Methods (San Diego, Calif.)[JOURNAL]
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200 papers
Integrated isotyping and CDR identification of mouse monoclonal antibodies using multiplex RT-PCR.
Hwang J, Kim E, Kim J … +2 more , Shin S, Lim HH
Methods · 2025 Dec · PMID 41015402 · Publisher ↗
The complementarity-determining regions (CDRs) of monoclonal antibodies are essential for antigen recognition and antibody engineering. Accurate determination of CDR sequences typically requires cDNA synthesis from hybri...
The complementarity-determining regions (CDRs) of monoclonal antibodies are essential for antigen recognition and antibody engineering. Accurate determination of CDR sequences typically requires cDNA synthesis from hybridoma-derived mRNA followed by sequencing of the variable regions. However, murine monoclonal antibodies are composed of diverse heavy and light chain isotypes, necessitating prior isotype determination to select appropriate primers for cDNA synthesis. Conventional workflows rely on immunoassays for isotype identification, which adds time and complexity. Here, we developed a streamlined, isotype-independent workflow for the molecular characterization of mouse monoclonal antibodies. A multiplex set of reverse transcription primers (Multiplex-RT) incorporating a universal adaptor sequence was designed to enable cDNA synthesis across major murine isotypes without prior isotype knowledge. Variable regions were subsequently amplified by isotype-specific PCR (Iso-PCR), allowing identification of antibody isotypes, IgG subclasses, and CDR sequences in a single workflow. We applied this method to characterize a murine antibody targeting the astrocytic membrane protein MLC1 and engineered a human-mouse chimeric antibody by grafting murine CDRs onto a human IgG1 backbone. The chimeric antibody retained antigen-binding activity, as demonstrated by immunoprecipitation and immunoblotting. This workflow provides a rapid and reliable strategy for sequencing and isotyping mouse monoclonal antibodies and facilitates downstream applications in antibody discovery, recombinant production, and engineering.
Analytical capability of Raman spectroscopy to detect biochemical changes in red blood cell membrane disorders.
Sarmah P, Khanna R, Bankapur A
Methods · 2025 Dec · PMID 40983255 · Publisher ↗
Detection of RBC membrane disorders with currently available modalities, such as osmotic fragility test (OFT), EMA binding test, ektacytometry, sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE), and n...
Detection of RBC membrane disorders with currently available modalities, such as osmotic fragility test (OFT), EMA binding test, ektacytometry, sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE), and next-generation sequencing (NGS), has been challenging as they either lack biochemical inferences or are complex in nature. Raman spectroscopy, a highly analytical method known to produce molecular fingerprints, has proven potential in extracting biochemical information from single individual cells. Recent advancements in membrane-targeted Raman measurements using excitation spots of donut and line intensity profiles can transform lab-on-chip Raman-activated cell sorting methods into a potential technique for RBC membrane disorder diagnosis. We, therefore, conjecture that Raman spectroscopy can be a strong contender as a diagnostic modality in RBC membranopathies. In this comprehensive review, we have attempted to encompass the disorder-specific molecular defects, present diagnostic modalities, and their limitations, and explored the translational possibility of Raman spectroscopy as a diagnostic tool for membranopathies.
Advancing antisense oligonucleotide delivery through click chemistry based chemical conjugation with designed short non-cationic peptides for Duchenne muscular dystrophy.
Ghosh S, Arshi MU, Ghosh S … +9 more , Jash M, Mukherjee N, Jana A, Shastry A, Karanth D, Nishad K, Rana NK, Bhattacharyya S, Ghosh S
Methods · 2025 Dec · PMID 40962198 · Publisher ↗
Duchenne muscular dystrophy (DMD) is a fatal X-linked neuromuscular disease caused by frame shift mutations in the gene encoding dystrophin. 2́-O-methyl phosphorothioate (2'-OMePS) serves as an antisense RNA platform cli...
