- Email: [email protected]
High-throughput sequencing reveals the diversity of TCR β chain CDR3 repertoire in patients with severe acne
Molecular Immunology 120 (2020) 23–31
Contents lists available at ScienceDirect
Molecular Immunology journal homepage: www.elsevier.com/locate/molimm
High-throughput sequencing reveals the diversity of TCR β chain CDR3 repertoire in patients with severe acne
T
Lei Shaoa,b,1, Yumei Liua,b,1, Junpu Meic,1, Dongmei Lid, Lijie Chena,b, Qingli Pana,b, Shujuan Zhanga,b, Xiangnong Daia,b, Jingyao Lianga,b,*, Silong Sunc,*, Jianqin Wanga,b,* a
Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, PR China Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, PR China c BGI Genomics, BGI-Shenzhen, Shenzhen 518083, PR China d Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, DC, USA b
A R T I C LE I N FO
A B S T R A C T
Keywords: Acne vulgaris Repertoire TCR CDR3 High-throughput sequencing
Acne is a common chronic inflammatory skin disease, and the inflammation immune response runs through all stages of acne lesions. In this study, we use a combination of multiplex-PCR and high-throughput sequencing technologies to analyze T cell receptor β chain CDR3 (complementarity-determining region 3) in peripheral blood isolated from severe acne patients. Once compared with healthy controls, we propose to identify acnerelevant CDR3 peptides. Our results reveal that the diversity of T cell receptor β chain (TRB) CDR3 sequences in the peripheral blood of the severe acne vulgaris (SA) group differed from that of the control group. In addition, we find 10 TRB CDR3 sequences, amino acid sequences and V-J combinations with significantly different expressions between the SA group and the non-acne (NA) group (P < 0.0001). These findings may contribute to a better understanding of the role of immunity in the pathogenesis of acne and may serve as biomarkers for evaluating risk or prognosis of severe acne disease in future.
1. Introduction Acne is a chronic inflammatory condition that is estimated to affect approximately 85 % of the population at some point in their lives (Thiboutot et al., 2018). Males were more frequently affected, particularly presenting with more severe forms of acne (Tan and Bhate, 2015). Although it is a benign condition, acne can exert some distress, including pain and discomfort, permanent scarring, and depression and anxiety leading to poor self-esteem, especially in patients with severe acne (Bhate and Williams, 2013; Farrar and Ingham, 2004). Inflammatory immune response has been demonstrated in all types of acne lesion including the preclinical microcomedo, comedones, inflammatory lesions, ‘post-inflammatory’ erythema or hyperpigmentation, and scarring (Dreno et al., 2015). The immune mechanism studies on acne have rapidly increased with better-appreciated molecular and cellular technologies. Currently, it is believed that patients with severe acne result from an increased cellular as well as humoral immune response to Propionibacterium acnes (P. acnes), demonstrated by significantly higher levels of complement fixing antibodies to P. acnes than individuals with mild acne or control
cases (Jappe et al., 2002). The correlation between inflammatory response and level of severity is reflected in the fact that the highest level of antibodies presents with the most severe disease (Ashbee et al., 1997). Furthermore, accumulating evidence has shown that T lymphocytes play an important role in the occurrence and development of acne. Indeed, immunological studies on acne have shown that the initial infiltrate into the acne lesion is lymphocytic, with later progression to a general infiltrate of mixed cell types with CD4+ cells predominating in which P. acnes plays an active role as well in the chronification of the inflammatory process (Moreno-Arrones and Boixeda, 2016; Norris and Cunliffe, 1988). Previous studies have suggested that P. acnes induces T-cell proliferation (Jappe, 2000), and these P. acnes-specific T helper 1(Th1) lymphocytes are presented in early inflamed acne lesions (Mouser et al., 2003). Kistowska M. et al. (Kistowska et al., 2015) showed that both P. acnes-specific Th 17 and Th 17/ Th 1 lymphocytes cells were more frequently found in the peripheral blood samples of patients suffering from acne than healthy individuals. T cell receptor (TCR) is a complex of integral membrane proteins on the cell surface of T lymphocytes that play key roles in adaptive
⁎
Corresponding authors at: Department of Dermatology, Guangzhou Institute of Dermatology, 56 Hengfu Road, Guangzhou 510095, PR China. E-mail addresses: [email protected] (J. Liang), [email protected] (S. Sun), [email protected] (J. Wang). 1 These three authors contributed equally to this work. https://doi.org/10.1016/j.molimm.2020.01.024 Received 9 April 2019; Received in revised form 16 January 2020; Accepted 31 January 2020 0161-5890/ © 2020 Elsevier Ltd. All rights reserved.
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
2.4. High-throughput sequencing and data analysis
immune responses (Miles et al., 2015). Healthy adults have approximately 2.5 × 108 unique TCRs in the peripheral blood, forming a highly specific immune response to ward off a wide variety of foreign antigens (Robins et al., 2009). In peripheral blood, more than 90 % TCRs consist of α chain and β chain. During T cell development the Variable (V), Diversity (D), Joining (J), and constant gene segments of each chain undergo somatic rearrangement and recombination. In addition, the random insertion and deletion of nucleotides to the V-D-J junctions of the β chain create an additional hypervariable complementary determining region-3 (CDR3), which comes into direct contact with the antigenic peptides bound by major histocompatibility complex molecules (Arstila et al., 1999; Garcia et al., 1999; von Budingen and Skulina, 2003). As CDR3 represents the most diverse and complex portion of the variable region, the diversity of CDR3 amino acid sequences provides a measure of T cell diversity in an antigenselected T cell repertoire (Hou et al., 2016b). In this work, we applied high-throughput sequencing technologies and multiplex-PCR to analysis TCR β chain (TRB) CDR3 repertoire in peripheral blood of patients with severe acne vulgaris to study the distinctive features of CDR3 in acne in order to identify acne-relevant CDR3 peptides by comparing patients with healthy controls.
The PCR products were sequenced on the Illumina sequencing platform. As raw data generated, we first filtered the raw data including adapter contamination (SOAPnuke software v 1.5.6; command: -l 15 -q 0.5 -n 0.1; https://github.com/BGI-flexlab/SOAPnuke). Reads with average quality score below 15 (Illumina 0–41 quality system) and with the proportion of N bases more than 5 % were removed. Also, reads with few bases and low quality (≤ 10) were removed, whereupon the remaining sequence lengths were more than 60 nt. After filtering, pairend (PE) read pairs were merged into one contiguous sequence. The merging process was carried out in two steps. First, aligning the tail parts of two sequences and assessing their identity (BGI developed software COPE v1.1.3; open-source code at ftp://ftp.genomics.org.cn/ pub/cope) (Liu et al., 2012). An overlap of at least 10 bases is required and the overlapped section should have a better than 90 % match of all bases. Second, since different primers might result in sequences of different lengths, it may happen that some might be too short (less than 100 bp) and go through all bases on the sequencing. In this case, reads were merged by aligning the head part of the sequence (BGI developed software FqMerger). After we had the merged contiguous sequences and the length distribution plot, we next used miTCR, developed by MiLaboratory (http://mitcr.milaboratory.com/downloads/), to perform the final alignment. This program has an automated adjustment mechanism for errors introduced by sequencing and PCR. Subsequently, it will provide alignment statistical information, such as the CDR3 expression and INDEL (insertion and deletion). After sequence alignment, the expression level of each clonotype was calculated. The frequency and frequency distribution of clonotypes of the DNA sequence, amino acid sequence and V-J combination in the CDR3 region were also analyzed. In addition, the diversity of the TCR repertoire was calculated based on the Gini-Simpson index (G-D) and the Shannon–Wiener index (H′) (Jiang et al., 2017; Keylock, 2010) of distinct DNA sequences, amino acid sequences, and V–J combinations. D and H′ were calculated by the following formulae respectively:
2. Materials and methods 2.1. Patients and controls Five severe acne patients who were diagnosed according to the standard of severe acne vulgaris of global acne grading system (GAGS) (Doshi et al., 1997) and 5 healthy individuals were recruited at Guangzhou Institute of Dermatology between August 2016 and October 2016. All of the 5 severe acne patients are male (mean age of 20.80 ± 2.86 years, ranging from 17 to 24 years and GAGS score of 33.60 ± 1.82, ranging from 32 to 36. 5 healthy subjects matched for age, sex, BMI and ethnicity served as controls. There were no significant differences in their health conditions between severe acne vulgaris (SA) group and non-acne (NA) group (Table S1). Written informed consent was obtained from all subjects in the study. This study was approved by the ethics committee of the Guangzhou Institute of Dermatology and adhered to the tenets of the Declaration of Helsinki.
G− D = 1 − m
H'= −∑
i=1
m
∑i =1 pi2
pi lnpi
Here we assume there are m species (types of CDR3) in an assemblage and species (types of CDR3) are indexed by i = 1, 2, …, m. Let pi denote the relative abundance of the ith repertoires.
2.2. DNA extraction Whole peripheral blood sample (5 ml) was collected from the participants. PBMCs were isolated from whole peripheral blood using lymphocyte separation medium by density gradient centrifugation, and then T cells from PBMCs by magnetic beads. DNA was extracted from 0.5 to 2.5 × 106 T cells using GenFIND DNA (Agencourt, Beckman Coulter, Brea, CA, USA) extraction kits following the manufacturer’s instructions and stored at −80 °C until used.
2.5. Statistical analysis The statistical analyses were conducted with SPSS20.0 statistical software (Chicago, IL, USA). Data were processed and mapped with GraphPad Prism V.6.0 (GraphPad Software, San Diego, CA, USA) and Excel 2016 (Microsoft, Redmond, WA, USA). The differences between groups were compared by using the Mann-Whitney U test For the expression of each single clone, P-values are based on Poisson distribution model alone with FDR and Bonferroni correction. P < 0.05 was considered statistically significant.
2.3. Multiplex-PCR amplification of the TRB CDR3 region As previous study described (Xiong et al., 2019), TCRβ CDR3 regions were amplified and sequenced by BGI Tech (Shenzhen, China). Briefly, TCR CDR3 regions from genomic DNA were rearranged by Multiplex-PCR, using 45 forward primers specific to functional TCRβ CDR3 V regions and 12 reverse primers specific to a TCR J segment (Tables S2 and S3). After amplification and agarose gel electrophoresis selection, the products were purified using QIAquick PCR Purification Kit. The final library was quantitated in two ways: by ABI Step One Plus Real-Time PCR System (TaqMan Probe) and by determining the average molecule length using the Agilent 2100 bioanalyzer instrument (Agilent DNA 1000 Reagents). The libraries were amplified with cBot to generate the cluster on the flow cell, and the amplified flow cell was pairend sequenced using a Hiseq2000 instrument.
