The metabolic domestication syndrome of budding yeast.

Cellular metabolism evolves through changes in the structure and quantitative states of metabolic networks. Here, we explore the evolutionary dynamics of metabolic states by focusing on the collection of metabolite levels, the metabolome, which captures key aspects of cellular physiology. Using a phylogenetic framework, we profiled metabolites in 27 populations of nine budding yeast species, providing a graduated view of metabolic variation across multiple evolutionary time scales. Metabolite levels evolve more rapidly and independently of changes in the metabolic network's structure, providing complementary information to enzyme repertoire. Although metabolome variation accumulates mainly gradually over time, it is profoundly affected by domestication. We found pervasive signatures of convergent evolution in the metabolomes of independently domesticated clades of Saccharomyces cerevisiae. Such recurring metabolite differences between wild and domesticated populations affect a substantial part of the metabolome, including rewiring of the TCA cycle and several amino acids that influence aroma production, likely reflecting adaptation to human niches. Overall, our work reveals previously unrecognized diversity in central metabolism and the pervasive influence of human-driven selection on metabolite levels in yeasts.

A systematic quantitative approach comprehensively defines domain-specific functional pathways linked to Schizosaccharomyces pombe heterochromatin regulation.

Heterochromatin plays a critical role in regulating gene expression and maintaining genome integrity. While structural and enzymatic components have been linked to heterochromatin establishment, a comprehensive view of the underlying pathways at diverse heterochromatin domains remains elusive. Here, we developed a systematic approach to identify factors involved in heterochromatin silencing at pericentromeres, subtelomeres, and the silent mating type locus in Schizosaccharomyces pombe. Using quantitative measures, iterative genetic screening, and domain-specific heterochromatin reporters, we identified 369 mutants with different degrees of reduced or enhanced silencing. As expected, mutations in the core heterochromatin machinery globally decreased silencing. However, most other mutants exhibited distinct qualitative and quantitative profiles that indicate domain-specific functions. For example, decreased mating type silencing was linked to mutations in heterochromatin maintenance genes, while compromised subtelomere silencing was associated with metabolic pathways. Furthermore, similar phenotypic profiles revealed shared functions for subunits within complexes. We also discovered that the uncharacterized protein Dhm2 plays a crucial role in maintaining constitutive and facultative heterochromatin, while its absence caused phenotypes akin to DNA replication-deficient mutants. Collectively, our systematic approach unveiled a landscape of domain-specific heterochromatin regulators controlling distinct states and identified Dhm2 as a previously unknown factor linked to heterochromatin inheritance and replication fidelity.

Principles of metabolome conservation in animals.

Metabolite levels shape cellular physiology and disease susceptibility, yet the general principles governing metabolome evolution are largely unknown. Here, we introduce a measure of conservation of individual metabolite levels among related species. By analyzing multispecies tissue metabolome datasets in phylogenetically diverse mammals and fruit flies, we show that conservation varies extensively across metabolites. Three major functional properties, metabolite abundance, essentiality, and association with human diseases predict conservation, highlighting a striking parallel between the evolutionary forces driving metabolome and protein sequence conservation. Metabolic network simulations recapitulated these general patterns and revealed that abundant metabolites are highly conserved due to their strong coupling to key metabolic fluxes in the network. Finally, we show that biomarkers of metabolic diseases can be distinguished from other metabolites simply based on evolutionary conservation, without requiring any prior clinical knowledge. Overall, this study uncovers simple rules that govern metabolic evolution in animals and implies that most tissue metabolome differences between species are permitted, rather than favored by natural selection. More broadly, our work paves the way toward using evolutionary information to identify biomarkers, as well as to detect pathogenic metabolome alterations in individual patients.

Phase-separated ribosome-nascent chain complexes in genotoxic stress response.

