Flavor esters are extensively used in food and cosmetic industries, yet their sustainable production remains challenging. This study developed a lipase bioreactor through artificial antibody-antigen-mediated immobilization for biocatalytic flavor ester synthesis via transesterification. Artificial antigens were prepared by lipase modification with p-nitrobenzaldehyde, while artificial antibodies were synthesized using 2-(4-nitrophenyl)-1,3-dioxolane (acetal-protected p-nitrobenzaldehyde analogue) as template molecules. These components self-assembled into immobilized lipase with 82.24 ± 0.13% immobilization efficiency, 17.59 ± 0.12 mg/g capacity, and 8.81 ± 0.27 U/mg specific activity. Integrating molecular simulations with acyl donor screening, the bioreactor achieved 97.18 ± 0.93% yield for cinnamyl acetate synthesis from cinnamyl alcohol and vinyl acetate. The system demonstrated exceptional continuous catalysis and scalability, confirming industrial translation potential. Successful synthesis of cinnamyl butyrate (86.25 ± 3.34%) and benzyl acetate (90.68 ± 2.25%) further established its versatility as a platform for diverse flavor ester production.

The overlap HPLC chromatograms of ATP standard (red) and ATP in cells (blue). Poroshell 120 EC-C18 (3 × 150 mm, 2.7 μm), 25°C, pH 6.8 buffer solution of 0.05 mol/L KH2PO4 - 0.05 mol/L K2HPO4 (V:V = 1:1) as mobile phase, 0.6 mL/min, 254 nm.

OBJECTIVES:To explore the reasons behind the lack of commutability in protein solution reference materials (RMs) and seeks to eliminate these factors in order to develop commutable reference materials, using human insulin (hINS) as example, to meet the growing demand for standardization in in vitro diagnostics. METHODS:A concept for development of commutable protein solution RMs by matrix matching, structural-activity analysis, higher order structure adjustment, active concentration measurement, and commutability verification was investigated. This concept was applied in the development of hINS solution candidate certified RMs (cCRMs). Bovine serum solution (7 %) was used for matrix matching and hINS-Zn2+ aggregates were found to be the key for commutability. hINS-Zn2+ aggregates were constructed in vitro and the presence of the aggregates was confirmed through circular dichroism spectroscopy and mass photometry. The active concentration of the aggregate solution was analyzed using surface plasmon resonance. Then, six levels of hINS solution cCRMs were developed and the commutability was evaluated using both CLSI EP14 and IFCC approaches. RESULTS:The hINS solution cCRMs exhibited excellent homogeneity and remained stable for at least 6 months when stored at -70 °C. The relative uncertainties of these cCRMs ranged from 4.0 to 5.0 %. Both CLSI EP14 and IFCC commutability evaluations indicated good commutability between routine chemiluminescent immunoassay systems. CONCLUSIONS:A new concept for developing commutable RMs with pure protein material, which avoids the challenges in developing commutable matrix RMs and should contribute to the standardization of clinical test results for proteins, was successfully applied to develop commutable hINS solution cCRMs.

Measurement of drug inhibitory activity on cancer cells is essential for anticancer drug development and cancer treatment. Conventional anticancer drug sensitivity testing (DST), such as colorimetric, bioluminescence, and fluorescence analysis, usually relies on culture-based endpoint detection, and the results are available only after several days. Developing alternative cost-effective and rapid screening drugs methods is highly desirable. The single cell metabolic activity can be characterized by D2O-single cell Raman spectroscopy to measure the Raman intensity ratio of C-D/(C-D+C-H). Relative activity is expressed by the ratio of cell metabolic activity without the drug and with the drug. The IC50 values of drugs on single cells can be observed through the decrease in the Raman peak area of C-D peak and calculated from the equation fitted from the curves of relative activity and drug concentration. A simple, sensitive and repeatable D2O-single cell Raman spectroscopy method has been developed to quantify the inhibitory activity of anticancer drug on cancer cell metabolism. The IC50 values obtained from A549 cells incubated with cisplatin and taxol are comparable with the results of CCK-8 and ATP luminescent cell viability assay. The method is sensitive and can give the cell metabolic activity in single cell scale and presenting the metabolic heterogeneity of cells. Our study presents the D2O-single cell Raman spectroscopy assay as a powerful and versatile tool to determine the single cell viability based on the whole cell metabolism, which can be applied broadly in various fields. In the future, calibration method should be established to improve accuracy and traceability. Furthermore, high-resolution and high through-put D2O metabolic activity assay at organelle level combined with AI should be developed to elucidate the mechanism of drugs and visualize their distribution.

