Histone deacetylase Hos2 regulates protein expression noise by potentially modulating the protein translation machinery.

Non-genetic variations derived from expression noise at transcript or protein levels can result in cell-to-cell heterogeneity within an isogenic population. Although cells have developed strategies to reduce noise in some cellular functions, this heterogeneity can also facilitate varying levels of regulation and provide evolutionary benefits in specific environments. Despite several general characteristics of cellular noise having been revealed, the detailed molecular pathways underlying noise regulation remain elusive. Here, we established a dual-fluorescent reporter system in Saccharomyces cerevisiae and performed experimental evolution to search for mutations that increase expression noise. By analyzing evolved cells using bulk segregant analysis coupled with whole-genome sequencing, we identified the histone deacetylase Hos2 as a negative noise regulator. A hos2 mutant down-regulated multiple ribosomal protein genes and exhibited partially compromised protein translation, indicating that Hos2 may regulate protein expression noise by modulating the translation machinery. Treating cells with translation inhibitors or introducing mutations into several Hos2-regulated ribosomal protein genes-RPS9A, RPS28B and RPL42A-enhanced protein expression noise. Our study provides an effective strategy for identifying noise regulators and also sheds light on how cells regulate non-genetic variation through protein translation.

A feature extraction free approach for protein interactome inference from co-elution data.

Protein complexes are key functional units in cellular processes. High-throughput techniques, such as co-fractionation coupled with mass spectrometry (CF-MS), have advanced protein complex studies by enabling global interactome inference. However, dealing with complex fractionation characteristics to define true interactions is not a simple task, since CF-MS is prone to false positives due to the co-elution of non-interacting proteins by chance. Several computational methods have been designed to analyze CF-MS data and construct probabilistic protein-protein interaction (PPI) networks. Current methods usually first infer PPIs based on handcrafted CF-MS features, and then use clustering algorithms to form potential protein complexes. While powerful, these methods suffer from the potential bias of handcrafted features and severely imbalanced data distribution. However, the handcrafted features based on domain knowledge might introduce bias, and current methods also tend to overfit due to the severely imbalanced PPI data. To address these issues, we present a balanced end-to-end learning architecture, Software for Prediction of Interactome with Feature-extraction Free Elution Data (SPIFFED), to integrate feature representation from raw CF-MS data and interactome prediction by convolutional neural network. SPIFFED outperforms the state-of-the-art methods in predicting PPIs under the conventional imbalanced training. When trained with balanced data, SPIFFED had greatly improved sensitivity for true PPIs. Moreover, the ensemble SPIFFED model provides different voting schemes to integrate predicted PPIs from multiple CF-MS data. Using the clustering software (i.e. ClusterONE), SPIFFED allows users to infer high-confidence protein complexes depending on the CF-MS experimental designs. The source code of SPIFFED is freely available at: https://github.com/bio-it-station/SPIFFED.

Short human eccDNAs are predictable from sequences.

BACKGROUND: Ubiquitous presence of short extrachromosomal circular DNAs (eccDNAs) in eukaryotic cells has perplexed generations of biologists. Their widespread origins in the genome lacking apparent specificity led some studies to conclude their formation as random or near-random. Despite this, the search for specific formation of short eccDNA continues with a recent surge of interest in biomarker development. RESULTS: To shed new light on the conflicting views on short eccDNAs' randomness, here we present DeepCircle, a bioinformatics framework incorporating convolution- and attention-based neural networks to assess their predictability. Short human eccDNAs from different datasets indeed have low similarity in genomic locations, but DeepCircle successfully learned shared DNA sequence features to make accurate cross-datasets predictions (accuracy: convolution-based models: 79.65 ± 4.7%, attention-based models: 83.31 ± 4.18%). CONCLUSIONS: The excellent performance of our models shows that the intrinsic predictability of eccDNAs is encoded in the sequences across tissue origins. Our work demonstrates how the perceived lack of specificity in genomics data can be re-assessed by deep learning models to uncover unexpected similarity.

