By
§
§
From the * Neuroimmunology Branch, National Institue of Neurological Disorders and Stroke,
National Institutes of Health, Bethesda, Maryland 20892-1400; Institut für Organische Chemie,
Universität Tübingen, 72076 Tübingen, Germany; § Naturwissenschaftliches und Medizinisches
Institut an der Universität Tübingen, 72762 Reutlingen, Germany; and
Department of Neurology,
Tübingen University Medical School, 72076 Tübingen, Germany
CD4+ class II-restricted T cells specific for self antigens are thought to be involved in the pathogenesis of most human autoimmune diseases and molecular mimicry between foreign and self ligands has been implicated as a possible mechanism for their activation. In this report we introduce combinatorial peptide libraries as a powerful tool to identify cross-reactive ligands for these T cells. The antigen recognition of a CD4+ T cell clone (TCC) specific for myelin basic protein peptide (MBP) (86-96) was dissected by the response to a set of 220 11-mer peptide sublibraries. Based on the results obtained with the libraries for each position of the antigen, artificial peptides were found that induced proliferative responses at much lower concentrations than MBP(86-96). In addition stimulatory ligands derived from protein sequences of self and microbial proteins were identified, some of them even more potent agonists than MBP(86-96). These results indicate that: (a) for at least some autoreactive CD4+ T cells antigen recognition is highly degenerate; (b) the autoantigen used to establish the TCC represents only a suboptimal ligand for the TCC; (c) a completely random and unbiased approach such as combinatorial peptide libraries can decrypt the spectrum of stimulatory ligands for a T cell receptor (TCR).
CD4+ T cells recognize via their TCR 11-14-mer
peptides derived from exogenous proteins after processing and presentation by a MHC class II-expressing
APC (1). CD4+ MHC class II-restricted T cells are not
only essential for the specific immune response to foreign
pathogens but also are thought to be involved in the pathogenesis of many autoimmune diseases. Based on sequence
homologies, cross-recognition by autoreactive T cells of foreign antigenic peptides has been demonstrated, and it was
hypothesized that self-reactive T cells expanded by foreign antigens may be involved in the pathogenesis of autoimmune diseases (2).
In recent years, peptide binding motifs of class II molecules have been identified by several experimental approaches. These motifs allow predictions about the binding
of peptides to the MHC molecule and have helped to understand which ligands are available for recognition by
CD4+ T cells. In parallel, determinants derived from foreign
and self antigens that are important for T cell recognition have
been mapped in detail using modified (truncated, single
amino acid [aa]1-substituted) peptides. Based on the concept of conserved TCR contact positions (5) it is well established that CD4+ T cells can recognize different peptides, but the number of possible ligands for a single T cell
receptor is thought to be limited. However, it was also
demonstrated that peptides sharing only a few amino acids
are able to stimulate the same T cell clone (6) as long as they
have conserved TCR contact residues (7). Using this information, a novel strategy to identify molecular mimicry peptides has been described, and stimulatory ligands derived
from microbial proteins have been identified for autoreactive
T cells, which do not share sequence homologies with the
autoantigen in positions other than TCR contacts (7).
However, approaches using single amino acid exchanges
of the peptide antigen in order to identify the anatomy of
antigen recognition and to search for cross-reactive ligands
are impaired by the large number of individual peptides
necessary to define a single T cell epitope. Furthermore,
little is known about how multiple alterations of a ligand
influence T cell recognition. Therefore, it has been impossible to define by formerly used approaches, how many
ligands are recognized by a single T cell receptor and the
full extent to which molecular mimicry can occur.
In contrast to the experiments mentioned above, combinatorial peptide libraries were introduced recently as an approach to allow epitope identification that is unbiased by
sequence homologies or binding motifs. Peptide libraries
have been successfully applied to define unknown antibody
specificities (8), peptide recognition by SH2-domains (9) or
enzyme substrate specificity (10). Peptide libraries have also
allowed a more detailed dissection of MHC class I and II
binding motifs (11, 12). Finally, 9-mer peptide libraries were
used to identify stimulatory ligands for tumor-specific (13)
or alloreactive CD8+ T cell clones (14).
