(2016) potential sequencing for detection of pathogenic bacteria
- 1. Potential of high-throughput sequencing for broad-range detection of pathogenic bacteria in spices and herbs M. Planý a, b , K. Soltys c , J. Budis d , A. Mader e , T. Szemes f , P. Siekel a, b , T. Kuchta a, * a Department of Microbiology, Molecular Biology and Biotechnology, Food Research Institute, National Agricultural and Food Centre, Priemyselna 4, SK- 82475 Bratislava, Slovakia b Department of Biology, Faculty of Natural Sciences, University of Ss. Cyril and Methodius, Nam. J. Herdu 2, SK-91701 Trnava, Slovakia c Comenius University Science Park, Ilkovicova 8, SK-84104 Bratislava, Slovakia d Department of Computer Science, Faculty of Mathematics, Physics and Informatics, Comenius University, Mlynska dolina, SK-84248 Bratislava, Slovakia e German Federal Institute for Risk Assessment, Department Biological Safety, Unit Microbial Toxins, Max-Dohrn-Straße 8-10, D-10589 Berlin, Germany f Department of Molecular Biology, Faculty of Natural Sciences, Comenius University, Ilkovicova 6, SK-84215 Bratislava, Slovakia a r t i c l e i n f o Article history: Received 12 September 2016 Received in revised form 12 December 2016 Accepted 14 December 2016 Available online xxx Keywords: Food safety Staphylococcus aureus Salmonella enterica Escherichia coli Paprika a b s t r a c t A broad-range culture-independent method was developed and evaluated regarding its sensitivity of detection of pathogenic bacteria in spices and herbs, with focus on paprika powder. The method involved DNA extraction using cetyltrimethylammonium bromide (CTAB), 16S rDNA amplification using universal bacterial polymerase chain reaction, and high-throughput sequencing on Illumina MiSeq platform. The sensitivity of the method was evaluated with series of model samples contaminated at different levels with Salmonella enterica and Escherichia coli (as representatives of Gram-negative bacteria) and Staph- ylococcus aureus (as a representative of Gram-positive bacteria). For spices (paprika, black pepper), the method had a screening-level sensitivity with limits of detection in the range of 104 e105 CFU/g, and a semi-quantitative response. Low sensitivity (LOD !107 CFU/g) was observed with herbs (oregano, parsley). The developed method demonstrated a good potential for microbiological screening of spices, with a prospect of further improvement of sensitivity based on progress in high-throughput sequencing technology. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction Spices and herbs are widely used as additives to foods either at culinary preparation of meals at home or at industrial production of processed foods. These minor components of foods are also known as important vehicles of pathogenic bacteria, thus contributing to the food-borne illness burden. In this regard, Salmonella enterica is the most frequent pathogenic bacterium in spices, followed by Bacillus spp. and Clostridium perfringens (EFSA, 2013; Food and Agriculture Organization of the United Nations (FAO) World Health Organization (WHO), 2014; Lehmacher, Bockemühl, Aleksic, 1995; Van Doren et al.,2013; Zweifel Stephan, 2012). As certain types of spices and herbs are imported from geographically distant countries, they can be contaminated with microorganisms that are unusual in the place of processing and consumption. The microbial contamination is, in case of this com- modity, more likely to reach the consumer as spices and herbs can only to a limited extent be antimicrobially treated prior to packing and distribution, as this would affect their organoleptic properties. Due to the established practice of controlling only selected patho- genic, toxinogenic and indicator microorganisms, “exotic” or un- usual microorganisms may escape detection by routine control laboratories. The coverage of the control system could be improved if a broad-range detection method is available. However, such method should be sensitive enough to be compatible with food safety requirements. A candidate for this purpose is the 16S rDNA- based metagenomic approach, which has become recently more attractive as the supporting technology, high-throughput sequencing, has become widely available (Ju Zhang, 2015; Karlsson et al., 2013; Mayo et al., 2014). In case of characterization of bacterial consortia, the approach is based on isolation of total DNA from the sample, amplification of a fragment of 16S rDNA, which is universally present in bacteria, high-throughput sequencing and data processing in order to* Corresponding author. E-mail address: kuchta@vup.sk (T. Kuchta). Contents lists available at ScienceDirect Food Control journal homepage: www.elsevier.com/locate/foodcont http://dx.doi.org/10.1016/j.foodcont.2016.12.026 0956-7135/© 2016 Elsevier Ltd. All rights reserved. Food Control xxx (2016) 1e5 Please cite this article in press as: Planý, M., et al., Potential of high-throughput sequencing for broad-range detection of pathogenic bacteria in spices and herbs, Food Control (2016), http://dx.doi.org/10.1016/j.foodcont.2016.12.026
