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. 2021 Feb 9;24(3):102168. doi: 10.1016/j.isci.2021.102168

Recombination machinery engineering for precise genome editing in methylotrophic yeast Ogataea polymorpha

Jiaoqi Gao 1,2,3, Ning Gao 1,3, Xiaoxin Zhai 1,3, Yongjin J Zhou 1,2,3,4,5,∗
PMCID: PMC7907465  PMID: 33665582

Summary

Methanol biotransformation can expand biorefinery substrate spectrum other than biomass by using methylotrophic microbes. Ogataea (Hansenula) polymorpha, a representative methylotrophic yeast, attracts much attention due to its thermotolerance, but the low homologous recombination (HR) efficiency hinders its precise genetic manipulation during cell factory construction. Here, recombination machinery engineering (rME) is explored for enhancing HR activity together with establishing an efficient CRISPR-Cas9 system in O. polymorpha. Overexpression of HR-related proteins and down-regulation of non-homologous end joining (NHEJ) increased HR rates from 20%–30% to 60%–70%. With these recombination perturbation mutants, a competition between HR and NHEJ is observed. This HR up-regulated system has been applied for homologous integration of large fragments and in vivo assembly of multiple fragments, which enables the production of fatty alcohols in O. polymorpha. These findings will simplify genetic engineering in non-conventional yeasts and facilitate the adoption of O. polymorpha as an attractive cell factory for industrial application.

Subject areas: Biological sciences, Molecular Microbiology, Bioengineering, Metabolic Engineering, Biotechnology, Microbial Biotechnology

Graphical abstract

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Highlights

  • •

    Establishing an efficient and convenient CRISPR-Cas9 system in Ogataea polymorpha

  • •

    Enhancing homologous recombination for precise genome editing in O. polymorpha

  • •

    Realizing seamless deletion and assembly of multiple fragments in O. polymorpha

Biological sciences; Molecular Microbiology; Bioengineering; Metabolic Engineering; Biotechnology; Microbial Biotechnology

Introduction

Single-carbon (C1) feedstocks represent as attractive substrates for future biorefinery owing to their abundance and no-food competition (Clomburg et al., 2017; Zhou et al., 2018). Among these feedstocks, methanol, which can be derived from coal, natural gas, or CO2, is an ideal substrate for bio-manufacturing owing to its liquid state for efficient mass transfer (Duan and Gao, 2018; Zhou et al., 2018). In nature, there exists a group of microorganisms named “methylotrophs,” which efficiently assimilate methanol for growth. Ogataea (Hansenula) polymorpha, as one of methylotrophic yeasts, possesses various advantages in the wide substrate spectrum like xylose and methanol and has extreme thermo-tolerance (over 50°C) (Saraya et al., 2012), which makes it a promising cell factory for protein expression and chemical production (Ubiyvovk et al., 2011; Voronovsky et al., 2009). However, similar to other non-conventional yeasts, the difficulties in convenient and precise genome editing in O. polymorpha will limit its metabolic engineering toward industrial production (Cai et al., 2019; Schwartz and Wheeldon, 2017).

In recent years, the CRISPR-Cas9 system has been applied for genetic engineering in numerous organisms with high efficiency and accuracy (McGinn and Marraffini, 2018; Raschmanova et al., 2018). Precise genome editing via the CRISPR-Cas9 system depends on Cas9 protein and single guide RNA (gRNA). Cas9 protein is a kind of RNA-mediated endonuclease with two active domains, HNH and RuvC, which cuts off double-stranded DNA with the assistance of nuclear locating signal and gRNA. As another essential component, gRNA is composed of CRISPR-targeting RNA (crRNA) and trans-activating crRNA. A 20-bp spacer in crRNA comes from the targeting sequence with a specific protospacer adjacent motif at the 3′ end. Cas9 protein is guided by gRNA with a specific secondary structure to perform double-strand break (DSB) (McGinn and Marraffini, 2018) (Figure 1).

Figure 1.

Figure 1

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Optimized CRISPR/Cas9 system in O. polymorpha with dynamically repressed NHEJ and enhanced HR

Cas9 with the guidance of single guide RNA (sgRNA) efficiently cuts DNA to form DSBs, which are subsequently repaired by either NHEJ or HR. While NHEJ occurs, DNA end is first protected by the Ku70-Ku80 heterodimer, which performs the recruitment of DNA-dependent protein kinase catalytic subunit (DNA-PKcs), Artemis, XRCC4/DNA ligase IV complex, etc. Hence, dynamically down-regulating this key protein Ku80 is supposed to be a reasonable strategy to decrease this error-prone and random repair pathway. On the contrary, HR process starts with DNA resection, and ssDNA is generated by a complex consisting of Mre11, Sae2, etc. Subsequently, with the help of Rad52, multiple HR-related proteins (Rad51) are recruited to form the complex for strand invasion and D-loop formation. At last, through a homology search, donor DNA fragments are precisely integrated into the specific sites by DNA polymerase and ligase. Therefore, overexpressing these HR-related proteins represents another alternative way to enhance HR efficiency in O. polymorpha.

Once the DSB is formed, cells immediately activate the DNA repair process to prevent genomic instability and cell death, which may eventually result in specific genome editing. Two main repair pathways may happen in the DSB repair process, including classical non-homologous end joining (NHEJ) and homologous recombination (HR) (Figure 1). NHEJ initiates by binding of the Ku70-Ku80 heterodimer to the DSB, which recruits NHEJ polymerase, nuclease, and ligase complexes, resulting in multiple rounds of nucleotide deletion and insertion. This process is error-prone, uncontrollable, and template independent in a random manner (Chang et al., 2017), which is obviously not suitable for metabolic engineering. On the contrary, HR is supposed to be a preferred DNA repair pattern over NHEJ, as HR may result in the site-specific integration or deletion of a target fragment. The choice and regulation of HR pathway is extremely complicated concerning cell cycle, end resection in DSBs, and multiple HR-related proteins like Rad51 (Ceccaldi et al., 2016).

NHEJ is the dominant repair mechanism in most non-conventional yeasts including O. polymorpha, which leads to the relatively low genome editing efficiencies (normally <30%), especially low HR rates in the currently reported CRISPR-Cas9 systems in O. polymorpha (Juergens et al., 2018; Numamoto et al., 2017; Wang et al., 2018), and these systems were far behind the requirements for precise pathways engineering and thus hinder extensive genetic engineering for metabolic reprogramming (Weninger et al., 2018; Yu et al., 2018). Here, we constructed and optimized a CRISPR-Cas9 system in O. polymorpha to enhance the genome cutting efficiency. Then we enhanced the HR rates and repressed the NHEJ process for precise genetic manipulation. With this endeavor, we successfully established an applicable platform in non-conventional yeast O. polymorpha, which enabled scarless gene deletion, in vivo assembly, and integration of multiple DNA fragments. In particular, this genome editing platform was applied in engineering O. polymorpha for production of fatty alcohols. We anticipate that this efficient genetic engineering system can make this O. polymorpha an important workhorse for methanol and biomass-based bio-manufacturing.

