Infection Dynamics Research Articles

Modelling the mechanisms of antibody mixtures in viral infections: the cases of sequential homologous and heterologous dengue infections.

Antibodies play an essential role in the immune response to viral infections, vaccination or antibody therapy. Nevertheless, they can be either protective or harmful during the immune response. Moreover, competition or cooperation between mixed antibodies can enhance or reduce this protective or harmful effect. Using the laws of chemical reactions, we propose a new approach to modelling the antigen-antibody complex activity. The resulting expression covers not only purely competitive or purely independent binding but also synergistic binding which, depending on the antibodies, can promote either neutralization or enhancement of viral activity. We then integrate this expression of viral activity in a within-host model and investigate the existence of steady-states and their asymptotic stability. We complete our study with numerical simulations to illustrate different scenarios: firstly, where both antibodies are neutralizing and secondly, where one antibody is neutralizing and the other enhancing. The results indicate that efficient viral neutralization is associated with purely independent antibody binding, whereas strong viral activity enhancement is expected in the case of purely competitive antibody binding. Finally, data collected during a secondary dengue infection were used to validate the model. The dataset includes sequential measurements of virus and antibody titres during viremia in patients. Data fitting shows that the two antibodies are in strong competition, as the synergistic binding is low. This contributes to the high levels of virus titres and may explain the antibody-dependent enhancement phenomenon. Besides, the mortality of infected cells is almost twice as high as that of susceptible cells, and the heterogeneity of viral kinetics in patients is associated with variability in antibody responses between individuals. Other applications of the model may be considered, such as the efficacy of vaccines and antibody-based therapies.

Circadian regulation of dengue virus transmission and replication: insights into vector activity and viral dynamics.

Dengue fever, caused by dengue virus, poses a significant global health challenge, particularly in tropical regions where Aedes aegypti serves as the primary vector. The circadian clock in Aedes aegypti governs key behavioral and physiological processes, including activity patterns, feeding behaviors, and susceptibility to dengue virus infection. This article explores the influence of circadian rhythms on the mosquito's ability to transmit dengue virus, emphasizing how the circadian regulation of gene expression, immune responses, and lipid metabolism in the mosquito vector creates temporal windows that affect viral replication efficiency.

Dynamics and Evolution of Donor-derived Cytomegalovirus Infection in 3 Solid Organ Transplant Recipients With the Same Multiorgan Donor.

Cytomegalovirus (CMV) infection poses a significant risk to immunosuppressed transplant recipients, manifesting through primary infection, reinfection, or reactivation. We analyzed the emergence of drug resistance in CMV infection in 3 patients who were later found to have received an allograft from a shared, deceased donor. The seronegative transplant recipients developed symptomatic CMV infections after bowel/pancreas, kidney, or lung transplantation. Prospective Sanger sequencing was used to identify mutations in the viral DNA polymerase (DP) and protein kinase (PK). DP and PK variants were retrospectively quantified by targeted next-generation sequencing. The impact of the novel DP-A505G substitution on drug susceptibility was assessed using a recombinant virus. Whole-genome sequencing of clinical CMV samples was enabled through target DNA enrichment. The DP-A505G substitution was found in all patient samples and could be associated with a natural polymorphism. A subsequent review of the patients' clinical histories revealed that they had all received organs from a single donor. The CMV infection exhibited divergent evolution among the patients: patient 1 developed resistance to ganciclovir and foscarnet because of 2 DP mutations (V715M and V781I), patient 2 showed no genotypic resistance, and patient 3 developed ganciclovir (PK-L595S) and maribavir resistance (PK-T409M). Interpatient variation across the entire CMV genome was minimal, with viral samples clustering in phylogenetic analysis. All 3 transplant recipients were infected with the same donor-derived CMV strain and readily developed different drug susceptibility profiles. This underscores the importance of judicious antiviral drug use and surveillance in preventing antiviral resistance emergence.

Pathogen contingency loci and the evolution of host specificity: Simple sequence repeats mediate Bartonella adaptation to a wild rodent host.

