Promoters maintain their relative activity levels under different growth conditions

A comparative analysis of NADPH supply strategies in Saccharomyces cerevisiae: Production of d-xylitol from d-xylose as a case study

Enhancing the supply of the redox cofactor NADPH in metabolically engineered cells is a critical target for optimizing the synthesis of many product classes, such as fatty acids or terpenoids. In S. cerevisiae, several successful approaches have been developed in different experimental contexts. However, their systematic comparison has not been reported. Here, we established the reduction of xylose to xylitol by an NADPH-dependent xylose reductase as a model reaction to compare the efficacy of different NADPH supply strategies in the course of a batch fermentation, in which glucose and ethanol are sequentially used as carbon sources and redox donors. We show that strains overexpressing the glucose-6-phosphate dehydrogenase Zwf1 perform best, producing up to 16.9 g L-1 xylitol from 20 g L-1 xylose in stirred tank bioreactors. The beneficial effect of increased Zwf1 activity is especially pronounced during the ethanol consumption phase. The same notion applies to the deletion of the aldehyde dehydrogenase ALD6 gene, albeit at a quantitatively lower level. Reduced expression of the phosphoglucose isomerase Pgi1 and heterologous expression of the NADP+-dependent glyceraldehyde-3-phosphate dehydrogenase Gdp1 from Kluyveromyces lactis acted synergistically with ZWF1 overexpression in the presence of glucose, but had a detrimental effect after the diauxic shift. Expression of the mitochondrial NADH kinase Pos5 in the cytosol likewise improved the production of xylitol only on glucose, but not in combination with enhanced Zwf1 activity. To demonstrate the generalizability of our observations, we show that the most promising strategies - ZWF1 overexpression and deletion of ALD6 - also improve the production of l-galactonate from d-galacturonic acid. Therefore, we expect that these findings will provide valuable guidelines for engineering not only the production of xylitol but also of diverse other pathways that require NADPH.

Single-cell heterogeneity in ribosome content and the consequences for the growth laws

Previous work has suggested that the ribosome content of a cell is optimized to maximize growth given the nutrient availability. The resulting correlation between ribosome number and growth rate appears to be independent of the rate limiting nutrient and has been reported in many organisms. The robustness and universality of this observation has given it the classification of a "growth law." These laws have had powerful impacts on many biological disciplines. They have fueled predictions about how organisms evolve to maximize reproduction, and informed models about how cells regulate growth. Due to methodological limitations, this growth law has rarely been studied at the level of individual cells. While populations of fast-growing cells tend to have more ribosomes than populations of slow-growing cells, it is unclear if individual cells tightly regulate their ribosome content to match their environment. Here, we use recent ground-breaking single-cell RNA sequencing techniques to study this growth law at the single-cell level in two different microbes, S. cerevisiae (a single-celled yeast and eukaryote) and B. subtilis (a bacterium and prokaryote). In both species, we find enormous variation in the ribosomal content of single cells that is not predictive of growth rate. Fast-growing populations include cells showing transcriptional signatures of slow growth and stress, as do cells with the highest ribosome content we survey. Broadening our focus to the levels of non-ribosomal transcripts reveals subpopulations of cells in unique transcriptional states suggestive of divergent growth strategies. These results suggest that single-cell ribosome levels are not finely tuned to match population growth rates or nutrient availability, at least not in a way that can be captured by a unifying law that applies to all cell types. Overall, this work encourages the expansion of these "laws" and other models that predict how growth rates are regulated or how they evolve to consider single-cell heterogeneity.

Species-aware DNA language models capture regulatory elements and their evolution

BACKGROUND

The rise of large-scale multi-species genome sequencing projects promises to shed new light on how genomes encode gene regulatory instructions. To this end, new algorithms are needed that can leverage conservation to capture regulatory elements while accounting for their evolution.

RESULTS

Here, we introduce species-aware DNA language models, which we trained on more than 800 species spanning over 500 million years of evolution. Investigating their ability to predict masked nucleotides from context, we show that DNA language models distinguish transcription factor and RNA-binding protein motifs from background non-coding sequence. Owing to their flexibility, DNA language models capture conserved regulatory elements over much further evolutionary distances than sequence alignment would allow. Remarkably, DNA language models reconstruct motif instances bound in vivo better than unbound ones and account for the evolution of motif sequences and their positional constraints, showing that these models capture functional high-order sequence and evolutionary context. We further show that species-aware training yields improved sequence representations for endogenous and MPRA-based gene expression prediction, as well as motif discovery.

CONCLUSIONS

Collectively, these results demonstrate that species-aware DNA language models are a powerful, flexible, and scalable tool to integrate information from large compendia of highly diverged genomes.

Increased CO2 fixation enables high carbon-yield production of 3-hydroxypropionic acid in yeast

CO2 fixation plays a key role to make biobased production cost competitive. Here, we use 3-hydroxypropionic acid (3-HP) to showcase how CO2 fixation enables approaching theoretical-yield production. Using genome-scale metabolic models to calculate the production envelope, we demonstrate that the provision of bicarbonate, formed from CO2, restricts previous attempts for high yield production of 3-HP. We thus develop multiple strategies for bicarbonate uptake, including the identification of Sul1 as a potential bicarbonate transporter, domain swapping of malonyl-CoA reductase, identification of Esbp6 as a potential 3-HP exporter, and deletion of Uga1 to prevent 3-HP degradation. The combined rational engineering increases 3-HP production from 0.14 g/L to 11.25 g/L in shake flask using 20 g/L glucose, approaching the maximum theoretical yield with concurrent biomass formation. The engineered yeast forms the basis for commercialization of bio-acrylic acid, while our CO2 fixation strategies pave the way for CO2 being used as the sole carbon source.

Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast

Microbes are increasingly employed as cell factories to produce biomolecules. This often involves the expression of complex heterologous biosynthesis pathways in host strains. Achieving maximal product yields and avoiding build-up of (toxic) intermediates requires balanced expression of every pathway gene. However, despite progress in metabolic modeling, the optimization of gene expression still heavily relies on trial-and-error. Here, we report an approach for in vivo, multiplexed Gene Expression Modification by LoxPsym-Cre Recombination (GEMbLeR). GEMbLeR exploits orthogonal LoxPsym sites to independently shuffle promoter and terminator modules at distinct genomic loci. This approach facilitates creation of large strain libraries, in which expression of every pathway gene ranges over 120-fold and each strain harbors a unique expression profile. When applied to the biosynthetic pathway of astaxanthin, an industrially relevant antioxidant, a single round of GEMbLeR improved pathway flux and doubled production titers. Together, this shows that GEMbLeR allows rapid and efficient gene expression optimization in heterologous biosynthetic pathways, offering possibilities for enhancing the performance of microbial cell factories.

