Multiple Transcriptional Mechanisms Collectively Mediate Copper

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Ecotoxicology and Human Environmental Health

Multiple transcriptional mechanisms collectively mediate copper resistance in Cupriavidus gilardii CR3 Ning Huang, Juan Mao, Yan Zhao, Mingzhong Hu, and Xiaoyu Wang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b06787 • Publication Date (Web): 28 Mar 2019 Downloaded from http://pubs.acs.org on April 1, 2019

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Environmental Science & Technology

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Multiple transcriptional mechanisms collectively

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mediate copper resistance in Cupriavidus gilardii CR3

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Ning Huang,† Juan Mao,‡ Yan Zhao,§ Mingzhong Hu,║ XiaoYu Wang, *, †,‡

4

†

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University, Changchun 130117, PR China

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‡

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Environmental Protection, Northeast Normal University, Changchun 130117, PR

8

China

9

§

Engineering Lab for Water Pollution Control and Resources, Northeast Normal

Key Laboratory of Wetland Ecology and Vegetation Restoration of National

School of Chemistry and Environmental Engineering, Changchun University of

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Science and Technology, Changchun 130022, PR China

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║

12

130012, PR China

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Abstract Bacteria resist copper (Cu) stress by implementing several metabolic

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mechanisms. However, these mechanisms are not fully understood. We investigated

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the mechanism of Cu resistance in Cupriavidus gilardii CR3, a Cu-resistant bacterium

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with a fully sequenced, annotated genome. The growth of CR3 was inhibited by

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higher Cu concentrations (≥1.0 mM) but not by lower ones (≤0.5 mM). CR3

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accumulated Cu intracellularly (ratios of intercellular to extracellular Cu were 11.6,

School of Chemical Engineering, Changchun University of Technology, Changchun

ACS Paragon Plus Environment

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4.24, and 3.9 in 0.1, 0.5, and 1.5 mM Cu treatments, respectively). A comparative

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transcriptome analysis of CR3 respectively revealed 310 and 413 differentially

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expressed genes under 0.5 mM and 1.5 mM Cu stress, most of which were

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up-regulated under Cu treatment. Gene Ontology and Kyoto Encyclopedia of Genes

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and Genomes functional enrichment analyses uncovered several genotype-specific

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biological processes related to Cu stress. Besides revealing known Cu

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resistance-related genes, our global transcriptomics approach indicated that sulfur

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metabolism, iron-sulfur cluster, and cell secretion systems are involved in mediating

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Cu resistance in strain CR3. These results suggest that bacteria collectively use

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multiple systems to cope with Cu stress. Our findings concerning the global

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transcriptome response to Cu stress in CR3 provide new information for

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understanding the intricate regulatory network of Cu homeostasis in prokaryotes.

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32

Introduction

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Copper (Cu) is the third most used metal in the world. Because it functions as a

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cofactor for enzymes involved in respiration in both prokaryotic and eukaryotic cells,

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Cu is an essential micronutrient. However, excess Cu is toxic to cells.1, 2 Cu can cause


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toxic effects on algae and fish or amphibians at as low as 5–10 ppb.3 Excessive Cu in

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the environment is due to industrial processes and agricultural activities, such as

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application of fertilizers, pesticides and herbicides.4 To survive in the presence of Cu,

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many bacteria have evolved an extensive network for Cu biosorption, transport, and

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intracellular distribution, allowing them to tolerate various extreme environments. The

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elucidation of bacterial Cu-resistance mechanisms is important for understanding how

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bacteria can be exploited for efficient bioremediation of Cu-contaminated sites.5, 6

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Previous studies have identified several resistance mechanisms in bacteria that

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can survive in Cu-rich environments, Such as extracellular sequestration, efflux,

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bioaccumulation, and transport mechanisms.7, 8 Under the extracellular sequestration

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scenario, extracellular polymeric substances (EPS) are secreted by cells, and

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functional groups in the cell wall can bind Cu ions to reduce the transportation of Cu

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inside the cell.9-14 Intracellular Cu-resistance mechanisms are more complicated

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processes that participate in efflux, bioaccumulation, and transport.8 From a molecular

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prospective, various copper gene clusters including cue, cus, and cop, have been

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identified from several different bacteria, e.g. Escherichia coli, Pseudomonas

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syringae, and Cupriavidus metallidurans CH34.15-17 The functions of some resistance

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genes have been elucidated. For example, cusCFBA in E. coli and copRSABCD in P.

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syringae encode Cu efflux operons,18,

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involved in multi-Cu oxidase activity to convert periplasmic Cu+ to less toxic Cu2+ in

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vivo.20 This multiplicity of resistance mechanisms serves as the basis for the use of

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bacteria in microbial bioremediation.21 Even though some mechanisms of Cu

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and cueO-controlled genes are primarily


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resistance have been revealed, however, the bacterial response to Cu stress is a very

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complex set of integrated processes and the details are largely unexplored.