The analysis of lipophilic shellfish toxins (LSTs) in foods is severely hampered by matrix interference and laborious sample preparation. To address these issues, we developed a split-flow in-situ matrix cleanup electroextraction (SF/ISMC-EE) method coupled with LC-MS/MS. This approach tackles two major limitations in electric field-assisted sample preparation (EFASP): bubble formation and difficulty of direct extraction from complex solid matrices. SF/ISMC-EE uses a multi-channel split-flow design to suppress bubbles, enabling high-voltage rapid enrichment (300 s). Chitosan-mediated in-situ cleanup releases analytes and blocks impurity co-extraction, eliminating need for matrix-matched calibration. The "electric field + cleanup materials" strategy allows direct electroextraction from solid/semi-solid foods, integrating extraction, cleanup, and enrichment. As the first EFASP method applied to LST analysis, it was validated with certified reference materials and real samples, demonstrating high accuracy, precision, and low detection limits meeting EU regulations. This work provides a robust and efficient tool for food safety monitoring.

Protein quantification plays a critical role in biopharmaceuticals and in vitro diagnostics. Traditional primary or authoritative methods for protein quantitation, such as the mass balance method or quantitative nuclear magnetic resonance method, are only applicable to solid samples or small peptides. For protein quantitation in solution, isotope dilution mass spectrometry (IDMS) remains the sole primary method, which lacks orthogonal method validation and may introduce bias. To address these limitations, our research group has developed three novel potential primary methods for protein quantification based on spectral techniques: high-performance liquid chromatography - circular dichroism (HPLC-CD), high-performance liquid chromatography - optical rotation dispersion (HPLC-ORD), and gas chromatography - isotope dilution infrared spectroscopy (GC-IDIR). Both HPLC-CD and HPLC-ORD use D-amino acids as standards to quantify L-amino acids in protein hydrolysates. When the D- and L-amino acid concentrations are equal, the circular dichroism or optical rotation dispersion signals reach zero. Since chiral isomers exhibit identical physicochemical properties in a non-chiral environment, these techniques minimize systematic and random errors, similar to isotope-based internal standards. Notably, the uncertainty of these methods is only one-fourth that of IDMS. Additionally, HPLC-ORD demonstrates higher sensitivity than HPLC-CD for non-UV absorbing amino acids. GC-IDIR integrates isotope dilution technology with the exceptional separation capability of gas chromatography, along with the infrared frequency shifts generated by bond energy changes after isotope labeling. It enables the identification and quantification of labeled and unlabeled molecules with high precision. Unlike traditional IDMS, GC-IDIR requires labeling only a single 13C atom for accurate quantification. Furthermore, multiple infrared spectra can be extracted from a single chromatographic peak, with each spectrum independently providing a quantification result, thus improving the reliability of the method. The newly proposed methods have been applied in the purity analysis and the development of reference materials for proteins and peptides, including porcine insulin, human insulin, and [Glu1]-human fibrinogen peptide B. The results are consistent with those obtained using traditional IDMS, offering lower or comparable uncertainty while ensuring the accuracy and traceability of protein quantification. In the future, our group aims to validate the effectiveness of these new methods by participating in international comparisons of protein purity measurements. We also plan to integrate these methods with traditional approaches to further develop protein reference materials, ensuring accurate value assignment.

