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Sep 2020

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Flow Cytometry-based Measurement of Reactive Oxygen Species in Cyanobacteria
基于流式细胞仪的蓝藻活性氧测量   

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Abstract

Cyanobacteria are Gram-negative oxygen-producing photosynthetic bacteria that are useful in the pharmaceutical and biofuel industries. Monitoring of oxidative stress under fluctuating environmental conditions is important for determining the fitness, survival, and growth of cyanobacteria in the laboratory as well as in large scale cultivation systems. Here, we provide a protocol developed using unicellular Synechococcus elongatus PCC 7942 and filamentous Fremyella diplosiphon BK14 cyanobacteria for high-throughput oxidative stress measurement by 2′,7′-dichlorodihydrofluorescein-diacetate (DCFH-DA) and flow cytometry (FCM). We also provide details for the optimization of cell number, dye concentration, and FCM parameters for each organism before it can be utilized to quantify reactive oxygen species (ROS). FCM-based method can be used to measure ROS in a large population of cyanobacterial cells in a high-throughput manner.


Graphical abstract:



Keywords: Flow Cytometry (流式细胞术), Fluorescence microscopy (荧光显微镜), Cyanobacteria (蓝藻), ROS (ROS), DCFH-DA (DCFH-DA), Oxidative stress (氧化应激)

Background

Cyanobacteria are a monophyletic group of Gram-negative bacteria that are found in a variety of habitats and produce oxygen similar to higher plants during photosynthesis (Dvořák et al., 2017). Cyanobacteria have evolved different mechanisms to adapt to a wide range of environmental conditions. These ecologically important organisms are well-known for their significant contribution to global carbon dioxide and nitrogen fixation, and as a result, they contribute significantly to the productivity of ecosystems (Kanno et al., 2017). Cyanobacteria have shown their potential in bioenergy and valuable chemical production due to their minimal growth requirements, high photosynthetic efficiency, amenability to genetic modification, and installation of novel metabolic pathways in their primary metabolic chassis (Rajneesh et al., 2017a). However, oxidation and reduction processes related to photosynthesis and respiration are affected by changing environmental conditions such as light quality and quantity, pH, salinity, temperature, and nutrient limitation. Altered oxidation and reduction processes in cyanobacterial thylakoid membranes result in generation of reactive oxygen species (ROS), which consequently cause oxidative stress (Niyogi, 1999). Increased levels of ROS in cyanobacteria are known to damage lipids, DNA, RNA, pigments, and proteins. ROS also results in photoinhibition due to damage to the oxygen-evolving complex and the D2 protein of photosystem II (Niyogi, 1999; Latifi et al., 2009). As a result, the development, growth, and survival of cyanobacterial cells are impaired by high levels of ROS that are generated under fluctuating environmental conditions (Niyogi, 1999; Latifi et al., 2009). Therefore, rapid and accurate methods to measure ROS are required for monitoring the health of cyanobacterial cells in cultivation systems that are used in commercial setups as well as in basic biological studies.


Earlier, we developed a method to measure ROS levels in cyanobacteria using 2′,7′-dichlorodihydrofluorescein-diacetate (DCFH-DA), a live cell-permeable fluorescent probe that can be visualized by fluorescence microscopy (Rastogi et al., 2010; Rajneesh et al., 2017b). DCFH-DA is a well-known fluorescent probe for detecting ROS in live cells. It hydrolyzes inside the cell to DCFH by the activity of esterases. DCFH cannot cross the cell membrane, and it is mostly non-fluorescent, but it emits green fluorescence when oxidized to dichlorofluorescein (DCF) by intracellular ROS (Kalyanaraman et al., 2012). The intensity of green fluorescence can be measured at 530 nm after excitation at 485 nm. Previous methods have been widely used to measure ROS levels in various organisms in addition to cyanobacteria (Rastogi et al., 2010; Rajneesh et al., 2017b; Li et al., 2017; Basso et al., 2018). However, despite its wide application, fluorescence microscopy-based methods are limited to small sample sizes (the number of cells analyzed is an individual choice, but analysis of at least 50 cells per replicate is recommended), and therefore, the entire population is not well represented (Mondal et al., 2020). Also, imaging a large number of cells in the darkroom is not easy as it is a time-consuming process, and longer exposure of samples to excitation light could result in a high background of green fluorescence due to photooxidation of the dye. Regular imaging for longer periods can also cause dry, itchy, and weary eyes, as well as headaches. Cell morphology is another disadvantage of fluorescence microscopy-based ROS monitoring, as visualizing and estimating ROS in small spherical shape cells is not possible (Mondal et al., 2020). However, FCM-based ROS-monitoring methods overcome the abovementioned limitations of fluorescence microscopy-based methods and provide a high-throughput platform to monitor the ROS in a large number of cells of various morphology. Furthermore, it allows simultaneously recording data on cell size and shape, granularity, chlorophyll, and phycobiliproteins while monitoring the ROS levels. The forward scatter (FSC) parameter of FCM provides information about cell size and shape, while the internal complexity, i.e., granularity, of a cell can be determined by measuring side scatter. Granules and the nucleus are two cellular components that influence side scatter; however, the nucleus is absent in cyanobacteria. Similar to fluorescence microscopy-based ROS-detection methods described earlier (Rastogi et al., 2010; Rajneesh et al., 2017b), this protocol can be optimized for different organisms for successful monitoring of ROS.

