Next Article in Journal
Adipose-Derived Stromal Cells within a Gelatin Matrix Acquire Enhanced Regenerative and Angiogenic Properties: A Pre-Clinical Study for Application to Chronic Wounds
Next Article in Special Issue
Small Cell Lung Carcinoma: Current Diagnosis, Biomarkers, and Treatment Options with Future Perspectives
Previous Article in Journal
Mixed-Culture Propagation of Uterine-Tissue-Resident Macrophages and Their Expression Properties of Steroidogenic Molecules
Previous Article in Special Issue
Optimal Selection of IFN-α-Inducible Genes to Determine Type I Interferon Signature Improves the Diagnosis of Systemic Lupus Erythematosus
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Biomedicines
Volume 11
Issue 3
10.3390/biomedicines11030986
biomedicines-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Communication

High-Throughput and Automated Detection of HLA-B*27 Using the LabTurboTM AIO System

by
Yung-Che Chou
1 and
Tze-Kiong Er
1,2,3,*
1
Division of Laboratory Medicine, Asia University Hospital, Asia University, Taichung 413, Taiwan
2
Department of Medical Laboratory Science and Biotechnology, Asia University, Taichung 413, Taiwan
3
Department of Nursing, Asia University, Taichung 413, Taiwan
*
Author to whom correspondence should be addressed.
Biomedicines 2023, 11(3), 986; https://doi.org/10.3390/biomedicines11030986
Submission received: 6 March 2023 / Revised: 14 March 2023 / Accepted: 20 March 2023 / Published: 22 March 2023
(This article belongs to the Special Issue Identification and Validation of New Biomarkers to Help the Creation of Clinical Diagnostics in Autoimmune and Cancer Diseases)
Browse Figure
Versions Notes

Abstract

:
The adoption of an automated system can decrease the hands-on time requirements in a clinical laboratory setting. For the detection of HLA-B*27, implementing a high-throughput and fully automated system has several advantages over using manual methods. Therefore, this study aimed to evaluate automation efficiency for the detection of HLA-B*27. Peripheral blood samples were obtained from 50 participants, and DNA was isolated from these samples. A Pharmigene PG27 detection kit was used for the qualitative detection of HLA-B*27. The performances of the semi-automated and fully automated LabTurboTM AIO systems in the detection of HLA-B*27 were compared. The mean absorbance (optical density) values for the MaelstromTM 8 and LabTurboTM AIO systems were found to be 1.88 and 1.9, respectively. The housekeeping gene was amplified and quantified using a real-time PCR assay across all DNA extracts to check the quality of the extracted human DNA. The results were expressed as the cycle threshold (Ct) values for all DNA extracts from both platforms. The mean Ct values for the Roche Cobas z480 and LabTurboTM AIO systems were found to be 22.7 and 20.4, respectively. This study demonstrated that the semi-automated method and the LabTurboTM AIO system yield consistent results for the detection of HLA-B*27. However, compared to the semi-automated method, the LabTurboTM AIO system provides standardized procedures, avoids manual handling, and improves turnaround time.

