An Integrated Quantitative and Targeted Proteomics Reveals Fitness

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An Integrated Quantitative and Targeted Proteomics Reveals Fitness Mechanisms of Aeromonas hydrophila under Oxytetracycline Stress Xiangmin Lin,*,†,‡,¶ Ling Lin,†,‡,¶ Zujie Yao,†,‡ Wanxin Li,†,‡ Lina Sun,†,‡ Danfeng Zhang,⊥ Ji Luo,§ and Wenxiong Lin*,†,‡ †

Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, PR China ‡ Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou 350002, PR China § AB Sciex Co. Ltd., Shanghai 200233, PR China ⊥ School of Biological Sciences and Biotechnology, Minnan Normal University, Zhangzhou 363000, PR China S Supporting Information *

ABSTRACT: To date, above ten thousand tons of antibiotics are used in aquaculture each year that lead to the deterioration of natural resources. However, knowledge is limited on the molecular biological behavior of common aquatic pathogens against antibiotics stress. In this study, proteomics profiles of Aeromonas hydrophila, which were exposed to different levels of oxytetracycline (OXY) stress, were displayed and compared using iTRAQ labeling and SWATH-MS based LC−MS/MS methods. A total 1383 proteins were identified by SWATH-MS method, and 2779 proteins were identified from iTRAQ labeling samples. There are 152 up-regulated and 52 downregulated proteins overlapped in 5 μg/mL OXY stress and both 83 up- and down-regulated proteins overlapped in 10 μg/mL OXY stress in both methods, respectively. Results show that many protein synthesis and translation related proteins increased, while energy generation related proteins decreased in OXY stress. The varieties of selected proteins involved in both pathways were further validated by sMRMHR, q-PCR, and enzyme activity assay. Furthermore, the concentrations of NAD+ and NADH were measured to verify the characteristic of energy generation process in OXY stress and OXY resistance strain. We demonstrate that the down-regulation of energy generation related metabolic pathways and up-regulation of translation may play an important role in antibiotics fitness or resistance of aquatic pathogens. KEYWORDS: Oxytetracycline, Aeromonas hydrophila, quantitative proteomics, antibiotics stress

1. INTRODUCTION Aeromonas hydrophila is one of the most common aquatic pathogens that causes significant harm to the normal cultured fishes. To control the loss, different types of antibiotics, such as oxytetracycline (OXY), sulfonamides, penicillin, cephalosporins, and β-lactams are widely used to treat the infected fishes.1−5 As a result, the multidrug resistance of A. hydrophila is becoming more and more serious, which severely influences the quality and safety of aquatic animal source foods and thereby finally threatens human life and health directly. However, the understanding of the mechanisms underlying functional changes in A. hydrophila to date in response to antibiotics remains limited.6 Thus, the study on the fish-origin A. hydrophila and its stress valuation against the treatment of antibiotics will help to prevent the potential of bacterial resistance and provide guidance for proper usage of drugs in the future. Proteomics technique is a promising strategy to investigate bacterial behavior in antibiotics stress.7,8 Generally, two-dimensional © XXXX American Chemical Society

gel electrophoresis (2DE) was used as a typical proteomics method to rapidly separate and compare differential expression proteins in adaptive or intrinsic resistance stress.9−12 However, because of the significant intrinsic limitations, such as low throughput, high load amount, poor separation of hydrophobic proteins, and identification of low abundant protein, 2DE is seriously challenged by a blossoming of new proteomics techniques. Many relative or absolute quantitation methods, such as label-free, SILAC, ICAT, isobaric tags for relative and absolute quantitation (iTRAQ), TMT, and sequential windowed acquisition of all theoretical fragment ions (SWATH), are rapidly developed and some of them, such as iTRAQ and label-free, are more popularly applied to discover the resistance mechanism in bacterium such as Staphylococcus aureus, Stenotrophomonas maltophilia, Acinetobacter baumannii, and Escherichia coli in Received: November 18, 2014

A

DOI: 10.1021/pr501188g J. Proteome Res. XXXX, XXX, XXX−XXX

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Journal of Proteome Research

ensure the equal proteins amount.23 About 250 μg of protein of each group was digested at 1:50 using filter-aided sample preparation (FASP) method following DTT reduction, IAA alkylation, and then trypsin digestion as previously described.24 After being washed three times with 0.5 M triethylammonium bicarbonate buffer (TEAB) pH 8.5 using 10 kDa cutoff filter (Millipore, Billerica, MA, USA), 100 μg of digested peptide of each group was taken out for further iTRAQ labeling as in our previous study.25 The labeling scheme was A. hydrophila in LB medium without OXY as 114 and 115, with 5 μg/mL OXY as 116, and with 10 μg/mL OXY as 117. Labeled peptides were separated to 10 fractions using RP HPLC at high pH to increase peptide and protein identification following the protocol described previously.26

