Human Experimental Challenge With Enterotoxigenic Escherichia coli Elicits Immune Responses to Canonical and Novel Antigens Relevant to Vaccine Development.

Background: Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrheal illness in the developing world. Enterotoxigenic E coli vaccinology has been challenged by genetic diversity and heterogeneity of canonical antigens. Examination of the antigenic breadth of immune responses associated with protective immunity could afford new avenues for vaccine development. Methods: Antibody lymphocyte supernatants (ALS) and sera from 20 naive human volunteers challenged with ETEC strain H10407 and from 10 volunteers rechallenged 4-6 weeks later with the same strain (9 of whom were completely protected on rechallenge) were tested against ETEC proteome microarrays containing 957 antigens. Results: Enterotoxigenic E coli challenge stimulated robust serum and mucosal (ALS) responses to canonical vaccine antigens (CFA/I, and the B subunit of LT) as well as a small number of antigens not presently targeted in ETEC vaccines. These included pathovar-specific secreted proteins (EtpA, EatA) as well as highly conserved E coli antigens including YghJ, flagellin, and pertactin-like autotransporter proteins, all of which have previously afforded protection against ETEC infection in preclinical studies. Conclusions: Taken together, studies reported here suggest that immune responses after ETEC infection involve traditional vaccine targets as well as a select number of more recently identified protein antigens that could offer additional avenues for vaccine development for these pathogens.

Towards Development of Improved Serodiagnostics for Tularemia by Use of Francisella tularensis Proteome Microarrays.

Tularemia in humans is caused mainly by two subspecies of the Gram-negative facultative anaerobe Francisella tularensis: F. tularensis subsp. tularensis (type A) and F. tularensis subsp. holarctica (type B). The current serological test for tularemia is based on agglutination of whole organisms, and the reactive antigens are not well understood. Previously, we profiled the antibody responses in type A and B tularemia cases in the United States using a proteome microarray of 1,741 different proteins derived from the type A strain Schu S4. Fifteen dominant antigens able to detect antibodies to both types of infection were identified, although these were not validated in a different immunoassay format. Since type A and B subspecies are closely related, we hypothesized that Schu S4 antigens would also have utility for diagnosing type B tularemia caused by strains from other geographic locations. To test this, we probed the Schu S4 array with sera from 241 type B tularemia cases in Spain. Despite there being no type A strains in Spain, we confirmed the responses against some of the same potential serodiagnostic antigens reported previously, as well as determined the responses against additional potential serodiagnostic antigens. Five potential serodiagnostic antigens were evaluated on immunostrips, and two of these (FTT1696/GroEL and FTT0975/conserved hypothetical protein) discriminated between the Spanish tularemia cases and healthy controls. We conclude that antigens from the type A strain Schu S4 are suitable for detection of antibodies from patients with type B F. tularensis infections and that these can be used for the diagnosis of tularemia in a deployable format, such as the immunostrip.

Plasmodium falciparum Protein Microarray Antibody Profiles Correlate With Protection From Symptomatic Malaria in Kenya.

BACKGROUND: Immunoglobulin G antibodies (Abs) to Plasmodium falciparum antigens have been associated with naturally acquired immunity to symptomatic malaria. METHODS: We probed protein microarrays covering 824 unique P. falciparum protein features with plasma from residents of a community in Kenya monitored for 12 weeks for (re)infection and symptomatic malaria after administration of antimalarial drugs. P. falciparum proteins recognized by Abs from 88 children (aged 1-14 years) and 86 adults (aged ≥ 18 years), measured at the beginning of the observation period, were ranked by Ab signal intensity. RESULTS: Abs from immune adults reacted with a total 163 of 824 P. falciparum proteins. Children gradually acquired Abs to the full repertoire of antigens recognized by adults. Abs to some antigens showed high seroconversion rates, reaching maximal levels early in childhood, whereas others did not reach adult levels until adolescence. No correlation between Ab signal intensity and time to (re)infection was observed. In contrast, Ab levels to 106 antigens were significantly higher in children who were protected from symptomatic malaria compared with those who were not. Abs to antigens predictive of protection included P. falciparum erythrocyte membrane protein 1, merozoite surface protein (MSP) 10, MSP2, liver-stage antigen 3, PF70, MSP7, and Plasmodium helical interspersed subtelomeric domain protein. CONCLUSIONS: Protein microarrays may be useful in the search for malaria antigens associated with protective immunity.

