795 Tri Ratna (Identification) Revisi.cdr IDENTIFICATION OF ENDOPHYTIC BACTERIA FROM Curcuma zedoaria BASED ON PROTEIN PROFILE USING MALDI-TOF MASS SPECTROMETRY 1* 2 TRI RATNA SULISTIYANI and PUSPITA LISDIYANTI 1 (LIPI) BogorResearch Center for Biology, Indonesian Institute of Sciences , Cibinong Science Center, 16911, Indonesia 2 (LIPI) aResearch Center for Biotechnology, Indonesian Institute of Sciences , Cibinong Science Center, Bogor 16911, Indonesi Received 30 December 2016 / Accepted 06 October 2017 ABSTRACT Valid identification of microorganisms is a vital information to establish culture collections. Currently, molecular approach based on 16S rDNA is widely used for bacterial identification. This approach is however, time consuming and expensive. Matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) allows the identification of microorganisms directly from colonies and it only takes some few minutes. The interest of this study was to identify endophytic bacteria associated with Curcuma zedoaria based on protein profile using MALDI-TOF MS system and compare with 16S rDNA sequence results. Endophytic bacteria were isolated from part of medicinal plant C. zedoaria collected from Bogor, West Java Indonesia. The identification of selected bacteria was performed by protein profile using MALDI-TOF MS. A total of 66 endophytic bacteria from C. zedoaria plant, were selected for identification. The result of MALDI-TOF MS analysis showed that eleven isolates (16.67%) were correctly identified to the species level and 23 isolates (34.85%) matched on genus level of molecular approach. These results demonstrates that the MALDI-TOF system is suitable and feasible approach for the bacterial identification, mainly for screening and grouping of large number isolates. Keywords: Curcuma zedoaria, endophytic bacteria, identification, MALDI-TOF MS INTRODUCTION Rapid and accurate identification of bacterial isolates has crucial role in the culture collections. Several methods of identification have been d e v e l o p e d . B a c t e r i a l i d e n t i f i c a t i o n i s p r e d o m i n a n t l y b a s e d o n p h e n o t y p i c , morphological (Gram-positive and negative) and biochemical properties testing analysis. However, classification and identification by these methods can be difficult because of variations in phenotypic characteristics, time-consuming and laborius (Seng et al. 2009; Rychert et al. 2013). Several years ago, molecular identification based on nucleotide sequencing of ribosomal DNA (rDNA) sequence analysis could replace the phenotypic, morphological and biochemical c h a r a c t e r i s t i c s f o r i d e n t i f i c a t i o n o f microorganisms to genus level (Rajendhran & Gunasekaran 2011). Molecular approach based on rDNA have widely been used for sequence identification of procaryotic taxa. The 16S rDNA sequences has confirmed the representativeness of the in bacterial phylogeny (Woo et al. sequence 2008). However this method is not suitable for a preliminary screening and grouping of large numbers of isolates in environmental and clinical microbiology laboratories. Analysis based on protein profile present in bacterial cells using Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) is becoming feasible and precise for bacterial identification (Bizzini et al. 2011; Santos et al. 2013). MALDI- TOF MS allows rapid identification of bacteria, less expensive on operational cost, accurate and low sample volume requirements compared to molecular approach (Wunschel et al. 2005; Singhal et al. 2015). It can be performed as soon as colonies are isolated and can be done just in a few minutes (Eigner et al. 2009; Seng et al. 2009; Neville et al. 2011; Rychert et al. 2013; Jamal et al. 2014).