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Environmental Science and Pollution Research

, Volume 25, Issue 23, pp 22437–22445 | Cite as

Application of protein typing in molecular epidemiological investigation of nosocomial infection outbreak of aminoglycoside-resistant Pseudomonas aeruginosa

  • Min Song
  • Min Tang
  • Yinghuan Ding
  • Zecai Wu
  • Chengyu Xiang
  • Kui Yang
  • Zhang Zhang
  • Baolin Li
  • Zhenghua Deng
  • Jinbo LiuEmail author
Interface Effect of Ultrafine Mineral Particles and Microorganisms
  • 969 Downloads

Abstract

Pseudomonas aeruginosan has emerged as an important pathogen elated to serious infections and nosocomial outbreaks worldwide. This study was conducted to understand the prevalence of aminoglycoside (AMG)-resistant P. aeruginosa in our hospital and to provide a scientific basis for control measures against nosocomial infections. Eighty-two strains of P. aeruginosa were isolated from clinical departments and divided into AMG-resistant strains and AMG-sensitive strains based on susceptibility test results. AMG-resistant strains were typed by drug resistance gene typing (DRGT) and protein typing. Five kinds of aminoglycoside-modifying enzyme (AME) genes were detected in the AMG-resistant group. AMG-resistant P. aeruginosa strains were classified into three types and six subtypes by DRGT. Four protein peaks, namely, 9900.02, 7600.04, 9101.25 and 10,372.87 Da, were significantly and differentially expressed between the two groups. AMG-resistant P. aeruginosa strains were also categorised into three types and six subtypes at the distance level of 10 by protein typing. AMG-resistant P. aeruginosa was cloned spread in our hospital; the timely implementation of nosocomial infection prevention and control strategies were needed in preventing outbreaks and epidemic of AMG-resistant P. aeruginosa. SELDI-TOF MS technology can be used for bacterial typing, which provides a new method of clinical epidemiological survey and nosocomial infection control.

Keywords

Pseudomonas aeruginosa Aminoglycoside-modifying enzymes Surface-enhanced laser desorption/ionization-time of flight mass spectrometry Resistance Molecular typing Nosocomial infection 

Abbreviations

AMG

Aminoglycoside

DRGT

Drug resistance gene typing

AME

Aminoglycoside-modifying enzyme

SELDI-TOF MS

Surface-enhanced laser desorption/ionization-time of flight mass spectrometry

MDR

Multidrug-resistant

APH

Aminoglycoside phosphoryltransferase

AAC

Aminoglycoside acetyltransferase

ANT

Aminoglycoside nucleotidyl transferase

AFLP

Amplified fragment length polymorphism

RFLP

Restriction fragment length polymorphism

REP-PCR

Repetitive extragenic palindromic polymerase chain reaction

PFGE

Pulsed-field gel electrophoresis

MLST

Multilocus sequence typing

CLSI

Clinical Laboratory Standards Institute

MICs

Minimal inhibitory concentrations

ACTH

Adrenocorticotropic hormone

MALDI

Matrix-assisted laser desorption and ionization

Introduction

Pseudomonas aeruginosa is a nonfermentative Gram-negative bacillus widely distributed in soil, air and human skin, mucous membranes, respiratory tract and gastrointestinal tract. Among risk factors, the widespread use of broad-spectrum antibiotics has accelerated the evolution and spread of antibiotic and multidrug-resistant (MDR) bacteria. In recent years, infections caused by P. aeruginosa have considerably increased. In 2011, the National Bacterial Resistance Monitoring System showed that the clinical separation rate of P. aeruginosa in nonfermenting bacteria was the highest (Yun et al. 2012). P. aeruginosa has emerged as the most well-known cause of serious infections and nosocomial outbreaks worldwide. It is also highly resistant to various antibiotics and thus considered the ultimate superbug.

