Systems biology of vaccination for seasonal influenza in humans

Helder I Nakaya, Jens Wrammert, Eva K Lee, Luigi Racioppi, Stephanie Marie-Kunze, W Nicholas Haining, Anthony R Means, Sudhir P Kasturi, Nooruddin Khan, Gui-Mei Li, Megan McCausland, Vibhu Kanchan, Kenneth E Kokko, Shuzhao Li, Rivka Elbein, Aneesh K Mehta, Alan Aderem, Kanta Subbarao, Rafi Ahmed, Bali Pulendran, Helder I Nakaya, Jens Wrammert, Eva K Lee, Luigi Racioppi, Stephanie Marie-Kunze, W Nicholas Haining, Anthony R Means, Sudhir P Kasturi, Nooruddin Khan, Gui-Mei Li, Megan McCausland, Vibhu Kanchan, Kenneth E Kokko, Shuzhao Li, Rivka Elbein, Aneesh K Mehta, Alan Aderem, Kanta Subbarao, Rafi Ahmed, Bali Pulendran

Abstract

Here we have used a systems biology approach to study innate and adaptive responses to vaccination against influenza in humans during three consecutive influenza seasons. We studied healthy adults vaccinated with trivalent inactivated influenza vaccine (TIV) or live attenuated influenza vaccine (LAIV). TIV induced higher antibody titers and more plasmablasts than LAIV did. In subjects vaccinated with TIV, early molecular signatures correlated with and could be used to accurately predict later antibody titers in two independent trials. Notably, expression of the kinase CaMKIV at day 3 was inversely correlated with later antibody titers. Vaccination of CaMKIV-deficient mice with TIV induced enhanced antigen-specific antibody titers, which demonstrated an unappreciated role for CaMKIV in the regulation of antibody responses. Thus, systems approaches can be used to predict immunogenicity and provide new mechanistic insights about vaccines.