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The genus Cupriavidus is known for its heavy metal resistance, especially against

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Cu.22, 23 This genus currently comprises 11 species.23-25 In particular, C. metallidurans

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CH34 exhibits periplasmic and cytoplasmic detoxification of Cu ions by

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copSRABCD, copI, and copF, as determined by both microarray and quantitative

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PCR methods.17 In our previous study, we reported the complete genome sequence of

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Cupriavidus gilardii CR326 (here after, CR3) and characterized its Cu response genes

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under 0.5 mM Cu stress27 and its application in Cu removal.28 Our study revealed that

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CR3 has distinctive genomic features compared with other heavy metal-resistant

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bacteria. In most bacteria, metal resistance genes are generally encoded in plasmid(s)

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or co-located in plasmid(s) and chromosomal DNA. CR3 has no plasmids, however,

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and all of its heavy metal resistance genes are encoded on its two chromosomes. This

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distinctive genomic feature of strain CR3 suggested that it may have unique heavy

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metal resistance mechanisms. Thus, CR3 was identified as a good candidate

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bacterium for studies on Cu resistance mechanisms.

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Detailed transcriptome analyses can provide insights into bacterial response to

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heavy metal stress.29 Current knowledge of bacterial Cu molecular resistance

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mechanisms is based on the results of studies using methods such as microarrays,

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real-time polymerase chain reaction, and gene mutation.17,

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methods can only be used to analyze known genes and pathways involved in bacterial

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response. The emerging technique of transcriptome sequencing (RNA-seq) is a more

30-32

However, these


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powerful tool to determine how an organism responds transcriptionally to a particular

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abiotic condition relative to transcriptional levels under normal physiological

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conditions. Thus, RNA-seq can extend the application of transcriptome studies to

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analyses of previously unidentified genes.33 To date, most RNA-seq studies on Cu

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stress responses have focused on eukaryotic organisms, for example Arabidopsis,

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grapevine, and hard-shelled mussel (Mytilus coruscus).34-36 Only one reported study

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has involved the use of RNA-seq to assess the stress response of prokaryotic cells

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(Pseudomonas aeruginosa),37 possibly because of the lack or incompleteness of

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reference genomes for Cu-resistant bacteria. A large number of differentially

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expressed genes (DEGs) were recently identified when C. gilardii CR3 was exposed

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to 0.5 mM Cu,27 but the Cu-resistance mechanisms and physiological changes of this

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strain were not explored.

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In this study, we used C. gilardii CR3 as a representative bacterium and

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examined its physiological changes under Cu stress by analysis of growth curves,

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measurement of extracellular biosorption and intracellular bioaccumulation, scanning

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electron microscopy (SEM) and confocal laser scanning microscopy (CLSM). We

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then used RNA-seq to elucidate the Cu-resistance mechanisms of CR3. Our aims were

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to explore: (a) the transcriptional responses of CR3 to Cu stress, (b) the pathways

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involved in Cu resistance, and (c) the connection between extracellular responses and

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the intercellular efflux system.

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Materials and Methods

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Microorganisms, media, and growth curves


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The CR3 strain of C. gilardii used in this study was isolated from a natural

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asphalt deposit, as reported in our previous study.26 The strain was cultivated at 30°C

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with shaking at 150 rpm in Luria Bertani (LB) medium (10.0 g tryptone, 5.0 g yeast

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extract, and 10.0 g NaCl per liter, pH 6.7).

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Growth curves for CR3 were obtained by growing cells in LB medium

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supplemented with different amounts of CuCl2 (0.1, 0.5, 1.0, and 1.5 mM). CR3

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grown in LB medium without Cu served as the control. Cells were incubated at 30°C

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on a shaker at 150 rpm for 144 h. OD600 values were recorded every 12 hours using a

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UV-visible spectrophotometer (Pgeneral T6, Beijing, China) and bacterial growth

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curves were constructed. Bacterial biomass can be correlated with optical density by

112

reference to a standard curve.38 The linear correlation between dry cell weight (DCW)

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(g l−1) and the OD600 of strain CR3 could be described by the following equation:

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DCW (g l−1) = 0.45848  OD600  0.00093 (with R2 = 0.99926). The OD600 was

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considered to represent bacterial biomass.

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Data were reported as mean values, with error bars representing the 95%

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confidence intervals around the average value. To identify the differences in growth

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curves under different Cu concentrations, a one-way analysis of variance with

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interaction was conducted using SPSS software (SPSS Inc., Chicago, IL, USA).