1. Introduction

The advancement in molecular diagnostics has facilitated the genetic testing of genetic diseases as well as the identification of multiple pathogens. The operation of these tests requires extensive training in molecular biology. The implementation of laboratory automation can simplify the process of analyzing multiple specimens, thereby increasing the throughput of specimen testing, standardizing the performance of molecular testing procedures, shortening testing turnaround times, and reducing labor time and cost. In essence, automation combines laboratory robotics and analytical software. Nowadays, automation is becoming more sophisticated than simply facilitating the integration of sample extraction, as it also supports nucleic acid amplification and detection. A fully automated molecular diagnostic system is a robust and useful system that is capable of a broad variety of applications [1,2].
As molecular diagnostics is a complex process involving several procedures from nucleic acid extraction to result interpretation, technologists can only process a few clinical samples at a time. Moreover, when high-volume testing is demanded, higher manpower costs are incurred in the long run. Additionally, regular laboratory testing is highly labor-intensive and may lead to manual errors, which can result in poor patient outcomes. If the number of clinical samples to be processed by laboratories increases dramatically, productivity has to be improved. Therefore, automated equipment such as robotic liquid-handling platforms can replace manual processes in molecular diagnostics workflows. This will reduce hands-on time and improve accuracy in a clinical laboratory setting. Bioinformatic software also facilitates standardized reporting and the interpretation of laboratory test results.
Recently, Chang et al. reported that the LabTurboTM AIO (Taigen Bioscience Corp., Taipei, Taiwan) COVID-19 RNA testing kit is a feasible and reliable method for SARS-CoV-2 detection [3]. They demonstrated a sample-pooling strategy using the LabTurboTM AIO extraction system, which is combined with a real-time reverse transcription polymerase chain reaction (rRT-PCR) platform. According to them, the pooling strategy applied in the LabTurboTM AIO system resulted in zero volume loss for SARS-CoV-2 detection using rRT-PCR [4]. Chung et al. also reported that the multiplex RT-PCR implemented on the LabTurboTM AIO system offered a high-throughput detection of SARS-CoV-2 variants, influenza A/B, and respiratory syncytial virus, along with shortening the duration of the entire process from its initiation to completion [5]. Until recently, the LabTurboTM AIO system had not been used for the detection of HLA-B*27.
The human leukocyte antigen (HLA) system is a gene complex encoding the major histocompatibility complex proteins in humans. These cell-surface proteins are in charge of the regulation of the immune system. Classic class I HLA consists of HLA-A, -B, and -C genes, whereas the main class II HLA genes are DP, DQ, and DR [6]. Studies demonstrated that HLA genetic variants are associated with systemic lupus erythematosus, rheumatoid arthritis, multiple sclerosis, type 1 diabetes mellitus, celiac disease, narcolepsy, and Sjögren’s syndrome [7,8]. HLA-B*27 is strongly associated with ankylosing spondylitis (AS), and HLA-B*27 detection is routinely applied in the diagnosis of this disease. The percentages of HLA-B*27 positivity in the general population and among AS patients are 5–10% and 90%, respectively [9]. Multiple molecular diagnostic techniques are applied for the routine typing of HLA-B*27, including PCR with sequence-specific primers, PCR with restriction fragment length polymorphism, and also PCR with sequence-based typing, flow cytometry, melting curve analysis, and real-time PCR assay [10,11,12,13,14]. Thus far, a fully automated procedure has not been applied to the detection of HLA-B*27. As mentioned above, the adoption of an automated system can decrease the hands-on time requirements in a clinical laboratory setting. For the detection of HLA-B*27, implementing a high-throughput and fully automated system has several advantages over using manual methods.
In the present study, we aimed to evaluate the efficiency of automation in the detection of HLA-B*27.

2. Materials and Methods

2.1. Study Population

The present study included a total of 50 participants who had requested HLA-B*27 typing. Out of the 50 samples that were tested, 35 (70%) were obtained from male patients while 15 (30%) were obtained from female patients. The median age of these 50 patients was 47.5 years (12–69). Peripheral blood specimens (10 mL) were collected in K2EDTA. One part of each sample was analyzed using a semi-automated procedure, whereas the other part was analyzed using a fully automated procedure. Ethical approval was obtained from the Institution Review Board of China Medical University Hospital (CMUH112-REC2-026) and (CMUH112-REC2-026 (AR-1)). The requirement for informed consent from each patient was waived.

