Session V13: Immune Sensing and Response II

Live

A ubiquitous way that cells share information is by sensing and secreting molecules. We consider this mechanism by developing a coarse-grained model of sense-and-secrete feedback. We first develop the theory of biochemical feedback at the single cell level, and then use this theory to investigate a model of two communicating cells. At the single cell level, we focus on an essential immune decision point: do I see something which is self or foreign? At steady state, near such a bifurcation, it is possible to map a class of models of feedback to the mean-field Ising model near the critical point. We use this mapping to analyze single-cell data and to consider the case of two communicating cells. We show that cell-to-cell molecule exchange induces a collective two-cell critical point and that the mutual information between the cells peaks at this critical point. Furthermore, information is subject to a trade-off: more information comes at the expense of slower collective dynamics. We conclude by discussing potential applications of our method to analyze experimental data.   

Live

The evolution of circulating viruses is shaped by their need to evade the adaptive immune system. The spike protein which mediates entry to the host cell, presented at a high density on the viral surface, is the main target of antibody response. As a result, antibody pressure acting on the spike forces it to mutate, leading to genetic drift. Using a computational model based on coarse-grained 3d structure and publically available sequences, we show that presentation geometry, through antibody pressure, shaped, to the first order, the surface mutability map of the SARS family and the seasonal flu H1N1 spikes.

Studying the mutability patterns of SARS-CoV-2 and the 2009 H1N1 pandemic spikes, we find that they are not predominantly geometrically shaped by antibody pressure. However, for SARS-CoV-2, we find that over time, it acquired, at low frequency, several mutations at antibody-accessible positions, which could indicate possible antibody escape. Hence, we offer a geometry-based approach to estimate and assess whether a pandemic virus is changing its mutational pattern to that indicative of a circulating virus.   

Live

Unsurprisingly, education research shows that students engage better when an instructional storyline begins with a surprising claim about a topic important in their own lives. Today, everyone understands the importance of immune response to their lives, and most students find it surprising and paradoxical to be told that some bonds strengthen under applied pulling force. So the recent discovery of catch-bond behavior in T-cell activation is a very good starting point to motivate study of many molecular biophysics ideas. To understand the claim, we must discuss the nature of bonds, replace "strength" by the statistical notion of mean lifetime, and then introduce the notion of random walks on energy landscapes. Rather than the elaborate and technical Kramers theory, however, students can readily perform simple simulations. The results include memorable animated graphics, that students can make themselves in a platform such as Python or MATLAB, and that yield conceptual insight into bond formation and breakage, isomerization, and so on. Abstractions such as Boltzmann distribution and exponentially distributed lifetime emerge as concrete consequences of simple rules, and the origin of catch bonding behavior is clear when multiple unbinding routes are available.   

Live

Carbonic anhydrases (CAs) are a family of enzymes that catalyze the reversible reaction of CO₂ and water into bicarbonate and protons. Several studies have pointed to the importance of the CAs with their up/down regulations as an indicator for various diseases. Of particular importance is the human isozyme CA1, has been suggested as a biomarker for identification of several diseases including cancers, pancreatitis, diabetes, and Sjogren’s syndrome. However, the lack of a rapid, cheap, accurate, and easy-to-use quantification technique has prevented widespread utilization of CA1 for practical clinical applications. In this work, we realized a label-free electronic biosensor for detection of CA1 utilizing highly sensitive graphene field effect transistors (G-FETs) as a transducer and specific RNA aptamers as a probe. These aptameric G-FET biosensors showed the binding affinity (KD) of ~2.3 ng/ml (70 pM), which is four orders lower than that reported using a gel shift assay. This lower value of K_D enabled us to achieve a detection range (10 pg/ml - 100 ng/ml) which is well in line with the clinically relevant range. These highly sensitive devices allowed us to further prove their clinical relevance by successfully detecting the presence of CA1 in human saliva sample.   

Live

Immune recognition of infected and malignant cells requires presentation on their surface of antigens (i.e. short peptides) by human leukocyte antigen class I (HLA-I) proteins, which are coded by one of the most polymorphic alleles in the human genome. We first introduce RBM-MHC, a method for prediction of HLA-presented antigens based on the statistical physics framework known as Restricted Boltzmann Machine (RBM) to infer generative models from amino acid sequence data. RBM-MHC can be trained on custom and newly available samples with no or a small amount of HLA annotations, it ensures improved predictions for rare HLA alleles and matches state-of-the-art performance for well characterized alleles while being less data-demanding. RBM-MHC is shown to be a flexible and easily interpretable method that can be used as predictor of cancer neo-antigens and viral epitopes, as tool for feature discovery, and to reconstruct peptide motifs presented on specific HLA molecules. Next we extend the RBM approach to modeling the complementary process of immune recognition of presented antigens. The approach is able to discriminate responses specific to different antigens and highlights amino acid patterns that are central to such specificity at the molecular level.   

