Biology subjects

Iwasaki, Y.

Publications and source records attributed to Iwasaki, Y..

35 records · Page 2Linked to original sources

bioRxiv2021

Immune cell multi-omics analysis reveals contribution of oxidative phosphorylation to B cell functions and organ damage of lupus

ObjectiveSystemic lupus erythematosus (SLE) is the prototypical systemic autoimmune disease, with a poor long-term prognosis. The type I interferon (IFN) signature, a prominent feature of SLE, is not an ideal therapeutic target or outcome predictor. To explore immunological pathways in SLE more precisely, we performed integrative analysis of transcriptomics, epigenomics, and genomics using each immune cell subset from peripheral blood. MethodsWe sorted 18 immune cell subsets and identified the mRNA expression profiles and genetic polymorphisms in 107 SLE patients and 92 healthy controls. Open chromatin information was also taken by ATAC-seq analysis. Combined differentially expressed genes (DEGs) and expression quantitative trait loci (eQTL) analysis was conducted to find key driver genes in SLE pathogenesis. ResultsWe found transcriptomic, epigenetic, and genetic importance of oxidative phosphorylation (OXPHOS)/mitochondrial dysfunction in SLE memory B cells. Particularly, we identified an OXPHOS-regulating gene, PRDX6, as a key driver in SLE B cells. Prdx6-deficient B cells showed upregulated mitochondrial respiration as well as antibody production. We revealed OXPHOS signature was associated with type I IFN signaling-related genes (ISRGs) signature in SLE memory B cells. Furthermore, the gene sets related to innate immune signaling among ISRGs presented correlation with OXPHOS and these two signatures showed associations with SLE organ damage as well as specific clinical phenotypes. ConclusionThis work elucidated the potential prognostic marker for SLE. Since OXPHOS consists of the electron transport chain, a functional unit in mitochondria, these findings suggest the importance of mitochondrial dysfunction as a key immunological pathway involved in SLE.

immunology↗

bioRxiv2021

CLPTM1L is a lipid scramblase involved in glycosylphosphatidylinositol biosynthesis

Glycosylphosphatidylinositols (GPIs) are membrane anchors of many eukaryotic cell surface proteins. Biosynthesis of GPIs is initiated at the cytosolic face of the endoplasmic reticulum (ER) and the second intermediate, glucosaminyl-phosphatidylinositol (GlcN-PI), is translocated across the membrane to the lumenal face for later biosynthetic steps and attachment to proteins. The mechanism of the lumenal translocation of GlcN-PI is unclear. We report that Cleft lip and palate transmembrane protein 1-like protein (CLPTM1L), an ER membrane protein of unknown function, is a lipid scramblase involved in GPI biosynthesis. Purified CLPTM1L scrambles GlcN-PI, PI, and several other phospholipids in vitro. Knockout of CLPTM1L gene in mammalian cultured cells partially decreased GPI-anchored proteins due to impaired usage of GlcN-PI, suggesting a major role of CLPTM1L in lumenal translocation of GlcN-PI. One-Sentence SummaryCLPTM1L translocates glucosaminyl-phosphatidylinositol across the membrane during glycosylphosphatidylinositol biosynthesis.

biochemistry↗

bioRxiv2021

Federated analysis of BRCA1 and BRCA2 variation in a Japanese cohort

More than 40% of the germline variants in ClinVar today are variants of uncertain significance (VUS). These variants remain unclassified in part because the patient-level data needed for their interpretation is siloed. Federated analysis can overcome this problem by "bringing the code to the data": analyzing the sensitive patient-level data computationally within its secure home institution and providing researchers with valuable insights from data that would not otherwise be accessible. We tested this principle with a federated analysis of breast cancer clinical data at RIKEN, derived from the BioBank Japan repository. We were able to analyze these data within RIKENs secure computational framework, without the need to transfer the data, gathering evidence for the interpretation of several variants. This exercise represents an approach to help realize the core charter of the Global Alliance for Genomics and Health (GA4GH): to responsibly share genomic data for the benefit of human health.

bioinformatics↗

bioRxiv2021

Unsupervised explainable AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome

In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: unsupervised and explainable AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of the viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4~6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers appeared after the epidemic start could be connected to mutations. Because BLSOM is an explainable AI, BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explained BLSOMs for various topics. The tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explained BLSOMs for various eukaryotes, such as fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found evident enrichments in transcription factor-binding sequences (TFBSs) in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) were separated by the corresponding amino acid.

