Bench-scale, axenic cultivation facilitates microalgal characterization and productivity optimization before subsequent process scale-up. Photobioreactors provide the necessary control for reliable and reproducible microalgal experiments and can be adapted to safely cultivate microalgae with the corrosive gases (CO2, SO2, NO2) from municipal or industrial combustion emissions.
Photobioreactors are illuminated cultivation systems for experiments on phototrophic microorganisms. These systems provide a sterile environment for microalgal cultivation with temperature, pH, and gas composition and flow rate control. At bench-scale, photobioreactors are advantageous to researchers studying microalgal properties, productivity, and growth optimization. At industrial scales, photobioreactors can maintain product purity and improve production efficiency. The video describes the preparation and use of a bench-scale photobioreactor for microalgal cultivation, including the safe use of corrosive gas inputs, and details relevant biomass measurements and biomass productivity calculations. Specifically, the video illustrates microalgal culture storage and preparation for inoculation, photobioreactor assembly and sterilization, biomass concentration measurements, and a logistic model for microalgal biomass productivity with rate calculations including maximum and overall biomass productivities. Additionally, since there is growing interest in experiments to cultivate microalgae using simulated or real waste gas emissions, the video will cover the photobioreactor equipment adaptations necessary to work with corrosive gases and discuss safe sampling in such scenarios.
Photobioreactors are useful for controlled experiments and cultivation of purer microalgal products than can be achieved by open ponds. Microalgal cultivation in bench-scale photobioreactors supports the development of fundamental knowledge that may be used for process scale-up. Slight changes to environmental conditions can significantly alter microbiological experiments and confound the results1. A sterile process with temperature, pH, and gas sparging control is advantageous for studying microalgal properties and performance under varied conditions. Additionally, the control over input gas concentrations, temperature, shear force from mixing, and medium pH can support diverse species that are otherwise challenging to cultivate. Photobioreactors can be run as a batch process with continuous gas feed and sparging, or as a chemostat flow-through system with continuous gas feed and sparging plus influent and effluent wastewater nutrient inputs. Here, we demonstrate the batch process with continuous gas feed and sparging.
The use of photobioreactors addresses several microalgal cultivation and production challenges. The field generally struggles with concerns of contamination by other microorganisms, efficient substrate utilization (which is especially important in the case of CO2 mitigation or wastewater treatment)2, pH control, illumination variability, and biomass productivity3. Photobioreactors enable researchers to study a wide range of phototrophs in closely-controlled batch systems, where even slow growing species are protected from predators or competing microorganisms4. These batch systems are also better at facilitating greater CO2 utilization rates and biomass productivity because they are closed systems that are more likely to be in equilibrium with supplied gases. Photobioreactor technology also offers pH control, the lack of which has hindered high biomass productivity in past studies5. At bench scale, the level of control offered by photobioreactors is advantageous to researchers. At larger industrial scales, photobioreactors can be used to maintain commercial bioproduct purity and improve production efficiency for nutraceutical, cosmetic, food, or feed applications6.
Microalgae are of great interest for biosequestration of CO2 because they can rapidly fix CO2 as biomass carbon. However, most anthropogenic sources of CO2 are contaminated with other corrosive and toxic gases or contaminants (NOx, SOx, CO, Hg), depending on combustion process fuel source. Growing interest in sustainable CO2 sequestration has prompted development of photobioreactor technologies to treat CO2-rich emissions, such as those from coal-fired power plants (Table 1). Unfortunately, there is inherent risk of human and environmental exposure to the corrosive and toxic contaminants during research and scale-up processes. As such, describing the safe assembly and operation of bioreactors using corrosive gases is necessary and instructive.
This method is for the use of a 2 L bench-scale photobioreactor for the growth of microalgae under carefully controlled experimental conditions. The protocol describes microalgal storage, inoculum preparation, and photobioreactor setup and sterilization. Beyond basic operation, this work describes microalgal biomass measurements and biomass productivity calculations, and adaptation of the equipment for microalgal cultivation with corrosive gases. The protocol described below is appropriate for researchers seeking to exert greater experimental control, optimize microalgal growth conditions, or axenically culture a range of phototrophic microbes. This method does not describe appropriate materials for cultivation of microbes that produce or consume flammable gases (e.g. CH4, H2, etc.)7.
1. Safe use and sampling of a photobioreactor sparged with corrosive gases
NOTE: This method does not describe appropriate procedures for safe sampling of microalgal cultures that produce or consume highly flammable gases.
