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CTL epitope distribution patterns in the Gag and Nef proteins of HIV-1 from subtype A infected subjects in Kenya: Use of multiple peptide sets increases the detectable breadth of the CTL response

Background Subtype A is a major strain in the HIV-1 pandemic in eastern Europe, central Asia and in certain regions of east Africa, notably in rural Kenya. While considerable effort has been focused upon mapping and defining immunodominant CTL epitopes in HIV-1 subtype B and subtype C infections, few epitope mapping studies have focused upon subtype A. Results We have used the IFN-γ ELIspot assay and overlapping peptide pools to show that the pattern of CTL recognition of the Gag and Nef proteins in subtype A infection is similar to that seen in subtypes B and C. The p17 and p24 proteins of Gag and the central conserved region of Nef were targeted by CTL from HIV-1-infected Kenyans. Several epitope/HLA associations commonly seen in subtype B and C infection were also observed in subtype A infections. Notably, an immunodominant HLA-C restricted epitope (Gag 296–304; YL9) was observed, with 8/9 HLA-CW0304 subjects responding to this epitope. Screening the cohort with peptide sets representing subtypes A, C and D (the three most prevalent HIV-1 subtypes in east Africa), revealed that peptide sets based upon an homologous subtype (either isolate or consensus) only marginally improved the capacity to detect CTL responses. While the different peptide sets detected a similar number of responses (particularly in the Gag protein), each set was capable of detecting unique responses not identified with the other peptide sets. Conclusion Hence, screening with multiple peptide sets representing different sequences, and by extension different epitope variants, can increase the detectable breadth of the HIV-1-specific CTL response. Interpreting the true extent of cross-reactivity may be hampered by the use of 15-mer peptides at a single concentration and a lack of knowledge of the sequence that primed any given CTL response. Therefore, reagent choice and knowledge of the exact sequences that prime CTL responses will be important factors in experimentally defining cross-reactive CTL responses and their role in HIV-1 disease pathogenesis and validating vaccines aimed at generating broadly cross-reactive CTL responses.

Background
The development of an efficacious prophylactic vaccine for human immunodeficiency virus type 1 (HIV-1) is the goal of a concerted worldwide research effort [1,2]. Although the precise correlates of protective immunity against HIV-1 infection are not clearly defined, a large body of accumulated data suggests that an ideal HIV-1 vaccine will need to stimulate both humoral and cellular immune responses against the virus [3]. While chronic untreated HIV-1 infection causes a profound immunodeficiency, the initial HIV-1 infection stimulates strong cellular and humoral immune responses against the virus [4,5]. CD8 cytotoxic T lymphocytes (CTL) constitute a major component of the cellular arm of the immune response, and have a central role in the control of initial viremia immediately following HIV-1 infection and in the establishment of long-term AIDS free survival [6,7]. The ability to rapidly and accurately characterize CTL responses in HIV-1 infected individuals has grown exponentially in recent years. New technologies to detect CTL responses by measuring interferon-gamma (IFNγ) release, such as the enzyme linked immunospot (ELIspot) assay and cytokine flow cytometry (CFC), have been coupled with overlapping pooled peptide technology (OLP) to give detailed and precise analyses of HIV-1-specific cellular immune responses [8][9][10][11]. The fine mapping of T cell epitopes and the identification of immunodominant regions of HIV-1 gene products is integral to vaccine design, to the development of immunotherapeutic strategies, and to the optimization of assays for assessing vaccine efficacy.
Genetic diversity is the foremost obstacle for any screening method for HIV-1-specific cellular immunity [12][13][14]. Geographically defined epidemics can be characterized by the dominance of distinct genetic subtypes of HIV-1, with at least 9 subtypes and 21 CRFs of HIV-1 currently recognized [15]. Since intra-subtype amino acid sequence variation can be as high as 10-15% (depending on the viral gene product) and inter-subtype variation can be much higher, any single sequence of HIV-1 used for screening for CTL responses will differ considerably from the sequence of the infecting virus in an individual. This is an important complicating factor for studying the CTL response, because CTL are primed in vivo in response to the autologous infecting virus. Although the use of autologous viral sequences has been employed in several studies, their general use is impractical and labor intensive since, not only does the viral sequence between individuals differ significantly, but the viral quasi-species in a single individual can also take many different forms [16][17][18]. A proposed solution to this seemingly intractable problem has been to use OLP sets based upon computationally derived consensus or ancestral sequences [19,20]. Viral consensus and ancestral sequences have the theoretical advantage of being more related on average to any given in vivo viral sequence than any arbitrary viral isolate would be. A further complicating factor for OLP screening is that practical peptide libraries usually comprise 15-20-mers overlapping by 10-12 amino acids, but the optimal length of peptides that bind to MHC class I molecules is 8-11 amino acids. However, this problem is overcome in most cases by exogenous addition of the peptides at biologically excess concentrations [21][22][23]. Despite these compromises the utility of screening for CTL responses with consensus sequence based OLP has been demonstrated in several recent studies, which have comprehensively analyzed the full breadth and magnitude of cellular immune responses to the entire HIV-1 proteome [10,11,[24][25][26]. Although consensus sequence based OLP have now become the de facto standard for studies of HIV-1 cellular immunity, the assumption that a subtype based consensus is implicitly better than a randomly chosen isolate from the same subtype and isolates from other subtypes has only recently been questioned formally [27][28][29][30].
This study was undertaken to assess the CTL response to the Gag and Nef proteins of HIV-1 infected individuals in Kenya, a predominantly HIV-1 subtype A endemic region, and to compare and contrast the CTL response measured with that determined by prior studies in subtype B and C epidemics. CTL responses directed against the gag and nef gene products were selected because previous studies have shown that these two gene products contain the highest epitope density and are the most frequently recognized HIV-1 proteins in subtype B and C infection [10,11,[24][25][26]31]. Detection of Gag-specific CTL responses was performed using peptide libraries representing a subtype A consensus, a subtype A isolate, a subtype C isolate and a subtype D isolate, to gain an insight into subtype-specificity of CTL responses in a region of multiple subtype endemicity. Detection of Nef-specific CTL responses was performed using peptide libraries representing a subtype A isolate, a subtype C isolate and a subtype D isolate. After sequence analysis of the gag and nef genes from proviral DNA confirmed that the cohort was predominantly HIV-1 subtype A infected, we integrated knowledge of the sequence of the infecting viral isolate, the HLA-type of the subject and the CTL response made by that subject to: (1) determine the frequency of recognition and pattern of CTL immunodominance within the Gag and Nef proteins in subtype A infections; (2) compare the frequently recognized epitopes in subtype A infection with those previously determined for subtype B and C infections; (3) compare subtype matched and mismatched peptide based peptides sets for their ability to detect CTL responses; (4) characterize an immunodominant HLA-C W 03 restricted CTL epitope from HIV-1. Within the framework of this study we were able to directly test the hypothesis that in a given cohort of HIV-1-infected subjects consensus and isolate-based peptide libraries derived from the homologous subtype would detect significantly broader and greater magnitude CTL responses than heterologous subtype-derived peptide libraries.

HIV-1 gag and nef region subtype analysis and HLA-typing
Full-length gag and nef sequence analysis of PBMC proviral DNA was performed to characterize the HIV-1 subtype distribution within the cohort. A single full-length gag and nef sequence could be obtained from 40 of the 42 subjects (sequence could not be obtained from 2 subjects). In the gag region, 31 of the 40 subjects harbored HIV-1 subtype A (29 sub-subtype A1 and 3 sub-subtype A2), 1 had subtype D. The remaining 8 gag sequences represented recombinant structures, 5 A1/D, 3 A2/D. Within the nef region, 35 of 40 subjects harbored HIV-1 subtype A (32 sub-subtype A1 and 3 sub-subtype A2), while the remaining 5 sequences represented 2 subtype D, 2 subtype C and 1 A1/D recombinant. Figure 1 shows phylogenetic trees of the gag (A) and nef (B) sequences obtained from the cohort, with the DNA sequence from which the isolate based sequences were derived shown for clarity. For both regions, the subtype A isolate shows closer branching to the majority of the cohort sequences than the subtype C or subtype D isolates. A pair-wise comparison of the translated autologous virus protein sequences (from all 40 subjects) with the sequence of each of the peptide sets to be used for the ELIspot screening was performed. The autologous Gag protein sequences have mean differences of 6.1%, 10.2%, 11.6% and 13.3% from the subtype A consensus, the subtype A isolate, subtype C isolate and sub-Phylogenetic trees of the gag (A) and nef (B) proviral DNA sequences obtained from the cohort Figure 1 Phylogenetic trees of the gag (A) and nef (B) proviral DNA sequences obtained from the cohort. Circled are the DNA sequences of the isolates from which the screening peptide sets were deduced. The large cluster of sequences in both trees represents subtype A. Bootstrap values are shown. type D isolate based Gag peptide sets respectively. The autologous Nef protein sequences have mean differences of 16.4%, 18.8% and 24.5% from the subtype A isolate, subtype C isolate and subtype D isolate based Nef peptide sets respectively. Therefore, the cohort is predominantly infected with HIV-1 subtype A viruses, and as would be expected, the Gag subtype A consensus and Nef subtype A isolate based peptide sets are closest in sequence to the viruses present in the cohort. The nucleotide sequences derived in this study were submitted to GenBank and are available under the following accession numbers: [DQ367261-DQ367332, AY945736-AY945739].