Duchenne muscular dystrophy (DMD) is a fatal X-linked neuromuscular disease caused by frame shift mutations in the gene encoding dystrophin. 2́-O-methyl phosphorothioate (2'-OMePS) serves as an antisense RNA platform clinically used in DMD patients to facilitate exon skipping and production of an internally truncated, yet functional dystrophin protein. Effective delivery and uptake of antisense oligonucleotides (ASOs) by target cells are crucial for their efficacy. Peptide-conjugated ASOs offer a promising next-generation platform, where a cell-penetrating peptide (CPP) is linked to the 2'-OMePS backbone to enhance cellular uptake. Herein, we designed and synthesized a new non-cationic short CPP sequence that can be efficiently conjugated with the negatively charged 2'-OMePS ASO backbone using click chemistry. Conjugation of the lead peptide ETWWK to 2'-OMePS ASO resulted in significant cellular internalization with precise nuclear localization of the ASO cargo. Cellular uptake was assessed in C2C12 and human DMD patient-derived myoblast cells via fluorescence microscopy and flow cytometry. Additionally, the synthesized ETWWK-ASO conjugate exhibits a significant 1.94 fold upregulation of dystrophin protein in the clinically relevant DMD patient-derived cell line. Our findings suggest that the identified peptide holds promise for facilitating ASO delivery at the site of splicing. This study highlights the efficient conjugation of CPPs to negatively charged 2'-OMePS ASO through tailored conjugation strategies, and will eventually be a therapeutic avenue for future ASO-based DMD treatments.
Optimization of C stable isotope labeling for the study of tricarboxylic cycle intermediates in mouse models.
Laro J, Ness M, Godinho J … +2 more , Coats R, McCall LI
Methods · 2025 Dec · PMID 40939985 · Full text
The tricarboxylic acid cycle (TCA), also known as the Krebs Cycle or the citric acid cycle, is an essential metabolic pathway involved in energy production that is often impacted by disease, making it of key interest to...
The tricarboxylic acid cycle (TCA), also known as the Krebs Cycle or the citric acid cycle, is an essential metabolic pathway involved in energy production that is often impacted by disease, making it of key interest to identify effective, affordable, and simple ways to monitor the impact of disease on TCA metabolism. C-based stable isotope labeling is a useful technique to track pathway alterations in living hosts. However, infusion-based methodologies are slow and expensive despite achieving steady-state labeling. Bolus-based methods are cheaper, faster, and compatible with biohazardous models, but require optimization to achieve maximum labeling. Herein, we performed bolus-based stable isotope labeling experiments in mouse models to identify the optimal dosage amount, label administration length, fast length prior to label administration, C-labeled precursor, and route of administration for the TCA cycle in the esophagus, heart, kidney, liver, plasma, and proximal colon. C-glucose at a concentration of 4 mg/g administered via intraperitoneal injection followed by a 90 min label incorporation period achieved the best overall TCA labeling. For most organs, a 3 h fast prior to label administration improved labeling, but labeling in the heart was better with no fasting period, showcasing the need to optimize methodology on an organ-by-organ basis. We also identified that bolus administration of glucose provided little impact on metabolism compared to vehicle control. The experiments outlined here provide critical information for designing in vivo stable isotope labeling experiments for the study of the TCA cycle.
ResDeepGS: A deep learning-based method for crop phenotype prediction.
Yan C, Li J, Feng Q … +2 more , Luo J, Luo H
Methods · 2025 Dec · PMID 40930401 · Publisher ↗
Genomic selection (GS) is a breeding technique that utilizes genomic markers to predict the genetic potential of crops and animals. This approach holds significant promise for accelerating the improvement of agronomic tr...
Genomic selection (GS) is a breeding technique that utilizes genomic markers to predict the genetic potential of crops and animals. This approach holds significant promise for accelerating the improvement of agronomic traits and addressing food security challenges. While traditional breeding methods based on statistical or machine learning techniques have been useful in predicting traits for some crops, they often fail to capture the complex interactions between genotypes and phenotypes. Additionally, these methods struggle to handle large-scale data, limiting their predictive performance. Recent advancements in deep learning offer a promising solution by better capturing nonlinear relationships and gene interactions. In this study, we propose a novel crop phenotype prediction method, ResDeepGS, which leverages deep learning techniques. The model consists of two main components: the feature selection module and the phenotype prediction module. The feature selection module employs an incremental recursive feature elimination method, combining the strengths of recursive feature elimination and incremental learning to improve both the efficiency and reliability of feature selection. The phenotype prediction module integrates an enhanced multi-layer convolutional neural network with residual structures and dropout strategies to better capture complex relationships in gene data, accelerate convergence, and reduce overfitting. Through extensive experimentation, we demonstrate that ResDeepGS outperforms current state-of-the-art methods on three datasets: wheat, maize, and soybean. Notably, on the wheat dataset, ResDeepGS improved prediction accuracy by 5% to 9%, highlighting its superior performance in genomic selection tasks. These results underscore the robustness and adaptability of ResDeepGS, offering a promising solution for enhancing crop breeding efficiency and addressing future food security challenges.
