Optimizing Antigen Preparation for Oxalyl-CoA Decarboxylase Enzyme Diagnostic Kit and ELISA System Cutoff Determination

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Oxalyl-CoA decarboxylase (OXC), an enzyme produced by the gut bacterium Oxalobacter formigenes, plays a crucial role in oxalate metabolism. Deficiencies in OXC activity can lead to the accumulation of oxalate, contributing to kidney stone formation. This study aimed to develop a reliable diagnostic assay for OXC by optimizing antigen production and establishing a cutoff value for an enzyme-linked immunosorbent assay (ELISA). We cloned, expressed, and purified recombinant OXC protein in Escherichia coli BL21(DE3), and generated specific polyclonal antibodies in rabbits. The ELISA system was optimized and validated using serum samples from 40 healthy individuals and 6 patients with oxalate-related disorders. The cutoff value was determined using the formula ( M + 2SD ), where ( M ) is the mean and ( SD ) is the standard deviation of the healthy sample results. The calculated cutoff value of 0.656750 effectively distinguished between healthy and affected individuals, with a sensitivity of 97.5% and a specificity of 83.3%. These findings provide a valuable tool for the early detection and management of oxalate-related disorders, with significant implications for clinical practice. oxalyl coA decarboxylase ELISA cut off Figures Figure 1 Introduction The prevalence of kidney stone disease is rising worldwide, with evidence indicating an increase in incidence and prevalence across gender, ethnicity, and age categories. Changes in eating choices and the consequences of global warming are thought to be major influences on this trend( 1 ). Risk factors for kidney stones include dehydration, dietary factors (high protein, sodium, low water, fruits, and vegetables), family or personal history of kidney stones, medical conditions (hypercalciuria, hyperoxaluria, etc.), obesity, certain medications, digestive diseases or surgeries, sedentary lifestyle, and urinary tract abnormalities( 2 ). Calcium oxalate stones are the most common type of kidney stone, accounting for up to 75% of all kidney stones formed. Oxalate is a natural substance found in many foods, and when there is too much oxalate in the urine, crystals can form and stick together to form a solid mass( 3 ). Oxalyl-CoA decarboxylase catalyzes the conversion of oxalyl-CoA into formyl-CoA and CO2, hence aiding in the breakdown of oxalate. This enzyme is largely generated by the gut bacterium Oxalobacter formigenes and is required for oxalate catabolism( 4 ). Deficiencies in OXC activity can cause oxalate and its precursor oxalyl-CoA to build up, contributing to the production of calcium oxalate kidney stones( 5 ). Research has shown that Oxalobacter formigenes, a bacterium capable of breaking down oxalate through OXC, is associated with a reduced risk of calcium oxalate urinary stones. One study found that people lacking this bacteria had higher urinary oxalate concentrations and an increased risk of kidney stone formation( 6 ). Oxalobacter formigenes is a Gram-negative anaerobic bacterium involved in oxalate metabolism in the gut. Previous studies have focused on the potential of Oxalobacter formigenes in reducing the risk of kidney stones. Of course, it is mentioned that this bacterium is not an ideal probiotic due to its antibiotic sensitivity and low pH( 7 ). The development of diagnostic approaches based on recombinant OXC protein and ELISA assays has made it possible to detect OXC deficits in people who are prone to calcium oxalate kidney stones. The expression of recombinant OXC in E. coli has been optimized as a method of producing the enzyme for use in oxalate-level detection kits. Researchers have developed OXC-based diagnostic approaches for detecting and measuring oxalate levels in individuals with calcium oxalate kidney stones. A study describes cloning and expressing the OXC gene from Bifidobacterium lactis, as well as using the purified recombinant OXC protein to create antigene for an ELISA assay. This ELISA system was later utilized to examine serum samples from patients with calcium oxalate kidney stones, which revealed that 88.8% of the patients lacked OXC antigen ( 8 ). A different study enhanced recombinant OXC expression in E. coli to achieve high amounts of the enzyme, with the intention of employing it in diagnostic kits to assess oxalate levels. The authors claimed that high levels of OXC expression can be attained by adjusting culture conditions such as medium, temperature, induction period, and inducer concentration( 9 ). Despite increased interest in OXC as a diagnostic biomarker, developing effective diagnostic tests presents major obstacles, notably in antigen synthesis and assay tuning. Antigen preparation is an important phase in the development of diagnostic kits, as it influences the assay's specificity, sensitivity, and reliability. Furthermore, proper cutoff values for ELISA systems are required to distinguish between positive and negative test findings, assuring diagnostic accuracy. In this respect, this work seeks to address these issues by improving the antigen production process for an OXC enzyme diagnostic kit and defining the cutoff value for an ELISA system. Our goal is to develop the most effective methods for antigen selection, extraction, purification, and validation. Additionally, by experimental validation, we hope to determine the best cutoff value for the ELISA system, taking into account critical performance parameters including sensitivity, specificity, and accuracy. Material and Method Preparation of Competent Cells: The aim of this section is to acquire the skills necessary for preparing competent bacterial cells such that the bacteria remain viable and can uptake plasmid DNA. The process involves cold treatment, calcium chloride, and subsequent heat shock to induce changes on the cell surface, allowing plasmid DNA to enter through the created pores. A single colony of engineered E. coli strain BL21 (DE3) without kanamycin resistance was cultured in 3 mL of LB medium. The culture was incubated overnight at 37°C with shaking at 200 rpm. The next day, 1 mL of the overnight culture was subcultured into 10 mL of fresh LB medium. The subculture was incubated at 37°C with shaking at 200 rpm until the optical density at 600 nm (OD600) reached 0.6. One milliliter of the bacterial culture was transferred to a microcentrifuge tube and placed on ice for 10 minutes. The cells were centrifuged at 3500 rpm for 5 minutes, and the supernatant was discarded. The pellet was resuspended in one-third of the initial volume of 100 mM CaCl2 solution and placed on ice for 10 minutes. The cells were centrifuged again, and the supernatant was discarded. The pellet was resuspended in one- twelve and a half of the initial volume of 100 mM CaCl2 solution to prepare for transformation. Transformation (Plasmid DNA Transfer to Live Bacteria): The competent cells were kept on ice, and 5 ng of plasmid pET28 b containing the oxalyl-CoA decarboxylase gene ( 8 ) was added. The mixture was incubated on ice for 30 minutes. The cells were subjected to a heat shock at 42°C for 40 seconds and then returned to ice for 2 minutes. Two hundred microliters of LB medium (without antibiotics) was added, and the cells were incubated at 37°C for 40–60 minutes to allow for two to three generations of growth. The transformation mixture was plated on LB agar plates for colony formation. Protein Expression: A single colony of bacteria containing the recombinant plasmid was cultured in 2–3 mL of LB medium with kanamycin (50 µg per mL) in a screw-cap tube. The culture was incubated overnight at 37°C with shaking at 200 rpm. The next day, the culture was subcultured and incubated until the OD reached 0.7. The plasmid promoter was induced with 1 mM IPTG, and samples were collected every two hours. The samples were placed on ice and sonicated. Twice the volume of cold acetone was added, and the mixture was kept in the freezer for at least two hours to overnight. The contents were centrifuged at 8000 rpm for 5 minutes, the supernatant was discarded, and the acetone was allowed to evaporate at room temperature. The samples were electrophoresed on an SDS-PAGE gel alongside a control sample from bacteria without the plasmid. Protein Purification (Enzyme): The plasmid pET28b contains a histidine tag at the N-terminus of the protein for purification using Ni-NTA chromatography. The cell pellet from the previous step was added to the chromatography column, which was inverted several times and incubated in the refrigerator for at least one hour to overnight. The column was washed with buffer, and elution buffer containing imidazole was added. The column was inverted several times and incubated for 30 minutes to 1 hour in the refrigerator. The column was placed on a stand, and the liquid was passed through the column several times, collecting the eluate containing the purified protein. Injection of Purified Target Protein into Rabbits: To generate antibodies, oxalyl-CoA decarboxylase protein was injected into three female rabbits. The first injection was with complete Freund’s adjuvant, and the subsequent two injections were without adjuvant. One week after the third injection, blood was collected from the rabbits’ ears, and serum was separated. IgG was purified from the serum using a protein A column. Injection of Target Protein into Laboratory Mice: To avoid interference in experiments, serum containing anti-oxalyl-CoA antibodies was injected into BALB/c mice, and serum was collected for use as an antigen (serum containing anti-oxalyl-CoA antibodies). ELISA Procedure: In the ELISA method, an antigen-antibody complex is formed. Initially, the mouse antibody was coated onto the ELISA plate. Remaining binding sites were blocked with an appropriate protein solution. Human serum was added to allow antigen-antibody binding. Rabbit antibody was then added, followed by a conjugated secondary antibody that produced color, which was measured using an ELISA reader. Coating Antibody on ELISA Plate: Concentrations of 0.25, 0.5, 0.75, 1.0, and 1.5 µg/mL of purified mouse IgG were prepared in coating buffer and 100 µL was added to each well of the plate. The plate was incubated overnight in the refrigerator. The next day, the wells were emptied, washed three times with wash buffer, and dried on clean paper towels. Three hundred microliters of blocking solution was added to each well and incubated for 1-1.5 hours at room temperature. The wells were emptied and washed again. Human serum samples (from healthy and diseased individuals) were added to the corresponding wells and incubated for 2–3 hours at room temperature. The wells were emptied and washed again. Purified rabbit IgG at the same concentration as the initial coating was prepared in coating buffer and 100 µL was added to each well. The plate was incubated for 2–3 hours at room temperature. The wells were emptied and washed again. A 1:10000 dilution of conjugate solution (100 µL) was added to each well and incubated for 1 hour in the dark at room temperature. The wells were emptied and washed again. One hundred microliters of TMB substrate solution was added to each well and incubated for 15 minutes in the dark. Finally, 50 µL of stop solution was added to each well, and the plate was read at 492 nm using an ELISA reader. These steps were repeated over 20 times with various antibody and serum dilutions to optimize the conditions and timing. To determine the cutoff value for the ELISA system, the assay is performed on 40 healthy people and 6 sick people samples, preferably from individuals over 40 years old, using the described method. Any results that are significantly higher or lower than the majority are excluded, and the cutoff rate is calculated using the formula M + 2SD, where M is the mean and SD is the standard deviation. This approach ensures the accuracy and reliability of the ELISA assay in distinguishing between positive and negative samples. Results In this project, the serum of 40 healthy people and 6 sick people were used (serum of sick people were used in this project so that it is clear that the system works correctly). The samples have been checked in the order (ELISA plate) of the table below. 0 1 2 3 4 5 6 7 8 9 10 11 12 A 1.327 1.338 1.354 1.223 1.119 1.1 0.885 0.872 1.129 1.282 0.253 3.64 B 1.292 1.274 1.212 1.164 0.855 0.849 0.994 0.89 0.401 0.316 0.175 0.246 C 1.262 1.391 1.271 1.284 1.143 1.182 1.194 0.907 0.890 0.922 0.280 0.356 D 1.207 1.193 1.032 1.136 1.102 1.097 0.972 0.893 1.103 0.985 0.433 0.321 E 1.37 1.363 1.298 1.284 1.005 1.05 0.935 0.957 0.943 0.986 0.243 0.202 F 1.427 1.295 1.223 1.103 1.155 1.072 0.843 0.837 1.245 1.445 0.526 0.421 G 1.539 1.445 1.277 1.122 1.228 1.128 0.988 1.038 1.087 1.267 0.120 0.01 H 1.123 1.331 1.3 1.302 1.13 1.095 1.067 1.054 1.264 1.389 0.127 0.190 Columns 1–3, 5-7-9, serum of healthy people (columns 2-4-6-8-10 repeat previous columns) with rows A, B, C, D, E, F, G, H Columns 11 and 12 with rows A, B, C, D, E, F of sick people's serum (suffering from kidney stones) in duplicate Samples description Count Mean SD Minimum Maximum group control outcome 40 1.1256 .2036 .3585 1.4920 case outcome 6 .5913 .6711 .2105 1.9465 AUC p-value Asymptotic 95% Confidence Interval Lower Bound Upper Bound .825 .011 .529 1.000 Area Under Curve (AUC): The AUC is calculated as 0.825, which indicates the discriminatory power of the test. The p-value associated with the analysis is 0.011, suggesting statistical significance. Control if Greater Than or Equal To Sensitivity 1 - Specificity .656750 .975 .167 Larger values of the test result variable(s) indicate stronger evidence for a control state and this table shows a cut off value: Control if Greater Than or Equal To 