Biology subjects

Hayashi, T.

Publications and source records attributed to Hayashi, T..

102 records · Page 6Linked to original sources

bioRxiv2019

An alternative nisin A resistance mechanism affects virulence in Staphylococcus aureus

Nisin A is a bacteriocin produced by Lactococcus lactis and is widely used as a food preservative. Staphylococcus aureus has the BraRS-VraDE system providing resistance against low concentrations of nisin A. The BraRS is one of a two-component system that senses nisin A by BraS and finally induces the expression of ABC transporter VraDE by phosphorylated BraR. Previously, we isolated a highly nisin A resistant strain with increased VraDE expression due to a mutation of braRS. In this study, we isolated a BraRS-VraDE-independent, nisin A resistant mutant from S. aureus MW2. These mutants, designated SAN2 (S. aureus nisin resistant) and SAN469, had a mutation in pmtR (MW1875) which encodes a transcriptional regulator responsible for the expression of the pmtA-D operon. As a result, this mutant exhibited a high level of constitutive production of PmtA-D, a transporter responsible for the export of phenol soluble modulin (PSM). We also obtained two pmtA-D overexpressing, nisin A resistant mutants which contained a point mutation in pmtR from other S. aureus strains.\n\nCharacterization of the mutants revealed that they have a decreased susceptibility to human beta defensin-3 and LL37, which are innate immune factors. Additionally, these mutants showed higher hemolytic activity than the MW2 original strain. Furthermore, in a mouse bacteremia model, the SAN2 strain exhibited a lower survival rate than the MW2 original strain. These results indicate that the over expression of pmtA-D due to the pmtR mutation is an alternative nisin A resistance, which also affects virulence in S. aureus.\n\nAuthor SummaryRecently, the emergence of antibiotic resistant bacteria such as MRSA, MDRP and CRE have brought serious problems for chemotherapy in the world. In addition, many antibacterial agents such as disinfectants and food additives are widely used. Therefore, it raises the possibility that bacteria are becoming resistant to all antibacterial agents. In this study, we investigated whether S. aureus become resistant against nisin A, one of the food additives. Finally, we isolated nisin A highly resistant S. aureus strains. Among these strains, we identified that one strain designated as SAN2 showed nisin A resistance by the overproduction of Pmts which were involved in the secretion of virulence factors called PSMs. We identified a mutation of pmtR gene encoding a regulator for pmt genes. SAN2 strain showed the decreased susceptibility to human antimicrobial peptides and the increased hemolytic activity. Finally, SAN2 showed higher lethal activity in mouse bacteremia model. Our study provides new insights into that S. aureus may cause resistance against various antibacterial food additives, together with the altering the virulence.

microbiology↗

bioRxiv2019

Benchmarking Single-Cell RNA Sequencing Protocols for Cell Atlas Projects

Single-cell RNA sequencing (scRNA-seq) is the leading technique for charting the molecular properties of individual cells. The latest methods are scalable to thousands of cells, enabling in-depth characterization of sample composition without prior knowledge. However, there are important differences between scRNA-seq techniques, and it remains unclear which are the most suitable protocols for drawing cell atlases of tissues, organs and organisms. We have generated benchmark datasets to systematically evaluate techniques in terms of their power to comprehensively describe cell types and states. We performed a multi-center study comparing 13 commonly used single-cell and single-nucleus RNA-seq protocols using a highly heterogeneous reference sample resource. Comparative and integrative analysis at cell type and state level revealed marked differences in protocol performance, highlighting a series of key features for cell atlas projects. These should be considered when defining guidelines and standards for international consortia, such as the Human Cell Atlas project.

genomics↗

bioRxiv2019

Towards HCP-Style Macaque Connectomes: 24-Channel 3T Multi-Array Coil, MRI Sequences and Preprocessing

Macaque monkeys are an important model species for understanding cortical organization of primates, yet tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the relatively thin macaque cortex, high spatial, temporal, and angular resolutions are required while maintaining high signal-to-noise ratio to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enabled adaptation of the Human Connectome Project (HCP) image acquisition protocols to the macaque brain. We also adapted HCP preprocessing methods optimized for the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provided high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold acceleration for dMRI and fMRI, respectively. Automated parcellation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available for humans.\n\nHighlights[tpltrtarr] 24-channel 3T MR receive coil designed for the smaller macaque brain.\n[tpltrtarr]In vivo macaque imaging protocols adapted according to guidelines from the HCP.\n[tpltrtarr]Parallel imaging yields five- and four-fold acceleration in fMRI and dMRI sampling.\n[tpltrtarr]HCPs minimal preprocessing and denoising pipelines adapted for macaques.\n[tpltrtarr]The multi-modal MRI data show considerable promise for HCP-style analyses.

