Biochemistry and Biophysics Reports最新文献

Quantitative PCR (qPCR) remains a widely used, cost-effective method for RNA quantitation, yet many published studies inadequately comply with MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) and FAIR (Findable, Accessible, Interoperable, Reproducible) data principles. Widespread reliance on the 2^-ΔΔCT method often overlooks critical factors such as amplification efficiency variability and reference gene stability. Furthermore, the absence of raw data and analysis code limits the community's ability to evaluate potential biases and reproduce findings. Here, we primarily aim to encourage researchers to share raw qPCR fluorescence data along with detailed analysis scripts that start from raw input and produce final figures and statistical tests. Using our recently published dataset, we model the complete qPCR analytical workflow-from raw fluorescence curves through to differential expression-highlighting key decision points that can influence results. We provide fully documented R scripts illustrating how ANCOVA (Analysis of Covariance), a flexible multivariable linear modeling approach, generally offers greater statistical power and robustness compared to 2^-ΔΔCT. Additionally, simulations support ANCOVA's applicability across diverse experimental conditions. We also demonstrate how general-purpose data repositories (e.g., figshare) and code repositories (e.g., GitHub) facilitate adherence to FAIR principles and promote transparency in qPCR research. Finally, we offer graphical examples that transparently depict both target and reference gene behavior within the same figure, enhancing interpretability. This work establishes practical resources and conceptual foundations to improve rigor, reproducibility, and openness in qPCR data analysis.Image 1.

Sepsis, a pressing global health challenge, is characterized by immune dysregulation and high mortality. This study, in response to this urgent need, integrated Single-cell RNA sequencing data from 53 samples and bulk transcriptomic data from 479 sepsis patients to analyze immune microenvironment heterogeneity and develop a prognostic signature. Using the scVI algorithm, eight immune cell types were identified. B, T, and NK cells were reduced in sepsis, while neutrophils were elevated. "BayesPrism" analysis linked higher macrophage abundance to improved survival. A pro-inflammatory FCGR3A + macrophage (Macro_1_FCGR3A) subset exhibited high M1 scores, enhanced antigen presentation, and activation of the PI3K-AKT-mTOR and TNF-NFκB pathways. Pseudotime analysis showed terminal differentiation with elevated HLA-DRB1 and CXCL10. A prognostic model using "StepCox + Ridge" selected 13 key genes, including CX3CR1, achieving AUCs (Area Under the Curve) of 0.77 (training) and 0.69 (validation). CX3CR1 showed strong diagnostic potential (AUC = 0.982). These findings reveal the pivotal role of FCGR3A + macrophages in sepsis prognosis.

Bikunin is a proteoglycan with a core protein and a low sulfated chondroitin 4-sulfate (Ch4S) chain. This chain has low 4-sulfated glucuronic acid-N-acetylgalactosamine (GlcUAβ1-3GalNAcβ1-4) repeating disaccharide units, and is covalently linked to the core protein through a glucuronic acid-galactose-galactose-xylose-serine the linkage tetrasaccharide (GlcUAβ1-3Galβ1-3Galβ1-4Xylβ1-O-Ser¹⁰). The linkage tetrasaccharide is sometimes complexly modified by phosphorylation on Xyl, sulfation on Gal, fucosylation on Xyl, or sialylation on Gal, or combinations of them. Bikunin is used in obstetrics to prevent preterm birth caused by bacterial infection inflammation in Japan. However, the role of the Ch4S chain in the anti-inflammatory action of bikunin has not been fully clarified. To investigate this role, the Ch4S chain was enzymatically removed resulting in a remaining hexasaccharide linkage (GlcUAβ1-3GalNAcβ1-4GlcUAβ1-3Galβ1-3Galβ1-4Xylβ1-O-Ser¹⁰) attached to the core peptide. The effects of exogenous bikunin or Ch4S-deficient bikunin on gene expression in lipopolysaccharide (LPS)-treated uterine cervical fibroblasts were comprehensively analyzed by DNA microarray. The expression of IL-8, an inflammation marker in this inflammatory model culture, was upregulated by LPS and the upregulation was inhibited by addition of bikunin together with LPS. Increased expression of genes, related to inflammation or collagen, by LPS was also suppressed by bikunin at the same time point. Ch4S-deficient bikunin did not show significant suppression compared to original bikunin, suggesting that the Ch4S structure of bikunin is important for the suppression of the inflammatory response induced by LPS.

