Biology subjects

Kinoshita, K.

Publications and source records attributed to Kinoshita, K..

32 records · Page 2Linked to original sources

bioRxiv2022

Cryo-EM structures of human zinc transporter ZnT7 reveal the mechanism of Zn2+ uptake into the Golgi apparatus

Zinc ions (Zn2+) are vital to most cells, with the intracellular concentrations of Zn2+ being tightly regulated by multiple zinc transporters located at the plasma and organelle membranes. We herein present the 2.8-2.9 [A]-resolution cryo-EM structures of a Golgi-localized human Zn2+/H+ antiporter ZnT7 (hZnT7) in its outward- and inward-facing forms. Cryo-EM analyses showed that hZnT7 exists as a homodimer via tight interactions in both the cytosolic and transmembrane (TM) regions of two protomers, each of which contains a single Zn2+-binding site in its TM domain. hZnT7 undergoes a TM-helix rearrangement to create a negatively charged cytosolic cavity for Zn2+ entry in the inward-facing form and a widened luminal cavity for Zn2+ release in the outward-facing form. An exceptionally long cytosolic histidine-rich loop characteristic of hZnT7 can bind at least two Zn2+ ions, likely facilitating Zn2+ recruitment from the cytosol. Unique mechanisms of hZnT7-mediated Zn2+ uptake into the Golgi are proposed.

molecular biology↗

bioRxiv2021

Uterus-specific transcriptional regulation underlies eggshell pigment production in Japanese quail

The precursor of heme, protoporphyrin IX (PPIX), accumulates abundantly in the uterus of birds, such as Japanese quail, Coturnix japonica, resulting in brown-speckled eggshells. The molecular basis of PPIX production in the uterus remains largely unknown. Here, we investigated the cause of low PPIX production in a classical Japanese quail mutant exhibiting white eggshells by comparing its gene expression in the uterus with that of the wild type using transcriptome analysis and performed genetic linkage mapping to identify the causative genomic region of the white eggshell phenotype. We showed that 11 genes, including the 5-aminolevulinic acid synthase 1 (ALAS1) and ferroxidase hephaestin-like 1 (HEPHL1) genes, were specifically upregulated in the wild-type uterus and downregulated in the mutant. We mapped the 172 kb candidate genomic region on chromosome 6, which contains several genes, including a part of the paired-like homeodomain 3 (PITX3), which encodes a transcription factor. ALAS1, HEPHL1, and PITX3 were expressed in the apical cells of the luminal epithelium and lamina propria cells of the uterine mucosa of the wild-type quail, and their expression was downregulated in these cells of the mutant quail. Biochemical analysis using uterine homogenates indicated that the restricted availability of 5-aminolevulinic acid is the main cause of low PPIX production. These results suggest that uterus-specific transcriptional regulation of heme-biosynthesis-related genes is an evolutionarily acquired mechanism of eggshell pigment production in Japanese quail.

genetics↗

bioRxiv2021

Prediction and Characterization of Disorder-Order Transition Regions in Proteins by Deep Learning

The biological functions of proteins are traditionally thought to depend on well-defined three-dimensional structures, but many experimental studies have shown that disordered regions lacking fixed three-dimensional structures also have crucial biological roles. In some of these regions, disorder-order transitions are also involved in various biological processes, such as protein-protein interaction and ligand binding. Therefore, it is crucial to study disordered regions and structural transitions for further understanding of protein functions and folding. Owing to the costs and time requirements of experimental identification of natively disordered or transitional regions, the development of effective computational methods is a key research goal. In this study, we used overall residue dependencies and deep representation learning for prediction and reused the obtained disordered regions for the prediction of disorder-order transitions. Two similar and related prediction tasks were combined. Firstly, we developed a novel deep learning method, Res-BiLstm, for residue-wise disordered region prediction. Our method outperformed other predictors with respect to almost all criteria, as evaluated using an independent test set. For disorder-order transition prediction, we proposed a transfer learning method, Res-BiLstm-NN, with an acceptable but unbalanced performance, yielding reasonable results. To grasp underlining biophysical principles of disorder-order transitions, we performed qualitative analyses on the obtained results and discovered that most transitions have strong disordered or ordered preferences, and more transitions are consistent with the ordered state than the disordered state, different from conventional wisdom. To the best of our knowledge, this is the first sizable-scale study of transition prediction. Availabilityhttps://github.com/Yanzziang/Transition_Disorder_Prediction Contactkengo@ecei.tohoku.ac.jp

bioinformatics↗

bioRxiv2020

Japonica Array NEO with increased genome-wide coverage and abundant disease risk SNPs