Saccharomyces boulardii promoters for control of gene expression in vivo

BACKGROUND

Interest in the use of engineered microbes to deliver therapeutic activities has increased in recent years. The probiotic yeast Saccharomyces boulardii has been investigated for production of therapeutics in the gastrointestinal tract. Well-characterised promoters are a prerequisite for robust therapeutic expression in the gut; however, S. boulardii promoters have not yet been thoroughly characterised in vitro and in vivo.

RESULTS

We present a thorough characterisation of the expression activities of 12 S. boulardii promoters in vitro in glucose, fructose, sucrose, inulin and acetate, under both aerobic and anaerobic conditions, as well as in the murine gastrointestinal tract. Green fluorescent protein was used to report on promoter activity. Promoter expression was found to be carbon-source dependent, with inulin emerging as a favourable carbon source. Furthermore, relative promoter expression in vivo was highly correlated with expression in sucrose (R = 0.99).

CONCLUSIONS

These findings provide insights into S. boulardii promoter activity and aid in promoter selection in future studies utilising S. boulardii to produce therapeutics in the gut.

Tradeoffs in bacterial physiology determine the efficiency of antibiotic killing

Antibiotic effectiveness depends on a variety of factors. While many mechanistic details of antibiotic action are known, the connection between death rate and bacterial physiology is poorly understood. A common observation is that death rate in antibiotics rises linearly with growth rate; however, it remains unclear how other factors, such as environmental conditions and whole-cell physiological properties, affect bactericidal activity. To address this, we developed a high-throughput assay to precisely measure antibiotic-mediated death. We found that death rate is linear in growth rate, but the slope depends on environmental conditions. Growth under stress lowers death rate compared to nonstressed environments with similar growth rate. To understand stress's role, we developed a mathematical model of bacterial death based on resource allocation that includes a stress-response sector; we identify this sector using RNA-seq. Our model accurately predicts the minimal inhibitory concentration (MIC) with zero free parameters across a wide range of growth conditions. The model also quantitatively predicts death and MIC when sectors are experimentally modulated using cyclic adenosine monophosphate (cAMP), including protection from death at very low cAMP levels. The present study shows that different conditions with equal growth rate can have different death rates and establishes a quantitative relation between growth, death, and MIC that suggests approaches to improve antibiotic efficacy.

Development of an efficient yeast platform for cannabigerolic acid biosynthesis

Cannabinoids are important therapeutical molecules for human ailments, cancer treatment, and SARS-CoV-2. The central cannabinoid, cannabigerolic acid (CBGA), is generated from geranyl pyrophosphate and olivetolic acid by Cannabis sativa prenyltransferase (CsPT4). Despite efforts to engineer microorganisms such as Saccharomyces cerevisiae (S. cerevisiae) for CBGA production, their titers remain suboptimal because of the low conversion of hexanoate into olivetolic acid and the limited activity and stability of the CsPT4. To address the low hexanoate conversion, we eliminated hexanoate consumption by the beta-oxidation pathway and reduced its incorporation into fatty acids. To address CsPT4 limitations, we expanded the endoplasmic reticulum and fused an auxiliary protein to CsPT4. Consequently, the engineered S. cerevisiae chassis showed a marked improvement of 78.64-fold in CBGA production, reaching a titer of 510.32 ± 10.70 mg l-1 from glucose and hexanoate.

Golden Standard: a complete standard, portable, and interoperative MoClo tool for model and non-model proteobacteria

Modular cloning has become a benchmark technology in synthetic biology. However, a notable disparity exists between its remarkable development and the need for standardization to facilitate seamless interoperability among systems. The field is thus impeded by an overwhelming proliferation of organism-specific systems that frequently lack compatibility. To overcome these issues, we present Golden Standard (GS), a Type IIS assembly method underpinned by the Standard European Vector Architecture. GS unlocks modular cloning applications for most bacteria, and delivers combinatorial multi-part assembly to create genetic circuits of up to twenty transcription units (TUs). Reliance on MoClo syntax renders GS fully compatible with many existing tools and it sets the path towards efficient reusability of available part libraries and assembled TUs. GS was validated in terms of DNA assembly, portability, interoperability and phenotype engineering in α-, β-, γ- and δ-proteobacteria. Furthermore, we provide a computational pipeline for parts characterization that was used to assess the performance of GS parts. To promote community-driven development of GS, we provide a dedicated web-portal including a repository of parts, vectors, and Wizard and Setup tools that guide users in designing constructs. Overall, GS establishes an open, standardized framework propelling the progress of synthetic biology as a whole.

Soluble and insoluble α-glucan synthesis in yeast by enzyme suites derived exclusively from maize endosperm

Molecular mechanisms that distinguish the synthesis of semi-crystalline α-glucan polymers found in plant starch granules from the synthesis of water-soluble polymers by nonplant species are not well understood. To address this, starch biosynthetic enzymes from maize (Zea mays L.) endosperm were isolated in a reconstituted environment using yeast (Saccharomyces cerevisiae) as a test bed. Ninety strains were constructed containing unique combinations of 11 synthetic transcription units specifying maize starch synthase (SS), starch phosphorylase (PHO), starch branching enzyme (SBE), or isoamylase-type starch debranching enzyme (ISA). Soluble and insoluble branched α-glucans accumulated in varying proportions depending on the enzyme suite, with ISA function stimulating distribution into the insoluble form. Among the SS isoforms, SSIIa, SSIII, and SSIV individually supported the accumulation of glucan polymer. Neither SSI nor SSV alone produced polymers; however, synergistic effects demonstrated that both isoforms can stimulate α-glucan accumulation. PHO did not support α-glucan production by itself, but it had either positive or negative effects on polymer content depending on which SS or a combination thereof was present. The complete suite of maize enzymes generated insoluble particles resembling native starch granules in size, shape, and crystallinity. Ultrastructural analysis revealed a hierarchical assembly starting with subparticles of approximately 50 nm diameter that coalesce into discrete structures of approximately 200 nm diameter. These are assembled into semi-crystalline α-glucan superstructures up to 4 μm in length filling most of the yeast cytosol. ISA was not essential for the formation of such particles, but their abundance was increased dramatically by ISA presence.

Matching metabolic supply to demand optimizes microbial growth

Recent research has strengthened the notion that microbes allocate their biosynthetic capacity to maximize the growth rate, λ. Yet many microbes can grow substantially faster after laboratory evolution. Chure and Cremer advance a resource-allocation model, which they derive from first principles, that offers resolution to this conundrum.

Flux regulation through glycolysis and respiration is balanced by inositol pyrophosphates in yeast

Although many prokaryotes have glycolysis alternatives, it's considered as the only energy-generating glucose catabolic pathway in eukaryotes. Here, we managed to create a hybrid-glycolysis yeast. Subsequently, we identified an inositol pyrophosphatase encoded by OCA5 that could regulate glycolysis and respiration by adjusting 5-diphosphoinositol 1,2,3,4,6-pentakisphosphate (5-InsP₇) levels. 5-InsP₇ levels could regulate the expression of genes involved in glycolysis and respiration, representing a global mechanism that could sense ATP levels and regulate central carbon metabolism. The hybrid-glycolysis yeast did not produce ethanol during growth under excess glucose and could produce 2.68 g/L free fatty acids, which is the highest reported production in shake flask of Saccharomyces cerevisiae. This study demonstrated the significance of hybrid-glycolysis yeast and determined Oca5 as an inositol pyrophosphatase controlling the balance between glycolysis and respiration, which may shed light on the role of inositol pyrophosphates in regulating eukaryotic metabolism.