oxacillin, imipenem, carbapenem, and chlortetracycline stress or resistance.13−15 The importance to combine multiple quantitative proteomic approaches to obtain more reliable results for bacterial antibiotics resistance or adaptation understanding is highlighted.16 Normally, the differential expression proteins are compared by quantitative proteomic methods and then validated by immunoassays. However, the Western blotting or ELISA procedure must be laborious and time-consuming in the antibodies preparation and the purification of target proteins. Furthermore, the specificity of antibody to targeted protein is always a challenge especially for posttranslational modification (PTM) of specific sites such as phosphorylation modification.17 Thus, a highthroughput, reproducible and multiplex-capable method is required for further expediting the evaluation process. Targeted proteomics strategies, based on multiple-reaction monitoring (MRM) or parallel reaction monitoring (PRM) assays, for example, are developed with mass spectrometry (MS) and have enabled the quantitative analysis of hundreds of proteins at a time that have been applied to the evaluation of clinical biomarker in recent studies.18,19 Recently, a scheduled high-resolution MRM (sMRMHR) method was reported as a highly specific method of protein detection allowing the combined acquisition of selective peptide precursor masses at high accuracy in the same run, which suggests its potential application in biomarkers detection and proteins validation.20 In this study, iTRAQ labeling and SWATH-MS based proteomics methods were performed to compare differential expression proteins of A. hydrophila in different doses of OXY treatment. Interested candidate proteins were selected to further validate by sMRMHR and qPCR assay. The whole validation process only takes several hours instead of at least two months with immunoassays. In this way, our research demonstrates the effect and mechanism of antibiotics stress on A. hydrophila through multiple researching technology platforms.

2.3. iTRAQ and SWATH Quantification Using TripleTOF 5600+

Digested directly or labeled peptides were analyzed by AB Sciex TripleTOF 5600 plus mass spectrometer (AB SCIEX, Concord, ON, USA) with an Eksigent nanoLC-Ultra 2D System combined with the cHiPLC-nanoflex system as previously described.27 Briefly, peptides were loaded on the cHiPLC trap (200 μm × 500 μm ChromXP C18-CL, 3 μm, 300 Å) first and then separated using a Nano cHiPLC column (75 μm × 15 cm ChromXP C18-CL 3 μm 120 Å) with a 60 min 2−98% ACN/ water gradient containing 0.1% formic acid at a constant flow rate of 300 nL/min. Eluant from the Nano cHiPLC column was further analyzed using the nanospray source on a TripleTOF 5600 system. For iTRAQ labeling identification and quantification, all ions were operated in the positive ion mode with ion spray voltage of 2.3 kV, an ion source temperature of 150 °C, a GS1 setting of 4, and curtain gas 30. Q1 was scanned from 400−1000 m/z, and MS/MS was followed by 30 product ion scan, with accumulation time of 100 ms per MS/MS with range from 100−1500 m/z. For targeted quantitation using MS/MSALL with SWATH acquisition, SWATH acquisition method was used where Q1 was followed by 40 product ion scan with accumulation time of 0.5 ms per MS/MS. Q1 was scanned from 350−1500 m/z, and MS/MS was acquired from 100−1500 m/z. Fragmentation data were interpreted by Proteinpilot 4.0 against the Aeromonas hydrophila database (download from TrEMBL database with 45 136 unreview sequences on Feb 1, 2014), and protein identifications were filtered by Paragon algorithm with following search parameters: cysteine alkylation setting was iodoacetamide, trypsin as enzyme, ID focused on biological modification and amino acid substitutions; the instrument was AB 5600 plus; bias correction and background correction were set to normalize the data; detected protein threshold was 0.05. The false discovery rate (FDR) analysis of the results was provided by Proteomics Performance Evaluation Pipeline Software (PSPEP) based on a decoy database of reverse sequences as Proteinpilot software suggested. For iTRAQ quantitation, sample type was set as iTRAQ 4plex (peptide labeled), and the group file was loaded into the MS/MS with SWATH Acquisition MicroApp in PeakView for SWATH quantitation. The protein confidences by iTRAQ labeling and SWATH quantitative methods were performed using a confidence threshold of 99% with a highly conservative threshold (fold change ⩾2.0 or ⩽0.5, FDR < 1%). The identified proteins with at least two peptides matched were considered for further analysis. For iTRAQ labeling, iTRAQ ratios also had to satisfy the criterion that P < 0.05. Each experiment was performed at least in triplicate as technical replicates and was normalized with related

2. MATERIALS AND METHODS 2.1. Bacterial Strains

The bacterial strain used in the current study was A. hydrophila ATCC7966 kindly provided by Dr. Jijuan Cao from Liaoning Entry-Exit Inspection and Quarantine Bureau, Dalian, PR. China. The minimum inhibitory concentration (MIC) of this strain to OXY was 2.5 μg/mL, and bacterial antibiotics stress assay was performed as previously described.6 An OXY-resistant strain (A.h-OXY-R) was selected from A. hydrophila ATCC7966 (A.h-CK) with the use of 10 sequential subcultures in 1/2 MIC concentration of the antibiotic as described previously.21 After the selection, the MIC of A.h-CK was increased from 2.5 to 40 μg/mL (A.h-OXY-R). The strain was diluted at 1:100 to fresh Luria−Bertani (LB) medium after routinely grown overnight in the same medium at 200 rpm, 30 °C. When it was grown at the middle of logarithmic phase (OD = 0.8−1.0), the bacteria were exposed to 2- and 4-fold of the MIC concentrations of OXY, that is 5 and 10 μg/mL, respectively, for 1 h and then harvested and washed with saline twice for further use. The growth curve was measured as described previously.22 2.2. Sample Preparation and iTRAQ Labeling