Results

Construction and optimization of CRISPR-Cas9 system

To achieve the expression of Cas9 protein, a human codon-optimized CAS9 gene was integrated into the genome by single crossover, which was controlled by the promoter of glyceraldehyde-3-phosphate dehydrogenase (PGAP) and the terminator of alcohol oxidase 1 (TAOX1), both from Komagataella phaffii. Strain 495-3 with a copy of the integrated CAS9 gene was verified by RT-PCR (Figure S1A) and had no growth defect compared with the wild-type strain.

An episomal plasmid for gRNA expression was adopted by inserting the autonomous replication start from Kluyveromyces lactis (panARS) (Figure S1B) (Liachko and Dunham, 2014). Considering the advantage of RNA pol III promoter (PtRNACUG) in yielding a functional mature gRNA without 5′ cap and 3′ tail (Figure 2A), a dual direction gRNA expression cassette was constructed with the promoter of tRNACUG from O. polymorpha (Numamoto et al., 2017). However, the mutation rate was less than 0.1% when targeting the gene OpADE2 in strain 495-3 (Table S1). In this case, the terminator TSUP4 from S. cerevisiae was replaced by a more effective terminator like SNR6t from O. polymorpha (Figures S1B and 2A). Unfortunately, the editing efficiency was still very low (around 0.4%) when targeting the OpADE2 gene (Table S1 and Figure 2D). To further enhance gRNA expression, a gRNA expression cassette mediated by RNA pol II promoter POpTEF1 (promoter of translation elongation factor EF-1 alpha from O. polymorpha) was constructed. This gRNA expression cassette enabled 93.4% editing efficiency for OpADE2, which was over 200-fold higher than that mediated by RNA pol III promoter (Table S1 and Figure 2D). Similarly, when targeting the gene OpKU80, all eight selected transformants had mutations around gRNA sites by sequencing, achieving a 100% editing efficiency (Table S1).

Figure 2.

Figure 2

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Optimization of gRNA expression for improving genome editing efficiency

(A) Dual direction of gRNA expression by RNA pol III promoter, generating a clean mature gRNA.

(B) gRNA expression by RNA pol II promoter (POpTEF1), generating a clean mature gRNA with the help of ribozyme HH and HDV.

(C and D) (C) Constant N6 sequence generates a mature gRNA with extra 6 bp of 5′ cap; (D) gene editing rate of targeting gene OpADE2 with different gRNA expression cassettes and N6 sequences. As OpADE2 disruption resulted in red colony, the editing rates were calculated as percentages of red colonies. Data are presented as mean ± SEM (n = 3 biologically independent samples). Statistical analysis using paired t test showed no significant difference (NSD) between variable and constant N6 sequences.

In the aforementioned system, ribozyme HH contains a variable 6-bp sequence that is reverse complement to the first 6 bp on gRNA sequence (Figure 2B), which makes it difficult and expensive to replace the 20-bp spacer when targeting another gene owing to the requirement of multiple long primers (Figure S1C). Hence, a constant N6 sequence reversely complementing to the last 6-bp sequence in ribozyme HH was adopted for convenient construction of gRNA expression cassettes (Figures 2C and S1C). We then tested the possible negative effect of the constant N6 sequence on genome editing rates by targeting multiple genes (Table S1 and Figure 2D). The mutation efficiency of constant N6 sequence showed no significant differences when compared with that of variable N6 sequence while targeting both OpADE2 and OpKU80. DNA sequencing showed that there were mostly indel mutations (1- or 2-bp deletion, insertion, and mutation) at editing sites and a few random insertions of the large DNA fragment (Figure S2), which suggested that the constant N6 sequence did not affect the guiding efficiency for Cas9 enzyme. Thus the constant N6 sequence was utilized for the further construction of gRNA expression cassettes.

Enhanced HR-mediated DSB repair

Low HR rate has been previously reported in O. polymorpha, which seriously hinders its application in extensive metabolic reprogramming (Juergens et al., 2018; Numamoto et al., 2017). We thus tried to enhance HR rate for precise genome engineering. We first explored to synchronize the expression of Cas9 protein from O. polymorpha in the late S and G2 phases of cell cycle, when HR activity remains the highest to meet the requirements of sister chromatid synapsis (Gutschner et al., 2016). Thus, an anaphase-promoting complex (APC)-dependent mitotic cyclin protein Pds1 from S. cerevisiae was fused to the C terminal of Cas9, which was functional in the S and G2 phases, and recognized, ubiquitinated, and degraded by APC in the M and G1 phases (Figure 3A) (Cohen-Fix et al., 1996). Similar to that in mammalian cells, Cas9-Pds1 fusion significantly enhanced the scarless gene deletion from 20%–40% to 50%–60% in strain O. polymorpha 495-3 (Figure 3B), which suggested that mitotic cyclin protein Pds1 from S. cerevisiae played a positive role in promoting the HR rate of O. polymorpha. However, unstable promotion of HR rates (5%–60%) was observed for targeting OpFAA1 and HpPOX1 in numerous experiments (Figures 3B and S3B), which might be attributed to the complex regulation of cell cycle (Aird et al., 2018).

Figure 3.

Figure 3

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Enhancing HR process promotes the efficiencies of scarless gene deletion

(A) A fusion of Cas9- and ScPds1-promoted HR activity synchronized with cell cycle. Cas9-Pds1 was ubiquitinated and degraded in the M and G1 phases and functional as the normal Cas9 protein in the late S and G2 phases. HR rates were calculated as the percentages of HR clones, which were determined by colony PCR of transformants and showed a shorter DNA band when compared with NHEJ colony. Ufw and Urv and Dfw and Drv are forward and reverse primers from upstream and downstream, respectively, for colony PCR.

(B) The HR rates were calculated while targeting genes OpPOX1, OpFAA1, and Ku80 promoter sequence (PKU80) in strains expressing Cas9 or Cas9-Pds1. In particular, multiple experiments were performed to prove an unstable behavior in strain Cas9-Pds1 while targeting genes OpPOX1 and OpFAA1 (red square).

(C) Overexpressing HR-related proteins improved HR rates for scarless disruption of succinate-CoA ligase encoding gene (OpLSC2). Total 20 colony from each biological parallel was picked and tested by colony PCR to calculate HR rate. Data are presented as means of two biologically independent samples with displayed data points. Red asterisks indicate statistical significance as determined using paired t test (∗p < 0.05; ∗∗p < 0.01).

We then explored other simple and stable approaches to promote HR-mediated repair process. It has been showed that three functional proteins Sae2, Rad52, and Rad51 played the main role in efficient HR in S. cerevisiae (Figure 1) (Krejci et al., 2012; Mimitou and Symington, 2008). We thus learned from S. cerevisiae with extremely high HR rates and reconstructed its HR system in O. polymorpha. HR-related proteins from S. cerevisiae demonstrated an obvious promotion in HR rate by 10%–20% in the overexpression strains (Figure 3C). In particular, strain y34 with the combination of S. cerevisiae genes ScSAE2, ScRAD52, and ScRAD51 had HR rates of ∼70%, when targeting succinate-CoA ligase gene OpLSC2 (Figure 3C) and the KU80 promoter PKU80 (Figure S4B), which were significantly higher than that of the control strain. Quantitative RT-PCR (qPCR) analysis confirms the functional transcription of these genes and proved that the expression level of these genes was dozens of times higher than that of endogenous gene OpRAD52 in wild-type (Figure S5A). A moderate expression level balanced the HR rate, the colony-forming units (CFU) per unit of cell (CFU/OD600), and cell growth. Despite the lower HR rates, some specific strains (y46, y47, and y48) showed an obviously higher CFU number due to an efficient DSB repair process (Figures S3C and S4C). Subsequently, endogenous OpRAD51 and OpRAD52 from O. polymorpha were identified and overexpressed, and unfortunately, OpSAE2 was not successfully identified based on homology search of O. polymorpha genome. OpRAD51 overexpression was lethal, and only OpRAD52 overexpression strain (y45) was obtained. OpRAD52 overexpression resulted in a significantly higher CFU/OD600 (Figure S3C) and HR rate (Figure 3C) in targeting gene OpLSC2 due to its extremely higher expression level (Figure S5A). However, targeting the promoter of KU80 in strain y45 had a fluctuation in HR rates (Figure S4). These data suggested that y34 had the most stable and significant increase in HR rate for genome manipulation.

