Multiple Fluorescence Labeling and Two Dimensional FTIR–13C

ARTICLE pubs.acs.org/est

Multiple Fluorescence Labeling and Two Dimensional FTIR
13C NMR Heterospectral Correlation Spectroscopy to Characterize Extracellular Polymeric Substances in Biofilms Produced during Composting Guang-Hui Yu,‡,† Zhu Tang,‡,† Yang-Chun Xu,† and Qi-Rong Shen*,† †

Jiangsu Key Lab for Organic Solid Waste Utilization, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, People's Republic of China

bS Supporting Information ABSTRACT: Knowledge on the structure and function of extracellular polymeric substances (EPS) in biofilms is essential for understanding biodegradation processes. Herein, a novel method based on multiple fluorescence labeling and two-dimensional (2D) FTIR
13C NMR heterospectral correlation spectroscopy was developed to gain insight on the composition, architecture, and function of EPS in biofilms during composting. Compared to other environmental biofilms, biofilms in the thermophilic (>55 °C) and cooling (mature) stage of composting have distinct characteristics. The results of multiple fluorescence labeling demonstrated that biofilms were distributed in clusters during the thermophilic stage (day 14), and dead cells were detected. In the mature stage (day 26), the biofilm formed a continuous layer with a thickness of approximately 20
100 μm around the compost, and recolonization of cells at the surface of the compost was easily observed. Through 2D FTIR
13C NMR correlation heterospectral spectroscopy, the following trend in the ease of the degradation of organic compounds was observed: heteropolysaccharides > cellulose > amide I in proteins. And proteins and cellulose showed significantly more degradation than heteropolysaccharides. In summary, the combination of multiple fluorescence labeling and 2D correlation spectroscopy is a promising approach for the characterization of EPS in biofilms.

’ INTRODUCTION Biofilms are well-organized communities of microorganisms embedded in a matrix of extracellular polymeric substances (EPS).1
4 The composition of EPS is complex and is dependent on the bacterial species and the growth conditions. However, the main constituents of EPS are proteins, polysaccharides, cellulose, and lipids.1,3
5 In many bioprocesses, the growth of biofilm affects the degradation and conversion of organic compounds.6 Unfortunately, a complete biochemical profile of biofilms is difficult to obtain.5 Therefore, the structure and function of biofilms must be elucidated to obtain a deeper understanding of bioprocesses. Currently, one of the best approaches for the investigation of biofilms in situ is the use of fluorescently labeled lectins.5,7 Many investigators have shown that multiple fluorescence labeling and confocal laser scanning microscopy (CLSM) can be combined to obtain a powerful tool for studying the composition, architecture, and function of biofilm constituents at the microscale.3,4,6
10 Nevertheless, the identification and quantification of specific biofilm constituents is limited by the availability of fluorescently labeled probes.11 CLSM and various methods based on chemical structural analysis, such as Fourier transform infrared (FTIR) and nuclear magnetic resonance (NMR) spectroscopy, can be combined to provide a comprehensive understanding of biofilm development. In previous studies, changes in the structure of biofilm r 2011 American Chemical Society

constituents have been detected via traditional FTIR12
14 or NMR11,14,15 spectroscopy. However, the individual spectral features of FTIR or NMR often overlap because of the extreme heterogeneity of biofilm constituents.16 Two-dimensional (2D) correlation spectroscopy17 can be used to resolve the overlapped peaks problems of traditional FTIR or NMR spectroscopy. By distributing spectral intensity trends within a data set collected as a function of the perturbation sequence (e.g., time, temperature, pressure) over a second dimension, one can get 2D correlation spectroscopy. The main advantages of 2D correlation spectra are as follows: (i) simplification of complex spectra consisting of many overlapped peaks, and enhancement of spectral resolution by spreading peaks over the second dimension; (ii) establishment of unambiguous assignments through correlation of bands; (iii) probing the specific sequencing of spectral intensity changes through asynchronous analysis; (iv) so-called heterospectral correlation, i.e., the investigation of correlation among bands in two different types of spectroscopy; and (v) truly universal applicability of the technique, which is not limited to any type of spectroscopy, or even any form of analytical technique (e.g., chromatography, microscopy, etc).18,19 Received: April 30, 2011 Accepted: September 13, 2011 Revised: August 16, 2011 Published: September 13, 2011 9224

dx.doi.org/10.1021/es201483f | Environ. Sci. Technol. 2011, 45, 9224–9231

Environmental Science & Technology Although the second derivative and peak fitting analysis would also be used to solve the peak overlapping problem and enhance spectral resolution,14,20 both of them could not be applied to probe the specific sequencing of spectral intensity changes and investigate the heterospectral correlation. However, information on the distribution and architecture of biofilms cannot be obtained using this method. To our knowledge, 2D correlation spectroscopy has not previously been applied to investigate the function of biofilms in a bioprocess. Composting is a cheap, efficient, and sustainable treatment for solid organic materials.21
23 Until now, composting research has mainly focused on optimization of process parameters, degradtion of organic matter, and assessment of maturity.21
25 Few studies have been explored in the structure and function of EPS in biofilms of compost, which is essential for understanding biodegradation processes. Thus, the objectives of the present study were to combine multiple fluorescence labeling and 2D correlation spectroscopy to characterize the composition, architecture and function of biofilms. For this purpose, two piles in a full-scale compost facility were constructed and biofilms were allowed to grow. Compared to other environmental biofilms, those present in compost are expected to have distinct characteristics because of the presence of thermophilic and cooling (mature) stages.

