大亚湾表层沉积物碳水化合物活性酶基因分布特征

doi:10.11978/2022216

热带海洋学报 ›› 2023, Vol. 42 ›› Issue (5): 76-91.doi: 10.11978/2022216CSTR: 32234.14.2022216

大亚湾表层沉积物碳水化合物活性酶基因分布特征

孙翠慈¹^,²(), 岳维忠³^,⁴, 赵文杰¹^,⁵, 王友绍¹^,²()

1. 热带海洋环境国家重点实验室(中国科学院南海海洋研究所), 广东广州 510301
2. 大亚湾海洋生物综合实验站(中国科学院南海海洋研究所), 广东深圳 518121
3. 海洋环境工程中心(中国科学院南海海洋研究所), 广东广州 510301
4. 阳江海上风电实验室, 广东阳江 529500
5. 中国科学院大学, 北京 100049

收稿日期:2022-10-10 修回日期:2022-11-22 出版日期:2023-09-10 发布日期:2023-01-09
作者简介:
孙翠慈(1977—), 女, 河北省辛集市人, 副研究员, 博士, 从事海洋环境生态研究。email: scuici@scsio.ac.cn
基金资助:
国家自然科学基金项目(42073078); 国家自然科学基金项目(U1901211); 广东省基础与应用基础研究基金项目(2020A1515011137); 国家重点研发计划项目(2017FY100700)

Distribution of the microbial Carbohydrate-Active enzymes genes in the surface sediment of the Daya Bay, China

SUN Cuici¹^,²(), YUE Weizhong³^,⁴, ZHAO Wenjie¹^,⁵, WANG Youshao¹^,²()

1. State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Sciences), Guangzhou 510301, China
2. Daya Bay Marine Biology Research Station (Chinese Academy of Sciences), Shenzhen 518121, China
3. Marine Environmental Center (South China Sea Institute of Oceanology, Chinese Academy of Sciences), Guangzhou 510301, China
4. Yangjiang Offshore Wind Power Laboratory, Yangjiang 529500, China
5. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2022-10-10 Revised:2022-11-22 Online:2023-09-10 Published:2023-01-09
Supported by:
National Natural Science Foundation of China(42073078); National Natural Science Foundation of China(U1901211); Guangdong Basic and Applied Basic Research Foundation(2020A1515011137); National Key Research and Development Program of China(2017FY100707)

摘要/Abstract

摘要：

微生物的碳水化合物活性酶(carbohydrate active enzymes, CAZymes)是海洋沉积物有机碳降解过程中的关键。文章基于大亚湾2020年春季表层沉积物的宏基因组数据, 分析鉴定编码CAZymes序列种类及其在微生物中的分布, 并预测了微生物群落对不同结构聚糖的利用。结果表明, 表层沉积物微生物群落对不同结构聚糖的利用能力不同。δ-变形菌纲是编码降解肽聚糖和几丁质相关酶类序列的最大贡献者; γ-变形菌纲、拟杆菌门和浮霉菌门具有最高的CAZymes家族的α-生态多样性(香浓指数), 是编码降解结构复杂多糖(岩藻聚糖、昆布多糖、纤维素等)的CAZymes基因优势种群; 酸杆菌是编码裂解寡聚半乳糖醛酸多糖酶序列的优势菌群。古菌对大部分CAZymes贡献低于1%, 但对编码降解纤维素和半纤维素的碳水化合物酯酶(carbohydrate esterase, CE)序列、结合模块(carbohydrate binding module, CBM)基因序列贡献较突出(贡献介于2.18%~ 11.1%)。CAZymes的底物主要源自于湾内自生的有机碎屑, 降解藻源有机碎屑的CAZymes序列的相对丰度于湾口高于湾东北部。与木质素降解相关的辅助活性家族(auxiliary activity families, AAs)序列相对丰度在湾东北部最高, 主导的AAs可能有助于增加木质纤维素的溶解度, 进而提高糖苷酶对木质纤维素的生物利用度。大亚湾表层沉积物中微生物及其CAZymes序列组成主要与上层水体有机颗粒沉降以及水深相关。

关键词: 微生物, 碳水化合物活性酶基因, 沉积物, 宏基因组, 大亚湾

Abstract:

