16S rRNA Gene Amplicon Sequencing Reveals Significant Changes

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16S rRNA gene amplicon sequencing reveals significant changes in microbial compositions during cyanobacteria-laden drinking water sludge storage Haiyan Pei, Hangzhou Xu, Jingjing Wang, Yan Jin, HongDi Xiao, Chunxia Ma, Jiongming Sun, and Hongmin Li Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b03085 • Publication Date (Web): 10 Oct 2017 Downloaded from http://pubs.acs.org on October 11, 2017

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Environmental Science & Technology

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16S rRNA gene amplicon sequencing reveals significant changes in microbial

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compositions during cyanobacteria-laden drinking water sludge storage

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Haiyan Pei1, 2 *, Hangzhou Xu1, Jingjing Wang3, Yan Jin1, Hongdi Xiao4, Chunxia

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Ma1, Jiongming Sun1, Hongmin Li1

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1

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China.

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2

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250061, China.

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3

School of Life Science, Shandong University, 250100, China.

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School of Physics, Shandong University, 250100, China.

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* Corresponding author: School of Environmental Science and Engineering,

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Shandong University, Jinan, 250100, P. R. China

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Tel./Fax: +86-531-88392983

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E-mail address: [email protected].

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Graphical Abstract

School of Environmental Science and Engineering, Shandong University, Jinan, 250100,

Shandong Provincial Engineering Center on Environmental Science and Technology, Jinan,

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Abstract

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This is the first study to systematically investigate the microbial community

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structure in cyanobacteria-laden drinking water sludge generated by different types of

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coagulants (including AlCl3, FeCl3, and polymeric aluminium ferric chloride (PAFC))

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using Illumina 16S rRNA gene MiSeq sequencing. Results show that Cyanobacteria, 1

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Proteobacteria, Firmicutes, Bacteroidetes, Verrucomicrobia, and Planctomycetes

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were the most dominant phyla in sludge, and because of the toxicity of high Al and Fe

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level in AlCl3 and FeCl3 sludges, respectively, the PAFC sludge exhibited greater

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microbial richness than that in AlCl3 and FeCl3 sludges. Due to lack of light and

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oxygen in sludge, relative abundance of the dominant genera Microcystis,

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Rhodobacter, Phenylobacterium, and Hydrogenophaga clearly decreased, especially

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after 4 d storage, and the amounts of extracellular microcystin and organic matter rose.

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As a result, the relative abundance of microcystin and organic degradation bacteria

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increased significantly, including pathogens such as Bacillus cereus, in particular after

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4 d storage. Hence, sludge should be disposed of within 4 d to prevent massive growth

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of pathogens. In addition, because the increase of extracellular microcystins, organic

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matter, and pathogens in AlCl3 sludge was higher than that in FeCl3 and PAFC

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sludges, FeCl3 and PAFC may be ideal coagulants in drinking water treatment plants.

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Keywords: Cyanobacteria-laden drinking water sludge; Illumina high-throughput

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sequencing; Bacterial community composition; Microcystins; Organic matter

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1. Introduction

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Cyanobacterial blooms are becoming increasingly common in freshwater

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ecosystems globally in recent years1-4, as eutrophication of surface water is a

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worldwide problem and getting more and more serious, which may be a threat to

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drinking water supply. For example, microcystins (MCs), a kind of secondary

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metabolite produced by several bloom-forming cyanobacteria5, can cause serious and

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even fatal human liver, digestive, neurological, and skin diseases6,7. Although active

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release of toxins can occur from healthy cells and the ratio of intra/extracellular toxins

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depends on the species, the state of health, the period in the growth cycle of the

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cyanobacteria5 and the region8, a healthy cyanobacterial cell can have high levels of 2


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toxin confined within its walls5. For example, for Microcystis aeruginosa more than

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95% of the toxin can be contained within healthy cells5. Furthermore, the organic

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matter except toxin released by the damaged cyanobacteria cell will produce toxic

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disinfection byproducts and burden the subsequent processes in drinking water

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treatment plant9. Because the released MCs and other organic matter are more

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difficult to remove and can pose a serious hazard to water safety, it has become very

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important to find an effective method of removing toxin-producing cyanobacteria

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without cell damage. Coagulation has been demonstrated as an effective approach to

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remove the toxin-producing cyanobacteria without causing damage to cells10,11,

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thereby avoiding the release of intracellular MCs and other organic matter.

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Drinking-water treatment sludge is a by-product of the clarification process,

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where a coagulant such as AlCl3, FeCl3, or PAFC is used to separate and remove color,

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turbidity, algae and humic substances from drinking water12,13. It is notable that

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several million tonnes of clarifier sludge, which contains suspended solids, colloidal

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matter, algae and color-causing organics from natural water, are generated yearly14,

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equivalent to 4–7% of the total drinking water produced12,15. In recent years, owing to

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global water scarcity, more and more drinking water sludge is treated and dewatered,

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with the extracted water being recycled into the production stream, achieving zero

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discharge of sewage from the drinking water treatment plant16. Due to the increasing

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occurrence of cyanobacteria blooms in drinking water sources, the level of

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cyanobacteria in drinking-water treatment sludge has risen substantially recently,

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especially in summer and autumn. According to our previous study9, the

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cyanobacteria cells in cyanobacteria-laden drinking water sludge would release MCs

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and other organic matter after 4 d storage. Hence, it may be a threat to the recycling of

