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Life
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Analysis of Amplification Curve Data
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Analysis of Amplification Curve Data

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Biochemistry, Biophysics and Computational Biology".

Deadline for manuscript submissions: closed (17 November 2021) | Viewed by 32366

Special Issue Editors

Dr. Stefan Rödiger

E-Mail Website
Guest Editor
Faculty of Health Sciences, Brandenburg University of Technology Cottbus-Senftenberg, 03046 Cottbus, Germany
Interests: statistical bioinformatics; functional bioanalytics; precision medicine; pharmacology
Dr. Andrej-Nikolai Spiess

E-Mail Website
Guest Editor
Center for Internal Medicine, The University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
Interests: statistics; bioinformatics; molecular biology; male reproduction
Dr. Michał Burdukiewicz

E-Mail Website
Guest Editor
1. Institute of Biotechnology and Biomedicine, Autonomous University of Barcelona, Campus Universitat Autònoma de Barcelona Plaça Cívica Bellaterra, s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
2. Clinical Research Centre, Medical University of Białystok, Kilińskiego 1, 15-369 Białystok, Poland
Interests: bioinformatics; functional analysis; structural proteomics; amyloidogenicity; antimicrobial peptides
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since the advent of PCR, amplification curve data has become common not only in molecular laboratories, but also in diagnostics and forensics. Although the principles of nucleic acid quantification appear to be simple, the data analysis proves to be challenging. Despite almost thirty years of development of methods for nucleic acid quantification, there is still a need for more precise and reproducible solutions. Another issue is the variability of the implementations of quantification algorithms which are built using different assumptions depending on the software. This includes methods for the analysis of quantitative PCRs, digital PCRs, and melting curve analyses. To overcome obstacles from the process of data generation (preparing and processing the sample material, reporting the experimental conditions), the scientific community focused on developing data analysis methods and standards (such as MIQE and digital MIQE guidelines).

This Special Issue will collect high-quality research for the analysis of qPCR amplification curve data. We welcome submissions that address this problem in vitro, by introducing new experimental methods, but also in silico. We especially encourage submissions of software/modules/packages devoted to the analysis of amplification curves. The submitted manuscripts do not have to be strictly mathematical, and we are very open towards more empirical experiences. We also appreciate studies describing the limitations of already implemented specific methods.

Dr. Stefan Rödiger
Dr. Andrej-Nikolai Spiess
Dr. Michał Burdukiewicz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Life is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • qPCR
  • dPCR
  • Isothermal amplification
  • Data analysis
  • Gene expression
  • High-throughput qPCR
  • Melting curve analysis

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Published Papers (5 papers)

