EVALUATION OF MYCOPLASMA HOMINIS PROTEOME TO IDENTIFY THE POTENTIAL VACCINE CANDIDATE PROTEINS

EVALUATION OF MYCOPLASMA HOMINIS PROTEOME TO IDENTIFY THE POTENTIAL VACCINE CANDIDATE PROTEINS

Shivakumar Madagi and Shilpa Shiragannavar ^*

Department of Studies and Research in Bioinformatics, Karnataka State Akkamahadevi Women’s University Vijayapura - 586108, Karnataka, India.

ABSTRACT: Objective: Mycoplasma hominisis a gram-negative bacteria belonging to class Mollicutes that is commonly present in men and women of reproductive age. At present, there is no effective prophylaxis for Mycoplasma hominis, as it has gained resistance for the drugs hence an in-silico approach was undertaken to find out the peptide-based vaccine for the pathogen. Methods: In women, it affects the genital tract and involved in causing pelvic inflammatory disease, ectopic pregnancy, early delivery, miscarriage and prolonged infection may lead to infertility. M. hominis can also be transmitted from mother during childbirth and cause fever and infection in the new-born baby. All the 529 protein sequences of Mycoplasma hominis were taken in FASTA format from the UniProt proteome database. Antigenicity study was done for all the proteins of the pathogen using VaxiJen v2.0 and the proteins with high antigenicity scores were taken for further analysis like structural and functional analysis using InterPro, molecular docking using Autodock and molecular simulation study was carried out using Charmm. Results: The study identifies 50S ribosomal protein L28, Potassium transporter KtrB, Cobalt ABC transporter permease and Membrane protein as the putative vaccine candidates which are membrane-bound with high antigenicity properties and show good molecular docking and simulations results. Conclusion: From the study and analysis of the results, the proteins identified might work as a vaccine against the pathogen as they have passed all the necessary in-silico screenings. However, the in-silico results have to be validated by in-vitro studies.

Mycoplasma hominis, Docking, Antigenicity, In-silico, Vaccine

INTRODUCTION: Mycoplasma hominisis a gram-negative bacterium often found in genito-vaginal tracts of women and in sexually active adult males ¹. The human pathogen is transmitted by direct contact during the intercourse and vertically from mother to offspring either during birth or in uterus ².

The pathogenicity of mycoplasmas in the female genital tract was previously confirmed by the presence of anti-mycoplasma antibodies among women with intra-amniotic infection and postpartum fevers ³. The symptoms of the bacterium involve vaginal discharge, genital warts and other inflammatory responses. Some of the studies link the pathogen to Pelvic Inflammatory disease and preterm labor ⁴.

The scientific classification of the pathogen is given in Table 1. The epidemiology of the pathogen is associated with colonization in the genitourinary tract and is seen in the patients of young age who are sexually active.

The clinical manifestations of the pathogen infection include Pelvic Inflammatory Disease, cervicitis, urethritis, post-partum fever, stillbirth, brain abscess, pyelonephritis. Pelvic inflammatory disease has minimal symptoms like fever, pelvic and abdominal pain and tenderness of the tissues of uterine, cervix and adnexal. Cervicitis and urethritis lead to vaginal discharge in women and urethral discharge in men and irritation during the urine pass. Epididymitis is the swelling of epididymis underlying the testis within the scrotum⁵.

The pathogen in some cases, is associated with the other pathogen U. urealyticum ⁶. However, a significant relationship exists between U. urealyticum and M. hominis and male infertility ⁷. There are several pathogens known to contribute to male infertility; the two types that most commonly occur are genital urea plasma and mycoplasma. They are ubiquitous resulting in colonization of the genitalia by sexual contact ⁸. Several studies have demonstrated that U. urealyticum and M. hominis play an etiologic role in male infertility, with these infections changing parameters of semen such as spermatozoa density and motility ⁹. The current treatment options include commonly prescribed antibiotics, and very few are effective against bacterial infections.

Nowadays, bacteria have gained resistance for antibiotics therefore vaccination can be a more effective way of treating bacterial infections ¹⁰. With the data from sequencing projects and advances in proteomics and genomics, the field of vaccine design and development have emerged to be more promising ¹¹.