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extracted water if sludge is not treated or disposed of within 4 days. 3



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It is generally accepted that the functional stability of the drinking water sludge

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primarily relies on the dominant microbial activities and interactions within highly

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diverse communities. The community structure, diversity and fluctuation will

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ultimately affect the ability of the coagulation-generated cyanobacteria-laden drinking

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water sludge to degrade organic matter and toxins17,18, which were mainly released

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from the dominant cyanobacteria19, during storage. Release of intracellular MCs and

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organic matter would also affect the microbial community structure and stability of

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the sludge during storage time, as cyanobacteria is the dominant species in

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cyanobacteria-laden drinking water sludge. In addition, Wurzer et al.20 investigated

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six different waterworks in different regions of Germany and found that drinking

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water treatment sludge may contain pathogenic bacteria and viruses, including

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Escherichia coli, Salmonella, Pseudomonas aeruginosa, Legionella, and poliovirus.

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Recently, high-throughput sequencing technology has shown considerable

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advantages for the analysis of the microbial communities in association with

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unprecedented sequencing depth21 and has been widely applied to investigations of

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bacterial community structure in drinking water, sea water, soil, and sewage sludge

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samples22-25. As regards the microbial communities related to drinking water systems,

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researchers have mainly focused on the bacterial communities of raw water and

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treated water24,26,27; although Chao et al.28 reported a pertinent investigation applying

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high throughput sequencing to the biofilms formed on drinking water distribution

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pipelines. There is basically no metagenomic work evaluating the microbial structure

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of drinking water sludges, especially the cyanobacteria-laden sludges, formed after

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coagulation in drinking water treatment plants.

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In recent studies conducted by our group19,29,30, the damage to algal cells in

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sludge during storage was different after coagulation with different types of 4


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coagulants (including AlCl3, FeCl3, and PAFC), meaning that the changes of algal

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cells were different after coagulation with different types of coagulants. Similarly, the

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bacterial community structure may be different after coagulation with different types

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of coagulants. What are the influences of coagulant species on microbial community

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structure? Which kind of coagulant is most beneficial for improving the water

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quality?

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In addition, how does water quality, such as the rise in levels of MCs and organic

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matter, contribute to the structure of bacterial communities? Were there some

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pathogens in the cyanobacteria-laden drinking water sludge and the relative

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abundance of pathogens increase during storage?

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To answer these questions, cyanobacteria-laden drinking water sludges generated

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by different types of coagulants (including AlCl3, FeCl3, and PAFC) were stored for

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10 d. By virtue of the Illumina metagenomics data, we determined the taxonomic

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differences between the three kinds of sludges and evaluated taxonomic changes in

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microbial community structure during sludge storage. Furthermore, the water quality,

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such as levels of MCs and DOC, was evaluated and the relationship between the

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bacterial community structure and water quality was also revealed in our study.

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2. Materials and methods

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2.1. Cyanobacteria-laden drinking water sludge production and storage

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Summaries of the materials and methods for sludge production and storage are

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provided below. In-depth details of these methods are provided in the Supporting

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information (SI).

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2.1.1 Algae cultivation

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Axenic cultures of Microcystis aeruginosa (M. aeruginosa, FACHB-905) was

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selected as the experimental cyanobacteria, and was grown in BG11 medium (pH 7.5). 5



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The cultures were maintained in an incubator at 25 °C under 2000 lux with a light–

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dark cycle of 12 h/12 h and harvested at the late exponential phase of growth with a

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final cell yield up to about 107 cells/mL.

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2.1.2 Raw water and bloom water

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The natural source water was sampled from the Queshan Reservoir, an important

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drinking water source in Jinan, China, in May. To simulate the algal bloom in a high

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algae-laden period, the raw water was spiked with M. aeruginosa cultures to achieve a

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final cell density of about 2×105 cells/mL (bloom water, pH 8.45).

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2.1.3 Cyanobacteria-laden drinking water sludge production

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Coagulation experiments were performed at room temperature (25±1°C) in a

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six-paddle stirrer under room light (about 2000 lux). For the coagulation experiments,

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each bloom water sample (1 L) was dosed with the stock solution when the rapid

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mixing began. Optimum coagulation conditions for the effective removal of M.

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aeruginosa cells by AlCl3, FeCl3, and PAFC, respectively, are listed in Table S1.

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Coagulation time for AlCl3, FeCl3, and PAFC was 21, 30.5, and 21 min, respectively

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(Table S1). After coagulation, samples were settled for 30 min under quiescent

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conditions to obtain the flocs (formed into sludge) and supernatants. After removing

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930 mL of supernatant, 70 mL of cyanobacteria-containing sludge remained. Then 0.5

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L AlCl3, FeCl3, and PAFC sludge samples, respectively, were housed in an incubator

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at 25 °C under 2000 lux illumination with the 12 h/12 h (light/dark) cycle for up to 10

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d. 70 mL sample for AlCl3, FeCl3, and PAFC sludge, respectively, were drawn every

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two days during the storage period and then centrifuged at 4000 rpm for 10 min, and

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the extracted water (i.e., the centrate) was collected. 10 mL extracted water from

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AlCl3, FeCl3, and PAFC sludge was used to measure pH, respectively. 50 mL

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extracted water from AlCl3, FeCl3, and PAFC sludge, respectively, was filtered 6


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through a 0.45 µm cellulose acetate membrane before characterizing for levels of

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MCs, DOC (dissolved organic carbon), TN (total nitrogen), TP (total phosphorus), Al,

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and Fe. 1 mL dewatered AlCl3, FeCl3, and PAFC sludge was used to detect

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intracellular MCs and DOC, respectively. 5 mL dewatered AlCl3, FeCl3, and PAFC

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sludge, respectively, was stored at −26°C and then was used for DNA extraction, 16S

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rRNA gene PCR amplification and Illumina MiSeq sequencing.

