Session S66: Pathogens and Parasites: Evolution and Immune Response

A statistical ensemble approach to immune discrimination

The immune system needs to distinguish molecular signatures of pathogens from those found in the organisms' own proteins. A naive, but universal way to discriminate is to whitelist everything that should not elicit a reaction. Can the immune system do better? To begin to answer this question we characterize the self and pathogen proteomes as statistical ensembles. Probabilistic models reveal how both universal and phyla-specific constraints on protein evolution shape the statistics of the proteomes. The models furthermore allow us to quantify to what extent the ensembles differ systematically. We analyze whether and how these differences might be used for efficient immune defense. Finally, we compare predictions to what is known about epitopes recognized by the immune system.   

Force-Induced Ultrasensitivity at Cell-Cell Interfaces

Recent experiments have revealed that B cells use mechanical forces transmitted by the actin cytoskeleton to discriminate between antigens of similar binding affinity and to internalize portions of the antigen-presenting membrane. However, there is no unifying theoretical framework to probe the role of forces in antigen discrimination at cell-cell interfaces. In this work, we develop a hybrid computational approach to account for key biophysical properties of immune cell interfaces, including stochastic receptor-ligand binding kinetics, membrane mechanics, and actin-mediated forces on the membrane. We show that the number of B cell receptors (BCRs) bound to antigens increases in an ultrasensitive manner as a function of the binding affinity, and that the stiffness of the antigen-presenting membrane influences the threshold of the response. Above the threshold, antigens are internalized through a mechanism involving BCR clustering. Taken together, our results highlight the importance of forces at B cell interfaces and suggest that affinity discrimination is enhanced by membrane deformations, intracellular forces, and the dynamic spatial organization of surface receptors.   

Active tuning of synaptic patterns enhances affinity discrimination

Immune cells learn about their antigenic targets using tactile sense: during recognition, a highly organized yet dynamic motif, named immunological synapse, forms between immune cells and antigen-presenting cells (APCs). Via synapses, immune cells selectively extract recognized antigen from APCs by applying mechanical pulling forces generated by the contractile cytoskeleton. Curiously, depending on its stage of development, an immune cell exhibits distinct synaptic patterns which appear to strongly impact its capacity of distinguishing antigen affinities. While complete phase separation between receptor-ligand complexes and bound adhesion molecules observed in naïve (antigen-inexperienced) cells can be captured by existing models, how and why maturing cells maintain a multifocal pattern characteristic of arrested phase separation remains an unsolved puzzle. In this talk, I introduce a statistical-mechanical model to show that normal cytoskeletal forces can tune the degree of phase separation and thereby actively control the transition between distinct patterns. What is more, we find that normal forces coupled to lateral organization of receptors provide a robust grading scheme that allows efficient and broad affinity discrimination essential for proper immune function.
  

Electronic Monitoring of Ligands-Induced Conformational Dynamics of Single Lysozymes

We have investigated the dynamic interactions between lysozyme and several potential inhibitors such as peptide-based inhibitors, small-molecule inhibitors, and urea. In particular, the peptide-based inhibitor showed a weak affinity to lysozyme due to the non-covalent interactions between the C-terminus and the active site of lysozyme. Compared to the peptidoglycan substrates, the peptide inhibitor induced large conformational changes of lysozyme as well as stayed longer in the active site pockets while binding. The overall effectiveness of the peptide inhibitor was 20% when tested in the presence of both peptidoglycan substrates and inhibitors. The information gained by this research fundamentally improves our knowledge of lysozyme-inhibitor interactions, potentially paving the way to more effective, mechanism-focused drugs.   

Macrophage phenotype bioengineered by magnetic field interference

Functionally different macrophages have different shape and molecular phenotype that depend on actin cytoskeleton. In all eukaryotic cells the cell shapes and the cell functions are reciprocally related. Thus, the mechanically/magnetically, genetically or biochemically enforced change in cell shape will profoundly reverberate at cell functions. Here we report that an exposure of macrophages to a nonuniform magnetic field causes extreme elongation of macrophages and has a profound effect on their molecular components and organelles. We observed that magnetic force rearranges the macrophage actin cytoskeleton, Golgi complex and cation channel receptor TRPM2 and modifies expression of macrophage molecular markers. We also analyzed magnetic-induced forces acting on macrophages and found that location and alignment of magnetic-field-elongated macrophages correlate very well with the simulated distribution and orientation of such magnetic-force lines. Such bioengineering of the macrophages properties has a potential to be used in development of novel anti-rejection therapies in clinical organ transplantation and anti-cancer and anti-metastatic therapies.   

