Recent progress and new challenges in metagenomics for biotechnology

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Navigating the complex relationship between human gut microbiota and breast cancer: Physiopathological, prognostic and therapeutic implications

The human body represents the habitat of trillions of symbiotic microorganisms, collectively known as human microbiota, approximately half of which residing in the gut. The development of next-generation sequencing techniques has boosted the profiling of human microbiota in recent years. A growing body of evidence seems to support a strict relationship between the disruption of the mutualistic relationship between the microbiota and the host (i.e., dysbiosis) and the development of several diseases, including breast malignancies. Breast cancer still represents the most frequent cause of cancer-related death in women. Its complex relationship with gut microbiota is the object of a growing body of evidence. In fact, the interaction with the host immune system and a direct impact of gut microbiota on estrogen, lipid and polyphenols metabolism, seem to potentially affect breast tumor development, progression and response to treatments. In this review, in an attempt to help oncologists navigating this rapidly-evolving research field, we provide an essential overview on the taxonomy, main analytical techniques and terminology most commonly adopted. We discuss what is currently known regarding the interaction between gut microbiota and breast cancer and potential efforts to harness this complex interplay for therapeutic purposes, and revise main ongoing studies. We also briefly provide an overview on breast cancer intratumoral microbiota and its potential role beyond gut microbiota.

Insufficiency in functional genomics studies, data, and applications: A case study of bio-prospecting research in ruminant microbiome

Over the last two decades, biotechnology has advanced at a rapid pace, propelled by the incorporation of bio-products into various aspects of pharmaceuticals, industry, and the environment. These developments have sparked interest in the bioprospecting of microorganisms and their products in a variety of niche environments. Furthermore, the use of omics technologies has greatly aided our analyses of environmental samples by elucidating the microbial ecological framework, biochemical pathways, and bio-products. However, the more often overemphasis on taxonomic identification in most research publications, as well as the data associated with such studies, is detrimental to immediate industrial and commercial applications. This review identifies several factors that contribute to the complexity of sequence data analysis as potential barriers to the pragmatic application of functional genomics, utilizing recent research on ruminants to demonstrate these limitations in the hopes of broadening our horizons and drawing attention to this gap in bioprospecting studies for other niche environments as well. The review also aims to emphasize the importance of routinely incorporating functional genomics into environmental metagenomics analyses in order to improve solutions that drive rapid industrial biocatalysis developments from derived outputs with the aim of achieving potential benefits in energy-use reduction and environmental considerations for current and future applications.

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity

Microorganisms growing in their habitat constitute a complex system. How the individual constituents of the environment contribute to microbial growth remains largely unknown. The present study focused on the contribution of environmental constituents to population dynamics via a high-throughput assay and data-driven analysis of a wild-type Escherichia coli strain. A large dataset constituting a total of 12,828 bacterial growth curves with 966 medium combinations, which were composed of 44 pure chemical compounds, was acquired. Machine learning analysis of the big data relating the growth parameters to the medium combinations revealed that the decision-making components for bacterial growth were distinct among various growth phases, e.g., glucose, sulfate, and serine for maximum growth, growth rate, and growth delay, respectively. Further analyses and simulations indicated that branched-chain amino acids functioned as global coordinators for population dynamics, as well as a survival strategy of risk diversification to prevent the bacterial population from undergoing extinction.

Friends or Foes-Microbial Interactions in Nature

Simple Summary

Microorganisms like bacteria, archaea, fungi, microalgae, and viruses mostly form complex interactive networks within the ecosystem rather than existing as single planktonic cells. Interactions among microorganisms occur between the same species, with different species, or even among entirely different genera, families, or even domains. These interactions occur after environmental sensing, followed by converting those signals to molecular and genetic information, including many mechanisms and classes of molecules. Comprehensive studies on microbial interactions disclose key strategies of microbes to colonize and establish in a variety of different environments. Knowledge of the mechanisms involved in the microbial interactions is essential to understand the ecological impact of microbes and the development of dysbioses. It might be the key to exploit strategies and specific agents against different facing challenges, such as chronic and infectious diseases, hunger crisis, pollution, and sustainability.

Abstract

Microorganisms are present in nearly every niche on Earth and mainly do not exist solely but form communities of single or mixed species. Within such microbial populations and between the microbes and a eukaryotic host, various microbial interactions take place in an ever-changing environment. Those microbial interactions are crucial for a successful establishment and maintenance of a microbial population. The basic unit of interaction is the gene expression of each organism in this community in response to biotic or abiotic stimuli. Differential gene expression is responsible for producing exchangeable molecules involved in the interactions, ultimately leading to community behavior. Cooperative and competitive interactions within bacterial communities and between the associated bacteria and the host are the focus of this review, emphasizing microbial cell–cell communication (quorum sensing). Further, metagenomics is discussed as a helpful tool to analyze the complex genomic information of microbial communities and the functional role of different microbes within a community and to identify novel biomolecules for biotechnological applications.

