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Aneuploidy, an imbalance in chromosome copy numbers, causes genetic disorders, and drives cancer progression, drug tolerance, and antimicrobial resistance. While aneuploidy can confer stress resistance, it is not well understood how cells overcome the fitness burden caused by aberrant chromosomal copy numbers. Studies using both systematically generated and natural aneuploid yeasts triggered an intense debate about the role of dosage compensation, concluding that aneuploidy is transmitted to the transcriptome and proteome without significant buffering at the chromosome-wide level, and is, at least in lab strains, associated with significant fitness costs. Conversely, systematic sequencing and phenotyping of large collections of natural isolates revealed that aneuploidy is frequent and has few - if any - fitness costs in nature. To address these discrepant findings at the proteomic level, we developed a platform that yields highly precise proteomic measurements across large numbers of genetically diverse samples, and applied it to natural isolates collected as part of the 1011 genomes project. For 613 of the isolates, we were able to match the proteomes to their corresponding transcriptomes and genomes, subsequently quantifying the effect of aneuploidy on gene expression by comparing 95 aneuploid with 518 euploid strains. We find, as in previous studies, that aneuploid gene dosage is not buffered chromosome-wide at the transcriptome level. Importantly, in the proteome, we detect an attenuation of aneuploidy by about 25% below the aneuploid gene dosage in natural yeast isolates. Furthermore, this chromosome-wide dosage compensation is associated with the ubiquitin-proteasome system (UPS), which is expressed at higher levels and has increased activity across natural aneuploid strains. Thus, through systematic exploration of the species-wide diversity of the yeast proteome, we shed light on a long-standing debate about the biology of aneuploids, revealing that aneuploidy tolerance is mediated through chromosome-wide dosage compensation at the proteome level.

BackgroundGenome-scale metabolic models provide an opportunity for rational approaches to studies of the different reactions taking place inside the cell. The integration of these models with gene regulatory networks is a hot topic in systems biology. The methods developed to date focus mostly on resolving the metabolic elements and use fairly straightforward approaches to assess the impact of genome expression on the metabolic phenotype.ResultsWe present here a method for integrating the reverse engineering of gene regulatory networks into these metabolic models. We applied our method to a high-dimensional gene expression data set to infer a background gene regulatory network. We then compared the resulting phenotype simulations with those obtained by other relevant methods.ConclusionsOur method outperformed the other approaches tested and was more robust to noise. We also illustrate the utility of this method for studies of a complex biological phenomenon, the diauxic shift in yeast.

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BACKGROUND The demand for colorants from natural bio‐based sources is increasing. Violacein is a natural purple‐blue hydrophobic pigment with interesting bioactivity whose expression in genetically modified Yarrowia lipolytica production was successfully achieved. RESULTS In this work, several surfactants were tested in the extraction of violacein from Y. lipolytica cells, and the operational conditions were optimized to maximize the extraction yield. After the optimization, the purification of violacein using aqueous biphasic systems (ABS) composed of Tween 20 and cholinium‐based ionic liquids (ILs) was pursued. The ABS were characterized and applied in the separation of violacein from contaminant proteins, reaching a maximum selectivity of 155 with violacein being fully concentrated in the Tween 20‐rich phase, with 80% of the contaminant proteins present in the extract being removed. CONCLUSION This work led to a conceptual downstream process based on a first step of (solid–liquid) extraction and a second step addressing the separation of violacein from contaminant proteins using ABS. © 2019 Society of Chemical Industry

Complex phenotypes, such as lipid accumulation, result from cooperativity between regulators and the integration of multiscale information. However, the elucidation of such regulatory programs by experimental approaches may be challenging, particularly in context-specific conditions. In particular, we know very little about the regulators of lipid accumulation in the oleaginous yeast of industrial interest Yarrowia lipolytica. This lack of knowledge limits the development of this yeast as an industrial platform, due to the time-consuming and costly laboratory efforts required to design strains with the desired phenotypes. In this study, we aimed to identify context-specific regulators and mechanisms, to guide explorations of the regulation of lipid accumulation in Y. lipolytica. Using gene regulatory network inference, and considering the expression of 6539 genes over 26 time points from GSE35447 for biolipid production and a list of 151 transcription factors, we reconstructed a gene regulatory network comprising 111 transcription factors, 4451 target genes and 17048 regulatory interactions (YL-GRN-1) supported by evidence of protein–protein interactions. This study, based on network interrogation and wet laboratory validation (a) highlights the relevance of our proposed measure, the transcription factors influence, for identifying phases corresponding to changes in physiological state without prior knowledge (b) suggests new potential regulators and drivers of lipid accumulation and (c) experimentally validates the impact of six of the nine regulators identified on lipid accumulation, with variations in lipid content from +43.2% to −31.2% on glucose or glycerol.

Gonadal development in medaka (Oryzias latipes) is dependent on the synergy between estrogens and androgens. Disruption of steroid hormone levels can lead to ovo‐testis. To determine the sensitive windows for hormonally induced sex reversal in medaka, we developed a novel 42sp50‐GFP_ChgH‐GFP transgenic medaka line, allowing the identification of female gonadal tissue by fluorescence present in developing oocytes. Germinal transgenesis resulted in a stable line exhibiting a strong green fluorescent protein signal constitutively in the ovaries and in the liver in response to estrogens. The sensitivity of this line to disruption of sex determination following 16‐d chronic exposures was in the nanograms per liter range. To identify the developmental period sensitive to exogenous agents, fry were exposed to 24‐h pulses of high concentrations of 17β‐estradiol (E2) or 5α‐dihydrotestosterone (DHT) at various time points between days postfertilization (dpf) 0 and 12. Evaluation of phenotype followed by genotyping at 16 dpf revealed sensitivity to E2 between 1 and 8 dpf as well as 2 periods of susceptibility to DHT between 0 and 1 dpf and 4 and 8 dpf. No phenotypic sex reversal was detected after exposure to DHT or E2 on 11 or 12 dpf. The observed effects persisted to at least 24 dpf. The identified sensitive embryonic time periods for disruption of sex determination will aid future research on sex determination and the development of screening assays using early embryonic life stages. Environ Toxicol Chem 2020;39:842–851. © 2020 SETAC