scholarly journals HOPS: Automated detection and authentication of pathogen DNA in archaeological remains

2019 ◽  
Author(s):  
Ron Hübler ◽  
Felix M. Key ◽  
Christina Warinner ◽  
Kirsten I. Bos ◽  
Johannes Krause ◽  
...  
Keyword(s):  
High Throughput ◽  
Ancient Dna ◽  
High Throughput Screening ◽  
Large Scale ◽  
Sequence Data ◽  
Evolutionary Relationship ◽  
Molecular Data ◽  
Clinical Samples ◽  
Archaeological Remains ◽  
Archaeological Material

AbstractHigh-throughput DNA sequencing enables large-scale metagenomic analyses of complex biological systems. Such analyses are not restricted to present day environmental or clinical samples, but can also be fruitfully applied to molecular data from archaeological remains (ancient DNA), and a focus on ancient bacteria can provide valuable information on the long-term evolutionary relationship between hosts and their pathogens. Here we present HOPS (HeuristicOperations forPathogenScreening), an automated bacterial screening pipeline for ancient DNA sequence data that provides straightforward and reproducible information on species identification and authenticity. HOPS provides a versatile and fast pipeline for high-throughput screening of bacterial DNA from archaeological material to identify candidates for subsequent genomic-level analyses.

scholarly journals HOPS: automated detection and authentication of pathogen DNA in archaeological remains

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Ron Hübler ◽  
Felix M. Key ◽  
Christina Warinner ◽  
Kirsten I. Bos ◽  
Johannes Krause ◽  
...  
Keyword(s):  
High Throughput ◽  
Dna Sequences ◽  
High Throughput Screening ◽  
Large Scale ◽  
Molecular Data ◽  
Archaeological Remains ◽  
Archaeological Material ◽  
Versatile Tool ◽  
Genome Level ◽  
Pathogen Dna

AbstractHigh-throughput DNA sequencing enables large-scale metagenomic analyses of complex biological systems. Such analyses are not restricted to present-day samples and can also be applied to molecular data from archaeological remains. Investigations of ancient microbes can provide valuable information on past bacterial commensals and pathogens, but their molecular detection remains a challenge. Here, we present HOPS (Heuristic Operations for Pathogen Screening), an automated bacterial screening pipeline for ancient DNA sequences that provides detailed information on species identification and authenticity. HOPS is a versatile tool for high-throughput screening of DNA from archaeological material to identify candidates for genome-level analyses.

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
Data Mining ◽  
Refractive Index ◽  
High Throughput ◽  
First Principles ◽  
High Throughput Screening ◽  
Large Scale ◽  
Computational Study ◽  
High Refractive Index ◽  
Structural Features ◽  
Learning Program

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>

Large-scale High-throughput Screening Revealed 5'-(carbonylamino)-2,3'- bithiophene-4'-carboxylate as Novel Template for Antibacterial Agents

2020 ◽  
Vol 17 (5) ◽  
pp. 716-724
Author(s):  
Yan A. Ivanenkov ◽  
Renat S. Yamidanov ◽  
Ilya A. Osterman ◽  
Petr V. Sergiev ◽  
Vladimir A. Aladinskiy ◽  
...  
Keyword(s):  
Antibacterial Activity ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Antibacterial Agents ◽  
Sos Response ◽  
Luciferase Assay ◽  
Translational Machinery ◽  
E Coli ◽  
New Class

