在实时定量PCR(qRT-PCR)过程中选择参考基因对于确定准确和可靠的mRNA表达至关重要。尽管如此,没有一项研究调查了候选参考基因的表达稳定性,以确定它们是否适合作为SARS-CoV-2感染或COVID-19相关毛霉菌病(CAM)的内部对照。使用qRT-PCR,我们确定了九种最常用的管家基因的表达稳定性,即,TATA-box结合蛋白(TBP),亲环蛋白(CypA),β-2-微球蛋白(B2M),18SrRNA(18S),过氧化物酶体增殖物激活受体γ(PPARG)共激活因子1α(PGC-1α),葡萄糖醛酸酶β(GUSB),次黄嘌呤磷酸核糖基转移酶1(HPRT-1),β-肌动蛋白,和甘油醛-3-磷酸脱氢酶(GAPDH)在不同严重程度的COVID-19患者中(无症状,温和,中度,和严重)和那些与CAM。我们使用了统计算法(delta-CT[阈值周期],NormFinder,BestKeeper,GeNorm,和RefFinder)选择最合适的参考基因,并观察到临床严重程度会严重影响参考基因的表达稳定性。无论疾病严重程度如何,CypA都表现出最一致的表达,并成为COVID-19和CAM中最合适的参考基因。顺便说一句,GAPDH,最常用的参考基因,显示表达的最大变化,并显示为最不合适的。接下来,我们测定了核因子红系2相关因子2(NRF2)的表达,白细胞介素-6(IL-6),和IL-15使用CypA和GAPDH作为内部对照,并且显示CypA标准化表达与这些基因的基于RNA测序的表达良好匹配。Further,IL-6表达与血浆IL-6和C反应蛋白水平相关,炎症的标志.总之,在COVID-19和CAM中,GAPDH是最不合适的,而CypA是最合适的参考基因。结果突出了由于疾病严重程度引起的管家基因的表达变异性,并为在其他慢性疾病中鉴定适当的参考基因提供了强有力的理由。重要性基因表达研究对于开发新的诊断方法至关重要,治疗学,和预后模式。然而,表达的准确确定需要用参考基因进行数据归一化,其表达在不同疾病阶段没有变化。参考基因的误认会产生不准确的结果。不幸的是,尽管COVID-19对全球产生了影响,并且迫切需要更好的治疗,没有一项研究调查了整个疾病谱中管家基因的表达稳定性,以确定它们是否适合作为内部对照。我们的研究将CypA和TBP确定为COVID-19和CAM的两个最合适的参考基因。Further,GAPDH,COVID-19研究中最常用的参考基因,结果证明是最不合适的。这项工作填补了该领域的重要空白,并有望促进基因准确表达的确定,以促进新型分子诊断和治疗的发展,以改善患者护理。
Selection of reference genes during real-time quantitative PCR (qRT-PCR) is critical to determine accurate and reliable mRNA expression. Nonetheless, not a single study has investigated the expression stability of candidate reference genes to determine their suitability as internal controls in SARS-CoV-2 infection or COVID-19-associated mucormycosis (CAM). Using qRT-PCR, we determined expression stability of the nine most commonly used housekeeping genes, namely, TATA-box binding protein (TBP), cyclophilin (
CypA), β-2-microglobulin (B2M), 18S rRNA (18S), peroxisome proliferator-activated receptor gamma (PPARG) coactivator 1 alpha (PGC-1α), glucuronidase beta (GUSB), hypoxanthine phosphoribosyltransferase 1 (HPRT-1), β-ACTIN, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in patients with COVID-19 of various severities (asymptomatic, mild, moderate, and severe) and those with CAM. We used statistical algorithms (delta-CT [threshold cycle], NormFinder, BestKeeper, GeNorm, and RefFinder) to select the most appropriate reference gene and observed that clinical severity profoundly influences expression stability of reference genes.
CypA demonstrated the most consistent expression irrespective of disease severity and emerged as the most suitable reference gene in COVID-19 and CAM. Incidentally, GAPDH, the most commonly used reference gene, showed the maximum variations in expression and emerged as the least suitable. Next, we determined expression of nuclear factor erythroid 2-related factor 2 (NRF2), interleukin-6 (IL-6), and IL-15 using
CypA and GAPDH as internal controls and show that CypA-normalized expression matches well with the RNA sequencing-based expression of these genes. Further, IL-6 expression correlated well with the plasma levels of IL-6 and C-reactive protein, a marker of inflammation. In conclusion, GAPDH emerged as the least suitable and
CypA as the most suitable reference gene in COVID-19 and CAM. The results highlight the expression variability of housekeeping genes due to disease severity and provide a strong rationale for identification of appropriate reference genes in other chronic conditions as well. IMPORTANCE Gene expression studies are critical to develop new diagnostics, therapeutics, and prognostic modalities. However, accurate determination of expression requires data normalization with a reference gene, whose expression does not vary across different disease stages. Misidentification of a reference gene can produce inaccurate results. Unfortunately, despite the global impact of COVID-19 and an urgent unmet need for better treatment, not a single study has investigated the expression stability of housekeeping genes across the disease spectrum to determine their suitability as internal controls. Our study identifies
CypA and then TBP as the two most suitable reference genes for COVID-19 and CAM. Further, GAPDH, the most commonly used reference gene in COVID-19 studies, turned out to be the least suitable. This work fills an important gap in the field and promises to facilitate determination of an accurate expression of genes to catalyze development of novel molecular diagnostics and therapeutics for improved patient care.