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PubMed2025

Plasma Proteomic Profiles Predict Individual Future Osteoarthritis Risk.

OBJECTIVE: Osteoarthritis (OA) is a widespread degenerative joint disease that causes a considerable socioeconomic burden. Despite progress in genetic and environmental insights, early diagnosis is still limited by the lack of evident symptoms during the initial phases and accurate biomarkers. This study aims to identify plasma proteins associated with future risk of OA and develop a predictive model. METHODS: We conducted a large-scale proteomic analysis of 45,307 participants from the UK Biobank, excluding those with baseline OA. Plasma samples were assayed using the Olink Explore Proximity Extension Assay targeting 1,463 unique proteins. Clinical variables and OA outcomes were extracted and linked to electronic health records. A predictive model was constructed using the LightGBM machine learning method, and SHapley Additive exPlanations (SHAP) were applied to evaluate the importance of variables. RESULTS: We identified a panel of proteins significantly associated with the risk of developing OA. Notably, after adjusting for multiple confounders, collagen type IX alpha 1 chain (COL9A1) and cartilage acidic protein 1 (CRTAC1) were the most significant predictors of incident OA, with hazard ratios of 1.54 (95% confidence interval [CI] 1.48-1.61) and 1.65 (95% CI 1.54-1.78), respectively. SHAP analysis allowed a profound interpretation of the contribution of each protein and clinical variable to the model, revealing the multifactorial nature of OA risk prediction. The temporal trajectories of plasma proteins indicated that the levels of COL9A1 and CRTAC1 began to deviate from normal for more than a decade before OA onset, suggesting their potential use in early detection strategies. The predictive model, developed using the LightGBM algorithm, integrated proteins with clinical covariates and demonstrated an area under the curve (AUC) of 0.729 for 5-year OA prediction, 0.721 for 10-year prediction, and 0.723 for all incident OA. The predictive accuracy of the model was further enhanced for hip and knee OA, achieving AUCs of 0.820 and 0.803 for 5-year predictions. CONCLUSION: Our study identified the role of plasma proteomics in predicting future OA risk, which could contribute to preemptive measures. The innovative model, which integrates proteomic biomarkers with clinical data, offers a potential tool for risk assessment, potentially optimizing OA management strategies and enhancing prevention efforts.

Humans↗

PubMed2026

Machine learning-assisted plasma PEA proteomics enables differential diagnosis of melancholic depression and bipolar disorder.

Differentiating bipolar disorder (BD) from major depressive disorder (MDD) remains a critical unmet need in psychiatry due to overlapping clinical presentations and the absence of reliable biological markers. In this study, we assessed the capacity of multivariate machine learning models to accurately differentiate BD from MDD with melancholic features using plasma proteomic profiles obtained via Proximity Extension Assay (PEA) technology. A total of 67 participants were included (23 BD, 20 MDD, and 24 HC), and plasma protein expression was assessed using the Olink Target 96 Neurology panel. Differential proteomic analysis revealed distinct disorder-specific expression patterns, identifying 21 differentially expressed proteins in BD versus MDD, 18 in BD versus healthy controls, and 7 in MDD versus healthy controls. Using a stepwise feature reduction strategy, machine learning models were trained on three feature sets comprising all proteins, the top 20 most informative proteins, and the top 5 most beneficial proteins, and evaluated across BD-MDD, BD-HC, and MDD-HC classification tasks using five algorithms. For BD-MDD discrimination, the Random Forest model achieved the highest performance when trained on the top 5 protein set (LXN, HAGH, MATN3, PLXNB1, and CTSC), yielding an AUC of 0.905, with similarly strong performance observed using the top 20 protein set. Feature importance analysis highlighted proteins involved in neurodevelopmental processes, immune regulation, and extracellular matrix organization. Overall, these findings demonstrate that integrating plasma proteomics with machine learning enables robust differentiation between BD and MDD with melancholic features, supporting the development of scalable and biologically informed diagnostic tools for precision psychiatry.

Bipolar disorder↗

PubMed2026

Protein Profiling Identifies Biomarkers for Predicting Disease Severity in Anti-NMDAR Encephalitis.

