Interesting paper on strategy to use PCR to simultaneously characterize eukaryotic, bacterial and archaeal microbes

Interesting new paper in PLOS One: PLOS ONE: Simultaneous Amplicon Sequencing to Explore Co-Occurrence Patterns of Bacterial, Archaeal and Eukaryotic Microorganisms in Rumen Microbial Communities

Full citation:  Kittelmann S, Seedorf H, Walters WA, Clemente JC, Knight R, et al. (2013) Simultaneous Amplicon Sequencing to Explore Co-Occurrence Patterns of Bacterial, Archaeal and Eukaryotic Microorganisms in Rumen Microbial Communities. PLoS ONE 8(2): e47879. doi:10.1371/journal.pone.0047879

Basically, the paper describes the development and use of a PCR strategy to simultaneously characterize eukaryotic, bacterial and archaeal microbes from samples.

Primers used are summarized in Table 2

The strategy they employ attempt to correct for differences in amplification differences between the different amplicons which should therefore allow better normalization of relative abundance estimates.  See results in Figure 2.

Definitely worth a look.

Nice review on HiSeq/MiSeq rRNA sequencing from Caporaso et al #microbes

Quick post -- nice review worth checking out: The ISME Journal - Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms

from Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R.

A key part of the paper, with highlighting from me:-

These observations, in agreement with studies that have addressed this question directly (Kuczynski et al., 2010), suggest that increasing the sequencing depth is not likely to provide additional insight into questions of beta diversity, and we therefore argue that (for questions of beta diversity in particular) the decreased cost of sequencing should be applied to study microbial systems using many more samples, for example, in dense temporal or spatial analyses, rather than with many more sequences per sample.  Of course, if the objective is to identify taxa that are very rare in communities, deeper sequencing will be advantageous. Additionally we note that while as few as 10 sequences per sample may be useful for differentiating very different environment types (for example, soil and feces), as environments become more similar (for example, two soil samples of different pH) more sequences will be required to differentiate them.

PCR amplification and pyrosequencing of rpoB as complement to rRNA

Figure 1. Number of OTUs as
 a function of fractional sequence difference
 (OTU cut-off) for the 16S rRNA marker
 gene (A) and the rpoB marker gene (B).

Interesting new paper in PLoS One: PLoS ONE: A Comparison of rpoB and 16S rRNA as Markers in Pyrosequencing Studies of Bacterial Diversity

In the paper they test and use PCR amplification and pyrosequencing of the rpoB gene for studies of the diversity of bacteria. Due to the lower level of conservation of rpoB than rRNA genes at the DNA level they focused on proteobacteria. It seems that with a little perseverance once can get PCR for protein coding genes to work reasonably well for even reasonably broad taxonomic groups (not totally new here but I am not aware of too many papers doing this with pyrosequencing). Anyway, the paper is worth a look.


Citation:
 Vos M, Quince C, Pijl AS, de Hollander M, Kowalchuk GA (2012) A Comparison of rpoB and 16S rRNA as Markers in Pyrosequencing Studies of Bacterial Diversity. PLoS ONE 7(2): e30600. doi:10.1371/journal.pone.0030600 Vos, M., Quince, C., Pijl, A., de Hollander, M., & Kowalchuk, G. (2012). A Comparison of rpoB and 16S rRNA as Markers in Pyrosequencing Studies of Bacterial Diversity PLoS ONE, 7 (2) DOI: 10.1371/journal.pone.0030600

Journal club today on bacteria in toilets - posting some notes here

I am heading a journal club discussion today of the following paper: PLoS ONE: Microbial Biogeography of Public Restroom Surfaces

I am going to use this page/post to put up some notes for the discussion.  Fortunately I have a good guide in this - Rob Dunn wrote a nice commentary/review for Scientific American blogs: Public bathrooms house thousands of kinds of bacteria

Stay tuned/come back to this page as I will be posting some more notes. Any suggestions for other things to look at/discuss would be welcome.

Notes (I note - I am copying much of the text from the paper not rewriting it.)

My first PLoS One paper .... yay: automated phylogenetic tree based rRNA analysis

Well, I have truly entered the modern world. My first PLoS One paper has just come out. It is entitled "An Automated Phylogenetic Tree-Based Small Subunit rRNA Taxonomy and Alignment Pipeline (STAP)" and well, it describes automated software for analyzing rRNA sequences that are generated as part of microbial diversity studies. The main goal behind this was to keep up with the massive amounts of rRNA sequences we and others could generate in the lab and to develop a tool that would remove the need for "manual" work in analyzing rRNAs.

The work was done primarily by Dongying Wu, a Project Scientist in my lab with assistance from a Amber Hartman, who is a PhD student in my lab. Naomi Ward, who was on the faculty at TIGR and is now at Wyoming, and I helped guide the development and testing of the software.

We first developed this pipeline/software in conjunction with analyzing the rRNA sequences that were part of the Sargasso Sea metagenome and results from the word was in the Venter et al. Sargasso paper. We then used the pipeline and continued to refine it as part of a variety of studies including a paper by Kevin Penn et al on coral associated microbes. Kevin was working as a technician for me and Naomi and is now a PhD student at Scripps Institute of Oceanography. We also had some input from various scientists we were working with on rRNA analyses, especially Jen Hughes Martiny

We made a series of further refinements and worked with people like Saul Kravitz from the Venter Institute and the CAMERA metagenomics database to make sure that the software could be run outside of my lab. And then we finally got around to writing up a paper .... and now it is out.

You can download the software here. The basics of the software are summarized below: (see flow chart too).

• Stage 1: Domain Analysis


• Take a rRNA sequence
• blast it against a database of representative rRNAs from all lines of life
• use the blast results to help choose sequences to use to make a multiple sequence alignment
• infer a phylogenetic tree from the alignment
• assign the sequence to a domain of life (bacteria, archaea, eukaryotes)


• Stage 2: First pass alignment and tree within domain
• take the same rRNA sequence
• blast against a database of rRNAs from within the domain of interest
• use the blast results to help choose sequences for a multiple alignment
• infer a phylogenetic tree from the alignment
• assign the sequence to a taxonomic group


• Stage 3: Second pass alignment and tree within domain
• extract sequences from members of the putative taxonomic group (as well as some others to balance the diversity)
• make a multiple sequence alignment
• infer a phylogenetic tree

From the above path, we end up with an alignment, which is useful for things such as counting number of species in a sample as well as a tree which is useful for determining what types of organisms are in the sample.

I note - the key is that it is completely automated and can be run on a single machine or a cluster and produces comparable results to manual methods. In the long run we plan to connect this to other software and other labs develop to build a metagenomics and microbial diversity workflow that will help in the processing of massive amounts of sequence data for microbial diversity studies.

I should note this work was supported primarily by a National Science Foundation grant to me and Naomi Ward as part of their “Assembling the Tree of Life” Program (Grant No. 0228651). Some final work on the project was funded by the Gordon and Betty Moore Foundation through grant #1660 to Jonathan Eisen and the CAMERA grant to UCSD.

Wu, D., Hartman, A., Ward, N., & Eisen, J. (2008). An Automated Phylogenetic Tree-Based Small Subunit rRNA Taxonomy and Alignment Pipeline (STAP) PLoS ONE, 3 (7) DOI: 10.1371/journal.pone.0002566