Lipid regulation and remodeling are pivotal in follicle development and oocyte maturation. Performing lipidome analysis on single oocytes is essential for optimizing assisted reproductive techniques and improving pregnancy outcomes. Conventional organic solvent extraction faces challenges in single-cell analysis, including excessive sample dilution and time-consuming processing. In this study, we developed an on-valve microflow supercritical fluid extraction and chromatography-mass spectrometry (μSFE-SFC-MS) method. Lipids in intact single oocytes are extracted online by supercritical carbon dioxide fluid, separated by a C18 capillary column, ionized, and annotated. Notably, this method significantly reduces sample pretreatment and chromatographic separation time to just 15 min per sample, compared to about 2 h of the conventional method. We analyzed of 276 lipid species from a single oocyte. Lipidomic differences in oocyte maturation stages clarify distinct metabolic remodeling of phospholipids into sphingomyelins and glycerides. The differential analysis suggests that several lipid species can be used as criteria for determining oocyte maturation at the single-cell level. The present work offers a fast and high-coverage lipidomic analysis for single oocytes, also providing a workflow for other single-cell and trace samples.

Biological control of plant diseases is important for crop production. Botrytis cinerea and Fusarium graminearum are two common pathogenic fungi which result in great harm to crop production, processing, and storage of foodstuffs. Yeasts have unique advantages to be the focus of biological control of plant diseases through multiple mechanisms, including producing volatile organic compounds (VOCs) with inhibitory effect. However, the discontinuous display of inhibitory effect by yeast VOCs on pathogenic fungi is restricted by the conventional confrontation method, and the inhibitory mechanisms are unclear. We developed a new method to detect the inhibitory effect of Saccharomyces cerevisiae (yeast) VOCs on B. cinerea and F. graminearum. Our results showed that the yeast VOCs inhibited the growth and development of B. cinerea and F. graminearum and the strength of the inhibitory effect is positively related to the yeast inoculation amount. We confirmed the inhibition effect of ethyl acetic, one of the main yeast VOCs, on both pathogenic fungi. We further found that the deletion or overexpression of the ethyl acetic synthesis-related genes (ATF1 and/or ATF2) did not change the inhibitory effect much. The overexpression of ATF1 changed the main composition of VOCs. One of the changed VOCs, phenethyl acetic, even had stronger inhibitory effect than ethyl acetic on F. graminearum when they were added alone. These results suggest that the inhibitory effect of yeast VOCs on pathogenic fungi is a complex module. The lonely added individual component of VOCs may inhibit the growth and development of pathogenic fungi, while the partial alternation of VOC composition through gene modification may not be enough to change the total inhibitory effect.

Single-cell metabolic analysis has not yet achieved the coverage of bulk analysis due to the diversity of cellular metabolites and the ionization competition among species. Direct ionization methods without separation lead to the masking of low-intensity species. By designing a capillary column emitter and introducing reverse-phase chromatography principles, we achieved the microseparation of lipophilic and hydrophilic metabolites and lowered the limit of detection of hydrophilic metabolites to the level of a single oocyte. We identified 517 metabolite species in a single oocyte, achieving coverage and reproducibility comparable to those of bulk analysis. By comparing oocytes at different maturation stages, 76 metabolic features were identified with significant differences between the germinal vesicle and meiosis II stages. Metabolite level changes suggested the roles of lipid metabolism remodeling, increased amino acid synthesis, and a shift from pyrimidine metabolism to purine metabolism in the process of oocyte maturation. This microseparation mass spectrometry analysis is expected to promote single-cell metabolomics.

Accurate quantification of glycated hemoglobin A1c (HbA1c) is essential for the diagnosis and glycemic control in diabetic patients. The validation of HbA1c certified reference material (CRM) enhances the accuracy and comparability of HbA1c measurements. An international co-validation of HbA1c CRMs was conducted among the National Institute of Metrology, P.R. China (NIM), the Korea Research Institute of Standards and Science (KRISS), and the National Metrology Institute of Japan (NMIJ). Candidate reference materials (RMs) of VHLTPE, glycated VHLTPE, and two levels of HbA1c were developed and supplied by NIM. NIM investigated the homogeneity and stability of these materials, finding no inhomogeneity and confirming stability throughout the co-validation period. Isotope dilution mass spectrometry was employed for the quantitation of both hexapeptides in solution and HbA1c in a matrix. All three national metrology institutes (NMIs) were involved in the quantification of hexapeptides in solution, whereas only NIM and KRISS were involved in the quantification of HbA1c in the matrix. En values for both hexapeptides and HbA1c in the matrix were calculated, all being less than 1, indicating good agreement with the certified values. The successful co-validation of these CRMs demonstrates the reliability of the certified values, thereby benefiting the accuracy and comparability of HbA1c measurements.

