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Somatic hypermutation of T cell receptor α chain contributes to selection in nurse shark thymus

  1. Jeannine A Ott
  2. Caitlin D Castro
  3. Thaddeus C Deiss
  4. Yuko Ohta
  5. Martin F Flajnik
  6. Michael F Criscitiello  Is a corresponding author
  1. College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, United States
  2. University of Maryland at Baltimore, United States
  3. Texas A&M Health Science Center, Texas A&M University, United States
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Cite this article as: eLife 2018;7:e28477 doi: 10.7554/eLife.28477

Abstract

Since the discovery of the T cell receptor (TcR), immunologists have assigned somatic hypermutation (SHM) as a mechanism employed solely by B cells to diversify their antigen receptors. Remarkably, we found SHM acting in the thymus on α chain locus of shark TcR. SHM in developing shark T cells likely is catalyzed by activation-induced cytidine deaminase (AID) and results in both point and tandem mutations that accumulate non-conservative amino acid replacements within complementarity-determining regions (CDRs). Mutation frequency at TcRα was as high as that seen at B cell receptor loci (BcR) in sharks and mammals, and the mechanism of SHM shares unique characteristics first detected at shark BcR loci. Additionally, fluorescence in situ hybridization showed the strongest AID expression in thymic corticomedullary junction and medulla. We suggest that TcRα utilizes SHM to broaden diversification of the primary αβ T cell repertoire in sharks, the first reported use in vertebrates.

https://doi.org/10.7554/eLife.28477.001

Introduction

All jawed vertebrates share fundamental components of the adaptive immune system. The cartilaginous fish (including sharks) are the most divergent jawed vertebrate group relative to mammals and use a polymorphic major histocompatibility complex (MHC) (Kasahara et al., 1992), multiple isotypes of immunoglobulin (Ig) heavy and light chains (Flajnik, 2002; Criscitiello and Flajnik, 2007), and the typical four T-cell receptor (TcR) chains (Rast et al., 1997). Shark lymphocyte antigen receptors are diversified by RAG-mediated V(D)J somatic rearrangement (Bernstein et al., 1994). After antigen exposure, B cells also use the enzyme activation-induced cytidine deaminase (AID) for receptor modification via somatic hypermutation (SHM) (Conticello et al., 2005), allowing activated B cells to extensively alter their rearranged Ig variable region genes (Muramatsu et al., 2000). Some of the variants produced by this process bind antigen with higher affinity, enhancing humoral immunity through affinity maturation. In addition to SHM in all jawed vertebrate Igs, AID catalyzes the processes of heavy chain class switch recombination (CSR) in tetrapods (and is implicated in shark CSR [Zhu et al., 2012]) and Ig gene conversion (in birds and some mammals) (Barreto and Magor, 2011). AID is a member of the APOBEC family of nucleic acid mutators, two of which likely diversify the variable lymphocyte receptor (VLR) system in the more ancient vertebrate lineages of lamprey and hagfish (Alder et al., 2005; Guo et al., 2009).

Although in general immunologists think TcR loci do not undergo somatic hypermutation, a few reports do exist of AID-mediated SHM in T cells. However, non-productive TcRα rearrangements in hybridomas (Marshall et al., 1999), TcRβ sequences from HIV-positive individuals (Cheynier et al., 1998), and reports of SHM in TcRα murine germinal center T cells (Zheng et al., 1994) are not thought to describe any normal physiology (Bachl and Wabl, 1995). More recent studies indicate that TcR δ and γ in the dromedary camel and TcR γ in the sandbar shark somatically hypermutate (see below) (Antonacci et al., 2011; Chen et al., 2012). Despite these findings, the general consensus has remained that AID does not target TcR loci (Pavri and Nussenzweig, 2011; Choudhary et al., 2018). In over 30 years of studies of TcR repertoires, it has been clear that SHM is not functioning to either generate or further enhance the TcR repertoire of mouse and human.

Recent studies in the sandbar shark (Carcharhinus plumbeus) revived the notion of SHM at TcR loci. Sequencing of the entire TcRγ translocon in C. plumbeus showed definitively that SHM is occurring at that locus (Chen et al., 2009). Shark TcRγ SHM occurs in two distinct patterns: point mutations and tandem mutations characteristic of B cell SHM in cartilaginous fish (Anderson et al., 1995; Lee et al., 2002; Rumfelt et al., 2002; Zhu et al., 2012), possibly suggesting two different cellular mechanisms for generating mutations (Chen et al., 2012). The sandbar shark analysis found targeted nucleotide motifs of AID activity at the TcRγ locus. Chen et al. (2012) examined ratios of replacement (R) and silent (S) mutations between CDR and framework regions to determine if mutation altered affinity of receptors, a method commonly used to study B cell affinity maturation by SHM. Finding no difference between R/S ratios in CDR versus framework regions, they concluded that TcRγ uses SHM to generate a more diverse repertoire rather than for affinity maturation. SHM-induced changes to TcRδ in camels showed similar results.

Early work in our lab also suggested that SHM occurs in the less restricted γδ T cells in nurse shark (Ginglymostoma cirratum) and perhaps in the alpha chain of MHC-restricted αβ T cells (Criscitiello et al., 2010), encouraging us to examine this phenomenon further. Thus, we performed a systematic analysis of this process in shark primary and secondary lymphoid tissues using thymocyte clones containing the same unique third complementarity-determining region (CDR3). Our data suggest that SHM of TcRα is involved in primary T cell repertoire diversification and the enhancement of positive or negative selection in the thymic cortex. This finding is consistent with a model put forward by Niels Jerne over 40 years ago to explain antigen receptor positive selection (Jerne, 1971).

Results

Somatic hypermutation in TcR γV and TcR δV

We assessed the presence of possible SHM within TcR V segments from γ, δ, and β chains. Using neighbor-joining consensus trees, we grouped sequences from each chain into V families based on 85% nucleotide identity and into V subfamilies based on 90% nucleotide identity. We then examined each V subfamily for the possibility of SHM. However, since none of the sequences from these chains contained CDR3 regions, we did not rigorously analyze mutations within these chains.

We first corroborated the original finding of SHM in TcRγ variable regions (V) in sandbar shark spleen (Chen et al., 2012; Chen et al., 2009) using peripheral lymphoid tissue from the spiral valve (intestine) of nurse shark. We also examined mutation in clones from the thymus. We conservatively assigned 69 sequences to 9 V genes from three TcRγ families (Figure 1). Even with a conservative assignment of clones to predicted germline V sequences, we found nearly twice as many V genes as in the sandbar shark locus (which only contains five Vs). Only TcR γ4 did not display mutations in the nurse shark, but since we found only two γ4 sequences, it is possible that it occurs but our sample was too small to observe it.

Alignment of Gamma V clones suggests minimal somatic hypermutation.

Thymocyte clones for nine γV groups from three different predicted V genes. CDR regions are marked above the scale for each γV alignment. Amino acids are shown under the nucleotide consensus sequence, and dots represent identity to this sequence. We highlighted nonsynonymous changes in black; synonymous changes are underlined. Gaps are used for alignment purposes and indicate a shortened sequence (at the beginning or end). Sequences are identified by a single clone number or a group of identical clones condensed to a single line (the number of clones are indicated). Clone numbers that contain ‘THY’ are from thymus, ‘PBL’ are from peripheral blood leukocytes, and ‘SPV’ are from spiral valve (intestine). We deposited all 69 sequences into GenBank under accession numbers KY351639 – KY351707.

https://doi.org/10.7554/eLife.28477.002

We then investigated the possibility of mutation occurring at the TcRδ locus. We analyzed mutation in clones from nurse shark thymus, peripheral blood leukocytes, and spiral valve, conservatively grouping 111 clones into 12 V genes from 7 TcRδ families (Figure 2). Only one of these families (TcR δ10) lacked mutation. We found that in five of the seven δV families, the same V-δ segments used to generate δ cDNA sequences also generated α cDNA sequences. The sequence diversity at TcRγ and TcRδ was in contrast to TcRβ, where we found no such evidence for mutation in 56 sequences representing six V segments from six different V families (Figure 3). Limited existing data also do not support mutation at NAR-TcR, a distinct TcR containing a NAR V domain supported by a more canonical V δ domain, each resulting from independent V(D)J rearrangements (Criscitiello et al., 2006) (data not shown).

Alignment of Delta V clones suggests somatic hypermutation.

Thymocyte clones for 12 δV groups from seven different predicted V genes. CDR regions are marked above the scale for each δV alignment. Amino acids are shown under the nucleotide consensus sequence, and dots represent identity to this sequence. We highlighted nonsynonymous changes in black; synonymous changes are underlined. Gaps are used for alignment purposes and indicate a shortened sequence (at the beginning or end). Sequences are identified by a single clone number or a group of identical clones condensed to a single line (the number of clones are indicated). Clone numbers that contain ‘THY’ are from thymus, ‘PBL’ are from peripheral blood leukocytes, and ‘SPV’ are from spiral valve (intestine). We deposited all 112 sequences into GenBank under accession numbers KY346705 – KY346816.

https://doi.org/10.7554/eLife.28477.003
Alignment of Beta V clones illustrates a lack of somatic hypermutation.

Thymocyte clones for βV groups from six different predicted V genes. CDR regions are marked above the scale for each βV alignment. Amino acids are shown under the nucleotide consensus sequence, and dots represent identity to this sequence. We observed three nonsynonymous changes within a single sequence (highlighted in black). Sequences are identified by a single clone number or a group of identical clones condensed to a single line (the number of clones are indicated). Clone numbers that contain ‘PBL’ are from peripheral blood leukocytes and ‘THY’ are from thymus. We deposited all 57 sequences into GenBank under accession numbers KY351708 – KY351764.

https://doi.org/10.7554/eLife.28477.004

Identification of TcR Vα genes in the nurse shark genome

We identified 17 germline α/δ V gene sequences corresponding to 12 unique V segments. Unfortunately, these segments matched only two groups of sequences in our TcRα dataset (TcRα/δ V4 and V9), likely due to inter-individual polymorphisms. In the absence of a complete germline sequence for this locus, we limited our database for TcRα to thymocyte clones with the same unique CDR3 signature. The CDR3 region results from the somatic recombination and assembly of variable (V) and joining (J) gene segments during lymphocyte development in the thymus (Kuklina, 2006; Lantelme et al., 2008). The recombination process cleaves DNA and initiates repair mechanisms that result in the random insertion of non-template (N) nucleotides within the join, forming a unique binding sequence that contributes to the diversity and specificity of a TcR (Gellert, 2002; Kuklina, 2006). Once recombination ceases and the thymocyte proliferates, this distinctive CDR3 sequence is perpetuated in all daughter cells (Murphy and Weaver, 2017). Since it is unlikely that two thymocytes would generate identical CDR3 sequences during VJ recombination, we predict that amplicons containing identical CDR3 sequences derived from the same progenitor and thus must contain the same germline V and J segments. Alpha CDR3s exhibited substantial variation within our shark sequences, despite the absence of diversity (D) segments. For example, TcRα V1 sequences using the same V and J segments had CDR3 lengths that differed by as many as six amino acids (18 nucleotides), and few CDR3s shared more than one amino acid within this V-J join (Figure 4). Further, the majority of sequences in our overall dataset do contain N and palindromic (P) nucleotides within this join. Using clones containing the same V segment from different sharks, we determined the putative end of each V segment. We first aligned sequences containing the same V segment. Then, assuming that any nucleotide present in the same position within more than one shark must be germline, we determined which nucleotides within a join belong to the V segment. We then repeated this process for each J segment. Of 290 clones, we found 197 (68%) unique sequences within this join (0–34 nucleotides in length), suggesting that most sequences contain N/P nucleotides (see Figure 4—source data 1). Finally, we never observed the same CDR3 sequence in more than one shark, suggesting both exonuclease activity and addition of N and P nucleotides help diversify alpha CDR3s in nurse shark. Therefore, even in the absence of an assembled locus, we were able to evaluate mutation to germline αV segments by considering changes within only those thymocyte clones containing identical CDR3s. Our extremely conservative approach of using only clones containing the same CDR3 encoding rearrangement and N and P nucleotide sequences provided us the assurance that we had distinct αVs descendant from clonal T cells, since it would be extremely unlikely that two T cells created receptors that contained the exact same nucleotide sequence by chance.

CDR3s of TcR Alpha chain are diverse.

Amino acid (aa) alignment of TcR αV1 thymocyte clones illustrating diversity of the third complementarity-determining region (CDR3). All clones contain identical variable (V) region sequence (aa 1–61). We grouped clones by shared, identical joining (J) regions (purple boxes) and highlight the differences in the V-J join (CDR3 region) in red boxes.

https://doi.org/10.7554/eLife.28477.005

Somatic hypermutation in nurse shark TcR αV

With SHM confirmed in γ and δ TcR chains but apparently not the TcR beta chain of nurse shark, we checked for mutation of the TcRα locus. One might expect mutation in γδ T cells since antigen binding more closely mirrors that of B cells. However, mutations to receptors of MHC-restricted αβ T cells would be surprising given that even minor modifications to these receptors could risk incompatibility with MHC.