Down-regulation of non-homologous end joining

NHEJ plays the dominant role in DSB repair in several non-conventional organisms including O. polymorpha (Figure S2) (Schwartz and Wheeldon, 2017). Ku heterodimer proteins Ku70 and Ku80 are key components for NHEJ-based DNA repair by binding the DNA DSB ends (Figure 1). Previous studies showed that the disruption of KU70 or KU80 repressed NHEJ and resulted in a relatively higher HR-mediated DSB repair (Juergens et al., 2018; Kretzschmar et al., 2013). Here we also showed that KU80 disruption significantly improved the relative HR-mediated DSB repair to almost 100% (Figure 4E). However, this KU80 disruption seriously reduced the CFU number (Figure 4D) and slightly retarded the cell growth (Figure 4B), which suggested that repressing Ku heterodimer proteins caused stress on cellular fitness. Alternatively, we dynamically repressed KU80 by replacing its native promoter with a responsive promoter of MET3 gene (POpMET3) that was repressed by methionine (Figure S6A) (Yoo et al., 2015). With this system, KU80 can be conditionally repressed during genetic manipulation by adding methionine in culture media and/or selection plates and de-repressed in bio-production conditions (Figure 4A). Expression level of the gene KU80 was obviously down-regulated in strain Ku80-dw with methionine (Figure S5B), which, however, was not as much lower as the reported level (10%–20%) (Yoo et al., 2015). Optimization of methionine concentrations showed that 1.7 mM methionine was enough to down-regulate Ku80 for enhancing HR rate in rich medium like YPD (Figures S6B and S6C), and a higher methionine concentration was recommended to compensate the possible consumption and metabolism during cultivation in basic medium (Figure S6D).

Figure 4.

Figure 4

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Down-regulation of KU80 enhanced HR rates by repressing NHEJ process

(A) KU80 expression under the control of POpMET3 promoter was down-regulated when methionine existed. A down-regulated KU80 prevented Ku complex formation, which eventually decreased NHEJ activity, and the repressed NHEJ process forced cells to select HR to repair DNA DSB for survival. Without methionine supplementation, the KU80 repression will be removed and enabled the normal cell growth during production condition.

(B–E) (B) Cell growth behaviors in strains wild-type (WT), KU80 disruption (ku80Δ), and KU80 down-regulation (Ku80-dw). Data are presented as mean ± SEM (n = 2 biologically independent samples). (C) Positive clones (positive rate×transformant number) targeting gene POX1 in strains WT, ku80Δ, and Ku80-dw. CFU/OD600 (D) and HR rate (E) in strains with both overexpressed HR-related proteins and down-regulated KU80 expression, when targeting gene OpLSC2. Total 20 colonies from each biological parallel were picked and tested by colony PCR to calculate the HR rate. Data are presented as means of two biologically independent samples with displayed data points. Red asterisks indicate statistical significance as determined using paired t test (∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001).

The dynamic down-regulation of KU80 (strain Ku80-dw) had a much higher CFU number when compared with that of KU80 disruption (strain ΔKu80) and was comparable with that of the wild-type strain (Figure 4D). Furthermore, strain Ku80-dw grew faster than the wild-type strain at the early log phase, whereas strain Ku80Δ had poorer growth in the late stage of log and stable phases (the differences were significant, Figure 4B). In total, this dynamic down-regulation of Ku80 enabled an over 3-fold higher HR rate (∼60%) with the highest positive clones (Figure 4C) when compared with the wild-type strain.

We then investigated whether the combination of overexpression of HR-related genes with down-regulation of KU80 (Ku80-dw) could further improve HR rates (Figures 4D and 4E). Additional overexpression of ScRAD51 with down-regulation of KU80 resulted in significantly lower CFU/OD600 (strain y31-Ku80dw, y32-Ku80dw, y33-Ku80dw, and y34-Ku80dw versus Ku80-dw). Overexpression of ScRAD52 with down-regulation of KU80 increased CFU/OD600, but had a marginal effect on the HR activity. Interestingly, combined overexpression of endogenous OpRAD52 with KU80 down-regulation resulted in much lower CFU/OD600 and HR rate, which suggested that an extensively regulated endogenous DSB repair system brought severe cellular stress. These data clearly showed that a combination of two strategies did not further promote the HR rate in O. polymorpha. Considering the balance of HR rates and CFU/OD600 numbers, y34 (overexpression of ScSAE2, ScRAD51, and ScRAD52) and Ku80-dw strain had similar HR rates of 60%–70% (Figures 3C and 4E).

Competitive binding of RPA and Ku80 to DSB sites

Down-regulation of KU80 (strain Ku80-dw) and overexpression of RADs (strain y34) both had more HR colonies and higher HR rates when compared with the wild-type strain (Figure 5A), which might be owing to a competitive binding of relating proteins in HR process and NHEJ pathway to DSB sites (O'Driscoll and Jeggo, 2006). Hence, the initial proteins RPA and Ku80 were selected to roughly profile the relative binding efficiencies to DSB sites (Heyer et al., 2010; Krejci et al., 2012). We here fused green fluorescent protein to the main component protein RPA (RPA-GFP) of the HR process and red fluorescent protein to Ku80 (Ku80-RFP) of the NHEJ pathway. After the induction of DNA damage at the OpLSC2 site, the intensities of fluorescence of GFP and RFP were both detected at 24 h by a microplate reader (Figure 5B).

Figure 5.

Figure 5

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A competitive binding to DSBs leads to the change in HR/NHEJ ratio

(A) HR colonies and NHEJ colonies in strains of wild-type (WT), KU80 down-regulation (Ku80-dw under repression of methionine), and overexpression of HR-related proteins (y34), which were calculated by multiplication of total colonies and HR rates (blue square).

(B) Schematic illustration of a competitive mechanism of HR (RPA) and NHEJ (Ku80). For controlling DSBs formation well, an inducible gRNA plasmid targeting LSC2 gene was constructed by using a methanol-induced promoter PDAS1. The relative abundance of RPA-GFP and Ku80-RFP was detected by fluorescence intensity.

(C) Fluorescence intensities of GFP (B) and RFP (C) were measured at 24 h in strains WT, Ku80-dw, and y34. In particular, 1.7 mM methionine was added to repress the Ku80 expression in strain Ku80-dw (Ku80-dw + Met). Cells were cultivated in Delft basic salt media containing 10 g/L methanol (Induction), or 20 g/L glucose (No induction), at 37°C, 220 rpm.