BackgroundIncreasing the power of genome-wide association studies in diverse populations is important for understanding the genetic determinants of disease risks, and large-scale genotype data are collected by genome cohort and biobank projects all over the world. In particular, ethnic-specific SNP arrays are becoming more important because the use of universal SNP arrays has some limitations in terms of cost-effectiveness and throughput. As part of the Tohoku Medical Megabank Project, which integrates prospective genome cohorts into a biobank, we have been developing a series of Japonica Arrays for genotyping participants based on reference panels constructed from whole-genome sequence data of the Japanese population. ResultsWe designed a novel version of the SNP Array for the Japanese population, called Japonica Array NEO, comprising a total of 666,883 SNPs, including tag SNPs of autosomes and X chromosome with pseudoautosomal regions, SNPs of Y chromosome and mitochondria, and known disease risk SNPs. Among them, 654,246 tag SNPs were selected from an expanded reference panel of 3,552 Japanese using pairwise r2 of linkage disequilibrium measures. Moreover, 28,298 SNPs were included for the evaluation of previously identified disease risk SNPs from the literature and databases, and those present in the Japanese population were extracted using the reference panel. The imputation performance of Japonica Array NEO was assessed by genotyping 286 Japanese samples. We found that the imputation quality r2 and INFO score in the minor allele frequency bin >2.5%-5% were >0.9 and >0.8, respectively, and >12 million markers were imputed with an INFO score >0.8. After verification, Japonica Arrays were used to efficiently genotype cohort participants from the sample selection to perform a quality assessment of the raw data; approximately 130,000 genotyping data of >150,000 participants has already been obtained. ConclusionsJaponica Array NEO is a promising tool for genotyping the Japanese population with genome-wide coverage, contributing to the development of genetic risk scores for this population and further identifying disease risk alleles among individuals of East Asian ancestry.

genomics↗

bioRxiv2020

Novel candidates of pathogenic variants of the BRCA1 and BRCA2 genes in a 3,552 Japanese whole-genome sequence dataset (3.5KJPNv2)

Identification of pathogenic germline variants yet no clinical evidence in BRCA genes has become important in patient care of hereditary breast and ovarian cancer syndrome (HBOC). Computational scoring and prospective cohort studies may help to identify such pathogenic variants. We annotated the variants in the BRCA1 and BRCA2 genes from a dataset of 3,552 whole-genome sequences obtained from members of the genome cohorts by Tohoku Medical Megabank Project (TMM) with the InterVar software. Computational impact scores (CADD_phred and Eigen_raw) and minor allele frequencies (MAF) of pathogenic (P) and likely pathogenic (LP) variants in ClinVar are used for filtration criteria. Familial predispositions in cancers among the 35,000 TMM genome cohort participants are analyzed to verify the pathogenicity. Seven potentially pathogenic variants were newly identified. Carriers of these potential pathogenic variants and definite P and LP variants among participants of the TMM prospective cohort show a statistically significant preponderance in cancer onset in sisters in the self-reported cancer history. Filtering by computational scoring and MAF is useful to identify potential pathogenic variants in BRCA genes for Japanese population. These results will be helpful to follow up the carriers of variants of uncertain significance in the HBOC genes.

genetics↗

bioRxiv2020

Involvement of I-BAR protein IRSp53 in tumor cell growth via extracellular microvesicle secretion

Cellular protrusions mediated by the membrane-deforming I-BAR domain protein IRSp53 are involved in cell migration, including metastasis. However, the role of IRSp53 in cell proliferation remains unclear. Here, we examined the role of IRSp53 in cell proliferation and found that it acts through secretion. Coculture of gingiva squamous carcinoma Ca9-22 cells and their IRSp53-knockout cells restored proliferation to parental Ca9-22 cell levels, suggesting possible secretion dependent on IRSp53. Notably, the amounts of microvesicle fraction proteins that were secreted into the culture medium were reduced in the IRSp53-knockout cells. The IRSp53-knockout cells exhibited decreased phosphorylation of mitogen-activated protein kinase, suggesting the decrease in the proliferation signals. The phosphorylation was restored by the addition of the microvesicles. In mice xenograft Ca9-22 cells, IRSp53-containing particles were secreted around the xenograft, indicating that IRSp53-dependent secretion occurs in vivo. In a tumor mice model, IRSp53 deficiency elongated lifespan. In some human cancers, the higher levels of IRSp53 mRNA expression was found to be correlated with shorter survival years. Therefore, IRSp53 is involved in tumor progression and secretion for cellular proliferation.

cell biology↗

bioRxiv2019

Construction and Integration of Three De Novo Japanese Human Genome Assemblies toward a Population-Specific Reference