Elispot Screening with Overlapping Peptide Pools
The cohort was screened for IFNγ T cell responses against four sets of Gag overlapping peptide pools and three sets of Nef overlapping peptide pools. The gag and nef genes were selected because these two gene products have been documented to contain the highest CD8 epitope density and are the most frequently recognized HIV-1 gene products [10,11,[24][25][26]. As described in the Methods section, the sequences of the peptide sets used for the study were based upon homologous and heterologous subtype isolates, and on a computationally derived subtype A consensus sequence for the Gag protein. IFNγ ELIspot responses from cryopreserved PBMC were assessed by peptide matrix screening, followed by individual peptide confirmation assays in order to maximize the information from individual specimens. In both the screening and confirmation assays, positive responses were defined as those where the test wells exceeded the 99% confidence interval of replicates of six negative control wells, while for the confirmation assays individual peptides were tested in triplicate. The 42 subjects included in the study all demonstrated strong responses to the SEB positive control (range = 515 -7795 SFU/10 6 PBMC, or confluence). Table 1 summarizes the IFNγ ELIspot screening data in terms of the number of subjects responding to each peptide set and the number of discrete responses detected. An epitope, or discrete epitopic region, was defined by a response to a single peptide or adjacent pair of overlapping peptides from an individual peptide set. While 33 subjects responded to at least 1 peptide from the 7 sets of screening peptides, 9 subjects showed no detectable Gag or Nef peptide specific response. Of the 33 subjects responding to any peptide set (Gag or Nef) 30 recognized at least 1 Gag peptide set. Of interest, similar numbers of subjects recognized at least 1 peptide from the 4 Gag peptide sets: the subtype A consensus was recognized by 26 subjects; the CRF01_AE peptide set by 25 subjects; the subtype C peptide set by 25 subjects; and the subtype D peptide set by 23 subjects. The total number of responses detected in all subjects was also evaluated. Among the Gag responding subjects a total of 65 responses were detected (mean of 2.2 epitopes per responding subject), with between 1 and 5 epitopes recognized. A slightly greater, although non-statistically significant, number of Magnitude of CTL responses measured for each subject in response to either Gag (A) or Nef (B) peptide sets (Con = consensus; Iso = isolate) Figure 2 Magnitude of CTL responses measured for each subject in response to either Gag (A) or Nef (B) peptide sets (Con = consensus; Iso = isolate). For each study subject all detected ELIspot responses against each peptide set were totaled (expressed as SFC/10 6 PBMC) and plotted beside each other.   Table 1). The total frequencies of cells, expressed as SFC/ 10 6 PBMC, responding to each of the Gag peptide sets is shown in Figure 2A. Within the cohort the measured frequency of responding cells was similar for each peptide set and no statistical difference among the peptide sets was observed (Friedman Test and Kruskal-Wallis Test). Therefore, the ability to detect Gag derived CTL epitopes in an ELIspot assay for IFNγ production was not significantly improved by using a set of peptides based upon the consensus of subtype A compared with randomly chosen homologous and heterologous subtype based isolate sequences.
Of the 33 subjects responding to any peptide set, 24 recognized at least 1 Nef peptide set. The 3 Nef peptide sets were also recognized by equivalent numbers of subjects: the subtype A peptide set was recognized by 24 subjects; the subtype C peptide set by 22 subjects; and the subtype D peptide set by 22 subjects. A total of 40 Nef directed responses were detected among the Nef responders with between 1 and 3 Nef epitopes recognized by each subject (mean of 1.7 epitopes per responding subject). The subtype A Nef peptide set was significantly (χ 2 test; p < 0.03) better at detecting the Nef-specific responses (detecting 38 of the 40 total responses) compared with the heterologous subtype based peptide sets (subtype C, 29 responses; and subtype D, 32 responses). There was however, no statistically significant difference between the magnitude of SFC detected in response to each of the 3 Nef peptide sets ( Figure 2B) (Friedman Test and Kruskal-Wallis Test). Figure 3 shows the cumulative frequency of responses against individual Gag peptides for the cohort. The profiles show a remarkably similar response pattern for each of the four Gag peptide sets, indicating a potentially high level of multi-subtype reactivity of Gag-specific CTL from subtype A infected subjects. Responses were directed primarily against the p17 (23 responses) and p24 (36 responses) proteins, with fewer responses detected against the p15 proteins (6 responses). Four epitopic regions of the subtype A Gag consensus peptide set were recognized by >10% of the subjects and were also cross-recognized within the isolate based peptide sets. Two of these regions were located in p17, peptides 4-5 and peptides 19-20 (amino acids 13-31 and 73-91 respectively) and two within p24, peptides 40-41 and peptides 73-74 (amino acids 161-175 and 289-307 respectively). These regions are rich in previously mapped CTL epitopes from subtypes B and C [15]. The study also showed a notable similarity in the response profiles against the 3 sets of Nef peptides ( Figure 4). The central conserved region of the Nef protein is recognized predominantly in all 3 peptide sets, and is also extremely conserved among the peptide sets. From amino acid position 60 through to 148 (peptides 19-36 for subtype A, and peptides 17-34 for subtypes C and D) the three peptide sets have only 13 amino acids which differ, and a single amino acid insertion the subtype C isolate with respect to the subtype A and D isolates. Not surprisingly, the majority (32/40) of the Nef responses detected by the 3 peptide sets reside within this 89 amino acid stretch. The subtype A peptide set is slightly offset with respect the subtype C and D peptide sets due to an 11 amino acid insertion after residue 27. This insertion did not contain any detected epitopes, nor did it appear to disrupt epitopes detected with the subtype C and D peptide sets or other previously defined epitopes [15]. Frequency of response histograms for all peptides from each Gag peptide set Since the overall analysis showed a high degree of similarity and multi-subtype recognition, the cohort was examined for the number of responses detected across all subtypes and those detected by a subset of subtypes or a single subtype. Overlapping Venn diagrams ( Figure 5) were used to display the number of responses detected by the individual peptide sets and by the various combinations of peptide sets. For example, Figure 5A shows that of 65 identified Gag responses, 22 were detected with all 4 peptide sets as shown by the central overlap of all 4 circles, each of which encompasses all responses detected by that peptide set. By this analysis 36 of the 65 Gag responses were detectable with at least 3 of the peptide sets, while the remaining 29 were detected with only 2 or 1 of the peptide sets. Strikingly, the consensus subtype A peptide set detected only 4 responses not detectable by any of the 3 isolate based peptide sets, and the isolate based peptide sets collectively, detected 15 responses not detected with the subtype A consensus peptide set. Moreover, the sub-type C and D heterologous isolate derived peptide sets detected 12 responses not detected by either of the two subtype A based peptide sets, with 11 of the responses representing different epitopic regions since only 2 were against the same peptide. It was reasoned that because the cohort contained 1 subtype C, 2 subtype D and 6 intersubtype recombinant gag genes, then these subjects may be the source of the responses not detected with the subtype A derived peptide sets. However, this was not the case, as only 1 of the 12 epitopes not detected with subtype A peptide sets could be attributed to subjects from which non-pure subtype A gag containing virus sequence was obtained. This response was detected with the subtype C peptide set and was from a subject (KSM4039) carrying an inter-subtype recombinant gag sequence (A1/D). Thus, the overall magnitude and breadth of the CTL response against subtype A Gag was underestimated when screening with any single peptide set. The use of a single peptide set derived from an homologous subtype Gag sequence (whether it be based upon an isolate or a consensus) did not give a complete representation of the repertoire of Gag-specific epitopes recognized by any given subject in this study. Similar analysis for the Nef protein showed that the homologous subtype A derived peptide set detected all but 2 of the Nef responses detected in this study. Most of the Nef responses were directed to the highly conserved central region of the protein with 26/40 total responses detected by all 3 isolate derived peptide sets. Notably, the number of responses detected with the subtype A Nef isolate peptide set (38) was significantly greater than that detected with either the subtype C Nef (29) or D Nef (32) peptide sets (p = 0.03; χ 2 test). Therefore in this cohort, the use of homologous subtype derived Nef sequences did maximize the detection of Nef CTL epitopes.

Characteristics of positive and discordant peptides in relation to each other and to autologous virus sequences
The identified CTL responses were next compared and examined in greater detail. All positively recognized peptides from all peptide sets were compared to the Gag or Nef sequence of autologous virus. First, the total number of possible responses detected in the study was calculated by multiplying the number of discrete Gag responses by 4 and the number of discrete Nef responses by 3. This calculation was performed since any response directed against Gag had 4 possible hits (one from each peptide set), and any response against Nef had 3 possible hits. Of a total of 260 possible responses directed against all Gag peptide sets, 171 were detected, while of a possible 120 responses against all Nef peptide sets, 99 were detected. When the peptides representing the 270 detected Gag and Nef responses were compared to the autologous virus sequence obtained from each host, approximately onethird (98) were identical to the autologous virus sequence Hence a greater number of responses were detected in subjects whose proviral DNA contained a different sequence compared to the peptide used to detect the response. To obtain a better impression of the cross-reactive nature of the CTL responses measured, the impact of "frame-of-epitope" and sequence variation between concordant and discordantly recognized peptides was also examined. The "frame-of-epitope" refers to the offset position of a 9-mer minimal epitope within a given 15-mer screening peptide and the effect has been the subject of several recent studies [21,23,30]. Because the screening peptide sets were derived from quite disparate subtypes, there was significant frame offsetting between peptides mapping to the same region of the different peptide sets. When a given epitope was detected with more than one peptide set, there were 70 examples of frame offsetting between the concordant (positive) peptides (Table 2). This indicates that despite significant minimal epitope offsetting, cross-recognition of the peptide sets was frequent. In addition, within the concordant peptides there were 74 examples of peptides with different sequences able to be recognized. These most likely represent truly cross-reactive responses, since more than one peptide sequence can be recognized by CTL from a single individual.
Next, the discordant peptides were compared to the corresponding positive peptides to identify the reason for noncross-recognition. The most likely reason for non-crossrecognition was a sequence difference between the peptides. In 76 discrete epitopic regions a discordant peptide had a different sequence compared with the corresponding positive peptide, and of these 52 were in the same frame while 24 were offset in frame. Importantly, it was noted that in 18 discrete epitopic regions, discordant results were obtained between peptide sets despite sequence identity across the corresponding regions. In 13 instances there was frame offsetting between the positive and discordant peptides, which could account for the disparity in recognition. However, in 5 instances peptides of identical primary sequence were discordantly scored as positive. In each of these 5 cases the positively scored peptide only marginally exceeded the cut-off for positivity. However, it was impossible to determine if these discordantly scored peptides were a result of a false positive (peptide incorrectly scored positive) or a false negative (discordant peptide incorrectly scored negative). In summary, the majority of examples of discordant detection of CTL responses were due to sequence variation, while the position of a minimal epitope within a screening peptide inconsistently affected detection of CTL responses. Artifactual false positive or false negative detection of CTL responses was also encountered on rare occasions.

Epitopes commonly targeted in subtype B and C are also targeted in subtype A infection
The most frequently recognized peptides (3 or more responders) were examined for the possession of common HLA alleles among the responder subjects and analyzed for known CTL epitopes. Table 3 outlines 11 commonly recognized peptides (15-mer) or peptide overlaps (11-mer) observed in the study and their probable HLA-restrictions. Of these 11 epitopes 8 have been described before [15] and are commonly recognized in both subtype B [10,11] and subtype C [25,26,31] infections. The previously described minimal epitopes are also listed in Table 3. One Nef peptide contains a previously defined HLA-B*3501 restricted epitope, or overlapping epitope, which is restricted by B*4201/02 and/or B*5301. Seven of the epitopes were detected with all peptide sets while 3 displayed variable cross-reactivity and 1 was subtype A Nef-specific. The well characterized and studied SL9 A*0201-restricted Gag p17 epitope (present in the A-Consensus and C-Isolate peptide sets) was recognized by 5 of 9 A*0201 subjects, but the variant (SLFNTIATL) was recognized by only 3 of these 5 subjects, indicating sequence dependent modulation of immunodominance and cross-reactivity for this epitope. Variable cross-reactivity was also observed for another previously characterized epitope -the Gag p24 KF11 B*5701/03 restricted epitope -was recognized by 5 of 5 B*5701/03 subjects, but the variant (KGFNPEVIPMF) was recognized by only 3 of these subjects. The B*4202 restricted Gag p24 epitope TL9 (TPQDLNMML) showed subtype specificity, in that of 4 B*4202 subjects responding to this epitope only 1 crossreacted with the peptides containing the variant TPQDL-NTML. Therefore, the M to T change in this epitope appears important for CTL recognition. Of the 4 Nef responses which could be assigned to a particular HLAallele, only the potential A*6802 restricted epitope (AVTSSNVNHPS) showed subtype specificity. Three A*6802 subjects responded to this epitope in the A-Nef peptide set, but none recognized the complementary peptides in the C-or D-Nef peptide sets. A deletion of 2 amino acids in the A-Nef isolate sequence relative to the C-and D-Nef isolates used in the study most likely accounts for this difference in recognition. The 3 other Nef epitopes which could assigned to HLA-alleles had been defined previously and were recognized and conserved in the 3 peptide sets. Seven subjects recognized the p24 peptide FRDYVDRFFKTLRAE (amino acids 293-307; HXB2 numbering) in all of the peptide sets. This sequence maps to a highly conserved region of p24 and is identical among 3 of the peptide sets and has a single substitution of F301Y in the UG57143 (subtype D) peptide set. In the subtype C peptide set, 2 peptides (#73 and #74) have this sequence spread across their overlap, and both were recognized by all 7 subjects. Further characterization of this epitope is performed below.

