SCMeTA: a pipeline for single-cell metabolic analysis data processing.

SUMMARY: To address the challenges in single-cell metabolomics (SCM) research, we have developed an open-source Python-based modular library, named SCMeTA, for SCM data processing. We designed standardized pipeline and inter-container communication format and have developed modular components to adapt to the diverse needs of SCM studies. The validation was carried out on multiple SCM experiment data. The results demonstrated significant improvements in batch effects, accuracy of results, metabolic extraction rate, cell matching rate, as well as processing speed. This library is of great significance in advancing the practical application of SCM analysis and makes a foundation for wide-scale adoption in biological studies. AVAILABILITY AND IMPLEMENTATION: SCMeTA is freely available on https://github.com/SCMeTA/SCMeTA and https://doi.org/10.5281/zenodo.13569643.

High-Throughput Metabolite Analysis of Unicellular Microalgae by Orthogonal Hybrid Ionization Label-Free Mass Cytometry.

Microalgae metabolite analysis is fundamental for the rational design of metabolic engineering strategies for the biosynthesis of high-value products. Mass spectrometry (MS) has been utilized for single-cell microalgae analysis. However, limitations in the detection throughput and polarities of detectable substances make it difficult to realize high-throughput screening of high-performance microalgae. Herein, a plasma-assisted label-free mass cytometry, named as PACyESI-MS, was proposed combining the advantages of orthogonal hybrid ionization and high-throughput MS analysis, which realized rapid metabolite detection of single microalgae. The cell detection throughput of PACyESI-MS was up to 52 cells/min. Dozens of the critical primary and secondary metabolites within single microalgae were detected simultaneously, including pigments, lipids, and energy metabolites. Furthermore, metabolite changes of Chlamydomonas reinhardtii and Haematococcus pluvialis under nitrogen deficiency stress were studied. Discrimination of Chlamydomonas under different nutrient conditions was realized using single-cell metabolite profiles obtained by PACyESI-MS. The relationships between the accumulation of bioactive astaxanthin and changes in functional primary metabolites of Haematococcus were investigated. It was demonstrated that PACyESI-MS can detect the flexible change of metabolites in single microalgae cells under different nutritional conditions and during the synthesis of high-value products, which is expected to become an important tool for the design of metabolic engineering-based high-performance microalgae factories.

Microfluidic Impedance Cytometry Enabled One-Step Sample Preparation for Efficient Single-Cell Mass Spectrometry.

Single-cell mass spectrometry (MS) is significant in biochemical analysis and holds great potential in biomedical applications. Efficient sample preparation like sorting (i.e., separating target cells from the mixed population) and desalting (i.e., moving the cells off non-volatile salt solution) is urgently required in single-cell MS. However, traditional sample preparation methods suffer from complicated operation with various apparatus, or insufficient performance. Herein, a one-step sample preparation strategy by leveraging label-free impedance flow cytometry (IFC) based microfluidics is proposed. Specifically, the IFC framework to characterize and sort single-cells is adopted. Simultaneously with sorting, the target cell is transferred from the local high-salinity buffer to the MS-compatible solution. In this way, one-step sorting and desalting are achieved and the collected cells can be directly fed for MS analysis. A high sorting efficiency (>99%), cancer cell purity (≈87%), and desalting efficiency (>99%), and the whole workflow of impedance-based separation and MS analysis of normal cells (MCF-10A) and cancer cells (MDA-MB-468) are verified. As a standalone sample preparation module, the microfluidic chip is compatible with a variety of MS analysis methods, and envisioned to provide a new paradigm in efficient MS sample preparation, and further in multi-modal (i.e., electrical and metabolic) characterization of single-cells.

Single-Cell Unsaturated Lipid Profiling for Studying Chemoresistance Heterogeneity of Triple-Negative Breast Cancer Cells.