Michaelis-Menten kinetics of RasGAP proteins by a rapid fluorescence-based assay.
Paul ME, Vish KJ, Boggon TJ
Methods · 2025 Dec · PMID 40930400 · Full text
Ras small GTPases are essential for a wide range of cellular processes. These proteins cycle between the GDP-loaded and GTP-loaded states, and the actions of GTPase activating proteins (GAPs) are necessary to stimulate R...
Ras small GTPases are essential for a wide range of cellular processes. These proteins cycle between the GDP-loaded and GTP-loaded states, and the actions of GTPase activating proteins (GAPs) are necessary to stimulate Ras-mediated GTP hydrolysis. Here, we provide a protocol to achieve Michaelis-Menten kinetic profiling of GAP-mediated stimulation of a small GTPase by real-time monitoring of inorganic phosphate release in vitro. This is achieved using fluorescence of the Phosphate Sensor protein, an MDCC conjugate with periplasmic phosphate binding protein (PstS). We use H-Ras small GTPase pre-loaded with GTP and its stimulation by p120RasGAP (RasGAP, RASA1) as an example of this protocol. We discuss protocol design, assay development, data collection, processing, and analysis. Typical assays comprise up to twenty simultaneous reactions with phosphate production rates on the order of tens of nM/s. We also provide guidelines for the optimization of reagent conditions, particularly salt concentrations, and assess their functional impact. The described protocol provides a convenient and comprehensive method to achieve accurate monitoring of small GTPase activation by GAP proteins using widely available materials and suitable to a range of applications.
Unveiling the pathogenicity of allosteric protein mutations via multifaceted feature ensembling.
Zhang H, Li X, Huang J … +4 more , Li Y, Cai S, Wang H, Wei Y
Methods · 2025 Dec · PMID 40930399 · Publisher ↗
Allostery proteins play a central role in biological processes and systems. Uncovering the biological effects of allosteric protein mutations and their role in disease progression remains a significant challenge. Theoret...
Allostery proteins play a central role in biological processes and systems. Uncovering the biological effects of allosteric protein mutations and their role in disease progression remains a significant challenge. Theoretically, computational approaches hold the potential to enable large-scale interpretation of genetic variants in allosteric proteins. Nevertheless, general-purpose variant effect prediction (VEP) methodologies overlook the characteristic disparities across different genes. What is more critical is that individual tools frequently display inconsistencies, biases, and fluctuations in quality. Consequently, the predictions obtained from existing VEP approaches are considered insufficiently reliable. In the present research, we constructed an a multifaceted-feature-based ensemble learning approach to forecast the pathogenicity of missense mutations within allosteric proteins. The proposed method used categorical boosting to integrate four types of features, namely, sequence information, AlphaFold2-extracted biochemical properties, prediction scores from other VEP methods, and allele frequency from gnomAD. Our method demonstrated superior performance with an AUC of 0.912 when tested on a benchmark allosteric protein dataset, outperforming 22 general VEP methods. To facilitate the identification of pathogenic mutations in the sea of rare variants discovered as sequencing studies expand on a large scale, we provided the pathogenicity probabilities of all potential amino acid substitutions in 202 allosteric-protein-encoding genes. To sum up, our research indicates that multifaceted-feature-based ensemble learning models can offer valuable independent evidence for interpreting missense mutations in allosteric proteins, which will be broadly applicable in both research and clinical contexts.
Deciphering cellular heterogeneity: Breakthroughs and prospects of single-cell-level SERS analysis in precision medicine.
Chen B, Gao J, Sun H … +3 more , Liu Y, Zhao Y, Qiu X
Methods · 2025 Dec · PMID 40925516 · Publisher ↗
Single-cell surface-enhanced Raman scattering (SERS) has emerged as a powerful tool for precision medicine owing to its label-free detection, ultrasensitivity, and unique molecular fingerprinting. Unlike conventional bul...
