Toward Quantitative Understanding of the ... - ACS Publications

Subscriber access provided by HKU Libraries

Article

Towards Quantitative Understanding of the Bioavailability of Dissolved Organic Matter in Freshwater Lake during Cyanobacteria Blooming Leilei Bai, Chicheng Cao, Changhui Wang, Huacheng Xu, Hui Zhang, Vera I Slaveykova, and He-Long Jiang Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 03 May 2017 Downloaded from http://pubs.acs.org on May 3, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 31

Environmental Science & Technology

1

Towards Quantitative Understanding of the Bioavailability of

2

Dissolved Organic Matter in Freshwater Lake during Cyanobacteria

3

Blooming

4

Leilei Bai†,‡, Chicheng Cao§, Changhui Wang†, Huacheng Xu†, Hui Zhang§, Vera I

5

Slaveykovaǁ, Helong Jiang*,†

6 7

†

8

Limnology, Chinese Academy of Sciences, Nanjing 210008, China

9

‡

10

§

11

Public Health, Southeast University, Nanjing, 210009, China

12

ǁ

13

of Geneva, Geneva, Switzerland.

State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and

Graduate University of Chinese Academy of Sciences, China Key Laboratory of Environmental Medicine Engineering of Ministry of Education, School of

Department F.-A. Forel for Environmental and Aquatic Sciences, Faculty of Sciences, University

14 15 16 17 18

*Corresponding author: Helong Jiang. Mailing address: Nanjing Institute of Geography and

19

Limnology, Chinese Academy of Sciences, China. Phone/Fax: +86 25 8688 2208. E-mail:

20

[email protected].

21

1

ACS Paragon Plus Environment


Page 2 of 31

22

ABSTRACT

23

Occurrence of cyanobacterial harmful algal blooms (CyanoHAB) can induce considerable

24

patchiness in the concentration and bioavailability of dissolved organic matter (DOM), which

25

could influence biogeochemical processes and fuel microbial metabolism. In the present study, a

26

laboratory 4-stage plug-flow bioreactor was used to successfully separate the CyanoHAB-derived

27

DOM isolated from the eutrophic Lake Taihu (China) into continuum classes of bioavailable

28

compounds. A combination of new state-of-the-art tools borrowed from analytical chemistry and

29

microbial ecology were used to characterize quantitatively the temporary evolution of DOM and

30

to get deeper insights into its bioavailability. The results showed a total 79% dissolved organic

31

carbon loss over time accompanied by depletion of protein-like fluorescent components,

32

especially the relatively hydrophilic ones. However, hydrophilic humic-like fluorescent

33

components exhibited bioresistant behavior. Consistently, ultrahigh resolution mass spectrometry

34

(FTICR-MS) revealed that smaller, less aromatic, more oxygenated and nitrogen-rich molecules

35

were preferentially consumed by microorganisms with the production of lipid-like species,

36

whereas recalcitrant molecules were primarily composed of carboxylic-rich alicyclic compounds.

37

Moreover, the bioavailability of DOM was negatively correlated with microbial community

38

diversity in the bioreactor. Results from this study provide deeper insights into the fate of DOM

39

and relevant biogeochemical processes in eutrophic lakes.

40

2


Page 3 of 31


41 42

TOC/Abstract graphic

43

3



44

Page 4 of 31

INTRODUCTION

45

The global incidence and severity of cyanobacterial harmful algal blooms (CyanoHAB) in

46

freshwater ecosystems have expanded during past decades due to anthropogenically-induced

47

eutrophication and climate warming.1,

48

cyanobacteria release high amounts of dissolved organic matter (DOM) into aquatic ecosystems.3

49

The DOM is composed of a wide spectrum of chemical compounds.4 Closely coupled associations

50

between primary productivity and bacteria growth/activity have led to the understanding that

51

phytoplankton-derived DOM is relatively bioavailable,5 but algal exudates derived from different

52

phytoplankton species may degrade at different rates.

2

The population breakouts of a few dominating

53

The bioavailable DOM is currently described as a continuum with labile, semi-labile and

54

refractory pools that are characterized by consecutive turnover-lives from minutes to multiple

55

millennia.6 These fractions can create a distinct sequence of ecological niches, influencing the

56

biogeochemical reactions related to bacterial succession and to carbon and energy cycles of

57

aquatic ecosystems.5 For example, labile DOM can boost short- and long-term bacterial activity,

58

enhance presumed trophic transfer, and support organic matter processing.7 Decomposition of

59

excessive DOM and subsequent dissolved oxygen depletion are considered as a possible reason

60

for the formation of black water in shallow freshwater lakes.8 Also, DOM turnover induces shifts

61

in transcription, metabolic pathway expression, and microbial growth that appear to be associated

62

with the attenuation of organic contaminants.9, 10

63

Cyanobacterial harmful algal blooms-derived dissolved organic matter (CyanoHAB-DOM)

64

also consists of dissolved organic nitrogen (DON) with varying reactivity and bioavailability.11

65

CyanoHAB-DOM can enhance DON loading into eutrophic lakes. Increased DON is of major 4


Page 5 of 31


66

concern for those who monitor water quality and aquatic ecosystem functioning, as bioavailable

67

DON can serve as a potential source of reactive nitrogen to the various harmful algal species,12

68

and biodegradable DON may be precursors for carcinogenic disinfectant byproducts.13 These

69

environmental and biogeochemical processes underscore the genuine requirement of deeper

70

insights into the bioavailability of CyanoHAB-DOM.

71

Bioreactivity of DOM in aquatic ecosystems is governed by the inherent quality of DOM

72

molecules and is closely related to its structure, composition and molecular characteristics.14-16 For

73

instance, amino acid-like fluorescent DOM (FDOM) was not found to be a causal factor in

74

biodegradation,16 and molecular weight or hydrophobicity of DOM fractions also contributed to

75

the variability in bacterial metabolism.15, 17, 18 Molecular analysis of terrigenous DOM revealed

76

that the less oxygenated and saturated nitrogen-bearing molecules were more biodegradable.19

77

DOM bioavailability is also dependent on bacterial communities that are capable of

78

biodegradation.20 However, no studies to date have investigated the linkage of CyanoHAB-DOM

79

composition evolution in biodegradation with an involved microbial community. With regard to

80

the molecular characterization, ultrahigh resolution electrospray ionization Fourier transform ion

81

cyclotron resonance mass spectrometry (ESI-FTICR-MS) has become a prevailing method for the

82

chemical composition characterization of DOM.19, 21-23 The superior capabilities of FTICR-MS

83

typically allow detection of thousands of individual peaks that are mainly in the region of 200–800

84

m/z and singly charged.23 The resolved peaks can further be assigned unique molecular formulas

