A Modular Toolkit for Generating Pichia pastoris ... - ACS Publications

Mar 2, 2017 - MIT Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States. ∇. Fraunhofer IGB,...
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A Modular Toolkit for Generating Pichia pastoris Secretion Libraries Ulrike Obst,†,§,#,⊗ Timothy K. Lu,‡,§,∥,⊥,# and Volker Sieber*,†,¶,∇,⊗ †

Chair of Chemistry for Biogenic Resources, Technical University of Munich, 94315 Straubing, Germany Catalysis Research Center, Technical University of Munich, 85748 Garching, Germany ‡ Biophysics Program, Harvard University, Cambridge, Massachusetts 02138, United States § Department of Electrical Engineering & Computer Science, ∥Department of Biological Engineering, ⊥Microbiology Program, and # MIT Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States ∇ Fraunhofer IGB, Straubing Branch Bio, Electro, and Chemocatalysis BioCat, 94315 Straubing, Germany ⊗ Straubing Centre of Science, 94315 Straubing, Germany ¶

S Supporting Information *

ABSTRACT: Yeasts are powerful eukaryotic hosts for the production of recombinant proteins due to their rapid growth to high cell densities and ease of genetic modification. For large-scale industrial production, secretion of a protein offers the advantage of simple and efficient downstream purification that avoids costly cell rupture, denaturation and refolding. The methylotrophic yeast Pichia pastoris (Komagataella phaf f i) is a well-established expression host that has the ability to perform post-translational modifications and is generally regarded as safe (GRAS). Nevertheless, optimization of protein secretion in this host remains a challenge due to the multiple steps involved during secretion and a lack of genetic tools to tune this process. Here, we developed a toolkit of standardized regulatory elements specific for Pichia pastoris allowing the tuning of gene expression and choice of protein secretion tag. As protein secretion is a complex process, these parts are compatible with a hierarchical assembly method to enable the generation of large and diverse secretion libraries in order to explore a wide range of secretion constructs, achieve successful secretion, and better understand the regulatory factors of importance to specific proteins of interest. To assess the performance of these parts, we built and characterized the expression and secretion efficiency of 124 constructs that combined different regulatory elements with two fluorescent reporter proteins (RFP, yEGFP). Intracellular expression from our promoters was comparatively independent of whether RFP or yEGFP, and whether plasmid-based expression or genomically integrated expression, was used. In contrast, secretion efficiency significantly varied for different genes expressed using identical regulatory elements, with differences in secretion efficiency of >10-fold observed. These results highlight the importance of generating diverse secretion libraries when searching for optimal expression conditions, and demonstrate that our toolkit is a valuable asset for the creation of efficient microbial cell factories. KEYWORDS: secretion, high-throughput, synthetic biology, yeast, Pichia pastoris

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creating novel organisms with useful characteristics.8,9 This approach is founded upon the idea that biological systems can be broken down into functional parts that can be reassembled in a modular way to generate new functionalities. To be able to achieve these functions, parts must be well-characterized for a particular host.10,11 To date, large libraries of genetic parts have been created to allow for fine control of gene expression.12 These include regulatory elements such as promoters,13,14 terminators15 and ribosome binding sites.16 The most widely used hosts for industrial production are the bacterium Escherichia coli and the yeast Saccharomyces cerevisiae.7 Although the majority of synthetic biology tools have been developed for E. coli,17 there are many advantages associated with yeast and

he engineering of microbes to act as cell factories has enabled the production of fuels, pharmaceuticals and fine chemicals in a sustainable and clean manner.1,2 Proteins, such as enzymes or therapeutic agents, are important industrial products. Although many have been successfully expressed using microbes, developing an efficient and robust production system can be time-consuming and costly.3,4 Difficulties stem from each protein being structurally unique with distinct conditions or types of host required to optimize expression.5 An important consideration in this process is balancing the burden of product formation and host vitality. This requires careful tuning of expression and thus well characterized genetic parts and tools.2,3,6,7 Furthermore, to ensure broad utility, a host should have well understood cell biology and robust growth under industrial fermentation conditions.1 The field of synthetic biology attempts to apply engineering principles or processes to biological systems with the aim of © 2017 American Chemical Society

