Organisms ensure the fidelity of their DNA by three overlapping pathways namely base selection, proofreading and mismatch repair. These pathways cumulate in replication fidelity of ~10^-10 mutations per bp per generation in E. coli (Lee et al. 2012). Overexpression of dominant negative variants of major players in this system can increase the mutation rate substantially. Recently, mutation rates up to 6.2×10^-6 mutations per bp and per generation were obtained by using a plasmid-borne mutator system (Badran, Liu 2015). We aim to make this mutator plasmid available for the whole iGEM community by rebuilding it with defined iGEM parts (see our BBa_K208117). We envision an application in the directed evolution of our binding protein. Furthermore, implementation in other directed evolution approaches could be feasibly in which our plasmid pose an in vivo alternative to error-prone PCR (Wilson, Keefe 2001) or exogene mutagens (reviewed in Wong et al. 2006; Steensels et al. 2014).

DNA is the single blueprint for all proteins of an organism. Minor changes in the DNA sequence are mostly without significant consequences, but in some cases the consequences are detrimental e.g. by rendering encoded crucial proteins useless. Therefore, an effective system of DNA repair mechanisms emerged during evolution. The DNA fidelity system is composed of three main mechanisms, which contribute to the high fidelity. The first fidelity mechanism lies in selecting the correct base for incorporation during replication of DNA. This process of base selection reduces the error rate by 10⁵ mutations per bp per generation. During replication, the acting polymerase (mainly polymerase III in E. coli) directly corrects falsely incorporated bases. This process is called proofreading and reduces the error rate by 10² mutations per bp per generation. Other mutations in the DNA e.g. introduced through replication errors or other mutagenic sources are repaired by the mismatch repair systems. This system reduces the error rate by 10³ mutations per bp per generation. (Schaaper 1993; Fijalkowska et al. 2012) All these fidelity mechanisms contributed to the error rate reduction, leading to a final rate of about 10^-10 mutations per bp per generation. (Lee et al. 2012).
Many variants of the participating proteins with (partial) loss-of-function were identified and described in the literature (Degnen, Cox 1974; Nghiem et al. 1988; Schaaper, Radman 1989; Fowler, Schaaper 1997; Junop et al. 2003). The common phenotype upon the mutants was a strongly increased mutation rate. It did not take long before better-characterized hypermutator strains arose as a tool to study the effect of random mutations on proteins or to improve proteins trough means of directed evolution (Greener et al. 1997; Selifonova et al. 2001; Stefan et al. 2001). A common issue among different applications of genomic mutator genes is the general genetic instability and frequent unviability of these strains. For example, the E. coli strain, which chromosomally harbors the strongest known mutator dnaQ926 is almost completely unviable without additional mutations (Fijalkowska, Schaaper 1996). Therefore, recent development was directed to the rational design of a plasmid-borne mutator system. Combination of strong mutator capabilities with a tight inducible promoter should result in a controllable mutagenesis system, generally circumventing many issues of chromosome-based hypermutator strains. Furthermore, the rational combination of different groups of mutator genes enables compositions, which have a very balanced mutagenesis spectra
Our mutation system was designed to use an untargeted mutation approach as an alternative to the error-prone polymerase I. Therefore, we reconstructed the previously described mutator plasmid (Badran, Liu 2015), which consists of six different genes.

Overexpression of these mutator genes rises the mutation frequency in E. coli to 6.2×10^-6 per bp per generation with induction and only ~4×10^-9 per bp per generation without induction. Moreover, the mutation spectrum is very diverse.

The dnaQ gene encodes ε-subunit of E. coli DNA polymerase III, which is responsible for the proof reading activity of this enzyme. DnaQ confers 3'-exonuclease activity, which excises falsely incorporated bases during replication. DnaQ926 contains two amino acid substitutions (D12A, E14A) in the Exo I region, which prevents coordination of an essential metal ion and therefore abolishes the proofreading activity (Fijalkowska, Schaaper 1996). The overall structure of DnaQ and interactions with other proteins of the DNA polymerase III complex are not affected by these substitutions. dnaQ926 acts as a dominant negative gene causing a strong mutator phenotype even in E. coli strains with chromosomal wild type dnaQ (Cox, Horner 1986). DnaQ926 competes against DnaQ about incorporation into the DNA polymerase III complex. Incorporation of DnaQ926 leads to proofreading deficient replication complexes. Therefore, overexpression or plasmid-based expression of dnaQ926 is supposed to yield an increased mutation effect. The huge amount of mutations introduced by dnaQ926 overwhelms the E. coli mismatch repair system leading to the manifestation of mutations from various sources (Schaaper, Radman 1989; Damagnez et al. 1989)
The exact rate and mutagenesis spectrum of DnaQ926 depends on the used cultivation media. Rich media leads high mutation frequency (3.7×10⁴ over background) with mostly transitions, while minimal media cause less mutations (4.8×10² over background) and mostly transversions (mainly AT → TA). The faster growth of bacteria in rich media decreases the time the time to remove errors before cell division via the repair mechanisms (Schaaper 1988).

