Frontiers in Molecular Biosciences最新文献

Protein dot blot is an efficient immunoblotting technique enabling qualitative/semi-quantitative protein analysis without electrophoresis, relying on antigen-antibody binding. Its workflow involves direct sample spotting on membranes, blocking, antibody incubation, and signal detection, completing within 3-5 h. Advantages include simplicity, high throughput, micro-sample compatibility, and cost-effectiveness, supporting basic life science research and clinical testing. However, it faces limitations like narrow dynamic range, inability to resolve protein variants, susceptibility to non-specific binding, and sensitivity to operational variables. This review systematically elaborates on its principles and procedures, analyzes key factors influencing sensitivity, and repeatability, and focuses on recent application progress in protein analysis, clinical biomarker detection, and food safety, along with technical innovations. It aims to provide comprehensive references for researchers and a theoretical basis for further optimization, with future advancements likely involving nanomaterial-based signal amplification, engineered antibodies, and integration with microfluidics or mass spectrometry to expand utility in biomedicine and public health.

Background and aim: Chronic kidney disease (CKD) incorporates a variety of progressive kidney function declines, ranging from mild impairment to end-stage renal disease (ESRD). As a global public health problem, early detection and monitoring remain critical for improving patient outcomes. This study aimed to evaluate the potential diagnostic significance and interrelationships of serum sclerostin, lncRNA H19, lncRNA MEG3, lncRNA MIAT, miR-135a, and miR-29a in patients with CKD and those undergoing hemodialysis.

Methods: A total of 150 participants were enrolled in this present case-control study: 50 hemodialysis patients, 50 CKD patients, and 50 healthy controls. Circulating serum sclerostin levels were measured using ELISA. Real-time quantitative PCR (RT-qPCR) was used to measure the circulating levels of lncRNAs (H19, MEG3, and MIAT) and microRNAs (miR-135a and miR-29a). A spectrophotometer was used to determine the levels of calcium, creatinine, urea, and phosphorus in the blood.

Results: Both the CKD and hemodialysis groups displayed significantly elevated levels of all studied biomarkers compared with controls. However, the highest levels of sclerostin, lncRNAs (H19, MEG3, and MIAT), and microRNAs (miR-135a and miR-29a) were found in the hemodialysis group. LncRNA MIAT, miR-135a, and miR-29a showed high sensitivity and specificity in distinguishing CKD patients from healthy controls. Additionally, H19, MEG3, and miR-29a displayed strong differentiating ability between CKD and hemodialysis patients. All studied biomarkers exhibited strong positive correlations. Predictive modeling identified lncRNAs H19, MEG3, and MIAT as significant predictors of hemodialysis status, while sclerostin, MEG3, and MIAT were the strongest predictors of CKD.

Conclusion: Serum sclerostin, lncRNAs (H19, MEG3, and MIAT), and microRNAs (miR-135a and miR-29a) are significantly interrelated and may serve as promising non-invasive molecular biomarkers for early detection and monitoring of CKD and hemodialysis patients.

Sepsis-associated acute kidney injury (SA-AKI) is a severe complication of sepsis characterized by dysregulated inflammation, endothelial injury, and metabolic reprogramming. Among the numerous inflammatory mediators involved, S100 calcium-binding protein A12 (S100A12), a neutrophil-derived alarmin, has emerged as a key amplifier of receptor for advanced glycation end-products (RAGE) and toll-like receptor 4 (TLR4) signaling in this context. Through activation of these pathways, S100A12 drives inflammatory amplification, promotes cytokine release, pyroptotic and apoptotic cell death, endothelial dysfunction, and impaired tubular repair, thereby exacerbating renal injury. Experimental studies demonstrate that inhibition of S100A12 or blockade of its downstream signaling attenuates inflammation and tissue damage, whereas clinical evidence associates elevated circulating and urinary S100A12 levels with disease severity and adverse prognosis in sepsis. Collectively, current evidence positions S100A12 as both a mechanistic driver of inflammatory and metabolic reprogramming and a clinically actionable biomarker in SA-AKI. This review summarizes recent advances in the molecular biology and immunometabolic roles of S100A12 in SA-AKI, emphasizes its systemic versus kidney-specific effects, and discusses its translational potential as a biomarker and therapeutic target, highlighting opportunities and challenges for precision diagnostics and targeted therapies in sepsis-related organ injury.

