Mechanisms of haploinsufficiency revealed by genome-wide profiling in yeast

The uS10c-BPG2 module mediates ribosomal RNA processing in chloroplast nucleoids

In plant chloroplasts, certain ribosomal proteins (RPs) and ribosome biogenesis factors (RBFs) are present in nucleoids, implying an association between nucleoids and ribosome biogenesis. In Arabidopsis, the YqeH-type GTPase Brassinazole-Insensitive Pale Green2 (BPG2) is a chloroplast nucleoid-associated RBF. Here, we investigated the relationship between nucleoids and BPG2-involved ribosome biogenesis steps by exploring how BPG2 targets ribosomes. Our findings demonstrate that BPG2 interacts with an essential plastid RP, uS10c, in chloroplast nucleoids in a ribosomal RNA (rRNA)-independent manner. We also discovered that uS10c is a haploinsufficient gene, as the heterozygous deletion of this gene leads to variegated shoots and chlorophyll aggregation. uS10c is integrated into 30S ribosomal particles when rRNA is relatively exposed and also exists in polysome fractions. In contrast, BPG2 exclusively associates with 30S ribosomal particles. Notably, the interaction between BPG2 and 30S particles is influenced by the absence of uS10c, resulting in BPG2 diffusing in chloroplasts instead of targeting nucleoids. Further, our results reveal that the loss of BPG2 function and the heterozygous deletion of uS10c impair the processing of 16S and 23S-4.5S rRNAs, reduce plastid protein accumulation, and trigger the plastid signaling response. Together, these findings indicate that the uS10c-BPG2 module mediates ribosome biogenesis in chloroplast nucleoids.

High-throughput assays to assess variant effects on disease

Interpreting the wealth of rare genetic variants discovered in population-scale sequencing efforts and deciphering their associations with human health and disease present a critical challenge due to the lack of sufficient clinical case reports. One promising avenue to overcome this problem is deep mutational scanning (DMS), a method of introducing and evaluating large-scale genetic variants in model cell lines. DMS allows unbiased investigation of variants, including those that are not found in clinical reports, thus improving rare disease diagnostics. Currently, the main obstacle limiting the full potential of DMS is the availability of functional assays that are specific to disease mechanisms. Thus, we explore high-throughput functional methodologies suitable to examine broad disease mechanisms. We specifically focus on methods that do not require robotics or automation but instead use well-designed molecular tools to transform biological mechanisms into easily detectable signals, such as cell survival rate, fluorescence or drug resistance. Here, we aim to bridge the gap between disease-relevant assays and their integration into the DMS framework.

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.

Translation variation across genetic backgrounds reveals a post-transcriptional buffering signature in yeast

Gene expression is known to vary among individuals, and this variability can impact the phenotypic diversity observed in natural populations. While the transcriptome and proteome have been extensively studied, little is known about the translation process itself. Here, we therefore performed ribosome and transcriptomic profiling on a genetically and ecologically diverse set of natural isolates of the Saccharomyces cerevisiae yeast. Interestingly, we found that the Euclidean distances between each profile and the expression fold changes in each pairwise isolate comparison were higher at the transcriptomic level. This observation clearly indicates that the transcriptional variation observed in the different isolates is buffered through a phenomenon known as post-transcriptional buffering at the translation level. Furthermore, this phenomenon seemed to have a specific signature by preferentially affecting essential genes as well as genes involved in complex-forming proteins, and low transcribed genes. We also explored the translation of the S. cerevisiae pangenome and found that the accessory genes related to introgression events displayed similar transcription and translation levels as the core genome. By contrast, genes acquired through horizontal gene transfer events tended to be less efficiently translated. Together, our results highlight both the extent and signature of the post-transcriptional buffering.

Doublesex is essential for masculinization but not feminization in Lygus hesperus

In most holometabolous insects, sex differentiation occurs via a hierarchical cascade of transcription factors, with doublesex (dsx) regulating genes that control sex-specific traits. Although less is known in hemimetabolous insects, early evidence suggests that substantial differences exist from more evolutionarily advanced insects. Here, we identified and characterized dsx in Lygus hesperus (western tarnished plant bug), a hemipteran pest of many agricultural crops in western North America. The full-length transcript for L. hesperus dsx (Lhdsx) and several variants encode proteins with conserved DNA binding and oligomerization domains. Transcript profiling revealed that Lhdsx is ubiquitously expressed, likely undergoes alternative pre-mRNA splicing, and, unlike several model insects, is sex-biased rather than sex-specific. Embryonic RNA interference (RNAi) of Lhdsx only impacted sex development in adult males, which lacked both internal reproductive organs and external genitalia. No discernible impacts on adult female development or reproductivity were observed. RNAi knockdown of Lhdsx in nymphs likewise only affected adult males, which lacked the characteristic dimorphic coloration but had dramatically elevated vitellogenin transcripts. Gene knockout of Lhdsx by CRISPR/Cas9 editing yielded only females in G0 and strongly biased heterozygous G1 offspring to females with the few surviving males showing severely impaired genital development. These results indicate that L. hesperus male development requires Lhdsx, whereas female development proceeds via a basal pathway that functions independently of dsx. A fundamental understanding of sex differentiation in L. hesperus could be important for future gene-based management strategies of this important agricultural pest.

Integrating network pharmacology: The next-generation approach in ocular drug discovery

With the spread of the "omics" sciences, the approaches of systems biology can be considered as new paradigms of pharmacological research for discovery of novel targets and/or treatments for complex multifactorial diseases. Data from omics sciences can be used for the design of biologic networks, that in turn can be quantitatively analyzed to identify new pharmacological targets. In this review, we will introduce the concept of network pharmacology, particularly the application of this innovative approach in the field of ocular pharmacology, with a focus on retinal diseases such as diabetic retinopathy (DR), age-related macular degeneration (AMD) and glaucoma.

Integration of Yeast Episomal/Integrative Plasmid Causes Genotypic and Phenotypic Diversity and Improved Sesquiterpene Production in Metabolically Engineered Saccharomyces cerevisiae

The variability in phenotypic outcomes among biological replicates in engineered microbial factories presents a captivating mystery. Establishing the association between phenotypic variability and genetic drivers is important to solve this intricate puzzle. We applied a previously developed auxin-inducible depletion of hexokinase 2 as a metabolic engineering strategy for improved nerolidol production in Saccharomyces cerevisiae, and biological replicates exhibit a dichotomy in nerolidol production of either 3.5 or 2.5 g L-1 nerolidol. Harnessing Oxford Nanopore's long-read genomic sequencing, we reveal a potential genetic cause─the chromosome integration of a 2μ sequence-based yeast episomal plasmid, encoding the expression cassettes for nerolidol synthetic enzymes. This finding was reinforced through chromosome integration revalidation, engineering nerolidol and valencene production strains, and generating a diverse pool of yeast clones, each uniquely fingerprinted by gene copy numbers, plasmid integrations, other genomic rearrangements, protein expression levels, growth rate, and target product productivities. Τhe best clone in two strains produced 3.5 g L-1 nerolidol and ∼0.96 g L-1 valencene. Comparable genotypic and phenotypic variations were also generated through the integration of a yeast integrative plasmid lacking 2μ sequences. Our work shows that multiple factors, including plasmid integration status, subchromosomal location, gene copy number, sesquiterpene synthase expression level, and genome rearrangement, together play a complicated determinant role on the productivities of sesquiterpene product. Integration of yeast episomal/integrative plasmids may be used as a versatile method for increasing the diversity and optimizing the efficiency of yeast cell factories, thereby uncovering metabolic control mechanisms.

