Functional and phenotypic flow cytometry characterization of Picochlorum soloecismus

Algal Research 43 (2019) 101614

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Functional and phenotypic flow cytometry characterization of Picochlorum soloecismus

T

Christina R. Steadman Tyler , Claire K. Sanders, Reece S. Erickson, Taraka Dale, Scott N. Twary, Babetta L. Marrone ⁎

Los Alamos National Laboratory, Bioenergy & Biome Sciences, Los Alamos, NM 87545, USA

ARTICLE INFO

ABSTRACT

Keywords: Flow cytometry Lipid accumulation Microalgae Picochlorum Cellular phenotype

Multiple physiological traits essential for efficient cellular function are important when considering the selection and engineering of algal species for biofuel and bioproduct generation. Bioengineering methods have become more ubiquitous producing several novel algal lines with potentially enhanced traits. Complex metabolic interactions, however, require greater depth in characterizing cellular responses to delineate mechanistic understanding. We have developed fluorescence-based high-throughput flow cytometry protocols to facilitate characterization of cell morphology, membrane permeability, metabolic activity, cell viability, intracellular pH, and reactive oxygen species in isolates derived from the species Picochlorum soloecismus. Flow cytometry parameters were optimized for each assay. This suite of molecular flow cytometry probes and procedures can be utilized for rapid screening of optimal phenotypes in microalgae under various environmental conditions as new technical strategies for improving algae strain productivity are established.

1. Introduction Recent concerted efforts among multiple laboratories have focused on bioengineering of algal strains to improve productivity for establishing sustainable advanced biofuels and bioproducts [1–3]. One of the many challenges in improving microorganism functionality is identifying important physiological processes, bioengineering targeted metabolic pathways, and assessing both primary improvements and secondary characteristics resulting from these efforts. Microorganisms like algae have rapid and dynamic changes in cellular function that traditional bulk assays or molecular biology methods are unable to quantify [4,5]. Additionally, these assays fail to assess variability within populations that can be exploited for improved performance. Flow cytometry provides a means for rapid, high-throughput screening that can be applied to understand native metabolic functions and desired mutant phenotypes in different cell types [6]. Further, multiparameter singlecell analysis can be applied to determine physiological states allowing for sorting of highly viable or productive subpopulations of cells. Currently, assessment of algal health, even using flow cytometric methods, relies on cell morphology based on forward scatter (FSC) and side scatter (SSC) or algal chlorophyll autofluorescence [7,8]. The majority of flow cytometry dyes/probes and protocols have been developed for

mammalian and/or bacterial systems [9,10]. Adapting these dyes and protocols for assessment of algae is uniquely challenging due to complex cell structure including recalcitrant cell walls and high autofluorescence interference [11]. Thus, our goal was to identify appropriate dyes that could be applied to microalgae and develop simple, robust protocols for assessment of algal health and function that extends beyond cell size, optical density, and cell count measurements. Algal strain improvement focuses on the following characteristics: outdoor robustness, growth rate, tolerance to environmental variability, and increased production or utilization of available and abundant nutrients, all while minimizing the input costs to improve economic sustainability [12]. We chose molecular tools for characterizing processes in algae that are directly related to these value-added outcomes. Results and protocols described herein focus on assessment of the following indicators: 1) lipid accumulation, indicative of nutrient utilization and stress; 2) DNA content, indicative of DNA ploidy, providing information about cell cycle dynamics for individual cells and populations; 3) internal cellular pH, indicative of appropriate carbon fixation and biomass accumulation; 4) enzyme functionality and reactive oxygen species production,

⁎ Corresponding author at: Bioenergy and Biome Sciences, Bioscience Division, Los Alamos National Laboratory, PO Box 1663 MS M888, Los Alamos, NM 87545, USA. E-mail address: [email protected] (C.R. Steadman Tyler).

https://doi.org/10.1016/j.algal.2019.101614 Received 22 January 2019; Received in revised form 13 July 2019; Accepted 14 July 2019 Available online 06 September 2019 2211-9264/ © 2019 Elsevier B.V. All rights reserved.

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indicative of active metabolism or intracellular stress; 5) microtubule formation, indicative of cellular growth and health;

(indicative of high lipid accumulation) were isolated using a BD FACSAria II flow cytometer (BD Biosciences, San Jose, CA). Sorted populations were regrown on agar plates. This process was repeated for several sorting “rounds” until a stable population with distinctively higher BODIPY 505/515 fluorescence than the parent population was isolated. Two isolates were derived from the “Sorted-High” subpopulation: the first isolate was sorted on the top 10% of the BODIPY 505/515 signal and the middle 50% autofluorescence signal for two rounds of sorting and is referred to as P2. The second isolate was sorted on the top 10% of BODIPY 505/515 signal for four rounds of sorting of the “Sorted-High” (parent) population and is referred to as P3. P. soloecismus P1 (WT) and its two isolates, P2 and P3 were used for protocol development.

The goal is to track algal physiology and function to optimize genetic and environmental interactions for maximum productivity. Understanding the basis for these responses enhances targeted improvements, provides greater predictability of growth rates, provides potential points in time in which the cells are more malleable for genetic engineering, and indicates potentially poor health of algal cells that may require intervention. The microalgae species Picochlorum soloecismus was isolated at Los Alamos National Laboratory from a culture of Nannochloropsis salina 1776 (UTEX) [13,14]. Of several hundred microalgae species, P. soloecismus was selected by the National Alliance for Advanced Biofuels and Bioproducts (NAABB) consortium for biofuel applications given its industrial potential and highly adaptive responses to non-ideal growth conditions [15]. Our ongoing efforts in genetic engineering of this species require significant understanding of typical growth responses, functionality, and phenotype. We explored method development in this potential biofuel production species to identify unique improvements within selected lines.

2.3. Data acquisition and analysis Unless otherwise noted, multi-parameter flow cytometric analysis was conducted on all cells using a BD Accuri™ C6 Plus flow cytometer (BD Biosciences, San Jose, CA) equipped with 488 and 640 nm lasers. Flow cytometry data described herein was detected from the 488 nm laser, including forward scatter (FSC), side scatter (SSC), 533/30 (FL-1), 585/40 (FL-2), and 670 long pass (FL-3) filters. A standard startup protocol was run per manufacturer's instructions and included daily analysis of Spherotech 8-Peak Validation Beads (BD Biosciences, San Jose, CA, #653144) to verify instrument repeatability. Specific parameters for analysis of each dye are provided below. Flow cytometry data was analyzed using BD CSampler Plus Analysis software. Representative figures, including scatter plots and histograms, were generated using FCS Express 6 Flow Cytometry Software (DeNovo Software, Glendale, CA).

