Biology subjects

Heffernan, J. M.

Publications and source records attributed to Heffernan, J. M..

7 recordsLinked to original sources

bioRxiv2025

The TEAIV model: Extending the standard TEIV model to account for viral budding ramp up

Understanding how viruses replicate and spread within a host is fundamental to predicting disease progression, timing, and dosage of effective therapeutic and prophylactic interventions. A target-cell limited approach is often used to model within-host viral kinetics to characterize disease infection dynamics. The standard target-cell limited model, the TEIV model, has been instrumental for understanding SARS-CoV-2 within-host viral kinetics, however, its core assumptions of instantaneous viral budding and exponentially distributed cell lifetimes oversimplify fundamental biological processes, potentially limiting predictive power. In this work, we consider a novel model approach, the TEAIV model: an extension to the TEIV model that considers an infected partially-productive cell state that ramps up through n stages to a fully productive state. We fit the TEAIV model to various SARS-CoV-2 viral load datasets, separated by hospitalized (severe infection) and non-hospitalized (mild infection) individual data, consider multiple different ramping functions, and compare to standard TEIV model fits. We further compare TEAIV and TEIV model fits with and without infected cell death incorporated in the eclipse (E) and partially infected (A) compartments and investigate best-fit frameworks up to 10 A states. We find that linear budding ramp-up dynamics minimizes the BIC (with {Delta}BIC > 2) across all model formulations when the total number of eclipse and budding compartments exceeds three. Furthermore, we find that the inclusion or exclusion of cell death applied to eclipse or ramping compartments does not substantially affect this result. Finally, we analytically consider the most general TEAIV model and discuss future modelling considerations. Our results demonstrate that accounting for non-instantaneous viral budding provides a better fit to SARS-CoV-2 viral load data and establishes a foundation for more mechanistically informed within-host models.

systems biology↗

bioRxiv2025

Machine Learning Reveals Distinct Immunogenic Signatures of Th1 Imprinting in ART-Treated Individuals with HIV Following Repeated SARS-CoV-2 Vaccination

The human immune system is intrinsically variable and remarkably diverse across a population. The immune response to antigens is driven by a complex interplay of time-dependent interdependencies across components of the immune system. After repeated vaccination, the humoral and cellular arms of the immune response display highly heterogeneous dynamics, further complicating the attribution of a phenotypic outcome to specific immune system components. We employ a random forest (RF) approach to classify informative differences in immunogenicity between older people living with HIV (PLWH) on ART and an age-matched control group who received up to five SARS-CoV-2 vaccinations over 104 weeks. RFs identify immunological variables of importance, interpreted as evidence for Th1 imprinting, and suggest novel distinguishing immune features, such as saliva-based antibody screening, as promising diagnostic features towards classifying responses (whereas serum IgG is not). Additionally, we implement supervised and unsupervised Machine Learning methods to produce physiologically accurate synthetic datasets that conform to the statistical distribution of the original immunological data, thus enabling further data-driven hypothesis testing and model validation. Our results highlight the effectiveness of RFs in utilizing informative immune feature interdependencies for classification tasks and suggests broad impacts of ML applications for personalized vaccination strategies among high-risk populations.

immunology↗

bioRxiv2024

Using virtual patient cohorts to uncover immune response differences in cancer and immunosuppressed COVID-19 patients