(D) The relative abundance of RPA and Ku80, which was calculated by the ratio of GFP fluorescence intensities and RFP fluorescence intensities, was highly consistent with the corresponding HR rates. Data are presented as means of three biologically independent samples with displayed data points. Red asterisks indicate statistical significance as determined using paired t test (∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001).

In methanol media (for inducing DSB formation), de-regulation of KU80 (strain Ku80-dw with methionine) improved the expression of the key protein RPA (RPA-GFP), which suggested repression of Ku80 (Figure 5C). Vice versa, enhancing the expression of HR-related proteins (strain y34) repressed the expression of NHEJ-related protein Ku80 (Figure 5D). Finally, RPA/Ku80 ratio demonstrated a relative binding efficiency to DSB sites, which eventually showed the relative strength of HR or NHEJ. The RPA/Ku80 ratio in strain Ku80-dw was double that of the control strain, and strain y34 had the highest RPA/Ku80 ratio, which was in line with the HR rates (Figure 5A) and suggested that y34 had extremely strong HR activity. Meanwhile, no fluorescence signal was detected in all strains growing in glucose media, which verified that the DSBs can only be created by methanol induction (Figures 5C and 5D). In particular, we counted 50,000 cells to calculate the relative expression level of RPA via flow cytometer (Figure S7). When setting the GFP fluorescence intensity >500 as HR-positive cells (because the GFP fluorescence intensity of y34 is around 500), the positive cells of control, Ku80-dw, and y34 accounted for 28.8%, 35.1%, 59.3%, respectively, which was in agreement with Figure 5. These data suggested that, through the competition of binding sites at DSB sites, the overexpressing HR-related proteins promoted HR-based DNA repair, which in turn decreased the NHEJ strength, and down-regulation of gene KU80 increased DSB repair via the HR pathway by decreasing the NHEJ strength, which was also highly consistent with qPCR results (Figure S5).

Application of CRISPR-Cas9 toolkit in genetic engineering

We first applied this CRISPR-Cas9 toolkit for scarless deletion of OpLSC2 gene and determined the minimal homology arm (HA) lengths for efficient HR in Ku80-dw and y34 strains (Figure 6A). 1,000-bp HA resulted in similar gene deletion efficiency (60%–70%) in these two strains, which were both significantly higher than that of the wild-type strain. However, HA lengths of 200 bp and 500 bp led to a dramatic decrease in HR rates in strain Ku80-dw, which was almost in line with those in the control strain, whereas strain y34 continued to have higher HR rate (∼40%) even with 200 bp HA. These data indicated that the strain y34 overexpressing HR-related proteins was best for further precise and convenient genome editing (Figures 6B and 6C).

Figure 6.

Figure 6

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Genetic engineering with enhanced HR process and optimized CRISPR/Cas9 toolkit

(A) Schematic illustration of gene scarless deletion with HA lengths of 200, 500, and 1,000 bp, respectively.

(B) HR rates for gene deletion with various HA lengths, in strains wild-type (WT), KU80 down-regulation (Ku80-dw), and overexpression of HR-related genes (y34).

(C) CFU/OD600 for gene deletion with various HA lengths, in strains wild-type (WT), Ku80-dw, and y34.

(D) Schematic illustration of homologous integration of a large fragment (ScIDP2 cassette at OpFAA1 locus) with HA of length of 200, 500, and 1,000 bp, respectively.

(E) HR rates for ScIDP2 integration with various HA lengths in strain y34.

(F) CFU/OD600 of ScIDP2 integration with various HA lengths in strain y34.

(G) Schematic illustration of in vivo self-assembly of a plasmid with size 20 kb, with HA length 500 bp.

(H) Positive rates of plasmid assembly via 3 parts, 4 parts, and 5 parts, respectively, in strain y34.

(I) CFU/OD600 of plasmid assembly via 3 parts, 4 parts, and 5 parts, respectively, in strain y34. Total 20 colonies from each biological parallel were picked and tested by colony PCR to calculate HR rate. Data are presented as means of two (A–C) or three (D–I) biologically independent samples. Red asterisks indicate statistical significance as determined using paired t test (∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001), and no significant differences were unmarked.

We then tested the possibility of strain y34 in site-specific integration of a large fragment. An expression cassette of gene ScIDP2 (5.5 kb), harboring FAA1 targeting HA with lengths of 200 bp, 500 bp, or 1,000 bp (Figure 6D), were transformed into strain y34. 1,000-bp HA enabled sufficient integration efficiency of 40%–50%, whereas shorter HA lengths resulted in lower positive rates (20% for 500 bp, 8.3% for 200 bp, Figures 6E and 6F). It should be mentioned that LiAc/ssDNA chemical transformation led to low integration efficiency (10%–20%) (Figure S8), which suggested that high transformation efficiency was required to uptake sufficient DNA fragments for HR-mediated integration.

Extensive metabolic engineering involves the construction and optimization of long biosynthetic pathways with multiple genes, which thus relies on rapid assembly of multiple DNA fragments in plasmids or genome (Shao et al., 2008). We thus explored the possibility of in vivo assembly of a 20-kb plasmid harboring a fatty alcohol biosynthetic pathway (Figure 6G). The plasmid was divided into 3–5 parts, and the HA lengths were set as about 500 bp. Although much lower than gene deletion, the CFU/OD600 numbers were similar among assemblies of 3 parts, 4 parts, and 5 parts (Figure 6H). Furthermore, considerably positive rates (up to 20%) were obtained (Figure 6I), which provided a convenient strategy for in vivo assembly of a large plasmid with multiple genes and would be helpful for pathway optimization as it was done in S. cerevisiae (Zhou et al., 2012, 2016b).

We finally applied this genetic platform for genome integration of biosynthetic pathways with multiple genes, which is considered to be stable in cell factory construction. A previous optimized fatty alcohol biosynthetic pathway (Zhou et al., 2016b) was integrated to the POX1 site in O. polymorpha y34 (Figures S9 and 7A). There were similar numbers of CFU/OD600 in spite of a slight decrease while integrating over one cassette (Figure 7B). As expected, a sharp decline in positive rates was observed with the increased number of integrated cassettes (Figure 7C). When integrating only one cassette containing gene MmCAR, the positive rate reached 70%, which was in line with previous integration of a large fragment (Figure 6E). However, in vivo self-assembly of four expression cassettes reduced the positive rate to less than 10% (Figure 7C).

Figure 7.

Figure 7

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Genomic integration of a biosynthetic pathway for fatty alcohol production

(A) Biosynthetic pathway for fatty alcohol production. Dual deletion of HFD1 and POX1 is helpful for fatty alcohol biosynthesis in O. polymorpha. Overexpression of carboxylic acid reductase from Mycobacterium marinum (MmCAR) and its co-factor npgA, alcohol dehydrogenase from S. cerevisiae (ADH5), and fatty acyl-CoA reductase (FaCoAR) from Marinobacter aquaeolei VT8 (Zhou et al., 2016a, 2016b), was supposed to achieve the production of fatty alcohol. In vivo pathway assembly for fatty alcohol production was carried out by integrating multiple expression cassettes.

(B and C) The CFU/OD600 (B) and positive rate (C) were both calculated with integration of different numbers of genes.

(D) The engineered strains were cultivated in basic salt media that containing 20 g/L glucose.