Our preliminary V α dataset contained 539 TcRα clones (encoding 286 unique amino acid sequences representing nine V α families) from three tissues (PBL, spleen, thymus) of two sharks (Joanie, Mary Junior). Of this total, only 447 sequences contained complete CDR3-J junctions (including all bases after the last predicted nucleotide of the V segment to the last predicted nucleotide of the J segment; see Table 1). We observed 239 (53.5%) sequences with unique V regions (from the first predicted nucleotide of the V segment to the last predicted nucleotide of the J segment) and 179 (40%) with unique V segments (from the first to the last predicted nucleotide of the V segment only). We found 226 sequences (50%) containing unique CDR3-J regions (all bases after the last predicted nucleotide of the V to the last predicted nucleotide of the J). However, we found 48 groups containing identical CDR3-J sequences across all nine V α families (suggesting they bear the V-J rearrangement from a single founder thymocyte), each V α family containing anywhere from one to ten clonal groups (Table 1). The majority of these groups contained no mutation within V, J or C regions. For example, one α V3 sequence group occurred 131 times, the most numerous sequence in the dataset, yet contained no mutation in any sequence. We did observe mutation in 12 of these 48 groups belonging to seven different V α families. Each family contained between one and four clonal groups, and each group contained two to nine sequences with identical CDR3-J regions (45 total sequences; see Table 1). We include these 45 sequences in our TcR V α dataset (see Table 1 – source data for sequence data).

Table 1
Summary of sequence data used in this paper.

Putative subfamilies within each TcR alpha V family share at least 85% nucleotide identity using nearest-neighbor consensus trees of V segments. Number of TcR alpha nucleotide (NUC), amino acid (AA) sequences or sequence groups within each category. Highlighted columns specifically refer to data used in this study. (See results for detailed descriptions of sequences included within each column.)

https://doi.org/10.7554/eLife.28477.007
Alpha V segmentPutative # Sub-familiesAll cloned sequencesComplete CDR3-J junction*Unique V Region Unique V segmentUnique CDR3-J§Groups with identical CDR3-J#CDR3-J groups in Study**Sequences in each dataset††
NUCAANUCAANUCAA
TRA V114040353424163432742, 3, 3, 5
TRA V231818131313101212315
TRA V33217194555235345150514
TRA V436028222221212121622, 2
TRA V5435341513981313312
TRA V6299775677100
TRA V759660494839384848922, 2
TRA V931919141412111313400
TRA V10245452926211927261024, 9
539447239229179163226224481345
  1. *A full list of these sequences can be found in Table 1—source data 1.

    V Region includes all bases between the 1 st predicted nucleotide of the V segment to the last predicted nucleotide of the J segment (V and J).

  2. ‡V Segment includes all bases between the 1 st predicted nucleotide of the V segment to the last predicted nucleotide of the V segment (V only).

    §CDR3-J includes all bases after the last predicted nucleotide of the V segment to the last predicted nucleotide of the J segment.

  3. #Number of groups with identical CDR3-J sequences, which we used to determine sequence relatedness (see text for details).

    **Number of groups with identical CDR3-J sequences used in this study. (Those not used contained no mutation with V segments.)

  4. ††Total number of sequences for each alpha V used to assess somatic hypermutation within this study (e.g., for aV1, 4 different clonal groups contained 2, 3, 3, and 5 identical CDR3-J regions, respectively).

Using these 45 sequences from both thymus and peripheral immune tissues, we found evidence for SHM acting on the TcRα genes. We divided our 45 clones into 13 CDR3-sharing groups from seven different α V families and then analyzed sequences within groups for potential mutation (Figure 5). We excluded two groups (four sequences) from analyses (αV1.3 and αV7.1) that contained no mutations within FR or CDR regions (leaving 41 clones for analysis). Two sequences (aV7.4m_THY09_051410 and aV5J_SPV17_102810) contained one 3-base insertion and one sequence (aV1.4J_SPV07_090110) contained an 18-base insertion; although SHM can result in insertions and deletions (Diaz et al., 2002), we did not include insertion nucleotides in mutation counts. All sequences were in-frame and contained no internal stop codons, suggesting functionality of cells. Average lengths of CDRs were as follows: CDR1: 7.0 amino acids (range: 5–8); CDR2: 5.7 amino acids (range: 5–7); and CDR3: 6.0 amino acids (range: 1–10). Naming of families and subfamilies followed Criscitiello et al. (2010). However, with the accumulation of sequence data over our previous analysis of nurse shark TcRα (Criscitiello et al., 2010), we expanded our nomenclature considerably. Additional annotation followed the IMGT guidelines for TcRs (Lefranc et al., 2003).

Alignment of Alpha V cDNA clones suggest somatic hypermutation at shark TCRα.

Thymocyte clones for all 11 αV groups with the same CDR3 from six different predicted V genes. Locations of framework regions (FR), complementarity determining regions (CDR), joining regions (J), and constant (C) regions are marked above the scale for each αV. In absence of germline sequence information, we used a Geneious-derived nucleotide consensus sequence for analysis of nucleotide changes in thymocyte clones. Amino acids are shown under the consensus sequence, and dots represent identity to this sequence. Nonsynonymous changes are highlighted in black; synonymous changes are underlined. Gaps are used for alignment purposes and indicate either a shortened sequence (at the beginning or end) or insertions or deletions within the sequence. Sequences are identified by a single clone number or a group of identical clones condensed to a single line (the number of clones are indicated). Clone numbers that contain ‘THY’ are from thymus, ‘PBL’ are from peripheral blood leukocytes, and ‘SPV’ are from spiral valve (intestine). We did not use clones from αV1.3 and αV7.1 because they did not contain mutations in FR or CDR regions. We deposited all 42 sequences into GenBank under accession numbers KY189332 – KY189354 or KY366469 – KY366487.

https://doi.org/10.7554/eLife.28477.009

Figure 5 shows all 12 αV CDR3 groups exhibiting mutation. The overall TcRα mutation frequency was 0.0226 substitutions per nucleotide (S/N), with 66% of all substitutions (187 of 283) resulting in amino acid replacements. The CDRs accumulated significantly more mutations than FRs (CDR: 0.0352 S/N; FR: 0.0188 S/N; p=0.0373), and substitutions in CDRs were twice as likely to be nonsynonymous changes (NSYN) than those in FRs (CDR: 0.0235 S/N; FR: 0.0122 S/N; p=0.0312; Table 2). There was no difference in frequency of synonymous (SYN) mutations between regions (CDR: 0.0117 S/N, FR: 0.0066 S/N; p=0.0705). Finally, although we found more tandemly mutated bases in CDRs (41 of 81, or 50.6% of all CDR mutations) than in FRs (73 of 192, or 38.0% of all FR mutations), this difference was not significant; p=0.721; Table 3). Tandem mutations ranged from two to four bases in length (mean = 2.78 bases). That this feature of SHM, specific of cartilaginous fish Ig (Rumfelt et al., 2001; Lee et al., 2002; Diaz et al., 1999), also occurs in the TcR strongly supports the validity of our analyses.

Table 2
Frequencies of somatic hypermutation in nurse shark alpha V groups (αV G) containing the same CDR3.

Mutation frequency is the total number of nucleotide changes to a Geneious-derived consensus sequence divided by the total number of nucleotides. We counted synonymous (S) and nonsynymous (N) mutations separately for each FR and CDR for 11 different CDR3 groups in seven predicted alpha V genes. [FR: framework region; CDR: complementarity-determining region; Seqs: sequences; Nuc: nucleotides; Freq: frequency]

https://doi.org/10.7554/eLife.28477.010
FR1FR2FR3FR Means
αV Group# Seqs# CodonsTotalMutationsTotalMutation# CodonsTotalMutationsTotalMutation# CodonsTotalMutationsTotalMutation
NucSNMutationFreq (%)NucSNMutationFreq (%)NucSNMutationFreq (%)SNALL
αV1.1325225212146.222171530221.307413694482.16861824
αV1.2525375108184.800172551893.5294161555101.626162137
αV1.43252251010.444171531342.614413694592.4396814
αV2.15253750000.000172551010.392426300000.000101
αV3.14253000441.333172040000.000404800110.208055
αV4.12251501232.000171020221.96143258117186.977121123
αV4.22251500000.000171021121.961432582793.4883811
αV5.12251500664.000171022354.902422521231.19031114
αV7.222515047117.333171021343.922412461672.84661622
αV10.14253000000.000172041120.980414924040.813516
αV10.2925675211131.926174594481.743401080311141.29692635
Sum4127530752050701872091122739455504935488367125192
Mean Mutation Freq (%)0.651.632.280.571.291.870.690.951.640.661.221.88
Standard Deviation2.9944.5476.5311.1362.2522.8413.1253.4145.4294.7428.20111.861
CDR1CDR2CDR3CDR Means
AlphaV Group# Seqs# CodonsTotalMutationsTotalMutation# CodonsTotalMutationsTotalMutation# CodonsTotalMutationsTotalMutation
NucSNMutationFreq (%)NucSNMutationFreq (%)NucSNMutationFreq (%)SNALL
αV1.138722245.5565451012.22210901677.7784812
αV1.2581205497.5005751234.00081201454.16771017
αV1.438720111.3895450000.0005450224.444033
αV2.1571050110.9525750000.0003450000.000011
αV3.146720334.1676720000.0001120000.000033
αV4.127423149.5246360112.7786362025.556527
αV4.227421124.7626360000.0006360000.000112
αV5.127420337.14363607719.4447420000.00001010
αV7.225300000.0007421124.7626360225.556134
αV10.147843033.5716720000.0007840333.571336
αV10.2971891894.76261622242.46971893031.58761016
Sum417787015243963696513186673571724275481
Mean Mutation Freq (%)1.722.764.480.721.872.590.952.313.271.172.353.52
Standard Deviation1.6902.3162.9790.6882.0892.2481.0272.0672.2722.6593.7545.626
Table 3
Number and frequency of DNA mutations that occur in tandem within framework regions (FR) and complementarity determining regions (CDR) in nurse shark alpha V (αV) groups.

All mutations include both tandem and point mutations within a region. [Seqs: sequences]

https://doi.org/10.7554/eLife.28477.011
FRCDR
# Nucleotides Tandemly MutatedAll mutationFrequency of tandem mutation# Nucleotides Tandemly MutatedAll mutationFrequency of tandem mutation
αV Group# Seqs234Sum234Sum
αV1.1310162425.030061250.0
αV1.25410113729.7510131776.5
αV1.4330061442.9000030.0
αV25000010.0000010.0
αV342004580.01002366.7
αV4.12410112347.80103742.9
αV4.2211051145.501032150.0
αV5210021414.311051050.0
αV7.22410112250.01002450.0
αV10.1430066100.0000060.0
αV10.29410113531.421071643.8
Total4127517319238.01350418150.6

Mutation frequency also varied by region (CDR or FR). The highest mutation frequency occurred in CDR1 and accumulated significantly more mutations overall than other regions (X¯=4.48%; see Figures 6 and 7a, Table 2). CDR3 displayed an unusually low mean mutation frequency (2.97%). However, these frequencies may be artificially low since our groups were based only on clones containing the same CDR3 sequence, and clones whose CDR3s deviated markedly from the consensus would have been excluded by our conservative grouping approach. We observed the lowest mean mutation frequency in FR3 (1.64%). These results are consistent with what is known about human TcR binding to MHC:Ag structures. CDR1 and CDR3 make more contacts with Ag while CDR2 interacts primarily with non-polymorphic regions of MHC (Buslepp et al., 2003; Garcia and Adams, 2005), making mutation in CDR2 less favorable; further, FR regions are important for the structural stability of the domain and mutations to these regions may affect the ability of the Ig superfamily domain to fold properly (Mantovani et al., 2002; Reinherz et al., 1999).

Mutation frequencies differed within TcR V regions.

Mutability of complementarity determining regions (CDR), especially CDR1, exceeded that of framework regions (FR) for all mutations together (black bars) and for nonsynonymous mutations alone (NSYN, hatched bars). We found no statistical difference in synonymous mutations (SYN, white bars) between CDRs and FRs.

https://doi.org/10.7554/eLife.28477.012
Mutation and motif locations within individual domains of TcR αV sequences.

