Nagoya, Aichi, Japan

July 4th - 6th, 2023

6th Workshop on Virus Dynamics
Abstract Book

6th Workshop on Virus Dynamics

List of presenters
KeynoteJoshua S. Weitz
Eco-evolutionary dynamics of bacteriophage, an imperfect viral predator
Jessica A. Belser
Modeling influenza A virus pathogenicity and transmissibility in ferrets
Miles Davenport
Mechanisms of immunity to SARS-CoV-2 infection
Takeshi Noda
The mechanism underlying long-term olfactory dysfunction induced by SARS-CoV-2 infection
Rob de Boer
T cells contributing little to a first response contribute more to subsequent immune responses
Akira Sasaki
Mathematical models describing evolutionary immune escapes of pathogens

Oral presentation
OC-01 Elissa J. Schwartz
Bacteriophage ΦX174 inhibition and escape dynamics
OC-02 Daniel Rüdiger
OP7, a defective interfering particle with mutations: in vitro infection experiments, intracellular model, impact of mutations andmode of antiviral action
OC-03 Shadi Esmaeili-Wellman
Differing intracellular and extracellular dynamics of viral DNA and infectious particles
OC-04 Jan Küchler
Absolute quantification of influenza A viral proteins during single-round replication in different host cells
OC-05 Vitaly V. Ganusov
Mathematical modeling suggests that olsetamivir increases the rate of clearance of influenza A virus-infected cells by cytotoxic
immunity
OC-06 Koichi Watashi
Drug discovery on a mpox cell culture infection assay
OC-07 Thomas James Williams
Inference on dual-spread models of viral infection within the host
OC-08 Rodolphe Thiebaut
How gene expression can inform dynamical models?
OC-09 Jérémie Guedj
Modelling the association between neutralizing antibody levels and SARS-CoV-2 viral dynamics : implications to define correlates ofprotection against infection
OC-10 Aurélien Marc
Impact of variants of concern on SARS-CoV-2 viral dynamics in non-human primates
OC-11 Joshua Tisdell Schiffer
in vitro overestimates of nirmatrelvir / ritonavir potency for SARS-CoV-2 infection in humans
OC-12 Yorifumi Satou
Establishment of HIV-timer system to analyze expression dynamics of HIV provirus
OC-13 Katherine Grace Lacy Owens
CAR T cells for HIV cure, a tale of four macaques
OC-14 Wang Jin
The impact of CD8+ lymphocytes on the SIV reservoir establishment under ART: a model-based data analysis approachOC-15 Steffen Docken
Mechanistic modelling of effect of target cell limitation on protection from HIV
OC-16 Bharadwaj Vemparala
Modeling SIV dynamics incorporating effector function measurements of CD8 T cells
OC-17 Anton Zilman
Ligand discrimination in cross-wired immune signaling pathways

List of presenters / 1

6th Workshop on Virus Dynamics

OC-18 Catherine A.A. Beauchemin
Yet another stochastic model of virus infection with some new results
OC-19 Nicolas Christian Ochsner
Testing phylogeographic inferences methods on simulated epidemics with realistic selection effects
OC-20 William Stephen Hart
Analysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 antigen testing asa case study
OC-21 Alex R Cook
Border policies to prevent COVID-19
OC-22 Keisuke Ejima
Age-dependent isolation guideline to reduce the burden of isolation of COVID-19: simulation using longitudinal viral load data from
SARS-CoV-2 Omicron cases in Singapore
OC-23 Anet Jorim Norbert Anelone
Modelling measles inoculum dose responses to study paradoxical mechanisms of immune control of acute viremia
OC-24 Naotoshi Nakamura
Dynamical systems phenotyping to stratify peg-IFN treatment efficacy in patients with chronic hepatitis B

Poster presentation
P-01 Xiangjie Sun
Dissecting the multifactorial roles of influenza A virus receptor binding specificity in the airborne transmission dynamics of an
H9N2 virus
P-02 Marwa Akao
Investigating the relationship between influenza viral dynamics and clinical symptoms using data from Phase 3 clinical trials ofoseltamivir
P-03 Troy Kieran
Using machine learning to identify predictive correlates in ferret in vivo model data for influenza A risk assessment
P-04 Shotaro Yamamoto
Estimation of treatment efficacy of drug candidates against mpox virus in combination
P-05 Maureen Rebecca Smith
Genome-based incidence estimation of SARS-CoV-2 with GInPipe
P-06 Daiki Tatematsu
Detection of changes in viral load in a randomized controlled trial of an anti-SARS-CoV-2 drug with high entry inhibition efficacy
P-07 Sharmin Nahar Sithi
Establishment of recombinant HIV with timer fluorescence protein to visualize virus transcription
P-08 Takara Nishiyama
Quantitative analysis of the antiviral effect of mucosal antibodies to suppress infectious SARS-CoV-2 shedding
P-10 Kosaku Kitagawa
Simulating booster vaccinations: a case study of Fukushima Vaccination Cohort
P-11 Hyeongki Park
Heterogeneity in duration of viral shedding in COVID-19 patient’s saliva may not be explained by basic clinical and micro-RNA
information
P-12 Mizuka Komatsu
Algebra-assisted PINN approach for SEIR modeling with unobserved variables
P-13 Yong Dam Jeong
Effective screening with antigen tests for identifying COVID-19 patients: simulation with viral dynamics model
P-14 Jun Koseki
Analysis of antiviral drug resistance caused by amino acid mutations
P-15 Choi Sooyoun
Prediction of the indicator for determining immune reconstruction syndrome (IRIS)-induced hepatic flare (HF) in HBV/HIV coinfected patients
P-16 Ryuichi Kumata
Evolutionary dynamics of virulence of helper and satellite viruses
P-17 Joohyeon Woo
Different efficacies of neutralizing antibodies and antiviral drugs on SARS-CoV-2 Omicron subvariants, BA.1 and BA.2
P-18 Yusuke Asai
Estimating the effect of medical intervention on the arrival time of infectious diseases
P-19 Megumi Oya
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6th Workshop on Virus Dynamics

An interpretable machine learning framework for monitoring and stratifying the time-varying prognostic risk of diseases
P-20 Kyoko Kojima
Public relations strategies for the non-scientific community in virus dynamics research
P-21 Yoshitaka Sato
Heterogeneity of individual B lymphocytes during transformation by Epstein-Barr virus infection
P-22 Takeru Matsuura
A machine learning model for predicting hepatocarcinogenesis in chronic hepatitis B patients
P-23 Shoya Iwanami
Quantification of age-related changes in hematopoietic stem cell differentiation

List of presenters / 3

Keynote

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus

Eco-evolutionary dynamics of bacteriophage, an imperfect viral predator
Speaker

Joshua S. Weitz, School of Biological Sciences, Georgia Institute of Technology

Summary of talk

Viruses of bacteria transform the fate of microbial cells, populations, and communities. This talk will introduce mathematical models ofphage-bacteria population dynamics along with experimental evidence that shows when such models work and when, because of(co)evolution, far more unusual dynamics can unfold. Then, I will show how to extend principles of phage-bacteria interactions torealistic settings, including the role of phage in antibacterial therapy and surface marine ecosystems, revealing how viral influencechanges when embedded as part of complex systems.

Keynote / 1

Keynote

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus

Modeling influenza A virus pathogenicity and transmissibility in ferrets
Speaker

Jessica A. Belser, Influenza Division, Centers for Disease Control and Prevention (US CDC)

Summary of talk

The ferret model serves as an invaluable species for the coincident study of influenza A virus (IAV) pathogenicity and transmissibility,
providing critical information towards understanding virus-host interactions, molecular determinants of virulence, immunogenicity andcorrelates of protection, and the evaluation of novel vaccines, antivirals, and therapeutics. However, interpreting and contextualizing
data generated from the ferret model can pose a challenge to both virologists and wider audiences interested in the public health
implications of this research. In addition to expected strain-specific and subtype-specific phenotypic differences between IAV following
infection in ferrets, there is underappreciated heterogeneity in experimental designs, sample collections, and reported results between
laboratories working with this model, which can limit rigorous interpretation of findings generated from this work. Here, use of theferret as an in vivo model to study IAV pathogenicity and transmissibility will be described, and studies linking results from this workwith data obtained following human infection with IAV will be highlighted. Meta-analyses inclusive of IAV that display a diverse rangeof phenotypes in ferrets can provide valuable information on a range of topics, offering insight into parallel studies conducted in vitro
as well as within-host and between-host viral dynamics in vivo; these can include identifying features of in vitro experimentation thatare most predictive of in vivo outcomes, and improving interpretation of viral spread at discrete sites of replication throughout the
respiratory tract post-infection in vivo. Understanding both the challenges and opportunities of translating data generated from IAVinfected ferrets for modelling applications can result in higher-quality studies, ultimately leading to improved utility of these efforts
towards understanding the pandemic potential of novel and emerging IAV.

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Keynote

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus

Mechanisms of immunity to SARS-CoV-2 infection
Speaker

Miles Davenport, Kirby Institute, University of New South Wales

Summary of talk

SARS-CoV-2 vaccination and infection elicit both cellular and humoral immune responses to viral proteins. Neutralising antibody titres
have been shown to predict protection from both symptomatic and severe COVID-19. Studies of antibody titres show they remain
predictive of protection over time and against emerging SARS-CoV-2 variants. In addition, studies of passive antibody administration(convalescent serum and monoclonal antibody) demonstrate that antibodies alone can directly mediate immune protection from both
symptomatic SARS-CoV-2 infection and from progression from symptomatic to severe COVID-19. Protection after passive antibody
administration occurs at similar antibody titres to that seen after vaccination, suggesting that neutralizing antibodies are a major factor
in vaccine-mediated protection. Despite immunity from vaccination and / or prior infection, ‘breakthrough infection’ is frequently
observed. This is accompanied by recall (activation and expansion) of both the humoral and cellular responses to infection. The
contribution of recall immunity to control of SARS-CoV-2 viral replication is unclear. However, the level of activated virus-specific CD8+
T cells present early in infection is predictive of lower viral peaks and faster viral clearance. By contrast, recall of serological responses
likely occurs too late to have a major effect on clinical outcome. Analysis of viral and immune kinetics has provided a unique insight
into the mechanisms of immune control in SARS-CoV-2 infection.

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Keynote

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus

The mechanism underlying long-term olfactory dysfunction induced by SARS-CoV-2
infection
SpeakerTakeshi Noda, Institute for Life and Medical Sciences, Kyoto University

Summary of talk

The nasal epithelium (NE) is the main target of SARS-CoV-2. The virus can cause persistent olfactory dysfunction as a sequela of
COVID-19. However, it is unclear how the virus replicates in human NE and causes long-term olfactory dysfunction. Here, using humanembryonic stem cells, we generated human NE organoids comprising not only nasal respiratory epithelia (NRE) but also olfactory
epithelia (OE) containing neuronal cells. The NE organoids supported efficient replication of SARS-CoV-2. Angiotensin-converting
enzyme 2 (ACE2)-knockout NE organoids demonstrated that SARS-CoV-2 replicates in human NE in an ACE2-dependent manner.
Single-cell RNA sequencing and immunostaining demonstrated that SARS-CoV-2 initially replicates in NRE and then spreads to neuralprecursor cells (NPCs) and basal stem cells, which are olfactory sensory neuron precursors in the OE. Cell damage- and cell deathassociated genes were upregulated in the NPCs and basal stem cells in the virus-infected organoids, suggesting that SARS-CoV-2
infections cause long-term disruptions in the repair and renewal of olfactory sensory neurons. These findings provide novel insights
into SARS-CoV-2 replication in human NE and suggest a mechanism underlying the long-term olfactory dysfunction in COVID-19
patients.

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Keynote

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus

T cells contributing little to a first response contribute more to subsequent immune
responses
SpeakerRob de Boer, Department of Biology, Utrecht University

Summary of talkDuring a primary immune response to a pathogen hundreds of naive T cells are recruited into clonal expansion. Some cells expand
vigorously and make up most of the immune response, and some cells stop dividing early and form only a small family of progeny[Gerlach et al Science 2013]. Using a novel experimental system by which one can trace the division history of a population, we
recently found that secondary immune responses originate from such small families, and that the large families contribute little[Bresser et al Nature Immunology 2022]. We develop mathematical models aiming to quantitatively and mechanistically combine andexplain these surprising observations.