Materials and Reagents

  1. 1.5 mL amber microcentrifuge tubes (Abdos, catalog number: P10204A)

  2. 3 mL round bottom polystyrene tubes (Becton Dickinson, catalog number: 156758)

  3. 20 mL 1 M HEPES pH 8.0 (Himedia, catalog number: RM380-500G)

  4. Glass slides (Borosil, catalog number: BT409100P02)

  5. Cover slips (Borosil, catalog number: 9115S01)

  6. 1 mL pipette tips (Abdos, catalog number: P10109)

  7. 200 µL pipette tips (Abdos, catalog number: P10140)

  8. 10 µL pipette tips (Abdos, catalog number: P10116)

  9. 1 cm quartz cuvette (Shimadzu, catalog number:226-85010-92)

  10. 0.2 µm size Millipore membrane filter (Merck, catalog number: GSWP04700)

  11. BD FACS Clean Solution (0.1% Sodium hypochlorite) (Becton Dickinson, catalog number: 340345)

  12. Hydrogen Peroxide (Merck, catalog number: 1.93408.0521)

  13. Milli-Q water

  14. Exponentially growing cultures of Synechococcus elongatus PCC 7942, Synechocystis sp. PCC 6803 and Fremyella diplosiphon BK14 grown in BG11 medium supplemented with 20 mM HEPES (Allen, 1968).

    Note: Synechococcus elongatus PCC 7942, Synechocystis sp. PCC 6803, and Fremyella diplosiphon BK14 (Kehoe and Grossman, 1996) were grown in BG11 liquid medium supplemented with 20 mM HEPES. Cells were inoculated from a solid BG11+20 mM HEPES agar plate. Synechococcus elongatus PCC 7942 and Synechocystis sp. PCC 6803 were grown under PAR (photosynthetically active radiation) (~80 µmol m-2 s-1), while Fremyella diplosiphon BK14 was grown in red light (Red LED Fluorescent light, Havells, India) (~20 µmol m-2 s-1) with ~150 rpm shaking at 25°C. The growth curves of all organisms were monitored, and cultures were maintained in the exponential phase by regular sub-culturing.

  15. DCFH-DA (Sigma-Aldrich, catalog number: D6883)

  16. Ethanol (Merck, catalog number: 1.00983.0511)

  17. Disodium hydrogen phosphate (Na2HPO4) (Merck, catalog number: 1.93622.0521)

  18. Sodium dihydrogen phosphate (NaH2PO4) (Merck, catalog number: 1.93624.0521)

  19. Sodium chloride (NaCl) (SRL, catalog number: 41721)

  20. 2 mM (w/v) DCFH-DA Stock solution (1 mL) (see Recipes)

  21. 0.1 M PBS pH 7.4 (100 mL) (see Recipes)

Equipment

  1. BD FACSCalibur flow cytometer (Becton Dickinson, catalog number: 342975)

  2. UV-VIS Spectrophotometer 1800 (Shimazdu, catalog number: 80626)

  3. Nikon 90i eclipse fluorescence microscope (Nikon, Japan)

  4. Cooling Centrifuge (Remi, India/NEYA16R)

Software

  1. BD CellQuest Pro (Becton Dickinson, USA)

  2. NIS elements AR software 4.0 (Nikon, Japan)

Procedure

  1. Optimization of FCM parameters

    1. Take 50 mL exponentially growing cultures of unicellular (S. elongatus PCC 7942 and Synechocystis sp. PCC 6803) and filamentous (Fremyella diplosiphon BK14) cyanobacteria grown under the abovementioned conditions (item 14 of Materials and Reagents).

    2. Remove growth medium by centrifugation at 6,000 × g and 25°C for 10 min and dilute the samples with 0.1 M PBS buffer to different O.D.750, i.e., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, and 0.8. Make 1 mL final volume of each cell concentration in a 1.5 mL microcentrifuge tube.

    3. Clean nozzle of BD FACSCalibur with 0.1% sodium hypochlorite solution and Milli-Q water.

      Note: Turn on the BD FACSCalibur flow cytometer 10–15 min before conducting the experiment. Calibration of BD FACSCalibur with QC beads at regular intervals is recommended.

    4. Draw two dot plots in BD CellQuest Pro software, i.e., Forward Scatter (FSC) vs. Side Scatter (SSC) and FSC vs. Fluorescence channel 3 (FL3). Similarly, draw two histogram plots of Fluorescence channel 1 (FL1) and FL3. Set log scale for all parameters. FL1 and FL3 are two Fluorescence channels that detect DCF fluorescence (green fluorescence, emission range 515–545 nm) and autofluorescence of Chlorophyll (Chl) ɑ (red fluorescence, emission range >670 nm), respectively. The FSC vs. SSC plot provides information about cell size, shape, and granularity; the FSC vs. FL-3 plot is used to select the cyanobacterial population-based on Chl ɑ autofluorescence and cell size. The FL-1 and FL-3 histogram plot provides the fluorescence intensity of DCF and Chl ɑ, respectively.