bioinformatics↗

bioRxiv2021

In vivo KRAS G12D/V Degradation Mediated by CANDDY Using a Modified Proteasome Inhibitor

"Undruggable" proteins, such as RAS proteins, remain problematic despite efforts to discover inhibitors against them. KRAS mutants are prevalent in human cancers. Recently, the KRAS G12C inhibitor have been clinically approved, but inhibitors for KRAS G12D/V are still under development. Here, we described the development of a novel chemical knockdown strategy, termed CANDDY (Chemical knockdown with Affinity aNd Degradation DYnamics). This strategy involves a CANDDY tag modified from a proteasome inhibitor inducing direct proteasomal degradation. We constructed TUS-007 as a multispecific small molecule tethered from a KRAS interactor and CANDDY tag to target KRAS G12D/V. We confirmed that the degradation by TUS-007 was independent of target ubiquitination. This allows to solve a laborious design of matchmaker in the current ubiquitination-dependent proteolysis technology. And TUS-007 successfully suppressed tumors due to in vivo degradation of KRAS G12D/V. The CANDDY technology could represent a simple and rational strategy to degrade currently "undruggable" proteins.

pharmacology and toxicology↗

bioRxiv2021

Time-series trend of pandemic SARS-CoV-2 variants visualized using batch-learning self-organizing map for oligonucleotide compositions

To confront the global threat of coronavirus disease 2019, a massive number of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome sequences have been decoded, with the results promptly released through the GISAID database. Based on variant types, eight clades have already been defined in GISAID, but the diversity can be far greater. Owing to the explosive increase in available sequences, it is important to develop new technologies that can easily grasp the whole picture of the big-sequence data and support efficient knowledge discovery. An ability to efficiently clarify the detailed time-series changes in genome-wide mutation patterns will enable us to promptly identify and characterize dangerous variants that rapidly increase their population frequency. Here, we collectively analyzed over 150,000 SARS-CoV-2 genomes to understand their overall features and time-dependent changes using a batch-learning self-organizing map (BLSOM) for oligonucleotide composition, which is an unsupervised machine learning method. BLSOM can separate clades defined by GISAID with high precision, and each clade is subdivided into clusters, which shows a differential increase/decrease pattern based on geographic region and time. This allowed us to identify prevalent strains in each region and to show the commonality and diversity of the prevalent strains. Comprehensive characterization of the oligonucleotide composition of SARS-CoV-2 and elucidation of time-series trends of the population frequency of variants can clarify the viral adaptation processes after invasion into the human population and the time-dependent trend of prevalent epidemic strains across various regions, such as continents.

bioinformatics↗

bioRxiv2021

Human cell-dependent, directional, time-dependent changes in the mono- and oligonucleotide compositions of SARS-CoV-2 genomes

BackgroundWhen a virus that has grown in a nonhuman host starts an epidemic in the human population, human cells may not provide growth conditions ideal for the virus. Therefore, the invasion of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which is usually prevalent in the bat population, into the human population is thought to have necessitated changes in the viral genome for efficient growth in the new environment. In the present study, to understand host-dependent changes in coronavirus genomes, we focused on the mono- and oligonucleotide compositions of SARS-CoV-2 genomes and investigated how these compositions changed time-dependently in the human cellular environment. We also compared the oligonucleotide compositions of SARS-CoV-2 and other coronaviruses prevalent in humans or bats to investigate the causes of changes in the host environment. ResultsTime-series analyses of changes in the nucleotide compositions of SARS-CoV-2 genomes revealed a group of mono- and oligonucleotides whose compositions changed in a common direction for all clades, even though viruses belonging to different clades should evolve independently. Interestingly, the compositions of these oligonucleotides changed towards those of coronaviruses that have been prevalent in humans for a long period and away from those of bat coronaviruses. ConclusionsClade-independent, time-dependent changes are thought to have biological significance and should relate to viral adaptation to a new host environment, providing important clues for understanding viral host adaptation mechanisms.

bioinformatics↗

bioRxiv2020

Unsupervised explainable AI for simultaneous molecular evolutionary study of forty thousand SARS-CoV-2 genomes

Unsupervised AI (artificial intelligence) can obtain novel knowledge from big data without particular models or prior knowledge and is highly desirable for unveiling hidden features in big data. SARS-CoV-2 poses a serious threat to public health and one important issue in characterizing this fast-evolving virus is to elucidate various aspects of their genome sequence changes. We previously established unsupervised AI, a BLSOM (batch-learning SOM), which can analyze five million genomic sequences simultaneously. The present study applied the BLSOM to the oligonucleotide compositions of forty thousand SARS-CoV-2 genomes. While only the oligonucleotide composition was given, the obtained clusters of genomes corresponded primarily to known main clades and internal divisions in the main clades. Since the BLSOM is explainable AI, it reveals which features of the oligonucleotide composition are responsible for clade clustering. The BLSOM has powerful image display capabilities and enables efficient knowledge discovery about viral evolutionary processes.

