Identification of Immunogenic Linear B-Cell Epitopes in C. burnetii Outer Membrane Proteins Using Immunoinformatics Approaches Reveals Potential Targets of Persistent Infections

Abstract

Coxiella burnetii is a global, highly infectious intracellular bacterium, able to infect a wide range of hosts and to persist for months in the environment. It is the etiological agent of Q fever—a zoonosis of global priority. Currently, there are no national surveillance data on C. burnetii’s seroprevalence for any South American country, reinforcing the necessity of developing novel and inexpensive serological tools to monitor the prevalence of infections among humans and animals—especially cattle, goats, and sheep. In this study, we used immunoinformatics and computational biology tools to predict specific linear B-cell epitopes in three C. burnetii outer membrane proteins: OMP-H (CBU_0612), Com-1 (CBU_1910), and OMP-P1 (CBU_0311). Furthermore, predicted epitopes were tested by ELISA, as synthetic peptides, against samples of patients reactive to C. burnetii in indirect immunofluorescence assay, in order to evaluate their natural immunogenicity. In this way, two linear B-cell epitopes were identified in each studied protein (OMP-H(51–59), OMP-H(91–106), Com-1(57–76), Com-1(191–206), OMP-P1(197–209), and OMP-P1(215–227)); all of them were confirmed as naturally immunogenic by the presence of specific antibodies in 77% of studied patients against at least one of the identified epitopes. Remarkably, a higher frequency of endocarditis cases was observed among patients who presented an intense humoral response to OMP-H and Com-1 epitopes. These data confirm that immunoinformatics applied to the identification of specific B-cell epitopes can be an effective strategy to improve and accelerate the development of surveillance tools against neglected diseases.

Sph2(176–191) and Sph2(446–459): Identification of B-Cell Linear Epitopes in Sphingomyelinase 2 (Sph2), Naturally Recognized by Patients Infected by Pathogenic Leptospires

“…First, we used a combination of algorithms to predict linear B-cell epitopes in L. interrogans serovar Lai Sph2. This approach had been used and improved by our group in recent years to predict epitopes in viruses [ 25 , 26 ], bacteria [ 24 ], and protozoans [ 28 , 48 , 49 ], resulting in prediction accuracy up to 90% in the most recent studies. Here, we predicted two sequences as antigenic and linear B-cell epitopes: GHDERAKRISKSDYVK (Sph2 (176-191) ) and TPTKSGHKKKYDQV (Sph2 (446-459) ), which did not present similar epitopes described in BLASTP, in the Immune Epitope Database (accessed on 20 June 2020) (data not shown), and also did not present similar sequences described in humans and mice, or in other databases from PeptideAtlas (accessed on 20 June 2020).…”

“…Samples of confirmed leptospirosis cases and the control group were screened for the presence of naturally acquired antibodies against the synthetic peptides via ELISA as previously described [ 24 ].…”

“…Therefore, this was the first study aiming to predict linear B-cell epitopes in L. interrogans Sph2, to evaluate their recognition as synthetic peptides antigens by serum samples from leptospirosis patients, and to investigate the associations between the specific immune responses to each validated epitope and the clinical data of patients. This strategy has been used successfully to identify epitopes for the development of novel vaccines, diagnostic methods, and therapeutics [ 22 , 23 , 24 , 25 , 26 , 27 , 28 ].…”

Immunoinformatics approach for designing a multi-epitope subunit vaccine against porcine epidemic diarrhea virus genotype IIA spike protein

“…Unlike T-cell epitopes, the optimal length to induce maximum activity in B-cell epitopes has not been identified; hence, multiple servers are usually employed to increase prediction accuracy. A peptide is considered a candidate LBL epitope if it is predicted by two or more prediction servers (Galanis et al ., 2021; Yang et al ., 2021 ; Fontes et al ., 2021 ). A total of 66 peptides were predicted by Bepipred 3.0, and validated by either BcePred, SVMTriP, or ABCpred.…”

Predicting Antigenic Peptides from Rocio Virus NS1 Protein for Immunodiagnostic Testing Using Immunoinformatics and Molecular Dynamics Simulation

“…In recent years, combinations of prediction algorithms have been used to improve the accuracy of linear B-cell epitope predictions against viruses [ 44 , 45 , 46 , 47 ], fungi [ 48 ], protozoa [ 49 , 50 ], and bacteria [ 51 , 52 , 53 , 54 ]. However, no in silico study has predicted linear B-cell epitopes of ROCV, only for other flaviviruses, and the targeting focused on the envelope protein [ 55 , 56 , 57 , 58 , 59 , 60 ], prM [ 57 , 60 ], NS1 [ 18 , 60 , 61 , 62 ], NS3, and NS5 [ 62 ], with similar algorithms used individually to explore the targets, predicting linear B-cell epitopes in each protein studied.…”