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Keynote

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus

Mathematical models describing evolutionary immune escapes of pathogens
Speaker

Akira Sasaki, School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies)

Summary of talk

Despite the propensity for complex and non-equilibrium dynamics in nature, eco-evolutionary analytical theory typically assumes that
populations are at equilibria. In particular, pathogens often show antigenic escape from host immune defenses, leading to repeatedepidemics, fluctuating selection, and diversification. We model the evolutionary chase and escape of pathogen antigenicity and hostimmune system by using a reaction-diffusion system in antigenicity space. The system describes the pathogen immune escape as
coupled traveling waves of pathogen antigenicity and host specific-immunity. Our analysis predicts how the speed of antigenic escapeof pathogen (traveling wave speed) depends on epidemiological and genetic parameters, as well as the condition under which a stable
traveling wave becomes destabilized, resulting in periodic bursts of pathogen outbreaks both in time and antigenicity space. Our model
also predicts how this antigenic escape impacts the evolution of transmission and virulence of a pathogen. An extended model
incorporating the effect of heterogeneity in host immune competence is also analyzed, showing that the presence of
immunocompetent hosts sensitively speeds up the evolution rate of antigenic escape.

Keynote / 6

Oral
Presentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-01]Bacteriophage ΦX174 inhibition and escape dynamics
Author(s)Elissa J. Schwartz, Washington State University (Presenter); Clayton L. Bailes, Washington State University; Karin R.H. Biggs,
Washington State University; LuAnn Scott, University of Idaho; Holly A. Wichman, University of Idaho

Short Abstract

As a consequence of target-cell limitation in microbial communities, bacteriophages evolve inhibitory mechanisms to suppress theircompetitors. One such mechanism is superinfection exclusion, in which a preexisting viral infection prevents a secondary infection. The
bacteriophage ΦX174 exhibits a potential superinfection inhibition mechanism (in which secondary infections are either blocked or
resisted) known as the ΦX174 reduction effect. In this auto-inhibitory phenomenon, when a portion of the ΦX174 genome – the 3’ endof the pilot protein gene (H), the 5’ end of the replication gene (A), and the H-A intergenic region – is present on a plasmid in the host
cell, almost complete protection from phage infection occurs. Utilizing this plasmid-based system, we examined inhibition and escapefrom the reduction effect. We demonstrated that partial to complete recovery (i.e., escape) from this inhibition is possible with minimal
viral evolution. Multiple paths to escape are seen, via either single point mutations or multiple mutations. Escape mutations occur inthe reduction sequence portion of the genome, predominantly in gene H. Furthermore, generally adaptive mutations segregate
spatially in H from mutations specific for the reduction effect. These findings indicate the potential importance of different regions ingene H for viral entry as well as for understanding the complex dynamics of virus escape in ΦX174 infection.

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Oral
Presentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-02]

OP7, a defective interfering particle with mutations: in vitro infection experiments,
intracellular model, impact of mutations and mode of antiviral action
Author(s)Daniel Rüdiger, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany (Presenter); Julita Piasecka,
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany; Jan Küchler, Max Planck Institute forDynamics of Complex Technical Systems, Magdeburg, Germany; Sascha Young Kupke, Max Planck Institute for Dynamics of Complex
Technical Systems, Magdeburg, Germany; Udo Reichl, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg,
Germany / Otto-von-Guericke University Magdeburg, Chair of Bioprocess Engineering, Magdeburg, Germany

Short Abstract

Defective interfering particles (DIPs) were applied successfully as antivirals in recent animal studies based on their interference withthe replication of wild-type viruses. DIPs can only replicate when a coinfection with their homologous standard virus (STV) occurs. In thepast, most experimental and model-based studies focused on DIPs carrying a large internal deletion in one of the viral genome
segments. In this work, we studied the viral dynamics during an OP7 and influenza STV coinfection in cell culture. OP7 is a recently
discovered influenza DIP that does not contain internal deletions but features 37 single-nucleotide substitutions (SNSs) on the viral
RNA genome segment 7 (S7). We monitored the infection dynamics of viral RNAs via real-time reverse transcription qPCR, quantified
viral protein levels using a novel mass spectrometry-based method, and determined virus titers. Based on these experimental data, weestablished a mathematical model of OP7 and STV coinfection and employed it to test various hypotheses related to the impact of theSNSs on virus replication. Experimental results show that the mutated OP7 S7 genomes outcompete all STV genome segments during
replication and accumulate to high levels in progeny virions. Model simulations suggest that the SNSs on OP7 S7 induce an increased
viral replication, a significant reduction of viral mRNA transcription and a disturbed virus particle assembly. Furthermore, we conclude
that the M1 protein translated from OP7 S7 mRNA is likely defective. The model closely predicts the propagation of OP7 and the
suppression of STV in an infected cell culture over multiple passages for varying initial conditions. In summary, we developed amathematical model that provides a detailed description of OP7 and STV coinfection, improves our understanding of DIP interference
mechanisms and supports the development of antiviral therapies.

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Oral
Presentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-03]Differing intracellular and extracellular dynamics of viral DNA and infectious particles
Author(s)Shadi Esmaeili-Wellman, Fred Hutchinson Cancer Research Center (Presenter); Joshua T. Schiffer, Fred Hutchinson Cancer ResearchCenter, University of Washington,; Marius Walter, Fred Hutchinson Cancer Research Center

Short Abstract

The standard viral dynamics model considers viral populations as a single entity but does not discriminate infectious viral particles
detected with viral culture (plaque assay) from non-infectious particles or viral replication intermediates which are captured withpolymerase chain reaction (PCR). These models also do not consider viral loads within and outside of cells. We developed dozens ofcompeting mechanistic mathematical models to describe the dynamics of herpes simplex virus (HSV) genomes and infectious particles
following high multiplicity of infection (MOI=3) and low MOI (MOI=0.01) experiments in vitro. The experimental data demonstrated
consistently higher levels of HSV DNA relative to infectious HSV over 72 hours under high and low MOI conditions. High viral loads
occurred later under low versus high MOI conditions. Expansion in levels of HSV DNA and infectious HSV was delayed in the
supernatant relative to intracellularly. Our best model closely recapitulated the observed viral kinetics. The model assumes a nonvariable eclipse phase in all infected cells prior to viral production and saturating levels of viral diffusion out of cells. Infected cells
produced approximately 375 HSV DNA genomes per infectious particle. Production rates of viral DNA were 227500-fold higher thandiffusion rates of viral DNA out of cells. Infectious particles diffused out of cells approximately 3 times faster than non-infectious HSVDNA. Clearance rates of infectious particles and HSV DNA from the supernatant were negligible suggesting that immune mechanisms
clear viral particles in vivo. Overall, our results suggest that the measurement of extracellular viral genomes using PCR misrepresents
the kinetics of intracellular formation of infectious viral particles.

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Oral
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6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-04]Absolute quantification of influenza A viral proteins during single-round replication indifferent host cells
Author(s)Jan Küchler (Presenter), Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg,
Germany; Patricia Opitz, Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg,
Germany; Ingo Jordan, ProBioGen AG, Herbert-Bayer-Str. 8, 13086, Berlin, Germany; Yvonne Genzel, Max Planck Institute for Dynamics
of Complex Technical Systems, Bioprocess Engineering, Magdeburg, Germany; Dirk Benndorf, Max Planck Institute for Dynamics ofComplex Technical Systems, Bioprocess Engineering, Magdeburg, Germany; Applied Biosciences and Process Engineering, Anhalt
University of Applied Sciences, Köthen, Germany; ;Otto von Guericke University Magdeburg, Bioprocess Engineering, Magdeburg,
Germany; Udo Reichl, Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Magdeburg,
Germany; Otto von Guericke University Magdeburg, Bioprocess Engineering, Magdeburg, Germany

Short Abstract

Various cell lines can be used as host for influenza vaccine production. In order to improve cell culture-based production yields, adetailed understanding and modelling of virus replication can be crucial. In this context, quantitative data regarding the dynamics ofviral protein expression could add highly valuable information, and support optimization of existing mathematical models of theinfluenza A virus replication cycle. Here, we present a mass spectrometry-based assay for the absolute quantification of five major
influenza A virus (IAV) proteins, namely hemagglutinin (HA), neuraminidase (NA), nucleoprotein (NP), matrix protein 1 (M1) and nonstructural protein 1 (NS1) in different suspension host cells. All investigated IAV proteins were detected over a single replication cycle
in MDCK, AGE1.CR and HEK293SF cells. In MDCK cells, M1 was predominantly produced with 2.8E+08 copies/cell at 12 hpi; NP(4.5E+07 copies/cell) and NS1 (1.5E+07 copies/cell) were less abundant, followed by HA (7.0E+06 copies/cell) and NA (7.4E+05
copies/cell). Differently to this, in AGE.CR cells, M1, NP and NS1 were produced at equimolar levels at 2 3E+07 copies/cell, whereas HA(3.5E+06 copies/cell) and NA (6.1E+05 copies/cell) were produced at relative ratios similar to those in MDCK cells. In HEK293SF cells
all measured IAV proteins could be detected as early as 2 hpi. Here, viral protein production increased linearly and resulted in similar
concentrations for NP (1.3E+09 copies/cell), M1 (8.4E+08 copies/cell) and NS1 (8.3E+08 copies/cell). Again, HA (2.6E+08 copies/cell)and NA (2.8E+08 copies/cell) were produced in lower quantities. In sum, absolute IAV protein copy numbers were quantified in different
infected host cells providing important insights into viral protein dynamics. A comparison of three cell lines revealed surprisingdifferences in expression profiles that may impact replication and morphogenesis of IAV.

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6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-05]Mathematical modeling suggests that olsetamivir increases the rate of clearance of
influenza A virus-infected cells by cytotoxic immunity
Author(s)John Maddox, University of Tennessee; Vitaly V. Ganusov, University of Tennessee (Presenter)

Short Abstract

Influenza A and B viruses cause infection of a limited duration in immunocompetent individuals yet mechanisms that are responsible
for the duration of viral shedding are not completely understood. It has been suggested that depletion of target cells, required for virus
replication, can explain influenza virus dynamics in humans. By using our recently digitized data from influenza A and B virus infectionof human volunteers in clinical trials of olsetamivir we tested if target cell limited model or our new immune response-mediated control
models describe best the data for over 250 volunteers. We found that all models could fit the shedding data from individual volunteers
with similar quality suggesting that such data are typically insufficient to discriminate between the alternatives. Interestingly, in thisanalysis we found no consistent impact of olsetamivir on model parameters that arose due to bias in sub-selecting volunteers with
sufficient number of measurements above the limit-of-detection. We then fitted the models to data for placebo- or olsetamvir-treatedvolunteers infected with influenza A virus using nonlinear mixed effects. We found that the model in which cytotoxic immune responsecontrols viral shedding explains the data for both cohorts with best quality. The best fit model predicted that variability in viral
shedding between individual volunteers comes primarily from the immune response-related parameters (the rate at which infected
cells are cleared by the immunity and immune response activation threshold) and that olsetamivir increased the rate of clearance ofvirus-infected cells. Our results, thus, provide novel insights into regulation of influenza virus shedding kinetics in humans and propose
a new mechanism by which olsetamivir controls influnza A virus infection in vivo.

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Oral
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6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-06]

Drug discovery on a mpox cell culture infection assay
Author(s)Koichi Watashi, Research Center for Drug and Vaccine Development, National Institute of Infectious Diseases, Tokyo, Japan (Presenter)

Short Abstract

Rapid drug discovery against emerging/re-emerging viruses is demanded along with the growing global risk for the expansion of
infectious diseases. So far, we have established infection cell culture systems for a panel of different class of viruses, including
coronaviruses, flaviviruses, paramyxoviruses, hepadnaviruses, deltaviruses, and poxviruses for widely conducting drug discovery
study. Given an international outbreak of mpox (monkeypox) from May 2022, we optimized a cell culture mpox infection assay andscreened a library consisting of over 3,000 approved clinical drugs. We selected 20 drugs that reduced the viral DNA levels in mpox
infected cells and profiled dose-dependent antiviral activity of the drugs in the cell culture system. Based on the pharmacokinetics
information already available, we calculated time-dependent antiviral activity after drug administration, which then provided an impact
on viral load in patients from mathematical modeling describing mpox infection (under the collaboration with Prof. S. Iwami’s group).
With the virus dynamics data in clinical mpox patients, we predicted the time course viral load in patients upon drug treatment. These
approaches selected atovaquone as one of the candidates potentially reducing the mpox viral load in the current clinical doses
approved. From the mechanistic analyses, we suggested that atovaquone inhibited mpox replication through the inhibition of
dihydroorotate dehydrogenase (DHODH), a rate limiting enzyme in de novo pyrimidine biosynthesis. We are now conducting an animal
infection assay to examine the in vivo activity of drugs. Our approach provided a scheme rapidly selecting and prioritizing drugcandidates that are relevant for testing in in vivo infection model and proposing as a drug candidate.

