Title: Spatially and Temporally Explicit Studies of the Human Microbiome
Sequencing is getting dramatically searching, as we all know. What we can do now is dramatically different than what we could do a decade ago.
We know, since the invention of the microscope, (van Leeuwenhoek in 1683), we know that the human body is covered in bacteria.
Why should you care about your microbes? They can have interesting effects, eg, determine whether tylenol is toxic to your liver. (PNAS). If you’re a fruit fly, it can determine your partner preferences (PNAS), steal genes from your food to help you digest it.
There are as many E. coli in your gut as there are people on earth. It’s not the dominant member in the cut, though – it’s just best at growing on a petri dish.
Any two people you pick have 99.9% the same genome, but E. coli genomes can differ up to 40%. Humans may not be unique like snow flakes, but our symbionts are!
Can start asking intelligent questions about our microbial selves.
How human are we? in terms of cells, we’re 10% of the cells in our body. only one percent of the DNA [if I got that right]
Most of the world is made of bacteria – animals and plants are a very small number of organisms. and 99% aren’t culturable.
How do we look at them, then? Get samples and extract DNA -> PCR amplify (usually SSU rRNA gene) -> sequence -> blast against genebank (but this is less and less useful. You now get a lot of hits on uncultured stuff. so skip this.) -> align and build trees to figure out what you can.
Problem: big trees are hard to understand and analyze.
Issue: need to interpret vast amounts of sequence/tree data. Interpretation isn’t trivial as trees become massive.
Experiment: microbial biogeography on the keyboard? (Are keys deserts for bacteria, different from fingertips?) Result: we have distinct cultures, each of us, but our keyboards mirror our fingertip bacteria. (PNAS) – it was on CSI: Miami, so you know it’s true.
Darwin’s “Origin” has the first phylogenitic tree. [I did not know that]
Calculating a community distance metric. If trees are identical, distance =0. If complete separation right from root, then distance = 1. [Very visually informative slides – discussing how we perceive the data in the metric.]
(Lozupone & Knight 2007, PNAS) [hope I got the name right – it’s jammed into the corner of a slide.] Experiment looking for related-ness among a large number of samples. They did see a significant divide between saline/non-saline.
Interesting: Extreme environments are not outliers. However, there are outliers: they’re in the vertibrate gut!
QIIME: integrating analysis of hundreds of samples using barcodes. Use 454 mostly, but also illumina. Use sequences to build phylogenetic trees.
[Joke about why we still call it “454”…. because that’s the temperature your money burns at when you do these experiments…. ]
[Joke section on sequencing technologies to watch out for… I can’t do it justice.]
but i digress…..
Different body habitats are very different from each other. (2009 Science) [I recall seeing this last year at AGBT, I think.] When on antibiotics, your communities change dramatically, and getting a picture of overall human microbiome variability.
You don’t need a lot of sequences per samples to see the patterns. same pattern in 10 seq/sample as 1500seq/sample.
Have done these studies over time – over 3 months , visualized in a live 3D graph. [worth seeing, actually, very cool.]
Picture of Rodrigo Salvadore Dali painting. (It’s a pretty picture, but doesn’t tell you the whole story)
Detailed biogography of the human face.
[Nifty visualizations for the visualization of distribution of bacteria on the face. Obviously can’t blog that.]
Where do the bacteria come from? (Which raises privacy issues.) Babies who come out vaginally all have vaginal communities, those that are born by c-section have a very different population.
Diversity of babies’ bacterial communities increases by day, and by the end of 3 years, they resemble their mother’s bacterial communities.
Do differences in the microbiome matter? Fat mouse experiment says yes. (Two examples – Leptin and TLR5) With TLR5 knockout mouse, the bacteria are different and seem to make the mouse hungrier – you can “rescue” the mouse by changing the bacteria. Same applies to Burmese pythons.
Fat vs thin are Bacteriodes vs Firmicules [missed which one is which, tho, and not sure about the spelling.]
Future directions: personalized medicine in developing nations. Pilot studies in “humanized mice” measuring input microbes, diet change and BMI. Can you develop test from gut microbes to predict effects of diet/obesity/etc?
Much of the work is in developing systems for measuring and recording environmental conditions, etc.
Earth Microbiome project coming…
Conclusion: we all have a microbiome, and anyone can do this type of work now that sequencing is so cheap – much of the cost of experiment is now in DNA extraction.
[A neat talk, summarizing a lot of published work. Unfortunately, I couldn’t read most of the citations. Talk was memorable for it’s good visualization tools and the excellent speaker.]