Advances in the Diagnosis and Treatment of Vasculitis

*Edited by Luis M. Amezcua-Guerra*

**ADVANCES IN**

**INTECHOPEN.COM**

**THE DIAGNOSIS AND**

Edited by **Luis M. Amezcua-Guerra**

**TREATMENT OF VASCULITIS**


*1.2. Corporate Governance in Indonesia*

In Indonesia, limited liability corporations are governed by Law No. 40 of 2007 on Limited Liability Companies (Company Law). The Company Law outlines the general responsibilities of a company's shareholders, boards of directors, boards of commissioners, employees, commercial partners, and the general public.

The Financial Services Authority (Otoritas Jasa Keuangan or OJK) additionally controls corporate governance for specific forms of organizations and companies. OJK regulations oversee corporate governance conditions for the financial sectors and public companies.

The Coordinating Ministry for Economic Affairs set up the National Committee on Governance (NGC) through the Decree of Coordinating Ministry for Economic Affairs No. KEP-49/M.EKON/11/TAHUN 2004. Subsequently, this ruling was revised by Coordinating Ministry for Economic Affairs Decree No. KEP-14/M.EKON/03/Year 2008. According to the NGC's stated mission, the Indonesian Code of Good Corporate Governance was formulated, promoted, and made easier to apply and enforce.

In 2006, the GCG Code was firstly issued. It was clearly stated that the GCG Code is not a lawful document and, intrinsically, corporations in Indonesia are not bound by it. The GCG Code is a methodology that gives corporate governance implementation guidelines for businesses [19].


**4.1. Multi-cell MISO RBF**

In this subsection, we review the recent results on the achievable sum rate of the multi-cell MISO RBF scheme under finite-SNR regime [22]. In particular, we first consider an extension of Lemma 3.1 to the multi-cell case subject to the ICI, and furthermore show the asymptotic sum-rate scaling law as the number of users per cell tends to infinity.

For the single-cell RBF case, the SINR distributions given in (17) and (18) are obtained in [20]. The following lemma establishes similar results for the multi-cell case

**Lemma 4.1.** *([22, Lemma 3.2], see also Section 4.2) In the multi-cell MISO RBF, the PDF and CDF of the SINR S* := *SINR*(*c*) *k*,*m,* ∀*k*, *m, have closed-form expressions given by*

$$f\_S^{(c)}(s) = \frac{e^{-s/\eta\_c}}{(s+1)^{M\_c-1} \prod\_{l=1, l \neq c}^{\mathbb{C}} \left(\frac{\mu\_{l,c}}{\eta\_c}s + 1\right)^{M\_l}} \left[\frac{1}{\eta\_c} + \frac{M\_c - 1}{s+1} + \sum\_{l=1, l \neq c}^{\mathbb{C}} \frac{M\_l}{s + \frac{\eta\_c}{\mu\_{l,c}}}\right],\tag{28}$$

$$F\_{\mathcal{S}}^{(c)}(s) = 1 - \frac{e^{-s/\eta\_{\mathcal{L}}}}{(s+1)^{M\_{\mathcal{L}}-1} \prod\_{l=1, l \neq c}^{\mathcal{C}} \left(\frac{\mu\_{l,\mathcal{L}}}{\eta\_{\mathcal{C}}}s + 1\right)^{M\_{l}}} \,. \tag{29}$$

10.5772/57131

39

http://dx.doi.org/10.5772/57131

numerical analytical

Random Beamforming in Multi – User MIMO Systems

  � � � � � � � *x*=−1

  � � � � � � �

*x*=−*ηc*/*µl*,*c*

, (32)

. (33)

5 10 15 20 25 30 35 40

Number of users

∏*C l*�=*c* � *x* + *η µl* �*nMl*

1

*t*�=*l*,*c* � *x* + *η µt* �*nMt*

1

*dn*(*Mc*−1)−*p*+1 *dxn*(*Mc*−1)−*p*+1

(*x* + 1)*n*(*Mc*−1)+1 ∏*C*

If the original feedback scheme in [20] is employed, (30) becomes a close approximation of the *c*-th sum rate. Note that no other results than Theorem 4.1 are available in the literature

Fig. 1 shows the analytical and numerical results on the RBF sum rate as a function of the number of users for both single-cell and two-cell systems. In the single-cell case, *M* = *NT* = 3, *η* = 20 dB, while in the two-cell case, *K*1 = *K*2, *M*1 = *M*2 = *NT* = 3, *η*1 = *η*2 = 20 dB, *µ*2,1 = 6 dB, and *µ*1,2 = 10 dB. It is observed that the sum-rate expressions in (19) and (30) are very accurate. Thus, it is possible to use Theorem 4.1 to compute all the sum-rate tradeoffs among different cells in a multi-cell RBF system, which leads to the achievable rate region. However, such a characterization requires intensive computations, and does not provide any

An attempt to extend the famous scaling law *M* log2 log *K* to the multi-cell RBF case has been made in [53] based on an approximation of the SINR's PDF (which is applicable if

4

*and thus given by [52, (2.102)]:*

*An*,*c*,*p* = 1

(*nMl* − *q*)!

for the multi-cell RBF sum rate.

*4.1.2. Asymptotic sum rate as Kc* → ∞

*An*,*l*,*q* = 1

useful insights.

6

8

single−cell

**Figure 1.** Comparison of the analytical and numerical results on the RBF sum rate.

(*n*(*Mc* − 1) − *p* + 1)!

*dnMl*−*q dxnMl*−*q*

two−cell

10

Sum Rate (bps/Hz)

12

14

16

#### *4.1.1. Sum rate with finite K*

With Lemma 4.1, Lemma 3.1 is readily generalized to the multi-cell case in the following theorem.

**Theorem 4.1.** *([22, Theorem 3.1]) The total sum rate of a C-cell MISO RBF system equals to* ∑*C c*=1 *R*(*c*) *RBF, in which the individual sum rate of the c-th cell, R*(*c*) *RBF, is given by*

$$\begin{split} R\_{\mathrm{RBF}}^{(c)} &= \frac{M\_{\mathrm{L}}}{\log 2} \sum\_{n=1}^{K\_{\mathrm{c}}} (-1)^{n} \binom{\mathrm{K}\_{\mathrm{c}}}{n} \prod\_{l=1, l \neq c}^{\mathrm{C}} \left( \frac{\eta\_{\mathrm{c}}}{\mu\_{l,c}} \right)^{n M\_{\mathrm{l}}} \times \\ & \left\{ \sum\_{p=1}^{n(M\_{\mathrm{L}}-1)+1} \frac{A\_{\mathrm{R},c,p}}{(p-1)!} \left[ e^{\frac{\mu}{\eta\_{\mathrm{c}}}} \left( -\frac{n}{\eta\_{\mathrm{c}}} \right)^{p-1} Ei \left( -\frac{n}{\eta\_{\mathrm{c}}} \right) - \sum\_{m=1}^{p-1} \left( -\frac{n}{\eta\_{\mathrm{c}}} \right)^{m-1} (p-1-m)! \right] \right. \\ & \left. + \sum\_{l=1, l \neq c}^{\mathrm{C}} \sum\_{q=1}^{nM\_{l}} \frac{A\_{\mathrm{u},l,q}}{(q-1)!} \left[ e^{\frac{\mu}{\eta\_{\mathrm{c}}}} \left( -\frac{n}{\eta\_{\mathrm{c}}} \right)^{q-1} Ei \left( -\frac{n}{\mu\_{l,c}} \right) \right. \\ & \left. - \sum\_{m=1}^{q-1} \left( -\frac{n}{\eta\_{\mathrm{c}}} \right)^{m-1} \left( \frac{\mu\_{l,c}}{\eta\_{\mathrm{c}}} \right)^{q-m} (q-1-m)! \right] \right\}, \quad (30) \end{split}$$

*where An*,*c*,*p's and An*,*l*,*q's are the coefficients from the following partial fractional decomposition:*

$$\frac{1}{n(\mathbf{x}+1)^{n(M\_{\ell}-1)+1} \prod\_{l \neq \pm \mathcal{L}}^{\mathbb{C}} \left(\mathbf{x} + \frac{\eta\_{\mathcal{L}}}{\mu\_{l,\mathcal{L}}}\right)^{nM\_{l}}} = \sum\_{p=1}^{n(M\_{\ell}-1)+1} \frac{A\_{\mathrm{n},\mathcal{L},p}}{(\mathbf{x}+1)^{p}} + \sum\_{l=1, l \neq \pm \mathcal{L}}^{\mathbb{C}} \sum\_{q=1}^{nM\_{l}} \frac{A\_{\mathrm{n},l,q}}{\left(\mathbf{x} + \frac{\eta\_{\mathcal{L}}}{\mu\_{l,\mathcal{L}}}\right)^{q}},\tag{31}$$

**Figure 1.** Comparison of the analytical and numerical results on the RBF sum rate.

*and thus given by [52, (2.102)]:*

12 Recent Trends in Multiuser MIMO Communications

*S* (*s*) = *e*−*s*/*ηc*

*F*(*c*)

*Mc*−1

*C* ∏ *l*=1,*l*�=*c*

*RBF, in which the individual sum rate of the c-th cell, R*(*c*)

 *C* ∏ *l*=1,*l*�=*c*  *ηc µl*,*c*

> *p*−1 *Ei* − *n ηc* − *p*−1 ∑ *m*=1

*q*−1 *Ei* − *n µl*,*c*

> − *n ηc*

*n*(*Mc*−1)+1 ∑ *p*=1

*where An*,*c*,*p's and An*,*l*,*q's are the coefficients from the following partial fractional decomposition:*

− *q*−1 ∑ *m*=1

=

 *µl*,*c ηc s* + 1 *Ml*

*S* (*s*) = 1 − *e*−*s*/*ηc* (*s* + 1)

*Mc*−1

With Lemma 4.1, Lemma 3.1 is readily generalized to the multi-cell case in the following

**Theorem 4.1.** *([22, Theorem 3.1]) The total sum rate of a C-cell MISO RBF system equals to*

*nMl* ×

(*s* + 1)

*of the SINR S* := *SINR*(*c*)

*4.1.1. Sum rate with finite K*

theorem.

*R*(*c*)

*RBF* = *Mc* log 2

+

*n*(*Mc*−1)+1 ∑ *p*=1

> *C* ∑ *l*=1,*l*�=*c*

(*x* + 1)*n*(*Mc*−1)+1 ∏*C*

*Kc* ∑ *n*=1

> *nMl* ∑ *q*=1

> > 1

*l*�=*c x* + *ηc µl*,*c nMl*

(−1)*n*

*An*,*c*,*p* (*p* − 1)!

> *An*,*l*,*q* (*q* − 1)!

*Kc n*

> *e n ηc* − *n ηc*

 *e n µl*,*c* − *n ηc*

∑*C c*=1 *R*(*c*)

*f* (*c*)

**Lemma 4.1.** *([22, Lemma 3.2], see also Section 4.2) In the multi-cell MISO RBF, the PDF and CDF*

 1 *ηc* +

*C* ∏ *l*=1,*l*�=*c*  *µl*,*c ηc s* + 1 *Ml*

*Mc* − 1 *s* + 1 +

*RBF, is given by*

 − *n ηc*

*m*−1 *µl*,*c*

*An*,*c*,*p* (*x* + 1)*p* +

*ηc*

*q*−*m*

*C* ∑ *l*=1,*l*�=*c* *nMl* ∑ *q*=1

 *x* + *ηc µl*,*c*

*An*,*l*,*q*

*m*−1

(*p* − 1 − *m*)!