Conflict of interest statement

COMPETING INTERESTS STATEMENT

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1
Analysis of humoral immunity to influenza vaccination. (a) Antibody response determined by HAI titers on the plasma of TIV (blue bars) and LAIV (black bars) vaccinees on day 28 post-vaccination. The bars represent the highest HAI response (fold-change day 28/ day 0) among all 3 influenza strains contained in the vaccine. Subjects were classified as “Low responders” if no increase higher than 2-fold was observed in the HAI response and as “High responders” if the HAI titers on day 28 is ≥4 times higher than the titers at baseline. (b) PBMCs collected from all vaccinees were assayed for influenza-specific IgG secreting plasmablasts by ELISPOT assay at 0 and 7 days after vaccination. Each sample was measured in duplicate, averaged and plotted as plasmablasts per million PBMCs. Median values are shown. (c) Flow cytometry analysis of plasmablasts in blood. The frequency of plasmablast gate (CD3−CD20−/loCD19+CD27hiCD38hi) is shown for a representative TIV (left panel) and LAIV (right panel) vaccinee. (d) Statistically significant positive correlation (Pearson r = 0.58, P-value (two-tail) < 0.0001) between the frequencies of plasmablasts at day 7 determined by flow cytometry and the number of influenza-specific IgG-secreting plasmablasts by ELISPOT on the same day. TIV and LAIV vaccinees are represented by blue and black dots, respectively. (e) Statistically significant positive correlation (Pearson r = 0.43, P-value (two-tail) = 0.02) between influenza-specific IgG secreting plasmablasts at day 7 and the antibody response at day 28 on TIV vaccinees.
Figure 2
Figure 2
Molecular signature induced by LAIV vaccination. (a) Interferon (IFN)-related genes differentially expressed after LAIV vaccination. Solid and dashed lines represent respectively, direct and indirect interactions reported for the genes. The colors represent the mean fold-change in gene expression on days 3 or 7 compared to day 0 in all LAIV vaccinees. Genes with expression fold-change highest at day 3 or day 7 post-vaccination are shown on the left or on the right of the network, respectively. (b) Induction of key IFN-related genes was confirmed by quantitative RT-PCR. PBMCs of healthy subjects were stimulated in vitro with different vaccines for 24h. The GAPDH-normalized expression levels of OAS1, IRF7, Mx2 and STAT1 in stimulated PBMCs were compared to those of PBMCs non-stimulated.
Figure 3
Figure 3
Molecular signatures induced by TIV vaccination. (a) Heat map of gene signatures of immune cells identified by meta-analysis (see Methods). Expression level of each gene (in rows) is represented by the number of standard deviations above (red) or below (blue) the average value for that gene across all samples (in columns). (b) Spider graph showing the fold enrichment of TIV up-regulated genes among the genes highly expressed in any PBMC subset. Fold enrichment is calculated as described in Methods. Cell subsets with statistically significant enrichment (Fisher’s exact test two tailed P-value < 10−10) were marked with asterisks. (c) Spider graph showing the fold enrichment of TIV up-regulated genes among the genes highly expressed in B cells and also highly expressed in a specific B cell subset. (d) Heat map of genes up-regulated by TIV vaccination and also highly expressed in B cells and antibody-secreting cells. The official gene symbol for each probe set is shown on the bottom of the heat map. Probe sets that mapped to antibody variable regions are named ‘abParts’ and those ones not annotated are represented by the Affymetrix probe ID. (e) Spider graph showing the fold enrichment of LAIV up-regulated genes among the genes highly expressed in any PBMC subset.
Figure 4
Figure 4