Aminoglycoside (AMG) antibiotics are widely utilised in clinical settings, especially in the treatment of life-threatening infections caused by nonfermenting bacteria, such as P. aeruginosa. These antibiotics are some of the few currently available antibiotics for the treatment of P. aeruginosa infections (Ramirez and Tolmasky 2010). Resistance to AMGs has become prevalent and emerged as an important issue in P. aeruginosa therapy (Over et al. 2001; Vaziri et al. 2011). Such resistance typically occurs through various AMG-modifying enzymes (AMEs) or inactivation enzymes, excessively expressed active efflux systems, biofilms, exogenous resistant genes, target mutation, methylation modification and riboswitch regulation (Livermore 2002; Shakil et al. 2008; Moore and Flaws 2011; Jia et al. 2013). Among these mechanisms, inactivation by plasmids or chromosome-encoded modifying enzymes, including AMG phosphoryl transferase (APH), AMG acetyltransferase (AAC) and AMG nucleotidyltransferase (ANT), is the most predominant (Vakulenko and Mobashery 2003). These three kinds of enzymes can be divided into many subtypes according to the modifications of different sites and types of antimicrobial agents, and more than 100 subtypes have been found (Ramirez and Tolmasky 2010). Common AME genes include aac(3)-II, aac(3)-I, aac(6′)-I, aac(6′)-II, ant(2″)-I, ant(3″)-I and gene. An individual P. aeruginosa can co-harbour multiple modifying enzyme genes, resulting in AMG resistance phenotype (Vaziri et al. 2011).

Nosocomial infections pose a serious health risk, and patient prognosis has revealed high morbidity and mortality. Nosocomial infections were associated with higher medical costs, which likely present a large burden on the patients with nosocomial infections and the respective health care system (Allegranzi et al. 2011; Wu et al. 2016; Heister et al. 2017). The outbreak or epidemic of nosocomial infections caused by MDR bacteria has been considered a major problem related to nosocomial infections (Singh et al. 2006). Consequently, molecular typing techniques have been used to help control cross infections and identify transmission pathways. A number of molecular typing methods, such as amplified fragment length polymorphism (AFLP), restriction fragment length polymorphism, repetitive extragenic palindromic polymerase chain reaction, pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing, have been proposed, and these methods are based on genes. Nowadays, genotyping is the most common strategy to discriminate bacterial strains. For this purpose, different methods are available, each with its pros and cons (Li et al. 2009). Liquid chromatography coupled with MS has been used to analyse bacterial proteins in a wider range of concentrations in both bottom-up and top-down proteomics studies aiming for the identification and typing of bacteria (Fenselau 2013; McFarland et al. 2014; Cheng et al. 2016). However, this technique is time-consuming and has not been implemented yet in clinical laboratories. There is a puzzle whether there will be a method based on proteins. In this study, protein-based typing method involving surface-enhanced lasers desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS) was proposed with specific typing advantages according to remarkable protein peaks. This method was faster and easier than gene-based methods. In an endemicity period, this method could distinguish an epidemiological strain from a non-epidemiological strain after P. aeruginosa was isolated from hospitalised patients.

Materials and methods

Bacterial isolates and materials

Eighty-two P. aeruginosa isolates retrieved from the clinical microbiology laboratory in our hospital from September 2014 to June 2015 were identified at a species level by using a MicroScan WalkAway 96SI automatic microorganism analyser according to the manufacturer’s instructions and stored at − 80 °C before they were cultured. Escherichia coli (ATCC 25922) and P. aeruginosa (ATCC 27853) were used as reference strains. A polymerase chain reaction (PCR) amplifier was obtained from BioRad (USA), and primers were synthesised by Sangon Biotech (Shanghai, China). Taq polymerase, dNTPs and maker were purchased from TaKaRa (Dalian, China). Protein calibration standards (insulin, cytochrome C and myoglobin), acetonitrile, trifluoroacetic acid and sinapic acid (SPA) were procured from Sigma. AU ProteinChip arrays, SELDI-TOF MS and Biomarker Wizard were obtained from Ciphergen.

Susceptibility test of bacterial isolates

An antimicrobial susceptibility test was conducted according to the reference methods published in M07-A9 for minimal inhibitory concentrations by the Clinical Laboratory Standards Institute (CLSI), and gentamicin, amikacin and tobramycin were the tested antimicrobial agents. The CLSI categorical interpretive criteria published in M100-S22 were applied to examine bacterial susceptibility and resistance. E. coli ATCC 25922, Staphylococcus aureus ATCC 29213 and P. aeruginosa ATCC 27853 were used for the quality control of the susceptibility test reagents and methods. According to susceptibility to AMG antibiotics, the 82 P. aeruginosa isolates were divided into two groups: (1) AMG-resistant strains which were resistant to at least one of the three AMG antibiotics, namely, amikacin, gentamicin and tobramycin, and (2) AMG-sensitive strains which were sensitive to these AMG antibiotics.