(E) Disrupted gene FAA1 further increased fatty alcohol production from glucose in basic salt media.

(F) Fatty alcohol production from methanol in basic salt media or YP media; 5 g/L methanol was supplemented at 24 and 48 h. Cells were cultured for 96 h, at 37°C, 220 rpm. Total 20 colonies from each biological parallel were picked and tested by colony PCR to calculate HR rate. Data are presented as mean of two (B and C), or three (D–F) biologically independent samples.

HFD1 gene in the aforementioned correct transformants with specific genes for fatty alcohol production were further disrupted, which was very essential for the production of fatty aldehyde-derived chemicals (Zhou et al., 2016b). Cassette integration had a marginal effect on cell growth (Figure S10A). Genome integration of fatty acid reductase gene MmCAR and its cofactor gene npgA enabled fatty alcohol biosynthesis in O. polymorpha. FacoAR, encoding fatty acyl-CoA reductase, was also beneficial for fatty alcohol biosynthesis (Figure 7D), which was consistent with that in S. cerevisiae (Zhou et al., 2016a, 2016b). It was interesting that the overexpression of S. cerevisiae ADH5 gene encoding alcohol dehydrogenase resulted in a 2.5-fold higher fatty alcohol production (strain C1-2-1 versus C1-3-12 in Figure 7D), which suggested that the alcohol dehydrogenase or aldehyde reductase were not comparable with the alcohol fermentation yeast S. cerevisiae and need to be enhanced for fatty alcohol production. To enhance the precursor fatty acid supply, gene FAA1 was disrupted, which eventually resulted in a dramatic increase in fatty alcohol titer to around 12 mg/L (Figure 7E). Finally, we showed that this strain C1-3 could produce 0.62 ± 0.01 mg/L and 3.26 ± 0.51 mg/L fatty alcohols from methanol when cultivated in basic salt and rich media, respectively (Figure 7F). Hence, the production of fatty acid-derived chemicals from methanol (Figure S10) showed the great potential of O. polymorpha as a chassis for methanol-based bio-refinery.

Discussion

Engineering methylotrophic microbes for methanol biotransformation provides a great opportunity in expanding the bio-manufacturing blueprint other than biomass-derived bio-refinery (Duan and Gao, 2018; Zhou et al., 2018). O. polymorpha is such a eukaryotic microbe that has been recognized as an attractive host for protein expression and ethanol fermentation due to its thermotolerance and methanol assimilation (Manfrão-Netto et al., 2019; Olson et al., 2015). However, the lack of genetic tools, especially the low HR activity, makes it challenging in expanding its product portfolio other than proteins and ethanol by engineering cellular metabolism. Here we thus established an efficient genetic platform in O. polymorpha by optimizing the CRISPR-Cas9 system and recombination machinery engineering (rME). We demonstrated the possible regulation of HR activity and NHEJ strength in this yeast, and the precise genome editing in the engineered strain may further promote its application as a cell factory for the biosynthesis of valuable products from methanol.

Our CRISPR-Cas9 system, composed of an integrated Cas9 protein and the optimized episomal gRNA expression vector, enabled the highest genome editing efficiency in O. polymorpha so far (Juergens et al., 2018; Numamoto et al., 2017; Wang et al., 2018). This system showed good convenience and time-saving pattern for extensive metabolic engineering due to the adoption of RNA pol II promoter with the aid of ribozyme and constant N6 sequence. Besides, we found that functional gRNA expression is very essential for guiding Cas9 toward targeting sites. In spite of the extensive adoption in S. cerevisiae and many other non-conventional yeasts (Cao et al., 2017; Horwitz et al., 2015; Mitsui et al., 2019; Nambu-Nishida et al., 2017; Schwartz et al., 2015) (Table 1), RNA pol III promoter failed to drive efficient gRNA expression, or no suitable RNA pol III promoter has been identified in O. polymorpha so far.

Table 1.

Genome editing by CRISPR-Cas9 in industrially important yeasts

Host Cas9
 sgRNA
 Editing rates HR
 Minimal HA Reference
Promoter Type Promoter Type Deletion Integration Marker needed
S. cerevisiae S. pyogenes Cas9 RNA pol III promoter Nearly 100% No 50 bp (Mitsui et al., 2019)
Scheffersomyces stipitis PENO1 Episomal PSNR52 Episomal 83%–100% – - (Cao et al., 2017)
K. phaffii PHTA1 Episomal PHTB1 Episomal 43%–95% 2.4% 24% Yes 1,000 bp (Weninger et al., 2016)
K. lactis PFBA1 Integrated PSNR52 Episomal – – 41%–55% No 500 bp (Horwitz et al., 2015)
Kluyveromyces marxianus PScPDC1 Episomal PScSNR52 Episomal – – 28% No 50 bp (Nambu-Nishida et al., 2017)
Yarrowia lipolytica PUAS1B8-TEF1 Episomal PSCR1’-tRNAGly Episomal c54%/92% – 16%–73% No/Yes 1,000 bp (Schwartz et al., 2015)
Ogataea. thermomethanolica PAOX1 Episomal PAOX1 Episomal 63%–97% – (Phithakrotchanakoon et al., 2018)
O. parapolymorpha PAaTEF1 Episomal PScTDH3 Episomal a0%/63% b0%/<1% – No 500 bp (Juergens et al., 2018)
O. polymorpha POpTDH3 Episomal POpSNR6-tRNACUG Episomal 17%–71% 47% – Yes 60 bp (Numamoto et al., 2017)
O. polymorpha PAaTEF1 Episomal PScTDH3 Episomal a0%/9% – – – – (Juergens et al., 2018)
O. polymorpha PScTEF1 Integrated PScSNR52 Integrated – 58%–65% 62%–66% Yes 500 bp (Wang et al., 2018)
O. polymorpha PKpGAP Integrated PTEF1 Episomal 90%–95% 60%–70% 40%–70% No 200 bp This study
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a

Upon transformation, none of the transformants exhibited mutated genotype; higher editing rate needed further 192 h of incubation in selective medium.

b

No transformants showed repair pattern via HR in wild-type, and KU80 disruption resulted in 7 of 1,900 transformants with a scarless gene deletion in O. parapolymorpha DL-1.

c

Editing rates were calculated after 2 and 4 days of outgrowth in selective liquid media.

Predictable and controllable genetic engineering is very essential for extensive metabolic rewiring in the construction of robust cell factories (Chen et al., 2020). Indeed, the high HR rate in S. cerevisiae is considered to be one of the main advantages as a preferred host for producing a variety of chemicals, because short homology arms are sufficient to bring nearly 100% targeted repair (Mitsui et al., 2019). However, the relatively high NHEJ always in non-conventional yeasts such as O. polymorpha retards the precise genetic manipulation as it repairs DSB in an unpredictable manner (Saraya et al., 2012). Thus we tried to enhance the HR rate with several strategies (Figure 1). Although coordination of Cas9 expression with the high HR activity cell phase (Gutschner et al., 2016; Yang et al., 2016) enabled doubling of HR-mediated genome editing as reported in other studies (Gutschner et al., 2016), the difficulty in controlling cell cycles led to the instability of HR rate. Alternatively, overexpression of HR-related proteins in strain y34 significantly promoted HR-mediated DNA repair process, and well-balanced HR rate, CFU number per OD600, and cell growth owing to a moderate expression level. These lessons told us that an appropriate level and even an induced, or dynamically regulated, system could be optimized for further enhancing the HR efficiency. Some similar results were also observed in mammalian cells with the overexpression of RAD51, RAD 52, or CtIP (Arjun et al., 2010; Charpentier et al., 2018; Di et al., 2005; Jayathilaka et al., 2008; Johnson et al., 1996; Shao et al., 2017; Vispé et al., 1998; Yáñez and Porter, 1999), which again proved that enhancing the expression of HR-related proteins effectively promoted HR-mediated DNA repair.

