The chemical genomic portrait of yeast: uncovering a phenotype for all genes

Genome engineering on size reduction and complexity simplification: A review

BACKGROUND

Genome simplification is an important topic in the field of life sciences that has attracted attention from its conception to the present day. It can help uncover the essential components of the genome and, in turn, shed light on the underlying operating principles of complex biological systems. This has made it a central focus of both basic and applied research in the life sciences. With the recent advancements in related technologies and our increasing knowledge of the genome, now is an opportune time to delve into this topic.

AIM OF REVIEW

Our review investigates the progress of genome simplification from two perspectives: genome size reduction and complexity simplification. In addition, we provide insights into the future development trends of genome simplification.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Reducing genome size requires eliminating non-essential elements as much as possible. This process has been facilitated by advances in genome manipulation and synthesis techniques. However, we still need a better and clearer understanding of living systems to reduce genome complexity. As there is a lack of quantitative and clearly defined standards for this task, we have opted to approach the topic from various perspectives and present our findings accordingly.

Uncovering the determinants of brain functioning, behavior and their interplay in the light of context

Notwithstanding the huge progress in molecular and cellular neuroscience, our ability to understand the brain and develop effective treatments promoting mental health is still limited. This can be partially ascribed to the reductionist, deterministic and mechanistic approaches in neuroscience that struggle with the complexity of the central nervous system. Here, I introduce the Context theory of constrained systems proposing a novel role of contextual factors and genetic, molecular and neural substrates in determining brain functioning and behavior. This theory entails key conceptual implications. First, context is the main driver of behavior and mental states. Second, substrates, from genes to brain areas, have no direct causal link to complex behavioral responses as they can be combined in multiple ways to produce the same response and different responses can impinge on the same substrates. Third, context and biological substrates play distinct roles in determining behavior: context drives behavior, substrates constrain the behavioral repertoire that can be implemented. Fourth, since behavior is the interface between the central nervous system and the environment, it is a privileged level of control and orchestration of brain functioning. Such implications are illustrated through the Kitchen metaphor of the brain. This theoretical framework calls for the revision of key concepts in neuroscience and psychiatry, including causality, specificity and individuality. Moreover, at the clinical level, it proposes treatments inducing behavioral changes through contextual interventions as having the highest impact to reorganize the complexity of the human mind and to achieve a long-lasting improvement in mental health.

Ancient and recent origins of shared polymorphisms in yeast

Shared genetic polymorphisms between populations and species can be ascribed to ancestral variation or to more recent gene flow. Here, we mapped shared polymorphisms in Saccharomyces cerevisiae and its sister species Saccharomyces paradoxus, which diverged 4-6 million years ago. We used a dense map of single-nucleotide diagnostic markers (mean distance 15.6 base pairs) in 1,673 sequenced S. cerevisiae isolates to catalogue 3,852 sequence blocks (≥5 consecutive markers) introgressed from S. paradoxus, with most being recent and clade-specific. The highly diverged wild Chinese S. cerevisiae lineages were depleted of introgressed blocks but retained an excess of individual ancestral polymorphisms derived from incomplete lineage sorting, perhaps due to less dramatic population bottlenecks. In the non-Chinese S. cerevisiae lineages, we inferred major hybridization events and detected cases of overlapping introgressed blocks across distinct clades due to either shared histories or convergent evolution. We experimentally engineered, in otherwise isogenic backgrounds, the introgressed PAD1-FDC1 gene pair that independently arose in two S. cerevisiae clades and revealed that it increases resistance against diverse antifungal drugs. Overall, our study retraces the histories of divergence and secondary contacts across S. cerevisiae and S. paradoxus populations and unveils a functional outcome.

The metabolic domestication syndrome of budding yeast

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

Recent advances in the characterization of essential genes and development of a database of essential genes

Over the past few decades, there has been a significant interest in the study of essential genes, which are crucial for the survival of an organism under specific environmental conditions and thus have practical applications in the fields of synthetic biology and medicine. An increasing amount of experimental data on essential genes has been obtained with the continuous development of technological methods. Meanwhile, various computational prediction methods, related databases and web servers have emerged accordingly. To facilitate the study of essential genes, we have established a database of essential genes (DEG), which has become popular with continuous updates to facilitate essential gene feature analysis and prediction, drug and vaccine development, as well as artificial genome design and construction. In this article, we summarized the studies of essential genes, overviewed the relevant databases, and discussed their practical applications. Furthermore, we provided an overview of the main applications of DEG and conducted comprehensive analyses based on its latest version. However, it should be noted that the essential gene is a dynamic concept instead of a binary one, which presents both opportunities and challenges for their future development.

A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds

Current approaches to define chemical-genetic interactions (CGIs) in human cell lines are resource-intensive. We designed a scalable chemical-genetic screening platform by generating a DNA damage response (DDR)-focused custom sgRNA library targeting 1011 genes with 3033 sgRNAs. We performed five proof-of-principle compound screens and found that the compounds' known modes-of-action (MoA) were enriched among the compounds' CGIs. These scalable screens recapitulated expected CGIs at a comparable signal-to-noise ratio (SNR) relative to genome-wide screens. Furthermore, time-resolved CGIs, captured by sequencing screens at various time points, suggested an unexpected, late interstrand-crosslinking (ICL) repair pathway response to camptothecin-induced DNA damage. Our approach can facilitate screening compounds at scale with 20-fold fewer resources than commonly used genome-wide libraries and produce biologically informative CGI profiles.

Bile acid fitness determinants of a Bacteroides fragilis isolate from a human pouchitis patient

IMPORTANCE

The Gram-negative bacterium Bacteroides fragilis is a common member of the human gut microbiota that colonizes multiple host niches and can influence human physiology through a variety of mechanisms. Identification of genes that enable B. fragilis to grow across a range of host environments has been impeded in part by the relatively limited genetic tractability of this species. We have developed a high-throughput genetic resource for a B. fragilis strain isolated from a UC pouchitis patient. Bile acids limit microbial growth and are altered in abundance in UC pouches, where B. fragilis often blooms. Using this resource, we uncovered pathways and processes that impact B. fragilis fitness in bile and that may contribute to population expansions during bouts of gut inflammation.