Parasites, including pathogens, can adapt to better exploit their hosts on many scales, ranging from within an infection of a single individual to series of infections spanning multiple host species. However, little is known about how the genomes of parasites in natural communities evolve when they face diverse hosts. We investigated how Bartonella bacteria that circulate in rodent communities in the dunes of the Negev Desert in Israel adapt to different species of rodent hosts. We propagated 15 Bartonella populations through infections of either a single host species (Gerbillus andersoni or Gerbillus pyramidum) or alternating between the two. After 20 rodent passages, strains with de novo mutations replaced the ancestor in most populations. Mutations in two mononucleotide simple sequence repeats (SSRs) that caused frameshifts in the same adhesin gene dominated the evolutionary dynamics. They appeared exclusively in populations that encountered G. andersoni and altered the dynamics of infections of this host. Similar SSRs in other genes are conserved and exhibit ON/OFF variation in Bartonella isolates from the Negev Desert dunes. Our results suggest that SSR-based contingency loci could be important not only for rapidly and reversibly generating antigenic variation to escape immune responses but that they may also mediate the evolution of host specificity.

Generation and Genetic Stability of a PolX and 5′ MGF-Deficient African Swine Fever Virus Mutant for Vaccine Development

The African swine fever virus (ASFV) causes fatal disease in pigs and is currently spreading globally. Commercially safe vaccines are urgently required. Aiming to generate a novel live attenuated vaccine (LAV), a recombinant ASFV was generated by deleting the viral O174L (PolX) gene. However, during in vitro generation, an additional spontaneous deletion of genes belonging to the multigene families (MGF) occurred, creating a mixture of two viruses, namely, Arm-ΔPolX and Arm-ΔPolX-ΔMGF. This mixture was used to inoculate pigs in a low and high dose to assess the viral dynamics of both populations in vivo. Although the Arm-ΔPolX population was a much lower proportion of the inoculum, in the high-dose immunized animals, it was the only resulting viral population, while Arm-ΔPolX-ΔMGF only appeared in low-dose immunized animals, revealing the role of deleted MGFs in ASFV fitness in vivo. Furthermore, animals in the low-dose group survived inoculation, whereas animals in the high-dose group died, suggesting that the lack of MGF and PolX genes, and not the PolX gene alone, led to attenuation. The two recombinant viruses were individually isolated and inoculated into piglets, confirming this hypothesis. However, immunization with the Arm-ΔPolX-ΔMGF virus did not induce protection against challenge with the virulent parental ASFV strain. This study demonstrates that deletion of the PolX gene alone neither leads to attenuation nor induces an increased mutation rate in vivo.

Introduction of nirsevimab in Catalonia, Spain: description of the incidence of bronchiolitis and respiratory syncytial virus in the 2023/2024 season.

Respiratory syncytial virus (RSV) causes most of the cases of bronchiolitis and thousands of deaths annually, particularly in infants less than 6months old. In Catalonia (Spain), infants born between April 2023 and March 2024 aged 0-6months during their first RSV season have been candidates to receive nirsevimab, the novel monoclonal antibody against RSV, since October 2023. We aimed to analyse the dynamics of all-causes bronchiolitis diagnoses and RSV community infections in the current season and compare them to pre-nirsevimab epidemics. We collected epidemiological data from the Information System for Surveillance of Infections in Catalonia (SIVIC) on daily all-causes bronchiolitis clinical diagnoses and RSV-confirmed cases provided by rapid antigen tests in primary care practices. We calculated the rate ratio (RR) for the incidence of all-causes bronchiolitis for children aged 0-11m-old with respect to 12-35m-old between September 2014 and January 2024. We analysed the RR of the incidence of RSV-confirmed infection for 0-11m-old and 12-35m-old with respect to the > 35m-old, from January 2021 to January 2024. We then computed the relative difference of the RR, designated as percentage of reduction of risk, between season 2023/2024 and former epidemics. With a global coverage recorded rate for nirsevimab of 82.2% in January 2024, the age-specific 0-11m-old RR (95% CI) of RSV infection incidence for > 35m-old was 1.7 (1.5-2.0) in season 2023/2024. The RR (95% CI) had been 7.4 (5.6-9.9), 8.8 (6.9-11.3), and 7.1 (5.7-8.9) in 2020/2021, 2021/2022, and 2022/2023, respectively. Regarding the incidence of all-causes bronchiolitis for the 0-11m-old group compared to the 12-35m-old, the pre-pandemic (2014/2015-2019/2020) and 2022/2023 RR (95% CI) were 9.4 (9.2-9.6) and 6.0 (5.7-6.2), respectively, significantly higher than the RR of 3.6 (3.4-3.8) for the most recent season, 2023/2024. Conclusion: Concurring with the introduction of nirsevimab, the risk of RSV infection for infants aged 0-11m-old compared to > 35m-old has been reduced by 75.6% (73.4-77.5) in last season, and the risk for all-causes bronchiolitis for 12-35m-old by 61.9% (60.9-62.9) from the pre-pandemic period and by 39.8% (39.3-40.2) from the 2022/2023 epidemic, despite high RSV community transmission, especially in older infants What is Known: • RSV is responsible for approximately 70% of bronchiolitis cases and causes severe disease, particularly in infants < 6months of age. • Nirsevimab effectiveness against RSV-associated disease, particularly hospitalisations, was expected to be around 80%; other Spanish regions, such as Galicia and Valencia, and European countries including Luxembourg and Germany, have already reported good results in implementing nirsevimab to prevent RSV-associated hospitalisations and PICU stays. What is New: • We provide insight into the community incidence of RSV and all-causes bronchiolitis for season 2023/2024, when nirsevimab has been introduced to the Catalan population, using. primary healthcare data, which enabled us to assess the burden of RSV infections and bronchiolitis in the commonly seasonally saturated primary healthcare practices. • Our study reveals that the risk of all-causes bronchiolitis for infants aged 0-11m-old compared to older infants was reduced by 40% compared to the previous season and 62% compared to pre-pandemic standards, and for RSV infection it was reduced by 76%.