Application of unimodal probability distribution models for morphological phenotyping of budding yeast

Morphological phenotyping of the budding yeast Saccharomyces cerevisiae has helped to greatly clarify the functions of genes and increase our understanding of cellular functional networks. It is necessary to understand cell morphology and perform quantitative morphological analysis (QMA) but assigning precise values to morphological phenotypes has been challenging. We recently developed the Unimodal Morphological Data image analysis pipeline for this purpose. All true values can be estimated theoretically by applying an appropriate probability distribution if the distribution of experimental values follows a unimodal pattern. This reliable pipeline allows several downstream analyses, including detection of subtle morphological differences, selection of mutant strains with similar morphology, clustering based on morphology, and study of morphological diversity. In addition to basic research, morphological analyses of yeast cells can also be used in applied research to monitor breeding and fermentation processes and control the fermentation activity of yeast cells.

Possibilities and limitations of antisense oligonucleotide therapies for the treatment of monogenic disorders

Antisense oligonucleotides (ASOs) are incredibly versatile molecules that can be designed to specifically target and modify RNA transcripts to slow down or halt rare genetic disease progression. They offer the potential to target groups of patients or can be tailored for individual cases. Nonetheless, not all genetic variants and disorders are amenable to ASO-based treatments, and hence, it is important to consider several factors before embarking on the drug development journey. Here, we discuss which genetic disorders have the potential to benefit from a specific type of ASO approach, based on the pathophysiology of the disease and pathogenic variant type, as well as those disorders that might not be suitable for ASO therapies. We further explore additional aspects, such as the target tissues, intervention time points, and potential clinical benefits, which need to be considered before developing a compound. Overall, we provide an overview of the current potentials and limitations of ASO-based therapeutics for the treatment of monogenic disorders.

From beer to breadboards: yeast as a force for biological innovation

The history of yeast Saccharomyces cerevisiae, aka brewer's or baker's yeast, is intertwined with our own. Initially domesticated 8,000 years ago to provide sustenance to our ancestors, for the past 150 years, yeast has served as a model research subject and a platform for technology. In this review, we highlight many ways in which yeast has served to catalyze the fields of functional genomics, genome editing, gene-environment interaction investigation, proteomics, and bioinformatics-emphasizing how yeast has served as a catalyst for innovation. Several possible futures for this model organism in synthetic biology, drug personalization, and multi-omics research are also presented.

Meta-analysis of dispensable essential genes and their interactions with bypass suppressors

Genes have been historically classified as essential or non-essential based on their requirement for viability. However, genomic mutations can sometimes bypass the requirement for an essential gene, challenging the binary classification of gene essentiality. Such dispensable essential genes represent a valuable model for understanding the incomplete penetrance of loss-of-function mutations often observed in natural populations. Here, we compiled data from multiple studies on essential gene dispensability in Saccharomyces cerevisiae to comprehensively characterize these genes. In analyses spanning different evolutionary timescales, dispensable essential genes exhibited distinct phylogenetic properties compared with other essential and non-essential genes. Integration of interactions with suppressor genes that can bypass the gene essentiality revealed the high functional modularity of the bypass suppression network. Furthermore, dispensable essential and bypass suppressor gene pairs reflected simultaneous changes in the mutational landscape of S. cerevisiae strains. Importantly, species in which dispensable essential genes were non-essential tended to carry bypass suppressor mutations in their genomes. Overall, our study offers a comprehensive view of dispensable essential genes and illustrates how their interactions with bypass suppressors reflect evolutionary outcomes.

Evolution of haploid and diploid populations reveals common, strong, and variable pleiotropic effects in non-home environments

Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in 'non-home' environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes.

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organism S. cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with bona fide tyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

The genotype-phenotype relationship and evolutionary genetics in the light of the Metabolic Control Analysis

Metabolic control analysis has long been used as a systemic model of the genotype-phenotype (GP) relationship. By considering kinetic parameters and enzyme concentrations as reflecting the genotype level and metabolic fluxes or pools as phenotypes related to fitness, MCA has given a biological basis to the relationship between these two levels. The non-linear and concave relationship between enzymes and fluxes can account for common genetic effects that reductionist approaches have been powerless to explain, such as the dominance of active alleles over less active alleles, the various types of epistasis and heterosis, and reveals the structural links between these genetic effects. The summation property of the flux control coefficients accounts for the L-shaped distribution of Quantitative Trait Locus (QTL) effects, irrespective of other possible causes. Metabolic models of response to selection results in evolutionary scenarios that are markedly different from those derived from the classical infinitesimal model of quantitative genetics. In particular, evolution towards selective neutrality appears to be a consequence of the diminishing return of the flux-enzyme relationship. In this paper, we survey the historical and recent achievements of MCA in genetics, quantitative genetics and evolution, focusing on epistasis and the evolution of flux in relation to enzyme concentrations.

Implications of differential size-scaling of cell-cycle regulators on cell size homeostasis

Accurate timing of division and size homeostasis is crucial for cells. A potential mechanism for cells to decide the timing of division is the differential scaling of regulatory protein copy numbers with cell size. However, it remains unclear whether such a mechanism can lead to robust growth and division, and how the scaling behaviors of regulatory proteins influence the cell size distribution. Here we study a mathematical model combining gene expression and cell growth, in which the cell-cycle activators scale superlinearly with cell size while the inhibitors scale sublinearly. The cell divides once the ratio of their concentrations reaches a threshold value. We find that the cell can robustly grow and divide within a finite range of the threshold value with the cell size proportional to the ploidy. In a stochastic version of the model, the cell size at division is uncorrelated with that at birth. Also, the more differential the cell-size scaling of the cell-cycle regulators is, the narrower the cell-size distribution is. Intriguingly, our model with multiple regulators rationalizes the observation that after the deletion of a single regulator, the coefficient of variation of cell size remains roughly the same though the average cell size changes significantly. Our work reveals that the differential scaling of cell-cycle regulators provides a robust mechanism of cell size control.

