Pub Date : 2025-04-03DOI: 10.1021/acs.analchem.4c05315
Yao-Yu Chen, Na An, Yan-Zhen Wang, Peng-Cheng Mei, Jun-Di Hao, Song-Mei Liu, Quan-Fei Zhu, Yu-Qi Feng
Metabolomics, which involves the comprehensive analysis of small molecules within biological systems, plays a crucial role in elucidating the biochemical underpinnings of physiological processes and disease conditions. However, current coverage of the metabolome remains limited. In this study, we present a heuristic strategy for untargeted metabolomics analysis (HeuSMA) based on multiple chromatographic gradients to enhance the metabolome coverage in untargeted metabolomics. This strategy involves performing LC-MS analysis under multiple gradient conditions on a given sample (e.g., a pooled sample or a quality control sample) to obtain a comprehensive metabolomics data set, followed by constructing a heuristic peak list using a retention index system. Guided by this list, heuristic peak picking in quantitative metabolomics data is achieved. The benchmarking and validation results demonstrate that HeuSMA outperforms existing tools (such as MS-DIAL and MZmine) in terms of metabolite coverage and peak identification accuracy. Additionally, HeuSMA improves the accessibility of MS/MS data, thereby facilitating the metabolite annotation. The effectiveness of the HeuSMA strategy was further demonstrated through its application in serum metabolomics analysis of human hepatocellular carcinoma (HCC). To facilitate the adoption of the HeuSMA strategy, we also developed two user-friendly graphical interface software solutions (HPLG and HP), which automate the analysis process, enabling researchers to efficiently manage data and derive meaningful conclusions (https://github.com/Lacterd/HeuSMA).
{"title":"HeuSMA: A Multigradient LC-MS Strategy for Improving Peak Identification in Untargeted Metabolomics","authors":"Yao-Yu Chen, Na An, Yan-Zhen Wang, Peng-Cheng Mei, Jun-Di Hao, Song-Mei Liu, Quan-Fei Zhu, Yu-Qi Feng","doi":"10.1021/acs.analchem.4c05315","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c05315","url":null,"abstract":"Metabolomics, which involves the comprehensive analysis of small molecules within biological systems, plays a crucial role in elucidating the biochemical underpinnings of physiological processes and disease conditions. However, current coverage of the metabolome remains limited. In this study, we present a heuristic strategy for untargeted metabolomics analysis (HeuSMA) based on multiple chromatographic gradients to enhance the metabolome coverage in untargeted metabolomics. This strategy involves performing LC-MS analysis under multiple gradient conditions on a given sample (e.g., a pooled sample or a quality control sample) to obtain a comprehensive metabolomics data set, followed by constructing a heuristic peak list using a retention index system. Guided by this list, heuristic peak picking in quantitative metabolomics data is achieved. The benchmarking and validation results demonstrate that HeuSMA outperforms existing tools (such as MS-DIAL and MZmine) in terms of metabolite coverage and peak identification accuracy. Additionally, HeuSMA improves the accessibility of MS/MS data, thereby facilitating the metabolite annotation. The effectiveness of the HeuSMA strategy was further demonstrated through its application in serum metabolomics analysis of human hepatocellular carcinoma (HCC). To facilitate the adoption of the HeuSMA strategy, we also developed two user-friendly graphical interface software solutions (HPLG and HP), which automate the analysis process, enabling researchers to efficiently manage data and derive meaningful conclusions (https://github.com/Lacterd/HeuSMA).","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"11 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Efficient ionization is essential for sensitive mass spectrometry (MS) analysis. Herein, a novel laser-assisted electrospray ionization (laser-assisted ESI) source was developed to efficiently ionize low-polar and thermal unstable compounds. By irradiating the electrospray nozzle with a simple and low-cost laser probe (450 nm, 500 mW), the sample droplets were stimulated with a laser beam as well as the high voltage of the electrospray, which significantly enhanced the ionization efficiency. In positive ionization mode, by further utilizing the reaction of Ag+ and tetrabromobisphenol A bis(allyl ether) (TBBPA-BAE), the established laser-assisted ESI strategy was able to efficiently ionize the low-polar and thermal unstable TBBPA-BAE. Specifically, a limit of detection (LOD) of 14 ng L–1, linear range of 0.1–10 μg L–1 (R2 > 0.99), and relative standard deviations (RSDs) of 2.5% (n = 7, intraday) and 6.2% (n = 3 per day for 5 days, interday) were achieved. In negative ionization mode, laser-assisted ESI also improved the detection sensitivity of tetrabromobisphenol A (TBBPA), achieving a LOD of 3.3 ng L–1, linear range of 0.01–10 μg L–1 (R2 > 0.99), and RSDs of 4.7% (n = 7, intraday) and 7.3% (n = 3 per day for 5 days, interday). Compared to extractive electrospray ionization mass spectrometry (EESI-MS) and ESI-MS, the LODs achieved with laser-assisted ESI-MS were 54 and 16 times lower for the detection of TBBPA-BAE and TBBPA, respectively. Notably, deep purification and preconcentration were not required to accurately detect TBBPA and TBBPA-BAE in river water and wastewater treatment plant effluent. The spiked recoveries were between 88.0% and 106.0%, demonstrating the high reliability and practicality of this method.
