Biology subjects

Hittinger, C. T.

Publications and source records attributed to Hittinger, C. T..

At least 19 recordsLinked to original sources

bioRxiv2026

Functional diversification across yeast lineages of the nucleus-vacuole junction forming protein Nvj1

Nucleus-vacuole junctions (NVJs) in Saccharomyces cerevisiae serve as an inter-organellar hub for multiple cell processes, including lipid transport and biosynthesis, an intra-nuclear quality control mechanism, and piecemeal microautophagy of the nucleus. NVJs are formed by complexes between Vac8 in the vacuole membrane and Nvj1 in the nuclear envelope. Nvj1 also links the inner and outer nuclear membranes across the perinuclear lumen. Orthologs of Nvj1 had previously only been found in yeasts of the order Saccharomycetales, raising the possibility that NVJs are restricted to this clade. Using homology and synteny, we discovered scores of novel Nvj1 orthologs across 200 million years of evolution within the subphylum Saccharomycotina. Not all orthologs mediate NVJ formation when expressed in S. cerevisiae, and some lack a sequence motif necessary for this function. Furthermore, the sequence motif required for binding the oxysterol binding protein Osh1 and an associated novel sequence motif, both found only in the order Saccharomycetales, were independently lost in three different lineages. This collection suggests specific opportunities to explore evolutionary and functional adaptations of Nvj1s in ecologically and physiologically diverse yeasts.

cell biology↗

bioRxiv2026

Evolutionary origins of protein novelty across an entire yeast subphylum

Novel protein-coding sequences fuel molecular and cellular evolutionary innovations and frequently contribute to species-defining characteristics. They can originate either de novo from previously noncoding sequences or through extreme divergence of already coding ones. How frequently each mechanism occurs and how they shape the structural and functional potential of the resulting proteins remains unclear. Here, we conducted a broad computational investigation of genetic and protein novelty throughout the entire subphylum of Saccharomycotina yeasts. We detected more than 5,000 robust de novo genes across 332 species and compared them to more than 6,000 novel genes resulting from extreme sequence divergence, revealing two quantitatively similar but qualitatively distinct modes of evolution of novelty. A remarkable 40% of de novo proteins are predicted to localize to mitochondria compared to only 20% of divergent, with the latter also being substantially longer and more disordered. A detailed analysis of conservatively predicted tertiary structures of novel proteins shows that ''invention'' of new folds occurs more frequently through de novo emergence. We also illustrate cases of evolutionary ''re-invention'' of existing protein folds from noncoding sequences. Our work deepens our understanding of the origins and importance of novel proteins, opening new directions for further structural and functional characterization.

genomics↗

bioRxiv2025

The Macroevolution of Filamentation Morphology Across the Saccharomycotina Yeast Subphylum

Saccharomycotina yeasts are a highly diverse and widely distributed subphylum of ascomycete fungi that exhibit diversity in their asexual growth morphologies; the human commensal yeast Candida albicans exhibits both unicellular and filamentous growth, whereas the bakers yeast Saccharomyces cerevisiae grows unicellularly by budding. Filamentous growth (and the production of hyphae) can comprise linear and branched budding cells that do not undergo cell separation, termed pseudohyphae, or of tubular filaments with septa that perforate allowing movement of organelles, termed true hyphae. We integrated phenotypic, genomic, metabolic, and isolation environment data from 1,154 strains from 1,051 Saccharomycotina species to examine the variation and evolutionary history of filamentation across Saccharomycotina and determine the extent to which genes, metabolic traits, and environments can predict filamentation types. We found that 63.37% of strains can form filaments; 6.56% can form true hyphae, 42.40% can form pseudohyphae, and 14.39% can form both true hyphae and pseudohyphae. We found that the distributions of species that can produce true hyphae or that can filament were more strongly correlated with the yeast phylogeny than the distribution of species with pseudohyphae. Ancestral state reconstruction suggested that the ability to form true hyphae and/or pseudohyphae evolved several times in yeast evolution. We infer that most yeast ancestors likely produced pseudohyphae or lacked filaments, while the Saccharomycotina last common ancestor likely produced pseudohyphae but not true hyphae. Machine learning models trained on genomic and metabolic features predicted filament morphologies with about 70% accuracy. Connecting the evolution of Saccharomycotina morphologies to their genomic, metabolic, and ecological characteristics will enrich our understanding of the evolution of the diversity of lifestyles observed in this lineage.

