• Comment: To identify that a topic is sufficiently notable to need a Wikipedia article, we look for "significant coverage in reliable sources that are independent of the subject." Chang C. Liu, leader of the group that developed this method, is listed in as an author in all the references currently on this article. They are therefore not independent of the subject. I would like to see what authors outside this group are saying about the method, both to demonstrate that it is notable, and to make sure that we adopt a WP:Neutral point of view. Mgp28 (talk) 15:08, 24 July 2024 (UTC)

OrthoRep is a hypermutation system used for the directed evolution of proteins. It was developed by the group of Chang C. Liu at the University of California, Irvine. It is one of the methods used for in vivo continuous evolution, which aims to expand the depth and scale in the evolutionary search for highly efficient proteins compared to conventional directed evolution. The method is based on a natural plasmid system in Kluveromyces lactis, which was ported to Saccharomyces cerevisiae, creating an extrachromosomal orthogonal error-prone replication system in yeast.[1]

Method principle

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OrthoRep in vivo hypermutation system. A highly error-prone orthogonal DNA polymerase (DNAP, green) specifically hyper-mutates a gene of interest located on a p1 plasmid (blue) in the cytosol of Saccharomyces cerevisiae through a protein-primed mechanism (red). The host genome is unaffected. The introduced mutations are shown as pink stars.

OrthoRep is based on a highly error-prone orthogonal DNA polymerase (DNAP), which specifically hyper-mutates a gene of interest (GOI) located on a so-called p1 plasmid in the cytosol of S. cerevisiae[2]. Although the GOI experiences a elevated mutation rate, the host genome of the cell is unaffected because of the highly specific protein-primed replication mechanism of p1 recognition by the error-prone polymerase.

As mutations are getting introduced onto the gene of interest, improved variants of the corresponding protein of interest can be identified by two possible approaches:

  1. Selection
    • the function of the GOI is linked to cell growth or survival (e.g., drug resistance, formation of an essential nutrient, ...)
    • by passaging of the cells in media with increased selection stringency (e.g., increased drug concentration, decreased nutrient concentration), only the cells bearing improved protein variant will survive
  2. High-throughput screening

Advantages over classical directed evolution

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Comparison of classical directed evolution and in vivo continuous evolution using OrthoRep. The main drawback of conventional evolution is that it relies on a manually staged library generation step using in vitro mutagenesis (e.g. error-prone PCR), which limits the sequence diversity that can be generated. In vivo continuous evolution eliminates this limitation by using in vivo hypermutation systems such as OrthoRep, where mutatitions are generated autonomously inside the cells.

OrthoRep is one of the examples of an in vivo hypermutation system (other examples include for instance MutaT7 or EvolvR)[2]. Compared to conventional directed evolution, which relies on a manually staged in vitro library generation (e.g., with error-prone PCR, which can generate very limited sequence diversity), such hypermutation systems enable genetic diversity to be generated autonomously inside the cells. When coupled to selection, all of the steps involved in directed evolution campaigns - (i) gene amplification and hypermutation, (ii) protein expression and (iii) selection - happen autonomously as the cells replicate, without any interference from the researcher.

As a consequence, OrthoRep enables multiple evolutionary pathways to be analysed simultaneously and in higher depth compared to conventional directed evolution, increasing the explored sequence space, and potentially leading to better performing protein variants.

Error-prone polymerases

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A number of orthogonal error-prone DNAPs have been engineered for the OrthoRep system. Some of the most commonly used ones are listed in Table 1. They vary in their error rates and their preferences for different mutation types (transitions and transversions).[3]

Table 1: mutation rates of selected orthogonal error-prone DNAPs
DNAP error rate (substitutions per base) fold increase over genomic mutation rate
TP-DNAP1-4-2[4] 10-5 100,000
BadBoy2[3] 10-4 1,000,000
BB-Tv[3] 10-5 100,000

Examples of use

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Tryptophan synthase evolution

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In an 2020 article in Nature Communications, Rix et al. reported the evolution of a highly efficient tryptophan synthase 𝛽-subunit (TrpB) from Thermotoga maritima[5]. The protein of interest catalyses the synthesis of L-tryptophan, an amino acid essential for growth of a tryptophan auxotrophic yeast strain. By coupling OrthoRep hypermutation with selection, the authors engineered a TrpB with increased tryptophan-forming activity and broadened secondary promiscuous activities toward related substrates.

