Using skimmed milk agar to functionally screen a gut metagenomic library for proteases may lead to false positives

AIMS: Functional screens using skimmed-milk agar to obtain protease activity is a common approach. The aim of this study was to determine the efficacy of this screen to obtain protease activity from a metagenomic library. METHODS AND RESULTS: A distal gut metagenomic library was functionally screened using a skimmed-milk agar. The functional screen provided 231 clones generating the characteristic clear halo indicative of protease production. Clone analysis revealed that they were not protease-positive, but expressed glycosidic hydrolases and produced acid, which was responsible for the clear halos. CONCLUSIONS: The current skimmed-milk agar method to obtain proteases is not sufficiently robust to provide a definitive screen. Other- non-protease activities will also give the same clear halo and these would be interpreted as protease positive clones without further analysis. Hence a more robust buffered medium or a specific protein should be used. SIGNIFICANCE AND IMPACT OF THE STUDY: Functional screens are a powerful approach to obtaining enzymes from large metagenomic libraries and proteases are a particularly interesting target. The skimmed-milk agar is not sufficiently robust to ensure that only proteases are isolated and in order to save time and money this study has shown that better designed media can aid in the process.     

温室黄瓜根结线虫发生地土壤微生物宏基因组文库的构建及其一个杀线虫蛋白酶基因的筛选

【目的】本研究旨在通过非培养手段构建和筛选宏基因组文库,以求找到新型的杀线虫蛋白酶基因。【方法】采用密度梯度离心法提取和纯化温室土壤微生物总DNA,经平末端、连接、包装、转染后,构建宏基因组Fosmid文库,同时,以脱脂奶为底物,以根结线虫为靶标,对文库进行功能初筛。【结果】该文库库容31008个克隆,平均插入片段36.5kb,包含1.13Gbp的微生物基因组信息,适合大规模的微生物功能基因筛选,通过功能初筛,筛选到1个含杀线虫蛋白酶基因的Fosmid克隆(pro12)。进一步构建和筛选出亚克隆(espro124a5),通过对基因结构进行了初步分析发现:espro124a5是一种分泌型胞外蛋白酶,与来自于Maricaulis maris MCS10(accession no.YP_756822at NCBI)的丝氨酸蛋白酶S15仅有45%的同源性,是一种新型的丝氨酸蛋白酶,有其保守的催化三元组:Asp469、His541和Ser348。【结论】密度梯度离心法提取到的DNA纯度高、片段长,完全能满足构建宏基因组Fosmid文库的要求;同时,构建的宏基因组Fosmid文库库容大,有利于我们从中筛选其他的微生物基因资源。     

Sequence analysis of a salt tolerant metagenomic clone

Metagenome represent an unlimited resource for discovery of novel genes. Here we report, sequence analysis of a salt tolerant metagenomic clone (6B4) from a pond water metagenomic library. Clone 6B4 had an insert of 2254 bp with G+C composition of 64.06%. DNA sequence from 6B4 showed homology to DNA sequences from pro-teobacteria indicating origin of 6B4 metagenomic insert from a yet uncharacterized proteobacteria. Two encoded proteins from clone 6B4 showed match with ATP-depen-dent Clp protease adaptor protein (ClpS) and phasin, while two truncated encoded proteins showed match with poly-3-hydroxybutyrate synthase and permease. Clp complex is known to play a role in stress tolerance. Expression of ClpS from metagenomic clone is proposed to be responsible for salt tolerance of the metagenomic clone 6B4.     

一种来自于土壤宏基因组文库的AprN基因的鉴定

宏基因组文库技术的发展拓宽了酶学的研究范围,从而导致了一系列新型的生物催化剂被发现和鉴定。采用蛋白酶的活性筛选策略,从已构建的碱性污染土壤宏基因组文库分离得到了一个表达蛋白酶的阳性克隆。生物信息学分析表明该克隆所包含的外源DNA片断编码一个由381个氨基酸编码组成的多肽,该多肽大约为39kDa,等电点为8.91。BLAST软件分析该外源DNA片断包含一个完整的碱性蛋白酶基因（ap01）,GC含量为46.3%。相关酶学数据表明该阳性克隆所分泌的碱性蛋白酶最适作用pH值为9.5,最佳作用温度为40℃。     