(A) Number of mutations (both single and tandem, 283 total) to A:T nucleotides (black bars, 122 mutations) or G:C nucleotides (blue bars, 161 mutations) observed at each position along the sequence length of TcR αV sequences. We counted mutations to Geneious-derived consensus sequences within framework and complementarity-determining region (CDR) domains (41 sequences within 11 αV groups). (B) Number of WA/TW motifs (black bars, indicating possible polymerase η action) or DGYW/WRCH motifs (blue bars, indicating hotspots for AID activity, and thus possible mutation) at each position along the sequence length. Position indicates the forward (3’ to 5’) location of the mutable base of each motif within a Geneious-derived consensus sequence for each TcR αV group (eleven groups). Red boxes indicate the location of CDR1 (positions 76–99), CDR2 (positions 151–171), and CDR3 (positions 300–328) within each panel. [WA/TW: A:T is the mutable position; DGYW/WRCH: G:C is the mutable position; W = A/T, D = A/G/T, Y = C/T, R = A/G, and H = T/C/A].

https://doi.org/10.7554/eLife.28477.014

Hotspots

We found 1327 G/C base pairs within DGYW/WRCH hotspot motifs (4,402 G/C base pairs occurred outside these motifs) and 2931 A/T base pairs within WA/WT hotspot motifs (3690 A/T base pairs occurred outside these motifs; see Table 4). Mutations of G:C nucleotides were strongly associated with DGYW/WRCH hotspots (Figure 7b,c). Overall, G:C mutations occurred 4.3x as often within hotspots as those outside hotspots (p=0.0267). However, G:C mutations were 1.4x more likely within CDRs than within FRs (p<0.0001). A:T nucleotides did not appear to prefer WA/TW hotspots (p=0.2248), although they were 2.3x as likely to mutate within hotspots than outside hotspots. Further, while A:T mutations occurred more often than expected in both FRs and CDRs (p=0.0015), the frequency of A:T mutations were 1.9x more likely in CDRs than FRs. Chen et al. (2012) observed similar results in TcR γV sequences of sandbar shark. The authors suggested that A:T mutations still are likely the result of DNA polymerase η use during mismatch repair mechanisms due to the lack of A:T point mutations in that study (the majority occurring in tandem with other mutations) (Rogozin et al., 2001; Chen et al., 2012; Wei et al., 2015). In nurse shark Ig light chain genes, the majority of mutation to A:T nucleotides (55%) also occurred in tandem (Alder et al., 2005). However, 63% (76 of 121) of A:T mutations occurred as point mutations in our study, which is inconsistent with DNA polymerase η use during mismatch repair (Rogozin et al., 2001; Chen et al., 2012; Wei et al., 2015). This result suggests that an alternate A:T motif is targeted or that shark TcRs employ a different mechanism to alter A:T nucleotides.

Table 4
Target nucleotide mutation frequency in DGYW/WRCH or WA/TW mutation hotspots within framework regions (FR) and complementarity determining regions (CDR).

[DGYW/WRCH (G:C is the mutable position; D = A/G/T, Y = C/T, W = A/T, R = A/G, and H = T/C/A); WA/TW (A:T is the mutable position; W = A/T); ‘ALL’ refers to nucleotides within a hotspot motif; ‘All other’ refers to nucleotides outside a hotspot motif]

https://doi.org/10.7554/eLife.28477.015
Mutated baseHotspot motifRegionTotal nucleotidesObserved # MutationsExpected # MutationsMutation freq (%)χ2 pT-test P
G/CDGYW/WRCHFR9275618.166.040.00000.0267
CDR4003526.228.75
ALL13279137.526.860.0000
Outside Motif440271124.481.61
A/TWA/TWFR25315436.072.130.00150.2248
CDR4002621.124.03
ALL29318055.972.520.0000
Outside Motif36904165.031.11
  1. *T-test analysis was used to compare mutations within hotspot motifs to those outside hotspot motifs. Mutations to G and C nucleotides occurred significantly more often within DGYW/WRCH motifs than outside these motifs, while mutations to A and T nucleotides showed no preference for WA/TW motifs.

    †χ2 analysis was used to compare observed and expected numbers of mutations between FR and CDR regions and between mutations inside and outside hotspot motifs. More mutations to all nucleotides occurred within hotspots than outside hotspots, and significantly more mutations occurred to nucleotides within CDRs than FRs.

Base substitution indices

We identified 283 mutations within the eleven CDR3 groups. There was a bias toward mutations of G and C nucleotides (p=0.0022) and G:C changes comprised 57% of all mutations (Table 5a). More mutations to both G and C nucleotides occurred in FRs (p=0.0037) while only C nucleotides showed greater mutation than expected in CDRs (p=0.1136). There were fewer mutations of A and T nucleotides in FRs (p=0.0082; Table 5b), but mutations of A and T nucleotides in CDRs did not differ from random (p=0.3620; Table 5c). The frequency of mutated nucleotides also varied by region: In FR1, more A and T nucleotides mutated while fewer C nucleotides mutated. Mutations of G and C nucleotides were lower in FR2 and FR3, respectively (Table 5b,c). In both CDR1 and CDR2, there were more A mutations and fewer G mutations than expected. However, more G nucleotides mutated in CDR3. We saw a bias toward G:A and C:T transitions (42.8%) among the TcR α mutations. Transition mutations appeared only slightly more often in CDRs (45.1%) than in FRs (41.7%). Transversions of C:A or G:T mutations occurred only 25.1% of the time (Table 5).

Table 5
Bias in base substitution during somatic hypermutation of TcR alpha V genes within all sequence regions (ALL), framework regions (FR), or complementarity determining regions (CDR).

Probability of occurrence is the proportion of that base out of the total nucleotides. [Nuc: nucleotides; OBS: Observed; EXP: expected; MI: mutability index; ChiSq: Chi squared]

https://doi.org/10.7554/eLife.28477.016
aALLBaseOccurrenceProbability of occurrenceOBSEXPMI*ChiSq
G28950.2307765.051.180.0022
C28340.2258563.681.33
A34980.2786478.600.810.0068
T33680.2675775.680.75
Total125951.00283283
GC Mutation: 57.0%; Transitions: 42.8%; Transversions: 25.1%
bFRBaseOccurrenceProbability of OccurrenceOBSEXPMI*ChiSq
G23780.235844.501.300.0037
C22680.225642.441.32
A27790.273852.000.730.0082
T28350.284053.050.75
Total102601.00192192
GC Mutation: 59.0%; Transitions: 41.7%; Transversions: 24.0%
cCDRBaseOccurrenceProbability of OccurrenceOBSEXPMIChiSq
G5170.221920.150.940.1336
C5660.242922.061.31
A7190.312628.020.930.3620
T5330.231720.770.82
Total23351.009191
GC Mutation: 52.9%; Transitions: 45.1%; Transversions: 27.5%
  1. *Mutability Index, as first defined in Chen et al., 2012. χ2 analysis was used to compare observed and expected numbers of mutations. G and C mutated significantly more often than expected, while A and T mutated significantly less often than expected. Base composition: 23.0% G, 22.5% C 27.8% A, 26.7% T.

Mutations, in situ hybridization, and AID expression in thymus

Since we cloned TcR αV sequences in both central (thymus) and peripheral (blood, spiral valve) lymphoid tissues, we analyzed mutation frequencies by tissue type. Although data were limited to only six sequences in two CDR3 groups (αV2, αV7.2), we found more mutations to FRs of peripheral sequences, though this was not significant (p=0.0541; Table 6). We found no differences between tissues within CDRs (p=0.2) from this limited data set. It is possible that positive and negative selection pressures remove more clonal sequences within the thymus, but with so few sequences to compare it is difficult to determine.

Table 6
Frequencies of somatic hypermutation in nurse shark thymus and peripheral lymphoid tissue (blood and spiral valve).

Mutations were analyzed only in alpha V groups containing the same third complementarity-determining region (CDR). Mutation frequency was measured as the total number of nucleotide changes to a Geneious-derived consensus sequence divided by the total number of nucleotides in all sequences. Nonsynymous (N) and synonymous (S) mutations (mut) were counted separately for each framework (FR) and CDR for two predicted alpha V genes. [FR1, FR2, FR3, CDR1, CDR2, and CDR3 refer to the first, second, or third FR or CDR region, respectively.]

https://doi.org/10.7554/eLife.28477.017
Tissue typeMut typeFR Mutations (#)CDR Mutations (#)FR mutation frequencyCDR mutation frequency
 FR1FR2FR3All FRCDR1CDR2CDR3All CDRFR1FR2FR3CDR1CDR2CDR3
Thymus
 (6 sequences)
N8872313370.5700.8710.3170.0710.3270.136
S8261610010.5700.2180.2720.0710.0000.000
ALL1610133923381.1401.0890.5900.5291.0751.235
Total Nucleotides140491822054527378279243900
Periphery
 (2 sequences)
N7461702241.4961.3070.8330.0001.8521.587
S401500000.8550.0000.1390.0000.0000.000
ALL11472202242.3501.3070.9720.0001.8521.587
Total Nucleotides4683067201494126108126360

The mutated sequences in the primary T lymphoid tissue suggests the activity of activation-induced cytidine deaminase (AID) in the thymus. We confirmed the expression of AID in the thymus through real-time RT-qPCR, where thymus tissue expressed AID at more than half (0.7x) the levels found in spleen (positive control, where B cell SHM is known to occur) and nearly 6x the levels observed in forebrain (negative control; Figure 8a). Further, colorimetric in situ hybridization (CISH) of nurse shark thymus revealed a diffuse signal of TcR β (Figure 8b, panels 1,2) and AID (Figure 8b, panels 3,4) mRNA expression throughout the thymic cortex. However, AID expression was greatest in the central cortex and cortico-medullary junction (CMJ), while TcR β expression was highest in the outer cortex. The thymic sequence data combined with the tissue localization of AID message strongly suggest that TcRα loci undergo AID-dependent SHM in the shark thymus.

Shark thymus expresses AID.

(A) Expression of AID in shark spleen (black bar), thymus (hashed bar), and forebrain (gray bar) using real-time quantitative PCR. Expression was measured using the delta delta Cq method and are normalized against shark muscle tissue using β2M as a reference gene. Data represent expression fold-change differences at four cDNA concentrations. (B) In situ hybridization of mRNA using ribo-probes on adult shark thymus sections. 1,2: Two different fields probing for TcRβ antisense. 3,4: AID antisense. 5,6: TcRβ sense. 7,8: AID sense. All micrographs at 10X magnification; black scale bar in lower right of each panel is 100 uM. Anatomical structures are designated on the top panels [c: cortex; m: medulla; sc: subcapsular region; cmj: corticomedullary junction].

https://doi.org/10.7554/eLife.28477.018

We refined our CISH results with RNA fluorescence in situ hybridization (FISH) using probes against the TcR alpha constant region (αC) and exons 2 and 3 of AID. Since Stellaris RNA FISH uses a mixture of shorter probes (~20 bp in length) that hybridize along the length of the target RNA, the resulting signal is detectable only when tens of probes hybridize to the target. This makes the technology very specific -- only those transcripts bound to numerous probes are visible -- and limits the potential for false-positive or false-negative results (Orjalo et al., 2011; Raj and Tyagi, 2010). Our FISH results indicated a more specific TcR αC signal within the inner cortex and medulla adjacent to the CMJ (Figure 9; Figure 9—figure supplement 1), regions where, in mammals, developing cells actively rearrange their alpha chain genes and where mature αβ T cells are found. AID expression occurred in ‘rings’ around areas of expressed TcR αC messages within the inner cortex and CMJ (where positive selection occurs in mammals) and the medulla (where negative selection occurs in mammals). Further, AID always co-localized with TcR αC (Figure 9). Thus, we observed a consistent pattern of expression where a ‘ring’ of cells expressing both TcR αC and AID surround a central cell expressing only TcR αC. The more specific signal generated by FISH may suggest that, once a T cell completes RAG-mediated somatic rearrangement of its alpha chain locus, it clonally expands to form a ring of daughter cells around it. These daughter T cells then express AID (and TcR αC), promoting somatic hypermutation within their TcR alpha sequences during times when cells also undergo positive and negative selection.

Figure 9 with 2 supplements see all
AID expression localized to inner cortex and cortico-medullary junction.