Rapid evolutionary repair by secondary perturbation of a primary disrupted transcriptional network.

The discrete steps of transcriptional rewiring have been proposed to occur neutrally to ensure steady gene expression under stabilizing selection. A conflict-free switch of a regulon between regulators may require an immediate compensatory evolution to minimize deleterious effects. Here, we perform an evolutionary repair experiment on the Lachancea kluyveri yeast sef1Δ mutant using a suppressor development strategy. Complete loss of SEF1 forces cells to initiate a compensatory process for the pleiotropic defects arising from misexpression of TCA cycle genes. Using different selective conditions, we identify two adaptive loss-of-function mutations of IRA1 and AZF1. Subsequent analyses show that Azf1 is a weak transcriptional activator regulated by the Ras1-PKA pathway. Azf1 loss-of-function triggers extensive gene expression changes responsible for compensatory, beneficial, and trade-off phenotypes. The trade-offs can be alleviated by higher cell density. Our results not only indicate that secondary transcriptional perturbation provides rapid and adaptive mechanisms potentially stabilizing the initial stage of transcriptional rewiring but also suggest how genetic polymorphisms of pleiotropic mutations could be maintained in the population.

Incompatibility of nuclear and mitochondrial genomes causes hybrid sterility between two yeast species.

Hybrids between species are usually unviable or sterile. One possible mechanism causing reproductive isolation is incompatibility between genes from different species. These "speciation" genes are interacting components that cannot function properly when mixed with alleles from other species. To test whether such genes exist in two closely related yeast species, we constructed hybrid lines in which one or two chromosomes were derived from Saccharomyces bayanus, and the rest were from Saccharomyces cerevisiae. We found that the hybrid line with Chromosome 13 substitution was completely sterile and identified Aep2, a mitochondrial protein encoded on Chromosome 13, to cause the sporulation defect as S. bayanus AEP2 is incompatible with S. cerevisiae mitochondria. This is caused by the inability of S. bayanus Aep2 protein to regulate the translation of the S. cerevisiae OLI1 mRNA. We speculate that AEP2 and OLI1 have evolved during the adaptation of S. bayanus to nonfermentable carbon sources, thereby driving speciation.

iTARGEX analysis of yeast deletome reveals novel regulators of transcriptional buffering in S phase and protein turnover.

Integrating omics data with quantification of biological traits provides unparalleled opportunities for discovery of genetic regulators by in silico inference. However, current approaches to analyze genetic-perturbation screens are limited by their reliance on annotation libraries for prioritization of hits and subsequent targeted experimentation. Here, we present iTARGEX (identification of Trait-Associated Regulatory Genes via mixture regression using EXpectation maximization), an association framework with no requirement of a priori knowledge of gene function. After creating this tool, we used it to test associations between gene expression profiles and two biological traits in single-gene deletion budding yeast mutants, including transcription homeostasis during S phase and global protein turnover. For each trait, we discovered novel regulators without prior functional annotations. The functional effects of the novel candidates were then validated experimentally, providing solid evidence for their roles in the respective traits. Hence, we conclude that iTARGEX can reliably identify novel factors involved in given biological traits. As such, it is capable of converting genome-wide observations into causal gene function predictions. Further application of iTARGEX in other contexts is expected to facilitate the discovery of new regulators and provide observations for novel mechanistic hypotheses regarding different biological traits and phenotypes.

Plastic Rewiring of Sef1 Transcriptional Networks and the Potential of Nonfunctional Transcription Factor Binding in Facilitating Adaptive Evolution.

