1 st International Olive Conference Table Olives: Pursuing Innovation - Exploring Trends Thessaloniki, Greece, 24-26 May 2018 Deciphering the microbiota of Greek table olives - A metagenomics approach Effie Tsakalidou Professor of Food Biochemistry Department of Food Science and Human Nutrition Agricultural University of Athens Iera Odos 75, 11855 Athens, Greece 1
Introduction 2
From Goddess Athena to table 3
Major varieties of Greek table olives Chalkidikis Trend Trend Production (tons) 123.000 Production (tons) 80.000 Producers 13.000 Producers 34.500 Trees 10.000.000 Trees 20.000.000 Kalamon Other Trend Trend Production (tons) 70.000 Production (tons) 6.000 Producers 13.500 Producers 1.000 Trees 10.000.000 Trees 1.000.000 http://www.ypaithros.gr 4
Overall production is Greece is increasing https://www.oliveoiltimes.com 5
Table Olives Microbiota Table olive fermentation occurs spontaneously, driven by the indigenous microbiota of the olives, without adding starter cultures The fermentation process is carried out by Lactic Acid Bacteria (e.g. Lb. plantarum) and Yeasts (e.g. Pichia sp., Candida sp.) Lactic Acid Bacteria are mainly responsible for the brine acidification providing microbiological stability and extended shelf life to the final product Yeasts mainly shape aroma and taste, degrade phenolic compounds and enhance the growth of Lactic Acid Bacteria Bonatsou et al. (2017) 6
Microbial biogeography Is the study of microbial diversity over time and space in an ecosystem, among others, in fermented foods It reveals the association of food microbial communities with the raw material environmental conditions processing technology High-throughput sequencing (HTS) technologies Metagenomics (diversity assay and shotgun) the study of the metagenome (the collective genome of microorganisms from a sample) that provides information on the microbial diversity & ecology of a specific ecosystem 7
Abundance of HTS studies of fermented foods and beverages grouped according to the food matrix De Filippis et al. (2017) 8
Pros and cons of shotgun metagenomics De Filippis et al. (2017) 9
Here we discuss the microbial ecology of Greek table olives prepared from 3 olive varieties in 3 different geographical regions of Greece using conventional microbiological analysis a metagenomics approach 10
Experimental set-up 11
Samples Kerasoelia (Mount Athos) (Amfissa region) Kalamon 12
Classical microbiological analysis 1. Total mesophilic microflora 2. Lactic acid bacteria isolation of colonies 3. Yeasts isolation of colonies 4. Propionic acid bacteria 5. Enterobacteriaceae 6. Pseudomonas 13
Identification of isolates A. Clustering Rep-PCR Bacteria BOXA1R primer Yeast (GTG) 5 primer B. Identification at the species level Bacteria 16S rdna 16S (F) / 16S (R) primers Yeasts ITS DNA ITS1 / ITS4 primers 14
Metagenomic analysis 1. Total DNA extraction in house protocol 2. DNA quality electrophoretically 3. Presence of Bacteria 16S rdna primers 27 (F) / 519 (R) Yeasts ITS DNA primers ITS1 (F) / ITS2 (R) Plant Actin Actin1 (F) / Actin2 (R) primers 4. Diversity Assay Illumina ΜiSeq platform 15
Results 16
log cfu/ml Microbial counts of lactic acid bacteria & yeasts 8.0 7.0 6.0 5.0 4.0 Kerasoelia (Mount Athos) Kalamon (Amfissa Region) 3.0 2.0 1.0 0.0 lactic acid bacteria yeast 17
rep-pcr 16S rrna gene sequencing M3: Pediococcus ethanolidurans BACTERIA M20: Pediococcus ethanolidurans M21: Pediococcus ethanolidurans M5: Pediococcus ethanolidurans M35: Lactobacillus plantarum M28: Lactobacillus plantarum M32: Lactobacillus plantarum M33: Lactobacillus plantarum M13: Lactobacillus plantarum M36: Lactobacillus plantarum M37: Lactobacillus plantarum M18: Lactobacillus plantarum 18
: Pichia membranifaciens : P. membranifaciens YEASTS : P. membranifaciens : P. membranifaciens : P. membranifaciens rep-pcr and ITS DNA sequencing : P. membranifaciens : P. membranifaciens : Groenewaldozyma auringiensis : G. auringiensis : Saccharomyces cerevisiae Candida cellae 87% Candida etchellsii 86% Candida apicola 85% Candida floris 83% Starmerella meliponinorum 83% C. cellae 87% C. etchellsii 86% C. apicola 85% C. floris 83% S. meliponinorum 82% : S. cerevisiae 19
Isolates Kerasoelia (Mount Athos) Kalamon (Amfissa Region) Total Lactic acid bacteria Lactobacillus plantarum/pentosus 39 15 12 66 Lactobacillus casei/paracasei 7 7 Lactobacillus brevis 6 6 Pediococcus parvulus 9 9 Pediococcus ethanolidurans 15 15 Yeasts Pichia membranifaciens 11 14 17 42 Saccharomyces cerevisiae 16 16 Groenewaldozyma auringiensis 10 10 Total 61 37 29 44 171 20