3. Results 3.1. TRB CDR3 sequences and data analysis Using high-throughput sequencing (Illumina Genome Analyzer), we sequenced TCR repertoires from T cells collected from the blood of five NA samples and five SA patients, obtaining a sun of 305,476,043 total raw reads and 322,022,783 total raw reads (pairs) in SA group and NA group, respectively. After filtering and removal of adaptor sequences, contamination and low-quality reads, we collected an average of 64,186,240.2 total raw reads per SA group and 60,845,102.8 total raw 24
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Table 1 TRB CDR3 sequences statistics of samples. Sample
Total reads(pair)
Filter rate (%)
All reads number
Total input sequences
Total good sequences
Sequencing information utilization(%)
Clones
Out of frame clones (%)
SA1 SA2 SA3 SA4 SA5 NA1 NA 2 NA 3 NA 4 NA 5
59526894 56248809 65173653 68864126 55662561 73141022 61757879 62558031 47711732 76854119
0.43 0.44 0.59 0.26 0.32 0.35 0.33 0.36 0.30 0.35
59271448 55998415 64787336 68685479 55482836 72885997 61556021 62335109 47570614 76583460
54617796 51767906 56022046 62070771 51695897 68251214 55398490 56817425 45266538 68745656
37431447 31450205 33047084 41182690 34709809 48979770 45727216 41348048 39686356 46043888
68.53 60.75 58.99 66.35 67.14 71.76 82.54 72.77 87.67 66.98
163462 135751 142278 166702 157525 180217 126230 141425 123242 164590
35.52 31.85 30.99 32.20 34.96 39.03 42.85 44.13 42.62 34.43
SA: severe acne vulgaris; NA: non- acne vulgaris.
index increases both when the number of types increases and when evenness among the types increases. To show whether the overall TCR clonal expansion exhibits evenness, we first summarize the unique clonotype distribution according to their abundance in each subject by a power-law distribution (Fig. 3). To produce comprehensive unrestricted profiles of TRB CDR3 repertoire diversity, we calculate the 1/(G-D) and H′ of each sample. The diversity increases as H′ increases, but decreases as 1/(G-D) increases. In our research, 1/(G-D) was lower in the SA group compared with the NA group at the DNA level, at the amino acid level and at the V-J level (Fig. 4a–c). We also found that H′ was higher in the SA group compared with the NA group at the DNA level, the amino acid level and the V-J level (Fig. 4d–f).
reads per NA group that met the quality requirements. The average clonotypes of TRB CDR3 in the SA group was higher than in the NA group. The total reads, all read numbers, total input sequences, total good sequences, and total clonotypes (distinct CDR3 sequences) per sample are shown in Table 1. 3.2. Distribution characteristics of amino acid length and TRBV/J/D gene usage analysis One of the key determinants of T cell repertoire diversity is the length of the TCR CDR3 loop. In the present study, we found that the amino acid length with a peak at 15 nt for the SA group and at 14 nt for the NA group. The 5 most frequently observed CDR3 lengths in both groups were 12, 13, 14, 15 and 16 nt, respectively (Fig. 1). Both the SA group and the NA group had the same V gene usage types, but with a slight difference in the cumulative frequencies. For example, the frequencies of TRBV2, TRBV7-2, TRBV19, TRBV20-1, V29-1 loci were higher in the SA samples, whereas the frequencies of TRBV4-1, TRBV4-2, TRBV6-5, TRBV7-8, TRBV10-1 were lower when compared with samples from the NA group (Fig.2a). In the J gene usage analysis, preference for TRBJ1-5, TRBJ2-1 and TRBJ2-7 loci was seen in SA samples, rather than TRBJ1-6, TRBJ2-3, and TRBJ2-5 loci (Fig.2b); as for D gene usage bias analysis, both groups demonstrated similar patterns, without an obvious preference (Fig. 2c).
3.4. The repertoire features of T cell with different clonotype abundance According to the CDR3 sequence frequency, CDR3 is divided into 5 groups (≥0.1 %, 0.01–0.1 %, 0.001–0.01 %, 0.0001–0.0.1 %, and ≤0.00.1 %, respectively), and we defined clones with a frequency of ≥ 0.1 % of the analyzed TCR to be highly expanded clones (HECs). A summary of TRB CDR3 and amino acid HECs sequences is presented in Supplemental Tables S4 and S5. In the two groups, the TRB CDR3 sequences were composed of a small number of high abundance clones and a large number of low abundance clones. Our results indicated that there was no significant difference among two groups in 5 expanded clone levels (Table 2 and Fig. 5). Rare clonotypes, which were detected as single copy, represented on average 55.29 % of all unique CDR3 sequence clonotypes per sample in the SA group and 60.37 % in the NA group, which we view as significantly different (p = 0.008). Using sample SA4 as an example, a total of 62 HECs (0.037 % of all the unique CDR3 sequences) accounted for 21.745 % of the T cell
3.3. The diversity of TRB CDR3 from samples A diversity index is a quantitative measure that reflects how many different types (such as species) there are in a dataset, and simultaneously takes into account how evenly the basic entities (such as individuals) are distributed among those types. The value of a diversity
Fig. 1. Length distribution of TRB CDR3 amino acid of the SA group (n = 5) and NA group (n = 5) (average of each group's). The amino acid length shown a peak at 15 nt of SA group and 14 nt of NA group. The 5 most frequently observed CDR3 lengths in both groups were 12, 13, 14, 15 and 16 nt, respectively. 25
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Fig. 2. Relative frequencies of each TRBV gene (a), TRBJ gene (b) and TRBD (c) gene family of SA group and NA group.
Fig. 3. The power-law distributions of TCR diversity of each sample (5 samples of SA group and 5 samples of NA group). The power-law distributions of diversity of each sample was calculated at different resolutions of distinct DNA (a), amino acid (b), and V–J (c).
sequences (total reads), whereas 92.344 % (n = 153940) of clones were very low-frequency clones (present at < 0.0001 % of all TCR sequences analyzed), which accounted for only 1.52 % of the T cell sequences that were present (total reads). The TGCAGTGCTAGGACCGCCGGGACTAG TGGCGGGGAGCTGTTTTTT sequence (clonotype abundance up to 879914) accounted for 2.137 % of the T cell sequences in the repertoire of donor SA4. This sequence was found in all severe acne samples (clonotype abundance were 4366, 3486, 4344, 3866 reads, respectively), while no read was found in the NA group.
acid sequences (Fig. 6a). The shared sequences number of the NA group was significantly lower than that of the SA group, which is 700 (0.42 %, 0.61 %, 0.54 %, 0.63 %, 0.46 %) (Fig. 6b). Next, we investigated whether HECs overlap between different individuals of the same group. However, we found no HECs sequence overlap within any group (Data not shown).
3.5. Patterns of TRB CDR3 sequences sharing among subjects
To investigate further, we filtered the top 10 TRB CDR3 sequences, amino acid sequences and V-J combinations in the SA group (Table 3) and NA group (Table 4), respectively. These top 10 TRB CDR3 sequences and amino acid sequences in SA were not shown in the control group. For example, the sequence, TGCAGTGCTAGGACCGCCGGGACT
3.6. The significant change in TRB CDR3 sequences, amino acid sequences and V-J combinations in SA group and NA group
UpSet plot was used to analyze the shared sequences of amino acid in SA group and NA group. We found that the SA group share 37677 24.62 %, 29.50 %, 28.28 %, 24.28 %, 25.55 %) of TRB CDR3 amino 26
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Fig. 4. Comparison of TCR diversity of the SA group and NA group. Comparison of the diversity of 1/(G-D) SA group and NA group in CDR3 sequences (a), amino acid sequences (b), and V-J combinations(b). Comparison of the diversity of (H′) SA group and NA group in CDR3 sequences (d), amino acid sequences (e), and V-J combinations(f).
the SA group except for one amino acid sequence, CASSAGTSGRSDTQYF, that appeared once in sample SA1. In the SA group, the 10 most common expressions of V-J combinations were significantly lower in the NA group, and the differences were statistically significant (P < 0.0001).
Table 2 Degree of expansion of T cell clones. Degree of expansion (%)
≥0.1 0.01–0.1 0.001–0.01 0.0001–0.001 <0.0001
CDR3 sequences SA
NA
P
0.02± 0.012 1.98±0.28 3.27±0.96 3.55±0.30 91.18± 0.96
0.03±0.01 1.47±0.60 5.20±2.54 3.90±1.67 89.41± 3.51
0.894 0.119 0.15 0.654 0.309
4. Discussion T cells play a central role in host protection against infectious pathogens by TCRs and contribute to the development of autoimmune and allergic diseases. For acne pathogenesis, a study of TCR variable region β (BV) gene usage in acne lesions has shown that most TCR BV families are represented in both peripheral blood mononuclear cells (PBMCs) and inflamed lesions from 7 acne patients (Holland et al., 1995). Using flow cytometry, the TCR variable BV repertoire was also undertaken by comparing the unstimulated and stimulated T cells with P. acnes (Jappe et al., 2002) But little is known about the clonality of V, D and J gene segments, or of CDR3 sequences in acne pathogenesis. High-throughput sequencing technologies have shown the possibilities for the in-depth evaluation of TCR repertoires. This method has been applied to study a variety of diseases, including cancers, infectious diseases, autoimmune diseases, organ transplantation, and other diseases with multiple causative factors, such as diabetes, psoriasis vulgaris and drug-induced hypersensitivity syndrome. In the present study, we coupled high-throughput sequencing with multiplex-PCR amplification to characterize the basic properties of CDR3 in the SA patients. To the best of our knowledge, this is the first study to describe the diversity of acne vulgaris TRB CDR3 in an overall analysis. Because different T cell clones have different sequences and CDR3 lengths, the diversity of T cell clones can be reflected by studying the diversity of CDR3 (Gorski et al., 1994; Hohn et al., 2002). We evaluated the distributions of TRB CDR3 amino acid length based upon a total of 399,606,513 good sequence reads, and the most common sequences and lengths were then assessed. We found that there was no significant change in the lengths of amino acids in the CDR3 region between the two groups in this study. In this study, the amino acid length of the SA group and NA group varied from 4 to 50 nt, with a peak at 15 nt of SA group and 14 nt of NA group. However, the 5 most frequently observed CDR3 lengths in both groups had a similar distribution.