碱性土壤微生物基因的克隆和多样性分析

从碱性土壤样品中直接抽提和分离宏基因组DNA, 首先构建了包含5 562个阳性克隆的碱性土壤16S rDNA文库, 随机抽取9个克隆测序后构建的系统进化树表明了碱性土壤环境微生物种群基因的多样性。纯化土壤宏基因组DNA后采用EcoRⅠ酶部分酶切处理, 我们又构建了以pGEM-3Zf(+)为载体的DNA部分文库AL01。AL01文库包含23650个克隆, 随机插入载体的外源DNA片段平均大小为3.2 kb左右, DNA文库的总容量为75.68 Mb。建库效率为从每克环境样品中获得6 000个左右的含随机外源DNA片段插入载体的克隆。采用酶活筛选策略, 我们从AL01文库中筛选到一个编号为pGXAA2011的阳性克隆携带有一个完整的碱性蛋白酶基因。蛋白酶活性检测其酶活作用最佳温度为40℃, 最适作用pH 值为9.5。另外, 我们还克隆和表达了一个新型b-葡萄糖苷酶基因unglu01, 该基因和现有数据库中的b-葡萄糖苷酶基因没有任何DNA或者氨基酸水平的同源性。将unglu01基因的ORF与表达载体pETBlue-2连接后导入宿主菌株Tuner(DE3)pLacI中, 该重组表达克隆在含柠檬酸高铁铵和七叶苷的LA平板上表现清晰的b-葡萄糖苷酶活性, SDS-PAGE电泳可以检测到29 kDa大小的目的蛋白。     

Expression and characterization of a novel mesophilic protease from metagenomic library derived from Antarctic coastal sediment

A metagenomic cosmid library was constructed, in which the insert DNA was derived from the coastal sediment near Antarctic China Zhongshan Station. One clone (ACPRO001) expressing protease activity was isolated from the library using milk agar plates. Sequencing of the clone revealed a novel protease gene. The amino acid sequence comparison and phylogenetic analysis indicated that it could be classified as a subtilisin-like serine protease, though the highly conserved residue Asp was replaced by Ala. The ACPRO001 protease gene was expressed in pET-His and purified for characterization. The optimal temperature and pH for the activity of the ACPRO001 protease were 60°C and pH 9.0, respectively. The enzyme retained about 73% of residual activity after 2 h incubation at 50°C in the presence of Ca²⁺. The presence of Ca²⁺ increased the thermostability of ACPRO001 protease obviously. The enzymatic activity was inhibited by 1 mM phenylmethyl sulfonylfluoride (PMSF) and hydrochloride 4-(2-aminoethyl)-benzenesulfonyl fluoride (AEBSF), indicating that it was a serine protease.     

The phylogenetic diversity of metagenomes

Phylogenetic diversity--patterns of phylogenetic relatedness among organisms in ecological communities--provides important insights into the mechanisms underlying community assembly. Studies that measure phylogenetic diversity in microbial communities have primarily been limited to a single marker gene approach, using the small subunit of the rRNA gene (SSU-rRNA) to quantify phylogenetic relationships among microbial taxa. In this study, we present an approach for inferring phylogenetic relationships among microorganisms based on the random metagenomic sequencing of DNA fragments. To overcome challenges caused by the fragmentary nature of metagenomic data, we leveraged fully sequenced bacterial genomes as a scaffold to enable inference of phylogenetic relationships among metagenomic sequences from multiple phylogenetic marker gene families. The resulting metagenomic phylogeny can be used to quantify the phylogenetic diversity of microbial communities based on metagenomic data sets. We applied this method to understand patterns of microbial phylogenetic diversity and community assembly along an oceanic depth gradient, and compared our findings to previous studies of this gradient using SSU-rRNA gene and metagenomic analyses. Bacterial phylogenetic diversity was highest at intermediate depths beneath the ocean surface, whereas taxonomic diversity (diversity measured by binning sequences into taxonomically similar groups) showed no relationship with depth. Phylogenetic diversity estimates based on the SSU-rRNA gene and the multi-gene metagenomic phylogeny were broadly concordant, suggesting that our approach will be applicable to other metagenomic data sets for which corresponding SSU-rRNA gene sequences are unavailable. Our approach opens up the possibility of using metagenomic data to study microbial diversity in a phylogenetic context.     