Characterization of an Immunodominant HLA-C w *0304 Restricted Gag Epitope
The immunodominant, cross-subtype response directed against the conserved sequence FRDYVDRFFLTLRAE (peptide #74 from the A-Gag consensus set) was further characterized. Several epitopes have been previously mapped to this region and hence it was of interest to map the minimal epitope and to determine if this response was restricted by one, or multiple, HLA alleles. All of the seven subjects responding to this epitope expressed the HLA-C W *0304 allele (or a closely related HLA-C W 03 family allele). While no exact match to the defined C W 0304 peptide-binding motif [34] was found in the 15-mer, an internal 9-mer (YVDRFFKTL; referred to as YL9) had the best possible match of any minimal peptide within the 15 mer peptide. Therefore, HLA restriction assays were carried out using BLCL with a partial HLA match with the test subjects and using BLCL expressing C W *0304. In addition, both the 15-mer and 9-mer peptides (YL9) were tested directly for up-regulation of IFN-γ gene expression. Representative data for one of the six responders (KNH1272) is shown in Figure 6A. The 15-mer and YL9 peptides elicit an IFN-γ response from an almost identical number of CD8 + T cells (3.24% and 3.64% respectively). The only common allele expressed by the BLCL able to present the 15 mer peptide is HLA-C W *0304 demonstrating that C W *0304 is the restricting allele for this epitope. To confirm that the YL9 was the minimal epitope, CTL effector cells were generated from PBMC of a C W *0304 responder subject (KNH1241) using an in vitro stimulation protocol with the 15-mer peptide. Following two rounds of in vitro stimulation the effector cells were used in a standard chromium release assay to test for cytotoxic activity against the 15-mer peptide #74 (FRDYVDRFFLTLRAE), two flanking peptides (#73 and #75) to which no response was detected in the screening ELIspot assays, and the YL9 peptide. Figure 6B shows the efficient specific killing (effector to target ratio = 20:1) of autologous BLCL pulsed with YL9 or peptide #74 (FRDYVDRFFLTLRAE), but not peptide #73 which has the C-terminal L of YL9 truncated, nor peptide #75 which has the N-terminal Y of TL9 truncated. Therefore the minimal epitope is YL9. In addition the effector cells also demonstrated efficient killing of BLCL pulsed with variants of YL9, which were observed in the cohort. As shown in Figure 6B, BLCL pulsed with each of three variants YL9-F6Y, YL9-T8V and YL9-T8C were efficiently lysed. The ability of related alleles within the C W 03 family to present the YL9 peptide was also tested. The effector cell line from KNH1241 was subjected to a further round of in vitro stimulation and the resultant cells used as effectors in a chromium release assay to test for cytotoxic activity against a panel of BLCL expressing different HLA-C W 03 family alleles. Figure 6C shows that C W *0302 and C W *0303 can present YL9 to a C W *0304-restricted CTL line. The peptide-pulsed cells are clearly lysed at a range of E:T ratios from 20:1 to 2.5:1 compared with the sham-pulsed control cells. The autologous BLCL (C W *0304 expressing), and BLCL which do not express any HLA-C W 03 alleles, were used as positive and negative controls respectively. Since the relative cross-reactivity of peptide variants can be over-estimated when using highly elevated concentrations of peptide, a titration of the response to YL9 and its variants was performed with PBMC from two YL9 responders. Figure 6D shows the sequence of the variants used and the number of occurrences of each variant in the proviral DNA of the cohort. In both subjects the response to YL9 (treated as the index peptide) was of higher avidity than that to any of the three variants ( Figure 7). Of note is that the YL9-T8C variant, the weakest stimulator of all the variants, was detected in the only one of nine C W *0304 positive subjects that did not respond to the YL9 epitope. Therefore the YL9 epitope can be presented by most alleles within the HLA-C W 03 Venn diagram display of responses (epitopes) detected with either Gag (A) or Nef (B) peptide sets  family, but in spite of sequence conservation potential escape mutants may already exist.

Discussion
While HIV-1 subtype C is the predominant circulating pure subtype in sub-saharan Africa, HIV-1 subtype A constitutes a significant proportion of the epidemic in eastern and central Africa [35][36][37]. Recent studies have estimated that HIV-1 subtype A constitutes >90% of the epidemic in terms of pure subtype and recombinant forms in eastern Africa, particularly in Kenya [35]. Comprehensive studies have characterized CTL responses in HIV-1 subtype B and C infections, however few studies have mapped in detail CTL cell responses in HIV-1 subtype A infections. Our results show that, as has been observed and described for subtype B and C infections, the Gag and Nef proteins are frequent targets of the CTL response of HIV-1 subtype A infections. Although the frequency of responses detected in this cohort against individual peptides was not as great as that detected in studies of subtype B infection (up to 50% of subjects responding to a single Nef peptide) [10,11], the pattern of CTL responses across the Gag and Nef proteins was remarkably similar to studies from other subtypes [10,11,26,31]. Hence, it appears likely that the N-and C-termini of p17, much of p24 and the central conserved region of Nef are immunodominant for CTL responses irrespective of the infecting subtype. Importantly, both the frequency of responding subjects, and the magnitude of the CTL responses detected against Gag and Nef using IFNγ ELIspot assay, was also consistent with results described in other studies of drug treatment naïve subjects from Africa [27,31].
Given the disparity of the different peptide sets used (derived from subtype A consensus, and subtype A, C and D isolates) and the fact that the subtype A derived peptide sets were much more similar on average to the viral sequences obtained from the studied cohort, it was surprising to observe that both the magnitude and pattern of recognition of the peptide sets was so similar for both Gag and Nef. CTL recognition is critically dependent upon peptide binding to MHC molecules and T cell receptor interactions with the peptide-MHC complex [38]; hence it was reasonable to expect that peptides from non-subtype A origin should be recognized to a lesser extent than the subtype A derived peptides. However, the results presented here demonstrate that viral sequence variability, and by extension the infecting subtype, does not predict the degree of subtype-specific responsiveness of CTL. The subtype A based peptide sets only marginally improved our ability to detect CTL responses, with no single peptide set capable of detecting all CTL responses. These observations are not without precedent, as we have demonstrated equivalent Gag, Env and Nef multiple-subtype recognition by CD8 T cells using a recombinant vaccinia virus based expression system producing full-length gene products in a similar cohort of Kenyan subjects [39]. In addition, in studies on individuals from Uganda, where subtype D and subtype A predominate in the HIV-1 epidemic, the lack of subtype-specificity and predictive capacity of the infecting subtype has also been described [27]. A simplistic interpretation of these results is that broadly cross-reactive CTL are generated by any subtype of infection and these responses may be predictive of the ability of a single isolate, or consensus sequence, based vaccine to generate broadly cross-protective responses. An important caveat associated with the experimental approach used in these studies need to be considered before such a profound conclusion can be reached with confidence. The concentration of 15-mer peptides used in these studies is very high -usually in the low micro-molar range, whereas minimal peptides have been shown to have half-maximal CTL stimulatory capacity in the low nano-molar range to high pico-molar range [40,41]. The excessive amounts of 15-mer peptide used in the screening assays may stimulate partially cross-reactive CTL, which might not recognize endogeneously processed and presented antigen on a virus infected cell. Titration of the HLA-C W *0304 restricted YL9 epitope variants performed in this study showed that even though cross-reactivity of the F6Y variant was detected for all responding subjects (8/9) in the screening and confirmation assays, CTL have a much lower avidity for the F6Y variant than the wildtype. Hence, true CTL cross-reactivity needs a more stringent definition -one that takes into account avidity for variant peptides, and translation of avidity measurements into biological relevance. This effect may be even more pronounced on HIV-1 infected cells where surface expression of HLA class I A-and B-alleles can be down-regulated by the Nef protein [42,43]. A further caveat associated with the use of 15-mer peptides is that minimal CTL epitopes -generally 9-10 amino acids in length -are embedded in the 15-mer peptides. Several recent studies have demonstrated that the relative position (or offset) of a minimal epitope within a 15-mer peptide can adversely affect the magnitude of the CTL response measured in response to a given 15-mer peptide [21,23]. While the precise mechanism behind the "epitope-offsetting" effect has not been elucidated it is assumed that amino acid residues flanking the minimal epitope may impair the ability of the 15-mer to be bound by MHC, and/or processed, prior to CTL recognition. As shown in the present study the epitope-offsetting effect can lead to artifactual false-negatives when comparing different sets of 15-mer OLPs. Hence, the high concentrations of 15-mer peptides used in screening assays may contribute to an over-estimation of cross-reactivity, and the offsetting of variant epitopes in different 15-mer peptide sets can lead to an under-estimation of cross-reactivity. Despite the potential to confound interpretation of our results, the epitope-offsetting effect was the exception rather than the rule, and as such we believe our overall interpretation of the results to be accurate. In support of this are prior studies, which have shown that multi-subtype reactivity can be readily detected using recombinant vaccinia viruses to deliver Gag, Nef and Env proteins into the cytoplasm -thereby enabling de novo antigen-processing and presentation to occur -avoiding concentrationdependent issues with peptide studies [28,39,44].
Reagent selection is a critical determinant for maximizing detection of CTL specific for different epitope variants of HIV-1. While the use of reagents that match the autologous virus sequence in a given host would be the ideal rea-gent of choice, practical limitations preclude this approach for large-scale cross-sectional screening studies. Consensus and ancestral sequence based peptide sets have been proposed as a practical solution for maximizing CTL epitope detection. However, as the data presented here shows, a consensus sequence representing a single subtype cannot fully capture the breadth of the CTL response. Utilization of multiple peptide sets clearly increases the breadth of detection of HIV-1-specific CTL, most likely because of the presence of different variants of many epitopes among the peptide sets. Using peptides representing different variants of epitopes -either in OLP sets or as minimal peptide epitopes -therefore gives a better account of the true CTL breadth, especially in locations where multiple subtypes co-circulate. The importance of revealing the true breadth of the CTL response in HIV-1 infection has been highlighted in the recent study of Frahm et al. [45], which showed that targeting of subdominant CTL epitopes was associated with better control of viral load. If this result proves to be generalizable, then CTL-based vaccine and immunotherapeutic strategies will need to maximize the breadth of the induced CTL response in order to be efficacious. This further highlights the importance of reagent selection for measuring CTL magnitude and breadth and for interpreting cross-reactivity in the setting of HIV-1 infection and vaccine trials.
While several HLA-C restricted epitopes from HIV-1 have been defined [15], this study presents, to our knowledge, the first evidence of HLA-C restricted immunodominance at the population level. Interestingly, the minimal 9-mer (YL9) defined here (and in reference [25]) with a HLA-C W *0304 allelic restriction, has been defined with HLA-B*1510 [31] and HLA-A*0207 [44] restrictions in other Peptide set (protein) Sequence Number of responders HLA allele in common Previously defined epitope A-Con 1 /C-Iso 2 (Gag) populations. However, the B*1510 restriction analysis of this peptide defined by Novitsky et al [31] did not completely rule out the possibility that HLA-C may have been the restricting locus because of the tight linkage disequilibrium of the HLA-B*1510 allele with C W 03 alleles. Given that YL9 is recognized in the context of most members of the HLA-C W 03 allele family, and at least two other HLA alleles, and is derived from a highly conserved region of the p24 protein, this peptide warrants inclusion in minimal epitope based vaccine strategies. It should be noted that the most frequently observed peptide response and HLA combination that we noted for the Nef protein was also a HLA-C allele: HLA-C W *0701 with peptide sequence KKRQEILDLWVYHTQ (defined as KY11 associated with C W *0701 allele possession in reference [25]). HLA-C alleles may offer an attractive alternative to the more commonly proposed HLA-A and -B loci for minimal epitope targeted vaccine strategies because they are refractory to down-regulation by the Nef protein [42,43].