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Extracellular biosorption and intracellular bioaccumulation

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To determine the extracellular biosorption and intracellular bioaccumulation of

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Cu, CR3 was grown in LB mediaium (100 ml) containing 0 mM, 0.1 mM, 0.5 mM, or

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1.5 mM Cu at 30°C for 96 h. The culture was centrifuged at 12,000 g for 5 min. After


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washing three times with deionized water, the cell pellets were resuspended in

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5 mM sterilized EDTA at 25 °C and agitated at 150 rpm for 30 min to remove Cu ions

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adsorbed to the cell surface.39, 40 The supernatant was centrifuged at 10,000 g for

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5 min and then used to determine Cu concentration of extracellular biosorption by

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atomic absorption spectrometry (Shimadzu AA-6300, Kyoto, Japan). The cell pellets

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were dried at 85°C for 24 h, and their dry weights were determined.

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After dry weight measurements, the biomass was subjected to acid digestion

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using 70% trace metal-grade nitric acid (Fluka, Buchs, Switzerland) at 80°C for 30

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min and then cooled to room temperature. The concentration of Cu ions in the

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digested cell pellet represented the fraction of Cu bioaccumulated by the cells. The

134

amounts of Cu by extracellular biosorption (q), or intracellular bioaccumulation (q),

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are calculated on dry cell weight basis, respectively.41, 42 The formula is expressed as

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followed: q (mg g−1) = V·C/ m,

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concentrations (mg l−1), and m is dry weight biomass (g) respectively.

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RNA Extraction, library preparation, and RNA-Seq

where V is

the

sample

volume, C is

the

Cu

139

Transcriptome studies were carried out by selecting two concentrations based on

140

the CR3 growth rate at different Cu concentrations: one that affected bacterial growth

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(1.5 mM) and one that did not (0.5 mM). Free Cu served as the control. Three

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biological repeats were performed for each treatment; and nine samples in total were

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sequenced to RNA-Seq. CR3 cells were cultured in 100 ml LB medium to an OD600

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value of 0.2 and then exposed to 0, 0.5, and 1.5 mM Cu. The cells were allowed to

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continue growing to an OD600 value of 1.0, and 1 ml of bacterial culture was then


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collected and centrifuged. RNA extraction, library preparation, and RNA-Seq were

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performed as described in Supporting Information. Gene expression data were

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obtained and quantified as reads per kilobase of coding sequence per million reads.43

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Raw reads were submitted to the NCBI Sequence Read Archive under the accession

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number SRP154974.

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Transcriptome annotation and functional enrichment analyses

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Gene functional annotation was presented in Supporting Information.

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We used GOATOOLS to perform GO enrichment analysis of the DEGs44 and GO

terms

for

gene

functional

categorization.

KOBAS

154

obtained

155

(http://kobas.cbi.pku.edu.cn/home.do) was used for pathway enrichment analysis

156

based on the KEGG database, where ‘pathway’ was set as the basic unit. Terms with a

157

P-adj (corrected p-value) < 0.05 in the GO and KEGG enrichment analyses were

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considered to be enriched.

159

Quantitative

160

(qRT-PCR)

reverse

transcriptase-polymerase

chain

reaction

analyses

161

Eight DEGs related to Cu resistance (cysD, cusA, copS, copR, copA, copB, iscA,

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and gshA) were randomly selected for validation of the RNA-seq results by qRT-PCR.

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A detailed description of qRT-PCR, and selection of reference genes can be found in

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the Supporting Information (Table S1).45, 46

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Biofilm EPS composition analysis by SEM and CLSM

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According to the transcriptomic data, type III secretion system genes were

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up-regulated in C. gilardii CR3. To verify the occurrence of type III secretion on the


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surface of C. gilardii CR3 cells under Cu stress, SEM and CLSM were used to

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examine C. gilardii CR3 in the absence (control) and presence of different Cu

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concentrations (0.1, 0.5, and 1.5 mM) for 96 h. SEM was used to observe cellular

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surface changes under Cu stress, while CLSM was used to investigate changes in

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proteins and polysaccharides in biofilm EPS under different Cu conditions.47 SEM

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and CLSM were performed as detailed in Supporting Information.

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All experiments were performed in triplicate.

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RESULTS

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Effect of initial Cu concentration on growth

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The growth curves of CR3 at lower Cu concentrations (0.1 and 0.5 mM) were

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similar to the curve of CR3 in the control (0 mM Cu), with no significant differences

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observed in OD600 values (p > 0.05) (Figure 1). When the Cu concentration was

180

increased to 1.0 or 1.5 mM, the bacterial biomass sharply decreased and growth was

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significantly inhibited (p < 0.05). The maximum biomass obtained after 96 h of

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growth in the 1.0 and 1.5 mM Cu treatments was decreased by 41.2% and 45.2%,

183

respectively, compared with that of the control. According to these results, CR3

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growth was therefore inhibited by Cu at high concentrations (1.0 and 1.5 mM) but not

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at low Cu concentrations (0.1 and 0.5 mM) (Figure 1).


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Figure 1. Growth of Cupriavidus gilardii CR3 in culture medium supplemented with different concentrations of Cu.