Received: November 8, 2016 Published: March 2, 2017 1016

DOI: 10.1021/acssynbio.6b00337 ACS Synth. Biol. 2017, 6, 1016−1025

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Figure 1. Pichia pastoris protein secretion platform. (A) Proteins produced in P. pastoris may either be expressed intracellularly or secreted extracellularly. The secretion pathway offers the possibilities of protein modifications such as proteolytic maturation, glycosylation or disulfide bonds.50 (B) After P. pastoris transformation, high-throughput screening of expression construct libraries can be performed in 96-well plates to find the optimal expression constructs. (C) Standardized and combinatorial assembly strategy for designing expression vectors. Parts are defined by flanking overhangs and are flexible and interchangeable. (*) For intracellular protein expression the coding sequence must be designed as a part with type 3 to ensure the correct overhang to the previous part type 2. For protein secretion, the secretion signal (part type 3a) and the coding sequence (part type 3b) are needed. White boxes correspond to new Pichia toolkit elements developed in this study; gray shaded boxes are taken from the existing YTK.32

eukaryotic cells.1,18 Yeasts are an attractive host for industry as they perform post-translational modifications, enable reactions to be compartmentalized in subcellular organelles, and are less susceptible to infection by viruses.3,19 The methylotrophic yeast Pichia pastoris (also known as Komagataella phaf f i) is a nonconventional yeast that has seen increased interest in recent years. P. pastoris makes an ideal host as it is industrially established20 and combines the benefits of high cell density cultivation, efficient secretory capabilities, the ability to perform post-translational modifications to proteins, and genetic tractability. Furthermore, it is an approved host for biopharmaceutical production18,21 and is capable of humanized glycosylation patterns.22,23 So far, the majority of P. pastoris research has focused on glycoengineering, generation of synthetic promoters24 and various approaches to strain engineering.21,25 When producing a protein product, secretion significantly simplifies product purification and avoids expensive cell rupture, denaturation and refolding processes.26 In P. pastoris, purification can be further simplified because it secretes no

proteases and only a few endogenous proteins.18,27 Protein secretion is a complex process that requires multiple steps to process the coding DNA sequence to a mature active protein (Figure 1A). An N-terminal signal sequence of the nascent protein is necessary to direct the protein into the secretory pathway. First, the nascent protein is transferred through the membrane of the endoplasmatic reticulum (ER), either cotranslationally or post-translationally. In the ER, posttranslational modifications, such as glycosylation, protein folding, and peptide cleavage, occur. Subsequently, the protein is translocated into the Golgi apparatus to be further processed and finally it is sorted and released into the media.28,29 The capacity of the secretion machinery is the main bottleneck for protein secretion. Folded proteins are translocated into the ER, but cellular stress can lead to misfolding and nonactive products.30,31 Due to this multistep process, there are many potential variables that may require optimization if a secreted protein is required. However, there is little understanding of each variable’s role and no standardized toolkits to efficiently create diverse regulatory libraries to modulate secretion. This 1017

DOI: 10.1021/acssynbio.6b00337 ACS Synth. Biol. 2017, 6, 1016−1025

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When designing cassette plasmids for P. pastoris, some parts (assembly connectors and E. coli marker and origin) can be directly applied from the YTK. However, parts of the transcriptional unit as well as the marker and origin have to be designed specifically for the application in P. pastoris. We have developed 21 new part plasmids compatible with the YTK. This includes 17 P. pastoris specific control elements (4 promoters, 10 secretion tags, 1 terminator, and 2 origins of replication) as well as red fluorescent protein (RFP) and yeast enhanced green fluorescent protein (yEGFP) genes that can be expressed either intracellularly or secreted. DNA for these parts was obtained via PCR or synthesized and where necessary, BsmBI or BsaI restriction sites removed to ensure compatibility with the assembly method. These new P. pastoris parts, combined with our selection of tested and functional YTK parts in P. pastoris, offer the ability to express a gene of interest in 264 different ways (Figure 1C). By combining the P. pastoris parts with all YTK’s existing S. cerevisiae parts (that may also function in P. pastoris), over 4000 different possibilities could be obtained. We successfully applied regulatory elements from the S. cerevisiae YTK in P. pastoris, highlighting the flexible platform design that offers the potential for further extensions to other yeast hosts. The combinatorial possibilities increase even further when considering multigene expression cassettes.32 These multigene cassettes can open up opportunities for the coexpression of secretion-related proteins. The overexpression of chaperones, foldases and trafficking proteins may enhance secretion capacities by improving protein-trafficking for ER-toGolgi and Golgi-to-plasma membrane processes or by supporting the folding and modification processes in the ER.18,19 For the characterization of our new parts, we constructed 124 cassette plasmids (Supplementary Table S4). All part and cassette plasmids have been sequence verified (Supplementary Table S2) and part plasmids have been submitted to Addgene for distribution. Characterization of Promoter Strengths. Strong production of a protein requires precise tuning of gene expression. Promoter elements that control the rate of transcription initiation are important to this process. When choosing a suitable promoter, many intrinsic properties need to be considered. These include: whether the promoter is constitutive or inducible, inducer concentrations that are necessary for activation, the promoter’s leakiness when inactive and overall promoter strength (e.g., induced expression foldchange).10 Furthermore, the gene itself may have toxic effects on the host, making selection of appropriate expression strength critical for successful expression and cell vitality. We developed four new promoter parts compatible with the YTK that are specific for P. pastoris.37 These included the widely used, strong and tightly regulated methanol inducible promoter of the alcohol oxidase gene (pAOX1), and constitutive promoters from the glyceraldehyde-3-phosphate dehydrogenase (pGAP), enolase (pENO1), and triose phosphate isomerase (pTPI1) genes. Selection was done to cover a broad range of expression levels (Supplementary Table S1). In addition, two existing YTK promoters from S. cerevisiae were included that have previously been reported to successfully drive gene expression in P. pastoris38 (promoters for the translation elongation factor (pTEF1) and 3phosphoglycerate kinase (pPGK1) genes). To ensure efficient termination of transcription, which can also affect gene expression level, we constructed a new terminator part taken