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.

The regulatory landscape of the yeast phosphoproteome

The cellular ability to react to environmental fluctuations depends on signaling networks that are controlled by the dynamic activities of kinases and phosphatases. Here, to gain insight into these stress-responsive phosphorylation networks, we generated a quantitative mass spectrometry-based atlas of early phosphoproteomic responses in Saccharomyces cerevisiae exposed to 101 environmental and chemical perturbations. We report phosphosites on 59% of the yeast proteome, with 18% of the proteome harboring a phosphosite that is regulated within 5 min of stress exposure. We identify shared and perturbation-specific stress response programs, uncover loss of phosphorylation as an integral early event, and dissect the interconnected regulatory landscape of kinase-substrate networks, as we exemplify with target of rapamycin signaling. We further reveal functional organization principles of the stress-responsive phosphoproteome based on phosphorylation site motifs, kinase activities, subcellular localizations, shared functions and pathway intersections. This information-rich map of 25,000 regulated phosphosites advances our understanding of signaling networks.

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.

Broad functional profiling of fission yeast proteins using phenomics and machine learning

Many proteins remain poorly characterized even in well-studied organisms, presenting a bottleneck for research. We applied phenomics and machine-learning approaches with Schizosaccharomyces pombe for broad cues on protein functions. We assayed colony-growth phenotypes to measure the fitness of deletion mutants for 3509 non-essential genes in 131 conditions with different nutrients, drugs, and stresses. These analyses exposed phenotypes for 3492 mutants, including 124 mutants of 'priority unstudied' proteins conserved in humans, providing varied functional clues. For example, over 900 proteins were newly implicated in the resistance to oxidative stress. Phenotype-correlation networks suggested roles for poorly characterized proteins through 'guilt by association' with known proteins. For complementary functional insights, we predicted Gene Ontology (GO) terms using machine learning methods exploiting protein-network and protein-homology data (NET-FF). We obtained 56,594 high-scoring GO predictions, of which 22,060 also featured high information content. Our phenotype-correlation data and NET-FF predictions showed a strong concordance with existing PomBase GO annotations and protein networks, with integrated analyses revealing 1675 novel GO predictions for 783 genes, including 47 predictions for 23 priority unstudied proteins. Experimental validation identified new proteins involved in cellular aging, showing that these predictions and phenomics data provide a rich resource to uncover new protein functions.

SUMOylation of yeast Pso2 enhances its translocation and accumulation in the mitochondria and suppresses methyl methanesulfonate-induced mitochondrial DNA damage

Saccharomyces cerevisiae Pso2/SNM1 is essential for DNA interstrand crosslink (ICL) repair; however, its mechanism of action remains incompletely understood. While recent work has revealed that Pso2/Snm1 is dual-localized in the nucleus and mitochondria, it remains unclear whether cell-intrinsic and -extrinsic factors regulate its subcellular localization and function. Herein, we show that Pso2 undergoes ubiquitination and phosphorylation, but not SUMOylation, in unstressed cells. Unexpectedly, we found that methyl methanesulfonate (MMS), rather than ICL-forming agents, induced robust SUMOylation of Pso2 on two conserved residues, K97 and K575, and that SUMOylation markedly increased its abundance in the mitochondria. Reciprocally, SUMOylation had no discernible impact on Pso2 translocation to the nucleus, despite the presence of steady-state levels of SUMOylated Pso2 across the cell cycle. Furthermore, substitution of the invariant residues K97 and K575 by arginine in the Pso2 SUMO consensus motifs severely impaired SUMOylation and abolished its translocation to the mitochondria of MMS-treated wild type cells, but not in unstressed cells. We demonstrate that whilst Siz1 and Siz2 SUMO E3 ligases catalyze Pso2 SUMOylation, the former plays a dominant role. Notably, we found that the phenotypic characteristics of the SUMOylation-defective mutant Pso2K97R/K575R closely mirrored those observed in the Pso2Δ petite mutant. Additionally, leveraging next-generation sequencing analysis, we demonstrate that Pso2 mitigates MMS-induced damage to mitochondrial DNA (mtDNA). Viewed together, our work offers previously unknown insights into the link between genotoxic stress-induced SUMOylation of Pso2 and its preferential targeting to the mitochondria, as well as its role in attenuating MMS-induced mtDNA damage.

Role of genetic architecture in phenotypic plasticity

Phenotypic plasticity, the ability of an organism to display different phenotypes across environments, is widespread in nature. Plasticity aids survival in novel environments. Herein, we review studies from yeast that allow us to start uncovering the genetic architecture of phenotypic plasticity. Genetic variants and their interactions impact the phenotype in different environments, and distinct environments modulate the impact of genetic variants and their interactions on the phenotype. Because of this, certain hidden genetic variation is expressed in specific genetic and environmental backgrounds. A better understanding of the genetic mechanisms of phenotypic plasticity will help to determine short- and long-term responses to selection and how wide variation in disease manifestation occurs in human populations.

Drug Drop Test: How to Quickly Identify Potential Therapeutic Compounds for Mitochondrial Diseases Using Yeast Saccharomyces cerevisiae

Mitochondrial diseases (MDs) refer to a group of clinically and genetically heterogeneous pathologies characterized by defective mitochondrial function and energy production. Unfortunately, there is no effective treatment for most MDs, and current therapeutic management is limited to relieving symptoms. The yeast Saccharomyces cerevisiae has been efficiently used as a model organism to study mitochondria-related disorders thanks to its easy manipulation and well-known mitochondrial biogenesis and metabolism. It has been successfully exploited both to validate alleged pathogenic variants identified in patients and to discover potential beneficial molecules for their treatment. The so-called "drug drop test", a phenotype-based high-throughput screening, especially if coupled with a drug repurposing approach, allows the identification of molecules with high translational potential in a cost-effective and time-saving manner. In addition to drug identification, S. cerevisiae can be used to point out the drug's target or pathway. To date, drug drop tests have been successfully carried out for a variety of disease models, leading to very promising results. The most relevant aspect is that studies on more complex model organisms confirmed the effectiveness of the drugs, strengthening the results obtained in yeast and demonstrating the usefulness of this screening as a novel approach to revealing new therapeutic molecules for MDs.

