Reference Genes for Quantitative Real-time Polymerase Chain Reaction (qPCR)) Analyses in Freshly Isolated Monocytes of Septic Patients

Background : Sepsis is a life-threatening organ dysfunction associated with unregulated host response to infection. About 20 million people develop sepsis annually, and up to 50% die. Monocytes and macrophages play a key role in the innate and adaptive immune responses but the fully role of these cells in patients with sepsis still remains to be investigated. One of the limitations for the studies of gene expression in monocytes/macrophages in sepsis is the choice of the reference genes. We determined herein the most stable internal gene (s) to investigate gene expressions in monocytes/macrophages of septic patients. Methods : The expression stability of fifteen commonly used reference genes was analyzed by determining the comparative threshold cycle (Ct) values, using the BestKeeper, GeNorm, and NormFinder algorithms. Results : BestKeeper analysis revealed the syntaxin and hypoxanthine genes are highly stable. GeNorm pointed out STX5A and phosphoglycerate kinase 1 (PGK1) as the most suitable combination, whereas through NormFinder glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and 14-3-3 zeta/delta protein (YWHAZ) was the most stable combination. All program analyses discarded the use of heterogeneous nuclear ribonucleoprotein A/B (HNRNPAB). GeNorm and NormFinder indicated actin-beta (ACTB) as the minor stable gene. Conclusions : The combined data indicated that STX5A, PGK1, GAPDH, and HPRT1 are highly suitable reference genes for qPCR analysis of septic patient monocytes. In choosing one reference gene, the results point out STX5A (first place by GeNorm and BestKeeper and third place by NormFinder). This study is the first report on reference genes in freshly obtained monocytes/macrophages from septic patients.


BACKGROUND
Monocytes and macrophages are the front-line innate defense cells against pathogens 1,2 . Monocytes are immature immune cells circulating in the bloodstream, and they are locally recruited and become mature macrophages when there is tissue injury 3 . Macrophages are plastic cells and can differentiate into pro-inflammatory (M1) or anti-inflammatory and tissue repair (M2) types according to the microenvironment 3,4 . Monocytes and macrophages play an essential role in immunomodulation that occurs during sepsis 5 . According to the most recent definition (Sepsis-3; 2016), sepsis is a lifethreatening organ dysfunction associated with unregulated host response to infection. Septic shock is a shock subset that exhibits circulatory and metabolic dysfunctions with high mortality risk 6 . About 20 million people develop sepsis annually, and 30%-50% die. Sepsis is still a serious public health problem 7,8 .
Monocytes and macrophages have a set of receptors known as pattern recognition receptors (PRR), which rapidly initiate the inflammatory response upon tissue damage or in the presence of pathogens.
The toll-like receptors (TLRs) are a subfamily of PRRs and are the major cellular components required for pathogen-associated molecular patterns (PAMPs) recognition and inflammatory response initiation. Among TLRs, TLR4 mediates lipopolysaccharide (LPS) recognition in the cell wall of gram-negative bacteria. Lipoteichoic acid and glycan peptides found in gram-positive bacteria activate TLR2. The activation of the TLR2 triggers an inflammatory response in sepsis 9,10 , and systemic activation of the immune response occurs due to the release of the PAMPs or DAMPs (damage-associated molecular patterns ) from microorganisms or lesioned tissue, respectively 9 .
Several parameters ensure reliability and reproducibility in the quantitative gene expression measurements. The mentioned parameters are variations in initial sample volume, RNA integrity, cDNA synthesis efficiency, and differences in overall transcriptional activity in tissues or cells analyzed 17,18 . The most widely used approach to the normalization of the interest gene expression is an inner control gene. The internal control gene would be the one that detection is constant and continued in all tissues. The internal control gene expression does not change in any experimental condition and treatment, allowing the normalization of the interest gene [17][18][19][20][21] . Usually, there are one or more genes constitutively expressed. Firstly, it is necessary to identify potential candidates and test their expression stability in the condition under investigation 17,20 . Every mRNA analysis requires stably expressed reference genes as control. Reproducibility and reliability of the qPCR results demand reference genes 20 . Herein, we determined the most stable internal genes in monocytes/macrophages freshly obtained from septic patients.