The complete sequence of the human genome is used as a reference for next-generation sequencing analyses. However, some ethnic ancestries are under-represented in the international human reference genome (e.g., GRCh37), especially Asian populations, due to a strong bias toward European and African ancestries in a single mosaic haploid genome consisting chiefly of a single donor. Here, we performed de novo assembly of the genomes from three Japanese male individuals using >100x PacBio long reads and Bionano optical maps per sample. We integrated the genomes using the major allele for consensus, and anchored the scaffolds using sequence-tagged site markers from conventional genetic and radiation hybrid maps to reconstruct each chromosome sequence. The resulting genome sequence, designated JG1, is highly contiguous, accurate, and carries the major allele in the majority of single nucleotide variant sites for a Japanese population. We adopted JG1 as the reference for confirmatory exome re-analyses of seven Japanese families with rare diseases and found that re-analysis using JG1 reduced false-positive variant calls versus GRCh37 while retaining disease-causing variants. These results suggest that integrating multiple genome assemblies from a single ethnic population can aid next-generation sequencing analyses of individuals originated from the population.

genomics↗

bioRxiv2019

A Recurrent Neural Network Based Method for Genotype Imputation on Phased Genotype Data

Genotype imputation estimates genotypes of unobserved variants from genotype data of other observed variants, and such estimation is enabled using haplotype data of a large number of other individuals. Although existing imputation methods explicitly use haplotype data, the accessibility of haplotype data is often limited because the agreement is necessary from donors of genome data. We propose a new imputation method that uses bidirectional recurrent neural network, and haplotype data of a large number of individuals are encoded as its model parameters through the training step, which can be shared publicly due to the difficulty in restoring genotype data at the individual-level. In the performance evaluation using the phased genotype data in the 1000 Genomes Project, the imputation accuracy of the proposed method in R2 is comparative with existing methods for variants with MAF [≥] 0.05 and is slightly worse than those of the existing methods for variants with MAF < 0.05. In a scenario of limited availability of haplotype data to the existing methods, the accuracy of the proposed method is higher than those of the existing methods at least for variants with MAF [≥] 0.005. Python code of our implementation for imputation is available at https://github.com/kanamekojima/rnnimp/.

bioinformatics↗

bioRxiv2019

A Pro-Diabetogenic mtDNA Polymorphism in the Mitochondrial-Derived Peptide, MOTS-c

Type 2 Diabetes (T2D) is an emerging public health problem in Asia. An Asian mitochondrial DNA variation m.1382A>C (rs111033358) leads to a K14Q amino acid replacement in MOTS-c, an insulin sensitizing mitochondrial-derived peptide. Meta-analysis of three cohorts (n=27,527, J-MICC, MEC, and TMM) showed that males but not females with the C-allele exhibit a higher prevalence of T2D. Furthermore, in J-MICC, only males with the C-allele in the lowest tertile of physical activity increased their prevalence of T2D, demonstrating a kinesio-genomic interaction. High-fat fed, male mice injected with MOTS-c showed reduced weight and improved glucose tolerance, but not K14Q-MOTS-c treated mice. Like the human data, female mice were unaffected. Mechanistically, K14Q-MOTS-c leads to diminished insulin-sensitization in vitro. Thus, the m.1382A>C polymorphism is associated with susceptibility to T2D in men, possibly interacting with exercise, and contributing to the risk of T2D in sedentary males by reducing the activity of MOTS-c.

genetics↗

bioRxiv2019

3.5KJPNv2, An allele frequency panel of 3,552 Japanese Individuals

The first step towards realizing personalized healthcare is to catalog the genetic variations in a population. Since the dissemination of individual-level genomic information is strictly controlled, it will be useful to construct population-level allele frequency panels and to provide them through easy-to-use interfaces. In the Tohoku Medical Megabank Project, we have sequenced nearly 4,000 individuals from a Japanese population, and constructed an allele frequency panel of 3,552 individuals after removing related samples. The panel is called the 3.5KJPNv2. It was constructed by using a standard pipeline including the 1KGP and gnomAD algorithms to reduce technical biases and to allow comparisons to other populations. Our database is the first largescale panel providing the frequencies of variants present on the X chromosome and on the mitochondria in the Japanese population. All the data are available on our original database at https://jmorp.megabank.tohoku.ac.jp.

