Analysis of microbial diversity and community structures in typical native karst environments
-
摘要: 为明确典型原生岩溶区水体和土壤微生物群落特征，以广西区四处区域水体和土壤为研究对象，利用高通量技术分析其微生物多样性和微生物群落结构，解析环境因子对微生物群落的影响，并探讨岩溶微生物在碳循环中的潜在功能。结果发现：典型岩溶区水体和土壤样品中变形菌门（Proteobacteria）是优势菌；水体和土壤中对细菌群落结构影响最大的环境因素分别是${\rm{NO}}_3^{-}$和SWC；两者与碳循环相关的功能类型占比最高的均为化能异养，占比分别为水体13.00%，14.00%和土壤6.70%，11.00%，糖酵解和三羧酸循环是细菌的主要代谢功能。微生物通过这些碳循环相关的地球生化功能在岩溶环境中发挥重要作用。Abstract:
Karst landscapes in China are widely distributed, covering 22 million km2 and accounting for 15% of the Earth's land area. The karst dynamic system is an open system characterized by a three-phase dynamic equilibrium among CaCO3 , H2O and CO2. Karst carbon cycling is considered as an important means to address climate change, with microorganisms inhabiting the karst environment playing a crucial role in this carbon cycle. Karst regions in Southwest China comprise nearly one-third of the total country’s karst area. Within these regions, karst landforms are widely distributed in the Guangxi Zhuang Autonomous Region, particularly concentrated and contiguous in the southwest, northwest, central and northeast parts of Guangxi, covering about 37.8% of its total land area. There are various types of karst development, which are rare worldwide. Karst regions in Southwest China, exemplified by Guilin in Guangxi, represents typical karst landscapes in this country. Analyzing microorganisms that survive in this local karst environment provides highly representative insights. Some studies have shown that carbonic anhydrase-producing microorganisms play a significant role in promoting carbonate deposition. However, the mechanisms by which these microorganisms and their carbonic anhydrase participate in this process, as well as their influence on karst action, remain to be investigated. To clarify the characteristics of water and soil microbial communities in typical native karst areas, this study analyzed microbial diversity and community structures in the water and soil of the Guilin region using high-throughput sequencing technology. Additionally, we examined the effects of environmental factors on microbial communities and explored the potential functions of karst microorganisms in the carbon cycle. In this study, we analyzed the environmental background of typical native karst regions, focusing on the physical and chemical properties as well as the elemental content of water and soil. High-throughput sequencing was then used to examine the diversity and community structures of bacteria in both water and soil within these karst regions. We utilized diversity indices, community composition analyses, correlation analyses between microbial communities and environmental factors, and potential function prediction analyses to enhance our understanding of bacterial species and community structures in typical karst regions. Additionally, we compared the bacteria from the Huanglong alpine karst area with the bacteria studied previously to analyze the differences of microorganisms across various karst geomorphological environments and to identify their unique microbial types. The study results are as follows: (1) The typical karst region in Guilin provides an environment conducive to calcium carbonate deposition. The average water temperature reaches around 25 ℃, with a pH above seven. The contents of Ca2+ and ${\rm{HCO}}_3^{-}$ are high, mainly in the ${\rm{HCO}}_3^{-}$-Ca2+ type of water quality. The soil is alkaline, which favors calcium carbonate deposition, and there are no significant differences in basic physical and chemical properties among the sample sites. Si is the main element in the soil, with the highest content at Site S3 (62.31%), followed by Al and Fe. Ca content is very little and varies considerably within the group. (2) A total of 106 phyla, 1132 genera and 635 becteria species were identified. Proteobacteria is the dominant bacterial phylum across all communities. In the water samples collected from Guilin, the dominant genera are Acinetobacter, Limnohabitans, Exiguobacterium, Chryseobacterium, and Deinococcus. In the soil, the dominant genera are norank Vicinamibacteraceae and norank Vicinamibacterales. Aeromonas is a distinctive genus found in water sample from Huanglong. (3) In water samples from Guilin, Cl− and ${\rm{NO}}_3^{-}$ have the most significant impact on the bacterial community structure, whereas