Image Analysis for Automatic Characterization of Polyhydroxyalcanoates Granules. In: Kamel M, Campilho A, editors. Image Analysis and Recognition. Berlin: Springer Berlin Heidelberg; 2013. pp. 790-7. [DOI: 10.1007/978-3-642-39094-4_91]

Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies

Polyhydroxyalkanoates (PHAs) produced from mixed microbial cultures (MMC), regarded as potential substitutes of petrochemical plastics, can be found as intracellular granules in various microorganisms under limited nutrient conditions and excess of carbon source. PHA is traditionally quantified by laborious and time-consuming chromatography analysis, and a simpler and faster method to assess PHA contents from MMC, such as quantitative image analysis (QIA), is of great interest. The main purpose of the present work was to upgrade a previously developed QIA methodology (as reported by Mesquita et al. (Anal Chim Acta 770:36-44, 2013a, Anal Chim Acta 865:8-15, 2015)) for MMC intracellular PHA contents quantification, increase the studied intracellular PHA concentration range, and extend to different sequencing batch reactor (SBR) operation strategies. Therefore, the operation of a new aerobic dynamic feeding (ADF) SBR allowed further extending the studied operating conditions, dataset, and range of the MMC intracellular PHA contents from the previously reported anaerobic/aerobic cycle SBR. Nile Blue A (NBA) staining was employed for epifluorescence microscope visualization and image acquisition, further fed to a custom developed QIA. Data from each of the feast and famine cycles of both SBR were individually processed using chemometrics analysis, obtaining the correspondent partial least squares (PLS) models. The PHA concentrations determined from PLS models were further plotted against the results obtained in the standard chromatographic method. For both SBR, the predicted ability was higher at the end of the feast stage than for the famine stage. Indeed, an independent feast and famine QIA data treatment was found to be fundamental to obtain the best prediction abilities. Furthermore, a promising overall correlation (R ² of 0.83) could be found combining the overall QIA data regarding the PHA prediction up to a concentration of 1785.1 mg L^-1 (37.3 wt%). Thus, the results confirm that the presented QIA methodology can be seen as promising for estimating higher intracellular PHA concentrations for a larger reactors operation systems and further extending the prediction range of previous studies.

Polyhydroxyalkanoate granules quantification in mixed microbial cultures using image analysis: Sudan Black B versus Nile Blue A staining

Polyhydroxyalkanoates (PHA) can be produced and intracellularly accumulated as inclusions by mixed microbial cultures (MMC) for bioplastic production and in enhanced biological phosphorus removal (EBPR) systems. Classical methods for PHA quantification use a digestion step prior to chromatography analysis, rendering them labor intensive and time-consuming. The present work investigates the use of two quantitative image analysis (QIA) procedures specifically developed for PHA inclusions identification and quantification. MMC obtained from an EBPR system were visualized by bright-field and fluorescence microscopy for PHA inclusions detection, upon Sudan Black B (SBB) and Nile Blue A (NBA) staining, respectively. The captured color images were processed by QIA techniques and the image analysis data were further treated using multivariate statistical analysis. Partial least squares (PLS) regression coefficients of 0.90 and 0.86 were obtained between QIA parameters and PHA concentrations using SBB and NBA, respectively. It was found that both staining procedures might be seen as alternative methodologies to classical PHA determination.