Recent advances in single-cell ultra-trace analysis

Single cell glycan-linkages profiling for hepatocellular carcinoma early diagnosis using lanthanide encoded bacteriophage MS2 based ICP-MS

Early diagnosis is paramount for enhancing survival rates and prognosis in the context of malignant diseases. Hepatocellular carcinoma (HCC), the second leading cause of cancer-related deaths worldwide, poses significant challenges for its early detection. In this study, we present an innovative approach which contributed to the early diagnosis of HCC. By lanthanide encoding signal amplification to map glycan-linkages at the single-cell level, the minute quantities of "soft" glycan-linkages on single cell surface were converted into "hard" elemental tags through the use of an MS2 signal amplifier. Harnessing the power of lanthanides encoded within MS2, we achieve nearly three orders of magnitude signal amplification. These encoded tags are subsequently quantified using single-cell inductively coupled plasma mass spectrometry (SC-ICP-MS). Linear discriminant analysis (LDA) identifies seven specific glycan-linkages (α-2,3-Sia, α-Gal, α-1,2-Fuc, α-1,6-Fuc, α-2,6-Sia, α-GalNAc, and Gal-β-1,3-GalNAc) as biomarkers. Our methodology is initially validated at the cellular level with 100% accuracy in discriminating between hepatic carcinoma HepG2 cells and their normal HL7702 cells. We apply this approach to quantify and classify glycan-linkages on the surfaces of 55 clinical surgical HCC specimens. Leveraging these seven glycan-linkages as biomarkers, we achieve precise differentiation between 8 normal hepatic specimens, 40 early HCC specimens, and 7 colorectal metastasis HCC specimens. This pioneering work represents the first instance of employing single-cell glycan-linkages as biomarkers promising for the early diagnosis of HCC with a remarkable 100% predictive accuracy rate, which holds immense potential for enhancing the feasibility and precision of HCC diagnosis in clinical practice.

Cellular nucleus image-based smarter microscope system for single cell analysis

Cell imaging technology is undoubtedly a powerful tool for studying single-cell heterogeneity due to its non-invasive and visual advantages. It covers microscope hardware, software, and image analysis techniques, which are hindered by low throughput owing to abundant hands-on time and expertise. Herein, a cellular nucleus image-based smarter microscope system for single-cell analysis is reported to achieve high-throughput analysis and high-content detection of cells. By combining the hardware of an automatic fluorescence microscope and multi-object recognition/acquisition software, we have achieved more advanced process automation with the assistance of Robotic Process Automation (RPA), which realizes a high-throughput collection of single-cell images. Automated acquisition of single-cell images has benefits beyond ease and throughout and can lead to uniform standard and higher quality images. We further constructed a single-cell image database-based convolutional neural network (Efficient Convolutional Neural Network, E-CNN) exceeding 20618 single-cell nucleus images. Computational analysis of large and complex data sets enhances the content and efficiency of single-cell analysis with the assistance of Artificial Intelligence (AI), which breaks through the super-resolution microscope's hardware limitation, such as specialized light sources with specific wavelengths, advanced optical components, and high-performance graphics cards. Our system can identify single-cell nucleus images that cannot be artificially distinguished with an accuracy of 95.3%. Overall, we build an ordinary microscope into a high-throughput analysis and high-content smarter microscope system, making it a candidate tool for Imaging cytology.

A Single Set of Well-Designed Aptamer Probes for Reliable On-site Qualitative and Ultra-Sensitive Quantitative Detection

Aptamer-based probes are pivotal components in various sensing strategies, owing to their exceptional specificity and versatile programmable structure. Nevertheless, numerous aptamer-based probes usually offer only a single function, limiting their capacity to meet the diverse requirements of multi-faceted sensing systems. Here, we introduced supersandwich DNA probes (SSW-DNA), designed and modified on the outer surface of nanochannels with hydrophobic inner walls, enabling dual functionality: qualitative detection for on-site analysis and quantitative detection for precise analysis. The fragmented DNAs resulting from the target recognition, are subsequently identified through lateral flow assays, enabling robust on-site qualitative detection of microcystin-LR with an impressively low limit of detection (LOD) at 0.01 μg/L. Meanwhile, the nanochannels enable highly sensitive quantification of microcystin-LR through the current analysis, achieving an exceptionally low LOD at 2.5×10-7  μg/L, with a broad dynamic range spanning from 1×10-6 to 1×102  μg/L. Furthermore, the process of target recognition introduces just a single potential error propagation, which reduces the overall risk of errors during the entire qualitative and quantitative detection process. This sensing strategy broadens the scope of applications for aptamer-based composite probes, holding promising implications across diverse fields, such as medical diagnosis, food safety, and environmental protection.