0.656750 Discussion Kidney stone disease is a common and debilitating condition affecting millions of people worldwide. Oxalate, a key component of kidney stones, is a major risk factor for stone formation( 10 ). Oxalyl-CoA decarboxylase (OXC) is a crucial enzyme involved in the metabolism of oxalate, a key component of kidney stones. This enzyme produced by Oxalobacter formigenes, a bacterium that colonizes the gut, plays a significant role in the catabolism of oxalate, which is linked to kidney stone formation( 11 ). The development of a reliable diagnostic kit for OXC enzyme activity is essential for the early detection and management of oxalate-related disorders( 8 ). The assessment of OXC enzyme activity is crucial for understanding the role of Oxalobacter formigenes in oxalate metabolism and identifying individuals at risk of kidney stone disease. Measuring OXC enzyme activity can help identify individuals with impaired oxalate metabolism( 12 ). Assessing OXC enzyme activity is valuable for monitoring the effectiveness of treatments aimed at reducing urinary oxalate levels( 13 ). This emphasizes the significance of OXC enzyme activity assessment in managing oxalate-related disorders and optimizing treatment strategies for individuals at risk of kidney stone formation. Despite its importance, there is currently no commercially available kit for assessing OXC enzyme activity. The development of a reliable and sensitive diagnostic kit is essential for early detection and prevention of kidney stone disease. Enzyme-linked immunosorbent assay (ELISA) is a widely used technique for detecting enzyme activity, but its accuracy relies heavily on the quality of the antigen preparation. Antigen preparation is a crucial aspect of developing an ELISA system, directly influencing the assay's sensitivity and specificity. Research has emphasized the significance of optimizing antigen preparation methods to enhance the performance of ELISA-based diagnostic kits. For example, studies have shown that utilizing recombinant antigens can significantly improve the sensitivity and specificity of ELISA assays compared to conventional antigen preparation techniques( 8 ). Determining the cutoff value for the ELISA system is essential for accurate result interpretation. Importance of setting an appropriate cutoff value using statistical methods like receiver operating characteristic (ROC) curve analysis is to optimize the assay's sensitivity and specificity. This approach helps minimize false-positive and false-negative results, ensuring the reliability of the diagnostic test. In this study, we develop and validate an enzyme-linked immunosorbent assay (ELISA) for the detection and quantification of OXC. We optimize the ELISA conditions and determine the cutoff value for the assay using healthy samples. The results of this study provide a valuable tool for the detection and quantification of OXC, which can be used in various applications, including research, diagnosis, and monitoring of diseases related to oxalate metabolism. The development of a sensitive and specific ELISA assay for OXC has significant implications for clinical practice, enabling the detection and quantification of the enzyme in various biological samples, including serum, urine. This assay can be used for the diagnosis and monitoring of oxalate-related disorders, such as primary hyperoxaluria, enteric hyperoxaluria, and oxalosis. Early detection and quantification of OXC can help identify individuals at risk of developing these disorders, allowing for timely intervention and treatment. Additionally, the assay can be used to monitor the efficacy of treatment strategies aimed at reducing oxalate levels or enhancing OXC activity. The ELISA assay can also be used to identify individuals with impaired OXC activity, which may be associated with an increased risk of kidney stone formation. Early identification of these individuals can lead to targeted interventions, such as increased fluid intake, dietary modifications, and pharmacological therapy, to reduce the risk of stone formation. There are several limitations that need to be addressed in future studies. These include the development of monoclonal antibodies or antibodies against specific epitopes to improve the assay's specificity and sensitivity, validation of the assay in larger cohorts and diverse populations, automation of the assay to improve its throughput and reproducibility, and investigation of the correlation between OXC activity and oxalate levels in biological samples. In this study, we aimed to address the challenges in developing effective diagnostic tests for oxalyl-CoA decarboxylase (OXC) by improving antigen production and defining the cutoff value for an ELISA system. Our results provide significant insights into the optimization of diagnostic assays for oxalate-related disorders. The use of a well-defined cutoff value ensures that the diagnostic test is both reliable and reproducible, making it a valuable tool for clinicians. While the current study has made substantial progress in optimizing the diagnostic assay for OXC, further research is needed to validate these findings in larger and more diverse populations. Additionally, exploring the potential of combining OXC detection with other biomarkers could enhance the diagnostic accuracy and provide a more comprehensive understanding of oxalate metabolism disorders. This holistic approach could lead to improved management strategies for patients suffering from these challenging conditions. Conclusion In this study, we developed a cut off for the detection of oxalyl-CoA decarboxylase (OXC) by ELISA system. Declarations Acnowledgement: The present study was carried out in the Cellular & Molecular Biology Research Center of Shahid Beheshti University of Medical Sciences, Tehran, Iran. and supported by Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran through Grant No 898 Funding This work was supported by the Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran, through Grant No. 898. The authors declare that no additional funds, grants, or other support were received during the preparation of this manuscript. Competing Interests The authors declare that they have no relevant financial or non-financial interests to disclose. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Davood Khavari Ardestani, Abbas Basiri, Mojgan Bandehpour, Afshin Abdi-Ghavidel, and Bahram Kazemi. The first draft of the manuscript was written by Davood Khavari Ardestani, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Ethics Approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Shahid Beheshti University of Medical Sciences (IR.SBMU.UNRC.REC.1401.035). Consent to Participate Informed consent was obtained from all individual participants included in the study. Consent to Publish The authors affirm that human research participants provided informed consent for the publication of the data included in this manuscript. Conflict of interest: The authors declare no conflict of interest. Data Availability Data supporting the findings of this study are provided within the manuscript file. References Stamatelou K, Goldfarb DS (2023) Epidemiology of Kidney Stones. Healthc (Basel). ;11(3) Shin S, Srivastava A, Alli NA, Bandyopadhyay BC (2018) Confounding risk factors and preventative measures driving nephrolithiasis global makeup. World J Nephrol 7(7):129–142 Elshal AM, Shamshoun H, Awadalla A, Elbaz R, Ahmed AE, El-Khawaga OY, Shokeir AA (2023) Hormonal and molecular characterization of calcium oxalate stone formers predicting occurrence and recurrence. Urolithiasis 51(1):76 Lung HY, Cornelius JG, Peck AB (1991) Cloning and expression of the oxalyl-CoA decarboxylase gene from the bacterium, Oxalobacter formigenes: prospects for gene therapy to control Ca-oxalate kidney stone formation. Am J Kidney Dis 17(4):381–385 Youssef HIA (2024) Detection of oxalyl-CoA decarboxylase (oxc) and formyl-CoA transferase (frc) genes in novel probiotic isolates capable of oxalate degradation in vitro. Folia Microbiol (Praha) Troxel SA, Sidhu H, Kaul P, Low RK (2003) Intestinal Oxalobacter formigenes colonization in calcium oxalate stone formers and its relation to urinary oxalate. J Endourol 17(3):173–176 Wigner P, Bijak M, Saluk-Bijak J (2022) Probiotics in the prevention of the calcium oxalate urolithiasis. Cells 11(2):284 Abarghooi-Kahaki F, Basiri A, Bandehpour M, Kazemi B (2019) Designing a diagnostic kit for Oxalyl CoA Decarboxylase enzyme by ELISA method. Immunol Lett 205:78–83 Kahaki FA, Dehnavi SM (2022) Expression Optimizing of Recombinant Oxalyl-CoA Decarboxylase in Escherichia coli. Adv Biomedical Res 11(1):110 Mitchell T, Kumar P, Reddy T, Wood KD, Knight J, Assimos DG, Holmes RP (2019) Dietary oxalate and kidney stone formation. Am J Physiol Ren Physiol 316(3):F409–f13 Sheng X, Liu Y, Zhang R (2014) A theoretical study of the catalytic mechanism of oxalyl-CoA decarboxylase, an enzyme for treating urolithiasis. RSC Adv 4(67):35777–35788 Jiang T, Chen W, Cao L, He Y, Zhou H, Mao H (2020) Abundance, Functional, and Evolutionary Analysis of Oxalyl-Coenzyme A Decarboxylase in Human Microbiota. Front Microbiol 11:672 Zhao C, Yang H, Zhu X, Li Y, Wang N, Han S et al (2017) Oxalate-Degrading Enzyme Recombined Lactic Acid Bacteria Strains Reduce Hyperoxaluria. Urology. ;113 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 Oct, 2024 Read the published version in Urolithiasis → Version 1 posted Editorial decision: Revision requested 09 Sep, 2024 Reviews received at journal 04 Jul, 2024 Reviewers agreed at journal 01 Jul, 2024 Reviewers invited by journal 30 Jun, 2024 Editor assigned by journal 15 Jun, 2024 Submission checks completed at journal 15 Jun, 2024 First submitted to journal 11 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4564741","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321411552,"identity":"cf56fdbf-240b-49cb-ac94-eba115e06bbc","order_by":0,"name":"Davood Khavari Ardestani","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences (SBMU)","correspondingAuthor":false,"prefix":"","firstName":"Davood","middleName":"Khavari","lastName":"Ardestani","suffix":""},{"id":321411553,"identity":"443f1fcc-5ace-4376-b9bb-13246a8d604e","order_by":1,"name":"Abbas Basiri","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences (SBMU)","correspondingAuthor":false,"prefix":"","firstName":"Abbas","middleName":"","lastName":"Basiri","suffix":""},{"id":321411554,"identity":"bb396eb9-d850-4203-84d5-9203557f5d18","order_by":2,"name":"Mojgan Bandehpour","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mojgan","middleName":"","lastName":"Bandehpour","suffix":""},{"id":321411555,"identity":"9ebd376b-eff6-4398-8bdf-f713764922a9","order_by":3,"name":"Afshin Abdi-Ghavidel","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Afshin","middleName":"","lastName":"Abdi-Ghavidel","suffix":""},{"id":321411556,"identity":"c2fc3df2-4c57-4eed-b166-17e7decdcaf0","order_by":4,"name":"Bahram Kazemi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYBACAwYeMM3D2N7AwEySFhnmngMkarFhn5FApBZz9rPHPvzMYeDhnfnG8HNBhQ0Df3t3Al4tlj15yTN7tzHwSM7OMZaecSaNQeLM2Q34HXYgx5iBF6jFcHaOgTRv22EGA4lcAlrOvzFm/AvUYn/zjPFv4rTcyDFmBtnCOIPHjDhbLGe8MWaWBWnpSSuz5jmTxkPQL+b8OcaMb7cx2DO2H958m6fCRo6/vRe/Fij4D8QcBiAWDzHKYYD9ASmqR8EoGAWjYAQBAO9IQCpXX+/cAAAAAElFTkSuQmCC","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Bahram","middleName":"","lastName":"Kazemi","suffix":""}],"badges":[],"createdAt":"2024-06-11 14:10:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4564741/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4564741/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00240-024-01635-7","type":"published","date":"2024-10-09T15:58:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60337751,"identity":"385004c3-dc8e-478d-8d2b-a6e32d602cd1","added_by":"auto","created_at":"2024-07-15 17:41:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9103,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eELISA plate well coated by antigen - antibody\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4564741/v1/043e9643ce5c28ca8d94604a.png"},{"id":66597879,"identity":"0a92beac-b819-4117-aabb-1cb785782f03","added_by":"auto","created_at":"2024-10-14 16:11:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":483578,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4564741/v1/5787430b-d9f7-467b-8155-6e341f7c296e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimizing Antigen Preparation for Oxalyl-CoA Decarboxylase Enzyme Diagnostic Kit and ELISA System Cutoff Determination","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe prevalence of kidney stone disease is rising worldwide, with evidence indicating an increase in incidence and prevalence across gender, ethnicity, and age categories. Changes in eating choices and the consequences of global warming are thought to be major influences on this trend(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRisk factors for kidney stones include dehydration, dietary factors (high protein, sodium, low water, fruits, and vegetables), family or personal history of kidney stones, medical conditions (hypercalciuria, hyperoxaluria, etc.), obesity, certain medications, digestive diseases or surgeries, sedentary lifestyle, and urinary tract abnormalities(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCalcium oxalate stones are the most common type of kidney stone, accounting for up to 75% of all kidney stones formed. Oxalate is a natural substance found in many foods, and when there is too much oxalate in the urine, crystals can form and stick together to form a solid mass(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOxalyl-CoA decarboxylase catalyzes the conversion of oxalyl-CoA into formyl-CoA and CO2, hence aiding in the breakdown of oxalate. This enzyme is largely