Biology subjects

Iwami, S.

Publications and source records attributed to Iwami, S..

At least 19 recordsLinked to original sources

bioRxiv2025

Mating status-dependent dopaminergic modulation of auditory sensory neurons in Drosophila

Mating status often modulates responses to courtship sounds in animals. The neural mechanisms underlying this modulation, however, have not been well clarified. Here, we show that dopaminergic signals are involved in modulating the responses of auditory sensory neurons in Drosophila melanogaster females depending on their mating status. These neurons abundantly express three types of dopamine receptors, with some having direct synaptic connections with dopaminergic neurons. Of these receptors, suppressing the expression of Dop1R2 reduces sound responses of auditory sensory neurons in unmated but not mated females. Moreover, expression of Dop1R2 in auditory sensory neurons enhances the song response behavior of unmated females, manifested by copulation receptivity when exposed to songs. Our research suggests that dopaminergic modulation via Dop1R2 is involved in mating state-dependent regulation of auditory sensory processing.

neuroscience↗

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

Evaluating the impact of NPC1 SNPs on entry efficiency of Filovirus in vitro: agent-based model approach

The interaction between the Niemann-Pick C1 (NPC1) protein and the glycoprotein (GP) of filoviruses is essential for viral entry into host cells. Single nucleotide polymorphisms (SNPs) in NPC1, which lead to amino acid substitutions, can significantly alter viral entry efficiency. However, the quantitative impact of these SNPs remains unclear. To address this, we investigate in vitro cell-to-cell infection using a plaque assay with vesicular stomatitis virus (VSV) expressing Ebola and Marburg GP. We employe an agent-based model (ABM) to estimate entry efficiency by simulating plaque growth, enabling a comparative analysis of SNP-specific effects on viral entry. Our quantitative analysis reveals that D508N, P424A, and S425L substitutions in NPC1 reduce entry efficiency in both viruses. These findings provide insights into host-pathogen interactions and demonstrate the value of ABM in virology research, potentially guiding therapeutic strategies targeting viral entry mechanisms. Author summaryEbola and Marburg viruses are highly pathogenic filoviruses that cause severe hemorrhagic fever in humans, with case fatality rates reaching around 50%. These viruses pose significant public health challenges due to their potential for large-scale outbreaks. A key step in their infection process is the interaction between the Niemann-Pick C1 (NPC1) protein on host cells and the viral glycoprotein, which facilitates viral entry. Genetic variations in NPC1 caused by single nucleotide polymorphisms (SNPs) can lead to amino acid substitutions, potentially altering the efficiency of viral entry. To better understand this process, we developed an agent-based model, a computational approach that simulates individual cell interactions and provides spatial resolution not achievable with traditional modeling techniques, to simulate viral plaque growth in vitro. By applying this model, we quantified how specific NPC1 substitutions, such as D508N, P424A, and S425L, affect the entry efficiency of Ebola and Marburg viruses. Our findings highlight the potential of computational modeling to uncover the impact of genetic variations on viral infections and provide insights that may inform therapeutic strategies against these deadly viruses.

systems biology↗

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

Stable platelet production via the bypass pathway explains the long-term reconstitution capacity of hematopoietic stem cells

Precise understanding how hematopoietic stem cells (HSCs) differentiate in vivo is difficult because we can not trace the in vivo differentiation of HSCs. The single-cell transplantation assay and our own paired daughter cell assay of phenotypic HSCs has revealed the presence of HSCs with reconstitution capacity whose differentiation potential is restricted to the myeloid lineage (MySCs) and the presence of novel direct differentiation pathway form HSCs to MySCs (named myeloid bypass pathway). However, how HSCs differentiate in vivo during hematopoiesis has remained unclear since the paired daughter cell assay was performed partially ex vivo. Aiming to characterize HSCs, including the myeloid bypass pathway, we examined the kinetics of HSC differentiation using a mathematical model. We analyzed data from single-cell transplantation assays in which five blood cell lineages were followed successively after transplantation. An age-related skewing to the myeloid lineage was quantitatively indicated as the production of B cells reduced with age. Dependence on platelet bypass increased with aging and consistently high dependence was associated with long-term reconstitution capacity of the HSCs. Focusing on the ratio of chimerism among cell lineages, the characteristics of dependence on platelet bypass can be accurately determined by the ratio of erythrocyte to platelet chimerism at 8 weeks after transplantation. This new identification criterion is an indicator of long-term reconstitution of HSCs that does not rely on observation of long-term transplantation experiments. These findings reveal the novel characteristics of HSCs related to aging and stemness and highlight the importance of the bypass pathway in HSC differentiation. Significance statementIn vivo differentiation of hematopoietic stem cells (HSCs) is important for understanding blood cell production. Here we investigated the differentiation kinetics of HSCs in single-cell transplantation assays by using a mathematical model. Our findings demonstrate the importance of the bypass pathway in platelet production for the long-term reconstitution capacity of HSCs. These results also suggest the utility of studying time changes in HSC differentiation. The new HSC characteristics and its detection criteria identified in this study are expected to be useful in understanding HSC diversity and aging.