(a) H and E staining of fixed shark thymus tissue illustrating thymic architecture (10x). The densely packed cells at the margins of the image comprise the cortex (cor), while the less densely packed cells in the center constitute the medulla (med). The region at the junction between cortex and medulla incorporates the corticomedullary junction (CMJ), delineated generally by a hashed white circle. [b-z] Single molecule RNA fluorescence in situ hybridization (FISH) probing fixed thymus sections simultaneously for AID (probes labeled with Quasar 670; pseudo colored red) and TcRα (probes labeled with CalFluor Red 610; pseudo colored green) and counterstained with DAPI (blue). (b) Composite of seven Z-stacked images (10x) depicting overall thymic architecture and the localization of AID expression to the inner cortex and cortico-medullary junction regions of shark thymus. We superimposed (and minimally adjusted) the outlined CMJ boundaries from (a) onto (b) to elucidate the junction between cortex and medulla. [c-z] We obtained images of each fluorophore using 10x, 20x, and 63x magnification and merged Z-stacked images together. Individual (10x) fluorophore images of DAPI [c-f], TcRα [g-j], and AID [k-n] and Z-stacked merged images [o-r] illustrate AID and TcRα expression in four locations of shark thymus. White boxes indicate the magnified regions of the 10x and 20x images shown in the 20x [s-v] and 63x [w-z] images, respectively. Scale bars [a,b,c,g,k,o] 150 μm, [s] 75 μm, and [w] 30 μm. [cor: cortex; med: medulla; CMJ: corticomedullary junction].

https://doi.org/10.7554/eLife.28477.019

Discussion

The role and diversifying mechanisms of SHM in B cells are well known (Li et al., 2004), as are the consequences of off-target AID activity (Álvarez-Prado et al., 2018). In B cells, AID mediates SHM within germinal centers of lymph nodes and spleen in mammals (Crouch et al., 2007), and we predict this is similarly occurring in the B cells zones identified in the shark splenic white pulp (Rumfelt et al., 2002). Somatic mutations occur in rearranged variable regions of B cells responding to antigen at rates of 10−3 mutations per base pair per cell division (Odegard and Schatz, 2006). These changes are dominated by point mutations (and in shark, tandem mutations), biased toward transitions (G:A and C:T), and preferentially targeted to the AID motifs DGYW/WRCH (and less to WA/TW) (Li et al., 2004; Malecek et al., 2005; Odegard and Schatz, 2006; Rogozin and Diaz, 2004). The sequences of B cell V genes have evolved to maximize mutational effects, targeting the accumulation of replacement mutation within the antigen-binding CDRs and limiting mutation within the more structural FRs. In humans, this focused mutation correlates with the long-term survival of B cell receptor repertoires (Saini and Hershberg, 2015). The ability of B cells to use SHM for receptor diversification and improved antigen affinity is the basis of adaptive immunity (Saini and Hershberg, 2015). Despite having similar developmental machinery as B cells (Gellert, 2002), the assumption has long been held that αβ T cells do not undergo SHM because mutation could have deleterious effects on the binding of TcRs to MHC:Ag complexes (MHC:Ag) (Wagner et al., 1995; Mantovani et al., 2002). Despite some suggestion that SHM was occurring in T cells, studies designed to either quantify or characterize mutation in mouse or human TcRs did not gain traction and the textbook definition of SHM still defines it as an exclusively B cell mechanism (Murphy and Weaver, 2017).

Recent studies reported the incidence of SHM in the γ chain of γδ T cells of sandbar shark (Chen et al., 2012; Chen et al., 2009) and in both γ and δ chains of dromedary camel (Antonacci et al., 2011; Ciccarese et al., 2014; Vaccarelli et al., 2012). In each study, SHM mirrored the mutational patterns observed in B cells during affinity maturation. However, in both sandbar shark γ and dromedary camel γ and δ chains, the authors hypothesized that T cells employ mutation as a means to generate a more diverse receptor repertoire rather than to improve receptor affinity to Ag (Chen et al., 2012; Antonacci et al., 2011; Vaccarelli et al., 2012). In contrast to αβ T cells, γδ T cells that interact with non-classical MHC often recombine tissue-specific, restricted sets of genes that have limited junctional diversity (Allison et al., 2001; Adams et al., 2005). Thus, it is reasonable to consider that SHM could be used as a receptor-diversifying mechanism to fine-tune ligand recognition within a prospective tissue or to allow changes within the loci that allow receptors to evolve more rapidly to changing ligand environments (Adams et al., 2005; Kazen and Adams, 2011). Further, many γδ T cells typically bind Ag in a manner more similar to that of Ig than to αβ T cells, recognizing and directly binding to small molecules and intact proteins without presentation by classical MHC:Ag complexes (Adams et al., 2005; Allison and Garboczi, 2002; Allison et al., 2001). Inflammation stimulates activation of γδ T cells earlier in an immune response, releasing pro-inflammatory cytokines and killing infected macrophages. Thus, γδ T cells combine an innate-like response with an adaptive recognition strategy, providing both an immediate response to pathogen invasion and an ongoing, adaptive response to inflammation (Adams et al., 2005; Allison and Garboczi, 2002; Allison et al., 2001). It is evident that how SHM presents a useful solution for accomplishing these tasks by creating a more diverse repertoire of these antibody-like γδ TcRs. Taken together, these studies clearly demonstrate that we can no longer regard SHM as a uniquely B cell mechanism. Considering the diversity of TcRs and TcR diversification mechanisms being found even in mammals (Hansen and Miller, 2015; Miller, 2010), perhaps we should prepare for more surprises in TCR antigen recognition.

In the present study, we verified SHM occurring within the γ and δ chains of γδ T cells in both thymic and peripheral immune tissue of nurse shark. Remarkably, we also detected SHM occurring in the α chain of αβ T cells. We observed mutational characteristics within α chain of nurse sharks similar to those found in B cell SHM. We observed an overall mutation frequency of 0.0226 substitutions per nucleotide (S/N) and a bias toward transition mutations. Further, we detected both single and tandem mutations, a pattern unique to sharks that also occurs in shark B cells. Changes to G and C nucleotides comprise 66.1% of all mutations. Mutation was twice as frequent in CDRs as in FRs (0.0352 versus 0.0188 S/N, respectively), and substitutions in CDRs were significantly more likely to result in amino acid changes. Further, mutations were strongly associated with AID hotspots, and substitutions to G and C nucleotides occurred nearly 1.4x as often within CDR hotspots than FR hotspots. Out of curiosity, we compared counts of AID hotspot motifs within CDR and FR regions between our 11 nurse shark TcR αV consensus sequences and 6 human TcR αV segments (V1.1, V1.2, V2, V3, V4 and V5). We found that shark TcR V segments exhibit far more WRCH/DGYW motifs per sequence than do human V segments (p=0.02). Further, motifs in CDRs of shark occurred 2-3x as often as in humans [human: average of 2.27 motifs per FR (range 1.97–2.65), 2.28 per CDR (range 1.97–2.59); shark: average of 3.25 motifs per FR (range 2.85–3.88), 5.09 per CDR (range 4.02–6.16); data not shown]. The bias we found for nonsynonymous and non-conservative mutations in TcRα CDRs in the shark thymus are consistent with more than simple repertoire diversification; it suggests selection for changes in paratope.

We identified SHM from identical cDNA clones originating from both thymus and spiral valve tissues (see Table 6), suggesting that T cells with SHM-modified receptors must have originated within the thymus and then traveled to peripheral gut-associated lymphoid tissue. Unsurprisingly, we detected the most AID expression within the inner cortex, medulla, and CMJ of shark thymus, where rearrangement and testing of TcRα takes place in mammals. Positive selection on self-MHC/self peptide for mature thymocytes begins with the CD4/CD8 double positive (DP) stage of development while differentiation into CD4/CD8 single positive (SP) cells requires that the TcR interact with MHC (Huesmann et al., 1991). If there is no TcR: MHC/peptide match found, T cell differentiation stalls with failure to be positively selected (Reinherz et al., 1999). However, the unusual nature of the TcRα locus, with up to 100 J segments depending on species, permits multiple successive rearrangements within a single cell, rescuing non-productive or self-selectable receptors with further gene rearrangements, a process called receptor editing (Bedel et al., 2012; Borgulya et al., 1992; Guo et al., 2002; Petrie et al., 1993). In mice, unlike the situation in developing B cells, receptor editing does not seem to rescue T cells from negative selection (Kreslavsky et al., 2013) and thus provides several opportunities for positive selection of DP thymocytes. Thymic nurse cells may help optimize these opportunities for selection by providing microenvironments favorable to secondary alpha chain rearrangement (Nakagawa et al., 2012).

In developing shark thymocytes, SHM in TcRα loci in conjunction with receptor editing (note that sharks, like all other gnathostomes, have a large number of TcRα J segments) could be involved in salvaging cells for positive selection or rescuing cells from death by negative selection. If AID-induced SHM occurs in conjunction with receptor editing and positive selection, AID should be upregulated in cells undergoing RAG-mediated alpha rearrangement (and thus in cells also expressing RAG). However, if SHM occurs after rearrangement of TcR α and thus used for rescuing cells during negative selection, the same T cell would not express both AID and RAG. While we cannot determine conclusively without RAG expression data, the patterns of AID and TcRα expression (Figure 9) suggest that AID is upregulated after cells proliferate and diversify following alpha rearrangement (within the ‘ring’ of cells). Thus, it is likely that AID is used primarily to rescue cells from negative selection, providing a ‘mini-expanded self-referential repertoire’ (Figure 10) and reducing the ‘profligate waste of thymocytes’ (Murphy and Weaver, 2017). However, based on the works above by Kreslavsky et al. and Nakagawa et al. in mice, we cannot discount the possibility that TcRs use SHM in conjunction with receptor editing for positive selection since developing shark T cells could still undergo negative selection after SHM (Figure 10). We cannot completely rule out AID use in mature shark T cells, although our sequence data show no greater mutation frequency in the periphery, and abatement of AID expression in the thymic medulla are consistent with AID being a mechanism used only in T cell development. Further studies examining expression data from single cells could elucidate the timing of AID-catalyzed SHM in relation to T cell development.

Model predicting how AID acts on T cells in the thymus.

CD4/CD8 double negative (DN) thymocytes in the subcapsular region (SC) and cortex rearrange the β chain, using a surrogate pTα receptor to test for expression signaling. Cells with productive β arrangements then proliferate and express both CD4 and CD8, becoming double positive thymocytes (DPs). As DPs move toward the inner cortex and cortico-medullary junction (CMJ) where α chain rearranges, cells may begin to express AID. Non-productive rearrangements can be rescued from apoptosis by receptor editing or by receptor salvaging, in which AID catalyzes SHM to produce cells with improved affinity to MHC:Ag complexes (to pass positive selection). Salvaged thymocytes then proliferate and express either CD4 or CD8 on their surface as single-positive (SP) cells. AID-mediated receptor salvaging may also reduce recognition of self-peptide, rescuing self-reactive thymocytes from apoptosis (to pass negative selection). [sc: subcapsular region; cmj: corticomedullary junction; green shading indicates region of AID expression].

https://doi.org/10.7554/eLife.28477.022

These results are not without precedent. Qin et al. (2011) reported endogenous AID expression by peripheral CD4+ T cells and immature B cells in mice. T cells that expressed AID also produce a distinctive cytokine profile, are associated with cell activation, and increase in abundance with age, suggesting these cells have distinctive long-term functions in aging cells. In immature B cells, AID expression may help negatively select autoreactive B cells and contribute to primary repertoire diversity. Together these results may indicate that AID expression in mice is a relic of a more extended expression in earlier species (Qin et al., 2011). Some mammals (e.g. rabbit, sheep, and cattle) use SHM in B cell primary repertoire diversification in the gut associated lymphoid tissues (Alitheen et al., 2010; Archer et al., 1963; Becker and Knight, 1990; Butler et al., 2011; Lanning et al., 2000; Reynaud et al., 1995; Reynaud et al., 1991; Reynolds and Morris, 1983). Even more recently, research implicated AID in central B cell tolerance in mammalian pre-B cells (Cantaert et al., 2015; Kuraoka et al., 2011), and there are examples of AID-mediated SHM being used alongside RAG-mediated V(D)J recombination in primary B cell repertoire generation in many mammals and in AID-mediated primary B cell diversification during gene conversion in the bird bursa of Fabricius (Reynaud et al., 1987; Thompson and Neiman, 1987). We suggest that these B-cell-specific features are much later mechanisms of AID-driven primary lymphocyte repertoire diversification and honing, perhaps mechanisms convergent with the thymic process we describe here. However, we predict that studies of this type in other vertebrate species will reveal the use of SHM as a T cell diversifying mechanism in a much broader collection of species.

Although recent studies report B cells present in the thymus of mice (Perera and Huang, 2015; Perera et al., 2013), Miracle et al. examined B cell expression levels (IgM and IgX) in various tissues (including thymus) at different ages in the clearnose skate. While skate thymus expressed both IgM and IgX in early life stages, adult skates no longer express Ig in the thymus (Miracle et al., 2001). Criscitiello and Flajnik, 2007 also found little evidence that Ig light chain is expressed in adult nurse shark thymus (see Fig S3 of paper), corroborating older northern blot studies with heavy chain in the species (Rumfelt et al., 2001; Rumfelt et al., 2004). A concurrent study within our lab used RT-qPCR to analyze IgM expression within shark thymus and found that, while young sharks do express IgM in the thymus, adult nurse sharks (which we used in the current study) do not express IgM (data not shown). Further, preliminary results using FISH probes to IgM constant region also indicate that adult nurse sharks do not express IgM in the thymus. What little Ig expression we found in the thymus did not co-localize with AID expression.

Shark TcRs are capable of a wide variety of diversification mechanisms. In addition to RAG-mediated combinatorial and junctional diversity from complex loci, TcRδ (and possibly α) rearrange Ig-TcR chimera using IgM and IgW V exons with TcR D-J-C (Criscitiello et al., 2010). The TcR δ locus also encodes the doubly rearranging NAR-TcR, a δ chain with two diverse V domains (Criscitiello et al., 2006). Interestingly, our existing data do not suggest that SHM targets the IgHV or the TcR δV of the NAR-TcR δV chains for diversification. This suggests great control over the (nearly synchronous if not concomitant) expression of the potentially genotoxic AID and RAG. Thus, SHM at the γ, δ, and α loci adds to the battery of extraordinary diversification mechanisms used by shark lymphocytes in antigen recognition, although we do not yet understand the full effects of SHM on the animal’s immunity to infectious disease. As for the dangers of any aberrant mutational activity genome-wide, sharks could be more resilient than other taxa due to their inherent slow rate of mutation (Martin, 1999), possibly linked to the exceptional longevity of some individuals (Nielsen et al., 2016).

In the broader scope of lymphocyte evolution, we must consider whether the ancestral vertebrate lymphocyte employed APOBEC-family-mediated diversification before the ‘big bang’ of RAG (reviewed in [Hirano, 2015]). Lamprey lymphocytes express at least two lymphocyte-specific cytidine deaminases (CDA1/CDA2) in the AID/APOBEC family. These deaminases emerged phylogenetically as the closest sister group in the AID/APOBEC family to the AID used by gnathostomes for Ig class-switch recombination, somatic hypermutation, and Ig gene conversion (Rogozin et al., 2007). CDA-mediated gene rearrangement in lampreys occurs in a manner similar to AID-induced immunoglobulin gene conversion in some birds and mammals (Rogozin et al., 2007; Zheng et al., 1994). One study suggested that VLRA (the analog to αβ TcR in jawed vertebrates) also might use CDA to affinity mature its receptors, indicating that CDA contributes both to repertoire generation and to somatic mutation after antigen exposure (Deng et al., 2010; Flajnik, 2014). If this is true, it may be possible that the ancestor to modern vertebrates also used an AID-like enzyme to assist with lymphocyte receptor development in a thymus-like organ. The expression of AID in the thymus of primitive sharks may be a remnant of this ancestral process, a mechanism lost in later vertebrates because of its potential for breaking down self-tolerance in mature lymphocytes. Perhaps, agnathans evolved specific APOBEC molecules for diversification of their B and T like VLRs, while gnathostomes evolved AID for T cell primary repertoire diversification (Neils Jerne’s ‘mutant breeding organ’ [Jerne, 1971]) and B cell affinity maturation, eventually co-opting AID for use in class switch recombination at IGH translocons, and later still, gene conversion and SHM for primary B cell repertoires.

From this trend of comparative TcR studies, we conclude with two hypotheses that we will test with further immunogenetic and functional studies in shark and other vertebrate models. First, the division between B and T cell repertoire diversification components and mechanisms was not as clear-cut in ancestral lymphocytes as in modern humans and mice. The second is that different vertebrate groups have not only evolved myriad diversifications for Ig repertoires and function, but TcR biology may be just as varied. This premise is already accumulating ample supporting evidence as IgHV domains (Parra et al., 2010; Parra et al., 2012), high allelic polymorphism (Criscitiello et al., 2004a; Criscitiello et al., 2004b), germline joined V exons (Wang and Miller, 2012; Wang et al., 2011), and now mechanisms such as SHM, all once considered the immune privilege of Ig or MHC genes, are also employed for TcRs.

Materials and methods

Study animals

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TCR sequence data used in this study came from two adult female nurse sharks (‘Joanie’ and ‘Mary Junior’; Ginglymostoma cirratum) delivered by caesarian section off the Florida Keys and matured in the aquatic vivarium of the University of Maryland’s Center of Marine Biotechnology. We used published T cell αV sequences (Criscitiello et al., 2010) as a baseline for αV locus numbering (sharks Yellow and 1299), though we did not analyze any of these sequences for mutation.

Total RNA isolation and cDNA synthesis

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We harvested tissues from animals after MS-222 (Argent, Redmond, WA) overdose, and immediately purified RNA with TRIzol reagent (Life Technologies, Carlsbad, CA). Nurse shark thymi are located dorsomedial to the gills (Luer et al., 1995) in the crevasse between the epaxial and brachial constrictor muscle groups. We used 5 ug total RNA from spiral valve, spleen, thymus, and peripheral blood leukocytes (PBL) for oligo-dT primed cDNA generation with Superscript III First Strand Synthesis System (Thermo Fisher Scientific, Inc., Waltham, MA). (Criscitiello et al., 2010) We estimated cDNA concentration using a Nanodrop 2000 Spectrophotometer (Thermo Fisher Scientific, Inc.).

RACE PCR, Cloning, and Sanger Sequencing

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We generated a 5’ RACE (Rapid Amplification of cDNA Ends) library using the GeneRacer Kit (Life Technologies) and reverse primers designed to the end of the shark TcRβ, TcRγ, or TcRδ variable (V) region or to the middle of the shark TcRα constant (C) region. We amplified RACE products using Phusion High-Fidelity DNA polymerase (New England Bio Labs, Inc., Ipswich, MA) to minimize PCR errors under these specific PCR conditions: primary denaturing at 94°C for 2 min; 30 cycles at 94°C for 30 s and 78°C for 1 min; and a final extension at 72°C for 10 min. Using this RACE library, we then amplified a specific α V region using a gene-specific primer to its leader region and the following PCR conditions: 98°C for 1 min; 25 cycles of 98°C for 5 s, 49–60°C for 30 s, 72°C for 150 s; 72°C for 10 min. Annealing temperatures varied for each amplified αV (see Table 7). We visualized PCR products with agarose gel (8%) electrophoresis and then excised bands of correct size. We then isolated amplified bands from agarose gels using the PureLink Quick Gel Extraction Kit (Life Technologies) or RICO chips (TaKaRa Bio USA, Mountain View, CA).

Table 7
List of forward (F) and reverse (R) primers used to generate T cell receptor (TcR) sequences and expression data.

[AID: Activation induced cytidine deaminase; B2M: beta-2 microglobulin; α: alpha; β: beta; γ: gamma; δ: delta; V: variable region; C: constant region].

https://doi.org/10.7554/eLife.28477.023
PrimerF/RIDLocationNucleotide sequence (5' to 3')Amino acidTm
TcR αV1FMFC370leader region of αV1ATG TTG CCT GAA GCT CMLPEA55
RMFC191alpha C regionCAT TGG TGG ATA GCA AGC CCT TCG ATSKGLLSTN76
TcR αV4FMFC122beginning of αV4GTC TCC TCA GTT GTT CGT ACVSSVVR58
RMFC123end of αV4CAG TAA TAC ACA GCA GCG TCDAAVYY58
FMFC374leader region of αV4TGG ATT GTG TGG GCA GTAWIVWAV54
RMFC191alpha C regionCAT TGG TGG ATA GCA AGC CCT TCG ATSKGLLSTN76
TcR αV5FMFC124beginning of αV5CTC AGG AAG GAG AGA TTA TCA CQEGEII60
RMFC125end of αV5CAA TGA TAC ACG GCG GAG TCDSAVYH60
FMFC124beginning of αV5CTC AGG AAG GAG AGA TTA TCA CQEGEII60
RMFC191alpha C regionCAT TGG TGG ATA GCA AGC CCT TCG ATSKGLLSTN76
TcR αV7FMFC376end of leader αV7AGC GAT GGA GTT TCT GTG ATTSDGVSVI58
RMFC191alpha C regionCAT TGG TGG ATA GCA AGC CCT TCG ATSKGLLSTN76
TcR αV10FMFC378leader region of αV10CTA TTT CTT CAC TAC CGC AGYFFTTA56
RMFC191alpha C regionCAT TGG TGG ATA GCA AGC CCT TCG ATSKGLLSTN76
TcR α 5'FGeneRacer 5' Nestedhomologous to RNA oligoGGA CAC TGA CAT GGA CTG AAG GAG TA--78
TcR α 3'RMFC191alpha C regionCAT TGG TGG ATA GCA AGC CCT TCG ATSKGLLSTN76
TcR βV1FMFC126beginning of bV1CTC CGT ACA TCG TCT CTA TTGPYIVSI60
RMFC127end of βV1CAC GCA CAG AAA TAG ACA GCAVYFCA58
TcR βV2FMFC128beginning of βV2CTA CGT GGA GCA GTC TCC ATCYVEQSP63
RMFC129end of βV2GCA CGC ACA ATA ATA GAC AGC CAVYYCAC62
TcR βV3FMFC130beginning of βV3CTA CGT GGA ACA GTC TCC TTCYVEQSP61
RMFC131end of βV3CAC GCG CAG AAA TAG ACA GVYFCA57
TcR βV5FMFCb50beginning of βV5GTT CGG TGC TCT TTC TCT GCMFGALSLH60
RMFCb54end of βV5GAC TGC AGT ATC AGT CGG CAC CLVPTDTAV66
TcR γV1FMFCg56beginning of γV1GTC GCT GTA TTA CTG GCT CAT TGMSLYYWL63
RMFCg59end of γV1GAG CGC ACA GTA ATA GGT GGC AGTATYYCAL67
TcR γV3FMFCg58beginning of γV3GAA GGG TCA CGT CCT TGC GMKGHVLA62
RMFCg61end of γV3GAT CCC AGA GTC ATC CTCEDDSGI56
FMFC170beginning of γV3CAA TAA CCA GAG CAC CGG GITRAP56
RMFC171end of γV3AGA TCC CAG AGT CGT CCT CEDDSGI56
TcR δV3FMFCd62beginning of δV3GAT TCC CCG TCC CTG GTG TCDSPSLVS65
RMFCd66end of δV3CAG TGC ACA GTG ATA CAC AGCAVYHCAL61
TcR δV5FMFCd63beginning of δV5GCA GCT ACT CAG TAT CTG GMQLLSIW57
RMFCd67end of δV5GAA AGC ACA GTA ATA CAG AGALYYCAF54
TcR δV7FMFC172beginning of δV7CTG TCA CTC AGT TAT TCT CCT CVTQLFS60
RMFC173end of δV7GCA GCC CAG TTA TAG TCA AACLTITGL60
TcR δV12FMFC174beginning of δV12CAG AGC CCA CCT CAG TTA CQSPPQ;60
RMFC175end of δV12GAG CGC AGT AAT AGA TGG CAIYYCA57
TcR δV16RMFC176end of δV16GCA GCT CCG AGA TAG ACA ACLSISEL60
FMFC177beginning of δV16GAG TCC TGG CTC ACG CAA TCESWLTQ63
TcR δV17FMFC178beginning of δV17CAG TCT TGG TCA GAA ATA ACCQSWSEIT57
RMFC179end of δV17CAA CTG AAG ATA AGT GAT CGITYLQL54
AIDFMFC342beginning of AID exon 1AGG CAC GAG ACC TAC ATG TTGRHETYML61
RMFC347end of AID exon 2TGA ACC AGG TGA GGC GGT AYRLTWF60
B2MFMFC211first cysteineAAC GTG TTG CTC TGT CAT GCNVLLCHA58
RMFC212before second cysteineGGG GTG AAC TCC ACA TAA CGRYVEFTP60

We transformed PCR amplicons into One-Shot Top10-competent cells (Thermo Fisher) using a pCR4-TOPO TA blunt end vector and cloning kit (Thermo Fisher) followed by a Zyppy plasmid miniprep kit (Zymo Research, Irvine, CA) for plasmid purification of individual clones (Criscitiello et al., 2012). We checked insert size using an Eco RI restriction enzyme (Promega Corp, Madison, WI), then amplified and purified the sequencing reaction using BigDye xTerminator Sequencing and Purification Kit (Thermo Fisher Scientific, Inc.). We submitted samples for sequencing to the DNA Technologies Core Lab on the Texas A and M University campus (College Station, TX). We deposited sequences in GenBank with the following accession numbers: Alpha KY189332-KY189354 and KY366469-KY355487; Beta KY351708-KY366487; Gamma KY351639-KY351707; Delta KY346705-KY346816.

Sequence alignment and tree building

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We used Geneious and BioEdit (v7.2.5, Ibis BioSciences, Carlsbad, CA) software to manage DNA sequence data. We aligned nucleotide and amino acid sequences using the ClustalW Multiple Alignment tool in Geneious with a gap penalty of 15, a gap extension penalty of 6.66, and free end gaps. We manually adjusted the alignments as necessary. We determined sequence relationships phylogenetically using the Geneious tree builder with default settings. We grouped sequences into unique V families based on 70% nucleotide sequence identity and 75% amino acid sequence identity (Brodeur and Riblet, 1984; Rumfelt et al., 2004) using the same α V numbering scheme as in Criscitiello et al. (2010). We created graphical alignments in BioEdit and imported these files into Microsoft Word to generate figures. Our preliminary dataset contained 564 TcRα clones (encoding 286 unique amino acid sequences representing nine Vα families) from three tissues (PBL, spleen, thymus) of two sharks (Joanie, Mary Junior). Using this dataset, we separated sequences containing identical CDR3 rearrangements and counted mutations within each TcR ‘clone family’ bearing the V-J rearrangement from single founder thymocytes.

Identification of TcR Vα genes in the nurse shark genome

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We probed the filter sets for the G. cirratum BAC library (Arizona Genomics Institute, Tucson, AZ) of shark ‘Yellow’ and screened with variable segment and constant region probes for TcRα and TcRδ. We cultured several positive clones and isolated BAC DNA according to manufacturer’s protocol with the Qiagen Large Construct Kit (Qiagen, Valencia, CA). We sent purified BAC DNA to the Duke University Center for Genomic and Computational Biology (Durham, NC) for PacBio SMRT (Menlo Park, CA) large insert (15–20 kb) library preparation, sequenced on the PacBio RSII platform with P6-C4 chemistry. Read correction and contig assembly were performed with the PBcR software (Koren et al., 2012), using the BLASR error correction method and the Celera Assembler 8.2. We annotated the resulting sequencing within the Geneious software suite (v9.1.5, Biomatters Ltd., Auckland, NZ) using a custom BLAST database of all TcR and IgH sequences for G. cirratum in the IMGT database (Montpellier, France).