2. Preparation of the microalgal inoculum
3. Setup and operation of photobioreactor
4. Adapting the photobioreactor and experimental setup for toxic gas use
CAUTION: The corrosive gases in real or simulated flue gas are corrosive and toxic. These gases pose serious risk if inhaled.
NOTE: This method does not describe appropriate materials for safe cultivation of microbes that produce or consume highly flammable gases (i.e., methane, hydrogen, etc.).
5. Measuring microalgal biomass productivity
6. Biomass productivity modeling and rate calculations
A calibration curve for the green microalgae, S. obliquus, harvested in the exponential phase, was established with OD750 and dried biomass concentrations (Figure 2). The linear regression had an R2 value of 0.9996.
An S. obliquus culture was started in a 250 mL Erlenmeyer flask from a culture stored on a refrigerated agar plate. The microalga was inoculated in 3N-BBM with 10 mM HEPES buffer and sparged with 2.2% CO2 in a 2 L photobioreactor with 1.5 L working volume (0.07 vvm) (Figure 1). The batch was tracked via OD750; the biomass concentrations were calculated from the calibration curve, and then modeled with a logistic curve (Figure 3). The photobioreactor maintained the culture at pH 6.8, 100 cm3 min-1 total gas flow rate, continuous 280 μmol m-2 s-1 illumination, and 27 °C. The logistic curve fit biomass concentration data from lag to exponential to stationary phase. From the logistic model, the maximum biomass concentration during the batch was 2070 ± 20 mg L-1, maximum biomass productivity occurred at 4.6 day, and the rate of specific biomass productivity was 1.0 d-1. The maximum biomass productivity, calculated from the derivative of the logistic curve at the time of maximum growth, was 532 ± 60 mg L-1 d-1.
The well-mixed room model was used to calculate the accumulated concentration of NO2, SO2, and CO in the case of fume hood failure for 24 h. These values were compared to the exposure limits (Table 2). For example, in the scenario where 0.05 L min-1 of 400 ppm NO2 is released during a fume hood failure period of 24 h, the well-mixed room model with inputs of calculated G = 0.0377 mg min-1, Q = 0.0001 m3 min-1, V = 100 m3, and maximum time for simulation = 1440 min predicts NO2 accumulation to 0.54 mg m-3 (0.29 ppm), which is above the acceptable chronic exposure limit (American Conference of Governmental Industrial Hygienists threshold limit value [ACGIH TLV]) and below the short-term exposure limit (STEL).
A promising preliminary trial with simulated flue gas achieved a greater maximum microalgal biomass productivity rate (690 ± 70 mg L-1 d-1) than that of 12% CO2 and ultra-zero air (510 ± 40 mg L-1 d-1) (Figure 4). Prior to the experiment, a gas monitor was calibrated with CO, NO2, and SO2. The simulated flue gas experiment was carried out without any risk to personnel or damage to equipment from corrosive gases.
Figure 1: Bench-top photobioreactor illuminated by red and blue LED lights. The photobioreactor operates as a 2 L batch reactor with 1.5 L working volume. The photobioreactor is continuously fed with gases through the sparging ring and excess gas vents through ports in the headplate. Adapted with permission from Molitor et al.5. Please click here to view a larger version of this figure.
Figure 2: Calibration curve relating OD750 到 S. obliquus cell dry weight. S. obliquus cell culture light absorption was measured at 750 nm, then cells were filtered and dried to obtain cell dry weight measurements. Reprinted with permission from Molitor et al.5. Please click here to view a larger version of this figure.
Figure 3: S. obliquus growth data at 2.2% CO2 input modeled with a logistic regression. The data points represent biomass values as calculated from optical density measurements. The data have been modeled with a logistic regression through a least squares fit; where L = 1955 mg L-1, k = 1.154 d-1, and x0 = 3.317 d. R2 = 0.995. Please click here to view a larger version of this figure.
Figure 4: Modeled S. obliquus growth at 12% CO2, with and without additional simulated flue gas components. The biomass measurements from each batch of microalgae were modeled with logistic regressions. Please click here to view a larger version of this figure.
Component | Percent |
H2O | 12.6% |
CO2 | 11.6% |
O2 | 5.8% |
CO | 0.048% |
SO2 | 0.045% |
NO2 | 0.022% |
N2 | 69.9% |
Table 1: Composition of coal-fired power plant emissions. These quantities were averaged from the University of Iowa power plant emissions data collected at minute intervals over the span of 10 h.