Prior and extensive plastic rewiring of a transcriptional network, followed by a functional switch of the conserved transcriptional regulator, can shape the evolution of a new network with diverged functions. The presence of three distinct iron regulatory systems in fungi that use orthologous transcriptional regulators suggests that these systems evolved in that manner. Orthologs of the transcriptional activator Sef1 are believed to be central to how iron regulatory systems developed in fungi, involving gene gain, plastic network rewiring, and switches in regulatory function. We show that, in the protoploid yeast Lachancea kluyveri, plastic rewiring of the L. kluyveri Sef1 (Lk-Sef1) network, together with a functional switch, enabled Lk-Sef1 to regulate TCA cycle genes, unlike Candida albicans Sef1 that mainly regulates iron-uptake genes. Moreover, we observed pervasive nonfunctional binding of Sef1 to its target genes. Enhancing Lk-Sef1 activity resuscitated the corresponding transcriptional network, providing immediate adaptive benefits in changing environments. Our study not only sheds light on the evolution of Sef1-centered transcriptional networks but also shows the adaptive potential of nonfunctional transcription factor binding for evolving phenotypic novelty and diversity.

Experimental evolution reveals a general role for the methyltransferase Hmt1 in noise buffering.

Cell-to-cell heterogeneity within an isogenic population has been observed in prokaryotic and eukaryotic cells. Such heterogeneity often manifests at the level of individual protein abundance and may have evolutionary benefits, especially for organisms in fluctuating environments. Although general features and the origins of cellular noise have been revealed, details of the molecular pathways underlying noise regulation remain elusive. Here, we used experimental evolution of Saccharomyces cerevisiae to select for mutations that increase reporter protein noise. By combining bulk segregant analysis and CRISPR/Cas9-based reconstitution, we identified the methyltransferase Hmt1 as a general regulator of noise buffering. Hmt1 methylation activity is critical for the evolved phenotype, and we also show that two of the Hmt1 methylation targets can suppress noise. Hmt1 functions as an environmental sensor to adjust noise levels in response to environmental cues. Moreover, Hmt1-mediated noise buffering is conserved in an evolutionarily distant yeast species, suggesting broad significance of noise regulation.

Heterologous Hsp90 promotes phenotypic diversity through network evolution.

Biological processes in living cells are often carried out by gene networks in which signals and reactions are integrated through network hubs. Despite their functional importance, it remains unclear to what extent network hubs are evolvable and how alterations impact long-term evolution. We investigated these issues using heat shock protein 90 (Hsp90), a central hub of proteostasis networks. When native Hsp90 in Saccharomyces cerevisiae cells was replaced by the ortholog from hypersaline-tolerant Yarrowia lipolytica that diverged from S. cerevisiae about 270 million years ago, the cells exhibited improved growth in hypersaline environments but compromised growth in others, indicating functional divergence in Hsp90 between the two yeasts. Laboratory evolution shows that evolved Y. lipolytica-HSP90-carrying S. cerevisiae cells exhibit a wider range of phenotypic variation than cells carrying native Hsp90. Identified beneficial mutations are involved in multiple pathways and are often pleiotropic. Our results show that cells adapt to a heterologous Hsp90 by modifying different subnetworks, facilitating the evolution of phenotypic diversity inaccessible to wild-type cells.

Hsp90 regulates nongenetic variation in response to environmental stress.

Nongenetic cell-to-cell variability often plays an important role for the survival of a clonal population in the face of fluctuating environments. However, the underlying mechanisms regulating such nongenetic heterogeneity remain elusive in most organisms. We report here that a clonal yeast population exhibits morphological heterogeneity when the level of Hsp90, a molecular chaperone, is reduced. The morphological heterogeneity is driven by the dosage of Cdc28 and Cla4, a key regulator of septin formation. Low Hsp90 levels reduce Cla4 protein stability and cause a subpopulation of cells to switch to a filamentous form that has been previously suggested to be beneficial under certain hostile environments. Moreover, Hsp90-dependent morphological heterogeneity can be induced by environmental stress and is conserved across diverse yeast species. Our results suggest that Hsp90 provides an evolutionarily conserved mechanism that links environmental stress to the induction of morphological diversity.

Genome plasticity in Paramecium bursaria revealed by population genomics.

