1,030 research outputs found

    In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing

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    The simplicity and potential of minimally invasive testing using sera from patients makes auto-antibody based biomarkers a very promising tool for use in cancer diagnostics. Protein microarrays have been used for the identification of such auto-antibody signatures. Because high throughput protein expression and purification is laborious, synthetic peptides might be a good alternative for microarray generation and multiplexed analyses. In this study, we designed 1185 antigenic peptides, deduced from proteins expressed by 642 cDNA expression clones found to be sero-reactive in both breast tumour patients and controls. The sero-reactive proteins and the corresponding peptides were used for the production of protein and peptide microarrays. Serum samples from females with benign and malignant breast tumours and healthy control sera (n=16 per group) were then analysed. Correct classification of the serum samples on peptide microarrays were 78% for discrimination of ‘malignant versus healthy controls’, 72% for ‘benign versus malignant’ and 94% for ‘benign versus controls’. On protein arrays, correct classification for these contrasts was 69%, 59% and 59%, respectively. The over-representation analysis of the classifiers derived from class prediction showed enrichment of genes associated with ribosomes, spliceosomes, endocytosis and the pentose phosphate pathway. Sequence analyses of the peptides with the highest sero-reactivity demonstrated enrichment of the zinc-finger domain. Peptides’ sero-reactivities were found negatively correlated with hydrophobicity and positively correlated with positive charge, high inter-residue protein contact energies and a secondary structure propensity bias. This study hints at the possibility of using in silico designed antigenic peptide microarrays as an alternative to protein microarrays for the improvement of tumour auto-antibody based diagnostics

    Systems Biology Approach Predicts Antibody Signature Associated with Brucella melitensis Infection in Humans

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    A complete understanding of the factors that determine selection of antigens recognized by the humoral immune response following infectious agent challenge is lacking. Here we illustrate a systems biology approach to identify the antibody signature associated with Brucella melitensis (Bm) infection in humans and predict proteomic features of serodiagnostic antigens. By taking advantage of a full proteome microarray expressing previously cloned 1406 and newly cloned 1640 Bm genes, we were able to identify 122 immunodominant antigens and 33 serodiagnostic antigens. The reactive antigens were then classified according to annotated functional features (COGs), computationally predicted features (e.g., subcellular localization, physical properties), and protein expression estimated by mass spectrometry (MS). Enrichment analyses indicated that membrane association and secretion were significant enriching features of the reactive antigens, as were proteins predicted to have a signal peptide, a single transmembrane domain, and outer membrane or periplasmic location. These features accounted for 67% of the serodiagnostic antigens. An overlay of the seroreactive antigen set with proteomic data sets generated by MS identified an additional 24%, suggesting that protein expression in bacteria is an additional determinant in the induction of Brucella-specific antibodies. This analysis indicates that one-third of the proteome contains enriching features that account for 91% of the antigens recognized, and after B. melitensis infection the immune system develops significant antibody titers against 10% of the proteins with these enriching features. This systems biology approach provides an empirical basis for understanding the breadth and specificity of the immune response to B. melitensis and a new framework for comparing the humoral responses against other microorganisms

    Serodiagnosis of Echinococcus spp. Infection: Explorative Selection of Diagnostic Antigens by Peptide Microarray

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    Crude or purified, somatic or metabolic extracts of native antigens are routinely used for the serodiagnosis of human helminthic infections. These antigens are often cross-reactive, i.e., recognized by sera from patients infected with heterologous helminth species. To overcome limitations in antigen production, test sensitivity and specificity, chemically synthesized peptides offer a pure and standardized alternative, provided they yield acceptable operative characteristics. Ongoing genome and proteome work create new resources for the identification of antigens. Making use of the growing amount of genomic and proteomic data available in public databases, we tested a bioinformatic procedure for the selection of potentially antigenic peptides from a collection of protein sequences including conceptually translated nucleotide sequence data of Echinococcus multilocularis and E. granulosus (Plathyhelminthes, Cestoda). The in silico selection was combined with high-throughput screening of peptides on microarray and systematic validation of reactive candidates in enzyme-linked immunosorbent assay. Our study proved the applicability of this approach for selection of peptide antigens with good diagnostic characteristics. Our results suggested the pooling of several peptides to reach a high level of sensitivity required for reliable immunodiagnosis

    Characterization of mutations in the receptor binding site of influenza A viruses determining virus host, tissue, and cell tropisms using systems biology approaches

