1. Mold and Cystic fibrosis: What can we learn
from studying fungal microbiota?
Laurence Delhaes1,2
, Sebastien Monchy3
, Magali Chabé1
, Anne Prévotat2
, Benoit
Wallaert2
, Eric Viscogliosi1
, Christophe Audebert 4
, Romain Dassonneville4
laurence.delhaes@pasteur-lille.fr
1
BDEEP – EA4547 (CIIL), Institut Pasteur de Lille, Université de Lille 2 – North of France
2
Lille Hospital, CHU de Lille – North of France
3
Université Littoral Côte d’Opale, Boulogne – North of France
4
PEGASE-GèneDiffusion, Institut Pasteur de Lille,– North of France
Indo-French Seminar/workshop, 20-22nd January 2014)

2.  Microorganisms (bacteria, archaea, yeasts, moulds, viruses) are
colonizing all ecological systems
 Such microorganisms are present even in extreme environments
 A majority of these microorganisms remains to be identified
1-4 106
bacteria / g of soil
(tropical rain forest)
2 108
cells / g of soil
(desert)
1,04 1020
cells / cm3
of water
(hypersaline water)
Introduction Worldwide microbial diversity

3.  Micromycetes: are present in various ecosystems
(but poorly studied/analyzed)
 Playing an important role within soil regeneration
(Heterotrophism)
Of note: Fungi (especially ascomycetes) have/fulfill
along with bacteria a central role in most land-based
ecosystems, as they are important decomposers,
breaking down organic substances.
 1 500 000 represents the number of fungus species
estimated for the entire earth/world
But only 97 000 have been identified
[Hibbett et al. 2007, Mycol Res , 111: 509-
547]
Introduction Microbial diversity: Place of the fungi

4.  As other ecological systems, there is a microbial diversity of human
organisms
Introduction Human Microbial diversity
Species number (bacteria)
Acid mine See Termite hindgut Human gut Soil
2008: (i) European project MetaHIT, and the
(ii) American “Common Fund's Human
Microbiome Project (HMP)” have been
developed
→ to characterize the microbial communities found at different sites on the
human body,
→ to analyze and compare the role of these microbes in human health and
disease.
Proctor LM (2011) The Human
Microbiome Project in 2011 and Beyond.
Cell Host & Microbe 10:287-91

5. The main bacteria isolated in Humans are belonging 4 phyla (among the 50 known phyla). There are
Firmicutes (in blue), Bacteroidetes (in pink), Actinobacteria (in green), and Proteobacteria (in
purple). Body sites: nasal passages, oral cavities, skin, gastrointestinal tract, and urogenital tract
http://www.larecherche.fr/content/recherche/article?
id=25319
 Human beings: Which bacteria are living in us (The genomes in our genome)?
[La Recherche – a 2011 up-date: 1st
panorama drawn from 7 studies realised from 2004 to 2007]
Introduction Human Microbial diversity
2 Missing elements
lungs = included in NIH
project as a site of
microbiota analysis. But
bacterial microbiota
analysis have been mainly
assessed while virome
and mycobiome are
significant / essential

6.  Respiratory function: A major issue for Public Heath
 In relation with the outdoor environment Every day we
breath 20,000 times, thereby inhaling ~10,000 liters of air (drawing and
expulsion of air; 15m3
of air / day / adult) with a fungal contamination
from to 108
to 103
spores/m3
in working to domestic usual exposure [OMS
2009; Pashley 2012]
 Lungs: Sterile organs?
[Morris et al. 2013; Beck et al.
2012; Erb-Downward et al. 2011;
Huang et al. 2011]
-Respiratory disorders: 1st
cause of worldwide consultations
-Chronic obstructive pulmonary disease (COPD): 4th
origin in
worldwide decease by 2030 (WHO)
-Cystic Fibrosis (CF): Most common serious hereditary disorder in the
Caucasian population[Rabe et al. « The year of the lung ». Lancet 2010]
Introduction Human Microbial diversity and Lung

