bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

1 Fcrl5 and T-bet define influenza-specific memory B cells that predict long-lived antibody 2 responses 3 4 Anoma Nellore1, Christopher D. Scharer2, Rodney G. King3, Christopher M. Tipton4, Esther 5 Zumaquero3, Christopher Fucile3,5, Betty Mousseau3, John E. Bradley6, Kevin Macon3, Tian Mi2, 6 Paul A. Goepfert1,3, John F. Kearney,3 Jeremy M. Boss,2 Troy D. Randall6, Ignacio Sanz4, 7 Alexander Rosenberg3,5, Frances E. Lund3 8 9 10 11 1Dept. of Medicine, Division of Infectious Disease, 3Dept. of Microbiology, 5Informatics Institute, 12 6Dept of Medicine, Division of Clinical Immunology and Rheumatology, at The University of 13 Alabama at Birmingham, Birmingham, AL 35294 USA 14 15 2Dept. of Microbiology and Immunology and 4Department of Medicine, Division of 16 Rheumatology, at Emory University, Atlanta, GA 30322, USA 17 18 19 20 21 22 23 24 25 26 27 28 Lead Contact and to whom correspondence should be addressed: [email protected] 29 30 Mailing address: Frances E. Lund, PhD 31 Charles H. McCauley Professor and Chair 32 Dept of Microbiology 33 University of Alabama at Birmingham (UAB) 34 Dept of Microbiology 35 University of Alabama at Birmingham (UAB) 36 276 BBRB Box 11 37 1720 2nd Avenue South 38 Birmingham AL 35294-2170 39 40 SHORT RUNNING TITLE: Effector memory B cell development after influenza vaccination 41 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

42 Abstract: Early surrogates for long-lived immunity after inactivated influenza vaccination (IIV) 43 are lacking. Antigen-specific memory B cells (Bmem) after IIV have been recently identified. We 44 show that the antigen-specific Bmem compartment after IIV is heterogenous and comprises a 45 clonotypically and transcriptionally distinct T-bethi subset that persists in circulation over time 46 after vaccination and exclusively correlates with the long-lived antibody response. We 47 demonstrate that this subset has an effector memory transcriptome and is epigenetically 48 remodeled to facilitate intracellular immunoglobulin production. Finally, via clonal sharing, we 49 show an enriched in vivo ontologic relationship between the secondary plasmablast response 50 that develops after vaccine boost and the T-bethi fraction of the flu-specific Bmem response that 51 forms after initial prime. Collectively, our data identify a novel biomarker of durable humoral 52 immunity after influenza vaccination. 53 54 55 Keywords: T-bet, memory B cells, plasmablasts, influenza vaccination, durable immunity 56 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

57 Introduction: 58 After inactivated influenza vaccination (IIV), durable humoral immunity is mediated by 59 long-lived antibody (Ab) secreting cells (ASCs) and memory B cells (Bmem).1 In the influenza 60 experienced adult, inactivated influenza vaccination (IIV) mobilizes pre-existing hemagglutinin 61 (HA) antigen-specific memory B cell (Bmem) subsets.2 These responding Bmem may assume 62 different fates. They may proliferate and affinity mature in the germinal center (GC) response to 63 produce daughter cohorts of HA-specific Bmem; they may die immediately upon activation; they 64 may directly differentiate into ASCs; or they may persist as long-term memory. The early cues 65 that direct vaccine-elicited antigen-specific Bmem toward any of these various fates and the 66 relationship of these Bmem fate decisions to the development of durable humoral immunity are 67 not completely clear.

68 Traditionally defined according to expression of the canonical memory marker, CD27,3-6 69 human Bmem are now appreciated to be a heterogeneous subset by transcriptional 70 programming, differentiation capacity and responsiveness to antigen. For instance, a subset of 71 atypical Bmem that express the lineage defining transcription factor (TF), T-bet, have been 72 identified in the context of infection, vaccination, aging and autoimmunity.7 We recently reported 73 in a murine model of influenza infection that T-bet expression in flu-specific B cells as necessary 74 for the development of long-lived ASCs to primary influenza infection as well as for the 75 development of the secondary ASC (plasmablast or PB) in response to challenge infection.8 76 This finding led us to query the relationship between vaccine-elicited durable immunity and the 77 early vaccine-specific Bmem response after IIV of healthy human subjects.

78 Here we study the clonotype, transcriptome and epigenome of circulating human Bmem 79 after IIV strictly classified according to antigen reactivity and T-bet expression. We find that the 80 BCR inhibitory signaling molecule, FcRL5,9 accurately identifies HA-specific Bmem by T-bet 81 expression. We also find HApos T-bethi Bmem are transcriptionally remodeled as effector 82 memory with increased accessibility at an Xbp1 enhancer locus that aligns with an established 83 T-bet binding site.10 We show that the early HApos T-bethi subset predicts the development of 84 long-lived Ab response to the vaccine. Finally, we demonstrate that HApos T-bethi Bmem clones 85 are preferentially recalled into the early antigen-specific PB repertoire after re-vaccination.

86 Results: 87 I. T-bet parses phenotypically distinct HA-specific humoral immune readouts after IIV 88 After inactivated influenza vaccination (IIV), there is an early expansion of the circulating 89 follicular helper T cell (cTfh, CD4+CXCR5+PD1+ICOS+ T cell)11,12 and plasmablast fractions bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

90 (CD27posCD38hi, PB) within 5-10 days of vaccine receipt. 13,14 The plasmablast fraction has 91 been extensively studied as a measure of vaccine induced antigen-specific humoral immunity.15- 92 18 However, plasmablasts are rapidly cycling, short-lived cells and therefore do not reflect 93 longitudinal immune protection after vaccination. Using fluorochrome labeled tetramer or 94 monomer reagents, hemaggulutinin (HA)-specific Bmems have been identified within one month 95 after IIV. 19-21 This antigen-specific Bmem compartment after IIV has been described as 96 heterogeneous, comprising typical and atypical memory B cells.19-21 We wanted to assess the 97 phenotype and kinetics of the HA-specific Bmem compartment after IIV and the relationship of 98 this compartment to the plasmablast and long-lived antibody (Ab) response. We hypothesized 99 that the HA-specific Bmem and plasmablast humoral immune responses are distinct vaccine 100 outputs. In order to test this hypothesis, we administered the 2015 IIV to 19 healthy subjects 101 and drew blood at sequential proximal time points (day 0, 7, 14, 21, 28) as well as distant time 102 points from vaccine receipt (day 120). Detailed vaccination and infectious histories from 103 subjects were not recorded. Gating strategies are shown in Supplemental Fig 1 A-C. Specificity 104 of our HA tetramer has been described22 and, unless specifically indicated, HA tetramer 105 matches relevant vaccine antigen strain (H1 or H3). Our 2015 cohort responded to the vaccine 106 as evidenced by a significant increase in the circulating cTfh and PB fraction from day 0 to day 7 107 of IIV (Supplemental Figure 1 B,1C). Also within 7 days of IIV, two phenotypically unique 108 IgDnegCD38med/lo HA-specific (H1) Bmem populations were identified in circulation. These two 109 populations are shown in representative FACS plots (Figure 1A) and are phenotypically distinct 110 from CD38hi B cells and from each other according to HA (H1)-tetramer, Ki-67, T-bet expression 111 and SSC-A parameters. These HA-specific Bmem subsets were further phenotyped as shown 112 in Supplemental Figure 1D. Both subsets were enriched in the expression of the canonical 113 memory B cell marker, CD27 (Supplemental Figure 1D). Consistent with prior description of 114 atypical T-bethi B cells,8,19,20,23-29 we found day 7 HApos T-bet hi Bmem to have increased 115 expression of the integrin CD11c and the inhibitory B cell receptor (BCR) signaling molecule 116 FcRL5 as well as decreased expression of the chemokine receptor CXCR5 and the complement 117 receptor CD21. Underscoring these phenotypic differences, we interrogated the morphology of 118 H1pos T-bethi Bmem using ImageStream and found them to be larger and more granular than 119 H1pos T-betlo Bmem (Supplemental Fig 1E). 120 Ki67 is not a binary marker of proliferation and its expression at any individual timepoint 121 does not necessarily reflect ongoing or future proliferative potential but may rather reflective 122 prior replicative history.30,31 Thus we evaluated for phenotypic changes in Ki-67 expression in 123 the HA-specific Bmem compartment over time after IIV. We found that Ki-67 expression was bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

124 not sustained over time in the circulating HApos T-bethi Bmem compartment nor did the 125 circulating HApos T-betlo compartment develop significant Ki-67 expression over time after 126 vaccination (Figure 1B). In our 2015 IIV cohort, the HApos (H1 and H3) T-bethi Bmem expanded 127 in the circulation within one month of IIV (Figure 1C, 1E). However, we did not consistently 128 observe a parallel expansion in the HApos T-betlo Bmem fraction in this cohort (Figure 1D, 1F). 129 We found an exclusive correlation between the day 7 cTfh and the day 7 HApos T-bethi Bmem 130 responses to the 2015 IIV (Supplemental Figure 1 F-I). Finally in our 2015 IIV cohort, we found 131 no correlations between the magnitudes of the day 7 HApos T-bet hi and HApos T-bet lo Bmem to 132 either the PB response (Figure 1 G-H) or to one another (Figure 1 I-J). Collectively, the data 133 suggest that the day 7 HApos T-bethi and T-betlo Bmem are unique humoral immune outputs to 134 the IIV. 135 II. HApos T-bethi Bmem transcriptionally and epigenetically resemble effector memory 136 T-bet is a lineage defining master transcriptional regulator of terminally differentiated 137 effector cell subsets32,33 and its role in B cell differentiation has been studied in various 138 pathologic in vivo and in vitro contexts.8,19,20,23-29 Murine studies of influenza infection in wild- 139 type versus B-Tbx21-/- chimeric mice demonstrate that T-bet is necessary for long-lived IgG2c 140 antibody production after primary infection and dispensable for the development and 141 maintenance of the flu-specific memory pool after primary infection.8 However, flu-specific 142 memory B-TBX21-/- cells cannot mount a recall antibody-secreting cell (ASC) response upon 143 antigen re-challenge. These data suggest that T-bet expression in antigen-specific B cells may 144 either directly mediate the initial transcriptional commitment toward terminal ASC differentiation 145 as “pre-ASCs,” or may mediate transcriptional commitment toward effector memory.34 Existing 146 transcriptional data sets of circulating human Bmem after IIV have compared the aggregate 147 Bmem compartment according to expression of atypical cell surface markers, CD7119 and 148 CD21.20 The latter study concluded that CD21lo Bmem after IIV had enhanced T-bet expression 149 and had coincident up-regulation of key ASC transcription factors (TFs), like PRDM1.20,35-38 We 150 hypothesized that the transcriptional evaluation of antigen-specific Bmem after IIV strictly 151 defined by T-bet expression would similarly show T-bet mediated transcriptional commitment 152 toward terminal ASC differentiation. 153 To test our hypothesis and characterize the transcriptome of HA-specific Bmem by T-bet 154 expression we used the cell surface marker FcRL5 to sort-purify Ca-H1pos T-bethi Bmem, Ca- 155 H1pos T-bet lo Bmem, naïve B cells and ASCs for RNA-seq from 6 donors at day 7 after 2017 IIV 156 The 2017 IIV included the Michigan 2015 (Mi) H1 antigen which only differs from the sort Ca-H1 157 tetramer by a single mutation and glycosylation residue.39,40 Figure 2A shows the principal bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

158 component analysis (PCA) of this transcriptional data. Utilizing FcRL5 as a cell surface 159 surrogate for T-bet expression accurately classified HApos Bmem according to T-bet and FcRL5 160 expression status (Figure 2B, Supplemental Fig 2A). For purposes of brevity, hereafter we refer 161 to the HA-Tetint Ki-67int T-bethi SSC-Ahi FcrRL5hi Bmem response to IIV as “HApos T-bet hi“ and 162 the HA-Tethi Ki-67loT-betlo SSC-Alo FcRL5lo response as “HApos T-bet lo.” 163 Expectedly, naïve, Bmem and PB subsets group separately on the PC1 axis. There 164 were 762 differentially expressed genes (DEGs) identified between H1pos T-bethi Bmem and 165 H1pos T-betlo Bmem. There were near equivalent DEGs identified between PBs and H1pos T-bethi 166 (3154) versus PBs and H1pos T-betlo Bmem (3571) and H1pos T-bethi Bmem did not group more 167 closely to PBs on either the PC1 or PC2 axis relative to H1pos T-betlo Bmem. Consistent with this 168 observation, we saw no differences in the gene expression (reads per kilobase per million, 169 RPKM) between HApos T-bet lo Bmem and HApos T-bet hi Bmem at key ASC defining TFs like 170 PRDM1,36-38 XBP1,41,42 IRF443,44 (Figure 2B). Instead we saw differential expression between 171 HApos T-bethi Bmem and HApos T-betlo Bmem at key effector cell TFs, like Zeb2,45,46 chemokine 172 receptor, CXCR3 that is a direct downstream target of TBX21,33 and a chemokine that 173 distinguishes effector from central memory, CCR7.47 We compared our transcriptional analysis 174 to curated gene lists of cell cycle genes and apoptosis genes (Qiagen RT2 profiler) (Figure 2C). 175 Expectedly we found that the vaccine elicited PBs, which are known to proliferate and are short- 176 lived, had differential expression at a number of cell cycle and apoptosis genes. Consistent with 177 transient expression of Ki-67 over time in the HApos T-bethi Bmem, we did not find significant 178 differences in cell cycle genes between day 7 H1pos T-bethi and day 7 H1pos T-betlo Bmem. 179 Consistent with terminal effector cell remodeling, we found that day 7 H1pos T-bethi Bmem 180 upregulated pro- apoptotic genes, like Fas, and down-regulated anti-apoptotic genes, like Bcl2, 181 in comparison to day 7 H1pos T-bet lo Bmem. Finally we performed gene set enrichment 182 analysis (GSEA) against curated gene sets with effector T cell genes (Figure 2D, Supplemental 183 2B)48-50 and found significant enrichment between the DEGs of day 7 HApos T-bethi Bmem over 184 day 7 HApos T-bet lo Bmem and these gene lists. 185 Next we asked whether HApos T-bethi Bmem were epigenetically more similar to PBs than 186 HApos T-bet lo Bmem. To test this we used the cell surface marker FcRL5 to sort purify day 7 187 H1pos T-bethi , H1 pos T-bet lo Bmem, PBs and H1neg T-bet hi Bmem to assess chromatin 188 accessibility in these subsets using ATAC-seq. We found 1923 significant differentially 189 accessible regions (DARs) between HApos T-bet hi and HApos T-bet lo populations. We also 190 identified 10,464 and 11,362 DARs between ASCs and HApos T-betlo and T-bethi Bmem 191 respectively. PCA representation of this ATAC-seq data is shown Figure 2E with PBs grouping bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

192 distinctly from both HApos Bmem subsets. We assessed the accessibility of genes known to be 193 targets of the ASC TF IRF4 in plasma cells51 across these various populations and we found no 194 difference in accessibility at these genes among HApos T-bethi and HApos T-betlo Bmem (Figure 195 2F). Finally, we analyzed our accessibility and transcriptional data concordantly using 196 PAGERANK (PR) analysis52 to discern TF motifs that result in changes in gene expression of 197 target genes. We identified 706 TFs that were predicted by PR to contribute to the transcription 198 gene networks of D7 HApos T-bethi over D7 HApos T-betlo Bmem (Figure 2G). Notably no ASC

