Unique Interaction Pattern Research Articles

Luminescence turn-on response of naphthalene diimide based chemosensor with Formaldehyde: A novel stratagem for estimation of formaldehyde in storage fish samples

A new strategy has been developed for selective estimation of toxic Formaldehyde (FA) in storage fish samples by a simple chemosensor (BNDI) based on naphthalene diimide core in aqueous medium at neutral pH. The rapid “lightning–up” fluorescence feature of BNDI has been implied to detect and estimate aqueous FA selectively at very low concentration. The chemosensing properties of BNDI with aqueous FA have been established through a unique interaction pattern which is proven by different spectroscopic and theoretical analysis.

Measuring Urban Vibrancy of Residential Communities Using Big Crowdsourced Geotagged Data.

The pervasiveness of mobile and sensing technologies today has facilitated the creation of Big Crowdsourced Geotagged Data (BCGD) from individual users in real time and at different locations in the city. Such ubiquitous user-generated data allow us to infer various patterns of human behavior, which helps us understand the interactions between humans and cities. In this article, we aim to analyze BCGD, including mobile consumption check-ins, urban geography data, and human mobility data, to learn a model that can unveil the impact of urban geography and human mobility on the vibrancy of residential communities. Vibrant communities are defined as places that show diverse and frequent consumer activities. To effectively identify such vibrant communities, we propose a supervised data mining system to learn and mimic the unique spatial configuration patterns and social interaction patterns of vibrant communities using urban geography and human mobility data. Specifically, to prepare the benchmark vibrancy scores of communities for training, we first propose a fused scoring method by fusing the frequency and the diversity of consumer activities using mobile check-in data. Besides, we define and extract the features of spatial configuration and social interaction for each community by mining urban geography and human mobility data. In addition, we strategically combine a pairwise ranking objective with a sparsity regularization to learn a predictor of community vibrancy. And we develop an effective solution for the optimization problem. Finally, our experiment is instantiated on BCGD including real estate, point of interests, taxi and bus GPS trajectories, and mobile check-ins in Beijing. The experimental results demonstrate the competitive performances of both the extracted features and the proposed model. Our results suggest that a structurally diverse community usually shows higher social interaction and better business performance, and incompatible land uses may decrease the vibrancy of a community. Our studies demonstrate the potential of how to best make use of BCGD to create local economic matrices and sustain urban vibrancy in a fast, cheap, and meaningful way.

Conformational selection of vasopressin upon V1a receptor binding

The neuropeptide vasopressin (VP) and its three G protein-coupled receptors (V1aR, V1bR and V2R) are of high interest in a wide array of drug discovery programs. V1aR is of particular importance due to its cardiovascular functions and diverse roles in the central nervous system. The structure–activity relationships underpinning ligand-receptor interactions remain however largely unclear, hindering rational drug design. This is not least due to the high structural flexibility of VP in its free as well as receptor-bound states. In this work, we developed a novel approach to reveal features of conformational selectivity upon VP-V1aR complex formation. We employed virtual screening strategies to probe VP’s conformational space for transiently adopted structures that favor binding to V1aR. To this end, we dissected the VP conformational space into three sub-ensembles, each containing distinct structural sets for VP’s three-residue C-terminal tail. We validated the computational results with experimental nuclear magnetic resonance (NMR) data and docked each sub-ensemble to V1aR. We observed that the conformation of VP’s three-residue tail significantly modulated the complex dissociation constants. Solvent-exposed and proline trans-configured VP tail conformations bound to the receptor with three-fold enhanced affinities compared to compacted or cis-configured conformations. The solvent-exposed and more flexible structures facilitated unique interaction patterns between VP and V1aR transmembrane helices 3, 4, and 6 which led to high binding energies. The presented “virtual conformational space screening” approach, integrated with NMR spectroscopy, thus enabled identification and characterization of a conformational selection-type complex formation mechanism that confers novel perspectives on targeting the VP-V1aR interactions at the level of the encounter complex – an aspect that opens novel research avenues for understanding the functionality of the evolutionary selected conformational properties of VP, as well as guidance for ligand design strategies to provide more potent and selective VP analogues.

