Identification of molecular signatures from different vaccine adjuvants in chicken by integrative analysis of microarray data.
An adjuvant is an agent that stimulates the immune system and increases the host response to an antigen without itself conferring a specific antigenic effect (Bowersock and Martin, 1999). Effective adjuvants utilize multiple compounds and mechanisms to achieve the desired immunological enhancement such as long lasting antigen depots, immunological presentation of vaccine antigens, and induction of T lymphocyte responses (Reed et al., 2009). As of present, much progress has been made to develop novel adjuvants that augment humoral and cell-mediated immunity by enhancing efficacy of vaccines (Bowersock and Martin, 1999; Newman and Powell, 1995), which is particularly crucial for commercial poultry industries in tackling economically important diseases such as Eimeria protozoa-induced avian coccidiosis (Shirley and Lillehoj, 2012).
Examples of adjuvants used with variety of vaccines include Montanide incomplete Seppic adjuvant (ISA) series, ISA 70 VG (ISA 70) and ISA 71 VG (ISA 71), and Quil A, cholesterol, dimethyl dioctadecyl ammonium bromide, and Carbopol (QCDC) adjuvant complex, whereby the former is a water-in-oil emulsion and the latter is composed of Quil A, cholesterol, dimethyl dioctadecyl ammonium bromide (DDA), and Carbopol (Aucouturier et al., 2006; Cox et al., 2003; Dominowski et al., 2009).
ISA 70 and ISA 71 have been successfully applied to enhance immune response against pathogens of poultry, cattle, and small ruminants (Dupuis et al., 2006). Previous studies have shown that either ISA 70 or ISA 71 in conjunction with the recombinant profilin, which is an Eimeria specific antigen, enhances protective immunity against experimental avian coccidiosis in chicken (Jang et al., 2010; Jang et al., 2011; Lee et al., 2011). Also, other than the Montanide ISA series, improvement in vaccine responses against a variety of veterinary pathogens has been demonstrated in the use of QCDC adjuvants (Dominowski et al., 2009). It has been understood that Carbopol, such as dextran, polyethelyne, glycol, or polyacrylic acid that has been added to the QCDC, improves the solubility of DDA and thus makes the final formulation a highly effective adjuvant. Further incorporation of Bay R1005, a synthetic glycolipid analogue, endows the complex with the ability to stimulate both Th1-and Th2-type immunity, giving the QCDCR adjuvant a broad range of desirable immune enhancing characteristics (Dominowski et al., 2009).
Chickens infected with Eimeria spp. commonly develop protective immunity against reinfection by the homologous parasite, which makes immunization with parasite vaccines a viable method to control coccidiosis (Lillehoj et al., 2000a). Basically, profilin in Eimeria stimulates cell-mediated immunity against experimental avian coccidiosis, which is what makes it a promising vaccine candidate (Lillehoj et al., 2000b; Yarovinsky et al., 2005). In addition, the evidence of profilin shown as a potential immunogenic protein has been published in two studies that, when Montanide ISA series and QCDC formulations were used, efficacy of the profilin vaccine was improved and thus lead to more protective immunity against coccidiosis (Jang et al., 2013). However, molecular signatures related to immune-stimulatory activities of these adjuvants have not been analyzed comparatively.
Therefore, in this study, we attempted to comparatively analyze integrated microarray data from two vaccine adjuvants in experimental coccidiosis model, i.e. ISAs and QCDCs, which confer protective immunity in combination with parasitic antigen, and sought to identify common gene ontology (GO) and pathways that are targeted by these adjuvants. The idea of integrating datasets from independent, but related, sources for a comparative analysis for this study stemmed from the increasing amount of research that has used microarray technology based datasets from publicly available repositories such as Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo), ArrayExpress (http://www.ebi.ac.uk/arrayexpress), and Stanford Microarray Database (http ://smd.princeton.edu).
MATERIALS AND METHODS
Associated microarray data
To investigate common immunological effects of four adjuvants, we used the Agilent Chicken Gene Expression Microarray dataset from two previous studies on vaccination effects that were obtained from GEO. In one of the studies, Montanide ISA 70 VG (ISA70) or Montanide ISA 71 VG (ISA71) with an Eimeria recombinant profilin protein was the experimental adjuvants used to immunize chickens subcutaneously, in comparison with only profilin immunization (accession number GSE40743). The other study used two novel adjuvant formulations, which were a combination of QCDC or QCDCR with a recombinant profilin (accession number GSE24966). The dataset used in this study was in reference to these previous studies, which contains details on immunization procedures (Kim et al., 2012; Jang et al., 2013). To briefly describe the procedure, seven-day-old Ross broiler chickens were subcutaneously immunized with profilin emulsified in each adjuvant or profilin alone. At 7 days post immunization, splenic lymphocytes were prepared from the chickens. Total RNAs were isolated from the cells using Trizol (Invitrogen, Carlsbad, CA, USA) and amplified with cyanine 3 (Cy3)- or Cy5-labeled CTP. The labeled RNAs were then hybridized to a Chicken Gene Expession Microarray (Agilent Technologies, Santa Clara, CA, USA).
