Multiplexed patterning of hybrid lipid membrane and protein arrays for cell signaling study

The supported lipid bilayer (SLB) is a powerful tool for studying dynamic cell-environment interactions and has been widely used for biosensing applications. Using a reusable microfluidic chip, we present here a strategy to fabricate highly multiplexed SLB and protein arrays for cell signaling research. This approach allows for the rapid patterning of hundreds of highly reproducible and size-tunable SLB arrays with distinct lipid composition and mobility. Using fluorescence microscopy and fluorescence correlation spectroscopy, the lipid mobility is found to play a central role for patterning this membrane assay. Adding protein rings as diffusion barriers extends the accessible mobility range and maintains long-term stability of the hybrid array. Subsequent protein functionalizations on the SLB could be conducted using standard conjugation methods. The utility of the hybrid array for cell signaling experiments is demonstrated by studying the immune NF-κB signaling, whose activity is triggered by the binding of the membrane receptor, toll-like-receptor 4 (TLR 4), to its ligand, lipopolysaccharide (LPS), that is functionalized on the SLB. The patterned array allows cells to adhere and spread on areas without LPS before migrating to interact with membrane-bound LPS to initiate NF-κB activation. Overall, the strategy offers an efficient route to rapidly generate easily controllable and multiplexed molecular arrays that can serve as versatile platforms for biosensing and cell signaling research.

Differential gene expression analysis of corneal endothelium indicates involvement of phagocytic activity in Fuchs' endothelial corneal dystrophy

Fuchs' endothelial corneal dystrophy (FECD) is a progressive vision impairing disease caused by thickening of Descemet's membrane and gradual degeneration and loss of corneal endothelial cells. The aim of this study was to identify differentially expressed genes between FECD-affected and unaffected corneal endothelium to gain insight into the pathophysiological mechanisms underlying this disease. Microarray gene expression analysis was performed on total RNA from FECD-affected and unaffected corneal endothelium-Descemet's membrane (CE-DM) specimens using the Illumina HumanHT-12 v4.0 expression array. RNA from pools of FECD-affected (n = 3 per pool) and individual unaffected (n = 3) specimens was used for comparison. Altered expression of a sub-set of differentially expressed genes was validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in independent specimens. Bioinformatics analysis was performed using InnateDB to reveal functional relationships among the differentially expressed genes and molecular pathways involved in the disease. A total of 16,513 genes were found expressed in the corneal endothelium of which 142 genes were differentially expressed between FECD-affected and unaffected endothelium (log₂ fold-change ≥1.5, corrected p-value ≤0.05). Most of the genes were up-regulated (126) and a small proportion down-regulated (16) in affected corneal endothelium. Of the twelve genes prioritised for validation, differential expression of 10 genes, including those ranked 57th and 81st by significance validated by qRT-PCR (8 up-regulated and 2 downregulated, corrected p ≤ 0.05), one gene showed a trend for up-regulation in affected endothelium, consistent with the microarray analysis and another was up-regulated in an independent study indicating robustness of the differential expression dataset. Bioinformatic analysis revealed significant over-representation of differentially expressed genes in extracellular matrix reorganisation, cellular remodelling, immune response, and inflammation. Network analysis showed functional inter-relatedness of the majority of the dysregulated genes and revealed known direct functional relationships between 20 of the genes; many of these genes have roles in macrophage differentiation, phagocytosis and inflammation. This is the second report of microarray gene expression analysis in FECD. This study revealed a set of highly dysregulated genes in the corneal endothelium in FECD. More than a third of the dysregulated genes in the disease have been discovered for the first time and thus are novel. The dysregulated genes strongly suggest the presence of phagocytic cells, most likely immune cells, and inflammation in corneal endothelium in the disease. This study provides a molecular framework for delineating the mechanisms underlying these cellular processes in FECD.

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.

