Oxidative stress-induced YAP1 expression is regulated by NCE102, CDA2, and BCS1.

Maintaining cellular homeostasis in the face of stress conditions is vital for the overall well-being of an organism. Reactive oxygen species (ROS) are among the most potent cellular stressors and can disrupt the internal redox balance, giving rise to oxidative stress. Elevated levels of ROS can severely affect biomolecules and have been associated with a range of pathophysiological conditions. In response to oxidative stress, yeast activator protein-1 (Yap1p) undergoes post-translation modification that results in its nuclear accumulation. YAP1 has a key role in oxidative detoxification by promoting transcription of numerous antioxidant genes. In this study, we identified previously undescribed functions for NCE102, CDA2, and BCS1 in YAP1 expression in response to oxidative stress induced by hydrogen peroxide (H2O2). Deletion mutant strains for these candidates demonstrated increased sensitivity to H2O2. Our follow-up investigation linked the activity of these genes to YAP1 expression at the level of translation. Under oxidative stress, global cap-dependent translation is inhibited, prompting stress-responsive genes like YAP1 to employ alternative modes of translation. We provide evidence that NCE102, CDA2, and BCS1 contribute to cap-independent translation of YAP1 under oxidative stress.

Cymoxanil disrupts RNA synthesis through inhibiting the activity of dihydrofolate reductase.

The agricultural fungicide cymoxanil (CMX) is commonly used in the treatment of plant pathogens, such as Phytophthora infestans. Although the use of CMX is widespread throughout the agricultural industry and internationally, the exact mechanism of action behind this fungicide remains unclear. Therefore, we sought to elucidate the biocidal mechanism underlying CMX. This was accomplished by first performing a large-scale chemical-genomic screen comprising the 4000 haploid non-essential gene deletion array of the yeast Saccharomyces cerevisiae. We found that gene families related to de novo purine biosynthesis and ribonucleoside synthesis were enriched in the presence of CMX. These results were confirmed through additional spot-test and colony counting assays. We next examined whether CMX affects RNA biosynthesis. Using qRT-PCR and expression assays, we found that CMX appears to target RNA biosynthesis possibly through the yeast dihydrofolate reductase (DHFR) enzyme Dfr1. To determine whether DHFR is a target of CMX, we performed an in-silico molecular docking assay between CMX and yeast, human, and P. infestans DHFR. The results suggest that CMX directly interacts with the active site of all tested forms of DHFR using conserved residues. Using an in vitro DHFR activity assay we observed that CMX inhibits DHFR activity in a dose-dependent relationship.

The Involvement of YNR069C in Protein Synthesis in the Baker's Yeast, Saccharomyces cerevisiae.

Maintaining translation fidelity is a critical step within the process of gene expression. It requires the involvement of numerous regulatory elements to ensure the synthesis of functional proteins. The efficient termination of protein synthesis can play a crucial role in preserving this fidelity. Here, we report on investigating a protein of unknown function, YNR069C (also known as BSC5), for its activity in the process of translation. We observed a significant increase in the bypass of premature stop codons upon the deletion of YNR069C. Interestingly, the genomic arrangement of this ORF suggests a compatible mode of expression reliant on translational readthrough, incorporating the neighboring open reading frame. We also showed that the deletion of YNR069C results in an increase in the rate of translation. Based on our results, we propose that YNR069C may play a role in translation fidelity, impacting the overall quantity and quality of translation. Our genetic interaction analysis supports our hypothesis, associating the role of YNR069C to the regulation of protein synthesis.

Hydrogen peroxide sensitivity connects the activity of COX5A and NPR3 to the regulation of YAP1 expression.