2. Methods and materials 2.1. Strain and culture conditions P. soloecismus “parent” wildtype and two isolate cultures were generated from cells on agar plates, inoculated in 1 l spin flasks, and maintained at ambient temperature, 800 μmolm−2 s−2 fluorescent light with a 16 h/8 h light:dark cycle, in modified f/2 media lacking silica and containing 8.8 mM sodium nitrate, 250 μM sodium phosphate monobasic monohydrate, standard trace metals and vitamins solutions, and Instant Ocean sea water [16,17]. Culture pH was maintained at 8.25 via probe-controlled mass flow of CO2. Cultures naturally deplete nitrate following several days of growth. Days in Culture are presented in all figures; nitrogen depletion occurred on day 6 in culture. Sterile sampling was used for obtaining aliquots on a daily basis; samples were stored at 4 °C prior to measurement of OD750 values and characteristic assessment using newly developed assays described herein. It should be noted that flow cytometric assessment of cellular characteristics is best performed on fresh samples. However, as protocol development requires a significant amount of time, all measurements (and protocols) were developed and performed using refrigerated samples (at least one month at 4 °C). Typically, samples cannot be snap frozen as this degrades the integrity of the cell walls: viable, whole intact cells are required to run through a flow cytometer instrument. These protocols described herein can be used with fresh samples (data not shown); however, the fluorescence signals are substantially greater. Thus, we do not recommend comparing flow data derived from fresh cells versus refrigerated cells with these probes.

2.4. Assessment of cell count, morphology, and autofluorescence P. soloecismus samples were collected from spin flasks and diluted with f/2 media (no Si) to an appropriate cell density to ensure a collection rate of 1000–10,000 events/s when run at a high flow rate (66 μl/min) on the BD Accuri™ C6 flow cytometer. Samples were run in quadruplicate in a 96-deep well plate for a fixed volume of 10 μl under fast fluidics setting with a threshold of 40,000 on forward scatter-height (FSC-H) to determine cell counts, light scatter, and chlorophyll content (autofluorescence). Gain adjustments are preset on the BD Accuri™ C6 Plus, which has a seven-log detection range. Cells were gated on forward scatter-area (FSC-A) vs side scatter-area (SSC-A) and included approximately 98% of the total event population. Cells within the primary gate are counted as cellular events per μl volume and final cell concentrations were determined by correcting for dilution factors and volume. FSC was used to determine relative cell size, with a higher FSC signal indicating a larger cell. Autofluorescence was assessed using the 488 nm excitation laser and 670 nm long pass emission filter. Microalgae cells can be monitored using chlorophyll autofluorescence as a proxy for algal health as chlorotic cells contain less chlorophyll and thus reduced autofluorescence [18].

2.2. Isolation of lipid accumulating subpopulations of Picochlorum soloecismus Flow cytometry methodology was used to isolate and characterize highly productive subpopulations of cells within the P. soloecismus culture. Previously, we reported on a population of “Sorted-High” P. soloecismus derived from multiple rounds of sequential fluorescence activated cell sorting (FACS) from the P. soloecismus parent species, referred to as P1 (WT) [1]. For FACS, cells were grown until nitrogen (N) depletion occurred, as determined by ion chromatography (see below). The cultures were maintained until there was significant accumulation of neutral lipids, as determined by staining with BODIPY 505/515 (ThermoFisher, Waltham, MA, #D3921, see Section 2.6.2) and analysis on a BD Accuri™ C6 flow cytometer (BD Biosciences, San Jose, CA). The top 10% of the BODIPY 505/515 stained population

2.5. Nitrate analysis via ion chromatography P. soloecismus samples from selected time points were centrifuged at 14,000 ×g for 5 min, at room temperature (RT). The supernatant was removed and diluted 1:10 in MilliQ water. Samples were analyzed using a Dionex ICS-100 ion chromatograph fitted with an AG23 (4 × 50 mm) guard column and an AS23 (4 × 250 mm) IonPac analysis column using SRS 300 suppressor and AS23 eluent concentrate (1:100 dilution with 4.5 mM sodium carbonate and 0.8 mM sodium bicarbonate). The SRS current was 22 mA. This analysis was performed to determine the exact day of nitrogen starvation in the cultures (data not shown) [18]. 2

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2.6. Staining protocols

at 9391 ×g and resuspended in f/2 media. H2O2-treated cells were then stained with the FDA probe as described above. Each algae sample was run in parallel with an internal H2O2-treated control. For all FDA experiments, the threshold for detection was 40,000 for FSC-H and 25,000 events were collected at a flow rate of 14 μl/min.

2.6.1. DNA content (DyeCycle Orange) DNA ploidy was determined in the P. soloecismus isolates over several days. Samples were obtained at the same time each day to determine the reproducibility and reliability of the dye. Cells were diluted 1:50 with f/2 media and incubated with 6.4 μM of DyeCycle Orange dye (DCO, ThermoFisher, Waltham, MA, #V35005) at 37 °C for 30 min. (This is 1 μl of 5 mM DCO in 776 ml total volume of media.) Cells were vortexed and allowed to incubate for an additional 15 min at RT in the dark. No spin or subsequent washings are necessary for this dye. The threshold for detection was set at 40,000 for FSC-H, and 50,000 events were collected at a flow rate of 14 μl/min.

2.6.5. Reactive oxygen species (chloromethyl-2′,7′-dichlorodihydrofluorescein diacetate) A stock solution of 200 μM chloromethyl-2′,7′-dichlorodihydrofluorescein diacetate (CM-H2DCFDA) (ThermoFisher, Waltham, MA, #C6827) was made with DMSO for each experiment. Algae cells were diluted 1:50 in LCIS and incubated with a final concentration of 10 μM CM-H2DCFDA for 4 h at RT in the dark. A positive control for each sample was made by treating the cells with 50 μl of 3% H2O2 during the incubation period with the dye. Minimal vortexing was performed every hour during the incubation period. Cells were centrifuged at 2348 ×g (5000 rpm) for 3 min, washed and resuspended in LCIS prior to assessment. (An Eppendorf 5424 bench-top centrifuge with a fixed angle rotor (FA-455-24-11) was used.) The threshold for detection was 40,000 for FSC-H and 25,000 events were collected at a flow rate of 14 μl/min.