genomics↗

bioRxiv2019

Management of family relationship informationfor a three-generation cohort study

A system for inputting and storing family information, named \"BirThree Enrollment,\" was developed to promote a birth and three-generation cohort study (BirThree Cohort Study), and this system was operated successfully. In the study, it was necessary to satisfy many operational demands. Input information is overwritten and changed continuously. Complex kinship information must be quickly and accurately input and corrected, and information on those families not yet recruited must be retrieved. For these purposes, many devices are needed, from an input interface to the internal data structure. In the field of genetic statistics, a simple standard expressive form is used for describing family structure. This form has sufficient information for genetics; however, we developed this form further for our purposes in conducting the BirThree Cohort Study. To provide information about family roles as required in the BirThree Cohort Study, we expanded the data structure, and constructed the system that is able to be used for the daily operation. In our system, family pedigree information is stored along with initial clinical information, and enabled the input of all self-reported information to the data base. Operators are able to input this family information before the day is out. As a result, when recruitment is completed, family information will be completed concurrently. Therefore, it is possible to immediately know a certain persons family structure. By using our system, data correction was improved dramatically, and the system was operated successfully. This study is the first report of the method for storing three generations of family data.

epidemiology↗

bioRxiv2018

Structural basis of HEAT-kleisin interactions in the human condensin I subcomplex

ABSTRUCTCondensin I is a multi-protein complex that plays an essential role in mitotic chromosome assembly and segregation in eukaryotes. It is composed of five subunits: two SMC (SMC2 and SMC4), a kleisin (CAP-H) and two HEAT-repeat (CAP-D2 and -G) subunits. Although it has been shown that balancing acts of the two HEAT-repeat subunits enable this complex to support dynamic assembly of chromosomal axes in vertebrate cells, its underlying mechanisms remain poorly understood. Here, we report the crystal structure of a human condensin I subcomplex comprising hCAP-G and hCAP-H. hCAP-H binds to the concave surfaces of a harp-shaped HEAT repeat domain of hCAP-G. A physical interaction between hCAP-G and hCAP-H is indeed essential for mitotic chromosome assembly recapitulated in Xenopus egg cell-free extracts. Furthermore, this study reveals that the human CAP-G-H subcomplex has the ability to interact with not only a double-stranded DNA, but also a single-stranded DNA, implicating potential, functional divergence of the vertebrate condensin I complex in mitotic chromosome assembly.

cell biology↗

bioRxiv2018

Molecular mechanism of depolarization-dependent inactivation in W366F mutant of Kv1.2

Voltage-gated potassium channels play crucial roles in regulating membrane potential. They are activated by membrane depolarization, allowing the selective permeation of potassium ions across the plasma membrane, and enter a nonconducting state after lasting depolarization of membrane potential, a process known as inactivation. Inactivation in voltage-activated potassium channels occurs through two distinct mechanisms, N-type inactivation and C-type inactivation. C-type inactivation is caused by conformational changes in the extracellular mouth of the channel, while N-type inactivation is elicited by changes in the cytoplasmic mouth of the protein. The W434F-mutated Shaker channel is known as a nonconducting mutant and is in a C-type inactivation state at a depolarizing membrane potential. To clarify the structural properties of C-type inactivated protein, we performed molecular dynamics simulations of the wild-type and W366F (corresponding to W434F in Shaker) mutant of the Kv1.2-2.1 chimera channel. The W366F mutant was in a nearly nonconducting state with a depolarizing voltage and recovered from inactivation with a reverse voltage. Our simulations and 3D-RISM analysis suggested that structural changes in the selective filter upon membrane depolarization trap potassium ions around the entrance of the selectivity filter and prevent ion permeation. This pore restriction is involved in the molecular mechanism of C-type inactivation.

physiology↗

bioRxiv2017

De novo profile generation based on sequence context specificity with the long short-term memory network

Long short-term memory (LSTM) is one of the most attractive deep learning methods to learn time series or contexts of input data. Increasing studies, including biological sequence analyses in bioinformatics, utilize this architecture. Amino acid sequence profiles are widely used for bioinformatics studies, such as sequence similarity searches, multiple alignments, and evolutionary analyses. Currently, many biological sequences are becoming available, and the rapidly increasing amount of sequence data emphasizes the importance of scalable generators of amino acid sequence profiles. We employed the LSTM network and developed a novel profile generator to construct profiles without any assumptions, except for input sequence context. Our method could generate better profiles than existing de novo profile generators, including CSBuild and RPS-BLAST, on the basis of profile-sequence similarity search performance with linear calculation costs against input sequence size. In addition, we analyzed the effects of the memory power of LSTM and found that LSTM had high potential power to detect long-range interactions between amino acids, as in the case of beta-strand formation, which has been a difficult problem in protein bioinformatics using sequence information. We demonstrated the importance of sequence context and the feasibility of LSTM on biological sequence analyses. Our results demonstrated the effectiveness of memories in LSTM and showed that our de novo profile generator, SPBuild, achieved higher performance than that of existing methods for profile prediction of beta-strands, where long-range interactions of amino acids are important and are known to be difficult for the existing window-based prediction methods. Our findings will be useful for the development of other prediction methods related to biological sequences by machine learning methods.

bioinformatics↗