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Based on the knowledge that PUL glycoside hydrolase (GH) enzymes are frequently co-expressed to saccharify a complex polysaccharide, and that one of the enzymes (PmGH87) is known to hydrolyse a major linkage of the extracellular polymeric substance (EPS) of cariogenic biofilms, we hypothesized that the predicted PUL (pPmPUL) GHs may be relevant to the degradation of biofilms associated with oral disease. To test this, the pPmPUL GHs were selected for cloning, recombinant expression and further study. GHs\u2014consisting of a family 87 mutanase (PmGH87), a family 97 glucosidase (PmGH97) and an enzyme of unknown function assigned to the GH71\/99 superfamily (PmGH99)\u2014were characterised both structurally and biochemically and were assessed for their ability to degrade caries-associated\n                    <jats:italic>Streptococcus mutans<\/jats:italic>\n                    biofilms formed in vitro, both individually and in combinations. The results were compared to a previously described heterologous combination of complex carbohydrate active enzymes (PmGH87 and CoGH66). Both assays quantifying the relative change in biomass and confocal microscope images confirm the ability of pPmPUL GHs to remove\n                    <jats:italic>S. mutans<\/jats:italic>\n                    biofilm.\n                  <\/jats:p>","DOI":"10.1007\/s11274-026-05104-8","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T08:54:34Z","timestamp":1785315274000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enzymatic tools for the treatment of caries-associated biofilms: Investigating the enzymes of a putative polysaccharide utilization locus from Prevotella melaninogenica and their application against Streptococcus mutans biofilm"],"prefix":"10.1007","volume":"42","author":[{"given":"Dylan James","family":"Erasmus","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adelita Carolina","family":"Santiago","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebasti\u00e3o","family":"Pratavieira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neil Thomas","family":"Stacey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Igor","family":"Polikarpov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,29]]},"reference":[{"key":"5104_CR1","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1038\/s41587-019-0036-z","volume":"37","author":"JJ Almagro Armenteros","year":"2019","unstructured":"Almagro Armenteros JJ, Tsirigos KD, S\u00f8nderby CK, Petersen TN, Winther O, Brunak S, von Heijne G, Nielsen H (2019) SignalP 5.0 improves signal peptide predictions using deep neural networks. 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