has led to challenges in the use of secretion due to an inability to compete with intracellular systems.26 Here, we address this problem by developing a set of genetic parts to control transcription, translation and protein secretion in P. pastoris that are compatible with an existing standardized assembly method.32 This forms the first such library of its type for P. pastoris, thus enabling the efficient generation of large numbers of expression cassettes to explore optimal vector design. We have developed 17 control elements (4 promoters, 10 secretion tags, 1 terminator, and 2 origins of replication) specific for P. pastoris, which, when combined with existing S. cerevisiae parts,32 allow for a gene of interest to be expressed in over 4000 different ways. As there is a limited supply of secretion tags, we constructed 7 synthetic hybrid tags that are designed to have variable signal peptides, but still ensure full cleavage of the tag during secretion. We characterized the effectiveness of this library-based approach by using two fluorescent proteins as our genes of interest. This enabled quantification of intra- and extracellular protein concentrations, and thus, a more direct assessment of secretion efficiency. We found that promoters driving intracellular protein expression for the two fluorescent reporters displayed strengths that were relatively independent of the coding sequence. However, protein secretion was found to be rather unpredictable, varying with the promoter, secretion tag and gene of interest used.



RESULTS AND DISCUSSION A Toolkit for the High-Throughput Construction of P. pastoris Expression Vectors. Genetic parts often have varying performance when used in different contexts,33,34 which makes it difficult to predict the parts necessary to achieve optimal expression for a particular gene of interest. Highthroughput screens are widely employed in bacterial systems to tackle this problem and explore many different combinations of genetic parts to tune gene expression. In contrast, yeast expression libraries are relatively small, having limited diversity in their sequence and functionality.11 This has hampered the ability for effective screenings using these organisms. Here, we address this issue by extending the Yeast Toolkit32 (YTK) and constructing a set of additional elements compatible with P. pastoris that focus on the control of protein secretion (Figure 1B). This broadens the potential applications of the YTK by making it compatible with a new type of host and including a new functional element. The YTK was originally developed for S. cerevisiae to offer a simple and robust method for hierarchical bottom-up design and construction of expression vectors. It consists of 96 “part plasmids” that encode the basic elements of the expression vector. These are combined to produce “cassette plasmids” that contain elements necessary to express a single gene, and optionally, these can be assembled into “multigene plasmids” that encode an entire metabolic pathway or genetic circuit. The assembly method relies on MoClo35,36 using Type IIs restriction enzymes. A core feature of the YTK is a carefully defined structure of 8 primary encoding parts which combine to produce a functional plasmid. Three of the parts are transcriptional units (TUs) comprising of a promoter, gene of interest and terminator, which allow the fine-tuning of gene expression. Five other types of parts control aspects such as the position of integration in the yeast genome or E. coli marker and origin (see Figure 1C).32 Furthermore, several of these types of parts can be split into subparts to allow for cases where tags may need to be appended (e.g., His-tagged coding regions). 1018

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Figure 2. Characterization of constitutive promoters. (A) Design of characterization construct. Black part names correspond to new elements; gray shaded parts are taken from the YTK. (B) The relative strength of 6 promoters was evaluated for intracellular RFP and yEGFP expression, either genomically integrated or expressed from a plasmid. Three biological replicates were analyzed and the mean fluorescence normalized to the OD600 is presented with error bars that denote ±1 standard deviation. Characterization was performed in 1% BMM for pAOX1 and 1% BMD for all other constitutive promoters.