(*q* − 1 − *m*)!

, (30)

*q* , (31)

*C* ∑ *l*=1,*l*�=*c*

*Ml s* + *ηc µl*,*c*

. (29)

, (28)

*k*,*m,* ∀*k*, *m, have closed-form expressions given by*

$$A\_{n,\mathcal{L},p} = \frac{1}{(n(M\_{\mathcal{L}}-1)-p+1)!} \frac{d^{n(M\_{\mathcal{L}}-1)-p+1}}{dx^{n(M\_{\mathcal{L}}-1)-p+1}} \left[ \frac{1}{\prod\_{l \neq c}^{\mathbb{C}} \left(x + \frac{\eta}{\mu\_l}\right)^{nM\_l}} \right] \Big|\_{x=-1} \tag{32}$$

$$A\_{n,l,q} = \frac{1}{(nM\_l - q)!} \frac{d^{nM\_l - q}}{dx^{nM\_l - q}} \left[ \frac{1}{(x+1)^{n(M\_l - 1) + 1} \prod\_{l \neq l,c}^{C} \left( x + \frac{\eta}{\mu\_l} \right)^{nM\_l}} \right] \bigg|\_{x = -\eta\_c/\mu\_{l,c}}.\tag{33}$$

If the original feedback scheme in [20] is employed, (30) becomes a close approximation of the *c*-th sum rate. Note that no other results than Theorem 4.1 are available in the literature for the multi-cell RBF sum rate.

Fig. 1 shows the analytical and numerical results on the RBF sum rate as a function of the number of users for both single-cell and two-cell systems. In the single-cell case, *M* = *NT* = 3, *η* = 20 dB, while in the two-cell case, *K*1 = *K*2, *M*1 = *M*2 = *NT* = 3, *η*1 = *η*2 = 20 dB, *µ*2,1 = 6 dB, and *µ*1,2 = 10 dB. It is observed that the sum-rate expressions in (19) and (30) are very accurate. Thus, it is possible to use Theorem 4.1 to compute all the sum-rate tradeoffs among different cells in a multi-cell RBF system, which leads to the achievable rate region. However, such a characterization requires intensive computations, and does not provide any useful insights.


More recently, new generation trimers such as the BG505 SOSIP.664 trimers (3, 4) and various forms of the native flexibly linked (NFL) trimers (5) were designed. These soluble spikes display superior threefold symmetric order and improved antigenic profiles. The SOSIP trimers were the progenitors, containing an internal cysteine linkage between gp120 and gp41 and an isoleucine (I) to proline (P) change in gp41 (I559P) to disfavor the post-fusion conformation of HIV-1 Env (2). The NFL trimers were constructed by replacing the furin cleavage site that is naturally present between the exterior glycoprotein gp120 and the transmembrane protein gp41 with a flexible linker composed of two repeats of four glycine and one serine residues (G4S)2. This modification renders these trimers cleavage- and furin-independent, forming a covalent linkage between gp120 and the ectodomain of gp41 (5–7). Besides the I559P change, further developments of the NFL trimers included the introduction of a set of substitutions selected from the BG505 Env sequence, referred to as trimerderived (TD), which favor the production of trimers that display ordered symmetry and desired antigenic profiles and can be applied to diverse HIV-1 strains (6). Additional modifications of the NFL TD trimer design performed in the context of the Indian clade C isolate 16055 was the introduction of a cysteine bond between residues I201C and A433C to retain gp120 in the pre-CD4-bound conformation, resulting in the 16055 NFL TD CC trimers (6). A set of glycine substitutions in selected gp41 coil-to-helix transition residues were also introduced to further stabilize the pre-fusion state (8).

In addition to efforts using targeted mutagenesis of Env to improve trimer stability, glutaraldehyde (GLA) cross-linking was shown to improve the thermostability of HIV-1 Env trimers as well as the induction of neutralizing antibody responses (7, 9, 10). Depending on the specific Env construct used, negative or positive selection of the trimers may be required prior to fixation to enrich for conformers with desired antigenicity. While intramolecular protein cross-linking may provide a benefit in terms of increasing the durability of conformationally sensitive neutralizing antibody epitopes *in vivo*, less is known about whether fixation affects other aspects of the Env-specific immune response. In this study, we addressed this issue by immunizing C57BL/6 mice with either fixed or unfixed 16055 NFL TD CC trimers formulated in AbISCO-100 adjuvant. After the first boost, we observed an overall reduction in Env-specific serum-binding antibody titers in mice inoculated with fixed trimers compared to mice inoculated with unfixed trimers, which was primarily detected when coating was performed with unfixed trimers. However, this difference was modest when fixed trimers were used for coating and especially after an additional boost. We further detected a pronounced skewing toward Th2 responses with significantly altered Envspecific IgG1:IgG2b ratios in the sera of mice immunized with GLA-fixed trimers compared to mice immunized with unfixed trimers. A similar effect was detected for the IgG1:IgG2c ratios and a trend toward increased production of Th2 cytokines from stimulated CD4+ T cells was observed in mice immunized with fixed trimers. These results demonstrate that protein crosslinking influences the induced antibody responses at several levels *in vivo.*

### MATERIALS AND METHODS

### Animals, Immunizations and Reagents

Male C57BL/6 Bom mice were purchased from Taconic, Denmark. Mice were immunized subcutaneously with 10 µg of recombinant 16055 NFL TD CC trimers together with 10 µg AbISCO-100 adjuvant (Isconova/Novavax) or with adjuvant alone. The mice were 7–9 weeks of age at the start of the immunizations, and booster immunizations were performed at 4-week intervals. All mice were kept at the animal facility of the Department of Microbiology, Tumor and Cell Biology at Karolinska Institutet. All animal experiments were performed under approved conditions and standard guidelines prior to the experimental start according to the regulations of the Committee for Animal Ethics (Stockholm, Sweden).

# Expression and Purification of Soluble Env Trimers

The 16055 trimers were produced as previously described (5, 6). Briefly, the trimers were expressed in 293F cells and were isolated by lectin-affinity chromatography using GNL (*Galanthus nivalis* lectin-agarose; Vector Labs), purified by size-exclusion chromatography (SEC) using Superdex™ 200 columns (GE Healthcare Life Sciences) to isolate the predominant trimeric fractions and further purified by negative selection affinity chromatography using the non-neutralizing CD4bs-directed mAb, GE136 (11).

### Trimer Cross-linking and Gel Analysis

Cross-linking of the purified 16055 trimers was conducted as previously described (7). Briefly, 0.5 mg/ml of trimer was fixed with 5 mM GLA (ACROS Organics) at room temperature (RT) for 5 min and then the reaction was quenched by excess 50 mM glycine, pH 7.5. The fixed trimers were negatively selected by GE136 antibody affinity chromatography and re-isolated by Superdex™ 200 size-exclusion chromatography and then analyzed by SDS-PAGE under reducing and non-reducing conditions and by Blue Native PAGE as described previously (7).

### Differential Scanning Calorimetry (DSC) and Negative-Stain Electron Microscopy (EM)

The thermal melting (Tm) of the trimers was determined using a Microcal VP-Capillary DSC (Malvern). Briefly, trimers were diluted in PBS pH 7.4 to 0.25 mg/ml and scanned at a rate of 1°C/min. Data collected were analyzed after buffer correction, normalization, and baseline subtraction using the VP-Capillary DSC Automated data analysis software. For EM analysis, the 16055 NFL unfixed and fixed trimers were negatively stained on glow-discharged carbon-coated copper mesh grids (Electron Microscopy Sciences) for 2 min. Following blotting to remove excess sample, grids were transferred onto droplets of 2% phosphotungstic acid (pH 6.7) for 2 min. Following blotting and drying the grids were analyzed on a Philips CM100 electron microscope and imaged at selected magnifications with a Megaview III charge-coupled-device camera.

## ELISA for Antigenic Profiling and Detection of Serological Antibody Responses

To assess binding by selected bNAbs and non-neutralizing mAbs, the 16055 NFL CC TD trimers were captured by their His-tag using a mouse anti-His antibody coated on the ELISA plate overnight (ON), followed by washing, blocking, and detection using anti-mouse IgG as described below. To detect Env-specific antibody responses in serum, 96-well highprotein-binding MaxiSorp (Nunc) plates were pre-coated with 1 µg/ml *Galanthus nivalis* lectin (Sigma) diluted in PBS and incubated ON at 4°C. Plates were then washed six times in washing buffer (PBS/0.05% Tween-20) followed by addition of 150 μl/ well blocking buffer (2% fat-free milk in PBS) and incubated for 1 h at RT. After incubation, the blocking buffer was removed from the plates and 200 ng/well unfixed or fixed NFL Env trimers were added and let to incubate at RT for 2 h. Plates were washed six times in washing buffer and were then incubated in blocking buffer for 1 h. After removing the blocking buffer, sera were added to the plates in threefold serial dilution starting at 1:25 dilution in blocking buffer and incubated for 2 h at RT. After washing the plates six times in washing buffer, secondary antibody diluted in PBS was added to each well. For total, Env-specific IgG ELISA, the secondary antibody goat anti-mouse IgG-horse radish peroxidase (HRP) (Southern Biotech) was used in a dilution of 1:1,000. For subclass-specific Env serum antibody detection, goat anti-mouse IgG1-HRP (Southern Biotech) (1:5,000), goat anti-mouse IgG2b-HRP (Southern Biotech) (1:5,000), goat antimouse IgG2c-HRP (Southern Biotech) (1:5,000), or goat antimouse IgG3-HRP (Southern Biotech) (1:1,500) were added. Secondary antibodies were incubated at RT for 1 h and removed by washing six times in wash buffer. To develop plates, 100 μl/ well of TMB stabilized chromogen substrate (Invitrogen) was added and incubated for 10 min in dark at RT. The reaction was stopped by adding 1 M H2SO4. The optical density was measured at 450 nm using an Asys Expert 96 ELISA reader (Biochrom).

# Preparation of Single Cell Suspension

The mice were sacrificed by cervical dislocation and spleens were taken out for further analysis. Single cell suspension of splenocytes was obtained by passing the dissociated spleen through a 70-µM nylon cell strainer. Hypotonic ammonium chloride solution was used to lyse the red blood cells. Splenocytes were then collected in complete RPMI 1640 medium (containing 5% FBS, 50 µM 2-mercaptoethanol, 2 mM l-glutamine, 100 U/ml penicillin, and 100 µM streptomycin), and cell numbers were calculated using the automated cell counter Countess (Invitrogen) for further experiments.