85

to differentiate the elemental composition of DOM compounds, even though the compounds with

86

different structures may have the same molecular formulas. Additionally, the combination of

87

high-performance liquid chromatography and multi-excitation/emission fluorescence scan 5



Page 6 of 31

88

(HPLC-EEM) directly relates DOM fluorescence spectra to hydrophobicity and reveals the

89

changes of hydrophobicity-distinguished components in degradation.18, 24

90

Bioassays using indigenous microbial incubations have been extensively conducted to track

91

changes in decomposition of DOM over time.22 However, this method is largely limited by the

92

length of time required (from weeks to months) for colonization and determination. Instead, a

93

plug-flow biofilm reactor was proposed as a rapid approach to identify DOM bioavailability.25

94

This colonized bioreactor utilizes successive microorganisms to produce longitudinal gradients of

95

diminishing DOM quantity and quality as it passed through reactors varying in size and, thus,

96

hydraulic retention times (HRTs). However, operators of the single-stage bioreactor may find it

97

inconvenient to analyze and compare bacterial communities that are exposed to decreasingly

98

bioavailable DOM fractions due to the unspecific biodegradation behavior inside bioreactor.

99

Based on the previous work,25, 26 a group of tandem plug-flow bioreactors with increasing HRTs

100

were developed in this study. DOM pools with a gradient of declining bioavailability can be

101

generalized through collecting the effluent of each reactor. Importantly, this method offers an

102

adequate opportunity to analyze the microbial community structure shift in response to a

103

succession of different levels in DOM bioavailability, as specific bacterial groups for degradation

104

of various bioavailable DOM can be enriched individually.

105

The present study focused on the CyanoHAB-DOM sampled from the eutrophic Lake Taihu

106

(China), which is of particular interest for studies due to the recurrent mucilaginous CyanoHAB

107

with Microcystis aeruginosa species.3, 27 The specific objectives were 2-fold: (i) to elucidate the

108

time-evolution of CyanoHAB-DOM bioavailability in terms of spectral signatures as well as

109

hydrophobicity-distinguished and molecular compositions; and (ii) to understand how 6


Page 7 of 31


110

CyanoHAB-DOM bioavailability influences the microbial community structure. Results of this

111

work will provide deeper insights towards identifying, tracking and resolving the fate of DOM and

112

its related biogeochemical behaviors in freshwater ecosystems dominated by CyanoHAB.

113 114

MATERIAL AND METHODS

115

Samples Collection and Bioreactor Operation.

116

Surface water samples containing mucilaginous cyanobacterial aggregations were collected

117

with glass bottles (precombusted at 450 ºC for 4 h) at Meiliang Bay, Taihu in July 2015

118

(Supporting Information (SI) Figure S1). Water samples were collected in 5 L amber glass bottles

119

(acid-washed and precombusted) and transported to the lab on ice within 4 h. On return to the lab,

120

samples were immediately filtered through precombusted 2.7 µm (Whatman GF/D) and 0.7 µm

121

(Whatman GF/F) glass fiber membranes to remove particles and algal aggregates. Then the

122

filtrates were stored at – 20 ºC before use.

123

The 4-stage plug-flow bioreactor consisted of 4 tandem darkened glass reactors with different

124

volumes (SI Figure S2).25 Each of the reactors was filled with precombusted porous glass beads as

125

the biological carriers. Theoretical HRTs of the 4 reactors were adjusted to 4, 20, 24 and 48 h,

126

respectively, by peristaltic pumps. An air pump was used to supply sufficient sterilized air (filtered

127

by 0.22 µm polyether sulfone filters) into each reactor for the growth of microorganisms. After 8

128

months of incubation with lake water, the bioreactor exhibited a stable and effective removal for

129

DOM (SI Figure S3). Then, the stored filtrates were pumped as influents and triplicate samples

130

were collected from the effluent of each reactor (Eff-1, Eff-2, Eff-3 and Eff-4, respectively) for

131

DOM analysis. Detailed set-up and operation procedures are provided in the SI. 7



Page 8 of 31

132

Concentrations of biodegradable DOM were expressed as the difference between dissolved

133

organic carbon (DOC) concentrations in the influent and 4 effluent samples. Attenuation of DOC

134

with increasing HRTs was fitted to a 3-pool G model, which consisted of the sum of exponential

135

decay terms for 3 bioavailability pools: labile, semi-labile and recalcitrant pool.28

136

Bulk and Spectral Analysis.

137

DOC was determined as non-purgeable organic carbon using a total organic carbon analyzer

138

(TOC-Vcph, Shimazu). The absorbance and fluorescent DOM characteristic parameters, including

139

a254, specific UV absorbance (SUVA254), spectral slope ratio (SR), 1st and 2nd derivative absorption

140

spectra, and humification index (HIX) were determined with detailed methods described

141

elsewhere.7,

142

modeling using the drEEMs toolbox (ver. 0.2.0) for MATLAB (R2012a).30 The HPLC-EEM

143

analysis was performed to obtain insights into the hydrophobicity-distinguished components

144

following recently developed methodology (SI Tables S1 and S2).24 Detailed measurement,

145

calculation and modelling of the spectral properties are described in the SI.

146

Molecular Characterization of DOM.

29

FDOM components were identified by a parallel factor analysis (PARAFAC)

147

DOM in the influent and 4 effluent samples were extracted with solid phase extraction

148

cartridges for molecular characterization using the Bruker Daltonics 7 Tesla Apex Qe FTICR-MS.3

149

A specific description of the extraction procedure, measurement and assignment of DOM

150

molecules can be found in the SI.

151

Microbial Community Analysis.

152

Microbial communities attached on the glass carriers in each reactor of the bioreactor were

153

detached and concentrated after sonication and filtration. DNA was extracted in duplicate for each 8


Page 9 of 31


154

sample using a PowerSoil kit (MO BIO Laboratories, Carlsbad, CA). The DNA solutions were

155

pooled to reduce sample variability. 16S rRNA was partially amplified from the DNA extracts

156

using a nearly universal bacterial primer set and processed by the Meiji Biotechnology Company

157

(Shanghai, China) for high-throughput DNA sequencing with the Illumina MiSeq System

158

(Illumina, San Diego, USA). Detailed procedures of DNA extraction, PCR amplification,

159

high-throughput sequencing and sequence analysis are given in the SI.

160

Statistical Analysis.

161

The means and standard deviations were calculated using Origin 8.5. The 1-sample T-Test

162

was applied to compare the means. Results were significant if p < 0.05. The 2-dimensional

163

correlation spectra technique (2D-COS) was used to explore the biodegradation heterogeneities of

164

CyanoHAB-DOM with respect to hydrophobicity-distinguished FDOM components. More

165

information about 2D-COS is provided in the SI.

