Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis

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.

Thanksgiving to Yeast, the HMGB Proteins History from Yeast to Cancer

Yeasts have been a part of human life since ancient times in the fermentation of many natural products used for food. In addition, in the 20th century, they became powerful tools to elucidate the functions of eukaryotic cells as soon as the techniques of molecular biology developed. Our molecular understandings of metabolism, cellular transport, DNA repair, gene expression and regulation, and the cell division cycle have all been obtained through biochemistry and genetic analysis using different yeasts. In this review, we summarize the role that yeasts have had in biological discoveries, the use of yeasts as biological tools, as well as past and on-going research projects on HMGB proteins along the way from yeast to cancer.

Mapping mitonuclear epistasis using a novel recombinant yeast population

Genetic variation in mitochondrial and nuclear genomes can perturb mitonuclear interactions and lead to phenotypic differences between individuals and populations. Despite their importance to most complex traits, it has been difficult to identify the interacting mitonuclear loci. Here, we present a novel advanced intercrossed population of Saccharomyces cerevisiae yeasts, called the Mitonuclear Recombinant Collection (MNRC), designed explicitly for detecting mitonuclear loci contributing to complex traits. For validation, we focused on mapping genes that contribute to the spontaneous loss of mitochondrial DNA (mtDNA) that leads to the petite phenotype in yeast. We found that rates of petite formation in natural populations are variable and influenced by genetic variation in nuclear DNA, mtDNA and mitonuclear interactions. We mapped nuclear and mitonuclear alleles contributing to mtDNA stability using the MNRC by integrating a term for mitonuclear epistasis into a genome-wide association model. We found that the associated mitonuclear loci play roles in mitotic growth most likely responding to retrograde signals from mitochondria, while the associated nuclear loci with main effects are involved in genome replication. We observed a positive correlation between growth rates and petite frequencies, suggesting a fitness tradeoff between mitotic growth and mtDNA stability. We also found that mtDNA stability was correlated with a mobile mitochondrial GC-cluster that is present in certain populations of yeast and that selection for nuclear alleles that stabilize mtDNA may be rapidly occurring. The MNRC provides a powerful tool for identifying mitonuclear interacting loci that will help us to better understand genotype-phenotype relationships and coevolutionary trajectories.

GenoPipe: identifying the genotype of origin within (epi)genomic datasets

Confidence in experimental results is critical for discovery. As the scale of data generation in genomics has grown exponentially, experimental error has likely kept pace despite the best efforts of many laboratories. Technical mistakes can and do occur at nearly every stage of a genomics assay (i.e., cell line contamination, reagent swapping, tube mislabelling, etc.) and are often difficult to identify post-execution. However, the DNA sequenced in genomic experiments contains certain markers (e.g., indels) encoded within and can often be ascertained forensically from experimental datasets. We developed the Genotype validation Pipeline (GenoPipe), a suite of heuristic tools that operate together directly on raw and aligned sequencing data from individual high-throughput sequencing experiments to characterize the underlying genome of the source material. We demonstrate how GenoPipe validates and rescues erroneously annotated experiments by identifying unique markers inherent to an organism’s genome (i.e., epitope insertions, gene deletions, and SNPs).

The ENA1 Na+-ATPase Gene Is Regulated by the SPS Sensing Pathway and the Stp1/Stp2 Transcription Factors

The Saccharomyces cerevisiae ENA1 gene, encoding a Na+-ATPase, responds transcriptionally to the alkalinization of the medium by means of a network of signals that involves the Rim101, the Snf1 and PKA kinases, and the calcineurin/Crz1 pathways. We show here that the ENA1 promoter also contains a consensus sequence, located at nt -553/-544, for the Stp1/2 transcription factors, the downstream components of the amino acid sensing SPS pathway. Mutation of this sequence or deletion of either STP1 or STP2 decreases the activity of a reporter containing this region in response to alkalinization as well as to changes in the amino acid composition in the medium. Expression driven from the entire ENA1 promoter was affected with similar potency by the deletion of PTR3, SSY5, or simultaneous deletion of STP1 and STP2 when cells were exposed to alkaline pH or moderate salt stress. However, it was not altered by the deletion of SSY1, encoding the amino acid sensor. In fact, functional mapping of the ENA1 promoter reveals a region spanning from nt -742 to -577 that enhances transcription, specifically in the absence of Ssy1. We also found that the basal and alkaline pH-induced expression from the HXT2, TRX2, and, particularly, SIT1 promoters was notably decreased in an stp1 stp2 deletion mutant, whereas the PHO84 and PHO89 gene reporters were unaffected. Our findings add a further layer of complexity to the regulation of ENA1 and suggest that the SPS pathway might participate in the regulation of a subset of alkali-inducible genes.

Compensatory gene expression potentially rescues impaired brain development in Kit mutant mice

While loss-of-function mutations in the murine dominant white spotting/Kit (W) locus affect a diverse array of cell lineages and organs, the brain, organ with the highest expression show the least number of defective phenotypes. We performed transcriptome analysis of the brains of Kit^W embryos and found prominent gene expression changes specifically in the E12.5 Kit^W/W homozygous mutant. Although other potentially effective changes in gene expression were observed, uniform downregulation of ribosomal protein genes and oxidative phosphorylation pathway genes specifically observed in the E12.5 brain may comprise a genetic compensation system exerting protective metabolic effects against the deleterious effect of Kit^W/W mutation in the developing brain.

Genetic requirements for repair of lesions caused by single genomic ribonucleotides in S phase

Single ribonucleoside monophosphates (rNMPs) are transiently present in eukaryotic genomes. The RNase H2-dependent ribonucleotide excision repair (RER) pathway ensures error-free rNMP removal. In some pathological conditions, rNMP removal is impaired. If these rNMPs hydrolyze during, or prior to, S phase, toxic single-ended double-strand breaks (seDSBs) can occur upon an encounter with replication forks. How such rNMP-derived seDSB lesions are repaired is unclear. We expressed a cell cycle phase restricted allele of RNase H2 to nick at rNMPs in S phase and study their repair. Although Top1 is dispensable, the RAD52 epistasis group and Rtt101^Mms1-Mms22 dependent ubiquitylation of histone H3 become essential for rNMP-derived lesion tolerance. Consistently, loss of Rtt101^Mms1-Mms22 combined with RNase H2 dysfunction leads to compromised cellular fitness. We refer to this repair pathway as nick lesion repair (NLR). The NLR genetic network may have important implications in the context of human pathologies.