# CD4**+** T Cell Depletion

To deplete CD4+ T cells, the protocol from EasySep negative selection kit was followed (Stemcell Technologies). Briefly, splenocytes were incubated with normal rat serum (Stemcell Technologies) and biotinylated rat anti-mouse CD4 antibody (clone: RM4-5; BD Pharmingen) for 10 min with mixing every third minute. EasySep Strepativin Rapid Sphere 50001 beads (Stemcell Technologies) were added to the cell mixture at a concentration of 75 µl/ml of cell suspension. CD4+ T cells were separated using an EasySep magnet (Stemcell Technologies) and the negative fraction was collected in a new tube and used for further experiments.

## Flow Cytometry

Total splenocytes and CD4-depleted cell fractions were stained on ice for 20 min with the following antibodies: CD3e-PE (145-2C11; eBioscience), CD8a-APC (53-6.7; BD Pharmingen), CD4-FITC (H129.19; BD Pharmingen), and B220-PerCP-Cy5.5 (RA3-6B2; BD Pharmingen). The samples were run on a FACSCalibur cytometer (BD Bioscience), and data were analyzed with FlowJo software version 10 (TreeStar).

# T Cell ELISpot Analysis

T cell ELISpot analysis was performed to measure cytokine production after stimulation of total splenocytes. 96-well Multiscreen-IP filter plates (Millipore) were pre-treated with 70% ethanol, washed three times in PBS followed by coating with 5 μg/well (50 µg/ml) of anti-mouse IFNγ (mAb: AN18), anti-mouse IL-2 (mAb: 1A12), or anti-mouse IL-4 (mAb: 11B11), all from Mabtech AB. Plates were incubated ON at 4°C. Before addition of splenocytes, the plates were washed six times with PBS/0.05% Tween-20 and blocked in complete RPMI medium for 2 h at 37°C/5% CO2 in a humidified incubator. After incubation splenocytes, in triplicates, were added to the wells in three different concentrations (200,000, 100,000, or 50,000 cells) in a final volume of 150 µl and stimulated with one of the following stimuli: ConA (2 µg/ml) (Sigma), unfixed or fixed NFL trimers (6.67 µg/ml), or left unstimulated in medium only. After 20 h stimulation at 37°C/5% CO2 in a humidified incubator, the cells were removed from the wells and the plates were washed six times with PBS/0.05% Tween-20. Then the following biotinylated secondary antibodies in a concentration of 1 µg/ml (Mabtech AB) were added to the corresponding wells: anti-mouse IFNγ (mAb: R4-6A2), anti-mouse IL-2 (mAb: 5H4), or anti-mouse IL-4 (BV06-24G2). After incubation at RT for 2 h, the plates were washed six times in PBS only and streptavidin-ALP (Mabtech AB) in a 1:1,000 dilution was added to wells and incubated at RT for 45 min. After washing with water, plates were developed with 100 μl/well of BCIP/NBT plus substrate (Mabtech AB) for 10 min at RT. To stop the reaction, wells were emptied and washed extensively in water followed by air-drying. The spots were counted in an ImmunoSpot analyzer (CTL Immunospot).

## Flow Cytometric Bead Array (CBA) to Detect Cytokines after *In Vitro* Stimulation

Total splenocytes from mice immunized three times were stimulated *in vitro* for detection of cytokine production. One million splenocytes were used for each stimulation in 48-well plates in a total volume of 500 µl. Each mouse was stimulated with either ConA (2 µg/ml) (Sigma), unfixed or fixed NFL trimers (6.67 µg/ml) or left unstimulated in medium only. The plates were incubated for 20 h at 37°C/5% CO2 in a humidified incubator. Plates were spun down, and supernatants were collected. To measure the secreted cytokine from each mouse and stimuli, the BD CBA Mouse Enhanced Sensitivity Master Buffer Kit (BD Bioscience) was used. IL-5, IL-10, and IL-13 (BD Bioscience) were measured in all samples according to manufacturer's instruction. Standards were prepared from Top Standard by threefold dilutions down to 1:729. Each sample was diluted in two different dilutions, 1:2 and 1:20. Diluted samples were mixed and incubated with Capture Beads for 2 h in dark at 4°C. The samples were then washed in FACS Flow for 5 min at 300*g*. Supernatant was flicked off before Mouse Detection Reagent was added and incubated for 2 h in dark at 4°C. After an additional washing step, the Enhanced Sensitivity Detection Reagent was added. After 1 h incubation in dark at 4°C, the samples were washed and ran on FACSVerse (BD Bioscience). Standard curves were generated for each cytokine. The samples were then calculated based on the median fluorescence values. If the value was lower than the standard curve, those samples were considered as 0. Samples higher than the detection limit (based on standard curve) was excluded.

### Statistical Analysis

GraphPad Prism software version 8 (San Diego, CA, USA) was used to analyze data by Student's *t*-test. Significance was defined as \**p* ≤ 0.05, \*\**p* ≤ 0.01, and \*\*\**p* ≤ 0.001.

### RESULTS

### *In Vitro* Characterization of Unfixed and Fixed Env Trimers

In this study, we used the well-ordered 16055 NFL TD CC Env trimers (**Figure 1A**) to investigate the effect of GLA fixation on Env-specific immune responses in C57BL/6 mice. Following the cross-linking procedure, the fixed trimers were isolated by negative selection and size-exclusion chromatography (SEC). Analysis of the purified GLA-fixed trimers by reducing SDS-PAGE confirmed that cross-linking of the trimers had occurred, by a shift in the apparent molecular weight (MW) relative to the unfixed trimers. GLA cross-linking rendered the trimers resistant to disulfide-directed reduction (**Figure 1B**, left). BN-PAGE analysis, under native conditions, revealed that both the unfixed and fixed trimers migrated with similar MWs (**Figure 1B**, right). Both sets of data indicated that the cross-linking had occurred between protomers within each trimer, but not across individual trimers. These results were consistent with what we had reported previously by these types of analyses (7). To measure the thermal stability of the unfixed and fixed 16055 NFL TD CC Env trimers, we used DSC. The GLA-fixed Env trimers displayed a higher thermostability compared to the unfixed counterpart. The thermal denaturation midpoint temperature (Tm) differed nearly 10°C between the two proteins (**Figure 1C**, left), indicating that GLA cross-linking contributes to the overall stability of the protein. The increased Tm was accompanied by a broadening of the thermal transition profile, indicating some molecular heterogeneity following the GLA cross-linking process. To confirm that the trimers remained as single particles following cross-linking and negative selection, we performed negative-stain EM and observed no marked difference in trimers at this level of resolution comparing unfixed to fixed populations (**Figure 1C**, right). To confirm trimer concentrations and that selected epitopes were minimally affected following fixation, we performed ELISA using the bNAbs VRC01, PGT121, and 2G12. We observed that PGT121 recognition was not greatly affected, indicating that the protein concentrations were accurate, whereas there was some decrease in VRC01 and 2G12 recognition following GLA fixation. We included the non-neutralizing antibodies 19b and GE136 that poorly recognized the unfixed trimers, as expected, whereas recognition of the GLA-fixed trimers by these mAbs was completely eliminated (**Figure 1D**).

# Env-Specific Binding Antibody Responses in Mice Immunized with Unfixed or GLA-Fixed Trimers

To evaluate the immunogenicity of the unfixed and GLA-fixed 16055 NFL TD CC trimers C57BL/6 mice were immunized three times at 4-week intervals. Sampling was performed 2 weeks after the second immunization and 8 days after the third immunization (**Figure 2A**). Serological responses were compared by first measuring the total Env-specific IgG binding titers after the immunizations. Following the second immunization, there was a clear difference in the total Env-specific IgG response between the two groups with higher responses detected in mice immunized with unfixed 16055 NFL TD CC Env trimers compared to those immunized with fixed trimers as shown by titration curves of the individual mice (Figure S1A in Supplementary Material) and as group means (**Figure 2B**). While this difference was detectable using both unfixed and GLA-fixed trimers as the antigenic target in the ELISA assay, it was more apparent when the unfixed protein was used for coating. After the third immunization, only a modest difference remained between the groups when the unfixed protein was used for coating the ELISA plates (**Figure 2B**), and an even smaller difference was observed when the fixed protein was used for coating (**Figure 2C**). Control mice injected with adjuvant alone showed no Env-specific binding.

### Env-Specific Antibody Subclass Responses in Mice Immunized with Unfixed or GLA-Fixed Trimers

To investigate potential qualitative differences in the response elicited by the unfixed and GLA-fixed 16055 NFL TD CC Env trimers, we assessed the elicited serum IgG subclass response after three immunizations. We observed that mice immunized with fixed Env trimers generated a different subclass pattern compared to the mice immunized with unfixed trimers. Specifically, while the IgG1 responses were similar, mice immunized with fixed trimers displayed lower IgG2b, IgG2c, and IgG3 titers compared to mice immunized with the unfixed trimers, independently of whether unfixed protein (**Figure 3A**) or fixed protein (**Figure 3B**) was used as the binding target on the ELISA plate. This difference was not observed when sera collected after two immunizations were analyzed, likely because the IgG subclass responses were still very low at this time point (Figure S1B in Supplementary Material). We also compared the ratios between the subclasses at a serum dilution of 1:25 and observed differences between the groups, which were significant for both IgG1:IgG2b and IgG1:IgG2c ratios when unfixed protein was used for coating (**Figure 3C**, upper

representation of the NFL TD CC Env trimer sequence with the flexible (G4S)2 peptide linker indicated between gp120 and gp41 (top) and cartoon of the unfixed and glutaraldehyde (GLA)-fixed Env trimers (bottom). (B) Left panel: SDS gel of unfixed trimers under non-reducing conditions and reducing conditions with molecular weight (MW) marker shown in between; middle panel: SDS gel of GLA-fixed under non-reducing conditions and reducing conditions with MW marker shown in between; right panel: blue native gel of unfixed and GLA-fixed trimers. (C) Left panel: differential scanning calorimetry curves comparing the *in vitro* stability of unfixed (dashed line) and GLA-fixed (solid line) 16055 NFL TD CC trimers; right panel: negative-stain electron microscopy (EM) images of unfixed and GLA-fixed 16055 NFL TD CC trimers. (D) ELISA comparing the antigenic profile using a set of Env-specific monoclonal antibodies of the unfixed (left) and GLA-fixed (right) 16055 NFL TD CC trimers.

panel) and for the IgG1:IgG2b ratio when fixed protein was used for coating (**Figure 3C**, lower panel). These serological results suggested a Th2-shifted response following immunization with the GLA-fixed 16055 NFL TD CC Env trimers. Control mice injected with adjuvant alone showed no Env-specific IgG1, IgG2a, IgG2c, or IgG3.

AbISCO-100 adjuvant, or with adjuvant alone (*n* = 2). Serum was collected 14 days following the second immunization and serum and spleens were collected 8 days following the third immunization. (B) Env-specific IgG binding titers were measured by ELISA after two or three immunizations using unfixed 16055 NFL TD CC Env trimers for coating: full titration curves (group means) are shown to the left and IC50 binding titers (individual animals) are shown for the post-3 serum to the right. (C) Env-specific IgG binding titers were measured by ELISA after two or three immunizations using fixed 16055 NFL TD CC Env trimers for coating: full titration curves are shown to the left (group means) and IC50 binding titers (individual animals) are shown for the post-3 serum to the right. Statistical significance (Student's *t*-test) between post-3 IC50 titers in mice injected with unfixed or fixed trimers immunized mice was tested. Fivefold serial dilution was used for all samples starting at a 1:25 dilution.