As it might compete with HR, we thus tried to repress the NHEJ by down-regulating the relating Ku heterodimer protein Ku80. As described in previous reports (Juergens et al., 2018; Kretzschmar et al., 2013), deletion of KU80 gene retarded cell growth and decreased CFU/OD600. Here, we first demonstrated a dynamically repressed CRISPR-Cas9 system in O. polymorpha with a methionine-repressed promoter POpMET3, which guaranteed the highest positive clones without retarding cell growth. This system might be extended as a general strategy in non-conventional yeasts (Schwartz et al., 2017). Interestingly, combining the overexpression of HR-related protein with the KU80 repression did not further improve the HR rate, suggesting that HR and NHEJ behaved competitively in the DSB repair process. This phenomenon could be roughly explained as the competition of binding site between HR proteins and Ku heterodimer proteins. Although down-regulation of KU80 (strain Ku80-dw) significantly improved HR efficiency, strain y34 with overexpressing HR-relating genes had better and stable performance when using shorter HA lengths and conducting complex genetic manipulation such as integration of large and multiple fragments.

This O. polymorpha optimized CRISPR-Cas9 system with enhanced HR rate significantly facilitated metabolic engineering to clearly realize the scareless gene deletion, genome integration of large fragment even with a short HA of 200 bp, and in vivo assembly of episomal plasmid with a large size up to 20 kb. Besides, we provide a feasible approach for the construction of genetically stable O. polymorpha for industrial process by genome integration of up to four gene expression cassettes, and the production of fatty acid-derived chemicals in O. polymorpha from both glucose and methanol were also achieved. Despite a lower titer (Cordova et al., 2020; D'Espaux et al., 2017; Liu et al., 2020; Mcneil and Stuart, 2017), we can expect that further engineering the fatty acid metabolism and methanol utilization would enhance fatty alcohol production as it has been done in S. cerevisiae.

Limitations of the study

In this study, the recombination machinery has been systematically engineered to establish an efficient and convenient CRISPR-Cas9 system with an enhanced HR rate in O. polymorpha. Yet, an inducible and dynamic system should be constructed to avoid any unpredictable growth defect in more harsh conditions. In particular, more strictly repressed promoter needs further investigation to down-regulate gene KU80. Moreover, an explicit mechanism on the competition of HR and NHEJ remains elusive for a comprehensive regulation in further applications. Finally, a fine regulation must be performed to significantly increase fatty alcohol production from both glucose and methanol.

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Yongjin J. Zhou (zhouyongjin@dicp.ac.cn).

Materials availability

gRNA plasmids (pHpgRNA13 and pHpgRNA50) generated in this study have been deposited to Addgene (Yongjin Zhou, 78587). Other materials generated in this study are available upon request from the Lead Contact with a completed Materials Transfer Agreement.

Data and code availability

The published article includes all datasets generated or analyzed during this study.

Methods

All methods can be found in the accompanying Transparent Methods supplemental file.

Acknowledgments

The work was financial supported by National Natural Science Foundation of China (21808216 and 21922812), Dalian Science and Technology Innovation Funding (2019J12GX030), DMTO research grant (grant no. DICP DMTO201701), and BioChE research grant (grant no. DICP BioChE-X201801) from Dalian Institute of Chemicals Physics (DICP), CAS. The authors thank the Energy Biotechnology Platform of DICP for providing facility assistance.

Author contributions

J.G. designed the research, performed most of the experiments, collected data, and prepared the manuscript. N.G. carried out partial transformation experiments and conducted analysis. X.Z. conducted the fermentation experiments for fatty alcohol production. Y.J.Z. conceived the concept, designed the experiment, and drafted the manuscript.

Declaration of interests

This work has been included in patent applications in Chinese (202010628649.3 and 202010626783.X) by Dalian Institute of Chemical Physics, CAS.

Published: March 19, 2021

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2021.102168.

Supplemental information

Document S1. Transparent methods, Figures S1–S10, and Tables S1–S3 and S5–S9
mmc1.pdf (3.6MB, pdf)
Table S4. Primers used in this study, related to Figures 2–7
mmc2.xlsx (19.9KB, xlsx)

