Periodic Reporting for period 1 - ProteoYeast (Unraveling the natural complexity of protein secretion to optimise novel robust yeast strains)
Periodo di rendicontazione: 2022-11-01 al 2024-10-31
Protein secretion is a universal trait among organisms, involving multiple steps of quality control, sorting, trafficking, and export; as well as various organelles. Numerous pressing challenges faced by society can be addressed by thoroughly understanding protein secretion. Disease mechanisms can be elucidated, new antimicrobials can be discovered, and high-value proteins can be produced. However, exactly because of its complexity, a full mechanistic understanding of protein secretion is still lacking, impeding full exploitation.
The yeast Saccharomyces cerevisiae is a promising model organism for studying protein secretion and is also a major expression host for industrial heterologous protein production. So far research has only focused on a few lab strains, that are inefficient protein secretors and that do not fully represent this yeast’s natural biodiversity. My preliminary data show that properties considered to be optimal in lab strains often are inferior to those observed in some other, more ‘wild’ yeast. Herein, I propose that natural S. cerevisiae strains can have more efficient protein production and secretion pathways and that the responsible alleles can be identified and exploited creating a robust protein-producing strain. In ProteoYeast, I will combine my skills in omics analyses and systems biology with the host lab’s QTL mapping expertise, unique yeast collection (>1200 strains) and advanced robotic systems to address the existing knowledge gap. This work will be divided into three parts: 1) High-throughput investigation of the natural biodiversity for protein secretion in a high-throughput manner; 2) ‘Round Robin’ QTL approach to identify novel alleles affecting protein secretion; and 3) development of robust strains for high-titer secretion of added-value proteins. Today’s urgent demand for a sustainable bio-based economy, combined with progress in laboratory automation and systems biology make this project timely and fitting to societal needs.
The yeast Saccharomyces cerevisiae is a promising model organism for studying protein secretion and is also a major expression host for industrial heterologous protein production. So far research has only focused on a few lab strains, that are inefficient protein secretors and that do not fully represent this yeast’s natural biodiversity. My preliminary data show that properties considered to be optimal in lab strains often are inferior to those observed in some other, more ‘wild’ yeast. Herein, I propose that natural S. cerevisiae strains can have more efficient protein production and secretion pathways and that the responsible alleles can be identified and exploited creating a robust protein-producing strain. In ProteoYeast, I will combine my skills in omics analyses and systems biology with the host lab’s QTL mapping expertise, unique yeast collection (>1200 strains) and advanced robotic systems to address the existing knowledge gap. This work will be divided into three parts: 1) High-throughput investigation of the natural biodiversity for protein secretion in a high-throughput manner; 2) ‘Round Robin’ QTL approach to identify novel alleles affecting protein secretion; and 3) development of robust strains for high-titer secretion of added-value proteins. Today’s urgent demand for a sustainable bio-based economy, combined with progress in laboratory automation and systems biology make this project timely and fitting to societal needs.
Initial aim was to identify specific genetic elements (promoter, leading sequence and terminator), as well as culturing conditions (medium composition, temperature, duration of culture) that would lead to optimal protein secretion in genetically distant S. cerevisiae strains. Moreover, the appropriate protocols had to be established that would guarantee robust and sensitive detection of secreted proteins. In total 12 different constructs were designed and tested on 20 different S. cerevisiae strains. Once the most promising construct was selected, a large scale screen with 250 S. cerevisiae strains was performed for β-glucosidase and AH3-mIgA secretion. This screen showcased that ≈70% of natural isolates were able to secrete higher amounts of protein than the most common lab strains, namely S288c and CEN.PK. Furthermore, protein secretion is a cargo-dependent phenotype, as there was no correlation between secretion of β-glucosidase and AH3-mIgA.
