Purification/Amplification-Free RNA Detection Platform for Rapid and Multiplex Diagnosis of Plant Viral Infections.

Genetic tests are highly sensitive, and quantitative methods for diagnosing human viral infections, including COVID-19, are also being used to diagnose plant diseases in various agricultural settings. Conventional genetic tests for plant viruses are mostly based on methods that require purification and amplification of viral genomes from plant samples, which generally take several hours in total, making it difficult to use them in rapid detection at point-of-care testing (POCT). In this study, we developed Direct-SATORI, a rapid and robust genetic test that eliminates the purification and amplification processes of viral genomes by extending the recently developed amplification-free digital RNA detection platform called SATORI, allowing the detection of various plant viral genes in a total of less than 15 min with a limit of detection (LoD) of 98 ∼ copies/µL using tomato viruses as an example. In addition, the platform can simultaneously detect eight plant viruses directly from ∼1 mg of tomato leaves with a sensitivity of 96% and a specificity of 99%. Direct-SATORI can be applied to various infections related to RNA viruses, and its practical use is highly anticipated as a versatile platform for plant disease diagnostics in the future.

Identification of triazenyl indoles as inhibitors of fungal fatty acid biosynthesis with broad-spectrum activity.

Rising drug resistance among pathogenic fungi, paired with a limited antifungal arsenal, poses an increasing threat to human health. To identify antifungal compounds, we screened the RIKEN natural product depository against representative isolates of four major human fungal pathogens. This screen identified NPD6433, a triazenyl indole with broad-spectrum activity against all screening strains, as well as the filamentous mold Aspergillus fumigatus. Mechanistic studies indicated that NPD6433 targets the enoyl reductase domain of fatty acid synthase 1 (Fas1), covalently inhibiting its flavin mononucleotide-dependent NADPH-oxidation activity and arresting essential fatty acid biosynthesis. Robust Fas1 inhibition kills Candida albicans, while sublethal inhibition impairs diverse virulence traits. At well-tolerated exposures, NPD6433 extended the lifespan of nematodes infected with azole-resistant C. albicans. Overall, identification of NPD6433 provides a tool with which to explore lipid homeostasis as a therapeutic target in pathogenic fungi and reveals a mechanism by which Fas1 function can be inhibited.

Overexpression profiling reveals cellular requirements in the context of genetic backgrounds and environments.

Overexpression can help life adapt to stressful environments, making an examination of overexpressed genes valuable for understanding stress tolerance mechanisms. However, a systematic study of genes whose overexpression is functionally adaptive (GOFAs) under stress has yet to be conducted. We developed a new overexpression profiling method and systematically identified GOFAs in Saccharomyces cerevisiae under stress (heat, salt, and oxidative). Our results show that adaptive overexpression compensates for deficiencies and increases fitness under stress, like calcium under salt stress. We also investigated the impact of different genetic backgrounds on GOFAs, which varied among three S. cerevisiae strains reflecting differing calcium and potassium requirements for salt stress tolerance. Our study of a knockout collection also suggested that calcium prevents mitochondrial outbursts under salt stress. Mitochondria-enhancing GOFAs were only adaptive when adequate calcium was available and non-adaptive when calcium was deficient, supporting this idea. Our findings indicate that adaptive overexpression meets the cell's needs for maximizing the organism's adaptive capacity in the given environment and genetic context.

Compact wide-field femtoliter-chamber imaging system for high-speed and accurate digital bioanalysis.

The femtoliter-chamber array is a bioanalytical platform that enables highly sensitive and quantitative analysis of biological reactions at the single-molecule level. This feature has been considered a key technology for "digital bioanalysis" in the biomedical field; however, its versatility is limited by the need for a large and expensive setup such as a fluorescence microscope, which requires a long time to acquire the entire image of a femtoliter-chamber array. To address these issues, we developed a compact and inexpensive wide-field imaging system (COWFISH) that can acquire fluorescence images with a large field of view (11.8 mm × 7.9 mm) and a high spatial resolution of ∼ 3 µm, enabling high-speed analysis of sub-million femtoliter chambers in 20 s. Using COWFISH, we demonstrated a CRISPR-Cas13a-based digital detection of viral RNA of SARS-CoV-2 with an equivalent detection sensitivity (limit of detection: 480 aM) and a 10-fold reduction in total imaging time, as compared to confocal fluorescence microscopy. In addition, we demonstrated the feasibility of COWFISH to discriminate between SARS-CoV-2-positive and -negative clinical specimens with 95% accuracy, showing its application in COVID-19 diagnosis. Therefore, COWFISH can serve as a compact and inexpensive imaging system for high-speed and accurate digital bioanalysis, paving a way for various biomedical applications, such as diagnosis of viral infections.

