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Miller, L.

Publications and source records attributed to Miller, L..

10 recordsLinked to original sources

A Bayesian model of acquisition and clearance of bacterial colonization incorporating within-host variation

Bacterial populations that colonize a host can play important roles in host health, including serving as a reservoir that transmits to other hosts and from which invasive strains emerge, thus emphasizing the importance of understanding rates of acquisition and clearance of colonizing populations. Studies of colonization dynamics have been based on assessment of whether serial samples represent a single population or distinct colonization events. With the use of whole genome sequencing to determine genetic distance between isolates, a common solution to estimate acquisition and clearance rates has been to assume a fixed genetic distance threshold below which isolates are considered to represent the same strain. However, this approach is often inadequate to account for the diversity of the underlying within-host evolving population, the time intervals between consecutive measurements, and the uncertainty in the estimated acquisition and clearance rates. Here, we present a fully Bayesian model that provides probabilities of whether two strains should be considered the same, allowing us to determine bacterial clearance and acquisition from genomes sampled over time. Our method explicitly models the within-host variation using population genetic simulation, and the inference is done using a combination of Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC). We validate the method with multiple carefully conducted simulations and demonstrate its use in practice by analyzing a collection of methicillin resistant Staphylococcus aureus (MRSA) isolates from a large recently completed longitudinal clinical study. An R-code implementation of the method is freely available at: https://github.com/mjarvenpaa/bacterial-colonization-model.git.\n\nAuthor summaryAs colonizing bacterial populations are the source for much transmission and a reservoir for infection, they are a major focus of interest clinically and epidemiologically. Understanding the dynamics of colonization depends on being able to confidently identify acquisition and clearance events given intermittent sampling of hosts. To do so, we need a model of within-host bacterial population evolution from acquisition through the time of sampling that enables estimation of whether two samples are derived from the same population. Past efforts have frequently relied on empirical genetic distance thresholds that forgo an underlying model or employ a simple molecular clock model. Here, we present an inferential method that accounts for the timing of sample collection and population diversification, to provide a probabilistic estimate for whether two isolates represent the same colonizing strain. This method has implications for understanding the dynamics of acquisition and clearance of colonizing bacteria, and the impact on these rates by factors such as sensitivity of the sampling method, pathogen genotype, competition with other carriage bacteria, host immune response, and antibiotic exposure.

bioinformatics

Haplotype Analysis of the TRB Locus by TCRB Repertoire Sequencing

Polymorphism within the T cell receptor beta variable gene (TRBV) has been implicated in autoimmune disease and immuneCrelated adverse events (IRAEs) during immunotherapy. Previous efforts to evaluate TRBV polymorphism by whole genome sequencing (WGS) have been hampered by the repetitive nature of the TCRB locus. We present a novel longCamplicon TCRB repertoire sequencing approach to evaluate TRBV polymorphism from peripheral blood, which we use to identify TRBV allele haplotypes in 81 Caucasians.

immunology

A Fixed Moderate-dose Combination of Tiletamine+Zolazepam Outperforms Midazolam in Induction of Short-term Immobilization of Ball Pythons (Python regius)

Laboratory animals are commonly anesthetized to prevent pain and distress and to provide safe handling. Anesthesia procedures are well-developed for common laboratory mammals, but not as well established in reptiles. We assessed the performance of intramuscularly injected tiletamine (dissociative anesthetic) and zolazepam (benzodiazepine sedative) in fixed combination (2 mg/kg and 3 mg/kg) in comparison to 2 mg/kg of midazolam (benzodiazepine sedative) in ball pythons (Python regius). We measured heart and respiratory rates and quantified induction parameters (i.e., time to loss of righting reflex, time to loss of withdrawal reflex) and recovery parameters (i.e., time to regain righting reflex, withdrawal reflex, normal behavior). Mild decreases in heart and respiratory rates (median decrease of <10 beats per minute and <5 breaths per minute) were observed for most time points among all three anesthetic dose groups. No statistically significant difference between the median time to loss of righting reflex was observed among animals of any group (p = 0.783). However, the withdrawal reflex was lost in all snakes receiving 3mg/kg of tiletamine+zolazepam but not in all animals of the other two groups (p = 0.0004). In addition, the time for animals to regain the righting reflex and resume normal behavior was longer in the drug combination dose groups compared to the midazolam group (p = 0.0055). Our results indicate that midazolam is an adequate sedative for ball pythons but does not suffice to achieve reliable immobilization or anesthesia, whereas tiletamine+zolazepam achieves short-term anesthesia in a dose-dependent manner.

zoology

NK cells inhibit Plasmodium falciparum growth in red blood cells via antibody dependent cellular cytotoxicity

Antibodies acquired naturally through repeated exposure to Plasmodium falciparum are essential in the control of blood-stage malaria. Antibody-dependent functions may include neutralization of parasite-host interactions, complement activation, and activation of Fc receptor functions. A role of antibody-dependent cellular cytotoxicity (ADCC) by natural killer (NK) cells in protection from malaria has not been established. Here we show that IgG isolated from adults living in a malaria-endemic region activated ADCC by primary human NK cells, which lysed infected red blood cells (RBCs) and inhibited parasite growth in an in vitro assay for ADCC-dependent growth inhibition. RBC lysis by NK cells was highly selective for infected RBCs in a mixed culture with uninfected RBCs. Human antibodies to P. falciparum antigens PfEMP1 and RIFIN were sufficient to promote NK-dependent growth inhibition. As these results implicate acquired immunity through NK-mediated ADCC, antibody-based vaccines that target bloodstream parasites should consider this new mechanism of action.

immunology

The fungal ligand chitin directly binds and signals inflammation dependent on oligomer size and TLR2