evolutionary biology↗

bioRxiv2025

A trait syndrome ties cell morphology to glycolysis across the yeast subphylum

Traits that co-vary across species can provide fundamental insights into the trade-offs and constraints that govern their evolution. It was recently reported that glucose uptake rates (GUR) are inversely correlated with the cell surface area-to-volume (SA:V) ratio across 11 yeast species. Here we substantially expand this analysis to 282 species to test whether the GUR-SA:V correlation generalizes across the ancient Saccharomycotina yeast subphylum and to determine the contribution of shared evolutionary history to the co-variation of these two traits. Using regression models that account for co-variation due to phylogeny, we found that extracellular acidification rates (ECAR, which we used as a scalable proxy for GUR) had a weak, but significant, correlation with SA:V across Saccharomycotina. We found additional weak, but significant, correlations between ECAR with genome sizes and growth rates. Our findings largely agree with the recently reported correlations between GUR and SA:V ratio, but they also show that there are likely several other associated variables, including genome size. Specifically, yeasts that consume glucose faster tend to have lower SA:V, faster growth rates, and larger genomes. Our results suggest that a trait syndrome governs several metabolic, genomic, and morphological traits across the yeast subphylum.

evolutionary biology↗

bioRxiv2025

An evolved strain of Spathaspora passalidarum produces ethanol from sugarcane bagasse and switchgrass lignocellulosic hydrolysates

Lignocellulosic hydrolysates, derived from plant biomass, contain various inhibitors that can hinder microbial growth. This study aimed to enable the growth and ethanol production by the xylose-fermenting yeast Spathaspora passalidarum in the presence of lignocellulosic hydrolysate inhibitors, particularly acetic acid. Ultraviolet (UV)-induced mutagenesis and adaptive laboratory evolution (ALE) were used to select for mutants with higher tolerance to these inhibitors. The initial mutant strain, MT01, was selected for increased growth in medium containing xylose and acetic acid. This strain underwent further evolution, resulting in the strain ME3.5.5, which showed significant improvements in both growth and ethanol production compared to the parental strain when tested in sugarcane bagasse hemicellulosic hydrolysate (SBHH). Genomic analysis identified non-synonymous and frameshift mutations in four genes, including CYR1 (encoding adenylate cyclase). These findings suggest that genetically optimized S. passalidarum strains could play a crucial role in advancing industrial bioethanol production from lignocellulosic biomass by overcoming the inhibitory effects of compounds found in lignocellulosic hydrolysates.

genomics↗

bioRxiv2025

MAESTRO uncovers tandem paralog dynamics as a core driver of fungal stress adaptation

Understanding how fungi adapt to diverse stresses is critical for mitigating emerging drug resistance and harnessing their robustness for biotechnology. Pichia kudriavzevii is a stress-tolerant and intrinsically drug-resistant yeast, with dual industrial and clinical importance. We analyzed 170 strains using MAESTRO, a machine-learning-assisted GWAS pipeline optimized for small cohorts. MAESTRO identified biologically meaningful features and revealed that copy number variation (CNV) of tandem paralogs (TPs) is a core mechanism of multi-stress adaptation. TPs were recurrently linked to tolerance of industrial inhibitors (HMF, phenolics, heat) and antifungal drugs (fluconazole, azoles), and deletion of the TP pair gene4260/gene4261 confirmed pleiotropic effects across stresses. These findings support a TP CNV model where recombination-driven TP CNVs and gene fusions enable rapid stress adaptation. Importantly, our results suggest that antifungal resistance can arise through co-option of mechanisms originally evolved for environmental stressors, raising a One Health concern about the environmental origins of drug-resistant pathogens.