BIONIC: biological network integration using convolutions.

Biological networks constructed from varied data can be used to map cellular function, but each data type has limitations. Network integration promises to address these limitations by combining and automatically weighting input information to obtain a more accurate and comprehensive representation of the underlying biology. We developed a deep learning-based network integration algorithm that incorporates a graph convolutional network framework. Our method, BIONIC (Biological Network Integration using Convolutions), learns features that contain substantially more functional information compared to existing approaches. BIONIC has unsupervised and semisupervised learning modes, making use of available gene function annotations. BIONIC is scalable in both size and quantity of the input networks, making it feasible to integrate numerous networks on the scale of the human genome. To demonstrate the use of BIONIC in identifying new biology, we predicted and experimentally validated essential gene chemical-genetic interactions from nonessential gene profiles in yeast.

Automated amplification-free digital RNA detection platform for rapid and sensitive SARS-CoV-2 diagnosis.

In the ongoing COVID-19 pandemic, rapid and sensitive diagnosis of viral infection is a critical deterrent to the spread of SARS-CoV-2. To this end, we developed an automated amplification-free digital RNA detection platform using CRISPR-Cas13a and microchamber device (opn-SATORI), which automatically completes a detection process from sample mixing to RNA quantification in clinical specimens within ~9 min. Using the optimal Cas13a enzyme and magnetic beads technology, opn-SATORI detected SARS-CoV-2 genomic RNA with a LoD of < 6.5 aM (3.9 copies µL-1), comparable to RT-qPCR. Additionally, opn-SATORI discriminated between SARS-CoV-2 variants of concern, including alpha, delta, and omicron, with 98% accuracy. Thus, opn-SATORI can serve as a rapid and convenient diagnostic platform for identifying several types of viral infections.

Clionamines stimulate autophagy, inhibit Mycobacterium tuberculosis survival in macrophages, and target Pik1.

The pathogen Mycobacterium tuberculosis (Mtb) evades the innate immune system by interfering with autophagy and phagosomal maturation in macrophages, and, as a result, small molecule stimulation of autophagy represents a host-directed therapeutics (HDTs) approach for treatment of tuberculosis (TB). Here we show the marine natural product clionamines activate autophagy and inhibit Mtb survival in macrophages. A yeast chemical-genetics approach identified Pik1 as target protein of the clionamines. Biotinylated clionamine B pulled down Pik1 from yeast cell lysates and a clionamine analog inhibited phosphatidyl 4-phosphate (PI4P) production in yeast Golgi membranes. Chemical-genetic profiles of clionamines and cationic amphiphilic drugs (CADs) are closely related, linking the clionamine mode of action to co-localization with PI4P in a vesicular compartment. Small interfering RNA (siRNA) knockdown of PI4KB, a human homolog of Pik1, inhibited the survival of Mtb in macrophages, identifying PI4KB as an unexploited molecular target for efforts to develop HDT drugs for treatment of TB.

Improving Measures of Chemical Structural Similarity Using Machine Learning on Chemical-Genetic Interactions.

A common strategy for identifying molecules likely to possess a desired biological activity is to search large databases of compounds for high structural similarity to a query molecule that demonstrates this activity, under the assumption that structural similarity is predictive of similar biological activity. However, efforts to systematically benchmark the diverse array of available molecular fingerprints and similarity coefficients have been limited by a lack of large-scale datasets that reflect biological similarities of compounds. To elucidate the relative performance of these alternatives, we systematically benchmarked 11 different molecular fingerprint encodings, each combined with 13 different similarity coefficients, using a large set of chemical-genetic interaction data from the yeast Saccharomyces cerevisiae as a systematic proxy for biological activity. We found that the performance of different molecular fingerprints and similarity coefficients varied substantially and that the all-shortest path fingerprints paired with the Braun-Blanquet similarity coefficient provided superior performance that was robust across several compound collections. We further proposed a machine learning pipeline based on support vector machines that offered a fivefold improvement relative to the best unsupervised approach. Our results generally suggest that using high-dimensional chemical-genetic data as a basis for refining molecular fingerprints can be a powerful approach for improving prediction of biological functions from chemical structures.

Genome-wide screening of genes associated with momilactone B sensitivity in the fission yeast Schizosaccharomyces pombe.