Chemoresistance to triple-negative breast cancer (TNBC) is a critical issue in clinical practice. Lipid metabolism takes a unique role in breast cancer cells; especially, unsaturated lipids involving cell membrane fluidity and peroxidation are highly remarked. At present, for the lack of a high-resolution molecular recognition platform at the single-cell level, it is still hard to systematically study chemoresistance heterogeneity based on lipid unsaturation proportion. By designing a single-cell mass spectrometry workflow based on CyESI-MS, we profiled the unsaturated lipids of TNBC cells to evaluate lipidomic remodeling under platinum stress. Profiling revealed the heterogeneity of the polyunsaturated lipid proportion of TNBC cells under cisplatin treatment. A cluster of cells identified by polyunsaturated lipid accumulation was found to be involved in platinum sensitivity. Furthermore, we found that the chemoresistance of TNBC cells could be regulated by fatty acid supplementation, which determinates the composition of unsaturated lipids. These discoveries provide insights for monitoring and controlling cellular unsaturated lipid proportions to overcome chemoresistance in breast cancer.

Single-cell metabolite profiling enables information-rich classification of lymphocyte types and subtypes.

Lymphocytes play crucial roles in the human immune system; however, detailed metabolite characteristics need to be further investigated. Herein, we propose a lymphocyte classification method based on metabolite profiling at the single-cell level. The percentages of different lymphocyte types were calculated with a low margin of error, confirming that the metabolites could serve as a basis for lymphocyte classification. Furthermore, we analyzed the CD4/CD8 ratio in human peripheral blood to verify the feasibility of this method for the classification of lymphocyte subtypes. The proposed method is expected to be a potential tool for the clinical diagnosis of lymphocyte-related diseases.

Regulation of the CRISPR-Cas12a system by methylation and demethylation of guide RNA.

Chemical modifications of CRISPR-Cas nucleases help decrease off-target editing and expand the biomedical applications of CRISPR-based gene manipulation tools. Here, we found that epigenetic modifications of guide RNA, such as m6A and m1A methylation, can effectively inhibit both the cis- and trans-DNA cleavage activities of CRISPR-Cas12a. The underlying mechanism is that methylations destabilize the secondary and tertiary structure of gRNA which prevents the assembly of the Cas12a-gRNA nuclease complex, leading to decreased DNA targeting ability. A minimum of three adenine methylated nucleotides are required to completely inhibit the nuclease activity. We also demonstrate that these effects are reversible through the demethylation of gRNA by demethylases. This strategy has been used in the regulation of gene expression, demethylase imaging in living cells and controllable gene editing. The results demonstrate that the methylation-deactivated and demethylase-activated strategy is a promising tool for regulation of the CRISPR-Cas12a system.

Covalent Organic Framework Nanosheets for Fluorescence Quantification of Peptide.

Rapid and sensitive quantification of peptides plays an important role in clinical diagnosis. Fluorescence assay is one of the most promising peptide detection tools, but it relies on intrinsic fluorescence or additional derivatization, resulting in poor versatility. Covalent organic frameworks (COFs) have shown a good application prospect in the field of fluorescence detection, but their application scope is limited to heavy metal ions and some small polar organic molecules. Herein, we report the application of COFs nanosheet for fluorescence detection of peptides. Fluorescent sp2 acrylonitrile-linked COFs nanosheets (TTAN-CON) were prepared by water-assisted ultrasonic exfoliation which performed with excellent fluorescence properties with Stokes shifts of 146 nm and fluorescence quantum yield of up to 24.45%. Compared to the bulk fluorescent COFs, exfoliated CONs films performed with better stability of fluorescence signal in solution. We found the fluorescence of TTAN-CON can be effectively quenched by hydrophobic peptides at a very rapid rate (less than 5 min per sample). TTAN-CON presented good sensitivity and selectivity for hydrophobic peptides detection via the static and dynamic joint quenching mechanism. TTAN-CON was further used to detect NLLGLIEAK and ProGRP31-98, two target peptide fragments of lung cancer biomarker ProGRP. The fluorescence intensities of TTAN-CON were negative linearly correlated with the amounts of hydrophobic NLLGLIEAK over the range of 5-1000 ng/mL with the correlation coefficients over 0.99, and the limit of detection was 1.67 ng/mL, displaying higher sensitivity and convenience than traditional optical methods. What's more, the quantification of ProGRP31-98 was achieved by the quantification of hydrophobic peptides in its enzyme hydrolysis products. We anticipate COFs nanosheets to be a universal fluorescence detection work-box for peptides biomarkers with clinical significance.