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a severe autoimmune neurological disorder characterized by pathogenic antibodies against the NMDAR. A systematic protein profiling approach is warranted to identify biomarkers capable of predicting disease status. An Olink proximity extension assay (PEA) profiled 91 inflammation-related proteins from anti-NMDAR encephalitis patients. Disease severity or prognosis were assessed by CASE score or mRS score at 6-month follow-up. Patients were stratified into distinct molecular clusters using unsupervised clustering. Logistic regression models incorporating selected biomarkers were developed to predict disease severity and prognosis, followed by absolute quantification using ELISA. Patients were classified into four consensus clusters. Clusters 1 and 2 corresponded to the mild group, while Cluster 3 represented the severe group, consistent with CASE score above 6. Cluster 4 showed heterogeneous clinical features. Elevated serum levels of IL-10, IL-6, and SIRT2, as well as increased CSF levels of CXCL10, CXCL11, and MMP10, were positively associated with severe disease. Conversely, several proteins including LTA and CCL11, CCL8, TGFB1, CXCL6 were associated with severe disease or unfavorable 6-month outcomes. A logistic regression model combining serum CXCL6 and CCL11 with CSF MMP10 achieved an area under the curve (AUC) of 0.95 for predicting disease severity. Serum CCL11 alone showed predictive value for 6-month prognosis, with an AUC of 0.79. These findings delineate distinct protein signatures associated with clinical heterogeneity of anti-NMDAR encephalitis. Prediction models incorporating multiple biomarkers may provide an approach for disease severity stratification and prognosis forecast.

Humans↗

PubMed2026

Comparison of endothelin-1 levels in plasma from human coronary arteries measured by enzyme linked immunosorbent assay and Olink high-throughput proteomics platform.

Endothelin-1 (ET-1) antagonists are increasingly being approved for new treatments for cardiovascular disease, where elevated ET-1 levels contribute to increased vasoconstriction. Further therapeutic targets, including coronary artery disease, are under investigation. The Olink Explore 3072 Proximity Extension Assay platform enables multiplexed high-throughput measurement of ~3000 plasma proteins, from minimal (≤6 µL) sample volumes. However, it is not known if the two oligonucleotide-tagged antibodies raised against preproET-11-212, used in this Olink assay, specifically measure biologically active ET-1 or the other inactive EDN1-encoded peptides, also secreted by human endothelial cells. Paired plasma samples from 29 patients with coronary artery disease were obtained, using a specialised intra-coronary sampling catheter, designed to obtain site specific biochemical information from within coronary arteries. We compared ET-1 concentrations measured with an ET-1 specific ELISA, demonstrated to have no cross-reactivity with other EDN1-encoded peptides versus values obtained using Olink Explore platform. Olink-measured ET-1 correlated significantly with ELISA-derived ET-1 levels (r = 0.53, p = 0.003), and Olink values predicted ELISA results. Olink ET-1 concentrations also correlated with ETB receptor levels (r = 0.40, p < 0.05). These findings indicate that the Olink Explore platform can detect relative changes in biologically active ET-1, supporting its use as a biomarker tool in clinical and translational studies.

Humans↗

PubMed2026

Proteomic Profile in Retinopathy of Prematurity: A Secondary Analysis of the Mega Donna Mega Randomized Clinical Trial.