7.  Lung microbial diversity in Cystic Fibrosis (CF):
- Lung diversity = Bacterial microbiota
exists in healthy people [Morris et al. 2013; Beck
et al. 2012; Erb-Downward et al. 2011; Huang et al.
2011]
- This bacterial community has been largely
studied in CF, and seems to be associated
with the evolution of the respiratory function
in CF [Maughan et al. 2012; Guss et al. 2011; van der
Gast et al. 2011; Rogers et al. 2010; Armougom et al.
2009; Bittar et al. 2008; Sibley et al. 2008; Tunney et al.
2008; Harris et al. 2007Goddard et al. 2012; Madan et
al. 2012; Fodor et al. 2012]
Introduction Human Microbial diversity and Lung

8.  The emerging world of the
fungal microbiome
[Huffnagle et al. Trends in Microbiology 2013]
Nobody is fungus-free
Human fungal microbiome is part of the rare biosphere of the entire
digestive microbiome
Evaluated at less than 0.1% of the genus in fecal material (from the
MetaHIT group analysis)
Introduction Human Microbial diversity and Lung

9. Authors argue that human activity is intensifying fungal disease
dispersal by modifying natural environments and thus creating new
opportunities for evolution
Introduction Fungal diversity and Emerging
Infectious Diseases
[Fisher et al. Review in Nature 2012]
 Pathogenic fungi are emerging as major threats to animal,
plant & ecosystem health

10. [From D. Denning, 2010]
 Patterns of Aspergillus interactions with humans
illustrating different host pathogen interactions, based on the
host damage response framework
Introduction Clinical features of Aspergillosis
 Invasive Aspergillosis +/- disseminated
 Local infection (aspergilloma, sinusitis)
 Hypersensitivity disease (ABPA or Hinson-
Pepys disease)
Pulmonary
Mycosis
Immuno-allergy
Mycosis

11. Invasive Aspergillosis = Poor Prognostic (mortality about 60-80%)
→ Difficult to diagnose, to treat
= Criteria of IA [De Pauw; Walsh 2008]
Air transmissionAir transmission
Opportunist fungiOpportunist fungi
 Fever unresponsive to broad–spectrum antibiotics with neutropenia (500/mm3, 10
days) Pulmonary symptoms early in the course, ± cutaneous or central nervous
metastases
 Patient at risk of IA: Immunocompromised patients
• OncoHaematology 3% – 14% >> allo-CT
[Castagnola 2008; Leeflang 2008; Neofytos 2013]
• IA mortality of 56% in France [Lortholary 2011] vs
57.5% in US [TRANSNET, Kontoyannis 2010 ]
• Solid Transplantation : Pulmonary Transplantation
IA = 4-6%, Major incidence in CF [Iversen 2008]
 Non-neutropenic patients ↑
• Corticotherapy [Lewis 2008; Castagnola 2008]
• Biotherapy (anti-TNF / Rituximab®) +++
[Stankovic K, 2006; Lebeaux 2009; Delhaes 2010 ]
• Chronic pulmonary diseases (COPD) 2.5%
[Guinea 2009; Ader 2006]
Introduction Clinical features of Aspergillosis

12. Computed tomography (CT) of the chest may be
used to identify the halo sign (Fig1.) a macronodule
surrounded by a perimeter of ground-glass opacity
= an early but transitory sign of invasive pulmonary
aspergillosis (IPA) (61% according to R. Greene et al.
2007)
Macronodule is also a frequent but not specific sign
(94% according to R. Greene et al. 2007)
Later: air-crescent signs (Fig2.) (10%
according to R. Greene et al. 2007). It
corresponds to an excavation (corresponding
to a central necrosis area when neutrophil
cells are increasing and immune response is
restored
www.learningradiology.com
 IPA= Fever unresponsive to broad–spectrum antibiotics with neutropenia
and pulmonary symptoms early in the course
Introduction Lung mycobiota in CF : backgrounds

13. Immune hyperactivity to A.
fumigatus chronic colonization
→ 2%, 5-15% in Asthma, CF patient
population [Denning 2003; Blandin 2008;
Gangneux 2008]
→ clinical diagnosis difficult
(easier in case of pulmonary
exacerbation)
→ Hyperthermia, Dyspnea,
pulmonary infiltrates
Introduction Clinical features of Aspergillosis

14.  Hyperthermia, Dyspnea, pulmonary infiltrates
Chest X-ray shows bilateral pulmonary
infiltrates (right > left) [lungindia.com]
→ Not specific of ABPA
→ ABPA clinical features (as
well as criteria) are usually
overlapping the underlying
disease, making the
diagnosis uneasy
Introduction Clinical features of Aspergillosis