Manipulation of sterol homeostasis for the production of 24-epi-ergosterol in industrial yeast

Brassinolide (BL) is the most biologically active compound among natural brassinosteroids. However, the agricultural applications are limited by the extremely low natural abundance and the scarcity of synthetic precursors. Here, we employ synthetic biology to construct a yeast cell factory for scalable production of 24-epi-ergosterol, an un-natural sterol, proposed as a precursor for BL semi-synthesis. First, we construct an artificial pathway by introducing a Δ²⁴⁽²⁸⁾ sterol reductase from plants (DWF1), followed by enzyme directed evolution, to enable de novo biosynthesis of 24-epi-ergosterol in yeast. Subsequently, we manipulate the sterol homeostasis (overexpression of ARE2, YEH1, and YEH2 with intact ARE1), maintaining a balance between sterol acylation and sterol ester hydrolysis, for the production of 24-epi-ergosterol, whose titer reaches to 2.76 g L^-1 using fed-batch fermentation. The sterol homeostasis engineering strategy can be applicable for bulk production of other economically important phytosterols.

Engineering Pheromone-Mediated Quorum Sensing with Enhanced Response Output Increases Fucosyllactose Production in Saccharomyces cerevisiae

Engineering dynamic control of gene expression is desirable because many engineered functions interfere with endogenous cellular processes that have evolved to facilitate growth and survival. Minimizing conflict between growth and production phases can therefore improve product titers in microbial cell factories. We developed an autoinduced gene expression system by rewiring the Saccharomyces cerevisiae pheromone response pathway. To ameliorate growth reduction due to the early onset response at low population densities, α-pheromone of Kluyveromyces lactis (Kα) instead of S. cerevisiae (Sα) was expressed in mating type "a" yeast. Kα-induced expression of pathway genes was further enhanced by the transcriptional activator Gal4p expressed under the control of the pheromone-responsive FUS1 promoter (P_fus1). As a demonstration, the engineered circuit combined with the deletion of the endogenous galactose metabolic pathway genes was applied to the production of human milk oligosaccharides, 2'-fucosyllactose (2'-FL) and 3-fucosllactose (3-FL). The engineered strains produced 3.37 g/L 2'-FL and 2.36 g/L 3-FL on glucose with a volumetric productivity of 0.14 and 0.03 g/L·h^-1 in batch flask cultivation, respectively. These represented 147 and 153% increases over the control strains on galactose wherein the respective pathway genes are expressed under GAL promoters only. Further fed-batch fermentation achieved titers of 32.05 and 20.91 g/L for 2' and 3-FL, respectively. The genetic program developed here thus represents a promising option for implementing dynamic regulation in yeast and could be used for the production of biochemicals that may place a heavy metabolic burden on cell growth.

Metabolic reconfiguration enables synthetic reductive metabolism in yeast

Cell proliferation requires the integration of catabolic processes to provide energy, redox power and biosynthetic precursors. Here we show how the combination of rational design, metabolic rewiring and recombinant expression enables the establishment of a decarboxylation cycle in the yeast cytoplasm. This metabolic cycle can support growth by supplying energy and increased provision of NADPH or NADH in the cytosol, which can support the production of highly reduced chemicals such as glycerol, succinate and free fatty acids. With this approach, free fatty acid yield reached 40% of theoretical yield, which is the highest yield reported for Saccharomyces cerevisiae to our knowledge. This study reports the implementation of a synthetic decarboxylation cycle in the yeast cytosol, and its application in achieving high yields of valuable chemicals in cell factories. Our study also shows that, despite extensive regulation of catabolism in yeast, it is possible to rewire the energy metabolism, illustrating the power of biodesign.

Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

Background

Starch, a vital plant-derived polysaccharide comprised of branched glucans, is essential in nutrition and many industrial applications. Starch is often modified post-extraction to alter its structure and enhance its functionality. Targeted metabolic engineering of crops to produce valuable and versatile starches requires knowledge of the relationships between starch biosynthesis, structure, and properties, but systematic studies to obtain this knowledge are difficult to conduct in plants. Here we used Saccharomyces cerevisiae as a testbed to dissect the functions of plant starch biosynthetic enzymes and create diverse starch-like polymers.

Results

We explored yeast promoters and terminators to tune the expression levels of the starch-biosynthesis machinery from Arabidopsis thaliana. We systematically modulated the expression of each starch synthase (SS) together with a branching enzyme (BE) in yeast. Protein quantification by parallel reaction monitoring (targeted proteomics) revealed unexpected effects of glucan biosynthesis on protein abundances but showed that the anticipated broad range of SS/BE enzyme ratios was maintained during the biosynthetic process. The different SS/BE ratios clearly influenced glucan structure and solubility: The higher the SS/BE ratio, the longer the glucan chains and the more glucans were partitioned into the insoluble fraction. This effect was irrespective of the SS isoform, demonstrating that the elongation/branching ratio controls glucan properties separate from enzyme specificity.

Conclusions

Our results provide a quantitative framework for the in silico design of improved starch biosynthetic processes in plants. Our study also exemplifies a workflow for the rational tuning of a complex pathway in yeast, starting from the selection and evaluation of expression modules to multi-gene assembly and targeted protein monitoring during the biosynthetic process.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01408-x.

Enhanced extracellular raw starch-degrading α-amylase production in Bacillus subtilis by promoter engineering and translation initiation efficiency optimization

Background

A raw starch-degrading α-amylase from Pontibacillus sp. ZY (AmyZ1), previously screened by our laboratory, showed a promising application potential for starch-processing industries. However, the AmyZ1 secretory production still under investigation, which seriously restricts its application in the starch-processing industry. On the other hand, Bacillus subtilis is widely used to achieve the extracellular expression of target proteins.

Results

AmyZ1 secretory production was achieved in B. subtilis and was enhanced by promoter engineering and translation initiation efficiency optimization. First, based on the different phase-dependent promoters, the dual-promoter P_spoVG–P_spoVG142 was constructed by combining dual-promoter engineering and promoter modification. The corresponding strain BZd34 showed an extracellular AmyZ1 activity of 1437.6 U/mL during shake flask cultivation, which was 3.11-fold higher than that of the original strain BZ1 (P_groE). Then, based on translation initiation efficiency optimization, the best strain BZd343 containing optimized 5'-proximal coding sequence (opt3) produced the highest extracellular α-amylase activity of 1691.1 U/mL, which was 3.65-fold higher than that of the strain BZ1. Finally, cultivation of BZd343 in 3-L fermenter exhibited an extracellular AmyZ1 activity of 14,012 U/mL at 48 h, with productivity of 291.9 U/mL·h.