Live

Microfabricated Coulter counters are attractive for point of care (POC) applications since they are label free and compact. Mechanical clog formation - rendering the counter inoperable - increases markedly with reductions in the size of the constriction, leading to a tradeoff between sample throughput and sensitivity. We present a simple microfluidic coplanar Coulter counter device design that overcomes constriction clogging and is capable of operating in microfluidic channels filled entirely with highly conductive sample while being cost effective. The device employs microfabricated planar electrodes projecting into one side of the microfluidic channel and is easily integrated with upstream electronic, hydrodynamic, or other focusing units to produce efficient counting which could allow for dramatically increased volumetric and sample throughput.   

Not Participating

Humans and other vertebrates are exposed to many pathogens over their lifetimes. One of the main challenges individuals’ immune systems face is the unpredictability of pathogen encounters, including those that have the ability to create new variants in order to escape recognition. The adaptive immune system has evolved to address this challenge in part by developing immunological memory. During an adaptive immune response, B cells undergo affinity maturation, a form of Darwinian evolution which produces two cell types: plasma cells, which are highly specific against past exposures, and memory B cells, which have lower affinity against previously encountered pathogens but potentially cross-react with future variants. Affinity maturation takes place in small structures known as germinal centers. In this talk, we analyze how the biophysical properties of the germinal center response enable and constrain the immune system’s ability to carry out effective strategies against pathogens, emphasizing that said strategies must account for the coupling between the dynamics of the memory repertoire and the evolution of the pathogens it protects against.   

Live

Highly mutable viruses present multiple competing antigenic targets (epitopes) with differing accessibility on the envelope protein; their geometry permits simultaneous binding of more than one antibodies. Increasing evidence suggests that seemingly passive antibodies can interfere with natural selection of B cells. But little is known about how such interference impacts polyclonal responses, especially the fate of clones that target evolutionarily conserved yet poorly accessible epitopes. We present an ecological model to account for mediated interactions between B cell lineages, which stem from physical coupling of eptiopes via an antigen molecule. We find that, under heterogeneous interference, B cells with different intrinsic fitness can coexist; antagonism among fit clones promotes expansion of unfit ones at the cost of reduced collective potency. This tradeoff, however, can be alleviated by synergy toward the unfit. This framework predicts system-level outcomes (e.g. immunodominance hierarchy) from biophysical measurements (antibody affinity and cross-interference). Our results also suggest new ways to amplify rare clones by leveraging interference structure.   

Live

In order to target threatening pathogens, the adaptive immune system performs a continuous reorganization of its repertoire of cells. Following an immune challenge, the B cell repertoire can evolve cells of increased specificity for the encountered strain. This process of affinity maturation generates a memory pool whose diversity and size remain difficult to predict. Here we assume that the immune system follows a strategy that maximizes the long term immune coverage and minimizes the short term metabolic costs associated with affinity maturation. This strategy is defined as an optimal decision process on a d-dimensional phenotypic space, where a pre-existing population of naive cells is sequentially challenged with a neutrally evolving strain. We unveil a trade-off between immune protection against future strains and the necessary reorganization of the repertoire. This plasticity of the repertoire drives the emergence of distinct regimes for the size and diversity of the memory pool, depending on the density of naive cells and on the mutation rate of the strain.   

Live

Generation of potent antibodies relies on positive selection of immune B cells expressing high affinity receptors. Effective selection during B cell affinity maturation (a rapid evolutionary process) requires efficient ranking of affinities. Yet, the mechanism by which affinity discrimination is achieved and how it affects B cell evolution remains unclear. Growing evidence shows that B cells use mechanical forces to actively extract antigens from the surface of antigen-presenting cells. Here we study the stochastic process of antigen extraction using theory and simulations. We find that application of mechanical forces alters the energy landscape of molecular interactions and consequently extends the range of distinguishable affinities. Integrating molecular extraction with population dynamics, we demonstrate that B cells may expend mechanical energy to accelerate affinity maturation.   

Live

Some bacteria and archaea possess an immune system, based on the CRISPR-Cas mechanism, that confers adaptive immunity against phage. In such species, individual bacteria maintain a "cassette" of viral DNA elements called spacers as a memory of past infections. The typical cassette contains a few dozen spacers. Given that bacteria can have very large genomes, and since having more spacers should confer a better memory, it is puzzling that so little genetic space would be devoted by bacteria to their adaptive immune system. Here, we identify a fundamental trade-off between the size of the bacterial immune repertoire and effectiveness of response to a given threat, and show how this tradeoff imposes a limit on the optimal size of the CRISPR cassette.