Functionally Verified Parts for Heterologous ... - ACS Publications

Research Article pubs.acs.org/synthbio

A Toolbox of Diverse Promoters Related to Methanol Utilization: Functionally Verified Parts for Heterologous Pathway Expression in Pichia pastoris Thomas Vogl,†,∥,⊥ Lukas Sturmberger,†,⊥ Thomas Kickenweiz,†,⊥ Richard Wasmayer,† Christian Schmid,† Anna-Maria Hatzl,† Michaela A. Gerstmann,† Julia Pitzer,† Marlies Wagner,‡ Gerhard G. Thallinger,†,§ Martina Geier,‡ and Anton Glieder*,†,‡ †

Institute of Molecular Biotechnology, NAWI Graz, Graz University of Technology, Petersgasse 14, Graz 8010, Austria Austrian Centre of Industrial Biotechnology (ACIB GmbH), Petersgasse 14, Graz 8010, Austria § Omics Center Graz, Stiftingtalstrasse 24, 8036 Graz, Austria ‡

S Supporting Information *

ABSTRACT: The heterologous expression of biosynthetic pathways for pharmaceutical or fine chemical production requires suitable expression hosts and vectors. In eukaryotes, the pathway flux is typically balanced by stoichiometric finetuning of reaction steps by varying the transcript levels of the genes involved. Regulated (inducible) promoters are desirable to allow a separation of pathway expression from cell growth. Ideally, the promoter sequences used should not be identical to avoid loss by recombination. The methylotrophic yeast Pichia pastoris is a commonly used protein production host, and single genes have been expressed at high levels using the methanol-inducible, strong, and tightly regulated promoter of the alcohol oxidase 1 gene (PAOX1). Here, we have studied the regulation of the P. pastoris methanol utilization (MUT) pathway to identify a useful set of promoters that (i) allow high coexpression and (ii) differ in DNA sequence to increase genetic stability. We noticed a pronounced involvement of the pentose phosphate pathway (PPP) and genes involved in the defense of reactive oxygen species (ROS), providing strong promoters that, in part, even outperform PAOX1 and offer novel regulatory profiles. We have applied these tightly regulated promoters together with novel terminators as useful tools for the expression of a heterologous biosynthetic pathway. With the synthetic biology toolbox presented here, P. pastoris is now equipped with one of the largest sets of strong and co-regulated promoters of any microbe, moving it from a protein production host to a general industrial biotechnology host. KEYWORDS: heterologous pathway expression, transcriptional fine-tuning, Pichia pastoris, promoters, transcriptional terminators, toolbox of modular parts

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for metabolic engineering should provide tight regulation by induction to enable a separation of cell growth from pathway expression and to avoid a constant additional metabolic burden.5 Promoters covering a wide range of expression levels should be at hand to enable expression fine-tuning, ranging from tight downregulation to high overexpression. To this end, either natural or synthetic promoters can be used. Synthetic promoters typically provide a wider range of expression levels (10−1000-fold) and finer increments.5 Commonly, promoter libraries are obtained from modifying a single natural sequence, and the final variants differ only slightly between their sequences (e.g., refs 6 and 7).

etabolic and biosynthetic pathways have been engineered and exploited for biofuel, pharmaceutical, or fine chemical production and are commonly heterologously expressed in microbial host organisms. However, simple coexpression of the genes of a pathway is seldom sufficient to achieve high yields and productivity, typically requiring an optimization of the flux toward the desired product and the removal of kinetic bottlenecks.1,2 Likewise, intricate synthetic biology applications commonly require the coordinated, balanced coexpression of multiple genes.3,4 Natural regulation of pathways and multigene coexpression is exerted at different levels ranging from transcription and translation to the protein level including feedback regulation by metabolites.5 For recombinant protein expression in eukaryotes, transcript levels are most commonly varied by employing different promoters since equivalents of ribosome binding sites are less well-defined compared to bacteria. Ideally, promoters © 2015 American Chemical Society

Received: October 11, 2015 Published: November 22, 2015 172

DOI: 10.1021/acssynbio.5b00199 ACS Synth. Biol. 2016, 5, 172−186

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Figure 1. Canonical and noncanonical parts of the P. pastoris methanol utilization pathway. The canonical MUT pathway is based on the most recent annotation43 and physiological studies.26 The part on ROS defense is based on ref 52. PPP is here shown as being associated with the assimilative branch of the MUT pathway; the oxidative (for NADPH regeneration) and nonoxidative phase are highlighted. Enzymes are named according to the names of the respective gene products (see Table S2 for the enzymatic functions). Peroxisomal membrane proteins Pex5, Pex8, and Pex14 involved in peroxisome biogenesis and peroxisomal signal sequence recognition and relevant reactions of glycolysis (catalyzed by Pfk1p, Gpi1p) are also shown. Alternative steps of the dissimilative MUT pathway (methylformate formation [putatively by ADH2] and demethylation thereof by a yet unknown enzyme), as annotated by Küberl et al.,43 are not shown. Abbreviations of metabolites: DHA, dihydroxyacetone; DHAP, dihydroxyacetone phosphate; ET4P, erythrose 4-phosphate; FRU1,6P, fructose-1,6-bisphosphate; FRU6P, fructose-6-phosphate; GAP, glyceraldehyde-3-phosphate; GLC1P, glucose-1-phosphate; GLC6P, glucose-6-phosphate; GSH, glutathione; GSSG, oxidized glutathione self-dimer; MetO, methionine sulfoxide; 6PGL, 6-phosphogluconolactone; 6PGT, 6-phosphogluconate; Pi, inorganic phosphate; PYR, pyruvate; RO5P, ribose 5-phosphate; RU5P, ribulose 5phosphate; SH7P, sedoheptulose 7-phosphate; TCA, tricarboxylic acid cycle; Xu5P, xylulose 5-phosphate. Legend: R′ in chemical formulas denotes a hydrogen, aliphatic, or aromatic organic group; a, nonribosomal peptide synthesis; b, issues with annotation (see Supporting Information S9); c, Tkl1p has also been assigned putative dihydroxyacetone synthase activity;26,43 d, transketolase activity is required for both the reaction of Xu5P + RI5P → SH7P + GAP and ET5P + Xu5P → F6P + GAP. *, The reaction of CH2O and GSH is occurring nonenzymatically.

Fine-tuning the expression of a multiple genes using such libraries is troubled by the high identities of the sequences, leading to inter-promoter recombination:8 On one hand, highly similar sequences complicate the in vitro DNA assembly of pathways when using overlap-directed DNA assembly methods such as Gibson assembly,9 as identical sequences can misalign. On the other hand, similar sequences may lead to homologous recombination in vivo and loss of parts of the expression cassettes (by loop-out recombination; ref 10 and references therein). The same issues also arise for terminators; ideally, a set of strong terminators with distinct sequences should be available.11,12 Concerning host platforms for metabolic engineering and synthetic biology, Escherichia coli and Saccharomyces cerevisiae are most commonly used.13 Due its long period of use as a basic eukaryotic model organism and the large amount of fundamental knowledge of it, the classic yeast S. cerevisiae is the standard platform, especially for eukaryotic pathways.14−16 However, S. cerevisiae also provides a limited set of tightly coregulated promoters; typically, only a few galactose (PGAL1, PGAL3, PGAL7, PGAL10) and copper (PCTR1, PCTR3, PCUP1) regulated promoters are used.15,17

Recently, alternative, nonconventional yeasts have also attracted considerable attention, having been successfully applied for various metabolic engineering endeavors.18 The methylotrophic yeast Pichia pastoris is one of the most commonly used expression hosts for heterologous protein production due to its beneficial traits, such as growth to exceptionally high cell densities (>150 g dry cell weight per liter19) and high yields of recombinant proteins. A recent literature survey on recombinant gene expression suggests that P. pastoris is applied even more frequently for single protein production than S. cerevisiae.20 Lately, P. pastoris has also been used for an increasing number of synthetic biology21 and metabolic engineering applications22−30 supported by the d evelo pm en t o f g en om e-sc ale met abolic mo dels (GSMMs).31−33 Recently, metabolic models have been revised on an improved annotation of the P. pastoris proteome.34 Yet, fundamental knowledge of P. pastoris is relatively limited compared to that for S. cerevisiae, and fewer molecular tools, such as promoters, terminators, or knockout strains, are available for it.35 In P. pastoris and related methylotrophic yeasts (for example, Hansenula polymorpha, Candida boidinii, Pichia methanolica), methanol-inducible promoters are typically used to drive 173


