Cyclic microchip assay for measurement of hundreds of functional proteins in single neurons

Detection of >400 Cluster of Differentiation Biomarkers and Pathway Proteins in Single Immune Cells by Cyclic Multiplex In Situ Tagging for Single-Cell Proteomic Studies

The identification and characterization of immune cell subpopulations are critical to reveal cell development throughout life and immune responses to environmental factors. Next-generation sequencing technologies have dramatically advanced single-cell genomics and transcriptomics for immune cell classification. However, gene expression is often not correlated with protein expression, and immunotyping is mostly accepted in protein format. Current single-cell proteomic technologies are either limited in multiplex capacity or not sensitive enough to detect the critical functional proteins. Herein, we present a single-cell cyclic multiplex in situ tagging (CycMIST) technology to simultaneously measure >400 proteins, a scale of >10 times than similar technologies. Such an ultrahigh multiplexity is achieved by reiterative staining of the single cells coupled with a MIST array for detection. This technology has been thoroughly validated through comparison with flow cytometry and fluorescence immunostaining techniques. Both peripheral blood mononuclear cells (PBMCs) and T cells are analyzed by the CycMIST technology, and almost the entire spectrum of cluster of differentiation (CD) surface markers has been measured. The landscape of fluctuation of CD protein expression in single cells has been uncovered by our technology. Further study found T cell activation signatures and protein-protein networks. This study represents the highest multiplexity of single immune cell marker measurement targeting functional proteins. With additional information from intracellular proteins of the same single cells, our technology can potentially facilitate mechanistic studies of immune responses under various disease conditions.

Picoliter Single-Cell Reactor for Proteome Profiling by In Situ Cell Lysis, Protein Immobilization, Digestion, and Droplet Transfer

Global profiling of single-cell proteomes can reveal cellular heterogeneity, thus benefiting precision medicine. However, current mass spectrometry (MS)-based single-cell proteomic sample processing still faces technical challenges associated with processing efficiency and protein recovery. Herein, we present an innovative sample processing platform based on a picoliter single-cell reactor (picoSCR) for single-cell proteome profiling, which involves in situ protein immobilization and sample transfer. PicoSCR helped minimize surface adsorptive losses by downscaling the processing volume to 400 pL with a contact area of less than 0.4 mm2. Besides, picoSCR reached highly efficient cell lysis and digestion within 30 min, benefiting from optimal reagent and high reactant concentrations. Using the picoSCR-nanoLC-MS system, over 1400 proteins were identified from an individual HeLa cell using data-dependent acquisition mode. Proteins with copy number below 1000 were identified, demonstrating this system with a detection limit of 1.7 zmol. Furthermore, we profiled the proteome of circulating tumor cells (CTCs). Data are available via ProteomeXchange with the identifier PXD051468. Proteins associated with epithelial-mesenchymal transition and neutrophil extracellular traps formation (which are both related to tumor metastasis) were observed in all CTCs. The cellular heterogeneity was revealed by differences in signaling pathways within individual cells. These results highlighted the potential of the picoSCR platform to help discover new biomarkers and explore differences in biological processes between cells.

The lncRNA lnc_AABR07044470.1 promotes the mitochondrial-damaged inflammatory response to neuronal injury via miR-214-3p/PERM1 axis in acute ischemic stroke

PURPOSE

We investigated the role of lnc_AABR07044470.1 on the occurrence and development of acute ischemic stroke (AIS) and neuronal injury by targeting the miR-214-3p/PERM1 axis to find a novel clinical drug target and prediction and treatment of AIS.

METHODS

The mouse AIS animal model was used in vivo experiments and hypoxia/reoxygenation cell model in vitro was established. Firstly, infarction volume and pathological changes of mouse hippocampal neurons were detected using HE staining. Secondly, rat primary neuron apoptosis was detected by flow cytometry assay. The numbers of neuron, microglia and astrocytes were detected using immunofluorescence (IF). Furthermore, binding detection was performed by bioinformatics database and double luciferase reporter assay. Lnc_AABR07044470.1 localization was performed using fluorescence in situ hybridization (FISH).Lnc_AABR07044470.1, miR-214-3pand PERM1mRNA expression was performed using RT-qPCR. NLRP3, ASC, Caspase-1 and PERM1 protein expression was performed using Western blotting. IL-1β was detected by ELISA assay.