The pellet was resuspended from 10 mL cultured LB with PBS buffer and broken by intermittent supersonic for a total of 15 min at 50% power with intervals of 9 s on ice. The protein content was measured by Bradford assay and stored at −80 °C before use. 1DE SDS-PAGE was performed as described previously to B


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sonic oscillation for a total of 15 min at 30% power with intervals of 7 s on ice. Supernatant was collected by centrifugation at 10 000 g for 10 min, and succinate dehydrogenase (SDH) and α ketoglutarate dehydrogenase (α KDGH) enzyme activities were measured using kits as manufacturer’s protocol (SuZhou Comin Biotechnology, Suzhou, China).

peptides of control. The samples were prepared independently for iTRAQ labeling and SWATH quantitation as biological replicates. 2.4. Gene Ontology Categories and Bioinformatics Analysis

The increase or decrease degree of overlapping proteins among different conditions of comparison was analyzed by the online Venny tool in a Venn diagram.28 The gene ontology (GO) terms of differential proteins in this study were analyzed using online AgBase-GOanna resource version 2.0 (http://agbase.msstate. edu/cgi-bin/tools/GOanna.cgi) against Agbase-UniProt database, which is a powerful homology-based approach for gene ontology enrichment analysis, and then plotted using WEGO tool.29,30 A KEGG pathway analysis of the homologous proteins was further performed using the online DAVID 6.7 bioinformatics resource (http://david.abcc.ncifcrf.gov/); the top ten enrichment of increasing or decreasing abundance KEGG terms were presented by pie charts.31

2.8. Statistical Analysis

All the experiment data were collected from at least three independent biological replicates and analyzed using GraphPad Prism 5.0 (Graphpad, San Diego, CA, USA). Group differences were assessed using one-way analysis of variance (ANOVA) followed by the post hoc Tukey honestly significant difference test (HSD). Differences among the lowercase letters above the bars indicate a significant (p < 0.05) difference among the six samples.

3. RESULT

2.5. Validation of Selected Altered Proteins by Scheduled High-Resolution Multiple Reaction Monitoring (sMRMHR MS)

3.1. Proteins Identification Using iTRAQ Labeling and SWATH-MS Method

To further validate the varieties of nine selected proteins of A. hydrophila in OXY stress, proteins were extracted from bacteria that were treated with and without 5 μg/mL OXY and then digested as the same method mentioned previously and then spiked in a synthetic peptide APLDNDIGVSEATR as internal control. The sMRMHR assay was performed using AB Sciex TripleTOF 5600 plus mass spectrometer as the same peptides separation and analysis conditions as those used for SWATH-MS. Transitions for each peptide were optimized and selected using the Skyline software (Table S2, Supporting Information).32 The final ratio of with/without 5 μg/mL OXY was normalized to protein input by internal peptide control.

Samples of 5 or 10 μg/mL OXY were added at the middle logarithmic growth culturing of A. hydrophila and showed significant dropping in growth curve (Figure 1A). After treated with antibiotics for 1 h, bacterial strains were harvested immediately, and proteins were extracted, and then 1DE SDS-PAGE was performed (Figure 1B). Results showed that the some bands increased or decreased according to the dose treatment, which indicated that OXY-induced A. hydrophila triggered some protective mechanisms to survival in toxic environment. To investigate this response behavior from a high-throughput level, proteins were digested by trypsin and then further analyzed using multiplexed proteomics technologies. Fractioned labeling and directly digested peptides were submitted to AB Sciex TripleTOF 5600+ for iTRAQ and SWATH quantitation, respectively. With a highly conservative threshold (confidence ⩾ 99%, and FDR < 1%), a total of 1383 proteins, including 11 431 peptides, was identified by SWATH-MS method, and 2779 proteins, including 47 503 peptides, were identified from iTRAQ labeling samples (Tables S1 and S2, Supporting Information). It is ambiguous to judge which strategy is better for sample identification or quantification in this study. Theoretically, iTRAQ labeling sample should get more protein information for its prefractioned procedures. Our results showed that 1254 identified proteins (up to 90%) in SWATH-MS method could also be identified in iTRAQ method (Figure 1C). That indicates the potential compatibility and reliability of identification information in both methods.