Story of an infection: Viral dynamics and host responses in the Caenorhabditis elegans-Orsay virus pathosystem.

Orsay virus (OrV) is the only known natural virus affecting Caenorhabditis elegans, with minimal impact on the animal's fitness due to its robust innate immune response. This study aimed to understand the interactions between C. elegans and OrV by tracking the infection's progression during larval development. Four distinct stages of infection were identified on the basis of viral load, with a peak in capsid-encoding RNA2 coinciding with the first signs of viral egression. Transcriptomic analysis revealed temporal changes in gene expression and functions induced by the infection. A specific set of up-regulated genes remained active throughout the infection, and genes correlated and anticorrelated with virus accumulation were identified. Responses to OrV mirrored reactions to other biotic stressors, distinguishing between virus-specific responses and broader immune responses. Moreover, mutants of early response genes and defense-related processes showed altered viral load progression, uncovering additional players in the antiviral defense response.

Hyers–Ulam stability of Nipah virus model using Atangana–Baleanu–Caputo fractional derivative with fixed point method

In this study, we present a novel investigation into the dynamics of the Nipah virus through the lens of fractional differential equations (FDEs), employing the Atangana–Baleanu–Caputo fractional derivative (ABCFD) and the fixed-point approach (FPA). The core contribution of this work lies in establishing the existence and uniqueness of solutions to the proposed FDEs, a critical step for validating the model. Furthermore, we explore the Hyers–Ulam (HU) stability of these generalized FDEs, providing a rigorous mathematical foundation for the stability analysis within the context of viral dynamics. By leveraging the ABCFD, our work extends the classical stability criteria, offering new insights into the role of memory effects in disease modeling. Additionally, we present approximate solutions across various compartments and fractional orders, highlighting the sensitivity of the system to key parameters. Numerical simulations, conducted using the Cullis method, illustrate the impact of fractional orders and validate the theoretical findings, positioning this work as a significant advancement in the application of fractional calculus to epidemiological models.

A six-compartment model for COVID-19 with transmission dynamics and public health strategies.

The global crisis of the COVID-19 pandemic has highlighted the need for mathematical models to inform public health strategies. The present study introduces a novel six-compartment epidemiological model that uniquely incorporates a higher isolation rate for unreported symptomatic cases of COVID-19 compared to reported cases, aiming to enhance prediction accuracy and address the challenge of initial underreporting. Additionally, we employ optimal control theory to assess the cost-effectiveness of interventions and adapt these strategies to specific epidemiological scenarios, such as varying transmission rates and the presence of asymptomatic carriers. By applying this model to COVID-19 data from India (30 January 2020 to 24 November 2020), chosen to capture the initial outbreak and subsequent waves, we calculate a basic reproduction number of 2.147, indicating the high transmissibility of the virus during this period in India. A sensitivity analysis reveals the critical impact of detection rates and isolation measures on disease progression, showing the robustness of our model in estimating the basic reproduction number. Through optimal control simulations, we demonstrate that increasing isolation rates for unreported cases and enhancing detection reduces the spread of COVID-19. Furthermore, our cost-effectiveness analysis establishes that a combined strategy of isolation and treatment is both more effective and economically viable. This research offers novel insights into the efficacy of non-pharmaceutical interventions, providing a tool for strategizing public health interventions and advancing our understanding of infectious disease dynamics.