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    Influenza A viruses (IAVs) cause occasional pandemics and seasonal epidemics, thus presenting continuous challenges to public health. Vaccination is the primary strategy for the prevention and control of influenza outbreaks. The antigenicity matched high-yield seed strain is critical for the success of influenza vaccine. Currently, there are several limitations for the influenza vaccine manufacture: 1) the conventional methods for generating such strains are time consuming; 2) egg-based vaccines, the predominant production platform, have several disadvantages including the emergence of viral antigenic variants that can be induced during egg passage; 3) vaccine seed viruses often do not grow efficiently in mammalian cell lines. Previous studies suggested that mutations in the receptor binding site (RBS) that locates at the globular head of the HA1 can change IAVs’ binding specificity, antigenicity, and yield and thus RBS would be an potential target for engineering vaccine seed strain. However, systematic analysis of the mutations on RBS affecting those viral phenotypes is lacking. Specifically, this dissertation has following aims: Firstly, we developed a novel method to rapidly generate high-yield candidate vaccine strains by integrating error-prone PCR, site-directed mutagenesis strategies, and reverse genetics. The error-prone PCR- based reverse genetic system could also be applied to gain-ofunction studies for influenza virus and other pathogens; Secondly, in this dissertation, we identified an Y161F mutation in the hemagglutinin (HA) that enhanced the infectivity and thermostability of virus without changing its original antigenic properties which would prompted the development of cell-based vaccines; Thirdly, the molecular mechanisms underlying host adaption of equine-origin influenza A(H3N8) virus from horses to dogs are unknown. This dissertation identified that a substitution of W222L in the HA of the equine-origin A(H3N8) virus facilitated its host adaption to dogs. This mutation increased binding avidity of the virus specifically to sialyl Lewis X motifs, which were found abundantly in the submucosal glands of dog trachea but not in equine trachea. To summary, this dissertation investigated the role of RBS in IAVs biology and expanded the current knowledge toward IAV vaccine strain engineering, IAV host adaption and evolution

    From Functional Genomics to Functional Immunomics: New Challenges, Old Problems, Big Rewards

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    The development of DNA microarray technology a decade ago led to the establishment of functional genomics as one of the most active and successful scientific disciplines today. With the ongoing development of immunomic microarray technology—a spatially addressable, large-scale technology for measurement of specific immunological response—the new challenge of functional immunomics is emerging, which bears similarities to but is also significantly different from functional genomics. Immunonic data has been successfully used to identify biological markers involved in autoimmune diseases, allergies, viral infections such as human immunodeficiency virus (HIV), influenza, diabetes, and responses to cancer vaccines. This review intends to provide a coherent vision of this nascent scientific field, and speculate on future research directions. We discuss at some length issues such as epitope prediction, immunomic microarray technology and its applications, and computation and statistical challenges related to functional immunomics. Based on the recent discovery of regulation mechanisms in T cell responses, we envision the use of immunomic microarrays as a tool for advances in systems biology of cellular immune responses, by means of immunomic regulatory network models

    Towards High-throughput Immunomics for Infectious Diseases: Use of Next-generation Peptide Microarrays for Rapid Discovery and Mapping of Antigenic Determinants

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    Complete characterization of antibody specificities associated to natural infections is expected to provide a rich source of serologic biomarkers with potential applications in molecular diagnosis, follow-up of chemotherapeutic treatments, and prioritization of targets for vaccine development. Here, we developed a highly-multiplexed platform based on next-generation high-density peptide microarrays to map these specificities in Chagas Disease, an exemplar of a human infectious disease caused by the protozoan Trypanosoma cruzi. We designed a high-density peptide microarray containing more than 175,000 overlapping 15mer peptides derived from T. cruzi proteins. Peptides were synthesized in situ on microarray slides, spanning the complete length of 457 parasite proteins with fully overlapped 15mers (1 residue shift). Screening of these slides with antibodies purified from infected patients and healthy donors demonstrated both a high technical reproducibility as well as epitope mapping consistency when compared with earlier low-throughput technologies. Using a conservative signal threshold to classify positive (reactive) peptides we identified 2,031 disease-specific peptides and 97 novel parasite antigens, effectively doubling the number of known antigens and providing a tenfold increase in the number of fine mapped antigenic determinants for this disease. Finally, further analysis of the chip data showed that optimizing the amount of sequence overlap of displayed peptides can increase the protein space covered in a single chip by at least ~3 fold without sacrificing sensitivity. In conclusion, we show the power of high-density peptide chips for the discovery of pathogen-specific linear B-cell epitopes from clinical samples, thus setting the stage for high-throughput biomarker discovery screenings and proteome-wide studies of immune responses against pathogens.Fil: Carmona, Santiago Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Schafer Nielsen, Morten. Schafer-N ApS; DinamarcaFil: Mucci, Juan Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Altech, J. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños ; ArgentinaFil: Balouz, Virginia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Tekiel, Valeria Sonia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Frasch, Alberto Carlos C.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Campetella, Oscar Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Buscaglia, Carlos Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Aguero, Fernan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; Argentin

    Molecular classification and prediction of metastatic potential in early malignant melanoma: improvement of prognostic accuracy by quantitative in situ proteomic analysis

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    The incidence of cutaneous malignant melanoma continues to increase every year, and remains the leading cause of skin cancer death in industrialized countries. In spite of the aggressive nature of advanced melanoma, there are no standard biological assays in clinical usage that can predict metastasis. This may be due, in part, to the inadequacy of reproducible assessment of protein expression using traditional immunohistochemistry. This dissertation will discuss the use of tissue microarrays combined with quantitative in situ molecular analysis of protein expression to allow prediction of melanoma metastasis. Through the identification and validation of novel prognostic biomarkers, we seek to identify subsets of patients that are at high or low risk for melanoma recurrence or melanoma-related death. Some of these biomarkers may also serve as potential targets for future biologic therapy in melanoma, a disease for which no effective medical treatment is currently available. We demonstrate that quantitative assessment of a small number of markers is predictive of metastasis and outcome, augmenting the current system of prognosis.The dissertation begins with a brief introduction on the current state of melanoma diagnosis, staging, and treatment, as well as a review of current efforts to understand the biology of melanoma progression and metastasis. The fundamentals of tissue microarray technology are then described. Critical aspects of quantitative immunohistochemistry, including a description of the Automated Quantitative Analysis (AQUA) system developed in our laboratory, are also addressed. The second chapter demonstrates the use of tissue microarray technology to examine melanoma specimens by the current field standard, with a study of activating transcription factor 2 (ATF2); an example of semi-quantitative immunohistochemical analysis of protein expression. The third chapter provides validation of the AQUA technology on melanoma tissue by evaluation of the human homologue of murine double minute 2 protein (HDM2). Chapter four demonstrates an example of the critical--and beneficial--aspect of subcellular compartmentalization that the AQUA system provides, demonstrating that the ratio of cytoplasmic-to-nuclear expression of activator protein 2 (AP-2) predicts outcome in melanoma patients. The last chapter draws these concepts together and presents results from the analysis of 50 protein biomarkers in melanoma. It also introduces the use of a number of statistical methods (traditional and novel) employed to develop an optimal biomarker set for future analyses

    Relationship between humoral response against hepatitis C virus and disease overcome

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    International audienceConclusionHumoral response against hepatitis C virus linear epitopes is partly modified according to the disease state. This study highlights the importance of considering relative quantities of antibodies with different specificities rather than the amount of each antibody.Hepatitis C virus infection leads to liver disease whose severity can range from mild to serious lifelong illness. However the parameters involved in the evolution of the disease are still unknown. Among other factors, the virus-elicited antibody profile is suspected to play a role in the outcome of the disease. Analysis of the relationship between anti-virus antibodies and disease state requires the analysis of a large number of serums from patients (hepatitis C virus+) and of epitopes from the viral proteins. Such a study would benefit from microarray-based screening systems that are appropriate for high-throughput assays.We used a method combining peptide chips and surface plasmon resonance imaging previously shown to be suitable for analyzing complex mediums and detecting peptide-protein interactions. 56 peptides covering the entire viral proteome were grafted on chips and their interaction with antibodies present in the 68 injected serums from infected and non-infected donors was measured. Statistical analyses were conducted to determine a possible relationship between antibodies (specificity and amount) and disease states.A good discrimination between infected and non-infected donors validated our approach, and several correlations between antibodies profiles and clinical parameters have been identified. In particular, we demonstrated that ratios between particular antibodies levels allow for accurate discrimination of patients according to their pathologic states

    Construction of tissue microarrays from prostate needle biopsy specimens

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    Needle biopsies are taken as standard diagnostic specimens for many cancers, but no technique exists for the high-throughput analysis of multiple individual immunohistochemical (IHC) markers using these samples. Here we present a simple and highly reliable technique for constructing tissue microarrays (TMAs) from prostatic needle biopsies. Serial sectioning of the TMAs, called ‘Checkerboard TMAs', facilitated expression analysis of multiple proteins using IHC markers. In total, 100% of the analysed biopsies within the TMA both preserved their antigenicity and maintained their morphology. Checkerboard TMAs will allow the use of needle biopsies (i) alongside other tissue specimens (trans-urethral resection of prostates and prostatectomies in the case of prostate cancer) in clinical correlation studies when searching for new prognostic markers, and (ii) in a diagnostic context for assessing expression of multiple proteins in cancers from patients prior to treatment

    Notable sequence homology of the ORF10 protein introspects the architecture of SARS-CoV-2

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    The current Coronavirus Disease 19 (COVID-19) pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) shows similar pathology to MERS and SARS-CoV, with a current estimated fatality rate of 1.4%. Open reading frame 10 (ORF10) is a unique SARS-CoV-2 accessory protein, which contains eleven cytotoxic T lymphocyte (CTL) epitopes each of nine amino acids in length. Twenty-two unique SARS-CoV-2 ORF10 variants have been identified based on missense mutations found in sequence databases. Some of these mutations are predicted to decrease the stability of ORF10 in silico physicochemical and structural comparative analyses were carried out on SARS-CoV-2 and Pangolin-CoV ORF10 proteins, which share 97.37% amino acid (aa) homology. Though there is a high degree of ORF10 protein similarity of SARS-CoV-2 and Pangolin-CoV, there are differences of these two ORF10 proteins related to their sub-structure (loop/coil region), solubility, antigenicity and shift from strand to coil at aa position 26 (tyrosine). SARS-CoV-2 ORF10, which is apparently expressed in vivo since reactive T cell clones are found in convalescent patients should be monitored for changes which could correlate with the pathogenesis of COVID-19
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