2.6. Validation of Selected Altered Proteins at the Level of mRNA Transcription by qPCR

Total RNA was extracted using the TaKaRa MiniBEST Universal RNA Extraction kit (Takara Shuzo, Otsu, Japan) according to the manufacturer’s directions. An equal quantity of total DNA-free RNA from each sample was reverse-transcribed using PrimeScript TM RT reagent kit with gDNA Eraser (Takara Shuzo, Otsu, Japan). In this study, glyceraldehyde-3-phosphate dehydrogenase (GAP-1) was used as an internal control.33 Primers for GAP-1 were forward 5′-AGAGCCTCAATGCCTATCTGC-3′ and reverse 5′-ACCCGAACTCGTTGTCATACC-3′. The primers of target genes are listed in Table S3 of the Supporting Information. These reactions were performed for 40 cycles (95 °C for 15 s, 60 °C for 35 s) after initial 30 s incubation at 95 °C. 2.7. Validation of Proteomic Analysis

3.2. Protein Quantitation Comparisons of A. hydrophila in and without Oxytetracycline Stress

+

The intracellular NAD and NADH concentrations in related strains were measured according to NAD(H) measurement kit (Comin biotechnology, Suzhou, China). Briefly, A.h-OXY-R and A.h-CK strains were cultured and treated with 0, 5, and 10 μg/mL OXY for 1 h as mentioned above. After centrifugation at 10 000 g for 1 min, duplicate 1-mL samples were pelleted and extracted NAD+ and NADH using HCl and NaOH extraction method respectively as described previously.34 The following procedures were performed as manufacturer’s protocol and finally monitored the reduction of MTT at 570 nm in a Tecan Infinite M200 pro spectrophotometer (Tecan Deutschland GmbH, Crailsheim, Germany). For enzyme activity assays, 5-mL samples were treated and collected as mentioned previously and then disrupted by intermittent

By using the SWATH-MS method, a total of 662 differential proteins, including 309 decreasing abundance and 353 increasing abundance, in 5 μg/mL OXY stress and a total of 670 proteins, including 440 decreasing abundance and 230 increasing abundance, in 10 μg/mL OXY were identified when compared with A. hydrophila cultured in LB medium without OXY. While the iTRAQ labeling method was used, a total of 463 differential proteins, including 75 decreased and 388 increased, in 5 μg/mL OXY stress and 308 proteins, including 119 decreased and 189 increased, in 10 μg/mL OXY stress were identified. The number of altered proteins by iTRAQ labeling is lower than that of the SWATH-MS method, partially because of the more rigidly significant criteria of iTRAQ searching (p < 0.05). The Venn C


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Figure 1. Comparative characteristics of Aeromonas hydrophila ATCC 7966 in OXY stress. (A) Growth curve of A. hydrophila ATCC 7966 in 2- and 4-folds MICs concentrations of OXY after incubated 2 h. (B) CBB-stained SDS-PAGE of A. hydrophila in 2-fold and 4-fold MICs concentrations, which equal 5 and 10 μg/mL of OXY, respectively. Lane M contained molecular mass standards. (C) The identification comparison of two workflows on A. hydrophila illustrated as a Venn diagram to demonstrate the overlap between SWATH-MS (green) and iTRAQ labeling (red) methods. (D) Pearson’s R2 and Spearman’s correlation (ρ) showed correlation of differentially expressed proteins between SWATH and iTRAQ methods in biological replicates. Scatter plots of iTRAQ quantified log2 (protein ratio) vs SWATH quantified in 5 (left) and 10 μg/mL OXY (right), respectively. (E, F) Venn diagrams showing the up (increasing) or down (decreasing) overlap between significantly different proteins under 5 and 10 μg/mL of OXY using SWATH-MS and iTRAQ labeling methods, respectively.

diagram showed that there are 152 up-regulated and 52 downregulated proteins overlapped in 5 μg/mL OXY stress and both 83 up- and down-regulated proteins overlapped in 10 μg/mL OXY stress in both methods, respectively (Figure 1 E,F). Although an opposite tendency was found in R4VY15, a kind of acyltransferase, the accuracy and consistence of both methods was valuable. The correlation analyses among both quantitative methods in differential dose of antibiotics showed that the log ratios of the common quantitative data from SWATH-MS in 5 μg/mL OXY were basically correlated with those from SWATH-MS in 5 μg/mL OXY, iTRAQ in 5 or 10 μg/mL OXY, respectively, with the regression coefficients greater than 0.8 (Figure 1D). Those results indicate that the combination of both quantitative proteomics methods will reduce the false-positive results and lead to more reliable conclusions.

There are many cases reported about OXY-resistant strains in aquatic systems, and some intrinsic resistance mechanisms have been well investigated. tet and otr genes are well-known tetracycline and OXY resistance genes, and most of them are coded for efflux pumps and ribosomal protection function.35,36 Although these proteins were not detected in this study, TetR family transcriptional regulator (R4 V984), which controls the expression of the tet genes, was found to increase up to three-fold using iTRAQ labeling methods. Of these common altered proteins, outer membrane proteins play important roles in antibiotics resistance. AheC (B2BP22, homologous to OprM) and HAS ABC exporter outer membrane component (A0KPL3, homologous to TolC) were in increasing abundance in OXY stress. They are well-known outer membrane pumps to efflux multidrugs out of cellular of A. hydrophila and other bacterial species.20,21 The DNA-binding response D


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Table 1. Selected Identification of Significantly Differential Proteins of Aeromonas hydrophila ATCC 7966 in 5 and 10 μg/mL Oxytetracycline Stresses Using SWATH-MS and iTRAQ Labeling Analysis iTRAQ

a

accession

description

% Cov (95)

iTRAQ peptides

A0KEV0 A0KFM6 A0KFY5 A0KL23 A0KQV3 K1JPN4 R4V825 R4V829 R4VCI9 R4VD26 R4VDH0 R4VFG6 R4VFY7 R4VGN8 R4VPV2 R4VS58 R4VSP5 R4VV09 R4VXC9 R4W0J5

