Biology subjects

Molina-Paris, C.

Publications and source records attributed to Molina-Paris, C..

8 recordsLinked to original sources

bioRxiv2025

A mathematical framework for human neutrophil state transitions inferred from single-cell RNA sequence data

Neutrophils, the most abundant immune cells in the human circulation, play a central role in the innate immune system. While neutrophil heterogeneity is a topic of increasing research interest, few efforts have been made to model the dynamics of neutrophil population subsets. We develop a mathematical model to describe the dynamics that characterizes the states and transitions involved in the maturation of human neutrophils. We use single-cell gene expression data to identify five clusters of healthy human neutrophils, and pseudo-time analysis to inform model structure. We find that precursor neutrophils transition into immature neutrophils, which then either transition to an interferon-responsive state or continue to mature through two further states. The key model parameters are the transition rates (the inverse of a transition rate is the mean waiting time in one state before transitioning to another). In this framework, the transition from the precursor to immature state (mean time less than an hour) is more rapid than subsequent transitions (mean times more than 12 hours). Approximately a quarter of neutrophils are estimated to follow the interferon-responsive path; the remainder continue along the standard maturation pathway. We use Bayesian inference to describe the variation, between individuals, in the fraction of cells within each cluster.

cell biology↗

bioRxiv2024

Exploring the therapeutic potential of defective interfering particles in reducing the replication of SARS-CoV-2

SARS-CoV-2 still presents a global threat to human health due to the continued emergence of new strains and waning immunity amongst vaccinated populations. Therefore, it is still relevant to investigate potential therapeutics, such as therapeutic interfering particles (TIPs). Mathematical and computational modelling are valuable tools to study viral infection dynamics for predictive analysis. Here, we expand on the previous work by Grebennikov et al. (2021) on SARS-CoV-2 intra-cellular replication dynamics to include defective interfering particles (DIPs) as potential therapeutic agents. We formulate a deterministic model that describes the replication of wild-type (WT) SARS-CoV-2 virus in the presence of DIPs. Sensitivity analysis of parameters to several model outputs is employed to inform us on those parameters to be carefully calibrated from experimental data. We then study the effects of co-infection on WT replication and how DIP dose perturbs the release of WT viral particles. Furthermore, we provide a stochastic formulation of the model that is compared to the deterministic one. These models could be further developed into population-level models or used to guide the development and dose of TIPs. Author summarySARS-CoV-2 continues to evolve, with new strains or sub-strains being identified thanks to efforts to monitor the virus. Consequently, new strains threaten human health as current vaccinations may not adequately protect against future strains. It is therefore important to understand the roles that additional therapeutics could play in protecting against these future strains. Therapeutic interfering particles (TIPs), otherwise referred to as defective interfering particles (DIPs), could provide an additional treatment option against future strains. Previous models have examined the role of DIPs at the within-host level during co-infection with wild-type virus, but have paid little attention to intra-cellular dynamics. Here we extend the previous intra-cellular replication model of SARS-CoV-2 by Grebennikov et al. (2021) to include co-infection of WT virus with DIPs. We show that DIPs lead to a reduction in the WT virus in a dose-dependent manner, with higher doses leading to up to 10-fold reduction in total WT virus released from a cell depending on the multiplicity of infection (MOI). We find these results to be consistent for both deterministic and stochastic formulations of the model. Our approaches could be developed into a within-host model or population-level model, which could then be used to guide therapeutic DIP doses.

microbiology↗

bioRxiv2023

Last in first out: SIV proviruses seeded later in infection are harbored in short-lived CD4+ T cells

HIV can persist in a latent form as integrated DNA (provirus) in resting CD4+ T cells of infected individuals and as such is unaffected by antiretroviral therapy (ART). Despite being a major obstacle for eradication efforts, the genetic variation and timing of formation of this latent reservoir remains poorly understood. Previous studies on when virus is deposited in the latent reservoir have come to contradictory conclusions. To reexamine the genetic variation of HIV in CD4+ T cells during ART, we determined the divergence in envelope sequences collected from 10 SIV infected rhesus macaques. We found that the macaques displayed a biphasic decline of the viral divergence over time, where the first phase lasted for an average of 11.6 weeks (range 4-28 weeks). Motivated by recent observations that the HIV-infected CD4+ T cell population is composed of short- and long-lived subsets, we developed a model to study the divergence dynamics. We found that SIV in short-lived cells was on average more diverged, while long-lived cells harbored less diverged virus. This suggests that the long-lived cells harbor virus deposited starting earlier in infection and continuing throughout infection, while short-lived cells predominantly harbor more recent virus. As these cell populations decayed, the overall proviral divergence decline matched that observed in the empirical data. This model explains previous seemingly contradictory results on the timing of virus deposition into the latent reservoir, and should provide guidance for future eradication efforts. Significance statementHIV can persist in a latent reservoir unaffected by antiretroviral drugs. The genetic variation of this latent virus population is a major obstacle for eradication efforts, but also a clue to when HIV variants are deposited in the reservoirs. Unfortunately, previous studies assessing when the virus was deposited in latent reservoirs have come to contradictory conclusions. Here, we propose SIV proviral DNA exists in both short- and long-lived CD4+ T cells, and that these two cell subsets harbor different genetically diverged virus populations. Our model explains the contradictory findings and shows that when CD4+ T cells decay under effective drug treatment, which prevents virus replication, the resulting virus divergence decreases and recapitulates observed data. This knowledge should help in improving future eradication efforts.

