In 2011, the term ‘‘enterotype" first appeared to the general public in Nature, which refers to stratification of human gut microbiota. However, with more studies on enterotypes conducted nowadays, doubts about the existence and robustness of enterotypes have also emerged. Here we reviewed current opinions about enterotypes from both conceptual and analytical points of view.We firstly illustrated the definition of the enterotype and various factors influencing enterotypes,such as diet, administration of antibiotics, and age. Then we summarized lines of evidence that pose the concept against the enterotype, and described the current methods for enterotype analysis.Finally, we showed that the concept of enterotype has been extended to other ecological niches.Based on current studies on enterotypes, it has been clear that more studies with larger sample sizes are needed to characterize the enterotypes. Improved computational methods are also required to build sophisticated models, reflecting the dynamics and resilience of enterotypes.
Agricultural activities, including stock-farming, planting industry, and fish aquaculture,can affect the physicochemical and biological characters of freshwater lakes. However, the effects of pollution producing by agricultural activities on microbial ecosystem of lakes remain unclear.Hence, in this work, we selected Honghu Lake as a typical lake that is influenced by agriculture activities. We collected water and sediment samples from 18 sites, which span a wide range of areas from impacted and less-impacted areas. We performed a geospatial analysis on the composition of microbial communities associated with physicochemical properties and antibiotic pollution of samples. The co-occurrence networks of water and sediment were also built and analyzed. Our results showed that the microbial communities of impacted and less-impacted samples of water were largely driven by the concentrations of TN, TP, NO_3^--N, and NO_2^--N, while those of sediment were affected by the concentrations of Sed-OM and Sed-TN. Antibiotics have also played important roles in shaping these microbial communities: the concentrations of oxytetracycline and tetracycline clearly reflected the variance in taxonomic diversity and predicted functional diversity between impacted and less-impacted sites in water and sediment samples, respectively. Furthermore, for samples from both water and sediment, large differences of network topology structures between impacted and less-impacted were also observed. Our results provide compelling evidence that the microbial community can be used as a sentinel of eutrophication and antibiotics pollution risk associated with agricultural activity; and that proper monitoring of this environment is vital to maintain a sustainable environment in Honghu Lake.
Maozhen HanMelissa DsouzaChunyu ZhouHongjun LiJunqian ZhangChaoyun ChenQi YaoChaofang ZhongHao ZhouJack A GilbertZhi WangKang Ning
In the May 22, 2015 issue of Science magazine, several articles （including the editorial, research papers, and perspectives） were published on the Tara Oceans Project and studies related to ocean microbes [1-8]. This represents truly a milestone for studies in both ocean ecology and microbial communities. As stated on the European Molecular Biology Laboratory （EMBL） website （http：//www.embl.de/tara-oceans/start/）： ＂Tara Oceans results reveal climate change insights, and a treasure trove of novel species and genes.＂
Next-generation sequencing （NGS） technology has revolutionized and significantly impacted metagenomic research.However,the NGS data usually contains sequencing artifacts such as low-quality reads and contaminating reads,which will significantly compromise downstream analysis.Many quality control （QC） tools have been proposed,however,few of them have been verified to be suitable or efficient for metagenomic data,which are composed of multiple genomes and are more complex than other kinds of NGS data.Here we present a metagenomic data QC method named Meta-QC-Chain.Meta-QC-Chain combines multiple QC functions： technical tests describe input data status and identify potential errors,quality trimming filters poor sequencing-quality bases and reads,and contamination screening identifies higher eukaryotic species,which are considered as contamination for metagenomic data.Most computing processes are optimized based on parallel programming.Testing on an 8-GB real dataset showed that Meta-QC-Chain trimmed low sequencing-quality reads and contaminating reads,and the whole quality control procedure was completed within 20 min.Therefore,Meta-QC-Chain provides a comprehensive,useful and high-performance QC tool for metagenomic data.Meta-QC-Chain is publicly available for free at： http：//computationalbioenergy.org/meta-qc-chain.html.