Single-Cell Caspase-3 Measurement Using a Biomimetic Nanochannel

Direct single-cell caspase-3 (Casp-3) analysis has remained challenging. A study of single-cell Casp-3 could contribute to revealing the fundamental pathogenic mechanisms in Casp-3-associated diseases. Here, a biomimetic nanochannel capable of single-cell sampling and ionic detection of intracellular Casp-3 is devised, which is established upon the installment of target-specific organic molecules (luc-DEVD) within the orifice of a glass nanopipette. The specific cleavage of luc-DEVD by Casp-3 could induce changes of inner-surface chemical groups and charge properties, thus altering the ionic response of the biomimetic nanochannel for direct Casp-3 detection. The practical applicability of this biomimetic nanochannel is confirmed by probing intracellular Casp-3 fluctuation upon drug stimulation and quantifying the Casp-3 evolution during induced apoptosis. This work realizes ionic single-cell Casp-3 analysis and provides a different perspective for single-cell protein analysis.

Expanding the boundaries of atomic spectroscopy at the single-cell level: critical review of SP-ICP-MS, LIBS and LA-ICP-MS advances for the elemental analysis of tissues and single cells

Metals have a fundamental role in microbiology, and accurate methods are needed for their identification and quantification. The inability to assess cellular heterogeneity is considered an impediment to the successful treatment of different diseases. Unlike bulk approaches, single-cell analysis allows elemental heterogeneity across genetically identical populations to be related to specific biological events and to the effectiveness of drugs. Single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) can analyse single cells in suspension and measure this heterogeneity. Here we explore advances in instrumental design, compare mass analysers and discuss key parameters requiring optimisation. This review has identified that the effect of pre-treatment of cell suspensions and cell fixation approaches require further study and novel validation methods are needed as using bulk measurements is unsatisfactory. SP-ICP-MS has the advantage that a large number of cells can be analysed; however, it does not provide spatial information. Techniques based on laser ablation (LA) enable elemental mapping at the single-cell level, such as laser-induced breakdown spectroscopy (LIBS) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). The sensitivity of commercial LIBS instruments restricts its use for sub-tissue applications; however, the capacity to analyse endogenous bulk components paired with developments in nano-LIBS technology shows great potential for cellular research. LA-ICP-MS offers high sensitivity for the direct analysis of single cells, but standardisation requires further development. The hyphenation of these trace elemental analysis techniques and their coupling with multi-omic technologies for single-cell analysis have enormous potential in answering fundamental biological questions.

Spatial single cell metabolomics: Current challenges and future developments

Single cell metabolomics is a rapidly advancing field of bio-analytical chemistry which aims to observe cellular biology with the greatest detail possible. Mass spectrometry imaging and selective cell sampling (e.g. using nanocapillaries) are two common approaches within the field. Recent achievements such as observation of cell-cell interactions, lipids determining cell states and rapid phenotypic identification demonstrate the efficacy of these approaches and the momentum of the field. However, single cell metabolomics can only continue with the same impetus if the universal challenges to the field are met, such as the lack of strategies for standardisation and quantification, and lack of specificity/sensitivity. Mass spectrometry imaging and selective cell sampling come with unique advantages and challenges which, in many cases are complementary to each other. We propose here that the challenges specific to each approach could be ameliorated with collaboration between the two communities driving these approaches.

Research on cell detection method for microfluidic single cell dispensing

Single cell dispensing techniques mainly include limiting dilution, fluorescent-activated cell sorting (FACS) and microfluidic approaches. Limiting dilution process is complicated by statistical analysis of clonally derived cell lines. Flow cytometry and conventional microfluidic chip methods utilize excitation fluorescence signals for detection, potentially causing a non-negligible effect on cell activity. In this paper, we implement a nearly non-destructive single-cell dispensing method based on object detection algorithm. To realize single cell detection, we have built automated image acquisition system and then employed PP-YOLO neural network model as detection framework. Through architecture comparison and parameter optimization, we select ResNet-18vd as backbone for feature extraction. We train and evaluate the flow cell detection model on train and test set consisting of 4076 and 453 annotated images respectively. Experiments show that the model inference an image of 320 × 320 pixels at least 0.9 ms with the precision of 98.6% on a NVidia A100 GPU, achieving a good balance of detection speed and accuracy.

