Biology subjects

Miller, M.

Publications and source records attributed to Miller, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2021

RT-QuIC amplification of CWD prions in winter ticks (Dermacentor albipictus) collected from North American elk (Cervus canadensis) in a CWD-endemic area

Chronic wasting disease (CWD) is a progressive and fatal spongiform encephalopathy of deer and elk species, caused by a misfolded variant of the normal prion protein. Horizontal transmission of the misfolded CWD prion between animals is thought to occur through shedding in saliva and other forms of excreta. The role of blood in CWD transmission is less clear, though infectivity has been demonstrated in various blood fractions. Blood-feeding insects, including ticks, are known vectors for a range of bacterial and viral infections in animals and humans, though to date there has been no evidence for their involvement in prion disease transmission. In the present study, we evaluated winter ticks (Dermacentor albipictus) collected from 136 North American elk (Cervus canadensis) in a CWD-endemic area for evidence of CWD prion amplification using the real time quaking-induced conversion assay (RT-QuIC). Although 30 elk were found to be CWD-positive (22%) postmortem, amplifiable prions were found in just a single tick collected from an elk in advanced stages of CWD infection, with some evidence for prions in ticks collected from elk in mid-stage infection. These findings suggest that further investigation of ticks as reservoirs for prion disease may be warranted. ImportanceThis study reports the first finding of detectable levels of prions linked to chronic wasting disease in a tick collected from a clinically infected elk. Using the real time quaking-induced conversion assay (RT-QuIC), evidence of amplifiable CWD prions was also found in ticks collected from elk in earlier stages of disease. Observed levels were at the lower end of our detection limits, though our findings suggest that additional research evaluating ticks collected from animals in late-stage disease may be warranted to further evaluate the role of ticks as potential vectors of chronic wasting disease.

microbiology↗

bioRxiv2021

RNA interference mediates RNA toxicity with parent-of-origin effects in C. elegans expressing CTG repeats

Nucleotide repeat expansions are a hallmark of over 40 neurodegenerative diseases. These repeats cause RNA toxicity and trigger multisystemic symptoms that worsen with age. RNA toxicity can trigger, through an unclear mechanism, severe disease manifestation in infants that inherited repeats from their mothers. Here we show in Caenorhabditis elegans how RNA interference machinery causes intergenerational toxicity through inheritance of siRNAs derived from CUG repeats. The maternal repeat-derived small RNAs cause transcriptomic changes in the offspring, reduce motility and shorten lifespan. However, the toxicity phenotypes in the offspring can be rescued by perturbing the RNAi machinery in affected mothers. This points to a novel mechanism linking maternal bias and the RNAi machinery and suggests that toxic RNA is transmitted to offspring and causes disease phenotypes through intergenerational epigenetic inheritance.

molecular biology↗

bioRxiv2021

Digital 3D Brain MRI Arterial Territories Atlas

The locus and extent of brain damage in the event of vascular insult can be quantitatively established quickly and easily with vascular atlases. Although highly anticipated by clinicians and clinical researchers, no digital MRI arterial atlas is readily available for automated data analyses. We created a digital arterial territory atlas based on lesion distributions in 1,298 patients with acute stroke. The lesions were manually traced in the diffusion-weighted MRIs, binary stroke masks were mapped to a common space, probability maps of lesions were generated and the boundaries for each arterial territory was defined based on the ratio between probabilistic maps. The atlas contains the definition of four major supra- and infra-tentorial arterial territories: Anterior, Middle, Posterior Cerebral Arteries and Vertebro-Basilar, and sub-territories (thalamoperforating, lenticulostriate, basilar and cerebellar arterial territories), in two hierarchical levels. This study provides the first publicly-available, digital, 3D deformable atlas of arterial brain territories, which may serve as a valuable resource for large-scale, reproducible processing and analysis of brain MRIs of patients with stroke and other conditions.

neuroscience↗

bioRxiv2021

A cell atlas of chromatin accessibility across 25 adult human tissues

Current catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of human gene regulatory elements in diverse cell types and tissues in the human body, we applied single cell chromatin accessibility assays to 25 distinct human tissue types from multiple donors. The resulting chromatin maps comprising [~]500,000 nuclei revealed the status of open chromatin for over 750,000 candidate cis-regulatory elements (cCREs) in 54 distinct cell types. We further delineated cell type-specific and tissue-context dependent gene regulatory programs, and developmental stage specificity by comparing with a recent human fetal chromatin accessibility atlas. We finally used these chromatin maps to interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues and organ systems.