KinomeRun: An interactive utility for kinome target screening and interaction fingerprint analysis towards holistic visualization on kinome tree

Kinases are key targets for many of the pathological conditions. Inverse screening of ligands serves as an essential mode to identify potential kinase targets in modern drug discovery research. Hence, we intend to develop KinomeRun, a robust pipeline for inverse screening and kinome tree visualization through the seamless integration of kinome structures, docking and kinome-drug interaction fingerprint analysis. In this pipeline, the hurdle of residue numbering in kinome is also resolved by creating a common index file with the conserved kinase pocket residues for comparative interaction analysis. KinomeRun can be used to screen the ligands of interest docked against multiple kinase structures in parallel around the kinase binding site and also to filter out the targets with unique interaction patterns. This automation is essential for prioritization of kinase targets that show specificity for a given drug and will also serve as a crucial tool kit for holistic approaches in kinase drug discovery. KinomeRun is developed using python and bash programming language and is distributed freely under the GNU GPL licence-3.0 and can be downloaded at https://github.com/inpacdb/KinomeRun. The tutorial videos for installation, target screening and customized filtration are available at https://www.youtube.com/playlist?list=PLuIaEFtMVgQ7v__WigQH9ilGVxrfI1LKs and also be downloaded for offline viewing from the github link.

Interactions Between Acute Infarcts and Cerebrovascular Pathology Predict Poststroke Dementia.

Chronic cerebrovascular pathology accelerates the incidence of poststroke dementia (PSD). Whether the risk of PSD varies according to different types of chronic cerebrovascular pathology remains unclear. We investigated whether PSD is associated with a unique pattern of interactions between chronic cerebrovascular pathologies and acute stroke lesions. In this case-control study of acute mild stroke patients (n=185), cases included patients who developed PSD at a 6-month poststroke follow-up, and controls included patients who remained nondemented at 6 months, matched on prestroke cognitive status. Magnetic resonance imaging was performed at initial stroke presentation; neuropsychological assessments were performed 6 months after the stroke. White matter hyperintensities (WMH), chronic lacunes, microbleeds, and acute infarcts were not associated with PSD after controlling for demographics, cardiovascular risk, and global cortical atrophy. The risk of PSD was largest for patients with acute large subcortical infarcts (>15 mm) and concomitant periventricular WMH compared with patients with large subcortical infarcts and punctate/absent periventricular WMH [odds ratio (OR)=5.85, 95% confidence interval (CI)=1.85-40.04]. A moderate risk of PSD was observed for patients with acute multiple small infarcts (3 to 15 mm) and concomitant lacunes (OR=2.48, 95% CI=0.94-6.51) or concomitant lobar microbleeds (OR=2.20, 95% CI=0.89-5.41), compared with patients with acute multiple small infarcts and absent lacunes or microbleeds. Single small infarcts did not interact with cerebrovascular pathology to affect PSD. The risk of PSD varies depending on the presence of chronic cerebrovascular pathologies and type of acute infarcts. Clinical implications support a precision medicine approach for stratifying those at highest risk of PSD.

Studies on the interaction mechanisms of Garcinia kolaviron constituents with selected diabetes and neurodegenerative disease targets

Emerging evidence has shown kolaviron, a Garcinia biflavonoid complex, as inhibitor of α-amylase, aldose reductase and acetylcholinesterase in vitro. Herein, analysis of each kolaviron constituent (GB1, GB2 and kolaflavanone) for its molecular binding signatures, interaction footprints and inhibitory potential against these proteins was performed in silico. Morelloflavone, an analog of the biflavonoids, was also assessed for its inhibitory potential and precise interaction against the proteins. Results obtained suggest all the biflavonoids as potential drug candidates in the treatment of diabetes and neurodegenerative disease; their relatively bigger size permits an efficient blockage of the enzymes’ active site, thus hindering substrate access. The biflavonoids were well accommodated and favorably occupied the active site of the proteins with high binding affinity. The numerous hydroxyl and few methoxyl groups of the biflavonoids are indispensable for their bioactivities. Kolaflavanone displayed the highest affinity to α-amylase, but lowest binding affinity to acetylcholinesterase. GB1 and GB2 showed good affinity and comparable binding conformation on the proteins. Morelloflavone formed consistent π–π interactions with all the proteins. This work is the first study to depict the unique interaction patterns of kolaviron constituents with the selected enzymes which may explain their potency and inhibitory mechanisms.

