Effect of sample vortex mixing on severe acute respiratory syndrome coronavirus 2 nucleic acid testing: Comparative analysis of individual samples and sample pools

Abstract

Objective

This study investigated the effect of sample vortex mixing on the cycle threshold (Ct) values of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid testing and further explored the underlying reasons for this effect.

Methods

We initially examined the impact of sample vortex mixing on Ct values. Subsequently, epithelial cells within the samples were quantified and stained using an improved Neubauer hemocytometer and Wright–Giemsa stain to elucidate the causative factors of Ct value changes. Finally, we expanded our sample size to validate the effect of vortex mixing on Ct values.

Results

We observed a significant decrease in Ct values (all p < 0.001) and an increase in epithelial cell concentration (all p < 0.001) following vortex mixing compared with no vortex mixing. Specifically, the Ct values of individual samples decreased after 2 min of vortex mixing compared with 30 s of vortex mixing (p < 0.001). However, the Ct values of the sample pools increased after 2 min of vortex mixing (p < 0.05). Validation with an expanded sample yielded similar results.

Conclusions

Our findings demonstrate that vortex mixing substantially decreases sample Ct values. These results contribute to the standardization of nucleic acid testing procedures.

Introduction

The coronavirus disease 2019 (COVID-19) pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). ¹ Studies have demonstrated that respiratory epithelial cells serve as the primary host cells for SARS-CoV-2, with viral entry mediated through the ACE2 receptor.^{2 –5} SARS-CoV-2 exhibits preferential tropism toward ciliated and secretory cells within the respiratory epithelium, achieving highly efficient replication.^6,7 Thus, the detected virus originates from viral particles replicating within these infected epithelial cells. If fewer epithelial cells are collected, it is considered a substandard sample and may affect the experiment results or lead to false-negative results. ⁸ Preanalytical factors may substantially compromise the reliability of test results.^{9 –12}

Among these preanalytical variables, the step of vortex mixing of specimens (to achieve a uniform distribution of epithelial cells in the viral transport medium) is usually overlooked in routine processing. A previous study suggested that omitting the step of vortex mixing can streamline workflows without compromising sensitivity. ¹³ However, this conclusion was derived from individual samples, and the sample pools employed in large-scale screening have not yet been evaluated. Notably, it remains to be elucidated whether the impact of vortex mixing on epithelial cells in samples constitutes the primary cause of variations in cycle threshold (Ct) values in nucleic acid testing (NAT).

In clinical settings, wherein low viral loads (often approaching the detection sensitivity threshold) are observed due to sample dilution, understanding the influence of vortex mixing on samples is crucial for standardizing protocols. This study investigated how sample vortex mixing affects Ct value, informing evidence-based guidelines for NAT preprocessing.

Materials and methods

All oropharyngeal swab samples were collected from the staff of the Women’s Hospital of Zhejiang University School of Medicine, Zhejiang, China. An individual sample contained specimens from only one person (one pharyngeal swab), whereas a sample pool included specimens from 10 people (10 pharyngeal swabs). The design scheme of the whole experiment is shown in Figure 1. We took 400 μL of sample before vortex mixing the samples and 400 μL after 30 s and 2 min of vortex mixing. Each 400-μL sample was used as follows: 200 μL for nucleic acid extraction, 150 μL for cell counting, and 50 μL for Wright–Giemsa stain. Before and after vortex mixing, the samples were subjected to nucleic acid extraction and quantitative real-time reverse transcription–polymerase chain reaction (rRT–PCR) experiments in the same batch. Each experiment was monitored with one external positive quality control (QC), two external negative QCs, and one blank. In this study, Ct values refer to housekeeping, except those indicated explicitly as the Ct values of target genes. The study was approved by the Medical Ethics Committee of the Women’s Hospital of Zhejiang University School of Medicine (Approval number: IRB-20220333-R, Date of approval: 2022-11-03) and conducted according to the ethical principles outlined in the Helsinki Declaration (2024 revision). Each participant signed an informed consent form.

Figure 1.

Diagram of the entire experimental design idea. The icons in this image are from https://www.docer.com/, and we edited the color of the icons.

Reagents and instruments

Fluorescence quantitative PCR instrument (QuantStudio^TM5, Thermo Fisher Scientific, USA), vortex instrument (SI-0256, Scientific Industries, USA), semi-automatic nucleic acid extractor (MD-NAS48, Mingde, China), Nucleic Acid Extraction and Purification Kit (Mingde, China) and SARS-CoV-2 rRT–PCR reaction kit (Mingde, China) were used. According to the reagent instruction, the target genes of SARS-CoV-2 were the nucleocapsid protein (N) gene and open reading frame 1ab (ORF1ab) gene, with RNaseP (R) as the housekeeping gene. Primer sequences for the genes (ORF1ab, N, and R) were proprietary to the manufacturer and not disclosed.