Figure 3. Characterization of the methanol-inducible pAOX1 promoter. (A) Design of pAOX1 promoter characterization constructs. All parts used are from this study. (B) The relative strength of the pAOX1 promoter under varying methanol concentrations was evaluated. RFP and yEGFP were expressed either from the genomically integrated or the plasmid-based construct. Sampling was performed at three different time points: 24 h (circle, light red/green/gray), 48 h (square, medium red/green/gray) and 72 h (triangle, dark red/green/gray). Total fluorescence in arbitrary units as well as the corresponding OD600 is shown. Three biological replicates were analyzed with the mean shown and error bars denoting ±1 standard deviation.

from the alcohol oxidase gene (tAOX1) of P. pastoris. To vary the overall expression mode, we also examined gene expression either from a genomically integrated construct (attB) or plasmid-based expression system (PARS) (see below for details). The strength of promoters in S. cerevisiae, in contrast to bacteria, are mostly independent of the downstream coding region.39 To verify this for P. pastoris, we tested each promoter expressing two different fluorescent reporter genes (RFP and yEGFP, intracellular variants) (Figure 2A). Promoter strength was determined from bulk fluorescence measurements from a plate reader (Materials and Methods). Promoter strengths were found to span over 3 orders of magnitude. As shown for S. cerevisiae,39 expression from genomically integrated constructs was relatively independent of downstream sequence context, with both RFP and yEGFP genes showing a similar ranking of expression levels. For plasmid-based constructs,

promoters also displayed similar rankings of strength for RFP and yEGFP (Figure 2B). However, weaker promoters had a tendency for stronger production of RFP when genomically integrated, and the weak pPGK1, pENO1 and pTPI1 promoters showed higher overall RFP and yEGFP expression when expressed from a plasmid. pAOX1 is one of the most commonly used inducible promoter systems in P. pastoris.37 It is strongly induced in the presence of methanol and repressed in the presence of glucose, glycerol or ethanol.27 We tested varying methanol concentrations and expression times to optimize protein expression (Figure 3). Methanol was the sole carbon source and its concentration was found to strongly influence cell growth. High methanol concentrations were found to be toxic, leading to decreased cell growth (Figure 3B,C). The highest OD600 was reached for all constructs at a 2% methanol concentration and after 72 h. Highest fluorescence levels were reached at 2% 1019

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Figure 4. Design of synthetic secretion signal peptides. (A) Overall structure of the α-mating factor secretion signal. The secretion signal is composed of a pre- and pro-region. The preregion interacts with the signal recognition particle to guide the protein into the ER. It consists of a basic amino terminus, a hydrophobic core as well as a polar region at the carboxy terminus. The preregion is cleaved off by signal peptidases. The proregion slows down transport to ensure proper protein folding and is thought to be important for the transport from the ER to the Golgi. It consists of hydrophobic amino acids, which are interrupted by charged or polar amino acids. The pro-region is cleaved at the dibasic KR site by the endoprotease KEX2 and the two EA repeats are removed by the STE13 dipeptidy amino peptidase.49,50,61 The STE13 cleavage is often problematic and results in a non-native amino acid sequence at the N-terminus of the heterologous protein.51 The αMF_no_EAEA sequence is the same as the αMF sequence except that the EAEA amino acids at the C-terminus are removed. (B) Design of new secretion tags. The newly designed tags were composed of a varying amino terminus followed by a deletion mutant of the α-mating factor.49

technology for P. pastoris allowing marker-less genome engineering. This could be used in place of our recombinasebased system to allow for insertion of the secretion cassette at virtually any desired genomic locus with high efficiency. For promoter characterization, we additionally performed plasmidbased expression using the Pichia Autonomous Replication Sequence (PARS).40 For both methods, no vector linearization was required. Transformation efficiency was approximately 102 transformants/μg DNA for recombinase-based genomic integration and 2 × 102 transformants/μg DNA for plasmidbased constructs. This is significantly below 105 transformants/ μg DNA as described by Cregg,40 but is sufficiently efficient for most tasks and allows for precise integration into the genome. All transformants were PCR verified. For genomically integrated constructs, primers spanning the defined BxbI locus were applied. For PARS-based constructs, primers within the expression construct were used. Design of Synthetic Secretion Signal Peptides. The overproduction of recombinant proteins can be challenging if ER folding and secretion capacity are overloaded. This can lead to the accumulation of misfolded or unfolded protein and consequently to cellular stress and low protein production yields.45 To overcome secretory bottlenecks and enhance secretion strength, optimization of the secretion signal or overexpression of translocon components and stabilizing cytosolic chaperones can be performed.31 The only requirement for a protein to enter the secretion pathway is a secretion signal peptide to be present at the Nterminus of the nascent polypeptide.45,46 A schematic overview of the secretion pathway is shown in Figure 1A. The secretion efficiency of a recombinant protein fused to a given signal peptide can differ strongly even for similar genes with only small differences in protein sequence, structure or gene expression regulation.45 Our toolkit allows for the rapid testing