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Oral
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6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-07]

Inference on dual-spread models of viral infection within the host
Author(s)Thomas Williams, University of Melbourne (Presenter); James McCaw, University of Melbourne; James Osborne, University of Melbourne

Short Abstract

There is growing popularity in the virus dynamics literature of models which track two modes of infection spread: infection by cell-freevirions, and infection by membrane-bound virus via cell-to-cell contact. These two mechanisms represent distinct biologicalmechanisms which interact with host biology and therapeutics in different ways. Therefore, it is of interest to understand and quantify
the influence they have on model dynamics. Here we perform analysis of the effect of two key model parameters - those controlling
the rate of infection via each mechanism - on model outcomes, and use bayesian inference methods to test our ability to infermechanism proportions from hypothetical experimental data.

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6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-08]How gene expression can inform dynamical models?
Author(s)Rodolphe Thiébaut (Presenter), ; Edouard Lhomme, Mélanie Huchon, Kalidou Ba, Boris Hejblum, Mélanie Prague, University of
Bordeaux, Vaccine Research Institute, Bordeaux, France

Short Abstract

The value of viral and immune dynamics mathematical modeling largely depends on the capacity of estimating model parameters withdata. These data are repeated measurements of viral or cellular concentrations in blood or other tissues. Unfortunately, thesemeasurements are usually sparse, which poses a challenge for practical identifiability. This is particularly prevalent for cellularconcentrations, as obtaining repeated venous sampling in substantial amount for flow cytometry is quite restrictive. We propose asolution based on leveraging gene expression measurements in whole blood. Firstly, deconvolution algorithms can be used to predict
the abundance of cell populations based on the whole blood gene expression. The underlying hypothesis is that the abundance ofparticular gene expressions in whole blood is mainly driven by the abundance of the cells expressing those genes, rather than by anincrease in gene expression at the single cell level. Therefore, a reference matrix relating gene expression with various cell types canbe used to predict the abundance of a specific cell type based on gene abundances measured in the whole blood. Secondly, whole
blood gene expression can be measured using a finger prick test, which allow study participants to perform the sampling themselves ina minimally invasive way. This in turn unlocks the path to much more intensive and frequent sampling. Thirdly, the frequently
predicted populations can be used in the observation model of a dynamical system. This approach helps overcome the challenges
posed by sparse data and restricted venous sampling, leading to better estimates of model parameters and improved understanding ofviral and immune dynamics. We are illustrating the approach at each step by presenting results and obstacles from several published(Obermoser et al., 2013, Rinchai et al., 2022) and unpublished studies (clinicaltrials.gov NCT04356495).

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6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-09]Modelling the association between neutralizing antibody levels and SARS-CoV-2 viral
dynamics : implications to define correlates of protection against infection
Author(s)Guillaume Lingas, Université Paris Cité, IAME, INSERM, F-75018, Paris; Delphine Planas, Virus and Immunity Unit, Institut Pasteur, CNRS
UMR3569, Université Paris Cité , Paris France ; Vaccine Research Institute, France.; Hélène Péré, Microbiology Department, Virology
Unit, APHP, Hôpital Européen Georges-Pompidou, F-75015, Paris, France ; Darragh Duﬀy, Institut Pasteur, Université Paris Cité , Paris,
France; Isabelle Staropoli, Institut Pasteur, Université Paris Cité , CNRS UMR3569, Paris, France.; Françoise Porrot, Virus and Immunity
Unit, Institut Pasteur, CNRS UMR3569, Université Paris Cité , Paris France ; Vaccine Research Institute, France.; Florence GuivelBenhassine, Virus and Immunity Unit, Institut Pasteur, CNRS UMR3569, Université Paris Cité , Paris France ; Vaccine Research Institute,France.; Nicolas Chapuis, Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d’hématologie biologique, Hôpital
Cochin, Paris, France; Camille Gobeaux, Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d’hématologie
biologique, Hôpital Cochin, Paris, France; David Veyer, Microbiology Department, Virology Unit, APHP Paris, France ; Université Paris
Cité, INSERM UMRS1138, Paris, France; Constance Delaugerre, Virology Department, AP-HP, Hôpital Saint-Louis, F-75010 Paris, France,
Université Paris Cité, Inserm U944, Biology of emerging viruses, F-75010, Paris, France; Jérôme Le Goff, Virology Department, AP-HP,
Hôpital Saint-Louis, F-75010 Paris, France, Université Paris Cité, Inserm U976, INSIGHT Team, F-75010, Paris, France; Prunelle Getten,
INSERM UMRS 970, Université Paris Descartes, Paris, France.; Jérôme Hadjadj, Department of Internal Medicine, National ReferenceCenter for Rare Systemic Autoimmune Diseases, AP-HP, APHP.CUP, Hôpital Cochin, Paris, France.; Adèle Bellino, Unité de Recherche
Clinique Cochin-Necker, AP-HP, Paris, France.; Béatrice Parfait, Fédération des Centres de Ressources Biologiques - Plateformes de
Ressources Biologiques AP-HP.Centre-Université Paris Cité, Centre de Ressources Biologiques Cochin, Hôpital Cochin, F-75014, Paris,
France; Jean-Marc Treluyer, Unité de Recherche clinique, Hôpital Cochin, AP-HP.Centre - Université de Paris, Paris, France.; Olivier
Schwartz, Microbiology Department, Virology Unit, APHP, Hôpital Européen Georges-Pompidou, F-75015, Paris, France ; Jérémie Guedj,
Université Paris Cité, IAME, INSERM, F-75018, Paris (presenter); Solen Kernéis, Université Paris Cité, IAME, INSERM, F-75018, Paris ;Equipe de Prévention du Risque Infectieux (EPRI), AP-HP, Hôpital Bichat, F-75018 Paris, France; Benjamin Terrier, Department ofInternal Medicine, National Reference Center for Rare Systemic Autoimmune Diseases, AP-HP, APHP.CUP, Hôpital Cochin, F-75014,
Paris, France ; Université Paris Cité, INSERM U970, Paris Cardiovascular Research Center, F-75015, Paris, France.

Short Abstract

While anti-SARS-CoV-2 antibody kinetics have been well described in large populations of vaccinated individuals, we still poorly
understand how they evolve during a natural infection and how this impacts viral clearance. For that purpose, we analyzed the kinetics
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https://iblab.bio.nagoya-u.ac.jp/special/2023/virusof both viral load and neutralizing antibody levels in a prospective cohort of individuals during acute infection by Alpha variant. Using amathematical model, we show that the progressive increase in neutralizing antibodies leads to a shortening of the half-life of both
infected cells and infectious viral particles. We estimated that the neutralizing activity reached 90% of its maximal level within 8 days
after symptoms onset and could reduce the half-life of both infected cells and infectious virus by a 6-fold factor, thus playing a key roleto achieve rapid viral clearance. Using this model, we conducted a simulation study to predict in a more general context the protection
conferred by the existence of pre-existing neutralization, due to either vaccination or prior infection. We predicted that a neutralizing
activity, as measured by ED50 >10^3, could reduce by 50% the risk of having viral load detectable by standard PCR assays and by
99% the risk of having viral load above the threshold of cultivable virus. This threshold value for the neutralizing activity could be used
to identify individuals with poor protection against disease acquisition.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-10]

Impact of variants of concern on SARS-CoV-2 viral dynamics in non-human primates
Author(s)Aurélien Marc, Université Paris Cité (Presenter); Romain Marlin, Université Paris-Saclay CEA; Flora Donati, Institut Pasteur, National
Reference Center for Respiratory Viruses; Mélanie Prague, Inria Bordeaux Sud-Ouest; Marion Kerioui, Université Paris Cité; Cécile
Hérate, Université Paris-Saclay CEA; Marie Alexandre, Inria Bordeaux Sud-Ouest; Nathalie Dereuddre-bosquet, Université Paris-Saclay
CEA; Julie Bertrand, Université Paris Cité ; Vanessa Contreras, Université Paris-Saclay CEA; Sylvie Behillil, Institut Pasteur, National
Reference Center for Respiratory Viruses; Pauline Maisonnasse, Université Paris-Saclay CEA; Sylvie Van Der Werf, Institut Pasteur,
National Reference Center for Respiratory Viruses; Roger Le Grand, Université Paris-Saclay CEA; Jérémie Guedj, Université Paris Cité

Short Abstract

The impact of variants of concern (VoC) on SARS-CoV-2 viral dynamics remains poorly understood and essentially relies on
observational studies subject to various sorts of biases. In contrast, experimental models of infection constitute a powerful model toperform controlled comparisons of the viral dynamics observed with VoC and better quantify how VoC escape from the immune
response. Here we used molecular and infectious viral load of 78 cynomolgus macaques to characterize in detail the effects of VoC on
viral dynamics. We first developed a mathematical model that recapitulate the observed dynamics, and we found that the best model
describing the data assumed a rapid antigen-dependent stimulation of the immune response leading to a rapid reduction of viral
infectivity. When compared with the historical variant, all VoC except beta were associated with an escape from this immune
response, and this effect was particularly sensitive for delta and omicron variant (p<10-6 for both). Interestingly, delta variant was
associated with a 1.8-fold increased viral production rate (p=0.046), while conversely omicron variant was associated with a 14-fold
reduction in viral production rate (p<10-6). During a natural infection, our models predict that delta variant is associated with a higher
peak viral RNA than omicron variant (7.6 log10 copies/mL 95% CI 6.8 – 8 for delta; 5.6 log10 copies/mL 95% CI 4.8 – 6.3 for omicron)while having similar peak infectious titers (3.7 log10 PFU/mL 95% CI 2.4 – 4.6 for delta; 2.8 log10 PFU/mL 95% CI 1.9 – 3.8 for omicron).
These results provide a detailed picture of the effects of VoC on total and infectious viral load and may help understand somedifferences observed in the patterns of viral transmission of these viruses.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-11]in vitro overestimates of nirmatrelvir / ritonavir potency for SARS-CoV-2 infection inhumansAuthor(s)Shadi Esmaeili-Wellman, Katherine Owens, Fabian Cardozo Ojeda, Joshua T Schiffer

Short Abstract

In a pivotal phase 2-3 randomized, double-blinded, placebo-controlled clinical trial, ritonavir-boosted nirmatrelvir (Paxlovid) decreased
hospitalization or death by 89% relative to placebo when given early during symptomatic infection to high-risk individuals. Paxlovid also
decreased nasal viral load 5 days after treatment initiation by 0.87 log10 copies / mL relative to placebo. To optimize future use of
Paxlovid, it is necessary to understand how in vivo potency of the drug compares to pre-clinical estimates obtained in vitro. We applieda mathematical model framework integrating viral-immune dynamic equations, nirmatrelvir pharmacokinetics, and pharmacodynamic
dose response curves to the clinical trial data. The viral dynamic model was first calibrated against data from the National Basketball
Association cohort and captures observed kinetics of several variants including viral rebound off treatment. The integrated model
recapitulated viral load trajectories in the placebo group of the clinical trial, as well as observed viral load reductions in the clinical trial
days 3, 5, 10 and 14 post treatment. The model estimates the plasma concentration of nirmatrelvir required to reduce cellular
infection by 50% in humans to be ~100-fold larger than the concentration required in vitro. We estimate that a maximally potent agent
could reduce viral load by ~3.0 log10 copies / mL at 5 days post treatment. Paxlovid antiviral effects are reduced by decreased in vivo
potency and by short drug half-life. These features in addition to lack of concurrent immune pressure early during infection also likely
explain the drug’s failure to achieve efficacy as post exposure prophylaxis in a subsequent trial. Finally, model output identifies
virologic conditions that predispose towards viral rebound and suggests that extending treatment to 10 days rather than increasing
daily dose is most likely to limit viral rebound.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-12]

Establishment of HIV-timer system to analyze expression dynamics of HIV provirus
Author(s)Yorifumi Satou, Division of Genomics and Transcriptomics, Joint Research Center for Human Retrovirus Infection, Kumamoto University,
Kumamoto, Japan (Presenter)