Broad auto-reactive IgM responses are common in critically ill patients, including those with COVID-19

The pathogenesis of severe coronavirus disease 2019 (COVID-19) remains poorly understood. While several studies suggest that immune dysregulation plays a central role, the key mediators of this process are yet to be defined. Here, we demonstrate that plasma from a high proportion (93%) of critically ill COVID-19 patients, but not healthy controls, contains broadly auto-reactive immunoglobulin M (IgM) and less frequently auto-reactive IgG or IgA. Importantly, these auto-IgMs preferentially recognize primary human lung cells in vitro, including pulmonary endothelial and epithelial cells. By using a combination of flow cytometry, analytical proteome microarray technology, and lactose dehydrogenase (LDH)-release cytotoxicity assays, we identify high-affinity, complement-fixing, auto-reactive IgM directed against 260 candidate autoantigens, including numerous molecules preferentially expressed on the cellular membranes of pulmonary, vascular, gastrointestinal, and renal tissues. These findings suggest that broad IgM-mediated autoimmune reactivity may be involved in the pathogenesis of severe COVID-19, thereby identifying a potential target for therapeutic interventions.

Dissecting the novel mechanism of reduning injection in treating Coronavirus Disease 2019 (COVID-19) based on network pharmacology and experimental verification

ETHNOPHARMACOLOGICAL RELEVANCE

Reduning injection (RDNI) is a patented Traditional Chinese medicine that contains three Chinese herbal medicines, respectively are the dry aboveground part of Artemisia annua L., the flower of Lonicera japonica Thunb., and the fruit Gardenia jasminoides J.Ellis. RDNI has been recommended for treating Coronavirus Disease 2019 (COVID-19) in the "New Coronavirus Pneumonia Diagnosis and Treatment Plan".

AIM OF THE STUDY

To elucidate and verify the underlying mechanisms of RDNI for the treatment of COVID-19.

METHODS

This study firstly performed anti-SARS-CoV-2 experiments in Vero E6 cells. Then, network pharmacology combined with molecular docking was adopted to explore the potential mechanisms of RDNI in the treatment for COVID-19. After that, western blot and a cytokine chip were used to validate the predictive results.

RESULTS

We concluded that half toxic concentration of drug CC50 (dilution ratio) = 1:1280, CC50 = 2.031 mg crude drugs/mL (0.047 mg solid content/mL) and half effective concentration of drug (EC50) (diluted multiples) = 1:25140.3, EC50 = 103.420 μg crude drugs/mL (2.405 μg solid content/mL). We found that RDNI can mainly regulate targets like carbonic anhydrases (CAs), matrix metallopeptidases (MMPs) and pathways like PI3K/AKT, MAPK, Forkhead box O s and T cell receptor signaling pathways to reduce lung damage. We verified that RDNI could effectively inhibit the overexpression of MAPKs, PKC and p65 nuclear factor-κB. The injection could also affect cytokine levels, reduce inflammation and display antipyretic activity.

CONCLUSION

RDNI can regulate ACE2, Mpro and PLP in COVID-19. The underlying mechanisms of RDNI in the treatment for COVID-19 may be related to the modulation of the cytokine levels and inflammation and its antipyretic activity by regulating the expression of MAPKs, PKC and p65 nuclear factor NF-κB.

Development and Application of Human Coronavirus Protein Microarray for Specificity Analysis

Coronavirus is an enveloped RNA virus that causes mild to severe respiratory diseases in humans, including HKU1-CoV, 229E-CoV, NL63-CoV, OC43-CoV, SARS-CoV, MERS-CoV, and SARS-CoV-2. Due to the outbreak of SARS-CoV-2, it is important to identify the patients and investigate their immune responses. Protein microarray is one of the best platforms to profile the antibodies in the blood because of its fast, multiplexed, and sensitive nature. To fully understand the immune responses and biological specificities, this study developed a human coronavirus (HCoV) protein microarray and included all seven human coronaviruses and three influenza viruses. Each protein was printed in triplicate and formed 14 identical blocks per array. The HCoV protein microarray showed high reproducibility and sensitivity to the monoclonal antibodies against spike and nucleocapsid protein with detection limits of 10-200 pg. The HCoV proteins that were immobilized on the array were properly folded and functional by showing interactions with a known human receptor, e.g., ACE2. By profiling the serum IgG and IgA from 32 COVID-19 patients and 36 healthy patients, the HCoV protein microarray demonstrated 97% sensitivity and 97% specificity with two biomarkers. The results also showed the cross-reactivity of IgG and IgA in COVID-19 patients to spike proteins from various coronaviruses, including that from SARS-CoV, HKU1-CoV, and OC43-CoV. Finally, an innate immune protein named surfactant protein D showed broad affinities to spike proteins in all human coronaviruses. Overall, the HCoV protein microarray is multiplexed, sensitive, and specific, which is useful in diagnosis, immune assessment, biological development, and drug screening.