genomics↗

bioRxiv2021

Identification of candidate susceptibility genes to Puccinia graminis f. sp. tritici in wheat

Wheat stem rust disease caused by Puccinia graminis f. sp. tritici (Pgt) is a global threat to wheat production. Fast evolving populations of Pgt limit the efficacy of plant genetic resistance and constrain disease management strategies. Understanding molecular mechanisms that lead to rust infection and disease susceptibility could deliver novel strategies to deploy crop resistance through genetic loss of disease susceptibility. We used comparative transcriptome-based and orthology-guided approaches to characterize gene expression changes associated with Pgt infection in susceptible and resistant Triticum aestivum genotypes as well as the non-host Brachypodium distachyon. We targeted our analysis to genes with differential expression in T. aestivum and genes suppressed or not affected in B. distachyon and report several processes potentially linked to susceptibility to Pgt, such as cell death suppression and impairment of photosynthesis. We complemented our approach with a gene co-expression network analysis to identify wheat targets to deliver resistance to Pgt through removal or modification of putative susceptibility genes.

plant biology↗

bioRxiv2021

Large-scale genetic association and single cell accessible chromatin mapping defines cell type-specific mechanisms of type 1 diabetes risk

Translating genome-wide association studies (GWAS) of complex disease into mechanistic insight requires a comprehensive understanding of risk variant effects on disease-relevant cell types. To uncover cell type-specific mechanisms of type 1 diabetes (T1D) risk, we combined genetic association mapping and single cell epigenomics. We performed the largest to-date GWAS of T1D in 489,679 samples imputed into 59.2M variants, which identified 74 novel association signals including several large-effect rare variants. Fine-mapping of 141 total signals substantially improved resolution of causal variant credible sets, which primarily mapped to non-coding sequence. To annotate cell type-specific regulatory mechanisms of T1D risk variants, we mapped 448,142 candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cell types using snATAC-seq of 131,554 nuclei. T1D risk variants were enriched in cCREs active in CD4+ T cells as well as several additional cell types including pancreatic exocrine acinar and ductal cells. High-probability T1D risk variants at multiple signals mapped to exocrine-specific cCREs including novel loci near CEL, GP2 and CFTR. At the CFTR locus, the likely causal variant rs7795896 mapped in a ductal-specific distal cCRE which regulated CFTR and the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in T1D pathogenesis and highlight the power of combining large-scale GWAS and single cell epigenomics to provide insight into the cellular origins of complex disease.

genetics↗

bioRxiv2021

An epigenetic switch regulates the ontogeny of AXL positive/EGFR-TKI resistant cells by modulating miR-335 expression

Lung cancer remains the leading cause of cancer-related mortality worldwide, despite current advancements in research and therapeutics. Many patients diagnosed with lung cancer will develop resistance to chemotherapeutic agents. In the context of non-small cell lung cancers (NSCLC) harboring EGFR oncogenic mutations, augmented levels of AXL and GAS6 have been found to drive Erlotinib resistance in certain tumors with mesenchymal-like features. By studying the ontogeny of AXL-positive cells, we have identified a novel non-genetic mechanism of drug resistance based on cell-state transition. We demonstrate that AXL-positive cells are already present as a sub-population of cancer cells in Erlotinib-naive tumors and tumor-derived cell lines, and that the expression of AXL is regulated through a stochastic mechanism centered on the epigenetic regulation of miR-335. The existence of a cell-intrinsic program through which AXL-positive/Erlotinib-resistant cells emerge infers the need of treating tumors harboring EGFR-oncogenic mutations upfront with combinatorial treatments targeting both AXL-negative and AXL-positive cancer cells.

cancer biology↗

bioRxiv2021

Transcriptomics data availability and reusability in the transition from microarray to next-generation sequencing

Over the last two decades, molecular biology has been changed by the introduction of high-throughput technologies. Data sharing requirements have prompted the establishment of persistent data archives. A standardized approach for recording and managing these data was first proposed in the Minimal Information About a Microarray Experiment (MIAME) guidelines. The Minimal Information about a high throughput nucleotide Sequencing Experiment (MINSEQE) proposal was introduced in 2008 as a logical extension of the guidelines to next-generation sequencing (NGS) technologies used for transcriptome analysis. We present a historical snapshot of the data-sharing situation focusing on transcriptomics data from both microarray and RNA-sequencing experiments published between 2009 and 2013, a period during which RNA-seq studies became increasingly popular for transcriptome analysis. We assess how much data from RNA-seq based experiments is actually available in persistent data archives, compared to data derived from microarray based experiments, and evaluate how these types of data differ. Based on this analysis, we provide recommendations to improve RNA-seq data availability, reusability, and reproducibility.