Stem Cell Impairment at the Host-Microbiota Interface in Colorectal Cancer

Colorectal cancer (CRC) initiation is believed to result from the conversion of normal intestinal stem cells (ISCs) into cancer stem cells (CSCs), also known as tumor-initiating cells (TICs). Hence, CRC evolves through the multiple acquisition of well-established genetic and epigenetic alterations with an adenoma-carcinoma sequence progression. Unlike other stem cells elsewhere in the body, ISCs cohabit with the intestinal microbiota, which consists of a diverse community of microorganisms, including bacteria, fungi, and viruses. The gut microbiota communicates closely with ISCs and mounting evidence suggests that there is significant crosstalk between host and microbiota at the ISC niche level. Metagenomic analyses have demonstrated that the host-microbiota mutually beneficial symbiosis existing under physiologic conditions is lost during a state of pathological microbial imbalance due to the alteration of microbiota composition (dysbiosis) and/or the genetic susceptibility of the host. The complex interaction between CRC and microbiota is at the forefront of the current CRC research, and there is growing attention on a possible role of the gut microbiome in the pathogenesis of CRC through ISC niche impairment. Here we primarily review the most recent findings on the molecular mechanism underlying the complex interplay between gut microbiota and ISCs, revealing a possible key role of microbiota in the aberrant reprogramming of CSCs in the initiation of CRC. We also discuss recent advances in OMICS approaches and single-cell analyses to explore the relationship between gut microbiota and ISC/CSC niche biology leading to a desirable implementation of the current precision medicine approaches.

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on "omics" driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in "omics" technologies, compare the pros and cons of the different "omics" technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of "omics" technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of "omics" technologies to agricultural and food biotechnology, and review the impact of "omics" on current COVID-19 research.

Bioprospecting of Novel Extremozymes From Prokaryotes-The Advent of Culture-Independent Methods

Extremophiles are remarkable organisms that thrive in the harshest environments on Earth, such as hydrothermal vents, hypersaline lakes and pools, alkaline soda lakes, deserts, cold oceans, and volcanic areas. These organisms have developed several strategies to overcome environmental stress and nutrient limitations. Thus, they are among the best model organisms to study adaptive mechanisms that lead to stress tolerance. Genetic and structural information derived from extremophiles and extremozymes can be used for bioengineering other nontolerant enzymes. Furthermore, extremophiles can be a valuable resource for novel biotechnological and biomedical products due to their biosynthetic properties. However, understanding life under extreme conditions is challenging due to the difficulties of in vitro cultivation and observation since > 99% of organisms cannot be cultivated. Consequently, only a minor percentage of the potential extremophiles on Earth have been discovered and characterized. Herein, we present a review of culture-independent methods, sequence-based metagenomics (SBM), and single amplified genomes (SAGs) for studying enzymes from extremophiles, with a focus on prokaryotic (archaea and bacteria) microorganisms. Additionally, we provide a comprehensive list of extremozymes discovered via metagenomics and SAGs.

Diversity and structure of prokaryotic communities within organic and conventional farming systems in central highlands of Kenya

Management practices such as tillage, crop rotation, irrigation, organic and inorganic inputs application are known to influence diversity and function of soil microbial populations. In this study, we investigated the effect of conventional versus organic farming systems at low and high input levels on structure and diversity of prokaryotic microbial communities. Soil samples were collected from the ongoing long-term farming system comparison trials established in 2007 at Chuka and Thika in Kenya. Physicochemical parameters for each sample were analyzed. Total DNA and RNA amplicons of variable region (V4-V7) of the 16S rRNA gene were generated on an Illumina platform using the manufacturer's instructions. Diversity indices and statistical analysis were done using QIIME2 and R packages, respectively. A total of 29,778,886 high quality reads were obtained and assigned to 16,176 OTUs at 97% genetic distance across both 16S rDNA and 16S rRNA cDNA datasets. The results pointed out a histrionic difference in OTUs based on 16S rDNA and 16S rRNA cDNA. Precisely, while 16S rDNA clustered by site, 16S rRNA cDNA clustered by farming systems. In both sites and systems, dominant phylotypes were affiliated to phylum Actinobacteria, Proteobacteria and Acidobacteria. Conventional farming systems showed a higher species richness and diversity compared to organic farming systems, whilst 16S rRNA cDNA datasets were similar. Physiochemical factors were associated differently depending on rRNA and rDNA. Soil pH, electrical conductivity, organic carbon, nitrogen, potassium, aluminium, zinc, iron, boron and micro-aggregates showed a significant influence on the observed microbial diversity. The observed higher species diversity in the conventional farming systems can be attributed to the integration of synthetic and organic agricultural inputs. These results show that the type of inputs used in a farming system not only affect the soil chemistry but also the microbial population dynamics and eventually the functional roles of these microbes.

Bioinformatics for Marine Products: An Overview of Resources, Bottlenecks, and Perspectives

The sea represents a major source of biodiversity. It exhibits many different ecosystems in a huge variety of environmental conditions where marine organisms have evolved with extensive diversification of structures and functions, making the marine environment a treasure trove of molecules with potential for biotechnological applications and innovation in many different areas. Rapid progress of the omics sciences has revealed novel opportunities to advance the knowledge of biological systems, paving the way for an unprecedented revolution in the field and expanding marine research from model organisms to an increasing number of marine species. Multi-level approaches based on molecular investigations at genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, and metabolomic levels are essential to discover marine resources and further explore key molecular processes involved in their production and action. As a consequence, omics approaches, accompanied by the associated bioinformatic resources and computational tools for molecular analyses and modeling, are boosting the rapid advancement of biotechnologies. In this review, we provide an overview of the most relevant bioinformatic resources and major approaches, highlighting perspectives and bottlenecks for an appropriate exploitation of these opportunities for biotechnology applications from marine resources.