* Corresponding author: trilisty01@gmail.com BIOTROPIA 5 2 8 112 120 Vol. 2 No. , 201 : - DOI: 10.11598/btb.2018.25.2.795 112 MALDI-TOF MS analysis was done by comparing the MALDI-TOF MS spectra or protein profile “fingerprints” obtained from bacterial cells to a library from proteomic database (Martiny et al. 2012; Guo et al. 2014). Protein profile are significantly different for each bacteria and it contain certain unique mass marker even over the small mass range detected. Each bacteria shows signature characteristic peaks that are distinct for species level (Cain et al. 1994). The identification of microorganisms by MALDI- TOF MS is based on the detection of mass signals from biomarkers that are specific at genus, species or sub-group level (Ferroni et al. 2010; Benagli et al. 2012), therefore changes in protein profiles would be easily identified. The protein profile from each bacteria can serve as unique information for bacteria chemotaxonomic marker, for example to differentiate closely related species, also could enriche the information contained in procaryotic protein sequence databases. Kudirkiene et al. (2015) reported that MALDI-TOF MS was succesfully used in sub-species identification of Streptococcus equi. Using MALDI-TOF MS, routine bacterial identification can be obtained much earlier than identification by molecular and conventional methods. Therefore, this technique can be used as quality control management of cultures deposited in Culture Collections. The main objective of the study was to evaluate the identification of endophytic bacteria associated with C. zedoaria based on protein profile using MALDI-TOF MS system compared with the results based on 16S rDNA sequence from previous study (Sulistiyani et al. 2014). MATERIALS AND METHODS Bacterial Strains A total of 66 endophytic bacteria isolates from B i o s y s t e m a t i c a n d C u l t u r e C o l l e c t i o n s Laboratory-Research Center for Biology, LIPI, was used to evaluate the MALDI-TOF MS analysis were recovered from previous study (Sulistiyani et al. 2014). The isolates were Opreserved in 10% glycerol stock at -80 C. The bacteria were grown using Nutrient Agar (NA) media. The bacteria isolates were from C. zedoaria (white turmeric) planted in 3 areas in Bogor, Indonesia, in 2013. The plants materials collected from private garden in Bojong Gede (BG), experiment garden of Research Center for Biology, Indonesian Institute of Sciences, Cibinong (CBN) and garden of medicinal plants collection of Biopharmaca Research Center, Bog or Ag ricultural University, Dramaga (DRMG). All bacteria were previously identified by molecular identification based on 16S r NA D sequence. The bacteria represented 23 genera and 46 species (Sulistiyani et al. 2014). Preparation of acterial ell xtractsB C E Bacterial isolates were cultured from glycerol stock on Nutrient Agar (NA) and incubated under standard conditions at 35-37 C for 48 O hours and subcultured twice to ensure all isolates were in the same physiological state. Cell extract was prepared by picking a single colony of a fresh culture and suspended in 20 µL formic acid of 25% concentration and then mixed until complete suspension is formed by vortex. The extract was sonicated for 10 min and spinned to get the supernatant. Finally, the supernatant was used for MALDI-TOF analysis. MALDI-TOF Analysis The bacterial cell extract of 0.5 µL was placed in duplicates onto a steel target plate and allowed to dry at room temperature. Each sample was overlaid with 1 µL matrix of α-cyano-4- hydroxycinnamic acid (CHCA) in ethanol : acetonitrile : water : trifluoroacetic acid. The sample and matrix were mixed thoroughly and air dried at room temperature. Measurements were taken using a MALDI-TOF MS Axima system (Microbiology Laboratory of the Mulhouse Hospital, France). The laser frequency was 50 Hz, the acceleration voltage was 20 kV, and the extraction delay time was 200 ns. Each spectrum resulted from 5 laser shots at 100 random positions within measuring spot. The spectra were recorded in the linear positive mode within a mass range of 2 to 20 kDa. All mass fingerprints were analyzed by the SARAMIS software, which first compares them to the superspectra and in a second step to the individual spectra of the database using AnagnosTec version 4.07 (Axima system manual). 