’ MATERIALS AND METHODS Composting Process and Biofilm Sample Collection. Two windows with dimensions of 13  1  1.5 m (length  height  width) were constructed from a mixture of swine manure and wheat straw. The moisture content, pH, water extractable organic carbon (WSC), and water extractable total nitrogen (WSN) content of the feedstock in the two piles were 66.8 ( 0.1%, 8.0 ( 0.1, 13.6 ( 0.3 mg g
1, and 2.0 ( 0.1 mg g
1, respectively. Composting was performed under aerobic conditions for 26 days, and the piles were turned when a temperature of 60 °C was attained. During the composting process, 2 kg of representative material was collected on days 0, 2, 6, 10, 14, 18, 22, and 26 of composting and was then divided into two subsamples. The detailed description of sampling could be seen in Tang et al.24 Multiple fluorescent labeling and CLSM were conducted on one subsample of compost, and biofilm was extracted from the other subsample to determine its chemical structure and composition of the biofilm. Briefly, the biofilm was separated from the compost by shaking the samples in deionized water (solid to water ratio of 1:10 w/v) for 24 h on a horizontal shaker at room temperature. The separated biofilm from the fresh compost was filtered through a 0.45-μm polytetrafluoroethylene (PTFE) filter in dead-end membrane filtration tests controlling 30 cmHg vacuum before being freeze-dried at
50 °C for 48 h prior to performing a FTIR and NMR spectral analysis. Multiple Fluorescence Labeling and CLSM Observation. The hydrated compost samples were labeled with fluorescent stains possessing different excitation and emission spectra, and the distribution patterns of proteins, α-polysaccharides, cellulose, total cells, and dead cells were simultaneously visualized according to the method of Chen et al.8 In brief, fluoresceinisothiocyanate (FITC), concanavalin A (Con A), calcofluor white (CW), STYO 63, and SYTOX blue identify proteins, α-polysaccharides, cellulose, total cells, and dead cells, respectively. Specifically, SYTO 63 (20 μM, 100 μL) was added to the

ARTICLE

sample, and the resulting mixture was placed on a shaker table for 30 min. Subsequently, 0.1 mol of NaHCO3 buffer (100 μL) was added to maintain a pH of 9. A solution of FITC (10 g/L, 10 μL) was added, and the mixture was stirred for 1 h. Next, a solution of Con A (250 mg/L, 100 μL) was added to the sample for 30 min, followed by CW (300 mg/L, 100 μL) for 30 min. After each stage of the labeling process, the sample was washed twice with phosphate buffered saline (PBS) solution to remove the extra probe. Finally, a solution of SYTOX blue (2.5 μM, 100 μL) was incubated with the sample for 10 min. The labeled samples were embedded for cryosectioning and were then frozen at
20 °C. Subsequently, 30-μm sections were cut on a cryomicrotome (Cyrotome E, Thermo Shandon Limited, U.K.) and were mounted onto gelatin-coated (0.1% gelatin and 0.01% chromium potassium sulfate) microscopic slides for CLSM (Leica TCS SP2 confocal spectral microscope imaging system, Germany) observation. Four slides were made for each sample. In order to ensure the integrity of each slide, it was important to keep bubbles out of the samples when the labeled samples were embedded for cryosectioning. The samples were imaged using a  20 objective. Detailed information about the sample preparation for the CLSM slides is shown as Figure S1 of the Supporting Information, SI. Three-dimensional reconstructions were obtained with Leica confocal software, and movie files generated from the image stack were saved as uncompressed AVI files. Morphological parameters of the CLSM image were determined using Image J software (NIH, Bethesda, MD, U.S.A.). Analysis of FTIR and Solid-State 13C NMR Spectroscopy. Samples were prepared as a mixture of 1 mg of freeze-dried sample and 100 mg of potassium bromide (KBr, IR grade) and then ground and homogenized to reduce light scatter.26 A subsample was then compressed between two clean, polished iron anvils twice in a hydraulic press at 20 000 psi to form a KBr window. The FTIR spectra were obtained by collecting 200 scans with a Nicolet 370 FTIR spectrometer. Solid-state 13C
CPMAS-NMR spectroscopy was conducted on a Bruker AV-400, equipped with a 4-mm wide-bore MAS probe. NMR spectra were obtained by applying the following parameters: rotor spin rate of 13 000 Hz, 1 s recycle time, 1 ms contact time, 20 ms acquisition time, and 4000 scans. Samples were packed in 4-mm zirconia rotors with Kel-F caps. The pulse sequence was applied with a 1H ramp to account for nonhomogeneity of the Hartmann
Hahn condition at high spin rotor rates. Structural carbons determined include the following group shifts: 0
50 ppm (alkyl), 50
112 ppm (alcohol, amine, carbohydrate, ether, methoxyl and acetal), 110
145 ppm (aromatic), 145
163 ppm (phenolic), 163
215 ppm (carboxyl and carbonyl). Chemical shifts were calibrated with adamantine. Analysis of 2D Correlation Spectroscopy. The 2D correlation spectra were produced according to the method of Noda and Ozaki.18 In this study, the composting time was applied as an external perturbation, and a set of time-dependent FTIR or NMR spectra was obtained. Let us consider analytical spectrum I(x, t). The variable x is the index variable representing the FTIR or NMR spectra induced by the perturbation variable t. We intentionally use x instead of the general notation used in conventional 2D correlation equations based on spectral index v. Analytical spectrum I(x, t) at m evenly spaced points in t (between Tmin and Tmax) can be represented as follows: Ij ðxÞ ¼ Iðx, tj Þ, j ¼ 1, 2, 3 3 3 , m 9225

