Biology subjects

Nakamura, N.

Publications and source records attributed to Nakamura, N..

17 recordsLinked to original sources

bioRxiv2026

A macrocyclic peptide-based fusion inhibitor targeting SARS-CoV-2 Spike S2 subunit

Continuous emergence of SARS-CoV-2 variants carrying mutations in Spike presents a significant challenge for durable antiviral agents. Here we screen for random 13-amino acid non-mimetic macrocyclic peptides that bind to Spike and identify PA-001 that inhibits SARS-CoV-2 infection with high potency at 0.23-2.9 nM as 50% inhibitory concentration (IC50). PA-001 bound to Spike S2 subunit and inhibited the membrane fusion during virus entry. Through drug-resistant selection, we revealed that PA-001 targeted the fusion peptide proximal region (FPPR) in S2, which has not been recognized as a drug target to date. Consistent with its highly conserved amino acid sequences beyond strains, PA-001 exhibited broad antiviral activity against all tested SARS-CoV-2 variants, in contrast to clinically-approved S1-targeting antibodies that lost activity to Omicron variants. PA-001 suppressed SARS-CoV-2 propagation and disease progression in mouse- and hamster-infection models, both by administration prophylactically and therapeutically. Combination therapy with remdesivir further enhanced antiviral profiles. In clinical phase-I trial, PA-001 was well-tolerated and showed high systemic exposure, with 4,300-10,300-fold concentration of IC50 as maximum plasma concentration by single administration to healthy volunteers. These evidence propose FPPR as an unexpected antiviral drug target accessible by macrocyclic peptides and identify PA-001 as a potent anti-SARS-CoV-2 fusion inhibitor.

microbiology↗

bioRxiv2026

An integrated scalable process for adherent cultivated meat production: From proliferative cell selection to safety-verified product development

Cultivated meat can contribute to the global food supply; therefore, establishing efficient production processes is an urgent task to meet the growing demand for sustainable protein. Although cell culture technology has historically focused on suspension cells in the pharmaceutical and, subsequently, cultivated meat industries, the development of efficient processes for most adhesion-dependent cells has lagged, with limited examples reported to date. Therefore, this study used primary duck liver-derived adherent cells to develop and evaluate an integrated three-step meat production process involving pre-culture to select highly proliferative cells, packed-bed bioreactor expansion for mass production, and final processing, including packaging and heating. The established process allowed the efficient growth of selected cell populations while maintaining their proliferative characteristics. Moreover, the developed product met the microbiological and heavy metal safety criteria. Comprehensive compositional analysis (nutritional, amino acid, and fatty acid profiles) revealed that the product exhibited a protein profile distinct from that of conventional duck liver paste, along with a unique lower-fat signature. As productivity is dependent on cell doubling time, culture duration and monthly production were estimated for cells from various animal species. Overall, this study established a practical integrated production process for cultivated meat using adherent cells, providing a technological foundation for cellular agriculture applicable to diverse cell types and useful for future food supply diversification. GraphicalAbstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/698307v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@18b1148org.highwire.dtl.DTLVardef@11bbcecorg.highwire.dtl.DTLVardef@102d99org.highwire.dtl.DTLVardef@21af6f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Breath as an internal context: Respiratory phase alignment between encoding and retrieval optimizes memory performance.

Increasing evidence suggests that respiratory rhythms are crucial for cognitive functions. Although recent findings suggest that respiratory activity may serve as an internal contextual framework during memory processes, the contribution of specific respiratory phases to encoding and retrieval remains unclear. Here, we investigated the breathing-dependent performance of 30 healthy volunteers during a visual delayed matching-to-sample recognition memory task while their nasal respiration was monitored. Reaction times (RTs) decreased when visual cues were both encoded and retrieved during the late phase of exhalation. In contrast, longer RTs were observed during late exhalation at retrieval when encoding occurred either (i) during a period that encompassed inspiratory onset (i.e., exhalation-to-inhalation transition or EI transition) or (ii) during the early phase of inhalation. These contrasting outcomes under identical retrieval conditions highlight the phase-dependent effects of respiration, specifically the alignment of respiratory timing between encoding and retrieval. Importantly, we found that the late phase of exhalation during both encoding and retrieval may represent a favorable temporal window for shaping memory performance. These findings suggest that respiratory phase alignment modulates memory processes by providing an interoceptive, phase-dependent context for cognition.

neuroscience↗

bioRxiv2025

Focused acoustic-radiation-force microscopy for live-cell selective nucleus deformation and nucleus viscoelasticity measurement