cell biology↗

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

Direct Relationship between Protein Expression and Progeny Yield of Herpes Simplex Virus 1 Unveils a Rate-limiting Step for Virus Production

Although viral protein expression and progeny virus production were independently shown to be highly heterogenous in individual cells, their direct relationship, analyzed by considering their heterogeneities, has not been investigated to date. This study established a system to fractionate cells infected with a herpesvirus based on the levels of the global expression of viral late proteins, which are largely virion structural proteins, and to titrate virus yields in these fractions. This system demonstrated a direct relationship and indicated there was a threshold for the levels of viral late protein expression for progeny virus production and suggested that viral DNA cleavage/packaging was a rate-limiting step for progeny virus production. These findings, which were masked in previous studies performed at the entire population level, have uncovered a sophisticated viral strategy for efficient progeny virus production and shed new light on an effective target for the development of anti-viral drugs.

microbiology↗

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↗

bioRxiv2023

Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution

During the COVID-19 pandemic, human behavior change as a result of nonpharmaceutical interventions such as isolation may have induced directional selection for viral evolution. By combining previously published empirical clinical data analysis and multi-level mathematical modeling, we found that the SARS-CoV-2 variants selected for as the virus evolved from the pre-Alpha to the Delta variant had earlier and higher infectious periods but a shorter duration of infection. Selection for increased transmissibility shapes the viral load dynamics, and the isolation measure is likely to be a driver of these evolutionary transitions. In addition, we showed that a decreased incubation period and an increased proportion of asymptomatic infection were also positively selected for as SARS-CoV-2 mutated to the extent that people did not isolate. We demonstrated that the Omicron variants evolved in these ways to adapt to human behavior. The quantitative information and predictions we present here can guide future responses in the potential arms race between pandemic interventions and viral evolution.

evolutionary biology↗

bioRxiv2022

Contact-number-driven virus evolution: a multi-level modeling framework for the evolution of acute or persistent RNA virus infection

Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as and SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and why the persistent viruses evolved has been rarely explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society.

evolutionary biology↗

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

Potential anti-monkeypox virus activity of atovaquone, mefloquine, and molnupiravir, and their potential use as treatments

Monkeypox virus (MPXV) is a zoonotic orthopoxvirus that causes smallpox-like symptoms in humans and caused an outbreak in May 2022 that led the WHO to declare global health emergency. In this study, from a screening of approved-drug libraries using an MPXV infection cell system, atovaquone, mefloquine, and molnupiravir exhibited anti-MPXV activity, with 50% inhibitory concentrations of 0.51-5.2 M, which is more potent than cidofovir. Whereas mefloquine was suggested to inhibit viral entry, atovaquone and molnupiravir targeted post-entry process to impair intracellular virion accumulation. Inhibitors of dihydroorotate dehydrogenase, an atovaquones target enzyme, showed conserved anti-MPXV activities. Combining atovaquone with tecovirimat enhanced the anti-MPXV effect of tecovirimat. Quantitative mathematical simulations predicted that atovaquone can promote viral clearance in patients by seven days at clinically relevant drug concentrations. Moreover, atovaquone and molnupiravir exhibited pan-Orthopoxvirus activity against vaccinia and cowpox viruses. These data suggest that atovaquone would be potential candidates for treating monkeypox.

microbiology↗

bioRxiv2022

Different efficacies of neutralizing antibodies and antiviral drugs on SARS-CoV-2 Omicron subvariants, BA.1 and BA.2