Metagenomic analysis of Streptomyces lividans reveals host-dependent functional expression

Most functional metagenomic studies have been limited by the poor expression of many genes derived from metagenomic DNA in Escherichia coli, which has been the predominant surrogate host to date. To expand the range of expressed genes, we developed tools for construction and functional screening of metagenomic libraries in Streptomyces lividans. We expanded on previously published protocols by constructing a system that enables retrieval and characterization of the metagenomic DNA from biologically active clones. To test the functionality of these methods, we constructed and screened two metagenomic libraries in S. lividans. One was constructed with pooled DNA from 14 bacterial isolates cultured from Alaskan soil and the second with DNA directly extracted from the same soil. Functional screening of these libraries identified numerous clones with hemolytic activity, one clone that produces melanin by a previously unknown mechanism, and one that induces the overproduction of a secondary metabolite native to S. lividans. All bioactive clones were functional in S. lividans but not in E. coli, demonstrating the advantages of screening metagenomic libraries in more than one host.     

MetaSee: An Interactive and Extendable Visualization Toolbox for Metagenomic Sample Analysis and Comparison

The NGS (next generation sequencing)-based metagenomic data analysis is becoming the mainstream for the study of microbial communities. Faced with a large amount of data in metagenomic research, effective data visualization is important for scientists to effectively explore, interpret and manipulate such rich information. The visualization of the metagenomic data, especially multi-sample data, is one of the most critical challenges. The different data sample sources, sequencing approaches and heterogeneous data formats make robust and seamless data visualization difficult. Moreover, researchers have different focuses on metagenomic studies: taxonomical or functional, sample-centric or genome-centric, single sample or multiple samples, etc. However, current efforts in metagenomic data visualization cannot fulfill all of these needs, and it is extremely hard to organize all of these visualization effects in a systematic manner. An extendable, interactive visualization tool would be the method of choice to fulfill all of these visualization needs. In this paper, we have present MetaSee, an extendable toolbox that facilitates the interactive visualization of metagenomic samples of interests. The main components of MetaSee include: (I) a core visualization engine that is composed of different views for comparison of multiple samples: Global view, Phylogenetic view, Sample view and Taxa view, as well as link-out for more in-depth analysis; (II) front-end user interface with real metagenomic models that connect to the above core visualization engine and (III) open-source portal for the development of plug-ins for MetaSee. This integrative visualization tool not only provides the visualization effects, but also enables researchers to perform in-depth analysis of the metagenomic samples of interests. Moreover, its open-source portal allows for the design of plug-ins for MetaSee, which would facilitate the development of any additional visualization effects.     

Metagenomics: Is it a powerful tool to obtain lipases for application in biocatalysis?

In recent years, metagenomic strategies have been widely used to isolate and identify new enzymes from uncultivable components of microbial communities. Among these enzymes, various lipases have been obtained from metagenomic libraries from different environments and characterized. Although many of these lipases have characteristics that could make them interesting for application in biocatalysis, relatively little work has been done to evaluate their potential to catalyze industrially important reactions. In the present article, we highlight the latest research on lipases obtained through metagenomic tools, focusing on studies of activity and stability and investigations of application in biocatalysis. We also discuss the challenges of metagenomic approaches for the bioprospecting of new lipases.     

元基因组学及其在转化医学中的应用

微生物群落遍布于人体的每个角落,与人共生并对人体健康产生重要和深刻的影响。与人类共生的全部微生物的基因组总和称为“元基因组”或“人类第二基因组”。研究人体微生物群落及相关元基因组数据,对转化医学领域的基础研究和临床应用具有重要的价值。通过对生物医学相关的高通量元基因组数据进行分析,不仅能为基础医学研究向医学临床应用转化提供新思路和新方法,而且具有广阔的应用前景。基于新一代测序技术产生的数据,元基因组分析技术和方法能够弥补以往人体微生物先培养后鉴定方法的缺陷,同时能有效鉴定和分析微生物群落的组成及功能,从而进一步探究和揭示微生物群落与机体生理状态之间的关系,为解决许多医学领域的难题提供了全新的切入角度和思维方法。文章系统介绍了元基因组研究的现状,包括元基因组的方法概念和研究进展,并以元基因组在医学研究中的应用为着眼点,综述了元基因组在转化医学方面的研究进展,进一步阐述了元基因组研究在转化医学应用领域中具有的重要地位。     