To determine if this difference was detected if additional boosts were performed, we performed an independent immunization experiment where mice were injected five sequential times with the unfixed or GLA-fixed 16055 NFL TD CC Env trimers in AbISCO-100. This experiment yielded very similar results with increased IgG1:IgG2b and IgG1:IgG2c ratios in mice immunized with GLA-fixed trimers compared to mice immunized with unfixed trimers. This difference was significant for the IgG1:IgG2b ratio using both unfixed and fixed protein for coating (Figure S2 in Supplementary Material).

## T Cell Responses Elicited in Mice Immunized with Unfixed or GLA-Fixed Trimers

Having observed that unfixed and fixed 16055 NFL TD CC Env trimers induce qualitatively different IgG subclass responses, we next investigated whether the Env-specific T cells responses also differed between animals in each of the groups. We first used a cytokine ELISpot analysis of splenocytes harvested after the third immunization for this analysis. We evaluated if the response measured by our protein stimulation conditions (20 h at 37°C) resulted from CD4+ T cells by comparing cytokine production in total splenocytes to the CD4+ T cell-depleted splenocytes (Figure S3A in Supplementary Material). This experiment confirmed that both the IFNγ and IL-2 cytokine production measured in response to protein stimulation was CD4+ T cell-dependent as the CD4+ T cell-depleted samples did not secrete cytokine levels that exceeded those of the medium control (Figures S3B,C in Supplementary Material). We next applied this method to analyze spleens harvested from mice immunized three times with unfixed or GLA-fixed 16055 NFL TD CC trimers and detected no significant differences in the number of IFNγ, IL-2, and IL-4 producing T cells upon stimulation with NFL trimers (unfixed or fixed) (**Figure 4A**). We concluded that mice immunized with unfixed or GLA-fixed 16055 NFL TD CC Env trimers had similar numbers of cytokineproducing cells, indicating similar uptake and processing of the GLA-fixed and unfixed trimers by antigen-presenting cells for CD4+ T cell activation. To specifically investigate the presence of T cells producing Th2-associated cytokines, we employed a flow cytometry-based bead assay to detect low levels of cytokines potentially present in supernatants from *in vitro*-stimulated T cells from mice immunized three times with unfixed or GLAfixed Env trimers. We detected varying levels of IL-5, IL-10, and IL-13 with several mice being under the limit of detection of the assay. However, the mice that did respond with detectable IL-5, IL-10, and IL-13 levels were almost exclusively found among the mice immunized with the GLA-fixed trimers, suggesting a potential connection to the antibody subclass response in these mice (**Figure 4B**).

Figure 4 | CD4+ T cell cytokine production after *in vitro* stimulation of splenocytes collected after three immunizations with unfixed or fixed 16055 native flexibly linked (NFL) trimer-derived (TD) CC Env trimers or adjuvant only. (A) IFNγ, IL-2, and IL-4 cytokine-producing cells (group means) were measured by ELISpot analysis after 20 h stimulation with unfixed or fixed Env trimers or with ConA (positive control) or medium (negative control). Each spot formed in the wells represents one cytokine-producing cell. The average number for cytokine-producing cells for each group was plotted for each stimulus. Statistical significance (Student's *t*-test) between mice immunized with unfixed and fixed protein was tested. (B) Detection of IL-5, IL-10, and IL-13 in supernatants following 20 h *in vitro* stimulation with unfixed NFL TD CC trimers, glutaraldehyde-fixed NFL TD CC trimers, Con A (positive control), or medium (negative control) using a flow cytometry-based bead assay. The results were plotted as picograms per milliliter cytokine produced for each condition. The detection limit of cytokines was 0.273 pg/ml.

# DISCUSSION

Here, we performed a comparative study in mice to examine the magnitude and quality of the Env-specific immune responses induced by unfixed or GLA-fixed 16055 NFL TD CC trimers. We demonstrate that the GLA-fixed 16055 NFL TD CC trimers displayed increased thermostability *in vitro*, reduced exposure of non-neutralizing antibody epitopes *in vitro* and lower *in vivo* Env-specific IgG antibody responses after two immunizations. However, following three immunizations the difference in Envspecific IgG titers was modest and only detectable when unfixed trimers were used as the target antigen in the ELISA. The difference in magnitude of the response induced by the unfixed trimers compared to the fixed trimers may be because unfixed trimers are more prone to unfolding or dissociation *in vivo*, resulting in exposure of immunogenic but non-neutralizing protein determinants. Thus, a reduced response may be a desired outcome if it means that less antibody responses to irrelevant epitopes. Induction of antibodies against non-desired, non-neutralizing epitopes may register by ELISA when unfixed trimers are used for coating but less so when the fixed protein is used. Thus, the use of both unfixed and fixed trimers as both immunogens and as binding targets in the ELISA plate provides useful information to deduce trends in the elicited antibody specificities *in vivo*. Whether GLA fixation offers an advantage for the quality of neutralizing antibody responses induced by the 16055 NFL TD CC trimers was not addressed in the present study, as this was previously investigated in the guinea pig model (7), as well as in the rabbit model using other well-ordered Env trimer designs (9, 10). We have previously reported tier 1 neutralizing activity in immunized mice (12, 13). However, immunogens that readily elicits tier 2 neutralizing antibody titers in rabbits (9, 10, 14) fail to do so in mice (15, 16).

The most significant observation in this study was that the Env-specific IgG response measured in animals inoculated with GLA-fixed trimers displayed a more Th2-skewed subclass profile than the response elicited in mice inoculated with unfixed trimers. We demonstrated this outcome by measuring Env-specific IgG1, IgG2b, and IgG2c. In mice, IgG1 represents a Th2-skewed response, while IgG2b and IgG2c represent a Th1-skewed response. A previous study in Balb/c mice reported that Env delivered in the form of a DNA vaccine induced a more Th2-biased antibody subclass response profile than did a DNA-based influenza virus hemagglutinin-based vaccine, as detected by an increased IgG1:IgG2a ratio in mice immunized with Env (17). This suggested an intrinsic difference in the type of response induced by the two viral antigens. We previously examined antibody subclass profiles induced by purified HIV-1 Env trimers formulated in the AbISCO-100 adjuvant in a headto-head comparison between Balb/c mice and C57BL/6 mice and found that balanced Th1/Th2 responses were induced in both strains, with potent Env-specific IgG1, IgG2a, and IgG2b responses detected in Balb/c mice and similarly potent IgG1, IgG2b, and IgG2c responses detected in C57BL/6 mice (13). In the current study, we detected potent IgG1, IgG2b, and IgG2c responses to the unfixed trimers but reduced IgG2b and IgG2c responses to the fixed trimers. This Th2 skewing of the antibody subclass responses was observed in all animals immunized with the GLA-fixed trimers, using either the unfixed or GLA-fixed Env trimers as the antigenic target coated on the ELISA plates and was observed in two independent experiments.

The unfixed and GLA-fixed trimers used here were formulated with the AbISCO-100 adjuvant (also called Matrix-M). We and others have previously shown that this adjuvant induces a balanced Th1/Th2 response also for other protein antigens (18–20). Our results show that the presence of GLA adducts on the trimers influenced the induced immune response in a manner that was not over-ridden by the presence of the adjuvant. We have previously shown that the response induced by protein antigens in AbISCO-100 can be shifted toward a more Th1-driven response by co-administration of a TLR9 agonist (18). Thus, co-stimulation of TLR9 may be one way to balance the Th2 skewing caused by the GLA fixation. Another strategy to direct the Env-specific response away from a Th2-biased profile is to prime with a viral vector expressing Env prior to protein boosting, which we previously showed induced a more Th1-biased response (21). While the assessment of Th1/Th2 skewing by measurements of IgG subclasses may not be readily translatable to other species, our finding may be worthy of further investigation in other models using additional assays of T helper function as different vaccine platforms are under evaluation and prioritization. While formaldehyde treatment of proteins was shown to limit antigen processing by constraining presentation to T cells in one study (22), we did not detect any measurable differences in the magnitude of cytokineproducing profiles of Env-specific CD4+ T cells in our study using unfixed or GLA-fixed protein for *in vitro* stimulation when IFNγ, IL-2, and IL-4 cytokine responses were measured by ELISPOT analysis. When a more sensitive flow cytometry-based bead assay was used to detect additional Th2 cytokines, we observed that the highest IL-5, IL-10, and IL-13 responders were found in the group of mice immunized with the GLA-fixed trimers. This result was non-significant since a majority of the mice were below the level of detection. Nevertheless, it indicated a trend toward an increased Th2 response after immunization with fixed trimers, which may be related to the skewed antibody subclass response.

Chemical fixation of viruses and antigens is used in some commercial vaccines, for example, to inactivate infection by replication-competent whole virus particles. This was successfully done for the polio vaccine but it was less successful for a candidate respiratory syncytial virus (RSV) vaccine (23). In the case of the clinically tested RSV vaccine, formaldehyde was used for fixation. This vaccine worsened clinical symptoms in children exposed to natural RSV infection, triggering its removal from commercial development (24). The negative outcome was associated with a shift in the responses from a Th1 to a Th2 profile, as well as lower levels of neutralizing antibodies (24–26), effects that were suggested to be related to the carbonyl groups on the vaccine antigens (27). These studies, as well as those presented here, indicate the need for an improved understanding of how modifications to protein-based vaccines influence the induced response at multiple levels. For example, protein adducts such as aldehyde groups may interact with scavenger receptors such as CD36 (28), which are expressed by both B cells and professional antigen-presenting cells. Whether such potential effects influence antigen-specific immune responses to HIV-1 Env or other viral proteins is not known, but may be elucidated by future investigations.

### ETHICS STATEMENT

All animal experiments were performed under approved conditions and standard guidelines prior to the experimental start according to the regulations of the Committee for Animal Ethics (Stockholm, Sweden). The ethical permit number is N4/16.

# AUTHOR CONTRIBUTIONS

MS: planning and performing *in vivo* experiments, data collection, data analysis, making figures, and writing manuscript. MA: performing *in vivo* experiments, data collection, and reviewing manuscript. JS: planning, performing, data collection and data analysis in T cell in vitro experiments. LY: preparing recombinant proteins for EM and performing EM analysis. YF, KT, RW, and JG: recombinant protein production and characterization, data analysis, making figures, and reviewing manuscript. RTW: planning the study and supervision and reviewing of manuscript. GKH: study planning, supervision, and writing manuscript.

### ACKNOWLEDGMENTS

This study was supported by grants from the Swedish Research Council and the National Institutes of Health (a P01 HIVRAD grant AI104722). We would like to thank the Scripps Research Institute EM Core facility for technical assistance.

### REFERENCES

# SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at http://www.frontiersin.org/article/10.3389/fimmu.2017.01654/ full#supplementary-material.

