Defensin Interactions in Relation to Monoclonal and Disease-Related Proteinase 3 Antibodies Binding at the Catalytic Site.

Proteinase 3 (PR3) is a neutrophil granulocyte enzyme and an autoantigen found in several forms of vasculitis. Due to the diagnostic and clinical importance of antibodies (Abs) to PR3, it is important to characterize the protein and the nature of its epitopes. Here, we have characterized PR3 monoclonal antibodies (MAbs) and disease-associated Abs and their dependency on the PR3 structure and modifications, especially interactions with α-defensins. Three MAbs (HYB 172-01, 172-04, 172-05), which bind to PR3 in its native and denatured forms and provide the disulphide bridges, were intact. α-1-antitrypsin (AT) binds to purified human neutrophil granulocyte PR3 and inhibits its proteolytic activity, towards a small synthetic peptide substrate and a large protein substrate (casein). AT also inhibited the binding of the three MAbs to PR3, indicating that they bind in a region affected by AT binding. However, the MAbs did not inhibit PR3 proteolytic activity with a small substrate, showing that they bound at the active site without restricting access to the substrate cleft. Patient-derived Abs showed essentially the same characteristics as the MAbs, with important implications for vasculitis diagnostics and pathophysiology. Current findings illustrate that PR3 epitopes depend on the three-dimensional structure of the PR3/defensin complex, and that the epitopes depend to a smaller or larger degree on PR3/defensin associations.

Assessing Population Diversity of Brettanomyces Yeast Species and Identification of Strains for Brewing Applications.

Brettanomyces yeasts have gained popularity in many sectors of the biotechnological industry, specifically in the field of beer production, but also in wine and ethanol production. Their unique properties enable Brettanomyces to outcompete conventional brewer's yeast in industrially relevant traits such as production of ethanol and pleasant flavors. Recent advances in next-generation sequencing (NGS) and high-throughput screening techniques have facilitated large population studies allowing the selection of appropriate yeast strains with improved traits. In order to get a better understanding of Brettanomyces species and its potential for beer production, we sequenced the whole genome of 84 strains, which we make available to the scientific community and carried out several in vitro assays for brewing-relevant properties. The collection includes isolates from different substrates and geographical origin. Additionally, we have included two of the oldest Carlsberg Research Laboratory isolates. In this study, we reveal the phylogenetic pattern of Brettanomyces species by comparing the predicted proteomes of each strain. Furthermore, we show that the Brettanomyces collection is well described using similarity in genomic organization, and that there is a direct correlation between genomic background and phenotypic characteristics. Particularly, genomic patterns affecting flavor production, maltose assimilation, beta-glucosidase activity, and phenolic off-flavor (POF) production are reported. This knowledge yields new insights into Brettanomyces population survival strategies, artificial selection pressure, and loss of carbon assimilation traits. On a species-specific level, we have identified for the first time a POF negative Brettanomyces anomalus strain, without the main spoilage character of Brettanomyces species. This strain (CRL-90) has lost DaPAD1, making it incapable of converting ferulic acid to 4-ethylguaiacol (4-EG) and 4-ethylphenol (4-EP). This loss of function makes CRL-90 a good candidate for the production of characteristic Brettanomyces flavors in beverages, without the contaminant increase in POF. Overall, this study displays the potential of exploring Brettanomyces yeast species biodiversity to find strains with relevant properties applicable to the brewing industry.

Immunoglobulin G structure and rheumatoid factor epitopes.

Antibodies are important for immunity and exist in several classes (IgM, IgD, IgA, IgG, IgE). They are composed of symmetric dimeric molecules with two antigen binding regions (Fab) and a constant part (Fc), usually depicted as Y-shaped molecules. Rheumatoid factors found in patients with rheumatoid arthritis are autoantibodies binding to IgG and paradoxically appear to circulate in blood alongside with their antigen (IgG) without reacting with it. Here, it is shown that rheumatoid factors do not react with native IgG in solution, and that their epitopes only become accessible upon certain physico-chemical treatments (e.g. heat treatment at 57 °C), by physical adsorption on a hydrophobic surface or by antigen binding. Moreover, chemical cross-linking in combination with mass spectrometry showed that the native state of IgG is a compact (closed) form and that the Fab parts of IgG shield the Fc region and thereby control access of rheumatoid factors and presumably also some effector functions. It can be inferred that antibody binding to pathogen surfaces induces a conformational change, which exposes the Fc part with its effector sites and rheumatoid factor epitopes. This has strong implications for understanding antibody structure and physiology and necessitates a conceptual reformulation of IgG models.