Soluble Antigen Arrays Efficiently Deliver Peptides and Arrest Spontaneous Autoimmune Diabetes

Antigen-specific immunotherapy (ASIT) offers a targeted treatment of autoimmune diseases that selectively inhibits autoreactive lymphocytes, but there remains an unmet need for approaches that address the limited clinical efficacy of ASIT. Soluble antigen arrays (SAgAs) deliver antigenic peptides or proteins in multivalent form, attached to a hyaluronic acid backbone using either hydrolysable linkers (hSAgAs) or stable click chemistry linkers (cSAgAs). They were evaluated for the ability to block spontaneous development of disease in a nonobese diabetic mouse model of type 1 diabetes (T1D). Two peptides, a hybrid insulin peptide and a mimotope, efficiently prevented the onset of T1D when delivered in combination as SAgAs, but not individually. Relative to free peptides administered at equimolar dose, SAgAs (particularly cSAgAs) enabled a more effective engagement of antigen-specific T cells with greater persistence and induction of tolerance markers, such as CD73, interleukin-10, programmed death-1, and KLRG-1. Anaphylaxis caused by free peptides was attenuated using hSAgA and obviated using cSAgA platforms. Despite similarities, the two peptides elicited largely nonoverlapping and possibly complementary responses among endogenous T cells in treated mice. Thus, SAgAs offer a novel and promising ASIT platform superior to free peptides in inducing tolerance while mitigating risks of anaphylaxis for the treatment of T1D.

Protein-Embedded Metalloporphyrin Arrays Templated by Circularly Permuted Tobacco Mosaic Virus Coat Proteins

Bioenergetic processes in nature have relied on networks of cofactors for harvesting, storing, and transforming the energy from sunlight into chemical bonds. Models mimicking the structural arrangement and functional crosstalk of the cofactor arrays are important tools to understand the basic science of natural systems and to provide guidance for non-natural functional biomaterials. Here, we report an artificial multiheme system based on a circular permutant of the tobacco mosaic virus coat protein (cpTMV). The double disk assembly of cpTMV presents a gap region sandwiched by the two C₂-symmetrically related disks. Non-native bis-his coordination sites formed by the mutation of the residues in this gap region were computationally screened and experimentally tested. A cpTMV mutant Q101H was identified to create a circular assembly of 17 protein-embedded hemes. Biophysical characterization using X-ray crystallography, cyclic voltammetry, and electron paramagnetic resonance (EPR) suggested both structural and functional similarity to natural multiheme cytochrome c proteins. This protein framework offers many further engineering opportunities for tuning the redox properties of the cofactors and incorporating non-native components bearing varied porphyrin structures and metal centers. Emulating the electron transfer pathways in nature using a tunable artificial system can contribute to the development of photocatalytic materials and bioelectronics.

IGF1R and Src inhibition induce synergistic cytotoxicity in HNSCC through inhibition of FAK

Head and neck cancer is the sixth most common cancer worldwide with a 5-year survival of only 65%. Targeting compensatory signaling pathways may improve therapeutic responses and combat resistance. Utilizing reverse phase protein arrays (RPPA) to assess the proteome and explore mechanisms of synergistic growth inhibition in HNSCC cell lines treated with IGF1R and Src inhibitors, BMS754807 and dasatinib, respectively, we identified focal adhesion signaling as a critical node. Focal Adhesion Kinase (FAK) and Paxillin phosphorylation were decreased as early as 15 min after treatment, and treatment with a FAK inhibitor, PF-562,271, was sufficient to decrease viability in vitro. Treatment of 3D spheroids demonstrated robust cytotoxicity suggesting that the combination of BMS754807 and dasatinib is effective in multiple experimental models. Furthermore, treatment with BMS754807 and dasatinib significantly decreased cell motility, migration, and invasion in multiple HNSCC cell lines. Most strikingly, treatment with BMS754807 and dasatinib, or a FAK inhibitor alone, significantly increased cleaved-PARP in human ex-vivo HNSCC patient tissues demonstrating a potential clinical utility for targeting FAK or the combined targeting of the IGF1R with Src. This ex-vivo result further confirms FAK as a vital signaling node of this combinatorial treatment and demonstrates therapeutic potential for targeting FAK in HNSCC patients.