BACKGROUND: Ciliates are an ancient and diverse eukaryotic group found in various environments. A unique feature of ciliates is their nuclear dimorphism, by which two types of nuclei, the diploid germline micronucleus (MIC) and polyploidy somatic macronucleus (MAC), are present in the same cytoplasm and serve different functions. During each sexual cycle, ciliates develop a new macronucleus in which newly fused genomes are extensively rearranged to generate functional minichromosomes. Interestingly, each ciliate species seems to have its way of processing genomes, providing a diversity of resources for studying genome plasticity and its regulation. Here, we sequenced and analyzed the macronuclear genome of different strains of Paramecium bursaria, a highly divergent species of the genus Paramecium which can stably establish endosymbioses with green algae. RESULTS: We assembled a high-quality macronuclear genome of P. bursaria and further refined genome annotation by comparing population genomic data. We identified several species-specific expansions in protein families and gene lineages that are potentially associated with endosymbiosis. Moreover, we observed an intensive chromosome breakage pattern that occurred during or shortly after sexual reproduction and contributed to highly variable gene dosage throughout the genome. However, patterns of copy number variation were highly correlated among genetically divergent strains, suggesting that copy number is adjusted by some regulatory mechanisms or natural selection. Further analysis showed that genes with low copy number variation among populations tended to function in basic cellular pathways, whereas highly variable genes were enriched in environmental response pathways. CONCLUSIONS: We report programmed DNA rearrangements in the P. bursaria macronuclear genome that allow cells to adjust gene copy number globally according to individual gene functions. Our results suggest that large-scale gene copy number variation may represent an ancient mechanism for cells to adapt to different environments.

Misfolding-prone proteins are reversibly sequestered to an Hsp42-associated granule upon chronological aging.

Alteration of protein localization is an important strategy for cells to regulate protein homeostasis upon environmental stresses. In the budding yeast Saccharomyces cerevisiae, many proteins relocalize and form cytosolic granules during chronological aging. However, the functions and exact components of these protein granules remain uncharacterized in most cases. In this study, we performed a genome-wide analysis of protein localization in stationary phase cells, leading to the discovery of 307 granule-forming proteins and the identification of new components in the Hsp42-stationary phase granule (Hsp42-SPG), P-bodies, Ret2 granules and actin bodies. We further characterized the Hsp42-SPG, which contains the largest number of protein components, including many molecular chaperones, metabolic enzymes and regulatory proteins. Formation of the Hsp42-SPG efficiently downregulates the activities of sequestered components, which can be differentially released from the granule based on environmental cues. We found a similar structure in the pre-whole genome duplication yeast species, Lachancea kluyveri, suggesting that the Hsp42-SPG is a common machinery allowing chronologically aged cells to contend with changing environments when available energy is limited. This article has an associated First Person interview with the first author of the paper.

Mitochondrial-nuclear co-evolution leads to hybrid incompatibility through pentatricopeptide repeat proteins.

Mitochondrial-nuclear incompatibility has a major role in reproductive isolation between species. However, the underlying mechanism and driving force of mitochondrial-nuclear incompatibility remain elusive. Here, we report a pentatricopeptide repeat-containing (PPR) protein, Ccm1, and its interacting partner, 15S rRNA, to be involved in hybrid incompatibility between two yeast species, Saccharomyces cerevisiae and Saccharomyces bayanus S. bayanus-Ccm1 has reduced binding affinity for S. cerevisiae-15S rRNA, leading to respiratory defects in hybrid cells. This incompatibility can be rescued by single mutations on several individual PPR motifs, demonstrating the highly evolvable nature of PPR proteins. When we examined other PPR proteins in the closely related Saccharomyces sensu stricto yeasts, about two-thirds of them showed detectable incompatibility. Our results suggest that fast co-evolution between flexible PPR proteins and their mitochondrial RNA substrates may be a common driving force in the development of mitochondrial-nuclear hybrid incompatibility.

Experimental Evolution Reveals Interplay between Sch9 and Polyploid Stability in Yeast.