166 167

RESULTS AND DISCUSSION

168

DOM Removal.

169

The influent DOM was decomposed as it traveled along the 4-stage bioreactor with increased

170

HRTs. The concentration of DOC decreased from 35.80 to 10.68 mg L−1 during the initial 24 h

171

(Table 1), whereas the DOC consumption was lower in the stage-3 and 4 even with a longer

172

residence time of 72 h. Thus, the microbial communities in the first 2 reactors played a major role

173

for DOC biodegradation, and the residual DOC was relatively recalcitrant. Fitting by G model

174

allowed to separate the DOC into labile (8.30 mg L−1), semi-labile (20.27 mg L−1) and refractory

175

(7.20 mg L−1) (R2 = 1.00) (SI Figure S4). Compared with the DOM in headwater streams and 9



Page 10 of 31

176

municipal wastewater effluents,31, 32 CyanoHAB-DOM exhibited a greater bioavailability of 79%

177

(equal to the sum of labile and semi-labile DOC). In fact, the 4-stage plug-flow bioreactor herein

178

showed a higher efficiency for DOM removal within a shorter time than the conventional bioassay

179

method (SI Table S3).

180 181

Spectral Characterization.

182

Values of a254 decreased from 36.71 to 20.88 m−1 and were significantly related to DOC

183

concentrations (p < 0.001). The obvious shift of peak a282 to a292 and then to a306 in the 2nd

184

derivate absorption spectra revealed that biodegradation caused qualitative shifts in chromophoric

185

DOM (SI Figure S5). Meanwhile, the increase in SUVA254 suggested that the dominant

186

component of light-absorbing DOM transformed to humic-like substances with a higher

187

aromaticity.29 The decrease in SR implied the degradation of small DOM molecules and/or the

188

production of large DOM molecules.27 In accordance with the change of SUVA254, the values of

189

HIX increased as water samples flowed through the bioreactor.

190

The 3-component PARAFAC model was well validated and highly overlapped for excitation

191

and emission spectra estimated by using split-half analysis (SI Figure S6). Components 1, 2, and 3

192

were labeled C1, C2, and C3 respectively. The peaks of C1 (Ex 265, 375/Em 462 nm), C2 (Ex 235,

193

275/Em 324 nm) and C3 (Ex 235, 325/Em 403 nm) were identified to correspond to humic-,

194

tryptophan- (peak T) and humic-like substances, respectively.16, 33 The FDOM (sum of Fmax of C1,

195

C2 and C3) decreased with a total loss of 60% along the bioreactor. The recalcitrant fraction of

196

proteinaceous FDOM (23%) may originate from the potential associations between the tryptophan

197

and the humic matrix, which can limit their accessibility to bacteria without inhibiting all 10


Page 11 of 31


198

tryptophan fluorescence.16 In contrast to the conservative behavior of humic-like FDOM (with no

199

changes or production) in previous findings,34 CyanoHAB-derived humic-like components were

200

more biodegradable due to their limited biodegradation history.26

201 202

Hydrophobicity-Distinguished Characterization.

203

The multi-excitation properties of FDOM coincided well with the result of PARAFAC, which

204

indicated that the protein-like C2 and humic-like C3 had dual peaks, whereas the humic-like C1

205

had triple peaks (SI Figure S7). The properties of the multi-excitation peaks made it feasible to

206

reflect all the fluorescent DOM species using an Emission-Time-Map that was conducted at a

207

constant excitation wavelength (235 nm) and variable emission wavelengths (300–500 nm). As

208

shown in Figure 1a, the shorter retention time of humic-like species (Em > 380 nm) indicated that

209

the humic-like species were more hydrophilic as compared with the protein-like species (Em
4.10 > 1.34 min (Figure 1e). So, biodegradation

233

rates of hydrophobic humic-like fractions were faster than the formation rates of hydrophilic

234

fractions, which were bioresistant due to their high-molecular-weight compositions.18

235 236

FTICR-MS Characterization.

237

A total of 4,882 formulas were assigned to the mass peaks detected in all water samples, and

238

3,163 unique formulas existed after removing duplicates. As shown in SI Table S4, the DOM in

239

influent was dominated by CHO formulas (39%), followed by CHON, CHOS and CHONS (34%,

240

17% and 10%, respectively). The most detectable structure for CyanoHAB-DOM was highly

241

unsaturated with oxygen, accounting for 488 formulas (49% of which were intensity-weighted). 12


Page 13 of 31


242

Elemental stoichiometries falling into the cluster of highly unsaturated molecules covered a range

243

of possible structural isomers with distinct biogeochemical reactivity, including nonchromophoric,

244

steroid-like, refractory compounds or chromophoric, terrigenous, photolabile aromatic

245

biomarkers.37 Peptide-like and aliphatic molecules correspond to intracellular abundant

246

metabolites released as DOM by live cyanobacterial cells.

247

As water flowed through the bioreactor, the DOM was depleted in CHON molecules and

248

highly unsaturated, high-oxygen molecules; meanwhile, CHO molecules, aliphatic molecules, and

249

highly unsaturated, low-oxygen molecules were enriched. The increase in aliphatic molecules and

250

the decrease in unsaturated molecules indicated that molecules in a wide range of H: C values

251

were bioavailable. The nitrogen- and sulfur-bearing unsaturated molecules were likely derived

252

from the subunits and/or fragments of functional cellular components of cyanobacterial biomass.7

253

Nucleotides (DNA and RNA), chlorophy Ⅱ and phycocyanin all contain heterocyclic rings and

254

H/C ratio ranging from 1 to 1.3. Moreover, the decrease in O/Cw and N/Cw suggested that high

255

oxygen and nitrogen-bearing molecules were readily utilized by microorganisms. This trend was

256

further confirmed by a strong decrease in highly unsaturated, high-oxygen molecules.

257

The H/C and O/C ratios were plotted versus mass to follow the specific changes in DOM

258

composition with different molecular masses (SI Figure S9). Several saturated DOM molecules

259

(H/C > 1.5) with high relative intensities were observed at masses between 200 and 400 m/z in

260

influent, whereas the relative intensities of these molecules were reduced in effluents.