Point mutations of homologs as an adaptive solution to the gene loss

Gene loss is common and influences genome evolution trajectories. Multiple adaptive strategies to compensate for gene loss have been observed, including copy number gain of paralogous genes and mutations in genes of the same pathway. By using the Ubl-specific protease 2 (ULP2) eviction model, we identify compensatory mutations in the homologous gene ULP1 by laboratory evolution and find that these mutations are capable of rescuing defects caused by the loss of ULP2. Furthermore, bioinformatics analysis of genomes of yeast gene knockout library and natural yeast isolate datasets suggests that point mutations of a homologous gene might be an additional mechanism to compensate gene loss.

New Features Surrounding the Cdc42-Ste20 Module that Regulates MAP Kinase Signaling in Yeast

Mitogen-activated protein kinase (MAPK) pathways regulate multiple cellular responses, including the response to stress and cell differentiation, and are highly conserved across eukaryotes from yeast to humans. In yeast, the canonical activation of several MAPK pathways includes the interaction of the small GTPase Cdc42p with the p21-activated kinase (PAK) Ste20p. We recently found that the active conformation of Cdc42p is regulated by turnover, which impacts the activity of the pathway that regulates filamentous growth (fMAPK). Here, we show that Ste20p is turned over by the 26S proteasome. Ste20p was stabilized when bound to Cdc42p, presumably to sustain MAPK pathway signaling. Ste20p is a major conduit by which signals flow through the fMAPK pathway; however, by genetic approaches we also identified a Ste20p-independent branch of the fMAPK pathway. Ste20p-dependent signaling required the 14-3-3 proteins, Bmh1p and Bmh2p, while Ste20p-independent signaling required the fMAPK pathway adaptor and Cdc42p-interacting protein, Bem4p. Ste20p-independent signaling was inhibited by one of the GTPase-activating proteins for Cdc42p in the fMAPK pathway, Rga1p, which also dampened basal but not active fMAPK pathway activity. Finally, the polarity adaptor and Cdc42p-interacting protein, Bem1p, which also regulates the fMAPK pathway, interacts with the tetra-span protein Sho1p, connecting a sensor at the plasma membrane to a protein that regulates the GTPase module. Collectively, these data reveal new regulatory features surrounding a Rho-PAK module that may extend to other pathways that control cell differentiation.

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.

Unravelling metabolic cross-feeding in a yeast-bacteria community using 13 C-based proteomics

Cross-feeding is fundamental to the diversity and function of microbial communities. However, identification of cross-fed metabolites is often challenging due to the universality of metabolic and biosynthetic intermediates. Here, we use ¹³ C isotope tracing in peptides to elucidate cross-fed metabolites in co-cultures of Saccharomyces cerevisiae and Lactococcus lactis. The community was grown on lactose as the main carbon source with either glucose or galactose fraction of the molecule labelled with ¹³ C. Data analysis allowing for the possible mass-shifts yielded hundreds of peptides for which we could assign both species identity and labelling degree. The labelling pattern showed that the yeast utilized galactose and, to a lesser extent, lactic acid shared by L. lactis as carbon sources. While the yeast provided essential amino acids to the bacterium as expected, the data also uncovered a complex pattern of amino acid exchange. The identity of the cross-fed metabolites was further supported by metabolite labelling in the co-culture supernatant, and by diminished fitness of a galactose-negative yeast mutant in the community. Together, our results demonstrate the utility of ¹³ C-based proteomics for uncovering microbial interactions.

Methionine Sulfoxide Reductases Suppress the Formation of the [PSI+] Prion and Protein Aggregation in Yeast

Prions are self-propagating, misfolded forms of proteins associated with various neurodegenerative diseases in mammals and heritable traits in yeast. How prions form spontaneously into infectious amyloid-like structures without underlying genetic changes is poorly understood. Previous studies have suggested that methionine oxidation may underlie the switch from a soluble protein to the prion form. In this current study, we have examined the role of methionine sulfoxide reductases (MXRs) in protecting against de novo formation of the yeast [PSI⁺] prion, which is the amyloid form of the Sup35 translation termination factor. We show that [PSI⁺] formation is increased during normal and oxidative stress conditions in mutants lacking either one of the yeast MXRs (Mxr1, Mxr2), which protect against methionine oxidation by reducing the two epimers of methionine-S-sulfoxide. We have identified a methionine residue (Met124) in Sup35 that is important for prion formation, confirming that direct Sup35 oxidation causes [PSI⁺] prion formation. [PSI⁺] formation was less pronounced in mutants simultaneously lacking both MXR isoenzymes, and we show that the morphology and biophysical properties of protein aggregates are altered in this mutant. Taken together, our data indicate that methionine oxidation triggers spontaneous [PSI⁺] prion formation, which can be alleviated by methionine sulfoxide reductases.

Disruption of phosphate metabolism and sterol transport-related genes conferring yeast resistance to vanillin and rapid ethanol production

Vanillin is a potent growth-inhibiting factor in Saccharomyces cerevisiae during lignocellulose biorefineries. Here, a haploid gene-deletion library was screened to search for vanillin-tolerant mutants and explain the possible tolerance mechanisms. Twenty-two deletion mutants were identified. The deleted genes in these mutants were involved in phosphate and inositol polyphosphate metabolism and intracellular sterol transport. Activation of the phosphate signaling pathway is not conducive to yeast against the pressure of vanillin. Furthermore, the findings indicate the role of inositol polyphosphates in altering vanillin tolerance by regulating phosphate metabolism. Meanwhile, reducing the transport of sterols from the plasma membrane enhanced tolerance to vanillin. In the presence of vanillin, the representative yeast deletions, pho84Δ and lam3Δ, showed good growth performance and promoted rapid ethanol production. Overall, this study identifies robust yeast strain alternatives for ethanol fermentation of cellulose and provides guidance for further genomic reconstruction of yeast strains.