The heterogeneity of oxidized lipids in individual tumor cells reveals NK cell-mediated cytotoxicity by label-free mass cytometry.

NK cell-mediated immunotherapy has received increasing attention in the past decade due to its efficacy and bio-safety. The composition and content of lipids in individual cells are closely related to NK cell-mediated cytotoxicity, especially polyunsaturated fatty acids (PUFA) which are oxidized during NK cell-mediated apoptosis. Here we investigated the changes of lipids in single HepG2 cells by label-free mass cytometry and obtained information on 53 lipids and 13 oxidized lipids after the interaction with NK92 MI cells. We found that the contents of lipids and oxidized lipids of HepG2 cells changed obviously during the NK cell-mediated apoptosis. The HepG2 cells could be classified into two phenotypes after co-culturing with NK92 MI cells based on the ratio of PC(38:6-2OH)/PC(38:6) in individual cells, which may serve as a feature to evaluate NK cell-mediated cytotoxicity. The present work used the lipids and oxidized lipids of individual cells to reveal the heterogeneity in NK cell-mediated apoptosis which would be a powerful method for evaluating the cytotoxicity of NK cells at the single-cell level.

Recent progress in mass spectrometry for single-cell metabolomics.

Metabolites are the end products of cellular vital activities and can reflect the state of cellular to a certain extent. Rapid change of metabolites and the low abundance of signature metabolites cause difficulties in single-cell detection, which is a great challenge in single-cell metabolomics analysis. Mass spectrometry (MS) is a powerful tool that uniquely suited to detect intracellular small-molecule metabolites and has shown good application in single-cell metabolite analysis. In this mini-review, we describe three types of emerging technologies for MS-based single-cell metabolic analysis in recent years, including nano-ESI-MS based single-cell metabolomics analysis, high-throughput analysis via flow cytometry, and cellular metabolic imaging analysis. These techniques provide a large amount of single-cell metabolic data, allowing the potential of MS in single-cell metabolic analysis is gradually being explored and is of great importance in disease and life science research.

A Rapid SARS-CoV-2 Nucleocapsid Protein Profiling Assay with High Sensitivity Comparable to Nucleic Acid Detection.

Existing nucleic acid and antigen profiling methods for COVID-19 diagnosis fail to simultaneously meet the demands in sensitivity and detection speed, hampering them from being a comprehensive way for epidemic prevention and control. Thus, effective screening of COVID-19 requires a simple, fast, and sensitive method. Here, we report a rapid assay for ultrasensitive and highly specific profiling of COVID-19 associated antigen. The assay is based on a binding-induced DNA assembly on a nanoparticle scaffold that acts by fluorescence translation. By binding two aptamers to a target protein, the protein brings the DNA regions into close proximity, forming closed-loop conformation and resulting in the formation of the fluorescence translator. Using this assay, saliva nucleocapsid protein (N protein) has been profiled quantitatively by converting the N protein molecule information into a fluorescence signal. The fluorescence intensity is enhanced with increasing N protein concentration caused by the metal enhanced fluorescence using a simple, specific, and fast profiling assay within 3 min. On this basis, the assay enables a high recognition ratio and a limit of detection down to 150 fg mL-1. It is 1-2 orders of magnitude lower than existing commercial antigen ELISA kits, which is comparative to or superior than the PCR based nucleic acid testing. Owing to its rapidity, ultrasensitivity, as well as easy operation, it holds great promise as a tool for screening of COVID-19 and other epidemics such as monkey pox.

Intact living-cell electrolaunching ionization mass spectrometry for single-cell metabolomics.