Acoustic-radiation-force (ARF) microscopy was developed for non-invasive, selective mechanical stimulation to a single live-cell nucleus and long-term measurement of its mechanical properties. High-frequency focused ultrasound wave achieved a spatially confined ARF field around target nucleus, and its cyclic deformation was induced by amplitude modulation on the ultrasound wave, which was captured by a dark-field microscopy. This method was applied to human mesenchymal stem cells, revealing their extremely high mechanical homeostasis.

biophysics↗

bioRxiv2025

High density invasion by the shrub Ardisia crenata in Florida, USA is associated with altered soil chemical properties and microbial communities

Invasive plants can reshape soil ecosystems by altering chemical conditions and microbial communities. However, field evidence for how these effects scale with invader density, and whether responses are nonlinear, remains limited. We examined whether local stem density of the invasive shrub Ardisia crenata is associated with shifts in soil chemistry and soil microbiomes. The local density of A. crenata, which reproduces clonally with apomictic seeds, forms a gradient from high density to low density across invaded stands. Our results show strong differences in soil ecosystems with invasion, including consistently lower soil moisture, pH, organic matter, total carbon, total nitrogen, and electrical conductivity. These changes were accompanied by shifts in the community composition of soil prokaryotes and fungi, such as increased abundances of Acidothermus and Saitozyma with higher density of A. crenata. While the exact mechanisms causing these changes could not be established, increases of more labile above- and below-ground litter, as well as A. crenata specific secondary metabolites, were possible causal factors. We conclude that strong changes in soil ecosystems can be caused by invasive plants in a mesic forest understory, especially when they occur at high densities. Hence, to maintain healthy soil ecosystems, it is recommendable to control aggressive invasive plants such as A. crenata before they reach high densities.

ecology↗

bioRxiv2025

Modeling viral shedding and symptom outcomes in oseltamivir-treated experimental influenza infection

Influenza remains a global public health concern, and although the antiviral drug oseltamivir is widely used to treat infections, questions regarding its actual antiviral efficacy and clinical benefits remain. Here, we evaluated the effects of oseltamivir on viral shedding dynamics in the context of experimental influenza infection. We analyzed individual participant data, including viral load, time to symptom alleviation, and laboratory test measurements, obtained from three publicly available clinical trials involving experimental infections with influenza A and B viruses. We applied mathematical modeling and estimated parameters using a nonlinear mixed-effects model to capture viral infection dynamics. Our analysis revealed that, compared with placebo groups, the oseltamivir-treated groups tended to have lower values in terms of viral load area under the curve, duration of infection, peak viral titer, and time to peak; however, most of these differences were not significant; and no dose-dependent effects were observed. Moreover, there was no significant correlation between time to symptom alleviation and viral load. Some laboratory test parameters showed opposing correlations with symptom-related and viral load-related outcomes. These findings are consistent with distinct mechanisms underlying the symptom-alleviating effects of oseltamivir and its antiviral activity. Our findings suggest that the availability of individual-level data for public use is essential because it enables the evaluation of mechanisms in clinical trials and the development of more appropriate outcome measures.

microbiology↗

bioRxiv2025

Longitudinal analysis of antibody titers after primary and booster mRNA COVID-19 vaccination can identify individuals at risk for breakthrough infection

A key issue in the post-COVID-19 era is the ongoing administration of COVID-19 vaccines. Repeated vaccination is essential for preparing against currently circulating and newly emerging SARS-CoV-2 variants while enabling people to continue with daily life. Optimizing vaccination strategies is crucial to efficiently manage medical resources and establish an effective vaccination framework. Therefore, it is important to quantitatively understand vaccine-induced immunity dynamics and to be able to identify poor responders with lower sustained antibody titers as potential priorities for revaccination. We investigated longitudinal antibody titer data in a cohort of 2,526 people in Fukushima, Japan, from April 2021 to November 2022 for whom basic demographic and health information was available. Using mathematical modeling and machine learning, we stratified the time-course patterns of antibody titers after 2 primary doses and 1 booster dose of mRNA COVID-19 vaccines. We identified 3 notable populations, which we refer to as the durable, the vulnerable, and the rapid-decliner populations, approximately half of which remained in the same population after the booster dose. Notably, the rapid-decliner population experienced earlier infections than the others. Furthermore, when comparing IgG(S) titers, IgA(S) titers, and T-spot counts between participants who experienced breakthrough infections after booster vaccination and those who did not, we found that IgA(S) titers were significantly lower in breakthrough infected participants during the early stage after booster vaccination. Our computational approach is adaptable to various types of vaccinations. This flexibility can inform policy decisions on vaccine distribution to enhance immunity both in future pandemics and in the post-COVID-19 era.