Microarray image analysis was performed to analyze immunological effects of adjuvants specifically, thus the four adjuvants were categorized into two groups (Table 1). Adjuvants were grouped according to ISA adjuvants (ISA70 and ISA71) and QCDC adjuvants (QCDC and QCDCR).
Identification and functional analysis of differentially expressed genes
R package 'limma' was used to normalize and qualify microarray images. Median signal intensities were corrected by adaptive background correction (Ritchie et al., 2007) and normalized by locally-weighted scatterplot smoothing method. The log2-transformed fold changes and standard errors were estimated by fitting a linear model and empirical Bayes statistics was applied for smoothing standard errors. Differentially expressed genes (DEG) were filtered by cutoff 0.1 of false discovery rate (FDR), with adjusted p-value of two-sample t-test. Annotation of DEGs and biological function analysis were performed using DAVID Bioinformatics Resources (http://david.abcc. ncifcrf.gov/).
Identification and annotation of differentially expressed genes
In the present study, microarray datasets from two independent studies were combined to analyze the discriminative effects of two different types of adjuvants, Montanide ISA series and QCDC formulations. All adjuvants were administered with recombinant profilin antigens. In the results, ISA adjuvants modified greater number of genes than those of QCDC adjuvants. The numbers of DEGs were 8,932 and 1,761 in the immunization of ISA adjuvants and QCDC adjuvants, respectively. The common DEGs altered by both ISA and QCDC adjuvants were 489 (Figure 1A).
In DEGs annotation analysis, DAVID annotation analysis tool was used. Among 8,932 DEGs from the ISA adjuvants immunization, 3,030 genes (33.9%) were mapped to the chicken gene names in DAVID database. In the treatment of QCDC adjuvants, 439 (24.9%) out of 1,761 DEGs were mapped to the chicken genes in DAVID database. Among the 489 genes, which were altered commonly by both adjuvants, 136 genes (27.8%) were annotated in DAVID (Figure 1B). The annotated DEGs were used to identify their biological functions and the pathways in which the genes are involved.
Biological function analysis
In the GO analysis, 165 and 27 terms of biological process (BPs) were significantly identified from the DEGs by the treatment of ISA and QCDC adjuvants, respectively. The GO terms of BP modified by ISA or QCDC adjuvants were grouped into 23 and 8 upper categories (Table 2). Among the upper categories, six terms, i.e., "Anatomical structure development", "Cell death", "Regulation of metabolic process", "Response to stimulus", "Signal transduction", and "Single organism cellular process" were common to both adjuvant groups. The significant BPs related with the terms of "Response to stimulus" and "Cell death" were shown in Table 3 and Figure 2, respectively. All significant BPs identified were listed in Supplementary Table S1.
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway terms enriched by DEGs from the treatment of two different adjuvant groups are listed in Table 4. Both adjuvant groups showed common effects on the pathway for "Regulation of actin cytoskeleton". QCDC adjuvants altered genes involved in "Cell adhesion molecules (CAMs)" pathway and ISA adjuvants modified the pathways related with "Spliceosome", "Ubiquitin mediated proteolysis", "Adherens junction", "Lysosome", "Natural killer (NK) cell mediated cytotoxicity", "Cell cycle", "Endocytosis", and "Focal adhesion".
For the comparative analysis of the effects of two different adjuvant types, we collected microarray datasets from the independent trials for each adjuvant groups, ISAs and QCDCs, and identified GO terms and pathways modified by the DEGs.
In the present study, the most enriched categories of BP affected by two adjuvants, showing 6 categories that are commonly affected by two adjuvants. But, further detailed analysis revealed that the categories consisting of the same BPs in both adjuvants are quite specific, rather than common. For example, in the term of "Response to stimulus", no BPs was identified simultaneously in the two different adjuvant groups (Table 3). Generally, the QCDC adjuvants showed effects on innate immune response and immune response to external stimulus, such as "Response to toxin" and "Response to bacterium". For the immune response to toxins, a good humoral immune response is required in the adjuvants. Most adjuvants on the market today mainly activate the humoral immune response. Nevertheless, it is obvious that the introduction of cell-mediated immune response by adjuvants is beneficial to control bacterial infection, where cytotoxic T cells and Th1 cells mediate these responses (Leclerc, 2003). In this sense, ISCOM, a component of QCDC adjuvants, has been known to generate both strong humoral and cellular immune responses in an extensive range of animal species (Drane et al., 2007). The ISCOMATRIX adjuvant has also shown to be safe and well tolerated as well as immunogenic, generating both antibody (Ab) and CD4+ and CD8+ T cell responses (Drane et al., 2007). Also, DDA is reported to promote both strong cell mediated immune responses and humoral immune responses, which are essential for the induction of protective immunity against most diseases (Davidsen et al., 2005).