While single-cell mass spectrometry can reveal cellular heterogeneity and the molecular mechanisms of intracellular biochemical reactions, its application is limited by the insufficient detection sensitivity resulting from matrix interference and sample dilution. Herein, we propose an intact living-cell electrolaunching ionization mass spectrometry (ILCEI-MS) method. A capillary emitter with a narrow-bore, constant-inner-diameter ensures that the entire living cell enters the MS ion-transfer tube. Inlet ionization improves sample utilization, and no solvent is required, preventing sample dilution and matrix interference. Based on these features, the detection sensitivity is greatly improved, and the average signal-to-noise (S/N) ratio is about 20 : 1 of single-cell peaks in the TIC of ILCEI-MS. A high detection throughput of 51 cells per min was achieved by ILCEI-MS for the single-cell metabolic profiling of multiple cell lines, and 368 cellular metabolites were identified. Further, more than 4000 primary single cells digested from the fresh multi-organ tissues of mice were detected by ILCEI-MS, demonstrating its applicability and reliability.

Arsenic retention in erythrocytes and excessive erythrophagocytosis is related to low selenium status by impaired redox homeostasis.

Arsenic (As) contamination in drinking water is a global public health problem. Epidemiological studies have shown that selenium (Se) deficiency is associated with an increasing risk of arsenism. However, the association between Se status and As retention in erythrocytes and mechanisms underlying this association have not been fully investigated. In the present study, a total of 165 eligible subjects were recruited and As was found to accumulate in blood mainly by retention in erythrocytes. Retention of As in erythrocytes was negatively correlated with Se status, antioxidant parameters related to Se and As methylation capacity, but positively correlated with the protein-binding capacity of As. Additionally, erythrocytes isolated from subjects with low Se status exhibited cellular damage along with lower protein levels of CD47, which could be aggravated by hydrogen peroxide treatment. Consistent with the human study, the erythrocytes from mice with sub-chronic As exposure exhibited similar cellular damage and shown to be phagocytosed by splenic macrophages, and these effects were mitigated by dietary Se supplementation. Furthermore, hydrogen peroxide treatment induced excessive phagocytosis of erythrocytes with As exposure by splenic macrophages, while co-treating erythrocytes with the reducing agent, N-Acetyl-l-cysteine, mitigated this excessive erythrophagocytosis. Hyperactivation of the NFκB pathway was also detected in splenic macrophages after excessive erythrophagocytosis. In conclusion, this study found that low Se status involving impaired redox homeostasis increased As retention in erythrocytes, which were subsequently phagocytosed by splenic macrophages and led to an increased inflammatory status of splenic macrophages. These findings provide insight into physiological features of arsenism related to Se status and redox homeostasis.

Determination of testosterone in serum by magnetic molecularly imprinted polymer-coupled nano-ESI-MS.

Monitoring clinical biomarkers, such as testosterone in serum, is important for disease assessment. Due to the very low concentration of testosterone in serum, we have developed a new strategy for its enrichment in serum samples by magnetic molecularly imprinted polymers (MMIPs) technology and detection by nano-electrospray ionization mass spectrometry (Nano-ESI-MS). Testosterone was selectively extracted and enriched by the imprinted polymers on the surface of magnetic particles and the complex matrix was eliminated from the serum. The linear calibration curve was in the range of 0.1-10 µg/L and the limit of detection was 11.4 ng/L. The recovery and repeatability of the spiked serum were satisfactory. These results demonstrate that the proposed method is a promising approach for quantitative analysis of testosterone in serum.

The simultaneous quantitative detection of multiple hormones based on PS-MS: affinity capture by a single antibody.

Steroid hormones play important roles in metabolism and metabolic diseases. Currently, various detection methods are employed in clinical labs, mainly immunoassays and LC-MS/MS, but these methods suffer from antibody cross-reactivity or the need for complex LC processes, respectively. Here, we utilized single antibody to capture and separate multiple hormones from samples to avoid LC procedures and used MS/MS to analyze multiple molecules in a single run. In our strategy, testosterone (T), androstenedione (4-AD), and androsterone (ADT) were affinity-captured simultaneously using only T antibody. The qualitative and quantitative analysis of three androgens was realized through MS/MS spectra using testosterone-D3 (T-D3) as an internal standard. Standard curves for standard solution or spiked serum samples were realized in the range of 0.01-2 µg L-1. The LODs for the three androgens were 2.3 × 10-3 µg L-1 for testosterone, 4.6 × 10-3 µg L-1 for androstenedione, and 2.8 × 10-3 µg L-1 for androsterone. The recovery results verified the reliability and stability of our method. This strategy has widespread potential for advancing the combination of immunoassay and MS methods in the analysis of small molecules, with high through-put and low cost.