Characterization of novel glycosyl hydrolases discovered by cell wall glycan directed monoclonal antibody screening and metagenome analysis of maize aerial root mucilage

An indigenous maize landrace from the Sierra Mixe region of Oaxaca, Mexico exhibits extensive formation of aerial roots which exude large volumes of a polysaccharide-rich gel matrix or "mucilage" that harbors diazotrophic microbiota. We hypothesize that the mucilage associated microbial community carries out multiple functions, including disassembly of the mucilage polysaccharide. In situ, hydrolytic assay of the mucilage revealed endogenous arabinofuranosidase, galactosidase, fucosidase, mannosidase and xylanase activities. Screening the mucilage against plant cell wall glycan-specific monoclonal antibodies recognized the presence of carbohydrate epitopes of hemicellulosic polysaccharides like xyloglucan (both non-fucosylated and fucosylated), xylan (both substituted and unsubstituted xylan domains) and pectic-arabinogalactans, all of which are potential carbon sources for mucilage microbial residents. Mucilage metagenome annotation using MG-RAST identified the members forming the microbial community, and gene fragments with predicted functions associated with carbohydrate disassembly. Data from the in situ hydrolytic activity and monoclonal antibody screening assays were used to guide the selection of five full length genes with predicted glycosyl hydrolase function from the GenBank database that were similar to gene fragments of high relative abundance in the mucilage metagenomes. These five genes were then synthesized for recombinant production in Escherichia coli. Here we report the characterization of an α-N-arabinofuranosidase (GH51) and an oligosaccharide reducing-end xylanase (GH8) from Flavobacterium johnsoniae; an α-L-fucosidase (GH29) and a xylan β-1,4 xylosidase (GH39) from Spirosoma linguale, and a β-mannosidase (GH2) from Agrobacterium fabrum. Biochemical characterization of these enzymes revealed a β-Mannosidase that also exhibits a secondary activity towards the cleavage of galactosyl residues. We also describe two xylanases (GH8 and GH39) from underexplored glycosyl hydrolase families, one thermostable α-L-Fucosidase (GH29) and a thermostable α-N-Arabinofuranosidase (GH51).

Retracted: Bacteria diversity overview and endoglucanase assessment from Himalayan Tapovan geothermal spring

The above article from the Journal of Basic Microbiology, published online on 25 August 2015 in Wiley Online Library as Early View (http://onlinelibrary.wiley.com/doi/10.1002/jobm.201500135/pdf), has been retracted by agreement between Naveen Kumar Navani and Ranjana Pathania, the Editor-in-Chief and Wiley-VCH GmbH & Co. KGaA. The retraction has been agreed because the article has been submitted and approved for publication by Jitendra Kumar Sahoo without consent in any form by the named co-authors Naveen Kumar Navani and Ranjana Pathania.

Assessment of bacterial superficial contamination in classical or ritually slaughtered cattle using metagenetics and microbiological analysis

The aim of this study was to investigate the influence of the slaughter technique (Halal vs Classical slaughter) on the superficial contamination of cattle carcasses, by using traditional microbiological procedures and 16S rDNA metagenetics. The purpose was also to investigate the neck area to identify bacteria originating from the digestive or the respiratory tract. Twenty bovine carcasses (10 from each group) were swabbed at the slaughterhouse, where both slaughtering methods are practiced. Two swabbing areas were chosen: one "legal" zone of 1600cm² (composed of zones from rump, flank, brisket and forelimb) and locally on the neck area (200cm²). Samples were submitted to classical microbiology for aerobic Total Viable Counts (TVC) at 30°C and Enterobacteriaceae counts, while metagenetic analysis was performed on the same samples. The classical microbiological results revealed no significant differences between both slaughtering practices; with values between 3.95 and 4.87log CFU/100cm² and 0.49 and 1.94log CFU/100cm², for TVC and Enterobacteriaceae respectively. Analysis of pyrosequencing data showed that differences in the bacterial population abundance between slaughtering methods were mainly observed in the "legal" swabbing zone compared to the neck area. Bacterial genera belonging to the Actinobacteria phylum were more abundant in the "legal" swabbing zone in "Halal" samples, while Brevibacterium and Corynebacterium were encountered more in "Halal" samples, in all swabbing areas. This was also the case for Firmicutes bacterial populations (families of Aerococcaceae, Planococcaceae). Except for Planococcoceae, the analysis of Operational Taxonomic Unit (OTU) abundances of bacteria from the digestive or respiratory tract revealed no differences between groups. In conclusion, the slaughtering method does not influence the superficial microbiological pattern in terms of specific microbiological markers of the digestive or respiratory tract. However, precise analysis of taxonomy at the genus level taxonomy highlights differences between swabbing areas. Although not clearly proven in this study, differences in hygiene practices used during both slaughtering protocols could explain the differences in contamination between carcasses from both slaughtering groups.

Metagenomics of Thermophiles with a Focus on Discovery of Novel Thermozymes

Microbial populations living in environments with temperatures above 50°C (thermophiles) have been widely studied, increasing our knowledge in the composition and function of these ecological communities. Since these populations express a broad number of heat-resistant enzymes (thermozymes), they also represent an important source for novel biocatalysts that can be potentially used in industrial processes. The integrated study of the whole-community DNA from an environment, known as metagenomics, coupled with the development of next generation sequencing (NGS) technologies, has allowed the generation of large amounts of data from thermophiles. In this review, we summarize the main approaches commonly utilized for assessing the taxonomic and functional diversity of thermophiles through metagenomics, including several bioinformatics tools and some metagenome-derived methods to isolate their thermozymes.

