Supplementary Note 1:
Reports on digital TCR signaling and digital nature of immediate transcriptional response and escalation in number of responding cells with dose:
1) Au-Yeung, B.B., et al. (2014) A sharp T-cell antigen receptor signaling threshold for T-cell proliferation. Proceedings of the National Academy of Sciences 111, E3679-E3688
2) Kingeter, L.M., et al. (2010) Cutting Edge: TCR Ligation Triggers Digital Activation of NF-κB. The Journal of Immunology 185, 4520-4524
3) Navarro, M.N., et al. (2014) Protein kinase D2 is a digital amplifier of T cell receptor–stimulated diacylglycerol signaling in naïve CD8+ T cells. Science Signaling 7, ra99-ra99
4) Podtschaske, M., et al. (2007) Digital NFATc2 Activation per Cell Transforms Graded T Cell Receptor Activation into an All-or-None IL-2 Expression. PLoS ONE 2, e935
5) Das, J., et al. (2009) Digital Signaling and Hysteresis Characterize Ras Activation in Lymphoid Cells. Cell 136, 337-351
6) Huang, J., et al. (2013) A Single Peptide-Major Histocompatibility Complex Ligand Triggers Digital Cytokine Secretion in CD4+ T Cells. Immunity 39, 846-857
Supplementary Note 2:
Reports used to infer the feed-forward interactions among transcription factors with SUM regulatory logic for target transcription:
1) Best, J.A., et al. (2013) Transcriptional insights into the CD8+ T cell response to infection and memory T cell formation. Nature immunology 14, 404-412
2) Bunting, K., et al. (2007) Genome-wide analysis of gene expression in T cells to identify targets of the NF-kappa B transcription factor c-Rel. Journal of immunology (Baltimore, Md. : 1950) 178, 7097-7109
3) Grumont, R., et al. (2004) The mitogen-induced increase in T cell size involves PKC and NFAT activation of Rel/NF-kappaB-dependent c-myc expression. Immunity 21, 19-30
4) Kane, L.P., et al. (2002) It's all Rel-ative: NF-kappaB and CD28 costimulation of T-cell activation. Open biology 23, 413-420
5) Ramos, J.C., et al. (2007) IRF-4 and c-Rel expression in antiviral-resistant adult T-cell leukemia/lymphoma. Blood 109, 3060-3068
6) Rao, S., et al. (2003) c-Rel is required for chromatin remodeling across the IL-2 gene promoter. Journal of immunology (Baltimore, Md. : 1950) 170, 3724-3731
7) Sen, R. and Smale, S.T. (2010) Selectivity of the NF-{kappa}B response. Cold Spring Harbor perspectives in biology 2, a000257
8) Shindo, H., et al. (2011) Interferon regulatory factor-4 activates IL-2 and IL-4 promoters in cooperation with c-Rel. Cytokine 56, 564-572
9) Laoukili, J., et al. (2005) FoxM1 is required for execution of the mitotic programme and chromosome stability. Nature cell biology 7, 126-136
10) Lefebvre, C., et al. (2010) A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers. Molecular systems biology 6, 377
11) Kurachi, M., et al. (2014) The transcription factor BATF operates as an essential differentiation checkpoint in early effector CD8+ T cells. Nature immunology 15, 373-383
12) Man, K., et al. (2013) The transcription factor IRF4 is essential for TCR affinity-mediated metabolic programming and clonal expansion of T cells. Nature immunology 14, 1155-1165
13) Backer, R.A., et al. (2014) A central role for Notch in effector CD8+ T cell differentiation. Nature Immunology 15, 1143-1151
14) Palomero, T., et al. (2006) NOTCH1 directly regulates c-MYC and activates a feed-forward-loop transcriptional network promoting leukemic cell growth. Proceedings of the National Academy of Sciences of the United States of America 103, 18261-18266
15) Slaninova, V., et al. (2016) Notch stimulates growth by direct regulation of genes involved in the control of glycolysis and the tricarboxylic acid cycle. 6
16) Chou, C., et al. (2014) c-Myc-induced transcription factor AP4 is required for host protection mediated by CD8+ T cells. Nature immunology 15, 884-893
17) Dang, C.V. (2013) MYC, metabolism, cell growth, and tumorigenesis. Cold Spring Harbor perspectives in medicine 3
18) Wang, R., et al. (2011) The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity 35, 871-882
Supplementary Note 3:
Reports demonstrating that negative feedbacks linearize the response:
1) Bachmann, J., et al. (2011) Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range. Molecular systems biology 7, 516
2) Bhalla, U.S., et al. (2002) MAP kinase phosphatase as a locus of flexibility in a mitogen-activated protein kinase signaling network. Science (New York, N.Y.) 297, 1018-1023
3) Madar, D., et al. (2011) Negative auto-regulation increases the input dynamic-range of the arabinose system of Escherichia coli. BMC systems biology 5, 111
4) Nevozhay, D., et al. (2009) Negative autoregulation linearizes the dose-response and suppresses the heterogeneity of gene expression. Proceedings of the National Academy of Sciences of the United States of America 106, 5123-5128
5) Paulsen, M., et al. (2011) Negative feedback in the bone morphogenetic protein 4 (BMP4) synexpression group governs its dynamic signaling range and canalizes development. Proceedings of the National Academy of Sciences of the United States of America 108, 10202-10207
6) Yu, R.C., et al. (2008) Negative feedback that improves information transmission in yeast signalling. Nature 456, 755-761
Supplementary Figure S1: System-wide reduction of transcripts belonging to the motility apparatus during CD8 T cell priming in vivo. a) Organization and information flow in the motility apparatus of leukocytes. b) Average expression level for each functional class relative to the ‘naïve’ state. Only those genes with at least 30% reduction in mRNA at one of the time-points were included, the fractions for which are included in each plot. Standard deviation within the functional class is also plotted. Gene set enrichment analysis revealed many of these classes to be significantly enriched among all the ‘down-regulated’ transcripts in the priming stage (Best JA et al., Nature Immunology 2013).
Supplementary Figure S2: System-wide reduction of transcripts belonging to the motility apparatus during during CD8 T cell priming in vivo. Row-normalized heatmap of expression changes for mRNA belonging to the motility apparatus. Normalization was by using the square root of sum of squares over the time-course for each transcript. Only those messages with at least 30% decrease, relative to ‘naïve’ state, in at least one of the time-points is included for the groups in the bottom row.
Supplementary Figure S3: System-wide reduction of transcripts belonging to the TCR signaling machinery during CD8 T cell priming in vivo. Average expression level for each functional class relative to the ‘naïve’ state is plotted. Only those genes with at least 30% reduction in mRNA in at least one of the time-points were included. The fraction of such instances is included for the class TCR proximal signaling proteins. For the other classes only the number of genes included in the plot is given. Standard deviation within the functional class is also plotted. Gene set enrichment analysis revealed many of these classes to be significantly enriched among all the ‘down-regulated’ transcripts in the priming stage (Best JA et al., Nature Immunology 2013).
Supplementary Figure S4: System-wide reduction of messages belonging to the TCR signaling machinery during CD8 T cell priming in vivo. Row-normalized heatmap of expression changes is shown for each class. Normalization was by using the square root of sum of squares over the time-course for each transcript. Only those messages with at least 30% decrease, relative to ‘naïve’ state, in at least one of the time-points is included in the heatmaps for each class.
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