199 defining TF network was identified by the PR algorithm with a log2 fold change of >1. However, 200 PR predicted the significant up-regulation of TF networks TBX21, BATF,53 BHLHE40,54 and the 201 downregulation of TF network TCF7,55 consistent with effector immune cell programming. 202 Collectively, these data do not support that HApos T-bethi Bmem at day 7 after vaccination are 203 transcriptionally or epigenetically committed to terminal differentiation as ASCs. Rather these 204 data support that day 7 HApos T-bethi Bmem are distinguished by an effector memory cell 205 program. Further analysis comparing the transcriptome and chromatin accessibility of day 14 206 HAposT-bethi over day 14 HApos T-betlo Bmem replicated the transcriptional and epigenetic 207 findings described above at the day 7 time point. (Supplemental Fig 2C, 2D, 2E) 208 III. HApos T-bethi Bmem are transcriptionally remodeled to facilitate intracellular HA- 209 specific immunoglobulin production 210 B cell differentiation into ASCs is known to be epigenetically regulated in a division 211 dependent manner56,57 and cell cycle arrest facilitates terminal immune cell differentiation.58 Top 212 up-regulated TFs in the PR analysis of the day 7 antigen-specific T-bet hi over T-bet lo Bmem 213 network, include SOX5 and E2F7 (Figure 2L), and these TFs inhibit cell proliferation and/or 214 effect cell cycle arrest.59-61 Concordantly, the PAX5 target molecule, Bach2,62,63 is 215 downregulated in the PR analysis of the day 7 HApos T-bet hi over T-bet lo network, and this 216 downregulation facilitates ASC differentiation in a division dependent manner.64,65 PR identified 217 CDKN2C or p18INK4 as a significant DEG target in the predicted E2F7 regulatory network of 218 day 7 HApos T-bethi over HApos T-betlo Bmem (Figure 2E). Interestingly, CDKN2C has previously 219 been demonstrated as critical to the development of the immunoglobulin production and 220 secretory function of ASCs by inhibiting G1/S cell cycle progression.66-68 From these 221 transcriptional and epigenetic network analyses we hypothesized that day 7 HApos T-bethi Bmem 222 may be distinguished by intracellular HA-specific immunoglobulin (Ig) production. To test this 223 hypothesis, we used ImageStream to visualize, enumerate and compare the external 224 (extracellular, EC) and internalized (internalized, intracellular IC) H1-tetramer intensity score 225 (IDEAS software) among circulating PBs, T-bet hi and T-bet lo Bmem within 7 days of IIV. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

226 Representative images of day 7 T-bet lo, T-bet hi and CD38 hi B cells are shown in Figure 3A. 227 HA intensity score (Figures 3B, 3C) among aggregate cells demonstrate, expectedly, that 228 CD38hi cells have the highest intensity score for H1-tetramer internal stain among these three 229 subsets. Interestingly, the intracellular intensity score of H1-tetramer stain in the T-bethi Bmem 230 compartment significantly exceeds that of T-betlo Bmem. We also assessed our ImageStream 231 data using an unsupervised analytic platform, FLOCK, to identify clusters of cells with shared 232 expression patterns of fluorochrome labeled targets. FLOCK independently identified a cluster 233 of cells with high CD38 and intracellular H1-tetramer expression (green) as well as a cluster of 234 cells with intermediate expression of intracellular H1-tetramer, low CD38 expression and high 235 expression of T-bet (red) (Supplemental 2F-H). These data provide functional evidence that day 236 7 HApos T-bethi Bmem produce more intracellular flu-Ig than HApos T-bet lo Bmem. 237 T-bet expression has been associated with altered metabolic programming of effector T 238 cells.69,70 Our finding that HApos T-bethi Bmem have intermediate production of intracellular 239 immunoglobulin prompted us to query the relationship between T-bet expression in HApos Bmem 240 and the unfolded protein response (UPR). First we compared the DEGs between day 7 naïve B 241 cells, PBs, HApos T-bethi Bmem and HApos T-betlo Bmem to a curated list of genes associated 242 with UPR (Qiagen RT2 Profiler) (Figure 3D). We found that PBs almost exclusively upregulated 243 the genes known to be associated with UPR. Next we used PR analysis to identify TFs that 244 regulate the gene network of day 7 HApos T-bethi Bmem over day 7 PBs. Not surprisingly, we 245 found that PR predicted down-regulation of master ASC TFs, Xbp1, PRDM1 and IRF4, as well 246 as master regulators of UPR, ATF4, in day 7 HApos T-bethi Bmem (Figure 3E).71 Thus, our 247 transcriptional and epigenetic data do not demonstrate that T-bet expression in HA-specific 248 Bmem is associated with the development of UPR. 249 We interrogated our transcriptional gene set further to understand the role of T-bet 250 expression in B cell metabolism by using GSEA to compare the DEGs between day 7 H1posT- 251 bethi Bmem over H1pos T-betlo Bmem to Gene Ontology (GO) gene sets. We found enrichment 252 against GO terms that clustered into 3 groups according to shared leading edge gene lists. 253 Representative GSEA plots of these 3 clusters are shown in Figure 3F and clusters 1 and 2 254 pertain to cellular metabolism and mitochondrial respiration. We used Ingenuity Pathway 255 Analysis IPA) on cluster 2 leading edge genes to understand predicted upstream regulators of 256 that gene set (Figure 3G). This cluster was chosen because there were sufficient leading edge 257 genes to permit this type of analysis. IPA predicted regulators of the metabolism cluster include 258 modulators of metabolic transitions to aerobic glycolysis (PCGEM1,72 LONP173 and TRAP174), 259 as well as established mediators of effector cell sustained respiratory capacity (SRC), Il-15.75 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

260 Finally we examined the genome plot of our ATAC-seq data at the Xbp1 locus to assess for 261 DARs at this gene. Of note, Xbp-1 is not a target gene in the Staudt et al Nature 2008 gene list 262 and accessibility at this locus is not shown in Figure 2F. We identified a DAR (FDR = 0.03) at 263 an Xbp-1 enhancer site between day 7 HApos T-bethi over HApos T-betlo Bmem that persists at 264 day 14 after vaccination (FDR <0.0004) (Figure 3H, Supplemental 2I) with predicted RUNX, Ets 265 and PU.IRF binding motifs. Although there are no predicted TBX21 binding motifs at this site, 266 this DAR directly aligns to peaks identified by published Tbx21 ChIP-seq data of GM12878 267 cells.10 Collectively, these data suggest that T-bet expression in HApos Bmem is associated with 268 altered mitochondrial respiration and cellular metabolism parameters and may facilitate 269 intracellular immunoglobulin production/UPR by associating with TF complexes at an Xbp1 270 enhancer locus to effect increased Xbp1 chromatin accessibility. 271 IV. Clonotypes from HApos T-bet hi Bmem Exclusively Persist in the Circulation 272 Our data show that HApos T-bethi Bmem have distinct kinetics from HApos T-betlo Bmem 273 after vaccination suggesting that this subset may also be clonotypically distinct from HApos T- 274 betlo Bmem. To test this possibility we used FcRL5 as a cell surface marker of T-bet expression 275 [Supplmental Fig 1D] to sort purify HApos Bmem by T-bet expression from the peripheral blood of 276 three subjects (donor 1, 2, 3) at various timepoints after 2016-7 IIV for BCR sequencing. Unique

277 clones across subsets were identified as having the same VH- and JH- gene annotations, 278 identical length at the CDR3-H and at least 85% sequence similarity between the CDR3. 279 Figure 4A shows representative clonality plots of H3pos T-bethi and H3pos T-betlo Bmem 280 with the number of sequences retrieved from each subset and the number of lineages resolved 281 from these sequences also represented. BCR repertoire diversity within each subset was 282 assessed through a variety of metrics including the number of clonotypes that composed the top pos lo 283 20% or 50% of all sequences (D20, D50). Circulating day 7 H3 T-bet Bmem were 284 clonotypically more diverse than circulating day 7 H3pos T-bethi Bmem (Figure 4A) in both donor hi lo hi 285 1 and 2 (Donor 1: D20, T-bet lo 29 vs. T-bet 14, D50, T-bet 151 vs T-bet 82; Donor 2: D20, T- lo hi lo hi 286 bet 3 vs. T-bet 1, D50 T-bet 11 vs T-bet 3). 287 Next we examined the frequency of shared clones between the H3pos T-bethi or H3pos T- 288 betlo Bmem populations in donors 1 and 2 (Figure 4B). We found that 6.1% and 5.1% of H3pos T- 289 bethi Bmem clones from donors 1 and 2 respectively were shared with clones from H3pos T-betlo 290 Bmem. Conversely, we found that 4.2% and 1.9% of H3pos T-bet lo Bmem clones from donors 1 291 and 2 respectively were shared with clones from the corresponding H3pos T-bethi Bmem subset. 292 These data indicate that HApos T-bet hi Bmem are largely clonotypically distinct from HApos T-bet 293 lo Bmem at a single time point. However, we also wanted to understand if the relationships bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

294 between these populations over time. Therefore we amplified the BCR sequences at day 14 295 after IIV in donor 1 according to H3 and T-bet expression for comparison to day 7 antigen- 296 specific clones. We found that a greater proportion of large day 14 H3pos T-bet hi Bmem clones 297 were enriched in unique clones from day 7 H3pos T-bethi Bmem population as compared to day 7 298 H3pos T-betlo Bmem population (Figure 4 D, Figure 4 F). In contrast, we found that clones from 299 day 14 H3pos T-bet lo Bmem were related to very few unique clones from day 7 H3pos T-bet lo 300 Bmem subset (Figure 4 C, Figure 4 E) . These observations remained true even at 100% CDR3 301 similarity (Supplemental File 2). We evaluated clonotypic relationships between HApos T-bet hi 302 and HApos T-bet lo Bmem at additional time points after IIV in a separate donor and again 303 detected that large clones of day 28 H1pos T-bet hi Bmem were enriched for unique clonotypes 304 from day 14 H1pos T-bethi Bmem over day 14 H1pos T-bet lo Bmem (Supplemental 3A-C). 305 V. HAposT-bethi Bmem Exclusively Correlate with the Long-lived Ab Response after IIV 306 In order to understand the relationship of circulating HApos T-bet hi and HApos T-bet lo 307 Bmem to each other and to any vaccine elicited germinal center response, we assessed the 308 heavy chain mutation rates between total and related antigen-specific T-bethi and T-bet lo Bmem 309 clones at matched time points (donor 1: day 7, day 14; donor 2: day 7, donor 3: day 14, day 28) 310 We also assessed the heavy chain mutation rates among shared antigen-specific T-bethi clones 311 across time in donor 1 (day 7 to day 14) and donor 3 (day 14 to day 28). We were unable to 312 resolve any consistent directionality (increased or decreased) in total, silent or non-silent 313 mutation rate differences among total or shared clonotypes by T-bet expression status. 314 The influenza antigen-specific Bmem compartment is significantly mutated as a result of 315 repeated infectious exposure and/or inoculations. Thus, the incremental differences in heavy 316 chain mutation across antigen-specific Bmem subsets after vaccination may be subtle and this 317 may not be the appropriate read-out of the germinal center response to vaccination.20 Therefore 318 we cloned single Ca-H1pos Bmem by T-bet/FcRL5 expression for recombinant monoclonal 319 antibody (rMAb) generation from three donors after 2017 IIV (donor 1, day 7; donor 3, day 14; 320 donor 4 day 14) to assess for binding to a panel of H1 antigens (California-H1, Ca7, Michigan- 321 15, Mi15, and Puerto Rico/8, PR8) in a multiplex bead assay as has been described 322 previously.76,77 We did not find any difference in relative binding reactivity to either the vaccine 323 antigen, Mi15, or the closely related sort antigen, Ca7 (Figure 4G). However, we observed an 324 enrichment in PR8 reactive clones among rMAbs generated from individual Ca-H1pos T-bet hi 325 Bmem (Figure 4G). Regardless of T-bet expression status, those clones with highest PR8 326 reactivity had relatively lower relative binding avidity for the vaccine H1 antigen, Mi15 or the 327 closely related Ca7 antigen than non-PR8 reactive clones. PR8 is antigenically more similar to bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

328 pre-2009 circulating and inoculating H1N1 strains that diverged from swine early in the 20th 329 century78 and is less similar to more recently circulating and inoculating H1N1 strains like Mi15 330 and Ca7 that are directly adapted from contemporaneous swine H1 strains.79 Thus, enrichment 331 of PR8 reactive clones in the T-bethi repertoire suggests that the repertoire of this fraction may 332 preferentially contain clones from temporally distant exposures to influenza viral variants. 333 Collectively, these BCR repertoire data suggest that HApos T-bethi Bmem are clonally dissimilar 334 from the HApos T-betlo Bmem repertoire. 335 Although we were unable to resolve differences in the mutation rates or relative binding 336 avidity to vaccine antigen of HApos Bmem by T-bet expression status, the unique persistence of 337 HApos T-bet hi clonotypes in the circulation across one month after IIV suggests that these may 338 mark the presence and or represent direct outputs of an ongoing germinal center response. We 339 further hypothesized that the long-lived antibody response would therefore correlate with the 340 magnitude of the HApos T-bethi Bmem response as the long-lived antibody responses to antigen 341 is impaired in the absence of germinal center responses.80 342 As a measure of durable humoral immunity induced by vaccination, we calculated the 343 fold change in the HA IgG Ab titer between days 0 and 120 after IIV. Expectedly, we found no 344 correlation between the magnitude of the day 7 PB response and long-lived antibody after 2015 345 IIV (Supplemental Figure 1J-K). However, the H1 and H3 long-lived Ab response correlated with 346 the peak day 7 H1 and H3 T-bet hi Bmem response (Figure 5 A-D). Notably, this correlation was 347 antigen-specific as the day 7 H1posT-bet hi Bmem did not correlate with the long-lived H3 Ab 348 response and vice versa (Supplemental Fig 1L-M). We found similar antigen-specific 349 correlations exclusively between the D14 HA-specific T-bethi Bmem and the long-lived Ab 350 response (Supplemental Figure 1 N-S). Therefore, these data suggest that HA-specific T-bethi 351 Bmem may serve as a putative early biomarker of the long-lived antibody response after IIV. 352 VI. T-bethi Bmem clonotypes are preferentially recalled into the PB repertoire 353 Effector memory B cells have been described as resident in the murine lung tissue and 354 directly differentiate into ASCs after antigen re-challenge.22 Our transcriptional data suggests 355 that HApos T-bet hi Bmem are effector memory B cells and therefore we hypothesized that this 356 subset will directly form ASCs after antigen re-challenge. To test this hypothesis we re- 357 vaccinated 2 cohorts of subjects across sequential vaccine years (2015 and 2016; 2016 and 358 2017) and assessed the magnitude of the HApos T-bethi and HApos T-betlo Bmem response within 359 7 days of vaccine receipt in each year. We found a significant increase in HA-titer after vaccine 360 (Figure 5E), demonstrating that all 10 subjects responded to the prime and had relatively high 361 titers of HA-Ab prior to vaccine boost. We found that re-vaccination contracted the HApos T-bet hi bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

