Dr. James Chalmers | Oriol Sibila

1. Microbial dysbiosis in CF and non-CF
bronchiectasis
James D Chalmers
Senior Clinical Lecturer and
Honorary Consultant Respiratory Physician,
University of Dundee

2. Microbial dysbiosis in CF and non-CF
bronchiectasis
James D Chalmers
Senior Clinical Lecturer and
Honorary Consultant Respiratory Physician,
University of Dundee
Oriol Sibila
Servei de Pneumologia
Hospital de Sant Pau, Barcelona

4. Antimicrobial treatment has transformed
CF
Age(years)
Pancreatic Enzymes
antistaphylococcal antibiotics
antipseudomonal antibiotics
rhDNase
Inhaled Tobramycin
Airway clearance
0
5
10
15
20
25
30
35
40
1st pathologic
description
CF gene
identified
Discovery
of high salt
in sweat
Sweat chloride
test developed
1st successful
pregnancy
Azithromycin
HTS
AZLI
TIP
Colobreathe
Ivacaftor
Bronchitol
Inhaled colistin
Neonatal
screening
Mist
tents
Centre care
Stratified/Precision
Medicine for CF
NPD and
Cl transport
RCTs

5. The adult CF microbiota
Fodor et al. Plos One 2012;7(9):e45001

6. Rogers B et al, Thorax 2015; 70: 74-81
n=6 n=6 n=6

7. The adult CF microbiota is stable over time and highly resistant to antibiotics
Fodor et al. Plos One 2012;7(9):e45001

8. Changes in the microbiome at stability and exacerbation
Carmody et al, Microbiome 2015 1;3:12.
95 samples from 4 patients with CF

9. Cuthbertson, ISME J 2015;10(5):1081-91
Antibiotic therapy causes reductions in
“Core” microbiota but not P. aeruginosa

10. Bacteria are not the end of the story……………
Kim et al, PLoS Pathog. 2015 Nov 20;11(11):e1005308

11. “Bronchiectasis one of the most neglected
diseases in respiratory medicine”
ERS White Book 2014
A disease characterised by recurrent
respiratory tract infections and chronic
bacterial “colonisation”
Neutrophil dominanted lung inflammation
No licensed therapies but most treatments are
antibiotic based and target airway infection
Bronchiectasis

12. Frequency of colonising bacteria in bronchiectasis
Author Year Country N Age Method Hi PA Sa Sp Mc Asp Myco NP
Nicotra 1995 USA 123 57 Sputum 30 31 7 11 2 5 23 23
Evans 1996 UK 135 - Sputum ND 12 ND ND ND ND ND ND
Wilson 1997 UK 87 54 Sputum 20 25 - - - - - 38
Pasteur 2000 UK 150 53 Sputum 35 31 14 13 20 2 ND 5
Angrill 2001 Spain 49 57 BAL 26 20 - 2 - - ND 28
Angrill 2002 Spain 42 58 Sputum 26 9 - 14 5 2 0 60
Angrill 2002 Spain 59 58 BAL 32 10 3 7 - - 0 32
Kelly 2003 UK 100 57 Sputum 54 21 8 16 20 ND ND -
Tsang 2005 Hong Kong 86 58 Sputum 11 27 - - - - - 60
King 2007 Australia 89 57 Sputum 47 12 4 7 8 2 2 21
Martinez-Garcia 2007 Spain 76 70 Sputum 18 20 - - - - - -
O’Connell 2010 USA 230 - Sputum - 31 9 - - - 35 87
Wong 2012 N.Zealand 141 60 Sputum 28 12 3 3 4 - - -
Goeminne 2012 Belgium 479 67 Sputum 31 30 23 20 15 20 - -
King 2012 Australia 178 58 Sputum 35 23 - - - - - 28
Chalmers 2013 UK 470 65 Sputum 30 15 9 6 12 ND ND 23
Haemophilus influenzae most common, then Pseudomonas
aeruginosa, Staphylococcus aureus and Moraxella
catarrhalis
20-40% grow no pathogens (depending on how hard you
look)
Chalmers et al Mol Immunol. 2013;55(1):27-34

13. Bacteria and neutrophilic
inflammation are linked
Chalmers et al, AJRCCM 2012;186(7):657-65N=385, single centre UK study

14. Sibila O et al, Respirology 2015; 20: 1082-1088

15. Prognostic impact of airway infection
n=608 patients over 4 years in a
single centre Scottish study
Chalmers et al, Am J Respir Crit Care Med. 2014;189(5):576-85