generated by the gut bacterium Oxalobacter formigenes and is required for oxalate catabolism(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDeficiencies in OXC activity can cause oxalate and its precursor oxalyl-CoA to build up, contributing to the production of calcium oxalate kidney stones(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch has shown that Oxalobacter formigenes, a bacterium capable of breaking down oxalate through OXC, is associated with a reduced risk of calcium oxalate urinary stones. One study found that people lacking this bacteria had higher urinary oxalate concentrations and an increased risk of kidney stone formation(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOxalobacter formigenes is a Gram-negative anaerobic bacterium involved in oxalate metabolism in the gut. Previous studies have focused on the potential of Oxalobacter formigenes in reducing the risk of kidney stones. Of course, it is mentioned that this bacterium is not an ideal probiotic due to its antibiotic sensitivity and low pH(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe development of diagnostic approaches based on recombinant OXC protein and ELISA assays has made it possible to detect OXC deficits in people who are prone to calcium oxalate kidney stones. The expression of recombinant OXC in E. coli has been optimized as a method of producing the enzyme for use in oxalate-level detection kits.\u003c/p\u003e \u003cp\u003eResearchers have developed OXC-based diagnostic approaches for detecting and measuring oxalate levels in individuals with calcium oxalate kidney stones. A study describes cloning and expressing the OXC gene from Bifidobacterium lactis, as well as using the purified recombinant OXC protein to create antigene for an ELISA assay. This ELISA system was later utilized to examine serum samples from patients with calcium oxalate kidney stones, which revealed that 88.8% of the patients lacked OXC antigen (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). A different study enhanced recombinant OXC expression in E. coli to achieve high amounts of the enzyme, with the intention of employing it in diagnostic kits to assess oxalate levels. The authors claimed that high levels of OXC expression can be attained by adjusting culture conditions such as medium, temperature, induction period, and inducer concentration(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite increased interest in OXC as a diagnostic biomarker, developing effective diagnostic tests presents major obstacles, notably in antigen synthesis and assay tuning. Antigen preparation is an important phase in the development of diagnostic kits, as it influences the assay's specificity, sensitivity, and reliability. Furthermore, proper cutoff values for ELISA systems are required to distinguish between positive and negative test findings, assuring diagnostic accuracy.\u003c/p\u003e \u003cp\u003eIn this respect, this work seeks to address these issues by improving the antigen production process for an OXC enzyme diagnostic kit and defining the cutoff value for an ELISA system. Our goal is to develop the most effective methods for antigen selection, extraction, purification, and validation. Additionally, by experimental validation, we hope to determine the best cutoff value for the ELISA system, taking into account critical performance parameters including sensitivity, specificity, and accuracy.\u003c/p\u003e"},{"header":"Material and Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePreparation of Competent Cells:\u003c/h2\u003e \u003cp\u003eThe aim of this section is to acquire the skills necessary for preparing competent bacterial cells such that the bacteria remain viable and can uptake plasmid DNA. The process involves cold treatment, calcium chloride, and subsequent heat shock to induce changes on the cell surface, allowing plasmid DNA to enter through the created pores. A single colony of engineered E. coli strain BL21 (DE3) without kanamycin resistance was cultured in 3 mL of LB medium. The culture was incubated overnight at 37\u0026deg;C with shaking at 200 rpm. The next day, 1 mL of the overnight culture was subcultured into 10 mL of fresh LB medium. The subculture was incubated at 37\u0026deg;C with shaking at 200 rpm until the optical density at 600 nm (OD600) reached 0.6.\u003c/p\u003e \u003cp\u003eOne milliliter of the bacterial culture was transferred to a microcentrifuge tube and placed on ice for 10 minutes. The cells were centrifuged at 3500 rpm for 5 minutes, and the supernatant was discarded. The pellet was resuspended in one-third of the initial volume of 100 mM CaCl2 solution and placed on ice for 10 minutes. The cells were centrifuged again, and the supernatant was discarded. The pellet was resuspended in one- twelve and a half of the initial volume of 100 mM CaCl2 solution to prepare for transformation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTransformation (Plasmid DNA Transfer to Live Bacteria):\u003c/h2\u003e \u003cp\u003eThe competent cells were kept on ice, and 5 ng of plasmid pET28 b containing the oxalyl-CoA decarboxylase gene (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) was added. The mixture was incubated on ice for 30 minutes. The cells were subjected to a heat shock at 42\u0026deg;C for 40 seconds and then returned to ice for 2 minutes. Two hundred microliters of LB medium (without antibiotics) was added, and the cells were incubated at 37\u0026deg;C for 40\u0026ndash;60 minutes to allow for two to three generations of growth. The transformation mixture was plated on LB agar plates for colony formation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eProtein Expression:\u003c/h2\u003e \u003cp\u003eA single colony of bacteria containing the recombinant plasmid was cultured in 2\u0026ndash;3 mL of LB medium with kanamycin (50 \u0026micro;g per mL) in a screw-cap tube. The culture was incubated overnight at 37\u0026deg;C with shaking at 200 rpm. The next day, the culture was subcultured and incubated until the OD reached 0.7. The plasmid promoter was induced with 1 mM IPTG, and samples were collected every two hours. The samples were placed on ice and sonicated. Twice the volume of cold acetone was added, and the mixture was kept in the freezer for at least two hours to overnight. The contents were centrifuged at 8000 rpm for 5 minutes, the supernatant was discarded, and the acetone was allowed to evaporate at room temperature. The samples were electrophoresed on an SDS-PAGE gel alongside a control sample from bacteria without the plasmid.