Magnesium-translocating P-type ATPase Fimbrial protein Pullulanase Anaerobic glycerol-3-phosphate dehydrogenase subunit A ADP-L-glycero-D-manno-heptose-6-epimerase Uncharacterized protein 30S ribosomal protein S19 30S ribosomal protein S17 PhoH family protein 5′-nucleotidase Uncharacterized protein Phosphate ABC transporter ATP-binding protein PrkA family serine protein kinase Uncharacterized protein 30S ribosomal protein S20 Fumarate reductase flavoprotein subunit 30S ribosomal protein S16 Acetaldehyde dehydrogenase Cbb3-type cytochrome c oxidase subunit II Ferrichrome receptor

56.8 91.1 78.1 87.8 95.9 48.1 72.8 87.8 71.9 89.4 78.7 69.9 87.2 46 62.1 83.2 84.2 86.7 68.6 47.5

33 39 125 75 72 11 35 39 26 306 13 15 76 9 36 257 56 147 17 19

SWATH

SWATH peptides

5/cka

10/cka

5/cka

10/cka

14 11 32 23 15 3 20 8 5 74 4 7 18 4 8 54 17 37 2 7

7.05 6.85 0.38 0.44 0.37 5.91 11.33 6.47 0.44 0.41 0.40 5.97 0.36 6.00 9.53 0.40 8.92 0.36 0.39 6.06

4.88 5.64 0.24 0.32 0.25 3.18 9.94 5.16 0.34 0.28 0.33 4.96 0.36 4.13 3.93 0.20 8.40 0.29 0.36 3.72

13.13 26.02 0.13 0.21 0.16 10.50 8.22 10.76 0.11 0.20 0.17 3.18 0.13 5.52 48.82 0.22 39.52 0.02 0.41 13.70

9.49 19.74 0.03 0.14 0.08 6.18 8.29 7.99 0.25 0.13 0.15 3.51 0.18 3.99 18.17 0.08 35.35 0.01 0.38 7.00

5/ck and 10/ck indicate the ratios of 5 and 10 μg/mL OXY treatments vs control using different quantitative methods.

regulator, A0KH19, which belong to LuxR family, was upregulated. That indicates that antibiotics impact the quorum sensing system to regulate the cell density to develop biofilm or escape from severe environments.37 Besides these, translation related proteins, such as 22 ribosome subunits, ribosome-recycling factor (A0KHG6), translation initiation factors IF-1 and IF-2(R4VFM8 and R4W0U9), and elongation factors (R4VT42 and R4VDH4), were increased in OXY stress (Table 1 and Table S1, Supporting Information). Meanwhile, we also identified five outer membranes (R4VRX0, R4VAF7, I3QPT8, A0KI84, and R4VBK9) that increased, which might be related with toxic efflux pump system for bacteria survival. However, energy metabolism related proteins, such as ATP synthase (R4VV29, R4W2U5 and R4VJ80), and largely of sugars transporting into bacteria (R4VMV4, R4VW15, R4 V8S9, R4VVL0, and A0KPR6) were found to be decreasing in abundance. Besides these, R4VQZ5 and R4VN72, the twinarginine translocation (Tat) pathway that mediates the transmembrane transport of folded proteins and Type VI secretion protein, K1KBE0 and K1JBN3, were attenuated in OXY stress, which suggests a bacterial survival strategy to reduce proteins transport and secretion. These results indicate some rules to follow, although the complied metabolic reactions occurred in bacterial antibiotics response.

According to the lower and over-representation of functional gene annotations, we found that metabolic changes were highly involved in bacteria response to antibiotics, up to 80% and 60% decreasing and increasing abundance of proteins were involved in cellular metabolic process and primary metabolic process in OXY stress. Generally, increasing abundance of proteins enriched more in biosynthetic process, establishment of localization and macromolecule metabolic process in biological processes, and structural constituent of ribosome in molecular function, while decreasing abundance of proteins enriched more in oxidation reduction, catabolic process, transport in biological processes, and catalytic in molecular function (Figure S1, Supporting Information). The following hierarchical clustering of the 238 proteins based on their iTRAQ and SWATH-MS ratios was performed to generate a dendrogram and colored heat map (Figure 2A). Detailed analysis revealed at least three interesting aspects of GO analysis. First, the log2 fold changes of A. hydrophila in 10 and 5 μg/mL OXY using SWATH-MS method were different from those using the iTRAQ method. The same quantitative method in different OXY stress was clustered together. Second, translation related ribosomal subunits, such as S17, L27, S18, S19, S16, and S20, were clustered in increasing expression proteins. Third, energy related pathway proteins, such as fumarate reductase iron sulfur subunit, furmarate reductase flavoprotein subunit, and maltose maltodextrin import ATP binding protein, were clustered in decreasing expression proteins. Further, KEGG pathway analysis in top ten abundance of altered proteins is consistent with the finding that ribosome (up to 44% in all top ten abundance KEGG annotation terms) increased, and starch and sucrose metabolism (11%), pyruvate metabolism (9%), glycolysis/gluconeogenesis (10%), and citrate cycle (10%, TCA cycle) related proteins decreased in OXY stress (Figure 2B). Meanwhile, we also found that amino acid metabolism (phenylalanine, tyrosine, and tryptophan