Outer Membrane Proteins OmpA, FhuA, OmpF, EstA, BtuB, and OmpX Have Unique Lipopolysaccharide Fingerprints.

The outer membrane of Gram-negative bacteria has a highly complex asymmetrical architecture, containing a mixture of phospholipids in the inner leaflet and almost exclusively lipopolysaccharide (LPS) molecules in the outer leaflet. In E. coli, the outer membrane contains a wide range of proteins with a β barrel architecture, that vary in size from the smallest having eight strands to larger barrels composed of 22 strands. Here we report coarse-grained molecular dynamics simulations of six proteins from the E. coli outer membrane OmpA, OmpX, BtuB, FhuA, OmpF, and EstA in a range of membrane environments, which are representative of the in vivo conditions for different strains of E. coli. We show that each protein has a unique pattern of interaction with the surrounding membrane, which is influenced by the composition of the protein, the level of LPS in the outer leaflet, and the differing mobilities of the lipids in the two leaflets of the membrane. Overall we present analyses from over 200 μs of simulation for each protein.

The Outer Membrane Proteins OmpA, FhuA, OmpF, EstA, BtuB and OmpX have Unique Lipopolysaccharide Fingerprints

The outer membrane of Gram-negative bacteria has a highly complex asymmetric architecture, containing a mixture of phospholipids in the inner leaflet and in the outer leaflet almost exclusively lipopolysaccharide (LPS) molecules. In E. coli, the outer membrane contains a wide range of membrane proteins with beta barrel architectures, that vary in size from the smallest having eight strands to larger barrels composed of twenty-two strands. Here we report coarse-grained molecular dynamics simulations of five proteins from the E. coli outer membrane OmpA, OmpX, OmpF, BtuB, FhuA and EstA from Pseudomonas aeruginosa in a range of LPS-containing membrane environments. We show that each protein has a unique pattern of interaction with the surrounding membrane, which is influenced by the composition of the protein, the level of LPS in the outer leaflet and the differing mobilities of the lipids in the two leaflets of the membrane. Overall we present analyses from over 200 microseconds of simulation for each protein.

Discovery of activities via statistical clustering of fixation patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Nanoparticle based simple electrochemical biosensor platform for profiling of protein-nucleic acid interactions

The analysis of protein-nucleic acid interactions is essential for biophysics related research. However, simple, rapid, and accurate methods for quantitative analysis of biomolecular interactions are lacking. We herein establish an electrochemical biosensor approach for protein-nucleic acid binding analysis. Nanoparticle based sensors are fabricated by highly-controlled inkjet printing followed by plasma conversion. A novel bioconjugation method is demonstrated as a simple and rapid approach for protein-based biosensor fabrication. As a proof of concept, we analyzed the binding interaction between unwinding protein 1 (UP1) and SL3ESS3 RNA, confirming the accuracy of this nanoparticle based electrochemical biosensor approach with traditional biophysical methods. We further accurately profiled and differentiated a unique binding interaction pattern of multiple G-tract nucleic acid sequences with heterogeneous nuclear ribonucleoprotein H1. Our study provides insights into a potentially universal platform for in vitro biomolecule interaction analysis using a nanoparticle based electrochemical biosensor approach.

Structural insights into the duplex DNA processing of TREX2.