    5. Transfer samples from step 2 to a 3 mL round bottom polystyrene tube and acquire all samples with a low flow rate (12 μL/min), adjusting the PMT voltages of FSC, SSC, FL1, and FL3 for different organisms, as shown in Figure 1A. The adjusted optimal PMT voltage is used for analyzing all the samples of the same organism, which provides fluorescence intensity from the cell in the absence of DCFH-DA. This background fluorescence of cells is excluded while measuring the mean fluorescence intensity of DCF in DCFH-DA treated cells to estimate ROS levels. Set FSC as the primary parameter and FL3 as the secondary parameter.

    6. Acquire 50,000–100,000 events. Keep sample acquisition rate below 1,000 events/second to avoid exposure of more than one cell to laser beam at the same time.

    7. Note the minimum O.D.750 (from step 2) value that gives sample acquisition rate between 500–1,000 events/second to determine the appropriate cell density of each cyanobacterium required for getting proper signals from FCM.



    Figure 1. Optimization of different flow cytometry (FCM) parameters for measurement of reactive oxygen species (ROS) levels using 2′,7′-dichlorodihydrofluorescein-diacetate (DCFH-DA).

    FCM histogram diagram for optimizing PMT voltage of different fluorescent channels of a flow cytometer (A). Graph of optimization of DCFH-DA concentration for test organism (B). Dot plot diagram of gating the population of interest based on FL3 (Chlorophyll ɑ) fluorescence and FSC-H (relative size) (C). Dot plot diagram of FSC-H vs. SSC-H showing relative size and cellular complexity, respectively, of the test organism (D).


  2. Optimization of DCFH-DA dye concentration

    1. Take 10 mL sample of optimized O.D.750 (refer to steps 2–7 of section A) for each organism in a 15 mL Falcon tube. Add 100 mM H2O2 to each sample and incubate for 1 h under growth conditions described in item 14 of the Materials and Reagents section.

    2. After incubation, pellet cells by centrifugation at 6000 × g and 25°C for 10 min, and wash the cells twice with 10 mL of 0.1 M PBS (pH 7.4).

    3. After washing, suspend the cells in 10 mL of 0.1 M PBS and divide into 1 mL of aliquots.

    4. Add different concentrations (0, 10, 15, 20, 25, 30, 35, and 40 µM) of DCFH-DA to 1 mL of cell aliquots using DCFH-DA stock solutions (item 20 of Materials and Reagents section).

    5. Incubate cells for 1 h in the dark with ~150 rpm rocking at 25°C.

    6. Analyze cells using FCM immediately after 1 h of incubation.

    7. Wash FCM and set BD CellQuest Pro software with optimized PMT voltage (refer to section A).

    8. Acquire samples with low flow rate (12 μL/min).

    9. Determine the minimum concentration of dye required for in vivo detection of ROS for each organism by analyzing the titration curve, as shown in Figure 1B.


  3. Detection of in vivo ROS using FCM

    1. After determining the optimum cell and dye concentration for each organism (refer to sections A and B), take cyanobacterial cells from different experimental conditions. Here, we used different cyanobacteria that were grown in conditions mentioned in item 14 of the Materials and Reagents section.

    2. Pellet cells by centrifugation at 6,000 × g and 25°C for 10 min, and wash the cells twice with 1 mL of 0.1 M PBS (pH 7.4). After washing, resuspend cells in 1 mL of 0.1 M PBS buffer.

    3. Incubate cells with the determined concentration of dye for 1 h in the dark with rocking.

    4. After incubation, separate samples in two microcentrifuge tubes and immediately acquire one of them with the help of a BD FACSCalibur flow cytometer using optimized settings. Use another aliquot of cells for ROS detection by fluorescence microscopy, as described by Rastogi et al. (2010) (Figure 2).



      Figure 2. Measurement of reactive oxygen species (ROS) in Synechococcus elongatus PCC 7942, Synechocystis sp. PCC 6803, and Fremyella diplosiphon BK14 using 2′,7′-dichlorodihydrofluorescein-diacetate (DCFH-DA) and fluorescence microscopy or Flow cytometry (FCM).

      Dichlorofluorescein (DCF) fluorescence showing ROS levels (Green) and autofluorescence of photosynthetic pigments (Red) in F. diplosiphon BK14, S. elongatus PCC 7942, and Synechocystis sp. PCC 6803 (A). Fluorescence from DCFH-DA only sample without cells represents the negative control. Images were acquired using a ×40 objective. Scale bars, 5 μm. FCM histograms showing fluorescence of dichlorofluorescein (DCF), i.e., ROS level, in S. elongatus PCC 7942, F. diplosiphon BK14, and Synechocystis sp. PCC 6803 (B). Histograms showing background fluorescence of FL1 channel from S. elongatus PCC 7942, F. diplosiphon BK14, and Synechocystis sp. PCC 6803 without DCFH-DA (C).