3.3. Functional Classification Annotation and Hierarchical Clustering Analysis of Altered Proteins

To acquire more reliable information from differential expression proteins, we only focused on the altered data (total 238 proteins). Those tendencies were confirmed by both SWATH-MS and iTRAQ labeling quantitation method. GO terms of these proteins were further annotated using AgBase-GOanna online software, which is for limited annotation species by homologous blast searching since there are still a large proportion of gene annotations of A. hydrophila unknown. E


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Figure 2. Bioinformatics analysis of differentially expressed proteins of Aeromonas hydrophila ATCC 7966 in OXY stress. (A) A heat map was used to visualize proteins, which displays increased and decreased expression from OXY treated (in 5 μg/mL and 10 μg/mL OXY) A. hydrophila using iTRAQ labeling and SWATH-MS qualitative method. The heat map contains four columns corresponding to the two iTRAQ labeling and two SWATH-MS samples in serial concentrations of OXY stress. (Columns 1 and 2, the log2 ratio of bacterial in 10 and 5 μg/mL OXY stress/normal medium based on SWATH-MS method; columns 3 and 4, the log2 ratio of bacterial in 10 and 5 μg/mL OXY stress/normal medium based on iTRAQ method). Results showed that the translation process increased abundance and the energy metabolic pathway related proteins decreased abundance. (B, C) KEGG pathways enrichment of the OXY-related (in 5 μg/mL and 10 μg/mL OXY) differentially increasing and decreasing proteins, respectively.

phosphotransferase system (10%, PTS) and ABC transporters (10%) were both found to be down-regulated (Figure 2C). In general, in OXY stress, the carbohydrate metabolism related pathways, such as sugar transport, energy metabolism system, and DNA metabolism, dramatically declined, while amino acid

biosynthesis 10%; arginine and proline metabolism 6%; D -Glutamine and D-glutamate metabolism 4%; and histidine metabolism 4%, respectively) and RNA degradation (8%) increased, while purine (10%), nitrogen metabolism (10%), and butanoate metabolism (10%) decreased. Moreover, the F


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Table 2. Validation of Seven Selected Proteins by sMRMHR Method and Verification of 14 Selected Genes by qPCR in Different Oxytetracycline Stressesa accession

description

ratio in SWATH

ratio in iTRAQ

ratio in sMRMHR

tendency in mRNA level

0.08 0.21 0.22 0.23 0.18

0.33 0.50 0.40 0.45 0.62

0.55 0.47 0.14 0.14 N

↓↓ ↑↑ ↑↓ ↓↓ ↓↓

3.37 3.57 7.42 10.76 9.33 8.22 9.33 39.50 8.63

3.59 4.41 3.69 6.47 3.94 11.33 4.00 8.92 4.14

1.60 2.33 1.85 N N N N N N

↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑ ↑↑

Energy Generation Process A0KFS2 Phosphoenolpyruvate carboxykinase R4VW15 Maltose ABC transporter periplasmic protein R4VS58 Fumarate reductase flavoprotein subunit R4VXT4 Fumarate reductase iron−sulfur subunit R4VMV4 Maltose/maltodextrin import ATP-binding protein MalK Translation-Related Process R4VIW9 50S ribosomal protein L17 R4VY09 Ribosome-binding factor A R4VJZ2 tRNA (guanine-N(7)−)-methyltransferase R4 V829 30S ribosomal protein S17 R4 V965 30S ribosomal protein S18 R4 V825 30S ribosomal protein S19 R4VPV2 30S ribosomal protein S20 R4VSP5 30S ribosomal protein S16 R4VKL6 50S ribosomal protein L27

Note: ↓ means decreasing; ↑ means increasing; and two continuous symbols mean mRNA tendencies in 5 and 10 mg/mL OXY stress, respectively. N means data do not measure; the ratios shown in SWATH, iTRAQ, and sMRMHR methods only represent the folds change in 5 μg/mL OXY stress. a

and then significantly decreased in 10 μg/mL OXY stress. Interestingly, R4VW15 was increased in both stress levels, which was opposite of the tendency of its protein level. These results suggested the phenomenon of time regulation delay between transcription and translation level. In general, the mRNA levels of the proteins that participated in energy pathways largely decreased, while those that take part in translation processes increased in OXY stress.

metabolism, RNA degradation, and protein and fatty acid biosynthesis rose. 3.4. Validation of Selected Altered Proteins Using Scheduled High-Resolution Multiple Reaction Monitoring (sMRMHR MS)

According to the proteomics results and data analysis, upregulated translation process and down-regulated energy generation process are main fitness behavior in OXY stress. To confirm this, we applied a selective, highly sensitive quantitative MS method, sMRMHR, for the targeted specific peptides quantitation only in OXY concentration of 5 μg/mL (Table 2 and Table S2, Supporting Information). A total of seven proteins were quantified and normalized by synthetic peptides, including four related with energy generation metabolic pathways including TCA cycle (R4VS58, R4VXT4), pyruvate metabolic pathway (A0KFS2), and glycolysis (R4VW15) and three with translations processes (R4VIW9, R4VY09, and R4VJZ2). Results showed the good coincidence with all tendencies of selected proteins, which suggested the high reliability of these altered proteins from two kinds of MS methods and the potential application of this highly sensitive sMRMHR method in highthroughput bacterial stress detection.