Short Abstract

HIV-1 infection spread through production of progeny viruses from infected host cells. Vigorous viral production induces cytopathic
effect on the host cells, resulting in depletion of the infected cells. Even so, some infected cells persist for a long time by minimizing
viral production, thereby contributing to the formation of latent viral reservoir. A remarkable advance of combined anti-retroviraltherapy (cART) can stop viral replication and inhibit onset of AIDS. However, cART is not potent enough to reduce latent viral reservoir
to achieve HIV cure. In addition, it is poorly understood how viral latent reservoir is established and maintained. To address thesequestions, we established a new in-vitro model to monitor HIV-1 proviral transcription by timer-fluorescence protein. We constructed
recombinant HIV-timer construct in which timer-fluorescent protein is under control of the HIV-1 promoter in the 5’ LTR. The timerfluorescent protein spontaneously shifts its emission spectrum from blue to red when expressed in cells, which enables us to visualize
proviral expression dynamics in infected cells. We infected Jurkat T cells with single-round timer-HIV and analyzed them by flow
cytometry. Timer-blue signal was not detectable at 12 hours but detectable at 24 hours after infection. We observed transition fromtimer-blue to timer-red in a time-dependent manner. As expected, most infected cells seemed to be removed by cell apoptosis.
However, there was a small cell fraction containing timer-red signal only, indicating the presence of just silenced infected cells. I’d liketo introduce this new in-vitro model for HIV latency research and share some key results so far in this presentation.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-13]

CAR T cells for HIV cure, a tale of four macaques
Author(s)Elizabeth R Duke, Fred Hutchinson Cancer Center, University of Washington;; Katherine Owens, Fred Hutchinson Cancer Center(presenter); ; Chloe Bracis, Fred Hutchinson Cancer Center, Université Grenoble Alpes;; Christopher W Peterson, Fred Hutchinson
Cancer Center, University of Washington; ; Hans-Peter Kiem, Fred Hutchinson Cancer Center, University of Washington; ; Joshua T
Schiffer, Fred Hutchinson Cancer Center, University of Washington;; E Fabian Cardozo-Ojeda, Fred Hutchinson Cancer Center

Short Abstract

The main barrier to curing human immunodeficiency virus (HIV) is a subset of long-lived, latently infected CD4+ T cells that reactivate
and cause viral rebound when people with HIV stop taking daily antiretroviral therapy (ART). This post-ART viral rebound may be
reduced by infusing T cells with HIV-specific chimeric antigen receptors (CAR T cells) to target and destroy reactivating latent cells. In apilot study, four rhesus macaques infected with Simian-HIV (SHIV) received a single infusion of CAR T cells during ART. After stopping
ART, macaques treated with CAR T cells had a lower viral peak than controls. We developed ordinary differential equations (ODE) tomodel this intervention. First, we identified a system of ODEs that recapitulates viral loads (VLs) during primary infection and following
ART interruption in the control animals. Then, we explored extensions of the best fit VL model to include CAR T cell dynamics. We fit
these candidate treatment models to plasma VLs and CD4+ and CD8+ CAR T cell measurements from CAR-treated macaques. In thebest fit version of the treatment model, the parameters that modulate CAR T cell proliferation in response to SHIV and the killing of
infected cells correlated with significantly lower post-analytical treatment interruption viral peaks. We simulated the data-validated
model for each macaque to find conditions in which the CAR T cell infusion achieved ART-free SHIV remission. Although gene and celltherapy strategies for HIV cure are in the initial stages, mathematical modeling might accelerate the success of these approaches.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-14]The impact of CD8+ lymphocytes on the SIV reservoir establishment under ART: amodel-based data analysis approach
Author(s)Maura Statzu, Emory University; Wang Jin, University of New South Wales (Presenter); Emily Fray, Johns Hopkins University; Andrew
Kam Ho Wong, Emory University; Mithra Kumar, Johns Hopkins University; Elizabeth Ferrer, Johns Hopkins University; Steffen Docken,
University of New South Wales; Mykola Pinkevych, University of New South Wales; Julia McBrien, Emory University; Christine
Fennessey, Frederick National Laboratory for Cancer Research; Brandon Keele, Frederick National Laboratory for Cancer Research;
Shan Liang, Emory University; Justin Harper, Emory University; Simona Mutascio, Emory University; Lavinia Franchitti, Emory
University; Hong Wang, Emory University; Davide Cicetti, Emory University; Steven Bosinger, Emory University; Diane Carnathan,
Emory University; Thomas Vanderford, Emory University; David Margolis, University of North Carolina at Chapel Hill; J. Victor GarciaMartinez, University of North Carolina at Chapel Hill; Ann Chahroudi, Emory University; Mirko Paiardini, Emory University; Janet
Siliciano, Johns Hopkins University; Miles Davenport, University of New South Wales; Deanna Kulpa, Emory University; Robert Siliciano,
Johns Hopkins University; Guido Silvestri, Emory University

Short Abstract

Persistence of the human immunodeficiency virus type-1 (HIV-1) latent reservoir in infected individuals remains a problem despite fully
suppressive antiretroviral therapy (ART). While reservoir formation begins during acute infection, the mechanisms responsible for its
establishment remain unclear. CD8+ T cells are important during the initial control of viral replication. However, the role of CD8+ T
cells on the SIV reservoir establishment also remains unclear. Here we examined the effect of CD8+ T cells on formation of the latent
reservoir in simian immunodeficiency virus (SIV)-infected macaques by performing experimental CD8+ depletion either before
infection or before early ART initiation. To quantify the role of CD8+ T cells, we proposed a nonlinear mixed-effects model to describe
the virus dynamics in the primary infection, in which both VL and RNA are described in terms of the DNA associated with short- andlong-lived infected cells. Calibrating the model to the grouped data, we found that the depletion of CD8+ T cells results in (i) slower
decline of plasma viremia, indicating that cytotoxic T lymphocytes (CTLs) reduce the average lifespan of productively infected cells,and (ii) increased ratio of cell-associated viral RNA/DNA. However, the CD8+ depletion did not change the size of the virus reservoir.
These results indicate that during acute SIV infection the persistent reservoir under ART is established mainly through direct formationand independent of CTL control.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-15]

Mechanistic modelling of effect of target cell limitation on protection from HIV
Author(s)Steffen S. Docken, UNSW (Presenter); Deborah Cromer, UNSW; Zachary Detwiler, CRISPR Therapeutics; Christian L. Boutwell, MIT andHarvard; Todd M. Allen, MIT and Harvard; Daniel T. Claiborne, The Wistar Institute; Miles P. Davenport, UNSW

Short Abstract

HIV infection of T cells involves binding to two cell surface proteins – the CD4 molecule and the CCR5 co-receptor. To date, the only
instances of HIV ‘cure’ were the result of transplantation with stem cells containing mutations in the CCR5 coreceptor gene, which
reduce the ability of most HIV strains to infect cells. Thus, researchers are pursuing different approaches to gene therapy alternatives
to reduce CCR5 expression on CD4+ T cells. One of the primary questions relating to the feasibility of gene therapy is what fraction oftarget cells must have acquired the mutation to achieve HIV cure or protection from HIV acquisition. To answer this question, mice
underwent human stem cell transplantation with mixtures of CCR5 intact and knock-out stem cells. Transplanted stem cells ranged
from 0% to nearly 100% CCR5 knock-out in roughly 25% increments, with each study arm containing 15 animals (13 in the 50% arm).
Animals were subsequently inoculated weekly with HIV, and the time-to-infection and post-infection viral levels were monitored. The
observed risk of infection per inoculation decreased from 28% in the 0% knock-out arm to 5% and 0% in the 75 and 100% knock-out
arms. We sought to mechanistically characterize the effect of CCR5 knock-out on infection risk, and therefore developed a probabilistic
model of CD4+ T cell infection and subsequent replication in the presence of different fractions of CCR5 knockout cells. Based on
goodness-of-fit and due to having fewer parameters, this mechanistic model captures the time-to-infection data better than estimating
infection risk separately for each study arm. From this observed relationship between number of cells infected and fraction of cells
containing CCR5, we can predict how viral levels and time-to-rebound following treatment interruption would decrease and increase,respectively, with CCR5 ablation in an individual living with HIV.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-16]

Modeling SIV dynamics incorporating effector function measurements of CD8 T cells
Author(s)Bharadwaj Vemparala, Indian Institute of Science (Presenter); Vincent Madelain, Université Paris-Diderot; Caroline Passaes, Institut
Pasteur, CEA-Université Paris-Saclay; Valérie Monceaux, Institut Pasteur; Nathalie Dereuddre-Bosquet, CEA-Université Paris-Saclay;
Roger Le Grand, CEA-Université Paris-Saclay; Véronique Avettand-Fenoel, Université Paris-Descartes, Assistance Publique-Hôpitaux deParis; Bruno Vaslin, CEA-Université Paris-Saclay; Asier Sáez-Cirión, Institut Pasteur; Narendra M Dixit, Indian Institute of Science;
Jérémie Guedj, Université Paris-Diderot

Short Abstract

Robust effector responses by CD8 T cells have been implicated in the long-term control of HIV/SIV infections. To quantify the effector
responses, recent studies have developed an ex vivo assay that measures the capacity of virus-specific CD8 T cells to suppress
infection. Understanding their effects, however, requires describing the assay using a mathematical model and incorporating thedescription into within-host virus dynamics models. Here, we have developed such a description. The assay involves inoculation of host
CD4 T cells in the presence or absence of CD8 T cells and measuring the suppressive capacity as the difference in the viral levels in
the two cultures. We developed a model to describe this assay procedure and consequently the suppressive capacity, which was thenused to derive a framework that can incorporate longitudinal measurements of suppressive capacity into within-host models. This
framework allowed parameter estimation using nonlinear mixed effects modeling and simultaneous analysis of the suppressive
capacity measurements and other canonical longitudinal markers like viremia and proviral DNA. We employed the formalism toelucidate novel correlates of natural control of SIV infections in macaques. This framework can be extended to analyzing posttreatment control.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-17]

Ligand discrimination in cross-wired immune signaling pathways
Author(s)Anton Zilman, University of Toronto; Duncan Kirby, University of Toronto

Short Abstract

Cytokine signaling plays central role in both the innate and adaptive immune response to infection. Puzzlingly, many cytokine signaling
pathways are highly cross-wired whereby extracellular ligand molecules act through shared receptors or overlapping pathways
downstream. It remains unclear how cells can reliably transmit information in such conditions especially when the ligands are present
in multiple combinations. Similar problems arise in TCR signaling and other immune contexts. I will present several theoretical modelsof accurate and specific input-output mapping in cross-wired signaling pathways, and show how a ligand-receptor signaling pathway
can be mapped onto a classifier of an artificial neural network type. I will present the results of the combined experimental andcomputational testing of some of the theoretical models on the example of a major class of signaling molecules of the innate immune
system, Type I Interferons (IFN), where multiple IFNs act through the same receptor. These results have important implications for thesignaling by a broad class of cross-wired signaling pathways and for the clinical use of signaling molecules in disease treatment.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-18]

Yet another stochastic model of virus infection with some new results
Author(s)Christian Quirouette, Toronto Metropolitan University; Daniel Cresta, Toronto Metropolitan University; Jizhou Li, RIKEN; Kathleen P.
Wilkie, Toronto Metropolitan University; Haozhao Liang, RIKEN/University of Tokyo; Catherine A.A. Beauchemin, RIKEN/Toronto
Metropolitan University (Presenter)

Short Abstract

Many have proposed and evaluated stochastic versions of the usually mean-field models describing the course of a virus infection
within a cell culture or a host. Here, we propose yet another stochastic model which differs from predecessors in one key aspect: it
explicitly represents the effect of random infection failure after a virus has successfully and irreversibly entered a cell. In comparing
antiviral modes of action, we find that for a given efficacy, an antiviral that enhances infection failure after a virus has irreversibly
entered a cell (e.g., endosomal fusion inhibitor, integrase inhibitor) always performs at least as well or better than one reducing either
the rate of virus entry into cells, or the rate of virus production by successfully infected cells. Beyond the probability that infection will
establish or go extinct under different antiviral therapies, we show that so-called established infections can be diverse, and the fractionof cells infected by such infections can vary significantly for a given probability of infection establishment. We show why the longstanding belief that an infection is more likely to fail if infected cells produce virus continuously over their infectious lifespan rather
than if they release it all at once as a single burst, is incorrect.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-19]Testing phylogeographic inferences methods on simulated epidemics with realistic
selection effects
Author(s)Nicolas Ochsner, ETH Zurich (Presenter); Roland Regoes, ETH Zurich; Sebastian Bonhoeffer, ETH Zurich