Conclusions

This is the first report of recombinant expression of AmyZ1 in B. subtilis and the expression level of AmyZ1 represents the highest raw starch-degrading α-amylase level in B. subtilis to date. The high-level expression of AmyZ1 in this work provides a foundation for its industrial production. The strategies used in this study also provide a strategic reference for improving the secretory expression of other enzymes in B. subtilis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01855-9.

The transcription factor network of E. coli steers global responses to shifts in RNAP concentration

The robustness and sensitivity of gene networks to environmental changes is critical for cell survival. How gene networks produce specific, chronologically ordered responses to genome-wide perturbations, while robustly maintaining homeostasis, remains an open question. We analysed if short- and mid-term genome-wide responses to shifts in RNA polymerase (RNAP) concentration are influenced by the known topology and logic of the transcription factor network (TFN) of Escherichia coli. We found that, at the gene cohort level, the magnitude of the single-gene, mid-term transcriptional responses to changes in RNAP concentration can be explained by the absolute difference between the gene's numbers of activating and repressing input transcription factors (TFs). Interestingly, this difference is strongly positively correlated with the number of input TFs of the gene. Meanwhile, short-term responses showed only weak influence from the TFN. Our results suggest that the global topological traits of the TFN of E. coli shape which gene cohorts respond to genome-wide stresses.

Analysing and meta-analysing time-series data of microbial growth and gene expression from plate readers

Responding to change is a fundamental property of life, making time-series data invaluable in biology. For microbes, plate readers are a popular, convenient means to measure growth and also gene expression using fluorescent reporters. Nevertheless, the difficulties of analysing the resulting data can be a bottleneck, particularly when combining measurements from different wells and plates. Here we present omniplate, a Python module that corrects and normalises plate-reader data, estimates growth rates and fluorescence per cell as functions of time, calculates errors, exports in different formats, and enables meta-analysis of multiple plates. The software corrects for autofluorescence, the optical density’s non-linear dependence on the number of cells, and the effects of the media. We use omniplate to measure the Monod relationship for the growth of budding yeast in raffinose, showing that raffinose is a convenient carbon source for controlling growth rates. Using fluorescent tagging, we study yeast’s glucose transport. Our results are consistent with the regulation of the hexose transporter (HXT) genes being approximately bipartite: the medium and high affinity transporters are predominately regulated by both the high affinity glucose sensor Snf3 and the kinase complex SNF1 via the repressors Mth1, Mig1, and Mig2; the low affinity transporters are predominately regulated by the low affinity sensor Rgt2 via the co-repressor Std1. We thus demonstrate that omniplate is a powerful tool for exploiting the advantages offered by time-series data in revealing biological regulation.

Time series of growth and of gene expression via fluorescent reporters are rich ways to characterise the behaviours of cells. With plate readers, it is straightforward to measure 96 independent time series in a single experiment, with readings taken every 10 minutes and each time series lasting tens of hours. Analysing such data can become challenging, particularly if multiple plate-reader experiments are required to characterise a phenomenon, which then should be analysed simultaneously. Taking advantage of existing packages in Python, we have written code that automates this analysis but yet still allows users to develop custom routines. Our omniplate software corrects both measurements of optical density to become linear in the number of cells and measurements of fluorescence for autofluorescence. It estimates growth rates and fluorescence per cell as continuous functions of time and enables tens of plate-reader experiments to be analysed together. Data can be exported in text files in a format immediately suitable for public repositories. Plate readers are a convenient way to study cells; omniplate provides an equally convenient yet powerful way to analyse the resulting data.

Intron-mediated induction of phenotypic heterogeneity

Intragenic regions that are removed during maturation of the RNA transcript—introns—are universally present in the nuclear genomes of eukaryotes¹. The budding yeast, an otherwise intron-poor species, preserves two sets of ribosomal protein genes that differ primarily in their introns^2,3. Although studies have shed light on the role of ribosomal protein introns under stress and starvation^4–6, understanding the contribution of introns to ribosome regulation remains challenging. Here, by combining isogrowth profiling⁷ with single-cell protein measurements⁸, we show that introns can mediate inducible phenotypic heterogeneity that confers a clear fitness advantage. Osmotic stress leads to bimodal expression of the small ribosomal subunit protein Rps22B, which is mediated by an intron in the 5′ untranslated region of its transcript. The two resulting yeast subpopulations differ in their ability to cope with starvation. Low levels of Rps22B protein result in prolonged survival under sustained starvation, whereas high levels of Rps22B enable cells to grow faster after transient starvation. Furthermore, yeasts growing at high concentrations of sugar, similar to those in ripe grapes, exhibit bimodal expression of Rps22B when approaching the stationary phase. Differential intron-mediated regulation of ribosomal protein genes thus provides a way to diversify the population when starvation threatens in natural environments. Our findings reveal a role for introns in inducing phenotypic heterogeneity in changing environments, and suggest that duplicated ribosomal protein genes in yeast contribute to resolving the evolutionary conflict between precise expression control and environmental responsiveness⁹.

Experiments in yeast show that introns have a role in inducing phenotypic heterogeneity and that intron-mediated regulation of ribosomal proteins confers a fitness advantage by enabling yeast populations to diversify under nutrient-scarce conditions.

Programmable Synthetic Upstream Activating Sequence Library for Fine-Tuning Gene Expression Levels in Saccharomyces cerevisiae

A wide dynamic range of promoters is necessary for fine-tuning transcription levels. However, weak intensity and narrow dynamic range limit transcriptional regulation via constitutive promoters. The upstream activation sequence (UAS) located upstream of the core promoter is a crucial region that could obviously enhance promoter strength. Herein, we created a random mutagenesis library consisting of 330 different variants based on the UAS of the TDH3 promoter with an ∼37-fold dynamic range by error-prone polymerase chain reaction (PCR) and obtained strong intensity mutant UAS, which was ∼12-fold greater than the wild-type UAS_TDH3. Analysis of the mutant library revealed 15 strength-enhancing sites and their corresponding bases of the UAS_TDH3 regions, which provided the impetus for a synthetic library. The resulting 32 768 mutant UAS library was constructed by permutation and combination of the bases of the 15 enhancing sites. To characterize the library, a strength prediction model was built by correlating DNA structural features and UAS strength, which provided a model between UAS sequence and intensity. Following characterization, the UAS library was applied to precisely regulate gene expression in the production of β-carotene, proving that the UAS library would be a useful tool for gene tuning in metabolic engineering. In summary, we designed, constructed, and characterized a UAS library that facilitated precise tuning of transcription levels of target proteins.