2.2. DNA Extraction and Real-Time PCR Analysis

In this study, the MaelstromTM 8 Autostage (Taiwan Advanced Nanotech, Taoyuan City, Taiwan) was used for extracting DNA from the whole blood samples using the TANBead® nucleic acid extraction kit (Taoyuan City, Taiwan), as per the manufacturer’s instructions. DNA was extracted from samples of 300 μL volume. The MaelstromTM 8 Autostage is a high-efficiency purification system driven by TANBead’s patented technology [15]. With TANBead MaelstromTM 8 Autostage, a maximum of eight samples can be processed during each run.
The LabTurboTM AIO system (LabTurbo Biotech Corporation, Taipei City, Taiwan) was used for extracting DNA from the whole blood samples using the LabTurbo Viral DNA/RNA Mini Kit (Cat. No. LVX480-500; Taigen Bioscience Corp., Taipei City, Taiwan), as per the manufacturer’s instructions. The total DNA extracted from the whole blood sample (50 µL) was a final eluate volume of 60 µL. With the LabTurboTM AIO system, a maximum of 48 samples can be processed during each run. The purity of the extracted DNA was determined using a spectrophotometer. We used the HLA-B*27 detection kit (Pharmigene, Inc., Taipei city, Taiwan) to the LabTurboTM AIO system, using specific primers and probes to detect the HLA-B*27 allele. The HLA-B*27 detection kit (Pharmigene, Inc., Taipei city, Taiwan) was handled according to the manufacturer’s instructions. The sensitivity and specificity of the HLA-B*27 detection kit were greater than 99%, which indicates the high sensitivity of major HLA-B*27 subtypes, including HLA-B*2701~2707. The procedures followed for the LabTurboTM AIO system are presented in the flow chart in the supplementary data (Figure S1).
For analysis on the LabTurboTM AIO system, each 25 μL reaction mixture contained 12.5 μL of 2 × PCR master mix, 2.5 μL of primer/probe mixture, 5 μL of RNase-free water, and 5 μL of extracted RNA. HLA-B*27 was detected using the following thermal cycling conditions: 95 °C for 10 min, 35 cycles at 95 °C for 15 s, and 71 °C for 60 s (collection of fluorescent signals at 71 °C).
For analysis on the Roche Cobas z480 system (Roche Molecular System Inc, Pleasanton, CA, USA), each 25 μL reaction mixture contained 12.5 μL of 2 × PCR master mix, 2.5 μL of primer/probe mixture, 8 μL of RNase-free water, and 2 μL of extracted RNA. HLA-B*27 was detected using the following thermal cycling conditions: 95 °C for 10 min, 35 cycles at 95 °C for 15 s, and 71 °C for 60 s (collection of fluorescent signals at 71 °C).

2.3. Statistical Analysis

The software used for the statistical analyses was SPSS version 22.0 (IBM Corp., Armonk, NY, USA) for Windows. The detailed results are represented in Figure 1. The box plot displays the distribution of the Ct values for the 50 samples analyzed in the present study, while the horizontal black bar represents the median Ct value. The lower and upper boxes indicate the 25th percentile to the 75th percentile.

3. Results

3.1. Semi-Automated and Fully Automated Procedures in DNA Extraction

The mean absorbance (optical density) values for the MaelstromTM 8 and LabTurboTM AIO systems were observed to be 1.88 and 1.9, respectively. The housekeeping gene was amplified and quantified using a real-time PCR assay in all of the DNA extracts to check the quality of the extracted human DNA, and the results were expressed as the cycle threshold (Ct) values for all DNA extracts from both platforms. The mean Ct values for the Roche Cobas z480 system (Roche Molecular System Inc, Pleasanton, CA, USA) and the LabTurboTM AIO system were 22.7 and 20.4, respectively. Figure 1 presents the Ct values of the distribution of the target genes of the MaelstromTM 8 and LabTurboTM AIO systems obtained by analyzing the clinical samples.

3.2. Semi-Automated and Fully Automated Procedures in HLA-B*27 Detection

We validated the performance of the semi-automated and fully automated assays designed in this study for the detection of HLA-B*27. The LabTurboTM AIO system obtained a positive percent agreement of 100% as well as a negative percent agreement of 100% by using a semi-automated assay (Table 1). The LabTurboTM AIO system performed HLA-B*27 detection on 48 samples in under 200 min compared to the semi-automated system. The incorporation of a fully automated extraction and real-time PCR assay on the LabTurboTM AIO system significantly reduced the operation time to 110 min compared to the semi-automated system (Table 2 and Table 3).