Polyploidization has crucial impacts on the evolution of different eukaryotic lineages including fungi, plants and animals. Recent genome data suggest that, for many polyploidization events, all duplicated chromosomes are maintained and genome reorganizations occur much later during evolution. However, newly-formed polyploid genomes are intrinsically unstable and often quickly degenerate into aneuploidy or diploidy. The transition between these two states remains enigmatic. In this study, laboratory evolution experiments were conducted to investigate this phenomenon. We show that robust tetraploidy is achieved in evolved yeast cells by increasing the abundance of Sch9-a protein kinase activated by the TORC1 (Target of Rapamycin Complex 1) and other signaling pathways. Overexpressing SCH9, but not TOR1, allows newly-formed tetraploids to exhibit evolved phenotypes and knocking out SCH9 diminishes the evolved phenotypes. Furthermore, when cells were challenged with conditions causing ancestral cells to evolve aneuploidy, tetraploidy was maintained in the evolved lines. Our results reveal a determinant role for Sch9 during the early stage of polyploid evolution.

A Comprehensive Analysis of Transcript-Supported De Novo Genes in Saccharomyces sensu stricto Yeasts.

Novel genes arising from random DNA sequences (de novo genes) have been suggested to be widespread in the genomes of different organisms. However, our knowledge about the origin and evolution of de novo genes is still limited. To systematically understand the general features of de novo genes, we established a robust pipeline to analyze >20,000 transcript-supported coding sequences (CDSs) from the budding yeast Saccharomyces cerevisiae. Our analysis pipeline combined phylogeny, synteny, and sequence alignment information to identify possible orthologs across 20 Saccharomycetaceae yeasts and discovered 4,340 S. cerevisiae-specific de novo genes and 8,871 S. sensu stricto-specific de novo genes. We further combine information on CDS positions and transcript structures to show that >65% of de novo genes arose from transcript isoforms of ancient genes, especially in the upstream and internal regions of ancient genes. Fourteen identified de novo genes with high transcript levels were chosen to verify their protein expressions. Ten of them, including eight transcript isoform-associated CDSs, showed translation signals and five proteins exhibited specific cytosolic localizations. Our results suggest that de novo genes frequently arise in the S. sensu stricto complex and have the potential to be quickly integrated into ancient cellular network.

Hsp90 mediates the crosstalk between galactose metabolism and cell morphology pathways in yeast.

Galactose metabolism in the yeast Saccharomyces cerevisiae is carried out by a specialized GAL pathway consisting of structural and regulatory proteins. It is known that cells with unbalanced Gal proteins accumulate toxic metabolic intermediates and exhibit severe growth defects. Recently, we found that the molecular chaperone Hsp90 controls the abundance of multiple Gal proteins, possibly to prevent these defects. Hsp90 regulates various cellular processes including cell morphology in response to environmental cues. Yeast cells are known to resort to filamentous growth upon exposure to galactose or other environmental stresses. Our previous and current findings support the "Hsp90 titration model" of Hsp90 buffering, which links the cell morphology and galactose pathways. Our results suggest that, when a large proportion of Hsp90 molecules are used to help Gal proteins, the Hsp90 client proteins in cell morphology pathways are left unattended, leading to filamentous growth. It remains unclear whether this phenomenon serves any biological function or simply reflects a cellular constraint. Nonetheless, it provides an alternative explanation why the GAL pathway is degenerated in some yeast species.

Dynamic large-scale chromosomal rearrangements fuel rapid adaptation in yeast populations.

Large-scale genome rearrangements have been observed in cells adapting to various selective conditions during laboratory evolution experiments. However, it remains unclear whether these types of mutations can be stably maintained in populations and how they impact the evolutionary trajectories. Here we show that chromosomal rearrangements contribute to extremely high copper tolerance in a set of natural yeast strains isolated from Evolution Canyon (EC), Israel. The chromosomal rearrangements in EC strains result in segmental duplications in chromosomes 7 and 8, which increase the copy number of genes involved in copper regulation, including the crucial transcriptional activator CUP2 and the metallothionein CUP1. The copy number of CUP2 is correlated with the level of copper tolerance, indicating that increasing dosages of a single transcriptional activator by chromosomal rearrangements has a profound effect on a regulatory pathway. By gene expression analysis and functional assays, we identified three previously unknown downstream targets of CUP2: PHO84, SCM4, and CIN2, all of which contributed to copper tolerance in EC strains. Finally, we conducted an evolution experiment to examine how cells maintained these changes in a fluctuating environment. Interestingly, the rearranged chromosomes were reverted back to the wild-type configuration at a high frequency and the recovered chromosome became fixed in less selective conditions. Our results suggest that transposon-mediated chromosomal rearrangements can be highly dynamic and can serve as a reversible mechanism during early stages of adaptive evolution.