{"title":"Novel Laser-Assisted Electrospray Ionization Mass Spectrometry (Laser-Assisted ESI-MS): A Sensitive Method for Determining Tetrabromobisphenol A and Its Derivative","authors":"Haonan Liu, Xiaoxuan Han, Shuo Gao, Fada Shi, Yong Tian, Ligang Hu, Jianbo Shi, Guibin Jiang","doi":"10.1021/acs.analchem.5c00166","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c00166","url":null,"abstract":"Efficient ionization is essential for sensitive mass spectrometry (MS) analysis. Herein, a novel laser-assisted electrospray ionization (laser-assisted ESI) source was developed to efficiently ionize low-polar and thermal unstable compounds. By irradiating the electrospray nozzle with a simple and low-cost laser probe (450 nm, 500 mW), the sample droplets were stimulated with a laser beam as well as the high voltage of the electrospray, which significantly enhanced the ionization efficiency. In positive ionization mode, by further utilizing the reaction of Ag<sup>+</sup> and tetrabromobisphenol A bis(allyl ether) (TBBPA-BAE), the established laser-assisted ESI strategy was able to efficiently ionize the low-polar and thermal unstable TBBPA-BAE. Specifically, a limit of detection (LOD) of 14 ng L<sup>–1</sup>, linear range of 0.1–10 μg L<sup>–1</sup> (R<sup>2</sup> > 0.99), and relative standard deviations (RSDs) of 2.5% (n = 7, intraday) and 6.2% (n = 3 per day for 5 days, interday) were achieved. In negative ionization mode, laser-assisted ESI also improved the detection sensitivity of tetrabromobisphenol A (TBBPA), achieving a LOD of 3.3 ng L<sup>–1</sup>, linear range of 0.01–10 μg L<sup>–1</sup> (R<sup>2</sup> > 0.99), and RSDs of 4.7% (n = 7, intraday) and 7.3% (n = 3 per day for 5 days, interday). Compared to extractive electrospray ionization mass spectrometry (EESI-MS) and ESI-MS, the LODs achieved with laser-assisted ESI-MS were 54 and 16 times lower for the detection of TBBPA-BAE and TBBPA, respectively. Notably, deep purification and preconcentration were not required to accurately detect TBBPA and TBBPA-BAE in river water and wastewater treatment plant effluent. The spiked recoveries were between 88.0% and 106.0%, demonstrating the high reliability and practicality of this method.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"58 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-03DOI: 10.1021/acs.analchem.4c07055
Chengjie Huang, Tianbao Ye, Xiuyuan Wang, Ke Li, Yiyang Li, Lai Jiang, Xianting Ding
Mass cytometry (CyTOF) and imaging mass cytometry (IMC), as cutting-edge technologies in single-cell analysis, are capable of detecting more than 40 biomarkers simultaneously on a single cell. However, their sensitivity and multiparameter detection capabilities have been long constrained by the development of metal labeling materials. Meanwhile, as an imaging technique, IMC has suffered from a rather slow data acquisition rate. Here, we present a luminescent PCN-224-OH material that exhibits both fluorescent and mass dual-functionality and is enriched with Zr–OH–/H2O active sites. Without the additional need for complex postmodification or chemical coupling reactions, PCN-224-OH can be directly functionalized with antibodies/aptamers and poly(ethylene glycol) (PEG), resulting in the production of PCN-224-Ab-PEG or PCN-224-Apt-PEG probes. We demonstrated that PCN-224-Ab-PEG was compatible with commercial polymer-based probes but with superior sensitivity and specificity. Meanwhile, since PCN-224-Apt-PEG expressed both fluorescence and mass signals, we could adopt fluorescence signals for rapid tissue section scanning to swiftly identify the regions of interest (ROIs), and then adopt IMC for multiparameter imaging at the specific ROIs. The application of the PCN-224-Apt-PEG probe could significantly reduce the blind IMC scanning time by up to 90% and effectively compensate for IMC’s low resolution. This study not only broadens the application scope of luminescent metal–organic frameworks but also offers a potentially novel toolbox for single-cell multiparameter detection.