Genomic DNA extraction

Bacterial DNA was extracted by boiling. The isolates stored at − 80 °C were grown overnight on chocolate agar plates at 35 °C, and five or six discrete colonies were emulsified in 200 μl of sterile distilled water in a 1-ml Eppendorf tube. Lysis was achieved by heating the tubes for 10 min at 100 °C. The genomic DNA existing in the supernatant was obtained through centrifugation at 8000 r/min for 5 min.

Protein extraction

The bacteria stored at − 80 °C were grown overnight on chocolate agar plates at 35 °C. Subsequently, five or six discrete colonies collected in the 1.0-ml Eppendorf tube were centrifuged at 13000 r/min for 2 min. Sediments were washed twice and resuspended with 250 μl of sterile distilled water. The bacterial suspensions mixed with 750 μl of anhydrous ethanol were centrifuged at 13000 r/min for 2 min. Similarly, the sediments mixed with 50 μl of 70% formic acid and 50 μl acetonitrile were centrifuged at 13000 r/min for 2 min. The bacterial protein in the supernatant was separated into three tubes and stored at − 80 °C until use.

AME gene detection

AME gene was detected as follows: AMG genes were amplified using the primers shown in Table 1. PCR was performed in a final volume of 25 μl. Each reaction mixture was composed of 2 μl of 4–8 ng/μl chromosomal DNA, 1 μl each of 5 μmol primers, 2.5 μl of 10× buffer, 1.5 μl of 25 mmol/l MgCl2, 0.5 μl of 5 units/μl Z-Taq and 0.2 μl of 25 mmol/l deoxynucleoside triphosphate mixture. The desired reaction volume was obtained by adding sterilised distilled water. The following PCR protocol was used: 5 min of denaturation at 96 °C; 34 cycles of 35 s at 95 °C (denaturation), 30 s at 55 °C (primer annealing) and 60 s at 72 °C (polymerase extension); and a final elongation at 72 °C for 10 min. The accuracy of the fragments was confirmed by genomic sequencing and sequence alignment. For each AMG-resistant P. aeruginosa strain, a panel of six drug resistance genes was amplified through PCR and checked through 1% agarose gel electrophoresis, whose image result was transformed via a binary mechanism, that is, a positive specific band was ‘1’, and a negative band was ‘0’. The result was further subjected to polygene cluster analysis in Statistic Package for Social Science (SPSS) 18.0.
Table 1

PCR primer sequences for detection of AME genes

Gene name

Primer sequence (5′ → 3′)

Expected size of amplicon (bp)

Reference or source

aac(3)-I

P1: ACCTACTCCCAACATCAGCC

169

(JIANG Mei-jie et al. 2009)

P2: ATATAGATCTCACTACGCGC

aac (3)-II

P1: ACTGTGATGGGATACGCGTC

237

(JIANG Mei-jie et al. 2009)

P2: CTCCGTCAGCGTTTCAGCTA

aac(6′)-I

P1: TATGAGTGGCTAAATCGA

394

(JIANG Mei-jie et al. 2009)

P2: CCCGCTTTCTCGTAGCA

aac(6′)-II

P1: TTCATGTCCGCGAGCACCCC

178

(JIANG Mei-jie et al. 2009)

P2: GACTCTTCCGCCATCGCTCT

ant(3″)-I

P1: TGATTTGCTGGTTACGGTGAC

284

(JIANG Mei-jie et al. 2009)

P2: CGCTATGTTCTCTTGCTTTTG

ant(2″)-I

P1: GAGCGAAATCTGCCGCTCTGG

320

(JIANG Mei-jie et al. 2009)

