scholarly journals Selection and validation of reference genes for quantitative real-time PCR in the green microalgae Tetraselmis chui

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245495
Author(s):  
Sonia Torres ◽  
Carmen Lama ◽  
Lalia Mantecón ◽  
Emmanouil Flemetakis ◽  
Carlos Infante
Keyword(s):  
Real Time ◽  
Reference Genes ◽  
Large Scale ◽  
Critical Factor ◽  
Continuous Phase ◽  
Culture Conditions ◽  
Green Microalgae ◽  
Industrial Facilities ◽  
Reverse Transcription Pcr ◽  
Tetraselmis Chui

Quantitative real-time reverse transcription PCR (RT-qPCR) is a highly sensitive technique that can be applied to analyze how genes are modulated by culture conditions, but identification of appropriate reference genes for normalization is a critical factor to be considered. For this reason, the expression stability of 18 candidate reference genes was evaluated for the green microalgae Tetraselmis chui using the widely employed algorithms geNorm, NormFinder, BestKeeper, the comparative ΔCT method, and RefFinder. Microalgae samples were collected from large scale outdoor photobioreactors during the growing phase (OUT_GP), and during the semi-continuous phase at different times of the day (OUT_DC). Samples from standard indoor cultures under highly controlled conditions (IND) were also collected to complement the other data. Different rankings for the candidate reference genes were obtained depending on the culture conditions and the algorithm employed. After comparison of the achieved ranks with the different methods, the references genes selected for samples from specific culture conditions were ALD and EFL in OUT_GP, RPL32 and UBCE in OUT_DC, and cdkA and UBCE in IND. Moreover, the genes EFL and cdkA or EFL and UBCE appeared as appropriate combinations for pools generated from all samples (ALL). Examination in the OUT_DC cultures of genes encoding the large and small subunits of ADP-glucose pyrophosphorylase (AGPL and AGPS, respectively) confirmed the reliability of the identified reference genes, RPL32 and UBCE. The present study represents a useful contribution for studies of gene expression in T. chui, and also represents the first step to set-up an RT-qPCR platform for quality control of T. chui biomass production in industrial facilities.

scholarly journals Fast and low-cost detection of SARS-CoV-2 peptides by tandem mass spectrometry in clinical samples

2020 ◽  
Author(s):  
Karina Helena Morais Cardozo ◽  
Adriana Lebkuchen ◽  
Guilherme Goncalves Okai ◽  
Rodrigo Andrade Schuch ◽  
Luciana Godoy Viana ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Low Cost ◽  
Large Population ◽  
Virus Detection ◽  
Standard Test ◽  
Clinical Samples ◽  
Rt Pcr ◽  
Reverse Transcription Pcr ◽  
Fast Processing

Abstract The current outbreak of severe acute respiratory syndrome associated with coronavirus 2 (SARS-CoV-2) is pressing public health systems around the world, and large population testing is a key step to control this pandemic disease. Real-time reverse-transcription PCR (real-time RT-PCR) is the gold standard test for virus detection but the soaring demand for this test resulted in shortage of reagents and instruments, severely limiting its applicability to large-scale screening. To be used either as an alternative, or as a complement, to real-time RT-PCR testing, we developed a high-throughput targeted proteomics assay to detect SARS-CoV-2 proteins directly from clinical respiratory tract samples. Sample preparation was fully automated by using a modified magnetic particle-based proteomics approach implemented on a robotic liquid handler, enabling a fast processing of samples. The use of turbulent flow chromatography included four times multiplexed on-line sample cleanup and UPLC separation. MS/MS detection of three peptides from SARS-CoV-2 nucleoprotein and a 15N-labeled internal global standard was achieved within 2.5 min, enabling the analysis of more than 500 samples per day. The method was validated using 562 specimens previously analyzed by real-time RT-PCR and was able to detect over 83% of positive cases. No interference was found with samples from common respiratory viruses, including other coronaviruses (NL63, OC43, HKU1, and 229E). The strategy here presented has high sample stability and low cost and should be considered as an option to large population testing.

scholarly journals GeneChip, geNorm, and gastrointestinal tumors: novel reference genes for real-time PCR

2007 ◽  
Vol 30 (3) ◽  
pp. 363-370 ◽  
Author(s):  
Mark Kidd ◽  
Boaz Nadler ◽  
Shrikant Mane ◽  
Geeta Eick ◽  
Maximillian Malfertheiner ◽  
...  
Keyword(s):  
Real Time ◽  
Reference Genes ◽  
Large Scale ◽  
Target Genes ◽  
Breast Tumors ◽  
Clinical Samples ◽  
Stable Gene ◽  
Data Set ◽  
Normal Tissues ◽  
Gene Database