ð1Þ

dx.doi.org/10.1021/es201483f |Environ. Sci. Technol. 2011, 45, 9224–9231

Environmental Science & Technology

ARTICLE

Figure 1. Performance of the composting process.

A set of dynamic spectra is given by the following: ~I ðx, tÞ ¼ Iðx, tj Þ
̅ lðxÞ

ð2Þ

where ̅ l(x) denotes the reference spectrum, which is typically the average spectrum and is expressed as ̅ l(x) = 1/m∑m j = 1I(x, tj). The synchronous correlation intensity can be directly calculated from the following dynamic spectra: ϕðx1 , x2 Þ ¼

1 m ~I j ðx1 Þ~I j ðx2 Þ m
1 j¼1

∑

ð3Þ

Asynchronous correlation can be obtained by the following: Lðx1 , x2 Þ ¼

m 1 m ~I j ðx1 Þ Njk~I j ðx2 Þ m
1 j¼1 k¼1

∑

∑

ð4Þ

The term Njk corresponds to the jth column and the kth raw element of the discrete Hilbert
Noda transformation matrix, which is defined as follows: 8 > 0 < if j ¼ k 1 ð5Þ Njk ¼ > : πðk
jÞ otherwise The intensity of a synchronous correlation spectrum (L(x1, x2)) represents simultaneous changes in two spectral intensities measured at x1 and x2 during the interval between Tmin and Tmax. In contrast, an asynchronous correlation spectrum (j(x1, x2)) includes out-of-phase or sequential changes in spectral intensities measured at x1 and x2.

Figure 2. CLSM images of biofilms in pile 1 after 14 (A) and 26 (B) days of cultivation. The images were obtained with a 20 objective lens: (a) proteins (FITC), green; (b) α-polysaccharides (Con A), light blue; (c) cellulose (CW), blue; (d) total cells (SYTO 63), red; (e) dead cells (SYTO blue), violet; (f) merged image of (a)-(e). Bar = 100 μm.

Prior to 2D analysis, the FTIR or NMR spectra were normalized by summing the absorbance from 4000 to 400 cm
1 or 0
200 ppm, respectively, and multiplying by 1000. Subsequently, normalized FTIR or NMR spectra were analyzed using principal component analysis (PCA) to reduce the level of noise.27 Finally, 2D correlation spectroscopy was produced using 2Dshige software (Kwansei-Gakuin University, Japan).

’ RESULTS Performance of the Compost. The temperature, moisture content, and pH at various stages of the composting process are shown in Figure 1. Both of the piles attained a plateau value of 65 °C at the second day after composting, indicating that the piles rapidly reached the thermophilic phase. The temperature decreased to approximately 50 °C on the 18th day and then remained constant at approximately 60 °C. The moisture content abruptly declined from 70% on the first day to 30% on the 16th day. Evolution of temperature, moisture content, and fluorescence excitation
emission matrix contours of dissolved organic matter (Figure S2 of the SI) indicated that the compost was mature after 18 days, which is consistent with the results of our previous investigations.22
24 The pH of the piles climbed rapidly from 8.2 on the first day to 8.6 on the eighth day and remained constant over time. During composting, the pH of both 9226