Short Abstract

In recent years computational methods such as phylodynamics have been used to infer population dynamic and evolutionary
parameters from epidemiological sequencing data. These methods are typically built on the assumption that selection is neutral,
which, e.g. in the case of HIV-1, is known to be violated. To estimate accuracy and biases of these methods when applied in a nonneutral selection regime we simulate viral epidemics in-vitro and in-silico. We use a process-based in-silico simulation that allows finegrained control of the evolutionary parameters, such as mutation rates, recombination rates and non-epistatic selection effects. In thisway we simulated the evolution of viral populations in two compartments with varying migration rates and selection regimes and findthat the migrations rates are systematically overestimated by phylogeographic models when there is non-neutral evolution. I will alsopresent our experimental setup that utilizes liquid handling robotics and high-throughput, long-read sequencing to trace theevolutionary trajectory of multiple viral populations. The precision and flexibility of the liquid handling robot allows us to simulate
complex processes such as migration or changing environments. At the same time high-fidelity PacBio sequencing yields a uniquedataset that recovers the population structure while preserving genetic linkage. In early applications of our setup we observe parallel
evolution on the level of the genome similar to what we expect from a non-neutral selection regime that we simulated in-silico.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-20]Analysis of the risk and pre-emptive control of viral outbreaks accounting for withinhost dynamics: SARS-CoV-2 antigen testing as a case study
Author(s)William S Hart, University of Oxford (Presenter); Hyeongki Park, Nagoya University; Yong Dam Jeong, Nagoya University; Kwang Su
Kim, Pukyong National University; Raiki Yoshimura, Nagoya University; Robin N Thompson, University of Warwick; Shingo Iwami,
Nagoya University

Short Abstract

Estimates of the risk of viral disease outbreaks occurring in different populations are important for effective allocation of limited
control resources. Here, we describe how within-host virus dynamics models can be used to inform outbreak risk calculations.
Compared to population-level models previously used to estimate outbreak risks, our approach enables more detailed analysis of how
the risk can be mitigated through pre-emptive interventions. Considering SARS-CoV-2 as a case study, we quantify the within-host
dynamics using data from individuals with omicron variant infections. We then explore how the local SARS-CoV-2 outbreak risk can be
mitigated through regular antigen testing of the local population. Our results demonstrate that antigen testing reduces, but may noteliminate, the outbreak risk, depending on the frequency of testing and characteristics of local transmission. Additionally, we show that
accounting for heterogeneity in within-host dynamics between individuals affects outbreak risk estimates and assessments of the
impact of antigen testing. We therefore provide both an adaptable framework for including within-host dynamics in outbreak risk
calculations for SARS-CoV-2 and other viruses, and insights into important factors to consider when using this approach to plan preemptive control.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-21]

Border policies to prevent COVID-19
Author(s)Alex R Cook, National University of Singapore (Presenter)

Short Abstract

Movement across borders was restricted to an unprecedented degree during the COVID-19 pandemic, with many countries
implementing testing or quarantine measures for extended periods. The implementation was, however, different in different polities
and over different phases of the pandemic, and as part of preparation for the next pandemic, it behoves us to ask which policies werereached the “best” combination of stringency (to protect the population) and lightness (to protect the economy). This requires fusing
information on the dynamics of disease at the individual level, the sensitivity of test results and the local and international
epidemiology. During COVID-19, the modelling group at the National University of Singapore worked closely with the Singapore
government to assess the effect of different implementations of border measures—considering different durations of quarantine, of
testing types (PCR and antigen tests) and frequencies, and different risk “budgets”—with some of the policies we evaluatedsubsequently being implemented. In this talk / poster, I will describe the formulation of the model we used, and the results, but also
the process and insights gained from working with government and industry to inform these policies, and the direction that future
models of border control should move towards.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-22]Age-dependent isolation guideline to reduce the burden of isolation of COVID-19:
simulation using longitudinal viral load data from SARS-CoV-2 Omicron cases in
Singapore
Author(s)Keisuke Ejima, Nanyang Technological University (Presenter)

Short Abstract

Even after effective pharmaceutical interventions for COVID-19 were developed and distributed around the world, non-pharmaceutical
approaches, especially isolation, take a critical role in controlling the pandemic. However, there has been a debate on how to designideal isolation guidelines. We propose the refined-fixed period approach, which sets different isolation period for different groups with
distinct viral load dynamics, and quantitatively compare it with the fixed-period approach, which sets the same length of isolation
period for all patients. To compare the two isolation guidelines, a simulator producing longitudinal viral load data of SARS-CoV-2 wasdeveloped. The simulator was based on the viral dynamics model, and the model parameters were estimated using the longitudinalviral load data from SARS-CoV-2 omicron patients in Singapore. The model accounted for sex and age as covariates. The refined-fixedperiod guideline was built considering the covariates which significantly impact on the viral dynamics. The risk and the burden werecomputed on the viral load data generated by the simulator to compare the two isolation guidelines. We found that age and sex
significantly impact on the viral dynamics. Especially, old age was associated with long duration of viral shedding. Thus, we set
different length of isolation for those at age 0-17, 18-49, and 50+ under the refined-fixed period guideline. Setting risk below 5% as an
acceptable level, we could minimize the burden to 8.2 days under the fixed-period guideline (14 days of isolation). The burden could
be reduced to 7.0 days under the refined-fixed-period guideline (isolation periods were 8 days, 13 days, and 15 days for those at age
0-17, 18-49, 50+, respectively). We could reduce the burden due to isolation by more than a day by simply adopting the refined-fixedperiod guideline. Our simulation framework could be used to quantitatively assess isolation guidelines of various infectious diseases.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-23]Modelling measles inoculum dose responses to study paradoxical mechanisms of
immune control of acute viremia
Author(s)Anet J.N. Anelone, National University of Singapore (Presenter); Hannah E. Clapham, National University of Singapore, Saw Swee HockSchool of Public Health Singapore

Short Abstract

The progression of infections can vary depending on the inoculum dose, the initial number of infecting pathogens. For measles (MV),the higher the inoculum dose, the earlier the peak of acute viremia, but the magnitude of the peak viremia remains almost constant.
Our understanding of the mechanisms underlying inoculum dose responses in infections is currently limited due to a lack ofexperimental and mathematical modelling studies. This is challenging in the context of the ‘measles paradox’ i.e., the seemingly
contradictory progression of MV infection to severe lymphocyte depletion before clearance of acute viremia, mediated by strong MVspecific T cell responses. Here, we investigated mechanisms underlying the dynamics of acute measles infection following variations ofwild-type MV inoculum dose. We fitted longitudinal data on MV infection in monkeys using maximum likelihood estimation, and used
the Akaike Information Criterion (AIC) to perform model selection to evaluate simple or sophisticated mechanisms for T cell proliferationand killing. The model with the lowest AIC shows that when the inoculum dose increases, the estimated initial number of activated MVspecific T cells tends to increase. The higher the initial number of activated T cells, the earlier the peak of both activated T cells andacute viremia, and the earlier the recovery of the total lymphocyte count. These variations allow similar magnitudes for lymphocyte
depletion, the peak of acute viremia, and the peak of the T cell response. Together, these results suggest the progression of MV
infection is influenced by sensible virus-host interactions at the start of the- infection. These insights may help clarifying historical andfuture clinical cases of measles infection.

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https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[OC-24]

Dynamical systems phenotyping to stratify peg-IFN treatment efficacy in patientswith chronic hepatitis B
Author(s)Naotoshi Nakamura, Nagoya University (Presenter); Kwang Su Kim, Pukyong National University; Shingo Iwami, Nagoya University

Short Abstract

The goal of antiviral treatment for chronic hepatitis B is to prevent disease progression by suppressing hepatitis activity; 48-weektreatment with peg-IFN is used as first-line antiviral treatment for persistently infected individuals. However, because treatment
efficacy is heterogeneous among individuals and treatment has side effects, it is desirable to be able to identify early which individuals
would benefit from treatment. In this study, time series data on three serum biomarkers, HBV DNA, HBsAg and HBcrAg, which
determine treatment response, were used to stratify the treatment efficacy of patients. First, a mathematical model describing thetime-series dynamics of these biomarkers was constructed and parameters were estimated for each individual using non-linear mixed
effects modeling. Clustering of patients based on these parameters showed that patients with high treatment efficacy wereconcentrated in a specific cluster. This cluster was characterized by lower biomarker levels at baseline compared to other clusters, with
HBsAg and HBV DNA declining by more than 1 log10 during the first several weeks of treatment. The degree of decline in the amountof cccDNA remaining in hepatocytes was also greater. Therefore, a machine learning model was created to predict this cluster using
random forest. The results showed that using both the initial biomarker levels at the start of treatment and the cumulative levels up to
several weeks after treatment, it was possible to identify a group of patients with high treatment efficacy with sufficient accuracy.
Other blood markers and patient background factors were also found to be associated with treatment response. Thus, dynamicalsystems phenotyping based on multivariable time-series biomarkers allows patient stratification and prediction of treatment efficacy.
We expect that such a method could also be used to stratify patients with other diseases.

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-01]

Dissecting the multifactorial roles of influenza A virus receptor binding specificity inthe airborne transmission dynamics of an H9N2 virus
Author(s)Xiangjie Sun*, Jessica A. Belser, Joanna A. Pulit-Penaloza, Nicole Brock, Troy J. Kieran, Taronna R. Maines; Influenza Division, National
Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, U.S.A

Short Abstract

As airborne transmissibility represents a prerequisite for a zoonotic influenza A virus to cause a pandemic, it is imperative tounderstand the viral factors that confer a transmissible phenotype. It has been previously shown that influenza A virus receptor binding
specificity for human like receptors (2,6-linked sialic acid) is an important determinant for airborne transmission among mammalianhosts, although the underlying mechanism is not yet been fully understood. We recently demonstrated that a human isolate of H9N2
virus (A/Anhui-Lujiang/39/2018), which possesses a leucine (L) residue at the HA 226 position (H3 numbering) which is indicative of ahuman-like receptor binding potential, acquired a limited capacity for airborne transmission in a ferret model. To dissect the role of the
HA L226 residue in virus airborne transmission, we rescued a mutant virus with a single substitution at HA 226 position from Leucine to
Glutamine (Q), a consensus residue in avian viruses. The L226Q mutant virus lost the ability to transmit by the air in a ferret model,
although the virus had a comparable capacity for replication and induced similar levels of mRNA expression of key immune mediatorsin the upper respiratory tract of ferrets. When virus-laden particles released by inoculated ferrets were quantified, significantly lower
levels of the mutant L226Q virus were detected in exhaled air. We further evaluated virus fitness in a co-infection model in ferrets
either by intranasal inoculation or aerosol inhalation and showed that the wildtype (WT) virus exhibited an increasing dominance innasal wash specimens during viral infection, whereas ferret ethmoid and soft palate tissues displayed different selective preferences
for mutant and WT viruses, respectively. Lastly, we compared virus infection doses by intranasal inoculation and found that the WT
virus could initiate infection at lower doses. Taken together, we conclude that influenza A virus receptor binding specificity plays
multifactorial roles in virus airborne transmission in mammalian hosts, which at least include modulating virus fitness in localized
respiratory tissues with differing receptor distributions, virus aerosolization and exhalation, and host susceptibility.