Quantitative approaches to study phenotypic effects of large-scale genetic perturbations

How microbes interact with their environment and how the complex interplay of their genes enables them to survive and thrive under stress is a fundamental question in microbial system biology, which is also important from a public health perspective. Large-scale studies of gene-gene, gene-drug, and drug-drug interactions have proven to be powerful tools for elucidating gene function and functional modules in the cell. Approaches that systematically quantify phenotypes in libraries of microbial strains with genome-wide genetic perturbations are crucial for progress in this area. Here, we review recent advances in this field, and point out applications to the study of gene-drug interactions. We highlight newly developed techniques for the rapid generation of genome-wide mutant libraries and the high-throughput measurement of more complex phenotypes and other observables, such as cell morphology or thermal stability of the proteome.

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.

Homo cerevisiae-Leveraging Yeast for Investigating Protein-Protein Interactions and Their Role in Human Disease

Understanding how genetic variation affects phenotypes represents a major challenge, particularly in the context of human disease. Although numerous disease-associated genes have been identified, the clinical significance of most human variants remains unknown. Despite unparalleled advances in genomics, functional assays often lack sufficient throughput, hindering efficient variant functionalization. There is a critical need for the development of more potent, high-throughput methods for characterizing human genetic variants. Here, we review how yeast helps tackle this challenge, both as a valuable model organism and as an experimental tool for investigating the molecular basis of phenotypic perturbation upon genetic variation. In systems biology, yeast has played a pivotal role as a highly scalable platform which has allowed us to gain extensive genetic and molecular knowledge, including the construction of comprehensive interactome maps at the proteome scale for various organisms. By leveraging interactome networks, one can view biology from a systems perspective, unravel the molecular mechanisms underlying genetic diseases, and identify therapeutic targets. The use of yeast to assess the molecular impacts of genetic variants, including those associated with viral interactions, cancer, and rare and complex diseases, has the potential to bridge the gap between genotype and phenotype, opening the door for precision medicine approaches and therapeutic development.

Direct tests of cytochrome c and c1 functions in the electron transport chain of malaria parasites

The mitochondrial electron transport chain (ETC) of Plasmodium malaria parasites is a major antimalarial drug target, but critical cytochrome (cyt) functions remain unstudied and enigmatic. Parasites express two distinct cyt c homologs (c and c-2) with unusually sparse sequence identity and uncertain fitness contributions. P. falciparum cyt c-2 is the most divergent eukaryotic cyt c homolog currently known and has sequence features predicted to be incompatible with canonical ETC function. We tagged both cyt c homologs and the related cyt c1 for inducible knockdown. Translational repression of cyt c and cyt c1 was lethal to parasites, which died from ETC dysfunction and impaired ubiquinone recycling. In contrast, cyt c-2 knockdown or knockout had little impact on blood-stage growth, indicating that parasites rely fully on the more conserved cyt c for ETC function. Biochemical and structural studies revealed that both cyt c and c-2 are hemylated by holocytochrome c synthase, but UV-vis absorbance and EPR spectra strongly suggest that cyt c-2 has an unusually open active site in which heme is stably coordinated by only a single axial amino acid ligand and can bind exogenous small molecules. These studies provide a direct dissection of cytochrome functions in the ETC of malaria parasites and identify a highly divergent Plasmodium cytochrome c with molecular adaptations that defy a conserved role in eukaryotic evolution.

Yeast Svf1 binds ceramides and contributes to sphingolipid metabolism at the ER cis-Golgi interface

Ceramides are essential precursors of complex sphingolipids and act as potent signaling molecules. Ceramides are synthesized in the endoplasmic reticulum (ER) and receive their head-groups in the Golgi apparatus, yielding complex sphingolipids (SPs). Transport of ceramides between the ER and the Golgi is executed by the essential ceramide transport protein (CERT) in mammalian cells. However, yeast cells lack a CERT homolog, and the mechanism of ER to Golgi ceramide transport remains largely elusive. Here, we identified a role for yeast Svf1 in ceramide transport between the ER and the Golgi. Svf1 is dynamically targeted to membranes via an N-terminal amphipathic helix (AH). Svf1 binds ceramide via a hydrophobic binding pocket that is located in between two lipocalin domains. We showed that Svf1 membrane-targeting is important to maintain flux of ceramides into complex SPs. Together, our results show that Svf1 is a ceramide binding protein that contributes to sphingolipid metabolism at Golgi compartments.

The proteomic landscape of genome-wide genetic perturbations

Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.

Constrained disorder principle-based variability is fundamental for biological processes: Beyond biological relativity and physiological regulatory networks

The constrained disorder principle (CDP) defines systems based on their degree of disorder bounded by dynamic boundaries. The principle explains stochasticity in living and non-living systems. Denis Noble described the importance of stochasticity in biology, emphasizing stochastic processes at molecular, cellular, and higher levels in organisms as having a role beyond simple noise. The CDP and Noble's theories (NT) claim that biological systems use stochasticity. This paper presents the CDP and NT, discussing common notions and differences between the two theories. The paper presents the CDP-based concept of taking the disorder beyond its role in nature to correct malfunctions of systems and improve the efficiency of biological systems. The use of CDP-based algorithms embedded in second-generation artificial intelligence platforms is described. In summary, noise is inherent to complex systems and has a functional role. The CDP provides the option of using noise to improve functionality.

Gene-by-environment interactions are pervasive among natural genetic variants

Gene-by-environment (GxE) interactions, in which a genetic variant's phenotypic effect is condition specific, are fundamental for understanding fitness landscapes and evolution but have been difficult to identify at the single-nucleotide level. Although many condition-specific quantitative trait loci (QTLs) have been mapped, these typically contain numerous inconsequential variants in linkage, precluding understanding of the causal GxE variants. Here, we introduce BARcoded Cas9 retron precise parallel editing via homology (CRISPEY-BAR), a high-throughput precision genome editing strategy, and use it to map GxE interactions of naturally occurring genetic polymorphisms impacting yeast growth. We identified hundreds of GxE variants within condition-specific QTLs, revealing unexpected genetic complexity. Moreover, we found that 93.7% of non-neutral natural variants within ergosterol biosynthesis pathway genes showed GxE interactions, including many impacting antifungal drug resistance through diverse molecular mechanisms. In sum, our results suggest an extremely complex, context-dependent fitness landscape characterized by pervasive GxE interactions while also demonstrating massively parallel genome editing as an effective means for investigating this complexity.

Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology

There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.

Identification of significant gene expression changes in multiple perturbation experiments using knockoffs

Large-scale multiple perturbation experiments have the potential to reveal a more detailed understanding of the molecular pathways that respond to genetic and environmental changes. A key question in these studies is which gene expression changes are important for the response to the perturbation. This problem is challenging because (i) the functional form of the nonlinear relationship between gene expression and the perturbation is unknown and (ii) identification of the most important genes is a high-dimensional variable selection problem. To deal with these challenges, we present here a method based on the model-X knockoffs framework and Deep Neural Networks to identify significant gene expression changes in multiple perturbation experiments. This approach makes no assumptions on the functional form of the dependence between the responses and the perturbations and it enjoys finite sample false discovery rate control for the selected set of important gene expression responses. We apply this approach to the Library of Integrated Network-Based Cellular Signature data sets which is a National Institutes of Health Common Fund program that catalogs how human cells globally respond to chemical, genetic and disease perturbations. We identified important genes whose expression is directly modulated in response to perturbation with anthracycline, vorinostat, trichostatin-a, geldanamycin and sirolimus. We compare the set of important genes that respond to these small molecules to identify co-responsive pathways. Identification of which genes respond to specific perturbation stressors can provide better understanding of the underlying mechanisms of disease and advance the identification of new drug targets.

Network expansion of genetic associations defines a pleiotropy map of human cell biology

Interacting proteins tend to have similar functions, influencing the same organismal traits. Interaction networks can be used to expand the list of candidate trait-associated genes from genome-wide association studies. Here, we performed network-based expansion of trait-associated genes for 1,002 human traits showing that this recovers known disease genes or drug targets. The similarity of network expansion scores identifies groups of traits likely to share an underlying genetic and biological process. We identified 73 pleiotropic gene modules linked to multiple traits, enriched in genes involved in processes such as protein ubiquitination and RNA processing. In contrast to gene deletion studies, pleiotropy as defined here captures specifically multicellular-related processes. We show examples of modules linked to human diseases enriched in genes with known pathogenic variants that can be used to map targets of approved drugs for repurposing. Finally, we illustrate the use of network expansion scores to study genes at inflammatory bowel disease genome-wide association study loci, and implicate inflammatory bowel disease-relevant genes with strong functional and genetic support.

Recovering false negatives in CRISPR fitness screens with JLOE

It is widely accepted that pooled library CRISPR knockout screens offer greater sensitivity and specificity than prior technologies in detecting genes whose disruption leads to fitness defects, a critical step in identifying candidate cancer targets. However, the assumption that CRISPR screens are saturating has been largely untested. Through integrated analysis of screen data in cancer cell lines generated by the Cancer Dependency Map, we show that a typical CRISPR screen has a ∼20% false negative rate, in addition to library-specific false negatives. Replicability falls sharply as gene expression decreases, while cancer subtype-specific genes within a tissue show distinct profiles compared to false negatives. Cumulative analyses across tissues improves our understanding of core essential genes and suggest only a small number of lineage-specific essential genes, enriched for transcription factors that define pathways of tissue differentiation. To recover false negatives, we introduce a method, Joint Log Odds of Essentiality (JLOE), which builds on our prior work with BAGEL to selectively rescue the false negatives without an increased false discovery rate.

A Genome-Wide Phenotypic Analysis of Saccharomyces cerevisiae’s Adaptive Response and Tolerance to Chitosan in Conditions Relevant for Winemaking

In the wine industry, the use of chitosan, a non-toxic biodegradable polysaccharide with antimicrobial properties, has been gaining interest with respect to envisaging the reduction in the use of sulfur dioxide (SO2). Although the mechanisms of toxicity of chitosan against fungal cells have been addressed before, most of the studies undertaken used other sources of chitosan and/or used conditions to solubilize the polymer that were not compatible with winemaking. Herein, the effect of a commercial formulation of chitosan approved for use in winemaking over the growth of the spoilage yeast species Dekkera anomala, Saccharomycodes ludwigii, Zygosaccharomyces bailii, and Pichia anomala was assessed. At the legally allowed concentration of 0.1 g/L, chitosan inhibited the growth of all spoilage yeasts, except for the tested Pichia anomala strains. Interestingly, the highly SO2-tolerant yeasts S. ludwigii and Z. bailii were highly susceptible to chitosan. The growth of commercial Saccharomyces cerevisiae was also impacted by chitosan, in a strain-dependent manner, albeit at higher concentrations. To dissect this differential inhibitory potential and gain further insight into the interaction of chitosan over fungal cells, we explored a chemogenomic analysis to identify all of the S. cerevisiae genes conferring protection against or increasing susceptibility to the commercial formulation of chitosan. Among the genes found to confer protection against chitosan, a high proportion was found to encode proteins required for the assembly and structuring of the cell wall, enzymes involved in the synthesis of plasma membrane lipids, and components of signaling pathways that respond to damages in the plasma membrane (e.g., the Rim101 pathway). The data obtained also suggest that the fungal ribosome and the vacuolar V-ATPase could be directly targeted by chitosan, since the deletion of genes encoding proteins required for the structure and function of these organelles was found to increase tolerance to chitosan. We also demonstrated, for the first time, that the deletion of ITR1, AGP2 and FPS1, encoding plasma membrane transporters, prominently increased the tolerance of S. cerevisiae to chitosan, suggesting that they can serve as carriers for chitosan. Besides providing new insights into the mode of action of chitosan against wine yeasts, this study adds relevant information for its rational use as a substitute/complementary preservative to SO2.