    5. Acquire at least 50000 events at a low flow rate (12 μL/min).

    6. Save the data in FCM format.

Data analysis

  1. The flowchart (Figure 3) shows steps involved in the detection of ROS (steps 1–3; refer to sections A, B, and C), and data analysis.

  2. Using BD CellQuest Pro software, gate cyanobacterial population with the help of FSC vs. FL3 (x-axis FSC and y-axis FL3) (Figure 1C).

  3. Generate histogram diagram of FL1 as shown in Figure 2.

  4. Record the mean fluorescence intensity (MFI) of the FL1 histogram from the gated population of cyanobacterial cells, which depicts the ROS level.

  5. MFI of FL1 channel histogram can also be represented as a bar diagram to depict the ROS level.

  6. The values of FL1 from different organisms can be analyzed using one-way ANOVA with Tukey post hoc function or other suitable statistical analysis.



    Figure 3. Steps involved in the detection of reactive oxygen species (ROS) and data analysis.

Notes

  1. To optimize the concentration of DCFH-DA, use a concentration of H2O2 that gives maximum ROS in the organism while killing less than 10% of the cells (Mondal et al., 2020). A live-dead assay can be performed by using different concentrations of H2O2 and the live cell-permeable nucleic acid binding fluorescent dye SYBR Green I. Cells were treated with different concentrations of H2O2, and live cells were detected using Sybr Green I and FCM to determine the concentration of H2O2 that causes less than 10% killing (Mondal et al., 2020).

  2. Flow cytometers have limitations regarding cell/filament size. The nozzle can analyze approximately 1 µm to 50 µm cell/filament length. Though the size range may vary, it is recommended to be careful when using filamentous cyanobacteria or organisms which make clumps or aggregates. Long filaments may clog the nozzle. It is advised to prepare short filament by using a sonicator before acquisition of sample through FCM, if required. However, impact of sonication on ROS levels and cell survival should be analyzed in advance. Samples can be sonicated in an ultrasonic bath sonicator for different time intervals, and fragmentation can be monitored by light microscopy. Filaments of Fremyella diplosiphon BK14 are shorter (<50 µm), and therefore fragmentation was not required for this cyanobacterium.

  3. DCFH-DA is a light sensitive fluorescence probe. It is advised to perform the entire experiment in minimal light and avoid direct exposure of samples and dye to light.

    Alternatively, the cell concentration can be determined by direct cell counting or turbidity measurement of the cell sample as scattering of light. A minimum of 1×105 cells are usually required for the acquisition in FCM.

Recipes

  1. 2 mM (w/v) DCFH-DA Stock solution (1 mL)

    1. 1 mL of 100% ethanol (Molecular Grade).

    2. Dissolve 0.974 mg of DCFH-DA in 1 mL of 100% ethanol.

    3. Mix by vortexing and store in the dark at -20°C (Can be stored for up to 3 months).

  2. 0.1 M PBS pH 7.4 (100 mL)

    1. Mix 40 mL of 0.2 M Disodium hydrogen phosphate (Na2HPO4) stock with 10 mL of sodium dihydrogen phosphate (NaH2PO4) stock.

    2. Add 0.9 g NaCl and stir until dissolved.

    3. Bring the volume to 100 mL with distilled H2O and adjust the pH to 7.4.

    4. Filter through 0.2 µm size Millipore membrane filter before use.

    5. Store at 4°C.

Acknowledgments

This work was supported by the funding from Institute of Eminence incentive grant, Banaras Hindu University (R/Dev/D/IOE/Incentive/2021-2022/32399) and SERB, New Delhi, India, in the form of Early Career Research Award (ECR/2016/000578) to Shailendra P. Singh. Soumila Mondal is thankful to UGC and BHU for providing UGC Research Fellowship. The author acknowledges DBT Interdisciplinary School of Life Sciences (ISLS) BHU for flow cytometry and fluorescence microscopy facility. This protocol was adapted from the procedure published by Mondal et al. (2020). Careful reading and suggestions from Pankaj K. Maurya and Anjali Gupta is also acknowledged.

Competing interests

The authors declare no competing financial and non-financial interests.