In this report, we used combinatorial peptide libraries to
study antigen recognition of a CD4+ T cell clone and to
search for cross-reactive high potency ligands. The response
of a MBP(86-96)-specific DR2b-restricted TCC to an undecapeptide library in the positional scan format (17, 18) was used to dissect its recognition pattern. Artificial peptide ligands based on the results derived from the library were
shown to be more potent ligands than MBP(86-96). Furthermore, screening of protein databases with the library
information revealed not only MBP as potential ligand for
the TCC but also several peptides derived from self and
foreign antigens. These ligands induced proliferation of the
TCC, some of them even at lower concentration than
MBP(86-96).
These data indicate: (a) for at least some class II-restricted T
cells antigen recognition is highly degenerate; (b) for these TCC a high number of ligands with different stimulatory
potency exist; (c) the autoantigen that was used to establish
the TCC represents a suboptimal ligand; (d) peptide ligands
from self and microbial antigens can be identified which are
more potent than MBP(86-96).
These results not only have important implications for
the understanding of how cross-reactivity is related to autoimmunity, but may also provide a model as to how degeneracy of antigen recognition might contribute to thymic selection.
Synthesis and Analysis of Undecapeptide Amides and Undecapeptide
Amidelibraries.
The synthetic randomized peptide libraries varying in length from 6 to 15 amino acids, the undecapeptide amide
sublibraries as well as individual undecapeptide amides were prepared by solid phase peptide synthesis using Fmoc/tBu chemistry
and Rink amide MBHA polystyrene resins as described recently
(12). In brief, in the case of peptide libraries, the introduction of
randomized sequence positions was performed in a double coupling step with equimolar mixtures of Fmoc-L-amino acids that
were used in an equimolar ratio with respect to the coupling sites
of the resins. For coupling of defined sequence positions a fivefold molar excess of single Fmoc-L-amino acids was used. An optimized diisopropylcarbodiimide/1-hydroxybenzotriazole method
was used for the synthesis of the libraries to yield equimolar mixtures (19). Defined peptides were synthesized by multiple peptide
synthesis (20). The identity of the defined undecapeptides was
confirmed by electrospray mass spectrometry and the purity of
the peptides was determined by HPLC. The amino acid composition in the randomized sequence positions of the sublibraries
was determined by pool sequencing, electrospray mass spectrometry, and amino acid analysis. Deviations from equimolar representation of the amino acids in randomized sequence positions were
found to be within the error limits of the analytical methods.
T Cell Clone TL 5G7.
The T cell clone TL 5G7 was established from peripheral blood lymphocytes of an MS patient by a
limiting dilution split well technique with MBP protein as described before (21). The TCC is DR2b (DR T Cell Proliferation.
Cell proliferation was measured by standard [3H]thymidine-incorporation as described (22). TCC were
rested for 8-12 d, washed and resuspended at 1 × 105 cells/ml in
complete medium (CM, IMDM containing 5% human serum, 1%
penicillin/streptomycin, 0.2% Gentamycin). 100 µl of this cell suspension were added to each well of 96-well U-bottom plates containing 5 ×104 irradiated (3,000 R) PBL and varying concentrations of peptide or peptide libraries. Cells were cultured for 48 h
at 37°C. During the last 6 h of culture, 1 µCi [3H]thymidine was
added to each well. Cells were then harvested and incorporated
radioactivity was measured by scintillation counting.
CTL Assay.
CTL assays were performed as described (23).
Briefly, target cells (5 × 105) were labeled overnight at 37°C in
500 µl of CTL medium (RPMI + 5% fetal calf serum) with 50 µCi 51Cr (Du Pont-New England Nuclear, Boston, MA). 51Crlabeled cells were incubated with different concentrations of peptide for 2 h, washed twice (200 g, 20°C, 10 min), and adjusted at
2 × 104 cells/ml. 2 × 103 targets were plated into 96-well U-bottom microtiter plates containing sufficient numbers of T cells to
reach desired E/T ratios. After a 4-h incubation (37°C), supernatants were counted in a gamma counter (ME Plus; ICN Micromedic, Huntsville, AL). Specific lysis was calculated according to
the following formula: ([test release {cpm} Database Searches.