Versatile Construction of Biomimetic Nanosensors for Electrochemical Monitoring of Intracellular Glutathione

The current strategies for nanoelectrode functionalization usually involve sophisticated modification procedures, uncontrollable and unstable modifier assembly, as well as a limited variety of modifiers. To address this issue, we propose a versatile strategy for large-scale synthesis of biomimetic molecular catalysts (BMCs) modified nanowires (NWs) to construct functionalized electrochemical nanosensors. This design protocol employs an easy, controllable and stable assembly of diverse BMCs-poly(3,4-ethylenedioxythiophene) (PEDOT) composites on conductive NWs. The intrinsic catalytic activity of BMCs combined with outstanding electron transfer ability of conductive polymer enables the nanosensors to sensitively and selectively detect various biomolecules. Further application of sulfonated cobalt phthalocyanine functionalized nanosensors achieves real-time electrochemical monitoring of intracellular glutathione levels and its redox homeostasis in single living cells for the first time.

Quantification of silver nanoparticle interactions with yeast Saccharomyces cerevisiae studied using single-cell ICP-MS

Silver nanoparticles (AgNPs) have been used in many fields due to their anticancer, antimicrobial, and antiviral potential. Single-cell ICP-MS (SC-ICP-MS) is an emerging technology that allows for the rapid characterization and quantification of a metal analyte across a cell population in a single analysis. In this study, a new rapid and sensitive SC-ICP-MS method was developed to quantitatively study the interactions of AgNPs with yeast Saccharomyces cerevisiae. The method can quantify the cell concentration, silver concentration per cell, and profile the nanoparticle distribution in a yeast cell population. AgNP dosing time, concentration, and AgNP size were quantitatively evaluated for their effects on AgNP-yeast cell interactions. The results showed that the initial uptake of AgNPs was rapid and primarily driven by the mass of Ag per cell. The optimal dosing particle concentrations for highest uptake were approximately 1820, 1000, and 300 AgNPs/cell for 10, 20, and 40 nm AgNPs, respectively. Furthermore, this study also validated a washing method for the application to a microorganism for the first time and was used to quantitatively determine the amount of cell surface-adsorbed AgNPs and intracellular AgNPs. These results indicated that the mass (Ag in ag/cell) ratios of intracelluar vs cell surface-adsorbed AgNPs were similar for different AgNP sizes. This high throughput and ultrasensitive SC-ICP-MS method is expected to have many potential applications, such as optimization of methods for green synthesis of AgNPs, nanotoxicity studies, and drug delivery. This is the first quantification study on the interactions of AgNPs and S. cerevisiae using SC-ICP-MS.

Single Cell Metabolite Detection Using Inertial Microfluidics-Assisted Ion Mobility Mass Spectrometry

Single-cell metabolite measurement remains highly challenging due to difficulties related to single cell isolation, metabolite detection, and identification of low levels of metabolites. Here, as a first step of the technological development, we propose a novel strategy integrating spiral inertial microfluidics and ion mobility mass spectrometry (IM-MS) for single-cell metabolite detection and identification. Cells in methanol suspension are inertially focused into a single stream in the spiral microchannel. This stream of separated cells is delivered to the nanoelectrospray needle to be lysed and ionized and subsequently analyzed in real time by IM-MS. This analytical system enables six to eight single-cell metabolic fingerprints to be collected per minute, including gas-phase collisional cross section (CCS) measurements as an additional molecular descriptor, giving increased confidence in metabolite identification. As a proof of concept, the metabolic profiles of three types of cancer cells (U2OS, HepG2, and HepG2.215) were successfully screened, and 19 distinct lipids species were identified with CCS value filtering. Furthermore, principal component analysis (PCA) showed differentiation of the three cancer cell lines, mainly due to cellular surface phospholipids. Taken together, our technology platform offers a simple and efficient method for single-cell lipid profiling, with additional ion mobility separation of lipids significantly improving the confidence toward identification of metabolites.

Determination of elemental distribution and evaluation of elemental concentration in single Saccharomyces cerevisiae cells using single cell-inductively coupled plasma mass spectrometry

Single-cell analysis using inductively coupled plasma mass spectrometry (SC-ICP-MS) is a method to obtain qualitative and quantitative information of the elemental content and distribution of single cells. Six intrinsic target elements were analyzed in yeast cells at different cell growth phases cultured in medium with different phosphorus concentrations (0, 7, 14 mM) to study its effect on cell growth and composition. SC-ICP-MS results were compared with those obtained by the acid digestion and the average ratio was 0.81. The limits of detection of this method were 0.08, 2.54, 12.5, 0.02, 0.02, and 0.08 fg cell-1 for Mg, P, K, Mn, Cu, and Zn, respectively. During the exponential growth phase, the cells exhibited higher elemental contents, wider distribution for most elements, and larger cell size in comparison to the stationary growth phase. Phosphorus-free conditions reduced the average P content in single cells of stationary growth phase from 650 to 80 fg. Phosphorus deficiency led to decreasing intracellular concentrations not only of P but also of K and Cu, and to increasing Zn concentration after 48 h. Mg maintained its concentration at ∼0.11 fg µm-3 and did not change significantly under the three investigated conditions after 48 h. Accordingly, Mg content was successfully used to estimate the intracellular concentration of other intrinsic elements in single yeast cells. SC-ICP-MS is suited to determine target elements in single yeast cells, and allows the study of heterogeneity of cell composition and effects of stressors on the elemental content, distribution, and concentrations of intrinsic elements.