dx.doi.org/10.1021/es201483f |Environ. Sci. Technol. 2011, 45, 9224–9231

Environmental Science & Technology piles ranged from 8.0 to 8.6, evidencing satisfactory microbial activity.25 The aforementioned results suggested that the characteristics of the piles were typical of those observed during composting. Moreover, the findings of the present study were consistent with those obtained from previous investigations.24,28,29 Architecture and Structure of Biofilms Observed by Multiple Fluorescence Labeling Combined with CLSM. Compared to biofilms observed during the cooling (mature) stage, biofilms in the thermophilic stage are expected to be distinct. Therefore, CLSM images of compost samples were obtained during both stages. For brevity, the CLSM images of pile 2 are provided in Figure S3 of the SI. Figure 2 displays the CLSM images of compost samples from pile 1 during the thermophilic (14th d) and mature stages (26th d), respectively. During the thermophilic stage, pig manure and wheat straw were visually apparent, with the former surrounding the latter. Bright images of the composts revealed that pig manure and wheat straw were present in the compost (Figure S4 of the SI). Proteins (FITC) were predominant in pig manure, whereas cellulose (CW) and αpolysaccharides (Con A) formed a continuous layer on the wheat straw. Total cells (SYTO 63) were primarily detected in wheat straw, while dead cells (SYTOX blue) were nearly ubiquitous in both pig manure and wheat straw. Three-dimensional reconstructions of the composts on the 14th day clearly demonstrated that biofilms in the thermophilic stage were highly dispersed throughout the material and were aggregated into clusters located along the outer of the compost (the movie documents generated from the image stack are provided in the Supporting Information). In addition, the wheat straw displayed the characteristics of lignocellulose, which suggested that most of the wheat straw was not completely degraded. During the mature stage, most of the pig manure was degraded, and only wheat straw was observed in the CLSM images. The fluorescence intensity of proteins, cellulose, and α-polysaccharides in the wheat straw during the mature stage was markedly lower that of the thermophilic stage. Moreover, the structure of wheat straw was loose, indicating that most of the wheat straw was degraded. Compared to the thermophilic stage, a quantity of cells in biofilm was observed during the mature stage. The total cell count in the mature stage was markedly greater than that of the thermophilic stage (14th d). Most of the total cells were distributed within the biofilm surrounding the wheat straw. Alternatively, dead cells were primarily observed in the interior of the wheat straw. These results revealed that cell recolonization occurs during the mature stage of composting. When composts were applied to soil, recolonized cells play an important role in the biological control of plant disease.31 In summary, multicolor fluorescence labeling provides information on the detailed architecture and distribution of biofilms in compost. The architecture and distribution patterns of biofilm constituents are closely related to the degradability of biofilms, which can be observed using 2D heterospectral correlation spectroscopy. Function of Biofilms Investigated by 2D Heterospectral Correlation Spectroscopy. The area-normalized FTIR and NMR spectra of the composts over time were noisy. Because the first two principal components accounted for 96% and 98% of the peaks in the FTIR and NMR spectra, respectively, the PCA noise reduction method was applied to reconstruct less noisy spectra. In the reconstructed spectra, the primary bands were maintained, and the level of noise was reduced (data not shown

ARTICLE

Figure 3. Synchronous and asynchronous 2D FTIR correlation maps generated from the 1800
900 cm
1 region of the spectra and 2D NMR correlation maps of dissolved organic matter in the two piles over time. Red represents positive correlations; a higher color intensity indicates a stronger positive correlation.

for brevity). All of the FTIR and NMR 2D correlation results presented below were generated from reduced-noise spectra. A synchronous spectrum is a symmetric spectrum with respect to a diagonal line. Correlation peaks include autopeak and crosspeak, which appear at both diagonal and off-diagonal positions, respectively. An autopeak represents the overall susceptibility of the corresponding spectral region to change in spectral intensity as an external perturbation is applied to the system. Crosspeaks represent simultaneous or coincidental changes of spectral intensities observed at two different spectral variables. Such a synchronized change, in turn, suggests the possible existence of a coupled or related origin of the spectral intensity variations. An asynchronous spectrum is antisymmetric with respect to the diagonal line, which has no autopeaks and consists exclusively of crosspeaks located at off-diagonal positions. The sign of an asynchronous cross peak can be either 9227

dx.doi.org/10.1021/es201483f |Environ. Sci. Technol. 2011, 45, 9224–9231

Environmental Science & Technology negative or positive. It provides useful information on the sequential order of events observed by the spectroscopic technique along the external variable. The 1800
900 cm
1 region of the 2D FTIR correlation spectra was evaluated because this region of the spectra contains bands corresponding to amides, carboxylic acids, esters, and carbohydrates.32 Time-dependent one-dimensional FTIR spectra during composting of the two piles are shown as Figure S5 of the SI for brevity. The synchronous maps of the biofilms (Figure 3) from the two piles were similar, and three major autopeaks were detected at 1650, 1380, and 1080 cm
1. The greatest change in intensity was observed in the band located at 1650 and 1380 cm
1, followed by the peak at 1080 cm
1. The band at 1650 cm
1 was attributed to amide I in proteinaceous compounds, the band at 1380 cm
1 was assigned to the OH bending vibration of cellulose, and the band at 1080 cm
1 was attributed to the C
O stretching of polysaccharides or polysaccharide-like substances.12,13,32,33 Polysaccharide-like substances are composed of cellulose and hemicellulose. Cellulose is a homopolysaccharide composed of D-glucose units linked to each other via β-1,4-glucosidic bonds; however, hemicellulose is a heteropolysaccharide composed of different sugar units, i.e, mannans, xylans, arabinans, and galactans.34 In this study, polysaccharide-like substances are referred to both homopolysaccharide and heteropolysaccharide, whereas cellulose is assigned to the homopolysaccharide. The above results suggested that proteins and cellulose degraded at a faster rate than polysaccharides during composting. Moreover, three crosspeaks at (1650 and 1380 cm
1), (1650 and 1080 cm
1), and (1380 and 1080 cm
1) were identified. These crosspeaks were positively correlated, suggesting that proteins, cellulose, and polysaccharides varied/degraded concurrently during composting. Compared to the synchronous maps, the asynchronous maps of the biofilms from the two piles displayed distinctive characteristics (Figure 3). In the map of pile 1, three positive crosspeaks were observed at (1690 and 1650 cm
1), (1550 and 1380 cm
1), and (1420 and 1380 cm
1). Moreover, five negative crosspeaks were observed at (1650 and 1550 cm
1), (1650 and 1380 cm
1), (1650 and 1110 cm
1), (1380 and 1110 cm
1), and (1380 and 1250 cm
1). However, in the map of pile 2, three positive crosspeaks were detected at (1650 and 1280 cm
1), (1400 and 1380 cm
1), and (1110 and 1080 cm
1). In addition, four negative crosspeaks were observed at (1650 and 1610 cm
1), (1650 and 1420 cm
1), (1650 and 1110 cm
1), and (1380 and 1110 cm
1) (Figure 3). According to Noda’s rule,18 the following trend in the degradation of peaks was observed during the composting of piles 1 and 2, respectively: 1550, 1420, 1110 cm
1 > 1380 cm
1 > 1650 cm
1 and 1110 cm
1 > 1080, 1420 cm
1 >1650 cm
1 > 1280 cm
1 for piles 1 and 2, respectively. Therefore, organic compounds in piles 1 and 2 were degraded in the following sequence: amide II, heteropolysaccharides > cellulose > amide I and heteropolysaccharides > cellulose > amide I for piles 1 and 2, respectively. In conclusion, cells embedded in the biofilms matrix of compost initially utilize easily degradable heteropolysaccharides. Subsequently, the cells degrade cellulose, followed by proteins. The synchronous map of 2D NMR spectra showed that during composting for the two piles, the greatest degradation of organic compounds was O-alkylated (HCOH) carbons (74 ppm), followed by long chain aliphatic carbons (38 ppm), mirroring the results of 2D FTIR spectra that heteropolysaccharides and

