binding properties of the unmutated global transcription machinery, more particularly σ⁷⁰ fragments that include region 4. Nucleic acid molecules encoding the truncated global transcription machinery also are provided, including nucleic acid molecules as contained in vectors and/or cells. The cells useful in the invention include prokaryotic cells and eukaryotic cells.

Prokaryotic cells include bacterial cells and archaeal cells. Eukaryotic cells include yeast cells, mammalian cells, plant cells, insect cells, stem cells, and fungus cells. Eukaryotic cells may be contained in, e.g., part of or all of, a multicellular organism. Multicellular organisms include mammals, nematodes such as Caenorhabditis elegans, plants such as Arabidopsis thaliana, Bombyx mori, Xenopus laevis, zebrafϊsh (Danio reriό), sea urchin and Drosophila melanogaster.

Examples of bacteria include Escherichia spp., Streptomyces spp., Zymonas spp., Acetobacter spp., Citrobacter spp., Synechocystis spp., Rhizobium spp., Clostridium spp., Corynebacterium spp., Streptococcus spp., Xanthomonas spp., Lactobacillus spp., Lactococcus spp., Bacillus spp., Alcaligenes spp., Pseudomonas spp., Aeromonas spp.,

Azotobacter spp., Comamonas spp., Mycobacterium spp., Rhodococcus spp., Gluconobacter spp., Ralstonia spp., Acidithiobacillus spp., Microlunatus spp., Geobacter spp., Geobacillus spp., Arthrobacter spp., Flavobacterium spp., Serratia spp., Saccharopolyspora spp., Thermus spp., Stenotrophomonas spp., Chromobacterium spp., Sinorhizobium spp.,

Saccharopolyspora spp., Agrobacterium spp. and Pantoea spp.

Examples of archaea (also known as archaebacteria) include Methylomonas spp.,

Sulfolobus spp., Methylobacterium spp. Halobacterium spp., Methanobacterium spp., Methanococci spp., Methanopyri spp., Archaeoglobus spp., Ferroglobus spp.,

Thermoplasmata spp. and Thermococci spp.

Examples of yeast include Saccharomyces spp., Schizosaccharomyces spp., Pichia spp., Paffia spp., Kluyveromyces spp., Candida spp., Talaromyces spp., and Debaryomyces spp. Examples of fungi include Aspergillus spp., Pennicilium spp., Fusarium spp.,

Rhizopus spp., Acremonium spp., Neurospora spp., Sordaria spp., Magnaporthe spp.,

Allomyces spp., Ustilago spp., Botrytis spp., and Trichoderma spp.

Examples of insect cells include Spodopterafrugiperda cell lines such as Sf9 and

SGl, Drosophila melanogaster cell lines such as Kc, Ca, 311, DH14, DH15, DH33P1, P2, P4 and SCHNEIDER-2 (D. Mel - S2) and Lymantria dispar cedll lines such as 652Y.

Examples of mammalian cells include primary cells, such as stem cells and dendritic cells, and mammalian cell lines such as Vero, HEK 293, Sρ2/0, P3UI, CHO, COS, HeLa,

BAE-I, MRC-5, NIH 3T3, L929, HEPG2, NSO, U937, HL60, YACl, BHK, ROS, Y79,

Neuro2a, NRK, MCF-IO, RAW 264.7, and TBY-2. Stem cell lines include hESC BGOl, hESC BGOlV, ES-C57BL/6, ES-D3 GL, Jl, Rl,

RW.4, 7AC5/EYFP, and Rl/E. Additional human stem cell lines include (NIH designations)

CHOI, CH02, GEOl, GE07, GE09, GE13, GE14, GE91, GE92, SA19, MBOl, MB02, MB03,

NCOl, NC02, NC03, RL05, RL07, RLlO, RLl 3, RLl 5, RL20, and RL21.

Directed evolution of global transcription machinery produces altered cells, some of which have altered phenotypes. Thus the invention also includes selecting altered cells for a predetermined phenotype or phenotypes. Selecting for a predetermined phenotype can be accomplished by culturing the altered cells under selective conditions. Selecting for a predetermined phenotype also can be accomplished by high-throughput assays of individual cells for the phenotype. For example, cells can be selected for tolerance to deleterious conditions and/or for increased production of metabolites. Tolerance phenotypes include tolerance of solvents such as ethanol, and organic solvents such as hexane or cyclohexane; tolerance of toxic metabolites such as acetate, para-hydroxybenzoic acid (pHBA), para- hydroxycinnamic acid, hydroxypropionaldehyde, overexpressed proteins, organic solvents and immuno-suppressant molecules; tolerance of surfactants; tolerance of osmotic stress; tolerance of high sugar concentrations; tolerance of high temperatures; tolerance of extreme pH conditions (high or low); resistance to apoptosis; tolerance of toxic substrates such as hazardous waste; tolerance of industrial media; increased antibiotic resistance, etc. Selection for ethanol tolerance, organic solvent tolerance, acetate tolerance, para-hydroxybenzoic acid tolerance, SDS tolerance and antibiotic resistance are exemplified in the working examples. In other working examples, selection for increased production of lycopene and polyhydroxybutyrate are exemplified. In working examples with yeast cells, selection for high sugar (glucose) tolerance,, osmotic stress (LiCl) tolerance, and multiple tolerance to both high glucose and ethanol concentrations are exemplified.

Additional phenotypes that are manifested in multicellular organisms also can be selected. Mutant versions of global transcription machinery can be introduced into mammalian or other eukaryotic cell lines, or even introduced into whole organism (e.g., through introduction into germ cells lines or injections into oocytes) to allow for a screening of phenotypes. Such phenotypes may or may not be manifested in a single cell of the organism, and include: one or more growth characteristics, generation time, resistance to one or more pests or diseases, production of fruit or other parts of a plant, one or more developmental changes, one or more lifespan alterations, gain or loss of function, increased robustness, etc. As used herein with respect to altered cells containing mutated global transcription machinery, "tolerance" means that an altered cell is able to withstand the deleterious conditions to a greater extent than an unaltered cell, or a previously altered cell. For example, the unaltered or previously altered cell is a "parent" of the "child" altered cell, or the unaltered or previously altered cell is the (n-l)^th generation as compared to the cell being tested, which is n^th generation. "Withstanding the deleterious conditions" means that the altered cell has increased growth and/or survival relative to the unaltered or previously altered cell. This concept also includes increased production of metabolites that are toxic to cells.

With respect to tolerance of high sugar concentrations, such concentrations can be > 100 g/L, > 120 g/L, ≥ 140 g/L, > 160 g/L, > 180 g/L, > 200 g/L, > 250 g/L, > 300 g/L, > 350 g/L, > 400 g/L, > 450 g/L, > 500 g/L, etc. With respect to tolerance of high salt concentrations, such concentrations can be > 1 M, > 2 M, > 3 M, > 4 M₃ > 5 M, etc. With respect to tolerance of high temperatures, the temperatures can be, e.g., >42°C, >44°C, >46°C, >48°C, >50°C for bacterial cells. Other temperature cutoffs may be selected according to the cell type used. With respect to tolerance of extreme pH, exemplary pH cutoffs are, e.g., ≥pHIO, ≥pHll, >ρH12, >pH13, or <pH4.0, <pH3.0, <pH2.0, ≤pHl.O. With respect to tolerance of surfactants, exemplary surfactant concentrations are >5% w/v, >6% w/v, >7% w/v, >8% w/v, >9% w/v, > 10% w/v, >12% w/v, >15% w/v, etc. With respect to tolerance of ethanol, exemplary ethanol concentrations are >4% v/v, >5% v/v, >6% v/v, >7% v/v, >8% v/v, >9% v/v, >10% v/v, etc. With respect to tolerance of osmotic stress, exemplary concentrations (e.g., of LiCl) that induce osmotic stress are >100 mM, >150 mM, >200 mM, >250 mM, >300 mM, >350 mM, >400 mM, etc. The invention includes obtaining increased production of metabolites by cells. As used herein, a "metabolite" is any molecule that is made or can be made in a cell. Metabolites include metabolic intermediates or end products, any of which maybe toxic to the cell, in which case the increased production may involve tolerance of the toxic metabolite. Thus metabolites include small molecules, peptides, large proteins, lipids, sugars, etc. Exemplary metabolites include the metabolites demonstrated in the working examples (lycopene, polyhydroxybutyrate and ethanol); therapeutic proteins, such as antibodies or antibody fragments.

The invention also provides for selecting for a plurality of phenotypes, such as tolerance of a plurality of deleterious conditions, increased production of a plurality of metabolites, or a combination of these. An example of this is the multiple tolerance of high glucose and ethanol by yeast demonstrated in the working examples.

It may be advantageous to use cells that are previously optimized for the predetermined phenotype prior to introducing mutated global transcription machinery. Thus, in the production of lycopene, for example, rather than starting with a bacterial cell that produces only a small amount of lycopene, one preferentially uses a cell that produces a higher amount of lycopene, more preferably an optimized amount of lycopene. In such cases, the mutated global transcription machinery is used to further improve an already-improved phenotype.