Expression profile of candidate reference genes using the BestKeeper software
BestKeeper software determines the stability of the candidate genes by performing a pair-wise comparative analysis based on crossing points, and the best stability values are indicated by the lowest standard deviation and coefficient of variance 22 . The BestKeeper software identified the STX5A as the most stable and 18S as the less stable gene among 15 evaluated (Table 3)  YWHAZ, and B2M. The program calculates the Vn/n+1 between two sequential normalization factors to determine the optimal number of reference genes for normalization. For the cut-off value of V=0.15, two genes are required for accurate normalization. The analysis indicated STX5A and PGK1 as the best reference genes based on the high stability and low combined variation ( Figure 2).

Expression profile of the 15 reported reference genes using the NormFinder algorithm
The NormFinder algorithm allows estimating the gene expression variation intergroup and intragroup. High stability of gene expression is indicated by a low stability value associated with the systematic error of each reference gene 17 . The best stability value is almost equal to zero. The ACTB and HNRNPAB genes exhibited higher expression stability values ( Table 4). The NormFinder analysis indicated the GAPDH as the most suitable single gene for qPCR normalization in sepsis and GAPDH and YWHAZ as the most stable combination.

Ranking of the 15 reported reference genes as indicated by the three software tools
According to the BestKeeper analysis, the expression of the STX5A, HPRT1, and PGK1 genes was more stable, with the lowest standard deviation values and coefficient of variance. The NormFinder analysis indicated that a combination of GAPDH and YWHAZ has high expression stability. The GeNorm classified STX5A and PGK1 as the most top stable genes with a low combinatorial variation. Expressions of ACTB, HNRNPAB, and 18S genes were considered the least stable ones, according to the highest M value (GeNorm), coefficient of variance (BestKeeper), and stability value (NormFinder), respectively (Table 5).

DISCUSSION
Only a few studies reported gene expression results in monocytes/macrophages in experimental sepsis approaches ( Table 1). The authors of the mentioned studies performed in vitro experiment using mice bone marrow-derived monocytes/macrophages 19,23 , J774A1 murine macrophage cell line 24 , monocytes from healthy donors stimulated with LPS 25 , and monocytes from patients with relapsing-remitting multiple sclerosis 26 . Fifteen different genes were used as reference genes to normalize qPCR results in monocytes/macrophages under the experimental sepsis conditions mentioned. We then determined the most appropriate reference genes for studies in monocyte/macrophage freshly obtained from septic patients.
In response to several stimuli as LPS, lipoteichoic acid, and glycan peptides, the expression of several genes modifies in monocytes 2 . The expression of reported reference genes in macrophages might also change in critical clinical conditions such as sepsis 22 . Thereby, to investigate changes in expression of the interest genes, it is first necessary to determine which reference gene expression is stable in monocytes/macrophages of septic patients.
A previous report using LPS stimuli in 6 hours cultured macrophages indicated the HNRNPAB as the most stable reference gene 19 . Two other studies reported ACTB as a reference gene in monocytes from septic patients 11,13 . We reported HNRNPAB and ACTB as two of the minor stable genes in freshly obtained monocytes/macrophages from septic patients, according to GeNorm, NormFinder, and BestKeeper tools.
The other two reports used 18S as a reference gene to normalize interest gene expressions in monocytes 15,27 . The NormFinder and BestKeeper analysis indicated 18S is the most unstable of the reference genes in freshly obtained monocytes/macrophages under the conditions of this study.
The use of GAPDH to normalize gene expression was reported in mononuclear cells from septic patients 16 and in an experimental septic model using immortalized monocyte 28 . GAPDH was considered herein as the most stable gene by the NormFinder analysis. Cummings et al. 29 evaluated the expression of HPRT1 and GAPDH in the whole blood of septic patients and identified that HPRT1 is more stable and reliable for data normalization than GAPDH. Our results indicate that GAPDH is a reliable gene for normalizing monocyte gene expression data; perhaps this is a result of the different samples and experimental conditions used.
Another study with monocytes from critically ill patients and septic patients used the geometric mean of five target genes with the minor variation as reference genes 12 . As mentioned, most of these studies used in vitro LPS-stimulated monocytes, which differ from cells freshly obtained from septic patients. Coulibaly et al. 30 identified that AKIRIN1 is a potential reference gene for sepsis. However, the cells studied were granulocytes and natural killer (NK) cells. In certain conditions, such as LPS stimulation, expressions of ACTB or GAPDH are modulated and cannot be considered good normalizers of gene expression in these samples [24].
We identified herein STX5A, PGK1, GAPDH, and HPRT1 as the most stable reference genes analyzing gene expression in monocytes freshly obtained from septic patients. In choosing one reference gene, the results point out STX5A; first place by GeNorm and BestKeeper and third place by NormFinder of the genes investigated. This study is the first report on reference genes in freshly obtained monocytes/macrophages from septic patients.

