Integrating microbial and host transcriptomics to characterize asthma-associated microbial communities.
BACKGROUND
The relationships between infections in early life and asthma are not completely understood. Likewise, the clinical relevance of microbial communities present in the respiratory tract is only partially known. A number of microbiome studies analyzing respiratory tract samples have found increased proportions of gamma-Proteobacteria including Haemophilus influenzae, Moraxella catarrhalis, and Firmicutes such as Streptococcus pneumoniae. The aim of this study was to present a new approach that combines RNA microbial identification with host gene expression to characterize and validate metagenomic taxonomic profiling in individuals with asthma.


METHODS
Using whole metagenomic shotgun RNA sequencing, we characterized and compared the microbial communities of individuals, children and adolescents, with asthma and controls. The resulting data were analyzed by partitioning human and microbial reads. Microbial reads were then used to characterize the microbial diversity of each patient, and potential differences between asthmatic and healthy groups. Human reads were used to assess the expression of known genes involved in the host immune response to specific pathogens and detect potential differences between those with asthma and controls.


RESULTS
Microbial communities in the nasal cavities of children differed significantly between asthmatics and controls. After read count normalization, some bacterial species were significantly overrepresented in asthma patients (Wald test, p-value < 0.05), including Escherichia coli and Psychrobacter. Among these, Moraxella catarrhalis exhibited ~14-fold over abundance in asthmatics versus controls. Differential host gene expression analysis confirms that the presence of Moraxella catarrhalis is associated to a specific M. catarrhalis core gene signature expressed by the host.


CONCLUSIONS
For the first time, we show the power of combining RNA taxonomic profiling and host gene expression signatures for microbial identification. Our approach not only identifies microbes from metagenomic data, but also adds support to these inferences by determining if the host is mounting a response against specific infectious agents. In particular, we show that M. catarrhalis is abundant in asthma patients but not in controls, and that its presence is associated with a specific host gene expression signature.
Computational Biology Institute, George Washington University, Ashburn, VA, 20147, USA. eduardo.castro@unab.cl.|Universidad Andrés Bello, Center for Bioinformatics and Integrative Biology, Facultad de Ciencias Biológicas, Av. República 239, Santiago, 8370146, Chile. eduardo.castro@unab.cl.
Eduardo
E
Castro-Nallar
Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, 02118, USA. yshen3@bu.edu.
Ying
Y
Shen
Division of Emergency Medicine, Children's National Medical Center, Washington, DC, 20010, USA. RFreishtat@childrensnational.org.
Robert J
RJ
Freishtat
Computational Biology Institute, George Washington University, Ashburn, VA, 20147, USA. mlosada@gwu.edu.|Division of Emergency Medicine, Children's National Medical Center, Washington, DC, 20010, USA. mlosada@gwu.edu.|CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, Vairão, 4485-661, Portugal. mlosada@gwu.edu.
Marcos
M
Pérez-Losada
Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, 02118, USA. mani2012@bu.edu.
Solaiappan
S
Manimaran
Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, 02118, USA. gangl@bu.edu.
Gang
G
Liu
Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, 02118, USA. wej@bu.edu.
W Evan
WE
Johnson
Computational Biology Institute, George Washington University, Ashburn, VA, 20147, USA. kcrandall@gwu.edu.
Keith A
KA
Crandall
D000293:Adolescent; D001249:Asthma / Q000235:genetics* / Q000276:immunology / Q000382:microbiology* / Q000821:virology; D002648:Child; D005260:Female; D020869:Gene Expression Profiling; D054884:Host-Pathogen Interactions / Q000235:genetics*; D006801:Humans; D008297:Male; D056186:Metagenomics; D064307:Microbiota / Q000235:genetics*; D017423:Sequence Analysis, RNA; D055815:Young Adult