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Research

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14 pages, 2521 KiB  
Article
Reliable and Scalable SARS-CoV-2 qPCR Testing at a High Sample Throughput: Lessons Learned from the Belgian Initiative
by Steven Van Vooren, James Grayson, Marc Van Ranst, Elisabeth Dequeker, Lies Laenen, Reile Janssen, Laurent Gillet, Fabrice Bureau, Wouter Coppieters, Nathalie Devos, Benjamin Hengchen, Pierre Wattiau, Sibylle Méhauden, Yvan Verlinden, Kurt Van Baelen, Theresa Pattery, Jean-Pierre Valentin, Kris Janssen, Martine Geraerts, John Smeraglia, Jan Hellemans, Pieter Wytynck, Pieter Mestdagh, Nienke Besbrugge, René Höfer, Friedel Nollet, Jo Vandesompele, Pieter De Smet, John Lebon, Emmanuel Vandewynckele, Steven Verstrepen, Wouter Uten, Arnaud Capron, Hugues Malonne, Jeroen Poels and Emmanuel Andréadd Show full author list remove Hide full author list
Life 2022, 12(2), 159; https://doi.org/10.3390/life12020159 - 21 Jan 2022
Cited by 4 | Viewed by 4532
Abstract
We present our approach to rapidly establishing a standardized, multi-site, nation-wide COVID-19 screening program in Belgium. Under auspices of a federal government Task Force responsible for upscaling the country’s testing capacity, we were able to set up a national testing initiative with readily [...] Read more.
We present our approach to rapidly establishing a standardized, multi-site, nation-wide COVID-19 screening program in Belgium. Under auspices of a federal government Task Force responsible for upscaling the country’s testing capacity, we were able to set up a national testing initiative with readily available resources, putting in place a robust, validated, high-throughput, and decentralized qPCR molecular testing platform with embedded proficiency testing. We demonstrate how during an acute scarcity of equipment, kits, reagents, personnel, protective equipment, and sterile plastic supplies, we introduced an approach to rapidly build a reliable, validated, high-volume, high-confidence workflow based on heterogeneous instrumentation and diverse assays, assay components, and protocols. The workflow was set up with continuous quality control monitoring, tied together through a clinical-grade information management platform for automated data analysis, real-time result reporting across different participating sites, qc monitoring, and making result data available to the requesting physician and the patient. In this overview, we address challenges in optimizing high-throughput cross-laboratory workflows with minimal manual intervention through software, instrument and assay validation and standardization, and a process for harmonized result reporting and nation-level infection statistics monitoring across the disparate testing methodologies and workflows, necessitated by a rapid scale-up as a response to the pandemic. Full article
(This article belongs to the Special Issue Analysis of Amplification Curve Data)
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15 pages, 1046 KiB  
Article
LoopTag FRET Probe System for Multiplex qPCR Detection of Borrelia Species
by Henning Hanschmann, Stefan Rödiger, Toni Kramer, Katrin Hanschmann, Michael Steidle, Volker Fingerle, Carsten Schmidt, Werner Lehmann and Peter Schierack
Life 2021, 11(11), 1163; https://doi.org/10.3390/life11111163 - 31 Oct 2021
Cited by 2 | Viewed by 2206
Abstract
Background: Laboratory diagnosis of Lyme borreliosis refers to some methods with known limitations. Molecular diagnostics using specific nucleic acid probes may overcome some of these limitations. Methods: We describe the novel reporter fluorescence real-time polymerase chain reaction (PCR) probe system LoopTag for detection [...] Read more.
Background: Laboratory diagnosis of Lyme borreliosis refers to some methods with known limitations. Molecular diagnostics using specific nucleic acid probes may overcome some of these limitations. Methods: We describe the novel reporter fluorescence real-time polymerase chain reaction (PCR) probe system LoopTag for detection of Borrelia species. Advantages of the LoopTag system include having cheap conventional fluorescence dyes, easy primer design, no restrictions for PCR product lengths, robustness, high sequence specificity, applicability for multiplex real-time PCRs, melting curve analysis (single nucleotide polymorphism analysis) over a large temperature range, high sensitivity, and easy adaptation of conventional PCRs. Results: Using the LoopTag probe system we were able to detect all nine tested European species belonging to the Borrelia burgdorferi (sensu lato) complex and differentiated them from relapsing fever Borrelia species. As few as 10 copies of Borrelia in one PCR reaction were detectable. Conclusion: We established a novel multiplex probe real-time PCR system, designated LoopTag, that is simple, robust, and incorporates melting curve analysis for the detection and in the differentiation of European species belonging to the Borrelia burgdorferi s.l. complex. Full article
(This article belongs to the Special Issue Analysis of Amplification Curve Data)
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18 pages, 2324 KiB  
Article
Estimating Real-Time qPCR Amplification Efficiency from Single-Reaction Data
by Joel Tellinghuisen
Life 2021, 11(7), 693; https://doi.org/10.3390/life11070693 - 14 Jul 2021
Cited by 4 | Viewed by 2435
Abstract
Methods for estimating the qPCR amplification efficiency E from data for single reactions are tested on six multireplicate datasets, with emphasis on their performance as a function of the range of cycles n1–n2 included in the analysis. The two-parameter [...] Read more.
Methods for estimating the qPCR amplification efficiency E from data for single reactions are tested on six multireplicate datasets, with emphasis on their performance as a function of the range of cycles n1–n2 included in the analysis. The two-parameter exponential growth (EG) model that has been relied upon almost exclusively does not allow for the decline of E(n) with increasing cycle number n through the growth region and accordingly gives low-biased estimates. Further, the standard procedure of “baselining”—separately estimating and subtracting a baseline before analysis—leads to reduced precision. The three-parameter logistic model (LRE) does allow for such decline and includes a parameter E0 that represents E through the baseline region. Several four-parameter extensions of this model that accommodate some asymmetry in the growth profiles but still retain the significance of E0 are tested against the LRE and EG models. The recursion method of Carr and Moore also describes a declining E(n) but tacitly assumes E0 = 2 in the baseline region. Two modifications that permit varying E0 are tested, as well as a recursion method that directly fits E(n) to a sigmoidal function. All but the last of these can give E0 estimates that agree fairly well with calibration-based estimates but perform best when the calculations are extended to only about one cycle below the first-derivative maximum (FDM). The LRE model performs as well as any of the four-parameter forms and is easier to use. Its proper implementation requires fitting to it plus a suitable baseline function, which typically requires four–six adjustable parameters in a nonlinear least-squares fit. Full article
(This article belongs to the Special Issue Analysis of Amplification Curve Data)
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Review