Ginsenoside Rg1 Delays Chronological Aging in a Yeast Model via CDC19- and SDH2-Mediated Cellular Metabolism

Ginsenosides, active substances in Panax ginseng C. A. Meyer (ginseng), extend lifespan in multiple species, ameliorate age-associated damage, and limit functional decline in multiple tissues. However, their active components and their molecular mechanisms are largely unknown. Here, ginsenoside Rg1 (Rg1) promoted longevity in Saccharomyces cerevisiae. Treatment with Rg1 decreased aging-mediated surface wrinkling, enhanced stress resistance, decreased reactive oxygen species' production and apoptosis, improved antioxidant enzyme activity, and decreased the aging rate. Proteomic analysis indicated that Rg1 delays S. cerevisiae senescence by regulating metabolic homeostasis. Protein-protein interaction networks based on differential protein expression indicated that CDC19, a homologue of pyruvate kinase, and SDH2, the succinate dehydrogenase iron-sulfur protein subunit, might be the effector proteins involved in the regulation by Rg1. Further experiments confirmed that Rg1 improved specific parameters of mitochondrial bioenergetics and core enzymes in the glycolytic pathway. Mutant strains were constructed that demonstrated the relationships between metabolic homeostasis and the predicted target proteins of Rg1. Rg1 could be used in new treatments for slowing the aging process. Our results also provide a useful dataset for further investigations of the mechanisms of ginseng in aging.

Reduced sphingolipid biosynthesis modulates proteostasis networks to enhance longevity

As the elderly population increases, chronic, age-associated diseases are challenging healthcare systems around the world. Nutrient limitation is well known to slow the aging process and improve health. Regrettably, practicing nutrient restriction to improve health is unachievable for most people. Alternatively, pharmacological strategies are being pursued including myriocin which increases lifespan in budding yeast. Myriocin impairs sphingolipid synthesis, resulting in lowered amino acid pools which promote entry into a quiescent, long-lived state. Here we present transcriptomic data during the first 6 hours of drug treatment that improves our mechanistic understanding of the cellular response to myriocin and reveals a new role for ubiquitin in longevity. Previously we found that the methionine transporter Mup1 traffics to the plasma membrane normally in myriocin-treated cells but is not active and undergoes endocytic clearance. We now show that UBI4, a gene encoding stressed-induced ubiquitin, is vital for myriocin-enhanced lifespan. Furthermore, we show that Mup1 fused to a deubiquitinase domain impairs myriocin-enhanced longevity. Broader effects of myriocin treatment on ubiquitination are indicated by our finding of a significant increase in K63-linked ubiquitin polymers following myriocin treatment. Although proteostasis is broadly accepted as a pillar of aging, our finding that ubiquitination of an amino acid transporter promotes longevity in myriocin-treated cells is novel. Addressing the role of ubiquitination/deubiquitination in longevity has the potential to reveal new strategies and targets for promoting healthy aging.

SWR1 chromatin remodeling complex prevents mitotic slippage during spindle position checkpoint arrest

Faithful chromosome segregation in budding yeast requires correct positioning of the mitotic spindle along the mother to daughter cell polarity axis. When the anaphase spindle is not correctly positioned, a surveillance mechanism, named as the spindle position checkpoint (SPOC), prevents the progression out of mitosis until correct spindle positioning is achieved. How SPOC works on a molecular level is not well understood. Here we performed a genome-wide genetic screen to search for components required for SPOC. We identified the SWR1 chromatin-remodeling complex (SWR1-C) among several novel factors that are essential for SPOC integrity. Cells lacking SWR1-C were able to activate SPOC upon spindle misorientation but underwent mitotic slippage upon prolonged SPOC arrest. This mitotic slippage required the Cdc14-early anaphase release pathway and other factors including the SAGA (Spt-Ada-Gcn5 acetyltransferase) histone acetyltransferase complex, proteasome components and the mitotic cyclin-dependent kinase inhibitor Sic1. Together, our data establish a novel link between SWR1-C chromatin remodeling and robust checkpoint arrest in late anaphase.

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.

Comparative analysis of gene ontology-based semantic similarity measurements for the application of identifying essential proteins

Identifying key proteins from protein-protein interaction (PPI) networks is one of the most fundamental and important tasks for computational biologists. However, the protein interactions obtained by high-throughput technology are characterized by a high false positive rate, which severely hinders the prediction accuracy of the current computational methods. In this paper, we propose a novel strategy to identify key proteins by constructing reliable PPI networks. Five Gene Ontology (GO)-based semantic similarity measurements (Jiang, Lin, Rel, Resnik, and Wang) are used to calculate the confidence scores for protein pairs under three annotation terms (Molecular function (MF), Biological process (BP), and Cellular component (CC)). The protein pairs with low similarity values are assumed to be low-confidence links, and the refined PPI networks are constructed by filtering the low-confidence links. Six topology-based centrality methods (the BC, DC, EC, NC, SC, and aveNC) are applied to test the performance of the measurements under the original network and refined network. We systematically compare the performance of the five semantic similarity metrics with the three GO annotation terms on four benchmark datasets, and the simulation results show that the performance of these centrality methods under refined PPI networks is relatively better than that under the original networks. Resnik with a BP annotation term performs best among all five metrics with the three annotation terms. These findings suggest the importance of semantic similarity metrics in measuring the reliability of the links between proteins and highlight the Resnik metric with the BP annotation term as a favourable choice.

MM-CCNB: Essential protein prediction using MAX-MIN strategies and compartment of common neighboring approach

BACKGROUND AND OBJECTIVE

Proteins are indispensable for the flow of the life of living organisms. Protein pairs in interaction exhibit more functional activities than individuals. These activities have been considered an essential measure in predicting their essentiality. Neighborhood approaches have been used frequently in the prediction of essentiality scores. All paired neighbors of the essential proteins are nominated for the suitable candidate seeds for prediction. Still now Jaccard's coefficient is limited to predicting functions, homologous groups, sequence analysis, etc. It really motivate us to predict essential proteins efficiently using different computational approaches.

METHODS

In our work, we proposed modified Jaccard's coefficient to predict essential proteins. We have proposed a novel methodology for predicting essential proteins using MAX-MIN strategies and modified Jaccard's coefficient approach.

RESULTS

The performance of our proposed methodology has been analyzed for Saccharomyces cerevisiae datasets with an accuracy of more than 80%. It has been observed that the proposed algorithm is outperforms with an accuracy of 0.78, 0.74, 0.79, and 0.862 for YDIP, YMIPS, YHQ, and YMBD datasets respectivly.

CONCLUSIONS

There are several computational approaches in the existing state-of-art model of essential protein prediction. It has been noted that our predicted methodology outperforms other existing models viz. different centralities, local interaction density combined with protein complexes, modified monkey algorithm and ortho_sim_loc methods.