Reverse Phase Protein Array Reveals Correlation of Retinoic Acid Metabolism With Cardiomyopathy in Friedreich's Ataxia

Identifying biomarkers is important for assessment of disease progression, prediction of symptom development, and determination of treatment effectiveness. While unbiased analyses of differential gene expression using next-generation sequencing methods are now routinely conducted, proteomics studies are more challenging because of traditional methods predominantly being low throughput and offering a limited dynamic range for simultaneous detection of hundreds of proteins that drastically differ in their intracellular abundance. We utilized a sensitive and high-throughput proteomic technique, reverse phase protein array (RPPA), to attain protein expression profiles of primary fibroblasts obtained from patients with Friedreich's ataxia (FRDA) and unaffected controls (CTRLs). The RPPA was designed to detect 217 proteins or phosphorylated proteins by individual antibody, and the specificity of each antibody was validated prior to the experiment. Among 62 fibroblast samples (44 FRDA and 18 CTRLs) analyzed, 30 proteins/phosphoproteins were significantly changed in FRDA fibroblasts compared with CTRL cells (p < 0.05), mostly representing signaling molecules and metabolic enzymes. As expected, frataxin was significantly downregulated in FRDA samples, thus serving as an internal CTRL for assay integrity. Extensive bioinformatics analyses were conducted to correlate differentially expressed proteins with critical disease parameters (e.g., selected symptoms, age of onset, guanine-adenine-adenine sizes, frataxin levels, and Functional Assessment Rating Scale scores). Members of the integrin family of proteins specifically associated with hearing loss in FRDA. Also, RPPA data, combined with results of transcriptome profiling, uncovered defects in the retinoic acid metabolism pathway in FRDA samples. Moreover, expression of aldehyde dehydrogenase family 1 member A3 differed significantly between cardiomyopathy-positive and cardiomyopathy-negative FRDA cohorts, demonstrating that metabolites such as retinol, retinal, or retinoic acid could become potential predictive biomarkers of cardiac presentation in FRDA.

Cut-like homeobox 1 (CUX1) tumor suppressor gene haploinsufficiency induces apoptosis evasion to sustain myeloid leukemia

While oncogenes promote tumorigenesis, they also induce deleterious cellular stresses, such as apoptosis, that cancer cells must combat by coopting adaptive responses. Whether tumor suppressor gene haploinsufficiency leads to such phenomena and their mechanistic basis is unclear. Here, we demonstrate that elevated levels of the anti-apoptotic factor, CASP8 and FADD-like apoptosis regulator (CFLAR), promotes apoptosis evasion in acute myeloid leukemia (AML) cells haploinsufficient for the cut-like homeobox 1 (CUX1) transcription factor, whose loss is associated with dismal clinical prognosis. Genome-wide CRISPR/Cas9 screening identifies CFLAR as a selective, acquired vulnerability in CUX1-deficient AML, which can be mimicked therapeutically using inhibitor of apoptosis (IAP) antagonists in murine and human AML cells. Mechanistically, CUX1 deficiency directly alleviates CUX1 repression of the CFLAR promoter to drive CFLAR expression and leukemia survival. These data establish how haploinsufficiency of a tumor suppressor is sufficient to induce advantageous anti-apoptosis cell survival pathways and concurrently nominate CFLAR as potential therapeutic target in these poor-prognosis leukemias.

Artificial Intelligence-Based Prediction of Covid-19 Severity on the Results of Protein Profiling

BACKGROUND

COVID-19 progresses slowly and negatively affects many people. However, mild to moderate symptoms develop in most infected people, who recover without hospitalization. Therefore, the development of early diagnosis and treatment strategies is essential. One of these methods is proteomic technology based on the blood protein profiling technique. This study aims to classify three COVID-19 positive patient groups (mild, severe, and critical) and a control group based on the blood protein profiling using deep learning (DL), random forest (RF), and gradient boosted trees (GBTs).