Molecular signatures that correlate with antibody titers to TIV. (a) Heat map of probe sets (in lines) whose baseline normalized expression at day 3 (top) or day 7 (bottom) correlates (Pearson, P-value < 0.05) to baseline-normalized antibody response at day 28 post-TIV vaccination. Blue and red bars on the right of the heat map indicate the probe sets with negative and positive correlation, respectively (number of probe sets shown). The colors represent the individual fold-change in gene expression at days 3 or 7 compared to day 0 in TIV vaccinees. Probe sets that correlate on both day 3 and 7 to HAI response were counted as “day 7” and the day7-day0 expression was used to represent the expression on heat map. (b) HAI response-correlated genes (Pearson, P-value < 0.05) associated with the Unfolded protein response (purple area), Antibody-secreting cell differentiation (light brown area) and/or regulated by the transcription factor XBP-1. Solid and dashed lines represent, respectively direct and indirect interactions reported for the genes. (c) Spider graph showing the fold enrichment of genes (among those highly expressed in any PBMC subset), whose expression on either day 3 or day 7 post-TIV vaccination is positively (red line) or negatively (blue line) correlated to HAI titers (Pearson, P-value < 0.05). Fold enrichment is calculated as described in Methods. Cell subsets with statistically significant enrichment (Fisher’s exact test two tailed P-value < 10−10) are marked with asterisks. (d) Heat map of probe sets highly expressed in B cells and antibody-secreting cells whose baseline normalized expression correlates (Pearson, P-value < 0.05) to baseline-normalized HAI response.
Figure 5
Figure 5
Signatures that predict the antibody response induced by TIV. (a) Schematic representation of the experimental design used to identify the early gene signatures that predict antibody responses to TIV vaccination. The 2008–2009 Trial was used as a “training set to identify predictive signatures, using the Discriminant Analysis of Mixed Integer Programming (DAMIP) model. These signatures were then tested on the data from the 2007–2008 trial, which represents the “testing set.” The expression of a subset of genes contained within the DAMIP predictive signatures using the 2007–2008 and 2008–2009 trials was then quantified by RT-PCR in a third independent trial (2009–2010 trial). The DAMIP model was again used to confirm the predictive signatures. (b) The expression of a subset of genes contained within the predictive signatures generated by the DAMIP model was validated using RT-PCR. There was a statistically significant positive correlation (2,897 XY pairs, Pearson r = 0.68, P-value < 10−11) between the changes in relative gene expression determined by microarray and RT-PCR analysis. Each point represents a single gene at a given time point. (c) Some of the DAMIP gene signatures identified using 2008–2009 trial as training set and 2007–2008 and 2009–2010 trials as validation sets (i.e. DAMIP model 3). The accuracy represents the number of subjects correctly classified as “low responders” or “high responders” (see legend of Fig. 1a).
Figure 6
Figure 6
CAMKIV regulates the antibody response to influenza vaccine. (a) Statistically significant negative correlation between the HAI response at day 28 and the levels of CaMKIV mRNA on PBMCs of vaccinees at day 3 post-vaccination. The left graph represents the TIV vaccinees of 2008–2009 trial (Pearson r = −0.47, P-value (two-tail) = 0.016) and the right graph represents the TIV vaccinees of 2007–2008 trial (Pearson r = −0.73, P-value (two-tail) = 0.024). (b) Statistically significant negative correlation between the number of influenza-specific IgG secreting plasmablasts by ELISPOT at day 7 and the levels of CAMKIV mRNA on PBMCs of vaccinees at day 3 post-vaccination. (c) Phosphorylation of mouse CaMKIV protein after in vitro stimulation of splenocytes with TIV, as determined by western blot. (d) Phosphorylation of CaMKIV protein after in vitro stimulation of human PBMCs treated with TIV for different time points, as determined by western blot. (e) Serum antigen-specific IgG1 (top) and IgG2c (bottom) responses of wild-type (black line) and CamkIV−/− (blue line) mice at day 7, 14 and 28 post-TIV immunization. Student t-test method was used to calculate the statistical significance of each comparison (* = p-value < 0.05, ** = p-value < 0.01). Individual wild type and CamkIV−/− mice are represented by black squares and blue triangles, respectively.