The microbial carbohydrate active enzymes (CAZymes) are important in the process of carbohydrate mineralization in marine sediment. In this study, metagenomic analysis is used to identify microbial CAZymes genes and predict glycan utilization in the surface sediments from the Daya Bay in spring. The microbial communities showed specific utilization for the different structure glycans. Delta-proteobacteria were dominant for encoding CAZymes genes for the degradation of peptidoglycan and chitin. Gammaproteobacteria, Bacteroides and Planctomycetes were the dominant groups encoding CAZymes genes for the degradation of complex polysaccharides (fucoidan, laminarin, cellulose and hemicellulose), which was associated with their highest Shannon diversity of CAZymes families. Acidobacter was the primary contributors of CAZymes genes for cleaving oligo-galacturonic acid. The contributions of Archaea to most CAZymes genes were less than 1%, while their contributions of genes encoding carbohydrate esterase, binding module relating cellulose and hemicellulose degradation ranged from 2.18 %to11.1%. According to the functional of glycoside hydrolases, the substrate of CAZymes were mostly derived from autochthonous debris, i.e., bacterial sugars (peptidoglycans and α- glucan), algal cell wall (fucoidan and laminarin) and chitin. The relative abundances of CAZymes genes in the mouth for the algal derived organic debris with complex chemical structure were higher than those in the east-northern of the bay. The relative abundances of Auxiliary Activity families (AAs) genes related to lignin degradation were the highest in the east-northern of the bay, and their dominant AAs may help to increase lignocellulose solubility and subsequently enhance the bioavailability of GHs to lignocellulose. The compositions of CAZymes genes were mainly related to the particulate organic matter deposition from water columns and the depth of water body.

Key words: microbial community, carbohydrate-active enzymes genes, sediment, metagenome, Daya Bay

孙翠慈, 岳维忠, 赵文杰, 王友绍. 大亚湾表层沉积物碳水化合物活性酶基因分布特征[J]. 热带海洋学报, 2023, 42(5): 76-91.

SUN Cuici, YUE Weizhong, ZHAO Wenjie, WANG Youshao. Distribution of the microbial Carbohydrate-Active enzymes genes in the surface sediment of the Daya Bay, China[J]. Journal of Tropical Oceanography, 2023, 42(5): 76-91.

图/表 9

表1

图1

图2

图3

图4

图5

图6

图7

表S1

CAZymes 主要功能列表"