Poster presentation / 1

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-02]

Investigating the relationship between influenza viral dynamics and clinicalsymptoms using data from Phase 3 clinical trials of oseltamivir
Author(s)Marwa Akao, Nagoya University (Presenter); Yasuhisa Fujita, Nagoya University; Daiki Tatematsu, Nagoya University; Naotoshi
Nakamura, Nagoya University; Shoya Iwanami, Nagoya University

Short Abstract

Influenza viruses cause an acute respiratory infection that affects an estimated 1 billion people every year around the world.
Oseltamivir, an antiviral drug used to treat influenza, has been shown to reduce the time from the beginning of the treatment toalleviation of clinical symptoms in early treatment and is approved in many countries. Virological measures such as the duration ofviral shedding and the area under the curve of viral titer have also been reported to be reduced with oseltamivir, however, the results
vary among trials. A recently published study (Hooker et al., 2021) refuted oseltamivir's efficacy on viral kinetics by detailed analysis
of individuals using data made available by Roche. In this study, we used the published clinical symptom scores and measurements
obtained from laboratory studies, in addition to the viral load. We analyzed these data sets using a mathematical model of influenza
virus infection and statistical models to examine the relationship between the effects of oseltamivir treatment on viral dynamics andthe patients’ clinical symptoms, a point not analyzed by the clinical trials or the above study. We first estimated the parameters of themathematical model using non-linear mixed effects modeling and calculated several features (peak, peak time, duration, area under
the curve) representing the viral dynamics for each patient. We then performed a clustering of patients using these features. Patientsin different clusters showed significant differences in model parameters, patients’ differential leukocyte counts and the time toalleviate symptoms. We further conducted a multivariate analysis to examine how these parameters and patients’ laboratory data
affected the time to alleviate symptoms. Taken together, our results support the hypothesis that both the viral dynamics and patient
background factors contribute to the time to alleviate clinical symptoms.

Poster presentation / 2

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-03]

Using machine learning to identify predictive correlates in ferret in vivo model datafor influenza A risk assessment
Author(s)Troy J. Kieran, Influenza Division, Centers for Disease Control and Prevention (presenter).; Jessica A. Belser, Influenza Division, Centers
for Disease Control and Prevention.; Xiangjie Sun, Influenza Division, Centers for Disease Control and Prevention.; Taronna R. Maines,
Influenza Division, Centers for Disease Control and Prevention.

Short Abstract

The ability of influenza A viruses to infect humans across species boundaries necessitates continual assessments of novel andemerging strains using a variety of viral, host, environmental, and ecological factors. To guide pandemic preparedness efforts, in vivo
assessments of viral pathogenicity and transmissibility in the ferret model are a crucial part of many risk assessment rubrics. However,there isn't a clear knowledge of which biological factors and/or data points from ferret risk assessment efforts are most useful for
predicting pathogenesis and transmission outcomes. Here, we compiled information from 20+ years of risk assessment operations
using the ferret model, including information on 125 different influenza A viruses. Our dataset includes viruses collected during avian
surveillance programs, zoonotic viruses that have jumped species barriers to cause human infection, and well-adapted human seasonal
circulating strains, spanning H1, H2, H3, H5, H7, and H9 subtypes. Several experimental results, including mortality, weight loss (as amarker of disease severity), and respiratory droplet transmission, were predicted using machine learning (ML) techniques. We
identified key empirically determined characteristics that are most consistently linked to high balanced accuracy, specificity, andsensitivity, among other metrics. Gradient boosting machines, random forest, and neural networks were consistently better performingwith balanced accuracy over 0.93 for lethality, 0.78 for weight loss, and 0.97 for transmission. Our findings show that ML algorithms
can be used to summarize complex in vivo experimental work into succinct summaries, determine the best methods for gathering
important experimental metrics, and inform and enhance risk assessment criteria for pandemic preparedness that take in vivo data
into account. Collectively, this study highlights the need for future investment in ML approaches for better analysis and contributes to amore sophisticated integration of statistical and ML methods into in vivo research for more data and biological insight.

Poster presentation / 3

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-04]

Estimation of treatment efficacy of drug candidates against mpox virus in
combination
Author(s)Shotaro Yamamoto, Nagoya University(Presenter); Takara Nishiyama, Nagoya University; Hyeongki Park, Nagoya University; Shingo
Iwami, Nagoya University; Shoya Iwanami, Nagoya University

Short Abstract

Mpox virus (MPXV) is one of zoonotic orthopoxvirus. Because of an outbreak of MPXV in May 2022, WHO declared global healthemergency to MPXV. Main symptoms of mpox, which is caused by infection of mpox virus, are fever and rash. There are few drugs
which are estimated to be effective against mpox virus. The only two drugs, tecovirimat and brincidofovir, have been approved for thetreatment of smallpox in the United States. In preparation for the spread of infection, exploration of other effective drugs and theirevaluation of treatment efficacy are required. In our previous research, atovaquone, a medication for the treatment of Pneumocystis
pneumonia, was suggested to have anti-monkeypox virus effect in infection assay in cell culture and mathematical modeling.
Moreover, combination treatment of atovaquone and tecovirimat was suggested to enhance their antiviral effect. In this study, we
analyzed interaction of these two drugs. For quantitative evaluation of interaction between atovaquone and tecovirimat, we estimatedmagnitude of interaction and calculated time-change in viral road in patients with clinical drug concentrations. First, we estimated thehalf maximal inhibitory concentration and hill coefficient which quantitatively characterize dose-dependent antiviral activity of eachdrug from data for single-drug treatment in infected cells. Next, we estimated magnitude of interaction from data of dose-dependent
antiviral activity in co-treatment. Estimated interaction parameters indicated that tecovirimat enhance antiviral effect of atovaquone.
Using quantified pharmacodynamics of two drugs, we calculated expected time-changes of antiviral effect with approved drug usage.
Finally, we simulated time-change of viral road in patient in clinical drug concentrations from calculated antiviral-effect and virus
dynamics estimated in patients. These results of our study indicate usefulness of combination treatment of atovaquone andtecovirimat.

Poster presentation / 4

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-05]

Genome-based incidence estimation of SARS-CoV-2 with GInPipe
Author(s)Maureen R. Smith, Robert Koch-Institute, Berlin, Germany (Presenter); Maria Trofimova, Robert Koch-Institute, Berlin, Germany; Max
von Kleist, Robert Koch-Institute, Berlin, Germany and Freie Universität Berlin, Germany

Short Abstract

The SARS-CoV-2 pandemic kept the whole world in suspense for 3 years and is still ongoing. Yet, most countries returned back tonormalcy, thanks to broadly available vaccines and less severe symptoms of currently circulating variants. Nevertheless, the virus iscontinuously evolving and new variants of concern are emerging, which may develop mechanisms to escape the immune response or(re-)infect individuals with fatal impacts. Hence, the surveillance of SARS-CoV-2 infections is still an important instrument to handle
local outbreaks. However, the reported number of infected people highly depends on current test strategies and policies, which changeover time, or like currently in many countries, are no longer given. Low reported case numbers may occur indeed as cause of few
infections. But also a low testing coverage can be the reason, be it due to asymptomatic infections or flu- or cold-like symptoms, andoutbreaks remain undetected. Here, we present a method which allows the reconstruction of the “true” incidence history by utilisingevolutionary signals inherent in genomic data of SARS-CoV-2. The rationale is given by the speed at which the virus evolves on
population level: Transmission happens in short time, usually a few days, entailing a limited duration of intra-patient evolution. Thismeans, the number of infected individuals is reflected by the evolutionary signal. Our recently developed workflow GInPipe takes viralsequences along with their collection date as input. Extracting evolutionary information, such as the number of haplotypes andmutants over time, allows us to approximate incidence correlates, i.e., the scaled effective population size. Including information about
the number of conducted tests and their outcome allows us further to infer changes of the relative case detection rates. By
incorporating the number of officially reported cases, we determine the minimum number of infected people and an estimation ofunder-reported cases.

Poster presentation / 5

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-06]

Detection of changes in viral load in a randomized controlled trial of an anti-SARSCoV-2 drug with high entry inhibition efficacy
Author(s)Daiki Tatamatsu, Nagoya University (Presenter); Marwa Akao, Nagoya University; Hyeongki Park, Nagoya University; Shingo Iwami,
Nagoya University; Keisuke Ejima, Nanyang Technological University; Shoya Iwanami, Nagoya University

Short Abstract

Various drugs against novel corona virus disease (COVID-19) have been actively developed. Many clinical trials have been conducted
to test the efficacy of candidate drugs on improvement of symptoms, prevention of severe illness, mortality risk reduction andreduction in viral shedding. Conducting appropriate randomized controlled trials (RCTs) require enough subjects planned prior to trials.
The increase in the sample size of trials leads to excessive costs and increased labor hours. Especially during a pandemic, a reductionin the working hours of healthcare workers is required. In this study, we focused on how viral load in COVID-19 patients change by
inclusion/exclusion criteria based on the days from symptom onset to treatment initiation and affect sample sizes in a RCT of an antiSARS-CoV-2 drug with high entry inhibition efficacy. First, we developed a mathematical model of SARS-CoV-2 infection dynamics andestimated model parameters based on reported SARS-CoV-2 viral load in COVID-19 patients. Using the obtained parameter
distributions, we generated virtual patients as sets of model parameters. Next, we conducted simulation experiments of RCTs for entry
inhibitors against SARS-CoV-2 infection with high entry inhibition efficacy to investigate the relationship between trial procedures as
inclusion/exclusion criteria and sample sizes obtained predicted viral load in virtual patients. From our analysis, the sample size would
be 189–11052 and 1017–30639 patients smaller for 95% and 99% entry inhibitor drugs, respectively, compared with a trial that
included all patients even if the patients included in the trial were within 4 days after symptom onset. These results are expected toprovide a meaningful insight for designing RCTs of SARS-CoV-2 entry inhibitors and lead to accelerate development of standard
treatment with antiviral drugs against infectious diseases causing pandemics. This study was published in the Journal of Theoretical
Biology in 2023.

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-07]

Establishment of recombinant HIV with timer fluorescence protein to visualize virustranscription
Author(s)Sharmin Nahar Sithi, Division of Genomics & Transcriptomics, Joint Research Center for Human Retrovirus Infection, Kumamoto
University (Presenter).; Omnia Reda, Division of Genomics & Transcriptomics, Joint Research Center for Human Retrovirus Infection,
Kumamoto University.; Wajihah Sakhor, Division of Genomics & Transcriptomics, Joint Research Center for Human Retrovirus Infection,
Kumamoto University.; Akhinur Rahman, Division of Genomics & Transcriptomics, Joint Research Center for Human Retrovirus
Infection, Kumamoto University.; Kazuaki Monde, Department of Microbiology, Faculty of Life Sciences, Kumamoto University.; Samiul
Alam Rajib, Division of Genomics & Transcriptomics, Joint Research Center for Human Retrovirus Infection, Kumamoto University.; Kenji
Sugata, Division of Genomics & Transcriptomics, Joint Research Center for Human Retrovirus Infection, Kumamoto University.; Hiroaki
Takeuchi, Department of Molecular Virology, Tokyo Medical and Dental University.; Masahiro Ono, Department of Life Sciences, Facultyof Natural Sciences, Imperial College.; Kenji Maeda, Division of Antiviral Therapy, Joint Research Center for Human Retrovirus Infection,
Kagoshima University.; Yorifumi Satou, Division of Genomics & Transcriptomics, Joint Research Center for Human Retrovirus Infection,
Kumamoto University.

Short Abstract

The integration of viral DNA into the host genome is a critical event in the cycle of replication and pathogenesis of HIV. Although mostHIV-infected cells are rapidly eliminated in vivo, integrated replication-competent but transcriptionally silent HIV provirus can form viralreservoirs that persist despite combination anti-retroviral therapy (cART). Those reservoirs are the center of efforts to completely
eradicate HIV infection. Timer fluorescent protein forms a short-lived chromophore that emits blue fluorescence (t1/2 ~ 4h) during
active transcription which transforms into red fluorescence (t1/2 ~ 120h) upon silencing. Utilizing this feature of Timer fluorescentprotein, reactivated (Blue+) and persistent transcribing population (Blue+Red+) can be separated from the just silenced population(Red+), enabling us to understand the dynamics of provirus activation and silencing. In this study, we have established a novel
fluorescent system to monitor transcription dynamics by constructing Timer in HIV-1 genome. Infecting Jurkat cells with HIV-1 NL4-3Timer single round virus, we were able to identify and separate the infected population where Blue+ indicated the actively transcribing
population, Blue+Red+ as persistent and Red+ as just silenced population. This rapid transition from blue to red enabled us to monitor
silencing process in a highly sensitive manner. We also established clones from the infected cells and some established clones
expressed Timer fluorescence proteins which were further characterized to reveal their genetic and epigenetic environment. Then, we
verified the efficiency of the clone to evaluate latency promoting agent (LPA) in different detection system. Thus, HIV-Timer system not
Poster presentation / 7

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus

only enables us to separate just silenced cells from the reactivated cells but also makes it a useful tool for evaluating novel LPAs.