Direct Tests of Cytochrome Function in the Electron Transport Chain of Malaria Parasites

The mitochondrial electron transport chain (ETC) of Plasmodium malaria parasites is a major antimalarial drug target, but critical cytochrome functions remain unstudied and enigmatic. Parasites express two distinct cyt c homologs ( c and c -2) with unusually sparse sequence identity and uncertain fitness contributions. P. falciparum cyt c -2 is the most divergent eukaryotic cyt c homolog currently known and has sequence features predicted to be incompatible with canonical ETC function. We tagged both cyt c homologs and the related cyt c ₁ for inducible knockdown. Translational repression of cyt c and cyt c ₁ was lethal to parasites, which died from ETC dysfunction and impaired ubiquinone recycling. In contrast, cyt c -2 knockdown or knock-out had little impact on blood-stage growth, indicating that parasites rely fully on the more conserved cyt c for ETC function. Biochemical and structural studies revealed that both cyt c and c -2 are hemylated by holocytochrome c synthase, but UV-vis absorbance and EPR spectra strongly suggest that cyt c -2 has an unusually open active site in which heme is stably coordinated by only a single axial amino-acid ligand and can bind exogenous small molecules. These studies provide a direct dissection of cytochrome functions in the ETC of malaria parasites and identify a highly divergent Plasmodium cytochrome c with molecular adaptations that defy a conserved role in eukaryotic evolution.

SIGNIFICANCE STATEMENT

Mitochondria are critical organelles in eukaryotic cells that drive oxidative metabolism. The mitochondrion of Plasmodium malaria parasites is a major drug target that has many differences from human cells and remains poorly studied. One key difference from humans is that malaria parasites express two cytochrome c proteins that differ significantly from each other and play untested and uncertain roles in the mitochondrial electron transport chain (ETC). Our study revealed that one cyt c is essential for ETC function and parasite viability while the second, more divergent protein has unusual structural and biochemical properties and is not required for growth of blood-stage parasites. This work elucidates key biochemical properties and evolutionary differences in the mitochondrial ETC of malaria parasites.

A universal sequencing read interpreter

Massively parallel DNA sequencing has led to the rapid growth of highly multiplexed experiments in biology. These experiments produce unique sequencing results that require specific analysis pipelines to decode highly structured reads. However, no versatile framework that interprets sequencing reads to extract their encoded information for downstream biological analysis has been developed. Here, we report INTERSTELLAR (interpretation, scalable transformation, and emulation of large-scale sequencing reads) that decodes data values encoded in theoretically any type of sequencing read and translates them into sequencing reads of another structure of choice. We demonstrated that INTERSTELLAR successfully extracted information from a range of short- and long-read sequencing reads and translated those of single-cell (sc)RNA-seq, scATAC-seq, and spatial transcriptomics to be analyzed by different software tools that have been developed for conceptually the same types of experiments. INTERSTELLAR will greatly facilitate the development of sequencing-based experiments and sharing of data analysis pipelines.

Genome-wide signatures of adaptation to extreme environments in red algae

The high temperature, acidity, and heavy metal-rich environments associated with hot springs have a major impact on biological processes in resident cells. One group of photosynthetic eukaryotes, the Cyanidiophyceae (Rhodophyta), has successfully thrived in hot springs and associated sites worldwide for more than 1 billion years. Here, we analyze chromosome-level assemblies from three representative Cyanidiophyceae species to study environmental adaptation at the genomic level. We find that subtelomeric gene duplication of functional genes and loss of canonical eukaryotic traits played a major role in environmental adaptation, in addition to horizontal gene transfer events. Shared responses to environmental stress exist in Cyanidiales and Galdieriales, however, most of the adaptive genes (e.g., for arsenic detoxification) evolved independently in these lineages. Our results underline the power of local selection to shape eukaryotic genomes that may face vastly different stresses in adjacent, extreme microhabitats.

HAP1, a new revolutionary cell model for gene editing using CRISPR-Cas9

The use of next-generation sequencing (NGS) technologies has been instrumental in the characterization of the mutational landscape of complex human diseases like cancer. But despite the enormous rise in the identification of disease candidate genetic variants, their functionality is yet to be fully elucidated in order to have a clear implication in patient care. Haploid human cell models have become the tool of choice for functional gene studies, since they only contain one copy of the genome and can therefore show the unmasked phenotype of genetic variants. Over the past few years, the human near-haploid cell line HAP1 has widely been consolidated as one of the favorite cell line models for functional genetic studies. Its rapid turnover coupled with the fact that only one allele needs to be modified in order to express the subsequent desired phenotype has made this human cell line a valuable tool for gene editing by CRISPR-Cas9 technologies. This review examines the recent uses of the HAP1 cell line model in functional genetic studies and high-throughput genetic screens using the CRISPR-Cas9 system. It covers its use in an attempt to develop new and relevant disease models to further elucidate gene function, and create new ways to understand the genetic basis of human diseases. We will cover the advantages and potential of the use of CRISPR-Cas9 technology on HAP1 to easily and efficiently study the functional interpretation of gene function and human single-nucleotide genetic variants of unknown significance identified through NGS technologies, and its implications for changes in clinical practice and patient care.

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.

Inorganic sulfur fixation via a new homocysteine synthase allows yeast cells to cooperatively compensate for methionine auxotrophy

The assimilation, incorporation, and metabolism of sulfur is a fundamental process across all domains of life, yet how cells deal with varying sulfur availability is not well understood. We studied an unresolved conundrum of sulfur fixation in yeast, in which organosulfur auxotrophy caused by deletion of the homocysteine synthase Met17p is overcome when cells are inoculated at high cell density. In combining the use of self-establishing metabolically cooperating (SeMeCo) communities with proteomic, genetic, and biochemical approaches, we discovered an uncharacterized gene product YLL058Wp, herein named Hydrogen Sulfide Utilizing-1 (HSU1). Hsu1p acts as a homocysteine synthase and allows the cells to substitute for Met17p by reassimilating hydrosulfide ions leaked from met17Δ cells into O-acetyl-homoserine and forming homocysteine. Our results show that cells can cooperate to achieve sulfur fixation, indicating that the collective properties of microbial communities facilitate their basic metabolic capacity to overcome sulfur limitation.