evolutionary biology↗

bioRxiv2020

A unique neurogenomic state emerges after aggressive confrontations in males of the fish Betta splendens

Territorial defense involves frequent aggressive confrontations with competitors, but little is known about how brain-transcriptomic profiles change between individuals competing for territory establishment. Our previous study elucidated that brain-transcriptomic synchronization occurs in a pair-specific manner between two males of the fish Betta splendens during fighting, reflecting a mutual assessment process between them at the level of gene expression. Here we evaluated how the brain-transcriptomic profiles of opponents change immediately after shifting their social status (i.e., the winner/loser has emerged) and 30 min after this shift. We showed that unique and carryover hypotheses can be adapted to this system, in which changes in the expression of certain genes are unique to different fighting stages and in which the expression patterns of certain genes are transiently or persistently changed across all fighting stages. Interestingly, the specificity of the brain-transcriptomic synchronization of a pair during fighting was gradually lost after fighting ceased, because of the decrease in the variance in gene expression across all individuals, leading to the emergence of a basal neurogenomic state. Strikingly, this unique state was more basal than the state that existed in the before-fighting group and resulted in the reduced and consistent expression of genes across all individuals. In spite of the consistent and basal overall gene expression in each individual in this state, expression changes for genes related to metabolism, learning and memory, and autism still differentiated losers from winners. The fighting system using male B. splendens thus provides a promising platform for investigating neurogenomic states of aggression in vertebrates. Author summaryCompetitive interactions involve complex decision-making tasks that are shaped by mutual feedback between participants. When two animals interact, transcriptomes across their brains synchronize in a way that reflects how they assess and predict the others fighting ability and react to each others decisions. Here, we elucidated the gradual loss of brain-transcriptomic synchrony between interacting opponents after their interaction ceased, leading to the emergence of a basal neurogenomic state, in which the variations in gene expression were reduced to a minimum among all individuals. This basal neurogenomic state shares common characteristics with the hibernation state, which animals adopt to minimize their metabolic rates to cope with harsh environmental conditions. We demonstrated that this unique neurogenomic state, which is newly characterized in the present study, is composed of the expression of a unique set of genes, each of which was presumably minimally required for survival, providing a hypothesis that this state represents the smallest unit of neurogenomic activity for sustaining an active life.

molecular biology↗

bioRxiv2020

Population-wide Screening for Germline Variants of Hereditary Cancer Genes in 12K Unselected Japanese Colorectal Cancers and 27K Controls

Background & AimsColorectal cancer (CRC) is one of the most common cancers in Western countries and Japan. Currently, a few % of CRCs can be attributed to recognizable hereditary germline variants of known CRC susceptibility genes, predominantly the DNA mismatch repair genes. To establish a universal screening strategy for hereditary CRCs, it is necessary to explore the prevalence of hereditary CRC and pathogenic variants of multiple cancer-predisposing genes in non-European populations. MethodsWe analyzed the coding regions of 27 cancer-predisposing genes, including mismatch repair genes, APC, and BRCA1/2, in 12,503 unselected Japanese CRC patients and 23,705 controls aged [≥] 60 years without any personal or family history of cancer by target sequencing and genome-wide SNP chip data. Their clinical significance was assessed using ClinVar and the guidelines by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP). ResultsWe identified 4,804 variants in the 27 genes and annotated them as 397 pathogenic variants, 941 benign variants, and 3,466 variants of uncertain significance, of which 43.6% were registered in neither ClinVar nor dbSNP. In total, 3.3% of the unselected CRC patients and 1.5% of the controls had a pathogenic variant of the 27 genes. The pathogenic variants of MSH2 (odds ratio (OR) =18.1), MLH1 (OR=8.6), MSH6 (OR=4.9), APC (OR=49.4), BRIP1 (OR=3.6), BRCA1 (OR=2.6), BRCA2 (OR=1.9), and TP53 (OR=1.7) were significantly associated with CRC development in the Japanese population (P-values < 0.01, FDR<0.05). Furthermore, we confirmed copy number variants (CNVs) of MSH2/EPCAM, MLH1, and APC by multiplex ligation-dependent probe amplification (MLPA) and quantitative PCR in this cohort (n = 23), including whole gene duplications of MSH2 and APC. These pathogenic variants were significantly associated with the diagnostic age and personal/family history of other types of cancer. In total, at least 3.5% of the Japanese CRC population had a pathogenic variant or CNV of the 27 cancer-predisposing genes. ConclusionsThis is the largest study of CRC heredity in the Asian population and would contribute to the development of guidelines for genetic testing and variant interpretation for heritable CRCs. Universal screening for CRC risk should be assessed in multiple genes, including BRCA1/2 and BRIP1. These data would facilitate risk assessment of cancer and optimize the screening strategy.