Background: The key issue in the development of novel antimicrobials is a rapid expansion of new bacterial strains resistant to current antibiotics. Indeed, World Health Organization has reported that bacteria commonly causing infections in hospitals and in the community, e.g. E. Coli, K. pneumoniae and S. aureus, have high resistance vs the last generations of cephalosporins, carbapenems and fluoroquinolones. During the past decades, only few successful efforts to develop and launch new antibacterial medications have been performed. This study aims to identify new class of antibacterial agents using novel high-throughput screening technique. Methods: We have designed library containing 125K compounds not similar in structure (Tanimoto coeff.< 0.7) to that published previously as antibiotics. The HTS platform based on double reporter system pDualrep2 was used to distinguish between molecules able to block translational machinery or induce SOS-response in a model E. coli system. MICs for most active chemicals in LB and M9 medium were determined using broth microdilution assay. Results: In an attempt to discover novel classes of antibacterials, we performed HTS of a large-scale small molecule library using our unique screening platform. This approach permitted us to quickly and robustly evaluate a lot of compounds as well as to determine the mechanism of action in the case of compounds being either translational machinery inhibitors or DNA-damaging agents/replication blockers. HTS has resulted in several new structural classes of molecules exhibiting an attractive antibacterial activity. Herein, we report as promising antibacterials. Two most active compounds from this series showed MIC value of 1.2 (5) and 1.8 μg/mL (6) and good selectivity index. Compound 6 caused RFP induction and low SOS response. In vitro luciferase assay has revealed that it is able to slightly inhibit protein biosynthesis. Compound 5 was tested on several archival strains and exhibited slight activity against gram-negative bacteria and outstanding activity against S. aureus. The key structural requirements for antibacterial potency were also explored. We found, that the unsubstituted carboxylic group is crucial for antibacterial activity as well as the presence of bulky hydrophobic substituents at phenyl fragment. Conclusion: The obtained results provide a solid background for further characterization of the 5'- (carbonylamino)-2,3'-bithiophene-4'-carboxylate derivatives discussed herein as new class of antibacterials and their optimization campaign.

scholarly journals Identification of a juvenile-hormone signaling inhibitor via high-throughput screening of a chemical library

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Takumi Kayukawa ◽  
Kenjiro Furuta ◽  
Keisuke Nagamine ◽  
Tetsuro Shinoda ◽  
Kiyoaki Yonesu ◽  
...  
Keyword(s):  
Juvenile Hormone ◽  
Cell Line ◽  
Signaling Pathway ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Ex Vivo ◽  
Agricultural Field ◽  
Chemical Library ◽  
Field Development

Abstract Insecticide resistance has recently become a serious problem in the agricultural field. Development of insecticides with new mechanisms of action is essential to overcome this limitation. Juvenile hormone (JH) is an insect-specific hormone that plays key roles in maintaining the larval stage of insects. Hence, JH signaling pathway is considered a suitable target in the development of novel insecticides; however, only a few JH signaling inhibitors (JHSIs) have been reported, and no practical JHSIs have been developed. Here, we established a high-throughput screening (HTS) system for exploration of novel JHSIs using a Bombyx mori cell line (BmN_JF&AR cells) and carried out a large-scale screening in this cell line using a chemical library. The four-step HTS yielded 69 compounds as candidate JHSIs. Topical application of JHSI48 to B. mori larvae caused precocious metamorphosis. In ex vivo culture of the epidermis, JHSI48 suppressed the expression of the Krüppel homolog 1 gene, which is directly activated by JH-liganded receptor. Moreover, JHSI48 caused a parallel rightward shift in the JH response curve, suggesting that JHSI48 possesses a competitive antagonist-like activity. Thus, large-scale HTS using chemical libraries may have applications in development of future insecticides targeting the JH signaling pathway.

scholarly journals Cytotoxic Profiling of Annotated and Diverse Chemical Libraries Using Quantitative High-Throughput Screening

2019 ◽  
Vol 25 (1) ◽  
pp. 9-20 ◽  
Author(s):  
Olivia W. Lee ◽  
Shelley Austin ◽  
Madison Gamma ◽  
Dorian M. Cheff ◽  
Tobie D. Lee ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
High Throughput ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Large Scale ◽  
Early Stage ◽  
Cancer Cell Line ◽  
Hek 293 ◽  
Cytotoxic Compounds

Cell-based phenotypic screening is a commonly used approach to discover biological pathways, novel drug targets, chemical probes, and high-quality hit-to-lead molecules. Many hits identified from high-throughput screening campaigns are ruled out through a series of follow-up potency, selectivity/specificity, and cytotoxicity assays. Prioritization of molecules with little or no cytotoxicity for downstream evaluation can influence the future direction of projects, so cytotoxicity profiling of screening libraries at an early stage is essential for increasing the likelihood of candidate success. In this study, we assessed the cell-based cytotoxicity of nearly 10,000 compounds in the National Institutes of Health, National Center for Advancing Translational Sciences annotated libraries and more than 100,000 compounds in a diversity library against four normal cell lines (HEK 293, NIH 3T3, CRL-7250, and HaCat) and one cancer cell line (KB 3-1, a HeLa subline). This large-scale library profiling was analyzed for overall screening outcomes, hit rates, pan-activity, and selectivity. For the annotated library, we also examined the primary targets and mechanistic pathways regularly associated with cell death. To our knowledge, this is the first study to use high-throughput screening to profile a large screening collection (>100,000 compounds) for cytotoxicity in both normal and cancer cell lines. The results generated here constitute a valuable resource for the scientific community and provide insight into the extent of cytotoxic compounds in screening libraries, allowing for the identification and avoidance of compounds with cytotoxicity during high-throughput screening campaigns.