High throughput mutagenesis and screening for yeast engineering

The eukaryotic yeast Saccharomyces cerevisiae is a model host utilized for whole cell biocatalytic conversions, protein evolution, and scientific inquiries into the pathogenesis of human disease. Over the past decade, the scale and pace of such studies has drastically increased alongside the advent of novel tools for both genome-wide studies and targeted genetic mutagenesis. In this review, we will detail past and present (e.g., CRISPR/Cas) genome-scale screening platforms, typically employed in the context of growth-based selections for improved whole cell phenotype or for mechanistic interrogations. We will further highlight recent advances that enable the rapid and often continuous evolution of biomolecules with improved function. Additionally, we will detail the corresponding advances in high throughput selection and screening strategies that are essential for assessing or isolating cellular and protein improvements. Finally, we will describe how future developments can continue to advance yeast high throughput engineering.

Bidirectional promoter activity from expression cassettes can drive off-target repression of neighboring gene translation

Targeted selection-based genome-editing approaches have enabled many fundamental discoveries and are used routinely with high precision. We found, however, that replacement of DBP1 with a common selection cassette in budding yeast led to reduced expression and function for the adjacent gene, MRP51, despite all MRP51 coding and regulatory sequences remaining intact. Cassette-induced repression of MRP51 drove all mutant phenotypes detected in cells deleted for DBP1. This behavior resembled the 'neighboring gene effect' (NGE), a phenomenon of unknown mechanism whereby cassette insertion at one locus reduces the expression of a neighboring gene. Here, we leveraged strong off-target mutant phenotypes resulting from cassette replacement of DBP1 to provide mechanistic insight into the NGE. We found that the inherent bidirectionality of promoters, including those in expression cassettes, drives a divergent transcript that represses MRP51 through combined transcriptional interference and translational repression mediated by production of a long undecoded transcript isoform (LUTI). Divergent transcript production driving this off-target effect is general to yeast expression cassettes and occurs ubiquitously with insertion. Despite this, off-target effects are often naturally prevented by local sequence features, such as those that terminate divergent transcripts between the site of cassette insertion and the neighboring gene. Thus, cassette-induced off-target effects can be eliminated by the insertion of transcription terminator sequences into the cassette, flanking the promoter. Because the driving features of this off-target effect are broadly conserved, our study suggests it should be considered in the design and interpretation of experiments using integrated expression cassettes in other eukaryotic systems, including human cells.

An RNA granule for translation quality control in Saccharomyces cerevisiae

Cytoplasmic RNA granules compartmentalize phases of the translation cycle in eukaryotes. We previously reported the localization of oxidized RNA to cytoplasmic foci called oxidized RNA bodies (ORBs) in human cells. We show here that ORBs are RNA granules in Saccharomyces cerevisiae. Several lines of evidence support a role for ORBs in the compartmentalization of no-go decay and ribosome quality control, the translation quality control pathways that recognize and clear aberrant mRNAs, including those with oxidized bases. Translation is required by these pathways and ORBs. Translation quality control factors localize to ORBs. A substrate of translation quality control, a stalled mRNA-ribosome-nascent-chain complex, localizes to ORBs. Translation quality control mutants have altered ORB numbers, sizes or both. In addition, we identify 68 ORB proteins by immunofluorescence staining directed by proteomics, which further support their role in translation quality control and reveal candidate new factors for these pathways.

Microfluidic screening and genomic mutation identification for enhancing cellulase production in Pichia pastoris

Background

Pichia pastoris is a widely used host organism for heterologous production of industrial proteins, such as cellulases. Although great progress has been achieved in improving protein expression in P. pastoris, the potential of the P. pastoris expression system has not been fully explored due to unknown genomic impact factors. Recently, whole-cell directed evolution, employing iterative rounds of genome-wide diversity generation and high-throughput screening (HTS), has been considered to be a promising strategy in strain improvement at the genome level.

Results

In this study, whole-cell directed evolution of P. pastoris, employing atmospheric and room temperature plasma (ARTP) mutagenesis and droplet-based microfluidic HTS, was developed to improve heterogenous cellulase production. The droplet-based microfluidic platform based on a cellulase-catalyzed reaction of releasing fluorescence was established to be suitable for methanol-grown P. pastoris. The validation experiment showed a positive sorting efficiency of 94.4% at a sorting rate of 300 droplets per second. After five rounds of iterative ARTP mutagenesis and microfluidic screening, the best mutant strain was obtained and exhibited the cellulase activity of 11,110 ± 523 U/mL, an approximately twofold increase compared to the starting strain. Whole-genome resequencing analysis further uncovered three accumulated genomic alterations in coding region. The effects of point mutations and mutant genes on cellulase production were verified using reconstruction of point mutations and gene deletions. Intriguingly, the point mutation Rsc1G22V was observed in all the top-performing producers selected from each round, and gene deletion analysis confirmed that Rsc1, a component of the RSC chromatin remodeling complex, might play an important role in cellulase production.

Conclusions

We established a droplet-based microfluidic HTS system, thereby facilitating whole-cell directed evolution of P. pastoris for enhancing cellulase production, and meanwhile identified genomic alterations by whole-genome resequencing and genetic validation. Our approaches and findings would provide guides to accelerate whole-cell directed evolution of host strains and enzymes of high industrial interest.

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.

Functional mapping of the N-terminal region of the yeast moonlighting protein Sis2/Hal3 reveals crucial residues for Ppz1 regulation

The function of the Saccharomyces cerevisiae Ppz1 phosphatase is controlled by its inhibitory subunit Hal3. Hal3 is a moonlighting protein, which associates with Cab3 to form a decarboxylase involved in the CoA biosynthetic pathway. Hal3 is composed by a conserved core PD region, required for both Ppz1 regulation and CoA biosynthesis, a long N-terminal extension, and an acidic C-terminal tail. Cab3 has a similar structure, but it is not a Ppz1 inhibitor. We show here that deletion or specific mutations in a short region of the N-terminal extension of Hal3 compromise its function as a Ppz1 inhibitor in vivo and in vitro without negatively affecting its ability to interact with the phosphatase. This study defines a R-K-X(3) -VTFS- sequence whose presence explains the unexpected ability of Cab3 (but not Hal3) to regulate Ppz1 function in Candida albicans. This sequence is conserved in a subset of fungi and it could serve to estimate the relevance of Hal3 or Cab3 proteins in regulating fungal Ppz enzymes. We also show that the removal of the motif moderately affects both Ppz1 intracellular relocalization and counteraction of toxicity in cells overexpressing the phosphatase. Thus, our work contributes to our understanding of the regulation of Ppz phosphatases, which are determinants for virulence in some pathogenic fungi.

