Protein Microarrays for High Throughput Hydrogen/Deuterium Exchange Monitored by FTIR Imaging.

Proteins form the fastest-growing therapeutic class. Due to their intrinsic instability, loss of native structure is common. Structure alteration must be carefully evaluated as structural changes may jeopardize the efficiency and safety of the protein-based drugs. Hydrogen deuterium exchange (HDX) has long been used to evaluate protein structure and dynamics. The rate of exchange constitutes a sensitive marker of the conformational state of the protein and of its stability. It is often monitored by mass spectrometry. Fourier transform infrared (FTIR) spectroscopy is another method with very promising capabilities. Combining protein microarrays with FTIR imaging resulted in high throughput HDX FTIR measurements. BaF2 slides bearing the protein microarrays were covered by another slide separated by a spacer, allowing us to flush the cell continuously with a flow of N2 gas saturated with 2H2O. Exchange occurred simultaneously for all proteins and single images covering ca. 96 spots of proteins that could be recorded on-line at selected time points. Each protein spot contained ca. 5 ng protein, and the entire array covered 2.5 × 2.5 mm2. Furthermore, HDX could be monitored in real time, and the experiment was therefore not subject to back-exchange problems. Analysis of HDX curves by inverse Laplace transform and by fitting exponential curves indicated that quantitative comparison of the samples is feasible. The paper also demonstrates how the whole process of analysis can be automatized to yield fast analyses.

Revisiting the antigen markers of vector-borne parasitic diseases identified by immunomics: identification and application to disease control.

INTRODUCTION: Protein microarray is a promising immunomic approach for identifying biomarkers. Based on our previous study that reviewed parasite antigens and recent parasitic omics research, this article expands to include information on vector-borne parasitic diseases (VBPDs), namely, malaria, schistosomiasis, leishmaniasis, babesiosis, trypanosomiasis, lymphatic filariasis, and onchocerciasis. AREAS COVERED: We revisit and systematically summarize antigen markers of vector-borne parasites identified by the immunomic approach and discuss the latest advances in identifying antigens for the rational development of diagnostics and vaccines. The applications and challenges of this approach for VBPD control are also discussed. EXPERT OPINION: The immunomic approach has enabled the identification and/or validation of antigen markers for vaccine development, diagnosis, disease surveillance, and treatment. However, this approach presents several challenges, including limited sample size, variability in antigen expression, false-positive results, complexity of omics data, validation and reproducibility, and heterogeneity of diseases. In addition, antigen involvement in host immune evasion and antigen sensitivity/specificity are major issues in its application. Despite these limitations, this approach remains promising for controlling VBPD. Advances in technology and data analysis methods should continue to improve candidate antigen identification, as well as the use of a multiantigen approach in diagnostic and vaccine development for VBPD control.

A Bayesian hierarchical model for signal extraction from protein microarrays.

Protein microarrays are a promising technology that measure protein levels in serum or plasma samples. Due to their high technical variability and high variation in protein levels across serum samples in any population, directly answering biological questions of interest using protein microarray measurements is challenging. Analyzing preprocessed data and within-sample ranks of protein levels can mitigate the impact of between-sample variation. As for any analysis, ranks are sensitive to preprocessing, but loss function based ranks that accommodate major structural relations and components of uncertainty are very effective. Bayesian modeling with full posterior distributions for quantities of interest produce the most effective ranks. Such Bayesian models have been developed for other assays, for example, DNA microarrays, but modeling assumptions for these assays are not appropriate for protein microarrays. Consequently, we develop and evaluate a Bayesian model to extract the full posterior distribution of normalized protein levels and associated ranks for protein microarrays, and show that it fits well to data from two studies that use protein microarrays produced by different manufacturing processes. We validate the model via simulation and demonstrate the downstream impact of using estimates from this model to obtain optimal ranks.

Systematic Evaluation of Antigenic Stimulation in Chronic Lymphocytic Leukemia: Humoral Immunity as Biomarkers for Disease Evolution.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the Western world. Studies of CLL antibody reactivity have shown differential targets to autoantigens and antimicrobial molecular motifs that support the current hypothesis of CLL pathogenesis. METHODS: In this study, we conducted a quantitative serum analysis of 7 immunoglobulins in CLL and monoclonal B-cell lymphocytosis (MBL) patients (bead-suspension protein arrays) and a serological profile (IgG and IgM) study of autoantibodies and antimicrobial antigens (protein microarrays). RESULTS: Significant differences in the IgA levels were observed according to disease progression and evolution as well as significant alterations in IgG1 according to IGHV mutational status. More representative IgG autoantibodies in the cohort were against nonmutagenic proteins and IgM autoantibodies were against vesicle proteins. Antimicrobial IgG and IgM were detected against microbes associated with respiratory tract infections. CONCLUSIONS: Quantitative differences in immunoglobulin serum levels could be potential biomarkers for disease progression. In the top 5 tumoral antigens, we detected autoantibodies (IgM and IgG) against proteins related to cell homeostasis and metabolism in the studied cohort. The top 5 microbial antigens were associated with respiratory and gastrointestinal infections; moreover, the subsets with better prognostics were characterized by a reactivation of Cytomegalovirus. The viral humoral response could be a potential prognosis biomarker for disease progression.

