identification-mouse-human-antibody-repertoires-next-generation

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

The immense adaptability of antigen recognition by antibodies is the basis of the acquired immune system. Despite our understanding of the molecular ...

Kwansei Gakuin University

The transcription factor E2F is the principal target of the tumor suppressor pRB. E2F plays crucial roles not only in cell proliferation by activating growth-related genes but also in tumor suppression by activating pro-apoptotic and growth-suppressive genes. We previously reported that, in human normal fibroblasts, the tumor suppressor genes ARF, p27(Kip1) and TAp73 are activated by deregulated E2F activity induced by forced inactivation of pRB, but not by physiological E2F activity induced by growth stimulation. In contrast, growth-related E2F targets are activated by both E2F activities, underscoring the roles of deregulated E2F in tumor suppression in the context of dysfunctional pRB. In this study, to further understand the roles of deregulated E2F, we explored new targets that are specifically activated by deregulated E2F using DNA microarray. The analysis identified nine novel targets (BIM, RASSF1, PPP1R13B, JMY, MOAP1, RBM38, ABTB1, RBBP4 and RBBP7), many of which are involved in the p53 and RB tumor suppressor pathways. Among these genes, the BIM gene was shown to be activated via atypical E2F-responsive promoter elements and to contribute to E2F1-mediated apoptosis. Our results underscore crucial roles of deregulated E2F in growth suppression to counteract loss of pRB function. 

Identification of novel target genes specifically activated by deregulated E2F in human normal fibroblasts.

G Protein-Coupled Receptors (GPCRs) are important pharmaceutical targets. More than 30% of currently marketed pharmaceutical medicines target GPCRs. Numerous studies have reported that GPCRs function not only as monomers but also as homo- or hetero-dimers or higher-order molecular complexes. Many GPCRs exert a wide variety of molecular functions by forming specific combinations of GPCR subtypes. In addition, some GPCRs are reportedly associated with diseases. GPCR oligomerization is now recognized as an important event in various biological phenomena, and many researchers are investigating this subject. We have developed a support vector machine (SVM)-based method to predict interacting pairs for GPCR oligomerization, by integrating the structure and sequence information of GPCRs. The performance of our method was evaluated by the Receiver Operating Characteristic (ROC) curve. The corresponding area under the curve was 0.938. As far as we know, this is the only prediction method for interacting pairs among GPCRs. Our method could accelerate the analyses of these interactions, and contribute to the elucidation of the global structures of the GPCR networks in membranes. Proteins 2016; 84:1224-1233. © 2016 Wiley Periodicals, Inc.

GGIP: Structure and sequence-based GPCR-GPCR interaction pair predictor.

The amino acid substitutions at a site are affected by mixture of various constraints. It is also known that the amino acid substitutions are accelerated at sites under positive selection. However, the relationship between the substitutions at positively selected sites and the constraints has not been thoroughly examined. The advances in computational biology have enabled us to divide the mixture of the constraints into the structural constraint and the remainings by using the amino acid sequences and the tertiary structures, which is expressed as the deviation of the mixture of constraints from the structural constraint. Here, two types of profiles, or matrices with the size of 20 x (site length), are compared. One of the profiles represents the mixture of constraints, and is generated from a multiple amino acid sequence alignment, whereas the other is designed to represent the structural constraints. We applied the profile comparison method to proteins under positive selection to examine the relationship between the positive selection and constraints. The results suggested that the constraint at a site under positive selection tends to be deviated from the structural constraint at the site. 

Profile comparison revealed deviation from structural constraint at the positively selected sites.

Vast diversity and high specificity of antigen recognition by antibodies are hallmarks of the acquired immune system. Although the molecular mechanisms that yield the extremely large antibody repertoires are precisely understood, comprehensive description of the global antibody repertoire generated in individual bodies has been hindered by the lack of powerful measures. To obtain holistic understanding of the antibody-repertoire space, we used next-generation sequencing (NGS) to analyze the deep profiles of naive and antigen-responding repertoires of the IgM, IgG1, and IgG2c classes formed in individual mice. The overall landscapes of naive IgM repertoires were almost the same for each mouse, whereas those of IgG1 and IgG2c differed considerably among naive individuals. Next, we immunized mice with a model antigen, nitrophenol (NP)-hapten linked to chicken γ-globulin (CGG) carrier, and compared the antigen-responding repertoires in individual mice. To extract the complete antigen response, we developed an intelligible method for detecting common components of antigen-responding repertoires. The major responding antibodies were IGHV1-72/IGHD1-1/IGHJ2 for NP-hapten and IGHV9-3/IGHD3-1/IGHJ2 for CGG-carrier protein. The antigen-binding specificities of the identified antibodies were confirmed through ELISA after antibody-gene synthesis and expression of the corresponding NGS reads. Thus, we deciphered antigen-responding antibody repertoires by inclusively analyzing the antibody-repertoire space generated in individual bodies by using NGS, which avoided inadvertent omission of key antibody repertoires.

Deciphering antigen-responding antibody repertoires by using next-generation sequencing and confirming them through antibody-gene synthesis.

The pre-B cell receptor (pre-BCR), consisting of the μ heavy chain (μHC) and the surrogate light chain (SLC, Vpre-B and λ5), plays important roles during B cell development. The formation of the pre-BCR, which enables the nascent immunoglobulin HC to associate with the SLC, is considered a prerequisite for B cell development. However, a significant number of peripheral mature (leaky) B cells exist in SLC-deficient mice. These leaky B cells develop in the absence of pre-BCR and do not undergo the pre-BCR checkpoint. The antibody repertoires of leaky B cells thus reflect the absence of pre-BCR function. To investigate how the absence of the pre-BCR is circumvented by these leaky-B cells and examine the effect of the pre-BCR checkpoint on the antibody system, we analyzed the antibody repertoires of λ5-deficient (λ5) mice using next-generation sequencing. In λ5 mice, spleen B cells displayed different patterns of VDJ-usage, relative to those in wild-type (WT) mice. Moreover, leaky B cells were neither derived from unusual B2 cells, characterized by particular LC gene rearrangements in the absence of pre-BCR signaling, nor from B1 cells, originating from different B cell progenitors. Analysis of the CDR-H3 amino acid sequences of μ-chain repertoires revealed that certain bone marrow B cells with particular CDR-H3 profiles undergo clonal expansion in λ5 mice. Part of these CDR-H3s contain arginine(s) in the middle of the CDR-H3 loop in λ5 mice, whereas few arginine(s) exist in this middle loop in WT CDR-H3s in the absence of clonal expansion. This CDR-H3 feature in λ5 mice presumably reflects the role of the pre-BCR in autoantibody regulation, since arginine(s) are often found in the antigen-binding site of autoantibodies. Here, we present a unique viewpoint on the role of pre-BCR, by assessing the whole antibody repertoire formed in SLC-deficient mice.

Article	Year
Identification of novel target genes specifically activated by deregulated E2F in human normal fibroblasts. Genes to cells : devoted to molecular & cellular mechanisms\| PubMed ID: 26201719	2015
GGIP: Structure and sequence-based GPCR-GPCR interaction pair predictor. Proteins\| PubMed ID: 27191053	2016
Profile comparison revealed deviation from structural constraint at the positively selected sites. Bio Systems\| PubMed ID: 27443483	2016
Deciphering antigen-responding antibody repertoires by using next-generation sequencing and confirming them through antibody-gene synthesis. Biochemical and biophysical research communications\| PubMed ID: 28412367	2017
Distorted antibody repertoire developed in the absence of pre-B cell receptor formation. Biochemical and biophysical research communications\| PubMed ID: 29191653	2018

Hiroyuki Toh

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