Nucleic acid tests are essential for the accurate diagnosis and control of infectious diseases. However, current assays are not easily scalable for a large population, due to the requirement of laboratory settings or special equipment. Here, we developed an integrated box for instant nucleic acid screening which fully integrates nucleic acid release, amplification, and results visualization for self-service standalone test. Importantly, the operation of the box runs on a novel gamepad-like interface, which allows deployment of the box in home settings and operation by users without any prior professional training. The performance of the box is empowered by an RNA extraction-free sample inactivation process and nested recombinase polymerase amplification chemistry and exhibits sensitivity comparable to reverse transcription-quantitative polymerase chain reaction with high specificity for severe acute respiratory syndrome coronavirus 2 RNA in a reaction time of 30 minutes directly from fresh swab sample to results. These innovations make the box a novel platform for a convenient, accurate, and deployable point-of-care testing scheme.

Rapid and accurate detection of rare circulating tumor cells (CTCs) in human blood still remains a challenge. We present a surface enhanced Raman spectroscopy (SERS) method based on aptamer-SERS bio-probe recognition coupled with micropore membrane filtration capture for the detection of CTCs at single cell level. The parylene micropore membrane with optimized micropore size installed on a filtration holder could capture bio-probe labeled CTCs by gravity in less than 10 s, and only with very less white blood cells (WBCs) residual. In order to facilitate the synthesis of the aptamer-SERS bio-probe, ethyl acetate dehydration method was established. The bio-probe can be rapidly synthesized within 2 h by binding SH-aptamer to 4- mercaptobenzoic acid (4-MBA) modified AuNPs with the help of ethyl acetate. The SERS bio-probe with selected specific aptamer could distinguish single human non-small cell lung cancer A549 cells from residual WBCs on membrane efficiently and reliably based on their Raman signal intensity difference at 1075 cm- 1. Through the filter membrane coupled with aptamer-SERS bio-probe system, even 20 A549 cells in blood solution simulating CTCs sample can be detected, which the recovery rate and recognition rate are more than 90%. This method is rapid, reliable and cost-effective, which indicates a good prospect in clinical application for CTCs detection.

In the 21st century, with the rapid development of biotechnology and bio-industry, coupled with growing challenges to human survival and health, the need for accurate and reliable biological data has become increasingly pronounced. It has not only given rise to the new discipline of biometrology but has also drawn global attention to its standards and biological reference materials (BRMs). Under the new circumstances, the volume of data from bioanalysis and measurement is increasing at an exponential rate. Biometrology plays a particularly crucial role in guaranteeing the validity of biological data. With over 20 years of development, the biometrology systems have been established and continuously enhanced through research efforts in China. Research and application efforts in nucleic acid and protein measurement technology and standard, along with the development of standard systems, have been initiated for the aim to establish and maintain the biomeasurement standard. These technologies have been used in many fields, including the detection nucleic acids and proteins in transgenic products, in vitro diagnostic, virus detection, and quarantine measures, facilitating the acquisition of accurate values and enabling traceability. Biometrology and standard research is also facing with challenges for these demands.