Accurate quantitation of target genes depends on correct normalization. Use of genes with variable tissue transcription ( GAPDH) is problematic, particularly in clinical samples, which are derived from different tissue sources. Using a large-scale gene database (Affymetrix U133A) data set of 36 gastrointestinal (GI) tumors and normal tissues, we identified 8 candidate reference genes and established expression levels by real-time RT-PCR in an independent data set ( n = 42). A geometric averaging method (geNorm) identified ALG9, TFCP2, and ZNF410 as the most robustly expressed control genes. Examination of raw CT values demonstrated that these genes were tightly correlated between themselves ( R2 > 0.86, P < 0.0001), with low variability [coefficient of variation (CV) <12.7%] and high interassay reproducibility ( r = 0.93, P = 0.001). In comparison, the alternative control gene, GAPDH, exhibited the highest variability (CV = 18.1%), was significantly differently expressed between tissue types ( P = 0.05), was poorly correlated with the three reference genes ( R2 < 0.4), and was considered the least stable gene. To illustrate the importance of correct normalization, the target gene, MTA1, was significantly overexpressed ( P = 0.0006) in primary GI neuroendocrine tumor (NET) samples (vs. normal GI samples) when normalized by geNormATZ but not when normalized using GAPDH. The geNormATZ approach was, in addition, applicable to adenocarcinomas; MTA1 was overexpressed ( P < 0.04) in malignant colon, pancreas, and breast tumors compared with normal tissues. We provide a robust basis for the establishment of a reference gene set using GeneChip data and provide evidence for the utility of normalizing a malignancy-associated gene ( MTA1) using novel reference genes and the geNorm approach in GI NETs as well as in adenocarcinomas and breast tumors.

scholarly journals Fast and low-cost detection of SARS-CoV-2 peptides by tandem mass spectrometry in clinical samples

2020 ◽  
Author(s):  
Karina Helena Morais Cardozo ◽  
Adriana Lebkuchen ◽  
Guilherme Goncalves Okai ◽  
Rodrigo Andrade Schuch ◽  
Luciana Godoy Viana ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Low Cost ◽  
Large Population ◽  
Virus Detection ◽  
Standard Test ◽  
Clinical Samples ◽  
Rt Pcr ◽  
Reverse Transcription Pcr ◽  
Fast Processing

Abstract The current outbreak of severe acute respiratory syndrome associated with coronavirus 2 (SARS-CoV-2) is pressing public health systems around the world, and large population testing is a key step to control this pandemic disease. Real-time reverse-transcription PCR (real-time RT-PCR) is the gold standard test for virus detection but the soaring demand for this test resulted in shortage of reagents and instruments, severely limiting its applicability to large-scale screening. To be used either as an alternative, or as a complement, to real-time RT-PCR testing, we developed a high-throughput targeted proteomics assay to detect SARS-CoV-2 proteins directly from clinical respiratory tract samples. Sample preparation was fully automated by using a modified magnetic particle-based proteomics approach implemented on a robotic liquid handler, enabling a fast processing of samples. The use of turbulent flow chromatography included four times multiplexed on-line sample cleanup and UPLC separation. MS/MS detection of three peptides from SARS-CoV-2 nucleoprotein and a 15N-labeled internal global standard was achieved within 2.5 min, enabling the analysis of more than 500 samples per day. The method was validated using 562 specimens previously analyzed by real-time RT-PCR and was able to detect over 83% of positive cases. No interference was found with samples from common respiratory viruses, including other coronaviruses (NL63, OC43, HKU1, and 229E). The strategy here presented has high sample stability and low cost and should be considered as an option to large population testing.

geNorm assessment of the efficacy of novel reference genes ALG9, TFCP2 and ZNF410 compared to GAPDH for real time normalization in GI carcinoids

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 20052-20052
Author(s):  
G. Eick ◽  
M. Kidd ◽  
S. Mane ◽  
B. Nadler ◽  
M. Champaneria ◽  
...  
Keyword(s):  
Real Time ◽  
Reference Genes ◽  
Large Scale ◽  
Target Genes ◽  
Marker Genes ◽  
Stable Gene ◽  
Rt Pcr ◽  
Experimental Conditions ◽  
Expression Levels ◽  
Accurate Normalization

20052 Background: Robust quantitation of potential clinical marker genes using quantitative real-time PCR (Q RT-PCR) is critically dependent on accurate normalization. Although GAPDH has historically been used for normalization, its expression has been shown to vary widely between different tissues and experimental conditions. Additionally, conventional normalization strategies based on a single housekeeping gene can lead to large normalization errors. The determination of a panel of genes that have robust expression in the experimental system being studied is therefore essential to ensure accurate normalization and interpretation of results. Methods: Based upon the availability of large-scale gene databases, we developed methodology to identify highly expressed genes (mean log-transformed expression levels: 4–8 in all samples) with low variability (S.D. < 0.22) in a Affymetrix U133A dataset of 36 gastrointestinal tumors and normal tissues. Eight novel candidate reference genes were identified and their expression levels established by Q RT-PCR in an independent set of GI tissue samples (n = 24). The geNorm tool was used to identify the most stably expressed set of genes amongst the 8 candidate genes. The expression levels of 3 potential GI tumor marker genes, namely the adhesin MAGE-D2, the metastasis-associated MTA1, and the mitosis regulator, NAP1L1, were normalized to GAPDH or geNorm and compared. Results: geNorm identified 3 genes, ALG9, TFCP2 and ZNF410, as the most robustly expressed control genes. GAPDH, in contrast, exhibited the highest variability and was considered the least stable gene of the nine evaluated. Two previously-identified target genes, MAGE-D2 and MTA1, were significantly elevated (p < 0.05) in malignant tumor samples (vs normal GI samples) when normalized by geNormATZ but not when normalized using GAPDH. NAP1L1 was only over-expressed in small intestinal carcinoids (normalized to geNormATZ). Expression levels of this gene were high in normal gastric mucosa. Conclusions: We provide a robust basis for the establishment of a reference gene set using GeneChip data and provide evidence for the clinical utility of identifying reference genes using the geNorm approach in GI neuroendocrine tumors. No significant financial relationships to disclose.

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