Fig. 5. Degree of expansion and frequency distribution of T cell clones.
AGTGGCGGGGAGCTGTTTTTT was shared by all 5 of the SA individuals (cloning accounting for 0.012 %, 0.0.1 %, 0.013 %, 2.137 %, 0.0.1 % reads, respectively and the expression frequency were 4366, 3486, 4344, 879,914, 3866, respectively, and this was not seen in any blood sample isolated from the NA group. Similarly, in the NA group, the top 10 of expression V-J combinations were significantly lower than in the SA group, and the differences were statistically significant (P < 0.0001). At the amino acid sequencing level, the 10 TRB CDR3 sequences filtered in the healthy control group were not expressed in 27
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Fig. 6. The extent of overlap of amino acid clonotypes in the NA group and SA group. The publicly shared TRB CDR3 amino acid sequences of total sequences in SA group (a), The publicly shared TRB CDR3 amino acid sequences of total sequences in NA group (b).
in healthy people, and the average number of CDR3 nucleotide clonotypes are spectacular up to 8,7125. HECs defined as clonotypes having an abundance beyond a cutoff value in their repertoires, but the cutoff value was not identified (Niu et al., 2015). At present, most studies used 0.1 % as the standard of HECs that showed 4.18 × 10−2 % of clones in healthy donors (Hou et al., 2016a; Lai et al., 2016). We found the large number of low frequency expanded clonotypes of TRB CDR3 at DNA and amino acid sequences, suggesting that these clones have not undergone clonal expansion. Our results were similar to those of most other inflammatory diseases in the previous studies (Cao et al., 2016; Clemente et al., 2013; Sui et al., 2015), a small number of HEC parts were present in each individual, which may be the result of physiological responses to pathogens or environmental antigens. Holland et al. (Holland et al., 1995) have shown that although mono- or oligoclonal and polyclonal expansions of VB families represented by T cells infiltrating acne lesions, the CDR3 size diversity of expressed VB genes is restricted to the monoor oligo-clonal expansions indicative of an antigen-driven response. Study of immune receptor repertoires was not possible before the advent of this high-throughput DNA sequencing technology when considering the dramatic discrepancy of TCRs between individuals. These new technologies allow us to better understand the overlap of TCR repertoire among individuals. For example, the identical TCRs
The diversity of the immune repertoire is vitally important for a healthy human being. Sui et al. (Sui et al., 2015) showed that the SLE patients have a very low TCR diversity at the nucleotide, the amino acid and V–J pair levels, when compared with the normal control group (Lai et al., 2016) found that the diversity of TCR repertoire in kidney transplantation group was relatively lower compared to normal control group. Different antigens can be recognized by different TCRs, and T cell function is closely associated with TCR diversity (Miyama et al., 2017). In this TCR diversity study in SA patients, we found that the diversity was significantly different from that of the control group, which may lead to immune imbalance that causes the chronicity in these patients. However, further studies should be conducted to explain the intricate interaction between the TCR diversity and immune imbalance. The cloning frequency is an important characteristic of T cells. Normally, in the absence of any antigen stimulation, T cells are in a positive polyclonal state. However, in the case of disease, specific antigen stimulation causes targeted T cell rearrangement and dramatic clonal expansion (Li et al., 2018). A type of TCR CDR3 corresponds to a type of T cell. Therefore, the frequency of the CDR3 region sequences can reflect the degree of the T cell clones and demonstrates the condition of immune function. Hou et al. (2016a) showed that the abundance of unique CDR3 sequence clonotype ranged from 1 to 2,836,517 28
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Table 3 The significant change in TRB CDR3 sequences, Amino acid sequences and V-J combinations in SA group. Clonotype
Public sequences
CDR3 nucleotide sequences
TGCAGTGCTAGGACCGCCGGGACTAGTGGCGGGGAGCTGTTTTTT ▲ TGCAGCGTGGAGGGACAGCCAAAAGAGACCCAGTACTTC ▲ TGCAGCGTTGAGGTCATATGATAGCAATCAGCCCCAGCATTTT ▲ TGCAGTGCCTCAGGATTTGCGGGGACTTTAAATGAGCAGTTCTTC▲ TGCAGTGTGACCGAACCCGGGTTTGTCAACATTCAGTACTTC ▲ TGCGCCAGCAGCTTGGAGCAGGGGGCGAGGACAGATACGCAGTATTTT ▲ TGTGCCACCAGCAGAGAAAGTCCGGGACAGGGTTGGTACGAGCAGTACTTC ▲ TGTGCCAGCAGCACCGGACTAGCGGAGGTCTTC▲ TGTGCCAGCAGTGAAGCGCCGGCTAGCGGGAGTCTACAATGAGCAGTTCTTC ▲ TGTGCCAGCAGTGAGAGCGGGAGCAGCACAGATACGCAGTATTTT ▲ CSVTEPGFVNIQYF▲ CASSLEQGARTDTQYF▲ CASSQTHSNQPQHF▲ CASSQTLRGRTNEQYF▲ CASSTGLAEVF▲ CATSRESPGQGWYEQYF▲ CSARTAGTSGGELFF▲ CSASGFAGTLNEQFF▲ CSVEGQPKETQYF▲ CASSFTGGVDTQYF▲ TRBV15,TRBJ2-1※ TRBV20-1,TRBJ2-1※ TRBV29-1,TRBJ1-1※ TRBV29-1,TRBJ2-1※ TRBV29-1,TRBJ2-2※ TRBV7-2,TRBJ2-2※ TRBV7-2,TRBJ2-7※ TRBV7-8,TRBJ1-5※ TRBV7-8,TRBJ2-1※ TRBV7-9,TRBJ2-3※
CDR3 amino acid sequences
V-J combinations
Note：▲ meanssequences filtrated in the SA group were not expressed in the NA group；※ means sequences significantly higher in the SA group, and the differences were statistically significant (P < 0.0001). Statistics based on Poison distribution model alone with FDR and bonferroni correction.
Table 4 The significant change in TRB CDR3 sequences, Amino acid sequences and V-J combinations in NA group. Clonotype
Public sequences
CDR3 nucleotide sequences
TGCAGCGTTGTGGGGCTAGAGTAGAAAAAAAACAAGAGACCCAGTACTTC ▲ TGCGCCAGCAGCCGAAACCCCACAGGGTCAGATTCACCCCTCCACTTT ▲ TGCGCCAGCAGTGCCGGGACTAGCGGACTCTCAGATACGCAGTATTTT▲ TGCGCCAGCAGTGCCGGGACTAGCGGGAGGTCAGATACGCAGTATTTT▲ TGTGCCAGCAGCAGATGGGGGAGCGGGAGGTCCTCCTACGAGCAGTACTTC ▲ TGTGCCAGCAGCCAAGAAGGACTAGCGGGAGGGAGAGACCCAGTACTTC ▲ TGTGCCAGCAGCCAAGAGGGCCCAGGGGGAAATTCACCCCTCCACTTT▲ TGTGCCAGCAGCTTAGTAGGCAGCACGCAGTATTTT▲ TGTGCCAGCAGTTACGCTGGGAGCACAGATACGCAGTATTTT▲ TGTGCCATCAAAACCGGGACAGACAATGAGCAGTTCTTC▲ CAIKTGTDNEQFF▲ CASSAGTSGLSDTQYF▲ CASSLVGSTQYF▲ CASSTWTGPQETQYF▲ CASSQEGPGGNSPLHF▲ CASSRNPTGSDSPLHF▲ CASSRWGSGRSSYEQYF▲ CASSYAGSTDTQYF▲ CASSRQGSYNEQFF▲ CASSAGTSGRSDTQYF※ TRBV10-2,TRBJ2-7※ TRBV28,TRBJ2-7※ TRBV3-1,TRBJ1-3※ TRBV3-1,TRBJ2-5※ TRBV5-1,TRBJ2-7※ TRBV6-1,TRBJ2-7※ TRBV6-4,TRBJ2-7※ TRBV6-5,TRBJ2-1※ TRBV6-5,TRBJ2-7※ TRBV6-6,TRBJ2-7※
CDR3 amino acid sequences
V J combinations
Note：▲ meanssequences filtrated in the NA group were not expressed in the SA group；※ means sequences significantly higher in the NA group, and the differences were statistically significant (P < 0.0001). Statistics based on Poison distribution model alone with FDR and bonferroni correction. 29
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Appendix A. Supplementary data
shared by multiple individuals in responding to a same antigenic epitope, namely public T cell response, have been observed in a variety of immune responses, including viral infections, tumorigenesis, and autoimmunity (Li et al., 2012). In the present study, we found that the number of sequences shared among SA individuals was obviously higher than in healthy individuals and nearly a quarter of the individuals in the severe acne group shared the same amino acid. Meanwhile, no HECs of amino acid were shared by different individuals. These findings reveal a likely important role of the immune response in the process of acne inflammation and the acne antigen contained polymorphisms. In this study, we found 10 TRB CDR3 sequences, amino acid sequences and V-J combinations that were highly relevant to the acne, including 1) those only expressed in severe acne samples and those significant upregulated in severe acne; 2) those only expressed in healthy controls. However, we are still uncertain which peptide or peptide pattern is the major driving force in the pathogenesis of acne. Also, it is not clear whether there is a difference in TRB CDR3 between different severities of acne. We speculate that there is not a certain TRB CDR3 peptide that plays a decisive role in the pathogenesis of acne, and perhaps the combined or sequential interaction of these peptides is a better explanation. Therefore, more studies with big sample size in future may help with identifying the pivotal peptides for acne. In conclusion, we successfully profile the unique features of TRB CDR3 repertoires in severe acne vulgaris using a combination of highthroughput sequencing and multiplex-PCR technology. Also, we proved that there is more shared amino acid sequencing in acne patients. Ultimately, we identified 10 TRB CDR3 sequences, amino acid sequences and V-J combinations that were significantly different expression between SA and NA groups. These specific T cell clones may be so important in the pathogenesis and development of acne as to provide a potential for us to optimize T cell clonotype selection for therapeutic benefit.