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Figure 2. Genome-wide transcriptional response of P. pastoris toward growth on different carbon sources. (A) P. pastoris bioreactor cultivations and sampling points used for the microarray analyses. Growth curves for the same strain in biological duplicates are shown; standard deviations are technical replicates of the OD measurements. Glucose depletion (equaling the end of the exponential phase) was determined by the oxygen peak and confirmed by glucose measurements. Glucose readdition was performed 1 h after methanol was depleted (31 h), and samples were taken at the time points indicated. Abbreviations of sampling points for microarrays: G, glucose; D, derepression; M, methanol; GR, glucose readdition. (B) Comparison of the transcriptional response under all tested growth conditions. In the lower left corner, the number of downregulated (DN), not regulated (NR), and upregulated (UP) genes is given (p < 0.01) [total number of probe sets, 5869]. In the upper right corner, deregulated (DN or UP) genes are listed by different fold change (FC) criteria [M1.0, 1.5, and 2.0 denote the respective log2 values]. (C) Comparative analysis of differential gene expression between growth under derepressed, methanol-induced, and glucose readdition conditions. These three conditions were each first normalized to growth on glucose. The number of unique and overlapping genes showing up-, down-, and deregulation is given (FC > log2(1.0), p < 0.05; the same criteria and normalization were applied for the analyses shown in panel D). (D) Functional grouping of differentially regulated genes to biologic processes by COG terms.56 The relative number of downregulated, not regulated, and upregulated genes assigned to the same COG terms is shown (each condition was compared to growth on glucose as in panel C). The total number of genes assigned to each COG term is given in parentheses. Full COG terms, if abbreviated: intracellular trafficking, secretion, and vesicular transport; secondary metabolites biosynthesis, transport and catabolism; inorganic ion transport and metabolism; post-translational modification, protein turnover, chaperones; translation, ribosomal structure and biogenesis; replication, recombination and repair; translation, ribosomal structure and biogenesis; coenzyme transport and metabolism; carbohydrate transport and metabolism; nucleotide transport and metabolism; amino acid transport and metabolism; and cell cycle control, cell division, chromosome partitioning. (E) Regulation of MUT genes shown in Figure 1 (relative to glucose). FC log2 values are shown; if the changes were not significant (p < 0.01), then the values are not shown (gray). In cases where multiple probe sets were present on the array (e.g., AOX1), the mean FC value is shown. Abbreviations: BPP, before branch point (to assimilative and dissimilative branches); PBI, peroxisomal biogenesis and import.

heterologous gene expression,36−40 and transcriptional regulation is the major response of these organisms when they are grown on different carbon sources.41 The most commonly used

P. pastoris promoter, of the alcohol oxidase 1 gene (PAOX1), is tightly repressed on carbon sources such as glucose, glycerol, and ethanol (AOX1 mRNA is undetectable). Upon methanol 174


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ACS Synthetic Biology induction, PAOX1 is strongly induced, resulting in about 5% of total mRNA and 30% of total soluble protein.39 Despite the annotation of a several dozen genes putatively involved in methanol metabolism42−44 alongside transcriptomics41,45,46 and proteomics studies47,48 that have hinted at targets of additional strong, methanol-regulated promoters, only five methanol-regulated promoters have been tested in P. pastoris (strong: PAOX1, PDAS2, PFLD1; weak: PAOX2, PPEX839) in the past 25 years since its development as a protein production system. Also, in related methylotrophic yeasts, transcriptomics studies have been performed;49,50 yet, again, only few promoters have been systematically characterized (e.g., five promoters in C. boidinii51). Here, we report a comprehensive characterization of the P. pastoris methanol utilization (MUT) pathway and connected biochemical detoxification mechanisms, providing a large set of tightly regulated, sequence-distinct promoters offering a wide range of expression levels (45 promoters tested). We have applied these promoters alongside a set of 20 novel terminators to express the carotenoid pathway as a model system to demonstrate their feasibility for heterologous pathway expression.

2A and Supporting Information S3). Our studies neglected growth rate-specific effects but were close to the most frequently applied cultivation strategies with different carbon sources applied in common protein production processes employing P. pastoris. The strong transcriptional changes between glucose and methanol closely resembled effects reported in previous studies and have been comprehensively discussed.41,45,49,50,54 Accordingly, genes involved in the assimilative and dissimilative branches of the MUT pathway were strongly transcriptionally upregulated (Figure 2E and Supporting Information S3). Also, genes involved in peroxisome biogenesis were clearly upregulated. Interestingly, genes of the PPP and genes involved in ROS detoxification showed no uniform trend, with a similar number of genes up- and downregulated. Concerning the PPP, it appears especially noteworthy that some genes coding for isoenzymes are oppositely regulated (see extended discussion below, including results from reporter fluorescence measurements [Supporting Information S7] and Rußmayer et al.54). However, gene regulation under derepressed conditions was even more different between methanol induction and growth on glucose than methanol and glucose were from one another (Figure 2B,C), indicating vast transcriptional changes. The changes were also more pronounced than differences observed upon growth of P. pastoris under glucose-limiting conditions in shake flasks.41 Notably, when preparing amplified RNA (aRNA) for the array hybridization, we already noticed lower yields for samples obtained under derepressed conditions as well as altered capillary electrophoresis migration patterns compared to the other samples (Supporting Information S4). Compared to gene expression on glucose, 75% of genes were significantly (p < 0.01) differentially regulated under derepressed conditions (4413 of 5869 probe sets), with an equal number of up- and downregulated genes. Among biological processes (classified by COG terms56), especially genes coding for proteins involved in translation, RNA processing and modification, cytoskeleton, nucleotide transport, and cell cycle control were downregulated (Figure 2D). Together with an upregulation of genes coding for proteins involved in defense mechanisms, cell wall, and extracellular structures, this response is in line with the anticipated cellular reaction toward nutrient depletion and adaption to the stationary phase. We also investigated the readdition of glucose to methanol grown cultures to study mRNA turnover and to create a basic data set relevant for pexophagy studies. Methylotrophic yeasts are model systems for peroxisome biogenesis and degradation,57 and similar shifts from methanol to glucose are commonly performed to trigger pexophagy (e.g., ref 58). The transcriptional response of glucose readdition appeared to be somewhat intermediate between the response toward glucose and methanol: Transcript levels of MUT genes were still upregulated compared to glucose, yet they were not as high as on methanol, suggesting persistence and only partial degradation of the mRNAs. Also, sugar transporters were strongly upregulated (e.g., HGT1 557-fold), as reported in a study comparing transcript levels between growth on glycerol and glucose.59 Downregulated genes compared to growth on methanol included peroxisomal proteins (e.g., PEX5, PEX6, PEX10, PER3), which is in line with anticipated pexophagy under glucose readdition conditions. However, the exact effects seen upon glucose readdition will depend on the time at which RNA is isolated. We sampled after 2 h, the same time interval applied for sampling after methanol induction (Figure 2A).

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RESULTS AND DISCUSSION Genome-Wide Transcriptional Response toward Different Carbon Sources. We hypothesized that the complex reactions of the MUT pathway of P. pastoris (Figure 1) and other methylotrophic yeasts should encompass a large network of transcriptionally co-regulated genes, offering tightly regulated promoters that can be harnessed for heterologous pathway expression. Typical considerations on the MUT pathway in P. pastoris have been limited to enzymes catalyzing direct reactions of methanol.26,42,43 This canonical MUT pathway is divided into a dissimilative branch (oxidation of methanol to CO2 and the generation of NADH for respiratory ATP production) and an assimilative branch (to produce biomass by formaldehyde fixation) (Figure 1). However, recent transcriptome analyses also suggest noncanonical parts of associated processes (e.g., peroxisome biogenesis, stress response, respiratory function)45,49,50 as targets for our search for a set of promoters for pathway expression. Concerning stress response, the defense against reactive oxygen species (ROS) is crucial since the oxidation of methanol to formaldehyde creates equimolar amounts of reactive hydrogen peroxide.52,53 Previous transcriptomics studies of methylotrophic yeasts were based on heterologous DNA microarray hybridization lacking MUT genes,46 different P. pastoris strains,45,46,54 or H. polymorpha,49,50 and typically only two conditions were compared (growth on glycerol vs methanol). Yet, typical MUT promoters show at least three levels of regulation:40 (1) repression in the presence of repressing carbon sources (in P. pastoris glucose, glycerol and ethanol); (2) derepression once the repressing carbon source is depleted; and (3) induction by methanol. Recently, a comprehensive P. pastoris transcriptomics study also investigated the effect of translation and glucose feed rates.41 In addition, the authors showed that growth on glycerol and glucose exerts highly similar transcriptional effects and that growth rates influence transcription.41 Here, we used custom Affymetrix microarray chips55 to compare the transcriptional response of P. pastoris grown in bioreactors under glucose-repressed, derepressed, methanolinduced conditions as well as after glucose readdition (Figure 175


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Figure 3. With an eGFP reporter gene, MUT promoters show a wide range of regulatory profiles and a range of expression levels. (A) Reporter protein fluorescence of MUT promoters in a time series experiment mimicking typical biphasic bioreactor cultivations. The promoters of MUT and associated genes (Supporting Information S2) were seamlessly cloned upstream of an eGFP reporter gene and transformed into P. pastoris. The strains were cultivated in a high-throughput 96-deep-well plate format63 in biological quadruplicates (mean values and standard deviations are shown) on glucose containing medium (BMD, buffered minimal dextrose) for 60 h and subsequently induced with methanol (BMM). Samples were taken under glucose repressed conditions (15.5 h), derepressed conditions (60 h), and 24 h methanol induction. eGFP fluorescence was normalized per OD600. Additional sampling points measured are shown in Supporting Information S6. Only the shortest promoter lengths tested are shown; alternative lengths tested did not affect reporter protein fluorescence (Supporting Information S5). The same abbreviations as those in Figure 2E are used. (B) MUT promoter reporter protein fluorescence on different carbon sources. The same strains as in panel (A) were cultivated for 60 h on the media indicated (BMD, glucose; BMG, glycerol; BME, ethanol; BMMan, mannitol; BMO, oleic acid; BMM, methanol). Measurement procedures, replicate handling, and data of glucose are identical to the 60 h data of panel A.