2.6.2. Lipid accumulation (BODIPY 505/515) Cells were stained using our previously established protocols [1,18]. Briefly, algae cells were diluted 1:40 in f/2 media to obtain an event rate of approximately ~7000 cells/μl on the BD Accuri™ C6 Plus flow cytometer. Samples were incubated with approximately 22.6 μM of BODIPY 505/515 in 2.8% dimethyl sulfoxide (DMSO) for 30 min at RT in the dark prior to analysis. No spin or subsequent washings were necessary for this dye. The threshold for detection was set at 40,000 for FSC-H and 50,000 events were collected at a flow rate of 14 μl/min.

2.6.6. Cellular structure (phalloidin) Cells were fixed and permeabilized prior to incubation with phalloidin dye (ThermoFisher, Waltham, MA, #A12379) as follows: 250 μl of algal culture was centrifuged at 2348 ×g for 3 min at RT and resuspended in 500 μl of 4% paraformaldehyde (PFA, Image-it™ Fixative solution; ThermoFisher, Waltham, MA, #FB002) and incubated for 15 min at RT. After incubation with 4% PFA, cells were centrifuged at 2348 ×g for 3 min at RT and resuspended in 500 μl of 25% ethanol (and water). Cells were incubated in ethanol for 1 h at 37 °C (in the dark), centrifuged at 2348 ×g for 3 min at RT, and resuspended in 500 μl f/2 media. The phalloidin desiccate was dissolved in 1.5 mL 100% methanol; 15 μl of this solution was added to 5 μl of cells. Cells were incubated with the dye for 45 min at 37 °C in the dark. The volume of solution was brought to 500 μl with LCIS and samples were loaded into a 96-well plate in triplicate. Unstained controls (treated with 15 μl of methanol) were run in parallel with all stained samples. Further incubation for 1 h at RT (in the dark) was performed prior to flow cytometry assessment. For all phalloidin experiments, the threshold for detection was 40,000 for FSC-H and 25,000 events were collected at a flow rate of 14 μl/min.

2.6.3. Intracellular pH (pHrodo Green AM) Cells were diluted 1:50 in live cell imaging solution (LCIS, ThermoFisher, Waltham, MA, #A14291DJ) to obtain an event rate of approximately ~6500 cells/μl. pHrodo Green AM™ dye (ThermoFisher, Waltham, MA, #P35373) was reconstituted in PowerLoad solution (1:10) per the manufacturer's instructions. From this stock solution, the appropriate quantity of the diluted dye was added to algae cells for a final concentration of 4 μM. Cells were incubated at 37 °C for 1 h in the dark and then centrifuged at 9391 ×g (10,000 rpm) for 5 min and washed with LCIS two times. (An Eppendorf 5424 bench-top centrifuge with a fixed angle rotor (FA-455-24-11) was used.) Washing of cells is critical to generate an optimal signal from this probe. An intracellular pH calibration buffer kit (ThermoFisher, Waltham, MA, #P35379) was used equilibrate the internal pH of cells to a known pH. After incubation with the dye, samples were resuspended in buffers of appropriate pH (4.5, 5.5, 6.5, 7.5) containing 10 μM nigericin and 10 μM valinomycin and incubated for an additional 10 min at 37 °C after the second wash and centrifugation. The threshold for detection was set at 40,000 for FSC-H and 25,000 events were collected at a flow rate of 14 μl/min. Data derived from the intracellular calibration kit was used to generate a linear regression plot for direct quantification of pH for each sample.

2.7. Statistics Statistical analyses were conducted on GraphPad Prism 6 Software, version 6.03 (GraphPad Software, San Diego, CA). Comparison of outputs from the P1, P2, and P3 populations for a single timepoint was assessed using one-factor analysis of variance (ANOVA) with a post-hoc Bonferroni correction. Multi-day comparisons over the time course among all three populations was assessed using a repeated measures two-factor ANOVA with a post-hoc Bonferroni correction. A student's ttest was used to determine significant differences in signals derived from an individual population and its respective positive or negative control. p-Values < 0.05 were considered significant. Details for all analyses are provided in the Results section, while F and p-values are provided in Supplementary Table 1.

2.6.4. Cellular viability (fluorescein diacetate) A 10 μM stock solution of fluorescein diacetate (FDA, ThermoFisher; Waltham, MA, #F1303) in DMSO was generated, and for each flow cytometry experiment, the stock solution was diluted with f/2 media and MilliQ water for a final working concentration of 12 nM in the algal cell suspension. Cells were diluted 1:100 in f/2 media and incubated with FDA for 45 min at RT (in the dark). After incubation, cells were washed with f/2 media and centrifuged for 5 min at 9391 ×g at RT two times. The supernatant was removed and algal cells were resuspended in LCIS. While the fluorescence signal decreased after each wash (with FDA potentially leaking out of cells), the washes were essential to overcome the potential fluorescein signal derived from cleavage in the absence of cells. Controls with FDA in LCIS solution without algae cells were analyzed concurrently with samples. The fluorescence signal derived from these controls (10 μl of solution) was subtracted as background from the fluorescence signal derived from the algae cells incubated with FDA dye. An appropriate negative control was used to determine a baseline for the viability signal. For this negative control, algal cells were diluted 1:100 in water and treated with 10 μl of H2O2 (3%) for 10 min. After H2O2 treatment, cells were centrifuged for 5 min

3. Results 3.1. Growth of P. soloecismus isolates under nitrogen starvation conditions P. soloecismus WT (P1) and isolates P2 and P3 were used for assay development. This species will rapidly accumulate neutral lipids in the form of C16 and C18 under nitrogen depletion culture conditions demonstrating its value as a potential biofuel production strain [14]. 3

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Fig. 1. Traditional flow cytometry assessment of microalgae growth includes optical density, cell size, and cell counts. A) Optical density measurements at 750 nm over the lifecycle of P. soloecismus wildtype (P1) and its isolates P2 and P3 during nitrogen starvation, which occurred on Day 6 of Days in Culture. B) Cell counts per ml of cell culture over the time course determined by flow cytometry, p < 0.0001. C) Representative dot plot of side scatter (SSC) versus forward scatter (FSC) of P. soloecismus WT P1 (green), P2 (red), and P3 (blue) during nitrogen starvation. D) Analysis of FSC over Days in Culture for P1 and its isolates P2 and P3, p < 0.0001. FSC of P2 is approximately 1.5 times larger than P1, and the FSC of P3 is approximately three times larger than P1. Supplemental Table 1 provides F and p values for all repeated measures, two-factor ANOVA statistical assessments. Analytical triplicates were assayed for all measurements, except cell counts which were done in quadruplicate. Data are shown as mean ± SEM (standard error of the mean); ****p < 0.0001 for P3 isolate compared with P1 and P2. P1 = parent P. soloecismus wildtype (green) P2 = isolate 1 of parent population (red) P3 = isolate 2 of parent population (blue). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Growth of isolates was monitored for approximately 36 days by optical density at 750 nm (Fig. 1A). Nitrogen depletion occurred at day 6 in culture. Cell counts and relative size were acquired from FSC and SSC signals for all flow cytometry experiments. The P1 culture contains significantly more cells than both P2 and P3 cultures (p < 0.0001) and cell counts do not significantly increase over time after N-depletion (Fig. 1B). Fig. 1C shows a representative dot plot of SSC vs FSC of the three isolates demonstrating that P3 (blue) has larger FSC than the other two isolates (shown in green and red). This is quantified in Fig. 1D, demonstrating that the P3 isolate is significantly larger than P1 and P2 (p < 0.0001). F and p values from ANOVA analyses are provided in Supplementary Table 1. Microscopy images of the isolates (Fig. 2) reveal morphological differences among the isolates; it appears that the P3 isolate may be a tetrad (images on the far right, Fig. 2).