4. Discussion

Multiple studies demonstrate that laboratory automation may be effective in reducing turnaround time and increasing laboratory productivity [16,17,18]. It may also enhance standardization for accreditation purposes, thereby improving the quality of testing, minimizing manually intensive labor, and strengthening sample management and traceability [17]. This study demonstrated that HLA-B*27 genotyping using fully-automated procedures is an efficient and accurate method compared to semi-automated procedures in the Taiwanese context.
Various types of methods can be employed to detect HLA-B*27, ranging from old, basic, tedious, and time-consuming procedures to rapid throughput techniques. In 1997, Nieto et al. reported the use of polymerase chain reaction with the restriction fragment length polymorphism (PCR-RFLP) for genotyping HLA-B*27. The authors concluded that PCR-RFLP demonstrated robustness, technical simplicity, and cost-effectiveness [19]. PCR-RFLP has also been used to compare the clinical features of AS, along with the frequencies of HLA-B*27 and its alleles in patients from Turkey [20]. However, the main drawbacks of RFLPs are that they are labor intensive and time consuming [21]. Tiemann et al. demonstrated that performing real-time PCR using LightCycler technology is a feasible method for the detection of HLA-B*27, and it is also an alternative to a conventional PCR with sequence-specific primers (PCR-SSP) [22]. Similarly, two studies reported that the use of real-time PCR assays for the detection of HLA-B*27 was fast and reliable in clinical settings [23,24]. Further, real-time PCR has also been applied to detect HLA-B*27 in the Dutch population [25]. Recently, Geiger et al. reported that direct real-time PCR-based HLA-B*27 testing in whole blood was in 100% concordance with the results derived from routine DNA-based HLA-B*27 genotyping [14]. Flow cytometry is also a diagnostic tool used for the detection of HLA-B*27 as it is economical and relatively simple [11,26]. Previously, Skalska et al. demonstrated that the genetic sequence-based method and the flow cytometry method provide consistent results in 99% of samples [27]. However, a limitation of flow cytometry is that it is unable to discriminate HLA-B*27 allelic variants. Priyathersini et al. suggested that flow cytometry is a reliable assay for the detection of HLA-B*27 during the screening of AS in the Indian population [11]. Moreover, Weckel et al. reported that three HLA-B*27-typing kits by flow cytometry are feasible and reliable for diagnosis in 90% of the routine cases [28]. However, another study demonstrated that PCR-SSP has certain advantages over flow cytometry, as it can be carried out with a lower quantity of blood samples, whereas flow cytometry requires more fresh samples for accurate results [29].
DNA extraction has evolved from solution- and solid-phase manual techniques, which were initially performed manually, to incorporate automated methods. The use of high-quantity and high-quality DNA is an important aspect of downstream applications. Therefore, nucleic acid extraction is an important step in laboratory procedures, which are required to carry out further molecular research applications. It is necessary to select a feasible and reliable extraction method, and there are a few things to consider when estimating the available options. These considerations may include cost-effectiveness, technical requirements, time efficiency, and storage requirements [30]. The MaelstromTM 8 Autostage (Taiwan Advanced Nanotech) utilizes a magnetic-bead-based system to extract nucleic acids. This system is designed to be easily used as it can process up to eight samples simultaneously. Our previous study reported that the MaelstromTM 8 Autostage offers standardized procedures, the avoidance of sample-to-sample cross contaminations, ease of use, improvement in turnaround time, and lesser hands-on time compared to the manual extraction method (QIAamp Viral RNA Mini Kit) [15].
The fully automated processing of clinical samples results in reduced hands-on time. Such processing also results in high-throughput ability, adequate yield, and purity, which are necessary to achieve routine downstream assay. The LabTurboTM AIO system has been designed as a fully automated and enclosed instrument to eliminate manual handling. In the present study, we demonstrated that the mean absorbance (optical density) values for the MaelstromTM 8 and LabTurboTM AIO systems were 1.88 and 1.9, respectively. Further, the housekeeping gene was amplified during the real-time PCR reaction as an internal control for the extraction method. The mean Ct values for the Roche Cobas z480 and LabTurboTM AIO systems were 22.7 and 20.4, respectively (Figure 1). Based on our findings, the LabTurboTM AIO system ensured the isolation of good-quality DNA.
After comparing the results of the semi-automated and fully automated assays, we found that the fully automated assay was superior in detecting HLA-B*27. Further, we found that the use of the LabTurboTM AIO system shortened the turnaround time by approximately 35.5% while simultaneously handling 48 samples. We required 60 min to load DNA samples and reagents (Pharmigene PG27) on a 96-well plate, whereas we only required 25 min to load DNA samples and reagents (Pharmigene PG27) on a 96-well plate on the LabTurboTM AIO system.
A major concern in the implementation of a fully automated assay is the potential for the cross-contamination of negative specimens as a consequence of aerosolization, faulty robotics, or robotic errors during the process of nucleic acid extraction for applications in amplification analysis [31]. However, we did not observe any specimen cross-contamination following extraction using the LabTurboTM AIO system.
As mentioned above, the multiplex RT-PCR implemented on the LabTurboTM AIO system offered a high-throughput detection of pathogens with a short turnaround time [5]. The LabTurboTM AIO system utilizes a patented “membrane tube vacuum flow extraction technology” to improve detection sensitivity by producing high-purity and high-yield total nucleic acid [32]. Recently, Jian et al. reported that the LabTurboTM AIO system can handle 864 samples per day in a continuous operation mode [32]. To the best of our knowledge, the present study was the first to detect HLA-B*27 among the Taiwanese population using the LabTurboTM AIO system. The main strength of our study is that it evaluates the performance of the LabTurboTM AIO system for the detection of HLA-B*27, whereas its main drawback is that it did not obtain clinical information about the patients from the physical examination center and, therefore, could not determine the frequency of HLA-B*27 in central Taiwan. Future studies should aim to overcome this limitation by including patients from the outpatient department.