{"title":"Luminescent Metal–Organic Framework Probes with Metallic and Fluorescent Dual-Properties for Mass Cytometry and Imaging","authors":"Chengjie Huang, Tianbao Ye, Xiuyuan Wang, Ke Li, Yiyang Li, Lai Jiang, Xianting Ding","doi":"10.1021/acs.analchem.4c07055","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c07055","url":null,"abstract":"Mass cytometry (CyTOF) and imaging mass cytometry (IMC), as cutting-edge technologies in single-cell analysis, are capable of detecting more than 40 biomarkers simultaneously on a single cell. However, their sensitivity and multiparameter detection capabilities have been long constrained by the development of metal labeling materials. Meanwhile, as an imaging technique, IMC has suffered from a rather slow data acquisition rate. Here, we present a luminescent PCN-224-OH material that exhibits both fluorescent and mass dual-functionality and is enriched with Zr–OH<sup>–</sup>/H<sub>2</sub>O active sites. Without the additional need for complex postmodification or chemical coupling reactions, PCN-224-OH can be directly functionalized with antibodies/aptamers and poly(ethylene glycol) (PEG), resulting in the production of PCN-224-Ab-PEG or PCN-224-Apt-PEG probes. We demonstrated that PCN-224-Ab-PEG was compatible with commercial polymer-based probes but with superior sensitivity and specificity. Meanwhile, since PCN-224-Apt-PEG expressed both fluorescence and mass signals, we could adopt fluorescence signals for rapid tissue section scanning to swiftly identify the regions of interest (ROIs), and then adopt IMC for multiparameter imaging at the specific ROIs. The application of the PCN-224-Apt-PEG probe could significantly reduce the blind IMC scanning time by up to 90% and effectively compensate for IMC’s low resolution. This study not only broadens the application scope of luminescent metal–organic frameworks but also offers a potentially novel toolbox for single-cell multiparameter detection.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"216 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RNA splicing is a key regulatory process of gene expression that can increase the transcriptome complexity. Simultaneous monitoring of multiple splicing variants in living cells is critical for gaining new insight into cell development. Herein, we demonstrate the development of proximity-activated, programmable multicomponent nucleic acid enzymes (MNAzymes) for the simultaneous visualization of multiple RNA splicing variants (i.e., BRCA1 WT and BRCA1 Δ11q) in living cells. The presence of BRCA1 WT and BRCA1 Δ11q can specifically bring their corresponding partzymes into the proximity of each other to form two active MNAzyme motifs. Subsequently, the active sites of reporter probes 1 and 2 are cyclically cleaved by two activated MNAzyme motifs, respectively, to release abundant Cy3 and Cy5 fluorescent molecules, generating enhanced fluorescence signals for the simultaneous detection of BRCA1 WT and BRCA1 Δ11q in vitro and in vivo. Notably, this assay can be simply and isothermally conducted in a one-step format without the necessity for unstable protein enzymes, precise temperature control, and complex operation procedures. This method can sensitively detect 2.46 fM BRCA1 WT and 2.77 fM BRCA1 Δ11q and accurately distinguish breast cancer patients from healthy individuals by measuring target BRCA1 splicing variants from the tissue samples. Moreover, this method can real-time image BRCA1 splicing variants in living cells and can be extended to detect other cellular target RNAs (e.g., miRNAs, piRNAs, lncRNAs, and circRNAs) by simply changing the sequences of substrate arms, holding promising applications in clinical diagnosis and precise therapy.
{"title":"Development of Proximity-Activated Programmable Multicomponent Nucleic Acid Enzymes for Simultaneous Visualization of Multiple mRNA Splicing Variants in Living Cells","authors":"Wen-jing Liu, Yun Han, Rui Song, Fei Ma, Chun-yang Zhang","doi":"10.1021/acs.analchem.5c01001","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c01001","url":null,"abstract":"RNA splicing is a key regulatory process of gene expression that can increase the transcriptome complexity. Simultaneous monitoring of multiple splicing variants in living cells is critical for gaining new insight into cell development. Herein, we demonstrate the development of proximity-activated, programmable multicomponent nucleic acid enzymes (MNAzymes) for the simultaneous visualization of multiple RNA splicing variants (i.e., BRCA1 WT and BRCA1 Δ11q) in living cells. The presence of BRCA1 WT and BRCA1 Δ11q can specifically bring their corresponding partzymes into the proximity of each other to form two active MNAzyme motifs. Subsequently, the active sites of reporter probes 1 and 2 are cyclically cleaved by two activated MNAzyme motifs, respectively, to release abundant Cy3 and Cy5 fluorescent molecules, generating enhanced fluorescence signals for the simultaneous detection of BRCA1 WT and BRCA1 Δ11q <i>in vitro</i> and <i>in vivo</i>. Notably, this assay can be simply and isothermally conducted in a one-step format without the necessity for unstable protein enzymes, precise temperature control, and complex operation procedures. This method can sensitively detect 2.46 fM BRCA1 WT and 2.77 fM BRCA1 Δ11q and accurately distinguish breast cancer patients from healthy individuals by measuring target BRCA1 splicing variants from the tissue samples. Moreover, this method can real-time image BRCA1 splicing variants in living cells and can be extended to detect other cellular target RNAs (e.g., miRNAs, piRNAs, lncRNAs, and circRNAs) by simply changing the sequences of substrate arms, holding promising applications in clinical diagnosis and precise therapy.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"61 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143775747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-03DOI: 10.1021/acs.analchem.4c05549
Ruihao Luo, Shuxia Guo, Julian Hniopek, Thomas Bocklitz
Nowadays, with the rise of artificial intelligence (AI), deep learning algorithms play an increasingly important role in various traditional fields of research. Recently, these algorithms have already spread into data analysis for Raman spectroscopy. However, most current methods only use 1-dimensional (1D) spectral data classification, instead of considering any neighboring information in space. Despite some successes, this type of methods wastes the 3-dimensional (3D) structure of Raman hyperspectral scans. Therefore, to investigate the feasibility of preserving the spatial information on Raman spectroscopy for data analysis, spatially aware deep learning algorithms were applied into a colorectal tissue data set with 3D Raman hyperspectral scans. This data set contains Raman spectra from normal, hyperplasia, adenoma, carcinoma tissues as well as artifacts. First, a modified version of 3D U-Net was utilized for segmentation; second, another convolutional neural network (CNN) using 3D Raman patches was utilized for pixel-wise classification. Both methods were compared with the conventional 1D CNN method, which worked as baseline. Based on the results of both epithelial tissue detection and colorectal cancer detection, it is shown that using spatially neighboring information on 3D Raman scans can increase the performance of deep learning models, although it might also increase the complexity of network training. Apart from the colorectal tissue data set, experiments were also conducted on a cholangiocarcinoma data set for generalizability verification. The findings in this study can also be potentially applied into future tasks regarding spectroscopic data analysis, especially for improving model performance in a spatially aware way.
