Natural Variation in Diauxic Shift between Patagonian Saccharomyces eubayanus Strains

The study of natural variation can untap novel alleles with immense value for biotechnological applications. Saccharomyces eubayanus Patagonian isolates exhibit differences in the diauxic shift between glucose and maltose, representing a suitable model to study their natural genetic variation for novel strains for brewing. However, little is known about the genetic variants and chromatin regulators responsible for these differences. Here, we show how genome-wide chromatin accessibility and gene expression differences underlie distinct diauxic shift profiles in S. eubayanus. We identified two strains with a rapid diauxic shift between glucose and maltose (CL467.1 and CBS12357) and one strain with a remarkably low fermentation efficiency and longer lag phase during diauxic shift (QC18). This is associated in the QC18 strain with lower transcriptional activity and chromatin accessibility of specific genes of maltose metabolism and higher expression levels of glucose transporters. These differences are governed by the HAP complex, which differentially regulates gene expression depending on the genetic background. We found in the QC18 strain a contrasting phenotype to those phenotypes described in S. cerevisiae, where hap4D, hap5D, and cin5D knockouts significantly improved the QC18 growth rate in the glucose-maltose shift. The most profound effects were found between CIN5 allelic variants, suggesting that Cin5p could strongly activate a repressor of the diauxic shift in the QC18 strain but not necessarily in the other strains. The differences between strains could originate from the tree host from which the strains were obtained, which might determine the sugar source preference and the brewing potential of the strain.Fil: Molinet, Jennifer. Universidad de Santiago de Chile; ChileFil: Eizaguirre, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales. Universidad Nacional del Comahue. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales; ArgentinaFil: Quintrel, Pablo. Universidad de Santiago de Chile; ChileFil: Bellora, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia de Área de Aplicaciones de la Tecnología Nuclear. Instituto de Tecnologías Nucleares para la Salud; ArgentinaFil: Villarroel, Carlos A.. Universidad de Talca; ChileFil: Villarreal, Pablo. Universidad de Santiago de Chile; ChileFil: Benavides Parra, José. Universidad de Santiago de Chile; ChileFil: Nespolo, Roberto F.. Universidad Austral de Chile; ChileFil: Libkind Frati, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales. Universidad Nacional del Comahue. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales; ArgentinaFil: Cubillos, Francisco A.. Universidad de Santiago de Chile; Chil

Generation of a Non-Transgenic Genetically Improved Yeast Strain for Wine Production from Nitrogen-Deficient Musts

The yeast Saccharomyces cerevisiae is the main species responsible for the process that involves the transformation of grape must into wine, with the initial nitrogen in the grape must being vital for it. One of the main problems in the wine industry is the deficiency of nitrogen sources in the grape must, leading to stuck or sluggish fermentations, and generating economic losses. In this scenario, an alternative is the isolation or generation of yeast strains with low nitrogen requirements for fermentation. In the present study, we carry out a genetic improvement program using as a base population a group of 70 strains isolated from winemaking environments mainly in Chile and Argentina (F0), making from it a first and second filial generation (F1 and F2, respectively) based in different families and hybrids. It was found that the trait under study has a high heritability, obtaining in the F2 population strains that consume a minor proportion of the nitrogen sources present in the must. Among these improved strains, strain “686” specially showed a marked drop in the nitrogen consumption, without losing fermentative performance, in synthetic grape must at laboratory level. When using this improved strain to produce wine from a natural grape must (supplemented and non-supplemented with ammonium) at pilot scale under wine cellar conditions, a similar fermentative capacity was obtained between this strain and a widely used commercial strain (EC1118). However, when fermented in a non-supplemented must, improved strain “686” showed the presence of a marked floral aroma absent for EC1118 strain, this difference being probably a direct consequence of its different pattern in amino acid consumption. The combination of the capacity of improved strain “686” to ferment without nitrogen addition and produce floral aromas may be of commercial interest for the wine industry.Fil: Kessi Pérez, Eduardo. Universidad de Santiago de Chile; ChileFil: Molinet, Jennifer. Universidad de Santiago de Chile; ChileFil: García, Verónica. Universidad de Santiago de Chile; ChileFil: Aguilera, Omayra. Universidad de Santiago de Chile; ChileFil: Cepeda, Fernanda. Universidad de Chile; ChileFil: López, María. Universidad de Chile; ChileFil: Sari, Santiago. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Mendoza-San Juan. Estación Experimental Agropecuaria Mendoza; ArgentinaFil: Cuello, Raúl Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Mendoza-San Juan. Estación Experimental Agropecuaria Mendoza; ArgentinaFil: Ciklic, Iván Francisco. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Mendoza-San Juan. Estación Experimental Agropecuaria Mendoza; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Rojo, María Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Mendoza-San Juan. Estación Experimental Agropecuaria Mendoza. Centro de Estudios Enológicos; ArgentinaFil: Combina, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Mendoza-San Juan. Estación Experimental Agropecuaria Mendoza. Centro de Estudios Enológicos; ArgentinaFil: Araneda, Cristián. Universidad de Chile; ChileFil: Martínez, Claudio. Universidad de Santiago de Chile; Chil

