Biology subjects

Maeda, N.

Publications and source records attributed to Maeda, N..

9 recordsLinked to original sources

bioRxiv2024

The effect of a short oxygen exposure period on algal biomass degradation and methane formation in eutrophic and oligotrophic lake sediments

Eutrophication is suggested to enhance lacustrine methane emissions, due to enhanced sedimentary decomposition rates of algal biomass, and more frequent occurrence of water column anoxia. We investigated methane emissions from sediments originating from both a eutrophic and oligotrophic lake, and tested the effect of additional algal C inputs. Additionally, we investigated the effect of a pulse supply of oxygen, a mediating measure that is currently being used in the investigated eutrophic lake. Our results show a large legacy effect of eutrophication, but the methane release from new algal biomass additions was the same, although the process proceeded more rapidly in the eutrophic sediments. A short, 3-week pulse of oxygen lowered the emitted methane from both types of sediments by 50%, not only reducing the emissions of algal biomass additions, but also reducing methane emissions from the experiments without fresh organic matter inputs. This effect was relatively long-lasting: its effects were visible for several weeks after anoxic conditions were re-established, making it a potentially interesting measure to lower methane emissions over a longer period. Volatile fatty acid concentrations in the sediments were lowered due to oxygen exposure. Both the methanogenic and methanotrophic community composition showed surprisingly little response to the oxygen or algal biomass pulses. Overall, our results show that providing sediments with a brief pulse of oxygen following an algal bloom event, could strongly mediate the methane emissions following such an event. Such measures could be considered by policy makers to limit greenhouse gas emissions from managed lakes.

molecular biology↗

bioRxiv2024

Asymmetric representation of symmetric semantic information in the human brain

Specific pairs of semantic entities have symmetric relationships, such as word pairs with opposite meanings (e.g., "intelligent" and "stupid"; "human" and "mechanical"). Such semantic symmetry is a key feature of semantic information. However, the representation of symmetric semantic information in the brain is not yet understood. Additionally, it is unclear whether symmetric pairs of semantic information do have symmetric representations in the brain? We addressed this question in a data-driven manner by using the voxelwise modeling of movie-evoked cortical response measured by functional magnetic resonance imaging. In this modeling, response in each voxel was predicted from semantic labels designated for each movie scene. The semantic labels consisted of 30 different items, including 15 pairs of semantically symmetric items. Each item was manually evaluated using a 5-point scale. By localizing the semantic representation associated with each item based on the voxelwise accuracy of brain-response predictions, we found that semantic representations of symmetric item pairs are broadly distributed but with little overlap in the cortex. Additionally, the weight of voxelwise models revealed highly complex, various patterns of cortical representations for each item pair. These results suggest that symmetric semantic information is rather asymmetric and heterogeneous representations in the human brain. Significance statementThis study aimed to investigate if symmetric pairs of semantic information have symmetric representations in the human brain using statistical modeling of functional magnetic resonance imaging signals evoked by naturalistic movies. We built a model based on movie labeling of symmetric semantic items to quantify the cortical representations of symmetric semantic entities. These findings showed that symmetric pairs of semantic entities are represented in widespread cortical regions; however, still exhibit little overlap in localization and heterogeneous representations. These results offer significant insights into the cortical representations of semantic symmetry and advance the understanding of representational structure of semantic information in the human brain.

neuroscience↗

bioRxiv2023

The human immune checkpoint molecule, HLA-G2, induces tolerance in monocytes and dendritic cells via upregulation of PD-L1

Human leukocyte antigen (HLA)-G is a non-classical HLA class I immunomodulatory molecule with restricted expression in the placenta, thymus and regulatory T cells. The spliced isoforms of HLA-G include an 2 domain-deleted isoform, HLA-G2, which specifically binds to the immune checkpoint leukocyte immunoglobulin-like receptor B2 (LILRB2), to suppress immune responses in myelomonocytic cells. We previously reported the structural and receptor binding characteristics of recombinant HLA-G2 protein and its immunosuppressive effects on inflammation in mouse models. However, the function and the mechanism of action of HLA-G2 on human immune cells have not been elucidated. In the present study, we demonstrate the immunosuppressive effect of HLA-G2 on human CD14-positive monocytic cells. HLA-G2 induced the production of the immunosuppressive cytokine, IL-10, and stimulated IL-6/STAT3/indoleamine-2,3-dioxygenase signaling by binding to LILRB2. HLA-G2 binding to LILRB2 also down-regulated cell surface expression of HLA-DR and CD86. Unexpectedly, HLA-G2 up-regulated cell surface expression of PD-L1 in both CD14-positive monocytic cells and interferon-induced dendritic cells (IFN-DCs). This observation suggests HLA-G2/LILRB2 signaling promotes PD-L1 expression. Furthermore, HLA-G2 treatment of IFN-DCs suppressed T cell proliferation in mixed lymphocyte reactions. These findings provide novel insights into the modulation of human immune responses of tolerogenic myelomonocytic cells induced by HLA-G2 binding to LILRB2, and suggest that targeting the HLA-G2-LILRB2 interaction could be a novel approach for immune checkpoint therapy. Significance statementDuring pregnancy, HLA-G isoforms are expressed by fetal trophoblasts to suppress maternal immune responses. Among various HLA-G isoforms, the HLA-G2 homodimer has been expected as an immunosuppressive biologic targeting myelomonocytic antigen-presenting cells via leukocyte immunoglobulin-like receptor B2. We previously reported significant immunosuppressive effects of HLA-G2 in autoimmune mouse models. Here, we first demonstrate that HLA-G2 isoform induces tolerogenic phenotypes of human peripheral immune cells by significantly upregulating an immune checkpoint molecule, PD-L1. Monocyte-derived dendritic cells stimulated by HLA-G2 suppressed T cell proliferation in mixed lymphocyte reactions. These results suggest that HLA-G2 can be a novel candidate for immune checkpoint therapy.