Via the actions of the mutated global transcription machinery, the altered cells will have altered expression of genes. The methods of the invention can, in certain aspects, include identifying the changes in gene expression in the altered cell. Changes in gene expression can be identified using a variety of methods well known in the art. Preferably the changes in gene expression are determined using a nucleic acid microarray. In some aspects of the invention, one or more of the changes in gene expression that are produced in a cell by mutated global transcription machinery can be reproduced in another cell in order to produce the same (or a similar) phenotype. The changes in gene expression produced by the mutated global transcription machinery can be identified as described above. Individual gene(s) can then be targeted for modulation, through recombinant gene expression or other means. For example, mutated global transcription machinery may produce increases in the expression of genes A, B, C, D, and E, and decreases in the expression of genes F, G, and H. The invention includes modulating the expression of one or more of these genes in order to reproduce the phenotype that is produced by the mutated global transcription machinery. To reproduce the predetermined phenotype, one or more of genes A, B, C, D, E, F, G, and H can be increased, e.g., by introducing into the cell expression vector(s) containing the gene sequence(s), increasing the transcription of one or more endogenous genes that encode the one or more gene products, or by mutating a transcriptional control (e.g., promoter/enhancer) sequence of the one or more genes, or decreased, e.g., by introducing into the first cell nucleic acid molecules that reduce the expression of the one or more gene products such as nucleic acid molecules are, or express, siRNA molecules, or by mutating one or more genes that encode the one or more gene products or a transcriptional control (e.g., promoter/enhancer) sequence of the one or more genes. Optionally, the changes in gene expression in the cell containing the mutated global transcription machinery are used to construct a model of a gene or protein network, which then is used to select which of the one or more gene products in the network to alter. Models of gene or protein networks can be produced via the methods of Ideker and colleagues (see, e.g., Kelley et al, Proc Natl Acad Sd USA 100(20), 11394-11399 (2003); Yeang et al. Genome Biology 6(7), Article R62 (2005); Ideker et al., Bioinformatics. 18 Suppl 1 :S233-40 (2002)) or Liao and colleagues (see, e.g., Liao et al., Proc Natl Acad Sd USA 100(26), 15522-15527 (2003); Yang et al., BMC Genomics 6, 90 (2005)),

The invention also includes cells produced by any of the methods described herein, and multicellular organisms that contain such cells. The cells are useful for a variety of purposes, including: industrial production of molecules (e.g., many of the tolerance phenotypes and increased metabolite production phenotypes); bioremediation (e.g., hazardous waste tolerance phenotypes); identification of genes active in cancer causation (e.g., apoptosis resistance phenotypes) ; identification of genes active in resistance of bacteria and other prokaryotes to antibiotics; identification of genes active in resistance of pests to pesticides; etc.

In another aspect, the invention provides methods for altering the production of a metabolite. The methods include mutating global transcription machinery to produce an altered cell, in accordance with the methods described elsewhere herein. The cell preferably is a cell that produces a selected metabolite, and as described above, preferably is previously optimized for production of the metabolite. Altered cells that produce increased or decreased amounts of the selected metabolite can then be isolated. The methods also can include culturing the isolated cells and recovering the metabolite from the cells or the cell culture. The steps of culturing cells and recovering metabolite can be carried out using methods well known in the art. Various preferred cell types, global transcription machinery and metabolites are provided elsewhere herein.

Another method provided in accordance with the invention is a method for bioremediation of a selected waste product. "Bioremediation", as used herein, is the use of microbes, such as bacteria and other prokaryotes, to enhance the elimination of toxic compounds in the environment. One of the difficulties in bioremediation is obtaining a bacterial strain or other microbe that effectively remediates a site, based on the particular toxins present at that site. The methods for altering the phenotype of cells described herein represents and ideal way to provide such bacterial strains. As one example, bioremediation can be accomplished by mutating global transcription machinery of a cell to produce an altered cell in accordance with the invention and isolating altered cells that metabolize an increased amount of the selected waste product relative to unaltered cells. The isolated altered cells then can be cultured, and exposed to the selected waste product, thereby providing bioremediation of the selected waste product. As an alternative, a sample of the materials in the toxic waste site needing remediation could serve as the selection medium, thereby obtaining microbes specifically selected for the particular mixture of toxins present at the particular toxic waste site.

The invention also provides collections of nucleic acid molecules, which may be understood in the art as a "library" of nucleic acid molecules using the standard nomenclature of molecular biology. Such collections/libraries include a plurality of different nucleic acid molecule species, with each nucleic acid molecule species encoding global transcription machinery that has different mutation(s) as described elsewhere herein. Other collections/libraries of the invention are collections/libraries of cells that include the collections/libraries of nucleic acid molecules described above. The collections/libraries include a plurality of cells, with each cell of the plurality of cells including one or more of the nucleic acid molecules. The cell types present in the collection are as described elsewhere herein, and include single cells as well as multicellular organisms that include one or more of such cells. In the libraries of cells, the nucleic acid molecules can exist as extrachromosomal nucleic acids (e.g., on a plasmid), can be integrated into the genome of the cells, and can replace nucleic acids that encode the endogenous global transcription machinery. The collections/libraries of nucleic acids or cells can be provided to a user for a number of uses. For example, a collection of cells can be screened for a phenotype desired by the user. Likewise, a collection of nucleic acid molecules can be introduced into a cell by the user to make altered cells, and then the altered cells can be screened for a particular phenotype(s) of interest. For example, to use a phenotype described herein, a user seeking to increase lycopene production and possessing a bacterial strain that produces a certain amount of lycopene could introduce a collection of mutated global transcriptions factor(s) into the bacterial strain, and then screen for improved production of lycopene. Subsequent rounds of directed evolution by mutation and reintroduction of the global transcription machinery also can be carried out to obtain further improvements in lycopene production. Collections/libraries can be stored in containers that are commonly used in the art, such as tubes, microwell plates, etc.

Examples

Materials and Methods

Strains and Media

E. coli DH5α (Invitrogen, Carlsbad, CA) was used for routine transformations as described in the protocol as well as for all phenotype analysis in this experiment. Strains were grown at 37°C with 225 RPM orbital shaking in either LB-Miller medium or M9- minimal medium containing 5 g/L D-glucose and supplemented with ImM thiamine (Maniatis, et al., Molecular cloning: a laboratory manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, 1982). Media was supplemented with 34 μg/ml of chloramphenicol for low copy plasmid propagation and 68 μg/ml of chloramphenicol, 20 μg/ml kanamycin, and 100 μg/ml ampicillin for higher copy plasmid maintenance as necessary. Cell density was monitored spectrophotometrically at 600 nm. M9 Minimal salts were purchased from US Biological (Swampscott, MA), X-gal was purchased from American Bioanalytical (Natick, MA) and all remaining chemicals were from Sigma- Aldrich (St. Louis, MO). Primers were purchased from Invitrogen.

Library Construction

A low copy host plasmid (pHACM) was constructed using pUC19 (Yanisch-Perron, et al., Gene 33: 103-119, 1985) as a host background strain and replacing ampicillin resistance with chloramphenicol using the CAT gene in pACYC184 (Chang, et al,₅ J Bacteriol 134: 1141-1156, 1978) and the pSClOl origin of replication from pSClOl (Bernardi, et al., Nucleic Acids Res 12: 9415-9426, 1984). The chloramphenicol gene from pACYC184 was amplified with AatII and Ahdl restriction site overhangs using primers CM_sense_AhdI: GTTGCCTGACTCCCCGTCGCCAGGCGTTTAAGGGCACCAATAAC (SEQ ED NO-.l) and CM_anti_AatII: CAGAAGCCACTGGAGCACCTCAAAACTGCAGT (SEQ ID NO:2). This fragment was digested along with the pUC19 backbone and ligated together to form ρUC19-Cm. The pSClOl fragment from pSClOl was amplified with AfIIII and Notl restriction site overhangs using primers pSC_sense_AflIII: CCCACATGTCCTAGACCTAGCTGCAGGTCGAGGA (SEQ ID NO:3) and pSC_anti_NotI: AAGGAAAAAAGCGGCCGCACGGGTAAGCCTGTTGATGA TACCGCTGCCTTACT (SEQ ID NO:4). This fragment was digested along with the pUC19-Cm construct and ligated together to form pHACM.

The rpoD gene (EcoGene Accession Number: EGl 0896; B-number: b3067; SEQ ID NO:27) was amplified from E. coli genomic DNA using HindIII and Sad restriction overhangs to target the lacZ gene in pHACM to allow for blue/white screening using primers rpoD_sense_SacI: AACCTAGGAGCTCTGATTTAACGGCTTAAGTGCCGAAGAGC (SEQ ID NO.5) and rρoD_anti_HindIII: TGGAAGCTTTAACGCCTGATCCGGCCTACCGATTAAT (SEQ ID NO:6). Fragment mutagenesis was performed using the GenemorphII Random Mutagenesis kit (Stratagene, La Jolla, CA) using various concentrations of initial template to obtain low, medium, and high mutation rates as described in the product protocol. Following PCR, these fragments were purified using a Qiagen PCR cleanup kit (Qiagen, Valencia, CA), digested by HindIII and Sacl overnight, ligated overnight into a digested pHACM backbone, and transformed into E. coli DH5α competent cells. Cells were plated on LB-agar plates and scraped off to create a liquid library. The total library size of white colonies was approximately 10⁵ to 10^δ.