P2: CGTAAGGGCCATGATGACTT

16Sr DNA

P1: CAGCTCGTGTCGTGAGATGT

150

This study

P2: CGTAAGGGCCATGATGACTT

16Sr DNA sequence number is JN562715.2, self-designed

SELDI-TOF MS

The bacterial protein extract stored at − 80 °C was melted in an ice box. Bacterial protein extracts (3 μl) were mixed with the same volume of half-saturation SPA solution. Then, 2 μl of the mixture was applied onto AU ProteinChip arrays that were activated according to the manufacturer’s instructions. After the spots dried, 2 μl of half-saturation SPA was added to each spot and air dried. Bacterial proteins bound to the surface of the gold chip were detected through SELDI-TOF MS at an optimisation mass ranging from 2000 to 20,000 Da, a mean laser intensity of 195 and a detector sensitivity of 8. Ciphergen ProteinChip and Biomarker Wizard 3.1 were respectively used to collect experimental data automatically and to analyse the variability of the protein peaks between AMG-resistant P. aeruginosa strains and AMG-sensitive strains. The intensities of significant protein peaks were subjected to cluster analysis by using Ward’s linkage rescaled distance cluster combine (SPSS18.0).

Quality control and repeatability

Fingerprints were externally calibrated using an all-in-one peptide molecular mass standard. They were also internally calibrated with this standard and with an adrenocorticotropic hormone (ACTH) as the standard molecule peptide. The ACTH mass spectral peak was found in the ACTH-added bacterial protein fingerprint. Subsequently, the ACTH calibration module was set up to calibrate the m/z of the mass spectral peak and peak intensity with Ciphergen ProteinChip 3.0. The impact on the results due to fluctuations in operating conditions was eliminated; thereby, the accuracy and reproducibility of the results were improved through this way.

The average coefficient of variance (CV) was determined to estimate the reproducibility of each SELDI protein chip array in an inner group and a separate group. For the separate group, the bacterial protein without ACTH was detected 10 times in 1 day and 10 times in 10 days contiguously on 1 chip by calibrating with the all-in-one peptide molecular mass standard. For the inner group, the bacterial protein mixture containing ACTH was detected 10 times in 1 day and 10 times in 10 days contiguously on 1 chip by all-in-one calibration and ACTH calibration. The average CV of representative protein fingerprint peaks from the inner and separate groups was calculated and estimated.

Results

Identifying drug resistance gene from the clinical isolates

Of the 82 isolates, 49 were resistant to AMG antibiotics and 33 were sensitive to these antibiotics. Of the six AMEs, five were detected in the AMG-resistant strains. Of the 49 isolates, 19 (38.8%) were positive for aac(3)-II gene, 19 (38.8%) were positive for aac(6′)-I, 18 (36.7%) were positive for aac(6′)-II, 35 (71.4%) were positive for ant(2″)-I and 13 (26.5%) were positive for ant (3)-I, while aac(3)-I was not detected (Table 2).
Table 2

The results of AMEs, protein typing and DRGT for aminoglycoside-resistant PAE

Strain number

aac(6′)-II

aac(3)-II

ant(3″)-I

ant (2″)-I

aac(6′)-I

Protein typing

DRGT

PA-17, 34

+

+

+

+

+

A1

F2

PA-45

+

+

+

A1

E2

PA-66

+

+

+

A1

F2

PA-68

+

+

+

A1

F2

PA-59, 72

+

+

A1

E2

PA-60, 61, 65, 67, 71, 77

+

A1

D2

PA-82

+

+

+

+

A2

F2

PA-42

+

+

+

A2

E2

PA-27

+

+

+

A2

F1

PA-69

+

+

+

A2

E1

PA-64

+

A2

D2

PA-26, 48

+

+

+

+

B1

F2

PA-70, 80

B1

D1

PA-75

+

+

B1

E2

PA-18

+

+

+

+

+

B2

F2

PA-54

+

+

+

+

B2

E1

PA-43, 44

+

+

+

B2

E2

PA-11, 74

+

+

+

B2

F1

PA-79

+

+

+

B2

E1

PA-13, 22, 24, 73

+

+

B2

E2

PA-57

+

B2

E1

PA-30

B2

D1

PA-81

B2

F1

PA-33

+

+

+

C1

F1

PA-58

+

+

C1

E1

PA-62

+

C1

D2

PA-40, 56

C1

D1

PA-8

+

+

+

C2

F1

PA-39, 28

+

+

+

C2

F2

PA-31

+

+

+

C2

F2

PA-63, 76, 78

+

C2

D2

Drug resistance gene typing

Forty-nine isolates of AMG-resistant P. aeruginosa were divided into three types (D, E and F) and six subtypes with the six kinds of AME gene as a molecular marker for cluster analysis. The three types were further grouped into two subtypes each (Table 2): type D with subtypes D1 and D2, type E with subtypes E1 and E2, and type F with subtypes F1 and F2.