Multi-omics characterization of the necrotrophic mycoparasite Saccharomycopsis schoenii.

Pathogenic yeasts and fungi are an increasing global healthcare burden, but discovery of novel antifungal agents is slow. The mycoparasitic yeast Saccharomycopsis schoenii was recently demonstrated to be able to kill the emerging multi-drug resistant yeast pathogen Candida auris. However, the molecular mechanisms involved in the predatory activity of S. schoenii have not been explored. To this end, we de novo sequenced, assembled and annotated a draft genome of S. schoenii. Using proteomics, we confirmed that Saccharomycopsis yeasts have reassigned the CTG codon and translate CTG into serine instead of leucine. Further, we confirmed an absence of all genes from the sulfate assimilation pathway in the genome of S. schoenii, and detected the expansion of several gene families, including aspartic proteases. Using Saccharomyces cerevisiae as a model prey cell, we honed in on the timing and nutritional conditions under which S. schoenii kills prey cells. We found that a general nutrition limitation, not a specific methionine deficiency, triggered predatory activity. Nevertheless, by means of genome-wide transcriptome analysis we observed dramatic responses to methionine deprivation, which were alleviated when S. cerevisiae was available as prey, and therefore postulate that S. schoenii acquired methionine from its prey cells. During predation, both proteomic and transcriptomic analyses revealed that S. schoenii highly upregulated and translated aspartic protease genes, probably used to break down prey cell walls. With these fundamental insights into the predatory behavior of S. schoenii, we open up for further exploitation of this yeast as a biocontrol yeast and/or source for novel antifungal agents.

Uncovering carbohydrate metabolism through a genotype-phenotype association study of 56 lactic acid bacteria genomes.

Owing to their unique potential to ferment carbohydrates, both homo- and heterofermentative lactic acid bacteria (LAB) are widely used in the food industry. Deciphering the genetic basis that determine the LAB fermentation type, and hence carbohydrate utilization, is paramount to optimize LAB industrial processes. Deep sequencing of 24 LAB species and comparison with 32 publicly available genome sequences provided a comparative data set including five major LAB genera for further analysis. Phylogenomic reconstruction confirmed Leuconostoc and Pediococcus species as independently emerging from the Lactobacillus genus, within one of the three phylogenetic clades identified. These clades partially grouped LABs according to their fermentation types, suggesting that some metabolic capabilities were independently acquired during LAB evolution. In order to apply a genome-wide association study (GWAS) at the multigene family level, utilization of 49 carbohydrates was also profiled for these 56 LAB species. GWAS results indicated that obligately heterofermentative species lack 1-phosphofructokinase, required for D-mannose degradation in the homofermentative pathway. Heterofermentative species were found to often contain the araBAD operon, involved in L-arabinose degradation, which is important for heterofermentation. Taken together, our results provide helpful insights into the genetic determinants of LAB carbohydrate metabolism, and opens for further experimental research, aiming at validating the role of these candidate genes for industrial applications.

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia.

BACKGROUND: Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D structure analysis has been utilised in order to discover indications of antigenic pressure. The latter has been mostly based on the 3D models of the clonotypic B cell receptor immunoglobulin (BcR IG) amino acid sequences. Therefore, their accuracy is directly dependent on the quality of the model construction algorithms and the specific methods used to compare the ensuing models. Thus far, reliable and robust methods that can group the IG 3D models based on their structural characteristics are missing. RESULTS: Here we propose a novel method for clustering a set of proteins based on their 3D structure focusing on 3D structures of BcR IG from a large series of patients with CLL. The method combines techniques from the areas of bioinformatics, 3D object recognition and machine learning. The clustering procedure is based on the extraction of 3D descriptors, encoding various properties of the local and global geometrical structure of the proteins. The descriptors are extracted from aligned pairs of proteins. A combination of individual 3D descriptors is also used as an additional method. The comparison of the automatically generated clusters to manual annotation by experts shows an increased accuracy when using the 3D descriptors compared to plain bioinformatics-based comparison. The accuracy is increased even more when using the combination of 3D descriptors. CONCLUSIONS: The experimental results verify that the use of 3D descriptors commonly used for 3D object recognition can be effectively applied to distinguishing structural differences of proteins. The proposed approach can be applied to provide hints for the existence of structural groups in a large set of unannotated BcR IG protein files in both CLL and, by logical extension, other contexts where it is relevant to characterize BcR IG structural similarity. The method does not present any limitations in application and can be extended to other types of proteins.

Human MHC-II with Shared Epitope Motifs Are Optimal Epstein-Barr Virus Glycoprotein 42 Ligands-Relation to Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disorder of unknown etiology, which is characterized by inflammation in the synovium and joint damage. Although the pathogenesis of RA remains to be determined, a combination of environmental (e.g., viral infections) and genetic factors influence disease onset. Especially genetic factors play a vital role in the onset of disease, as the heritability of RA is 50-60%, with the human leukocyte antigen (HLA) alleles accounting for at least 30% of the overall genetic risk. Some HLA-DR alleles encode a conserved sequence of amino acids, referred to as the shared epitope (SE) structure. By analyzing the structure of a HLA-DR molecule in complex with Epstein-Barr virus (EBV), the SE motif is suggested to play a vital role in the interaction of MHC II with the viral glycoprotein (gp) 42, an essential entry factor for EBV. EBV has been repeatedly linked to RA by several lines of evidence and, based on several findings, we suggest that EBV is able to induce the onset of RA in predisposed SE-positive individuals, by promoting entry of B-cells through direct contact between SE and gp42 in the entry complex.

A chromosome conformation capture ordered sequence of the barley genome.

Cereal grasses of the Triticeae tribe have been the major food source in temperate regions since the dawn of agriculture. Their large genomes are characterized by a high content of repetitive elements and large pericentromeric regions that are virtually devoid of meiotic recombination. Here we present a high-quality reference genome assembly for barley (Hordeum vulgare L.). We use chromosome conformation capture mapping to derive the linear order of sequences across the pericentromeric space and to investigate the spatial organization of chromatin in the nucleus at megabase resolution. The composition of genes and repetitive elements differs between distal and proximal regions. Gene family analyses reveal lineage-specific duplications of genes involved in the transport of nutrients to developing seeds and the mobilization of carbohydrates in grains. We demonstrate the importance of the barley reference sequence for breeding by inspecting the genomic partitioning of sequence variation in modern elite germplasm, highlighting regions vulnerable to genetic erosion.

Structural Characterization of Peptide Antibodies.

The role of proteins as very effective immunogens for the generation of antibodies is indisputable. Nevertheless, cases in which protein usage for antibody production is not feasible or convenient compelled the creation of a powerful alternative consisting of synthetic peptides. Synthetic peptides can be modified to obtain desired properties or conformation, tagged for purification, isotopically labeled for protein quantitation or conjugated to immunogens for antibody production. The antibodies that bind to these peptides represent an invaluable tool for biological research and discovery. To better understand the underlying mechanisms of antibody-antigen interaction here we present a pipeline developed by us to structurally classify immunoglobulin antigen binding sites and to infer key sequence residues and other variables that have a prominent role in each structural class.

Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected].

Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

Probing the structure of human protein disulfide isomerase by chemical cross-linking combined with mass spectrometry.

Protein disulfide-isomerase (PDI) is a four-domain flexible protein that catalyzes the formation of disulfide bonds in the endoplasmic reticulum. Here we have analyzed native PDI purified from human placenta by chemical cross-linking followed by mass spectrometry (CXMS). In addition to PDI the sample contained soluble calnexin and ERp72. Extensive cross-linking was observed within the PDI molecule, both intra- and inter-domain, as well as between the different components in the mixture. The high sensitivity of the analysis in the current experiments, combined with a likely promiscuous interaction pattern of the involved proteins, revealed relatively densely populated cross-link heat maps. The established X-ray structure of the monomeric PDI could be confirmed; however, the dimer as presented in the existing models does not seem to be prevalent in solution as modeling on the observed cross-links revealed new models of dimeric PDI. The observed inter-protein cross-links confirmed the existence of a peptide binding area on calnexin that binds strongly both PDI and ERp72. On the other hand, interaction sites on PDI and ERp72 could not be uniquely identified, indicating a more non-specific interaction pattern. BIOLOGICAL SIGNIFICANCE: The present work demonstrates the use of chemical cross-linking and mass spectrometry (CXMS) for the determination of a solution structure of natural human PDI and its interaction with the chaperones ERp72 and calnexin. The data shows that the dimeric structure of PDI may be more diverse than indicated by present models. We further observe that the temperature influences the cross-linking pattern of PDI, but this does not influence the overall folding pattern of the molecule.

Prediction of site-specific interactions in antibody-antigen complexes: the proABC method and server.

MOTIVATION: Antibodies or immunoglobulins are proteins of paramount importance in the immune system. They are extremely relevant as diagnostic, biotechnological and therapeutic tools. Their modular structure makes it easy to re-engineer them for specific purposes. Short of undergoing a trial and error process, these experiments, as well as others, need to rely on an understanding of the specific determinants of the antibody binding mode. RESULTS: In this article, we present a method to identify, on the basis of the antibody sequence alone, which residues of an antibody directly interact with its cognate antigen. The method, based on the random forest automatic learning techniques, reaches a recall and specificity as high as 80% and is implemented as a free and easy-to-use server, named prediction of Antibody Contacts. We believe that it can be of great help in re-design experiments as well as a guide for molecular docking experiments. The results that we obtained also allowed us to dissect which features of the antibody sequence contribute most to the involvement of specific residues in binding to the antigen. AVAILABILITY: http://www.biocomputing.it/proABC. CONTACT: anna.tramontano@uniroma1.it or paolo.marcatili@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Igs expressed by chronic lymphocytic leukemia B cells show limited binding-site structure variability.

Ag selection has been suggested to play a role in chronic lymphocytic leukemia (CLL) pathogenesis, but no large-scale analysis has been performed so far on the structure of the Ag-binding sites (ABSs) of leukemic cell Igs. We sequenced both H and L chain V(D)J rearrangements from 366 CLL patients and modeled their three-dimensional structures. The resulting ABS structures were clustered into a small number of discrete sets, each containing ABSs with similar shapes and physicochemical properties. This structural classification correlates well with other known prognostic factors such as Ig mutation status and recurrent (stereotyped) receptors, but it shows a better prognostic value, at least in the case of one structural cluster for which clinical data were available. These findings suggest, for the first time, to our knowledge, on the basis of a structural analysis of the Ab-binding sites, that selection by a finite quota of antigenic structures operates on most CLL cases, whether mutated or unmutated.

A database of immunoglobulins with integrated tools: DIGIT.

The DIGIT (Database of ImmunoGlobulins with Integrated Tools) database (http://biocomputing.it/digit) is an integrated resource storing sequences of annotated immunoglobulin variable domains and enriched with tools for searching and analyzing them. The annotations in the database include information on the type of antigen, the respective germline sequences and on pairing information between light and heavy chains. Other annotations, such as the identification of the complementarity determining regions, assignment of their structural class and identification of mutations with respect to the germline, are computed on the fly and can also be obtained for user-submitted sequences. The system allows customized BLAST searches and automatic building of 3D models of the domains to be performed.

The association of heavy and light chain variable domains in antibodies: implications for antigen specificity.

The antigen-binding site of immunoglobulins is formed by six regions, three from the light and three from the heavy chain variable domains, which, on association of the two chains, form the conventional antigen-binding site of the antibody. The mode of interaction between the heavy and light chain variable domains affects the relative position of the antigen-binding loops and therefore has an effect on the overall conformation of the binding site. In this article, we analyze the structure of the interface between the heavy and light chain variable domains and show that there are essentially two different modes for their interaction that can be identified by the presence of key amino acids in specific positions of the antibody sequences. We also show that the different packing modes are related to the type of recognized antigen.

Structural repertoire of immunoglobulin λ light chains.

The immunoglobulin λ isotype is present in nearly all vertebrates and plays an important role in the human immune system. Despite its importance, few systematic studies have been performed to analyze the structural conformation of its variable regions, contrary to what is the case for κ and heavy chains. We show here that an analysis of the structures of λ chains allows the definition of a discrete set of recurring conformations (canonical structures) of their hypervariable loops and, most importantly, the identification of sequence constraints that can be used to predict their structure. We also show that the structural repertoire of λ chains is different and more varied than that of the κ chains, consistently with the current view of the involvement of the two major light-chain families in complementary strategies of the immune system to ensure a fine tuning between diversity and stability in antigen recognition.