Experimental designs that take advantage of high-throughput sequencing to generate datasets include RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), sequencing of 16S rRNA gene fragments, metagenomic analysis and selective growth experiments. In each case the underlying data are similar and are composed of counts of sequencing reads mapped to a large number of features in each sample. Despite this underlying similarity, the data analysis methods used for these experimental designs are all different, and do not translate across experiments. Alternative methods have been developed in the physical and geological sciences that treat similar data as compositions. Compositional data analysis methods transform the data to relative abundances with the result that the analyses are more robust and reproducible. Data from an in vitro selective growth experiment, an RNA-seq experiment and the Human Microbiome Project 16S rRNA gene abundance dataset were examined by ALDEx2, a compositional data analysis tool that uses Bayesian methods to infer technical and statistical error. The ALDEx2 approach is shown to be suitable for all three types of data: it correctly identifies both the direction and differential abundance of features in the differential growth experiment, it identifies a substantially similar set of differentially expressed genes in the RNA-seq dataset as the leading tools and it identifies as differential the taxa that distinguish the tongue dorsum and buccal mucosa in the Human Microbiome Project dataset. The design of ALDEx2 reduces the number of false positive identifications that result from datasets composed of many features in few samples. Statistical analysis of high-throughput sequencing datasets composed of per feature counts showed that the ALDEx2 R package is a simple and robust tool, which can be applied to RNA-seq, 16S rRNA gene sequencing and differential growth datasets, and by extension to other techniques that use a similar approach.

/pdf/unifying-the-analysis-of-high-throughput-sequencing-datasets-42wzo951bs.pdf

Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis

Antibiotic resistance is a natural feature of diverse microbial ecosystems. Although recent studies of the antibiotic resistome have highlighted barriers to the horizontal transfer of antibiotic resistance genes between habitats, the rapid global spread of genes that confer resistance to carbapenem, colistin and quinolone antibiotics illustrates the dire clinical and societal consequences of such events. Over time, the study of antibiotic resistance has grown from focusing on single pathogenic organisms in axenic culture to studying antibiotic resistance in pathogenic, commensal and environmental bacteria at the level of microbial communities. As the study of antibiotic resistance advances, it is important to incorporate this comprehensive approach to better inform global antibiotic resistance surveillance and antibiotic development. It is increasingly becoming apparent that although not all resistance genes are likely to geographically and phylogenetically disseminate, the threat presented by those that are is serious and warrants an interdisciplinary research focus. In this Review, we highlight seminal work in the resistome field, discuss recent advances in the studies of resistomes, and propose a resistome paradigm that can pave the way for the improved proactive identification and mitigation of emerging antibiotic resistance threats.

/pdf/next-generation-approaches-to-understand-and-combat-the-rsgpgsstu5.pdf

Next-generation approaches to understand and combat the antibiotic resistome

Plant pathogens are responsible for many crop plant diseases, resulting in economic losses. The use of bacterial agents is an excellent option to fight against plant pathogens and an excellent alternative to the use of chemicals, which are offensive to the environment and to human health. Two of the most common biocontrol agents are members of the Bacillus and Pseudomonas genera. Both bacterial genera have important traits such as plant growth-promoting (PGP) properties. This review analyzes pioneering and recent works and the mechanisms used by Bacillus and Pseudomonas in their behaviour as biocontrol and PGP agents, discussing their mode of action by comparing the two genera. Undoubtedly, future integrated research strategies for biocontrol and PGP will require the help of known and novel species of both genera.

Mechanisms of biocontrol and plant growth-promoting activity in soil bacterial species of Bacillus and Pseudomonas: a review

Functional metagenomics for enzyme discovery: challenges to efficient screening.

