scholarly journals Sequencing the pandemic: rapid and high-throughput processing and analysis of COVID-19 clinical samples for 21st century public health

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 48
Author(s):  
Megan L Folkerts ◽  
Darrin Lemmer ◽  
Ashlyn Pfeiffer ◽  
Danielle Vasquez ◽  
Chris French ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Cost Effective ◽  
Turnaround Time ◽  
Clinical Samples ◽  
Disease Epidemiology ◽  
Genomic Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Retrospective Data Analysis ◽  
Retrospective Monitoring

Genomic epidemiology has proven successful for real-time and retrospective monitoring of small and large-scale outbreaks. Here, we report two genomic sequencing and analysis strategies for rapid-turnaround or high-throughput processing of metagenomic samples. The rapid-turnaround method was designed to provide a quick phylogenetic snapshot of samples at the heart of active outbreaks, and has a total turnaround time of <48 hours from raw sample to analyzed data. The high-throughput method was designed for semi-retrospective data analysis, and is both cost effective and highly scalable. Though these methods were developed and utilized for the SARS-CoV-2 pandemic response in Arizona, U.S, and we envision their use for infectious disease epidemiology in the 21st Century.

scholarly journals Development of High-Throughput Multiplex Serology to Detect Serum Antibodies against Coxiella burnetii

2021 ◽  
Vol 9 (11) ◽  
pp. 2373
Author(s):  
Rima Jeske ◽  
Larissa Dangel ◽  
Leander Sauerbrey ◽  
Dimitrios Frangoulidis ◽  
Lauren R. Teras ◽  
...  
Keyword(s):  
Coxiella Burnetii ◽  
High Throughput ◽  
Large Scale ◽  
Q Fever ◽  
Reference Group ◽  
Clinical Manifestations ◽  
Cost Effective ◽  
Population Monitoring ◽  
Increased Risk ◽  
Multiplex Serology

The causative agent of Q fever, the bacterium Coxiella burnetii (C. burnetii), has gained increasing interest due to outbreak events and reports about it being a potential risk factor for the development of lymphomas. In order to conduct large-scale studies for population monitoring and to investigate possible associations more closely, accurate and cost-effective high-throughput assays are highly desired. To address this need, nine C. burnetii proteins were expressed as recombinant antigens for multiplex serology. This technique enables the quantitative high-throughput detection of antibodies to multiple antigens simultaneously in a single reaction. Based on a reference group of 76 seropositive and 91 seronegative sera, three antigens were able to detect C. burnetii infections. Com1, GroEL, and DnaK achieved specificities of 93%, 69%, and 77% and sensitivities of 64%, 72%, and 47%, respectively. Double positivity to Com1 and GroEL led to a combined specificity of 90% and a sensitivity of 71%. In a subgroup of seropositives with an increased risk for chronic Q fever, the double positivity to these markers reached a specificity of 90% and a sensitivity of 86%. Multiplex serology enables the detection of antibodies against C. burnetii and appears well-suited to investigate associations between C. burnetii infections and the clinical manifestations in large-scale studies.

scholarly journals A Short-Read Multiplex Sequencing Method for Reliable, Cost-Effective and High-Throughput Genotyping in Large-Scale Studies

2013 ◽  
Vol 35 (2) ◽  
pp. 270-270 ◽  
Author(s):  
Hongzhi Cao ◽  
Yu Wang ◽  
Wei Zhang ◽  
Xianghua Chai ◽  
Xiandong Zhang ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Cost Effective ◽  
Short Read ◽  
Sequencing Method ◽  
Multiplex Sequencing

Cell-based models for mycotoxin screening and toxicity evaluation: an update

2014 ◽  
Vol 7 (2) ◽  
pp. 153-166 ◽  
Author(s):  
F. Cheli ◽  
E. Fusi ◽  
A. Baldi
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Mycotoxin Research ◽  
Cost Effective ◽  
Screening Tests ◽  
Test Model ◽  
Related Factors ◽  
Technical Problems ◽  
Third Dimension

This review presents the applications of cell-based models in mycotoxin research, with a focus on models for mycotoxin screening and cytotoxicity evaluation. Various cell-based models, cell and cell culture condition related factors, toxicity endpoints and culture systems as well as predictive value of cell-based bioassays are reviewed. Advantages, drawbacks and technical problems regarding set up and validation of consistent, robust, reproducible and high-throughput cell-based models are discussed. Various cell-based models have been developed and used as screening tests for mycotoxins but the data obtained are difficult to compare. However, the results highlight the potential of cell-based models as promising in vitro platforms for the initial screening and cytotoxicity evaluation of mycotoxins and as a significant analytical approach in mycotoxin research before any animal or human clinical studies. To develop cell-based models as powerful high-throughput laboratory platforms for the analysis of large numbers of samples, there are mainly two fundamental requirements that should be met, i.e. the availability of easy-to-use and, if possible, automated cell platforms and the possibility to obtain reproducible results that are comparable between laboratories. The transition from a research model to a test model still needs optimisation, standardisation, and validation of analytical protocols. The validation of a cell-based bioassay is a complex process, as several critical points, such as the choice of the cellular model, the assay procedures, and the appropriate use and interpretation of the results, must be strictly defined to ensure more consistency in the results. The development of cell-based models exploring the third dimension together with automation and miniaturisation will bring cellular platforms to a level appropriate for cost-effective and large-scale analysis in the field of mycotoxin research.

scholarly journals SKA: Split Kmer Analysis Toolkit for Bacterial Genomic Epidemiology

2018 ◽  
Author(s):  
S. R. Harris
Keyword(s):  
High Performance ◽  
Sequence Data ◽  
Real Life ◽  
Single Linkage ◽  
Disease Epidemiology ◽  
Genomic Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Genome Data ◽  
Real Life Data ◽  
Genome Assemblies

AbstractGenome sequencing is revolutionising infectious disease epidemiology, providing a huge step forward in sensitivity and specificity over more traditional molecular typing techniques. However, the complexity of genome data often means that its analysis and interpretation requires high-performance compute infrastructure and dedicated bioinformatics support. Furthermore, current methods have limitations that can differ between analyses and are often opaque to the user, and their reliance on multiple external dependencies makes reproducibility difficult. Here I introduce SKA, a toolkit for analysis of genome sequence data from closely-related, small, haploid genomes. SKA uses split kmers to rapidly identify variation between genome sequences, making it possible to analyse hundreds of genomes on a standard home computer. Tests on publicly available simulated and real-life data show that SKA is both faster and more efficient than the gold standard methods used today while retaining similar levels of accuracy for epidemiological purposes. SKA can take raw read data or genome assemblies as input and calculate pairwise distances, create single linkage clusters and align genomes to a reference genome or using a reference-free approach. SKA requires few decisions to be made by the user, which, along with its computational efficiency, allows genome analysis to become accessible to those with only basic bioinformatics training. The limitations of SKA are also far more transparent than for current approaches, and future improvements to mitigate these limitations are possible. Overall, SKA is a powerful addition to the armoury of the genomic epidemiologist. SKA source code is available from Github (https://github.com/simonrharris/SKA).

scholarly journals Detecting SARS-CoV-2 variants with SNP genotyping

2020 ◽  
Author(s):  
Helen Harper ◽  
Amanda J. Burridge ◽  
Mark Winfield ◽  
Adam Finn ◽  
Andrew D. Davidson ◽  
...  
Keyword(s):  
High Throughput ◽  
Low Cost ◽  
Cost Effective ◽  
Snp Genotyping ◽  
Clinical Samples ◽  
Marker Panel ◽  
Qrt Pcr ◽  
Crucial Information ◽  
The Uk ◽  
Genotyping Panel

AbstractTracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020- and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 76% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with our marker panel at a cost of < £1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation.

scholarly journals Detecting SARS-CoV-2 variants with SNP genotyping

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0243185 ◽  
Author(s):  
Helen Harper ◽  
Amanda Burridge ◽  
Mark Winfield ◽  
Adam Finn ◽  
Andrew Davidson ◽  
...  
Keyword(s):  
High Throughput ◽  
Low Cost ◽  
Cost Effective ◽  
Snp Genotyping ◽  
Clinical Samples ◽  
Marker Panel ◽  
Qrt Pcr ◽  
Crucial Information ◽  
The Uk ◽  
Genotyping Panel

Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system, we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020 and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 61.9% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with a marker panel at a cost of < £1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation.

scholarly journals Rapid Extraction from and Direct Identification in Clinical Samples of Methicillin-Resistant Staphylococci Using the PCR

2000 ◽  
Vol 38 (9) ◽  
pp. 3407-3412 ◽  
Author(s):  
Richard I. Jaffe ◽  
Janae D. Lane ◽  
Stephen V. Albury ◽  
Debra M. Niemeyer
Keyword(s):  
Dna Sequences ◽  
Extraction Method ◽  
Clinical Laboratory ◽  
Methicillin Resistance ◽  
Cost Effective ◽  
Turnaround Time ◽  
Clinical Samples ◽  
Identification System ◽  
Methicillin Resistant ◽  
Primer Sets

Methicillin-resistant staphylococci (MRS) are one of the most common causes of nosocomial infections and bacteremia. Standard bacterial identification and susceptibility testing frequently require as long as 72 h to report results, and there may be difficulty in rapidly and accurately identifying methicillin resistance. The use of the PCR is a rapid and simple process for the amplification of target DNA sequences, which can be used to identify and test bacteria for antimicrobial resistance. However, many sample preparation methods are unsuitable for PCR utilization in the clinical laboratory because they either are not cost-effective, take too long to perform, or do not provide a satisfactory DNA template for PCR. Our goal was to provide same-day results to facilitate rapid diagnosis and therapy. In this report, we describe a rapid method for extraction of bacterial DNA directly from blood culture bottles that gave quality DNA for PCR in as little as 20 min. We compared this extraction method to the standard QIAGEN method for turnaround time (TAT), cost, purity, and use of template in PCR. Specific identification of MRS was determined using intragenic primer sets for bacterial and Staphylococcus 16S rRNA and mecAgene sequences. The PCR primer sets were validated with 416 isolates of staphylococci, including methicillin-resistant Staphylococcus aureus (n = 106), methicillin-sensitive S. aureus (n = 134), and coagulase-negativeStaphylococcus (n = 176). The total supply cost of our extraction method and PCR was $2.15 per sample with a result TAT of less than 4 h. The methods described herein represent a rapid and accurate DNA extraction and PCR-based identification system, which makes the system an ideal candidate for use under austere field conditions and one that may have utility in the clinical laboratory.

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 A Robust and Cost-Effective Luminescent-Based High-Throughput Assay for Fructose-1,6-Bisphosphate Aldolase A

2020 ◽  
Vol 25 (9) ◽  
pp. 1038-1046
Author(s):  
Eun Jeong Cho ◽  
Ashwini K. Devkota ◽  
Gabriel Stancu ◽  
Ramakrishna Edupunganti ◽  
Ginamarie Debevec ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Cancer Survival ◽  
Hypoxia Inducible Factor ◽  
Cost Effective ◽  
High Rate ◽  
Statistical Parameters ◽  
Fructose 1,6 Bisphosphate ◽  
Aldolase A

Hypoxic solid tumors induce the stabilization of hypoxia-inducible factor 1 alpha (HIF1α), which stimulates the expression of many glycolytic enzymes and hypoxia-responsive genes. A high rate of glycolysis supports the energetic and material needs for tumors to grow. Fructose-1,6-bisphosphate aldolase A (ALDOA) is an enzyme in the glycolytic pathway that promotes the expression of HIF1α. Therefore, inhibition of ALDOA activity represents a potential therapeutic approach for a range of cancers by blocking two critical cancer survival mechanisms. Here, we present a luminescence-based strategy to determine ALDOA activity. The assay platform was developed by integrating a previously established ALDOA activity assay with a commercial NAD/NADH detection kit, resulting in a significant (>12-fold) improvement in signal/background (S/B) compared with previous assay platforms. A screening campaign using a mixture-based compound library exhibited excellent statistical parameters of Z′ (>0.8) and S/B (~20), confirming its robustness and readiness for high-throughput screening (HTS) application. This assay platform provides a cost-effective method for identifying ALDOA inhibitors using a large-scale HTS campaign.

scholarly journals Cost-effective epigenetic age profiling in shallow methylation sequencing data

2021 ◽  
Author(s):  
Alexandre Trapp ◽  
Vadim N Gladyshev
Keyword(s):  
High Throughput ◽  
Aging Process ◽  
Large Scale ◽  
Cost Effective ◽  
Cellular Reprogramming ◽  
Biological Aging ◽  
Sequencing Data ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Fold Reduction

There is a critical need for robust, high-throughput assays of biological aging trajectories. Among various approaches, epigenetic aging clocks emerged as reliable molecular trackers of the aging process. However, current methods for epigenetic age profiling are inherently costly and lack throughput. Here, we leverage the scAge framework for accurate prediction of biological age from very few bisulfite sequencing reads in bulk samples, thereby enabling drastic (100-1,000-fold) reduction in sequencing costs per sample. Our approach permits age assessment based on distinct assortments of CpG sites in different samples, without the need for targeted site enrichment or specialized reagents. We demonstrate the efficacy of this method to quantify the age of mouse blood samples across independent cohorts, identify the effect of calorie restriction as an attenuator of the aging process, and discern rejuvenation upon cellular reprogramming. We propose that this framework may be used for epigenetic age prediction in extremely high-throughput applications, enabling robust, large-scale and inexpensive interventions testing and age profiling.

Sign in / Sign up

Export Citation Format

Share Document