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Seventy-nine cytokines, chemokines, and growth factors were measured by protein array analysis in the cerebrospinal fluid of patients with meningitis and controls. Several factors were found to be regulated, which have not been studied in the CNS before, e.g., macrophage inflammatory protein-1delta (CCL15) and neutrophil-activating peptide-2 (CXCL7). In pneumococcal meningitis, other new observations were an increase of macrophage migration inhibitory factor, monocyte chemoattractant protein-2 (CCL8), pulmonary and activation-regulated chemokine (CCL18), and macrophage inflammatory protein-3alpha (CCL20), and a sustained upregulation of several growth factors. In viral meningitis, new findings were an elevation of CCL8, thrombopoietin, and vascular endothelial growth factor.
With the advent of high-throughput proteomic experiments such as arrays of purified proteins comes the need to analyse sets of proteins as an ensemble, as opposed to the traditional one-protein-at-a-time approach. Although there are several publicly available tools that facilitate the analysis of protein sets, they do not display integrated results in an easily-interpreted image or do not allow the user to specify the proteins to be analysed.
Characterising tumour-associated antigens (TAAs) not only represents an important approach to the identification of new diagnostic/prognostic markers, but can also provide information on disease processes and additional potential therapeutic targets. Preliminary screening of a protein macroarray, containing more than 12,000 different proteins, with sera from anaplastic lymphoma kinase (ALK)-negative and ALK-positive anaplastic large cell lymphoma (ALCL) patients identified ribonuclease and tumour suppressor protein Ribonuclease T2 (RNASET2), phosphatase lipid phosphate phosphatase-related protein type 3 (LPPR3) and apoptotic adaptor molecule Fas-associating protein (FADD) as ALK-negative ALCL-associated TAAs. Further validation of these observations was confirmed using the ALCL sera in reverse ELISAs. The circulating anti-RNASET2 autoantibodies present in ALCL patients' sera also recognised eukaryotically expressed RNASET2 protein. RNASET2 expression was then investigated in normal tissues and in lymphomas to explore its clinical potential. RNASET2 protein and mRNA levels showed highest expression in the spleen, leucocytes and pancreas. RNASET2 protein expression was not restricted to ALK-negative ALCL (81%), being expressed in ALK-positive ALCL (65%) as well as in a number of other lymphomas. The immunological recognition of RNASET2, its expression in ALCL and other lymphomas together with its known tumourigenic properties suggest that further studies on this autoantigen are warranted.
Fluorescence-based microarray offers great potential in clinical diagnostics due to its high-throughput capability, multiplex capabilities, and requirement for a minimal volume of precious clinical samples. However, the technique relies on expensive and complex imaging systems for the analysis of signals. In the present study, we developed a smartphone-based application to analyze signals from protein microarrays to quantify disease biomarkers. The application adopted Android Studio open platform for its wide access to smartphones, and Python was used to design a graphical user interface with fast data processing. The application provides multiple user functions such as "Read", "Analyze", "Calculate" and "Report". For rapid and accurate results, we used ImageJ, Otsu thresholding, and local thresholding to quantify the fluorescent intensity of spots on the microarray. To verify the efficacy of the application, three antigens each with over 110 fluorescent spots were tested. Particularly, a positive correlation of over 0.97 was achieved when using this analytical tool compared to a standard test for detecting a potential biomarker in lupus nephritis. Collectively, this smartphone application tool shows promise for cheap, efficient, and portable on-site detection in point-of-care diagnostics.