Literature search strategy
We used the National Center for Biotechnology Information (NCBI) public PubMed database (http/www.ncbi.nlm.nih.gov/pubmed) for article search. We defined combinations using SEPSIS, SEPTIC SHOCK, MONOCYTE, MACROPHAGE, REFERENCE GENE, and GENE EXPRESSION.  [20].

Monocyte preparation
We collected 20 mL of blood in tubes containing EDTA from septic patients. Samples were centrifuged at 400 x g to obtain cells. We diluted the cells in phosphate buffer saline pH 7.4 and added Histopaque 1077 (Sigma Chemical Co, St Louis, MO, USA). We centrifuged the tubes at 400 x g and 4 °C for 30 minutes resulting in the isolation of mononuclear cells, which were cultured for one hour in RPMI-1640 medium (Sigma-Aldrich, St. Louis, MO, USA) supplemented with 10% fetal bovine serum (Sigma-Aldrich) at 37 °C in a 5% CO2 incubator. Following incubation, the monocytes adhered to the culture plate were isolated in Trizol® (Invitrogen, Carlsbad, California, EUA) and stored at -80 °C for further analysis.

RNA isolation and cDNA synthesis
According to the manufacturer protocol, total RNA was extracted from monocytes using RNAqueous Microkit® (Invitrogen, Carlsbad, California, USA). The determination of the concentration and purity of the RNA samples was performed by absorbance analysis at 260/280 nm using a Thermo Scientific NanoDrop (Thermo Fisher Scientific, Waltham, Massachusetts, USA).
cDNA was synthesized from the extracted RNA (1000 μg) using the High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, Waltham, Massachusetts, USA). We used a similar procedure in previous studies 31 .

Selection of candidates for reference genes
We first listed 15 reference genes previously used in studies with monocytes/macrophages from different sepsis experimental approaches, primarily in bone marrow-derived cells and the J7741 murine macrophage cell line (Table 1). We obtained specific primers for each gene using the National Maryland, USA) to design the primers ( Table 2). The hybridization temperature of the primers was standardized for the experiment (60°C).
The 25 μL reaction mix had 12.5 μL Power SYBR Green PCR Master Mix (ThermoFisher, Waltham, Massachusetts, EUA); 40 ng cDNA, and one μM forward and reverse primers (EXXTEND, Paulínia, São Paulo, Brazil); and 6.9 μL nuclease-free water, added to a 96-well plate. The cycling conditions followed the protocol of the SYBR Green manufacturer. We analyzed the melt curve to determine the specificity of the qPCR products and the absence of primer-dimer formation. We used a similar procedure in previous studies 31 . We followed the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines 32 .

Bioinformatic tools used
The expression stabilities of the reference genes were determined using the BestKeeper

Ethics approval and consent to participate
All participants included in this study were over 18 years old, and all signed the informed consent form. The Ethics Committee of the University of São Paulo Hospital (HU-USP-Process number 1513 of 29th January 2016) approved the study.

Consent for publication
Not applicable.

Availability of data and materials
The datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Competing interests
The authors declared that no conflict of interest exists.

Funding
We thank the following financial support:

SUPPLEMENTARY MATERIAL
We used the melting curve to determine the specificity of the primers. The presence of a single amplification peak indicates the specificity of the primers used. Figure 1 Cycle quanti cation (Ct) values of reference genes in plasma monocytes of septic patients harvested during hospitalization and immediately after hospital ICU discharge. The bars represent the average with standard deviation.

Supplementary Files
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