An Update on MYBPC3 Gene Mutation in Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is the most prevalent genetically inherited cardiomyopathy that follows an autosomal dominant inheritance pattern. The majority of HCM cases can be attributed to mutation of the MYBPC3 gene, which encodes cMyBP-C, a crucial structural protein of the cardiac muscle. The manifestation of HCM's morphological, histological, and clinical symptoms is subject to the complex interplay of various determinants, including genetic mutation and environmental factors. Approximately half of MYBPC3 mutations give rise to truncated protein products, while the remaining mutations cause insertion/deletion, frameshift, or missense mutations of single amino acids. In addition, the onset of HCM may be attributed to disturbances in the protein and transcript quality control systems, namely, the ubiquitin-proteasome system and nonsense-mediated RNA dysfunctions. The aforementioned genetic modifications, which appear to be associated with unfavorable lifelong outcomes and are largely influenced by the type of mutation, exhibit a unique array of clinical manifestations ranging from asymptomatic to arrhythmic syncope and even sudden cardiac death. Although the current understanding of the MYBPC3 mutation does not comprehensively explain the varied phenotypic manifestations witnessed in patients with HCM, patients with pathogenic MYBPC3 mutations can exhibit an array of clinical manifestations ranging from asymptomatic to advanced heart failure and sudden cardiac death, leading to a higher rate of adverse clinical outcomes. This review focuses on MYBPC3 mutation and its characteristics as a prognostic determinant for disease onset and related clinical consequences in HCM.

Evolutionary trade-off and mutational bias could favor transcriptional over translational divergence within paralog pairs

How changes in the different steps of protein synthesis-transcription, translation and degradation-contribute to differences of protein abundance among genes is not fully understood. There is however accumulating evidence that transcriptional divergence might have a prominent role. Here, we show that yeast paralogous genes are more divergent in transcription than in translation. We explore two causal mechanisms for this predominance of transcriptional divergence: an evolutionary trade-off between the precision and economy of gene expression and a larger mutational target size for transcription. Performing simulations within a minimal model of post-duplication evolution, we find that both mechanisms are consistent with the observed divergence patterns. We also investigate how additional properties of the effects of mutations on gene expression, such as their asymmetry and correlation across levels of regulation, can shape the evolution of paralogs. Our results highlight the importance of fully characterizing the distributions of mutational effects on transcription and translation. They also show how general trade-offs in cellular processes and mutation bias can have far-reaching evolutionary impacts.

Global analysis of the yeast knockout phenome

Genome-wide phenotypic screens in the budding yeast Saccharomyces cerevisiae, enabled by its knockout collection, have produced the largest, richest, and most systematic phenotypic description of any organism. However, integrative analyses of this rich data source have been virtually impossible because of the lack of a central data repository and consistent metadata annotations. Here, we describe the aggregation, harmonization, and analysis of ~14,500 yeast knockout screens, which we call Yeast Phenome. Using this unique dataset, we characterized two unknown genes (YHR045W and YGL117W) and showed that tryptophan starvation is a by-product of many chemical treatments. Furthermore, we uncovered an exponential relationship between phenotypic similarity and intergenic distance, which suggests that gene positions in both yeast and human genomes are optimized for function.

A tractable physical model for the yeast polarity predicts epistasis and fitness

Accurate phenotype prediction based on genetic information has numerous societal applications, such as crop design or cellular factories. Epistasis, when biological components interact, complicates modelling phenotypes from genotypes. Here we show an approach to mitigate this complication for polarity establishment in budding yeast, where mechanistic information is abundant. We coarse-grain molecular interactions into a so-called mesotype, which we combine with gene expression noise into a physical cell cycle model. First, we show with computer simulations that the mesotype allows validation of the most current biochemical polarity models by quantitatively matching doubling times. Second, the mesotype elucidates epistasis emergence as exemplified by evaluating the predicted mutational effect of key polarity protein Bem1p when combined with known interactors or under different growth conditions. This example also illustrates how unlikely evolutionary trajectories can become more accessible. The tractability of our biophysically justifiable approach inspires a road-map towards bottom-up modelling complementary to statistical inferences.

This article is part of the theme issue ‘Interdisciplinary approaches to predicting evolutionary biology’.

Efficient and rapid fluorescent protein knock-in with universal donors in mouse embryonic stem cells

Fluorescent protein (FP) tagging is a key method for observing protein distribution, dynamics and interaction with other proteins in living cells. However, the typical approach using overexpression of tagged proteins can perturb cell behavior and introduce localization artifacts. To preserve native expression, fluorescent proteins can be inserted directly into endogenous genes. This approach has been widely used in yeast for decades, and more recently in invertebrate model organisms with the advent of CRISPR/Cas9. However, endogenous FP tagging has not been widely used in mammalian cells due to inefficient homology-directed repair. Recently, the CRISPaint system used non-homologous end joining for efficient integration of FP tags into native loci, but it only allows C-terminal knock-ins. Here, we have enhanced the CRISPaint system by introducing new universal donors for N-terminal insertion and for multi-color tagging with orthogonal selection markers. We adapted the procedure for mouse embryonic stem cells, which can be differentiated into diverse cell types. Our protocol is rapid and efficient, enabling live imaging in less than 2 weeks post-transfection. These improvements increase the versatility and applicability of FP knock-in in mammalian cells.

Targeted Mutations Produce Divergent Characteristics in Pedigreed Sake Yeast Strains

Modification of the genetic background and, in some cases, the introduction of targeted mutations can play a critical role in producing trait characteristics during the breeding of crops, livestock, and microorganisms. However, the question of how similar trait characteristics emerge when the same target mutation is introduced into different genetic backgrounds is unclear. In a previous study, we performed genome editing of AWA1, CAR1, MDE1, and FAS2 on the standard sake yeast strain Kyokai No. 7 to breed a sake yeast with multiple excellent brewing characteristics. By introducing the same targeted mutations into other pedigreed sake yeast strains, such as Kyokai strains No. 6, No. 9, and No. 10, we were able to create sake yeasts with the same excellent brewing characteristics. However, we found that other components of sake made by the genome-edited yeast strains did not change in the exact same way. For example, amino acid and isobutanol contents differed among the strain backgrounds. We also showed that changes in yeast cell morphology induced by the targeted mutations also differed depending on the strain backgrounds. The number of commonly changed morphological parameters was limited. Thus, divergent characteristics were produced by the targeted mutations in pedigreed sake yeast strains, suggesting a breeding strategy to generate a variety of sake yeasts with excellent brewing characteristics.

A biallelic variant in POLR2C is associated with congenital hearing loss and male infertility: Case report

BACKGROUND

DNA-directed RNA polymerase II subunit 3 (RPB3) is the third largest subunit of RNA polymerase II and is encoded by the POLR2C (OMIM:180663). A large Iranian family with congenital hearing loss and infertility is described here with genetic and clinical characterizations of five male patients.

