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Bioprocess."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Statistical screening of media components is essential for identifying the key variables that govern protease yield from\n                      <jats:italic>Bacillus<\/jats:italic>\n                      species. We used a 12-run Plackett\u2013Burman Design (PBD) to screen ten independent variables\u2014dipotassium phosphate, monopotassium phosphate, ammonium sulphate, sodium nitrate, magnesium sulphate heptahydrate, calcium chloride, carbon source, nitrogen source, agitation speed, and pH\u2014for their effects on extracellular protease production by\n                      <jats:italic>Bacillus<\/jats:italic>\n                      sp. MTCC 511 under four mutagenic stress conditions: thermal treatment at 70\u00a0\u00b0C and 80\u00a0\u00b0C (10\u00a0min each) and UV irradiation (2 and 3\u00a0min).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Enzyme activity was quantified by Folin\u2013Ciocalteu assay against a tyrosine standard (R2 = 0.998). The highest protease activity, 8.66\u00a0U\/mL, was recorded under 3-min UV irradiation in a medium containing starch (1%), yeast extract (0.1%), K\n                      <jats:sub>2<\/jats:sub>\n                      HPO\n                      <jats:sub>4<\/jats:sub>\n                      (0.05\u00a0M), KH\n                      <jats:sub>2<\/jats:sub>\n                      PO\n                      <jats:sub>4<\/jats:sub>\n                      (0.05\u00a0M), (NH\n                      <jats:sub>4<\/jats:sub>\n                      )\n                      <jats:sub>2<\/jats:sub>\n                      SO\n                      <jats:sub>4<\/jats:sub>\n                      (0.05\u00a0M), NaNO\n                      <jats:sub>3<\/jats:sub>\n                      (0.1\u00a0M), MgSO\n                      <jats:sub>4<\/jats:sub>\n                      \u00b77H\n                      <jats:sub>2<\/jats:sub>\n                      O (0.002\u00a0M), and CaCl\n                      <jats:sub>2<\/jats:sub>\n                      (0.002\u00a0M) at pH 9 and 120\u00a0rpm, representing a 20.6-fold improvement over the unsupplemented basal medium. ANOVA showed R2 &gt; 97% for the 70\u00a0\u00b0C, 80\u00a0\u00b0C, and UV-3\u00a0min models; the UV-2\u00a0min model was statistically inadequate (R2 = 56.52%). Pareto analysis pointed to agitation speed, NaNO\n                      <jats:sub>3<\/jats:sub>\n                      , MgSO\n                      <jats:sub>4<\/jats:sub>\n                      \u00b77H\n                      <jats:sub>2<\/jats:sub>\n                      O, and carbon source as the most influential factors. Pearson correlation between thermal and UV-3\u00a0min responses (r = 0.72\u20130.83) is consistent with previously described \u03c3\n                      <jats:sup>B<\/jats:sup>\n                      -dependent stress\u2013response pathways.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The PBD screening efficiently identified significant factors whose effects are consistent with established regulatory mechanisms including nitrogen catabolite repression, carbon catabolite repression, and dissolved oxygen-dependent secretion. Follow-up response surface optimization is warranted to characterize factor interactions and identify the global optimum.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s40643-026-01134-0","type":"journal-article","created":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T05:21:08Z","timestamp":1791436868000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Screening and identification of significant media components using Plackett\u2013Burman design for enhanced extracellular protease production by Bacillus sp. 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