Antibody Profiling and In Silico Functional Analysis of Differentially Reactive Antibody Signatures of Glioblastomas and Meningiomas.

Studies on tumor-associated antigens in brain tumors are sparse. There is scope for enhancing our understanding of molecular pathology, in order to improve on existing forms, and discover new forms, of treatment, which could be particularly relevant to immuno-oncological strategies. To elucidate immunological differences, and to provide another level of biological information, we performed antibody profiling, based on a high-density protein array (containing 8173 human transcripts), using IgG isolated from the sera of n = 12 preoperative and n = 16 postoperative glioblastomas, n = 26 preoperative and n = 29 postoperative meningiomas, and n = 27 healthy, cancer-free controls. Differentially reactive antigens were compared to gene expression data from an alternate public GBM data set from OncoDB, and were analyzed using the Reactome pathway browser. Protein array analysis identified approximately 350-800 differentially reactive antigens, and revealed different antigen profiles in the glioblastomas and meningiomas, with approximately 20-30%-similar and 10-15%-similar antigens in preoperative and postoperative sera, respectively. Seroreactivity did not correlate with OncoDB-derived gene expression. Antigens in the preoperative glioblastoma sera were enriched for signaling pathways, such as signaling by Rho-GTPases, COPI-mediated anterograde transport and vesicle-mediated transport, while the infectious disease, SRP-dependent membrane targeting cotranslational proteins were enriched in the meningiomas. The pre-vs. postoperative seroreactivity in the glioblastomas was enriched for antigens, e.g., platelet degranulation and metabolism of lipid pathways; in the meningiomas, the antigens were enriched in infectious diseases, metabolism of amino acids and derivatives, and cell cycle. Antibody profiling in both tumor entities elucidated several hundred antigens and characteristic signaling pathways that may provide new insights into molecular pathology and may be of interest for the development of new treatment strategies.

Protein Microarrays and their Fabrication.

Protein microarrays are an important tool when analyzing multiple analytes simultaneously. As the human genome contains approximately 20,000 genes, examining the interactions of even just one representative protein for each gene requires a high-throughput technique. For instance, the interaction between glycosaminoglycans (GAGs), a form of polysaccharide, and chemokines, small chemoattractant proteins, is critical for local inflammation. GAGs present in the glycocalyx on the surface of the cell bind to chemokines, which are released in response to injury. These chemokines can then form concentration gradients that direct the migration and recruitment of leucocytes via leukocyte receptors which in turn leads to immune cell responses, inflammation, or innate immunity and cell or antibody-mediated immune responses. Discovering the novel interactions between the GAGs and chemokines can help in designing drugs which can alter cellular binding to organ tissues, thereby potentially reducing damaging innate immune (inflammation) or acquired immune (antibody-mediated) responses.

Exploring High-Throughput Immunoassays for Biomarker Validation in Rheumatic Diseases in the Context of the Human Proteome Project.

Rheumatic diseases are high prevalence pathologies with different etiology and evolution and low sensitivity in clinical diagnosis. Therefore, it is necessary to develop an early diagnosis method which allows personalized treatment, depending on the specific pathology. The biology/disease initiative, at Human Proteome Project, is an integrative approach to identify relevant proteins in the human proteome associated with pathologies. A previously reported literature data mining analysis, which identified proteins related to osteoarthritis (OA), rheumatoid arthritis (RA), and psoriatic arthritis (PSA) was used to establish a systematic prioritization of potential biomarkers candidates for further evaluation by functional proteomics studies. The aim was to study the protein profile of serum samples from patients with rheumatic diseases such as OA, RA, and PSA. To achieve this goal, customized antibody microarrays (containing 151 antibodies targeting 121 specific proteins) were used to identify biomarkers related to early and specific diagnosis in a screening of 960 serum samples (nondepleted) (OA, n = 480; RA, n = 192; PSA, n = 288). This functional proteomics screening has allowed the determination of a panel (30 serum proteins) as potential biomarkers for these rheumatic diseases, displaying receiver operating characteristics curves with area under the curve values of 80-90%.