IMPORTANCE: Identifying early proteomic profiles in infants who develop severe retinopathy of prematurity (ROP) may reveal targets for preventive interventions to reduce retinal vessel loss and the subsequent risk of severe ROP. OBJECTIVE: To assess early longitudinal profiles of blood protein levels in preterm infants with or without severe ROP and the effect of arachidonic acid (AA) and docosahexaenoic acid (DHA) supplementation. DESIGN, SETTING, AND PARTICIPANTS: This was an exploratory, post hoc analysis of serum proteome profiles in preterm infants in the double-masked Mega Donna Mega (MDM) randomized clinical trial using targeted Olink Proximity Extension Assay proteomics covering 538 analytes. The setting was 3 university hospitals in Sweden and included extremely preterm infants born before 28 weeks of gestational age (GA), from 2016 to 2019. Data were analyzed from January to March 2025. EXPOSURES: All infants received standard nutrition; additionally, half received enteral lipid supplementation with AA/DHA (100/50 mg/kg per day) from birth to term equivalent age. MAIN OUTCOMES AND MEASURES: Longitudinal protein profiles during the first month of life were examined using mixed models for repeated measures, adjusted for GA, study center, and AA/DHA supplementation, and tested for the interaction between severe ROP (stage ≥3 and/or treated) and postnatal age. RESULTS: A total of 177 extremely preterm infants (mean [SD] GA, 25.6 [1.4] weeks; 100 male [56.5%]) were included, of whom 50 (28.2%) developed severe ROP. Of 538 longitudinal analyzed proteins, 109 protein profiles in the first month of life associated with severe ROP, proteins related to immune response, apoptotic processes, blood coagulation, and lipid metabolism. The most pronounced association with severe ROP was a fast rise in fibroblast growth factor 21 (FGF-21; β = 0.68; 95% CI, 0.39-0.97; Q =.002) and tissue plasminogen activator (tPA; β = 0.21; 95% CI, 0.13-0.29; Q <.001) during the first postnatal days. The increase in serum FGF-21 level in the first week of life was associated with lower GA, lower birth weight, low enteral energy intake, and more days receiving mechanical ventilation. No association was observed between AA/DHA supplementation and the proteome. CONCLUSIONS AND RELEVANCE: In this post hoc exploratory analysis of data from the MDM randomized clinical trial, a fast rise in FGF-21 levels, a metabolic stress-induced hormone, during the first postnatal days was strongly associated with the development of severe ROP in extremely preterm infants. These findings suggest that early interventions improving bioenergetic status may help prevent severe ROP. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03201588.

Humans↗

PubMed2025

Comprehensive proteomic and pathological profiling identifies PRAS40 as a novel biomarker and mediator of primary immune checkpoint blockade resistance in non-small cell lung cancer.

BACKGROUND: Immune checkpoint blockade (ICB) has revolutionized the treatment landscape of non-small cell lung cancer (NSCLC), yet primary resistance remains a significant clinical challenge. Recent evidence implicates PRAS40 (AKT1S1) in regulating cellular survival and immune responses, but its role in immunotherapy resistance is not fully understood. METHODS: Transcriptomic data from TCGA and GTEx cohorts were analyzed to assess PRAS40 expression. Prognostic value was evaluated using Cox regression. Immune microenvironment features were characterized with CIBERSORT and TIMER. Predictive efficacy for ICB response was examined using TIDE and IPS. Plasma PRAS40 levels in 66 NSCLC patients receiving ICB were quantified by proximity extension assay (PEA), and multiplex immunohistochemistry assessed associations among PRAS40, PD-L1, and CD8+ T cells in tumor tissues. RESULTS: High PRAS40 expression was associated with poor prognosis, reduced CD8+ T cell infiltration, and downregulation of immune checkpoint genes. Elevated circulating PRAS40 predicted primary ICB resistance and shorter progression-free survival, independent of PD-L1 or CD8+ T cell status. CONCLUSION: PRAS40 is strongly associated with primary ICB resistance in NSCLC and may serve as a novel predictive biomarker. These findings support its potential to guide personalized immunotherapy in lung cancer.

Humans↗

PubMed2025

Plasma proteomic markers of pain and emotional dysfunction in fibrous dysplasia/McCune-Albright syndrome.

Pain in Fibrous dysplasia/McCune-Albright syndrome (FD/MAS) remains poorly understood and inadequately managed due to uncertainties regarding clinical or biological drivers. This cross-sectional pilot study aimed to use plasma proteomics to identify markers that inform on molecular pathways associated with pain and emotional symptoms in FD/MAS. Seventeen individuals (15 females, 2 males), aged 16 to 63 years, with confirmed diagnoses of monostotic FD, polyostotic FD, or MAS participated in a single study visit conducted at Boston Children's Hospital and Massachusetts General Brigham. During the visit, participants completed validated questionnaires assessing neuropathic pain characteristics, pain interference, anxiety symptoms, depression symptoms, and perceived stress, and provided plasma samples. These samples were analyzed for 57 proteins using Olink proximity extension assay. Associations between protein concentrations and symptom scores were evaluated using Spearman's correlations with false discovery rate correction (|r| > 0.5, p < 0.05). After FDR correction, the concentrations of seven proteins (TNF-α, LTA, CCL19, CSF2, CCL2, CCL4, CCL7) significantly correlated with pain interference, HADS-depression scores, or perceived stress. Four protein concentrations (TNF-α, CCL19, CSF2, CCL7) significantly correlated with multiple clinical measures. This pilot study identified several pain-associated proteins in individuals with FD/MAS, suggesting that proteomic profiling may be a promising approach for discovering pain biomarkers. Larger, longitudinal studies are needed to validate these results and investigate whether targeting immune pathways can alleviate pain and improve emotional health in FD/MAS.

