The bioindustrial production of fuels, chemicals, and therapeutics typically relies upon carbohydrate inputs derived from agricultural plants, resulting in the entanglement of food and chemical commodity markets. We demonstrate the efficient production of sucrose from a cyanobacterial species, Synechococcus elongatus, heterologously expressing a symporter of protons and sucrose (cscB). cscB-expressing cyanobacteria export sucrose irreversibly to concentrations of >10 mM without culture toxicity. Moreover, sucrose-exporting cyanobacteria exhibit increased biomass production rates relative to wild-type strains, accompanied by enhanced photosystem II activity, carbon fixation, and chlorophyll content. The genetic modification of sucrose biosynthesis pathways to minimize competing glucose-or sucrose-consuming reactions can further improve sucrose production, allowing the export of sucrose at rates of up to 36.1 mg liter ؊1 h illumination ؊1 . This rate of production exceeds that of previous reports of targeted, photobiological production from microbes. Engineered S. elongatus produces sucrose in sufficient quantities (up to ϳ80% of total biomass) such that it may be a viable alternative to sugar synthesis from terrestrial plants, including sugarcane.

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

SummaryDietary restriction is arguably the most promising nonpharmacological intervention to extend human life and health span. Yet, only few genetic regulators mediating the cellular response to dietary restriction are known, and the question remains which other regulatory factors are involved. Here, we measured at the genomewide level the chronological lifespan of Saccharomyces cerevisiae gene deletion strains under two nitrogen source regimens, glutamine (nonrestricted) and γ‐aminobutyric acid (restricted). We identified 473 mutants with diminished or enhanced extension of lifespan. Functional analysis of such dietary restriction genes revealed novel processes underlying longevity by the nitrogen source quality, which also allowed us to generate a prioritized catalogue of transcription factors orchestrating the dietary restriction response. Importantly, deletions of transcription factors Msn2, Msn4, Snf6, Tec1, and Ste12 resulted in diminished lifespan extension and defects in cell cycle arrest upon nutrient starvation, suggesting that regulation of the cell cycle is a major mechanism of chronological longevity. We further show that STE12 overexpression is enough to extend lifespan, linking the pheromone/invasive growth pathway with cell survivorship. Our global picture of the genetic players of longevity by dietary restriction highlights intricate regulatory cross‐talks in aging cells.

The ascomycetous yeast Kazachstania humilis is an active species in backslopped sourdough and in the spontaneous fermentation of several traditional foods and beverages. Here, we report the draft genome sequence of a K. humilis strain isolated from agave must from a traditional distillery in Mexico.

The chronological lifespan of budding yeast is a model of aging and age-related diseases. This paradigm has recently allowed genome-wide screening of genetic factors underlying post-mitotic viability in a simple unicellular system, which underscores its potential to provide a comprehensive view of the aging process. However, results from different large-scale studies show little overlap and typically lack quantitative resolution to derive interactions among different aging factors. We previously introduced a sensitive, parallelizable approach to measure the chronological-lifespan effects of gene deletions based on the competitive aging of fluorescence-labeled strains. Here, we present a thorough description of the method, including an improved multipleregression model to estimate the association between death rates and fluorescent signals, which accounts for possible differences in growth rate and experimental batch effects. We illustrate the experimental procedure-from data acquisition to calculation of relative survivorship-for ten deletion strains with known lifespan phenotypes, which is achieved with high technical replicability. We apply our method to screen for gene-drug interactions in an array of yeast deletion strains, which reveals a functional link between protein glycosylation and lifespan extension by metformin. Competitive-aging screening coupled to multiple-regression modeling provides a powerful, straight-forward way to identify aging factors in yeast and their interactions with pharmacological interventions.

No abstract

Subtelomeric gene silencing is the negative transcriptional regulation of genes located close to telomeres. This phenomenon occurs in a variety of eukaryotes with salient physiological implications, such as cell adherence, virulence, immune-system escape, and aging. The process has been widely studied in the budding yeast Saccharomyces cerevisiae, where genes involved in this process have been identified mostly on a gene-by-gene basis. Here, we introduce a quantitative approach to study gene silencing, that couples the classical URA3 reporter with GFP monitoring, amenable to high-throughput flow cytometry analysis. This dual silencing reporter was integrated into several subtelomeric loci in the genome, where it showed a gradual range of silencing effects. By crossing strains with this dual reporter at the COS12 and YFR057W subtelomeric query loci with gene-deletion mutants, we carried out a large-scale forward screen for potential silencing factors. The approach was replicable and allowed accurate detection of expression changes. Results of our comprehensive screen suggest that the main players influencing subtelomeric silencing were previously known, but additional potential factors underlying chromatin conformation are involved. We validate and report the novel silencing factor LGE1, a protein with unknown molecular function required for histone H2B ubiquitination. Our strategy can be readily combined with other reporters and gene perturbation collections, making it a versatile tool to study gene silencing at a genome-wide scale.

ABSTRACTThe chronological lifespan of budding yeast is a model of aging and age-related diseases. This paradigm has recently allowed genome-wide screening of genetic factors underlying post-mitotic viability in a simple unicellular system, which underscores its potential to provide a comprehensive view of the aging process. However, results from different large-scale studies show little overlap and typically lack quantitative resolution to derive interactions among different aging factors. We previously introduced a sensitive, parallelizable approach to measure the chronological-lifespan effects of gene deletions based on the competitive aging of fluorescence-labeled strains. Here, we present a thorough description of the method, including an improved multiple-regression model to estimate the association between death rates and fluorescent signals, which accounts for possible differences in growth rate and experimental batch effects. We illustrate the experimental procedure—from data acquisition to calculation of relative survivorship—for ten deletion strains with known lifespan phenotypes, which is achieved with high technical replicability. We apply our method to screen for gene-drug interactions in an array of yeast deletion strains, which reveals a functional link between protein glycosylation and lifespan extension by metformin. Competitive-aging screening coupled to multiple-regression modeling provides a powerful, straight-forward way to identify aging factors in yeast and their interactions with pharmacological interventions.