[PRION+] States Are Associated with Specific Histone H3 Post-Translational Modification Changes

Prions are proteins able to take on alternative conformations and propagate them in a self-templating process. In Saccharomyces cerevisiae, prions enable heritable responses to environmental conditions through bet-hedging mechanisms. Hence, [PRION⁺] states may serve as an atypical form of epigenetic control, producing heritable phenotypic change via protein folding. However, the connections between prion states and the epigenome remain unknown. Do [PRION⁺] states link to canonical epigenetic channels, such as histone post-translational modifications? Here, we map out the histone H3 modification landscape in the context of the [SWI⁺] and [PIN⁺] prion states. [SWI⁺] is propagated by Swi1, a subunit of the SWI/SNF chromatin remodeling complex, while [PIN⁺] is propagated by Rnq1, a protein of unknown function. We find [SWI⁺] yeast display decreases in the levels of H3K36me2 and H3K56ac compared to [swi^-] yeast. In contrast, decreases in H3K4me3, H3K36me2, H3K36me3 and H3K79me3 are connected to the [PIN⁺] state. Curing of the prion state by treatment with guanidine hydrochloride restored histone PTM to [prion^-] state levels. We find histone PTMs in the [PRION⁺] state do not match those in loss-of-function models. Our findings shed light into the link between prion states and histone modifications, revealing novel insight into prion function in yeast.

Synthetic Platforms for Characterizing and Targeting of SARS-CoV-2 Genome Capping Enzymes

Essential viral enzymes have been successfully targeted to combat the diseases caused by emerging pathogenic RNA viruses (e.g., viral RNA-dependent RNA polymerase). Because of the conserved nature of such viral enzymes, therapeutics targeting these enzymes have the potential to be repurposed to combat emerging diseases, e.g., remdesivir, which was initially developed as a potential Ebola treatment, then was repurposed for COVID-19. Our efforts described in this study target another essential and highly conserved, but relatively less explored, step in RNA virus translation and replication, i.e., capping of the viral RNA genome. The viral genome cap structure disguises the genome of most RNA viruses to resemble the mRNA cap structure of their host and is essential for viral translation, propagation, and immune evasion. Here, we developed a synthetic, phenotypic yeast-based complementation platform (YeRC0M) for molecular characterization and targeting of SARS-CoV-2 genome-encoded RNA cap-0 (guanine-N7)-methyltransferase (N7-MTase) enzyme (nsp14). In YeRC0M, the lack of yeast mRNA capping N7-MTase in yeast, which is an essential gene in yeast, is complemented by the expression of functional viral N7-MTase or its variants. Using YeRC0M, we first identified important protein domains and amino acid residues that are essential for SARS-CoV-2 nsp14 N7-MTase activity. We also expanded YeRC0M to include key nsp14 variants observed in emerging variants of SARS-CoV-2 (e.g., delta variant of SARS-CoV-2 encodes nsp14 A394V and nsp14 P46L). We also combined YeRC0M with directed evolution to identify attenuation mutations in SARS-CoV-2 nsp14. Because of the high sequence similarity of nsp14 in emerging coronaviruses, these observations could have implications on live attenuated vaccine development strategies. These data taken together reveal key domains in SARS-CoV-2 nsp14 that can be targeted for therapeutic strategies. We also anticipate that these readily tractable phenotypic platforms can also be used for the identification of inhibitors of viral RNA capping enzymes as antivirals.

Heterozygous Mutations in Aromatic Amino Acid Synthesis Genes Trigger TOR Pathway Activation in Saccharomyces cerevisiae

The highly conserved complexes of Target of Rapamycin (TORC1 and TORC2) are central regulators to many vital cellular processes including growth and autophagy in response to nutrient availability. Previous research has extensively elucidated exogenous nutrient control on TORC1/TORC2; however, little is known about the potential alteration of nutrient pools from mutations in biosynthesis pathways and their impact on Tor pathway activity. Here, we analyze the impacts of heterozygous mutations in aromatic amino acid biosynthesis genes on TOR signaling via differential expression of genes downstream of TORC1 and autophagy induction for TORC1 and TORC2 activity.

Regulation of Cdc42 protein turnover modulates the filamentous growth MAPK pathway

Rho GTPases are central regulators of cell polarity and signaling. How Rho GTPases are directed to function in certain settings remains unclear. Here, we show the protein levels of the yeast Rho GTPase Cdc42p are regulated, which impacts a subset of its biological functions. Specifically, the active conformation of Cdc42p was ubiquitinated by the NEDD4 ubiquitin ligase Rsp5p and HSP40/HSP70 chaperones and turned over in the proteasome. A GTP-locked (Q61L) turnover-defective (TD) version, Cdc42pQ61L+TD, hyperactivated the MAPK pathway that regulates filamentous growth (fMAPK). Cdc42pQ61L+TD did not influence the activity of the mating pathway, which shares components with the fMAPK pathway. The fMAPK pathway adaptor, Bem4p, stabilized Cdc42p levels, which resulted in elevated fMAPK pathway signaling. Our results identify Cdc42p turnover regulation as being critical for the regulation of a MAPK pathway. The control of Rho GTPase levels by stabilization and turnover may be a general feature of signaling pathway regulation, which can result in the execution of a specific developmental program.

The vacuolar transporter LaMTP8.1 detoxifies manganese in leaves of Lupinus albus

Manganese (Mn) is an essential microelement, but overaccumulation is harmful to many plant species. Most plants have similar minimal Mn requirements, but the tolerance to elevated Mn varies considerably. Mobilization of phosphate (P) by plant roots leads to increased Mn uptake, and shoot Mn levels have been reported to serve as an indicator for P mobilization efficiency in the presence of P deficiency. White lupin (Lupinus albus L.) mobilizes P and Mn with outstanding efficiency due to the formation of determinate cluster roots that release carboxylates. The high Mn tolerance of L. albus goes along with shoot Mn accumulation, but the molecular basis of this detoxification mechanism has been unknown. In this study, we identify LaMTP8.1 as the transporter mediating vacuolar sequestration of Mn in the shoot of white lupin. The function of Mn transport was demonstrated by yeast complementation analysis, in which LaMTP8.1 detoxified Mn in pmr1∆ mutant cells upon elevated Mn supply. In addition, LaMTP8.1 also functioned as an iron (Fe) transporter in yeast assays. The expression of LaMTP8.1 was particularly high in old leaves under high Mn stress. However, low P availability per se did not result in transcriptional upregulation of LaMTP8.1. Moreover, LaMTP8.1 expression was strongly upregulated under Fe deficiency, where it was accompanied by Mn accumulation, indicating a role in the interaction of these micronutrients in L. albus. In conclusion, the tonoplast-localized Mn transporter LaMTP8.1 mediates Mn detoxification in leaf vacuoles, providing a mechanistic explanation for the high Mn accumulation and Mn tolerance in this species.