MUT Promoter Analysis Employing Reporter Genes. Microarray results provide information only about relative changes in transcript levels and no information on the level of actual absolute expression. Therefore, all promoters containing DNA parts of canonical MUT pathway genes (following the most recent annotation/model26,43) and associated, noncanonical pathways (PPP, ROS defense, selected peroxisomal proteins, and glycolysis/gluconeogenesis enzymes) were cloned upstream of an enhanced green fluorescent reporter protein (eGFP) and assayed for reporter protein fluorescence under various growth conditions (Figure 3). The promoter of the glyceraldehyde 3-phosphate dehydrogenase gene (PGAP) was included as a strong, constitutive P. pastoris reference promoter.39 The length of yeast promoters can vary considerably (with the median length in S. cerevisiae being 455 bp), and for promoter comparisons, for example, lengths of 1000, 800, and 600 bp have been used.62 For assembling and expressing pathways, short promoters are desirable as they reduce the size of expression cassettes (facilitating transformation) and mutations in PCR amplification are less likely to occur. We have selected the promoter sequences as the distance from the start codon to the respective upstream gene (Supporting Information Table S2 for gene names and

Therefore, our experiments provided a large data set, yet the differential regulation of the most interesting gene candidates for further studies still need to be verified by a time series, e.g., by RT-qPCR. Although MUT genes such as AOX1 have been reported to be only slightly derepressed (2−4% of induced values),39 they were among the most strongly upregulated genes in the derepressed set of the microarray experiments (Figure 2E and Supporting Information S3). AOX1 was, for example, 39-fold upregulated under derepressed conditions compared to that in the presence of glucose. We assume that these surprisingly high values arise from the pairwise microarray comparison where the fold change (FC) between two conditions is calculated. If a gene is not expressed under a certain condition, then the background noise will determine the FC value. In previous studies, AOX1 mRNA was undetectable on glucose and slightly derepressed upon glucose depletion (2−4% of induced values).39,60,61 Calibrating the moderate signal from derepression to the very low background expression results in a high FC value. To this end, the FC values relative to repressed conditions have to be treated with care when analyzing putatively repressed genes. In these cases, we based our interpretations on reporter protein experiments (Figure 3). 176


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The trends observed in the microarray experiments (Figure 2E) widely correlated with the output of the reporter gene constructs. A notable exception is the derepressed phase, where bioreactor-derived microarray data gave higher changes than could be deduced from the paralleled small-scale reporter fluorescence measurements. Small-scale cultivations appear to underestimate the derepression effect (extended discussion in Supporting Information S7). Therefore, for the interpretation and practical relevance, we relied more on the small-scale reporter gene results than the microarray data to avoid overestimation of derepression effects. Special emphasis was placed on derepression, transcriptional regulation of isoenzymes (Supporting Information S8), sequence features, and practical relevance in view of the envisioned access to a new toolbox of co-regulated promoters for synthetic biology and metabolic engineering. PCAT1 Initiates Transcription Based on Derepression, Matching PAOX1 for Some Specific Examples. In P. pastoris, so far no natural strong derepressed MUT promoters have been characterized, but synthetic PAOX1 variants have been reported, enabling methanol-free processes solely regulated by glucose/ glycerol levels.7,65 In contrast to P. pastoris, in related methylotrophic yeasts derepressed expression levels of natural MUT promoters may reach up to 70% of methanol-induced expression,40 allowing simple, methanol-free expression. Therefore, in our analyses, we placed special emphasis on the glucose repression and derepression phases. Derepression effects between MUT promoters varied considerably: Several promoters such as PAOX1, PDAS1, PDAS2, PPMP20, PTAL2, PFBA2 showed very tight regulation with no significant detectable derepressed reporter protein fluorescence. PFGH1, PDAK1, PFLD1, and PFDH1 showed slight to intermediate derepression effects (Figure 3). The promoter of the CAT1 gene showed tight repression on glucose and the highest level of derepression (29% of the strong constitutive PGAP) and could be induced with methanol to similar levels as those with PAOX1 (Figures 3A,E and 4). Therefore, we focused on PCAT1 as a representative promoter to evaluate the suitability of derepressed promoters for protein production in P. pastoris. For the first time, we demonstrated that PCAT1 is also the only P. pastoris MUT promoter that can also be induced with oleic acid to reach similar levels as those with methanol (Figure 3E). It is worth noting that with the first tested promoter lengths, PCAT1−692 and PCAT1−1000 constructs (Supporting Information S5), we experienced problems with transformation background (colonies showing no reporter protein expression when recultivated). After experimental evaluations, we suggest using a 500 bp promoter fragment as the default length of PCAT1 for all standard applications. These findings for PCAT1-driven expression under derepressed conditions were inferred from the fluorescence levels of the eGFP reporter protein, a cytoplasmic protein that is easily folded and well-tolerated by P. pastoris.7,66,67 However, heterologous protein production in P. pastoris is preferably achieved by secretion, as downstream processing is facilitated (no cell breakage, etc. required). Therefore, we also tested secretory expression of two industrially relevant enzymes, Candida antarctica lipase B (CalB) and horseradish peroxidase (HRP) fused to the commonly used mating factor alpha secretion signal sequence. Under derepressed conditions after carbon source depletion in deep-well plates, we obtained 35% (CalB) and 21% (HRP) volumetric activity of the constitutive state-of-the-art promoter PGAP (Figure 4B,C). Methanol

promoter lengths tested and Supporting Information Figure S9 for genomic organization). Promoter lengths already reported in the literature were also tested. In the case of ambiguous sequence information (e.g., multiple ORFs, putative annotations), a promoter length of 1000 bp was used (Supporting Information S5). All promoters were seamlessly fused to the reporter gene (i.e., the transition from promoter to start codon is native, without additional restriction enzyme recognition sites in between). High-throughput 96-deep-well plate cultivations63 of the 45 strains allowed expression to be easily assayed on different carbon sources and at different time points (Figure 3 and Supporting Information S6). We used commonly applied cultivation protocols mimicking typical two-phase fed-batch bioreactor cultivations (Figure 3A). The strains were at first grown on glucose until depletion and were then induced with methanol over 72 h (full time series shown in Supporting Information S6). Samples were taken under glucose repressed, derepressed, and methanol-induced conditions (similar to the microarray cultivations shown in Figure 2A). In methylotrophic yeast species, the response toward alternative carbon sources is variable,40 and effects on MUT promoters have never been systemically and functionally assayed. Therefore, we also tested growth on commonly used alternative carbon sources (glycerol, ethanol, oleic acid, mannitol) (Figure 3D). In cases where different length promoters were tested, no effects on reporter gene fluorescence were noticed (Supporting Information S5; only the shortest lengths are shown in Figure 3). Several canonical MUT promoters (PFLD1, PFDH1, PDAS1, PDAS2) showed strong methanol-inducible reporter fluorescence, reaching at least half of the read out obtained with the common AOX1 promoter. Similar to early studies64 and based on these GFP measurements, PDAS2 even outperformed PAOX1. Some promoters showed weaker methanol inducible expression (PFGH1, PDAK1, PPEX5, PFBA2, PAOX2). Other promoters showed constitutive expression (PADH2, PTPI1, PFBP1, PPGI1) as has been, in part, previously reported;39 however, their expression was clearly lower than the commonly used constitutive GAP promoter. Promoters of genes involved in ROS defense showed varying results: PCAT1 and PPMP20 resulted in strong expression on methanol and a few promoters showed low to intermediate expression (PSOD2, PSOD3, PMSR1c3). However, several ROS promoters did not show any detectable reporter gene fluorescence, suggesting either no expression or low expression under the detection limit. In case of the five methionine sulfoxide reductase promoters tested, only a single promoter showed clear reporter gene fluorescence, suggesting that MSR1c3 is the major methionine sulfoxide reductase in P. pastoris. PPP promoters showed a strong variability in regulatory profiles and expression levels, the implications of which are discussed below. Cultivations on alternative carbon sources did not show remarkable general trends (Figure 3B), but certain promoters were specifically regulated in correlation with the function of their natural gene product: PADH2 (alcohol dehydrogenase) was clearly upregualted on ethanol and PCAT1 was strongly induced on oleic acid (presumably owing to the detoxification function of catalase toward hydrogen peroxide arising from beta oxidation of fatty acids). Canonical MUT genes were only slightly upregulated on oleic acid compared to that on glucose, suggesting that the regulation thereof is not overlapping. 177