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.molimm.2020.01.024. References Arstila, T.P., Casrouge, A., Baron, V., Even, J., Kanellopoulos, J., Kourilsky, P., 1999. A direct estimate of the human alphabeta T cell receptor diversity. Science 286, 958–961. Ashbee, H.R., Muir, S.R., Cunliffe, W.J., Ingham, E., 1997. IgG subclasses specific to Staphylococcus epidermidis and Propionibacterium acnes in patients with acne vulgaris. Br. J. Dermatol. 136, 730–733. Bhate, K., Williams, H.C., 2013. Epidemiology of acne vulgaris. Br. J. Dermatol. 168, 474–485. Cao, X., Wa, Q., Wang, Q., Li, L., Liu, X., An, L., Cai, R., Du, M., Qiu, Y., Han, J., Wang, C., Wang, X., Guo, C., Lu, Y., Ma, X., 2016. High throughput sequencing reveals the diversity of TRB-CDR3 repertoire in patients with psoriasis vulgaris. Int. Immunopharmacol. 40, 487–491. Clemente, M.J., Przychodzen, B., Jerez, A., Dienes, B.E., Afable, M.G., Husseinzadeh, H., Rajala, H.L., Wlodarski, M.W., Mustjoki, S., Maciejewski, J.P., 2013. Deep sequencing of the T-cell receptor repertoire in CD8+ T-large granular lymphocyte leukemia identifies signature landscapes. Blood 122, 4077–4085. Doshi, A., Zaheer, A., Stiller, M.J., 1997. A comparison of current acne grading systems and proposal of a novel system. Int. J. Dermatol. 36, 416–418. Dreno, B., Gollnick, H.P., Kang, S., Thiboutot, D., Bettoli, V., Torres, V., Leyden, J., Global Alliance to Improve Outcomes in, A, 2015. Understanding innate immunity and inflammation in acne: implications for management. J. Eur. Acad. Dermatol. Venereol. 29 (Suppl. 4), 3–11. Farrar, M.D., Ingham, E., 2004. Acne: inflammation. Clin. Dermatol. 22, 380–384. Garcia, K.C., Teyton, L., Wilson, I.A., 1999. Structural basis of T cell recognition. Annu. Rev. Immunol. 17, 369–397. Gorski, J., Yassai, M., Zhu, X., Kissela, B., Kissella, B., Keever, C., Flomenberg, N., 1994. Circulating T cell repertoire complexity in normal individuals and bone marrow recipients analyzed by CDR3 size spectratyping. Correlation with immune status. J. Immunol. 152, 5109–5119. Hohn, H., Neukirch, C., Freitag, K., Necker, A., Hitzler, W., Seliger, B., Maeurer, M.J., 2002. Longitudinal analysis of the T-cell receptor (TCR)-VA and -VB repertoire in CD8+ T cells from individuals immunized with recombinant hepatitis B surface antigen. Clin. Exp. Immunol. 129, 309–317. Holland, D.B., Morrison, J.F.J., Cunliffe, W.J., 1995. Oligoclonality in T-cell receptor Vβ gene usage in acne lesions. J. Invest. Dermatol. 105, 482. Hou, X., Lu, C., Chen, S., Xie, Q., Cui, G., Chen, J., Chen, Z., Wu, Z., Ding, Y., Ye, P., Dai, Y., Diao, H., 2016a. High throughput sequencing of t cell antigen receptors reveals a conserved TCR repertoire. Medicine (Baltimore) 95, e2839. Hou, X., Wang, M., Lu, C., Xie, Q., Cui, G., Chen, J., Du, Y., Dai, Y., Diao, H., 2016b. Analysis of the repertoire features of TCR Beta chain CDR3 in human by highthroughput sequencing. Cell. Physiol. Biochem. 39, 651–667. Jappe, U., 2000. Superantigens and their association with dermatological inflammatory diseases: facts and hypotheses. Acta Derm. Venereol. 80, 321. Jappe, U., Ingham, E., Henwood, J., Holland, K.T., 2002. Propionibacterium acnes and inflammation in acne; P. acnes has T-cell mitogenic activity. Br. J. Dermatol. 146, 202–209. Jiang, J., Shang, P., Zhang, Z., Li, X., 2017. Permutation entropy analysis based on Gini–Simpson index for financial time series. Phys. A Stat. Mech. Its Appl. 486, 273–283. Keylock, C., 2010. Simpson diversity and the Shannon-Wiener index as special cases of a generalized entropy. Oikos 109, 203–207. Kistowska, M., Meier, B., Proust, T., Feldmeyer, L., Cozzio, A., Kuendig, T., Contassot, E., French, L.E., 2015. Propionibacterium acnes promotes Th17 and Th17/Th1 responses in acne patients. J. Invest. Dermatol. 135, 110–118. Lai, L., Wang, L., Chen, H., Zhang, J., Yan, Q., Ou, M., Lin, H., Hou, X., Chen, S., Dai, Y., Sui, W., 2016. T cell repertoire following kidney transplantation revealed by highthroughput sequencing. Transpl. Immunol. 39, 34–45. Li, H., Ye, C., Ji, G., Han, J., 2012. Determinants of public T cell responses. Cell Res. 22, 33–42. Li, Q., Zhou, J., Cao, X., Liu, Q., Li, Q., Li, W., Wang, X., 2018. Clonal characteristics of Tcell receptor repertoires in violent and non-violent patients with schizophrenia. Front. Psychiatry 9, 403. Liu, B., Yuan, J., Yiu, S.M., Li, Z., Xie, Y., Chen, Y., Shi, Y., Zhang, H., Li, Y., Lam, T.W., Luo, R., 2012. COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly. Bioinformatics 28, 2870–2874. Miles, J.J., McCluskey, J., Rossjohn, J., Gras, S., 2015. Understanding the complexity and malleability of T-cell recognition. Immunol. Cell Biol. 93, 433–441. Miyama, T., Kawase, T., Kitaura, K., Chishaki, R., Shibata, M., Oshima, K., Hamana, H., Kishi, H., Muraguchi, A., Kuzushima, K., Saji, H., Shin, I.T., Suzuki, R., Ichinohe, T., 2017. Highly functional T-cell receptor repertoires are abundant in stem memory T cells and highly shared among individuals. Sci. Rep. 7, 3663. Moreno-Arrones, O.M., Boixeda, P., 2016. The importance of innate immunity in acne. Actas Dermosifiliogr. 107, 801–805. Mouser, P.E., Baker, B.S., Seaton, E.D., Chu, A.C., 2003. Propionibacterium acnes-reactive T helper-1 cells in the skin of patients with acne vulgaris. J. Invest. Dermatol. 121, 1226–1228. Niu, J., Jia, Q., Ni, Q., Yang, Y., Chen, G., Yang, X., Zhai, Z., Yu, H., Guan, P., Lin, R.,
Contribution of the authors Lei Shao: conducted experiments, performed data analysis and wrote - original draft preparation. Yumei Liu: performed data analysis and wrote - original draft preparation. Junpu Mei: conducted experiments. Dongmei Li: helped data curation and polished language. Lijie Chen: helped data curation. Qingli Pan: helped data curation. Shujuan Zhang: provided resources. Xiangnong Dai: provided resources. Jingyao liang: wrote - reviewing and editing, designed the experiments and supervised the work. Silong Sun: designed the experiments. Jianqin Wang: wrote - reviewing and editing, designed the experiments and supervised the work. Funding This study was supported by the Natural Science Foundation of Guangdong (2018A0303130011), the Science and Technology Program of Guangzhou (Grant No. 201904010191), theMedical and Health Technology Projects of Guangzhou (Grant No. 20171A011284), the Major Scientific and Technological Project of Health and Family Planning of Guangzhou (Grant No. 20181A03003), and the Medical Science and Technology Research Foundation of Guangdong Province (Grant No. A2017311). Declaration of Competing Interest The authors declare that they have no conflict of interest. 30
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Bettoli, V., Casintahan, F., Chow, S., da Costa, A., El Ouazzani, T., Goh, C.L., Gollnick, H.P.M., Gomez, M., Hayashi, N., Herane, M.I., Honeyman, J., Kang, S., Kemeny, L., Kubba, R., Lambert, J., Layton, A.M., Leyden, J.J., Lopez-Estebaranz, J.L., Noppakun, N., Ochsendorf, F., Oprica, C., Orozco, B., Perez, M., Piquero-Martin, J., See, J.A., Suh, D.H., Tan, J., Lozada, V.T., Troielli, P., Xiang, L.F., 2018. Practical management of acne for clinicians: an international consensus from the Global Alliance to improve Outcomes in Acne. J. Am. Acad. Dermatol. 78 S1-S23 e21. von Budingen, H.C., Skulina, C., 2003. Following the tracks of immune responses. Trends Biotechnol. 21, 415–417. Xiong, H., Wang, L., Jiang, M., Chen, S., Yang, F., Zhu, H., Zhu, Q., Tang, C., Qin, S., Xing, Q., Luo, X., 2019. Comprehensive assessment of T cell receptor beta repertoire in Stevens-Johnson syndrome/toxic epidermal necrolysis patients using highthroughput sequencing. Mol. Immunol. 106, 170–177.
