Letter pubs.acs.org/journal/estlcu
Noninvasive Mapping of Photosynthetic Heterogeneity in Biological Soil Crusts by Positron Emission Tomography: Carbon Fixation Nicholas T. Vandehey,*,† Trent R. Northen,† Eoin L. Brodie,‡,§ and James P. O’Neil† †
Life Sciences Division and ‡Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States § Department of Environmental Science, Policy and Management, University of California, Berkeley, California 94720-3114, United States ABSTRACT: Biological soil crusts (BSCs) are critical contributors to the biogeochemistry of ecosystems in arid and semi-arid regions worldwide. Photosynthetic microorganisms such as cyanobacteria are often the predominant primary producers, fixing both carbon and nitrogen and producing polysaccharides that aid in soil stabilization. Here, we exposed BSCs to 11CO2 and quantified the spatial distribution of carbon fixation in BSCs on a millimeter scale using positron emission tomography (PET). These experiments showed that live BSCs fixed up to 20 times more carbon than abiotic controls. The results present values for correlations between biological carbon fixation and a proxy for chlorophyll concentration derived from photographs. For the first time, we apply PET imaging, a tool that holds great potential for noninvasively characterizing and mapping biological function either on the surface or deep within opaque environmental matrices, to gain a better understanding of system function and organization with application to photosynthetic microbes in biological soil crusts.
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INTRODUCTION Biological soil crusts (BSCs) are key to the functioning of ecosystems in arid and semi-arid regions around the world, covering up to 70% of the land surface in these regions. Although their biological composition and morphology vary greatly with developmental stage and regional distribution, these microbial communities generally reside in the top 1−2 mm of soil and play key roles in fixing carbon and nitrogen, limiting wind and water erosion, and enhancing water retention following rainfall.1,2 Mature BSCs in general have a wide range of biological diversity, including lichens, mosses, microfungi, and bryophytes.1 In contrast, early developmental stage BSCs are characteristically dominated by filamentous cyanobacteria such as Microcoleous vaginatus,3 an organism that is resistant to extreme temperatures and long periods of desiccation. Previous work by us and others has shown that M. vaginatus responds rapidly to sporadic wetting events.4−6 Following a wetting event, these cyanobacteria rise to the surface through extracellular sheaths, primarily through a hydrotactic response, and rapidly activate photosynthetic pathways through a cascade of rapid biological changes.5,7,8 These pathways in hydrated BSCs fix carbon at a rate equivalent to that of phanerogmous leaves,9 accounting for an estimate of some 1014 g of carbon fixed in BSCs worldwide.10 However, like many microbial communities, BSCs are known to have a high degree of spatial heterogeneity (“patchiness”) in both distribution and function from the microscale to landscape scale, making it difficult to estimate their global impact. Furthermore, there is currently a © 2014 American Chemical Society
lack of scientific tools at the micro- and mesoscales for the quantification of heterogeneity.8,11 Here, we employ positron emission tomography (PET), an imaging modality principally used in medicine, in a proof-ofprinciple experiment aimed at quantifying the spatial distribution of fixed carbon at the millimeter scale in early developmental stage BSCs (light crusts) from the Colorado Plateau region of the United States. PET images represent a spatially resolved measurement (with 2−4 mm resolution) of the concentration of molecules radiolabeled with short-lived, positron-emitting isotopes (i.e., 11C, 13N, 15O, 18F, etc.).12 A PET camera (scanner) remotely detects high-energy γ-rays emitted from radiolabeled molecules (from potentially >20 cm deep within a sample) and reconstructs an image representing the three-dimensional (3D) spatial distribution of the isotope concentration. The use of PET can be particularly useful in environmental applications in that it is highly sensitive and nondestructive, allowing for samples to be their own control. We hypothesized that the spatial distribution of photosynthetically active organisms may be determined through the PET analysis of 11C retention. To test this hypothesis, we tested whether spatial patterns of 11CO2 uptake correlated to surface “greening” of the BSCs that occurs due to the chlorophyll Received: Revised: Accepted: Published: 393
July 3, 2014 August 29, 2014 September 2, 2014 September 2, 2014 dx.doi.org/10.1021/ez500209c | Environ. Sci. Technol. Lett. 2014, 1, 393−398
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Figure 1. Time course of the longitudinal experiment. Each measurement interval is shown as a vertical line. Wetting events are marked as raindrops with qualitative estimates of moisture content depicted as blue/brown gradients in the background. The measured temperature is depicted by the red line. The lamp was on during periods where the x-axis is yellow and off where the x-axis is gray.
