Biology subjects

Okada, T.

Publications and source records attributed to Okada, T..

30 records · Page 2Linked to original sources

bioRxiv2023

Evasion of APOBEC1-mediated Intrinsic Immunity by a Herpesvirus Uracil DNA Glycosylase Is a Determinant of Viral Encephalitis

Herpes simplex virus 1 (HSV-1) is the most common cause of viral encephalitis, which can be lethal or result in severe neurological defects, even when treated with antiviral therapy. We demonstrated that activation of HSV-1 uracil-DNA glycosylase (vUNG) by phosphorylation, essential for its enzymatic activity, counteracted APOBEC1 to promote viral replication and encephalitis in the central nervous system (CNS) of mice. The activation of vUNG protected HSV-1 genomes from APOBEC1-mediated DNA editing, allowing efficient viral replication to occur. The presence of APOBEC1 markedly improved lethal encephalitis in mice infected with an HSV-1 mutant carrying a mutation in the phosphorylation site and an UNG inhibitor protected wild-type HSV-1-infected mice from lethal encephalitis. These findings re-define vUNG as an important factor that allows evasion from intrinsic anti-viral immunity mediated by APOBEC1 in the CNS, and suggest a new therapeutic approach for the treatment of fetal and critical HSV-1 encephalitis.

microbiology↗

bioRxiv2023

Engineering a highly durable adeno-associated virus receptor for analytical applications

Adeno-associated virus (AAV) is a major viral vector used in gene therapy. There are multiple AAV serotypes, and many engineered AAV serotypes with modified capsids altering tissue tropism are enthusiastically being developed. The universal AAV receptor (AAVR) is an essential receptor for multiple AAV infections. Since most AAV serotypes used in gene therapy infect cells via interaction with AAVR, the quantification of the vector-binding ability of AAV to AAVR could be an important quality check for therapeutic AAV vectors. To enable a steady evaluation of the AAV-AAVR interaction, we created an engineered AAVR through mutagenesis. Engineered AAVR showed high durability against acid while retaining its AAV-binding activity and an affinity chromatography column with engineered AAVR was also developed. This column enabled repeated binding and acid dissociation measurements of AAVR with various AAV serotypes. Our data showed that the binding affinities of AAV to AAVR were diverse among serotypes, providing insight into the relationship with the infection efficiency of AAV vectors. Thus, this affinity column can be used in process development for quality checks, quantitating capsid titers, and affinity purification of AAV vectors. Furthermore, this column may work for a useful tool of novel AAV vector capsid engineering.

bioengineering↗

bioRxiv2022

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we dont yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift will be informative for parameterizing evolutionary models and studying potential mechanisms for increased drift. Author SummaryThe transmission of pathogens like SARS-CoV-2 is strongly affected by chance effects in the contact process between infected and susceptible individuals, collectively referred to as random genetic drift. We have an incomplete understanding of how genetic drift changes across time and locations. To address this gap, we developed a computational method that infers the strength of genetic drift from time series genomic data that corrects for non-biological noise and is computationally scalable to the large numbers of sequences available for SARS-CoV-2, overcoming a major challenge of existing methods. Using this method, we quantified the strength of genetic drift for SARS-CoV-2 transmission in England throughout time and across locations. These estimates constrain potential mechanisms and help parameterize models of SARS-CoV-2 evolution. More generally, the computational scalability of our method will become more important as increasingly large genomic datasets become more common.

evolutionary biology↗

bioRxiv2022

Distance-based global analysis of consistent cis-bonds in protein backbones

Biological polypeptides are known to contain cis-linkage in their main chain as a minor but important feature. Such anomalous connection of amino acids has different structural and functional effects on proteins. Experimental evidence of cis-bonds in proteins is mainly obtained using X-ray crystallography and other methods in the field of structural biology. To date, extensive analyses have been carried out on the experimentally found cis-bonds using the Protein Data Bank entry bases and/or residue bases; however, their consistency in each protein has not been examined on a global scale. Data accumulation and advances in methodology enable the use of new approaches from a proteomic point of view. Here, we sought to describe a simple procedure for the detection and confirmation of cis-bonds from a set of experimental coordinates for a protein to discriminate this type of bond from isomerizable and/or misassigned bonds. The resulting set of consistent cis bonds provides unprecedented insights into the trend of "high cis content" proteins and the upper limit of consistent cis bonds per polypeptide length. Recognizing such limit would not only be important for a practical check of upcoming structures, but also for the design of novel protein folds beyond the evolutionally-acquired repertoire.

biophysics↗

bioRxiv2021

Non-glycosylated Seipin to Cause a Motor Neuron Disease Induces ER stress and Apoptosis by Inactivating the ER Calcium Pump SERCA2b