methanol and 72 h expression time for the genomically integrated RFP (837 ± 113 a.u.) and yEGFP (776 ± 124 a.u.), and the plasmid-based yEGFP (496 ± 72 a.u.). RFP expression from plasmids was highest at 1% methanol at 72 h (187 ± 11 a.u.). Genomic integration was found to generally lead to higher expression levels than for plasmid-based expression. Transformation of Pichia pastoris. High-throughput screening methods rely on efficient transformation strategies to ensure that a large portion of the potential range of designs can be tested. In general, yeast transformations have a significantly lower transformation efficiency (P. pastoris 103− 105 transformants/μg DNA40) in comparison to E. coli (109− 1010 transformants/μg DNA41). This can become a limiting factor for the generation of libraries. For P. pastoris, expression can either be plasmid-based or from a genomically integrated gene of interest. Even though transformation efficiency of plasmid systems is one to 2 orders of magnitude higher than integrations, the latter is usually preferred as it is more stable.25,40 Several transformation methods are available: spheroplast generation,40 electroporation or polyethylene glycol (PEG) treatment.42 Integration of a construct into the genome is based on homologous recombination (HR) and nonhomologous end joining (NHEJ), but integration frequencies are low and random integration of DNA fragments are problematic. Näaẗ saari et al.25 developed a P. pastoris ku70 deletion strain with increased HR rates, but growth rates were 10−30% lower depending on the carbon source used and linearization of the vector is still necessary. Here, we used a P. pastoris strain containing a attP site,43 which enables precise single-copy insertion of plasmid DNA into a known genomic region via BxbI recombinasemediated integration. Therefore, the cassette plasmid encoding the genetic construct of interest and the attB site was cotransformed with a plasmid for the transient expression of BxbI. Recently, Weninger et al.44 established the CRISPR/Cas9 1020

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Figure 5. Characterization of secretion tags. (A) Vector design for secretion analysis. Ten different secretion tags, as well as the intracellular variant, for fluorescent reporter expression were analyzed under the control of 5 different promoters. White boxes correspond to new elements developed in this study; gray shaded boxes are taken from existing YTK. (B) For all samples, the total fluorescence as well as the fluorescence of the supernatant after centrifugation was determined. The characterization was performed in 1% BMM for all pAOX1 constructs and in 1% BMD for all constitutive constructs. (C) Bars represent the mean fluorescence of three biological replicates normalized to OD600 (a.u./OD600). Error bars denote ±1 standard deviation.

Kex2p recognition site.51 Additionally, to prevent the tag from being too long, we used a double deletion variant of the αmating factor that has been previously shown to have higher cleavage activity in comparison to the full length α-mating factor secretion peptide.49 We also included different modified signal peptides of the α-mating factor. Characterization of Secretion Signal Peptides. To test the suitability of the library and the feasibility of our combinatorial approach in identifying optimal combinations of elements for protein secretion, we designed a library of 100 secretion constructs. By applying the hierarchical assembly method with the recombinase-based system for integration into a defined P. pastoris locus, we were able to produce this library in a matter of weeks. If we had instead used more common P. pastoris cloning methods,25,52 the same library would have taken months to complete. We used RFP and yEGFP as reporters to allow for accurate but indirect measurement of protein levels being expressed intracellularly or secreted (Figure 5). For each reporter, we analyzed our 10 different signal peptides, each under the control of 5 different promoters. Characterization was performed in 1% BMM (Buffered Minimal Methanol) for all pAOX1 constructs and in 1% BMD (Buffered Minimal Dextrose) for all constitutive constructs. Results of overall expression and secretion efficiency are shown in Figure 5C. First, bulk measurements of the total fluorescence from a well were taken. Next, the cells were spun

of multiple combinations of 5 promoters and 10 secretion tags, to find optimal secretion conditions. The recognition of the secretion tag has a high degree of flexibility. A study where random sequence modifications were performed on the invertase signal sequence showed that 20% of the signal peptides were still recognized.47 Even though signal peptides appear to have a simple structure with interchangeable domains and a low information content, even minor variations can affect protein targeting, translocation, signal sequence cleavage and further postcleavage processes.48 The most commonly used signal peptide is the S. cerevisiae αmating factor (αMF) (Figure 4A). To enhance efficiency of the secretion tag, various studies have been performed. Random mutagenesis of single amino acid substitution did not show positive influence.49 Site-directed mutagenesis and the generation of deletion mutants gave higher activities of the horseradish peroxidase (HRP) reporter protein.49 Also, alternative signal sequences, including invertase, inulinase or glucoamylase signal peptides, are available (Figure 4B; Supplementary Table S1).50 We designed synthetic secretion tags by combining established leader sequences (N-terminal) with an optimized α-mating factor secretion tag (C-terminal) (Figure 4B). Modulation in the N-terminal region was expected to influence the signal recognition. As the Ste13p cleavage is often problematic, we designed the C-terminus to end at the 1021