Figure 2. Exposure chamber (left) as photographed from above. Schematic diagram (right) of the exposure chamber, arrangement of BSCs, and associated plumbing, detector, and flow controllers.
content13 of cyanobacteria that migrate to the soil surface. We designed a series of experiments in which we monitored CO2 uptake in BSCs following exposure to radiolabeled 11CO2 gas in a sealed chamber and measured the retention of 11C spatially across the surface. This is the first use of this radiotracer technique for studying BSCs, a technique that allowed for measurements to be made nondestructively over 2.5 extended light/dark cycles and over multiple wetting events in investigating the role of water and light in the spatial distribution of uptake of CO2 by BSCs.
not lead to pooling of water. Similarly, 3.5−4 mL of water was added for the third wetting, with none added to the AC wet sample as it was still saturated. Following wetting events, the relative humidity in the chamber is expected to have approached 100% as water condensed on the walls of the exposure chamber. Qualitative water content estimates given in Figures 1 and 4 are based on visual observation of the crusts. Note that the crusts were more noticeably more saturated just prior to the wetting event on day 2 than prior to the wetting event on day 3. Hereafter, we refer to samples based on day and measurement interval, i.e., 2B for day 2 and measurement interval B. During the experiment, the BSC dishes were fixed to the base of an acrylic exposure chamber designed to be compatible with the PET/CT imaging system (Figure 2). Its internal dimensions are 2.6 cm × 17.5 cm × 17.5 cm, giving an internal volume of 810 mL, with a small fan inside to circulate air in the chamber and luer-lock fittings for connecting gas delivery lines to the sealed chamber. Radiation detectors15 were placed near the entrance and exit ports for monitoring internal radiation levels during exposure periods. The chamber was positioned 1.0 m below a 1000 W metal halide lamp (Digilux 1000 MH) at a 12° zenith angle to achieve a light flux of 300 μmol of photons m−2 s−1 to the top surface of the exposure chamber. As this work was performed in a “hot cell”, an enclosed space built for radioactive work, the lamp’s heat resulted in an increase in temperature to 37 °C during “daytime” periods, cooling to 24 °C during “night”, as measured in the air adjacent to the chamber. Radiolabeled 11CO2 (half-life of 20.3 min) was produced via the 14N(p,α)11C reaction on a CTI RDS111 11 MeV cyclotron at the Lawrence Berkeley National Laboratory Biomedical Isotope Facility by irradiating a 1% O2/N2 gas mixture. The newly formed 11CO2 was separated from the O2/N2 mix by trapping it on a room-temperature carbosieves column16,17 and eluted off the column (at 125 °C) into the exposure chamber in a stream of helium at a rate of 5 mL/min, passing by a radiation
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METHODS Experiments were performed on a sample set of cyanobacteriadominated BSCs previously characterized by Rajeev et al.,5 consisting of >60% M. vaginatus. Briefly, five subsamples of BSCs were collected from outside Moab, UT, United States (38°42′53.9″N, 109°41′34.6″W), in 6 cm diameter Petri dishes and stored desiccated in the dark until experimentation.14 Crusts were extracted from Petri dishes by gently shaking to remove underlying soil, gently tracing the circumference of the dish with a needle to free the edges, and inverting into the Petri dish lid, leaving the intact crust. One of the five samples was autoclaved (AC) for 55 min at 121 °C and 15 psi 1 day prior to experimentation, with larger, contiguous crust segments extracted and placed in smaller dishes (3 cm diameter), serving as abiotic controls for dry and wet-up conditions. BSCs were manipulated and imaged over the course of 3 days, going through three wetting events over two 32 h light/ dark cycles, allowing for staggering of light and dark conditions during the hours that cyclotron-produced 11CO2 was available. The overall scheme is shown in Figure 1, with vertical lines showing the time of imaging experiments. Initially, wetting consisted of adding 9 mL of deionized water to each crust sample and 2 mL to the wet AC sample; volumes were chosen to achieve full BSC saturation with a thin layer of water pooling on top. The second wetting event comprised of 3 and 0.5 mL (AC) of water added, which fully saturated the crusts but did 394
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Figure 3. Images from day 3, interval D, as an example of the image processing steps. (A) Visible light photograph with a close-up inset image. Note the green filamentous cyanobacteria in the inset. (B) Pcyano image with a close-up inset image (scale shown in panel D). (C) Fused image of PET and Pcyano (unsmoothed). (D) Two-dimensional histogram of smoothed Pcyano vs PET with axes shown as color bars (0−0.1 for Pcyano and 0−1 for PET). Grayscale intensity represents the number of voxels in a histogram bin. The blue line represents the linear regression (r2 = 0.81). (E) Smoothed Pcyano image. (F) PET image (scale shown in panel D).
Figure 4. Summary of experimental conditions (top), similar to Figure 1. Lamp ON/OFF shown as yellow/gray. Hydration shown as color gradient and height. PET images (middle) of four intact BSCs and two autoclaved controls over 12 imaging experiments. Colors in circles on the right correspond to bar charts below. Mean pixel values (bottom) in each BSC.
detector for the determination of the total amount of delivered 11 CO2. On average, 37 mCi of 11CO2 was delivered for 11 min, after which, the chamber was flushed with dry compressed air for 10 min at a rate of 500 mL/min, completely flushing out unreacted 11CO2. The exposure chamber was then transported to a Siemens Biograph 6 PET/CT scanner, where a spiral CT (computed tomography) image (130 keV, CARE dose4D enabled, 1.25 mm slices) and a 10 min duration static PET image were acquired. PET images were reconstructed using the scanner’s TrueX reconstruction algorithm with quantitative units of becquerels per milliliter. Images were normalized to delivered activity values and scaled to the range of 0−1, resulting in unitless
images. CT images were registered to PET images for delineation of BSC boundaries. Volumetric data were cropped to include just the region containing the BSCs, transformed to give isotropic pixel sizes, and summed across slices to give a single planar image. Summation of slices was necessary with such a thin sample (approximately 2−5 mm) as the PET scanner’s capabilities (4 mm resolution) do not allow resolution of the 11C signal on the surface of the crust from the 11C signal that originates from immediately below the surface. These processing steps resulted in images with pixel values proportional to 11C retention summed through the entire thickness of each BSC sample. 395
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Figure 5. Correlation of PET images with Pcyano images. Each column represents an experiment and BSC sample. PET is scaled in color (see Figure 4), while Pcyano is shown overlaid on PET as grayscale. Values below each image represent r2 values of how well PET and smoothed Pcyano images (note that an unsmoothed image is shown) correlate with cell color scaled to its r2 value (red = 0, yellow = 0.4, green = 0.8). The bottom row gives an average of r2 values for each experiment.