Growth-rate-dependent and nutrient-specific gene expression resource allocation in fission yeast

Cellular resources are limited and their relative allocation to gene expression programmes determines physiological states and global properties such as the growth rate. Here, we determined the importance of the growth rate in explaining relative changes in protein and mRNA levels in the simple eukaryote Schizosaccharomyces pombe grown on non-limiting nitrogen sources. Although expression of half of fission yeast genes was significantly correlated with the growth rate, this came alongside wide-spread nutrient-specific regulation. Proteome and transcriptome often showed coordinated regulation but with notable exceptions, such as metabolic enzymes. Genes positively correlated with growth rate participated in every level of protein production apart from RNA polymerase II-dependent transcription. Negatively correlated genes belonged mainly to the environmental stress response programme. Critically, metabolic enzymes, which represent ∼55-70% of the proteome by mass, showed mostly condition-specific regulation. In summary, we provide a rich account of resource allocation to gene expression in a simple eukaryote, advancing our basic understanding of the interplay between growth-rate-dependent and nutrient-specific gene expression.

Metabolic engineering of threonine catabolism enables Saccharomyces cerevisiae to produce propionate under aerobic conditions

BACKGROUND

Propionate is widely used as a preservative in the food and animal feed industries. Propionate is currently produced by petrochemical processes, and fermentative production of propionate remains challenging.

METHODS AND RESULTS

In this study, a synthetic propionate pathway was constructed in the budding yeast Saccharomyces cerevisiae, for propionate production under aerobic conditions. Through expression of tdcB and aldH from Escherichia coli and kivD from Lactococcus lactis, L-threonine was converted to propionate via 2-ketobutyrate and propionaldehyde. The resulting yeast aerobically produced 0.21 g/L propionate from glucose in a shake flask. Subsequent overexpression of pathway genes and elimination of competing pathways increased propionate production to 0.37 g/L. To further increase propionate production, carbon flux was pulled into the propionate pathway by weakened expression of pyruvate kinase (PYK1), together with overexpression of phosphoenolpyruvate carboxylase (ppc). The final propionate production reached 1.05 g/L during fed-batch fermentation in a fermenter.

CONCLUSIONS AND IMPLICATIONS

In this work, a yeast cell factory was constructed using synthetic biology and metabolic engineering strategies to enable propionate production under aerobic conditions. Our study demonstrates engineered S. cerevisiae as a promising alternative for the production of propionate and its derivatives. This article is protected by copyright. All rights reserved.

Modular, synthetic chromosomes as new tools for large scale engineering of metabolism

The construction of powerful cell factories requires intensive genetic engineering for the addition of new functionalities and the remodeling of native pathways and processes. The present study demonstrates the feasibility of extensive genome reprogramming using modular, specialized de novo-assembled neochromosomes in yeast. The in vivo assembly of linear and circular neochromosomes, carrying 20 native and 21 heterologous genes, enabled the first de novo production in a microbial cell factory of anthocyanins, plant compounds with a broad range pharmacological properties. Turned into exclusive expression platforms for heterologous and essential metabolic routes, the neochromosomes mimic native chromosomes regarding mitotic and genetic stability, copy number, harmlessness for the host and editability by CRISPR/Cas9. This study paves the way for future microbial cell factories with modular genomes in which core metabolic networks, localized on satellite, specialized neochromosomes can be swapped for alternative configurations and serve as landing pads for the addition of functionalities.

Saccharomyces cerevisiae as a Heterologous Host for Natural Products

Cell factories can provide a sustainable supply of natural products with applications as pharmaceuticals, food-additives or biofuels. Besides being an important model organism for eukaryotic systems, Saccharomyces cerevisiae is used as a chassis for the heterologous production of natural products. Its success as a cell factory can be attributed to the vast knowledge accumulated over decades of research, its overall ease of engineering and its robustness. Many methods and toolkits have been developed by the yeast metabolic engineering community with the aim of simplifying and accelerating the engineering process.In this chapter, a range of methodologies are highlighted, which can be used to develop novel natural product cell factories or to improve titer, rate and yields of an existing cell factory with the goal of developing an industrially relevant strain. The addressed topics are applicable for different stages of a cell factory engineering project and include the choice of a natural product platform strain, expression cassette design for heterologous or native genes, basic and advanced genetic engineering strategies, and library screening methods using biosensors. The many engineering methods available and the examples of yeast cell factories underline the importance and future potential of this host for industrial production of natural products.

An integrated yeast-based process for cis,cis-muconic acid production

Cis,cis‐muconic acid (CCM) is a promising polymer building block. CCM can be made by whole‐cell bioconversion of lignin hydrolysates or de novo biosynthesis from sugar feedstocks using engineered microorganisms. At present, however, there is no established process for large‐scale CCM production. In this study, we developed an integrated process for manufacturing CCM from glucose by yeast fermentation. We systematically engineered the CCM‐producing Saccharomyces cerevisiae strain by rewiring the shikimate pathway flux and enhancing phosphoenolpyruvate supply. The engineered strain ST10209 accumulated less biomass but produced 1.4 g/L CCM (70 mg CCM per g glucose) in microplate assay, 71% more than the previously engineered strain ST8943. The strain ST10209 produced 22.5 g/L CCM in a 2 L fermenter with a productivity of 0.19 g/L/h, compared to 0.14 g/L/h achieved by ST8943 in our previous report under the same fermentation conditions. The fermentation process was demonstrated at pilot scale in 10 and 50 L steel tanks. In 10 L fermenter, ST10209 produced 20.8 g/L CCM with a CCM yield of 0.1 g/g glucose and a productivity of 0.21 g/L/h, representing the highest to‐date CCM yield and productivity. We developed a CCM recovery and purification process by treating the fermentation broth with activated carbon at low pH and low temperature, achieving an overall CCM recovery yield of 66.3% and 95.4% purity. In summary, we report an integrated CCM production process employing engineered S. cerevisiae yeast.

De novo biosynthesis of bioactive isoflavonoids by engineered yeast cell factories

Isoflavonoids comprise a class of plant natural products with great nutraceutical, pharmaceutical and agricultural significance. Their low abundance in nature and structural complexity however hampers access to these phytochemicals through traditional crop-based manufacturing or chemical synthesis. Microbial bioproduction therefore represents an attractive alternative. Here, we engineer the metabolism of Saccharomyces cerevisiae to become a platform for efficient production of daidzein, a core chemical scaffold for isoflavonoid biosynthesis, and demonstrate its application towards producing bioactive glucosides from glucose, following the screening-reconstruction-application engineering framework. First, we rebuild daidzein biosynthesis in yeast and its production is then improved by 94-fold through screening biosynthetic enzymes, identifying rate-limiting steps, implementing dynamic control, engineering substrate trafficking and fine-tuning competing metabolic processes. The optimized strain produces up to 85.4 mg L^-1 of daidzein and introducing plant glycosyltransferases in this strain results in production of bioactive puerarin (72.8 mg L^-1) and daidzin (73.2 mg L^-1). Our work provides a promising step towards developing synthetic yeast cell factories for de novo biosynthesis of value-added isoflavonoids and the multi-phased framework may be extended to engineer pathways of complex natural products in other microbial hosts.

