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Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing‐ like lipid biosynthesis, flavinogenesis, and halotolerance – yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica, Debaryomyces hansenii, and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a “network‐first” approach where a generalized metabolic network serves as a scaffold for mapping genes and a “cluster‐first” approach where unsupervised machine learning co‐expression analysis clusters genes. Both approaches provide insight into strain behavior. The network‐first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster‐first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions. 

Abstract Probiotic yeasts are emerging as preventative and therapeutic solutions for disease. Often ingested via cultured foods and beverages, they can survive the harsh conditions of the gastrointestinal tract and adhere to it, where they provide nutrients and inhibit pathogens like Candida albicans. Yet, little is known of the genomic determinants of these beneficial traits. To this end, we have sequenced 2 food-derived probiotic yeast isolates that mitigate fungal infections. We find that the first strain, KTP, is a strain of Saccharomyces cerevisiae within a small clade that lacks any apparent ancestry from common European/wine S. cerevisiae strains. Significantly, we show that S. cerevisiae KTP genes involved in general stress, pH tolerance, and adherence are markedly different from S. cerevisiae S288C but are similar to the commercial probiotic yeast species S. boulardii. This suggests that even though S. cerevisiae KTP and S. boulardii are from different clades, they may achieve probiotic effect through similar genetic mechanisms. We find that the second strain, ApC, is a strain of Issatchenkia occidentalis, one of the few of this family of yeasts to be sequenced. Because of the dissimilarity of its genome structure and gene organization, we infer that I. occidentalis ApC likely achieves a probiotic effect through a different mechanism than the Saccharomyces strains. Therefore, this work establishes a strong genetic link among probiotic Saccharomycetes, advances the genomics of Issatchenkia yeasts, and indicates that probiotic activity is not monophyletic and complimentary mixtures of probiotics could enhance health benefits beyond a single species. 

Phosphorus (P) loss from cropland to ground and surface waters is a global concern. In cold climates (CCs), freeze–thaw cycles, snowmelt runoff events, and seasonally wet soils increase P loss potential while limiting P removal effectiveness of riparian buffer zones (RBZs) and other practices. While RBZs can help reduce particulate P transfer to streams, attenuation of dissolved P forms is more challenging. Moreover, P transport studies often focus on either cropland or RBZs exclusively rather than spanning the natural cropland–RBZ–stream gradient, defined here as the cropland–RBZ–stream continuum. Watershed P transport models and agronomic P site indices are commonly used to identify critical source areas; however, RBZ effects on P transport are usually not included. In addition, the coarse resolution of watershed P models may not capture finer-scale soil factors affecting P mobilization. It is clear that site microtopography and hydrology are closely linked and important drivers of P release and transport in overland flow. Combining light detection and ranging (LiDAR) based digital elevation models with P site indices and process-based models show promise for mapping and modeling P transport risk in cropland-RBZ areas; however, a better mechanistic understanding of processes controlling mobile P species across regions is needed. Broader predictive approaches integrating soil hydro-biogeochemical processes with real-time hydroclimatic data and risk assessment tools also hold promise for improving P transport risk assessment in CCs. 

Cyanobacteria are tiny organisms that can harness the energy of the sun to power their cells. Many of the tools required for this complex photosynthetic process are packaged into small compartments inside the cell, the carboxysomes. In Synechococcus elongatus, a cyanobacterium that is shaped like a rod, the carboxysomes are positioned at regular intervals along the length of the cell. This ensures that, when the bacterium splits itself in half to reproduce, both daughter cells have the same number of carboxysomes. Researchers know that, in S. elongatus, a protein called McdA can oscillate from one end of the cell to the other. This protein is responsible for the carboxysomes being in the right place, and some scientists believe that it helps to create an internal skeleton that anchors and drags the compartments into position. Here, MacCready et al. propose another mechanism and, by combining various approaches, identify a new partner for McdA. This protein, called McdB, is present on the carboxysomes. McdB also binds to McdA, which itself attaches to the nucleoid – the region in the cell that contains the DNA. McdB forces McdA to release itself from DNA, causing the protein to reposition itself along the nucleoid. Because McdB attaches to McdA, the carboxysomes then follow suit, constantly seeking the highest concentrations of McdA bound to nearby DNA. Instead of relying on a cellular skeleton, these two proteins can organize themselves on their own using the nucleoid as a scaffold; in turn, they distribute carboxysomes evenly along the length of a cell. Plants also obtain their energy from the sun via photosynthesis, but they do not carry carboxysomes. Scientists have tried to introduce these compartments inside plant cells, hoping that it could generate crops with higher yields. Knowing how carboxysomes are organized so they can be passed down from one generation to the next could be important for these experiments. 

Synthetic biology is creating genetically engineered organisms at an increasing rate for many potentially valuable applications, but this potential comes with the risk of misuse or accidental release. To begin to address this issue, we have developed a system called GUARDIAN that can automatically detect signatures of engineering in DNA sequencing data, and we have conducted a blinded test of this system using a curated Test and Evaluation (T&E) data set. GUARDIAN uses an ensemble approach based on the guiding principle that no single approach is likely to be able to detect engineering with perfect accuracy. Critically, ensembling enables GUARDIAN to detect sequence inserts in 13 target organisms with a high degree of specificity that requires no subject matter expert (SME) review.