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The dewatered cyanobacteria-laden sludges obtained from AlCl3, FeCl3, and

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PAFC coagulation and stored for 0, 4, and 8 d were named AC0, AC4, AC8, FC0,

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FC4, FC8, PC0, PC4, and PC8, respectively (Table S2). To evaluate the experimental

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repeatability, the biological replicates of them were also analyzed (Table S2).

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2.2 Measurement of pH, DO, DOC, MCs, TN, TP, Al and Fe

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The methods of analysis of pH, DO, DOC, MCs, TN, TP, residual Al and Fe

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were shown in the SI. Furthermore, to investigate the degradation of intracellular

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MCs and DOC during storage, extracellular MCs and DOC levels were measured

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after storage for 0, 2, 4, 6, 8, and 10 d, respectively. The levels of degraded MCs and

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DOC were then calculated and the detailed information was shown in the SI.

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2.3 DNA extraction, PCR amplification and sequencing, and data analysis

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The details for DNA extraction, 16S rRNA gene PCR amplification and sequencing were available in the SI.

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To obtain more accurate and reliable results in subsequent bioinformatics

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analyses, the raw data was pre-processed to get clean data by an in-house procedure

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(as shown in the SI). If the two paired-end reads overlapped, the consensus sequence

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was generated by FLASH (Fast Length Adjustment of SHort reads, v1.2.11)31, and the

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detailed method was as follows: (1) minimal overlapping length: 15 bp; (2) mismatch

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in ratio of overlapped region: ≤0.1. The paired-end reads without overlaps were 7



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removed. The high quality paired-end reads were combined into tags based on

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overlaps, 2,105,988 tags were obtained in total, with 116,999 tags per sample on

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average, and the average length was 252 bp.

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The tags were clustered into OTUs (Operational Taxonomic Unit) by scripts

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calling the software USEARCH (v7.0.1090), detailed as follows: (1) the tags were

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clustered into OTUs with a 97% threshold by using UPARSE; (2) chimeras were

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filtered out by using UCHIME (v4.2.40); (3) all tags were mapped to each OTU

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representative sequence using USEARCH GLOBAL. OTU-representative sequences

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were taxonomically classified using Ribosomal Database Project (RDP) Classifier

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v.2.2 trained on the Greengenes database, using 0.6 confidence values as cutoff.

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After removing low quality sequences and chimeras, at least 74,937 effective

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sequences were obtained for each sample. The sequence number of each sample was

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normalized and 536-736 OTUs were generated with a threshold of 0.97 (Table 1). All

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rarefaction curves tended to approach the saturation plateau (Figure S1), indicating

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that the data volume of sequenced reads was reasonable, and the discovery of a high

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number of reads made a small contribution to the total number of OTUs.

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A rarefaction analysis based on Mothur v1.31.2 was conducted to reveal the

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diversity indices, including the Chao, ACE, Shannon, and Simpson diversity indices.

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A beta diversity analysis was performed using UniFrac to compare the results of

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Non-metric multidimensional scaling (NMDS) using the community ecology package,

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R-forge. Principal component analysis (PCA) was performed using CANOCO

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software version 5.0 to determine the relationships between environmental parameters

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and bacterial community compositions. LEfSe analysis was done using the software

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LEFSE. Heat map analysis of the 24 most abundant genera in each group was

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conducted in the R software environment (version 3.1.1). Furthermore, the raw 8


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sequencing data has been submitted to the NCBI Sequence Read Archive with the

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project access number of SRP092495.

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3. Results and discussion

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3.1 Release and degradation of intracellular MCs and DOC during sludge storage

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The initial concentration of intracellular MCs in the three systems was similar,

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(about 26 µg/L) (Figure 1(a)). Due to clear increase in permeability of the M.

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aeruginosa membrane after 4 d storage as previously reported9, the intracellular MCs

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began to be released to outside and thus intracellular levels decreased (Figure 1(a)).

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Based on our previous study, lysis of M. aeruginosa cells in AlCl3 sludge was more

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serious than that in FeCl3 and PAFC sludges, while the cell’s integrity in the latter two

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systems stayed at almost the same level. Therefore, the release of intracellular MCs in

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the AlCl3 system was more substantial than that in FeCl3 and PAFC systems (Figure

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1(a)). Figure 1(b) shows variation of intracellular organic matter during storage

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process. Initial intracellular DOC was 51.2±0.54 mg/L and decreased with prolonged

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storage time, especially after 4 days’ storage, in the three systems. The decline of

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intracellular DOC was more evident in the cyanobacteria-containing AlCl3 sludge

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than in FeCl3 and PAFC sludges (Figure 1(b)), a similar trend to that seen with the

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intracellular MCs (Figure 1(a)). Furthermore, the amount of degraded MCs and DOC

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increased with prolonged storage time, and the degradation of MCs and DOC in AlCl3