immunology↗

bioRxiv2022

2-Thiouridine is a broad-spectrum antiviral nucleoside analogue against positive-strand RNA viruses

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes significant morbidity and mortality worldwide, seriously impacting not only human health but also the global economy. Furthermore, over 1 million cases of newly emerging or re-emerging viral infections, specifically dengue virus (DENV), are known to occur annually. Because no virus-specific and fully effective treatments against these and many other viruses have been approved, they continue to be responsible for large-scale epidemics and global pandemics. Thus, there is an urgent need for novel, effective therapeutic agents. Here, we identified 2-thiouridine (s2U) as a broad-spectrum antiviral nucleoside analogue that exhibited antiviral activity against SARS-CoV-2 and its variants of concern, including the Delta and Omicron variants, as well as a number of other positive-sense single-stranded RNA (ssRNA+) viruses, including DENV. s2U inhibits RNA synthesis catalyzed by viral RNA-dependent RNA polymerase, thereby reducing viral RNA replication, which improved the survival rate of mice infected with SARS-CoV-2 or DENV in our animal models. Our findings demonstrate that s2U is a potential broad-spectrum antiviral agent not only against SARS-CoV-2 and DENV but other ssRNA+ viruses.

microbiology↗

bioRxiv2022

ADAMTS2 regulates radial neuronal migration by activating TGF-β signaling at the subplate layer of the developing neocortex

During the development of the mammalian brain, neocortical structures are formed by the sequential radial migration of newborn excitatory neurons. The early migrating neurons exhibit a multipolar shape, but they undergo a multipolar-to-bipolar transition at the subplate (SP) layer, where extracellular matrix (ECM) components are abundantly expressed. In this study, we revealed that the TGF-{beta} signaling-related ECM proteins, such as latent TGF-{beta}-binding protein 1 (LTBP1) and fibrillin 2, and TGF-{beta} receptor II (TGF-{beta}RII) and its downstream effector, p-smad2/3, are selectively expressed at the SP layer, suggesting that TGF-{beta} is sequestered in a latent form by forming complexes with these ECM components and then its signaling is activated by ECM remodeling. We found that the migrating multipolar neurons transiently express a disintegrin and metalloproteinase with thrombospondin motif 2 (ADAMTS2), an ECM metalloproteinase, just below the SP layer. Knockdown and knockout of Adamts2 suppressed the multipolar-to-bipolar transition of migrating neurons, and therefore, disturbed radial migration. Similar phenotypes were observed by the perturbation of TGF-{beta} signaling in the migrating neurons. Time-lapse luminescence imaging of TGF-{beta} signaling indicated that ADAMTS2 activates this signaling pathway in the migrating neurons during the multipolar-to-bipolar transition at the SP layer. These results suggest that the ADAMTS2 secreted by the migrating multipolar neurons activates TGF-{beta} signaling by ECM remodeling of the SP layer, leading to the multipolar-to-bipolar transition. We propose that the SP layer plays an essential role in the radial neuronal migration as a signaling center of the developing neocortex. SIGNIFICANCEThe neocortex is formed by the sequential radial migration of newborn neurons, which undergo a multipolar-to-bipolar transition at the subplate (SP) layer. The extracellular matrix (ECM) is abundantly expressed in the SP layer. However, the roles of the ECM in the SP layer have been unclear. We found that migrating neurons transiently express a disintegrin and a metalloproteinase with thrombospondin motif 2 (ADAMTS2), an ECM metalloproteinase, just below the SP layer. We show that ADAMTS2 secreted by multipolar migrating neurons activates TGF-{beta} signaling through remodeling of the ECM in the SP layer, leading to the multipolar-to-bipolar transition. Thus, the SP layer plays an essential role in radial migration as a signaling center of the developing neocortex

neuroscience↗

bioRxiv2022

Decoding Individual Differences in Mental Information from Human Brain Response Predicted by Convolutional Neural Networks

Recent advantages in brain decoding with functional magnetic resonance imaging (fMRI) have enabled us to estimate individual differences in mental information from brain responses to natural stimuli. However, the physical constraints and costs of fMRI measurements prevent brain decoding from achieving real-world applications. We address this issue by building a novel framework to decode individual differences in mental information under natural situations from brain responses predicted using convolutional neural networks (CNNs). Once the CNN-based prediction model is trained using measured response, mental information can be decoded from the predicted responses of individual brains with no need for additional fMRI measurements. The model was found to capture individual-difference patterns consistent with conventional decoding using measured responses in 81/87 items to be decoded. Our framework has great potential to decode personal mental information with low dependence on fMRI measurements, which could help substantially expand the applicability of brain decoding in daily life.