Identification of acetic acid sensitive strains through biosensor-based screening of a Saccharomyces cerevisiae CRISPRi library

Background

Acetic acid tolerance is crucial for the development of robust cell factories for conversion of lignocellulosic hydrolysates that typically contain high levels of acetic acid. Screening mutants for growth in medium with acetic acid is an attractive way to identify sensitive variants and can provide novel insights into the complex mechanisms regulating the acetic acid stress response.

Results

An acetic acid biosensor based on the Saccharomyces cerevisiae transcription factor Haa1, was used to screen a CRISPRi yeast strain library where dCas9-Mxi was set to individually repress each essential or respiratory growth essential gene. Fluorescence-activated cell sorting led to the enrichment of a population of cells with higher acetic acid retention. These cells with higher biosensor signal were demonstrated to be more sensitive to acetic acid. Biosensor-based screening of the CRISPRi library strains enabled identification of strains with increased acetic acid sensitivity: strains with gRNAs targeting TIF34, MSN5, PAP1, COX10 or TRA1.

Conclusions

This study demonstrated that biosensors are valuable tools for screening and monitoring acetic acid tolerance in yeast. Fine-tuning the expression of essential genes can lead to altered acetic acid tolerance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01938-7.

Application of the Mutant Libraries for Candida albicans Functional Genomics

Candida albicans is a typical opportunistic pathogen in humans that causes serious health risks in clinical fungal infections. The construction of mutant libraries has made remarkable developments in the study of C. albicans molecular and cellular biology with the ongoing advancements of gene editing, which include the application of CRISPR-Cas9 and novel high-efficient transposon. Large-scale genetic screens and genome-wide functional analysis accelerated the investigation of new genetic regulatory mechanisms associated with the pathogenicity and resistance to environmental stress in C. albicans. More importantly, sensitivity screening based on C. albicans mutant libraries is critical for the target identification of novel antifungal compounds, which leads to the discovery of Sec7p, Tfp1p, Gwt1p, Gln4p, and Erg11p. This review summarizes the main types of C. albicans mutant libraries and interprets their applications in morphogenesis, biofilm formation, fungus-host interactions, antifungal drug resistance, and target identification.

MTM1 displays a new function in the regulation of nickel resistance in Saccharomyces cerevisiae

Nickel (Ni) is an essential yet toxic trace element. Although a cofactor for many metalloenzymes, nickel function and metabolism is not fully explored in eukaryotes. Molecular biology and metallomic methods were utilized to explore the new physiological functions of nickel in Saccharomyces cerevisiae. Here we showed that MTM1 knockout cells displayed much stronger nickel tolerance than wild-type cells and mitochondrial accumulations of Ni and Fe of mtm1Δ cells dramatically decreased compared to wild-type cells when exposed to excess nickel. Superoxide dismutase 2 (Sod2p) activity in mtm1Δ cells was severely attenuated and restored through Ni supplementation in media or total protein. SOD2 mRNA level of mtm1Δ cells was significantly higher than that in the wild-type strain but was decreased by Ni supplementation. MTM1 knockout afforded resistance to excess nickel mediated through reactive oxygen species levels. Meanwhile, additional Ni showed no significant effect on the localization of Mtm1p. Our study reveals the MTM1 gene plays an important role in nickel homeostasis and identifies a novel function of nickel in promoting Sod2p activity in yeast cells.

Saccharomyces cerevisiae as a Model System for Eukaryotic Cell Biology, from Cell Cycle Control to DNA Damage Response

The yeast Saccharomyces cerevisiae has been used for bread making and beer brewing for thousands of years. In addition, its ease of manipulation, well-annotated genome, expansive molecular toolbox, and its strong conservation of basic eukaryotic biology also make it a prime model for eukaryotic cell biology and genetics. In this review, we discuss the characteristics that made yeast such an extensively used model organism and specifically focus on the DNA damage response pathway as a prime example of how research in S. cerevisiae helped elucidate a highly conserved biological process. In addition, we also highlight differences in the DNA damage response of S. cerevisiae and humans and discuss the challenges of using S. cerevisiae as a model system.

Recent insights into the evolution of mutation rates in yeast

Mutation is the origin of all genetic variation, good and bad. The mutation process can evolve in response to mutations, positive or negative selection, and genetic drift, but how these forces contribute to mutation-rate variation is an unsolved problem at the heart of genetics research. Mutations can be challenging to measure, but genome sequencing and other tools have allowed for the collection of larger and more detailed datasets, particularly in the yeast-model system. We review key hypotheses for the evolution of mutation rates and describe recent advances in understanding variation in mutational properties within and among yeast species. The multidimensional spectrum of mutations is increasingly recognized as holding valuable clues about how this important process evolves.

Chaperone requirements for de novo folding of Saccharomyces cerevisiae septins

Polymers of septin protein complexes play cytoskeletal roles in eukaryotic cells. The specific subunit composition within complexes controls functions and higher-order structural properties. All septins have globular GTPase domains. The other eukaryotic cytoskeletal NTPases strictly require assistance from molecular chaperones of the cytosol, particularly the cage-like chaperonins, to fold into oligomerization-competent conformations. We previously identified cytosolic chaperones that bind septins and influence the oligomerization ability of septins carrying mutations linked to human disease, but it was unknown to what extent wild-type septins require chaperone assistance for their native folding. Here we use a combination of in vivo and in vitro approaches to demonstrate chaperone requirements for de novo folding and complex assembly by budding yeast septins. Individually purified septins adopted nonnative conformations and formed nonnative homodimers. In chaperonin- or Hsp70-deficient cells, septins folded slower and were unable to assemble posttranslationally into native complexes. One septin, Cdc12, was so dependent on cotranslational chaperonin assistance that translation failed without it. Our findings point to distinct translation elongation rates for different septins as a possible mechanism to direct a stepwise, cotranslational assembly pathway in which general cytosolic chaperones act as key intermediaries.