immunology↗

bioRxiv2024

Stratification of viral shedding patterns in saliva of COVID-19 patients

Living with COVID-19 requires continued vigilance against the spread and emergence of variants of concern (VOCs). Rapid and accurate saliva diagnostic testing, alongside basic public health responses, is a viable option contributing to effective transmission control. Nevertheless, our knowledge regarding the dynamics of SARS-CoV-2 infection in saliva is not as advanced as our understanding of the respiratory tract. Here we analyzed longitudinal viral load data of SARS-CoV-2 in saliva samples from 144 patients with mild COVID-19 (a combination of our collected data and published data). Using a mathematical model, we quantified individual-level viral dynamics and stratified them into three groups using a clustering approach. Notably, the three groups exhibited distinct differences viral RNA detection durations: 11.5 days (95% CI: 10.6 to 12.4), 17.4 days (16.6 to 18.2), and 30.0 days (28.1 to 31.8), respectively. Surprisingly, this stratified grouping remained unexplained despite our analysis of 47 types of clinical data, including basic demographic information, clinical symptoms, results of blood tests, and vital signs. Additionally, we quantified the expression levels of 92 micro-RNAs in a subset of saliva samples, but these also failed to explain the observed stratification, although the mir-1846 level may have been weakly correlated with peak viral load. Our study provides insights into SARS-CoV-2 infection dynamics in saliva, highlighting the challenges in predicting the duration of viral RNA detection without indicators that directly reflect an individuals immune response, such as antibody induction. Given the significant individual heterogeneity in the kinetics of saliva viral shedding, identifying biomarker(s) for viral shedding patterns will be crucial for improving public health interventions in the era of living with COVID-19.

microbiology↗

bioRxiv2023

A YIPF5-GOT1A/B complex directs a transcription independent function of ATF6 in ER export

Exit from the endoplasmic reticulum is mediated by the Sar1/COPII machinery and a number of accessory factors. How the initial steps of cargo recruitment upstream of Sar1/COPII are mediated remains unclear, but the dihydropyridine FLI-06 inhibits cargo recruitment into ER exit sites. Here, we used chemical genetics screening approaches in conjunction with FLI-06 treatment and identified the ER membrane proteins YIPF5 and GOT1A/B as putative components of early export processes. Surprisingly, the two homologous proteins GOT1A and GOT1B, coded by GOLT1A and GOLT1B, respectively, exhibited opposite functions after treatment with FLI-06: increasing the expression of GOT1A or reducing the expression of GOT1B or YIPF5 prevented inhibition of ER-export by FLI-06. Inhibiting ER export with FLI-06 elicited a specific ER stress-related gene expression signature distinct from the ER-stress signature induced by Thapsigargin. The interactomes of GOT1A and GOT1B suggested a connection to ER-stress mediators. Moreover, RNA-Seq data showed that FLI-06-induced genes are strongly enriched for ATF6 target genes which are suppressed by GOLT1A overexpression or GOLT1B knock-down. This suggests that ATF6 signaling is involved in FLI-06-mediated toxicity, and we could demonstrate that siRNA-mediated knock-down or specific inhibitor of ATF6 rescued cells from FLI-06-mediated cell death. Knock-down or inhibition of ATF6 is sufficient to resume transport from the ER under FLI-06-treatment, suggesting that ATF6 is directly involved in the FLI-06-mediated ER-export block. Surprisingly, our data show that this ATF6 function is independent of de novo transcription, implying a novel, transcription-independent function of ATF6.

cell biology↗

bioRxiv2023

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation for analyzing extracellular viral markers

Chronic infection of hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. The quantifying and understanding dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, it requires a liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because of the ethical aspect. We here aimed to develop a non-invasive method for quantifying cccDNA in the liver using surrogate markers present in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations (PDEs), integrates experimental data from in vitro and in vivo investigations. By applying this model, we successfully predicted the amount and dynamics of intrahepatic cccDNA using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The non-invasive quantification of cccDNA using our proposed methodology holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

microbiology↗

bioRxiv2022

Prediction of elimination of intrahepatic cccDNA in hepatitis B virus-infected patients by a combination of noninvasive viral markers