Phenotype Selection

Samples from the liquid library were placed into challenging environments to select for surviving mutants. For ethanol tolerance, strains were placed in filtered-LB containing 50 g/L of ethanol. These cultures were performed in 30 x 115 mm closed top centrifuge tubes shaking at 37°C. Strains were plated after 20 hours and selected for individual colony testing. For acetate tolerance, strains were serial subcultured twice in increasing concentrations of acetate starting at 20 g/L and increasing to 30 g/L in M9 minimal media. Cells were then plated onto LB plates and several colonies were selected for single-colony assays. For para-hydroxybenzoic acid (pHBA) tolerance, strains were cultured in 20 g/L of pHBA in M9 minimal media and plated after 20 hours to select for surviving cells. The plasmids from all strains identified with improved phenotypes were recovered and retransformed into a fresh batch of competent cells. Several colonies were selected from each plate to perform biological replicates to verify phenotypes.

Sequence Analysis Sequences of mutant sigma factors were sequenced using the following set of primers:

Sl: CCATATGCGGTGTGAAATACCGC (SEQ ID NO:7),

S2: CACAGCTGAAACTTCTTGTCACCC (SEQ ID NO:8),

S3: TTGTTGACCCGAACGCAGAAGA (SEQ ID NO:9),

S4: AGAAACCGGCCTGACCATCG (SEQ ID NO: 10), Al : GCTTCGATCTGACGGATACGTTCG (SEQ ID NO: 11 ),

A2: CAGGTTGCGTAGGTGGAGAACTTG (SEQ ID NO: 12),

A3: GTGACTGCGACCTTTCGCTTTG (SEQ ID NO:13),

A4: CATCAGATCATCGGCATCCG (SEQ ID NO: 14),

A5: GCTTCGGCAGCATCTTCGT (SEQ ID NO: 15), and A6: CGGAAGCGATCACCTATCTGC (SEQ ID NO: 16).

Sequences were aligned and compared using Clustal W version 1.82. Example l:

The main sigma factor, σ⁷⁰, was subjected to directed evolution in E. coli in search for increased tolerance phenotypes. This main sigma factor was chosen on the premise that mutations will alter promoter preferences and transcription rates and thus modulate the transcriptome at a global level. The rpoD gene and native promoter region were subjected to error-prone PCR and cloned into a low-copy expression vector (Fig. 1). A nearly 10⁵ to 10 viable-mutant library was initially constructed and transformed into strains.

This library was subjected to selection by culturing in the extreme conditions of high ethanol, high acetate and high para-hydroxybenzoic acid (pHBA) concentrations. These conditions were selected because of their industrial relevance: Acetate is an E. coli byproduct that is inhibitory to cell growth while prospects for bioethanol production can be enhanced by engineering a strain with increased tolerance to ethanol, thus increasing possible yields (L. O. Ingram et al, Biotechnol Bioeng 58, 204-14 (Apr 5, 1998)). Furthermore, there is considerable industrial interest in the production of pHBA as a precursor for electronic coatings, which is, however, extremely toxic to cells (T. K. Van Dyk, L. J. Templeton, K. A. Cantera, P. L. Sharpe, F. S. Sariaslani, JBacteriol 186, 7196-204 (Nov, 2004); J. L. Barker, J. W. Frost, Biotechnol Bioeng 76, 376-90 (Dec, 2001)). Each of these tolerance phenotypes has been investigated by traditional methods of randomized cellular mutagenesis, gene complementation and knockout searches, and microarray analysis (R. T. Gill, S. Wildt, Y. T. Yang, S. Ziesman, G. Stephanopoulos, Proc Natl Acad Sd USA 99, 7033-8 (May 14, 2002)), with limited success to-date.

Ethanol tolerance Mutants of the sigma factor library were first selected on the basis of ability to grow in the presence of high concentrations of ethanol in LB complex medium (L. P. Yomano, S. W. York, L. O. Ingram, J Ind Microbiol Biotechnol 20, 132-8 (Feb, 1998)). For this selection, strains were serially sύbcultured twice at 50 g/L of ethanol overnight, then plated to select for tolerant mutants. A total of 20 colonies were selected and assayed for growth in varying ethanol concentrations. After isolation and validation of improved strains, the best mutant sigma factor was subjected to sequential rounds of evolution. With both subsequent iterations, the selection concentration was increased to 70 and 80 g/L of ethanol. In these enrichment experiments, cells were plated after 4 and 8 hours of incubation due to the strong selection pressure used. Isolated mutants from each round show improved overall growth in various ethanol concentrations (Fig. 2A).

Fig. 2B identifies the sequences of the best mutants isolated from each round of mutagenesis. Sequence alignments of ethanol tolerant sigma factors are provided in Fig. 2D. Interestingly, the second round mutation led to the formation of a truncated factor which is apparently instrumental in increasing overall ethanol fitness. This truncation arose from an artifact in the restriction enzyme digestion and includes part of region 3 and the complete region 4 of the protein. Region 4 is responsible for binding to the promoter region and a truncated form has been previously shown to increase binding affinity relatively to that of the foil protein (U. K. Sharma, S. Ravishankar, R. K. Shandil, P. V. K. Praveen, T. S. Balganesh, J. Bacterial. 181, 5855-5859 (1999)). It is therefore possible that this truncated mutant serves to act as a potent and specific inhibitor of transcription by binding to preferred promoter regions and preventing transcription since the remainder of the sigma factor machinery is removed. In the truncated form of the round 2 mutant, the 151 IV mutation of the first round was reverted back to an isoleucine, leaving only one mutation.

This truncated form was subjected to a third round of mutagenesis and selection to yield a factor with 8 additional mutations. In this final round, the R603C mutation found in the prior two rounds was reverted back to the original residue and many new mutations appeared, leaving only the truncation as the only visible similarity between round 2 and round 3. These rounds of mutagenesis and resulting sequences suggest a difference compared with protein directed evolution. In the latter case, mutations which increase protein function are typically additive in nature. On the other hand, the mutations incurred in altering transcription machinery are not necessarily additive as these factors act as conduits to the transcriptome. In this regard, many local maxima may occur in the sequence space due to the various subsets of gene alterations which may lead to an improved phenotype.

All isolated strains harboring the mutant sigma factors exhibited increased growth rates relative to the control at elevated ethanol concentrations. Furthermore, the growth phenotype of the mutant strains in the absence of ethanol was not impacted (Table 1).

Table 1: Directed evolution of ethanol tolerant sigma factors. Improvements in the fold reduction of doubling time are presented for increasing concentrations of ethanol for the three rounds of directed evolution. The mutants in Rounds 2 and 3 show significant increases in the growth rate at higher concentrations of ethanol. A continual increase in the highest concentrations of sustainable cellular growth is seen throughout the rounds of directed evolution.

The truncated mutant isolated in the second round showed increased growth rates at higher ethanol concentrations; however, its growth rate was reduced at lower ethanol concentrations compared with the first round mutant. The mutant isolated from the third round showed recovered growth rates, similar to that of the first round, between 20 and 50 g/L of ethanol. Most importantly, each subsequent round increased the highest ethanol concentration at which cells were able to sustain growth for longer than 8 hours, without succumbing to the ethanol toxicity with an accompanying decrease in cell density. The drastic increase in ethanol tolerance obtained through this method is illustrated by the growth curves of the round 3 strain shown in (Fig. 2C) along with those of the wild type control. Sigma factor engineering (SFE) was able to increase the ethanol tolerance beyond the levels previously reported in the literature using more traditional methods. Furthermore, the application of iterative rounds of SFE was illustrated to be capable of further improving the cellular phenotype. Acetate and pHBA tolerance

As a second example, the original sigma factor mutant library was serial subcultured twice on 20 g/L followed by 30 g/L of acetate in M9-minimal medium. Single colonies were isolated from this mixture, retransformed to preclude any chromosome-based growth adaptation, and assayed for growth in varying acetate concentrations. Isolated strains showed a drastic increase in tolerance in the presence of high levels of acetate. Additionally, the growth rate was, once again, not substantially affected in the absence of acetate (Table 2). At 30 g/L of acetate, isolated strains had doubling times of 10.5 — 12.5 hours, approximately 1/5 of the doubling time of the severely inhibited control (56 hours doubling time).

Table 2: Application of transcription machinery engineering for additional phenotypes.

Mutants were isolated which showed an increased tolerance in either elevated acetate levels or in the presence of high levels of pHBA. Increases in the tolerance are seen at elevated levels of the chemicals, however, no adverse effects are seen in the growth rates or yields in the absence of these chemicals.

Fig. 3 A summarizes the various mutations classified by region in the isolated sigma factors eliciting an increased cellular tolerance for acetate. Sequence alignments of acetate tolerant sigma factors are provided in Fig. 3B. Only one of the five isolated mutants was truncated. The M567V mutation appeared in two of the acetate mutants and most of the mutations appear to be distributed among the functional domains of the sigma factor. It is interesting to note that even though strains have similar tolerance profiles, the underlying mutations are different suggesting different molecular mechanisms influencing the transcription profiles.