Our search yielded 17 α/δ V germline segments, significantly fewer than expected based on TcR αV segment numbers in other species (Murphy and Weaver, 2017). Of these 17 segments, only 13 contained unique nucleotide sequences, and all V segments were highly similar to each other (69–100% nucleotide and 52–100% amino acid identity). Twelve germline V segments shared >93% nucleotide identity (>85% amino acid identity), with three segments differing by only a single nucleotide (Figure 11). Based on the variability we observed in our sequence data, these 17 germline α/δ V segments must represent only a small portion of the available Vs in the nurse shark genome.

We compared these 17 germline α/δ V segments to our TcR αV database containing all nine potential V families from two different sharks. All 17 germline α/δ V segments aligned to our αV4 data with >75% nucleotide identity, while 15 segments shared >93% nucleotide identity to at least one sequence in our αV4 dataset. Of the 60 sequences in our αV4 dataset, 37 sequences aligned specifically to eight germline α/δ V segments, with alignments containing one to 17 aV4 sequences per germline segment (nucleotide alignments shared >97% identity; Figure 12.). While we did observe nucleotide differences within alignments, most differed by fewer than four nucleotides from the germline α/δ V segments. Because several germline segments differed by only a single nucleotide and we are certain that we have not found all α/δ V segments in the genome, these differences could represent variation in alleles or individuals rather than mutation. Thus, we chose not to rely on these data for mutational analysis.

Observed TcR Alpha/Delta germline Vs exhibit high sequence identity.

Nucleotide (A) and amino acid (B) alignments of 17 germline variable (V) region gene segments. Two V groups contained three identical germline gene segments each (highlighted in gray), leaving only 13 unique V gene segments. Boxes surround conserved amino acids. Numbers at the ends of sequences indicate percent identity to the first germline sequence (α/δ V5) within the alignment.

https://doi.org/10.7554/eLife.28477.024
Observed germline sequences align only to TcR αV4 clones.

Nucleotide alignments of TcR αV4 thymocyte clones to known germline V segments. Highlighted and underlined bases denote nonsynonymous and synonymous differences (respectively) to the germline V segment. Boxed regions represent nucleotides of the third complementarity-determining region (CDR3) according to IMGT guidelines, accounting for differences between clone and germline sequences. We highlight the single nucleotide/amino acid change between α/δ V7 and α/δ V10 germline segments in red.

https://doi.org/10.7554/eLife.28477.025

Mutation frequency

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We defined mutation frequency as the number of nucleotide changes divided by the total number of nucleotides within a particular region (e.g. FR, CDR, J, C) based on differences to a consensus sequence. We classified all nucleotide changes as either synonymous (SYN) or non-synonymous (NSYN) mutations based on whether or not the codon was unaltered or altered, respectively. For tandem base changes, we assessed the effect of each nucleotide change independent of its neighboring mutation(s). We then compared mutation frequencies between CDR and FR regions for all clone families that contained mutations using a Student’s 1-tailed t-test unless otherwise noted.

Determination of hotspots

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We searched for the ProSite motifs DGYW/WRCH (G:C mutable target) and WA/TW (A:T mutable target) using the motif search function in Geneious. These motifs serve as common ‘hotspots’ for SHM within Ig variable regions, where AID favors the G/C bases within DGYW/WRCH motifs during the first phase of SHM while low-fidelity polymerases (i.e., polymerase η) preferentially target A/T bases within WA/TW motifs during the second phase of SHM (Wei et al., 2015; Rogozin and Diaz, 2004; Chen et al., 2012). We counted only motifs present in the consensus sequence (rather than those created by the mutation) as hotspots. For each domain, we first counted the number of target nucleotides within DGYW/WRCH or WA/TW hotspots. We then examined each mutation to determine if it occurred inside or outside a hotspot. We counted changes from the consensus sequence to a target nucleotide within its respective motif as a hotspot mutation. We defined the frequency of hotspot mutation as the number of mutations (of target nucleotides) occurring within hotspots divided by the total number of mutations for each region. From these data, we compared the mutability of bases between FR and CDR regions using χ2 Analysis.

Base substitution indices

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We calculated a mutability index for each nucleotide using methods similar to Chen et al. (2012). In our case, we derived the expected number of mutations by multiplying the frequency of a particular nucleotide within a family of sequences (e.g. α V2) by the total number of observed mutations within that family. We then defined the mutability index as in Chen et al. (2012) [the observed number of mutations of a specific nucleotide divided by the expected number of mutations of that nucleotide, with a value of 1.00 indicating random mutation]. We used χ2 analysis to compare mutability indices between FR and CDR regions.

In situ hybridization

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We used thymus tissue from an adult nurse shark for in situ hybridization as previously described (Criscitiello et al., 2010). We generated a probe for G. cirratum AID mRNA with primers NSAIDEH2 and NSAIDEH1 (Table 7) designed to amplify 211 base pairs of cDNA sequence of the first two AID exons (sequence and primers kindly shared by Ellen Hsu). We acquired images on an Axioscop2 microscope with AxioCam MRc5 (Zeiss, Thornwood CT) using Zeiss Axio Vision software.

Additionally, we performed fluorescence in situ hybridization (FISH) on adult nurse shark (‘Black’) thymus tissue. Slides contained two 8 μm thick sections of flash frozen thymus tissue preserved in OCT. We designed custom Stellaris FISH Probes against the TcR alpha constant region (αC) for T cell identification and exons 1 and 2 of AID by utilizing the Stellaris RNA FISH Probe Designer (Biosearch Technologies Inc., Petaluma, CA) available online at www.biosearchtech.com/stellarisdesigner (Version 2). We hybridized TcR αC with the CalFluor Red 610 fluorophore and the AID sequence with the Quasar 670 fluorophore for the Stellaris RNA FISH Probe set (Biosearch Technologies, Inc.). We followed all manufacturer’s instructions for frozen tissue (available online at www.biosearchtech.com/stellarisprotocols), allowing hybridization probes to incubate for 16 hr. We counterstained slides with wash buffer containing 5 ng/mL of DAPI (Sigma-Aldrich, St. Louis, MO). We obtained 10x, 20x, and 63x images using a Zeiss Stallion Digital Imaging Workstation including a 2x CoolSnap HQ Camera and Zeiss Stallion software. We merged Z-stacked images of each fluorophore together and edited and processed images using ImageJ software, version 1.47 (Schneider et al., 2012).

Real-time qPCR for AID expression

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We synthesized cDNA from nurse shark spleen, thymus, muscle, and forebrain RNA (see RNA purification and extraction methods above) using SuperScript III First-strand Synthesis System (Thermo Fisher Scientific, Inc.) and a 1:1 mixture of oligo-dT and random hexamer primers. We then amplified cDNA using touchdown PCR on an MJ mini thermal cycler (Bio-Rad, Hercules, CA) and GoTaq colorless DNA polymerase (Promega Corp) using the following conditions: primary denaturing at 94°C for 2 min, five cycles at 94°C for 30 s and 56°C for 4 min; five cycles at 94°C for 30 s and 54°C for 4 min; 20 cycles at 94°C for 30 s, and 52°C for 30 s, and 72°C for 4 min; with a final extension at 72°C for 10 min. We visualized PCR products using agarose gel electrophoresis (as described above) to verify presence of AID in each tissue. We then cloned and sequenced the resulting PCR products to confirm the sequence was AID.

We looked for relative AID expression in shark spleen (positive control, where B cell AID-mediated SHM is known to occur), thymus, and forebrain (negative control) at four tissue concentrations (50 ng, 25 ng, 12.5 ng, and 6.25 ng) using the SYBR-green RT-PCR reagents kit (Thermo Fisher Scientific, Inc.) on a LightCycler 480 System (Roche Diagnostics Corp, Indianapolis, IN). We analyzed relative quantification using the LightCycler480 software and quantified relative AID expression using the ΔΔCq method. We normalized results against shark muscle tissue using beta2-microglobulin (β2M) as a reference gene. We present data as expression-fold changes of AID to β2M.

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Decision letter

  1. David G Schatz
    Reviewing Editor; Yale University School of Medicine, United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "Somatic hypermutation of T cell receptor α chain contributes to thymic positive selection in nurse sharks thymus" for consideration by eLife. Your article has been favorably evaluated by Michel Nussenzweig (Senior Editor) and three reviewers, one of whom, David Schatz (Reviewer #1), served as a Guest Reviewing Editor. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

The authors demonstrate and characterize somatic hypermutation (SHM) in TcRα, γ, and δ chains in the nurse shark. TcRα hypermutation is described for the first time in any TcRαβ system, although it was previously observed in sandbar shark TcRγδ chains. No mutation was observed for nurse shark TcRβ. SHM had been predicted to be disallowed in TcRαβ systems as it was never observed in mammals and has the potential to disrupt TcR-MHC I/II interactions. The findings here challenge that view and suggest that at least in shark, SHM of TcRα in the thymus contributes to repertoire diversification and potentially to α-β T cell positive selection. Consistent with the findings from TcR chain sequencing, the authors provide evidence in favor of AID expression in the thymic cortex and corticomedullary junction. The authors are experts in the field of comparative VDJ immunity and have published widely on this topic. The presentation of the findings and the discussion of their implications are clear and interesting. The finding highlights an important and unexpected aspect of TcR biology with implications for TcRαβ function in jawed vertebrates. This study should be of significant general interest to immunologists and evolutionary biologists.

Essential revisions:

1) The major challenge facing the authors is that they do not have the germline sequence of most nurse shark Vαα gene segments, and hence they have to infer a germline sequence from the cDNA sequences they obtain. To do this, the authors assume that if the same CDR3 sequence arises more than once, it must derive from the same original V-to-J rearrangement, and hence that sequence differences between two such clones must represent somatic mutations. Unfortunately, while this argument is strong for IgH, TcRδ, and TcRβ sequences that include D segments, it is potentially weak for TcRα rearrangements where a single joint is formed and junctional diversity can be low. To have confidence that duplicate CDR3 sequences represent unique rearrangements, one would want to examine the extent of nucleotide deletion and addition; only in joints with significant addition/deletion would one be confident that the junction is likely to be unique. The problem is compounded by the fact that VDJ recombination has a tendency to use microhomologies (if they exist) at the ends of the two gene segments to mediate joining, and this can lead to the same junction repeatedly. Was the same CDR3 sequence ever observed in different sharks? The authors need to justify their underlying assumption and provide an explicit discussion of the specificity of CDR3 sequence for rearrangements in each chain.

2) In addition, the data contain a significant puzzle: a very high level of shared CDR3 among a relatively small number of unique sequences. Specifically, 72 unique amino acid sequences, representing 12 V-α families, were obtained, which would correspond to an average of 6 unique sequences per V family, and an average of only 3 unique sequences per V family per shark. Given that the starting 5 microgram aliquots of RNA should derive from hundreds of thousands of cells, each starting RNA sample should contain a large number of independent V-J rearrangements for any given V. Given this and that there appear to be multiple Jα gene segments in the nurse shark, the chance of finding the same CDR3 sequence in a handful of sequences for a given V would be predicted to be very low. The chance of finding 42 sequences out of the 72 (more than half!) that share CDR3 with another sequence seems exceedingly unlikely. The authors need to carefully address this issue. The authors should provide a table that lists the number of unique aa sequences obtained for each V family within the 72 sequences, and of those, the number that have an identical CDR3.

The authors did in fact derive the germline sequence of two V family members (V4 and V9). Why not focus the analysis on these two families, where such ambiguities would be less of an issue? Furthermore, one of the reported set of sequences does arise from the V4 family, but it does not appear that the germline sequence information was taken advantage of. Why? And, were other sequences from V4 and V9 obtained in the dataset, and did they show mutations compared to the germline sequences?

It is noted that all reviewers agreed that the nature of the sequence differences observed (focus on hotspots, abundance of tandem mutations, etc.) are consistent with the mutations being real SHM events.

3) Expression of Aicda is not particularly clear in the ISH analysis. The data show a generally darker appearance with the antisense compared to the sense probe, but these differences are not completely convincing. Furthermore, it was difficult to distinguish the cortex vs. the medulla and the appearance is so uniform overall that claims for region specificity for Aicda are unconvincing. More annotation highlighting thymic structure and the probes used would be helpful. Scale bars should be included instead of objective magnification. Overall, it was felt that the Aicda ISH data need to be improved. Possibly other images or higher magnification images would help.