fluorescence [19]. DyeCycle Orange™ was selected for two main reasons: 1) the fluorescence emission spectrum of this dye does not overlap with autofluorescence or BODIPY 505/515 emission spectra (see below), thus allowing for multiplexing; 2) this dye does not require fixation to readily cross cell membranes and walls. After DyeCycle Orange™ permeates the cell wall, it partitions into subcellular compartments and binds to double-stranded DNA in a stoichiometric fashion. As cells grow and divide, the total DNA content is altered in a cyclical nature that can be directly detected as DyeCycle Orange™ fluorescence. Supplementary Fig. 1 shows representative data from days 10, 20, and 30 in culture for the isolates demonstrating the repeatability of DyeCycle Orange™ staining and the consistency of DNA content across the growth period. Fig. 3A shows overlays of histograms (plotted as DCO intensity versus cell count) demonstrating single primary populations of cells in P1 and P2, and three distinct populations of cells in P3. Gates drawn over each peak provide quantitative assessment of the fraction of cells and approximate DNA content of those cells based on fluorescence. As DyeCycle Orange™ binds to dsDNA in a stoichiometric

3.2. DNA content using DyeCycle Orange™ Several probes exist for directly determining DNA content, but many of them require fixation or spectrally overlap with chlorophyll 4

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Fig. 2. 100× Brightfield microscopy images depicting differences in morphology among P. soloecismus wildtype (P1) and its flow-sorted isolates, P2 and P3.

fashion, its fluorescence is directly proportional to total DNA content. Reports suggest that Picochlorum sp. is haploid [7,14,20]. The approximate DNA ploidy (N) is indicated in Fig. 3B and C as N = 1, 2, 4, or 8, where we designate that N = 1 is haploid. This analysis suggests that most cells comprising the parent (P1) population are in the haploid state as a single synchronized population. P2 isolate cells contain twice the DNA of the parent population (N = 2), with the majority of cells in the diploid state. The P3 population contains approximately two to four times the DNA of P1 and seems to lack haploid cells, thus containing three distinct, unsynchronized populations of cells with different ploidy. Based on this analysis, P1 is primarily haploid, P2 is primarily diploid, and P3 is divided between diploid and tetrad. The number of events per gate (where N = 1, 2, 4, or 8) out of total events (% events) were determined for each isolate as shown in Fig. 3B. The mean fluorescence intensity in each of the gates is approximately twofold of the previous gate (Fig. 3C). Given these data, isolates from P. soloecismus may potentially have differences in cell cycle dynamics and circadian rhythms. It should be noted that cell division has ceased for these samples due to N-depletion and cell counts are not significantly increasing (Fig. 1C). DyeCycle Orange™ can be used to define cellular growth and replication which are likely to be highly specific not only for a given species of microalgae but for sorted isolates.

temperature, nutrient availability, light intensity, and the photoperiod cue the formation of lipids in microalgae species [21–23]. Researchers have utilized the BODIPY 505/515 probe to assess total neutral lipid content in microalgae cells, particularly after nitrogen depletion [24]. This nonpolar, lipophilic dye rapidly diffuses across the cell membrane and/or cell wall and binds to neutral lipids. Its fluorescence is directly proportional to total neutral lipid content within the cell with linear correlations to analytical FAME (fatty acid methyl ester) analysis [25]; thus, this dye functions as an appropriate proxy for lipid content. Studies have demonstrated that BODIPY 505/515 is a superior dye compared to Nile Red, not only for its insensitively to light and oxidation but also for its maintained fluorescence [24,26,27]. However, the use of BODIPY 505/515 for lipid accumulation in microalgae cells is not universal as the response of the dye is species dependent. Previous research performed at LANL has demonstrated the efficient, robust use of BODIPY 505/515 to assess total lipid content in P. soloecismus and subsequent isolates generated via FACS [1]. Here, we recapitulated growth of the P. soloecismus wildtype (P1) and sorted isolates under nitrogen depletion conditions and measured their subsequent lipid accumulation (as described in Methods Section 2.6.2). A representative histogram of BODIPY 505/515 fluorescence from the P1 and P3 isolates at days 10 and 30 in culture is shown in Fig. 4A. Lipid accumulation increases (as observed via right-shift in the fluorescence signal) as the days in culture increase. Fig. 4B shows the mean fluorescence intensity of BODIPY 505/515 for each isolate over the time course during nitrogen depletion. These data suggest that the P3 isolate accumulated significantly more neutral lipids than P1 and P2 (p < 0.0001). However, the greater the cell size, the greater number of dye molecules partition into the cells; thus, it is necessary to take

3.3. Lipid accumulation using BODIPY 505/515 Morphological and DNA ploidy differences in isolated populations of P. soloecismus may result in differential responses to stress and subsequently divergent cellular phenotypes. Several reports demonstrate that environmental stress or stimuli, including changes in pH,

Fig. 3. DNA ploidy assessment in P. soloecismus wildtype and its isolates using DyeCycle Orange fluorescent probe. A) Overlay of DCO intensity vs cell count at 30 days in culture for the P. soloecismus isolates P1 (green), P2 (red), and P3 (blue). B) Quantitative assessment of the approximately percentage of the DCO fluorescence intensity in each gate for each isolate. N indicates relative ploidy, where N = 1 is haploid, N = 2 is diploid, etc. C) Differences in mean fluorescence intensity (A.U. = arbitrary units) for each gate. DCO intensity was measured in triplicate for each isolate at each timepoint; data are shown as mean ± SEM (standard error of the mean). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 5

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Fig. 4. Lipid accumulation assessment in P. soloecismus wildtype and its isolates using BODIPY 505/515 fluorescent probe. A) Fluorescence intensity of cells stained with BODIPY (505/515) used to measure lipid accumulation in P. soloecismus P1 and its isolates P2 and P3, over the time course during N-depletion. The BODIPY signal increases along the time course for all isolates. P1 and P3 on days 6 and 30 are shown in the representative histogram; complete N-starvation occurred at day 6 in culture. B) Quantification of fluorescence intensity of BODIPY (505/515) dye for P1, P2, and P3 over the time course. Supplemental Table 1 provides F and p values for all repeated measures, two-factor ANOVA statistical assessments. BODIPY 505/515 intensity was measured in triplicate for each isolate at each timepoint. Data are shown as mean ± SEM (error bars are difficult to see due to scale); ****p < 0.0001 for P3 isolate compared with P1 and P2.