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with different regulatory profiles for optimal yields. These effects may be caused by effects on overall mRNA levels, degradation, or even translation initiation (since the 5′untranslated regions are also different). These results suggest that derepressed expression is also possible with secreted proteins, although titers and promoters showed different correlations. In contrast to limited carbon source feeding in bioreactors, derepressed cells in deep-well plates rely on intracellular stored energy for protein production, which limits their productivity. Secretion typically exerts more stress on the cell and may induce the UPR (unfolded protein response) or ERAD (endoplasmic-reticulum-associated protein degradation),68 resulting in additional metabolic demands. Although higher productivity and product titers can be expected from bioreactor cultivations that apply limited carbon source feeds for controlled derepression effects, assays in deepwell plates allow highly producing strains to be screened without requiring a lengthy methanol induction procedure. It still remains to be clarified how exactly the CAT1 promoter of P. pastoris is induced in the absence of glucose/glycerol or in the presence of methanol or oleic acid. However, based on literature data from other hosts, PCAT1 could be induced by different stimuli and transcription factors. For example, the peroxisomal S. cerevisiae CAT1 homologue is regulated by carbon source-responsive transcription factors (Adr1p, Oaf1p),69 correlating with P. pastoris PCAT1 activation after glucose depletion in our experiments (Figure 4A). However, processes associated with the adaption to glucose depletion may also be indirectly involved in PCAT1 regulation. The primary biochemical function of Cat1p after glucose depletion most probably is detoxification of H2O2, arising from ROS stress due to adaptation to the stationary phase (e.g., fatty acid betaoxidation results in considerable amounts of H2O2). Therefore, ROS could also act as an activating stimulus of PCAT1, similar to the cytosolic catalase (CTT1) of S. cerevisiae, which is activated under various stress conditions and by transcription factors such as Yap1p70 (P. pastoris contains only a single catalase gene with a predicted peroxisomal targeting sequence). Also, the involvement of nitrogen regulation has been suggested for P. pastoris CAT1.71 However, applying different ammonium sulfate concentrations did not show any significant trend in our studies (data not shown). Ultimately, we consider derepressed promoters such as PCAT1 to be important tools that enable shorter, inducible, methanolfree processes alongside glycerol-repressed/glucose-inducible promoters previously reported.59 Regulatory Implications and Sequence Features. Interestingly, the core promoters of all MUT and associated promoters show a striking enrichment in TATA box motifs (Supporting Information S2). Yeast core promoters follow two fundamental types of architecture:72,73 (1) TATA box containing promoters are highly regulated and depend on the SAGA (Spt-Ada-Gcn5 acetyltransferase) coactivator; (2) TATA-less promoters are rather constitutively active and depend on the TFIID coactivator (TFIID). While TFIIDdependent promoters account for ∼90% of promoters in S. cerevisiae, only ∼19% of promoters contain a TATA box and approximately half of those are SAGA-dependent.72 Remarkably, 9/13 promoters of genes of the assimilative and dissimilative MUT pathway contained a clear TATA box consensus motif in close proximity (67%; intermediate, 33−67%; weak, 18-fold difference in lycopene formation between different genetic constructs. Apparently the use of certain promoter combinations leads to incomplete conversion of lycopene to β-carotene. Although high productivity for β-carotene was not the major goal of this study, total β-carotene concentrations in our experiments reached more than 5 mg per gram of cell dry weight, which is comparable to an optimized S. cerevisiae strain82 and more than 10 times higher than that with other strains generated more recently,84,85 and it is much easier to obtain high cell densities with Pichia pastoris. Further perturbation of the expression levels by our experiments employing weaker and differently regulated promoters (strains 5−12) did not further boost the yields of this pathway, at least in shake flask experiments. However, this was not too surprising since expression under derepressed (carbon source limited) conditions by glucose or glycerol depletion disfavors the accumulation of excess lipids in lipid droplets, which are important86 for the storage or even the synthesis of water-insoluble carotenes. Nevertheless, with methanol induction, similar effects (variable yields and intermediate accumulation) were evident (e.g., lycopene yields of construct 12 vs constructs 9−11). Our results suggest that MUT promoters are versatile tools for combinatorial transcriptional fine-tuning. Both applying different sets of promoters and shuffling the position of similarly strong promoters had a pronounced effect on product yield and side-product formation. Future research may focus on finding a rational method of predicting the optimal promoter combination for a set of genes by implementing information on mRNA secondary structures and metabolic flux. Conclusions. Here, we have shown, that P. pastoris provides, to our knowledge, the largest set of natural tightly co-regulated promoters known in biotechnological expression hosts. Testing 45 promoters of the MUT pathway and associated processes resulted in 15 methanol-regulated promoters, with about half showing very high expression levels (Table 1). Such a toolbox of strong promoters is valuable for overexpressing heterologous multigene pathways. Yet, the weaker promoters also appear to be useful for transcriptional fine-tuning of stoichiometric ratios between pathway steps or as

pathway due to its general biotechnological relevance and ease of detection of different pathway (side-) products. Carotenoids are isoprenoid derivatives involved in diverse biological processes such as light harvesting in photosynthesis and coloration pigments, and β-carotene is the precursor of vitamin A. Biotechnological applications range from food coloring and cosmetic purposes to fighting malnutrition caused by vitamin A deficiency (golden rice).28,77,78 Carotenoids have been heterologously produced in microorganisms such as E. coli, S. cerevisiae, and P. pastoris.28,30,79−82 Carotenoid production colors P. pastoris cells red (lycopene) or orange (β-carotene). Thereby, successful production can be semiquantitatively estimated from the color of the cultures. So far in P. pastoris, four genes (crtE, crtB, crtI, and crtY) were employed for βcarotene production from farnesyl diphosphate via the intermediate lycopene.28 Previously, these four genes were constitutively expressed using the GAP promoter and AOX1 transcriptional terminator for all genes.28 Also, peroxisomal targeting of constitutively expressed carotenoid enzymes77 and the application of self-processing viral 2A sequences30 for a more compact pathway design was investigated in P. pastoris. Here, we used tightly regulated MUT promoters to avoid a constant metabolic burden and diverse promoter and terminator sequences to avoid loop-out recombination10 of identical sequences in the expression cassette. In contrast to the use of a single promoter and polycistronic 2A sequences,30 multiple promoters allow every reaction step to be fine-tuned individually and different regulatory patterns to be tested (i.e., induction/derepression), even in combination. Therefore, 12 expression vectors from three pools (groups) of promoters were generated. For each pool, the position of the promoters was shuffled (Figure 6A): (1) constructs 1−4 bear strong, tightly repressed methanol-inducible promoters (PAOX1, PDAS1, PDAS2, PPMP20); (2) constructs 5−8 contain two strong, tightly regulated promoters (PDAS1, PPMP20) and two tightly regulated promoters of intermediate strength (PTAL2, PFBA2); and (3) constructs 9−12 were designed with four different derepressed promoters (PCAT1, PPEX5, PFLD1, PFDH1). In addition, four strong terminators (TAOX1, TDAS1, TDAS2, TPMP20) were used in all plasmids. We recommend using strong terminators (as defined by high reporter protein fluorescence) for heterologous pathway expression as the default to avoid having too many variables at one time. Using promoters instead of terminators for transcriptional fine-tuning has the advantage that no superfluous mRNA is transcribed that would get degraded faster in the case of weak terminators.11 The expression constructs were assembled by Gibson assembly,9 and P. pastoris cells were transformed with linearized expression cassettes and cultivated with methanol induction in a high-throughput deep-well plate (DWP) system.63 Multiple clones were tested since P. pastoris may show high variability between transformants of the same construct83 (Figure 6B). Before methanol induction, only constructs 9−12 bearing derepressed promoters were very weakly orange colored (data not shown). After methanol induction, transformants of all constructs showed varying orange color, indicating functional expression of the carotenoid pathway in all cases. Interestingly, the number of colored clones varied between constructs: For 11 of the 12 different constructs, 68−98% of transformants tested were colored Figure 6A (rightmost column). For pathway construct 4, only 6% of the transformants were colored. Apparently the choice and positioning of the promoter affects the ratio of positive transformants obtained. We 181


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ACS Synthetic Biology “tuning knobs” for balancing multigene coexpression in synthetic biology applications. Despite their similar regulation, the promoters tested in this study show little to no sequence similarities, possibly because short regulatory elements such as transcription factor binding sites may be variably dispersed over the whole promoter (as shown for PAOX1, PDAS2, and PPEX839,87,88). In contrast to highly similar variants of a mutant promoter library, which are typically derived by small changes of a single promoter, the low sequence similarity between natural MUT promoters appears to be favorable for in vitro overlap-directed DNA assembly and also in vivo stability. From a basic research perspective, this low sequence similarity between highly coregulated promoters is puzzling and may suggest the use of MUT promoters as a model system for studying transcriptional regulation. Growth and metabolism of the inexpensive inducer methanol may also bear additional benefits for certain applications. In recent work on artemisinic acid production in S. cerevisiae,15 oxidative stress arising due to cytochrome P450 (CYP) expression was counteracted by increasing the levels of cytosolic catalase. P. pastoris has been shown to be a highly suitable expression system for CYPs,22,89,90 and growth on methanol necessitates a high tolerance to ROS stress (caused by oxidation of methanol to formaldehyde; Figure 1). Over the last 2 decades, P. pastoris has become a popular expression host, surpassing S. cerevisiae20 for high-level single protein production. Considering the recent development of GSMMs and the availability of suitable promoters and terminators as well as the feasibility of new and simple pathway assembly methods, P. pastoris with its robust and fast growth to high cell densities as well as its low natural tendency for homologous recombination also appears to be a promising alternative to S. cerevisiae for metabolic engineering endeavors requiring tight transcriptional regulation of large heterologous pathways, efficient CYP expression or other membrane protein expression, compartmentalization in peroxisomes or other organelles, and oxidative stress tolerance.

