Computational Vaccine Designed to Target Tapeworm Infections in Livestock

Researchers have computationally designed a multi-epitope chimeric vaccine intended to protect livestock against infections by parasitic tapeworms of the genus Taenia, according to a study published in Discover Life on 19 August 2026. The vaccine exists so far only as a computer model: every step, from protein selection to immune-response prediction, was performed with bioinformatics tools, and the authors themselves stress that laboratory and animal testing remains essential before any real-world use can be considered.

The motivation is substantial. Taenia solium, Taenia saginata and Taenia asiatica cause taeniasis and cysticercosis in endemic countries, and the parasites move between humans and livestock in a two-host life cycle. Adult worms inhabit the human intestine, while larval stages infect intermediate hosts such as cattle, sheep and pigs. In humans, larval infection can involve the muscles or the central nervous system; the paper cites surveys attributing roughly 30 to 45 percent of epileptic cases to neurocysticercosis, and notes that 30 to 50 percent infectivity has been observed among slaughtered pigs in animal studies. The World Health Organization has placed Taenia at the top of its list of foodborne parasites and classifies the infection as a neglected tropical disease.

The economic toll is also significant. Losses in animal husbandry stem mainly from reduced value of cyst-infected pork and carcass condemnation, and the parasite also reduces cattle growth. One study covering western and central African countries estimated total annual losses from taeniasis and cysticercosis at approximately 25 million Euros. Existing control measures have drawbacks: deworming drugs can foster resistance, re-infection remains a risk, and treating free-roaming pigs is difficult. The leading existing vaccine, TSOL18, works well against pigs but targets only the oncosphere stage of T. solium and no other species, which is precisely the gap the new study set out to address with a broader, cross-species design.

The team, led by Swati Sharma, Prerna Verma and Amit Prasad, used a subtractive proteomics pipeline combined with immuno-informatics. They retrieved the whole proteomes of all three Taenia species from public databases and applied BLAST searches to identify 840 conserved homologous proteins shared across the parasites, using a greater than 95 percent sequence identity threshold. To reduce the risk of the vaccine triggering an autoimmune response in livestock, they then screened against the proteomes of cattle, sheep and pigs, retaining only proteins with less than 50 percent identity to host sequences. This filtering yielded 418, 863 and 426 non-homologous proteins for Bos taurus, Sus scrofa and Ovis aries respectively, with 387 proteins common to all three hosts.

Successive computational filters narrowed this pool further. Transmembrane prediction tools TMHMM and Phobius identified 48 membrane proteins, and subcellular localization analysis with DeepLoc flagged 30 extracellular and 31 membrane proteins, giving 77 candidates likely to be accessible to the host immune system. Removing predicted allergens with AlgPred 2.0 left 60 proteins, and the VaxiJen v2.0 antigenicity tool selected 44. From these, the researchers predicted cytotoxic T-lymphocyte epitopes with NetMHCpan 4.1, helper T-lymphocyte epitopes with NetMHCIIpan 2.1 and the IEDB MHC-II binding tool, and linear B-cell epitopes with ABCpred, generating 258 candidate epitopes in total. Filtering for non-toxic, non-allergenic and antigenic peptides ultimately produced 11 epitopes drawn from three conserved antigenic proteins, TsM_000038200, TsM_00061000 and TsM_000523100, all annotated as integral plasma membrane components.

These epitopes were assembled into a single chimeric construct. Cytotoxic T-cell epitopes were joined with KK linkers, helper T-cell and B-cell epitopes with GPGPG linkers, and a beta-defensin adjuvant, a known agonist of the TLR1, TLR2 and TLR4 innate immune receptors, was attached at the N-terminus via a KPKPKP linker. The finished construct is 272 amino acids long with a molecular weight of 28.94 kilodaltons. Predicted physicochemical properties suggest a stable, soluble, hydrophilic and thermostable protein: an instability index of 37.81, a GRAVY hydropathicity index of minus 0.434, an aliphatic index of 61.32 and a Protein-Sol solubility score of 0.709.