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sludge was higher than that in FeCl3 and PAFC sludges (Figure 1). As shown in

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Figure 1(a), the extracellular MCs reached the maximum level on the sixth day and

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then decreased in the three systems, suggesting an increase in the degradation rate as

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storage time increases. On the contrary, the extracellular DOC had a minimum level

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on the fourth day and then began to increase in the three systems (Figure 1(b)),

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indicating an increase in release rate with prolonged storage time. 9



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3.2 Overview of microbial community diversity

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Illumina high-throughput sequencing was used to investigate the diversity and

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structure of microbial communities in the sludges. There are large variations in total

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number of OTUs in different samples (Table 1 and Figure S1). The total number of

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OTUs in AlCl3 sludge was 646, 720, and 576 after 0, 4, and 8 d storage, respectively.

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In FeCl3 sludge, the total number of OTUs was 614, 660, and 640 after 0, 4, and 8 d

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storage, respectively. Furthermore, the total number of OTUs was 547, 626, and 738

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after 0, 4, and 8 d storage, respectively, in PAFC sludge. Results above suggest that

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PAFC sludge exhibited greater species richness than AlCl3 and FeCl3 sludges on the

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eighth day. This finding may be attributable to the fact that high concentrations of Al

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and Fe are toxic to the growth of bacteria in AlCl3 and FeCl3 sludges, whereas in

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PAFC sludge low levels of Al have shown little toxic effect on bacteria growth and

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moderate amounts of Fe were beneficial to growth19. The variations of Chao and ACE

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indices in Table 1 were in line with the OTU numbers and also verified the previous

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conclusions. To assess the diversity and evenness of microbial populations among the

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groups, the Shannon index and Simpson index were calculated (Table 1). The higher

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the value of Shannon index, the richer the diversity, while the higher the Simpson

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index, the lower the diversity. Results showed that PAFC sludge had higher diversity

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than AlCl3 and FeCl3 sludges on the eighth day (Table 1).

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3.3 Shifts in microbial community structure and composition

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The duplicate relative abundances of annotated bacteria contiguous sequences at

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phylum and genus levels were compared (Figure S2). It is both qualitatively and

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quantitatively evident from the scatter plots and line of best fit statistics that there is a

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high level of reproducibility (i.e., results are nonrandom) in metagenome annotation

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and sequencing. PCA indicated that the replicates were clustered (Figure 2), which 10


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also verified that the sequencing results were reproducible and reliable. Furthermore,

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PCA was used to observe the overall variation of the bacterial communities among the

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three systems with different storage times. Usually, the closer the plotting of two

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samples, the more similar is the composition. Despite the fact that initial microbial

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communities in AlCl3, FeCl3 and PAFC sludges were similar, the bacterial

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communities varied obviously as the storage time was prolonged (Figure 2). Because

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TN, TP and DOC were the stronger factors influencing the bacterial community as

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shown in Figure 2, the variation above may be due to the increase of nutrients (TN,

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TP, and DOC (Table S3)) as the storage time was prolonged and the increment in

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AlCl3 sludge was higher than that in FeCl3 and PAFC sludges. Furthermore, high

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levels of Al and Fe in AlCl3 and FeCl3 sludges, respectively, may be toxic to the

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growth of some bacteria, whereas low concentrations of Al have shown little toxic

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effect on bacteria growth and moderate amounts of Fe were beneficial to growth in

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PAFC sludge19. In addition, the results of NMDS (Figure S3) were consistent with

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these PCA results.

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To identify the taxonomic diversity of bacterial communities in the three systems,

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sequences were classified using the RDP database with a bootstrap confidence

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threshold of 60%32,33 followed by a breakdown of the percentage (%) of total

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sequences classified (or unclassified) at each level. Of the total sequences, 1.23%

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were not classified at the phylum level, and the major phyla for each sample are

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shown in Figure 3. The most dominant phyla were Cyanobacteria, Proteobacteria,

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Firmicutes, Bacteroidetes, Verrucomicrobia, and Planctomycetes in the fresh sludge

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(without storage), which were presented in descending order. Chao et al.24

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investigated microbial community structure of raw water from a reservoir and found

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that Proteobacteria, Actinobacteria, Cyanobacteria, Bacteroidetes, Firmicutes, 11



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Verrucomicrobia, Planctomycetes, and Chloroflexi (in descending order) were the

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most dominant phyla, i.e., almost the same as our results. Bacterial community

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structure in drinking water biofilms that formed on pipes has also been investigated

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and Proteobacteria, Chloroflexi, Bacteroidetes, Actinobacteria, Cyanobacteria, and

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Firmicutes (in descending order) were reported as the most dominant phyla28. The

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differences in the relative abundances may be due to the different source waters and

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treatment processes. For example, because the raw water was collected in July,

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relative abundance of the Cyanobacteria was high, reaching 15%24. However, the

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drinking water biofilms were formed from purified water treated by the conventional

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drinking water treatment process (e.g., coagulation/sedimentation, disinfection) and

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lacking oxygen and light, resulting in low relative abundance of Cyanobacteria (1–

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3%)28. Results above were highly consistent with the bacterial communities in the

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activated sludges produced in full-scale and laboratory-scale wastewater treatment

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plants, across a wide range of geographic locations and reactor configurations17,34,35.