362 Bmem fraction but did not significantly alter the magnitude of the total day 7 HApos Bmem or the 363 day 7 HApos T-bet lo Bmem response (Figure 5F-H) across vaccine seasons. Next we compared 364 the 2016 HApos T-bethi and HApos T-bet lo Bmem clonotypes to those of the 2016 and 2017 PB 365 subset in 3 subjects who received IIV in 2016 and 2017. Expanded clones in the 2017 PB 366 repertoire were preferentially related to clones from the 2016 HApos T-bethi Bmem subset under 367 both 85% and 100% CDR3 similarity constraints (Figure 5 I-K, Supplemental Figure 3 D, 368 Supplemental File 2). These data suggest that clonotypes HApos T-bethi Bmem directly seed the 369 secondary ASC compartment to provide immune protection after challenge infection. 370 371 Discussion 372 Here we define two HA-specific Bmem subsets that circulate within seven days of IIV 373 and have differential expression of the lineage defining TF T-bet. We show that T-bet 374 expression divides the HA-specific Bmem compartment into effector memory (TCF7lo, CCR7lo) 375 and central memory compartments (TCF7hi, CCR7hi). Consistent with an effector memory 376 profile, we show that HApos T-bethi Bmem exclusively persist in the blood compartment within 377 one month of vaccination and that clonotypes of this subset are recalled into the circulating 378 expanded PB lineages upon antigen re-challenge. 379 T-bet expressing B cells have been described in the context of aging, autoimmunity, 380 infection, and vaccination as atypical memory and this subset is now regarded as 381 heterogeneous.7 For instance, CD27neg T-bethi Bmem (double negative 2, DN2) have been 382 shown in lupus subjects as an activated extrafollicular B cell subset that arise directly from naïve 383 B cells and respond to IL-21 and TLR7 signaling alone to differentiate into ASCs.25,81 However, 384 this same population has been characterized in patients with chronic infection from HIV, HCV 385 and malaria as exhausted and unresponsive to BCR signaling.82-85 In contrast to these studies, 386 our study reports DEGs between antigen-specific Bmem that are enriched in canonical CD27 387 expression by T-bet expression (Supplemental Figure 1D) While there are multiple shared 388 targets in our gene list and gene lists that compare DN2 to canonical memory (e.g. TBX21, 389 CXCR5, Tcf7, Zeb2, Bach2, ITGAX) there are also important differences. Notably DN2 390 exclusively upregulate IL21R expression relatively to canonical memory, suggesting the DN2 391 subset and the HApos T-bethi Bmems described here have different ontogeny, cytokine 392 responsiveness and consequent functions in vivo. 393 In the context of vaccination against influenza, atypical memory B cells have been 394 identified in the HA-specific Bmem compartment with T-bet expression.19,20 Our study is 395 distinguished from these previous reports because we did not discern a pre-ASC transcriptional bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

396 signature in the atypical Bmem compartment after IIV. Rather we found that the antigen-specific 397 T-bethi Bmem subset to retain transcriptional and epigenetic programming as effector memory. 398 This discrepancy in findings may pertain to differences in study design with respect to the 399 inclusion of antigen-specific versus aggregate vaccine-elicited atypical Bmem in transcriptional 400 analysis, the transcriptional timepoint under study after vaccination (day 7 vs day 14), and the 401 use of different cell surface surrogates to parse Bmem into subsets with consequent 402 heterogeneity in the resolution of the T-bet dependent programming signature (Supplemental 403 Fig 1D, Supplemental Figure 2A). 404 Effector immune cells are distinguished from central immune cells according to cellular 405 metabolism, respiration and mitochondrial dynamics.75,86,87 Although it is currently unclear if 406 metabolic re-programming alone directly shapes cellular fate decisions,88 TFs that orchestrate 407 terminal cellular fate commitments concordantly orchestrate cellular metabolic program 408 changes.70 ASCs are a terminally differentiated effector cell of the humoral immune arm. This 409 differentiation is mediated by PRDM1 beyond an early timepoint.36 Production of 410 immunoglobulin by ASCs is a nutrient intensive process that requires cellular adaptation termed 411 the unfolded protein response (UPR). ASCs exhibit a transcriptionally unique UPR from other 412 cell types that is felt to occur early in ASC differentiation and prior to high Ig secretion.89-91 413 Xbp1/IRE-1 is a key regulator of the ASC UPR41,42 and its expression in B cells is directly 414 modulated by PRDM1 as part of terminal ASC differentiation.91,92 Here we show a significant 415 DAR at an Xbp1 enhancer locus between the HApos T-bethi over HApos T-bet lo Bmem subsets 416 that is located at a published TBX21 ChIP-seq binding site.10 Although Xbp1 has been shown 417 to be dispensable for plasma cell terminal differentiation, absence of Xbp1 attenuates Ig 418 secretory function.93 In fact, PRDM1 has been demonstrated as dispensable for the initiation of 419 Ab secretion.36 In keeping with this finding, the change in Xbp1 locus accessibility that we 420 observed in HApos T-bethi Bmem is unlikely to be regulated by PRDM1 as there are no predicted 421 PRDM1 binding motifs at this enhancer site. Thus, while our data do not suggest that HApos T- 422 bethi Bmem have made a transcriptional or epigenetic commitment to PRDM1-mediated terminal 423 ASC differentiation, our data do suggest that T-bet manipulates the metabolic programming of 424 HApos Bmem via DNA binding effects at the Xbp1 locus to facilitate chromatin accessibility at 425 that site with consequent intracellular immunoglobulin production. It is also possible that there 426 are DNA binding independent effects of T-bet on HApos B cell metabolism through functional Bcl- 427 6 antagonism,69 as has been described in the context of CD4 T cell effector function, but these 428 are not clearly elucidated in the transcriptional network analysis presented here. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

429 Bone marrow resident long-lived ASCs mediated durable immunity and are distinguished 430 from other ASC subsets, including PBs, by metabolic programs like autophagy as well as 431 morphologic and phenotypic characteristics like the expression of surface Ig.94,95 Current early 432 immune readouts after IIV, include early antigen-specific PBs and cTfh and are not known to 433 predict durable immunity after vaccination.11,95,96 In fact, in our 2015 IIV cohort, the magnitude of 434 the day 7 plasmablast and cTfh response did not correlate with the fold change in HA-IgG titer 435 at day 120 after vaccination (Supplemental Fig 1J-K) In the absence of germinal centers, the 436 long-lived ASC response is impaired.80 Consistent with this finding, network analysis of PBMC 437 transcriptome datasets after IIV correlate early proliferation gene signatures with the 438 development of an antibody response.97 Our data demonstrate a correlation between the 439 circulating early HApos T-bethi response and long-lived HA IgG titer that is antigen specific. These 440 data suggest that the HApos T-bethi Bmem subset reflects the induction of a new germinal center 441 response by the IIV. Although we were unable to demonstrate, via incremental increases in 442 mutation rates or increase in HA binding affinity, evidence that either HApos T-bethi or T-betlo 443 Bmem are direct outputs of a new GC response to vaccine, we did find exclusive persistence of 444 HApos T-bethi Bmem clonotypes in circulation and an enriched reactivity of these clonotypes to 445 H1 viral variants (Figure 4G). These findings may reflect this subset’s origin from an ongoing 446 GC response (Figure 5L), which is less stringent to the selection of B cells by affinity/epitope 447 reactivity.98-100 448 It is as yet unclear if circulating HApos T-bethi Bmem simply serve as a biomarker of the 449 long-lived ASC response or actually represent the direct precursors of bone marrow resident 450 long-lived ASCs. In this study we used serial annual influenza vaccination of three subjects with 451 the 2016 and 2017 IIV to follow the fate of circulating HA-specific Bmem clonotypes by T-bet 452 expression after antigen re-challenge. The 2016 and 2017 IIV formulations were highly 453 conserved as they shared the same H3 and influenza B antigens and only differed according to 454 the H1 antigen (Ca-H1 vs Mi-H1). In fact, these two H1 antigens were also highly similar 455 between formulations, distinguished only by a single K166Q mutation and an adjacent N-linked 456 glycosylation site.39 Sequential influenza vaccination with conserved antigens has been shown 457 to attenuate the vaccine-specific plasmablast101 and Bmem response17 possibly because pre- 458 existing Ab mediate epitope masking or epitope clearance.102 We did not observe a reduction in 459 the total or T-betlo HApos Bmem fraction after re-vaccination (Figure 5F). This discrepancy from 460 prior reports may be due to our directly enumerating the antigen-specific Bmem compartment 461 versus assaying the compartment indirectly via ELISPOT as was done previously. However, 462 and in keeping with prior reports,17,101 we observed relatively fewer accumulations of bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

463 connections between PB clones across successive vaccine seasons than between T-bethi 464 Bmem and PB clones in two of three donors tested [Figure 5I, J, Supplemental 3D]. 465 It is interesting to note that large lineages from the circulating 2016 D7 HApos T-bet hi 466 subset were not consistently recalled into the 2017 PB compartment after repeat IIV [Figure 5K]. 467 The fate of these large clonotypes is not clear. They may have differentiated into short or long- 468 lived ASCs or may have died in the intercurrent time period between sequential vaccines. 469 Recent data demonstrate HA-specific Bmem in non-lymphoid tissues like the human lung as 470 enriched in atypical memory marker expression.3 In fact, CXCR3+ flu-specific effector Bmem in 471 the murine lung are broadly reactive against HA viral variants103 and directly differentiate into 472 ASCs after antigen challenge for local immune protection.22 These data suggest raise the 473 alternative possibility that circulating expanded HApos T-bethi Bmem clones migrate and are 474 maintained in non-lymphoid tissues as resident effector memory against influenza viral variants 475 [Figure 5L]. Elucidating clonotypic relationships among effector and central HA-specific Bmem 476 at various human tissue sites (blood, lymphoid, mucosal) and with the circulating flu-specific Ig 477 repertoire will be an important goal of future studies. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

478 Author Contributions: F.E.L. conceived the idea for the project and secured the initial funding. 479 F.E.L. and A.N. designed the experiments that were performed by A.N., C.D.S., R.G.K, C.M.T., 480 E.Z., B.M. and K.M. B cell tetramers were developed and produced by J.E.B. Human samples 481 used in this study were obtained via the Alabama Vaccine Research Clinic, directed by P.A.G. 482 Bioinformatic analyses were performed by A.F.R, C.D.S., C.F. and T.M. All other data was 483 analyzed by A.N and F.E.L. A.N., A.F.R. and F.E.L wrote the manuscript and prepared final 484 figures. Critical feedback on the project and manuscript were provided by A.F.R, T.D.R, J.F.K., 485 I. S., and J.M.B. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

486 Acknowledgements: We thank the Alabama Vaccine Research Clinic and particularly Pamela 487 Cunningham, Heather Logan, Aeryn Peck, Catrena Johnson and Megan Oelschig for recruiting 488 and consenting subjects for this study. We also thank Vidyasagar Hanumanthu, director of the 489 UAB Flow Core Facility, for his assistance with flow sorts and ImageStream experiments. We 490 are grateful to Amy S. Weinmann for her thoughtful commentary regarding this manuscript. 491 Funding for the work was provided by the US National Institutes of Health (NIH): P01 AI125180 492 (I.S., F.E.L, J.M.B, C.D.S), U19 AI 109962 (F.E.L, T.D.R). A.N. received pilot grant support from 493 the UAB AMC21 Immunology Autoimmunity and Transplantation Strategic Initiative as well as 494 funding from the UAB CCTS (UL1 TR001417) to support this work. NIH P30 AR048311 and 495 P30 AI027767 provided support for the UAB Consolidated Flow Cytometry Core. The authors 496 have no known conflicts of interest to disclose. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

497 Materials and Methods: 498 Human Subjects and Samples. The UAB Institutional Review Board approved all study 499 protocols for influenza vaccinated subjects. All subjects gave written informed consent as part of 500 participation prior to providing peripheral blood for analysis. Influenza vaccinated patients self- 501 identified as healthy and were recruited through the Alabama Vaccine Research Clinic (AVRC). 502 Subjects received either the 2015-2016 Fluzone (Sanofi-Pasteur), 2015-2016 FluMist 503 (AztraZeneca) the 2016-2017 Fluvirin (Sequiris), the 2017-2018 Fluzone (Sanofi-Pasteur) and 504 the 2018-2019 Fluzone (Sanofi-Pasteur). Blood was drawn on days 0, 7, 14, 21, 28 and 120 505 days +/- 1 week.

506 Lymphocyte and plasma isolation. Peripheral blood from human subjects was drawn into K2- 507 EDTA tubes (BD Bioscience). Peripheral blood mononuclear cells (PBMCs) and plasma were 508 isolated by density gradient centrifugation over Lymphocyte Separation Medium (CellGro). Red 509 blood cells were lysed with ammonium chloride solution (StemCell). Plasma and PBMCs were 510 either used immediately or aliquoted and stored in -80C freezers.

511 Human B cell purification. Total B cells were negatively selected from PBMCs by using EsaySep 512 TM B cell enrichment kits (StemCell). Antigen-specific B cells were further sort-purified for 513 sequencing experiments as outlined below.

514 Influenza Hemagglutinin Tetramer production and staining. The coding sequencing (encoding 515 amino acids 18-524) of the hemagglutinin ectodomain were synthesized from the following 516 influenza virus strains, A/California/VRDL7/2009, A/Switzerland/9715293/2013, A/Hong 517 Kong/4801/204, and A/Michigan/45/2015, were synthesized (GeneArt, Regensburg, Germany) 518 in frame with the human CD5 signal sequence located 5’ to the HA coding region. Two 519 mammalian expression constructs were made with a 6XHIS tag or an AviTag located 3’ to the 520 trimerization domain. HA-6X HIS and HA-AviTag were co-transfected in a 2:1 ration into 521 FreeStyle TM 293-F Cells (ThermoFisher Scientific). Recombinant HA trimers with an average 522 of 2 HIS6X monomers and 1AviTag monomer per trimer were purified from media by FPLC 523 using a HisTrap HP column (GE Healthcare) for biotinylation in vitro using BirA biotin-protein 524 ligase (Avidity). Tetramers of HA trimers were made by titrating in fluorochorome-conjugated 525 streptavidin to biotinylated HA trimers until the volumetric ratio for saturation was reached. To 526 detect HA-binding B cells, cells were treated at 37C with 0.5U/ml neuraminidase (C. 527 perfringens, Sigma) to remove sialic acid, and then were washed, blocked and stained with HA 528 tetramers. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

529 Hemagglutinin ELISAs. Recombinantly generated hemagglutinin proteins (see above) were 530 coated onto EIA/RIA ELISA plates (Costar) at 1:500 to 1:1000 dilution. Plasma from vaccinated 531 samples were serially diluted onto these coated plates. HA-specific IgG antibodies from vaccine 532 samples were detected using peroxidase-conjugated anti-human IgG secondary antibodies 533 (Jackson ImmunoResearch) and were developed using ABTS development with acid stop. 534 Absorbance was measured at 415nm using a SpectraMaxM2 (Molecular Devices).