Reactive oxygen species (ROS) are among the most severe types of cellular stressors with the ability to damage essential cellular biomolecules. Excess levels of ROS are correlated with multiple pathophysiological conditions including neurodegeneration, diabetes, atherosclerosis, and cancer. Failure to regulate the severely imbalanced levels of ROS can ultimately lead to cell death, highlighting the importance of investigating the molecular mechanisms involved in the detoxification procedures that counteract the effects of these compounds in living organisms. One of the most abundant forms of ROS is H2 O2 , mainly produced by the electron transport chain in the mitochondria. Numerous genes have been identified as essential to the process of cellular detoxification. Yeast YAP1, which is homologous to mammalian AP-1 type transcriptional factors, has a key role in oxidative detoxification by upregulating the expression of antioxidant genes in yeast. The current study reveals novel functions for COX5A and NPR3 in H2 O2 -induced stress by demonstrating that their deletions result in a sensitive phenotype. Our follow-up investigations indicate that COX5A and NPR3 regulate the expression of YAP1 through an alternative mode of translation initiation. These novel gene functions expand our understanding of the regulation of gene expression and defense mechanism of yeast against oxidative stress.

Differential gene expression provides leads to environmentally regulated soybean seed protein content.

Soybean is an important global source of plant-based protein. A persistent trend has been observed over the past two decades that soybeans grown in western Canada have lower seed protein content than soybeans grown in eastern Canada. In this study, 10 soybean genotypes ranging in average seed protein content were grown in an eastern location (control) and three western locations (experimental) in Canada. Seed protein and oil contents were measured for all lines in each location. RNA-sequencing and differential gene expression analysis were used to identify differentially expressed genes that may account for relatively low protein content in western-grown soybeans. Differentially expressed genes were enriched for ontologies and pathways that included amino acid biosynthesis, circadian rhythm, starch metabolism, and lipid biosynthesis. Gene ontology, pathway mapping, and quantitative trait locus (QTL) mapping collectively provide a close inspection of mechanisms influencing nitrogen assimilation and amino acid biosynthesis between soybeans grown in the East and West. It was found that western-grown soybeans had persistent upregulation of asparaginase (an asparagine hydrolase) and persistent downregulation of asparagine synthetase across 30 individual differential expression datasets. This specific difference in asparagine metabolism between growing environments is almost certainly related to the observed differences in seed protein content because of the positive correlation between seed protein content at maturity and free asparagine in the developing seed. These results provided pointed information on seed protein-related genes influenced by environment. This information is valuable for breeding programs and genetic engineering of geographically optimized soybeans.

Species-specific microRNA discovery and target prediction in the soybean cyst nematode.

The soybean cyst nematode (SCN) is a devastating pathogen for economic and food security considerations. Although the SCN genome has recently been sequenced, the presence of any miRNA has not been systematically explored and reported. This paper describes the development of a species-specific SCN miRNA discovery pipeline and its application to the SCN genome. Experiments on well-documented model nematodes (Caenorhabditis elegans and Pristionchus pacificus) are used to tune the pipeline's hyperparameters and confirm its recall and precision. Application to the SCN genome identifies 3342 high-confidence putative SCN miRNA. Prediction specificity within SCN is confirmed by applying the pipeline to RNA hairpins from known exonic regions of the SCN genome (i.e., sequences known to not be miRNA). Prediction recall is confirmed by building a positive control set of SCN miRNA, based on a limited deep sequencing experiment. Interestingly, a number of novel miRNA are predicted to be encoded within the intronic regions of effector genes, known to be involved in SCN parasitism, suggesting that these miRNA may also be involved in the infection process or virulence. Beyond miRNA discovery, gene targets within SCN are predicted for all high-confidence novel miRNA using a miRNA:mRNA target prediction system. Lastly, cross-kingdom miRNA targeting is investigated, where putative soybean mRNA targets are identified for novel SCN miRNA. All predicted miRNA and gene targets are made available in appendix and through a Borealis DataVerse open repository ( https://borealisdata.ca/dataset.xhtml?persistentId=doi:10.5683/SP3/30DEXA ).

Genome-wide analysis of cold imbibition stress in soybean, Glycine max.