- 2. identify individual taxons or groups of taxons. Isolation of DNA always needs to be adapted to the matrix, taking into account its physical and chemical properties, and should produce amplifiable DNA. Regarding spices and herbs, a wide evaluation of DNA isola- tion methods (both based on solid-phase extraction, SPE, and liquid-liquid extraction, LLE) was performed previously and the LLE technique with treatment with cetyltrimethylammonium bromide (CTAB; Jankiewicz, Broll, Zagon, 1999) was adapted to a range of matrices of this type, such as ground red paprika, black pepper, cinnamon, parsley, oregano and thyme. The adaptation consisted in using different volumes of solutions and different centrifugation speeds (Minarovicova et al., 2017). This study was aimed at adaptation and evaluation of the met- agenomic approach based on high-throughput sequencing for the detection of pathogenic and toxinogenic bacteria in spices and herbs. Because the power of the approach at characterization of diversity in microbial consortia is well established, the main parameter of our interest was the sensitivity of the approach. The evaluation was based on determination of detection limits using series of model samples of paprika (as a representative of spices) and oregano (as a representative of herbs) contaminated at different levels with Salmonella enterica or Escherichia coli (as rep- resentatives of Gram-negative bacteria) and Staphylococcus aureus (as a representative of Gram-positive bacteria). Additionally, the potential of Staph. aureus detection in black pepper and parsley were also analysed. In order to eliminate possible strain-specific properties, regarding susceptibility of bacterial cells to lysis and subsequent DNA extractability, mixtures of three strains were al- ways used for preparation of model samples. 2. Materials and methods 2.1. Plant material used Dried fruits of paprika (Capsicum annuum) and black pepper (Piper nigrum), ground to the particle size of 140 mme355 mm and 500 mm respectively, microbiologically decontaminated by steam treatment, and untreated dried leaves of oregano (Oreganum vul- gare) and parsley (Petroselinum crispum), ground to the particle size of 355 mm and 300 mm respectively, were obtained from FUCHS Gewürze GmbH, Dissen, Germany. The samples were specifically prepared for research use in frames of the SPICED project. 2.2. Microorganisms Salmonella Infantis Lj 9 was a food isolate from University of Ljubljana, Slovenia; S. Typhimurium CCM 4419 was a collection strain from Czech Collection of Microorganisms, Brno, Czech Re- public; S. Enteritidis SVU 26 was a food isolate from Veterinary and Food Institute in Bratislava, Slovakia. Escherichia coli CCM 2024 and E. coli CCM 3988 were collection strains from Czech Collection of Microorganisms, Brno, Czech Republic, and E. coli SZU 106 was a food isolate from National Institute of Public Health, Center for Health, Nutrition and Food, Brno, Czech Republic. Staphylococcus aureus NCTC 10656 was a collection strain obtained from National Collection of Type Cultures, Salisbury, United Kingdom, Staph. aureus VUP 622 was isolated from food and identified in Food Research Institute NAFC, Bratislava, Slovakia, and Staph. aureus HPL 468/1 was a clinical isolate from HPL Laboratories of Clinical Microbiology, Bratislava, Slovakia. Pure cultures of each strain were grown for 16e18 h in Brain Heart Broth (Merck, Darmstadt, Ger- many) at 37 C with shaking of 2 Hz. 2.3. Preparation of model samples Pure bacterial suspensions of three strains of each species were mixed at a ratio of 1:1:1; (v/v/v). The obtained mixture was deci- mally diluted (101 e107 -fold) with 9 g/L NaCl. Densities of diluted bacterial suspensions were checked by plating on Baird-Parker agar (Merck) for Staph. aureus, on Xylose lysine deoxycholate agar (Merck) for S. enterica, and on Chromocult coliform agar (Merck) for E. coli. The plates were incubated at 37 C and colonies were counted after 24 h and 48 h. An amount of 1 g of dried mild paprika powder was contaminated with 100 mL of a strain mixture of a specified density, to obtain contamination levels ranging from 101 to 107 CFU per gram of matrix. 