Evaluation of intrahepatic covalently closed circular DNA (cccDNA) is a key for searching an elimination of hepatitis B virus (HBV) infection. HBV RNA and HBV core-related antigen have been proposed as surrogate markers for evaluating cccDNA activity, although they do not necessarily estimate the amount of cccDNA. Here, we developed a novel multiscale mathematical model describing intra- and inter-cellular viral propagation, based on the experimental quantification data in both HBV-infected cell culture and humanized mouse models. We applied it to HBV-infected patients under treatment and developed a model which can predict intracellular HBV dynamics only by use of noninvasive extracellular surrogate biomarkers. Importantly, the model prediction of the amount of cccDNA in patients over time was confirmed to be well-correlated with the liver biopsy data. Thus, our noninvasive method enables to predict the amount of cccDNA in patients and contributes to determining the treatment endpoint required for elimination of intrahepatic cccDNA.

microbiology↗

bioRxiv2022

Two cyclic electron flows around photosystem I differentially participate in C4 photosynthesis

C4 plants assimilate CO2 more efficiently than C3 plants because of their C4 cycle that concentrates CO2. However, the C4 cycle requires additional ATP molecules, which may be supplied by the cyclic electron flow around photosystem I. One cyclic electron flow route, which depends on a chloroplast NADH dehydrogenase-like (NDH) complex, is suggested to be crucial for C4 plants despite the low activity in C3 plants. The other route depends on proton gradient regulation 5 (PGR5) and PGR5-like photosynthetic phenotype 1 (PGRL1), which is considered a major cyclic electron flow route to generate the proton gradient across the thylakoid membrane in C3 plants. However, its contribution to C4 photosynthesis is still unclear. In this study, we investigated the contribution of the two cyclic electron flow routes to the NADP-malic enzyme subtype of C4 photosynthesis in Flaveria bidentis. We observed that the suppression of the NDH-dependent route drastically delayed growth and decreased the CO2 assimilation rate to approximately 30% of the wild-type rate. On the other hand, the suppression of the PGR5/PGRL1-dependent route did not affect plant growth and resulted in a CO2 assimilation rate that was approximately 80% of the wild-type rate. Our data indicate that the NDH-dependent cyclic electron flow substantially contributes to the NADP-malic enzyme subtype of C4 photosynthesis and that the PGR5/PGRL1-dependent route cannot complement the NDH-dependent route in F. bidentis. These findings support the fact that during the C4 evolution, the photosynthetic electron flow may be optimized to provide the energy required for C4 photosynthesis.

plant biology↗

bioRxiv2021

Complete sequences of epidermin and nukacin encoding plasmids from oral-derived Staphylococcus epidermidis and their antibacterial activity

Staphylococcus epidermidis is a commensal bacterium in humans. To persist in the bacterial flora of the host, some bacteria produce antibacterial factors such as the antimicrobial peptides known as bacteriocins. In this study, we tried to isolate bacteriocin-producing S. epidermidis strains. Among 150 S. epidermidis isolates from the oral cavities of 287 volunteers, we detected two bacteriocin-producing strains, KSE56 and KSE650. Complete genome sequences of the two strains confirmed that they carried the epidermin-harbouring plasmid pEpi56 and the nukacin IVK45-like- harbouring plasmid pNuk650. The amino acid sequence of epidermin from KSE56 was identical to the previously reported sequence, but the epidermin synthesis-related genes were partially different. The prepeptide amino acid sequences of nukacin KSE650 and nukacin IVK45 showed one mismatch, but both mature peptides were entirely similar. pNuk650 was larger and had an additional seven ORFs compared to pIVK45. We then investigated the antibacterial activity of the two strains against several skin and oral bacteria and found their different activity patterns. In conclusion, we report the complete sequences of 2 plasmids coding for bacteriocins from S. epidermidis, which were partially different from those previously reported. Furthermore, this is the first report to show the complete sequence of an epidermin-carrying plasmid, pEpi56.

microbiology↗

bioRxiv2020

NRF1 and NRF3 complementarily maintain a basal proteasome activity in cancer cells through CPEB3-mediated translational repression