Figure S1 | Total Env-specific IgG and subclass-specific responses measured by ELISA. (A) ELISA curves for Env-specific IgG for individual mice (post-2 and post-3) using unfixed 16055 native flexibly linked (NFL) trimer-derived (TD) CC Env trimers (left) or fixed 16055 NFL TD CC Env trimers (right) as the target antigen. (B) ELISA curves (group means) for Env-specific IgG1, IgG2b, IgG2c, and IgG3 from post-2 sera using fixed 16055 NFL TD CC Env trimers as the target antigen. Fivefold serial dilution was used for all samples starting at a 1:25 dilution.

Figure S2 | Env-specific antibody subclass responses after five immunizations measured by ELISA. (A) ELISA curves (group means) for Env-specific IgG1, IgG2b, and IgG2c using unfixed 16055 native flexibly linked (NFL) trimer-derived (TD) CC Env trimers as target antigen. (B) ELISA curves (group means) for Env-specific IgG1, IgG2b, and IgG2c using fixed 16055 NFL TD CC Env trimers as target antigen. (C) Ratios of IgG1:IgG2b and IgG1:IgG2c calculated using either unfixed and glutaraldehyde-fixed protein coated on the ELISA plates. The serum samples were added to the plates in fivefold serial dilutions starting at 1:50. \* and \*\* indicate statistical significance (Student's *t*-test) between mice immunized with unfixed and fixed 16055 NFL TD CC Env trimers.

Figure S3 | CD4+ T cell depletion of splenocytes. (A) Assessment of the purity after CD4+ T cell depletion. The FACS plots show the changes in CD4, CD8, and B220 cell populations before and after CD4 depletion. IFNγ (B) and IL-2 (C) cytokine-producing cells were measured by ELISpot 20 h after stimulation with unfixed 16055 NFL TD CC trimers or with Con A (positive control) or medium (negative control) of splenocytes with or without CD4+ T cell depletion.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2017 Soldemo, Àdori, Stark, Feng, Tran, Wilson, Yang, Guenaga, Wyatt and Karlsson Hedestam. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

*Department of Medicine, Solna, Karolinska*

# Regulation of Subunit-Specific Germinal Center B Cell Responses to the HIV-1 Envelope Glycoproteins by Antibody-Mediated Feedback

*Mattias N. E. Forsell1,2\*, Linda Kvastad2†, Saikiran K. Sedimbi <sup>2</sup> , John Andersson3 and Mikael C. I. Karlsson2*

*Division of Immunology, Department of Clinical Microbiology, Umeå University, Umeå, Sweden, 2Department of*

*Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden, 3*

### *Edited by:*

*1*

*Institutet, Stockholm, Sweden*

*Persephone Borrow, University of Oxford, United Kingdom*

### *Reviewed by:*

*Leonidas Stamatatos, Seattle Biomedical Research Institute, United States Oliver Bannard, University of Oxford, United Kingdom Kai-Michael Toellner, University of Birmingham, United Kingdom*

### *\*Correspondence:*

*Mattias N. E. Forsell<EMAIL_ADDRESS>
### *†Present address:*

*Linda Kvastad, Science for Life Laboratory, School of Biotechnology, Royal Institute of Technology (KTH), Solna, Sweden*

### *Specialty section:*

*This article was submitted to HIV and AIDS, a section of the journal Frontiers in Immunology*

*Received: 19 April 2017 Accepted: 12 June 2017 Published: 30 June 2017*

### *Citation:*

*Forsell MNE, Kvastad L, Sedimbi SK, Andersson J and Karlsson MCI (2017) Regulation of Subunit-Specific Germinal Center B Cell Responses to the HIV-1 Envelope Glycoproteins by Antibody-Mediated Feedback. Front. Immunol. 8:738. doi: 10.3389/fimmu.2017.00738*

The regulation of germinal center (GC) B cell responses to single epitopes is well investigated. How monoclonal B cells are regulated within the polyclonal B cell response to protein antigens is less so. Here, we investigate the primary GC B cell response after injection of mice with HIV-1 envelope glycoproteins. We demonstrate that single GCs are seeded by a diverse number of B cell clones shortly after a single immunization and that the presence of Env-specific antibodies can inhibit the development of early GC B cells. Importantly, the suppression was dependent on the GC B cells and the infused antibodies to target the same subunit of the injected HIV-1 envelope glycoproteins. An affinity-dependent antibody feedback has previously been shown to regulate GC B cell development. Here, we propose that this antibody-based feedback acts on GC B cells only if they target the same or overlapping epitopes. This study provides important basic information of GC B cell regulation, and for future vaccine designs with aim to elicit

Keywords: epitope-specific antibodies, regulation of germinal centers, HIV-1, envelope glycoproteins, epitopespecific B cells

# INTRODUCTION

neutralizing antibodies against HIV-1.

There is abundant evidence that some HIV-1-infected patients develop broadly neutralizing antibodies (bNabs) at the chronic stage of the infection (1, 2). This demonstrates that the human immune system is, under certain circumstances, capable to produce antibodies that may be useful if they could be re-elicited by vaccination. Being the only virally derived component on the outside of the virion, it is not surprising that known bNabs target the HIV-1 envelope glycoproteins (Env) (3). It has been postulated that humoral immune responses to immunodominant regions of Env may suppress responses to less immunogenic regions, and that this could explain why bNabs are infrequently elicited during infection and has, to date, not been elicited by vaccination. Clearly, a better understanding of the regulatory processes for epitope-specific regulation and maturation of B cell responses is of great importance for the development of improved vaccine strategies.

Immunization with recombinant proteins in adjuvant generates T-dependent humoral immune responses that are characterized by the formation of germinal centers (GCs). In GCs, antigen-specific B cells undergo affinity maturation and differentiation into memory B cells and Ab-secreting plasma cells [reviewed in Ref. (4)]. The resulting polyclonal Ab response comprises a number of different antibodies that each target a distinct epitope surface on the injected protein antigen (5). In the GC, B cell clones that target the same epitope on model antigens are competitively regulated and there is a bias for survival of high-affinity clones (6–8). It was demonstrated that B cell clones with a high-affinity BCR are better at presenting antigenic peptides to Tfh than are B cells with low affinity, and therefore gain a competitive advantage (9), and the importance of robust Tfh responses for the generation of neutralizing antibodies against HIV-1 has been extensively discussed elsewhere (10). However, even within single GCs a wide range of intra- and inter-clonal affinity maturation of B cells occur (11, 12). It is therefore possible that regulatory mechanisms exist to allow for clonal expansion and maturation of B cells with different epitope specificity after challenge with physiologically relevant multi-epitope proteins, such as HIV-1 Env. By dampening the ability of B cells to recognize the immunodominant V3-region on Env, we have previously shown that antibody and plasma cell responses to distinctly different epitope regions were independently regulated after repeated immunizations with recombinant soluble HIV-1 Env in mice (13). Similar results were subsequently found when instead immunosilencing the trimerization domain of Env (14). These findings were not unique to Env, as similar observations had previously been described for a number of therapeutic proteins, including *Pseudomonas* exotoxin A [reviewed in Ref. (15)]. Immunodominance may therefore be driven by a mechanism that is largely independent of inter-clonal competition and additional regulatory mechanisms might play a significant role for the regulation of B cell clones with distinct BCR specificities within the polyclonal response after immunization.

For decades, it has been known that IgG can feedback regulate the humoral immune response, and that this is dependent on the nature of the antigen and subclass [reviewed in Ref. (16)]. It was demonstrated that IgM could mediate inhibition of GC B cell responses by direct binding to antigen, thereby occluding it from recognition by antigen-specific BCRs on B cells (17). Since IgM is readily elicited early during the development of T cell-dependent GC B cell responses, it is unlikely to provide a strong inhibitory effect on GC B cells under physiological conditions. However, an antibody-mediated feedback mechanism that is dependent on the binding specificity of IgG could potentially explain our results where independent expansion of epitope-specific plasma cell responses to HIV-1 Env was observed (13).

A single injection with Env in adjuvant was not sufficient to induce potent Env-specific IgG-secreting plasma cells in mice, rabbits, and non-human primates (13, 18, 19). If antigen-specific GC B cells had been developed at the same time point, this would allow us to investigate how Env-specific GC B cell responses develop without the interference of endogenously produced antigen-specific antibodies. According to this rationale, we set out to define the characteristics of the GC B cell response after one injection of Balb/C mice with Env, and then to address if an antibody-mediated feedback had potential to regulate GC B cell responses in an epitope-specific manner.

# MATERIALS AND METHODS

### Recombinant Proteins

The design and cloning of trimeric soluble recombinant envelope glycoproteins Env and monomeric gp120 for injection, and trimeric Env, gp120, and gp120ΔV3 for site-specific biotinylation has been previously described (20, 21). All recombinant proteins were produced by using the FreeStyle™ 293 Expression system (Invitrogen) and purified by sequential lectin and his-tag affinity chromatograph (22). Site-specific biotinylation was performed by treating AviTagged recombinant Env and gp120 with biotinprotein ligase (GeneCopoeia, Rockville, MD, USA) (20).

### Immunizations

For injections, 10 μg of Env or gp120 was emulsified in Imject™ Alum adjuvant (Thermo Fischer Scientific) and 7- to 10-weekold BALB/c mice were injected *via* the intraperitoneal route. To generate immune serum to Env or gp120, groups of six mice were injected with recombinant Env or gp120 in Imject™ Alum adjuvant two times at a 2-week interval, and serum was collected 2 weeks after the last injection. Serum from mice injected with Adjuvant alone was used as control. Mice were kept at the animal facility at Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet or at the Umeå Center for Comparative Biology, Umeå University, Sweden.

## Immunohistochemistry and Laser Microdissection

For immunohistochemistry and laser capture microdissection of GC structures, 8 μm sections of OCT embedded spleens were fixed on super frost plus glass slides (Thermo Scientific) or on PPS membrane slides (MicroDissect GmbH), and fixed using ice-cold acetone. For subsequent laser microdissection, we chose the mid section of a three consecutive 8 μm sections that all demonstrated a GC structure of same shape and relative location in the spleen. To inhibit non-specific binding, sections were treated with 5% goat serum (Dako) and subsequently treated with Avidin/Biotin blocking kit. Slides were then stained with FITC-conjugated anti-IgD (BD Pharmingen) and biotinylated peanut agglutinin (PNA) followed by Alexa555-conjugated streptavidin (Thermo Fisher Scientific). Confocal microscopy was performed on the glass slides with a DM IRBE system (Leica). Laser microdissection was performed on PPS membrane slides in a LMD7000 system (Leica). Single GC structures were defined as PNA<sup>+</sup>, IgD<sup>−</sup> areas inside splenic follicles (IgD<sup>+</sup>, PNA<sup>−</sup>) in the center section of each spleen, and collected in RLT buffer for subsequent mRNA extraction.