Song, Z., Li, Q.J., Hao, F., Zhong, H., Wan, Y., 2015. Association of CD8(+) T lymphocyte repertoire spreading with the severity of DRESS syndrome. Sci. Rep. 5, 9913. Norris, J.F., Cunliffe, W.J., 1988. A histological and immunocytochemical study of early acne lesions. Br. J. Dermatol. 118, 651–659. Robins, H.S., Campregher, P.V., Srivastava, S.K., Wacher, A., Turtle, C.J., Kahsai, O., Riddell, S.R., Warren, E.H., Carlson, C.S., 2009. Comprehensive assessment of T-cell receptor beta-chain diversity in alphabeta T cells. Blood 114, 4099–4107. Sui, W., Hou, X., Zou, G., Che, W., Yang, M., Zheng, C., Liu, F., Chen, P., Wei, X., Lai, L., Dai, Y., 2015. Composition and variation analysis of the TCR beta-chain CDR3 repertoire in systemic lupus erythematosus using high-throughput sequencing. Mol. Immunol. 67, 455–464. Tan, J.K., Bhate, K., 2015. A global perspective on the epidemiology of acne. Br. J. Dermatol. 172 (Suppl. 1), 3–12. Thiboutot, D.M., Dreno, B., Abanmi, A., Alexis, A.F., Araviiskaia, E., Barona Cabal, M.I.,
31
Contents lists available at ScienceDirect
Molecular Immunology journal homepage: www.elsevier.com/locate/molimm
High-throughput sequencing reveals the diversity of TCR β chain CDR3 repertoire in patients with severe acne
T
Lei Shaoa,b,1, Yumei Liua,b,1, Junpu Meic,1, Dongmei Lid, Lijie Chena,b, Qingli Pana,b, Shujuan Zhanga,b, Xiangnong Daia,b, Jingyao Lianga,b,*, Silong Sunc,*, Jianqin Wanga,b,* a
Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, PR China Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, PR China c BGI Genomics, BGI-Shenzhen, Shenzhen 518083, PR China d Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, DC, USA b
A R T I C LE I N FO
A B S T R A C T
Keywords: Acne vulgaris Repertoire TCR CDR3 High-throughput sequencing
Acne is a common chronic inflammatory skin disease, and the inflammation immune response runs through all stages of acne lesions. In this study, we use a combination of multiplex-PCR and high-throughput sequencing technologies to analyze T cell receptor β chain CDR3 (complementarity-determining region 3) in peripheral blood isolated from severe acne patients. Once compared with healthy controls, we propose to identify acnerelevant CDR3 peptides. Our results reveal that the diversity of T cell receptor β chain (TRB) CDR3 sequences in the peripheral blood of the severe acne vulgaris (SA) group differed from that of the control group. In addition, we find 10 TRB CDR3 sequences, amino acid sequences and V-J combinations with significantly different expressions between the SA group and the non-acne (NA) group (P < 0.0001). These findings may contribute to a better understanding of the role of immunity in the pathogenesis of acne and may serve as biomarkers for evaluating risk or prognosis of severe acne disease in future.
1. Introduction Acne is a chronic inflammatory condition that is estimated to affect approximately 85 % of the population at some point in their lives (Thiboutot et al., 2018). Males were more frequently affected, particularly presenting with more severe forms of acne (Tan and Bhate, 2015). Although it is a benign condition, acne can exert some distress, including pain and discomfort, permanent scarring, and depression and anxiety leading to poor self-esteem, especially in patients with severe acne (Bhate and Williams, 2013; Farrar and Ingham, 2004). Inflammatory immune response has been demonstrated in all types of acne lesion including the preclinical microcomedo, comedones, inflammatory lesions, ‘post-inflammatory’ erythema or hyperpigmentation, and scarring (Dreno et al., 2015). The immune mechanism studies on acne have rapidly increased with better-appreciated molecular and cellular technologies. Currently, it is believed that patients with severe acne result from an increased cellular as well as humoral immune response to Propionibacterium acnes (P. acnes), demonstrated by significantly higher levels of complement fixing antibodies to P. acnes than individuals with mild acne or control
cases (Jappe et al., 2002). The correlation between inflammatory response and level of severity is reflected in the fact that the highest level of antibodies presents with the most severe disease (Ashbee et al., 1997). Furthermore, accumulating evidence has shown that T lymphocytes play an important role in the occurrence and development of acne. Indeed, immunological studies on acne have shown that the initial infiltrate into the acne lesion is lymphocytic, with later progression to a general infiltrate of mixed cell types with CD4+ cells predominating in which P. acnes plays an active role as well in the chronification of the inflammatory process (Moreno-Arrones and Boixeda, 2016; Norris and Cunliffe, 1988). Previous studies have suggested that P. acnes induces T-cell proliferation (Jappe, 2000), and these P. acnes-specific T helper 1(Th1) lymphocytes are presented in early inflamed acne lesions (Mouser et al., 2003). Kistowska M. et al. (Kistowska et al., 2015) showed that both P. acnes-specific Th 17 and Th 17/ Th 1 lymphocytes cells were more frequently found in the peripheral blood samples of patients suffering from acne than healthy individuals. T cell receptor (TCR) is a complex of integral membrane proteins on the cell surface of T lymphocytes that play key roles in adaptive
⁎
Corresponding authors at: Department of Dermatology, Guangzhou Institute of Dermatology, 56 Hengfu Road, Guangzhou 510095, PR China. E-mail addresses: [email protected] (J. Liang), [email protected] (S. Sun), [email protected] (J. Wang). 1 These three authors contributed equally to this work. https://doi.org/10.1016/j.molimm.2020.01.024 Received 9 April 2019; Received in revised form 16 January 2020; Accepted 31 January 2020 0161-5890/ © 2020 Elsevier Ltd. All rights reserved.
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
2.4. High-throughput sequencing and data analysis
immune responses (Miles et al., 2015). Healthy adults have approximately 2.5 × 108 unique TCRs in the peripheral blood, forming a highly specific immune response to ward off a wide variety of foreign antigens (Robins et al., 2009). In peripheral blood, more than 90 % TCRs consist of α chain and β chain. During T cell development the Variable (V), Diversity (D), Joining (J), and constant gene segments of each chain undergo somatic rearrangement and recombination. In addition, the random insertion and deletion of nucleotides to the V-D-J junctions of the β chain create an additional hypervariable complementary determining region-3 (CDR3), which comes into direct contact with the antigenic peptides bound by major histocompatibility complex molecules (Arstila et al., 1999; Garcia et al., 1999; von Budingen and Skulina, 2003). As CDR3 represents the most diverse and complex portion of the variable region, the diversity of CDR3 amino acid sequences provides a measure of T cell diversity in an antigenselected T cell repertoire (Hou et al., 2016b). In this work, we applied high-throughput sequencing technologies and multiplex-PCR to analysis TCR β chain (TRB) CDR3 repertoire in peripheral blood of patients with severe acne vulgaris to study the distinctive features of CDR3 in acne in order to identify acne-relevant CDR3 peptides by comparing patients with healthy controls.
The PCR products were sequenced on the Illumina sequencing platform. As raw data generated, we first filtered the raw data including adapter contamination (SOAPnuke software v 1.5.6; command: -l 15 -q 0.5 -n 0.1; https://github.com/BGI-flexlab/SOAPnuke). Reads with average quality score below 15 (Illumina 0–41 quality system) and with the proportion of N bases more than 5 % were removed. Also, reads with few bases and low quality (≤ 10) were removed, whereupon the remaining sequence lengths were more than 60 nt. After filtering, pairend (PE) read pairs were merged into one contiguous sequence. The merging process was carried out in two steps. First, aligning the tail parts of two sequences and assessing their identity (BGI developed software COPE v1.1.3; open-source code at ftp://ftp.genomics.org.cn/ pub/cope) (Liu et al., 2012). An overlap of at least 10 bases is required and the overlapped section should have a better than 90 % match of all bases. Second, since different primers might result in sequences of different lengths, it may happen that some might be too short (less than 100 bp) and go through all bases on the sequencing. In this case, reads were merged by aligning the head part of the sequence (BGI developed software FqMerger). After we had the merged contiguous sequences and the length distribution plot, we next used miTCR, developed by MiLaboratory (http://mitcr.milaboratory.com/downloads/), to perform the final alignment. This program has an automated adjustment mechanism for errors introduced by sequencing and PCR. Subsequently, it will provide alignment statistical information, such as the CDR3 expression and INDEL (insertion and deletion). After sequence alignment, the expression level of each clonotype was calculated. The frequency and frequency distribution of clonotypes of the DNA sequence, amino acid sequence and V-J combination in the CDR3 region were also analyzed. In addition, the diversity of the TCR repertoire was calculated based on the Gini-Simpson index (G-D) and the Shannon–Wiener index (H′) (Jiang et al., 2017; Keylock, 2010) of distinct DNA sequences, amino acid sequences, and V–J combinations. D and H′ were calculated by the following formulae respectively:
2. Materials and methods 2.1. Patients and controls Five severe acne patients who were diagnosed according to the standard of severe acne vulgaris of global acne grading system (GAGS) (Doshi et al., 1997) and 5 healthy individuals were recruited at Guangzhou Institute of Dermatology between August 2016 and October 2016. All of the 5 severe acne patients are male (mean age of 20.80 ± 2.86 years, ranging from 17 to 24 years and GAGS score of 33.60 ± 1.82, ranging from 32 to 36. 5 healthy subjects matched for age, sex, BMI and ethnicity served as controls. There were no significant differences in their health conditions between severe acne vulgaris (SA) group and non-acne (NA) group (Table S1). Written informed consent was obtained from all subjects in the study. This study was approved by the ethics committee of the Guangzhou Institute of Dermatology and adhered to the tenets of the Declaration of Helsinki.
G− D = 1 − m
H'= −∑
i=1
m
∑i =1 pi2
pi lnpi
Here we assume there are m species (types of CDR3) in an assemblage and species (types of CDR3) are indexed by i = 1, 2, …, m. Let pi denote the relative abundance of the ith repertoires.
2.2. DNA extraction Whole peripheral blood sample (5 ml) was collected from the participants. PBMCs were isolated from whole peripheral blood using lymphocyte separation medium by density gradient centrifugation, and then T cells from PBMCs by magnetic beads. DNA was extracted from 0.5 to 2.5 × 106 T cells using GenFIND DNA (Agencourt, Beckman Coulter, Brea, CA, USA) extraction kits following the manufacturer’s instructions and stored at −80 °C until used.
2.5. Statistical analysis The statistical analyses were conducted with SPSS20.0 statistical software (Chicago, IL, USA). Data were processed and mapped with GraphPad Prism V.6.0 (GraphPad Software, San Diego, CA, USA) and Excel 2016 (Microsoft, Redmond, WA, USA). The differences between groups were compared by using the Mann-Whitney U test For the expression of each single clone, P-values are based on Poisson distribution model alone with FDR and Bonferroni correction. P < 0.05 was considered statistically significant.
2.3. Multiplex-PCR amplification of the TRB CDR3 region As previous study described (Xiong et al., 2019), TCRβ CDR3 regions were amplified and sequenced by BGI Tech (Shenzhen, China). Briefly, TCR CDR3 regions from genomic DNA were rearranged by Multiplex-PCR, using 45 forward primers specific to functional TCRβ CDR3 V regions and 12 reverse primers specific to a TCR J segment (Tables S2 and S3). After amplification and agarose gel electrophoresis selection, the products were purified using QIAquick PCR Purification Kit. The final library was quantitated in two ways: by ABI Step One Plus Real-Time PCR System (TaqMan Probe) and by determining the average molecule length using the Agilent 2100 bioanalyzer instrument (Agilent DNA 1000 Reagents). The libraries were amplified with cBot to generate the cluster on the flow cell, and the amplified flow cell was pairend sequenced using a Hiseq2000 instrument.
3. Results 3.1. TRB CDR3 sequences and data analysis Using high-throughput sequencing (Illumina Genome Analyzer), we sequenced TCR repertoires from T cells collected from the blood of five NA samples and five SA patients, obtaining a sun of 305,476,043 total raw reads and 322,022,783 total raw reads (pairs) in SA group and NA group, respectively. After filtering and removal of adaptor sequences, contamination and low-quality reads, we collected an average of 64,186,240.2 total raw reads per SA group and 60,845,102.8 total raw 24
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Table 1 TRB CDR3 sequences statistics of samples. Sample
Total reads(pair)
Filter rate (%)
All reads number
Total input sequences
Total good sequences
Sequencing information utilization(%)
Clones
Out of frame clones (%)
SA1 SA2 SA3 SA4 SA5 NA1 NA 2 NA 3 NA 4 NA 5
59526894 56248809 65173653 68864126 55662561 73141022 61757879 62558031 47711732 76854119
0.43 0.44 0.59 0.26 0.32 0.35 0.33 0.36 0.30 0.35
59271448 55998415 64787336 68685479 55482836 72885997 61556021 62335109 47570614 76583460
54617796 51767906 56022046 62070771 51695897 68251214 55398490 56817425 45266538 68745656
37431447 31450205 33047084 41182690 34709809 48979770 45727216 41348048 39686356 46043888
68.53 60.75 58.99 66.35 67.14 71.76 82.54 72.77 87.67 66.98
163462 135751 142278 166702 157525 180217 126230 141425 123242 164590
35.52 31.85 30.99 32.20 34.96 39.03 42.85 44.13 42.62 34.43
SA: severe acne vulgaris; NA: non- acne vulgaris.
index increases both when the number of types increases and when evenness among the types increases. To show whether the overall TCR clonal expansion exhibits evenness, we first summarize the unique clonotype distribution according to their abundance in each subject by a power-law distribution (Fig. 3). To produce comprehensive unrestricted profiles of TRB CDR3 repertoire diversity, we calculate the 1/(G-D) and H′ of each sample. The diversity increases as H′ increases, but decreases as 1/(G-D) increases. In our research, 1/(G-D) was lower in the SA group compared with the NA group at the DNA level, at the amino acid level and at the V-J level (Fig. 4a–c). We also found that H′ was higher in the SA group compared with the NA group at the DNA level, the amino acid level and the V-J level (Fig. 4d–f).
reads per NA group that met the quality requirements. The average clonotypes of TRB CDR3 in the SA group was higher than in the NA group. The total reads, all read numbers, total input sequences, total good sequences, and total clonotypes (distinct CDR3 sequences) per sample are shown in Table 1. 3.2. Distribution characteristics of amino acid length and TRBV/J/D gene usage analysis One of the key determinants of T cell repertoire diversity is the length of the TCR CDR3 loop. In the present study, we found that the amino acid length with a peak at 15 nt for the SA group and at 14 nt for the NA group. The 5 most frequently observed CDR3 lengths in both groups were 12, 13, 14, 15 and 16 nt, respectively (Fig. 1). Both the SA group and the NA group had the same V gene usage types, but with a slight difference in the cumulative frequencies. For example, the frequencies of TRBV2, TRBV7-2, TRBV19, TRBV20-1, V29-1 loci were higher in the SA samples, whereas the frequencies of TRBV4-1, TRBV4-2, TRBV6-5, TRBV7-8, TRBV10-1 were lower when compared with samples from the NA group (Fig.2a). In the J gene usage analysis, preference for TRBJ1-5, TRBJ2-1 and TRBJ2-7 loci was seen in SA samples, rather than TRBJ1-6, TRBJ2-3, and TRBJ2-5 loci (Fig.2b); as for D gene usage bias analysis, both groups demonstrated similar patterns, without an obvious preference (Fig. 2c).
3.4. The repertoire features of T cell with different clonotype abundance According to the CDR3 sequence frequency, CDR3 is divided into 5 groups (≥0.1 %, 0.01–0.1 %, 0.001–0.01 %, 0.0001–0.0.1 %, and ≤0.00.1 %, respectively), and we defined clones with a frequency of ≥ 0.1 % of the analyzed TCR to be highly expanded clones (HECs). A summary of TRB CDR3 and amino acid HECs sequences is presented in Supplemental Tables S4 and S5. In the two groups, the TRB CDR3 sequences were composed of a small number of high abundance clones and a large number of low abundance clones. Our results indicated that there was no significant difference among two groups in 5 expanded clone levels (Table 2 and Fig. 5). Rare clonotypes, which were detected as single copy, represented on average 55.29 % of all unique CDR3 sequence clonotypes per sample in the SA group and 60.37 % in the NA group, which we view as significantly different (p = 0.008). Using sample SA4 as an example, a total of 62 HECs (0.037 % of all the unique CDR3 sequences) accounted for 21.745 % of the T cell
3.3. The diversity of TRB CDR3 from samples A diversity index is a quantitative measure that reflects how many different types (such as species) there are in a dataset, and simultaneously takes into account how evenly the basic entities (such as individuals) are distributed among those types. The value of a diversity
Fig. 1. Length distribution of TRB CDR3 amino acid of the SA group (n = 5) and NA group (n = 5) (average of each group's). The amino acid length shown a peak at 15 nt of SA group and 14 nt of NA group. The 5 most frequently observed CDR3 lengths in both groups were 12, 13, 14, 15 and 16 nt, respectively. 25
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Fig. 2. Relative frequencies of each TRBV gene (a), TRBJ gene (b) and TRBD (c) gene family of SA group and NA group.
Fig. 3. The power-law distributions of TCR diversity of each sample (5 samples of SA group and 5 samples of NA group). The power-law distributions of diversity of each sample was calculated at different resolutions of distinct DNA (a), amino acid (b), and V–J (c).
sequences (total reads), whereas 92.344 % (n = 153940) of clones were very low-frequency clones (present at < 0.0001 % of all TCR sequences analyzed), which accounted for only 1.52 % of the T cell sequences that were present (total reads). The TGCAGTGCTAGGACCGCCGGGACTAG TGGCGGGGAGCTGTTTTTT sequence (clonotype abundance up to 879914) accounted for 2.137 % of the T cell sequences in the repertoire of donor SA4. This sequence was found in all severe acne samples (clonotype abundance were 4366, 3486, 4344, 3866 reads, respectively), while no read was found in the NA group.
acid sequences (Fig. 6a). The shared sequences number of the NA group was significantly lower than that of the SA group, which is 700 (0.42 %, 0.61 %, 0.54 %, 0.63 %, 0.46 %) (Fig. 6b). Next, we investigated whether HECs overlap between different individuals of the same group. However, we found no HECs sequence overlap within any group (Data not shown).
3.5. Patterns of TRB CDR3 sequences sharing among subjects
To investigate further, we filtered the top 10 TRB CDR3 sequences, amino acid sequences and V-J combinations in the SA group (Table 3) and NA group (Table 4), respectively. These top 10 TRB CDR3 sequences and amino acid sequences in SA were not shown in the control group. For example, the sequence, TGCAGTGCTAGGACCGCCGGGACT
3.6. The significant change in TRB CDR3 sequences, amino acid sequences and V-J combinations in SA group and NA group
UpSet plot was used to analyze the shared sequences of amino acid in SA group and NA group. We found that the SA group share 37677 24.62 %, 29.50 %, 28.28 %, 24.28 %, 25.55 %) of TRB CDR3 amino 26
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Fig. 4. Comparison of TCR diversity of the SA group and NA group. Comparison of the diversity of 1/(G-D) SA group and NA group in CDR3 sequences (a), amino acid sequences (b), and V-J combinations(b). Comparison of the diversity of (H′) SA group and NA group in CDR3 sequences (d), amino acid sequences (e), and V-J combinations(f).
the SA group except for one amino acid sequence, CASSAGTSGRSDTQYF, that appeared once in sample SA1. In the SA group, the 10 most common expressions of V-J combinations were significantly lower in the NA group, and the differences were statistically significant (P < 0.0001).
Table 2 Degree of expansion of T cell clones. Degree of expansion (%)
≥0.1 0.01–0.1 0.001–0.01 0.0001–0.001 <0.0001
CDR3 sequences SA
NA
P
0.02± 0.012 1.98±0.28 3.27±0.96 3.55±0.30 91.18± 0.96
0.03±0.01 1.47±0.60 5.20±2.54 3.90±1.67 89.41± 3.51
0.894 0.119 0.15 0.654 0.309
4. Discussion T cells play a central role in host protection against infectious pathogens by TCRs and contribute to the development of autoimmune and allergic diseases. For acne pathogenesis, a study of TCR variable region β (BV) gene usage in acne lesions has shown that most TCR BV families are represented in both peripheral blood mononuclear cells (PBMCs) and inflamed lesions from 7 acne patients (Holland et al., 1995). Using flow cytometry, the TCR variable BV repertoire was also undertaken by comparing the unstimulated and stimulated T cells with P. acnes (Jappe et al., 2002) But little is known about the clonality of V, D and J gene segments, or of CDR3 sequences in acne pathogenesis. High-throughput sequencing technologies have shown the possibilities for the in-depth evaluation of TCR repertoires. This method has been applied to study a variety of diseases, including cancers, infectious diseases, autoimmune diseases, organ transplantation, and other diseases with multiple causative factors, such as diabetes, psoriasis vulgaris and drug-induced hypersensitivity syndrome. In the present study, we coupled high-throughput sequencing with multiplex-PCR amplification to characterize the basic properties of CDR3 in the SA patients. To the best of our knowledge, this is the first study to describe the diversity of acne vulgaris TRB CDR3 in an overall analysis. Because different T cell clones have different sequences and CDR3 lengths, the diversity of T cell clones can be reflected by studying the diversity of CDR3 (Gorski et al., 1994; Hohn et al., 2002). We evaluated the distributions of TRB CDR3 amino acid length based upon a total of 399,606,513 good sequence reads, and the most common sequences and lengths were then assessed. We found that there was no significant change in the lengths of amino acids in the CDR3 region between the two groups in this study. In this study, the amino acid length of the SA group and NA group varied from 4 to 50 nt, with a peak at 15 nt of SA group and 14 nt of NA group. However, the 5 most frequently observed CDR3 lengths in both groups had a similar distribution.
Fig. 5. Degree of expansion and frequency distribution of T cell clones.
AGTGGCGGGGAGCTGTTTTTT was shared by all 5 of the SA individuals (cloning accounting for 0.012 %, 0.0.1 %, 0.013 %, 2.137 %, 0.0.1 % reads, respectively and the expression frequency were 4366, 3486, 4344, 879,914, 3866, respectively, and this was not seen in any blood sample isolated from the NA group. Similarly, in the NA group, the top 10 of expression V-J combinations were significantly lower than in the SA group, and the differences were statistically significant (P < 0.0001). At the amino acid sequencing level, the 10 TRB CDR3 sequences filtered in the healthy control group were not expressed in 27
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Fig. 6. The extent of overlap of amino acid clonotypes in the NA group and SA group. The publicly shared TRB CDR3 amino acid sequences of total sequences in SA group (a), The publicly shared TRB CDR3 amino acid sequences of total sequences in NA group (b).
in healthy people, and the average number of CDR3 nucleotide clonotypes are spectacular up to 8,7125. HECs defined as clonotypes having an abundance beyond a cutoff value in their repertoires, but the cutoff value was not identified (Niu et al., 2015). At present, most studies used 0.1 % as the standard of HECs that showed 4.18 × 10−2 % of clones in healthy donors (Hou et al., 2016a; Lai et al., 2016). We found the large number of low frequency expanded clonotypes of TRB CDR3 at DNA and amino acid sequences, suggesting that these clones have not undergone clonal expansion. Our results were similar to those of most other inflammatory diseases in the previous studies (Cao et al., 2016; Clemente et al., 2013; Sui et al., 2015), a small number of HEC parts were present in each individual, which may be the result of physiological responses to pathogens or environmental antigens. Holland et al. (Holland et al., 1995) have shown that although mono- or oligoclonal and polyclonal expansions of VB families represented by T cells infiltrating acne lesions, the CDR3 size diversity of expressed VB genes is restricted to the monoor oligo-clonal expansions indicative of an antigen-driven response. Study of immune receptor repertoires was not possible before the advent of this high-throughput DNA sequencing technology when considering the dramatic discrepancy of TCRs between individuals. These new technologies allow us to better understand the overlap of TCR repertoire among individuals. For example, the identical TCRs
The diversity of the immune repertoire is vitally important for a healthy human being. Sui et al. (Sui et al., 2015) showed that the SLE patients have a very low TCR diversity at the nucleotide, the amino acid and V–J pair levels, when compared with the normal control group (Lai et al., 2016) found that the diversity of TCR repertoire in kidney transplantation group was relatively lower compared to normal control group. Different antigens can be recognized by different TCRs, and T cell function is closely associated with TCR diversity (Miyama et al., 2017). In this TCR diversity study in SA patients, we found that the diversity was significantly different from that of the control group, which may lead to immune imbalance that causes the chronicity in these patients. However, further studies should be conducted to explain the intricate interaction between the TCR diversity and immune imbalance. The cloning frequency is an important characteristic of T cells. Normally, in the absence of any antigen stimulation, T cells are in a positive polyclonal state. However, in the case of disease, specific antigen stimulation causes targeted T cell rearrangement and dramatic clonal expansion (Li et al., 2018). A type of TCR CDR3 corresponds to a type of T cell. Therefore, the frequency of the CDR3 region sequences can reflect the degree of the T cell clones and demonstrates the condition of immune function. Hou et al. (2016a) showed that the abundance of unique CDR3 sequence clonotype ranged from 1 to 2,836,517 28
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Table 3 The significant change in TRB CDR3 sequences, Amino acid sequences and V-J combinations in SA group. Clonotype
Public sequences
CDR3 nucleotide sequences
TGCAGTGCTAGGACCGCCGGGACTAGTGGCGGGGAGCTGTTTTTT ▲ TGCAGCGTGGAGGGACAGCCAAAAGAGACCCAGTACTTC ▲ TGCAGCGTTGAGGTCATATGATAGCAATCAGCCCCAGCATTTT ▲ TGCAGTGCCTCAGGATTTGCGGGGACTTTAAATGAGCAGTTCTTC▲ TGCAGTGTGACCGAACCCGGGTTTGTCAACATTCAGTACTTC ▲ TGCGCCAGCAGCTTGGAGCAGGGGGCGAGGACAGATACGCAGTATTTT ▲ TGTGCCACCAGCAGAGAAAGTCCGGGACAGGGTTGGTACGAGCAGTACTTC ▲ TGTGCCAGCAGCACCGGACTAGCGGAGGTCTTC▲ TGTGCCAGCAGTGAAGCGCCGGCTAGCGGGAGTCTACAATGAGCAGTTCTTC ▲ TGTGCCAGCAGTGAGAGCGGGAGCAGCACAGATACGCAGTATTTT ▲ CSVTEPGFVNIQYF▲ CASSLEQGARTDTQYF▲ CASSQTHSNQPQHF▲ CASSQTLRGRTNEQYF▲ CASSTGLAEVF▲ CATSRESPGQGWYEQYF▲ CSARTAGTSGGELFF▲ CSASGFAGTLNEQFF▲ CSVEGQPKETQYF▲ CASSFTGGVDTQYF▲ TRBV15,TRBJ2-1※ TRBV20-1,TRBJ2-1※ TRBV29-1,TRBJ1-1※ TRBV29-1,TRBJ2-1※ TRBV29-1,TRBJ2-2※ TRBV7-2,TRBJ2-2※ TRBV7-2,TRBJ2-7※ TRBV7-8,TRBJ1-5※ TRBV7-8,TRBJ2-1※ TRBV7-9,TRBJ2-3※
CDR3 amino acid sequences
V-J combinations
Note：▲ meanssequences filtrated in the SA group were not expressed in the NA group；※ means sequences significantly higher in the SA group, and the differences were statistically significant (P < 0.0001). Statistics based on Poison distribution model alone with FDR and bonferroni correction.
Table 4 The significant change in TRB CDR3 sequences, Amino acid sequences and V-J combinations in NA group. Clonotype
Public sequences
CDR3 nucleotide sequences
TGCAGCGTTGTGGGGCTAGAGTAGAAAAAAAACAAGAGACCCAGTACTTC ▲ TGCGCCAGCAGCCGAAACCCCACAGGGTCAGATTCACCCCTCCACTTT ▲ TGCGCCAGCAGTGCCGGGACTAGCGGACTCTCAGATACGCAGTATTTT▲ TGCGCCAGCAGTGCCGGGACTAGCGGGAGGTCAGATACGCAGTATTTT▲ TGTGCCAGCAGCAGATGGGGGAGCGGGAGGTCCTCCTACGAGCAGTACTTC ▲ TGTGCCAGCAGCCAAGAAGGACTAGCGGGAGGGAGAGACCCAGTACTTC ▲ TGTGCCAGCAGCCAAGAGGGCCCAGGGGGAAATTCACCCCTCCACTTT▲ TGTGCCAGCAGCTTAGTAGGCAGCACGCAGTATTTT▲ TGTGCCAGCAGTTACGCTGGGAGCACAGATACGCAGTATTTT▲ TGTGCCATCAAAACCGGGACAGACAATGAGCAGTTCTTC▲ CAIKTGTDNEQFF▲ CASSAGTSGLSDTQYF▲ CASSLVGSTQYF▲ CASSTWTGPQETQYF▲ CASSQEGPGGNSPLHF▲ CASSRNPTGSDSPLHF▲ CASSRWGSGRSSYEQYF▲ CASSYAGSTDTQYF▲ CASSRQGSYNEQFF▲ CASSAGTSGRSDTQYF※ TRBV10-2,TRBJ2-7※ TRBV28,TRBJ2-7※ TRBV3-1,TRBJ1-3※ TRBV3-1,TRBJ2-5※ TRBV5-1,TRBJ2-7※ TRBV6-1,TRBJ2-7※ TRBV6-4,TRBJ2-7※ TRBV6-5,TRBJ2-1※ TRBV6-5,TRBJ2-7※ TRBV6-6,TRBJ2-7※
CDR3 amino acid sequences
V J combinations
Note：▲ meanssequences filtrated in the NA group were not expressed in the SA group；※ means sequences significantly higher in the NA group, and the differences were statistically significant (P < 0.0001). Statistics based on Poison distribution model alone with FDR and bonferroni correction. 29
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Appendix A. Supplementary data
shared by multiple individuals in responding to a same antigenic epitope, namely public T cell response, have been observed in a variety of immune responses, including viral infections, tumorigenesis, and autoimmunity (Li et al., 2012). In the present study, we found that the number of sequences shared among SA individuals was obviously higher than in healthy individuals and nearly a quarter of the individuals in the severe acne group shared the same amino acid. Meanwhile, no HECs of amino acid were shared by different individuals. These findings reveal a likely important role of the immune response in the process of acne inflammation and the acne antigen contained polymorphisms. In this study, we found 10 TRB CDR3 sequences, amino acid sequences and V-J combinations that were highly relevant to the acne, including 1) those only expressed in severe acne samples and those significant upregulated in severe acne; 2) those only expressed in healthy controls. However, we are still uncertain which peptide or peptide pattern is the major driving force in the pathogenesis of acne. Also, it is not clear whether there is a difference in TRB CDR3 between different severities of acne. We speculate that there is not a certain TRB CDR3 peptide that plays a decisive role in the pathogenesis of acne, and perhaps the combined or sequential interaction of these peptides is a better explanation. Therefore, more studies with big sample size in future may help with identifying the pivotal peptides for acne. In conclusion, we successfully profile the unique features of TRB CDR3 repertoires in severe acne vulgaris using a combination of highthroughput sequencing and multiplex-PCR technology. Also, we proved that there is more shared amino acid sequencing in acne patients. Ultimately, we identified 10 TRB CDR3 sequences, amino acid sequences and V-J combinations that were significantly different expression between SA and NA groups. These specific T cell clones may be so important in the pathogenesis and development of acne as to provide a potential for us to optimize T cell clonotype selection for therapeutic benefit.
