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A narrow repertoire of transcriptional modules responsive to pyogenic bacteria is impaired in patients carrying loss-of-function mutations in MYD88 or IRAK4

Nature Immunology volume 15, pages 1134–1142 (2014)Cite this article

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Abstract

Loss of function of the kinase IRAK4 or the adaptor MyD88 in humans interrupts a pathway critical for pathogen sensing and ignition of inflammation. However, patients with loss-of-function mutations in the genes encoding these factors are, unexpectedly, susceptible to only a limited range of pathogens. We employed a systems approach to investigate transcriptome responses following in vitro exposure of patients' blood to agonists of Toll-like receptors (TLRs) and receptors for interleukin 1 (IL-1Rs) and to whole pathogens. Responses to purified agonists were globally abolished, but variable residual responses were present following exposure to whole pathogens. Further delineation of the latter responses identified a narrow repertoire of transcriptional programs affected by loss of MyD88 function or IRAK4 function. Our work introduces the use of a systems approach for the global assessment of innate immune responses and the characterization of human primary immunodeficiencies.

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Figure 1: Transcriptional responses in blood following in vitro exposure to purified agonists of TLR or IL-1R.
Figure 2: Transcriptional responses in blood following in vitro exposure to whole bacteria.
Figure 3: Modular transcriptome repertoire of whole-blood responses to stimulation with TIR agonists and Gram-positive bacteria.
Figure 4: Literature profiles of module clusters 4, 5 and 6.
Figure 5: Modular transcriptome-repertoire mapping of residual responsiveness of patients to TIRs agonists and whole bacteria.
Figure 6: Residual responsiveness following in vitro exposure to whole bacteria, for modules of cluster 6.
Figure 7: Transcriptional responses in blood following in vitro exposure to C. albicans, BCG and HSV.

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Acknowledgements

We thank L. Marodi, J.C. Rodriguez Gallego, G. Davies, Y. Camcioglu, A. Bousfiha, J. Vasconcelos and J.I. Aróstegui for blood from the patients with deficiency in IRAK4 or MyD88; B. Lemoine and P. Nguyen for sample processing; E. Varon (Assistance Publique-Hôpitaux de Paris) for bacterial strains; F.J. Barrat (Dynavax Technologies) for CpG reagents; M. Chrabieh for technical help; and the patients and their families for help. Supported by the US National Institutes of Health (1R21AI085523-01, U01AI082110, U19-AI089987, U19-AI057234 and R01ARO50770-02), the Dana Foundation, La Fundació La Caixa (L.Al., 2008–2010) and the Instituto de Salud Carlos III (PFIS12/01990 (also financed by the European Regional Development Fund) to L.Al., 2012 to the present).

Author information

Authors and Affiliations

  1. Baylor Institute for Immunology Research and Baylor Research Institute, Dallas, Texas, USA

    Laia Alsina, Nicole Baldwin, Huanying Qin, Zongbo Jin, Romain Banchereau, Esperanza Anguiano, Alexei Ionan, Virginia Pascual & Damien Chaussabel

  2. Allergy and Clinical Immunology Department, Hospital Sant Joan de Déu, Barcelona Universitat de Barcelona, Barcelona, Spain

    Laia Alsina

  3. Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA

    Elisabeth Israelsson, Matthew C Altman, Kristen K Dang & Damien Chaussabel

  4. Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM UMR 1163, IMAGINE Institute, Paris, France

    Pegah Ghandil, Laura Israel, Horst von Bernuth, Laurent Abel, Anne Puel, Capucine Picard & Jean Laurent Casanova

  5. Paris Descartes University, Paris, France

    Pegah Ghandil, Laura Israel, Horst von Bernuth, Laurent Abel, Anne Puel, Capucine Picard & Jean Laurent Casanova

  6. Department of Pediatric Pneumology and Immunology, Charité Hospital–Humboldt University, Berlin, Germany

    Horst von Bernuth

  7. St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, USA

    Anne Puel, Capucine Picard & Jean Laurent Casanova

  8. Study Center of Primary Immunodeficiencies, Assistance Publique-Hôpitaux de Paris, Necker Hospital, Paris, France

    Capucine Picard

  9. Howard Hughes Medical Institute, New York, USA

    Capucine Picard & Jean Laurent Casanova

  10. Pediatric Hematology-Immunology Unit, Necker Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France

    Jean Laurent Casanova

  11. Sidra Medical and Research Center, Doha, Qatar

    Damien Chaussabel

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  1. Laia Alsina
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Contributions

L.Al., acquisition of data, analysis and interpretation of data and drafting of the manuscript; E.I, M.C.A. and K.K.D., analysis and interpretation of data and drafting of the manuscript; K.K.D., figures prepared with the Circos visualization tool; Z.J., acquisition of data; P.G., H.v.B., A.P., L.I. and C.P., sample collection and whole-blood stimulation; A.P. and C.P., critical revision of the manuscript; C.P., sending of patients' blood; N.B., modular analysis; H.Q., R.B. and, A.I., statistical analysis of microarray data; E.A., sample collection and data acquisition; and L.Ab., V.P., J.L.C. and D.C., study conception and design and critical revision of the manuscript.

