The human milk microbiome healthy breasts, mothers, and babies. James A. Foster 22 September 2010

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1 The human milk microbiome healthy breasts, mothers, and babies James A. Foster 22 September 2010

2 The human milk microbiome healthy breasts, mothers, and babies James A. Foster 22 September 2010

3 Who cares about breast milk? introduction who cares?

4 Who cares about breast milk? introduction who cares? Approximately half of all existing adults Mastitis: choose between intense pain, starving your infant, or using less healthy formula (often with dirty water)

5 Who cares about breast milk? introduction who cares? Approximately half of all existing adults Mastitis: choose between intense pain, starving your infant, or using less healthy formula (often with dirty water) Nursing infants (future adults) intestinal disease is the number one infant killer in the world which is better : breast milk or formula, given that clean water is a luxury in most places

6 Key questions introduction key questions Is there a milk microbiome? What is the ecology of the milk microbiome? Which bacteria are present? (who?) How complex is the milk microbiome?

7 Key questions introduction key questions Is there a milk microbiome? What is the ecology of the milk microbiome? Which bacteria are present? (who?) How complex is the milk microbiome? Where do(es) the milk microbiome(s) come from? Is a womanʼs microbiome stable over time? What are the bacteria doing? Are there healthy or unhealthy milk microbiomes? Maternal disease (e.g. mastitis) Infant disease (e.g. intestinal disease, sepsis, premies) Maternal and infant health (e.g. prophylaxis, positive benefit)

8 Key questions introduction key questions Is there a milk microbiome? What is the ecology of the milk microbiome? Which bacteria are present? (who?) How complex is the milk microbiome? Where do(es) the milk microbiome(s) come from? Is a womanʼs microbiome stable over time? What are the bacteria doing? Are there healthy or unhealthy milk microbiomes? Maternal disease (e.g. mastitis) Infant disease (e.g. intestinal disease, sepsis, premies) Maternal and infant health (e.g. prophylaxis, positive benefit)

9 What is known introduction is there milk microbiome?

10 What is known introduction is there milk microbiome? Two dogmas Momʼs: Duh, of course there are bacteria in milk Medical: of course not, healthy milk is ʻsterileʼ - translation: if there arenʼt any pathogens, who cares? - evidence: milk on plates doesnʼt produce (many) colonies, and what we find looks like it came from the skin [J. Appl. Microbiol. 95, (2003)]

11 What is known introduction is there milk microbiome? Two dogmas Momʼs: Duh, of course there are bacteria in milk Medical: of course not, healthy milk is ʻsterileʼ - translation: if there arenʼt any pathogens, who cares? - evidence: milk on plates doesnʼt produce (many) colonies, and what we find looks like it came from the skin [J. Appl. Microbiol. 95, (2003)] Our study 16 women, 3 time points over 4 weeks, collected aseptically barcoded pyrosequencing of V1-V3 region of 16S rrna gene: over 230K sequences, average 4000 reads per sample, approximately 240bp each bioinformatics: RDP classifier, mothur, R

12 Data reduction: quality control QC Step Raw data Remove reads/w low quality scores, ambiguities, homopolymers Align, remove unalignable characters #/reads 448,051 (233bp avg) 435, ,876 (40,005 unique) Precluster, remove chimeras 271,180 (16,327 unique, 60% of original)

13 Data reduction: quality control Remove reads/w low quality scores, ambiguities, homopolymers 435, ,051 (233bp avg) median=255bp sd= Raw data Length of reads for breastmilk microbiome 0 #/reads number of reads QC Step 50 Align, remove unalignable characters 301,876 (40,005 unique) Precluster, remove chimeras 271,180 (16,327 unique, 60% of original) basepairs

14 Data reduction: quality control Remove reads/w low quality scores, ambiguities, homopolymers 435, ,051 (233bp avg) median=255bp sd= Raw data Length of reads for breastmilk microbiome 0 #/reads number of reads QC Step Length of reads breastmilk for microbiome ,180 (16,327 unique, 60% of original) median=191bp sd= Precluster, remove chimeras basepairs 0 301,876 (40,005 unique) number of reads Align, remove unalignable characters basepairs 220

15 rrna amplicon bioinformatics methods 16S fingerprinting

16 rrna amplicon bioinformatics methods 16S fingerprinting Guiding principle: when in doubt, throw it out 16,327 unique sequences representing 301,867 high quality reads (from 448,051)

rrna amplicon bioinformatics methods 16S fingerprinting Guiding principle: when in doubt, throw it out Bioinformatics analysis Initial QC Remove short, low quality, ambiguous reads Sanity Checks