A causal relationship between endoplasmic reticulum (ER) stress and the development of neurodegenerative diseases remains controversial. Here, we focused on Seipinopathy, a dominant motor neuron disease, based on the finding that its causal gene product, Seipin, is a hairpin-like transmembrane protein in the ER. Gain-of-function mutations of Seipin produce non-glycosylated Seipin (ngSeipin), which was previously shown to induce ER stress and apoptosis at both cell and mouse levels albeit with no clarified mechanism. We found that aggregation-prone ngSeipin dominantly inactivated SERCA2b, the major calcium pump in the ER, and decreased the calcium concentration in the ER, leading to ER stress and apoptosis. This inactivation required oligomerization of ngSeipin and direct interaction of the ngSeipin C-terminus with SERCA2b, and was observed in Seipin-deficient human colorectal carcinoma-derived cells (HCT116) expressing ngSeipin at a level comparable with that in neuroblastoma cells (SH-SY5T). Our results thus provide a new direction to controversy noted above.

cell biology↗

bioRxiv2021

Realization of phosphorylation hypothesis of sleep by mammalian CaMKIIβ

The reduced sleep duration observed in Camk2a and Camk2b knockout mice revealed the role of Ca2+/calmodulin-dependent protein kinase II (CaMKII)/CAMKII{beta} as sleep-promoting kinases and lead to the phosphorylation hypothesis of sleep. However, the underlying mechanism of sleep regulation by kinases and protein phosphorylation is largely unknown. Here, we demonstrate that the phosphorylation states of CaMKII{beta} regulates sleep duration and sleep needs. Importantly, the activation or inhibition of CaMKII{beta} can increase or decrease sleep duration by almost two-fold, supporting the role of CaMKII{beta} as a core sleep regulator in mammals. This sleep regulation depends on the kinase activity of CaMKII{beta} in excitatory neurons. Furthermore, CaMKII{beta} mutants mimicking different phosphorylation states can regulate various sleep steps including sleep induction, sleep maintenance, and sleep cancelation. Key CaMKII{beta} residues responsible for the mode switch undergo ordered (auto-)phosphorylation. We thus propose that ordered multi-site phosphorylation of CaMKII{beta} underlies multi-step sleep regulation in mammals.

neuroscience↗

bioRxiv2021

Dynamic sampling bias and overdispersion induced by skewed offspring distributions

Natural populations often show enhanced genetic drift consistent with a strong skew in their offspring number distribution. The skew arises because the variability of family sizes is either inherently strong or amplified by population expansions, leading to so-called jackpot events. The resulting allele frequency fluctuations are large and, therefore, challenge standard models of population genetics, which assume sufficiently narrow offspring distributions. While the neutral dynamics backward in time can be readily analyzed using coalescent approaches, we still know little about the effect of broad offspring distributions on the dynamics forward in time, especially with selection. Here, we employ an exact asymptotic analysis combined with a scaling hypothesis to demonstrate that over-dispersed frequency trajectories emerge from the competition of conventional forces, such as selection or mutations, with an emerging time-dependent sampling bias against the minor allele. The sampling bias arises from the characteristic time-dependence of the largest sampled family size within each allelic type. Using this insight, we establish simple scaling relations for allele frequency fluctuations, fixation probabilities, extinction times, and the site frequency spectra that arise when offspring numbers are distributed according to a power law n-(1+). To demonstrate that this coarse-grained model captures a wide variety of non-equilibrium dynamics, we validate our results in traveling waves, where the phenomenon of gene surfing can produce any exponent 1 < < 2. We argue that the concept of a dynamic sampling bias is useful generally to develop both intuition and statistical tests for the unusual dynamics of populations with skewed offspring distributions, which can confound commonly used tests for selection or demographic history.

evolutionary biology↗

bioRxiv2020

Origin of diverse phosphorylation patterns in the ERBB system

Intercellular signals induce various cellular responses, including growth, proliferation, and differentiation, via the dynamic processes of signal transduction pathways. For cell-fate decisions, ligand-binding induces the phosphorylation of ERBB receptors, which in turn activate downstream molecules. The ERBB family includes four subtypes, which diverged through two gene duplications from a common ancestor, of different kinetic properties. Differences in the expression patterns of the subtypes have been reported between different organs in the human body. However, how these different kinetic and expression properties influence the diverse phosphorylation dynamics of ERBB proteins is not well understood. Here we study the phosphorylation dynamics by experimental and mathematical analyses. The experimental measurements clarified that the phosphorylation dynamics heavily depend on the ERBB expression profiles. We developed a mathematical model consisting of the four subtypes as monomers, homodimers and heterodimers and estimated the rate constants governing the phosphorylation dynamics from the experimental data. To understand the origin of the diversity of the phosphorylation responses of the ERBB system, we analyzed the expression profiles and reaction rates of the ERBB subtypes. The difference in phosphorylation rates between ERBB subtypes showed a much larger contribution to the diversity of the phosphorylation responses than did the dimerization rates. This result implies that divergent evolution in phosphorylation reactions rather than in dimerization reactions after whole genome duplications was essential for increasing the diversity of the phosphorylation responses. Statement of SignificanceIt is known that the expression patterns of a protein family are different between different organs in the human body. This difference is considered essential for the functional diversity between organs. However, the dynamical processes that translate expression patterns into function are not well understood. Here we study the origin of the diversity in ERBB phosphorylation patterns by combining experimental and mathematical methods. We confirmed experimentally that phosphorylation patterns depend on the ERBB expression profiles. Our mathematical model found that differences in phosphorylation rates made the largest contribution to the diversity of phosphorylation patterns between ERBB subtypes.