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ACS Synthetic Biology Table 1. Secretion Efficiency for Combinations of Tags, Promoters and Genes after 48 h RFP secretion tag

pAOX1

pGAP

None αMFΔ Invertase-αMFΔ Killer-αMFΔ Glucoamylase-αMFΔ αMF αMFΔ_no_Kex αMF_no_EAEA SA-αMFΔ Inulinase-αMFΔ αAmylase-αMFΔ

0.01 0.04 0.02 0.02 0.02 0.87 0.01 0.92 0.38 0.25

0.02 0.02 0.01 0.01

pENO1

pPGK1

pAOX1

0.38

0.52

0.08 0.33 0.04

0.06 0.19 0.12 0.13 0.12 0.75 0.11 0.77 0.59 0.53 0.71

0.04 0.88

0.78 0.37

yEGFP

pTEF1

0.01 0.60

0.72

0.78 0.13 0.13

0.81 0.81

0.02

pGAP

pTEF1

pENO1

pPGK1

0.44

0.79

0.47

0.02

0.78 0.02 0.67

0.44

our findings do clearly highlight the importance of testing multiple tags when designing new secretion constructs. Effect of Methanol on Protein Secretion. An interesting result from the characterization of the secretion tags was that while the two strongest promoters, pAOX1 and pGAP, were found to produce similar total amounts of protein, pAOX1 displayed significantly higher levels of secretion. This was puzzling because the protein itself should have been constant, and thus, similar secretion was expected. A potential cause for this difference could be the use of BMM media for the inducible pAOX1 promoter, which could affect normal cell physiology, versus the use of BMD media for pGAP. In comparison to glucose utilization, growth on methanol has high oxygen demands that can be critical for high cell density cultivation.54,55 To understand whether higher fluorescent titers arose from the secretion construct itself or resulted from differences in media, we further analyzed all pGAP expression constructs in 1% BMM media (Supplementary Figure S1). Overall cell growth was significantly higher in BMD (OD600 of 4.6−6.1) than in BMM (OD600 of 1.7−2.3), which led to overall higher fluorescence. However, fluorescence normalized to the OD600 was higher in BMM. Importantly, the fraction of secreted protein compared to the overall expressed protein was much higher for samples grown in BMM. The choice of carbon source has a strong impact on the metabolism of recombinant strains as it can result in different biomass yields and product concentrations. Prielhofer et al.56 analyzed the gene-specific response of P. pastoris to varying carbon sources and showed an upregulation of genes involved in protein production for cells grown on methanol compared to glycerol. Their study revealed that the power of methanol induction is not only due to the strong pAOX1 promoter itself but it is also linked to differential growth effects of methanol. To achieve strong secretion, central energy metabolism, the additional burden of heterologous protein production and the capacity of the secretory machinery must be balanced.30,57 Therefore, the characterization of genetic constructs must account for cultivation conditions in addition to regulatory elements. Growth on glucose allowed for higher specific growth rates and higher overall product titers while growth on methanol enabled fine-tuning and higher secretory capacity.27 P. pastoris is a widely used host for secretion of heterologous proteins because of few contaminants of host cell protein. Furthermore, the majority of P. pastoris expression processes utilize methanol as a substrate and inducer because it offers tight gene regulation and high product titers. However,