ARTICLE

Figure 4. Synchronous maps obtained via 2D heterospectral correlation analysis of the FTIR and 13C NMR spectra of dissoloved organic matter in the composting piles over time. Red represents positive correlations and blue represents negative correlations; a higher color intensity indicates a stronger positive or negative correlation.

cellulose degradated much more than proteins. Moreover, the asynchronous map of 2D NMR spectra further demonstrated that during composting, long chain aliphatic carbons (38 ppm) degraded prior to O-alkylated (HCOH) carbons (74 ppm). The 2D heterospectral correlation maps were used to examine the covariation between bands in the FTIR and 13C NMR spectra. As shown in Figure 4, the FTIR bands at 1650, 1380, 1080 cm
1 were positively correlated with the NMR band at 38 ppm. In addition, a negative correlation between the three FTIR bands and the NMR band at 74 ppm was observed. Lastly, the FTIR bands at 1650 and 1380 cm
1 were positively correlated with the NMR band at 168 ppm. These results revealed that proteins, cellulose, and heteropolysaccharides in the biofilms consisted of long chain aliphatic carbons rather than O-alkylated (HCOH) carbons. Moreover, proteins and cellulose in the biofilm also contained carboxyl groups, suggesting that O-alkyl carbons were produced during the degradation of long chain aliphatic compounds (i.e., proteins, cellulose, and heteropolysaccharides). These results are supported by those of previous investigations, which showed that the aromatic process performed by microorganisms occurs predominantly in the water-soluble phase.22,24 The fluorescence EEM data (Figure S2 of the SI) also suggested that the extent of aromatic polycondensation conjugated chromophores content and degree of humification increased with an increase in composting time.

’ DISCUSSION Heterogeneity of the Biofilms in Composts. Fluorescence labeling is a valuable tool for assessing the in situ detection of EPS glycoconjugates in undisturbed and fully hydrated and complex environmental biofilms. Although the previous investigations had shown the microscale heterogeneities of bacteria in biofilms,6 few studies are conducted in the compost system. Quantitative 9228