References

  1. Allen, M. M. (1968). Simple conditions for growth of unicellular blue-green algae on plates (1, 2). J Phycol 4(1): 1-4.
  2. Basso, V., Garcia, A., Tran, D. Q., Schaal, J. B., Tran, P., Ngole, D., Aqeel, Y., Tongaonkar, P., Ouellette, A. J. and Selsted, M. E. (2018). Fungicidal potency and mechanisms of theta-defensins against multidrug-resistant Candida species. Antimicrob Agents Chemother 62(6): e00111-18.
  3. Dvořák, P., Casamatta, D. A., Hašler, P., Jahodářová, E., Norwich, A. R. and Poulíčková, A. (2017). Diversity of the cyanobacteria. In: Modern topics in the phototrophic prokaryotes (pp. 3-46). Hallenbeck, P. C. (Ed.). Springer.
  4. Kalyanaraman, B., Darley-Usmar, V., Davies, K. J., Dennery, P. A., Forman, H. J., Grisham, M. B. and Ischiropoulos, H. (2012). Measuring reactive oxygen and nitrogen species with fluorescent probes: Challenges and limitations. Free Radic Biol Med 52(1): 1-6.
  5. Kanno, M., Carroll, A. L. and Atsumi, S. (2017). Global metabolic rewiring for improved CO2 fixation and chemical production in cyanobacteria. Nat Commun 8: 14724.
  6. Kehoe, D. M. and Grossman, A. R. (1996). Similarity of a chromatic adaptation sensor to phytochrome and ethylene receptors. Science 273(5280): 1409-1412.
  7. Latifi, A., Ruiz, M. and Zhang, C. C. (2009). Oxidative stress in cyanobacteria. FEMS Microbiol Rev 33(2): 258-278.
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  12. Rajneesh, Singh, S. P., Pathak, J. and Sinha, R. P. (2017a). Cyanobacterial factories for the production of green energy and value-added products: An integrated approach for economic viability. Renew Sust Energ Rev 69: 578-595.
  13. Rastogi, R. P., Singh, S. P., Häder, D. -P. and Sinha, R. P. (2010). Detection of reactive oxygen species (ROS) by the oxidant-sensing probe 2',7'-dichlorodihydrofluorescein diacetate in the cyanobacterium Anabaena variabilis PCC 7937. Biochem Biophys Res Commun 397(3): 603-607.

简介

蓝细菌是革兰氏阴性产氧光合细菌,可用于制药和生物燃料行业。 在波动的环境条件下监测氧化应激对于确定实验室以及大规模培养系统中蓝藻的适应性、存活和生长非常重要。 在这里,我们提供了使用单细胞细长聚球藻 PCC 7942 和丝状 Fremyella diplosiphon BK14 蓝细菌开发的协议,用于通过 2',7'-二氯二氢荧光素二乙酸酯 (DCFH-DA) 和流式细胞仪 (FCM) 进行高通量氧化应激测量。 我们还提供了优化每个生物体的细胞数量、染料浓度和 FCM 参数的详细信息,然后才能将其用于量化活性氧 (ROS)。 基于 FCM 的方法可用于以高通量方式测量大量蓝藻细胞中的 ROS。


背景

蓝细菌是革兰氏阴性菌的单系群,存在于各种栖息地,在光合作用过程中产生类似于高等植物的氧气(德沃夏克 等。 , 2017) 。蓝藻已经进化出不同的机制来适应广泛的环境条件。这些具有重要生态意义的生物因其对全球二氧化碳和固氮的重大贡献而闻名,因此,它们对生态系统的生产力做出了重大贡献( Kanno et al ., 2017)。蓝藻在生物能源和有价值的化学品生产方面显示出潜力,因为它们的生长要求最低、光合作用效率高、易于进行基因改造以及在其主要代谢底盘中安装了新的代谢途径(Rajneesh等, 2017a)。然而,与光合作用和呼吸作用相关的氧化和还原过程会受到环境条件变化的影响,例如光质量和光量、pH、盐度、温度和营养限制。蓝藻类囊体膜中改变的氧化和还原过程导致产生活性氧(ROS),从而导致氧化应激(Niyogi , 1999)。已知蓝藻中 ROS 水平升高会损害脂质、DNA、RNA、色素和蛋白质。 ROS 还由于对放氧复合物和光系统 II 的 D2 蛋白的损害而导致光抑制(Niyogi,1999 ; Latifi等人, 2009)。结果,在波动的环境条件下产生的高水平 ROS 损害了蓝藻细胞的发育、生长和存活(Niyogi,1999; 拉蒂菲 等。 , 2009)。因此,需要快速准确地测量 ROS 的方法来监测用于商业设置和基础生物学研究的培养系统中蓝藻细胞的健康状况。
早些时候,我们开发了一种使用 2',7'-二氯二氢荧光素二乙酸酯 (DCFH-DA) 测量蓝藻中 ROS 水平的方法,这是一种可通过荧光显微镜观察到的活细胞可渗透荧光探针(Rastogi等人, 2010 年; Rajneesh等人, 2017b )。 DCFH-DA 是一种众所周知的用于检测活细胞中 ROS 的荧光探针。它通过酯酶的活性在细胞内水解成 DCFH 。 DCFH不能穿过细胞膜,多不发荧光,但被细胞内活性氧氧化成二氯荧光素(DCF)后发出绿色荧光( Kalyanaraman ) 等人, 2012)。在 485 nm 激发后,可以在 530 nm 测量绿色荧光的强度。除蓝藻外,以前的方法已被广泛用于测量各种生物体中的 ROS 水平(Rastogi等人, 2010; Rajneesh等人, 2017b ;Li等人, 2017; 巴索等人。 , 2018)。然而,尽管应用广泛,但基于荧光显微镜的方法仅限于小样本量(分析的细胞数量是个人选择,但建议每次重复分析至少 50 个细胞),因此,整个群体不能很好的代表(Mondal et al ., 2020)。此外,在暗室中对大量细胞进行成像并不容易,因为这是一个耗时的过程,并且由于染料的光氧化,样品长时间暴露在激发光下可能会导致绿色荧光的高背景。长时间定期成像也会导致眼睛干燥、发痒和疲倦,以及头痛。细胞形态是基于荧光显微镜的 ROS 监测的另一个缺点,因为无法可视化和估计小球形细胞中的 ROS(Mondal等人, 2020)。然而,基于 FCM 的 ROS 监测方法克服了上述基于荧光显微镜的方法的局限性,并提供了一个高通量平台来监测大量各种形态的细胞中的 ROS。此外,它允许同时记录细胞大小和形状、粒度、叶绿素和藻胆蛋白的数据,同时监测 ROS 水平。 FCM 的前向散射 (FSC) 参数提供有关细胞大小和形状的信息,而细胞的内部复杂性,即粒度,可以通过测量侧向散射来确定。颗粒和细胞核是影响侧向散射的两种细胞成分;然而,蓝细菌中没有细胞核。类似于前面描述的基于荧光显微镜的 ROS 检测方法(Rastogi等人, 2010 ; Rajneesh等人, 2017b ) ,该协议可以针对不同的生物体进行优化,以成功监测 ROS。