As for the adjuvants of ISA series, these modified the BPs that regulate cell movement such as cell locomotion, chemotaxis, and cell migration. Although ISA and QCDC adjuvants modified biological functions related to the regulation of cell death and apoptosis, they showed a different manner in mode of action. The effects of ISA adjuvants on cell death were both of positive and negative regulation while the QCDC adjuvants had no function in regulating cell death negatively. Such apoptotic and necrotic effects are reported to be associated with emulsion-type vaccine adjuvants such as the ISA series and QCDC whereby both are composed of various oils and surfactants (Yang et al., 2004). The mechanism behind the surfactants is that their amphiphilic nature adsorbs not only the oil/water interface in the emulsion, but also biological membranes, resulting in an increase in surface pressure that thus lead to apoptosis and necrosis of the cells (Yang et al., 2004). This suggests that the surfactants in ISA adjuvants and Quil A in QCDC adjuvants could induce apoptosis or cell death during immunization. In the results of pathway analysis, "Adherens junctions" and "Focal adhesion" pathways were the two main types of junction that were modified by ISA adjuvants, which are known to mediate adhesion in epithelial cells (Yeatman, 2004). Cell-cell adherens junctions are important for maintaining tissue architecture and cell polarity and can limit cell movement and proliferation. Cell-matrix adhesions, also called focal adhesions, play essential roles in important BPs including cell motility, cell proliferation, cell differentiation, regulation of gene expression and cell survival. Collectively, the ISA adjuvants may have effects on cell mobility and mitigate cytotoxicity through the cellular junction pathways.
In addition, lysosomal and endocytic reactions were also modified by ISA adjuvants. In the case of lysosomes, the lysosomal enzymes' important role in the inflammatory process has been documented in previous studies in arthritic condition induced by injection of Freund's complete adjuvant (FCA) in rats (Anderson, 1970; Reddy and Dhar, 1988; Geetha and Varalakshmi, 1999). When endocytosis takes place, adjuvants first exert their targeting mechanism by binding to antigens and the adjuvant-antigen complex is delivered to antigen-presenting cells (APCs) to form aggregates that are then engulfed by APCs to form endosomes (Cox and Coulter, 1997; Zamze et al., 2002). More effective targeting can be achieved by using adjuvants with residues that are recognized by receptors on APCs such as the mannose receptor that belongs to the endocytic pattern recognition receptors (PRRs) that bind compounds containing mannose, N-acetylglucosamine, or fucose residues and sulfated oligosaccharides (Stahl and Ezekowitz, 1998).
The ISA adjuvants' functions related with cellular response to oxidative stress shown from our result can be used to partly explain the immune-stimulatory properties of adjuvants that induce inflammation and oxidative stress in the host animal (Kumar and Roy, 2007). An example can be drawn from previous studies that showed that intra-articular injection of a well-known adjuvant, i.e., FCA, induced inflammation as well as immune response and produced features that resembled rheumatoid arthritis in humans. Such acute inflammatory response induced by FCA is associated with leukocyte infiltration, mast cell activation, and release of cytokines and free radicals (Nigrovic and Lee, 2005; Yamada et al., 2006). Despite the shared similarity both ISA adjuvants and FCA and FIA (Freund's incomplete adjuvant) have with respect to antibody responses, the fact that less inflammatory response is induced by ISA adjuvants relative to FCA and FIA needs to be taken into account (Johnston et al., 1991; Leenaars et al., 1994; Leenaars et al., 1995; Leenaars et al., 1998).
In the pathway analysis, QCDC adjuvants altered genes involved in "CAMs" pathway. Inflammatory and immune responses involve adhesive interactions that mediate migration of cells to sites of inflammation and the effector functions of cell within the lesions. Therefore, CAMs, as complex proteins expressed on the cell surface and precisely regulated by cytokines and other biologic response modifiers, are versatile mediators of the complex dynamics of cell interactions in the inflammatory/immune response (Crawford and Watanabe, 1994).
In conclusion, the integrative analysis of microarray datasets from the treatment of two different types of adjuvants, ISA series and QCDC formulations, has provided discriminative and common molecular signatures as well as aided the distinction of immunological functions of the two adjuvant groups in chicken. Although much progress has been undertaken in the formulation of novel adjuvants that augment the immunogenicity of protein vaccines, very little information is available in poultry (Baldridge and Ward, 1997; Gupta and Siber, 1995; Richards et al., 1996). Therefore, this study could contribute to the selection of appropriate adjuvants according to the types of vaccines or diseases as well as the development of efficient vaccine adjuvants in poultry industry. Furthermore, the potent immune adjuvants might promise another usefulness of vaccine as therapeutic agents rather than prophylactic agents.
Limitations such as small sample size and limited case numbers are weaknesses of this study; however, to our knowledge, this is the first integrative approach to identify molecular signatures impacted by adjuvant in livestock, especially in chicken. Therefore, this study could serve as an informative framework to integrated microarray data to identify molecular signatures that can be used to develop precise adjuvants based on their immunological functions.