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in millions of deaths globally. Adults with immunosuppression (e.g., solid organ transplant recipients) and those undergoing active cancer treatments experience worse infections and more severe COVID-19. It is difficult to conduct clinical studies in these populations, resulting in a restricted amount of data that can be used to relate mechanisms of immune dysfunction to COVID-19 outcomes in these vulnerable groups. To study immune dynamics after infection with SARS-CoV-2 and to investigate drivers of COVID-19 severity in individuals with cancer and immunosuppression, we adapted our mathematical model of the immune response during COVID-19 and generated virtual patient cohorts of cancer and immunosuppressed patients. The cohorts of plausible patients recapitulated available longitudinal clinical data collected from patients in Montreal, Canada area hospitals. Our model predicted that both cancer and immunosuppressed virtual patients with severe COVID-19 had decreased CD8+ T cells, elevated interleukin-6 concentrations, and delayed type I interferon peaks compared to those with mild COVID-19 outcomes. Additionally, our results suggest that cancer patients experience higher viral loads (however, with no direct relation with severity), likely because of decreased initial neutrophil counts (i.e., neutropenia), a frequent toxic side effect of anti-cancer therapy. Furthermore, severe cancer and immunosuppressed virtual patients suffered a high degree of tissue damage associated with elevated neutrophils. Lastly, parameter values associated with monocyte recruitment by infected cells were found to be elevated in severe cancer and immunosuppressed patients with respect to the COVID-19 reference group. Together, our study highlights that dysfunction in type I interferon and CD8+ T cells are key drivers of immune dysregulation in COVID-19, particularly in cancer patients and immunosuppressed individuals.

immunology↗

bioRxiv2023

Within-host evolution of SARS-CoV-2: how often are mutations transmitted?

Despite a relatively low mutation rate, the large number of SARS-CoV-2 infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as parameter estimates for within-host SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of de novo SARS-CoV-2 mutations. For narrow bottlenecks, we find mutations affecting pertarget-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding), have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion). We further find that mutations affecting the eclipse rate (with phenotypes associated with reorganization of cellular metabolic processes and synthesis of viral budding precursor material) are highly favoured relative to all other traits examined. We find mutations leading to reduced removal rates of infected cells (with phenotypes associated with innate immune evasion) have limited transmission advantage relative to mutations leading to humoral evasion. Predicted transmission probabilities, however, for mutations affecting innate immune evasion are more consistent with the range of clinically-estimated household transmission probabilities for de novo mutations. This result suggests that although mutations affecting humoral evasion are more easily transmitted when they occur, mutations affecting innate immune evasion may occur more readily. We examine our predictions in the context of a number of previously characterized mutations in circulating strains of SARS-CoV-2. Our work offers both a null model for SARS-CoV-2 substitution rates and predicts which aspects of viral life history are most likely to successfully evolve, despite low mutation rates and repeated transmission bottlenecks.

genetics↗

bioRxiv2023

Immunogenicity of COVID-19 vaccines and their effect on the HIV reservoir in older people with HIV

Older individuals and people with HIV (PWH) were prioritized for COVID-19 vaccination, yet comprehensive studies of the immunogenicity of these vaccines and their effects on HIV reservoirs are not available. We followed 68 PWH aged 55 and older and 23 age-matched HIV-negative individuals for 48 weeks from the first vaccine dose, after the total of three doses. All PWH were on antiretroviral therapy (cART) and had different immune status, including immune responders (IR), immune non-responders (INR), and PWH with low-level viremia (LLV). We measured total and neutralizing Ab responses to SARS-CoV-2 spike and RBD in sera, total anti-spike Abs in saliva, frequency of anti-RBD/NTD B cells, changes in frequency of anti-spike, HIV gag/nef-specific T cells, and HIV reservoirs in peripheral CD4+ T cells. The resulting datasets were used to create a mathematical model for within-host immunization. Various regimens of BNT162b2, mRNA-1273, and ChAdOx1 vaccines elicited equally strong anti-spike IgG responses in PWH and HIV- participants in serum and saliva at all timepoints. These responses had similar kinetics in both cohorts and peaked at 4 weeks post-booster (third dose), while half-lives of plasma IgG also dramatically increased post-booster in both groups. Salivary spike IgA responses were low, especially in INRs. PWH had diminished live virus neutralizing titers after two vaccine doses which were rescued after a booster. Anti-spike T cell immunity was enhanced in IRs even in comparison to HIV- participants, suggesting Th1 imprinting from HIV, while in INRs it was the lowest. Increased frequency of viral blips in PWH were seen post-vaccination, but vaccines did not affect the size of the intact HIV reservoir in CD4+ T cells in most PWH, except in LLVs. Thus, older PWH require three doses of COVID-19 vaccine to maximize neutralizing responses against SARS-CoV-2, although vaccines may increase HIV reservoirs in PWH with persistent viremia.