Aggregation of alpha-synuclein may contribute to neuropathology in Parkinson's disease patients and in transgenic animal models. Natively unfolded alpha-synuclein binds to various proteins and conformational changes due to alpha-synuclein misfolding may alter physiological interactions. In the present study, we used protein arrays spotted with 5000 recombinant human proteins for a large scale interaction analysis of monomeric versus oligomeric alpha-synuclein. Monomeric alpha-synuclein bound to arrayed cAMP regulated phosphoprotein 19 and binding appears to be disrupted by alpha-synuclein oligomerization. Incubation with recombinant alpha-synuclein oligomers lead to the identification of several GTPase activating proteins and Cdc42 effector proteins as binding partners. Protein database searches revealed a Cdc42/Rac interactive binding domain in some interactors. To demonstrate in vivo relevance, we analyzed brainstem protein extracts from alpha-synuclein(A30P) transgenic mice. Pull-down assays using beads conjugated with a Cdc42/Rac interactive binding domain lead to an enrichment of endogenous alpha-synuclein oligomers. Cdc42 effector proteins were also co-immunoprecipitated with alpha-synuclein from brainstem lysates and were colocalized with alpha-synuclein aggregates in brain sections by double immunostaining. By two-dimensional gel electrophoretic analysis of synaptosomal fractions from transgenic mouse brains we detected additional isoforms of septin 6, a downstream target of Cdc42 effector proteins. Small GTPases have recently been identified in a genetic modifier screen to suppress alpha-synuclein toxicity in yeast. Our data indicate that components of small GTPase signal transduction pathways may be directly targeted by alpha-synuclein oligomers which potentially leads to signaling deficits and neurodegeneration.
Room-temperature (RT) protein crystallography provides significant information to elucidate protein function under physiological conditions. In particular, contrary to typical binding assays, X-ray crystal structure analysis of a protein-ligand complex can determine the three-dimensional (3D) configuration of its binding site. This allows the development of effective drugs by structure-based and fragment-based (FBDD) drug design. However, RT crystallography and RT crystallography-based protein-ligand complex analyses require the preparation and measurement of numerous crystals to avoid the X-ray radiation damage. Thus, for the application of RT crystallography to protein-ligand complex analysis, the simultaneous preparation of protein-ligand complex crystals and sequential X-ray diffraction measurement remain challenging. Here, we report an RT crystallography technique using a microfluidic protein crystal array device for protein-ligand complex structure analysis. We demonstrate the microfluidic sorting of protein crystals into microwells without any complicated procedures and apparatus, whereby the sorted protein crystals are fixed into microwells and sequentially measured to collect X-ray diffraction data. This is followed by automatic data processing to calculate the 3D protein structure. The microfluidic device allows the high-throughput preparation of the protein-ligand complex solely by the replacement of the microchannel content with the required ligand solution. We determined eight trypsin-ligand complex structures for the proof of concept experiment and found differences in the ligand coordination of the corresponding RT and conventional cryogenic structures. This methodology can be applied to easily obtain more natural structures. Moreover, drug development by FBDD could be more effective using the proposed methodology.
Malaria parasites modify their human host cell, the mature erythrocyte. This modification is mediated by a large number of parasite proteins that are exported to the host cell, and is also the underlying cause for the pathology caused by malaria infection. Amongst these proteins are many Hsp40 co-chaperones, and a single Hsp70. These proteins have been implicated in several processes in the host cell, including a potential role in protein transport, however the further molecular players in this process remain obscure. To address this, we have utilized chemical cross-linking followed by mass spectrometry and immunoblotting to isolate and characterize proteins complexes containing an exported Hsp40 (PFE55), and the only known exported Hsp70 (PfHsp70x). Our data reveal that both of these proteins are contained in high molecular weight protein complexes. These complexes are found both in the infected erythrocyte, and within the parasite-derived compartment referred to as the parasitophorous vacuole. Surprisingly, our data also reveal an association of PfHsp70x with components of PTEX, a putative protein translocon within the membrane of the parasitophorous vacuole. Our results suggest that the P. falciparum- infected human erythrocyte contains numerous high molecular weight protein complexes, which may potentially be involved in host cell modification.
Surface proteins play key roles in the interaction between cells and their environment, and in pathogenic microorganisms they are the best targets for drug or vaccine discovery and/or development. In addition, surface proteins can be the basis for serodiagnostic tools aiming at developing more affordable techniques for early diagnosis of infection in patients. We carried out a proteomic analysis of a collection of pediatric clinical isolates of Streptococcus pneumoniae, an important human pathogen responsible for more than 1.5 million child deaths worldwide. For that, cultured live bacterial cells were "shaved" with trypsin, and the recovered peptides were analyzed by LC/MS/MS. We selected 95 proteins to be produced as recombinant polypeptides, and printed them on an array. We probed the protein array with a collection of patient sera to define serodiagnostic antigens. The mass spectrometry proteomics data correspond to those published in [1] and have been deposited to the ProteomeXchange Consortium [2] via the PRIDE partner repository [3] with the dataset identifier PXD001740. The protein array raw data are provided as supplemental material in this article.