bioinformatics↗

bioRxiv2020

Reaction-Diffusion Model of Cortical Atrophy Spread during Early Stages of Alzheimer's Disease

1.This study introduces a reaction-diffusion model of atrophy spread across the rhinal cortex during early stages of Alzheimers disease. Our finite elements model of atrophy spread is motivated by histological evidence of a spatio-temporally specific pattern of neurofibrillary tau accumulation, and evidence of grey matter atrophy correlating with sites of neurofibrillary tau accumulation. The goal is to estimate disease-related parameters such as the origin of atrophy, the speed at which atrophy spreads, and the stage of the disease. We solve a constrained optimization problem using the adjoint state method and gradient descent to match modeled cortical thickness to observed cortical thickness as calculated from 3T MRI scans. Simulation testing shows that disease-related parameters can be estimated accurately with as little as 2 years of annual observations, depending on the stage of the disease. Case studies of 3 subjects suggests that we can pinpoint the origin of atrophy to the anterior transentorhinal cortex, and that the speed of atrophy spread is less than 1 mm per year. In the future, this type of modeling could be useful to stage the progression of the disease prior to the onset of clinical symptoms. 2. Author SummaryMisfolded tau proteins are associated with Alzheimers disease. They are known to accumulate and spread across the rhinal cortex, which is an area of the temporal lobe. Recent imaging studies suggest that we can detect grey matter thinning that occurs in pattern similar to tau spread. In this study, we introduce a model of disease spread to examine where thinning begins, how fast it spreads, and the stage of the disease. The results show that the origin of thinning corresponds with the earliest known location of tau accumulation, and spreads at a rate of less than 1 mm per year. Future work may focus on staging the progression of the disease using this type of model.

neuroscience↗

bioRxiv2020

A Library Of Induced Pluripotent Stem Cells From Clinically Well-Characterized, Diverse Healthy Human Individuals

A library of well-characterized human induced pluripotent stem cell (hiPSC) lines from clinically healthy human subjects could serve as a useful resource of normal controls for in vitro human development, disease modeling, genotype-phenotype association studies, and drug response evaluation. We report generation and extensive characterization of a gender-balanced, racially/ethnically diverse library of hiPSC lines from 40 clinically healthy human individuals who range in age from 22-61. The hiPSCs match the karyotype and short tandem repeat identity of their parental fibroblasts, and have a transcription profile characteristic of pluripotent stem cells. We provide whole genome sequencing data for one hiPSC clone from each individual, genomic ancestry determination, and analysis of Mendelian disease genes and risks. We document similar transcriptomic profiles, single-cell RNA-seq derived cell clusters and physiology of cardiomyocytes differentiated from multiple independent hiPSC lines. This extensive characterization makes this hiPSC library a valuable resource for many studies on human biology.

cell biology↗

bioRxiv2020

Super-relaxed state of myosin in human skeletal muscle is fiber-type dependent

The myosin super-relaxed state (SRX) in skeletal muscle is hypothesized to play an important role in regulating muscle contractility and thermogenesis in humans, but has only been examined in model organisms. Here we report the first human skeletal muscle SRX measurements, using quantitative epifluorescence microscopy of fluorescent 2/3-O-(N-methylanthraniloyl) ATP (mantATP) single-nucleotide turnover. Myosin heavy chain (MHC) isoform expression was determined using gel electrophoresis for each permeabilized vastus lateralis fiber, to allow for novel comparisons of SRX between fiber-types. We find that the fraction of myosin in SRX is less in MHC IIA fibers than in MHC I and IIAX fibers (p = 0.008). ATP turnover of SRX is faster in MHC IIAX fibers compared to MHC I and IIA fibers (p = 0.001). We conclude that SRX biochemistry is measurable in human skeletal muscle, and our data indicate that SRX depends on fiber type as classified by MHC isoform. Extension from this preliminary work would provide further understanding regarding the role of SRX in human muscle physiology.