5. Conclusions

In summary, the LabTurboTM AIO system is a fast and reliable technique for HLA-B*27 detection during routine laboratory testing. We have demonstrated the feasibility and reliability of a fully automated molecular analysis of HLA-B*27 with high throughput and significantly less hands-on time by using the LabTurboTM AIO system.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/biomedicines11030986/s1, Figure S1: Flow chart of automation.

Author Contributions

Concept and design of the experiments: Y.-C.C. and T.-K.E. Performance of the experiments: Y.-C.C. and T.-K.E. Data analysis and discussion: Y.-C.C. and T.-K.E. Contribution of reagents/materials/analysis tools: Y.-C.C. and T.-K.E. Manuscript preparation: Y.-C.C. and T.-K.E. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by grants from Asia University and China Medical University Hospital (ASIA-109-51019, ASIA-110-51005, and ASIA-111-51003).

Institutional Review Board Statement

Ethics approval was obtained from the Institution Review Board of China Medical University Hospital (CMUH112-REC2-026) and (CMUH112-REC2-026 (AR-1)).

Informed Consent Statement

The requirement for informed consent from each patient was waived. In this study, we used deidentified samples and no clinical information obtained from the participants.

Data Availability Statement

Not applicable.

Acknowledgments

We would like to thank Yu-Yu Chen (Taigen Bioscience Corp., Taipei city, Taiwan) for his assistance.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Yonekawa, T.; Watanabe, H.; Hosaka, N.; Semba, S.; Shoji, A.; Sato, M.; Hamasaki, M.; Yuki, S.; Sano, S.; Segawa, Y.; et al. Fully Automated Molecular Diagnostic System “Simprova” for Simultaneous Testing of Multiple Items. Sci. Rep. 2020, 10, 5409. [Google Scholar] [CrossRef] [Green Version]
  2. Jonguitud-Borrego, N.; Malci, K.; Anand, M.; Baluku, E.; Webb, C.; Liang, L.; Barba-Ostria, C.; Guaman, L.P.; Hui, L.; Rios-Solis, L. High-throughput and automated screening for COVID-19. Front. Med. Technol. 2022, 4, 969203. [Google Scholar] [CrossRef]
  3. Chang, C.K.; Jian, M.J.; Chung, H.Y.; Lin, J.C.; Hsieh, S.S.; Tang, S.H.; Perng, C.L.; Chen, C.W.; Hung, K.S.; Chang, F.Y.; et al. Clinical Comparative Evaluation of the LabTurbo(TM) AIO((R)) Reverse Transcription-Polymerase Chain Reaction and World Health Organization-Recommended Assays for the Detection of Emerging SARS-CoV-2 Variants of Concern. Infect. Drug Resist. 2022, 15, 595–603. [Google Scholar] [CrossRef] [PubMed]
  4. Chung, H.Y.; Jian, M.J.; Chang, C.K.; Lin, J.C.; Yeh, K.M.; Chen, C.W.; Yang, Y.S.; Hsieh, S.S.; Chen, E.S.; Yang, M.H.; et al. Multicenter study evaluating novel multi-specimen pooling assay for the detection of SARS-CoV-2: High sensitivity and high throughput testing. J. Microbiol. Immunol. Infect. 2022, 55 Pt 1, 1069–1075. [Google Scholar] [CrossRef] [PubMed]