4) There were some concerns about the Aicda RT-PCR data. The results are expressed in delta Ct, which is a logarithmic measure, and it would be better to calculate a fold-difference in the expression of AID in spleen and thymus. How much of a difference in expression is there between the negative control (forebrain) and thymus? Was the resulting PCR product cloned and sequenced to confirm its identity? Are there B cells in the nurse shark thymus as there are in mouse and perhaps other cartilaginous fish such as the skate? If so, are the authors sure that AID expression is in T cells in the ISH and RT-PCR analyses? The authors should consider discussing this in the manuscript.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Somatic hypermutation of T cell receptor α chain contributes to positive selection in nurse shark thymus" for further consideration at eLife. Your article has been favorably evaluated by Michel Nussenzweig (Senior Editor) and three reviewers, one of whom served as Guest Reviewing Editor.

The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:

The authors have added new RNA fluorescence in situ hybridization data that strengthen the claim that AID is expressed in the shark thymus, and have adequately addressed some of the points previously raised. There remain a number of significant issues that need to be addressed satisfactorily before publication can be considered.

Major Points:

1) Based on the information provided by the authors in their response to the review, it is now clear that the analysis of mutations in TcRβ, γ, and δ (no CDR3 sequence obtained) was less rigorous and less definitive than in TcRαα (and, the TcRβ analysis is weaker than the rest because of the small number of sequences obtained (56)). Hence, all claims that mutations were not found in TcRβ must either be removed or carefully qualified. For example, the second sentence of the Abstract contrasts the findings at TcRβ (no mutation) and TcRα (mutation found) with no qualification, leaving the reader with the mistaken impression that the two analyses were equivalent and the two conclusions equally strong. The same problem was found in the last paragraph of the Introduction, subsection “Somatic hypermutation in TcR γV and TcR δV but not TcR βV”, and in the third paragraph of the Discussion.

2) "Since it is highly improbable that two thymocytes would generate identical CDR3 sequences during VJ recombination…" As was pointed out in the original review, this claim is not obvious; it should not be stated in this fashion. Indeed, there are a priori reasons to think that the same CDR3 sequence could readily arise from independent V-J rearrangements. The authors should present this claim as a hypothesis that they then carefully validate with data (which they begin to do in the first paragraph of the subsection “Somatic hypermutation in nurse shark TcR αV”). Furthermore, the conclusion of this sentence that "amplicons containing identical CDR3 sequences must have derived from the same progenitor" is overstated. At best, the conclusion could be that they are "likely to have derived from the same progenitor". A statistical analysis of the V-J sequences might allow the authors to make a quantitative claim of just how likely this is, but in the absence of such an analysis, the claims should be stated cautiously. The manuscript needs to be rewritten to accommodate these points. Same issue in the aforementioned paragraph.

3) Closely related to this: The authors have clarified that a larger number of sequences were obtained than was apparent in the initial submission, but this information is not provided in the Results section. Since most readers will not look at the Materials and methods section, it is suggested that the authors add information to the second paragraph of the subsection “Somatic hypermutation in nurse shark TcR αV” to inform readers of the total number of underlying sequences from the two relevant sharks. In addition, the Materials and methods states that sequences were obtained from four sharks; it is confusing that data from only two of the sharks was actually used. Why are all 4 sharks mentioned if data from only two of them were used? How many total sequences were obtained from the two relevant sharks? This is highly relevant given that these are (apparently) the only data from which the analyzed TcRα sequences are derived. This is directly relevant to the concern, expressed in the original review, that the identification of so many repeated CDR3 regions from a small sequence dataset is extremely unlikely. This issue has not been satisfactorily resolved in the resubmission. The requested table that shows how many unique aa sequences were obtained for each V family, and of those, the number that have an identical CDR3, was not provided. Nor have the authors provided a detailed description of the proportion of TcRα sequences that have N/P nucleotides (which would provide higher confidence of assigning SHM) versus those that are directly joined (less confidence). The reviewers remain concerned by the possibility that the number of repeat CDR3 sequences is exceedingly unlikely given the number of sequences obtained. The authors should carefully address this concern.

4) The new RNA fluorescence FISH analysis is a significant improvement over the ISH analysis, but despite the claimed specificity of the method used, experiments to document specificity are needed. Ideally, a tissue not expressing AID would be analyzed (or do the authors feel that the negative portions of the thymus provide sufficient specificity controls?). Given that the authors now present a detailed model for AID expression/SHM in shark thymus (Figure 10) based on the RNA fluorescence FISH data, it is particularly important to address specificity.

5) The claim made in the last paragraph of the subsection “Mutations, in situ hybridization, and AID expression in thymus “that TcRα expression is more diffuse than that of AID is unconvincing. TcRαA and AID expression appear to coincide in all areas visible in Figure 9. The authors should not push their interpretation just because it fits with the proposed role of AID in selection. Similarly, the organization of AID in rings around TcRα+ regions is intriguing and while the authors' interpretation in terms of relative timing of expression is plausible, it is quite speculative and should be clearly stated as such.

6) The in situ hybridization in Figure 8B (panels 3,4) for AID is still hard to interpret as the signal is weak and diffuse. The apparent expression pattern suggested by these images does not seem to correspond to the localized patterns seen in the fluorescent in situs in Figure 9 and Figure 9—figure supplement 1. Why is this? Is this a matter of scale? It is a concern that one set of data seems to contradict the other.

https://doi.org/10.7554/eLife.28477.032

Author response

Essential revisions:

1) The major challenge facing the authors is that they do not have the germline sequence of most nurse shark Vα gene segments, and hence they have to infer a germline sequence from the cDNA sequences they obtain. To do this, the authors assume that if the same CDR3 sequence arises more than once, it must derive from the same original V-to-J rearrangement, and hence that sequence differences between two such clones must represent somatic mutations. Unfortunately, while this argument is strong for IgH, TcRδ, and TcRβ sequences that include D segments, it is potentially weak for TcRα rearrangements where a single joint is formed and junctional diversity can be low. To have confidence that duplicate CDR3 sequences represent unique rearrangements, one would want to examine the extent of nucleotide deletion and addition; only in joints with significant addition/deletion would one be confident that the junction is likely to be unique. The problem is compounded by the fact that VDJ recombination has a tendency to use microhomologies (if they exist) at the ends of the two gene segments to mediate joining, and this can lead to the same junction repeatedly. Was the same CDR3 sequence ever observed in different sharks? The authors need to justify their underlying assumption and provide an explicit discussion of the specificity of CDR3 sequence for rearrangements in each chain.

In our shark sequences, we found substantial diversity within CDR3 regions. We present data to illustrate CDR3 junctional diversity and include a new figure (Figure 4) depicting this diversity. (We observed similar results in other α V segments as well.) We never observed the same CDR3 sequence in more than one shark.

We included a paragraph under the “Somatic hypermutation in nurse shark TcR αV” section of the results to discuss these data: “Despite the absence of diversifying segments, α CDR3s exhibited substantial variation within our shark sequences. For example, TcRα V1 sequences using the same V and J segments had CDR3 lengths that differed by as many as 6 amino acids (12 nucleotides), and few CDR3s shared more than one amino acid within this V-J join (Figure 4). Further, we never observed the same CDR3 sequence in more than one shark, suggesting both exonuclease activity and addition of N and P nucleotides help diversify α CDR3s in nurse shark.”

2) In addition, the data contain a significant puzzle: a very high level of shared CDR3 among a relatively small number of unique sequences. Specifically, 72 unique amino acid sequences, representing 12 V-α families, were obtained, which would correspond to an average of 6 unique sequences per V family, and an average of only 3 unique sequences per V family per shark. Given that the starting 5 microgram aliquots of RNA should derive from hundreds of thousands of cells, each starting RNA sample should contain a large number of independent V-J rearrangements for any given V. Given this and that there appear to be multiple Jα gene segments in the nurse shark, the chance of finding the same CDR3 sequence in a handful of sequences for a given V would be predicted to be very low. The chance of finding 42 sequences out of the 72 (more than half!) that share CDR3 with another sequence seems exceedingly unlikely. The authors need to carefully address this issue. The authors should provide a table that lists the number of unique aa sequences obtained for each V family within the 72 sequences, and of those, the number that have an identical CDR3.

As written, the paper does suggest an incredible coincidence of shared CDR3s among our sequences. However, we actually acquired significantly more sequences than the 72 we describe in the paper. We have revised this section to include a discussion of the total number of sequences (564) from which we found those with shared CDR3s.

Within the Materials and methods section titled “Sequence Alignment and Tree Building,” we added: “Our preliminary dataset contained 564 TcRα clones (encoding 286 unique amino acid sequences representing nine Vα families) from three tissues (PBL, spleen, thymus) of four sharks (Joanie, Mary Junior, Yellow, and 1299). Using this dataset, we separated sequences containing identical CDR3 rearrangements and counted mutations within each TcR “clone family” bearing the V-J rearrangement from single founder thymocytes.”

The authors did in fact derive the germline sequence of two V family members (V4 and V9). Why not focus the analysis on these two families, where such ambiguities would be less of an issue? Furthermore, one of the reported set of sequences does arise from the V4 family, but it does not appear that the germline sequence information was taken advantage of. Why? And, were other sequences from V4 and V9 obtained in the dataset, and did they show mutations compared to the germline sequences?

We added two figures and a couple of paragraphs in the Materials and methods section “Identification of TcR Genes in the Nurse Shark Genome” explaining our reasons for not using germline alignments for SHM analysis:

“Our search yielded 17 α/δ V germline segments, significantly fewer than expected based on TcR αV segment numbers in other species (Murphy and Weaver, 2017). […] Thus, we chose not to rely on these data for mutational analysis.”

It is noted that all reviewers agreed that the nature of the sequence differences observed (focus on hotspots, abundance of tandem mutations, etc.) are consistent with the mutations being real SHM events.

3) Expression of Aicda is not particularly clear in the ISH analysis. The data show a generally darker appearance with the antisense compared to the sense probe, but these differences are not completely convincing. Furthermore, it was difficult to distinguish the cortex vs. the medulla and the appearance is so uniform overall that claims for region specificity for Aicda are unconvincing. More annotation highlighting thymic structure and the probes used would be helpful. Scale bars should be included instead of objective magnification. Overall, it was felt that the Aicda ISH data need to be improved. Possibly other images or higher magnification images would help.

We present new fluorescence in situ hybridization (FISH) data to illustrate more clearly the thymic architecture and regional specificity of AID expression within the shark thymus. The development of this technique delayed our resubmission. In a new figure (Figure 9), we provide a composite of seven Z-stacked images (10x) depicting the localization of AID expression to the cortico-medullary junction and medullary regions of shark thymus. We also present individual fluorophore images of DAPI, TcRα, and AID and the Z-stacked merged images (10x, 20x, and 63x) to illustrate the pattern of AID and TcRα expression within four locations of shark thymus. To ensure our probes were hybridizing independently of one another, we probed AID and TRA individually on adjacent slides and looked for co-localization of the probes (see Figure 9—figure supplement 1).

We also included a paragraph in the Results section describing these data: “We confirmed our colorimetric ISH results with RNA fluorescence in situ hybridization (FISH) using probes against the TcR α constant region (αC) and exons 2 and 3 of AID. […] These daughter T cells then express AID, promoting somatic hypermutation within their TcR α sequences during a time when cells also undergo positive and negative selection.”

4) There were some concerns about the Aicda RT-PCR data. The results are expressed in delta Ct, which is a logarithmic measure, and it would be better to calculate a fold-difference in the expression of AID in spleen and thymus. How much of a difference in expression is there between the negative control (forebrain) and thymus?

We present expression-fold changes in the different tissues (see Figure 8A). We also included the expression-fold difference between forebrain and thymus: “We confirmed the expression of AID in the thymus through real-time RT-qPCR, where thymus tissue expressed AID at roughly half (0.7x) the levels found in spleen (where B cell SHM is known to occur) and nearly 6x the levels observed in forebrain (negative control; Figure 8A).”

Was the resulting PCR product cloned and sequenced to confirm its identity?

Yes. We included a sentence in the qPCR Materials and methods section to inform readers: “We then cloned and sequenced the resulting PCR products to confirm the sequence was AID.”

Are there B cells in the nurse shark thymus as there are in mouse and perhaps other cartilaginous fish such as the skate? If so, are the authors sure that AID expression is in T cells in the ISH and RT-PCR analyses? The authors should consider discussing this in the manuscript.

We addressed thymic B cells in the Discussion: “Although recent studies report B cells present in the thymus of mice (Perera and Huang, 2015, Perera et al., 2013), Miracle et al. (2001) examined B cell expression levels (IgM and IgX) in various tissues (including thymus) at different ages in the clearnose skate. […] Further, preliminary results using FISH probes to IgM constant region also indicate that adult nurse sharks do not express IgM in the thymus."

These preliminary data (both RT-qPCR and FISH) give us confidence that the phenomenon we are seeing is not due to the presence of B cells in the thymus. However, these data are part of a larger study with a different aim, and we prefer not to report the data in this paper. However, we provide them here for you to assess their potential importance. The bar graph (Author response image 1) illustrates RT-qPCR expression of various immune cell markers in thymus tissue from sharks of varying ages. The red bars indicate IgM/IgW expression, which is clearly absent in the older sharks (red box).