We developed a protocol for measuring intracellular pH in P. soloecismus using pHrodo Green AM™ dye. This rhodamine-based indicator dye partitions easily into the cell, where upon entry, its lipophilic acetoxymethyl ester (AM) groups are cleaved by intracellular non-specific esterases. The uncharged probe is retained within the cell and interacts with hydrogen ions resulting in fluorescence. While it is unknown which organelle this dye localizes to once inside the algal cell, pHrodo Green AM™ has previously been used to detect changes in pH during macrophage engulfment of apoptotic cells [29,32]. The cleaved probe is photo-stable once inside the cell, and quantification of the intracellular pH is accomplished using calibration buffers containing nigericin and valinomycin which equilibrate the internal with the external pH. The fluorescence is weak at neutral pH (pKa 6.5), but as pH decreases (more binding of H+ ions with probe), the fluorescence of the dye increases. The pKa of 6.5 is ideal for algal species as the intracellular pH of naïve untransformed cells is 6.8. When used with calibration buffers, this dye is able to detect small changes in pH ranging from pH 4–9. Additionally, given its excitation/emission spectra (510/533), pHrodo Green AM™ is optimal for avoiding signal interference from chlorophyll autofluorescence. Multiple experiments were performed to determine the optimal concentration of the dye, the volume of incubation solution, and the number of algae cells. Supplementary Fig. 3 shows a representative flow cytometry histogram of unstained P. soloecismus cells, with gates dividing the presumably healthy, live population (to the right) and presumably dead, unhealthy population (to the left), based on autofluorescence. Cells with low autofluorescence either do not uptake the dye readily, the dye leaks out, or they potentially have a higher pH than those live cell populations (left histogram in A1). The media pH is maintained at 8.25 for lined-in CO2 spinner flasks. Unhealthy algae populations have compromised membrane integrity that could be contributing to the higher pH assessed (potentially due to refrigeration). This is quantified using mean fluorescence intensity and reveals that if the dead population were assessed, the ideal algal cell dilution is 1:10 in total volume (Supplementary Fig. 3B). However, two populations emerge from the high autofluorescent algal cells after staining with the dye (histogram to the right). One signal (A2, left) is derived from cells that do not uptake the dye; the other signal (A2, right) is derived from cells that readily uptake the dye. Supplementary Fig. 3C shows that an ideal dilution is closer to x = 0.04 (1:25) of the total

cellular characteristics into account when performing comparative analysis using flow cytometric data. Supplementary Fig. 2A shows BODIPY 505/515 fluorescence normalized to FSC to determine size-corrected lipid content for the isolates. While FSC can be used as an approximation of cell size, precise measurements of cell size depend on the optical and electronic characteristics of the flow cytometer, the cell type, and where the cell is in its growth cycle [28]. Supplementary Fig. 2B shows BODIPY 505/515 fluorescence multiplied by the total number of cells in culture as another method for analysis of lipid accumulation. This analysis represents a better overall perspective of total productivity of the cultures. Statistical analyses, including F and p-values for repeated measures, two-way ANOVA with Bonferroni correction for post-hoc analyses are provided in Supplementary Table 1. While these data suggest that the P3 isolate may accumulate lipids at a different rate, further analysis into stress (and other environmental perturbations) and cellular characteristics among the isolates must be taken into account. 3.4. Intracellular pH using pHrodo-Green AM™ Photosynthetic species, including many species of algae, strictly control pH during the conversion of fixed carbon dioxide into carbohydrates, proteins, and lipids. To further understand carbon fixation, biomass accumulation, and the behavior of these isolates, a protocol for assessing intracellular pH was developed. Several dyes can be utilized with flow cytometry to determine intracellular pH. The most common, BCECF (2′,7′-Bis-(2-Carboxyethyl)-5-(and-6)-carboxyfluorescein), is a fluorescein-based dye that red-shifts as pH increases; however, BCECF is a ratiometric dye, requiring dual excitation and detection to measure pH changes [29,30]. Fluorescence intensity ratios based on two excitation profiles are therefore required for calculation of the pH along with calibration curves limiting excitation and emission spectra for multiplexing with other fluorescent probes. Additionally, one of the required excitation wavelengths is not widely available on flow cytometers. For our purposes, we sought to develop a simple, efficient protocol using a fluorescent probe that would not only respond to changes in pH but also maintain steady state fluorescence, as photobleaching is a common issue with all fluorescein-based probes [31]. To fulfill these requirements, a different, more selective probe with a narrower excitation and emission spectra was chosen. 6