Understanding the dynamics of nipah virus (NiV) transmission and outbreaks in India from Kerala’s perspective

This comprehensive analysis delves into the series of Nipah virus (NiV) outbreaks across India, with a particular focus on occurrences in Kerala. NiV, which belongs to the Paromyxoviridae family and Henipavirus genus, originated in Malaysia in 1998 and has consistently posed significant global health threats. In India, NiV outbreaks have sporadically emerged since the initial case in West Bengal in 2001, often with alarming mortality rates. The 2018 resurgence in Kerala exhibited an astonishing case fatality rate of 89%, emphasizing the need for tailored diagnostic and management strategies due to substantial variability in the incubation period and clinical manifestations. Understanding the predominant person-to-person transmission underscores the importance of comprehending transmission dynamics. Early detection, facilitated by the Integrated Disease Surveillance Program (IDSP), remains vital, as treatment options are currently confined to supportive care, necessitating the exploration of more effective therapeutics. The sporadic nature of NiV outbreaks, exemplified by the recent Kerala episode, emphasizes the urgency for robust response mechanisms, while collaborative efforts and capacity-building initiatives are essential for effectively managing these occurrences. Continued focus on prompt detection, advanced laboratory testing, accessibility to cutting-edge facilities, and heightened infection control measures remains imperative to mitigate future incidents.

Exploring variations in dengue symptoms: a comparative study of 2013, 2019, and 2023 in a tertiary care hospital of Bangladesh

Background: Dengue fever remains a major public health issue in Bangladesh, with repeated outbreaks. This study compares dengue symptoms in a tertiary care hospital during 2013, 2019, and 2023. The purpose of this study is to evaluate the variations in dengue symptoms among Bangladeshi dengue patients from 2013 and 2019 to 2023. Methods: This was a cross-sectional study, conducted on 100 dengue positive patients, admitted between 1st January to 7th August 2023, to the Medicine Department, Holy Family Red Crescent Medical College and Hospital, Dhaka. Demographic data, sign and symptoms and laboratory investigation reports were collected. These data were compared with a previously published study from the same institute comparing dengue symptoms between 2013 and 2019 among admitted dengue patients. The study employed a convenience sampling method for participant selection, and data analysis was carried out using SPSS version 26. Results: Analysis of 100 sero-positive dengue cases reveals a predominant occurrence in the 20 to 40 age group (51%), with the mean age of patients being 34.5 years. Among these cases, a higher prevalence is observed in males (62%) compared to females (38%). Symptomatology exhibits variations over time, with fever being consistently present. Other symptoms such as headache (90%, 23% and 12%), retroorbital pain (45%, 3% and 16%), skin rash (16%, 4% and 1%) and constipation (32%, 1% and 5%) showing fluctuations, respectively in 2013, 2019 and 2023. Notably, a significant proportion of patients in 2023 exhibit normal ultrasound findings (53%). Conclusions: In conclusion, our study provides a comprehensive analysis of Dengue infection dynamics over a decade, highlighting significant variations in clinical manifestations, laboratory findings, and abdominal ultrasound results among Bangladeshi patients. The findings suggest that Dengue remains a considerable public health concern, with fluctuations observed in symptomatology, including fever and other associated symptoms, and changes in laboratory parameters over time. BIRDEM Med J 2024; 14(3): 131-136

Highly Heterogeneous Kaposi Sarcoma-Associated Herpesvirus Oral Shedding Kinetics Among People With and Without Kaposi Sarcoma and Human Immunodeficiency Virus Coinfection.