Assessment of the breadth of binding promiscuity of heme towards human proteins.

Heme regulates important biological processes by transient interactions with many human proteins. The goal of the present study was to assess extends of protein binding promiscuity of heme. To this end we evaluated interaction of heme with >9000 human proteins. Heme manifested high binding promiscuity by binding to most of the proteins in the array. Nevertheless, some proteins have outstanding heme binding capacity. Bioinformatics analyses revealed that apart from typical haemoproteins, these proteins are frequently involved in metal binding or have the potential to recognize DNA. This study can contribute for understanding the regulatory functions of labile heme.

Evolution of biomarker research in autoimmunity conditions for health professionals and clinical practice.

Medical abzymology has made a great contribution to the development of general autoimmunity theory: it has put the autoantibodies (Ab) as the key brick of the theory to the level of physiological functionality by providing such Ab with the ability to catalyze and mediate direct and independent cytotoxic effect on cellular and molecular targets. Natural catalytic autoantibodies (abzymes) while being a pool of canonical Abs and possessing catalytic activity belong to the new group of physiologically active substances whose features and properties are evolutionary consolidated in one functionally active biomolecule. Therefore, further studies on Ab-mediated autoAg degradation and other targeted Ab-mediated proteolysis may provide biomarkers of newer generations and thus a supplementary tool for assessing the disease progression and predicting disability of the patients and persons at risks. This chapter is a summary of current knowledge and prognostic perspectives toward catalytic Abs in autoimmunity and thus some autoimmune clinical cases, their role in pathogenesis, and the exploitation of both whole molecules and their constituent parts in developing highly effective targeted drugs of the future to come, and thus the therapeutic protocols being individualized.

Reverse Phase Protein Arrays in cancer stem cells.

The scenario of proteogenomics is rapidly evolving and novel technologies are enabling comprehensive molecular exploration down to single cells. Likewise, digital (immuno-)assays are revolutionizing the field of biomarker detection and have reached the grade for population-level screenings with single-molecule sensitivity. Nonetheless, cost- and time-effective, high-throughput targeted phospho-proteomics at a preclinical stage still relies on ad hoc microarray platforms, such as the Reverse-Phase Protein microArrays (RPPA). Although this technique requires specific knowledge and equipment and different laboratories worldwide have implemented alternative methodological strategies, the application of RPPA to biomarker discovery has proven successful on diverse types of samples, including tissues and biological fluids as well as nanovesicles and in vitro cultured lines. Among these, cancer stem(-like) cells (CSC) represent an ideal experimental model system for preclinical discovery and definition of novel drug targets. The present methodological article provides the basic knowledge and steps on how to deploy an RPPA analysis with specific reference to an ideal experimental setup of drug testing on CSC.

Rise of the SARS-CoV-2 Variants: can proteomics be the silver bullet?

INTRODUCTION: The challenges posed by emergent strains of SARS-CoV-2 need to be tackled by contemporary scientific approaches, with proteomics playing a significant role. AREAS COVERED: In this review, we provide a brief synthesis of the impact of proteomics technologies in elucidating disease pathogenesis and classifiers for the prognosis of COVID-19 and propose proteomics methodologies that could play a crucial role in understanding emerging variants and their altered disease pathology. From aiding the design of novel drug candidates to facilitating the identification of T cell vaccine targets, we have discussed the impact of proteomics methods in COVID-19 research. Techniques varied as mass spectrometry, single-cell proteomics, multiplexed ELISA arrays, high-density proteome arrays, surface plasmon resonance, immunopeptidomics, and in silico docking studies that have helped augment the fight against existing diseases were useful in preparing us to tackle SARS-CoV-2 variants. We also propose an action plan for a pipeline to combat emerging pandemics using proteomics technology by adopting uniform standard operating procedures and unified data analysis paradigms. EXPERT OPINION: The knowledge about the use of diverse proteomics approaches for COVID-19 investigation will provide a framework for future basic research, better infectious disease prevention strategies, improved diagnostics, and targeted therapeutics.

Deciphering Biomarkers for Leptomeningeal Metastasis in Malignant Hemopathies (Lymphoma/Leukemia) Patients by Comprehensive Multipronged Proteomics Characterization of Cerebrospinal Fluid.

In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease.

High-throughput and multi-phases identification of autoantibodies in diagnosing early-stage breast cancer and subtypes.