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Fig. 5. Calibration curves are required for pHrodo Green AM™ measurement of intracellular pH in P. soloecismus and its isolates. A) Representative histogram of pHrodo Green AM fluorescence signal from P. soloecismus WT (P1) cells. The sample was treated with buffers from a calibration kit at pH 7.5 (blue line) and pH 6.5 (red line). The signal from the untreated sample is shown in black. B) The MFIs from the sample incubated with the dye and appropriate calibration buffers (pH 4.5, 5.5, 6.5, and 7.5) are used to generate a linear regression plot to determine the pH of the sample. C) 2D scatter plot depicting autofluorescence (Y-axis) versus pHrodo Green AM dye fluorescence intensity (X-axis) for P. soloecismus WT (P1) cells at day 6 in culture. The line indicates division of low versus high autofluorescent populations with approximately 97% of the P1 population with high autofluorescence. D) 2D scatter plot depicting autofluorescence (Yaxis) versus pHrodo Green AM dye fluorescence intensity (X-axis) for P. soloecismus WT (P1) cells at day 30 in culture with approximately 77% of the P1 population with high autofluorescence. As days in culture progress, the percentage of high autofluorescent cells decreases. E) The calculated intracellular pH of P. soloecismus cells with high autofluorescence in the P1, P2, and P3 isolate populations. At days 15, 20, 25, and 30 in culture, the P2 isolate has a significantly higher pH than P1 and P3 isolates. pHrodo Green AM fluorescence intensity was measured in triplicate for each isolate at each timepoint; data are shown as mean ± SEM (standard error of the mean); ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05. F) The calculated intracellular pH of P. soloecismus cells with low autofluorescence in the P1, P2, and P3 isolate populations. At days 15, 20, 25, and 30 in culture, all isolates have close to the same pH in the low autofluorescent population of cells. pHrodo Green AM fluorescence intensity was measured in triplicate for each isolate at each timepoint; data are shown as mean ± SEM (standard error of the mean); ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05. Supplemental Table 1 provides F and p values for all repeated measures, two-factor ANOVA statistical assessments. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Fig. 6. Representative flow cytometry 2D scatter plots of P. soloecismus wildtype (P1) demonstrating changes in fluorescein diacetate signal after treatment with hydrogen peroxide. A) Representative 2D scatter plot of P. soloecismus WT P1 unstained cells showing two distinct autofluorescent populations (low and high) separated by black line. B) 2D scatter plot of P. soloecismus WT P1 cells stained with fluorescein diacetate (FDA) results in new population of cells (right shifted) with increased FDA intensity, indicative of metabolically healthy cells. C) 2D scatter plot of P. soloecismus WT P1 cells treated with H2O2 and then stained with FDA; the FDA-stained population has shifted to the left indicating lower FDA intensity and unhealthy cells. The low autofluorescent population remains unchanged, suggesting that H2O2 treatment inhibits viability and activity but does not induce cell death. D) Mean fluorescence intensity of the FDA probe at days 10, 20, and 30 in culture for the P1 isolate showing negative control treatment with H2O2. FDA fluorescence intensity was measured in triplicate for each isolate at each timepoint and for each treatment. Data are shown as mean ± SEM.

volume. The saturation of the interaction between the dye and algae cells was determined for solutions of cells at pH 4.5 and pH 7.5, using buffers provided in the ThermoFisher calibration kit (as described in Methods Section 2.6.3). As with most biomolecules, an inverted U-histogram of saturation was found using the pHrodo Green AM™ probe. Even at high concentrations, a sub-population of cells did not uptake the dye. Saturation curves generated from the mean fluorescence intensity of the dye versus dye concentration (μM) incubated in P. soloecismus WT cells are shown in Supplementary Fig. 3D and E. Saturation curves were generated for P. soloecismus WT cells, treated with buffers to induce an intracellular pH of 4.5 or 7.5. The mean fluorescence intensity (MFI) derived from P. soloecismus WT treated with calibration buffers at pH 4.5 and pH 7.5 stained with pHrodo Green AM™ dye is shown in Supplementary Fig. 3F. Fluorescence intensity of the dye increases as pH decreases; algae cells equilibrated in a pH 7.5 buffer exhibit weaker fluorescence than those adjusted to pH 4.5. From these experiments, we determined the optimal dilution of algae (1:50) and dye (4 μM) for assessing intracellular pH of the isolates with this probe. Fig. 5A shows a representative figure of the fluorescence signal from P. soloecismus WT (P1) incubated with buffers of pH 6.5 and 7.5 and a linear regression plot generated from the fluorescence data (Fig. 5B). To determine the intracellular pH during nitrogen depletion, samples from culture days 0, 10, 15, 20, 25, and 30 for all isolates were stained with pHrodo Green AM™, and a customized calibration curve was generated for each sample. Given the differences in staining among high and low autofluorescent populations, a gate dividing these populations was used prior to mean fluorescence intensity assessment (Supplementary Fig. 3A). The pH was calculated for both low and high autofluorescent populations at each time point for each isolate (Supplementary Fig. 4A–C). Repeated measures, two-way ANOVA analysis comparing low and high autofluorescent populations over days in culture for each isolate is provided in Supplementary Table 1. A summary of this data is shown for high (Fig. 5E) and low (Fig. 5F) autofluorescent populations for all three isolates. Variability in pH is seen among the isolates in the high but not the low autofluorescent populations. The pH should provide information for the carbon use efficiency of the cell; while the pH of the culture is typically 8.25 (in pH-controlled growth chambers using CO2 on demand), the pH of the cells is a better indication of how well the cells are utilizing carbon. Potentially, a higher pH in this case may constitute less lipid accumulation. The pattern of pH for the isolates coincides with the BODIPY 505/515 data on lipid accumulation, in which, even when accounting for cell size or ploidy, the P2 isolate accumulated significantly less lipid than both P1 and P3. These data demonstrate that pHrodo Green AM™ probe dynamically responds to changes in pH over the growth cycle.

3.5. Metabolic activity using fluorescein diacetate Cell viability can be assessed using fluorescein diacetate. Modification of the fluorescein diacetate molecule with AM ester groups forms an uncharged probe that easily permeates cell membranes. Once inside the cell, the lipophilic AM groups are cleaved by nonspecific esterases. The activity of these esterases can be used as a proxy for cellular health, viability, and metabolism. The resulting fluorescein molecule is fluorescent and retained within the cell after cleavage. This probe has previously been used in marine algae [33], but is not without its disadvantages. As other researchers have noted, fluorescein diacetate dye has multiple issues including, 1) leakage out of live cells, 2) conversion or hydrolysis to fluorescein in the absence of live cells, and 3) fluorescence quenching [31]. To overcome these confounds we included several wash steps (see Methods Section 2.6.4) to mitigate loss of the fluorescence signal over time and to subtract the potential signal derived from cleavage in the absence of cells. Controls with fluorescein diacetate in LCIS solution without algae cells were analyzed concurrently with samples. Further, control samples were run to determine the background signal and a baseline for the viability signal. We previously experimented with DMSO and menadione as treatments to induce cellular stress resulting in reduction in the fluorescein diacetate signal [34,35]. These treatments either interfered with the fluorescence signal (i.e. fluorescein diacetate signal increased with DMSO likely due to better partitioning into the cells but did not provide a very good positive control) or did not provide significant stress in the algae cells. Treatment with H2O2 provided the best negative control. Algae cells from the P1 culture from Day 6 were used for developing the protocol with the fluorescein diacetate probe. Flow cytometry 2D scatter plots depicting autofluorescence vs FDA probe fluorescence are shown in Fig. 6. Two distinctive autofluorescent populations are present in P. soloecismus WT (P1) cells (Fig. 6A); after staining with fluorescein diacetate, a new population is observed (Fig. 6B). This fluorescence is indicative of a healthy, viable algae cell population. Treatment with H2O2 inhibits viability and metabolic activity, as show in Fig. 6C. The stained population has shifted to the left in the scatter plot, indicating lower fluorescein diacetate intensity and unhealthy cells. The low autofluorescent (and unstained) population remains unchanged as seen in all three scatter plots, further strengthening the conclusion that these are unhealthy or dead cells. Thus, H2O2 treated cells can be used as a proxy for unhealthy algae populations providing a good negative control for this dye. Fig. 6D shows a representative plot of FDA mean fluorescence intensity of the P1 isolate for cells untreated and treated with H2O2, demonstrating quantification of the negative control. The P2 and P3 isolates responded in the same manner to H2O2 treatment as the P1 isolate (data not shown). 8