261

Simultaneously, a large number of molecules with higher masses (500–700 m/z) were bioproduced,

262

meaning that bacteria can release high-molecular-weight materials as byproducts. In the O/C

263

versus mass peak diagrams (Figure 2), molecules with higher O/C values (> 0.4) at 200–400 m/z 13



Page 14 of 31

264

exhibited a decrease in relative intensity with biodegradation. This limited removal of low oxygen

265

compounds was consistent with previous findings with temperate and tropical stream water.15 A

266

high degree of reduction may be less enzymatically accessible; even these compounds would be

267

energetically advantageous targets for metabolism. The occurrence of many large molecules with

268

low O/C (< 0.4) in final effluent DOM corresponded to the plots of H/C versus mass. Moreover,

269

2D-COS based on total number of CHO formulas at each specific O/C further revealed that new

270

low oxygen molecules at O/C of 0.1–0.4 were added to the DOM pool, accompanied by the

271

decrease in number of molecules at 0.4–0.7 and 0.7–1.1 (SI Figure S10). Thus, the smaller

272

molecules with a higher degree of oxidation were easier to be metabolized by microorganisms

273

than the larger molecules with a lower ratio of O/C.

274

The change of peptide-like molecules was inconsistent with the reduction of protein-like

275

FDOM in the bioreactor. The relationship between FDOM and FTICR-MS structures is still far

276

from being straightforward, although several preliminary studies have been conducted.26, 37 FDOM

277

represents an unknown group of fluorophores with variable fluorescence quantum yields.38 Thus,

278

FDOM is restricted to only an unknown fraction of total carbon and nitrogen within DOM.

279

However, FTICR-MS accounts for the ionizable compounds which are also an unknown fraction

280

of DOM molecules. Previous study revealed that only 31% of the total molecules assigned to

281

protein-like components contained nitrogen.37 Moreover, the peak T relevant compounds were of

282

lower nitrogen content than those formulas associated with marine/microbial humic. These

283

observations implied that many structures associated to peak T were nitrogen-depleted and did not

284

have fluorescence. Also, some small, nitrogen-free aromatic compounds, e.g., gallinic acid, have

285

been reported to exhibit a strong fluorescence signal in the region of peak T.39 As a result, the 14


Page 15 of 31


286

metabolism of nitrogen-free aromatic molecules may be involved in the decrease of peak T.

287 288

Molecular Structure and Bioavailability Classification.

289

According to the G-modelling results, the compounds in influent DOM were classified into

290

labile, semi-labile, and refractory molecules according to their attenuation profiles in the

291

bioreactor. The labile and semi-labile DOM pools were both composed of peptide-like,

292

sulfur-bearing aliphatics and nitrogen-bearing unsaturated molecules (SI Figure S11 and Table S5).

293

A small group of unsaturated CHOS and CHONS with low O/C (0.0–0.2) were also bioavailable.

294

The refractory molecules exhibited an even narrow distribution in unsaturated compounds (69%)

295

and showed distinct elemental composition (65% CHO, 29% CHON, 6% CHOS, 0% CHONS)

296

when compared with the labile and semi-labile molecules (Figure 3a). Additionally, a dense

297

population of refractory peaks (55%) fell into the region of carboxylic-rich alicyclic molecules

298

(CRAM), which was bioresistant due to its structural diversity and substantial content of alicyclic

299

rings and branching.40 This species shared some structural characteristics which were detected in

300

membrane constituents and secondary metabolites in a wide range of prokaryotic and eukaryotic

301

organisms.40 This means that the occurrence and decomposition of the cyanobacterial cell wall and

302

membrane components should be reasonable sources of CRAM. Multi-step and massively parallel

303

biotic and subordinated abiotic transformations of CyanoHAB-DOM caused progressive

304

formation of CRAM from summer to fall.3 The average modified aromaticity index (AImod) of

305

refractory molecules was higher than that of labile and semi-labile molecules, indicating the

306

negative relationship between bioavailability and aromaticity. Overall, the bioavailable

307

components had a higher number of H, N and S, and were abundant with nitrogen-bearing 15



308

Page 16 of 31

molecules.

309

New molecules in final effluent DOM appeared as bioproduced refractory molecules.

310

Nevertheless, it is also possible that the appearance of new molecules could have originated from

311

the molecules that were previously masked by the more easily-recognized ionized molecules in

312

influent DOM. Many heteroatom-bearing molecules were observed in O/C of 0.0–0.4 and H/C of

313

1.0–2.0 (Figure 3b). According to van-Krevelen diagram chemical classifications,21 the region

314

with H/C of 1.5–2.0 and O/C of 0.0–0.3 was attributed to the cluster of lipid-like molecules. This

315

class of molecules in soil DOM has been found to be negatively correlated with biodegradability

316

by using Spearman rank correlation.41 The low bioavailability of lipid-like molecules may be due

317

to the hydrophobic nature of alkyl carbon compounds that can prevent access to degrading

318

enzymes. Based on formula numbers, the higher average mass of these molecules (m/z of 479) as

319

compared with other 3 DOM pools suggested that the microbial organisms utilized the small

320

heteroatom-bearing compounds, and simultaneously released the large heteroatom-bearing

321

compounds.

322

The nitrogen-bearing molecules (sum of CHON and CHONS) were further examined to track

323

the changes in DON. The bioavailability classification of DON molecules was similar to that of

324

DOM molecules (SI Figure S12). The newly formed nitrogen-bearing molecules were highly

325

saturated and low in oxygen, whereas the saturated DON molecules with abundant oxygen were

326

relatively bioavailable. This indicated that the reactive DON molecules were transformed into less

327

oxygenated, highly saturated molecules during biodegradation. Refractory molecules were also

328

distributed in the center region of van-Krevelen diagram, confirming that CyanoHAB was a

329

significant source of recalcitrant DON structures. The numbers of labile, semi-labile, refractory 16


Page 17 of 31


330

and bioproduced DON molecules were 307, 130, 87 and 314, respectively. This implied that

331

microbes changed the carbon skeleton of a proportion of nitrogen-bearing molecules without

332

concomitant consumption of nitrogen.19 Obviously, although the main components were relatively

333

bioavailable, a certain number of recalcitrant molecules appeared in CyanoHAB-DOM. In fact, a

334

significant refractory component was found in algal DOC pools in temperate lakes.42

335 336

Microbial Community Analysis.