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Overall, these observations were highly consistent with the concept of ecological

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coherence of bacterial groups at taxonomic ranks higher than the species36.

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Usually, the phylum Proteobacteria is the most dominant community in drinking

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water systems26,28. Because the sludges in our study were produced by bloom water

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containing M. aeruginosa, Cyanobacteria was the most dominant phylum in the fresh

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sludge (without storage), accounting for 51.1±3.8% of the total effective bacterial

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sequences on average in the three systems. It was also found that Cyanobacteria were

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mainly composed by the genus Microcystis (Figure S4). Due to the damage known to

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occur to Cyanobacteria cells when sludge is stored for a period of time19, the relative

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abundance of Cyanobacteria may decrease with prolonged storage time. The result

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was also verified by the result of LEfSe (Figure S5), and detail analysis was shown in 12


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the SI. Furthermore, relative abundance of Cyanobacteria in AlCl3 sludge was 12.7%

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on the fourth day, which was lower than that in FeCl3 and PAFC sludges (24.7% and

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30.6%, respectively), and a similar trend was also found in the three systems after 8 d

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storage (Figure 3). These results also verified the changes in intracellular MCs and

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organic matter shown in Figure 1. Correspondingly, relative abundance of Firmicutes

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increased with prolonged storage time, and in AlCl3 sludge the increment was higher

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than that in FeCl3 and PAFC sludges. Relative abundance of the phylum

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Proteobacteria also increased during the first four days of storage, and in AlCl3

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sludge the increment was higher than that in FeCl3 and PAFC sludges. However,

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relative abundance of Proteobacteria in the three systems manifested no increment

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from days 4 to 8 and relative abundance of Proteobacteria in AlCl3 sludge even

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declined. This may be due to the lack of light and oxygen in the sludge, which is

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harmful to the growth of some photosynthetic bacteria (such as genus Rhodobacter)

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and strictly aerobic non-motile bacteria (such as genus Phenylobacterium) in phylum

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Proteobacteria. Furthermore, the detailed analysis about Proteobacteria was shown in

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Table S4 and SI.

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3.4 Potential function of dominant genera

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It is notable that there were a large proportion of sequences (17.1–54.8%) not

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assigned to any genera (Figure 4). With development of metagenome sequencing

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technologies, it may become possible to reconstruct the genome of the dominant or

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even minor species from the sludge communities in the future37. Sequences classified

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at genus level were compared using the Bray–Curtis similarity index. The values were

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then used to build a second dendrogram that was shown integrated with the heat map

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of the most abundant genera (Figure 4). The similarity between samples declined

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when going from higher to lower taxonomic levels. 13



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A total of 390 genera were classified among the test samples, and 24 genera were

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selected for comparison as given in the heat map (Figure 4). Eleven genera were

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abundant (>0.5%) in the sludges with Microcystis, Bacillus, Rhodobacter,

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Paenibacillus, Hydrogenophaga, and Alkaliphilus being the most dominant. Genus

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Microcystis within class Cyanophyceae was the most dominant in fresh sludge and

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decreased with prolonged storage time. It was also found that the rates of decline in

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AlCl3 sludges were higher than those in FeCl3 and PAFC sludges, consistent with the

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taxonomic composition distribution of phylum-level data in Figure 3. Meanwhile,

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genera Rhodobacter and Phenylobacterium within class Alphaproteobacteria and

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genus Hydrogenophaga within Betaproteobacteria class manifested similar trends of

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changes to those of Microcystis. For example, the abundance of Hydrogenophaga

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decreased from initial 4.84%, 3.76%, and 4.99% to 3.82%, 3.75% and 3.01% after 4 d

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storage, and then further declined to 1.57%, 2.43%, and 2.82% when stored for 8 d in

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AlCl3, FeCl3, and PAFC sludges, respectively (Figure 4). The relative abundance of

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these genera declined faster in AlCl3 sludge than in FeCl3 and PAFC sludges,

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consistent with the taxonomic composition distribution of phylum-level data in Figure

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3.

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As we know, Cyanobacteria are probably the largest, most diverse, and most

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widely distributed group of photosynthetic prokaryotes38. Hence, adequate light is

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needed for growth of genus Microcystis within phylum Cyanobacteria. Because the

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light was not sufficient in sludge, relative abundance of Microcystis declined and

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Microcystis cell damage with prolonged storage time. Similarly, relative abundance of

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the typically photosynthetic bacterium Rhodobacter28,39 also decreased and

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Rhodobacter cell may also damage with prolonged storage time. Eberspächer and

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Lingens40 reported that the Phenylobacterium genus from the family of 14


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Caulobacteraceae comprised gram-negative bacteria that may be typical inhabitants

348

of the upper aerobic part of the soil. Although different strains of Phenylobacterium

349

have been isolated from soil samples originating from various locations all over the

350

world, the breakdown of chloridazon, which is the active ingredient of the herbicide

351

Pyramin and is used for isolation of bacteria with the ability to grow on chloridazon as

352

the sole carbon source, in soil or in mud samples under anaerobic conditions failed,

353

meaning that the Phenylobacterium genus comprises strictly aerobic non-motile

354

bacteria. Yet dissolved oxygen concentration in the sludges was between 1.76-3.78

355

mg/L (Table S5), similar with the results of Tanaka et al.41, signifying that the

356

dissolved oxygen in the sludges was insufficient, thus explaining the decline of

357

Phenylobacterium abundance above (Figure 4). The genus Hydrogenophaga

358

comprises gram-negative, facultatively autotrophic hydrogen bacteria42, preferring

359

carboxylic acids and/or amino acids as growth substrates, but limited in the utilization

360

of carbohydrates and generally not hydrolyzing proteins, carbohydrates or fats43.