Extracellular biosorption and intracellular bioaccumulation of Cu

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To understand the extra- and intracellular bioaccumulation of Cu, the

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bioaccumulation of Cu in C. gilardii CR3 at different Cu concentrations was

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determined. Extracellular biosorption increased from 3.66 mg g1 to 49.81 mg g1 and

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intracellular bioaccumulation increased from 42.46 mg g1 to 194.29 mg g1 as the Cu

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concentration increased from 0.1 mM to 1.5 mM (Figure 2). The analysis revealed

195

that intracellular Cu was more abundant, as the ratio of intercellular to extracellular

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Cu was 11.6, 4.24, and 3.9 in the 0.1, 0.5, and 1.5 mM Cu treatments, respectively.

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These results demonstrate the significantly higher capacity of CR3 for intracellular Cu

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bioaccumulation than for extracellular biosorption (p < 0.05) (Figure 2).


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Figure 2. Amount of copper (Cu) removed due to biosorption and bioaccumulation after culturing Cupriavidus gilardii CR3 in media with different Cu concentrations. Initial Cu concentrations were 0, 0.1, 0.5, and 1.0 mM. NA: not available.

Differential gene expression under Cu exposure as determined by RNA-Seq

204

To investigate genes associated with Cu stress responses in CR3, RNA-Seq was

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used for sequencing analysis. Details of the Illumina sequencing data for the nine

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tested samples are listed in Table S2. In total, 220 million raw reads (2.2 Gbps) were

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generated. After removing residual rRNA and low-quality reads, 216 million clean

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reads (2.16 Gbps) were obtained for further alignment and analysis. Out of all the

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RNA sequence reads, 94.2%–99.35% were mapped to the genome of CR3 (Table S2),

210

indicating that the sequencing data were completely reliable. The principal component

211

analysis showed good parallel correlations and obvious differences for each set

212

(Figure S1A).

213

Compared with CR3 in the control group, CR3 treated with 0.5 mM or 1.5 mM

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Cu showed strong responses at the transcriptome level (Figure S1B). In total, 310

215

genes (302 up- and 8 down-regulated) and 413 genes (380 up- and 33 down-regulated)


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were significantly differentially expressed (FDR < 0.05, |log2FC|  1) by 0.5 mM and

217

1.5 mM Cu, respectively (Figure S1B). The overall expression profile of the DEGs

218

was analyzed by hierarchical clustering (Figure S1C). The resulting heatmaps were

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largely indistinguishable between libraries from the same treatment, but large

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differences were observed in transcript expressions between Cu stress treatments and

221

the control (Figure S1C). The differential expression between 0.5 mM and 1.5 mM Cu

222

stress was not significant.

223

To validate the RNA-seq results, eight genes differentially expressed in response

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to Cu treatment were randomly selected for qRT-PCR analysis. In seven of these eight

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genes, the expression fold changes in strain CR3 were in good agreement between

226

RNA-seq and qRT-PCR (Table S3). The exception was the iscA gene, where the

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log2FC was 2.92 according to RNA-seq vs. 0.295 by qRT-PCR (Table S3). A

228

significant correlation was observed between the RNA-Seq and qRT-PCR data (R2 =

229

0.858, p < 0.001), thus indicating that the RNA-Seq data were reliable (Figure S2).

230

GO and KEGG functional enrichment analyses of DEGs

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To determine the possible metabolic pathways affected by Cu stress in CR3, GO

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and KEGG pathway enrichment analyses were performed on the set of identified

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DEGs (P-adj < 0.05). The enrichment analysis of GO terms classified the genes into

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two functional categories: biological process and molecular function (Figure 3). In

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total, 14 and 13 GO terms were significantly overrepresented at 0 vs. 0.5 mM and 0 vs.

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1.5 mM Cu, respectively (Figure 3). Thirteen enriched GO terms were similar

237

between the two levels of Cu stress. A little exception was oxidoreductase activity


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(GO:0016667), which was enriched by 0.5 mM Cu but not 1.5 mM Cu. The 13 GO

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terms included four Cu ion binding or transporter homeostasis terms (GO:0005507,

240

0006878, 0055070, and 0006825); five sulfur compound transport or transporter

241

activity terms (GO: 1902358, 0015116, 0008272, 001541, and 1901682), two

242

metallo-sulfur or iron-sulfur (Fe-S) cluster assembly terms (GO: 0031163 and

243

0016226), one inorganic anion transmembrane transport term (GO:0098661), and one

244

metal ion binding term (GO: 0046914, 0005507) (Figure 3).

245 246 247 248 249 250 251 252

Figure 3. GO functional enrichment scatter diagram of Cupriavidus gilardii CR3 after exposure to different concentrations of copper (Cu). GO functional enrichment was represented by an enrichment factor, the P-value, and the number of unigenes enriched (enrichment factor is ratio of numbers of differentially expressed genes annotated in a particular pathway term to numbers of all genes annotated in this pathway term). Names of GO functional enrichment classes are listed along the y-axis. P-adj ranged from 0 to 0.05, with a P-adj closer to 0 indicateing greater enrichment.