113 MALDI-TOF Mass Spectrometry for identification of endophyitic bacteria – Sulistiyani and Lisdiyanti such as morphologic, phenotypic, physiologic and molecular methods. However, as mentioned earlier, these methods are not suitable for a preliminary screening and grouping of large numbers of isolates from environmental and clinical samples and also, for controlling the identity and purity of microbial cultures preserved in Culture Collections. To overcome these problems, the present study evaluated the capability of MALDI-TOF MS for species identification of microorganisms such as bacteria isolates. Validity of MALDI-TOF MS results was compared with the results of molecular identification based on 16S rDNA sequences as a Calibration and Validation Analysis The instrument was calibrated and validated using a control strain of Escherichia coli K12 InaCC B5. Several strain were also used for quality control including of Bacillus substilis InaCC B1, Pseudomonas aeruginosa InaCC B3 and Staphylococcus aureus InaCC B4. RESULTS AND DISCUSSION Accurate identification of bacteria could be obtained from several identification methods, Figure 1 Spectral profiles of three isolates K. pneumoniae obtained from different part of white turmeric plant. These mass signals spectra (3,853; 4,365; 6,292; 7,245; 7,384; 7,705; 9,140; and 9,479 m/z) are specific to K. pneumoniae. BIOTROPIA Vol. 25 No. 2, 2018 114 reference method. The results of MALDI-TOF MS analysis are indicated in percentages of similarity compared to spectra profiles of known s t r a i n i n S A R A M I S D a t a a s e S y s t e mb . Superspectra contain common peaks to different strains of the same species. iate Individual spectra correspond to the spectra of ed each strain cultivated under specific conditions. The manufacturer recommends validation of superspectra identifications with the confidence level between 85.00 and 99.9%. Accuracy of the identification strongly relies upon the robustness of the database and the choice of reference isolates. This is especially important when the genera involving species of environmental and clinical a high genetic diversity samples represents (Benagli 2012)et al. . The spectra were analysed in a mass range of 2 to 20 kDa and this mass range representing ribosomal proteins were obtained from bacterial extract. These proteins are numerous in the cell and are positively charged. Fig. 1 shows the representative results of spectral profiles from Klebsiella pneumonia based on the mass signals obtained. Isolated bacteria from different part of plant (rhizome, stem, leaves) and locations (Dar mag a and Bojong) showed similar identification due to their identical protein profiles which were indicated by mass spectra value. Three isolates of K. pneumoniae isolated from rhizome, stem and leaves of C. zedoaria plant showed almost the same spectral profiles. It had several specific mass signals 3,853; 4,365; 6,292; 7,245; 7,384; 7,705; 9,140; and 9,479 m/z. Each mass signal is specific at species and family level. Mass signal of 3,853; 6,292; 7,384; 7,705; and 9,479 m/z were specific for species level, while 4,365; 7,245; 9,140 m/z were specific for family level. According to these results, it is clear that each species of bacteria has specific mass spectra, and can be used as a taxonomic marker identification. Compared with the data presented in Table 1, these mass signals correspond to the superspectrum database of K. pneumoniae. The identification results obtained by MALDI-TOF MS and 16S rRNA gene sequencing shown in Table 2. of 66 isolates are Forty-three (43) of the 66 isolates (65.15%) showed the intepretable MALDI-TOF MS spectra By sequence comparison analysis, . MALDI-TOF MS spectra allowed good identification to the species, genus and family level total of 43 endophytic bacteria with a covering 16 genus and 21 species. An additional 11 isolates (16 67%) with the . gave similar results sequencing results, correctly identified to the and Mass (m/z) Identification level 3853.5 Species level 4155.3 Species level 4365.1 Family level 5381.6 Family level 