Autoantibodies (AAbs) targeted tumor-associated antigens (TAAs) have the potential for early detection of breast cancer. Here, 574 early-stage breast cancer (ES-BC) patients containing 4 subtypes (Luminal A, Luminal B, HER2+, TN), 126 benign breast disease (BBD) patients, and 199 normal healthy controls (NHC) were separated into three-phases to discover, verify, and validate AAbs. In discovery phase using high-throughput protein microarray, 37 AAbs with sensitivity of 31.25%-86.25% and specificity over 73% in ES-BC, and 40 AAbs with different positive rates between subtypes were identified as candidates. In verification phase, 18 AAbs were significantly increased compared with the Control (BBD and NHC) in focused array. Ten out of 18 AAbs exhibited a significant difference between subtypes (P < .05). In ELISA validation phase, 5 novel AAbs (anti-KJ901215, -FAM49B, -HYI, -GARS, -CRLF3) exhibited significantly higher levels in ES-BC compared with BBD/NHC (P < .05). The sensitivities of individual AAb and a 5-AAbs panel were 20.41%-28.57% and 38.78%, whereas the specificities were over 90% and 85.94%. Simultaneously, 4 AAbs except anti-GARS differed significantly between TN and non-TN subtype (P < .05). We constructed 3 random forest classifier models based on AAbs to discriminant ES-BC from Control or BBD, and to discern TN subtype, which yielded an area under the curve of 0.870, 0.860, and 0.875, respectively. Biological interaction analysis revealed 4 TAAs, except for KJ901215, that were associated with well known proteins of BC. This study discovered and stepwise validated 5 novel AAbs with the potential to diagnose ES-BC and discern TN subtype, indicating easy-to-detect and minimally invasive diagnostic value of serum AAbs ahead of biopsy for future application.

Identification of Tumor Antigens in Ovarian Cancers Using Local and Circulating Tumor-Specific Antibodies.

Ovarian cancers include several disease subtypes and patients often present with advanced metastatic disease and a poor prognosis. New biomarkers for early diagnosis and targeted therapy are, therefore, urgently required. This study uses antibodies produced locally in tumor-draining lymph nodes (ASC probes) of individual ovarian cancer patients to screen two separate protein microarray platforms and identify cognate tumor antigens. The resulting antigen profiles were unique for each individual cancer patient and were used to generate a 50-antigen custom microarray. Serum from a separate cohort of ovarian cancer patients encompassing four disease subtypes was screened on the custom array and we identified 28.8% of all ovarian cancers, with a higher sensitivity for mucinous (50.0%) and serous (40.0%) subtypes. Combining local and circulating antibodies with high-density protein microarrays can identify novel, patient-specific tumor-associated antigens that may have diagnostic, prognostic or therapeutic uses in ovarian cancer.

Molecular Expression Profile of Changes in Rat Acute Spinal Cord Injury.

Background: Spinal cord injury (SCI) is a highly lethal and debilitating disease with a variety of etiologies. To date, there is no effective therapeutic modality for a complete cure. The pathological mechanisms of spinal cord injury at the molecular gene and protein expression levels remain unclear. Methods: This study used single-cell transcriptomic analysis and protein microarray analysis to analyzes changes in the gene expression profiles of cells and secretion of inflammatory factors respectively, around the lesion site in a rat SCI model. Results: Single-cell transcriptomic analysis found that three types of glial cells (microglia, astrocyte, and oligodendrocyte) becomes activated after acute injury, with GO exhibiting a variety of inflammatory-related terms after injury, such as metabolic processes, immune regulation, and antigen presentation. Protein microarray results showed that the levels of four inflammatory cytokines favoring SCI repair decreased while the levels of nine inflammatory cytokines hindering SCI repair increased after injury. Conclusion: These findings thus reveal the changes in cellular state from homeostatic to reactive cell type after SCI, which contribute to understand the pathology process of SCI, and the potential relationship between glial cells and inflammatory factors after SCI, and provides new theoretical foundation for further elucidating the molecular mechanisms of secondary SCI.

Antibody signatures of asymptomatic Plasmodium falciparum malaria infections measured from dried blood spots.