in the soil, the structure is primarily influenced by Soil Water Content (SWC) and Ca. (4) Microbial species such as Proteobacteria, Bacteroidota, Deinococcata, Acidobacteria and Firmicutes play significant roles in the karst environment through carbon cycle-related functions,including aerobic chemoheterotrophy, fermentation, and photosynthesis, as well as through various carbon-related metabolic pathways,such as carbon metabolism, glycolysis, amino acid synthesis and carbon fixation. Functional predictions reveal that most bacteria participate in the carbon cycle, with similar functional types present in both water and soil environments but in different proportions, dominated by chemoheterotrophy. Metabolic potential analysis highlighted glycolysis and the tricarboxylic acid (TCA) cycle as key pathways. (5) A comparison of microorganisms across different karst environments shows species differences at various taxonomic levels. The composition of bacterial communities is closely related to their specific karst microenvironments, and these bacteria significantly influence biogeochemical cycles, particularly the carbon cycle, within the karst systems. These findings enhance our understanding of microbial contributions to the carbon cycle in karst landscapes and offer insights into the biological mechanisms driving carbon sink formation. -
图 1 研究区域位置
注：基于国家地理信息公共服务平台天地图网站GS（2024）0650号的标准地图制作，底图边界无修改。
Figure 1. Sampling locations
Note: The map is based on the standard map from the National Geographic Information Public Service Platform Tianditu website, licensed under number GS(2024)0650. The boundaries of the base map have not been altered.
图 2 对典型岩溶水体和土壤细菌进行不同分类水平上的丰度柱状图绘制(A：门 B：属)
Figure 2. Histograms depicting bacterial abundance in the water and soil samples obtained from typical karst areas (A: phylum B: genus)
图 3 对典型岩溶区域水体和土壤细菌进行 α 多样性分析（Chao1，Shannon 和 Observed species 指数）及韦恩图绘制。
注：A, B, C 分别为典型岩溶水体细菌 Chao1，Shannon 和 Observed species 箱型图 D, E, F 分别为典型岩溶土壤细菌 Chao1，Shannon 和 Observed species 箱型图 G, H, I 是岩溶水体和土壤原核微生物间的细菌 Chao1，Shannon 和 Observed species 箱型图 J 是水体和土壤样品共有 OTU 的韦恩图
Figure 3. Alpha-diversity of (Chao1, Shannon, and observed species indices) and Venn diagrams for bacteria community present in the water and soil samples obtained from typical karst areas in Guilin
Note:A, B, and C are box plots of water bacterial communities showing Chao1, Shannon, and observed species indices, respectively D, E, and F are box plots of soil bacterial communities representing Chao1, Shannon, and observed species indices, respectively G, H, and I are box plots of bacterial Chao1, Shannon, and observed species indices between bacteria in water and soil samples J is a Venn diagram of the OTUs shared between water and soil samples
图 4 PCoA分析的典型岩溶区域水体（W1-W4）和土壤（S1-S4）环境中的细菌群落结构
Figure 4. Bacterial community structures in water samples(W1-W4) and soil samples (S1-S4) obtained from typical karst areas in Guilin by PCoA
图 5 RDA分析的水体(A)和土壤(B)环境因子与其微生物群落结构的关系
Figure 5. Relationships between environmental factors (A:water, B:soil) and bacterial community structures by RDA
图 6 基于FAPROTAX（A）和PICRUSt（B）分析的原生岩溶水体和土壤中原核微生物群落的潜在功能
Figure 6. Potential functions of bacterial communities in native karst water and soil based on FAPROTAX (A) and PICRUSt (B)
图 7 原生岩溶与高寒岩溶细菌多样性分析
注：A和B分别为两地样品细菌门和属水平前十的物种丰度比较，其余为others C为样品的PCoA分析，同组样品使用同一颜色表示 D为两种岩溶样品FAPROTAX功能的组间差异检验，选择丰度前十的功能类型进行比较；横坐标是样品某一功能的百分数值，纵坐标是功能名称，不同颜色表示不同分组，最右侧为P值，*为0.01<P<0.05，**为0.001<P<0.01，***为P<0.001。W：原生岩溶水体，S：原生岩溶土壤，HW：高寒岩溶水体。
Figure 7. Analysis of bacterial diversity in native karst and alpine karst
Note:A and B show the top 10 most abundant bacterial phyla and genera in samples from the two sites, respectively, with the remaining taxa grouped as “others” C presents PCoA of the samples, where samples from the same group are indicated by the same color D displays the between-group differences in FAPROTAX functional profiles for the two karst sample types, comparing the top 10 most abundant functional groups; The x-axis represents the relative abundance (%) of a given function in the samples, while the y-axis lists the functional categories, with different colors denoting different groups. P-values are shown on the right, where * indicates 0.01 < P ≤ 0.05, ** indicates 0.001 < P ≤ 0.01, and *** indicates P ≤ 0.001. W: native karst water; S: native karst soil; HW: alpine karst water.