Metabolic potential of microbial mats and microbialites: Autotrophic capabilities described by an in silico stoichiometric approach from shared genomic resources

Microbialites and microbial mats are complex communities with high phylogenetic diversity. These communities are mostly composed of bacteria and archaea, which are the earliest living forms on Earth and relevant to biogeochemical evolution. In this study, we identified the shared metabolic pathways for uptake of inorganic C and N in microbial mats and microbialites based on metagenomic data sets. An in silico analysis for autotrophic pathways was used to trace the paths of C and N to the system, following an elementary flux modes (EFM) approach, resulting in a stoichiometric model. The fragility was analyzed by the minimal cut sets method. We found four relevant pathways for the incorporation of CO2 (Calvin cycle, reverse tricarboxylic acid cycle, reductive acetyl-CoA pathway, and dicarboxylate/4-hydroxybutyrate cycle), some of them present only in archaea, while nitrogen fixation was the most important source of N to the system. The metabolic potential to incorporate nitrate to biomass was also relevant. The fragility of the network was low, suggesting a high redundancy of the autotrophic pathways due to their broad metabolic diversity, and highlighting the relevance of reducing power source. This analysis suggests that microbial mats and microbialites are "metabolic pumps" for the incorporation of inorganic gases and formation of organic matter.

Discovery Strategies of Bioactive Compounds Synthesized by Nonribosomal Peptide Synthetases and Type-I Polyketide Synthases Derived from Marine Microbiomes

Considering that 70% of our planet's surface is covered by oceans, it is likely that undiscovered biodiversity is still enormous. A large portion of marine biodiversity consists of microbiomes. They are very attractive targets of bioprospecting because they are able to produce a vast repertoire of secondary metabolites in order to adapt in diverse environments. In many cases secondary metabolites of pharmaceutical and biotechnological interest such as nonribosomal peptides (NRPs) and polyketides (PKs) are synthesized by multimodular enzymes named nonribosomal peptide synthetases (NRPSes) and type-I polyketide synthases (PKSes-I), respectively. Novel findings regarding the mechanisms underlying NRPS and PKS evolution demonstrate how microorganisms could leverage their metabolic potential. Moreover, these findings could facilitate synthetic biology approaches leading to novel bioactive compounds. Ongoing advances in bioinformatics and next-generation sequencing (NGS) technologies are driving the discovery of NRPs and PKs derived from marine microbiomes mainly through two strategies: genome-mining and metagenomics. Microbial genomes are now sequenced at an unprecedented rate and this vast quantity of biological information can be analyzed through genome mining in order to identify gene clusters encoding NRPSes and PKSes of interest. On the other hand, metagenomics is a fast-growing research field which directly studies microbial genomes and their products present in marine environments using culture-independent approaches. The aim of this review is to examine recent developments regarding discovery strategies of bioactive compounds synthesized by NRPS and type-I PKS derived from marine microbiomes and to highlight the vast diversity of NRPSes and PKSes present in marine environments by giving examples of recently discovered bioactive compounds.

Exploring the Bacterial Diversity of Belgian Steak Tartare Using Metagenetics and Quantitative Real-Time PCR Analysis

Steak tartare is a popular meat dish in Belgium. It is prepared with raw minced beef and is eaten with sauce, vegetables, and spices. Because it contains raw meat, steak tartare is highly prone to bacterial spoilage. The objective of this study was to explore the diversity of bacterial flora in steak tartare in Belgium according to the source and to determine which bacteria are able to grow during shelf life. A total of 58 samples from butchers' shops, restaurants, sandwich shops, and supermarkets were collected. These samples were analyzed using 16S rDNA metagenetics, a classical microbiological technique, and quantitative real-time PCR (qPCR) targeting the Lactobacillus genus. Samples were analyzed at the beginning and at the end of their shelf life, except for those from restaurants and sandwich shops, which were analyzed only on the purchase date. Metagenetic analysis identified up to 180 bacterial species and 90 genera in some samples. But only seven bacterial species were predominant in the samples, depending on the source: Brochothrix thermosphacta, Lactobacillus algidus, Lactococcus piscium, Leuconostoc gelidum, Photobacterium kishitani, Pseudomonas spp., and Xanthomonas oryzae. With this work, an alternative method is proposed to evaluate the total flora in food samples based on the number of reads from metagenetic analysis and the results of qPCR. The degree of underestimation of aerobic plate counts at 30°C estimated with the classical microbiology method was demonstrated in comparison with the proposed culture-independent method. Compared with culture-based methods, metagenetic analysis combined with qPCR targeting Lactobacillus provides valuable information for characterizing the bacterial flora of raw meat.

Metatranscriptomics of Soil Eukaryotic Communities

Functions expressed by eukaryotic organisms in soil can be specifically studied by analyzing the pool of eukaryotic-specific polyadenylated mRNA directly extracted from environmental samples. In this chapter, we describe two alternative protocols for the extraction of high-quality RNA from soil samples. Total soil RNA or mRNA can be converted to cDNA for direct high-throughput sequencing. Polyadenylated mRNA-derived full-length cDNAs can also be cloned in expression plasmid vectors to constitute soil cDNA libraries, which can be subsequently screened for functional gene categories. Alternatively, the diversity of specific gene families can also be explored following cDNA sequence capture using exploratory oligonucleotide probes.

Methylotrophs in natural habitats: current insights through metagenomics

The focus of this review is on the recent data from the omics approaches, measuring the presence of methylotrophs in natural environments. Both Bacteria and Archaea are considered. The data are discussed in the context of the current knowledge on the biochemistry of methylotrophy and the physiology of cultivated methylotrophs. One major issue discussed is the recent metagenomic data pointing toward the activity of "aerobic" methanotrophs, such as Methylobacter, in microoxic or hypoxic conditions. A related issue of the metabolic distinction between aerobic and "anaerobic" methylotrophy is addressed in the light of the genomic and metagenomic data for respective organisms. The role of communities, as opposed to single-organism activities in environmental cycling of single-carbon compounds, such as methane, is also discussed. In addition, the emerging issue of the role of non-traditional methylotrophs in global metabolism of single-carbon compounds and the role of methylotrophy pathways in non-methylotrophs is briefly mentioned.