253

According to the KEGG enrichment results, four pathways were significantly

254

enriched after 0.5 mM Cu treatment (Table 1): sulfur metabolism, bacterial secretion

255

system, seleno-compound metabolism, and the two-component system (P-adj < 0.05).

256

The sulfur metabolism pathway was significantly enriched after 1.5 mM Cu treatment

257

(P-adj < 0.001), and the bacterial secretion system and two-component system were


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also enriched, with significant uncorrected p-values (p < 0.05) (Table 1). Thus, Cu at

259

different concentrations induced similar transcriptional responses in CR3. Pathways

260

associated with Cu resistance, sulfur metabolism, Fe-S cluster assembly, and cell

261

secretion system were significantly enriched under Cu stress, which suggests that they

262

play important roles in Cu resistance.

263 264 265

Table 1. Enrichment of KEGG pathways in Cupriavidus gilardii CR3 exposed to copper (Cu) (0.5 mM and 1.5 mM) compared with a non-Cu control. P-adj < 0.05 indicates significant enrichment. pathway

KEGG Id

0.5 mM

1.5 mM

Adjusted p-value

Adjusted p-value

Sulfur metabolism

ko00920

6.56E-05

2.21E-07

Bacterial secretion system

ko03070

0.006905

0.188

Two-component system

ko02020

0.032918

0.146

Selenocompound metabolism

ko00450

0.021674

0.682

266

Cu resistance genes exhibited the biggest response to both concentrations of Cu.

267

Most genes (31 for 0.5 mM Cu and 35 for 1.5 mM Cu) showed significant

268

up-regulation under Cu stress (FDR < 0.05). These DEGs included five putative Cu

269

resistance

270

copKHFIDCBARS, cusFABgene1401, and merRcopAcopZ (Table S4). Cu resistance

271

genes that were induced under Cu stress in CR3 encoded proteins that are involved in

272

the two-component signal system (copRS), copper efflux system (cusFABgene1401),

273

copper binding (copK, copI, copZ, and copH), copper ion transport (copB and copD),

274

and multicopper oxidase (copA).

275

gene

clusters:

copSRABCD,

copQLFGJIDCBARS_ompC_copKBA,

GO and KEGG analyses indicated that sulfur metabolism was enriched under Cu


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stress (24 and 20 genes were up-regulated by 0.5 mM and 1.5 mM Cu, respectively;

277

Table 1 and Figure 3). At both concentrations, Cu induced significant up-regulation of

278

genes encoding proteins in sulfur assimilation pathways, including cysPUWA, cysND,

279

cysH, cysI, ssuP, and tauD. Additionally, genes encoding proteins involved in

280

glutathione29 biosynthesis (gshA, gshB, and E1.11.1.9), tyrosine metabolism (fahA and

281

hmgA) and the biosynthesis of phenylalanine (phhA and paaA), glutamate (putA), and

282

glycine (betA) were significantly up-regulated in CR3 treated with Cu at 0.5 mM and

283

1.5 mM (Table S4), supporting their involvement in the Cu detoxification response.

284

The GO analyses also revealed that some of the DEGs in CR3 treated with Cu at

285

0.5 mM and 1.5 mM were enriched in pathways related to Fe-S clusters (GO:0016226)

286

(Figure 3). Further analyses of our RNA-seq data revealed that Cu supplementation

287

resulted in significant up-regulation of the isc operon (iscRSU-iscA-hscBA), which

288

drives the synthesis of Fe-S clusters (9 and 10 genes up-regulated by treatment with

289

0.5 mM and 1.5 mM Cu, respectively) (Table S4).

290

Two cell secretion systems, type II secretion system (T2SS) and type III

291

secretion system (T3SS), were detected in strain CR3. Interestingly, the T3SS in CR3

292

was significantly induced under 0.5mM Cu stress (ko03070) (p < 0.01) (Table 1),

293

whereas the T2SS was not. These results suggest that Cu may affect EPS secretion

294

and the cell membrane via the T3SS.

295

Characterization of extracellular Cu in CR3

296

The SEM analyses revealed the mucous nature of the EPS surrounding bacterial

297

cells and biofilm. The EPS on the cell membrane surface was significantly thicker in


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the 0.1mM Cu treatment than in the control (Figure 4a, b); in the 0.5 mM Cu

299

treatment, however, the EPS was very similar to that in the control (Figure 4c). In the

300

1.5 mM Cu treatment, cell surface secretion was significantly reduced and the biofilm

301

was affected (Figure 4d), which suggests that Cu affects cellular activity. The EDS

302

analysis revealed two additional Cu signals in the EDX spectrum following Cu stress

303

(Figure 4e, f), indicating that the cell surface bioaccumulated Cu.

