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

Abstract

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 (Mesquita et al., 2013a, 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 (R2 of 0.83) could be found combining the overall QIA data regarding the PHA prediction up to a concentration of 1785.1 mgL-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.