6292.8 Species level 6384.1 Family level 6857.4 Family level 7165.8 Family level 7245.2 Family level 7272.7 Family level 7319.6 Family level 7384.9 Species level 7705.3 Species level 7735.2 Species level 8310.1 Family level 8852.1 Family level 9093.2 Species level 9140.1 Family level 9479.5 Species level 9852.3 Species level Table 1 Superspectrum database of K. pneumoniae 115 MALDI-TOF Mass Spectrometry for identification of endophyitic bacteria – Sulistiyani and Lisdiyanti Level of ID and isolates 16S rDNA sequencing MALDI-TOF MS Species ID Level of ID Species ID Reference database Correctly identified into species level DI.P.3 Alcaligenes faecalis Species Alcaligenes faecalis A RB.P.1 Bacillus subtilis Species Bacillus subtilis A RL.S.2 Enterobacter aerogenes Species Enterobacter aerogenes A RI.P.2 Enterobacter cloacae Species Enterobacter cloacae A BB.P.3 Klebsiella pneumoniae Species Klebsiella pneumoniae A RI.S.2 Klebsiella pneumoniae Species Klebsiella pneumoniae A RI.S.9 Klebsiella pneumoniae Species Klebsiella pneumoniae A RI.P.3 Pantoea dispersa Species Pantoea dispersa A DB.S.1 Pseudomonas stutzeri Species Pseudomonas stutzeri A RB.P.4 Pseudomonas stutzeri Species Pseudomonas stutzeri A RI.P.7 Stenotrophomonas maltophilia Species Stenotrophomonas maltophilia A Correctly identified into genus level RI.S.3 Acinetobacter calcoaceticus Genus Acinetobacter baumannii A DL.P.5 Bacillus safensis Genus Bacillus pumilus NA RI.P.5 Bacillus thuringiensis Genus Bacillus cereus/ mycoides/thuringiensis A RI.P.1 Burkholderia cenocepacia Genus Burkholderia sp. A DI.P.1 Enterobacter cancerogenus Genus Enterobacter sp. A DL.P.4 Enterobacter cancerogenus Genus Enterobacter cloacae A RI.P.8 Enterobacter ludwigii Genus Enterobacter sp. NA BI.P.3 Enterobacter ludwigii Genus Enterobacter sp. NA DB.P.1 Klebsiella pneumoniae Genus Enterobacteriaceae A RB.P.2 Klebsiella pneumoniae Genus Enterobacteriaceae A DI.P.4 Klebsiella variicola Genus Klebsiella pneumoniae NA RI.S.8 Klebsiella variicola Genus Klebsiella pneumoniae NA RB.S.3 Klebsiella variicola Genus Enterobacteriaceae NA BI.S.2 Klebsiella variicola Genus Klebsiella pneumoniae NA RI.P.4 Microbacterium trichothecenolyticum Genus Microbacterium arborescens NA DB.S.4 Micrococcus yunnanensis Genus Micrococcus luteus NA RI.S.7 Pantoea agglomerans Genus Pantoea dispersa A RI.S.6 Pseudomonas azotoformans Genus Pseudomonas fluorescens NA RB.P.3 Pseudomonas denitrificans Genus Pseudomonasnitroreducens NA DL.P.3 Pseudomonas denitrificans Genus Pseudomonas nitroreducens NA DB.S.3 Pseudomonas gessardii Genus Pseudomonas fluorescens NA DI.S.1 Pseudomonas korensis Genus Pseudomonas aeruginosa NA DI.S.6 Pseudomonas korensis Genus Pseudomonas sp. NA Not precisely identified BB.S.8 Bacillus subtilis Lysinibacillus sphaericus A BI.S.3 Citrobacter freundii Enterobacter sp. A DI.S.4 Microbacterium laevaniformans Klebsiella pneumoniae A BI.S.6 Microbacterium laevaniformans Arthrobacter russicus A BI.P.1 Microbacterium resistens Pseudomonas aeruginosa A DI.S.7 Microbacterium testaceum Oligella urethralis A BB.S.3 Microbacterium trichothecenolyticum Gordonia alkanivorans NA RI.P.6 Pseudomonas geniculata Stenotrophomonas maltophilia NA BI.S.1 Ralstonia mannitolilytica Rhizobium radiobacter A Not identified yet DB.P.2 Agrobacterium larrymoorei No ID NA DL.P.6 Bacillus subtilis No ID A BL.P.2 Bacillus subtilis No ID A RL.S.1 Bacillus safensis No ID NA RB.S.5 Bosea thiooxidans No ID NA RB.S.2 Enterobacter ludwigii No ID NA BB.P.4 Erwinia chrysanthemi No ID NA DL.S.1 Methylobacterium organophilum No ID NA BB.S.5 Microbacterium hominis No ID NA Table 2 Identification results for the 66 isolates obtained by MALDI-TOF MS in comparison to those obtained by 16S rDNA 116 BIOTROPIA Vol. 25 No. 2, 2018 species level; 23 isolates (34 85%) matched genus . level of molecular approach, and among them 3 isolates were identified to the family level. For three isolates (DB.P.1, RB.P.2, RB.S.3), MALDI- TOF MS correctly identified to the family level, whereas 16S r NA sequencing gave a species D