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Synonymous mutations in protein-coding genes do not alter protein sequences and are thus generally presumed to be neutral or nearly neutral 1 – 5 . Here, to experimentally verify this presumption, we constructed 8,341 yeast mutants each carrying a synonymous, nonsynonymous or nonsense mutation in one of 21 endogenous genes with diverse functions and expression levels and measured their fitness relative to the wild type in a rich medium. Three-quarters of synonymous mutations resulted in a significant reduction in fitness, and the distribution of fitness effects was overall similar—albeit nonidentical—between synonymous and nonsynonymous mutations. Both synonymous and nonsynonymous mutations frequently disturbed the level of mRNA expression of the mutated gene, and the extent of the disturbance partially predicted the fitness effect. Investigations in additional environments revealed greater across-environment fitness variations for nonsynonymous mutants than for synonymous mutants despite their similar fitness distributions in each environment, suggesting that a smaller proportion of nonsynonymous mutants than synonymous mutants are always non-deleterious in a changing environment to permit fixation, potentially explaining the common observation of substantially lower nonsynonymous than synonymous substitution rates. The strong non-neutrality of most synonymous mutations, if it holds true for other genes and in other organisms, would require re-examination of numerous biological conclusions about mutation, selection, effective population size, divergence time and disease mechanisms that rely on the assumption that synoymous mutations are neutral. A survey of 8,341 mutations in 21 yeast genes shows that synonymous mutations are nearly as harmful as nonsynonymous mutations, in part because they both affect the mRNA level of the gene mutated.

Saccharomyces cerevisiae is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of S. cerevisiae by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis. Understanding how yeast organizes its functional proteome is a fundamental task in systems biology. Here, the authors conduct a multiomics analysis on yeast cells cultured with different growth rates, identifying a linear dependence of the functional proteome on the growth rate.

Novel protein-coding genes can arise either from pre-existing genes or de novo ; here it is shown that functional genes emerge de novo through transitory proto-genes generated by widespread translational activity in non-genic sequences. New genes from unlikely beginnings De novo gene birth has occurred in many lineages during evolution, but how functional protein-coding genes emerge in non-functional sequences — rather than through gene rearrangement — remains unresolved. These authors observe in the yeast Saccharomyces cerevisiae that hundreds of species-specific non-genic transcripts are differentially regulated upon stress. These previously overlooked translation events seem to act as a reservoir of adaptive potential, in the form of open reading frames that occupy an evolutionary continuum ranging from non-genic sequences to genes. On the basis of their genome-wide observations, the authors suggest that de novo gene birth from the proto-gene reservoir may be more prevalent than sporadic gene duplication. Novel protein-coding genes can arise either through re-organization of pre-existing genes or de novo 1 , 2 . Processes involving re-organization of pre-existing genes, notably after gene duplication, have been extensively described 1 , 2 . In contrast, de novo gene birth remains poorly understood, mainly because translation of sequences devoid of genes, or ‘non-genic’ sequences, is expected to produce insignificant polypeptides rather than proteins with specific biological functions 1 , 3 , 4 , 5 , 6 . Here we formalize an evolutionary model according to which functional genes evolve de novo through transitory proto-genes 4 generated by widespread translational activity in non-genic sequences. Testing this model at the genome scale in Saccharomyces cerevisiae , we detect translation of hundreds of short species-specific open reading frames (ORFs) located in non-genic sequences. These translation events seem to provide adaptive potential 7 , as suggested by their differential regulation upon stress and by signatures of retention by natural selection. In line with our model, we establish that S. cerevisiae ORFs can be placed within an evolutionary continuum ranging from non-genic sequences to genes. We identify ∼1,900 candidate proto-genes among S. cerevisiae ORFs and find that de novo gene birth from such a reservoir may be more prevalent than sporadic gene duplication. Our work illustrates that evolution exploits seemingly dispensable sequences to generate adaptive functional innovation.

