Esther Singer opened the day talking about “Metagenomics to Reveal Correlations between Switchgrass Ecotypes and their Microbial Communities”. She told a nice story about the ecotype-specificity of the rhizosphere and phyllosphere microbial communities. I was surprised that for some bacteria this was evident even at the phylum level… so big differences.
Daria Van Tyne “Changes in Antibiotic Use Drive Enterococcal Evolution During a Hospital Outbreak”. She started by asking us to step back from metagnomics and think about a single species. Another really nice study using whole genome sequencing to study an outbreak, but this time an outbreak from the 1980’s with strains kept in the freezer. big differences in pre and post outbreak strains. Outbreak strains lost CRISPR/Cas, gained antibiotic resistance, and had a much higher number of mobile genetic elements. When treatment changed during the outbreak, the resistance mutations shifted which is expected but nice to see demonstrated.
Kostas Konstantinidis “Toward Microbial Diagnosis Using Metagenomics: A Case of the Runs”. Talked about the impact of diarrhea disease on the endogenous human gut microbiome. They are trying to obtain strain-level resolution of pathogens (E. coli and Salmonella) from metagenomics.
Sadly I had to take a phone call and I missed the talk right after the break. The talk was by Stephen Nayfach and he was discussing MIDAS – metagenomic intra-species diversity analysis system. Sounded interesting from Twitter, see the Storify for more information.
Henry Schreiber “Regulation is Key – Understanding the Paradox of Genetic Diversity in Uropathogeneic E. coli“. More genome sequencing… this time showing that “model” UPEC is much less phylogeneticly diverse than clinical UPEC. There seems to be some big problems in simply defining a UPEC strain… not just in the clinic but even from genomes since (like all E. coli) there is so much variability between strains.
Katrine Whiteson “Microbial Fermentation Products as Indicators and Instigators in Cystic Fibrosis”. She talked about the use of island biogeography as a model for how communities at bodies sites interact. I didn’t realize that less than 1% of observable metabolites can be identified, still very much a growing field. Overall told a fascinating story of a metabolite, probably from an oral microbe, that potentially influenced behavior of another microbe in the lung.
Starting the evening talks was Shuiquan Tang, “Standardizing Metagenomics – Removing Bias from Sample Collection through Analysis”. He began by emphasizing how much variation there is between protocols, from sample collection to bioinformatics… resulting in different results from different groups, even on the same sample. Advertising the ZYMO Microbial Community Standard, which even before this talk I thought was a fabulous idea and this or something equivalent should be in every run. Also talked about sample storage buffer, biases in DNA extraction kits, PCR bias,
Tanja Woyke “Identification of Taxonomic Blind Spots Using Single Cell Approaches”. She started off by describing taxonomic blind spots, which are clades that are either very rare or not amplified by standard PCR techniques. We are clearly missing a lot of stuff out there. Did a really cool search of all public genomes and metagenomics and looked for 16S sequences being missed by the usual primers… classify what’s left. They have done single-cell genomes on bacteria that were PCR-negative, and then done assemblies and *still* not seen 16S sequences.
Adam Phillippy “How to Compare and Cluster Every Known Genome and Metagenome”. Started off talking about the MinION, then about MinHash which is a tool for comparing genomes at lightning speed. Use the MinHash algorithm inside an assembler called “Canu” which works for PacBio and MinION data (gets complete genomes!). Had some great thoughts on democratizing sequencing, data sharing, ending traditional bacterial taxonomy etc.
The last talk of the day was Lawrence Etweiller on “Transcription Start Sites at Single Base resolution in a Model Prokaryotes and the Gut Microbiome”. Started with a nice review on transcriptional control of gene expression. Described a method called “Cappable-seq” which identifies the transcription start site at base resolution. This allows them to enrich RNA data for primary transcripts.