neuroscience↗

bioRxiv2019

Injection practices in 2011-2015: A rapid review using data from the Demographic and Health Surveys (DHS)

BackgroundReuse of injection devices to give healthcare injections decreased from 39.8% to 5.5% between 2000 and 2010, but trends since 2011 have not been described. We reviewed results of Demographic and Health Surveys (DHS) to describe injection practices worldwide from 2011 to 2015.\n\nMethodsWe searched the DHS Internet site for data published on injection practices conducted in countries from 2011 to 2015, extracted information on frequency (number of healthcare injections per person in the last 12 months) and safety (proportion of syringes and needles taken from a new, unopened package). We compared gender groups and WHO regions in terms of frequency and safety. For countries with data available, we compared injection practices 2004- 2010 and 2011-2015.\n\nResultsSince 2011, 40 of 92 countries (43%) that had DHS surveys reported on injection practices. On average, the frequency of injection was 1.64 per person per year (from 3.84 in WHO Eastern Mediterranean region to 1.18 in WHO African region). Among those, 96.1% of injections reportedly used new injection devices (from 90.2% in the WHO Eastern Mediterranean region to 98.8% in the WHO Western Pacific region). On average, women received more injections per year (1.85) than men (1.41). Among 16 (40%) countries with data up to 2010 and since 2011, 69% improved in terms of safety. The annual number of unsafe injections was reduced in 81% of countries, with the notable exception of Pakistan where the number of unsafe injections was the highest and did not decrease between 2006 and 2012.\n\nConclusionInjection practices have continued to improve in most countries worldwide, although the Eastern Mediterranean region in particular is facing residual unsafe practices that are not improving. Further efforts are needed to completely eliminate unsafe injection practices in health care settings, including through the use of reuse-prevention devices. Despite some limitations, DHS is an easily available method to measure progress over time.

epidemiology↗

bioRxiv2019

Divisively normalized integration of multisensory error information develops motor memories specific to vision and proprioception

Both visual and proprioceptive information contribute to accurate limb movement, but the mechanism of integration of these different modality signals for movement control and learning remains controversial. Here, we aimed to elucidate the mechanism of integration by examining motor adaptation when various combinations of visual and proprioceptive perturbations were applied during reaching movements. We found that the movement corrections by adaptation were explained by a mechanism known as a divisive normalization, which was previously reported to be the mechanism underlying the integration of multisensory signals in neurons. Furthermore, we found evidence that the motor memory for each sensory modality was formed separately and the outputs from these memories were integrated. These results provide a novel view of the utilization of different sensory modality signals in motor control and adaptation.

neuroscience↗

bioRxiv2019

A NMF-based approach to discover overlooked differentially expressed gene regions from single-cell RNA-seq data

Single-cell RNA sequencing has enabled researchers to quantify the transcriptomes of individual cells, infer cell types, and investigate differential expression among cell types, which will lead to a better understanding of the regulatory mechanisms of cell states. Transcript diversity caused by phenomena such as aberrant splicing events have been revealed, and differential expression of previously unannotated transcripts might be overlooked by annotation-based analyses. Accordingly, we have developed an approach to discover overlooked differentially expressed (DE) gene regions that complements annotation-based methods. We applied our algorithm to two datasets and discovered several intriguing DE transcripts, including a transcript related to the modulation of neural stem/progenitor cell differentiation.

bioinformatics↗

bioRxiv2019

Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets

BackgroundRead coverage of RNA sequencing data reflects gene expression and RNA processing events. Single-cell RNA sequencing (scRNA-seq) methods, particularly "full-length" ones, provide read coverage of many individual cells and have the potential to reveal cellular heterogeneity in RNA transcription and processing. However, visualization tools suited to highlighting cell-to-cell heterogeneity in read coverage are still lacking. ResultsHere, we have developed Millefy, a tool for visualizing read coverage of scRNA-seq data in genomic contexts. Millefy is designed to show read coverage of all individual cells at once in genomic contexts and to highlight cell-to-cell heterogeneity in read coverage. By visualizing read coverage of all cells as a heat map and dynamically reordering cells based on diffusion maps, Millefy facilitates discovery of "local" region-specific, cell-to-cell heterogeneity in read coverage, including variability of transcribed regions. ConclusionsMillefy simplifies the examination of cellular heterogeneity in RNA transcription and processing events using scRNA-seq data. Millefy is available as an R package (https://github.com/yuifu/millefy) and a Docker image to help use Millefy on the Jupyter notebook (https://hub.docker.com/r/yuifu/datascience-notebook-millefy).