Objective: This study aimed to investigate the prognostic value and biological implications of cuproptosis/ferroptosis-related genes in breast cancer, and to develop a robust molecular signature for risk stratification and treatment guidance.

Methods: Integrative bioinformatic analysis of TCGA and GEO datasets identified cuproptosis/ferroptosis-related genes. LASSO and Cox regression were used to refine a multi-gene signature. Unsupervised clustering stratified molecular subtypes. Genomic alterations, immune microenvironment composition, and drug sensitivity were assessed using bioinformatic tools. Experimental validation included immunohistochemistry and Western blot using clinical samples and cell lines (MCF-10A, MDA-MB-231, BT-549, SKBR-3, MCF-7).

Results: A four-gene signature (MTDH, PROM2, IFNG, SLC1A4) with independent prognostic value was established. Subtype-specific expression patterns emerged: IFNG associated with basal-like tumors and cytotoxic immunity, while SLC1A4 (HER2-enriched/luminal) and MTDH/PROM2 correlated with immunosuppressive microenvironments. Disease progression showed stage-dependent attenuation of IFNG/MTDH/PROM2 and progressive SLC1A4 upregulation. Genomic profiling revealed recurrent mutations and frequent copy-number amplifications, notably of MTDH (60.37 %) and loci on chromosomes 2/3. Functional assays demonstrated IFNG/MTDH/SLC1A4-mediated resistance to anthracyclines and microtubule inhibitors, contrasting with PROM2-associated chemosensitivity. Unsupervised clustering identified two molecular subtypes with divergent survival, characterized by distinct pathway activation. Prognostic nomograms achieved robust predictive accuracy (C-index: 0.755). Validation confirmed upregulation of all four genes in breast cancer.

Conclusion: The cuproptosis/ferroptosis-related genes-based signature serves as a reliable prognostic tool, reflecting immune landscape remodeling and genomic instability in BRCA. These findings provide insights into subtype-specific therapeutic vulnerabilities and suggest potential strategies for targeting cuproptosis/ferroptosis pathways in precision oncology.

Aims: Individuals with diabetic nephropathy (DN), a major diabetic complication, have been disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to investigate the molecular interplay between COVID-19 and DN using bioinformatics and systems biology approaches to identify shared mechanisms and therapeutic targets for their improved synergistic clinical management.

Methods: Transcriptomic datasets (COVID-19, GSE171110; DN, GSE30528) were analyzed to identify differentially expressed genes (DEGs). Additionally, functional enrichment, protein-protein interaction (PPI) networks, transcription factor (TF)-microRNA (miRNA) regulatory networks, and drug-gene associations were explored. The diagnostic potential of hub genes was validated using receiver operating characteristic curves.

Results: In total, 3975 DEGs (2796 upregulated; 1179 downregulated) were identified in patients with COVID-19 versus controls, and 348 DEGs (93 upregulated; 255 downregulated) were found in patients with DN. Among them, 83 DEGs overlapped, presenting shared molecular pathways, including hematopoietic cell lineage, focal adhesion, and complement/coagulation cascades. PPI analysis revealed five major hub genes (IL7R, CD2, GZMA, CD3D, and FCER1A) associated with immune regulation and tissue injury, and regulatory network analysis identified 46 TFs and 88 miRNAs interacting with them. Based on transcriptomic signatures, drug repurposing candidates, such as alpha-d-mannose, aspirin, and methotrexate, were identified. Additionally, hub genes showed a high diagnostic potential (area under the curve >0.80 for COVID-19 and DN). Finally, we use external datasets to validate hub genes.

Conclusions: The findings of this study reveal shared molecular pathways and hub genes between COVID-19 and DN, providing insights into immune dysregulation and tissue injury mechanisms. Strategies associated with identified biomarkers and therapeutic candidates, including interleukin-7 receptor-targeting strategies, offer the potential for improving clinical outcomes in patients with comorbid COVID-19 and DN. Lastly, these findings underscore the value of integrative bioinformatics in guiding precision medicine approaches for complex disease interactions.