As a another example, the mutant library was cultured in the presence of 20 g/L of pHBA to select for strains with increased tolerance to this compound in terms of growth and viability at high pHBA concentrations. One strain was isolated with marked improvement in the growth yield at 13 hours compared with the control and essentially unchanged growth phenotype in the absence of pHBA (Table 2). Mutant HBAl showed a truncated form of the sigma factor with a total of six mutations (Fig. 3A), with 4 of 6 residues being changed to a valine. Sequence alignments of pHBA tolerant sigma factors are provided in Fig. 3C.

These examples illustrate the potential of sigma factor engineering to introduce global transcriptonie changes that allow the organism to access novel cellular phenotypes. Recently, we have successfully extended the concept of global transcription machinery engineering beyond tolerance phenotypes to select for mutants which increase metabolite overproduction rates (see below). Furthermore, this concept has been explored with other host systems including eukaryotic transcription machinery components. In each of these examples, the global changes brought about by random mutations in the components of transcriptional regulatory machinery is shown to improve to cellular phenotypes beyond levels attainable through rational engineering or traditional strain improvement by random mutagenesis.

For the first time, we demonstrated the application of directed evolution to alter the global transcription machinery. This strategy allowed for the directed modification of the genetic control of multiple genes simultaneously, as opposed to typical consecutive, gene-by- gene strategies. Furthermore, we found the paradigm of directed evolution to be applicable as it allowed sequential phenotypic improvements by probing deeper into the vast sequence space of transcription factor engineering. As a result, it is now possible to unlock complex phenotypes regulated by multiple genes which would be very unlikely to reach by the relatively inefficient iterative search strategies.

It is worth noting that the described method can also be applied in reverse to uncover the complicated interactions of the genotype-phenotype landscape. In such applications, one would employ a number of high-throughput cellular and molecular assays to assess the altered cellular state and ultimately deduce systematic mechanisms of action underlying the observed phenotype in these mutants. The application of directed evolution to global transcription machinery as described here is a paradigm shifting method for identifying genetic targets, eliciting desired phenotypes and realizing the goal of whole cell engineering.

Example 2:

Organic Solvent Tolerance

The application of global transcription machinery engineering has been extended to include additional tolerance phenotypes. Bacterial strain tolerance to organic solvents is useful in several situations: (1) bioremediation of hazardous waste, (2) bioproduction of organic solvents from bacteria, and (3) bioprocessing applications requiring a two-phase reactor (i.e. extractive fermentations to continuously remove hydrophobic products operation). To investigate the potential to increase solvent tolerance in E. coli, the original rpoD (σ⁷⁰) mutant library was cultured and harvested in exponential phase and transferred to a two-phase system containing LB medium and hexanes (10% v/v). Strains were isolated after 18 hours of growth in the presence of hexane. These individual colonies were again cultured to exponential phase and then cultured in the presence of hexane. Cell densities are measured after 17 hours. Cell densities from culture with hexane are shown in Fig. 4. The strains shown in Fig. 4 are re-transformed strains performed in biological replicates. All selected strains had an increase in cell density over the control strain containing an un- mutated version of the rpoD gene. Furthermore, PCR analysis indicated that mutant strains Hex-3, Hex-8, Hex-11, Hex-12, Hex-13, Hex-17 andHex-19 have a whole version of the sigma factor while strains Hex-2, Hex-6, Hex-9, Hex- 10, and Hex- 18 have a truncated version. Fig. 4 also shows the sequence (location of mutations) for the two best-performing mutants, Hex-12 and Hex- 18.

Additionally, these strains were tested for growth in the presence of cyclohexane, which is known to be a more toxic organic solvent to microorganisms than hexane. Fig. 5 shows the cell densities from cultures with cyclohexane. Several of the strains isolated from the hexane selection also showed and increase in cell density over the control. Example 3:

Antibiotic Resistance

The application of global transcription machinery engineering has been extended to include antibiotic resistance. Antibiotic resistance among microorganisms is becoming a significant problem placing a stress on health care and pharmaceutical companies to find alternatives ways to fight infections. Many resistant strains are known to contain specific genes encoding for a resistance. However, before microorganisms are able to evolve such a gene, they must first gain an initial resistance in an effort to persist in the presence of antibiotics. While incurring random mutations in the genome is one alternative, cells can also change their gene expression in response to these antibiotics. The use of global transcription machinery engineering was tested to identify the possibility of creating antibiotic resistant strains. This phenotype would ultimately be controlled by the altered expression of the transcriptome, mediated through the mutant transcription machinery. An analysis of the gene expression of these strains could lead to the identification of novel gene targets and enzymes which control the resistance of the strain. These targets could then lead to the development of small molecule drugs which inhibit or enhance the activity of the identified enzymes. The topic of antibiotic resistance was tested by culturing the mutant sigma factor library in the presence of 250 μg/ml of nalidixic acid, a quinolone (the same family of drugs as Ciprofloxacin), which is in excess of the minimum inhibitory concentration of the control of around 80 μg/ml. Fig. 6 presents the cell density (OD600) for various isolated strains at increasing concentrations of nalidixic acid. Several isolated strains showed significant growth in the presence of high concentrations of nalidixic acid. These strains are tested for verification after transformation of the plasmids into fresh host strains. Furthermore, these mutants are sequenced; PCR analysis indicated that mutant strains NdA-7 and NdA- 15 are whole length sigma factors while NdA-10, NdA-11, NdA-12 and NdA-13 are truncated versions.

Example 4: Metabolite overproduction phenotypes

The basic tenet of global transcription machinery engineering is the ability to create multiple and simultaneous gene expression modifications. Previously, this method was successfully employed for the identification of mutants with increased tolerance phenotypes. In these subsequent examples, a mutant library of the principal sigma factor, encoded by rpoD, was examined for its capacity to enhance metabolite overproduction phenotypes beyond those levels achievable by single genetic modifications.

Lvcopene Production

Previously, we have identified a number of single and multiple gene knockout targets which showed an increase of lycopene production in the background of a pre-engineereed strain (Alper et al., Nat Biotechnol 2005 and Alper et al., Metab Eng 2005). hi this study, we sought to utilize the technique of global transcription machinery engineering to enhance lycopene production. Utilizing several available strain backgrounds which were previously engineered along with the parental strain, it was possible search for mutant factors, independently in each background, which resulted in an increased lycopene production. For this study, the parental strain, Ahnr, and the two identified global maximum strains, AgdhAAaceEAfdhF, and AgdhAAaceEA^yjiD, were selected. The best mutant from each of the four tested genetic backgrounds was then swapped to investigate the landscape created by mixing 4 strains with the 4 identified mutant sigma factors.

Identification of mutant sigma factors The mutant sigma factor library was transformed into each of the four strains and selected based on lycopene production on minimal medium plates supplemented with 5 g/L of glucose. Selected strains were then cultured and assayed for lycopene production at 15 and 24 hours using M9 medium. Figs. 7 A - 7D illustrate the results of these searches along with the sequence of sigma factor mutant from the best strain. Lycopene production is indicated for the strain with and without the control plasmid. For some backgrounds, this control plasmid resulted in a large decrease in lycopene production over the strain absent of this plasmid. It is interesting to note that all of these identified factors have been truncated. Furthermore, the mutant identified from the hnr knockout background was simply truncated and contained no mutations. Given the suspected mode of action for this truncation, it is possible that this mutant factor essentially suppresses all of the normal genes expressed under the control of rpoD. In an hnr mutant, a higher steady state level of the stationary phase sigma factor, σ^s, is available to take over the remainder of transcription. Furthermore, the second highest mutant in this background resulted in a full length sigma factor containing several mutations.

Combinations of strains and identified mutant factors The four strains with varying genetic backgrounds were then combined with the four independently identified mutant sigma factors to examine the resulting 16 strain landscape. It is interesting to initially note that none of the identified mutants in Figs. 7 A - 7D which were sequenced for a given genetic background overlapped with those identified in another genetic background. As a result, it is initially suspected that the landscape would be diagonally dominant, indicating that the effect elicited by the mutant factor is specific to the genetic background. These 16 strains along with the controls were cultured in a 2x M9 medium with staged glucose feed. The lycopene level was assayed at 15, 24, 39, and 48 hour timepoints. Fig. 8 presents a dot plot which depicts the maximum fold increase in lycopene production achieved over the control during the fermentation. The size of the circle is proportional to the fold increase. As suspected, the landscape is clearly diagonally-dominant with mutant factors predominantly working in the strain background in which they were identified.

Fig. 9 illustrates the lycopene content after 15 hours for several strains of interest. The single round of mutagenesis in both the parental strain and hnr knockout was able to achieve similar results as strains previously engineered through the introduction of three distinct gene knockouts. However, in these backgrounds, lycopene levels were able to be further increased through the introduction of an additional mutant sigma factor.

These results indicate that (1) global transcription machinery engineering (gTME) is able to elicit metabolic phenotypes and, more importantly, (2) a single round of selection using gTME is more effective than a single knockout or overexpression modification. Furthermore, the identified mutant is not generally transferable across strain backgrounds, which suggests that there may be different modes of lycopene production in each of the strains. As an example of these modes, the maximum fold difference in the wild type strain was realized after only 15 hours and then converged with the control strain by the end of the fermentation. Conversely, the mutant factor in the AgdhAAaceEApyjiD strain progressively increased in lycopene content compared with the control for increasing timepoints.