序号	CAZymes		名称或主要功能
1	GH3		β-葡萄糖苷酶/β-N-乙酰基己糖胺酶
2	GH4		α-半乳糖醛酸酶/麦芽糖-6-磷酸葡萄糖苷酶/6-磷酸-β-葡萄糖苷
3	GH5		内葡聚糖酶
4	GH13		异淀粉酶/1,4-α-葡聚糖分支酶/α-葡萄糖苷酶/α淀粉酶
5	GH15		葡聚糖酶/α-海藻糖酶/糖化酶
6	GH16		内切-1,3-β-葡聚糖酶
7	GH17		内切-1,3-β-葡萄糖苷酶
8	GH18		几丁质酶
9	GH20		己糖胺酶
10	GH23		溶菌酶/可溶性溶菌素转糖基酶/膜结合溶菌素转糖基酶
11	GH29		α-L-岩藻糖苷酶
12	GH30		β-葡萄糖苷酶/葡糖基神经酰胺酶/β-葡萄糖醛酸酶/内切-β-1,6-半乳糖苷酶
13	GH31		α-D-木糖苷木糖水解酶/α-葡萄糖苷酶/寡糖4-α-D-葡萄糖基转移酶
14	GH32		果聚糖内切酶
15	GH33		唾液酸酶或神经氨酸酶/反式唾液酸酶/脱水唾液酸酶/2-酮-3-脱氧壬酸水解酶
16	GH43		木聚糖1,4-β-木糖苷酶
17	GH57		1,4-α-葡聚糖分支酶
18	GH65		麦芽糖磷酸化酶/海藻糖磷酸化
19	GH73		溶菌酶
20	GH77		4-α-葡聚糖转移酶
21	GH78		α-L-氨苷酶
22	GH95		α-L-岩藻糖苷酶2
23	GH102		肽聚糖裂解转糖苷酶
24	GH103		肽聚糖裂解转糖苷酶
25	GH105		不饱和鼠李糖乳糖酰水解酶
26	GH106		α-L-鼠李糖苷酶
27	GH108		N-乙酰胞壁质酶
28	GH109		N-乙酰氨基己糖苷酶
29	GH127			β-L-阿拉伯糖苷酶
30	GH130			β-1,2-甘露糖磷酸化酶
31	GH145			L-鼠李糖-α-1,4-D-葡萄糖醛酸裂解酶
32	GH149			β-1,3-葡聚糖磷酸化酶
33	CE1			乙酰木聚糖酯酶/S-甲酰谷胱甘肽水解酶/聚羟基丁酸解聚酶/ /羧酸酯酶
34	CE2			乙酰木聚糖酯酶
35	CE3			乙酰木聚糖酯酶
36	CE4			乙酰木聚糖酯酶/甲壳素脱乙酰酶/壳寡糖脱乙酰酶肽聚糖脱乙酰酶/肽聚糖 N-乙酰胞壁酸脱乙酰酶
37	CE6			乙酰木聚糖酯酶
38	CE7			乙酰木聚糖酯酶
39	CE8			果胶酯酶
40	CE9			N-乙酰氨基葡萄糖6-磷酸脱乙酰酶/N-乙酰氨基半乳糖6-磷酸脱乙酰酶
41	CE10			芳香酯酶/羧基酯酶等
42	CE11			尿苷二磷酸-3-O-[3-羟基肉豆蔻酰基]N-乙酰氨基葡萄糖脱乙酰酶/尿苷二磷酸-3-O-[3-羟基肉豆蔻酰]N-乙酰基葡萄糖胺脱乙酰酶/3-羟基酰基-[酰基载体蛋白]脱水酶
43	CE12			果胶乙酰酯酶
44	CE13			果胶乙酰酯酶
45	CE14			二乙酰基壳二糖去乙酰化酶
46	CE15			4-O-甲基葡萄糖醛酸甲酯酶
47	CE16			乙酰酯酶
48	AA2			过氧化氢酶过氧化物酶
49	AA3			葡萄糖-甲醇-胆碱氧化还原酶家族/胆碱脱氢酶
50	AA4			乙醇酸氧化酶/D-乳酸脱氢酶(细胞色素)
51	AA6			醌还原酶
52	AA7			葡萄糖氧化酶/壳寡糖氧化酶/纤维低聚糖脱氢酶
53	AA9			依赖铜的裂解多糖单加氧酶