Single-cell surface-enhanced Raman scattering (SERS) has emerged as a powerful tool for precision medicine owing to its label-free detection, ultrasensitivity, and unique molecular fingerprinting. Unlike conventional bulk analysis, it enables detailed characterization of cellular heterogeneity, with particular promise in circulating tumor cell (CTC) identification, tumor microenvironment (TME) metabolic profiling, subcellular imaging, and drug sensitivity assessment. Coupled with microfluidic droplet systems, SERS supports high-throughput single-cell analysis and multiparametric screening, while integration with complementary modalities such as fluorescence microscopy and mass spectrometry enhances temporal and spatial resolution for monitoring live cells. Despite hurdles in nanoprobe safety, complex spectral interpretation, and clinical translation, advances in AI-driven data processing (e.g., convolutional neural networks) and miniaturized devices are accelerating progress toward intraoperative guidance, improved liquid biopsy, and primary healthcare adoption. Looking ahead, its applications in single-cell metabolomics, exosome studies, and microbial detection hold promise for uncovering disease mechanisms and fostering personalized diagnostics and therapeutics.
Strain promoted click labeling of oligonucleotides on solid-phase support.
Beranova M, Grossova P, Demuth J … +4 more , Kostelansky F, Novakova V, Zimcik P, Miletin M
Methods · 2025 Dec · PMID 40921341 · Publisher ↗
Chemically modified oligonucleotides (ONs) are essential tools in molecular biology, diagnostics, and therapeutics. Strain-promoted azide-alkyne cycloaddition (SPAAC) offers an efficient and bioorthogonal method for ON f...
Chemically modified oligonucleotides (ONs) are essential tools in molecular biology, diagnostics, and therapeutics. Strain-promoted azide-alkyne cycloaddition (SPAAC) offers an efficient and bioorthogonal method for ON functionalization. While SPAAC reactions on solid-phase support provide distinct advantages, particularly for the incorporation of lipophilic labels, factors influencing their efficiency remain poorly characterized. The interplay between the physicochemical properties of the modifying molecule, the nature of the solid support, and the labeling site within the ON chain has not been systematically evaluated. In this study, we systematically investigate how modifying molecule properties (size, polarity) and concentration, solid support type, labeling site within the ON chain, and reaction time influence efficiency of labeling. Our findings demonstrate that while polar modifying molecules react efficiently across all solid supports, lipophilic molecules can exhibit reduced reactivity on glass-based supports, particularly in positions close to the 3́-end of the oligonucleotide attached to the support. We further show that conjugation at the 5'-terminus consistently yields the highest efficiencies, with a gradual decline observed as the modification site approaches the 3'-end. A 1 mM concentration of labeling reagent was sufficient to achieve high yields on polystyrene support for all labels and on CPG 500 for the polar labels. The size of the modifying molecule had a lesser effect compared to other factors. The method also benefits from recovery and reusability of the unreacted label. These results enable the rational design of efficient ON labeling protocols on solid-phase support while minimizing reagent consumption, contributing to both cost-effectiveness and environmental sustainability.
AI-augmented prediction of high-risk PINK1 variants associated with Parkinson's disease: integrating multilayered bioinformatics, MD simulation, and deep learning.
Rehman HU, Warraich DA, Rehman A … +12 more , Fatima I, Meng Y, Aldaw M, Ding Y, Zhang R, Ni Y, He Z, Zhang H, Wang Z, Feng L, Yu Y, Liao M
Methods · 2025 Dec · PMID 40914318 · Publisher ↗
Parkinson's disease is a prevalent neurodegenerative disease, in which genetic mutations in many genes play an important role in its pathogenesis. Among these, a mutation in the PINK1 gene, a mitochondrial-targeted serin...
Parkinson's disease is a prevalent neurodegenerative disease, in which genetic mutations in many genes play an important role in its pathogenesis. Among these, a mutation in the PINK1 gene, a mitochondrial-targeted serine/threonine putative kinase 1 that protects cells from stress-induced mitochondrial dysfunction, is implicated in autosomal recessive Parkinsonism. However, the exact etiology is not well understood. Therefore, this study aimed to identify the most damaging non-synonymous single-nucleotide polymorphisms (nsSNPs) distributed in the kinase domain of the PINK1 gene and their structural and functional alterations using a range of bioinformatics and deep learning tools. Next, to find the possible impact of these mutations on PINK1 interactions and binding affinities, a protein-protein interaction and molecular docking analysis were conducted. Finally, molecular dynamics (MD) simulations were performed to observe the stability and dynamic behaviour of the pathogenic SNPs on the PINK1 protein over time. Our integrated bioinformatics and deep learning approaches predicted 5 SNPs (C166R, E240K, D362N, D362Y, and C388R) as high-risk candidates for disrupting PINK1 structure and function. In conclusion, we propose that the pathogenicity of these variants may provide an important clue to understanding the mechanism by which pathogenic nsSNPs contribute to PD, thereby enhancing future diagnostic value for the disease and serving as potential targets for new drugs.