Nevertheless, the highest lycopene production resulted in using gTME in the background of a previously engineered strain indicating that, given only one round of selection, it is better to start in an optimized strain. However, the results of ethanol tolerance suggest that it is possible to achieve continual improvements in fitness through the application of directed, evolution, indicating that it may be possible to increase lycopene production further.

Bioproduction of Polyhydroxybutyrate (PHB) The application of global transcription machinery engineering has been extended to include a further example of metabolite overproduction. An additional metabolic phenotype (in addition to production of lycopene), bioproduction of polyhydroxybutyrate (PHB), was investigated using transcription machinery engineering. PHB is produced from the precursor molecule of acetyl-coA.

Materials/Methods

Escherichia coli (XL-I Blue, Stratagene, La Jolla, Calif.) transformed with a modified ρJOE7 (Lawrence, A. G., J. Choi, C. Rha, J. Stubbe, and A. J. Sinskey. 2005. Biomacromolecules 6:2113-2119) plasmid was cultured at 37°C in Luria-Bertani (LB) medium containing 20 g/L glucose and 25 is μg/mL kanamycin. The modified pJOE7 was graciously given to us by Dr. Anthony Sinskey (MIT, Cambridge, MA) and contains phaAB from C. necator and the phEC from Allochromatium vinosum and encodes kanamycin resistance. As a no PHB control, the same plasmid without the pha genes was also cultured. Optical density was used to track cell growth using an Ultraspec 2100 pro (Amersham Biosciences, Uppsala, Sweden).

Staining and Flow Cytometry

A nile red (Sigma- Aldrich, St. Louis, MO) stock solution was made by dissolving to 1 mg/mL in dimethyl sulfoxide unless otherwise noted. 3 μL of stock solution was added to 1 mL of staining buffer as indicated in the staining optimization. Flow cytometry was carried out on a FACScan (Becton Dickinson, Mountain View, CA) using the following settings;

Synechocystis FSC=EOO, SSC=411, FL-1=582, FL-2=551 and E. coli FSC=EOO, SSO411,

FL-1=582, FL-2=535. Cells were excited with an air-cooled argon ion laser (488 run), and

FL-2 (585nm) was used to detect nile red fluorescence. Flow cytometry analysis was done on 50,000 cells using WinMDI 2.8.

Staining effectiveness was characterized by resolution, Rs (Eq. 1), where M_n is the geometric mean of the fluorescence distribution of n (n=l is the PHB producing cell, n=2 is the no PHB control). δ_n is the standard deviation of the fluorescence distribution. Rs is a quantitative measure of the ability to differentiate two populations.

2(U₁ -M₁) δ_λ + δ₂

Cell viability was accessed by ratio of the cfu in the final stained preparation to cells from the media.

Chemical PHB Analysis PHB was analyzed as shown previously (Taroncher-Oldenburg, G., and G.

Stephanopoulos. 2000. Applied Microbiology and Biotechnology 54:677-680). >10 mg of cells was collected from culture by centrifugation (10 min, 3,200xg). The resulting pellet was washed once with cold deionized H₂O and dried overnight at 80°C. The dry pellets were boiled in 1 ml of concentrated H₂SO₄ for 60 min, diluted with 4 ml of 0.014 M H₂SO₄. Samples were centrifuged (15 min, 18,000xg) to remove cell debris, and liquid was analyzed by HPLC using an Aminex HPX-87H ion-exclusion column (300 x 7.8 mm; Bio-Rad, Hercules, Calif.) (Karr, D. B., J. K. Waters, and D. W. Emerich. 1983. Applied and Environmental Microbiology 46:1339-1344). Commercially available PHB (Sigma-Aldrich, St. Louis, Mo.), processed in parallel with the samples, was used as standards.

E. coli Staining Optimization

E. coli XLl -blue harboring the modified pJOE and the no PHB control were cultured as described.

Shock optimization: Cultures were grown to stationary phase. A variety of different permeabilization methods were tested for resolution and viability after the shock. Sucrose shock was carried out as shown previously (Vazquez-Laslop, N., H. Lee, R. Hu, and A. A. Neyfakh. 2001. J. Bacteriol. 183:2399-2404). 1 mL of cells was cooled to 4⁰C for 10 min. The cells were then centrifuged (3 min, 3000xg, 4⁰C) and resuspended in 1 mL ice-cold TSE buffer (10 mM Tris-Cl [ρH=7.5], 20% sucrose, 2.5 mM Na-EDTA). The cells were incubated on ice for 10 min then resuspended (3 min, 3000xg, 4⁰C) in 1 mL deionized water with 3μL nile red stock solution. Cells were stained in the dark for 30 min and analyzed on the FACScan. Isopropanol shocked cells were centrifuged (3 min, 3000xg) and resuspended in 70% isopropanol for 15 min. Cells were then centrifuged (3 min, 3000^χg) and resuspended in deionized water with 3μL nile red stock solution. Cells were incubated for 30 min in the dark and analyzed on the FACScan. DMSO shock was performed by centrifuging (3 min, 3000xg) ImL of cell culture. 50 μL of nile red stock solution was added directly to the pellet. The pellet was quickly vortexed and diluted to 1 mL in water after incubating for 30 s. Cells were incubated for 30 min in dark and analyzed on the FACScan. Heat shock was performed as in competent cell preparation (Sambrook, J., E. F. Fritsch, and T. Maniatis. 1989. Molecular Cloning: A Laboratory Manual, 2nd ed. Cold Spring Harbor Laboratory Press). 1 mL of cells was cooled for 10 min. Cells were then centrifuged (3 min, 3000xg, 4⁰C), and resuspended in 1 mL cold 80 mM MgCl₂ / 20 mM CaCl₂. Cells were centrifuged (3 min, 3000^χg, 4⁰C) and resuspended in 1 mL 0.1 M CaCl₂ with 3μL nile red stock solution. Cells were heat shocked at 42⁰C for 90 s. Cells were incubated for 30 min in dark then analyzed on the FACScan.

Concentration optimization: Cells were prepared by sucrose shock using 3μL of different nile red solutions to a final concentration between 30 - 30,000 ng/niL.

Sucrose concentration optimization: Cells were prepared by sucrose shock using TSE buffer with varying sucrose concentrations (0, 5, 10, 15, 20%).

The mutant sigma factor library was introduced into Escherichia coli as described above. Strains were selected for increased exponential phase PHB in a glucose-minimal media. Additionally, a random knockout library created using transposon mutagenesis was also tested to compare the efficacy of transcription machinery engineering to that of traditional strain improvement methods. Fig. 1OA presents the data for various strains (bars in red and yellow represent controls) obtained using sigma factor engineering. In comparison, Fig. 1OB presents the results of selected strains from a random knockout library. Several mutants obtained using sigma factor engineering produced nearly 25% dew (dry cell weight) of PHB. The best strain obtained in one round of sigma factor engineering was far superior to the best strain obtained using random knockouts. A second round of mutagenesis in the background of the best mutant is carried out as described above for further improvement of the PHB phenotype. Example 5:

Library diversity and construction

The size and breadth of the sigma factor library is increased in one or more of the following ways.

(1) The library includes not only the main sigma factor of E. coli (σ⁷⁰, encoded by rpoD), but also one or more alternative forms, e.g., rpoS, rpoF, rpoH, rpoN, rpoE and/or fed.

It may be possible to further improve phenotypes and search for optimized strains through the simultaneous introduction of multiple mutant versions of transcription machinery units. The mutated sigma factor genes (or other global transcription machinery) are expressed, for example, using expression cassettes which coexpress two or more of these genes. The two or more genes may be two or more of the same type of transcription machinery (e.g., two versions of an rpoD) or may be two or more distinct transcription machinery (e.g., rpoD and rpoS). Likewise, more than one different mutant versions of global transcription machinery may be beneficial to properly optimize for a phenotype. For example, multiple mutated sigma 70 (rpoD) genes can be coexpressed.

(2) In addition to random mutations introduced by error prone PCR as described above, the library includes all possible truncations from both the C terminus and N terminus and combinations thereof.

(3) Furthermore, the library includes alternative chimeras of various regions of the sigma factors by artificially fusing the regions. For example, Region 1 of sigma factor 70 is used to replace Region 1 of sigma factor 38. A similar approach by using DNA shuffling to create diversity is well known in the art (e.g., gene shuffling patents of W. Stemmer et al., assigned to Maxygen; see listing at maxygen.com/science-patents).

(4) Sigma factors from other bacteria are included in the library in the same configurations (e.g., random mutations, truncations, chimeras, shuffling) as described for E. coli sigma factor 70 above. These factors may possess unique properties of DNA binding and may help to create a diversity of transcriptome changes. Example 6:

Global transcription machinery engineering in eukaryotic cells

The directed evolution of global transcription machinery is applied to yeast and mammalian systems (e.g., CHO, HeLa, Hek cell lines) for enhanced recombinant protein production and resistance to apoptosis in inducing conditions.