An improved understanding of oral Kaposi sarcoma-associated herpesvirus (KSHV) viral dynamics could provide insights into transmission risk and guide vaccine development. We evaluated KSHV oral shedding dynamics in Ugandan adults stratified by Kaposi sarcoma (KS) and human immunodeficiency virus (HIV) status. Participants were followed for ≥4 weeks, with daily home oral swab collection to quantify KSHV using polymerase chain reaction. Shedding rates were defined by number of days with KSHV DNA detected divided by total days with swabs and compared by group using hurdle models. Two hundred ninety-five participants were enrolled; median age was 35 years (range, 18-71 years), and 134 (45%) were male. KSHV was detected more frequently among participants with KS (HIV positive [HIV+]/KS+, 56/76 [74%]; HIV negative [HIV-]/KS+, 9/18 [50%]) than those without KS (HIV+/KS-, 36/125 [29%]; HIV-/KS-, 16/76 [21%]); odds of shedding did not differ significantly by HIV status. Among participants with KSHV detected, shedding rates did not differ significantly by group. Median per-participant viral loads among positive samples were lowest in HIV+/KS+ (3.1 log10 copies/mL) and HIV-/KS+ (3.3 log10 copies/mL) participants relative to HIV+/KS- (3.8 log10 copies/mL) and HIV-/KS- (4.0 log10 copies/mL) participants. All groups had participants with low viral load intermittent shedding and participants with high viral load persistent shedding. Within each group, individual KSHV shedding rate positively correlated with median KSHV log10 copies/mL, and episode duration positively correlated with peak viral load. Oral KSHV shedding is highly heterogeneous across Ugandan adults with and without KS and HIV. Persistent shedding is associated with higher median viral loads regardless of HIV and KS status.

Innovation in viruses: fitness valley crossing, neutral landscapes, or just duplications?

Viruses evolve by periods of relative stasis interleaved with sudden, rapid series of mutation fixations, known as evolutionary bursts. These bursts can be triggered by external factors, such as environmental changes, antiviral therapies, or spill-overs from reservoirs into novel host species. However, it has also been suggested that bursts may result from the intrinsic evolutionary dynamics of viruses. Indeed, bursts could be caused by fitness valley crossing, or a neutral exploration of a fitness plateau until an escape mutant is found. In order to investigate the importance of these intrinsic causes of evolutionary bursts, we used a simulation software package to perform massive evolution experiments of viral-like genomes. We tested two conditions: (i) after an external change and (ii) in a constant environment, with the latter condition guaranteeing the absence of an external triggering factor. As expected, an external change was almost systematically followed by an evolutionary burst. However, we also observed bursts in the constant environment as well, albeit much less frequently. We analyzed how many of these bursts are triggered by deleterious, quasi-neutral, or beneficial mutations and show that, while bursts can occasionally be triggered by valley crossing or traveling along neutral ridges, many of them were triggered by chromosomal rearrangements and, in particular, segmental duplications. Our results suggest that combinatorial differences between the different mutation types lead to punctuated evolutionary dynamics, with long periods of stasis occasionally interrupted by short periods of rapid evolution, akin to what is observed in virus evolution.

Predictive modeling of hepatitis B viral dynamics: a caputo derivative-based approach using artificial neural networks

A fractional model for the kinetics of hepatitis B transmission was developed. The hepatitis B virus significantly affects the world’s economic and health systems. Acute and chronic carrier phases play a crucial part in the spread of the HBV infection. The Hepatitis B infection can be spread by chronic carriers even though they show no symptoms. In this article, we looked into the Hepatitis B virus’s various stages of infection-related transmission and built a nonlinear epidemic. Then, a fractional hepatitis B virus model using a Caputo derivative and vaccine effects is created. First, we determined the proposed model’s essential reproductive value and equilibria. With the aid of Fixed Point Theory, a qualitative analysis of the problem’s approximative root has been produced. The Adams-Bashforth predictor-corrector scheme is used to aid in the iterative approximate technique’s evaluation of the fractional system under consideration that has the Caputo derivative. In the final section, a graphical representation compares various noninteger orders and displays the discovered scheme findings. In this study, we’ve utilized Artificial Neural Network (ANN) techniques to partition the dataset into three categories: training, testing, and validation. Our analysis delves deep into each category, comprehensively examining the dataset’s characteristics and behaviors within these divisions. The study comprehensively analyzes the fractional HBV transmission model, incorporating both mathematical and computational approaches. The findings contribute to a better understanding of the dynamics of HBV infection and can inform the development of effective public health interventions.

Kinetics of Viral Shedding for Outbreak Surveillance of Emerging Infectious Diseases: Modeling Approach to SARS-CoV-2 Alpha and Omicron Infection.