361

Despite DOC increased with prolonged storage (Table S3), carboxylic acids and/or

362

amino acids may be limited in sludges, thus explaining the decrease of

363

Hydrogenophaga abundance. In addition, because high concentration of Al in AlCl3

364

sludge was toxic to bacteria44, whereas in PAFC sludge low level of Al showed little

365

toxic effect on bacteria growth and moderate amount of Fe were beneficial to

366

growth19, the relative abundances of these genera decreased faster in AlCl3 sludge

367

than in PAFC sludge. As we know, high Fe levels are toxic to microorganisms, and

368

Wang et al.45 found that the species M. aeruginosa would clearly be inhibited when

369

the Fe concentration was higher than 1377 µg/L. However, relative abundance of the

370

dominant genera such as Microcystis and Rhodobacter in FeCl3 sludge did not exhibit

371

notable decrease as in AlCl3 sludge, and rather was similar to that in PAFC sludge. 15



Page 16 of 34

372

The reason may be the large size and high density of the flocculated sludge flocs in

373

FeCl3 sludge, which had a protective effect on the microorganisms19.

374

Correspondingly, the relative abundance of some genera such as Bacillus,

375

Paenibacillus,

Alkaliphilus,

Lactococcus,

Sporosarcina,

Enterococcus,

and

376

Brevibacillus increased with prolonged storage time, and relative abundance of these

377

genera increased faster in AlCl3 sludge than in FeCl3 and PAFC sludges. Among these

378

genera above, variation of relative abundances of Bacillus and Paenibacillus was the

379

most dramatic. Relative abundance of Bacillus increased obviously from the initial

380

2.94%, 10.58%, and 8.01% to 39.31%, 29.86%, and 20.85% in the three systems after

381

8 d storage, respectively. Similarly, the relative abundance of Paenibacillus also

382

increased substantially from initial 1.93%, 4.50%, and 2.46% to 19.13%, 13.60%, and

383

8.07% after 8 d storage in AlCl3, FeCl3, and PAFC sludges, respectively.

384

Increase of relative abundance of the genus Alkaliphilus may be due to the rise of

385

the sludge’s pH (Table S3), owing to the basophilia of Alkaliphilus genus. It is

386

extremely interesting to note that the other dominant genera including Bacillus,

387

Paenibacillus, Sporosarcina, Enterococcus, and Brevibacillus were classified as the

388

class Bacilli. Bacillus is the most common genus in class Bacilli, and almost

389

ubiquitous in nature. Bacillus species can be obligate aerobes or facultative anaerobes.

390

Young et al.46 found that Bacillus subtilis can biodegrade dissolved organic matter,

391

especially preferring to degrade lower-molecular-mass components. Paenibacillus is a

392

genus of facultative anaerobic bacteria, and has been detected in a variety of

393

environments, such as soil and sludge47,48. Furthermore, researchers also observed that

394

Paenibacillus can be grown on agar, which is a polysaccharide, as the carbon and

395

energy source49. Lactococcus is a genus of lactic acid bacteria and can produce a

396

single product, lactic acid in this case, as the major or only product of glucose 16


Page 17 of 34


397

fermentation. Because most species of Sporosarcina are facultative aerobic organisms,

398

they can perform metabolism in the absence of oxygen50. Some species, such as

399

Sporosarcina ureae, have the enzyme urease and are thus able to break down urea51.

400

Enterococcus is a facultative anaerobic organism, which can grow in both

401

oxygen-rich and oxygen-poor environments52, and can reduce nitroaromatics into

402

corresponding aromatic amines53. Manage et al.54 reported that the genus

403

Brevibacillus was able to degrade MCs as the carbon and energy source.

404

Remarkably, relative abundance of these genera rose faster in AlCl3 sludge than

405

in FeCl3 and PAFC sludges, owing to the higher levels of extracellular DOC and MCs

406

in AlCl3 sludge than those in FeCl3 and PAFC sludges, as shown in Figure 1 and

407

Table S3. Above all, the changes of bacterial community may be due to the

408

differences in environmental factors including DOC, MCs, Al, and Fe, with different

409

sludges and storage times (Table S3). Furthermore, the decrease of relative abundance

410

of Microcystis and other phototrophs (e.g., Rhodobacter), which was due to the lack

411

of light, also caused the increase of other microbes with prolonged storage time.

412

Because pathogenic microorganisms could cause serious harm to humans and the

413

ecology, the pathogens in sludge were investigated and Bacillus cereus within genus

414

Bacillus was assessed. Bacillus cereus is known to cause bacteraemia in

415

immunocompromised patients as well as symptoms such as vomiting and diarrhoea55.

416

It also causes food poisoning similar to that caused by Staphylococcus55. Relative

417

abundance of Bacillus cereus increased slightly from the initial 2.8% and 10.3% to

418

8.9% and 22.5% after 4 d storage in AlCl3 and FeCl3 sludges, respectively (Figure S6).