3.6. NAD+/NADH Ratios Were Decreased in OXY Stress

We further verified the energy metabolic behavior in OXY stress by measuring the concentrations of NAD+, NADH, and the ratio of NAD+/NADH in A.h-CK and A.h-OXY-R strains. Results showed that the concentration of NAD+ in A.h-CK was up to 1.0 nmol/mg in normal LB medium; however, when treated with 5 and 10 μg/mL OXY, it dropped sharply down to 0.46 and 0.43 nmol/mg, respectively. Furthermore, the concentration of NAD+ in OXY resistant strain, A.h-OXY-R without and with 5 and 10 μg/mL OXY stresses, was 0.41 and 0.65 and 0.63 nmol/mg, respectively, which is much lower than the measurement in A.h-CK strain (Figure 3B). The concentrations of NADH among those groups changed slightly. Compared to A.h-CK, there were not significant changes among OXY stress, while decreased slightly when A.h-OXY-R in normal LB medium was compared to OXY treatment (Figure 3C). The decreasing tendency of the ratio of NAD+/NADH in A.h-CK under OXY stress would depress the TCA cycle process. Interestingly, the ratio of NAD+/NADH in A.h-OXY-R is lower than A.h-OXY in normal LB medium but rises back to similar ratio of A.h-CK when treated with OXY (Figure 3D). Our results illustrate the use of NAD+ and NADH in A.h-CK and A.h-OXY-R strains and indicate the decreasing energy generation process that may be a strategy for bacterial survival in OXY stress.

3.5. Validation of the mRNA Transcription Level of Selected Altered Proteins

To further validate the different OXY response behavior in A. hydrophila, we investigated the mRNA levels of total 14 selected genes, which were altered in protein level using qPCR. Of these 14 genes, seven genes were verified in proteins level using sMRMHR method as mentioned above, others including one related with energy generation metabolic pathways (R4VMV4) and six related with translation processes (R4 V829, R4 V965, R4 V825, R4VPV2, R4VSP5, R4VKL6), which were clustered using heat map analysis. The results showed that mRNA level of translation related genes was consistent with the trends of related proteomics conclusions. In the transcripts of energy generation related mRNAs, all genes were increased as their protein levels in both 5 and 10 μg/mL OXY stress. R4VS58, R4VXT4, and R4VMV4 were slightly changed in 5 μg/mL OXY

3.7. Validation of Energy Generation Process Using Enzyme Activity Assay

To further validate the decreasing energy generation process in OXY stress, we measured two enzyme activities, SDH and α-KDGH, which were key enzymes involved in the TCA cycle. Both enzyme activities in A.h-CK are decreased or decreasing trend in OXY stress. In A.h-OXY-R, no significant difference was G


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Figure 3. The validation of proteomic analysis by qPCR, NAD+/NADH, and enzyme activities assay. (A) The mRNA levels of nine translation and five energy generation process related genes were analyzed by qPCR method in OXY stresses. (B−D) The concentrations of NAD+ and NADH and the ratio of NAD+/NADH in A.h-CK and A.h-OXY-R in different OXY treatments. (E, F) The SDH and α-KDGH enzyme activity assays in A.h-CK and A.h-OXY-R in different OXY treatments.

strains indicate that the OXY resistance strain has adapted the antibiotics stress, and the energy generation process may play a role in antibiotics resistance.

found among each treatment group. However, when compared to A.h-CK, the SDH activity in A.h-OXY-R was decreased, while no change was found for α-KDGH activity. Generally, these results were consistent with our quantitative and target proteomics and qPCR analysis conclusions, that is, the energy generation process of A.h-CK is decreased in OXY stress. Furthermore, the different responses to OXY stress between two

4. DISCUSSION Generally, the major methods for the prevention and treatment of fish diseases are the use of chemical drugs, antibiotics, H


