Potential Mechanisms and Environmental Controls of TiO2

Nov 20, 2013 - Bren School of Environmental Science and Management,. ‡ ... underlying mechanisms.10,11 From an ecological perspective, there are two...
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Potential Mechanisms and Environmental Controls of TiO2 Nanoparticle Effects on Soil Bacterial Communities Yuan Ge,†,‡,§ John H. Priester,†,‡,§ Laurie C. Van De Werfhorst,†,‡,§ Joshua P. Schimel,‡,§,∥ and Patricia A. Holden*,†,‡,§ †

Bren School of Environmental Science and Management, ‡Earth Research Institute, §Center for the Environmental Implications of Nanotechnology (UC CEIN), and ∥Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, California 93106, United States S Supporting Information *

ABSTRACT: It has been reported that engineered nanoparticles (ENPs) alter soil bacterial communities, but the underlying mechanisms and environmental controls of such effects remain unknown. Besides direct toxicity, ENPs may indirectly affect soil bacteria by changing soil water availability or other properties. Alternatively, soil water or other environmental factors may mediate ENP effects on soil bacterial communities. To test, we incubated nano-TiO2-amended soils across a range of water potentials for 288 days. Following incubation, the soil water characteristics, organic matter, total carbon, total nitrogen, and respiration upon rewetting (an indicator of bioavailable organic carbon) were measured. Bacterial community shifts were characterized by terminal restriction fragment length polymorphism (T-RFLP). The endpoint soil water holding had been reported previously as not changing with this nano-TiO2 amendment; herein, we also found that some selected soil properties were unaffected by the treatments. However, we found that nano-TiO2 altered the bacterial community composition and reduced diversity. Nano-TiO2-induced community dissimilarities increased but tended to approach a plateau when soils became drier. Taken together, nano-TiO2 effects on soil bacteria appear to be a result of direct toxicity rather than indirectly through nanoTiO2 affecting soil water and organic matter pools. However, such directs effects of nano-TiO2 on soil bacterial communities are mediated by soil water.

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INTRODUCTION The increasing industrial application of engineered nanoparticles (ENPs) will inevitably increase their environmental release, with soils predicted to be a substantial sink.1,2 Although some ENPs (i.e., metal or metal oxide) can alter soil bacterial communities,3−7 reduce microbial biomass,4,8,9 and affect bacterial taxa associated with nitrogen fixation, methane oxidation, and organic compound decomposition,5 there remain questions about the extent of such effects and the underlying mechanisms.10,11 From an ecological perspective, there are two possible classes of mechanisms that can explain the observed adverse effects of ENPs on soil bacteria. The first is direct toxicity: ENPs may directly damage cells through attachment-related membrane disruption, DNA damage, and reactive oxygen species (ROS) production, or through the release of toxic ions; such processes are observed in well-mixed laboratory cultures.12−16 The second involves indirect effects. These could include food web effects, such as toxicity to protozoa that consume bacteria17,18 or impacts on fungi that compete with bacteria for resources. Importantly, indirect effects could also include altering the physical environment of the soil; because of their high specific surface area and © XXXX American Chemical Society

reactivity, ENPs may influence water characteristics or other soil properties that are vital for bacterial survival and growth.19,20 However, it is unknown whether the observed adverse effects of ENPs on soil bacterial communities are dominated by direct toxicity or indirect effects. In addition to the potential effects of ENPs on soil properties and thus on soil bacteria, environmental factors (e.g., soil water characteristics) may alter the interactions between ENPs and soil bacteria and thus mediate ENP effects on soil bacterial communities. Because soil bacterial populations may function as meta-populations that reside in spatially segregated microhabitat patches connected through water films,21,22 soil water can change the size and connectivity of microhabitat patches by changing the distribution of water films in soil pores. Again, however, it is not known how varying soil water content mediates ENP effects on soil bacterial communities. Received: July 30, 2013 Revised: November 18, 2013 Accepted: November 20, 2013

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To elucidate the underlying mechanisms and environmental controls of ENP effects on soil bacterial communities, we incubated soils amended with nanoparticulate titanium dioxide (nano-TiO2) across a range of water potentials that were regulated through isopiestic equilibration. Nano-TiO2 was chosen due to its wide application in sunscreens, cosmetics, and coatings; it therefore is released into the environment in substantial amounts.1,23 Following a 288 day equilibration, the soils were evaluated for soil water characteristics, organic matter (OM), total carbon (C), total nitrogen (N), and respiration upon rewetting (an indicator of bioavailable organic C). Soil DNA was extracted to characterize bacterial community shifts and was analyzed by terminal restriction fragment length polymorphism (T-RFLP) profiling. We hypothesized that (1) nano-TiO2 can affect soil water or organic matter pools, thereby indirectly affecting soil bacteria, and (2) soil water characteristics can mediate the direct toxic effects of nano-TiO2 on soil bacteria. Our results falsified the first hypothesis but supported the second, showing that nano-TiO2 effects on soil bacteria are not due to the effects on soil water or organic matter pools but that soil water characteristics can mediate toxic effects.