A synthetic promoter system for well-controlled protein expression with different carbon sources in Saccharomyces cerevisiae

Background

Saccharomyces cerevisiae is an important synthetic biology chassis for microbial production of valuable molecules. Promoter engineering has been frequently applied to generate more synthetic promoters with a variety of defined characteristics in order to achieve a well-regulated genetic network for high production efficiency. Galactose-inducible (GAL) expression systems, composed of GAL promoters and multiple GAL regulators, have been widely used for protein overexpression and pathway construction in S. cerevisiae. However, the function of each element in synthetic promoters and how they interact with GAL regulators are not well known.

Results

Here, a library of synthetic GAL promoters demonstrate that upstream activating sequences (UASs) and core promoters have a synergistic relationship that determines the performance of each promoter under different carbon sources. We found that the strengths of synthetic GAL promoters could be fine-tuned by manipulating the sequence, number, and substitution of UASs. Core promoter replacement generated synthetic promoters with a twofold strength improvement compared with the GAL1 promoter under multiple different carbon sources in a strain with GAL1 and GAL80 engineering. These results represent an expansion of the classic GAL expression system with an increased dynamic range and a good tolerance of different carbon sources.

Conclusions

In this study, the effect of each element on synthetic GAL promoters has been evaluated and a series of well-controlled synthetic promoters are constructed. By studying the interaction of synthetic promoters and GAL regulators, synthetic promoters with an increased dynamic range under different carbon sources are created.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01691-3.

Efficient production of shinorine, a natural sunscreen material, from glucose and xylose by deleting HXK2 encoding hexokinase in Saccharomyces cerevisiae

Mycosporine-like amino acids (MAAs), microbial secondary metabolites with ultraviolet (UV) absorption properties, are promising natural sunscreen materials. Due to the low efficiency of extracting MAAs from natural producers, production in heterologous hosts has recently received attention. Shinorine is a well characterized MAA with strong UV-A absorption property. Previous, we developed Saccharomyces cerevisiae strain producing shinorine by introducing four shinorine biosynthetic genes from cyanobacterium Nostoc punctiforme. Shinorine is produced from sedoheptulose 7-phosphate (S7P), an intermediate in the pentose phosphate pathway. Shinorine production was greatly improved by using xylose as a co-substrate, which can increase the S7P pool. However, due to a limited xylose-utilizing capacity of the engineered strain, glucose was used as a co-substrate to support cell growth. In this study, we further improved shinorine production by attenuating glucose catabolism via glycolysis, which can redirect the carbon flux from glucose to the pentose phosphate pathway favoring shinorine production. Of the strategies we examined to reduce glycolytic flux, deletion of HXK2, encoding hexokinase, was most effective in increasing shinorine production. Furthermore, by additional expression of Ava3858 from Anabaena variabilis, encoding a rate-limiting enzyme 2-demethyl 4-deoxygadusol synthase, 68.4 mg/L of shinorine was produced in an optimized medium containing 14 g/L glucose and 6 g/L xylose, achieving a 2.2-fold increase compared with the previous strain.

Sequence polarity between the promoter and the adjacent gene modulates promoter activity

Promoter engineering has been employed as a strategy to enhance and optimize the production of bio-products. Availability of promoters with predictable activities is needed for downstream application. However, whether promoter activity remains the same in different gene contexts remains unknown. Six consecutive promoters that have previously been determined to have different activity levels were used to construct six different versions of plasmid backbone pTH1227, followed by inserted genes encoding two polymer-producing enzymes. In some cases, promoter activity in the presence of inserted genes did not correspond to the reported activity levels in a previous study. After removing the inserted genes, the activity of these promoters returned to their previously reported level. These changes were further confirmed to occur at the transcriptional level. Polymer production using our newly constructed plasmids showed polymer accumulation levels corresponding to the promoter activity reported in our study. Our study demonstrated the importance of re-assessing promoter activity levels with regard to gene context, which could influence promoter activity, leading to different outcomes in downstream applications.

A call for caution in analysing mammalian co-transfection experiments and implications of resource competition in data misinterpretation

Transient transfections are routinely used in basic and synthetic biology studies to unravel pathway regulation and to probe and characterise circuit designs. As each experiment has a component of intrinsic variability, reporter gene expression is usually normalized with co-delivered genes that act as transfection controls. Recent reports in mammalian cells highlight how resource competition for gene expression leads to biases in data interpretation, with a direct impact on co-transfection experiments. Here we define the connection between resource competition and transient transfection experiments and discuss possible alternatives. Our aim is to raise awareness within the community and stimulate discussion to include such considerations in future experimental designs, for the development of better transfection controls.

Decoupling transcription factor expression and activity enables dimmer switch gene regulation

Gene-regulatory networks achieve complex mappings of inputs to outputs through mechanisms that are poorly understood. We found that in the galactose-responsive pathway in Saccharomyces cerevisiae, the decision to activate the transcription of genes encoding pathway components is controlled independently from the expression level, resulting in behavior resembling that of a mechanical dimmer switch. This was not a direct result of chromatin regulation or combinatorial control at galactose-responsive promoters; rather, this behavior was achieved by hierarchical regulation of the expression and activity of a single transcription factor. Hierarchical regulation is ubiquitous, and thus dimmer switch regulation is likely a key feature of many biological systems. Dimmer switch gene regulation may allow cells to fine-tune their responses to multi-input environments on both physiological and evolutionary time scales.

Global coordination of metabolic pathways in Escherichia coli by active and passive regulation

Microorganisms adjust metabolic activity to cope with diverse environments. While many studies have provided insights into how individual pathways are regulated, the mechanisms that give rise to coordinated metabolic responses are poorly understood. Here, we identify the regulatory mechanisms that coordinate catabolism and anabolism in Escherichia coli. Integrating protein, metabolite, and flux changes in genetically implemented catabolic or anabolic limitations, we show that combined global and local mechanisms coordinate the response to metabolic limitations. To allocate proteomic resources between catabolism and anabolism, E. coli uses a simple global gene regulatory program. Surprisingly, this program is largely implemented by a single transcription factor, Crp, which directly activates the expression of catabolic enzymes and indirectly reduces the expression of anabolic enzymes by passively sequestering cellular resources needed for their synthesis. However, metabolic fluxes are not controlled by this regulatory program alone; instead, fluxes are adjusted mostly through passive changes in the local metabolite concentrations. These mechanisms constitute a simple but effective global regulatory program that coarsely partitions resources between different parts of metabolism while ensuring robust coordination of individual metabolic reactions.

Suboptimal Global Transcriptional Response Increases the Harmful Effects of Loss-of-Function Mutations

The fitness impact of loss-of-function mutations is generally assumed to reflect the loss of specific molecular functions associated with the perturbed gene. Here, we propose that rewiring of the transcriptome upon deleterious gene inactivation is frequently nonspecific and mimics stereotypic responses to external environmental change. Consequently, transcriptional response to gene deletion could be suboptimal and incur an extra fitness cost. Analysis of the transcriptomes of ∼1,500 single-gene deletion Saccharomyces cerevisiae strains supported this scenario. First, most transcriptomic changes are not specific to the deleted gene but are rather triggered by perturbations in functionally diverse genes. Second, gene deletions that alter the expression of dosage-sensitive genes are especially harmful. Third, by elevating the expression level of downregulated genes, we could experimentally mitigate the fitness defect of gene deletions. Our work shows that rewiring of genomic expression upon gene inactivation shapes the harmful effects of mutations.