dx.doi.org/10.1021/es201483f |Environ. Sci. Technol. 2011, 45, 9224–9231

Environmental Science & Technology analysis with Image J software clearly demonstrated that the biofilms were approximately 20
100 μm thick (Figure S6 of the SI), suggesting that significant heterogeneity in the biofilm of composts was observed. This result will help to modify the modeling of compost degradation. The individual colonies were observed in the biofilm and penetrated the composts for significant depths. Since the performance of the compost system is closely connected with its characteristic, it is reasonable to suppose that a good biofilm may be developed by adjustment of oxygen and moisture content, which will be beneficial for achieving a good performance of composting. Moreover, the distribution of organic compounds observed by a fluorescence labeling approach could also be applied to explain their degradation patterns. The organic compounds of composts, i.e., proteins, α-polysacchrides, and cellulose, were found to have a distinct distribution pattern, determining that the degradation pattern of them may also be different.1 In this study, during the thermophilic stage, α-polysacchrides had the same distribution pattern with cells, whereas cellulose possessed a similar distribution pattern with cells (Figure 2). However, proteins had a distinct distribution with cells. As a consequence, the heteropolysacchrides and cellulose in compost were degraded prior to proteins (Figure 3). Cells observed during the thermophilic stage were associated with cellulose and α-polysaccharides; thus, these cells were attributed to cellulose- and α-polysaccharides-degrading bacteria rather than protein-degrading bacteria. The results of previous investigations also suggest that the majority of cellulose-degraded bacteria are thermophilic.30 Alternatively, the dead cells were attributable to the poor adaption of mesophilic bacteria to the thermophilic environment. The CLSM observations also revealed that cells were evenly distributed throughout the wheat straw, suggesting that degradation did not occur from the outside. It should be noted that a fluorescence labeling approach depends on the specificity of the selected probes or stains and limits by a lack of understanding of EPS composition and structure.15 Zippel and Neu35 showed that the fluorescence labeling approach is not completely free of uncertainties and the selected probes or stains interact with their target through multiple binding sites increases affinity and specificity, owing to the enormous variety of macromolecules in complex natural microbial biofilms. It has been suggested that determination of “dead cells” by SYTOX blue is questionable. Therefore, investigators should be cautious when they want to apply a fluorescence labeling approach. Degradation of Organic Compounds in Biofilms. Characterizing the chemical and biological changes of organic matter can improve the knowledge of organic matter transformations and maturity assessment during the composting process. In previous investigations, the degradation of organic compounds during composting was often studied by conventional methods. For example, Francou et al. 36 demonstrated that at the thermophilic phase, the hemicellulose fraction varied as cellulose, but with lower contents. Our results also support the codegradation of polysaccharides, cellulose, and proteins during composting by the conventional methods (Figure S7 of the SI), which is consistent with that proteins, cellulose, and heteropolysaccharides varied/degraded concurrently during composting by the synchronous map (Figure 3). Nevertherless, it is difficult to give the sequencing of organic compounds degradation by the conventional methods. Therefore, the findings in this study need to

ARTICLE

be further verified by independent methods in the future investigation. Through 2D FTIR—13C NMR correlation heterospectral spectroscopy, our results for the first time demonstrated that the degradation of organic compounds in biofilm followed the order: heteropolysaccharides > cellulose > amide I in proteins. The degradation sequencing is closely related to the nature of organic compounds. As we all know, cellulose is a semicrystalline polymeric material containing both crystalline and amorphous components, whereas hemicellulose is considered as an amorphous component.34,37 Himmel et al. 37 had shown that crystalline cellulose is resistant to degradation because of the strong interchain hydrogen-bonding network, whereas hemicellulose and amorphous cellulose are readily degradable. M€aki-Arvela et al. 34 also demonstrated that the crystalline structure in cellulose is very stable. Therefore, heteropolysaccharides were degraded prior to cellulose during composting. In this study, the thermophilic phase were attained at the second day for the two piles after composting (Figure 1), in which cellulose—rather than proteins—degraded bacteria should be predominant.30 As a consenquence, proteins were degraded at the last sequencing. However, another investigation (unpublished data) showed that the degradation of organic compounds during composting was related to the distribution of them in materials. Therefore, as for the different materials, the degradation sequencing of organic compounds may be different. Environmental Implications. Although 13C NMR is a powerful approach to investigating functional group variations, it suffers from ambiguities in the structural information it provides. For example, the carbonyl band (CdO) of carboxyl, amide, and aliphatic esters in biofilms all resonate at the same position (around 175 ppm). FTIR can be used to provide an additional view of the functional groups, and can help to resolve the carboxyl, amide, and aliphatic ester contributions to biofilms. Therefore, their complementarity in providing information on the distribution of biofilms functional groups could help to construct a more comprehensive picture of the change in biofilms. The novelty of this study is that we applied, for the first time, two-dimensional correlation spectroscopy to characterize the function of biofilms, which provide many advantages when compared with traditional FTIR or NMR spectroscopy. Knowledge on the composition, architecture, and function of biofilms is essential for understanding biodegradation processes. In the present study, a novel method for the characterization of the composition, architecture, and function of biofilms was developed by combining multiple fluorescence labeling and two-dimensional correlation spectroscopy. Multiple fluorescence labeling supplies structural information on the distribution of biofilm constituents in situ, while two-dimensional correlation spectroscopy provides detailed but locally unresolved information on biofilm constituents. The combination of multiple fluorescence labeling and 2D correlation spectroscopy is a promising approach for the characterization of biofilms. Knowledge on the constituents of biofilm contributes to our understanding of the composting process and provides novel information for engineering applications and scientific research.

’ ASSOCIATED CONTENT

bS

Supporting Information. Detailed descriptions of determination of fluorescence EEM, FTIR, and solid-state 13C NMR spectroscopy; one table listing evolution of Pi,n (%) during

9229

dx.doi.org/10.1021/es201483f |Environ. Sci. Technol. 2011, 45, 9224–9231

Environmental Science & Technology composting achieved from fluorescence regional integrity (FRI) analysis; one figure showing fluorescence EEM contours of composts; two figures showing the CLSM images of biofilms for compost from pile 2 and bright images of composts in pile; one figure showing image analysis results; one figure presenting the degradation of organic matter by the conventional method. This material is available free of charge via the Internet at http:// pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*Phone: +86-25-8439 5212; fax: +86-21-8439 5212; e-mail: [email protected]. Author Contributions ‡

