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Steenwyk, J. L.

Publications and source records attributed to Steenwyk, J. L..

At least 19 recordsLinked to original sources

A geometric atlas of how ESM3 organizes modalities across depth

Protein language models learn general-purpose representations from large collections of protein sequences and structures, and have advanced the prediction of protein structure and function. ESM3 is a multimodal protein language model that ingests a protein through several channels at once, including amino-acid sequence, three-dimensional structure, secondary structure (SS8), solvent accessibility (SASA), and discrete functional annotations, summing their embeddings into a single residual stream. Little is known about whether these modalities occupy separate subspaces and the depth at which they fuse. The present analysis examines ESM3 (esm3-sm-open-v1; 1.4 billion parameters; 48 transformer layers) once per modality in isolation and applies representational-similarity analysis across all 48 layers. The four physical modalities (sequence, structure, SS8, SASA) begin in distinct subspaces, remain maximally separated through roughly the first half of layers, and then fuse into a shared low-dimensional subspace between layers 25 and 35. The fusion is ordered. The structure-derived modalities (structure, SS8, SASA) are mutually aligned from the input, whereas sequence joins last, after layer 28. The functional-annotation modality never fuses; instead, it remains representationally orthogonal to the physical modalities at every layer, and this orthogonality holds whether the annotation is supplied as whole-protein or per-residue, suggesting that it is content-driven rather than a tokenization arti-fact. The fusion is a learned property, absent in a randomly initialized model of the same architecture, holds at the residue level below the mean-pool, and reorganizes variance, converting between-condition variance into within-condition variance while the stream never approaches isotropy. Fusion depth is independent of protein length but is delayed by structural disorder. The phenomenon is universal across diverse organisms. Across 5,555 proteins from 12 organisms spanning eukaryota, bacteria, and archaea, every superkingdom (and every individual organism) reaches peak modality fusion at the same network depth (layer 35).

bioinformatics↗

Structure tokens sharpen the feature vocabulary of protein language models

Protein language models predict structure and function from amino acid sequences, but the internal computations that produce these predictions remain opaque. We applied sparse autoencoders to ESM-2 (650M parameters, sequence-only) and ESM-3 (1.4B parameters, multimodal) and found that 78% of learned features converge between the two architectures (permutation null: 14.2%, p < 0.001). These convergent features account for nearly all functional knowledge encoded by the models (functional site AUROC 0.925 versus 0.661 for architecture-unique features). Structure tokens in ESM-3 do not create a new feature vocabulary. Instead, the 15.2% of features most activated by structure tokens are more convergent with sequence-only ESM-2 than structure-invariant features are (r = 0.54 versus 0.45) and carry richer biological annotation (134 versus 29 enriched GO terms). Attention analysis identified a single geometric head (L0H7) as the bottleneck through which structural information enters the network; ablating this head alone changed secondary structure predictions at 40% of residues, while ablating random layer-0 heads altered fewer than 17%. Steering vectors, attribution patching, and sparse feature circuits confirmed that these features sit within the models causal pathway. Two architecturally distinct models, trained on different objectives and input modalities, converge on a shared biological vocabulary -- and explicit structure tokens sharpen that vocabulary rather than rewriting it.

bioinformatics↗

Antarctic marine microplastics reveals environmental persistence and rapid evolution of Candida auris

Candida (Candidozyma) auris is a critical priority fungal pathogen that emerged two decades ago near simultaneously on multiple continents. Since emergence, C. auris resistance to all four classes of antifungal drugs has been described, including pan-drug resistant isolates, sometimes evolving within patients. Here, we confirm the first isolation of C. auris from Antarctica and show cold-adapted phenotypes and an affinity for binding to nylon. We also provide evidence to suggest mutator phenotypes contribute to the rapid evolution of C. auris and are responsible for the emergence of multiple, distinct genetic clades worldwide. Isolates in clades I, III and IV with a mutator phenotype displayed elevated mutation rates compared to non-auris Candida species. This phenotype had a complex genetic basis and was associated with drug resistance mutations. We postulate that the mutator phenotype has a significant effect on evolutionary potential and is responsible for the emergence and rapid spread of drug-resistance C. auris and novel genetic clades.

microbiology↗

PAQman: reference-free ensemble evaluation of long-read eukaryotic genome assemblies