535 Flow Cytometry: Single cell suspensions were blocked with 2% human serum before cell 536 surface staining. Antibodies used to stain lymphocytes are listed in Supplemental File 2. 7AAD 537 or LIVE/DEAD Fixable Dead Cell Stain Kits (Molecular Probes/ThermoFisher) were used to 538 discriminate live cells. Intracellular staining was performed after staining with antibodies specific 539 for cell surface markers. Cells were then fixed with formalin solution (neutral buffered, 10%; 540 Sigma) and permeabilized with 0.1% IGEPAL (Sigma) in the presence of antibodies or 541 fluorochrome labeled HA tetramers. Stained cells were analyzed using a FACSCanto II (BD 542 Bioscience) or the Attune NxT flow cytometer (Invitrogen, ThermoFisher). Cells were sort- 543 purified with a FACSAria (BD Biosciences) or Melody (BD Biosciences) in the UAB 544 Comprehensive Flow Cytometry Core. FlowJo v9.9.3 or FlowJo v10.2 were used to perform 545 analysis.

546 RNA-seq library preparation and analysis: RNA was isolated from HA-specific Bmem as well as 547 ASCs and Naïve B cell by flow sorting these populations directly into RLT buffer (Qiagen) and 548 snap freezing in liquid nitrogen. RNA was extracted using the QuickRNA Micro Prep Kit (Zymo). 549 All resulting RNA from six biological replicates per B cell subset at the day 7 timepoint and four 550 biological replicates per B cell subset at the day 14 timepoint was used as input for the SMART- 551 seq v4 cDNA synthesis kit (Takara). Final libraries were constructed using 200 pg cDNA as 552 input for the NexteraXT kit (Illumina) and quality assessed on a bioanalyzer. Libraries were 553 pooled and sequenced using 50 bp paired-end chemistry on a HiSeq2500. Sequencing reads 554 were mapped to the hg38 version of the human genome using STAR with the default settings 555 and the UCSC KnownGene table as a reference transcriptome. Reads overlapping exons were 556 tabulated using the GenomicRanges package in R/Bioconductor. Genes expressed at 3 reads 557 per million or more in all samples from one group were considered detected and used as input 558 for edgeR to identify differentially expressed genes. P-values were false-discovery rate (FDR) 559 corrected using the Benjamin-Hochberg method with genes of an FDR <0.05 considered 560 significant. Expression data was normalized to reads per kilobase per million mapped reads 561 (RPKM). bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

562 GSEA analyses. Gene set enrichment analysis were submitted to the GSEA program 563 (http://software.broadinstitute.org/gsea/index.jsp). Detected genes were ranked by multiplying 564 the –log10 of the P-value from edgeR by the sign of the fold change for use as input in the 565 GSEA PreRanked ananlysis. 566 Ingenuity Pathway Analysis (IPA). IPA upstream regulator analysis (Qiagen Redwood City CA) 567 was performed using the log2 fold change in gene expression between genes that were 568 significantly differentially expressed as defined by corrected FDR of P <0.05, between T- 569 bethi/FcRL5hi HA-specific Bmem over T-betlo/FcRL5lo HA-specific Bmem. Upstream regulators 570 with an activation z-score of >/2 or

573 ATAC-seq preparation and analysis. ATAC-seq was performed on HA-specific Bmem as 574 follows. Cells were re-suspended in 25 ul of tagmentation reaction buffer (2.5 ul Tn5, 575 1xTagment DNA Buffer, 0.02% Digitonin, 0.01% Tween-20) and incubated for 1hr at 37C. Cells 576 were then lysed with 25 ul 2x Lysis Buffer (composed of 300 mM NaCl, 100 mL EDTA, 0.6% 577 SDS, 1.6 ug Proteinase-K) for 30 min at 40C, low molecular weight DNA purified by size- 578 selection with SPRI-beads (Agencourt), and PCR amplified using Nextera primers with 2x HiFi 579 Polymerase Master Mix (KAPA Biosystems). Amplified, low molecular weight DNA was isolated 580 using another SPRI-bead size selection. Quality control was performed on a bioanalyzer. 581 Libraries were sequenced using a 50bp paired end run at the UAB Heflin Genomics Center. 582 Raw sequencing reads were mapped to the hg38 version of the human genome using Bowtie 583 (Langmead et al 2009) with the default settings. Duplicate reads were annotated using the 584 Picard Tools MarkDuplicates function (http://broadinstitute.github.io/picard/) and eliminated from 585 downstream analysis. Enriched peaks were identified using MACS2 with the default settings. 586 Genomic and motif annotations were computer for ATAC-seq peaks using the HOMER104 587 annotatePeaks.pl script. Read counts for all peaks were annotated for each sample from the 588 bam file using the GenomicRanges105 R/Bioconductor package and normalized to reads per 589 peak per million (rppm).106

590 Illumina MiSeq: HA-specific Bmem and plasmablasts were sort-purified into RLT buffer and 591 snap frozen in liquid nitrogen. RNA was extracted using the quick start protocol from QIAGEN 592 RNeasy Mini Kit. First strain cDNA synthesis was performed using iScript cDNA synthesis kit 593 (BioRad) and 8ul of RNA following manufacturer protocol. First round amplification of IgG, IgA, 594 and IgM was performed in a 25 ul reaction volume using 4-8 ul cDNA, Platinum PCR SuperMix bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

595 High Fidelity (Invitrogen), and 1ul gene specific primers (120 nM) of Vn1-Vh7 FR1 (forward) and 596 Ca, Cu, Cg (reverse). First round PCR conditions were: 95C for 3 min, 42 cycles of 30s 95C, 597 30s 58C, 30s 72C, and 72C for 3 minutes. Amplification was verified using 1.2% agarose gels 598 (Lonza). Samples were ligated in a second round PCR with Nextera Index kit (Illumina). PCR2 599 conditions for indexing were: 72C for 3 minutes, 98C for 30s and 5 cycles of 98C for 10s, 63C 600 for 30s, and 72 C for 3 minutes. Products were purified with Agencourt AMPure XP beads 601 (Beckman) and nanodropped for final concentration before pooling into a final library. Library 602 was denatured using 0.2N NaOH and quenched with cold HT1 per manufacturer (Illumina) 603 instruction. Denatured libraries were diluted with 20% PhiX (Illumina) as an internal quality 604 control and loaded onto a 600-cycle V3 MiSEQ cartridge (Illumina) for amplification.

605 Clonotype Assembly and Analysis. Raw sequence reads were processed using a combination 606 of in-house and public analytic tools. Full methodology for this data processing has been 607 described elsewhere.107 Pair-end reads were joined and filtered based on sequence length and 608 quality thresholds. Alignment was performed using IMGT/Hi-Vquest, sequences and analyzed 609 for clonality and for mutations in the V region by a custom program written by the authors (AFR, 610 CF) in perl and Matlab that is available on request. Frequency and distribution of somatic 611 hypermutation was determined on the basis of non-gap mismatches of expressed sequences 612 with closest germline Vh sequence. For visualization, alluvial plots and lineage accumulation 613 curves were constructed in Matlab. Detailed clonotype analysis is presented in Supplemental 614 File 2.

615 BCR Cloning/Recombinant Antibody Screening 616 Antigen binding B cells were index sorted by Fcrl5 expression status as single cells into 617 hypotonic lysis buffer in 384 well plates i and stored at -80deg. Lysates were used to generate 618 cDNA using the High-capacity cDNA generation kit (Roche) following manufactures instructions. 619 PCR was performed using primers specific for nucleotides encoding the amino terminus of the 620 mature IGHV, IGKV, and IGLV proteins. The resulting amplicons were inserted into a 621 mammalian expression plasmid containing the IGG1, IGKC, or IGLC gene sequence. To 622 generate recombinant antibody, plasmids encoding Ig heavy light chain pairs were co- 623 transfected into 293FreeStyle cells (Invitrogen) using standard Polyethylenimine transfection 624 methods. Supernatant was assayed for recombinant antibody expression and for antigen 625 specificity using the flow cytometric bead array (Spherotech). conjugated to IgG or to 626 recombinant hemagglutinin antigen as has been described elsewhere (PLOS ONE, Kelsoe).76 627 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

628 Statistical Analysis. Detailed statistical analytic details are presented in Supplemental File 2. 629 Analysis was performed using GraphPad Prism version 7.0a. 630 Supplemental File 1. Supplemental Figures 1-3 as outlined in Figure Legends. 631 Supplemental File 2. Detailed statistical and clonotype type data. 632 Supplemental File 3. Full RNA-seq, ATAC-seq, and PAGERANK network analysis for the data 633 presented in Figures 2, 3, and Supplemental Figure 2. 634 Figure Legends 635 636 Figure 1. IIV elicits two phenotypically and kinetically distinct hemagglutinin (HA)-specific 637 memory B cell (Bmem) subsets that have no correlation to each other or to the early 638 plasmablast (PB) response. 639 640 (A) Representative flow panel depicting CD19pos IgDneg B cells from the peripheral mononuclear 641 blood cells (PBMCs) of one subject 7 days after IIV classified into 4 subsets according to 642 expression of H1-tetramer and Ki-67. Accompanying histograms demonstrate differences in Ki- 643 67, CD38, T-bet, H1-tetramer expression as well as side scatter (SSC-A) parameters in these 4 644 subsets. 645 (B) Geometric mean fluorescence intensity (gMFI) of Ki-67 stain in HA-specific T-bethi (red) and 646 HA-specific T-betlo Bmem (blue) in 8 subjects at weekly time points after IIV 647 (C-J) Nineteen healthy subjects received the 2015 IIV that included the California-H1 (Ca-H1) 648 and Switzerland-H3 (Sw-H3) vaccine antigens. 649 (C-F) Frequencies of circulating T-bethi (red) and T-betlo (blue) Ca-H1 or Sw-H3 Bmem subsets 650 were assessed at weekly time points one month after vaccine. Populations are represented as 651 percent of parent non-plasma cell gate (CD19pos IgDneg CD38med/lo, NPCs). Gating strategy to 652 identify NPCs is depicted in Supplemental Fig 1. 653 (G-H) Correlation between fold change in plasmablasts (CD27pos CD38hi or PB) between days 0 654 and 7 and the frequency of circulating T-bethi (red) and T-betlo (blue) California H1 (Ca-H1) or 655 Switzerland H3 (Sw-H3) Bmem expressed as a percent of the parent non-plasma cell (NPC) 656 compartment. Gating strategy to identify PBs is shown in Supplemental Figure 1. 657 (I-J) Correlation between the circulating day 7 Ca-H1 and Sw-H3-specific T-bethi and T-betlo 658 Bmem response from 19 subjects given the 2015 IIV. HA-specific Bmem response is expressed 659 as a percent of the parent NPC gate. 660 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

661 Statistical analyses were performed with one way ANOVA testing (B), Wilcoxon rank sum 662 testing (C-F), and Spearman correlation coefficient (G-J), paired Student’s t-test. *p< 0.05, **, 663 p<0.01, *** p<0.001, **** p <0.0001 ns= non-significant 664 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

665 Figure 2. FcrL5hi HA-specific Bmem have T-bet dependent programming and an effector 666 memory profile. 667 668 (A-B) Circulating plasmablasts (PB, green), naïve B cells (brown, CD19pos CD27neg IgDpos, 669 gating strategy in Supplemental Figure 1), and Ca-H1pos Bmem classified by FcrL5 expression 670 (T-bet/Fcrl5hi, red; T-bet/Fcrl5lo, blue) were sort-purified from (6) subjects at day 7 after 2017 IIV 671 for comparative transcriptional analysis via RNA-seq. Principal component analysis of these 672 populations is shown in (A). 673 Reads per Kilobase per Million (RPKM) for target genes of interest by sorted population is 674 shown in (B) with significance of gene expression differences between day 7 Ca-H1pos T-bethi 675 over day 7 Ca-H1pos T-betlo Bmem indicated. Significance of target gene expression differences 676 between other depicted populations is provided in the Supplemental File 2. 677 (C) Heat maps of gene expression in various subsets (I: naïve, II: PB, III: D7 Ca-H1pos T-bethi 678 Bmem, IV: D7 Ca-H1pos T-betlo Bmem) curated by function as related to cell cycle and apoptosis 679 (Qiagen RT2 profiler). Differentially expressed genes (DEGs) between populations are 680 represented as dots with colors of dots indicating the identity of comparator subsets. 681 (D) Gene set enrichment analysis (GSEA) comparing the transcriptome profile of day 7 Ca-H1pos 682 T-bethi over day 7 Ca-H1pos T-betlo Bmem to published gene sets of effector memory T cells over 683 central memory T cells.48 Data is reported as enrichment score (ES) plotted against ranked 684 gene list (n = 10992 genes) of day 7 Ca-H1pos T-bethi over day 7 Ca-H1pos T-betlo Bmem with the 685 dotted line indicating the leading edge of genes and the purple triangle demarcating the change 686 in gene expression polarity. Normalized enrichment score (NES) and p value are also reported. 687 (E-F) Circulating PB (green, n=5), D7 H1pos T-bethi Bmem (red, n=2), D7 H1pos T-betlo Bmem 688 (blue, n=5), and D7 H1neg T-bethi Bmem (pink, n=3) were sort-purified from healthy subjects after 689 2018 IIV for analysis of chromatin accessibility by ATAC-seq. Fcrl5 was used as a cell surface 690 surrogate for T-bet expression (see Supplemental Fig 2). Principal component analysis of 691 ATAC-seq data with relevant populations indicated by color and label is shown in (E). (F) 692 Defined as Reads per Peak per Million (RPPM), accessibility at genes known to function as 693 target genes of IRF4 in human plasma cells51 was assessed in each population sorted for 694 ATAC-seq as shown in Figure 2E. 695 (G) Transcription factors (TFs) that regulate the D7 H1pos T-bethi Bmem network over D7 H1pos 696 T-betlo Bmem network were identified using PageRank (PR) analysis. PR log fold change (FC) 697 versus differential gene expression (DEG) by RNA-seq analysis of these TFs is depicted. 698 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

699 Statistical analysis was performed using two-way ANOVA (B) and multiple t-test testing (F). *p< 700 0.05, **, p<0.01, *** p<0.001, **** p <0.0001 ns= non-significant 701 702 703 704 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

705 Figure 3. T-bethi HA-specific Bmem accommodate the production of Intermediate 706 quantities of intracellular flu-specific immunoglobulin (Ig). 707 708 (A-C) A healthy individual received the 2018 IIV and had PBMCs harvested at day 7 after 709 vaccination for staining of B cells with H1 tetramer extracellularly and intracellularly. B cells were 710 then visualized using ImageStream. Images of three candidate cells are shown with relevant 711 fluorochrome labeled targets depicted (A). Intensity of H1 tetramer extracellular (B) and 712 intracellular (C) stain as calculated by IDEAS software for individual T-bet hi, T-bet lo or CD38 hi B 713 cells. 714 (D) Heat map of gene expression in various subsets (I: naïve, II: PB, III: D7 H1pos T-bet hi 715 Bmem, IV: D7 H1pos T-bet lo Bmem) curated by function as related to the unfold protein 716 response (Qiagen RT2 profiler). Differentially expressed genes (DEGs) between populations 717 are represented as dots with colors of dots indicating the identity of comparator subsets. 718 (E) Using PageRank (PR) analysis, transcription factors (TFs) that regulate the D7 H1pos T-bet hi 719 Bmem network over D7 PB network were identified and shown as PR log fold change plotted 720 against DEGs from RNA-seq data set (see Figure 2). 721 (F) GSEA comparing the transcriptome profile of day 7 Ca-H1pos T-bet hi over day 7 Ca-H1pos T- 722 bet lo Bmem against Gene Ontology terms was performed. Network analysis on the output 723 identified 3 clusters of gene ontology terms grouped by shared leading edge genes. 724 Representative GSEA plots from each of these clusters, labeled 1-3, is shown. 725 (G) Ingenuity pathway analysis (IPA) was performed on the genes that comprised clusters 2. 726 Predicted upstream regulators of cluster 2 are shown in a bar plot with bar color indicating z- 727 score. Regulators that are predicted with bias are demarcated with a dot above that regulator. 728 (H) Genome plot of chromatin accessibility for the XBP1 locus is shown in D7 PB, D7 H1pos T- 729 bet hi Bmem, D7 H1pos T-bet lo Bmem aligned with previously published T-bet binding sites as 730 assessed by CHiP-seq.10 Data is reported as RPPM. 731 732 733 Statistical analysis was performed using one-way ANOVA testing (B, C). *p< 0.05, **, p<0.01, 734 *** p<0.001, **** p <0.0001 ns= non-significant 735 736 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