Capturing G protein-coupled receptors into native lipid-bilayer nanodiscs using new diisobutylene/maleic acid (DIBMA) copolymers.
Chu C, Vargas C, Barbosa MC … +7 more , Sommerhage S, Rechberger GN, Pahovnik D, Žagar E, Schröder GF, Keller S, Etzkorn M
Methods · 2025 Dec · PMID 40914317 · Publisher ↗
Many membrane proteins, including G protein-coupled receptors (GPCRs), are susceptible to denaturation when extracted from their native membrane by detergents. Therefore, alternative methods have been developed, includin...
Many membrane proteins, including G protein-coupled receptors (GPCRs), are susceptible to denaturation when extracted from their native membrane by detergents. Therefore, alternative methods have been developed, including amphiphilic copolymers that enable the direct extraction of functional membrane proteins along with their surrounding lipids. Among these amphiphilic copolymers, styrene/maleic acid (SMA) and diisobutylene/maleic acid (DIBMA) polymers have been extensively studied. Despite their many benefits, SMA and DIBMA polymers also have considerable drawbacks limiting their applications. Herein, we describe a series of new amphiphilic copolymers derived from DIBMA via partial amidation of the carboxylate pendant groups with various biocompatible amines. We characterize the new polymer's nanodisc-forming properties and ability to extract the melanocortin 4 receptor (MCR), a prototypical class A GPCR. While each new DIBMA variant displays features that may be favorable for selected applications, we identified a PEGylated DIBMA variant called mPEG-DIBMA as particularly promising. In the tested system mPEG-DIBMA abolishes unspecific interactions and outperforms other polymers by achieving higher extraction efficiencies of MCR from Sf9 insect cell membranes. The new nanodisc-forming polymer combines two key advantages that are crucial for investigating GPCRs in a well-defined but still native lipid-bilayer environment, thus paving the way for manifold future applications.
Efficient RNA nucleotide encoding enhances the accurate prediction of ac4C modifications.
Li N, Wang X, Zeng M … +3 more , Cao F, Qiu K, Qiao J
Methods · 2025 Dec · PMID 40897232 · Publisher ↗
RNA N4-acetylcytidine (ac4C) modification plays a vital role in gene regulation and cellular function. Accurate identification of ac4C sites is essential for elucidating their biological significance. However, existing p...
RNA N4-acetylcytidine (ac4C) modification plays a vital role in gene regulation and cellular function. Accurate identification of ac4C sites is essential for elucidating their biological significance. However, existing prediction methods struggle to capture complex sequence patterns, limiting their accuracy. To address this, we propose GO-ac4C, an efficient prediction framework that integrates byte-pair encoding with nucleotide compositional features. GO-ac4C employs dynamic byte-pair encoding to learn optimal subsequence representations and enhances them with compositional features to effectively capture key motifs in RNA sequences. Experimental results demonstrate that GO-ac4C significantly outperforms state-of-the-art methods across multiple evaluation metrics and offers new insights into the mechanisms of RNA modification.
Rapid in vitro and computer-aided method for assessing synergistic interactions between NSAIDs and analgesics.
Silva F, Costa G, Veiga F … +5 more , Moura V, Dias F, Cerqueira F, Medeiros R, Paiva-Santos AC
Methods · 2026 Jan · PMID 40889536 · Publisher ↗
Pain is a complex phenomenon that plays a significant role in various diseases, influencing both the physical and psychological well-being of individuals. In clinical practice, combining nonsteroidal anti-inflammatory dr...