337

Totally, 49,906 sequences were generated and passed through the quality control of the

338

Quantitative Insights into Microbial Ecology (QIIME v1.6.0) pipeline for the microbial groups

339

collected from the 4-stage plug-flow bioreactor. These sequences were assigned to 8,302 OTUs

340

with a cutoff of 0.03. The microbial community structures in each unit of the bioreactor on

341

phylum and class levels are depicted in Figures 4a and 4b. Proteobacteria was the dominant

342

phylum in stage-1 (43%), followed by Bacteroidetes (21%), whereas the relative abundance of

343

these 2 phyla decreased in stage-4 (23% and 7%, respectively). Meanwhile, the relative abundance

344

of several other phyla increased, such as Planctomycetes (from 4% to 22%), Chloroflexi (from 1%

345

to 10%), and Actinobacteria (from less than 1% to 5%). Interestingly, Planctomycetes

346

communities were also presented at high levels in diatom and cyanobacterial aggregates.43 This

347

microbial group has been associated with the degradation of macroalgal residuals deposited in

348

sediments during post-bloom periods.44 Planctomycetes and Actinobacteria possessed abundant

349

monooxygenase genes such as cytochrome P450, and were able to catalyze the oxidation reaction

350

of recalcitrant and xenobiotic substances including humic substances and toxic chemicals.10

351

At the class level, beta-Proteobacteria, Saprospirae and Chloracidobacteria were generally 17



Page 18 of 31

352

the most abundant groups in stage-1, suggesting that they were the most likely groups for

353

assimilating the labile part presented in CyanoHAB-DOM. On the contrary, the relative abundance

354

of Planctomycetia (from 3% to 18%), alpha-Proteobacteria (from 7% to 15%), Anaerolineae

355

(from 1% to 6%) and Chlamydiia (from less than 1% to 5%) increased in response to the

356

increasing amount of refractory substances. Previous findings showed that the addition of humic

357

substances led to the enrichment of specific alpha-Proteobacteria, such as members of the

358

Rhodobacteraceae group, in an oligotrophic lake.45 However, beta-Proteobacteria and

359

Bacteroidetes were linked with the labile DOM depletion (e.g., proteins and sugars) due to the

360

wide range of organic degradation capabilities of numerous microbial groups within them.10 The

361

genus level characterization further illustrates variations in the bacterial community (SI Figure

362

S13). Comamonas and Nitrospira were the dominant genera in stage-1, while Planctomyces and

363

Mycobacterium were more abundant in other stages. A further principal coordinate analysis was

364

used to compare the bacterial communities (beta-diversity) (SI Figure S14). Communities

365

cultivated in stage-2, 3 and 4 were grouped together and were distinctly different from those in

366

stage-1, indicating that the microbial community compositions in stage-1 with a higher

367

concentration of bioavailable DOM, were distinct from the other stages.

368

The alpha-diversity of the bacterial communities in each stage of the bioreactor were

369

represented as the Shannon index (Figure 4c), which is positively correlated with species richness

370

and evenness. The microbial communities living in stage-3 and 4 had a higher diversity than those

371

in stage-1 and 2. A negative correlation between microbial diversity and bioavailable DOC

372

concentration was proposed.10 A possible explanation can be that microbial groups like

373

beta-Proteobacteria harbored high metabolism and assimilation rates (as evidenced by the higher 18


Page 19 of 31


374

biodegradation rates in stage-1 and 2) when exposed to abundant labile DOM. However, the

375

proportion of less bioavailable DOM increased with the exhaustion of labile DOM, and selected

376

for the co-existence of numerous microbial groups with variable metabolic functions. The growth

377

of more diverse microbial groups promoted co-metabolic processes that were likely to target the

378

recalcitrant DOM.

379 380

Implications of the Impact of CyanoHAB-DOM on Lake Environments.

381

The application of a 4-stage plug-flow bioreactor allows a quick and reliable bioavailability

382

assessment of DOM and has important environmental implications for the improved

383

understanding of the impact of CyanoHAB-DOM on lake environments. The continuous

384

once-through feeding provides a unidirectional supply of carbon, inorganic nutrients and energy.

385

Some molecules in influent DOM were bioavailable and changed as they moved through the

386

bioreactor, whereas some compounds did not undergo transformation. As a result, specific bacteria

387

communities for various bioavailable DOM were then enriched on the inert carriers in each reactor,

388

which preferentially consumed the labile or semi-labile components in DOM. In fact, there existed

389

an appropriate scaling to transfer the DOM behavior information obtained in the bioreactor to the

390

fate of DOM in the environment.46 While bioavailable DOM detected in the bioreactor will

391

decompose in several days in natural waters through vertical exchange of water masses,47 the

392

recalcitrant DOM remains in aquatic systems with longer but unknown turnover times.

393

Multiple

analytical

tools

including

DOC,

absorption

and

fluorescence

spectra,

394

hydrophobicity-distinguished components, and molecular compositions were used to characterize

395

the temporary evolution in the composition and structure of DOM in the bioreactor (SI Figure 19



Page 20 of 31

396

S15). These data provided a deeper insight into the relationship between the composition and

397

structure of DOM and its biodegradation. Compared with the DOM in streams, effluents and

398

soils,31, 32, 41 the CyanoHAB-DOM showed a greater bioavailability. The synchronous removal of

399

peak T, nitrogen-rich structures and DOC indicated that nitrogen and carbon pools were readily

400

available to fuel microbial productivity and respiration. This strong decomposition of bioavailable

401

DOM would deplete dissolved oxygen, creating ‘Dead Zones’ in the water column, thereby

402

establishing hypoxic conditions.8 Therefore, the relatively bioavailable CyanoHAB-DOM may

403

increase the risk for ‘black water’ and cause deterioration of water quality.

404

Besides the algae-produced refractory molecules, the utilization of labile and semi-labile

405

DOM also produced some new refractory molecules. This result emphasized the role of the

406

microbial carbon pump that was a conceptual framework for understanding the microbial

407

processes in refractory DOM generation. CyanoHAB can produce DOM through CO2 fixation as a

408

biological pump, and then microbial heterotrophic activity, the fundamental driver of a microbial

409

carbon pump, transforms some organic carbon from the reactive DOM pools to a recalcitrant

410

carbon reservoir. With regard to DON, a number of less oxygenated nitrogen-bearing molecules

411

were bioproduced in company with the removal of labile DON molecules with high O/C and H/C.

412

This implied that the microbial transformation could alter DON composition and bioavailability

413

with limited consumption of nitrogen.

414

The hydrophobic-distinguished DOM exhibited distinct behaviors during biodegradation,

415

possibly affecting its interaction with contaminants. DOM can form complexes with organic

416

contaminants, e.g., antibiotics and endocrine disrupting chemicals, through hydrophobic

417

interaction and other potential mechanisms.48 Proteins generally play a major role in the 20


Page 21 of 31


418

complexation, whereas the binding capacities of hydrophobic DOM fractions were greater than

419

hydrophilic binding capacities. Hence, although the CyanoHAB-DOM can stabilize the organic

420

contaminants temporarily, the significant enrichment of hydrophilic humic fraction after

421

biodegradation may decrease the binding affinity of organic contaminants to DOM, posing an

422

unknown toxicity to aquatic organisms.

423

The present results are also consistent and confirm prior findings that the bioavailability of

424

organic compounds is an important factor in shaping the microbial community.49

425

CyanoHAB-DOM well approximates the environmentally relevant chemical mixtures present in

426

naturally occurring DOM, better than the pure compound nutrient additions (such as peptone and

427

humic acid) frequently used in such experiments.10, 50 Compared with labile DOM, semi-labile and

428

refractory DOM pools favored the growth of more diverse microbial groups. Specific resource

429

partitioning of DOM by different bacterial species causes a temporal succession of taxa, metabolic

430

pathway expression, and chemical transformations associated with DOM turnover. Microbial

431

communities exposed to refractory DOM have been expected to harbor versatile capacities in

432

chemical compound utilization including refractory environmental contaminants,10 so the

433

post-bloom formation of an oligotrophic microbial community may be effective in the attenuation

434

of refractory organic chemicals. On the contrary, the large amount of labile and semi-labile DOM

435

produced in strong bloom events may slow down the removal of these contaminants through

436

selection of low diverse microbial communities.

437 438

AUTHOR INFORMATION

439

Corresponding Author 21



440

*E-mail: [email protected] (H.L. Jiang). Phone/Fax: 0086-25-86882208.

441

Notes

442

The authors declare no competing financial interest.

Page 22 of 31

443 444

ACKNOWLEDGEMENTS

445

This work was supported by grants from the National Natural Science Foundation of China

446

(51379199, and 51679228), and CAS Interdisciplinary Innovation Team.

447 448

ASSOCIATED CONTENT

449

Supporting Information Available

450

Expanded experimental section and additional tables and figures referenced in this paper are

451

provided as Supporting Information (PDF). This information is available free of charge via the

452

Internet at http://pubs.acs.org.

453

22


Page 23 of 31


454

REFERENCES

455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473

（1）Paerl, H. W.; Paul, V. J., Climate change: Links to global expansion of harmful cyanobacteria. Water Res.

474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496

2012, 46, (5), 1349-1363. （2）Wang, C. H.; Jiang, H. L., Chemicals used for in situ immobilization to reduce the internal phosphorus loading from lake sediments for eutrophication control. Crit. Rev. Env. Sci. Tec. 2016, 46, (10), 947-997. （3）Zhang, F. F.; Harir, M.; Moritz, F.; Zhang, J.; Witting, M.; Wu, Y.; Schmitt-Kopplin, P.; Fekete, A.; Gaspar, A.; Hertkorn, N., Molecular and structural characterization of dissolved organic matter during and post cyanobacterial bloom in Taihu by combination of NMR spectroscopy and FTICR mass spectrometry. Water Res. 2014, 57, (0), 280-294. （4）Henderson, R. K.; Baker, A.; Parsons, S. A.; Jefferson, B., Characterisation of algogenic organic matter extracted from cyanobacteria, green algae and diatoms. Water Res. 2008, 42, (13), 3435-3445. （5）Teeling, H.; Fuchs, B. M.; Becher, D.; Klockow, C.; Gardebrecht, A.; Bennke, C. M.; Kassabgy, M.; Huang, S. X.; Mann, A. J.; Waldmann, J.; Weber, M.; Klindworth, A.; Otto, A.; Lange, J.; Bernhardt, J.; Reinsch, C.; Hecker, M.; Peplies, J.; Bockelmann, F. D.; Callies, U.; Gerdts, G.; Wichels, A.; Wiltshire, K. H.; Glöckner, F. O.; Schweder, T.; Amann, R., Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science 2012, 336, (6081), 608-611. （6）Hansell, D. A.; Carlson, C. A., Biogeochemistry of marine dissolved organic matter. Academic Press: 2014. （7）Bittar, T. B.; Vieira, A. A. H.; Stubbins, A.; Mopper, K., Competition between photochemical and biological degradation of dissolved organic matter from the cyanobacteria Microcystis aeruginosa. Limnol. Oceanogr. 2015, 60, (4), 1172-1194. （8）Chen, M.; Li, X. H.; He, Y. H.; Song, N.; Cai, H. Y.; Wang, C. H.; Li, Y. T.; Chu, H. Y.; Krumholz, L. R.; Jiang, H. L., Increasing sulfate concentrations result in higher sulfide production and phosphorous mobilization in a shallow eutrophic freshwater lake. Water Res. 2016, 96, 94-104. （9）Tan, D. T.; Temme, H. R.; Arnold, W. A.; Novak, P. J., Estrone degradation: Does organic matter (quality), matter? Environ. Sci. Technol. 2015, 49, (1), 498-503. （10）Li, D.; Alidina, M.; Drewes, J. E., Role of primary substrate composition on microbial community structure and function and trace organic chemical attenuation in managed aquifer recharge systems. Appl. Microbiol. Biotechnol. 2014, 98, (12), 5747-5756. （11）Bronk, D. A.; Glibert, P. M.; Ward, B. B., Nitrogen uptake, dissolved organic nitrogen release, and new production. Science 1994, 265, (5180), 1843. （12）Seitzinger, S. P.; Sanders, R. W.; Styles, R., Bioavailability of DON from natural and anthropogenic sources to estuarine plankton. Limnol. Oceanogr. 2002, 47, (2), 353-366. （13）Bond, T.; Huang, J.; Templeton, M. R.; Graham, N., Occurrence and control of nitrogenous disinfection by-products in drinking water–a review. Water Res. 2011, 45, (15), 4341-4354. （14）Kothawala, D. N.; von Wachenfeldt, E.; Koehler, B.; Tranvik, L. J., Selective loss and preservation of lake water dissolved organic matter fluorescence during long-term dark incubations. Sci. Total Environ. 2012, 433, 238-246. （15）Kim, S.; Kaplan, L. A.; Hatcher, P. G., Biodegradable dissolved organic matter in a temperate and a tropical stream determined from ultra-high resolution mass spectrometry. Limnol. Oceanogr. 2006, 51, (2), 1054-1063. （16）Cory, R. M.; Kaplan, L. A., Biological lability of streamwater fluorescent dissolved organic matter. Limnol. Oceanogr. 2012, 57, (5), 1347-1360. （17）Amon, R. M. W.; Benner, R., Bacterial utilization of different size classes of dissolved organic matter. Limnol. Oceanogr. 1996, 41, (1), 41-51. 23