737 Figure 4. T-bethi HA-specific Bmem clonotypes exclusively persist in circulation after IIV. 738 739 Three individuals (Donors 1-3) were given the 2016 IIV and had PBMCs collected at serial time

740 points within one month of vaccination for assessment of the heavy chain repertoire (Vh families 741 1-7) of flu-specific subsets using next generation sequencing. Data from Donors 1 and 2 are 742 shown here. Data from donor 3 is shown in Supplemental Figure 3. The cumulative percentage 743 of sequences (Y-axis) versus lineage (clonal) size (X-axis) ranked by lineage size is shown in 744 (A). pos hi pos lo 745 (B) Relationship between the day 7 H3 T-bet Bmem and the day 7 H3 T-bet Bmem Vh 746 repertoire is shown as an alluvial plot for donor 1 and 2. Cumulative percentage of sequences 747 are ordered into lineages and ribbons connect lineages that have 85% CDR3 similarity between 748 the two populations. 749 (C-F) Alluvial plots and accumulation curves depict connectivity of clonotypes in donor 1 over 750 time after IIV. Corresponding summary table depicting percent of shared lineages between 751 Bmem over time is shown in the Supplementary File 2. Connectivity between D7 H3pos T-bet lo 752 Bmem and D7 H3pos T-bet hi clonotypes and D14 H3pos T-bet lo Bmem clonotypes (C) or D14 753 H3pos T-bet hi Bmem clonotypes (D) is shown. Connectivity is defined according to 85% CDR3 754 sequence similarity. Red-yellow ribbons correspond to clones shared across 3 populations. 755 Green-blue ribbons correspond to clones shared across 2 populations. Only those lineages that 756 have connectivity with day 14 clones are depicted here. (E-F) Lineages of day 14 H3pos Bmem 757 populations are rank ordered by descending size and the percent of day 7 H3pos Bmem lineages 758 that are shared by rank ordered day 14 clonotype is plotted. Day 7 H3pos Bmem lineages are 759 divided as total T-bet hi clones (solid red line), T-bet hi exclusive clones (dotted red line), total T- 760 bet lo clones (solid blue line), T-bet lo exclusive clones (dotted blue line). 761 (G) Three donors (donor 1, donor 3, donor 4) received 2017 IIV with single cell sort-purification 762 of Ca-H1pos T-bet hi Bmem and Ca-H1pos T-bet lo Bmem within 7-14 days of vaccine for 763 recombinant monoclonal antibody (rMAb) generation. Luminex diagram shows reactivity of 764 these rMAbs to various H1 antigens, Michigan 15 (Mi15), California07 (Ca7), Puerto Rico/8 765 (PR8). Clones with high PR8 reactivity (gMFI >4000) are colorized by T-bet expression status 766 and shown on CA7 and MI15 Luminex diagrams. 767 768 Statistical analysis was done with Student’s t-test and post-testing for cumulative distribution. 769 (G). *p< 0.05, **, p<0.01, *** p<0.001, **** p <0.0001 ns= non-significant 770 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

771 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

772 Figure 5. T-bethi HA-specific Bmem correlate with long-lived Ab after IIV with clones that 773 are preferentially recalled into the PB repertoire upon antigen re-challenge. 774 775 (A-D) Correlation between fold change in HA-IgG (day 0 to day 120) and the magnitude of the 776 day 7 HApos T-bethi and day 7 HApos T-betlo Bmem response (expressed as percent of total 777 NPCs) in 19 healthy individuals who received the 2015 IIV. The 2015 IIV included the California 778 H1 (Ca-H1) and Switzerland H3 (Sw-H3) antigens. Correlations between HA antigen-specific 779 populations and corresponding HA titer is shown. Other relevant correlations are shown in 780 Supplemental Figure 1. 781 (E-K) Ten individuals under study received serial IIV and had the HA-specific B cell subset 782 assessed by flow cytometry. Three of these individuals (donor 1, 2, and 3) were examined using 783 next-generation sequencing for repertoire analysis in both vaccine years. Data from donor 3 is 784 shown in Supplemental Figure 3. 785 (E) Pre-vaccine HA-IgG titer in subjects under study who received the IIV in sequential vaccine 786 seasons. 787 (F) Dot plot shows the magnitude by year of the total, T-bet hi and T-bet lo D7 HA-specific Bmem 788 population expressed as a percent of the NPC gate in 10 individuals given sequential IIV. 789 (G) Representative FACS plot from a single individual vaccinated in 2015 and 2016 showing the 790 frequency of the H1 population by T-bet expression within 7 days of IIV. The H1 vaccine antigen 791 was conserved between the 2015 and 2016 IIV. 792 (H) Representative FACS plot from a single individual vaccinated in 2016 and 2017 showing the 793 frequency of the H3 population by T-bet expression within 7 days of IIV. The H3 vaccine antigen 794 was conserved between the 2016 and 2017 IIV. 795 (I-J) Lineages of D7 2017 PBs (thick green line) were rank ordered by descending size and the 796 percent of day 7 2016 Bmem and 2016 PB lineages (thin green line) that are shared with these 797 rank ordered day 7 2017 PB clonotypes is plotted. 2016 D7 H3pos Bmem lineages are divided as 798 total T-bet hi clones (solid red line), T-bethi exclusive clones (dotted red line), total T-bet lo clones 799 (solid blue line), T-bet lo exclusive clones (dotted blue line). Corresponding summary table 800 depicting percent of shared lineages between Bmem and PB subsets over time is shown in the 801 Supplementary File 2. 802 (K) Alluvial plot depicts the clonal relatedness of 2017 D7 PB clones to those from the 2016 D7 803 H3 T-bet hi and H3 T-bet lo Bmem subsets from Donor 2. Brown ribbons correspond to clones 804 shared across 3 populations. Green-blue ribbons correspond to clones shared across 2 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

805 populations. Only those lineages that have connectivity with 2017 D7 PB clones are depicted 806 here. 807 (L) Candidate model. Abbreviations for long-lived antibody-secreting cells (LL-ASCs), effector

808 Bmem (BEM) and central Bmem (BCM) are used. 809 810 Statistical analyses were performed with Spearman correlations (A-D), Student’s t-test (E) and 811 one-way ANOVA (Friedman test) (F). *p< 0.05, **, p<0.01, *** p<0.001, **** p <0.0001 ns= non- 812 significant 813 814 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

815 Supplemental Figure 1. 816 817 (A-C) Gating strategy that defines the IgDneg, non-plasma cell (NPC) CD38 hi and naïve B cell 818 (A), plasmablast, PB (B), and circulating Tfh (cTfh) (C) populations. Among 19 subjects who 819 received the 2015 IIV, the magnitude of the PB response expressed as percent live CD19+ B 820 cells between day 0 to day 7 after IIV (B) and the cTfh response expressed as percent live CD4 821 T cells between day 0 and day 7 (C) is also depicted. 822 (D) FACS plots depict phenotyping of H1pos T-bet hi (red), H1pos T-bet lo (blue), non-H1pos T-bet lo 823 (gray), and non H1pos T-bet hi (pink) populations according to CD27, CD11c, Fcrl5, CXCR5 and 824 CD21 expression. 825 (E) ImageStream analysis of B cells within 7 days of IIV. Representative Brightfield images of 15 826 CD38 hi, H1pos T-bet hi Bmem, and H1 pos T-bet lo Bmem are depicted. 827 (F-S) These data refer to correlations between various subsets among 19 healthy subjects who 828 received the 2015 IIV that included the California H1 (Ca-H1) and Switzerland (Sw-H3) 829 antigens. 830 (F-I) Correlations between the fold change in cTfh from day 0 to day 7 after IIV with percent day 831 7 antigen specific (Ca-H1 or Sw-H3) T-bet hi and T-bet lo Bmem out of the total NPC gate. 832 (J-K) Correlation between fold change in H1 and H3 IgG titer from day 0 to day 120 after IIV 833 and the fold change in the day 7 PB and cTfh response expressed as percent from live CD19+ B 834 and CD4+ T cells respectively. 835 (L) Correlation between fold change in H3 IgG titer from day 0 to day 120 after IIV and the 836 percent day 7 Ca-H1pos T-bethi Bmem subset from the parent NPC gate. 837 (M) Correlation between the fold change in H1 IgG titer from day 0 to day 120 after IIV and the 838 percent day 7 Sw-H3 T-bet hi Bmem subset from the parent NPC gate. 839 (N) Correlation between the fold change in H1 titer from day 0 to day 120 after IIV and the 840 percent day 14 Ca-H1 pos T-bet hi Bmem subset from the parent NPC gate. 841 (O) Correlation between the fold change in H3 titer from day 0 to day 120 after IIV and the 842 percent day 14 Ca-H1pos T-bethi Bmem subset from the parent NPC gate. 843 (P) Correlation between the fold change in H1 titer from day 0 to day 120 after IIV and the 844 percent D14 Ca-H1 T-bet lo Bmem subset from the parent NPC gate. 845 (Q) Correlation between the fold change in H3 IgG from day 0 to day 120 and the percent day 846 14 Sw-H3 T-bet hi Bmem subset from the parent NPC gate. 847 (R) Correlation between the fold change in H1 IgG from day 0 to day 120 and the percent day 848 14 Sw-H3 T-bet hi Bmem subset from the parent NPC gate. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

849 (S) Correlation between the fold change in H3 IgG from day 0 to day 120 and the day 14 Sw-H3 850 T-bet lo Bmem subset from the parent NPC gate. 851 852 Statistical analysis was done with Student’s t-test (B, C) and Spearman correlation (F-S). *p< 853 0.05, **, p<0.01, *** p<0.001, **** p <0.0001 ns= non-significant 854 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

855 Supplemental Figure 2 856 857 (A) Comparison of DEGs (defined as log 2FC, q <0.05) between published CD21lo over CD21hi 858 Bmem after IIV20 and day HA pos T-bet hi (Fcrl5hi) over day 7 HA pos T-bet lo Fcrl5lo Bmem studied 859 here. Significant DEGs that are shared between gene lists and different between gene lists are 860 distingusihed by color. Target genes of interest are annotated. 861 (B) Gene set enrichment analysis (GSEA) comparing the transcriptome profile of day 7 H1pos T- 862 bethi over day 7 H1pos T-betlo Bmem to additional published gene sets of effector memory T cells 863 over central memory T cells.48-50 Data is reported as enrichment score (ES) plotted against 864 ranked gene list (n = 10992 genes) of day 7 H1pos T-bethi over day 7 H1pos T-betlo Bmem with the 865 dotted line indicating the leading edge of genes and the purple triangle demarcating the change 866 in gene expression polarity. Normalized enrichment score (NES) and p value are also reported. 867 (C) Circulating plasmablasts (PB, green), naïve B cells (brown, CD19pos CD27neg IgDpos, gating 868 strategy in Supplemental Figure 1), and H1pos Bmem classified by FcrL5 expression (T- 869 bet/Fcrl5hi, red; T-bet/Fcrl5lo, blue) were sort-purified from (4) subjects at day 14 after 2017 IIV 870 for comparative transcriptional analysis via RNA-seq. Principal component analysis of these 871 data is shown. 872 (D) Circulating H1 pos T-bet hi (N=4) Bmem, H1 pos T-bet lo Bmem (N=4), and day 7 PB (N=5) 873 were sort-purified for ATAC-seq using Fcrl5 as a cell surface surrogate for T-bet expression . 874 Principal component analysis of these data is show here. 875 (E) Defined as Reads per Peak per Million (RPPM), accessibility at genes known to function as 876 target genes of IRF4 in human plasma cells51 was assessed in each population sorted for 877 ATAC-seq as shown in Supplemental Figure 2D. 878 (F-H) Live CD19+ B cells were purified in one subject within 7 days of IIV for ImageStream 879 resolution of the H1pos Bmem compartment by T-bet expression. FLOCK analysis of 880 Imagestream data is shown as heat map with cluster size indicated by an accompanying bar 881 plot. Five target clusters of interest were identified and colorized (green, pink, magenta, red, 882 blue). Expression of intracellular and extracellular tetramer stain of these 5 target clusters 883 shown by dot plot (G-H). 884 (I) Genome plot of chromatin accessibility for the XBP1 locus is shown in D7 PB, D14 H1pos T- 885 bet hi Bmem, D14 H1pos T-bet lo Bmem aligned with previously published T-bet binding sites as 886 assessed by ChiP-seq.10 Data is reported as RPPM. 887 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

888 Supplemental Figure 3 889 890 (A) Alluvial plots depict connectivity of clonotypes in donor 3 over time after IIV. Connectivity 891 between D14 Ca-H1 T-betlo Bmem and D7 Ca-H1 Fcrl5hi clonotypes and D14 HK-H3pos T-betlo 892 Bmem clonotypes or D14 HK-H3 Fcrl5hi Bmem clonotypes is shown. Connectivity is defined 893 according to 85% CDR3 sequence similarity. Red-yellow ribbons correspond to clones shared 894 across 3 populations. Green-blue ribbons correspond to clones shared across 2 populations. 895 Only those lineages that have connectivity with day 14 clones are depicted here. (B-C) 896 Lineages of day 28 H1pos Bmem populations were rank ordered by descending size and the 897 percent of day 14 H1pos T-bet hi (B) or day 14 H1 pos T-bet lo (C) Bmem lineages that are shared 898 by rank ordered D28 clonotype is plotted. Day 14 H3pos Bmem lineages are divided as total T- 899 bet hi clones (solid red line), T-bet hi exclusive clones (dotted red line), total T-bet lo clones (solid 900 blue line), T-bet lo exclusive clones (dotted blue line). Corresponding summary table depicting 901 percent of shared lineages between Bmem over time is shown in the Supplementary File 2. 902 (D) Lineages of D7 2017 PBs were rank ordered by descending size and the percent of D14 903 2016 Bmem and 2016 PB lineages that are shared with these rank ordered D7 2017 PB 904 clonotypes are plotted. Day 14 H3pos Bmem lineages are divided as total T-bet hi clones (solid 905 red line), T-bet hi exclusive clones (dotted red line), total T-bet lo clones (solid blue line), T-bet lo 906 exclusive clones (dotted blue line). Corresponding summary table depicting percent of shared 907 lineages between Bmem and PB subsets over time is shown in the Supplementary File 2. 908 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