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RESULTS AND DISCUSSION As expected, following wetting of the BSCs and exposure to light, filamentous cyanobacteria exhibited hydrotaxis and migrated to the surface in a heterogeneous pattern, with each crust sample having a different distribution and density of growth. The autoclaved wet sample did not show any cyanobacterial migration. As these experiments were performed over the course of minutes and considering the short half-life of 11 C (20 min), it is important to note the potential decrease in the amount of fixed carbon resulting from biomass mineralization, for example, upon cell death would be of minimal effect over this time scale due to the slow growth rate and stability of the BSCs. Accordingly, the pattern and magnitude of the signal in the images are taken to simply represent the spatial distribution of 11C within the crust (Figure 4). On day 1, the desiccated samples showed some 11CO2 uptake with a similar distribution under both light and dark conditions. This pattern roughly matched the visual appearance of fractures on the BSC surface, and accordingly, an ad-hoc analysis comparing PET and CT images revealed a strong relationship with crust thickness and CO2 uptake. Furthermore, abiotic controls (AC) showed similar CO2 uptake, suggesting that the uptake of CO2 by dry soil was primarily abiotic. Following wetting (1C and 1D), uptake was diminished by a factor of 4.5, even in the dry autoclaved sample, suggesting that humidity influences abiotic uptake. This initial wetting event
To analyze regions in which cyanobacteria had migrated to the surface of the crusts, each BSC was photographed prior to each experiment on days 2 and 3, but not on day 1 as there was no visible indication of surface cyanobacteria at this point. Photos were taken from directly above the crusts using a Canon PowerShot SX30 IS camera in “automatic” mode. Each photograph was manually coregistered with CT images to give photographs the same field of view and pixel dimension as the PET and CT images. This visible light photograph was processed in a pixelwise manner for its likelihood for having cyanobacteria located at that location (Pcyano), based on its RGB value similar to the crust index used by Karneili et al.:18 P(x , y)cyano =
G(x , y) − G(x , y) +
R(x , y) + B(x , y) 2 R(x , y) + B(x , y) 2
As shown by the example in Figure 3, the Pcyano images were smoothed with a 1.33 mm full width at half-maximum Gaussian filter to give it noise characteristics and spatial resolution similar to those of the PET image. For each BSC image, linear regression analysis was applied to the series of the paired image values between PET and Pcyano images, using the coefficient of determination, r2, as the metric quantifying the degree of the linear relationship between values in a smoothed Pcyano image and its corresponding PET image. 396
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physical, chemical, and biological properties. We also expect that modified protocols could be used to address different scientific questions such as quantifying both the rate and location of CO2 uptake using dynamic imaging or by using another radiolabeled molecule such as 13N2 to characterize N2 fixation, a project that is currently underway in our laboratory. Finally, as PET allows for 3D imaging, function can be investigated anywhere radiotracers can be delivered to, such as deep within samples much thicker than BSCs. While there are indeed many potential applications of this technology, this work presents the first use of this radioisotope imaging in the study of functional spatial heterogeneity in BSCs, a proof-ofprinciple experiment that demonstrates the utility of this technique for tracing biogeochemical processes in any type of soil system.