The three prime repair exonuclease 2 (TREX2) is an essential 3′-to-5′ exonuclease that functions in cell proliferation, genome integrity and skin homeostasis maintenance. The abnormal expression level of TREX2 can result in broken chromosome, increased susceptibility to skin carcinogenesis and Psoriasis. However, the molecular mechanisms of how TREX2 binds and processes its natural substrates, dsDNA or chromosomal DNA, to maintain genome stability remain unclear. In this study, we present four new crystal structures: apo-TREX2, TREX2 in complex with two different dsDNA substrates, and TREX2 in complex with a processed dsDNA product. Analysis of the structures reveals that TREX2 stacks with the 5′-terminal of dsDNA by a Leu20-Pro21-Asn22 cluster for precisely trimming the 3′-overhang. In addition, TREX2 specifically interacts with the non-scissile strand of dsDNA by an α-helix-loop region. The unique interaction patterns of the TREX2–dsDNA complex highlight the requirement of long double-stranded region for TREX2 binding and provide evidence of the functional role of TREX2 in processing chromosomal DNA. Moreover, the non-processive property of TREX2 is elucidated by the structure of TREX2–product complex. Our work discloses the first structural basis of the molecular interactions between TREX2 and its substrates and unravels the mechanistic actions of TREX2.

Discovery of activities via statistical clustering of fixation patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a piloting an aircraft, where activities with distinct visual signatures might be things like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as delta. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration delta, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to integer counts by multiplying by delta divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. The method has been applied to approximately 100 hours of eye movement data collected from pilots in a high-fidelity B747 flight simulator, and the results have been compared to synthetic data in which the each activity is represented as first-order Markov process with random probabilities assigned to the AOIs. Randomly-generated synthetic activities can require thousands of fixations to be discriminated with statistical significance, while the human data can be clustered using averaging windows of some 10's of seconds, suggesting that the actual activities are much more narrowly focused than random Markov models.

Preclinical pharmacology of AZD9977: A novel mineralocorticoid receptor modulator separating organ protection from effects on electrolyte excretion.

Excess mineralocorticoid receptor (MR) activation promotes target organ dysfunction, vascular injury and fibrosis. MR antagonists like eplerenone are used for treating heart failure, but their use is limited due to the compound class-inherent hyperkalemia risk. Here we present evidence that AZD9977, a first-in-class MR modulator shows cardio-renal protection despite a mechanism-based reduced liability to cause hyperkalemia. AZD9977 in vitro potency and binding mode to MR were characterized using reporter gene, binding, cofactor recruitment assays and X-ray crystallopgraphy. Organ protection was studied in uni-nephrectomised db/db mice and uni-nephrectomised rats administered aldosterone and high salt. Acute effects of single compound doses on urinary electrolyte excretion were tested in rats on a low salt diet. AZD9977 and eplerenone showed similar human MR in vitro potencies. Unlike eplerenone, AZD9977 is a partial MR antagonist due to its unique interaction pattern with MR, which results in a distinct recruitment of co-factor peptides when compared to eplerenone. AZD9977 dose dependently reduced albuminuria and improved kidney histopathology similar to eplerenone in db/db uni-nephrectomised mice and uni-nephrectomised rats. In acute testing, AZD9977 did not affect urinary Na+/K+ ratio, while eplerenone increased the Na+/K+ ratio dose dependently. AZD9977 is a selective MR modulator, retaining organ protection without acute effect on urinary electrolyte excretion. This predicts a reduced hyperkalemia risk and AZD9977 therefore has the potential to deliver a safe, efficacious treatment to patients prone to hyperkalemia.