We used isopiestic equilibration with saturated salt solutions to incubate control and nano-TiO2-amended soils across a range of water potentials. As detailed before and briefly described herein,25 each equilibration system consisted of 200 mL of saturated salt solution in a polycarbonate/polypropylene desiccator (model #5315, Nalgene, Rochester, NY, U.S.A.), with a perforated aluminum disc above the solution surface to position six soil-containing glass bottles (41−43 mm diameter) with 25 g (dry mass basis) of soil per bottle. Because water vapor exchanges between the soil and the saturated salt solution, the soil water potential converges on that of the salt solution over time. The saturated salt solutions used in this study were H2O (water potential: 0 MPa), K2SO4 (−2.6 MPa), KNO3 (−6.3 MPa), KCl (−20.8 MPa), and NaCl (−36.9 MPa). The saturated salt solutions were prepared by adding each salt (Sigma-Aldrich, St. Louis, MO, U.S.A.) to 200 mL of H2O at a mass twice that required to achieve a saturated solution. For the six soil samples in each equilibration chamber (desiccator), three were used as triplicate samples for the endpoint analyses and three for a time-course water content measurement.25 The desiccators were sealed with a thin layer of vacuum grease to prevent water vapor transfer to the surrounding air, placed in a temperature controlled room (measured range: 13.6−14.3 °C) for 288 days, and ventilated for less than 30 s at regular intervals when making a time-course mass measurement for interval water content calculations. This design resulted in three replicates per exposure dose of nanoTiO2 (0 or 20 mg g−1 soil) and saturated salt solution treatment (H2O, K2SO4, KNO3, KCl, or NaCl). The full details of the experimental setup, plus the soil physical characteristics over time and at the experiment conclusion, were reported previously.25 Soil Water and Other Selected Properties. The soil water potential was determined with a thermocouple psychrometer (True Psi model SC10, Decagon, Pullman, WA, U.S.A.) according to the manufacturer’s instructions. In brief, 1.5 cm3 of soil was used to fill the sample holder and was quickly loaded into the thermocouple psychrometer to avoid water vapor exchange between the samples and the ambient atmosphere. After 20 min of thermal equilibration, the soil water potential was measured by thermocouple psychrometry. The soil water content was measured gravimetrically by calculating the mass difference prior to versus following 105 °C drying for 48 h.27 Organic matter was determined using the loss-on-ignition (LOI) method.28 In brief, following the final water content measurement, each weighing bottle sample was heated to 550 °C for 5 d, cooled to room temperature in a desiccator, and weighed a final time. Organic matter was calculated as the difference between the dry soil mass (post 105 °C heating) and the mass following 550 °C heating. Total C and total N were measured with an automated organic elemental analyzer (CEC 440HA; Control Equipment, Chelmsford, MA, U.S.A.) by the UC Santa Barbara Marine Science Institute Analytical Laboratory (http://www.msi.ucsb. edu/services/analytical-lab) using the Dumas combustion method. The bioavailable C was evaluated by measuring respiration potential after rewetting soils.29 As such, at the conclusion of the experiment, 10 g of soil from each replicate and 1 mL of water were added to amber round bottles, sealed with Mininert caps (Fisher, Rochester, NY, U.S.A.), and mixed by shaking; the respiration potential was quantified by measuring the CO2 concentration in the headspace of the