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.molimm.2020.01.024. References Arstila, T.P., Casrouge, A., Baron, V., Even, J., Kanellopoulos, J., Kourilsky, P., 1999. A direct estimate of the human alphabeta T cell receptor diversity. Science 286, 958–961. Ashbee, H.R., Muir, S.R., Cunliffe, W.J., Ingham, E., 1997. IgG subclasses specific to Staphylococcus epidermidis and Propionibacterium acnes in patients with acne vulgaris. Br. J. Dermatol. 136, 730–733. Bhate, K., Williams, H.C., 2013. Epidemiology of acne vulgaris. Br. J. Dermatol. 168, 474–485. Cao, X., Wa, Q., Wang, Q., Li, L., Liu, X., An, L., Cai, R., Du, M., Qiu, Y., Han, J., Wang, C., Wang, X., Guo, C., Lu, Y., Ma, X., 2016. High throughput sequencing reveals the diversity of TRB-CDR3 repertoire in patients with psoriasis vulgaris. Int. Immunopharmacol. 40, 487–491. Clemente, M.J., Przychodzen, B., Jerez, A., Dienes, B.E., Afable, M.G., Husseinzadeh, H., Rajala, H.L., Wlodarski, M.W., Mustjoki, S., Maciejewski, J.P., 2013. Deep sequencing of the T-cell receptor repertoire in CD8+ T-large granular lymphocyte leukemia identifies signature landscapes. Blood 122, 4077–4085. Doshi, A., Zaheer, A., Stiller, M.J., 1997. A comparison of current acne grading systems and proposal of a novel system. Int. J. Dermatol. 36, 416–418. Dreno, B., Gollnick, H.P., Kang, S., Thiboutot, D., Bettoli, V., Torres, V., Leyden, J., Global Alliance to Improve Outcomes in, A, 2015. Understanding innate immunity and inflammation in acne: implications for management. J. Eur. Acad. Dermatol. Venereol. 29 (Suppl. 4), 3–11. Farrar, M.D., Ingham, E., 2004. Acne: inflammation. Clin. Dermatol. 22, 380–384. Garcia, K.C., Teyton, L., Wilson, I.A., 1999. Structural basis of T cell recognition. Annu. Rev. Immunol. 17, 369–397. Gorski, J., Yassai, M., Zhu, X., Kissela, B., Kissella, B., Keever, C., Flomenberg, N., 1994. Circulating T cell repertoire complexity in normal individuals and bone marrow recipients analyzed by CDR3 size spectratyping. Correlation with immune status. J. Immunol. 152, 5109–5119. Hohn, H., Neukirch, C., Freitag, K., Necker, A., Hitzler, W., Seliger, B., Maeurer, M.J., 2002. Longitudinal analysis of the T-cell receptor (TCR)-VA and -VB repertoire in CD8+ T cells from individuals immunized with recombinant hepatitis B surface antigen. Clin. Exp. Immunol. 129, 309–317. Holland, D.B., Morrison, J.F.J., Cunliffe, W.J., 1995. Oligoclonality in T-cell receptor Vβ gene usage in acne lesions. J. Invest. Dermatol. 105, 482. Hou, X., Lu, C., Chen, S., Xie, Q., Cui, G., Chen, J., Chen, Z., Wu, Z., Ding, Y., Ye, P., Dai, Y., Diao, H., 2016a. High throughput sequencing of t cell antigen receptors reveals a conserved TCR repertoire. Medicine (Baltimore) 95, e2839. Hou, X., Wang, M., Lu, C., Xie, Q., Cui, G., Chen, J., Du, Y., Dai, Y., Diao, H., 2016b. Analysis of the repertoire features of TCR Beta chain CDR3 in human by highthroughput sequencing. Cell. Physiol. Biochem. 39, 651–667. Jappe, U., 2000. Superantigens and their association with dermatological inflammatory diseases: facts and hypotheses. Acta Derm. Venereol. 80, 321. Jappe, U., Ingham, E., Henwood, J., Holland, K.T., 2002. Propionibacterium acnes and inflammation in acne; P. acnes has T-cell mitogenic activity. Br. J. Dermatol. 146, 202–209. Jiang, J., Shang, P., Zhang, Z., Li, X., 2017. Permutation entropy analysis based on Gini–Simpson index for financial time series. Phys. A Stat. Mech. Its Appl. 486, 273–283. Keylock, C., 2010. Simpson diversity and the Shannon-Wiener index as special cases of a generalized entropy. Oikos 109, 203–207. Kistowska, M., Meier, B., Proust, T., Feldmeyer, L., Cozzio, A., Kuendig, T., Contassot, E., French, L.E., 2015. Propionibacterium acnes promotes Th17 and Th17/Th1 responses in acne patients. J. Invest. Dermatol. 135, 110–118. Lai, L., Wang, L., Chen, H., Zhang, J., Yan, Q., Ou, M., Lin, H., Hou, X., Chen, S., Dai, Y., Sui, W., 2016. T cell repertoire following kidney transplantation revealed by highthroughput sequencing. Transpl. Immunol. 39, 34–45. Li, H., Ye, C., Ji, G., Han, J., 2012. Determinants of public T cell responses. Cell Res. 22, 33–42. Li, Q., Zhou, J., Cao, X., Liu, Q., Li, Q., Li, W., Wang, X., 2018. Clonal characteristics of Tcell receptor repertoires in violent and non-violent patients with schizophrenia. Front. Psychiatry 9, 403. Liu, B., Yuan, J., Yiu, S.M., Li, Z., Xie, Y., Chen, Y., Shi, Y., Zhang, H., Li, Y., Lam, T.W., Luo, R., 2012. COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly. Bioinformatics 28, 2870–2874. Miles, J.J., McCluskey, J., Rossjohn, J., Gras, S., 2015. Understanding the complexity and malleability of T-cell recognition. Immunol. Cell Biol. 93, 433–441. Miyama, T., Kawase, T., Kitaura, K., Chishaki, R., Shibata, M., Oshima, K., Hamana, H., Kishi, H., Muraguchi, A., Kuzushima, K., Saji, H., Shin, I.T., Suzuki, R., Ichinohe, T., 2017. Highly functional T-cell receptor repertoires are abundant in stem memory T cells and highly shared among individuals. Sci. Rep. 7, 3663. Moreno-Arrones, O.M., Boixeda, P., 2016. The importance of innate immunity in acne. Actas Dermosifiliogr. 107, 801–805. Mouser, P.E., Baker, B.S., Seaton, E.D., Chu, A.C., 2003. Propionibacterium acnes-reactive T helper-1 cells in the skin of patients with acne vulgaris. J. Invest. Dermatol. 121, 1226–1228. Niu, J., Jia, Q., Ni, Q., Yang, Y., Chen, G., Yang, X., Zhai, Z., Yu, H., Guan, P., Lin, R.,
Contribution of the authors Lei Shao: conducted experiments, performed data analysis and wrote - original draft preparation. Yumei Liu: performed data analysis and wrote - original draft preparation. Junpu Mei: conducted experiments. Dongmei Li: helped data curation and polished language. Lijie Chen: helped data curation. Qingli Pan: helped data curation. Shujuan Zhang: provided resources. Xiangnong Dai: provided resources. Jingyao liang: wrote - reviewing and editing, designed the experiments and supervised the work. Silong Sun: designed the experiments. Jianqin Wang: wrote - reviewing and editing, designed the experiments and supervised the work. Funding This study was supported by the Natural Science Foundation of Guangdong (2018A0303130011), the Science and Technology Program of Guangzhou (Grant No. 201904010191), theMedical and Health Technology Projects of Guangzhou (Grant No. 20171A011284), the Major Scientific and Technological Project of Health and Family Planning of Guangzhou (Grant No. 20181A03003), and the Medical Science and Technology Research Foundation of Guangdong Province (Grant No. A2017311). Declaration of Competing Interest The authors declare that they have no conflict of interest. 30
Molecular Immunology 120 (2020) 23–31
L. Shao, et al.
Bettoli, V., Casintahan, F., Chow, S., da Costa, A., El Ouazzani, T., Goh, C.L., Gollnick, H.P.M., Gomez, M., Hayashi, N., Herane, M.I., Honeyman, J., Kang, S., Kemeny, L., Kubba, R., Lambert, J., Layton, A.M., Leyden, J.J., Lopez-Estebaranz, J.L., Noppakun, N., Ochsendorf, F., Oprica, C., Orozco, B., Perez, M., Piquero-Martin, J., See, J.A., Suh, D.H., Tan, J., Lozada, V.T., Troielli, P., Xiang, L.F., 2018. Practical management of acne for clinicians: an international consensus from the Global Alliance to improve Outcomes in Acne. J. Am. Acad. Dermatol. 78 S1-S23 e21. von Budingen, H.C., Skulina, C., 2003. Following the tracks of immune responses. Trends Biotechnol. 21, 415–417. Xiong, H., Wang, L., Jiang, M., Chen, S., Yang, F., Zhu, H., Zhu, Q., Tang, C., Qin, S., Xing, Q., Luo, X., 2019. Comprehensive assessment of T cell receptor beta repertoire in Stevens-Johnson syndrome/toxic epidermal necrolysis patients using highthroughput sequencing. Mol. Immunol. 106, 170–177.
Song, Z., Li, Q.J., Hao, F., Zhong, H., Wan, Y., 2015. Association of CD8(+) T lymphocyte repertoire spreading with the severity of DRESS syndrome. Sci. Rep. 5, 9913. Norris, J.F., Cunliffe, W.J., 1988. A histological and immunocytochemical study of early acne lesions. Br. J. Dermatol. 118, 651–659. Robins, H.S., Campregher, P.V., Srivastava, S.K., Wacher, A., Turtle, C.J., Kahsai, O., Riddell, S.R., Warren, E.H., Carlson, C.S., 2009. Comprehensive assessment of T-cell receptor beta-chain diversity in alphabeta T cells. Blood 114, 4099–4107. Sui, W., Hou, X., Zou, G., Che, W., Yang, M., Zheng, C., Liu, F., Chen, P., Wei, X., Lai, L., Dai, Y., 2015. Composition and variation analysis of the TCR beta-chain CDR3 repertoire in systemic lupus erythematosus using high-throughput sequencing. Mol. Immunol. 67, 455–464. Tan, J.K., Bhate, K., 2015. A global perspective on the epidemiology of acne. Br. J. Dermatol. 172 (Suppl. 1), 3–12. Thiboutot, D.M., Dreno, B., Abanmi, A., Alexis, A.F., Araviiskaia, E., Barona Cabal, M.I.,
31