METHODS

After doing clinical examinations, the proband was subjected to karyotyping and GJB2/6 sequencing to rule out the most evident chromosomal and gene abnormalities for male infertility and hearing loss, respectively. A custom-designed next-generation sequencing panel was also used to detect mutations in deafness-related genes. Finally, to reveal the underlying molecular cause(s) justifying hearing loss and male infertility, five male patients and 2 healthy male controls within the family were subjected to paired-end whole-exome sequencing (WES). Linkage analysis was also performed based on the data.

RESULTS

All male patients showed prelingual sensorineural hearing loss and also decreased sperm motility. Linkage analysis determined 16q21 as the most susceptible locus in which a missense variant in exon 7 of POLR2C-NM_032940.3:c.545T>C;p.(Val182Ala)-was identified as a 'likely pathogenic' variant co-segregated with phenotypes.

CONCLUSIONS

Using segregation and in silico analyses, for the first time, we suggested that the NM_032940.3:c.545T>C; p.(Val182Ala) in POLR2C is associated with hearing loss and male infertility.

Impact of Growth Rate on the Protein-mRNA Ratio in Pseudomonas aeruginosa

Our understanding of how bacterial pathogens colonize and persist during human infection has been hampered by the limited characterization of bacterial physiology during infection and a research bias toward in vitro, fast-growing bacteria. Recent research has begun to address these gaps in knowledge by directly quantifying bacterial mRNA levels during human infection, with the goal of assessing microbial community function at the infection site. However, mRNA levels are not always predictive of protein levels, which are the primary functional units of a cell. Here, we used carefully controlled chemostat experiments to examine the relationship between mRNA and protein levels across four growth rates in the bacterial pathogen Pseudomonas aeruginosa. We found a genome-wide positive correlation between mRNA and protein abundances across all growth rates, with genes required for P. aeruginosa viability having stronger correlations than nonessential genes. We developed a statistical method to identify genes whose mRNA abundances poorly predict protein abundances and calculated an RNA-to-protein (RTP) conversion factor to improve mRNA predictions of protein levels. The application of the RTP conversion factor to publicly available transcriptome data sets was highly robust, enabling the more accurate prediction of P. aeruginosa protein levels across strains and growth conditions. Finally, the RTP conversion factor was applied to P. aeruginosa human cystic fibrosis (CF) infection transcriptomes to provide greater insights into the functionality of this bacterium in the CF lung. This study addresses a critical problem in infection microbiology by providing a framework for enhancing the functional interpretation of bacterial human infection transcriptome data. IMPORTANCE Our understanding of bacterial physiology during human infection is limited by the difficulty in assessing bacterial function at the infection site. Recent studies have begun to address this question by quantifying bacterial mRNA levels in human-derived samples using transcriptomics. One challenge for these studies is the poor predictivity of mRNA for protein levels for some genes. Here, we addressed this challenge by measuring the transcriptomes and proteomes of P. aeruginosa grown at four growth rates. Our results revealed that the growth rate does not impact the genome-wide correlation of mRNA and protein levels. We used statistical methods to identify the genes for which mRNA and protein were poorly correlated and developed an RNA-to-protein (RTP) conversion factor that improved the predictivity of protein levels across strains and growth conditions. Our results provide new insights into mRNA-protein correlations and tools to enhance our understanding of bacterial physiology from transcriptome data.

Mendelian inheritance revisited: dominance and recessiveness in medical genetics

Understanding the consequences of genotype for phenotype (which ranges from molecule-level effects to whole-organism traits) is at the core of genetic diagnostics in medicine. Many measures of the deleteriousness of individual alleles exist, but these have limitations for predicting the clinical consequences. Various mechanisms can protect the organism from the adverse effects of functional variants, especially when the variant is paired with a wild type allele. Understanding why some alleles are harmful in the heterozygous state - representing dominant inheritance - but others only with the biallelic presence of pathogenic variants - representing recessive inheritance - is particularly important when faced with the deluge of rare genetic alterations identified by high throughput DNA sequencing. Both awareness of the specific quantitative and/or qualitative effects of individual variants and the elucidation of allelic and non-allelic interactions are essential to optimize genetic diagnosis and counselling.

QTL study reveals candidate genes underlying host resistance in a Red Queen model system

Specific interactions of host and parasite genotypes can lead to balancing selection, maintaining genetic diversity within populations. In order to understand the drivers of such specific coevolution, it is necessary to identify the molecular underpinnings of these genotypic interactions. Here, we investigate the genetic basis of resistance in the crustacean host, Daphnia magna, to attachment and subsequent infection by the bacterial parasite, Pasteuria ramosa. We discover a single locus with Mendelian segregation (3:1 ratio) with resistance being dominant, which we call the F locus. We use QTL analysis and fine mapping to localize the F locus to a 28.8-kb region in the host genome, adjacent to a known resistance supergene. We compare the 28.8-kb region in the two QTL parents to identify differences between host genotypes that are resistant versus susceptible to attachment and infection by the parasite. We identify 13 genes in the region, from which we highlight eight biological candidates for the F locus, based on presence/absence polymorphisms and differential gene expression. The top candidates include a fucosyltransferase gene that is only present in one of the two QTL parents, as well as several Cladoceran-specific genes belonging to a large family that is represented in multiple locations of the host genome. Fucosyltransferases have been linked to resistance in previous studies of Daphnia-Pasteuria and other host-parasite systems, suggesting that P. ramosa spore attachment could be mediated by changes in glycan structures on D. magna cuticle proteins. The Cladoceran-specific candidate genes suggest a resistance strategy that relies on gene duplication. Our results add a new locus to a growing genetic model of resistance in the D. magna-P. ramosa system. The identified candidate genes will be used in future functional genetic studies, with the ultimate aim to test for cycles of allele frequencies in natural populations.

MicroRNAs play regulatory roles in genomic balance

Classic genetics studies found that genomic imbalance caused by changing the dosage of part of the genome (aneuploidy) has more detrimental effects than altering the dosage of the whole genome (ploidy). Previous analysis revealed global modulation of gene expression triggered by aneuploidy across various species, including maize (Zea mays), Arabidopsis, yeast, mammals, etc. Plant microRNAs (miRNAs) are a class of 20- to 24-nt endogenous small noncoding RNAs that carry out post-transcriptional gene expression regulation. That miRNAs and their putative targets are preferentially retained as duplicates after whole-genome duplication, as are many transcription factors and signaling components, indicates miRNAs are likely to be dosage-sensitive and potentially involved in genomic balance networks. This review addresses the following questions regarding the role of miRNAs in genomic imbalance. (1) How do aneuploidy and polyploidy impact the expression of miRNAs? (2) Do miRNAs play a regulatory role in modulating the expression of their targets under genomic imbalance?