304 305 306 307 308

Figure 4. Scanning electron micrographs and energy dispersive X-ray spectrographs of Cupriavidus gilardii CR3 exposed to different concentrations of copper (Cu). (a) 0 mM Cu; (b) 0.1 mM Cu; (c) 0.5 mM Cu; (d) 1.5 mM Cu; (e) 0 mM Cu (control); (f) 0.1 mM Cu (treated).

309

The ratio of protein and polysaccharide in biofilm EPS was determined by

310

CLSM after 96 h exposure to different Cu concentrations (Figure S3). In the biofilm

311

without any Cu exposure, the ratio of protein to polysaccharide was 0.15 ± 0.04, and

312

the composition of the biofilm EPS was mainly polysaccharides (Figure S3A). In

313

biofilm under exposure to various Cu concentrations, ratios of protein to

314

polysaccharide were 1.52 ± 0.49, 0.38 ± 0.14 and 0.93 ± 0.38 for 0.1, 0.5, and 1.5 mM


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Cu treatments, respectively (Figure S3B, C, D), which were significantly higher than

316

the ratio in the absence of Cu treatment (t-test, p < 0.05). These results demonstrate

317

that Cu stimulated the more secretion of extracellular protein.

318

DISCUSSION

319

The goal of this work was to obtain a global description of bacterial Cu

320

resistance response mechanisms under Cu stress. The RNA-seq analyses showed that

321

Cu at both tested concentrations led to transcriptional changes in CR3 (302 up- and 8

322

down-regulated and 380 up- and 33 down-regulated genes in 0.5 mM and 1.5 mM Cu

323

Cu2+ treatments, respectively). In a previous study, 293 up- and 126 down-regulated

324

genes were detected in response to 0.5 mM Cu in P. aeruginosa.37 Although there

325

were a similar number of DEGs under Cu stress in the two bacteria, the transcriptional

326

results for P. aeruginosa did not exhibit significant enrichment of particular metabolic

327

pathways. However, analyses of CR3 revealed significant enrichment of several GO

328

and KEGG pathways under Cu stress, including Cu resistance genes, sulfur

329

metabolism, Fe-S cluster assembly, and bacterial secretion systems. The results

330

suggest that these metabolic pathways respond to Cu and affect how the bacterium

331

tolerates Cu stress.

332

Cu resistance-related genes

333

Cu resistance genes are important for bacterial persistence in Cu-contaminated

334

areas. In our study, many virulence genes were up-regulated in CR3 under Cu stress.

335

In particular, the expression levels of genes encoding copABCD, copGDCBARSKB,


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and copKDCBARS were increased 2.95- to 12.98-fold in this study (Table S4), much

337

higher than the up-regulation of copRS, copA1, copZ1, and copZ2 reported in P.

338

aeruginosa under 0.5 mM CuSO4 stress (1.79- to 3.95-fold).37 This difference

339

indicates that Cu resistance genes have a stronger transcriptional response in CR3

340

than in P. aeruginosa. Two-component regulatory systems (copRS) can detect elevated

341

levels of Cu ions outside the cytoplasm and are involved in the regulation of Cu

342

homoeostasis genes.48 Such a system was first described in P. syringae49 and has now

343

been identified and characterized in a variety of bacteria. The Cu efflux system is

344

responsible for acquiring Cu(I) ions from the cytoplasm and facilitating their efflux

345

into the periplasmic space.50 A Cu-transporting ATPase transports a significant

346

proportion of internal Cu across cell membranes. Cu-binding proteins can bind Cu(I)

347

or Cu(II) at different sites,51-54 and multicopper oxidase can oxidize Cu+ to the less

348

toxic Cu2+.16 These pathways were enriched by Cu in CR3, suggesting that enhanced

349

Cu transport led to an increase in Cu efflux out of the cell and maintenance of Cu

350

homeostasis to resist Cu toxicity. This multi-pronged approach would allow the

351

bacterium to survive in areas contaminated with high concentrations of Cu and helps

352

to explain why CR3 can grow normally in the presence of 0.5 mM Cu2+. In contrast,

353

non-resistant bacteria show decreased microbial growth in response to Cu at lower

354

concentrations; for example, 16 μM in E. coli, 9 ppm in Desulfovibrio sp., and 100

355

mg dm3 in Rhizopus arrhizus.55-57

356

Sulfur metabolism

357

As a vital element for all living organisms, sulfur is required for the synthesis of


18

Page 19 of 30


358

proteins and essential cofactors.58 In our study, the enrichment of genes involved in

359

sulfur assimilation suggested the important role of this process in Cu detoxification.

360

Sulfate assimilation pathway genes that were highly expressed in the presence of Cu

361

encode a key enzyme in cysteine biosynthesis (PAPS),59,

362

(CysHIJ),59 and enzymes involved in GSH precursor synthesis (Figure 5, Table S4).