used. For the cultivation of horseradish peroxidase (HRP) expression strains, hemin was added to a final concentration of 25 μM to the starting medium and in the medium for the first induction step.93 P. pastoris Transformation and Screening. P. pastoris was transformed with SwaI-linearized plasmids according to the condensed protocol of Lin-Cereghino et al.94 A low amount of DNA was transformed to avoid multicopy integrations that would bias comparisons. Transformation with 1 μg of pPpT4_S typically yields only single-copy transformants (ref 67 and repeated observation from unpublished results). Therefore, an equimolar amount of the vectors with inserts equaling 1 μg of pPpT4_S was used for transformation. Transformant selection was performed as previously reported67 to avoid clonal variation.83,95 In short, 42 transformants were screened; typically, this landscape showed uniform expression, except for a few transformants showing no expression or elevated expression. Three transformants from the linear range of the landscape were streaked for single colonies and confirmed by rescreening for uniform expression. One representative transformant was used in further work. Cultivation Conditions. DWP cultivations were performed following the protocol reported by Weis et al.63 In short, cell material from single colonies was inoculated into 96 DWPs and cultivated for 60 h on BMD (250 μL). Subsequently, an equal amount of BMM2 (1% methanol v/v to achieve a final concentration of 0.5%) was added. The cells were additionally induced with 50 μL of BMM10 medium (5% methanol v/v) for 12, 24, and 48 h after the first induction. Samples were taken and measured at the indicated time points. Shake flask cultivations were performed in 250 mL baffled flask (25 mL BMD starting volume) and inoculated to a starting OD600 of 0.05. The flasks were induced after 48 h with 25 mL of BMM2 and after 12 and 24 h of the first induction with BMM10. Glucose concentrations were measured using a hexokinase method based kit (Glucose UV kit, DIPROmed, Vienna, Austria). One milliliter of the reaction solution was mixed with 10 μL of sample and incubated for 10 min at room temperature. The resulting NADH signal was measured at 340 nm and compared to a calibration curve. Microarray Analyses. Strains for the microarray experiments were cultivated in 1.5 L bioreactors. Due to precipitation occurring with standard P. pastoris bioreactor cultivation media (modified basal salt medium based on ref 96), which might complicate RNA isolations and OD600 measurements, we used buffered minimal dextrose medium for all bioreactor cultivations (20 g/L glucose, 13.4 g/L BD Difco yeast nitrogen base (Franklin Lakes, NJ, USA) and 200 mM potassium phosphate buffer (pH 6.0)). A P. pastoris strain bearing a pPpT4 based zeocin resistance plasmid served as a reference if the data was to be compared to heterologous protein expressing strains. The 1.5 L fedbatch-pro bioreactor system (DASGIP AG, Juelich, Germany) containing 600 mL of BMD medium was inoculated to an OD600 of 0.25. All cultivations were started in biological triplicates with a batch phase on glucose as the sole carbon source at 28 °C and aeration at 0.7 L air/min. Agitation was set between 500 and 1200 rpm to keep oxygen saturation at 30%. As a pH control agent and nitrogen source, 25% ammonia solution was used. After all of the glucose was consumed (shown with glucose detection strips (Combur Test strips, Roche Diagnostics, Rotkreuz, Switzerland)), methanol induction was started by addition of 0.5% methanol. After methanol was consumed

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MATERIALS AND METHODS Strains, Plasmids, Chemicals, and Media. The P. pastoris CBS7435 wild-type strain was used for most expression studies. The reporter enzymes CalB and HRP were expressed in P. pastoris CBS7435 muts because higher yields compared to that of the wild type have previously been reported in the literature26 and screening on a small scale is more reliable. The reporter plasmids were based on the zeocin-selectable pPpT4_S vector reported by Näaẗ saari et al.,74 and cloning was performed by restriction site-free cloning (RSFC)91 or Gibson assembly.9 See Supporting Information S1 for a detailed description of plasmid construction and cloning of the promoters, terminators, and the carotenoid pathway expression cassettes (primer sequences are provided in Supporting Information S2). Chemicals, enzymes, cloning kits, and E. coli cultivations were used and performed as recently described.67 P. pastoris media for standard deep-well plate cultivations (glucose cell growth phase followed by methanol induction) were prepared as reported by Weis et al.:63 buffered minimal dextrose (1% w/ v) (BMD) and buffered minimal methanol medium (BMM) with 0.5% (v/v) methanol. For growth on alternative carbon sources, 1% (w/v) glycerol (BMG), 1% (v/v) ethanol (BME), 1% (w/v) mannitol (BMMan), and 0.2% (w/v) oleic acid supplemented with 0.02% (v/v) Tween-4092 (BMO) were 182


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quantified by external calibration using the corresponding reference material (also, small amounts of other stereoisomers [e.g., 9-cis-β-carotene and 13-cis-β-carotene] were detected, and peak areas were added to calculate total yields).

(deduced from differential nitrogen feed and oxygen consumption levels), reinduction at 2% glucose was performed. The samples for RNA isolation were taken at the time points indicated in Figure 2A. All samples were centrifuged immediately after collection and stored in RNase later solution (Life Technologies, Carlsbad, CA, USA) at −80 °C until further processing. Total RNA was isolated using a RiboPureTM yeast RNA kit (Ambion, Austin, TX, United States). Purity and integrity were assessed with an Agilent Bioanalyzer 2100 using the RNA 6000 Nano Assay kit (Agilent Technologies, CA, United States). For reverse transcription and labeling, an Affymetrix GeneChip 3′IVT Express Kit (Affymetrix, Santa Clara, CA, United States) was used with an initial RNA amount of 450 ng. First- and second-strand syntheses were performed according to the manufacturer’s protocol at 40 °C for 4 h. Quantities and size distributions were again assayed with an Agilent Bioanalyzer 2100. For both fragmentation and hybridization mix preparation, 15 μg of DNA was used and incubated with custom Affymetrix microarray chips as previously reported in detail.55 Analysis was performed with the new annotation of the CBS 7435 strain.43 Reporter Activity Measurements. eGFP fluorescence measurements were performed in microtiter plates (Nunc MicroWell 96-well optical-bottom plates with polymer base, black; Thermo Fisher Scientific) using a Synergy MX plate reader (Biotek, Winooski, VT, USA).67 Fluorescence was measured at 488/507 nm (excitation/emission). Fluorescence measurements were normalized per OD600 measured to account for different dilution factors required to stay within the linear range of the plate reader. HRP activity was measured using 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) as substrate as described in the literature.26,97 CalB activity was measured using 4-nitrophenyl butyrate (Sigma-Aldrich, Vienna, Austria) as substrate as described in the literature.26 β-Carotene producing strains were cultivated in shake flasks as described above. After 72 h of methanol induction, a cell pellet corresponding to 100 OD600 units was harvested by centrifugation (3200g, 10 min, RT) and resuspended in 1 mL of yeast lysis buffer (1 M sorbitol, 100 mM EDTA, 14 mM, βmercaptoethanol). One-hundred microliters of a zymolyase stock solution (1000 U/mL) was added, and the reaction mixture was incubated at 30 °C for 30 min. The thus generated spheroplasts were pelleted by centrifugation (5 min, max. speed). For carotenoid extraction, the spheroplasts were resuspended in 500 μL of methanol−chloroform (1:1 v/v) and incubated at 60 °C for 15 min. The extraction step was repeated until the remaining cell pellet was colorless. The combined organic phases were dried using a stream of dry nitrogen gas, and the dried residues were dissolved in 2 mL of methanol−chloroform (1:1 v/v). HPLC analysis was performed with a HPLC instrument (1200 series, Agilent Technologies) equipped with a photodiode array detector. Carotenoids were separated on a C30 carotenoid column (150 × 4.0 mm, 5 μm; YMC Europe) using H2O−MeOH (4:96 v/v; phase A) and MeOH−MTBE (5:95 v/v; phase B) as the mobile phases. The linear gradient elution program was as follows: 0−20 min, 5−65% phase B; 20−25 min, 65% phase B; 25.01−30 min, 65−5% phase B. The flow rate was maintained at 0.75 mL/min at 30 °C. Carotenoid detection was conducted at 450 nm. All-trans-β-carotene and lycopene eluted after 17.2 and 25.6 min, respectively. β-Carotene and lycopene were

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssynbio.5b00199. Detailed construction of the vectors (S1); derepressed samples yield less aRNA for hybridizations (S4); different promoter lengths tested (S5); full time series of Figure 3A (S6); differences between reporter fluorescence measurements and microarray data (S7); regulation of isoenzyme pairs (S8); testing for ARS function of the terminators (S10); and supporting references (PDF) List of promoters, terminators and primers (S2) (XLSX) Lists of genes differentially regulated in the microarray data (S3) (XLS) Genomic organization of the genes and promoter sequences (S9) (PDF)

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AUTHOR INFORMATION

Corresponding Author

*Tel.: +43 316 873 4074. Fax: +43 316 873 9302. E-mail: [email protected]. Present Address ∥

(T.V.) Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia. Author Contributions ⊥