  5. Chung, H.Y.; Jian, M.J.; Chang, C.K.; Lin, J.C.; Yeh, K.M.; Yang, Y.S.; Chen, C.W.; Hsieh, S.S.; Tang, S.H.; Perng, C.L.; et al. Multicenter study evaluating one multiplex RT-PCR assay to detect SARS-CoV-2, influenza A/B, and respiratory syncytia virus using the LabTurbo AIO open platform: Epidemiological features, automated sample-to-result, and high-throughput testing. Aging 2021, 13, 24931–24942. [Google Scholar] [CrossRef]
  6. Klein, J.; Sato, A. The HLA system. First of two parts. N. Engl. J. Med. 2000, 343, 702–709. [Google Scholar] [CrossRef] [PubMed]
  7. Caillat-Zucman, S. Molecular mechanisms of HLA association with autoimmune diseases. Tissue Antigens 2009, 73, 1–8. [Google Scholar] [CrossRef] [PubMed]
  8. Gough, S.C.; Simmonds, M.J. The HLA Region and Autoimmune Disease: Associations and Mechanisms of Action. Curr. Genom. 2007, 8, 453–465. [Google Scholar]
  9. Sims, A.M.; Wordsworth, B.P.; Brown, M.A. Genetic susceptibility to ankylosing spondylitis. Curr. Mol. Med. 2004, 4, 13–20. [Google Scholar] [CrossRef]
  10. Lara-Armi, F.F.; Visentainer, J.E.L.; Alves, H.V.; Rocha-Loures, M.A.; Neves, J.S.F.; Colli, C.M.; Lima Neto, Q.A.; Moliterno, R.A.; Sell, A.M. Optimization of HLA-B*27 ALLELE Genotyping by PCR-SSP. Clinics 2020, 75, e1840. [Google Scholar] [CrossRef]
  11. Priyathersini, N.; Shanmugam, S.G.; Devi, S.S.; Chinambedu Dandapani, M.P.; Rajendiran, S.; D’Cruze, L. Detection of Human Leukocyte Antigen B27 by Flowcytometry in Patients With Suspected Ankylosing Spondylitis in a Tertiary Care Centre. Cureus 2021, 13, e13560. [Google Scholar]
  12. Fraile, A.; Martin, J.; Lopez-Nevot, M.A.; Mataran, L.; Nieto, A. HLA-B*27 subtyping by PCR-RFLP in Spanish patients with ankylosing spondylitis. Tissue Antigens 1998, 52, 492–496. [Google Scholar] [CrossRef]
  13. Kim, S.Y.; Chang, H.E.; Song, S.H.; Park, K.U.; Song, J. Rapid genotyping of HLA-B27 among Korean population by real-time PCR melting curve analysis. Clin. Chim. Acta 2011, 412, 1912–1917. [Google Scholar] [CrossRef] [PubMed]
  14. Geiger, K.; Zach, C.; Leiherer, A.; Fraunberger, P.; Drexel, H.; Muendlein, A. Real-time PCR based HLA-B*27 screening directly in whole blood. HLA 2020, 95, 189–195. [Google Scholar] [CrossRef]
  15. Chen, S.Y.; Chou, Y.C.; Huang, J.W.; Er, T.K. Comparison of Manual and Automated Nucleic Acid Extraction Methods in Virus Transport Medium. Clin. Lab. 2021, 67. [Google Scholar] [CrossRef] [PubMed]
  16. Seaberg, R.S.; Stallone, R.O.; Statland, B.E. The role of total laboratory automation in a consolidated laboratory network. Clin. Chem. 2000, 46, 751–756. [Google Scholar] [CrossRef] [Green Version]
  17. Lippi, G.; Da Rin, G. Advantages and limitations of total laboratory automation: A personal overview. Clin. Chem. Lab. Med. 2019, 57, 802–811. [Google Scholar] [CrossRef]
  18. Lou, A.H.; Elnenaei, M.O.; Sadek, I.; Thompson, S.; Crocker, B.D.; Nassar, B. Evaluation of the impact of a total automation system in a large core laboratory on turnaround time. Clin. Biochem. 2016, 49, 1254–1258. [Google Scholar] [CrossRef] [PubMed]
  19. Nieto, A.; Fraile, A.; Vinasco, J.; Martin, J. HLA-B*27 typing by PCR-restriction fragment length polymorphism. Tissue Antigens 1997, 49 Pt 1, 283–286. [Google Scholar] [CrossRef] [PubMed]