left a thin layer of water sitting on the surface of the crust, which could have also reduced the amount of CO2 from the surrounding air diffusing into the surface of the crust. Abiotic controls showed consistent uptake from intervals 1C through 3D, with a magnitude ranging from 5 to 100% of the intact crusts’ uptake. On day 2, following hydration and exposure to light, cyanobacteria had migrated to the crust surface and crusts remained moist at this point as air flow slowly increased the rate of drying. Given these conditions, three of the four crusts fixed CO2 to a much greater degree, but the rate of uptake in crust 3 was decreased. The second wetting event (day 2) did not appear to significantly impact the uptake of CO2, suggesting water was nonlimiting at this point. On day 3, as expected, crusts were drier than on day 2 because of air flow, and although some CO2 was retained during the dark period (3A), only slightly more was retained when lights were on (3B). As the abiotic controls showed lower carbon uptake, it is possible that other nonphotosynthetic carbon fixation pathways contributed to dark carbon uptake (e.g., a chemoautotrophic process like ammonia oxidation19). Following the wetting event on day 3, crusts 1, 2, and 4 readily resumed CO2 fixation while uptake in crust 3 was diminished. This effect illustrates the idea that these crusts vary across samples not only in cyanobacterial distribution but also in function, a distinction that PET imaging is well suited for measuring. The pattern of CO2 uptake supported the hypothesis that regions of the crust samples that appeared visually green would preferentially fix more CO2, as shown in Figure 5, where PET and Pcyano images are overlaid and r2 relationships between modalities given. On average, this relationship was strongest at measurement intervals where the crusts were well hydrated and exposed to light (2B−2D, 3C, and 3D; mean r2 = 0.49) as opposed to dry crusts under light (2A and 3B; mean r2 = 0.39) and dry crusts in the dark (3A; mean r2 = 0.28). A particularly interesting result is that the weakest correlation between photosynthesis and Pcyano in the four BSCs was found for a very dark green crust (crust 1), indicating that having green regions (phototrophic organisms) on the crust surface does not necessarily indicate photosynthetic activity, a result similar to previous work correlating indices based on surface adsorption measures and photosynthetic activity.20,21 This mismatch (quantified as a lower r2 value) may be a result of internal shading or more complex processes that were not investigated in this work. Further analyses could help deconstruct such discrepancies and would help improve our understanding of what regulates photosynthetic activity in BSCs to improve future estimates of global BSC contributions to carbon cycling. In this work, we apply PET imaging to the study of biological soil crusts, highlighting its utility for defining millimeter−meter scale heterogeneities in the distribution of microbial function in soils. With this capability, we imagine that experiments could be designed to help interpret results from experiments at a much larger scale by relating imaging results across scales. Furthermore, due to its noninvasive nature, PET imaging holds potential to be useful upstream of other destructive analytical methods that can be employed at a much finer scale such as genomic/metabolomics analyses or stable-isotope spectroscopy. In this case, PET can be used to guide the identification of microbial “hot spots” at the millimeter to meter scale under a broad range of experimental conditions. These hot spots can be deconstructed to understand their relevant
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS We thank Dr. Mustafa Janabi for his help preparing radioisotopes and Alissa Bruno for preparing the image for the abstract graphic and the table of contents graphic. This material is based in part on work supported by the Laboratory Directed Research and Development program at Lawrence Berkeley National Laboratory and the Radiochemistry and Instrumentation Scientific focus Area as funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. T.R.N. is supported by the Department of Energy, Early Career Research Program. This manuscript was written by an author at Lawrence Berkeley National Laboratory under Contract DE-AC02-05CH11231 with the U.S. Department of Energy.
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REFERENCES