Poster presentation / 8

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-08]

Quantitative analysis of the antiviral effect of mucosal antibodies to suppress
infectious SARS-CoV-2 shedding
Author(s)Takara Nishiyama, Nagoya University (Presenter); Hyeongki Park, Nagoya University; Shingo Iwami, Nagoya University

Short Abstract

Although the COVID-19 pandemic is converging, it is imperative to develop novel technologies to effectively control future pandemics
caused by emerging variants of concern (VOCs) and respiratory virus infections. Currently, mRNA vaccines are widely used and havebeen shown to be effective in mitigating SARS-CoV-2 entry. However, their efficacy in suppressing virus shedding from infectedindividuals remains limited. Mucosal immunity, a pivotal component of respiratory viral infections, is anticipated to play a crucial role incurtailing viral shedding and transmission to humans. However, knowledge of the role of mucosal immunity in suppressing viral
shedding in individuals with respiratory viral infections, including COVID-19, remains limited. In this study, we used nasopharyngeal
swabs over time from individuals infected with SARS-CoV-2 omicron variants collected in a cohort study conducted by the Japanese
Ministry of Health, Labor and Welfare for analysis. Few cohorts have measured mucosal antibody and viral dynamics over time in thenasopharynx in this way, and we used mathematical models to extract quantitative information at the individual level. Subsequently,
we investigated the correlation between virus shedding dynamics and mucosal antibody responses in the upper respiratory tract
subsequent to SARS-CoV-2 infection. A significant finding of our study was that secretory immunoglobulin A (S-IgA) played a key role in
suppressing infectious virus shedding in nasopharyngeal swabs. In addition, our results underscored the importance of rapid productionof S-IgA in controlling infectious virus shedding. These results provide evidence for the possibility of controlling the spread of
respiratory viral infections.

Poster presentation / 9

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-10]

Simulating booster vaccinations: a case study of Fukushima Vaccination Cohort
Author(s)Kosaku Kitagawa, Nagoya University (Presenter)

Short Abstract

It has been a few years since COVID-19 pandemic, and we are about to enter the era of living with COVID-19. Based on detailed dataand insights accumulated from the largest infectious outbreak, it is important to establish appropriate vaccination strategies foranother possible future pandemic. Additional booster vaccinations following the primary two-dose regimen is expected to maintain an
individual's antibody titer at a higher level and contribute to good protection against SARS-CoV-2 breakthrough infection. However, thebooster effect varies from person to person. Vulnerable people who have remained at a low level of antibody titer for a long time areparticularly concerned as groups at high risk of breakthrough infection. Additionally, there might be a group that shows a rapid declineof antibody titer after vaccination. It is important to take such diversity into account for more appropriate vaccination strategies. We
investigated longitudinal data in a cohort of 2,526 people in Fukushima, Japan, for more than 500 days using a mathematical modelthat describes the dynamics of individual antibody titer. We predicted the results of possible different vaccination strategies bysimulating based on this data and real-world population structures.

Poster presentation / 10

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-11]

Heterogeneity in duration of viral shedding in COVID-19 patient’s saliva may not be
explained by basic clinical and micro-RNA information
Author(s)Hyeongki Park, Nagoya University (Presenter); Shingo Iwami, Nagoya University

Short Abstract

In our previous study, we conducted the randomized controlled trial (jRCT2071200023) to evaluate the effect of nelfinavir on reducing
SARS-CoV-2 in saliva, but we did not observe a significant effect. On the other hand, in this clinical trial, viral load in saliva and various
clinical data of many patients were frequently measured for about a month after the symptom onset. As a result, we could collect highquality longitudinal viral load data annotated with various clinical information contained basic information, results of blood test andvital signs, etc. Although salivary diagnostics testing has potential as a convenient tool for rapid and accurate testing in controlling
infectious disease, SARS-CoV-2 infection dynamics within saliva are poorly understood compared with those in respiratory tract.
Therefore, in this study, we used saliva samples collected from the nelfinavir clinical trial to investigate SARS-CoV-2 infection dynamics
in saliva. In addition, we tried to find factors that determine pattern of viral shedding by utilizing the basic clinical and micro-RNA data.
First, we reconstructed individual-level viral dynamics using a mathematical model, and stratified patterns of viral shedding using aclustering method. Next, we used supervised random forest to find factors that explain stratified groups among the 57 types of clinicaland 138 types of micro-RNA data. While our analysis identified three groups of patients that clearly discriminated the patterns of viral
shedding, no factor was found to identify stratified groups among examined clinical and micro-RNA data. Overall, this study provides
insights into SARS-CoV-2 infection dynamics in saliva. Additionally, our findings suggest that predicting the duration of viral shedding
without biomarkers which directly reflect an individual’s immune response, such as antibody induction, is challenging.

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-12]

Algebra-assisted PINN approach for SEIR modeling with unobserved variables
Author(s)Koki Shichiri, Kobe University ; Mizuka Komatsu, Kobe University (Presenter); Takenao Ohkawa, Kobe University

Short Abstract

Physics-informed neural networks, abbreviated as PINNs, are deep neural networks for modeling physical phenomena conventionallydescribed by, e.g., (partial) differential equations. PINN generates a solution for equations related to considered phenomena after
being trained in unsupervised ways. While training, the equations representing prior physical knowledge are incorporated in loss
functions working as regularizers. Thanks to this, the trained network can be regarded as a mesh-free solver. In addition, PINNs can be
employed for inverse problems, e.g., parameter estimation. In such problems, observed data is used for supervised learning without
the modification of the network architecture. With the benefit of deep learning frameworks, such as expressivity and generalizability,
they are successful in various applications. Recently, PINNs are applied to infectious disease modeling. In this field, compartment
models such as the SIR and its variations are classical. Besides, estimating model parameters is a crucial aspect of analyzing infectious
trends. Based on this, several attempts to incorporate such compartment models into PINNs and solve inverse problems can be seen in
the literature. In such situations, training data corresponding to each variable of the compartment model is supposed to be available.
However, such data is not always available in practice. This often causes the failure of learning, and hence, parameter estimation. To
overcome such a difficulty, in this study, we propose a modified PINN based on algebraic observability allowing weakly supervised
learning of unobservable variables. Furthermore, we apply the proposed approach for the SEIR model, which is one of the models used
for analyzing trends of, for example, COVID-19. Numerical results show the validity of our approach in parameter estimation of theSEIR model in the PINN approach under limited observation.

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-13]

Effective screening with antigen tests for identifying COVID-19 patients: simulation
with viral dynamics model
Author(s)Yong Dam Jeong, Nagoya University (Presenter); Keisuke Ejima, Nanyang Technological University; Marco Ajelli, Indiana University
School of Public Health-Bloomington; Shingo Iwami, Nagoya University

Short Abstract

During the pandemic, COVID-19 transmissions in schools and offices have been an important issue. Centers for Disease Control andPrevention (CDC) recommended taking all precautions such as vaccination and universal indoor masking. But, even if thoseprecautions were implemented, people might have been infected outside of the facilities. Thus, identifying those infected individuals
through screening tests was crucial. However, it was unclear which screening strategy was able to identify infected individuals more
effectively. In this study, we thus assessed the effectiveness of various screening strategies with antigen tests in schools andworkplaces through quantitative simulation. The primary outcome is the proportion of identified infected individuals. Screening
strategies were varied by screening schedule, sensitivity of antigen tests, available tests per person, and so on. 59.5% (95% CI: 52.461.5) of positive individuals were identified by symptom screening with daily testing and 4 antigen tests available for each person,
whereas 42.6% (95% CI: 39.6-45.4) were identified through only symptom screening. Using high sensitivity antigen tests, it could be
increased to 70.6% (95% CI: 67.7-73.6). The number of antigen tests had less impact compared with other parameters of thescreening strategy. Immediate initiation of screening tests, high sensitivity antigen tests, and high frequency screening tests were thekey to maintaining educational and economic activities in the midst of COVID-19. Our computational framework will be useful to assess
screening strategy by incorporating situation-specific factors for infectious disease transmission.

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-14]

Analysis of antiviral drug resistance caused by amino acid mutations
Author(s)Jun Koseki, Nagoya University （Presenter）; Shuto Hayashi, Tokyo Medical and Dental University; Shiho Torii, Osaka University; Shingo
Iwami, Nagoya University; Takasuke Fukuhara, Hokkaido University; Teppei Shimamura, Tokyo Medical and Dental University

Short Abstract

Because the SARS-CoV-2 virus uses RNA-dependent RNA polymerase for replication of its own genome and transcription of its genes,
Remdesivir, an antiviral drug that targets this protein, has been used. Remdesivir is incorporated into nsP12, a key protein of the RNAdependent RNA polymerase of the SARS-CoV-2 virus, and its drug effect occurs by inhibiting the elongation of new RNA. On the other
hand, it has been reported that specific mutations in the virus can lead to Remdesivir resistance. However, it was not well understood
what mutations induce drug resistance and why. Therefore, we created the platform DAIS, which enables comparison of the structuralchanges caused by amino acid mutations in the target groups, and analyzed the factors that induce drug resistance by analyzing theconformational and molecular behavior changes of nsP12. DAIS combines the Persistent Homology method, one of the Topological
Data Analysis methods, and the Molecular Dynamics method, which can sample the thermodynamic molecular behavior of proteins, toextract the points of conformational change by comparing the WT and target mutants. This method can also capture differences inconformational flexibility. The use of DAIS suggested that nsP12, which produces Remdesivir resistance, has greater structural
flexibility of the RNA-binding site compared to WT. Crystallographic analysis of Remdesivir-incorporated nsP12 indicates thatpyrophosphate, which is truncated when Remdesivir is incorporated into the RNA, inhibits the supply of new nucleic acids. Our
theoretical analysis indicates that the pyrophosphate may be released by increasing the structural flexibility of the RNA binding site incertain mutants, resulting in a loss of inhibitory effect. Other details of the results will be presented on the same day.

Poster presentation / 14

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-15]

Prediction of the indicator for determining immune reconstruction syndrome (IRIS)induced hepatic flare (HF) in HBV/HIV co-infected patients
Author(s)Sooyoun Choi, interdisciplinary Biology Laboratory (iBLab), Division of Biological Science, Graduate School of Science, Nagoya
University, Nagoya, Japan., Department of mathematics, Pusan National University, Busan, Republic of Korea (Presenter); Kwang Su
Kim, Department of mathematics, Department of Scientific Computing, Pukyong National University, Busan, Republic of Korea; Shingo
Iwami, interdisciplinary Biology Laboratory (iBLab), Division of Biological Science, Graduate School of Science, Nagoya University,
Nagoya, Japan.

Short Abstract

Immune reconstitution syndrome (IRIS) is a phenomenon that often occurs in HIV infected patients initiating antiretroviral therapy(ART). IRIS may cause a hepatic flare (IRIS-HF), an event in which alanine aminotransferase (ALT) levels suddenly rise above 5 times
the upper limit of normal within 12 months of initiation of ART therapy, and it is seen in about 20% of HBV/HIV co-infected patients on
the therapy. IRIS-HF is closely associated with HBsAg loss in co-infected patients and causes confusion, such as unnecessary change oftreatment or discontinuation during ART. Thus, whether IRIS-HF or not is an important factor in determining the treatment method andpurpose when treating HBV/HIV co-infected patients. In this work, we propose an approach to predict IRIS-HF in advance by developing
a multi-scale mathematical model which adds extracellular viral mechanisms including ALT to intracellular HBV dynamics. The
dynamics of HBsAg and ALT in co-infected patients are quantitatively estimated through the model based on clinical data.
Furthermore, a threshold to distinguish between IRIS-HF and non IRIS-HF patients is presented through the calculation of ALT elevationand HBsAg decrease according to the time of ART treatment. Our approach could help to predict IRIS-HF and reduce the treatment
burden for HBV/HIV co-infected patients

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-16]

Evolutionary dynamics of virulence of helper and satellite viruses
Author(s)Ryuichi Kumata, SOKENDAI (Presenter); Hisashi Ohtsuki, SOKENDAI; Akira Sasaki, SOKENDAI

Short Abstract

Satellite viruses are subviral agents that depend on the gene products of other viruses, called helper viruses, that co-infect the same
host in their replication. Satellite viruses are known to have diverse effects on the pathogenicity of helper viruses. Though somesatellites mitigate the pathogenicity (virulence) of co-infecting helpers (e.g., totivirus), they often increase the pathogenicity of coinfecting helpers (e.g., hepatitis delta virus). Despite numerous studies on the evolution of pathogen virulence, little attention has been
paid either to the evolution of the virulence-modification effects of satellites or to the evolution of virulence of helper virus in thepresence of the satellites. This study aims to investigate the evolutionary dynamics of the satellite’s virulence modifier traits andhelper’s virulence. We constructed a mathematical model that describes the epidemiological dynamics of satellites and their helpers. In
the model, we assume that either satellites or helpers may be lost when they are simultaneously transmitted between hosts and thatsatellites can superinfect the hosts infected only by helpers. Demographic dynamical study of the model reveals that when satellites
enhance the transmission efficiency of helpers, bistability arises, in which the extinction and coexistence of both the satellite and thehelper are simultaneously stable. Adaptive dynamical study of the model under a conventional transmission-virulence tradeoff reveals
that more virulent helpers evolve when satellites mitigate the helper's virulence and that more virulent satellites evolve when thehelper’s virulence is less than optimal in the absence of satellites. This suggests that the virulence-related traits of helpers andsatellites coevolve in a complementary fashion.