2.4. DNA extraction DNA was extracted from samples, including uncontaminated matrices, by a chaotropic liquid-liquid extraction (LLE) method using cetyltrimethylammonium bromide (CTAB; Official Collection of Test Methods, 1998; Jankiewicz et al., 1999) modified by Minarovicova et al. (2017). The success of DNA extraction from samples with different contamination levels was checked by real- time polymerase chain reaction (PCR) according to Minarovicova et al. (2017). DNA from bacterial strains was extracted by chaot- ropic solid-phase extraction using DNeasy Blood and Tissue kit (Qiagen, Hilden, Germany). 2.5. DNA amplification A fragment of 16S rDNA was amplified by PCR using a temper- ature programme composed of initial denaturation step (95 C for 2 min), followed by 35 cycles (94 C for 1 min; 54 C for 1 min; 72 C for 2 min) and final polymerization step (72 C for 10 min). Each sample of extracted DNA was amplified in 6 replicates to increase the amount of the product. The reaction volume (25 mL) contained 2.5 mL Cheetah Taq Dilution Buffer (Biotium, Hayward, CA, USA), 1.5 mM MgCl2, 250 mM of each dNTP (Applied Biosystems, Foster City, CA, USA), 500 nM of primer 27F (50-AGA GTT TGA TCM TGG CTC AG-30; Lane, 1991), 500 nM of primer 1062R (50-ACA GCC ATG CAG CAC CT-30; Youssef et al., 2009; both oligonucleotides syn- thesized by Sigma-Aldrich), 1.5 U Cheetah Hotstart Taq DNA poly- merase (Biotium) and 3 mL of the template DNA solution. PCR was carried out in a Veriti thermocycler (Applied Biosystems). After PCR, the products were analysed by 1.5% agarose gel electropho- resis using 100 bp DNA Ladder (Biolabs, Ipswich, MA, USA) to check the amplicon homogenity, replicates were pooled and purified by QIAquick PCR Purification Kit (Qiagen). 2.6. High-throughput sequencing PCR product clean-up was carried out by Zymo DNA Clean and Concentrator-5 (Zymo Research, Irvine, CA, USA) according to the standard protocol. Sample quantification was carried out by Qubit High sensitivity assay (Life Technologies, Carlsbad, CA, USA), which enabled precise concentration determination and further sample dilution to 0.2 ng/ml. An amount of 0.5 ng of sample in a volume of 2.5 mL was used for transposome-based shot-gun library prepara- tion using Nextera XT Library Preparation Kit (Illumina, San Diego, CA, USA) by a protocol optimized to the initial amount of sample. All amplicons (also shorter than 500 bp) generated by sample tag- mentation and further PCR amplification were recovered by use of 1.8Â Agencourt AMPure XP (Beckman Coulter, Brea, CA, USA). The molarity of the final DNA library was assessed and calculated from library fragment size (bp) determined by Agilent 2100 Bioanalyzer (Agilent Technologies, Waldbronn, Germany) and library M. Planý et al. / Food Control xxx (2016) 1e52 Please cite this article in press as: Planý, M., et al., Potential of high-throughput sequencing for broad-range detection of pathogenic bacteria in spices and herbs, Food Control (2016), http://dx.doi.org/10.1016/j.foodcont.2016.12.026
- 3. concentration was measured by Qubit 2.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA, USA). Dual indexing of amplicons was used, which enabled paired-end sequencing on Illumina MiSeq platform using MiSeq Sequencing Kit v3 (Illumina, San Diego, CA, USA). 2.7. Data processing Sequence data were first analysed by MiSeq Reporter (MSR) Metagenomics Workflow with default parameters. Because of different numbers of reads generated in individual runs (ranging from approx. 142 000 to 1 980 000), subsets of 100 000 reads were extracted randomly from the data set of each sample. Alternatively, low quality ends of reads were trimmed using Trimmomatic (Bolger, Lohse, Usadel, 2014) with parameters SLIDINGWINDOW: 5:20, HEADCROP: 11 and MINLEN:35. Fragments with sufficient size of both reads were assembled into contigs by Emirge (Quast et al., 2013) guided by 16S reference sequences from the Silva database, version v119 (Quast et al., 2013). Chimeric contigs were further filtered by UCHIME (Miller, 2011) to exclude artificial con- tigs. Remaining contigs were annotated with taxonomic labels based on closest homologue in the Silva database. Trimmed reads were alternately classified by Metaxa2 (Bengtsson-Palme et al., 2015). Final taxonomy graphs were generated by Krona (Ondov, Bergman, Phillippy, 2011). 