Transcriptome Analysis of the Influence of High-Pressure Carbon Dioxide on Saccharomyces cerevisiae under Sub-Lethal Condition

High-pressure carbon dioxide (HPCD), a novel non-thermal pasteurization technology, has attracted the attention of scientists due to its high pasteurization efficiency at a lower temperature and pressure. However, the inactivation mechanism has not been well researched, and this has hindered its commercial application. In this work, we used a sub-lethal HPCD condition (4.0 MPa, 30 °C) and a recovery condition (30 °C) to repair the damaged cells. Transcriptome analysis was performed by using RNA sequencing and gene ontology analysis to investigate the detailed lethal mechanism caused by HPCD treatment. RT-qPCR analysis was conducted for certain upregulated genes, and the influence of HPCD on protoplasts and single-gene deletion strains was investigated. Six major categories of upregulated genes were identified, including genes associated with the pentose phosphate pathway (oxidative phase), cell wall organization or biogenesis, glutathione metabolism, protein refolding, phosphatidylcholine biosynthesis, and AdoMet synthesis, which are all considered to be associated with cell death induced by HPCD. The inactivation or structure alteration of YNL194Cp in the organelle membrane is considered the critical reason for cell death. We believe this work contributes to elucidating the cell-death mechanism and providing a direction for further research on non-thermal HPCD sterilization technology.

Real-time visualization of phagosomal pH manipulation by Cryptococcus neoformans in an immune signal-dependent way

Understanding of how intracellular pathogens survive in their host cells is important to improve management of their diseases. This has been fruitful for intracellular bacteria, but it is an understudied area in fungal pathogens. Here we start elucidating and characterizing the strategies used by one of the commonest fungal pathogens, Cryptococcus neoformans, to survive intracellularly. The ability of the fungus to survive inside host cells is one of the main drivers of disease progression, yet it is unclear whether C. neoformans resides in a fully acidified, partially acidic, or neutral phagosome. Using a dye that only fluoresce under acidic conditions to stain C. neoformans, a hypha-defective Candida albicans mutant, and the nonpathogenic Saccharomyces cerevisiae, we characterized the fungal behaviors in infected macrophages by live microscopy. The main behavior in the C. albicans mutant strain and S. cerevisiae-phagosomes was rapid acidification after internalization, which remained for the duration of the imaging. In contrast, a significant number of C. neoformans-phagosomes exhibited alternative behaviors distinct from the normal phagosomal maturation: some phagosomes acidified with subsequent loss of acidification, and other phagosomes never acidified. Moreover, the frequency of these behaviors was affected by the immune status of the host cell. We applied the same technique to a flow cytometry analysis and found that a substantial percentage of C. neoformans-phagosomes showed impaired acidification, whereas almost 100% of the S. cerevisiae-phagosomes acidify. Lastly, using a membrane-damage reporter, we show phagosome permeabilization correlates with acidification alterations, but it is not the only strategy that C. neoformans uses to manipulate phagosomal acidification. The different behaviors described here provide an explanation to the confounding literature regarding cryptococcal-phagosome acidification and the methods can be applied to study other intracellular fungal pathogens.

A multiplexed, three-dimensional pooling and next-generation sequencing strategy for creating barcoded mutant arrays: construction of a Schizosaccharomyces pombe transposon insertion library

Arrayed libraries of defined mutants have been used to elucidate gene function in the post-genomic era. Yeast haploid gene deletion libraries have pioneered this effort, but are costly to construct, do not reveal phenotypes that may occur with partial gene function and lack essential genes required for growth. We therefore devised an efficient method to construct a library of barcoded insertion mutants with a wider range of phenotypes that can be generalized to other organisms or collections of DNA samples. We developed a novel but simple three-dimensional pooling and multiplexed sequencing approach that leveraged sequence information to reduce the number of required sequencing reactions by orders of magnitude, and were able to identify the barcode sequences and DNA insertion sites of 4391 Schizosaccharomyces pombe insertion mutations with only 40 sequencing preparations. The insertion mutations are in the genes and untranslated regions of nonessential, essential and noncoding RNA genes, and produced a wider range of phenotypes compared to the cognate deletion mutants, including novel phenotypes. This mutant library represents both a proof of principle for an efficient method to produce novel mutant libraries and a valuable resource for the S. pombe research community.

Top-Down, Knowledge-Based Genetic Reduction of Yeast Central Carbon Metabolism

Saccharomyces cerevisiae, whose evolutionary past includes a whole-genome duplication event, is characterized by a mosaic genome configuration with substantial apparent genetic redundancy. This apparent redundancy raises questions about the evolutionary driving force for genomic fixation of “minor” paralogs and complicates modular and combinatorial metabolic engineering strategies. While isoenzymes might be important in specific environments, they could be dispensable in controlled laboratory or industrial contexts. The present study explores the extent to which the genetic complexity of the central carbon metabolism (CCM) in S. cerevisiae, here defined as the combination of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and a limited number of related pathways and reactions, can be reduced by elimination of (iso)enzymes without major negative impacts on strain physiology. Cas9-mediated, groupwise deletion of 35 of the 111 genes yielded a “minimal CCM” strain which, despite the elimination of 32% of CCM-related proteins, showed only a minimal change in phenotype on glucose-containing synthetic medium in controlled bioreactor cultures relative to a congenic reference strain. Analysis under a wide range of other growth and stress conditions revealed remarkably few phenotypic changes from the reduction of genetic complexity. Still, a well-documented context-dependent role of GPD1 in osmotolerance was confirmed. The minimal CCM strain provides a model system for further research into genetic redundancy of yeast genes and a platform for strategies aimed at large-scale, combinatorial remodeling of yeast CCM.

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.

Glutathione degradation activity of γ-glutamyl peptidase 1 manifests its dual roles in primary and secondary sulfur metabolism in Arabidopsis

Glutathione (GSH) functions as a major sulfur repository and hence occupies an important position in primary sulfur metabolism. GSH degradation results in sulfur reallocation and is believed to be carried out mainly by γ-glutamyl cyclotransferases (GGCT2;1, GGCT2;2, and GGCT2;3), which, however, do not fully explain the rapid GSH turnover. Here, we discovered that γ-glutamyl peptidase 1 (GGP1) contributes to GSH degradation through a yeast complementation assay. Recombinant proteins of GGP1, as well as GGP3, showed high degradation activity of GSH, but not of oxidized glutathione (GSSG), in vitro. Notably, the GGP1 transcripts were highly abundant in rosette leaves, in agreement with the ggp1 mutants constantly accumulating more GSH regardless of nutritional conditions. Given the lower energy requirements of the GGP- than the GGCT-mediated pathway, the GGP-mediated pathway could be a more efficient route for GSH degradation than the GGCT-mediated pathway. Therefore, we propose a model wherein cytosolic GSH is degraded chiefly by GGP1 and likely also by GGP3. Another noteworthy fact is that GGPs are known to process GSH conjugates in glucosinolate and camalexin synthesis; indeed, we confirmed that the ggp1 mutant contained higher levels of O-acetyl-l-Ser, a signaling molecule for sulfur starvation, and lower levels of glucosinolates and their degradation products. The predicted structure of GGP1 further provided a rationale for this hypothesis. In conclusion, we suggest that GGP1 and possibly GGP3 play vital roles in both primary and secondary sulfur metabolism.