The ESTHER database, which is freely available via a web server (http://bioweb.ensam.inra.fr/esther) and is widely used, is dedicated to proteins with an α/β-hydrolase fold, and it currently contains >30 000 manually curated proteins. Herein, we report those substantial changes towards improvement that we have made to improve ESTHER during the past 8 years since our 2004 update. In particular, we generated 87 new families and increased the coverage of the UniProt Knowledgebase (UniProtKB). We also renewed the ESTHER website and added new visualization tools, such as the Overall Table and the Family Tree. We also address two topics of particular interest to the ESTHER users. First, we explain how the different enzyme classifications (bacterial lipases, peptidases, carboxylesterases) used by different communities of users are combined in ESTHER. Second, we discuss how variations of core architecture or in predicted active site residues result in a more precise clustering of families, and whether this strategy provides trustable hints to identify enzyme-like proteins with no catalytic activity.

https://hal.archives-ouvertes.fr/hal-01218998/document

ESTHER, the database of the α/β-hydrolase fold superfamily of proteins: tools to explore diversity of functions

Chloramphenicol and florfenicol are broad-spectrum antibiotics. Although the bacterial resistance mechanisms to these antibiotics have been well documented, hydrolysis of these antibiotics has not been reported in detail. This study reports the hydrolysis of these two antibiotics by a specific hydrolase that is encoded by a gene identified from a soil metagenome. Hydrolysis of chloramphenicol has been recognized in cell extracts of Escherichia coli expressing a chloramphenicol acetate esterase gene, estDL136. A hydrolysate of chloramphenicol was identified as p-nitrophenylserinol by liquid chromatography-mass spectroscopy and proton nuclear magnetic resonance spectroscopy. The hydrolysis of these antibiotics suggested a promiscuous amidase activity of EstDL136. When estDL136 was expressed in E. coli, EstDL136 conferred resistance to both chloramphenicol and florfenicol on E. coli, due to their inactivation. In addition, E. coli carrying estDL136 deactivated florfenicol faster than it deactivated chloramphenicol, suggesting that EstDL136 hydrolyzes florfenicol more efficiently than it hydrolyzes chloramphenicol. The nucleotide sequences flanking estDL136 encode proteins such as amidohydrolase, dehydrogenase/reductase, major facilitator transporter, esterase, and oxidase. The most closely related genes are found in the bacterial family Sphingomonadaceae, which contains many bioremediation-related strains. Whether the gene cluster with estDL136 in E. coli is involved in further chloramphenicol degradation was not clear in this study. While acetyltransferases for chloramphenicol resistance and drug exporters for chloramphenicol or florfenicol resistance are often detected in numerous microbes, this is the first report of enzymatic hydrolysis of florfenicol resulting in inactivation of the antibiotic.

Inactivation of Chloramphenicol and Florfenicol by a Novel Chloramphenicol Hydrolase

Using two forest soils, we previously constructed two fosmid libraries containing 113,700 members in total. The libraries were screened to select active antifungal clones using Saccharomyces cerevisiae as a target fungus. One clone from the Yuseong pine tree rhizosphere soil library, pEAF66, showed S. cerevisiae growth inhibition. Despite an intensive effort, active chemicals were not isolated. DNA sequence analysis and transposon mutagenesis of pEAF66 revealed 39 open reading frames (ORFs) and indicated that eight ORFs, probably in one transcriptional unit, might be directly involved in the expression of antifungal activity in Escherichia coli. The deduced amino acid sequences of eight ORFs were similar to those of the core genes encoding type II family polyketide synthases, such as the acyl carrier protein (ACP), ACP synthases, aminotransferase, and ACP reductase. The gene cluster involved in antifungal activity was similar in organization to the putative antibiotic production locus of Pseudomonas putida KT2440, although we could not select a similar active clone from the KT2440 genomic DNA library in E. coli. ORFs encoding ATP binding cassette transporters and membrane proteins were located at both ends of the antifungal gene cluster. Upstream ORFs encoding an IclR family response regulator and a LysR family response regulator were involved in the positive regulation of antifungal gene expression. Our results suggested the metagenomic approach as an alternative to search for novel antifungal antibiotics from unculturable soil bacteria. This is the first report of an antifungal gene cluster obtained from a soil metagenome using S. cerevisiae as a target fungus.