Next, three strains which exhibited high protein secretion for both β-glucosidase and AH3-mIgA, as well as two strains each of which was a good secretor of a single protein were selected and crossed in a “Round Robin” scheme to create in total two "Round Robins" and eight unique hybrids. Each of these hybrids was used for Bulk Segregant Analysis (BSA) and altogether 750 F1 haploid segregants per cross were phenotyped for their capacity to secrete proteins. Importantly, crossing of parents capable to secrete high amounts of proteins resulted to “Best parent heterosis”, since ≈10% of the segregants secreted up to Log2fold ≥ 1.5 more protein than their parents.
These "superior" segregantsas well as an equal pool of "inferior" segregants (i.e segregants that secreted less protein than the original parents) were used for a QTL study, where 8 loci which could be linked to the secretion of both cargos were identified. Aiming to identify specific alleles and genes which are responsible for the improved protein secretion phenotype Reciprocal Hemizygosity Analysis (RHA) was performed for 4 of the identified loci. Therefore, genes responsible for the observed phenotype were detected, while allele swap between the parental strains pinpointed the causative alleles. Several SNPs detected in these alleles were engineered in two different strain backgrounds, a commonly used lab strain and a bioethanol strain which in the initial screen exhibited limited secretion capacity. The most promising of these SNPs led to significant increase of protein secretion and as a result the newly engineered strains could perform equally well with the best identified candidates of the original high-throughput screen.
Next, three strains which exhibited high protein secretion for both β-glucosidase and AH3-mIgA, as well as two strains each of which was a good secretor of a single protein were selected and crossed in a “Round Robin” scheme to create in total two "Round Robins" and eight unique hybrids. Each of these hybrids was used for Bulk Segregant Analysis (BSA) and altogether 750 F1 haploid segregants per cross were phenotyped for their capacity to secrete proteins. Importantly, crossing of parents capable to secrete high amounts of proteins resulted to “Best parent heterosis”, since ≈10% of the segregants secreted up to Log2fold ≥ 1.5 more protein than their parents.
These "superior" segregantsas well as an equal pool of "inferior" segregants (i.e segregants that secreted less protein than the original parents) were used for a QTL study, where 8 loci which could be linked to the secretion of both cargos were identified. Aiming to identify specific alleles and genes which are responsible for the improved protein secretion phenotype Reciprocal Hemizygosity Analysis (RHA) was performed for 4 of the identified loci. Therefore, genes responsible for the observed phenotype were detected, while allele swap between the parental strains pinpointed the causative alleles. Several SNPs detected in these alleles were engineered in two different strain backgrounds, a commonly used lab strain and a bioethanol strain which in the initial screen exhibited limited secretion capacity. The most promising of these SNPs led to significant increase of protein secretion and as a result the newly engineered strains could perform equally well with the best identified candidates of the original high-throughput screen.
The outcomes of ProteoYeast have the potential to significantly improve the scientific community’s ability to understand the complex topic of heterologous protein production and secretion. Specific focus was given to the industrial workhorse S. cerevisiae which is commonly utilised to produce key proteins such as insulin and HPV vaccines. One of the most important findings of ProteoYeast, resulted from the screen of more than 250 S. cerevisiae strains’ protein secretion phenotype. Based on that screen we concluded that use of lab strains such as CEN.PK and S288c leads to suboptimal results and thus research focus should shift to strains with improved protein secretion capacity. Moreover, during ProteoYeast we successfully showcased that selective crossing and breeding of “good secretors” can even further significantly improve protein secretion. This finding has huge implications for any industrial production of proteins where use of genetically modified organisms (GMO) is not a possibility. Furthermore, the SNPs identified in ProteoYeast pave the road for novel engineering strategies which can significantly increase the potential of S. cerevisiae as a major heterologous protein secretion organism. It is important to highlight that the widely used engineering strategies, suffer from cargo and strain specific limitations, while the polymorphisms we identified led to improved secretion of proteins with distinct physiochemical properties, regardless of the strain background and the genetic elements (promoter and leading sequence) used.