3. Results and discussion A broad-range culture-independent method for detection of pathogenic bacteria in spices and herbs was developed and eval- uated in this study, using series of artificially contaminated sam- ples. The method involved DNA extraction using cetyltrimethylammonium bromide (CTAB), 16S rDNA amplification using universal bacterial PCR, and high-throughput sequencing on Illumina MiSeq platform. Sensitivity (in terms of limits of detection, LOD) and response proportionality (quantification potential) were evaluated, taking into account also comparison of different bio- informatic processing procedures. The method was evaluated for analysis of red paprika powder and oregano, supported by analysis of Staph. aureus in black pepper and parsley. The study utilized series of model samples of mild red paprika powder contaminated at different levels with S. enterica or E. coli (as representatives of Gram-negative bacteria) and Staph. aureus (as a representative of Gram-positive bacteria). Results of evaluation of sensitivity (LOD) of high-throughput sequencing at the detection of S. enterica, E. coli and Staph. aureus in paprika are presented in Tables 1 and 5. As LOD, a minimum contamination level was taken, which produced, in both replicates, the percentage of positive reads greater, by at least an order of magnitude, than the background. The determined LODs of 104 e105 CFU/g are sufficient for broad-range screening purposes, but considerably high when compared with species-specific microbiological detection methods for food (ISO 6579:2002, ISO 6888-3:2003). Therefore, a method with such sensitivity would have to be treated as a “screening method”, i.e. negative results should not be taken as definitive. Regarding the potential of the method to produce quantitative results, data in Table 1 demonstrate that, by all three data pro- cessing methods, percentages of positive reads for increasing contamination levels were clearly increasing. Such results show the semi-quantitative character of the detection. Regarding sensitivity, certain differences were observed when using different data processing methods. Different accuracy was demonstrated already at sequencing 16S rDNA from pure cultures (Table 2). Further differences were observed at analysing full data sets versus subsets of 100 000 reads. The evidence of read number influence was the analysis by Emirge, where LODs for E. coli in paprika and Staph. aureus in black pepper were shifted from 105 to 104 CFU/g (from 0.00 to 8.98/10.3% and 1.19/1.42%, respectively; Tables 1 and 4). On the other hand, false positive results were recorded as presence of Salmonella in paprika powder contaminated artificially by Staph. aureus. Also in results from full data analysed by Metaxa, many false positive reads were registered, probably as an intrinsic feature of this method, and therefore only results above 1.00% were taken into account as percent of classified reads. Comparable sensitivity of the method (LODs of 104 e105 CFU/g) was determined for Staph. aureus in black pepper. However, low sensitivity (LODs ranging from 106 to 107 CFU/g or higher) was demonstrated for the three bacteria in oregano (Table 3) and for Staph. aureus in parsley (Table 4). These data suggest that the po- tential of this method could be limited to spices and non-green Table 1 Percentage of positive reads detected by MSR, Emirge and Metaxa in paprika (1st replicate/2nd replicate) for three pathogens on genus level. Contamination level (CFU/g) Percentage of positive reads (%) Salmonella Escherichia Staphylococcus MSR Emirge Metaxa MSR Emirge Metaxa MSR Emirge Metaxa 100 0.03/0.00 0.00/0.00 0.00/0.00 0.04/0.05 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 101 0.02/0.02 0.00/0.00 0.00/0.00 0.03/0.04 0.00/0.00 0.00/0.00 0.01/0.01 0.00/0.00 0.00/0.00 102 0.00/0.03 0.00/0.00 0.00/0.00 0.07/0.08 0.00/0.00 0.00/0.00 0.01/0.01 0.00/0.00 0.00/0.00 103 0.04/0.04 0.00/0.00 0.00/0.00 0.28/0.35 0.00/0.00 0.00/0.00 0.01/0.02 0.00/0.00 0.00/0.00 104 0.28/0.24 0.00/0.00 0.00/0.00 2.52/2.49 0.00/0.00 (8.98/10.3) 4.29/4.49 0.08/0.11 0.00/0.00 0.00/0.00 105 2.58/2.46 7.59/6.04 2.32/2.12 13.9/14.8 52.3/52.6 24.7/24.6 1.68/1.91 3.65/2.85 1.78/2.01 106 19.9/20.1 40.3/38.8 16.9/16.6 30.8/32.9 94.3/94.2 49.7/51.9 n. d. n. d. n. d. Underlined data indicate contamination levels corresponding with LOD. Data in brackets were calculated from full set, i.e. without extracting a 100 000 read subset. n. d. e not done. Table 2 Percentage of positive reads assigned to given genera