down and pelleted and the supernatant was remeasured to provide the secreted level. The secretion efficiency Se was then calculated as Se = Ss/St, where St is the total fluorescence measurement of the cells in culture in arbitrary units (a.u.), and Ss is the fluorescence measurement from the supernatant in a.u. The value of Se ranges from 0, when no protein is secreted, to 1, when all protein is secreted (Table 1). Even though RFP and yEGFP are both beta-barrel proteins,53 their secretion was found to differ when expressed from identical regulatory elements. Furthermore, high overall protein expression did not necessarily result in high protein secretion. The most commonly used secretion tags are the αMF and its derivative, αMF_no_EAEA, in which the EA repeat is removed. Using these secretion tags generally led to the largest amount of secretion, especially for RFP, while for yEGFP secretion exhibited a rather reduced dependence on the tag used. Remarkably, we found that using these secretion tags was either highly efficient, with almost all of the expressed protein being secreted, or there was no detectable protein expression. The αMF and αMF_no_EAEA secretion tags guided RFP secretion very efficiently for all promoters (Se = 0.6−0.92) except for the combinations, pGAP-αMF and pENO-αMF_no_EAEA, where no RFP was detectable. For yEGFP, these tags strongly drove secretion under the regulation of pAOX1 and pGAP (Se = 0.67−0.78) but for all weak promoters, no yEGFP was detectable. The newly designed synthetic hybrid tags were less efficient but also achieved protein secretion, thus demonstrating that there is flexibility in secretion tag design. In contrast to the most commonly used αMF and αMF_no_EAEA tags, a majority of constructs showed protein expression without successful secretion. However, the synthetic SA-αMFΔ tag secreted RFP well when this cassette was under the control of a strong promoter. For RFP secretion under the control of a weak promoter, there were only three tags leading to secretion: αMF, αMF_no_EAEA, and αMFΔ. For yEGFP expression, the synthetic αAmylase-αMFΔ tag was the only tag resulting in secretion under weak promoters. When using a strong promoter with the αAmylase-αMFΔ tag, secretion was not achieved for RFP but was seen for yEGFP. Thus, in contrast to promoter strength, the efficiency of the secretion tag was found to be unpredictable and varied based on the promoter and the downstream coding region used. It is unclear if these contextual effects arise due to interactions at DNA, RNA or protein levels with components in the secretion process or between the gene and secretion tag used. However, 1022

DOI: 10.1021/acssynbio.6b00337 ACS Synth. Biol. 2017, 6, 1016−1025

Research Article

ACS Synthetic Biology

manufactures instructions) was used. Standard cloning techniques were applied for all plasmid manipulation.59 Library construction was performed as described in Lee et al.32 New part plasmids were constructed according to the standard Golden Gate (MoClo) assembly protocol. Cassette plasmids were assembled from MoClo-YTP part plasmids and newly designed P. pastoris plasmids. This assembly can be performed either using the standard Golden Gate (MoClo) assembly protocol32 or using restriction cloning. For the generation of complex libraries, we suggest designing a preassembled integration vector (e.g., vector backbone) using a GFP dropout, as recommended in the YTK.32 This approach reduces the number of parts to be assembled and improves the efficiency of the Golden Gate reaction. For cassette plasmid generation from 9 initial part plasmids, higher efficiency was gained using the restriction cloning approach. Therefore, part plasmids were BsaI digested and fragments were purified via agarose gel electrophoresis and subsequent gel extraction (Qiagen). One μL of each purified part was combined with 10× T4 DNA Ligase buffer and sterile, deionized water to a total volume of 20 μL. One μL of T4 DNA Ligase was added, the reaction was incubated (25 °C, 30 min) and heat inactivated (65 °C, 10 min). This ligation mix was directly used for transformation of E. coli. Transformation. For genomic integration in P. pastoris, transformation was performed using electroporation as described in Perez-Pinera et al. 2016.43 Competent cells were prepared according to the “Pichia Expression Kit” (Invitrogen). Subsequently, 80 μL competent cells were mixed with 5 μg circular recombinase expression vector43 (BxbI plasmid) and 5 μg circular cassette vector. The mix was incubated on ice (5 min) and then pulsed according to the parameters for S. cerevisiae as suggested by the manufacturer (1500 V, 25 μF, 200 Ohm, 2 mm cuvette). Immediately afterward, 1 mL 1 M sorbitol was added and the mix was transferred into a tube containing 1 mL 2x YP. After recovery (8 h, 30 °C, 260 rpm), 50 μL was plated on YPD supplemented with 0.75 μg/mL Zeocin. Transformation of P. pastoris based on the PARS (Pichia autonomously replication sequence) was performed as described above but no BxbI plasmid was added and recovery was 2 h. Characterization. Characterization was performed as described in Qin et al.,60 with modifications. Cultivation was carried out in 2 mL, 96-deep-well plates (dwp) containing 900 μL media at 30 °C, 900 rpm on a microtiter plate shaker (Edmund Bühler GmbH). A preculture in BMD (0.2% glucose) was inoculated from a glycerol stock master plate and grown until statured for 48 h. The expression culture in BMD (1% glucose) or BMM (1% methanol) was inoculated with 30 μL of the preculture and incubated. Measurements were performed after 24, 48, and 72 h, with a set of plates for each time point. All constructs were analyzed in triplicate. Optical density (OD600) and fluorescence (relative fluorescence units or RFU) were measured in a microplate reader Infinite M200 (Tecan). Excitation and emission wavelengths were for yEGFP 488 nm/515 nm and for RFP 561 nm/600 nm. For OD600 determination, samples were diluted using Phosphatebuffered saline (PBS) buffer, pH 7.4. For fluorescence measurements, 100 μL culture as well as 100 μL culture supernatant (centrifugation: 10 min, 4 °C, 1500 rpm) were measured. Fluorescent intensity of each sample was normalized to its OD600, if not stated otherwise. Background fluorescence was determined from the parent P. pastoris strain not expressing