METHODS

The dataset consists of 93 samples (60 COVID-19 patients, 33 control), and 370 variables obtained from an open-source website. The current dataset contains age, gender, and 368 protein, used to predict the relationship between disease severity and proteins using DL and machine learning approaches (RF, GBTs). An evolutionary algorithm tunes hyperparameters of the models and the predictions are assessed through accuracy, sensitivity, specificity, precision, F1 score, classification error, and kappa performance metrics.

RESULTS

The accuracy of RF (96.21%) was higher as compared to DL (94.73%). However, the ensemble classifier GBTs produced the highest accuracy (96.98%). TGB1BP2 in the cardiovascular II panel and MILR1 in the inflammation panel were the two most important proteins associated with disease severity.

CONCLUSIONS

The proposed model (GBTs) achieved the best prediction of disease severity based on the proteins compared to the other algorithms. The results point out that changes in blood proteins associated with the severity of COVID-19 may be used in monitoring and early diagnosis/treatment of the disease.

Identification and Biochemical Characterization of High Mobility Group Protein 20A as a Novel Ca2+/S100A6 Target

During screening of protein-protein interactions, using human protein arrays carrying 19,676 recombinant glutathione s-transferase (GST)-fused human proteins, we identified the high-mobility protein group 20A (HMG20A) as a novel S100A6 binding partner. We confirmed the Ca²⁺-dependent interaction of HMG20A with S100A6 by the protein array method, biotinylated S100A6 overlay, and GST-pulldown assay in vitro and in transfected COS-7 cells. Co-immunoprecipitation of S100A6 with HMG20A from HeLa cells in a Ca²⁺-dependent manner revealed the physiological relevance of the S100A6/HMG20A interaction. In addition, HMG20A has the ability to interact with S100A1, S100A2, and S100B in a Ca²⁺-dependent manner, but not with S100A4, A11, A12, and calmodulin. S100A6 binding experiments using various HMG20A mutants revealed that Ca²⁺/S100A6 interacts with the C-terminal region (residues 311–342) of HMG20A with stoichiometric binding (HMG20A:S100A6 dimer = 1:1). This was confirmed by the fact that a GST-HMG20A mutant lacking the S100A6 binding region (residues 311–347, HMG20A-ΔC) failed to interact with endogenous S100A6 in transfected COS-7 cells, unlike wild-type HMG20A. Taken together, these results identify, for the first time, HMG20A as a target of Ca²⁺/S100 proteins, and may suggest a novel linkage between Ca²⁺/S100 protein signaling and HMG20A function, including in the regulation of neural differentiation.

Drug Discovery in Liver Disease Using Kinome Profiling

The liver is one of the most important organs, playing critical roles in maintaining biochemical homeostasis. Accordingly, disease of the liver is often debilitating and responsible for untold human misery. As biochemical nexus, with kinases being master regulators of cellular biochemistry, targeting kinase enzymes is an obvious avenue for treating liver disease. Development of such therapy, however, is hampered by the technical difficulty of obtaining comprehensive insight into hepatic kinase activity, a problem further compounded by the often unique aspects of hepatic kinase activities, which makes extrapolations from other systems difficult. This consideration prompted us to review the current state of the art with respect to kinome profiling approaches towards the hepatic kinome. We observe that currently four different approaches are available, all showing significant promise. Hence we postulate that insight into the hepatic kinome will quickly increase, leading to rational kinase-targeted therapy for different liver diseases.

Controlling the immobilization process of an optically enhanced protein microarray for highly reproducible immunoassay

By virtue of its high throughput multiplex detection capability, superior read-out sensitivity, and tiny analyte consumption, an optically enhanced protein microarray assay has been developed as a promising diagnostic tool for various applications, ranging from the field of pharmacology to diagnostics. However, so far, the development of an optically enhanced protein microarray (OEPM) toward widespread commercial availability is mainly hampered by insufficient detection reproducibility. Here, we develop an OEPM platform with an order of magnitude optical enhancement induced by the interference effect. High assay reproducibility of the OEPM is achieved by optimizing the protein immobilization schemes, linking to the surface energy of the substrate, surfactant-tuned wetting ability, and the washing and drying dynamics. As a result, smearing-free and uniform spot arrays with a coefficient of variation less than 7% can be achieved. Furthermore, we demonstrate the assay performance of the OEPM by detecting five biomarkers, showing an order of magnitude higher sensitivity, many-fold higher throughput, and 10 times less analyte consumption than those of the commercial enzyme-linked immunosorbent assay kits. Our results provide new insight for improving the reproducibility of OEPMs toward practical and commercial diagnostic assays.