G.H.Y. and Z.T. contributed equally to this work

’ ACKNOWLEDGMENT The work was funded by the National Basic Research Program of China (No. 2011CB100503), the National Natural Science Foundation of China (No. 21007027), Specialized Research Fund for the Doctoral Program of Higher Education (No. 20100097120015), China Postdoctoral Science Foundation (No. 20100481156), the Agricultural Ministry of China (No. 2011-G27 and 201103004), and Key Agricultural Project of Jiangsu Province (SX(2010)220). We would also like to thank three anonymous reviewers for their helpful comments and Dr. David Chadwick from North Wyke Research, U.K. for his careful revision on this manuscript. ’ REFERENCES (1) Yu, G. H.; He, P. J.; Shao, L. M.; Zhu, Y. S. Extracellular proteins, polysaccharides and enzymes impact on sludge aerobic digestion after ultrasonic pretreatment. Water Res. 2008, 42, 1925–1934. (2) Wagner, M.; Ivleva, N. P.; Haisch, C.; Niessner, R. Combined use of confocal laser scanning microscopy (CLSM) and Raman microscopy (RM): Investigations on EPS-matrix. Water Res. 2009, 43, 63–76. (3) Adav, S. S.; Lin, J. C. T.; Yang, Z.; Whiteley, C. G.; Lee, D. J.; Peng, X. F.; Zhang, Z. P. Stereological assessment of extracellular polymeric substances, exo-enzymes, and specific bacterial strains in bioaggregates using fluorescence experiments. Biotechnol. Adv. 2010, 28, 255–280. (4) Dominik, D. M.; Nielsen, J. L.; Nielsen, P. H. Extracellular DNA is abundant and important for microcolony strength in mixed microbial biofilms. Environ. Microbiol. 2010, 13, 710–721. (5) Flemming, H. C.; Neu, T. R.; Wozniak, D. J. The EPS matrix: the “house of biofilm cells. J. Bacteriol. 2007, 189, 7945–7947. (6) Stewart, P. S.; Franklin, M. J. Physiological heterogeneity in biofilms. Nat. Rev. Microbiol. 2008, 6, 199–210. (7) Neu, T. R.; Kuhlicke, U.; Lawrence, J. R. Assessment of fluorochromes for two photon laser scanning microscopy of biofilms. Appl. Environ. Microbiol. 2002, 68, 901–909. (8) Chen, M. Y.; Lee, D. J.; Tay, J. H. Distribution of extracellular polymeric substances in aerobic granules. Appl. Microbiol. Biotechnol. 2007, 73, 1463–1469. (9) Yu, G. H.; Juang, Y. C.; Lee, D. J.; He, P. J.; Shao, L. M. Enhanced aerobic granulation with extracellular polymeric substances (EPS)-free pellets. Bioresour. Technol. 2009, 100, 4611–4615. (10) Yu, G. H.; Lee, D. J.; He, P. J.; Shao, L. M.; Lai, J. Y. Fouling layer with fractionated extracellular polymeric substances of activated sludge. Sep. Sci. Technol. 2010, 45, 993–1002. (11) Garny, K.; Neu, T. R.; Horn, H.; Volke, F.; Manz, B. Combined application of 13C NMR spectroscopy and confocal laser scanning