Assemblysomes are EDTA- and RNase-resistant ribonucleoprotein (RNP) complexes of paused ribosomes with protruding nascent polypeptide chains. They have been described in yeast and human cells for the proteasome subunit Rpt1, and the disordered amino-terminal part of the nascent chain was found to be indispensable for the accumulation of the Rpt1-RNP into assemblysomes. Motivated by this, to find other assemblysome-associated RNPs we used bioinformatics to rank subunits of Saccharomyces cerevisiae protein complexes according to their amino-terminal disorder propensity. The results revealed that gene products involved in DNA repair are enriched among the top candidates. The Sgs1 DNA helicase was chosen for experimental validation. We found that indeed nascent chains of Sgs1 form EDTA-resistant RNP condensates, assemblysomes by definition. Moreover, upon exposure to UV, SGS1 mRNA shifted from assemblysomes to polysomes, suggesting that external stimuli are regulators of assemblysome dynamics. We extended our studies to human cell lines. The BLM helicase, ortholog of yeast Sgs1, was identified upon sequencing assemblysome-associated RNAs from the MCF7 human breast cancer cell line, and mRNAs encoding DNA repair proteins were overall enriched. Using the radiation-resistant A549 cell line, we observed by transmission electron microscopy that 1,6-hexanediol, an agent known to disrupt phase-separated condensates, depletes ring ribosome structures compatible with assemblysomes from the cytoplasm of cells and makes the cells more sensitive to X-ray treatment. Taken together, these findings suggest that assemblysomes may be a component of the DNA damage response from yeast to human.

Characterization of antibiotic resistomes by reprogrammed bacteriophage-enabled functional metagenomics in clinical strains.

Functional metagenomics is a powerful experimental tool to identify antibiotic resistance genes (ARGs) in the environment, but the range of suitable host bacterial species is limited. This limitation affects both the scope of the identified ARGs and the interpretation of their clinical relevance. Here we present a functional metagenomics pipeline called Reprogrammed Bacteriophage Particle Assisted Multi-species Functional Metagenomics (DEEPMINE). This approach combines and improves the use of T7 bacteriophage with exchanged tail fibres and targeted mutagenesis to expand phage host-specificity and efficiency for functional metagenomics. These modified phage particles were used to introduce large metagenomic plasmid libraries into clinically relevant bacterial pathogens. By screening for ARGs in soil and gut microbiomes and clinical genomes against 13 antibiotics, we demonstrate that this approach substantially expands the list of identified ARGs. Many ARGs have species-specific effects on resistance; they provide a high level of resistance in one bacterial species but yield very limited resistance in a related species. Finally, we identified mobile ARGs against antibiotics that are currently under clinical development or have recently been approved. Overall, DEEPMINE expands the functional metagenomics toolbox for studying microbial communities.

Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan.

Metabolism is deeply intertwined with aging. Effects of metabolic interventions on aging have been explained with intracellular metabolism, growth control, and signaling. Studying chronological aging in yeast, we reveal a so far overlooked metabolic property that influences aging via the exchange of metabolites. We observed that metabolites exported by young cells are re-imported by chronologically aging cells, resulting in cross-generational metabolic interactions. Then, we used self-establishing metabolically cooperating communities (SeMeCo) as a tool to increase metabolite exchange and observed significant lifespan extensions. The longevity of the SeMeCo was attributable to metabolic reconfigurations in methionine consumer cells. These obtained a more glycolytic metabolism and increased the export of protective metabolites that in turn extended the lifespan of cells that supplied them with methionine. Our results establish metabolite exchange interactions as a determinant of cellular aging and show that metabolically cooperating cells can shape the metabolic environment to extend their lifespan.

Plasticity and Stereotypic Rewiring of the Transcriptome Upon Bacterial Evolution of Antibiotic Resistance.

Bacterial evolution of antibiotic resistance frequently has deleterious side effects on microbial growth, virulence, and susceptibility to other antimicrobial agents. However, it is unclear how these trade-offs could be utilized for manipulating antibiotic resistance in the clinic, not least because the underlying molecular mechanisms are poorly understood. Using laboratory evolution, we demonstrate that clinically relevant resistance mutations in Escherichia coli constitutively rewire a large fraction of the transcriptome in a repeatable and stereotypic manner. Strikingly, lineages adapted to functionally distinct antibiotics and having no resistance mutations in common show a wide range of parallel gene expression changes that alter oxidative stress response, iron homeostasis, and the composition of the bacterial outer membrane and cell surface. These common physiological alterations are associated with changes in cell morphology and enhanced sensitivity to antimicrobial peptides. Finally, the constitutive transcriptomic changes induced by resistance mutations are largely distinct from those induced by antibiotic stresses in the wild type. This indicates a limited role for genetic assimilation of the induced antibiotic stress response during resistance evolution. Our work suggests that diverse resistance mutations converge on similar global transcriptomic states that shape genetic susceptibility to antimicrobial compounds.