scholarly journals High Throughput Phenotypic Screening of The Human Spermatozoon

Reproduction ◽  
2021 ◽  
Author(s):  
Zoe Claire Johnston ◽  
Franz S Gruber ◽  
Sean Brown ◽  
Neil R Norcross ◽  
Jason R Swedlow ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Hormonal Contraceptives ◽  
Diagnostic Tools ◽  
Sperm Function ◽  
Phenotypic Screening ◽  
Environmental Chemical ◽  
Potential Applications

Despite recent advances in male reproductive health research, there remain many elements of male (in)fertility where our understanding is incomplete. Consequently, diagnostic tools and treatments for men with sperm dysfunction, other than medically assisted reproduction, are limited. On the other hand, the gaps in our knowledge of the mechanisms which underpin sperm function have hampered the development of male non-hormonal contraceptives. The study of mature spermatozoa is inherently difficult. They are a unique and highly specialised cell type which does not actively transcribe or translate proteins and cannot be cultured for long periods of time or matured in vitro. One, large scale, approach to both increasing understanding of sperm function, and the discovery and development of compounds that can modulate sperm function, is to directly observe responses to compounds with phenotypic screening techniques. These target agnostic approaches can be developed into high-throughput screening platforms with the potential to drastically increase advances in the field. Here we discuss the rationale and development of high-throughput phenotypic screening platforms for mature human spermatozoa, and the multiple potential applications these present, as well as the current limitations and leaps in our understanding and capabilities needed to overcome them. Further development and use of these technologies could lead to the identification of compounds which positively or negatively affect sperm cell motility or function, or novel platforms for toxicology or environmental chemical testing among other applications. Ultimately, each of these potential applications is also likely to increase understanding within the field of sperm biology.

scholarly journals Repurposing a Histamine Detection Platform for High-Throughput Screening of Histidine Decarboxylase

2018 ◽  
Vol 23 (9) ◽  
pp. 974-981
Author(s):  
Yu-Chi Juang ◽  
Xavier Fradera ◽  
Yongxin Han ◽  
Anthony William Partridge
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Histidine Decarboxylase ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Gastric Ulcers ◽  
Statistical Parameters ◽  
Time Resolved ◽  
Neurological Response

Histidine decarboxylase (HDC) is the primary enzyme that catalyzes the conversion of histidine to histamine. HDC contributes to many physiological responses as histamine plays important roles in allergic reaction, neurological response, gastric acid secretion, and cell proliferation and differentiation. Small-molecule modulation of HDC represents a potential therapeutic strategy for a range of histamine-associated diseases, including inflammatory disease, neurological disorders, gastric ulcers, and select cancers. High-throughput screening (HTS) methods for measuring HDC activity are currently limited. Here, we report the development of a time-resolved fluorescence resonance energy transfer (TR-FRET) assay for monitoring HDC activity. The assay is based on competition between HDC-generated histamine and fluorophore-labeled histamine for binding to a Europium cryptate (EuK)-labeled anti-histamine antibody. We demonstrated that the assay is highly sensitive and simple to develop. Assay validation experiments were performed using low-volume 384-well plates and resulted in good statistical parameters. A pilot HTS screen gave a Z′ score > 0.5 and a hit rate of 1.1%, and led to the identification of a validated hit series. Overall, the presented assay should facilitate the discovery of therapeutic HDC inhibitors by acting as a novel tool suitable for large-scale HTS and subsequent interrogation of compound structure–activity relationships.

scholarly journals Large-scale, high-throughput screening for coagulation and hematologic phenotypes in mice*