ARTICLE

microscopy-investigation on biofilm structure and physic-chemical properties. Chem. Eng. Sci. 2010, 65, 4691–4700. (12) Hu, Z. H.; Liu, S. Y.; Yue, Z. B.; Yan, L. F.; Yang, M. T.; Yu, H. Q. Microscale analysis of in vitro anaerobic degradation of lignocellulosic wastes by rumen microorganisms. Environ. Sci. Technol. 2008, 42, 276–281. (13) Cao, B.; Shi, L.; Brown, R. N.; Xiong, Y. J.; Fredrickson, J. K.; Romine, M. F.; Marshall, M. J.; Lipton, M. S.; Beyenal, H. Extracellular polymeric substances from Shewanella sp. HRCR-1 biofilms: Characterization by infrared spectroscopy and proteomics. Environ. Microbiol. 2011, 13, 1018–1031. (14) Yuan, S. J.; Sun, M.; Sheng, G. P.; Li, Y.; Li, W. W.; Yao, R. S.; Yu, H. Q. Identification of key constituents and structure of the extracellular polymeric substances excreted by Bacillus megaterium TF10 for their flocculation capacity. Environ. Sci. Technol. 2011, 45, 1152–1157. (15) Seviour, T.; Lambert, L. K.; Pijuan, M.; Yuan, Z. G. Structural determination of a key exopolysaccharide in mixed culture aerobic sludge granules using NMR spectroscopy. Environ. Sci. Technol. 2010, 44, 8964–8970. (16) Plaza, C.; Senesi, N.; Brunetti, G.; Mondelli, D. Evolution of the fulvic acid fractions during co-composting of olive oil mill wastewater sludge and tree cuttings. Bioresour. Technol. 2007, 98, 1964–1971. (17) Noda, I. Generalized two-dimensional correlation method applicable to infrared, Raman, and other types of spectroscopy. Appl. Spectrosc. 1993, 47, 1329–1336. (18) Noda, I., Ozaki, Y., Eds. Two-Dimensional Correlation Spectroscopy- Applications in Vibrational and Optical Spectroscopy; John Wiley & Sons: England, 2004. (19) Noda, I. Two-dimensional correlation spectroscopy-biannual survey 2007
2009. J. Mol. Struct. 2010, 974, 3–24. (20) Abdulla, H. A.; Minor, E. C.; Dias, R. F.; Hatcher, P. G. Changes in the compound classes of dissolved organic matter along an estuarine transect: A study using FTIR and 13C NMR. Geochim. Cosmochim. Acta 2010, 74, 3815–3838. (21) Gajalakshmi, S.; Abbasi, S. A. Solid waste management by composting: State of the art. Crit. Rev. Environ. Sci. Technol. 2008, 38, 311–400. (22) Yu, G. H.; Luo, Y. H.; Wu, M. J.; Tang, Z.; Liu, D. Y.; Yang, X. M.; Shen, Q. R. PARAFAC modeling of fluorescence excitationemission spectra for rapid assessment of compost maturity. Bioresour. Technol. 2010, 101, 8244–8251. (23) Yu, G. H.; Wu, M. J.; Luo, Y. H.; Yang, X. M.; Ran, W.; Shen, Q. R. Fluorescence excitation-emission spectroscopy with regional integration analysis for assessment of compost maturity. Waste Manage. 2011, 31, 1729–1736. (24) Tang, Z.; Yu, G. H.; Liu, D. Y.; Xu, D. B.; Shen, Q. R. Different analysis techniques for fluorescence excitation-emission matrix spectroscopy to assess compost maturity. Chemosphere 2010, 82, 1202–1208. (25) Bernal, M. P.; Alburquerque, J. A.; Moral, R. Composting of animal manures and chemical criteria for compost maturity assessment: A review. Bioresour. Technol. 2009, 100, 5444–5453. (26) Yu, G. H.; He, P. J.; Shao, L. M.; Lee, D. J. Enzyme activities in activated sludge flocs. Appl. Microbiol. Biotechnol. 2007, 77, 605–612. (27) Jung, Y. M.; Shin, H. S.; Kim, S. B.; Noda, I. New approach to generalized two-dimensional correlation spectroscopy. 1: Combination of principal component analysis and two-dimensional correlation spectroscopy. Appl. Spectrosc. 2002, 56, 1562–1567. (28) Wang, C. M.; Watson, P.; Michel, M. E.; Hoitink, H. A. J. Assessment of the reliability of the solvitaw maturity test for composted manures. Compost Sci. Util. 2003, 11, 125–143. (29) Bustamante, M. A.; Paredes, C.; Marhuenda-Egea, F. C.; PerezEspinosa, A.; Bernal, M. P.; Moral, R. Co-composting of distillery wastes with animal manures: carbon and nitrogen transformations in the evaluation of compost stability. Chemosphere 2008, 72, 551–557. (30) Bergquist, P. L.; Gibbs, M. D.; Morris, D. D.; Te’o, V. S. J.; Saul, D. J.; Morgan, H. W. Molecular diversity of thermophilic cellulolytic and hemicellulolytic bacteria. FEMS Microb. Ecol. 1999, 28, 99–110. 9230

dx.doi.org/10.1021/es201483f |Environ. Sci. Technol. 2011, 45, 9224–9231

Environmental Science & Technology

ARTICLE

(31) Hoitink, H. A. J.; Stone, A. G.; Han, D. Y. Suppression of plant diseases by composts. HortScience 1997, 32, 184–187. (32) Abdulla, H. A. N.; Minor, E. C.; Hatcher, P. G. Using twodimensional correlations of 13C NMR and FTIR to investigate changes in the chemical composition of dissolved organic matter along an estuarine transect. Environ. Sci. Technol. 2010, 44, 8044–8049. (33) Tandy, S.; Healey, J. R.; Nason, M. A.; Williamson, J. C.; Jones, D. L.; Thain, S. C. FT-IR as an alternative method for measuring chemical properties during composting. Bioresour. Technol. 2010, 101, 5431–5436. (34) M€aki-Arvela, P.; Salmi, T.; Holmbom, B.; Willf€or, S.; Murzin, D. Y. Synthesis of sugars by hydrolysis of hemicelluloses—A review. Chem. Rev. 2011, DOI: 10.1021/cr2000042. (35) Zippel, B.; Neu, T. R. Characterization of glycoconjugates of extracellular polymeric substances in tufa-associated biofilms by using fluorescence lectin-binding analysis. Appl. Environ. Microbiol. 2011, 77, 505–516. (36) Francou, C.; Lineres, M.; Derenne, S.; Le Villio-Poitrenaud, M.; Houot, S. Influence of green waste, biowaste and paper-cardboard initial ratios on organic matter transformations during composting. Bioresour. Technol. 2008, 99, 8926–8934. (37) Himmel, M. E.; Ding, S. Y.; Johnson, D. K.; Adney, W. S.; Nimlos, M. R.; Brady, J. W.; Foust, T. D. Biomass recalcitrance: Engineering plants and enzymes for biofuels production. Science 2007, 315, 804–807.

9231

dx.doi.org/10.1021/es201483f |Environ. Sci. Technol. 2011, 45, 9224–9231