Dynamic metabolic change of cancer cells induced by natural killer cells at the single-cell level studied by label-free mass cytometry.

Natural killer cells (NK cells) are important immune cells which have attracted increasing attention in cancer immunotherapy. Due to the heterogeneity of cells, individual cancer cells show different resistance to NK cytotoxicity, which has been revealed by flow cytometry. Here we used label-free mass cytometry (CyESI-MS) as a new tool to analyze the metabolites in Human Hepatocellular Carcinoma (HepG2) cells at the single-cell level after the interaction with different numbers of NK92 MI cells. A large amount of chemical information from individual HepG2 cells was obtained showing the process of cell apoptosis induced by NK cells. Nineteen metabolites which consecutively change during cell apoptosis were revealed by calculating their average relative intensity. Four metabolic pathways were impacted during cell apoptosis which hit 4 metabolites including glutathione (GSH), creatine, glutamic acid and taurine. We found that the HepG2 cells could be divided into two phenotypes after co-culturing with NK cells according to the bimodal distribution of concentration of these 4 metabolites. The correlation between metabolites and different apoptotic pathways in the early apoptosis cell group was established by the 4 metabolites at the single-cell level. This is a new idea of using single-cell specific metabolites to reveal the metabolic heterogeneity in cell apoptosis which would be a powerful means for evaluating the cytotoxicity of NK cells.

Combination of liquid crystal and deep learning reveals distinct signatures of Parkinson's disease-related wild-type α-synuclein and six pathogenic mutants.

α-Synuclein is a central player in Parkinson's disease (PD) pathology. Various point mutations in α-synuclein have been identified to alter the protein-phospholipid binding behavior and cause PD. Therefore, exploration of α-synuclein-phospholipid interaction is important for understanding the PD pathogenesis and helping the early diagnosis of PD. Herein, a phospholipid-decorated liquid crystal (LC)-aqueous interface is constructed to investigate the binding between α-synucleins (wild-type and six familial mutant A30P, E46K, H50Q, G51D, A53E and A53T) and phospholipid. The application of deep learning analyzes and reveals distinct LC signatures generated by the binding of α-synuclein and phospholipid. This system allows for the identification of single point mutant α-synucleins with an average accuracy of 98.3±1.3% in a fast and efficient manner. We propose that this analytical methodology provides a new platform to understand α-synuclein-lipid interactions, and can be potentially developed for easy identification of α-synuclein mutations in common clinic.

Rapid quantitative analysis of hormones in serum by multilayer paper spray MS: Free MS from HPLC.

Developing rapid and reliable method for simultaneous hormones quantitation is of great significant because of important roles of hormones in metabolism. However, current methods are faced with problems of low throughput or complicated operation procedure to remove matrices from serum samples in routine clinical diagnosis. In the present work, a multilayer PS-MS method was developed for rapid and simple detection of hormones. In the strategy, multilayer filter paper acted as the Liquid Chromatography in LC-MS/MS for separation of hormones and biological matrices. Qualitative and quantitative analysis of three hormones, testosterone (T), androsterone (ADT) and androstenedione (4-AD) were realized through MS/MS spectra. The method exhibited linearity in the range of 0.02-2 µg/L and the results of recovery and repeatability were satisfactory for standard samples and spiked serum. The time-cost of a whole detection process was less than 3 min. The established multilayer PS-MS realized rapid, simple and reliable quantitative analysis of various hormones and provided broad prospect for clinical analysis of small molecules in different biological samples. Moreover, it provides a novel MS approach with high through-put and free HPLC, meeting the requirements of point-of-care testing (POCT).

Rapid Disulfide Mapping in Peptides and Proteins by meta-Chloroperoxybenzoic Acid (mCPBA) Oxidation and Tandem Mass Spectrometry.