A gene encoding global transcription machinery (e.g., TFIID) is subjected to error prone PCR, truncation and/or DNA shuffling in order to create a diverse library of global transcription machinery mutants. The library is introduced into the yeast or mammalian cells and, in a first experiment, the production of recombinant protein by the cells is examined. A readily assayable protein is preferred for these experiments, such as SEAP or a fluorescent protein (e.g., GFP). In the case of fluorescent proteins, cells can be selected using a fluorescence activated cell sorter or if grown in multiwell plates, a fluorescence plate reader can be used to determine the enhancement in protein production. In a second experiment, anti-apoptosis phenotypes are examined in the yeast or mammalian cells.

Example 7: SDS tolerance

The directed evolution of global transcription machinery was applied to the problem of cellular tolerance to sodium dodecyl sulfate (SDS).

The mutant rpoD library was transformed into Escherichia coli DH5α, which were then subcultured in LB medium containing increasing amounts of SDS (5%, then 15 % SDS, by mass). Strains were selected for increased tolerance in SDS. Strain SDS-2 was selected and retransformed to verify the phenotype. Strain SDS-2 was then tested at 5-20% SDS (by mass). This mutant was found to have increased growth at elevated SDS levels, without any detrimental effects to the growth in the absence of SDS. Fig. 11 shows the cell densities of cultures of isolated strains of SDS-tolerant sigma factor mutants at increasing concentrations of SDS, along with the sequence of the sigma factor mutant from the best strain. Example 8:

Engineering multiple phenotypes

Global transcription machinery engineering was applied to the problem of imparting a multiple tolerance phenotype in E. coli. In order to obtain the tolerance to both ethanol and SDS, in a first set of experiments, strains were isolated following three alternative strategies: (i) mutants were isolated after treatment/selection in both ethanol and SDS, (ii) mutants were isolated which were tolerant to ethanol first, then subjected to an additional round of mutagenesis and selected using an ethanol/SDS mixture, and (iii) mutants were isolated which were tolerant to SDS first, then subjected to an additional round of mutagenesis and selected using an ethanol/SDS mixture. These strains were tested for growth in the presence of various concentrations of ethanol and SDS to obtain growth curves and to assess the effectiveness of these strategies. The experiments were conducted using the protocols described in other examples above.

In a second set of experiments, a mutant sigma factor is isolated from an ethanol tolerant strain and is co-expressed with a mutant sigma factor that is isolated from an SDS tolerant strain. These experiments are conducted using the protocols described in other examples above.

Example 9:

Extension of global transcription machinery engineering (gTME) to yeast systems

In any type of cellular system, a subset of proteins is responsible for coordinating global gene expression. As such, these proteins provide access points for diverse transciptome modifications broadly impacting phenotypes of higher organisms. This example demonstrates the application of gTME to the eukaryotic model system of yeast (Saccharomyces cerevisiae). In stark contrast to the transcriptional machinery of the prokaryotic system, eukaryotic transcription machinery is more complex in terms of the number of components and factors associated with regulating promoter specificity. First, there are three RNA polymerase enzymes with separate functions in eukaryotic systems while only one exists in prokaryotes. Furthermore, an example of this complexity is exemplified by nearly 75 components classified as a general transcription factor or coactivator of the RNA Pol π system (Hahn, Nat Struct MoI Biol, 11(5), 394-403, 2004). Components of the general factor TFIID include the TATA binding protein (Sptl5) and 14 other associated factors (TAFs) and are thought to be the main DNA binding proteins regulating promoter specificity (Hahn, 2004). Moreover, TATA-binding protein mutants have been shown to change the preference of the three polymerases, suggesting a pivotal role for orchestrating the overall transcription in yeast (Schultz, Reeder, & Hahn, Cell, 69(4), 697-702, 1992). The focus of this study will be on two major proteins of transcription: the TATA-binding protein (Sptl5) and a TAF (TAF25). Crystal structures are available for the TATA-binding protein and clearly illustrate portions of the protein for direct DNA binding and other portions for protein binding with the TAFs and parts of the polymerase (Bewley, Gronenborn, & Clore, Anna Rev Biophys Biomol Struct, 27, 105-131, 1998; Chasman et al, Proc Natl Acad Sd USA, 90(17), 8174-8178, 1993; J. L. Kim, Nikolov, & Burley, Nature, 365(6446), 520-527, 1993). This structure consists of two repeat regions which interact with the DNA and two helices which interact with proteins. Assays and mutational analysis suggest that the TATA-binding protein plays an important role in promoter specificity and global transcription. Furthermore, important residues have been suggested for DNA contact points and protein interaction points (Arndt et al., Mo/ Cell Biol, 12(5), 2372-2382, 1992; J. Kim & Iyer, Mo/ Cell Biol, 24(18), 8104-8112, 2004; Kou et al., MoI Cell Biol, 23(9), 3186-3201, 2003; Schultz, Reeder, & Hahn, 1992;

Spencer & Arndt, MoI Cell Biol, 22(24), 8744-8755, 2002). The TAFs have received varying amounts of attention. The TAF25 protein, the subject of this study, has been analyzed using sequence alignment and through mutation analysis and has been shown to impact transcription of many genes (Kirchner et al., MoI Cell Biol, 21(19), 6668-6680, 2001). This protein is seen to have a series of helices and linkers which are critical to protein interactions. These proteins were investigated using the method of gTME to elicit three phenotypes of interest: (1) LiCl tolerance to model osmotic stress, (2) high glucose tolerance, and (3) the simultaneous tolerance to high ethanol and high glucose.

Methods

S. cerevisiae strain BY4741 (MATa; Ms3Al; leu2A0; metl5A0; urα3A0) used in this study was obtained from EUROSCARF, Frankfurt, Germany. It was cultivated in YPD medium (1O g of yeast extract/liter, 20 g of Bacto Peptone/liter and 20 g glucose/liter). For yeast transformation, the Frozen-EZ Yeast Transformation II (ZYMO RESEARCH) was used. To select and grow yeast transformants bearing plasmids with URA3 as selectable marker, a yeast synthetic complete (YSC) medium was used containing 6.7 g of Yeast Nitrogen Base (Difco)/liter, 20 g glucose/liter and a mixture of appropriate nucleotides and amino acids (CSM-URA, Qbiogene) referred here as to YSC Ura^". Medium was supplemented with 1.5% agar for solid media.

The library was created and cloned behind the TEF-mut2 promoter created previously as part of a yeast promoter library (Alper et al., Proc Natl Acad Sci USA, 102(36), 12678- 12683, 2005). The Taf25 gene was cloned from genomic DNA using the primers TAF25_Sense: TCGAGTGCTAGCAAAATGGATTTTGAGGAAGATTACGAT (SEQ ID NO:28) and TAF25_Anti: CTAGCGGTCGACCTAACGATAAAAGTCTGGGCGACCT (SEQ ID NO:29). The Sptl5 gene was cloned from genomic DNA using the primers SPT15_Sense: TCGAGTGCTAGCAAAATGGCCGATGAGGAACGTTTAAAGG (SEQ ID NO:30) and SPT15_Anti: CTAGCGGTCGACTCACATTTTTCTAAATTCACTTAGCACA (SEQ ID NO:31). Genes were mutated using the GeneMorph II Mutagenesis Kit and products were digested using Nhel and Sail and ligated to plasmid backbone digested with Xbal and Sail. The plasmids were transformed into E. coli DH5α, isolated using a plasmid MiniPrep Spin Kit and transformed into yeast. Plasmids were sequenced using the primers: Seq_Forward: TCACTCAGTAGAACGGGAGC (SEQ ID NO:32)and Seq_Reverse: AATAGGGACCTAGACTTCAG (SEQ ID NO:33).

Strains were isolated by serial subculturing in 200 to 400 mM LiCl, 200 to 300 g/L of glucose, and 5% Ethanol/100 g/L glucose to 6% Ethanol/120 g/L glucose as appropriate. Cells were isolated by plating onto selective medium plates and assayed for performance. Plasmids were isolated and retransformed to revalidate phenotypes in biological replicates.

LiCl tolerance

Osmotic stress response and tolerance is a complex, pleiotropic response in cells. For yeast, it has been shown that elevated LiCl concentration can induce osmotic stress at concentrations around 100 mM (Haro, Garciadeblas, & Rodriguez-Navarro, FEBS Lett, 291(2), 189-191, 1991; Lee, Van Montagu, & Verbruggen, Proc Natl Acad Sci USA, 96(10), 5873-5877, 1999; Park et al., Nat Biotechnol, 21(10), 1208-1214, 2003). Yeast cell libraries carrying the mutant versions of either the TBP or TAF25 were serially subcultured in the presence of 200 to 400 mM LiCl. Strains were isolated and retransformed to revalidate the phenotype was a result of the mutant factor. Interestingly, the best strains from each library showed varying improvements to LiCl. The TAF25 outperformed the respective TAF25 unmutated control at lower LiCl concentrations, but was not effective at concentrations above around 200 mM. Conversely, the SPTl 5 mutant was able to outperform the control at elevated levels of 150 to 400 mM. In each case, the growth phenotype in the absence of LiCl was not impacted by the presence of the mutant factor. A summary of the improvement in growth yield is provided in Figure 12. A sequence analysis (Figure 13) indicates that the improvement in LiCl tolerance was controlled by a single mutation in each of the proteins, with the SPTl 5 mutation occurring in the unconserved region.