Toxic gas | TWA | CEILING | STEL | NIOSH IDLH | NIOSH REL | ACGIH TLV | CDC Description |
CO | 35 ppm | 200 ppm | – | 1,200 ppm | 35 ppm | 25 ppm | Colorless, odorless |
SO2 | 2 ppm | 100 ppm | 5 ppm | 100 ppm | 2 ppm | 2 ppm | Colorless gas with a characteristic, irritating, pungent odor |
NO2 | 3 ppm | 5 ppm | 1 ppm | 13 ppm | 1 ppm | 0.2 ppm | Yellowish-brown liquid or reddish-brown gas (above 70 °F) with a pungent, acrid odor |
Table 2: Exposure limits and descriptions for toxic gases (CO, SO2, NO2) in flue gas. OSHA TWA: time weighted average (usually 8 h period), CEILING: value never to be reached, STEL: short-term exposure limit (TWA over 15 min), NIOSH IDLH: danger to life and health, NIOSH REL: 15 min exposure limit, ACGIH TLV: acceptable chronic exposure limit, no ill effects.
Compound | mM |
NaNO3 | 8.82 x 100 |
MgSO4·7H2O | 3.04 x 10-1 |
NaCl | 4.28 x 10-1 |
K2HPO4 | 4.31 x 10-1 |
KH2PO4 | 1.29 x 100 |
CaCl2·2H2O | 1.70 x 10-1 |
ZnSO4·7H2O | 3.07 x 10-2 |
MnCl2·4H2O | 7.28 x 10-3 |
MoO3 | 4.93 x 10-3 |
CuSO4·5H2O | 6.29 x 10-3 |
Co(NO3)2·6H2O | 1.68 x 10-3 |
H3BO3 | 1.85 x 10-1 |
EDTA | 1.71 x 10-1 |
KOH | 5.52 x 10-1 |
FeSO4·7H2O | 1.79 x 10-2 |
H2SO4 (concentrated) | 1 x 10-3 μL |
Table 3: Composition of triple-nitrogen Bold’s basal medium (3N-BBM). The quantity of nitrogen has been tripled from the original Bold’s basal medium11.
Batch, axenic photobioreactor experiments with regulated pH, temperature, gas flow rate, and gas concentration promote meaningful results by eliminating contamination by non-target algal strains and variability in culture conditions. Accurate pure culture growth kinetics can be obtained even in the presence of corrosive gases (CO2, SO2, NO2), which serve as nutrients, turning waste gases into a valuable product such as animal feed.
Prior to beginning any microalgal experiment, the chosen microalga culture should be taken from storage and readapted to liquid culture. Growing the microalgae into exponential phase improves the probability that experiments have equivalent initial conditions and that the microalgae do not stagnate in lag phase after inoculation.
Calibration curves relating optical density and biomass concentrations are especially important during studies of biomass productivity. High microalgal biomass productivity is one of the key goals of the microalgal industry and, as such, is often an indicator of research success12. Therefore, accurate calculations of biomass concentrations from optical density measurements must stem from species-specific, precise, and accurate calibration curve data. To avoid potential optical interferences, it is important that measurements for the calibration curve and during the experiment be made in equivalent background solutions. Additionally, the calibration curve should be made with measurements taken from microalgae in the growth phase(s) most representative of those in the experiments. Certain microalgal species can have dramatic differences in cell size during different growth phases which can alter the optical density and perceived biomass concentrations. It should be noted that biomass productivity is related to, but not equivalent to, growth rate. Specific growth rate depends on the number of cells (change in cell density over time/cell density) present, and specific biomass productivity depends on the bulk mass of cells (change in mg/L biomass over time per mg/L biomass)13 present.
When microalgal biomass concentrations are modeled with a logistic curve, experimental results can be meaningfully compared by interpolating biomass concentrations and accurately calculating biomass productivities. However, care should be taken when interpreting these experimental results; it is inappropriate to compare overall and maximum batch biomass productivity. While maximum biomass productivity values are useful to compare batch results, overall biomass productivity is misleading without further information on the experiment duration and microalgal growth phases. These rates change continuously during the lag, log growth, and stationary phases.