Advances in long-read sequencing have made it easier and more cost effective to generate high-quality genome assemblies. However, assessing assembly quality remains a challenge, as existing tools often focus on a few metrics and/or require a reference assembly for comparison. Furthermore, the number of available metrics and associated tools for genome evaluation have expanded in recent years, making it more difficult for researchers to easily use and develop comprehensive pipelines. To address this, we developed the Post-Assembly Quality manager (PAQman), a tool that lowers the barrier to entry for assembly quality assessment by measuring seven reference-free features of genome quality within a single framework: Contiguity, Gene content, Completeness, Accuracy, Correctness, Coverage, and Telomerality. PAQman integrates multiple commonly used tools alongside custom scripts, requiring users to provide only a query genome assembly and its underlying long-read data, while providing a streamlined and consistent framework for quality assessment across datasets. Impact StatementPAQman is an ensemble-based tool for comprehensive, reference-free evaluation of genome assemblies derived from long-read sequencing data. The simultaneous integration of seven quality features enables users to easily assess assembly quality within a standardized, reproducible framework across diverse organisms, while lowering the barrier to entry for biologists analyzing their data.

bioinformatics↗

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↗

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↗

OrthoHMM: Improved Inference of Ortholog Groups using Hidden Markov Models

Accurate orthology inference is essential for comparative genomics and phylogenomics. However, orthology inference is challenged by sequence divergence, which is pronounced among anciently diverged organisms. We present OrthoHMM, an algorithm that infers orthologous gene groups using Hidden Markov Models parameterized from substitution matrices, which enables better detection of remote homologs. Benchmarking indicates OrthoHMM outperforms currently available methods; for example, using a curated set of Bilaterian orthogroups, OrthoHMM showed a 10.3 - 138.9% improvement in precision. Rank-based benchmarking using Bilaterian orthogroups and a novel dataset of orthogroups from organisms in three major eukaryotic kingdoms revealed OrthoHMM had the best overall performance (6.7 - 97.8% overall improvement). These findings suggest that Hidden Markov Models improve orthogroup inference.

bioinformatics↗

RCVT: a novel diagnostic to quantify compositional biases among taxa for phylogenomics

Phylogenomics aims to reconstruct the history of genes and genomes. However, noise or error during inference can stem from diverse sources, such as compositional biases. Here, we introduce RCVT (Relative Composition Variability among Taxa), a metric to quantify compositional biases among taxa. We demonstrate the utility of RCVT using example data and quantify compositional biases in 16 empirical phylogenomic datasets, revealing variation in bias among taxa within phylogenomic data matrices. Systematic removal of taxa with high RCVT scores substantially reduces compositional heterogeneity compared to randomly pruning taxa among large phylogenomic data matrices. RCVT may help researchers diagnose and potentially ameliorate phylogenomic noise associated with compositional biases.

bioinformatics↗

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↗

The Role of Metabolism in Shaping Enzyme Structures Over 400 Million Years of Evolution

The functions of cells and proteins depend on their biochemical microenvironment. To understand how biochemical constraints shaped protein structural evolution, we coupled the extensive genetic and metabolic data from the Saccharomycotina subphylum with the capability of AlphaFold2 to systematically predict protein structures from sequence. Determining how 11,269 enzyme structures catalysing 361 different metabolic reactions evolved over 400 million years alongside their molecular functions, we report that metabolism has shaped the structural evolution of enzymes at different levels: the organisms overall metabolism; the topological organisation of the metabolic network; and each enzymes molecular properties. For example, structural evolution depends on each enzymes reaction mechanism, on the variability rather than the amount of metabolic flux, and on biosynthetic cost. Evolutionary cost-optimization is stronger on highly abundant enzymes and acts differently on different structural domains, with the exception of small-molecule binding sites, which are prioritised over other structural domains and lack cost-optimisation. Finally, while enzyme surfaces are less constrained, surface residues can also be exposed to positive selection for the co-evolution of protein-protein interaction sites. Accessing AlphaFolds power to predict protein structures systematically and across species barriers, facilitating the integration of protein structures with functional genomics, we were thus able to map biological constraints which shape protein structural evolution at scale and over long timelines.

systems biology↗

The Genomes of Nematode-Trapping Fungi Provide Insights into the Origin and Diversification of Fungal Carnivorism

Nematode-trapping fungi (NTF), most of which belong to a monophyletic lineage in Ascomycota, cannibalize nematodes and other microscopic animals, raising questions regarding the types and mechanisms of genomic changes that enabled carnivorism and adaptation to the carbon-rich and nitrogen-poor environment created by the Permian-Triassic extinction event. Here, we conducted comparative genomic analyses of 21 NTF and 21 non-NTF to address these questions. Carnivorism-associated changes include expanded genes for nematode capture, infection, and consumption (e.g., adhesive proteins, CAP superfamily, eukaryotic aspartyl proteases, and serine-type peptidases). Although the link between secondary metabolite (SM) production and carnivorism remains unclear, we found that the numbers of SM gene clusters among NTF are significantly lower than those among non-NTF. Significantly expanded cellulose degradation gene families (GH5, GH7, AA9, and CBM1) and contracted genes for carbon-nitrogen hydrolases (enzymes that degrade organic nitrogen to ammonia) are likely associated with adaptation to the carbon-rich and nitrogen-poor environment. Through horizontal gene transfer events from bacteria, NTF acquired the Mur gene cluster (participating in synthesizing peptidoglycan of the bacterial cell wall) and Hyl (a virulence factor in animals). Disruption of MurE reduced NTFs ability to attract nematodes, supporting its role in carnivorism. This study provides new insights into how NTF evolved and diversified after the Permian-Triassic mass extinction event.