The malaria parasite chaperonin containing TCP-1 (CCT) complex: Data integration with other CCT proteomes

The multi-subunit chaperonin containing TCP-1 (CCT) is an essential molecular chaperone that functions in the folding of key cellular proteins. This paper reviews the interactome of the eukaryotic chaperonin CCT and its primary clients, the ubiquitous cytoskeletal proteins, actin and tubulin. CCT interacts with other nascent proteins, especially the WD40 propeller proteins, and also assists in the assembly of several protein complexes. A new proteomic dataset is presented for CCT purified from the human malarial parasite, P. falciparum (PfCCT). The CCT8 subunit gene was C-terminally FLAG-tagged using Selection Linked Integration (SLI) and CCT complexes were extracted from infected human erythrocyte cultures synchronized for maximum expression levels of CCT at the trophozoite stage of the parasite's asexual life cycle. We analyze the new PfCCT proteome and incorporate it into our existing model of the CCT system, supported by accumulated data from biochemical and cell biological experiments in many eukaryotic species. Together with measurements of CCT mRNA, CCT protein subunit copy number and the post-translational and chemical modifications of the CCT subunits themselves, a cumulative picture is emerging of an essential molecular chaperone system sitting at the heart of eukaryotic cell growth control and cell cycle regulation.

The epitranscriptome in ageing and stress resistance: A systematic review

Modifications of RNA, collectively called the "epitranscriptome", might provide novel biomarkers and innovative targets for interventions in geroscience but are just beginning to be studied in the context of ageing and stress resistance. RNA modifications modulate gene expression by affecting translation initiation and speed, miRNA binding, RNA stability, and RNA degradation. Nonetheless, the precise underlying molecular mechanisms and physiological consequences of most alterations of the epitranscriptome are still only poorly understood. We here systematically review different types of modifications of rRNA, tRNA and mRNA, the methodology to analyze them, current challenges in the field, and human disease associations. Furthermore, we compiled evidence for a connection between individual enzymes, which install RNA modifications, and lifespan in yeast, worm and fly. We also included resistance to different stressors and competitive fitness as search criteria for genes potentially relevant to ageing. Promising candidates identified by this approach include RCM1/NSUN5, RRP8, and F33A8.4/ZCCHC4 that introduce base methylations in rRNA, the methyltransferases DNMT2 and TRM9/ALKBH8, as well as factors involved in the thiolation or A to I editing in tRNA, and finally the m⁶A machinery for mRNA.

Modelling the fitness landscapes of a SCRaMbLEd yeast genome

The use of microorganisms for the production of industrially important compounds and enzymes is becoming increasingly important. Eukaryotes have been less widely used than prokaryotes in biotechnology, because of the complexity of their genomic structure and biology. The Yeast2.0 project is an international effort to engineer the yeast Saccharomyces cerevisiae to make it easy to manipulate, and to generate random variants using a system called SCRaMbLE. SCRaMbLE relies on artificial evolution in vitro to identify useful variants, an approach which is time consuming and expensive. We developed an in silico simulator for the SCRaMbLE system, using an evolutionary computing approach, which can be used to investigate and optimize the fitness landscape of the system. We applied the system to the investigation of the fitness landscape of one of the S. saccharomyces chromosomes, and found that our results fitted well with those previously published. We then simulated directed evolution with or without manipulation of SCRaMbLE, and revealed that controlling the SCRaMbLE process could effectively impact directed evolution. Our simulator can be applied to the analysis of the fitness landscapes of any organism for which SCRaMbLE has been implemented.

Loss-of-heterozygosity facilitates a fitness valley crossing in experimentally evolved multicellular yeast

Determining how adaptive possibilities do or do not become evolutionary realities is central to understanding the tempo and mode of evolutionary change. Some of the simplest evolutionary landscapes arise from underdominance at a single locus where the fitness valley consists of only one less-fit genotype. Despite their potential for rapid evolutionary change, few such examples have been investigated. We capitalized on an experimental system in which a significant evolutionary shift, the transition from uni-to-multicellularity, was observed in asexual diploid populations of Saccharomyces cerevisiae experimentally selected for increased settling rates. The multicellular phenotype results from recessive single-locus mutations that undergo loss-of-heterozygosity (LOH) events. By reconstructing the necessary heterozygous intermediate steps, we found that the evolution of multicellularity involves a decrease in size during the first steps. Heterozygous genotypes are 20% smaller in size than genotypes with functional alleles. Nevertheless, populations of heterozygotes give rise to multicellular genotypes more readily than unicellular genotypes with two functional alleles, by rapid LOH events. LOH drives adaptation that may enable rapid evolution in diploid yeast. Together these results show discordance between the phenotypic and genotypic multicellular transition. The evolutionary path to multicellularity, and the adaptive benefits of increased size, requires initial size reductions.

An in vivo gene amplification system for high level expression in Saccharomyces cerevisiae

Bottlenecks in metabolic pathways due to insufficient gene expression levels remain a significant problem for industrial bioproduction using microbial cell factories. Increasing gene dosage can overcome these bottlenecks, but current approaches suffer from numerous drawbacks. Here, we describe HapAmp, a method that uses haploinsufficiency as evolutionary force to drive in vivo gene amplification. HapAmp enables efficient, titratable, and stable integration of heterologous gene copies, delivering up to 47 copies onto the yeast genome. The method is exemplified in metabolic engineering to significantly improve production of the sesquiterpene nerolidol, the monoterpene limonene, and the tetraterpene lycopene. Limonene titre is improved by 20-fold in a single engineering step, delivering ∼1 g L-1 in the flask cultivation. We also show a significant increase in heterologous protein production in yeast. HapAmp is an efficient approach to unlock metabolic bottlenecks rapidly for development of microbial cell factories.

Differential Proteome and Interactome Analysis Reveal the Basis of Pleiotropy Associated With the Histidine Methyltransferase Hpm1p

The methylation of histidine is a post-translational modification whose function is poorly understood. Methyltransferase histidine protein methyltransferase 1 (Hpm1p) monomethylates H243 in the ribosomal protein Rpl3p and represents the only known histidine methyltransferase in Saccharomyces cerevisiae. Interestingly, the hpm1 deletion strain is highly pleiotropic, with many extraribosomal phenotypes including improved growth rates in alternative carbon sources. Here, we investigate how the loss of histidine methyltransferase Hpm1p results in diverse phenotypes, through use of targeted mass spectrometry (MS), growth assays, quantitative proteomics, and differential crosslinking MS. We confirmed the localization and stoichiometry of the H243 methylation site, found unreported sensitivities of Δhpm1 yeast to nonribosomal stressors, and identified differentially abundant proteins upon hpm1 knockout with clear links to the coordination of sugar metabolism. We adapted the emerging technique of quantitative large-scale stable isotope labeling of amino acids in cell culture crosslinking MS for yeast, which resulted in the identification of 1267 unique in vivo lysine-lysine crosslinks. By reproducibly monitoring over 350 of these in WT and Δhpm1, we detected changes to protein structure or protein-protein interactions in the ribosome, membrane proteins, chromatin, and mitochondria. Importantly, these occurred independently of changes in protein abundance and could explain a number of phenotypes of Δhpm1, not addressed by expression analysis. Further to this, some phenotypes were predicted solely from changes in protein structure or interactions and could be validated by orthogonal techniques. Taken together, these studies reveal a broad role for Hpm1p in yeast and illustrate how crosslinking MS will be an essential tool for understanding complex phenotypes.