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MATERIALS AND METHODS Experimental Design. Ten 2 kg surface soil samples (0− 10 cm) were randomly collected and mixed to form one composite sample from an annual grassland at the University of California Sedgwick Reserve (34°40′32″ N, 120°2′27″ W). The site has a Mediterranean climate with hot dry summers and cool wet winters. The soil is a weakly acidic Pachic Argiustoll in the Botella series.24 Soil was placed in a sterile plastic bag, sealed, and transported to the laboratory on ice. Visible rocks, roots, and fresh litter were removed and then the soil was sieved to 2 mm and was refrigerated (4 °C) to minimize microbial activity during the storage. The sieved soil had a water potential of −20 MPa and a water content of 8%. Soil pH (6.45), texture (sandy clay loam, 51% sand, 27% silt, and 22% clay), soluble salts (0.28 dS m−1), cation exchange capacity (24.44 meq per 100 g), and nutrients were characterized by the UC Davis Analytical Laboratory (Davis, CA; http://anlab. ucdavis.edu/) and were reported previously.25 The dry powder nano-TiO2 used in this study was comprised of semispherical particles with a primary size of 20−30 nm that agglomerated in deionized water to 194 nm. The dry powder specific surface area was 51.5 m2 g−1, isoelectric point 6.2, and purity 98%.26 The mineralogical content was 81% anatase and 19% rutile (Evonik Degussa, Parsippany, NJ, U.S.A.). The nano-TiO2-amended soil (20 mg g−1) was prepared by adding 16 g of dry powder nanoparticles to 800 g of sieved soil and mechanically mixing in a 2 L polyethylene bottle (diameter = 11 cm, height = 22 cm) on a roller table for 24 h in the dark at room temperature. Soil without nano-TiO2 was used as the control. Our previous studies showed that the same batch of nano-TiO2 at lower concentrations (0, 0.5, 1, and 2 mg g−1) altered bacterial communities from soils sampled previously at the same site. The alterations included some functionally significant taxa that were impacted in a dose-dependent manner.5 In this study, we amended soil with nano-TiO2 at a relatively high concentration (20 mg g−1) because this concentration was predicted to alter soil specific surface area and also water holding; this concentration was also shown to plausibly occur in soil hot spots given assumptions for global nano-TiO2 distribution in the year 2025.25 B

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assumptions of ANOVA were checked using the Kolmogorov−Smirnov test (for normality) and the Levene’s test (for variance homogeneity), showing that all variables met the normality assumption, but a few variables (i.e., soil water potential and water content) did not meet the equal variance assumption. Therefore, two nonparametric methods, Kruskal− Wallis and Friedman’s tests, were used to validate the ANOVA results. Both nonparametric tests achieved the same results as ANOVA at the significance level of 0.05. Principal coordinates analysis (PCoA) and distance-based redundancy analysis (dbRDA) were employed to examine the Bray−Curtis distances between T-RFLP profiles. PCoA is a widely used unconstrained ordination approach to illustrate community shift patterns using distance matrices, while dbRDA is a constrained ordination approach using a multivariate regression-based model to predict community shift patterns based on additional environmental variables.34 dbRDA is an extension of classical RDA, which processes Euclidean distances between samples. However, dbRDA can analyze other types of community distance, e.g., Bray−Curtis, to better suit community data which may contain many “zero” values (absent peaks).35 For dbRDA, the T-RFLP profiles were used as community variables, and the significant (P < 0.05 by Monte Carlo permutation test with 999 permutations 34) environmental variables (nano-TiO2, soil water potential, water content, and bioavailable C) were used as constrained variables. For a Monte Carlo permutation test, the values of the environmental variables are randomly permutated for 999 times, while keeping the community data unchanged. For each of the permutated data sets, the statistical value (e.g., F-statistic) is calculated and compared with the statistical value calculated using the original data set. The significance level of the Monte Carlo permutation test is then calculated as P = (nx+1)/(N+1), where nx is the number of the permutations yielding the statistical value as large or larger than that from the original data set, and N is the total number of permutations (e.g., 999).34 As in other statistical tests, the usual scientific convention of α = 0.05 is used for interpreting the significance of the Monte Carlo permutation test result. Within the environmental variables (nano-TiO2, soil water potential, water content, organic matter, bioavailable C, total C, total N, and the C/N ratio) tested by the Monte Carlo permutation test, nano-TiO2, soil water potential, water content, and bioavailable C significantly (P < 0.05) explained a portion of the community variations. Therefore, only these four environmental variables were used as constrained variables for dbRDA, and their relative effects were identified through variation partitioning.36,37 Nonparametric multivariate ANOVA (NP-MANOVA), a multivariate analogue to Fisher’s F-ratio, was conducted to statistically test for the effects of nano-TiO2 and water equilibration on soil bacterial community structure.38 Regression analysis was conducted to examine nano-TiO 2 effects on bacterial community dissimilarity (Bray−Curtis distances) and changes of terminal restriction fragment (TRF)-based diversity, according to soil water characteristics. Analyses were conducted using SPSS (SPSS, Chicago, IL, U.S.A.), SigmaPlot (Systat Software, San Jose, CA, U.S.A.), or CANOCO (Microcomputer Power, Ithaca, NY, U.S.A.).