Inducible promoters are essential for precise control of target gene expression in synthetic biological systems. However, engineering eukaryotic promoters is often more challenging than engineering prokaryotic promoters due to their greater mechanistic complexity. In this study, we describe a simple and reliable approach for constructing strongly inducible synthetic promoters with minimum leakiness in yeasts. The results indicate that the leakiness of yeast-inducible synthetic promoters is primarily the result of cryptic transcriptional activation of heterologous sequences that may be avoided by appropriate insulation and operator mutagenesis. Our promoter design approach has successfully generated robust, inducible promoters that achieve a > 10 3 -fold induction in reporter gene expression. The utility of these promoters is demonstrated by using them to produce various biologics with titers up to 2 g/L, including antigens designed to raise specific antibodies against a SARS-CoV-2 omicron variant through chicken immunization. Inducible promoters that control gene expression in response to small molecules are essential in synthetic biology. Here, the authors describe a simple and reliable approach for constructing strongly inducible synthetic yeast promoters, which are validated for use in large-scale protein production.

Microbial production of cannabinoids promises to provide a consistent, cheaper, and more sustainable supply of these important therapeutic molecules. However, scaling production to compete with traditional plant-based sources is challenging. Our ability to make strain variants greatly exceeds our capacity to screen and identify high producers, creating a bottleneck in metabolic engineering efforts. Here, we present a yeast-based biosensor for detecting microbially produced Δ 9 -tetrahydrocannabinol (THC) to increase throughput and lower the cost of screening. We port five human cannabinoid G protein-coupled receptors (GPCRs) into yeast, showing the cannabinoid type 2 receptor, CB2R, can couple to the yeast pheromone response pathway and report on the concentration of a variety of cannabinoids over a wide dynamic and operational range. We demonstrate that our cannabinoid biosensor can detect THC from microbial cell culture and use this as a tool for measuring relative production yields from a library of Δ 9 -tetrahydrocannabinol acid synthase (THCAS) mutants. Microbial production of cannabinoids promises a cheaper and more sustainable route to these important therapeutic molecules, but strain improvement and screening is challenging. Here, the authors develop a yeast-based Δ9-tetrahydrocannabinol (THC) biosensor for screening microbial mutant libraries.

The exact positions of nucleosomes along genomic DNA can influence many aspects of chromosome function. However, existing methods for mapping nucleosomes do not provide the necessary single-base-pair accuracy to determine these positions. Here we develop and apply a new approach for direct mapping of nucleosome centres on the basis of chemical modification of engineered histones. The resulting map locates nucleosome positions genome-wide in unprecedented detail and accuracy. It shows new aspects of the in vivo nucleosome organization that are linked to transcription factor binding, RNA polymerase pausing and the higher-order structure of the chromatin fibre. A new technique for mapping nucleosomes genome-wide with single-base-pair accuracy, by chemical modification of engineered histones. A detailed yeast nucleosome map The positions of nucleosomes along genomic DNA can influence many aspects of chromosome function. Kristin Brogaard et al . have developed an innovative approach for mapping nucleosomes genome-wide in vivo in Saccharomyces cerevisiae , using highly localized hydroxyl radicals, to modify engineered histones. The map defines nucleosome centre positions with single base-pair accuracy. The exact locations of nucleosomes are shown to be associated with a variety of genomic features, including the exact locations of transposon integration sites, and RNA polymerase pause sites.

Ploidy changes are frequent in nature and contribute to evolution, functional specialization and tumorigenesis. Analysis of model organisms of different ploidies revealed that increased ploidy leads to an increase in cell and nuclear volume, reduced proliferation, metabolic changes, lower fitness, and increased genomic instability, but the underlying mechanisms remain poorly understood. To investigate how gene expression changes with cellular ploidy, we analyzed isogenic series of budding yeasts from 1N to 4N. We show that mRNA and protein abundance scales allometrically with ploidy, with tetraploid cells showing only threefold increase in protein abundance compared to haploids. This ploidy-dependent sublinear scaling occurs via decreased rRNA and ribosomal protein abundance and reduced translation. We demonstrate that the activity of Tor1 is reduced with increasing ploidy, which leads to diminished rRNA gene repression via a Tor1-Sch9-Tup1 signaling pathway. mTORC1 and S6K activity are also reduced in human tetraploid cells and the concomitant increase of the Tup1 homolog Tle1 downregulates the rDNA transcription. Our results suggest that the mTORC1-Sch9/S6K-Tup1/TLE1 pathway ensures proteome remodeling in response to increased ploidy. Increasing the number of chromosome sets alters the physiology of cells. Here, the authors show that although the number of chromosome sets increases, the proteome does not scale linearly with the increasing ploidy.