Metagenomic Guilt by Association: An Operonic Perspective

Next-generation sequencing projects continue to drive a vast accumulation of metagenomic sequence data. Given the growth rate of this data, automated approaches to functional annotation are indispensable and a cornerstone heuristic of many computational protocols is the concept of guilt by association. The guilt by association paradigm has been heavily exploited by genomic context methods that offer functional predictions that are complementary to homology-based annotations, thereby offering a means to extend functional annotation. In particular, operon methods that exploit co-directional intergenic distances can provide homology-free functional annotation through the transfer of functions among co-operonic genes, under the assumption that guilt by association is indeed applicable. Although guilt by association is a well-accepted annotative device, its applicability to metagenomic functional annotation has not been definitively demonstrated. Here a large-scale assessment of metagenomic guilt by association is undertaken where functional associations are predicted on the basis of co-directional intergenic distances. Specifically, functional annotations are compared within pairs of adjacent co-directional genes, as well as operons of various lengths (i.e. number of member genes), in order to reveal new information about annotative cohesion versus operon length. The results suggests that co-directional gene pairs offer reduced confidence for metagenomic guilt by association due to difficulty in resolving the existence of functional associations when intergenic distance is the sole predictor of pairwise gene interactions. However, metagenomic operons, particularly those with substantial lengths, appear to be capable of providing a superior basis for metagenomic guilt by association due to increased annotative stability. The need for improved recognition of metagenomic operons is discussed, as well as the limitations of the present work.     

Gut microbiome alterations and its link to corticosteroid resistance in immune thrombocytopenia

Quantitative metagenomic studies have linked the gut microbiota to autoimmune disorders.Here,we performed deep shotgun metagenomic sequencing of fecal samples f...     

An analysis of the validity and utility of the proximon proposition

The utilization of metagenomic functional interactions represents a key technique for metagenomic functional annotation efforts. By definition, metagenomic operons represent such interactions, but many operon predictions protocols rely on information about orthology and/or gene function that is frequently unavailable for metagenomic genes. Recently, the concept of the metagenomic proximon was proposed for use in metagenomic scenarios where supplemental information is sparse. In this paper, we examine the validity and utility of the proximon proposition by measuring the extent to which proximons emulate actual operons. Using the Escherichia coli K-12 genome, we compare proximons and operons from the same genome and observe the configurations and cardinalities among their corresponding mappings. The results demonstrate that the vast majority of proximons map discretely to a single operon in a conservative fashion where a typical proximon is synonymous to an equivalent or truncated operon. However, a large proportion of operons had no corresponding mappings to any proximon. Various perspectives of operon and proximon intersection are discussed, along with the potential limitations for proximon detection and usage.     

Enriching plant microbiota for a metagenomic library construction

Plant microbiota (the microorganisms that live in any associations with plant tissues) represents a rather unexplored area of metagenomic research compared with soils and oceans. Constructing a metagenomic library for plant microbiota is technically challenging. Using all the biomass without pre-enrichment could lead to vast proportions of the host plant DNA in the metagenomic library, doubtless obliterating the microbial contribution. Therefore, the first and essential step is to enrich for the constituent microorganisms from plant tissues. Here, a strong enrichment for plant microbiota was achieved by coupling SDS (sodium dodecyl sulfate) with NaCl, creating a predominantly microbial metagenomic library that contains 88% bacterial inserts. 16S rDNA sequence analysis revealed that the metagenomic DNA of enrichments originates from very diverse microorganisms. At least 74 distinct ribotypes (at a 97% threshold) from seven different bacterial phyla were identified and mainly distributed among Actinobacteria and Proteobacteria. Additionally, a simplified version of Amplified Ribosomal DNA Restriction Analysis (ARDRA) was developed for a quick and efficient assessment of the enriching procedures. This work opens further insight into the great biotechnical potential of plant microbiota, holding more potential for drug discovery through a metagenomic strategy, and paving the way for recovery and biochemical characterization of functional gene repertoire from plant microbiota.     