bottles with an infrared gas analyzer (EGM-4; PP Systems, Amesbury, MA, U.S.A.) at 5 min intervals for 1 h. Soil DNA Extraction, Polymerase Chain Reaction (PCR), and T-RFLP. Soil DNA was extracted from 0.3 g soil subsampled at the end of the experiment using the Powersoil DNA isolation kit (Mo Bio, Carlsbad, CA, U.S.A.) according to the manufacturer’s instructions. Each of the three endpoint replicates for each treatment were subsampled, thus providing the same degree of replication for DNA analyses as for other (chemical and physical) analyses. DNA was quantified through a fluorescence detection-based method using the Quant-iT DNA assay kit, high sensitivity (Invitrogen, Eugene, OR, U.S.A.).4 Genes encoding 16S rRNA were PCR amplified using the extracted DNA as template and using universal bacterial primers HEX-labeled 8F (AGA GTT TGA TCC TGG CTC AG) and 1389R (ACG GGC GGT GTG TAC AAG).30 The PCR was run on a PCR Sprint thermal cycler (Thermo Scientific, Lafayette, CO, U.S.A.) in 0.25 or 0.5 mL tubes. The final volume of the reaction mixtures was 50 μL, containing 1× PCR buffer, 1× Q-solution (facilitating amplification of templates that have a high degree of secondary structure or that are GC-rich), 0.7 mM MgCl2, 0.2 mM of each dNTP, 0.525 μM of each primer, 1.25 U Taq DNA polymerase (Taq PCR Core Kit; Qiagen, Valencia, CA, U.S.A.), 0.2 μg μL−1 bovine serum albumin (BSA), and 25 ng of template DNA. The thermal cycling scheme involved an initial denaturation at 95 °C for 4 min, followed by 58 °C for 1 min and 72 °C for 90 s. The samples were then held at 72 °C while the Taq and dNTPs were added, followed by 28 cycles of denaturation at 94 °C for 45 s, annealing at 58 °C for 45 s, and extension at 72 °C for 90 s, and a final extension step at 72 °C for 10 min. Negative controls, containing all the components except DNA templates, were included to test for contamination. For each sample, duplicate PCR runs were pooled to reduce random PCR bias. After size and quality verification by 1.2% agarose gel electrophoresis (Flashgel DNA system; Lonza, Allendale, NJ, U.S.A.), PCR products were purified using the QIAquick PCR purification kit (Qiagen, Valencia, CA, U.S.A.) and quantified using the Quant-iT dsDNA assay kit, broad range (Invitrogen, Eugene, OR, U.S.A.). The purified PCR products (600 ng) were digested at 37 °C for 16 h using the HhaI restriction enzyme (New England BioLabs, Ipswich, MA, U.S.A.), followed by deactivation at 65 °C for 20 min. The digested products were purified using the QIAquick nucleotide removal kit (Qiagen, Valencia, CA, U.S.A.). T-RFLP analysis was performed on an ABI PRISM 3100 genetic analyzer (Applied Biosystems, Foster City, CA, U.S.A.) at the Research Technology Support Facility (Michigan State University). Individual fragment peak heights were normalized to the percentage of total height for each sample. Only those fragments between 50 and 1000 bp in size with relative peak heights >1% were included in the analysis. T-RFLP profiles were aligned using the crosstab Excel macro “treeflap”.31 This offers a reproducible and convenient DNA-based community profiling method. Though T-RFLP provides a taxonomic resolution coarser than the species level, it offers a consistent comparative measure of community composition and diversity that is appropriate for evaluating changes with experimental treatments.32,33 Statistical Analysis. Two-way analysis of variance (ANOVA) was performed to test the effects of exposure dose and water characteristics on measured variables. The

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RESULTS AND DISCUSSION Soil Water and Other Selected Properties. As reported previously, after 288 days of isopiestic incubation, a soil moisture gradient was established, with soil water potentials C