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eProtein Purification (Enzyme):\u003c/h2\u003e \u003cp\u003eThe plasmid pET28b contains a histidine tag at the N-terminus of the protein for purification using Ni-NTA chromatography. The cell pellet from the previous step was added to the chromatography column, which was inverted several times and incubated in the refrigerator for at least one hour to overnight. The column was washed with buffer, and elution buffer containing imidazole was added. The column was inverted several times and incubated for 30 minutes to 1 hour in the refrigerator. The column was placed on a stand, and the liquid was passed through the column several times, collecting the eluate containing the purified protein.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eInjection of Purified Target Protein into Rabbits:\u003c/h2\u003e \u003cp\u003eTo generate antibodies, oxalyl-CoA decarboxylase protein was injected into three female rabbits. The first injection was with complete Freund\u0026rsquo;s adjuvant, and the subsequent two injections were without adjuvant. One week after the third injection, blood was collected from the rabbits\u0026rsquo; ears, and serum was separated. IgG was purified from the serum using a protein A column.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eInjection of Target Protein into Laboratory Mice:\u003c/h2\u003e \u003cp\u003eTo avoid interference in experiments, serum containing anti-oxalyl-CoA antibodies was injected into BALB/c mice, and serum was collected for use as an antigen (serum containing anti-oxalyl-CoA antibodies).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eELISA Procedure:\u003c/h2\u003e \u003cp\u003eIn the ELISA method, an antigen-antibody complex is formed. Initially, the mouse antibody was coated onto the ELISA plate. Remaining binding sites were blocked with an appropriate protein solution. Human serum was added to allow antigen-antibody binding. Rabbit antibody was then added, followed by a conjugated secondary antibody that produced color, which was measured using an ELISA reader.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCoating Antibody on ELISA Plate:\u003c/h2\u003e \u003cp\u003eConcentrations of 0.25, 0.5, 0.75, 1.0, and 1.5 \u0026micro;g/mL of purified mouse IgG were prepared in coating buffer and 100 \u0026micro;L was added to each well of the plate. The plate was incubated overnight in the refrigerator. The next day, the wells were emptied, washed three times with wash buffer, and dried on clean paper towels. Three hundred microliters of blocking solution was added to each well and incubated for 1-1.5 hours at room temperature. The wells were emptied and washed again. Human serum samples (from healthy and diseased individuals) were added to the corresponding wells and incubated for 2\u0026ndash;3 hours at room temperature. The wells were emptied and washed again. Purified rabbit IgG at the same concentration as the initial coating was prepared in coating buffer and 100 \u0026micro;L was added to each well. The plate was incubated for 2\u0026ndash;3 hours at room temperature. The wells were emptied and washed again. A 1:10000 dilution of conjugate solution (100 \u0026micro;L) was added to each well and incubated for 1 hour in the dark at room temperature. The wells were emptied and washed again. One hundred microliters of TMB substrate solution was added to each well and incubated for 15 minutes in the dark. Finally, 50 \u0026micro;L of stop solution was added to each well, and the plate was read at 492 nm using an ELISA reader. These steps were repeated over 20 times with various antibody and serum dilutions to optimize the conditions and timing.\u003c/p\u003e \u003cp\u003eTo determine the cutoff value for the ELISA system, the assay is performed on 40 healthy people and 6 sick people samples, preferably from individuals over 40 years old, using the described method. Any results that are significantly higher or lower than the majority are excluded, and the cutoff rate is calculated using the formula M\u0026thinsp;+\u0026thinsp;2SD, where M is the mean and SD is the standard deviation. This approach ensures the accuracy and reliability of the ELISA assay in distinguishing between positive and negative samples.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn this project, the serum of 40 healthy people and 6 sick people were used (serum of sick people were used in this project so that it is clear that the system works correctly).\u003c/p\u003e \u003cp\u003eThe samples have been checked in the order (ELISA plate) of the table below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e3.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eColumns 1\u0026ndash;3, 5-7-9, serum of healthy people (columns 2-4-6-8-10 repeat previous columns) with rows A, B, C, D, E, F, G, H\u003c/p\u003e \u003cp\u003eColumns 11 and 12 with rows A, B, C, D, E, F of sick people's serum (suffering from kidney stones) in duplicate\u003c/p\u003e \u003cp\u003eSamples description\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003econtrol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eoutcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.1256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.2036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.3585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.4920\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eoutcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.5913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.6711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.2105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.9465\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eAsymptotic 95% Confidence Interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLower Bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUpper Bound\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eArea Under Curve (AUC): The AUC is calculated as 0.825, which indicates the discriminatory power of the test. The p-value associated with the analysis is 0.011, suggesting statistical significance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl if Greater Than or Equal To\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 - Specificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e.656750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLarger values of the test result variable(s) indicate stronger evidence for a control state and this table shows a cut off value: Control if Greater Than or Equal To 0.656750\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eKidney stone disease is a common and debilitating condition affecting millions of people worldwide. Oxalate, a key component of kidney stones, is a major risk factor for stone formation(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOxalyl-CoA decarboxylase (OXC) is a crucial enzyme involved in the metabolism of oxalate, a key component of kidney stones. This enzyme produced by Oxalobacter formigenes, a bacterium that colonizes the gut, plays a significant role in the catabolism of oxalate, which is linked to kidney stone formation(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The development of a reliable diagnostic kit for OXC enzyme activity is essential for the early detection and management of oxalate-related disorders(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe assessment of OXC enzyme activity is crucial for understanding the role of Oxalobacter formigenes in oxalate metabolism and identifying individuals at risk of kidney stone disease. Measuring OXC enzyme activity can help identify individuals with impaired oxalate metabolism(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAssessing OXC enzyme activity is valuable for monitoring the effectiveness of treatments aimed at reducing urinary oxalate levels(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This emphasizes the significance of OXC enzyme activity assessment in managing oxalate-related disorders and optimizing treatment strategies for individuals at risk of kidney stone formation.