DNA technologies: what's next applied to microbiology research?

Comparative assessment of next-generation sequencing, denaturing gradient gel electrophoresis, clonal restriction fragment length polymorphism and cloning-sequencing as methods for characterizing commercial microbial consortia

Characterization of commercial microbial consortia products for human and environmental health risk assessment is a major challenge for regulatory agencies. As a means to develop an approach to assess the potential environmental risk of these products, research was conducted to compare four genomics methods for characterizing bacterial communities; (i) Denaturing Gradient Gel Electrophoresis (DGGE), (ii) Clonal-Restriction Fragment Length Polymorphism (C/RFLP), (iii) partial 16S rDNA amplification, cloning followed by Sanger sequencing (PRACS) and (iv) Next-Generation Sequencing (NGS) based on Ion Torrent technology. A commercially available microbial consortium, marketed as a remediation agent for degrading petroleum hydrocarbon contamination in soil and water, was assessed. The bacterial composition of the commercial microbial product was characterized using the above four methods. PCR amplification of 16S rDNA was performed targeting the variable region V6 for DGGE, C/RFLP and PRACS and V5 for Ion Torrent sequencing. Ion Torrent technology was shown to be a promising tool for initial screening by detecting the majority of bacteria in the consortium that were also detected by DGGE, C/RFLP and PRACS. Additionally, Ion Torrent sequencing detected some of the bacteria that were claimed to be in the product, while three other methods failed to detect these specific bacteria. However, the relative proportions of the microbial composition detected by Ion Torrent were found to be different from DGGE, C/RFLP and PRACS, which gave comparable results across these three methods. The discrepancy of the Ion Torrent results may be due to the short read length generated by this technique and the targeting of different variable regions on the 16S rRNA gene used in this study. Arcobacter spp. a potential pathogenic bacteria was detected in the product by all methods, which was further confirmed using genus and species-specific PCR, RFLP and DNA-based sequence analyses. However, the viability of Arcobacter spp. was not confirmed. This study suggests that a combination of two or more methods may be required to ascertain the microbial constituents of a commercial microbial consortium reliably and for the presence of potentially human pathogenic contaminants.

Microfluidics and Raman microscopy: current applications and future challenges

Raman microscopy systems are becoming increasingly widespread and accessible for characterising chemical species. Microfluidic systems are also progressively finding their way into real world applications. Therefore, it is anticipated that the integration of Raman systems with microfluidics will become increasingly attractive and practical. This review aims to provide an overview of Raman microscopy-microfluidics integrated systems for researchers who are actively interested in utilising these tools. The fundamental principles and application strengths of Raman microscopy are discussed in the context of microfluidics. Various configurations of microfluidics that incorporate Raman microscopy methods are presented, with applications highlighted. Data analysis methods are discussed, with a focus on assisting the interpretation of Raman-microfluidics data from complex samples. Finally, possible future directions of Raman-microfluidic systems are presented.

Megraft: a software package to graft ribosomal small subunit (16S/18S) fragments onto full-length sequences for accurate species richness and sequencing depth analysis in pyrosequencing-length metagenomes and similar environmental datasets

Metagenomic libraries represent subsamples of the total DNA found at a study site and offer unprecedented opportunities to study ecological and functional aspects of microbial communities. To examine the depth of a community sequencing effort, rarefaction analysis of the ribosomal small subunit (SSU/16S/18S) gene in the metagenome is usually performed. The fragmentary, non-overlapping nature of SSU sequences in metagenomic libraries poses a problem for this analysis, however. We introduce a software package - Megraft - that grafts SSU fragments onto full-length SSU sequences, accounting for observed and unobserved variability, for accurate assessment of species richness and sequencing depth in metagenomics endeavors.

Bacterial genomes: habitat specificity and uncharted organisms

The capability and speed in generating genomic data have increased profoundly since the release of the draft human genome in 2000. Additionally, sequencing costs have continued to plummet as the next generation of highly efficient sequencing technologies (next-generation sequencing) became available and commercial facilities promote market competition. However, new challenges have emerged as researchers attempt to efficiently process the massive amounts of sequence data being generated. First, the described genome sequences are unequally distributed among the branches of bacterial life and, second, bacterial pan-genomes are often not considered when setting aims for sequencing projects. Here, we propose that scientists should be concerned with attaining an improved equal representation of most of the bacterial tree of life organisms, at the genomic level. Moreover, they should take into account the natural variation that is often observed within bacterial species and the role of the often changing surrounding environment and natural selection pressures, which is central to bacterial speciation and genome evolution. Not only will such efforts contribute to our overall understanding of the microbial diversity extant in ecosystems as well as the structuring of the extant genomes, but they will also facilitate the development of better methods for (meta)genome annotation.

Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets

The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. In addition to being present in the nucleus of eukaryotes and the core genome of prokaryotes, the gene is also found in the mitochondria of eukaryotes and in the chloroplasts of photosynthetic eukaryotes. These three sets of genes are conceptually paralogous and should in most situations not be aligned and analyzed jointly. To identify the origin of SSU sequences in complex sequence datasets has hitherto been a time-consuming and largely manual undertaking. However, the present study introduces Metaxa ( http://microbiology.se/software/metaxa/ ), an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin. Using data from reference databases and from full-length organelle and organism genomes, we show that Metaxa detects and scores SSU sequences for origin with very low proportions of false positives and negatives. We believe that this tool will be useful in microbial and evolutionary ecology as well as in metagenomics.

Viable but non-culturable (VBNC) bacteria: Gene expression in planktonic and biofilm cells

Viable but non-culturable (VBNC) bacteria are common in nutrient poor and/or stressed environments as planktonic cells and biofilms. This article discusses approaches to researching VBNC bacteria to obtain knowledge that is lacking on their gene expression while in the VBNC state, and when they enter into and then recover from this state, when provided with the necessary nutrients and environmental conditions to support growth and cell division. Two-dimensional gel electrophoresis of proteins, global gene expression, reverse-transcription polymerase chain reaction (PCR) analysis and sequencing by synthesis coupled with data on cell numbers, viability and species present are central to understanding the VBNC state.