Collapse and contingency in phage infections of migrating bacterial populations

Natural bacterial populations are subject to constant predation pressure by phages. Since phage are non-motile perhaps the simplest defense against phage is for bacteria to outrun their predators. In particular, chemotaxis may help the bacteria escape slowly diffusing phages. Here we study phage infection dynamics in migrating bacterial populations driven by chemotaxis. We find that expanding phage-bacteria populations support two migrating fronts, an outermost "bacterial" front driven by nutrient uptake and chemotaxis and an inner "phage" front at which bacterial population collapses due to phage infection. We show that with increasing adsorption rate and initial phage population, the rate of migration of the phage front increases, eventually overtaking the bacterial front and driving the system from a regime where bacteria outrun a phage infection to one where they must evolve phage resistance to survive. We suggest that this process requires phages to hitchhike with the migrating bacterial front by repeatedly re-infecting the fastest moving bacteria. A deterministic model recapitulates the transition. Our work opens a new, spatiotemporal, line of investigation into the eco-evolutionary struggle between bacteria and their phage predators.

  

Bacterial Phage Resistance Emergence in Complex Landscapes of Stress

We have begun studies of the emergence of loss of sensitivity of {\em E. coli} to the phages T4 and T4r using a microfabricated stress landscape where phage titers are distributed across an array of localized metapopulations. Sensitivity emerges from local biofilm-like pockets of bacteria and and spreads as a form of colony hopping across the landscape. Sequencing on the insensitive bacterial colonies tests for both genetic mutations and additions of viral genome fragments in the CRISPR intervening spacer regions.   

A physical model for the selective assembly of HIV-1.

We report on finding an intramolecular bound state of the structural Gag capsid protein of HIV-1 using a combination of all-atom Molecular Dynamics (MD) simulations and statistical mechanical modeling. The presence of this bound state prevents premature capsid assembly on non-viral host RNA. It would unify numerous observations that have been made on HIV-1. We show that the presence of a GFP sequence inserted into the Gag gene interferes with the formation of the bound-state, suggesting that such constructs can not be considered as representative of the wild-type Gag. The central role of the bound-state for the kinetics suggests a variety of possible routes for interfering with HIV-1 assembly.   

Gaussian curvature and the budding kinetics of enveloped viruses

Recent Brownian dynamics simulations of enveloped virus budding (Lazaro et al. 2018) have reproduced the puzzling pausing and stalling phenomena observed on in-vivo viral budding. We show that the pausing/stalling can be understood as a purely kinetic phenomenon associated with a ``geometrical" energy barrier. This barrier does not show in the equilibrium thermodynamics of the system but it must be overcome by capsid proteins diffusing along the membrane prior to incorporation into the viral capsid. The barrier is generated by the conflict between the positive Gauss curvature of the capsid and the large negative Gauss curvature of the neck region. The theory is compared with the Brownian simulations of the budding of enveloped viruses.   

Investigation of Lymphatic Filariasis via Computational Modeling

Lymphatic filariasis is a disease caused by parasitic worm such as W. bancrofti, which lives and spreads between human and mosquitoes. The condition is prevalent in tropical countries, and its complication such as lymphedema affects millions worldwide. Although the filariasis-causing parasite can be treated, limited understanding of the interaction between lymphatic valve, vessel, and the parasite slows the effort to create an effective treatment for filariasis complications. To further investigate the parasite interaction with the lymphatic system, we present a fully-coupled, three-dimensional fluid-solid computational model that incorporates the parasite movement inside the lymphatic vessel. First, the parasite movement against various flow condition inside lymphatic system is simulated to investigate the mechanism behind worm’s ability to stay and navigate complex and constricting flow environment like the lymphatic system. Then, the parasite’s interaction with lymphatic valves is investigated under different worm and valve parameters, which helps to understand how the worm’s motion inside the lymphatic system may lead to valve damage and complications like lymphedema.   

A mean-field computational approach to intra-host HIV mutational dynamics

During HIV infection, the intra-host population is attacked by host cytotoxic T lymphocyte (CTL) responses. CTLs kill HIV-infected cells by recognizing certain HIV peptides presented on their surface. HIV strains with mutations in these regions escape CTL recognition and hence gain a relative fitness advantage. Can the dynamics of HIV mutations during intra-host infection be predicted? The intrinsic fitness landscapes of various HIV proteins, describing replicative capacity as a function of amino acid sequence, have been inferred from the global prevalence of strains infecting diverse hosts. Here, we present a new method to compute intra-host HIV mutational dynamics given an intrinsic fitness landscape and CTL responses, which we designate the evolutionary mean-field (EMF) method. EMF is a high-recombination-rate model of HIV dynamics that outputs effective fields and frequencies of mutations at each residue over time. We show via an example how intrinsic fitness costs and epistatic effects, skewed CTL responses, etc. impact the identities and time course of HIV escape mutations. We also explain features of longer-term dynamics using the effective fitnesses yielded by EMF. Finally, we extend EMF to stochastic population dynamics and quantify stochasticity in infection outcomes.   