neuroscience↗

bioRxiv2022

Absolute Winding Number Differentiates Spatial Navigation Strategies with Genetic Risk for Alzheimer's Disease

Spatial navigation and orientation are emerging as promising markers for altered cognition in prodromal Alzheimers disease, and even in cognitively normal individuals at risk for Alzheimers disease. The different APOE gene alleles confer various degrees of risk. The APOE2 allele is considered protective, APOE3 is seen as control, while APOE4 carriage is the major known genetic risk for Alzheimers disease. We have used mouse models carrying the three humanized APOE alleles and tested them in a spatial memory task in the Morris water maze. We introduce a new metric, the absolute winding number, to characterize the spatial search strategy, through the shape of the swim path. We show that this metric is robust to noise, and works for small group samples. Moreover, the absolute winding number better differentiated APOE3 carriers, through their straighter swim paths relative to both APOE2 and APOE4 genotypes. Finally, this novel metric was sensitive to sex differences, supporting increased vulnerability in females. We hypothesized differences in spatial memory and navigation strategies are linked to differences in brain networks, and showed that different genotypes have different reliance on the hippocampal and caudate putamen circuits, pointing to a role for white matter connections. Moreover, differences were most pronounced in females. This departure from a hippocampal centric to a brain network approach may open avenues for identifying regions linked to increased risk for Alzheimers disease, before overt disease manifestation. Further exploration of novel biomarkers based on spatial navigation strategies may enlarge the windows of opportunity for interventions. The proposed framework will be significant in dissecting vulnerable circuits associated with cognitive changes in prodromal Alzheimers disease.

neuroscience↗

bioRxiv2020

Behavioral correlates of cortical semantic representations modeled by word vectors

The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field of natural language processing, provide a powerful tool for such quantitative modeling. However, whether semantic representations revealed by the word vector-based models actually capture our perception of semantic information remains unclear, as there has been no study explicitly examining the behavioral correlates of the modeled semantic representations. To address this issue, we compared the semantic structure of nouns and adjectives estimated from word vector-based brain models with that evaluated from human behavior. The brain models were constructed using voxelwise modeling to predict the functional magnetic resonance imaging (fMRI) response to natural movies from semantic contents in each movie scene through a word vector space. The semantic dissimilarity of word representations was then evaluated using the brain models. Meanwhile, data on human behavior reflecting the perception of semantic dissimilarity between words were collected in psychological experiments. We found a significant correlation between brain model- and behavior-derived semantic dissimilarities of words. This finding suggests that semantic representations in the brain modeled via word vectors appropriately capture our perception of word meanings. Author summeryWord vectors, which have been originally developed in the field of engineering (natural language processing), have been extensively leveraged in neuroscience studies to model semantic representations in the human brain. These studies have attempted to model brain semantic representations by associating them with the meanings of thousands of words via a word vector space. However, there has been no study explicitly examining whether the modeled semantic representations actually capture our perception of semantic information. To address this issue, we compared the semantic representational structure of words estimated from word vector-based brain models with that evaluated from behavioral data in psychological experiments. The results revealed a significant correlation between these model- and behavior-derived semantic representational structures of words. This indicates that the brain semantic representations modeled using word vectors actually reflect the human perception of word meanings. Our findings contribute to the establishment of word vector-based brain modeling as a useful tool in studying human semantic processing.

neuroscience↗

bioRxiv2020

Multi-sample Full-length Transcriptome Analysis of 22 Breast Cancer Clinical Specimens with Long-Read Sequencing

Although transcriptome alteration is considered as one of the essential drivers of carcinogenesis, conventional short-read RNAseq technology has limited researchers from directly exploring full-length transcripts, only focusing on individual splice sites. We developed a pipeline for Multi-Sample long-read Transcriptome Assembly, MuSTA, and showed through simulations that it enables construction of transcriptome from the transcripts expressed in target samples and more accurate evaluation of transcript usage. We applied it to 22 breast cancer clinical specimens to successfully acquire cohort-wide full-length transcriptome from long-read RNAseq data. By comparing isoform existence and expression between estrogen receptor positive and triple-negative subtypes, we obtained a comprehensive set of subtype-specific isoforms and differentially used isoforms which consisted of both known and unannotated isoforms. We have also found that exon-intron structure of fusion transcripts tends to depend on their genomic regions, and have found three-piece fusion transcripts that were transcribed from complex structural rearrangements. For example, a three-piece fusion transcript resulted in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and supposed to protect fetus from maternal rejection, and expression of which were increased in several TCGA samples with ERVFRD-1 fusions. Our analyses of real clinical specimens and simulated data provide direct evidence that full-length transcript sequencing in multiple samples can add to our understanding of cancer biology and genomics in general.

genomics↗