  20. Gunal, E.K.; Sarvan, F.O.; Kamali, S.; Gul, A.; Inanc, M.; Carin, M.; Konice, M.; Aral, O.; Ocal, L. Low frequency of HLA-B27 in ankylosing spondylitis patients from Turkey. Jt. Bone Spine 2008, 75, 299–302. [Google Scholar] [CrossRef] [PubMed]
  21. Yang, W.; Kang, X.; Yang, Q.; Lin, Y.; Fang, M. Review on the development of genotyping methods for assessing farm animal diversity. J. Anim. Sci. Biotechnol. 2013, 4, 2. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Tiemann, C.; Vogel, A.; Dufaux, B.; Zimmer, M.; Krone, J.R.; Hagedorn, H.J. Rapid DNA typing of HLA-B27 allele by real-time PCR using lightcycler technology. Clin. Lab. 2001, 47, 131–134. [Google Scholar] [PubMed]
  23. Cho, E.H.; Lee, S.G.; Seok, J.H.; Park, B.Y.; Lee, E.H. Evaluation of two commercial HLA-B27 real-time PCR kits. Korean J. Lab. Med. 2009, 29, 589–593. [Google Scholar] [CrossRef] [PubMed]
  24. Intharanut, K.; Ruanthong, F.; Chidtrakoon, S.; Nathalang, O. Comparative Analysis of a Developed Probe-Based Real-Time PCR and PCR-SSP for HLA-B*27 Detection among Thai Blood Donors. Clin. Lab. 2022, 68. [Google Scholar] [CrossRef] [PubMed]
  25. Roelandse-Koop, E.A.; Buisman, B.; van Hannen, E.J.; van der Zee, A.; Kortlandt, W.; Hermans, M.H.; van Houte, A.J.; van Rhee-Luderer, R. Rapid HLA-B27 screening with real-time TaqMan PCR: A clinical validation in the Dutch population. Clin. Chem. Lab. Med. 2011, 49, 1979–1985. [Google Scholar] [CrossRef] [PubMed]
  26. Seo, B.Y.; Won, D.I. Flow cytometric human leukocyte antigen-B27 typing with stored samples for batch testing. Ann. Lab. Med. 2013, 33, 174–183. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Skalska, U.; Kozakiewicz, A.; Maslinski, W.; Jurkowska, M. HLA-B27 detection-comparison of genetic sequence-based method and flow cytometry assay. Reumatologia 2015, 53, 74–78. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Waeckel, L.; Kennel, A.; Berger, A.E.; Lambert, C. Human leukocyte antigen-B27 typing by flow cytometry: Comparison of three CE-IVD methods. Cytom. B Clin. Cytom. 2022, 1–8. [Google Scholar] [CrossRef]
  29. Afshan, N.; Bashir, M.; Tipu, H.N.; Hussain, M. Optimization of an in-house PCR method for the detection of HLA-B*27 alleles. Biomed. Rep. 2018, 8, 385–390. [Google Scholar] [CrossRef] [Green Version]
  30. Carpi, F.M.; Di Pietro, F.; Vincenzetti, S.; Mignini, F.; Napolioni, V. Human DNA extraction methods: Patents and applications. Recent Pat DNA Gene Seq. 2011, 5, 1–7. [Google Scholar] [CrossRef]
  31. Knepp, J.H.; Geahr, M.A.; Forman, M.S.; Valsamakis, A. Comparison of automated and manual nucleic acid extraction methods for detection of enterovirus RNA. J. Clin. Microbiol. 2003, 41, 3532–3536. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Jian, M.J.; Chung, H.Y.; Chang, C.K.; Lin, J.C.; Yeh, K.M.; Chiu, S.K.; Wang, Y.H.; Liao, S.J.; Li, S.Y.; Hsieh, S.S.; et al. Novel automated sample-to-result SARS-CoV-2 laboratory-developed RT-PCR assay for high-throughput testing using LabTurbo AIO 48 system. Clin. Chim. Acta 2021, 514, 54–58. [Google Scholar] [CrossRef] [PubMed]