Wright–Giemsa stain

First, a slide was marked, and a straight line was drawn at each end of the smear to prevent the stain from spilling during staining. Then, a 50-μL sample was obtained, and a smear was prepared on the slide, letting it dry naturally. The Wright–Giemsa staining solution was added to cover the smear and let it stain for 1 min. Subsequently, a 2–3 times higher amount of buffer was added to the staining solution and mixed well, followed by staining for 4–10 min. Finally, the slide was rinsed with flowing distilled water for 30 s, and it was allowed to dry for microscopic examination.

Cell counting

This study used an improved Neubauer hemocytometer (Shanghai Qiujing Biochemical Instrument Co., Ltd) to count epithelial cells. The improved Neubauer hemocytometer was divided into two pools, with each split equally divided into nine large squares. We counted epithelial cells in five large squares around the center. Epithelial cell concentration = (N/5) × 10⁶ cells/mL, where N is the number of epithelial cells in the surrounding and central squares. For epithelial cell counts, three independent technicians measured each sample twice, and six results were averaged to minimize intraobserver differences.

Statistical analysis

We analyzed the data using IBM SPSS (version 23.0) with a significance level of p < 0.05. The normality of continuous variables (Ct values and epithelial cell concentrations) was assessed using the Shapiro–Wilk test. For within-group comparisons (e.g. prevortex vs. postvortex in the same sample), paired Student’s t-test was used for normally distributed data, and the Wilcoxon signed-rank test was applied to non-normal data. For between-group comparisons (e.g. 30 s vs. 2 min), an independent Student’s t-test was used if both groups met normality and homogeneity of variance. The Mann–Whitney U test was used for non-normal distributions or unequal variances.

Results

Effect of sample vortex mixing on Ct values and epithelial cell concentration

Following vortex mixing, the Ct values of both individual samples and sample pools significantly decreased (all p < 0.001), whereas the number of epithelial cells significantly increased (all p < 0.001), as shown in Figures 2 and 3.

Figure 2.

Effect of sample vortex mixing on Ct values. (a, b) Individual sample; (c, d) Sample pool. (a, c) Effect of vortex mixing of samples on Ct values. (b, d) Different times of sample vortex mixing lead to changes in Ct values. ΔCt1 = Ct (No vortex) − Ct (Vortex 30 s); ΔCt2 = Ct (No vortex) − Ct (Vortex 2 min); ΔCt3 = Ct (Vortex 30 s) − Ct (Vortex 2 min). *p < 0.05; **p < 0.001; NS: not significant.

Figure 3.

Effect of sample vortex mixing on epithelial cell concentration. (a) Individual samples. (b) Sample pools and (c) the samples were vortex-mixed and then stained with Wright–Giemsa stain. *p < 0.05; **p < 0.001.

Effect of time of sample vortex mixing on Ct values and epithelial cell concentration

When vortex mixing time was extended from 30 s to 2 min, the Ct values of individual samples further decreased (p < 0.05; Figure 2(a)), whereas the Ct values of sample pools unexpectedly increased (p < 0.05; Figure 2(c)). The variation in Ct values (ΔCt2) for individual samples following 2 min of vortex mixing was more significant than the variation in Ct values (ΔCt1) following 30 s of vortex mixing (p < 0.05; Figure 2(b)). However, there was no difference in the variation of Ct values for the sample pools (p = 0.559; Figure 2(d)). Similarly, the epithelial cell concentration was significantly higher after vortex mixing the samples for 2 min (all p < 0.001) (Figure 3).

Compared with 30-s vortex mixing, 2-min vortex mixing resulted in a slight increase in epithelial cell concentration in individual samples (p < 0.05; Figure 3(a) and (c)). Conversely, sample pools exhibited a decrease in epithelial cell concentration (p < 0.05; Figure 3(b) and (c)).

Effect of sample placement for 4 h on Ct values

After storage at 4°C for 4 h, the sample pools were subjected to vortex mixing. Compared with no vortex mixing, both 30-s and 2-min vortex mixing significantly reduced Ct values (all p < 0.001; Figure 4(a)) and increased epithelial cell concentration (all p < 0.001; Figure 4(c) and (d)). However, there was no significant difference in Ct value changes between 30-s vortex mixing and 2-min vortex mixing (p = 0.557) (Figure 4(b)). At the same time, compared with 30-s vortex mixing, a decrease in epithelial cell concentration was observed in 2-min vortex mixing (p < 0.05) (Figure 4(c) and (d)).

Figure 4.

Effect of sample pool placement at 4°C for 4 h on Ct values and epithelial cell concentration. (a) Effect of vortex mixing of sample pools on Ct values. (b) Different times of sample pools vortex mixing lead to changes in Ct values. (c) Effect of vortex mixing of sample pools on epithelial cell concentration and (d) the sample pools were vortex-mixed and then stained with Wright–Giemsa stain. *p < 0.05; **p < 0.001; NS: not significant.