CONFLICT OF INTEREST
We certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.
The authors thank Dr. Song, Ki Duk and Ahn, Hyun Ju for their significant contribution to this research. This work was supported by a grant from the Next-Generation BioGreen 21 Program (No. PJ01104401), Rural
Development Administration, Republic of Korea.
Anderson, A. J. 1970. Lysosomal enzyme activity in rats with adjuvant-induced arthritis. Ann. Rheum. Dis. 29:307-13.
Aucouturier, J., S. Ascarateil, and L. Dupuis. 2006. The use of oil adjuvants in therapeutic vaccines. Vaccine 24 (Suppl 2):S44S45.
Baldridge, J. R. and J. R. Ward. 1997. Effective adjuvants for the induction of antigen-specific delayed-type hypersensitivity. Vaccine 15:395-401.
Bowersock, T. L. and S. Martin. 1999. Vaccine delivery to animals. Adv. Drug Deliv. Rev. 38:167-194.
Cox, J. C. and A. R. Coulter. 1997. Adjuvants--A classification and review of their modes of action. Vaccine 15:248-256.
Cox, S. J., N. Aggarwal, R. J. Statham, and P. V. Barnett. 2003. Longevity of antibody and cytokine responses following vaccination with high potency emergency FMD vaccines. Vaccine 21:1336-1347.
Crawford, J. M. and K. Watanabe. 1994. Cell adhesion molecules in inflammation and immunity: Relevance to periodontal diseases. Crit. Rev. Oral Biol. Med. 5:91-123.
Davidsen, J., I. Rosenkrands, D. Christensen, A. Vangala, D. Kirby, Y. Perrie, E. M. Agger, and P. Andersen. 2005. Characterization of cationic liposomes based on dimethyldioctadecylammonium and synthetic cord factor from M. tuberculosis (trehalose 6,6'-dibehenate)-a novel adjuvant inducing both strong CMI and antibody responses. Biochim. Biophys. Acta Biomembranes 1718:22-31.
Dominowski, P. J., R. M. Mannan, R. L. Krebs, J. R. Thompson, T. A. Childers, M. K. Olsen, J. R. J. Yancey, R. Weeratna, S. Zhang, and C. M. Bagi. 2009. Novel adjuvant compositions. US 2009/0324641 A1. Pfizer Inc., New York, NY , USA.
Drane, D., C. Gittleson, J. Boyle, and E. Maraskovsky. 2007. ISCOMATRIX adjuvant for prophylactic and therapeutic vaccines. Expert Rev. Vaccines 6:761-772.
Dupuis, L., S. Ascarateil, J. Aucouturier, and V. Ganne. 2006. SEPPIC vaccine adjuvants for poultry. Ann. NY Acad. Sci. 1081:202-205.
Geetha, T. and P. Varalakshmi. 1999. Effect of lupeol and lupeol linoleate on lysosomal enzymes and collagen in adjuvant-induced arthritis in rats. Mol. Cell. Biochem. 201:83-87.
Gupta, R. K. and G R. Siber. 1995. Adjuvants for human vaccines--current status, problems and future prospects. Vaccine 13:1263-1276.
Jang, S. I., D. K. Kim, H. S. Lillehoj, S. H. Lee, K. W. Lee, F. Bertrand, L. Dupuis, S. Deville, J. Ben Arous, and E. P. Lillehoj. 2013. Evaluation of Montanide ISA 71 VG adjuvant during profilin vaccination against experimental coccidiosis. PLoS One 8(4):e59786.
Jang, S. I., H. S. Lillehoj, S. H. Lee, K. W. Lee, E. P. Lillehoj, F. Bertrand, L. Dupuis, and S. Deville. 2011. Mucosal immunity against Eimeria acervulina infection in broiler chickens following oral immunization with profilin in Montanide adjuvants. Exp. Parasitol. 129:36-41.
Jang, S. I., H. S. Lillehoj, S. H. Lee, K. W. Lee, M. S. Park, G R. Bauchan, E. P. Lillehoj, F. Bertrand, L. Dupuis, and S. Deville. 2010. Immunoenhancing effects of Montanide ISA oil-based adjuvants on recombinant coccidia antigen vaccination against Eimeria acervulina infection. Vet. Parasitol. 172:221-228.
Johnston, B. A., H. Eisen, and D. Fry. 1991. An evaluation of several adjuvant emulsion regimens for the production of polyclonal antisera in rabbits. Lab. Anim. Sci. 41:15-21.
Kim, D. K., H. S. Lillehoj, S. H. Lee, P. Dominowski, R. J. Yancey, and E. P. Lillehoj. 2012. Effects of novel vaccine/adjuvant complexes on the protective immunity against Eimeria acervulina and transcriptome profiles. Avian Dis. 56:97-109.
Kumar, V. L. and S. Roy. 2007. Calotropis procera latex extract affords protection against inflammation and oxidative stress in Freund's complete adjuvant-induced monoarthritis in rats. Mediators Inflamm. Article ID 47523.