497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540

Page 24 of 31

（18）He, X. S.; Xi, B. D.; Li, W. T.; Gao, R. T.; Zhang, H.; Tan, W. B.; Huang, C. H., Insight into the composition and evolution of compost-derived dissolved organic matter using high-performance liquid chromatography combined with Fourier transform infrared and nuclear magnetic resonance spectra. J. Chromatogr. A 2015, 1420, 83-91. （19）Lusk, M. G.; Toor, G. S., Dissolved organic nitrogen in urban streams: Biodegradability and molecular composition studies. Water Res. 2016, 96, 225-235. （20）Logue, J. B.; Stedmon, C. A.; Kellerman, A. M.; Nielsen, N. J.; Andersson, A. F.; Laudon, H.; Lindstrom, E. S.; Kritzberg, E. S., Experimental insights into the importance of aquatic bacterial community composition to the degradation of dissolved organic matter. ISME J. 2016, 10, (3), 533-545. （21）Stubbins, A.; Spencer, R. G. M.; Chen, H. M.; Hatcher, P. G.; Mopper, K.; Hernes, P. J.; Mwamba, V. L.; Mangangu, A. M.; Wabakanghanzi, J. N.; Six, J., Illuminated darkness: Molecular signatures of Congo River dissolved organic matter and its photochemical alteration as revealed by ultrahigh precision mass spectrometry. Limnol. Oceanogr. 2010, 55, (4), 1467-1477. （22）Spencer, R. G. M.; Guo, W. D.; Raymond, P. A.; Dittmar, T.; Hood, E.; Fellman, J.; Stubbins, A., Source and biolability of ancient dissolved organic matter in glacier and lake ecosystems on the Tibetan Plateau. Geochim. Cosmochim. Ac. 2014, 142, 64-74. （23）Stenson, A. C.; Marshall, A. G.; Cooper, W. T., Exact masses and chemical formulas of individual Suwannee River fulvic acids from ultrahigh resolution electrospray ionization fourier transform ion cyclotron resonance mass spectra. Anal. Chem. 2003, 75, (6), 1275-1284. （24）Li, W. T.; Xu, Z. X.; Li, A. M.; Wu, W.; Zhou, Q.; Wang, J. N., HPLC/HPSEC-FLD with multi-excitation/emission scan for EEM interpretation and dissolved organic matter analysis. Water Res. 2013, 47, (3), 1246-1256. （25）Søndergaard, M.; Worm, J., Measurement of biodegradable dissolved organic carbon (BDOC) in lake water with a bioreactor. Water Res. 2001, 35, (10), 2505-2513. （26）Sleighter, R. L.; Cory, R. M.; Kaplan, L. A.; Abdulla, H. A. N.; Hatcher, P. G., A coupled geochemical and biogeochemical approach to characterize the bioreactivity of dissolved organic matter from a headwater stream. J. Geophys. Res.: Biogeosci. 2014, 119, (8), 1520-1537. （27）Zhang, Y. L.; Liu, X. H.; Wang, M. Z.; Qin, B. Q., Compositional differences of chromophoric dissolved organic matter derived from phytoplankton and macrophytes. Org. Geochem. 2013, 55, (0), 26-37. （28）Westrich, J. T.; Berner, R. A., The role of sedimentary organic-matter in bacterial sulfate reduction - the G model tested. Limnol. Oceanogr. 1984, 29, (2), 236-249. （29）He, W.; Chen, M.; Park, J. E.; Hur, J., Molecular diversity of riverine alkaline-extractable sediment organic matter and its linkages with spectral indicators and molecular size distributions. Water Res. 2016, 100, 222-231. （30）Murphy, K. R.; Stedmon, C. A.; Graeber, D.; Bro, R., Fluorescence spectroscopy and multi-way techniques. PARAFAC. Anal. Methods 2013, 5, (23), 6557-6566. （31）Hosen, J. D.; McDonough, O. T.; Febria, C. M.; Palmer, M. A., Dissolved organic matter quality and bioavailability changes across an urbanization gradient in headwater streams. Environ. Sci. Technol. 2014, 48, (14), 7817-7824. （32）Saadi, I.; Borisover, M.; Armon, R.; Laor, Y., Monitoring of effluent DOM biodegradation using fluorescence, UV and DOC measurements. Chemosphere 2006, 63, (3), 530-539. （33）Coble, P. G.; Del Castillo, C. E.; Avril, B., Distribution and optical properties of CDOM in the Arabian Sea during the 1995 Southwest Monsoon. Deep Sea Res. Part II 1998, 45, (10), 2195-2223. （34）Cory, R. M.; McKnight, D. M.; Chin, Y. P.; Miller, P.; Jaros, C. L., Chemical characteristics of fulvic acids from Arctic surface waters: Microbial contributions and photochemical transformations. J. Geophys. Res.: 24


Page 25 of 31


541 542 543 544 545

Biogeosci. 2007, 112, (G04S51), DOI:10.1029/2006JG000343.

546 547 548

（37）Stubbins, A.; Lapierre, J. F.; Berggren, M.; Prairie, Y. T.; Dittmar, T.; del Giorgio, P. A., What’s in an EEM?

549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583

（38）Fellman, J. B.; Hood, E.; Spencer, R. G. M., Fluorescence spectroscopy opens new windows into dissolved

（35）Tomaszewski, J. E.; Schwarzenbach, R. P.; Sander, M., Protein Encapsulation by Humic Substances. Environ. Sci. Technol. 2011, 45, (14), 6003-6010. （36）Noda, I.; Ozaki, Y., Two-dimensional correlation spectroscopy: applications in vibrational and optical spectroscopy. John Wiley and Sons Inc. London: 2005.

Molecular signatures associated with dissolved organic fluorescence in Boreal Canada. Environ. Sci. Technol. 2014, 48, (18), 10598-10606.