T.V., L.S., and T.K. contributed equally to this work. T.V., L.S., and T.K. designed the promoter experiments. L.S., T.K., R.W., and T.V. performed the promoter experiments. T.V. and M.G. designed the terminator experiments. C.S. and J.P. performed the terminator experiments. M.G. and T.V. designed the pathway experiments. A.-M.H., M.A.G., L.S., M.W., and C.S. performed the pathway experiments. G.G.T. designed and analyzed the microarray experiments. T.V. wrote the majority of the manuscript. T.V., A.G., and M.G. conceived the study. A.G. and M.G. supervised the research. All authors read and approved the final version of the manuscript.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This project was co-financed by the European Union’s Seventh Framework Programme FP7/2007-2013 under grant agreement no. 289646 (Kyrobio). The research leading to these results has also received funding from the Innovative Medicines Initiative Joint Undertaking project CHEM21 under grant agreement no. 115360, the resources of which are composed of financial contributions from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution. In addition, the work has been supported by the Federal Ministry of Science, Research and Economy (BMWFW), the Federal Ministry of Traffic, Innovation and Technology (bmvit), the Styrian Business Promotion Agency SFG, the Standortagentur Tirol and ZIT − Technology Agency of the City of Vienna through the COMET-Funding Program managed by the Austrian Research 183


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(16) Hong, K.-K., and Nielsen, J. (2012) Metabolic engineering of Saccharomyces cerevisiae: a key cell factory platform for future biorefineries. Cell. Mol. Life Sci. 69, 2671−90. (17) Da Silva, N. A., and Srikrishnan, S. (2012) Introduction and expression of genes for metabolic engineering applications in Saccharomyces cerevisiae. FEMS Yeast Res. 12, 197−214. (18) Liu, L., Redden, H., and Alper, H. S. (2013) Frontiers of yeast metabolic engineering: diversifying beyond ethanol and Saccharomyces. Curr. Opin. Biotechnol. 24, 1023−30. (19) Jahic, M., Veide, A., Charoenrat, T., Teeri, T., and Enfors, S.-O. (2006) Process technology for production and recovery of heterologous proteins with Pichia pastoris. Biotechnol. Prog. 22, 1465−73. (20) Bill, R. M. (2014) Playing catch-up with Escherichia coli: using yeast to increase success rates in recombinant protein production experiments. Front. Microbiol. 5, 85. (21) Vogl, T., Hartner, F. S., and Glieder, A. (2013) New opportunities by synthetic biology for biopharmaceutical production in Pichia pastoris. Curr. Opin. Biotechnol. 24, 1094−101. (22) Wriessnegger, T., Augustin, P., Engleder, M., Leitner, E., Müller, M., Kaluzna, I., Schürmann, M., Mink, D., Zellnig, G., Schwab, H., and Pichler, H. (2014) Production of the sesquiterpenoid (+)-nootkatone by metabolic engineering of Pichia pastoris. Metab. Eng. 24, 18. (23) Nocon, J., Steiger, M. G., Pfeffer, M., Sohn, S. B., Kim, T. Y., Maurer, M., Rußmayer, H., Pflügl, S., Ask, M., Haberhauer-Troyer, C., Ortmayr, K., Hann, S., Köllensperger, G., Gasser, B., Lee, S. Y., and Mattanovich, D. (2014) Model based engineering of Pichia pastoris central metabolism enhances recombinant protein production. Metab. Eng. 24, 129−38. (24) Schroer, K., Peter Luef, K., Stefan Hartner, F., Glieder, A., and Pscheidt, B. (2010) Engineering the Pichia pastoris methanol oxidation pathway for improved NADH regeneration during wholecell biotransformation. Metab. Eng. 12, 8−17. (25) Gasser, B., Dragosits, M., and Mattanovich, D. (2010) Engineering of biotin-prototrophy in Pichia pastoris for robust production processes. Metab. Eng. 12, 573−80. (26) Krainer, F. W., Dietzsch, C., Hajek, T., Herwig, C., Spadiut, O., and Glieder, A. (2012) Recombinant protein expression in Pichia pastoris strains with an engineered methanol utilization pathway. Microb. Cell Fact. 11, 22. (27) Jeong, E., Shim, W. Y., and Kim, J. H. (2014) Metabolic Engineering of Pichia pastoris for Production of Hyaluronic Acid with High Molecular Weight. J. Biotechnol. 185, 28−36. (28) Araya-Garay, J. M., Feijoo-Siota, L., Rosa-dos-Santos, F., VeigaCrespo, P., and Villa, T. G. (2012) Construction of new Pichia pastoris X-33 strains for production of lycopene and β-carotene. Appl. Microbiol. Biotechnol. 93, 2483−92. (29) Araya-Garay, J. M., Ageitos, J. M., Vallejo, J. A., Veiga-Crespo, P., Sánchez-Pérez, A., and Villa, T. G. (2012) Construction of a novel Pichia pastoris strain for production of xanthophylls. AMB Express 2, 24. (30) Geier, M., Fauland, P., Vogl, T., and Glieder, A. (2015) Compact multi-enzyme pathways in P. pastoris. Chem. Commun. 51, 1643−46. (31) Sohn, S. B., Graf, A. B., Kim, T. Y., Gasser, B., Maurer, M., Ferrer, P., Mattanovich, D., and Lee, S. Y. (2010) Genome-scale metabolic model of methylotrophic yeast Pichia pastoris and its use for in silico analysis of heterologous protein production. Biotechnol. J. 5, 705−15. (32) Chung, B. K., Selvarasu, S., Andrea, C., Ryu, J., Lee, H., Ahn, J., Lee, H., and Lee, D. (2010) Genome-scale metabolic reconstruction and in silico analysis of methylotrophic yeast Pichia pastoris for strain improvement. Microb. Cell Fact. 9, 50. (33) Caspeta, L., Shoaie, S., Agren, R., Nookaew, I., and Nielsen, J. (2012) Genome-scale metabolic reconstructions of Pichia stipitis and Pichia pastoris and in silico evaluation of their potentials. BMC Syst. Biol. 6, 24. (34) Renuse, S., Madugundu, A. K., Kumar, P., Nair, B. G., Gowda, H., Prasad, T. S. K., and Pandey, A. (2014) Proteomic analysis and

Promotion Agency FFG. T.V. was supported by Austrian Science Fund (FWF) project no. W901 (DK “Molecular Enzymology” Graz) while performing this research. The authors gratefully acknowledge support from NAWI Graz. We would like to thank Clemens Farnleitner and Eva-Maria Köhler for excellent technical assistance and Florian W. Krainer for fruitful discussions. We would also like to thank an anonymous reviewer for helpful comments. The schematic illustration of the P. pastoris cell in the graphical abstract was taken from Vogl et al.21

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REFERENCES

(1) Stephanopoulos, G. (2012) Synthetic biology and metabolic engineering. ACS Synth. Biol. 1, 514−25. (2) Du, J., Yuan, Y., Si, T., Lian, J., and Zhao, H. (2012) Customized optimization of metabolic pathways by combinatorial transcriptional engineering. Nucleic Acids Res. 40, e142. (3) Brophy, J. A. N., and Voigt, C. A. (2014) Principles of genetic circuit design. Nat. Methods 11, 508−20. (4) Nielsen, A. A., Segall-Shapiro, T. H., and Voigt, C. a. (2013) Advances in genetic circuit design: novel biochemistries, deep part mining, and precision gene expression. Curr. Opin. Chem. Biol. 17, 878−92. (5) Blazeck, J., and Alper, H. S. (2013) Promoter engineering: recent advances in controlling transcription at the most fundamental level. Biotechnol. J. 8, 46−58. (6) Alper, H., Fischer, C., Nevoigt, E., and Stephanopoulos, G. (2005) Tuning genetic control through promoter engineering. Proc. Natl. Acad. Sci. U. S. A. 102, 12678−83. (7) Hartner, F. S., Ruth, C., Langenegger, D., Johnson, S. N., Hyka, P., Lin-Cereghino, G. P., Lin-Cereghino, J., Kovar, K., Cregg, J. M., and Glieder, A. (2008) Promoter library designed for fine-tuned gene expression in Pichia pastoris. Nucleic Acids Res. 36, e76. (8) Montiel, D., Kang, H.-S., Chang, F.-Y., Charlop-Powers, Z., and Brady, S. F. (2015) Yeast homologous recombination-based promoter engineering for the activation of silent natural product biosynthetic gene clusters. Proc. Natl. Acad. Sci. U. S. A. 112, 8953. (9) Gibson, D. G., Young, L., Chuang, R., Venter, J. C., Hutchison, C. A., and Smith, H. O. (2009) Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343−5. (10) Aw, R., and Polizzi, K. M. (2013) Can too many copies spoil the broth? Microb. Cell Fact. 12, 128. (11) Curran, K. A., Karim, A. S., Gupta, A., and Alper, H. S. (2013) Use of expression-enhancing terminators in Saccharomyces cerevisiae to increase mRNA half-life and improve gene expression control for metabolic engineering applications. Metab. Eng. 19, 88−97. (12) Yamanishi, M., Ito, Y., Kintaka, R., Imamura, C., Katahira, S., Ikeuchi, A., Moriya, H., and Matsuyama, T. (2013) A Genome-Wide Activity Assessment of Terminator Regions in Saccharomyces cerevisiae Provides a ″Terminatome″ Toolbox. ACS Synth. Biol. 2, 337−347. (13) Peralta-Yahya, P. P., and Keasling, J. D. (2010) Advanced biofuel production in microbes. Biotechnol. J. 5, 147−62. (14) Nielsen, J., Larsson, C., van Maris, A., and Pronk, J. (2013) Metabolic engineering of yeast for production of fuels and chemicals. Curr. Opin. Biotechnol. 24, 398−404. (15) Paddon, C. J., Westfall, P. J., Pitera, D. J., Benjamin, K., Fisher, K., McPhee, D., Leavell, M. D., Tai, a, Main, a, Eng, D., Polichuk, D. R., Teoh, K. H., Reed, D. W., Treynor, T., Lenihan, J., Fleck, M., Bajad, S., Dang, G., Dengrove, D., Diola, D., Dorin, G., Ellens, K. W., Fickes, S., Galazzo, J., Gaucher, S. P., Geistlinger, T., Henry, R., Hepp, M., Horning, T., Iqbal, T., Jiang, H., Kizer, L., Lieu, B., Melis, D., Moss, N., Regentin, R., Secrest, S., Tsuruta, H., Vazquez, R., Westblade, L. F., Xu, L., Yu, M., Zhang, Y., Zhao, L., Lievense, J., Covello, P. S., Keasling, J. D., Reiling, K. K., Renninger, N. S., and Newman, J. D. (2013) Highlevel semi-synthetic production of the potent antimalarial artemisinin. Nature 496, 528−32. 184