biophysics↗

bioRxiv2020

Examination of a first-in-class bis-dialkylnorspermidine-terphenyl antibiotic in topical formulation against mono and polymicrobial biofilms

Biofilm-impaired tissue is a significant factor in chronic wounds such as diabetic foot ulcers. Most, if not all, anti-biotics in clinical use have been optimized against planktonic phenotypes. In this study, an in vitro assessment was performed to determine the potential efficacy of a unique first-in-class series of antibiofilm antibiotics and compare outcomes to current clinical standards of care. The agent, CZ-01179, was formulated into a hydrogel and tested against mature biofilms of a clinical isolate of methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa ATCC 27853 using two separate methods. In the first method, biofilms were grown on cellulose discs on an agar surface. Topical agents were spread on gauze and placed over the biofilms for 24 h. Biofilms were quantified and imaged with confocal and scanning electron microscopy. In the second method, biofilms were grown on bioabsorbable collagen coupons in a modified CDC biofilm reactor. Coupons were immersed in treatment for 24 h. The first method was limited in its ability to assess efficacy. Efficacy profiles against biofilms grown on collagen were more definitive, with CZ-01179 gel eradicating well-established biofilms to a greater degree compared to clinical standards. In conclusion, CZ-01179 may be a promising topical agent that targets the biofilm phenotype. Pre-clinical work is currently being performed to determine the translatable potential of CZ-01179 gel.

microbiology↗

bioRxiv2020

A novel tool for standardizing clinical data in a realism-based common data model

Standardizing clinical information in a common data model is important for promoting interoperability and facilitating high quality research. Semantic Web technologies such as Resource Description Framework can be utilized to their full potential when a clinical data model accurately reflects the reality of the clinical situation it describes. To this end, the Open Biomedical Ontologies Foundry provides a set of ontologies that conform to the principles of realism and can be used to create a realism-based clinical data model. However, the challenge of programmatically defining such a model and loading data from disparate sources into the model has not been addressed by pre-existing software solutions. The PennTURBO Semantic Engine is a tool developed at the University of Pennsylvania that works in conjunction with data aggregation software to transform source-specific RDF data into a source-independent, realism-based data model. This system sources classes from an application ontology and specifically defines how instances of those classes may relate to each other. Additionally, the system defines and executes RDF data transformations by launching dynamically generated SPARQL update statements. The Semantic Engine was designed as a generalizable RDF data standardization tool, and is able to work with various data models and incoming data sources. Its human-readable configuration files can easily be shared between institutions, providing the basis for collaboration on a standard realism-based clinical data model.

bioinformatics↗

bioRxiv2020

Bio-Node - Bioinformatics in the Cloud

MotivationThe applicability and reproducibility of bioinformatics methods and results often depend on the structure and software architecture of their development. Exponentially growing data sets require ever more optimization and performance with conventional computing capacities lacking this process. This creates a large overhead for software development in a research area which is primarily interested in solving complex biological problems rather than developing new, performant software solutions. In pure computer science, new structures in the field of web development have produced more efficient processes for container-based software solutions. The advantages of these structures have rarely been explored in a broader scientific scale. This is also the case with the trend of migrating computations from on premise resources to the cloud. ResultsWe created Bio-Node, a new platform for large scale bio data analysis utilizing cloud compute resources (publicly available at https://bio-node.de). Bio-Node enables building complex workflows using a sophisticated web interface. We applied Bio-Node to implement bioinformatic workflows for rapid metagenome function annotation. We further developed "Auto-Clustering", a workflow that automatically extracts the most suited clustering parameters for specific data types and subsequently enables to optimally segregate unknown samples of the same type. Compared to existing methods and approaches Bio-Node improves performance and costs of bioinformatics data analyses while providing an easier and faster development process with focus on reproducibility and reusability. Supplementary information is available at https://doi.org/10.5281/zenodo.3753146

bioinformatics↗

bioRxiv2020

Open source software tool for the automated detection and characterization of epithelial cells from trace biological samples

This paper presents a strategy for an unsupervised workflow for identifying epithelial cells in microscopic images and characterizing their morphological and/or optical properties. The proposed method can be used on cells that have been stained with fluorescent dyes and imaged using conventional optical microscopes. The workflow was tested on cell populations that were imaged directly on touch/contact surfaces and stained with nucleic acid dyes to visualize genetic content. Our results show that this approach could be a useful strategy for characterizing differences in staining efficiency and/or morphological properties of individual cells or aggregate populations within a biological sample. Further, they can potentially reduce the laborious nature of microscopic analysis and increase throughput and reproducibility of similar studies.

