Improved robustness of an ethanologenic yeast strain through adaptive evolution in acetic acid is associated with its enzymatic antioxidant ability

Aims: To investigate multiple tolerance of Saccharomyces cerevisiae obtained through a laboratory strategy of adaptive evolution in acetic acid, its relation with enzymatic ROS detoxification and bioethanol 2G production. Methods and Results: After adaptive evolution in acetic acid, a clone (Y8A) was selected for its tolerance to high acetic acid concentrations (13 g l−1) in batch cultures. Y8A was resistant to multiple stresses: osmotic, thermic, oxidative, saline, ethanol, organic acid, phenolic compounds and slow freeze-thawing cycles. Also, Y8A was able to maintain redox homeostasis under oxidative stress, whereas the isogenic parental strain (Y8) could not, indicating higher basal activity levels of antioxidative enzyme Catalase (CAT) and Gluthatione S-transferase (GST) in Y8A. Y8A reached higher bioethanol levels in a fermentation medium containing up to 8 g l−1 of acetic acid when compared to parental strain Y8. Conclusions: A multiple-stress-tolerant clone was obtained using adaptive evolution in acetic acid. Stress cross-tolerance could be explained by its enzymatic antioxidative capacity, namely CAT and GST. Significance and Impact of the Study: We demonstrate that adaptive evolution used in S. cerevisiae was a useful strategy to obtain a yeast clone tolerant to multiple stresses. At the same time, our findings support the idea that tolerance to oxidative stress is the common basis for stress cotolerance, which is related to an increase in the specific enzymes CAT and GST but not in Superoxide dismutase, emphasizing the fact that detoxification of H2O2 and not O2˙ is a key condition for multiple stress tolerance in S. cerevisiae.Fil: Gurdo, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Novelli Poisson, Guido Fernando. Universidad de Buenos Aires; ArgentinaFil: Juárez, Angela Beatriz. Universidad de Buenos Aires; ArgentinaFil: Rios de Molina, M.C.. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Galvagno, Miguel Angel. Universidad de Buenos Aires; Argentin

Design and validation of a 63K genome-wide SNP-genotyping platform for caribou/reindeer (Rangifer tarandus)

Background Development of large single nucleotide polymorphism (SNP) arrays can make genomic data promptly available for conservation problematic. Medium and high-density panels can be designed with sufficient coverage to offer a genome-wide perspective and the generated genotypes can be used to assess different genetic metrics related to population structure, relatedness, or inbreeding. SNP genotyping could also permit sexing samples with unknown associated metadata as it is often the case when using non-invasive sampling methods favored for endangered species. Genome sequencing of wild species provides the necessary information to design such SNP arrays. We report here the development of a SNP-array for endangered Rangifer tarandus using a multi-platform sequencing approach from animals found in diverse populations representing the entire circumpolar distribution of the species. Results From a very large comprehensive catalog of SNPs detected over the entire sample set (N = 894), a total of 63,336 SNPs were selected. SNP selection accounted for SNPs evenly distributed across the entire genome (~ every 50Kb) with known minor alleles across populations world-wide. In addition, a subset of SNPs was selected to represent rare and local alleles found in Eastern Canada which could be used for ecotype and population assignments - information urgently needed for conservation planning. In addition, heterozygosity from SNPs located in the X-chromosome and genotyping call-rate of SNPs located into the SRY gene of the Y-chromosome yielded an accurate and robust sexing assessment. All SNPs were validated using a high-throughput SNP-genotyping chip. Conclusion This design is now integrated into the first genome-wide commercially available genotyping platform for Rangifer tarandus. This platform would pave the way to future genomic investigation of populations for this endangered species, including estimation of genetic diversity parameters, population assignments, as well as animal sexing from genetic SNP data for non-invasive samples

Widening of the genetic and clinical spectrum of Lamb-Shaffer syndrome, a neurodevelopmental disorder due to SOX5 haploinsufficiency

Purpose Lamb-Shaffer syndrome (LAMSHF) is a neurodevelopmental disorder described in just over two dozen patients with heterozygous genetic alterations involving SOX5, a gene encoding a transcription factor regulating cell fate and differentiation in neurogenesis and other discrete developmental processes. The genetic alterations described so far are mainly microdeletions. The present study was aimed at increasing our understanding of LAMSHF, its clinical and genetic spectrum, and the pathophysiological mechanisms involved. Methods Clinical and genetic data were collected through GeneMatcher and clinical or genetic networks for 41 novel patients harboring various types ofSOX5 alterations. Functional consequences of selected substitutions were investigated. Results Microdeletions and truncating variants occurred throughout SOX5. In contrast, most missense variants clustered in the pivotal SOX-specific high-mobility-group domain. The latter variants prevented SOX5 from binding DNA and promoting transactivation in vitro, whereas missense variants located outside the high-mobility-group domain did not. Clinical manifestations and severity varied among patients. No clear genotype-phenotype correlations were found, except that missense variants outside the high-mobility-group domain were generally better tolerated. Conclusions This study extends the clinical and genetic spectrum associated with LAMSHF and consolidates evidence that SOX5 haploinsufficiency leads to variable degrees of intellectual disability, language delay, and other clinical features

Disruption of RFX family transcription factors causes autism, attention-deficit/hyperactivity disorder, intellectual disability, and dysregulated behavior

Purpose We describe a novel neurobehavioral phenotype of autism spectrum disorder (ASD), intellectual disability, and/or attention-deficit/hyperactivity disorder (ADHD) associated with de novo or inherited deleterious variants in members of the RFX family of genes. RFX genes are evolutionarily conserved transcription factors that act as master regulators of central nervous system development and ciliogenesis. Methods We assembled a cohort of 38 individuals (from 33 unrelated families) with de novo variants in RFX3, RFX4, and RFX7. We describe their common clinical phenotypes and present bioinformatic analyses of expression patterns and downstream targets of these genes as they relate to other neurodevelopmental risk genes. Results These individuals share neurobehavioral features including ASD, intellectual disability, and/or ADHD; other frequent features include hypersensitivity to sensory stimuli and sleep problems. RFX3, RFX4, and RFX7 are strongly expressed in developing and adult human brain, and X-box binding motifs as well as RFX ChIP-seq peaks are enriched in the cis-regulatory regions of known ASD risk genes. Conclusion These results establish a likely role of deleterious variation in RFX3, RFX4, and RFX7 in cases of monogenic intellectual disability, ADHD and ASD, and position these genes as potentially critical transcriptional regulators of neurobiological pathways associated with neurodevelopmental disease pathogenesis

Global Spatial Risk Assessment of Sharks Under the Footprint of Fisheries

Effective ocean management and conservation of highly migratory species depends on resolving overlap between animal movements and distributions and fishing effort. Yet, this information is lacking at a global scale. Here we show, using a big-data approach combining satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively) and were also associated with significant increases in fishing effort. We conclude that pelagic sharks have limited spatial refuge from current levels of high-seas fishing effort. Results demonstrate an urgent need for conservation and management measures at high-seas shark hotspots and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real time, dynamic management

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14