Humans↗

PubMed2024

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with ∼5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p < 0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Humans↗

PubMed2026

Serum Olink Proteomics Reveals Novel Biomarkers for Early Diagnosis of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly prevalent malignant tumor in China, and early diagnosis critically affects the prognosis. Current imaging and pathological biopsy techniques have limitations, including high invasiveness and limited accessibility, while the insufficient sensitivity of serum biomarkers (such as AFP) restricts their use in early screening. In this study, using the Olink proteomics platform based on the proximity extension assay (PEA), we screened for hepatocellular carcinoma-related differentially expressed proteins (DEPs) and constructed a multiprotein diagnostic model. In the discovery cohort, we included 15 patients with newly diagnosed HCCs and 16 healthy controls. DEPs were identified using Olink, and their diagnostic performance was analyzed to identify the candidate biomarkers. In an independent validation cohort, including 116 HCC patients (50 early stage, 66 late stage) and 83 healthy controls, we further validated the expression levels and diagnostic performance of identified proteins─C1QA and GFER. The C1QA and GFER expression levels were significantly higher in the serum of patients with early and late HCC stages compared to healthy controls. By constructing a multiprotein diagnostic model, we identified C1QA, GFER, and AFP as the optimal diagnostic combination, demonstrating a combined diagnostic AUC of 0.92 and 0.99 for early-stage and advanced-stage HCC, respectively.

Humans↗

PubMed2026

Machine learning-based analysis of oral rinse samples to identify candidate proteomic signatures for severe periodontitis: a pilot study.

This pilot study investigated whether candidate protein signatures from oral rinse samples can distinguish patients with severe periodontitis (stage III/IV) and its subtypes, generalized and localized periodontitis, from non-periodontitis controls. Participants rinsed with phosphate-buffered saline, and samples were analyzed using a Proximity Extension Assay targeting 92 inflammatory and 92 immuno-oncology proteins. A machine learning approach using repeated nested cross-validation and SHAP was implemented to identify protein signatures. The study included 38 patients (18 with localized periodontitis and 20 with generalized periodontitis) and 16 controls. After data preprocessing, 54 samples and 141 proteins were retained. Proteins Gal-1, HGF, TNFSF14, CD27, and ARG1 distinguished periodontitis from controls (ROC-AUC = 0.85, 95% CI 0.82, 0.87). For generalized periodontitis, we found a protein signature including TNFSF14, Gal-1, STAMBP, MUC-16, S100A12, HGF, CASP-8, CD27, LAP TGF-β1, TNFRSF9, and uPA (ROC-AUC = 0.92, 95% CI 0.90, 0.94). For localized periodontitis, we identified ARG1 (ROC-AUC = 0.72, 95% CI 0.68, 0.76). No proteomic signature distinguishing generalized periodontitis from localized periodontitis was identified. This pilot study indicated that oral rinses are suitable for proteomic profiling, and there was a putative protein signature that could differentiate periodontitis, generalized periodontitis, and localized periodontitis from controls. These findings warrant validation in larger independent cohorts, including a clearly defined gingivitis group, before real-world non-invasive screening applications can be considered.

Humans↗

PubMed2025

Differential expression of plasma proteins and pathway enrichments in pediatric diabetic ketoacidosis.