16. Exacerbations
• P. aeruginosa colonization vs lack of P. aeruginosa
– Mortality increased by ~3x*
– Hospital admissions ~7x increased risk
– Average of 1 additional exacerbation per patient per year
– 15% lower FEV1 % predicted
– Clinically significant impact on quality of life as measured by SGRQ
Finch et al, Ann Am Thoracic Soc. 2015 12(11):1602-11
Study of Subgroup
Odds Ratio Odds Ratio
M-H, Random, 95% CI M-H, Random, 95% CI
Aliberti 2004 31.16 [1.58, 616.55]
Chalmers 2014 2.85 [1.50, 5.43]
Chalmers 2015 2.09 [0.77, 5.64]
Goeminne 2014 10.25 [3.81, 27.57]
Loebinger 2009 1.82 [0.65, 5.15]
Martinez-Garcia 2014 2.42 [1.46, 4.01]
McDonnell 2014 1.73 [0.68, 4.38]
McDonnell 2015 3.46 [1.55, 7.73]
Total (95% CI) 2.95 [1.98, 4.40]*
0.05 0.2 1 5 20
Protective Harmful
Heterogeneity: Tau2=0.13; Chi2=11.72, df=7 (P=0.11); I2=40%
Test for overall effect: Z=5.29 (P < 0.00001)

17. Culture based microbiology
Extensive data
• H. influenzae and P. aeruginosa the most
commonly isolated pathogens
• Strong association between P. aeruginosa
and poor outcomes, although direct role in
disease progression not fully established
• Bacteriology alone insufficient to explain
variation in exacerbation frequency or
disease progression

18. Microbiome in bronchiectasis
Lonni A et al, Ann Am Thor Soc 2014; 11 (4): 496-503
- Worse lung function
- Higher inflammation

19. Microbiome in bronchiectasis
Tunney et al. Am J Respir Crit Care Med. 2013;187(10):1118-26.

20. Remarkable stability over time
Tunney et al. Am J Respir Crit Care Med. 2013;187(10):1118-26.

21. Rogers et al. Lancet Respir Med. 2014;2(12):988-96

22. Bronchiectasis microbiome
B
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%OTUs
Dicker et al. Presented at ATS 2016
n=140

23. Bronchiectasis severity index
Mild
Mod.
Severe
Dicker et al. Presented at ATS 2016

24. Exacerbations
0
1-2
3+
Dicker et al. Presented at ATS 2016

25. Culture independent microbiology
in bronchiectasis
Limited data
• Anaerobes (Veillonella, Prevotella) are common along with
traditional pathogens Haemophilus sp. and Pseudomonas sp.
• Microbiome is related to disease severity
• Diversity is reduced at exacerbation
• Diversity is reduced by macrolide therapy

26. Microbial Community Structure: CF and BE
CF BE
Einarsson et al 2015 unpublished

27. N=137 Bronchiectasis patients
N=114 COPD patients
All clinically stable for 4 weeks at
baseline
0
2 0
4 0
6 0
8 0
1 0 0
P revotella V e illon ella
S tre p to c o c c u s L e p to tric h iaN e is se ria
H a e m o p h ilu s
M oraxe lla
P se u d o m o n a s
S te n o tro p h o m o n a s
R o th ia
A c tin o b a c illu sP a ste u re lla
U n k n o w n E n te ro b a c te ria ce a eA c in e to b a c te r
C O P D B ro n c h ie c ta s is
0
2 0
4 0
6 0
8 0
1 0 0
P revotella V e illon ella S tre p to c o c c u s L e p to tric h iaN e is se riaH a e m o p h ilu s M oraxe llaP se u d o m o n a s
S te n o tro p h o m o n a s R o th iaA c tin o b a c illu sP a ste u re lla U n k n o w n E n te ro b a c te ria ce a eA c in e to b a c te r
C O P D B ro n c h ie c ta s is
Dicker et al. Presented at ATS 2016

28. Summary
• Culture based and culture independent studies
provide complementary information about the
role of bacteria in CF an non-CF bronchiectasis
• Both methods confirm the critical role of P.
aeruginosa in both diseases
• There are large similarities in core microbiota
composition between BE and COPD.

29. Future directions
• Fungal, viral and Mycobacterial sequencing is needed to
fully understand the complexity of airway community
dynamics
• The microbiome alone does not appear to explain
phenotypic diversity in CF and BE- microbiome data needs
to be integrated with clinical and inflammatory data
• The consistent finding that loss of diversity is associated
with disease severity is provocative – suggests the
possible need for antibiotic stewardship, particularly in
early stage disease

31. Endotyping in CF and BE
Host response
Proteome
Airway and systemic infl.
Host gene expression
Microbiome
Diversity
Dominance
“Bronchotypes”
Dynamics
Upper airway
Gut/Lung axis
Transmission
Clinical phenotyping
Antibiotic use
Pulmonary function
Exacerbations
Interspecies signalling
Gene expression
Virulence
Quorum sensing
Interspecies competition
Mycobiome/virome/others
Viruses
Fungi
Mycobacteria

32. Acknowledgements
Post-docs
Dr Alison Dicker
Dr Holger Kneuper
Taybridge study
Professor Sara Marshall
Dr Tom Fardon
Dr Simon Finch
Dr Jeffrey Huang
Dr Sebastian Ferri
Barcelona
Guillermo Suarez-Cuartin
Oriol Sibila
Students
Alex Smith
Christopher Fong
Wasyla Ibrahim
Samantha Ong
Research Nurses
Gayle Scott
Gill Brady
Debbie Forbes
Study co-ordinator
Megan Crichton
Belfast
Professor Stuart Elborn
Gisli Einarsson