419

In PAFC sludge, relative abundance of Bacillus cereus decreased slightly from the

420

initial 7.8% to 5.9% when the sludge was stored for 4 d. However, relative abundance

421

of Bacillus cereus reached 38.5%, 27.6%, and 20.4% in AlCl3, FeCl3, and PAFC 17



Page 18 of 34

422

sludges, respectively, when the sludges were stored for 8 d (Figure S6). Bacillus

423

cereus was found in the cyanobacteria-laden drinking water sludge for the first time.

424

It has important reference and guidance for the detection of pathogenic

425

microorganisms in the related drinking water sludge. Many important clinical

426

infections including urinary tract infections, bacteraemia, bacterial endocarditis,

427

diverticulitis, and meningitis were caused by Enterococcus56. Although the genus

428

Enterococcus was found (Figure 4), the Enterococcus species was not identified.

429

There might be some pathogens belong to Enterococcus in the sludge and the species

430

in Enterococcus should be a subject of further investigation. In addition, Chao et al.28

431

found 6 genera of potentially pathogenic bacteria in drinking water biofilms

432

(Pseudomonas,

433

Streptococcus), which differs from our results. Firstly, this difference may be due to

434

the source water. For example, the pH and DOC of the raw water in our study were

435

8.46 and 3.16 mg/L, respectively, whereas, the pH and DOC were 7.3 and 1.9 mg/L in

436

Chao’s study28. Secondly, the biofilm in Chao’s study was formed in purified water

437

treated by conventional coagulation/sedimentation and disinfection, which could

438

remove some pathogens; those potentially pathogenic bacteria detected may be

439

relatively resistant to disinfection, such as the Mycobacterium that has been detected

440

in well-operated and -maintained drinking-water supplies with heterotrophic plate

441

counts less than 500/mL and total chlorine residuals of up to 2.8 mg/L55.

442

3.5 Relationship between environmental factors and bacterial community structure

Mycobacterium,

Legionella,

Brucella,

Clostridium,

and

443

To investigate the effect of water quality on the structure of bacterial

444

communities, relationship between some major genera and the environmental factors,

445

such as DOC and MCs, is presented in Figure 5. The increased relative abundance of

446

genera

Bacillus,

Paenibacillus,

Alkaliphilus,

Lactococcus,

18


Sporosarcina,

Page 19 of 34


447

Enterococcus, and Brevibacillus was consistent with the degraded DOC in AlCl3

448

sludge (Figure 5(a)), as these genera comprise heterotrophic bacteria and can use

449

organic matter to grow. We also found that the increased relative abundance of these

450

genera was not obvious when the AlCl3 sludge was stored for 4 d. In FeCl3 and PAFC

451

sludges, similar results were also found (Figure 5(b) and (c)). Interestingly, it is

452

notable that the increases in relative abundance of these genera in FeCl3 and PAFC

453

sludges were lower than that in AlCl3 sludge, which may be attributable to the DOC

454

in FeCl3 and PAFC sludges being less than that in AlCl3 sludge.

455

It has been reported that the genera Bacillus and Brevibacillus are

456

microcystin-degrading bacteria54,57,58, which increased with the increase of

457

extracellular MCs. The relationship between MC degradation and increase of the

458

genera Bacillus and Brevibacillus in AlCl3, FeCl3, and PAFC sludges with storage for

459

0, 4, and 8 d, respectively, was investigated (Figure 5(d)). The increased relative

460

abundance of genera Bacillus and Brevibacillus was in agreement with MC

461

degradation and the increases of genera Bacillus and Brevibacillus in AlCl3 sludge

462

was higher than those in FeCl3 and PAFC sludges after 8 d storage, which was

463

consistent with the degradation of MCs in the three systems (Figure 1).

464

This work shows that sludge systems share a characteristic profile at high

465

taxonomic rank observed in sludges with AlCl3, FeCl3, and PAFC coagulation, and the

466

most dominant phyla were Cyanobacteria, Proteobacteria, Firmicutes, Bacteroidetes,

467

Verrucomicrobia, and Planctomycetes. However, relative abundance of bacterial

468

communities was different, owing to different Al and Fe concentration in the three

469

systems. The dominant genera within class Bacilli, including Bacillus, Paenibacillus,

470

Lactococcus, Sporosarcina, Enterococcus, and Brevibacillus, increased with

471

prolonged storage time, especially after 4 d storage, whereas the other dominant 19



472

genera, such as Microcystis, Rhodobacter, Phenylobacterium, and Hydrogenophaga,

473

declined.

474

The lysis of Microcystis cells and other bacteria, such as Rhodobacter, in

475

drinking water sludge would result in the release of intracellular organic matter, which

476

could not only impose a burden on subsequent processes and production of toxic

477

disinfection byproducts, but also lead to growth of some bacteria. Even more

478

unhappily, some bacteria are pathogens, for example, Bacillus cereus. The damage of

479

Microcystis would lead to the release of many types of toxic compounds, such as MCs.

480

Fortunately, breakage of Microcystis cells was not serious, and the increase of relative

481

abundance of Bacillus cereus was not obvious when sludge was stored for 4 d. Hence,

482

the sludge should be treated or disposed of within 4 d. In addition, FeCl3 or PAFC

483

may be ideal coagulants, as the lysis of Microcystis cells was lower, and a similar

484

trend was also found for Bacillus cereus.