BACKGROUND: In children with type 1 diabetes (T1D), diabetic ketoacidosis (DKA) triggers a significant inflammatory response; however, the specific effector proteins and signaling pathways involved remain largely unexplored. This pediatric case-control study utilized plasma proteomics to explore protein alterations associated with severe DKA and to identify signaling pathways that associate with clinical variables. METHODS: We conducted a proteome analysis of plasma samples from 17 matched pairs of pediatric patients with T1D; one cohort with severe DKA and another with insulin-controlled diabetes. Proximity extension assays were used to quantify 3072 plasma proteins. Data analysis was performed using multivariate statistics, machine learning, and bioinformatics. RESULTS: This study identified 214 differentially expressed proteins (162 upregulated, 52 downregulated; adj P < 0.05 and a fold change > 2), reflecting cellular dysfunction and metabolic stress in severe DKA. We characterized protein expression across various organ systems and cell types, with notable alterations observed in white blood cells. Elevated inflammatory pathways suggest an enhanced inflammatory response, which may contribute to the complications of severe DKA. Additionally, upregulated pathways related to hormone signaling and nitrogen metabolism were identified, consistent with increased hormone release and associated metabolic processes, such as glycogenolysis and lipolysis. Changes in lipid and fatty acid metabolism were also observed, aligning with the lipolysis and ketosis characteristic of severe DKA. Finally, several signaling pathways were associated with clinical biochemical variables. CONCLUSIONS: Our findings highlight differentially expressed plasma proteins and enriched signaling pathways that were associated with clinical features, offering insights into the pathophysiology of severe DKA.

Humans↗

PubMed2025

Plasma inflammatory proteome profiles identify MASLD among children with overweight or obesity.

BACKGROUND & AIMS: Pediatric metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly prevalent among children with overweight or obesity, yet its early diagnosis remains a major clinical challenge. This study aimed to identify circulating inflammatory proteins associated with MASLD and to develop a proteomic risk score (ProScore) to improve diagnostic accuracy. METHODS: In this cross-sectional study of 161 children (median age 8.5 years) with overweight or obesity, MASLD was assessed by vibration-controlled transient elastography, with 42 cases identified. Plasma concentrations of 92 inflammation-related proteins were quantified using a high-throughput proximity extension assay. The ProScore was compared with eleven conventional anthropometric/metabolic indices (WHtR, METS-IR, SPISE, PNFI, VAI, LAP, TyG, TyG-ALT, TyG-WC, TyG-WHtR, and TyG-BMI) and a genetic risk score (GRS). Six machine learning algorithms were employed and diagnostic performance was assessed using area under the curve (AUC) with fivefold cross-validation. RESULTS: Fifteen proteins were significantly associated with MASLD. A six-protein panel (FGF-21, CDCP1, CD244, OPG, Flt3L, MCP-1) achieved the highest diagnostic accuracy (AUC = 0.84), exceeding that of all conventional indices (AUC = 0.65-0.78; all P < 0.05). ProScore performance remained robust in school-based validation (AUC = 0.83), with no substantial improvement when combined with conventional indices. Diagnostic accuracy was higher in children with lower GRS (AUC = 0.92) than in those with higher GRS (AUC = 0.80; P = 0.003). CONCLUSIONS: A proteomic signature of systemic inflammation provides accurate, non-invasive identification of MASLD in at-risk children, outperforming conventional metabolic and genetic tools, and may have utility in clinical and public health settings.

Humans↗

PubMed2026

DNA Methylation and Proteomic Profiling of Postmortem Brain Tissue Reveals Epigenetic Dysregulation and Neuroinflammatory in Fragile X-associated Tremor/Ataxia Syndrome (FXTAS).