TFLink: an integrated gateway to access transcription factor-target gene interactions for multiple species.

Analysis of transcriptional regulatory interactions and their comparisons across multiple species are crucial for progress in various fields in biology, from functional genomics to the evolution of signal transduction pathways. However, despite the rapidly growing body of data on regulatory interactions in several eukaryotes, no databases exist to provide curated high-quality information on transcription factor-target gene interactions for multiple species. Here, we address this gap by introducing the TFLink gateway, which uniquely provides experimentally explored and highly accurate information on transcription factor-target gene interactions (∼12 million), nucleotide sequences and genomic locations of transcription factor binding sites (∼9 million) for human and six model organisms: mouse, rat, zebrafish, fruit fly, worm and yeast by integrating 10 resources. TFLink provides user-friendly access to data on transcription factor-target gene interactions, interactive network visualizations and transcription factor binding sites, with cross-links to several other databases. Besides containing accurate information on transcription factors, with a clear labelling of the type/volume of the experiments (small-scale or high-throughput), the source database and the original publications, TFLink also provides a wealth of standardized regulatory data available for download in multiple formats. The database offers easy access to high-quality data for wet-lab researchers, supplies data for gene set enrichment analyses and facilitates systems biology and comparative gene regulation studies. Database URL https://tflink.net/.

A single early introduction governed viral diversity in the second wave of SARS-CoV-2 epidemic in Hungary.

Retrospective evaluation of past waves of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic is key for designing optimal interventions against future waves and novel pandemics. Here, we report on analysing genome sequences of SARS-CoV-2 from the first two waves of the epidemic in 2020 in Hungary, mirroring a suppression and a mitigation strategy, respectively. Our analysis reveals that the two waves markedly differed in viral diversity and transmission patterns. Specifically, unlike in several European areas or in the USA, we have found no evidence for early introduction and cryptic transmission of the virus in the first wave of the pandemic in Hungary. Despite the introduction of multiple viral lineages, extensive community spread was prevented by a timely national lockdown in March 2020. In sharp contrast, the majority of the cases in the much larger second wave can be linked to a single transmission lineage of the pan-European B.1.160 variant. This lineage was introduced unexpectedly early, followed by a 2-month-long cryptic transmission before a soar of detected cases in September 2020. Epidemic analysis has revealed that the dominance of this lineage in the second wave was not associated with an intrinsic transmission advantage. This finding is further supported by the rapid replacement of B.1.160 by the alpha variant (B.1.1.7) that launched the third wave of the epidemic in February 2021. Overall, these results illustrate how the founder effect in combination with the cryptic transmission, instead of repeated international introductions or higher transmissibility, can govern viral diversity.

Proteome-wide landscape of solubility limits in a bacterial cell.

Proteins are prone to aggregate when expressed above their solubility limits. Aggregation may occur rapidly, potentially as early as proteins emerge from the ribosome, or slowly, following synthesis. However, in vivo data on aggregation rates are scarce. Here, we classified the Escherichia coli proteome into rapidly and slowly aggregating proteins using an in vivo image-based screen coupled with machine learning. We find that the majority (70%) of cytosolic proteins that become insoluble upon overexpression have relatively low rates of aggregation and are unlikely to aggregate co-translationally. Remarkably, such proteins exhibit higher folding rates compared to rapidly aggregating proteins, potentially implying that they aggregate after reaching their folded states. Furthermore, we find that a substantial fraction (~ 35%) of the proteome remain soluble at concentrations much higher than those found naturally, indicating a large margin of safety to tolerate gene expression changes. We show that high disorder content and low surface stickiness are major determinants of high solubility and are favored in abundant bacterial proteins. Overall, our study provides a global view of aggregation rates and hence solubility limits of proteins in a bacterial cell.

Underground metabolism as a rich reservoir for pathway engineering.