363

Sulfur and cysteine have been previously reported to participate in Cu detoxification

364

in microorganisms.32, 61 For instance, Camila et al. conducted microarray analyses and

365

found that cysD, cysI, and cysN were up-regulated under 325 mM Cu stress in

366

Acidithiobacillus ferrooxidans strain D2.61 cysDN encode ATP sulfurylase which

367

converts sulfate to adenosine 5-phosphosulfate (APS),62 while cysI encodes an

368

iron-sulfur protein that uses a siroheme cofactor to reduce sulfite to sulfide.63 Garrett

369

et al. detected significant up-regulation of the M. sedula cysNHI operon in the

370

presence of 4 or 8 mM Cu, but this operon was not up-regulated by other metal

371

stimuli. 32

60

sulfite reductase

372

Sulfate assimilation pathways also provide sulfate for the synthesis of GSH,

373

glycine, and tyrosine.64 GSH is composed of a tripeptide of L-cysteine, L-glutamate

374

and glycine,65 which is able to chelate metal ions and thus increase organism

375

resistance to heavy metals.66, 67 Previous studies have extensively revealed the roles of

376

GSH in enhancing resistance to heavy metals in yeast and plant cells.64, 68-70 However,

377

there are fewer studies investigating the roles of GSH in binding Cu in bacteria. Miras

378

et al. have posited that GSH increases intracellular accumulation of Cu and proposed

379

that Cu binds to GSH and various thiol-rich proteins in E. coli.71 In this study, we


19


Page 20 of 30

380

found that genes encoding proteins involved in GSH biosynthesis (gshA, gshB, and

381

E1.11.1.9) were significantly up-regulated in CR3 under Cu stress (Figure 5, Table

382

S4), which provides transcriptional evidence that GSH is involved in the Cu resistance

383

of C. gilardii CR3. Chelation with Cu during the process of GSH detoxification might

384

be responsible for the higher intracellular bioaccumulation of Cu in CR3. The

385

up-regulation of genes, including those related to tyrosine metabolism (fahA and

386

hmgA), methionine (msrA), and the biosynthesis of phenylalanine (phhA and paaA),

387

glutamate (putA), and glycine (betA), also contribute to the bioaccumulation of Cu in

388

CR3. These genes are all involved in the biosynthesis of Cu-resistance genes (copCD,

389

azurin) associated with binding to Cu2+ or Cu+ in cells.48 According to our study

390

results, transcription under Cu stress can be linked to the higher intercellular

391

bioaccumulation of Cu.

392

Iron-sulfur clusters

393

In organisms, Iron-sulfur clusters (Fe-S) play an important role in the growth,

394

respiration, and metabolism, such as DNA repair, gene regulation, biosynthetic

395

pathways, and aerobic and anaerobic respiration.72,

396

generally bind Fe, but may bind Cu if Cu replaces Fe in the Fe-S cluster by occupying

397

the cysteine-thiolate donor positions.55 This binding promotes the accumulation of Cu

398

in the cell. Genes encoding Fe-S clusters and cysteine biosynthesis proteins are

399

up-regulated in Bacillus subtilis under Cu stress; the higher Fe-S cluster and cysteine

400

contents would help to complex intracellular Cu, hence decreasing its toxic effect.73, 74

401

In present study, GO and KEGG analyses revealed that genes in the Fe-S cluster

73

Fe-S assembly systems


20

Page 21 of 30


402

assembly system were significantly enriched under Cu stress (Figure 3, Table 1), thus

403

indicating that our results are consistent with those of the previous study. The

404

up-regulation of Fe-S cluster genes therefore partly contributed to the higher observed

405

intracellular accumulation of Cu in CR3.

406

Cell secretion system

407

To our surprise, we observed significant enrichment of genes encoding

408

components of the T3SS in CR3 cells grown in the presence of Cu. The T3SS can

409

secrete substrate proteins into the extracellular environment and translocate effector

410

proteins to the inside of eukaryotic cells via a syringe-like needle apparatus that

411

extends from the bacterial surface.75 Previous studies on Xanthomonas citri have

412

shown that the T3SS is essential for bacterial biofilm formation.76 The lack of the

413

T3SS led to altered expression of proteins involved in metabolism, energy, EPS, and

414

cell motility.76 In our SEM analyses, we observed a similar morphological distribution

415

of EPS between the 0.5 mM Cu treatment and the control (Figure 4), which suggests

416

that the cellular secretion system might stimulate a compensatory mechanism to

417

counteract the toxicity induced by 0.5 mM Cu. At the same time, the CLMS analysis

418

showed that protein secretion in CR3 biofilm EPS increased significantly after Cu

419

treatment (Figure S3). Some studies have demonstrated that Cu directly affects the

420

cellular activity and extracellular secretions of bacteria,77,

421

proteins may be directly involved in heavy metal resistance by enhancing

422

biosorption79-85.

423

Gram-negative bacteria.