Particularly the epitope-based vaccines elicit specific and accurate immune responses ¹². Hence in the current work, various in-silico tools are used to obtain the immunogenic proteins from the bacteria which significantly reduces the time and cost in the developmental process. All the proteome of the bacteria was collected and checked for antigenicity, allergenicity, structural and functional analysis for identifying the more immunogenic proteins within the bacterial proteome. Finally, an attempt was made to design an effective peptide-based vaccine. The results of the study identify novel vaccine candidate proteins for development of a vaccine against Mycoplasma hominis.

TABLE 1: SCIENTIFIC CLASSIFICATION OF THE PATHOGEN M. HOMINIS

MATERIALS AND METHODS:

Retrieval of all the Proteins of Mycoplasma hominis: The proteome of the M. hominis contains 529 proteins. All the 529 proteins were retrieved from UniProt ¹³. Proteome database in FASTA format.

Structural and Functional Analysis of Proteins: Protein structural and functional analysis is important to know their role in the organism’s survival. The physic-chemical properties of proteins were studied using ProtParam ¹⁴. Interpro ¹⁵ was used to get the number of conserved domains and other important sites within the proteins.

Localization, Antigenicity and Allergy Study of the Proteins: M. hominis lacks cell wall hence is a gram-negative bacterium. Sub-cellular localization prediction and Antigenicity study for all the retrieved proteins was done using SOSUIGramN ¹⁶ and VaxiJen v2.0 ¹⁷. AlgPred ¹⁸ was used to eliminate the allergic proteins and the non-allergic proteins were considered for further analysis.

Protein Modelling, Validation and Protein Optimization: Due to the unavailability of the protein structures in the database, the three-dimensional structure of the proteins was generated using Swiss Model ¹⁹. The protein models generated were then validated for the correctness using Ramchandran Plot analysis tools Rampage ²⁰ and Procheck ²¹. The models with more than 90% accuracy were then subjected to energy minimization to obtain a stable structure before docking using Swiss PDB Viewer ²².

Molecular Docking and Molecular Simulation study: The docking studies were performed using AutoDock ²³. To obtain the specific interactions between the drug and proteins the active binding sites for proteins were predicted using Metapocket ²⁴. As the study focuses on designing the in-silico vaccine for the pathogen, the drug azithromycin ²⁵ was used for docking to know the stability and sustainability of the proteins against the drug. To further know the suitability of the proteins to be the vaccine candidates, Molecular dynamics and simulation studies were performed using CHARMM ²⁶. VMD and NAMD are files compatible with CHARMM. 100000 molecular dynamic steps were run for getting intense results.

RESULTS AND DISCUSSION: 529 proteins of the M. hominis were collected in fasta format from the UniProt Proteome database.

The parameters like molecular weight, theoretical pI, number of amino acids, amino acid composition, atomic composition, extinction coefficient, estimated half-life, aliphatic index, instability index, and grand average of hydropathicity (GRAVY) were obtained from the ProtParam, and the functional analysis of proteins was done using InterPro by classifying them into families, predicting domains and other important sites.

Table 2 below gives the details of the protein parameters.

TABLE 2: PROTPARAM RESULTS FOR THE FINAL VACCINE CANDIDATE PROTEINS

The protein screening was done based on the Vaxijen scores with a threshold of 0.4. The proteins with antigenicity scores more than 0.5 were considered for further investigation. Then the proteins were checked for the localization using SOSUIGramN. Non-allergenic proteins were then identified using AlgPred, the mapping of protein with the IgE epitopes is done to predict the allergen score. Table 3 gives the vaxijen score and the localization and allergen scores for the vaccine candidate proteins.

TABLE 3: VAXIJEN SCORE AND THE LOCALIZATION PREDICTION FOR THE PROTEINS

Due to the lack of the 3D structure of the proteins in the database, homology modeling was performed using SwissModel using Alignment Mode. All the models with good Qmean scores were then validated for the accuracy of the structures with RAMPAGE and PROCHECK, Table 4 gives the validation scores. The predicted models were subjected to energy minimization using SwissPDB Viewer. The XYZ coordinates or the active sites were predicted using the prediction tool Metapocket to get the site-specific interactions.