evolutionary biology↗

Characterization of Genome-wide Phylogenetic Conflict Uncovers Evolutionary Modes of Carnivorous Fungi

Mass extinction has often paved the way for rapid evolutionary radiation, resulting in the emergence of diverse taxa within specific lineages. While the emergence and diversification of carnivorous nematode-trapping fungi (NTF) in Ascomycota has been linked to the Permian-Triassic (PT) extinction, the processes underlying NTF radiation remain unclear. Here, we conducted phylogenomic analyses using 23 genomes spanning three NTF lineages, each employing distinct nematode traps -- mechanical traps (Drechslerella spp.), three-dimensional (3-D) adhesive traps (Arthrobotrys spp.), and two-dimensional (2-D) adhesive traps (Dactylellina spp.), and one non-NTF species as the outgroup. This analysis revealed how diverse mechanisms contributed to the tempo of NTF evolution and rapid radiation. The genome-scale species tree of NTFs suggested that Drechslerella emerged earlier than Arthrobotrys and Dactylellina. Extensive genome-wide phylogenetic discordance was observed, mainly due to incomplete lineage sorting (ILS) between lineages ([~]81.3%). Modes of non-vertical evolution (i.e., introgression and horizontal gene transfer) also contributed to phylogenetic discordance. The ILS genes that are associated with hyphal growth and trap morphogenesis (e.g., those associated with the cell membrane system and cellular polarity division) exhibited signs of positive selection.

evolutionary biology↗

Genome-wide patterns of non-coding sequence variation in the major fungal pathogen Aspergillus fumigatus

A. fumigatus is a deadly fungal pathogen, responsible for >400,000 infections/year and high mortality rates. A. fumigatus strains exhibit variation in infection-relevant traits, including in their virulence. However, most A. fumigatus protein-coding genes, including those that modulate its virulence, are shared between A. fumigatus strains and closely related non-pathogenic relatives. We hypothesized that A. fumigatus genes exhibit substantial genetic variation in the non-coding regions immediately upstream to the start codons of genes, which could reflect differences in gene regulation between strains. To begin testing this hypothesis, we identified 5,812 single-copy orthologs across the genomes of 263 A. fumigatus strains. A. fumigatus non-coding regions showed higher levels of sequence variation compared to their corresponding protein-coding regions. Specifically, we found that 1,274 non-coding regions exhibited <75% nucleotide sequence similarity (compared to 928 protein-coding regions) and 3,721 non-coding regions exhibited between 75% and 99% similarity (compared to 2,482 protein-coding regions) across strains. Only 817 non-coding regions exhibited [&ge;]99% sequence similarity compared to 2,402 protein-coding regions. By examining 2,482 genes whose protein-coding sequence identity scores ranged between 75% and 99%, we identified 478 total genes with signatures of positive selection only in their non-coding regions and 65 total genes with signatures only in their protein-coding regions. 28 of the 478 non-coding regions and 5 of the 65 protein-coding regions under selection are associated with genes known to modulate A. fumigatus virulence. Non-coding region variation between A. fumigatus strains included single nucleotide polymorphisms and insertions or deletions of at least a few nucleotides. These results show that non-coding regions of A. fumigatus genes harbor greater sequence variation than protein-coding regions, raising the hypothesis that this variation may contribute to A. fumigatus phenotypic heterogeneity.

evolutionary biology↗

A genome-scale Opisthokonta tree of life: toward phylogenomic resolution of ancient divergences