microbiology↗

bioRxiv2023

Modeling the evolution of segment trees reveals deficiencies in current inferential methods for genomic reassortment

Reassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to novel progeny formed from the mixture of parental segments. Because large-scale genome rearrangements have the potential to generate new phenotypes, reassortment is important to both evolutionary biology and public health research. However, statistical inference of the pattern of reassortment events from phylogenetic data is exceptionally difficult, potentially involving inference of general graphs in which individual segment trees are embedded. In this paper, we argue that, in general, the number and pattern of reassortment events are not identifiable from segment trees alone, even with theoretically ideal data. We call this fact the fundamental problem of reassortment, which we illustrate using the concept of the first-infection tree, a typically but not always counterfactual genealogy that would have been observed in the segment trees had no reassortment occurred. Further, we illustrate four additional problems that can arise logically in the inference of reassortment events and show, using simulated data, that these problems are not rare and can potentially distort our perception of reassortment even in small data sets. Finally, we discuss how existing methods can be augmented or adapted to account for not only the fundamental problem of reassortment but also the four additional situations that can complicate the inference of reassortment.

evolutionary biology↗

bioRxiv2022

Tuning of cytokine signaling through imbalanced abundances of receptors and kinases

Cells use surface receptors to detect extra-cellular ligands (e.g., growth factors or cytokines) and engender signaling cascades. We explore the effect of cell-to-cell variability in receptor subunit copy number for cells responding to{gamma} c cytokines (e.g., IL-2, IL-7 and IL-15). We find that primary T cells expressing higher levels of the common{gamma} c receptor chain have weaker responses to IL-7, both in terms of lowered STAT5 phosphorylation amplitude and higher EC50. A mathematical model that accounts for abundance imbalance (e.g., insufficient expression of JAK kinases compared to the number of receptors, or{gamma} c competition for other receptor subunit chains) predicts the formation of non-signalling complexes, consistent with the observed cellular behaviour. This type of built-in limit on signaling responses illustrates how phenotypic heterogeneity generates biological functional diversity. Significance StatementCells rely on cytokines to coordinate their activation, differentiation, proliferation and survival. In particular,{gamma} c cytokines (interleukins IL-2, 4, 7, 9, 15, and 21) regulate the fate of leukocytes. The signaling cascade induced by these cytokines is relatively simple, and involves the phosphorylation of receptor-associated Janus-like kinases (JAK). Here, we explore the cell-to-cell variability of cytokine responses in primary mouse T cells, and find a paradoxical and quantitative imprint of receptor expression levels and other signaling components. For instance, high abundance of the common{gamma} c chain reduces cytokine responses (both in terms of signaling amplitudes and characteristic cytokine concentrations triggering 50% of the response). We develop mathematical models to quantify how limited abundances of signaling components (e.g., JAK or other cytokine receptor subunit chains) may explain our experimental observations. We conclude by generalizing this observation of cell-to-cell signaling variability to other ligand-receptor-kinase systems.

systems biology↗

bioRxiv2021

Competitive binding of STATs to receptor phospho-Tyr motifs accounts for altered cytokine responses in autoimmune disorders