图 8 桂林峰丛[61]（A）与黄龙高寒钙华（B）两种岩溶景观
Figure 8. Guilin peak cluster(A) and Huanglong alpine travertine(B)
表 1 样品采集点
Table 1. Sampling points
采样点编号 地理位置 地貌 W1 马山弄拉 典型峰丛洼地地貌 W2 冠岩南圩村 南圩河分江入口处
水流入冠岩地下河W3 国际岩溶研究中心
基地附近竹江村漓江东岸岩溶地貌 W4 平果果化 典型峰丛洼地地区 T1 马山弄拉 典型峰丛洼地地貌 T2 冠岩南圩村 与冠岩隔山相连 T3 国际岩溶研究中心基地 漓江东岸岩溶地貌 T4 平果果化 典型峰丛洼地地区 
下载: 导出CSV
表 2 水体样品理化性质
Table 2. Physicochemical properties of water samples
理化指标 W1 W2 W3 W4 T /℃ 25.30±0.20 b 19.10±0.17 d 27.40±0.26 a 23.30±0.26 c pH 7.26±0.01 c 7.59±0.01 a 7.46±0.02 b 7.21±0.01 d EC /μS 375.00±3.00 c 280.00±2.00 d 515.00±4.36 a 433.00±3.61 b ORP /mV 282.00±7.21 b 305.50±3.12 a 267.30±5.80 c 274.00±3.61 bc DO/mg∙L−1 0.69±0.04 c 1.71±0.04 a 1.65±0.03 a 0.93±0.04 b ${\rm{HCO}}_3^{-}$ /mg∙L−1 266.96±6.93 c 183.06±5.19 d 373.75±5.19 a 289.85±3.75 b TN /mg∙L−1 1.69±0.01 b 1.74±0.03 a 1.55±0.02 c 1.76±0.03 a TP /mg∙L−1 0.49±0.03 b 0.50±0.03 b 0.69±0.04 a 0.41±0.03 c Ca /mg∙L−1 89.15±0.06 b 58.44±0.05 d 116.50±0.02 a 80.40±0.05 c Si /mg∙L−1 2.21±0.03 c 3.28±0.04 a 2.24±0.04 c 2.49±0.06 b K /mg∙L−1 0.57±0.03 a 0.55±0.05 a 0.37±0.07 b 0.57±0.06 a Mg /mg∙L−1 1.97±0.03 c 2.86±0.16 b 1.52±0.07 d 9.88±0.02 a Sr /mg∙L−1 0.05±0.01 b 0.03±0.00 b 0.05±0.01 b 0.11±0.02 a Cl− /mg∙L−1 1.48±0.06 b 1.04±0.08 c 0.48±0.02 d 1.67±0.01 a ${\rm{NO}}_3^{-}$ /mg∙L−1 4.87±0.03 c 6.90±0.03 a 0.33±0.02 d 6.61±0.03 b ${\rm{SO}}_4^{2-}$ /mg∙L−1 5.69±0.06 b 4.12±0.03 c 3.11±0.02 d 7.82±0.03 a
下载: 导出CSV
表 3 土壤样品理化性质
Table 3. Physicochemical properties of soil samples
理化指标 S1 S2 S3 S4 SWC/% 13.16±1.52 b 18.97±1.27 a 14.92±1.32 b 18.48±1.19 a pH 8.54±0.05 a 8.10±0.03 b 8.58±0.24 a 8.28±0.05 b EC/μS 224.40±31.10 a 174.67±2.37 b 193.30±3.46 b 177.37±3.34 b OM/mg∙kg−1 31.40±3.30 b 54.89±1.11 a 27.77±1.58 b 55.96±1.87 a TOC/mg∙kg−1 18.22±1.91 b 31.84±0.65 a 14.37±0.92 b 32.46±1.08 a TN/mg∙kg−1 8.92±0.03 b 8.46±0.06 d 9.16±0.02 a 8.55±0.04 c TP/mg∙kg−1 2.60±0.90 b 3.78±0.05 a 2.65±0.13 b 2.01±0.10 b Si/% 39.27±0.00 d 48.96±0.00 b 62.31±0.00 a 59.57±0.00 c Ca/% 11.81±0.00 a 1.54±0.00 c 1.09±0.00 d 1.90±0.00 b Al /% 29.94±0.00 b 30.16±0.00 a 21.72±0.00 d 22.62±0.00 c Fe/% 14.14±0.00 a 13.71±0.00 b 9.51±0.00 d 9.72±0.00 c
下载: 导出CSV
-
[1] 钟亮, 张春来, 胡芬, 曹建华. 基于Web of Science的岩溶碳循环及碳汇效应研究动态分析[J]. 中国岩溶, 2024, 43(4): 766-779, 809. doi: 10.11932/karst20240403ZHONG Liang, ZHANG Chunlai, HU Fen, CAO Jianhua. Analysis of development trend of karst carbon cycle and carbon sink effect based on Web of Science[J]. Carsologica Sinica, 2024, 43(4): 766-779, 809. doi: 10.11932/karst20240403 [2] 晏红波, 曾金钊, 卢献健, 赵凤阳. 近30年岩溶地区碳储量时空变化分析及预测: 以红水河流域为例[J]. 