# Flow Cytometry and Cell Sorting

Single-cell suspension of splenocytes was achieved by passing spleen through a 70-µm nylon mesh. RBCs were subsequently lysed with hypotonic ammonium chloride solution for 1 min, and the remaining cells were washed and resuspended in complete RPMI 1640 medium (Sigma) containing 5% FBS, 50 µM 2-ME, 2 mM l-glutamine, 100 U/ml penicillin, and 100 µM streptomycin. Where applicable, splenocytes were enumerated by flow cytometry using AccuCheck Counting Beads (Life Technologies). The amount of live cells in samples was determined by using a Live/Dead aqua viability kit (Thermo Fischer Scientific). Antibodies used for stainings were FITC-conjugated anti-GL7 antigen, PerCP.Cy5.5-conjugated anti-IgD, PE-conjugated anti-CD95, and Pacific Blue-conjugated anti-B220 (all BioLegend). To determine antigen specificity, cells were incubated with 10 μg/ml biotinylated Env trimers, gp120 trimers, or gp120ΔV3 trimers and subsequently with APC-conjugated streptavidin. Data were collected on a BD LSRFortessa™ X20, and cell sorting was performed on a BD Facs Jazz™ (All BD Biosciences). Analysis of flow cytometric data was performed using FlowJo (FlowJo, LLC).

### B Cell Receptor Fragment Analysis

The B-cell repertoire was assessed by spectratyping of VDJ regions of heavy chain families 1, 2, 3, 5, 6, and 7. Briefly, mRNA from tissues was extracted with an RNAeasy kit (Invitrogen), and corresponding cDNA was then generated using iScript (BioRad), according to the manufacturer's instructions. Previously published primers for amplification of the VDJ region (with focus on the uniqueness of the CDR3) of the variable region heavy chain (Vh) families 1 and 2 of mice were used to amplify the target regions [Vh1 forward: TCCAGCACAGCCTACATGCAGCTC; Vh2 forward: CAGGTGCAGCTGAAGGAGTCAGG; and Jrev (common primer in the JH-region): CTTACCTGAGGAGACGGTGA] (23, 24). The amplifications were performed in a total volume of 20 µL, using 2× GoTaq (Promega), 2 µL (1 µM final) of each primer, and 2 µL of cDNA. After 1 min at 95°C, amplification was performed for 40 cycles as follows: 30 s at 95°C, 30 s at 55°C, and 1 min 30 s at 72°C, and ended with a step of 10 min at 72°C. To label the amplified fragments, 5 µL of each P CR product was mixed with 0.5 µM 6-fluorescein amidite (FAM)-labeled Jrev-primer and 5 µL GoTaq and subjected to 10 runoff cycles as follows: 2 min at 95°C, 2 min at 55°C, and 20 min at 72°C, and ended with a 10-min step at 72°C. FAM-labeled products were then processed on an ABI3130 Genetic analyzer (Applied Biosystems). Data were analyzed using PeakScanner v1.0 software (Applied Biosystems). Each peak in the resulting histogram represents one or many B cell clones with identical nucleotide length of the VDJ region of a certain Vh family. For an approximation of a distinct number of clones present in a single GC, a stringent cutoff of 1,000 response units (RUs) was applied to select for dominant clones. The relative dominance of the single fragment with the highest RU value in a GC was calculated with respect to the sum of RUs of all detected fragments in the same (%dominance = RUdominant fragment × 100/Σ RUall fragments).

# Enzyme-Linked Immunosorbent Assay

High-protein-binding MaxiSorp plates (Nunc) were coated with 100 or 200 ng/well of recombinant Env or gp120 at 4°C overnight. The coated plates were blocked with 2% fat-free milk in PBS. After washing (PBS, 0.05% Tween-20), serum was added at different concentrations. The wells were then incubated with HRP-conjugated anti-mouse IgG or IgM (Southern Biotech). After washing, a colorimetric HPA substrate containing 3,3′,5,5′-tetramethylbenzidine (Invitrogen) was added. Adding one volume of 1 M H2SO4 stopped the enzymatic reaction, and OD was read at 450 or 450–620 nm. All incubations were performed at room temperature for 1 h, unless otherwise stated.

# Statistical Analysis

Statistical analysis was performed using GraphPad Prism V5.04 (GraphPad Software). Data sets were first analyzed with the D'Agostino and Pearson omnibus normality test. Sets conforming to normal distribution were then analyzed further using ANOVA or non-paired two-tailed Student's *t*-test to determine the significance of observed differences. Data sets not exhibiting normal distribution were analyzed using a non-parametric ANOVA, Mann–Whitney *U* test, or the Wilcoxon matched-pairs signed-rank test.

# Ethics Statement

All animal experiments were pre-approved and performed in accordance with the Swedish Animal Welfare Act under protocols Dnr 234/12-dnr 11/13 (approved by Stockholms Norra djurförsöksetiska nämnd, Sweden) and Dnr A 59-15 (approved by Umeå försöksdjursetiska nämnd, Sweden).

# RESULTS

# GC B Cell Responses after Immunization with HIV-1 Env

To determine if potent GC B cell responses occur after a single injection with Env, we devised an injection regimen to characterize the development of GC B cells after immunization with Env in Imject Alum™ adjuvant. By immunofluorescence microscopy, we found that distinct GC formation (PNA<sup>+</sup>IgD<sup>−</sup>) could be detected on day 6 by histology (**Figure 1A**). The numbers of splenic GCs had significantly increased on day 11, but were reduced in numbers again by day 21 after the immunization. To quantify our findings, we assessed the frequency of splenic GC B cells (B220<sup>+</sup>IgD<sup>−</sup>CD 95<sup>+</sup>GL7<sup>+</sup>) by flow cytometry at the same time points. Consistent with our histological results, we found that the overall frequency of GC B cells had reached detectable levels at day 6, that a major expansion had occurred between days 7 and 11 (**Figure 1B**). We could also quantify the overall reduction of GC B cells between days 11 and 21 after immunization Collectively, these data verify that GC B cell responses develop after a single injection of mice with Env in adjuvant.

## Clonal Expansion and Contraction of B Cells in GCs after Immunization with HIV-1 Env in Mice

It has been previously shown that the number of dominant B cell clones in a single GC could vary after immunization with other recombinant proteins (11, 25–27). If a monoclonal B cell population seeds separate GCs after immunization with Env, this could explain the lack of competition between the responses to different epitopes within the antigen. To address this, we isolated single GCs (IgD−PNA+) by laser capture microdissection and approximated the relative clonality of these at different time points after immunization. This was done by assessing the number of VDJ regions of heavy chain (Vh) with variable nucleotide lengths

left panel). The number of GCs in spleen sections from individual mice was enumerated at the indicated time points (right panel). (B) Flow cytometric quantification for the frequency of GC B cells (B220+IgD−GL7+CD95+) of total splenocytes is shown at the indicated time points. *N*(adjuvant, d4) = 4 animals; *N*(d6, d11, d21) = 5 animals.

that could be amplified from spleen sections from mice shown in **Figure 1**. We focused on the Vh1 family that cover a large part of the total Vh-repertoire of mice, and on the Vh2-family that cover a limited part of the Vh-repertoire (28). To validate the method, we first amplified Vh1 and Vh2 VDJ regions from a sectioned spleen. As expected, we could amplify a large number of Vh1 and Vh2 VDJ fragments from the polyclonal population of B cells in the spleen section, and the frequency of amplified fragments were closely adhering to a Gaussian distribution with respect to fragment length (**Figure 2A**). Focusing on the Vh1 family, we could amplify a large number of VDJ fragments from single GCs at days 6 and 21 after injection with Env, whereas a significant number of GCs contained a relatively few Vh-1 fragments at day 11 (**Figure 2B**). This suggested that significant clonal selection had occurred between days 6 and 11, but that the GC B cell population had then diversified with respect to fragment lengths between days 11 and 21 after the immunization. To quantify this, we investigated the relative dominance of the most abundant Vh1 VDJ fragment among all amplified Vh1 VDJ fragments from single GCs over time. Consistent with polyclonal GC B cell populations, the dominance of a single VDJ fragment in separate GCs was on average 16.5% (range: 16–17%) or 18% (range: 12–31%) of all VDJ fragments on days 6 or 21 after injection (**Figure 2C**). By contrast, the average dominance of a single VDJ was 36% (range: 18–61%) on day 11 after the injection. This supports that GCs at peak response have reduced

B cell clonality, but that fully monoclonal GCs were rare. Instead, GCs at peak response display variable degrees of clonal dominance. A similar variation of clonal dominance in single GCs was previously shown after injection of mice with chicken gamma globulin, *Bacillus anthracis* protective antigen and influenza hemagglutinin (11, 12).

could be found in each of the isolated single GCs on day 6 (*N* = 3), day 11 (*N* = 14), and day 21 (*N* = 7) was performed (right panel). (C) The relative dominance of the VDJ fragment with the highest frequency among all detected Vh1-family VDJ fragments is shown. (D) Shown is an enumeration of how many distinct Vh2 fragments that could be found in each of the

(B220+IgD−GL7+CD95+, red) and non-GC B (B220+IgD−GL7−CD95−, blue) cells were sorted and assessed for the frequency and number of amplified

Gaussian distribution of different fragments with respect to their relative

isolated single GCs at different time-points. (E) GC B cells

2

Vh2-family VDJ fragments. The *r*

frequency.

Detection of clones from the Vh2-family in single GCs was rare at all time-points and when detected, comprised up to five fragments (**Figure 2D**). By contrast, a large number of clones of the Vh2-family could be detected after flow cytometric sorting of GC B cells 11 days after immunization of mice with Env (**Figure 2E**). The conflicting data are likely explained by the presence of a cross-section of all responding GC B cell clones after the flow cytometric sorting, whereas the laser capture microdissection allowed for analysis of GC B cell clones from single GCs. A Gaussian distribution analysis of the sorted cells revealed that non-GC Vh2 B cell clones were normally distributed with respect to their BCR length (*r*<sup>2</sup> = 0.97). By contrast, the distribution of Vh2-related GC B cells was slightly skewed (*r*<sup>2</sup> = 0.78). Even though seeding and recruitment of Vh2-family B cells to single GCs was low in comparison to Vh1 clones, biased selection of GC B cell clones had occurred, if assessed on a global level.

# Development of Antigen and Epitope-Specific GC B Cell Responses after Immunization of Mice with HIV-1 Envelope Glycoproteins

A requirement for an investigation to understand if antibodies can mediate a feedback to regulate epitope-specific GC B cells was that we could also measure GC B cell responses to two distinctly different regions of Env. Here, we took advantage of a probe-based system that we had previously used to enumerate subunit-specific plasma cell responses after repeated immunizations with Env (20). To test this system, we first assessed the capacity of splenic GC B cells to bind to Env, the gp120 subunit, or to a gp120 subunit that lack the variable region 3 (gp120ΔV3) 11 days after injection with Env. We found that an average of 45% of GC B cells was specific for Env, and that approximately 50% of those could bind to both gp120 and the gp120ΔV3 probes (**Figure 3A**). Importantly, we had previously shown that repeated injection of Env into mice did produce significant B cell responses to the non-exposed inside of Env trimers (20). Therefore, the Env-specific response was evenly distributed between epitopes that span the gp120 or the gp41 subunits, whereas no significant response had developed against the variable region 3 at this time point.

Next, we assessed changes in frequency of Env-binding GC B cells over time by flow cytometry. We injected mice with Env and found that GC B cells had reached sufficient numbers and affinity for Env to be detectable in our analysis after 11 days (**Figure 3B**). This suggested that significant proliferation, antigen-specific affinity maturation, and selection of GC B cells had occurred during the second week after the injection. The frequency of B cells that could bind to the Env-based probe was not significantly changed between days 11 (median: 41%) and 21 (median: 50%).