(1) Belnap, J. The world at your feet: Desert biological soil crusts. Frontiers in Ecology and the Environment 2003, 1, 181−189. (2) Belnap, J. The potential roles of biological soil crusts in dryland hydrologic cycles. Hydrol. Processes 2006, 20, 3159−3178. (3) Garcia-Pichel, F.; López-Cortés, A.; Nübel, U. Phylogenetic and morphological diversity of cyanobacteria in soil desert crusts from the Colorado Plateau. Appl. Environ. Microb. 2001, 67, 1902−1910. (4) Lan, S.; Wu, L.; Zhang, D.; Hu, C. Desiccation provides photosynthetic protection for crust cyanobacteria Microcoleus vaginatus from high temperature. Physiol. Plant 2014, DOI: 10.1111/ppl.12176. (5) Rajeev, L.; Nunes da rocha, U.; Klitgord, N.; Luning, E. G.; Fortney, J.; Axen, S. D.; Shih, P. M.; Bouskill, N. J.; Bowen, B. P.; Kerfeld, C. A.; Garcia-Pichel, F.; Brodie, E. L.; Northen, T. R.; Mukhopadhyay, A. Dynamic cyanobacterial response to hydration and dehydration in a desert biological soil crust. ISME J. 2013, 7, 2178− 2191. (6) Rosentreter, R.; Belnap, J. Biological Soil Crusts of North America. In Biological soil crusts: Structure, function, and management; Belnap, J., Lange, O. L., Eds.; Springer: Berlin, 2003; pp 31−50. (7) Garcia-Pichel, F.; Castenholz, R. W. Photomovement of microorganisms in benthic and soil microenvironments. In Comprehensive Series in Photosciences; Elsevier: Amsterdam, 2001; pp 403−420. (8) Garcia-Pichel, F.; Belnap, J. Small-scale environments and distribution of biological soil crusts. In Biological soil crusts: Structure, function, and management; Belnap, J., Lange, O. L., Eds.; Springer: Berlin, 2003; pp 193−201. 397
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(9) Lange, O. L. Photosynthesis of Soil-Crust Biota as Dependent on Environmental Factors. In Biological soil crusts: Structure, function, and management; Belnap, J., Lange, O. L., Eds.; Springer: Berlin, 2003; pp 217−240. (10) Garcia-Pichel, F.; Belnap, J.; Neuer, S.; Schanz, F. Estimates of global cyanobacterial biomass and its distribution. Algol. Stud. 2003, 109, 213−227. (11) Grondin, A. E.; Johansen, J. R. Microbial spatial heterogeneity in microbiotic crusts in Colorado National Monument. Western North American Naturalist 1993, 53, 24−30. (12) Levin, C. S. Primer on molecular imaging technology. Eur. J. Nucl. Med. Mol. Imaging 2005, 32, S325−S345. (13) Lange, O. L. Photosynthesis of soil-crust biota as dependent on environmental factors. In Biological soil crusts: Structure, function, and management; Belnap, J., Lange, O. L., Eds.; Springer: Berlin, 2003; pp 217−240. (14) Strauss, S. L.; Day, T. A.; Garcia-Pichel, F. Nitrogen cycling in desert biological soil crusts across biogeographic regions in the Southwestern United States. Biogeochemistry 2012, 108, 171−182. (15) Powell, J.; O’Neil, J. P. A simple low-cost photodiode radiation detector for monitoring in process PET radiochemistry. In Automation and Chemistry; Proceedings of the 14th International Workshop on Targetry and Target Chemistry, Playa Del Carmen, Mexico, August 26−29, 2012; Avila-Rodriguez, M. A., O’Neil, J. P., Barnhart, T. E., Dick, D. W., Koziorowski, J., Lapi, S., Lewis, J. S., Eds.; American Institute of Physics: Melville, NY, 2012; pp 249−254. (16) Mock, B. H.; Vavrek, M. T.; Mulholland, G. K. Solid-phase reversible trap for [11C]carbon dioxide using carbon molecular sieves. J. Nucl. Med. 1995, 22, 667−670. (17) Vandehey, N. T.; O’Neil, J. P. Capturing [11C]CO2 for use in aqueous applications. Appl. Radiat. Isot. 2014, 90, 74−78. (18) Karnieli, A. Development and implementation of spectral crust index over dune sands. International Journal of Remote Sensing 1997, 18, 1207−1220. (19) Marusenko, Y.; Bates, S. T.; Anderson, I.; Johnson, S. L.; Soule, T.; Garcia-Pichel, F. Ammonia-oxidizing archaea and bacteria are structured by geography in biological soil crusts across North American arid lands. Ecological Processes 2013, 2, 9. (20) Burgheimer, J.; Wilske, B.; Maseyk, K.; Karnieli, A.; Zaddy, E.; Yakir, D.; Kesselmeier, J. Relationship between normalized difference vegetation index (NDVI) and carbon fluxes of biological soil crusts assessed by ground measurements. Journal of Arid Environments 2006, 64, 651−669. (21) Yamano, H.; Chen, J.; Zhang, Y.; Tamura, M. Relating photosynthesis of biological soil crusts with reflectance: Preliminary assessment based on a hydration experiment. International Journal of Remote Sensing 2006, 27, 5393−5399.
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