1. Biochemistry and Chemical Biology
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Immunoproteasome functions explained by divergence in cleavage specificity and regulation

  1. Michael B Winter
  2. Florencia La Greca
  3. Shirin Arastu-Kapur
  4. Francesco Caiazza
  5. Peter Cimermancic
  6. Tonia J Buchholz
  7. Janet L Anderl
  8. Matthew Ravalin
  9. Markus F Bohn
  10. Andrej Sali
  11. Anthony J O'Donoghue  Is a corresponding author
  12. Charles S Craik  Is a corresponding author
  1. University of California, San Francisco, United States
  2. Inc., an Amgen subsidiary, United States
  3. California Institute for Quantitative Biosciences, University of California, San Francisco, United States
  4. University of California, San Diego, United States
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Cite this article as: eLife 2017;6:e27364 doi: 10.7554/eLife.27364

Abstract

The immunoproteasome (iP) has been proposed to perform specialized roles in MHC class I antigen presentation, cytokine modulation, and T cell differentiation and has emerged as a promising therapeutic target for autoimmune disorders and cancer. However, divergence in function between the iP and the constitutive proteasome (cP) has been unclear. A global peptide library-based screening strategy revealed that the proteasomes have overlapping but distinct substrate specificities. Differing iP specificity alters the quantity of production of certain MHC I epitopes but does not appear to be preferentially suited for antigen presentation. Furthermore, iP specificity was found to have likely arisen through genetic drift from the ancestral cP. Specificity differences were exploited to develop isoform-selective substrates. Cellular profiling using these substrates revealed that divergence in regulation of the iP balances its relative contribution to proteasome capacity in immune cells, resulting in selective recovery from inhibition. These findings have implications for iP-targeted therapeutic development.

https://doi.org/10.7554/eLife.27364.001

Introduction

Mammalian proteasomes are complexes with multiple protease active sites that carry out the regulated degradation of proteins, mediating processes such as the clearance of mutated or misfolded proteins, cell signaling, and antigen presentation (Kisselev et al., 2012; Stadtmueller and Hill, 2011). The 20S proteasome core particle is a barrel-shaped structure composed of four stacked heptameric rings (Tomko and Hochstrasser, 2013). The two outer rings, containing the α-subunits, act as binding sites for regulatory complexes (e.g., 19S, 11S, and PA200 families) that stimulate its peptidase activity and modulate access of cytosolic proteins into the proteasome inner chamber (Stadtmueller and Hill, 2011; Tomko and Hochstrasser, 2013). The two inner rings contain the β-subunits, three of which (β1, β2, and β5) have an active site containing a catalytic threonine residue (Tomko and Hochstrasser, 2013). These catalytic subunits have been traditionally referred to as "caspase-,” "trypsin-,” and "chymotrypsin-like" (CT-L), respectively, based on their general substrate specificity preferences (Kisselev et al., 2012).

In addition to the constitutive proteasome (cP), which is expressed in all cell types, an immunoproteasome (iP) isoform is predominantly expressed in cells of hematopoietic origin (McCarthy and Weinberg, 2015). The overall architecture of the iP and cP core particles is identical; however, the iP contains different catalytic subunits – referred to as LMP2 (iβ1), MECL-1 (iβ2), and LMP7 (iβ5) – that share respectively 62%, 59%, and 71% sequence identity with their cP counterparts (Ferrington and Gregerson, 2012). Expression of all immuno catalytic subunits, along with the 11S-type activator PA28, is upregulated by pro-inflammatory signals, such as IFN-γ, during the immune response. Mapping of the LMP2 (PSMB9) and LMP7 (PSMB8) genes to the major histocompatibility complex (MHC) locus combined with interferon-induced activation first led to the proposal that the iP carries out a specialized role in generating peptides for MHC class I antigen presentation (Ferrington and Gregerson, 2012). Furthermore, early biochemical evidence suggested that the iP catalytic subunits show an enhanced ability to generate peptides with specific C-terminal residues that may better match the terminal (anchor) amino acid residue preferences of MHC I molecules (Gaczynska et al., 1993; Driscoll et al., 1993; Gaczynska et al., 1994; Cardozo and Kohanski, 1998; Toes et al., 2001). More recently, it was found that mice completely lacking in iP catalytic subunits display an antigen repertoire that differed from wild-type mice and resulted in transplant rejection (Kincaid et al., 2011). These findings have suggested a possible role for iP cleavage specificity in shaping the immune response.

Inhibition of proteasome CT-L activity was initially pursued as a therapeutic strategy for the treatment of cancers with highly proliferative and proteasome-dependent cells; however, current FDA-approved proteasome inhibitors lack selectivity between the cP and iP (Kisselev et al., 2012; Adams, 2004). Bortezomib (Velcade), a reversible boronic acid-based inhibitor, provided clinical validation of proteasome inhibition in multiple myeloma (Richardson et al., 2003). The second-generation proteasome inhibitor, carfilzomib (CFZ; Kyprolis or PR-171), which also targets the CT-L subunits, uses an irreversible epoxyketone warhead and shows reduced off-target inhibition, while circumventing resistance against bortezomib (Arastu-Kapur et al., 2011; Siegel et al., 2012). Recently, considerable effort has been dedicated toward the development of iP-selective inhibitors (Johnson et al., 2017; Dubiella et al., 2015; Sosič et al., 2016; Muchamuel et al., 2009) in the interest of selectively targeting iP-dominant cells for the treatment of autoimmune disorders and certain cancers. In particular, the epoxyketone inhibitor, ONX 0914 (PR-957), which preferentially inhibits the LMP7 subunit, was able to block cytokine production and attenuate disease progression in a rheumatoid arthritis mouse model at a significantly lower dose than bortezomib or CFZ (Muchamuel et al., 2009). In addition, ONX 0914 has showed promise for the treatment of lupus and multiple sclerosis (Ichikawa et al., 2012; Basler et al., 2014) and for inflammation-associated colorectal cancer (Koerner et al., 2017; Vachharajani et al., 2017).

Although the iP has emerged as a promising therapeutic target, it is not well understood how its functions diverge from those of the cP, which is often found within the same cell. Here, we applied a recently-developed peptide library-based profiling strategy (O'Donoghue et al., 2012; O'Donoghue et al., 2015) to define the substrate specificities of each proteasome in a global and an unbiased manner. This analysis revealed that the iP and cP have overlapping substrate specificities, with some significant differences. These differences were exploited to rationally design LMP7- and β5-selective fluorogenic peptide substrates for the cellular profiling of each proteasome. The global substrate specificities of the iP and cP were then compared to MHC I peptides and further queried experimentally using a synthetic peptide library designed from amino acid sequences flanking MHC I peptide-processing sites. This analysis suggested that the specificity of the iP may alter the extent of display of certain MHC I peptides but does not appear to be preferentially suited for MHC I epitope generation. Furthermore, an evolutionary analysis suggested that divergent iP substrate specificity is due to genetic drift from the cP. Finally, the iP- and cP-selective fluorogenic substrates were used to probe the contribution of the iP to ubiquitin-proteasome system (UPS) capacity in immune cells and assess proteasome recovery (or ‘bounce-back’) (Radhakrishnan et al., 2010; Sha and Goldberg, 2014; Radhakrishnan et al., 2014; Weyburne et al., 2017) from iP-selective inhibitor treatment. Our results suggest that divergence in iP substrate specificity primarily impacts the content of the immune repetoire by altering the quantity of production of certain epitopes and that divergence in iP regulation balances the contribution of each proteasome to the total UPS capacity.

Results

Global substrate specificity screen of the iP and cP

To provide biochemical insight into the substrate specificities of the iP and cP, we performed a global substrate screening approach referred to as Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS) (Figure 1) (O'Donoghue et al., 2012; O'Donoghue et al., 2015). The MSP-MS assay uses an equimolar mixture of 228 rationally-designed, 14-mer peptide substrates and provides an unbiased assessment of protease substrate specificity. The iP or cP was added to the peptide library and peptide cleavage products were identified after 60, 120, 240, and 480 min of incubation through liquid chromatography-tandem mass spectrometry (LC-MS/MS). Only cleavage sites found in two biological replicates of each proteasome are reported. The proteasomes were found to have broad substrate specificity, being capable of hydrolyzing 391 (iP) and 330 (cP) different peptide bonds after 480 min of incubation; this corresponds to 13.2% and 11.1% of the total cleavage sites in the library for the iP and cP, respectively. Saturation of new cleavage-site usage was evident by the 480 min assay time point (Figure 1—figure supplement 1), reflecting depletion of the most favored cleavage sites in the library, and the ability of the MSP-MS assay to readily detect the most dominant cleavage events, as described in Figure 1—figure supplement 2.

Figure 1 with 4 supplements see all
Global substrate specificity profiling of the iP and cP with Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS) reveals shared and differential substrate specificity features.

(A) iceLogo representations of iP and cP substrate specificity (P4–P4ʹ) at the 480 min assay time point (p≤0.05 for non-grayed residues (Colaert et al., 2009); ‘n’ is norleucine). (B) Quantification of the total shared and non-overlapping iP- and cP-derived cleavages in the peptide library at the 480 min assay time point. Venn diagrams for additional assay time points are provided in Figure 1—figure supplement 1, demonstrating a time-dependent increase in cleavage overlap. (C) Heat map representation of iP and cP specificity differences using Z-scores (Colaert et al., 2009) calculated for the P4-P4ʹ positions. Differences in P1 specificity are highlighted. Heat maps for additional time points are provided in Figure 1—figure supplement 3. MSP-MS revealed that the iP has an increased preference for certain bulky, hydrophobic amino acid residues at the P1 position, whereas the cP has an increased preference for smaller and polar amino acid residues at the P1 position. A qualitative comparison of the P1 specificity differences identified using the MSP-MS library with those reported in Toes et al., 2001 and Mishto et al., 2014 is provided in Figure 1—figure supplement 4. Two biological replicates were assayed for each proteasome and only overlapping cleavages between replicates are reported. An analysis of biological (Figure 1—figure supplement 1) and technical (Supplementary file 1) reproducibility is provided.

https://doi.org/10.7554/eLife.27364.002

Statistical analysis of both cleaved and uncleaved positions in the peptide library was performed to represent the fold enrichment and de-enrichment of amino acid residue types at the four sub-sites on both sides of the scissile bond (Colaert et al., 2009). This analysis revealed that the iP and cP have similar overall substrate specificity motifs (Figure 1A). Specificity is dominated by non-prime-side residues, in particular the P1 position, with a shared enrichment of extended hydrophobic residues at P1, P3 and P4 as well as lysine at P2. The preferred specificity for hydrophobic residues and arginine in the P1 position suggest that the CT-L subunits (β5 and LMP7) and trypsin-like subunits (β2 and MECL-1) cleave many more peptide bonds than the β1 and LMP2 subunits of the cP and iP, respectively. This is particularly clear from the lack of aspartic acid enrichment in the P1 position.

Comparison of individual peptide cleavage events within the MSP-MS library demonstrated that the iP and cP also have differential substrate specificity with 32.1% and 19.5% non-overlapping cleavage sites at 480 min for the iP and cP, respectively (Figure 1B, Figure 1—figure supplement 1, and Supplementary file 1 for additional time points and reproducibility). To quantify global differences in substrate specificity, a difference map was generated using Z-scores derived from residue preferences at each sub-site (Figure 1C and Figure 1—figure supplement 3 for additional time points) (Colaert et al., 2009). This analysis revealed significant physicochemical differences in P1 specificity. The iP displayed an increased preference for cleavage following bulky, hydrophobic amino acid residues such as tryptophan. In contrast, the cP displayed an increased preference for cleavage after basic residues such as arginine in addition to polar and smaller amino acid residues such as serine, threonine, glutamine, glycine, and alanine (Figure 1—figure supplement 3 and Figure 1—figure supplement 4).

Rational design of fluorogenic substrates with LMP7 and β5 selectivity

Using the specificity differences identified in the peptide degradation assay, we sought to develop chemical tools (de Bruin et al., 2016; Dubiella et al., 2016) that are substrate-based for readily monitoring LMP7 and β5 activities in cellular lysate conditions because these subunits represent a major activity of both proteasomes. To do this, we identified individual peptides in the MSP-MS library that displayed selectivity for the iP or cP and reflected hydrophobic specificity at the P1 position (Figure 2A). For LMP7, an internally-quenched (IQ) fluorogenic substrate was synthesized that corresponded to the P5 to P2ʹ residues surrounding a Trp-Pro bond in an individual peptide. This substrate was designed to evaluate an LMP7-selective probe containing prime-side residues but proved to be non-selective for the iP when in IQ substrate format (Figure 2B). However, a shorter tetrapeptide sequence (P4-P1) bearing a 7-amino-4-carbamoylmethylcoumarin (ACC) fluorophore at the P1ʹ position, EWHW-ACC, afforded 4.5-fold iP selectivity at 10 μM substrate concentration (Figure 2B). An additional tetrapeptide, PDFY-ACC, which shares no common amino acid residues with EWHW-ACC, was also synthesized. The PDFY-ACC substrate was preferentially cleaved by the iP, albeit with reduced activity and selectivity (2.2-fold) (Figure 2B). Taken together, these initial studies indicated that short peptide sequences identified in the MSP-MS assay could be optimized to develop substrates with improved iP selectivity.