15. Immune hyperactivity to A.
fumigatus chronic colonization
→ 2%, 5-15% in Asthma, CF patient
population [Denning 2003; Blandin 2008;
Gangneux 2008]
→ clinical diagnosis difficult
(easier in case of pulmonary
exacerbation)
→ Hyperthermia, Dyspnea,
pulmonary infiltrates
→ Associated with immediate
hyper-sensitivity
(hypereosinophilia, serum total
IgE) and IgG-mediated immune
response
Introduction Clinical features of Aspergillosis
Patient
serum
Ouchterlony method
Total Ag of A. fumigatus
Total Ag of A.
flavus
4-5 precipitin
bands (Ag-Ac
complex) with
high intensity

16.  An ongoing study to analyze the relevance of fungi
in CF pulmonary exacerbation
→ Pulmonary exacerbation = key event in CF lung alteration
→ the role of ABPA (allergic bronchopulmonary aspergillosis)
in such exacerbation?
→ with the idea of deciphering the place of Aspergillus spp
Aspergillus spp. especially A. fumigatus isolated
from respiratory secretions is often a dilemma for
the CF clinician in terms of clinical relevance and
treatment
What is the clinical significance of filamentous fungi positive sputum cultu
Liu et al. J Cyst Fibros. 2013 May
Purpose Clinical features of Aspergillosis

17. Aim: What is the fungal microbiota (or Mycobiota)
of CF patients?
Is the fungal microbiota stable?
Are the mycobiota diversity and
richness associated to the clinical
status of CF patient? …
What is the fungal composition of lung
microbiota in CF?
⇒ Mycobiota analysis by developping and using high
throughput sequencing approach
Which relation we observed between the
mycobiota and the bacterial composition?
Purpose Studying lung mycobiota in CF

18. DNA Extraction depends on matrix/substrate
PCRs targeted conserved genes that allow the
amplification of species distant/different
phylogenetically (V3 of 16s rDNA – ITS2)
Massive sequencing (multi-parallelized, 454 FLX
system) – getting hundreds of thousands of reads
Bio-informatic analysis
Identification by local blast to 2 databases: BLASTN ≠
- Silva SSU rRNA database release 102
- ITS2dbScreen that we designed de novo
Read assignments and clustering
(at the species or genus level)
To allow a biologic analysis of the data,
comparison between samples
(diversity analysis using MEGAN, U-clust, MEGANE5 progamms)
Collected sputum samples of CF patients
Materials & Methods Deep-sequencing approach

19. ⇒ 36 sputum samples From patients with (18) and without (18)
pulmonary exacerbation were compared (clinical, radiological,
biological data)
⇒ Microbial analysis done:
(i) Microbial cultures
(ii) using RT-PCR targeting RNA respiratory viruses (Seeplex
RV15 ACE Detection kit (Seegene))
(iii) using deep-sequencing fungal/bacterial diversity analysis
⇒ Statistical approach under process
a first PCA (principal component analysis) taking into account
the whole set of variables for
analyzing mycobiota vs bacterial microbiota at the genus level
we limited our analyses to the number of genera that were
present at least in 3 patients and the number of OTU present at
1% (relative abundance).
Materials & Methods Lung Microbiota: Relevance
in
CF exacerbation

20. ⇒ 36 Sputum samples
A) S-K score= Score de Shwachman-Kulczycki
Without exacerbation With exacerbation
Results Lung Microbiota in CF exacerbation

21. A) S-K score= Score de Shwachman-Kulczycki
Without exacerbation With exacerbation
B) Rhinovirus
Other RN viruses
C) SMG
D) Mould
We confirme the significant
association between HRV and
pulmonary exacerbation
[Goffard et al. 2014 in revision]
⇒ Conventional microbial
analysis:
(i) Microbial cultures
(ii) RT-PCR targeting RNA
respiratory viruses (Seeplex
RV15 ACE Detection kit - Seegene)
⇒ 36 Sputum samples
Results Lung Microbiota in CF exacerbation
No association between Milleri
group streptococcus and
pulmonary exacerbation
Only 2 patients colonized with
Scedosporium apiospermum
No association between A.
fumigatus and exacerbation