Expanded sample size for validation

To validate the impact of vortex mixing on Ct values, we expanded the sample size to 104 individual samples and 96 sample pools. Compared with no vortex mixing, all samples exhibited significantly lower Ct values after 30 s of vortex mixing (all p < 0.001; Figure 5(a) and (c)). Extending to 2 min further reduced Ct values (all p < 0.001; Figure. 5(a) and (c)). Furthermore, the change in Ct values (ΔCt2) after 2 min of vortex mixing was significantly larger than that after 30 s (ΔCt1) in individual samples (p < 0.001; Figure 5(b)) but not in sample pools (Figure 5(d)).

Figure 5.

Expanded sample size for validation. (a, b) Individual sample; (c, d) Sample pool. (a, c) Effect of vortex mixing of samples on Ct values. (b, d) Different times of sample vortex mixing lead to changes in Ct values. ΔCt1 = Ct (No vortex) − Ct (Vortex 30 s); ΔCt2 = Ct (No vortex) − Ct (Vortex 2 min); ΔCt3 = Ct (Vortex 30 s) − Ct (Vortex 2 min). *p < 0.05; **p < 0.001; NS: not significant.

Discussion

This study aimed to examine the impact of sample vortex mixing on the Ct values of SARS-CoV-2 NAT. We found that the Ct value decreased after vortexing the sample because more epithelial cells were available for nucleic acid extraction. These data underscore that vortex mixing is a non-negotiable preanalytical step to maximize nucleic acid yield from epithelial cells, thereby ensuring the reliability of downstream molecular analyses.

Vortex mixing is a critical yet understudied preanalytical step in NAT. Kanji et al. ¹³ reported that vortex mixing significantly reduces Ct values without compromising NAT sensitivity (supporting its omission for workflow simplification). In contrast to previous suggestions that vortex mixing may be omitted to streamline workflows, our findings demonstrate that this step is indispensable for ensuring analytical reliability. To mechanistically validate this observation, we verified this finding via epithelial cell counting and Wright–Giemsa staining (Figures 3(c) and 4(d)). We found that the decrease in Ct values was primarily attributable to the increased number of epithelial cells obtained for nucleic acid extraction after vortex mixing.

Previous studies have only focused on individual samples and have not explored the sample pools used in large-scale population screening.^13,14 During early infection stages, the low viral load in the sample pool may be further diluted below the detection limit when pooled, thereby elevating the risk of false-negative results.^15,16 Specimen pools contain multiple individual samples, making it challenging to assess the quality of each constituent specimen uniformly. Therefore, vortex mixing of the sample pool is critical because each sample has a different mass, and only vigorous vortex mixing can ensure the release of epithelial cells from all constituent samples. In this study, experimental results showed that vortex mixing of the sample pool produced similar results to those obtained from individual samples, with significantly higher epithelial cell concentrations (p < 0.001) and significantly lower Ct values (p < 0.001). Subsequently, we validated these findings by scaling up the sample size, confirming the reproducibility of the results. In addition, our data demonstrated that the coefficient of variation (CV) for an individual sample was greater than that for the sample pool (Supplementary Table S1).

The collection guidelines state that samples should not be left for more than 4 h.^17,18 Finally, we analyzed the effect of storage and vortex duration on the Ct value and epithelial cell concentration. Microscopic analysis revealed that epithelial cells in pharyngeal swabs initially appeared as clustered aggregates, which were progressively dissociated by vortex mixing. Consequently, a 2-min vortex mixing step significantly increased the epithelial cell concentration in individual specimens. In contrast, a notable decrease in cellular concentration was observed in sample pools following 2 min of vortex mixing. This phenomenon may be attributed to the higher density of swab fibers in sample pools, which, during prolonged vortex mixing, could compromise cellular membrane integrity, fragmenting epithelial cells into cellular debris. For example, morphological analysis, as demonstrated in Figures 3(c) and 4(d), confirmed that prolonged vortex mixing leads to increased epithelial cell fragmentation. In addition, the sample pool contains a larger volume of preservation solution, and long-term mixing may cause local concentration gradients.

Our investigation examined the effect of vortex mixing on Ct values and explored the underlying reasons for this effect and previously unstudied sample pools. However, several limitations warrant consideration. First, although vortex-mediated cellular dispersion may improve detection sensitivity during early infection stages, this hypothesis necessitates rigorous validation by analyzing positive specimens. Second, persistent technical limitations in vortex processing warrant attention. Although we observed a statistically significant reduction in Ct values following vortex mixing, the generalizability of this finding to high-prevalence settings remains uncertain. In pooled samples containing multiple positive specimens, heterogeneous dispersion of epithelial cells or viral aggregates during mechanical agitation may exacerbate intersample variability. Finally, our sequential vortex processing of sample pools presents challenges for large-scale samples. Future iterations of fully automated nucleic acid extraction systems should incorporate standardized vortex mixing protocols capable of maintaining analytical consistency.

In conclusion, obtaining reliable NAT results requires vortex mixing of samples. Therefore, this step remains indispensable, particularly in large-scale screening and automated systems. The integration of this step into laboratory protocols will facilitate the standardization of NAT detection procedures.

Data availability statement

The data in this study are available from the corresponding author upon request. Due to hospital regulations, these data are not publicly available.

Supplementary material

Supplemental material for this article is available online.