During experiments with corrosive gases which are characteristic of power plant or industrial combustion emissions, caution should be exercised for both human health and equipment longevity. Standard parts must be replaced with more robust materials, and consumables such as tubing should be inspected and replaced more frequently to resist corrosion, prevent leaks, and avoid human exposure. Extra safety measures and risk awareness are essential to safe and successful operation and sampling. The method is not appropriate for flammable gases because there is potential for gas accumulation within the headspace and the equipment is neither designed for such risks nor suitable for safe adaptation to such conditions.
The authors have nothing to disclose.
This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1546595. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The work was also supported by a University of Iowa Graduate and Professional Student Government research grant, and the University of Iowa Foundation, Allen S. Henry endowment. Research was conducted in the W. M. Keck Phytotechnologies Laboratory. The authors would like to thank the University of Iowa power plant staff, especially Mark Maxwell, for expertise and financial support for the simulated flue gases. The authors would also like to acknowledge Emily Moore for her assistance with sampling and analysis and Emily Greene for her assistance and participation in the protocol video.
Biostat A bioreactor | Sartorius Stedim | 2-liter bioreactor for microbial fermentation; designed to be autoclaved; pH, temperature, gas flow rate control | |
Bump test NO2 gas | Grainger | GAS34L-112-5 | Calibration gas for MultiRAE gas detector |
Bump test O2, CO, LEL gas | Grainger | GAS44ES-301A | Calibration gas for MultiRAE gas detector |
Bump test SO2 gas | Grainger | GAS34L-175-5 | Calibration gas for MultiRAE gas detector |
Corrosion resistant tubing for NO2 gas | Swagelok | SS-XT4TA4TA4-6 | PTFE Core Hose Smooth Bore X Series—Fiber Braid and 304 SS Braid Reinforcement |
Corrosion resistant tubing for SO2 gas | QC Supply | 120325 | Reinforced Braided Natural EVA Tubing – 1/4" ID |
cozIR 100% CO2 meter | Gas Sensing Solutions Ltd. | CM-0121 at CO2meter.com | CO2 meter for concentrations up to 100% |
cozIR 20% CO2 meter | Gas Sensing Solutions Ltd. | CM-0123 at CO2meter.com | CO2 meter for concentrations up to 20% |
Durapore Membrane Filter, 0.45 μm | Millipore Sigma | HVLP04700 | Hydrophilic, plain white, 47 mm diameter, 0.45 μm pore size, PVFD membrane filters |
Gas cylinder regulators | Praxair | PRS 40221331-660 | Single-stage stainless steel regulator configured for 0-15 psi outlet assembly diaphragm valve with 1/4" MNPT threads, Stainless steel to resist corrosion from NOx and SOx |
Gas cylinders | Praxair | Ulta-zero air, high purity CO2, or custom gas composition | Dependent on study objectives |
Gas monitoring and leak detection system | RAE Systems by Honeywell | MAB3000235E020 | Pumped model that detects O2, SO2, NO2, CO, and LEL |
GasLab software | GasLab | v2.0.8.14 | Software for CO2 meter measurements and data logging |
Hose barb | Grainger | Item # 3DTN3 | Used to adapt regulators to tubing, Stainless steel to resist corrosion from NOx and SOx |
K30 1% CO2 meter | Senseair | CM-0024 at CO2meter.com | CO2 meter for concentrations less than 1% |
LED grow panels | Roleadro | HY-MD-D169-S | Red & blue LED light panels |
Memosens dissolved oxygen probe | Endress+ Hauser | COS22D-19M6/0 | Autoclavable (with precautions) dissolved oxygen probe for bioreactor |
Memosens pH probe | Endress+ Hauser | CPS71D-7TB41 | Autoclavable (with precautions) pH probe for bioreactor |
Oven, Isotemp 500 Series | Fisher Scientific | 13246516GAQ | Small oven for drying |
Prism GraphPad software | GraphPad Software | Version 7.03 or 8.0.1 | Graphing software for data organization, data analysis, and publication-quality graphs |
Stem to hose barb fitting | Swagelok | SS-4-HC-A-6MTA | Stainless Steel Hose Connector, 6 mm Tube Adapter, 1/4 in. Hose ID |
Tubing, dilute acid/base transfer | Allied Electronics and Automation | 6678441 | Silicone TP Process Tubing; 1.6mm Bore Size; 3000mm Long; Food Grade |
Tubing, gas transfer | Allied Electronics and Automation | 6678444 | Silicone TP Process Tubing; 3.2mm Bore Size; 3000mm Long; Food Grade |