An Overview of Peptides and Peptide Pools for Antigen-Specific Stimulation in T-Cell Assays.

The analysis of antigen-specific T-cell responses has become routine in many laboratories. Functional T-cell assays like enzyme-linked-immuno-spot (ELISPOT), which depend on antigen-specific stimulation, increasingly use peptides to represent the antigen of interest. Besides single peptides, mixtures of peptides (peptide pools) are very frequently applied. Such peptide pools may, for example, represent entire proteins (with overlapping peptides covering a protein sequence) or include noncontiguous peptides such as a collection of T-cell-stimulating peptides. The optimum specification of single peptides or peptide pools for T-cell stimulation assays will depend on the purpose of the test, the target T-cell population, the availability of sample, requirements regarding reproducibility, and, last but not least, the available budget, to mention only the most important factors. Because of the way peptides are produced, they will always contain certain amounts of impurities such as peptides with deletions or truncated peptides, and there may be additional by-products of peptide synthesis. Optimized synthesis protocols as well as purification help reduce impurities that might otherwise cause false-positive assay results. However, specific requirements with respect to purity will vary depending on the purpose of an assay. Finally, storage conditions significantly affect the shelf life of peptides, which is relevant especially for longitudinal studies. The present book chapter addresses all of these aspects in detail. It should provide the researcher with all necessary background knowledge for making the right decisions when it comes to choosing, using, and storing peptides for ELISPOT and other T-cell stimulation assays.

New method for peptide purification based on selective removal of truncation peptide impurities after SPPS with orthogonal capping.

Peptide purification by high-performance liquid chromatography (HPLC) is associated with high solvent consumption, relatively large effort and lack of efficient parallelization. As an alternative, many catch-and-release (c&r) purification methods have been developed over the last decades to enable the efficient parallel purification of peptides originating from solid-phase peptide synthesis (SPPS). However, with one exception, none of the c&r systems has been widely established in industry and academia until today. Herein, we present an entirely new chromatography-free purification concept for peptides synthesized on a solid support, termed reactive capping purification (RCP). The RCP method relies on the capping of truncation peptides arising from incomplete coupling of amino acids during SPPS with a reactive tag. The reactive tag contains a masked functionality that, upon liberation during cleavage from the resin, enables straightforward purification of the peptide by incubation with a resin-bound reactive moiety. In this work, two different reactive tags based on masked thiols were developed. Capping with these reactive tags during SPPS led to effective modification of truncated sequences and subsequent removal of the latter by chemoselective reaction with a maleimide-functionalized solid support. By introducing a suitable protecting group strategy, the thiol-based RCP method described here could also be successfully applied to a thiol-containing peptide. Finally, the purification of a 15-meric peptide by the RCP method was demonstrated. The developed method has low solvent consumption, has the potential for efficient parallelization, uses readily available reagents, and is experimentally simple to perform.

Primary ChAdOx1 vaccination does not reactivate pre-existing, cross-reactive immunity.

Currently available COVID-19 vaccines include inactivated virus, live attenuated virus, mRNA-based, viral vectored and adjuvanted protein-subunit-based vaccines. All of them contain the spike glycoprotein as the main immunogen and result in reduced disease severity upon SARS-CoV-2 infection. While we and others have shown that mRNA-based vaccination reactivates pre-existing, cross-reactive immunity, the effect of vector vaccines in this regard is unknown. Here, we studied cellular and humoral responses in heterologous adenovirus-vector-based ChAdOx1 nCOV-19 (AZ; Vaxzeria, AstraZeneca) and mRNA-based BNT162b2 (BNT; Comirnaty, BioNTech/Pfizer) vaccination and compared it to a homologous BNT vaccination regimen. AZ primary vaccination did not lead to measurable reactivation of cross-reactive cellular and humoral immunity compared to BNT primary vaccination. Moreover, humoral immunity induced by primary vaccination with AZ displayed differences in linear spike peptide epitope coverage and a lack of anti-S2 IgG antibodies. Contrary to primary AZ vaccination, secondary vaccination with BNT reactivated pre-existing, cross-reactive immunity, comparable to homologous primary and secondary mRNA vaccination. While induced anti-S1 IgG antibody titers were higher after heterologous vaccination, induced CD4+ T cell responses were highest in homologous vaccinated. However, the overall TCR repertoire breadth was comparable between heterologous AZ-BNT-vaccinated and homologous BNT-BNT-vaccinated individuals, matching TCR repertoire breadths after SARS-CoV-2 infection, too. The reasons why AZ and BNT primary vaccination elicits different immune response patterns to essentially the same antigen, and the associated benefits and risks, need further investigation to inform vaccine and vaccination schedule development.

T-cell proliferation assay for the detection of SARS-CoV-2-specific T-cells.

Both infection with and vaccination against SARS-CoV-2 trigger a complex B-cell and T-cell response. Methods for the analysis of the B-cell response are now well established. However, reliable methods for measuring the T-cell response are less well established and their usefulness in clinical settings still needs to be proven. Here, we have developed and validated a T-cell proliferation assay based on 3H thymidine incorporation. The assay is using SARS-CoV-2 derived peptide pools that cover the spike (S), the nucleocapsid (N) and the membrane (M) protein for stimulation. We have compared this novel SARS-CoV-2 lymphocyte transformation test (SARS-CoV-2 LTT) to an established ELISA assay detecting Immunoglobulin G (IgG) antibodies to the S1 subunit of the SARS-CoV-2 spike protein. The study was carried out using blood samples from both vaccinated and infected health care workers as well as from a non-infected control group. Our novel SARS-CoV-2 LTT shows excellent discrimination of infected and/or vaccinated individuals versus unexposed controls, with the ROC analysis showing an area under the curve (AUC) of > 0.95. No false positives were recorded as all unexposed controls had a negative LTT result. When using peptide pools not only representing the S protein (found in all currently approved vaccines) but also the N and M proteins (not contained in the vast majority of vaccines), the novel SARS-CoV-2 LTT can also discriminate T-cell responses resulting from vaccination against those induced by infection.

Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides.

The prediction of fragment ion intensities and retention time of peptides has gained significant attention over the past few years. However, the progress shown in the accurate prediction of such properties focused primarily on unlabeled peptides. Tandem mass tags (TMT) are chemical peptide labels that are coupled to free amine groups usually after protein digestion to enable the multiplexed analysis of multiple samples in bottom-up mass spectrometry. It is a standard workflow in proteomics ranging from single-cell to high-throughput proteomics. Particularly for TMT, increasing the number of confidently identified spectra is highly desirable as it provides identification and quantification information with every spectrum. Here, we report on the generation of an extensive resource of synthetic TMT-labeled peptides as part of the ProteomeTools project and present the extension of the deep learning model Prosit to accurately predict the retention time and fragment ion intensities of TMT-labeled peptides with high accuracy. Prosit-TMT supports CID and HCD fragmentation and ion trap and Orbitrap mass analyzers in a single model. Reanalysis of published TMT data sets show that this single model extracts substantial additional information. Applying Prosit-TMT, we discovered that the expression of many proteins in human breast milk follows a distinct daily cycle which may prime the newborn for nutritional or environmental cues.

Cross-reactive CD4+ T cells enhance SARS-CoV-2 immune responses upon infection and vaccination.

The functional relevance of preexisting cross-immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a subject of intense debate. Here, we show that human endemic coronavirus (HCoV)­reactive and SARS-CoV-2­cross-reactive CD4+ T cells are ubiquitous but decrease with age. We identified a universal immunodominant coronavirus-specific spike peptide (S816-830) and demonstrate that preexisting spike- and S816-830­reactive T cells were recruited into immune responses to SARS-CoV-2 infection and their frequency correlated with anti­SARS-CoV-2-S1-IgG antibodies. Spike­cross-reactive T cells were also activated after primary BNT162b2 COVID-19 messenger RNA vaccination and displayed kinetics similar to those of secondary immune responses. Our results highlight the functional contribution of preexisting spike­cross-reactive T cells in SARS-CoV-2 infection and vaccination. Cross-reactive immunity may account for the unexpectedly rapid induction of immunity after primary SARS-CoV-2 immunization and the high rate of asymptomatic or mild COVID-19 disease courses.

The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires.

Standardization of immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages to interrogate immunopeptidomics datasets and found that Peaks reproducibly reports substantially more peptide sequences (~30-70%) compared with Maxquant, Comet, and MS-GF+ at a global false discovery rate (FDR) of <1%. We noted that these differences are driven by search space and spectral ranking. Furthermore, we observed differences in the proportion of peptides binding the human leukocyte antigen (HLA) alleles present in the samples, indicating that sequence-related differences affected the performance of each tested engine. Utilizing data from single HLA allele expressing cell lines, we observed significant differences in amino acid frequency among the peptides reported, with a broadly higher representation of hydrophobic amino acids L, I, P, and V reported by Peaks. We validated these results using data generated with a synthetic library of 2000 HLA-associated peptides from four common HLA alleles with distinct anchor residues. Our investigation highlights that search engines create a bias in peptide sequence depth and peptide amino acid composition, and resulting data should be interpreted with caution.

Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics.

Characterizing the human leukocyte antigen (HLA) bound ligandome by mass spectrometry (MS) holds great promise for developing vaccines and drugs for immune-oncology. Still, the identification of non-tryptic peptides presents substantial computational challenges. To address these, we synthesized and analyzed >300,000 peptides by multi-modal LC-MS/MS within the ProteomeTools project representing HLA class I & II ligands and products of the proteases AspN and LysN. The resulting data enabled training of a single model using the deep learning framework Prosit, allowing the accurate prediction of fragment ion spectra for tryptic and non-tryptic peptides. Applying Prosit demonstrates that the identification of HLA peptides can be improved up to 7-fold, that 87% of the proposed proteasomally spliced HLA peptides may be incorrect and that dozens of additional immunogenic neo-epitopes can be identified from patient tumors in published data. Together, the provided peptides, spectra and computational tools substantially expand the analytical depth of immunopeptidomics workflows.

Peptide microarray-based analysis of antibody responses to SARS-CoV-2 identifies unique epitopes with potential for diagnostic test development.

Humoral immunity to the Severe Adult Respiratory Syndrome (SARS) Coronavirus (CoV)-2 is not fully understood yet but is a crucial factor of immune protection. The possibility of antibody cross-reactivity between SARS-CoV-2 and other human coronaviruses (HCoVs) would have important implications for immune protection but also for the development of specific diagnostic ELISA tests. Using peptide microarrays, n = 24 patient samples and n = 12 control samples were screened for antibodies against the entire SARS-CoV-2 proteome as well as the Spike (S), Nucleocapsid (N), VME1 (V), R1ab, and Protein 3a (AP3A) of the HCoV strains SARS, MERS, OC43, and 229E. While widespread cross-reactivity was revealed across several immunodominant regions of S and N, IgG binding to several SARS-CoV-2-derived peptides provided statistically significant discrimination between COVID-19 patients and controls. Selected target peptides may serve as capture antigens for future, highly COVID-19-specific diagnostic antibody tests.

SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the rapidly unfolding coronavirus disease 2019 (COVID-19) pandemic1,2. Clinical manifestations of COVID-19 vary, ranging from asymptomatic infection to respiratory failure. The mechanisms that determine such variable outcomes remain unresolved. Here we investigated CD4+ T cells that are reactive against the spike glycoprotein of SARS-CoV-2 in the peripheral blood of patients with COVID-19 and SARS-CoV-2-unexposed healthy donors. We detected spike-reactive CD4+ T cells not only in 83% of patients with COVID-19 but also in 35% of healthy donors. Spike-reactive CD4+ T cells in healthy donors were primarily active against C-terminal epitopes in the spike protein, which show a higher homology to spike glycoproteins of human endemic coronaviruses, compared with N-terminal epitopes. Spike-protein-reactive T cell lines generated from SARS-CoV-2-naive healthy donors responded similarly to the C-terminal region of the spike proteins of the human endemic coronaviruses 229E and OC43, as well as that of SARS-CoV-2. This results indicate that spike-protein cross-reactive T cells are present, which were probably generated during previous encounters with endemic coronaviruses. The effect of pre-existing SARS-CoV-2 cross-reactive T cells on clinical outcomes remains to be determined in larger cohorts. However, the presence of spike-protein cross-reactive T cells in a considerable fraction of the general population may affect the dynamics of the current pandemic, and has important implications for the design and analysis of upcoming trials investigating COVID-19 vaccines.

New Approaches for Absolute Quantification of Stable-Isotope-Labeled Peptide Standards for Targeted Proteomics Based on a UV Active Tag.

Targeted proteomics depends on the availability of stable isotope labeled (SIL) peptide standards, which for absolute protein quantification need to be absolutely quantified. In the present study, three new approaches for absolute quantification of SIL peptides are developed. All approaches rely on a quantification tag (Qtag) with a specific UV absorption. The Qtag is attached to the peptide during synthesis and is removed by tryptic digestion under standard proteomics workflow conditions. While one quantification method (method A) is designed to allow the fast and economic production of absolutely quantified SIL peptides, two other methods (methods B and C) are developed to enable the straightforward re-quantification of SIL peptides after reconstitution to control and monitor known problems related to peptide solubility, precipitation, and adhesion to vials. All methods yield consistent results when compared to each other and when compared to quantification by amino acid analysis. The precise quantitation methods are used to characterize the in vivo specificity of the H3 specific histone methyltransferase EZH2.

A non-functional neoepitope specific CD8+ T-cell response induced by tumor derived antigen exposure in vivo.

Cancer-associated mutations, mostly single nucleotide variations, can act as neoepitopes and prime targets for effective anti-cancer T-cell immunity. T cells recognizing cancer mutations are critical for the clinical activity of immune checkpoint blockade (ICB) and they are potent vaccine antigens. High frequencies of mutation-specific T cells are rarely spontaneously induced. Hence, therapies that broaden the tumor specific T-cell response are of interest. Here, we analyzed neoepitope-specific CD8+ T-cell responses mounted either spontaneously or after immunotherapy regimens, which induce local tumor inflammation and cell death, in mice bearing tumors of the widely used colon carcinoma cell line CT26. A comprehensive immune reactivity screening of 2474 peptides covering 628 transcribed CT26 point mutations was conducted. All tested treatment regimens were found to induce a single significant CD8+ T-cell response against a non-synonymous D733A point mutation in the Smc3 gene. Surprisingly, even though Smc3 D733A turned out to be the immune-dominant neoepitope in CT26 tumor bearing mice, neither T cells specific for this neoepitope nor their T cell receptors (TCRs) were able to recognize or lyse tumor cells. Moreover, vaccination with the D733A neoepitope did not result in anti-tumoral activity despite induction of specific T cells. This is to our knowledge the first report that neoepitope specific CD8+ T cells primed by tumor-released antigen exposure in vivo can be functionally irrelevant.

ProteomeTools: Systematic Characterization of 21 Post-translational Protein Modifications by Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) Using Synthetic Peptides.

The analysis of the post-translational modification (PTM) state of proteins using mass spectrometry-based bottom-up proteomic workflows has evolved into a powerful tool for the study of cellular regulatory events that are not directly encoded at the genome level. Besides frequently detected modifications such as phosphorylation, acetylation and ubiquitination, many low abundant or less frequently detected PTMs are known or postulated to serve important regulatory functions. To more broadly understand the LC-MS/MS characteristics of PTMs, we synthesized and analyzed ∼5,000 peptides representing 21 different naturally occurring modifications of lysine, arginine, proline and tyrosine side chains and their unmodified counterparts. The analysis identified changes in retention times, shifts of precursor charge states and differences in search engine scores between modifications. PTM-dependent changes in the fragmentation behavior were evaluated using eleven different fragmentation modes or collision energies. We also systematically investigated the formation of diagnostic ions or neutral losses for all PTMs, confirming 10 known and identifying 5 novel diagnostic ions for lysine modifications. To demonstrate the value of including diagnostic ions in database searching, we reprocessed a public data set of lysine crotonylation and showed that considering the diagnostic ions increases confidence in the identification of the modified peptides. To our knowledge, this constitutes the first broad and systematic analysis of the LC-MS/MS properties of common and rare PTMs using synthetic peptides, leading to direct applicable utility for bottom-up proteomic experiments.

PROCAL: A Set of 40 Peptide Standards for Retention Time Indexing, Column Performance Monitoring, and Collision Energy Calibration.

Beyond specific applications, such as the relative or absolute quantification of peptides in targeted proteomic experiments, synthetic spike-in peptides are not yet systematically used as internal standards in bottom-up proteomics. A number of retention time standards have been reported that enable chromatographic aligning of multiple LC-MS/MS experiments. However, only few peptides are typically included in such sets limiting the analytical parameters that can be monitored. Here, we describe PROCAL (ProteomeTools Calibration Standard), a set of 40 synthetic peptides that span the entire hydrophobicity range of tryptic digests, enabling not only accurate determination of retention time indices but also monitoring of chromatographic separation performance over time. The fragmentation characteristics of the peptides can also be used to calibrate and compare collision energies between mass spectrometers. The sequences of all selected peptides do not occur in any natural protein, thus eliminating the need for stable isotope labeling. We anticipate that this set of peptides will be useful for multiple purposes in individual laboratories but also aiding the transfer of data acquisition and analysis methods between laboratories, notably the use of spectral libraries.

Building ProteomeTools based on a complete synthetic human proteome.

We describe ProteomeTools, a project building molecular and digital tools from the human proteome to facilitate biomedical research. Here we report the generation and multimodal liquid chromatography-tandem mass spectrometry analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products, and we exemplify the utility of these data in several applications. The resource (available at http://www.proteometools.org) will be extended to >1 million peptides, and all data will be shared with the community via ProteomicsDB and ProteomeXchange.

Protective efficacy of adenovirus/protein vaccines against SIV challenges in rhesus monkeys.

Preclinical studies of viral vector-based HIV-1 vaccine candidates have previously shown partial protection against neutralization-resistant virus challenges in rhesus monkeys. In this study, we evaluated the protective efficacy of adenovirus serotype 26 (Ad26) vector priming followed by purified envelope (Env) glycoprotein boosting. Rhesus monkeys primed with Ad26 vectors expressing SIVsmE543 Env, Gag, and Pol and boosted with AS01B-adjuvanted SIVmac32H Env gp140 demonstrated complete protection in 50% of vaccinated animals against a series of repeated, heterologous, intrarectal SIVmac251 challenges that infected all controls. Protective efficacy correlated with the functionality of Env-specific antibody responses. Comparable protection was also observed with a similar Ad/Env vaccine against repeated, heterologous, intrarectal SHIV-SF162P3 challenges. These data demonstrate robust protection by Ad/Env vaccines against acquisition of neutralization-resistant virus challenges in rhesus monkeys.

H1N1 viral proteome peptide microarray predicts individuals at risk for H1N1 infection and segregates infection versus Pandemrix(®) vaccination.

A high content peptide microarray containing the entire influenza A virus [A/California/08/2009(H1N1)] proteome and haemagglutinin proteins from 12 other influenza A subtypes, including the haemagglutinin from the [A/South Carolina/1/1918(H1N1)] strain, was used to gauge serum IgG epitope signatures before and after Pandemrix(®) vaccination or H1N1 infection in a Swedish cohort during the pandemic influenza season 2009. A very narrow pattern of pandemic flu-specific IgG epitope recognition was observed in the serum from individuals who later contracted H1N1 infection. Moreover, the pandemic influenza infection generated IgG reactivity to two adjacent epitopes of the neuraminidase protein. The differential serum IgG recognition was focused on haemagglutinin 1 (H1) and restricted to classical antigenic sites (Cb) in both the vaccinated controls and individuals with flu infections. We further identified a novel epitope VEPGDKITFEATGNL on the Ca antigenic site (251-265) of the pandemic flu haemagglutinin, which was exclusively recognized in serum from individuals with previous vaccinations and never in serum from individuals with H1N1 infection (confirmed by RNA PCR analysis from nasal swabs). This epitope was mapped to the receptor-binding domain of the influenza haemagglutinin and could serve as a correlate of immune protection in the context of pandemic flu. The study shows that unbiased epitope mapping using peptide microarray technology leads to the identification of biologically and clinically relevant target structures. Most significantly an H1N1 infection induced a different footprint of IgG epitope recognition patterns compared with the pandemic H1N1 vaccine.

Mass-spectrometry-based draft of the human proteome.

Proteomes are characterized by large protein-abundance differences, cell-type- and time-dependent expression patterns and post-translational modifications, all of which carry biological information that is not accessible by genomics or transcriptomics. Here we present a mass-spectrometry-based draft of the human proteome and a public, high-performance, in-memory database for real-time analysis of terabytes of big data, called ProteomicsDB. The information assembled from human tissues, cell lines and body fluids enabled estimation of the size of the protein-coding genome, and identified organ-specific proteins and a large number of translated lincRNAs (long intergenic non-coding RNAs). Analysis of messenger RNA and protein-expression profiles of human tissues revealed conserved control of protein abundance, and integration of drug-sensitivity data enabled the identification of proteins predicting resistance or sensitivity. The proteome profiles also hold considerable promise for analysing the composition and stoichiometry of protein complexes. ProteomicsDB thus enables navigation of proteomes, provides biological insight and fosters the development of proteomic technology.

Peptide microarrays enable rapid mimotope optimization for pharmacokinetic analysis of the novel therapeutic antibody IMAB362.

As membrane proteins play an important role in a variety of life-threatening diseases, the development of therapeutic monoclonal antibodies against membrane proteins is of significant interest. Among many other requirements, the process of antibody drug development requires a set of tailor-made assays for the characterization of the antibodies and for monitoring their activity. Designing assays to characterize antibodies directed to membrane proteins is challenging, because the natural targets are often not available in a format that is compatible with a biochemical assay setup. Thus, alternatives that mimic the targeted membrane proteins are needed. In this study, we developed optimal peptidic mimotopes for the ELISA-based detection of the novel therapeutic antibody IMAB362 in biological samples. Initial hits were identified using phage display and these hits were optimized with the help of structure-activity relationship analysis on peptide microarrays. The optimized peptides showed binding constants in the low nanomolar to picomolar range, an improvement by a factor of up to 30 compared to the initial hits. The best mimotope (apparent KD = 0.15 nM) was successfully used for the ELISA-based quantification of IMAB362 in samples from a mouse pharmacokinetic study. The process described allows the rapid discovery of mimotopes for target proteins that are difficult to produce or handle, which can then be used in pre-clinical and clinical assays or for the purification of biological products.