Leclerc, C. 2003. New approaches in vaccine development. Comp. Immunol. Microbiol. Infect. Dis. 26:329-341.
Lee, K. W., H. S. Lillehoj, S. H. Lee, S. I. Jang, G. D. Ritter, D. A. Bautista, and E. P. Lillehoj. 2011. Impact of fresh or used litter on the posthatch immune system of commercial broilers. Avian Dis. 55:539-544.
Leenaars, P. P. A. M., C. F. M. Hendriksen, A. F. Angulo, M. A. Koedam, and E. Claassen. 1994. Evaluation of several adjuvants as alternatives to the use of Freund's adjuvant in rabbits. Vet. Immunol. Immunopathol. 40:225-241.
Leenaars, P. P., C. F. Hendriksen, M. A. Koedam, I. Claassen, and E. Claassen. 1995. Comparison of adjuvants for immune potentiating properties and side effects in mice. Vet. Immunol. Immunopathol. 48:123-138.
Leenaars, P. P., M. A. Koedam, P. W. Wester, V. Baumans, E. Claassen, and C. F. Hendriksen. 1998. Assessment of side effects induced by injection of different adjuvant/antigen combinations in rabbits and mice. Lab. Anim. 32:387-406.
Lillehoj, E. P., C. H. Yun, and H. S. Lillehoj. 2000a. Vaccines against the avian enteropathogens Eimeria, Cryptosporidium, and Salmonella. Anim. Health Res. Rev. 1:47-65.
Lillehoj, H. S., K. D. Choi, M. C. Jenkins, V. N. Vakharia, K. D. Song, J. Y Han, and E. P. Lillehoj. 2000b. A recombinant Eimeria protein inducing interferon-gamma production: Comparison of different gene expression systems and immunization strategies for vaccination against coccidiosis. Avian Dis. 44:379-389.
Newman, M. J. and M. F. Powell. 1995. Immunological and formulation design considerations for subunit vaccines. Pharm. Biotechnol. 6:1-42.
Nigrovic, P. A. and D. M. Lee. 2005. Mast cells in inflammatory arthritis. Arthritis Res. Ther. 7:1-11.
Reddy, G. K. and S. C. Dhar. 1988. Studies on carbohydrate moieties of glycoproteins in established adjuvant induced arthritis. Agents Actions 25:63-70.
Reed, S. G., S. Bertholet, R. N. Coler, and M. Friede. 2009. New horizons in adjuvants for vaccine development. Trends Immunol. 30:23-32.
Richards, R. L., C. R. Alving, and N. M. Wassef. 1996. Liposomal subunit vaccines: Effects of lipid A and aluminum hydroxide on immunogenicity. J. Pharm. Sci 85:1286-1289.
Ritchie, M. E., J. Silver, A. Oshlack, M. Holmes, D. Diyagama, A. Holloway, and G. K. Smyth. 2007. A comparison of background correction methods for two-colour microarrays. Bioinformatics 23:2700-2707.
Shirley, M. W. and H. S. Lillehoj. 2012. The long view: A selective review of 40 years of coccidiosis research. Avian Pathol. 41:111-121.
Stahl, P. D. and R. A. B. Ezekowitz. 1998. The mannose receptor is a pattern recognition receptor involved in host defense. Curr. Opin. Immunol. 10:50-55.
Yamada, K., T. Nakamura, and H. Utsumi. 2006. Enhanced intraarticular free radical reactions in adjuvant arthritis rats. Free Radic. Res. 40:455-460.
Yang, Y W., C. A. Wu, and W. J. W. Morrow. 2004. Cell death induced by vaccine adjuvants containing surfactants. Vaccine 22:1524-1536.
Yarovinsky, F., D. Zhang, J. F. Andersen, G. L. Bannenberg, C. N. Serhan, M. S. Hayden, S. Hieny, F. S. Sutterwala, R. A. Flavell, S. Ghosh, and A. Sher. 2005. TLR11 activation of dendritic cells by a protozoan profilin-like protein. Science 308:16261629.
Yeatman, T. J. 2004. A renaissance for SRC. Nat. Rev. Cancer 4:470-480.
Zamze, S., L. Martinez-Pomares, H. Jones, P. R. Taylor, R. J. Stillion, S. Gordon, and S. Y C. Wong. 2002. Recognition of bacterial capsular polysaccharides and lipopolysaccharides by the macrophage mannose receptor. J. Biol. Chem. 277:4161341623.
