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The Research On Microbial Community Structure In Different Water Environment Through DNA Metabarcoding Technology

Posted on:2018-11-23Degree:MasterType:Thesis
Country:ChinaCandidate:J Q WangFull Text:PDF
GTID:2321330512988569Subject:Environmental Science
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In recent years,various pollutants have serious impact on the aquatic ecosystems which resulted in serious degradation on these systerms.The function of ecosystem and biodiversity suffered various degrades of damages which brought about the widespread attention of the environmental protection department and the administrative department.Biological community structure condition can reflect the health status of aquatic ecosystems.Therefore,the research about biological community structure in aquatic ecosystems is the foundation of the protection of acquatic ecosystem health.In this study,DNA metabarcoding technology was used to access the microbiological community diversity and analyse the community structure status,the influence on the community distribution characteristics and biodiversity by environmental factors.The main results were as follows:(1)The results showed that the eukaryotic phytoplankton of 12 sampling sites in the Liaohe River Basin covered 134 species,of which 62.2% OTU of eukaryotic phytoplankton could be annotated to the genus.Charophyta,Cryptophyta,Haptophyta and Chrysophyceae,have never been detected in the same sampling point of the Liaohe River.According to the comparison analysis of the richness and abundance of the algae community,the dominant community of phytoplankton algae in the Liaohe River was diatomophytes and chlorophyta.The results of high-throughput sequencing were consistent with the traditional microscopic results.The phylogeny analysis clustered the Cryptophyta and Pyrroptata at phylum level.The different genera of Cryptophyta and part of families or genera of Pyrroptata were clustered and distinguished by phylogeny analysis.The results of RDA showed that NH4+-N,PO43+-P and NO3-were the most important environmental factors of eukaryotic phytoplankton in Liaohe river.The study also indicated high-throughput sequencing has great application potential in investigation of phytoplankton and the water environment quality assessment in Liaohe river.(2)129 algal OTUs were revealed in the 15 samples of the Bohai sea,of which 71.3% of the OTUs could be annotated to the genus,49.6% could be annotated to the species.The dominant phylum were dinoflagellate and chlorophytaand the most highly abundant phylum was the dinoflagellate.The results showed that the community structure and diversity of the northern sampling sites were obviously different from the sampling points of the southern sampling sites.The results of planktonic bacteria community in the 10 samples of the shallow sea area revealled 12 phylum,26 familise,54 orders,83 families and 122 genera.The most abundanttaxa was the Pseudoalteromonas genus,Proteobacteria phylum.The relationship of environmental factors and community structure showed that the main influencing factors of bacterial community were water depth and longitude.A large number of Vibrio and Alteromonas were distributed in the deep water area.Phytoplankton sequence phylogenetic tree results showed that the 18 S rRNA V9 region used in the study could distinguish the phytoplankton at the phylum level.The 16 rRNA V4 region could also distinguish planktonic bacteria at the phylum level.(3)The biome structure of ecosystems could be studied effectively through DNA metabarcoding technology.DNA metabarcoding technology could basically recapture the micro organisms community structure and diversityA large number of species that cpuld not be cultivated or identified by traditional methods could be revealed by the DNA metabarcoding technology.In brief,DNA metabarcoding technology has great potential on taxa identification,community structure analysis and revealing the relationship of biological communities structures and environmental factors.
Keywords/Search Tags:DNA metabarcoding, Aquatic ecosystem, Biodiversity, Community structure, Micro-organisms, High-throughput sequencing
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