{"title":"3D Hyperspectral Data Analysis with Spatially Aware Deep Learning for Diagnostic Applications","authors":"Ruihao Luo, Shuxia Guo, Julian Hniopek, Thomas Bocklitz","doi":"10.1021/acs.analchem.4c05549","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c05549","url":null,"abstract":"Nowadays, with the rise of artificial intelligence (AI), deep learning algorithms play an increasingly important role in various traditional fields of research. Recently, these algorithms have already spread into data analysis for Raman spectroscopy. However, most current methods only use 1-dimensional (1D) spectral data classification, instead of considering any neighboring information in space. Despite some successes, this type of methods wastes the 3-dimensional (3D) structure of Raman hyperspectral scans. Therefore, to investigate the feasibility of preserving the spatial information on Raman spectroscopy for data analysis, spatially aware deep learning algorithms were applied into a colorectal tissue data set with 3D Raman hyperspectral scans. This data set contains Raman spectra from normal, hyperplasia, adenoma, carcinoma tissues as well as artifacts. First, a modified version of 3D U-Net was utilized for segmentation; second, another convolutional neural network (CNN) using 3D Raman patches was utilized for pixel-wise classification. Both methods were compared with the conventional 1D CNN method, which worked as baseline. Based on the results of both epithelial tissue detection and colorectal cancer detection, it is shown that using spatially neighboring information on 3D Raman scans can increase the performance of deep learning models, although it might also increase the complexity of network training. Apart from the colorectal tissue data set, experiments were also conducted on a cholangiocarcinoma data set for generalizability verification. The findings in this study can also be potentially applied into future tasks regarding spectroscopic data analysis, especially for improving model performance in a spatially aware way.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"37 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143775744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-03DOI: 10.1021/acs.analchem.4c07123
Haoni Yan, Yan Zhang, Yujie Shi, Jiahui Ding, Hengxing Su, Wenqiong Su, Yan Wang, Yanfei Mao, Tawfik A. Khattab, Salhah D. Al-Qahtani, Aynur Abdulla, Lai Jiang, Xianting Ding
Sepsis, a lethal organ dysfunction caused by a dysregulated host response to infection, is the leading cause of worldwide in-hospital mortality. However, the early diagnostic methods for sepsis are still urgent for guiding accurate antibiotic usage and improving the survival rate of the patients. Herein, we constructed a PD-L1 antibody affinity microfluidic (PAAM) chip for early sepsis diagnosis and severity assessment. The chip was used to capture PD-L1-expressing leukocytes from whole blood samples obtained from healthy control (HC) volunteers (n = 15) and sepsis patients on day 1 (D1) and day 7 (D7) (n = 20), and there was a statistically significant difference between HC and sepsis patients (p < 0.0001), and the AUC was 0.96. However, there was no significant difference in the number of cells captured on-chip between sepsis patients on D1 and D7 (p = 0.16). Therefore, we performed immunofluorescence staining of PD-L1, CD64, and CD123 on the chip. The results showed that the combination of PD-L1, CD64, and CD123 for sepsis diagnosis had an AUC of 0.98, and there was a significant difference in PD-L1+/CD64+/CD123+ leukocytes between sepsis patients on D1 and on D7 (p < 0.0001). In conclusion, we found that the combination of multiple biomarkers was more precise and dependable for sepsis diagnosis and severity assessment.
{"title":"Combining CD64 and CD123 Biomarkers for Sepsis Early Diagnosis and Severity Assessment via PD-L1 Antibody Affinity Microfluidic (PAAM) Chip in Trace Clinical Samples","authors":"Haoni Yan, Yan Zhang, Yujie Shi, Jiahui Ding, Hengxing Su, Wenqiong Su, Yan Wang, Yanfei Mao, Tawfik A. Khattab, Salhah D. Al-Qahtani, Aynur Abdulla, Lai Jiang, Xianting Ding","doi":"10.1021/acs.analchem.4c07123","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c07123","url":null,"abstract":"Sepsis, a lethal organ dysfunction caused by a dysregulated host response to infection, is the leading cause of worldwide in-hospital mortality. However, the early diagnostic methods for sepsis are still urgent for guiding accurate antibiotic usage and improving the survival rate of the patients. Herein, we constructed a PD-L1 antibody affinity microfluidic (PAAM) chip for early sepsis diagnosis and severity assessment. The chip was used to capture PD-L1-expressing leukocytes from whole blood samples obtained from healthy control (HC) volunteers (<i>n</i> = 15) and sepsis patients on day 1 (D1) and day 7 (D7) (<i>n</i> = 20), and there was a statistically significant difference between HC and sepsis patients (<i>p</i> < 0.0001), and the AUC was 0.96. However, there was no significant difference in the number of cells captured on-chip between sepsis patients on D1 and D7 (<i>p</i> = 0.16). Therefore, we performed immunofluorescence staining of PD-L1, CD64, and CD123 on the chip. The results showed that the combination of PD-L1, CD64, and CD123 for sepsis diagnosis had an AUC of 0.98, and there was a significant difference in PD-L1<sup>+</sup>/CD64<sup>+</sup>/CD123<sup>+</sup> leukocytes between sepsis patients on D1 and on D7 (<i>p</i> < 0.0001). In conclusion, we found that the combination of multiple biomarkers was more precise and dependable for sepsis diagnosis and severity assessment.