Reproducibility

The reproducibility of each SELDI ProteinChip assay was adjusted through internal calibration. ACTH as an internal standard was added to the test samples for SELDI-TOF MS detection. The experiment showed that the average CV was reduced compared with that of external calibration (only all-in-one: separate group). The CVs of the inner and separate groups of the representative protein fingerprint peaks are shown in Table 3.
Table 3

The reproducibility of inner group and separate group

Peaks

Mass (CV %)

Intensity (CV %)

Inner group

Separate group

Inner group

Separate group

9215.90

0.05

0.15

10.89.

13.56

6439.92

0.08

0.10

8.28

14.53

7715.96

0.06

0.18

13.08

18.95

\( \overline{x} \)

0.06

0.14

10.75

15.68

Differential protein expression between the two groups

Four protein peaks at 9900.02, 7600.04, 9101.25 and 10,372.87 Da were significantly and differentially expressed between the AMG-resistant strains and the AMG-sensitive strains (Table 4). The protein spectra revealed that the expression of the protein peaks at 9900.02 Da was downregulated in the AMG-resistant strains, whereas the expression of the peaks at 7600.04, 9101.25 and 10,372.87 Da was upregulated (Figs. 1 and 2).
Table 4

The intensity for distinct protein peaks of aminoglycoside-resistant strain and aminoglycoside-sensitive strain

(m/z)

(\( \overline{x} \) ± s)

t

p

Aminoglycoside-resistant group

Aminoglycoside-sensitive group

9900.02

23.61 ± 10.31

30.90 ± 8.74

3.33

< 0.05

9101.25

18.23 ± 4.69

14.93 ± 3.87

3.35

< 0.05

7600.04

12.30 ± 7.58

7.22 ± 2.55

2.70

< 0.05

10,372.87

13.49 ± 5.45

9.69 ± 4.36

3.35

< 0.05

Fig. 1

Differential expression of the SELDI peaks at 9900.02, 7600.04, 9101.25 and 10,372.87 Da of the two groups. Notes: horizontal axis, m/z; vertical axis: intensity of protein peaks; R, aminoglycoside-resistant strains; S, aminoglycoside-sensitive strains

Fig. 2

Differential line of the SELDI peaks at 9900.02, 7600.04, 9101.25 and 10,372.87 Da of the two groups. Notes: horizontal axis, m/z; vertical axis, intensity of protein peaks; R, aminoglycoside-resistant strains; S, aminoglycoside-sensitive strains

Protein typing

Forty-nine isolates of AMG-resistant P. aeruginosa were divided into three types (A, B and C) and six subtypes at a distance level of 10. The three types were further grouped into two subtypes each (Table 3): type A with subtypes A1 and A2, type B with subtypes B1 and B2, and type C with subtypes C1 and C2.