Interaction of stereotypical trustworthiness, facial resemblance, and group membership in the perception of trustworthiness and other traits

ABSTRACTTrust begins with our first impression of others. But which matters most in forming the first impression that others possess stereotypically trustworthy facial features, that they look like us, or that they belong to our social group? This study explored the interaction among stereotypical trustworthiness, kinship (based on facial resemblance), and group membership (using arbitrary groups) in the formation of first impressions. Each participant rated 48 stimuli varying in stereotypical trustworthiness (trustworthy vs. untrustworthy), facial resemblance (self vs. other), and group membership (ingroup vs. outgroup) on three traits (trustworthiness, competence, and attractiveness). We observed unique interaction patterns for each of the three traits and we speculate that there is a match between the primacy of the information and the primacy of the evaluated dimension that influences the formation of first impressions. In addition, we propose that group membership may drive first impressions in the absence of kinship information. Our integrative approach brings us closer to understanding the formation of first impressions, and thus trustworthiness and trust, in real-life situations. Our findings outline stimulating directions for further research.

Football, Place, and Community in a New Zealand Mining Town, 1877–1939

Resource towns (such as lumber camps, power plants, and mining towns) are by their very nature peripheral. They frequently exist in a space of isolation, not only geographically but also culturally as well. The South Island mining town of Kaitangata is a classic example of this process – an industrial, working class, and heavily migrant community positioned within an otherwise agricultural, conservation, and homogenous tract of rural New Zealand. Kaitangata, in the words of one writer, ‘possessed a unique character and pattern of social interaction’ that marked it out from its immediate environment. One way in which these differences manifested themselves was in the sporting activities of the town. In a part of the world where rugby union held absolute hegemony, the town broke the mould by also fielding teams in association football, rugby league, and even Australian Rules football (distinguishing itself as the only town outside of the provincial capital of Dunedin where these three sports obtained a foothold). This paper analyses how these sporting activities contributed to a unique sense of space, addressing themes including class, ethnicity, masculinity, and identity.

Erratum to: Acidic domains differentially read histone H3 lysine 4 methylation status and are widely present in chromatin-associated proteins

Histone methylation is believed to provide binding sites for specific reader proteins, which translate histone code into biological function. Here we show that a family of acidic domain-containing proteins including nucleophosmin (NPM1), pp32, SET/TAF1β, nucleolin (NCL) and upstream binding factor (UBF) are novel H3K4me2-binding proteins. These proteins exhibit a unique pattern of interaction with methylated H3K4, as their binding is stimulated by H3K4me2 and inhibited by H3K4me1 and H3K4me3. These proteins contain one or more acidic domains consisting mainly of aspartic and/or glutamic residues that are necessary for preferential binding of H3K4me2. Furthermore, we demonstrate that the acidic domain with sufficient length alone is capable of binding H3K4me2 in vitro and in vivo. NPM1, NCL and UBF require their acidic domains for association with and transcriptional activation of rDNA genes. Interestingly, by defining acidic domain as a sequence with at least 20 acidic residues in 50 continuous amino acids, we identified 655 acidic domain-containing protein coding genes in the human genome and Gene Ontology (GO) analysis showed that many of the acidic domain proteins have chromatin-related functions. Our data suggest that acidic domain is a novel histone binding motif that can differentially read the status of H3K4 methylation and is broadly present in chromatin-associated proteins.

Comparative influenza protein interactomes identify the role of plakophilin 2 in virus restriction

Cellular protein interaction networks are integral to host defence and immune signalling pathways, which are often hijacked by viruses via protein interactions. However, the comparative virus–host protein interaction networks and how these networks control host immunity and viral infection remain to be elucidated. Here, we mapped protein interactomes between human host and several influenza A viruses (IAV). Comparative analyses of the interactomes identified common and unique interaction patterns regulating innate immunity and viral infection. Functional screening of the ‘core‘ interactome consisting of common interactions identified five novel host factors regulating viral infection. Plakophilin 2 (PKP2), an influenza PB1-interacting protein, restricts IAV replication and competes with PB2 for PB1 binding. The binding competition leads to perturbation of the IAV polymerase complex, thereby limiting polymerase activity and subsequent viral replication. Taken together, comparative analyses of the influenza–host protein interactomes identified PKP2 as a natural inhibitor of IAV polymerase complex.