cell biology↗

bioRxiv2020

Solving the where problem in neuroanatomy: a generative framework with learned mappings to register multimodal, incomplete data into a reference brain

A current focus of research in neuroscience is to enumerate, map and annotate neuronal cell types in whole vertebrate brains using different modalities of data acquisition. Mapping these molecular and anatomical datasets into a common reference space remains a key challenge. While several brain-to-atlas mapping workflows exist, they do not adequately address challenges of modern high throughput neuroimaging, including multimodal and multiscale signals, missing data or non reference signals, and geometric quantification of individual variation. Our solution is to implement a generative statistical model that describes the likelihood of imaging data given a sequence of transforms of an atlas image, and a framework for maximum a posteriori estimation of unknown parameters capturing the issues listed above. The key idea in our approach is to minimize the difference between synthetic image volumes and real data over these parameter. Rather than merely using mappings as a "normalization" step, we implement tools for using their local metric changes as an opportunity for geometric quantification of technical and biological sources of variation in an unprecedented manner. While the framework is used to compute pairwise mappings, our approach particularly allows for easy compositions across chains of multimodality datasets. We apply these methods across a broad range of datasets including various combinations of in-vivo and ex-vivo MRI, 3D STP and fMOST data sets, 2D serial histology sections, and brains processed for snRNAseq with tissue partially removed. We show biological utility by quantifying cell density and diffeomorphic characterization of brain shape fluctuations across biological covariates. We note that the magnitude of individual variation is often greater than differences between different sample preparation techniques. To facilitate community accessibility, we implement our algorithm as open source, include a web based framework, and implement input and output dataset standards. Our work establishes a quantitative, scalable and streamlined workflow for unifying a broad spectrum of multi-modal whole-brain light microscopic data volumes into a coordinate-based atlas framework. This work enables large scale integration of whole brain data sets that are essential in modern neuroscience.

neuroscience↗

bioRxiv2020

Visualizing synaptic plasticity in vivo by large-scale imaging of endogenous AMPA receptors

Elucidating how synaptic molecules such as AMPA receptors mediate neuronal communication and tracking their dynamic expression during behavior is crucial to understand cognition and disease, but current technological barriers preclude large-scale exploration of molecular dynamics in vivo. We have developed a suite of innovative methodologies that break through these barriers: a new knockin mouse line with fluorescently tagged endogenous AMPA receptors, two-photon imaging of hundreds of thousands of labeled synapses in behaving mice, and computer-vision-based automatic synapse detection. Using these tools, we can longitudinally track how the strength of synapses changes during behavior. We used this approach to generate an unprecedentedly detailed spatiotemporal map of synaptic plasticity underlying sensory experience. More generally, these tools can be used as an optical probe capable of measuring functional synapse strength across entire brain areas during any behavioral paradigm, describing complex system-wide changes with molecular precision.

neuroscience↗

bioRxiv2020

Snow Microbiome Functional Analyses Reveal Novel Microbial Metabolism of Complex Organic Compounds

Microbes active in extremely cold environments are not as well explored as those of other extreme environments. Studies have revealed a substantial microbial diversity and identified cold-specific microbiome molecular functions. We analyzed the metagenomes and metatranscriptomes of twenty snow samples collected during early and late spring in Svalbard, Norway using our computational read-based microbiome function annotation tool, mi-faser. Our results revealed a more diverse microbiome functional capacity and activity in the early compared to in the late spring samples. The dissimilarity between the metagenomes and metatranscriptomes of the same samples was also significantly higher in the early spring. These findings suggest that early spring samples may contain a larger fraction of DNA of dormant organisms, while late spring samples reflect a new community that is metabolically active. We additionally showed that the abundance of the sequencing reads mapping to the fatty acid synthesis-related microbial pathways was significantly positively correlated with organic acid levels, in both our late spring metagenomes and metatranscriptomes. Moreover, the geraniol degradation pathway and the styrene degradation pathway read abundances correlated and inversely correlated, respectively, with the organic acid levels. These results suggest a possible nutrient switch. Our study thus highlights the activity of microbial degradation pathways of complex organic compounds previously unreported at low temperatures.

bioinformatics↗