Three-Dimensional Interfacing of Cells with Hierarchical Silicon Nano/Microstructures for Midinfrared Interrogation of In Situ Captured Proteins

Label-free optical detection of biomolecules is currently limited by a lack of specificity rather than sensitivity. To exploit the much more characteristic refractive index dispersion in the mid-infrared (IR) regime, we have engineered three-dimensional IR-resonant silicon micropillar arrays (Si-MPAs) for protein sensing. By exploiting the unique hierarchical nano- and microstructured design of these Si-MPAs attained by CMOS-compatible silicon-based microfabrication processes, we achieved an optimized interrogation of surface protein binding. Based on spatially resolved surface functionalization, we demonstrate controlled three-dimensional interfacing of mammalian cells with Si-MPAs. Spatially controlled surface functionalization for site-specific protein immobilization enabled efficient targeting of soluble and membrane proteins into sensing hotspots directly from cells cultured on Si-MPAs. Protein binding to Si-MPA hotspots at submonolayer level was unambiguously detected by conventional Fourier transform IR spectroscopy. The compatibility with cost-effective CMOS-based microfabrication techniques readily allows integration of this novel IR transducer into fully fledged bioanalytical microdevices for selective and sensitive protein sensing.

Identification of Novel Serological Autoantibodies in Takayasu Arteritis Patients Using HuProt Arrays

To identify novel autoantibodies of Takayasu arteritis (TAK) using HuProt array-based approach, a two-phase approach was adopted. In Phase I, serum samples collected from 40 TAK patients, 15 autoimmune disease patients, and 20 healthy subjects were screened to identify TAK-specific autoantibodies using human protein (HuProt) arrays. In phase II, the identified candidate autoantibodies were validated with TAK-focused arrays using an additional cohort comprised of 109 TAK patients, 110 autoimmune disease patients, and 96 healthy subjects. Subsequently, the TAK-specific autoantibodies validated in phase II were further confirmed using western blot analysis. We identified and validated eight autoantibodies as potential TAK-specific diagnostic biomarkers, including anti-SPATA7, -QDPR, -SLC25A2, -PRH2, -DIXDC1, -IL17RB, -ZFAND4, and -NOLC1 antibodies, with AUC of 0.803, 0.801, 0.780, 0.696, 0.695, 0.678, 0.635, and 0.613, respectively. SPATA7 could distinguish TAK from healthy and disease controls with 73.4% sensitivity at 85.4% specificity, while QDPR showed 71.6% sensitivity at 86.4% specificity. SLC25A22 showed the highest sensitivity of 80.7%, but at lower specificity of 67.0%. In addition, PRH2, IL17RB, and NOLC1 showed good specificities of 88.3%, 85.9%, and 86.9%, respectively, but at lower sensitivities (<50%). Finally, DIXDC1 and ZFAND4 showed moderate performance as compared with the other autoantibodies. Using a decision tree model, we could reach a specificity of 94.2% with AUC of 0.843, a significantly improved performance as compared with that by each individual biomarker. The performances of three autoantibodies, namely anti-SPATA7, -QDPR, and -PRH2, were successfully confirmed with western blot analysis. Using this two-phase strategy, we identified and validated eight novel autoantibodies as TAK-specific biomarker candidates, three of which could be readily adopted in a clinical setting.

Multi-omic molecular profiling reveals potentially targetable abnormalities shared across multiple histologies of brain metastasis

The deadly complication of brain metastasis (BM) is largely confined to a relatively narrow cross-section of systemic malignancies, suggesting a fundamental role for biological mechanisms shared across commonly brain metastatic tumor types. To identify and characterize such mechanisms, we performed genomic, transcriptional, and proteomic profiling using whole-exome sequencing, mRNA-seq, and reverse-phase protein array analysis in a cohort of the lung, breast, and renal cell carcinomas consisting of BM and patient-matched primary or extracranial metastatic tissues. While no specific genomic alterations were associated with BM, correlations with impaired cellular immunity, upregulated oxidative phosphorylation (OXPHOS), and canonical oncogenic signaling pathways including phosphoinositide 3-kinase (PI3K) signaling, were apparent across multiple tumor histologies. Multiplexed immunofluorescence analysis confirmed significant T cell depletion in BM, indicative of a fundamentally altered immune microenvironment. Moreover, functional studies using in vitro and in vivo modeling demonstrated heightened oxidative metabolism in BM along with sensitivity to OXPHOS inhibition in murine BM models and brain metastatic derivatives relative to isogenic parentals. These findings demonstrate that pathophysiological rewiring of oncogenic signaling, cellular metabolism, and immune microenvironment broadly characterizes BM. Further clarification of this biology will likely reveal promising targets for therapeutic development against BM arising from a broad variety of systemic cancers.

O-glycosylated clusterin as a sensitive marker for diagnosing early stages of prostate cancer

BACKGROUND

Prostate-specific antigen (PSA) has been the most popular diagnostic marker for prostate cancer. The frequent occurrence of low PSA values (<10 ng/ml) in patients with highly suspicious prostate cancer, however, has undermined the accuracy of clinical examinations. The aim of this study was to develop a better resolution for diagnosing prostate cancer to overcome the disadvantage of PSA.

METHODS

We focused on the glycosylation status of patients' serum proteins and conducted comprehensive lectin microarray analyses to characterize N- and O-glycans using sera from prostate cancer and benign prostatic diseases. Next, we retrieved candidate serum proteins with characteristic glycan structures using lectin-immobilized beads and identified them by quantitative mass spectrometry using a technique referred to as isobaric tag for relative and absolute quantitation (iTRAQ) labeling. Finally, we constructed a new assay to quantify a candidate glycoprotein with the newly identified glycans.

RESULTS

Lectin microarray analyses revealed that sera from patients with prostate cancer had a higher affinity for Jacalin, Amaranthus caudatus (ACA) lectin, and Maclura pomifera (MPA) lectin, compared with that from patients with benign prostatic diseases and normal subjects, suggesting that O-glycosylated proteins are more abundant in sera from patients with prostate cancer. Then, serum glycoproteins preferentially adsorbed onto Jacalin-Agarose as well as biotin-ACA/and biotin-MPA/streptavidin-immobilized magnetic beads were isolated, labeled with iTRAQ, and identified using quantitative mass spectrometry. It was found that the ACA- and MPA-recognizable clusterin was more enriched in patients' sera from prostate cancer compared with those from benign prostatic diseases. Following this discovery, we constructed a Luminex-based assay to quantify O-glycosylated clusterin, in which total serum clusterin was first captured on anti-clusterin antibody-immobilized beads, and then clusterin-associated O-glycans were determined by the pair of biotin-MPA and streptavidin-phycoerythrin. When PSA values registered less than 10 ng/ml, the corresponding serum level of MPA-recognized clusterin determined by this assay was beneficial for distinguishing the patients with prostate cancer from the patients with benign prostatic disease.

CONCLUSION

For PSA values that measure less than 10 ng/ml, the serum O-glycosylated clusterin level can be a complementary indicator for the malignancy of prostate cancer.

Rice protein-binding microarrays: a tool to detect cis-acting elements near promoter regions in rice

The present study showed that a rice (Oryza sativa)-specific protein-binding microarray (RPBM) can be applied to analyze DNA-binding motifs with a TF where binding is evaluated in extended natural promoter regions. The analysis may facilitate identifying TFs and their downstream genes and constructing gene networks through cis-elements. Transcription factors (TFs) regulate gene expression at the transcriptional level by binding a specific DNA sequence. Thus, predicting the DNA-binding motifs of TFs is one of the most important areas in the functional analysis of TFs in the postgenomic era. Although many methods have been developed to address this challenge, many TFs still have unknown DNA-binding motifs. In this study, we designed RPBM with 40-bp probes and 20-bp of overlap, yielding 49 probes spanning the 1-kb upstream region before the translation start site of each gene in the entire genome. To confirm the efficiency of RPBM technology, we selected two previously studied TFs, OsWOX13 and OsSMF1, and an uncharacterized TF, OsWRKY34. We identified the ATTGATTG and CCACGTCA DNA-binding sequences of OsWOX13 and OsSMF1, respectively. In total, 635 and 932 putative feature genes were identified for OsWOX13 and OsSMF1, respectively. We discovered the CGTTGACTTT DNA-binding sequence and 195 putative feature genes of OsWRKY34. RPBM could be applicable in the analysis of DNA-binding motifs for TFs where binding is evaluated in the promoter and 5' upstream CDS regions. The analysis may facilitate identifying TFs and their downstream genes and constructing gene networks through cis-elements.

