47 1 Vol.47, No.1 2016 1 OCEANOLOGIA ET LIMNOLOGIA SINICA Jan., 2016 * ( 116023) (Apostichopus japonicus),, 3, 9 26503 37825, 1502 5741 (OTUs) : (1), 3 ; (2) 9 26,, 17 ; (3),, 50.54% 99.91% ; ; S917.1 doi: 10.11693/hyhz20150300088 (Apostichopus japonicus), (Bordbar et al, 2011; Purcell et al, 2012),,,, (Wang et al, 2005), (, 2006; Deng et al, 2009; Li et al, 2010a), (Paerl et al, 2003; Luo et al, 2006),,,, (Amann et al, 1995; Hugenholtz et al, 2009),, (Rosselló-Mora et al, 2001; Auguet et al, 2009),, 16S rdna,, 16S rrna, PCR,, (Youssef et al, 2009; Caporaso et al, 2011), (2010) (2010) (2014), DGGE DGGE,, ;, *, 201105007-2,, E-mail: yandou1989@126.com :,,, E-mail: dingjun1119@dlou.edu.cn : 2015-03-24, : 2015-06-15
1 : 123 16S rrna,,, 16S rrna,,,, (Bell et al, 2013; Ren et al, 2015; Yang et al, 2015), Miseq ( ) ( ),, 1 1.1 2014 10 11 ( ) ( 1) 40cm 1L, 2 5cm 100g(, 2010), 表 1 样品标记信息 Tab.1 Labels of samples DJ1 DJ2 DJ9 DJ5 DJ6 DJ11 DJ12 DJ13 DJ14 1.2 DNA 0.22μm DNA OMEGA DNA (OMEGA Water DNA Kit, D5525) DNA (OMEGA Soil DNA Kit, D5625) 16S rrna V3-V4 : 341F (5 -CCTACGGGNG GCWGCAG-3 ) 805R (5 -GACTACHVGGGTATCTA ATCC-3 ) ( ) Illumina Miseq 1.3,, : : (1) Prinseq (PRINSEQ-lite 0.19.5) 3, ; (2) Flash (FLASH v1.2.7), barcode, ; (3) Prinseq (PRINSEQ-lite 0.19.5) : (1) Mothur (Schloss et al, 2009) Pre.cluster, 1/150; (2) SILVA, UCHIME (Edgar et al, 2011), 1.4 UCLUST (UCLUST v1.1.579) 97% OTUs (Operational Taxonomic Units, OTUs) Mothur Alpha, (Richness) ACE (ACE Index) Chao1 (Chaos1 Index) (Coverage) OTUs ( ) RDP classifier, 0.8 2 2.1 9 28977 42115, NCBI SRA, SRP052819, 9 26503 37825 ( 2) 表 2 9 个样品中序列分析 Tab.2 Analysis of sequence from nine samples DJ1 41340 41334 12 4441 36881 DJ2 40343 40336 4 2507 37825 DJ9 37490 37487 17 1826 35644 DJ5 38006 38003 0 4647 33356 DJ6 42115 42111 1 5112 36998 DJ11 38453 38453 2 7664 30787 DJ12 28977 28971 4 2464 26503 DJ13 30469 30465 33 2938 27494 DJ14 29102 29098 0 2082 27016 2.2 9
124 47 1502 5655 OTUs ( 1) 9 ACE Chao 1 5579 25014 3240 15231, DJ9 DJ11 DJ13 DJ14, DJ1 DJ2 DJ5 DJ6 DJ12 ( 2) 86% 97%, DJ9 DJ11 DJ13 DJ14, DJ9 DJ1 DJ2, DJ11 DJ5 DJ6, DJ14 DJ12 DJ13, DJ13, DJ2 DJ6, DJ13 DJ6 DJ2 1 OUT ACE Chao 1 Alpha Fig.1 The Alpha diversity of bacteria associated with samples, and the numbers of OTUs observed and predicted (ACE and Chao 1) Fig.2 2 Richness rarefaction plot from all samples 2.3, 9 26 69 105 249 890, Proteobacteria Bacteroidetes Chloroflexi Planctomycetes Cyanobacteria Acidobacteria Verrucomicrobia Firmicutes Actinobacteria ( 3), 17 9 1%, Caldiserica Archaea Tenericutes Fibrobacteres Synergistetes Nitrospira Elusimicrobia Armatimonadetes Chlamydiae - Deinococcus- Thermus Chlorobi Gemmatimonadetes Fusobacteria Lentisphaerae Aquificae Deferribacteres Spirochaetes DJ1 19, Bacteroidetes (52.03%), Proteobacteria (41.93%); DJ2 18, (63.90%), (24.50%); DJ9 (21 ), (58.05%), (12.20%); DJ5 (12 ), (88.21%), (10.89%); DJ6 15, (50.80%), (38.34%); DJ11 20, (59.92%), (18.92%); DJ12 15, (50.94%),