In Canada, the length of the frost-free season necessitates planting crops as early as possible to ensure that the plants have enough time to reach full maturity before they are harvested. Early planting carries inherent risks of cold water imbibition (specifically less than 4°C) affecting seed germination. A marker dataset developed for a previously identified Canadian soybean GWAS panel was leveraged to investigate the effect of cold water imbibition on germination. Seed from a panel of 137 soybean elite cultivars, grown in the field at Ottawa, ON, over three years, were placed on filter paper in petri dishes and allowed to imbibe water for 16 hours at either 4°C or 20°C prior to being transferred to a constant 20°C. Observations on seed germination, defined as the presence of a 1 cm radicle, were done from day two to seven. A three-parameter exponential rise to a maximum equation (3PERM) was fitted to estimate germination, time to the one-half maximum germination, and germination uniformity for each cultivar. Genotype-by-sequencing was used to identify SNPs in 137 soybean lines, and using genome-wide association studies (GWAS - rMVP R package, with GLM, MLM, and FarmCPU as methods), haplotype block analysis, and assumed linkage blocks of ±100 kbp, a threshold for significance was established using the qvalue package in R, and five significant SNPs were identified on chromosomes 1, 3, 4, 6, and 13 for maximum germination after cold water imbibition. Percent of phenotypic variance explained (PVE) and allele substitution effect (ASE) eliminated two of the five candidate SNPs, leaving three QTL regions on chromosomes 3, 6, and 13 (Chr3-3419152, Chr6-5098454, and Chr13-29649544). Based on the gene ontology (GO) enrichment analysis, 14 candidate genes whose function is predicted to include germination and cold tolerance related pathways were identified as candidate genes. The identified QTLs can be used to select future soybean cultivars tolerant to cold water imbibition and mitigate risks associated with early soybean planting.

Large-scale data mining pipeline for identifying novel soybean genes involved in resistance against the soybean cyst nematode.

The soybean cyst nematode (SCN) [Heterodera glycines Ichinohe] is a devastating pathogen of soybean [Glycine max (L.) Merr.] that is rapidly becoming a global economic issue. Two loci conferring SCN resistance have been identified in soybean, Rhg1 and Rhg4; however, they offer declining protection. Therefore, it is imperative that we identify additional mechanisms for SCN resistance. In this paper, we develop a bioinformatics pipeline to identify protein-protein interactions related to SCN resistance by data mining massive-scale datasets. The pipeline combines two leading sequence-based protein-protein interaction predictors, the Protein-protein Interaction Prediction Engine (PIPE), PIPE4, and Scoring PRotein INTeractions (SPRINT) to predict high-confidence interactomes. First, we predicted the top soy interacting protein partners of the Rhg1 and Rhg4 proteins. Both PIPE4 and SPRINT overlap in their predictions with 58 soybean interacting partners, 19 of which had GO terms related to defense. Beginning with the top predicted interactors of Rhg1 and Rhg4, we implement a "guilt by association" in silico proteome-wide approach to identify novel soybean genes that may be involved in SCN resistance. This pipeline identified 1,082 candidate genes whose local interactomes overlap significantly with the Rhg1 and Rhg4 interactomes. Using GO enrichment tools, we highlighted many important genes including five genes with GO terms related to response to the nematode (GO:0009624), namely, Glyma.18G029000, Glyma.11G228300, Glyma.08G120500, Glyma.17G152300, and Glyma.08G265700. This study is the first of its kind to predict interacting partners of known resistance proteins Rhg1 and Rhg4, forming an analysis pipeline that enables researchers to focus their search on high-confidence targets to identify novel SCN resistance genes in soybean.

Peptides of a Feather: How Computation Is Taking Peptide Therapeutics under Its Wing.

Leveraging computation in the development of peptide therapeutics has garnered increasing recognition as a valuable tool to generate novel therapeutics for disease-related targets. To this end, computation has transformed the field of peptide design through identifying novel therapeutics that exhibit enhanced pharmacokinetic properties and reduced toxicity. The process of in-silico peptide design involves the application of molecular docking, molecular dynamics simulations, and machine learning algorithms. Three primary approaches for peptide therapeutic design including structural-based, protein mimicry, and short motif design have been predominantly adopted. Despite the ongoing progress made in this field, there are still significant challenges pertaining to peptide design including: enhancing the accuracy of computational methods; improving the success rate of preclinical and clinical trials; and developing better strategies to predict pharmacokinetics and toxicity. In this review, we discuss past and present research pertaining to the design and development of in-silico peptide therapeutics in addition to highlighting the potential of computation and artificial intelligence in the future of disease therapeutics.