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ranging from −2.0 to −36.9 MPa and associated soil water contents ranging from 13.7% to 7.0%.25 These ranges of soil water potential and water content are environmentally relevant because the natural soil collected for this study had a water potential of −20 MPa and a water content of 8% at the time of sampling. While isopiestic equilibration with saturated salt solutions significantly affected soil water potential and water content (P < 0.05 for both variables), nano-TiO2 did not affect either (P = 0.09 for water potential, and P = 0.15 for water content). Neither nano-TiO2 nor isopiestic equilibration affected soil OM, total C, total N, or the C/N ratio (P > 0.05 for all combinations; Figure S1, Supporting Information). Two-way ANOVA showed that nano-TiO2 did not affect the respiration potential upon rewetting (P > 0.05); however, the moisture status of the soil prior to rewetting did significantly affect respiration potential upon rewetting (P < 0.05, Figure 1). A

Figure 2. (a) Principal coordinates analysis (PCoA), (b) distancebased redundancy analysis (dbRDA), and (c) variation partitioning to illustrate the effects of nano-TiO2, soil water characteristics, and bioavailable C on soil bacterial communities.

water content, water potential, and organic carbon availability affect soil microbial community composition.41,42 Soil Water-Mediated Nano-TiO2 Effects on Soil Bacterial Communities. We explored the effects of nanoTiO2 on soil bacterial communities under varying soil water characteristics. The results showed that community dissimilarity between control and nano-TiO2-amended soils increased but tended to approach a plateau when soils became drier (Figure 3). The richness (J) and Shannon (H′) indices were calculated from the T-RFLP profiles to explore the effects of nano-TiO2 and water potential on the diversity of terminal restriction fragments (TRFs), which are coarse indicators of phylogenetic diversity. Both nano-TiO2 and water potential affected TRF richness and the Shannon index (P < 0.05 for all combinations,

Figure 1. Effects of nano-TiO2 and isopiestic equilibration on respiration potential (an indicator of bioavailable C) after soil rewetting. Error bars indicate the standard error of the mean (n = 3).

previous study showed that metal oxide nanoparticles do not change soil OM and extractable soil organic carbon.39 The strong response to the endpoint soil water characteristic of respiration potential upon rewetting may be due to differing bioavailabilities of labile C under varying soil water conditions. As soil dries, labile C becomes unavailable to microbial degradation due to the disconnected water films in soil pores; however, this C becomes bioavailable after rewetting.24,40 Therefore, respiration potential measured in this study was used as an indicator of labile C that had accumulated during the long equilibration.29 Soil Bacterial Communities. Both principal coordinates analysis (PCoA) and distance-based redundancy analysis (dbRDA) illustrated the shifts of bacterial communities from nano-TiO2 exposure and along soil water and bioavailable C gradients induced by the water potential treatments (Figure 2a,b). Variation partitioning showed that nano-TiO2 explained 18.4%, soil water (water content and water potential) 9.9%, and bioavailable C 4.1% of the community variations (Figure 2c). Compared to other possible combinations, the interaction effect of soil water and bioavailable C was high (8.6%). The results of NP-MANOVA coincide well with the results of PCoA and dbRDA and showed significant effects of nano-TiO2 and water potential on bacterial community structure (P < 0.05 for both treatments; results of pairwise comparisons are given in Table S1, Supporting Information). Our previous studies also showed that nano-TiO2 can change soil bacterial communities with lower doses (up to 2 mg g−1 soil).4,5 Furthermore, soil

Figure 3. Regression analysis to illustrate the community dissimilarity between nano-TiO2 treated samples and non-nano-TiO2 treated samples as a function of (a) soil water potential and (b) soil water content. In the range of soil water potential (or soil water content) conducted in this experiment, the community dissimilarities increased but tended to approach a plateau when soils became drier. The boundary of the box closest to zero indicates the 25th percentile, a line within the box marks the median, and the boundary of the box farthest from zero indicates the 75th percentile. Error bars above and below the box indicate the 90th and 10th percentiles, respectively. D