Supplementary Table S1. Significant biological process (BPs) from differentially expressed genes by the treatment of ISA and QCDC adjuvants Categories Adjuvants Biological process P-value Anatomical ISA Angiogenesis 7.26E-04 structure Vasculature development 7.36E-04 development Blood vessel morphogenesis 1.24E-03 Blood vessel development 1.53E-03 Heart development 1.20E-02 Cell motion 1.93E-02 In utero embryonic 4.19E-02 development Liver development 4.52E-02 QCDC Gut development 1.65E-02 Cell death ISA Regulation of programmed 2.49E-05 cell death Regulation of cell death 2.96E-05 Regulation of apoptosis 4.80E-05 Negative regulation of 1.42E-03 cell death Negative regulation of 1.42E-03 programmed cell death Negative regulation 2.00E-03 of apoptosis Programmed cell death 6.40E-03 Apoptosis 7.51E-03 Death 9.84E-03 Cell death 1.32E-02 Regulation of neuron 1.55E-02 apoptosis Positive regulation 1.93E-02 of apoptosis Positive regulation of 1.93E-02 programmed cell death Positive regulation of 2.23E-02 cell death Anti-apoptosis 3.80E-02 QCDC Regulation of apoptosis 1.16E-02 Regulation of programmed 1.35E-02 cell death Regulation of cell death 1.40E-02 Positive regulation 1.69E-02 of apoptosis Positive regulation of 1.69E-02 programmed cell death Positive regulation 1.79E-02 of cell death Regulation of ISA Positive regulation of 1.26E-03 metabolic macromolecule process metabolic process Regulation of cellular 2.08E-03 protein metabolic process Regulation of 4.62E-03 phosphorylation Regulation of kinase 5.19E-03 activity Regulation of phosphate 5.30E-03 metabolic process Regulation of phosphorus 5.30E-03 metabolic process Regulation of protein 7.32E-03 kinase activity Regulation of transferase 7.41E-03 activity Negative regulation of 7.65E-03 macromolecule metabolic process Regulation of translation 9.95E-03 Regulation of peptidyl- 1.32E-02 tyrosine phosphorylation Negative regulation of 1.50E-02 kinase activity Negative regulation of 1.50E-02 protein kinase activity Negative regulation of 1.58E-02 molecular function Positive regulation of 2.10E-02 DNA metabolic process Positive regulation of 2.17E-02 nucleobase, nucleoside, nucleotide and nucleic acid metabolic process Negative regulation of 2.42E-02 cellular protein metabolic process Negative regulation of 2.42E-02 protein metabolic process Negative regulation of 2.45E-02 biosynthetic process Positive regulation of 2.54E-02 protein kinase cascade Regulation of system 2.72E-02 process Positive regulation of 2.74E-02 cellular biosynthetic process Negative regulation of 2.84E-02 transferase activity Positive regulation of 2.98E-02 biosynthetic process Negative regulation of 3.02E-02 catalytic activity Positive regulation of 3.20E-02 macromolecule biosynthetic process Regulation of protein 3.24E-02 kinase cascade Positive regulation of 3.26E-02 cellular protein metabolic process Positive regulation of 3.60E-02 nitrogen compound metabolic process Positive regulation of 3.86E-02 protein metabolic process Negative regulation of 3.93E-02 nucleobase, nucleoside, nucleotide and nucleic acid metabolic process Negative regulation of 4.06E-02 macromolecule biosynthetic process Negative regulation of 4.32E-02 cellular biosynthetic process Negative regulation of 4.80E-02 nitrogen compound metabolic process Positive regulation of 4.96E-02 catalytic activity QCDC Regulation of 1.23E-02 phosphorylation Regulation of phosphate 1.57E-02 metabolic process Regulation of phosphorus 1.57E-02 metabolic process Positive regulation of 4.56E-02 catalytic activity Positive regulation of 3.34E-02 molecular function Response to ISA Cellular response to 2.69E-04 stimulus stress Response to oxidative 2.06E-03 stress Positive regulation 4.61E-03 of locomotion Positive regulation 7.27E-03 of chemotaxis Regulation of chemotaxis 7.27E-03 Chemotaxis 9.95E-03 Taxis 9.95E-03 Positive regulation 1.20E-02 of behavior Regulation of behavior 1.20E-02 Response to tumor 1.74E-02 necrosis factor Cellular response to 2.02E-02 oxidative stress Positive regulation of 3.17E-02 cell migration Response to inorganic 3.34E-02 substance Positive regulation of 3.41E-02 cell motion Fibroblast growth factor 3.42E-02 receptor signaling pathway QCDC Immune response 9.48E-04 Response to toxin 1.78E-02 Defense response 2.01E-02 Response to bacterium 4.49E-02 Innate immune response 4.85E-02 Signal ISA Positive regulation of 4.18E-04 transduction signal transduction Positive regulation of 4.49E-04 cell communication Small GTPase mediated 1.45E-02 signal transduction Intracellular 2.30E-02 signaling cascade Positive regulation of 3.42E-02 calcium-mediated signaling