909 References: 910 1. Chiu C, Ellebedy AH, Wrammert J, Ahmed R. B cell responses to influenza infection and 911 vaccination. Curr Top Microbiol Immunol. 2015;386:381-398. 912 2. Guthmiller JJ, Wilson PC. Harnessing immune history to combat influenza viruses. Curr 913 Opin Immunol. 2018;53:187-195. 914 3. Tangye SG, Liu YJ, Aversa G, Phillips JH, de Vries JE. Identification of functional human 915 splenic memory B cells by expression of CD148 and CD27. J Exp Med. 916 1998;188(9):1691-1703. 917 4. Klein U, Rajewsky K, Kuppers R. Human immunoglobulin (Ig)M+IgD+ peripheral blood B 918 cells expressing the CD27 cell surface antigen carry somatically mutated variable region 919 genes: CD27 as a general marker for somatically mutated (memory) B cells. J Exp Med. 920 1998;188(9):1679-1689. 921 5. Maurer D, Fischer GF, Fae I, et al. IgM and IgG but not cytokine secretion is restricted to 922 the CD27+ B lymphocyte subset. J Immunol. 1992;148(12):3700-3705. 923 6. Agematsu K, Nagumo H, Yang FC, et al. B cell subpopulations separated by CD27 and 924 crucial collaboration of CD27+ B cells and helper T cells in immunoglobulin production. 925 Eur J Immunol. 1997;27(8):2073-2079. 926 7. Myles A, Sanz I, Cancro MP. T-bet(+) B cells: A common denominator in protective and 927 autoreactive antibody responses? Curr Opin Immunol. 2019;57:40-45. 928 8. Stone SL, Peel JN, Scharer CD, et al. T-bet Transcription Factor Promotes Antibody- 929 Secreting Cell Differentiation by Limiting the Inflammatory Effects of IFN-gamma on B 930 Cells. Immunity. 2019. 931 9. Haga CL, Ehrhardt GR, Boohaker RJ, Davis RS, Cooper MD. Fc receptor-like 5 inhibits 932 B cell activation via SHP-1 tyrosine phosphatase recruitment. Proc Natl Acad Sci U S A. 933 2007;104(23):9770-9775. 934 10. Soderquest K, Hertweck A, Giambartolomei C, et al. Genetic variants alter T-bet binding 935 and gene expression in mucosal inflammatory disease. PLoS Genet. 936 2017;13(2):e1006587. 937 11. Morita R, Schmitt N, Bentebibel SE, et al. Human blood CXCR5(+)CD4(+) T cells are 938 counterparts of T follicular cells and contain specific subsets that differentially support 939 antibody secretion. Immunity. 2011;34(1):108-121. 940 12. Herati RS, Reuter MA, Dolfi DV, et al. Circulating CXCR5+PD-1+ response predicts 941 influenza vaccine antibody responses in young adults but not elderly adults. J Immunol. 942 2014;193(7):3528-3537. 943 13. Wrammert J, Smith K, Miller J, et al. Rapid cloning of high-affinity human monoclonal 944 antibodies against influenza virus. Nature. 2008;453(7195):667-671. 945 14. Lee FE, Halliley JL, Walsh EE, et al. Circulating human antibody-secreting cells during 946 vaccinations and respiratory viral infections are characterized by high specificity and lack 947 of bystander effect. J Immunol. 2011;186(9):5514-5521. 948 15. Wrammert J, Koutsonanos D, Li GM, et al. Broadly cross-reactive antibodies dominate 949 the human B cell response against 2009 pandemic H1N1 influenza virus infection. J Exp 950 Med. 2011;208(1):181-193. 951 16. Andrews SF, Huang Y, Kaur K, et al. Immune history profoundly affects broadly 952 protective B cell responses to influenza. Sci Transl Med. 2015;7(316):316ra192. 953 17. Andrews SF, Kaur K, Pauli NT, Huang M, Huang Y, Wilson PC. High preexisting 954 serological antibody levels correlate with diversification of the influenza vaccine 955 response. J Virol. 2015;89(6):3308-3317. 956 18. Jackson KJ, Liu Y, Roskin KM, et al. Human responses to influenza vaccination show 957 seroconversion signatures and convergent antibody rearrangements. Cell Host Microbe. 958 2014;16(1):105-114. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

959 19. Ellebedy AH, Jackson KJ, Kissick HT, et al. Defining antigen-specific plasmablast and 960 memory B cell subsets in human blood after viral infection or vaccination. Nat Immunol. 961 2016;17(10):1226-1234. 962 20. Lau D, Lan LY, Andrews SF, et al. Low CD21 expression defines a population of recent 963 germinal center graduates primed for plasma cell differentiation. Sci Immunol. 2017;2(7). 964 21. Koutsakos M, Wheatley AK, Loh L, et al. Circulating TFH cells, serological memory, and 965 tissue compartmentalization shape human influenza-specific B cell immunity. Sci Transl 966 Med. 2018;10(428). 967 22. Allie SR, Bradley JE, Mudunuru U, et al. The establishment of resident memory B cells 968 in the lung requires local antigen encounter. Nat Immunol. 2019;20(1):97-108. 969 23. Knox JJ, Buggert M, Kardava L, et al. T-bet+ B cells are induced by human viral 970 infections and dominate the HIV gp140 response. JCI Insight. 2017;2(8). 971 24. Wang S, Wang J, Kumar V, et al. IL-21 drives expansion and plasma cell differentiation 972 of autoreactive CD11c(hi)T-bet(+) B cells in SLE. Nat Commun. 2018;9(1):1758. 973 25. Jenks SA, Cashman KS, Zumaquero E, et al. Distinct Effector B Cells Induced by 974 Unregulated Toll-like Receptor 7 Contribute to Pathogenic Responses in Systemic 975 Lupus Erythematosus. Immunity. 2018;49(4):725-739 e726. 976 26. Rubtsova K, Rubtsov AV, van Dyk LF, Kappler JW, Marrack P. T-box transcription factor 977 T-bet, a key player in a unique type of B-cell activation essential for effective viral 978 clearance. Proc Natl Acad Sci U S A. 2013;110(34):E3216-3224. 979 27. Rubtsova K, Rubtsov AV, Thurman JM, Mennona JM, Kappler JW, Marrack P. B cells 980 expressing the transcription factor T-bet drive lupus-like autoimmunity. J Clin Invest. 981 2017;127(4):1392-1404. 982 28. Peng SL, Szabo SJ, Glimcher LH. T-bet regulates IgG class switching and pathogenic 983 autoantibody production. Proc Natl Acad Sci U S A. 2002;99(8):5545-5550. 984 29. Barnett BE, Staupe RP, Odorizzi PM, et al. Cutting Edge: B Cell-Intrinsic T-bet 985 Expression Is Required To Control Chronic Viral Infection. J Immunol. 986 2016;197(4):1017-1022. 987 30. Sobecki M, Mrouj K, Colinge J, et al. Cell-Cycle Regulation Accounts for Variability in Ki- 988 67 Expression Levels. Cancer Res. 2017;77(10):2722-2734. 989 31. Miller I, Min M, Yang C, et al. Ki67 is a Graded Rather than a Binary Marker of 990 Proliferation versus Quiescence. Cell Rep. 2018;24(5):1105-1112 e1105. 991 32. Lazarevic V, Glimcher LH, Lord GM. T-bet: a bridge between innate and adaptive 992 immunity. Nat Rev Immunol. 2013;13(11):777-789. 993 33. Szabo SJ, Kim ST, Costa GL, Zhang X, Fathman CG, Glimcher LH. A novel transcription 994 factor, T-bet, directs Th1 lineage commitment. Cell. 2000;100(6):655-669. 995 34. Sanz I, Wei C, Lee FE, Anolik J. Phenotypic and functional heterogeneity of human 996 memory B cells. Semin Immunol. 2008;20(1):67-82. 997 35. Kallies A, Hasbold J, Tarlinton DM, et al. Plasma cell ontogeny defined by quantitative 998 changes in blimp-1 expression. J Exp Med. 2004;200(8):967-977. 999 36. Kallies A, Hasbold J, Fairfax K, et al. Initiation of plasma-cell differentiation is 1000 independent of the transcription factor Blimp-1. Immunity. 2007;26(5):555-566. 1001 37. Shapiro-Shelef M, Lin KI, McHeyzer-Williams LJ, Liao J, McHeyzer-Williams MG, 1002 Calame K. Blimp-1 is required for the formation of immunoglobulin secreting plasma 1003 cells and pre-plasma memory B cells. Immunity. 2003;19(4):607-620. 1004 38. Shaffer AL, Lin KI, Kuo TC, et al. Blimp-1 orchestrates plasma cell differentiation by 1005 extinguishing the mature B cell gene expression program. Immunity. 2002;17(1):51-62. 1006 39. Raymond DD, Bajic G, Ferdman J, et al. Conserved epitope on influenza-virus 1007 hemagglutinin head defined by a vaccine-induced antibody. Proc Natl Acad Sci U S A. 1008 2018;115(1):168-173. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

1009 40. Linderman SL, Chambers BS, Zost SJ, et al. Potential antigenic explanation for atypical 1010 H1N1 infections among middle-aged adults during the 2013-2014 influenza season. 1011 Proc Natl Acad Sci U S A. 2014;111(44):15798-15803. 1012 41. Iwakoshi NN, Lee AH, Vallabhajosyula P, Otipoby KL, Rajewsky K, Glimcher LH. 1013 Plasma cell differentiation and the unfolded protein response intersect at the 1014 transcription factor XBP-1. Nat Immunol. 2003;4(4):321-329. 1015 42. Iwakoshi NN, Lee AH, Glimcher LH. The X-box binding protein-1 transcription factor is 1016 required for plasma cell differentiation and the unfolded protein response. Immunol Rev. 1017 2003;194:29-38. 1018 43. Ochiai K, Maienschein-Cline M, Simonetti G, et al. Transcriptional regulation of germinal 1019 center B and plasma cell fates by dynamical control of IRF4. Immunity. 2013;38(5):918- 1020 929. 1021 44. Sciammas R, Shaffer AL, Schatz JH, Zhao H, Staudt LM, Singh H. Graded expression of 1022 interferon regulatory factor-4 coordinates isotype switching with plasma cell 1023 differentiation. Immunity. 2006;25(2):225-236. 1024 45. Omilusik KD, Best JA, Yu B, et al. Transcriptional repressor ZEB2 promotes terminal 1025 differentiation of CD8+ effector and memory T cell populations during infection. J Exp 1026 Med. 2015;212(12):2027-2039. 1027 46. Dominguez CX, Amezquita RA, Guan T, et al. The transcription factors ZEB2 and T-bet 1028 cooperate to program cytotoxic T cell terminal differentiation in response to LCMV viral 1029 infection. J Exp Med. 2015;212(12):2041-2056. 1030 47. Schaerli P, Moser B. Chemokines: control of primary and memory T-cell traffic. Immunol 1031 Res. 2005;31(1):57-74. 1032 48. Kaech SM, Hemby S, Kersh E, Ahmed R. Molecular and functional profiling of memory 1033 CD8 T cell differentiation. Cell. 2002;111(6):837-851. 1034 49. Wherry EJ, Ha SJ, Kaech SM, et al. Molecular signature of CD8+ T cell exhaustion 1035 during chronic viral infection. Immunity. 2007;27(4):670-684. 1036 50. Luckey CJ, Bhattacharya D, Goldrath AW, Weissman IL, Benoist C, Mathis D. Memory T 1037 and memory B cells share a transcriptional program of self-renewal with long-term 1038 hematopoietic stem cells. Proc Natl Acad Sci U S A. 2006;103(9):3304-3309. 1039 51. Shaffer AL, Emre NC, Lamy L, et al. IRF4 addiction in multiple myeloma. Nature. 1040 2008;454(7201):226-231. 1041 52. Yu B, Zhang K, Milner JJ, et al. Epigenetic landscapes reveal transcription factors that 1042 regulate CD8(+) T cell differentiation. Nat Immunol. 2017;18(5):573-582. 1043 53. Kurachi M, Barnitz RA, Yosef N, et al. The transcription factor BATF operates as an 1044 essential differentiation checkpoint in early effector CD8+ T cells. Nat Immunol. 1045 2014;15(4):373-383. 1046 54. Kanda M, Yamanaka H, Kojo S, et al. Transcriptional regulator Bhlhe40 works as a 1047 cofactor of T-bet in the regulation of IFN-gamma production in iNKT cells. Proc Natl 1048 Acad Sci U S A. 2016;113(24):E3394-3402. 1049 55. Zhou X, Yu S, Zhao DM, Harty JT, Badovinac VP, Xue HH. Differentiation and 1050 persistence of memory CD8(+) T cells depend on T cell factor 1. Immunity. 1051 2010;33(2):229-240. 1052 56. Scharer CD, Barwick BG, Guo M, Bally APR, Boss JM. Plasma cell differentiation is 1053 controlled by multiple cell division-coupled epigenetic programs. Nat Commun. 1054 2018;9(1):1698. 1055 57. Caron G, Hussein M, Kulis M, et al. Cell-Cycle-Dependent Reconfiguration of the DNA 1056 Methylome during Terminal Differentiation of Human B Cells into Plasma Cells. Cell 1057 Rep. 2015;13(5):1059-1071. 1058 58. Buttitta LA, Edgar BA. Mechanisms controlling cell cycle exit upon terminal 1059 differentiation. Curr Opin Cell Biol. 2007;19(6):697-704. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

