Dataset Information

A Simple and Non-destructive Method for Chlorophyll Quantification of Chlamydomonas Cultures Using Digital Image Analysis.

ABSTRACT: Growing interest in the use of microalgae as a sustainable feedstock to support a green, circular, bio-economy has led to intensive research and development initiatives aimed at increasing algal biomass production covering a wide range of scales. At the heart of this lies a common need for rapid and accurate methods to measure algal biomass concentrations. Surrogate analytical techniques based on chlorophyll content use solvent extraction methods for chlorophyll quantification, but these methods are destructive, time consuming and require careful disposal of the resultant solvent waste. Alternative non-destructive methods based on chlorophyll fluorescence require expensive equipment and are less suitable for multiple sampling of small cultures which need to be maintained under axenic growth conditions. A simple, inexpensive and non-destructive method to estimate chlorophyll concentration of microalgal cultures in situ from digital photographs using the RGB color model is presented. Green pixel intensity and chlorophyll a, b and total chlorophyll concentration, measured by conventional means, follow a strong linear relationship (R 2 = 0.985-0.988). In addition, the resulting standard curve was robust enough to accurately estimate chlorophyll concentration despite changes in sample volume, pH and low concentrations of bacterial contamination. In contrast, use of the same standard curve during nitrogen deprivation (causing the accumulation of neutral lipids) or in the presence of high quantities of bacterial contamination led to significant errors in chlorophyll estimation. The low requirement for equipment (i.e., a simple digital camera, available on smartphones) and widely available standard software for measuring pixel intensity make this method suitable for both laboratory and field-based work, particularly in situations where sample, qualified personnel and/or equipment is limited. By following the methods described here it should be possible to produce a standard curve for chlorophyll analysis in a wide range of testing conditions including different microalga cultures, culture vessel and photographic set up in any particular laboratory.

SUBMITTER: Wood NJ

PROVIDER: S-EPMC7386287 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Simple and Non-destructive Method for Chlorophyll Quantification of <i>Chlamydomonas</i> Cultures Using Digital Image Analysis.

Wood Nicola J NJ Baker Alison A Quinnell Rupert J RJ Camargo-Valero Miller Alonso MA

Frontiers in bioengineering and biotechnology 20200721

Growing interest in the use of microalgae as a sustainable feedstock to support a green, circular, bio-economy has led to intensive research and development initiatives aimed at increasing algal biomass production covering a wide range of scales. At the heart of this lies a common need for rapid and accurate methods to measure algal biomass concentrations. Surrogate analytical techniques based on chlorophyll content use solvent extraction methods for chlorophyll quantification, but these methods ...[more]

PMID: 32793564

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Project description:There is a growing interest in using 18F-DPA-714 PET to study neuroinflammation and microglial activation through imaging the 18-kDa translocator protein (TSPO). Although quantification of 18F-DPA-714 binding can be achieved through kinetic modeling analysis with an arterial input function (AIF) measured with blood sampling procedures, the invasiveness of such procedures has been an obstacle for wide application. To address these challenges, we developed an image-derived input function (IDIF) that noninvasively estimates the arterial input function from the images acquired for 18F-DPA-714 quantification.MethodsThe method entails three fully automatic steps to extract the IDIF, including a segmentation of voxels with highest likelihood of being the arterial blood over the carotid artery, a model-based matrix factorization to extract the arterial blood signal, and a scaling optimization procedure to scale the extracted arterial blood signal into the activity concentration unit. Two cohorts of human subjects were used to evaluate the extracted IDIF. In the first cohort of five subjects, arterial blood sampling was performed, and the calculated IDIF was validated against the measured AIF through the comparison of distribution volumes from AIF (VT,AIF) and IDIF (VT,IDIF). In the second cohort, PET studies from twenty-eight healthy controls without arterial blood sampling were used to compare VT,IDIF with VT,REF measured using a reference region-based analysis to evaluate whether it can distinguish high-affinity (HAB) and mixed-affinity (MAB) binders.ResultsIn the arterial blood-sampling cohort, VT derived from IDIF was found to be an accurate surrogate of the VT from AIF. The bias of VT, IDIF was -5.8 ± 7.8% when compared to VT,AIF, and the linear mixed effect model showed a high correlation between VT,AIF and VT, IDIF (p < 0.001). In the nonblood-sampling cohort, VT, IDIF showed a significance difference between the HAB and MAB healthy controls. VT, IDIF and standard uptake values (SUV) showed superior results in distinguishing HAB from MAB subjects than VT,REF.ConclusionsA novel IDIF method for 18F-DPA-714 PET quantification was developed and evaluated in this study. This IDIF provides a noninvasive alternative measurement of VT to quantify the TSPO binding of 18F-DPA-714 in the human brain through dynamic PET scans.

Project description:BACKGROUND:The bacterial leaf pathogen Pseudomonas syringae pv tomato (Pst) is the most popular model pathogen for plant pathology research. Previous methods to study the plant-Pst interactions rely on destructive quantification of Pst colonisation, which can be labour- and time-consuming and does not allow for spatial-temporal monitoring of the bacterial colonisation. Here, we describe a rapid and non-destructive method to quantify and visualise spatial-temporal colonisation by Pst in intact leaves of Arabidopsis and tomato. RESULTS:The method presented here uses a bioluminescent Pst DC3000 strain that constitutively expresses the luxCDABE operon from Photorhabdus luminescens (Pst::LUX) and requires a common gel documentation (Gel Doc) system with a sensitive CCD/CMOS camera and imaging software (Photoshop or Image J). By capturing bright field and bioluminescence images from Pst::LUX-infected leaves, we imaged the spatiotemporal dynamics of Pst infection. Analysis of bioluminescence from live Pst bacteria over a 5-day time course after spray inoculation of Arabidopsis revealed transition of the bacterial presence from the older leaves to the younger leaves and apical meristem. Colonisation by Pst:LUX bioluminescence was obtained from digital photos by calculating relative bioluminescence values, which is adjusted for bioluminescence intensity and normalised by leaf surface. This method detected statistically significant differences in Pst::LUX colonisation between Arabidopsis genotypes varying in basal resistance, as well as statistically significant reductions in Pst::LUX colonisation by resistance-inducing treatments in both Arabidopsis and tomato. Comparison of relative bioluminescence values to conventional colony counting on selective agar medium revealed a statistically significant correlation, which was reproducible between different Gel Doc systems. CONCLUSIONS:We present a non-destructive method to quantify colonisation by bioluminescent Pst::LUX in plants. Using a common Gel Doc system and imaging software, our method requires less time and labour than conventional methods that are based on destructive sampling of infected leaf material. Furthermore, in contrast to conventional strategies, our method provides additional information about the spatial-temporal patterns of Pst colonisation.

Dataset Information

A Simple and Non-destructive Method for Chlorophyll Quantification of Chlamydomonas Cultures Using Digital Image Analysis.

Publications

A Simple and Non-destructive Method for Chlorophyll Quantification of <i>Chlamydomonas</i> Cultures Using Digital Image Analysis.

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