The tolerated amino acids for each position
of the 11-mer peptide were used to search human proteins in
Swissprot using protein motif search engine (Virtual Genome Center, http://alces.med.umn.edu/dbmotif.html). In addition, sequences based on the peptide predictions were used to search
Swissprot using BLITZ search engine (http://www.ebi.ac.uk/searches/blitz_input.html). Peptide sequences from self or foreign
peptides that matched at least 6 aa of the predicted aa in core positions were chosen.
TL 5G7 is
a DR2b (DR
The X11 library induced a nearly maximal response and is less diverse than libraries of longer peptides. Therefore, further studies were based on a 11-mer
peptide library in the positional scanning format consisting
of 220 sublibraries each containing 10 degenerated (X) and
one defined sequence position (0). According to peptide
binding data of MBP(83-99/87-99) to DR2b (the restriction element of TL 5G7) and the crystal structure of peptides bound to HLA-DR molecules (26, 27), V87 is bound
in pocket I, F90 in pocket IV and T95 in pocket IX of the
MHC molecule. Amino acids H88, F89, K91, N92, I93,
and V94 are exposed to the TCR. To evaluate whether the
TCR determinants can be detected with a library approach, we tested TCC TL 5G7 with positional scanning sublibraries, based on three aa that represent potential TCR determinants located in the middle of the epitope (F89 [F1
{FXXXXXXXXX} to F11{XXXXXXXXXF}], K91 [K1
to K11], N92 [N1 to N11]) and on G (G1 to G11) that is not present in the MBP sequence. The sublibraries with F in
position 4, 5, and 6, K in position 6, 7, and 11, and N in
position 7 and 8 elicited an increased proliferative response
compared to the X11 library (Fig. 1 B). The response to
the sublibraries with the fixed G in core positions 4 to 8 was reduced. The results matched the sequence of MBP(8696) (VVHFFKNIVTP) with F89 (position 4), F90 (position
5), K91 (position 6), and N92 (position 7) or MBP(85-95)
(PVVHFFKNIVT) with F89 (position 5), F90 (position 6),
K91 (position 7), and N92 (position 8) (Fig. 1 B). Single aa N and K in the core of the epitope were detected by a
positive response for two adjacent sublibraries, whereas
double F in the MBP epitope (F89, F90) was detected by a
positive response to three adjacent sublibraries. Based on
these results, we can expect, that each matched aa of the
epitope will appear as a double peak in the response to a
large panel of sublibraries, whereas two identical aa in adjacent positions of the peptide will show a triple peak in the
response to the panel of sublibraries. This doubling effect
can be attributed to different mechanisms. The minimal
epitope for the TCC is less than 10 aa, and therefore, the
sublibraries allow sliding by one amino acid in the binding groove, which influences the way they are recognized by
the TCR. For example, if K is fixed in position 6 the
amino acid side chains of positions 2, 5, and 10 could bind
to the MHC molecule, whereas if K is fixed in position 7, position 3, 6, and 11 would contact the MHC. The second
possibility, would indicate a sliding of the TCR when interacting with the MHC peptide complex. However, given the recent crystal structure of the TCR-MHC peptide
complex (28), this seems highly unlikely.