Chitin is a highly abundant polysaccharide and linked to fungal infection and asthma. Unfortunately, its polymeric structure has hampered the identification of immune receptors directly binding chitin and signaling immune activation and inflammation, because purity, molecular structure and molarity are not well definable for a polymer typically extracted from biomass. Therefore, by using defined chitin (N-acetyl-glucosamine) oligomers, we identified six subunit long chitin chains as the smallest immunologically active motif and the innate immune receptor Toll-like receptor (TLR) 2 as the primary fungal chitin receptor on human and murine immune cells. Chitin oligomers directly bound TLR2 with nanomolar affinity and showed both overlapping and distinct signaling outcomes compared to known mycobacterial TLR2 ligands. Conversely, chitin oligomers shorter than 6 subunits were inactive or showed antagonistic effects on chitin/TLR2-mediated signaling, hinting to a size-dependent sensing/activation system unexpectedly conserved in plants and humans. Since blocking the chitin-TLR2 interaction effectively prevented chitin-mediated inflammation in vitro and in vivo, our study highlights the chitin TLR2 interaction as a potential target for developing novel therapies in chitin-related pathologies and fungal disease.

immunology

NuMA is a negative regulator of 53BP1 in DNA double-strand break repair

Accumulation of 53BP1 at DNA breaks determines DNA repair pathway choice and promotes checkpoint activation. Here, we show regulation of 53BP1 beyond repair foci. 53BP1 movements are constrained in the nucleoplasm and increase in response to DNA damage. 53BP1 interacts with the structural protein NuMA, which controls 53BP1 diffusion. This interaction, and colocalization between the two proteins in vitro and in breast tissues, is reduced after DNA damage. In cell lines and breast carcinoma, NuMA prevents 53BP1 accumulation at DNA breaks and high NuMA expression predicts better patient outcomes. Manipulating NuMA expression alters PARP inhibitor sensitivity of BRCA1-null cells, end-joining activity, and immunoglobulin class switching that rely on 53BP1. We propose a new mechanism that involves the sequestration of 53BP1 by NuMA in the absence of DNA damage. Such mechanism may have evolved to disable repair functions and may be a decisive factor for tumor responses to genotoxic treatments.

cell biology

Modular assembly of the nucleolar large subunit processome

Early co-transcriptional events of eukaryotic ribosome assembly result in the formation of the small and large subunit processomes. We have determined cryo-EM reconstructions of the nucleolar large subunit processome in different conformational states at resolutions up to 3.4 [A]ngstroms. These structures reveal how steric hindrance and molecular mimicry are used to prevent premature folding states and binding of later factors. This is accomplished by the concerted activity of 21 ribosome assembly factors that stabilize and remodel pre-ribosomal RNA and ribosomal proteins. Mutually exclusive conformations of these particles suggest that the formation of the polypeptide exit tunnel is achieved through different folding pathways during subsequent stages of ribosome assembly.

biochemistry

A Neural Population Mechanism For Rapid Learning

Long-term learning of language, mathematics, and motor skills likely requires plastic changes in the cortex, but behavior often requires faster changes, sometimes based even on single errors. Here, we show evidence of one mechanism by which the brain can rapidly develop new motor output, seemingly without altering the functional connectivity between or within cortical areas. We recorded simultaneously from hundreds of neurons in the premotor (PMd) and primary motor (M1) cortices, and computed models relating these neural populations throughout adaptation to reaching movement perturbations. We found a signature of learning in the \"null subspace\" of PMd with respect to M1. Earlier experiments have shown that null subspace activity allows the motor cortex to alter preparatory activity without directly influencing M1. In our experiments, the null subspace planning activity evolved with the adaptation, yet the \"potent\" mapping that captures information sent to M1 was preserved. Our results illustrate a population-level mechanism within the motor cortices to adjust the output from one brain area to its downstream structures that could be exploited throughout the brain for rapid, online behavioral adaptation.

neuroscience

Modern machine learning far outperforms GLMs at predicting spikes

Neuroscience has long focused on finding encoding models that effectively ask \"what predicts neural spiking?\" and generalized linear models (GLMs) are a typical approach. It is often unknown how much of explainable neural activity is captured, or missed, when fitting a GLM. Here we compared the predictive performance of GLMs to three leading machine learning methods: feedforward neural networks, gradient boosted trees (using XGBoost), and stacked ensembles that combine the predictions of several methods. We predicted spike counts in macaque motor (M1) and somatosensory (S1) cortices from standard representations of reaching kinematics, and in rat hippocampal cells from open field location and orientation. In general, the modern methods (particularly XGBoost and the ensemble) produced more accurate spike predictions and were less sensitive to the preprocessing of features. This discrepancy in performance suggests that standard feature sets may often relate to neural activity in a nonlinear manner not captured by GLMs. Encoding models built with machine learning techniques, which can be largely automated, more accurately predict spikes and can offer meaningful benchmarks for simpler models.

neuroscience

A cryptography-based approach for movement decoding

Brain decoders use neural recordings to infer a users activity or intent. To train a decoder, we generally need infer the variables of interest (covariates) using simultaneously measured neural activity. However, there are many cases where this approach is not possible. Here we overcome this problem by introducing a fundamentally new approach for decoding called distribution alignment decoding (DAD). We use the statistics of movement, much like cryptographers use the statistics of language, to find a mapping between neural activity and motor variables. DAD learns a linear decoder which aligns the distribution of its output with the typical distribution of motor outputs by minimizing their KL-divergence. We apply our approach to a two datasets collected from the motor cortex of non-human primates (NHPs): a reaching task and an isometric force production task. We study the performance of DAD and find regimes where DAD provides comparable and in some cases, better performance than a typical supervised decoder. As DAD does not rely on the ability to record motor-related outputs, it promises to broaden the set of potential applications of brain decoding.

neuroscience