Cytotoxicity of Extracts from Petiveria alliacea Leaves on Yeast

Petiveria alliacea L. is a plant used in traditional medicine harboring pharmacological properties with anti-inflammatory, antinociceptive, hypoglycemiant and anesthetic activities. This study assessed the potential cytotoxic, genotoxic and mutagenic effects of ethanolic extract of P. alliacea on Saccharomyces cerevisiae strains. S. cerevisiae FF18733 (wild type) and CD138 (ogg1) strains were exposed to fractioned ethanolic extracts of P. alliacea in different concentrations. Three experimental assays were performed: cellular inactivation, mutagenesis (canavanine resistance system) and loss of mitochondrial function (petites colonies). The chemical analyses revealed a rich extract with phenolic compounds such as protocatechuic acid, cinnamic and catechin epicatechin. A decreased cell viability in wild-type and ogg1 strains was demonstrated. All fractions of the extract exerted a mutagenic effect on the ogg1 strain. Only ethyl acetate and n-butanol fractions increased the rate of petites colonies in the ogg1 strain, but not in the wild-type strain. The results indicate that fractions of mid-polarity of the ethanolic extract, at the studied concentrations, can induce mutagenicity mediated by oxidative lesions in the mitochondrial and genomic genomes of the ogg1-deficient S. cerevisiae strain. These findings indicate that the lesions caused by the fractions of P. alliacea ethanolic extract can be mediated by reactive oxygen species and can reach multiple molecular targets to exert their toxicity.

AIBP Regulates Metabolism of Ketone and Lipids but Not Mitochondrial Respiration

Accumulating evidence indicates that the APOA1 binding protein (AIBP)-a secreted protein-plays a profound role in lipid metabolism. Interestingly, AIBP also functions as an NAD(P)H-hydrate epimerase to catalyze the interconversion of NAD(P)H hydrate [NAD(P)HX] epimers and is renamed as NAXE. Thus, we call it NAXE hereafter. We investigated its role in NAD(P)H-involved metabolism in murine cardiomyocytes, focusing on the metabolism of hexose, lipids, and amino acids as well as mitochondrial redox function. Unbiased metabolite profiling of cardiac tissue shows that NAXE knockout markedly upregulates the ketone body 3-hydroxybutyric acid (3-HB) and increases or trends increasing lipid-associated metabolites cholesterol, α-linolenic acid and deoxycholic acid. Paralleling greater ketone levels, ChemRICH analysis of the NAXE-regulated metabolites shows reduced abundance of hexose despite similar glucose levels in control and NAXE-deficient blood. NAXE knockout reduces cardiac lactic acid but has no effect on the content of other NAD(P)H-regulated metabolites, including those associated with glucose metabolism, the pentose phosphate pathway, or Krebs cycle flux. Although NAXE is present in mitochondria, it has no apparent effect on mitochondrial oxidative phosphorylation. Instead, we detected more metabolites that can potentially improve cardiac function (3-HB, adenosine, and α-linolenic acid) in the Naxe^-/- heart; these mice also perform better in aerobic exercise. Our data reveal a new role of NAXE in cardiac ketone and lipid metabolism.

The NPR/Hal family of protein kinases in yeasts: biological role, phylogeny and regulation under environmental challenges

Protein phosphorylation is the most common and versatile post-translational modification occurring in eukaryotes. In yeast, protein phosphorylation is fundamental for maintaining cell growth and adapting to sudden changes in environmental conditions by regulating cellular processes and activating signal transduction pathways. Protein kinases catalyze the reversible addition of phosphate groups to target proteins, thereby regulating their activity. In Saccharomyces cerevisiae, kinases are classified into six major groups based on structural and functional similarities. The NPR/Hal family of kinases comprises nine fungal-specific kinases that, due to lack of similarity with the remaining kinases, were classified to the “Other” group. These kinases are primarily implicated in regulating fundamental cellular processes such as maintaining ion homeostasis and controlling nutrient transporters’ concentration at the plasma membrane. Despite their biological relevance, these kinases remain poorly characterized and explored. This review provides an overview of the information available regarding each of the kinases from the NPR/Hal family, including their known biological functions, mechanisms of regulation, and integration in signaling pathways in S. cerevisiae. Information gathered for non-Saccharomyces species of biotechnological or clinical relevance is also included.

Antifungal discovery

Fungi have a profound impact on human health, leading to billions of infections and millions of deaths worldwide each year. Exacerbating the public health burden is the continued emergence of drug-resistant fungal pathogens coupled with a dearth of treatment options to combat serious infections. Despite this health threat, scientific advances in chemistry, genetics, and biochemistry methodologies have enabled novel antifungal compounds to be discovered. Here, we describe current approaches for the discovery and characterization of novel antifungals, focusing on the identification of novel chemical matter and elucidation of the cellular target of bioactive compounds, followed by a review of the most promising emerging therapies in the antifungal-development pipeline.

Genomic Approaches to Antifungal Drug Target Identification and Validation

The last several decades have witnessed a surge in drug-resistant fungal infections that pose a serious threat to human health. While there is a limited arsenal of drugs that can be used to treat systemic infections, scientific advances have provided renewed optimism for the discovery of novel antifungals. The development of chemical-genomic assays using Saccharomyces cerevisiae has provided powerful methods to identify the mechanism of action of molecules in a living cell. Advances in molecular biology techniques have enabled complementary assays to be developed in fungal pathogens, including Candida albicans and Cryptococcus neoformans. These approaches enable the identification of target genes for drug candidates, as well as genes involved in buffering drug target pathways. Here, we examine yeast chemical-genomic assays and highlight how such resources can be utilized to predict the mechanisms of action of compounds, to study virulence attributes of diverse fungal pathogens, and to bolster the antifungal pipeline.