However,

surface

display

systems

78

and that cell surface

vary

among

different


21


Page 22 of 30

424

A role for the secretory system to counter heavy metal stress has been rarely

425

reported. In a recent study of the pathogenic bacterium Edwardsiella tarda, Cu stress

426

inhibited the expression of genes encoding components of the T3SS, resulting in

427

reduced biofilm growth and host cell adhesion.86 Our results are inconsistent with

428

those for E. tarda, genes encoding components of the T3SS were up-regulated in CR3

429

under Cu stress. This opposite results might be due to the fact that strain CR3 is a

430

typical Cu-resistant bacterium, suggesting that the T3SS probably contributes to Cu

431

resistance. An elevated Cu concentration in the external environment may stimulate

432

the T3SS in CR3, resulting in increased secretion of EPS and the adsorption of Cu

433

ions to the cell surface to prevent entry of Cu into the cell. To our knowledge, T3SS

434

involvement has not been reported in any Cu-resistant bacterium. Hence, more studies

435

are needed to verify whether the T3SS in Cu-resistant bacteria plays a role in Cu

436

resistance processes in the future.

437

Multifaceted response of CR3 to Cu exposure

438

Overall, our transcriptome analysis linked the observed physiological effects

439

under Cu stress and revealed that the resistance of CR3 to Cu is a multi-system

440

collaborative process (Figure 5). We found that CR3 exhibits four significant

441

mechanistic responses to Cu stress: Cu resistance gene expression, as well as

442

activation of the Fe-S assembly system, sulfur metabolism, and the cell secretion

443

system. Together, these responses allow CR3 to achieve a relatively stable cellular

444

environment for survival. Under excess Cu stress, genes in the cell secretion system

445

are up-regulated, and this stimulates the production of proteins on the cell surface.


22

Page 23 of 30


446

Although extracellular proteins can enhance Cu adsorption and prevent Cu from

447

entering the cell, excessive Cu can still be transported into cells and trigger

448

up-regulated expression of Cu resistance genes. The up-regulation of Cu resistance

449

genes leads to an increase in the efflux of intercellular Cu into the periplasmic space.

450

The sulfur metabolism system is also highly expressed. The sulfur metabolism

451

pathway is closely related to the biosynthesis of cysteine and GSH, which are related

452

to the chelation and detoxification of Cu ions.32, 61, 71 We therefore infer that sulfur

453

metabolism plays an vital role in the Cu resistance process. Strong expression of the

454

Fe-S assembly system under Cu stress possibly means that Cu ions can bind to Fe

455

binding sites to achieve Cu chelation. Collectively, the results of our combined

456

transcriptome and physiological analyses provide a better understanding of the Cu

457

resistance and response mechanisms of bacteria.

458


23


459 460 461 462 463

Page 24 of 30

Figure 5. Proposed model for resistance response mechanisms of Cupriavidus gilardii CR3 to copper (Cu) stress and C. gilardii survival strategies. Colored text indicates genes that are highly up-regulated under Cu stress: Cu-resistance genes (mustard green), sulfate assimilation pathway genes (purple), iron-sulfur cluster genes (green), Type III secretion system genes (orange), and genes encoding GSH and related enzymes (red).

464

AUTHOR INFORMATION

465

Corresponding Author

466

* Phone: +86 13504403055; E-mail: [email protected];

467

Notes

468

The authors declare no competing financial interest.

469

ACKNOWLEDGMENTS

470

This work was funded by the National Natural Science Foundation of China (no.

471

51678122) and the Jilin Provincial Science and Technology Department Project (no.

472

20150414046GH). We also thank Dr. Yanhong Xiao, Experimental Center of the

473

School of the Environment, Northeast Normal University, for her assistance with

474

primer design.

475

Supporting Information Available

476

RNA Extraction, library preparation, and RNA-Seq; Transcriptome annotation;

477

Quantitative reverse transcriptase-polymerase chain reaction analyses (qRT-PCR);

478

Scanning electron microscope-energy dispersive spectroscopy analyses; Biofilm

479

composition determination by confocal laser scanning microscopy (CLMS);

480

Transcriptome analysis of Cupriavidus gilardii CR3 in response to different

481

concentrations of copper (Cu) (0, 0.5, and 1.5 mM) (Figure S1); Correlation between


24

Page 25 of 30


482

RNA-Seq and qRT-PCR for the eight selected genes (Figure S2); CLSM images of

483

Cupriavidus gilardii CR3 exposed to different concentrations of copper (Cu) (Figure

484

S3) (PDF)

485

The list of primers used for qRT-PCR (Table S1), sequencing and assembly statistics

486

for the nine transcriptome data of copper treatment and control group(Table S2), the

487

data of RNA-Seq and qRT-PCR for the selected eight genes (Table S3) and list of

488

DEGs belonging to copper resistance mechanism (Table S4) were provided in Excel,

489

and separately (XLS)

490

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

491

REFERENCES

492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514

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Multiple Transcriptional Mechanisms Collectively Mediate Copper

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