Rewiring Central Carbon Metabolism Ensures Increased Provision of Acetyl-CoA and NADPH Required for 3-OH-Propionic Acid Production

The central carbon metabolite acetyl-CoA and the cofactor NADPH are important for the synthesis of a wide array of biobased products. Here, we constructed a platform yeast strain for improved provision of acetyl-CoA and NADPH, and used the production of 3-hydroxypropionic acid (3-HP) as a case study. We first demonstrated that the integration of phosphoketolase and phosphotransacetylase improved 3-HP production by 41.9% and decreased glycerol production by 48.1% compared with that of the control strain. Then, to direct more carbon flux toward the pentose phosphate pathway, we reduced the expression of phosphoglucose isomerase by replacing its native promoter with a weaker promoter, and increased the expression of glucose-6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase by replacing their native promoters with stronger promoters. This further improved 3-HP production by 26.4%. Furthermore, to increase the NADPH supply we overexpressed cytosolic aldehyde dehydrogenase, and improved 3-HP production by another 10.5%. Together with optimizing enzyme expression of acetyl-CoA carboxylase and malonyl-CoA reductase, the final strain is able to produce 3-HP with a final titer of 864.5 mg/L, which is a more than 24-fold improvement compared with that of the starting strain. Our strategy combines the PK pathway with the oxidative pentose phosphate pathway for the efficient provision of acetyl-CoA and NADPH, which provides both a higher theoretical yield and overall yield than the reported yeast-based 3-HP production strategies via the malonyl-CoA reductase-dependent pathway and sheds light on the construction of efficient platform cell factories for other products.

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Understanding the genetic regulatory code governing gene expression is an important challenge in molecular biology. However, how individual coding and non-coding regions of the gene regulatory structure interact and contribute to mRNA expression levels remains unclear. Here we apply deep learning on over 20,000 mRNA datasets to examine the genetic regulatory code controlling mRNA abundance in 7 model organisms ranging from bacteria to Human. In all organisms, we can predict mRNA abundance directly from DNA sequence, with up to 82% of the variation of transcript levels encoded in the gene regulatory structure. By searching for DNA regulatory motifs across the gene regulatory structure, we discover that motif interactions could explain the whole dynamic range of mRNA levels. Co-evolution across coding and non-coding regions suggests that it is not single motifs or regions, but the entire gene regulatory structure and specific combination of regulatory elements that define gene expression levels.

Multi-omics Analysis of CRISPRi-Knockdowns Identifies Mechanisms that Buffer Decreases of Enzymes in E. coli Metabolism

Enzymes maintain metabolism, and their concentration affects cellular fitness: high enzyme levels are costly, and low enzyme levels can limit metabolic flux. Here, we used CRISPR interference (CRISPRi) to study the consequences of decreasing E. coli enzymes below wild-type levels. A pooled CRISPRi screen with 7,177 strains demonstrates that metabolism buffers fitness defects for hours after the induction of CRISPRi. We characterized the metabolome and proteome responses in 30 CRISPRi strains and elucidated three gene-specific buffering mechanisms: ornithine buffered the knockdown of carbamoyl phosphate synthetase (CarAB) by increasing CarAB activity, S-adenosylmethionine buffered the knockdown of homocysteine transmethylase (MetE) by de-repressing expression of the methionine pathway, and 6-phosphogluconate buffered the knockdown of 6-phosphogluconate dehydrogenase (Gnd) by activating a bypass. In total, this work demonstrates that CRISPRi screens can reveal global sources of metabolic robustness and identify local regulatory mechanisms that buffer decreases of specific enzymes. A record of this paper's transparent peer review process is included in the Supplemental Information.

Engineered signal-coupled inducible promoters: measuring the apparent RNA-polymerase resource budget

Inducible promoters are a central regulatory component in synthetic biology, metabolic engineering, and protein production for laboratory and commercial uses. Many of these applications utilize two or more exogenous promoters, imposing a currently unquantifiable metabolic burden on the living system. Here, we engineered a collection of inducible promoters (regulated by LacI-based transcription factors) that maximize the free-state of endogenous RNA polymerase (RNAP). We leveraged this collection of inducible promotors to construct simple two-channel logical controls that enabled us to measure metabolic burden – as it relates to RNAP resource partitioning. The two-channel genetic circuits utilized sets of signal-coupled transcription factors that regulate cognate inducible promoters in a coordinated logical fashion. With this fundamental genetic architecture, we evaluated the performance of each inducible promoter as discrete operations, and as coupled systems to evaluate and quantify the effects of resource partitioning. Obtaining the ability to systematically and accurately measure the apparent RNA-polymerase resource budget will enable researchers to design more robust genetic circuits, with significantly higher fidelity. Moreover, this study presents a workflow that can be used to better understand how living systems adapt RNAP resources, via the complementary pairing of constitutive and regulated promoters that vary in strength.

Promoter Architecture and Promoter Engineering in Saccharomyces cerevisiae

Promoters play an essential role in the regulation of gene expression for fine-tuning genetic circuits and metabolic pathways in Saccharomyces cerevisiae (S. cerevisiae). However, native promoters in S. cerevisiae have several limitations which hinder their applications in metabolic engineering. These limitations include an inadequate number of well-characterized promoters, poor dynamic range, and insufficient orthogonality to endogenous regulations. Therefore, it is necessary to perform promoter engineering to create synthetic promoters with better properties. Here, we review recent advances related to promoter architecture, promoter engineering and synthetic promoter applications in S. cerevisiae. We also provide a perspective of future directions in this field with an emphasis on the recent advances of machine learning based promoter designs.

Promoter-Library-Based Pathway Optimization for Efficient (2S)-Naringenin Production from p-Coumaric Acid in Saccharomyces cerevisiae

Pathway optimization plays an important role in fine-tuning metabolic pathways. In most conditions, more than three genes are involved in the biosynthesis pathway of a specific target product. To improve the titer of products, rational regulation of a group of genes by a series of promoters with different strengths is essential. On the basis of a series of RNA-Seq data, a set of 66 native promoters was chosen to fine-tune gene expression in Saccharomyces cerevisiae. Promoter strength was characterized by measuring the fluorescence strength of the enhanced green fluorescent protein through fluorescence-activated cell sorting. The expressions of P_TDH1, P_PGK1, P_INO1, P_SED1, and P_CCW12 were stronger than that of P_TDH3, whereas those of another 15 promoters were stronger than that of P_TEF1. Then, 30 promoters were chosen to optimize the biosynthesis pathway of (2S)-naringenin from p-coumaric acid. With a high-throughput screening method, the highest titer of (2S)-naringenin in a 5 L bioreactor reached 1.21 g/L from p-coumaric acid, which is the highest titer according to the currently available reports.