genomics↗

bioRxiv2025

Discovery of additional ancient genome duplications in yeasts

Whole genome duplication (WGD) has had profound macroevolutionary impacts on diverse lineages1,2, preceding adaptive radiations in vertebrates3-5, teleost fish6,7, and angiosperms8,9. In contrast to the many known ancient WGDs in animals10,11 and especially plants12-14, we are aware of evidence for only four in fungi15,16. The oldest of these occurred [~]100 million years ago (mya) and is shared by [~]60 extant Saccharomycetales species17,18, including the bakers yeast Saccharomyces cerevisiae (Fig. 1). Notably, this is the only known ancient WGD in the yeast subphylum Saccharomycotina. The dearth of ancient WGD events in fungi remains a mystery15. Some studies have suggested that fungal lineages that experience chromosome19 and genome15 duplication quickly go extinct, leaving no trace in the genomic record, while others contend that the lack of known WGD is due to an absence of data15,16. Under the second hypothesis, additional sampling and deeper sequencing of fungal genomes should lead to the discovery of more WGD events. Coupling hundreds of recently published genomes from nearly every described Saccharomycotina species with three additional long-read assemblies, we discovered three novel WGD events. While the functions of retained duplicate genes originating from these events are broad, they bear many similarities to the well-known WGD that occurred in the Saccharomycetales17. Our results suggest that WGD may be a more common evolutionary force in fungi than previously believed. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/673279v1_fig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@6a8f47org.highwire.dtl.DTLVardef@1e4a790org.highwire.dtl.DTLVardef@b4e0eforg.highwire.dtl.DTLVardef@11b7795_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Three additional whole genome duplications in Saccharomycotina yeasts. Rates of gene duplication are mapped onto Saccharomycetales (left) and Dipodascales (right) phylogenies. Whole genome duplications indicated along the lineages in which they are predicted to occur. Trees have been pruned for visualization purposes. C_FIG HighlightsO_LIEvidence for three whole genome duplications (WGDs) in Dipodascales yeasts C_LIO_LIImpacts of WGD are broad but bear many similarities to the known WGD in Saccharomycetales yeasts C_LIO_LIDuplicates with many protein-protein interactions are more likely to be retained over long timescales C_LIO_LIWGD in fungi is likely underreported C_LI

evolutionary biology↗

bioRxiv2025

Machine learning identifies novel signatures of antifungal drug resistance in Saccharomycotina yeasts

Antifungal drug resistance is a major challenge in fungal infection management. Numerous genomic changes are known to contribute to acquired drug resistance in clinical isolates of specific pathogens, but whether they broadly explain natural resistance across entire lineages is unknown. We leveraged genomic, ecological, and phenotypic trait data from naturally sampled strains from nearly all known species in subphylum Saccharomycotina to examine the evolution of resistance to eight antifungal drugs. The phylogenetic distribution of drug resistance varied by drug; fluconazole resistance was widespread, while 5-fluorocytosine resistance was rare, except in Lipomycetales. A random forest algorithm trained on genomic data predicted drug-resistant yeasts with 54-75% accuracy. In general, frequency of drug resistance correlated with prediction accuracy, with fluconazole resistance being consistently predicted with the highest accuracy (74.9%). Fluconazole resistance accuracy was similar between models trained on genome-wide variation in the presence and number of InterPro protein annotations across Saccharomycotina (74.9% accuracy) and those trained on amino acid sequence alignment data of Erg11, a protein known to be involved in fluconazole resistance (74.3-74.9% accuracy). Interestingly, the top Erg11 residues for predicting fluconazole resistance across Saccharomycotina do not overlap with, are not spatially close to, and are less conserved than those previously linked to resistance in clinical isolates of Candida albicans. In silico deep mutational scanning of the C. albicans Erg11 protein revealed that amino acid variants implicated in clinical cases of resistance are almost universally destabilizing while variants in our most informative residues are energetically more neutral, explaining why the latter are much more common than the former in natural populations. Importantly, previous experimental analyses of C. albicans Erg11 have shown that amino acid variation in our most informative residues, despite having never been directly implicated in clinical cases, can directly contribute to resistance. Our results suggest that studies of natural resistance in yeast species never encountered in the clinic will yield a fuller understanding of antifungal drug resistance.

microbiology↗

bioRxiv2025

Ancient co-option of LTR retrotransposons as yeast centromeres

The evolutionary origins of the genetic point centromere in the brewers yeast Saccharomyces cerevisiae, a member of the order Saccharomycetales, are still unknown. Competing hypotheses suggest that the point centromere tripartite genetic centromere DNA elements (CDEs) either evolved from ancestral epigenetic centromeres by descent with modification or were gained through horizontal transfer from selfish DNA plasmids.1,2 Here, we identified centromeres in the sister order Saccharomycodales and termed them "proto-point centromeres" due to sequence features that bridge the evolutionary gap between point centromeres and ancestral centromeres types. Comparative genomic analyses across multiple yeast orders showed an unexpected evolutionary link between point and proto-point centromeres to the long terminal repeats (LTRs) of Ty5 retrotransposons. Strikingly, one Saccharomycodales species, Saccharomycodes ludwigii, harbors compact Ty5-based centromeres, where its CDEII elements are divergent AT-rich Ty5 LTRs. These living fossil centromeres show how retrotransposon cis-regulation was likely co-opted for genetic centromere specification. These insights show that point centromeres are direct descendants of retrotransposons and have evolved by descent with modification. Ultimately, the many diverse centromere types across the yeast subphylum may share a common ancestry rooted in retrotransposon activity.

evolutionary biology↗

bioRxiv2025

Stable hypermutators revealed by the genomic landscape of DNA repair genes among yeast species