Antibody evolution

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'Autonomous hypermutation yeast surface display' (AHEAD), a technology based on the OrthoRep system reported in 2021[6], has been used to generate potent nanobodies against the SARS-Cov-2 S-glycoprotein and other targets.

Optimization of cis,cis-muconic acid biosynthetic pathway

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In a 2021 article in Microbial Biotechnology journal, the biosynthetic pathway for the production of cis,cis-muconic acid (CCM, precursor used for bioplastic and coatings) was optimised using OrthoRep[7]. The evolution of the rate-limiting enzyme in the pathway, PCA decarboxylase, was followed in high throughput using a transcription-based biosensor, yielding a fluorescent readout, and enabling coupling to FACS.

References

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  1. ^ Ravikumar, Arjun; Arrieta, Adrian; Liu, Chang C. (2014). "An orthogonal DNA replication system in yeast". Nature Chemical Biology. 10 (3): 175–177. doi:10.1038/nchembio.1439. ISSN 1552-4469. PMID 24487693.
  2. ^ a b Molina, Rosana S.; Rix, Gordon; Mengiste, Amanuella A.; Álvarez, Beatriz; Seo, Daeje; Chen, Haiqi; Hurtado, Juan E.; Zhang, Qiong; García-García, Jorge Donato; Heins, Zachary J.; Almhjell, Patrick J.; Arnold, Frances H.; Khalil, Ahmad S.; Hanson, Andrew D.; Dueber, John E. (2022-05-19). "In vivo hypermutation and continuous evolution". Nature Reviews Methods Primers. 2 (1): 1–22. doi:10.1038/s43586-022-00119-5. ISSN 2662-8449. PMC 10108624. PMID 37073402.
  3. ^ a b c Rix, Gordon; Williams, Rory L.; Spinner, Hansen; Hu, Vincent J.; Marks, Debora S.; Liu, Chang C. (2023-11-14). "Continuous evolution of user-defined genes at 1-million-times the genomic mutation rate". bioRxiv: 2023.11.13.566922. doi:10.1101/2023.11.13.566922. PMC 10680746. PMID 38014077.
  4. ^ Ravikumar, Arjun; Arzumanyan, Garri A.; Obadi, Muaeen K.A.; Javanpour, Alex A.; Liu, Chang C. (2018). "Scalable, Continuous Evolution of Genes at Mutation Rates above Genomic Error Thresholds". Cell. 175 (7): 1946–1957.e13. doi:10.1016/j.cell.2018.10.021. ISSN 0092-8674. PMC 6343851. PMID 30415839.
  5. ^ Rix, Gordon; Watkins-Dulaney, Ella J.; Almhjell, Patrick J.; Boville, Christina E.; Arnold, Frances H.; Liu, Chang C. (2020-11-06). "Scalable continuous evolution for the generation of diverse enzyme variants encompassing promiscuous activities". Nature Communications. 11 (1): 5644. Bibcode:2020NatCo..11.5644R. doi:10.1038/s41467-020-19539-6. ISSN 2041-1723. PMC 7648111. PMID 33159067.
  6. ^ Wellner, Alon; McMahon, Conor; Gilman, Morgan S. A.; Clements, Jonathan R.; Clark, Sarah; Nguyen, Kianna M.; Ho, Ming H.; Hu, Vincent J.; Shin, Jung-Eun; Feldman, Jared; Hauser, Blake M.; Caradonna, Timothy M.; Wingler, Laura M.; Schmidt, Aaron G.; Marks, Debora S. (2021). "Rapid generation of potent antibodies by autonomous hypermutation in yeast". Nature Chemical Biology. 17 (10): 1057–1064. doi:10.1038/s41589-021-00832-4. ISSN 1552-4469. PMC 8463502. PMID 34168368.
  7. ^ Jensen, Emil D.; Ambri, Francesca; Bendtsen, Marie B.; Javanpour, Alex A.; Liu, Chang C.; Jensen, Michael K.; Keasling, Jay D. (2021). "Integrating continuous hypermutation with high-throughput screening for optimization of cis,cis-muconic acid production in yeast". Microbial Biotechnology. 14 (6): 2617–2626. doi:10.1111/1751-7915.13774. ISSN 1751-7915. PMC 8601171. PMID 33645919.