of pathogens detected in pure strain cultures by the given approach. Strain Percentage of positive reads (%) MSR Emirge Metaxa S. Infantis Lj 9 14.3 100 45.8 S. Typhimurium CCM 4419 17.8 100 41.7 S. Enteritidis SVU 26 15.3 100 42.6 E. coli CCM 2024 28.5 100 61.0 E. coli CCM 3988 32.7 100 62.8 E. coli SZU 106 34.5 100 60.5 Staph. aureus NCTC 10656 75.1 100 90.4 Staph. aureus VUP 622 73.2 100 89.7 Staph. aureus HPL 468/1 75.6 100 91.6 M. Planý et al. / Food Control xxx (2016) 1e5 3 Please cite this article in press as: Planý, M., et al., Potential of high-throughput sequencing for broad-range detection of pathogenic bacteria in spices and herbs, Food Control (2016), http://dx.doi.org/10.1016/j.foodcont.2016.12.026
- 4. plant materials (summarized in Table 5). A possible reason may be the competition of chloroplast 16S rDNA, as 80e90% of reads from oregano and parsley were classified as chloroplast DNA (paprika 40e60%, black pepper 10e20%; data not shown). This limitation could be overcome by choosing different primers to amplify spe- cifically bacterial 16S rDNA in the excess of plant DNA (Dorn-In, Bassitta, Schwaiger, Bauer, H€olzel, 2015). Results of our study present preliminary evaluation of the approach, as performed on a limited number of samples, but illustrate its overall potential. It can be anticipated that further development of the technique will lead to a certain improvement in its sensitivity, which will lead to a “stronger positive signal” or to a “weaker background signal”. This will be facilitated by the progress in high-throughput sequencing technology (regarding number of reads per sample, read length, reduction of error rate) and by extending 16S rDNA sequence databases. Another way to improve the performance of 16S rDNA amplicon-based high-throughput sequencing at broad-range analysis of pathogenic bacteria in spices and herbs may be the implementation of an internal standard based on certain bacteria surely absent from the analysed matrix. Acknowledgements This research was carried out in frames of the FP7-SEC-2012-1 project „Securing the spices and herbs commodity chains against deliberate, accidental or natural biological and chemical contami- nation (SPICED, No. 312631)“. The study is a result of imple- mentation of project REVOGENE e Research centre for molecular genetics (ITMS 26240220067) supported by the Research and Development Operational Programme funded by ERDF. Authors thank to Dr. H. Drahovska and Dr. E. Kaclíkova for valuable dis- cussions, and to Dr. K. Zenisova, Dr. J. Minarovicova and T. Cab- icarova for technical assistance. References Bengtsson-Palme, J., Hartmann, M., Eriksson, K. M., Pal, C., Thorell, K., Larsson, D. G., et al. 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Contamination level (CFU/g) Percentage of positive reads (%) Salmonella Escherichia Staphylococcus MSR Emirge Metaxa MSR Emirge Metaxa MSR Emirge Metaxa 100 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 101 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 102 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 103 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 104 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 105 0.00/0.00 0.00/0.00 0.00/0.00 0.01/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 106 0.00/0.12 0.00/0.00 0.00/0.00 0.17/0.14 0.00/0.00 0.00/0.00 n. d. n. d. n. d. 107 2.37/2.85 4.75/4.88 2.16/2.54 n. d. n. d. n. d. n. d. n. d. n. d. Underlined data indicate contamination levels corresponding with LOD. n. d. e not done. Table 4 Percentage of positive reads for Staphylococcus spp. detected by MSR, Emirge and Metaxa in black pepper and parsley (1st replicate/2nd replicate). Contamination level (CFU/g) Percentage of positive reads (%) Black pepper Parsley MSR Emirge Metaxa MSR Emirge Metaxa 100 0.13/0.01 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 101 n. d. n. d. n. d. 0.00/0.00 0.00/0.00 0.00/0.00 102 n. d. n. d. n. d. 0.00/0.00 0.00/0.00 0.00/0.00 103 0.14/0.05 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 0.00/0.00 104 0.59/0.57 0.00/0.00 (1.19/1.42) 1.51/1.41 0.00/0.00 0.00/0.00 0.00/0.00 105 12.3/6.08 20.6/21.9 13.4/13.0 0.00/0.00 0.00/0.00 0.00/0.00 106 40.1/21.4 61.4/62.3 44.1/44.3 0.00/0.00 0.00/0.00 0.00/0.00 107 n. d. n. d. n. d. 0.00/0.00 0.00/0.00 0.00/0.00 Underlined data indicate contamination levels corresponding with LOD. Data in brackets were calculated from full set, i.e. without extracting a 100 000 read subset. n. d. e not done. 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