关键字:流式细胞术, 荧光显微镜, 蓝藻, ROS, DCFH-DA, 氧化应激

材料和试剂
1.1.5 mL琥珀色微量离心管( Abdos ,目录号:P10204A)
2.3 mL圆底聚苯乙烯管(Becton Dickinson,目录号:156758)
3.20 mL 1 M HEPES pH 8.0( Himedia ,目录号:RM380-500G) 
4.载玻片( Borosil ,目录号:BT409100P02)
5.盖玻片( Borosil ,目录号:9115S01)
6.1 mL移液器吸头( Abdos ,目录号:P10109)
7.200 µL 移液器吸头( Abdos ,目录号:P10140)
8.10 µL 移液器吸头( Abdos ,目录号:P10116)
9.1 cm石英比色皿(Shimadzu,目录号:226-85010-92)
10.0.2 µm 尺寸的 Millipore 膜过滤器(Merck,目录号:GSWP04700)
11.BD FACS清洁溶液(0.1%次氯酸钠)( Becton Dickinson ,目录号: 340345)
12.过氧化氢(Merck,目录号:1.93408.0521)
13.Milli-Q 水
14.Synechococcus elongatus PCC 7942、 Synechocystis sp.呈指数增长的培养物。 PCC 6803 和Fremyella 在补充有 20 mM HEPES (Allen, 1968)的 BG11 培养基中生长的双环管 BK14 。
注: Synechococcus elongatus PCC 7942, Synechocystis sp. PCC 6803和Fremyella dilosiphon BK14 (Kehoe and Grossman, 1996) 在补充有 20 mM HEPES 的 BG11 液体培养基中生长。从固体 BG11+20 mM HEPES 琼脂板上接种细胞。 Synechococcus elongatus PCC 7942和Synechocystis sp。 PCC 6803 在 PAR(光合有效辐射)(~80 µmol m -2 s -1 )下生长,而Fremyella dilosiphon BK14 在红光下生长(红色 LED 荧光灯,Havells,印度)( ~20 µmol m -2 s -1 ) ,在 25°C 下以 ~150 rpm 摇动。监测所有生物的生长曲线,并通过定期传代培养将培养物维持在指数期。
15.DCFH-DA(Sigma-Aldrich,目录号:D6883)
16.乙醇(Merck,目录号:1.00983.0511)
17.磷酸氢二钠(Na 2 HPO 4 )(Merck,目录号:1.93622.0521)
18.磷酸二氢钠(NaH 2 PO 4 )(Merck,目录号:1.93624.0521)
19.氯化钠(NaCl)(SRL,目录号: 41721)
20.2 mM (w/v) DCFH-DA 储备溶液 (1 mL) (参见配方)
21.0.1 M PBS pH 7.4 (100 mL) (见食谱)




设备


1.BD FACSCalibur流式细胞仪( Becton Dickinson,目录号:342975 )
2.UV-VIS分光光度计1800( Shimazdu ,目录号:80626 )
3.尼康 90i 日食荧光显微镜(日本尼康)
4.冷却离心机(印度雷米/NEYA16R)




软件


1.BD CellQuest Pro(美国 Becton Dickinson )
2.NIS elements AR软件4.0 (日本尼康)