Figure 2 with 4 supplements see all
Rational optimization of tetrapeptide ACC substrates with iP and cP selectivity.

(A) Example 14-mer peptides from the iP and cP MSP-MS assays associated with Figure 1 illustrating cleavages that were used as a template for rational fluorogenic substrate design. All cleavages common between two biological replicates of each proteasome are reported with the time point of first appearance noted for each replicate. (B) Selectivity of parental IQ and tetrapeptide ACC fluorogenic substrates derived from an iP-favored cleavage (Figure 2A, top) in the MSP-MS library. Subsequent rational substrate optimization is shown. (C) Michaelis-Menten characterization and chemical structure of the lead iP substrate, EWFW-ACC. (D) Optimization of an ACC substrate with cP selectivity using a similar approach. Shortening the peptide sequence to a tripeptide and addition of an N-terminal capping group were found to be important for improving substrate selectivity and maintaining specific activity. (E) Michaelis-Menten characterization and chemical structure of the lead cP substrate iso-VQA-ACC. For all fluorogenic substrate assays, mean activity is reported with error bars representing the standard deviation from n = 3 replicates.

https://doi.org/10.7554/eLife.27364.008

To identify candidate residue positions for rational sequence optimization, both proteasomes were assayed using Positional Scanning-Synthetic Combinatorial Libraries (PS-SCLs) to further assess non-prime-side specificity preferences at the P4, P3, and P2 positions (Figure 2—figure supplement 1) (Harris et al., 2000). The PS-SCLs are divided into pooled sub-libraries of tetrapeptides (160,000 total) containing a fixed amino acid residue at a given position, an isokinetic mixture of 20 amino acid residues at each remaining site, and an ACC fluorophore at the P1ʹ position. Cleavage sensitivity to CFZ pretreatment was used to probe LMP7 or β5 specificity at each site (Figure 2—figure supplement 2). To improve the iP selectivity of the EWHW-ACC parent substrate, select amino acid residues were integrated within the sequence (Figure 2B and Figure 2—figure supplement 3) based on amino acid preferences identified using both profiling approaches. Among the residues queried, a P2 phenylalanine substitution (EWFW-ACC) resulted in the most dramatic improvement in both specific activity and iP selectivity. Supporting Michaelis-Menten analysis further demonstrated that EWFW-ACC had 7-fold improvement in Km for the iP with 16-fold selectivity at Vmax compared to the 6-fold selectivity of the parent substrate (Figure 2C and Supplementary file 2).

To develop a fluorogenic substrate with β5 selectivity, an MSP-MS peptide cleavage with cP selectivity (Figure 2A) was used to synthesize an initial tetrapeptide ACC substrate, SHRn-ACC (Figure 2D). However, this substrate had only modest cP selectivity (Figure 2D). An existing in-house substrate (YVQA-ACC), bearing P1 alanine as well as the cP-favored P2 glutamine was evaluated. This substrate was found to afford similar selectivity (1.8-fold) but higher cP activity (Figure 2D). Modifications to the YVQA-ACC sequence with cP-favored residues, such as P1 serine and glycine, did not offer improvements in selectivity. Therefore we evaluated the effect of modifying the peptide length. A tripeptide bearing the sequence VQA-ACC was found to have dramatically reduced activity but increased cP selectivity (3.0- versus 1.8-fold selectivity at 10 μM substrate concentration) (Figure 2D). Next, N-terminal capping groups were screened and found to greatly improve activity of the tripeptide substrate. The 5-methylisoxazolyl (iso) group utilized in the β5-favored inhibitor, PR-825, yielded both the highest cP specific activity and selectivity (4.4-fold), suggesting that the iso-VQA-ACC probe was a promising lead candidate (Figure 2D and Figure 2E). Selectivity of the EWFW-ACC and iso-VQA-ACC substrates was retained under varied proteasome activation conditions (Figure 2—figure supplement 4).

Fluorogenic substrates enable cellular activity profiling of LMP7 and β5

To confirm the respective selectivity of the EWFW-ACC and iso-VQA-ACC probes for the iP and cP under more complex assay conditions, activity assays were performed using defined mixtures of each proteasome (Figure 3A). Both probes retained selectivity for their target proteasomes under conditions of iP and cP competition, as evidenced by direct correlation of probe activity with the level of the respective target proteasome. In contrast, the commercial β5/LMP7 substrate, LLVY-AMC, was unable to distinguish between the two proteasomes when assayed at a comparable substrate concentration (Figure 3A and Figure 3—figure supplement 1). Probe efficacy was further evaluated in clinically relevant cell lysates from whole blood, a T-lymphoblast cell line (MOLT-4), and peripheral blood mononuclear cells (PBMCs), which contain varied proteasome ratios (Figure 3A). Relative substrate cleavage rates correlated with the ratios of active LMP7 to β5 in each cell lysate (1:99, 43:57, and 100:0, respectively), as determined using the ProCISE assay, which relies on direct active site labeling and ELISA measurement (Figure 3—figure supplement 2) (Parlati et al., 2009). To confirm iso-VQA-ACC and EWFW-ACC selectivity for the β5 and LMP7 subunits, the lysates underwent pretreatment with 100 nM CFZ or the LMP7- and β5-selective inhibitors, ONX 0914 and PR-825, respectively (Muchamuel et al., 2009). Substrate cleavage in the cell lysates correlated with the expected pattern of inhibition (Figure 3B); further dose-response curves using the MOLT-4 lysate (Figure 3C) yielded IC50 values that matched those obtained from the ProCISE assay, demonstrating the isoform selectivity of the substrates even at the approximately 50:50 proteasome level (Supplementary file 3). In contrast, a commercial substrate (Ac-WLA-AMC) commonly used to measure β5 activity was unable to specifically detect proteasome activity using this lysate condition (Figure 3—figure supplement 3). Together, these activity-profiling results suggest that the fluorogenic substrates can selectively monitor LMP7 and β5 activity in lysates and that similar CT-L substrate specificity determinants operate under cellular conditions.

Figure 3 with 3 supplements see all
Optimal fluorogenic substrates enable the selective monitoring of LMP7 and β5 activity in cell lysates containing varied proteasome ratios.

(A) Demonstration of EWFW-ACC (10 μM) and iso-VQA-ACC (30 μM) selectivity for the iP and cP, respectively, compared to the universal substrate LLVY-AMC (30 μM) using mixed ratios of purified proteasomes. A comparison is provided of EWFW-ACC and iso-VQA-ACC specificity in whole blood, MOLT-4, and PBMC lysates. (B) Pretreatment of the lysates with 100 nM CFZ, an LMP7-favored inhibitor (ONX 0914), or a β5-favored inhibitor (PR-825) demonstrates the ability of the substrates to distinguish their target proteasomes under lysate conditions. (C) IC50 determination for CFZ, ONX 0914, and PR-825 in the mixed LMP7/β5 MOLT-4 lysate using LLVY-AMC and the selective substrates. For all assays, mean activity is reported with error bars representing the standard deviation from n = 3 replicates.

https://doi.org/10.7554/eLife.27364.013

Substrate specificity of the iP primarily alters MHC I peptide cleavage efficiency

Our global assessment of iP and cP peptide degradation patterns revealed that these enzymes have similar substrate specificities, with some clear differences. To expand the scope of our analysis, we sought to address the extent to which the substrate specificities of the iP and cP shape the repertoire of peptides displayed during MHC class I antigen presentation. Using the substrate specificity profiles from the MSP-MS assay, we initially applied a bioinformatic approach to score MHC I peptides based on their relative propensity for cleavage by either proteasome (Figure 4—figure supplement 1). Peptide scoring was performed using a recently reported large proteomic dataset of MHC I peptides (n = 22,598) that were displayed by allelic-diverse MHC I complexes in multiple human cell lines (Bassani-Sternberg et al., 2015). In this dataset, the most frequently occurring C-terminal amino acid residues were the long-chain residues leucine (27.6%), lysine (19.1%), and tyrosine (10.8%). In our specificity differentiation profiles (Figure 1C and Figure 1—figure supplement 3), the iP and cP had an overall similar preference for cleavage on the C-terminal side (P1 position) of these residues, particularly lysine, which indicates that many MHC I peptides have a similar potential of being generated by either proteasome (Figure 4—figure supplement 1). Peptides with C-terminal tryptophan are much more likely to be generated by the iP relative to the cP but were observed in only 0.30% of MHC I peptides. Similarly, peptides with smaller and polar C-terminal residues are more likely to be generated by the cP and were also less frequently observed (e.g., 6.0% for alanine and less than 0.4% for serine, threonine, and other cP-favored amino acids). Notably, comparison of MHC I C-terminal amino acid residue distribution to the human proteome revealed de-enrichment of these preferential P1 residues (Figure 4—figure supplement 1), suggesting that their propensity for display by MHC I molecules might be reduced compared to residues that are similarly preferred by both proteasomes.

To provide an experimental measure of iP and cP cleavage selectivity for MHC I peptides, we constructed a synthetic peptide library consisting of the 7 amino acid residues flanking sites of MHC I processing, using sequences selected at random from the proteomic data set. The peptides in the library were pooled at equimolar concentration and incubated with the iP or cP. Peptide cleavage products were identified over time using LC-MS/MS, and label-free quantitation was used to calculate relative rates of peptide hydrolysis (between positions 7 and 8 at the MHC I site). In agreement with our bioinformatic approach, the proteasomes hydrolyzed most peptides at a similar rate (≤2 fold difference) (Figure 4A). However, several peptides were clearly favored by either the cP or iP with up to 12-fold and 15-fold selectivity, respectively. Among the majority of cleavages with P1 specificity for hydrophobic residues, the sequences HTQVIEL^ERKFSHQ and VSEGTHF^LETIETP displayed the greatest cP and iP selectivity, respectively. As expected, the peptide substrate containing a P1 tryptophan, KNTFPKW^KPGSLAS, was preferentially cleaved by the iP (Figure 4B). Taken together, our bioinformatic and substrate profiling approaches revealed that the majority of MHC I peptides have a similar potential for being generated by either proteasome. Differing iP specificity appears to impact the content of the MHC I repertoire primarily by altering the quantity of production of certain epitopes. We note that this outcome appears to be only partly explained by the differential preference of the iP for certain P1 residues.

Figure 4 with 2 supplements see all
Differential substrate specificity of the iP alters MHC I peptide cleavage and is likely due to neutral evolution from the ancestral cP.

(A) Label-free quantitation of relative iP and cP cleavage rates against a library of synthetic peptides derived from sequences flanking sites of MHC I peptide processing (Bassani-Sternberg et al., 2015). Residues corresponding to the C-terminal portion of a given MHC I peptide are at positions 1–7 in the peptide library, whereas residues corresponding to the subsequent parent protein sequence are at positions 8–14. Average relative cleavage rates (log2) are provided for iP and cP substrates between positions 7 and 8 (P1/P1ʹ) for all peptides in the library that underwent cleavage at this site and for which quantification in all replicates was possible (n = 4). Two-fold differences in relative cleavage rate (log2 = 1) are indicated with a dashed line. Non-grayed bars represent statistically significant (q < 0.05) differences in selectivity as determined using a Student’s t-test (see Statistical methods). (B) Example kinetic traces from the MHC I peptide library time course showing cleavages following hydrophobic residues that have either high selectivity or no significant selectivity for the iP. Mean peak areas are reported with error bars representing the standard deviation (n = 4). (C) Evolutionary selection of residues in the β5 and LMP7 subunits across species that contain both proteasome isoforms. The β5 subunit has undergone more significant non-neutral evolution (residues are colored in orange) compared to the LMP7 subunit. Differences in evolutionary selection may account for the divergence in LMP7 and β5 cleavage specificity. Sequence alignments are provided in Figure 4—figure supplement 2.

https://doi.org/10.7554/eLife.27364.017

Divergence of LMP7 specificity likely occurred by neutral evolution

Because of the lack of preferential correlation of iP specificity with MHC I C-terminal residue preferences, we sought to provide an evolutionary basis for the divergence in iP and cP cleavage specificities. Notably, the 14 subunits of the cP are more ancient proteins than those of the iP; the catalytic iP subunits first emerged through gene duplication in jawed vertebrates along with other components of the immune system (Kesmir et al., 2003). To characterize potential differences in evolutionary selection of the iP and cP, we compared LMP7 and β5 sequence conservation across organisms that contain both proteasomes (Sutoh et al., 2012). We then estimated the balance between neutral mutations, purifying selection, and positive selection through comparison of rates of nonsynonymous (amino acid residue-changing) and synonymous (amino acid residue-preserving) nucleotide substitution (Massingham and Goldman, 2005). This analysis revealed that residues at LMP7 subunit interfaces and within the active site are highly varied among species and have undergone genetic drift. In contrast, the corresponding residues in the β5 subunit are highly conserved and have evolved through purifying selection (Figure 4C). These neutrally evolved residues in human LMP7 include Val31 in the S1 pocket, Cys48 (Gly in β5) in the S2 pocket, and Ser27 and Ala28 (Ala and Ser, respectively, in β5) in the S3 pocket and suggest lack of evolutionary pressure on iP specificity (Figure 4—figure supplement 2). Thus, neutral mutations may have helped diversify iP specificity in the presence of the rapidly evolving proteomes of diverse pathogens while preserving essential core recognition of host cell proteins.

iP activity contributes to ups capacity and undergoes selective recovery from inhibition.

The importance of the iP in antigen presentation has been well appreciated; however, the contribution of the iP to cellular proteostasis and its regulation under basal (or non-immunostimulatory) conditions is not well understood. To confirm that iP activity has an impact on UPS capacity in immune cells under basal conditions, we used the selective substrates to identify a B-lymphoblast cell line (SUP-B15) (Bassani-Sternberg et al., 2015) with predominantly LMP7 activity (80:20). A pulse-treatment strategy was employed with ONX 0914 and PR-825 to evaluate the relative contribution of each active site to the turnover of ubiquitinated substrates under conditions with optimal inhibitor selectivity (Muchamuel et al., 2009). SUP-B15 cells were pulse-treated for one hour, and inhibitor selectivity was confirmed in cytosolic lysates up to three hours post-treatment through monitoring selective reduction of EWFW-ACC and iso-VQA-ACC cleavage (Figure 5A). Immunoblotting demonstrated global accumulation of ubiquitinated protein upon inhibition of LMP7 activity with ONX 0914, whereas no significant change in ubiquitination was observed upon inhibition of β5 activity with PR-825 (Figure 5A and Figure 5—figure supplement 1). This finding suggests that the iP makes a significant contribution to proteasome capacity in agreement with Seifert et al., 2010 and that in SUP-B15 cells this contribution is correlated with the higher relative LMP7 activity level.

Figure 5 with 3 supplements see all
iP activity makes a significant contribution to UPS capacity and undergoes selective and coordinated recovery from inhibition.

(A) Ubiquitin western blot and matched activity assay for the SUP-B15 cell line (with approximately 80:20 LMP7: β5 activity) showing a substantial increase in global ubiquitination levels upon one-hour pulse treatment with ONX 0914. A significant increase in ubiquitination was not observed with PR-825 treatment, suggesting that LMP7 is a more dominant contributor to UPS capacity in this cell line in accordance with the proportionally higher LMP7 activity level. Selective recovery of LMP7 activity over 24 hr in the (B) SUP-B15 and MOLT-4 cell lines and in (C) primary PBMCs from a healthy donor (see also Figure 5—figure supplement 2) upon one-hour pulse treatment with ONX 0914. The SUP-B15 and MOLT-4 lower panels show the fold change in LMP7 and β5 activity levels normalized to the one-hour time point. For all activity assays, mean activity is reported with error bars representing the standard deviation from n = 3–6 replicates. (D) Corresponding qRT-PCR analysis of PSMB8 (LMP7) and PSMB5 (β5) mRNA dynamics in the cell lines and PBMCs following ONX 0914 treatment. Mean expression levels are reported with normalization to GAPDH. Statistically significant differences are indicated (*p≤0.05) as determined using a Student’s t-test with error bars representing the SEM from n = 3 replicates. (E) Corresponding western blots demonstrating accumulation of processed Nrf1 (p110) in RIPA lysates from the cell lines and PBMCs following ONX 0914 treatment. Full-length (FL) Nrf1 was observed in the PBMC lysates. .

https://doi.org/10.7554/eLife.27364.021

Because iP activity significantly contributes to basal UPS capacity, we next assessed whether immune cells upregulate proteasome activity as a recovery response to selective and irreversible LMP7 inhibition. The SUP-B15 cell line was pulse-treated with ONX 0914 for one hour, and LMP7 and β5 activities were followed over an extended 24 hr time course. We observed that irreversible LMP7 inhibition in the SUP-B15 cell line was associated with a rapid recovery (or ‘bounce-back’) of LMP7 activity without an appreciable compensatory increase in the basal β5 activity level (Figure 5B), suggesting that iP activity is critical to proteasome capacity in this cell line and that cP activity may be differentially regulated. For comparison, we also subjected the MOLT-4 cell line, which has an approximately 50:50 ratio of LMP7 to β5 activity (Figure 3), to treatment with ONX 0914. Similar recovery of LMP7 activity following ONX 0914 inhibition was also observed in this cell line (Figure 5B) and confirmed in primary human PBMCs from healthy donors (Figure 5C and Figure 5—figure supplement 2). To establish whether iP recovery is associated with transcriptional upregulation of PSMB8 (LMP7), qRT-PCR was performed and revealed increased PSMB8 mRNA levels in the cell lines and the PBMCs with kinetics that correlated with their relative rates of recovery in activity (Figure 5D). In particular, the SUP-B15 cell line displayed a rapid spike in PSMB8 levels before subsequent reduction, presumably due to an elevated rate of translation or PSMB8 degradation. Immunoblotting was performed and indicated a correlated induction of LMP7 on the protein level in both of the cell lines and in the PBMCs (Figure 5—figure supplement 3).

Notably, in the absence of an appreciable change in β5 activity, we also observed a compensatory increase in PSMB5 mRNA and β5 protein levels (Figure 5D and Figure 5—figure supplement 3). Inhibition of the cP is well known to induce expression of new cP subunits through the transcription factor Nrf1 upon its proteolytic cleavage and release from the endoplasmic reticulum (ER) membrane as a response to proteasome-induced stress (Radhakrishnan et al., 2010; Sha and Goldberg, 2014; Radhakrishnan et al., 2014; Weyburne et al., 2017). Here, an increase in processed Nrf1 was observed following selective iP inhibition (Figure 5E) that correlated with the production of PSMB5; however, this production was decoupled from an associated change in total β5 activity, indicating a cellular mechanism for maintenance of homeostatic iP and cP activity levels. Together, our results clearly highlight the contribution of the iP to UPS capacity and suggest that immune cells counter a loss in iP load through selective recovery of iP activity, balancing the relative capacities of both proteasomes.

Discussion

The iP has emerged as a promising therapeutic target for the treatment of autoimmune disorders and cancer; however, it is not well understood how the substrate specificities of the iP and cP diverge. Our global and unbiased peptide library-based strategy (MSP-MS) revealed that the iP and cP have overall similar substrate specificities but that certain cleavage preferences exist for each proteasome. The iP displays a particularly increased preference for cleavage following certain bulky hydrophobic amino acid residues such as tryptophan, whereas the cP displays a greater preference for cleavage following smaller and polar amino acid residues. Indeed, supporting crystallographic evidence suggests that LMP7 has a larger S1 pocket than β5 due to a Met45 conformation that allows for greater access to the binding pocket (Huber et al., 2012). Differences may exist in profiling peptide versus protein-based substrates (as well as between biochemical and cellular contexts); however, our peptide library-based approach has a key advantage of affording chemically defined substrates with uniform amino acid distribution. The differences in P1 specificity discovered combined with additional non-prime-side specificity determinants were exploited to develop LMP7- and β5-selective fluorogenic substrates for monitoring the activity of each proteasome under cellular conditions. Compared to activity-based probes, fluorogenic substrates have the advantage of enzymatic signal amplification and enabling a continuous assay readout. In contrast, activity-based probes afford direct subunit labeling for downstream biochemical or cellular applications and are a more direct template for inhibitor development. We envision that the global substrate specificity features identified in this study will aid in next-generation isoform-selective probe and inhibitor design and improve the prediction of endogenous cleavage-site preferences.

Degradation of protein substrates by the proteasome generates the pool of peptides made available for display to cytotoxic CD8+ T cells during the MHC I antigen presentation pathway. Proteasomal cleavage preferences are reflected in the C-terminal specificity of MHC I peptides, although additional peptide selection steps further shape the MHC I peptide repertoire, including trafficking into the ER through TAP (transporter associated with antigen processing), binding to allelic-diverse MHC I molecules, and N-terminal trimming by ER-resident aminopeptidases (Rock et al., 2004). Initial biochemical studies following the discovery of the iP subunits led to the long-held suggestion that the specificity of the iP is better suited for the generation of peptides for display by MHC I molecules. However, these studies relied on querying limited sets of peptide substrates and inhibitors or on the degradation of model protein substrates. They provided, at times, conflicting evidence that the iP has an increased preference for cleavage following certain basic (arginine), aromatic (phenylalanine and tyrosine), or branched chain amino acids (leucine, valine, and isoleucine) (Gaczynska et al., 1993; Driscoll et al., 1993; Gaczynska et al., 1994; Cardozo and Kohanski, 1998; Toes et al., 2001; Boes et al., 1994; Eleuteri et al., 1997). Furthermore, advances in mass spectrometry have only recently made deep coverage of the MHC I peptidome feasible.

To assess the relative impact of iP specificity on the MHC I peptide repertoire, we compared the cP and iP MSP-MS specificity profiles to a large proteomic data set of MHC I-bound peptides. We further queried iP and cP cleavage preferences using a synthetic peptide library that mimics the protein sequences from which these MHC I peptides are derived. This analysis suggested that the majority of MHC I peptides have a similar potential to be generated by either the iP or cP (within a 2-fold difference in cleavage rate). We also show that preferred substrates exist for each proteasome isoform; however, iP specificity differences may primarily alter the extent of display of these epitopes. This appears to only partially result from the increased preference of the iP for specific P1 residues. For example, tryptophan was found to be the most iP-selective P1 amino acid residue but de-enriched at the C-terminal position of displayed MHC I peptides compared to its natural abundance in the human proteome.

Recent evidence suggests that the iP and cP have comparable protein-level selectivity because they bind ubiquitin conjugates similarly and degrade ubiquitinated proteins at similar rates (Nathan et al., 2013). In the absence of differences in upstream protein-level selectivity, divergence in iP and cP cleavage preference likely shapes the amount of certain epitopes available for antigen presentation, in combination with basal or conditional (e.g., interferon-induced) differences in proteome composition and the relative activity levels of each proteasome in a given cell. The significant overlap in iP and cP cleavage specificity reported here is consistent with the immune repertoire identified from the splenocytes of iP knockout mice. This repertoire differed from that of wild-type mice by only 50 percent, and furthermore, only certain viral epitopes exhibited an appreciable reduction in display during viral infection in this model (Kincaid et al., 2011). These findings have supported the suggestion that the ‘quantity’ of substrate cleavage, as opposed to strong ‘qualitative’ differences in specificity, (Mishto et al., 2014) impacts the contribution of each proteasome to the MHC I peptide content.

In addition to differential production of certain peptides for antigen presentation, we have shown that iP activity contributes to basal UPS capacity and undergoes a selective recovery response to counter a critical loss in protein load. Irreversible inhibition of LMP7 in immune cells results in selective recovery of LMP7 activity, which is correlated with transcriptional up-regulation of PSMB8. However, in immune cells with predominant iP activity, inhibition of LMP7 results in clear compensatory induction of PSMB5 in the absence of an appreciable change in β5 activity, suggesting that regulation of cP stability, assembly, and/or activation ultimately serves to maintain homeostatic iP and cP activity levels. The transcription factor Nrf1 is well known to mediate production of new cP subunits as a stress recovery response to cP inhibition (Radhakrishnan et al., 2010; Sha and Goldberg, 2014; Radhakrishnan et al., 2014; Weyburne et al., 2017). In our study, Nrf1 activation is correlated with production of PSMB5 following inhibition of the iP. Recovery of the iP under basal conditions appears to occur through a distinct (Nrf1-independent) mechanism; however, basal iP and cP expression are clearly coupled, as an imbalance in iP capacity results in induction of subunits from both proteasomes.

Gene duplication in jawed vertebrates resulted in the emergence of the iP. We have shown that the iP and cP have overlapping substrate specificities as well as distinct cleavage preferences. In addition, both proteasomes are controlled through distinct yet interconnected mechanisms of regulation. Divergence in regulation balances the relative contribution of each proteasome to basal cellular capacity and in addition, enables induction of the iP during an immune response. Thus, relative cellular capacity and differences in cleavage efficiency for certain peptides likely contribute to iP-specialized roles in signaling and epitope presentation.

Materials and methods

Biological reagents

Purified human immunoproteasome core particle (i20S) (cat. E-370), constitutive proteasome core particle (c20S) (cat. E-360), and PA28α (cat. E-380) were purchased from Boston Biochem (Cambridge, MA). Proteasome subunit stoichiometry was assessed as described in the ProCISE section below. The following antibodies were purchased from Cell Signaling Technology (Danvers, MA): GAPDH (D16H11) XP rabbit mAb (cat. 5174), ubiquitin (P4D1) mouse mAb (cat. 3936), PSMB8/LMP7 (1A5) mouse mAb (cat. 13726), and PSMB5 (D1H6B) rabbit mAb (cat. 12919). The following HRP-conjugated secondary antibodies were used as appropriate: goat anti-mouse IgG (cat. 172–1011, Bio-Rad, Hercules, CA) and goat anti-rabbit IgG (cat. ab97051, Abcam, Cambridge, MA). TaqMan gene expression assays were purchased from Life Technologies (Waltham, MA) for PSMB5 (GeneID: 5693, Assay ID: Hs00605652_m1), PSMB8 (GeneID: 5696, Assay ID: Hs00544758_m1), and GAPDH (GeneID: 2597, Assay ID: Hs02786624_g1); all TaqMan assays contained MGB probes with a FAM reporter dye.

Cell culture

The following human cancer cell lines were purchased from American Type Culture Collection (ATCC, Manassas, VA) – SUP-B15 (cat. CRL-1929) and MOLT-4 (cat. CRL-1582) – and were used directly with minimal passaging. Authentication of cell lines was performed at ATCC using STR profiling, and cell lines were mycoplasma negative. The cell lines used are not contained on the list of commonly misidentified cell lines from the International Cell Line Authentication Committee. Primary human peripheral blood mononuclear cells (PBMCs) (cat. PB005F) were purchased from AllCells (Alameda, CA). The SUP-B15 cell line was propagated in RPMI-1640 medium (2.0 g/L glucose) with 20% FBS, and the MOLT-4 cell line was propagated in RPMI-1640 medium (4.5 g/L glucose) with 10% FBS. Cells were incubated at 37°C under a 5% CO2 atmosphere.

Multiplex substrate profiling by mass spectrometry (MSP-MS)

Global substrate specificity profiling was performed on PA28α-activated 20S proteasomes with the MSP-MS assay using established methods (O'Donoghue et al., 2012; O'Donoghue et al., 2015; Winter et al., 2016). Briefly, human i20S or c20S was activated with 12 eq. of PA28 activator α subunit according to the manufacturer’s instructions. Assays were performed using two biological replicates of each proteasome. Proteasomes from different biological replicates were normalized based on activity against the fluorogenic substrate Suc-LLVY-AMC (catalog number AS-63892, Anaspec, Fremont, CA ). Activated proteasomes and corresponding PA28α-only no-enzyme control were pre-incubated at room temperature for 1 hr in assay buffer (20 mM Tris-HCl, pH 8.0, 0.5 mM EDTA). Following pre-incubation, all samples were diluted two-fold into a 228-member library of peptides pooled in assay buffer (500 nM final peptide concentration). Aliquots (20 μL) were removed after the indicated time points and quenched with 4 μL of 2% formic acid. Samples were desalted using C18 LTS tips (Rainin, Oakland, CA) and rehydrated using 0.2% formic acid prior to mass spectrometry acquisition.

Peptide sequencing was performed on an LTQ Orbitrap-XL mass spectrometer (Thermo) equipped with an EASY-Spray ion source (Thermo) and 10,000 psi nanoACQUITY Ultra Performance Liquid Chromatography system (Waters, Milford, MA). Peptide liquid chromatography was performed on an EASY-Spray PepMap C18 column (Thermo, ES800; 3 μm bead size, 75 μm x 150 mm) at a 300 nL/min flow rate from 2% to 50% (vol/vol) acetonitrile in 0.1% formic acid. Survey scans for MS/MS analysis were recorded over a 325–1500 m/z mass range. Peptide fragmentation was carried out with collision-induced dissociation (CID) on the six most intense precursor ions, with a minimum of 1000 counts, using an isolation width of 2.0 Th, and a minimum normalized collision energy of 25.

Mass spectrometry peak lists were generated using previously reported software called PAVA (Guan et al., 2011). To identify peptide cleavage products, data searches were performed against the library of 228 peptides using Protein Prospector software (http://prospector.ucsf.edu/prospector/mshome.htm, UCSF) (Chalkley et al., 2008). Octapeptide (P4-P4ʹ) cleavage products used to generate the specificity profiles, the sequences of the 228-member peptide library, and supporting mass spectrometry peptide reports are provided (see Figure 1—source data 1). All raw spectrum (.RAW) files from the MSP-MS experiments are available at the massIVE resource (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp; massIVE accession: MSV000081698). We note that the peptide library was synthesized with norleucine in place of methionine. In database searching, leucine is used to represent norleucine. Tolerances of 20 ppm and 0.8 Da were used for parent and fragment ions, respectively. The following variable modifications were selected with a maximum of 2 modifications per peptide: amino acid oxidation (proline, tryptophan, and tyrosine) and N-terminal pyroglutamate conversion from glutamine. Protein Prospector score thresholds were set to 22 and 21 with maximum expectation values of 0.01 and 0.05 for protein and peptide matches, respectively. Only overlapping peptide cleavages between biological replicates of each proteasome and those not appearing in the no-enzyme control are reported. Peptide cleavage products were imported into iceLogo software v.1.2 to generate protease substrate specificity profiles as described (Colaert et al., 2009). Octapeptides (P4-P4ʹ) corresponding to the peptide cleavage products were used as the positive dataset, and octapeptides corresponding to all possible cleavage sites in the 228-member library were used as the background dataset (Figure 1—source data 1).

MHC I peptide library cleavage assay

Proteasome cleavage assays against the library of 89 MHC I peptides and subsequent mass spectrometry work-flows were carried out as described above for the MSP-MS assay with the following exceptions. Assays were performed against the MHC I peptide library (500 nM final concentration in assay buffer) using 100 nM c20S or i20S that had been activated with 1200 nM PA28α. Aliquots (10 μL) were removed after 15, 30, 60, 120, 240, 1440, and 2880 min and quenched with 2 μL of 2% formic acid. Assays were performed in duplicate with 2 LC-MS/MS injections per sample (n = 4). Liquid chromatography was performed from 2% to 20% (vol/vol) acetonitrile in 0.1% formic acid.

The sequences of the MHC library and supporting mass spectrometry peptide reports are provided (see Figure 4—source data 1). All raw spectrum (.RAW) files from the MHC peptide cleavage assay are available at the massIVE resource (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp; massIVE accession: MSV000081699). Database searching was performed against the library of peptides using Protein Prospector with protein and peptide score thresholds set to 15. MS1 extracted ion chromatograms for label-free quantitation were obtained using Skyline software (v.3.5; University of Washington) (MacLean et al., 2010) on quantifiable precursors identified in both independent assays. Initial rates were calculated from a linear fit of the progress curves using Prism (v.6.0) and averaged for calculation of relative cleavage rates. Initial rates were averaged for both cleavage products from a given substrate when possible. Statistical significance (p-values) was calculated with a two-tailed Student’s t-test.

Positional scanning-synthetic combinatorial library (PS-SCL) profiling

Non-prime-side substrate specificity profiling was performed with a complete, diverse library of 160,000 fluorogenic substrates containing the general structure acetyl-P4-P3-P2-P1-(7-amino-4-carbamoylmethylcourmarin, ACC) (Harris et al., 2000). For each sub-library, 10 nM human i20S or c20S underwent SDS pre-activation for 1 hr at room temperature in assay buffer (20 mM Tris, pH 8.0, 0.5 mM EDTA) containing 0.03% SDS. Inhibitor pre-incubations were performed in the presence of 40 nM CFZ. Activity assays were carried out over 1 hr following two-fold sample dilution in the same 0.03% SDS-containing buffer that also contained a 250 μM final concentration of PS-SCL substrate pool. Activity was recorded in black 96-well round bottom plates (Costar, COrning, NY) using a BioTek Synergy H4 Hybrid Multi-Mode Microplate Reader set to λex = 380 nm and λem = 460 nm (gain = 63). Initial velocity in relative fluorescence units per second (RFU/s) was calculated using a linear fit of the progress curves with Gen5 software v.2.03.

Synthesis of fluorogenic peptide substrates

Fluorogenic substrates for the iP and cP were prepared using standard solid-phase peptide synthesis protocols. For peptides bearing a C-terminal ACC fluorophore, P1 amino acids were coupled to previously described ACC-substituted Rink amide resin (Maly et al., 2002). P1 residues underwent double coupling for two 24 hr periods in N,N-dimethylformamide (DMF) with Fmoc-protected P1 amino acid (5 eq.), HATU (5 eq.), and 2,4,6-collidine (5 eq.). For the P4, P3, and P2 positions, double couplings were carried out for two 1 hr periods with Fmoc-amino acid (6.5 eq.), HBTU (6.5 eq.), and N-methylmorpholine (13 eq.). Fmoc deprotection for each step was afforded with 20% 4-methylpiperidine in DMF (v/v). For N-terminal capping groups, double acetylation (Ac) was performed for two 1 hr periods with a 1:1:5:5 (v/v) solution of acetic anhydride (excess), triethylamine (TEA), DMF, and dichloromethane (DCM). N-morpholinyl (m) or 5-methylisoxazolyl (iso) addition was afforded with double coupling for two 1 hr periods with 4-morpholinylacetic acid hydrochloride (6.5 eq.), HBTU (6.5 eq.), and N-methylmorpholine (26 eq.) or 5-methylisoxazole-3-carboxylic acid (6.5 eq.), HBTU (6.5 eq.), and N-methylmorpholine (13 eq.), respectively.

An internally quenched fluorogenic substrate GEWHWPS (P5-P2ʹ) was synthesized bearing an N-terminal 7-methoxycoumarin (MCA) fluorophore and C-terminal 2,4-dinitrophenyl (DNP) quencher with the sequence D-Arg-D-Arg-Lys(MCA)-Gly-Glu-Trp-His-Trp-Pro-Ser-Lys(DNP). Residues comprising the GEWHWPS sequence were coupled to preloaded Fmoc-Lys(DNP) Wang resin (AnaSpec) using a Symphony Quartet 4-channel peptide synthesizer (Protein Technologies, Tucson, AZ). Double couplings for all amino acids were carried out in DMF with Fmoc-amino acid (6.5 eq.), HBTU (6.5 eq.), and N-methylmorpholine (13 eq.) as described above with the following exception. The Fmoc-Lys(MCA)-OH (AnaSpec, Inc) fluorophore (3 eq.) underwent a single overnight coupling with HBTU (3 eq.) and N-methylmorpholine (6 eq.).

Trifluoroacetic acid (TFA) cleavage and amino acid side chain deprotection were carried out with a solution (v/v) of TFA (95%), water (2.5%), and triisopropylsilane (2.5%). Peptides were precipitated into diethyl ether, and the crude product was dried under ambient conditions for an overnight period. Peptides were purified by reversed phase high performance liquid chromatography (HPLC) on a Vydac C18 column (10 μm bead size, 22 mm x 250 mm) using an Agilent 1200 Series or Waters 2535 preparative HPLC system. Peptide separation was carried out at a flow rate of 10 mL/min using a gradient of 95% acetonitrile in 0.1% aqueous TFA. Peptide purity was assessed by peak area (A330) using reversed phase HPLC with an Agilent 1100 Series analytical HPLC system. Peptides were resolved on a Vydac C18 column (10 μm bead size, 4.6 mm x 250 mm) at 1 mL/min using a 46 min linear gradient from 5% to 95% acetonitrile in 0.1% aqueous TFA.

Mass spectra were recorded for the following substrates with LC-MS using a Thermo MSQ Plus mass spectrometer in positive ion mode. MS Calcd. (Found): [M + H] NH2-PDFY-ACC 741.3 (741.4); [M + H] NH2-EWHW-ACC 857.3 (857.5); [M + H] NH2-SHRn-ACC 712.3 (712.5); [M + H] NH2-InQT-ACC 674.3 (674.3). Mass spectra were recorded for the following substrates on an Applied Biosystems Voyager DE-STR MALD-TOF in positive ion mode using a 1:1 α-cyano-4-hydroxycinnamic acid: sample ratio (v/v). MS Calcd. (Found): [M + H] NH2-PWHW-ACC 825.3 (824.9); [M + H] NH2-PDHW-ACC 754.3 (754.1); [M + H] NH2-PDEW-ACC 746.3 (746.1); [M + H] NH2-PDFW-ACC 764.3 (764.0); [M + H] NH2-KWHW-ACC 856.4 (856.0); [M + H] NH2-EKHW-ACC 799.3 (799.0); [M + H] NH2-EKFW-ACC 809.4 (809.2); [M + H] NH2-EWFW-ACC 867.3 (867.1); [M + H] NH2-YVQA-ACC 680.3 (680.1); [M + H] NH2-YVQS-ACC 696.3 (696.0); [M + H] NH2-YVQG-ACC 666.3 (665.9); [M + H] NH2-IVQA-ACC 630.3 (630.1); [M + H] NH2-YFQA-ACC 728.3 (728.1); [M + H] NH2-YVHA-ACC 689.3 (689.1); [M + H] NH2-YVSA-ACC 639.3 (639.1); [M + H] NH2-YVIA-ACC 665.3 (665.2); [M + Na] Ac-YVQA-ACC 744.3 (744.0); [M + H] NH2-VQA-ACC 517.2 (516.9); [M + Na] Ac-VQA-ACC 581.2 (580.9); [M + H] m-VQA-ACC 644.3 (644.0); [M + Na] iso-VQA-ACC 648.2 (648.0); [M + H] DArg-DArg-Lys(MCA)-Gly-Glu-Trp-His-Trp-Pro-Ser-Lys(DNP) 1847.8 (1848.5).

MHC I peptide library design and synthesis

Peptides for the MHC I library were designed to include the C-terminal region of known MHC I peptides (at positions 1–7) and the subsequent parent protein sequence (at positions 8–14) to query proteasome cleavage selectivity between positions 7 and 8 (P1/P1ʹ). Peptide sequences for library construction were selected at random from a proteomic database of MHC I peptides (Bassani-Sternberg et al., 2015) (n = 22,598) based on their predicted iP or cP cleavage score to not bias by proteasome cleavage preference. The cleavage score was calculated for each peptide by multiplying the P4-P1 amino acid frequencies for the iP and cP obtained from the MSP-MS assay.

A 95-member MHC I library was synthesized (89 were assayed due to solubility reasons) on 12.5-μmol scale using standard solid-phase peptide synthesis protocols with pre-loaded Fmoc-D-Arg(Pbf)-Wang resin (Anaspec), resulting in 15-mer peptides with a C-terminal D-Arg residue. For the 14-mer sequences, double couplings were performed using Fmoc-amino acid (5 eq.), HCTU (5 eq.), and N-methylmorpholine (20 eq.) with a 96-channel Syro II automated peptide synthesizer (Biotage). TFA cleavage was carried out using a 48-position transfer unit (Biotage, Charlotte, NC). Peptides were purified with reversed phase HPLC on an Agilent Pursuit 5 C18 column (5 μm bead size, 150 mm x 21.2 mm) using an Agilent PrepStar 218 series preparative HPLC system under the solvent conditions described above. MS1 spectra were recorded on an AXIMA Performance MALD-TOF/TOF mass spectrometer (Shimadzu, Columbia, MD) in positive ion mode using a 1:1 α-cyano-4-hydroxycinnamic acid: sample ratio (v/v).

Purified proteasome activity assays

Activity assays with individual fluorogenic substrates were carried out as described above for the PS-SCL assays using final concentrations of 5 nM SDS-activated i20S or c20S and 10 μM substrate except where noted below. The commercial substrates Suc-LLVY-AMC, Ac-WLA-AMC (Boston Biochem, S-330), and Ac-ANW-AMC (Boston Biochem, S-320) were used as supplied. To convert cleaved substrate RFU to free AMC or ACC dye concentration, calibration curves were prepared through total enzymatic hydrolysis of ACC- or AMC-containing peptides that had been quantified through amino acid analysis (Alphalyse, Inc.). Substrate selectivity of PA28α- and SDS-activated 20S proteasomes was compared following 1 hr pre-incubation at room temperature either in the presence of 0.03% SDS or with 12 molar equivalents of PA28α activator in the absence of SDS. For substrate selectivity assays with mixed, purified proteasomes, i20S and c20S underwent individual SDS pre-activation prior to assaying with 5 nM final concentration of pooled 20S. Proteasome ratio assays were performed with 10 μM EWFW-ACC, 30 μM iso-VQA-ACC, and 30 μM Suc-LLVY-AMC. All activity measurements were recorded on the BioTek plate reader described above using λex = 380 nm and λem = 460 nm (gain = 63) for ACC substrates and Suc-LLVY-AMC; 345 nm and λem = 445 nm (gain = 63) for Ac-WLA-AMC and Ac-ANW-AMC; and λex = 328 nm and λem = 393 nm (gain = 75) for the GEWHWPS IQ substrate. Michaelis-Menten calculations were performed using a non-linear fit in Prism v.6.0.

Cell lysate proteasome activity assays

Three lysates containing varied proteasome ratios (whole blood, PBMCs, and the MOLT-4 cell line) were assayed in the absence or presence of proteasome inhibitors as described above. Lysates were generated by washing cells in PBS and lysing the resulting cell pellet in a two-fold greater volume of cold lysis buffer (20 mM Tris, pH 8.0, 5 mM EDTA). Total protein concentration was determined using the BCA Protein Assay Kit (Thermo Scientific Pierce) with bovine serum albumin (BSA) as the protein standard. The cell lysates (1.6 mg/ml for whole blood and 0.4 mg/ml for PBMCs and MOLT-4) underwent pre-incubation for 1 hr at room temperature with 100 nM inhibitor (CFZ, ONX 0914, or PR-825) in assay buffer (20 mM Tris, pH 8.0, 0.5 mM EDTA) without SDS. For IC50 measurements with the MOLT-4 lysate, pre-incubations were performed with seven inhibitor concentrations ranging from 40 μM to 0.04 nM CFZ, ONX 0914, or PR-825. Activity assays were carried out over 1 hr following two-fold sample dilution in the same assay buffer containing final concentrations of 10 μM NH2-EWFW-ACC, 30 μM iso-VQA-ACC, or 30 μM Suc-LLVY-AMC. Activity measurements were recorded on the BioTek plate reader described above in 384-well plates using either λex = 380 nm and λem = 460 nm (gain = 85) for the ACC substrates or λex = 345 nm and λem = 445 nm (gain = 85) for the AMC substrate.

ProCISE quantification of proteasome subunit levels and IC50values

The ProCISE assay was performed as previously described (Parlati et al., 2009) to determine the quantities of chymotrypsin-like subunits in each lysate type. For IC50 determinations, diluted lysates (20 mM Tris, pH 8.0, 0.5 mM EDTA) were pretreated with CFZ, ONX 0914, or PR-825 for 1 hr at room temperature before the addition of the proteasome active-site probe (PABP, Nanosyn). Following 2 hr room temperature incubation with biotinylated PABP, lysate was denatured in guanidine hydrochloride and probe-bound subunits were isolated via incubation with streptavidin-conjugated sepharose beads (GE Healthcare Bio-Sciences, Pittsburgh, PA) in 0.65 µm filter plates (EMD Millipore, Burlington, MA). Samples were rinsed of denaturant and probed overnight at 4°C with subunit-specific primary antibodies. Subsequent to primary antibody removal, HRP-conjugated secondary antibodies (Jackson ImmunoResearch, West Grove, PA) were allowed to bind for 2 hr at room temperature before removal and signal generation utilizing a chemiluminescent substrate (Thermo Scientific Pierce). For subunit level determination in lysates, absolute values of subunit per microgram of total protein were based on a purified proteasome standard curve. For IC50 determination, percent activity relative to DMSO-treated controls was calculated for dose-response curves.

In a commercial preparation of c20S (E-360) obtained from Boston Biochem, the subunit levels were found to be as follows by LC-MS/MS analysis (quantification by the emPAI method): β5/LMP7 (92% and 8%), β2/MCEL-1 (92% and 8%), and β1/LMP2 (98% and 2%). For a commercial preparation of i20S (E-370), the subunit levels were found to be as follows: β5/LMP7 (20% and 80%), β2/MCEL-1 (10% and 90%), and β1/LMP2 (48% and 52%). We note that the β1/LMP2 (caspase-like) subunits are the smallest contributor to the overall specificity of both proteasomes (Figure 1A).

Cellular proteasome inhibition and recovery assays

Cellular inhibitor treatments were performed with ONX 0914 (200 nM) and PR-825 (100 or 125 nM) to achieve optimal LMP7 or β5 selectivity, respectively (Muchamuel et al., 2009). SUP-B15 and MOLT-4 cells were seeded at 2 × 106/mL in RPMI media containing 10% FBS 24 hr prior to inhibition assays; PBMC vials were thawed and seeded at 4.4 × 106/mL in RPMI media with 10% FBS 3 hr prior to inhibition assays. Cells were diluted 2-fold with serum-free RPMI media containing 2X inhibitor or vehicle control (0.5% DMSO and 5% FBS final). Inhibitor treatments were carried out for 1 hr at 37°C, and to remove unbound inhibitor, cells were immediately washed three times (SUP-B15 and PBMCs) or six times (MOLT-4) with D-PBS for 1 hr time points or RPMI media containing 5% FBS for subsequent time points. Cells were incubated at 37°C for the duration of the time course and washed two times in D-PBS to remove serum upon harvest. The cell pellets were flash-frozen in liquid N2 prior to storage at −80°C.

Cell pellets were thawed and incubated for 30 min on ice in non-denaturing lysis buffer (20 mM Tris, pH 8.0, 5 mM EDTA) or RIPA buffer that contained cOmpleteTM EDTA-free inhibitor cocktail (Roche, Pleasanton, CA). Total protein concentration in supernatants was determined using a Bradford Protein Assay Kit (Thermo Scientific Pierce) or BCA Protein Assay Kit (Cell Signaling Technology), respectively, with BSA as the protein standard. Lysate activity assays were performed following 2-fold dilution of 0.1–0.4 mg/mL lysate into assay buffer as described above. Corresponding western blots were performed following SDS-PAGE in MOPS buffer with NuPAGETM4–12% Bis-Tris gels (Invitrogen). Wet transfer to Immun-Blot PVDF membrane (Bio-Rad) was performed at 200V and 220A (constant) for 60–90 min. Blocking was performed in 5% milk (in PBS-T), and the antibodies used are described above. Secondary detection was afforded with SuperSignal West Pico or Femto chemiluminescent substrate (Thermo Scientific Pierce). Chemiluminescent imaging was performed with a ChemiDocTM MP Imaging System (Bio-Rad). 

qRT-PCR. 

Total RNA was extracted from cells using the RNeasy Plus Mini kit (Qiagen, Germantown, MD). The quantity and quality of RNA was confirmed by absorption measurements at 260 and 280 nm. Single strand cDNA synthesis and PCR amplification were carried out in a 1-step reaction using the Brilliant II QRT-PCR Master Mix (Agilent, Santa Clara, CA). 100 ng of RNA was loaded in 96-well plate format and amplified with 0.9 μM of primers, 0.25 μM of MGB probe, and 30 nM of ROX passive reference dye. The reaction was carried out in a Mx3005P instrument (Agilent) with the following parameters: an RT step at 50°C for 30 min was followed by a preincubation step at 95°C for 10 min, 50 cycles of denaturation at 95°C for 15 s, and annealing/extension at 60°C for 1 min. Efficiencies for each primer/probe set were calculated from a serial dilution of Human Reference Total RNA (Agilent) and were >95%. Relative quantification of gene expression was calculated with the comparative cycle threshold method, normalizing for GAPDH expression levels.

Proteasome evolution

β5 and LMP7 orthologs were selected from multiple species as defined previously (Sutoh et al., 2012). Protein sequences were aligned using MSAProbs (Liu et al., 2010a) for each isoform separately. These alignments were then used to align the respective nucleotide sequences of the coding regions for each gene using an in-house python script. We then calculated phylogenetic trees using MrBayes (Huelsenbeck and Ronquist, 2001) with default parameter values. Finally, the evolution of sites in the isoform sequences was estimated using the SLR algorithm (Massingham and Goldman, 2005).

Statistical methods

Statistical significance (p-values) was determined using a Student’s t-test. For multiple comparison correction (q-values), we used the methodology by Storey (Storey, 2002). We chose an FDR level of 0.05 and λ = 0 to be conservative and also equivalent with the methodology of Benjamini and Hochberg (Benjamini and Hochberg, 1995) at α = 0.05. Errors bars represent the standard deviation unless otherwise noted. Numbers of replicates associated with each figure are provided in the corresponding figure legend.

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Decision letter

  1. Michael A Marletta
    Reviewing Editor; University of California, Berkeley, United States

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

Thank you for submitting your article "Immunoproteasome Functions Explained by Divergence in Cleavage Specificity and Regulation" for consideration by eLife. Your article has been reviewed by two peer reviewers (reviewers 2 and 3), and the evaluation has been overseen by a Guest Reviewing Editor and Michael Marletta as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Peter M Kloetzel (Reviewer #1); Herman Overkleeft (Reviewer #2).

The reviewers have discussed the reviews with one another and the Guest Reviewing Editor has drafted this decision to help you prepare a revised submission.

The manuscript is in principle within the scope of eLife's interest/mission. Both reviewers raise valid points, so rather than try to condense these two reviews, I suggest that the authors be given access to the full reviews and be given the opportunity to submit a properly revised version within the time line customarily allotted by eLife. I look forward to seeing a revised manuscript.

Reviewer #1:

Winter et al., have analysed the differences in cleavage properties of standard and immunoproteasome and they rightly state that these differences still are not fully understood. It has been previously shown that both isoforms in principle have the ability to cleave behind any of the 20 aa residues but that sP and iP depending on the substrate reveal differences in relative cleavage site usage. Based on peptide library based profiling Winter et al. now conclude that sP and iP exhibit overlapping but distinct substrate specificities. The authors also designed novel isoform selective substrates and confirm previous studies by showing that iP function affects proteostasis in cells predominantly expressing iP.

This reviewer appreciates this multi-disciplinary study to improve our knowledge and to eventually confute former models. The paper however raises a number of concerns with regard to the experiments and the conclusions drawn as will be outlined in detail below.

Figure 1.

The authors use a rationally designed peptide library comprising 228 14mer peptides to test their degradation by sP or iP. However, this multi-substrate approach and the data deduced raise a number of question and important information is lacking.

In order to be able to reproduce the experiments one has to know:a) what are the sequences of the peptides in the library?b) what was the rationale behind the design of the peptide library?

Given that the proteasomes can cleave behind any given residue the percentages of cleavage sites identified (18.4% and 21.3% of 2964 potential cleavage sites) seems to be very low and questions the overall sensitivity of the assays. It is well known that different substrates will be degraded with different efficiencies by either sP or iP. However, such differences will strongly influence the validation of cleavage site usage unless the cleavage site usage is not corrected for max/2 turnover of the substrate. Importantly, proteasomes are known to cut less efficiently and also slowly within short peptides. Dolenc et al. (FEBS Lett 1998) identified a length of 13 residues as lower limit to have an efficient degradation rate. Since the MSP-MS method uses 14mers, this reviewer thinks that it is mandatory to repeat the MSP-MS assay with much longer kinetics than 60 min (2,4,6,8 hours).

The authors neither report on the number of experiments performed to generate the data shown in Figure 1 nor on the reproducibility or the overlap between different experiments.

Assuming that technical replicates of the MS analysis and biological replicates (proteasome digestions) were performed, it will be very important to know the number of unique cleavage sites between:

- technical replicates;

- biological replicates;

- biological replicates performed at different time points using either sP or iP. The latter is a particular relevant control. I suppose that the alleged unique cleavage sites reported in Figure 1B will not be confirmed by performing the assays with longer time-point. (Also see comment to Figure 4).

I am also intrigued by the fact that the authors identified 217 cleavage sites being specific for sP. However, as stated in Materials and methods the commercial PBMC derived iP contains between 10% and 48% standard subunits. How can it be that such mixed-type proteasomes cannot cleave at all at sites used by the sP?

Performing and showing the outcomes of the requested controls will help to understand whether sP and iP really have such a large number of unique cleavage sites (348 of 762 cleavage sites identified). Using longer kinetics will most likely dramatically reduce this number. Even in case that there are only very few differences this would not affect the relevance of the study but will modify one of the main take home messages of the study.

I would also suggest to add a supplementary figure comparing the outcome of Figure 1C, with those of Toes et al., JEM 2001 and Mishto et al., EurJI 2014 to better understand differences and similarities.

Figure 2.

Figure 2A and 2B may serve the purpose of the idea but are not very informative. It is not clear how the experiment was performed. Were these peptides individually processed by either sP or iP and if so, what were the conditions. Are these peptides equally well degraded by both isoforms; are these all the cleavage sites detected by MS?

Figure 2—figure supplement 1.

There seems to be an editorial error for the km value of EWFW-ACC for i20S. It probably should read 1.8 μm instead 7.0 uM.

Figure 3A.

It is somewhat surprising that independent of the sP/iP ratio the activity measured with the commonly used substrate Suc-LLVY-AMC remained unchanged. This certainly stands in contrast to several reports by Gaczynska and coworkers (cited) as well as by many others.

Figure 4.

I do not really understand why the authors state that iP clearly expands the MHC-I repertoire when the authors don´t find proteasome isoform specific cleavage sites which generate the tested epitopes. As documented in Figure 4B the most sP preferred epitope HTQVIEL>ERKFSHQ is also generated by iP, albeit less efficiently. Similarly, the most iP favoured epitope is also generated by sP. My interpretation of the data shown is that there are epitopes which are more efficiently generated by either sP or iP which consequently will affect their presentation at the cell surface. (in this context see Zanker, D., Waithman, J., Yewdell, J. W. and Chen, W.. J. Immunol. 2013. 191: 52-59.)

In part the experiments shown also answer my concerns expressed for the data in Figure 1. Here, in Figure 4 the authors have performed longer kinetics as requested above and conclude that many peptides have an equivalent potential of being generated by either proteasome isoform. Even the tryptophan-cleavage site, although preferred by iP is shown to be used by sP as well, albeit less efficiently (Figure 4B).

This reviewer has some concerns regarding the label-free quantification of the peptides. It is well known that the MS ion signal strongly varies between peptides of different sequence. This is irrelevant with a dataset of thousands of peptides but render not applicable the label-free strategy to quantify a small number of short peptides (Bassani-Sternberg et al., MCP 2015; Liepe et al., Science 2016; Tenzer et al., Nat Immunol 2009).

In Materials and methods it is stated that 89 epitope derived peptides were analysed but only slightly more the 50 are documented in Figure 5A (please explain).

Figure 5.

The authors show that in cells mostly expressing iP, selective inhibition of LMP7 results in an accumulation of ub-conjugates. They infer from these results that iP activity makes a significant contribution to UPS capacity. This conclusion is in agreement with previously published data Seifert et al. Cell (2010), which I would suggest to cite in this context. That inhibition of the beta5 site doesn´t evoke similar effects is most likely due to the small amounts of sP present in these samples.

The authors observe a bounce back of LMP7 activity after irreversible inhibition of LMP7 as well as upregulation of both PSMB8 and PSMB5 mRNAs during the recovery phase. This is a well-known phenomenon. That PSMB5 mRNAs has little impact on β 5 activity is also to be expected because in the presence of both β 5 and LMP7 units, incorporation of LMP7 is dominant due its higher binding affinity for the proteasome maturation protein POMP.

Reviewer #2:

As I see it this paper consists of two parts that are interconnected by the use of the fluorogenic beta5c/beta5i substrates developed in Figure 13 to link iCP activity, set off against cCP activity, in global proteasomal proteolysis (Figure 5) and MHCI ligand production (Figure 4). These two (or three) sections feel somewhat disconnected to me and the main aim: to establish substrate preferences of the various proteasomal activities and to connect these to cellular processes has not been reached to satisfaction. Despite this, the workflow to identify substrate preferences and to derive two new and considerably beta5c and beta5i-selective substrates – the part of the work I am able to judge best – is executed very well and the resulting reagents should be of considerable interest to the research community. I have a few points that may need clarification:

Different proteasome preparations are being used in the various assays: sometimes SDS-activated and sometimes PA28-activated. To what extent are these methods providing similarly activated proteasomes?

Peptides, rather than (unfolded) proteins are being used to establish cleavage preferences. To what extent are peptides suitable protein substitutes? what about concentration, reaction times, other factors that may be different in cells?

Why only beta5c/beta5i?

Are ONX0914 and PR825 – developed for murine proteasomes, equally selective against their respective human proteasome targets (given that recent literature point towards differences in the active sites of especially the chymotryptic sites from these two species)?

Why, in designing selective fluorogenic substrates, not considering non-proteinogenic amino acids, also in view of the literature on likewise-designed inhibitors?

In using the substrates in mixtures containing both proteasome species: how to correct for minor processing of the 'unwanted' proteasome (since the reagents are not truly selective?)

Next top cP and iP species mixed proteasomes exist and that may have other substrate preferences: how does the work take the possible existence of such species into account?

Presentation of the work, I would favour some chemical structures, possibly also a chemical scheme (even though the methodology to synthesise the compounds has been published from the same group some time ago). In general I find the manuscript hard to get into, with lots of abbreviations.

A survey of the pros and cons of fluorogenic substrates in comparison with other methodology (activity-based protein profiling, the Procise assay) would be helpful.

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

Thank you for resubmitting your work entitled "Immunoproteasome Functions Explained by Divergence in Cleavage Specificity and Regulation" for further consideration at eLife. Your revised article has been favorably evaluated by Michael Marletta as the Senior and Reviewing Editor, and one reviewer.

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

We try hard to avoid requiring more experiments after one round of revision. I ask that you consider the points raised below and send a response to me before initiating a new round experiments (the replicates referred to below).

Reviewer #1:

I appreciate the additional work by Winter et al. Their efforts certainly improved the manuscript. In particular, the kinetics experiments and the biological replicates of the MSP-MS assays give now a clearer picture of the results and the potency of the method.

Having said this, there still remain some points which in my mind cast doubt onto the robustness of some the experiments.

The authors show that:a) they have a 70% reproducibility of technical replicate at 8 h digestion (they show it only for immunoproteasome and at 8h, though);b) they have around 70% reproducibility of biological replicate at 8 h digestion (as far as I get from Figure 1—figure supplement 1);c) there is a strong increase of the number of cleavage-sites identified over time;d) they have 19.5% cleavage sites identified only in cP digestions although their iP has 10-48% cP subunits. How can it be that a cP-iP mixed population doesn't use all cleavage-sites used by cP?e) After 8 h, 11-13% of the cleavage-sites have been used by proteasomes.

Comment: The surprisingly low number of cleavage sites identified is not compatible with the extent of cleavage site usage published in the literature and also the fact that proteasomes cleave more or less behind any amino acid. When single polypeptide substrates are analysed a cleavage site coverage of >60% is the rule.

I raised the issue of the sensitivity of the MSP-MS before. In the point by point review this issue is however only partially addressed. I now see the rationale behind the design of the library, but considering the cleavage site coverage in the experiments I start to wonder whether what works perfectly for conventional proteases also will work for the proteasome with extremely little cleavage site specificity. (This does not imply that proteasomes don´t have cleavage site preferences).

The authors propose that the MSP-MS method represents an improvement for understanding the proteasome dynamics. Despite all the work published in the past two decades, understanding proteasome dynamics still is an important issue. Because of this, the authors should try to give a robust answer to the question they raised: does iP differ from cP in terms of cleavage-site usage? Is the truth close to "only quantitative differences" as stated by a few or close to "strong qualitative differences" as published by others?

The authors rephrased several parts of the text to satisfy both hypotheses. They would have, however, the opportunity to provide strong evidence supporting one of the two hypotheses. Such an answer would be a significant improvement in the field and certainly worth publishing.

To this end, the authors ought to strengthen their MS analysis. Here I have some suggestions:

a) The authors should perform more technical replicates than 2 (5 are sufficient in our set up), considering the reproducibility that they have.

b) They should add the new peptides identified in each replicate to the final list of identified peptides (and thus cleavage-sites used), instead of focusing only on the common peptide products. Because if only the common peptide products (and cleavage-sites) are true, it means that the authors have an experimental FDR =30%. Clearly too high to say anything about differences between cP and iP.

For example, in Figure 1—figure supplement.1B I see 101 cleavage-sites used by cP and 134 by iP after 1h. In the first submitted Figure 1, they had 631 cleavage-sites for cP and 545 for iP. What did happen to the others? I guess the discrepancy is due to the new data analysis used. In fact, even considering the cleavage-sites identified in only one of the biological replicates, in the new Figure 1—figure supplement 1B, after 1 h digestion, I see around 220 cleavage-sites identified in cP and 250 in iP.

I suggest, that the authors should try to increase the coverage of the peptide products. Considering only the products common to the replicates the authors likely analyse only the most abundant peptide products. Therefore, my question is, do the authors want to study only the most frequently used cleavage-sites (top 10 I would say since they identified only 11-13% of the cleavage-sites) or all cleavage-sites used by proteasome? If the intention is to focus on the top ten only, they should re-phrase the entire manuscript.

With 5 technical replicates, they could have a better view of the cleavage-site usages by proteasome isoforms. And I guess they will also increase the number of cleavage-sites used by proteasome since 11-13% is really not compatible with proteasomes cleaving after almost any amino acid (see also above).

c) The authors may perform longer digestions. In their experiments, the authors see a decline in the number of newly identified cleavage-sites over time. However, this could also be due to inhibitory effects of the products on proteasome activity (see Liepe et al., eLife 2015). To minimize this problem, the authors could (should) also increase the concentration of proteasome.

Everything that it is useful to identify at least 40-50% of the potential cleavage sites or at least reaching a plateau in terms of cleavage-sites used by proteasome. Otherwise the authors are watching only the tip of the iceberg.

d) Concerning the MS analysis, FDR=0.05 is not conservative. The other parameters (Materials and methods) should be better clarified without referring to other studies.

I wonder if the analysis of the MHC-I peptides using the outcome of the MSP-MS would be different using a more sensitive approach and if it would show differences between cP and iP.

e) The authors added the statement: "Proteasomes from different biological replicates were normalized based on activity against the fluorogenic substrate Suc-LLVY-AMC (Anaspec, AS-63892)".

It is generally accepted that the hydrolytic activity measured with short fluorogenic substrates such as Suc-LLVY-AMC may have very little to do with the ability of proteasomes to degrade larger polypeptide substrates. Identical peptide hydrolysing activities or adjustment of the amounts of proteasomes to obtain identical activities is by no way a reliable method if one wants to study the processing of polypeptides by different proteasome subtypes or by different commercially available proteasome charges.

As pointed out in my first review in a different context, it is essential to monitor the turnover of the substrate(s) and compare fragment patterns or cleavage site usage when approx.. 40% of the substrates is turned over. In this way, it is possible to compare the cleavage site usage of two proteasome samples more or less independent of their activity and independent of different substrate degradation kinetics (which often differ between substrates and certainly will do so in a library).

f) The authors should make the RAW files of the XL measurements available by depositing them in an online archive. They should also provide in Figure 1—source data 1 and Figure 4—source data 1 enough info (MS scan, RT) to reproduce the results. They also ought to provide the list of the peptide library (not on a collaboration-base) as supplementary material in this manuscript. I think this is the eLife policy. The aim is allowing other scientists to reproduce the results

g) The Supplementary file 1 is not clear. I did not find a caption explaining the meaning of #1, #2, #3. Are they biological replicates? No enzyme is the control without any enzyme? If yes, where are the peptides listed identified in the No Enzyme Control? Why is the reproducibility of the cP not reported here?

https://doi.org/10.7554/eLife.27364.029

Author response

Reviewer #1:

[…] This reviewer appreciates this multi-disciplinary study to improve our knowledge and to eventually confute former models. The paper however raises a number of concerns with regard to the experiments and the conclusions drawn as will be outlined in detail below.

Figure 1.

The authors use a rationally designed peptide library comprising 228 14mer peptides to test their degradation by sP or iP. However, this multi-substrate approach and the data deduced raise a number of question and important information is lacking.

In order to be able to reproduce the experiments one has to know:a) what are the sequences of the peptides in the library?b) what was the rationale behind the design of the peptide library?

We appreciate the necessity for any group to reproduce the experiments outlined in the study. To address this point, we have made the peptide library available through academic collaboration with our research groups (subsection “Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS)”, last paragraph). In Figure 1—source data 1, we have provided a list of all iP and cP cleavage site data used to generate Figures 1 and 2.

The MSP-MS peptide library has been described in O’Donoghue et al. Nat. Methods 2012 (PMID:23023596). The library design is based on the specificity preference of proteases for two optimally positioned amino acids within a substrate. For example, the amino acids in the P1 and P1ʹ position generally drive the specificity of aspartic acid proteases, whereas matrix metalloproteases have important substrate binding interactions in the S2 and S1ʹ sub-sites. In another example, the substrate specificity for caspase 3 and granzyme B is primarily located in the S4 and S1 pockets. Therefore, we designed an unbiased and diverse library of 14-mer peptides containing all possible neighbor (XY) and near neighbor (X*Y and X**Y) amino acid pairs so that all proteases would be able to cleave a selection of peptides. We have shown that highly specific proteases, such as human rhinovirus-14 protease, cleave a single peptide within the library (Nat. Methods 2012), whereas proteases with broad specificity, such as human cathepsin E, cleave 277 peptide bonds (Ivry et al. Clin Cancer Res 2017; PMID: 28424202). The mathematical formula used to design these sequences was published in our 2012 Nat. Methods paper.

Given that the proteasomes can cleave behind any given residue the percentages of cleavage sites identified (18.4% and 21.3% of 2964 potential cleavage sites) seems to be very low and questions the overall sensitivity of the assays. It is well known that different substrates will be degraded with different efficiencies by either sP or iP. However, such differences will strongly influence the validation of cleavage site usage unless the cleavage site usage is not corrected for max/2 turnover of the substrate. Importantly, proteasomes are known to cut less efficiently and also slowly within short peptides. Dolenc et al. (FEBS Lett 1998) identified a length of 13 residues as lower limit to have an efficient degradation rate. Since the MSP-MS method uses 14mers, this reviewer thinks that it is mandatory to repeat the MSP-MS assay with much longer kinetics than 60 min (2,4,6,8 hours).

In the Dolenc et al.paper, the cleavage rate of a 14-mer peptide by Thermoplasma acidophilum proteasome is equivalent to a 16-mer and 23-mer peptide. Therefore, the length of our starting substrates is likely to be sufficient for these assays. However, to address the concern from the reviewer about cleavage events that take place after 1 h, we have repeated the MSP-MS assay and performed an 8-hour time course. These additional time points have allowed for the generation of progress curves for iP and cP cleavage of the library (Figure 1—figure supplement 1A). As predicted by the reviewer, the number of new cleavage sites identified increases with time; however, the rate of new cleavage sites generated by each proteasome reduces as the assay progresses (Figure 1—figure supplement 1A and 1B). We have also provided heat maps to compare proteasome specificity throughout the extended assay time course (Figure 2—figure supplement 2).

The authors neither report on the number of experiments performed to generate the data shown in Figure 1 nor on the reproducibility or the overlap between different experiments.

Assuming that technical replicates of the MS analysis and biological replicates (proteasome digestions) were performed, it will be very important to know the number of unique cleavage sites between:

- technical replicates;

- biological replicates;

- biological replicates performed at different time points using either sP or iP. The latter is a particular relevant control. I suppose that the alleged unique cleavage sites reported in Figure 1B will not be confirmed by performing the assays with longer time-point. (Also see comment to Figure 4).

All MSP-MS assays have now been performed with two commercial stocks of cP and iP (different lot numbers). In our manuscript, only cleavage sites that were found in two independent cP assays and in two independent iP assays (summarized in Figure 1—figure supplement 1B) are reported and discussed. We have modified the main text (subsection “Global Substrate Specificity Profiling of the iP and cP”, first paragraph) and figure legends to clearly state that only cleavage sites that are common between two biological replicates are considered in our study.

For technical replicates, we have shown that the number of peptides identified in duplicate technical replicate assays ranges from an average of 78.5% at the start of the assay (before addition of proteasome) to 70.0% after 8 hours of incubation with proteasome. A table showing these data has been included in Supplementary file 1.

As suggested, we have provided the overlap between biological replicates throughout the assay time course (Figure 1—figure supplement 1B). This analysis indicated that indeed the iP and cP have increased cleavage overlap at longer time points but that the proteasomes also retain unique specificity features (Figure 1—figure supplement 2). We feel that this experiment helped strengthen the message of the manuscript and thank the reviewer for the suggestion.

I am also intrigued by the fact that the authors identified 217 cleavage sites being specific for sP. However, as stated in Materials and methods the commercial PBMC derived iP contains between 10% and 48% standard subunits. How can it be that such mixed-type proteasomes cannot cleave at all at sites used by the sP?

The reviewer has correctly pointed out that each proteasome sample used in this study has β1, β2, β5, LMP2, MCEL-1 and LMP7 subunits although the ratio of each subunit differs considerably between the iP and cP preparations. With extended incubation time, iP and cP may eventually hydrolyze the peptide library into the same set of cleavage products. The differences in cleavage site preferences that are detected in our assay over the course of 8 hours are likely due to differences in cleavage efficiency. Therefore, we have removed the term “unique” cleavage sites from the manuscript to avoid confusion.

Performing and showing the outcomes of the requested controls will help to understand whether sP and iP really have such a large number of unique cleavage sites (348 of 762 cleavage sites identified). Using longer kinetics will most likely dramatically reduce this number. Even in case that there are only very few differences this would not affect the relevance of the study but will modify one of the main take home messages of the study.

We have performed the experiments requested by the reviewer and feel that they have strengthened the message of the paper. Our results suggest that specificity differences are clearly evident between the two proteasomes. We agree with the reviewer that the altered substrate specificity largely results in the proteasomes displaying differing efficiencies of cleavage for certain substrates. Therefore, we have removed the term “unique” cleavage sites from the paper to avoid confusion as stated above. See also our comment to Figure 4 regarding epitope generation.

I would also suggest to add a supplementary figure comparing the outcome of Figure 1C, with those of Toes et al., JEM 2001 and Mishto et al., EurJI 2014 to better understand differences and similarities.

We have now provided a comparison of the results from Figure 1C with those from Toes et al. and Mishto et al. (Figure 1—figure supplement 3).

Figure 2.

Figure 2A and 2B may serve the purpose of the idea but are not very informative. It is not clear how the experiment was performed. Were these peptides individually processed by either sP or iP and if so, what were the conditions. Are these peptides equally well degraded by both isoforms; are these all the cleavage sites detected by MS?

The legend in Figure 2 has been modified to clarify that the cleavages shown are from the MSP-MS assays associated with Figure 1. The MSP-MS assay conditions are provided in the Materials and methods section. In Figure 2, the time point of first appearance now has been noted for the cleavages used in fluorogenic substrate design to provide a measure of cleavage selectivity. Only cleavages are shown that are common to both biological replicates of each proteasome.

Figure 2—figure supplement 1.

There seems to be an editorial error for the km value of EWFW-ACC for i20S. It probably should read 1.8 μm instead 7.0 uM.

The Km values provided for the table in Supplementary file 2 are correct. The selectivity of the EWFW-ACC substrate for the iP is driven by the greater kcat.

Figure 3A.

It is somewhat surprising that independent of the sP/iP ratio the activity measured with the commonly used substrate Suc-LLVY-AMC remained unchanged. This certainly stands in contrast to several reports by Gaczynska and coworkers (cited) as well as by many others.

The assay was performed using a comparable substrate concentration of 30 μM LLVY where similar iP and cP activity is observed (10 μM EWFW and 30 μM iso-VQA were used by comparison). This has been clarified in the Results section (subsection 2 Fluorogenic Substrates Enable Cellular Activity Profiling of LMP7 and β5”), and substrate concentrations have been provided in the legend for Figure 3. A supplemental Michaelis-Menten plot for LLVY (Figure 3—figure supplement 1) also has been added to demonstrate the maximal 2.0-fold iP selectivity observed at Vmax.

Figure 4.

I do not really understand why the authors state that iP clearly expands the MHC-I repertoire when the authors don´t find proteasome isoform specific cleavage sites which generate the tested epitopes. As documented in Figure 4B the most sP preferred epitope HTQVIEL>ERKFSHQ is also generated by iP, albeit less efficiently. Similarly, the most iP favoured epitope is also generated by sP. My interpretation of the data shown is that there are epitopes which are more efficiently generated by either sP or iP which consequently will affect their presentation at the cell surface. (in this context see Zanker, D., Waithman, J., Yewdell, J. W. and Chen, W.. J. Immunol. 2013. 191: 52-59.)

We agree that the current language about the iP “expanding” the peptide repertoire may be confusing. We have changed this language in the Abstract and throughout the manuscript to state that iP specificity may alter the MHC I peptides displayed due to the different cleavage efficiency of the iP for certain epitopes.

In part the experiments shown also answer my concerns expressed for the data in Figure 1. Here, in Figure 4 the authors have performed longer kinetics as requested above and conclude that many peptides have an equivalent potential of being generated by either proteasome isoform. Even the tryptophan-cleavage site, although preferred by iP is shown to be used by sP as well, albeit less efficiently (Figure 4B).

This reviewer has some concerns regarding the label-free quantification of the peptides. It is well known that the MS ion signal strongly varies between peptides of different sequence. This is irrelevant with a dataset of thousands of peptides but render not applicable the label-free strategy to quantify a small number of short peptides (Bassani-Sternberg et al., MCP 2015; Liepe et al., Science 2016; Tenzer et al., Nat Immunol 2009).

The reviewer is correct that MS ion signal is strongly dependent upon peptide sequence composition. To clarify, the figure only compares relative cleavage rates by the iP and cP for each individual peptide. Therefore, the figure provides a relative ranking of iP versus cP peptide cleavage selectivity against the set of epitopes queried.

In Materials and methods it is stated that 89 epitope derived peptides were analysed but only slightly more the 50 are documented in Figure 5A (please explain).

Only the 56 peptides are shown that were cleaved between positions 7 and 8 (the MHC site) and for which accurate label-free quantification was possible. This information is provided in the Figure 4 legend for clarity.

Figure 5.

The authors show that in cells mostly expressing iP, selective inhibition of LMP7 results in an accumulation of ub-conjugates. They infer from these results that iP activity makes a significant contribution to UPS capacity. This conclusion is in agreement with previously published data Seifert et al. Cell (2010), which I would suggest to cite in this context.

We thank the reviewer for the suggestion and have now included the Seifert et al. reference.

That inhibition of the beta5 site doesn´t evoke similar effects is most likely due to the small amounts of sP present in these samples.

The authors observe a bounce back of LMP7 activity after irreversible inhibition of LMP7 as well as upregulation of both PSMB8 and PSMB5 mRNAs during the recovery phase. This is a well-known phenomenon. That PSMB5 mRNAs has little impact on β 5 activity is also to be expected because in the presence of both β 5 and LMP7 units, incorporation of LMP7 is dominant due its higher binding affinity for the proteasome maturation protein POMP.

We agree with the reviewer that recovery of LMP7 is indeed a known phenomenon (for example, Lee Br. J. Haematol.; PMID: 27071340). However, to our knowledge, the present study is the first to report the dynamics of LMP7 and beta5 recovery following selective inhibition of the iP (as opposed to CFZ treatment). Dissecting the activities LMP7 and beta5 individually has been made possible by the fluorogenic substrates developed.

Reviewer #2:

[…] Different proteasome preparations are being used in the various assays: sometimes SDS-activated and sometimes PA28-activated. To what extent are these methods providing similarly activated proteasomes?

We compared cleavage of LLVY and our lead fluorogenic substrates using both activation methods and found cleavage to be quite similar (Figure 2—figure supplement 4). SDS detergent was not compatible with our MS assay, and therefore, MS-based profiling was performed only with PA28 activation.

Peptides, rather than (unfolded) proteins are being used to establish cleavage preferences. To what extent are peptides suitable protein substitutes? what about concentration, reaction times, other factors that may be different in cells?

We agree that assaying peptides may yield differences compared to intact protein substrates. However, the peptide library used has the advantage of consisting of chemically defined sequences with uniform amino acid distribution. Linking biochemical conditions to cellular contexts is a challenge of any biochemical assay, and we have added the caveats mentioned to the Discussion section for clarity (first paragraph).

Why only beta5c/beta5i?

We have elected to focus on substrate development for the beta5 and LMP7 subunits because these subunits represent the dominant activities of each proteasome, and they have been the major focus of pharmaceutical drug development efforts to date. We agree that substrates could in principle be designed for the remaining catalytic subunits using a similar strategy.

Are ONX0914 and PR825 – developed for murine proteasomes, equally selective against their respective human proteasome targets (given that recent literature point towards differences in the active sites of especially the chymotryptic sites from these two species)?

The compounds ONX-0914 and PR-825 were initially developed against the human proteasome and are cross-reactive with the mouse proteasome. ONX-0914 and PR-825 have similar potency for their target proteasomes (Figure 1 and Supplementary Figure 2 in Muchamuel Nat. Med. 2009; PMID:19525961).

Why, in designing selective fluorogenic substrates, not considering non-proteinogenic amino acids, also in view of the literature on likewise-designed inhibitors?

We completely agree that non-proteinogenic amino acids could be an excellent strategy to improve the selectivity of the substrates. With the exception of norleucine, both substrate libraries used in our study consist of proteinogenic amino acids, and therefore our fluorescent substrate design only focused on these amino acids. Several groups, such as the Marcin Drag lab at Wroclaw University of Technology, have developed substrate libraries that use non-proteinogenic amino acids and may use the specificity information revealed here as a starting point for development of improved substrates. However, we feel that the proteinogenic tools developed here have sufficient selectivity to function in cellular lysates and further modification with non-proteinogenic amino acids is beyond the scope of the study.

In using the substrates in mixtures containing both proteasome species: how to correct for minor processing of the 'unwanted' proteasome (since the reagents are not truly selective?)

The reagents developed can be combined with subunit-selective inhibitors to correct for processing by the unwanted proteasome. Continued optimization of subunit-selective inhibitors in parallel will only improve the feasibility of this approach.

Next top cP and iP species mixed proteasomes exist and that may have other substrate preferences: how does the work take the possible existence of such species into account?

We certainly appreciate both the interest in and the challenge of assaying / discriminating mixed proteasomes. It is not well known to what extent the specificity of these species differ. However, we feel that this topic is well beyond the scope of the study because, to our knowledge, the mixed proteasome selectivity of any fluorogenic substrate or small molecule developed to date has not been fully elucidated.

Presentation of the work, I would favour some chemical structures, possibly also a chemical scheme (even though the methodology to synthesise the compounds has been published from the same group some time ago). In general I find the manuscript hard to get into, with lots of abbreviations.

We have now provided chemical structures of the lead substrates (Figure 2) and a synthetic scheme (Figure 2—figure supplement 3) to make the manuscript more approachable for a wider audience.

A survey of the pros and cons of fluorogenic substrates in comparison with other methodology (activity-based protein profiling, the Procise assay) would be helpful.

We have added a survey of the pros and cons of fluorogenic substrates to the Discussion section (first paragraph).

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

Reviewer #1:

I appreciate the additional work by Winter et al. Their efforts certainly improved the manuscript. In particular, the kinetics experiments and the biological replicates of the MSP-MS assays give now a clearer picture of the results and the potency of the method.

Having said this, there still remain some points which in my mind cast doubt onto the robustness of some the experiments.

The main criticism from the reviewer is that we are not sampling a large enough number of cleavages from the library to comment on whether each proteasome truly has unique substrates. To increase the number of cleavages, the reviewer proposes (a) increasing the number of replicates from two to five, (b) comparing ALL and not just cleavages common between replicate assays, and (c) letting the assay run longer until it "reaches a plateau." The number the reviewer suggests is 40-50% of cleavage-site usage (up to 1482 out of 2964 possible cleavage-sites in the 228-member library).

Our Response:

1) The data presented in the paper using the MSP-MS and PS-SCL technologies represent the most extensive extended substrate specificity analysis performed on the iP and the cP to date. Because of the global approach (e.g., breadth) that attempts to comprehensively evaluate the specificity of the enzymes, detailed analysis (e.g., depth) on each of the substrates is sacrificed. This global approach allowed us to develop iP- and cP-selective substrates, which was ultimately one of the goals of our study.

2) The MSP-MS assay detects the most dominant cleavage products in the diverse set of tetradecapeptides when run under Michaelis Menten conditions as we have done in the manuscript. This is best seen in the progress curves provided in Figure 1—figure supplement 1, which demonstrate that the number of new peptide bonds being cleaved in the library by the iP and cP begins to slow after 60 minutes. At 60 minutes, the iP and cP cleaved 264 and 225 peptide bonds corresponding to 8.9% and 7.5% of the 2,964 peptide bonds in the library. After 4 hours of incubation, the total number of new cleavage sites had not yet doubled (498 for the iP and 425 for the cP).

1)

3) As the peptides get smaller due to hydrolysis by the proteasome, they eventually become too small to detect reliably, as now schematically illustrated in Figure 1—figure supplement 2. This is why the assay predominately detects initial cleavage products and running the assay longer will not uncover additional activities.

4) The MSP-MS peptide library has now been used to uncover the substrate specificity of ~80 proteases including enzymes with substrate preferences that are similar to the β1 (caspase-like) and β2 (trypsin-like) subunits of the proteasomes. For example, caspase activity was identified in a recent paper (Julien et al. PNAS 2016; PMID: 27006500). Similarly, tryptic and chymotryptic activities were identified in a separate paper (Winter et al. MBio 2016; PMID: 27624133). Therefore, our assay can detect these same specificities associated with the proteasome. However, since most of the specificity discovered in our study is chymotrypsin-like, we don’t believe that the assay lacks “sensitivity.”

5) The commercial preparations of the iP we used contain a significant portion of the β1 subunit from the cP. However, we are primarily detecting activity associated with the chymotrypsin-like subunit of the iP (LMP7) since it is the major activity of the proteasome. This is consistent with the development of the proteasome inhibitors carfilzomib and bortezomib, which target this subunit. Our assays detect the most dominantly cleaved substrates. However, we are also able to detect other activities as mentioned above.

6) Points: The reviewer misidentifies the false discovery rate (FDR) from the MS experiments. The "0.05" referred to is the maximum expectation value for peptide hits. The peptide FDR from our original paper introducing the MSP-MS assay is <0.17% (O’Donoghue et al. Nat Methods 2012; PMID 23023596). The reviewer also disagrees with the use of the universal LLVY fluorogenic substrate to normalize the proteasome input for the MSP-MS assays. However, our MSP-MS data proves that at the concentration used, LLVY cleavage is an appropriate normalization strategy because we achieve very similar numbers of cleavages for the two proteasomes against our unbiased MSP-MS library using this approach.

7) The sum total of the data presented in the paper suggests that if we were able to run the MSP-MS assay to its theoretical limit, each site cleaved by one proteasome would ultimately be cleaved by the other. For example, from the more sophisticated label-free quantitation in the MSP-MS assay performed with the MHC peptides (Figure 4), it is clear that even highly favored sequences are cleaved by the opposing proteasome at some rate. This is even the case for the optimized fluorogenic substrates. Therefore, our conclusion in the paper is that proteasome substrate specificity preferences (which clearly exist) primarily lead to differences in "quantity" of substrate cleavage and epitope generation, as opposed to strong “qualitative” differences.

Revisions to the Manuscript:

1) The Results section has been modified (subsection “Global Substrate Specificity Screen of the iP and cP”, first paragraph) to emphasize that the MSP-MS assay is being performed as a screening strategy for iP and cP cleavage and that discriminatory peptides have been identified with a particular emphasis on the β5/LMP7 subunits of the proteasome. We have also clarified that the β1 (caspase-like) activity is only a minor contributor to the overall cleavage profile (subsection “Global Substrate Specificity Screen of the iP and cP”, second paragraph and subsection “ProCISE Quantification of Proteasome Subunit Levels and IC50 Values”, last paragraph).

2) The limitations of the MSP-MS assay now have been stated in the Results section (subsection “Global Substrate Specificity Screen of the iP and cP”, first paragraph) to clarify the percentage of peptides that are being cleaved and why running the assay under longer or under other conditions would not provide additional information. We have also added a figure to illustrate this concept (Figure 1—figure supplement 2).

3) We have re-emphasized throughout the manuscript (Abstract, Results, and Discussion) that the substrate specificity differences displayed by the proteasome lead to predominately quantitative differences in substrate cleavage and epitope generation (as opposed to absolute differences in selectivity).

4) As requested by the reviewer, we have deposited the raw mass spectrometry data from the paper (subsection “Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS)”, last paragraph and subsection “MHC I Peptide Library Cleavage Assay”, last paragraph). We have also provided the mass spectrometry peptide reports and sequences for both the MSP-MS library (Figure 1—source data 1) and MHC library (Figure 4—source data 1).

https://doi.org/10.7554/eLife.27364.030

Article and author information

Author details

  1. Michael B Winter

    Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    Present address
    CytomX Therapeutics, South San Francisco, United States
    Contribution
    Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Writing—original draft, Writing—review and editing
    Contributed equally with
    Florencia La Greca and Shirin Arastu-Kapur
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4824-8024
  2. Florencia La Greca

    Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    Contribution
    Formal analysis, Investigation, Methodology, Writing—original draft, Writing—review and editing
    Contributed equally with
    Michael B Winter and Shirin Arastu-Kapur
    Competing interests
    No competing interests declared
  3. Shirin Arastu-Kapur

    1. Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    2. Onyx Pharmaceuticals, Inc., an Amgen subsidiary, San Francisco, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Project administration, Writing—review and editing
    Contributed equally with
    Michael B Winter and Florencia La Greca
    Competing interests
    Employee of Onyx Pharmaceuticals, Inc., an Amgen subsidiary
  4. Francesco Caiazza

    Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    Contribution
    Formal analysis, Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4228-1130
  5. Peter Cimermancic

    Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, United States
    Present address
    Verily Life Sciences, South San Francisco, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  6. Tonia J Buchholz

    Onyx Pharmaceuticals, Inc., an Amgen subsidiary, San Francisco, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Investigation, Methodology, Project administration, Writing—review and editing
    Competing interests
    Tonia J Buchholz: Employee of Onyx Pharmaceuticals, Inc., an Amgen subsidiary
  7. Janet L Anderl

    Onyx Pharmaceuticals, Inc., an Amgen subsidiary, San Francisco, United States
    Contribution
    Formal analysis, Investigation, Methodology, Writing—review and editing
    Competing interests
    Janet L Anderl: Employee of Onyx Pharmaceuticals, Inc., an Amgen subsidiary
  8. Matthew Ravalin

    Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    Contribution
    Conceptualization, Formal analysis, Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  9. Markus F Bohn

    Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    Contribution
    Conceptualization, Formal analysis, Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  10. Andrej Sali

    1. Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    2. Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, United States
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Project administration, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0435-6197
  11. Anthony J O'Donoghue

    Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, San Diego, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Writing—original draft, Project administration, Writing—review and editing
    Contributed equally with
    Charles S Craik
    For correspondence
    ajodonoghue@ucsd.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5695-0409
  12. Charles S Craik

    Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Project administration, Writing—review and editing
    Contributed equally with
    Anthony J O'Donoghue
    For correspondence
    charles.craik@ucsf.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7704-9185

Funding

National Institutes of Health (F32CA168150)

  • Michael B Winter

University of California, San Francisco (Program for Breakthrough Biomedical Research)

  • Michael B Winter
  • Matthew Ravalin
  • Charles S Craik

University of California, San Francisco (Enabling Technologies Advisory Committee)

  • Michael B Winter
  • Matthew Ravalin
  • Charles S Craik

National Institutes of Health (R21CA186077)

  • Andrej Sali
  • Charles S Craik

National Institutes of Health (R21AI133393)

  • Anthony J O'Donoghue

National Institutes of Health (P41CA196276)

  • Charles S Craik

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

Acknowledgements

Mass spectrometry was performed in collaboration with the UCSF Mass Spectrometry Facility (directed by Prof. Alma Burlingame). This work was supported by the UCSF and Onyx Oncology Innovation Alliance, National Institutes of Health (NIH) grants R21CA186077 (to AS and CSC), R21AI133393 (to AJO), P41CA196276 (to CSC), and P41GM103481 (UCSF Mass Spectrometry Facility), a UCSF Program for Breakthrough Biomedical Research (PBBR) award (to CSC, MBW, and MR), and a UCSF Enabling Technologies Advisory Committee (ETAC) award (to CSC, MBW, and MR). M.B.W. was supported by NIH postdoctoral fellowship F32CA168150. We gratefully acknowledge Dr. Cammie Edwards for program management of the UCSF-Onyx alliance. We also acknowledge Prof. Ryan Hernandez, Dr. Giselle Knudsen, Dr. Judd Hultquist, and Prof. Jason Gestwicki (UCSF) and Dr. Christopher Kirk (Kezar Life Sciences) for helpful discussions.

Reviewing Editor

  1. Michael A Marletta, University of California, Berkeley, United States

Publication history

  1. Received: March 31, 2017
  2. Accepted: November 11, 2017
  3. Version of Record published: November 28, 2017 (version 1)

Copyright

© 2017, Winter et al.

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

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