genetics↗

bioRxiv2020

Intron retention as a new marker of the pre-disease state and its recovery to the normal state by a traditional Japanese multi-herbal medicine

Intron retention (IR) is an important regulatory mechanism that affects gene expression and protein functions. Using klotho mice at the pre-symptomatic state, we discovered that retained-introns accumulated in several organs including the liver and that among these retained introns in the liver a subset was recovered to the normal state by a Japanese traditional herbal medicine. This is the first report of IR recovery by a medicine. IR-recovered genes fell into two categories: those involved in liver-specific metabolism and in splicing. Metabolome analysis of the liver showed that the klotho mice were under starvation stress. In addition, our differentially expressed gene analysis showed that liver metabolism was actually recovered by the herbal medicine at the transcriptional level. By analogy with the widespread accumulation of intron-retained pre-mRNAs induced by heat shock stress, we propose a model in which retained-introns in klotho mice were induced by an aging stress and in which this medicine-related IR recovery is indicative of the actual recovery of liver-specific metabolic function to the healthy state. Accumulation of retained-introns was also observed at the pre-symptomatic state of aging in wild-type mice and may be an excellent marker for this state in general.

molecular biology↗

bioRxiv2019

Odd-paired is a late-acting pioneer factor coordinating with Zelda to broadly regulate gene expression in early embryos

Pioneer factors such as Zelda help initiate zygotic transcription in Drosophila early embryos, but whether other factors support this dynamic process is unclear. Odd-paired (Opa), a zinc-finger transcription factor expressed at cellularization, controls transition of genes from pair-rule to segmental patterns along the anterior-posterior axis. Finding that Opa also regulates late expression through enhancer sog_Distal, along the dorso-ventral axis, we hypothesized that Opa acts as a general timing factor. Chromatin-immunoprecipitation (ChIP-seq) confirmed Opa in vivo binding to sog_Distal but also identified widespread binding throughout the genome, comparable to Zelda. Furthermore, chromatin assays (ATAC-seq) demonstrate that Opa, like Zelda, influences chromatin accessibility genome-wide, suggesting both are pioneer factors with common as well as distinct targets. Lastly, embryos lacking opa exhibit widespread, late patterning defects spanning both axes. Collectively, these data suggest Opa, a general timing factor and likely a late-acting pioneer factor, heralds in a secondary wave of zygotic gene expression.

developmental biology↗

bioRxiv2019

Evaluation of ACMG Rules for In silico Evidence Strength Using An Independent Computational Tool Absent of Circularities on ATM and CHEK2 Breast Cancer Cases and Controls

The American College of Medical Genetics and Genomics (ACMG) guidelines for sequence variant classification include two criteria, PP3 and BP4, for combining computational data with other evidence types contributing to sequence variant classification. PP3 and BP4 assert that computational modeling can provide \"Supporting\" evidence for or against pathogenicity within the ACMG framework. Here, leveraging a meta-analysis of ATM and CHEK2 breast cancer case-control mutation screening data, we evaluate the strength of evidence determined from the relatively simple computational tool Align-GVGD. Importantly, application of Align-GVGD to these ATM and CHEK2 data is free of logical circularities, hidden multiple testing, and use of other ACMG evidence types. For both genes, rare missense substitutions that are assigned the most severe Align-GVGD grade exceed a \"Moderate pathogenic\" evidence threshold when analyzed in a Bayesian framework; accordingly, we argue that the ACMG classification rules be updated for well-calibrated computational tools. Additionally, congruent with previous analyses of ATM and CHEK2 case-control mutation screening data, we find that both genes have a considerable burden of pathogenic missense substitutions, and that severe ATM rare missense have increased odds ratios compared to truncating and splice junction variants, indicative of a potential dominant-negative effect for those missense substitutions.

genetics↗

bioRxiv2019

An annotation dataset facilitates automatic annotation of whole-brain activity imaging of C. elegans

