Selecting the right detection method for your sample

Fast, accurate, and scalable methods that utilize real-time quantitative PCR (RT-qPCR) and PCR genotyping to detect viral and microbial pathogens are essential for preventing and controlling infectious disease outbreaks. The versatility of these PCR technologies enables the development of new methods that are tailored to specific types of organisms and sample processing requirements.

Specialized RT-qPCR- and PCR-based detection methods have been developed for a wide variety of pathogens, including respiratory viruses such as SARS-CoV-2, antibiotic-resistant and disease-causing bacteria present in water and soil samples, and plant pathogens that can decimate crops. Optimized protocols are available for processing specific sample types, including clinical research samples (such as saliva, swab washes, and stool suspensions) as well as environmental and agricultural samples, and for direct detection from a variety of crude samples. Small-scale detection methods are suitable for many purposes, while automated, high-throughput detection methods are ideal for large-scale studies and can play an important role in controlling disease outbreaks by increasing the availability of fast and accurate screening.

Harnessing the power and versatility of RT-qPCR-based detection

RT-qPCR-based methods provide the basis for efficient, specific, and sensitive detection of a variety of viral and bacterial pathogens, including SARS-CoV-2. One-step RT-qPCR utilizes a quick and simple protocol that allows the reverse transcription and qPCR reactions to be performed in the same tube, reducing the risk of contamination and providing sensitive, reliable results.  Our one-step PrimeScript RT-qPCR technology was used to develop the first screening test for SARS-CoV-2 (Zhu et al. 2020) and our RT-qPCR kits include the One Step PrimeScript III RT-qPCR Mix, the most sensitive one-step RT-qPCR master mix available, which is used worldwide for SARS-CoV-2 detection down to five viral copies.

The ease and efficiency of RT-qPCR-based detection can be limited by the need to purify viral and bacterial RNA and DNA prior to performing a detection assay. However, this time-consuming nucleic acid purification step can be eliminated by performing RT-qPCR directly on crude samples using a specialized reaction mix that is resistant to PCR inhibitors such as heparin (blood) and humic acid (soil). Our PrimeDirect Probe RT-qPCR Mix, which can be used to perform direct RT-qPCR on viruses, bacteria, and other crude biological samples (Figure 1), is able to detect as few as 20 copies of H1N1 in nasal cavity swab samples and saliva samples and 2 copies from mouth swab samples. Our Direct One-Step RT-qPCR Mix for SARS-CoV-2 has been shown to provide reliable detection of SARS-CoV-2 directly from crude saliva samples.

Detecting pathogens using automated, high-throughput RT-qPCR

Controlling disease outbreaks depends upon the ability to detect viral and microbial pathogens from a large number of samples with precision, reproducibility, and speed. Our SmartChip Real-Time PCR System (Figure 2) is an automated, high-throughput qPCR system that minimizes false positives and negatives, accurately captures transcripts down to single-digit copy numbers, reduces hands-on time, and maximizes the number of samples processed per day. It has been used to automate SARS-CoV-2 detection, as well as screen for antibiotic-resistant bacteria from sources such as manure, sewage, soil, sediment, sludge, water, and hospital air conditioning filters.

For detailed information, watch our webinars on using the SmartChip system to detect SARS-CoV-2 and detect and quantify antibiotic resistance genes and SARS-CoV-2 in wastewater. 

Figure 2. The SmartChip Real-Time PCR System workflow. Add your samples and assays to the SmartChip MyDesign Kit and then analyze using the SmartChip Real-Time PCR System.

Screening for bacterial pathogens using PCR-based genotyping

The ability to distinguish a pathogenic strain of bacteria from other related subspecies is crucial for developing an effective screening method that can be used to determine how the bacteria is transmitted, in order to prevent or control infectious disease outbreaks. PCR-based genotyping that amplifies and detects gene variants between closely related bacterial strains can be used to accurately identify bacterial pathogens.

A fast, accurate detection assay using PCR-based genotyping was developed by Xu et al. to identify the bacteria that causes Stewart's Wilt, a serious bacterial disease that infects corn crops. Watch the video to learn how Titanium Taq DNA Polymerase was used to distinguish this pathogen from several related strains.

PCR genotyping methods were also used to screen environmental samples for a waterborne illness, leptospirosis, using multiplex PCR analysis with Takara Ex Taq HS DNA polymerase to detect bacteria using 16S rRNA targets, which they analyzed by NGS (Sato et al. 2019). A similar procedure was carried out using PrimeSTAR HS DNA Polymerase to detect 12S rRNA from vertebrate animals in the same environmental samples, in order to understand which vertebrate species are more likely to harbor Leptospira bacteria. The multiplex PCR method used in the study helped determine how Leptospira outbreaks can occur by showing how the environment can impact the development of this pathogen and revealing how it interacts with hosts/carriers.

References

• Sato, Y. et al. Environmental DNA metabarcoding to detect pathogenic Leptospira and associated organisms in leptospirosis-endemic areas of Japan. Sci. Rep. 9, 1–11 (2019). Available at: https://www.nature.com/articles/s41598-019-42978-1
• Xu, R., Chen, Q., Robleh Djama, Z. & Tambong, J. T. Miniprimer PCR assay targeting multiple genes: a new rapid and reliable tool for genotyping Pantoea stewartii subsp. stewartii. Lett. Appl. Microbiol. 50, 216–222 (2010). Available at: https://sfamjournals.onlinelibrary.wiley.com/doi/full/10.1111/j.1472-765X.2009.02780.x
• Zhu, N. et al. A novel coronavirus from patients with pneumonia in China, 2019.  Engl. J. Med. NEJMoa2001017 (2020). Available at: https://www.nejm.org/doi/full/10.1056/NEJMoa2001017