AbstractAncient divergences within Opisthokonta--a major lineage that includes organisms in the kingdoms Animalia, Fungi, and their unicellular relatives-- remain contentious, hindering investigations of the evolutionary processes that gave rise to two kingdoms and the repeated emergence of iconic phenotypes like multicellularity. Here, we use genome-scale amounts of data to reconstruct the most taxon-rich Opisthokonta tree of life to date (348 species) and place divergences in geologic time, suggesting a Mesoproterozoic origin ([~] 1.11 billion years ago). By dissecting multiple dimensions of phylogenomic error, such as the influence of taxon sampling and model complexity, we found that deep divergences within Holozoa remain unresolved and suggest Pluriformea is either sister to Ichthyosporea and Filozoa (Pluriformea-sister hypothesis) or is monophyletic to Ichthyosporea, forming the Teretosporea lineage (Teretosporea-sister hypothesis). A combination of information theory and sensitivity analyses revealed that the inferred unicellular Holozoa relationships are largely robust to common sources of analytical error, such as insufficient model complexity, and suggest that previous reports likely suffered from insufficient taxon sampling. Our study presents a robust Opisthokonta phylogenomic framework, highlights the challenges in resolving the relationships of unicellular Holozoa, and paves the way for illuminating ancient evolutionary episodes concerning the origin of two kingdoms.

evolutionary biology↗

Diverse signatures of convergent evolution in cacti-associated yeasts

Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question. Here, we leverage a comprehensive dataset of genomic and phenotypic data from 1,049 yeast species in the subphylum Saccharomycotina (Kingdom Fungi, Phylum Ascomycota) to explore signatures of convergent evolution in cactophilic yeasts, ecological specialists associated with cacti. We inferred that the ecological association of yeasts with cacti arose independently [~]17 times. Using machine-learning, we further found that cactophily can be predicted with 76% accuracy from functional genomic and phenotypic data. The most informative feature for predicting cactophily was thermotolerance, which is likely associated with duplication and altered evolutionary rates of genes impacting the cell envelope in several cactophilic lineages. We also identified horizontal gene transfer and duplication events of plant cell wall-degrading enzymes in distantly related cactophilic clades, suggesting that putatively adaptive traits evolved through disparate molecular mechanisms. Remarkably, multiple cactophilic lineages and their close relatives are emerging human opportunistic pathogens, suggesting that the cactophilic lifestyle--and perhaps more generally lifestyles favoring thermotolerance--may preadapt yeasts to cause human disease. This work underscores the potential of a multifaceted approach involving high throughput genomic and phenotypic data to shed light onto ecological adaptation and highlights how convergent evolution to wild environments could facilitate the transition to human pathogenicity.

evolutionary biology↗

Gene loss and cis-regulatory novelty shaped core histone gene evolution in the apiculate yeast Hanseniaspora uvarum

Across eukaryotic species, core histone genes display a remarkable diversity of cis-regulatory mechanisms despite their protein sequence conservation. However, the dynamics and significance of this regulatory turnover are not well understood. Here we describe the evolutionary history of core histone gene regulation across 400 million years in Saccharomycotina yeasts, revealing diverse lineage-specific solutions to core histone expression. We further characterize the emergence of a novel regulatory mode in the Hanseniaspora genus, which coincided with the loss of one copy of its paralogous core histones genes from its fast-evolving lineage. By analyzing the growth dynamics using live cell imaging of genetically modified Hanseniaspora uvarum, we observed a regulatory decoupling of core histone synthesis from DNA synthesis and propose that this may be adaptive for its rapid cell cycle progression. Overall, our findings imply that the frequent turnover of core histone cis-regulatory mechanisms likely provides distinct adaptive solutions for specific life histories.

evolutionary biology↗

A phylogenetic approach to explore the Aspergillus fumigatus conidial surface-associated proteome and its role in pathogenesis

Aspergillus fumigatus, an important pulmonary fungal pathogen causing several diseases collectively called aspergillosis, relies on asexual spores or conidia for initiating host infection. Here, we used a phylogenomic approach to compare proteins in the conidial surface of A. fumigatus, two closely related non-pathogenic species, Aspergillus fischeri and Aspergillus oerlinghausenensis, and the cryptic pathogen Aspergillus lentulus. After identifying 62 proteins uniquely expressed on the A. fumigatus conidial surface, we deleted 42 genes encoding conidial proteins. We found deletion of 33 of these genes altered susceptibility to macrophage killing, penetration and damage to epithelial cells, and cytokine production. Notably, a gene that encodes glycosylasparaginase, which modulates levels of the host pro-inflammatory cytokine IL-1{beta}, is important for infection in an immunocompetent murine model of fungal disease. These results suggest that A. fumigatus conidial surface proteins and effectors are important for evasion and modulation of the immune response at the onset of fungal infection.

microbiology↗

CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair

Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Cryptococcus neoformans, a prevalent human fungal pathogen greatly diverged from model yeasts, approximately 60% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a C. neoformans Co-Expression Network (CryptoCEN), successfully recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. With 100% predictive accuracy, we used CryptoCEN to identify 13 new DNA damage response genes, underscoring the utility of guilt-by-association for determining gene function. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes.

genetics↗