Growth kinetics of microalgae in microfluidic static droplet arrays
ABSTRACT We investigated growth kinetics of microalgae, Chlorella vulgaris, in immobilized arrays of nanoliter-scale microfluidic drops. These static drop arrays enabled simultaneous monitoring of growth of single as well as multiple cells encapsulated in individual droplets. To monitor the growth, individual drop volumes were kept nearly intact for more than a month by controlling the permeation of water in and out of the microfluidic device. The kinetic growth parameters were quantified by counting the increase in the number of cells in each drop over time. In addition to determining the kinetic parameters, the cell-size distribution of the microalgae was correlated with different stages of the growth. The single-cell growth kinetics of C. vulgaris showed significant heterogeneity. The specific growth rate ranged from 0.55 to 1.52 day(-1) for different single cells grown in the same microfluidic device. In comparison, the specific growth rate in bulk-scale experiment was 1.12 day(-1) . It was found that the average cell size changes significantly at different stages of the cell growth. The mean cell-size increased from 5.99 ± 1.08 to 7.33 ± 1.3 µm from exponential to stationary growth phase. In particular, when multiple cells are grown in individual drops, we find that in the stationary growth phase, the cell size increases with the age of cell suggesting enhanced accumulation of fatty acids in older cells. Biotechnol. Bioeng. © 2012 Wiley Periodicals, Inc.
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- "Since SCRS offers real-time monitoring and bioprocess diagnosis capabilities without prior knowledge of any cellular component or metabolite as biomarker, and needs no labeling to the cell, its application may not be limited to the investigation of TAG accumulation, but also to bio-prospecting of novel phenotypes in yet-to-be-culture or mutant cells. Further development in hardware and software, such as microfluidics devices, and more statistical tools should allow for improvement of the specificity, sensitivity, spatial resolution and throughput of SCRS, and establish it as a general approach for characterization, screening, isolation and in-depth analysis of microbial cells or live-cell-mediated processes for broad applications [11,41]. "
ABSTRACT: Rapid, real-time and label-free measurement of the cellular contents of biofuel molecules such as triacylglycerol (TAG) in populations at single-cell resolution are important for bioprocess control and understanding of the population heterogeneity. Raman microspectroscopy can directly detect the changes of metabolite profile in a cell and thus can potentially serve these purposes. Single-cell Raman spectra (SCRS) of the unicellular oleaginous microalgae Nannochloropsis oceanica from the cultures under nitrogen depletion (TAG-producing condition) and nitrogen repletion (non-TAG-producing condition) were sampled at eight time points during the first 96 hours upon the onset of nitrogen depletion. Single N. oceanica cells were captured by a 532-nm laser and the SCRS were acquired by the same laser within one second per cell. Using chemometric methods, the SCRS were able to discriminate cells between nitrogen-replete and nitrogen-depleted conditions at as early as 6 hours with >93.3% accuracy, and among the eight time points under nitrogen depletion with >90.4% accuracy. Quantitative prediction of TAG content in single cells was achieved and validated via SCRS and liquid chromatography-mass spectrometry (LC-MS) analysis at population level. SCRS revealed the dynamics of heterogeneity in TAG production among cells in each isogenic population. A significant negative correlation between TAG content and lipid unsaturation degree in individual microalgae cells was observed. Our results show that SCRS can serve as a label-free and non-invasive proxy for quantitatively tracking and screening cellular TAG content in real-time at single-cell level. Phenotypic comparison of single cells via SCRS should also help investigating the mechanisms of functional heterogeneity within a cellular population.Biotechnology for Biofuels 04/2014; 7(1):58. DOI:10.1186/1754-6834-7-58 · 6.22 Impact Factor
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- "Growth of the cultures was estimated by measurement the optical density at 530 nm and by counting cell number in a Burker chamber after appropriate dilution . The specific growth rate was calculated using the following equation: l ¼ dlnðFÞ=dðtÞ where l is the specific growth rate, N is the number of cells, and t is the time (Dewan et al., 2012). All the experiments performed in this study were conducted by using Nannochloropsis s. cell suspensions harvested after 7 days of nitrogen starvation, corresponding to 20 ± 2 mg/ml of dry biomass. "
ABSTRACT: Triacylglycerols recovery from wet microalgae is a key aspect of biodiesel production, because of the energetic balance gained from avoiding biomass drying. In order to isolate TAG from Nannochloropsis cells, the possibility to concentrate biomass and to recover TAG in a single step by membrane process was studied. Different polymeric membranes were selected and screened on the basis of adsorption test and permeation flux. Results showed that membrane of regenerated cellulose (RC) with nominal molecular weight cutoff of 100kDa and 30kDa gave the best performance. Indeed, permeate flux was stable during ultrafiltration experiment in concentration mode and no severe fouling/cake deposition was observed. Both membranes allowed to recover permeates with high content of triacylglicerols. However, a more purity of the triacylglicerols from the other co-products was only obtained with the 30kDa RC membrane because the retention of the unwanted proteins was in the range of 89%.Bioresource Technology 04/2013; 140C:172-178. DOI:10.1016/j.biortech.2013.04.073 · 5.04 Impact Factor
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ABSTRACT: Biological cells in a population are variable in practically every property. Much is known about how variability of single cells is reflected in the statistical properties of infinitely large populations; however, many biologically relevant situations entail finite times and intermediate-sized populations. The statistical properties of an ensemble of finite populations then come into focus, raising questions concerning inter-population variability and dependence on initial conditions. Recent technologies of microfluidic and microdroplet-based population growth realize these situations and make them immediately relevant for experiments and biotechnological application. We here study the statistical properties, arising from metabolic variability of single cells, in an ensemble of micro-populations grown to saturation in a finite environment such as a micro-droplet. We develop a discrete stochastic model for this growth process, describing the possible histories as a random walk in a phenotypic space with an absorbing boundary. Using a mapping to Polya's Urn, a classic problem of probability theory, we find that distributions approach a limiting inoculum-dependent form after a large number of divisions. Thus, population size and structure are random variables whose mean, variance and in general their distribution can reflect initial conditions after many generations of growth. Implications of our results to experiments and to biotechnology are discussed.PLoS ONE 12/2012; 7(12):e52105. DOI:10.1371/journal.pone.0052105 · 3.23 Impact Factor