The evolutionary dynamics of tRNA-gene copy number and codon-use in E. coli.

BACKGROUND: The introduction of foreign DNA by Lateral Gene Transfer (LGT) can quickly and drastically alter genome composition. Problems can arise if the genes introduced by LGT use codons that are not suited to the host's translational machinery. Here we investigate compensatory adaptation of E. coli in response to the introduction of large volumes of codons that are rarely used by the host genome. RESULTS: We analyze genome sequences from the E. coli/Shigella complex, and find that certain tRNA genes are present in multiple copies in two pathogenic Shigella and O157:H7 subgroups of E. coli. Furthermore, we show that the codons that correspond to these multi-copy number tRNA genes are enriched in the high copy number Selfish Genetic Elements (SGE's) in Shigella and laterally introduced genes in O157:H7. We analyze the duplicate copies and find evidence for the selective retention of tRNA genes introduced by LGT in response to the changed codon content of the genome. CONCLUSION: These data support a model where the relatively rapid influx of LGT genes and SGE's introduces a large number of genes maladapted to the host's translational machinery. Under these conditions, it becomes advantageous for the host to retain tRNA genes that are required for the incorporation of amino acids at these codons. Subsequently, the increased number of copies of these specific tRNA genes adjusts the cellular tRNA pool to the demands set by global shifts in codon usage.

On the Nature and Evolutionary Impact of Phenotypic Robustness Mechanisms.

Biologists have long observed that physiological and developmental processes are insensitive, or robust, to many genetic and environmental perturbations. A complete understanding of the evolutionary causes and consequences of this robustness is lacking. Recent progress has been made in uncovering the regulatory mechanisms that underlie environmental robustness in particular. Less is known about robustness to the effects of mutations, and indeed the evolution of mutational robustness remains a controversial topic. The controversy has spread to related topics, in particular the evolutionary relevance of cryptic genetic variation. This review aims to synthesize current understanding of robustness mechanisms and to cut through the controversy by shedding light on what is and is not known about mutational robustness. Some studies have confused mutational robustness with non-additive interactions between mutations (epistasis). We conclude that a profitable way forward is to focus investigations (and rhetoric) less on mutational robustness and more on epistasis.

A population study of killer viruses reveals different evolutionary histories of two closely related Saccharomyces sensu stricto yeasts.

Microbes have evolved ways of interference competition to gain advantage over their ecological competitors. The use of secreted killer toxins by yeast cells through acquiring double-stranded RNA viruses is one such prominent example. Although the killer behaviour has been well studied in laboratory yeast strains, our knowledge regarding how killer viruses are spread and maintained in nature and how yeast cells co-evolve with viruses remains limited. We investigated these issues using a panel of 81 yeast populations belonging to three Saccharomyces sensu stricto species isolated from diverse ecological niches and geographic locations. We found that killer strains are rare among all three species. In contrast, killer toxin resistance is widespread in Saccharomyces paradoxus populations, but not in Saccharomyces cerevisiae or Saccharomyces eubayanus populations. Genetic analyses revealed that toxin resistance in S. paradoxus is often caused by dominant alleles that have independently evolved in different populations. Molecular typing identified one M28 and two types of M1 killer viruses in those killer strains. We further showed that killer viruses of the same type could lead to distinct killer phenotypes under different host backgrounds, suggesting co-evolution between the viruses and hosts in different populations. Taken together, our data suggest that killer viruses vary in their evolutionary histories even within closely related yeast species.