Research Article

ACS Synthetic Biology genome annotation of Pichia pastoris, a recombinant protein expression host. Proteomics 14, 2769−79. (35) Dikicioglu, D., Wood, V., Rutherford, K. M., McDowall, M. D., and Oliver, S. G. (2014) Improving functional annotation for industrial microbes: a case study with Pichia pastoris. Trends Biotechnol. 32, 396− 9. (36) Yurimoto, H., Oku, M., and Sakai, Y. (2011) Yeast methylotrophy: metabolism, gene regulation and peroxisome homeostasis. Int. J. Microbiol. 2011, 101298. (37) van der Klei, I. J., Yurimoto, H., Sakai, Y., and Veenhuis, M. (2006) The significance of peroxisomes in methanol metabolism in methylotrophic yeast. Biochim. Biophys. Acta, Mol. Cell Res. 1763, 1453. (38) Yurimoto, H. (2009) Molecular Basis of Methanol-Inducible Gene Expression and Its Application in the Methylotrophic Yeast Candida boidinii. Biosci., Biotechnol., Biochem. 73, 793−800. (39) Vogl, T., and Glieder, A. (2013) Regulation of Pichia pastoris promoters and its consequences for protein production. New Biotechnol. 30, 385−404. (40) Hartner, F. S., and Glieder, A. (2006) Regulation of methanol utilisation pathway genes in yeasts. Microb. Cell Fact. 5, 39−59. (41) Prielhofer, R., Cartwright, S. P., Graf, A. B., Valli, M., Bill, R. M., Mattanovich, D., and Gasser, B. (2015) Pichia pastoris regulates its gene-specific response to different carbon sources at the transcriptional, rather than the translational, level. BMC Genomics 16, 1−17. (42) De Schutter, K., Lin, Y.-C., Tiels, P., Van Hecke, A., Glinka, S., Weber-Lehmann, J., Rouzé, P., Van de Peer, Y., and Callewaert, N. (2009) Genome sequence of the recombinant protein production host Pichia pastoris. Nat. Biotechnol. 27, 561−6. (43) Küberl, A., Schneider, J., Thallinger, G. G., Anderl, I., Wibberg, D., Hajek, T., Jaenicke, S., Brinkrolf, K., Goesmann, A., Szczepanowski, R., Pühler, A., Schwab, H., Glieder, A., and Pichler, H. (2011) Highquality genome sequence of Pichia pastoris CBS7435. J. Biotechnol. 154, 312−20. (44) Mattanovich, D., Graf, A., Stadlmann, J., Dragosits, M., Redl, A., Maurer, M., Kleinheinz, M., Sauer, M., Altmann, F., and Gasser, B. (2009) Genome, secretome and glucose transport highlight unique features of the protein production host Pichia pastoris. Microb. Cell Fact. 8, 29. (45) Liang, S., Wang, B., Pan, L., Ye, Y., He, M., Han, S., Zheng, S., Wang, X., and Lin, Y. (2012) Comprehensive structural annotation of Pichia pastoris transcriptome and the response to various carbon sources using deep paired-end RNA sequencing. BMC Genomics 13, 738. (46) Sauer, M., Branduardi, P., Gasser, B., Valli, M., Maurer, M., Porro, D., and Mattanovich, D. (2004) Differential gene expression in recombinant Pichia pastoris analysed by heterologous DNA microarray hybridisation. Microb. Cell Fact. 3, 17−30. (47) Vanz, A. L., Nimtz, M., and Rinas, U. (2014) Decrease of UPRand ERAD-related proteins in Pichia pastoris during methanol-induced secretory insulin precursor production in controlled fed-batch cultures. Microb. Cell Fact. 13, 23. (48) Vanz, A. L., Lünsdorf, H., Adnan, A., Nimtz, M., Gurramkonda, C., Khanna, N., and Rinas, U. (2012) Physiological response of Pichia pastoris GS115 to methanol-induced high level production of the Hepatitis B surface antigen: catabolic adaptation, stress responses, and autophagic processes. Microb. Cell Fact. 11, 103. (49) van Zutphen, T., Baerends, R. J. S., Susanna, K. A., de Jong, A., Kuipers, O. P., Veenhuis, M., and van der Klei, I. J. (2010) Adaptation of Hansenula polymorpha to methanol: a transcriptome analysis. BMC Genomics 11, 1. (50) Ravin, N. V, Eldarov, M. A., Kadnikov, V. V, Beletsky, A. V, Schneider, J., Mardanova, E. S., Smekalova, E. M., Zvereva, M. I., Dontsova, O. A., Mardanov, A. V, and Skryabin, K. G. (2013) Genome sequence and analysis of methylotrophic yeast Hansenula polymorpha DL1. BMC Genomics 14, 837. (51) Yurimoto, H., Komeda, T., Lim, C. R., Nakagawa, T., Kondo, K., Kato, N., and Sakai, Y. (2000) Regulation and evaluation of five methanol-inducible promoters in the methylotrophic yeast Candida boidinii. Biochim. Biophys. Acta, Gene Struct. Expression 1493, 56−63.

(52) Yano, T., Takigami, E., Yurimoto, H., and Sakai, Y. (2009) Yap1-regulated glutathione redox system curtails accumulation of formaldehyde and reactive oxygen species in methanol metabolism of Pichia pastoris. Eukaryotic Cell 8, 540−9. (53) Yano, T., Yurimoto, H., and Sakai, Y. (2009) Activation of the oxidative stress regulator PpYap1 through conserved cysteine residues during methanol metabolism in the yeast Pichia pastoris. Biosci., Biotechnol., Biochem. 73, 1404−11. (54) Rußmayer, H., Buchetics, M., Gruber, C., Valli, M., Grillitsch, K., Modarres, G., Guerrasio, R., Klavins, K., Neubauer, S., Drexler, H., Steiger, M., Troyer, C., Al Chalabi, A., Krebiehl, G., Sonntag, D., Zellnig, G., Daum, G., Graf, A. B., Altmann, F., Koellensperger, G., Hann, S., Sauer, M., Mattanovich, D., and Gasser, B. (2015) Systemslevel organization of yeast methylotrophic lifestyle. BMC Biol. 13, 80. (55) Vogl, T., Thallinger, G. G., Zellnig, G., Drew, D., Cregg, J. M., Glieder, A., and Freigassner, M. (2014) Towards improved membrane protein production in Pichia pastoris: general and specific transcriptional response to membrane protein overexpression. New Biotechnol. 31, 538−52. (56) Tatusov, R. L., Galperin, M. Y., Natale, D. a, and Koonin, E. V. (2000) The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 28, 33−6. (57) Gasser, B., Prielhofer, R., Marx, H., Maurer, M., Nocon, J., Steiger, M., Puxbaum, V., Sauer, M., and Mattanovich, D. (2013) Pichia pastoris: protein production host and model organism for biomedical research. Future Microbiol. 8, 191−208. (58) Leao-Helder, A. N., Krikken, A. M., van der Klei, I. J., Kiel, J. a K. W., and Veenhuis, M. (2003) Transcriptional down-regulation of peroxisome numbers affects selective peroxisome degradation in Hansenula polymorpha. J. Biol. Chem. 278, 40749−56. (59) Prielhofer, R., Maurer, M., Klein, J., Wenger, J., Kiziak, C., Gasser, B., and Mattanovich, D. (2013) Induction without methanol: novel regulated promoters enable high-level expression in Pichia pastoris. Microb. Cell Fact. 12, 5. (60) Ellis, S. B., Brust, P. F., Koutz, P. J., Waters, A. F., Harpold, M. M., and Gingeras, T. R. (1985) Isolation of alcohol oxidase and two other methanol regulatable genes from the yeast Pichia pastoris. Mol. Cell. Biol. 5, 1111−21. (61) Cregg, J. M., Madden, K. R., Barringer, K. J., Thill, G. P., and Stillman, C. A. (1989) Functional characterization of the two alcohol oxidase genes from the yeast Pichia pastoris. Mol. Cell. Biol. 9, 1316− 23. (62) Kristiansson, E., Thorsen, M., Tamás, M. J., and Nerman, O. (2009) Evolutionary forces act on promoter length: identification of enriched cis-regulatory elements. Mol. Biol. Evol. 26, 1299−307. (63) Weis, R., Luiten, R., Skranc, W., Schwab, H., Wubbolts, M., and Glieder, A. (2004) Reliable high-throughput screening with Pichia pastoris by limiting yeast cell death phenomena. FEMS Yeast Res. 5, 179−89. (64) Tschopp, J. F., Brust, P. F., Cregg, J. M., Stillman, C. A., and Gingeras, T. R. (1987) Expression of the lacZ gene from two methanol-regulated promoters in Pichia pastoris. Nucleic Acids Res. 15, 3859−76. (65) Ruth, C., Zuellig, T., Mellitzer, A., Weis, R., Looser, V., Kovar, K., and Glieder, A. (2010) Variable production windows for porcine trypsinogen employing synthetic inducible promoter variants in Pichia pastoris. Syst. Biol. Synth. Biol. 4, 181−91. (66) Xuan, Y., Zhou, X., Zhang, W., Zhang, X., Song, Z., and Zhang, Y. (2009) An upstream activation sequence controls the expression of AOX1 gene in Pichia pastoris. FEMS Yeast Res. 9, 1271−82. (67) Vogl, T., Ruth, C., Pitzer, J., Kickenweiz, T., and Glieder, A. (2014) Synthetic Core Promoters for Pichia pastoris. ACS Synth. Biol. 3, 188−91. (68) Mattanovich, D., Gasser, B., Hohenblum, H., and Sauer, M. (2004) Stress in recombinant protein producing yeasts. J. Biotechnol. 113, 121−35. (69) Gurvitz, A., Hiltunen, J. K., Erdmann, R., Hamilton, B., Hartig, A., Ruis, H., and Rottensteiner, H. (2001) Saccharomyces cerevisiae 185