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Fig. 7. Flow cytometric analysis of cell viability using FDA probe and oxidative stress using CM-H2DCFDA in P. soloecismus isolates. A) Total FDA fluorescence for P1, P2, P3 samples on days 10, 20, 30 in culture. B) Mean fluorescence intensity of the CM-H2DCFDA probe for days 10, 20, and 30 in culture for all isolates. FDA and CM-H2DCFDA fluorescence intensity were each measured in triplicate for each isolate at every time point. Data are shown as mean ± SEM (standard error of the mean); ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05.

Cell viability was determined for all three isolates over the time course during N-depletion. Quantitative assessment of fluorescein diacetate mean fluorescence intensity (FDA MFI) data for all isolates at days 10, 20, and 30 in culture is shown in Fig. 7A. For all isolates, as the number of days in culture increases, the fluorescence intensity of healthy, viable cells diminishes, particularly between days 10 and 20 (p < 0.0001). Fluorescein diacetate fluorescence is dependent upon cell size (i.e. more fluorescein diacetate dye partitions into a larger cell resulting in a greater fluorescence signal); thus, a better indication of cell viability is the ratio of FDA fluorescence to FSC-A, an approximation of cell size as noted in the above discussion on BODIPY fluorescence. The ratio of fluorescein diacetate fluorescence intensity to FSC for all isolates on days 10, 20, and 30 in culture is shown in Supplementary Fig. 5. Again, analysis of flow cytometry data requires consideration of the behavior of the dye itself before making conclusions. Two-way, repeated measures ANOVA statistical analysis of FDA/FSC, including F and p-values, is provided Supplementary Table 1. Overall, cells lose viability as the days in culture progress during Ndepletion, suggesting that the fluorescein diacetate probe can be used to detect dynamic changes in viability. To further demonstrate that the dye can distinguish among physiological states, analysis of cell viability was performed on the P1 isolate during light and dark phases of the cell cycle. The fluorescein diacetate fluorescence in P1 is greater (p < 0.0001) in the dark cycle than in the light part of the cycle; samples were taken approximately 6 h apart from one another. This demonstrates the sensitivity of the fluorescein diacetate probe, as a traditional bulk assay would likely not detect the new population of highly viable cells in the dark portion of the cell cycle. See Supplementary Fig. 6A.

species resulting in oxidative damage that disrupts cellular metabolism, interferes with photosynthetic processes in microalgae, and if left unregulated, eventually results in cell death [36]. However, research suggests that increased production of long-chain fatty acids may induce the formation of ROS antioxidants, and reactive oxygen species may function as a secondary regulator of lipid metabolism [37]. Monitoring oxidative products is useful for assessing algal health and may be utilized as an early indicator of pond performance and productivity. Detecting reactive oxygen species and subsequent oxidative damage in biological systems is challenging due to probe sensitivity and specificity. The 2′,7′-dichlorodihydrofluorescein diacetate (H2DCFDA) probe has been used ubiquitously in biomedical research to detect reactive oxygen species intermediates [38]. This dye is cell-permeant and its acetate groups are cleaved via intracellular esterases; after cleavage, the dye becomes oxidized via interaction with reactive oxygen species and is converted from nonfluorescent H2DCFDA to fluorescent 2′,7′-dichlorofluorescein (DCF). This probe is widely used for directly assessing cell redox states for several reasons. The probe is easy to use, relatively inexpensive, sensitive to changes in redox potential, and useful for repeated measures experiments to monitor changes in redox state over time [39]. However, H2DCFDA responds to all reactive oxygen species and therefore cannot be used to directly measure specific reactive oxygen species, such as nitric oxide. Additionally, the fluorescent DCF molecule functions in a feed forward manner to prime the formation of itself via photosensitizing H2DCFDA for oxidation resulting in production of new free radicals. Typically, H2DCFDA must be used in conjunction with a cell viability indicator to determine the reactive oxygen species production from live cells. The chloromethyl derivative of H2DCFDA (CM-H2DCFDA) is retained only within live cells, thus eliminating the need for multiplexing with a cell viability indicator [39]. The chloromethyl group (CM) on CM-H2DCFDA also aids in assessing cellular stress. The chloromethyl group reacts with glutathione and other thiols producing a fluorescent adduct which remains trapped within the live cell; therefore, this probe is stable over time after oxidation. The CM-H2DCFDA probe was utilized to assess cellular stress (for which we refrain from specifying particular reactive oxygen species) in the P. soloecismus isolates throughout the time course under nitrogen depletion conditions. Similar to the fluorescein diacetate protocol development, H2O2 was used as a control when assessing the uptake of the dye; treatment with H2O2 increased reactive oxygen species production and dye fluorescence (data not shown). Fig. 7B shows the mean CM-H2DCFDA fluorescence intensity of each isolate for days 10, 20, and 30 in culture. As days in culture progress, each isolate produces less reactive oxygen

3.6. Reactive oxygen species quantification using CM-H2DCFDA Reactive oxygen species (ROS) are actively produced by algae cells during both normal metabolism and under stress conditions. Reactive oxygen species production is tightly regulated and plays multiple roles in cell signaling, stress responses, pathogen defenses, and cell autophagy. Therefore, accumulation of reactive oxygen species in a cell can simultaneously represent both actively growing cells (indicative of high rates of photosynthesis) or stressed cells. Reactive oxygen species data for algae cells in particular must be coupled to other assays to better determine the status of cellular stress and metabolism. Environmental stress, including nutrient deprivation of nitrogen, induces the accumulation of lipids in several microalgae species. Nutrient deprivation also causes the formation of reactive oxygen 9