17 rrna amplicon bioinformatics methods 16S fingerprinting Guiding principle: when in doubt, throw it out Bioinformatics analysis Initial QC Remove short, low quality, ambiguous reads Sanity Checks Check number, length of pruned & retained reads, homopolymers Community analysis Define treatments 16,327 unique sequences representing 301,867 high quality reads (from 448,051) Who's there? Classify sequences Ecological analysis Align sequences: use secondary structure Biologically likely? Are number, lengths, quality reasonable? Estimate richness, evenness Trim ends, filter characters Determine OTUs: compute similarity, cluster OTU names match above? Estimate rarefaction, richness, evenness Select/classify OTU representatives

18 Microbiomes are complex results milk microbiomes are complex Estimated and observed richness Estimated (ACE) and observed species richness Woman ACE richness estimate with 95% confidence intervals (open circles) and observed richness (vertical bars).

19 Mothers are similar results core microbiome!"#$#"%#&'#('")*+%,)'+-.&/+&0)' $"!#,"!#+"!#*"!#)"!#("!#'"!#&"!#%"!#$" -./ " " B695.2<>6" B2.7>6" -17><C2?2<65" D/6A8/7>E2=>4?" F0>992<0996" G0?0996" I3:<2?8305" J.70/"!" S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S )03'4/)&%50+%#&' Genera are consistent within each woman over time, and all women share a core of four major genera.

20 Mothers are different results personalized microbiomes Comparison of microbial community structures Bray-Curtis community similarity Bray-Curtis measure of community similarity: women's communities are similar over time but differ from other women.

21 similar but different

22 Conclusions conclusions this study

23 Conclusions conclusions this study There is a (rich) milk microbiome that differs significantly from woman to woman

24 Conclusions conclusions this study There is a (rich) milk microbiome that differs significantly from woman to woman There is a core microbiome that all women share, comprising a few very abundant genera

25 Conclusions conclusions this study There is a (rich) milk microbiome that differs significantly from woman to woman There is a core microbiome that all women share, comprising a few very abundant genera Mothersʼ microbiome differ significantly, due to very rich and diverse collection of scarce bacteria

26 Next steps discussion next steps

27 Next steps discussion next steps Are these results representative? Need more samples from more mothers over longer periods of time. Refined resolution of ecological questions drill down to strain level when possible Where do the milk microbiomes come from? Succession? Is a womanʼs microbiome stable? Are there cycles? Are there fixed points? What are the bacteria doing? Are there healthy or unhealthy milk microbiomes? What can the microbiomes tell us about disease diagnosis and treatment and preventative care? Maternal and infant health (e.g. prophylaxis, positive benefit) Maternal disease (mastitis) Infant disease (e.g. intestinal disease, sepsis, premies) Develop better bioinformatics

28 Acknowledgements Human Microbiome Katherine Hunt Mark McGuire Michelle McGuire Daniel Beck Larry Forney Ursel Schüette Zaid Abdo Wade Copeland (many more!) IBEST Facilities Matt Settles Suresh Iyer Dan Rob Lyon Trent Nelson Colby Blair Funding COBRE (Forney) NIH P20 RR16448 INBRE (Bohach) NIH P20 RR NSF Evolution in Action STC DBI

29 questions? Let the conversations begin!

30 ACE richness estimation extra ACE richness estimation ni = The number of OTUs with i individuals Srare = The number of OTUs with 10 or fewer individuals Sabund = The number of OTUs with more than 10 individuals abund = the threshold to be considered an 'abundant' OTU (10) Essentially: estimated richness = observed richness + unobserved richness estimated from proportion of rare to common species ( the tail ) (equations from Mothur documentation)

31 Bray-Curtis structural similarity extra Bray-Curtis community comparison where, SA,i = the number of individuals in the ith OTU of community A SB, i = the number of individuals in the ith OTU of community B Essentially: ratios of abundances in correspondingly ranked OTUs (equations from Mothur documentation)

32 Data reduction: Quality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

Supplementary Figures. Supplementary Figure 1. Treatment schematic of SIV infection and ARV and PP therapies.

Supplementary Figures. Supplementary Figure 1. Treatment schematic of SIV infection and ARV and PP therapies. Supplementary Figures Supplementary Figure 1. Treatment schematic of SIV infection and ARV and PP therapies. Supplementary Figure 2. SIV replication and CD4 + T cell count. (A) Log SIVmac239 copies/ml