bioinformatics↗

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↗

bioRxiv2018

A comprehensive reference transcriptome resource for the Iberian ribbed newt Pleurodeles waltl, an emerging model for developmental and regeneration biology

Urodele amphibian newts have unique biological properties, notably including prominent regeneration ability. Iberian ribbed newt, Pleurodeles waltl, is a promising model newt along with the successful development of the easy breeding system and efficient transgenic and genome editing methods. However, genetic information of P. waltl was limited. In the present study, we conducted an intensive transcriptome analysis of P. waltl using RNA-sequencing to build gene models and annotate them. We generated 1.2 billion Illumina reads from a wide variety of samples across 11 different tissues and 9 time points during embryogenesis. They were assembled into 202,788 non-redundant contigs that appear to cover nearly complete (~98%) P. waltl protein-coding genes. Using the gene set as a reference, our gene network analysis identified regeneration-, developmental-stage-, and tissue-specific co-expressed gene modules. Ortholog analyses with other vertebrates revealed the gene repertoire evolution of amphibians which includes urodele-specific loss of bmp4 and duplications of wnt11b. Our transcriptome resource will enhance future research employing this emerging model animal for regeneration research as well as other areas such as developmental biology, stem cell biology, cancer research, ethology and toxico-genomics. These data are available via our portal website, iNewt (http://www.nibb.ac.jp/imori/main/).

genomics↗

bioRxiv2017

Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts (at a rate of 30%-50%) and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes in total from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

genomics↗

bioRxiv2017

A randomized comparison of different hormone replacement protocols for thawed blastocyst transfer

BackgroundThere are no randomized controlled trials evaluating the pregnancy rates after thawed blastocyst transfers in patients treated with various hormone replacement regimens.\n\nMethodsA prospective randomized controlled trial was conducted to evaluate the outcomes in three different hormone replacement protocols for thawed blastocyst transfer. A total of 330 women (median age 38.2 years) who were undergoing IVF at our clinic were enrolled.\n\nResultsSerum estradiol (E2) levels were 267.71 pg/ml in Premarin group, 391.22 pg/ml in Estrogel group and 495.12 pg/ml in Estrana tape group. Therefore, serum E2 levels in Estrana tape group were higher than those of the other two groups (P<0.01). The pregnancy rate in the Estrogel group was higher than that in the Premarin group (30.0% versus 17.3%, P=0.026, odds ratio 2.05, 95% confidence interval: 1.09-3.87). Furthermore, the pregnancy rate in the Estrana tape group was higher than that in the Estrogel group (43.6% versus 30.0%, P=0.036, odds ratio 1.81, 95% confidence interval: 1.04-3.14).\n\nConclusionThe serum E2 levels contributed to differences observed in the pregnancy rate among the three different protocols. Thus, Estrana tape has an advantage as a hormone replacement protocol for thawed blastocyst transfer.

clinical trials↗

bioRxiv2016

SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation

The analysis of RNA-Seq data from individual differentiating cells enables us to reconstruct the differentiation process and the degree of differentiation (in pseudo-time) of each cell. Such analyses can reveal detailed expression dynamics and functional relationships for differentiation. To further elucidate differentiation processes, more insight into gene regulatory networks is required. The pseudo-time can be regarded as time information and, therefore, single-cell RNA-Seq data are time-course data with high time resolution. Although time-course data are useful for inferring networks, conventional inference algorithms for such data suffer from high time complexity when the number of samples and genes is large. Therefore, a novel algorithm is necessary to infer networks from single-cell RNA-Seq during differentiation.\n\nIn this study, we developed the novel and efficient algorithm SCODE to infer regulatory networks, based on ordinary differential equations. We applied SCODE to three single-cell RNA-Seq datasets and confirmed that SCODE can reconstruct observed expression dynamics. We evaluated SCODE by comparing its inferred networks with use of a DNaseI-footprint based network. The performance of SCODE was best for two of the datasets and nearly best for the remaining dataset. We also compared the runtimes and showed that the runtimes for SCODE are significantly shorter than for alternatives. Thus, our algorithm provides a promising approach for further single-cell differentiation analyses.\n\nThe R source code of SCODE is available at https://github.com/hmatsu1226/SCODE.

bioinformatics↗