Integrin-mediated 4.86E-02 signaling pathway QCDC Intracellular signaling 2.21E-02 cascade Single organism ISA Cell cycle 2.53E-02 cellular Cell cycle process 4.44E-02 process QCDC Collagen fibril 4.30E-02 organization Categories Adjuvants Biological process Number of genes Anatomical ISA Angiogenesis 21 structure Vasculature development 34 development Blood vessel morphogenesis 28 Blood vessel development 32 Heart development 30 Cell motion 39 In utero embryonic 23 development Liver development 7 QCDC Gut development 4 Cell death ISA Regulation of programmed 69 cell death Regulation of cell death 69 Regulation of apoptosis 67 Negative regulation of 36 cell death Negative regulation of 36 programmed cell death Negative regulation 35 of apoptosis Programmed cell death 33 Apoptosis 32 Death 35 Cell death 34 Regulation of neuron 12 apoptosis Positive regulation 27 of apoptosis Positive regulation of 27 programmed cell death Positive regulation of 27 cell death Anti-apoptosis 15 QCDC Regulation of apoptosis 14 Regulation of programmed 14 cell death Regulation of cell death 14 Positive regulation 8 of apoptosis Positive regulation of 8 programmed cell death Positive regulation 8 of cell death Regulation of ISA Positive regulation of 77 metabolic macromolecule process metabolic process Regulation of cellular 38 protein metabolic process Regulation of 38 phosphorylation Regulation of kinase 28 activity Regulation of phosphate 39 metabolic process Regulation of phosphorus 39 metabolic process Regulation of protein 27 kinase activity Regulation of transferase 28 activity Negative regulation of 52 macromolecule metabolic process Regulation of translation 13 Regulation of peptidyl- 11 tyrosine phosphorylation Negative regulation of 10 kinase activity Negative regulation of 10 protein kinase activity Negative regulation of 19 molecular function Positive regulation of 10 DNA metabolic process Positive regulation of 57 nucleobase, nucleoside, nucleotide and nucleic acid metabolic process Negative regulation of 14 cellular protein metabolic process Negative regulation of 14 protein metabolic process Negative regulation of 42 biosynthetic process Positive regulation of 15 protein kinase cascade Regulation of system 23 process Positive regulation of 60 cellular biosynthetic process Negative regulation of 10 transferase activity Positive regulation of 60 biosynthetic process Negative regulation of 14 catalytic activity Positive regulation of 58 macromolecule biosynthetic process Regulation of protein 17 kinase cascade Positive regulation of 18 cellular protein metabolic process Positive regulation of 57 nitrogen compound metabolic process Positive regulation of 18 protein metabolic process Negative regulation of 37 nucleobase, nucleoside, nucleotide and nucleic acid metabolic process Negative regulation of 39 macromolecule biosynthetic process Negative regulation of 40 cellular biosynthetic process Negative regulation of 37 nitrogen compound metabolic process Positive regulation of 30 catalytic activity QCDC Regulation of 10 phosphorylation Regulation of phosphate 10 metabolic process Regulation of phosphorus 10 metabolic process Positive regulation of 8 catalytic activity Positive regulation of 9 molecular function Response to ISA Cellular response to 53 stimulus stress Response to oxidative 15 stress Positive regulation 14 of locomotion Positive regulation 8 of chemotaxis Regulation of chemotaxis 8 Chemotaxis 13 Taxis 13 Positive regulation 8 of behavior Regulation of behavior 8 Response to tumor 5 necrosis factor Cellular response to 6 oxidative stress Positive regulation of 11 cell migration Response to inorganic 9 substance Positive regulation of 12 cell motion Fibroblast growth factor 5 receptor signaling pathway QCDC Immune response 13 Response to toxin 3 Defense response 8 Response to bacterium 5 Innate immune response 4 Signal ISA Positive regulation of 32 transduction signal transduction Positive regulation of 33 cell communication Small GTPase mediated 36 signal transduction Intracellular 93 signaling cascade Positive regulation of 5 calcium-mediated signaling Integrin-mediated 10 signaling pathway QCDC Intracellular signaling 20 cascade Single organism ISA Cell cycle 41 cellular Cell cycle process 30 process QCDC Collagen fibril 3 organization
Duk Kyung Kim (1), Kyeong Hye Won, Seung Hyun Moon, and Hak-Kyo Lee *
Department of Animal Biotechnology, Chonbuk National University, Jeonju 561-756, Korea
* Corresponding Author: Hak-Kyo Lee. Tel: +82-63-270-2548, Fax: +82-63-270-2614, E-mail: firstname.lastname@example.org
(1) C&K Genomics, Seoul 151-919, Korea.
