AGBT Talk: Joseph Petrosino, Baylor College of Medicine

Title: Toward Improved Bacterial  and Viral Metagenomic Sequencing and AnalysisStrategies in Healthy and Diseased individuals.

[EDIT: I found this talk really hard to take notes on – many of the slides did not have easily extractable messages, despite being interesting.  Errors are likely in the content below.]

Will focus more on viruses, as Dr. Knight focused more on bacteria.

NIH Human Microbiome Project (HMP).  Genomes from 900 microbiome bacteria  – has grown to 3000.  Characterize microbiome from healthy people (baseline), doing transcriptome, viral an eukaryotic microbiome. 15 disease-oriented Demonstration Projects.

Sample sites are 15/18 locations on the body, depending on gender of subject.

[skipping poo joke….   right… carying on.]

Sample -> enrich bacteia, virueses fungi -> extract DNA, – > sequence (which ever strategy) -> community structure and other value info (pathways/etc).

Descrtiption of sample sites and collection techniques – you need to do a lot of standardization.  [I’m not going into details, and the speaker is covering it very briefly.]

Moving on to the bacterial communities dedrograms.  Samples cluster by location of colection, and very specific to environment. (tongue different from saliva, etc.)

Many new disease relationshp projects (long list…) includes astronaut microbiomes.

Viral Metagenomics: detect encasidated viruses in clinical samples to discover relationships to health and disease.  (Virus hunting.)

In healthy patients, you have small virus loads.

Upstream processing covered – much filtering done. [review of cDNA library construction]  Can require over 80 PCR cycles.

Do random primer designs sample viruses equally well?  How much depth is needed to capture viral diversity?  454 vs illumina?  (Huge Human contamination.)

Some slides comparing results, [couldn’t pull out take home message fast enough]. plateu out aroung 30-40% of reads of a lane. [GAII?  not sure.]

Sampling is difficult, you don’t know if you’re capturing the whole population, but what you see caps out at 30-40%.

Random primer construction- does it work? Compared 6 different strategies.  [No take home message that I heard.]

Does more sample = more viruses, maybe.  You don’t need huge amounts of sample.

Virus families captured by random primers: many of them.  [I’m not listing, but there’s a difference by which primers are used.]

Data section:

Viral familyies detected in 4 subjects.  Patterns starting to emerge. [I can’t see them, though] Both DNA and RNA viruses detected.  Hits need to be verified. Are these colonizing, or are they just “passing through”.

Phage: 48 phages in 1st pass query against database.  Phage population can give you info about the microbiome.

Virus protocol differentiates stool and nasal wash viruses.   [yes, you can tell the difference, qualitatively.]

Some Diseases:

  • Kawasaki disease
    • children’s disease, usually found in children of asian decent. Cause is unknown.
    • [unpublished data] – seems to be a few viruses associated – still needs to be validated.
  • Elephant Herpes virus
    • all 6 calves born at houston zoon in last 2 decates have died from EEHV.
    • At zoo, they named the baby elephant “Baylor” to up the ante.
    • Did the usual process to try to pull out virus
    • Able to assemble EEHV1
    • research still underway

Many other projects ongoing.  Upward trend for viral metagenomic strategies.

Many areas to improve still, including improved curration of viral db. Better measures for coloniztion/passing through viruses.

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