54	AA12			吡咯喹啉醌依赖性氧化还原酶
55	AA13			依赖铜的裂解多糖单加氧酶
56	PL1			果胶裂解酶
57	PL2			果胶裂解酶
58	PL4			鼠李糖半乳糖醛酸内切酶
59	PL5			海藻酸裂解酶
60	PL6			海藻酸裂解酶
61	PL7			海藻酸裂解酶
62	PL8			软骨素裂解酶
63	PL9			果胶裂解酶
64	PL10			果胶裂解酶
65	PL12			硫酸肝素裂解酶
66	PL14			聚(β-甘露糖醛酸)裂解酶/M-特异性海藻酸裂解酶
67	PL15			海藻酸裂解酶/肝素裂解酶/肝素裂解酶 I/肝素-硫酸盐裂解酶/肝素裂解酶 Ⅲ
68	PL17			海藻酸裂解酶
69	PL18			海藻酸裂解酶
70	PL21			肝素裂解酶/肝素-硫酸盐裂解酶/阿查兰-硫酸盐裂解酶
71	PL22			低聚半乳糖醛酸裂解酶
72	PL24			石莼多糖裂解酶
73	CBM6			结合纤维素、β-1,4-木聚糖、β-1,13-葡聚糖、β-1, 3-1,4-葡聚糖和β-1,3-葡聚糖
74	CBM9			结合纤维素
75	CBM11			与β-1,4-葡聚糖和β-1,3-1,4-混合连接葡聚糖结合
76	CBM16			结合纤维素和葡甘聚糖
77	CBM13			与纤维素结合
78	CBM20			与淀粉结合
79	CBM23			与甘露聚糖结合
80	CBM32			结合半乳糖、乳糖和N-乙酰-D-乳糖胺
81	CBM37			与木聚糖、几丁质、显微晶质和磷酸纤维素结合
82	CBM40			与GH33结合
83	CBM41			与α-葡聚糖-直链淀粉、支链淀粉、普鲁兰聚糖结合
84		CBM44		结合纤维素和木聚糖
85		CBM47		与岩藻糖结合
86		CBM48		附加到GH13模块
87		CBM50		附着于GH18、GH19、GH23、GH24、GH25和GH73家族的各种酶, 即裂解甲壳素或肽聚糖的酶
88		CBM57		附着于各种糖苷酶
89		CBM66		与果聚糖的果糖苷末端结合, 辅助β-果糖苷外切酶
90		CBM67		与L-鼠李糖结合
91		GT2		纤维素、几丁质、葡聚糖、甘露聚糖、透明质酸合成酶/N-乙酰氨基葡萄糖基转移酶等
92		GT4		蔗糖合成酶/蔗糖-磷酸合成酶/α-葡萄糖基转移酶/脂多糖N-乙酰氨基葡萄糖基转移酶等
93		GT9		脂多糖-乙酰氨基葡萄糖转移酶
94		GT26		β-N-乙酰甘露糖苷酰转移酶/β-1,4-葡萄糖基转移酶β-1,4-半乳糖基转移酶
95		GT28		1,2-二酰甘油3-β-半乳糖基转移酶; 1,2-二酰甘油3-β-葡萄糖基转移酶/β-N-乙酰氨基葡萄糖基转移酶/双半乳糖基二酰甘油合成酶
96		GT30		α-3-脱氧-D-甘露聚糖-辛酸转移酶
97		GT35		糖原或淀粉磷酸化酶
98		GT39		蛋白α-甘露糖基转移酶
99		GT51		胞壁质聚合酶
100		GT81		葡萄糖基-3-磷酸甘油酸合成酶/甘露糖基 -3-磷酸甘油酸合成酶/ 葡萄糖基-2-甘油酸合成酶/甘露糖基-3-磷酸甘油酸合成酶/3-磷酸甘油酸α-甘露糖基转移酶
101		GT83		4-氨基-4-脱氧-β-L-阿拉伯糖基转移酶/半乳糖醛酸基转移酶