The most common and lethal type of intracranial tumors include the astrocytomas. Grade IV astrocytoma or Glioblastoma (GBM) is highly aggressive and treatment-refractory with a median survival of only 14 to 16 months. Molecular profiling of GBMs reveals a high degree of intra- and inter-tumoral heterogeneity, and hence it is important to understand the important signalling axes that get deregulated in different GBM subtypes to provide effective tailor-made therapies. In this study, we have carried out extensive analysis of Reverse Phase Protein Array (RPPA) data from TCGA cohort to develop protein signatures that define glioma grades or subtypes. The protein signatures that distinguished Grade II or III from GBM had largely overlapped, and pathway analysis revealed the positive enrichment of extracellular matrix proteins (ECM), MYC pathway, uPAR pathway and G2/M checkpoint genes in GBM. We also identified protein signatures for GBMs with genetic alterations (IDH mutation, p53 mutation, EGFR amplification or mutation, CDKN2A/CDKN2B deletion, and PTEN mutation) that occur at high frequency. G-CIMP positive GBM-specific protein signature showed a large similarity with IDH1-mutant protein signature, thus signifying the importance of IDH1 mutation driving the G-CIMP. Gene expression subtype analysis revealed an association of specific proteins to classical (EGFR and phosphor variants), mesenchymal (SERPINE1, TAZ, and Myosin-IIa_pS1943), neural (TUBA1B), and proneural (GSK3_pS9) types. Univariate Cox regression analysis identified several proteins showing significant correlation with GBM survival. Multivariate analysis revealed that IGFBP2 and RICTOR_pT1135 are independent predictors of survival. Overall, our analyses reveal that specific proteins are regulated in different glioma subtypes underscoring the importance of diverse signalling axes playing important role in the pathogenesis of glioma tumors.
The creation of a complete genome-wide map of transcription factor binding sites is essential for understanding gene regulatory networks in vivo. However, current prediction methods generally rely on statistical models that imperfectly model transcription factor binding. Generation of new prediction methods that are based on protein binding data, but do not rely on these models may improve prediction sensitivity and specificity.
The aim of this study was to evaluate the effect of curcumin on morphine tolerance and the corresponding cytokine/chemokine changes. Male ICR mice were made tolerant to morphine by daily subcutaneous injection for 7 days. Intraperitoneal injections of vehicle, low-dose or high-dose curcumin were administered 15 min after morphine injection, either acutely or chronically for 7 days to test the effect of curcumin on morphine-induced antinociception and development of morphine tolerance. On day 8, cumulative dose-response curves were generated and the 50% of maximal analgesic dose values were calculated and compared among groups. Corresponding set of mice were used for analyzing the cytokine responses by antibody-based cytokine protein array. Acute, high-dose curcumin enhanced morphine-induced antinociception. While morphine tolerance was attenuated by administration of low-dose curcumin following morphine injections for 7 days, it was aggravated by chronic high-dose curcumin following morphine injection, suggesting a biphasic effect of curcumin on morphine-induced tolerance. Of the 96 cytokine/chemokines analyzed by mouse cytokine protein array, 14 cytokines exhibited significant changes after the different 7-day treatments. Mechanisms for the modulatory effects of low-dose and high-dose curcumin on morphine tolerance were discussed. Even though curcumin itself is a neuroprotectant and low doses of the compound serve to attenuate morphine tolerance, high-doses of curcumin might cause neurotoxicity and aggravate morphine tolerance by inhibiting the expression of antiapoptotic cytokines and neuroprotective factors. Our results indicate that the effect of curcumin on morphine tolerance may be biphasic, and therefore curcumin should be used cautiously.