Rule-Based Pruning and In Silico Identification of Essential Proteins in Yeast PPIN

Proteins are vital for the significant cellular activities of living organisms. However, not all of them are essential. Identifying essential proteins through different biological experiments is relatively more laborious and time-consuming than the computational approaches used in recent times. However, practical implementation of conventional scientific methods sometimes becomes challenging due to poor performance impact in specific scenarios. Thus, more developed and efficient computational prediction models are required for essential protein identification. An effective methodology is proposed in this research, capable of predicting essential proteins in a refined yeast protein–protein interaction network (PPIN). The rule-based refinement is done using protein complex and local interaction density information derived from the neighborhood properties of proteins in the network. Identification and pruning of non-essential proteins are equally crucial here. In the initial phase, careful assessment is performed by applying node and edge weights to identify and discard the non-essential proteins from the interaction network. Three cut-off levels are considered for each node and edge weight for pruning the non-essential proteins. Once the PPIN has been filtered out, the second phase starts with two centralities-based approaches: (1) local interaction density (LID) and (2) local interaction density with protein complex (LIDC), which are successively implemented to identify the essential proteins in the yeast PPIN. Our proposed methodology achieves better performance in comparison to the existing state-of-the-art techniques.

In Silico Pleiotropy Analysis in KEGG Signaling Networks Using a Boolean Network Model

Pleiotropy, which refers to the ability of different mutations on the same gene to cause different pathological effects in human genetic diseases, is important in understanding system-level biological diseases. Although some biological experiments have been proposed, still little is known about pleiotropy on gene–gene dynamics, since most previous studies have been based on correlation analysis. Therefore, a new perspective is needed to investigate pleiotropy in terms of gene–gene dynamical characteristics. To quantify pleiotropy in terms of network dynamics, we propose a measure called in silico Pleiotropic Scores (sPS), which represents how much a gene is affected against a pair of different types of mutations on a Boolean network model. We found that our model can identify more candidate pleiotropic genes that are not known to be pleiotropic than the experimental database. In addition, we found that many types of functionally important genes tend to have higher sPS values than other genes; in other words, they are more pleiotropic. We investigated the relations of sPS with the structural properties in the signaling network and found that there are highly positive relations to degree, feedback loops, and centrality measures. This implies that the structural characteristics are principles to identify new pleiotropic genes. Finally, we found some biological evidence showing that sPS analysis is relevant to the real pleiotropic data and can be considered a novel candidate for pleiotropic gene research. Taken together, our results can be used to understand the dynamics pleiotropic characteristics in complex biological systems in terms of gene–phenotype relations.

Defect-buffering cellular plasticity increases robustness of metazoan embryogenesis

Developmental processes are intrinsically robust so as to preserve a normal-like state in response to genetic and environmental fluctuations. However, the robustness and potential phenotypic plasticity of individual developing cells under genetic perturbations remain to be systematically evaluated. Using large-scale gene perturbation, live imaging, lineage tracing, and single-cell phenomics, we quantified the phenotypic landscape of C. elegans embryogenesis in >2,000 embryos following individual knockdown of over 750 conserved genes. We observed that cellular genetic systems are not sufficiently robust to single-gene perturbations across all cells; rather, gene knockdowns frequently induced cellular defects. Dynamic phenotypic analyses revealed many cellular defects to be transient, with cells exhibiting phenotypic plasticity that serves to alleviate, correct, and accommodate the defects. Moreover, potential developmentally related cell modules may buffer the phenotypic effects of individual cell position changes. Our findings reveal non-negligible contributions of cellular plasticity and multicellularity as compensatory strategies to increase developmental robustness.

Identifying essential proteins from protein-protein interaction networks based on influence maximization

BACKGROUND

Essential proteins are indispensable to the development and survival of cells. The identification of essential proteins not only is helpful for the understanding of the minimal requirements for cell survival, but also has practical significance in disease diagnosis, drug design and medical treatment. With the rapidly amassing of protein-protein interaction (PPI) data, computationally identifying essential proteins from protein-protein interaction networks (PINs) becomes more and more popular. Up to now, a number of various approaches for essential protein identification based on PINs have been developed.

RESULTS

In this paper, we propose a new and effective approach called iMEPP to identify essential proteins from PINs by fusing multiple types of biological data and applying the influence maximization mechanism to the PINs. Concretely, we first integrate PPI data, gene expression data and Gene Ontology to construct weighted PINs, to alleviate the impact of high false-positives in the raw PPI data. Then, we define the influence scores of nodes in PINs with both orthological data and PIN topological information. Finally, we develop an influence discount algorithm to identify essential proteins based on the influence maximization mechanism.

CONCLUSIONS

We applied our method to identifying essential proteins from saccharomyces cerevisiae PIN. Experiments show that our iMEPP method outperforms the existing methods, which validates its effectiveness and advantage.

Heterologous (Over) Expression of Human SoLute Carrier (SLC) in Yeast: A Well-Recognized Tool for Human Transporter Function/Structure Studies

For more than 20 years, yeast has been a widely used system for the expression of human membrane transporters. Among them, more than 400 are members of the largest transporter family, the SLC superfamily. SLCs play critical roles in maintaining cellular homeostasis by transporting nutrients, ions, and waste products. Based on their involvement in drug absorption and in several human diseases, they are considered emerging therapeutic targets. Despite their critical role in human health, a large part of SLCs' is 'orphans' for substrate specificity or function. Moreover, very few data are available concerning their 3D structure. On the basis of the human health benefits of filling these knowledge gaps, an understanding of protein expression in systems that allow functional production of these proteins is essential. Among the 500 known yeast species, S. cerevisiae and P. pastoris represent those most employed for this purpose. This review aims to provide a comprehensive state-of-the-art on the attempts of human SLC expression performed by exploiting yeast. The collected data will hopefully be useful for guiding new attempts in SLCs expression with the aim to reveal new fundamental data that could lead to potential effects on human health.