Compositional profile of α / β-hydrolase fold proteins in mangrove soil metagenomes: prevalence of epoxide hydrolases and haloalkane dehalogenases in oil-contaminated sites

The occurrence of genes encoding biotechnologically relevant α/β-hydrolases in mangrove soil microbial communities was assessed using data obtained by whole-metagenome sequencing of four mangroves areas, denoted BrMgv01 to BrMgv04, in São Paulo, Brazil. The sequences (215 Mb in total) were filtered based on local amino acid alignments against the Lipase Engineering Database. In total, 5923 unassembled sequences were affiliated with 30 different α/β-hydrolase fold superfamilies. The most abundant predicted proteins encompassed cytosolic hydrolases (abH08; ∼ 23%), microsomal hydrolases (abH09; ∼ 12%) and Moraxella lipase-like proteins (abH04 and abH01; < 5%). Detailed analysis of the genes predicted to encode proteins of the abH08 superfamily revealed a high proportion related to epoxide hydrolases and haloalkane dehalogenases in polluted mangroves BrMgv01-02-03. This suggested selection and putative involvement in local degradation/detoxification of the pollutants. Seven sequences that were annotated as genes for putative epoxide hydrolases and five for putative haloalkane dehalogenases were found in a fosmid library generated from BrMgv02 DNA. The latter enzymes were predicted to belong to Actinobacteria, Deinococcus-Thermus, Planctomycetes and Proteobacteria. Our integrated approach thus identified 12 genes (complete and/or partial) that may encode hitherto undescribed enzymes. The low amino acid identity (< 60%) with already-described genes opens perspectives for both production in an expression host and genetic screening of metagenomes.

Mining a database of single amplified genomes from Red Sea brine pool extremophiles-improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.

Development of quantitative PCR and metagenomics-based approaches for strain quantification of a defined mixed-strain starter culture

Although the strain composition of mixed cultures may hugely affect production of various fermented foods, such as e.g. cheese, tools for investigating it have so far been limited. In this study, two new approaches for quantification of seven Lactococcus lactis subsp. cremoris strains (S1-S7) in a defined mixed-strain starter culture were developed and verified. By mapping NGS reads from 47 sequenced L. lactis strains to de novo assembly contigs of the seven strains, two strain-specific sequence regions (SEQ1 and SEQ2) were identified for each strain for qPCR primer design (A1 and A2). The qPCR assays amplified their strain-specific sequence region target efficiently. Additionally, high reproducibility was obtained in a validation sample containing equal amounts of the seven strains, and assay-to-assay coefficients of variance (CVs) for six (i.e. S1, S2, S4-S7) of the seven strains correlated to the inter-plate CVs. Hence, at least for six strains, the qPCR assay design approach was successful. The metagenomics-based approach quantified the seven strains based on average coverage of SEQ1 and SEQ2 by mapping sequencing reads from the validation sample to the strain-specific sequence regions. Average coverages of the SEQ1 and SEQ2 in the metagenomics data showed CVs of ≤17.3% for six strains (i.e. S1-S4, S6, S7). Thus, the metagenomics-based quantification approach was considered successful for six strains, regardless of the strain-specific sequence region used. When comparing qPCR- and metagenomics-based quantifications of the validation sample, the identified strain-specific sequence regions were considered suitable and applicable for quantification at a strain level of defined mixed-strain starter cultures.

A linear concatenation strategy to construct 5'-enriched amplified cDNA libraries using multiple displacement amplification

In various experimental systems, limiting available amounts of RNA may prevent a researcher from performing large-scale analyses of gene transcripts. One way to circumvent this is to 'pre-amplify' the starting RNA/cDNA, so that sufficient amounts are available for any downstream analysis. In the present study, we report the development of a novel protocol for constructing amplified cDNA libraries using the Phi29 DNA polymerase based multiple displacement amplification (MDA) system. Using as little as 200 ng of total RNA, we developed a linear concatenation strategy to make the single-stranded cDNA template amenable for MDA. The concatenation, made possible by the template switching property of the reverse transcriptase enzyme, resulted in the amplified cDNA library with intact 5' ends. MDA generated micrograms of template, allowing large-scale polymerase chain reaction analyses or other large-scale downstream applications. As the amplified cDNA library contains intact 5' ends, it is also compatible with 5' RACE analyses of specific gene transcripts. Empirical validation of this protocol is demonstrated on a highly characterized (tomato) and an uncharacterized (corn gromwell) experimental system.

mBLAST: Keeping up with the sequencing explosion for (meta)genome analysis

Recent advances in next-generation sequencing technologies require alignment algorithms and software that can keep pace with the heightened data production. Standard algorithms, especially protein similarity searches, represent significant bottlenecks in analysis pipelines. For metagenomic approaches in particular, it is now often necessary to search hundreds of millions of sequence reads against large databases. Here we describe mBLAST, an accelerated search algorithm for translated and/or protein alignments to large datasets based on the Basic Local Alignment Search Tool (BLAST) and retaining the high sensitivity of BLAST. The mBLAST algorithms achieve substantial speed up over the National Center for Biotechnology Information (NCBI) programs BLASTX, TBLASTX and BLASTP for large datasets, allowing analysis within reasonable timeframes on standard computer architectures. In this article, the impact of mBLAST is demonstrated with sequences originating from the microbiota of healthy humans from the Human Microbiome Project. mBLAST is designed as a plug-in replacement for BLAST for any study that involves short-read sequences and includes high-throughput analysis. The mBLAST software is freely available to academic users at www.multicorewareinc.com.

