Dataset Information

Detection methods for SARS-CoV-2 in tissue.

ABSTRACT:

Background

Analyses for the presence of SARS-CoV‑2 in the tissues of COVID-19 patients is important in order to improve our understanding of the disease pathophysiology for interpretation of diagnostic histopathological findings in autopsies, biopsies, or surgical specimens and to assess the potential for occupational infectious hazard.

Material and methods

In this review we identified 136 published studies in PubMed's curated literature database LitCovid on SARS-CoV‑2 detection methods in tissues and evaluated them regarding sources of error, specificity, and sensitivity of the methods, taking into account our own experience.

Results

Currently, no sufficiently specific histomorphological alterations or diagnostic features for COVID-19 are known. Therefore, three approaches for SARS-CoV‑2 detection are used: RNA, proteins/antigens, or morphological detection by electron microscopy. In the preanalytical phase, the dominant source of error is tissue quality, especially the different intervals between sample collection and processing or fixation (and its duration) and specifically the interval between death and sample collection in autopsies. However, this information is found in less than half of the studies (e.g., in only 42% of autopsy studies). Our own experience and first studies prove the significantly higher sensitivity and specificity of RNA-based detection methods compared to antigen or protein detection by immunohistochemistry or immunofluorescence. Detection by electron microscopy is time consuming and difficult to interpret.

Conclusions

Different methods are available for the detection of SARS-CoV‑2 in tissue. Currently, RNA detection by RT-PCR is the method of choice. However, extensive validation studies and method harmonization are not available and are absolutely necessary.

SUBMITTER: von Stillfried S

PROVIDER: S-EPMC7994356 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSensitive, rapid, and accessible diagnostics continue to be critical to track the COVID-19 pandemic caused by the SARS-CoV-2 virus. RT-qPCR is the gold standard test, and comparison of methodologies and reagents, utilizing patient samples, is important to establish reliable diagnostic pipelines.MethodsHere, we assessed indirect methods that require RNA extraction with direct RT-qPCR on patient samples. Four different RNA extraction kits (Qiagen, Invitrogen, BGI and Norgen Biotek) were compared. For detection, we assessed two recently developed Taqman-based modules (BGI and Norgen Biotek), a SYBR green-based approach (NEB Luna Universal One-Step Kit) with published and newly-developed primers, and clinical results (Seegene STARMag RNA extraction system and Allplex 2019-nCoV RT-qPCR assay). We also tested and optimized direct, extraction-free detection using these RT-qPCR systems and performed a cost analysis of the different methods evaluated here.ResultsMost RNA isolation procedures performed similarly, and while all RT-qPCR modules effectively detected purified viral RNA, the BGI system provided overall superior performance (lower detection limit, lower Ct values and higher sensitivity), generating comparable results to original clinical diagnostic data, and identifying samples ranging from 65 copies to 2.1 × 105 copies of viral genome/μl. However, the BGI detection system is more expensive than other options tested here. With direct RT-qPCR, simply adding an RNase inhibitor greatly improved detection, without the need for any other treatments (e.g. lysis buffers or boiling). The best direct methods detected ~ 10 fold less virus than indirect methods, but this simplified approach reduced sample handling, as well as assay time and cost.ConclusionsWith extracted RNA, the BGI RT-qPCR detection system exhibited superior performance over the Norgen system, matching initial clinical diagnosis with the Seegene Allplex assay. The BGI system was also suitable for direct, extraction-free analysis, providing 78.4% sensitivity. The Norgen system, however, still accurately detected samples with a clinical Ct < 33 from extracted RNA, provided significant cost savings, and was superior to SYBR green assays that exhibited reduced specificity.