A Correlation between 3'-UTR of OXA1 Gene and Yeast Mitochondrial Translation.

Mitochondria possess their own DNA (mtDNA) and are capable of carrying out their transcription and translation. Although protein synthesis can take place in mitochondria, the majority of the proteins in mitochondria have nuclear origin. 3' and 5' untranslated regions of mRNAs (3'-UTR and 5'-UTR, respectively) are thought to play key roles in directing and regulating the activity of mitochondria mRNAs. Here we investigate the association between the presence of 3'-UTR from OXA1 gene on a prokaryotic reporter mRNA and mitochondrial translation in yeast. OXA1 is a nuclear gene that codes for mitochondrial inner membrane insertion protein and its 3'-UTR is shown to direct its mRNA toward mitochondria. It is not clear, however, if this mRNA may also be translated by mitochondria. In the current study, using a ß-galactosidase reporter gene, we provide genetic evidence for a correlation between the presence of 3'-UTR of OXA1 on an mRNA and mitochondrial translation in yeast.

P-TarPmiR accurately predicts plant-specific miRNA targets.

microRNAs (miRNAs) are small non-coding ribonucleic acids that post-transcriptionally regulate gene expression through the targeting of messenger RNA (mRNAs). Most miRNA target predictors have focused on animal species and prediction performance drops substantially when applied to plant species. Several rule-based miRNA target predictors have been developed in plant species, but they often fail to discover new miRNA targets with non-canonical miRNA-mRNA binding. Here, the recently published TarDB database of plant miRNA-mRNA data is leveraged to retrain the TarPmiR miRNA target predictor for application on plant species. Rigorous experiment design across four plant test species demonstrates that animal-trained predictors fail to sustain performance on plant species, and that the use of plant-specific training data improves accuracy depending on the quantity of plant training data used. Surprisingly, our results indicate that the complete exclusion of animal training data leads to the most accurate plant-specific miRNA target predictor indicating that animal-based data may detract from miRNA target prediction in plants. Our final plant-specific miRNA prediction method, dubbed P-TarPmiR, is freely available for use at http://ptarpmir.cu-bic.ca . The final P-TarPmiR method is used to predict targets for all miRNA within the soybean genome. Those ranked predictions, together with GO term enrichment, are shared with the research community.

DBP7 and YRF1-6 Are Involved in Cell Sensitivity to LiCl by Regulating the Translation of PGM2 mRNA.

Lithium chloride (LiCl) has been widely researched and utilized as a therapeutic option for bipolar disorder (BD). Several pathways, including cell signaling and signal transduction pathways in mammalian cells, are shown to be regulated by LiCl. LiCl can negatively control the expression and activity of PGM2, a phosphoglucomutase that influences sugar metabolism in yeast. In the presence of galactose, when yeast cells are challenged by LiCl, the phosphoglucomutase activity of PGM2p is decreased, causing an increase in the concentration of toxic galactose metabolism intermediates that result in cell sensitivity. Here, we report that the null yeast mutant strains DBP7∆ and YRF1-6∆ exhibit increased LiCl sensitivity on galactose-containing media. Additionally, we demonstrate that DBP7 and YRF1-6 modulate the translational level of PGM2 mRNA, and the observed alteration in translation seems to be associated with the 5'-untranslated region (UTR) of PGM2 mRNA. Furthermore, we observe that DBP7 and YRF1-6 influence, to varying degrees, the translation of other mRNAs that carry different 5'-UTR secondary structures.

IRES-mediated translation in bacteria.

Despite the similarity in fundamental goals of translation initiation between different domains of life, it is one of the most phylogenetically diverse steps of the central dogma of molecular biology. In a classical view, the translation signals for prokaryotes and eukaryotes are distinct from each other. This idea was challenged by the finding that the Internal Ribosome Entry Site (IRES) belonging to Plautia stali intestine virus (PSIV) could bypass the domain-specific boundaries and effectively initiate translation in E. coli. This finding led us to investigate whether the ability of PSIV IRES to initiate translation in E. coli is specific to this IRES and also to study features that allow this viral IRES to mediate prokaryotic translation initiation. We observed that certain IRESs may also possess the ability to initiate E. coli translation. Our results also indicated that the structural integrity of the PSIV IRES in translation in prokaryotes does not appear to be as critical as it is in eukaryotes. We also demonstrated that two regions of the PSIV IRES with complementarity to 16S ribosomal RNA are important for the ability of this IRES to initiate translation in E. coli.