Biomedicines 11 00986 g001 550
Figure 1. Ct value of the distribution of target genes of MaelstromTM 8 and LabTurboTM AIO system when analyzing the clinical samples. Box plots illustrate the median value and interquartile range, and whiskers represent the nearest value to 1.5 times IQR. Outliers are plotted separately. IC (internal control), PG27 (HLA-B*27).
Figure 1. Ct value of the distribution of target genes of MaelstromTM 8 and LabTurboTM AIO system when analyzing the clinical samples. Box plots illustrate the median value and interquartile range, and whiskers represent the nearest value to 1.5 times IQR. Outliers are plotted separately. IC (internal control), PG27 (HLA-B*27).
Biomedicines 11 00986 g001
Table
Table 1. Detected and undetected results on the semi-automated and fully automated assay.
Table 1. Detected and undetected results on the semi-automated and fully automated assay.
Semi-Automated
Fully AutomatedPositiveNegativeTotal
Positive20020
Negative03030
Total203050
Table
Table 2. Sequential flow of manual steps and the time required for each step in the detection of HLA-B*27.
Table 2. Sequential flow of manual steps and the time required for each step in the detection of HLA-B*27.
StepActivityTypeComplexityDuration
1DNA extraction
(MaelstromTM 8)		Semi-automatedMedium110 min
2DNA quantification and concentration adjustment
(MaestroNano® Pro Spectrophotometer)		Semi-automatedMedium40 min
3Load samples and reagents (Pharmigene PG27) on 96-wellManualHigh60 min
4Real-time PCR (Z480)AutomatedLow85 min
5Test results verificationManualLow15 min
Table
Table 3. Sequential flow of automated steps and the time required for each step in the detection of HLA-B*27.
Table 3. Sequential flow of automated steps and the time required for each step in the detection of HLA-B*27.
StepActivityTypeComplexityDuration
1DNA extraction
(LabTurboTM AIO system)		AutomatedMedium80 min
2DNA quantification and concentration adjustment
(MaestroNano® Pro Spectrophotometer)		Semi-automatedMedium20 min
3Load samples and reagents (Pharmigene PG27) on 96-well(LabTurboTM AIO system)AutomatedLow25 min
4Real-time PCR (LabTurboTM AIO system)AutomatedLow70 min
5Test results verification
(LabTurboTM AIO system)		AutomatedLow5 min
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chou, Y.-C.; Er, T.-K. High-Throughput and Automated Detection of HLA-B*27 Using the LabTurboTM AIO System. Biomedicines 2023, 11, 986. https://doi.org/10.3390/biomedicines11030986

AMA Style

Chou Y-C, Er T-K. High-Throughput and Automated Detection of HLA-B*27 Using the LabTurboTM AIO System. Biomedicines. 2023; 11(3):986. https://doi.org/10.3390/biomedicines11030986

Chicago/Turabian Style

Chou, Yung-Che, and Tze-Kiong Er. 2023. "High-Throughput and Automated Detection of HLA-B*27 Using the LabTurboTM AIO System" Biomedicines 11, no. 3: 986. https://doi.org/10.3390/biomedicines11030986

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop