Genome-guided Profiling of Functional Potential in Bacillus licheniformis Toward Feed and Industrial Applications

Authors

  • Dan Râmbu 1.Laboratory of Animal Nutrition and Biotechnology, National Research and Development Institute for Biology and Animal Nutrition-IBNA Balotesti, Calea Bucuresti No. 1, 077015 Balotesti, Romania; 2. Faculty of Biotechnology, University of Agricultural Sciences and Veterinary Medicine, 011464 Bucharest, Romania;
  • Mihaela Dumitru Laboratory of Animal Nutrition and Biotechnology, National Research and Development Institute for Biology and Animal Nutrition-IBNA Balotesti, Calea Bucuresti No. 1, 077015 Balotesti, Romania;
  • Georgeta Ciurescu rambu.dan96@gmail.com
  • Emanuel Vamanu Faculty of Biotechnology, University of Agricultural Sciences and Veterinary Medicine, 011464 Bucharest, Romania;

Keywords:

screening, secretome prediction, enzymatic activity, probiotic potential, antimicrobial resistance

Abstract

Interest in probiotic strains with functional characteristics that can support zootechnical health, improve production performance, enable the development of feed additives, and facilitate the discovery of novel bioactive molecules is steadily increasing. However, strains belonging to the same species can exhibit substantial genomic variability. This translates into significant differences in functional potential. In this context, genome-based prospecting represents a powerful strategy for the rapid identification of strains with desirable traits. This includes secretion capacity, production of hydrolytic enzymes, and antimicrobial activity, while simultaneously ensuring the absence of transferable antimicrobial resistance determinants. Such an approach enables early-stage screening and prioritization of candidate strains, reducing the need for extensive experimental testing on unsuitable isolates. From a practical perspective, this strategy can significantly accelerate strain selection pipelines in feed and industrial biotechnology by focusing experimental efforts only on high-potential candidates. This leads to reduced costs, shorter development timelines, and increased efficiency in identifying strains suitable for probiotic applications or enzyme production. Therefore, in this study, we demonstrate that genome-guided analysis of Bacillus licheniformis can reliably predict key functional traits, including enzymatic potential, antimicrobial activity and some safety-related features. Current approach represents a critical first step toward the rational development of microbial strains and provides a robust foundation for subsequent in-depth functional and in vivo validation studies.

References

Xiao, F., Zhang, Y., Zhang, L., Li, S., Chen, W., Shi, G., Li, Y., Advancing Bacillus licheniformis as a superior expression platform through promoter engineering, Microorganisms, 2024, 12(8), 1693. doi: 10.3390/microorganisms12081693.

Qian, J., Wang, Y., Hu, Z., Shi, T., Wang, Y., Ye, C., Huang, H., Bacillus sp. as a microbial cell factory: Advancements and future prospects. Biotechnol. Adv. 2023, doi: 10.1016/j.biotechadv.2023.108278

Danilova, I., Sharipova, M., The practical potential of bacilli and their enzymes for industrial production. Front. Microbiol. 2020, 11, 1782. doi: 10.3389/fmicb.2020.01782.

Cotter, P. D., Ross, R. P., Hill, C., Bacteriocins-a viable alternative to antibiotics? Nat. Rev. Microbiol. 2013, 11(2), 95-105. doi:10.1038/nrmicro2937.

Shleeva, M. O., Kondratieva, D. A., Kaprelyants, A. S., Bacillus licheniformis: A producer of antimicrobial substances, including antimycobacterials, which are feasible for medical applications, Pharmaceutics, 2023, 15(7), 1893. doi:10.3390/pharmaceutics15071893.

Singer, R. S., Johnson, T. J., Assessing the risk of antimicrobial resistant enterococcal infections in humans due to bacitracin usage in poultry. J. Food Prot. 2024, 87(5), 100267. doi: 10.1016/j.jfp.2024.100267.

Oladele, P., Wickware, C. L., Trachsel, J., Looft, T., Johnson, T., A., In-feed bacitracin methylene disalicylate alters microbiota function and increases antibiotic resistance in a dose-dependent manner, BioRxiv, 2025, doi:10.1101/2025.02.16.638580

Yu, X., Liu, Z., Liu, Y., Li, X., Wang, B., Yin, J., Antimicrobial roles of probiotics: Molecular mechanisms and application prospects, Trends Food Sci. Technol. 2025, 163, 105146. doi: 10.1016/j.tifs.2025.105146

EFSA Panel on Biological Hazards (BIOHAZ), Statement on how to interpret the QPS qualification on ‘acquired antimicrobial resistance genes’, EFSA J. 2023, https://doi.org/10.2903/j.efsa.2023.8323

Olson, R. D., Assaf, R., Brettin, T., Conrad, N., Cucinell, C., Davis, J.J., et al., Introducing the bacterial and viral bioinformatics resource center (BV-BRC): A resource combining PATRIC, IRD and ViPR, Nucleic Acids Res. 2023, 51(D), D678-D689 doi:10.1093/nar/gkac1003

Carattoli, A., Zankari, E., García-Fernández, A., et al., In Silico detection and typing of plasmids using plasmidfinder and plasmid multilocus sequence typing, ASM J., Antimicrob. Agents Chemother. 2014, doi: 10.1128/aac.02412-1412.

Bertelli, C., Laird, M. R., Williams, K. P., IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets, Nucleic Acids Res. 2017, doi: 10.1093/nar/gkx343

Liu, M., Li, X., Xie, Y., Bi, D., Sun, J., Li, J., Tai, C., Deng, Z., Ou, H. Y., ICEberg 2.0: An updated database of bacterial integrative and conjugative elements, Nucleic Acids Res. 2019, 47, D660–D665

Zheng, J., Ge, Q., Yan, Y., Zhang, X., Huang L., Yin, Y., dbCAN3: automated carbohydrate-active enzyme and substrate annotation, Nucleic Acids Res, 2023, doi:10.1093/nar/gkad32875.

Teufel, F., Almagro Armenteros, J. J., Johansen, A. R., et al., SignalP 6.0 predicts all five types of signal peptides using protein language models. Nat. Biotechnol. 2022, doi:10.1038/s41587-021-01156-3

Hallgren, J., Tsirigos, K. D., Pedersen, M. D., Almagro Armenteros, J. J., Marcatili, P., Nielsen, H., Krogh, A., Winther, O., DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks, BioRxiv, 2022, doi:10.1101/2022.04.08.487609

van Heel, A. J., de Jong, A., Song, C., Viel, J. H., Kok, J., Kuipers, O. P., BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins, Nucleic Acids Res. 2018, doi:10.1093/nar/gky383

Dumitru, M., Râmbu, D. T., Ciurescu, G., Cornescu, G. M., Panaite, T. D., Enhanced Enzyme Production and Probiotic Viability in Oilseed Cakes Fermented with Bacillus subtilis for Piglet Nutrition. Fermentation 2025, doi:10.3390/fermentation11110607

Mârza, S. M., Munteanu, C., Papuc, I., Radu, L., Purdoiu, R. C., The Role of Probiotics in Enhancing Animal Health: Mechanisms, Benefits, and Applications in Livestock and Companion Animals. Animals, 2025, 15(20), 2986. doi: 10.3390/ani15202986

Montassier, E., Valdés-Mas, R., Batard, E. et al. Probiotics impact the antibiotic resistance gene reservoir along the human GI tract in a person-specific and antibiotic-dependent manner. Nat. Microbiol. 2021, 6, 1043-1054

Tian, Q., Ye, H., Zhou, X., Wang J., Zhang L., Sun W., Duan C., Fan M., Zhou W., Bi C., Ye Q., Wong A., Evaluating the health risk of probiotic supplements from the perspective of antimicrobial resistance. Microbiol. Spectr. 2025

Doi:10.1128/spectrum.00019-24

Johnson, C. M., Grossman, A. D., Integrative and Conjugative Elements (ICEs): What They Do and How They Work. Ann. Rev. Genet. 2015, 49, 577-601. doi: 10.1146/annurev-genet-112414-055018

Langille, M., Hsiao, W. & Brinkman, F. Detecting genomic islands using bioinformatics approaches. Nat Rev Microbiol 8, 373–382 (2010). https://doi.org/10.1038/nrmicro2350

Wei, Y., McPherson, D. C., Popham, D. L., A mother cell-specific class B penicillin-binding protein, PBP4b, in Bacillus subtilis., J. Bacteriol. 2004 186(1), 258-61. doi: 10.1128/JB.186.1.258-261.2004.

Luo, Y., Helmann, J. D., Analysis of the role of Bacillus subtilis σM in β-lactam resistance reveals an essential role for c-di-AMP in peptidoglycan homeostasis. Mol. Microbiol. 2012, 83(3), 623-39. doi: 10.1111/j.1365-2958.2011.07953.x.

Sumi, C. D., Yang, B. W., Yeo, I. C., Hahm, Y. T., Antimicrobial peptides of the genus Bacillus: a new era for antibiotics. Canadian J. Microbiol. 2014, 61(2), 93-103. Doi:10.1139/cjm-2014-0613

Grahovac, N., Aleksić, M., Trajkovska, B., Marjanović Jeromela, A., Nakov, G., Extraction and Valorization of Oilseed Cakes for Value-Added Food Components-A Review for a Sustainable Foodstuff Production in a Case Process Approach, Foods, 2025, 14, 2244. https://doi.org/10.3390/foods14132244

Bedford, M. R., Apajalahti J. H., The role of feed enzymes in maintaining poultry intestinal health, J. Sci. Food Agric. 2022, 102(5), 1759-1770. doi: 10.1002/jsfa.11670.

Rinttila, T. Apajalahti, J., Intestinal microbiota and metabolites-Implications for broiler chicken health and performance, J. Appl. Poult. Res. 2013, 22(3), 647-658. doi:10.3382/japr.2013-00742

de Oliveira Sousa, T., Araújo da Silva, N., de Melo Oliveira, V., da Silva Ramos, A. V., et al., Use of proteases for animal feed supplementation: scientific and technological updates, Preparative Biochemistry & Biotechnology, 2025, doi: 10.1080/10826068.2025.2465957

Gupta, R. K., Gangoliya, S. S., Singh, N. K., Reduction of phytic acid and enhancement of bioavailable micronutrients in food grains. J. Food Sci. Technol. 2015, 52(2), 676-684. doi: 10.1007/s13197-013-0978-y.

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Published

2026-06-01