Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data.

Next-generation sequencing techniques, and PhyloChip, have made simultaneous phylogenetic analyses of hundreds of microbial communities possible. Insight into community structure has been limited by the inability to integrate and visualize such vast datasets. Fast UniFrac overcomes these issues, allowing integration of larger numbers of sequences and samples into a single analysis. Its new array-based implementation offers orders of magnitude improvements over the original version. New 3D visualization of principal coordinates analysis results, with the option to view multiple coordinate axes simultaneously, provides a powerful way to quickly identify patterns that relate vast numbers of microbial communities. We show the potential of Fast UniFrac using examples from three data types: Sanger-sequencing studies of diverse free-living and animal-associated bacterial assemblages and from the gut of obese humans as they diet, pyrosequencing data integrated from studies of the human hand and gut, and PhyloChip data from a study of citrus pathogens. We show that a Fast UniFrac analysis using a reference tree recaptures patterns that could not be detected without considering phylogenetic relationships and that Fast UniFrac, coupled with BLAST-based sequence assignment, can be used to quickly analyze pyrosequencing runs containing hundreds of thousands of sequences, showing patterns relating human and gut samples. Finally, we show that the application of Fast UniFrac to PhyloChip data could identify well-defined subcategories associated with infection. Together, these case studies point the way toward a broad range of applications and show some of the new features of Fast UniFrac

Community transcriptomics reveals unexpected high microbial diversity in acidophilic biofilm communities.

A fundamental question in microbial ecology relates to community structure, and how this varies across environment types. It is widely believed that some environments, such as those at very low pH, host simple communities based on the low number of taxa, possibly due to the extreme environmental conditions. However, most analyses of species richness have relied on methods that provide relatively low ribosomal RNA (rRNA) sampling depth. Here we used community transcriptomics to analyze the microbial diversity of natural acid mine drainage biofilms from the Richmond Mine at Iron Mountain, California. Our analyses target deep pools of rRNA gene transcripts recovered from both natural and laboratory-grown biofilms across varying developmental stages. In all, 91.8% of the ∼ 254 million Illumina reads mapped to rRNA genes represented in the SILVA database. Up to 159 different taxa, including Bacteria, Archaea and Eukaryotes, were identified. Diversity measures, ordination and hierarchical clustering separate environmental from laboratory-grown biofilms. In part, this is due to the much larger number of rare members in the environmental biofilms. Although Leptospirillum bacteria generally dominate biofilms, we detect a wide variety of other Nitrospira organisms present at very low abundance. Bacteria from the Chloroflexi phylum were also detected. The results indicate that the primary characteristic that has enabled prior extensive cultivation-independent 'omic' analyses is not simplicity but rather the high dominance by a few taxa. We conclude that a much larger variety of organisms than previously thought have adapted to this extreme environment, although only few are selected for at any one time

Continuous-flow sorting of microalgae cells based on lipid content by high frequency dielectrophoresis

This paper presents a continuous-flow cell screening device to isolate and separate microalgae cells (Chlamydomonas reinhardtii) based on lipid content using high frequency (50 MHz) dielectrophoresis. This device enables screening of microalgae due to the balance between lateral DEP forces relative to hydrodynamic forces. Positive DEP force along with amplitude-modulated electric field exerted on the cells flowing over the planar interdigitated electrodes, manipulated low-lipid cell trajectories in a zigzag pattern. Theoretical modelling confirmed cell trajectories during sorting. Separation quantification and sensitivity analysis were conducted with time-course experiments and collected samples were analysed by flow cytometry. Experimental testing with nitrogen starveddw15-1 (high-lipid, HL) and pgd1 mutant (low-lipid, LL) strains were carried out at different time periods, and clear separation of the two populations was achieved. Experimental results demonstrated that three populations were produced during nitrogen starvation: HL, LL and low-chlorophyll (LC) populations. Presence of the LC population can affect the binary separation performance. The continuous-flow micro-separator can separate 74% of the HL and 75% of the LL out of the starting sample using a 50 MHz, 30 voltages peak-to-peak AC electric field at Day 6 of the nitrogen starvation. The separation occurred between LL (low-lipid: 86.1% at Outlet # 1) and LC (88.8% at Outlet # 2) at Day 9 of the nitrogen starvation. This device can be used for onsite monitoring; therefore, it has the potential to reduce biofuel production cost

Bioinformatics and molecular biology for the quantification of closely related bacteria

10.1007/s00253-013-4943-5Applied Microbiology and Biotechnology97146489-6502AMBI