1060 59. Rakhmanov M, Sic H, Kienzler AK, et al. High levels of SOX5 decrease proliferative 1061 capacity of human B cells, but permit plasmablast differentiation. PLoS One. 1062 2014;9(6):e100328. 1063 60. Mitxelena J, Apraiz A, Vallejo-Rodriguez J, Malumbres M, Zubiaga AM. E2F7 regulates 1064 transcription and maturation of multiple microRNAs to restrain cell proliferation. Nucleic 1065 Acids Res. 2016. 1066 61. Westendorp B, Mokry M, Groot Koerkamp MJ, Holstege FC, Cuppen E, de Bruin A. 1067 E2F7 represses a network of oscillating cell cycle genes to control S-phase progression. 1068 Nucleic Acids Res. 2012;40(8):3511-3523. 1069 62. Schebesta A, McManus S, Salvagiotto G, Delogu A, Busslinger GA, Busslinger M. 1070 Transcription factor Pax5 activates the chromatin of key genes involved in B cell 1071 signaling, adhesion, migration, and immune function. Immunity. 2007;27(1):49-63. 1072 63. Casolari DA, Makri M, Yoshida C, Muto A, Igarashi K, Melo JV. Transcriptional 1073 suppression of BACH2 by the Bcr-Abl oncoprotein is mediated by PAX5. Leukemia. 1074 2013;27(2):409-415. 1075 64. Hipp N, Symington H, Pastoret C, et al. IL-2 imprints human naive B cell fate towards 1076 plasma cell through ERK/ELK1-mediated BACH2 repression. Nat Commun. 1077 2017;8(1):1443. 1078 65. Le Gallou S, Caron G, Delaloy C, Rossille D, Tarte K, Fest T. IL-2 requirement for 1079 human plasma cell generation: coupling differentiation and proliferation by enhancing 1080 MAPK-ERK signaling. J Immunol. 2012;189(1):161-173. 1081 66. Tourigny MR, Ursini-Siegel J, Lee H, et al. CDK inhibitor p18(INK4c) is required for the 1082 generation of functional plasma cells. Immunity. 2002;17(2):179-189. 1083 67. Morse L, Chen D, Franklin D, Xiong Y, Chen-Kiang S. Induction of cell cycle arrest and 1084 B cell terminal differentiation by CDK inhibitor p18(INK4c) and IL-6. Immunity. 1085 1997;6(1):47-56. 1086 68. Schrantz N, Beney GE, Auffredou MT, Bourgeade MF, Leca G, Vazquez A. The 1087 expression of p18INK4 and p27kip1 cyclin-dependent kinase inhibitors is regulated 1088 differently during human B cell differentiation. J Immunol. 2000;165(8):4346-4352. 1089 69. Oestreich KJ, Read KA, Gilbertson SE, et al. Bcl-6 directly represses the gene program 1090 of the glycolysis pathway. Nat Immunol. 2014;15(10):957-964. 1091 70. Hough KP, Chisolm DA, Weinmann AS. Transcriptional regulation of T cell metabolism. 1092 Mol Immunol. 2015;68(2 Pt C):520-526. 1093 71. Takayanagi S, Fukuda R, Takeuchi Y, Tsukada S, Yoshida K. Gene regulatory network 1094 of unfolded protein response genes in endoplasmic reticulum stress. Cell Stress 1095 Chaperones. 2013;18(1):11-23. 1096 72. Hung CL, Wang LY, Yu YL, et al. A long noncoding RNA connects c-Myc to tumor 1097 metabolism. Proc Natl Acad Sci U S A. 2014;111(52):18697-18702. 1098 73. Gibellini L, Losi L, De Biasi S, et al. LonP1 Differently Modulates Mitochondrial Function 1099 and Bioenergetics of Primary Versus Metastatic Colon Cancer Cells. Front Oncol. 1100 2018;8:254. 1101 74. Yoshida S, Tsutsumi S, Muhlebach G, et al. Molecular chaperone TRAP1 regulates a 1102 metabolic switch between mitochondrial respiration and aerobic glycolysis. Proc Natl 1103 Acad Sci U S A. 2013;110(17):E1604-1612. 1104 75. van der Windt GJ, Everts B, Chang CH, et al. Mitochondrial respiratory capacity is a 1105 critical regulator of CD8+ T cell memory development. Immunity. 2012;36(1):68-78. 1106 76. McCarthy KR, Watanabe A, Kuraoka M, et al. Memory B Cells that Cross-React with 1107 Group 1 and Group 2 Influenza A Viruses Are Abundant in Adult Human Repertoires. 1108 Immunity. 2018;48(1):174-184 e179. 1109 77. Wang J, Hilchey SP, Hyrien O, et al. Multi-Dimensional Measurement of Antibody- 1110 Mediated Heterosubtypic Immunity to Influenza. PLoS One. 2015;10(6):e0129858. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

1111 78. Xu R, Ekiert DC, Krause JC, Hai R, Crowe JE, Jr., Wilson IA. Structural basis of 1112 preexisting immunity to the 2009 H1N1 pandemic influenza virus. Science. 1113 2010;328(5976):357-360. 1114 79. Smith GJ, Vijaykrishna D, Bahl J, et al. Origins and evolutionary genomics of the 2009 1115 swine-origin H1N1 influenza A epidemic. Nature. 2009;459(7250):1122-1125. 1116 80. Takahashi Y, Dutta PR, Cerasoli DM, Kelsoe G. In situ studies of the primary immune 1117 response to (4-hydroxy-3-nitrophenyl)acetyl. V. Affinity maturation develops in two 1118 stages of clonal selection. J Exp Med. 1998;187(6):885-895. 1119 81. Zumaquero E, Stone SL, Scharer CD, et al. IFNgamma induces epigenetic programming 1120 of human T-bet(hi) B cells and promotesTLR7/8 and IL-21 induced differentiation. Elife. 1121 2019;8. 1122 82. Isnardi I, Ng YS, Menard L, et al. Complement receptor 2/CD21- human naive B cells 1123 contain mostly autoreactive unresponsive clones. Blood. 2010;115(24):5026-5036. 1124 83. Moir S, Ho J, Malaspina A, et al. Evidence for HIV-associated B cell exhaustion in a 1125 dysfunctional memory B cell compartment in HIV-infected viremic individuals. J Exp 1126 Med. 2008;205(8):1797-1805. 1127 84. Kardava L, Moir S, Shah N, et al. Abnormal B cell memory subsets dominate HIV- 1128 specific responses in infected individuals. J Clin Invest. 2014;124(7):3252-3262. 1129 85. Obeng-Adjei N, Portugal S, Holla P, et al. Malaria-induced interferon-gamma drives the 1130 expansion of Tbethi atypical memory B cells. PLoS Pathog. 2017;13(9):e1006576. 1131 86. Buck MD, O'Sullivan D, Klein Geltink RI, et al. Mitochondrial Dynamics Controls T Cell 1132 Fate through Metabolic Programming. Cell. 2016;166(1):63-76. 1133 87. Buck MD, Sowell RT, Kaech SM, Pearce EL. Metabolic Instruction of Immunity. Cell. 1134 2017;169(4):570-586. 1135 88. Phan AT, Doedens AL, Palazon A, et al. Constitutive Glycolytic Metabolism Supports 1136 CD8(+) T Cell Effector Memory Differentiation during Viral Infection. Immunity. 1137 2016;45(5):1024-1037. 1138 89. Gass JN, Gifford NM, Brewer JW. Activation of an unfolded protein response during 1139 differentiation of antibody-secreting B cells. J Biol Chem. 2002;277(50):49047-49054. 1140 90. Gass JN, Jiang HY, Wek RC, Brewer JW. The unfolded protein response of B- 1141 lymphocytes: PERK-independent development of antibody-secreting cells. Mol Immunol. 1142 2008;45(4):1035-1043. 1143 91. Tellier J, Shi W, Minnich M, et al. Blimp-1 controls plasma cell function through the 1144 regulation of immunoglobulin secretion and the unfolded protein response. Nat Immunol. 1145 2016;17(3):323-330. 1146 92. Shaffer AL, Shapiro-Shelef M, Iwakoshi NN, et al. XBP1, downstream of Blimp-1, 1147 expands the secretory apparatus and other organelles, and increases protein synthesis 1148 in plasma cell differentiation. Immunity. 2004;21(1):81-93. 1149 93. Taubenheim N, Tarlinton DM, Crawford S, Corcoran LM, Hodgkin PD, Nutt SL. High rate 1150 of antibody secretion is not integral to plasma cell differentiation as revealed by XBP-1 1151 deficiency. J Immunol. 2012;189(7):3328-3338. 1152 94. Pengo N, Scolari M, Oliva L, et al. Plasma cells require autophagy for sustainable 1153 immunoglobulin production. Nat Immunol. 2013;14(3):298-305. 1154 95. Halliley JL, Tipton CM, Liesveld J, et al. Long-Lived Plasma Cells Are Contained within 1155 the CD19(-)CD38(hi)CD138(+) Subset in Human Bone Marrow. Immunity. 1156 2015;43(1):132-145. 1157 96. Nakaya HI, Hagan T, Duraisingham SS, et al. Systems Analysis of Immunity to Influenza 1158 Vaccination across Multiple Years and in Diverse Populations Reveals Shared Molecular 1159 Signatures. Immunity. 2015;43(6):1186-1198. bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

1160 97. Tan Y, Tamayo P, Nakaya H, Pulendran B, Mesirov JP, Haining WN. Gene signatures 1161 related to B-cell proliferation predict influenza vaccine-induced antibody response. Eur J 1162 Immunol. 2014;44(1):285-295. 1163 98. Takahashi Y, Kelsoe G. Role of germinal centers for the induction of broadly-reactive 1164 memory B cells. Curr Opin Immunol. 2017;45:119-125. 1165 99. Finney J, Yeh CH, Kelsoe G, Kuraoka M. Germinal center responses to complex 1166 antigens. Immunol Rev. 2018;284(1):42-50. 1167 100. Kuraoka M, Schmidt AG, Nojima T, et al. Complex Antigens Drive Permissive Clonal 1168 Selection in Germinal Centers. Immunity. 2016;44(3):542-552. 1169 101. Sanyal M, Holmes TH, Maecker HT, et al. Diminished B-Cell Response After Repeat 1170 Influenza Vaccination. J Infect Dis. 2019;219(10):1586-1595. 1171 102. Zarnitsyna VI, Ellebedy AH, Davis C, Jacob J, Ahmed R, Antia R. Masking of antigenic 1172 epitopes by antibodies shapes the humoral immune response to influenza. Philos Trans 1173 R Soc Lond B Biol Sci. 2015;370(1676). 1174 103. Onodera T, Takahashi Y, Yokoi Y, et al. Memory B cells in the lung participate in 1175 protective humoral immune responses to pulmonary influenza virus reinfection. Proc Natl 1176 Acad Sci U S A. 2012;109(7):2485-2490. 1177 104. Heinz S, Benner C, Spann N, et al. Simple combinations of lineage-determining 1178 transcription factors prime cis-regulatory elements required for macrophage and B cell 1179 identities. Mol Cell. 2010;38(4):576-589. 1180 105. Lawrence M, Huber W, Pages H, et al. Software for computing and annotating genomic 1181 ranges. PLoS Comput Biol. 2013;9(8):e1003118. 1182 106. Scharer CD, Blalock EL, Barwick BG, et al. ATAC-seq on biobanked specimens defines 1183 a unique chromatin accessibility structure in naive SLE B cells. Sci Rep. 2016;6:27030. 1184 107. Tipton CM, Fucile CF, Darce J, et al. Diversity, cellular origin and autoreactivity of 1185 antibody-secreting cell population expansions in acute systemic lupus erythematosus. 1186 Nat Immunol. 2015;16(7):755-765. 1187 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Figure 1 A CD19pos IgDneg D7 IIV 105 104 103

0 H1-Tet 0 103 104 105 0 103 104 105 0 103 104 105 0 103 104 105 0 103 104 105 0 50K 150K 250K Ki-67 Ki-67 CD38 T-bet H1-Tet SSC-A

B 1500 * HA Tbet hi 1000 HA Tbet lo

500 Ki-67 gMFI

0 0 7 14 21 28 0 7 14 21 28 Day after Vaccine C * D * E * * * F * * * * * ns ns ns 6 * 8 * * * * * 6 * 6 * * * *

6 hi lo hi lo * * * * * * 4 * 4 4 * * * * * * 2 * * 3 4 * * 2 * 2 1 2 * 1 0 0 0 0 % D7 Ca-H1-T-bet % D7 Sw-H3-T-bet % D7 Sw-H3-T-bet % D7 Ca-H1-T-bet 0 7 14 21 28 0 7 14 21 28 0 7 14 21 28 0 7 14 21 28 Day after Vaccine Day after Vaccine Day after Vaccine Day after Vaccine

G H I J 2.0 4 lo 25 ns 25 ns ns lo ns 20 20 1.5 3 hi hi 15 D7 Ca-H1 Tbet 15 D7 Sw-H3 Tbet lo PB 1.0 PB D7 Ca-H1 Tbet lo D7 Sw-H3 Tbet 2 ∆ ∆ 10 10 5 5 0.5 1 0 0 % D7 Ca-H1-T-bet 1 2 3 4 1 2 3 4 0.0 % D70 Sw-H3-T-bet -5 -5 1 2 3 4 0.5 1.0 1.5 2.0 2.5 % of NPCs % of NPCs % D7 Ca-H1-T-bethi % D7 Sw-H3-T-bethi bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Figure 2

A B

2 1500 D7 Naive ns 400 D7 PBs

1 200

pos **** D7 H1 200 ** 150 0 lo T-bet ** **** RPKM 100 ns ns -1 PC2 17.6% 50 D7 H1pos 0 -2 hi 0 T-bet PRDM1 XBP1 IRF4 FCRL5 TBX21 ZEB2 CXCR3 CCR7 -2 0 2 4 H1pos T-betlo H1pos T-bethi PB Naive PC1 51.1% C Cell Cycle D KAECH_DAY8_EFF_VS_ MEMORY_CD8_TCELL_UP I. 0.6 NES: 1.86 0.3

ES p <0.0001 II. 0

hi lo III. T-bet T-bet Rank in Gene List

IV. CCND1 CDK5R1 BCL2 CDKN3 MCM4 MAD2L1 CCNF CCNB1 CDC20 MKI67 CDK1 CCNB2 CDC6 BIRC5 CCNA2 CDK6 TFDP2 BRCA2 GTSE1 CHEK1 CDC25A CDC25C BRCA1 CCNE1 CDKN2C CDKN2A RAD51 WEE1 CDC34 CCNG2 RBBP8 KNTC1 SKP2 MNAT1 CHEK2 RAD9A HUS1 TP53 CUL2 CCNH CUL3 CDK8 CCNT1 CDK7 RAD1 CDKN1B RBL1 MRE11A SERTAD1 KPNA2 CKS2 RBL2 E2F4 MCM5 MCM3 RB1 CUL1 CDKN1A CCND3 CASP3 CCND2 MCM2 CKS1B STMN1 CCNC GADD45A TFDP1 RAD17 CDK4 CDC16 CCNG1 MAD2L2 BCCIP NBN CDK5RAP1 MDM2 CDK2 AURKB AURKA ATM ANAPC2 ATR ABL1

Apoptosis

I.

II.

III.