Pain is a complex phenomenon that plays a significant role in various diseases, influencing both the physical and psychological well-being of individuals. In clinical practice, combining nonsteroidal anti-inflammatory drugs (NSAIDs) with analgesics, such as paracetamol or metamizole, has become a widely adopted strategy to manage pain. Although the synergistic effects of combining NSAIDs with analgesics are well recognized in clinical practice, this approach is primarily based on empirical clinical experience. Our work aims to present a rapid method for evaluating the anti-inflammatory effects of drug combinations through in vitro assays combined with computer-aided data processing and analysis. We conducted two simple and rapid in vitro assays, the Griess and DPPH assays, to evaluate the effects of NSAID-analgesic combinations and demonstrate their synergistic interactions, using the free web application SynergyFinder Plus. This computer-aided analysis enabled a quantitative assessment of drug interactions, enhancing the interpretation of the experimental data. Furthermore, to better understand the results obtained from previous experiments, we analysed the anti-inflammatory effects of ketoprofen and dexketoprofen in combination with metamizole and paracetamol through quantitative real-time PCR (qRT-PCR). Our findings reveal synergistic interactions between NSAIDs and analgesics in terms of their anti-inflammatory and antioxidant activities. This work could be the first step for the study of the mechanisms behind the synergistic interactions between NSAIDs and analgesics for the treatment of pain, mainly when inflammatory processes are involved. Consequently, this study aims to contribute to the exploration of non-opioid drug combinations, addressing the urgent need for alternative analgesic strategies that minimize opioid use.
Validation of combo ichroma as a reliable concentration-based alternative for AST and ALT measurement in liver disease monitoring.
Kim M, Kim SA, Kim JM … +6 more , Kim HY, Yoon HY, Park SW, Park D, Han JS, Suk KT
Methods · 2025 Nov · PMID 40882780 · Publisher ↗
BACKGROUND: Traditional assays for aspartate aminotransferase (AST) and alanine aminotransferase (ALT) measure enzymatic activity, which degrades during long-term frozen storage, threatening the accuracy of the assay. In...
BACKGROUND: Traditional assays for aspartate aminotransferase (AST) and alanine aminotransferase (ALT) measure enzymatic activity, which degrades during long-term frozen storage, threatening the accuracy of the assay. Instead, Combo ichroma (CI), a fluorescence immunoassay that quantifies AST and ALT concentrations, is a robust alternative for retrospective and point-of-care liver function testing, free from the influence of long-term storage. METHODS: Serum samples from 256 individuals (controls and patients with hepatitis, cirrhosis, or liver cancer) were collected and stored at -80 °C for an average of three years. AST and ALT were measured using CI, the 7180 clinical analyzer (HT), and Atellica CH 930 analyzer performed immediately after collection (HL). Correlations between AST, ALT, and AST/ALT ratios were analyzed. Random Forest Regression (RFR) models using CI or HT data were developed to predict HL-derived AST/ALT ratios. RESULTS: CI-AST showed strong correlation with HL-AST across all groups (R2 > 0.95), outperforming HT-AST, especially in controls (R2 = 0.58). CI-ALT moderately correlated with HL-ALT (R2 = 0.87), surpassing HT-ALT (R2 = 0.71). AST/ALT ratios varied across methods due to ALT variability, but RFR using CI data accurately predicted HL ratios (R2 = 0.85-0.91). Subgroup analysis confirmed CI's superior concordance across etiologies. CONCLUSIONS: CI enables activity-independent, reliable measurement of AST and ALT even after extended storage, outperforming enzymatic assays in precision and correlation. Its simplicity, and compatibility with machine learning models position CI as a promising tool for liver enzyme diagnostics in both clinical and resource-limited settings.
Volumetric dried blood spot microsampling: A sustainable, patient-friendly, and practical approach for retinol and α-tocopherol analysis in a clinical setting.
Suwanvecho C, Krčmová LK, Švec F
Methods · 2025 Nov · PMID 40850402 · Publisher ↗
Dried blood spot (DBS) technique has gained significant attention due to the growth of decentralized diagnostics. This technique reduces the number of hospital visits for patients and the workload for personnel in specia...