BACKGROUND: Screening malaria-specific antibody responses on protein microarrays can help identify immune factors that mediate protection against malaria infection, disease, and transmission, as well as markers of past exposure to both malaria parasites and mosquito vectors. Most malaria protein microarray work has used serum as the sample matrix, requiring prompt laboratory processing and a continuous cold chain, thus limiting applications in remote locations. Dried blood spots (DBS) pose minimal biohazard, do not require immediate laboratory processing, and are stable at room temperature for transport, making them potentially superior alternatives to serum. The goals of this study were to assess the viability of DBS as a source for antibody profiling and to use DBS to identify serological signatures of low-density Plasmodium falciparum infections in malaria-endemic regions of Myanmar. METHODS: Matched DBS and serum samples from a cross-sectional study in Ingapu Township, Myanmar were probed on protein microarrays populated with P. falciparum antigen fragments. Signal and trends in both sample matrices were compared. A case-control study was then performed using banked DBS samples from malaria-endemic regions of Myanmar, and a regularized logistic regression model was used to identify antibody signatures of ultrasensitive PCR-positive P. falciparum infections. RESULTS: Approximately 30% of serum IgG activity was recovered from DBS. Despite this loss of antibody activity, antigen and population trends were well-matched between the two sample matrices. Responses to 18 protein fragments were associated with the odds of asymptomatic P. falciparum infection, albeit with modest diagnostic characteristics (sensitivity 58%, specificity 85%, negative predictive value 88%, and positive predictive value 52%). CONCLUSIONS: Malaria-specific antibody responses can be reliably detected, quantified, and analysed from DBS, opening the door to serological studies in populations where serum collection, transport, and storage would otherwise be impossible. While test characteristics of antibody signatures were insufficient for individual diagnosis, serological testing may be useful for identifying exposure to asymptomatic, low-density malaria infections, particularly if sero-surveillance strategies target individuals with low previous exposure as sentinels for population exposure.

Protein Microarray-Based Proteomics for Disease Analysis.

As we approach the twentieth anniversary of completing the international Human Genome Project, the next (and arguably most significant) frontier in biology consists of functionally understanding the proteins, which are encoded by the genome and play a crucial role in all of biology and medicine. To accomplish this challenge, different proteomics strategies must be devised to examine the activities of gene products (proteins) at scale. Among them, protein microarrays have been used to accomplish a wide variety of investigations such as examining the binding of proteins and proteoforms to DNA, small molecules, and other proteins; characterizing humoral immune responses in health and disease; evaluating allergenic proteins; and profiling protein patterns as candidate disease-specific biomarkers. In Protein Microarray for Disease Analysis: Methods and Protocols, expert researchers involved in the field of protein microarrays provide concise descriptions of the methodologies that they currently use to fabricate microarrays and how they apply them to analyze protein interactions and responses of proteins to dissect human disease.

Systematic and Rational Design of Protein Arrays in Noncontact Printers: Pipeline and Critical Aspects.

The systematic design and construction of customized protein microarrays are critical for the further successful screening of biological samples in biomedical research projects. In general protein microarrays are classified according to the content, detection method, and printing methodology, among others. Here, we are focused on the type of printing: contact and noncontact. Both approaches have advantages and disadvantages; however, in any of the approaches, a prior well design and systematic preparation of materials and/or instruments required for the customized antibody arrays is critical. In this chapter, the process for an antibody microarray by a noncontact printer is described in detail from the preparation of array content to the analysis, including quality control steps.

Analysis of Protein-Protein Interactions by Protein Microarrays.

The analysis of the proteome and the interactome would be useful for a better understanding of the pathophysiology of several disorders, allowing the identification of potential specific markers for early diagnosis and prognosis, as well as potential targets of intervention. Among different proteomic approaches, high-density protein microarrays have become an interesting tool for the screening of protein-protein interactions and the interactome definition of disease-associated dysregulated proteins. This information might contribute to the identification of altered signaling pathways and protein functions involved in the pathogenesis of a disease. Remarkably, protein microarrays have been already satisfactorily employed for the study of protein-protein interactions in cancer, allergy, or neurodegenerative diseases. Here, we describe the utilization of recombinant protein microarrays for the identification of protein-protein interactions to help in the definition of disease-specific dysregulated interactomes.

Profiling Autoantibody Responses to Devise Novel Diagnostic and Prognostic Markers Using High-Density Protein Microarrays.

Protein microarrays are a diverse and high-throughput platform for screening biomolecular interactions, autoantigens, and protein expression profiles across tissues, etc. Autoantibodies produced against aberrant protein expression are often observed in malignancies which makes protein microarrays a powerful platform to elucidate biomarkers of translational interest. Early diagnosis of malignancies is an enduring clinical problem that has a direct impact on disease prognosis. Here, we provide an overview of a method employed to screen autoantibodies using patient sera in brain tumors. In case of brain malignancies, early diagnosis is particularly challenging and often requires highly invasive brain biopsies as a confirmatory test. This chapter summarizes the various considerations for applying a serum-based autoantibody biomarker discovery pipeline that could provide a minimally invasive initial diagnostic screen, potentiating classical diagnostic approaches.