Two-Dimensional Cytometry Platform for Single-Particle/Cell Analysis with Laser-Induced Fluorescence and ICP-MS

A two-dimensional cytometry platform (CytoLM) with high sensitivity and high temporal resolution is developed for single-particle and single-cell sampling and analysis. First, a Dean flow-assisted vortex capillary cell sampling (VCCS) unit confines the sample stream in curved flow and drives to focus and align the particles or cells in a small probe volume. By coupling VCCS to a laser-induced fluorescence (LIF) detector with data acquisition and processing capability, a high-throughput single-particle/cell analysis system (VCCS-LIF) was established. The particle analysis throughput of 119.42/s and a detection recovery of 78.20 ± 1.75% were achieved at a density of 9.16 × 10⁴/mL for fluorescent particles, and the cell analysis throughput is 48.20/s at a density of 1.5 × 10⁵/mL. Second, the CytoLM platform is constructed by hyphenating VCCS-LIF with inductively coupled plasma mass spectrometry (ICP-MS). In the analysis of HepG2 cells by Ag⁺ incubation and AO staining, 10,760 fluorescence bursts and 3068 MS events were observed in 240 s. Invalid signals due to undispersed cells were controlled at 3.80% for LIF and 1.01% for MS, with a proportion of effective signal of >96.20%. After peak identification and integral processing of the original data, the statistical results including peak area, height, width, and spacing are obtained concurrently and the information on concentration and elemental quantification of single cells is evaluated. CytoLM facilitates high-throughput, multi-dimensional, and multi-parameter characterization of particles and cells, and it may provide vast potential in life science analysis.

Single-cell fucosylation breakdown: Switching fucose to europium

Fucosylation and its fucosidic linkage-specific motifs are believed to be essential to understand their distinct roles in cellular behavior, but their quantitative information has not yet been fully disclosed due to the requirements of ultra-sensitivity and selectivity. Herein, we report an approach that converts fucose (Fuc) to stable europium (Eu) isotopic mass signal on hard ionization inductively coupled plasma mass spectrometry (ICP-MS). Metabolically assembled azido-fucose on the cell surface allows us to tag them with an alkyne-customized Eu-crafted bacteriophage MS2 capsid nanoparticle for Eu signal multiplication, resulting in an ever lowest detection limit of 4.2 zmol Fuc. Quantitative breakdown of the linkage-specific fucosylation motifs in situ preserved on single cancerous HepG2 and paracancerous HL7702 cells can thus be realized on a single-cell ICP-MS platform, specifying their roles during the cancering process. This approach was further applied to the discrimination of normal hepatocellular cells and highly, moderately, and poorly differentiated hepatoma cells collected from real hepatocellular carcinoma tissues.

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Switching facile fucose to stable Eu mass signal on a single-cell ICP-MS platform

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Ever lowest LOD of 4.2 zmol FucAz was achieved using a Eu-decorated MS2 nanoparticle

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Single-cell breakdown of fucosidic linkage-specific motifs

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Discrimination of highly, moderately, and poorly differentiated HCC from normal ones

The up-to-date strategies for the isolation and manipulation of single cells

Due to the large cellular heterogeneity, the strategies for the isolation and manipulation of single cells have been pronounced indispensable in the fields of disease diagnostics, drug delivery, and cancer biology at the single-cell resolution. Herein, an overview of the up-to-date techniques for precise manipulation/separation and analysis of single-cell is accomplished, these include the various approaches for the isolation and detection of individual cells in flow cytometry, microfluidic systems, micromodule systems, and others. In addition, the advanced application of these protocols is discussed. In particular, a few designs are highlighted for visualization, non-invasion, and intelligentization in single cell analysis, i.e., imaging flow cytometry, label-free microfluidic platform, single-cell capillary probe, and other related techniques. At the present, the main barriers in the various schemes for single cell manipulation which limited their practical applications are their cumbersome construction and single-functionality. The future opportunities and outstanding challenges in the isolation/manipulation of single cells are depicted.