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariant BA.2 has spread in many countries, replacing the earlier Omicron subvariant BA.1 and other variants. Here, using a cell culture infection assay, we quantified the intrinsic sensitivity of BA.2 and BA.1 compared with other variants of concern, Alpha, Gamma, and Delta, to five approved-neutralizing antibodies and antiviral drugs. Our assay revealed the diverse sensitivities of these variants to antibodies, including the loss of response of both BA.1 and BA.2 to casirivimab and of BA.1 to imdevimab. In contrast, EIDD-1931 and nirmatrelvir showed a more conserved activities to these variants. The viral response profile combined with mathematical analysis estimated differences in antiviral effects among variants in the clinical concentrations. These analyses provide essential evidence that gives insight into variant emergences impact on choosing optimal drug treatment.

microbiology↗

bioRxiv2022

Characterization of various remdesivir-resistant mutations of SARS-CoV-2 by mathematical modeling and molecular dynamics simulation.

Mutations continue to accumulate within the SARS-CoV-2 genome, and the ongoing epidemic has shown no signs of ending. It is critical to predict problematic mutations that may arise in clinical environments and assess their properties in advance to quickly implement countermeasures against future variant infections. In this study, we identified mutations resistant to remdesivir, which is widely administered to SARS-CoV-2-infected patients, and discuss the cause of resistance. First, we simultaneously constructed eight recombinant viruses carrying the mutations detected in in vitro serial passages of SARS-CoV-2 in the presence of remdesivir. Time course analyses of cellular virus infections showed significantly higher infectious titers and infection rates in mutant viruses than wild type virus under treatment with remdesivir. Next, we developed a mathematical model in consideration of the changing dynamic of cells infected with mutant viruses with distinct propagation properties and defined that mutations detected in in vitro passages canceled the antiviral activities of remdesivir without raising virus production capacity. Finally, molecular dynamics simulations of the NSP12 protein of SARS-CoV-2 revealed that the molecular vibration around the RNA-binding site was increased by the introduction of mutations on NSP12. Taken together, we identified multiple mutations that affected the flexibility of the RNA binding site and decreased the antiviral activity of remdesivir. Our new insights will contribute to developing further antiviral measures against SARS-CoV-2 infection. Significance StatementConsidering the emerging Omicron strain, quick characterization of SARS-CoV-2 mutations is important. However, owing to the difficulties in genetically modifying SARS-CoV-2, limited groups have produced multiple mutant viruses. Our cutting-edge reverse genetics technique enabled construction of eight reporter-carrying mutant SARS-CoV-2 in this study. We developed a mathematical model taking into account sequential changes and identified antiviral effects against mutant viruses with differing propagation capacities and lethal effects on cells. In addition to identifying the positions of mutations, we analyzed the structural changes in SARS-CoV-2 NSP12 by computer simulation to understand the mechanism of resistance. This multidisciplinary approach promotes the evaluation of future resistance mutations.

microbiology↗

bioRxiv2020

Anti-severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) potency of Mefloquine as an entry inhibitor in vitro

Coronavirus disease 2019 (COVID-19) has caused serious public health, social, and economic damage worldwide and effective drugs that prevent or cure COVID-19 are urgently needed. Approved drugs including Hydroxychloroquine, Remdesivir or Interferon were reported to inhibit the infection or propagation of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2), however, their clinical efficacies have not yet been well demonstrated. To identify drugs with higher antiviral potency, we screened approved anti-parasitic/anti-protozoal drugs and identified an anti-malarial drug, Mefloquine, which showed the highest anti-SARS-CoV-2 activity among the tested compounds. Mefloquine showed higher anti-SARS-CoV-2 activity than Hydroxychloroquine in VeroE6/TMPRSS2 and Calu-3 cells, with IC50 = 1.28 M, IC90 = 2.31 M, and IC99 = 4.39 M in VeroE6/TMPRSS2 cells. Mefloquine inhibited viral entry after viral attachment to the target cell. Combined treatment with Mefloquine and Nelfinavir, a replication inhibitor, showed synergistic antiviral activity. Our mathematical modeling based on the drug concentration in the lung predicted that Mefloquine administration at a standard treatment dosage could decline viral dynamics in patients, reduce cumulative viral load to 7% and shorten the time until virus elimination by 6.1 days. These data cumulatively underscore Mefloquine as an anti-SARS-CoV-2 entry inhibitor.