In Saccharomyces cerevisiae , deletion of large ribosomal subunit protein-encoding genes increases the replicative lifespan in a Gcn4-dependent manner. However, how Gcn4, a key transcriptional activator of amino acid biosynthesis genes, increases lifespan, is unknown. Here we show that Gcn4 acts as a repressor of protein synthesis. By analyzing the messenger RNA and protein abundance, ribosome occupancy and protein synthesis rate in various yeast strains, we demonstrate that Gcn4 is sufficient to reduce protein synthesis and increase yeast lifespan. Chromatin immunoprecipitation reveals Gcn4 binding not only at genes that are activated, but also at genes, some encoding ribosomal proteins, that are repressed upon Gcn4 overexpression. The promoters of repressed genes contain Rap1 binding motifs. Our data suggest that Gcn4 is a central regulator of protein synthesis under multiple perturbations, including ribosomal protein gene deletions, calorie restriction, and rapamycin treatment, and provide an explanation for its role in longevity and stress response. The transcription factor Gcn4 is known to regulate yeast amino acid synthesis. Here, the authors show that Gcn4 also acts as a repressor of protein biosynthesis in a range of conditions that enhance yeast lifespan, such as ribosomal protein knockout, calorie restriction or mTOR inhibition.

In the unicellular eukaryote Saccharomyces cerevisiae , Cln3–cyclin-dependent kinase activity enables Start, the irreversible commitment to the cell division cycle. However, the concentration of Cln3 has been paradoxically considered to remain constant during G1, due to the presumed scaling of its production rate with cell size dynamics. Measuring metabolic and biosynthetic activity during cell cycle progression in single cells, we found that cells exhibit pulses in their protein production rate. Rather than scaling with cell size dynamics, these pulses follow the intrinsic metabolic dynamics, peaking around Start. Using a viral-based bicistronic construct and targeted proteomics to measure Cln3 at the single-cell and population levels, we show that the differential scaling between protein production and cell size leads to a temporal increase in Cln3 concentration, and passage through Start. This differential scaling causes Start in both daughter and mother cells across growth conditions. Thus, uncoupling between two fundamental physiological parameters drives cell cycle commitment. By measuring metabolic and biosynthetic activity with cell cycle progression, Litsios et el. uncover pulses in protein production rate that do not scale with cell size but drive cell cycle entry in budding yeast.

Application of microfluidic platforms facilitated high-precision measurements of yeast replicative lifespan (RLS); however, comparative quantification of lifespan across strain libraries has been missing. Here we microfluidically measure the RLS of 307 yeast strains, each deleted for a single gene. Despite previous reports of extended lifespan in these strains, we found that 56% of them did not actually live longer than the wild-type; while the remaining 44% showed extended lifespans, the degree of extension was often different from what was previously reported. Deletion of SIS2 gene led to the largest RLS increase observed. Sis2 regulated yeast lifespan in a dose-dependent manner, implying a role for the coenzyme A biosynthesis pathway in lifespan regulation. Introduction of the human PPCDC gene in the sis2Δ background neutralized the lifespan extension. RNA-seq experiments revealed transcriptional increases in cell-cycle machinery components in sis2Δ background. High-precision lifespan measurement will be essential to elucidate the gene network governing lifespan. Using a microfluidic single-cell aging platform, the authors report how single-cell lifespan varies across more than 300 yeast strains, each missing a single gene. Their top hit, Sis2, was found to regulate yeast lifespan in a dose-dependent fashion.