Microbial taxonomy is increasingly influenced by genome-based computational methods. Yet such analyses can be complex and require expert knowledge. Here we introduce TYGS, the Type (Strain) Genome Server, a user-friendly high-throughput web server for genome-based prokaryote taxonomy, connected to a large, continuously growing database of genomic, taxonomic and nomenclatural information. It infers genome-scale phylogenies and state-of-the-art estimates for species and subspecies boundaries from user-defined and automatically determined closest type genome sequences. TYGS also provides comprehensive access to nomenclature, synonymy and associated taxonomic literature. Clinically important examples demonstrate how TYGS can yield new insights into microbial classification, such as evidence for a species-level separation of previously proposed subspecies of Salmonella enterica. TYGS is an integrated approach for the classification of microbes that unlocks novel scientific approaches to microbiologists worldwide and is particularly helpful for the rapidly expanding field of genome-based taxonomic descriptions of new genera, species or subspecies.

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TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy

Phylogenomic studies have resolved countless branches of the tree of life, but remain strongly contradictory on certain, contentious relationships. Here, we use a maximum likelihood framework to quantify the distribution of phylogenetic signal among genes and sites for 17 contentious branches and 6 well-established control branches in plant, animal and fungal phylogenomic data matrices. We find that resolution in some of these 17 branches rests on a single gene or a few sites, and that removal of a single gene in concatenation analyses or a single site from every gene in coalescence-based analyses diminishes support and can alter the inferred topology. These results suggest that tiny subsets of very large data matrices drive the resolution of specific internodes, providing a dissection of the distribution of support and observed incongruence in phylogenomic analyses. We submit that quantifying the distribution of phylogenetic signal in phylogenomic data is essential for evaluating whether branches, especially contentious ones, are truly resolved. Finally, we offer one detailed example of such an evaluation for the controversy regarding the earliest-branching metazoan phylum, for which examination of the distributions of gene-wise and site-wise phylogenetic signal across eight data matrices consistently supports ctenophores as the sister group to all other metazoans. Thanks to phylogenomics, reconstruction of the tree of life is now possible, yet different datasets and methods can yield contradictory relationships. Here, the authors quantify phylogenetic signals and show that contentious relationships can be supported by a tiny amount of data.

Contentious relationships in phylogenomic studies can be driven by a handful of genes.

Tempo and Mode of Genome Evolution in the Budding Yeast Subphylum.

Understanding the phylogenetic relationships among the yeasts of the subphylum Saccharomycotina is a prerequisite for understanding the evolution of their metabolisms and ecological lifestyles. In the last two decades, the use of rDNA and multilocus data sets has greatly advanced our understanding of the yeast phylogeny, but many deep relationships remain unsupported. In contrast, phylogenomic analyses have involved relatively few taxa and lineages that were often selected with limited considerations for covering the breadth of yeast biodiversity. Here we used genome sequence data from 86 publicly available yeast genomes representing nine of the 11 known major lineages and 10 nonyeast fungal outgroups to generate a 1233-gene, 96-taxon data matrix. Species phylogenies reconstructed using two different methods (concatenation and coalescence) and two data matrices (amino acids or the first two codon positions) yielded identical and highly supported relationships between the nine major lineages. Aside from the lineage comprised by the family Pichiaceae, all other lineages were monophyletic. Most interrelationships among yeast species were robust across the two methods and data matrices. However, eight of the 93 internodes conflicted between analyses or data sets, including the placements of: the clade defined by species that have reassigned the CUG codon to encode serine, instead of leucine; the clade defined by a whole genome duplication; and the species Ascoidea rubescens. These phylogenomic analyses provide a robust roadmap for future comparative work across the yeast subphylum in the disciplines of taxonomy, molecular genetics, evolutionary biology, ecology, and biotechnology. To further this end, we have also provided a BLAST server to query the 86 Saccharomycotina genomes, which can be found at http://y1000plus.org/blast.

Reconstructing the Backbone of the Saccharomycotina Yeast Phylogeny Using Genome-Scale Data.

Efficient xylose utilization is one of the most important pre-requisites for developing an economic microbial conversion process of terrestrial lignocellulosic biomass into biofuels and biochemicals. A robust ethanol producing yeast Saccharomyces cerevisiae has been engineered with heterologous xylose assimilation pathways. A two-step oxidoreductase pathway consisting of NAD(P)H-linked xylose reductase and NAD+-linked xylitol dehydrogenase, and one-step isomerase pathway using xylose isomerase have been employed to enable xylose assimilation in engineered S. cerevisiae. However, the resulting engineered yeast exhibited inefficient and slow xylose fermentation. In order to improve the yield and productivity of xylose fermentation, expression levels of xylose assimilation pathway enzymes and their kinetic properties have been optimized, and additional optimizations of endogenous or heterologous metabolisms have been achieved. These efforts have led to the development of engineered yeast strains ready for the commercialization of cellulosic bioethanol. Interestingly, xylose metabolism by engineered yeast was preferably respiratory rather than fermentative as in glucose metabolism, suggesting that xylose can serve as a desirable carbon source capable of bypassing metabolic barriers exerted by glucose repression. Accordingly, engineered yeasts showed superior production of valuable metabolites derived from cytosolic acetyl-CoA and pyruvate, such as 1-hexadecanol and lactic acid, when the xylose assimilation pathway and target synthetic pathways were optimized in an adequate manner. While xylose has been regarded as a sugar to be utilized because it is present in cellulosic hydrolysates, potential benefits of using xylose instead of glucose for yeast-based biotechnological processes need to be realized.

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Production of fuels and chemicals from xylose by engineered Saccharomyces cerevisiae: a review and perspective.

Ascomycete yeasts are metabolically diverse, with great potential for biotechnology. Here, we report the comparative genome analysis of 29 taxonomically and biotechnologically important yeasts, including 16 newly sequenced. We identify a genetic code change, CUG-Ala, in Pachysolen tannophilus in the clade sister to the known CUG-Ser clade. Our well-resolved yeast phylogeny shows that some traits, such as methylotrophy, are restricted to single clades, whereas others, such as l-rhamnose utilization, have patchy phylogenetic distributions. Gene clusters, with variable organization and distribution, encode many pathways of interest. Genomics can predict some biochemical traits precisely, but the genomic basis of others, such as xylose utilization, remains unresolved. Our data also provide insight into early evolution of ascomycetes. We document the loss of H3K9me2/3 heterochromatin, the origin of ascomycete mating-type switching, and panascomycete synteny at the MAT locus. These data and analyses will facilitate the engineering of efficient biosynthetic and degradative pathways and gateways for genomic manipulation.

https://www.pnas.org/content/pnas/113/35/9882.full.pdf

Tanya M Long

Papers

Comparative genomics of biotechnologically important yeasts