RESULTS

Mouse four-vessel occlusion could easily establish the animal model, and AIS animal model had an obvious time-dependence. HE staining showed that, compared with the sham group, infarction volume and pathological changes of mouse hippocampal neurons were deteriorated in the model group. Furthermore, compared with the sham group, neurons were significantly reduced, while microglia and astrocytes were significantly activated. Moreover, the bioinformatics prediction and detection of double luciferase reporter confirmed the binding site of lnc_AABR07044470.1 to miR-214-3p and miR-214-3p to Perm1. lnc_AABR07044470.1 and PERM1 expression was significantly down-regulated and miR-214-3pexpression was significantly up-regulated in AIS animal model in vivo. At the same time, the expression of inflammasome NLRP3, ASC, Caspase-1 and pro-inflammatory factor IL-1β was significantly up-regulated in vivo and in vitro. The over-expression of lnc_AABR07044470.1 and miR-214-3p inhibitor could inhibit the neuron apoptosis and the expression of inflammasome NLRP3, ASC, Caspase-1 and pro-inflammatory factor IL-1β and up-regulate the expression of PERM1 in vitro. Finally, over-expression of lnc_AABR07044470.1 and miR-214-3p inhibitor transfected cell model was significant in relieving the AIS and neuronal injury.

CONCLUSION

Lnc_AABR07044470.1 promotes inflammatory response to neuronal injury via miR-214-3p/PERM1 axis in AIS.

Single-Cell Spatial MIST for Versatile, Scalable Detection of Protein Markers

High-multiplex detection of protein biomarkers across tissue regions has been an attractive spatial biology approach due to significant advantages over traditional immunohistochemistry (IHC) methods. Different from most methods, spatial multiplex in situ tagging (MIST) transfers the spatial protein expression information to an ultrahigh-density, large-scale MIST array. This technique has been optimized to reach single-cell resolution by adoption of smaller array units and 30% 8-arm PEG polymer as transfer medium. Tissue cell nuclei stained with lamin B have been clearly visualized on the MIST arrays and are colocalized with detection of nine mouse brain markers. Pseudocells defined at 10 μm in size have been used to fully profile tissue regions including cells and the intercellular space. We showcased the versatility of our technology by successfully detecting 20 marker proteins in kidney samples with the addition of five minutes atop the duration of standard immunohistochemistry protocols. Spatial MIST is amenable to iterative staining and detection on the same tissue samples. When 25 proteins were co-detected on 1 mouse brain section for each round and 5 rounds were executed, an ultrahigh multiplexity of 125 proteins was obtained for each pseudocell. With its unique abilities, this single-cell spatial MIST technology has the potential to become an important method in advanced diagnosis of complex diseases.

Multiplex Protein Imaging through PACIFIC: Photoactive Immunofluorescence with Iterative Cleavage

Multiplex protein imaging technologies enable deep phenotyping and provide rich spatial information about biological samples. Existing methods have shown great success but also harbored trade-offs between various pros and cons, underscoring the persisting necessity to expand the imaging toolkits. Here we present PACIFIC: photoactive immunofluorescence with iterative cleavage, a new modality of multiplex protein imaging methods. PACIFIC achieves iterative multiplexing by implementing photocleavable fluorophores for antibody labeling with one-step spin-column purification. PACIFIC requires no specialized instrument, no DNA encoding, or chemical treatments. We demonstrate that PACIFIC can resolve cellular heterogeneity in both formalin-fixed paraffin-embedded (FFPE) samples and fixed cells. To further highlight how PACIFIC assists discovery, we integrate PACIFIC with live-cell tracking and identify phosphor-p70S6K as a critical driver that governs U87 cell mobility. Considering the cost, flexibility, and compatibility, we foresee that PACIFIC can confer deep phenotyping capabilities to anyone with access to traditional immunofluorescence platforms.

Rapid, High-Throughput Single-Cell Multiplex In Situ Tagging (MIST) Analysis of Immunological Disease with Machine Learning

The cascade of immune responses involves activation of diverse immune cells and release of a large amount of cytokines, which leads to either normal, balanced inflammation or hyperinflammatory responses and even organ damage by sepsis. Conventional diagnosis of immunological disorders based on multiple cytokines in the blood serum has varied accuracy, and it is difficult to distinguish normal inflammation from sepsis. Herein, we present an approach to detect immunological disorders through rapid, ultrahigh-multiplex analysis of T cells using single-cell multiplex in situ tagging (scMIST) technology. scMIST permits simultaneous detection of 46 markers and cytokines from single cells without the assistance of special instruments. A cecal ligation and puncture sepsis model was built to supply T cells from two groups of mice that survived the surgery or died after 1 day. The scMIST assays have captured the T cell features and the dynamics over the course of recovery. Compared with cytokines in the peripheral blood, T cell markers show different dynamics and cytokine levels. We have applied a random forest machine learning model to single T cells from two groups of mice. Through training, the model has been able to predict the group of mice through T cell classification and majority rule with 94% accuracy. Our approach pioneers the direction of single-cell omics and could be widely applicable to human diseases.

Recent advances in microfluidics for single-cell functional proteomics

Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.