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19 pages, 373 KiB  
Review
Obtaining Reliable RT-qPCR Results in Molecular Diagnostics—MIQE Goals and Pitfalls for Transcriptional Biomarker Discovery
by Christian Grätz, Maria L. U. Bui, Granit Thaqi, Benedikt Kirchner, Robert P. Loewe and Michael W. Pfaffl
Life 2022, 12(3), 386; https://doi.org/10.3390/life12030386 - 7 Mar 2022
Cited by 20 | Viewed by 6363
Abstract
In this review, we discuss the development pipeline for transcriptional biomarkers in molecular diagnostics and stress the importance of a reliable gene transcript quantification strategy. Hence, a further focus is put on the MIQE guidelines and how to adapt them for biomarker discovery, [...] Read more.
In this review, we discuss the development pipeline for transcriptional biomarkers in molecular diagnostics and stress the importance of a reliable gene transcript quantification strategy. Hence, a further focus is put on the MIQE guidelines and how to adapt them for biomarker discovery, from signature validation up to routine diagnostic applications. First, the advantages and pitfalls of the holistic RNA sequencing for biomarker development will be described to establish a candidate biomarker signature. Sequentially, the RT-qPCR confirmation process will be discussed to validate the discovered biomarker signature. Examples for the successful application of RT-qPCR as a fast and reproducible quantification method in routinemolecular diagnostics are provided. Based on the MIQE guidelines, the importance of “key steps” in RT-qPCR is accurately described, e.g., reverse transcription, proper reference gene selection and, finally, the application of automated RT-qPCR data analysis software. In conclusion, RT-qPCR proves to be a valuable tool in the establishment of a disease-specific transcriptional biomarker signature and will have a great future in molecular diagnostics or personalized medicine. Full article
(This article belongs to the Special Issue Analysis of Amplification Curve Data)
22 pages, 3270 KiB  
Review
Use and Misuse of Cq in qPCR Data Analysis and Reporting
by Adrián Ruiz-Villalba, Jan M. Ruijter and Maurice J. B. van den Hoff
Life 2021, 11(6), 496; https://doi.org/10.3390/life11060496 - 29 May 2021
Cited by 45 | Viewed by 15388
Abstract
In the analysis of quantitative PCR (qPCR) data, the quantification cycle (Cq) indicates the position of the amplification curve with respect to the cycle axis. Because Cq is directly related to the starting concentration of the target, and the difference [...] Read more.
In the analysis of quantitative PCR (qPCR) data, the quantification cycle (Cq) indicates the position of the amplification curve with respect to the cycle axis. Because Cq is directly related to the starting concentration of the target, and the difference in Cq values is related to the starting concentration ratio, the only results of qPCR analysis reported are often Cq, ΔCq or ΔΔCq values. However, reporting of Cq values ignores the fact that Cq values may differ between runs and machines, and, therefore, cannot be compared between laboratories. Moreover, Cq values are highly dependent on the PCR efficiency, which differs between assays and may differ between samples. Interpreting reported Cq values, assuming a 100% efficient PCR, may lead to assumed gene expression ratios that are 100-fold off. This review describes how differences in quantification threshold setting, PCR efficiency, starting material, PCR artefacts, pipetting errors and sampling variation are at the origin of differences and variability in Cq values and discusses the limits to the interpretation of observed Cq values. These issues can be avoided by calculating efficiency-corrected starting concentrations per reaction. The reporting of gene expression ratios and fold difference between treatments can then easily be based on these starting concentrations. Full article
(This article belongs to the Special Issue Analysis of Amplification Curve Data)
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