Proteogenomic analysis of a thermophilic bacterial consortium adapted to deconstruct switchgrass

Thermophilic bacteria are a potential source of enzymes for the deconstruction of lignocellulosic biomass. However, the complement of proteins used to deconstruct biomass and the specific roles of different microbial groups in thermophilic biomass deconstruction are not well-explored. Here we report on the metagenomic and proteogenomic analyses of a compost-derived bacterial consortium adapted to switchgrass at elevated temperature with high levels of glycoside hydrolase activities. Near-complete genomes were reconstructed for the most abundant populations, which included composite genomes for populations closely related to sequenced strains of Thermus thermophilus and Rhodothermus marinus, and for novel populations that are related to thermophilic Paenibacilli and an uncultivated subdivision of the little-studied Gemmatimonadetes phylum. Partial genomes were also reconstructed for a number of lower abundance thermophilic Chloroflexi populations. Identification of genes for lignocellulose processing and metabolic reconstructions suggested Rhodothermus, Paenibacillus and Gemmatimonadetes as key groups for deconstructing biomass, and Thermus as a group that may primarily metabolize low molecular weight compounds. Mass spectrometry-based proteomic analysis of the consortium was used to identify >3000 proteins in fractionated samples from the cultures, and confirmed the importance of Paenibacillus and Gemmatimonadetes to biomass deconstruction. These studies also indicate that there are unexplored proteins with important roles in bacterial lignocellulose deconstruction.

Isolation and characterization of the grain mold fungi Cochliobolus and Alternaria spp. from sorghum using semiselective media and DNA sequence analyses

Mold diseases, caused by fungal complexes including Alternaria, Cochliobolus, and Fusarium species, limit sorghum grain production. Media were tested by plating Fusarium thapsinum, Alternaria sp., and Curvularia lunata, individually and competitively. Dichloran chloramphenicol rose bengal (DRBC) and modified V8 juice (ModV8) agars, found to be useful, were compared with commonly used agar media, dichloran chloramphenicol peptone (DCPA) and pentachloronitrobenzene (PCNB). Radial growth, starting with mycelia or single-conidia and hyphal tips, demonstrated an effect of media. For isolation of grain fungi, DRBC and ModV8 were similar or superior to DCPA and PCNB. When seedlings were inoculated with conidia of C. lunata, Alternaria sp., F. thapsinum, or mixtures, the percentage of root infection ranged from 28% to 77%. For mixed inoculations, shoot weights, lesion lengths, and percentage of root infections were similar to F. thapsinum inoculations; most colonies recovered from roots were F. thapsinum. For Alternaria grain isolates, 5 morphological types, including Alternaria alternata, were distinguished by colony morphologies and conidial dimensions. Sequence analysis using a portion of the endo-polygalacturonase gene was able to further distinguish isolates. Cochliobolus isolates were identified morphologically as C. lunata, Curvularia sorghina, and Bipolaris sorghicola. Multiple molecular genotypes were apparent from rRNA internal transcribed spacer region sequences from Cochliobolus grain isolates.

Critical role of bioinformatics in translating huge amounts of next-generation sequencing data into personalized medicine

Realizing personalized medicine requires integrating diverse data types with bioinformatics. The most vital data are genomic information for individuals that are from advanced next-generation sequencing (NGS) technologies at present. The technologies continue to advance in terms of both decreasing cost and sequencing speed with concomitant increase in the amount and complexity of the data. The prodigious data together with the requisite computational pipelines for data analysis and interpretation are stressors to IT infrastructure and the scientists conducting the work alike. Bioinformatics is increasingly becoming the rate-limiting step with numerous challenges to be overcome for translating NGS data for personalized medicine. We review some key bioinformatics tasks, issues, and challenges in contexts of IT requirements, data quality, analysis tools and pipelines, and validation of biomarkers.

Complete genome sequences of six strains of the genus Methylobacterium

The complete and assembled genome sequences were determined for six strains of the alphaproteobacterial genus Methylobacterium, chosen for their key adaptations to different plant-associated niches and environmental constraints.

Glycoside hydrolases from a targeted compost metagenome, activity-screening and functional characterization

Background

Metagenomics approaches provide access to environmental genetic diversity for biotechnology applications, enabling the discovery of new enzymes and pathways for numerous catalytic processes. Discovery of new glycoside hydrolases with improved biocatalytic properties for the efficient conversion of lignocellulosic material to biofuels is a critical challenge in the development of economically viable routes from biomass to fuels and chemicals.

Results

Twenty-two putative ORFs (open reading frames) were identified from a switchgrass-adapted compost community based on sequence homology to related gene families. These ORFs were expressed in E. coli and assayed for predicted activities. Seven of the ORFs were demonstrated to encode active enzymes, encompassing five classes of hemicellulases. Four enzymes were over expressed in vivo, purified to homogeneity and subjected to detailed biochemical characterization. Their pH optima ranged between 5.5 - 7.5 and they exhibit moderate thermostability up to ~60-70°C.

Conclusions

Seven active enzymes were identified from this set of ORFs comprising five different hemicellulose activities. These enzymes have been shown to have useful properties, such as moderate thermal stability and broad pH optima, and may serve as the starting points for future protein engineering towards the goal of developing efficient enzyme cocktails for biomass degradation under diverse process conditions.