References

  1. Aird E.J., Lovendahl K.N., Martin A.S., Harris R.S., Gordon W.R. Increasing Cas9-mediated homology-directed repair efficiency through covalent tethering of DNA repair template. Commun. Biol. 2018;1:54. doi: 10.1038/s42003-018-0054-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Arjun K., Giuseppe R., Di P.C., Vania L., Arturo F., Alvaro G. Enhancement of gene targeting in human cells by intranuclear permeation of the Saccharomyces cerevisiae Rad52 protein. Nucleic Acids Res. 2010;38:e149. doi: 10.1093/nar/gkq486. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Cai P., Gao J., Zhou Y. CRISPR-mediated genome editing in non-conventional yeasts for biotechnological applications. Microb. Cell Fact. 2019;18:63. doi: 10.1186/s12934-019-1112-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Cao M., Gao M., Lopez-Garcia C.L., Wu Y., Seetharam A.S., Severin A.J., Shao Z. Centromeric DNA facilitates nonconventional yeast genetic engineering. ACS Synth. Biol. 2017;6:1545. doi: 10.1021/acssynbio.7b00046. [DOI] [PubMed] [Google Scholar]
  5. Ceccaldi R., Rondinelli B., D’Andrea A.D. Repair pathway choices and consequences at the double-strand break. Trends Cell Biol. 2016;26:52–64. doi: 10.1016/j.tcb.2015.07.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chang H.H., Pannunzio N.R., Adachi N., Lieber M.R. Non-homologous DNA end joining and alternative pathways to double-strand break repair. Nat. Rev. Mol. Cell Bio. 2017;18:495. doi: 10.1038/nrm.2017.48. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Charpentier M., Khedher A., Menoret S., Brion A., Lamribet K., Dardillac E., Boix C., Perrouault L., Tesson L., Geny S. CtIP fusion to Cas9 enhances transgene integration by homology-dependent repair. Nat. Commun. 2018;9:1133. doi: 10.1038/s41467-018-03475-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chen R., Yang S., Zhang L., Zhou Y.J. Advanced strategies for production of natural products in yeast. iScience. 2020;23:100879. doi: 10.1016/j.isci.2020.100879. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Clomburg J.M., Crumbley A.M., Gonzalez R. Industrial biomanufacturing: the future of chemical production. Science. 2017;355:aag0804. doi: 10.1126/science.aag0804. [DOI] [PubMed] [Google Scholar]
  10. Cohen-Fix O., Peters J.-M., Kirschner M.W., Koshland D. Anaphase initiation in Saccharomyces cerevisiae is controlled by the APC-dependent degradation of the anaphase inhibitor Pds1p. Gene Dev. 1996;10:3081–3093. doi: 10.1101/gad.10.24.3081. [DOI] [PubMed] [Google Scholar]
  11. Cordova L.T., Butler J., Alper H.S. Direct production of fatty alcohols from glucose using engineered strains of Yarrowia lipolytica. Metab. Eng. Comm. 2020;10:e00105. doi: 10.1016/j.mec.2019.e00105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. D’Espaux L., Ghosh A., Runguphan W., Wehrs M., Xu F., Konzock O., Dev I., Nhan M., Gin J., Reider Apel A. Engineering high-level production of fatty alcohols by Saccharomyces cerevisiae from lignocellulosic feedstocks. Metab. Eng. 2017;42:115–125. doi: 10.1016/j.ymben.2017.06.004. [DOI] [PubMed] [Google Scholar]
  13. Di P.C., Alvaro G., Tiziana C., Monica Z., Giuseppe R. Potentiation of gene targeting in human cells by expression of Saccharomyces cerevisiae Rad52. Nucleic Acids Res. 2005;33:4639–4648. doi: 10.1093/nar/gki778. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Duan X., Gao J., Y.J. Z. Advances in engineering methylotrophic yeast for biosynthesis of valuable chemicals from methanol. Chin. Chem. Lett. 2018;29:681–686. [Google Scholar]
  15. Gutschner T., Haemmerle M., Genovese G., Draetta G.F., Chin L. Post-translational regulation of Cas9 during G1 enhances homology-directed repair. Cell Rep. 2016;14:1555–1566. doi: 10.1016/j.celrep.2016.01.019. [DOI] [PubMed] [Google Scholar]
  16. Heyer W.-D., Ehmsen K.T., Liu J. Regulation of homologous recombination in eukaryotes. Annu. Rev. Genet. 2010;44:113–139. doi: 10.1146/annurev-genet-051710-150955. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Horwitz A.A., Walter J.M., Schubert M.G., Kung S.H., Hawkins K., Platt D.M., Hernday A.D., Mahatdejkul-Meadows T., Szeto W., Chandran S.S. Efficient multiplexed integration of synergistic alleles and metabolic pathways in yeasts via CRISPR-Cas. Cell Syst. 2015;1:88. doi: 10.1016/j.cels.2015.02.001. [DOI] [PubMed] [Google Scholar]
  18. Jayathilaka K., Sheridan S.D., Bold T.D., Bochenska K., Logan H.L., Weichselbaum R.R., Bishop D.K., Connell P.P. A chemical compound that stimulates the human homologous recombination protein RAD51. Proc. Natl. Acad. Sci. U S A. 2008;105:15848–15853. doi: 10.1073/pnas.0808046105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Johnson B.L., Thyagarajan B., Krueger L., Hirsch B., Campbell C. Elevated levels of recombinational DNA repair in human somatic cells expressing the Saccharomyces cerevisiae RAD52 gene. Mutat. Res./DNA Repair. 1996;363:179–189. doi: 10.1016/0921-8777(96)00007-9. [DOI] [PubMed] [Google Scholar]
  20. Juergens H., Varela J.A., Gorter de Vries A.R., Perli T., Gast V.J., Gyurchev N.Y., Rajkumar A.S., Mans R., Pronk J.T., Morrissey J.P. Genome editing in Kluyveromyces and Ogataea yeasts using a broad-host-range Cas9/gRNA co-expression plasmid. FEMS Yeast Res. 2018;18:foy012. doi: 10.1093/femsyr/foy012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Krejci L., Altmannova V., Spirek M., Zhao X. Homologous recombination and its regulation. Nucleic Acids Res. 2012;40:5795–5818. doi: 10.1093/nar/gks270. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kretzschmar A., Otto C., Holz M., Werner S., Hübner L., Barth G. Increased homologous integration frequency in Yarrowia lipolytica strains defective in non-homologous end-joining. Curr. Genet. 2013;59:63–72. doi: 10.1007/s00294-013-0389-7. [DOI] [PubMed] [Google Scholar]
  23. Liachko I., Dunham M.J. An autonomously replicating sequence for use in a wide range of budding yeasts. FEMS Yeast Res. 2014;14:364–367. doi: 10.1111/1567-1364.12123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Liu D., Geiselman G.M., Coradetti S., Cheng Y., Gladden J. Exploiting nonionic surfactants to enhance fatty alcohol production in Rhodosporidium toruloides. Biotechnol. Bioeng. 2020;117:1418–1425. doi: 10.1002/bit.27285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Manfrão-Netto J.H., Gomes A.M., Parachin N.S. Advances in using Hansenula polymorpha as chassis for recombinant protein production. Front. Bioeng. Biotech. 2019;7:94. doi: 10.3389/fbioe.2019.00094. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. McGinn J., Marraffini L.A. Molecular mechanisms of CRISPR-Cas spacer acquisition. Nat. Rev. Microbiol. 2018;17:7. doi: 10.1038/s41579-018-0071-7. [DOI] [PubMed] [Google Scholar]
  27. Mcneil B.A., Stuart D.T. Optimization of C16 and C18 fatty alcohol production by an engineered strain of Lipomyces starkeyi. J. Ind. Microbiol. Biotechnol. 2017;45:1–14. doi: 10.1007/s10295-017-1985-1. [DOI] [PubMed] [Google Scholar]
  28. Mimitou E.P., Symington L.S. Sae2, Exo1 and Sgs1 collaborate in DNA double-strand break processing. Nature. 2008;455:770. doi: 10.1038/nature07312. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Mitsui R., Yamada R., Ogino H. CRISPR system in the yeast Saccharomyces cerevisiae and its application in the bioproduction of useful chemicals. World J. Microbiol. Biotechnol. 2019;35:111. doi: 10.1007/s11274-019-2688-8. [DOI] [PubMed] [Google Scholar]