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pools, thereby indirectly affecting soil bacterial communities. Our results did not support this hypothesis and showed that nano-TiO2 altered soil bacterial community composition as evaluated by T-RFLP (Figure 2 and Table S1, Supporting Information) but did not change selected soil properties, i.e., soil water,25 soil OM, total C, total N, the C/N ratio, and bioavailable C (reflected by respiration potential) (Figure S1, Supporting Information and Figure 1). Therefore, any effect on bacterial community composition must be direct or from more subtle effects on soil resources that were not measured in this study. The release of hazardous ions, as observed for other ENPs,9,45 is unlikely to explain the effects measured here because nano-TiO2 is insoluble.46 Previously, we concluded from this experimental setup that nano-TiO2 is somewhat hydrophobic or amphiphilic in this soil,25 and we argued that such characteristics could enable this ENP to be bioavailable to bacteria in soil. While we do not know the spatial relationships between nano-TiO2 and soil bacteria, we can conclude that the toxicity observed herein must be direct. Our conclusion stems from our having modulated soil water potential and, upon examining interactive effects on bacteria of soil water versus nano-TiO2, discovering that soil bacterial community effects increased with drying soil, i.e., resulting in reductions in bacterial community diversity and richness. This suggests that nano-TiO 2 becomes more concentrated around bacteria as soil dries, which would not happen unless the ENPs were already in proximity to bacteria. The fact that the community dissimilarities between control and nano-TiO2 treatments were higher in this study versus a previous experiment4 shows that the increased nano-TiO2 concentration used here (Figure S2, Supporting Information) enhanced the dose-dependent impact. Because the higher nanoTiO2 concentration did not affect soil water characteristics,25 the apparent scaling of biological effects between the previous work4 and this study would suggest that the former results4,5 were also because of direct toxicity.

two-way ANOVA). Overall, nano-TiO2 reduced TRF-based community diversity, but the effect changed along the soil water gradient, as reflected by a greater difference between control and nano-TiO2-amended samples with drier soils (Figure 4). As

Figure 4. Effects of nano-TiO2 and soil water characteristics on the number of terminal restriction fragments (TRFs; a and b) and TRFbased community diversity (Shannon index; c and d).

soils dry, TRF-based community richness and the Shannon index increased in controls due to the increased spatial isolation of microhabitats with drier soils, thus decreasing the competition among species.43 Consistent with our control observations, a previous study also showed that bacterial richness and diversity in sandy soils (90% sand or more) increased as water potential decreased (from −1.5 to −5.5 kPa) and soils became drier.44 Although different soils (sandy clay loam soil versus sandy soil) were used, both studies indicated that in the undisturbed environment low soil pore connectivity may contribute to high bacterial diversity. However, we did not observe the diversity variation along soil water gradient in nano-TiO2-amended samples, indicating that nano-TiO2 may inhibit the expected increase in soil bacterial diversity. Our observations of increased effects of nano-TiO2 on soil bacterial community composition and diversity in drier soils could be attributed to the multiplicative combination of direct water stress, reduced substrate supply (from reduced diffusion), and ENP stress. As soil dries and water potential declines, water-covered microhabitats become more disconnected. Normally, the decreased connectivity of microhabitats could increase soil bacterial diversity due to the spatial isolation of microhabitats, thus reducing competition among species.43,44 Alternatively, soil bacterial communities could be more vulnerable due to increased water stress, reduced substrate supply, and enhanced toxin exposure when toxins are bioavailable. Here, in drier soils, ENPs in proximity to soil microbes were increasingly concentrated, thereby enhancing ENP effects on soil bacterial communities. Nano-TiO2 Effects on Soil Bacteria Are Likely Due to Direct Toxicity. A prime study objective was to test whether nano-TiO2 can affect either soil water holding or organic matter

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ASSOCIATED CONTENT

S Supporting Information *

Information includes the effects of nano-TiO2 and isopiestic equilibration on soil OM, total C, total N, and the C/N ratio (Figure S1), comparison of community dissimilarities between previous work4 and this study (Figure S2), and pairwise comparisons of nano-TiO2 and isopiestic equilibration effects on soil bacterial communities using NP-MANOVA (Table S1). This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: 805-893-3195. Fax: 805893-7612. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This material is based upon work supported by the National Science Foundation and the Environmental Protection Agency under Cooperative Agreement Number DBI 0830117. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science E