The proliferative response of the TCC to different concentrations of the 220-peptide sublibraries in the positional
scan format was tested. Each sublibrary carries one defined
amino acid in one of the positions P1-P11, and the entire
panel covers all 20 amino acids in the 11 different positions
(only cysteine was replaced by the structurally related synthetic analogue B [
No significant differences were observed in position (P1)
(Fig. 2). Sublibraries with defined residues I, L, M, V, and
F in position 2 induced an increased response in comparison to X11. The same aa were found for P3. In P4 aa F, M,
Q, I, L, and W and in P5 F and Y were identified. In P6 aa
K and R and in P7 aa N elicited increased responses. aa V
and B in P8 and aa V, I, and B in P9 were positive. Finally,
sublibraries with aa I, L, and V in P10 and aa K in P11 induced a positive response. Whether the positive response of
aa I, L, and V in P11 is real or just the double peak from
P10 can not be defined. Table 1 shows the results for each
of the 11 positions. To summarize, aa in positions 2, 5, and
10 are thought to interact with the HLA-DR2b molecule. In accordance with binding studies, only hydrophobic aromatic and aliphatic aa were tolerated in position 2 (pocket
I) and only the aromatic, uncharged aa F and Y in position
5 (pocket IV). For P10 (pocket IX) only aliphatic aa were
found with the library. In predicted TCR contact positions
only the aliphatic aa were detected in position 3 (P3) and
Q and the hydrophobic aromatic and aliphatic aa in P4. In
contrast, P6 tolerated only the positively charged aa K and
R and P7 only the aa N. P8 and P9 tolerate only aliphatic
aa and the aa B. As described above, no clear conclusions can be drawn for P1 and P11. Interestingly, only 6 aa of the
MBP(86-99) sequence matched with optimal library predictions for P2-P10.
Table 1.
Library Predictions and Deduced Peptide Sequences
+ DRB1*1501)-
restricted and specific for MBP(86-96/83-99).
spontaneous release
{cpm}] / [total incorporation {cpm}
spontaneous release {cpm}]) × 100.
The Response to Completely Randomized Combinatorial Peptide
Libraries Suggests Degeneracy in Antigen Recognition.
+ DRB1*1501)-restricted Th0-like TCC
generated and grown using MBP as described (21, 22). The
TCC is specific for the immunodominant peptide MBP(8399) and MBP(86-96). The response to MBP(86-96) is two
orders of magnitude weaker than to MBP(83-99) due to
the lower MHC binding affinity of the shorter 11-mer
peptide (24, 25). The TCC was first tested for its response
to completely randomized peptide libraries. The libraries with defined peptide length were generated by random synthesis for each position with all 20 naturally occurring aa
(only C is replaced by B[
-aminobutyric acid]) (12). They
contain a homogeneous mixture of all possible combinations of the 20 aa within the given peptide length. The
equimolar distribution of all 20 aa in each randomized position of the defined undecapeptides was confirmed by
electrospray mass spectrometry and the purity of the peptides was determined by HPLC. The aa composition in the
randomized sequence positions of the sublibraries was determined by pool sequencing, electrospray mass spectrometry, and amino acid analysis (12). The peptide libraries contain large numbers of different peptides; the number is
related to the length of peptides in the library (i.e., for a 11mer peptide library 2011 = 2 × 1014 different sequences).
Peptide libraries with different peptide length ranging from
6-mer (X6) to 15-mer peptides (X15) were used in the assay (Fig. 1 A). X6 to X9 induced no response whereas X10
to X15 induced significant proliferation of the TCC. The
observation that the TCC responds to a mixture of 2 × 1014 different peptides (X11) almost as strongly as it does to
11-mer MBP peptide(86-96), suggests a high degree of degeneracy in antigen recognition by this TCC.
Fig. 1.
Proliferative response of TL 5G7 to MBP(86-96) and different combinatorial peptide libraries. A displays the response to a sizing scan
with completely randomized libraries ranging in length from 6 (X6) to 15 aa (X15), B shows the response to peptide sublibraries with fixed amino acid
phenylalanine (F), lysine (K), asparagine (N), or glycine (G) in position 1 to 11. The proliferation is compared either to MBP(86-96) (A) or randomized library X11 (B). Note that each selected amino acid of the MBP sequence is recognized by two adjacent sublibraries, whereas the double F of
the MBP sequence is recognized by three adjacent sublibraries. The peptide library concentration is 100 µg/ml. BG = background. One representative out of three separate experiments yielding similar results is shown.
[View Larger Versions of these Images (15 + 23K GIF file)]
-aminobutyric acid]). Differences in
the proliferative response were found at 100 and 250 µg/
ml (Fig. 2). The results were analyzed taking into account
the rules established with the F-, K-, and N-scan sublibraries; (a) each matched aa of the MBP sequence resulted in a
response with two adjacent sublibraries and (b) two adjacent tolerated aa resulted in a response in at least three adjacent sublibraries (Fig. 1 B). Therefore, when a sublibrary
induced a stronger response than the X11 library (positive
response), the fixed corresponding aa of the sublibraries was
evaluated as being optimal for this position of a putative antigenic peptide (first peak). If the same aa was positive in
two more adjacent sublibraries, the aa was also considered
optimal for the following position of the antigenic peptide.
If one specific aa gave a positive response in only two position, the second was considered an artefact due to the sliding effect.
Fig. 2.
Proliferative responses of TL 5G7 to 220 undecapeptide sublibraries with defined amino acid (20 for each of the 11 positions). Sublibraries
starting with the defined amino acids in position P2 elicit very different responses in the TCC. Positional scan sublibraries, that induce responses stronger
than X11 are considered positive for the first position they appear (* marked). If one amino acid induced an optimal response in three or more consecutive positions, it was considered positive in more than one position. Proliferation is shown by CPM induced by 100 (black bars) or 250 µg/ml (gray bars)
of the libraries. Lane B represents -aminobutyric acid.
[View Larger Versions of these Images (30 + 26 + 12K GIF file)]
Position
P1
P2
P3
P4
P5
P6
P7
P8
P9
P10
P11
Library predictions
No
I,V,L,M,F
I,V,L,M,F
F,M,W,Q,L,I
F,Y
K,R
N
V,B
V,I,B
I,V,L
K (I,V,L)
MBP
Myelin basic protein (86-96)
V
V
H
F
F
K
N
I
V
T
P
H1
Hypothetical peptide
D
L
I
F
Y
R
N
V
V
I
K
H2
Hypothetical peptide
D
L
I
F
Y
K
N
V
V
I
K
H3
Hypothetical peptide
D
L
I
M
Y
K
N
V
V
I
K
H4
Hypothetical peptide
D
L
I
M
Y
R
N
V
V
I
K
H5
Hypothetical peptide
D
L
I
M
Y
R
N
V
V
I
A
S1
Ras GTPase-activating-like protein
IQGAP1(1581-1591)
Q
V
N
Q
F
K
N
V
I
F
E
S2
Protein-glutamine gamma-
glutamyltransferase(675-685)
A
V
K
G
F
R
N
V
I
I
G
S3
NAD-dependent methylenetetrahy-
drofolate dehydrogenase(311-321)
V
A
M
L
M
K
N
T
I
I
A
S4
Tyrosine-protein kinase BTK
(124-134)
W
I
H
Q
L
K
N
V
I
R
Y
F1
Protein kinase CHK1[schizosaccharo-
myces pombe](473-483)
W
R
K
F
F
K
N
V
V
S
S
F2
Hypothetical protein UL71[human
cytomegalovirus](166-176)
D
I
L
I
L
K
L
V
V
G
E
F3
UDP-N-acetylenolpyruvoyl-
glucosamine reductase
[Salmonella typhimurium](227-237)
A
G
S
F
F
K
N
P
V
V
A
Based on the results
of the 220 peptide sublibraries individual (defined) 11-mer
peptides with optimal aa in position P2 to P10 were deduced and synthesized (Table 1). In P1 a D residue and in
P11 a K residue was introduced to increase solubility. Testing these peptides in proliferation assays, it became evident that TCC TL 5G7 responded to all peptides at much lower
antigen concentration than MBP(86-96). The ligands induced maximal stimulation at a concentration as low as 1 ng/ml, whereas 100 µg/ml were needed for MBP(86-96)
(Fig. 3 A). These data confirm the library predictions and identify MBP(86-96) as a suboptimal ligand for TCC TL 5G7.
Library Predictions Identify Stimulatory Peptides Derived from Microbial and Self Peptides.
To identify peptides derived from
natural proteins we searched the Swissprot database for peptide
sequences using the library predictions for P2 to P10. The
protein motif search for human entries in Swissprot identified
several candidate self peptides. Interestingly, the MBP sequence was among them. Another search with sequences
based on optimal aa combinations for P2 to P10 of the 11-mer
peptide using BLITZ-search for the entire Swissprot database revealed several sequences of microbial antigens. Candidate peptides from both database searches, which matched at
least 6 aa with the library prediction for P2-P10 were synthesized and tested in proliferation assays with TCC TL
5G7 (Table 1). Several peptides derived from human (Fig. 3
B) and microbial proteins (Fig. 3 C) were stimulatory for
the TCC. In addition, self and foreign peptides (S2, F2, F3,
Fig. 3) were identified that were more potent agonist for
TCC TL 5G7 than MBP(86-96). To exclude any non-
TCR-mediated activation of the TCC by these new
ligands, four other MBP(86-96 or 83-99)- and two influenza hemaglutinin HA(306-318)-specific TCC were tested
with the same concentration range and showed no response to any of the synthetic ligands listed in Table 1 (data
not shown). In addition, we tested the weakly cytotoxic
TCC TL 5G7 for its ability to lyse HLA-matched targets pulsed with these peptides. B cells expressing HLA-DRB1*
1501 pulsed with MBP(86-96), H1 or F2 were lysed (Fig. 4
A), but not B cells expressing other HLA-DR molecules
(Fig. 4 B). Again the peptides that were stronger agonists
than MBP(86-96) in the proliferation assay induced stronger cytolysis. When we compared the sequences of the
stimulatory ligands to the aa predicted by the library, we
found a correlation between agonist activity and number of aa matched with library predictions. Peptides that matched
9 of 9 (H1-H5, not considering P1 and P11) induced proliferation at a concentration below 1 ng/ml, whereas peptides that matched 6 or 7 of 9 aa induced a proliferative response at 0.1-10 µg/ml.
Combinatorial peptides libraries are useful tools to define peptide protein interactions, such as MHC binding motifs or antibody antigen interactions (8, 10). Recently, peptide libraries have been used to define the peptide repertoire of CD8+ TCC (13). CD8+ TCC recognize 9-mer peptides and therefore can be studied by a 9-mer combinatorial library. In contrast, for CD4+ class II-restricted T cells the minimal epitope is usually 11 aa, and longer libraries (such as an X11) are required for studying antigen recognition of these cells. Allowing 20 different aa in a X position, extending the length by 2 aa results in an increase of complexity by a factor of 400. Despite this increase in complexity, we were able to apply an 11-mer peptide library to dissect the antigen recognition pattern of an MBP-specific human class II-restricted TCC and identified several tolerated aa for most positions of the epitope. The data obtained by 220 undecapeptide sublibraries were confirmed by the positive response to synthetic individual 11-mer peptides based on optimal amino acids for each position. Crossreactive ligands derived from human and microbial proteins, some of them even more potent than MBP(86-96), were easily identified by database searches.
These results allow several important conclusions. Functional peptide recognition by at least some class II-restricted T
cells is extremely degenerate. The fact that a TCC responds
to a randomized mixture of 11-mer peptides suggests, that
many ligands are recognized by this TCR. The X11 library
consists of 2.05 × 1014 (2011) different peptides resulting in
assay concentrations of 4.88 × 1019 g/ml for each single
peptide (at 0.1 mg/ml total peptide concentration). Given
the minimal concentration of one of the best hypothetical ligands, H1, to induce proliferation (1 × 10
9 g/ml, respectively) (Fig. 3), we can hypothesize that a high number
of different ligands are stimulatory for the TCC. Although only a few of these amino acid sequences will be generated
from natural proteins and even fewer will be presented to
T cells after processing, a very high number of ligands that
can positively engage the TCR of TL 5G7 will still occur
naturally. This observation is consistent with our previous
observations using MBP-specific TCC (29). Based on single aa substituted peptides we established that many amino
acid exchanges in the MBP peptides are tolerated and some
even induce a stronger agonist response than the MBP peptide itself without increasing the MHC binding (superagonist modifications). In addition, we demonstrated that alterations of primary and secondary TCR contact positions,
which usually abrogate T cell responses, can be restored by
superagonist modifications at other positions. This suggested
that the recognition of these TCC is degenerate and ligands
exist that are much stronger agonists than the autoantigen
itself.
Peptide libraries provide a tool to test the hypothesis of degeneracy in antigen recognition. For each position of the peptide antigen the optimal amino acid can be defined by the response to the sublibraries. The agonist activity of ligands correlates with the number of optimal amino acids for the positions of the antigenic peptide. The fact that TCR recognition can be predicted based on peptide libraries with only one amino acid fixed suggests that each amino acid independently contributes to TCR recognition. Accordingly, the strength of interaction given by the integration of the effect of each aa defines the agonist activity of a ligand. Even if some aa do not fit with the criteria of being optimal for a certain position, the ligand may still be stimulatory if enough suitable aa can counterbalance with positive effects in other positions. This observation does not fit models that argue that specific conformations of the peptide are the major determinant of recognition by the TCR.
A large number of ligands exists for each T cell that can positively engage the TCR. Among these ligands, a hierarchy exists with respect to agonist activity. The potency of the ligand determines at which antigen concentration the T cell becomes activated. Two different routes of activation for T cell with degenerate antigen recognition can be hypothesized; a single strong agonist ligand can reach the threshold for activation when applied at sufficient concentration (i.e., during microbial infection). Alternatively, a large number of different stimulatory ligands, i.e., the pool of self peptides or the X11 library can activate the T cell. These observations may be relevant to several immunological processes. Thymic selection and peripheral tolerance take place in an environment that is characterized by high numbers of different ligands rather than high concentrations of one ligand. Therefore, degeneracy of antigen recognition combined with the possibility that each ligand can interact with several different TCRs (30) might determine selection in the thymus by a pool of self peptides (31). T cells carrying TCR with a very low level of degeneration may not reach the threshold for activation to undergo positive selection (few ligands from the pool are recognized = low affinity interaction). In contrast, T cells with highly degenerate TCR recognition may undergo negative selection due to a strong activation imposed by the large amount of stimulatory ligands from the pool of self peptides (high-affinity interaction). Similar mechanisms may also regulate T cell responses in the periphery. The pool of self peptides that selected the T cells in the thymus will constantly impose a low level of activation on the T cells that escaped selection in the thymus. Once the immune system is exposed to a microbial organism, its antigens will replace locally part of the pool of self peptides. This will result in a stimulation and expansion of cells expressing a high-affinity receptor for these antigens. The responding T cells will clear the microbe from the body and the pool of self peptides will then replace the foreign antigens, turning the microbial-specific T cells back to a state of low activation. However, the T cells that encountered the foreign antigen, will develop into memory cells that become more efficient in recognition of antigenic ligands during recall responses due to their different repertoire of costimulatory ligands. If such a differentiation to the memory stage occurs with T cells that crossreact with self peptides, these cells will be more prone to activation by subsequent stimuli, if, for example, the respective autoantigen is released during local tissue damage. The release of these and other self peptides from the damaged target organ may activate other T cells with different specificities and eventually lead to acute or chronic organ destruction.
Address correspondence to Roland Martin, Neuroimmunology Branch, NINDS, National Institutes of Health, Bldg. 10 Room 5B16, 10 Center DR, MSC 1400, Bethesda, MD 20892-1400.
Received for publication 27 January 1997.
B. Hemmer is a post-doctoral (He 2386/1-2) and R. Martin a Heisenberg Fellow of the Deutsche Forschungsgemeinschaft (Ma 965/4-1). G. Jung thanks the Deutsche Forschungsgemeinschaft for financial support.We thank R. Germain, Laboratory of Immunology, NIAID, NIH and B. Biddison NIB/NINDS, NIH for discussion and critical comments.
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