BACKGROUND: Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a late-onset neurodegenerative disorder caused by FMR1 premutation CGG repeat expansions (55-200 repeats). The epigenetic landscape of the FXTAS brain remains uncharacterized. We performed genome-wide DNA methylation profiling of postmortem prefrontal cortex tissue to identify differentially methylated positions (DMPs) and candidate genes, and sought protein-level support for a neuroinflammatory signal. METHODS: DNA methylation was profiled in postmortem prefrontal cortex (Brodmann area 9) from 27 male FXTAS cases and 29 male controls using the Illumina MethylationEPIC array (EPICv1 and EPICv2 platforms), merging 721,802 common probes. Surrogate variable analysis (SVA) controlled for confounders. DMPs were defined by |Δβ| > 0.10 and FDR < 0.05; exploratory Reactome 2024 pathway analysis was performed on the DMP-associated gene list. Targeted proteomic profiling was performed in the same brain region using the Olink (proximity extension assay) Inflammation panel in 9 FXTAS cases and 12 controls, with SVA-adjusted differential abundance analysis, and concordance assessment against a prior mass spectrometry dataset. RESULTS: We identified 108 significant cg-type DMPs mapping to 80 genes (50 hypermethylated, 58 hypomethylated in FXTAS). The strongest signal was CYP2E1 (7 concordant hypomethylated DMPs, mean Δβ = -0.143), an oxidative stress gene also implicated in Parkinson's disease. FTCD, a one-carbon cycle enzyme, carried 5 hypermethylated DMPs (mean Δβ = +0.210). A cluster of DMP-associated genes with established roles in innate immune and NF-κB signaling, TRAF3 (the single most significant DMP among the inflammation genes, hypermethylated), BATF, RCOR1, and MSI2; they pointed toward neuroinflammatory dysregulation. Additional genes included LINGO1 (myelination inhibitor), SYT3 (synaptic vesicle), and SLC39A4 (zinc transporter). Exploratory Reactome enrichment using the DMP-associated gene set nominated themes including neuroinflammation resolution, axonal growth inhibition, zinc homeostasis, and CYP2E1 metabolism at nominal significance (p<0.05); however, the gene-to-pathway mapping rate was low and no pathway survived correction for multiple testing. Olink proteomic analysis independently identified 60 significantly altered inflammation proteins (59 downregulated), including CXCL8, CXCL10, IL6, IL15, IL18, TLR3, IRAK1/4, and complement C1QA, which were directionally concordant with prior mass spectrometry data. CONCLUSIONS: This integrated study reveals a genome-wide epigenetic signature in the FXTAS prefrontal cortex implicating oxidative stress, myelination failure, zinc dysregulation, one-carbon cycle disruption, and most notably a coordinated set of epigenetically altered genes governing innate immune and NF-κB signaling. Convergence of TRAF3 hypermethylation with independent downregulation of TLR3 and NF-κB-pathway proteins at the protein level supports a coherent, cross-platform model of dysregulated neuroinflammatory signaling in FXTAS, identified here through individual gene- and protein-level convergence rather than formal pathway enrichment. FTCD hypermethylation proposes a self-reinforcing epigenetic loop via SAM depletion. These multi-omic findings establish FXTAS as a disorder of pervasive epigenetic reprogramming and nominate candidate genes for future mechanistic and therapeutic investigation.

CYP2E1↗

PubMed2005

Proximity extension of circular DNA aptamers with real-time protein detection.

Multivalent circular aptamers or 'captamers' have recently been introduced through the merger of aptameric recognition functions with the basic principles of DNA nanotechnology. Aptamers have strong utility as protein-binding motifs for diagnostic applications, where their ease of discovery, thermal stability and low cost make them ideal components for incorporation into targeted protein assays. Here we report upon a property specific to circular DNA aptamers: their intrinsic compatibility with a highly sensitive protein detection method termed the 'proximity extension' assay. The circular DNA architecture facilitates the integration of multiple functional elements into a single molecule: aptameric target recognition, nucleic acid hybridization specificity and rolling circle amplification. Successful exploitation of these properties is demonstrated for the molecular analysis of thrombin, with the assay delivering a detection limit nearly three orders of magnitude below the dissociation constants of the two contributing aptamer-thrombin interactions. Real-time signal amplification and detection under isothermal conditions points towards potential clinical applications, with both fluorescent and bioelectronic methods of detection achieved. This application elaborates the pleiotropic properties of circular DNA aptamers beyond the stability, potency and multitargeting characteristics described earlier.

Aptamers, Nucleotide↗

PubMed1999

An in vitro screening technique for DNA polymerases that can incorporate modified nucleotides. Pseudo-thymidine as a substrate for thermostable polymerases.

DNA polymerases are desired that incorporate modified nucleotides into DNA with diminished pausing, premature termination and infidelity. Reported here is a simple in vitro assay to screen for DNA polymerases that accept modified nucleotides based on a set of primer extension reactions. In combination with the scintillation proximity assay (SPA[trade]), this allows rapid and simple screening of enzymes for their ability to elongate oligonucleotides in the presence of unnatural nucleotides. A proof of the concept is obtained using pseudo-thymidine (psiT), the C-nucleoside analog of thymidine, as the unnatural substrate. The conformational properties of psiT arising from the carbon-carbon bond between the sugar and the base make it an interesting probe for the importance of conformational restraints in the active site of polymerases during primer elongation. From a pool of commercially available thermostable polymerases, the assay identified Taq DNA polymerase as the most suitable enzyme for the PCR amplification of oligonucleotides containing psiT. Subsequent experiments analyzing PCR performance and fidelity of Taq DNA polymerase acting on psiT are presented. This is the first time that PCR has been performed with a C-nucleoside.