Metatranscriptomic analysis of small RNAs present in soybean deep sequencing libraries

A large number of small RNAs unrelated to the soybean genome were identified after deep sequencing of soybean small RNA libraries. A metatranscriptomic analysis was carried out to identify the origin of these sequences. Comparative analyses of small interference RNAs (siRNAs) present in samples collected in open areas corresponding to soybean field plantations and samples from soybean cultivated in greenhouses under a controlled environment were made. Different pathogenic, symbiotic and free-living organisms were identified from samples of both growth systems. They included viruses, bacteria and different groups of fungi. This approach can be useful not only to identify potentially unknown pathogens and pests, but also to understand the relations that soybean plants establish with microorganisms that may affect, directly or indirectly, plant health and crop production.

Tavaxy: integrating Taverna and Galaxy workflows with cloud computing support

BACKGROUND

Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts.

RESULTS

In this paper, we present Tavaxy, a stand-alone system for creating and executing workflows based on using an extensible set of re-usable workflow patterns. Tavaxy offers a set of new features that simplify and enhance the development of sequence analysis applications: It allows the integration of existing Taverna and Galaxy workflows in a single environment, and supports the use of cloud computing capabilities. The integration of existing Taverna and Galaxy workflows is supported seamlessly at both run-time and design-time levels, based on the concepts of hierarchical workflows and workflow patterns. The use of cloud computing in Tavaxy is flexible, where the users can either instantiate the whole system on the cloud, or delegate the execution of certain sub-workflows to the cloud infrastructure.

CONCLUSIONS

Tavaxy reduces the workflow development cycle by introducing the use of workflow patterns to simplify workflow creation. It enables the re-use and integration of existing (sub-) workflows from Taverna and Galaxy, and allows the creation of hybrid workflows. Its additional features exploit recent advances in high performance cloud computing to cope with the increasing data size and complexity of analysis.The system can be accessed either through a cloud-enabled web-interface or downloaded and installed to run within the user's local environment. All resources related to Tavaxy are available at http://www.tavaxy.org.

Bioactive compounds synthesized by non-ribosomal peptide synthetases and type-I polyketide synthases discovered through genome-mining and metagenomics

Non-ribosomal peptide synthetases (NRPS) and type-I polyketide synthases (PKS-I) are multimodular enzymes involved in biosynthesis of oligopeptide and polyketide secondary metabolites produced by microorganisms such as bacteria and fungi. New findings regarding the mechanisms underlying NRPS and PKS-I evolution illustrate how microorganisms expand their metabolic potential. During the last decade rapid development of bioinformatics tools as well as improved sequencing and annotation of microbial genomes led to discovery of novel bioactive compounds synthesized by NRPS and PKS-I through genome-mining. Taking advantage of these technological developments metagenomics is a fast growing research field which directly studies microbial genomes or specific gene groups and their products. Discovery of novel bioactive compounds synthesized by NRPS and PKS-I will certainly be accelerated through metagenomics, allowing the exploitation of so far untapped microbial resources in biotechnology and medicine.

Monitoring microbial diversity of bioreactors using metagenomic approaches

With the rapid development of molecular techniques, particularly 'omics' technologies, the field of microbial ecology is growing rapidly. The applications of next generation sequencing have allowed researchers to produce massive amounts of genetic data on individual microbes, providing information about microbial communities and their interactions through in situ and in vitro measurements. The ability to identify novel microbes, functions, and enzymes, along with developing an understanding of microbial interactions and functions, is necessary for efficient production of useful and high value products in bioreactors. The ability to optimize bioreactors fully and understand microbial interactions and functions within these systems will establish highly efficient industrial processes for the production of bioproducts. This chapter will provide an overview of bioreactors and metagenomic technologies to help the reader understand microbial communities, interactions, and functions in bioreactors.

A novel fungal family of oligopeptide transporters identified by functional metatranscriptomics of soil eukaryotes

Functional environmental genomics has the potential to identify novel biological functions that the systematic sequencing of microbial genomes or environmental DNA may fail to uncover. We targeted the functions expressed by soil eukaryotes using a metatranscriptomic approach based on the use of soil-extracted polyadenylated messenger RNA to construct environmental complementary DNA expression libraries. Functional complementation of a yeast mutant defective in di/tripeptide uptake identified a novel family of oligopeptide transporters expressed by fungi. This family has a patchy distribution in the Basidiomycota and Ascomycota and is present in the genome of a Saccharomyces cerevisiae wine strain. High throughput phenotyping of yeast mutants expressing two environmental transporters showed that they both displayed broad substrate specificity and could transport more than 60-80 dipeptides. When expressed in Xenopus oocytes one environmental transporter induced currents upon dipeptide addition, suggesting proton-coupled co-transport of dipeptides. This transporter was also able to transport specifically cysteine. Deletion of the two copies of the corresponding gene family members in the genome of the wine yeast strain severely reduced the number of dipeptides that it could assimilate. These results demonstrate that these genes are functional and can be used by fungi to efficiently scavenge the numerous, low concentration, oligopeptides continuously generated in soils by proteolysis.

Molecular basis of human body odour formation: insights deduced from corynebacterial genome sequences

During the past few decades, there has been an increased interest in the essential role of commensal skin bacteria in human body odour formation. It is now generally accepted that skin bacteria cause body odour by biotransformation of sweat components secreted in the human axillae. Especially, aerobic corynebacteria have been shown to contribute strongly to axillary malodour, whereas other human skin residents seem to have little influence. Analysis of odoriferous sweat components has shown that the major odour-causing substances in human sweat include steroid derivatives, short volatile branched-chain fatty acids and sulphanylalkanols. In this mini-review, we describe the molecular basis of the four most extensively studied routes of human body odour formation, while focusing on the underlying enzymatic processes. Considering the previously reported role of β-oxidation in odour formation, we analysed the genetic repertoire of eight Corynebacterium species concerning fatty acid metabolism. We particularly focused on the metabolic abilities of the lipophilic axillary isolate Corynebacterium jeikeium K411.

