Metagenome: Fungal and Bacterial interactions

Laurence Delhaeslaurence.delhaes@pasteur-lille.fr

1BDEEP – EA4547 (CIIL), Institut Pasteur de Lille, Université de Lille 2 – France2Département de Microbiologie, Service de Parasitologie-Mycologie, CHU de Lille - France.

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: Global microbial diversity

Micromycetes: are present in various ecosystems (but poorly studied/analyzed)

Playing an important role within soil regeneration (nutriment - metabolism of plant decomposition)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

As other ecological systems, there is a microbial community /diversity of human organisms

Introduction: Human Microbial diversity

Species number (bacteria)

Acid mine See Termite hindgut Human gut Soil

Proctor LM (2011) The Human Microbiome Project in 2011 and Beyond. Cell Host & Microbe 10:287-91

Recently, the Common Fund's Human Microbiome Project (HMP) has been developed.It aims to characterize the microbial communities found at several different sites on the human body, including nasal passages, oral cavities, skin, gastrointestinal tract, and urogenital tract, and to analyze the role of these microbes in human health and disease.

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).

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

Respiratory function: A major issue for Public Heath

In relation with the outdoor environment As for the other air-breathing animals, human lungs are dealing with gas exchange (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]

Lungs: Sterile organs: an old dogma? [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

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

Purpose: 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?

Introduction: Human Microbial diversity and Lung

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) – getting hundreds of thousands of reads

Bio-informatic analysisIdentification 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)

Collectd sputum samples of CF patients

Materials & Methods: Metagenomic approach

-Bacteria [16s rDNA region V3] : 326,277 pyrosequences (with 93% : 450-500 bp)

-Fungi [ITS2] : 133,317 pyrosequences (with 85% : 300-450 bp)

-With adequate rarefaction curves (confirming we have a good evaluation of the sample diversity)

Lung mycobiota in CF: Results of the pilot study

Determine:• Bacterial diversity (comparable to published data) • Fungal diversity

Evaluate the relation between fungal/bacterial community structure and patient clinical status

8 sputum samples (4 patients) using 454 FLX system

Lung mycobiota in CF: Results of the pilot studyFungal diversity- Among the 24 species /genera

identified as fungi using deep-sequencing, only 4 have been isolated by cultures.

- Genomic methods allowed the identification of additional species that are recognized as microorganismsinvolved in respiratory or

infectious diseases

- The median [IQ] number of microorganism genera per sputum sample was 3.5 [3; 7.5] micromycetes [Bouchara et al. 2009].

Fungal richness (Choa1 index)

S-K score= Shwachman-Kulczycki Score (overall clinical status, activity, lung function, pulnmonary radiography)

Body Mass Index

(kg/m2)

Lung mycobiota in CF: Results of the pilot studyRelation between species richness & clinical

status

Body Mass Index

(kg/m2)

Lung mycobiota in CF: Results of the pilot studyRelation between species richness & clinical

status

Prokaryote richness (Choa1 index)

S-K score= Shwachman-Kulczycki Score (overall clinical status, activity, lung function, pulnmonary radiography)

Body Mass Index

(kg/m2)

Lung mycobiota in CF: Results of the pilot studyRelation between species richness & clinical

status

Choa1 indexes

S-K score= Shwachman-Kulczycki Score (overall clinical status, activity, lung function, pulnmonary radiography)

Pat. 3 (09/2007) Pat. 3 (09/2008)

Patients 2

Patient 1 (01/2008)Patient 1 (01/2009)

Patient 4 (10/2008)Patient 4 (08/2008)

- Chao1 indexes of fungi and bacteria are statistically (p<0.05) associated with S-K score and BMI.

- For bacteria, these results are in agreement with published data [van der Gast et al. 2011; Klepas-Ceraj et al. 2010].

% Forced Vital Capacity (FVC)

% Forced Expiratory Volume (FEV1)

Pat. 3 (09/2007)

Pat. 3 (09/2008)

Patient 1 (01/2008)Patient 1 (01/2009)

Patient 4 (10/2008)Patient 4 (08/2008)

Patients 2 (03/2008)

Patients 2 (03/2009)- Chao1 indexes of fungi and bacteria are statistically (p<0.05) associated with FVC and FEV1.

Lung mycobiota in CF: Results of the pilot studyRelation between species richness & clinical

status

Validation of the molecular approach (ITS2 DB+++)

We observed a decrease of diversity and richness for fungal and bacterial communities significantly associated with poor clinical status (S-K score and BMI) and decreased lung function (FEV1 and FVC)

Our results documented the complexity of fungal and bacterial communities in CF, with potential interaction between species (biofilm)

[Delhaes et al. 2012]

Lung mycobiota in CF: Results of the pilot study

36 sputum samples From patients with (18) and without (18) pulmonary exacerbation were compared (clinical, radiological, biological data – 40 variables per patient)

Microbial analysis is under process: (i) using deep-sequencing fungal/bacterial analysis (ii) using RT-PCR targeting RNA respiratory viruses (iii) using q-PCR targeting DNA respiratory viruses

Mathematical approach under process a first PCA (principal component analysis) taking into account the whole set of variables (40 per patient) for analyzing Mycobiota versus 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%.

Lung mycobiota in CF: Relevance in CF exacerbation

Lung mycobiota in CF: Relevance in CF exacerbation

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

Lung mycobiota in CF: Relevance in CF exacerbation

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

Lung mycobiota in CF: Relevance in CF exacerbation

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 plus some environmental fungi”, as well as FEV1 – SK-score[Zemanick et al. 2013]

Lung mycobiota in CF: Relevance in CF exacerbation Aspergillus

- Unfortunately, our PCA model doesn’t explained this mold

Malassezia - As some anaerobes, M. furfur and

M. sympodialis are difficult to culture, both obligatory lipophilic, and skin flora yeasts of humans

Classically, they are associated with superficial infections of the skin (pityriasis versicolor - folliculitis)

They appear + correlated with anaerobes in agreement with their lipophyly (since anaerobes can produce fatty acids)

ChromAgar Malassezia

→ Integrate virus data→ Continue mathematical analysis

Muco-Bac-Myco: Ecology & dynamics of fungal and bacterial communities of sputum samples from CF patients under antimicrobial treatment: A French prospective study based on deep-sequencing

Lung mycobiota in CF: To conclude

Validation of mycobiota analysis based on ITS2 (ITS2DB)

→ Candida et A. fumigatus = Main species/genus isolated [Charlson et al. 2012; Delhaes et al. 2012]

→ Role in the decrease of pulmonary function

→ Which place for fungi in CF exacerbation?

→ What is mycobiota evolution and role when ATB treatment are managed? [Muco-Bac-Myco project]

- F Botterel & L Delhaes under process]

Mycobiota = dynamic event, part of the overall lung microbiome

Determining exhaustively the microbial community composition in CF patient sputa.

Developing new approaches based on deep-sequencing, (standardization)

Larger studies are now required to better understand CF associated communities

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: Perspectives

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

Requiring multidisciplinary approaches (due to the massive data generated)

Acknowledgments