Erythropoietin (Epo) is a glycoprotein hormone primarily known for regulating red blood cell production. Beyond erythropoiesis, Epo has been reported to exert tissue-protective effects, including neuroprotective and neuroregenerative properties. While its erythropoietic activity is mediated by the Epo receptor (EpoR), its tissue-protective function has been suggested to involve alternative receptor(s), the existence of which remains unclear. To investigate the effects of Epo on neuronal cell growth and explore potential tissue-protective receptors in the future, we stably expressed the human EPO gene in the mouse neuroblastoma cell line Neuro-2A (N2A) and hippocampal neuronal cell line HT22 and investigated the effects of Epo overexpression on neuronal cell proliferation. ELISA and Western blot analyses confirmed successful Epo overexpression in both cell lines. Notably, N2A cells overexpressing Epo (N2A^+Epo) exhibited a rapid increase in cell number compared to vector-only controls, suggesting Epo-stimulated cell proliferation. Consistent with this observation, N2A^+Epo cells showed increased BrdU incorporation and elevated levels of cell proliferation markers, including proliferating cell nuclear antigen (PCNA) and nucleophosmin (NPM1), as revealed by Western blot analysis, compared to the vector-only controls. These findings indicate increased DNA synthesis and cell proliferation in N2A^+Epo cells. Additionally, CRISPR-Cas9-mediated knockdown of EPO resulted in the abrogation of cell proliferation, whereas EPOR knockdown showed no effect, suggesting that Epo promotes N2A cell proliferation through an EpoR-independent mechanism. Collectively, these findings highlight the potential of the N2A^+Epo cell line as a model for identifying alternative tissue-protective Epo receptors.

Serum amyloid A1 (SAA1) is a 122-amino acid protein that, after cleavage, matures into a 104-amino acid form. Its N-terminus is responsible for binding high-density lipoprotein (HDL), while the C-terminus maintains its structural integrity. As an acute-phase protein, SAA1 is produced by the liver in response to acute inflammation. SAA1 is also a precursor to amyloid A (AA), and its accumulation can lead to AA amyloidosis-a condition secondary to chronic inflammation that causes tissue damage and organ dysfunction. Our study explores methods to disaggregate SAA1 fibrils isolated from the cat spleen, chicken liver, and cow liver. Specifically, we investigate the use of epigallocatechin-3-gallate (EGCG), a polyphenolic flavonoid extracted from green tea known for its anti-inflammatory and antioxidant properties, to disaggregate these fibrils. Dynamic light scattering (DLS) and transmission electron microscopy (TEM) were used to analyze these fibrils after treatment with 1 % DMSO and 400 μM of EGCG in 10 mM PBS (pH 7.4). The results demonstrated that EGCG effectively reduced fibril size, as confirmed by DLS characterization, with the disappearance or diminished prominence of the 10^3-4 nm peak. Additional TEM results confirmed that EGCG disaggregated amyloid-beta fibrils isolated from Alzheimer's disease brains. These findings suggest that compounds like EGCG could be valuable in treating inflammatory and neurodegenerative conditions by disaggregating amyloid fibrils.

Allergic rhinitis (AR) is a chronic inflammatory disease with complex causes. Traditional Chinese medicine (TCM) shows promise for treating AR. This study aimed to explore the mechanisms behind TCM's effectiveness. In this study, we collected peripheral blood mononuclear cells (PBMCs) from AR patients before and after TCM treatment. Single-cell RNA sequencing (scRNA-seq) was performed to identify cell types and differentially expressed genes (DEGs) and analyzed immune cell pathways to understand how TCM treats AR. Cell-cell communication and regulatory networks were also investigated. Accordingly, 11 major cell types were annotated. The strength of the outgoing interaction between CD14⁺ monocytes and Central Memory CD4⁺ T cells and Transitional B cells decreased and in-creased, respectively. Transcription factors (TFs), VDR, and RUNX3 regulated the balance of Th1/Th2 cells to improve AR symptoms. This study confirms the therapeutic effect of Peiyuan Tongqiao Decoction on AR and provides insights into its mechanism of action.