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trophic transfer from Pseudomonas aeruginosa. Appl. Environ. Microbiol. 2013, 79 (18), 5616−5624. (18) Werlin, R.; Priester, J. H.; Mielke, R. E.; Kramer, S.; Jackson, S.; Stoimenov, P. K.; Stucky, G. D.; Cherr, G. N.; Orias, E.; Holden, P. A. Biomagnification of cadmium selenide quantum dots in a simple experimental microbial food chain. Nat. Nanotechnol. 2011, 6 (1), 65− 71. (19) Guo, L.; Bussche, A. V. D.; Buechner, M.; Yan, A.; Kane, A. B.; Hurt, R. H. Adsorption of essential micronutrients by carbon nanotubes and the implications for nanotoxicity testing. Small 2008, 4 (6), 721−727. (20) Tuller, M.; Or, D. Water films and scaling of soil characteristic curves at low water contents. Water Resour. Res. 2005, 41 (9), W09403. (21) Holden, P. A. How do the microhabitats framed by soil structure impact soil bacteria and the processes that they regulate? In The Architecture and Biology of Soils: Life in Inner Space; Ritz, K., Young, I., Eds.; CABI: Oxfordshire, 2011; pp 118−148. (22) Vos, M.; Wolf, A. B.; Jennings, S. J.; Kowalchuk, G. A. Microscale determinants of bacterial diversity in soil. FEMS Microbiol. Rev. 2013, 37 (6), 936−954. (23) Robichaud, C. O.; Uyar, A. E.; Darby, M. R.; Zucker, L. G.; Wiesner, M. R. Estimates of upper bounds and trends in nano-TiO2 production as a basis for exposure assessment. Environ. Sci. Technol. 2009, 43 (12), 4227−4233. (24) Xiang, S.-R.; Doyle, A.; Holden, P. A.; Schimel, J. P. Drying and rewetting effects on C and N mineralization and microbial activity in surface and subsurface California grassland soils. Soil Biol. Biochem. 2008, 40 (9), 2281−2289. (25) Priester, J. H.; Ge, Y.; Chang, V.; Stoimenov, P. K.; Schimel, J. P.; Stucky, G. D.; Holden, P. A. Assessing interactions of hydrophilic nanoscale TiO2 with soil water. J. Nanopart. Res. 2013, 15 (9), 1899 DOI: 10.1007/s11051-013-1899-4. (26) Keller, A. A.; Wang, H.; Zhou, D.; Lenihan, H. S.; Cherr, G.; Cardinale, B. J.; Miller, R.; Ji, Z. Stability and aggregation of metal oxide nanoparticles in natural aqueous matrices. Environ. Sci. Technol. 2010, 44 (6), 1962−1967. (27) Gardner, W. H. Water Content. In Methods of Soil Analysis. Part 1. Physical and Mineralogical Methods; Klute, A., Ed.; Soil Science Society of America: Madison, WI, 1986; pp 493−541. (28) Nelson, D. W.; Sommers, L. E. Total Carbon, Organic Carbon, And Organic Matter. In Methods of Soil Analysis. Part 3. Chemical Methods; Sparks, D. L., Ed.; Soil Science Society of America: Madison, WI, 1996; pp 961−1010. (29) Lawrence, C. R.; Neff, J. C.; Schimel, J. P. Does adding microbial mechanisms of decomposition improve soil organic matter models? A comparison of four models using data from a pulsed rewetting experiment. Soil Biol. Biochem. 2009, 41 (9), 1923−1934. (30) Cao, Y.; Green, P. G.; Holden, P. A. Microbial community composition and denitrifying enzyme activities in salt marsh sediments. Appl. Environ. Microbiol. 2008, 74 (24), 7585−7595. (31) Rees, G. N.; Baldwin, D. S.; Watson, G. O.; Perryman, S.; Nielsen, D. L. Ordination and significance testing of microbial community composition derived from terminal restriction fragment length polymorphisms: application of multivariate statistics. Antonie Van Leeuwenhoek 2004, 86 (4), 339−347. (32) Fierer, N.; Jackson, R. B. The diversity and biogeography of soil bacterial communities. Proc. Natl. Acad. Sci. U.S.A. 2006, 103 (3), 626−631. (33) Lueders, T.; Friedrich, M. W. Evaluation of PCR amplification bias by terminal restriction fragment length polymorphism analysis of small-subunit rRNA and mcrA genes by using defined template mixtures of methanogenic pure cultures and soil DNA extracts. Appl. Environ. Microbiol. 2003, 69 (1), 320−326. (34) Lepš, J.; Šmilauer, P. Multivariate Analysis of Ecological Data Using CANOCO; Cambridge University Press: New York, 2003. (35) Ramette, A. Multivariate analyses in microbial ecology. FEMS Microbiol. Ecol. 2007, 62 (2), 142−160.

Foundation or the Environmental Protection Agency. This work has not been subjected to EPA review and no official endorsement should be inferred.

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