Relevance in pathogenesis research

Research on pathogenesis of bacterial diseases involves exploration of the intricate and complex interactions among pathogen, host, and environment. Host-parasite-environment interactions that were relatively simple were the first to be understood. They include intoxications in which ingestion of a powerful bacterial toxin was sufficient to cause disease. In more complex cases bacteria occupy a variety of niches in the host and attack at an opportune time. Some bacterial pathogens have a brief encounter with the host; others are long-term guests. This variety of relationships involves a wide range of strategies for survival and transmission of bacterial pathogens. Molecular genetics, genomics and proteomics have facilitated understanding of the pathogens and hosts. Massive information often results from such studies and determining the relevance of the data is frequently a challenge. In vitro studies often attempt to simulate one or two critical aspects of the environment, such as temperature, pH, and iron concentration, that may provide clues as to what goes on in the host. These studies sometimes identify critical bacterial virulence factors but regulation of bacterial virulence and host response is complex and often not well understood. Pathogenesis is a process of continuous change in which timing and degree of gene expression are critical and are highly regulated by the environment. It is impossible to get the full picture without the use of natural or experimental infections, although experimental infections involve ethical and economic considerations which may act as a deterrent.

The impact of next-generation sequencing on genomics

This article reviews basic concepts, general applications, and the potential impact of next-generation sequencing (NGS) technologies on genomics, with particular reference to currently available and possible future platforms and bioinformatics. NGS technologies have demonstrated the capacity to sequence DNA at unprecedented speed, thereby enabling previously unimaginable scientific achievements and novel biological applications. But, the massive data produced by NGS also presents a significant challenge for data storage, analyses, and management solutions. Advanced bioinformatic tools are essential for the successful application of NGS technology. As evidenced throughout this review, NGS technologies will have a striking impact on genomic research and the entire biological field. With its ability to tackle the unsolved challenges unconquered by previous genomic technologies, NGS is likely to unravel the complexity of the human genome in terms of genetic variations, some of which may be confined to susceptible loci for some common human conditions. The impact of NGS technologies on genomics will be far reaching and likely change the field for years to come.

Metagenomic analyses: past and future trends

Metagenomics has revolutionized microbiology by paving the way for a cultivation-independent assessment and exploitation of microbial communities present in complex ecosystems. Metagenomics comprising construction and screening of metagenomic DNA libraries has proven to be a powerful tool to isolate new enzymes and drugs of industrial importance. So far, the majority of the metagenomically exploited habitats comprised temperate environments, such as soil and marine environments. Recently, metagenomes of extreme environments have also been used as sources of novel biocatalysts. The employment of next-generation sequencing techniques for metagenomics resulted in the generation of large sequence data sets derived from various environments, such as soil, the human body, and ocean water. Analyses of these data sets opened a window into the enormous taxonomic and functional diversity of environmental microbial communities. To assess the functional dynamics of microbial communities, metatranscriptomics and metaproteomics have been developed. The combination of DNA-based, mRNA-based, and protein-based analyses of microbial communities present in different environments is a way to elucidate the compositions, functions, and interactions of microbial communities and to link these to environmental processes.

Metagenomic analyses: past and future trends

Metagenomics has revolutionized microbiology by paving the way for a cultivation-independent assessment and exploitation of microbial communities present in complex ecosystems. Metagenomics comprising construction and screening of metagenomic DNA libraries has proven to be a powerful tool to isolate new enzymes and drugs of industrial importance. So far, the majority of the metagenomically exploited habitats comprised temperate environments, such as soil and marine environments. Recently, metagenomes of extreme environments have also been used as sources of novel biocatalysts. The employment of next-generation sequencing techniques for metagenomics resulted in the generation of large sequence data sets derived from various environments, such as soil, the human body, and ocean water. Analyses of these data sets opened a window into the enormous taxonomic and functional diversity of environmental microbial communities. To assess the functional dynamics of microbial communities, metatranscriptomics and metaproteomics have been developed. The combination of DNA-based, mRNA-based, and protein-based analyses of microbial communities present in different environments is a way to elucidate the compositions, functions, and interactions of microbial communities and to link these to environmental processes.

Optimization of whole-transcriptome amplification from low cell density deep-sea microbial samples for metatranscriptomic analysis

Limitation in sample quality and quantity is one of the big obstacles for applying metatranscriptomic technologies to explore gene expression and functionality of microbial communities in natural environments. In this study, several amplification methods were evaluated for whole-transcriptome amplification of deep-sea microbial samples, which are of low cell density and high impurity. The best amplification method was identified and incorporated into a complete protocol to isolate and amplify deep-sea microbial samples. In the protocol, total RNA was first isolated by a modified method combining Trizol (Invitrogen, CA) and RNeasy (QIAGEN, CA) method, amplified with a WT-Ovation™ Pico RNA Amplification System (NuGEN, CA), and then converted to double-strand DNA from single-strand cDNA with a WT-Ovation™ Exon Module (NuGEN, CA). The products from the whole-transcriptome amplification of deep-sea microbial samples were assessed first through random clone library sequencing. The BLAST search results showed that marine-based sequences are dominant in the libraries, consistent with the ecological source of the samples. The products were then used for next-generation Roche GS FLX Titanium sequencing to obtain metatranscriptome data. Preliminary analysis of the metatranscriptomic data showed good sequencing quality. Although the protocol was designed and demonstrated to be effective for deep-sea microbial samples, it should be applicable to similar samples from other extreme environments in exploring community structure and functionality of microbial communities.