Mutator phenotypes are short-lived due to the rapid accumulation of deleterious mutations. Yet, recent observations reveal that certain fungi can undergo prolonged accelerated evolution after losing DNA repair genes. Here, we surveyed 1,154 yeast genomes representing nearly all known yeast species of the subphylum Saccharomycotina to examine the relationship between reduced DNA repair repertoires and elevated evolutionary rates. We identified three distantly related lineages--encompassing 12% of species--with substantially reduced sets of DNA repair genes and the highest evolutionary rates in the entire subphylum. Two of these "faster-evolving lineages" (FELs)--a subclade within the order Pichiales and the Wickerhamiella/Starmerella (W/S) clade (order Dipodascales)--are described here for the first time, while the third corresponds to a previously documented Hanseniaspora FEL. Examination of DNA repair gene repertoires revealed a set of genes predominantly absent in these three FELs, suggesting a potential role in the observed acceleration of evolutionary rates. Genomic signatures in the W/S clade are consistent with a substantial mutational burden, including pronounced A|T bias and signatures of endogenous DNA damage. The W/S clade appears to mitigate UV-induced damage through horizontal acquisition of a bacterial photolyase gene, underscoring how gene loss may be offset by nonvertical evolution. These findings highlight how the loss of DNA repair genes gave rise to hypermutators that persist across macroevolutionary timescales, with horizontal gene transfer as an avenue for partial functional compensation.

evolutionary biology↗

bioRxiv2025

Genomic factors limiting the diversity of Saccharomycotina plant pathogens

The Saccharomycotina fungi have evolved to inhabit a vast diversity of habitats over their 400-million-year evolution. There are, however, only a few known fungal pathogens of plants in this subphylum, primarily belonging to the genera Eremothecium and Geotrichum. We compared the genomes of 12 plant-pathogenic Saccharomycotina strains to 360 plant-associated strains to identify features unique to the phytopathogens. Characterization of the oxylipin synthesis genes, a compound believed to be involved in Eremothecium pathogenicity, did not reveal any differences in gene presence within or between the plant-pathogenic and plant-associated strains. A reverse-ecological approach, however, revealed that plant pathogens lack several metabolic enzymes known to assist other phytopathogens in overcoming plant defenses. This includes L-rhamnose metabolism, formamidase and nitrilase genes. This result suggests that the Saccharomycotina plant pathogens are limited to infecting ripening fruits as they are without the necessary enzymes to degrade common phytohormones and secondary metabolites produced by plants.

genomics↗

bioRxiv2025

pH adjustment increases biofuel production from inhibitory switchgrass hydrolysates

Biofuels derived from renewable and sustainable lignocellulosic biomass, such as switchgrass, offer a promising means to limit greenhouse gas emissions. However, switchgrass grown under drought conditions contains high levels of chemical compounds that inhibit microbial conversion to biofuels. Fermentation of drought switchgrass hydrolysates by engineered Saccharomyces cerevisiae and Zymomonas mobilis generates less ethanol than fermentation of hydrolyzed switchgrass from an average rainfall year. Here, we demonstrate that this inhibitory effect can be alleviated by altering the pH of drought-switchgrass hydrolysates made from two different pretreatment methods: Ammonia Fiber Expansion (AFEX) and Soaking in Aqueous Ammonia (SAA). Fermentation rates and biofuel production from AFEX- and SAA-pretreated switchgrass hydrolysates from normal and drought years were higher at pH 5.8 than at pH 5.0 for both Saccharomyces cerevisiae and Zymomonas mobilis. Additionally, SAA pretreatment of drought switchgrass enabled increased fermentation rates and titers compared to AFEX pretreatment. Using a synthetic mimic of switchgrass hydrolysate, we identified relief from pH-dependent inhibition by lignocellulose-derived inhibitors as the cause of increased biofuel production above a pH of 5.0. These results demonstrate that SAA pretreatment and pH adjustment can significantly improve fermentation and biofuel production from switchgrass hydrolysates and especially from drought-switchgrass hydrolysates by industrial microorganisms.

microbiology↗

bioRxiv2024

Machine learning uncovers gene families impacting oxidative stress resistance across yeasts

Reactive oxygen species (ROS) are highly reactive molecules encountered by yeasts during routine metabolism and during interactions with other organisms, including host infection. Here, we characterized the variation in resistance to ROS across the ancient yeast subphylum Saccharomycotina and used machine learning (ML) to identify gene families whose sizes were predictive of ROS resistance. The most predictive features were enriched in gene families related to cell wall organization and included two reductase gene families. We estimated the quantitative contributions of features to each species classification to guide experimental validation and showed that overexpression of the old yellow enzyme (OYE) reductase increased ROS resistance in Kluyveromyces lactis, while Saccharomyces cerevisiae mutants lacking multiple mannosyltransferase-encoding genes were hypersensitive to ROS. Altogether, this work provides a framework for how ML can uncover genetic mechanisms underlying trait variation across diverse species and inform trait manipulation for clinical and biotechnological applications.