Conclusion
In conclusion, we have shown that in subtype A infections the pattern of immunodominance and epitope clustering observed within the Gag and Nef proteins of HIV-1 is similar to that seen in subtype B and C infections. Importantly, similar epitope clustering patterns were observed using either a subtype matched consensus-based peptide set, or isolate-based peptide sets from heterologous subtypes. In agreement with previous studies, knowledge of the predominant infecting subtype in a given population does not necessarily predict the subtype-specificity of the CTL response. An extension of this observation was the finding that no single screening sequence, even a subtype matched consensus sequence, can fully capture the true breadth of the CTL response. Future studies aimed at capturing the true breadth and cross-reactivity of HIV-1-specific CTL responses in multiple-subtype endemic regions will require: (1) monitoring the viral quasi-species longitudinally to give a sense of what sequences may be driving a measured CTL response; (2) high resolution HLA-typing data from the subjects studied, (3) titration studies with synthetic peptides representing minimal epitopes of multiple variants or peptides based upon the autologous viral sequence and; (4) an understanding of how closely the avidity of a CTL for a variant peptide needs to match that for the index peptide to be considered truly cross-reactive. Finally, vaccine trials offer the best setting for testing the true extent CTL cross-reactivity, since this is the only circumstance in which the exact sequence that primes a CTL response is known with certainty.

Study subjects
Anonymously donated HIV-1 positive blood units were collected between 1999 and 2000 from Kericho District Hospital (Kericho), Rift Valley Provincial Hospital (Nakuru) and Kenyatta National Hospital (Nairobi), all in southern Kenya, under a study approved by both Kenyan and U.S. based Institutional Review Boards. Names, personal information and medical conditions of the subjects were not available, but all subjects were antiretroviral treatment naïve. Blood units were identified only by an alphanumeric code and because of the nature of collection, CD4 counts and viral load data were not available. HIV-1 positivity was assessed by Serostrip (Saliva Diagnostic Systems, Medford NY, USA) and confirmed by ELISA (Organon Teknika/BioMerieux, Inc., Marcy l'Etiole, France).

PCR-based HLA class I Typing
HLA typing was performed on all subjects at the University of Alabama (Birmingham, AL), using DNA extracted from either PBMC or autologous B lymphoblastoid cell A. The YL9 response is HLA-C W *0304 restricted Figure 6 A. The YL9 response is HLA-C W *0304 restricted. CFC assays for IFNγ up-regulation were performed using 15-mer peptide pulsed (solid bars) or sham-pulsed (open bars), partially HLA-matched BLCL as antigen-presenting cells for PBMC. Media alone, and media containing SEB (hatched bars), served as negative and positive controls respectively. The SEB response has been truncated for clarity and the frequency of responding cells appended beside the bar. All panels were gated based upon the CD3 + CD8 + CD69 HIGH cell population in the PBMC. Only BLCL possessing the HLA-C W *0304 allele (boxed) can present the peptide. The parent 15-mer (peptide #74 from A-consensus peptide set), and the minimal 9-mer peptide (YL9) added alone to the PBMC stimulated an equivalent frequency of CD8 + T cells. B. A CTL line generated by in vitro stimulation with peptide #74 from the A-Gag consensus peptide set efficiently lysed autologous BLCL pulsed with the same peptide, but not adjacent peptides #73 or #75, in a standard chromium release assay. Autologous BLCL pulsed with the predicted minimal epitope (9-mer YL9), and three variants of this epitope detected in the same cohort, were also lysed. Symbols for the effector to target ratios are denoted below the figure panel. C. Effector cells from the re-stimulated CTL line from above were able to lyse YL9-pulsed allogeneic BLCL, which express different alleles from the HLA-C W 03 family. For each BLCL tested sham-and peptide pulsed targets are shown at a range of E:T ratios from 20:1 down to 2.

Enzyme-linked immunospot (ELIspot) assay
All assays were performed using RPMI-1640 medium containing 10% normal human serum, 100 U/ml penicillin and 100 µg/ml streptomycin (complete medium; CM). Cryopreserved PBMC were recovered from liquid nitrogen, thawed rapidly, washed twice with CM and incubated at 2-5 × 10 6 cells/ml in CM for 14-16 hours. After the overnight rest, the PBMC were enumerated prior to addition to the ELIspot assay plates at 1-2 × 10 5 viable cells per well. Ninety-six well ELIspot plates (Multiscreen ® -IP plates MAIP type plates, Millipore, MA) were prepared by pre-wetting with 50 µl of 70% ethanol (in water) per well and incubating for 5 minutes at room temperature followed by washing six times with PBS. Plates were coated with mouse anti-human IFNγ monoclonal antibody pot tests and controls were performed in triplicate wells. Plates were incubated for 20-24 hours at 37°C (5% CO 2 ), washed six times with PBS/0.05% Tween 20 buffer and incubated for two hours with biotinylated mouse antihuman IFNγ monoclonal antibody (7B6-1-biotin, Mabtech AB, Sweden) at 2 µg/ml in PBS/0.05% Tween 20 buffer. ELIspot development consisted of a one hour incubation with an avidin horseradish peroxidase complex (Vectastain ® ABC kit, Vector Labs, CA) in PBS/0.05% Tween 20 buffer followed by washing six times with PBS, and incubation with peroxidase substrate AEC for five minutes (AEC substrate Kit, Vector Labs, CA). ELIspot plates were examined under a stereomicroscope and spots were evaluated with an Automated Elispot Reader System using KS 4.3 software (Carl Zeiss, Thornwood, NY) by an independent scientist in a blinded fashion (Henry M. Jackson Foundation, Rockville, MD). Positive IFNγ spot forming units (SFU) representing single cells were counted and expressed as SFU per one million input PBMC. Assays were considered valid if responses of greater than 500 SFU per 1 million PBMC were detected with SEB. In the screening assays the seven peptide sets were tested in a matrix format consisting of 11 pools of 11 or 12 peptides for the Gag OLP sets and 7 pools of 7 or 8 peptides for the Nef OLP sets. After matrix deconvolution most of the individual peptides were screened in triplicate to confirm the response. Positive responses were defined as those where the mean of the test wells exceeded the 99% confidence interval of replicates of six negative control wells.

CTL effector cell generation
Effector cells were prepared by in vitro stimulation of thawed cryopreserved PBMC. Peptide pulsed (10 µg/ml overnight), irradiated (10000 rad) autologous BLCL (2 × 10 6 cells) were washed three times with CM and then cocultured with 10 -20 × 10 6 PBMC in 10 ml CM supplemented with 5 ng/ml rhIL-7 (R&D Systems, Minneapolis, MN) for 4 days. 5 ng/ml rhIL-2 (R&D Systems, Minneapolis, MN) was then added to the co-cultures, and the cultures were maintained and split with fresh CM and rhIL-2 for up to 24 days. Effector cell lines were then maintained by re-stimulation every 7-14 days with irradiated, peptide pulsed, autologous BLCL and 5 ng/ml rhIL-2 in CM.
Chromium release assay for cytotoxic activity CTL effector cells prepared as above were screened for cytotoxic activity against peptide pulsed autologous or partially HLA matched BLCL. BLCL (1 × 10 6 ) were incubated overnight with 10 µg/ml of relevant peptide in the presence of 100 µCi of 51 Cr-labelled sodium chromate (NEN, Boston, MA) and then washed three times with RPMI-1640 to remove excess 51 Cr-sodium chromate and peptide. Non-peptide pulsed BLCL served as the negative control for cytotoxic activity. CTL activity was titrated at several effector to target (E:T) ratios and expressed as percentage of maximal specific lysis of 2500 51 Cr-labelled target cells per well. Maximum release was determined by lysis of 51 Cr-labelled target cells with 5% SDS. Percent specific cytotoxicity was calculated using the formula: 100 × [(test release -spontaneous release)/(maximum releasespontaneous release)]. Assays were considered valid if spontaneous release was <30%. All assay tests were performed in triplicate and a specific activity of >10% was considered to be positive.

Cytokine flow cytometry (CFC) assay
Cryopreserved PBMC were thawed rapidly, washed twice with CM and either used immediately, or incubated at 2-5 × 10 6 cells/ml in CM for 14-16 hours. PBMC were added at 0.5 to 1.0 × 10 6 cells per well into 96 well polypropylene tissue culture trays and stimulated either directly with SEB, or with autologous or allogeneic peptide-pulsed BLCL. BLCL were pulsed overnight with relevent peptide (10 µg/ml), washed five times after the overnight incubation, and distributed at 1 × 10 5 cells per well (ratio 10:1, PBMC:BLCL). As a positive control for functional integrity of the cryopreserved cells, SEB was added to a single well at 5 µg/ml final concentration. The assays were incubated for 6 hours at 37°C (5% CO 2 ) in the presence of the protein transport inhibitor Brefeldin A (10 µg/ml; Sigma, St.Louis, MO), and were then terminated by transfer to 4°C overnight. Cells were stained for surface markers and intracellular IFNγ expression (CFC assay) the following day. Co-cultured PBMC (prepared above) were washed once with flow buffer (DPBS/0.1% BSA/0.1% sodium azide) and incubated in the 96-well tissue culture tray wells for 10 minutes in 200 µl flow buffer (containing 1 mM EDTA) at room temperature (same volume, temperature and base buffer used for all subsequent washings and incubations). Cells were washed once, fixed in 2% formaldehyde for 30 min and washed again. Fixed cells were permeabilized with 0.5% saponin (Sigma, St. Louis MO.) for 30 min, washed and resuspended in 0.5% saponin containing the following monoclonal antibodies: FITC-conjugated anti-interferon-γ (clone 25723.11); PE-conjugated anti-CD69 (clone L78); PerCP-Cy5.5-conjugated anti-CD8 (clone SK1); and APC-conjugated anti-CD3 (clone SK7)(BD Biosciences, San Jose, CA). After 30 min incubation, cells were washed three times with flow buffer and finally re-suspended in 200 µl of flow buffer. Stained cells were stored at 4°C and analyzed by flow cytometry within 24 hours. Data acquisition was performed on a FACScalibur flow cytometer (Becton Dickinson, San Jose, CA). Initial gating was performed using a total lymphocyte gate based on forward and side scatter characteristics and acquisition of 50, 000 -200, 000 cells within this gate. Color compensation was performed using similarly prepared cells from an HIV-1 sero-negative donor and staining singly labeled cells with anti-CD3 labeled with FITC, PE, PerCP-Cy5.5 and APC fluorochromes (BD Biosciences). Data sets were analyzed using FlowJo software (version 4) (TreeStar, Cupertino, CA). Test wells were considered positive if at least a two-fold increase in gated positive events was detected compared with the appropriate negative control. The mean background IFNγ positive CD8 T cells was 0.026% and 0.81% for the media only controls and sham-pulsed BLCL respectively.


extfieldsofstudy: Chemistry Medicine

s2fieldsofstudy:
Biology
Computer Science

text:
The Tyrosine Kinase Syk Regulates TPL2 Activation Signals*

Tpl2/Cot is a serine/threonine kinase that plays a key physiological role in the regulation of immune responses to pro-inflammatory stimuli, including tumor necrosis factor-α (TNF-α). TNF-α stimulates the JNK, ERK, and p38 mitogen-activated protein kinases and the NF-κB pathway by recruiting RIP1 and TRAF2 to the TNF receptor 1. Here we showed that Tpl2 activation by TNF-α signals depends on the integrity of the Tpl2-interacting proteins RIP1 and TRAF2, which are required for the engagement of the ERK mitogen-activated protein kinase pathway. However, neither RIP1 nor TRAF2 overexpression was sufficient to activate Tpl2 and ERK. We also showed that Tpl2 activation by TNF-α depends on a tyrosine kinase activity that is detected in TNF-α-stimulated cells. Based on both genetic and biochemical evidence, we concluded that in a variety of cell types, Syk is the tyrosine kinase that plays an important role in the activation of Tpl2 upstream of ERK. These data therefore dissect the TNF receptor 1 proximal events that regulate Tpl2 and ERK and highlight a role for RIP1, TRAF2, and Syk in this pathway.

Despite the profound biological effects of overexpressed Tpl2, Tpl2 knock-out (Tpl2 Ϫ/Ϫ ) mice are viable and have no obvious phenotypic defects (10). However, a detailed analysis of these mice revealed a critical role for Tpl2 in the regulation of innate and adaptive immunity and in the response to inflammatory signals through the modulation of the ERK MAPK signaling pathway. Lipopolysaccharide (LPS)-stimulated Tpl2 Ϫ/Ϫ macrophages exhibit impaired synthesis of tumor necrosis factor-␣ (TNF-␣) and cyclooxygenase-2, because of a specific defect in ERK activation (10,11). As a result, Tpl2 Ϫ/Ϫ mice are resistant to LPS/ D-galactosamine-induced septic shock (10). In other studies we found that Tpl2 is also required for the transduction of ERK activation signals initiated by CD40 engagement and contributes to IgE synthesis in B lymphocytes stimulated with interleukin 4 and anti-CD40 mAb (12). Similarly, we found that ERK phosphorylation induced by TNF-␣ is also severely impaired in Tpl2 Ϫ/Ϫ macrophages and that the ERK activation signals are induced by triggering the p55 TNF receptor 1 (TNFR1) (12). Fibroblasts isolated from Tpl2 Ϫ/Ϫ mice demonstrate additional defects in NF-B transactivation and JNK signal transduction in response to TNF stimulation (13). Taken together, these findings may provide an explanation to the reported protection of Tpl2 knock-out mice from TNF-␣-induced inflammatory bowel disease (14).
The mechanism by which Tpl2 is regulated by and contributes to the transduction of pro-inflammatory signals is currently the subject of intense investigation. Previous studies demonstrated that Tpl2 forms a stoichiometric, high affinity complex with the cytoplasmic NF-B inhibitory protein p105 NF-B1 (15) and that the Tpl2:NF-B1 binding stabilizes but inactivates Tpl2. LPS and TNF signals promote the dissociation of Tpl2 from p105 (16). Unbound Tpl2 is active but unstable and undergoes rapid degradation via the proteasome (16). As expected, the steady-state levels of Tpl2 are very low in NF-B1 Ϫ/Ϫ macrophages, and the ability of LPS to activate ERK and its downstream target cyclooxygenase-2 is severely impaired in these cells (16). Although not fully defined, this regulatory event occurs downstream of the IB kinase (IKK) signaling complex that is responsible for the stimulus-dependent serine phosphorylation of NF-B1 and its subsequent degradation by the proteasome (17). Indeed, the inactivation of the IKK␤ catalytic subunit of the IKK signaling complex results not only in impaired NF-B signaling but also in diminished activation of Tpl2 and ERK in response to TNF-␣ or LPS (18,19). IKK␤ is also required for the direct phosphorylation of Tpl2 at Thr 290 , which regulates Tpl2 binding to NF-B1 (20,21). However, although IKK␤ and NF-B1 are required for the activation of Tpl2, additional molecules that regulate Tpl2 are likely to exist. Thus, a role for protein-tyrosine kinases in Tpl2 signaling has been recently highlighted by the inhibitory effects of the broad spectrum tyrosine kinase inhibitor herbimycin-A on LPS-induced Tpl2 activation (22).
The binding of soluble TNF-␣ to TNFR1 induces the recruitment of receptor-interacting protein-1 (RIP1) and TNF receptor-associated factor-2 (TRAF2) to the cytoplasmic C terminus of TNFR1 (23), which results in the transduction of signals that regulate the MAPK pathways and NF-B (24 -26). In the present study, we focused on the mechanisms of Tpl2 activation by TNF-␣, upstream of ERK. Our data demonstrate that Tpl2 plays an important role in the TNF-␣-mediated activation of MEK and ERK across different cell lineages. In addition, our data show that RIP1 and TRAF2 associate with Tpl2 and that their expres-sion is necessary but not sufficient for the transduction of Tpl2 activation signals engaged by TNF-␣. Finally, we provide biochemical and genetic data that demonstrate that the activation of the Tpl2/MEK/ERK cascade by TNF-␣ depends on the tyrosine kinase Syk.

MATERIALS AND METHODS
Cell Culture and Transfections-Cell culture, transfections, and reporter assays were performed as described previously (10,27,28). H33HJ-JA1 and Jurkat E6.1 cells were purchased from European Collection of Animal Cell Culture and maintained in RPMI supplemented with 10% fetal calf serum (Invitrogen). HeLa and MCF7 cells were obtained from the Cancer Research UK Cell Culture facility, London, UK, and cultured in Dulbecco's modified Eagle's medium supplemented with 10% fetal calf serum. Macrophage and fibroblast cultures were performed as described previously (12). Chemical inhibitors (LY, BisI, PP2, PP3, Pic, and HerbA) were purchased from Calbiochem and dissolved in Me 2 SO prior to use. A Myc-tagged Syk expression vector was kindly provided by Professor Steve Watson, University of Birmingham, UK.
Immunocomplex Kinase Assays-To assay Tpl2 kinase activity, 400 -600 g of whole cell lysate was immunoprecipitated for 4 -5 h with anti-Tpl2 antibody M20 coupled to protein-A-Sepharose (Santa Cruz Biotechnology) or unconjugated protein-A beads as a control. Bound proteins were washed twice with kinase lysis buffer (20 mM Tris, pH 7.6, 0.5% Triton X-100, 250 mM NaCl, 3 mM EGTA, 3 mM EDTA, 1 mM Na 3 VO 4 , 0.5 mM sodium pyrophosphate, 25 mM ␤-glycerophosphate, 10 g/ml leupeptin, 5 g/ml aprotinin, and 1 mM DTT) and twice with kinase reaction buffer (KRB: 20 mM MOPS, pH 7.2, 5 mM EGTA, 1 mM Na 3 VO 4 , 25 mM ␤-glycerophosphate, and 1 mM DTT). The beads were resuspended in 20 l of KRB containing 200 M ATP, 22 mM MgCl 2 , 0.4 g of inactive GST-MEK1 (Upstate Biotechnology, Inc.), and 1 g of inactive GST-ERK2 (Upstate Biotechnology, Inc.). Following incubation for 30 min at 30°C in a shaking incubator, the beads were pellet by centrifugation, and 6 l of the supernatant was transferred to a fresh tube together with 10 l of KRB, 10 l of MBP (Invitrogen) substrate (2 mg/ml stock in KRB), and 10 l of diluted [␥-32 P]ATP (10 Ci of [␥-32 P]ATP in KRB containing 500 M ATP and 75 mM MgCl 2 ). The reaction was incubated for 10 min at 30°C in a shaking incubator, and 10 l were spotted on a 2 ϫ 2-cm P81 paper square (Whatman) in duplicate or triplicate. The squares were washed three times with 0.75% phosphoric acid for 5 min per wash, once with acetone for 5 min, and then left to dry. The [␥-32 P]ATP that was incorporated to MBP was measured in a scintillation counter, and specific activity was calculated. Immunocomplex JNK and ERK in vitro kinase assays using GST-c-Jun (Cell Signaling Technology) and GST-Elk1 (Cell Signaling Technology) as substrates, respectively, were performed as described previously (12,29). For IKK kinase assays, cells were lysed in kinase lysis buffer and cleared by centrifugation (13,000 rpm, 10 min). 500 g of the lysates were then immunoprecipitated with 1.2 g of the anti-IKK␤ mAb H4 (Santa Cruz Biotechnology) and protein-G beads for 3 h. Bound proteins were washed twice with kinase lysis buffer and twice with IKK kinase reaction buffer (20 mM Hepes, pH 7.6, 20 mM MgCl 2 , 1 mM Na 3 VO 4 , 20 mM ␤-glycerophosphate), and the kinase reaction was performed in 20 l of reaction buffer containing 10 M ATP, 5 Ci of [␥-32 P]ATP, and 1 g of GST-IB␣ (Upstate Biotechnology, Inc.) for 30 min at 30°C in a shaking incubator. 20 l of SDS-gel loading buffer was then added to terminate the reaction, and the products were resolved on a 10% gel, transferred to nitrocellulose, and exposed to autoradiography. The membrane was then incubated with anti-IKK␤ polyclonal antibody H470 to confirm similar levels of immunoprecipitated IKK. Activation of Syk was measured by autophosphorylation assays, as described previously (30). Briefly, anti-Syk immunoprecipitates were washed once in kinase lysis buffer and three times with Syk kinase reaction buffer (25 mM Hepes, pH 7.5, 5 mM MgCl 2 , 5 mM MnCl 2 ). The kinase reaction was performed in 30 l of reaction buffer containing 20 Ci of [␥-32 P]ATP for 10 min at 30°C in a shaking incubator. 20 l of SDS gel loading buffer was then added to terminate the reaction, and the products were resolved on a 9% gel, which was dried and exposed to autoradiography.
Antibodies, Immunoblotting and Immunoprecipitations-Antibodies to phosphorylated IBa, MEK, ERK, Syk, and p38 and "total" ERK and p38 were purchased from Cell Signaling Technologies and used in immunoblotting at 1:1000 dilution. Msk1, p50/NF-B1, Akt, Syk 4D10 mAb, and phosphotyrosine 4G10 antibodies were purchased from Upstate Biotechnology, Inc. Polyclonal antibodies against IB␣, p65, TRAF2, and Syk were purchased from Santa Cruz Biotechnology. Agarose and HRP-conjugated anti-Tpl2 polyclonal antibody M20 was also obtained from Santa Cruz Biotechnology. For immunoprecipitations in 293 cells, 500 g of cell extracts were incubated overnight with 2 g of anti-RIP1 antibody (Pharmingen), and the precipitated proteins were analyzed by immunoblot. Syk was immunoprecipitated from 400 g of total cell lysates using 1 g of anti-Syk C-20 (Santa Cruz Biotechnology) or 4D10 antibody and immunoblotted with 4G10 mAb. For detection of NF-B1/Tpl2 interactions, a goat polyclonal NF-B1 antibody (Santa Cruz Biotechnology) was first coupled to protein A-Sepharose beads using dimethyl pimelimidate. The coupled antibody was then incubated with 2 mg of protein extracts overnight, and immunoprecipitated NF-B1 was immunoblotted with either HRP-conjugated Tpl2 or a rabbit polyclonal anti-NF-B1 (Upstate). A similar approach was used to detect endogenous TNFR1/Syk interactions in TNF-␣-stimulated macrophages, using an anti-TNFR1 antibody from R & D Systems.
RNA Interference-For delivery of small interfering RNAs (siRNA), 1 ϫ 10 5 MCF7 cells were plated in each well of a 24-well plate (Costar), and the next day siRNA duplexes were transfected using the siIM-PORTER transfection reagent (Upstate Biotechnology), according to the instructions of the manufacturer. Syk was targeted with the Syk siRNA duplexes GUCGAGCAUUAUUCUUAUAdTdT (and its antisense) and CCUCAUCAGGGAAUAUGUG (and its antisense). As a control, the firefly luciferase siRNA duplex CGUACGCGGAAUACU-UCGAdTdT (and antisense) was used. All siRNAs were synthesized by MWG Biotec, Ebersberg, Germany. Following a 6-h incubation with Syk or luciferase siRNA duplexes, an equal volume of media was added. Cells were then left to recover for 10 h and were re-plated in 24-well dishes. The next day, the cells were subjected to a second round of transfection to increase the siRNA-mediated gene suppression. Twenty four hours later, cultures were serum-starved overnight and then stimulated with TNF-␣, before lysis.