Acidic domains differentially read histone H3 lysine 4 methylation status and are widely present in chromatin-associated proteins

Histone methylation is believed to provide binding sites for specific reader proteins, which translate histone code into biological function. Here we show that a family of acidic domain-containing proteins including nucleophosmin (NPM1), pp32, SET/TAF1β, nucleolin (NCL) and upstream binding factor (UBF) are novel H3K4me2-binding proteins. These proteins exhibit a unique pattern of interaction with methylated H3K4, as their binding is stimulated by H3K4me2 and inhibited by H3K4me1 and H3K4me3. These proteins contain one or more acidic domains consisting mainly of aspartic and/or glutamic residues that are necessary for preferential binding of H3K4me2. Furthermore, we demonstrate that the acidic domain with sufficient length alone is capable of binding H3K4me2 in vitro and in vivo. NPM1, NCL and UBF require their acidic domains for association with and transcriptional activation of rDNA genes. Interestingly, by defining acidic domain as a sequence with at least 20 acidic residues in 50 continuous amino acids, we identified 655 acidic domain-containing protein coding genes in the human genome and Gene Ontology (GO) analysis showed that many of the acidic domain proteins have chromatin-related functions. Our data suggest that acidic domain is a novel histone binding motif that can differentially read the status of H3K4 methylation and is broadly present in chromatin-associated proteins.

The Interaction of UDP-N-Acetylglucosamine 2-Epimerase/N-Acetylmannosamine Kinase (GNE) and Alpha-Actinin 2 Is Altered in GNE Myopathy M743T Mutant.

UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase (GNE) is the gene mutated in GNE myopathy. In an attempt to elucidate GNE functions that could account for the muscle pathophysiology of this disorder, the interaction of GNE with α-actinins has been investigated. Surface plasmon resonance and microscale thermophoresis analysis revealed, that in vitro, GNE interacts with α-actinin 2, and that this interaction has a 10-fold higher affinity compared to the GNE-α-actinin 1 interaction. Further, GNE carrying the M743T mutation, the most frequent mutation in GNE myopathy, has a 10-fold lower binding affinity to α-actinin 2 than intact GNE. It is possible that this decrease eventually affects the interaction, thus causing functional imbalance of this complex in skeletal muscle that could contribute to the myopathy phenotype. In vivo, using bi-molecular fluorescent complementation, we show the specific binding of the two proteins inside the intact cell, in a unique interaction pattern between the two partners. This interaction is disrupted in the absence of the C-terminal calmodulin-like domain of α-actinin 2, which is altered in α-actinin 1. Moreover, the binding of GNE to α-actinin 2 prevents additional binding of α-actinin 1 but not vice versa. These results suggest that the interaction between GNE and α-actinin 1 and α-actinin 2 occur at different sites in the α-actinin molecules and that for α-actinin 2 the interaction site is located at the C-terminus of the protein.

A Mathematical Model of T1D Acceleration and Delay by Viral Infection.

Type 1 diabetes (T1D) is often triggered by a viral infection, but the T1D prevalence is rising among populations that have a lower exposure to viral infection. In an animal model of T1D, the NOD mouse, viral infection at different ages may either accelerate or delay disease depending on the age of infection and the type of virus. Viral infection may affect the progression of T1D via multiple mechanisms: triggering inflammation, bystander activation of self-reactive T-cells, inducing a competitive immune response, or inducing a regulatory immune response. In this paper, we create mathematical models of the interaction of viral infection with T1D progression, incorporating each of these four mechanisms. Our goal is to understand how each viral mechanism interacts with the age of infection. The model predicts that each viral mechanism has a unique pattern of interaction with disease progression. Viral inflammation always accelerates disease, but the effect decreases with age of infection. Bystander activation has little effect at younger ages and actually decreases incidence at later ages while accelerating disease in mice that do get the disease. A competitive immune response to infection can decrease incidence at young ages and increase it at older ages, with the effect decreasing over time. Finally, an induced Treg response decreases incidence at any age of infection, but the effect decreases with age. Some of these patterns resemble those seen experimentally.