microbiology↗

bioRxiv2024

Convergent expansions of keystone gene families drive metabolic innovation in a major eukaryotic clade

Many remarkable innovations have repeatedly occurred across vast evolutionary distances. When convergent traits emerge on the tree of life, they are sometimes driven by the same underlying gene families, while other times many different gene families are involved. Conversely, a gene family may be repeatedly recruited for a single trait or many different traits. To understand the general rules governing convergence at both genomic and phenotypic levels, we systematically tested associations between 56 binary metabolic traits and gene count in 14,710 gene families from 993 species of Saccharomycotina yeasts. Using a recently developed phylogenetic approach that reduces spurious correlations, we discovered that gene family expansion and contraction was significantly linked to trait gain and loss in 45/56 (80%) of traits. While 601/746 (81%) of significant gene families were associated with only one trait, we also identified several keystone gene families that were significantly associated with up to 13/56 (23%) of all traits. These results indicate that metabolic innovations in yeasts are governed by a narrow set of major genetic elements and mechanisms.

evolutionary biology↗

bioRxiv2024

Specialization restricts the evolutionary paths available to yeast sugar transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence-function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an -glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning approximately 400 million years of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast -glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

evolutionary biology↗

bioRxiv2024

Unique trajectory of gene family evolution from genomic analysis of nearly all known species in an ancient yeast lineage

Gene gains and losses are a major driver of genome evolution; their precise characterization can provide insights into the origin and diversification of major lineages. Here, we examined gene family evolution of 1,154 genomes from nearly all known species in the medically and technologically important yeast subphylum Saccharomycotina. We found that yeast gene family and genome evolution are distinct from plants, animals, and filamentous ascomycetes and are characterized by small genome sizes and smaller gene numbers but larger gene family sizes. Faster-evolving lineages (FELs) in yeasts experienced significantly higher rates of gene losses--commensurate with a narrowing of metabolic niche breadth--but higher speciation rates than their slower-evolving sister lineages (SELs). Gene families most often lost are those involved in mRNA splicing, carbohydrate metabolism, and cell division and are likely associated with intron loss, metabolic breadth, and non-canonical cell cycle processes. Our results highlight the significant role of gene family contractions in the evolution of yeast metabolism, genome function, and speciation, and suggest that gene family evolutionary trajectories have differed markedly across major eukaryotic lineages.

evolutionary biology↗

bioRxiv2024

Genomic factors shaping codon usage across the Saccharomycotina subphylum

Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. The biased use of synonymous codons has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces. The Saccharomycotina, the fungal subphylum containing the yeasts Saccharomyces cerevisiae and Candida albicans, has been a model system for studying codon usage. We characterized codon usage across 1,154 strains from 1,051 species to gain insight into the biases, molecular mechanisms, evolution, and genomic features contributing to codon usage patterns across the subphylum. We found evidence of a general preference for A/T-ending codons and correlations between codon usage bias, GC content, and tRNA-ome size. Codon usage bias is also distinct between the 12 orders within the subphylum to such a degree that yeasts can be classified into orders with an accuracy greater than 90% using a machine learning algorithm trained on codon usage. We also characterized the degree to which codon usage bias is impacted by translational selection. Interestingly, the degree of translational selection was influenced by a combination of genome features and assembly metrics that included the number of coding sequences, BUSCO count, and genome length. Our analysis also revealed an extreme bias in codon usage in the Saccharomycodales associated with a lack of predicted arginine tRNAs. The order contains 24 species, and 23 are computationally predicted to lack tRNAs that decode CGN codons, leaving only the AGN codons to encode arginine. Analysis of Saccharomycodales gene expression, tRNA sequences, and codon evolution suggests that extreme avoidance of the CGN codons is associated with a decline in arginine tRNA function. Codon usage bias within the Saccharomycotina is generally consistent with previous investigations in fungi, which show a role for both genomic features and GC bias in shaping codon usage. However, we find cases of extreme codon usage preference and avoidance along yeast lineages, suggesting additional forces may be shaping the evolution of specific codons.

genomics↗

bioRxiv2024

Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will only be maintained if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74-94% of the variance in aneuploid strains growth rates is explained by the additive cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of snoRNAs and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.

genomics↗