TABLE 4: PROTEIN MODEL VALIDATION RESULTS FOR THE PROTEINS USING RAMPAGE

TABLE 5: XYZ COORDINATES USED FOR AUTODOCK AND THE BINDING ENERGIES FOR THE PROTEINS

The drug was used for docking azithromycin. The protein-drug docking was performed with AutoDock, the binding energies for the protein-drug complexes were noted and used for further investigation. Table 5 gives the binding energies. The interactions the drug azithromycin with proteins is shown in Fig. 1. The complexes with minimum binding energy were then taken for the molecular dynamics simulation with 100000 steps. CHARMM simulation package was used for molecular simulation studies. Fig. 2 shows the distance and histogram graphs of simulation.

FIG. 1: THE INTERACTIONS THE DRUG AZITHROMYCIN WITH PROTEINS A. 50S RIBOSOMAL PROTEIN L28 B. POTASSIUM TRANSPORTER KTRB C. COBALT ABC TRANSPORTER PERMEASE D. MEMBRANE PROTEIN

FIG. 2: DISTANCE AND HISTOGRAM GRAPHS OF SIMULATION STUDIES FOR THE VACCINE CANDIDATE PROTEIN MOLECULES PROTEINS A.50S RIBOSOMAL PROTEIN L28 B. POTASSIUM TRANSPORTER KTRB C. COBALT ABC TRANSPORTER PERMEASE D. MEMBRANE PROTEIN

50S ribosomal protein L28, Cobalt ABC transporter permease, Membrane protein, Potassium transporter KtrB are the proteins that are highly antigenic and have good docking scores.

CONCLUSION: The untreated M. hominis infection continues to have a negative impact on human reproductive health because of a lack of adequate treatment options. In the present study, an effort is made to design a peptide-based potential vaccine candidate proteins that are effective against the pathogen and invoke the immune responses.

With the continued growth and development of Computational tools, it is likely that drug design plays an indispensable role in the future development of sub-unit or epitope vaccines. A number of screening methods were implemented so as to obtain an effective vaccine candidate protein. Among the whole of the proteome of the Mycoplasma homonis the proteins 50S ribosomal protein L28, Potassium transporter KtrB, Cobalt ABC transporter permease and Membrane protein were identified as potential vaccine candidate proteins which are highly antigenic and non-allergenic with conserved domains that have good immunogenic properties.

ACKNOWLEDGEMENT: The authors wish to thank DBT BIF center, Department of Bioinformatics for financial assistance.

CONFLICTS OF INTEREST: Authors declare that they have no conflict of interest and this article does not contain any studies with human and animal subjects by any of the authors.

REFERENCES:

1. Horner P, Donders G, Cusini M, Gomberg M, Jensen JS, and Unemo M: Should we be testing for urogenital Mycoplasma hominis, Ureaplasma parvum and Ureaplasma urealyticum in men and women?–a position statement from the European STI Guidelines Editorial Board. Journal of the European Academy of Dermatology and Venereology 2018; 32(11): 1845-51.
2. Arya OP, Tong C Y W, Hart CA, Pratt BC, Hughes S, Roberts P and Goddard AD: Is Mycoplasma hominis a vaginal pathogen? Sexually transmitted infections 2001; 77(1): 58-62.
3. Cunningham SA, Mandrekar JN, Rosenblatt JE and Patel R: Rapid PCR Detection of Mycoplasma hominis, Ureaplasma urealyticum, and Ureaplasma parvum. International Journal of Bacteriology 2013.
4. Nagata Y, Iwasaka T and Wada T: Mycoplasma infection and infertility. Fertility and Sterility 1979; 31(4): 392-95.
5. Bradshaw CS, Jensen JS, Tabrizi SN, Read TR, Garland SM, Hopkins CA and Fairley CK: Azithromycin failure in Mycoplasma genitalium Emerging Infectious Diseases 2006; 12(7): 1149.
6. Gdoura R, Kchaou W, Ammar‐Keskes L, Chakroun N, Sellemi A, Znazen A and Hammami A: Assessment of Chlamydia trachomatis, Ureaplasma urealyticum, Ureaplasma parvum, Mycoplasma hominis, and Mycoplasma genitalium in semen and first void urine specimens of asymptomatic male partners of infertile couples. Journal of Andrology 2008; 29(2): 198-206.
7. Huang C, Zhu HL, Xu KR, Wang SY, Fan LQ and Zhu WB: Mycoplasma and ureaplasma infection and male infertility: a systematic review and meta‐analysis. Andrology 2015; 3(5): 809-16.
8. Taylor‐Robinson D and Lamont RF: Mycoplasmas in pregnancy. BJOG: An International Journal of Obstetrics & Gynaecology 2011; 118(2): 164-74.
9. Liu J, Wang Q, Ji X, Guo S, Dai Y, Zhang Z and Lee Y: Prevalence of Ureaplasma urealyticum, Mycoplasma hominis, Chlamydia trachomatis infections, and semen quality in infertile and fertile men in China. Urology 2014; 83(4): 795-99.
10. Kılıç D, Başar MM, Kaygusuz S, Yılmaz E, Başar H and Batislam E: Prevalence and treatment of Chlamydia trachomatis, Ureaplasma urealyticum and Mycoplasma hominis in patients with Nongonococcal Urethritis. Jpn J Infect Dis 2004; 57(1): 17-20.
11. Grandi G: Antibacterial vaccine design using genomics and proteomics. Trends in Biotechnology 2001; 19(5): 181-88.
12. Buckanovich RJ, Coukos G and Facciabene A. (2019). U.S. Patent Application No. 10/174,120.
13. Apweiler R, Bairoch A, Wu CH, Barker WC, Boeckmann B, Ferro S and Martin MJ: UniProt: the universal protein knowledgebase. Nucleic Acids Research 2004; 32(S1): D115-D119.
14. Gasteiger E, Hoogland C, Gattiker A, Wilkins MR, Appel RD and Bairoch A: Protein identification and analysis tools on the ExPASy server. In The proteomics protocols handbook 2005: 571-07.
15. Finn RD, Attwood, TK, Babbitt PC, Bateman A, Bork P, Bridge AJ and Gough J: InterPro in 2017-beyond protein family and domain annotations. Nucleic Acids Research 2016; 45(D1): D190-D199.
16. Imai K, Asakawa N, Tsuji T, Akazawa F, Ino A, Sonoyama M and Mitaku S: SOSUI-Gram N: high performance prediction for sub-cellular localization of proteins in gram-negative bacteria. Bioinformation 2008; 2(9): 417.
17. Zaharieva N, Dimitrov I, Flower DR and Doytchinova I: VaxiJen Dataset of Bacterial Immunogens: An Update. Current computer-aided drug design 2019.
18. Sharma N, Kaushik S and Tomar RS: Prediction of the allergic response of extracellular amylase producing bacteria through in-silico International Journal of Research in Pharmaceutical Sci 2019; 10(2): 1185-89.
19. Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R and Lepore R: SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Research 2018.
20. PIWord, L. S. C. D. I. W. A. W. JM (2003) Structure validation by Calpha geometry: phi, psi and Cbeta deviation. Proteins 2003; 50: 437-50.
21. Sowmya H: A Comparative study of homology modeling algorithms for NPTX2 structure prediction. Research Journal of Pharmacy and Technology 2019; 12(4): 1895-00.
22. Johansson MU, Zoete V, Michielin O and Guex N: Defining and searching for structural motifs using DeepView/Swiss-PdbViewer. BMC bioinformatics 2012; 13(1): 173.
23. Eckstein J: ISOA/ARF drug development tutorial. In Institute for the Study of Aging/Alzheimer’s Drug Discovery Foundation and Alzheimer’s Research Forum, New York 2005; 19.
24. Iryani I, Amelia F and Iswendi I: Active sites prediction and binding analysis E1-E2 protein human papillomavirus with biphenylsulfon acetic acid. In IOP Conference Series: Materials Science and Engineering 2018; 335(1): 012031.
25. Pereyre S, Bebear CM and Bebear C: Mycoplasma hominis, M. genitalium and Ureaplasma Antimicrobial therapy and vaccines (3^rd Edition). Appel Trees Production, NY, USA 2015.
26. Best RB, Zhu X, Shim J, Lopes PE, Mittal J, Feig M, and MacKerell AD: Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone ϕ, ψ and side-chain χ1 and χ2 dihedral angles. Journal of Chemical Theory and Computation 2012; 8(9): 3257-73.
    

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    How to cite this article:

    Madagi SK and Shiragannavar S: Evaluation of Mycoplasma hominis proteome to identify the potential vaccine candidate proteins. Int J Pharm Sci & Res 2020; 11(4): 1831-36. doi: 10.13040/IJPSR.0975-8232.11(4).1831-36.

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