Previous studies have highlighted the importance of viral shedding using cycle threshold (Ct) values obtained via reverse transcription polymerase chain reaction to understand the epidemic trajectories of SARS-CoV-2 infections. However, it is rare to elucidate the transition kinetics of Ct values from the asymptomatic or presymptomatic phase to the symptomatic phase before recovery using individual repeated Ct values. This study proposes a novel Ct-enshrined compartment model to provide a series of quantitative measures for delineating the full trajectories of the dynamics of viral load from infection until recovery. This Ct-enshrined compartment model was constructed by leveraging Ct-classified states within and between presymptomatic and symptomatic compartments before recovery or death among people with infections. A series of recovery indices were developed to assess the net kinetic movement of Ct-up toward and Ct-down off recovery. The model was applied to (1) a small-scale community-acquired Alpha variant outbreak under the "zero-COVID-19" policy without vaccines in May 2021 and (2) a large-scale community-acquired Omicron variant outbreak with high booster vaccination rates following the lifting of the "zero-COVID-19" policy in April 2022 in Taiwan. The model used Bayesian Markov chain Monte Carlo methods with the Metropolis-Hastings algorithm for parameter estimation. Sensitivity analyses were conducted by varying Ct cutoff values to assess the robustness of the model. The kinetic indicators revealed a marked difference in viral shedding dynamics between the Alpha and Omicron variants. The Alpha variant exhibited slower viral shedding and lower recovery rates, but the Omicron variant demonstrated swifter viral shedding and higher recovery rates. Specifically, the Alpha variant showed gradual Ct-up transitions and moderate recovery rates, yielding a presymptomatic recovery index slightly higher than 1 (1.10), whereas the Omicron variant had remarkable Ct-up transitions and significantly higher asymptomatic recovery rates, resulting in a presymptomatic recovery index much higher than 1 (152.5). Sensitivity analysis confirmed the robustness of the chosen Ct values of 18 and 25 across different recovery phases. Regarding the impact of vaccination, individuals without booster vaccination had a 19% higher presymptomatic incidence rate compared to those with booster vaccination. Breakthrough infections in boosted individuals initially showed similar Ct-up transition rates but higher rates in later stages compared to nonboosted individuals. Overall, booster vaccination improved recovery rates, particularly during the symptomatic phase, although recovery rates for persistent asymptomatic infection were similar regardless of vaccination status once the Ct level exceeded 25. The study provides new insights into dynamic Ct transitions, with the notable finding that Ct-up transitions toward recovery outpaced Ct-down and symptom-surfacing transitions during the presymptomatic phase. The Ct-up against Ct-down transition varies with variants and vaccination status. The proposed Ct-enshrined compartment model is useful for the surveillance of emerging infectious diseases in the future to prevent community-acquired outbreaks.

HIV-1 diversity in viral reservoirs obtained from circulating T-cell subsets during early ART and beyond.

Even during extended periods of effective immunological control, a substantial dynamic of the viral genome can be observed in different cellular compartments in HIV-1 positive individuals, indicating the persistence of active viral reservoirs. To obtain further insights, we studied changes in the proviral as well as in the viral HIV-1 envelope (Env) sequence along with transcriptional, translational and viral outgrowth activity as indicators for viral dynamics and genomic intactness. Our study identified distinct reservoir patterns that either represented highly sequence-diverse HIV-1 populations or only a single / few persisting virus variants. The single dominating variants were more often found in individuals starting ART during early infection phases, indicating that early treatment might limit reservoir diversification. At the same time, more sequence-diverse HIV reservoirs correlated with a poorer immune status, indicated by lower CD4 count, a higher number of regimen changes and more co-morbidities. Furthermore, we noted that in T-cell populations in the peripheral blood, replication-competent HIV-1 is predominantly present in Lymph node homing TN (naïve) and TCM (central memory) T cells. Provirus genomes archived in TTM (transitional memory) and TEM (effector memory) T cells more frequently tended to carry inactivating mutations and, population-wise, possess changes in the genetic diversity. These discriminating properties of the viral reservoir in T-cell subsets may have important implications for new early therapy strategies, underscoring the critical role of early therapy in preserving robust immune surveillance and constraining the viral reservoir.

Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections.