GTR1 Affects Nitrogen Consumption and TORC1 Activity in Saccharomyces cerevisiae Under Fermentation Conditions

The TORC1 pathway coordinates cell growth in response to nitrogen availability present in the medium, regulating genes related to nitrogen transport and metabolism. Therefore, the adaptation of Saccharomyces cerevisiae to changes in nitrogen availability implies variations in the activity of this signaling pathway. In this sense, variations in nitrogen detection and signaling pathway are one of the main causes of differences in nitrogen assimilation during alcoholic fermentation. Previously, we demonstrated that allelic variants in the GTR1 gene underlying differences in ammonium and amino acids consumption between Wine/European (WE) and West African (WA) strains impact the expression of nitrogen transporters. The GTR1 gene encodes a GTPase that participates in the EGO complex responsible for TORC1 activation in response to amino acids availability. In this work, we assessed the role of the GTR1 gene on nitrogen consumption under fermentation conditions, using a high sugar concentration medium with nitrogen limitation and in the context of the WE and WA genetic backgrounds. The gtr1Δ mutant presented a reduced TORC1 activity and increased expression levels of nitrogen transporters, which in turn favored ammonium consumption, but decreased amino acid assimilation. Furthermore, to identify the SNPs responsible for differences in nitrogen consumption during alcoholic fermentation, we studied the polymorphisms present in the GTR1 gene. We carried out swapping experiments for the promoter and coding regions of GTR1 between the WE and WA strains. We observed that polymorphisms in the coding region of the WA GTR1 gene are relevant for TORC1 activity. Altogether, our results highlight the role of the GTR1 gene on nitrogen consumption in S. cerevisiae under fermentation conditions.This work was supported by the Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) Programa Formación de Capital Humano Avanzado (PCHA) Doctorado Nacional (Grant No. 2014-21140935 to JM), Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT) (Grant No. 1150522 to CM and Grant No. 11170158 to FS) and Programa de Cooperación Internacional (CONICYT/PCI) (Grant No. REDI170239 to FS and CM); by the Instituto Milenio iBio – Iniciativa Científica Milenio MINECON to FS; and by the Spanish Government through “Ministerio de Ciencia, Innovación y Universidades” (MICINN) and “Fondo Europeo de Desarrollo Regional” (FEDER) (Grant No. PCIN-2015-143; European Project ERA-IB “YeastTempTation” to JG).Peer reviewe

Genetic variants of TORC1 signaling pathway affect nitrogen consumption in Saccharomyces cerevisiae during alcoholic fermentation