RESULTS
Tpl2 Is Largely Responsible for the Engagement of the MEK/ERK Pathway by TNF-␣-The role of Tpl2 in TNF-induced ERK signaling was first examined in bone marrow-derived macrophages (BMDM) isolated from the Tpl2 ϩ/ϩ and Tpl2 Ϫ/Ϫ mice. Cell cultures were stimulated with human TNF-␣, which selectively engages the mouse TNFR1. Western blots of cell lysates harvested at sequential time points were probed with antibodies against the phosphorylated and active forms of ERK1 and ERK2, the total (phosphorylated and nonphosphorylated) ERK, and the phosphorylated form of the ERK kinase MEK. The results confirmed our previous finding that the TNF-␣-mediated ERK phosphorylation is severely impaired, although not abolished, in Tpl2 Ϫ/Ϫ BMDM (12) (Fig.  1A). Moreover, the results of the present analysis extend this finding by the demonstration that MEK phosphorylation is also significantly reduced in TNF-␣ stimulated Tpl2 Ϫ/Ϫ BMDM (Fig. 1A). Therefore, Tpl2 functions upstream of MEK in the molecular pathway that is initiated by TNFR1 and results in the phosphorylation of ERK.
To confirm that the effect of Tpl2 on TNF-induced ERK signaling is not a macrophage-restricted phenomenon, we performed similar analysis in immortalized Tpl2 ϩ/ϩ and Tpl2 Ϫ/Ϫ fibroblasts. The results showed diminished ERK phosphorylation in TNF-stimulated Tpl2 Ϫ/Ϫ fibroblasts (Fig. 1B). Similarly, the TNF-mediated activation of ERK, as measured by in vitro kinase assays using GST-Elk1 as a substrate, was significantly reduced in MCF7 breast carcinoma cells transfected with low amounts of Tpl2KM, a catalytically inactive Tpl2 (Fig. 1C). Therefore, Tpl2 Tp12KM, a plays an important role in TNF-induced ERK signaling in a range of different cell types. However, additional Tpl2independent mechanisms of ERK signaling are also engaged by TNF stimulation.
RIP1 and TRAF2 Are Necessary for the Activation of the Tpl2/ERK Cascade in Response to TNF-␣ Stimulation-However, RIP1 or TRAF2 overexpression is not sufficient for ERK activation. In an effort to characterize the pathway through which Tpl2 regulates TNFR1-transduced ERK activation signals, we first examined whether Tpl2 is recruited to a RIP1-containing complex in TNF-stimulated cells. To this end, endogenous RIP1 was immunoprecipitated from Tpl2 ϩ/ϩ macrophages before, and 2.5 and 5 min after stimulation with TNF-␣. Immunoprecipitates were then immunoblotted with either an HRP-conjugated Tpl2 antibody or with anti-RIP1. The results showed weak association of RIP1 and Tpl2 in unstimulated cultures, which was significantly increased following treatment with TNF-␣ ( Fig. 2A). The ability of Tpl2 to complex with RIP1 was confirmed in human embryonic kidney (HEK) 293 cells transiently transfected with Myc-tagged Tpl2 or, as a negative control, FLAG-tagged Msk1. RIP1 immunoprecipitates from these cultures were immunoblotted with anti-Tpl2, Msk1, or RIP1 antibodies. It was found that overexpressed Tpl2, but not Msk1, associates with endogenous RIP1 (Fig. 2B). Similar experiments were performed in cells transfected with Myc-tagged NF-B1, a Tpl2-interacting protein.
RIP1 also interacts with TRAF2 following stimulation with TNF-␣ (23, 25). TRAF2 co-immunoprecipitates with overexpressed Tpl2 (28), but the physiological role of TRAF2 in TNF-induced Tpl2/MEK/ERK signaling is unknown. This issue was addressed in fibroblasts isolated from TRAF2 ϩ/ϩ and TRAF2 Ϫ/Ϫ mice (Fig. 2D). Examination of the effects of TNF on ERK phosphorylation in TRAF2 ϩ/ϩ fibroblasts demonstrated significant activation of ERK at 10 and 20 min, which returned to basal levels by 30 min of treatment (Fig. 2E). Most interestingly, the activation of ERK in TRAF2 Ϫ/Ϫ cells was reduced at 10 min and was abolished at 20 min of stimulation with TNF-␣ (Fig. 2E). Therefore, TRAF2 plays an important role in TNFR1-transduced ERK activation signals. This observation raised the question of whether TRAF2 is required for Tpl2 activation in response to TNF-␣. To this end, TRAF2 ϩ/ϩ and TRAF2 Ϫ/Ϫ fibroblasts were treated with TNF-␣ for 10 or 20 min or left untreated, and lysates from these cultures were immunoprecipitated with anti-Tpl2 antibody and subjected to an in vitro coupled kinase assay using inactive MEK, ERK2, and MBP as sequential substrates. The results showed significant increase in the endogenous Tpl2 kinase activity in TNF-stimulated TRAF2 ϩ/ϩ fibroblasts, which was absent in TRAF2 Ϫ/Ϫ cells (Fig. 2F). We conclude that TRAF2 is required for TNFR1 signaling on the Tpl2/MEK/ERK axis.
Overexpression of RIP1 or TRAF2 activates the JNK, p38, and NF-B pathways (31)(32)(33). To determine whether overexpression of TRAF2 and RIP1 also results in the activation of the Tpl2/MEK/ERK pathway, HEK293 cells were first transfected with RIP1, and its effects on the endogenous ERK2 activation were examined by in vitro kinase assays using GST-Elk1 as a substrate. As a control, the effects of transfected RIP1 on JNK1 activation were also assessed by in vitro kinase assays using GST-c-Jun as a substrate. RIP1 overexpression was found to increase the kinase activity of endogenous JNK1 but not ERK2 (Fig. 3, A  and B). Unlike RIP1, Tpl2 overexpression potently induced the activation of both ERK2 and JNK1 (Fig. 3, A and B). Similar results were obtained when the phosphorylation status of transfected HA-ERK1 or HA-JNK1 was examined in RIP1 overexpressing HEK293 cells (data not shown).
We next examined the effects of TRAF2 on the activation of the Tpl2/MEK/ERK pathway. To this end, HEK293 cells were transfected with empty vector (Fig. 3C, 1st 4 lanes), TRAF2 (5th lane) or, as a control, Tpl2 (6th lane), and they were either left untreated (1st, 5th, and 6th lanes) or stimulated with TNF-␣ for 10, 20, or 30 min (Fig. 3C, 2nd to 4th lanes). Endogenous ERK2 or, as a control, JNK1 was immunoprecipitated and examined for catalytic activity using GST-Elk1 or GST-c-Jun as a substrate, respectively. The results showed that expression of TRAF2 induced an ϳ2.2-fold increase in activation of JNK but failed to activate the endogenous ERK in these cells. However, transfection of Tpl2 or treatment with TNF-␣ engaged both signaling pathways (Fig.  3C). Similar results were obtained upon co-transfection of TRAF2 and HA-ERK1 (Fig. 3D), suggesting that the inability of TRAF2 to activate ERK is not merely a consequence of insufficient expression levels of TRAF2 versus ERK. The effects of TRAF2 on the kinase activity of Tpl2 . Serum-starved BMDM or fibroblasts from Tpl2 ϩ/ϩ and Tpl2 Ϫ/Ϫ mice were left untreated or stimulated with 25 ng/ml human TNF-␣ for various time intervals as indicated. Cell lysates were analyzed for phosphorylated MEK and ERK or for total ERK protein levels by immunoblot. C, expression of low amounts of catalytically inactive Tpl2 (Tpl2KM) suppresses TNF-induced ERK activation in MCF7 breast carcinoma cells. MCF7 cells (6 ϫ 10 5 cells per 30-mm dish) were transfected with 1 g of HA-ERK1 and 80 ng of a Tpl2KM construct (9) or control vector and 24 h later were serum-starved overnight. Next day, the transfected cells were stimulated with 40 ng/ml TNF-␣ or left untreated and ERK activation was determined by in vitro kinase assays (IVK) using GST-Elk1 as a substrate.
was also determined. Although TNF stimulation significantly increased the catalytic activity of Tpl2 in a time-dependent manner, transfection of TRAF2 had no effect (Fig. 3D). Taken together, these data suggest that the expression of RIP1 and TRAF2 is necessary but not sufficient for the activation of the Tpl2/ERK cascade in response to TNF-␣ stimulation.
The Syk Tyrosine Kinase Inhibitor Piceatannol Suppresses the TNFmediated Activation of the Tpl2/MEK/ERK Pathway-On the basis of the preceding data, we hypothesized that activation of Tpl2, following its recruitment to the TNFR1-RIP1-TRAF2 complex, requires additional TNF-induced signals. Previous studies had shown that tyrosine kinase signaling may play an important role in Tpl2/MAPK activation by LPS in RAW264.7 macrophages (22). To determine whether tyrosine kinases are also required for the activation of Tpl2 by TNF-␣ in BMDM, we treated these cells with the broad spectrum tyrosine kinase inhibitor herbimycin-A (HerbA), prior to stimulation with TNF-␣, and we analyzed their lysates for the expression and phosphorylation of MEK and ERK. The results showed a dramatic reduction in both MEK and ERK activation in TNF-␣-stimulated macrophages pretreated with HerbA, compared with cells exposed to TNF-␣ alone (Fig. 4A). On the basis of this observation, we proceeded to evaluate the effects of chemical inhibitors that target specific tyrosine kinases. To this end, Tpl2 ϩ/ϩ macrophages were treated with the Syk tyrosine kinase inhibitor piceatannol (Pic) (34), the PI 3-kinase inhibitor LY (35), the Src tyrosine kinase family inhibitor PP2, or its inactive control compound PP3, prior to stimulation with TNF. Moreover, we examined whether BisI (36), which inhibits the protein kinase C isoforms ␣, ␤I, ␤II, ␥, ␦, and ⑀, affects TNF-induced MEK/ERK signaling. The results showed a dramatic reduction in TNF-mediated phosphorylation of MEK and ERK by piceatannol but not by LY, PP2, PP3, or BisI (Fig. 4A). To confirm that LY was otherwise functional, we determined the kinase activity of Akt, an established PI 3-kinase target (37), using in vitro kinase assays with cross-tide as the substrate (38). TNF induced an increase in Akt kinase activity that was abolished in LY-treated cells (data not shown). Moreover, BisI suppressed the 12-O-tetradecanoylphorbol-13-acetate-induced phosphorylation of ERK (data not shown), which is known to occur via a protein kinase C-dependent (39) but Tpl2-independent (10) pathway.
Piceatannol could, theoretically, target the Tpl2-independent arm of TNF-induced ERK phosphorylation (see Fig. 1). To address this issue, immunoblot was re-probed for RIP1 expression. Whole cell lysates (WCL; 50 g) were also analyzed to confirm expression of transfected Msk1 and Tpl2. C, endogenous RIP1 co-precipitates with overexpressed Myc-tagged NF-B1, a Tpl2-interacting protein. D, expression of TRAF2 and Tpl2 in TRAF2 ϩ/ϩ and TRAF2 Ϫ/Ϫ fibroblasts as determined by immunoblot analysis of whole cell lysates. E, TRAF2 contributes to TNF-induced ERK activation. TRAF2 ϩ/ϩ and TRAF2 Ϫ/Ϫ fibroblasts were either left untreated or stimulated with TNF-␣, as indicated. Cell lysates were immunoblotted for phosphorylated or total ERK. Data are representative of four independent experiments. F, TRAF2 is required for TNF-induced Tpl2 activation. TRAF2 ϩ/ϩ and TRAF2 Ϫ/Ϫ fibroblasts were stimulated with TNF-␣ for 0, 10, or 20 min, as indicated, and lysed. Endogenous Tpl2 was immunoprecipitated from these lysates and subjected to in vitro coupled kinase assay using inactive MEK, ERK2, and MBP as sequential substrates. The relative increases in MBP phosphorylation (ϮS.D.) from three independent experiments are shown.
Tpl2 ϩ/ϩ and Tpl2 Ϫ/Ϫ BMDM were pretreated with piceatannol and then stimulated with TNF-␣ for 10 min. Piceatannol inhibited the TNFmediated activation of ERK in Tpl2 ϩ/ϩ but not in Tpl2 Ϫ/Ϫ BMDM (Fig.  4B), suggesting that Syk or a Syk-related kinase functions upstream of Tpl2 in TNFR1 signaling. The inhibition of ERK phosphorylation in response to TNF-␣ was not restricted to mouse macrophages, as piceatannol also suppressed the TNF-induced phosphorylation of ERK in H33HJ-JA1 Jurkat T cells, as well as in HeLa human cervical carcinoma cells (Fig. 4C). Both H33HJ-JA1 and HeLa are known to express Syk (40,41). The effects of piceatannol on TNF-induced Tpl2 activation were FIGURE 3. Overexpression of RIP1 or TRAF2 is insufficient to activate the ERK pathway. A and B, RIP1 overexpression activates JNK but not ERK. HEK293 cells were transfected with RIP1 or, as a control, Myc-tagged Tpl2. Anti-ERK2 immunoprecipitates (I.P.) of total cell lysates were subjected to in vitro kinase assay (IVK) using GST-Elk1 as a substrate (A). vec, vector. To confirm that under these experimental conditions the expression of RIP1 was functional, the same lysates were immunoprecipitated using anti-JNK1 antibody prior to examination of JNK kinase activity by in vitro kinase assays (B). C, TRAF2 overexpression fails to activate ERK. HEK293 cells were transfected with TRAF2 or, as a control, Myc-tagged Tpl2. Anti-ERK2 immunoprecipitates of total cell lysates were subjected to in vitro kinase assay using GST-Elk1 as a substrate. Parallel cultures were stimulated with 40 ng/ml TNF-␣ prior to lysis and evaluation of ERK2 kinase activity. To confirm that under these experimental conditions the expression of TRAF2 was functional, the same lysates were immunoprecipitated using anti-JNK1 antibody prior to examination of JNK kinase activity by in vitro kinase assays using GST-c-Jun as a substrate. D, TRAF2 overexpression does not promote the phosphorylation of co-expressed HA-ERK1 in HEK293 cells. E, TRAF2 overexpression does not activate Tpl2. HEK293 cells were transfected with TRAF2 or stimulated with TNF-␣, as indicated, and Tpl2 activity was assessed by coupled in vitro kinase assays. Data shown are the mean values (ϮS.D.) from three independent experiments. The inset shows the levels of immunoprecipitated Tpl2 in a representative experiment.

FIGURE 4. The Syk tyrosine kinase inhibitor piceatannol severely impairs the TNF-mediated activation of the Tpl2/MEK/ERK pathway.
A, the tyrosine kinase inhibitor HerbA and the Syk tyrosine kinase inhibitor piceatannol (Pic) severely impair TNF-induced phosphorylation of MEK and ERK in BMDM. Serum-starved Tpl2 ϩ/ϩ macrophages were pretreated with HerbA (1 g/ml), piceatannol (30 M), the protein kinase C inhibitor BisI (10 M), the PI 3-kinase inhibitor LY (20 M), and the Src family tyrosine kinase inhibitor PP2 (20 M) or its control compound PP3 (20 M) and then stimulated with 25 ng/ml TNF-␣ for 10 min. Lysates were analyzed for phosphorylated MEK and ERK or for total ERK by immunoblot. DMSO, Me 2 SO. B, piceatannol does not suppress ERK phosphorylation in Tpl2 Ϫ/Ϫ macrophages. Tpl2 ϩ/ϩ and Tpl2 Ϫ/Ϫ macrophages were pretreated with piceatannol for 1.5 h and then stimulated with TNF-␣ for 10 min or left untreated. Cell lysates were examined for ERK phosphorylation by immunoblot. C, piceatannol suppresses ERK phosphorylation in the Jurkat T cell lymphoma clone H33HJ-JA1 and the cervical carcinoma cell line HeLa. Cells were pretreated with piceatannol as in B and then they were either left untreated or stimulated with TNF-␣ at 40 ng/ml (H33HJ-JA1) or 30 ng/ml (HeLa). Lysates were analyzed for ERK phosphorylation by immunoblot. D, piceatannol inhibits TNF-induced Tpl2 kinase activity. Lysates from Tpl2 ϩ/ϩ BMDM treated as in A were subjected to in vitro coupled kinase assay using inactive MEK/ERK and MBP as substrates, respectively. Data shown are the mean values (ϮS.D.) from four independent experiments. then determined by in vitro coupled kinase assays. The results of this analysis showed a 3.7-fold increase in Tpl2 kinase activity following stimulation with TNF, which was reduced by more than 70% in piceatannol-treated cultures (Fig. 4D).
We next examined whether piceatannol treatment impinges on the TNF-mediated dissociation of Tpl2 from NF-B1, a critical step for Tpl2 activation (16,18). To this end, Tpl2 ϩ/ϩ macrophages or H33HJ-JA1 Jurkat cells were either left untreated or treated with piceatannol and then stimulated with TNF-␣. Endogenous NF-B1 was immunoprecipitated from these cultures and immunoblotted with antibodies against Tpl2 or NF-B1. As reported previously (18), TNF treatment promoted the dissociation of the long form of Tpl2 (Tpl2 L ) from NF-B1. Most interestingly, this effect was blocked by pretreatment with piceatannol in both lines (Fig. 5A). As IKK␤ and its regulatory subunit, IKK␥, are critical upstream regulators of the NF-B1-Tpl2 complex (18), the effect of piceatannol on TNF-␣-induced IKK activity was examined. The results showed that this inhibitor suppresses the TNF-mediated phosphorylation of IB␣ (Fig. 5B) and the catalytic activity of endogenous IKK␤ in macrophages (Fig. 5C) and H33HJ-JA1 cells (data not shown). Therefore, piceatannol inhibits the TNF-mediated activation of the Tpl2/MEK/ERK pathway by functioning upstream of the IKK signaling complex.
Role of Syk in TNF-mediated Activation of the Tpl2/MEK/ERK Pathway-The preceding data implicate Syk in Tpl2 signaling inasmuch as the Syk inhibitor piceatannol suppresses the TNF-mediated activation of Tpl2 and its downstream targets MEK and ERK. Piceatannol, however, may also target kinases other than Syk. We therefore sought to obtain additional evidence for the role of Syk in TNFR1 signaling upstream of the Tpl2/MEK/ERK pathway. To this end, we first examined the effects of TNF stimulation on Syk tyrosine phosphorylation, a prerequisite for its activation. Total cell lysates from Tpl2 ϩ/ϩ BMDM were isolated before and 1, 2.5, 5, or 10 min after stimulation with TNF-␣ and immunoblotted with the anti-phosphotyrosine antibody 4G10. The results showed increased tyrosine phosphorylation of an ϳ72-kDa protein within 2.5 min of stimulation (Fig. 6A). Re-probing the same immunoblot with an anti-Syk polyclonal antibody verified the identity of this protein as Syk. To confirm its phosphorylation in response to TNF-␣, Syk was immunoprecipitated from TNF-stimulated and control untreated Tpl2 ϩ/ϩ and Tpl2 Ϫ/Ϫ BMDM and immunoblotted with anti-phosphotyrosine (4G10) or anti-Syk antibodies (Fig.  6B). Furthermore, Syk activation was confirmed by in vitro kinase assays of immunoprecipitated Syk before and after TNF stimulation. In these experiments, the activation of Syk was dramatically suppressed in cells that were treated with piceatannol prior to TNF stimulation (Fig. 6C). Interestingly, Syk was also detected in TNFR1 immunoprecipitates from TNF-stimulated macrophage lysates (Fig. 6D).
Next, we sought to obtain genetic evidence for the role of Syk in the TNF-mediated activation of the Tpl2/MEK/ERK pathway. To this end, we first used a Jurkat T cell derivative (Jurkat E6.1) that lacks expression of Syk as a result of a single nucleotide insertion in the Syk open reading frame, leading to premature translational termination (40). The absence of Syk expression in Jurkat clone E6.1 and the expression of significant levels of Syk in H33HJ-JA1 Jurkat T cells (40) were confirmed by immunoblotting (Fig. 7A). H33HJ-JA1 and Jurkat E6.1 cells were then compared for the activation of the Tpl2/MEK/ERK cascade following stimulation with TNF-␣. The results showed significant activation of ERK in TNF-treated H33HJ-JA1 but diminished response in Jurkat E6.1 cells (Fig. 7B). The kinase activity of Tpl2 mirrored the phosphorylation of ERK, showing diminished response in Jurkat E6.1 lymphocytes (Fig. 7C). Moreover, TNF-stimulated Jurkat E6.1 cells also showed delayed and reduced IB␣ degradation compared with H33HJ-JA1 cultures (Fig.  7B), consistent with the reported critical role of IKK␤/IKK␥ in TNFinduced Tpl2 activation (18,19).
To explore further the role of Syk in TNFR1 signaling upstream of Tpl2, we performed knock-down experiments in MCF7 breast carcinoma cells, which are known to express Syk (42), using Syk-specific small interfering RNAs (siRNAs). Lysates of MCF7 cells transfected with siRNAs targeting Syk or the unrelated luciferase gene, were analyzed for the expression of Syk, as well as Tpl2 and ␤-actin as controls, by immunoblotting. Transfection of the Syk siRNA induced a significant reduction in the expression of Syk but not Tpl2 or ␤-actin (Fig. 7D). Lysates of parallel cultures, stimulated with TNF-␣ for 15 min or left untreated, were analyzed for the expression of phosphorylated and total ERK by immunoblotting. The results demonstrated significant phosphorylation of ERK in luciferase but not Syk siRNA-transfected cells (Fig. 7E). In addition, although stimulation of luciferase siRNA-transfected cells with TNF-␣ resulted in robust IB␣ degradation, this effect was significantly impaired in Syk siRNA-transfected cultures (Fig. 7E). Analysis of cell lysates for Tpl2 kinase activity using in vitro coupled kinase assays confirmed that Syk plays an important role in the TNFmediated activation of Tpl2 (Fig. 7F). immunoprecipitates (IP) from 2 mg of these lysates were immunoblotted (IB) with HRPconjugated Tpl2 or NFB1 antibodies. Tpl2 and NFB1 expression in 50 g of whole cell lysate (WCL) from unstimulated cultures is also shown. B, piceatannol (Pic) suppresses the TNF-mediated phosphorylation of IB␣. Tpl2 ϩ/ϩ BMDM were pretreated with 30 M piceatannol and then stimulated with TNF-␣ for 10 min or left untreated. Lysates were analyzed for IB␣ and ERK phosphorylation by immunoblot. The levels of total ERK were also evaluated as a loading control. Note that the effect of Pic on IB␣ phosphorylation precedes that on ERK. C, treatment of Tpl2 ϩ/ϩ BMDM with piceatannol suppresses the TNF-induced IKK␤ kinase activity. Cells were pretreated with 30 M piceatannol and then stimulated with TNF-␣ for 5 min or left untreated. Lysates were immunoprecipitated with an anti-IKK␤ mAb and analyzed for catalytic activity by in vitro kinase assays (IVK) using GST-IB␣ as a substrate. The immunoprecipitated IKK␤ was immunoblotted and probed with a polyclonal anti-IKK␤ to confirm that similar levels of the enzyme were analyzed.
The effects of Syk overexpression on TNF-induced Tpl2/MEK/ERK activation were then investigated. To this end, HEK293 cells, which express very low levels of endogenous Syk (Fig. 8), were transiently transfected with HA-ERK1 in the presence or absence of a Myc-tagged Syk expression vector. Cells were then stimulated with TNF-␣ or left untreated, and lysates were examined for expression of Syk and phosphorylated and total HA-ERK1 by immunoblot. Lysates were also immunoprecipitated with anti-Tpl2 and exposed to in vitro kinase assays using GST-MEK as a substrate. The results showed that Syk overexpression significantly enhances the TNF-␣-mediated phospho-FIGURE 6. Syk becomes tyrosine-phosphorylated following TNF stimulation. A and B, TNF-␣ promotes the tyrosine phosphorylation of Syk. Tpl2 ϩ/ϩ BMDM were stimulated with TNF-␣ for various time intervals or left untreated, as indicated. Cell lysates were subjected to immunoblot (I.B.) using the phosphotyrosine mAb 4G10. The blot was then stripped and re-probed with an antibody raised against the C terminus of Syk. The relative levels of Syk phosphorylation (ratio of phosphorylated versus total protein) were quantitated by using the Scion Image processing and analysis software and are expressed as fold increase relative to unstimulated control (A). To confirm that Syk is the tyrosine-phosphorylated protein detected following TNF stimulation, Syk was immunoprecipitated (IP) from untreated and TNF-activated Tpl2 ϩ/ϩ BMDM and immunoblotted with the phosphotyrosine mAb 4G10. The blot was then re-probed with an anti-Syk antibody (B). C, Syk activation following TNF stimulation of Tpl2 ϩ/ϩ BMDM. Tpl2 ϩ/ϩ macrophages were pretreated with Pic or left untreated and then stimulated with 25 ng/ml TNF-␣, as indicated. Syk was immunoprecipitated and examined for auto-phosphorylation by in vitro kinase assays, as described under "Materials and Methods." D, Syk is recruited to the TNF receptor signaling complex following TNF stimulation. Lysates (2.5 mg) from TNF-␣ stimulated Tpl2 ϩ/ϩ BMDM and untreated controls were immunoprecipitated with an anti-TNFR1 antibody coupled to protein-A-Sepharose beads. The immunoprecipitates were then immunoblotted for either Syk or TNFR1. Two additional experiments were performed and gave similar results. rylation of ERK1 and the activation of endogenous Tpl2 (Fig. 8). Taken together, the preceding data demonstrate that Syk plays an important role in the activation of the Tpl2/MEK/ERK pathway in response to TNF-␣.

DISCUSSION
This study dissects the TNF receptor-proximal events that lead to the engagement of the ERK MAPK cascade by TNF-␣ in macrophages. It shows that the stimulation of TNFR1 results in ERK activation via two independent signaling pathways. The first involves the activation of Tpl2 and is responsible for the majority of the TNF-␣-induced MEK/ ERK signals (Fig. 1). The second pathway is Tpl2-independent and mediates the relatively low level MEK and ERK phosphorylation observed in Tpl2 Ϫ/Ϫ BMDM and MEFs.
Mutational analysis of the cytoplasmic tail of TNFR1 has identified a region called the "death domain" as being responsible for ERK signaling (43). This region binds the adaptor proteins TRADD (44) and MADD (45). TRADD acts as a platform for the recruitment of RIP1 and TRAF2, which mediate the activation of NF-B and MAPKs, and of FADD, which mediates caspase activation and apoptosis (46,47). MADD overexpression results in the activation of JNK, p38, and ERK MAPKs (45), but its physiological role in TNF signal transduction is currently unknown.
Previous studies using RIP1 Ϫ/Ϫ cells had shown that RIP1 is required for the TNF-␣-induced activation of NF-B, JNK, p38, and ERK (24,26,48), suggesting that bifurcation of signals originating in TNFR1 must occur downstream of RIP1. TRAF2, which interacts with RIP1, is obligatory for JNK activation and contributes to the activation of NF-B by TNF-␣ (49). Its physiological contribution to TNF-induced ERK signaling is, however, unknown. Data presented here demonstrate that TRAF2 plays an important role in the engagement of ERK in response to TNF stimulation (Fig. 2D). Thus, we have shown that TNF-␣-induced Tpl2 activation and ERK phosphorylation are significantly impaired in TRAF2 Ϫ/Ϫ fibroblasts. Given that Tpl2 co-immunoprecipitates with both RIP1 (Fig. 2, A and B) and TRAF2 (28), we propose that, following TNFR1 stimulation, Tpl2 is recruited to and is activated by the RIP1-TRAF2 signaling complex (see proposed model in Fig. 9).
It is of interest that although TRAF2 and RIP1 are essential for the activation of the Tpl2/MEK/ERK axis by TNFR1, their overexpression is not sufficient to activate ERK. Thus, although overexpressed TRAF2 and RIP1 readily engage JNK, they do not activate Tpl2 and ERK (Fig. 3).
These findings suggest that Tpl2 is activated by TRAF2-and RIP1transduced signals operating in concert with additional converging signals, also induced by TNF-␣. Another molecule that behaves similar to TRAF2 and RIP1 is IKK␤ that plays a critical role in the TNF-␣-mediated activation of both the NF-B (50 -52) and the Tpl2/MEK/ERK pathways (18). Tpl2 activation is severely impaired in IKK␤ Ϫ/Ϫ fibroblasts treated with TNF-␣ (18). However, overexpression of IKK␤ in HEK293 cells failed to induce the phosphorylation of co-expressed ERK1 (data not shown). The preceding data, coupled with the results of the published studies, raised the possibility that in addition to RIP1/ TRAF2/IKK␤, other molecules are required for the activation of Tpl2 in response to TNF stimulation. Here we demonstrate that one of these molecules is the tyrosine kinase Syk.
Tyrosine kinases have been implicated in signal transduction by a plethora of cytokines and growth factors. A recent report has shown that the broad spectrum tyrosine kinase inhibitor herbimycin-A severely impairs the ability of LPS to activate Tpl2 and its downstream target MEK in macrophages (22). Several candidate tyrosine kinases were considered unlikely targets of herbimycin-A in the preceding experiments. Specifically, the Src kinases were unlikely to be responsible for the herbimycin effect, because Src is not expressed in BMDM (53). Moreover, macrophages from triple knock-out mice lacking the Src family kinases Hck, Fgr, and Lyn exhibit normal LPS-induced ERK phosphorylation (53), which is Tpl2-dependent (10). In agreement with these predictions, PP2, an inhibitor of the Src kinase family, did not interfere with activation of ERK by TNF-␣ (Fig. 4A). Other tyrosine kinases, such as Tyk2 and FAK, are also unlikely targets of herbimycin-A as Tyk2 Ϫ/Ϫ and FAK Ϫ/Ϫ cells also exhibit normal ERK signaling in response to LPS and TNF-␣, respectively (54,55). Akt, a downstream target of PI 3-kinase, which has been reported to phosphorylate Tpl2/ Cot at its C terminus (56), is not involved in the activation of Tpl2 in response to TNF-␣, as suggested by the finding that the TNF-induced  We propose that following stimulation with TNF-␣, Syk becomes activated and acts in concert with RIP1 and TRAF2 to activate Tpl2 upstream of MEK and ERK. Syk appears to modulate signaling on the Tpl2/MEK/ERK axis by functioning upstream of IKK␤, which controls the dissociation of Tpl2 from NF-B1, a prerequisite for Tpl2 activation. A role for additional tyrosine kinases in TNF-␣-induced Tpl2/ERK signaling cannot be excluded. Arrows indicate the main ERK pathway. Dotted lines depict pathways that have not been fully characterized yet (see text for details).
activation of ERK in BMDM is not affected by the PI 3-kinase inhibitor LY294002 (Fig. 4A).
In addition to the above kinases, we examined the role of the tyrosine kinase Syk in Tpl2/ERK signaling. This investigation was prompted by a number of published observations. First, Syk is expressed in a plethora of cell types, including monocytes, B and T lymphocytes (57), epithelial cells (41,42,58), and fibroblasts (59). Second, Syk is recruited to the TLR4 signaling complex following LPS stimulation (60) and undergoes tyrosine phosphorylation in LPS-treated neutrophils and macrophages (60,61). Third, Syk has been implicated in the activation of JNK and NF-B in neutrophils and T cells exposed to TNF-␣ (30,62), and its knock-down in epithelial cells affects TNF-induced phenotypic effects, such as IL6 synthesis and ICAM1 expression (58).
Data presented in this report, demonstrate that Syk is indeed involved in the activation of Tpl2. Thus, Syk became tyrosine-phosphorylated following TNF stimulation, and the Syk inhibitor piceatannol significantly reduced the activation of Tpl2 as well as the phosphorylation of MEK and ERK in TNF-␣-stimulated Tpl2 ϩ/ϩ but not Tpl2 Ϫ/Ϫ macrophages (Fig. 4). This finding suggests that Syk has an active role upstream of Tpl2 signal transduction and is not merely a scaffold for components of the TNFR1 pathway. Similarly, we have found that piceatannol suppressed the LPS-mediated activation of the Tpl2/MEK/ ERK pathway in macrophages (data not shown), consistent with its reported ability to confer protection against LPS-induced septic shock in mice (63). Moreover, we have shown that cell lines that either lack or express reduced levels of Syk exhibited diminished activation of Tpl2 and ERK in response to TNF-␣ treatment, whereas the overexpression of Syk augmented TNF-induced Tpl2/ERK signaling (Figs. 7 and 8). More importantly, interference with Syk levels and function by either knock-down of Syk expression or piceatannol treatment hindered the TNF-mediated activation of IKK␤ (Figs. 5 and 7), which is required for the inducible dissociation of Tpl2 from NF-B1 and the subsequent activation of Tpl2 (18,19). These findings suggest that Syk functions upstream of the IKK signaling complex to control the activation of Tpl2 via dissociation from NF-B1.
In summary, the present study dissects a signaling pathway that is triggered by TNF-␣ and results in ERK MAPK activation (Fig. 9). The data show that TNF-␣ activates Tpl2 via signals transduced by RIP1 and TRAF2 and that Tpl2 is required for the activation of the MEK/ERK axis. Genetic and biochemical evidence presented in this study also shows that Tpl2 activation depends on the tyrosine kinase Syk, which is activated following TNF-␣ stimulation. Given the key role of Tpl2 in immunity and inflammation, understanding the mechanisms of its activation may have significant implications for the design of novel therapeutic strategies against a variety of inflammatory syndromes.