Extraction of total DNA 0 1 2 3 4 0 1 2 No Sample DNA ng/well 260/280 1 Kalamon 600 1.9 2 600 2.0 3 (Amfissa Region) 600 1.8 4 S. macedonicus (+) 600 1.9 No Sample DNA ng/well 260/280 1 Kerasoelia (Mount Athos) 600 1.9 2 S. macedonicus (+) 600 1.9 0: MM ladder 21
Confirmation of bacteria and yeast DNA * * * * * 1 2 3 4 5 6 7 8 9 Bacteria Yeast Plant Bacteria Yeast Plant No Sample No Sample No Sample No Sample No Sample No Sample 1 blank 2 3 Kalamon 6 blank 7 8 Kalamon 12 blank 13 14 Kalamon 1 Kerasoelia (Mount Athos) 2 S. macedonicus (+) 3 blank 4 Kerasoelia (Mount Athos) 5 S. pombe (+) 6 blank 7 Kerasoelia (Mount Athos) 8 S. pombe (-) 9 blank 4 (Amfissa Region) 5 S. macedonicus (+) 9 (Amfissa Region) 10 S. pombe (+) 11 S. macedonicus (-) 15 (Amfissa Region) 16 S. pombe (-) 17 S. macedonicus (-) Olive samples (+) control 18 Koroneiki (+) *: MM ladder 22
Bacteria genera Kerasoelia (Mount Athos) Raoultella (2%) Cellulosimicrobium (17%) Citrobacter (2%) Leuconostoc (2%) Lactobacillus (74%) Kalamon Bacteroides (3%) Cellulosimicrobium (90%) Pseudomonas (2%) Lactobacillus (4%) Cellulosimicrobium (90%) Pediococcus (3%) (Amfissa Region) Cellulosimicrobium (39%) Lactobacillus (12%) Idiomarina (13%) Halanaerobium (10%) Salinicola (17%) 23
Kerasoelia (Mount Athos) Yeast genera Marasmius (5%) Sporobolomyces (6%) Debaryomyces (5%) Saccharomyces (50%) Taphrina (6%) Kalamon Kluyveromyces (3%) Debaryomyces (7%) Kluyveromyces (3%) Debaryomyces (6%) Kluyveromyces (2%) (Amfissa Region) Schwanniomyces (11%) Debaryomyces (9%) Pichia (80%) Pichia (86%) Pichia (69%) 24
Differences at dominant bacteria genera level Genus (%) Kerasoelia (Mount Athos) Kalamon (Amfissa Region) Cellulosimicrobium 17 90 90 39 Lactobacillus 74 1.2 4 12 Differences at dominant yeast genera level Genus (%) Kerasoelia (Mount Athos) Kalamon (Amfissa Region) Pichia 0.01 80 86 69 Saccharomyces 50 0.01 0.01 0.04 25
Kerasoelia (Mount Athos) leptolyngbya spp. streptococcus thermophilus Bacteria species Lactobacillus brevis (17%) Citrobacter freundii (2%) Lactobacillus sp. (39%) Cellulosimicrobium cellulans (17%) Lactobacillus paracasei (6%) Pseudomonas fragi (1%) Kalamon (Evoia Olive.Kalamon Island) Bacteroides sp. (3%) Carnobacterium maltaromaticum (2%) Cellulosimicrobium cellulans (90%) Lactococcus lactis (1%) (Evoia Olive. Island) Lactobacillus buchneri (3%) Pediococcus parvulus (3%) Cellulosimicrobium cellulans (90%) Lactobacillus plantarum (11%) Olive.Amfissa (Amfissa Region) Salinicola halomonas salaria (16%) Lactobacillus plantarum (6%) Idiomarina sp. (13%) Halanaerobium salsuginis (10%) Cellulosimicrobium cellulans (39%) 26
Kerasoelia (Mount Athos) Yeast species Taphrina kruchii (5%) Debaryomyces hansenii (5%) Saccharomyces bayanus (50%) Sporobolomyces singularis (6%) Marasmius menieri (5%) Kalamon Olive.Kalamon Debaryomyces hansenii (7%) Olive. Debaryomyces hansenii (6%) Pichia manshurica (15%) Olive.Amfissa (Amfissa Region) Debaryomyces hansenii (9%) Schwanniomyces etchellsii (11%) Pichia manshurica (46%) Pichia membranifaciens (33%) Pichia membranifaciens (71%) Pichia manshurica (28%) Pichia membranifaciens (40%) 27
Differences at dominant bacteria species level Species (%) Kerasoelia (Mount Athos) Kalamon (Amfissa Region) Cellulosimicrobium cellulans 17 90 90 39 Lactobacillus brevis 17 0.002 0.003 0.2 Differences at dominant yeast species level Species (%) Kerasoelia (Mount Athos) Kalamon (Amfissa Region) Saccharomyces bayanus 50 0.01 0.01 0.03 Pichia manshurica 0 46 15 28 Pichia membranifaciens 0.01 33 71 40 28
Conclusions The present work is one of the first metagenomics approaches of naturally fermented Greek table olives It clearly reveals the impact of the cultivar and the environmental conditions on the table olives microbiota However, a more thorough study is needed, including samples from all Greek varieties and with a much broader geographical dispersion It highlights the need of a polyphasic and holistic fingerprinting approach in a food ecosystem 29
The group Kostas Papadimitriou, PhD Maria Kazou, PhD student Voula Alexandraki, PhD student & Marina Georgalaki, PhD Rania Anastasiou, PhD Georgia Zoumpopoulou, PhD Eugenia Manolopoulou, MSc PAVET (2014-2016) Developing methodologies for complete quality control-characterization of bioactive molecules of extra virgin olive oil and table olives, using modern techniques and chemometric analysis 30
Thank you for your attention! 31