Subtracting gp120-specific responses for the total Env-specific response allowed us to determine the specific response to the gp41 subunit of Env. As expected, gp120 and gp41 subunitspecific responses developed with the same kinetics as the total Env-specific response and required between 7 and 11 days to develop sufficient affinity for detection (**Figure 3C**). No further increase in the frequency of gp120- or gp41-binding GC B cells had occurred between days 11 and 21 after a single immunization of mice with Env. Collectively, gp120-specific GC B cells accounted for a median of 51% (day 11) and 58% (day 21) of total Env-specific GC B cells. Consistently, gp41-specific GC B cells accounted for the remaining 49% (day 11) and 42% (day 21) of total Env-specific GC B cells.

Figure 3 | Detection of antigen and subunit-specific germinal center (GC) B cell responses after a single injection of mice with Env. (A) The frequency of GC B cells (B220+IgD−GL7+CD95+) 11 days after injection which were able to bind biotinylated Env, gp120, or gp120ΔV3 was assessed by flow cytometry after addition of APC-conjugated streptavidin. Staining of cells with APC-conjugated streptavidin (SA) in the absence of Env was used verify the specificity of the binding. (B) The frequency of Env-specific GC B cells of total GC B on days 6, 11, and 21 after injection of mice with Env is shown. (C) The frequency of GC B cells (B220+IgD−GL7+CD95+) that could bind to the gp120 subunit of Env was assessed in a similar manner (left panel). By subtraction of the gp120-specific GC B cells from the total Env-specific GC B cells, we could also determine the proportion of gp41-specific GC B cells that had been induced at the same time points (right panel). *N* = 4–5 animals per group.

# Regulation of Subunit-Specific GC B Cell Responses to the HIV-1 Envelope Glycoproteins

To study feedback regulation, we generated serum by repeated injections of mice with soluble Env or with gp120, that either contained antibodies to both the gp120 and gp41 subunits (Env injection) or only to the gp120 subunit (gp120 injection). We subsequently normalized the harvested serum so that both had a similar binding capacity to Env with regard to IgG and IgM (**Figure 4A**). Respective serum was then further diluted 2× in PBS and 200 μl was infused into mice that had been immunized with Env 4 days earlier (**Figure 4B**). We chose this time point to allow for similar initiation of the GC response toward Env in all groups prior to the serum infusion (29), and that it was just before GC B cells could be detected by flow cytometry (**Figure 1A**). Moreover, it would allow for similar trafficking and retention of Env to the network of follicular dendritic cells in GC

for the first 4 days after immunization (30, 31). Since the injected serum levels was below those that can be induced by repeated Env injections into BALB/c mice, the potential regulatory function of antibodies on GC B cell responses likely mimic that of the endogenous high-affinity anti-Env antibody response after it has been generated.

Two weeks after immunization of mice with Env, we could detect low-levels of circulating Env-specific IgG after one injection (**Figure 4C**). This represented the background levels of the endogenous response at a time point when Env-specific GC B cells had developed. In both the serum-infused groups, we found distinct levels of circulating Env-binding IgG. Since these levels were significantly higher than that of the endogenous response, this demonstrated that specific IgG from the serum infusion had remained in circulation for more than a week. This is consistent with a half-life of murine IgG of approximately 8 days (32). We did not detect significant antigen-specific IgM in any of immunized animals at this time-point.

To understand if the development of subunit-specific GC B cells had been influenced by the serum injection, we determined the absolute number of splenic gp120- and gp41-specific GC B cells that had been induced in respective groups of mice. Here, we found that a distinct inhibition of gp120-specific GC B cells had occurred in both of the serum-infused groups (**Figure 4D**). This verified that the infused Env-specific and gp120-specific serum had similar capacity to suppress gp120 specific GC B cell responses. By contrast, inhibition of gp41 specific GC B cells had only occurred in the groups of mice that had received Env-specific serum. This suggested that gp41 specific GC B cell responses had been negatively regulated in the presence of high-affinity Env-specific antibodies that target the gp41 subunit, but not by antibodies that targeted the gp120 subunit.

Collectively, these data suggest that high-affinity antibodies at the level of a normal immune response can provide a negative feedback to repress the development of specific GC B cell responses, but that this only occurs if the antibodies and the GC B cells target the same or overlapping epitopes on Env.

### DISCUSSION

Here, we performed a characterization of GC B cell responses to Env after a single immunization in mice, and subsequently addressed if antibodies have potential to regulate the development of GC B cells through an epitope-specific feedback mechanism. Our data suggest that single GCs are seeded by a polyclonal B cell population within a week after immunization with Env. To note, only two mice of six had developed distinct GCs at this time point. While we could not definitively rule out contamination from naïve B cells at this early time point, prior to clonal outgrowth, our data are consistent with the diverse early GC response after immunization of mice with chicken gammaglobulin, as has previously been shown (11). During the second week after immunization, varying degrees of clonal dominance is established in single GCs (**Figure 2C**). This coincides with peak frequency of total GC B cells in spleens of injected animals, and the detection of Env-specific GC B cells. To minimize the influence of non-cognate B cells that transport antigen to follicular dendritic cells or residual background from follicular B cells that did not participate in the GC reaction (33–35), we also made a qualitative approximation of clones in single GCs (**Figures 2B,D**). In this setting, we found that 9 of 14 single GCs contained between 1 and 4 distinct Vh1 fragments, where 3 GCs had potential to be fully monoclonal within the Vh1-family VDJ fragment length. During the third and fourth week after immunization, clonal dominance in single GCs had returned to levels that were indistinguishable from day 6. It was previously shown that tens to hundreds of individual B cell clones participate in the initial GC reaction (11). By the spectratyping approach used here, it was not possible to directly enumerate individual B cell clones but it was sufficient to approximate the relative clonality of single GCs at separate time points after injection of mice with Env.

After a single injection of mice with Env, we could demonstrate that up to 50% of the GC B cell response was focused on the gp41 subunit of Env. Consistent with these findings, gp41 specific plasma cells represent up of 50% of all Env-specific B cells after a booster injection (20). This suggests that GC B cells that develop in mice after a single injection of Env may differentiate into plasma cells after a subsequent booster injection. In line with this, the absence of V3-specific GC B cell development after a single injection with Env could therefore explain the absence of V3-specific plasma cells after a booster injection, as previously shown (13, 20).

Importantly, we proceeded to generate evidence that antibodies can feedback regulate the development of epitopespecific B cells. By injection of high-affinity polyclonal serum in mice at a time point where the endogenous GC response had been initiated, but prior to detection of Env-specific GC B cells, we found that preexisting antibodies to the gp120 subunit could repress gp120-specific but not gp41-specific GC B cells (**Figure 4D**). By contrast, infusion of Env-specific serum could repress both gp120 and gp41-specific GC B cell responses. Since V3-specific GC B cells had not developed after a single injection of mice with Env, we could not assess if also V3-specific GC B cell responses could be suppressed by a similar mechanism. Interestingly, infusion of Env in complex with a V3-specific Fab was recently shown to specifically suppress endogenous V3-directed antibody responses in Guinea pigs (36). This suggests that the development of V3-specific GC B cells may also be regulated by a similar antibody feedbackmediated mechanism as we here describe for gp41-specific GC B cells.

Since T cells are rapidly primed within the first days after antigenic challenge (37, 38), it is unlikely that priming of Tfh cells was affected by the day 4 serum injection. Moreover, presentation of antigenic peptides on MHC class II cannot directly explain a regulatory feedback mechanism that is dependent on the binding specificity of GC B cells. Similarly, a regulatory feedback mechanism that is dependent on the binding specificity of soluble antibodies is difficult to explain by engagement of the constant Fc-region of the infused IgG to the inhibitory Fc-gamma receptor IIb (39). In fact, a recent study demonstrated that antibody feedback of epitope-specific GCs during experimental antigen challenge act independently of Fc-gamma receptor engagement (40).

We therefore propose Env-specific B cell responses to HIV-1 Env are feedback regulated by epitope masking of antigen by highaffinity antibodies, and that this leads to a subsequent inability of low-affinity B cell clones with similar specificity to acquire stimulation *via* their BCR. In GCs, the antibody-mediated occlusion may occur on antigen that has been deposited on the FDC network, as was previously proposed by infusion of IgM (17). In our study, we investigated how early low-affinity GC B cells were affected by infusion of high-affinity IgG.

Clearly, additional research is required to fully understand how the epitope-specific GC B cell response is regulated during the gradual affinity increase and subsequent termination or differentiation of GC B cells during an endogenous immune response after vaccination with HIV-1 Env, but also if and how an antibody-based feedback can regulate the fate of memory B cells after re-challenge, as recently discussed (40–43).

Collectively, we provide data that strongly suggest that the development of GC B cells to a biologically relevant antigen is directly regulated by the presence of physiological levels of circulating antibodies. An affinity-dependent and antibody-mediated feedback to regulate affinity maturation of GC B cells has been suggested (17). We propose that this feedback acts on GC B cells only if they share the same or overlapping specificity as the circulating antibodies. Undoubtedly, the future development of well-defined mouse-derived monoclonal will allow for a more detailed investigation with regards to the biochemical and molecular properties of the inhibitory function of antibodies that target overlapping, partially overlapping, and non-overlapping epitopes of Env. Such data would be invaluable for the future designs of novel antigens for vaccination against HIV-1.

Importantly, the data presented here suggest that nonneutralizing or strain-specific neutralizing determinants on vaccine antigens have potential to suppress the development of bNab only if they share an overlapping binding site with these on Env. Our study therefore validates previous and on-going efforts to develop Env-based vaccine antigens with reduced exposure of non-neutralizing epitopes to the immune system (44–46), and we propose that it is crucial to focus these efforts on areas of Env where non-neutralizing epitopes overlap with broadly neutralizing epitopes.

### ETHICS STATEMENT

All animal experiments were pre-approved and performed in accordance with the Swedish Animal Welfare Act under protocols Dnr 234/12-dnr 11/13 (approved by Stockholms Norra djurförsöksetiska nämnd, Sweden) and Dnr A 59-15 (approved by Umeå försöksdjursetiska nämnd, Sweden).

### AUTHOR CONTRIBUTIONS

MF: experimental design, performed experiments, analyzed data, and wrote the manuscript. MK: experimental design, analyzed data, and wrote the manuscript. LK, SS, JA: performed experiments.

# ACKNOWLEDGMENTS

We thank Martina Soldemo and Gunilla Karlsson Hedestam for their contribution of Env-specific probes toward this study and Shrikant Kolan for help with figures. We also want to thank the personnel at the animal facility of the Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet and the Umeå Center for Comparative Medicine, for excellent technical assistance.

# FUNDING

This work was supported by a Mathilde Krim Fellowship in Basic Biomedical Research from the American Foundation for AIDS Research (109234-58-RKVA) and intramural funds from Umeå University to MF and the Swedish Science Council to MK.

# REFERENCES

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer OB and handling Editor declared their shared affiliation and the handling Editor states that the process nevertheless met the standards of a fair and objective review.