程序


A.FCM参数优化


1.取 50 毫升 单细胞( S. elongatus PCC 7942 和Synechocystis sp. PCC 6803)和丝状( Fremyella dilosiphon BK14)在上述条件下生长的蓝藻(材料和试剂第 14 项)。
2.× g和 25°C下离心 10 分钟去除生长培养基,并用 0.1 M PBS 缓冲液将样品稀释至不同的 OD 750 ,即0.1、0.2、0.3、0.4、0.5、0.6、0.7 和 0.8。在 1.5 mL微量离心管中使每个细胞浓度的最终体积为 1 mL 。
3.用 0.1% 次氯酸钠溶液和 Milli-Q 水清洁 BD FACSCalibur的喷嘴。
在进行实验前 10-15 分钟打开BD FACSCalibur流式细胞仪。建议定期使用 QC 微珠校准 BD FACSCalibur 。
4.CellQuest Pro 软件中绘制两个点图,即前向散射(FSC)对侧向散射(SSC)和FSC对荧光通道3(FL3)。同样,绘制荧光通道 1 (FL1) 和 FL3 的两个直方图。为所有参数设置对数比例。 FL1 和 FL3 是两个荧光通道,可检测 DCF 荧光(绿色荧光,发射范围 515 – 545 nm)和叶绿素 ( Chl ) ɑ的自发荧光(红色荧光,发射范围 >670 nm), 分别。 FSC与SSC 图提供有关细胞大小、形状和粒度的信息; FSC与FL-3 图用于根据Chl ɑ自发荧光和细胞大小选择蓝藻种群。 FL-1 和 FL-3 直方图提供 DCF 和Chl的荧光强度 ɑ ,分别。
5.将步骤 2 中的样品转移到3 mL 圆底聚苯乙烯管中,以低流速(12 μL /min)采集所有样品,针对不同生物体调整 FSC、SSC、FL1 和 FL3 的 PMT 电压,如图1A。调整后的最佳 PMT 电压用于分析同一生物体的所有样品,在没有 DCFH-DA 的情况下提供来自细胞的荧光强度。在测量 DCFH-DA 处理的细胞中 DCF 的平均荧光强度以估计 ROS 水平时,排除了细胞的这种背景荧光。设置 FSC 为主要参数,FL3 为次要参数。
6.获取 50,000 – 100,000 个事件。将样本采集速率保持在 1,000 个事件/秒以下,以避免多个细胞同时暴露于激光束。
7.请注意最小 OD 750 (来自步骤 2)值,该值提供 500 – 1,000 个事件/秒之间的样本采集速率,以确定从 FCM 获得正确信号所需的每个蓝藻的适当细胞密度。


 


图 1. 使用 2',7'-二氯二氢荧光素-二乙酸酯 (DCFH-DA) 优化不同流式细胞术 (FCM) 参数以测量活性氧 (ROS) 水平。
用于优化流式细胞仪不同荧光通道的 PMT 电压的 FCM 直方图 (A)。测试有机体 (B) 的 DCFH-DA 浓度优化图。基于 FL3(叶绿素ɑ )荧光和 FSC-H(相对大小)(C)的门控群体的点图。 FSC-H与SSC-H的点图分别显示了测试生物体 (D) 的相对大小和细胞复杂性。


B.DCFH-DA染料浓度的优化


1.采集 10 mL 优化 OD 750样品(参见 A 部分的步骤2-7 ) 。将 100 mM H 2 O 2添加到每个样品中,并在材料和试剂部分第 14 项所述的生长条件下孵育 1 小时。
2.× g和 25°C下离心10分钟沉淀细胞,并用 10 mL 的0.1 M PBS (pH 7.4)洗涤细胞两次。
3.洗涤后,将细胞悬浮在 10 mL 的 0.1 M PBS 中,并分成 1 mL 的等分试样。
4.使用 DCFH-DA 库存溶液(材料和试剂部分的第 20 项)将不同浓度(0、10、15、20、25、30、35 和 40 μM)的 DCFH-DA 添加到 1 mL 的细胞等分试样中。
5.将细胞在黑暗中孵育 1 小时,在 25°C 下摇动约 150 转。
6.孵育 1 小时后立即使用 FCM 分析细胞。
7.清洗 FCM 并使用优化的 PMT 电压设置 BD CellQuest Pro 软件(请参阅 A 部分)。
8.以低流速 (12 μL /min) 采集样品。
9.体内检测 ROS所需的染料的最低浓度,如图 1B 所示。


C.使用 FCM检测体内ROS


1.在确定每种生物体的最佳细胞和染料浓度后(参见 A 和 B 部分),从不同的实验条件中获取蓝藻细胞。在这里,我们使用了在材料和试剂部分第 14 项中提到的条件下生长的不同蓝藻。
2.通过在 6,000 × g和 25°C 下离心 10分钟来沉淀细胞,并用 1 mL 的0.1 M PBS (pH 7.4)洗涤细胞两次。洗涤后,将细胞重新悬浮在 1 mL 的 0.1 M PBS 缓冲液中。
3.用确定浓度的染料在黑暗中摇动孵育细胞 1 小时。
4.FACSCalibur流式细胞仪的帮助下使用优化设置立即获取其中一个。如 Rastogi等人所述,使用另一等分的细胞通过荧光显微镜检测 ROS。 (2010 年)(图 2)。




 