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species. However, CM-H2DCFDA behaves similar to fluorescein diacetate, in that its fluorescence is dependent upon cell size. Supplementary Fig. 5B shows the mean CM-H2DCFDA fluorescence signal divided by the FSC for each isolate on days 10, 20 and 30 in culture. This is likely a better quantification of the total amount of reactive oxygen species per cell given the morphological differences among the isolates. A summary of the statistical analyses is provided in Supplementary Table 1. As with the fluorescein diacetate probe, the CM-H2DCFDA probe can distinguish among physiological states, not just morphological differences. To further validate its efficient assessment of reactive oxygen species production, and demonstrate its dynamic range, analysis of oxidative stress was performed on the P1 isolate during light and dark phases of the cell cycle. Samples were taken approximately 6 h apart from one another. The CM-H2DCFDA fluorescence in P1 is greater (p < 0.0001) in the dark cycle than in the light part of the cycle (Supplementary Fig. 6B). This demonstrates the sensitivity of the CMH2DCFDA probe, as a traditional bulk assay would likely not be able to detect the new population of cells with increased oxidative stress in the dark portion of the cell cycle.

permeabilization conditions without adversely affecting the chlorophyll content of cells. While these data do not suggest that this particular ethanol exposure adversely affects the F-actin polymer structure, it should be noted that previous reports demonstrate exposure to high concentrations of ethanol (200 mM) for extended periods of time (24 h) negatively impact F-actin [43]. Additional considerations when using phalloidin dye include the volume of the incubation solution and the decay in fluorescence signal over time (Supplementary Fig. 7B). The probability of interaction between the dye and cells increases with lower volumes, and we found that lower volumes resulted in greater uniformity in staining compared to larger volumes and higher cell numbers. Additionally, at least 200,000 cells were needed for optimal staining with phalloidin; however, this relatively low number of cells (~1500 cells/μl) results in slower acquisition of data for flow cytometry assessment. Further, 1 h of incubation after loading into the 96-well plate is required as the dye's fluorescence exponentially decreases within 15 min after dilution and becomes stabilized after 1 h. Supplementary Fig. 7B shows the fluorescence decay of the dye (lime green) and the percent fluorescence (green). The red arrow indicates the time at which the fluorescence signal essentially becomes stable; the optimal time for fluorescence measurement is within 70% of the original fluorescence signal. Cellular structure of all isolates over the time course was assessed using the phalloidin dye. A representative histogram demonstrating median fluorescence intensity of phalloidin for the isolates compared to an unstained control is shown in Fig. 8A. Fluorescence intensity of phalloidin for P1, P2, and P3 on days 5, 10, 20, and 30 in culture are shown in Fig. 8B. This data suggests that the isolates are significantly different in their cellular structure (p < 0.00001), and that cellular structure diminishes as the days in culture progress (p = 0.0014). F and p-values are provided in Supplementary Table 1. As with BODIPY 505/ 515, fluorescein diacetate, and CM-H2DCFDA, the phalloidin signal was normalized to FSC, shown in Supplementary Fig. 5C. This data suggests that the P3 isolate has less structural proteins than the P1 and P2 isolates at specific days in culture, when accounting for size, which is potentially due to accumulation of more lipid bodies.

3.7. Cellular structure using phalloidin Assessment of cellular structure, including microtubule formation particularly of actin polymers, can indicate the overall health of a cell. Actin polymers play multiple roles and contribute not only to cellular structure (and division) but also to cell communication and viability [40]. One common probe used to visualize F-actin molecules (the polymer of actin, versus the G-actin monomer) is phalloidin, a bicyclic toxin derived from Amanita phalloides. Fluorescently labeled conjugates of phalloidin bind stoichiometrically to one subunit of actin per phallotoxin in mammalian cells [41]. Phalloidin staining requires fixation and permeabilization of the cell and is not amenable for FACS (sorting) and subsequent re-culturing of cells. However, this dye can be used in conjunction with fluorescein diacetate and CM-H2DCFDA to provide a global picture of algal health. We selected phalloidin conjugated to Alexa-Fluor 488 for staining F-actin in P. soloecismus isolates. Previous reports suggest that permeabilization with ethanol is effective in other species for staining with phalloidin [42]. Thus, we assessed various concentrations and incubation periods with ethanol for optimal permeabilization of the cell without cellular leakage. Supplementary Fig. 6A shows a representative histogram of autofluorescence of cells after incubation with various concentrations of ethanol. The data suggest that 25% ethanol treatment for 1 h produced the best

4. Conclusion There is currently a concerted effort towards the development of highly productive microalgae strains to provide an alternative modality to generate biofuel and bioproducts. Strain improvement efforts target enhancement of growth, increased outdoor robustness, tolerance to

Fig. 8. Assessment of cellular structure of P. soloecismus WT and its isolates using a phalloidin conjugated dye. A) Representative histogram of phalloidin fluorescence for the unstained control and the P1, P2, and P3 isolates. B) Phalloidin fluorescence for all three isolates over the growth cycle during nitrogen depletion. Phalloidin fluorescence intensity was each measured in triplicate for each isolate at every time point. Data are shown as mean ± SEM (standard error of the mean; error bars are difficult to see due to scale); ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05. 10

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environmental variability, and appropriate usage of available and abundant nutrients. A significant challenge in the development of these advanced strains is understanding how bioengineering impacts microalgae physiology. Facile, robust, and efficient methods to rapidly assess functional and phenotypic traits extending beyond cell counts and optical density are needed. To address this challenge, we developed flow cytometry methods specifically for P. soloecismus, allowing for high throughput, single-cell analysis of multiple cellular characteristics. The suite of molecular probes presented here can be used to ascertain algal health, growth cycle responses, and altered metabolism and physiology. Using three different isolates of P. soloecismus, we provide data demonstrating how researchers can use these protocols to assess phenotypic differences in algae strains, how to determine changes in cellular characteristics over growth periods and during nitrogen starvation, and how these probes dynamically respond to physiological differences in microalgae species. These protocols focus on dyes for assessment of lipid accumulation, DNA content, cellular metabolism, viability, pH, reactive oxygen species, and microtubule structure. This suite of molecular flow cytometry probes and procedures can be utilized for rapid screening to elucidate optimal phenotypes in microalgae under various environmental conditions and integrated into new technical strategies for improving algae strain productivity. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.algal.2019.101614.

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[9] [10] [11] [12] [13]

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Funding

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This work was funded by the Office of Energy Efficiency and Renewable Energy under contract from the Bioenergy Technologies Office (agreement number NL0026328).

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Author contributions

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CRST, CKS, SNT, BLM conceived the research and designed experiments; TD contributed algae isolates; CRT, CKS, RSE performed the experiments; CRST analyzed data, including statistical analysis, and wrote the manuscript; BLM, SNT, TD, CKS critically revised and edited the manuscript; funding was obtained by SNT and BLM; all authors read and approved the final manuscript. CR Steadman Tyler ([email protected]) and Scott N. Twary ([email protected]) take responsibility for the integrity of the work as a whole, from inception to finished article.

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Declaration of competing interest

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No conflicts, informed consent, human or animal rights applicable.

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