Stabilization of fine-scale host-pathogen diversity by spatiotemporal chaos

DNA sequencing studies have increasingly found that within microbial species, fine-scale genetic diversity coexists. A major open question is how such diversity can develop and be maintained under pervasive selection when the subtypes all compete locally. Host-pathogen interactions are often cited as a cause of diversity. But the behavior with large numbers of closely related (but distinct) types is not understood. We analyze a generalized Lotka-Volterra model of host-pathogen interactions. The set of pathogens are all similar, as are the hosts: we thus assume no explicit specificity and approximate the variations in the host-pathogen interactions as being random. The negative effect of a pathogen on a host is correlated with the positive-effect of that host on the pathogen: thus the full matrix of interactions has antisymmetric correlations. With purely antisymmetric interactions, there is a stable chaotic phase with many types surviving but the population of each type fluctuating wildly. Deviations from this special case cause runaway extinctions. We show that the addition of spatial structure can stabilize the chaos: there are local extinctions, but repopulations from other islands prevent a substantial fraction of the types from going globally extinct.   

Revealing Determinants for Antibody-Antigen Coevolutionary Outcome Using a Shape-Space Model

B cells in the adaptive immune system produce antibody molecules that bind foreign antigens for removal. The binding affinity of antibodies for an antigen is improved in vivo through affinity maturation (AM) – a speedy Darwinian process occurring in numerous modest-size B cell populations housed by individual germinal centers (GC). A significant challenge arises when highly mutable pathogens (notably HIV) evolve on similar timescales as do B cell populations, evading an effective immune response.

Existing theoretical studies have ignored demographic fluctuations and precluded alternative evolutionary outcomes. In this talk, I extend the classic shape-space model to describe antibody-antigen coevolution via mutation and mutual selection. Using agent-based stochastic simulations, we show that consideration of population dynamics reveals diverse evolutionary outcomes and uncovers key determinants that can potentially be manipulated, including initial antigen diversity and epitope conservation. Moreover, we find population subdivision may slow down mutational escape of antigen. Finally, we suggest a possible route to evolving cross-reactive antibodies amenable to experimental search.
  

Ultra small carbon nanodots as fluorescence markers in primary human cells: uptake and cellular distribution

Carbon nanodots (CNDs) are promising candidates for fluorescence labeling of cellular components as well as for drug and gene delivery. Therefore, the uptake dynamics of CNDs and their cellular distribution are of vital interest. Here, we report the preparation of CNDS by a simple pyrolysis process, their structural and spectroscopic characterization, and the observation of cell-specific uptake rates by the leukocyte family as well as for hematopoietic stem cells. Large uptake rates are observed, resulting in up to approximately $10^9$ CNDs per cell after 24 hours of incubation. [1] The CNDs distribute non-uniformly across the cells. In particular, they do not enter the nucleus and have a tendency to accumulate in the Golgi apparatus in living cells. Fixation of the cells leads to a homogenization of the CND distribution across the cytoplasm. We show that this behavior suggests uptake via endocytosis, followed by intra-cellular storage inside nanoscale vesicles. Furthermore, the CNDs have only a small effect on the cell viabilities over a period of 72 hours even at very large CND concentrations.
[1] S. Fasbender et al., RSC Advances 7, 12208 (2017).   

Antimicrobial activity of sulphur-doped graphene quantum dots coupled with methylene blue for photodynamic therapy applications

Graphene quantum dots (GQDs) have attracted much attention and are a promising material with potential applications in many fields. One application of GQDs is as a photodynamic therapy agent that generates singlet oxygen. In this work, GQDs were grown by focusing nanosecond laser pulses into benzene and then were later combined with methylene blue (MB) and used to eradicate the Gram-negative bacteria, Escherichia coli, and Gram-positive bacteria, Micrococcus luteus. Theoretical calculation of pressure evolution was calculated using the standard finite difference method. Detailed characterization was performed with TEM, SEM, FTIR, UV-Vis, and photoluminescence spectra. Combining MB with GQDs caused enhanced singlet oxygen generation. Our results show that the MB-GQD combination efficiently destroys bacteria. The MTT assay was used to determine if GQDs in dark conditions caused human cellular side-effects and affected cancer and noncancer cellular viability. We found that even high concentrations of GQDs do not alter viability under dark conditions. These results suggest that the MB-GQD combination is a promising form of photodynamic therapy.