Consequences of Chromosome Loss: Why Do Cells Need Each Chromosome Twice?

Aneuploidy is a cellular state with an unbalanced chromosome number that deviates from the usual euploid status. During evolution, elaborate cellular mechanisms have evolved to maintain the correct chromosome content over generations. The rare errors often lead to cell death, cell cycle arrest, or impaired proliferation. At the same time, aneuploidy can provide a growth advantage under selective conditions in a stressful, frequently changing environment. This is likely why aneuploidy is commonly found in cancer cells, where it correlates with malignancy, drug resistance, and poor prognosis. To understand this "aneuploidy paradox", model systems have been established and analyzed to investigate the consequences of aneuploidy. Most of the evidence to date has been based on models with chromosomes gains, but chromosome losses and recurrent monosomies can also be found in cancer. We summarize the current models of chromosome loss and our understanding of its consequences, particularly in comparison to chromosome gains.

Overdominant and partially dominant mutations drive clonal adaptation in diploid Saccharomyces cerevisiae

Identification of adaptive targets in experimental evolution typically relies on extensive replication and genetic reconstruction. An alternative approach is to directly assay all mutations in an evolved clone by generating pools of segregants that contain random combinations of evolved mutations. Here, we apply this method to six Saccharomyces cerevisiae clones isolated from four diploid populations that were clonally evolved for 2,000 generations in rich glucose medium. Each clone contains 17-26 mutations relative to the ancestor. We derived intermediate genotypes between the founder and the evolved clones by bulk mating sporulated cultures of the evolved clones to a barcoded haploid version of the ancestor. We competed the resulting barcoded diploids en masse and quantified fitness in the experimental and alternative environments by barcode sequencing. We estimated average fitness effects of evolved mutations using barcode-based fitness assays and whole genome sequencing for a subset of segregants. In contrast to our previous work with haploid evolved clones, we find that diploids carry fewer beneficial mutations, with modest fitness effects (up to 5.4%) in the environment in which they arose. In agreement with theoretical expectations, reconstruction experiments show that all mutations with a detectable fitness effect manifest some degree of dominance over the ancestral allele, and most are overdominant. Genotypes with lower fitness effects in alternative environments allowed us to identify conditions that drive adaptation in our system.

Plant cytoplasmic ribosomal proteins: an update on classification, nomenclature, evolution and resources

Standardized naming systems are essential to integrate and unify distinct research fields, and to link multi-species data within and across kingdoms. We conducted a comprehensive survey of cytoplasmic ribosomal proteins (CRPs) in the dicot model Arabidopsis thaliana and the monocot model rice, noting that the standardized naming system has not been widely adopted in the plant community. We generated a database linking the old classical names to their updated and compliant names. We also explored the sequences, molecular evolution, and structural and functional characteristics of all plant CRP families, emphasizing evolutionarily conserved and plant-specific features through cross-kingdom comparisons. Unlike fungal CRP paralogs that were mainly created by whole-genome duplication (WGD) or retroposition under a concerted evolution mode, plant CRP genes evolved primarily through both WGD and tandem duplications in a rapid birth-and-death process. We also provide a web-based resource (http://www.plantcrp.cn/) with the aim of sharing the latest knowledge on plant CRPs and facilitating the continued development of a standardized framework across the entire community.

The cellular response to drug perturbation is limited: comparison of large-scale chemogenomic fitness signatures

Background

Chemogenomic profiling is a powerful approach for understanding the genome-wide cellular response to small molecules. First developed in Saccharomyces cerevisiae, chemogenomic screens provide direct, unbiased identification of drug target candidates as well as genes required for drug resistance. While many laboratories have performed chemogenomic fitness assays, few have been assessed for reproducibility and accuracy. Here we analyze the two largest independent yeast chemogenomic datasets comprising over 35 million gene-drug interactions and more than 6000 unique chemogenomic profiles; the first from our own academic laboratory (HIPLAB) and the second from the Novartis Institute of Biomedical Research (NIBR).

Results

Despite substantial differences in experimental and analytical pipelines, the combined datasets revealed robust chemogenomic response signatures, characterized by gene signatures, enrichment for biological processes and mechanisms of drug action. We previously reported that the cellular response to small molecules is limited and can be described by a network of 45 chemogenomic signatures. In the present study, we show that the majority of these signatures (66%) are also found in the companion dataset, providing further support for their biological relevance as conserved systems-level, small molecule response systems.

Conclusions

Our results demonstrate the robustness of chemogenomic fitness profiling in yeast, while offering guidelines for performing other high-dimensional comparisons including parallel CRISPR screens in mammalian cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08395-x.

Psychiatric Onset Alexander Disease: An Important Challenge in Neuropsychiatric Diagnosis: A Case Report

INTRODUCTION

Alexander disease is a heterogeneous group of diseases with various manifestations based on the age of disease onset. This rare leukodystrophy syndrome with mutations in the GFAP gene could present with developmental delay and seizure in the infantile form to ataxia and bulbar palsy in adulthood. However, psychiatric symptoms are not well-defined and are usually evaluated after disease diagnosis, not before disease investigations.

CASE REPORT

Our patient is a 52-year-old Iranian woman with a history of depression since 17 years ago, a suicidal attempt two years ago, and ingestion of a large amount of opium with the intention of suicide 2 months ago. She was presented with disorientation and probably a delirious state in the last interview. Eventually, in comprehensive investigations, white matter hyperintensity in MRI and leukodystrophy was diagnosed to determine the cause of these changes, we did a gene study, found whole exon deletion of the GFAP gene, and made a diagnosis of late-onset Alexander disease.

CONCLUSION

Neurological-onset manifestation of Alexander disease, specifically late-onset form, is the most common clinical picture of disease and was seen in about 90% of patients, but psychiatric symptoms are not well-known, and psychiatric-onset disease was not described yet. Various gene mutations were described in late-onset Alexander disease; however, the large whole exon deletion which was revealed in our patient is a novel mutation and significantly needs to be explored. Here authors describe a late-onset Alexander disease with psychiatric-onset symptoms and novel large exon deletion in the GFAP gene.

HIGHLIGHTS

Alexander disease is a rare heterogeneous disorder that could have various symptoms of the central nervous system involvement.The whole-exons deletion of the GFAP gene in an adult patient with features of Alexander disease is the first Gene mutation that was revealed in this case.Psychiatric onset Alexander disease is the one differential diagnosis in the patients with atypical psychiatric symptoms combined with soft neurological signs.Neurologic consultation and appropriate imaging and laboratory procedures could help early diagnosis and potential treatment.