Incorporating post-translational modifications and unnatural amino acids into high-throughput modeling of protein structures.

MOTIVATION: Accurately predicting protein side-chain conformations is an important subproblem of the broader protein structure prediction problem. Several methods exist for generating fairly accurate models for moderate-size proteins in seconds or less. However, a major limitation of these methods is their inability to model post-translational modifications (PTMs) and unnatural amino acids. In natural living systems, the chemical groups added following translation are often critical for the function of the protein. In engineered systems, unnatural amino acids are incorporated into proteins to explore structure-function relationships and create novel proteins. RESULTS: We present a new version of SIDEpro to predict the side chains of proteins containing non-standard amino acids, including 15 of the most frequently observed PTMs in the Protein Data Bank and all types of phosphorylation. SIDEpro uses energy functions that are parameterized by neural networks trained from available data. For PTMs, the [Formula: see text] and [Formula: see text] accuracies are comparable with those obtained for the precursor amino acid, and so are the RMSD values for the atoms shared with the precursor amino acid. In addition, SIDEpro can accommodate any PTM or unnatural amino acid, thus providing a flexible prediction system for high-throughput modeling of proteins beyond the standard amino acids. AVAILABILITY AND IMPLEMENTATION: SIDEpro programs and Web server, rotamer libraries and data are available through the SCRATCH suite of protein structure predictors at http://scratch.proteomics.ics.uci.edu/

Submicroscopic and asymptomatic Plasmodium falciparum and Plasmodium vivax infections are common in western Thailand - molecular and serological evidence.

BACKGROUND: Malaria is a public health problem in parts of Thailand, where Plasmodium falciparum and Plasmodium vivax are the main causes of infection. In the northwestern border province of Tak parasite prevalence is now estimated to be less than 1% by microscopy. Nonetheless, microscopy is insensitive at low-level parasitaemia. The objective of this study was to assess the current epidemiology of falciparum and vivax malaria in Tak using molecular methods to detect exposure to and infection with parasites; in particular, the prevalence of asymptomatic infections and infections with submicroscopic parasite levels. METHODS: Three-hundred microlitres of whole blood from finger-prick were collected into capillary tubes from residents of a sentinel village and from patients at a malaria clinic. Pelleted cellular fractions were screened by quantitative PCR to determine parasite prevalence, while plasma was probed on a protein microarray displaying hundreds of P. falciparum and P. vivax proteins to obtain antibody response profiles in those individuals. RESULTS: Of 219 samples from the village, qPCR detected 25 (11.4%) Plasmodium sp. infections, of which 92% were asymptomatic and 100% were submicroscopic. Of 61 samples from the clinic patients, 27 (44.3%) were positive by qPCR, of which 25.9% had submicroscopic parasite levels. Cryptic mixed infections, misdiagnosed as single-species infections by microscopy, were found in 7 (25.9%) malaria patients. All sample donors, parasitaemic and non-parasitaemic alike, had serological evidence of parasite exposure, with 100% seropositivity to at least 54 antigens. Antigens significantly associated with asymptomatic infections were P. falciparum MSP2, DnaJ protein, putative E1E2 ATPase, and three others. CONCLUSION: These findings suggest that parasite prevalence is higher than currently estimated by local authorities based on the standard light microscopy. As transmission levels drop in Thailand, it may be necessary to employ higher throughput and sensitivity methods for parasite detection in the phase of malaria elimination.

Mapping the structural topology of the yeast 19S proteasomal regulatory particle using chemical cross-linking and probabilistic modeling.

