ArticleArchives of microbiology2026
Molecular and structural characterization of the C-phycocyanin β-subunit in native cyanobacteria from temple ponds: implications for biopigment yield and function.
Article in Archives of microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
C-phycocyanin (C-PC) is a high-value blue phycobiliprotein extensively utilized as a natural colorant and multifunctional bioactive compound. This study employed a polyphasic framework to characterize eleven native cyanobacterial isolates (NTBN series) from temple ponds in Tamil Nadu, India, with the aim of quantifying extractable C-PC and correlating pigment yield with molecular traits of the C-PC β-subunit. All isolates were cultivated under identical, non-optimized conditions (BG-11 medium, 25 ± 2 °C, 16:8 h light: dark, ~ 50 µmol photons m⁻² s⁻¹, 21 days, n = 3). Crude pigments were extracted and quantified spectrophotometrically, while cpcB sequences were subjected to homology modeling and physicochemical profiling (GRAVY, aliphatic index, instability index). Among the isolates, NTBN-07 and NTBN-15 exhibited the highest extractable C-PC content. Strains with lower GRAVY values (greater hydrophilicity) and moderate aliphatic indices consistently showed higher pigment productivity, as supported by multivariate analyses (heatmap and PCA). Homology models revealed conserved chromophore-binding residues with subtle tertiary conformational variations potentially influencing pigment stability and extractability. Although several native isolates yielded more C-PC than the laboratory reference Synechocystis sp. PCC 6803 under uniform, non-optimized conditions, their yields remained lower than those reported for optimized Arthrospira cultures. Study limitations include the use of crude extracts and reliance on in silico predictions pending protein-level validation. Overall, this work identifies temple-pond cyanobacteria as promising native bioresources for predictive strain selection, downstream process optimization, and sustainable pigment biotechnology.
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