PLAIN LANGUAGE SUMMARY

Patients with atypical psychiatric symptoms are usually visited more times in the year without any significant benefit. They receive numerous medications and encounter significant complications due to mentioned polypharmacy. However, genetic, metabolic, or neurological causes could be considered in some treatment-resistant cases. We described the rare genetic disorder(Late-Onset Alexander disease) in the Iranian woman with atypical and treatment-resistant depression with suicidal attempts. We proposed holistic assessment in the patients with psychiatric symptoms which have atypical course or response to treatment or are accompanied by neurological and cognitive symptoms.

The good, the bad, and the ugly: Evolutionary and pathological aspects of gene dosage alterations

Diploid organisms contain a maternal and a paternal genome complement that is thought to provide robustness and allow developmental progression despite genetic perturbations that occur in heterozygosity. However, changes affecting gene dosage from the chromosome down to the individual gene level possess a significant pathological potential and can lead to developmental disorders (DDs). This indicates that expression from a balanced gene complement is highly relevant for proper cellular and organismal function in eukaryotes. Paradoxically, gene and whole chromosome duplications are a principal driver of evolution, while heteromorphic sex chromosomes (XY and ZW) are naturally occurring aneuploidies important for sex determination. Here, we provide an overview of the biology of gene dosage at the crossroads between evolutionary benefit and pathogenicity during disease. We describe the buffering mechanisms and cellular responses to alterations, which could provide a common ground for the understanding of DDs caused by copy number alterations.

Repetitive stress fracture: a warning sign of genetic susceptibility to fracture? A case report of a heterozygous variant in SERPINF1

The occurrence of fractures in young individuals is frequently overlooked by physicians, especially when associated with exercise or trauma. Nevertheless, multiple fractures should always be investigated since underlying conditions can predispose to such events. We describe here the case of a young, healthy woman who sustained multiple fractures in the lower limbs, which were initially considered to be "stress fractures". Further investigation, including a panel of genes associated with osteogenesis imperfecta, revealed that the patient is a heterozygous carrier of a SERPINF1 variant. According to criteria recommended by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology, this variant is classified as likely benign (PM2, PP3, PP4, BP1, and BP4). The patient's mother and brother were also asymptomatic carriers of the variant and had sustained previous minor fractures. The patient had normal biochemical profile and bone density. This condition has been rarely described and is not associated with low bone mineral density or altered bone turnover markers. This case highlights the importance of investigating multiple fractures in young patients who are otherwise healthy since these may be a warning sign of rare genetic conditions associated with fragility fractures.

Ploidy and recombination proficiency shape the evolutionary adaptation to constitutive DNA replication stress

In haploid budding yeast, evolutionary adaptation to constitutive DNA replication stress alters three genome maintenance modules: DNA replication, the DNA damage checkpoint, and sister chromatid cohesion. We asked how these trajectories depend on genomic features by comparing the adaptation in three strains: haploids, diploids, and recombination deficient haploids. In all three, adaptation happens within 1000 generations at rates that are correlated with the initial fitness defect of the ancestors. Mutations in individual genes are selected at different frequencies in populations with different genomic features, but the benefits these mutations confer are similar in the three strains, and combinations of these mutations reproduce the fitness gains of evolved populations. Despite the differences in the selected mutations, adaptation targets the same three functional modules in strains with different genomic features, revealing a common evolutionary response to constitutive DNA replication stress.

Harnessing model organism genomics to underpin the machine learning-based prediction of essential genes in eukaryotes - Biotechnological implications

The availability of high-quality genomes and advances in functional genomics have enabled large-scale studies of essential genes in model eukaryotes, including the 'elegant worm' (Caenorhabditis elegans; Nematoda) and the 'vinegar fly' (Drosophila melanogaster; Arthropoda). However, this is not the case for other, much less-studied organisms, such as socioeconomically important parasites, for which functional genomic platforms usually do not exist. Thus, there is a need to develop innovative techniques or approaches for the prediction, identification and investigation of essential genes. A key approach that could enable the prediction of such genes is machine learning (ML). Here, we undertake an historical review of experimental and computational approaches employed for the characterisation of essential genes in eukaryotes, with a particular focus on model ecdysozoans (C. elegans and D. melanogaster), and discuss the possible applicability of ML-approaches to organisms such as socioeconomically important parasites. We highlight some recent results showing that high-performance ML, combined with feature engineering, allows a reliable prediction of essential genes from extensive, publicly available 'omic data sets, with major potential to prioritise such genes (with statistical confidence) for subsequent functional genomic validation. These findings could 'open the door' to fundamental and applied research areas. Evidence of some commonality in the essential gene-complement between these two organisms indicates that an ML-engineering approach could find broader applicability to ecdysozoans such as parasitic nematodes or arthropods, provided that suitably large and informative data sets become/are available for proper feature engineering, and for the robust training and validation of algorithms. This area warrants detailed exploration to, for example, facilitate the identification and characterisation of essential molecules as novel targets for drugs and vaccines against parasitic diseases. This focus is particularly important, given the substantial impact that such diseases have worldwide, and the current challenges associated with their prevention and control and with drug resistance in parasite populations.

Can gene-inactivating mutations lead to evolutionary novelty?

Evolutionary novelty is difficult to define. It typically involves shifts in organismal or biochemical phenotypes that can be seen as qualitative as well as quantitative changes. In laboratory-based experimental evolution of novel phenotypes and the human domestication of crops, the majority of the mutations that lead to adaptation are loss-of-function mutations that impair or eliminate the function of genes rather than gain-of-function mutations that increase or qualitatively alter the function of proteins. Here, I speculate that easier access to loss-of-function mutations has led them to play a major role in the adaptive radiations that occur when populations have access to many unoccupied ecological niches. I discuss five possible objections to this claim: that genes can only survive if they confer benefits to the organisms that bear them, antagonistic pleiotropy, the importance of pre-existing genetic variation in populations, the danger that adaptation by breaking genes will, over long times, cause organisms to run out of genes, and the recessive nature of most loss-of-function mutations.

Disruption of ECM33 in diploid wine yeast EC1118: cell morphology and aggregation and their influence on fermentation performance

When investigating yeast gene function in relation to fermentation, many screens rely on haploid yeast derivatives. This, however, is not representative of industrial strains, which are typically diploid. One such example is the disruption of ECM33, which was associated with improved fermentation in the haploid wine yeast C911D, but remains uncharacterised in a diploid industrial strain background. We report on the homozygous disruption of ECM33 in Lalvin EC1118 using CRISPR/Cas9. EC1118 ecm33 resulted in a reduction of fermentation duration in a defined medium with limiting and sufficient nitrogen (-20% and -13%, respectively) when shaken. Increased cell size and aggregation, a phenotype previously unidentified in ecm33∆ as haploid yeast tend to aggregate, was also observed. This phenotype led to premature settling thereby the yeast behaving similarly to EC1118 in wine-like semi-static fermentations in a chemically defined medium. Further assessment in semi-static Riesling and Chardonnay fermentations inoculated based on cell number or biomass resulted in no significant difference or significantly slower fermentation duration in comparison the EC1118, nullifying the benefits of this mutation unless agitation is applied. This study draws attention to phenotypes being condition-dependent, highlighting the need to characterise and verify fermentation efficiency mutations in industrial yeast.