Significant variations have been observed in viral copies generated during SARS-CoV-2 infections. However, the factors that impact viral copies and infection dynamics are not fully understood, and may be inherently dependent upon different viral and host factors. Here, we conducted virus whole genome sequencing and measured viral copies using RT-qPCR from 9,902 SARS-CoV-2 infections over a 2-year period to examine the impact of virus genetic variation on changes in viral copies adjusted for host age and vaccination status. Using a genome-wide association study (GWAS) approach, we identified multiple single-nucleotide polymorphisms (SNPs) corresponding to amino acid changes in the SARS-CoV-2 genome associated with variations in viral copies. We further applied a marginal epistasis test to detect interactions among SNPs and identified multiple pairs of substitutions located in the spike gene that have non-linear effects on viral copies. We also analyzed the temporal patterns and found that SNPs associated with increased viral copies were predominantly observed in Delta and Omicron BA.2/BA.4/BA.5/XBB infections, whereas those associated with decreased viral copies were only observed in infections with Omicron BA.1 variants. Our work showcases how GWAS can be a useful tool for probing phenotypes related to SNPs in viral genomes that are worth further exploration. We argue that this approach can be used more broadly across pathogens to characterize emerging variants and monitor therapeutic interventions.

A reporter Oropouche virus expressing ZsGreen from the M segment enables pathogenesis studies in mice.

Oropouche fever caused by Oropouche virus (OROV) is a significant zoonosis in Central and South America. Despite its public health significance, we lack high-throughput diagnostics, therapeutics, and a comprehensive knowledge of OROV biology. Reporter viruses are valuable tools to rapidly study virus dynamics and develop neutralization and antiviral screening assays. OROV is a tri-segmented bunyavirus, which makes generating a reporter virus challenging, as introducing foreign elements into the viral genome typically affects fitness. We previously demonstrated that the non-structural gene NSm on the OROV medium (M) segment is non-essential for replication in vitro. Taking advantage of this, we have now generated a recombinant OROV expressing fluorescent protein ZsGreen in place of NSm. This reporter OROV is both stable and pathogenic in IFNAR-/- mice and provides a powerful tool for OROV pathogenesis studies and assay development.IMPORTANCEEmerging and reemerging infectious agents such as zoonotic bunyaviruses are of global health concern. Oropouche virus (OROV) causes recurring outbreaks of acute febrile illness in the Central and South American human populations. Biting midges are the primary transmission vectors, whereas sloths and non-human primates are their reservoir hosts. As global temperatures increase, we will likely see an expansion in arthropod-borne pathogens such as OROV. Therefore, developing reagents to study pathogen biology to aid in identifying druggable targets is essential. Here, we demonstrate the feasibility and use of a fluorescent OROV reporter in mice to study viral dynamics and pathogenesis. We show that this reporter OROV maintains characteristics such as growth and pathogenicity similar to the wild-type virus. Using this reporter virus, we can now develop methods to assist OROV studies and establish various high-throughput assays.

Abstract B049: Oncolytic virotherapy as an effective tool to synergistically enhance therapeutic efficacy of standard systemic treatments for pancreatic cancer