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"34 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Compound 6:2 chlorinated polyfluoroalkyl ether sulfonate (6:2 Cl-PFESA) is an emerging per- and polyfluoroalkyl substance (PFAS) with potential toxicity and health risks to biosystems and ecosystems. Here, we developed a metabolomics method based on single-cell mass spectrometry to investigate the hepatotoxicity and heterogeneous responses in zebrafish exposed to 6:2 Cl-PFESA. Zebrafish were exposed to an environmentally relevant concentration (200 ng/L) of 6:2 Cl-PFESA for 14 days. The livers were dissociated and prepared as cell suspensions and then introduced to high-throughput single-cell mass spectrometry for analysis of 6:2 Cl-PFESA and endogenous metabolites in individual primary liver cells. Significant sex-specific heterogeneity in 6:2 Cl-PFESA accumulation was observed (p < 0.05). Metabolomics analysis revealed perturbations in lipid metabolism, particularly affecting unsaturated fatty acids, ether lipids, and sphingolipids in zebrafish liver cells, indicating potential hepatotoxicity. Sex-dependent metabolic responses were evident: males showed notable changes in glucose and fatty acid metabolism, whereas females experienced pronounced disruptions in glycerophospholipid and amino acid pathways. ROC analysis identified sex-specific biomarkers, including FA(18:3) and FA(16:1) in males (AUC > 0.85), as well as proline and phosphatidylcholine in females (AUC > 0.90). These findings reflect metabolic dysregulation and highlight sex-specific responses. This study demonstrates the feasibility of single-cell metabolomics to elucidate the cellular mechanisms and metabolic responses of pollutant exposure, offering insights into precise and comprehensive toxicity assessments at the single-cell level.
{"title":"High-Throughput Single-Cell Mass Spectrometry Reveals Sex-Specific Metabolic Responses to 6:2 Chlorinated Polyfluoroalkyl Ether Sulfonate in Zebrafish Liver Cells","authors":"Chunfei Zhong, Haishen Zeng, Jiewei Deng, Quchang Li, Ziqing Li, Junqiu Zhai, Xinyan Li, Tiangang Luan","doi":"10.1021/acs.analchem.4c06345","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c06345","url":null,"abstract":"Compound 6:2 chlorinated polyfluoroalkyl ether sulfonate (6:2 Cl-PFESA) is an emerging per- and polyfluoroalkyl substance (PFAS) with potential toxicity and health risks to biosystems and ecosystems. Here, we developed a metabolomics method based on single-cell mass spectrometry to investigate the hepatotoxicity and heterogeneous responses in zebrafish exposed to 6:2 Cl-PFESA. Zebrafish were exposed to an environmentally relevant concentration (200 ng/L) of 6:2 Cl-PFESA for 14 days. The livers were dissociated and prepared as cell suspensions and then introduced to high-throughput single-cell mass spectrometry for analysis of 6:2 Cl-PFESA and endogenous metabolites in individual primary liver cells. Significant sex-specific heterogeneity in 6:2 Cl-PFESA accumulation was observed (<i>p</i> < 0.05). Metabolomics analysis revealed perturbations in lipid metabolism, particularly affecting unsaturated fatty acids, ether lipids, and sphingolipids in zebrafish liver cells, indicating potential hepatotoxicity. Sex-dependent metabolic responses were evident: males showed notable changes in glucose and fatty acid metabolism, whereas females experienced pronounced disruptions in glycerophospholipid and amino acid pathways. ROC analysis identified sex-specific biomarkers, including FA(18:3) and FA(16:1) in males (AUC > 0.85), as well as proline and phosphatidylcholine in females (AUC > 0.90). These findings reflect metabolic dysregulation and highlight sex-specific responses. This study demonstrates the feasibility of single-cell metabolomics to elucidate the cellular mechanisms and metabolic responses of pollutant exposure, offering insights into precise and comprehensive toxicity assessments at the single-cell level.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"32 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-03DOI: 10.1021/acs.analchem.5c00118
Zhenhao Long, Jingjing Yu, Tao Bing
Rapid selection methods are crucial for promoting the discovery and application of aptamers across various fields. We previously reported a highly efficient aptamer selection strategy by using unique molecular identifiers (UMIs), enabling the efficient isolation of aptamers from a single cell by only one round. The strategy integrates an ultrasensitive DNA barcoding technology with high-throughput sequencing to accurately quantify aptamer candidates, thereby mitigating issues such as PCR bias and sequence overenrichment that are inherent in traditional multiround selection. Here, we conduct a systematically theoretical analysis of this strategy in the elucidation of the theoretical basis, advantages, and applicability. The feasibility and advantages of isolating aptamers from low-enriched DNA libraries was investigated at a theoretical level, showing that this strategy is effective in reducing nonspecific binding and thus increasing the success of selecting high-affinity aptamers. Our theoretical analysis supports the broad applicability of the strategy for the single-round aptamer selection, paving the way for its widespread adoption in high-efficiency aptamer discovery and aptamer-based cell atlas.