GmSWEET29 and Paralog GmSWEET34 Are Differentially Expressed between Soybeans Grown in Eastern and Western Canada.

Over the past two decades soybeans grown in western Canada have persistently had lower seed protein than those grown in eastern Canada. To understand the discrepancy in seed protein content between eastern- and western-grown soybeans, RNA-seq and differential expression analysis have been investigated. Ten soybean genotypes, ranging from low to high in seed protein content, were grown in four locations across eastern (Ottawa) and western (Morden, Brandon, and Saskatoon) Canada. Differential expression analysis revealed 34 differentially expressed genes encoding Glycine max Sugars Will Eventually be Exported Transporters (GmSWEETs), including paralogs GmSWEET29 and GmSWEET34 (AtSWEET2 homologs) that were consistently upregulated across all ten genotypes in each of the western locations over three years. GmSWEET29 and GmSWEET34 are likely candidates underlying the lower seed protein content of western soybeans. GmSWEET20 (AtSWEET12 homolog) was downregulated in the western locations and may also play a role in lower seed protein content. These findings are valuable for improving soybean agriculture in western growing regions, establishing more strategic and efficient agricultural practices.

A computational approach to rapidly design peptides that detect SARS-CoV-2 surface protein S.

The coronavirus disease 19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prompted the development of diagnostic and therapeutic frameworks for timely containment of this pandemic. Here, we utilized our non-conventional computational algorithm, InSiPS, to rapidly design and experimentally validate peptides that bind to SARS-CoV-2 spike (S) surface protein. We previously showed that this method can be used to develop peptides against yeast proteins, however, the applicability of this method to design peptides against other proteins has not been investigated. In the current study, we demonstrate that two sets of peptides developed using InSiPS method can detect purified SARS-CoV-2 S protein via ELISA and Surface Plasmon Resonance (SPR) approaches, suggesting the utility of our strategy in real time COVID-19 diagnostics. Mass spectrometry-based salivary peptidomics shortlist top SARS-CoV-2 peptides detected in COVID-19 patients' saliva, rendering them attractive SARS-CoV-2 diagnostic targets that, when subjected to our computational platform, can streamline the development of potent peptide diagnostics of SARS-CoV-2 variants of concern. Our approach can be rapidly implicated in diagnosing other communicable diseases of immediate threat.

Lithium chloride sensitivity connects the activity of PEX11 and RIM20 to the translation of PGM2 and other mRNAs with structured 5'-UTRs.

Lithium chloride (LiCl) is a widely used and extensively researched drug for the treatment of bipolar disorder (BD). As a result, LiCl has been the subject of research studying its toxicity, mode of action, and downstream cellular responses. LiCl has been shown to influence cell signaling and signaling transduction pathways through protein kinase C and glycogen synthase kinase-3 in mammalian cells. LiCl's significant downstream effects on the translational pathway necessitate further investigation. In yeast, LiCl is found to lower the activity and alter the expression of PGM2, a gene encoding a sugar-metabolism enzyme phosphoglucomutase. When phosphoglucomutase activity is reduced in the presence of galactose, intermediates of galactose metabolism aggregate, causing cell sensitivity to LiCl. In this study, we identified that deleting the genes PEX11 and RIM20 increases yeast LiCl sensitivity. We further show that PEX11 and RIM20 regulate the expression of PGM2 mRNA at the translation level. The observed alteration of translation seems to target the structured 5'-untranslated region (5'-UTR) of the PGM2 mRNA.

Novel QTL for Low Seed Cadmium Accumulation in Soybean.