22. ⇒ 36 sputum samples From patients with (18) and without (18)
pulmonary exacerbation were compared (clinical, radiological,
biological data)
⇒ Microbial analysis done:
(i) Microbial cultures
(ii) using RT-PCR targeting RNA respiratory viruses (Seeplex
RV15 ACE Detection kit (Seegene))
(iii) using deep-sequencing fungal/bacterial diversity analysis
⇒ Statistical approach under process
a first PCA (principal component analysis) taking into account
the whole set of variables for
analyzing mycobiota vs bacterial microbiota at the genus level
we limited our analyses to the number of genera that were
present at least in 3 patients and the number of OTU present at
1% (relative abundance).
 953 999 reads size from 315 to 468 pb - 2/3 16s rDNA + 1/3 ITS2
 Optimal rarefaction curves
 Modelization under process
Results Lung Microbiota in CF exacerbation

23. According to PCA graph:
Addition of the 2 axes = the
explained part of the variability →
33% [42% in Zemanick et al. 2013]
For each variable, arrow lengh
is proportional to the load of the
corresponding variable on the
first 2 principal components
(Dim/axes 1-2) (the longer the arrow
is = the more the axes explained the
variable)
Our model and axes explained a
lot of microorganisms
Results Lung Microbiota in CF exacerbation

24. Key point to read a PCA graph:
Interpreting a correlation
between microorganisms as
follow
Right angle =
No correlation
Acute angle =
Positive correlation
180° angle =
Negative correlation
Results Lung Microbiota in CF exacerbation

25.  Pseudomonas
- is alone [Zemanick et al. 2013]
- not correlated with
“Malassezia plus Prevotella
group” [Zemanick et al 2013]
- neither with the “Candida
plus Rothia group” (which is
not well explained by our axes
since the arrows are short)
- but is negatively correlated
with the “group of oral flora
including streptococcus
plus some environmental
fungi”, as well as FEV1 –
SK-score [Zemanick et al. 2013]
Results Lung Microbiota in CF exacerbation

26.  Aspergillus
- Unfortunately, our PCA model
explained poorly this mold (short
arrows, anti-correlated to SK-score,
FEV1, ),
- Neither exacerbation status: There
was no differentiation between the
group of patients with and without
pulmonary exacerbation (according
to PCA-barycenter of each patient
group)
Results Lung Microbiota in CF exacerbation
*
*
→ Continue statistical analysis focusing on streptococcus species
and less abundant (but more diverse) components of the mycobiota
(rare biosphere - <0.1%)

27.  Determining exhaustively the microbial community
composition in CF patient sputa.
 Developing new approaches based on deep-sequencing,
(standardization, ARN analysis)
Improving management/survival of CF patients
 Development of ex vivo model biofilm to adapt drug
treatment (anti-bacterial/fungal)
 Predict the efficiency of drug treatment
Lung mycobiota
Improving our knowledge of microbiome by
Lung mycobiota in CF: Concluding remarks
 Mycobiota = dynamic event, part of the overall lung microbiome
(consisting of dynamic communities of virus, bacteria, & fungi)
Larger studies are now required to better understand
associated fungal communities in CF, ABPA
 Studying mycobiota evolution when patients are treated
with ATB cures [Muco-Bac-Myco project - F Botterel & L Delhaes
ongoing project]
 International study to decipher lung microbiome evolution
during exacerbation in CF patients [IMAGin-CF, submitted]

28. Institut Pasteur-Lille / Université de Lille 2
• Laurence Delhaes
• Eric Viscogliosi
• Eduardo Dei-Cas
• Anne Goffard
• Magali Chabé
Université Littoral Côte d’Opale
• Sébastien Monchy
• Christine Hubans / Stéphanie Ferreira
Faculté de Médecine de Lille
• Benoit Wallaert
• Anne Prévotat
• Julia Salleron
• Fréderic Wallet
• Rodrigues Dessein
• Sylvie Leroy
Société Genoscreen-Lille
Département de Microbiologie
AP-HP Créteil
•Françoise Botterel
•Odile Cabaret
•Jean-Winoc Decousser
•Jean-Philippe Barnier
Consortium Pegase
• Christophe Audebert / Romain Dassonneville
Multidisciplinary approaches
(due to the massive data generated)
Collaborations: