Metabolic Reprogramming Induces Germinal Center B Cell

Article

Metabolic Reprogramming
Induces Germinal CenterB Cell Differentiation through Bcl6 LocusRemodeling
Graphical Abstract

Highlights

d IL-4-signaling induces Bcl6 expression and GC B cell

differentiation

d IL-4 alters TCA cycle to accumulate aKG, a cofactor for

H3K27-demethylase

d STAT6 recruits H3K27-demethylase UTX, leading to

activation of the Bcl6 locus

d GC B cell development requires aKG and enzymes regulating

aKG level

Haniuda et al., 2020, Cell Reports 33, 108333November 3, 2020 ª 2020 The Author(s).https://doi.org/10.1016/j.celrep.2020.108333

Authors

Kei Haniuda, Saori Fukao,

Daisuke Kitamura

[email protected] (K.H.),[email protected] (D.K.)

In Brief

The germinal center reaction is vital for

long-lasting humoral immunity, yet

molecular mechanisms underlying the

induction of Bcl6, the master regulator for

germinal center B cell differentiation,

remain unclear. Haniuda et al. show that

IL-4-signaling induces Bcl6 expression

by reprogramming the TCA cycle

metabolism that controls epigenomic

remodeling.

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Article

Metabolic Reprogramming InducesGerminal Center B Cell Differentiationthrough Bcl6 Locus RemodelingKei Haniuda,1,* Saori Fukao,1 and Daisuke Kitamura1,2,*1Division ofMolecular Biology, Research Institute for Biomedical Sciences (RIBS), TokyoUniversity of Science, Noda, Chiba 278-0022, Japan2Lead Contact

*Correspondence: [email protected] (K.H.), [email protected] (D.K.)


SUMMARY

The germinal center (GC) reaction is essential for long-lived humoral immunity. However, molecular require-ments for the induction of Bcl6, the master regulator for GC B cell differentiation, remain unclear. Throughscreening forcytokinesandother stimuli that regulateBcl6expression,we identify IL-4as thestrongest inducer.IL-4 signaling alters the metabolomic profile in activated B cells and induces accumulation of the TCA cycle in-termediate a-ketoglutarate (aKG), which is required for activation of theBcl6 gene locus. Mechanistically, afterIL-4 treatment, STAT6 bound to the known enhancers in the Bcl6 locus recruits UTX, a demethylase for therepressive histone mark H3K27me3 that requires aKG as a cofactor. In turn, the H3K27me3 demethylation ac-tivates the enhancers and transcription of theBcl6 gene.Wepropose that IL-4-mediatedmetabolic reprogram-ming in B cells is pivotal for epigenomic activation of Bcl6 expression to promote GC B cell differentiation.

INTRODUCTION

One of the hallmarks of the adaptive immune response is the

generation of immunological memory. Long-lived memory B

cells and plasma cells (PCs) with high affinity for antigen are

formed in the germinal center (GC) through B cell proliferation,

somatic hypermutation (SHM) and affinity-based selection (Vic-

tora and Nussenzweig, 2012). Thus, GC formation is essential

for efficient adaptive immune responses. Upon antigen recogni-

tion by their B cell receptor (BCR), B cells interact with cognate

T cells and are activated by signals through CD40 and cytokine

receptors, determining their cell fate. Only B cells expressing

the transcriptional repressor Bcl6 can differentiate into GC B

cells. Bcl6 is the master regulator for GC B cell differentiation;

it directly suppresses the expression of many genes involved

in signal transduction throughBCR andCD40, PC differentiation,

cell-cycle arrest, and DNA damage responses (Basso and Dalla-

Favera, 2012). Therefore, Bcl6 expression prevents premature

activation and terminal differentiation, and makes it possible

for GC B cells to undergo massive proliferation, SHM, and the

consequent affinity maturation (Basso and Dalla-Favera, 2012).

Although the function of Bcl6 has been studied in detail, the mo-

lecular mechanisms underlying the induction of Bcl6 expression

remain elusive. This is mainly due to the lack of an in vitro system

in which Bcl6 expression can be reliably induced.

Immune cell activation is accompanied by metabolic reprog-

ramming to meet increased bioenergetic and biosynthetic de-

mands for cellular growth and proliferation (Pearce et al., 2013).

Once activated, lymphocytes engage in aerobic glycolysis, pro-

ducing lactate, rather than in mitochondrial oxidative metabolism,

CThis is an open access article under the CC BY-N

even in the presenceof oxygen. This process is knownas theWar-

burg effect, a common feature of actively proliferating cells, which

allows cells to produce ATP quickly and to generate themetabolic

intermediates required for biosynthesis (Vander Heiden et al.,

2009). Thus, after BCR or CD40 stimulation, B cells dramatically

increase glycolytic activity (Woodland et al., 2008). Furthermore,

among highly proliferative GC B cells, a fraction of light-zone B

cells that can receive T cell help activate mammalian target of ra-

pamycin complex 1 (mTORC1) signaling and express c-Myc, both

of which positively regulate glycolysis and anabolic metabolism

and are required for GC development (Calado et al., 2012; Domi-

nguez-Sola et al., 2012; Ersching et al., 2017).

A growing body of evidence suggests that some metabolic

pathways influence epigenetic gene regulation by providing do-

nors and cofactors for epigenetic modifiers. For example, the

threonine-fueled metabolism in embryonic stem cells (ESCs)

provides S-adenosylmethionine, the methyl-group donor for

methylation, to maintain the histone methylation required for plu-

ripotency (Shyh-Chang et al., 2013). Another example is that

enhanced glycolysis elevates cytosolic acetyl-coenzyme A

(CoA), a universal donor for acetylation, to enhance histone acet-

ylation and expression of Ifng in activated T cells (Peng et al.,

2016). Furthermore, the accumulation of the tricarboxylic acid

(TCA) cycle intermediate a-ketoglutarate (aKG), a required

cofactor for Jumonji C domain-containing (JmjC) histone deme-

thylases and ten-eleven translocation (TET) DNA dioxygenases,

has been reported to be required for maintaining the pluripo-

tency of ESCs (Carey et al., 2015) and primordial germ cells

(Tischler et al., 2019) and for activating effector gene programs

in T cells (Chisolm et al., 2017).

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To date, it is unknown whether B cell metabolism can control

differentiation gene programs beyondmeeting their bioenergetic

and biosynthetic demands. Here, we demonstrated that IL-4-

mediated reprogramming of TCA cycle metabolism drives the

accumulation of aKG that integrates epigenetic activation of

the Bcl6 gene to induce GC B cell differentiation.

RESULTS

IL-4 Signaling and Mitochondrial Metabolism ControlBcl6 ExpressionTo elucidate the mechanisms upregulating Bcl6 expression in B

cells at a molecular level, we used our previously reported B cell

culture system called ‘‘iGB culture’’ (Nojima et al., 2011). In this

system, splenic B cells are cultured with interleukin-4 (IL-4) on

feeder cells expressing CD40L and B-cell activating factor

BAFF (40LB) and extensively proliferate and efficiently undergo

class switching to immunoglobulin G1 (IgG1) and IgE. These B

cells (called iGB cells) express modest levels of Bcl6 mRNA (No-

jima et al., 2011) and protein (Figure 1A), probably because

chronic CD40 stimulation suppresses Bcl6 expression (Saito

et al., 2007; Zhang et al., 2017). ‘‘Plain culture’’ with medium

alone for 1 day after removal of the feeder cells at day 3 of the

iGB culture produced a distinct population of IgG1+ B cells highly

expressing Bcl6 (Figure 1A). However, 60%–70% of the IgG1+ B

cells remained Bcl6� after the plain culture, despite the preced-

ing stimulation. Thus, we sought to find stimuli that induce Bcl6

expression in activated B cells by screening cytokines and other

stimuli that could convert these Bcl6� cells into Bcl6+ cells.

We treated the iGB cells with a panel of cytokines and anti-

bodies (Abs) during the plain culture period for 1 day and then

analyzed them by flow cytometry. We found that IL-4, IL-6, IL-

13, and IL-21 increased the frequency of Bcl6+ cells among

IgG1+ cells, and that IL-4 was the most potent inducer (Figures

1B, 1C, and S1A). In contrast, BCR stimulation by anti-IgG Ab

strongly reduced the frequency of Bcl6+ cells, but instead

increased the CD138+ PC (Figures 1B, 1C, and S1A). In line with

these data, IL-4 upregulated Bcl6 mRNA expression, whereas

anti-IgG Ab downregulated it and upregulated Irf4 expression

(Figure 1D). To assess the impact of IL-4 on GC development,

we administered IL-4 complexedwith an anti-IL4Ab (IL-4c), which

extends the bioactive half-life of the cytokine (Finkelman et al.,

1993) into immunizedmice during the early stage ofGC formation.

IL-4c treatment significantly increased the number of (4-hydroxy-

3-nitrophenyl)acetyl (NP)-specific GC B cells (Figure S1D).

Given that cellular metabolism has been reported to be linked

to gene expression and differentiation (Pearce et al., 2013), we

next assessed the metabolic properties of the iGB cells after

stimulation during the plain culture period. We measured mito-

chondrial membrane potential (DJm) intimately linked to elec-

tron transport chain (ETC) activity by stainingwith the fluorescent

dye TMRM (tetramethylrhodamine, methyl ester, perchlorate).

We found that stimulation with IL-4 increased the DJm of iGB

cells, whereas anti-IgG stimulation decreased it, as compared

to non-stimulated cultures (Figure 1E). Next, we measured

lactate production 4 h after stimulation and found that anti-IgG

but not IL-4 facilitated its production (Figure 1F). These data indi-

cated that IL-4-receptor (IL-4R) or BCR signaling activates mito-

2 Cell Reports 33, 108333, November 3, 2020

chondrial or glycolytic metabolism, respectively. The inhibition of

mitochondrial oxidative metabolism by treatment with oligomy-

cin, an inhibitor of the mitochondrial ETC (Figure S1E), abolished

Bcl6 upregulation after IL-4 stimulation, but not PC differentia-

tion by anti-IgG (Figure 1G). These findings suggest that IL-4

signaling upregulates Bcl6 expression through potentiating

mitochondrial oxidative metabolism.

GC B Cell Development Depends on MitochondrialOxidative MetabolismGiven theuniquedependencyofBcl6expressiononmitochondrial

oxidative metabolism, we decided to characterize the metabolic

status of B cell subsets that develop after antigen challenge. To

identify antigen-specific precursors of GC B cells (pre-GC B cell)

and GC B cells, we transferred naive B (NB) cells from CD45.1

mice carrying a knockin allele encoding a hapten NP-specific VH

region (B1-8hi) into C57BL/6 (B6) mice, which were immunized

with a conjugate of NP and chicken g-globulin (CGG) in alum the

next day. Among the donor-derived B220+ NP-binding B cells,

pre-GCB cells were defined asGL7+ CD38hi cells on day 3.5 after

immunization and GC B cells as GL7+ CD38lo cells on day 7. We

analyzed these cells, aswell asPCsonday 7 andNBcells fromun-

immunized mice (Figures 2A and S2A), for mitochondrial mass,

DJm, and mitochondrial reactive oxygen species (ROS) by stain-

ingwithMitoTracker, TMRM, orMitoSOX, respectively.Mitochon-

drial mass, DJm, and mitochondrial ROS were higher in pre-GC

and GC B cells than in NB cells or PCs (Figure 2B), suggesting

activated mitochondrial metabolism in pre-GC and GC B cells.

Glycolytic activity, assessed by the uptake of 2-NBDG (2-(N-(7-ni-

trobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose; a fluores-

cent analog of glucose) and production of lactate (an end product

of glycolysis) was markedly high in pre-GC B cells and PCs and

modest but higher than in NB cells in GC B cells (Figures 2B and

2C). The enzymatic activity of pyruvate dehydrogenase (PDH),

which promotes pyruvate entry into the TCA cycle at the expense

of lactate production (Figure S1E), was increased in GC B cells

compared with NB cells or PCs (Figures 2D and S2C), with a

concomitant decrease in the inhibitory PDH phosphorylation in

GC B cells (Figure S2D). These data indicate that GC B cells

have activatedmitochondrial oxidativemetabolismand restrained

aerobic glycolysis, suggesting that the Warburg effect may not fit

overall GC B cells, even though GC B cells display an increased

cellular size, intimately linked to biosynthesis, and the highest pro-

liferative capacity of any of the B cell subsets (Figures 2B and 2E).

To address the requirement for mitochondrial oxidative meta-

bolism in each B cell subset, we treated immunizedmice with oli-

gomycin for 1 day before analysis (Figure 2F). The administration

of oligomycin partially but significantly reduced the number of

GC B cells, but not of pre-GC B cells, PCs, or follicular helper

T (Tfh) cells (known to be required for GC formation) (Victora

and Nussenzweig, 2012), and attenuated the expression of

Bcl6 in GC B cells but not in Tfh cells (Figures 2G, 2H, and

S2E–S2G). In addition, inhibition of the first step of glycolysis

by administrating 2-deoxyglucose at the same time point also

diminishedGCB cell numbers (data not shown), as reported pre-

viously (Jellusova et al., 2017). Our results show that GC B cell

development relies on mitochondrial oxidative metabolism,

possibly fueled by glycolysis.

A B

C D

E F G

Figure 1. IL-4 and Mitochondrial Metabolism Regulate Bcl6 Expression

(A) Schema of the iGB culture followed by the plain culture and flow cytometric profiles of IgG1+ gated cells at the end of each culture.

(B) Quantification of Bcl6+ or CD138+ cells among IgG1+ cells after the plain culture with the indicated cytokines or Abs for 1 day. The results are presented as

relative to the cells cultured in medium alone.

(C–G) Analysis of IgG1+ iGB cells (gated as in Figure S1B) after the plain culture in medium alone (�) or with IL-4 or anti-IgG for 1 day.

(C) Flow cytometric analysis.

(D) qRT-PCR analysis of sorted IgG1+ cells (Figure S1C).

(E) TMRM staining.

(F) Lactate production by the sorted cells after the plain culture for 4 h.

(G) Analysis as in (C), except additional supplement of oligomycin or vehicle alone (�) in culture.

Data are means ± SDs of 2–4 (B) or 3 (F) biological replicates or 3 technical replicates (D). Each symbol represents a biologically independent sample (B and F).

The data are pooled from 2–4 independent experiments (B), or representative of at least 3 (A, C, and D) or 2 (E–G) independent experiments. p values were

calculated by 1-way ANOVA with Tukey’s test (F). See also Figure S1.

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IL-4 Signaling Reprograms B Cell Metabolome toAccumulate the TCA Cycle Intermediate aKGTo elucidate how mitochondrial metabolism contributes to the in-

duction of Bcl6 expression, we profiled the metabolome of iGB

cells treated with IL-4 or anti-IgG for 6 h, or untreated, without

feeder cells (Figure 3A). At this time point, expression levels of

Bcl6 and Blimp1 mRNA were unchanged (Figure S3A). The

metabolite profiling revealed different alterations between the

Cell Reports 33, 108333, November 3, 2020 3

A B

C D E F

G H

Figure 2. GC B Cells Depend on Mitochondrial Metabolism for Their Development(A–E) Characterization of the metabolic status of B cell subsets in the spleen.

(A) Experimental protocol for (B), (C) and (E). Each subset was defined as in Figure S2A.

(B) Mean fluorescent intensity (MFI) of MitoTracker, TMRM, MitoSOX or 2-NBDG, or forward scatter (FSC).

(C) Lactate production by sorted cells during 4-h ex vivo culture.

(D) Mitochondrial PDH activity in the cells prepared as in Figure S2B.

(E) Flow cytometric analysis for in vivo bromodeoxyuridine (BrdU) incorporation.

(F–H) In vivo treatment with oligomycin or vehicle alone (�).

(F) Experimental protocol. Each subset was defined as in Figure S2A.

(G) The number of indicated cells per spleen.

(H) MFI of Bcl6- or Irf4-staining.

Data are means ± SDs of 6 (B), 3 (C and D), 5 (E) or 7 (G and H) biological replicates. Each symbol represents an individual mouse (B, E, G, and H) or a biological

sample pooled from n = 2 (NB; C and D), 10 (pre-GC B, GC B, and PC; C), or 30 mice (GC B and PC; D). The data are representative of 2 (B, E, G, and H) in-

dependent experiments, or are pooled from 3 independent experiments (C and D). p values were calculated by 1-way ANOVA with Tukey’s test (B–E) or 2-tailed

unpaired Student’s t test (G and H). See also Figure S2.

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cells stimulated with IL-4 or anti-IgG (Figure S3B), among which

the TCA cycle was the most significantly altered pathway (Fig-

ure 3B). Among the TCA cycle metabolites, the amount of aKG

was strikingly higher in the cells stimulated with IL-4 than anti-


IgG or the unstimulated cells (Figure 3C). Kinetics analysis demon-

strated that the amount of aKG was elevated by 6 h and then

became almost stable at least until 24 h after stimulation with IL-

4 (Figure S3C). However, the lactate:pyruvate ratio was highest

A C D

B

E F G H

KJI

Figure 3. IL-4 Induces aKG Accumulation That Stimulates Bcl6 Expression(A–D) Metabolome analysis of IgG1+ iGB cells stimulated with IL-4 or anti-IgG for 6 h or left unstimulated (�) for 1 h.

(A) Outline of the experiment.

(B) Metabolite set enrichment analysis selecting the top 15 most enriched metabolic pathways by treatment with IL-4 compared to anti-IgG, listed from top to

bottom according to p value.

(C) Abundance of TCA cycle-related metabolites.

(D) Lactate/pyruvate ratios.

(E) Amount of aKG in NB or GC B cells prepared as in Figure S2B.

(F) Amount of aKG in IgG1+ iGB cells after the plain culture for 6 h with IL-4 in the presence or absence of oligomycin.

(G–K) Effects of DMaKG or DE-Suc supplementation in low (Lo) glucose (Glc) culture.

(G) Experimental protocol.

(H) qRT-PCR analysis of iGB cells treated as indicated.

(I) Flow cytometric estimation of Fixable viability dye (FVD)-negative cells among total cells treated as indicated.

(J) qRT-PCR analysis of the same cells as in (I).

(K) Analysis of spleens of the cell-transferred mice on day 8 after immunization. Shown are the numbers of donor GC B cells

(CD45.1+NP+GL7+CD19+CD138�CD38lo) per spleen (right) estimated from flow cytometric analysis (left; numbers indicate frequency among live lymphocytes).

(legend continued on next page)


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in the anti-IgG-stimulated cells, suggesting increased aerobic

glycolysis, which consumes pyruvate for producing lactate and

limits the TCA cycle (Figure 3D). Similarly, ex vivoGC B cells con-

tained a higher amount of aKG than NB cells (Figure 3E). We next

assessed the impact of mitochondrial oxidative metabolism on

the intracellular aKG levels. In accord with a previous report that

ETC inhibitors lower the aKG level (Fendt et al., 2013), treatment

with oligomycin during the IL-4 stimulation significantly decreased

the amount of aKG in iGB cells (Figure 3F).

Given the parallel effects of oligomycin in suppressing both IL-

4-induced aKG accumulation (above) and Bcl6 expression (Fig-

ure 1G), as well as in vivo GC development and Bcl6 expression

(Figures 2G and 2H), we next sought to reveal the molecular link

between aKG and Bcl6 expression. For this purpose, iGB cells

were plain cultured with IL-4 under low glucose conditions to limit

aKG production via the TCA cycle and supplemented or not with

dimethyl-aKG (DMaKG), a cell-permeable aKG derivative (Fig-

ure 3G). Under the low glucose conditions, the expression of

Bcl6 was mostly abolished, while supplementation with DMaKG

restored the expression ofBcl6 but not of Irf4 (Figure 3H). Supple-

mentation with diethyl-succinate (DE-Suc), a cell-permeable de-

rivative of succinate that is a downstream metabolite of aKG in

the TCA cycle, did not restoreBcl6 expression but viability of cells

cultured under low glucose conditions (Figures 3I and 3J). These

data suggest that Bcl6 expression is driven by aKG produced in

the glucose-fueled TCA cycle in IL-4-stimulated cells and that

this aKG function is distinct from a general role of TCA cycle me-

tabolites on energy production. To test the effect of aKG on GC B

cell differentiation, we cultured B1-8hi B cells under the same con-

ditions as above and transferred them into NP-CGG-immunized

B6 mice (Figure 3G). B cells cultured with low glucose barely

developed into GC B cells in vivo, but supplementation with

DMaKG rescued the GCB cell development (Figure 3K). Our find-

ings indicate that IL-4 signaling reprograms mitochondrial meta-

bolism in activated B cells, which in turn accumulates aKG and

drives the expression of Bcl6.

IL-4 Signaling Activates the Bcl6 Locus throughEpigenetic Remodeling Mediated by a-KGaKG is a cofactor for aKG-dependent dioxygenases, many of

which function as epigenetic modifiers, and the accumulation

of aKG is known to activate aKG-dependent histone demethy-

lases (Carey et al., 2015; Chisolm et al., 2017; Tischler et al.,

2019). Thus, we focused on the epigenetic regulation of Bcl6

expression.We found that in GCB cells, the global trimethylation

of histone H3 lysine 27 (H3K27me3), a repressive histone mark

contributing to chromatin compaction, was decreased and the

acetylation of H3K27 (H3K27Ac) was increased, whereas the tri-

methylation of H3K4 and H3K9 remained mostly unchanged as

compared with NB cells (Figure 4A).

We next analyzed published chromatin immunoprecipitation

(ChIP) coupled with high-throughput sequencing (ChIP-seq) data

Data aremeans ± SDs of 3 (C–F), 2 (I), and 5 (K) biological replicates or 3 technical

(C, D, F, and I), a biological sample pooled from n = 5 (NB in E) or 30 mice (GC B

experiments (F, H, J, and K), from an experiment (B–E), or pooled from 2 independe

(C, D, and K) or 2-tailed unpaired Student’s t test (E and F). See also Figure S3.


ofNBcells andGCBcells, and found thatH3K27me3was reduced

in GCB cells in a region spanning from ~140 to ~360 kb upstream

of theBcl6 transcriptional start site (FigureS4A). This region largely

overlapped with two enhancer elements (enhancer 1 and 2) that

are activated specifically in GC B cells and interact with the Bcl6

promoter region (Bunting et al., 2016; Ryan et al., 2015). These

enhancer regions were enriched in GC B cells with an enhancer

mark H3K4me1 together with H3K27Ac (Figure S4A), a modifica-

tion associated with enhancer activity (Calo and Wysocka, 2013).

Knock out of these regions has been reported to result in a defec-

tive GC formation, indicating that these enhancers are crucial for

Bcl6 expression during GC B cell development (Bunting et al.,

2016). Our ChIP coupled with quantitative PCR (qPCR) analysis

confirmed that H3K27me3 was significantly lower in GC B cells

than in NB cells, in the same enhancer regions of the Bcl6 locus,

except for position �163 kb, where H3K27me3 was equally low

in NB cells (Figure 4B). Therefore, we hypothesized that the

H3K27me3marksat theBcl6enhancersareactivelydemethylated

to drive the transcription of the Bcl6 locus to promote GC B cell

development. To test this hypothesis, we assessed the histone

modifications in iGB cells treated with IL-4 or anti-IgG for 6 h in

comparison to untreated cells. Our ChIP-qPCR assay revealed

that treatment with IL-4 decreased H3K27me3 at enhancer 1

and 2 of the Bcl6 locus, again except for position �163 kb,

concomitant with an increase in H3K27Ac on the enhancer and

promoter regions (Figures 4C, 4D, andS4B). In contrast, treatment

with IL-4 or anti-IgG had no effect on H3K27me3 levels in both

enhancer and promoter regions of the Irf4 locus (Chapuy et al.,

2013; Raisner et al., 2018), although anti-IgG increased

H3K27Ac in these regions (Figures 4E, 4F, S4C, and S4D).

Given the dependence of Bcl6 expression on mitochondrial

oxidative metabolism that regulates aKG accumulation, we

next assessed whether IL-4-mediated reduction of H3K27me3

at the Bcl6 enhancers depends on this metabolism. First, we

demonstrated that treatment with oligomycin resulted in an in-

crease in H3K27me3 at the Bcl6 enhancers (Figure S4E) and a

marked decrease in Bcl6 mRNA expression that was partially

restored by the addition of DMaKG (Figure S4F). Second, to

determine whether aKG is required for the IL-4-mediated loss

of H3K27me3 in the Bcl6 enhancers, we treated glucose-

restricted iGB cells with DMaKG in the presence of IL-4.

Whereas H3K27me3 on enhancer 1 and 2 of the Bcl6 locus

was increased by the restriction of glucose, the addition of

DMaKG restored it to a lower level (Figure 4G). These data sug-

gested that IL-4 signaling induces epigenetic remodeling of the

Bcl6 locus and activates its enhancers through mechanisms de-

pending on mitochondrial oxidative metabolism and aKG.

An H3K27me3-Specific Demethylase UTX Is Requiredfor Bcl6 Induction and GC B Cell DevelopmentGiven the finding that aKG lowers H3K27me3 at the Bcl6

enhancers, we addressed the possible involvement of an

replicates (H and J). Each symbol represents a biologically independent sample

in E) or an individual mouse (K). The data are representative of 2 independent

nt experiments (I). p valueswere calculated by 1-way ANOVAwith Tukey’s test

A B G

C E

D F

Figure 4. aKG Supports IL-4-Mediated Epigenetic Changes in the Bcl6 Locus

(A and B) Immunoblot analysis of (A) and ChIP-qPCR analysis for H3K27me3 at the Bcl6 locus in (B) NB or GC B cells prepared as in Figure S2B. H3, histone H3.

(C–F) ChIP-qPCR analysis at the Bcl6 (C and D) or Irf4 (E and F) locus in IgG1+ iGB cells treated with IL-4 or anti-IgG for 6 h, or left unstimulated (�) for 1 h.

(G) ChIP-qPCR analysis at Bcl6 locus in IgG1+ iGB cells cultured with IL-4 for 6 h with the indicated supplements.

All of the ChIP-qPCR data were normalized to input DNA. The numbers on the x axis indicate the distance (kb) from TSS (+0). The data are means ± SDs of 3

biological replicates (B), each of which was pooled from n = 2 (NB) or 10mice (GC B); or of 3 technical replicates (C–G). The data are representative of 3 (A, C, and

D) or 2 (E–G) independent experiments or from an experiment (B). p values were calculated by 2-tailed unpaired Student’s t test (B). See also Figure S4.

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aKG-dependent H3K27me3-specific demethylase. Treatment of

iGB cells with GSK-J4 (Kruidenier et al., 2012), a potent inhibitor

of UTX (encoded by Kdm6a), resulted in an increase in

H3K27me3 at the Bcl6 enhancers and a concomitant reduction

in Bcl6 expression after IL-4-treatment (Figures 5A and 5B). In

addition, the treatment of immunized mice with GSK-J4 during

the early stage of the GC formation significantly decreased the

number of antigen-specific GC B cells (Figure 5C). Moreover,

small hairpin RNA (shRNA)-mediated knockdown of UTX in iGB

cells (Figures S5A and S5B) increased H3K27me3 at the Bcl6 en-

hancers and decreased the expression of Bcl6 after treatment

with IL-4 (Figures 5D and 5E). To assess the role of UTX in the

aKG-mediated GC formation in vivo, B cells transduced with

shControl or shUTX and cultured under low glucose conditions

with or without DMaKG were transferred into NP-CGG-immu-

nized B6 mice (Figure S5C). Supplementation with DMaKG

restored the GC formation of B cells transduced with shControl

but not of those with shUTX (Figure S5D). These data highlight

that active H3K27me3-demethylation mediated by UTX with

aKG is required forBcl6 upregulation and GCB cell development.

STAT6 Is Required for the Recruitment of UTX to theBcl6 Enhancers during GC B Cell DevelopmentSince the addition of DMaKG alone to iGB cells cultured without

IL-4 did not result in an increase in Bcl6 expression (Figure S6A),

general activation of UTX by aKG appears insufficient for the

Bcl6 induction. Thus, we next sought to clarify the mechanisms

by which the genome-wide epigenetic modifier UTX targets the

Bcl6 locus after the IL-4 stimulation. The IL-4-IL-4R axis is known

to activate transcription factors signal transducer and activator

of transcription 3 (STAT3), STAT5, and STAT6, and this was

the case for iGB cells (Figure 6A). shRNA-mediated knockdown

revealed that STAT6 but not STAT3 or STAT5 was responsible

for the upregulation of Bcl6 expression after IL-4 treatment (Fig-

ures 6B and S6B). Then, we assessed the effect of STAT6 knock-

down in vivo. We transduced in vivo-primed B1-8hi B cells with

the STAT6-knockdown vector in the absence of IL-4 in vitro

and then transferred them into B6 mice 1 day before immuniza-

tion with NP-CGG (Figure S6C). Consistent with an earlier finding

(Turqueti-Neves et al., 2014), the knockdown of STAT6 remark-

ably inhibited the formation of GC B cells (Figure 6C), indicating


A B C D E

Figure 5. The H3K27me3-Specific Demethylase UTX Mediates Bcl6 Induction

(A and B) IgG1+ iGB cells were stimulated with IL-4 in the absence (�) or presence of GSK-J4.

(A) ChIP-qPCR analysis after 6 h of stimulation.

(B) qRT-PCR analysis after 1 day of stimulation.

(C) Immunized mice were injected with vehicle alone (�) or GSK-J4 (left, top). The numbers of NP+ GC B cells (right) were estimated by flow cytometric analysis

(left, bottom; the numbers indicate frequencies among NP+B220+CD138– cells).

(D and E) Analysis of iGB cells transduced with shControl or shUTX as in Figure S5A and stimulated with IL-4.

(D) ChIP-qPCR analysis after 6 h of stimulation.

(E) qRT-PCR analysis after 1 day of stimulation.

The data are means ± SDs of 3 technical replicates (A, D, and E) or 3 (B) or 6 (C) biological replicates. Each symbol represents a biologically independent sample

(B) or an individual mouse (C). The data are representative of 2 (A–E) independent experiments. p values were calculated by 2-tailed unpaired Student’s t test (B

and C). See also Figure S5.

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that STAT6-activating stimuli are important for GC B cell devel-

opment in vivo. We next assessed whether STAT6 is necessary

for the IL-4-mediated demethylation of the Bcl6 locus. The

knockdown of STAT6 increased H3K27me3 at regions including

the Bcl6 enhancers and decreased H3K27Ac at the enhancer

and the regions around the transcription start site, after IL-4

treatment (Figure 6D). As an exception, the knockdown of

STAT6 markedly increased H3K27me3 but did not diminish

H3K27Ac at positions �225, �10, and �5 kb, suggesting that

H3K27me3 demethylation of these regions does not directly

affect the transcriptional state of the chromatin.

Using published ChIP-seq data frommacrophages stimulated

with IL-4 (Czimmerer et al., 2018), we found that STAT6 binds to

Bcl6 enhancer 1 and 2 in addition to a known binding site in the

promoter region (Chevrier et al., 2017) (Figure S4A). Our ChIP-

qPCR analysis of iGB cells confirmed the STAT6 binding in the

same regions of the Bcl6 enhancers and promoter after IL-4

treatment (Figure 6E, top). Notably, UTX was also recruited to

the same regions of the enhancers that were bound by STAT6 af-

ter IL-4 treatment (Figure 6E, bottom). Co-immunoprecipitation

(coIP) analysis of iGB cells revealed a physical association of

STAT6 with UTX, increasing along with the IL-4 treatment time

course (Figure 6F). Furthermore, knock down of STAT6 reduced

the UTX binding to the Bcl6 enhancers (Figure 6G), suggesting a

functional association between STAT6 and UTX. Based on all of

these observations, we concluded that STAT6 recruits UTX to

the Bcl6 enhancers, where it demethylates H3K27me3 and tran-

scriptionally activates the chromatin at the enhancer and pro-

moter regions, thus activating the transcription of the Bcl6

gene during IL-4-mediated differentiation of GC B cells.

IL-4 Signaling Regulates the TCA Cycle Enzymes toAccumulate Intracellular aKGTo understand how IL-4 signaling results in the accumulation of

aKG, we assessed enzymatic activities of isocitrate dehydroge-


nases (IDHs) and aKG dehydrogenase (aKGDH), the aKG-pro-

ducing and -consuming enzymes in the oxidative TCA cycle,

respectively (Figure 7A), in the mitochondrial fraction of GC B

cells and iGB cells. The activities of nicotinamide adenine dinu-

cleotide phosphate (NADP)+-dependent IDH2 and NAD+-depen-

dent IDH3 were higher in GC B cells, while the activity of aKGDH

was lower than in NB cells (Figure 7B). Similar trends were

observed in iGB cells treated with IL-4 as compared with those

treated with anti-IgG or untreated (Figure 7C). Since the

enhancement of the enzymatic activity of IDH2 was higher than

that of IDH3 in both GC B cells and IL-4-stimulated iGB cells,

we focused on IDH2. Knock down of IDH2 in IL-4-treated iGB

cells significantly decreased the amount of intracellular aKG

and the expression of Bcl6 (Figures 7D, 7E, and S7A). Accord-

ingly, IDH2-knockdown B cells developed less well into GC B

cells than control B cells in recipient mice after immunization

(Figure 7F).

To elucidate how IL-4 treatment downmodulates aKGDH

activity, we assessed the expression of its three subunits: E1 (ox-

oglutarate dehydrogenase [OGDH]), E2 (dihydrolipoamide

succinyltransferase [DLST]), and E3 (dihydrolipoamide dehydro-

genase [DLD]). We found that the level of DLST protein, but not

mRNA, was lower in GC B cells than in NB cells, and also in

iGB cells treated with IL-4 than those treated with anti-IgG or

left unstimulated (Figures 7G, 7H, and S7B–S7D), indicating

post-transcriptional regulation of DLST. The proteasomal inhibi-

tor MG-132 restored DLST protein level in the presence of IL-4,

whereas a lysosomal inhibitor bafilomycin A1 (BafA1) had no ef-

fect (Figure 7I). In addition, we found that DLST protein in iGB

cells was polyubiquitinated after treatment with IL-4, but not

with anti-IgG, as seen in the presence of MG-132 (Figure 7J).

Given the previous report that DLST is targeted by the E3 ubiq-

uitin ligase SIAH2 for proteasomal degradation (Habelhah et al.,

2004), we focused on the function of SIAH2. We found that, after

treatment of iGB cells with IL-4, SIAH2 was associated with

A

D

B C

E F

G

Figure 6. STAT6 Recruits UTX and Activates Transcription of the Bcl6 Locus

(A) Immunoblot analysis of iGB cells after treatment with IL-4 for the indicated times.

(B) Flow cytometric analysis of iGB cells transducedwith shControl or shSTAT as in Figure S5A and cultured with IL-4 for 1 day. Shown are representative plots of

GFP+IgG1+ cells.

(C) Analysis of spleen cells from mice day 7 post-immunization that had received B1-8hi B cells transduced with shControl or shSTAT6 as in Figure S6C. The

numbers of the transduced (GFP+) NP+ GC B cells (right) were estimated by flow cytometric analysis (left; the numbers indicate frequency among donor GC B

cells [CD45.1+NP+GL7+B220+CD138�CD38lo]).(D) ChIP-qPCR analysis at Bcl6 locus of iGB cells transduced with shControl or shSTAT6 and culture with IL-4 for 6 h.

(E) ChIP-qPCR analysis for STAT6 or UTX binding at Bcl6 locus of IgG1+ iGB cells treated with IL-4 or left untreated (�) for 3 h.

(F) Immunoblot detection of UTX and STAT6 in proteins immunoprecipitated (IP) with control IgG or anti-STAT6 Ab from whole-cell lysate (WCL) of iGB cells

cultured with IL-4 for the indicated times.

(G) ChIP-qPCR analysis for UTX binding at Bcl6 locus of iGB cells transduced with shControl or shSTAT6 and treated with IL-4 for 3 h.

Data are means ± SDs of 6 biological replicates (C) or 3 technical replicates (D, E, and G). Each symbol represents an individual mouse (C). The data are

representative of 2 (A, C, D, and G) or 3 (B, E, and F) independent experiments. p values were calculated by 2-tailed unpaired Student’s t test (C). See also

Figure S6.

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DLST (Figure 7K). Furthermore, knock down of SIAH2 in IL-4-

treated iGB cells resulted in an increase in DLST protein and a

decrease in the level of aKG and Bcl6 mRNA (Figures 7L–7N

and S7E). SIAH2 knockdown in B cells did not significantly affect

their development up to pre-GC B cells, but it did markedly

inhibit their differentiation to GC B cells in the recipient mice after

immunization (Figures S7F and S7O). Finally, the overexpression

of DLST in iGB cells suppressed Bcl6 expression in vitro and

their development into GC B cells in vivo (Figures S7G and

S7H). We concluded that IL-4 signaling modulates the amount

and/or activity of the aKG-regulating enzymes, resulting in the

accumulation of aKG, which drives Bcl6 expression and the

consequent GC B cell differentiation.

DISCUSSION

In this study, we have revealed that IL-4-mediated reprogram-

ming of TCA cycle metabolism in activated B cells drives the

accumulation of aKG that integrates STAT6-UTX-dependent

epigenetic activation of the Bcl6 locus, leading to the induction

of Bcl6 expression and GC B cell differentiation. In accord with

earlier findings (Cunningham et al., 2002; Gonzalez et al., 2018;


A B C D E F

G H I J K

L M N O

Figure 7. IL-4 Signaling Controls the Activity of aKG-Regulating Enzymes

(A) Schema of a partial oxidative TCA cycle highlighting the enzymes regulating aKG production.

(B and C) Mitochondrial dehydrogenase activity in NB or GC B cells (B) or in IgG1+ iGB cells stimulated with either IL-4 or anti-IgG, or left unstimulated, for 6 h (C).

(D and E) Analysis of iGB cells transduced with shControl or shIDH2 as in Figure S5A and stimulated with IL-4.

(D) Intracellular aKG level after 6 h of stimulation.

(E) qRT-PCR analysis after 1 day of stimulation.

(F) Analysis of spleens from mice transferred with B1-8hi B cells transduced with shControl or shIDH2 as in Figure 6C. The data are presented as in Figure 6C.

(G andH) Immunoblot analysis for aKGDH subunits in NB or GCB cells (G), or in IgG1+ iGB cells cultured with either IL-4 or anti-IgG, or left unstimulated (�), for 6 h

(H).

(I) Immunoblot analysis for DLST in IgG1+ iGB cells cultured for 6 h with (+) or without (�) IL-4 in the absence (�) or presence of MG-132 or bafilomycin A1 (BafA1).

(J) Immunoblot analysis for ubiquitination (Ub) in proteins IP with anti-V5 Ab or control IgG from WCL of iGB cells transduced with DLST-V5 and cultured for 6 h

with IL-4, anti-IgG, or medium alone (�), and MG-132 (top). NS, nonspecific bands. Bottom: anti-V5 blot.

(K) Immunoblot detection of DLST in the proteins precipitated with anti-FLAG Ab from WCL (top), or in the WCL (bottom), of iGB cells transduced with FLAG-

SIAH2 and cultured as in (J). FLAG, anti-FLAG blot.

(L–N) iGB cells transduced with shControl or shSIAH2 were stimulated with IL-4.

(L) Immunoblot analysis after 6 h of stimulation.

(M) Intracellular aKG level after 6 h of stimulation.

(N) qRT-PCR analysis after 1 day of stimulation.

(O) Analysis of spleens frommice transferred with B1-8hi B cells transduced with shControl or shSIAH2 and immunized as in (F). The data are presented as in (F).

Data are means ± SDs of 3 technical replicates from 1 biological sample pooled from n = 3 (NB in B) or 20 (GC B in B), or 3 (C–E, M, and N) or 6 (F and O) biological

replicates. Each symbol represents a biological sample of triplicate culture (C), a biological sample of triplicate transductions (D, E, M, and N), or an individual

mouse (F and O). The data are representative of 2 (B–F and J–O) or 3 (G and H) independent experiments, or from 1 experiment (I). p values were calculated by 1-

way ANOVA with Tukey’s test (C) or 2-tailed unpaired Student’s t test (D–F and M–O). See also Figure S7.

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Turqueti-Neves et al., 2014), we demonstrated that the IL-4-

signaling axis is an important instructive signal for GC B cell dif-

ferentiation. We further revealed that IL-4 signaling is the key

inducer of Bcl6 and identified the detailed molecular mecha-


nisms for Bcl6 induction. In B cells stimulated with IL-4 for 6 h,

the DJm was elevated and cellular metabolism was rapidly re-

programmed, especially in the TCA cycle, which resulted in the

accumulation of intracellular aKG that was required for the

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induction of Bcl6 expression. Under conditions of limited

glucose, supplementation with aKG was sufficient to induce

Bcl6 expression in vitro and GC B cell development in vivo.

aKG accumulation was mainly due to the following modulations

of TCA cycle enzymes: (1) decreased aKGDH activity through

the SIAH2-mediated degradation of DLST (Habelhah et al.,

2004) and (2) enhanced IDH2 activity by as yet unknown mech-

anisms. The elevatedDJm and aKG accumulation, as well as the

alterations in the activity of aKGDH and IDH2, were also

observed in ex vivo GC B cells, suggesting that the same mech-

anism forBcl6 expression ismaintained throughout theGCB cell

development process.

Despite the previous evidence for a crucial role of glutaminol-

ysis in producing aKG (Carey et al., 2015; Chisolm et al., 2017),

our data indicate that reprogramming TCA cycle regulation

mainly contributes to the accumulation of intracellular aKG in

IL-4-stimulated B cells. This is consistent with the recent report

that aKG-accumulation relies on mitochondrial oxidative meta-

bolism in primordial germ cells (Tischler et al., 2019). It was re-

ported that pharmacological inhibition of the ETC suppresses

pyruvate entry into the TCA cycle and activates the reductive

TCA cycle, a reverse reaction relative to the canonical oxidative

TCA cycle (Mullen et al., 2011). The reductive TCA cycle pro-

motes the conversion of aKG into citrate, providing growth-pro-

moting nutrients such as acetyl-CoA and lowering the aKG level

(Fendt et al., 2013). Consistently, we observed that ETC inhibi-

tion in IL-4-stimulated B cells suppressed aKG accumulation

and Bcl6 expression, further illustrating that the oxidative TCA

cycle is important for the aKG accumulation in differentiating B

cells. Ex vivo GC B cells also exhibited elevated DJm, and GC

B cell development was dependent on the mitochondrial oxida-

tive metabolism. These data strongly suggest that mitochondrial

oxidative metabolism plays a dominant role in GC B cell meta-

bolism as observed in IL-4-activated differentiating B cells. While

wewere completing this manuscript, another study reported that

GC B cells primarily usemitochondrial oxidative metabolism that

is mainly fueled with fatty acids (FAs), but minimally use glycol-

ysis (Weisel et al., 2020). This study mainly focused on estab-

lished GC B cells (at day 14 postimmunization) with in vivo inter-

vention starting from day 9; however, our data instead represent

an early phase of GC B cell development. They also showed that

early GC B cells (at day 8 postimmunization) do not significantly

rely on exogenous FAs, but peak (day 13) or late (day 23) GC B

cells do so. Thus, the fuels required for the mitochondrial oxida-

tive metabolism in GC B cells may differ in their developing

phase and maintenance phase.

We demonstrated that STAT6 is a key transcriptional activator

of Bcl6 expression and acts cooperatively with accumulated

aKG. After IL-4 treatment, STAT6 bound to the Bcl6 locus, espe-

cially at the upstream enhancers that have been reported to be

the GC B cell-specific super-enhancers responsible for Bcl6

expression (Bunting et al., 2016; Ryan et al., 2015). In NB cells,

the same regions were abundant in H3K27me3, a characteristic

of poised enhancers that cannot drive gene expression (Calo and

Wysocka, 2013). Once such H3K27me3 are demethylated and

acquire acetylation at the same residue (H3K27Ac), the poised

enhancer regions become activated (Calo and Wysocka, 2013;

Rada-Iglesias et al., 2011). In line with this, we observed that

the Bcl6 enhancer-bound STAT6 recruited UTX, an aKG-depen-

dent JmjC-histone demethylase, which in turn reduced

H3K27me3 and increased H3K27Ac in the enhancers and then

activated Bcl6 transcription. UTX has recently been reported to

associate with an H3K27 acetyltransferase, p300/CBP (Calo

and Wysocka, 2013; Wang et al., 2017), a known co-activator

of STAT6 (Gingras et al., 1999). We demonstrated a physical as-

sociation of STAT6 andUTX in the IL-4-stimulated B cells; thus, it

is possible that STAT6 interacts indirectly with UTX via p300/

CBP. In addition, UTX has been shown to associate with

mixed-lineage leukemia (MLL)3/4 (Piunti and Shilatifard, 2016),

methyltransferases that deposit the H3K4me1 enhancer mark,

and with the SWI/SNF chromatin remodeler complex (Miller

et al., 2010). Hence, we speculate that the IL-4-activated

STAT6-UTX axis may exert multiple-layered epigenetic modula-

tion at the super-enhancers in the Bcl6 locus. We propose a

model in which, during GCB cell differentiation, IL-4 signaling re-

programs TCA cycle metabolism to accumulate aKG, which in-

tegrates the epigenetic activation of the Bcl6 locus mediated

by the STAT6-UTX axis.

Considering our data demonstrating that (1) GC B cells accu-

mulated aKG, (2) they displayed a global decrease in the

H3K27me3 mark, and (3) their development was dependent on

H3K27me3-demethylase activity, we propose that the aKG-

dependent demethylation of H3K27me3 actively occurs in GC B

cells. H3K27me3 has been considered to be dynamically

controlled, which allows genes to be switched on and off during

differentiation. For example, naive ESCs display aKG-accumula-

tion with a global decrease in H3K27me3 rendered by the aKG-

dependent demethylation process, whereas more differentiated

ESCs gain H3K27me3 in genes involved in cell fate determination,

concomitant with a decrease in intracellular aKG levels (Carey

et al., 2015; Hawkins et al., 2010; Zhu et al., 2013). By analogy,

we speculate that accumulated aKG in GC B cells may support

H3K27me3-demethylation, by which actively dividing GC B cells

may inherit the GC phenotype andmaintain the plasticity to differ-

entiate into memory B cells or long-lived PCs. In contrast to this

scenario, a histone methyltransferase enhancer of zeste homolog

2 (EZH2)-mediated deposition of H3K27me3 has been reported to

be required for the development ofGCBcells by inhibiting cell-cy-

cle arrest (Beguelin et al., 2013; Caganova et al., 2013). This

apparent discrepancy may be explained as follows: domains tar-

geted by H3K27me3-demethylase and those by H3K27me3-

methyltransferase do not completely overlap in GC B cells, as a

previous report showed that more than half of the genes activated

by UTX are not activated by the loss of EZH2 in multiple myeloma

cells (Ezponda et al., 2017).

In line with their involvement in GC development (Kopf et al.,

1998; Linterman et al., 2010; Turqueti-Neves et al., 2014; Zotos

et al., 2010), IL-6, IL-13, and IL-21 also upregulated Bcl6 expres-

sion in vitro, albeit modestly as compared to IL-4. The fact that

IL-6 and IL-21 do not use STAT6 for signaling implies STAT6-

independent mechanisms for Bcl6 induction. It was reported

that the IL-4/IL-13-STAT6 axiswas required for GC formation after

helminth infection or immunization with ovalbumin in alum or

sheep red blood cells (SRBCs), but not after infection with lym-

phocytic choriomeningitis virus (LCMV) or murine cytomegalo-

virus (MCMV) (Turqueti-Neves et al., 2014). Other reports


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OPEN ACCESS

demonstrated that STAT6-deficient B cells exhibited almost

normal GC responses in mixed bone marrow chimeric mice

when immunized with SRBC, but a markedly reduced GC

response after influenza virus infection; functional redundancy of

STAT6 and IL-21 signaling was apparent in both (Chevrier et al.,

2017). In line with our data, it was reported that STAT6 contributes

to the expansion of Bcl6hi GC B cells beyond the pre-GC stage,

whereas IL-21 is required for pre-GC B cell expansion, in mice

immunized with NP-ovalbumin in alum (Gonzalez et al., 2018).

Although differences in experimental settings may cause some

discrepancy, these results suggest that the extent of the contribu-

tion of IL-4-STAT6 axis to Bcl6 induction and GC formation in vivo

may vary depending on different antigens, adjuvants, immuniza-

tion protocols, and so on, and can be induced by IL-4-STAT6-in-

dependent signaling pathways in some situations. Clarifying such

alternative pathways will provide deeper insight into the mecha-

nisms regulating GC B cell development.

Finally, given our results revealing that metabolic reprogram-

ing is a crucial factor regulating the expression of a key transcrip-

tion factor and GC B cell differentiation, one may need to

consider such dysregulated B cell metabolism, possibly caused

in a cell-intrinsic manner and/or by some environmental factors

(e.g., nutrients), as a component of the pathogenesis of immuno-

logical disorders and lymphomagenesis.

STAR+METHODS

Detailed methods are provided in the online version of this paper

and include the following:

d KEY RESOURCES TABLE

d RESOURCE AVAILABILITY

12

B Lead Contact

B Materials Availability

B Data and Code Availability

d EXPERIMENTAL MODEL AND SUBJECT DETAILS

B Mice

B iGB cell culture

d METHOD DETAILS

B Immunization and in vivo treatments

B Ex vivo cell purification

B Flow cytometry

B BrdU incorporation assay

B Immunoblotting and immunoprecipitation

B RT-PCR, qPCR

B Dehydrogenase activity assay

B Lactate production assay

B Plasmid constructions

B Retroviral Transduction

B Metabolomics

B aKG measurement

B Chromatin immunoprecipitation (ChIP) analysis

d QUANTIFICATION AND STATISTICAL ANALYSIS

SUPPLEMENTAL INFORMATION

Supplemental Information can be found online at https://doi.org/10.1016/j.

celrep.2020.108333.

Cell Reports 33, 108333, November 3, 2020

ACKNOWLEDGMENTS

We thankM. Nussenzweig (Rockefeller University) and T. Kurosaki (OsakaUni-

versity) for B1-8hi mice; N. Yakushiji-Kaminatsui (RIKEN) for technical advice

and critical comments; H. Ebiko and H. Hasegawa (RIBS) for technical assis-

tance; T. Koike (RIBS) for plasmid constructs and suggestions; and P. Burrows

for critical reading of the manuscript. This work was supported by the Japan

Society for the Promotion of Science KAKENHI Grant-in-Aid for Young Scien-

tists (A) (17H05072) (to K.H.) and Grant-in-Aid for Challenging Exploratory

Research (16K15295) (to D.K.), and by the Kanae Foundation, the Inamori

Foundation, the Naito Foundation, and the Nakajima Foundation (all to K.H.).

AUTHOR CONTRIBUTIONS

K.H. conceived and supervised the project, designed and performed experi-

ments, analyzed the data, andwrote themanuscript. S.F. designed, performed

experiments, edited the manuscript, and originally suggested that metabolism

is a fate-determining factor of B cells. D.K. supervised the project and wrote

the manuscript.

DECLARATION OF INTERESTS

The authors declare no competing interests.

Received: April 29, 2020

Revised: July 8, 2020

Accepted: October 8, 2020

Published: November 3, 2020

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STAR+METHODS

KEY RESOURCES TABLE

REAGENT or RESOURCE SOURCE IDENTIFIER

Antibodies

Biotin anti-mouse IgM Biolegend Cat# 406504; RRID: AB_315054

PE anti-mouse IgD Biolegend Cat# 405706; RRID: AB_315028

PerCP-Cy5.5 anti-mouse IgD Biolegend Cat# 405710; RRID: AB_1575113

FITC anti-mouse IgG1 BD Biosciences Cat# 553443; RRID: AB_394862

BV421 anti-mouse IgG1 BD Biosciences Cat# 562580; RRID: AB_2737664

APC anti-mouse IgG1 BD Biosciences Cat# 560089; RRID: AB_1645625

PE anti-mouse IgE Biolegend Cat# 406908; RRID: AB_493290

Biotin anti-mouse IgE Biolegend Cat# 406904; RRID: AB_315075

PE anti-mouse CD4 Biolegend Cat# 100512; RRID: AB_312715

Biotin anti-mouse CD4 Biolegend Cat# 100404; RRID: AB_312689


Purified anti-mouse CD16/32 BD Biosciences Cat# 553142; RRID: AB_394657

PE-Cy7 anti-mouse CD19 Biolegend Cat# 115520; RRID: AB_313655

APC-Cy7 anti-mouse CD19 Biolegend Cat# 115530; RRID: AB_830707




FITC anti-mouse CD45.1 Biolegend Cat# 110706; RRID: AB_313495

BV421 anti-mouse CD45.1 Biolegend Cat# 110732; RRID: AB_2562563

Biotin anti-mouse CD49b Biolegend Cat# 108904; RRID: AB_313411



BV421 anti-mouse CD138 Biolegend Cat# 142508; RRID: AB_11203544

Biotin anti-mouse CXCR5 Biolegend Cat# 145510; RRID: AB_2562126

PE-Cy7 anti-mouse B220 Biolegend Cat# 103222; RRID: AB_313005

APC-Cy7 anti-mouse B220 Biolegend Cat# 103224; RRID: AB_313007

APC anti-human/mouse Bcl6 Biolegend Cat# 358506; RRID: AB_2562472

Alexa Fluor 647 anti-BrdU Thermo Fisher Scientific Cat# B35140; RRID: AB_2536440

FITC anti-mouse/human GL7 Biolegend Cat# 144604; RRID: AB_2561697

BV421 anti-mouse/human GL7 BD Biosciences Cat# 562967; RRID: AB_2737922

Alexa Fluor 647 anti-mouse/human GL7 Biolegend Cat# 144606; RRID: AB_2562185

Biotin anti-mouse H-2Kd Biolegend Cat# 116604; RRID: AB_313739

PE anti-IRF4 eBiosciences Cat# 12-9858-82; RRID: AB_10852721

PE-Cy7 anti-mouse PD-1 Biolegend Cat# 109110; RRID: AB_572017

BV510 anti-mouse TER119 Biolegend Cat# 116237; RRID: AB_2561661

Biotin anti-mouse TER119 Biolegend Cat# 116204; RRID: AB_313705

HRP anti-goat IgG Jackson ImmunoResearch Cat# 805-035-180; RRID: AB_2340874

HRP anti-rabbit IgG Jackson ImmunoResearch Cat# 711-035-152; RRID: AB_10015282

HRP anti-mouse kappa SouthernBiotech Cat# 1050-05; RRID: AB_2650508

Anti-mouse IgG F(ab’)2 Jackson ImmunoResearch Cat# 115-006-071; RRID: AB_2338472

Anti-actin Santa Cruz Biotechnology Cat# sc-1616; RRID: AB_630836

Anti-mouse CD40 BioXCell Cat# BE0016-2; RRID: AB_1107647

Anti-DLD Bethyl Laboratories Cat# A304-733A; RRID: AB_2620928

(Continued on next page)

Cell Reports 33, 108333, November 3, 2020 e1

Continued


Anti-DLST Cell Signaling Technology Cat# 5556S; RRID: AB_10695157

Anti-FLAG-tag (M2) Sigma Cat# F3165; RRID: AB_259529

Anti-Histone H3 Cell Signaling Technology Cat# 4499S; RRID: AB_10544537

Anti-H3K4me3 Active Motif Cat# 39915; RRID: AB_2687512

Anti-H3K9me3 Cell Signaling Technology Cat# 13969S; RRID: AB_2798355

Anti-H3K27me3 Cell Signaling Technology Cat# 9733S; RRID: AB_2616029

Anti-H3K27Ac Cell Signaling Technology Cat# 8173S; RRID: AB_10949503

Anti-mouse IL-4 BioXCell Cat# BE0045; RRID: AB_1107707

Anti-OGDH Cell Signaling Technology Cat# 26865S; RRID: AB_2737585

Anti-PDH-E1a Cell Signaling Technology Cat# 3205S; RRID: AB_2162926

Anti-phospho-PDH-E1a (S293) Calbiochem Cat# AP1062; RRID: AB_10616069

Anti-STAT3 Santa Cruz Biotechnology Cat# sc-482; RRID: AB_632440

Anti-phospho-STAT3 (Y705) Cell Signaling Technology Cat# 9145S; RRID: AB_2491009

Anti-STAT5 Cell Signaling Technology Cat# 94205S; RRID: AB_2737403


Anti-STAT6 Santa Cruz Biotechnology Cat# sc-981; RRID: AB_632450


Anti-Tubulin Sigma Cat# T9026; RRID: AB_477593

Anti-UTX Cell Signaling Technology Cat# 33510S; RRID: AB_2721244

Anti-V5-tag Thermo Fisher Cat# R960-25; RRID: AB_2556564

Rabbit IgG Cell Signaling Technology Cat# 3900S; RRID: AB_1550038

Rabbit IgG Jackson ImmunoResearch Cat# 011-000-003; RRID: AB_2337118

Chemicals, Peptides, and Recombinant Proteins

Fixable Viability Dye eFluor 506 Thermo Fisher Scientific Cat# 65-0866-18

Recombinant murine IL-1a PeproTech Cat# 211-11A

Recombinant murine IL-1b PeproTech Cat# 211-11B

Recombinant murine IL-2 PeproTech Cat# 212-12








Recombinant murine IL-12 Biolegend Cat# 210-12



Recombinant murine IL-17A PeproTech Cat# 210-17

Recombinant murine IL-17F PeproTech Cat# 210-17F


Recombinant mouse IL-23 Biolegend Cat# 589002

Recombinant mouse IL-27 Biolegend Cat# 577402

Recombinant murine IL-28A (IFNl2) PeproTech Cat# 250-33


Recombinant mouse IFNa Biolegend Cat# 752802

Recombinant murine IFNg PeproTech Cat# 315-05

Recombinant human TGFb1 PeproTech Cat# 100-21

Recombinant SCF PeproTech Cat# 250-03


e2 Cell Reports 33, 108333, November 3, 2020

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OPEN ACCESS

Continued


Recombinant murine GM-CSF PeproTech Cat# 315-03

SYBR Green qPCR Master Mix Cat#

Tetramethylrhodamine, Methyl Ester,

Perchlorate (TMRM)

Thermo Fisher Scientific Cat# T668

MitoTracker Deep Red FM Thermo Fisher Scientific Cat# M22426

MitoSOX Red Thermo Fisher Scientific Cat# M36008

2-NBDG Thermo Fisher Scientific Cat# N13195

Oligomycin A Sigma Cat# 75351

5-Bromo-20-deoxyuridine (BrdU) Sigma Cat# B5002

Dimethyl a-ketoglutarate (DMaKG) Sigma Cat# 349631

Diethyl Succinate (DE-Suc) WAKO Cat# 056-03922

Sheep red blood cell (SRBC) Nippon Bio-supp. Center N/A

Internal standards for metabolomics Human Metabolome Technologies Cat# H3304-1002

2-isopropylmalic acid Sigma Cat# 333115

Methoxylamine hydrochloride MP Biomedicals Cat# 155405

N-methyl-N-trimethylsilyl-

trifluoroacetamide

GL Science Cat# 1022-11060

Formaldehyde Wako Cat# 064-00406

DNase I Sigma Cat# D5025

RNase A Sigma Cat# R6513

Proteinase K Merck Cat# 1.24568.0100

GSK-J4 Sigma Cat# SML0701

PEI Max (Mw 40,000) Polysciences Cat# 24765-1

NP-Osu Biosearch Technologies Cat# N-1010

NP14-BSA-Alexa Fluor 647 (Haniuda et al., 2016) N/A

NP14-BSA-Biotin (Haniuda et al., 2016) N/A

NP34-CGG (Haniuda et al., 2016) N/A

NP53-Ficoll Biosearch Technologies Cat# F-1420

DOTAP Liposomal Transfection Reagent Sigma Cat# 11202375001

Streptavidin-BV 421 Biolegend Cat# 405225

Streptavidin-PE-Cy7 Biolegend Cat# 405206

Streptavidin Particle Plus DM BD Biosciences Cat# 557812

Anti-FITC microbeads Miltenyi Biotec Cat# 130-048-701

Anti-PE microbeads Miltenyi Biotec Cat# 130-048-801

Dynabead Protein G Thermo Fisher Scientific Cat# 10004D

Protein G Sepharose 4 Fast Flow GE Healthcare Cat# 17061801

Anti-FLAG M2 Affinity Gel Sigma Cat# A2220

Anti-V5 Agarose Affinity Gel Sigma Cat# A7345-1ML

Mouse IgG�Agarose Sigma Cat# A0919

TRI Reagent Sigma Cat# T9424

Oligo(dT)20 Primer Thermo Fisher Scientific Cat# 18418020

Rotenone Sigma Cat# R8875

Nitro Blue Tetrazolium Chloride WAKO Cat# 148-01996

Phenazine methosulfate WAKO Cat# 166-09211

MG-132 WAKO Cat# 135-18453

Bafilomycin A1 Abcam Cat# ab120497



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Continued


Critical Commercial Assays

Foxp3/Transcription Factor Staining Buffer

Set

Thermo Fisher Scientific Cat# 00-5523-00

Fixation/Permeabilization Solution Kit BD Biosciences Cat# 554714

Glycolysis Cell-Based Assay Kit BioVision Cat# 600450

Alpha Ketoglutarate Dehydrogenase

Activity Colorimetric Assay Kit

BioVision Cat# K678-100

PDH enzyme activity dipstick assay kit Abcam Cat# ab109882

Alpha Ketoglutarate Assay Kit Abcam Cat# ab83431

QIAquick PCR Purification Kit QIAGEN Cat# 28106

RNeasy Mini Kit QIAGEN Cat# 74106

ReverTra Ace TOYOBO Cat# TRT-101

Thunderbird SYBR qPCR Mix TOYOBO Cat# QPS-201

KOD Fx Neo DNA polymerase TOYOBO Cat# KFX-201

BCA Protein Assay Kit TAKARA Cat# T9300A

Deposited Data

H3K4me3, H3K4me1 ChIP-seq dataset (Braz~ao et al., 2016) GEO: GSE72017

H3K27me3 ChIP-seq dataset (Vian et al., 2018) GEO: GSE82144

H3K27me3 ChIP-seq dataset (Caganova et al., 2013) GEO: GSE50912

H3K27Ac ChIP-seq dataset (Meng et al., 2014) GEO: GSE62296

STAT6 ChIP-seq dataset (Czimmerer et al., 2018) GEO: GSE106701

Experimental Models: Cell Lines

40LB feeder cell (Nojima et al., 2011) N/A

PLAT-E retroviral packaging cell line Dr. Toshio Kitamura (Tokyo University) RRID: CVCL_B488

Experimental Models: Organisms/Strains

Mouse: C57BL/6NCrSlc Japan SLC Inc. N/A

Mouse: B1-8hi (Shih et al., 2002) N/A

Mouse: C57BL/6-CD45.1 RIKEN BRC Cat# RBRC00144,

RRID:IMSR_RBRC00144

Oligonucleotides

For details of qPCR/ChIP primers and

shRNA used in this study, see Table S2

This paper N/A

Recombinant DNA

pMXs-IRES-GFP Dr. Toshio Kitamura (Tokyo University) N/A

pMXs-DLST-V5-IRES-GFP This paper N/A

pMXs-FLAG-SIAH2-IRES-Puro This paper N/A

pVSV-G Clontech Cat# 631530

pSIREN-GFP shLuciferase (shControl) (Koike et al., 2019) N/A

pSIREN-GFP shUTX This paper N/A

pSIREN-GFP shSTAT3 This paper N/A



pSIREN-GFP shIDH2 This paper N/A

pSIREN-GFP shSIAH2 This paper N/A

Software and Algorithms

FlowJo https://www.flowjo.com/solutions/flowjo RRID: SCR_008520

MetaboAnalyst 4.0 https://www.metaboanalyst.ca RRID:SCR_015539

Morpheus https://software.broadinstitute.org/

morpheus/

RRID:SCR_014975



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https://www.flowjo.com/solutions/flowjo

https://www.metaboanalyst.ca

https://software.broadinstitute.org/morpheus/


Continued


Galaxy https://main.g2.bx.psu.edu/ RRID:SCR_006281

ImageJ https://imagej.nih.gov/ij/ RRID:SCR_003070

Bowtie2 http://bowtie-bio.sourceforge.net/bowtie2/

index.shtml

RRID:SCR_005476

UCSC Genome Browser https://genome.ucsc.edu RRID:SCR_005780

GraphPad Prism 8 GraphPad Software RRID:SCR_002798

Articlell

OPEN ACCESS

RESOURCE AVAILABILITY

Lead ContactFurther information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Daisuke

Kitamura ([email protected])

Materials AvailabilityThe reagents generated in this study may be made available on request upon completing a Materials Transfer Agreement.

Data and Code AvailabilityThe data that support the findings of this study are available from the corresponding author on request.

EXPERIMENTAL MODEL AND SUBJECT DETAILS

MiceC57BL/6NCrSlc (B6) mice were purchased from Japan SLC Inc. B1-8hi mice (Shih et al., 2002) were backcrossed to congenic B6-

CD45.1 strain. All animals were maintained in a mouse facility in Research Institute for Biomedical Sciences, Tokyo University of

Science (TUS) under specific pathogen-free conditions and were treated under protocols approved by the Animal Care and Use

Committee of the TUS. Experiments were done using sex- and age-matched mice between 6-12 weeks of age.

iGB cell cultureNaive B (NB) cells were purified from spleens by magnetic negative sorting using a cocktail of biotinylated Abs for CD4, CD8, CD43,

CD49b, Ter119, and Streptavidin Particles Plus DM and IMag system (BD Biosciences), and MACS system (Miltenyi Biotec) as

described previously (Nojima et al., 2011). Typically, 1x106 purified B cells were plated on 3x106 80-Gy-irradiated 40LB cells in a

10-cm dish and cultured for 3 days at 37�C with 5% CO2, 1 ng/mL IL-4 in 30 mL B cell medium (BCM): RPMI-1640 medium

(Wako) supplemented with 10% heat-inactivated fetal bovine serum (FBS), 50 mM 2-mercaptoethanol (2-ME), 10 mM HEPES pH

7.5 (HEPES), 100 U/ml penicillin and 100 mg/ml streptomycin (Pen-Strep) (GIBCO). To isolate iGB cells from the culture, 40LB cells

were removed using biotinylated anti-H-2Kd Ab (Biolegend), Streptavidin Particle Plus DM and the IMag system (BD Biosciences). In

some experiments, biotinylated anti-IgM and anti-IgE Abs (Biolegend) were further added to purify IgG1+ cells as shown in Fig-

ure S1C. To induce Bcl6+ cells, iGB cells cultured for 3 days were isolated and further cultured for 1 day in the BCM without feeder

cells (plain culture). As indicated, reagents were added to the plain culture at the concentration shown in Table S1. In some exper-

iments, 1 mM oligomycin, 10 mM GSK-J4, 10 mM MG-132, or 0.1 mM bafilomycin A1 were added to the plain culture as indicated. In

some cases, the plane culture was performed in glucose-free RPMI-1640 (Wako) supplemented with dialyzed 10% FBS, 2-ME,

HEPES, Pen-Strep and glucose at low (0.1 mM) or normal (10 mM) concentration with or without 5 mM DMaKG (Sigma) or 5 mM

DE-Suc (Wako). For iGB cell transfer experiment, 5 3 106 live iGB cells derived from CD45.1-B1-8hi mice were isolated and trans-

ferred into B6 mice on day 4 after immunization.

METHOD DETAILS

Immunization and in vivo treatmentsMice were immunized i.p. with 100 mg of NP34-CGG in alum unless otherwise noted. For isolation of GC B cells and PCs, mice were

administered i.v. with 5x108 of sheep red blood cells (SRBC) (Nippon Bio-Supp. Center). The following reagents or vehicle alone were

injected i.p. into immunizedmice: oligomycin (0.5mg/kg, Sigma) or GSK-J4 (10mg/kg, Sigma), each dissolved in PBS containing 5%

Tween 80 and 5% PEG 400; IL-4 complex (IL-4c), recombinant mouse IL-4 (2 mg, PeproTech) and anti-mouse IL-4 (10 mg, BioXCell,

clone: 11B11), mixed and diluted in 200 ml of PBS.



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Articlell

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Ex vivo cell purificationGCB cells and PCs weremagnetically enriched from pooled spleens of SRBC-immunizedmice using FITC-conjugated anti-GL7 and

PE-conjugated anti-CD138 Abs (Biolegend), anti-FITC and anti-PE MicroBeads (Miltenyi Biotec), with the MACS system (Miltenyi

Biotec). After enrichment, cells were further stainedwith respective Abs and sorted using FACSAria II or III (BDBiosciences) as shown

in Figure S2B. NB cells were sorted from unimmunized B6mice using FACSAria II or III as shown in Figure S2B. For in vivo analysis of

antigen-specific B cells, NB cells were purified from B1-8hi mice as described above, and the frequency of NP+ cells was determined

by flow cytometry, and then NB cells containing 104 NP+ B cells were transferred into B6 mice, which were then immunized i.p. with

NP-CGG in alum on the next day. For the lactate production assay, CD45.1+ donor B cells were magnetically enriched from pooled

spleens on day 3.5 or day 7 after immunization using FITC-conjugated anti-CD45.1 Ab (Biolegend), anti-FITC MicroBeads and the

MACS system. Then, enriched cells were further stained with respective Abs and sorted using FACSAria II or III with the gating strat-

egy as shown in Figure S2A.

Flow cytometrySingle-cell suspensions from spleens were prepared at the indicated days after immunization, red blood cells were lysed with ammo-

nium chloride buffer, and then cells were incubated with anti-CD16/32 Ab (2.4G2) to block FcgRs. iGB cells were collected with

MACS buffer (PBS supplemented with 0.5% BSA, 2 mM EDTA) at the indicated days of culture. Cells were stained with Abs and re-

agents on ice (for splenocytes) or at room temperature (for iGB cells). For staining total (surface and intracellular) IgG1 and IgE, iGB

cells were treated with a Fixation/Permeabilization solution and Perm/Wash buffer (BD Biosciences) or Foxp3/Transcription Factor

Staining Buffer Set (Thermo Fisher Scientific) according to the manufacturer’s protocol as described (Haniuda et al., 2016). Intracel-

lular Bcl6 was stained in cells treated with the Foxp3/Transcription Factor Staining Buffer Set. To monitor the mitochondrial or glyco-

lytic activity, cells were loaded with 100 nM MitoTracker, 500 nM TMRM, 5 mM MitoSOX Red or 10 mg/mL 2-NBDG (Thermo Fisher

Scientific) at 37�C with 5% CO2 for 30 min (or 10 min for MitoSOX) in glucose-free RPMI-1640 medium (Wako). After washing, cells

were stained for surface markers as described above and subjected to flow cytometric analysis. All samples were analyzed using

FACSCanto II, FACSAria II or III (BD Biosciences) with FlowJo software (Tree Star, Inc.). The gating strategies for iGB cells or B cells

ex vivo are shown in Figures S1B or S2B, respectively.

BrdU incorporation assayImmunized mice were given i.v. injection of 3 mg of BrdU (5-bromodeoxyuridine) (Sigma) dissolved in PBS, 1 h prior to euthanasia for

sampling. Splenocytes from these mice were washed with cold PBS, resuspended in 0.5 mL cold 0.15 M NaCl, to which 1.2 mL cold

95% ethanol was added dropwise while the tube was gently vortexed, and then left on ice for 30 min. These cells were then washed

and fixed with 1 mL of PBS containing 1% paraformaldehyde and 0.05% Tween 20 overnight at 4 C. Fixed cells were resuspended in

1 mL of DNase I buffer (0.15 M NaCl, 4.2 mM MgCl2, 10 mM HCl and 30 U/ml DNase I (Sigma)) and incubated for 30 min at room

temperature. The cells were washed and stained with Alexa 647-conjugated anti-BrdU Ab (Thermo Fisher Scientific) overnight at

4 C.

Immunoblotting and immunoprecipitationiGB cells were lysed with RIPA buffer (40 mM Tris-HCl pH 7.5, 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate, 0.1% SDS and

1mMEDTA) supplemented with protease and phosphatase inhibitors for 25min on ice. Lysates were sonicated and then weremixed

with sample buffer and dithiothreitol (DTT) and boiled. NB cells and GC B cells were directly lysed with sample buffer with DTT, son-

icated and boiled. Boiled lysates were resolved on SDS-PAGE or Tricine-SDS-PAGE and transferred to PVDF membrane (Millipore),

followed by immunoblotting as previously described (Haniuda et al., 2016). For immunoprecipitation (IP) of STAT6, cells were lysed

with lysis buffer (40 mM Tris-HCl pH 7.5, 400 mM NaCl, 1 mMMgCl2, 0.1% NP-40, 1 mM EDTA, 0.5 mMDTT and 20% glycerol) with

protease and phosphatase inhibitors for 20 min on ice. Lysates were diluted with equal volume of dilution buffer (40 mM Tris-HCl pH

7.5, 5 mMMgCl2, 1.3 mg/ml bovine serum albumin (BSA), 0.5 mMDTT and 20% glycerol), precleared and then incubated with rabbit

anti-STAT6 Ab (Santa Cruz Biotechnology) or control IgG, followed by precipitation with Protein G Sepharose 4 Fast Flow (GEHealth-

care). For IP of FLAG- or V5-tagged protein, cells were lysed with 1% NP-40 lysis buffer (40 mM Tris-HCl pH 7.5, 150 mM NaCl, 1%

NP-40, and 1mMEDTA) with protease and phosphatase inhibitors for 25min on ice. The lysates were precleared and then incubated

with anti-FLAG (M2) Ab- or anti-V5 Ab-conjugated beads or control mouse IgG-conjugated beads (Sigma). After extensive washing

with IP-Wash buffer (40 mM Tris-HCl pH 7.5, 150 mMNaCl, 0.5% NP-40, 1 mM EDTA and 5% glycerol), the precipitates were boiled

in sample buffer with DTT and subjected to SDS-PAGE, followed by immunoblotting.

RT-PCR, qPCRTRI Reagent (Sigma) or RNeasyMini (QIAGEN) was used to isolate total RNA from B cells. cDNAwas generated from total RNA using

ReverTra Ace (TOYOBO) with oligo(dT)20 primer (Thermo Fisher Scientific) according to the manufacturer’s protocols. Quantitative

real-time PCR (qPCR) was performed using Thunderbird SYBR qPCRMix (TOYOBO) with 7500 fast Real-time PCR system or Quant-

Studio 3 (Applied Biosystems). For quantification of gene expression level, each samplewas normalized to the expression of a control

housekeeping gene,Gapdh,Hprt or Actb. The fold change in expression of each gene compared to a control sample, set as 1.0, was

calculated with the 2-ddCT method. Primers used in this study are listed in Table S2.


Articlell

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Dehydrogenase activity assayPDH activity in cell lysates wasmeasured using the Enzyme Activity Dipstick Assay Kit (Abcam): Cells were lysed in the sample buffer

provided by the manufacturer, and protein concentration in the lysates were measured with BCA Protein Assay (Takara). Equal

amounts of lysates were used formeasuring PDH activity according to themanufacturer’s protocol. Band density was analyzed using

the ImageJ software. Mitochondria were isolated and mitochondrial IDH activity was assessed using a colorimetric assay as

described previously (Sun and Denko, 2014) with some modifications detailed in the following: To isolate mitochondria, 5-10 3

106 cells (iGB cell) or 2-6 3 107 cells (NB and GC B) were resuspended in 750 ml of hypotonic buffer (10 mM Tris-HCl pH 7.5,

10 mM NaCl and 1.5 mM MgCl2), incubated for 5 min on ice and homogenized by 20 stroke in 1 mL syringe with 26G needle. After

adding 500 mL of 2.5 3MS buffer (12.5 mM Tris-HCl pH 7.5, 2.5 mM EDTA, 175 mM sucrose and 525 mMmannitol), nuclei and un-

broken cells were removed by centrifugation at 8003 g for 5 min at 4�C, twice. Mitochondria were collected from the supernatant by

centrifuging at 10,0003 g for 10 min at 4�C and washed with 13MS buffer (diluted with water). The protein amount was determined

by BCA Protein Assay (Takara) and equal amounts of isolated mitochondria were lysed with IDH reaction buffer (50 mM Tris-HCl pH

7.5, 8mMMgCl2, 1mMMnCl2, 0.05mMEDTA, 0.2%Triton X-100, 10 mM rotenone, 10mM sodium citrate, 1.5mMsodium isocitrate,

2 mM ADP, 0.75 mM Nitro Blue Tetrazolium Chloride and 0.05mM Phenazine methosulfate) supplemented with either 2 mM NAD or

1 mM NADP, and incubated in 96 well plate at 37�C with 5% CO2 for 30 min. The reaction was stopped, and resultant blue formazan

was solubilized by adding an equal volume of 20%SDS in 0.02MHCl and incubating at 37�Covernight. OD at 590 nmwasmeasured.

For aKGDH activity, mitochondria were isolated as described above and the same amounts of mitochondria were loaded and

measured using the a-Ketoglutarate Dehydrogenase Activity Colorimetric Assay Kit (BioVision) according to the manufacturer’s

protocol.

Lactate production assayIsolated B cells were cultured in phenol red-free RPMI-1640 medium (Wako) supplemented with HEPES and incubated at 37�C with

5% CO2 for 4 hr. Lactate concentrations in the supernatant were measured with Glycolysis Cell-Based Assay Kit (BioVision) accord-

ing to the manufacturer’s protocol.

Plasmid constructionscDNAs forDLST and SIAH2were cloned by PCR fromRNA of day 3 B6-iGB cells using KOD FxNeo DNA polymerase (TOYOBO). V5-

tag (GKPIPNPLLGLDST) or FLAG-tag (DYKDDDDK) was fused to the C-terminal of DLST or N-terminal of SIAH, respectively, by

ligating the corresponding sequences with these cDNA using PCR-generated de novo restriction enzyme sites. The resultant

DNA was cloned into pMXs-IRES-GFP or pMXs IRES-Puro vector (kindly provided by T. Kitamura, University of Tokyo). For RNAi,

the target sequences of shRNAs, as listed in Table S2, were inserted into a pSIREN-GFP vector (Koike et al., 2019).

Retroviral TransductionTo produce retrovirus, pSIREN- or pMXs-based plasmids were co-transfected together with pVSV-G into Plat-E cells (kindly pro-

vided by T. Kitamura, University of Tokyo) by PEI Max (Mw 40,000; Polysciences). The virus-containing supernatant was harvested

2 days after transfection. For retroviral transduction of iGB cells, day 2 iGB cells weremixedwith the virus-containing supernatant and

were spin-infected at 2,000 rpm, 37�C for 90 min with 10 mg/ml DOTAP Liposomal Transfection Reagent (Sigma) and IL-4 (Pepro-

tech). One day later, cells were harvested, re-plated on new 40LB feeder layers with IL-4, and harvested on day 4 as shown in Fig-

ure S5A. Retroviral transduction of in-vivo-activated primary B cells and their transfer into mice were performed as previously

described (Koike et al., 2019). In brief, B1-8hi mice were injected i.p. with 50 mg of NP53-Ficoll, and then B cells were purified from

the spleens of these mice 6 hr later and stimulated in vitro with 2 mg/ml anti-CD40 Ab (BioXCell, clone: FGK4.5) for 18 hr. Cultured

B cells were mixed with the virus-containing supernatant and were spin-infected as above without IL-4. The resultant viable 106 B

cells were transferred into B6 mice, which were then immunized i.p. with NP-CGG in alum on the next day.

MetabolomicsFor metabolome analysis using capillary electrophoresis coupled with mass spectrometry (CE-MS), iGB cells (3-6 3 106 cells/sam-

ple) were washed twice by 5% mannitol solution and were lysed with 800 ml of methanol. The cell extract was mixed with 550 ml of

MilliQ water containing internal standards (H3304-1002, Human Metabolome Technologies, Inc., Tsuruoka, Japan) to standardize

the metabolite intensity and to adjust the migration time, and centrifuged at 2,3003 g for 5 min at 4�C. Eight hundred ml of the upper

aqueous layer was centrifugally filtered through a Millipore 5-kDa cutoff filter (Millipore) at 9,100 3 g for 120 min at 4�C to remove

proteins. The filtrate was centrifugally concentrated and resuspended in 50 ml of Milli-Q water and analyzed by Human Metabolome

Technologies Inc. (Yamagata, Japan) using CE-MS. Cationic compounds were measured in the positive mode of CE-TOFMS and

anionic compounds were measured in the positive and negative modes of CE-MS/MS as described previously (Soga and Heiger,

2000; Soga et al., 2002, 2003). Metabolite set enrichment analysis was performed using the MetaboAnalyst 4.0 web-based pipeline

(https://www.metaboanalyst.ca) to visualize metabolic pathway enrichment. Hierarchical clustering and the heatmap were gener-

ated using the Morpheus web interface (https://software.broadinstitute.org/morpheus/).


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Articlell

OPEN ACCESS

aKG measurementB cells (1-83 107) were lysed with 400 ml of methanol containing 25 mM 2-isopropylmalic acid (Sigma) and centrifuged at 16,0003 g

for 5 min at 4�C. The supernatant was mixed with 320 ml of a mixture of water and chloroform (1:1), incubated for 5 min with agitation,

and was further mixed with 400 ml of water. After incubation for 5 min, the mixture was centrifuged as above, and the upper layer was

mixed with 320 ml of water and incubated for 5 min with agitation. The mixture was centrifuged as above, and the supernatant was

dried and re-dissolved in 60 ml of 20 mg/ml 2-methoxyamine hydrochloride (MP Biomedicals) in pyridine at 37�C for 1.5 hr. This so-

lution was mixed with 30 ml of N-methyl-N-trimethylsilyl-trifluoroacetamide (MSTFA) (GL Science), incubated at 37�C for 0.5 hr and

centrifuged at 16,0003 g for 5 min at 20�C. The resultant supernatant was subjected to gas chromatography coupled with MS (GC/

MS) measurement using GCMS-TQ8030 (Shimadzu) by Chemicals Evaluation and Research Institute (Saitama, Japan). Alternatively,

the amount of aKG was determined using alpha Ketoglutarate Assay Kit (Abcam) according to the manufacturer’s protocol.

Chromatin immunoprecipitation (ChIP) analysisOne times 107 cells were fixedwith 1% formaldehyde for 10minutes at room temperature and then lysedwith NB1 (50mMHEPESpH

7.9, 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% NP-40 and 0.25% Triton X-100). Nuclei were collected by centrifugation at

1,200 3 g for 5 min at 4�C and washed with NB2 (40 mM Tris-HCl pH 8.0, 200 mM NaCl, 1 mM EDTA and 0.5 mM EGTA) and lysed

with NB3 (40 mM Tris-HCl pH 8.0, 300 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1% Triton X-100, 0.5% SDS and 0.1% sodium deox-

ycholate) and sheared by sonication for 10 min using Bioruptor (Sonic Bio) in TPX microtubes. The soluble chromatin supernatant

(‘input’) was incubated with the indicated Abs and precipitated with Dynabeads Protein G (Thermo Fisher Scientific). After de-cross-

linking for 4 hr at 65�C, samples were treated with RNase A (Sigma) for 30 min at 37�C, followed by treatment with Proteinase K

(Merck) for 1 hr at 55�C. Eluted DNA from ‘input’ and the immunoprecipitate were purified using QIAquick PCR Purification Kit (QIA-

GEN) according to the manufacturer’s protocol and analyzed by qPCR. Amounts of the products from the precipitated DNA were

presented as percentages of those from ‘input’ DNA. The primers were used for ChIP-qPCR are listed in Table S2. To analyze pub-

lished ChIP-sequencing data, available ChIP-seq Fastq files were obtained from GEO (https://www.ncbi.nlm.nih.gov/geo/) with

accession number GSE72017 (H3K4me3, H3K4me1) (Braz~ao et al., 2016), GSE82144 (H3K27me3, NB) (Vian et al., 2018),

GSE50912 (H3K27me3, GC B) (Caganova et al., 2013), GSE62296 (H3K27Ac) (Meng et al., 2014), and GSE106701 (STAT6) (Czim-

merer et al., 2018). Data were analyzed using the Galaxy platform (https://main.g2.bx.psu.edu/) and mapped onto the mm10 murine

genome using Bowtie2 aligner software (Version 2.3.4) as described previously (Yakushiji-Kaminatsui et al., 2018). Aligned read files

were visualized by obtaining snapshot tracks using the University of California Santa Cruz (UCSC) genome browser.

QUANTIFICATION AND STATISTICAL ANALYSIS

All statistical analyses were performed using GraphPad Prism 8 software. Comparisons between two groups were performed by a

two-tailed unpaired Student t test, except for the quantification of western blot analysis (Figure S7D), in which a two-tailed paired

Student t test was used. Comparisons between multiple groups were performed by one-way ANOVA with Tukey’s multiple compar-

ison or two-way ANOVA with Sidak’s test. P values less than or equal to 0.05 were considered statistically significant. Details

regarding statistical analyses of experiments can be found in the respective figure legends.


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Cell Reports, Volume 33

Supplemental Information

Metabolic Reprogramming Induces

Germinal Center B Cell Differentiation

through Bcl6 Locus Remodeling

Kei Haniuda, Saori Fukao, and Daisuke Kitamura

Figure S1. IL-4 accelerates Bcl6 expression and GC B cell development, Related to Figure 1

(A) Quantification of changes in the number of IgG1+ cells (top) or the frequency of Fixable viability dye (FVD) positive

dead cells among total cells (bottom) after stimulation with the indicated cytokines or Abs during the plain culture of iGB

cells for 1 d as in Figure 1B. Results are presented as relative to the cells cultured with medium alone. (B) Gating strategy for

flow cytometric analysis of fixed iGB cells after the plain culture for 1 d with medium alone. FVD–, singlet cells in a

lymphocyte gate, as defined by forward and side scatters (FSC, SSC), were gated for IgG1+ or IgE+. (C) Enrichment of IgG1+

iGB cells by removing 40LB cells and IgM+ and IgE+ cells from the iGB cultures on day 3 using anti-H2Kd, anti-IgM, and

anti-IgE Abs (left), verified by flow cytometry (right). (D) Flow cytometric analysis of spleen cells from C57BL/6 (B6) mice

that had been immunized with 50 µg of NP-CGG in alum 7 days previously and administrated with PBS alone (–) or IL-4

complex (IL-4c) daily during day 4 to 6. Experimental procedure (left), the frequency of GC B cells (GL7+CD38lo) among

NP-specific B cells (NP+B220+CD138–) (middle) and the number of the NP-specific GC B cells per spleen (right). (E) Schema

of glycolysis and mitochondrial oxidative metabolism. PDH, pyruvate dehydrogenase; ETC, electron transport chain; I-V,

complex I-V. Data are mean±s.d. of two to four biological replicates (A). Each symbol represents an individual mouse and

horizontal lines indicate mean ±s.d. of six biological replicates (D). Data are pooled from two to four independent

experiments (A), or representative of at least three (B and C) or two (D) independent experiments. P values were calculated

by two-tailed unpaired Student’s t-test (D).

A B

C

Glucose

Pyruvate Lactate

PDH

Acetyl-CoA

TCA cycleNADHFADH2

ATP

ETCOligomycinV

IVIIIIII

Glycolysis

E

0 103 104 105

0

103

104

105

87

IgG1

IgE

40LB + IL-4, 3 d – 40LB– IgM+

– IgE+

IgG1+ cellenrichment

DC

ells

per

spl

een

(x 1

05 )

–IL-

4c

0 103 104 105

0

103

104

105

GL7

CD

38

– IL-4c

24 55

P = 0.0004

B6

NP-CGGalum

0day: 4 5 6 7

–IL-4c

0

2

4

6

8

10

Rel

ativ

e to

med

ium

alo

ne

anti-I

gG

anti-C

D40SCFGMCSF

TGFβIFNγ

IFNα

IL-33

IL-28

A

IL-23

IL-27

IL-21

IL-17

F

IL-17

A

IL-15

IL-13

IL-12

IL-10IL-9

IL-7

IL-6

IL-5

IL-4

IL-3

IL-2

IL-1β

IL-1α

Number of IgG1+

0

1

2

3

0

1

2

3FVD+ dead cell

0 100K 200K

0

103

104

105

FSC-A

FVD

74 99

0 100K 200KFSC-A

SSC

-A

0

100K

200K

SSC

-W

990 100K 200K

FSC-H

0

100K

200K

0 103 104 105

0

103

104

105

IgG1

IgE

50

16

990 100K 200K

SSC-H

SSC

-W

0

100K

200K

Figure S2. Gating strategies for flow cytometry, analyses of PDH in sorted B cell subsets, and effect of oligomycin on

Tfh cell development, Related to Figure 2

(A) Gating strategy for flow cytometric analysis of spleen cells from B6 mice (CD45.2+) that had been transferred with B

cells of CD45.1+ B1-8hi mice and immunized with NP-CGG in alum on the following day. Within FVD- and TER-119-negative

singlet cells in a lymphocyte gate, defined are pre-GC B cells (CD45.1+B220+CD138–NP+GL7+CD38hi, on day 3.5 after

immunization), GC B cells (CD45.1+B220+CD138–NP+GL7+CD38lo, on day 7), and plasma cells (PC: CD45.1+B220loCD138+,

on day 7) in the immunized mice, and naive B cells (NB: B220+IgD+) in unimmunized B6 mice. (B) Sorting strategy for GC

0 103 104 105

CD138

0

103

104

105

B220

12

86

48

50

A

0 100K 200KFSC-A

SSC

-A

0

100K

200K

0 100K 200KFSC-H

FSC

-W0

100K

200K

88

0 100K 200KSSC-H

SSC

-W

0

100K

200K

97

83

0 103 104 105

B220

0

103

104

105

IgD

47

920 100K 200K

FSC-A

0

103

104

105

FVD

TER

-119

0.13

2.6

0 103 104 105

CD45.1

0

103

104

105

CD

138

51

830 103 104 105

GL7

0

103

104

105

CD

38

82

90

0 103 104 105

0

103

104

105

NP-

bind

ing

B220

NB

pre-GC BDay 3.5

Day 7

Unimmunized

GC B

PC

CNB GC B PC

PDH activity

D

-37

PDH-E1α

p-PDH-E1α

NB GC B

-37

B

9850

0 103 104 105

CD38

0

103

104

105

B220

NB

Post-flow cytometry sorting

B6

SRBC i.v.

0 8 Spleenday:GL7+ cellsCD138+ cellsmagnetic sorting

Flow cytometrysorting

0 103 104 105

CD138

0

103

104

105

B220

50

20

100

100

0 103 104 105

CD138

0

103

104

105

B220

570 103 104 105

GL7

0

103

104

105

CD

38

GC B

0 103 104 105

GL7

0

103

104

105

CD

38

PC

Post-magnetic sorting



B6Unimmunized

–

Oligomyci

n0

50

100

150 P = 0.20

Bcl6

+ (%)

0 103 104 105

Bcl6

0Even

ts(%

of m

ax)

100

80

60

40

20

PCGC BGC B

–Oligomycin

E

F

0 103 104 105

0

103

104

105

CXCR5

PD-1 4.6 4.3

Oligomycin–

Non-TfhTfhTfh

–Oligomycin

0 103 104 105

Bcl6

0Even

ts(%

of m

ax)

100

80

60

40

20

GBc

l6 M

FI in

Tfh

(x 1

03 )

–

Oligomyci

n0.0

0.5

1.0

1.5 P = 0.32

0

5

10

15

20

Cel

ls p

er s

plee

n (x

105 )

P = 0.77

–

Oligomyci

n

Unimmun

ized

B, PC and NB cells. From spleen cells of B6 mice immunized with SRBC 8 d previously, both GL7+ cells and CD138+ cells

were enriched by magnetic sorting, and then GC B cells (B220+GL7+CD38lo) and PC (B220+GL7+CD38lo) were further sorted

by flow cytometry (left). NB cells (B220+CD38+) were sorted from unimmunized B6 mice (right). (C) Representative images

of a dipstick assay measuring enzymatic activity of PDH in mitochondrial fractions of indicated B cells sorted as in (B).

Quantified data are shown in Figure 2D. (D) Immunoblot analysis with the antibodies specific for phosphorylated (p-) or total

PDH-E1a subunit of the sorted NB and GC B cells as in (B). (E) Gating for Bcl6+ cells on GC B cells defined as in (A) for

Figure 2H (left), and the frequency of Bcl6+ cells among GC B cells (right). (F and G) Flow cytometric analysis of Tfh cells

in the spleen from B6 mice immunized with NP-CGG in alum 8 d previously and administered 0.5 mg/kg oligomycin or

vehicle alone (–) i.p. 1 d prior to analysis. The frequency of Tfh cells (CXCR5hiPD-1hi) among CD4+ cells (F, left), the number

of Tfh cells per spleen (F, right), Bcl6-staining in Tfh and Non-Tfh cells (CD4+CXCR5–PD-1–) (G, left), and MFI of Bcl6-

staining (G, right) are shown. Data are mean±s.d. of seven (E) or six (F and G) biological replicates and each symbol

represents an individual mouse (E-G). Data are representative of at least three (A-C) or two (D and E) independent experiments

or from an experiment (F and G). P values were calculated by two-tailed unpaired Student’s t-test (E and G) or one-way

ANOVA with Tukey’s test (F).

Figure S3. IL-4 induces metabolic reprograming in iGB cells, Related to Figure 3

(A) Quantification of Blimp1 and Bcl6 mRNAs by qRT-PCR in purified IgG1+ iGB cells stimulated with either IL-4 or anti-

IgG for 6 hr, or left untreated (–) for 1 hr, as in Figure 3A. (B) Heatmap representing metabolite content profiling for IgG1+

iGB cells prepared as in Figure 3A. Metabolite profile of each sample of the cells is depicted as a row (n = 3 biologically

independent samples per group). Columns show normalized levels of each metabolite concentration (z-score). Clustering of

the treatments is described by the dendrogram on the right. Clustering of metabolites is described by the dendrogram on the

top. (C) Amount of aKG in purified IgG1+ iGB cells treated with IL-4 for 3, 6, 24 hr or left unstimulated (–) for 1 hr. Data

are mean ±s.d. of three technical replicates (A) or three biological replicates (C). Each symbol represents a biologically

independent sample (C). Data are representative of two independent experiments (A) or from an experiment (B and C).

A Column z-score

-2 0 2

–

Ile

Sper

min

eH

omoc

yste

ine

NAD

PH6-

Phos

phog

luco

nic

acid

Succ

inic

aci

dM

alic

aci

dN

ADH

AMP

ADP

Beta

ine

Gln

cAM

PN

ADP+

NAD

+U

DP-

gluc

ose

S-Ad

enos

ylho

moc

yste

ine

Glu

tath

ione

(GSS

G)

Putre

scin

ePr

oAs

nH

ydro

xypr

olin

eH

MG

CoA

Sper

mid

ine

Citr

ullin

eC

arno

sine

Aden

ine

Ala

Phos

phoe

nolp

yruv

ic a

cid

Ser

Orn

ithin

e2,

3-D

ipho

spho

glyc

eric

aci

dAd

enyl

osuc

cini

c ac

idTh

rAr

gini

nosu

ccin

ic a

cid

Cre

atin

ine

Gly

cera

ldeh

yde

3-ph

osph

ate

2-Ph

osph

ogly

ceric

aci

d3-

Phos

phog

lyce

ric a

cid

Fum

aric

aci

dR

ibos

e 1-

phos

phat

eG

uano

sine

Phos

phoc

reat

ine

Gal

acto

se 1

-pho

spha

teN

-Ace

tylg

luta

mic

aci

dC

reat

ine

α-K

etog

luta

ric a

cid

Car

bam

oylp

hosp

hate

Citr

ic a

cid

cis-

Acon

itic

acid

ATP

Isoc

itric

aci

dG

lyAD

P-rib

ose

Glu

cose

6-p

hosp

hate

Fruc

tose

6-p

hosp

hate

Asp

Glu

tath

ione

(GSH

)2-

Hyd

roxy

glut

aric

aci

dC

arni

tine

Glu

Rib

ulos

e 5-

phos

phat

eXM

PIM

PH

ypox

anth

ine

Inos

ine

Rib

ose

5-ph

osph

ate

Dih

ydro

xyac

eton

e ph

osph

ate

Acet

yl C

oAFo

lic a

cid

N-C

arba

moy

lasp

artic

aci

dG

TPXa

nthi

neU

ric a

cid

Gly

cero

l 3-p

hosp

hate

γ-Am

inob

utyr

ic a

cid

Cys

tath

ioni

neS-

Aden

osyl

met

hion

ine

Trp

GD

PLy

sPy

ruvi

c ac

idβ-

Ala

Gua

nine

Fruc

tose

1-p

hosp

hate

PRPP

Fruc

tose

1,6

-dip

hosp

hate

Lact

ic a

cid

Val

Leu

GM

PH

isM

etPh

eTy

rAr

gAd

enos

ine

CoA

cGM

PG

luco

se 1

-pho

spha

teSa

rcos

ine

Cys

IL-4

anti-IgGmR

NA

expr

essi

on(re

lativ

e)

–

6 hr IL

-4

6 hr a

nti-Ig

G

Blimp1Bcl6

0

1

2

B

0

1

2

3

4

5αKG

Rel

ativ

e am

ount

1 3 6 24 hr

–IL-4

C

Figure S4. Histone modification and STAT6 binding at the Bcl6 and Irf4 locus, Related to Figure 4

(A) Genome browser tracks of ChIP-seq analysis showing histone modifications and STAT6-binding over the Bcl6 gene locus.

Data were obtained from GEO public database with accession number GSE72017 (H3K4me3, H3K4me1), GSE82144

(H3K27me3, NB), GSE50912 (H3K27me3, GC B), GSE62296 (H3K27Ac), GSE106701 (STAT6). The positions of primers

for ChIP-qPCR analysis used in this study are shown as red lines, and the numbers in red indicate distance (kb) from

the transcription start site (+0). Act.B, activated B cells by stimulation with anti-CD40 and IL-4 for 2.5 d; Mf, bone marrow

derived macrophage stimulated with IL-4 for 1 hr. (B) ChIP-qPCR analysis with control rabbit IgG at the Bcl6 locus of purified

IgG1+ iGB cells after the plain culture with IL-4 or anti-IgG for 6 hr. Data were normalized to the input DNA. Numbers on

the x-axis indicate the distance (kb) from the transcription start site (+0). (C) Genome browser tracks of ChIP-seq analysis of

the Irf4 locus presented as in (A). Data were obtained as in (A). (D) ChIP-qPCR analysis at the Irf4 locus performed as in (B).

(E) ChIP-qPCR analysis for H3K27me3 at the Bcl6 locus of purified IgG1+ iGB cells treated for 6 hr with IL-4 in the absence

(–) or presence of oligomycin (1 µM). (F) qRT-PCR analysis for Bcl6 mRNA in purified iGB cells treated with IL-4 for 1 d

in the absence (–) or presence of oligomycin (1 µM) or DMaKG (5 mM). Data are mean ±s.d. of three technical replicates

(B, D-F) and representative of at least three (B and D) or two (E and F) independent experiments.

Figure S5. Retroviral transduction of iGB cells and knockdown of UTX, Related to Figure 5

(A) Strategy for retrovirus (Rv) transduction of iGB cells. Day 2 iGB cells were infected with Rv, further cultured for 2 d,

then isolated, and cultured in medium alone for 1 d. A representative flow cytometry data of the cells transduced with pMXs-

IRES-GFP empty vector (Ev) is shown on the right, with numbers indicating the frequency of GFP+ cells among live singlet

iGB cells on day 5. (B) Analysis for Kdm6a knockdown efficiency. iGB cells were transduced as in (A) with Rv (pSIREN-

GFP) containing an shRNA for either luciferase (shControl) or Kdm6a (shUTX). At day 4 of culture, GFP+ iGB cells were

sorted by flow cytometry for the RT-qPCR analysis. (C and D) iGB cells derived from CD45.1 B1-8hi were transduced with

Rv expressing GFP and shControl or shUTX as in (A), purified at day 4 and treated with IL-4 for 1 d under low glucose (Lo,

0.1 mM) conditions with or without 5 mM DMaKG, and then transferred into recipient mice that had been immunized i.p.

with NP-CGG in alum 4 d previously. Spleen cells from the mice were analyzed by flow cytometry on day 8 after

immunization. Experimental protocol (C). Shown are representative plots with numbers indicating the frequency of

CD45.1+GFP+ cells among live lymphocytes (D, left), and the number of the donor GFP+ GC B cells

(CD45.1+GFP+CD19+CD138–NP+GL7+CD38lo) per spleen (D, right). Data are mean ±s.d. of three technical replicates (B)

or five biological replicates (D). Each symbol represents an individual mouse (D). Data are representative of at least four (A)

or two (B and D) independent experiments. P values were calculated by two-way ANOVA with Sidak’s test (D).

A B

0.0

0.4

0.8

1.2

mR

NA

expr

essi

on(re

lativ

e)

shCon

trol

shUTX

Kdm6a

B6

40LB + IL-4

– 40LBRv

2 40day: 5Medium

0 103 104 105

GFP

FSC

-A

0

100K

200K

pMXs-IG (Ev)

78

C

B6

NP-CGG in alum

4 80day:

Low Glc± DMαKG

CD45.1 B1-8hi

IL-440LB + IL-4

– 40LBRv

2 40day: 5

i.v.

D

0 103 104 105

0

103

104

105

GFP

CD

45.1 0.21 1.5 0.16 0.30

Glc:DMαKG:

Lo–

Lo+

shControl shUTXLo–

Lo+

0

1

2

Lo+

Lo–

Glc:DMαKG:

shControl shUTX

Lo+

Lo–

P = 0.20P < 0.0001P < 0.0001

Cel

ls p

er s

plee

n (x

106 )

Figure S6. Knockdown of STAT and retroviral transduction of in vivo-activated primary B cells, Related to Figure 6

(A) Flow cytometric analysis of iGB cells after the plain culture in medium in the absence (–) or presence of 5 mM DMaKG

for 1 d. Numbers indicate frequencies of Bcl6+ cells and CD138+ PCs among IgG1+ gated cells. (B) Analysis for Stat

knockdown efficiency. B6 iGB cells were transduced as in Figure S5A with Rv (pSIREN-GFP) containing an shControl or an

shRNA for each Stat. At day 4 of the culture, GFP+ iGB cells were sorted by flow cytometry, and then analyzed by RT-qPCR

for expression of each indicated Stat mRNA. (C) Experimental procedure of Rv transduction for in vivo analysis. CD45.1 B1-

8hi B cells primed by NP-Ficoll in vivo were cultured with anti-CD40 Ab, transduced with Rv, and then transferred into B6

mice, which were then immunized with NP-CGG in alum. At day 7 after immunization, splenocytes from these mice were

analyzed by flow cytometry. To estimate transduction efficiency, the Rv-infected B cells were further cultured for 1 d in

medium alone and analyzed by flow cytometry for the frequency of GFP+ cells among NP-binding B cells (a representative

data is shown). Data are mean ±s.d. of three technical replicates (B) and representative of at least three (A), two (B) or four

(C) independent experiments.

A

C

Stat3 Stat5a Stat6Stat5b

mR

NA

expr

essi

on(re

lativ

e)

shCon

trol

shSTAT3

0.0

0.4

0.8

1.2

0.0

0.4

0.8

1.2

0.0

0.4

0.8

1.2

0.0

0.4

0.8

1.2

shCon

trol

shSTAT5

shCon

trol

shSTAT5

shCon

trol

shSTAT6

anti-CD40

Rv infection18 hr

6 hr

NP-Ficoll 3 hr

B6

NP-CGGalum

0 7-1day:

CD45.1 B1-8hi

48

0 100K 200KFSC-A

0

103

104

105

NP-

bind

ing

0 103 104 105

GFP

49

0

103

104

105

NP-

bind

ing

pMXs-IG (mock)1 d

Medium

i.v.

B

0 103 104 105

0

103

104

105

CD138Bc

l6

– DMαKG33

3.1

29

4.0

Figure S7. Analyses of expression and function of DLST, Related to Figure 7

(A) Analysis of Idh2 knockdown efficiency. B6 iGB cells were transduced as in Figure S5A with Rv (pSIREN-GFP)

containing an shControl or an shIDH2. At day 4 of the culture, GFP+ iGB cells were sorted by flow cytometry, and then

analyzed by RT-qPCR. (B and C) qRT-PCR analysis for the expression of aKGDH subunits, in NB or GC B cells sorted as in

Figure S2B (B), or in purified IgG1+ iGB cells after the plain culture with either IL-4 or anti-IgG for 6 hr (C). (D)

Quantification of the relative expression of DLST protein in NB and GC B cells analyzed by immunoblotting as in Figure 7G.

Densitometric data were normalized to those of tubulin served as loading controls. (E) Siah2 knockdown efficiency analyzed

by RT-qPCR as in (A). (F) Flow cytometric analysis of spleen cells from mice day 3.5 post-immunization that had received

B cells transduced with Rv expressing GFP and shControl or shSIAH2. Shown are representative plots with numbers

indicating the frequency of GFP+ cells among donor pre-GC B cells (CD45.1+B220+CD138–NP+GL7+CD38hi) (left), and the

number of the donor GFP+ pre-GC B cells per spleen (right). (G) Flow cytometric analysis of iGB cells transduced as in

Figure S5A with empty Rv (pMXs-IRES-GFP; Ev) or Rv expressing DLST, and cultured with IL-4 for the last 1 d. Shown is

a representative flow cytometry plots with numbers indicating frequencies of Bcl6+ cells or CD138+ PCs among GFP+IgG1+

cells. (H) Flow cytometric analysis on day 7 after immunization with NP-CGG in alum of mice that had been transferred with

B1-8hi B cells of post-transduction (as in Figure S6C) with Ev or Rv expressing DLST. Frequency of gene-transduced (GFP+)

cells among the donor GC B cells (CD45.1+B220+CD138–NP+GL7+CD38lo) (left) and the number of the GFP+ donor GC B

cells per spleen (right). Data are mean ±s.d. of three (A, D and E) six (F) or five (H) biological replicates or three technical

replicates (B and C). Each symbol represents a biological sample of triplicate transductions (A and E), a biological sample

from n = 1 mice (NB in D) or pooled from 10 mice (GC B in D), or an individual mouse (F and H). Data are representative

of two (A-C, E and G) independent experiments, or are pooled from three independent experiments (D), or from an experiment

(F and H). P values were calculated by two-tailed unpaired (A, E, F and H) or paired (D) Student’s t-test.

A EBm

RN

A ex

pres

sion

(rela

tive)

shCon

trol

shIDH2

0.0

0.4

0.8

1.2Idh2

shCon

trol

shSIAH2

0.0

0.4

0.8

1.2

mR

NA

expr

essi

on(re

lativ

e)

Siah2

mR

NA

expr

essi

on(re

lativ

e)

Ogdh Dlst Dld0.0

0.5

1.0

1.5

2.0 NBGC B

IL-4anti-IgG

Ogdh Dlst Dld0.0

0.5

1.0

1.5

mR

NA

expr

essi

on(re

lativ

e)

C D

NBGC B

0.0

0.4

0.8

1.2

Prot

ein

expr

essi

on(re

lativ

e)

DLST

H

Cel

ls p

er s

plee

n (x

105 )

G

0 103 104 105

0

103

104

105

CD138

Bcl6

Ev DLST

32

115.5

66

0 103 104 105

0

103

104

105

GFP

CD

45.1

Ev DLST

29

EvDLS

T

P = 0.0061

P = 0.0030 P < 0.0001P = 0.0002

0

2

4

6

8F

0

1

2

3

Cel

ls p

er s

plee

n (x

105 )

shCon

trol

shSIAH2

P = 0.078

45

0 103 104 105

0

103

104

105

GFP

CD

45.1

shControl shSIAH2

39 35

Donor pre-GC B cells

Table S1. List of cytokines used in this study, Related to STAR Methods

Cytokine or Ab Manufacture

IL-1a 10 ng/mL PeproTechIL-1b 10 ng/mL PeproTechIL-2 10 ng/mL PeproTechIL-3 10 ng/mL PeproTechIL-4 1 ng/mL PeproTechIL-5 10 ng/mL PeproTechIL-6 10 ng/mL PeproTechIL-7 10 ng/mL PeproTechIL-9 10 ng/mL PeproTechIL-10 10 ng/mL PeproTechIL-12 10 ng/mL BiolegendIL-13 10 ng/mL PeproTechIL-15 40 ng/mL PeproTechIL-17A 10 ng/mL PeproTechIL-17F 10 ng/mL PeproTechIL-21 10 ng/mL PeproTechIL-23 1 ng/mL BiolegendIL-27 100 ng/mL BiolegendIL-28A 10 ng/mL PeproTechIL-33 10 ng/mL PeproTechIFNa 200 ng/mL BiolegendIFNg 20 ng/mL PeproTechTGFb 2 ng/mL PeproTechGMCSF 10 ng/mL PeproTechSCF 10 ng/mL PeproTechanti-CD40 5 µg/mL BioXCellF(ab')2 anti-mouse IgG 5 µg/mL Jackson ImmunoResearch

Conc.

Table S2. List of primers used in this study, Related to STAR Methods

For RT-qPCR For ChIP-qPCR Bcl6 locus For ChIP-qPCR Irf4 locusPrimer name Sequence 5' to 3' Primer name Sequence 5' to 3' Primer name Sequence 5' to 3'Actb Fw CTAAGGCCAACCGTGAAAAG –359 Fw ACCCCGGGGCTTACTGTTAT –60 Fw ACCTGGTACGGTGGCTATCT

Actb Rv ACCAGAGGCATACAGGGACA –359 Rv CAGGCGGGTCAGAGACAATA –60 Rv TGCTACGAAGGCTGGTCTTG

Bcl6 Fw CCGGCACGCTAGTGATGTT –352 Fw CTCGCCCTCGTGTATCCTCT –35 Fw TGGGGCGTCTATGAGTCCAT

Bcl6 Rv TGTCTTATGGGCTCTAAACTGCT –352 Rv TGGTGGACCTAGGCCATTCT –35 Rv ATGGCAAGGGTGTGACTCTC

Dld Fw GGGAGCACATATTCTAGGACCA –225 Fw TTTAAATGCTGCCCACGGTC –12 Fw GGATGAGGCCCCTGGAATTT

Dld Rv TCACAGGAAGCACCATATTCC –225 Rv ACTTGGGCCCCATTGTTTCA –12 Rv TCCAAAGCACGCTGTCAGAT

Dlst Fw AGCCTCCTTCTAGCAAACCA –217 Fw CTCATTTGGCACGCTCCCTA –1.4 Fw GCAGCAAGGCTGTGCTATCT

Dlst Rv ACGCAGACCTTTAGCAGCTC –217 Rv CCTACCATGCCATCAGCACT –1.4 Rv AACACCTTCTGTCTGTCGGG

Gapdh Fw TGAAGCAGGCATCTGAGGG –213 Fw CAGCAGTGATCCGTGAAGGT –0.5 Fw TCGTCGGTTTCATTCACCCA

Gapdh Rv CGAAGGTGGAAGAGTGGGAG –213 Rv TCCCAGGTCCCCATAATGCT –0.5 Rv GGCAAAGCGGAGTCTTGTCT

Hprt Fw TCCTCCTCAGACCGCTTTT –176 Fw TGGGCTGATCACAGACAACC 0 Fw CTAGGACCTGTGCACTTCGG

Hprt Rv CCTGGTTCATCATCGCTAATC –176 Rv ACCACTGTTCCAAGGTCGTG 0 Rv CAGTCCCATTAGCTCGTCCC

Idh2 Fw GGATGTACAACACCGACGAGT –163 Fw GCTCGGTGAGAGTGACTGAC +1.1 Fw GACTTCGGAGACTCTGGCAC

Idh2 Rv CGGCCATTTCTTCTGGATAG –163 Rv ATGAATCTGTCCGCAGCGTT +1.1 Rv CCCTGCAACTACCTTCGCAT

Irf4 Fw CTACCCCATGACAGCACCTT –146 Fw CCTTCGCCCCACCGTATAAA

Irf4 Rv CCAAACGTCACAGGACATTG –146 Rv GGGCTGTGAATGCCTGCTAT

Kdm6a Fw CGGGTTCGTGAGGTTTCAT –10 Fw CAGTCTAGGTCATTGGCGCT

Kdm6a Rv GAGATTCGTAGCAGCGAACA –10 Rv GCGGCATGACCTCTGTCTTTA

Ogdh Fw TCTCATCCACAGACAAACTTGG –5 Fw ACTTTTCCATTCACATCTCCACAG

Ogdh Rv AGGAAGTGCTGGCTCCTGT –5 Rv TGAAAAAGTTTCTGCGGGCG

Prdm1 Fw GAACCTGCTTTTCAAGTATGCTG –1.8 Fw AAGTCCTTCAAGTGGCTCGT

Prdm1 Rv AGTGTAGACTTCACCGATGAGG –1.8 Rv AAGCCCACGTTTAGGGTTGT

Siah2 Fw ATGCCGCCAGAAGTTAAGC 0 Fw CTGGTGTCCGGCCTTTCCTA

Siah2 Rv CAGCCCGTGGTAGCATACTTA 0 Rv CCGCAGCTCAAATTCCGAGA

Stat3 Fw GTTCCTGGCACCTTGGATT +0.9 Fw ACTGCCTCGACTCCAACCAA

Stat3 Rv CAACGTGGCATGTGACTCTT +0.9 Rv GTTTTGGGAAGGCTTCGCTT

Stat5a Fw GAGCTGGTGTTCCAGGTGA +1.2 Fw AAACACAGCTTGCACCAAGG

Stat5a Rv GGTGGCAGTAGCATTGTGG +1.2 Rv GGCCGCGGTGTTTGTATTTT

Stat5b Fw GAAACGAGCTGGTCTTTCAAGT +4 Fw GGTGCTACTGGTCCGTATCG

Stat5b Rv CTGGCTGCCGTGAACAAT +4 Rv TCCTACACTGCGCAACAAGT

Stat6 Fw GTCCATGAGTGTACTGCCATCT +7 Fw GGAGATTTCCGCCCAACCTT

Stat6 Rv GGCATGGTTATCTGGCTCAT +7 Rv CCCAGTCTCCACGGTTTCAG

+10 Fw ATCCTGGCACTGTAGGCAAC

shRNA +10 Rv CCCTCTGGCCCTTCACTAAC

sh Name Target Sequence 5' to 3' +17 Fw TCTGCTGGAGCGTGGTTATC

shSTAT3 GGAGCAGCATCTTCAGGATGT +17 Rv CTGGCACTTACCGTCTCCAG

shSTAT5 GCAACCACCTCGAGGACTACA +24 Fw AAATAGCGACCTGACGCACA

shSTAT6 GGAAGGGAAACAGCATCTTGC +24 Rv GGGTGACCGACAGACATTCA

shUTX GCAGAATACTTCTGATAATTG +35 Fw TGCCACCTTGTGGCCATTCT

shIDH2 GCACGTTCAAGTTGGTCTTCA +35 Rv TTTTAGCAACTCTTGGCTTCCCA

shSIAH2 GGAAGCTGTGATGTCCCATCT

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