快速筛选方法对于促进各领域的适配体发现和应用至关重要。我们之前报道了一种利用独特分子标识符（UMI）的高效适配体筛选策略，只需一轮就能从单个细胞中高效分离出适配体。该策略将超灵敏 DNA 条形码技术与高通量测序技术相结合，准确量化了候选的适配体，从而缓解了传统多轮筛选中固有的 PCR 偏差和序列过度富集等问题。在此，我们对这一策略进行了系统的理论分析，以阐明其理论基础、优势和适用性。我们从理论层面研究了从低富集 DNA 文库中分离适配体的可行性和优势，结果表明这种策略能有效减少非特异性结合，从而提高选择高亲和性适配体的成功率。我们的理论分析支持该策略在单轮适配体筛选中的广泛适用性，为其在高效适配体发现和基于适配体的细胞图谱中的广泛应用铺平了道路。
{"title":"Theoretical Basis for the Highly Efficient Aptamer Selection Using Unique Molecular Identifiers","authors":"Zhenhao Long, Jingjing Yu, Tao Bing","doi":"10.1021/acs.analchem.5c00118","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c00118","url":null,"abstract":"Rapid selection methods are crucial for promoting the discovery and application of aptamers across various fields. We previously reported a highly efficient aptamer selection strategy by using unique molecular identifiers (UMIs), enabling the efficient isolation of aptamers from a single cell by only one round. The strategy integrates an ultrasensitive DNA barcoding technology with high-throughput sequencing to accurately quantify aptamer candidates, thereby mitigating issues such as PCR bias and sequence overenrichment that are inherent in traditional multiround selection. Here, we conduct a systematically theoretical analysis of this strategy in the elucidation of the theoretical basis, advantages, and applicability. The feasibility and advantages of isolating aptamers from low-enriched DNA libraries was investigated at a theoretical level, showing that this strategy is effective in reducing nonspecific binding and thus increasing the success of selecting high-affinity aptamers. Our theoretical analysis supports the broad applicability of the strategy for the single-round aptamer selection, paving the way for its widespread adoption in high-efficiency aptamer discovery and aptamer-based cell atlas.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"73 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143775748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-02DOI: 10.1021/acs.analchem.5c00373
Lingling Luo, Yuying Zhou, Yaqin Chai, Ruo Yuan, Hongyan Liu
The minor changes of miRNA levels due to various diseases and cancers bring great challenges for early diagnosis. Here we propose a “signal on-off-super on” PEC biosensor based on a homogeneous multicycle cascaded DNA circuit and a SnSe/CdS photoanode for sensitive detection of biomarker miRNA-222. Specifically, a Z-type SnSe/CdS heterojunction with greatly enhanced photoanodic performance was developed to provide the initial “on” signal. The target miRNA-222 was converted to a dendritic DNA structure through a cascade DNA circuit. The PEC signal can be switched off by the dendritic DNA structure and further switched super on by the loading of photosensitizer manganese porphyrin (MnPP). It is worth noting that the homogeneous multicycle cascaded DNA circuit not only improved the reaction kinetics but also avoided the leakage of signal. Compared with the traditional “signal-on” or “signal-off” readout, this “signal on-off-super on” strategy avoids the false response and background, thereby enhancing the sensitivity and accuracy of the PEC biosensor. The detection limit of the constructed PEC sensor is 0.3 fM in the linear range from 1 fM to 10 nM. The PEC biosensor with outstanding reproducibility, stability, and sensitivity provides a promising platform for biomarker detection and early disease diagnosis.