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-17]

Different efficacies of neutralizing antibodies and antiviral drugs on SARS-CoV-2
Omicron subvariants, BA.1 and BA.2
Author(s)Joohyeon Woo, Nagoya University (Presenter); Shingo Iwami, Nagoya University

Short Abstract

The recent international issue regarding SARS-CoV-2 has caused a rapid increase in the number of patients as well as a serious impact
on society. Especially, Omicron subvariant BA.5 has spread in worldwide, replacing the earlier Omicron subvariant BA.1, BA.2 and othervariants. Facing this pandemic situation, we considered that analyzing the efficacies of neutralizing antibodies as well as antiviral drugs
depending on SARS-CoV-2 subvariants is necessary for treating patients effectively. To begin with, we analyzed the published SARSCoV-2 data, especially the virus’ amino acid mutations among different subvariants. Since Omicron subvariants (BA.1, BA.2) had
unique mutation patterns, we thought that those different patterns affect their sensitivities to approved drugs/ antibodies against SARSCoV-2. On top of that, using a cell culture infection assay, we quantified the intrinsic sensitivity of BA.2 and BA.1 compared with othervariants of concern, Alpha, Gamma, and Delta, to five approved-neutralizing antibodies and antiviral drugs. Furthermore, most reports
have so far evaluated only 50% (or 90%) inhibitory concentrations to quantify the drug activity. Yet, these concentrations arepharmacologically not the sole factor that determines antiviral efficacy. Thus, we also estimated the slopes of dose-response sigmoid
curves to quantitatively discuss their drug effects at clinical drug concentrations (Koizumi et al., 2017; Shen et al., 2008). As a result,
our assay revealed the diverse sensitivities of these variants to antibodies, including the loss of response of both BA.1 and BA.2 tocasirivimab 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 clinicalconcentrations. These analyses provide essential evidence that gives insight into variant emergence’s impact on choosing optimal
drug treatment.

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-18]

Estimating the effect of medical intervention on the arrival time of infectious
diseases
Author(s)Yusuke Asai, National Center for Global Health and Medicine (Presenter)

Short Abstract

Public health measures to control the international spread of infectious diseases include increased quarantine and border closures.
While these measures are effective in delaying the introduction of infectious diseases, they also have a significant economic impact bystopping the flow of people and goods. Arrival times of infectious diseases are often used to evaluate the effectiveness of quarantine.
Although arrival times are highly dependent on the number of infected patients in the endemic country, direct comparisons have notbeen made. Therefore, in this study, we explicitly derive the relationship between the number of infected cases and arrival time.
Transmission and contact pattern show stochastic behavior and deterministic models are not always realistic. In this study, random
differential equations, which are differential equations with stochastic processes, are used to describe the dynamics of infection in an
endemic country. We also described the flow of travelers from the endemic country in terms of survival time and calculated the timeof arrival in disease-free countries. In addition, we considered scenarios for the distribution of PCR kits between endemic and diseasefree countries and evaluated the impact of different distribution rates on arrival times. The simulation results showed that increasing
the distribution of PCR kits in the endemic country was more effective in delaying arrival time than using PCR kits in quarantine in the
disease-free countries. In addition, increasing the proportion of identified infected individuals and leading them to isolation in theendemic country was found to be more important and effective in delaying arrival time than increasing the number of PCR tests.

Poster presentation / 18

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-19]

An interpretable machine learning framework for monitoring and stratifying the timevarying prognostic risk of diseases
Author(s)Megumi Oya, RIKEN, Chiba University (Presenter); Tetsuo Ishikawa, RIKEN, Keio University; Masahiro Shinoda, Tokyo Shinagawa
Hospital; Koichi Ashizaki, RIKEN, Tokyo Shinagawa Hospital; Shinichiro Ota, Tokyo Shinagawa Hospital; Kazuhiro Sakurada, RIKEN, Keio
University; Eiryo Kawakami, RIKEN, Chiba University; Masaharu Shinkai, Tokyo Shinagawa Hospital

Short Abstract

In this study, we propose a dynamic prognostic risk assessment framework based on longitudinal data during hospitalization forunvaccinated COVID-19 patients and make it interpretable. In some cases, unvaccinated COVID-19 patients who showed no signs ofseverity at admission suddenly became severe and died during hospitalization, suggesting that the risk of severity and mortalitychanges dynamically. To dynamically evaluate the mortality risk of patients during hospitalization, we used Random Survival Forest(RSF) for the incorporated information which is updated daily during hospitalization. The variables were including background factors
such as age and BMI, as well as biomarkers and vital information measured over time during hospitalization. We used the 7-day
cumulative hazard function (CHF) calculated with the RSF as an index to evaluate the mortality risk. For all four fatal cases in thevalidation dataset, an increase in the mortality risk was observed approximately one week after admission. Conversely, in patients
recovering from invasive or non-invasive ventilation, the CHF increased after admission as in the fatal cases, but then decreased.
Then, we applied survSHAP(t), which is based on SHapley Additive exPlanations, for the time-dependent explanation of the RSF model.
The survSHAP(t) lets us know how each variable affects the survival function at each time point. Our results demonstrate that the
dynamic risk assessment is effective for the early detection of high-risk cases, and what kind of variable changes are important formonitoring.

Poster presentation / 19

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-20]

Public relations strategies for the non-scientific community in virus dynamics
research
Author(s)Kyoko Kojima, Nagoya University (Presenter); Kazuma Morikawa, Nagoya University; Marina Hoshiai, Nagoya University; Shingo Iwami,
Nagoya University

Short Abstract

In general, one of the ways to disseminate research papers to society is through press releases. On the other hand, disseminating
research to a wider non-scientific community, especially targeting young people, is also a challenge for next-generation education in
the field of virology. In this presentation, I will discuss two research papers on SARS-CoV-2 conducted by my laboratory. I will introduce
two public relations strategies on how to effectively disseminate those papers, one is the press release method and the other is the
youth-oriented content method. First, for press releases, it is important to collaborate with newspaper reporters and illustrators in orderto proceed accurately and quickly. I will give examples of past cases and introduce some of the key points. Next, regarding contents
for young people, the challenge is how to attract their interest; in other words, to eliminate the "difficult image" of mathematicalmodels and computer simulations that generally exist. Therefore, I will introduce a wide range of PR strategies centered on video
distribution content via YouTube using VTuber and other SNS. Although still in the process of improvement and expansion, an overview
shows that there are two pillars to the social PR strategy of the study. The first is "common language" and the second is "stakeholder
management. "Common language" refers to the need to chew on language and communicate in a way that bridges the gap, based on
the premise that what is "normal" in virus dynamics research may not be so for the non-scientific community. This requires sciencevisualization and dialogue to chew through the jargon. "Stakeholder management" is about building good, mutually beneficial
relationships, rather than communicating in a solipsistic way. This requires communicating with those involved in press releases andbuilding an open community with target audience.

Poster presentation / 20

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-21]

Heterogeneity of individual B lymphocytes during transformation by Epstein-Barrvirus infection
Author(s)Yoshitaka Sato, Department of Virology, Nagoya University Graduate School of Medicine, Nagoya, Japan (Presenter); Takayuki Murata,
Department of Virology, Fujita Health University School of Medicine, Toyoake, Japan; Ken Sagou, Department of Virology, Nagoya
University Graduate School of Medicine, Nagoya, Japan, Department of Hematology and Oncology, Nagoya University Graduate Schoolof Medicine, Nagoya, Japan; Yusuke Okuno, Department of Virology, Graduate School of Medicine, Nagoya City University, Nagoya,Japan; Hiroshi Kimura, Department of Virology, Nagoya University Graduate School of Medicine, Nagoya, Japan

Short Abstract

Epstein-Barr virus (EBV) is an oncogenic gammaherpesvirus present in >90% of adults. EBV infection with human primary B cells
induces their continuous proliferation leading to lymphoblastoid cell lines with a range of alterations in the host cells. Here, we
performed single-cell transcriptomics analyses at multiple and long-term follow-up after EBV infection to elucidate the transforming
cellular landscape during the oncogenic viral infection. We defined several signaling pathways activated during EBV-driven
transformation and demonstrated that the stage-specific perturbations of unfolded protein response signaling at the mid-stage of EBVdriven transformation and NFkB at the early-stage impaired cell proliferation of infected cells. Our longitudinal data described theheterogeneity of infected cells such as immunoglobulin expression, viral gene expression and stage-specific subpopulations, providinga resource for understanding mechanisms that underlie the EBV-driven transformation of B cells.

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PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-22]A machine learning model for predicting hepatocarcinogenesis in chronic hepatitis B
patients
Author(s)Takeru Matsuura, Nagoya University (Presenter); Raiki Yoshimura, Nagoya University; Shingo Iwami, Nagoya University

Short Abstract

Hepatitis B is a serious liver infection caused by the hepatitis B virus. It affects approximately 296 million people and contributes to an
estimated 820,000 deaths every year. If the infection becomes chronic, there is no cure that completely eliminates the virus, and if it
develops into hepatocarcinoma, treatment options are further limited and the prognosis is generally not good. In fact, the mostcommon risk factor for liver cancer is chronic hepatitis virus infection. Therefore, it is important to identify chronic hepatitis B patients
at high risk for carcinogenesis early and to provide patient-tailored prevention. In this study, we developed a machine learning model tostratify patients and predict liver carcinogenesis using clinical data. Specifically, we created a random forest model to predict liver
carcinogenesis from long-term observational data of chronic hepatitis B patients. We identified biomarkers and examination findingsthat are likely to be associated with hepatocarcinogenesis. Furthermore, by quantifying the degree of similarity between patients
based on the model, we were able to stratify the patients into several clusters. Some clusters contained predominantly patients whodeveloped cancer, while other clusters contained only non-cancer patients. These results suggest the possibility of early intervention
and cancer prevention in the management of chronic hepatitis B patients.

Poster presentation / 22

PosterPresentation

6th Workshop on Virus Dynamics
https://iblab.bio.nagoya-u.ac.jp/special/2023/virus[P-23]

Quantification of age-related changes in hematopoietic stem cell differentiation
Author(s)Shoya Iwanami, Nagoya University

Short Abstract

Hematopoietic stem cells (HSCs) are considered to be at the top of the differentiation hierarchy of blood and immune cells and tomaintain hematopoietic system by their capacity for multipotency and self-renewal over the long term. How HSCs differentiate into
different cell lineages and how diseases associated with aged HSCs are caused is an open question. Understanding the differentiation
mechanisms of hematopoietic stem cells is also important for understanding the immune system, which is responsible for defense
against viral infections. We developed a mathematical model describing HSC differentiation dynamics including self-renewal anddifferentiation into restricted cell linages. To consider the fractions of HSC division modes, we obtained the frequency of expression ofphenotypes indicative of HSC self-renewal ability in ex vivo cell culture and quantified them as a continuous probability distribution
with respect to aging. Using this mathematical model describing HSC differentiation, we analyzed data obtained from mice andquantitatively captured the changes of ability of HSC with aging. The results of the analysis suggested that the self-renewal ability of
HSCs declines with age, while their differentiation ability increases. Our quantitative data analysis revealed the differentiation kineticsof HSCs, which is expected to be useful in elucidating the causes of diseases related to aging hematopoietic stem cells and ininvestigating means of treatment and other interventions.

Poster presentation / 23