*Copyright © 2017 Forsell, Kvastad, Sedimbi, Andersson and Karlsson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*


*3.1. Transcriptional Regulation*

To date, numerous instances of transcriptional regulation of TCTP synthesis have been reported [5], but precise mechanistic investigations were only performed in a few cases. Thiele and coworkers demonstrated that TCTP synthesis is induced by phorbolester (PMA) through the cAMP-PKA signalling pathway and activation of transcription factor CREB [58]. They also studied the regulation of TCTP expression under stress conditions, such as heavy metals, and showed that copper induced TCTP synthesis at both the transcriptional and the translational level [59]. Several similar studies showed that TCTP is transcriptionally regulated under a variety of stress conditions [5].

Of particular relevance for cancer research was the demonstration that the tumor suppressor protein p53, acting as a transcription factor, negatively a ffects TCTP expression [40]. Since p53 is frequently mutated in cancers, this contributes to the observed deregulation of TCTP synthesis in cancers. A more recent paper reported another example of transcriptional regulation of TCTP expression [31]. The authors studied a specific transcription factor, insulin-response element binding protein 1 (IRE-BP1), whose decreased expression in insulin target tissues contributes to the development of insulin-resistant diabetes in rats. Normally, insulin-induced PI3K signalling results in the proteolytic cleavage of IRE-BP1 and release of the active C-terminal fragment of the protein. In order to study the target genes of IRE-BP1, the investigators analysed the proteome of pancreatic islets from transgenic mice overexpressing the active fragment of IRE-BP1, compared to the corresponding proteome from control mice. The overexpression of two of the identified target genes of IRE-BP1 in the transgenic mice was further confirmed by Western blotting, specifically the genes for RACK1 and for TCTP. Moreover, the authors discovered the interaction of RACK1 with TCTP by Co-IP experiments [31].


**About the Editor**

**Anne Humeau-Heurtier** received her Ph.D. degree in Biomedical Engineering in France. She is currently a full professor in Engineering at the University of Angers, France. Her research interests include signal and image processing, mainly multiscale and entropy-based analyses and data-driven methods.


Author details

Brian Albert Robson The Australian National University, Canberra, Australia

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapteris distributed underthe terms oftheCreative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


**9. AT, Coronavirus Disease 2019 (COVID-19), and Antioxidants**

AT is one of the essential tissues that modulate innate and adaptive immune responses in the body. This tissue modulates these responses by secreting adipokines such as leptin and adiponectin. However, during obesity, the function of this tissue is impaired. This means that the secretion of leptin and adiponectin increases and decreases, respectively, and eventually, the immune system's role is impaired [109]. In such cases, the chest wall is also affected by fat accumulation and impairs the lungs' proper functioning [110]. One of the consequences of an impaired immune system is the induction of inflammatory cytokines and the development of viral infections such as COVID-19 due to reduced natural killer (NK) cell activity. This infectious disease is caused by SARS-COV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) (Figure 2) [111–113].

**Figure 2.** During obesity, adipose tissue (ATs) function is impaired, and secretion of leptin and adiponectin increases and decreases, respectively. Moreover, the immune system's function is impaired. One of the consequences of an impaired immune system is the induction of viral infections such as COVID-19 due to reduced natural killer (NK) cell activity. COVID-19 requires binding to the Angiotensin-Converting Enzyme 2 (ACE2) receptor and porphyrins on the cell surface to enter and then infect fat cells. Eventually, heme oxygenase-1 (HO-1) and ROS levels decrease and increase, respectively [109–113].

COVID-19 was first seen in December 2019 in Wuhan Province, China. Then, in January 2020, the disease's first cases were reported outside China (one in Japan and two in Thailand). Since then, the disease has spread rapidly to all countries of the world [114,115]. The condition was declared a pandemic on 11 March 2020, by WHO on 11 March 2020, and to date (22 February 2021), the total number of infected patients has reached 112,045,556, of which 2,479,625 people lost their lives (https://www.worldometers.info/coronavirus/, accessed on 20 February 2021). The virus requires binding to the Angiotensin-Converting Enzyme 2 (ACE2) receptor and porphyrins on the cell surface to enter and then infect fat cells. Eventually, heme oxygenase-1 enzymes (HO-1) and ROS levels decrease and increase, respectively [116–118].

Fatigue, headache, fever, and loss of taste and smell are symptoms associated with this disease, and most of these infected people recover without hospitalization. Various studies examining healthy people and people with underlying conditions have shown

that people with cardiovascular disease, kidney damage, diabetes, and severe obesity (BMI ≥ 30 kg/m2) are more susceptible to the virus [119]. The risk of developing COVID-19 does not depend on age, and the severity of the disease follows a different pattern at each age. According to Public Health England (PHE), the risk of COVID-19 death in people with a BMI between 35 and 40 kg/m2 increases by 40%. However, this increase of risk in people with a BMI ≥ 40 kg reaches 90% [120]. As mentioned, obesity is directly related to COVID-19 disease and leads to increased inflammation, mitochondrial dysfunction, and increased ACE2 receptors. Numerous studies have shown that high BMI (≥30 kg/m2) and excess visceral fat (VF) are effective methods in diagnosing the severity of COVID-19, especially in obese patients [115,119,121].

For more than a year, the COVID-19 disease has affected human society in all aspects of life. The medical community has been able to develop effective vaccines against the disease. Furthermore, scientists in authoritative articles have suggested various drugs and nutrients reduce inflammation in the immune system, indirectly helping cure the disease. Among the various nutrients, antioxidants (vitamins C, D, and E, iron, and selenium) have always been at the forefront of strengthening the immune system and reducing inflammation in various body tissues, especially AT [122]. The recommended dose of vitamins C, D, and E in healthy individuals is 200 mg/day, 2000 IU/day (50 μg/day), and 15 mg/day, respectively. However, in patients who have inflammation in their immune system, it is better to increase the daily intake of vitamin C to 1-2 gr. It has also been suggested that the daily dose of vitamin D in these patients be increased to 10,000 IU in the first few weeks and then continued at a dose of 5000 IU. Also, the daily intake of vitamin E in these patients should be increased to 200 IU [123,124]. Consumption levels of another nutrient, iron, are usually about 8 mg daily in men, approximately 18 mg in women between the ages of 19 and 50, and around 8 mg in women over 51 years of age. However, if the person has inflammation in the immune system, 60 mg Fe should be consumed daily in both men and women and all age groups [114]. The daily intake of selenium in healthy men and women is 50 μg, respectively, but in inflammatory conditions, this amount increases to 200 μg per day [125].


**3.6 Steric effect**

comparison studies revealed that the metal complex formed from chelating ligands are thermodynamically more stable than the complex formed from monodentate ligand. For example, formation of complexes from hydrated cadmium ion,

2þ < ½ � Cd en ð Þ 2þ <½ � Cd trien ð Þ 2þ

A macrocyclic ligand is a cyclic molecule that contains nine or more atoms in

Resonance increases the stability of the complexes. For example, acetylacetonate

anion ligand shows resonance, and as a result it forms stable complexes upon reacting with metal ion (**Figure 1**). The ligand-metal π bonding increases the delocalization of electrons compared to free enolate as shown below and leads to

the cyclic structure and has three or more potential donor atoms which can coordinate to the metal ion. It has been observed that the stability of metal complexes in the presence of macrocyclic ligand of appropriate size is higher than the stability of complexes coordinated to open-ended multidentate chelating ligands. Some notable examples of macrocyclic ligands include cyclic crown

netetramine (trien), and their stability is in the following order:

Cd CH ð Þ 3NH2 4

*Stability and Applications of Coordination Compounds*

2+ with methylamine (CH3NH2), ethylenediamine (en) and triethyle-

[Cd(H2O)4]

**3.4 Macrocyclic effect**

polyether, heme, etc. [12].

increased stability (**Figure 2**).

*Resonance structure of acetonylacetonate ligand.*

**3.5 Resonance effect**

**Figure 1.**

**Figure 2.**

**30**

*Acetonylacetonate-metal complex.*

The presence of bulky substituents in the ligands can affect the stability of the metal complex, and this type of destabilization of metal complex due to bulkiness of the substituent is called as steric effect [13]. For example, consider the ligand 8-hydroxy quinoline and its methyl substituted derivative 2-methyl-8-hydroxy quinolone. Both are bidentate ligands and form chelated complexes with Ni2+ ion as shown in **Figure 3**.

**Figure 3.** *Chelating complexes of Ni(II) ion showing steric effect.*

The complex (II) is less stable than complex (I) because of bulky group attached to an atom adjacent to donor atom which cause a steric hindrance and lower the stability of the complex.

#### **3.7 Crystal field stabilization energy (CFSE)**

The crystal field stabilization energy (CFSE) is one of the most important factors that decides the stability of the metal complexes. CFSE is the stability that arises when a metal ion coordinates to a set of ligands, which is due to the generation of a crystal field by the ligands. Thus, a higher value of CFSE means that the complex is thermodynamically stable and kinetically inert. Some of the notable examples of complexes that have high CFSE are low spin 5d6 complexes of Pt4+ and Ir3+ and square planar 5d8 complexes of Pt2+. All these complexes are thermodynamically stable and kinetically inert, which undergo ligand substitution reactions extremely slowly [3, 4].


**5. Conclusions**

In this paper, we have identified several properties of *q*-cosine Euler polynomials and *q*-sine Euler polynomials. In addition, the relationship between polynomials was confirmed according to the various conditions of the variables. We were able to assume the structure of the approximate roots of the *q*-cosine Euler polynomials and the *q*-sine Euler polynomials and finally, produce some speculations. The structure of the approximate roots will come out in various ways depending on the condition of the variables, and new methods and theorems related to approaching this needs to be created and proved.

**Author Contributions:** Conceptualization, J.Y.K.; Data curation, C.S.R.; Formal analysis, C.S.R.; Methodology, J.Y.K.; Software, J.Y.K.; Writing—original draft, J.Y.K. These authors contributed equally to this work. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (No. 2017R1E1A1A03070483).

**Acknowledgments:** The authors would like to thank the referees for their valuable comments, which improved the original manuscript in its present form.

**Conflicts of Interest:** The authors declare that there is no conflict of interests regarding the publication of this paper.


*Regular Physical Activity Influences Gut Microbiota with Positive Health Effects DOI: http://dx.doi.org/10.5772/intechopen.110725*

The use of probiotics has recently received increasing attention. Probiotics have potential health benefits, generally improving or restoring the gut microbiota, and have been shown to modulate the immune system. Recent studies have shown that probiotics reduce upper respiratory tract illness (URTI) and the onset and severity of gastrointestinal symptoms as well as gut barrier function impairment during intense exercise. By improving the immune system, they indirectly influence the performance of athletes by preventing diseases that negatively affect healthy exercise. Through SCFAs produced by probiotic bacteria, they contribute to improved energy production and reduce inflammation in the gut of physically active individuals. Selected probiotic strains have been associated with improved body composition and lean body mass, improved recovery from muscle-damaging exercise, normalization of age-related decline in testosterone levels, and reduction in cortisol levels and exerciseinduced lactate. The use of probiotics is a promising approach to improve the health, well-being, and performance of athletes.