表S1

参考文献 45

[1]	牟新悦, 陈敏, 张琨, 等, 2017. 夏季大亚湾悬浮颗粒有机物碳、氮同位素组成及其物源指示[J]. 海洋学报, 39(2): 39-52.
	MOU XINYUE, CHEN MIN, ZHANG KUN, et a1, 2017. Stable carbon and nitrogen isotopes as tracers of sources of suspended particulate organic matter in the Daya Bay in summer[J]. Acta Oceanologica Sinica, 39(2): 39-52 (in Chinese with English abstract).
[2]	中华人民共和国国家质量监督检验检疫总局和中国国家标准化管理委员会, 2007. 海洋监测规范(GB17378. 5—2007)[S]. 北京: 中国标准出版社 (in Chinese).
[3]	ANDRADE A C, FRÓES A, LOPES F A C, et al, 2017. Diversity of Microbial Carbohydrate-Active enzymes (CAZYmes) associated with freshwater and soil samples from Caatinga Biome[J]. Microbial Ecology, 74(1): 89-105. doi: 10.1007/s00248-016-0911-9 pmid: 28070679
[4]	ARNDT S, JORGENSEN B B, LAROWE D E, et al, 2013. Quantifying the degradation of organic matter in marine sediments: A review and synthesis[J]. Earth-Science Reviews, 123: 53-86. doi: 10.1016/j.earscirev.2013.02.008
[5]	ARNOSTI C, WIETZ M, BRINKHOFF T, et al, 2021. The Biogeochemistry of marine polysaccharides: sources, inventories, and bacterial drivers of the carbohydrate cycle[J]. Annual Review of Marine Science, 13: 81-108. doi: 10.1146/marine.2021.13.issue-1
[6]	BALMONTE J P, SIMON M, GIEBEL H A, et al, 2021. A sea change in microbial enzymes: Heterogeneous latitudinal and depth-related gradients in bulk water and particle-associated enzymatic activities from 30°S to 59°N in the Pacific Ocean[J]. Limnology and Oceanography, 66(9): 3489-3507. doi: 10.1002/lno.v66.9
[7]	BALTAR F, ZHAO ZIHAO, HERNDL G J, 2021. Potential and expression of carbohydrate utilization by marine fungi in the global ocean[J]. Microbiome, 9(1): 106. doi: 10.1186/s40168-021-01063-4 pmid: 33975640
[8]	BEN FRANCIS T, BARTOSIK D, SURA T, et al, 2021. Changing expression patterns of TonB-dependent transporters suggest shifts in polysaccharide consumption over the course of a spring phytoplankton bloom[J]. Isme Journal, 15(8): 2336-2350. doi: 10.1038/s41396-021-00928-8 pmid: 33649555
[9]	BOEY J S, MORTIMER R, COUTURIER A, et al, 2021. Estuarine microbial diversity and nitrogen cycling increase along sand-mud gradients independent of salinity and distance[J]. Environmental Microbiology, 24(1): 50-65. doi: 10.1111/1462-2920.15550 pmid: 33973326
[10]	BOLGER A M, LOHSE M, USADEL B, 2014. Trimmomatic: a flexible trimmer for Illumina sequence data[J]. Bioinformatics, 30(15): 2114-2120. doi: 10.1093/bioinformatics/btu170 pmid: 24695404
[11]	BURD A B, JACKSON G A, 2009. Particle aggregation[J]. Annual Review of Marine Science, 1: 65-90. pmid: 21141030
[12]	CANTAREL B L, LOMBARD V, HENRISSAT B, 2012. Complex carbohydrate utilization by the healthy human microbiome[J]. Plos One, 7(6): e28742. doi: 10.1371/journal.pone.0028742
[13]	CHIRANIA P, HOLWERDA E K, GIANNONE R J, et al, 2022. Metaproteomics reveals enzymatic strategies deployed by anaerobic microbiomes to maintain lignocellulose deconstruction at high solids[J]. Nature Communications, 13(1): 3870. doi: 10.1038/s41467-022-31433-x pmid: 35790765
[14]	COSTA O Y A, DE HOLLANDER M, PIJL A, et al, 2020. Cultivation-independent and cultivation-dependent metagenomes reveal genetic and enzymatic potential of microbial community involved in the degradation of a complex microbial polymer[J]. Microbiome, 8(1): 76. doi: 10.1186/s40168-020-00836-7 pmid: 32482164
[15]	DAVIS M P A, VAN DONGEN S, ABREU-GOODGER C, et al, 2013. Kraken: A set of tools for quality control and analysis of high-throughput sequence data[J]. Methods, 63(1): 41-49. doi: 10.1016/j.ymeth.2013.06.027 pmid: 23816787