The lack of effective and accurate diagnostic tools contributes to the high prevalence of tuberculosis (TB) worldwide. The current serodiagnostics for TB are inadequate mainly due to lack of TB-specific antigens with highly accurate diagnosis. In the current study, we aimed to identify novel diagnostic antigens using glutathione S-transferase (GST)-fusion protein technique. We determined the reactivity of these recombinant proteins arrayed in solution and on GSH-immobilized microplates with TB patient sera. Of 409 TB proteins produced, ninety-two yielded seropositive reactions, fourteen including eight novel proteins showed strong immunoreactivity. Further, six were selected and constructed as a multiple-antigen combination set through analysis of various combinations. A comparative study of the multiple-antigen combination set and a commercially available kit revealed that the combination set showed 66.3% (95% CI 60.5-71.8) sensitivity, which was significantly higher than that of the commercial kit [31.6% (95% CI 26.3-37.3)]. The specificity of both methods was similar at 89.6% (95% CI 83.3-95.4) and 90.6% (95% CI 83.0-95.6), respectively. This study provides a set of novel diagnostic protein markers with great potential for the development of novel diagnostic tools for active TB.
Dried blood spot samples (DBSS) on filter paper offer several advantages compared to conventional serum/plasma samples: they do not require any phlebotomy or separation of blood by centrifugation; they are less invasive; they allow sample stability and shipment at room temperature; and they pose a negligible risk of infection with blood-borne viruses, such as HIV, HBV and HCV, to those who handle them. Therefore dried blood spot samples (DBSS) on filter paper can be a quick, convenient and inexpensive means of obtaining blood samples for biomarker discovery, disease screening, diagnosis and treatment monitoring in non-hospitalized, public health settings. In this study, we investigated for the first time the potential application of dried blood spot samples (DBSS) in protein expression profiling using antibody array technology. First, optimal conditions for array assay performance using dried blood spot samples (DBSS) was established, including sample elution buffer, elution time, elution temperature and assay blocking buffer. Second, we analyzed dried blood spot samples (DBSS) using three distinct antibody array platforms, including sandwich-based antibody arrays, quantitative antibody arrays and biotin-label-based antibody arrays. In comparison with paired serum samples, detection of circulating proteins in dried blood spot samples (DBSS) correlated well for both low- and high-abundance proteins on all three antibody array platforms. In conclusion, our study strongly indicates the novel application of multiplex antibody array platforms to analyze dried blood spot samples (DBSS) on filter paper represents a viable, cost-effective method for protein profiling, biomarker discovery and disease screening in a large, population-based survey.
Protein arrays are frequently used to profile antibody repertoires in humans and animals. High-throughput protein array characterisation of complex antibody repertoires necessitates the use of extensively validated secondary detection antibodies. This article details the validation of an affinity-isolated anti-chicken IgY antibody produced in rabbit and a goat anti-rabbit IgG antibody conjugated with alkaline phosphatase using protein arrays consisting of 7,390 distinct human proteins. Probing protein arrays with secondary antibodies in absence of chicken serum revealed non-specific binding to 61 distinct human proteins. Despite the identified non-specific binding, the tested antibodies are well suited for use in protein array experiments as the cross-reactive binding partners can be readily excluded from further analysis. The evident cross-reactivity of the tested secondary detection antibodies points towards the necessity of platform-specific antibody characterisation studies for all secondary immunoreagents. Furthermore, secondary antibody characterisation using protein arrays enables the generation of reference lists of cross-reactive proteins, which can be then marked as potential false positives in follow-up experiments. Providing such cross-reactivity reference lists accessible to the wider research community may help to interpret data generated with the same antibodies in applications not only related to protein arrays such as immunoprecipitation, Western blots or other immunoassays.