Using FISH (Author response image 2), we found many IgM transcripts expressed in spleen (right) but few expressed in thymus (right). With the lack of IgM expression indicated by RT-qPCR, this may suggest that cells transcribe the IgM message when the DNA is open and the cell also is transcribing TcR genes, but translation of the IgM message does not occur. We need more evidence to make further conclusions.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Major Points:

1) Based on the information provided by the authors in their response to the review, it is now clear that the analysis of mutations in TcRβ, γ, and δ (no CDR3 sequence obtained) was less rigorous and less definitive than in TcRα (and, the TcRβ analysis is weaker than the rest because of the small number of sequences obtained (56)). Hence, all claims that mutations were not found in TcRβ must either be removed or carefully qualified. For example, the second sentence of the Abstract contrasts the findings at TcRβ (no mutation) and TcRα (mutation found) with no qualification, leaving the reader with the mistaken impression that the two analyses were equivalent and the two conclusions equally strong. The same problem was found in the last paragraph of the Introduction, subsection “Somatic hypermutation in TcR γV and TcR δV but not TcR βV”, and in the third paragraph of the Discussion.

Agreed. We are in the process of repeating the mutation analysis of the other chains to the same rigor as α. Collecting enough CDR3-sharing sequences is taking some time. However, for this manuscript, we removed language that implies the analyses or conclusions are equivalent. In the above order, these changes are as follows:

“Remarkably, we found SHM acting in the thymus on α chain of shark T cell receptors (TcR).”

“Our data suggest that SHM of TcRα is involved in primary T cell repertoire diversification and the enhancement of positive selection in the thymic cortex.”

“Somatic hypermutation in TcR γV and TcR δV”.

“Remarkably we also detected SHM occurring in the α chain of αβ T cells.”

2) "Since it is highly improbable that two thymocytes would generate identical CDR3 sequences during VJ recombination…" As was pointed out in the original review, this claim is not obvious; it should not be stated in this fashion. Indeed, there are a priori reasons to think that the same CDR3 sequence could readily arise from independent V-J rearrangements. The authors should present this claim as a hypothesis that they then carefully validate with data (which they begin to do in the first paragraph of the subsection “Somatic hypermutation in nurse shark TcR αV”). Furthermore, the conclusion of this sentence that "amplicons containing identical CDR3 sequences must have derived from the same progenitor" is overstated. At best, the conclusion could be that they are "likely to have derived from the same progenitor". A statistical analysis of the V-J sequences might allow the authors to make a quantitative claim of just how likely this is, but in the absence of such an analysis, the claims should be stated cautiously. The manuscript needs to be rewritten to accommodate these points. Same issue in the aforementioned paragraph.

We modified this section to be less speculative. “Since it is highly unlikely that two thymocytes would generate identical CDR3 sequences during VJ recombination, we predict that amplicons containing identical CDR3 sequences derived from the same progenitor and thus must contain the same germline V and J segments. […] Therefore, even in the absence of an assembled locus, we were able to evaluate mutation to germline αV segments by considering changes within only those thymocyte clones containing identical CDR3s.”

3) Closely related to this: The authors have clarified that a larger number of sequences were obtained than was apparent in the initial submission, but this information is not provided in the Results section. Since most readers will not look at the Materials and methods section, it is suggested that the authors add information to the second paragraph of the subsection “Somatic hypermutation in nurse shark TcR αV” to inform readers of the total number of underlying sequences from the two relevant sharks. In addition, the Materials and methods states that sequences were obtained from four sharks; it is confusing that data from only two of the sharks was actually used. Why are all 4 sharks mentioned if data from only two of them were used? How many total sequences were obtained from the two relevant sharks? This is highly relevant given that these are (apparently) the only data from which the analyzed TcRα sequences are derived. This is directly relevant to the concern, expressed in the original review, that the identification of so many repeated CDR3 regions from a small sequence dataset is extremely unlikely. This issue has not been satisfactorily resolved in the resubmission. The requested table that shows how many unique aa sequences were obtained for each V family, and of those, the number that have an identical CDR3, was not provided. Nor have the authors provided a detailed description of the proportion of TcRα sequences that have N/P nucleotides (which would provide higher confidence of assigning SHM) versus those that are directly joined (less confidence). The reviewers remain concerned by the possibility that the number of repeat CDR3 sequences is exceedingly unlikely given the number of sequences obtained. The authors should carefully address this concern.

We apologize for not including the requested table. We misunderstood the initial request. We include this table now (Table 1) and discuss the table in the Results section titled “Somatic hypermutation in nurse shark TcR αV”:

“Our preliminary V α dataset contained 539 TcRα clones (encoding 286 unique amino acid sequences representing nine V α families) from three tissues (PBL, spleen, thymus) of two sharks (Joanie, Mary Junior). […] We include these 45 sequences in our TcR Vα dataset (see Table 1 – source data for sequence data).”

During the construction of this new table, we realized we had omitted sequences in our initial mutation analysis. Further, we decided to divide our aV4 group so that we estimated mutation even more conservatively. Thus, we reanalyzed our entire mutation data set. While the overall conclusions of this study did not change, some of the results did change. Most notably, we found that A:T mutations did not prefer WA/TW hotspots. This is consistent with data reported in sandbar sharks for TcR γ (Chen et al., 2012). However, our data suggest a different A:T motif may be targeted or that sharks employ a different mechanism than DNA pol eta use during mismatch repair to alter A:T nucleotides.

“A:T nucleotides did not appear to prefer WA/TW hotspots (p=0.2248), though they were 2.3x as likely to mutate within hotspots than outside hotspots. […] This result suggests that an alternate A:T motif is targeted or that sharks employ another mechanism altogether to alter A:T nucleotides.”

Further, we no longer found a significant difference in tandemly mutated bases between CDRs and FRs, which is consistent with results observed for TcR-γ in sandbar sharks. “Finally, though we found more tandemly mutated bases in CDRs (41 of 81, or 50.6% of all CDR mutations) than in FRs (73 of 192, or 38.0% of all FR mutations), this difference was not significant; p=0.721; Table 2).”

We also added a section at the beginning of the Materials and methods to clarify the confusion over sharks. We used sequences from only two sharks in our mutation analyses. However, we used published data from two different sharks to aid in loci identification to ensure consistency. This paragraph reads as follows: “Study Animals: TCR sequence data used in this study came from two adult female nurse sharks (“Joanie” and “Mary Junior”; Ginglymostoma cirratum) delivered by caesarian section off the Florida Keys and matured in the aquatic vivarium of the University of Maryland’s Center of Marine Biotechnology. We used published T cell αV sequences (Criscitiello et al., 2010) as a baseline for αV locus numbering (sharks Yellow and 1299), though we did not analyze any of these sequences for mutation.”

As for the presence of N/P nucleotides, please see our response to #2, above.

4) The new RNA fluorescence FISH analysis is a significant improvement over the ISH analysis, but despite the claimed specificity of the method used, experiments to document specificity are needed. Ideally, a tissue not expressing AID would be analyzed (or do the authors feel that the negative portions of the thymus provide sufficient specificity controls?). Given that the authors now present a detailed model for AID expression/SHM in shark thymus (Figure 10) based on the RNA fluorescence FISH data, it is particularly important to address specificity.

We analyzed a non-immune tissue (shark brain) as a negative FISH control for AID and TcRα fluorescence. We created a new supplementary figure with images of these slides (Figure 9—figure supplement 2). This figure depicts some background fluorescence regardless of probe application. However, we observed no AID or TcRα expression in brain tissue like the patterns we saw in thymus (immune tissue).

5) The claim made in the last paragraph of the subsection “Mutations, in situ hybridization, and AID expression in thymus “that TcRα expression is more diffuse than that of AID is unconvincing. TcRαA and AID expression appear to coincide in all areas visible in Figure 9. The authors should not push their interpretation just because it fits with the proposed role of AID in selection. Similarly, the organization of AID in rings around TcRα+ regions is intriguing and while the authors' interpretation in terms of relative timing of expression is plausible, it is quite speculative and should be clearly stated as such.

We modified the text to better reflect what our images depict (see also #7, below). “Our FISH results indicated a more specific TcR αC signal within the inner cortex and medulla adjacent to the CMJ (Figure 9; Figure 9—figure supplement 1), regions where, in mammals, cells actively rearrange their α chain and where mature αβ T cells are found. […] Thus, we observed a consistent pattern of expression where a “ring” of cells expressing both TcR αC and AID surround a central cell expressing only TcR αC.”

6) The in situ hybridization in Figure 8B (panels 3,4) for AID is still hard to interpret as the signal is weak and diffuse. The apparent expression pattern suggested by these images does not seem to correspond to the localized patterns seen in the fluorescent in situs in Figure 9 and Figure 9—figure supplement 1. Why is this? Is this a matter of scale? It is a concern that one set of data seems to contradict the other.

We auto-adjusted the colors on the CISH image in ImageJ to darken the signal expression [old image (L) and darkened image (R), Author response image 3]. We adjusted images in all eight panels uniformly, ensuring we did not alter expression differences between panels. This should make it easier to see the signal itself, with AID expression localized to the cortex and CMJ and minimal expression within the medulla.

As you point out, it is a much more diffuse signal. Because the Stellaris FISH method uses a mixture of short probes for binding the transcript, the pattern we see in the is much more specific – the image will only show those areas with many bound probes rather than the presence of a transcript in general. For example, the CISH image of TcR αC from Criscitiello et al.,2010 (Author response image 4) shows a much more diffuse pattern of expression than what we see with FISH as well.

We believe the expression patterns revealed with the two different methods are both correct, but they tell us different things. AID (and TcR αC) expression occurs throughout the cortex (and medulla for TcR αC; based on the diffuse signal from CISH), but the greatest expression of both messages occurs near the CMJ (based on the much more precise and higher intensity signal from FISH). We currently are working with another method that incorporates both a colorimetric and fluorescent signal to verify this explanation, but we have not been successful with that approach yet.

We modified the text to explain this difference in method.

CISH section: “Further, colorimetric in situ hybridization (CISH) of nurse shark thymus revealed a diffuse signal of TcR β (Figure 8B, panels 1,2) and AID (Figure 8B, panels 3,4) mRNA expression throughout the thymic cortex. However, AID expression was greatest in the central cortex and cortico-medullary junction (CMJ), while TcR β expression was highest in the outer cortex.”

FISH section: “We refined our CISH results with RNA fluorescence in situ hybridization (FISH) using probes against the TcR α constant region (αC) and exons 2 and 3 of AID. […] These daughter T cells then express AID (and TcR αC), promoting somatic hypermutation within their TcR α sequences during a time when cells also undergo positive and negative selection.”

https://doi.org/10.7554/eLife.28477.033

Article and author information

Author details

  1. Jeannine A Ott

    Comparative Immunogenetics Laboratory, Department of Veterinary Pathobiology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, Texas, United States
    Contribution
    Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3537-8631
  2. Caitlin D Castro

    Department of Microbiology and Immunology, University of Maryland at Baltimore, Baltimore, United States
    Contribution
    Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
  3. Thaddeus C Deiss

    Comparative Immunogenetics Laboratory, Department of Veterinary Pathobiology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, Texas, United States
    Contribution
    Software, Formal analysis, Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  4. Yuko Ohta

    Department of Microbiology and Immunology, University of Maryland at Baltimore, Baltimore, United States
    Contribution
    Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
  5. Martin F Flajnik

    Department of Microbiology and Immunology, University of Maryland at Baltimore, Baltimore, United States
    Contribution
    Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing—review and editing
    Competing interests
    No competing interests declared
  6. Michael F Criscitiello

    1. Comparative Immunogenetics Laboratory, Department of Veterinary Pathobiology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, Texas, United States
    2. Department of Microbial Pathogenesis and Immunology, College of Medicine, Texas A&M Health Science Center, Texas A&M University, Texas, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Investigation, Project administration, Writing—review and editing
    For correspondence
    mcriscitiello@cvm.tamu.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4262-7832

Funding

National Science Foundation (IOS 1257829)

  • Michael F Criscitiello

National Institute of Allergy and Infectious Diseases (R01OD0549)

  • Martin F Flajnik

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We acknowledge expert technical assistance from Pat Chen and Ferenc Livak for helpful advice and comments on the manuscript. Ellen Hsu kindly shared a partial nurse shark AID sequence.

Ethics

Animal experimentation: These studies were carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The protocol was approved by the Animal Care and Use Committees at Texas A&M University and University of Maryland School of Medicine. Experiments in the Criscitiello lab were performed under Texas A&M University Institutional Biosafety Committee permit IBC 2014-293 and Animal Use Protocol 2015-0374.

Reviewing Editor

  1. David G Schatz, Yale University School of Medicine, United States

Publication history

  1. Received: May 9, 2017
  2. Accepted: April 16, 2018
  3. Accepted Manuscript published: April 17, 2018 (version 1)
  4. Version of Record published: May 2, 2018 (version 2)
  5. Version of Record updated: May 2, 2018 (version 3)

Copyright

© 2018, Ott et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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