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.

Immune profiling of SARS-CoV-2 epitopes in asymptomatic and symptomatic pediatric and adult patients.

BACKGROUND: The infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has unpredictable manifestations of coronavirus disease (COVID-19) and variable clinical course with some patients being asymptomatic whereas others experiencing severe respiratory distress, or even death. We aimed to evaluate the immunoglobulin G (IgG) response towards linear peptides on a peptide array containing sequences from SARS-CoV-2, Middle East respiratory syndrome-related coronavirus (MERS) and common-cold coronaviruses 229E, OC43, NL63 and HKU1 antigens, in order to identify immunological indicators of disease outcome in SARS-CoV-2 infected patients. METHODS: We included in the study 79 subjects, comprising 19 pediatric and 30 adult SARS-CoV-2 infected patients with increasing disease severity, from mild to critical illness, and 30 uninfected subjects who were vaccinated with one dose of SARS-CoV-2 spike mRNA BNT162b2 vaccine. Serum samples were analyzed by a peptide microarray containing 5828 overlapping 15-mer synthetic peptides corresponding to the full SARS-CoV-2 proteome and selected linear epitopes of spike (S), envelope (E) and membrane (M) glycoproteins as well as nucleoprotein (N) of MERS, SARS and coronaviruses 229E, OC43, NL63 and HKU1 (isolates 1, 2 and 5). RESULTS: All patients exhibited high IgG reactivity against the central region and C-terminus peptides of both SARS-CoV-2 N and S proteins. Setting the threshold value for serum reactivity above 25,000 units, 100% and 81% of patients with severe disease, 36% and 29% of subjects with mild symptoms, and 8% and 17% of children younger than 8-years reacted against N and S proteins, respectively. Overall, the total number of peptides in the SARS-CoV-2 proteome targeted by serum samples was much higher in children compared to adults. Notably, we revealed a differential antibody response to SARS-CoV-2 peptides of M protein between adults, mainly reacting against the C-terminus epitopes, and children, who were highly responsive to the N-terminus of M protein. In addition, IgG signals against NS7B, NS8 and ORF10 peptides were found elevated mainly among adults with mild (63%) symptoms. Antibodies towards S and N proteins of other coronaviruses (MERS, 229E, OC43, NL63 and HKU1) were detected in all groups without a significant correlation with SARS-CoV-2 antibody levels. CONCLUSIONS: Overall, our results showed that antibodies elicited by specific linear epitopes of SARS-CoV-2 proteome are age dependent and related to COVID-19 clinical severity. Cross-reaction of antibodies to epitopes of other human coronaviruses was evident in all patients with distinct profiles between children and adult patients. Several SARS-CoV-2 peptides identified in this study are of particular interest for the development of vaccines and diagnostic tests to predict the clinical outcome of SARS-CoV-2 infection.

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.

Pan-claudin family interactome analysis reveals shared and specific interactions.

Claudins are a family of transmembrane proteins expressed in epithelial tissues and are the major components of tight junctions (TJs), which define barrier properties in epithelia and maintain cell polarity. How claudins regulate the formation of TJs and which functions they exert outside of them is not entirely understood. Although the long and unstructured C-terminal tail is essential for regulation, it is unclear how it is involved in these functions beyond interacting with TJ-associated proteins such as TJ protein ZO-1 (TJP1). Here, we present an interactome study of the pan-claudin family in Madin-Darby canine kidney (MDCK)-C7 cells by combining two complementary mass spectrometry-based pull-down techniques creating an interaction landscape of the entire claudin family. The interaction partners of the claudins' C termini reveal their possible implications in localized biological processes in epithelial cells and their regulation by post-translational modifications (PTMs).

Expanding the Malaria Antibody Toolkit: Development and Characterisation of Plasmodium falciparum RH5, CyRPA, and CSP Recombinant Human Monoclonal Antibodies.

Malaria, an infection caused by apicomplexan parasites of the genus Plasmodium, continues to exact a significant toll on public health with over 200 million cases world-wide, and annual deaths in excess of 600,000. Considerable progress has been made to reduce malaria burden in endemic countries in the last two decades. However, parasite and mosquito resistance to frontline chemotherapies and insecticides, respectively, highlights the continuing need for the development of safe and effective vaccines. Here we describe the development of recombinant human antibodies to three target proteins from Plasmodium falciparum: reticulocyte binding protein homologue 5 (PfRH5), cysteine-rich protective antigen (PfCyRPA), and circumsporozoite protein (PfCSP). All three proteins are key targets in the development of vaccines for blood-stage or pre-erythrocytic stage infections. We have developed potent anti-PfRH5, PfCyRPA and PfCSP monoclonal antibodies that will prove useful tools for the standardisation of assays in preclinical research and the assessment of these antigens in clinical trials. We have generated some very potent anti-PfRH5 and anti-PfCyRPA antibodies with some clones >200 times more potent than the polyclonal anti-AMA-1 antibodies used for the evaluation of blood stage antigens. While the monoclonal and polyclonal antibodies are not directly comparable, the data provide evidence that these new antibodies are very good at blocking invasion. These antibodies will therefore provide a valuable resource and have potential as biological standards to help harmonise pre-clinical malaria research.

SARS-CoV-2 mRNA vaccinations fail to elicit humoral and cellular immune responses in patients with multiple sclerosis receiving fingolimod.

BACKGROUND: SARS-CoV-2 mRNA vaccination of healthy individuals is highly immunogenic and protective against severe COVID-19. However, there are limited data on how disease-modifying therapies (DMTs) alter SARS-CoV-2 mRNA vaccine immunogenicity in patients with autoimmune diseases. METHODS: As part of a prospective cohort study, we investigated the induction, stability and boosting of vaccine-specific antibodies, B cells and T cells in patients with multiple sclerosis (MS) on different DMTs after homologous primary, secondary and booster SARS-CoV-2 mRNA vaccinations. Of 126 patients with MS analysed, 105 received either anti-CD20-based B cell depletion (aCD20-BCD), fingolimod, interferon-ß, dimethyl fumarate, glatiramer acetate, teriflunomide or natalizumab, and 21 were untreated MS patients for comparison. RESULTS: In contrast to all other MS patients, and even after booster, most aCD20-BCD- and fingolimod-treated patients showed no to markedly reduced anti-S1 IgG, serum neutralising activity and a lack of receptor binding domain-specific and S2-specific B cells. Patients receiving fingolimod additionally lacked spike-reactive CD4+ T cell responses. The duration of fingolimod treatment, rather than peripheral blood B and T cell counts prior to vaccination, determined whether a humoral immune response was elicited. CONCLUSIONS: The lack of immunogenicity under long-term fingolimod treatment demonstrates that functional immune responses require not only immune cells themselves, but also access of these cells to the site of inoculation and their unimpeded movement. The absence of humoral and T cell responses suggests that fingolimod-treated patients with MS are at risk for severe SARS-CoV-2 infections despite booster vaccinations, which is highly relevant for clinical decision-making and adapted protective measures, particularly considering additional recently approved sphingosine-1-phosphate receptor antagonists for MS treatment.

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.

Profiling the HCV Immune Response in Patients with Chronic Liver Diseases and Hepatocellular Carcinoma by Peptide Microarray Analysis.

BACKGROUND: Chronic infection with hepatitis C virus (HCV) is among the major causes of hepatic fibrosis, cirrhosis, as well as hepatocellular carcinoma (HCC), and it is associated with a significant risk of developing lymphoproliferative disorders. The rate of clinical disease progression is variable depending on multiple host and viral factors, including immune response. METHODS: To perform a comprehensive epitope mapping of anti-HCV antibodies in patients suffering from HCV-related liver or lymphoproliferative diseases, we analyzed clinical samples on a peptide microarray platform made of 5952 overlapping 15-mer synthetic peptides derived from the whole HCV proteome. We evaluated the antibody profile of 71 HCV-positive patients diagnosed with HCC, mixed cryoglobulinemia (MC), and HCV chronic infection. Antibody reactivity against virus peptides was detected in all HCVpositive patients. Importantly, the signal amplitude varied significantly within and between diverse patient groups. RESULTS: Antibody reactivity against C peptides were found generally low in HCV chronically infected asymptomatic subjects and increasingly high in HCC and MC patients. Moreover, we found a statistically significant higher IgG response in HCC and MC patients against specific domains of HCV C, E2, NS3, NS4A, NS4B, NS5A, and p7 compared to HCV-positive subjects. CONCLUSION: In conclusion, our data suggest that immune response against specific HCV protein domains may represent useful biomarkers of disease progression among HCVpositive patients and suggest that peptide microarrays are good tools for the screening of immunotherapy targets in preclinical HCV research.

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.

A Universal Peptide Matrix Interactomics Approach to Disclose Motif-Dependent Protein Binding.

Protein-protein interactions mediated by intrinsically disordered regions are often based on short linear motifs (SLiMs). SLiMs are implicated in signal transduction and gene regulation yet remain technically laborious and notoriously challenging to study. Here, we present an optimized method for a protein interaction screen on a peptide matrix (PRISMA) in combination with quantitative MS. The protocol was benchmarked with previously described SLiM-based protein-protein interactions using peptides derived from EGFR, SOS1, GLUT1, and CEBPB and extended to map binding partners of kinase activation loops. The detailed protocol provides practical considerations for setting up a PRISMA screen and subsequently implementing PRISMA on a liquid-handling robotic platform as a cost-effective high-throughput method. Optimized PRISMA can be universally applied to systematically study SLiM-based interactions and associated post-translational modifications or mutations to advance our understanding of the largely uncharacterized interactomes of intrinsically disordered protein regions.

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.

PRISMA and BioID disclose a motifs-based interactome of the intrinsically disordered transcription factor C/EBPα.

C/EBPα represents a paradigm intrinsically disordered transcription factor containing short linear motifs and post-translational modifications (PTM). Unraveling C/EBPα protein interaction networks is a prerequisite for understanding the multi-modal functions of C/EBPα in hematopoiesis and leukemia. Here, we combined arrayed peptide matrix screening (PRISMA) with BioID to generate an in vivo validated and isoform specific interaction map of C/EBPα. The myeloid C/EBPα interactome comprises promiscuous and PTM-regulated interactions with protein machineries involved in gene expression, epigenetics, genome organization, DNA replication, RNA processing, and nuclear transport. C/EBPα interaction hotspots coincide with homologous conserved regions of the C/EBP family that also score as molecular recognition features. PTMs alter the interaction spectrum of C/EBP-motifs to configure a multi-valent transcription factor hub that interacts with multiple co-regulatory components, including BAF/SWI-SNF or Mediator complexes. Combining PRISMA and BioID is a powerful strategy to systematically explore the PTM-regulated interactomes of intrinsically disordered transcription factors.

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.

Multiplex enzyme activity imaging by MALDI-IMS of substrate library conversions.

Enzymes are fundamental to biological processes and involved in most pathologies. Here we demonstrate the concept of simultaneously mapping multiple enzyme activities (EA) by applying enzyme substrate libraries to tissue sections and analyzing their conversion by matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). To that end, we spray-applied a solution of 20 naturally derived peptides that are known substrates for proteases, kinases, and phosphatases to zinc-fixed paraffin tissue sections of mouse kidneys. After enzyme conversion for 5 to 120 min at 37 °C and matrix application, the tissue sections were imaged by MALDI-IMS. We could image incubation time-dependently 16 of the applied substrates with differing signal intensities and 12 masses of expected products. Utilizing inherent enzyme amplification, EA-IMS can become a powerful tool to locally study multiple, potentially even lowly expressed, enzyme activities, networks, and their pharmaceutical modulation. Differences in the substrate detectability highlight the need for future optimizations.

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.

Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.

In mass-spectrometry-based proteomics, the identification and quantification of peptides and proteins heavily rely on sequence database searching or spectral library matching. The lack of accurate predictive models for fragment ion intensities impairs the realization of the full potential of these approaches. Here, we extended the ProteomeTools synthetic peptide library to 550,000 tryptic peptides and 21 million high-quality tandem mass spectra. We trained a deep neural network, termed Prosit, resulting in chromatographic retention time and fragment ion intensity predictions that exceed the quality of the experimental data. Integrating Prosit into database search pipelines led to more identifications at >10× lower false discovery rates. We show the general applicability of Prosit by predicting spectra for proteases other than trypsin, generating spectral libraries for data-independent acquisition and improving the analysis of metaproteomes. Prosit is integrated into ProteomicsDB, allowing search result re-scoring and custom spectral library generation for any organism on the basis of peptide sequence alone.

Envelope-Specific Recognition Patterns of HIV Vaccine-Induced IgG Antibodies Are Linked to Immunogen Structure and Sequence.

Background: A better understanding of the parameters influencing vaccine-induced IgG recognition of individual antigenic regions and their variants within the HIV Envelope protein (Env) can help to improve design of preventive HIV vaccines. Methods: Env-specific IgG responses were mapped in samples of the UKHVC003 Standard Group (UK003SG, n = 11 from UK) and TaMoVac01 (TMV01, n = 17 from Tanzania) HIV vaccine trials. Both trials consisted of three immunizations with DNA, followed by two boosts with recombinant Modified Vaccinia Virus Ankara (MVA), either mediating secretion of gp120 (UK003SG) or the presentation of cell membrane bound gp150 envelopes (TMV01) from infected cells, and an additional two boosts with 5 µg of CN54gp140 protein adjuvanted with glucopyranosyl lipid adjuvant (GLA). Env immunogen sequences in UK003SG were solely based on the clade C isolate CN54, whereas in TMV01 these were based on clades A, C, B, and CRF01AE. The peptide microarray included 8 globally representative Env sequences, CN54gp140 and the MVA-encoded Env immunogens from both trials, as well as additional peptide variants for hot spots of immune recognition. Results: After the second MVA boost, UK003SG vaccinees almost exclusively targeted linear, non-glycosylated antigenic regions located in the inter-gp120 interface. In contrast, TMV01 recipients most strongly targeted the V2 region and an immunodominant region in gp41. The V3 region was frequently targeted in both trials, with a higher recognition magnitude for diverse antigenic variants observed in the UK003SG (p < 0.0001). After boosting with CN54gp140/GLA, the overall response magnitude increased with a more comparable recognition pattern of antigenic regions and variants between the two trials. Recognition of most immunodominant regions within gp120 remained significantly stronger in UK003SG, whereas V2-region recognition was not boosted in either group. Conclusions: IgG recognition of linear antigenic Env regions differed between the two trials particularly after the second MVA boost. Structural features of the MVA-encoded immunogens, such as secreted, monomeric gp120 vs. membrane-anchored, functional gp150, and differences in prime-boost immunogen sequence variability most probably contributed to these differences. Prime-boosting with multivalent Env immunogens during TMV01 did not improve variant cross-recognition of immunodominant peptide variants in the V3 region.