Reverse-phase protein array (RPPA) technology uses panels of high-specificity antibodies to measure proteins and protein post-translational modifications in cells and tissues. The approach offers sensitive and precise quantification of large numbers of samples and has thus found applications in the analysis of clinical and pre-clinical samples. For effective integration into drug development and clinical practice, robust assays with consistent results are essential. Leveraging a collaborative RPPA model, we set out to assess the variability between three different RPPA platforms using distinct instrument set-ups and workflows. Employing multiple RPPA-based approaches operated across distinct laboratories, we characterised a range of human breast cancer cells and their protein-level responses to two clinically relevant cancer drugs. We integrated multi-platform RPPA data and used unsupervised learning to identify protein expression and phosphorylation signatures that were not dependent on RPPA platform and analysis workflow. Our findings indicate that proteomic analyses of cancer cell lines using different RPPA platforms can identify concordant profiles of response to pharmacological inhibition, including when using different antibodies to measure the same target antigens. These results highlight the robustness and the reproducibility of RPPA technology and its capacity to identify protein markers of disease or response to therapy.
NTAP is designed to analyze ChIP-chip data generated by the NimbleGen tiling array platform and to accomplish various pattern recognition tasks that are useful especially for epigenetic studies. The modular design of NTAP makes the data processing highly customizable. Users can either use NTAP to perform the full process of NimbleGen tiling array data analysis, or choose post-processing modules in NTAP to analyze pre-processed epigenetic data generated by other platforms. The output of NTAP can be saved in standard GFF format files and visualized in GBrowse.
Protein-protein interaction (PPI) analysis is a key process to understand protein functions. Recently, we constructed a human protein array (20 K human protein beads array) consisting of 19,712 recombinant human proteins produced by a wheat cell-free protein production system. Here, we developed a cell-free protein array technology for proximity biotinylation-based PPI identification (CF-PPiD). The proximity biotinylation enzyme AirID-fused TP53 and -IκBα proteins each biotinylated specific interacting proteins on a 1536-well magnetic plate. In addition, AirID-fused cereblon was shown to have drug-inducible PPIs using CF-PPiD. Using the human protein beads array with AirID-IκBα, 132 proteins were biotinylated, and then selected clones showed these biological interactions in cells. Although ZBTB9 was not immunoprecipitated, it was highly biotinylated by AirID-IκBα, suggesting that this system detected weak interactions. These results indicated that CF-PPiD is useful for the biochemical identification of directly interacting proteins.
The human papillomaviruses (HPV) are a group of double-stranded DNA viruses that exhibit an exclusive tropism for squamous epithelia. HPV can either be low- or high-risk depending on its ability to cause benign lesions or cancer, respectively. Unsurprisingly, the majority of epigenetic research has focused on the high-risk HPV types, neglecting the low-risk types in the process. Therefore, the main objective of this study is to better understand the epigenetics of wart formation by investigating the differences in methylation between HPV-induced cutaneous warts and normal skin. A number of clear and very significant differences in methylation patterns were found between cutaneous warts and normal skin. Around 55% of the top-ranking 100 differentially methylated genes in warts were protein coding, including the EXOC4, KCNU, RTN1, LGI1, IRF2, and NRG1 genes. Additionally, non-coding RNA genes, such as the AZIN1-AS1, LINC02008, and MGC27382 genes, constituted 11% of the top-ranking 100 differentially methylated genes. Warts exhibited a unique pattern of methylation that is a possible explanation for their transient nature. Since the genetics of cutaneous wart formation are not completely known, the findings of the present study could contribute to a better understanding of how HPV infection modulates host methylation to give rise to warts in the skin.
Phosphatase of regenerating liver 3 (PRL-3) promotes cancer metastasis and progression via increasing cell motility and invasiveness, however the mechanism is still not fully understood. Previous reports showed that PRL-3 increases the phosphorylation of many important proteins and suspected that PRL-3-enhanced protein phosphorylation may be due to its regulation on cytokines. To investigate PRL-3's impact on protein phosphorylation and cytokine secretion, we performed antibody arrays against protein phosphorylation and cytokines separately. The data showed that PRL-3 could enhance tyrosine phosphorylation and serine/threonine phosphorylation of diverse signaling proteins. Meanwhile, PRL-3 could affect the secretion of a subset of cytokines. Furthermore, we discovered the PRL-3-increased IL-1α secretion was regulated by NF-κB and Jak2-Stat3 pathways and inhibiting IL-1α could reduce PRL-3-enhanced cell migration. Therefore, our result indicated that PRL-3 promotes protein phosphorylation by acting as an 'activator kinase' and consequently regulates cytokine secretion.
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