Glass Slide-Printed Protein Arrays as a Platform to Discover Serodiagnostic Antigens Against Bacterial Infections

Infectious diseases represent a major cause of morbidity and mortality worldwide. Early detection of infections is capital for managing life-threatening cases. So far, traditional diagnostic methods such as microbiological cultures are slow and, sometimes, inaccurate. In the molecular era, high-throughput techniques are essential for providing tools that are able to diagnose in a fast and reliable way, as well as they can be used for monitoring the humoral response of groups of people in a program of epidemiological surveillance when an outbreak occurs, or when a vaccine is being evaluated. Antigen-based protein microarrays are an ideal means for these purposes, as they can carry up to thousands of protein antigens from pathogenic sources and be probed with sera from different human groups (acute or chronic infected people, convalescent, controls). For the diagnosis of bacterial infections, the best antigens are in principle the surface proteins, as they have the highest chances to raise an effective immune response. Here we describe a general protocol for fabricating a glass slide-based protein microarray using recombinant bacterial surface antigens, according to our own expertise in the study of pneumococcal disease. The probing with human sera aims to evaluate differences between diseased and healthy people, in order to discover discriminating antigens that can be used, after appropriate validation, in further easy-to-use formats such as immunostrips.

Epitope Mapping of Food Allergens Using Noncontact Piezoelectric Microarray Printer

Peptide microarrays have been used to study protein-protein interaction, enzyme-substrate profiling, epitope mapping, vaccine development, and immuno-profiling. Unlike proteins, peptides are cheap to produce, and can be produced in a high-throughput manner, in a reliable and consistent procedure that reduces batch-to-batch variability. All this provides the peptide microarrays a great potential in the development of new diagnostic tools. Noncontact printing, such as piezoelectric systems, results in a considerable advance in protein and peptide microarray production. In particular, they improve drop deposition, sample distribution, quality control, and flexibility in substrate deposition and eliminate cross-contamination and carryover. These features contribute to creating reproducible assays and generating more reliable data. Here we describe the methods and materials for epitope mapping of food allergens using peptide microarrays produced with a noncontact piezoelectric microarray printer.

An "epitomic" analysis of the specificity of conformation-dependent, anti-Aß amyloid monoclonal antibodies

Antibodies against Aß amyloid are indispensable research tools and potential therapeutics for Alzheimer's disease. They display several unusual properties, such as specificity for aggregated forms of the peptide, the ability to distinguish polymorphic aggregate structures, and the ability to recognize generic aggregation-related epitopes formed by unrelated amyloid sequences. Understanding the mechanisms underlying these unusual properties and the structures of their corresponding epitopes is crucial for the understanding why antibodies display different therapeutic activities and for the development of more effective therapeutic agents. Here we employed a novel "epitomic" approach to map the fine structure of the epitopes of 28 monoclonal antibodies against amyloid-beta using immunoselection of random sequences from a phage display library, deep sequencing, and pattern analysis to define the critical sequence elements recognized by the antibodies. Although most of the antibodies map to major linear epitopes in the amino terminal 1 to 14 residues of Aß, the antibodies display differences in the target sequence residues that are critical for binding and in their individual preferences for nontarget residues, indicating that the antibodies bind to alternative conformations of the sequence by different mechanisms. Epitomic analysis also identifies discontinuous, nonoverlapping sequence Aß segments that may constitute the conformational epitopes that underlie the aggregation specificity of antibodies. Aggregation-specific antibodies recognize sequences that display a significantly higher predicted propensity for forming amyloid than antibodies that recognize the monomer, indicating that the ability of random sequences to aggregate into amyloid is a critical element of their binding mechanism.

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.