Forest soil metagenome gene cluster involved in antifungal activity expression in Escherichia coli.

The microbial diversity in soil ecosystems is higher than in any other microbial ecosystem. The majority of soil microorganisms has not been characterized, because the dominant members have not been readily culturable on standard cultivation media; therefore, the soil ecosystem is a great reservoir for the discovery of novel microbial enzymes and bioactivities. The soil metagenome, the collective microbial genome, could be cloned and sequenced directly from soils to search for novel microbial resources. This review summarizes the microbial diversity in soils and the efforts to search for microbial resources from the soil metagenome, with more emphasis on the potential of bioprospecting metagenomics and recent discoveries.

/pdf/bioprospecting-potential-of-the-soil-metagenome-novel-3c81mfj1ug.pdf

Bioprospecting Potential of the Soil Metagenome: Novel Enzymes and Bioactivities

Soil metagenome constitutes a reservoir for discovering novel enzymes from the unculturable microbial diversity. From three plant rhizosphere metagenomic libraries comprising a total of 142,900 members of recombinant plasmids, we obtained 14 recombinant fosmids that exhibited lipolytic activity. A selected recombinant plasmid, pFLP-2, which showed maximum lipolytic activity, was further analyzed. DNA sequence analysis of the subclone in pUC119, pELP-2, revealed an open reading frame of 1,191 bp encoding a 397-amino-acid protein. Purified EstD2 exhibited maximum enzymatic activity towards p-nitrophenyl butyrate, indicating that it is an esterase. Purified EstD2 showed optimal activity at 35 °C and at pH 8.0. The K
 m and K
 cat values were determined to be 79.4 μM and 120.5/s, respectively. The esterase exhibited an increase in enzymatic activity in the presence of 15% butanol and 15% methanol. Phylogenetic analysis revealed that the lipolytic protein EstD2 may be a member of a novel family of lipolytic enzymes. Several hypothetical protein homologs of EstD2 were found in the database. A hypothetical protein from Phenylobacterium zucineum HLK1, a close homolog of EstD2, displayed lipolytic activity when the corresponding gene was expressed in Escherichia coli. Our results suggest that the other hypothetical protein homologs of EstD2 might also be members of this novel family.

A new esterase EstD2 isolated from plant rhizosphere soil metagenome

A metagenome is a unique resource to search for novel microbial enzymes from the unculturable microorganisms in soil. A forest soil metagenomic library using a fosmid and soil microbial DNA from Gwangneung forest, Korea, was constructed in Escherichia coli and screened to select lipolytic genes. A total of seven unique lipolytic clones were selected by screening of the 31,000-member forest soil metagenome library based on tributyrin hydrolysis. The ORFs for lipolytic activity were subcloned in a high copy number plasmid by screening the secondary shortgun libraries from the seven clones. Since the lipolytic enzymes were well secreted in E. coli into the culture broth, the lipolytic activity of the subclones was confirmed by the hydrolysis of p-nitrophenyl butyrate using culture supernatant. Deduced amino acid sequence analysis of the identified ORFs for lipolytic activity revealed that 4 genes encode hormone-sensitive lipase (HSL) in lipase family IV. Phylogenetic analysis indicated that 4 proteins were clustered with HSL in the database and other metagenomic HSLs. The other 2 genes and 1 gene encode non-heme peroxidase-like enzymes of lipase family V and a GDSL family esterase/lipase in family II, respectively. The gene for the GDSL enzyme is the first description of the enzyme from metagenomic screening.

http://www.koreascience.or.kr:80/article/JAKO200709906364088.pdf

Myung Hwan Lee

Papers

Inactivation of Chloramphenicol and Florfenicol by a Novel Chloramphenicol Hydrolase

Forest soil metagenome gene cluster involved in antifungal activity expression in Escherichia coli.

Bioprospecting Potential of the Soil Metagenome: Novel Enzymes and Bioactivities

A new esterase EstD2 isolated from plant rhizosphere soil metagenome

Selection and characterization of forest soil metagenome genes encoding lipolytic enzymes