Dried blood spot (DBS) technique has gained significant attention due to the growth of decentralized diagnostics. This technique reduces the number of hospital visits for patients and the workload for personnel in specialized hospitals. This microsampling method provides an environmentally friendly (green) and patient-friendly alternative to conventional phlebotomy. Challenges related to sample heterogeneity in traditional DBS cards have been overcome by the volumetric DBS sampling using new types of commercially available devices. Due to the unstable nature of the analytes, commercial volumetric DBS devices allow blood sampling at primary care units in remote settings and facilitate transport it via temperature-controlled systems. Blood sample stability has improved from 24 h at 4-8 °C to 30 days at -80°C. DBS also requires over 1000 times less shipping and storage space than liquid blood. We optimized the DBS method to require only 10 µL of blood and achieve extraction efficiencies of over 90 % for retinol when the result from validated method is the reference value. However, α-tocopherol recovery varied from 53 to 75 % depending on the filter paper type used. Furthermore, we successfully developed a liquid-liquid extraction method for both analytes from whole blood, with over 90 % recovery. Our approaches eliminate the need for separate serum and erythrocyte extractions, simplify sample preparation, and reduce reagent use and energy consumption. Both devices enable reliable volumetric collection. Our approach makes micronutrient monitoring more accessible and enables sample collection in decentralized settings. This aligns with the objectives of green analytical chemistry and universal health coverage.
Optimized CUT&Tag enables robust epigenome profiling in Schizosaccharomyces pombe.
Huang CZ, Zhou KD, Ma W
Methods · 2025 Nov · PMID 40850401 · Publisher ↗
We optimized permeabilization for CUT&Tag in S. pombe, enabling robust H3K9me3 profiling using lightly fixed permeabilized sepheroplasts, overcoming limitations of ChIP-seq including crosslinking artifacts and high cell...
We optimized permeabilization for CUT&Tag in S. pombe, enabling robust H3K9me3 profiling using lightly fixed permeabilized sepheroplasts, overcoming limitations of ChIP-seq including crosslinking artifacts and high cell input. We established an optimized Cleavage Under Targets and Tagmentation (CUT&Tag) protocol for high-resolution epigenome profiling inSchizosaccharomyces pombeusing Critical permeabilization refinements identified Lywallzyme as the optimal enzyme for spheroplast generation (>95 % efficiency in 60 min at 10 mg/mL), outperforming Zymolyase-20 T and combinatorial treatments. Systematic parameter optimization revealed concentration-dependent digestion kinetics and an inverse cell load-efficiency relationship (5 × 10 cells achieving > 90 % conversion in 50 min at 5 mg/mL). Validated through H3K9me3 mapping in wild-type andclr4Δstrains (10⁶ cells/replicate), this approach captured specific heterochromatic enrichment at centromeres/telomeres with complete signal ablation in mutants, while reduced spike-in DNA (0.2 pg) significantly enhanced signal-to-noise ratios. The protocol enables robust epigenomic analysis with minimal cell input and enhanced resolution.
Coffee - a ubiquitous substitute for uranyl acetate in staining of biological ultrathin sections for electron microscopy studies.
Mayrhofer C, Zandonella R, Salvenmoser W … +1 more , Letofsky-Papst I
Methods · 2025 Nov · PMID 40848866 · Publisher ↗
The use of uranyl acetate, a staining agent successfully used for decades in electron microscopy of biological specimens, is now strictly regulated by law due to its toxicity and radioactivity. It is even banned in some...
The use of uranyl acetate, a staining agent successfully used for decades in electron microscopy of biological specimens, is now strictly regulated by law due to its toxicity and radioactivity. It is even banned in some laboratories. In the meantime, there are a number of substitutes on the market, none of which comes close to the very good staining results of uranyl acetate, or only partially, and some of which are also toxic. In this paper, two alternatives to uranyl acetate are presented, namely coffee, which is used in countless households, and pure chlorogenic acid, which is a component of coffee. We used the well-known zebrafish as biological test material, focusing on the mitochondrial membranes. The staining ability of coffee and chlorogenic acid compared with commercially available staining agents as well as uranyl acetate is assessed by the interference contrast between membranes and their environment. This work also describes how a subjective impression of good or bad contrast can be cast into an objective and comparable numerical value.
Exploiting Anisotropic Orientation in Nanoparticle-Aided Cryo-Electron Microscopy Sampling.
Kim Y, Kim C, Yang Y … +1 more , Ihee H
Methods · 2025 Nov · PMID 40848865 · Publisher ↗
Measuring the conformational distribution of small proteins is essential to understanding their role in biological systems. Multi-Tilt Nanoparticle-aided cryo-electron microscopy sampling (MT-NACS) was devised to measure...