Construction of a metagenomic library for the marine sponge Halichondria okadai

Symbionts of the marine sponge Halichondria okadai are promising as a source of natural products. Metagenomic technology is a powerful tool for accessing the genetic and biochemical potential of bacteria. Hence, we established a method of recovering bacterial-enriched metagenomic DNA by stepwise centrifugation. The metagenomic DNA was analyzed by ultrafast 454-pyrosequencing technology, and the results suggested that more than three types of bacterial DNA, Alphaproteobacteria, Actinobacteria, and Cyanobacteria, had been recovered, and that eukaryotic genes comprised only 0.02% of the metagenomic DNA. These results indicate that stepwise centrifugation and real-time quantitative PCR were effective for separating sponge cells and symbiotic bacteria, and that we constructed a bacteria-enriched metagenomic library from a marine sponge, H. okadai, selectively for the first time.     

Evaluating the fidelity of de novo short read metagenomic assembly using simulated data

A frequent step in metagenomic data analysis comprises the assembly of the sequenced reads. Many assembly tools have been published in the last years targeting data coming from next-generation sequencing (NGS) technologies but these assemblers have not been designed for or tested in multi-genome scenarios that characterize metagenomic studies. Here we provide a critical assessment of current de novo short reads assembly tools in multi-genome scenarios using complex simulated metagenomic data. With this approach we tested the fidelity of different assemblers in metagenomic studies demonstrating that even under the simplest compositions the number of chimeric contigs involving different species is noticeable. We further showed that the assembly process reduces the accuracy of the functional classification of the metagenomic data and that these errors can be overcome raising the coverage of the studied metagenome. The results presented here highlight the particular difficulties that de novo genome assemblers face in multi-genome scenarios demonstrating that these difficulties, that often compromise the functional classification of the analyzed data, can be overcome with a high sequencing effort.     

Class Prediction and Feature Selection with Linear Optimization for Metagenomic Count Data

The amount of metagenomic data is growing rapidly while the computational methods for metagenome analysis are still in their infancy. It is important to develop novel statistical learning tools for the prediction of associations between bacterial communities and disease phenotypes and for the detection of differentially abundant features. In this study, we presented a novel statistical learning method for simultaneous association prediction and feature selection with metagenomic samples from two or multiple treatment populations on the basis of count data. We developed a linear programming based support vector machine with and joint penalties for binary and multiclass classifications with metagenomic count data (metalinprog). We evaluated the performance of our method on several real and simulation datasets. The proposed method can simultaneously identify features and predict classes with the metagenomic count data.     

Intracellular screen to identify metagenomic clones that induce or inhibit a quorum-sensing biosensor

The goal of this study was to design and evaluate a rapid screen to identify metagenomic clones that produce biologically active small molecules. We built metagenomic libraries with DNA from soil on the floodplain of the Tanana River in Alaska. We extracted DNA directly from the soil and cloned it into fosmid and bacterial artificial chromosome vectors, constructing eight metagenomic libraries that contain 53,000 clones with inserts ranging from 1 to 190 kb. To identify clones of interest, we designed a high throughput "intracellular" screen, designated METREX, in which metagenomic DNA is in a host cell containing a biosensor for compounds that induce bacterial quorum sensing. If the metagenomic clone produces a quorum-sensing inducer, the cell produces green fluorescent protein (GFP) and can be identified by fluorescence microscopy or captured by fluorescence-activated cell sorting. Our initial screen identified 11 clones that induce and two that inhibit expression of GFP. The intracellular screen detected quorum-sensing inducers among metagenomic clones that a traditional overlay screen would not. One inducing clone carries a LuxI homologue that directs the synthesis of an N-acyl homoserine lactone quorum-sensing signal molecule. The LuxI homologue has 62% amino acid sequence identity to its closest match in GenBank, AmfI from Pseudomonas fluorescens, and is on a 78-kb insert that contains 67 open reading frames. Another inducing clone carries a gene with homology to homocitrate synthase. Our results demonstrate the power of an intracellular screen to identify functionally active clones and biologically active small molecules in metagenomic libraries.