Momilactone B is a natural product with dual biological activities, including antimicrobial and allelopathic properties, and plays a major role in plant chemical defense against competitive plants and pathogens. The pharmacological effects of momilactone B on mammalian cells have also been reported. However, little is known about the molecular and cellular mechanisms underlying its broad bioactivity. In this study, the genetic determinants of momilactone B sensitivity in yeast were explored to gain insight into its mode of action. We screened fission yeast mutants resistant to momilactone B from a pooled culture containing genome-wide gene-overexpressing strains in a drug-hypersensitive genetic background. Overexpression of pmd1, bfr1, pap1, arp9, or SPAC9E9.06c conferred resistance to momilactone B. In addition, a drug-hypersensitive, barcoded deletion library was newly constructed and the genes that imparted altered sensitivity to momilactone B upon deletion were identified. Gene Ontology and fission yeast phenotype ontology enrichment analyses predicted the biological pathways related to the mode of action of momilactone B. The validation of predictions revealed that momilactone B induced abnormal phenotypes such as multiseptated cells and disrupted organization of the microtubule structure. This is the first investigation of the mechanism underlying the antifungal activity of momilactone B against yeast. The results and datasets obtained in this study narrow the possible targets of momilactone B and facilitate further studies regarding its mode of action.

A globin-family protein, Cytoglobin 1, is involved in the development of neural crest-derived tissues and organs in zebrafish.

The zebrafish is an excellent model animal that is amenable to forward genetics approaches. To uncover unknown developmental regulatory mechanisms in vertebrates, we conducted chemical mutagenesis screening and identified a novel mutation, kanazutsi (kzt). This mutation is recessive, and its homozygotes are embryonic lethal. Mutant embryos suffered from a variety of morphological defects, such as head flattening, pericardial edema, circulation defects, disrupted patterns of melanophore distribution, dwarf eyes, a defective jaw, and extensive apoptosis in the head, which indicates that the main affected tissues are derived from neural crest cells (NCCs). The expression of tissue-specific markers in kzt mutants showed that the early specification of NCCs was normal, but their later differentiation was severely affected. The mutation was mapped to chromosome 3 by linkage analyses, near cytoglobin 1 (cygb1), the product of which is a globin-family respiratory protein. cygb1 expression was activated during somitogenesis in somites and cranial NCCs in wild-type embryos but was significantly downregulated in mutant embryos, despite the normal primary structure of the gene product. The kzt mutation was phenocopied by cygb1 knockdown with low-dose morpholino oligos and was partially rescued by cygb1 overexpression. Both severe knockdown and null mutation of cygb1, established by the CRISPR/Cas9 technique, resulted in far more severe defects at early stages. Thus, it is highly likely that the downregulation of cygb1 is responsible for many, if not all, of the phenotypes of the kzt mutation. These results reveal a requirement for globin family proteins in vertebrate embryos, particularly in the differentiation and subsequent development of NCCs.

Expression of a fungal exo-ß-1,3-galactanase in Arabidopsis reveals a role of type II arabinogalactans in the regulation of cell shape.

Arabinogalactan-proteins (AGPs) are a family of plant extracellular proteoglycans implicated in many physiological events. AGP is decorated with type II arabinogalactans (AGs) consisting of a ß-1,3-galactan backbone and ß-1,6-galactan side chains, to which other sugars are attached. Based on the fact that a type II AG-specific inhibitor, ß-Yariv reagent, perturbs growth and development, it has been proposed that type II AGs participate in the regulation of cell shape and tissue organization. However, the mechanisms by which type II AGs participate have not yet been established. Here, we describe a novel system that causes specific degradation of type II AGs in Arabidopsis, by which a gene encoding a fungal exo-ß-1,3-galactanase that specifically hydrolyzes ß-1,3-galactan backbones of type II AGs is expressed under the control of a dexamethasone-inducible promoter. Dexamethasone treatment increased the galactanase activity, leading to a decrease in Yariv reagent-reactive AGPs in transgenic Arabidopsis. We detected the typical oligosaccharides released from type II AGs by Il3GAL in the soluble fraction, demonstrating that Il3GAL acted on type II AG in the transgenic plants. Additionally, this resulted in severe tissue disorganization in the hypocotyl and cotyledons, suggesting that the degradation of type II AGs affected the regulation of cell shape.

Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interactions.