A mechanism of mismatch repair is the Dam-directed mismatch repair (DDMR). Parental and daughter DNA strands are modified by methylation at GATC sites. These methylations are added after replication by the DNA adenine methylase (Dam). In the timeframe between daughter strand synthesis and Dam methylation the repair mechanisms can distinguish between the correct base on the methylated parent strand (template) and the falsely incorporated base on the non-methylated daughter strand (product). This modification is used by the mismatch repair proteins MutS, MutL and MutH, which repair the daughter strand relying on information from the parent strand (Horst et al. 1999).
SeqA is a GATC-binding protein, which also controls the methylation state of DNA. It counteracts Dam by demethylating DNA. This results in hypomethylated DNA on both strands, which further decreases the efficiency of DNA mismatch repair (Yang et al. 2004).
Combined overexpression of dam and seqA strongly shifts the methylation state of the DNA. Methylation of the parental strand by SeqA is reduced while the methylation of the daughter strand via Dam is increased. Both effects abrogate the methylation difference between parental and daughter strand and prevent effective mismatch repair.

As mentioned before, the main factor of replication fidelity is the correct base incorporation during replication. This is mainly dependent on the α-subunit of DNA polymerase III, but the intracellular concentrations of the single nucleotidetriphosphates are important too (ref?). A strong imbalance between the single nucleotide-triphosphates or a high concentration of base analogs can increase the rate of erroneous base incorporation (Gon et al. 2011).
This metabolic imbalance is achieved by the overexpression of emrR. The transcription repressor EmrR reduces the expression of the repressor of the emrAB operon. This operon encodes an efflux pump, which is linked to multidrug resistance (Lomovskaya et al. 1995). However, the native function of EmrAB is the export of intermediates of the purine and pyrimidine metabolism. An overexpression of emrR reduces the concentration of EmrA and EmrB leading to increased concentration of nucleotide precursors inside the cell. At high concentrations, these nucleotide precursors can act as base analogs. Mutations are caused either incorporation of the nucleotide precursor or by failure during the repair attempt of an erroneous base incorporation(Gabrovsky et al. 2005).

Cytidin deaminases (cda) are DNA editing enzymes in eukaryotes, which have multiple functions like the generation of antibody diversity, defence against retroviruses and demethylation during development (Lada et al. 2011).
The main activity of CDAs is the deamination from cytidin to uracil in CG base pairs. The resulting UG base pairs split in replication in one CG and one UA basepair. Therefore, the main mutations created by CDAs are C → T transitions.

Organisms have created mechanism to repair mismatches as UG pairs via the base excision repair (BER). Thereby the mismatched base is cut out by the uracil-DNA-glycosylase (UNG). The resulting abasic site (AP-site) is cleaved by an AP-endonuclease and the patch is filled by a variety of specialized proteins (Krokan, Bjoras 2013).
Overexpression of eukaryotic cytidin deaminase increases the mutation rate in bacteria. The CDA1 of Pteromyzon marinus was identified in a comprehensive screen as the most potent cytidin deaminase when expressed in E. coli. Overexpression of P. marinus cda1 increases the mutation rate to 10^-6-10^-5 per bp. In ung deficient strains the effect was amplified by a factor of 50 due to the lack of UNG induced BER (Lada et al. 2011).
The CDS of P. marinus cda1 was codon optimized for E. coli integrated into our mutagenesis plasmid to increase the expression. Moreover, the uracil-DNA-glycosylase inhibitor (ugi) was added. This short protein mimics the structure of abasic sides, binds to UNG and inhibits the UNG mediated BER pathway (Serrano-Heras et al. 2007).

See here how we characterized our genome wide mutator by reversion assays and high-throughput sequencing

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