Research Article

ACS Synthetic Biology Adr1p governs fatty acid beta-oxidation and peroxisome proliferation by regulating POX1 and PEX11. J. Biol. Chem. 276, 31825−30. (70) Lee, J., Godon, C., Lagniel, G., Spector, D., Garin, J., Labarre, J., and Toledano, M. B. (1999) Yap1 and Skn7 control two specialized oxidative stress response regulons in yeast. J. Biol. Chem. 274, 16040− 6. (71) Rumjantsev, A. M., Padkina, M. V., and Sambuk, E. V. (2013) Effect of nitrogen source on gene expression of first steps of methanol utilization pathway in Pichia pastoris. Russ. J. Genet. 49, 394−400. (72) Hahn, S., and Young, E. T. (2011) Transcriptional regulation in Saccharomyces cerevisiae: transcription factor regulation and function, mechanisms of initiation, and roles of activators and coactivators. Genetics 189, 705−36. (73) Basehoar, A. D., Zanton, S. J., and Pugh, B. F. (2004) Identification and distinct regulation of yeast TATA box-containing genes. Cell 116, 699−709. (74) Näaẗ saari, L., Mistlberger, B., Ruth, C., Hajek, T., Hartner, F. S., and Glieder, A. (2012) Deletion of the Pichia pastoris KU70 homologue facilitates platform strain generation for gene expression and synthetic biology. PLoS One 7, e39720. (75) Chen, S., Reger, R., Miller, C., and Hyman, L. E. (1996) Transcriptional terminators of RNA polymerase II are associated with yeast replication origins. Nucleic Acids Res. 24, 2885−93. (76) Shalem, O., Carey, L., Zeevi, D., Sharon, E., Keren, L., Weinberger, A., Dahan, O., Pilpel, Y., and Segal, E. (2013) Measurements of the impact of 3′ end sequences on gene expression reveal wide range and sequence dependent effects. PLoS Comput. Biol. 9, e1002934. (77) Lee, P. C., Yoon, Y. G., and Schmidt-Dannert, C. (2009) Investigation of cellular targeting of carotenoid pathway enzymes in Pichia pastoris. J. Biotechnol. 140, 227−33. (78) Wilson, S. A., and Roberts, S. C. (2014) Metabolic engineering approaches for production of biochemicals in food and medicinal plants. Curr. Opin. Biotechnol. 26, 174−82. (79) Yoon, S.-H., Lee, S.-H., Das, A., Ryu, H.-K., Jang, H.-J., Kim, J.Y., Oh, D.-K., Keasling, J. D., and Kim, S.-W. (2009) Combinatorial expression of bacterial whole mevalonate pathway for the production of beta-carotene in E. coli. J. Biotechnol. 140, 218−26. (80) Alper, H., Miyaoku, K., and Stephanopoulos, G. (2005) Construction of lycopene-overproducing E. coli strains by combining systematic and combinatorial gene knockout targets. Nat. Biotechnol. 23, 612−6. (81) Lee, P. C., Momen, A. Z. R., Mijts, B. N., and Schmidt-Dannert, C. (2003) Biosynthesis of structurally novel carotenoids in Escherichia coli. Chem. Biol. 10, 453−62. (82) Verwaal, R., Wang, J., Meijnen, J. P., Visser, H., Sandmann, G., Van Den Berg, J. A., and Van Ooyen, A. J. J. (2007) High-level production of beta-carotene in Saccharomyces cerevisiae by successive transformation with carotenogenic genes from Xanthophyllomyces dendrorhous. Appl. Environ. Microbiol. 73, 4342−50. (83) Cregg, J. M., Tolstorukov, I., Kusari, A., Sunga, J., Madden, K., and Chappell, T. (2009) Expression in the yeast Pichia pastoris. Methods Enzymol. 463, 169−89. (84) López, J., Essus, K., Kim, I.-K., Pereira, R., Herzog, J., Siewers, V., Nielsen, J., and Agosin, E. (2015) Production of β-ionone by combined expression of carotenogenic and plant CCD1 genes in Saccharomyces cerevisiae. Microb. Cell Fact. 14, 84. (85) Li, Q., Sun, Z., Li, J., and Zhang, Y. (2013) Enhancing betacarotene production in Saccharomyces cerevisiae by metabolic engineering. FEMS Microbiol. Lett. 345, 94. (86) Davidi, L., Levin, Y., Ben-Dor, S., and Pick, U. (2015) Proteome analysis of cytoplasmatic and plastidic beta-carotene lipid droplets in Dunaliella bardawil. Plant Physiol. 167, 60−79. (87) Kranthi, B. V., Kumar, R., Kumar, N. V., Rao, D. N., and Rangarajan, P. N. (2009) Identification of key DNA elements involved in promoter recognition by Mxr1p, a master regulator of methanol utilization pathway in Pichia pastoris. Biochim. Biophys. Acta, Gene Regul. Mech. 1789, 460−8.

(88) Kranthi, B. V., Kumar, H. R. V., and Rangarajan, P. N. (2010) Identification of Mxr1p-binding sites in the promoters of genes encoding dihydroxyacetone synthase and peroxin 8 of the methylotrophic yeast Pichia pastoris. Yeast 27, 705−11. (89) Geier, M., Braun, A., Emmerstorfer, A., Pichler, H., and Glieder, A. (2012) Production of human cytochrome P450 2D6 drug metabolites with recombinant microbes - a comparative study. Biotechnol. J. 7, 1346−58. (90) Gudiminchi, R. K., Geier, M., Glieder, A., and Camattari, A. (2013) Screening for cytochrome P450 expression in Pichia pastoris whole cells by P450-carbon monoxide complex determination. Biotechnol. J. 8, 146−52. (91) Vogl, T., Ahmad, M., Krainer, F. W., Schwab, H., and Glieder, A. (2015) Restriction site free cloning (RSFC) plasmid family for seamless, sequence independent cloning in Pichia pastoris. Microb. Cell Fact. 14, 103. (92) Wriessnegger, T., Gübitz, G., Leitner, E., Ingolic, E., Cregg, J., de la Cruz, B. J., and Daum, G. (2007) Lipid composition of peroxisomes from the yeast Pichia pastoris grown on different carbon sources. Biochim. Biophys. Acta, Mol. Cell Biol. Lipids 1771, 455−61. (93) Krainer, F. W., Capone, S., Jäger, M., Vogl, T., Gerstmann, M., Glieder, A., Herwig, C., and Spadiut, O. (2015) Optimizing cofactor availability for the production of recombinant heme peroxidase in Pichia pastoris. Microb. Cell Fact. 14, 4. (94) Lin-Cereghino, J., Wong, W. W., Xiong, S., Giang, W., Luong, L. T., Vu, J., Johnson, S. D., and Lin-Cereghino, G. P. (2005) Condensed protocol for competent cell preparation and transformation of the methylotrophic yeast Pichia pastoris. BioTechniques 38, 44. (95) Viader-Salvadó, J. M., Cab-Barrera, E. L., Galán-Wong, L. J., and Guerrero-Olazarán, M. (2006) Genotyping of recombinant Pichia pastoris strains. Cell. Mol. Biol. Lett. 11, 348−59. (96) Hellwig, S., Robin, F., Drossard, J., Raven, N. P., VaqueroMartin, C., Shively, J. E., and Fischer, R. (1999) Production of carcinoembryonic antigen (CEA) N-A3 domain in Pichia pastoris by fermentation. Biotechnol. Appl. Biochem. 30, 267−75. (97) Näaẗ saari, L., Krainer, F. W., Schubert, M., Glieder, A., and Thallinger, G. G. (2014) Peroxidase gene discovery from the horseradish transcriptome. BMC Genomics 15, 227.

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