identification. ine isolates (13 64%) were not N . accurately identified and 23 isolates (34 85%) were . rated as n- 3 .no identifiable (Table ) This study has proved that MALDI-TOF MS is useful for identification of microorganisms into species level in a relatively short time. Of the 66 isolates analyzed, 43 isolates (65.15%) were identified and 23 isolates (34.85%) were not identified (Table 3). Eleven isolates (16.67%) of 43 isolates showed good result, concordant with the 16S rDNA sequencing result. However, twenty-three isolates (34.85%) could not be identified. These included 12 isolates of Microbacterium genus, Mycobacterium cosmeticum, Mycobacterium simiae, Agrobacterium larrymoorei, Erwinia chrysanthemi, Xanthobacter flavus, Enterobacter ludwigii, Bosea thiooxidans, Stenotrophomonas maltophilia, Methylobacterium organophilum, Providencia vermicola, Phenylobacterium koreense, Bacillus safensis, Roseomonas mucosa, Rhizobium tarimense. Among them, 14 isolates could not be identified due to the absence of reference spectra database. Non-identifiable isolates for MALDI-TOF was as a result of an incomplete database, and can be resolved with the addition of appropriate reference. Supplementation of the MALDI-TOF database, can reduce the rate of non-identifiable results. Among 66 isolates of endophytic bacteria, 30 isolates had no reference spectra database (Table 3). Currently, a total of 1,309 references spectra are contained in SARAMIS Database System. This is inadequate to identify indigenous microbes that have been abundant in Indonesia. MALDI-TOF MS library can be enriched with protein profile of strain or species of indigenous microbes from Indonesia, and will be important for future studies. MALDI-TOF MS generates protein mass spectra which can be used for grouping and identification of bacteria. These mass spectra contain mainly peaks corresponding to ribosomal protein that are in abundance in the bacterial cell (Rhyzhov & Fenselau 2001). Protein profile of mass spectra will help in characterizing the Level of ID and isolates 16S rDNA sequencing MALDI-TOF MS Species ID Level of ID Species ID Reference database Correctly identified into species level Table 2 Continued RL.P.4 Phenylobacterium koreense No ID NA RL.P.1 Providencia vermicola No ID NA DI.S.5 Rhizobium tarimense No ID NA RL.S.3 Roseomonas mucosa No ID NA BL.P.1 Stenotrophomonas maltophila No ID A DL.P.2 Stenotrophomonas maltophila No ID A BB.S.7 Xanthobacter flavus No ID NA DB.S.2 Microbacterium laevaniformans No ID A BI.P.6 Microbacterium laevaniformans No ID A DI.S.2 Microbacterium resistens No ID A DI.S.3 Microbacterium testacneum No ID A DL.P.1 Microbacterium testaceum No ID A BL.S.2 Mycobacterium cosmeticum No ID NA BB.S.6 Mycobacterium simiae No ID A Note: A: Available; NA: Not Available Table 3 Distribution of the discrepancies observed in the MALDI-TOF MS Axima-SARAMIS Level of identification by MALDI-TOF MS No. (%) of Reference database Available Not available Total Correctly identified into species level 11 (16.67) 0 11 (16.67) Correctly identified into genus level 8 (12.12) 15 (22.73) 23 (34.85) Not precisely identified 7(10.60) 2 (3.03) 9 (13.64) Not identified yet 10 (15.15) 13 (19.70) 23 (34.85) Total 36(54.54) 30(45.46) 66 117 MALDI-TOF Mass Spectrometry for identification of endophyitic bacteria – Sulistiyani and Lisdiyanti incorrectly identified microbes by comparing its protein profile spectra to those in the reference spectra database. These spectra can generate patterns that provide unbiased identification of particular species and even genotypes within species. Data presented in Table 3, shows that 9 isolates were incorrectly identified. As stated earlier, each species of bacteria has specific protein profile mass spectra, therefore the identification result from MALDI-TOF MS should be same to the identification result of 16S rDNA. The result will be incorrect when experimental factors occur, such as sample contamination and/or sample preparation. MALDI-TOF MS analysis is affected by several experimental factors, such