References

    1. Sasaki S, et al. Comparison of the influenza virus-specific effector and memory B-cell responses to immunization of children and adults with live attenuated or inactivated influenza virus vaccines. J Virol. 2007;81:215–228.
    1. Fiore AE, et al. Prevention and control of influenza with vaccines: recommendations of the Advisory Committee on Immunization Practices (ACIP), 2010. MMWR Recomm Rep. 2010;59:1–62.
    1. Sasaki S, et al. Influence of prior influenza vaccination on antibody and B-cell responses. PLoS One. 2008;3:e2975.
    1. Zeman AM, et al. Humoral and cellular immune responses in children given annual immunization with trivalent inactivated influenza vaccine. Pediatr Infect Dis J. 2007;26:107–115.
    1. Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010;33:516–529.
    1. Querec TD, et al. Systems biology approach predicts immunogenicity of the yellow fever vaccine in humans. Nat Immunol. 2009;10:116–125.
    1. Gaucher D, et al. Yellow fever vaccine induces integrated multilineage and polyfunctional immune responses. J Exp Med. 2008;205:3119–3131.
    1. Pulendran B. Learning immunology from the yellow fever vaccine:innate immunity to systems vaccinology. Nat Rev Immunol. 2009;9:741–747.
    1. Monath TP. Yellow fever vaccine. Expert Rev Vaccines. 2005;4:553–574.
    1. Querec T, et al. Yellow fever vaccine YF-17D activates multiple dendritic cell subsets via TLR2, 7, 8, and 9 to stimulate polyvalent immunity. J Exp Med. 2006;203:413–424.
    1. Barrett AD, Teuwen DE. Yellow fever vaccine -how does it work and why do rare cases of serious adverse events take place? Curr Opin Immunol. 2009;21:308–313.
    1. Johnson PR, Jr, Feldman S, Thompson JM, Mahoney JD, Wright PF. Comparison of long-term systemic and secretory antibody responses in children given live, attenuated, or inactivated influenza A vaccine. J Med Virol. 1985;17:325–335.
    1. Beyer WE, Palache AM, de Jong JC, Osterhaus AD. Cold-adapted live influenza vaccine versus inactivated vaccine: systemic vaccine reactions, local and systemic antibody response, and vaccine efficacy. A meta-analysis. Vaccine. 2002;20:1340–1353.
    1. Administration, F.a.D. Guidance for Industry: Clinical Data Needed to Support the Licensure of Pandemic Influenza Vaccines. 2007.
    1. Wrammert J, et al. Rapid cloning of high-affinity human monoclonal antibodies against influenza virus. Nature. 2008;453:667–671.
    1. Takaoka A, Yanai H. Interferon signalling network in innate defence. Cell Microbiol. 2006;8:907–922.
    1. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc NatlAcad Sci U S A. 2001;98:5116–5121.
    1. Iwakoshi NN, et al. Plasma cell differentiation and the unfolded protein response intersect at the transcription factor XBP-1. Nat Immunol. 2003;4:321–329.
    1. Iwakoshi NN, Lee AH, Glimcher LH. The X-box binding protein-1 transcription factor is required for plasma cell differentiation and the unfolded protein response. Immunol Rev. 2003;194:29–38.
    1. Ron D, Walter P. Signal integration in the endoplasmic reticulum unfolded protein response. Nat Rev Mol Cell Biol. 2007;8:519–529.
    1. Ueda Y, et al. Frequencies of dendritic cells (myeloid DC and plasmacytoid DC) and their ratio reduced in pregnant women: comparison with umbilical cord blood and normal healthy adults. Hum Immunol. 2003;64:1144–1151.
    1. Shen-Orr SS, et al. Cell type-specific gene expression differences in complex tissues. Nat Methods. 2010;7:287–289.
    1. Avery DT, et al. BAFF selectively enhances the survival of plasmablasts generated from human memory B cells. J Clin Invest. 2003;112:286–297.
    1. Park SW, et al. The regulatory subunits of PI3K, p85alpha and p85beta, interact with XBP-1 and increase its nuclear translocation. Nat Med. 2010;16:429–437.
    1. Liu B, Li Z. Endoplasmic reticulum HSP90b1 (gp96, grp94) optimizes B-cell function via chaperoning integrin and TLR but not immunoglobulin. Blood. 2008;112:1223–1230.
    1. Apostolou A, Shen Y, Liang Y, Luo J, Fang S. Armet, a UPR-upregulated protein, inhibits cell proliferation and ER stress-induced cell death. Exp Cell Res. 2008;314:2454–2467.
    1. Huleatt JW, et al. Potent immunogenicity and efficacy of a universal influenza vaccine candidate comprising a recombinant fusion protein linking influenza M2e to the TLR5 ligand flagellin. Vaccine. 2008;26:201–214.