中国岩溶, 2025, 44(1): 100-112, 123.YAN Hongbo, ZENG Jinzhao, LU Xianjian, ZHAO Fengyang. Analysis and prediction of spatial and temporal variation of carbon storage in limestone area in recent 30 years: A case study of the Hongshui River Basin[J]. Carsologica Sinica, 2025, 44(1): 100-112, 123. [3] Veress M. Karst types and their karstification[J]. Journal of Earth Science, 2020, 31(3): 621-634. doi: 10.1007/s12583-020-1306-x [4] Andreychouk V, Blachowicz T, Dłużewski M. Fractal analysis of tropical karst relief - South China karst case study[J]. Geological Quarterly, 2019, 63(4): 729-740. [5] 高旭波, 潘振东, 龚培俐, 江玉, 李成城, 李鸿煜. 微生物诱导碳酸盐岩沉淀过程及作用机理[J]. 中国岩溶, 2022, 41(3): 441-452.GAO Xubo, PAN Zhendong, GONG Peili, JIANG Yu, LI Chengcheng, LI Hongyu. Process and mechanism of microbial induced carbonate precipitation[J]. Carsologica Sinica, 2022, 41(3): 441-452. [6] 康卫华, 程从雨, 李为, 余龙江. 微型生物在岩溶碳循环中的作用研究回顾与展望[J]. 中国岩溶, 2022, 41(3): 453-464.KANG Weihua, CHENG Congyu, LI Wei, YU Longjiang. Review and prospect of research on the role of micro-organisms in karst carbon cycle[J]. Carsologica Sinica, 2022, 41(3): 453-464. [7] Durak G M, Brownlee C, Wheeler G L. The role of the cytoskeleton in biomineralisation in haptophyte algae[J]. Scientific Reports, 2017, 7(1): 1-12. doi: 10.1038/s41598-016-0028-x [8] Chin Y L, Turchyn A V, Zvi S, Pieter B, Lampronti G I, Tosca N J. The role of microbial sulfate reduction in calcium carbonate polymorph selection[J]. Geochimica et Cosmochimica Acta, 2018, 237: 184-204. doi: 10.1016/j.gca.2018.06.019 [9] Schwantes-cezario N, Medeiros L P, De Oliveira A G, Nakazato G, Takayama Kobayashi R K, Toralles B M. Bioprecipitation of calcium carbonate induced by Bacillus subtilis isolated in Brazil[J]. International Biodeterioration & Biodegradation, 2017, 123: 200-205. [10] Bai Y, Guo X J, Li Y Z, Huang T. Experimental and visual research on the microbial induced carbonate precipitation by Pseudomonas aeruginosa[J]. AMB Express, 2017, 7(1): 1-9. doi: 10.1186/s13568-016-0313-x [11] 刘璐, 李福春, 李磊, 张宠宏, 吕杰杰. 细菌碳酸酐酶促进形成的碳酸盐矿物[J]. 中国岩溶, 2017, 36(4): 433-440.LIU Lu, LI Fuchun, LI Lei, ZHANG Chonghong, LYU Jiejie. Carbonic anhydrase excreted by bacteria induces the formation of carbonate minerals[J]. Carsologica Sinica, 2017, 36(4): 433-440. [12] 李福春, 马恒, 苏宁, 王金平, 刘铭艳, 汪君, 滕飞. 梭菌对含镁方解石形态的控制及其可能机理[J]. 高校地质学报, 2011, 17(1): 13-20.LI Fuchun, MA Heng, SU Ning, WANG Jinping, LIU Mingyan, WANG Jun, TENG Fei. Clostridium sp. controlled morphology of Mg-bearing calcite and its implication for possible mechanism[J]. Geological Journal of China Universities, 2011, 17(1): 13-20. [13] 李一良, 王汝成, 周根涛, 张传伦. 微生物成矿(英文)[J]. 高校地质学报, 2005(2): 167-180.LI Yiliang, WANG Rucheng, ZHOU Gentao, ZHANG Chuanlun. Microbial biomineralization[J]. Geological Journal of China Universities, 2005(2): 167-180. [14] 周雪莹, 杜叶, 连宾. 