immunology↗

bioRxiv2022

Longitudinal Assessment of SARS-CoV-2 Specific T Cell Cytokine-Producing Responses for 1 Year Reveals Persistence of Multi-Cytokine Proliferative Responses, with Greater Immunity Associated with Disease Severity

Cellular-mediated immunity is critical for long-term protection against most viral infections, including coronaviruses. We studied 23 SARS-CoV-2-infected survivors over a one year post symptom onset (PSO) interval by ex vivo cytokine ELISpot assay. All subjects demonstrated SARS-CoV-2-specific IFN-{gamma}, IL-2, and Granzyme B (GzmB) T cell responses at presentation, with greater frequencies in severe disease. Cytokines, mainly produced by CD4+ T cells, targeted all structural proteins (Nucleocapsid, Membrane, Spike) except Envelope, with GzmB > IL-2 > IFN-{gamma}. Mathematical modeling predicted that: 1) cytokine responses peaked at 6 days for IFN-{gamma}, 36 days for IL-2, and 7 days for GzmB, 2) severe illness was associated with reduced IFN-{gamma} and GzmB, but increased IL-2 production rates, 3) males displayed greater production of IFN-{gamma}, whereas females produced more GzmB. Ex vivo responses declined over time with persistence of IL-2 in 86% and of IFN-{gamma} and GzmB in 70% of subjects at a median of 336 days PSO. The average half-life of SARS-CoV-2-specific cytokine-producing cells was modelled to be 139 days ([~]4.6 months). Potent T cell proliferative responses persisted throughout observation, were CD4 dominant, and were capable of producing all 3 cytokines. Several immunodominant CD4 and CD8 epitopes identified in this study were shared by seasonal coronaviruses or SARS-CoV-1 in the Nucleocapsid and Membrane regions. Both SARS-CoV-2-specific CD4+ and CD8+ T cell clones were able to kill target cells, though CD8 tended to be more potent. ImportanceOur findings highlight the relative importance of SARS-CoV-2-specific GzmB-producing T cell responses in SARS-CoV-2 control, shared CD4 and CD8 immunodominant epitopes in seasonal coronaviruses or SARS-CoV-1, and indicate robust persistence of T cell memory at least one year after infection. Our findings should inform future strategies to induce T cell vaccines against SARS-CoV-2 and other coronaviruses.

immunology↗

bioRxiv2021

Infusion of CCR5 Gene-Edited T Cells Allows Immune Reconstitution, HIV Reservoir Decay, and Long-Term Virological Control

Antiretroviral therapy (ART) fails to fully restore immune function and is not curative. A single infusion of CCR5 gene-edited autologous CD4+ T cells (SB-728-T) led to sustained increases in CD4+ T cell counts, improved T cell homeostasis, and reduced the estimated size of the HIV reservoir. These outcomes were associated with the expansion and long-term persistence of a novel CCR5 gene-edited CD4+ T memory stem cell (CD45RAintROint TSCM) subset that can replenish the pool of more differentiated memory cells. We showed that novel CD45RAintROint TSCM cells are transcriptionally distinct from the previously described CD45RA+ TSCM and are minimally differentiated cells uncommitted to a specific Th-lineage. Subsequently, we showed in an independent trial that infusion of the SB-728-T cell product resulted in partial control of viral replication upon cessation of ART which was correlated with the frequencies of CCR5 gene-edited TSCM and their TEM progeny. Interestingly, one participant that remained off ART to this date demonstrated long-term maintenance of CCR5 gene-edited cells and increased frequency of polyfunctional HIV-specific CD4+ and CD8+ T cells, contributing to low levels of viral load 5 years post-infusion. Consequently, the generation of HIV protected memory CD4+ T cells by CCR5 disruption can contribute toward novel interventions aimed at achieving a sustained ART-free viral remission of HIV disease.

immunology↗