图 2。 Synechococcus elongatus PCC 7942, Synechocystis sp.中活性氧 (ROS) 的测量。 PCC 6803 和Fremyella 双虹吸管 BK14 使用 2',7'-二氯二氢荧光素-二乙酸酯 (DCFH-DA) 和荧光显微镜或流式细胞术 (FCM)。
二氯荧光素 (DCF) 荧光显示F. dilosiphon中光合色素 (红色) 的 ROS 水平 (绿色) 和自发荧光 BK14、 S. elongatus PCC 7942 和Synechocystis sp。 PCC 6803 (A)。来自 DCFH-DA 的仅不含细胞的样品的荧光代表阴性对照。使用×40 物镜获取图像。比例尺,5 μm 。 FCM 直方图显示了S. elongatus PCC 7942、 F. dilosiphon中二氯荧光素(DCF) 的荧光,即ROS 水平 BK14 和集胞藻属。 PCC 6803 (B)。显示来自S. elongatus PCC 7942、 F. diplosiphon的 FL1 通道的背景荧光的直方图 BK14 和集胞藻属。不带 DCFH-DA (C) 的 PCC 6803。 


5.μL /min)采集至少 50000 个事件。
6.以 FCM 格式保存数据。




数据分析


1.流程图(图 3)显示了 ROS 检测所涉及的步骤(步骤 1-3;请参阅 A、B 和 C 部分)和数据分析。
2.使用 BD CellQuest Pro 软件,在 FSC与FL3(x 轴 FSC 和 y 轴 FL3)的帮助下门控蓝藻种群(图 1C)。
3.生成 FL1 的直方图,如图 2 所示。
4.记录来自门控蓝藻细胞群的 FL1 直方图的平均荧光强度 (MFI),它描述了 ROS 水平。
5.FL1 通道直方图的 MFI 也可以表示为条形图来描述 ROS 水平。
6.来自不同生物体的 FL1 值可以使用 Tukey 事后函数的单向方差分析或其他合适的统计分析来分析。


 


图 3. 检测活性氧 (ROS) 和数据分析所涉及的步骤。




笔记


1.要优化 DCFH-DA 的浓度,请使用一定浓度的 H 2 O 2以在生物体中产生最大 ROS,同时杀死不到 10% 的细胞(Mondal等人, 2020)。可以使用不同浓度的 H 2 O 2和活细胞可渗透的核酸结合荧光染料 SYBR Green I 进行活-死检测。用不同浓度的 H 2 O 2 处理细胞,使用不同浓度的 H 2 O 2检测活细胞Sybr Green I 和 FCM 确定导致低于 10% 杀灭率的 H 2 O 2浓度(Mondal等人, 2020 年)。
2.流式细胞仪在细胞/细丝尺寸方面存在限制。喷嘴可以分析大约 1 µm 到 50 µm 的细胞/灯丝长度。尽管尺寸范围可能有所不同,但建议在使用丝状蓝藻或形成团块或聚集体的生物时要小心。长丝可能会堵塞喷嘴。如果需要,建议在通过 FCM 采集样品之前使用超声波仪准备短丝。然而,应提前分析超声处理对 ROS 水平和细胞存活的影响。样品可以在超声波浴超声仪中超声处理不同的时间间隔,并且可以通过光学显微镜监测碎片。 Fremyella的细丝 dilosiphon BK14 更短(<50 µm),因此这种蓝藻不需要碎裂。
3.DCFH-DA 是一种光敏荧光探针。建议在最小光线下进行整个实验,避免样品和染料直接暴露在光线下。
或者,可以通过直接细胞计数或细胞样品的浊度测量作为光散射来确定细胞浓度。在 FCM 中采集通常需要至少 1×10 5 个细胞。




食谱


1.2 mM (w/v) DCFH-DA 储备溶液 (1 mL)
a.1 mL 100% 乙醇(分子级)。
b.在 1 mL 的 100% 乙醇中溶解 0.974 mg DCFH-DA。
c.通过涡旋混合并在-20 °C的黑暗中储存(可储存长达 3 个月)。


2.0.1 M PBS pH 7.4(100 毫升)
a.将 40 mL 的 0.2 M 磷酸氢二钠 (Na 2 HPO 4 ) 库存与 10 mL 的磷酸二氢钠 (NaH 2 PO 4 ) 库存混合。
b.加入 0.9 g NaCl 并搅拌直至溶解。
c.2 O将体积调至 100 mL,并将 pH 调节至 7.4。
d.使用前通过 0.2 µm 尺寸的 Millipore 膜过滤器过滤。
e.储存在 4 °C。




致谢


这项工作得到了 Banaras 印度教大学 (R/Dev/D/IOE/Incentive/2021-2022/32399) 和印度新德里 SERB 以早期职业研究奖的形式提供的资助。 (ECR/2016/000578) 发给 Shailendra P. Singh。 Soumila Mondal 感谢 UGC 和 BHU 提供 UGC 研究奖学金。作者感谢 DBT 跨学科生命科学学院 (ISLS) BHU 的流式细胞术和荧光显微镜设施。该协议改编自 Mondal等人发布的程序。 (2020 年)。 Pankaj K. Maurya 和 Anjali Gupta的仔细阅读和建议也得到认可。




利益争夺


作者声明没有相互竞争的财务和非财务利益。




参考


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引用:Mondal, S. and Singh, S. P. (2022). Flow Cytometry-based Measurement of Reactive Oxygen Species in Cyanobacteria. Bio-protocol 12(10): e4417. DOI: 10.21769/BioProtoc.4417.
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