  30. Nambu-Nishida Y., Nishida K., Hasunuma T., Kondo A. Development of a comprehensive set of tools for genome engineering in a cold-and thermo-tolerant Kluyveromyces marxianus yeast strain. Sci. Rep. 2017;7:1–8. doi: 10.1038/s41598-017-08356-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Numamoto M., Maekawa H., Kaneko Y. Efficient genome editing by CRISPR/Cas9 with a tRNA-sgRNA fusion in the methylotrophic yeast Ogataea polymorpha. J. Biosci. Bioeng. 2017;124:487–492. doi: 10.1016/j.jbiosc.2017.06.001. [DOI] [PubMed] [Google Scholar]
  32. O'Driscoll M., Jeggo P.A. The role of double-strand break repair-insights from human genetics. Nat. Rev. Genet. 2006;7:45–54. doi: 10.1038/nrg1746. [DOI] [PubMed] [Google Scholar]
  33. Olson D.G., Sparling R., Lynd L.R. Ethanol production by engineered thermophiles. Curr. Opin. Biotechnol. 2015;33:130–141. doi: 10.1016/j.copbio.2015.02.006. [DOI] [PubMed] [Google Scholar]
  34. Phithakrotchanakoon C., Puseenam A., Wongwisansri S., Eurwilaichitr L., Ingsriswang S., Tanapongpipat S., Roonsawang N. CRISPR-Cas9 enabled targeted mutagenesis in the thermotolerant methylotrophic yeast Ogataea thermomethanolica. FEMS Microbiol. Lett. 2018;365:fny105. doi: 10.1093/femsle/fny105. [DOI] [PubMed] [Google Scholar]
  35. Raschmanova H., Weninger A., Glieder A., Kovar K., Vogl T. Implementing CRISPR-Cas technologies in conventional and non-conventional yeasts: current state and future prospects. Biotechnol. Adv. 2018;36:641–665. doi: 10.1016/j.biotechadv.2018.01.006. [DOI] [PubMed] [Google Scholar]
  36. Saraya R., Krikken A.M., Kiel J.A., Baerends R.J., Veenhuis M., van der Klei I.J. Novel genetic tools for Hansenula polymorpha. FEMS Yeast Res. 2012;12:271–278. doi: 10.1111/j.1567-1364.2011.00772.x. [DOI] [PubMed] [Google Scholar]
  37. Schwartz C., Frogue K., Ramesh A., Misa J., Wheeldon I. CRISPRi repression of nonhomologous end-joining for enhanced genome engineering via homologous recombination in Yarrowia lipolytica. Biotechnol. Bioeng. 2017;114:2896–2906. doi: 10.1002/bit.26404. [DOI] [PubMed] [Google Scholar]
  38. Schwartz C., Wheeldon I. Genome and metabolic engineering in non-conventional yeasts: current advances and applications. Synth. Syst. Biotechnol. 2017;2:198–207. doi: 10.1016/j.synbio.2017.08.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Schwartz C.M., Hussain M.S., Blenner M., Wheeldon I. Synthetic RNA polymerase III promoters facilitate high-efficiency CRISPR-Cas9-mediated genome editing in Yarrowia lipolytica. ACS Synth. Biol. 2015;5:356. doi: 10.1021/acssynbio.5b00162. [DOI] [PubMed] [Google Scholar]
  40. Shao S., Ren C., Liu Z., Bai Y., Chen Z., Wei Z., Wang X., Zhang Z., Xu K. Enhancing CRISPR/Cas9-mediated homology-directed repair in mammalian cells by expressing Saccharomyces cerevisiae Rad52. Int. J. Biochemi. Cell Biol. 2017;92:43–52. doi: 10.1016/j.biocel.2017.09.012. [DOI] [PubMed] [Google Scholar]
  41. Shao Z., Zhao H., Zhao H. DNA assembler, an in vivo genetic method for rapid construction of biochemical pathways. Nucleic Acids Res. 2008;37:e16. doi: 10.1093/nar/gkn991. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Ubiyvovk V.M., Ananin V.M., Malyshev A.Y., Kang H.A., Sibirny A.A. Optimization of glutathione production in batch and fed-batch cultures by the wild-type and recombinant strains of the methylotrophic yeast Hansenula polymorpha DL-1. BMC Biotechnol. 2011;11:8. doi: 10.1186/1472-6750-11-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Vispé S., Cazaux C., Lesca C., Defais M. Overexpression of Rad51 protein stimulates homologous recombination and increases resistance of mammalian cells to ionizing radiation. Nucleic Acids Res. 1998;26:2859–2864. doi: 10.1093/nar/26.12.2859. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Voronovsky A.Y., Rohulya O.V., Abbas C.A., Sibirny A.A. Development of strains of the thermotolerant yeast Hansenula polymorpha capable of alcoholic fermentation of starch and xylan. Metab. Eng. 2009;11:234–242. doi: 10.1016/j.ymben.2009.04.001. [DOI] [PubMed] [Google Scholar]
  45. Wang L., Deng A., Zhang Y., Liu S., Liang Y., Bai H., Cui D., Qiu Q., Shang X., Yang Z. Efficient CRISPR–Cas9 mediated multiplex genome editing in yeasts. Biotechnol. Biofuels. 2018;11:277. doi: 10.1186/s13068-018-1271-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Weninger A., Fischer J.E., Raschmanová H., Kniely C., Vogl T., Glieder A. Expanding the CRISPR/Cas9 toolkit for Pichia pastoris with efficient donor integration and alternative resistance markers. J. Cell. Biochem. 2018;119:3183–3198. doi: 10.1002/jcb.26474. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Weninger A., Hatzl A.-M., Schmid C., Vogl T., Glieder A. Combinatorial optimization of CRISPR/Cas9 expression enables precision genome engineering in the methylotrophic yeast Pichia pastoris. J. Biotechnol. 2016;235:139–149. doi: 10.1016/j.jbiotec.2016.03.027. [DOI] [PubMed] [Google Scholar]
  48. Yáñez R.J., Porter A.C.G. Gene targeting is enhanced in human cells overexpressing hRAD51. Gene Ther. 1999;6:1282–1290. doi: 10.1038/sj.gt.3300945. [DOI] [PubMed] [Google Scholar]
  49. Yang D., Scavuzzo M.A., Chmielowiec J., Sharp R., Bajic A., Borowiak M. Enrichment of G2/M cell cycle phase in human pluripotent stem cells enhances HDR-mediated gene repair with customizable endonucleases. Sci. Rep. 2016;6:21264. doi: 10.1038/srep21264. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Yoo S.J., Chung S.Y., Lee D.-j., Kim H., Cheon S.A., Kang H.A. Use of the cysteine-repressible HpMET3 promoter as a novel tool to regulate gene expression in Hansenula polymorpha. Biotechnol. Lett. 2015;37:2237–2245. doi: 10.1007/s10529-015-1902-5. [DOI] [PubMed] [Google Scholar]
  51. Yu T., Zhou Y.J., Huang M., Liu Q., Pereira R., David F., Nielsen J. Reprogramming yeast metabolism from alcoholic fermentation to lipogenesis. Cell. 2018;174:1549–1558. doi: 10.1016/j.cell.2018.07.013. [DOI] [PubMed] [Google Scholar]
  52. Zhou Y.J., Buijs N.A., Zhu Z., Gómez D.O., Boonsombuti A., Siewers V., Nielsen J. Harnessing yeast peroxisomes for biosynthesis of fatty-acid-derived biofuels and chemicals with relieved side-pathway competition. J. Am. Chem. Soc. 2016;138:15368–15377. doi: 10.1021/jacs.6b07394. [DOI] [PubMed] [Google Scholar]
  53. Zhou Y.J., Buijs N.A., Zhu Z., Qin J., Siewers V., Nielsen J. Production of fatty acid-derived oleochemicals and biofuels by synthetic yeast cell factories. Nat. Commun. 2016;7:11709. doi: 10.1038/ncomms11709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Zhou Y.J., Gao W., Rong Q., Jin G., Chu H., Liu W., Yang W., Zhu Z., Li G., Zhu G. Modular pathway engineering of diterpenoid synthases and the mevalonic acid pathway for miltiradiene production. J. Am. Chem. Soc. 2012;134:3234–3241. doi: 10.1021/ja2114486. [DOI] [PubMed] [Google Scholar]
  55. Zhou Y.J., Kerkhoven E.J., Nielsen J. Barriers and opportunities in bio-based production of hydrocarbons. Nat. Energy. 2018;3:925–935. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Transparent methods, Figures S1–S10, and Tables S1–S3 and S5–S9
mmc1.pdf (3.6MB, pdf)
Table S4. Primers used in this study, related to Figures 2–7
mmc2.xlsx (19.9KB, xlsx)

Data Availability Statement

The published article includes all datasets generated or analyzed during this study.

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