\u003c/p\u003e \u003cp\u003eDespite its importance, there is currently no commercially available kit for assessing OXC enzyme activity. The development of a reliable and sensitive diagnostic kit is essential for early detection and prevention of kidney stone disease. Enzyme-linked immunosorbent assay (ELISA) is a widely used technique for detecting enzyme activity, but its accuracy relies heavily on the quality of the antigen preparation.\u003c/p\u003e \u003cp\u003eAntigen preparation is a crucial aspect of developing an ELISA system, directly influencing the assay's sensitivity and specificity. Research has emphasized the significance of optimizing antigen preparation methods to enhance the performance of ELISA-based diagnostic kits. For example, studies have shown that utilizing recombinant antigens can significantly improve the sensitivity and specificity of ELISA assays compared to conventional antigen preparation techniques(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDetermining the cutoff value for the ELISA system is essential for accurate result interpretation. Importance of setting an appropriate cutoff value using statistical methods like receiver operating characteristic (ROC) curve analysis is to optimize the assay's sensitivity and specificity. This approach helps minimize false-positive and false-negative results, ensuring the reliability of the diagnostic test.\u003c/p\u003e \u003cp\u003eIn this study, we develop and validate an enzyme-linked immunosorbent assay (ELISA) for the detection and quantification of OXC. We optimize the ELISA conditions and determine the cutoff value for the assay using healthy samples. The results of this study provide a valuable tool for the detection and quantification of OXC, which can be used in various applications, including research, diagnosis, and monitoring of diseases related to oxalate metabolism. The development of a sensitive and specific ELISA assay for OXC has significant implications for clinical practice, enabling the detection and quantification of the enzyme in various biological samples, including serum, urine. This assay can be used for the diagnosis and monitoring of oxalate-related disorders, such as primary hyperoxaluria, enteric hyperoxaluria, and oxalosis. Early detection and quantification of OXC can help identify individuals at risk of developing these disorders, allowing for timely intervention and treatment. Additionally, the assay can be used to monitor the efficacy of treatment strategies aimed at reducing oxalate levels or enhancing OXC activity. The ELISA assay can also be used to identify individuals with impaired OXC activity, which may be associated with an increased risk of kidney stone formation. Early identification of these individuals can lead to targeted interventions, such as increased fluid intake, dietary modifications, and pharmacological therapy, to reduce the risk of stone formation. There are several limitations that need to be addressed in future studies. These include the development of monoclonal antibodies or antibodies against specific epitopes to improve the assay's specificity and sensitivity, validation of the assay in larger cohorts and diverse populations, automation of the assay to improve its throughput and reproducibility, and investigation of the correlation between OXC activity and oxalate levels in biological samples.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to address the challenges in developing effective diagnostic tests for oxalyl-CoA decarboxylase (OXC) by improving antigen production and defining the cutoff value for an ELISA system. Our results provide significant insights into the optimization of diagnostic assays for oxalate-related disorders.\u003c/p\u003e \u003cp\u003eThe use of a well-defined cutoff value ensures that the diagnostic test is both reliable and reproducible, making it a valuable tool for clinicians.\u003c/p\u003e \u003cp\u003eWhile the current study has made substantial progress in optimizing the diagnostic assay for OXC, further research is needed to validate these findings in larger and more diverse populations. Additionally, exploring the potential of combining OXC detection with other biomarkers could enhance the diagnostic accuracy and provide a more comprehensive understanding of oxalate metabolism disorders. This holistic approach could lead to improved management strategies for patients suffering from these challenging conditions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, we developed a cut off for the detection of oxalyl-CoA decarboxylase (OXC) by ELISA system.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcnowledgement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was carried out in the Cellular \u0026amp; Molecular Biology Research Center of Shahid Beheshti University of Medical Sciences, Tehran, Iran. and supported by Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran through Grant No 898\u003c/p\u003e\n\u003ch4\u003eFunding\u003c/h4\u003e\n\u003cp\u003eThis work was supported by the Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran, through Grant No. 898. The authors declare that no additional funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003ch4\u003eCompeting Interests\u003c/h4\u003e\n\u003cp\u003eThe authors declare that they have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003ch4\u003eAuthor Contributions\u003c/h4\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Davood Khavari Ardestani, Abbas Basiri, Mojgan Bandehpour, Afshin Abdi-Ghavidel, and Bahram Kazemi. The first draft of the manuscript was written by Davood Khavari Ardestani, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch4\u003eEthics Approval\u003c/h4\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Shahid Beheshti University of Medical Sciences (IR.SBMU.UNRC.REC.1401.035).\u003c/p\u003e\n\u003ch4\u003eConsent to Participate\u003c/h4\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003ch4\u003eConsent to Publish\u003c/h4\u003e\n\u003cp\u003eThe authors affirm that human research participants provided informed consent for the publication of the data included in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData supporting the findings of this study are provided within the manuscript file.