International audienceIn the alcoholic fermentation process, Saccharomyces cerevisiae strains present differences in their nitrogen consumption profiles, these phenotypic outcomes have complex genetic and molecular architectures. In this sense, variations in nitrogen signaling pathways regulated by TORC1 represent one of the main sources of phenotypic diversity in nitrogen consumption. This emphasizes the possible roles that allelic variants from the TORC1 pathway have in the nitrogen consumption differences observed in yeast during the alcoholic fermentation. Here, we studied the allelic diversity in the TORC1 pathway across four yeast strains and determined how these polymorphisms directly impact nitrogen consumption during alcoholic fermentation. Using a reciprocal hemizygosity approach combined with phenotyping under fermentative conditions, we found that allelic variants of GTR1, TOR2, SIT4, SAP185, EAP1, NPR1 and SCH9 underlie differences in the ammonium and amino acids consumption phenotypes. Among these, GTR1 alleles from the Wine/European and West African genetic backgrounds showed the greatest effects on ammonium and amino acid consumption, respectively. Furthermore, we identified allelic variants of SAP185, TOR2, SCH9 and NPR1 from an oak isolate that increased the amino acid consumption preference over ammonium; representing putative candidates coming from a non-domesticated strain that could be used for genetic improvement programs. In conclusion, our results demonstrated that a large number of allelic variants within the TORC1 pathway significantly impacts on regulatory mechanisms of nitrogen assimilation during alcoholic fermentation

Wild Patagonian yeast improve the evolutionary potential of novel interspecific hybrid strains for lager brewing.

Lager yeasts are limited to a few strains worldwide, imposing restrictions on flavour and aroma diversity and hindering our understanding of the complex evolutionary mechanisms during yeast domestication. The recent finding of diverse S. eubayanus lineages from Patagonia offers potential for generating new lager yeasts with different flavour profiles. Here, we leverage the natural genetic diversity of S. eubayanus and expand the lager yeast repertoire by including three distinct Patagonian S. eubayanus lineages. We used experimental evolution and selection on desirable traits to enhance the fermentation profiles of novel S. cerevisiae x S. eubayanus hybrids. Our analyses reveal an intricate interplay of pre-existing diversity, selection on species-specific mitochondria, de-novo mutations, and gene copy variations in sugar metabolism genes, resulting in high ethanol production and unique aroma profiles. Hybrids with S. eubayanus mitochondria exhibited greater evolutionary potential and superior fitness post-evolution, analogous to commercial lager hybrids. Using genome-wide screens of the parental subgenomes, we identified genetic changes in IRA2, IMA1, and MALX genes that influence maltose metabolism, and increase glycolytic flux and sugar consumption in the evolved hybrids. Functional validation and transcriptome analyses confirmed increased maltose-related gene expression, influencing greater maltotriose consumption in evolved hybrids. This study demonstrates the potential for generating industrially viable lager yeast hybrids from wild Patagonian strains. Our hybridization, evolution, and mitochondrial selection approach produced hybrids with high fermentation capacity and expands lager beer brewing options

The evolution, evolvability and engineering of gene regulatory DNA

Mutations in non-coding regulatory DNA sequences can alter gene expression, organismal phenotype and fitness1-3. Constructing complete fitness landscapes, in which DNA sequences are mapped to fitness, is a long-standing goal in biology, but has remained elusive because it is challenging to generalize reliably to vast sequence spaces4-6. Here we build sequence-to-expression models that capture fitness landscapes and use them to decipher principles of regulatory evolution. Using millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Saccharomyces cerevisiae, we learn deep neural network models that generalize with excellent prediction performance, and enable sequence design for expression engineering. Using our models, we study expression divergence under genetic drift and strong-selection weak-mutation regimes to find that regulatory evolution is rapid and subject to diminishing returns epistasis; that conflicting expression objectives in different environments constrain expression adaptation; and that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for using such models to detect signatures of selection on expression from natural variation in regulatory sequences and use it to discover an instance of convergent regulatory evolution. We assess mutational robustness, finding that regulatory mutation effect sizes follow a power law, characterize regulatory evolvability, visualize promoter fitness landscapes, discover evolvability archetypes and illustrate the mutational robustness of natural regulatory sequence populations. Our work provides a general framework for designing regulatory sequences and addressing fundamental questions in regulatory evolution

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.