Measuring the conformational distribution of small proteins is essential to understanding their role in biological systems. Multi-Tilt Nanoparticle-aided cryo-electron microscopy sampling (MT-NACS) was devised to measure the three-dimensional interparticle distance distribution (P(d)) of two gold nanoparticles (AuNPs) labeled on a protein by taking cryogenic electron microscopy (cryo-EM) images at multiple-tilt angles. However, tracking the same particles in a pseudo-tomographic manner during the multi-tilt cryo-EM experiments and data analysis requires extensive time and effort. Here, we report that proper incorporation of AuNP pair angle distribution allows reliable determination of the P(d) only using the cryo-EM images collected at a single tilt angle. The trends of structural changes in calmodulin (CaM) measured by single-tilt angle NACS (ST-NACS) and MT-NACS are consistent, as the tendencies of changes in the P(d) of AuNP-labeled CaM measured by both methods are similar. Our approach provides an efficient tool for measuring the conformational distribution and structural transition of small proteins.
PCR-generated DNA templates enable efficient, rapid, and cost-effective mRNA synthesis.
Kumar N, Hazell NC, Bei J … +2 more , Nguyen T, Hu H
Methods · 2025 Nov · PMID 40825451 · Publisher ↗
In vitro transcription (IVT) is a widely used technique for mRNA synthesis in both basic research and the development mRNA-based vaccines and therapies. The efficiency of IVT critically depends on the quality and integri...
In vitro transcription (IVT) is a widely used technique for mRNA synthesis in both basic research and the development mRNA-based vaccines and therapies. The efficiency of IVT critically depends on the quality and integrity of the linear DNA templates. The conventional method for template DNA preparation involves plasmid propagation in bacteria followed by enzymatic linearization, which is labor-intensive and costly. Here, we describe a cell-free, PCR-based approach for generating high-quality, high-yield linear DNA templates. We extensively compared the PCR-based method with the conventional plasmid-based approach in terms of IVT efficiency, mRNA production, and the immunogenicity of the resulting mRNA-LNP (lipid nanoparticle) vaccines. Compared to the plasmid-derived DNA, the PCR-based method yielded higher amounts of both DNA templates and transcribed mRNA, while maintaining mRNA quality and integrity. Importantly, mRNA-LNP vaccines encoding the SARS-CoV-2 spike protein, generated from both methods, elicited robust and comparable immune responses in mice, with no significant differences observed between the two template methods. Our findings highlight the advantages of PCR-generated DNA templates as a rapid, efficient, and cost-effective alternative for mRNA synthesis, with broad applications in vaccine and therapeutic development.
Insights of Surface Enhancing Raman Spectroscopy for Biomedical Application.
Sharma N, Singh A, Ratnesh RK … +3 more , Adhana A, Tyagi L, Singh J
Methods · 2025 Nov · PMID 40812527 · Publisher ↗
Raman spectroscopy is a powerful, non-invasive analytical technique that enables rapid identification of molecules based on their unique spectral fingerprints. Its sensitivity has been significantly enhanced through the...
Raman spectroscopy is a powerful, non-invasive analytical technique that enables rapid identification of molecules based on their unique spectral fingerprints. Its sensitivity has been significantly enhanced through the use of metal nanoparticles in Surface-Enhanced Raman Spectroscopy (SERS), where molecules adsorbed on rough metallic surfaces or colloids produce Raman signals amplified by several orders of magnitude. This enhancement has opened new possibilities for molecular detection, particularly in surface chemistry and biomedical diagnostics. In clinical applications, timely and accurate diagnosis is critical, yet conventional bioanalytical methods often require multiple biochemical tests, leading to delays that are especially problematic in emergency settings. SERS provides a promising alternative, offering high sensitivity, specificity, and rapid analysis with minimal sample preparation. This review explores the integration of Raman spectroscopy-especially SERS-for both in vivo and ex vivo biomedical diagnostics. It covers sample preparation techniques, spectral data interpretation, and the correlation of Raman signals with disease-specific biomarkers. Special focus is given to the application of Raman-based methods in diagnosing brain disorders, various cancers, drug abuse, and COVID-19. Finally, the article discusses future prospects and challenges to guide the continued advancement of biomedical Raman technologies.
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