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStamatelou K, Goldfarb DS (2023) Epidemiology of Kidney Stones. Healthc (Basel). ;11(3)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShin S, Srivastava A, Alli NA, Bandyopadhyay BC (2018) Confounding risk factors and preventative measures driving nephrolithiasis global makeup. World J Nephrol 7(7):129\u0026ndash;142\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElshal AM, Shamshoun H, Awadalla A, Elbaz R, Ahmed AE, El-Khawaga OY, Shokeir AA (2023) Hormonal and molecular characterization of calcium oxalate stone formers predicting occurrence and recurrence. Urolithiasis 51(1):76\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLung HY, Cornelius JG, Peck AB (1991) Cloning and expression of the oxalyl-CoA decarboxylase gene from the bacterium, Oxalobacter formigenes: prospects for gene therapy to control Ca-oxalate kidney stone formation. Am J Kidney Dis 17(4):381\u0026ndash;385\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoussef HIA (2024) Detection of oxalyl-CoA decarboxylase (oxc) and formyl-CoA transferase (frc) genes in novel probiotic isolates capable of oxalate degradation in vitro. Folia Microbiol (Praha)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTroxel SA, Sidhu H, Kaul P, Low RK (2003) Intestinal Oxalobacter formigenes colonization in calcium oxalate stone formers and its relation to urinary oxalate. J Endourol 17(3):173\u0026ndash;176\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWigner P, Bijak M, Saluk-Bijak J (2022) Probiotics in the prevention of the calcium oxalate urolithiasis. Cells 11(2):284\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbarghooi-Kahaki F, Basiri A, Bandehpour M, Kazemi B (2019) Designing a diagnostic kit for Oxalyl CoA Decarboxylase enzyme by ELISA method. Immunol Lett 205:78\u0026ndash;83\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKahaki FA, Dehnavi SM (2022) Expression Optimizing of Recombinant Oxalyl-CoA Decarboxylase in Escherichia coli. Adv Biomedical Res 11(1):110\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitchell T, Kumar P, Reddy T, Wood KD, Knight J, Assimos DG, Holmes RP (2019) Dietary oxalate and kidney stone formation. Am J Physiol Ren Physiol 316(3):F409\u0026ndash;f13\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSheng X, Liu Y, Zhang R (2014) A theoretical study of the catalytic mechanism of oxalyl-CoA decarboxylase, an enzyme for treating urolithiasis. RSC Adv 4(67):35777\u0026ndash;35788\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang T, Chen W, Cao L, He Y, Zhou H, Mao H (2020) Abundance, Functional, and Evolutionary Analysis of Oxalyl-Coenzyme A Decarboxylase in Human Microbiota. Front Microbiol 11:672\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao C, Yang H, Zhu X, Li Y, Wang N, Han S et al (2017) Oxalate-Degrading Enzyme Recombined Lactic Acid Bacteria Strains Reduce Hyperoxaluria. Urology. ;113\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"urolithiasis","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ures","sideBox":"Learn more about [Urolithiasis](http://link.springer.com/journal/240)","snPcode":"240","submissionUrl":"https://submission.nature.com/new-submission/240/3","title":"Urolithiasis","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"oxalyl coA decarboxylase, ELISA, cut off","lastPublishedDoi":"10.21203/rs.3.rs-4564741/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4564741/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe prevalence of kidney stone disease is increasing globally, with calcium oxalate stones being the most common type. Oxalyl-CoA decarboxylase (OXC), an enzyme produced by the gut bacterium Oxalobacter formigenes, plays a crucial role in oxalate metabolism. Deficiencies in OXC activity can lead to the accumulation of oxalate, contributing to kidney stone formation. This study aimed to develop a reliable diagnostic assay for OXC by optimizing antigen production and establishing a cutoff value for an enzyme-linked immunosorbent assay (ELISA). We cloned, expressed, and purified recombinant OXC protein in Escherichia coli BL21(DE3), and generated specific polyclonal antibodies in rabbits. The ELISA system was optimized and validated using serum samples from 40 healthy individuals and 6 patients with oxalate-related disorders. The cutoff value was determined using the formula ( M\u0026thinsp;+\u0026thinsp;2SD ), where ( M ) is the mean and ( SD ) is the standard deviation of the healthy sample results. The calculated cutoff value of 0.656750 effectively distinguished between healthy and affected individuals, with a sensitivity of 97.5% and a specificity of 83.3%. These findings provide a valuable tool for the early detection and management of oxalate-related disorders, with significant implications for clinical practice.\u003c/p\u003e","manuscriptTitle":"Optimizing Antigen Preparation for Oxalyl-CoA Decarboxylase Enzyme Diagnostic Kit and ELISA System Cutoff Determination","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-15 17:40:56","doi":"10.21203/rs.3.rs-4564741/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-09T13:40:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-04T20:43:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179891194019642729590178052240896364174","date":"2024-07-01T17:20:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-30T16:15:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-15T08:53:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-15T08:52:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Urolithiasis","date":"2024-06-11T14:08:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"urolithiasis","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ures","sideBox":"Learn more about [Urolithiasis](http://link.springer.com/journal/240)","snPcode":"240","submissionUrl":"https://submission.nature.com/new-submission/240/3","title":"Urolithiasis","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"46bec84d-b562-4f9f-9282-038865103030","owner":[],"postedDate":"July 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-14T16:09:00+00:00","versionOfRecord":{"articleIdentity":"rs-4564741","link":"https://doi.org/10.1007/s00240-024-01635-7","journal":{"identity":"urolithiasis","isVorOnly":false,"title":"Urolithiasis"},"publishedOn":"2024-10-09 15:58:02","publishedOnDateReadable":"October 9th, 2024"},"versionCreatedAt":"2024-07-15 17:40:56","video":"","vorDoi":"10.1007/s00240-024-01635-7","vorDoiUrl":"https://doi.org/10.1007/s00240-024-01635-7","workflowStages":[]},"version":"v1","identity":"rs-4564741","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4564741","identity":"rs-4564741","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}