scholarly journals Rapid Generation of Medical Countermeasure Candidates Via Computational Variation Analysis

2019 ◽  
Author(s):  
Darrell O. Ricke
Keyword(s):  
High Throughput Sequencing ◽  
Antigenic Variation ◽  
Emerging Infectious Diseases ◽  
Treatment Strategies ◽  
Variation Analysis ◽  
T Cell Vaccination ◽  
Rapid Responses ◽  
Large Numbers ◽  
Rapid Generation ◽  
Medical Countermeasures

AbstractRapid responses to emerging infectious diseases are needed for viral and bacterial pathogens. For some pathogens, no medical countermeasures (MCMs) yet exist. Pathogen heterogeneity and antigenic variation lead to immune response escape mutations for some pathogens (e.g., influenza) limiting the effectiveness of medical countermeasures. High throughput sequencing enables characterization of large numbers of pathogen isolates to which residue variation analysis can be applied to identify low variability targets. Multiple approaches are proposed that leverage these low variability targets as the first step of medical countermeasure development. Classes of MCMs informed by this approach include the following: DNA or RNA vaccines, both B-cell and T-cell vaccination strategies, anti-viral RNA targeting, antibody therapeutics, and aptamer targeting of viral protein complex interfaces as potential treatment strategies for infected individuals. Variation analysis-designed countermeasures targeting the Ebola glycoprotein are presented to illustrate the concepts for the proposed multiple targeted countermeasures.

scholarly journals Behavior Individuality: A Focus on Drosophila melanogaster

2021 ◽  
Vol 12 ◽  
Author(s):  
Rubén Mollá-Albaladejo ◽  
Juan A. Sánchez-Alcañiz
Keyword(s):  
Gene Expression ◽  
Drosophila Melanogaster ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Great Effort ◽  
Behavioral Differences ◽  
Adult Behavior ◽  
Large Numbers ◽  
Environmental Variations ◽  
And Function

Among individuals, behavioral differences result from the well-known interplay of nature and nurture. Minute differences in the genetic code can lead to differential gene expression and function, dramatically affecting developmental processes and adult behavior. Environmental factors, epigenetic modifications, and gene expression and function are responsible for generating stochastic behaviors. In the last decade, the advent of high-throughput sequencing has facilitated studying the genetic basis of behavior and individuality. We can now study the genomes of multiple individuals and infer which genetic variations might be responsible for the observed behavior. In addition, the development of high-throughput behavioral paradigms, where multiple isogenic animals can be analyzed in various environmental conditions, has again facilitated the study of the influence of genetic and environmental variations in animal personality. Mainly, Drosophila melanogaster has been the focus of a great effort to understand how inter-individual behavioral differences emerge. The possibility of using large numbers of animals, isogenic populations, and the possibility of modifying neuronal function has made it an ideal model to search for the origins of individuality. In the present review, we will focus on the recent findings that try to shed light on the emergence of individuality with a particular interest in D. melanogaster.

Recent Advances in Medical Device Triage Technologies for Chemical, Biological, Radiological, and Nuclear Events

2015 ◽  
Vol 30 (3) ◽  
pp. 320-323 ◽  
Author(s):  
Krystal Lansdowne ◽  
Christopher G. Scully ◽  
Loriano Galeotti ◽  
Suzanne Schwartz ◽  
David Marcozzi ◽  
...  
Keyword(s):  
Medical Device ◽  
Emerging Infectious Diseases ◽  
Science Research ◽  
Identification System ◽  
Publication Type ◽  
Novel Technologies ◽  
Medical Apps ◽  
Recent Advances ◽  
Nuclear Events ◽  
Medical Countermeasures

AbstractIn 2010, the US Food and Drug Administration (Silver Spring, Maryland USA) created the Medical Countermeasures Initiative with the mission of development and promoting medical countermeasures that would be needed to protect the nation from identified, high‐priority chemical, biological, radiological, or nuclear (CBRN) threats and emerging infectious diseases. The aim of this review was to promote regulatory science research of medical devices and to analyze how the devices can be employed in different CBRN scenarios. Triage in CBRN scenarios presents unique challenges for first responders because the effects of CBRN agents and the clinical presentations of casualties at each triage stage can vary. The uniqueness of a CBRN event can render standard patient monitoring medical device and conventional triage algorithms ineffective. Despite the challenges, there have been recent advances in CBRN triage technology that include: novel technologies; mobile medical applications (“medical apps”) for CBRN disasters; electronic triage tags, such as eTriage; diagnostic field devices, such as the Joint Biological Agent Identification System; and decision support systems, such as the Chemical Hazards Emergency Medical Management Intelligent Syndromes Tool (CHEMM-IST). Further research and medical device validation can help to advance prehospital triage technology for CBRN events.LansdowneK, ScullyCG, GaleottiL, SchwartzS, MarcozziD, StraussDG. Recent advances in medical device triage technologies for chemical, biological, radiological, and nuclear events. Prehosp Disaster Med. 2015;30(3):1-4

scholarly journals Cooperation between PDGF and FGF converts slowly dividing O-2Aadult progenitor cells to rapidly dividing cells with characteristics of O-2Aperinatal progenitor cells.

1992 ◽  
Vol 118 (4) ◽  
pp. 889-900 ◽  
Author(s):  
G Wolswijk ◽  
M Noble
Keyword(s):  
Progenitor Cells ◽  
Adult Brain ◽  
High Rate ◽  
Adult Rat ◽  
Large Numbers ◽  
Dividing Cells ◽  
Rapid Generation ◽  
And Migration

We have shown previously that oligodendrocyte-type-2 astrocyte (O-2A) progenitor cells isolated from adult rat optic nerves can be distinguished in vitro from their perinatal counterparts on the basis of their much slower rates of division, differentiation, and migration when grown in the presence of cortical astrocytes or PDGF. This behavior is consistent with in vivo observations that there is only a modest production of oligodendrocytes in the adult CNS. As such a behavior is inconsistent with the likely need for a rapid generation of oligodendrocytes following demyelinating damage to the mature CNS, we have been concerned with identifying in vitro conditions that allow O-2Aadult progenitor cells to generate rapidly large numbers of progeny cells. We now provide evidence that many slowly dividing O-2Aadult progenitor cells can be converted to rapidly dividing cells by exposing adult optic nerve cultures to both PDGF and bFGF. In addition, these O-2Aadult progenitor cells appear to acquire other properties of O-2Aperinatal progenitor cells, such as bipolar morphology and high rate of migration. Although many O-2Aadult progenitor cells in cultures exposed to bFGF alone also divide rapidly, these cells are multipolar and migrate little in vitro. Oligodendrocytic differentiation of O-2Aadult progenitor cells, which express receptors for bFGF in vitro, is almost completely inhibited in cultures exposed to bFGF or bFGF plus PDGF. As bFGF and PDGF appear to be upregulated and/or released after injury to the adult brain, this particular in vitro response of O-2Aadult progenitor cells to PDGF and bFGF may be of importance in the generation of large numbers of new oligodendrocytes in vivo following demyelination.

scholarly journals Private haplotype barcoding facilitates inexpensive high-resolution genotyping of multiparent crosses

2017 ◽  
Author(s):  
Daniel A. Skelly ◽  
John H. McCusker ◽  
Eric A. Stone ◽  
Paul M. Magwene
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
High Throughput Sequencing ◽  
Hidden Markov ◽  
Model Systems ◽  
Model Organisms ◽  
Large Numbers ◽  
Private Haplotype ◽  
Individual Offspring ◽  
Base Sequencing

AbstractInexpensive, high-throughput sequencing has led to the generation of large numbers of sequenced genomes representing diverse lineages in both model and non-model organisms. Such resources are well suited for the creation of new multiparent populations to identify quantitative trait loci that contribute to variation in phenotypes of interest. However, despite significant drops in per-base sequencing costs, the costs of sample handling and library preparation remain high, particularly when many samples are sequenced. We describe a novel method for pooled genotyping of offspring from multiple genetic crosses, such as those that that make up multiparent populations. Our approach, which we call "private haplotype barcoding” (PHB), utilizes private haplotypes to deconvolve patterns of inheritance in individual offspring from mixed pools composed of multiple offspring. We demonstrate the efficacy of this approach by applying the PHB method to whole genome sequencing of 96 segregants from 12 yeast crosses, achieving over a 90% reduction in sample preparation costs relative to non-pooled sequencing. In addition, we implement a hidden Markov model to calculate genotype probabilities for a generic PHB run and a specialized hidden Markov model for the yeast crosses that improves genotyping accuracy by making use of tetrad information. Private haplotype barcoding holds particular promise for facilitating inexpensive genotyping of large pools of offspring in diverse non-model systems.

scholarly journals Deep genome annotation of the opportunistic human pathogenStreptococcus pneumoniaeD39

2018 ◽  
Author(s):  
Jelle Slager ◽  
Rieza Aprianto ◽  
Jan-Willem Veening
Keyword(s):  
Single Molecule ◽  
Genome Annotation ◽  
Antigenic Variation ◽  
Current Knowledge ◽  
Bacterial Genome ◽  
Treatment Strategies ◽  
Human Pathogens ◽  
Genome Data ◽  
Manual Curation ◽  
Automated Tools

ABSTRACTA precise understanding of the genomic organization into transcriptional units and their regulation is essential for our comprehension of opportunistic human pathogens and how they cause disease. Using single-molecule real-time (PacBio) sequencing we unambiguously determined the genome sequence ofStreptococcus pneumoniaestrain D39 and revealed several inversions previously undetected by short-read sequencing. Significantly, a chromosomal inversion results in antigenic variation of PhtD, an important surface-exposed virulence factor. We generated a new genome annotation using automated tools, followed by manual curation, reflecting the current knowledge in the field. By combining sequence-driven terminator prediction, deep paired-end transcriptome sequencing and enrichment of primary transcripts by Cappable-Seq, we mapped 1,015 transcriptional start sites and 748 termination sites. Using this new genomic map, we identified several new small RNAs (sRNAs), riboswitches (including twelve previously misidentified as sRNAs), and antisense RNAs. In total, we annotated 92 new protein-encoding genes, 39 sRNAs and 165 pseudogenes, bringing theS. pneumoniaeD39 repertoire to 2,151 genetic elements. We report operon structures and observed that 9% of operons lack a 5’-UTR. The genome data is accessible in an online resource called PneumoBrowse (https://veeninglab.com/pneumobrowse) providing one of the most complete inventories of a bacterial genome to date. PneumoBrowse will accelerate pneumococcal research and the development of new prevention and treatment strategies.

scholarly journals SNP Variable Selection by Generalized Graph Domination

2018 ◽  
Author(s):  
Shuzhen Sun ◽  
Zhuqi Miao ◽  
Blaise Ratcliffe ◽  
Polly Campbell ◽  
Bret Pasch ◽  
...  
Keyword(s):  
Variable Selection ◽  
High Throughput Sequencing ◽  
Dominating Set ◽  
Similarity Measures ◽  
Correlation Coefficients ◽  
Biological Research ◽  
Pairwise Linkage Disequilibrium ◽  
Graph Theoretic ◽  
Large Numbers ◽  
Highly Correlated

AbstractHigh-throughput sequencing technology has revolutionized both medical and biological research by generating exceedingly large numbers of genetic variants. The resulting datasets share a number of common characteristics that might lead to poor generalization capacity. Concerns include noise accumulated due to the large number of predictors, sparse information regarding the p ≫ n problem, and overfitting and model mis-identification resulting from spurious collinearity. Additionally, complex correlation patterns are present among variables. As a consequence, reliable variable selection techniques play a pivotal role in predictive analysis, generalization capability, and robustness in clustering, as well as interpretability of the derived models.K-dominating set, a parameterized graph-theoretic generalization model, was used to model SNP (single nucleotide polymorphism) data as a similarity network and searched for representative SNP variables. In particular, each SNP was represented as a vertex in the graph, (dis)similarity measures such as correlation coefficients or pairwise linkage disequilibrium were estimated to describe the relationship between each pair of SNPs; a pair of vertices are adjacent, i.e. joined by an edge, if the pairwise similarity measure exceeds a user-specified threshold. A minimum K-dominating set in the SNP graph was then made as the smallest subset such that every SNP that is excluded from the subset has at least k neighbors in the selected ones. The strength ofk-dominating set selection in identifying independent variables, and in culling representative variables that are highly correlated with others, was demonstrated by a simulated dataset. The advantages of k-dominating set variable selection were also illustrated in two applications: pedigree reconstruction using SNP profiles of 1,372 Douglas-fir trees, and species delineation for 226 grasshopper mouse samples. A C++ source code that implements SNP-SELECT and uses Gurobi™ optimization solver for the k-dominating set variable selection is available (https://github.com/transgenomicsosu/SNP-SELECT).

scholarly journals COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms

2021 ◽  
Vol 12 ◽  
Author(s):  
Robert W. Malone ◽  
Philip Tisdall ◽  
Philip Fremont-Smith ◽  
Yongfeng Liu ◽  
Xi-Ping Huang ◽  
...  
Keyword(s):  
Mechanism Of Action ◽  
Cell Activation ◽  
Treatment Strategies ◽  
Signs And Symptoms ◽  
Histamine Receptor ◽  
Mechanisms Of Action ◽  
Mast Cell Activation ◽  
Dose Selection ◽  
Principal Mechanism ◽  
Medical Countermeasures

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. SARS-CoV-2 infection is necessary but not sufficient for development of clinical COVID-19 disease. Currently, there are no approved pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We have investigated several plausible hypotheses for famotidine activity including antiviral and host-mediated mechanisms of action. We propose that the principal mechanism of action of famotidine for relieving COVID-19 symptoms involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release. Based on these findings and associated hypothesis, new COVID-19 multi-drug treatment strategies based on repurposing well-characterized drugs are being developed and clinically tested, and many of these drugs are available worldwide in inexpensive generic oral forms suitable for both outpatient and inpatient treatment of COVID-19 disease.

scholarly journals Current status of use of high throughput nucleotide sequencing in rheumatology

RMD Open ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. e001324
Author(s):  
Sebastian Boegel ◽  
John C Castle ◽  
Andreas Schwarting
Keyword(s):  
Rheumatic Diseases ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Treatment Strategies ◽  
Current Status ◽  
Nucleotide Sequencing ◽  
Rna Seq ◽  
Manual Search ◽  
Molecular Features ◽  
Manual Curation

ObjectiveHere, we assess the usage of high throughput sequencing (HTS) in rheumatic research and the availability of public HTS data of rheumatic samples.MethodsWe performed a semiautomated literature review on PubMed, consisting of an R-script and manual curation as well as a manual search on the Sequence Read Archive for public available HTS data.ResultsOf the 699 identified articles, rheumatoid arthritis (n=182 publications, 26%), systemic lupus erythematous (n=161, 23%) and osteoarthritis (n=152, 22%) are among the rheumatic diseases with the most reported use of HTS assays. The most represented assay is RNA-Seq (n=457, 65%) for the identification of biomarkers in blood or synovial tissue. We also find, that the quality of accompanying clinical characterisation of the sequenced patients differs dramatically and we propose a minimal set of clinical data necessary to accompany rheumatological-relevant HTS data.ConclusionHTS allows the analysis of a broad spectrum of molecular features in many samples at the same time. It offers enormous potential in novel personalised diagnosis and treatment strategies for patients with rheumatic diseases. Being established in cancer research and in the field of Mendelian diseases, rheumatic diseases are about to become the third disease domain for HTS, especially the RNA-Seq assay. However, we need to start a discussion about reporting of clinical characterisation accompany rheumatological-relevant HTS data to make clinical meaningful use of this data.

scholarly journals Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis

2019 ◽  
Vol 10 (1) ◽  
pp. 151-163 ◽  
Author(s):  
Anna Tyler ◽  
J. Matthew Mahoney ◽  
Gregory W. Carter
Keyword(s):  
Systemic Sclerosis ◽  
Lung Function ◽  
Lung Disease ◽  
Association Studies ◽  
Treatment Strategies ◽  
Specific Treatment ◽  
Genetic Interactions ◽  
Genome Wide Association Studies ◽  
Lung Pathology ◽  
Large Numbers

Scleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprising WNT5A, RBMS3, and MSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin.

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