Jin Zeng

Bio: Jin Zeng is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Macrophyte & Bacterioplankton. The author has an hindex of 21, co-authored 70 publications receiving 1167 citations. Previous affiliations of Jin Zeng include Hong Kong University of Science and Technology & Nanjing University.

Vertical distribution of bacterial community structure in the sediments of two eutrophic lakes revealed by denaturing gradient gel electrophoresis (DGGE) and multivariate analysis techniques

Abstract: Vertical distribution of bacterial community structure was investigated in the sediments of two eutrophic lakes of China, Lake Taihu and Lake Xuanwu. Profiles of bacterial communities were generated using a molecular fingerprinting technique, denaturing gradient gel electrophoresis (DGGE) followed by DNA sequence analysis, and the results were interpreted with multivariate statistical analysis. To assess changes in the genetic diversity of bacterial communities with changing depth, DGGE banding patterns were analysed by cluster analysis. Distinct clusters were recognized in different sampling stations of Lake Taihu. Canonical correspondence analysis (CCA) was carried out to infer the relationship between environmental variables and bacterial community structure. DGGE samples collected at the same sampling site clustered together in both lakes. Total phosphorus, organic matter and pH were considered to be the key factors driving the changes in bacterial community composition.

Macrophyte species drive the variation of bacterioplankton community composition in a shallow freshwater lake.

Abstract: Macrophytes play an important role in structuring aquatic ecosystems. In this study, we explored whether macrophyte species are involved in determining the bacterioplankton community composition (BCC) in shallow freshwater lakes. The BCC in field areas dominated by different macrophyte species in Taihu Lake, a large, shallow freshwater lake, was investigated over a 1-year period. Subsequently, microcosm experiments were conducted to determine if single species of different types of macrophytes in an isolated environment would alter the BCC. Denaturing gradient gel electrophoresis (DGGE), followed by cloning and sequence analysis of selected samples, was employed to analyze the BCC. The DGGE results of the field investigations indicated that the BCC changed significantly from season to season and that the presence of different macrophyte species resulted in lower BCC similarities in the summer and fall. LIBSHUFF analysis of selected clone libraries from the summer demonstrated different BCCs in the water column surrounding different macrophytes. Relative to the field observations, the microcosm studies indicated that the BCC differed more pronouncedly when associated with different species of macrophytes, which was also supported by LIBSHUFF analysis of the selected clone libraries. Overall, this study suggested that macrophyte species might be an important factor in determining the composition of bacterial communities in this shallow freshwater lake and that the species-specific influence of macrophytes on BCC is variable with the season and distance.

The heterogeneity of composition and assembly processes of the microbial community between different nutrient loading lake zones in Taihu Lake

Abstract: To investigate the differences in the microbial community composition and assembly process in two lake zones (Meiliang Bay (MLB) and Xukou Bay (XKB) in Taihu Lake, China) with different nutrient loadings, water samples were collected. Both the 16S ribosomal RNA (rRNA) gene for the bacterial community and the 18S rRNA gene for the microeukaryote community were investigated using the Illumina second-generation sequencing platform (2 × 250 paired-end). The results indicated that both the bacterioplankton and microeukaryote community composition derived from the two lake zones were significantly different. Significantly higher operational taxonomic unit (OTU) richness (P 0.05). Environmental factors significantly affected the community compositions in XKB for both the bacterioplankton and microeukaryotes. However, they did not significantly influence the microbial community composition in MLB, except for a weak correlation between dissolved organic carbon (DOC) and the microeukaryote community. The microbial communities tended to be more phylogenetically clustered than expected by chance in the two lake zones. Moreover, the results of the phylogenetic structure suggest that deterministic processes played overwhelming roles in driving the assembly of both the bacterioplankton and microeukaryote community in XKB.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

Keystone taxa as drivers of microbiome structure and functioning

Abstract: Microorganisms have a pivotal role in the functioning of ecosystems. Recent studies have shown that microbial communities harbour keystone taxa, which drive community composition and function irrespective of their abundance. In this Opinion article, we propose a definition of keystone taxa in microbial ecology and summarize over 200 microbial keystone taxa that have been identified in soil, plant and marine ecosystems, as well as in the human microbiome. We explore the importance of keystone taxa and keystone guilds for microbiome structure and functioning and discuss the factors that determine their distribution and activities.

Distinct patterns and processes of abundant and rare eukaryotic plankton communities following a reservoir cyanobacterial bloom.

Abstract: Plankton communities normally consist of few abundant and many rare species, yet little is known about the ecological role of rare planktonic eukaryotes. Here we used a 18S ribosomal DNA sequencing approach to investigate the dynamics of rare planktonic eukaryotes, and to explore the co-occurrence patterns of abundant and rare eukaryotic plankton in a subtropical reservoir following a cyanobacterial bloom event. Our results showed that the bloom event significantly altered the eukaryotic plankton community composition and rare plankton diversity without affecting the diversity of abundant plankton. The similarities of both abundant and rare eukaryotic plankton subcommunities significantly declined with the increase in time-lag, but stronger temporal turnover was observed in rare taxa. Further, species turnover of both subcommunities explained a higher percentage of the community variation than species richness. Both deterministic and stochastic processes significantly influenced eukaryotic plankton community assembly, and the stochastic pattern (e.g., ecological drift) was particularly pronounced for rare taxa. Co-occurrence network analysis revealed that keystone taxa mainly belonged to rare species, which may play fundamental roles in network persistence. Importantly, covariations between rare and non-rare taxa were predominantly positive, implying multispecies cooperation might contribute to the stability and resilience of the microbial community. Overall, these findings expand current understanding of the ecological mechanisms and microbial interactions underlying plankton dynamics in changing aquatic ecosystems.

Stochastic processes shape microeukaryotic community assembly in a subtropical river across wet and dry seasons

Abstract: The deep mechanisms (deterministic and/or stochastic processes) underlying community assembly are a central challenge in microbial ecology. However, the relative importance of these processes in shaping riverine microeukaryotic biogeography is still poorly understood. Here, we compared the spatiotemporal and biogeographical patterns of microeukaryotic community using high-throughput sequencing of 18S rRNA gene and multivariate statistical analyses from a subtropical river during wet and dry seasons. Our results provide the first description of biogeographical patterns of microeukaryotic communities in the Tingjiang River, the largest river in the west of Fujian province, southeastern China. The results showed that microeukaryotes from both wet and dry seasons exhibited contrasting community compositions, which might be owing to planktonic microeukaryotes having seasonal succession patterns. Further, all components of the microeukaryotic communities (including total, dominant, always rare, and conditionally rare taxa) exhibited a significant distance-decay pattern in both seasons, and these communities had a stronger distance-decay relationship during the dry season, especially for the conditionally rare taxa. Although several variables had a significant influence on the microeukaryotic communities, the environmental and spatial factors showed minor roles in shaping the communities. Importantly, these microeukaryotic communities were strongly driven by stochastic processes, with 89.9%, 88.5%, and 89.6% of the community variation explained by neutral community model during wet, dry, and both seasons, respectively. The neutral community model also explained a large fraction of the community variation across different taxonomic groups and levels. Additionally, the microeukaryotic taxa, which were above and below the neutral prediction, were ecologically and taxonomically distinct groups, which might be interactively structured by deterministic and stochastic processes. This study demonstrated that stochastic processes are sufficient in shaping substantial variation in river microeukaryotic metacommunity across different hydrographic regimes, thereby providing a better understanding of spatiotemporal patterns, processes, and mechanisms of microeukaryotic community in waters.