IV. CD27 TNFRSF1B PARP1 GRB2 CTSS MCL1 BNIP2 CASP3 BAK1 BCL2A1 CD40 TNFRSF10A BIRC3 CASP8 PYCARD SQSTM1 BECN1 CYCS BNIP3L BAX CASP4 BIRC5 BIK TNF TNFRSF1A MAPK8 NAIP IGF1R IGF1 TP73 ESR1 DAPK1 TNFRSF25 CD70 XIAP ULK1 TNFSF8 BMF BCL2 BAG3 FAS TNFRSF10B NOD1 MAP1LC3A HTT HRK NFKB1 TNFSF10 COMMD4 CFLAR TRAF3 TP53BP2 RPS6KB1 DFFA BIRC6 HSPBAP1 CRADD BCL2L1 BNIP3 TMEM57 DIABLO CASP9 BFAR BRAF SPATA2 TXNL4B PIK3C3 C1orf159 FADD CASP10 BID PARP2 EIF5B CASP6 BCL2L11 CASP7 DENND4A CASP1 GAA RIPK2 BAD BCL10 TP53 CASP2 GADD45A TRADD CTSB BIRC2 BAG1 TRAF2 CYLD ATG3 APP AKT1 APAF1 ATG7 ABL1 AIFM1 ATG16L1 ATG12 ATG5

Log I. Naive II. PB III. D7 H1pos T-bethi IV. D7 H1pos T-bet lo 10 pos hi pos lo pos lo pos hi Expression H1 T-bet vs H1 T-bet PB vs H1 T-bet PB vs H1 T-bet 0 Max

D7 H1pos T-bethi over D7 H1pos T-betlo E F **** G E2F7 TBX21 3 neg hi SOX5 D7 H1 T-bet 15 BATF KLF4 BHLHE40 2 ns BHLHE41 TFEC pos hi ARID3A 10-2 D7 H1 T-bet CUX1 10 ns ETS2 MBD2 IRF5 D7 PBs E2F5 TERF2 RPPM -1 5 ETV3 CEBPG PC2 12.6 % pos lo ZKSCAN3 D7 H1 T-bet PKNOX1 ZNF281 ZNF202 HBP1 PATZ1 TGIF2 RNAseq logFC -3 BCL11A SNAI3 0 RELB -4 -2 0 2 4 6 8 Shaffer IRF4 TP63 PRDM4 E2F2MAFF PGR LEF1 MLXIP PC1 51.7% UP in PCs THRA SMAD3 TCF7 HIVEP2 BACH2 NR3C2 -2 -1 0 1 2 -4 -2 0 2 4 PageRank logFC bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Figure 3

A Brightfield CD19 CD38 T-bet H1-Tet IC H1-Tet EC Composite Tet

B **** C **** **** 300000 40000 **** 150000 **** 20000 H1pos T-bethi H1pos T-betlo 40000 **** hi 5000 CD38 20000 0 H1-Tet EC Intensity 0 H1-Tet IC Intensity -5000 D7 H1pos T-bet hi over D7 PB D Unfolded Protein Response E

I. SOX5 EGR2 TFEC SPIB HHEX IRF8 TBX21 FOS NR4A2 II. IRF5 BHLHE40

2 HES1 RFX5 TCF7 FOXP4 TBX19 PRKRIR III. ZNF740 ATF4 RNAseq logFC SNAI3

-2 ATF5 IV. MYB XBP1 PRDM1 RUNX2 IRF4 MIXL1 GFI1 VDR

TCP1 MYBL2 RRM2 UHRF1 TYMS GINS2 ERN1 MCM4 DNAJC3 MAPK8 KCNMB3 HSPA2 MAPK9 CEBPB RNF5 MBTPS2 SREBF1 PPP1R15A PPIA HERPUD1 XBP1 HSPA5 CANX PDIA3 RPN1 CALR MANF SIL1 SEL1L CREB3 GANC BEX2 TRIB3 FBXO6 UGGT1 HTRA2 UFD1L PCNA SEC63 EIF2A NPLOC4 SCAP SEC62 INSIG2 TOR1A USP14 DERL1 HSPA1B EIF2AK3 PFDN5 EDEM1 SERP1 DNAJB9 OS9 GANAB DNAJC10 DDIT3 HSPH1 BAX UBXN4 NUCB1 UBE2G2 HSPA4 CCT4 MBTPS1 ERP44 SYVN1 PRKCSH ATXN3 ATF6B ATF6 ASNS AMFR ATF4 VCP VIMP E2F2

E2F8 BHLHA15 -6 -4 0 4 6

pos hi pos lo Log I. Naive II. PB III. D7 H1 T-bet IV. D7 H1 T-bet 10 -4 -2 0 2 4 pos hi pos lo pos lo pos hi Expression H1 T-bet vs H1 T-bet PB vs H1 T-bet PB vs H1 T-bet 0 Max PageRank logFC

F G PROTON TRANSPORTING INNER MITOCHONDRIAL ANTIGEN PROCESSING 20 Metabolism-Related Terms TWO SECTOR ATPASE MEMBRANE PROTEIN & PRESENTATION (Cluster 2) COMPLEX (1) COMPLEX (2) OF PEPTIDE ANTIGEN (3) 15 0.7 0.8 NES: 2.3 NES: 2.3 0.6 NES: 2.1 10 z-Score 0.4 p <0.0001 0.4 p <0.0001 p <0.0001 4 0.3 5

0(B-H p-value) 0 0 0 1 0 LONP1 TRAP1EGLN TNFSF13 -4 0 PCGEM1IL15 SPP1TCR PLA2R1 HistoneSREBF1 h3 NUBPLAMPKAIFM1MYCNFE2L2ESSRG FBXW7ESRRAHK2MTOR ES -log T-bet hi T-bet lo T-bet hi T-bet lo T-bet hi T-bet lo Rank in Gene List

H XBP1 D7 PB XBP1

D7 H1pos T-bethi

D7 H1pos T-betlo FDR < 0.03

TBX21 ChIP-seq

chr22:28791683-28803118 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Figure 4

A Donor 1 D7 Donor 2 D7 B Donor 1 Donor 2 100 100 100 100 100 100 90 90 90 90 80 80 80 80 80 80 70 70 70 70 60 60 60 60 50 50 50 50 50 50 40 40 40 40 30 30 30 30 20 20 20 20 30 30 10 10 10 10 Cumulative % of Sequences 0 0 0 0

0 2 4 6 0 2 4 6 0 10 20 0 10 20 Cumulative Percent of Sequences Normalized Lineage Size (%) 0 0 Sequences:44394 29876 43587 12349 D7 H3pos D7 H3pos D7 H3pos D7 H3pos Lineages: 2761 2025 375 316 T-bet hi T-bet lo T-bet hi T-bet lo H3pos T-bet lo H3pos T-bet hi C Donor 1 D Donor 1 100 100

80 80

50 50

30 30 Cumulative Percent of Sequences Cumulative Percent of Sequences 0 0 D7 H3pos D14 H3pos D7 H3pos D7 H3pos D14 H3pos D7 H3pos T-bet hi T-bet lo T-bet lo T-bet hi T-bet hi T-bet lo Donor 1 Donor 1 E D7 H3pos Tbet hi F D7 H3pos Tbet hi pos hi pos hi 15 D7 H3 Tbet only 15 D7 H3 Tbet only D7 H3 pos Tbet lo D7 H3 pos Tbet lo D7 H3 pos Tbet lo only D7 H3 pos Tbet lo only

10 10

5 5 % of D7 Bmem Lineages % of D7 Bmem Lineages 0 0 10 10 1 1 .1 .1 .01 .01 .001 Lineage Size (%) .001 Lineage Size (%) .0001 .0001 1 1163 1 1209 D14 Tbet lo Lineages Ordered by Descending Size D14 Tbet hi Lineages Ordered by Descending Size

M15 CA7 PR8 G 60000 ns 60000 ns 60000 p = 0.02

30000 30000 30000 30000 30000 30000 4.0% 2.0% 25000 25000 25000

20000 20000

gMFI 20000

15000 15000 15000

10000 10000 10000

5000 5000 5000

0 T-bet T-bet 0 T-bet T-bet 0 T-bet T-bet

hi lo hi lo hi lo bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Figure 5 A B C D 25 6 r = 0.7 20 r = 0.8 6 ns ns p = 0.003 p = 0.001 20 4 4 4 15 2 2 H3-Abs H3-Abs H1-Abs H1-Abs 10 ∆ 2 ∆ ∆ ∆ 0 0 5 0.5 1.0 1.5 2.0 1 2 3 4 0 0 -2 % D7 Ca-H1-T-bethi 0.5 1.0 2 -2 % D7 Ca-H1-T-betlo hi 1 2 3 4 % D7 Sw-H3-T-bet % D7 Sw-H3-T-betlo ns E ** F 10 800 ns 8 600 * 6 400 Y1 4 200 Y2 HA Titer 2 0 0

% of D7-2 NPC gate -200 Total HApos HApos Yr 1 Yr 2 HApos T-bet hi T-bet lo G D7 NPC gate H D7 NPC gate 2015 2016 2016 2017 5 105 0.7 2.6 105 0.9 0.6 105 1.6 3.9 10 3.0 0.9 104 104 104 104 103 103 3 103 10 0 0

H1-Tet 0 87.2 10.7 0 89.7 8.8 85 9.6 91.2 5.0 H3-Tet 0 103 104 105 0 103104 105 0 103 104105 0 103 104 105 T-bet T-bet I Donor 1 J Donor 2 4 D7 H3pos Tbet hi 25 D7 H3pos Tbet hi D7 H3pos Tbet hi only D7 H3pos Tbet hi only 3 D7 H3pos Tbet lo 20 D7 H3pos Tbet lo D7 H3pos Tbet lo only D7 H3pos Tbet lo only 2016 D7 PB 15 2016 D7 PB 2 10 1 5

% of 2016 Bmem/PB Lineages 0 % of 2016 Bmem/PB Lineages 0 10 10 1 2017 D7 PB 1 2017 D7 PB .1 .1 .01 .01 .001 .001 Lineage Size (%) Lineage Size (%) .0001 .0001 1 2017 PB Lineages Ordered by Descending Size 998 1 2017 PB Lineages Ordered by Descending Size 4777

K Donor 2 L 100

80

50

30 Cumulative Percent of Sequences 0 2016 D7 2017 D7 PB 2016 D7 H3pos T-bet hi H3pos T-bet lo bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Supplemental Figure 1 Live CD19 Live CD19 IgDpos A IgDpos CD38hi neg IgD NPC Naive IgD CD19 IgD FSC-H SSC-A CD27 FSC-A FSC-A CD4 & L/D CD38 CD38 IgD Live CD19 5 PB ** B 4 3

% PB 2 1 SSC-A FSC-H CD19 CD27 0 FSC-A FSC-A CD4 & L/D CD38 0 7 C 0.8 **

0.4

cTfh % cTfh CD4 CD45RA CD4 FSC-H SSC-A PD-1 0.0 FSC-A FSC-A CD19 & L/D CD45RO ICOS CXCR5 0 7 D7 IIV NPC CD27 CD11c FcrL5 CXCR5 CD21 D

H1-Tet 3 4 5 3 4 5 3 4 5 3 4 5 3 4 5 T-bet 0 10 10 10 0 10 10 10 0 10 10 10 0 10 10 10 0 10 10 10 F ns 80 r = 0.47 E H1pos T-betlo H1pos T-bethi 80 G 40 60 p = 0.045 CD38hi 10 Bmem Bmem cTfh 40 cTfh ∆ 20 5 0 ∆ -20 0.5 1.0 1.5 2.0 0 lo % D7 Ca-H1-T-bet 0 1 2 3 4 % D7 Ca-H1-T-bethi H 80 ns I 80 60 40

cTfh 40 cTfh 10 ∆ ∆ 20 5 r = 0.5 0 p = 0.035 1 2 3 4 0 -20 % D7 Sw-H3-T-betlo 0.0 0.5 1.0 1.5 2.0 2.5 % D7 Sw-H3-T-bethi 25 J 25 ns K ns 20 20 15 15 Ab Ab 10 ∆ ∆ 10 5 5 H1 Ab 0 0 H3 Ab 0.2 0.4 0.6 0.8 -5 1 2 3 4 -5 D7 PB D7 cTFH L 25 M ns ns 20 3 15 2 10 1 H3-Abs H1-Abs 0

∆ 5 ∆ 1.0 1.5 2.0 2.5 0 -1 1 2 3 4 -2 % D7 Ca-H1-T-bethi % D7 Sw-H3-T-bethi N 25 6 O P r = 0.59 20 p = 0.02 ns 6 ns 4 15 4 2 10 H1-Abs H3-Abs 5 2 ∆ H1-Abs 0 ∆ 2 4 6 0 ∆ 0 -2 0 2 4 6 2 4 6 8 % D14 Ca-H1-T-bethi % D14 Ca-H1-T-bethi -2 % D14 Ca-H1-T-betlo Q 20 r = 0.7 R ns S 25 ns 3 10 p = 0.008 15 4 2 4 3

H1-Abs 1 H3-Abs H3-Abs 2 2 ∆ ∆ ∆ 1 0 0 0 1 1 2 4 6 0 .5 .0 .5 .0 4 6 -1 1 2 3 4 5 % D14 Sw-H3-T-bethi % D14 Sw-H3-T-bethi % D14 Sw-H3-T-betlo bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Supplemental Figure 2

A 6 CXCR3 4 FC

2 PRDM1 TBX21

log 2 hi

XBP1 0

D7 HApos T-bet hi over over CD21 -2 D7 HApos T-betlo lo -4 Shared

CD21 CD21lo over CD21hi -6 -6 -3 0 3 6 pos hi pos lo D7 HA T-bet over D7 HA T-bet log2FC B GSE9650_EFFECTOR_VS_ GSE9650_EFFECTOR_VS_ GOLDRATH_EFF_VS_ KAECH_DAY8_EFF_VS_ MEMORY_CD8_TCELL_UP MEM_CD8_TCELL_DN MEMORY_CD8_TCELL_DN MEMORY_CD8_TCELL_DN 0.1 0.6 NES: 1.95 0.1 0.1 0.3 0 NES 0 NES: 0 NES:

ES p <0.0001 -0.3 : -1.55 -0.3 -1.50 -0.3 -1.62 0 p < 0.0001 p = 0.003 p < 0.0001 -0.5 -0.5 -0.5 T-bet hi T-bet lo T-bet hi T-bet lo T-bet hi T-bet lo T-bet hi T-bet lo Rank in Gene List **** C D E D14 Naive 4 D14 H1pos T-bethi

D7 3 PBs pos D14 H1 1 ns D7 PBs

lo 0 T-bet RPPM PC2 12.3% -1 0 1 2 PC2 13.5% D14 H1pos D14 H1pos -2 -1 2 -2 hi T-bet lo

-3 T-bet -3 0 5 10 15 -2 0 2 4 -4 -2 042 6 8 Shaffer IRF4 PC1 54% PC1 52% UP in PCs

Cluster Centroid

F G H H1-Tet IC 4000 4000

H1-Tet EC 3000 3000 3000

T-bet 2000 2000 2000 H1-Tet EC CD38 H1-Tet EC Dimensions 1000 1000 1000 CD19 0 0 0 0 1000 2000 3000 4000 0 1000 2000 3000 4000 H1-Tet IC 4 H1-Tet IC

8 Fraction (%)

I XBP1 D7 PB XBP1

D14 H1pos T-bethi D14 H1pos FDR < 0.0004 T-betlo TBX21 ChIP-seq

chr22:28791683-28803118 bioRxiv preprint doi: https://doi.org/10.1101/643973; this version posted May 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Supplemental Figure 3 A Donor 3 Donor 3 100 100

80 80

50 50

30 30 Cumulative Percent of Sequences Cumulative Percent of Sequences 0 0 D14 Ca-H1 D14 Ca-H1 D28 Ca-H1 D14 Ca-H1 D14 Ca-H1 D28 Ca-H1 lo hi hi lo T-bet hi T-bet lo T-bet T-bet T-bet T-bet

B Donor 3 C Donor 3 D14 H1pos Tbet hi D14 H1pos Tbet hi 35 35 D14 H1pos Tbet hi only D14 H1pos Tbet hi only 30 D14 H1pos Tbet lo 30 D14 H1pos Tbet lo 25 D14 H1pos Tbet lo only 25 D14 H1pos Tbet lo only 20 20

15 15

10 10

5 5 % of D14 Bmem Lineages % of D14 Bmem Lineages 0 0 10 10 1 1 D28 H1pos Tbet lo D28 H1pos Tbet hi .1 .1 .01 .01 .001

.001 Lineage Size (%) Lineage Size (%) .0001 .0001 1 590 1 1428 D28 Tbet lo Lineages Ordered by Descending Size D28 Tbet hi Lineages Ordered by Descending Size

D Donor 3 6 D14 H1pos Tbet hi pos hi 5 D14 H1 Tbet only D14 H1pos Tbet lo 4 D14 H1pos Tbet lo only 2016 D7 PB 3

2

1

0 % of 2016 Bmem/PB Lineages 10 1 2017 D7 PB .1 .01 .001

Lineage Size.0001 (%) 1 6025 2017 PB Lineages Ordered by Descending Size