organic matter dynamics in freshwater ecosystems: A review. Limnol. Oceanogr. 2010, 55, (6), 2452-2462. （39）Maie, N.; Scully, N. M.; Pisani, O.; Jaffé, R., Composition of a protein-like fluorophore of dissolved organic matter in coastal wetland and estuarine ecosystems. Water Res. 2007, 41, (3), 563-570. （40）Hertkorn, N.; Benner, R.; Frommberger, M.; Schmitt-Kopplin, P.; Witt, M.; Kaiser, K.; Kettrup, A.; Hedges, J. I., Characterization of a major refractory component of marine dissolved organic matter. Geochim. Cosmochim. Ac. 2006, 70, (12), 2990-3010. （41）Ohno, T.; Parr, T. B.; Gruselle, M. C. I.; Fernandez, I. J.; Sleighter, R. L.; Hatcher, P. G., Molecular composition and biodegradability of soil organic matter: A case study comparing two new England forest types. Environ. Sci. Technol. 2014, 48, (13), 7229-7236. （42）Guillemette, F.; McCallister, S. L.; Giorgio, P. A., Differentiating the degradation dynamics of algal and terrestrial carbon within complex natural dissolved organic carbon in temperate lakes. J. Geophys. Res.: Biogeosci. 2013, 118, (3), 963-973. （43）Cai, H. Y.; Yan, Z. S.; Wang, A. J.; Krumholz, L. R.; Jiang, H. L., Analysis of the attached microbial community on mucilaginous cyanobacterial aggregates in the eutrophic lake Taihu reveals the importance of Planctomycetes. Microb. Ecol. 2013, 66, (1), 73-83. （44）Vetterli, A.; Hyytiainen, K.; Ahjos, M.; Auvinen, P.; Paulin, L.; Hietanen, S.; Leskinen, E., Seasonal patterns of bacterial communities in the coastal brackish sediments of the Gulf of Finland, Baltic Sea. Estuar. Coast. Shelf S. 2015, 165, 86-96. （45）Hutalle-Schmelzer, K. M. L.; Grossart, H. P., Changes in the bacterioplankton community of oligotrophic Lake Stechlin (northeastern Germany) after humic matter addition. Aquat. Microb. Ecol. 2009, 55, (2), 155-167. （46）Kaplan, L. A.; Wiegner, T. N.; Newbold, J. D.; Ostrom, P. H.; Gandhi, H., Untangling the complex issue of dissolved organic carbon uptake: a stable isotope approach. Freshwater Biol. 2008, 53, (5), 855-864. （47）Maki, K.; Kim, C.; Yoshimizu, C.; Tayasu, I.; Miyajima, T.; Nagata, T., Autochthonous origin of semi-labile dissolved organic carbon in a large monomictic lake (Lake Biwa): carbon stable isotopic evidence. Limnology 2010, 11, (2), 143-153. （48）Ruiz, S. H.; Wickramasekara, S.; Abrell, L.; Gao, X.; Chefetz, B.; Chorover, J., Complexation of trace organic contaminants with fractionated dissolved organic matter: Implications for mass spectrometric quantification. Chemosphere 2013, 91, (3), 344-350. （49）Wear, E. K.; Carlson, C. A.; James, A. K.; Brzezinski, M. A.; Windecker, L. A.; Nelson, C. E., Synchronous shifts in dissolved organic carbon bioavailability and bacterial community responses over the course of an upwelling-driven phytoplankton bloom. Limnol. Oceanogr. 2015, 60, (2), 657-677. （50）Allers, E.; Gomez-Consarnau, L.; Pinhassi, J.; Gasol, J. M.; Simek, K.; Pernthaler, J., Response of Alteromonadaceae and Rhodobacteriaceae to glucose and phosphorus manipulation in marine mesocosms. Environ. Microbiol. 2007, 9, (10), 2417-2429.

584 25



585

Page 26 of 31

Figure Captions:

586 587

Figure 1. Hydrophobicity-distinguished characterization for fluorescent DOM. (a) HPLC

588

fluorescence Emission-Time-Map at Ex 235 nm of the influent DOM, (b) 2D-COS synchronous

589

map of protein-like species, (c) 2D-COS asynchronous map of protein-like species, (d) 2D-COS

590

synchronous map of humic-like species, and (e) 2D-COS asynchronous map of humic-like species.

591

Red represents positive correlations and blue represents negative correlations; a higher color

592

intensity indicates a stronger positive or negative correlation.

593 594

Figure 2. O/C versus mass of DOM molecules. (a) O/C versus mass of influent DOM, and (b)

595

O/C versus mass of final effluent DOM.

596 597

Figure 3. van-Krevelen diagrams for refractory DOM molecules. (a) Refractory molecules in

598

influent, and (b) bioproduced refractory molecules.

599 600

Figure 4. Microbial community analysis. The relative abundance (percent) of microbial groups on

601

(a) phylum level and (b) class level at 10 cm depth of each stage of the bioreactor, and (c)

602

Shannon diversity index of microbial communities.

603 604

26


Page 27 of 31


Table 1. DOM quantity and quality parameters after having passed through the 4-stage plug-flow bioreactor. (Means ± SD) Timea

DOC

a254

SUVA254

FDOM SR

Sample –1

–1

–1

C1b

C2b

C3b

HIX

–1

R.U.

(h)

(mg L )

(m )

(L mg C m )

Influent

0

35.77 ± 6.19

36.71 ± 3.08

0.46 ± 0.04

1.70 ± 0.20

1.10 ± 0.16

0.97 ± 0.06

0.2 ± 0.02

0.52 ± 0.06

0.25 ± 0.02

Eff-1

4

21.60 ± 0.88

30.01 ± 0.21

0.60 ± 0.02

1.29 ± 0.12

0.97 ± 0.06

0.71 ± 0.07

0.15 ± 0.01

0.36 ± 0.05

0.20 ± 0.01

Eff-2

24

10.68 ± 0.34

26.12 ± 0.72

1.06 ± 0.04

1.09 ± 0.05

1.15 ± 0.11

0.55 ± 0.02

0.14 ± 0.00

0.24 ± 0.02

0.17 ± 0.00

Eff-3

48

8.62 ± 1.35

24.48 ± 0.54

1.24 ± 0.07

0.98 ± 0.02

1.39 ± 0.04

0.45 ± 0.03

0.12 ± 0.01

0.16 ± 0.01

0.16 ± 0.01

Eff-4

96

7.44 ± 0.51

20.88 ± 0.63

1.23 ± 0.07

0.85 ± 0.07

1.63 ± 0.02

0.39 ± 0.01

0.12 ± 0.00

0.12 ± 0.01

0.15 ± 0.00

a

Total retention time

b

C1 represented humic-like substances, C2 represented tryptophan-like substances, and C3 represented humic-like substances

27



500

Page 28 of 31

(a)

Em 320 nm Em 420 nm

Em (nm)

450 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

400 350 300 0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

HPLC-Time (min)

Figure 1

28


Page 29 of 31


(a)

CHO CHON CHOS CHONS

1.0

(b)

1

1.0 0.8

0.6

0

O/C

O/C

0.8

0.6

0.4

0.4

0.2

0.2

0.0

1

CHO CHON CHOS CHONS

-1 200

300

400

500

600

700

0.0

0

-1 200

300

m/z

400

500

600

700

m/z

Figure 2

29



(a)

(b)

CHO CHON CHOS CHONS

2.0

1.5 H/C

H/C

Lipid-like

2.0

1.5

1.0

CRAM

0.5

0.0

Page 30 of 31

0.2

0.4

0.6

0.8

1.0

CHO CHON CHOS CHONS

0.5

1.0

0.0

0.2

0.4

O/C

0.6

0.8

1.0

O/C

Figure 3

30


Page 31 of 31


(c)

Shannon index

9.0

8.0

7.0 Stage-1 Stage-2 Stage-3 Stage-4

6.0 0

3000

6000

9000 12000 No. of sequences

15000

18000

Figure 4

31


Toward Quantitative Understanding of the ... - ACS Publications

Recommend Documents