Field of Science

IHMC11 Friday first session

Paul Spicer: Indigenous communities and genomics:  lessons for the microbiome.  He's an anthropologist (?) reporting on what the feedback/pushback is from indigenous people.  Bottom line - they're not impressed.

Tribes think scientists are too obsessed with data, not with the needs of the people.  Researchers benefit but the subjects don't.  He recognizes that this isn't really true, but it's the impression we give.  Our apparent difference to human suffering ("we need to bank the DNA before the people vanish...")  ELSI is 'research on research' - of no value to the indigenous communities.  But we're not funded to benefit them, but to get the research done.  We certainly shouldn't claim to offer unreasonable benefits (destroys trust).

We need to develop the capacity for partnerships - build ability of communities to benefit.  Need to work with village schools, not just target PhD and post-doc programs to the communities.  They try to form partnerships with us, to get what they value, but these attempts fail.  We need to find ways to benefit them.

Makedonka Mitreva: The microbiome of healthy humans commonalities and variations.  HMP goals:  sequences of target genomes, unbiased 16S surveys, metagenomics.  She'll report on metagenome analysis.  100 individuals, 2 visits for most, 6 body sites.

Presence of matches to reference genomes (she says 'strains'):  Alignment with 80% identity to reference genomes.  Depending on site, 33-77% of reads find a match.  Complex clustering (based on 'DCPM') by site .  (I don't know what this is supposed to illuminate.  She must be assuming more expertise than I have, as she hasn't said what questions this is supposed to answer.)

Using alignments to reference genomes, the bacteria up your nose don't overlap much with those in your vagina.  Other sites show more overlap.  But how does this change if they instead measure diversity by 16S sequences?  Not too much - there's a good overlap for most sites.  Not so good for dorsal surface of the tongue.

What about genetic variation with an identified taxon ('strain')?  e.g. Streptococcus oralis.  See lots of SVP variation, different alleles in different oral sub-sites.  She doesn't interpret but this must mean that different strains of S. oralis are present in different parts of the mouth.

Metabolic profiling?  Just analysis of the diversity and correlations of the profiles.  Correlations between visits are not very strong.  Now she mentions biology!  What can we learn?  'Differential KOs'?  (Google: Kegg Orthology groups).  Two-component system pathways in Staph.

Larry Forney:  (terrific talk!) The temporal dynamics of the vaginal microbiota in reproductive age women.

Common 'wisdom' about the vagina: Dominated by Lactobacillus, nedcessary for health, restricts growth of baddies by low pH (~4.5), high lactate, other factors.  Transitions through lifespan:  colonized at birth but not studied in childhood.  Puberty:  estrogen production, colonization aand succession.  Menopause:  estrogen down, less glycogen, less lactic acid.

Bacterial vaginosis = 'disturbed microbiota' (?).  Clinical criteria or Gram stain for lactobacillus.  Some women at much higher risk than other.  IS his due to differences in vaginal comminities?

Questions:  what are the communities?  Are they dynamic? What factors determine the community structure?  Are these communities and factors associated with disease?

Study:  410 healthy women, 4 races, 16S 454 sequencing.  In 95% of women, find one of 5 different community types, 4 dominated by different single Lactobacillus species, and one with heterogeneous lactic acid bacteria.  (5% of women don't fit any of these.) But in individuals, the communities were all different, approaching more-or-less to one or two of the five types.

Longitudinal studies over 16 weeks:  Hypotheses?  1.  Each woman's state is stable over time.  2. Each woman's state varies over time.  3 Each woman's state varies but resiliently returns to its core state.  4.  The number of states is limited...(?).

He shows one woman's time course, with blips in community composition corresponding with menstruation.  But only one woman had this.  Another woman: two and a half weeks of very different communities around two menstruation cycles, but stability over other cycles.  And the two changes were not similar to each other!  Other women, dramatic changes irrespective of menstruation or other activities.  He has a movie showing the changes but it vanished from the screen!  

Over the 16 weeks, it looks like most women's communities had a stable core type, with intermittent temporary switches to other types. Vaginal intercourse didn't disturb the communities.  We don't have data about changes over reproductive lifespan.

(Now some heavy ecological diversity statistics...)

Diversity within species:  See changes in ribotypes of the dominant species, even where community type is stable.  So there's quite a lot of variation in the specific strains that are dominant, sometimes correlated with changes in the abundances of other species.

Lactobacillus iners:  very dependent on nutrients from the host and the microbial community (a nutritional network).  The L. iners-type communities are more likely to undergo changes than are other types of communities.

Now doing a daily-sample study of 135 women over 10 weeks, including episodes of vaginosis.

Questions:  childhood (ongoing), pregnancy (little info but becomes more stable), menopause (a few cross-sectional studies, Lactobacillus present still)?  Time scale faster than at other sites?  Diet?  Innate immunity?  Sexual arousal? 

L. Caetano Antunes:  (NOT a terrific talk)  A metabolomic analysis of the mammalian gut microbiota.  Starts with the obvious (host vs pathogens, basic info about microbial communities and omics), he should have cut all of this from his talk for this audience.  Then he wouldn't have to talk so fast!  Bad slides too - tiny text, or blurry images with illegible text.  I bet this is a job talk, speeded up to fit in the short time allowed.

Mice:  collect feces before and after treatment with streptomycin, extract with acetonitrile (accomplishes what?), use mass spec to identify metabolites.  His story is about leukotriene B$ levels, which vary a lot, in response to streptomycin treatment and between individuals.

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