A Simple Evolutionary Model of Genetic Robustness After Gene Duplication

When a dispensable gene is duplicated (referred to the ancestral dispensability denoted by O⁺), genetic buffering and duplicate compensation together maintain the duplicate redundancy, whereas duplicate compensation is the only mechanism when an essential gene is duplicated (referred to the ancestral essentiality denoted by O^-). To investigate these evolutionary scenarios of genetic robustness, I formulated a simple mixture model for analyzing duplicate pairs with one of the following states: double dispensable (DD), semi-dispensable (one dispensable one essential, DE), or double essential (EE). This model was applied to the yeast duplicate pairs from a whole-genome duplication (WGD) occurred about 100 million years ago (mya), and the mouse duplicate pairs from a WGD occurred about more than 500 mya. Both case studies revealed that the proportion of essentiality for those duplicates with ancestral essentiality [P_E(O^-)] was much higher than that for those with ancestral dispensability [P_E(O⁺)]. While it was negligible in the yeast duplicate pairs, P_E(O⁺) (about 20%) was shown statistically significant in the mouse duplicate pairs. These findings, together, support the hypothesis that both sub-functionalization and neo-functionalization may play some roles after gene duplication, though the former may be much faster than the later.

Comparative chemical genomic profiling across plant-based hydrolysate toxins reveals widespread antagonism in fitness contributions

The budding yeast Saccharomyces cerevisiae has been used extensively in fermentative industrial processes, including biofuel production from sustainable plant-based hydrolysates. Myriad toxins and stressors found in hydrolysates inhibit microbial metabolism and product formation. Overcoming these stresses requires mitigation strategies that include strain engineering. To identify shared and divergent mechanisms of toxicity and to implicate gene targets for genetic engineering, we used a chemical genomic approach to study fitness effects across a library of S. cerevisiae deletion mutants cultured anaerobically in dozens of individual compounds found in different types of hydrolysates. Relationships in chemical genomic profiles identified classes of toxins that provoked similar cellular responses, spanning inhibitor relationships that were not expected from chemical classification. Our results also revealed widespread antagonistic effects across inhibitors, such that the same gene deletions were beneficial for surviving some toxins but detrimental for others. This work presents a rich dataset relating gene function to chemical compounds, which both expands our understanding of plant-based hydrolysates and provides a useful resource to identify engineering targets.

Genome-wide identification of resistance genes and transcriptome regulation in yeast to accommodate ammonium toxicity

Background

Ammonium is an important raw material for biomolecules and life activities, and the toxicity of ammonium is also an important ecological and agricultural issue. Ammonium toxicity in yeast has only recently been discovered, and information on its mechanism is limited. In recent years, environmental pollution caused by nitrogen-containing wastewater has been increasing. In addition, the use of yeast in bioreactors to produce nitrogen-containing compounds has been developed. Therefore, research on resistance mechanisms that allow yeast to grow under conditions of high concentrations of ammonium has become more and more important.

Results

To further understand the resistance mechanism of yeast to grow under high concentration of ammonium, we used NH₄Cl to screen a yeast non-essential gene-deletion library. We identified 61 NH₄Cl-sensitive deletion mutants from approximately 4200 mutants in the library, then 34 of them were confirmed by drop test analysis. Enrichment analysis of these 34 genes showed that biosynthesis metabolism, mitophagy, MAPK signaling, and other pathways may play important roles in NH₄Cl resistance. Transcriptome analysis under NH₄Cl stress revealed 451 significantly upregulated genes and 835 significantly downregulated genes. The genes are mainly enriched in: nitrogen compound metabolic process, cell wall, MAPK signaling pathway, mitophagy, and glycine, serine and threonine metabolism.

Conclusions

Our results present a broad view of biological pathways involved in the response to NH₄Cl stress, and thereby advance our understanding of the resistance genes and cellular transcriptional regulation under high concentration of ammonium.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08742-y.

C16orf72/HAPSTR1 is a molecular rheostat in an integrated network of stress response pathways

All cells contain specialized signaling pathways that enable adaptation to specific molecular stressors. Yet, whether these pathways are centrally regulated in complex physiological stress states remains unclear. Using genome-scale fitness screening data, we quantified the stress phenotype of 739 cancer cell lines, each representing a unique combination of intrinsic tumor stresses. Integrating dependency and stress perturbation transcriptomic data, we illuminated a network of genes with vital functions spanning diverse stress contexts. Analyses for central regulators of this network nominated C16orf72/HAPSTR1, an evolutionarily ancient gene critical for the fitness of cells reliant on multiple stress response pathways. We found that HAPSTR1 plays a pleiotropic role in cellular stress signaling, functioning to titrate various specialized cell-autonomous and paracrine stress response programs. This function, while dispensable to unstressed cells and nematodes, is essential for resilience in the presence of stressors ranging from DNA damage to starvation and proteotoxicity. Mechanistically, diverse stresses induce HAPSTR1, which encodes a protein expressed as two equally abundant isoforms. Perfectly conserved residues in a domain shared between HAPSTR1 isoforms mediate oligomerization and binding to the ubiquitin ligase HUWE1. We show that HUWE1 is a required cofactor for HAPSTR1 to control stress signaling and that, in turn, HUWE1 feeds back to ubiquitinate and destabilize HAPSTR1. Altogether, we propose that HAPSTR1 is a central rheostat in a network of pathways responsible for cellular adaptability, the modulation of which may have broad utility in human disease.

Recentering neuroscience on behavior: The interface between brain and environment is a privileged level of control of neural activity

Despite the huge and constant progress in the molecular and cellular neuroscience fields, our capability to understand brain alterations and treat mental illness is still limited. Therefore, a paradigm shift able to overcome such limitation is warranted. Behavior and the associated mental states are the interface between the central nervous system and the living environment. Since, in any system, the interface is a key regulator of system organization, behavior is proposed here as a unique and privileged level of control and orchestration of brain structure and activity. This view has relevant scientific and clinical implications. First, the study of behavior represents a singular starting point for the investigation of neural activity in an integrated and comprehensive fashion. Second, behavioral changes, accomplished through psychotherapy or environmental interventions, are expected to have the highest impact to specifically reorganize the complexity of the human mind and thus achieve a solid and long-lasting improvement in mental health.