microbiology↗

bioRxiv2020

Identifications of novel avian and mammalian deltaviruses filled the large evolutionally gaps and revealed inter-family transmission of deltaviruses

Hepatitis delta virus (HDV) is a satellite virus that requires hepadnavirus envelope proteins for its transmission. Although recent studies identified HDV-related deltaviruses in certain animals, the evolution of deltaviruses, such as the origin of HDV and the mechanism of its coevolution with its helper viruses, is unknown, mainly because of the phylogenetic gaps among deltaviruses. Here we identified novel deltaviruses of passerine birds, woodchucks, and white-tailed deer by extensive database searches and molecular surveillance. Phylogenetic and molecular epidemiological analyses suggest that HDV originated from mammalian deltaviruses and the past interspecies transmission of mammalian and passerine deltaviruses. Further, metaviromic and experimental analyses suggest that the satellite-helper relationship between HDV and hepadnavirus was established after the divergence of the HDV lineage from non-HDV mammalian deltaviruses. Our findings enhance our understanding of deltavirus evolution, diversity, and transmission, indicating the importance of further surveillance for deltaviruses.

microbiology↗

bioRxiv2020

Multidrug treatment with nelfinavir and cepharanthine against COVID-19

Antiviral treatments targeting the emerging coronavirus disease 2019 (COVID-19) are urgently required. We screened a panel of already-approved drugs in a cell culture model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and identified two new antiviral agents: the HIV protease inhibitor Nelfinavir and the anti-inflammatory drug Cepharanthine. In silico modeling shows Nelfinavir binds the SARS-CoV-2 main protease consistent with its inhibition of viral replication, whilst Cepharanthine inhibits viral attachment and entry into cells. Consistent with their different modes of action, in vitro assays highlight a synergistic effect of this combined treatment to limit SARS-CoV-2 proliferation. Mathematical modeling in vitro antiviral activity coupled with the known pharmacokinetics for these drugs predicts that Nelfinavir will facilitate viral clearance. Combining Nelfinavir/Cepharanthine enhanced their predicted efficacy to control viral proliferation, to ameliorate both the progression of disease and risk of transmission. In summary, this study identifies a new multidrug combination treatment for COVID-19.

microbiology↗

bioRxiv2020

Direct evidence of abortive lytic infection-mediated establishment of Epstein-Barr virus latency during B-cell infection

Viral infection induces dynamic changes in transcriptional profiles. Virus-induced and anti-viral responses are intertwined during the infection. Epstein-Barr virus (EBV) is a human gammaherpesvirus that provides a model of herpesvirus latency. To measure the transcriptome changes during the establishment of EBV latency, EBV-negative Akata cells were infected with EBV-EGFP and observed by transcriptome sequencing (RNA-seq) at 0, 2, 4, 7, 10, and 14 days after infection. We found transient downregulation of mitotic division-related genes, reflecting reprograming of cell growth by EBV. Moreover, a burst of viral lytic gene expression was detected in the early phase of infection. Experimental and mathematical investigations demonstrated that infectious virions were not produced in the pre-latent phase, suggesting the presence of an abortive lytic infection. Finally, we conducted fate mapping using recombinant EBV, enabling the noninvasive, continuous observation of infected cells during EBV infection. Our tracking analysis provided direct evidence that the abortive lytic infection in the pre-latent phase converges to latent infection during EBV infection of B-cells, shedding light on novel roles of viral lytic gene(s) in establishing latency. Author summaryViral infection is a complex process that activates both virus-triggered and host anti-viral responses. This process has classically been studied by snapshot analysis such as microarray and RNA-seq at discrete time points as population averages. Snapshot data lead to invaluable findings in host-pathogen interactions. However, these "snapshot" omics, even from a single cell, lack temporal resolution. Because the behavior of infected cells is highly dynamic and heterogenous, continuous analysis is required for deciphering the fate of infected cells during viral infection. Here, we exploited fate mapping techniques with recombinant Epstein-Barr virus (EBV) to track the infected cells and recorded a log of lytic gene expression during EBV infection. Our continuous observation of infected cells revealed that EBV established latency in B-cells via an abortive lytic infection in the pre-latent phase.

microbiology↗