systems biology↗

bioRxiv2020

Brain/MINDS Beyond Human Brain MRI Study: Multi-Site Harmonization for Brain Disorders Throughout the Lifespan

Psychiatric and neurological disorders are afflictions of the brain that can affect individuals throughout their lifespan. Many brain magnetic resonance imaging (MRI) studies have been conducted; however, imaging-based biomarkers are not yet well established for diagnostic and therapeutic use. This article describes an outline of the planned study, the Brain/MINDS Beyond human brain MRI project (FY2018 [~] FY2023), which aims to establish clinically-relevant imaging biomarkers with multi-site harmonization by collecting data from healthy traveling subjects (TS) at 13 research sites. Collection of data in psychiatric and neurological disorders across the lifespan is also scheduled at 13 sites, whereas designing measurement procedures, developing and analyzing neuroimaging protocols, and databasing are done at three research sites. The Harmonization protocol (HARP) was established for five high-quality 3T scanners to obtain multimodal brain images including T1 and T2-weighted, resting state and task functional and diffusion-weighted MRI. Data are preprocessed and analyzed using approaches developed by the Human Connectome Project. Preliminary results in 30 TS demonstrated cortical thickness, myelin, functional connectivity measures are comparable across 5 scanners, providing high reproducibility and sensitivity to subject-specific connectome. A total of 75 TS, as well as patients with various psychiatric and neurological disorders, are scheduled to participate in the project, allowing a mixed model statistical harmonization. The HARP protocols are publicly available online, and all the imaging, demographic and clinical information, harmonizing database will also be made available by 2024. To the best of our knowledge, this is the first project to implement a rigorous, prospective harmonization protocol with multi-site TS data. It explores intractable brain disorders across the lifespan and may help to identify the disease-specific pathophysiology and imaging biomarkers for clinical practice.

neuroscience↗

bioRxiv2019

Repertoire of morphable proteins in an organism

All living organisms have evolved to contain a set of proteins with variable physical and chemical properties. Efforts in the field of structural biology have contributed to uncovering the shape and the variability of each component. A set of experimental coordinates for a given protein can be used to define the \"morphness/unmorphness\". Here we show the results of global analysis of more than a thousand E. coli proteins, demonstrating that it would be a comprehensive method of understanding the evolved repertoire in an organism. By collecting \"UnMorphness Factor\" (UMF) determined for each of the proteins, the lowest and the highest boundaries of the experimentally observable structural variation are understood. The distribution of UMFs obtained for an organism is expected to represent how rigid and flexible components are balanced. The present analysis extends to evaluate the growing data from single particle cryo-electron microscopy, providing valuable information on effective interpretation to structural changes of proteins and the supramolecular complexes. The data and the method presented here also conform to FAIR data principles, having potential significance to advance the field of structural and molecular cell biology.

biophysics↗

bioRxiv2018

Does the Diffusion Tensor Model Predict the Neurite Distribution of Cerebral Cortical Gray Matter? - Cortical DTI-NODDI

Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value =3000 sec/mm2). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI does not reasonably characterize cortical microarchitecture.

neuroscience↗

bioRxiv2017

Evaluation of variability in human protein X-ray structures

Systematic analysis of statistical and dynamical properties of proteins is critical to understanding cellular events. Extraction of biologically relevant information from a set of high-resolution structures is important because it can provide mechanistic details behind the functional properties of protein families, enabling rational comparison between families. Most of the current structure comparisons are pairwise-based, which hampers the global analysis of increasing contents in the Protein Data Bank. Additionally, pairing of protein structures introduces uncertainty with respect to reproducibility because it frequently accompanies other settings for superimposition. This study introduces intramolecular distance scoring, for the analysis of human proteins, for each of which at least several high-resolution are available. We show that the results are comprehensively used to overview advances at the atomic level exploration of each protein and protein family. This method, and the interpretation based on model calculations, provide new criteria for understanding specific and non-specific structure variation in a protein, enabling global comparison of the dynamics among a vast variety of proteins from different species.

biophysics↗