Animals↗

PubMed1992

Structure of the human alpha-2 macroglobulin gene and its promotor.

The human alpha 2-macroglobulin gene was isolated in five overlapping clones. The gene spans approx. 48 kb and consists of 36 exons, from 21 to 229 bp in size and with consensus splice sites. Intron sizes range from 145 bp to 7.5 kb. The alpha 2M gene is a single copy gene in the human genome. A sequence polymorphism within the bait domain, coding for an Arg to His substitution within the primary cleavage site for trypsin, was identified in 1 of 132 individuals tested so far. Three transcription initiation sites have been identified in liver by primer extension and RNase protection assays. The most proximal, major site (+1) is preceded by a TATA-like structure (ATAAA) at -26 bp. Only 2 mRNA species were found in uterus and in cultured lung fibroblasts, while alpha 2M is not expressed to a detectable level in skin fibroblasts. The far distal transcription initiation site which is preceded by an intact TATA box and a potential HP-1 binding site is thus specific for liver.

Amino Acid Sequence↗

PubMed2001

Computation-directed identification of OxyR DNA binding sites in Escherichia coli.

A computational search was carried out to identify additional targets for the Escherichia coli OxyR transcription factor. This approach predicted OxyR binding sites upstream of dsbG, encoding a periplasmic disulfide bond chaperone-isomerase; upstream of fhuF, encoding a protein required for iron uptake; and within yfdI. DNase I footprinting assays confirmed that oxidized OxyR bound to the predicted site centered 54 bp upstream of the dsbG gene and 238 bp upstream of a known OxyR binding site in the promoter region of the divergently transcribed ahpC gene. Although the new binding site was near dsbG, Northern blotting and primer extension assays showed that OxyR binding to the dsbG-proximal site led to the induction of a second ahpCF transcript, while OxyR binding to the ahpCF-proximal site leads to the induction of both dsbG and ahpC transcripts. Oxidized OxyR binding to the predicted site centered 40 bp upstream of the fhuF gene was confirmed by DNase I footprinting, but these assays further revealed a second higher-affinity site in the fhuF promoter. Interestingly, the two OxyR sites in the fhuF promoter overlapped with two regions bound by the Fur repressor. Expression analysis revealed that fhuF was repressed by hydrogen peroxide in an OxyR-dependent manner. Finally, DNase I footprinting experiments showed OxyR binding to the site predicted to be within the coding sequence of yfdI. These results demonstrate the versatile modes of regulation by OxyR and illustrate the need to learn more about the ensembles of binding sites and transcripts in the E. coli genome.

Bacterial Outer Membrane Proteins↗

PubMed2005

Parallel minisequencing followed by multiplex matrix-assisted laser desorption/ionization mass spectrometry assay for beta-thalassemia mutations.

Beta-thalassemia is a common monogenic disease caused by mutations in the human beta-globin gene (HBB), many of which are differentially represented in human subpopulations stratified by ethnicity. This study describes an efficient and highly accurate method to screen for the eight most-common disease-causing mutations, covering more than 98% of HBB alleles in the Taiwanese population, using parallel minisequencing and multiplex assay by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The MALDI-TOF MS was optimized for sensitivity and resolution by "mass tuning" the PinPoint assay for eight HBB SNPs. Because of the close proximity and clustering of mutations in HBB, primer extension reactions were conducted in parallel. Efficient sequential desalting using POROS and cationic exchange chromatography allowed for an unambiguous multiplex genotyping by MALDI-TOF MS. The embellishing SNP assay allowed for highly accurate identification of the eight most-common beta-thalassemia mutations in homozygous normal control, carrier, and eight heterozygous carrier mixtures, as well as the diagnosis of a high-risk family. The results demonstrated a flexible strategy for rapid identification of clustering SNPs in HBB with a high degree of accuracy and specificity. It can be adapted easily for high-throughput diagnosis of various hereditary diseases or to establish family heritage databases for clinical applications.

Base Sequence↗