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antibiotics stress, although there were some miscorrelations between protein and mRNAs levels. The analysis results from selected candidates were largely in accordance with the conclusion using SWATH-MS and iTRAQ labeling methods, which suggested that the up-regulation of translation process and down-regulation of energy generation pathway may involve in the bacterial antibiotics fitness. Finally, the measure data of intracellular NAD+/NADH ratio and two TCA cycle related enzyme activities verified that the energy generation pathway did sharp decrease in OXY stress. Furthermore, the decrease of energy generation process was detected in OXY resistance strain, which suggest that this phenomenon may not only be a kind of fitness response, but also a common antibiotics resistance mechanism. The following suppression of target ribosomal subunits or the stimulation of bacterial intracellular energy generation process would be potential strategies for future antibiotics resistance therapy. In summary, our results provide not only an insight into the mechanism of antibiotics fitness in A. hydrophila, but also a potential prevention strategy for drug development. Finally, it has been noted that our data in this study were obtained from isolated bacteria to simulate natural environment. It is more complicated in real environments because microflora must face differential fluctuant conditions such as temperature, nutrients, toxicity, antibiotics, and competing with other species. According to recent meta-genomics and meta-proteomics research, pathogens may overexpress many kinds of efflux pump systems against fluctuant environments including antibiotics stress.49,50 The whole process is complicated and related with many mechanisms such as stress response, biofilm formation, virulent infection, antibiotics secretion, and quorum sensing. Outer membrane proteins, translation elongation factors, and chaperone and stress response proteins were reported to be active proteins in this process.51,52 Thus, the discovered behaviors of A. hydrophila microbiota response to natural environments will be an attractive and challenging research field.

or attenuated vaccines. In aquaculture, the long-term uses or abuses of antibiotics frequently cause the bacterial resistance, such as A. hydrophila, Vibrio anguillarum, and Escherichia coli, and lead to huge economic losses.38−41 Many researchers have carried out extensive works in the area of bacterial resistance, especially for the long-term monitoring of some important pathogens in specific regions.42,43 However, little research has been focused on the cellular characteristics of aquatic germs in antibiotics stress. Moreover, the intricate variations and intracellular compensation mechanisms of bacterial antibiotics response complicate the identification and quantification of functional proteins associated with antibiotics treatment in aquatic pathogens. Accordingly, a promising proteomics strategy combining SWATH-MS, iTRAQ labeling quantitative proteomics technologies with sMRMHR targeted proteomics method was conducted. Primarily, samples of A. hydrophila with/without 2- and 4-fold OXY MICs treatment were performed by SWATH-MS and iTRAQ labeling procedure and analyzed using LC−MS/MS, respectively. We only focused on those altered candidates with similar tendencies between both methods by using a very conservative set of identification criteria (FDR < 1%, the folds cut-off higher 2 or lower 0.5, at least two peptides match and for iTRAQ labeling, iTRAQ p < 0.05). The following gene ontology categories showed significant increasing enrichment on translation process and decreasing abundance on glycolysis/ gluconeogenesis and TCA cycle. These results are partially consistant with our previous research about translation process and energy metabolism in E. coli in chlortetracycline stress.6 Further bioinformatics analysis showed that translation related proteins, such as 22 ribosomal subunits and translation initiation and elongation factors, were increasing abundance in OXY stress. Considering the 30S ribosome attacking function of OXY and the important role of ribosome in living life, the reason for increasing translation expression is easy to understand. It should be a resistance strategy against antibiotics to overexpress target subunits for survival. In our previous study, the depletion of the lamB gene, a maltose transport protein located on the outer membrane, would increase the multidrug resistance properties of Escherichia coli.44 The decline of sugar transport would limit the usage of sugar and depress sugar metabolism and finally lead to the decreasing of energy generation (phosphotransferase system, TCA cycle) that might be a general evolutional tactics for bacteria to survive in threatening environments.45 The increasing antibiotics resistance in starvation medium and thermal stress supported this proposal.46,47 In this study, the expression of LamB in A. hydrophila was fluctuant. However, maltose ABC transporter periplasmic protein, MalE (R4VW15) and maltose/maltodextrin import ATP-binding protein MalK (R4VMV4), which complex with LamB for maltose transport, were constantly decreased. Meanwhile, energy process related proteins were largely decreasing abundance in OXY stress. Our data further confirmed the hypothesis that the decreasing of energy generation maybe a common phenomenon for bacteria species responding to antibiotics. Although the intrinsic resistance mechanism of the decreasing energy generation process remains largely unknown, some key mutagenesis in TCA cycle were reported to increase the survival of E. coli in multidrugs stress.48 That suggests the important role of down-regulated energy generation process in antibiotics resistance and may be potential targets for bacteria control. MS-based sMRMHR and qPCR methods were conducted to obtain more confident proofs for the bacteria behavior in

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ASSOCIATED CONTENT

S Supporting Information *

Identification and quantification results using SWATH and iTRAQ labeling methods in 5 and 10 μg/mL OXY stresses. Selected peptides list and result using sMRMHR method in 5 μg/mL OXY stress. Primers designed for q-PCR in this study. Gene ontology categories for the differentially expressed proteins of Aeromonas hydrophila ATCC 7966 in OXY stress according to Wego analysis. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. Phone: +8618344932236. Fax: +86059183769440. *E-mail: [email protected]. Author Contributions ¶

X.L. and L.L. contributed equally to this work.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was sponsored by grants from NSFC projects (No.31200105, No. 31470238) and the Fujian Agricultural and I


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Forestry University Foundation for Distinguished Young Scholars (No. XJQ201201). We thank Dr. Jijuan Cao from Liaoning Entry−Exit Inspection and Quarantine Bureau, Dalian, PR. China, who kindly provided the Aeromonas hydrophila ATCC 7966 strain.

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An Integrated Quantitative and Targeted Proteomics Reveals Fitness

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