High glucose tolerance

High glucose fermentations have been explored for increased the ethanol produced from a batch culture of yeast. However, these "very high gravity fermentations" are often quite inhibitory to cell growth and typically are treated by altering the medium composition, rather than altering the cells (Bafrncova et al., Biotechnology Letters, 21(4), 337 - 341, 1999; Bai et al., J Biotechnol, 110(3), 287-293, 2004; Thatipamala, Rohani, & Hill, Biotechnology and Bioengineering, 40(2), 289-297, 1992). To explore this problem using gTME, yeast cell libraries carrying the mutant versions of either the TBP or TAF25 were serially subcultured in the presence of 200 to 400 g/L of glucose. Strains were isolated and retransformed to revalidate the phenotype was a result of the mutant factor. Strains showed a 2 to 2.5 fold increase in cell density after 16 hours of culturing. Unlike the case with LiCl, both the TAF25 and SPT 15 proteins showed a similar response to elevated glucose with the maximum improvement over the control occurring between 150 and 250 g/L. However, the SPT15 mutant showed a larger improvement over the TAF25. Figure 14 presents the growth improvement of these mutants and the sequences are presented in Figure 15. In this case, both proteins had only a single mutation, however several suboptimal mutants were isolated for the SPTl 5 protein, some of which having as many as seven mutations. Both mutations shown here are located in known protein contact areas, especially the 1143 residue in the TAF25 protein (Schultz, Reeder, & Hahn, 1992).

Ethanol and glucose multiple tolerance

Successful fermentations of bioethanol for yeast require tolerance to both high glucose and ethanol concentrations. To this end, the multiple tolerance phenotype was tested through the simultaneous treatment of both mutant libraries to elevated levels of ethanol and glucose (5% and 100 g/L). Isolated strains were retransformed and assayed under a range of glucose concentrations in the presence of 5 and 6% ethanol. Interestingly, the SPT 15 mutants outperformed the control at all concentrations tested, upwards of 13 fold improvement in some concentrations. This improvement far exceeded the overall improvement of the TAF25 mutant which was not able to grow in the presence of 6% ethanol. Figure 16 highlights the growth analysis of these best strains and sequences are provided in Figure 17. The improvements achieved through the introduction of the mutant transcription machinery far exceed the improvements obtained through other means of improving cellular phenotype. Furthermore, these results advance the potential to use yeast as a viable source of high ethanol production using a high gravity fermentation.

Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Such equivalents are intended to be encompassed by the following claims. AU references disclosed herein are incorporated by reference in their entirety.

We claim:

Claims

Claims

1. A method for altering the phenotype of a cell comprising: mutating a nucleic acid encoding global transcription machinery and, optionally, its promoter, expressing the nucleic acid in a cell to provide an altered cell that includes mutated global transcription machinery, and culturing the altered cell.

2. The method of claim 1 , further comprising determining the phenotype of the altered cell.

3. The method of claim 1, further comprising repeating the mutation of the nucleic acid to produce a n^th generation altered cell.

4. The method of claim 1 , further comprising determining the phenotype of the n^th generation altered cell.

5. The method of claim 3, wherein the step of repeating the mutation of the global transcription machinery comprises isolating a nucleic acid encoding the mutated global transcription machinery and optionally, its promoter, from the altered cell, mutating the nucleic acid, and introducing the mutated nucleic acid into another cell.

6. The method of claim 1 , wherein the cell is a prokaryotic cell.

7. The method of claim 6, wherein the prokaryotic cell is a bacterial cell or an archaeal cell.

8. The method of claim 7, wherein the global transcription machinery is a sigma factor or an anti-sigma factor.

9. The method of claim 8, wherein a nucleic acid encoding the sigma factor is a rpoD (σ⁷⁰) gene, a rpoF (σ² ) gene, a rpo^¹ (σ³⁸) gene, a rpoH (σ³²) gene, a r/røiV (σ⁵⁴) gene, a rpoE (σ²⁴) gene or afecl(σ¹⁹) gene.

10. The method of claim 8, wherein the sigma factor or anti-sigma factor is expressed from an expression vector.

11. The method of claim 1 , wherein the cell is a eukaryotic cell.

12. The method of claim 11, wherein the eukaryotic cell is a yeast cell.

13. The method of claim 11 , wherein the eukaryotic cell is a mammalian cell.

14. The method of claim 11 , wherein the eukaryotic cell is a plant cell.

15. The method of claim 11 , wherein the eukaryotic cell is an insect cell.

16. The method of claim 11 , wherein the eukaryotic cell is a stem cell.

17. The method of claim 11, wherein the eukaryotic cell is a fungus cell.

18. The method of any of claims 11-17, wherein the eukaryotic cell is contained in a multicellular organism.

19. The method of claim 11, wherein the nucleic acid is expressed in the cell from a tissue-specific promoter, a cell-specific promoter, or an organelle-specific promoter.

20. The method of claim 11 , wherein the global transcription machinery binds to an RNA polymerase I, an RNA polymerase II or an RNA polymerase HI, or a promoter of an RNA polymerase I, an RNA polymerase II or an RNA polymerase III.

21. The method of claim 20, wherein the global transcription machinery is TFIID or a subunit thereof.

22. The method of claim 21 , wherein the subunit is T ATA-binding protein (TBP) or a TBP-associated factor (TAP), such as TAF25.

23. The method of claim 20, wherein a nucleic acid encoding the global transcription machinery is a GALl 1 gene, a SIN4 gene, a RGRl gene, a HRSl gene, a PAFl gene, a MED2 gene, a SNF6 gene, a SNF2 gene, or a SWIl gene.

24. The method of claim 20, wherein the global transcription machinery is a nucleic acid methyltransferase, a histone methyltransferase, a histone acetylase or a histone deacetylase.

25. The method of claim 20 or claim 24, wherein the global transcription machinery is expressed from an expression vector.

26. The method of claim 11, wherein the nucleic acid is a nucleic acid of an organelle of the eukaryotic cell.

27. The method of claim 26, wherein the organelle is a mitochondrion or a chloroplast.

28. The method of claim 1 , wherein the nucleic acid is part of an expression vector.

29. The method of claim 1 , wherein the nucleic acid is a member of a collection of nucleic acids.

30. The method of claim 29, further comprising introducing the collection into the cell.

31. The method of claim 1 , wherein the step o f expressing the nucleic acid comprises integrating the nucleic acid into the genome or replacing a nucleic acid that encodes the endogenous global transcription machinery.

32. The method of claim 1 , wherein the mutation of the nucleic acid comprises directed evolution of the nucleic acid.

33. The method of claim 32, wherein the directed evolution comprises mutation by error prone PCR.

34. The method of claim 32, wherein the directed evolution comprises mutation by gene shuffling.

35. The method of claim 1 , wherein the mutation of the nucleic acid comprises synthesizing the nucleic acid with one or more mutations.

36. The method of claim 1, wherein the nucleic acid mutations is/are one or more point mutations.

37. The method of claim 1 , wherein the nucleic acid mutations is/are one or more truncations or deletions.

38. The method of claim 37, wherein a promoter binding region of the global transcription machinery is not disrupted or removed by the one or more truncations or deletions.

39. The method of claim 1 , wherein the mutated global transcription machinery exhibits increased transcription of genes relative to the unmutated global transcription machinery.

40. The method of claim 1 , wherein the mutated global transcription machinery exhibits decreased transcription of genes relative to the unmutated global transcription machinery.

41. The method of claim 1 , wherein the mutated global transcription machinery exhibits increased repression of gene transcription relative to the unmutated global transcription machinery.

42. The method of claim 1 , wherein the mutated global transcription machinery exhibits decreased repression of gene transcription relative to the unmutated global transcription machinery.

43. The method of claim 1, further comprising selecting the altered cell for a predetermined phenotype.

44. The method of claim 43, wherein the step of selecting comprises culturing the altered cell under selective conditions.

45. The method of claim 43, wherein the step of selecting comprises high-throughput assays of individual cells for the phenotype.

46. The method of claim 43, wherein the phenotype is increased tolerance of deleterious culture conditions.

47. The method of claim 46, wherein the phenotype is solvent tolerance or hazardous waste tolerance.

48. The method of claim 47, wherein the solvent is ethanol, hexane or cyclohexane.

49. The method of claim 46, wherein the phenotype is tolerance of industrial media.

50. The method of claim 46, wherein the phenotype is tolerance of high sugar concentration.

51. The method of claim 46, wherein the phenotype is tolerance of high salt concentration or osmotic stress.

52. The method of claim 46, wherein the phenotype is tolerance of high temperatures.

53. The method of claim 46, wherein the phenotype is tolerance of extreme pH.

54. The method of claim 46, wherein the phenotype is tolerance of surfactants.

55. The method of claim 46, wherein the phenotype is tolerance of a plurality of deleterious conditions, such as tolerance of high sugar and ethanol concentrations.