[16]	DEDYSH S N, 2011. Cultivating uncultured bacteria from northern wetlands: knowledge gained and remaining gaps[J]. Frontiers in Microbiology, 2: 00184.
[17]	DONG HONG-PO, HONG YI-GUO, LU SONGHUI, et al, 2014. Metaproteomics reveals the major microbial players and their biogeochemical functions in a productive coastal system in the northern South China Sea[J]. Environmental Microbiology Reports, 6(6): 683-695. doi: 10.1111/emi4.2014.6.issue-6
[18]	FRANCIS B, URICH T, MIKOLASCH A, et al, 2021. North Sea spring bloom-associated Gammaproteobacteria fill diverse heterotrophic niches[J]. Environmental Microbiome, 16(1): 15. doi: 10.1186/s40793-021-00385-y pmid: 34404489
[19]	GOWDA K, PING D, MANI M, et al, 2022. Genomic structure predicts metabolite dynamics in microbial communities[J]. Cell, 185(3): 530-546. doi: 10.1016/j.cell.2021.12.036
[20]	GUILLÉN D, SÁNCHEZ S, RODRÍGUEZ-SANOJA R, 2010. Carbohydrate-binding domains: multiplicity of biological roles[J]. Applied Microbiology and Biotechnology, 85(5): 1241-1249. doi: 10.1007/s00253-009-2331-y pmid: 19908036
[21]	HOFFMANN K, BIENHOLD C, BUTTIGIEG P L, et al, 2020. Diversity and metabolism of Woeseiales bacteria, global members of marine sediment communities[J]. Isme Journal, 14(4): 1042-1056. doi: 10.1038/s41396-020-0588-4 pmid: 31988474
[22]	HOSHINO T, DOI H, URAMOTO G I, et al, 2020. Global diversity of microbial communities in marine sediment[J]. Proceedings of the National Academy of Sciences of the United States of America, 117(44): 27587-27597.
[23]	KOCH H, DURWALD A, SCHWEDER T, et al, 2019. Biphasic cellular adaptations and ecological implications of Alteromonas macleodii degrading a mixture of algal polysaccharides[J]. Isme Journal, 13(1): 92-103. doi: 10.1038/s41396-018-0252-4 pmid: 30116038
[24]	LAZAR C S, BAKER B J, SEITZ K, et al, 2016. Genomic evidence for distinct carbon substrate preferences and ecological niches of Bathyarchaeota in estuarine sediments[J]. Environmental Microbiology, 18(4): 1200-1211. doi: 10.1111/1462-2920.13142 pmid: 26626228
[25]	LLOYD K G, SCHREIBER L, PETERSEN D G, et al, 2013. Predominant archaea in marine sediments degrade detrital proteins[J]. Nature, 496(7444): 215-218. doi: 10.1038/nature12033
[26]	MCGIVERN B B, TFAILY M M, BORTON M A, et al, 2021. Decrypting bacterial polyphenol metabolism in an anoxic wetland soil[J]. Nature Communications, 12(1): 2466. doi: 10.1038/s41467-021-22765-1 pmid: 33927199
[27]	MENG JUN, XU JUN, QIN DAN, et al, 2014. Genetic and functional properties of uncultivated MCG archaea assessed by metagenome and gene expression analyses[J]. Isme Journal, 8(3): 650-659. doi: 10.1038/ismej.2013.174 pmid: 24108328
[28]	MORI T, KOYAMA G, KAWAGISHI H, et al, 2016. Effects of homologous expression of 1,4-Benzoquinone reductase and homogentisate 1,2-Dioxygenase genes on wood decay in hyper-lignin-degrading fungus Phanerochaete sordida YK-624[J]. Current Microbiology, 73(4): 512-518. doi: 10.1007/s00284-016-1089-6 pmid: 27363425
[29]	ORSI W D, RICHARDS T A, FRANCIS W R, 2018. Predicted microbial secretomes and their target substrates in marine sediment[J]. Nature Microbiology, 3(1): 32-37. doi: 10.1038/s41564-017-0047-9 pmid: 29062087
[30]	SICHERT A, CORZETT C H, SCHECHTER M S, et al, 2020. Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan[J]. Nature Microbiology, 5(8): 1026-1039. doi: 10.1038/s41564-020-0720-2 pmid: 32451471