2002 ◽  
Vol 11 (3) ◽  
pp. 185-193 ◽  
Author(s):  
Luanne L. Peters ◽  
Eleanor M. Cheever ◽  
Heather R. Ellis ◽  
Phyllis A. Magnani ◽  
Karen L. Svenson ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Inbred Mouse ◽  
Inbred Strains ◽  
Sample Volume ◽  
Small Sample ◽  
Mouse Strains ◽  
Phenotypic Data ◽  
Multiple Tests

The Mouse Phenome Project is an international effort to systematically gather phenotypic data for a defined set of inbred mouse strains. For such large-scale projects the development of high-throughput screening protocols that allow multiple tests to be performed on a single mouse is essential. Here we report hematologic and coagulation data for more than 30 inbred strains. Complete blood counts were performed using an Advia 120 analyzer. For coagulation testing, we successfully adapted the Dade Behring BCS automated coagulation analyzer for use in mice by lowering sample and reagent volume requirements. Seven automated assay procedures were developed. Small sample volume requirements make it possible to perform multiple tests on a single animal without euthanasia, while reductions in reagent volume requirements reduce costs. The data show that considerable variation in many basic hematological and coagulation parameters exists among the inbred strains. These data, freely available on the World Wide Web, allow investigators to knowledgeably select the most appropriate strain(s) to meet their individual study designs and goals.

scholarly journals ZF-AutoML: An Easy Machine-Learning-Based Method to Detect Anomalies in Fluorescent-Labelled Zebrafish

Inventions ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 72
Author(s):  
Ryota Sawaki ◽  
Daisuke Sato ◽  
Hiroko Nakayama ◽  
Yuki Nakagawa ◽  
Yasuhito Shimada
Keyword(s):  
Machine Learning ◽  
Image Analysis ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Fluorescent Protein ◽  
Learning Program ◽  
High Throughput Analysis ◽  
Easy Method ◽  
High Fecundity

Background: Zebrafish are efficient animal models for conducting whole organism drug testing and toxicological evaluation of chemicals. They are frequently used for high-throughput screening owing to their high fecundity. Peripheral experimental equipment and analytical software are required for zebrafish screening, which need to be further developed. Machine learning has emerged as a powerful tool for large-scale image analysis and has been applied in zebrafish research as well. However, its use by individual researchers is restricted due to the cost and the procedure of machine learning for specific research purposes. Methods: We developed a simple and easy method for zebrafish image analysis, particularly fluorescent labelled ones, using the free machine learning program Google AutoML. We performed machine learning using vascular- and macrophage-Enhanced Green Fluorescent Protein (EGFP) fishes under normal and abnormal conditions (treated with anti-angiogenesis drugs or by wounding the caudal fin). Then, we tested the system using a new set of zebrafish images. Results: While machine learning can detect abnormalities in the fish in both strains with more than 95% accuracy, the learning procedure needs image pre-processing for the images of the macrophage-EGFP fishes. In addition, we developed a batch uploading software, ZF-ImageR, for Windows (.exe) and MacOS (.app) to enable high-throughput analysis using AutoML. Conclusions: We established a protocol to utilize conventional machine learning platforms for analyzing zebrafish phenotypes, which enables fluorescence-based, phenotype-driven zebrafish screening.

scholarly journals Hypothesis Testing in High-Throughput Screening for Drug Discovery

2012 ◽  
Vol 17 (4) ◽  
pp. 519-529 ◽  
Author(s):  
Michael Prummer
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Single Point ◽  
Error Rates ◽  
P Value ◽  
Distribution Analysis ◽  
Use Of Resources ◽  
Compound Screening

Following the success of small-molecule high-throughput screening (HTS) in drug discovery, other large-scale screening techniques are currently revolutionizing the biological sciences. Powerful new statistical tools have been developed to analyze the vast amounts of data in DNA chip studies, but have not yet found their way into compound screening. In HTS, characterization of single-point hit lists is often done only in retrospect after the results of confirmation experiments are available. However, for prioritization, for optimal use of resources, for quality control, and for comparison of screens it would be extremely valuable to predict the rates of false positives and false negatives directly from the primary screening results. Making full use of the available information about compounds and controls contained in HTS results and replicated pilot runs, the Z score and from it the p value can be estimated for each measurement. Based on this consideration, we have applied the concept of p-value distribution analysis (PVDA), which was originally developed for gene expression studies, to HTS data. PVDA allowed prediction of all relevant error rates as well as the rate of true inactives, and excellent agreement with confirmation experiments was found.

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