Genes Encoding Teleost Orthologs of Human Haploinsufficient and Monoallelically Expressed Genes Remain in Duplicate More Frequently Than the Whole Genome

Gene dosage is an important issue both in cell and evolutionary biology. Most genes are present in two copies or alleles in diploid eukariotic cells. The most outstanding exception is monoallelic gene expression (MA) that concerns genes localized on the X chromosome or in regions undergoing parental imprinting in eutherians, and many other genes scattered throughout the genome. In diploids, haploinsufficiency (HI) implies that a single functional copy of a gene in a diploid organism is insufficient to ensure a normal biological function. One of the most important mechanisms ensuring functional innovation during evolution is whole genome duplication (WGD). In addition to the two WGDs that have occurred in vertebrate genomes, the teleost genomes underwent an additional WGD, after their divergence from tetrapods. In the present work, we have studied on 57 teleost species whether the orthologs of human MA or HI genes remain more frequently in duplicates or returned more frequently in singleton than the rest of the genome. Our results show that the teleost orthologs of HI human genes remained more frequently in duplicate than the rest of the genome in all of the teleost species studied. No signal was observed for the orthologs of genes mapping to the human X chromosome or subjected to parental imprinting. Surprisingly, the teleost orthologs of the other human MA genes remained in duplicate more frequently than the rest of the genome for most teleost species. These results suggest that the teleost orthologs of MA and HI human genes also undergo selective pressures either related to absolute protein amounts and/or of dosage balance issues. However, these constraints seem to be different for MA genes in teleost in comparison with human genomes.

The miR166-SlHB15A regulatory module controls ovule development and parthenocarpic fruit set under adverse temperatures in tomato

Fruit set is inhibited by adverse temperatures, with consequences on yield. We isolated a tomato mutant producing fruits under non-permissive hot temperatures and identified the causal gene as SlHB15A, belonging to class III homeodomain leucine-zipper transcription factors. SlHB15A loss-of-function mutants display aberrant ovule development that mimics transcriptional changes occurring in fertilized ovules and leads to parthenocarpic fruit set under optimal and non-permissive temperatures, in field and greenhouse conditions. Under cold growing conditions, SlHB15A is subjected to conditional haploinsufficiency and recessive dosage sensitivity controlled by microRNA 166 (miR166). Knockdown of SlHB15A alleles by miR166 leads to a continuum of aberrant ovules correlating with parthenocarpic fruit set. Consistent with this, plants harboring an Slhb15a-miRNA166-resistant allele developed normal ovules and were unable to set parthenocarpic fruit under cold conditions. DNA affinity purification sequencing and RNA-sequencing analyses revealed that SlHB15A is a bifunctional transcription factor expressed in the ovule integument. SlHB15A binds to the promoters of auxin-related genes to repress auxin signaling and to the promoters of ethylene-related genes to activate their expression. A survey of tomato genetic biodiversity identified pat and pat-1, two historical parthenocarpic mutants, as alleles of SlHB15A. Taken together, our findings demonstrate the role of SlHB15A as a sentinel to prevent fruit set in the absence of fertilization and provide a mean to enhance fruiting under extreme temperatures.

Hsp90 Co-chaperones Form Plastic Genetic Networks Adapted to Client Maturation

Heat shock protein 90 (Hsp90) is a molecular chaperone regulating the activity of diverse client proteins together with a plethora of different co-chaperones. Whether these functionally cooperate has remained enigmatic. We analyze all double mutants of 11 Saccharomyces cerevisiae Hsp90 co-chaperones in vivo concerning effects on cell physiology and the activation of specific client proteins. We find that client activation is supported by a genetic network with weak epistasis between most co-chaperones and a few modules with strong genetic interactions. These include an epistatic module regulating protein translation and dedicated epistatic networks for specific clients. For kinases, the bridging of Hsp70 and Hsp90 by Sti1/Hop is essential for activation, whereas for steroid hormone receptors, an epistatic module regulating their dwell time on Hsp90 is crucial, highlighting the specific needs of different clients. Thus, the Hsp90 system is characterized by plastic co-chaperone networks fine-tuning the conformational processing in a client-specific manner.

Technologies for High-Throughput Identification of Antibiotic Mechanism of Action

There are two main strategies for antibiotic discovery: target-based and phenotypic screening. The latter has been much more successful in delivering first-in-class antibiotics, despite the major bottleneck of delayed Mechanism-of-Action (MOA) identification. Although finding new antimicrobial compounds is a very challenging task, identifying their MOA has proven equally challenging. MOA identification is important because it is a great facilitator of lead optimization and improves the chances of commercialization. Moreover, the ability to rapidly detect MOA could enable a shift from an activity-based discovery paradigm towards a mechanism-based approach. This would allow to probe the grey chemical matter, an underexplored source of structural novelty. In this study we review techniques with throughput suitable to screen large libraries and sufficient sensitivity to distinguish MOA. In particular, the techniques used in chemical genetics (e.g., based on overexpression and knockout/knockdown collections), promoter-reporter libraries, transcriptomics (e.g., using microarrays and RNA sequencing), proteomics (e.g., either gel-based or gel-free techniques), metabolomics (e.g., resourcing to nuclear magnetic resonance or mass spectrometry techniques), bacterial cytological profiling, and vibrational spectroscopy (e.g., Fourier-transform infrared or Raman scattering spectroscopy) were discussed. Ultimately, new and reinvigorated phenotypic assays bring renewed hope in the discovery of a new generation of antibiotics.

The Role of Structural Variation in Adaptation and Evolution of Yeast and Other Fungi

Mutations in DNA can be limited to one or a few nucleotides, or encompass larger deletions, insertions, duplications, inversions and translocations that span long stretches of DNA or even full chromosomes. These so-called structural variations (SVs) can alter the gene copy number, modify open reading frames, change regulatory sequences or chromatin structure and thus result in major phenotypic changes. As some of the best-known examples of SV are linked to severe genetic disorders, this type of mutation has traditionally been regarded as negative and of little importance for adaptive evolution. However, the advent of genomic technologies uncovered the ubiquity of SVs even in healthy organisms. Moreover, experimental evolution studies suggest that SV is an important driver of evolution and adaptation to new environments. Here, we provide an overview of the causes and consequences of SV and their role in adaptation, with specific emphasis on fungi since these have proven to be excellent models to study SV.