1 : 125 (46.16%); DJ13 20, (68.64%), (13.56%); DJ14 18, Cyanobacteria (41.07%), 36.96% 13.58%,,, 50.54% 99.91% Fig.3 3 Relative abundance of phylum-level bacterial communities in different samples 10 OUTs ( 3) 9 10 OTUs, DJ1 Cellulophaga (11.34%) Bacteroidetes (8.32%) Polaribacter (7.80% 1.24%) Glaciecola (6.66%) Rhodobacteraceae (3.96%) Psychroserpens (2.59% 1.71%) Proteobacteria (2.50%) Acinetobacter (1.47%); DJ2 (11.37%) Roseovarius (7.24%) Flavobacteriaceae (6.09% 2.70%) γ- Gammaproteobacteria (3.92% 2.14%) (3.18%) Agrococcus (2.89%) α- Aphlaproteobacteria (2.33%) Nisaea (2.17%); DJ9 Desulfopila (6.37%) γ- (2.68% 1.26%) Kofleria (2.53%) Sulfurovum (1.95%) Bacteria (1.82%) Pelobacter (1.69%) Bellilinea (1.47%) Desulfosarcina (1.14%) Actibacter (1.05%); DJ5 Vibrio (59.37% 1.20%) Sulfitobacter (3.91%) Bacteriovorax (2.64%) (2.62%) (2.37%) Glaciecola (2.12%) Flavobacteriales (0.91%) Tenacibaculum (0.83%); DJ6 (8.21% 7.81%) (5.56% 4.09%) Cyanobacteria (5.27%) (5.00%) Kordia (4.39%) Thalassobacter (4.29%) γ- (3.60%); DJ11 Sporacetigenium (7.31%) Desulfopila (3.34% 0.78%) Actibacter (2.67%) (2.48%) Loktanella (1.84%) Haliea (0.93% 0.85%) Neptunomonas (0.70%); DJ12 (25.48% 1.36%) (23.13% 2.78%) Glaciecola (3.07%) Lewinella (2.95%) Phaeobacter (1.92%) (1.05%) Kordia (0.84%) Thalassomonas (0.72%); DJ13 Alteromonas (2.63% 1.30%) Sedimenticola (2.54%) Euzebya (2.52%) Litoreibacter (2.50%) (1.92%) α- (1.09%) Nisaea (1.03%) Glaciecola (1.03%) Thalassobacter (0.96%); DJ14 (6.76% 0.64%) Loktanella (2.17%) Pseudoalteromonas (1.43%), DJ5 DJ12, 59.37% 1.20% 23.13% 2.78% 3 (Next Generation Sequence, NGS) 16S rrna [ (Woese, 1987)],,, (Wang et al, 2007) 454 (Herlemann et al, 2011; Xia et al, 2011) Illumina 454
126 47
1 : 127,, Illumina,, Illumina Miseq 250bp 300bp (Jeon et al, 2015), (Bell et al, 2013; Yang et al, 2015) Illumina Miseq 3, 9 26503 37825, 1502 5741 (OTUs), 9 (Li et al, 2010;, 2010;, 2010;, 2014), - 17, 9 1%, Illumina Miseq, 3 Lozupone (2007) (Li et al, 2010b;, 2015) γ- α- γ- Glaciecola γ-,,,,, (Ivanova et al, 2003; Payne et al, 2006), γ-, (Bakunina et al, 1999; Huber et al, 2004) α-,, CO 2 (, 2009), DNA, (Cottrell et al, 2000; O Sullivan et al, 2002),,, (, 1995), (Rosselló-Mora et al, 1999) 3,,, CO 2 O 2,, (, 2009),, (DJ14) 41.07%, (2006) (2014) V. splendidus V. tubiashii,,, (, 2013) (2007) 1, (2007) V. alginolyticus (2006), Deng (2009) 8,, Photobacterium Arthrobacter Staphylococcus, 4,,, (Thompson et al, 2004; Thompson et al, 2005),,,,,,,,
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1 : 129 PCR-DGGE. Aquaculture International, 18(6): 977 990 Lozupone C A, Knight R, 2007. Global patterns in bacterial diversity. Proceedings of the National Academy of Sciences of the United States of America, 104(27): 11436 11440 Luo P, Hu C Q, Xie Z Y et al, 2006. PCR-DGGE analysis of bacterial community composition in brackish water Litopenaeus vannamei culture system. Journal of Tropical Oceanography, 25(2): 49 53 O Sullivan L A, Weightman A J, Fry J C, 2002. New degenerate Cytophaga-Flexibacter-Bacteroides-specific 16S ribosomal DNA-targeted oligonucleotide probes reveal high bacterial diversity in River Taff epilithon. Applied and Environmental Microbiology, 68(1): 201 210 Paerl H W, Dyble J, Moisander P H et al, 2003. Microbial indicators of aquatic ecosystem change: current applications to eutrophication studies. FEMS Microbiology Ecology, 46(3): 233 246 Payne M S, Hall M R, Bannister R et al, 2006. Microbial diversity within the water column of a larval rearing system for the ornate rock lobster (Panulirus ornatus). Aquaculture, 258(1 4): 80 90 Purcell S W, Hair C A, Mills D J, 2012. Sea cucumber culture, farming and sea ranching in the tropics: progress, problems and opportunities. Aquaculture, 368 369: 68 81 Ren G D, Ren W J, Teng Y T et al, 2015. Evident bacterial community changes but only slight