Chemical-genetic interactions-observed when the treatment of mutant cells with chemical compounds reveals unexpected phenotypes-contain rich functional information linking compounds to their cellular modes of action. To systematically identify these interactions, an array of mutants is challenged with a compound and monitored for fitness defects, generating a chemical-genetic interaction profile that provides a quantitative, unbiased description of the cellular function(s) perturbed by the compound. Genetic interactions, obtained from genome-wide double-mutant screens, provide a key for interpreting the functional information contained in chemical-genetic interaction profiles. Despite the utility of this approach, integrative analyses of genetic and chemical-genetic interaction networks have not been systematically evaluated. We developed a method, called CG-TARGET (Chemical Genetic Translation via A Reference Genetic nETwork), that integrates large-scale chemical-genetic interaction screening data with a genetic interaction network to predict the biological processes perturbed by compounds. In a recent publication, we applied CG-TARGET to a screen of nearly 14,000 chemical compounds in Saccharomyces cerevisiae, integrating this dataset with the global S. cerevisiae genetic interaction network to prioritize over 1500 compounds with high-confidence biological process predictions for further study. We present here a formal description and rigorous benchmarking of the CG-TARGET method, showing that, compared to alternative enrichment-based approaches, it achieves similar or better accuracy while substantially improving the ability to control the false discovery rate of biological process predictions. Additional investigation of the compatibility of chemical-genetic and genetic interaction profiles revealed that one-third of observed chemical-genetic interactions contributed to the highest-confidence biological process predictions and that negative chemical-genetic interactions overwhelmingly formed the basis of these predictions. We also present experimental validations of CG-TARGET-predicted tubulin polymerization and cell cycle progression inhibitors. Our approach successfully demonstrates the use of genetic interaction networks in the high-throughput functional annotation of compounds to biological processes.

Y-box protein-associated acidic protein (YBAP1/C1QBP) affects the localization and cytoplasmic functions of YB-1.

The Y-box proteins are multifunctional nucleic acid-binding proteins involved in various aspects of gene regulation. The founding member of the Y-box protein family, YB-1, functions as a transcription factor as well as a principal component of messenger ribonucleoprotein particles (mRNPs) in somatic cells. The nuclear level of YB-1 is well correlated with poor prognosis in many human cancers. Previously, we showed that a Y-box protein-associated acidic protein, YBAP1, which is identical to complement component 1, q subcomponent-binding protein (C1QBP, also called gC1qR, hyaluronan-binding protein 1 [HABP1] or ASF/SF2-associated protein p32), relieves translational repression by YB-1. Here we show that the nuclear localization of YB-1 harboring a point mutation in the cold shock domain was inhibited when co-expressed with YBAP1, whereas cytoplasmic accumulation of the wild-type YB-1 was not affected. We showed that YBAP1 inhibited the interaction between YB-1 and transportin 1. In the cytoplasm, YBAP1 affected the accumulation of YB-1 to processing bodies (P-bodies) and partially abrogated the mRNA stabilization by YB-1. Our results, indicating that YBAP1/C1QBP regulates the nucleo-cytoplasmic distribution of YB-1 and its cytoplasmic functions, are consistent with a model that YBAP1/C1QBP acts as an mRNP remodeling factor.

Errata: Functional annotation of chemical libraries across diverse biological processes.

This corrects the article DOI: 10.1038/nchembio.2436.

Errata: Functional annotation of chemical libraries across diverse biological processes.

This corrects the article DOI: 10.1038/nchembio.2436.

Functional annotation of chemical libraries across diverse biological processes.

Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

PRMT1 is required for RAP55 to localize to processing bodies.

In eukaryotic cells, components of messenger ribonucleoproteins (mRNPs) are often detected in cytoplasmic granules, such as processing bodies (P-bodies) and stress granules (SGs) where translationally repressed mRNAs accumulate. RAP55A, which is an RNA binding component of mRNPs, acts as a translational repressor and localizes to P-bodies and SGs. We found here that a homologous protein RAP55B also localized to P-bodies when expressed in human cultured cells. When RAP55A or RAP55B was highly expressed in the cells, they induced the formation of SG-like large cytoplasmic mRNP granules that contained both P-body and SG components, indicating that RAP55 is important for the assembly of cytoplasmic mRNP granules. In addition, we found that RAP55A associated with protein arginine methyltransferases PRMT1 and PRMT5. Multiple arginine residues of RAP55A were indeed asymmetrically dimethylated in the cell and PRMT1 was shown to be a component of large mRNP granules induced by RAP55A overexpression. Although PRMT1 did not accumulate in P-bodies, siRNA-mediated knockdown of PRMT1 impaired the localization of RAP55A to P-bodies, while other components were still retained in these structures. Thus, our data indicate that RAP55 is important for the assembly of cytoplasmic mRNP granules and that PRMT1 is required for RAP55A to localize to P-bodies.