Disulfide bonds are a class of important post-translational modifications that play important roles in modulating the structures and functions of proteins. Therefore, the mapping of disulfide linkages in peptides and proteins is indispensable for complete structure characterization and functional studies. As disulfide bonds in protonated ions do not dissociate readily under low-energy collision-induced dissociation (CID), they are usually chemically cleaved or activated prior to mass spectrometry (MS) or tandem MS (MS/MS) analysis. In this study, we report a new method that allows the mapping of disulfide linkages in peptides and proteins through meta-chloroperoxybenzoic acid (mCPBA)-based disulfide oxidation and MS/MS. Upon oxidation, the disulfide bond is converted to a thiosulfinate group, i.e., S(═O)-S, in a rapid (>60% yield in 1 min) and highly specific approach in an aqueous phase. The thiosulfinate group is then preferentially cleaved by MS/MS. For interchain disulfide linkages, this leads to a facile peptide chain separation and the identification of disulfide-linked peptides. For intrachain disulfide linkages, collisional activation of the thiosulfinate leads to disulfide cleavage and fragmentation of the peptide backbone constrained by the disulfide loop, enabling a near-complete peptide sequencing. The mCPBA oxidation-based disulfide mapping strategy can be readily integrated with bottom-up or top-down protein analysis for comprehensive protein structure elucidation, e.g., digested lysozyme and intact human insulin.

Discriminating Leukemia Cellular Heterogeneity and Screening Metabolite Biomarker Candidates using Label-Free Mass Cytometry.

Discriminating various leukocyte subsets with specific functions is critical due to their important roles in the development of many diseases. Here, we proposed a general strategy to unravel leukocytes heterogeneity and screen differentiated metabolites as biomarker candidates for leukocyte subtypes using the label-free mass cytometry (CyESI-MS) combined with a homemade data processing workflow. Taking leukemia cells as an example, metabolic fingerprints of single leukemia cells were obtained from 472 HL-60, 416 THP-1, 313 U937, 356 Jurkat, and 366 Ramos cells, with throughput up to 40 cells/min. Five leukemia subtypes were clearly distinguished by unsupervised learning t-SNE analysis of the single-cell metabolic fingerprints. Cell discrimination in the mixed leukemia cell samples was also realized by supervised learning of the single-cell metabolic fingerprints with high recovery and good repetition (98.31 ± 0.24%, -102.35 ± 4.82%). Statistical analysis and metabolite assignment were carried out to screen characteristic metabolites for discrimination and 36 metabolites with significant differences were annotated. Then, differentiated metabolites for pairwise discrimination of five leukemia subtypes were further selected as biomarker candidates. Furthermore, discriminating cultured leukemia cells from human normal leukocytes, separated from fresh human peripheral blood, was performed based on single-cell metabolic fingerprints as well as the proposed biomarker candidates, unveiling the potential of this strategy in clinical research. This work makes efforts to realize high-throughput single-leukocyte metabolic analysis and metabolite-based discrimination of leukocytes. It is expected to be a powerful means for the clinical molecular diagnosis of hematological diseases.

Combination of Structured Illumination Microscopy with Hyperspectral Imaging for Cell Analysis.

Existing structured illumination microscopy (SIM) allows super-resolution live-cell imaging in few color channels that provide merely morphological information but cannot acquire the sample spectrum that is strongly relevant to the underlying physicochemical property. We develop hyperspectral SIM which enables high-speed spectral super-resolution imaging in SIM for the first time. Through optically mapping the three-dimensional (x, y, and λ) datacube of the sample to the detector plane, hyperspectral SIM allows snapshot spectral imaging of the SIM raw image, detecting the sample spectrum while retaining the high-speed and super-resolution characteristics of SIM. We demonstrate hyperspectral SIM imaging and reconstruct a datacube containing 31 super-resolution images of different wavelengths from only 9 exposures, achieving a 15 nm spectral resolution. We show time-lapse hyperspectral SIM imaging that achieves an imaging speed of 2.7 s per datacube-31-fold faster than the existing wavelength scanning strategy. To demonstrate the great prospects for further combining hyperspectral SIM with various spectral analysis methods, we also perform spectral unmixing of the hyperspectral SIM result while imaging the spectrally overlapped sample.