56. The method of claim 43, wherein the phenotype is increased metabolite production.

57. The method of claim 56, wherein the metabolite is lycopene or ethanol.

58. The method of claim 56, wherein the metabolite is polyhydroxybutyrate (PHB).

59. The method of claim 56, wherein the metabolite is a therapeutic protein.

60. The method of claim 59, wherein the therapeutic protein is an antibody or an antibody fragment.

61. The method of claim 43, wherein the phenotype is tolerance to a toxic substrate, metabolic intermediate or product.

62. The method of claim 61, wherein the toxic metabolite is an organic solvent.

63. The method of claim 62, wherein the toxic metabolite is acetate or para- hydroxybenzoic acid (pHBA).

64. The method of claim 62, wherein the toxic metabolite is an overexpressed protein.

65. The method of claim 43, wherein the phenotype is antibiotic resistance.

66. The method of claim 43, wherein the phenotype is increased resistance to apoptosis.

67. The method of any of claims 43-45, wherein the cell is contained in a multicellular organism.

68. The method of claim 67, wherein the phenotype is one or more growth characteristics, generation time, resistance to one or more pests or diseases, production of fruit or other parts of a plant, one or more developmental changes, one or more lifespan alterations, gain or loss of function and/or increased robustness.

69. The method of claim 1, wherein the cell used in the method is optimized for the phenotype prior to mutating the global transcription machinery.

70. The method of claim 1, further comprising identifying the changes in gene expression in the altered cell.

71. The method of claim 70, wherein the changes in gene expression are determined using a nucleic acid microarray.

72. A method for altering the phenotype of a cell comprising altering the expression of one or more gene products in a first cell that are identified by detecting changes in gene expression in a second cell, wherein the changes in gene expression in the second cell are produced by mutating global transcription machinery of the second cell.

73. The method of claim 72, wherein altering the expression of the one or more gene products in the first cell comprises increasing expression of one or more gene products that were increased in the second cell.

74. The method of claim 73, wherein the expression of the one or more gene products is increased by introducing into the first cell one or more expression vectors that express the one or more gene products.

75. The method of claim 73, wherein the expression of the one or more gene products is increased by increasing the transcription of one or more endogenous genes that encode the one or more gene products.

76. The method of claim 75, wherein increasing the transcription of the one or more endogenous genes comprises mutating a transcriptional control sequence of the one or more genes.

77. The method of claim 72, wherein altering the expression of the one or more gene products in the first cell comprises decreasing expression of one or more gene products that were decreased in the altered cell.

78. The method of claim 77, wherein the expression of the one or more gene products is decreased by introducing into the first cell nucleic acid molecules that reduce the expression of the one or more gene products.

79. The method of claim 78, wherein the nucleic acid molecules are, or express, siRNA molecules.

80. The method of claim 77, wherein the expression of the one or more gene products is decreased by mutating one or more genes that encode the one or more gene products or a transcriptional control sequence of the one or more genes.

81. The method of claim 72, wherein the changes in gene expression in the second cell are determined using a nucleic acid microarray.

82. The method of claim 72, wherein the changes in gene expression in the second cell are used to construct a model of a gene or protein network, and wherein the model is used to select which of the one or more gene products in the network to alter.

83. The method of any of claims 1 -82, wherein the global transcription machinery comprises more than one nucleic acid and/or polypeptide or is encoded by more than one nucleic acid.

84. A cell produced by the method of any of claims 1-83.

85. A method for altering the production of a metabolite, comprising mutating, according to any of claims 1-83, global transcription machinery of a cell that produces a selected metabolite to produce an altered cell, and isolating altered cells that produce increased or decreased amounts of the selected metabolite.

86. The method of claim 85, wherein the method further comprises culturing the isolated cells, and recovering the metabolite from the cells or the cell culture.

87. The method of claim 85, wherein the metabolite is lycopene or ethanol.

88. The method of claim 85, wherein the metabolite is polyhydroxybutyrate (PHB).

89. The method of claim 85, wherein the metabolite is a therapeutic protein.

90. The method of claim 85, wherein the therapeutic protein is a recombinant protein.

91. The method of claim 89, wherein the therapeutic protein is an antibody or an antibody fragment.

92. The method of claim 85, wherein the cells are prokaryotic cells.

93. The method of claim 92, wherein the prokaryotic cells are bacterial cells or archaeal cells.

94. The method of claim 85, wherein the cells are eukaryotic cells.

95. The method of claim 85, wherein the eukaryotic cells are yeast cells.

96. The method of claim 94, wherein the eukaryotic cells are mammalian cells.

97. The method of claim 94, wherein the eukaryotic cells are plant cells.

98. The method of claim 94, wherein the eukaryotic cells are insect cells.

99. The method of claim 94, wherein the eukaryotic cells are stem cells.

100. The method of claim 94, wherein the eukaryotic cells are fungus cells.

101. The method of claim 85, wherein the global transcription machinery is encoded by nucleic acid of an organelle of the eukaryotic cell.

102. The method of claim 101, wherein the organelle is a mitochondrion or a chloroplast.

103. A collection comprising a plurality of different nucleic acid molecule species, wherein each nucleic acid molecule species encodes global transcription machinery comprising different mutation(s).

104. The collection of claim 103, wherein the global transcription machinery is a sigma factor or an anti-sigma factor.

105. The collection of claim 104 wherein a nucleic acid encoding the sigma factor is a rpoD (σ⁷⁰) gene, a rpoF (σ²⁸) gene, a rpoS (σ³⁸) gene, a rpoH(σ³²) gene, a rpoN(a⁵⁴) gene, a rpoE (σ²⁴) gene or a feel (σ¹⁹) gene.

106. The collection of claim Cl, wherein the global transcription machinery binds to an RNA polymerase I, an RNA polymerase II or an RNA polymerase III, or a promoter of an

RNA polymerase I, an RNA polymerase II or an RNA polymerase III.

107. The collection of claim 106, wherein the global transcription machinery is TFIID or a subunit thereof

108. The collection of claim 107, wherein the subunit is TATA-binding protein (TBP) or a TBP-associated factor (TAF), such as TAF25.

109. The collection of claim 103, wherein the global transcription machinery is a nucleic acid methyltransferase, a histone methyltransferase, a histone acetylase or a histone deacetylase.

110. The collection of claim 103, wherein the nucleic acid molecule species are contained in expression vectors.

111. The collection of claim 110, wherein the nucleic acid is expressed from a tissue- specific promoter, a cell-specific promoter, or an organelle-specific promoter.

112. The collection of claim 110, wherein the expression vectors contain a plurality of different nucleic acid molecule species, wherein each nucleic acid molecule species encodes different global transcription machinery.

113. The collection of claim 103, wherein the global transcription machinery is mutated by directed evolution.

114. The collection of claim 113, wherein the directed evolution is performed using error prone PCR.

115. The collection of claim 113, wherein the directed evolution is performed using gene shuffling.

116. The collection of claim 103, wherein the mutation(s) in the global transcription machinery is/are one or more point mutations.

117. The collection of claim 103, wherein the mutation(s) in the global transcription machinery is/are one or more truncations or deletions.

118. The collection of claim 117, wherein the truncation does not include the promoter binding region of the global transcription machinery.

119. The collection of claim 103, wherein the global transcription machinery of a cell is mutated according to any of claims 1-83.

120. A collection of cells comprising the collection of nucleic acid molecules of any of claims 103-119.

121. The collection of claim 120, comprising a plurality of cells, each of the plurality of cells comprising one or more of the nucleic acid molecules.

122. The collection of claim 120, wherein the cells are prokaryotic cells.

123. The collection of claim 122, wherein the prokaryotic cells are bacterial cells or archaeal cells.

124. The collection of claim 120, wherein the cells are eukaryotic cells.

125. The collection of claim 124, wherein the eukaryotic cells are yeast cells.

126. The collection of claim 124, wherein the eukaryotic cells are mammalian cells.

127. The collection of claim 124, wherein the eukaryotic cells are plant cells.

128. The collection of claim 124, wherein the eukaryotic cells are insect cells.

129. The collection of claim 124, wherein the eukaryotic cells are stem cells.

130. The collection of claim 124, wherein the eukaryotic cells are fungus cells.

131. The collection of claim 120, wherein the nucleic acid molecules are integrated into the genome of the cells or replace nucleic acids that encode the endogenous global transcription machinery.

132. A nucleic acid encoding global transcription machinery produced by a plurality of rounds of mutation.

133. The nucleic acid of claim 132, wherein the plurality of rounds of mutation comprise directed evolution.

134. The nucleic acid of claim 133, wherein the directed evolution comprises mutation by error prone PCR.

135. The nucleic acid of claim 133, wherein the directed evolution comprises mutation by gene shuffling.

136. The nucleic acid of claim 132, wherein the nucleic acid encodes a plurality of different global transcription machinery species.

137. The nucleic acid of claim 132, wherein the nucleic acid encodes a plurality of different versions of the same type of global transcription machinery species.

138. Global transcription machinery encoded by the nucleic acid of claim 132-136.

139. A truncated sigma factor protein comprising (carboxy-terminal) region 4.

140. A method for bioremediation of a selected waste product, comprising mutating, according to any of claims 1-83, global transcription machinery of a cell to produce an altered cell, isolating altered cells that metabolize an increased amount of the selected waste product relative to unaltered cells, culturing the isolated cells, and exposing the altered cells to the selected waste product, thereby providing bioremediation of the selected waste product.