Cytokines elicit pleiotropic and non-redundant activities despite strong overlap in their usage of receptors, JAKs and STATs molecules. We use IL-6 and IL-27 to ask how two cytokines activating the same signaling pathway have different biological roles. We found that IL-27 induces more sustained STAT1 phosphorylation than IL-6, with the two cytokines inducing comparable levels of STAT3 phosphorylation. Mathematical and statistical modelling of IL-6 and IL-27 signaling identified STAT3 binding to GP130, and STAT1 binding to IL-27R, as the main dynamical processes contributing to sustained pSTAT1 by IL-27. Mutation of Tyr613 on IL-27R decreased IL-27-induced STAT1 phosphorylation by 80% but had limited effect on STAT3 phosphorylation. Strong receptor/STAT coupling by IL-27 initiated a unique gene expression program, which required sustained STAT1 phosphorylation and IRF1 expression and was enriched in classical Interferon Stimulated Genes. Interestingly, the STAT/receptor coupling exhibited by IL-6/IL-27 was altered in patients with Systemic lupus erythematosus (SLE). IL-6/IL-27 induced a more potent STAT1 activation in SLE patients than in healthy controls, which correlated with higher STAT1 expression in these patients. Partial inhibition of JAK activation by sub-saturating doses of Tofacitinib specifically lowered the levels of STAT1 activation by IL-6. Our data show that receptor and STATs concentrations critically contribute to shape cytokine responses and generate functional pleiotropy in health and disease.

bioinformatics↗

bioRxiv2020

Fusion and fission events regulate endosome maturation and viral escape

Many intra-cellular processes rely on transport by endosomes. Recent experimental techniques have provided insights into organelle maturation and its specific role in, for instance, the ability of a virus to escape an endosome and release its genetic material in the cytoplasm. Endosome maturation and dynamics depend on GTPases called Rabs, found on their membrane. Here, we introduce a mathematical framework, combining coagulation and fragmentation of endosomes with two variables internal to each organelle, to model endosomes as intra-cellular compartments characterised by their levels of (active) Rab5 and Rab7. The key element in our framework is the "per-cell endosomal distribution" and its its dynamical equation or Boltzmann equation. The Boltzmann equation, then, allows one to deduce simple equations for the total number of endosomes in a cell, and for the mean and standard deviation of the Rab5 and Rab7 levels. We compare our solutions with experimental data sets of Dengue viral escape from endosomes. The relationship between endosomal Rab levels and pH suggests a mechanism which can account for the observed variability in viral escape times, which in turn regulate the viability of a viral intra-cellular infection. Author summaryEndosomes are intra-cellular receptacle-like organelles, which transport endocytosed cargo upon internalisation from the plasma membrane. These early endosomes, also known as sorting endosomes, mature to late endosomes, with a lower pH than early ones, as a consequence of the intricate dynamics of a family of molecules called Rabs. Viruses exploit this endosomal pH drop to their advantage. Here we bring together experimental data on Dengue viral escape times from endosomes and a novel mathematical framework inspired by the theory of droplet coalescence, to improve our understanding of endosome maturation, and in turn to quantify the large variability of viral escape times. This mathematical framework can easily be generalised to model the dynamics of other intra-cellular organelles, such as mitochondria or the endoplasmic reticulum.

systems biology↗

bioRxiv2019

Receptor tyrosine kinases regulate signal transduction through a liquid-liquid phase separated state

Receptor tyrosine kinases (RTKs), the largest class of transmembrane cell surface receptors, initiate signalling pathways which regulate diverse cellular processes. On activation these receptors rapidly recruit multiple downstream effector proteins to moderate affinity tyrosyl phosphate (pY) binding sites. However, the mechanism for expedient downstream effector protein recruitment via random molecular diffusion through the cytoplasm is not fully understood. One way in which the probabilistic outcome associated with random diffusion could be alleviated is through localized accumulation of high effective concentrations of signalling proteins in discrete pools in the cell (1). The inclusion of interacting proteins into liquid-liquid phase-separated (LLPS), membraneless protein droplets maintains functionally relevant proteins at high concentrations in a liquid phase at the required point of action, enhancing equilibrium binding and enzyme activity (2-6). These LLPS states have been associated with a wide range of cellular functions including regulation of signalling through, for example, nephrin (7, 8), the T-cell receptor (9), mTOR (10), and Sos-Ras (11), however, whether LLPS extends to RTK-mediated signal transduction has not been investigated. Here, we show that an RTK, fibroblast growth factor receptor 2 (FGFR2), forms a signalling competent LLPS state with two downstream effectors, a tandem Src homology 2 (SH2) domain-containing protein tyrosine phosphatase 2 (Shp2), and 1-phosphatidylinositol 4,5-bisphosphate phosphodiesterase gamma 1 (Plc{gamma}1). We show that these proteins assemble into a ternary complex which exploits LLPS condensation to simultaneously modulate kinase, phosphatase and phospholipase activities. Therefore, LLPS formation ensures that the requirement for prolonged, high-fidelity signalling is achieved. Additional RTKs also form LLPS with their downstream effectors, suggesting that formation of biological condensates is a key organising principle of RTK-mediated signalling, with broad implications for further mechanistic studies as well as therapeutic intervention.

cell biology↗