Discussion

Aminoglycoside-modifying enzymes, including AACs, ANTs or APHs, catalyse the modification at –NH2 or –OH groups of a 2-deoxystreptamine nucleus or sugar moieties. The combination of mutagenesis, which leads to continuous generation of new enzyme variants that can utilise an ever-growing number of antibiotics as substrates, with the coding genes’ ability to transfer at the molecular level as part of integrons, gene cassettes, transposons, or integrative conjugative elements and at the cellular level through conjugation, as part of mobilizable or conjugative plasmids, natural transformation or transduction, results in the ability of this resistance mechanism to reach virtually all bacterial types (Quiroga et al. 2007). Different AMEs can also modify various substrates, that is, different AMEs can alter various AMG antibiotics. The subclass aac(3)-I confers resistance to gentamicin, sisomicin and fortimicin (astromicin) and exists in a large number of Enterobacteriaceae and other Gram-negative clinical isolates (Ramirez and Tolmasky 2010). The subclass aac(3)-II is characterised by resistance to gentamicin, netilmicin, tobramycin, sisomicin and dibekacin (Shaw et al. 1993). The subclass aac(6′)-I exhibits a high activity against amikacin, kanamycin, gentamicin, netilmicin and tobramycin (Ramirez and Tolmasky 2010). The subclass aac(6′)-II is highly active against netilmicin, tobramycin and kanamycin. The subclass ant(2″)-I widely distributed as a gene cassette in class 1 and 2 integrons (Vakulenko and Mobashery 2003; Ramírez et al. 2005) mediates resistance to gentamicin, tobramycin, dibekacin, sisomicin and kanamycin. Ant(3″)-I is resistant to spectinomycin and streptomycin (Ramirez and Tolmasky 2010).

Five AME genes, namely, aac(3)-II, aac(6′)-I, aac(6′)-II, ant(2″)-I and ant(3″)-I, were detected in 49 strains of AMG-resistant P. aeruginosa. Among these genes, positive rate of ant(2″)-I was in the first place, whereas positive rate of ant(3″)-I was in the lowest place. The prevalent types of AME genes differ from those obtained in other areas or countries (Yan et al. 2012; Poonsuk et al. 2013; Odumosu et al. 2015), and these regional variations may be due to the different uses of antimicrobial agents in various countries or areas. In the present study, AME genes were not detected in six isolates, but these isolates were resistant to the antimicrobial drugs. This finding showed that P. aeruginosa in our hospital possesses a different resistance mechanism that was not examined in our study. As such, this mechanism should be further investigated by examining additional resistance mechanisms and genes.

Proteomics technology can be applied to detect changes occurring in proteins expressed of the pathogen under the action of antibacterial drugs and to provide a theoretical basis for studies on resistance mechanisms and epidemiological investigations on pathogens. SELDI-TOF MS is a new proteomics technology based on matrix-assisted laser desorption and ionization which has been widely used in proteomics research on pathogenic microbes. Encouraging results have been achieved in the identification of pathogenic microorganisms, biomarker monitoring, pathogenesis, resistance mechanisms, novel drugs and potential vaccines (Bongat et al. 2010; Xu et al. 2011; Li et al. 2012; Xiao et al. 2014). Four protein peaks were also significantly and differentially expressed. Although these peaks have been identified in the protein database Swiss-Prot, the protein measuring 9900.02 Da with a downregulated expression in AMG-resistant strains might be a 30S ribosomal protein or RNA polymerase omega subunits, which mainly control the transcription and translation of bacterial proteins. The protein with a m/z of 7600.04 Da and with an upregulated expression in AMG-resistant strains might be a cold-shock protein which plays an important role in adapting to low-temperature environments and enhances the antifreezing ability of bacteria. The protein with a m/z of 9101.25 Da and an upregulated expression in AMG-resistant strains might be sRNA chaperones or membrane protein insertion efficiency factors. Membrane proteins participate in bacterial resistance. For example, the lack of a protein in the bacterial outer membrane and a low expression cause difficulty in achieving the target of antimicrobial agents. The effects of membrane protein insertion efficiency on membrane protein should be further investigated. The protein with a m/z of 10,372.87 Da and an upregulated expression in AMG-resistant strains might be coenzyme PQQ or MinE protein. MinE consists of two functional domains, namely, the N-terminal and the C-terminal, which affect bacterial division. The abnormal expression of MinE protein may lead to an abnormal division of strains. These differentially expressed proteins should be further investigated to provide a basis for future research on drug resistance mechanisms, new drugs and potential vaccines at a molecular level. Our next study will focus on the relationship between these differentially expressed proteins and drug resistance genes.

