Selection of vaccine-candidate peptides from Mycobacterium avium subsp. paratuberculosis by in silico prediction, in vitro T-cell line proliferation, and in vivo immunogenicity.

Mycobacterium avium subspecies paratuberculosis (MAP) is a global concern in modern livestock production worldwide. The available vaccines against paratuberculosis do not offer optimal protection and interfere with the diagnosis of bovine tuberculosis. The aim of this study was to identify immunogenic MAP-specific peptides that do not interfere with the diagnosis of bovine tuberculosis. Initially, 119 peptides were selected by either (1) identifying unique MAP peptides that were predicted to bind to bovine major histocompatibility complex class II (MHC-predicted peptides) or (2) selecting hydrophobic peptides unique to MAP within proteins previously shown to be immunogenic (hydrophobic peptides). Subsequent testing of peptide-specific CD4+ T-cell lines from MAP-infected, adult goats vaccinated with peptides in cationic liposome adjuvant pointed to 23 peptides as being most immunogenic. These peptides were included in a second vaccine trial where three groups of eight healthy goat kids were vaccinated with 14 MHC-predicted peptides, nine hydrophobic peptides, or no peptides in o/w emulsion adjuvant. The majority of the MHC-predicted (93%) and hydrophobic peptides (67%) induced interferon-gamma (IFN-γ) responses in at least one animal. Similarly, 86% of the MHC-predicted and 89% of the hydrophobic peptides induced antibody responses in at least one goat. The immunization of eight healthy heifers with all 119 peptides formulated in emulsion adjuvant identified more peptides as immunogenic, as peptide specific IFN-γ and antibody responses in at least one heifer was found toward 84% and 24% of the peptides, respectively. No peptide-induced reactivity was found with commercial ELISAs for detecting antibodies against Mycobacterium bovis or MAP or when performing tuberculin skin testing for bovine tuberculosis. The vaccinated animals experienced adverse reactions at the injection site; thus, it is recommend that future studies make improvements to the vaccine formulation. In conclusion, immunogenic MAP-specific peptides that appeared promising for use in a vaccine against paratuberculosis without interfering with surveillance and trade tests for bovine tuberculosis were identified by in silico analysis and ex vivo generation of CD4+ T-cell lines and validated by the immunization of goats and cattle. Future studies should test different peptide combinations in challenge trials to determine their protective effect and identify the most MHC-promiscuous vaccine candidates.

Interferon-inducible TRIM22 contributes to maintenance of HIV-1 proviral latency in T cell lines.

The human immunodeficiency virus type-1 (HIV-1) establishes a state of latent infection in a small number of CD4+ T lymphocytes that, nonetheless, represent a major obstacle to viral eradication. We here show that Tripartite Motif-containing protein 22 (TRIM22), an epigenetic inhibitor of Specificity protein 1 (Sp1)-dependent HIV-1 transcription, is a relevant factor in maintaining a state of repressed HIV-1 expression at least in CD4+ T cell lines. By knocking-down (KD) TRIM22 expression, we observed an accelerated reactivation of a doxycycline (Dox)-controlled HIV-1 replication in the T lymphocytic SupT1 cell line. Furthermore, we here report for the first time that TRIM22 is a crucial factor for maintaining a state of HIV-1 quiescence in chronically infected ACH2 -T cell line while its KD potentiated HIV-1 expression in both ACH-2 and J-Lat 10.6 cell lines upon cell stimulation with either tumor necrosis factor-α (TNF-α) or histone deacetylase inhibitors (HDACi). In conclusion, TRIM22 is a novel determinant of HIV-1 latency, at least in T cell lines, thus representing a potential pharmacological target for strategies aiming at curtailing or silencing the pool of latently infected CD4+ T lymphocytes constituting the HIV-1 reservoir in individuals receiving combination antiretroviral therapy.