Abstract Background: Standard therapies provide marginal benefits in overall survival and leading immunologic agents have proven ineffective in the immunologically cold environment of pancreatic ductal adenocarcinoma (PDAC). Current standard of care chemotherapies experience demonstrable resistance in the clinical setting with primary and secondary resistance frequently leading to poor outcomes. Oncolytic virus (OV) therapies are emerging as an avenue of therapeutic potential with vesicular stomatitis virus (VSV) providing an onco- selective platform with potential for rapid replication and minimal outside virulence. The aim of this project is to determine if the addition of OV to the standard systemic treatments would result in a synergistic improvement of the therapeutic efficacy, and investigate the potential mechanisms involved. Methods: A VSV variant containing the Morreton G protein inserted into a wild-type VSV backbone (VMG)was propagated and purified for in vitro and in vivo studies. In vitro studies investigating oncolytic potential and viral kinetics of VSV in combination with FOLFIRINOX (FFX) and Gemcitabine Paclitaxel (GP) therapies were compared to monotherapy in multiple cell culture formats including 2D Monolayer, 3D Spheroid, and ongoing investigation into patient derived organoids. Proteomics analysis of monotherapies along with combination therapy was performed on in vitro cultures. Ongoing in vivo studies are investigating the therapeutic potential of concurrent treatments. Results: Cytotoxicity assay studies of equivalent multiplicities of infection (MOI) demonstrated increased cytotoxicity of combination therapy (Percent viable 10.2% ± 1.3%) compared to virus alone (30.7% ± 1.9%) or FFX alone (84.4% ± 6.6%) in Hs766T PDAC cell lineAsPC-1 cell line demonstrated similar effects with minimal cytotoxicity from FFX alone (100% ± 5%) with comparable resistance to virus alone (69.9% ± 1.8%) in comparison to combination therapy (40.3% ± 1.0%). Additional cell lines including Panc-01 and MiaPaCa2 provided similar results. Treatment of formed spheroids with combination therapy resulted in reduction in overall size of spheroid along with increased Viral GFP marker fluorescence, in combination group, compared to monotherapy with each treatment. Proteomic analysis investigating concomitant treatment with both standards of care produced unique expression profiles. Multiple pathways including cell cycle regulation, apoptosis, MAPK signaling, PI3K-Akt signaling, ErbB signaling showed significant regulatory changes in protein expression across all treatment groups. Conclusion: VSV oncolytic virus in conjunction with standard of care therapy demonstrates a potentially effective approach for synergistic enhancement of the therapeutic efficacy against PDAC. Ongoing research is investigating the immunomodulatory and metabolic effects of both monotherapies in conjunction with combination therapy to further determine the synergistic mechanisms involved and how they can be further utilized to overcome treatment resistance in PDAC. Citation Format: Conner Hartupee, Amirsalar Mansouri, Joycelynn Coleman-Barnett, Dana Adamcova, Dorota Wyczechowska, Bolni Marius Nagalo, Mulu Tesfay, Jovanny Zabaleta, Luis Del Valle, John West, Jiri Adamec, Omeed Moaven. Oncolytic virotherapy as an effective tool to synergistically enhance therapeutic efficacy of standard systemic treatments for pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B049.

346 Investigating the potential of incorporating indirect genetic effects into genetic evaluations of dairy calf disease traits

Abstract The goal of infectious disease control is often local eradication, but this is theoretically impossible to achieve based on classical quantitative genetic theory. Current methods focus on the susceptibility of individuals to disease and assume that exposure to a pathogen is 1) constant over time, 2) equal among individuals, and (3) due entirely to the environment. For this reason, it is likely that conventional genetic methods are capturing only a fraction of genetic variation in disease occurrence. The incorporation of epidemiological theory into quantitative genetics provides an opportunity to better determine the level of genetic variation in infectious disease traits. This stems from the ability to include the positive feed-back dynamics of infectious disease transmission. From an epidemiolocal perspective, both susceptibility and infectivity also have indirect genetic effects (IGE), because the genotype of one individual impacts the risk of infection of other individuals, and this can drastically affect the rate and direction of response to selection. Epidemiological models unravel the genetic heterogeneity in both susceptibility and infectivity traits, and account for the impact each animal has on its contemporaries compared with conventional quantitative genetic approaches. From a calf health perspective, there is a shift towards group housing dairy calves, primarily due to welfare and social acceptability. In turn, this will lead to increased animal interactions from a young age. Therefore, the aim of this study was to investigate the potential of incorporating IGE into current quantitative approaches to determine its impact on selection potential. Our study looked at two common infectious diseases in calves on dairy farms: respiratory problems (RESP) and diarrhea (DIAR). Producer-recorded data comprised of 19,445 records collected on 34 herds that group housed calves between 2007 and 2020. Calves were allocated into pen groups based on birth dates and herd specific housing practices. Original phenotypes were split into 10 records, each representing a week of life, to determine when exactly calves became sick and infective. Several scenarios were investigated with respect to the time an animal was infective for following a disease case (1 or 2 wk), and the maximum difference in weeks between animal birth dates to be included within the same pen (2 to 5 wk). Variance components were estimated using a generalized linear mixed model fitting a complementary-log-log link function with offset for exposure. Initial heritability estimates for susceptibility on the observed scale for DIAR ranged from 0.03 to 0.07, and from 0.02 to 0.03 for RESP across scenarios. While heritability estimates for infectivity are currently being investigated, the results for susceptibility highlight the potential for incorporating IGE into genetic evaluation of disease traits and provide an introduction towards incorporating epidemiological theory into classical quantitative approaches to better respect the transmission dynamics of infections.