degradation when polluted with pyrene in a red soil. Frontiers in Microbiology, 6: 22 Rosselló-Mora R, Aman R, 2001. The species concept for prokaryotes. FEMS Microbiology Reviews, 25(1): 39 67 Rosselló-Mora R, Thamdrup B, Schäfer H et al, 1999. The response of the microbial community of marine sediments to organic carbon input under anaerobic conditions. Systematic and Applied Microbiology, 22(2): 237 248 Schloss P D, Westcott S L, Ryabin T et al, 2009. Introducing mothur: open-source, platform-independent, communitysupported software for describing and comparing microbial communities. Applied and Environmental Microbiology, 75(23): 7537 7541 Thompson F L, Iida T, Swings J, 2004. Biodiversity of vibrios. Microbiology and Molecular Biology Reviews, 68(3): 403 431 Thompson J R, Pacocha S, Pharino C et al, 2005. Genotypic diversity within a natural coastal bacterioplankton population. Science, 307(5713): 1311 1313 Wang Q, Garrity G M, Tiedje J M et al, 2007. Naïve Bayesian classifier for rapid assignment of rrna sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73(16): 5261 5267 Wang Y G, Zhang C Y, Rong X J et al, 2005. Diseases of cultured sea cucumber, Apostichopus japonicus, in China. FAO Fisheries Technical Paper, 297 310 Woese C R, 1987. Bacterial evolution. Microbiological Reviews, 51(2): 221 271 Xia W W, Zhang C X, Zeng X W et al, 2011. Autotrophic growth of nitrifying community in an agricultural soil. The International Society for Microbial Ecology Journal, 5(7): 1226 1236 Yang Y Y, Wang Z, He T et al, 2015. Sediment Bacterial Communities Associated with Anaerobic Biodegradation of Bisphenol A. Microbial Ecology, 70(1): 97 104 Youssef N, Sheik C S, Krumholz L R et al, 2009. Comparison of species richness estimates obtained using nearly complete fragments and simulated pyrosequencing-generated fragments in 16S rrna gene-based environmental surveys. Applied and Environmental Microbiology, 75(16): 5227 5236 APPLICATION OF HIGH-THROUGHPUT SEQUENCING FOR ANALYZING BACTERIAL COMMUNITIES IN EARTHEN PONDS OF SEA CUCUMBER AQUACULTURE IN NORTHERN CHINA DOU Yan, ZHAO Xiao-Wei, DING Jun, HE Peng (Key Laboratory of Mariculture & Stock Enhancement in North China s Sea, Ministry of Agriculture, Dalian Ocean University, Dalian 116023, China) Abstract Sea cucumber Apostichopus japonicus has become an economically valuable holothurian species because of their anti-tumor properties and good nutritional values. We applied high-throughput sequencing to explore bacterial community in earthen aquaculture ponds of the sea cucumber in Dalian, North China. For nine samples collected, the number of effective sequences ranged 26503 37825, and they could be classified into 1502 5741 operational taxonomic units. Results show great bacterial diversities in the aquaculture. The estimated richness and diversity indices were higher in sediment samples than those in water samples. In total, 26 phyla were identified, among which Proteobacteria, Bacteroidetes, Chloroflexi, Planctomycetes, Cyanobacteria, Acidobacteria, Verrucomicrobia, Firmicutes, and Actinobacteria were commonly reported, and other 17 were firstly detected and rarely reported. Despite the differences in microbe composition, Proteobacteria and Bacteroidetes (50.54% 99.91%) were the dominant phyla in all samples. Key words sea cucumber Apostichopus japonicus; high-throughput sequencing; bacterial communities