Introduction: Colorectal cancer (CRC) is the third most diagnosed cancer worldwide and the second leading cause of cancer-related deaths. A major challenge in CRC treatment is drug resistance, which limits the efficacy of conventional therapies. Ferroptosis, an iron-dependent form of regulated cell death driven by the accumulation of reactive oxygen species (ROS), has emerged as a promising therapeutic strategy. Erastin (ER), a small-molecule compound, induces ferroptosis through ROS accumulation.

Methods: We performed microarray gene expression analysis on two CRC cell lines, HCT116 and HT-29, to examine the transcriptional response to ER exposure and identify differentially expressed genes and pathways involved in ER-induced ferroptosis.

Results: Our gene expression analysis revealed distinct transcriptional profiles between the two cell lines, and 26 transcripts commonly enriched in response to ER treatment were identified in both HCT116 and HT-29 cells. Notably, several of these genes-including ASNS, PCK2, CHAC1, and DDIT4-were significantly enriched, suggesting a conserved ferroptotic response. The induction of these genes was further confirmed in an additional CRC cell line, DLD-1. Interestingly, SOD1 and NQO1 genes, involved in oxidative stress response, were significantly upregulated by ER in HCT116 cells.

Conclusion: Our findings highlight ASNS, CHAC1, PCK2, DDIT4, and ATF3/4 as potential biomarkers for ferroptosis in CRC. Monitoring the expression of these genes may help identify patients who are responsive to ferroptosis inducers and facilitate the development of personalized treatment strategies.

Different yeast species, including Ogataea polymorpha, are often used as hosts for recombinant protein production. One of the most important factors limiting such applications is yeast-specific modifications of glycoside chains attached to secretory proteins. This problem can potentially be solved by the identification and inactivation of genes responsible for these modifications. Previously we demonstrated that the exceptional resistance of O. polymorpha to vanadate depends on the ABV1 gene responsible for the mannosylphosphorylation of protein glycoside chain in the Golgi apparatus. Here we show that mutations altering protein glycosylation in the secretory pathway can be selected in the abv1Δ mutant by screening for vanadate resistance. For one such mutant, we identified the responsible gene, which encodes a putative α-1,2-mannosyltransferase. To ensure the absence of phosphomannosylation, both O. polymorpha genes, ABV1 and MNN4, which encode mannosylphosphate transferase homologs, were inactivated. Some vanadate resistant mutants generated in this strain showed defects in N-glycosylation of a recombinant glycoprotein. This demonstrates that the effects of N-glycosylation on vanadate resistance in O. polymorpha are not mediated by phosphomannosylation per se and that identification of certain genes responsible for N-glycosylation in this yeast can be performed via selection of vanadate resistant clones.

Introduction: Kawasaki disease (KD) is an acute autoimmune vasculitis that predominantly affects children under 5 years of age. Although immune dysregulation is considered central to KD pathogenesis, the cellular heterogeneity and regulatory mechanisms underlying this process remain incompletely understood. Single-cell multi-omics technologies provide an opportunity to characterize immune alterations at high resolution.

Methods: Peripheral blood mononuclear cells (PBMCs) were obtained from two children with typical KD and two age-matched healthy controls. Integrated single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) were performed to characterize immune cell composition, transcriptional profiles, and chromatin accessibility. Comparative analyses were conducted to identify altered immune cell subsets and dysregulated signaling pathways in KD.

Results: Children with KD exhibited marked immune dysregulation, characterized by altered proportions and functional states of multiple PBMC subsets, including T cells, B cells, and natural killer (NK) cells. Notably, specific NK cell subsets were associated with the pathogenesis of intravenous immunoglobulin (IVIG)-resistant KD. Pathway analyses revealed significant dysregulation of toll-like receptor signaling, B cell and T cell receptor signaling, Th17 and Th1/Th2 differentiation, NK cell-mediated cytotoxicity, and platelet activation pathways.

Discussion: By integrating scRNA-seq and scATAC-seq data, this study delineates the heterogeneity of immune cell populations in KD at the single-cell level. The findings highlight coordinated immune and platelet activation pathways that may contribute to KD-associated inflammation and IVIG resistance. These results provide mechanistic insights into KD immunopathogenesis and suggest potential cellular and molecular targets for therapeutic intervention.

This study is a comprehensive analysis of PAR-1 - involved in thrombin interaction with platelets (PLT), present on PLT and microparticles (PMP) - to understand its role in diabetic macroangiopathy (DM) and atherosclerosis obliterans (AO). The applied RT-PCR, aggregometry, flow cytometry, a proprietary method for PMP level determination, ELISA, and multidimensional statistical analysis allowed for the determination of: PAR-1 activation levels, its polymorphisms, PLT/PMP aggregation capacity, hemostatic factors, and their interrelationships. In DM, the -506D/D and IVS-14A/A polymorphisms were significantly more frequent, whereas the -506I/D was much more common in AO, suggesting the protective properties of the I allele and its potential significance as a prognostic factor for a milder course of atherosclerosis. Similarly, increased PMP activity in DM indicates that activated PMP contribute to the atherosclerosis progression. A probable explanation for the reduced PAR-1 activation in AO is its association with the observed lower levels of von Willebrand factor. Interaction analysis showed that although the percentage of PMP did not affect the odds of AO (among AO and DM), at high PMP percentages, increased PAR-1 activation became a factor elevating the AO odds. Quantitative assessment of PAR-1 and PMP allows for predicting the severity of atherosclerosis.

MicroRNAs (miRNAs) are post-transcriptional regulators that play essential roles in cancer initiation, progression, and therapy response. Single nucleotide polymorphisms (SNPs) that affect miRNA-mRNA interactions, termed regulatory quantitative trait loci (regQTLs), have emerged as critical modulators of gene expression landscapes in tumors. These regQTLs can disrupt or enhance miRNA binding to target sites, modulate transcript stability, and influence oncogenic or tumor-suppressive pathways, thus shaping individual cancer susceptibility and clinical outcomes. In this review, we comprehensively examine the biological, computational, and translational aspects of regQTLs in cancer. We summarize key computational approaches used to investigate germline influences on miRNA-mediated regulation, including interaction-based regQTL models, miR- and isomiR-eQTL analyses, and sequence-based prediction tools. We further discuss emerging miRNA-TWAS methods, which do not directly detect regQTLs but provide a valuable upstream strategy by identifying genetically regulated miRNAs that may participate in downstream regQTL interactions. We also summarize publicly available datasets and annotation platforms supporting large-scale discovery efforts. Through critical evaluation of recent experimental validations and clinical association studies, we highlight regQTLs that serve as biomarkers for prognosis and therapy response in diverse cancers such as breast, lung, prostate, and colorectal. Furthermore, we explore the therapeutic potential of targeting miRNA-SNP interactions, including emerging strategies in miRNA-tailored immunotherapies and mRNA vaccines. We propose a strategic roadmap for future research, emphasizing the need for population-specific analyses, single-cell regQTL mapping, and mechanistic dissection using multi-omic models. By connecting genetic variation, regulatory biology, and clinical translation, this review provides a foundational framework to harness miRNA-regulatory QTLs for precision oncology.

Introduction: Carotid plaque rupture is a major cause of cerebrovascular events. This study explores the integration of hemodynamic parameters with structural biomarkers for improved risk stratification.

Methods: Fifty-seven patients with moderate-to-severe carotid stenosis underwent 4D-flow magnetic resonance imaging (MRI) and high-resolution MRI. Hemodynamic parameters [wall shear stress (WSS) and velocity] were analyzed using GT-Flow software at upstream, throat, and downstream plaque regions. After comparison of characteristic values between symptomatic and asymptomatic plaques, variables with p < 0.1 were included in the multivariate logistic regression model to identify independent risk factors.

Results: WSS was significantly higher at plaque throat (0.891 ± 0.422 Pa) and downstream (0.971 ± 0.587 Pa) versus upstream (0.649 ± 0.297 Pa; p < 0.001). Symptomatic plaques showed elevated 3D-WSSmean (1.041 ± 0.418 vs. 0.797 ± 0.402 Pa, p = 0.032), WSS up_max (1.345 ± 0.570 vs. 0.970 ± 0.383 Pa, p = 0.004), and stenosis velocity (31.7 ± 9.9 vs. 25.8 ± 10.3 cm/s, p = 0.036). The thin fibrous cap (TFC, OR = 5.34, p = 0.007) and normalized wall index (NWI, adjusted OR = 59.89, p = 0.029) independently predicted symptomatic plaques. The combined model (NWI + TFC + WSS down_max) predicted cerebral ischemic events within 6 months with an AUC of 0.809 (95% CI: 0.699-0.919).

Conclusion: Integration of downstream hemodynamic profiling (WSS) with structural biomarkers (TFC and NWI) provides a robust stratification tool for cerebrovascular risk assessment. These quantitative parameters offer potential as molecular diagnostics for plaque vulnerability.