Structural characterization of proteasome complexes is an essential step toward understanding the ubiquitin-proteasome system. Currently, high resolution structures are not available for the 26S proteasome holocomplex as well as its subcomplex, the 19S regulatory particle (RP). Here we have employed a novel integrated strategy combining chemical cross-linking with multistage tandem mass spectrometry to define the proximity of subunits within the yeast 19S RP to elucidate its topology. This has resulted in the identification of 174 cross-linked peptides of the yeast 19S RP, representing 43 unique lysine-lysine linkages within 24 nonredundant pair-wise subunit interactions. To map the spatial organization of the 19S RP, we have developed and utilized a rigorous probabilistic framework to derive maximum likelihood (ML) topologies based on cross-linked peptides determined from our analysis. Probabilistic modeling of the yeast 19S AAA-ATPase ring (i.e., Rpt1-6) has produced an ML topology that is in excellent agreement with known topologies of its orthologs. In addition, similar analysis was carried out on the 19S lid subcomplex, whose predicted ML topology corroborates recently reported electron microscopy studies. Together, we have demonstrated the effectiveness and potential of probabilistic modeling for unraveling topologies of protein complexes using cross-linking data. This report describes the first study of the 19S RP topology using a new integrated strategy combining chemical cross-linking, mass spectrometry, and probabilistic modeling. Our results have provided a solid foundation to advance our understanding of the 19S RP architecture at peptide level resolution. Furthermore, our methodology developed here is a valuable proteomic tool that can be generalized for elucidating the structures of protein complexes.

Application of a Novel Proteomic Microarray Reveals High Exposure to Diarrhoeagenic Escherichia coli among Children in Zambia Participating in a Phase I Clinical Trial.

Diarrhoeagenic E. coli (DEC) significantly contributes to the burden of diarrhoea among children. Currently, there is no approved vaccine against DEC, but several vaccines against the enterotoxigenic E. coli (ETEC) pathotype are in advanced clinical trial stages, including the ETVAX® vaccine, undergoing evaluation in Zambia. This study reports on the reactivity of antibodies from ETVAX® vaccine and placebo recipients in a phase I clinical trial to proteins derived from (DEC) other than ETEC. Plasma samples collected at two time points (prior to any vaccination and post-third dose vaccination) from 16 vaccinated and 4 placebo participants in a phase 1 clinical trial examining the safety, tolerability, and immunogenicity of ETVAX® with dmLT adjuvant were evaluated for IgG response to E. coli antigens other than ETEC using the Pan-DEC protein microarray. This was the first field application of the novel pan-DEC array as a new tool in assessing the antigenic breadth of antibody responses induced by the ETVAX vaccine, as well as to assess early life exposure to DEC pathotypes and other bacterial enteric pathogens. We observed that plasma obtained from ETVAX® and placebo recipients had high antibody reactivity to Ipa, SseC and EspB proteins. These findings suggest that there is high exposure early in life to DEC pathogens, like EPEC, EHEC, EAEC and EIEC in addition to ETEC, in the Zambian population. These immunological observations are consistent with the results of recent epidemiological studies assessing the etiology of diarrheal disease among infants and young children in Zambia.

Development of a novel cross-linking strategy for fast and accurate identification of cross-linked peptides of protein complexes.

Knowledge of elaborate structures of protein complexes is fundamental for understanding their functions and regulations. Although cross-linking coupled with mass spectrometry (MS) has been presented as a feasible strategy for structural elucidation of large multisubunit protein complexes, this method has proven challenging because of technical difficulties in unambiguous identification of cross-linked peptides and determination of cross-linked sites by MS analysis. In this work, we developed a novel cross-linking strategy using a newly designed MS-cleavable cross-linker, disuccinimidyl sulfoxide (DSSO). DSSO contains two symmetric collision-induced dissociation (CID)-cleavable sites that allow effective identification of DSSO-cross-linked peptides based on their distinct fragmentation patterns unique to cross-linking types (i.e. interlink, intralink, and dead end). The CID-induced separation of interlinked peptides in MS/MS permits MS(3) analysis of single peptide chain fragment ions with defined modifications (due to DSSO remnants) for easy interpretation and unambiguous identification using existing database searching tools. Integration of data analyses from three generated data sets (MS, MS/MS, and MS(3)) allows high confidence identification of DSSO cross-linked peptides. The efficacy of the newly developed DSSO-based cross-linking strategy was demonstrated using model peptides and proteins. In addition, this method was successfully used for structural characterization of the yeast 20 S proteasome complex. In total, 13 non-redundant interlinked peptides of the 20 S proteasome were identified, representing the first application of an MS-cleavable cross-linker for the characterization of a multisubunit protein complex. Given its effectiveness and simplicity, this cross-linking strategy can find a broad range of applications in elucidating the structural topology of proteins and protein complexes.

Computational and single-molecule force studies of a macro domain protein reveal a key molecular determinant for mechanical stability.

Resolving molecular determinants of mechanical stability of proteins is crucial in the rational design of advanced biomaterials for use in biomedical and nanotechnological applications. Here we present an interdisciplinary study combining bioinformatics screening, steered molecular dynamics simulations, protein engineering, and single-molecule force spectroscopy that explores the mechanical properties of a macro domain protein with mixed alpha + beta topology. The unique architecture is defined by a single seven-stranded beta-sheet in the core of the protein flanked by five alpha-helices. Unlike mechanically stable proteins studied thus far, the macro domain provides the distinct advantage of having the key load-bearing hydrogen bonds (H bonds) buried in the hydrophobic core protected from water attacks. This feature allows direct measurement of the force required to break apart the load-bearing H bonds under locally hydrophobic conditions. Steered molecular dynamics simulations predicted extremely high mechanical stability of the macro domain by using constant velocity and constant force methods. Single-molecule force spectroscopy experiments confirm the exceptional mechanical strength of the macro domain, measuring a rupture force as high as 570 pN. Furthermore, through selective deletion of shielding peptide segments, we examined the same key H bonds under hydrophilic environments in which the beta-strands are exposed to solvent and verify that the high mechanical stability of the macro domain results from excellent shielding of the load-bearing H bonds from competing water. Our study reveals that shielding water accessibility to the load-bearing strands is a critical molecular determinant for enhancing the mechanical stability of proteins.

Use of an ETEC Proteome Microarray to Evaluate Cross-Reactivity of ETVAX® Vaccine-Induced IgG Antibodies in Zambian Children.

Developing a broadly protective vaccine covering most ETEC variants has been elusive. The most clinically advanced candidate yet is an oral inactivated ETEC vaccine (ETVAX®). We report on the use of a proteome microarray for the assessment of cross-reactivity of anti-ETVAX® IgG antibodies against over 4000 ETEC antigens and proteins. We evaluated 40 (pre-and post-vaccination) plasma samples from 20 Zambian children aged 10-23 months that participated in a phase 1 trial investigating the safety, tolerability, and immunogenicity of ETVAX® adjuvanted with dmLT. Pre-vaccination samples revealed high IgG responses to a variety of ETEC proteins including classical ETEC antigens (CFs and LT) and non-classical antigens. Post-vaccination reactivity to CFA/I, CS3, CS6, and LTB was stronger than baseline among the vaccinated compared to the placebo group. Interestingly, we noted significantly high post-vaccination responses to three non-vaccine ETEC proteins: CS4, CS14, and PCF071 (p = 0.043, p = 0.028, and p = 0.00039, respectively), suggestive of cross-reactive responses to CFA/I. However, similar responses were observed in the placebo group, indicating the need for larger studies. We conclude that the ETEC microarray is a useful tool for investigating antibody responses to numerous antigens, especially because it may not be practicable to include all antigens in a single vaccine.

SIDEpro: a novel machine learning approach for the fast and accurate prediction of side-chain conformations.

Accurate protein side-chain conformation prediction is crucial for protein modeling and existing methods for the task are widely used; however, faster and more accurate methods are still required. Here we present a new machine learning approach to the problem where an energy function for each rotamer in a structure is computed additively over pairs of contacting atoms. A family of 156 neural networks indexed by amino acid and contacting atom types is used to compute these rotamer energies as a function of atomic contact distances. Although direct energy targets are not available for training, the neural networks can still be optimized by converting the energies to probabilities and optimizing these probabilities using Markov Chain Monte Carlo methods. The resulting predictor SIDEpro makes predictions by initially setting the rotamer probabilities for each residue from a backbone-dependent rotamer library, then iteratively updating these probabilities using the trained neural networks. After convergences of the probabilities, the side-chains are set to the highest probability rotamer. Finally, a post processing clash reduction step is applied to the models. SIDEpro represents a significant improvement in speed and a modest, but statistically significant, improvement in accuracy when compared with the state-of-the-art for rapid side-chain prediction method SCWRL4 on the following datasets: (1) 379 protein test set of SCWRL4; (2) 94 proteins from CASP9; (3) a set of seven large protein-only complexes; and (4) a ribosome with and without the RNA. Using the SCWRL4 test set, SIDEpro's accuracy (χ(1) 86.14%, χ(1+2) 74.15%) is slightly better than SCWRL4-FRM (χ(1) 85.43%, χ(1+2) 73.47%) and it is 7.0 times faster. On the same test set SIDEpro is clearly more accurate than SCWRL4-rigid rotamer model (RRM) (χ(1) 84.15%, χ(1+2) 71.24%) and 2.4 times faster. Evaluation on the additional test sets yield similar accuracy results with SIDEpro being slightly more accurate than SCWRL4-flexible rotamer model (FRM) and clearly more accurate than SCWRL4-RRM; however, the gap in CPU time is much more significant when the methods are applied to large protein complexes. SIDEpro is part of the SCRATCH suite of predictors and available from: http://scratch.proteomics.ics.uci.edu/.

Engineered synthetic polymer nanoparticles as IgG affinity ligands.

A process for the preparation of an abiotic protein affinity ligand is described. The affinity ligand, a synthetic polymer hydrogel nanoparticle (NP), is formulated with functional groups complementary to the surface presentation of the target protein. An iterative process is used to improve affinity by optimizing the composition and proportion of functional monomers. Since the polymer NPs are formed by a kinetically driven process, the sequence of functional monomers in the polymer chain is not controlled; only the average composition can be adjusted by the stoichiometry of the monomers in the feed. To compensate for this the hydrogel NP is lightly cross-linked resulting in chain flexibility that takes place on a submillisecond time scale allowing the polymer to "map" onto a protein surface with complementary functionality. In this study, we report a lightly cross-linked (2%) N-isopropyl acrylamide (NIPAm) synthetic polymer NP (50-65 nm) incorporating hydrophobic and carboxylate groups that binds with high affinity to the Fc fragment of IgG. The affinity and amount of NP bound to IgG is pH dependent. The hydrogel NP inhibits protein A binding to the Fc domain at pH 5.5, but not at pH 7.3. A computational analysis was used to identify potential NP-protein interaction sites. Candidates include a NP binding domain that overlaps with the protein A-Fc binding domain at pH 5.5. The computational analysis supports the inhibition experimental results and is attributed to the difference in the charged state of histidine residues. Affinity of the NP (3.5-8.5 nM) to the Fc domain at pH 5.5 is comparable to protein A at pH 7. These results establish that engineered synthetic polymer NPs can be formulated with an intrinsic affinity to a specific domain of a large biomacromolecule.

Biomimetic Design of Protein Nanomaterials for Hydrophobic Molecular Transport.

Biomaterials such as self-assembling biological complexes have demonstrated a variety of applications in materials science and nanotechnology. The functionality of protein-based materials, however, is often limited by the absence or locations of specific chemical conjugation sites. In this investigation, we developed a new strategy for loading organic molecules into the hollow cavity of a protein nanoparticle that relies only on non-covalent interactions, and we demonstrated its applicability in drug delivery. Based on a biomimetic model that incorporates multiple phenylalanines to create a generalized binding site, we retained and delivered the antitumor compound doxorubicin by redesigning a caged protein scaffold. Through an iterative combination of structural modeling and protein engineering, we obtained new variants of the E2 subunit of pyruvate dehydrogenase with varying levels of drug-carrying capabilities. We found that an increasing number of introduced phenylalanines within the scaffold cavity generally resulted in greater drug loading capacities. Drug loading levels could be achieved that were greater than conventional nanoparticle delivery systems. These protein nanoparticles containing doxorubicin were taken up by breast cancer cells and induced significant cell death. Our novel approach demonstrates a universal strategy to design de novo hydrophobic binding domains within protein-based scaffolds for molecular encapsulation and transport, and it broadens the ability to attach guest molecules to this class of materials.

The TY3 Gag3 spacer controls intracellular condensation and uncoating.

Cells expressing the yeast retrotransposon Ty3 form concentrated foci of Ty3 proteins and RNA within which virus-like particle (VLP) assembly occurs. Gag3, the major structural protein of the Ty3 retrotransposon, is composed of capsid (CA), spacer (SP), and nucleocapsid (NC) domains analogous to retroviral domains. Unlike the known SP domains of retroviruses, Ty3 SP is highly acidic. The current studies investigated the role of this domain. Although deletion of Ty3 SP dramatically reduced retrotransposition, significant Gag3 processing and cDNA synthesis occurred. Mutations that interfered with cleavage at the SP-NC junction disrupted CA-SP processing, cDNA synthesis, and electron-dense core formation. Mutations that interfered with cleavage of CA-SP allowed cleavage of the SP-NC junction, production of electron-dense cores, and cDNA synthesis but blocked retrotransposition. A mutant in which acidic residues of SP were replaced with alanine failed to form both Gag3 foci and VLPs. We propose a speculative "spring" model for Gag3 during assembly. In the first phase during concentration of Gag3 into foci, intramolecular interactions between negatively charged SP and positively charged NC domains of Gag3 limit multimerization. In the second phase, the NC domain binds RNA, and the bound form is stabilized by intermolecular interactions with the SP domain. These interactions promote CA domain multimerization. In the third phase, a negatively charged SP domain destabilizes the remaining CA-SP shell for cDNA release.

Rationally selected single-site mutants of the Thermoascus aurantiacus endoglucanase increase hydrolytic activity on cellulosic substrates.

Variants of the Thermoascus aurantiacus Eg1 enzyme with higher catalytic efficiency than wild-type were obtained via site-directed mutagenesis. Using a rational mutagenesis approach based on structural bioinformatics and evolutionary analysis, two positions (F16S and Y95F) were identified as priority sites for mutagenesis. The mutant and parent enzymes were expressed and secreted from Pichia pastoris and the single site mutants F16S and Y95F showed 1.7- and 4.0-fold increases in k(cat) and 1.5- and 2.5-fold improvements in hydrolytic activity on cellulosic substrates, respectively, while maintaining thermostability. Similar to the parent enzyme, the two variants were active between pH 4.0 and 8.0 and showed optimal activity at temperature 70°C at pH 5.0. The purified enzymes were active at 50°C for over 12 h and retained at least 80% of initial activity for 2 h at 70°C. In contrast to the improved hydrolysis seen with the single mutation enzymes, no improvement was observed with a third variant carrying a combination of both mutations, which instead showed a 60% reduction in catalytic efficiency. This work further demonstrates that non-catalytic amino acid residues can be engineered to enhance catalytic efficiency in pretreatment enzymes of interest.

Strong off-target antibody reactivity to malarial antigens induced by RTS,S/AS01E vaccination is associated with protection.

The RTS,S/AS01E vaccine targets the circumsporozoite protein (CSP) of the Plasmodium falciparum (P. falciparum) parasite. Protein microarrays were used to measure levels of IgG against 1000 P. falciparum antigens in 2138 infants (age 6-12 weeks) and children (age 5-17 months) from 6 African sites of the phase III trial, sampled before and at 4 longitudinal visits after vaccination. One month postvaccination, IgG responses to 17% of all probed antigens showed differences between RTS,S/AS01E and comparator vaccination groups, whereas no prevaccination differences were found. A small subset of antigens presented IgG levels reaching 4- to 8-fold increases in the RTS,S/AS01E group, comparable in magnitude to anti-CSP IgG levels (~11-fold increase). They were strongly cross-correlated and correlated with anti-CSP levels, waning similarly over time and reincreasing with the booster dose. Such an intriguing phenomenon may be due to cross-reactivity of anti-CSP antibodies with these antigens. RTS,S/AS01E vaccinees with strong off-target IgG responses had an estimated lower clinical malaria incidence after adjusting for age group, site, and postvaccination anti-CSP levels. RTS,S/AS01E-induced IgG may bind strongly not only to CSP, but also to unrelated malaria antigens, and this seems to either confer, or at least be a marker of, increased protection from clinical malaria.

High-throughput prediction of protein antigenicity using protein microarray data.

MOTIVATION: Discovery of novel protective antigens is fundamental to the development of vaccines for existing and emerging pathogens. Most computational methods for predicting protein antigenicity rely directly on homology with previously characterized protective antigens; however, homology-based methods will fail to discover truly novel protective antigens. Thus, there is a significant need for homology-free methods capable of screening entire proteomes for the antigens most likely to generate a protective humoral immune response. RESULTS: Here we begin by curating two types of positive data: (i) antigens that elicit a strong antibody response in protected individuals but not in unprotected individuals, using human immunoglobulin reactivity data obtained from protein microarray analyses; and (ii) known protective antigens from the literature. The resulting datasets are used to train a sequence-based prediction model, ANTIGENpro, to predict the likelihood that a protein is a protective antigen. ANTIGENpro correctly classifies 82% of the known protective antigens when trained using only the protein microarray datasets. The accuracy on the combined dataset is estimated at 76% by cross-validation experiments. Finally, ANTIGENpro performs well when evaluated on an external pathogen proteome for which protein microarray data were obtained after the initial development of ANTIGENpro. AVAILABILITY: ANTIGENpro is integrated in the SCRATCH suite of predictors available at http://scratch.proteomics.ics.uci.edu. CONTACT: pfbaldi@ics.uci.edu

Data-driven high-throughput prediction of the 3-D structure of small molecules: review and progress.

Accurate prediction of the 3-D structure of small molecules is essential in order to understand their physical, chemical, and biological properties, including how they interact with other molecules. Here, we survey the field of high-throughput methods for 3-D structure prediction and set up new target specifications for the next generation of methods. We then introduce COSMOS, a novel data-driven prediction method that utilizes libraries of fragment and torsion angle parameters. We illustrate COSMOS using parameters extracted from the Cambridge Structural Database (CSD) by analyzing their distribution and then evaluating the system's performance in terms of speed, coverage, and accuracy. Results show that COSMOS represents a significant improvement when compared to state-of-the-art prediction methods, particularly in terms of coverage of complex molecular structures, including metal-organics. COSMOS can predict structures for 96.4% of the molecules in the CSD (99.6% organic, 94.6% metal-organic), whereas the widely used commercial method CORINA predicts structures for 68.5% (98.5% organic, 51.6% metal-organic). On the common subset of molecules predicted by both methods, COSMOS makes predictions with an average speed per molecule of 0.15 s (0.10 s organic, 0.21 s metal-organic) and an average rmsd of 1.57 Å (1.26 Å organic, 1.90 Å metal-organic), and CORINA makes predictions with an average speed per molecule of 0.13s (0.18s organic, 0.08s metal-organic) and an average rmsd of 1.60 Å (1.13 Å organic, 2.11 Å metal-organic). COSMOS is available through the ChemDB chemoinformatics Web portal at http://cdb.ics.uci.edu/ .

A primary Chlamydia trachomatis genital infection of rhesus macaques identifies new immunodominant B-cell antigens.

To identify immunodominant antigens that elicit a humoral immune response following a primary and a secondary genital infection, rhesus monkeys were inoculated cervically with Chlamydia trachomatis serovar D. Serum samples were collected and probed with a protein microarray expressing 864/894 (96.4%) of the open reading frames of the C. trachomatis serovar D genome. The antibody response to the primary infection was analyzed in 72 serum samples from 12 inoculated monkeys. The following criteria were utilized to identify immunodominant antigens: proteins found to be recognized by at least 75% (9/12) of the infected monkeys with at least 15% elevations in signal intensity from week 0 to week 8 post infection. All infected monkeys developed Chlamydia specific serum antibodies. Eight proteins satisfied the selection criteria for immunodominant antigens: CT242 (OmpH-like protein), CT541 (mip), CT681 (ompA), CT381 (artJ), CT443 (omcB), CT119 (incA), CT486 (fliY), and CT110 (groEL). Of these, three antigens, CT119, CT486 and CT381, were not previously identified as immunodominant antigens using non-human primate sera. Following the secondary infection, the antibody responses to the eight immunodominant antigens were analyzed and found to be quite different in intensity and duration to the primary infection. In conclusion, these eight immunodominant antigens can now be tested for their ability to identify individuals with a primary C. trachomatis genital infection and to design vaccine strategies to protect against a primary infection with this pathogen.

Diverse Humoral Immune Responses in Younger and Older Adult COVID-19 Patients.

We sought to discover links between antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and patient clinical variables, cytokine profiles, and antibodies to endemic coronaviruses. Serum samples from 30 patients of younger (26 to 39 years) and older (69 to 83 years) age groups and with varying clinical severities ranging from outpatient to mechanically ventilated were collected and used to probe a novel multi-coronavirus protein microarray. This microarray contained variable-length overlapping fragments of SARS-CoV-2 spike (S), envelope (E), membrane (M), nucleocapsid (N), and open reading frame (ORF) proteins created through in vitro transcription and translation (IVTT). The array also contained SARS-CoV, Middle East respiratory syndrome coronavirus (MERS-CoV), human coronavirus OC43 (HCoV-OC43), and HCoV-NL63 proteins. IgG antibody responses to specific epitopes within the S1 protein region spanning amino acids (aa) 500 to 650 and within the N protein region spanning aa 201 to 300 were found to be significantly higher in older patients and further significantly elevated in those older patients who were ventilated. Additionally, there was a noticeable overlap between antigenic regions and known mutation locations in selected emerging SARS-CoV-2 variants of current clinical consequence (B.1.1.7, B1.351, P.1, CAL20.C, and B.1.526). Moreover, the older age group displayed more consistent correlations of antibody reactivity with systemic cytokine and chemokine responses than the younger adult group. A subset of patients, however, had little or no response to SARS-CoV-2 antigens and disproportionately severe clinical outcomes. Further characterization of these slow-low-responding individuals with cytokine analysis revealed significantly higher interleukin-10 (IL-10), IL-15, and interferon gamma-induced protein 10 (IP-10) levels and lower epidermal growth factor (EGF) and soluble CD40 ligand (sCD40L) levels than those of seroreactive patients in the cohort. IMPORTANCE As numerous viral variants continue to emerge in the coronavirus disease 2019 (COVID-19) pandemic, determining antibody reactivity to SARS-CoV-2 epitopes becomes essential in discerning changes in the immune response to infection over time. This study enabled us to identify specific areas of antigenicity within the SARS-CoV-2 proteome, allowing us to detect correlations of epitopes with clinical metadata and immunological signals to gain holistic insight into SARS-CoV-2 infection. This work also emphasized the risk of mutation accumulation in viral variants and the potential for evasion of the adaptive immune responses in the event of reinfection. We additionally highlighted the correlation of antigenicity between structural proteins of SARS-CoV-2 and endemic HCoVs, raising the possibility of cross-protection between homologous lineages. Finally, we identified a subset of patients with minimal antibody reactivity to SARS-CoV-2 infection, prompting discussion of the potential consequences of this alternative immune response.