Submitted Dec. 8, 2014; Revised Jan. 9, 2015; Accepted Feb. 11, 2015
Table 1. Designs used in microarray image analysis using R 'limma ' package Adjuvants group GEO series No. Case Control ISA adjuvants GSE40743 ISA70+profilin Profilin ISA71+profilin QCDC adjuvants GSE24966 QCDC+profilin Profilin QCDCR+profilin Adjuvants group Reference ISA adjuvants Jang et al. (2013) QCDC adjuvants Kim et al. (2012) ISA, incomplete Seppic adjuvant; QCDC, Quil A, cholesterol, dimethyl dioctadecyl ammonium bromide, and Carbopol. Table 2. Categories for the significant biological processes identified from DEGs in the treatment of two different adjuvant groups ISA adjuvants QCDC adjuvants Anatomical structure development Anatomical structure development Cell death Cell death Regulation of metabolic process Regulation of metabolic process Response to stimulus Response to stimulus Signal transduction Signal transduction Single organism cellular process Single-organism cellular process Biological regulation Regulation of cellular process Cell adhesion Single-multicellular organism Cell developmental process process Cellular component organization Cellular metabolic process Cellular process Circulatory system process Immune system process Macromolecule localization Macromolecule metabolic process Metabolic process Organelle organization Protein metabolic process Regulation of biological process Regulation of cell communication Regulation of transport RNA metabolic process DEGs, differentially expressed genes; ISA, incomplete Seppic adjuvant; QCDC, Quil A, cholesterol, dimethyl dioctadecyl ammonium bromide, and Carbopol. Table 3. Significant biological processes for DEGs in the treatment of adjuvants which were categorized to the term of "Response to stimulus" Adjuvants group Biological process p-value ISA adjuvants Cellular response to stress 2.69E-04 Response to oxidative stress 2.06E-03 Positive regulation of locomotion 4.61E-03 Positive regulation of chemotaxis 7.27E-03 Regulation of chemotaxis 7.27E-03 Chemotaxis 9.95E-03 Taxis 9.95E-03 Positive regulation of behavior 1.20E-02 Regulation of behavior 1.20E-02 Response to tumor necrosis factor 1.74E-02 Cellular response to oxidative stress 2.02E-02 Positive regulation of cell migration 3.17E-02 Response to inorganic substance 3.34E-02 Positive regulation of cell motion 3.41E-02 Fibroblast growth factor receptor 3.42E-02 signaling pathway QCDC adjuvants Immune response 9.48E-04 Response to toxin 1.78E-02 Defense response 2.01E-02 Response to bacterium 4.49E-02 Innate immune response 4.85E-02 Adjuvants group Biological process No. of genes ISA adjuvants Cellular response to stress 53 Response to oxidative stress 15 Positive regulation of locomotion 14 Positive regulation of chemotaxis 8 Regulation of chemotaxis 8 Chemotaxis 13 Taxis 13 Positive regulation of behavior 8 Regulation of behavior 8 Response to tumor necrosis factor 5 Cellular response to oxidative stress 6 Positive regulation of cell migration 11 Response to inorganic substance 9 Positive regulation of cell motion 12 Fibroblast growth factor receptor 5 signaling pathway QCDC adjuvants Immune response 13 Response to toxin 3 Defense response 8 Response to bacterium 5 Innate immune response 4 DEGs, differentially expressed genes; ISA, incomplete Seppic adjuvant; QCDC, Quil A, cholesterol, dimethyl dioctadecyl ammonium bromide, and Carbopol. Table 4. Significantly changed pathways from the DEGs in the treatment of ISA adjuvants or QCDC adjuvants Adjuvants KEGG pathway p-value group ISA adjuvants Spliceosome 4.34E-04 Ubiquitin mediated proteolysis 5.86E-03 Adherens junction 9.53E-03 Lysosome 1.86E-02 Natural killer cell mediated cytotoxicity 1.93E-02 Cell cycle 2.49E-02 Endocytosis 2.74E-02 Focal adhesion 2.81E-02 Regulation of actin cytoskeleton 3.44E-02 QCDC adjuvants Cell adhesion molecules (CAMs) 3.61E-02 Regulation of actin cytoskeleton 4.91E-02 Adjuvants KEGG pathway Number group of genes ISA adjuvants Spliceosome 38 Ubiquitin mediated proteolysis 38 Adherens junction 24 Lysosome 30 Natural killer cell mediated cytotoxicity 23 Cell cycle 33 Endocytosis 47 Focal adhesion 49 Regulation of actin cytoskeleton 48 QCDC adjuvants Cell adhesion molecules (CAMs) 8 Regulation of actin cytoskeleton 11 DEGs, differentially expressed genes; ISA, incomplete Seppic adjuvant; QCDC, Quil A, cholesterol, dimethyl dioctadecyl ammonium bromide, and Carbopol; KEGG, Kyoto Encyclopedia of Genes and Genomes. Figure 1. Differentially expressed genes (DEGs) and their annotation. (A) Venn diagram showing the number of DEGs by the treatment of two different types of adjuvants. False discovery rate (FDR) <0.1, (B) DEGs mapped to the chicken gene names in DAVID database. (B) No. of DEGs DEGs Mapped DEGs ISA 8932 3030 QCDC 1761 439 ISA & QCDC 489 136 Note: Table made from bar graph.
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|Author:||Kim, Duk Kyung; Won, Kyeong Hye; Moon, Seung Hyun; Lee, Hak-Kyo|
|Publication:||Asian - Australasian Journal of Animal Sciences|
|Date:||Jul 1, 2016|
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