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Correspondence to Laia Alsina or Damien Chaussabel.

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Integrated supplementary information

Supplementary Figure 1 Pathway analysis of Pan-TLR agonist gene set.

Blood from healthy controls or patients was stimulated in vitro for 2 hours with TLR ligands and cytokines (batch 1); out of the responsive transcripts after TLR stimulation (263, 168, 202, 522, 57, and 286 for Poly(I:C), PAM3, Flagellin, R848, 3M13, and 3M2 stimulations, respectively), 70 were found to be in common between all TLR stimulations tested, excluding Poly(I:C). The predicted protein-protein interaction network for the 59 unique genes (derived from those 70 transcripts) was constructed using the STRING program’s seven active prediction methods (STRING v9.1, http://string-db.org). The cutoff used for interaction was a confidence score >0.4. The gene network was drawn in Cytoscape (www.cytoscape.org) using a force directed layout from the overall confidence scores for each gene pair. Reactome Pathway Database (www.reactome.org) was then used to sort genes into groups according to functional interactions, yielding the 5 colored groupings, and annotated using pathway enrichment. The top scoring pathway for each group is shown in the annotation. Those genes that were not predicted in this network are shown below in grey.

Supplementary Figure 2 Blood transcriptional responses following in vitro exposure to purified agonists of TLRs or IL-1Rs.

Changes in expression levels of transcripts responsive to TIRs agonists are represented on a heatmap. Blood from healthy controls or patients was stimulated in vitro for 2 hours with TLR ligands and cytokines (batch 1); responsive transcripts were arranged by rows via hierarchical clustering (398, 263 168, 202, 522, 57, 286, 93, and 106 for TNF, Poly(I:C), PAM3, flagellin, R848, 3M13, 3M2, IL-1b, and IL-18 stimulations, respectively), and individual subjects by columns from left to right: healthy controls, MyD88-deficient patients, IRAK-4-deficient patients. Changes versus the nonstimulated condition are represented by a color scale: red = up-regulated; blue = downregulated; yellow = no change. Bar graphs represent overall individual levels of responsiveness relative to the average of controls: the number of responsive probes in a given subject / average of differentially expressed probes in healthy controls x 100. Responses to PMA/ionomycin, LPS, and PAM2 are presented similarly in Figure 1a.

Supplementary Figure 3 Modular transcriptome repertoire mapping of patient residual responsiveness to TIR agonists.

For visualization purposes, circular heatmaps were generated to represent the transcriptional modular activity of IRAK4-/- patients (outer rings) and MYD88-/- patients (inner rings) with respect to healthy controls in response to TIR agonists. The values plotted represent residual responsiveness relative to the average of healthy subjects on a color scale ranging from -1 (saturated blue, intact module down regulation) to +1 (saturated red, intact module up-regulation). Values close to zero are shown in white or very pale color. The cases where a value was missing are represented by grey color. The histogram values shown are the absolute value of the normalized module scores (calculated above) averaged across patients. Values shown range between 0 and 1, where cases with values >1 have an asterisk above the bar. Residual responses to four heat-killed bacteria, PAM2, and LPS are presented similarly in Figure 5.

Supplementary Figure 4 Residual responsiveness following in vitro exposure to whole bacteria for C6 modules.

This box plot displays residual responsiveness of individual patients relative to the average of healthy subjects following 2 hours in vitro exposure to heat killed S. pneumoniae (R11470 and R8450 strains). Red dots = IRAK4-/- patients; Blue triangles = MYD88-/- patients (batch 1 and 2). Modules represented here belong to cluster C6. Figure 6 in the main manuscript show residual responses to S. pneumoniae’s R6 strain and S. aureus.

Supplementary Figure 5 Reevaluation of transcriptional responses to TLR agonists and whole bacteria in a new set of patients.

Blood from healthy controls or patients (combining batch 2 and new set of samples, batch 3) was stimulated in vitro for 2 hours with three strains of heat killed S. pneumoniae and S. aureus and PAM2 (TLR2 agonist); graphs represent overall individual levels of responsiveness in patients relative to the average of control subjects: the number of responsive probes in a given subject / average of differentially expressed probes in healthy controls x 100. No differences are observed in the pattern of responsiveness between batch 2 and 3. Same blunted responses to PAM2 in TIR patients and residual responses to bacteria.

Supplementary Figure 6 Reevaluation of residual responsiveness to whole bacteria for C6 modules in a new set of patients.

Blood from healthy controls or patients (batch 3, including repeat blood draws from 2 patients (IRAK4-/- P5 and MYD88-/- P4) and 2 new patients (IRAK4-/- P6 and MYD88-/- P7) was stimulated in vitro for 2 hours with three strains of heat killed S. pneumoniae and S. aureus. All showed low residual responsiveness for M4.3, M4.7 and M6.3 replicating the results seen in the previous experiments (batch 1 and 2).

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Alsina, L., Israelsson, E., Altman, M. et al. A narrow repertoire of transcriptional modules responsive to pyogenic bacteria is impaired in patients carrying loss-of-function mutations in MYD88 or IRAK4. Nat Immunol 15, 1134–1142 (2014). https://doi.org/10.1038/ni.3028

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