不同培养条件对胶质芽孢杆菌诱导碳酸钙晶体形成的影响[J]. 微生物学报, 2010, 50(7): 955-961.ZHOU Xueying, DU Ye, LIAN Bin. Effect of different culture conditions on carbonic anhydrase from Bacillus mucilaginosus inducing calcium carbonate crystal formation[J]. Acta Microbiologica Sinica, 2010, 50(7): 955-961. [15] 韩金鑫, 连宾, 唐源, 刘世荣, 龚国洪. 恶臭假单胞菌对碳酸钙的诱导矿化作用[J]. 南京大学学报(自然科学版), 2013, 49(06): 681-688.HAN Jinxin, LIAN Bin, TANG Yuan, LIU Shirong, GONG Guohong. Induced mineralization of calcium carbonate by Pseudomonas putida[J]. Journal of Nanjing University (natural science), 2013, 49(06): 681-688. [16] 连宾, 袁道先, 刘再华. 岩溶生态系统中微生物对岩溶作用影响的认识[J]. 科学通报, 2011, 56(26): 2158-2161. doi: 10.1360/csb2011-56-26-2158LIAN Bin, YUAN Daoxian, LIIU Zaihua. Effect of microbes on karstification in karst ecosystems[J]. Chinese Science Bull, 2011, 56(26): 2158-2161. doi: 10.1360/csb2011-56-26-2158 [17] Sun S Y, Guo P Y, Zou X, Lin S. The indication of environmental significance by mineral characteristics during biomineralization of living coccolithophores[J]. Frontier of Environmental Science, 2016, 5(1): 28-31. [18] 杨清清. 产碳酸酐酶矿化菌固化砂土试验研究[D]. 绵阳: 西南科技大学, 2018.YANG Qingqing. Experimental study on the sand soil solidification using carbonic anhydrase induced precipitation[D]. Mianyang: Southwest University of Science and Technology, 2018. [19] 杨清清, 何鑫, 李琼芳, 于璐嘉, 王旭辉, 潘玲. 不同固化方式对碳酸酐酶矿化菌固化砂土效果影响研究[J]. 工业建筑, 2018, 48(7): 38-43.YANG Qingqing, HE Xin, LI Qiongfang, YU Lujia, WANG Xuhui, PAN Ling. Study of effects of different cementing methods for carbonic anhydrase mineralized bacteria on cementation of sand soil[J]. Industrial Construction, 2018, 48(7): 38-43. [20] 刘世豪. 微生物诱导碳酸钙沉淀(MICP)固化粗颗粒盐渍土的试验研究[D]. 兰州: 兰州理工大学, 2021.LIU Shihao. Experimental study on the solidification of coarse-grained saline soil by microbial-induced calcium carbonate precipitation(MICP)[D]. Lanzhou: Lanzhou University of Technology, 2021. [21] 赵茜. 微生物诱导碳酸钙沉淀(MICP)固化土壤实验研究[D]. 北京: 中国地质大学, 2014.ZHAO Qian. Experimental study on soil improvement using microbial induced calcite precipitation(MICP)[D]. Beijing: China University of Geosciences, 2014. [22] 彭劼, 何想, 刘志明, 冯清鹏, 何稼. 低温条件下微生物诱导碳酸钙沉积加固土体的试验研究[J]. 岩土工程学报, 2016, 38(10): 1769-1774.PENG Jie, HE Xiang, LIU Zhiming, FENG Qingpeng, HE Jia. Experimental research on influence of low temperature on MICP-treated soil[J]. Chinese Journal of Geotechnical Engineering, 2016, 38(10): 1769-1774. [23] 李琼芳, 何鑫, 陈超, 杨清清, 吕治州. 两株嗜冷碳酸钙矿化菌对大理石表面修复效果研究[J]. 人工晶体学报, 2018, 47(1): 172-178.LI Qiongfang, HE Xin, CHEN Chao, YANG Qingqing, LYU Zhizhou. Effect of two psychrotrophic calcium carbonate mineralized bacteria on the surface repair of marble[J]. Journal of Synthetic Crystals, 2018, 47(1): 172-178. [24] 竹文坤. 微生物诱导碳酸钙矿化及其在石质材料表面覆膜基础研究[D]. 绵阳: 西南科技大学, 2011.ZHU Wenkun. Fundamental studies of calcium carbonate mineralization induced by microbiologically in stone materials surface protection[D]. Mianyang: Southwest University of Science and Technology, 2011. [25] Pentecost A. The quaternary travertine deposits of Europe and Asia Minor[J]. Quaternary Science Reviews, 1995, 14(10): 1005-1028. doi: 10.1016/0277-3791(95)00101-8 [26] 杨富巍. 无机胶凝材料在不可移动文物保护中的应用[D]. 杭州: 浙江大学, 2011.YANG Fuwei. Study of inorganic gelling materials for the conservation of immovable relics[D]. Hangzhou: Zhejiang University, 2011. [27] Dhami N K, Reddy M S, Mukherjee A. Application of calcifying bacteria for remediation of stones and cultural heritages[J]. Frontiers in Microbiology, 2014, 5(304): 304-317. [28] Hershey O S, Kallmeyer J, Wallace A, Barton M D, Barton H A. High microbial diversity despite extremely low biomass in a deep karst aquifer[J]. Frontiers in Microbiology, 2018, 9: 1-13. doi: 10.3389/fmicb.2018.00001 [29] Yuan C, Wang H, Dai X, Chen M, Luo J, Yang R, Ding F. Effect of karst microhabitats on the structure and function of the rhizosphere soil microbial community of rhododendron pudingense[J]. Sustainability, 2023, 15(9): 1-20. [30] Jiang C, Zeng H. Comparison of soil microbial community structure and function for karst tiankeng with different degrees of degradation[J]. Ecology and Evolution, 2022, 12(12): 1-11. [31] Yun Y, Wang H, Man B, Xiang X, Zhou J, Qiu X, Duan Y, Engel AS. The relationship between pH and bacterial communities in a single karst ecosystem and its implication for soil acidification[J]. Front Microbiol, 2016, 7: 1-14. [32] Jiang C, Li H, Zeng H. Karst tiankeng create a unique habitat for the survival of soil microbes: Evidence from ecoenzymatic stoichiometry[J]. Frontiers in Ecology and Evolution, 2022(10): 1-10. [33] Mucsi M, Krett G, Szili-Kovács T, Móga J, Borsodi A K. Denaturing gradient gel electrophoresis and multi-SIR profiles of soil microbial communities from a karst doline at Aggtelek National Park, Hungary[J]. Folia Microbiol, 2021, 66: 107-114. doi: 10.1007/s12223-020-00828-y [34] Liu F T, Kou D, Chen Y L, Xue K, Jessica G E, Chen L Y, Yang G B, Yang Y H. Altered microbial structure and function after thermokarst formation. Global Change Biology. 2021, 4(27): 823-835. [35] Wang C W, Li W, Shen T M, Cheng W L, Yan Z, Yu L J. Influence of soil bacteria and carbonic anhydrase on karstification intensity and regulatory factors in a typical karst area. Geoderma, 2018, 313: 17-24. [36] 靳振江, 汤华峰, 李敏, 黄炳富, 李强, 张家喻, 黎桂文. 典型岩溶土壤微生物丰度与多样性及其对碳循环的指示意义[J]. 环境科学, 2014, 35(11): 4284-4290.JIN Zhenjiang, YANG Huafeng, LI Min, HUANG Bingfu, LI Qiang, ZHANG Jiayu, LI Guiwen. Microbial community abundance and diversity in typical karst ecosystem to indicate soil carbon cycle[J]. Environmental Science, 2014, 35(11): 4284-4290. [37] 魏复盛. 水和废水监测分析方法[M]. 北京: 中国环境科学出版社, 2002. [38] 鲁如坤. 土壤农业化学分析方法[M]. 北京: 中国农业科技出版社, 2000. [39] Magoč T, Salzberg S L. Flash: fast length adjustment of short reads to improve genome assemblies[J]. Bioinformatics, 2011, 27(21): 2957-2963. doi: 10.1093/bioinformatics/btr507 [40] Bokulich N, Subramanian S, Faith J, Gevers D, Gordon J, Knight R, Mills D, Caporaso G. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing[J]. Nature Methods, 2013, 10(1): 57-59. doi: 10.1038/nmeth.2276 [41] Rognes T, Flouri T, Nichols B, Quince C, Mahé F. Vsearch: a versatile open source tool for metagenomics[J]. PeerJ, 2016, 4: 1-22. [42] Haas B J, Gevers D, Earl A M, Feldgarden M, Ward D V, Giannoukos G, Ciulla D, Tabbaa D, Highlander S K, Sodergren E, Methé B, Desantis T Z, Petrosino J F, Knight R, Birren B W. Chimeric 16S rRNA sequence formation and detection in sanger and 454- pyrosequenced PCR amplicons[J]. Genome Research, 2011, 21(3): 494-504. doi: 10.1101/gr.112730.110 [43] Edgar R C. Uparse: highly accurate OTU sequences from microbial amplicon reads[J]. Nature Methods, 2013, 10(10): 996-998. doi: 10.1038/nmeth.2604 [44] Wang Q, Garrity G M, Tiedje J M, Cole J R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy[J]. Applied and Environmental Microbiology, 2007, 73(16): 5261-5267. doi: 10.1128/AEM.00062-07 [45] Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner F O. The silva ribosomal RNA gene database project: improved data processing and web-based tools[J]. Nucleic Acids Research, 2013, 41(D1): D590-D596. [46] Chikkanna A, Ghosh D, Sajeev K. Bio-weathering of granites from Eastern Dharwar Craton (India): a tango of bacterial metabolism and mineral chemistry[J]. Biogeochemistry, 2021, 153: 303-322. doi: 10.1007/s10533-021-00791-x [47] Li Y X, Hao W J, Peng S J, Sun T T, Zhao J M, Dong Z J. Composition and potential functions of bacterial communities associated with aurelia polyps[J]. Frontiers in Marine Science, 2022, 9: 1-11. [48] Louca S, Parfrey L W, Doebeli M. Decoupling function and taxonomy in the global ocean microbiome[J]. Science, 2016, 353: 1272-1277. doi: 10.1126/science.aaf4507 [49] Wang Q, Lv R Y, Rene E R, Qi X Y, Hao Q, Du Y D, Zhao C C, Xu F, Kong Q. Characterization of microbial community and resistance gene (CzcA) shifts in up-flow constructed wetlands-microbial fuel cell treating Zn (II) contaminated wastewater[J]. Bioresource Technology, 2020, 302: 1-9. [50] Xu Z S, Dai X H, Chai X L. Effect of different carbon sources on denitrification performance, microbial community structure and denitrification genes[J]. Science of The Total Environment, 2018, 634: 195-204. doi: 10.1016/j.scitotenv.2018.03.348 [51] Porter N T, Luis A S, Martens E C. Bacteroides thetaiotaomicron[J]. Trends in Microbiology, 2018, 26(11): 966-967. doi: 10.1016/j.tim.2018.08.005 [52] Wang H X, Zhang M L, Lv Q, Xue J B, Yang J, Han X M. Effective co-treatment of synthetic acid mine drainage and domestic sewage using multi-unit passive treatment system supplemented with silage fermentation broth as carbon source[J]. Journal of Environmental Management, 2022, 310: 1-13. [53] Helmi F M, Elmitwalli H R, Elnagdy S M, El-Hagrassy A F. Calcium carbonate precipitation induced by ureolytic bacteria Bacillus licheniformis[J]. Ecological Engineering, 2016, 90: 367-371. doi: 10.1016/j.ecoleng.2016.01.044 [54] Karishma M, Trivedi V D, Choudhary A, Mhatre A, Kambli P, Desai J, Phale P S. Analysis of preference for carbon source utilization among three strains of aromatic compounds degrading Pseudomonas[J]. FEMS Microbiology Letters, 2015, 362(20): 1-7. [55] Chandel N S. Glycolysis[J]. Cold Spring Harbor Perspectives in Biology, 2021, 13: 1-12. [56] Arnold P K, Finley L W S. Regulation and function of the mammalian tricarboxylic acid cycle[J]. Journal of Biological Chemistry, 2023, 299(2): 1-21. [57] Ragsdale S W. Stealth reactions driving carbon fixation[J]. 2018, Science, 359: 517-518. [58] 董发勤, 李刚, 代群威, 周琳, 王富东, 赵学钦, 蒋忠诚, 张强. 雪宝顶区块流域钙华形成的生物作用研究[J]. 中国岩溶, 2021, 40(1): 11-18.DONG Faqin, LI Gang, DAI Qunwei, ZHOU Lin, WANG Fudong, ZHAO Xueqin, JIANG Zhongcheng, ZHANG Qiang. Biological effects on travertine forming in Xuebaoding drainage basin region[J]. Carsologica Sinica, 2021, 40(1): 11-18. [59] 肖玉军. 黄龙风景区水体细菌多样性研究[D]. 雅安: 四川农业大学, 2014.XIAO Yujun. Study of the water bacterial diversity from Huanglong[D]. Ya'an: Sichuan Agricultural University, 2014. [60] Gao W H, Zhang J, Sun D, Zhang W Z, Wang S K, Guo J W, Xu H, Zhao S J, Zeng Y, Liu X Z. Water environmental characteristics and eutrophication evaluation of alpine karst mountains in Huanglong, Sichuan, China[J]. ACS Earth and Space Chemistry, 2023, 7(5): 1083-1096. doi: 10.1021/acsearthspacechem.3c00015 [61] Yang X W, Tang G A, Meng X, Xiong L Y. Classification of karst fenglin and fengcong landform units based on spatial relations of terrain feature points from DEMs[J]. Remote Sens, 2019, 11: 1950. doi: 10.3390/rs11161950 -
点击查看大图
图(8) / 表(3)
计量
- 文章访问数: 14
- HTML浏览量: 10
- PDF下载量: 0
- 被引次数: 0