methanol is not always favored for large-scale production. Jahic et al.58 compared host cell protein release from cultures grown on methanol and glucose. The degree of cell lysis in cells grown on methanol and therefore contamination of the secreted protein was much higher. Together with the fact that it is a highly flammable substrate and results in strong heat production and oxygen consumption, the use of methanol in the pAOX1 system may not always be the ideal method of choice. However, pAOX1 does offer users of the toolkit a way of tuning expression rate using a single construct before deciding on the strength of constitutive promoters to use in the final design.



CONCLUSION To economically engineer yeast as protein production platforms, many parts have to be tuned, and thus the fast generation of expression variation as well as methods for highthroughput product analysis are necessary. Standards are essential to efficiently design expression vectors and engineer heterologous protein production using flexible libraries based on well characterized parts. To avoid the creation of different standards and increase the rational diversity of an existing toolbox, we have extended the YTK.32 Specifically, we added new functional modules that allow for heterologous protein expression and secretion in P. pastoris. We characterized 124 expression constructs for protein expression and secretion, a library size that was made possible due to our efficient assembly protocol and recombinase-based integration procedure. The design of more well-characterized parts and part characterization using different reporters could expand this toolbox even further, thus allowing for flexible combinatorial design or expression systems for diverse forms of yeast.



MATERIALS AND METHODS

Strains, Media and Growth Conditions. E. coli strain DH5α was used for plasmid construction purposes. Culturing was performed in Luria-Broth (LB) supplemented with Chloramphenicol (25 μg/mL) or Kanamycin (30 μg/mL) (37 °C, 300 rpm, 12 h). P. pastoris NRRL Y-11430, ATCC 76273 containing the attP site for BxbI guided recombination43 was used for expression studies. Yeast cultures were grown either in YPD media (1% yeast extract, 2% peptone and 2% glucose) or BMGY/BMMY media (1% yeast extract, 2% peptone, 100 mM potassium phosphate (pH 6.0), 1.34% yeast nitrogen base, 4 × 10−5% biotin and 2% glycerol or 1% methanol, respectively). Shake flask cultivation was carried out in wide neck, baffled shake flasks covered with aluminium foil (30 °C, 150 rpm, 48 h). P. pastoris parts characterization was performed using BMD/BMM (100 mM potassium phosphate (pH 6.0), 1.34% yeast nitrogen base, 4 × 10−5% biotin and 0.2%/1% glucose or 1% methanol). Plasmids and Library Construction. Plasmids used in this study are listed in Tables S1 and S3 for the part plasmids and Table S4 for the cassette plasmids. The MoClo-YTK was obtained from Addgene (Kit: 1000000061). Oligonucleotides used are listed in Tables S5 and S6 and were ordered from Integrated DNA Technologies (IDT). Enzymes were purchased from New England Biolabs (NEB). Source DNA was either generated via PCR or synthesis (IDT). For PCR amplification of new parts, KAPA HiFi DNA Polymerase (Kapa Biosystems, manufactures instructions) was used. For colony PCR, KAPA2G Robust DNA Polymerase (Kapa Biosystems, 1023

DOI: 10.1021/acssynbio.6b00337 ACS Synth. Biol. 2017, 6, 1016−1025

Research Article

ACS Synthetic Biology any fluorescent protein. This strain was assayed along with the constructs on each plate. The mean background was calculated over all parent P. pastoris strains and subtracted from the expression strains. Data Analysis and Plotting. All data analysis was performed using custom scripts run using Python version 2.7.11.



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ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssynbio.6b00337. Figure S1: Comparison of pGAP-guided secretion in BMM and BMD; Table S1: Pichia toolkit plasmids; Table S2: Pichia toolkit plasmid sequences; Table S3: Saccharomyces toolkit plasmids; Table S4: Expression plasmids; Table S5: Oligonucleotides for part plasmid generation; Table S6: Primer for integration proof and plasmid verification (PDF)



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Volker Sieber: 0000-0001-5458-9330 Author Contributions

U.O., T.K.L and V.S. conceived the study. U.O. performed all experiments and data analysis. T.K.L. and V.S. supervised the research. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS U.O. was supported from the People Programme (Marie Skłodowska-Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013/under REA grant agreement no. 612614 and the Technical University of Munich Graduate School. This work was supported by the National Institutes of Health (DP2 OD008435, P50 GM098792, R01 EB017755), the Office of Naval Research (N00014-13-1-0424), and the National Science Foundation (MCB-1350625).



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