485

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Acknowledgements

655

This work was supported by the International Science & Technology

656

Cooperation Program of China (2010DFA91150), International Cooperation Research

657

of Shandong Province (2011176), National Science Fund for Excellent Young

658

Scholars (51322811), and The Program for New Century Excellent Talents in

659

University of the Ministry of Education of China (Grant No. NCET-12-0341), Natural

660

Science Foundation of China (51478251). The authors acknowledge Dr. David I.

661

Verrelli for revising the English in the manuscript.

662

Supporting Information

663

Details for cyanobacteria-laden drinking water sludge production and

664

storage, measurement of pH, DO, DOC, MCs, TN, TP, Al and Fe, and DNA

665

extraction, 16S rRNA gene PCR amplification and sequencing are available in the

666

Supporting Information. Six figures and five tables showing additional study details.

667

This information is available free of charge via the Internet at http://pubs.acs.org.

668

Conflict of Interest 27



669

The authors declare no conflict of interest.

670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692

28


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693

Table 1. MiSeq sequencing results and diversity estimates for each drinking water

694

sludge. Sample

695 696 697

a

Average sequencing results

Average diversity estimatesb

Total sequences Total OTUsa

Chao ACE Shannon Simpson

AC0

97448

646

710

738

2.65

0.30

AC4

100792

720

787

803

3.81

0.06

AC8

104681

572

643

656

2.90

0.18

FC0

85743

614

680

698

2.90

0.22

FC4

123366

660

727

747

3.29

0.12

FC8

136874

640

698

715

3.24

0.14

PC0

89981

547

615

635

2.56

0.27

PC4

94692

626

709

720

3.34

0.11

PC8

102534

738

806

825

3.92

0.06

Species level 97% similarity threshold used to define operational taxonomic units

(OTUs) b

Chao: Chao’s species richness estimator; higher number represents higher diversity.

698

ACE: abundance-based coverage estimator; higher number represents higher diversity.

699

Shannon: Shannon – Weiner diversity index; higher number represents higher

700

diversity. Simpson: Simpson’s diversity index; higher number represents lower

701

diversity.

702 703 704 29



705 706

Figure 1. Variation of (a) MCs concentration, and (b) DOC level in AlCl3, FeCl3, and

707

PAFC sludges after storage for 0, 2, 4, 6, 8, and 10 d. System A represents AlCl3

708

sludge; System B represents FeCl3 sludge; System C represents PAFC sludge. Data

709

are shown as the mean ±SD (N=3).

710 711 712 713 714

30


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715 716

Figure 2. Principle component analysis of bacterial community structures from the

717

nine different drinking water sludges with respect to the 6 measurable variables.

718

Arrows indicate the direction and magnitude of variables. AC0, AC4, and AC8

719

represent the sludges formed by AlCl3 and stored for 0, 4, and 8 d, respectively. FC0,

720

FC4, and FC8 represent the sludges formed by FeCl3 and stored for 0, 4, and 8 d,

721

respectively. PC0, PC4, and PC8 represent the sludges formed by PAFC and stored for

722

0, 4, and 8 d, respectively. AC0-2, AC4-2, AC8-2, FC0-2, FC4-2, FC8-2, PC0-2,

723

PC4-2, and PC8-2 were the biological replicates of them.

724 725 726 727 728

31



729 730

Figure 3. Percentages of the major phyla in each drinking water sludge, including the

731

biological replicates of them (AC0-2, AC4-2, AC8-2, FC0-2, FC4-2, FC8-2, PC0-2,

732

PC4-2, and PC8-2). AC0, AC4, and AC8 represent the sludges formed by AlCl3 and

733

stored for 0, 4, and 8 d, respectively. FC0, FC4, and FC8 represent the sludges formed

734

by FeCl3 and stored for 0, 4, and 8 d, respectively. PC0, PC4, and PC8 represent the

735

sludges formed by PAFC and stored for 0, 4, and 8 d, respectively.

736 737 738 739 740 741 742 743 744

32


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745 746

Figure 4. Heat map of the most abundant bacterial genera found in the drinking water

747

sludge samples, including the biological replicates of them (AC0-2, AC4-2, AC8-2,

748

FC0-2, FC4-2, FC8-2, PC0-2, PC4-2, and PC8-2). Cluster analysis was performed

749

using the Bray – Curtis similarity index. Longitudinal clustering indicates the

750

similarity of all species among different samples, and the horizontal clustering

751

indicates the similarity of certain species among different samples, the closer the

752

distance is and the shorter the branch length is, the more similar the species

753

composition is between the samples. AC0, AC4, and AC8 represent the sludges

754

formed by AlCl3 and stored for 0, 4, and 8 d, respectively. FC0, FC4, and FC8

755

represent the sludges formed by FeCl3 and stored for 0, 4, and 8 d, respectively. PC0,

756

PC4, and PC8 represent the sludges formed by PAFC and stored for 0, 4, and 8 d,

757

respectively. 33



758 759

Figure 5. The relationship between DOC degradation and the increase of average

760

relative abundance of some dominant bacteria in (a) AlCl3, (b) FeCl3, and (c) PAFC

761

sludges with storage for 0, 4, and 8 d, respectively; (d) the relationship between MCs

762

degradation and the increase of the genera Bacillus and Brevibacillus in AlCl3, FeCl3,

763

and PAFC sludges with storage for 0, 4, and 8 d, respectively.

34


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16S rRNA Gene Amplicon Sequencing Reveals Significant Changes

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