Proteasomes are protease complexes essential for cellular homeostasis, and their activity is crucial for cancer cell growth. However, the mechanism of how proteasome activity is maintained in cancer cells has remained unclear. The CNC family transcription factor NRF1 induces the expression of almost all proteasome-related genes under proteasome inhibition. NRF1 and its phylogenetically closest homolog NRF3 are both highly expressed in several types of cancers, such as colorectal cancer. Herein, we demonstrate that NRF1 and NRF3 complementarily maintain basal proteasome activity in cancer cells. A double knockdown of NRF1 and NRF3 impaired the basal proteasome activity in cancer cells and the cancer cell resistance to a proteasome inhibitor anticancer drug bortezomib by significantly reducing basal expression of seven proteasome-related genes, including PSMB3, PSMB7, PSMC2, PSMD3, PSMG2, PSMG3, and POMP. Interestingly, the molecular basis behind these cellular consequences was that NRF3 repressed NRF1 translation by the gene induction of translational regulator CPEB3, which binds to NRF1-3'UTR and decreases polysome formation on NRF1 mRNA. Consistent results were obtained from clinical analysis, wherein patients with cancer having higher CPEB3/NRF3-expressing tumors exhibit poor prognosis. These results provide the novel regulatory mechanism of basal proteasome activity in cancer cells through an NRF3-CPEB3-NRF1 translational repression axis.

molecular biology↗

bioRxiv2019

ppGpp functions as an alarmone in metazoa

Guanosine 3,5-bis(pyrophosphate) (ppGpp) functions as a second messenger in bacteria to adjust their physiology in response to environmental changes. In recent years, the ppGpp-specific hydrolase, metazoan SpoT homolog-1 (Mesh1), was shown to have important roles for growth under nutrient deficiency in Drosophila melanogaster. Curiously, however, ppGpp has never been detected in animal cells, and therefore the physiological relevance of this molecule, if any, in metazoans has not been established. Here, we report the detection of ppGpp in Drosophila and human cells and demonstrate that ppGpp accumulation induces metabolic changes, cell death, and eventually lethality in Drosophila. Our results provide the first evidence of the existence and function of the ppGpp-dependent stringent response in animals.

molecular biology↗

bioRxiv2019

Single-Cell RNA-Seq Reveals Novel Mitochondria-related Musculoskeletal Cell Populations during Adult Axolotl Limb Regeneration Process

While the capacity to regenerate tissues or limbs is limited in mammals including humans, unlike us, axolotls are able to regrow entire limbs and major organs. The wound blastema have been extensively studied in limb regeneration. However, due to the inadequate characterization and coordination of cell subpopulations involved in the regeneration process, it hinders the discovery of the key clue for human limb regeneration. In this study, we applied unbiased large-scale single-cell RNA sequencing to classify cells throughout the adult axolotl limb regeneration process. We computationally identified 7 clusters in regenerating limbs, including the novel regeneration-specific mitochondria-related cluster supporting regeneration through energy providing and the COL2+ cluster contributing to regeneration through cell-cell interactions signals. We also discovered the dedifferentiation and re-differentiation of the COL1+/COL2+ cellular subpopulation and uncovered a COL2-mitochondria sub-cluster supporting the musculoskeletal system regeneration. On the basis of these findings, we reconstructed the dynamic single-cell transcriptome atlas of adult axolotl limb regenerative process, and identified the novel regenerative mitochondria-related musculoskeletal populations, which yielded deeper insights into the crucial interactions between cell clusters within the regenerative microenvironment.

genomics↗

bioRxiv2019

LAVENDER: latent axes discovery from multiple cytometry samples with non-parametric divergence estimation and multidimensional scaling reconstruction

Computational cytometry methods are now frequently used in flow and mass cytometric data analyses. However, systematic bias-free methodologies to assess inter-sample variability have been lacking, thereby hampering efficient data mining from a large set of samples. Here, we devised a computational method termed LAVENDER (latent axes discovery from multiple cytometry samples with nonparametric divergence estimation and multidimensional scaling reconstruction). It measures the Jensen-Shannon distances between samples using the k-nearest neighbor density estimation and reconstructs samples in a new coordinate space, called the LAVENDER space. The axes of this space can then be compared against other omics measurements to obtain biological information. Application of LAVENDER to multidimensional flow cytometry datasets of 301 Japanese individuals immunized with a seasonal influenza vaccine revealed an axis related to baseline immunological characteristics of each individual. This axis correlated with the proportion of plasma cells and the neutrophil-to-lymphocyte ratio, a clinical marker of the systemic inflammatory response. The same method was also applicable to mass cytometry data with more molecular markers. These results demonstrate that LAVENDER is a useful tool for identifying critical heterogeneity among similar, yet different, single-cell datasets.

bioinformatics↗