Humanized yeast to model human biology, disease and evolution

For decades, budding yeast, a single-cellular eukaryote, has provided remarkable insights into human biology. Yeast and humans share several thousand genes despite morphological and cellular differences and over a billion years of separate evolution. These genes encode critical cellular processes, the failure of which in humans results in disease. Although recent developments in genome engineering of mammalian cells permit genetic assays in human cell lines, there is still a need to develop biological reagents to study human disease variants in a high-throughput manner. Many protein-coding human genes can successfully substitute for their yeast equivalents and sustain yeast growth, thus opening up doors for developing direct assays of human gene function in a tractable system referred to as 'humanized yeast'. Humanized yeast permits the discovery of new human biology by measuring human protein activity in a simplified organismal context. This Review summarizes recent developments showing how humanized yeast can directly assay human gene function and explore variant effects at scale. Thus, by extending the 'awesome power of yeast genetics' to study human biology, humanizing yeast reinforces the high relevance of evolutionarily distant model organisms to explore human gene evolution, function and disease.

From systems to structure - using genetic data to model protein structures

Understanding the effects of genetic variation is a fundamental problem in biology that requires methods to analyse both physical and functional consequences of sequence changes at systems-wide and mechanistic scales. To achieve a systems view, protein interaction networks map which proteins physically interact, while genetic interaction networks inform on the phenotypic consequences of perturbing these protein interactions. Until recently, understanding the molecular mechanisms that underlie these interactions often required biophysical methods to determine the structures of the proteins involved. The past decade has seen the emergence of new approaches based on coevolution, deep mutational scanning and genome-scale genetic or chemical-genetic interaction mapping that enable modelling of the structures of individual proteins or protein complexes. Here, we review the emerging use of large-scale genetic datasets and deep learning approaches to model protein structures and their interactions, and discuss the integration of structural data from different sources.

CRISPR/Cas9 and genetic screens in malaria parasites: small genomes, big impact

The ∼30 Mb genomes of the Plasmodium parasites that cause malaria each encode ∼5000 genes, but the functions of the majority remain unknown. This is due to a paucity of functional annotation from sequence homology, which is compounded by low genetic tractability compared with many model organisms. In recent years technical breakthroughs have made forward and reverse genome-scale screens in Plasmodium possible. Furthermore, the adaptation of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-Associated protein 9 (CRISPR/Cas9) technology has dramatically improved gene editing efficiency at the single gene level. Here, we review the arrival of genetic screens in malaria parasites to analyse parasite gene function at a genome-scale and their impact on understanding parasite biology. CRISPR/Cas9 screens, which have revolutionised human and model organism research, have not yet been implemented in malaria parasites due to the need for more complex CRISPR/Cas9 gene targeting vector libraries. We therefore introduce the reader to CRISPR-based screens in the related apicomplexan Toxoplasma gondii and discuss how these approaches could be adapted to develop CRISPR/Cas9 based genome-scale genetic screens in malaria parasites. Moreover, since more than half of Plasmodium genes are required for normal asexual blood-stage reproduction, and cannot be targeted using knockout methods, we discuss how CRISPR/Cas9 could be used to scale up conditional gene knockdown approaches to systematically assign function to essential genes.

Gradients in gene essentiality reshape antibacterial research

Essential genes encode the processes that are necessary for life. Until recently, commonly applied binary classifications left no space between essential and non-essential genes. In this review, we frame bacterial gene essentiality in the context of genetic networks. We explore how the quantitative properties of gene essentiality are influenced by the nature of the encoded process, environmental conditions and genetic background, including a strain's distinct evolutionary history. The covered topics have important consequences for antibacterials, which inhibit essential processes. We argue that the quantitative properties of essentiality can thus be used to prioritize antibacterial cellular targets and desired spectrum of activity in specific infection settings. We summarize our points with a case study on the core essential genome of the cystic fibrosis pathobiome and highlight avenues for targeted antibacterial development.

Systematic characterization of gene function in the photosynthetic alga Chlamydomonas reinhardtii

Most genes in photosynthetic organisms remain functionally uncharacterized. Here, using a barcoded mutant library of the model eukaryotic alga Chlamydomonas reinhardtii, we determined the phenotypes of more than 58,000 mutants under more than 121 different environmental growth conditions and chemical treatments. A total of 59% of genes are represented by at least one mutant that showed a phenotype, providing clues to the functions of thousands of genes. Mutant phenotypic profiles place uncharacterized genes into functional pathways such as DNA repair, photosynthesis, the CO₂-concentrating mechanism and ciliogenesis. We illustrate the value of this resource by validating phenotypes and gene functions, including three new components of an actin cytoskeleton defense pathway. The data also inform phenotype discovery in land plants; mutants in Arabidopsis thaliana genes exhibit phenotypes similar to those we observed in their Chlamydomonas homologs. We anticipate that this resource will guide the functional characterization of genes across the tree of life.

Systematic phenotyping of 58,101 mutants of the model eukaryotic alga Chlamydomonas reinhardtii under 121 environmental and chemical stress conditions provides a large resource for characterizing gene function.

Genome-Wide Identification of Cellular Pathways and Key Genes That Respond to Sodium Bicarbonate Stress in Saccharomyces cerevisiae

Sodium bicarbonate (NaHCO₃) is an important inorganic salt. It is not only widely used in industrial production and daily life, but is also the main stress in alkaline saline soil. NaHCO₃ has a strong ability to inhibit the growth of fungi in both natural environment and daily application. However, the mechanism by which fungi respond to NaHCO₃ stress is not fully understood. To further clarify the toxic mechanisms of NaHCO₃ stress and identify the specific cellular genes and pathways involved in NaHCO₃ resistance, we performed genome-wide screening with NaHCO₃ using a Saccharomyces cerevisiae deletion mutant library. A total of 33 deletion mutants with NaHCO₃ sensitivity were identified. Compared with wild-type strains, these mutants had significant growth defects in the medium containing NaHCO₃. Bioinformatics analysis found that the corresponding genes of these mutants are mainly enriched in the cell cycle, mitophagy, cell wall integrity, and signaling pathways. Further study using transcriptomic analysis showed that 309 upregulated and 233 downregulated genes were only responded to NaHCO₃ stress, when compared with yeast transcriptomic data under alkaline and saline stress. Upregulated genes were mainly concentrated in amino acid metabolism, steroid biosynthesis, and cell wall, while downregulated genes were enriched in various cellular metabolisms. In summary, we have identified the cellular pathways and key genes that respond to NaHCO₃ stress in the whole genome, providing resource and direction for understanding NaHCO₃ toxicity and cellular resistance mechanisms.