MOTIVATION: Bioproduction of value-added compounds is frequently achieved by utilizing enzymes from other species. However, expression of such heterologous enzymes can be detrimental due to unexpected interactions within the host cell. Recently, an alternative strategy emerged, which relies on recruiting side activities of host enzymes to establish new biosynthetic pathways. Although such low-level 'underground' enzyme activities are prevalent, it remains poorly explored whether they may serve as an important reservoir for pathway engineering. RESULTS: Here, we use genome-scale modeling to estimate the theoretical potential of underground reactions for engineering novel biosynthetic pathways in Escherichia coli. We found that biochemical reactions contributed by underground enzyme activities often enhance the in silico production of compounds with industrial importance, including several cases where underground activities are indispensable for production. Most of these new capabilities can be achieved by the addition of one or two underground reactions to the native network, suggesting that only a few side activities need to be enhanced during implementation. Remarkably, we find that the contribution of underground reactions to the production of value-added compounds is comparable to that of heterologous reactions, underscoring their biotechnological potential. Taken together, our genome-wide study demonstrates that exploiting underground enzyme activities could be a promising addition to the toolbox of industrial strain development. AVAILABILITY AND IMPLEMENTATION: The data and scripts underlying this article are available on GitHub at https://github.com/pappb/Kovacs-et-al-Underground-metabolism. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gene loss and compensatory evolution promotes the emergence of morphological novelties in budding yeast.

Deleterious mutations are generally considered to be irrelevant for morphological evolution. However, they could be compensated by conditionally beneficial mutations, thereby providing access to new adaptive paths. Here we use high-dimensional phenotyping of laboratory-evolved budding yeast lineages to demonstrate that new cellular morphologies emerge exceptionally rapidly as a by-product of gene loss and subsequent compensatory evolution. Unexpectedly, the capacities for invasive growth, multicellular aggregation and biofilm formation also spontaneously evolve in response to gene loss. These multicellular phenotypes can be achieved by diverse mutational routes and without reactivating the canonical regulatory pathways. These ecologically and clinically relevant traits originate as pleiotropic side effects of compensatory evolution and have no obvious utility in the laboratory environment. The extent of morphological diversity in the evolved lineages is comparable to that of natural yeast isolates with diverse genetic backgrounds and lifestyles. Finally, we show that both the initial gene loss and subsequent compensatory mutations contribute to new morphologies, with their synergistic effects underlying specific morphological changes. We conclude that compensatory evolution is a previously unrecognized source of morphological diversity and phenotypic novelties.

Negative trade-off between neoantigen repertoire breadth and the specificity of HLA-I molecules shapes antitumor immunity.

Human leukocyte antigen class I (HLA-I) genes shape our immune response against pathogens and cancer. Certain HLA-I variants can bind a wider range of peptides than others, a feature that could be favorable against a range of viral diseases. However, the implications of this phenomenon on cancer immune response are unknown. Here we quantified peptide repertoire breadth (or promiscuity) of a representative set of HLA-I alleles and found that patients with cancer who were carrying HLA-I alleles with high peptide-binding promiscuity have significantly worse prognosis after immune checkpoint inhibition. This can be explained by a reduced capacity of the immune system to discriminate tumor neopeptides from self-peptides when patients carry highly promiscuous HLA-I variants, shifting the regulation of tumor-infiltrating T cells from activation to tolerance. In summary, HLA-I peptide-binding specificity shapes neopeptide immunogenicity and the self-immunopeptidome repertoire in an antagonistic manner, and could underlie a negative trade-off between antitumor immunity and genetic susceptibility to viral infections.

Suboptimal Global Transcriptional Response Increases the Harmful Effects of Loss-of-Function Mutations.

The fitness impact of loss-of-function mutations is generally assumed to reflect the loss of specific molecular functions associated with the perturbed gene. Here, we propose that rewiring of the transcriptome upon deleterious gene inactivation is frequently nonspecific and mimics stereotypic responses to external environmental change. Consequently, transcriptional response to gene deletion could be suboptimal and incur an extra fitness cost. Analysis of the transcriptomes of ∼1,500 single-gene deletion Saccharomyces cerevisiae strains supported this scenario. First, most transcriptomic changes are not specific to the deleted gene but are rather triggered by perturbations in functionally diverse genes. Second, gene deletions that alter the expression of dosage-sensitive genes are especially harmful. Third, by elevating the expression level of downregulated genes, we could experimentally mitigate the fitness defect of gene deletions. Our work shows that rewiring of genomic expression upon gene inactivation shapes the harmful effects of mutations.

Exploring the fitness benefits of genome reduction in Escherichia coli by a selection-driven approach.