as matrix p r e p a r a t i o n , s p e c t r a l r e p r o d u c i b i l i t y, contaminants, sample preparation, mass range and measurement accuracy on the database search (Demirev et al. 1999). A total of 12 isolates of Microbacterium genus were incorectly identified, might be due to the complex structure of their cell walls. Specific sample extraction procedures to breakdown the cell wall are required before MALDI-TOF MS analysis. The process of sample preparation for identification of microbes depends upon the source of isolated microbe, or on chemical structure of the constituents of its cell wall. Different group of microbes has different sample preparation (Singhal et al. 2015). Alatoom et al. (2011) reported that sample extraction was needed for identification of Gram- positive bacteria. Furthermore, the lower score values, may be caused by the incomplete separation of protein. The protein interfered with the sample and disrupt the mass spectrum (Reich et al. 2013). Gram-positive bacteria like Mycobacterium sp., also require specific extraction procedure. The extraction was done by lysed cells in boiling water, followed by ethanol precipitation of proteins. The precipitated proteins were dried, resuspended in 70% formic acid and acetonitrile, and analyzed by MALDI-TOF MS (Verroken et al. 2010). To investigate the reproducibility of the instrument during the study we included InaCC , strains in every analysis of identifications as positive controls and reference isolates. The instruments correctly identified the control strains. The incorrect identification by MALDI- TOF MS was to sample preparation attributed failure such as sample volume and the large also, amount of matrix was not sufficient. Consequently the sample and matrix were not completely mix and only a few small crystal ed were obtained. A sufficient number of bacterial cells (typically ~10 cells per well) are required to 4 generate detectable MALDI-TOF MS ion signals (Chiu 2014). Lohman et al. (2013) reported that MALDI- TOF system succesfully identified 312 isolates. Furthermore 2,860 of 2,900 (99%) samples identified by MALDI-TOF MS matched with the identification results obtained using other methods (standard and high end microbiological identification methods including automated b i o c h e m i c a l a n a l y s e s a n d m o l e c u l a r identification) (Reich et al. 2013). Study of Guo et al. (2014) informed that using MALDI-TOF MS for 1,025 isolates, 1,021 (99.60%) isolates were accurately identified at the genus level, and 957 (93.37%) isolates at the species level. Theel et al. (2012) reported that from 90 yeast and 78 Corynebacterium species isolates, were obtained 95.6% and 81.1% of yeast, also 96.1% and 92.3% of Cor ynebacterium isolates were correctly identified to the genus and species levels, respectively. As compared to other studies, the result of this study showed small percentage of correctly identified to the genus and species levels, however this method provide reliable results. Therefore MALDI-TOF MS could be used for screening and grouping of large numbers o f b a c t e r i a l i s o l a t e s. M i c r o o r g a n i s m identification by mass spectrometry is already considered as a revolution of bacteriology, offering many advantages compared with the conventional biochemical identification of microorganisms. Within the next few years MALDI-TOF-MS based identification of microorganisms will replace conventional methods. CONCLUSION Among the 66 selected isolates, 43 isolates were identified. Eleven isolates (16.67%) that were tested matched on species level of molecular approach. Spectral analysis of microbial diversity from Indonesia is one way to build up the MALDI-TOF MS library. rotein profile spectra P of each species be used as ataxonomic could marker. MALDI-TOF MS systems for bacterial 118 BIOTROPIA Vol. 25 No. 2, 2018 identification was good for grouping large number of isolates. However molecular analysis also must be done as a standard reference. 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