The monitoring and control of nosocomial infections have been remarkably considered in infection management. Epidemiologic studies on nosocomial infections caused by specific strains can be performed by molecular typing which can confirm assumptions of clinical and epidemiological findings and track the outbreak of epidemic strains. Thus, effective infection control measures are proposed to prevent the reoccurrence of an epidemic. In our study, 49 isolates of AMG-resistant P. aeruginosa were divided into three types and six subtypes with the six kinds of AME gene as a molecular marker for cluster analysis by drug resistance gene typing (DRGT). DRGT is a modified typing method that possibly offers a specific grouping advantage according to the presence of an MDR gene, and its typeability is comparable with that of PFGE and better than that of AFLP in relatively closed areas, such as hospitals. DRGT is an efficient technique for epidemic strain genotyping with additional information on antibiotic genes (Jin et al. 2009). In our study, 49 isolates of AMG-resistant P. aeruginosa were divided into three types and six subtypes based on the intensity of the four distinct protein peaks. The typing results of the two typing methods were analogical (Table 2). For instance, the subgroups PA-60, PA-61, PA-65, PA-67, PA-71 and PA-77 in subtype A1 of DRGT were classified into subtype D2 by proteotyping, and they possessed ant(2″)-I drug-resistant gene. Interestingly, the strains PA-13, PA-22, PA-24 and PA-73 in type B2 by prototyping were divided into types E1 and E2 by DRGT. Drug resistance gene aac(3)-II was carried by the former, while the latter did not carried. The strains PA-17, PA-34 and PA-82 among the type F2 by DRGT were divided into types A1 and A2 by proteotyping. Drug resistance gene ant (2″)-I was detected in the former, while it was not detected in the latter. This difference might be due to the complex process of strain protein expression which was affected not only by resistance genes but also by many other factors. We will purify bacterial proteins in further studies.

Traceability indicated that AMG-resistant P. aeruginosa was found mainly in the intensive care unit (ICU) ward and the burn unit. A-type clones in the ICU ward of our hospital yielded the highest detection rate and were distributed in other departments, indicating that A-type clones have spread among several departments in our hospital. Cross infection might exist between departments, thereby leading to an increase in the number of drug-resistant strains and causing nosocomial infection outbreak. PA-60, PA-61 and PA-65 belonging to subtype A1 had the ant(2″)-I drug-resistant gene, and these isolates were derived from sputum, urine and secretion in ICU ward on March 12, 14 and 18, 2015, respectively. These isolates might also be derived from the clone epidemic of P. aeruginosa strain. The strains in the burn unit were mainly type B strains, indicating that different wards had various epidemic strains. PA-22 and PA-24 belonging to subtype A1 possessed ant(2″)-I and aac(6′)-I drug-resistant genes, and these isolates were obtained from secretions of surgical wounds in the same unit in the burn department on November 12 and 14, 2014, respectively. This finding suggested that the two strains might be transmitted in the burn unit. Thus, proteotyping can be used in bacterial typing that has certain guiding significance in nosocomial infection control and epidemiological investigations. Strain typing results also implied that the infection management of wards should be enhanced, infection control measures should be established and nosocomial pathways of pathogenic infections should be timely and effectively cut off to avoid the outbreak of pathogens causing nosocomial infections.

Conclusions

This study revealed that AMG-resistant P. aeruginosa spreading in our hospital was cloned, and the timely prevention and control of nosocomial infections were necessary to avoid outbreaks and epidemic of AMG-resistant P. aeruginosa. SELDI-TOF MS technology can be used for bacterial typing, which provides not only a new method of clinical epidemiological survey and nosocomial infection control but also new ideas for studies on drug resistance mechanism.

Notes

Funding Information

This research was funded by the National Natural Fund Project of China (No. 41472046), the Key Program of National Natural Science Project of China (No. 41130746), the Science and Technology Project of Sichuan Province, China (No. 2016JY0045), the Strategic Cooperation Project of the Luzhou People’s Government and Sichuan University, China (No. 2013CDLZ-S15) and the Fund Project of the Science and Technology Leader of Sichuan Province (No. 15031).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Min Song
    • 1
  • Min Tang
    • 1
  • Yinghuan Ding
    • 1
  • Zecai Wu
    • 1
  • Chengyu Xiang
    • 1
  • Kui Yang
    • 1
  • Zhang Zhang
    • 1
  • Baolin Li
    • 1
  • Zhenghua Deng
    • 1
  • Jinbo Liu
    • 1
    Email author
  1. 1.Department of Laboratory Medicinethe Affiliated Hospital of Southwest Medical UniversityLuzhouChina

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