Artificial simplification of bacterial genomes is thought to have the potential to yield cells with reduced complexity, enhanced genetic stability, and improved cellular economy. Of these goals, economical gains, supposedly due to the elimination of superfluous genetic material, and manifested in elevated growth parameters in selected niches, have not yet been convincingly achieved. This failure might stem from limitations of the targeted genome reduction approach that assumes full knowledge of gene functions and interactions, and allows only a limited number of reduction trajectories to interrogate. To explore the potential fitness benefits of genome reduction, we generated successive random deletions in E. coli by a novel, selection-driven, iterative streamlining process. The approach allows the exploration of multiple streamlining trajectories, and growth periods inherent in the procedure ensure selection of the fittest variants of the population. By generating single- and multiple-deletion strains and reconstructing the deletions in the parental genetic background, we showed that favourable deletions can be obtained and accumulated by the procedure. The most reduced multiple-deletion strain, obtained in five deletion cycles (2.5% genome reduction), outcompeted the wild-type, and showed elevated biomass yield. The spectrum of advantageous deletions, however, affecting only a few genomic regions, appears to be limited.

Unmatched Level of Molecular Convergence among Deeply Divergent Complex Multicellular Fungi.

Convergent evolution is pervasive in nature, but it is poorly understood how various constraints and natural selection limit the diversity of evolvable phenotypes. Here, we analyze the transcriptome across fruiting body development to understand the independent evolution of complex multicellularity in the two largest clades of fungi-the Agarico- and Pezizomycotina. Despite >650 My of divergence between these clades, we find that very similar sets of genes have convergently been co-opted for complex multicellularity, followed by expansions of their gene families by duplications. Over 82% of shared multicellularity-related gene families were expanding in both clades, indicating a high prevalence of convergence also at the gene family level. This convergence is coupled with a rich inferred repertoire of multicellularity-related genes in the most recent common ancestor of the Agarico- and Pezizomycotina, consistent with the hypothesis that the coding capacity of ancestral fungal genomes might have promoted the repeated evolution of complex multicellularity. We interpret this repertoire as an indication of evolutionary predisposition of fungal ancestors for evolving complex multicellular fruiting bodies. Our work suggests that evolutionary convergence may happen not only when organisms are closely related or are under similar selection pressures, but also when ancestral genomic repertoires render certain evolutionary trajectories more likely than others, even across large phylogenetic distances.

Chemical-genetic profiling reveals limited cross-resistance between antimicrobial peptides with different modes of action.

Antimicrobial peptides (AMPs) are key effectors of the innate immune system and promising therapeutic agents. Yet, knowledge on how to design AMPs with minimal cross-resistance to human host-defense peptides remains limited. Here, we systematically assess the resistance determinants of Escherichia coli against 15 different AMPs using chemical-genetics and compare to the cross-resistance spectra of laboratory-evolved AMP-resistant strains. Although generalizations about AMP resistance are common in the literature, we find that AMPs with different physicochemical properties and cellular targets vary considerably in their resistance determinants. As a consequence, cross-resistance is prevalent only between AMPs with similar modes of action. Finally, our screen reveals several genes that shape susceptibility to membrane- and intracellular-targeting AMPs in an antagonistic manner. We anticipate that chemical-genetic approaches could inform future efforts to minimize cross-resistance between therapeutic and human host AMPs.

Integrated evolutionary analysis reveals antimicrobial peptides with limited resistance.

Antimicrobial peptides (AMPs) are promising antimicrobials, however, the potential of bacterial resistance is a major concern. Here we systematically study the evolution of resistance to 14 chemically diverse AMPs and 12 antibiotics in Escherichia coli. Our work indicates that evolution of resistance against certain AMPs, such as tachyplesin II and cecropin P1, is limited. Resistance level provided by point mutations and gene amplification is very low and antibiotic-resistant bacteria display no cross-resistance to these AMPs. Moreover, genomic fragments derived from a wide range of soil bacteria confer no detectable resistance against these AMPs when introduced into native host bacteria on plasmids. We have found that simple physicochemical features dictate bacterial propensity to evolve resistance against AMPs. Our work could serve as a promising source for the development of new AMP-based therapeutics less prone to resistance, a feature necessary to avoid any possible interference with our innate immune system.