Engineering yeast phospholipid metabolism for de novo oleoylethanolamide production

Phospholipids, the most abundant membrane lipid components, are crucial in maintaining membrane structures and homeostasis for biofunctions. As a structurally diverse and tightly regulated system involved in multiple organelles, phospholipid metabolism is complicated to manipulate. Thus, repurposing phospholipids for lipid-derived chemical production remains unexplored. Herein, we develop a Saccharomyces cerevisiae platform for de novo production of oleoylethanolamide, a phospholipid derivative with promising pharmacological applications in ameliorating lipid dysfunction and neurobehavioral symptoms. Through deregulation of phospholipid metabolism, screening of biosynthetic enzymes, engineering of subcellular trafficking and process optimization, we could produce oleoylethanolamide at a titer of 8,115.7 µg l^-1 and a yield on glucose of 405.8 µg g^-1. Our work provides a proof-of-concept study for systemically repurposing phospholipid metabolism for conversion towards value-added biological chemicals, and this multi-faceted framework may shed light on tailoring phospholipid metabolism in other microbial hosts.

Promoter Activity Buffering Reduces the Fitness Cost of Misregulation

Organisms regulate gene expression through changes in the activity of transcription factors (TFs). In yeast, the response of genes to changes in TF activity is generally assumed to be encoded in the promoter. To directly test this assumption, we chose 42 genes and, for each, replaced the promoter with a synthetic inducible promoter and measured how protein expression changes as a function of TF activity. Most genes exhibited gene-specific TF dose-response curves not due to differences in mRNA stability, translation, or protein stability. Instead, most genes have an intrinsic ability to buffer the effects of promoter activity. This can be encoded in the open reading frame and the 3' end of genes and can be implemented by both autoregulatory feedback and by titration of limiting trans regulators. We show experimentally and computationally that, when misexpression of a gene is deleterious, this buffering insulates cells from fitness defects due to misregulation.

Rewiring carbon metabolism in yeast for high level production of aromatic chemicals

The production of bioactive plant compounds using microbial hosts is considered a safe, cost-competitive and scalable approach to their production. However, microbial production of some compounds like aromatic amino acid (AAA)-derived chemicals, remains an outstanding metabolic engineering challenge. Here we present the construction of a Saccharomyces cerevisiae platform strain able to produce high levels of p-coumaric acid, an AAA-derived precursor for many commercially valuable chemicals. This is achieved through engineering the AAA biosynthesis pathway, introducing a phosphoketalose-based pathway to divert glycolytic flux towards erythrose 4-phosphate formation, and optimizing carbon distribution between glycolysis and the AAA biosynthesis pathway by replacing the promoters of several important genes at key nodes between these two pathways. This results in a maximum p-coumaric acid titer of 12.5 g L⁻¹ and a maximum yield on glucose of 154.9 mg g⁻¹.

Microbial production of aromatic amino acid (AAA)-derived chemicals remains an outstanding metabolic engineering challenge. Here, the authors engineer baker’s yeast for high levels p-coumaric acid production by rewiring the central carbon metabolism and channeling more flux to the AAA biosynthetic pathway.

Widespread Cumulative Influence of Small Effect Size Mutations on Yeast Quantitative Traits

Quantitative traits are influenced by pathways that have traditionally been defined through genes that have a large loss- or gain-of-function effect. However, in theory, a large number of small effect size genes could cumulatively play a substantial role in pathway function. Here, we determine the number, strength, and identity of all non-essential test genes that affect two quantitative galactose-responsive traits in addition to re-analyzing two previously screened quantitative traits. We find that over a quarter of assayed genes have a detectable, quantitative effect on phenotype. Despite their ubiquity, these genes are enriched in core cellular processes in a trait-specific manner. In a simulated population with 50% frequency of all-or-none alleles, we show that small effect size alleles are capable of contributing more to trait variation than alleles in a canonical, large effect size pathway. In total, by demonstrating that the genes effecting quantitative traits can be highly distributed and interconnected, this work challenges the concept of pathways as modular and independent.

Expanding the Dynamic Range of a Transcription Factor-Based Biosensor in Saccharomyces cerevisiae

Metabolite biosensors are useful tools for high-throughput screening approaches and pathway regulation approaches. An important feature of biosensors is the dynamic range. To expand the maximum dynamic range of a transcription factor-based biosensor in Saccharomyces cerevisiae, using the fapO/FapR system from Bacillus subtilis as an example case, five native promoters, including constitutive and glucose-regulated ones, were modified. By evaluating different binding site (BS) positions in the core promoters, we identified locations that resulted in a high maximum dynamic range with low expression under repressed conditions. We further identified BS positions in the upstream element region of the TEF1 promoter that did not influence the native promoter strength but resulted in repression in the presence of a chimeric repressor consisting of FapR and the yeast repressor Mig1. These modified promoters with broad dynamic ranges will provide useful information for the engineering of future biosensors and their use in complex genetic circuits.

Complex genetic and epigenetic regulation deviates gene expression from a unifying global transcriptional program

Environmental or genetic perturbations lead to gene expression changes. While most analyses of these changes emphasize the presence of qualitative differences on just a few genes, we now know that changes are widespread. This large-scale variation has been linked to the exclusive influence of a global transcriptional program determined by the new physiological state of the cell. However, given the sophistication of eukaryotic regulation, we expect to have a complex architecture of specific control affecting this program. Here, we examine this architecture. Using data of Saccharomyces cerevisiae expression in different nutrient conditions, we first propose a five-sector genome partition, which integrates earlier models of resource allocation, as a framework to examine the deviations from the global control. In this scheme, we recognize invariant genes, whose regulation is dominated by physiology, specific genes, which substantially depart from it, and two additional classes that contain the frequently assumed growth-dependent genes. Whereas the invariant class shows a considerable absence of specific regulation, the rest is enriched by regulation at the level of transcription factors (TFs) and epigenetic modulators. We nevertheless find markedly different strategies in how these classes deviate. On the one hand, there are TFs that act in a unique way between partition constituents, and on the other, the action of chromatin modifiers is significantly diverse. The balance between regulatory strategies ultimately modulates the action of the general transcription machinery and therefore limits the possibility of establishing a unifying program of expression change at a genomic scale.

How can we understand expression changes observed as a result of environmental or genetic perturbations? This issue has been conventionally answered by examining small groups of genes whose expression becomes qualitatively altered after these perturbations. But this approach is too simplistic, as we now know that extensive variation is typically observed. To explain this variation, recent works proposed a model in which genome-wide changes are explained by the action of a general program of transcription. Our manuscript reasons that given the complexity of eukaryotic transcriptional control, a unifying program of regulation cannot be achievable. Instead, we propose within an integrated framework of resource allocation that a rich structure of deviations from it exists and that by characterizing these deviations we can fully appreciate large-scale expression change.