Structural modelling and validation followed. The PSIPRED tool estimated the secondary structure at 20.95 percent alpha-helix, 12.86 percent beta-strand and 66.17 percent coil, while I-TASSER generated a three-dimensional model that was refined with 3Drefine and GalaxyRefine. Quality checks were broadly favourable: ProSA-web returned a z-score of minus 6.04, the ERRAT score was 70.954, Verify3D placed 92.65 percent of residues above the average 3D-1D score threshold, and the Ramachandran plot showed 78.1 percent of residues in the most favoured region, with only 3.6 percent in disallowed regions, which the authors note is common and acceptable in flexible loop regions.

To probe how the construct might interact with the immune system, the team docked the vaccine against TLR4 receptors of cattle and pigs, models of which had to be built computationally because no experimentally resolved crystal structures exist for these species. ClusPro docking produced weighted scores of minus 1068.5 for the bovine complex and minus 901.4 for the porcine complex, and HADDOCK site-specific docking returned z-scores of minus 2.6 and minus 2.2 respectively, with multiple hydrogen bonds and hydrophobic contacts anchoring the vaccine to the receptor’s extracellular domain. One-hundred-nanosecond molecular dynamics simulations in GROMACS showed the complexes remaining structurally intact, with root-mean-square deviations of 7.88 and 8.79 angstroms, sustained hydrogen bonding between 400 and 540 bonds, and stable radii of gyration of 3.23 and 3.14 nanometres for the bovine and porcine complexes.

Immune simulation with the C-ImmSim server, which models the human immune system, predicted rising immunoglobulin levels across three simulated doses given at one-month intervals, elevated interferon-gamma and interleukin-2 consistent with a Th1-type response, and proliferation of helper and cytotoxic T cells, B cells and memory cell populations. The authors caution, however, that the qualitative dynamics may only partially translate to livestock, since most of the prediction tools used, including VaxiJen, AlgPred, NetChop and C-ImmSim, are trained primarily on human datasets, and NetMHCIIpan 2.1 has limited training data for bovine and swine MHC alleles. Porcine helper T-cell epitopes had to be predicted using human alleles as proxies, an acknowledged limitation.

The final step was in-silico cloning: the vaccine sequence was reverse translated, codon-optimized for expression in E. coli K12, raising the codon adaptation index from 0.62 to 1.0 with a GC content of 54.90 percent, and computationally inserted into the pET28b(+) expression vector, producing an 816-nucleotide DNA sequence ready for future laboratory work. The authors conclude that the construct meets essential computational criteria and could theoretically disrupt the Taenia life cycle across all known hosts, but they are explicit that in-vitro and in-vivo validation is imperative. No animal has been immunized, no protective efficacy has been measured, and the study’s own limitations section emphasizes that all results should be read as approximate indicators guiding future experiments rather than evidence of a working vaccine. As an early-stage computational design, the work illustrates how reverse vaccinology can cheaply generate testable candidates for neglected tropical diseases, while leaving the decisive question of real-world protection entirely open.

Subject of Research: Computational design of a multi-epitope chimeric vaccine candidate against Taenia infections in livestock

Article Title: Immuno-informatics strategy for designing and development of a multi-epitope chimeric vaccine for livestock against Taenia infections

Article References: Sharma, S., Verma, P., Keshri, A. K., Chaudhary, A., Mehra, P., Kapoor, A., Panda, P. R., Rawat, S. S., & Prasad, A. (2026). Immuno-informatics strategy for designing and development of a multi-epitope chimeric vaccine for livestock against Taenia infections. Discover Life, 56(1), Article 39. https://doi.org/10.1007/s11084-026-09756-2

Image Credits: AI Generated

DOI: 10.1007/s11084-026-09756-2

Keywords: Taenia, livestock, vaccine design, immunoinformatics, reverse vaccinology, multi-epitope vaccine, cysticercosis, TLR4, molecular dynamics, subtractive proteomics, neglected tropical diseases, in silico