d-Phenylalanine (d-Phe) is a small chiral organic molecule that is both an important pharmaceutical intermediate and used as a calibrator for quantifying amino acids in liquid chromatography-circular dichroism. We have developed a process for a national certified reference material (CRM) for d-Phe following ISO 17034:2016. The identity of d-Phe was confirmed using mass spectrometry (MS) and nuclear magnetic resonance (NMR), infrared, and ultraviolet (UV) spectroscopy. The absolute optical conformation was also determined using circular dichroism (CD) spectroscopy and optical rotation measurements. Impurities were identified via liquid chromatography (LC) with a UV–Vis detector and a charged aerosol detector (CAD) and LC–MS. Both mass balance and quantitative NMR were employed for value assessment, and the associated uncertainty was evaluated. The certified purity was determined to be 0.995 ± 0.003 g/g, a validation that was confirmed by CD using l-Phe CRM as a calibrator. Twenty milligrams of raw material was packed in sealed brown glass tubes for storage, and no inhomogeneity was observed. Stability tests revealed that the d-Phe CRM remained stable at −20 °C for at least 26 months, at 4 °C for at least 14 days, and at 25 °C and 60 °C for at least 7 days. The d-Phe CRM can be used to ensure the accuracy and reliability of d-Phe quantitation in the pharmaceutical field and also as a calibrator to ensure traceability to the International System of Units (SI) for l-Phe quantitation and protein purity analysis using LC-CD methods. The approach outlined in this paper also has potential for use in the development of other chiral CRMs.

As the state-of-the-art sequencing technologies and computational methods enable investigation of challenging regions in the human genome, an update variant benchmark is demanded. Herein, we sequenced a Chinese Quartet, consisting of two monozygotic twin daughters and their biological parents, with multiple advanced sequencing platforms, including Illumina, BGI, PacBio, and Oxford Nanopore Technology. We phased the long reads of the monozygotic twin daughters into paternal and maternal haplotypes using the parent-child genetic map. For each haplotype, we utilized advanced long reads to generate haplotype-resolved assemblies (HRAs) with high accuracy, completeness, and continuity. Based on the ingenious quartet samples, novel computational methods, high-quality sequencing reads, and HRAs, we established a comprehensive variant benchmark, including 3,883,283 SNVs, 859,256 Indels, 9,678 large deletions, 15,324 large insertions, 40 inversions, and 31 complex structural variants shared between the monozygotic twin daughters. In particular, the preciously excluded regions, such as repeat regions and the human leukocyte antigen (HLA) region, were systematically examined. Finally, we illustrated how the sequencing depth correlated with the de novo assembly and variant detection, from which we learned that 30 × HiFi is a balance between performance and cost. In summary, this study provides high-quality haplotype-resolved assemblies and a variant benchmark for two Chinese monozygotic twin samples. The benchmark expanded the regions of the previous report and adapted to the evolving sequencing technologies and computational methods.

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

Certified RNA reference materials are indispensable for assessing the reliability of RNA sequencing to detect intrinsically small biological differences in clinical settings, such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multi-omics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two samples, providing cross-platform and cross-laboratory ‘ground truth’. Investigation of the intrinsically subtle biological differences among the Quartet samples enables sensitive assessment of cross-batch integration of transcriptomic measurements at the ratio level. The Quartet RNA reference materials, combined with the ratio-based reference datasets, can serve as unique resources for assessing and improving the quality of transcriptomic data in clinical and biological settings.

Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.

BACKGROUND:Genomic DNA reference materials are widely recognized as essential for ensuring data quality in omics research. However, relying solely on reference datasets to evaluate the accuracy of variant calling results is incomplete, as they are limited to benchmark regions. Therefore, it is important to develop DNA reference materials that enable the assessment of variant detection performance across the entire genome. RESULTS:We established a DNA reference material suite from four immortalized cell lines derived from a family of parents and monozygotic twins. Comprehensive reference datasets of 4.2 million small variants and 15,000 structural variants were integrated and certified for evaluating the reliability of germline variant calls inside the benchmark regions. Importantly, the genetic built-in-truth of the Quartet family design enables estimation of the precision of variant calls outside the benchmark regions. Using the Quartet reference materials along with study samples, batch effects are objectively monitored and alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Moreover, the matched RNA and protein reference materials and datasets from the Quartet project enables cross-omics validation of variant calls from multiomics data. CONCLUSIONS:The Quartet DNA reference materials and reference datasets provide a unique resource for objectively assessing the quality of germline variant calls throughout the whole-genome regions and improving the reliability of large-scale genomic profiling.