Soybean is a valuable crop, used in animal feed and for human consumption. Selecting soybean cultivars with low seed cadmium (Cd) concentration is important for the purpose of minimizing the transfer of Cd into the human body. To ensure international trade, farmers need to produce soybean that meets the European Union (EU) Cd limit of 0.2 mg kg-1. In this study, we evaluated two populations of recombinant inbred lines (RILs), X5154 and X4050, for seed Cd accumulation. Linkage maps were constructed with 325 and 280 polymorphic simple sequence repeat (SSR) markers, respectively, and used to identify a novel minor quantitative trait locus (QTL) on chromosome 13 in the X4050 population between SSR markers Satt522 and Satt218. Based on a gene ontology search within the QTL region, seven genes were identified as candidates responsible for low seed Cd accumulation, including Glyma.13G308700 and Glyma.13G309100. In addition, we confirmed the known major gene, Cda1, in the X5154 population and developed KASP and CAPS/dCAPS allele-specific markers for efficient marker-assisted breeding for Cda1.

Discovery and identification of genes involved in DNA damage repair in yeast.

DNA repair defects are common in tumour cells and can lead to misrepair of double-strand breaks (DSBs), posing a significant challenge to cellular integrity. The overall mechanisms of DSB have been known for decades. However, the list of the genes that affect the efficiency of DSB repair continues to grow. Additional factors that play a role in DSB repair pathways have yet to be identified. In this study, we present a computational approach to identify novel gene functions that are involved in DNA damage repair in Saccharomyces cerevisiae. Among the primary candidates, GAL7, YMR130W, and YHI9 were selected for further analysis since they had not previously been identified as being active in DNA repair pathways. Originally, GAL7 was linked to galactose metabolism. YHI9 and YMR130W encode proteins of unknown functions. Laboratory testing of deletion strains gal7Δ, ymr130wΔ, and yhi9Δ implicated all 3 genes in Homologous Recombination (HR) and/or Non-Homologous End Joining (NHEJ) repair pathways, and enhanced sensitivity to DNA damage-inducing drugs suggested involvement in the broader DNA damage repair machinery. A subsequent genetic interaction analysis revealed interconnections of these three genes, most strikingly through SIR2, SIR3 and SIR4 that are involved in chromatin regulation and DNA damage repair network.

Photoperiod Affects Node Appearance Rate and Flowering in Early Maturing Soybean.

The photoperiod plays a critical role in the control of flowering timing in soybean (Glycine max (L.) Merr.) with long days increasing the time to flowering. Early flowering cultivars have been developed from breeding programs for environments with long photoperiods; however, this effect is challenging to isolate in field experiments because of other environmental influences. Our experiment examined the effect of photoperiod on the node appearance rate and time to flower for 13 early maturing soybean cultivars ranging in maturity group (MG) between 000.9 and 1.3. Growth chambers were programmed to 14, 15, 16, and 17 h photoperiods and temperature was kept at 25 °C. The date of emergence and main stem node appearance were recorded until flowering. The node appearance rate was slowest for the first node and increased thereafter. All cultivars required more time to flowering in the longer photoperiod treatments and the later rated MG had the greatest sensitivity to photoperiod. A delay in time to flower from a longer photoperiod can delay maturity and expose the crop to fall frost that can reduce seed yield and quality. Understanding and documentation of soybean photoperiod sensitivity will help plant breeders develop suitable cultivars for environments with long photoperiods.

A Broad Review of Soybean Research on the Ongoing Race to Overcome Soybean Cyst Nematode.

Plant pathogens greatly impact food security of the ever-growing human population. Breeding resistant crops is one of the most sustainable strategies to overcome the negative effects of these biotic stressors. In order to efficiently breed for resistant plants, the specific plant-pathogen interactions should be understood. Soybean is a short-day legume that is a staple in human food and animal feed due to its high nutritional content. Soybean cyst nematode (SCN) is a major soybean stressor infecting soybean worldwide including in China, Brazil, Argentina, USA and Canada. There are many Quantitative Trait Loci (QTLs) conferring resistance to SCN that have been identified; however, only two are widely used: rhg1 and Rhg4. Overuse of cultivars containing these QTLs/genes can lead to SCN resistance breakdown, necessitating the use of additional strategies. In this manuscript, a literature review is conducted on research related to soybean resistance to SCN. The main goal is to provide a current understanding of the mechanisms of SCN resistance and list the areas of research that could be further explored.