Application of high-content image analysis for quantitatively estimating lipid accumulation in oleaginous yeasts with potential for use in biodiesel production. (March 2016)

• Record Type: Journal Article
• Authors: Capus, Aurélie; Monnerat, Marianne; Ribeiro, Luiz Carlos; de Souza, Wanderley; Martins, Juliana Lopes; Sant'Anna, Celso
• Is Part Of: Bioresource technology. Volume 203(2016)
• Page Start: 309
• Page End: 317
• Publication Date: 2016-03
• Subjects: High-content image analysis -- Biofuel -- Biodiesel -- Oleaginous microorganisms -- Lipid droplets; Biomass -- Periodicals; Biomass energy -- Periodicals; Bioremediation -- Periodicals; Agricultural wastes -- Periodicals; Factory and trade waste -- Periodicals; Organic wastes -- Periodicals; Bioénergie -- Périodiques; Déchets agricoles -- Périodiques; Déchets industriels -- Périodiques; Déchets organiques -- Périodiques; Déchets (Combustible) -- Périodiques; 662.88
• DOI: 10.1016/j.biortech.2015.12.067
• Languages: English
• ISSNs: 0960-8524

Abstract

Highlights: A HCA method for screening oleaginous microorganisms is proposed. HCA generated lipid dynamics data at the single cell level. Image segmentation method accurately determines LD volume, weight and productivity. Low peptone and high glucose medium trigger lipid accumulation in yeast. Abstract: Biodiesel from oleaginous microorganisms is a viable substitute for a fossil fuel. Current methods for microorganism lipid productivity evaluation do not analyze lipid dynamics in single cells. Here, we described a high-content image analysis (HCA) as a promising strategy for screening oleaginous microorganisms for biodiesel production, while generating single-cell lipid dynamics data in large cell density. Rhodotorula slooffiae yeast were grown in standard (CTL) or lipid trigger medium (LTM), and lipid droplet (LD) accumulation was analyzed in deconvolved confocal microscopy images of cells stained with the lipophilic fluorescent Nile red (NR) dye using automated cell and LD segmentation. The 'vesicle segmentation' method yielded valid morphometric results for limited lipid accumulation in smaller LDs (CTL samples) and for high lipid accumulation in larger LDs (LTM samples), and detected LD localization changes. Thus, HCA can be used to analyze the lipid accumulation patterns likely to be encountered in screens for biodiesel production.