[31]	SMITH M W, HERFORT L, RIVERS A R, et al, 2019. Genomic signatures for sedimentary microbial utilization of phytoplankton detritus in a fast-flowing estuary[J]. Frontiers in Microbiology, 10: 02475. doi: 10.3389/fmicb.2019.02475
[32]	SMITS S A, LEACH J, SONNENBURG E D, et al, 2017. Seasonal cycling in the gut microbiome of the Hadza hunter-gatherers of Tanzania[J]. Science, 357(6353): 802-806. doi: 10.1126/science.aan4834 pmid: 28839072
[33]	SPRING S, BUNK B, SPRÖER C, et al, 2016. Characterization of the first cultured representative of Verrucomicrobia subdivision 5 indicates the proposal of a novel phylum[J]. Isme Journal, 10(12): 2801-2816. doi: 10.1038/ismej.2016.84 pmid: 27300277
[34]	TAYLOR J D, CUNLIFFE M, 2016. Multi-year assessment of coastal planktonic fungi reveals environmental drivers of diversity and abundance[J]. Isme Journal, 10(9): 2118-2128. doi: 10.1038/ismej.2016.24 pmid: 26943623
[35]	TEELING H, FUCHS B M, BECHER D, et al, 2012. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom[J]. Science, 336(6081): 608-611. doi: 10.1126/science.1218344 pmid: 22556258
[36]	TEELING H, FUCHS B M, BENNKE C M, et al, 2016. Recurring patterns in bacterioplankton dynamics during coastal spring algae blooms[J]. Elife, 5: e11888. doi: 10.7554/eLife.11888
[37]	VAN VLIET D M, PALAKAWONG NA AYUDTHAYA S, DIOP S, et al, 2019. Anaerobic degradation of sulfated polysaccharides by two novel Kiritimatiellales Strainsisolated from Black Sea sediment[J]. Frontiers in Microbiology, 10: 253. doi: 10.3389/fmicb.2019.00253
[38]	VIDAL-MELGOSA S, SICHERT A, BEN FRANCIS T, et al, 2021. Diatom fucan polysaccharide precipitates carbon during algal blooms[J]. Nature Communications, 12(1): 1150. doi: 10.1038/s41467-021-21009-6
[39]	WANG XIAOQING, SHARP C E, JONES G M, et al, 2015. Stable-Isotope probing identifies uncultured Planctomycetes asprimary degraders of a complex heteropolysaccharide in soil[J]. Applied and Environmental Microbiology, 81(14): 4607-4615. doi: 10.1128/AEM.00055-15
[40]	WU JIAPENG, HONG YIGUO, LIU XIAOHAN, et al, 2021. Variations in nitrogen removal rates and microbial communities over sediment depth in Daya Bay, China[J]. Environmental Pollution, 286: 117267. doi: 10.1016/j.envpol.2021.117267
[41]	XING PENG, HAHNKE R L, UNFRIED F, et al, 2015. Niches of two polysaccharide-degrading Polaribacter isolates from the North Sea during a spring diatom bloom[J]. Isme Journal, 9(6): 1410-1422. doi: 10.1038/ismej.2014.225 pmid: 25478683
[42]	YU TIANTIAN, WU WEICHAO, LIANG WENYUE, et al, 2018. Growth of sedimentary Bathyarchaeota on lignin as an energy source[J]. Proceedings of the National Academy of Sciences of the United States of America, 115(23): 6022-6027.
[43]	ZHANG HAN, YOHE T, HUANG LE, et al, 2018. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation[J]. Nucleic Acids Research, 46(W1): W95-W101. doi: 10.1093/nar/gky418
[44]	ZHAO ZIHAO, BALTAR F, HERNDL G J, 2020. Linking extracellular enzymes to phylogeny indicates a predominantly particle-associated lifestyle of deep-sea prokaryotes[J]. Science Advances, 6(16): eaaz4354. doi: 10.1126/sciadv.aaz4354
[45]	ZHENG RIKUAN, CAI RUINING, LIU RUI, et al, 2021. Maribellus comscasis sp. nov., a novel deep-sea Bacteroidetes bacterium, possessing a prominent capability of degrading cellulose[J]. Environmental Microbiology, 23(8): 4561-4575. doi: 10.1111/1462-2920.15650 pmid: 34196089

站位	S1	S5	S11
经度	114°37′59.88″E	114°33′42.12″E	114°43′0.12″E
纬度	22°31′59.88″N	22°35′35.88″N	22°46′0.12″N
水深/m	19.5	13.5	8.0
含水率/%	38.2	35.1	62.4
砂土百分比/%	13.4	5.9	0
粉砂土百分比/%	64.9	71.9	62.7
黏土百分比/%	21.7	22.2	37.54
平均粒径/μm	6.4	6.4	7.59
中值粒径/μm	6.6	6.3	7.49
总有机碳(TOC)/(%·g^-1)	0.50±0.02	0.47±0.01	1.63±0.05
硫化物含量/(μg· g^-1)	33.41±1.12	81.8±2.37	218.7±5.49
总磷(TP)/(mg·kg^-1)	160.5±8.27	130.7±5.18	142.4±6.76
总氮(TN)/(mg·kg^-1)	214.5±8.1	248.8±9.3	441.6±12.8
TOC : TN	27.3	22.0	43.1
水体叶绿素浓度/(μg·L^-1)	1.47	1.51	1.76

大亚湾表层沉积物碳水化合物活性酶基因分布特征

Distribution of the microbial Carbohydrate-Active enzymes genes in the surface sediment of the Daya Bay, China

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 9

参考文献 45

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	莫丹杨, 宁志铭, 杨斌, 夏荣林, 刘志金. 涠洲岛珊瑚礁区沉积物硝酸盐异化还原过程对温度变化的响应[J]. 热带海洋学报, 2024, 43(4): 137-143.
[2]	奚琛, 林宗轩, 萨如拉, 邓玺, 刘强, 倪亮, 罗来才, 马腾, 谢智杰, 陈思若, 陈松泽. 基于双浮标连续监测资料分析大亚湾西南部海域水体环境变化特征及其影响因素[J]. 热带海洋学报, 2024, 43(4): 153-164.
[3]	高洁, 余克服, 许慎栋, 黄学勇, 陈飚, 王永刚. 西沙群岛永乐环礁礁外坡沉积物中有机碳的含量与来源分析[J]. 热带海洋学报, 2024, 43(3): 131-145.
[4]	孙婷婷, 郝雯瑾, 徐鹏臻, 叶丽靖, 董志军. 海水酸化对海月水母螅状体共附生微生物的影响[J]. 热带海洋学报, 2023, 42(6): 111-119.
[5]	邢楠楠, 任润馨, 唐振洲, 罗志宏, 夏辰曦, 刘永宏, 彭亮, 陈显强. 涠洲岛海洋沉积物来源真菌Aspergillus sp. GXIMD02003的代谢产物研究[J]. 热带海洋学报, 2023, 42(5): 154-160.
[6]	董俊德, 黄小芳, 龙爱民, 王友绍, 凌娟, 杨清松. 红树林固氮微生物及其生态功能研究进展[J]. 热带海洋学报, 2023, 42(4): 1-11.
[7]	宋星宇, 林雅君, 张良奎, 向晨晖, 黄亚东, 郑传阳. 粤港澳大湾区近海中小型浮游动物分布特征及影响因素^*[J]. 热带海洋学报, 2023, 42(3): 136-148.
[8]	姜迅, 武文, 宋德海. 大亚湾水质对人类活动响应的关键控制指标识别和量化解析[J]. 热带海洋学报, 2023, 42(1): 182-191.
[9]	叶锦成, 陈毅青, 高琳, 周鲜娇, 钟才荣, 张颖, 王芸. 红树植物拟海桑及其亲本的根际细菌群落特征分析[J]. 热带海洋学报, 2022, 41(6): 75-89.
[10]	陈靖夫, 钟瑜, 王磊, 郭雨沛, 邱大俊. 环境DNA分析大亚湾夜光藻藻华对真核浮游生物群落的影响^*[J]. 热带海洋学报, 2022, 41(5): 121-132.
[11]	李震, 李云凯, 刘永虎, 程前, 张硕. 渤海表层沉积物中化学浸取不同形态氮的释放潜力[J]. 热带海洋学报, 2022, 41(4): 163-171.
[12]	王朝晖, 张宇宁, 王文婷, 谢昌良, 陈佳卓, 郑虎, 王军星. 福建东山湾表层沉积物中甲藻孢囊分布研究[J]. 热带海洋学报, 2022, 41(4): 154-162.
[13]	张婉茹, 刘庆霞, 黄洪辉, 覃晓青, 李佳俊, 陈建华. 2020年冬季大亚湾西南海域主要渔业生物碳氮稳定同位素研究[J]. 热带海洋学报, 2022, 41(3): 147-155.
[14]	李存, 崔林青, 杨红强, 龙丽娟, 田新朋. 三份南海岛礁珊瑚砂样品中可培养细菌多样性[J]. 热带海洋学报, 2022, 41(2): 149-158.
[15]	李华薇, 徐向荣. 中国典型红树林沉积物中多溴联苯醚和替代型溴系阻燃剂污染特征[J]. 热带海洋学报, 2022, 41(1): 117-130.