Annotation of cell identity is an essential process in neuroscience that allows for comparing neural activities across different animals. In C. elegans, although unique identities have been assigned to all neurons, the number of annotatable neurons in an intact animal is limited in practice and comprehensive methods for cell annotation are required. Here we propose an efficient annotation method that can be integrated with the whole-brain imaging technique. We systematically identified neurons in the head region of 311 adult worms using 35 cell-specific promoters and created a dataset of the expression patterns and the positions of the neurons. The large positional variations illustrated the difficulty of the annotation task. We investigated multiple combinations of cell-specific promoters to tackle this problem. We also developed an automatic annotation method with human interaction functionality that facilitates annotation for whole-brain imaging.

neuroscience↗

bioRxiv2019

Cold Vacuum Extracts of Double Cherry Blossom (Gosen-Sakura) Leaves Show Antitumor Activity

The present research examines the possibility of finding bio-molecular compounds from the double cherry blossom (termed as Gosen-Sakura of Gosen-city, Niigata-prefecture, Japan) leaves, which have been long used in the preparation of the traditional Japanese sweet (wagashi) - sakura-mochi. Based on its indicated anti-microbial properties historically, our study provides a new low temperature vacuum extraction method for extracting near natural form of water soluble leaf (cell) extracts from the Gosen-Sakura, and demonstrates the presence of some novel compound(s) with anti-tumor cell lines proliferation inhibitory affects through the MTT assay. To our knowledge, no reports exist on the sakura tree leaf (cell) extracts inhibiting tumor cell line growth. We further examined and compared the effects of known compounds with anti-tumor activity, coumarin and benzyl alcohol with Gosen-Sakura leaf extract; results lead us to hypothesize that the Gosen-Sakura leaf extract contains substance(s) other than the above 2 known compounds, with antitumor effect. Additionally, we speculate on the underlying mechanism of action of the Gosen-Sakura leaf extract by targeting cell division at the point of DNA synthesis and causing apoptosis. In conclusion, we present scientific evidence on the presence of a certain novel biomolecule(s), with anti-tumor activity, in the Gosen-Sakura leaf which has been long used as a Japanese - the sakura-mochi.

plant biology↗

bioRxiv2019

Long-read sequencing identifies GGC repeat expansion in human-specific NOTCH2NLC associated with neuronal intranuclear inclusion disease

Neuronal intranuclear inclusion disease (NIID) is a progressive neurodegenerative disease characterized by eosinophilic hyaline intranuclear inclusions in neuronal and somatic cells. The wide range of clinical manifestations in NIID makes ante-mortem diagnosis difficult 1-8, but skin biopsy realized its ante-mortem diagnosis 9,10 and many NIID cases have been diagnosed by skin biopsy11,12. Most cases of NIID are sporadic, but several familial cases are known. Using a large NIID family, we conducted linkage mapping, found a 58.1-Mb linked-region at 1p22.1-q21.3 with a maximum logarithm of odds (LOD) score of 4.21, and successfully identified a GGC repeat expansion in the 5 portion of NOTCH2NLC in all affected members by long-read sequencing, but not in unaffected members. We further found the similar expansions in additional 8 unrelated families with NIID as well as 39 sporadic NIID patients. Repeat-primed PCR consistently detected the GGC repeat expansion in all the familial and sporadic patients diagnosed by skin biopsy, but never in unaffected family members nor 200 controls. This shows that pathogenic changes in a human-specific gene evolutionarily generated by segmental duplication indeed causes a human disease.

genetics↗

bioRxiv2017

An ensemble learning approach to auto-annotation for whole-brain C. elegans imaging

Shifting from individual neuron analysis to whole-brain neural network analysis opens up new research opportunities for Caenorhabditis elegans (C. elegans). An automated data processing pipeline, including neuron detection, segmentation, tracking and annotation, will significantly improve the efficiency of analyzing whole-brain C. elegans imaging. The resulting large data sets may motivate new scientific discovery by exploiting many promising analysis tools for big data. In this study, we focus on the development of an automated annotation procedure. With only around 180 neurons in the central nervous system of a C. elegans, the annotation of each individual neuron still remains a major challenge because of the high density in space, similarity in neuron shape, unpredictable distortion of the worms head during motion, intrinsic variations during worm development, etc. We use an ensemble learning approach to achieve around 25% error for a test based on real experimental data. Also, we demonstrate the importance of exploring extra source of information for annotation other than the neuron positions.

bioinformatics↗