{"title":"Homogeneous Multicycle Cascaded DNA Circuit for Sensitive “Signal On-Off-Super On” PEC Biosensing","authors":"Lingling Luo, Yuying Zhou, Yaqin Chai, Ruo Yuan, Hongyan Liu","doi":"10.1021/acs.analchem.5c00373","DOIUrl":"https://doi.org/10.1021/acs.analchem.5c00373","url":null,"abstract":"The minor changes of miRNA levels due to various diseases and cancers bring great challenges for early diagnosis. Here we propose a “signal on-off-super on” PEC biosensor based on a homogeneous multicycle cascaded DNA circuit and a SnSe/CdS photoanode for sensitive detection of biomarker miRNA-222. Specifically, a Z-type SnSe/CdS heterojunction with greatly enhanced photoanodic performance was developed to provide the initial “on” signal. The target miRNA-222 was converted to a dendritic DNA structure through a cascade DNA circuit. The PEC signal can be switched off by the dendritic DNA structure and further switched super on by the loading of photosensitizer manganese porphyrin (MnPP). It is worth noting that the homogeneous multicycle cascaded DNA circuit not only improved the reaction kinetics but also avoided the leakage of signal. Compared with the traditional “signal-on” or “signal-off” readout, this “signal on-off-super on” strategy avoids the false response and background, thereby enhancing the sensitivity and accuracy of the PEC biosensor. The detection limit of the constructed PEC sensor is 0.3 fM in the linear range from 1 fM to 10 nM. The PEC biosensor with outstanding reproducibility, stability, and sensitivity provides a promising platform for biomarker detection and early disease diagnosis.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"128 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-02DOI: 10.1021/acs.analchem.4c06305
Connor D. Flynn, Zhenwei Wu, Amy Bantle, Scott E. Isaacson, Dingran Chang, Alam Mahmud, Hanie Yousefi, Jagotamoy Das, Shana O. Kelley
The development of biomolecular sensing technologies with high sensitivity and specificity remains an important goal in modern analytical science. Molecular pendulum sensing has emerged as a new reagentless method capable of detecting a wide array of biomolecules directly in biological fluids. This sensing approach relies heavily on the modulation of hydrodynamic drag of molecular probes through solution, such that alterations in hydrodynamic diameter can transduce biomolecular interactions. Here, we explore the use of nanobodies as an alternative receptor in pendulum-based systems due to their small size and robust affinities. We compare the performance of nanobodies with that of aptamers and antibodies integrated into the molecular pendulum system by targeting the inflammatory indicator interleukin-6 (IL-6). Nanobody molecular pendulums demonstrate enhanced sensor response and sensitivity compared to those of the other receptors, enabling fine control over detection in the low physiological range of IL-6. In addition, we demonstrate the ability of nanobody sensors to function in complex biological matrices and at physiological temperature.
{"title":"Nanobody Receptors Enable High-Sensitivity Monitoring of IL-6 Using Molecular Pendulum Bioanalysis","authors":"Connor D. Flynn, Zhenwei Wu, Amy Bantle, Scott E. Isaacson, Dingran Chang, Alam Mahmud, Hanie Yousefi, Jagotamoy Das, Shana O. Kelley","doi":"10.1021/acs.analchem.4c06305","DOIUrl":"https://doi.org/10.1021/acs.analchem.4c06305","url":null,"abstract":"The development of biomolecular sensing technologies with high sensitivity and specificity remains an important goal in modern analytical science. Molecular pendulum sensing has emerged as a new reagentless method capable of detecting a wide array of biomolecules directly in biological fluids. This sensing approach relies heavily on the modulation of hydrodynamic drag of molecular probes through solution, such that alterations in hydrodynamic diameter can transduce biomolecular interactions. Here, we explore the use of nanobodies as an alternative receptor in pendulum-based systems due to their small size and robust affinities. We compare the performance of nanobodies with that of aptamers and antibodies integrated into the molecular pendulum system by targeting the inflammatory indicator interleukin-6 (IL-6). Nanobody molecular pendulums demonstrate enhanced sensor response and sensitivity compared to those of the other receptors, enabling fine control over detection in the low physiological range of IL-6. In addition, we demonstrate the ability of nanobody sensors to function in complex biological matrices and at physiological temperature.","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"38 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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