    1. Treanor JJ, et al. Safety and immunogenicity of a recombinant hemagglutinin influenza-flagellin fusion vaccine (VAX125) in healthy young adults. Vaccine. 2010;28:8268–8274.
    1. Talbot HK, et al. Immunopotentiation of trivalentinfluenza vaccine when given with VAX102, a recombinant influenza M2e vaccine fused to the TLR5 ligand flagellin. PLoS One. 2010;5:e14442.
    1. He XS, et al. Cellular immune responses in children and adults receiving inactivated or live attenuated influenza vaccines. J Virol. 2006;80:11756–11766.
    1. Le Bon A, et al. Cutting edge: enhancement of antibody responses through direct stimulation of B and T cells by type I IFN. J Immunol. 2006;176:2074–2078.
    1. Lee EK. Large-scale optimization-basedclassification models in medicine and biology. Ann Biomed Eng. 2007;35:1095–1109.
    1. Brooks JP, Lee EK. Analysis of the consistency of a mixed integer programming-based multi-category constrained discriminant model. Annals of Operations Research. 2010;174:147–168.
    1. Sullivan SJ, Jacobson R, Poland GA. Advances in the vaccination of the elderly against influenza: role of a high-dose vaccine. Expert Rev Vaccines. 2010;9:1127–1133.
    1. Anderson KJ, Allen RL. Regulation of T-cell immunity by leucocyte immunoglobulin-like receptors: innate immune receptors for self on antigen-presenting cells. Immunology. 2009;127:8–17.
    1. Thomas R, Matthias T, Witte T. Leukocyte immunoglobulin-like receptors as new players in autoimmunity. Clin Rev Allergy Immunol. 2010;38:159–162.
    1. Brown D, Trowsdale J, Allen R. The LILR family: modulators of innate and adaptive immune pathways in health and disease. Tissue Antigens. 2004;64:215–225.
    1. Krebs J, Wilson A, Kisielow P. Calmodulin-dependent protein kinase IV during T-cell development. Biochem Biophys Res Commun. 1997;241:383–389.
    1. Wang SL, Ribar TJ, Means AR. Expression of Ca(2+)/calmodulin-dependent protein kinase IV (caMKIV) messenger RNA during murine embryogenesis. Cell Growth Differ. 2001;12:351–361.
    1. Anderson KA, Means AR. Defective signaling in a subpopulation of CD4(+) T cells in the absence of Ca(2+)/calmodulin-dependent protein kinase IV. Mol Cell Biol. 2002;22:23–29.
    1. Illario M, et al. Calmodulin-dependent kinase IV links Toll-like receptor 4 signaling with survival pathway of activated dendritic cells. Blood. 2008;111:723–731.
    1. Sato K, et al. Regulation of osteoclast differentiation and function by the CaMK-CREB pathway. Nat Med. 2006;12:1410–1416.
    1. Kitsos CM, et al. Calmodulin-dependent protein kinase IV regulates hematopoietic stem cell maintenance. J Biol Chem. 2005;280:33101–33108.
    1. Pulendran B, Ahmed R. Immunological mechanisms of vaccination. Nat Immunol. 2011;131:509–517.
    1. Moldoveanu Z, Clements ML, Prince SJ, Murphy BR, Mestecky J. Human immune responses to influenza virus vaccines administered by systemic or mucosal routes. Vaccine. 1995;13:1006–1012.
    1. Shubinsky G, Schlesinger M. The CD38 lymphocyte differentiation marker: new insight into its ectoenzymatic activity and its role as a signal transducer. Immunity. 1997;7:315–324.
    1. Deaglio S, Mehta K, Malavasi F. Human CD38: a (r)evolutionary story of enzymes and receptors. Leuk Res. 2001;25:1–12.
    1. Clements ML, Betts RF, Tierney EL, Murphy BR. Serum and nasal wash antibodies associated with resistance to experimental challenge with influenza A wild-type virus. J Clin Microbiol. 1986;24:157–160.
    1. Potter CW, Oxford JS. Determinants of immunity to influenza infection in man. Br Med Bull. 1979;35:69–75.
    1. Hirota Y, et al. Antibody efficacy as a keen index to evaluate influenza vaccine effectiveness. Vaccine. 1997;15:962–967.
    1. Belshe RB. Current status of live attenuated influenza virus vaccine in the US. Virus Res. 2004;103:177–185.
    1. Chen GL, Lamirande EW, Jin H, Kemble G, Subbarao K. Safety, immunogencity, and efficacy of a cold-adapted A/Ann Arbor/6/60 (H2N2) vaccine in mice and ferrets. Virology. 2010;398:109–114.
    1. Crotty S, et al. Cutting edge: long-term B cell memory in humans after smallpox vaccination. J Immunol. 2003;171:4969–4973.
    1. Wu JY, et al. Spermiogenesis and exchange of basic nuclear proteins are impaired in male germ cells lacking Camk4. Nat Genet. 2000;25:448–452.

Source: PubMed

3
Předplatit