Comparative Genomics Supports That Brazilian Bioethanol Saccharomyces cerevisiae Comprise a Unified Group of Domesticated Strains Related to Cachaça Spirit Yeasts

Abstract

Ethanol production from sugarcane is a key renewable fuel industry in Brazil. Major drivers of this alcoholic fermentation are Saccharomyces cerevisiae strains that originally were contaminants to the system and yet prevail in the industrial process. Here we present newly sequenced genomes (using Illumina short-read and PacBio long-read data) of two monosporic isolates (H3 and H4) of the S. cerevisiae PE-2, a predominant bioethanol strain in Brazil. The assembled genomes of H3 and H4, together with 42 draft genomes of sugarcane-fermenting (fuel ethanol plus cachaça) strains, were compared against those of the reference S288C and diverse S. cerevisiae. All genomes of bioethanol yeasts have amplified SNO2(3)/SNZ2(3) gene clusters for vitamin B1/B6 biosynthesis, and display ubiquitous presence of a particular family of SAM-dependent methyl transferases, rare in S. cerevisiae. Widespread amplifications of quinone oxidoreductases YCR102C/YLR460C/YNL134C, and the structural or punctual variations among aquaporins and components of the iron homeostasis system, likely represent adaptations to industrial fermentation. Interesting is the pervasive presence among the bioethanol/cachaça strains of a five-gene cluster (Region B) that is a known phylogenetic signature of European wine yeasts. Combining genomes of H3, H4, and 195 yeast strains, we comprehensively assessed whole-genome phylogeny of these taxa using an alignment-free approach. The 197-genome phylogeny substantiates that bioethanol yeasts are monophyletic and closely related to the cachaça and wine strains. Our results support the hypothesis that biofuel-producing yeasts in Brazil may have been co-opted from a pool of yeasts that were pre-adapted to alcoholic fermentation of sugarcane for the distillation of cachaça spirit, which historically is a much older industry than the large-scale fuel ethanol production.

Alignment-Free Analysis of Whole-Genome Sequences From Symbiodiniaceae Reveals Different Phylogenetic Signals in Distinct Regions

“…Overall, k -mer-based phylogenetic approaches have proven robust against among-site rate variation issues and various molecular evolution scenarios based on analysis of simulated and empirical sequence data ( Chan et al, 2014 ; Bernard et al, 2016a ). Their demonstrated scalability ( Bernard et al, 2016b ; Bernard et al, 2018 ; Jacobus et al, 2021 ) enables the capture of comprehensive phylogenetic signal from large, whole-genome sequence data. This signal provides useful evidence to guide the taxonomic analysis of microbial eukaryotes, including Symbiodiniaceae ( González-Pech et al, 2021 ; Dougan et al, 2022 ), for which classification may be confounded by subtle variation in morphology and the ineffectiveness of established phylogenetic markers.…”

“…based on k -mers), while not relying on sophisticated evolutionary models, provide a scalable approach to infer biologically meaningful evolutionary relationships from whole-genome data. Support for the inferred clades on an alignment-free tree can be assessed using the jackknife technique ( Bernard et al, 2016a ; Jacobus et al, 2021 ) that provides a value similar to bootstrap support in a maximum-likelihood tree. What the different sequence regions in Symbiodiniaceae genomes can teach us about adaptation and evolutionary processes remain to be more thoroughly investigated in future studies as done for model taxa, such as Drosophila ( Oti et al, 2018 ), among others ( Gemmell, 2021 ).…”

“…In a k -mer-based phylogenetic approach, the proportion of shared k -mers between two genomes is used to calculate a pairwise distance that is used to derive a phylogenetic relationship. This approach is robust, even with the existence of genetic recombination and rearrangements ( Chan et al, 2014 ; Bernard et al, 2016a ), and has been shown to efficiently reconstruct biologically relevant phylogenies among hundreds ( Bernard et al, 2016b ; Jacobus et al, 2021 ) and thousands of microbial genomes ( Bernard et al, 2018 ). By not focusing on specific genes, alignment-free phylogenetic approaches enable the capture of phylogenomic signal from whole-genome sequences.…”

Consistency between Saccharomyces cerevisiae S288C Genome Scale Models (iND750 and iMM904)

“…Hence, it is plausible to conceive that S. cerevisiae S288C has been examined for biofuel production [11][12][13].…”

Multi-omics network model reveals key genes associated with p-coumaric acid stress response in an industrial yeast strain

“…Although some reports show that certain S. cerevisiae strains are capable of surviving high concentrations of pCA, or even being engineered to serve as templates for the production of this compound 28 , 29 , the same cannot be said for strains currently in use in the 2G bioethanol industry. These strains have a significantly different genomic makeup, in the form of nucleotide variation and structural rearrangements, caused by the intense selection process that this particular group of S. cerevisiae was subjected to 30 – 33 , and appear to be more susceptible to the inhibitory effects of these compounds 26 , 34 , 35 . Moreover, pCA is insoluble in water, but easily reacts and solubilizes in ethanol, posing a significant challenge for any type of industrial-scale fermentation process 36 .…”