Identification of clinically relevant subsets CD39+PD-1+CD8+ T cells and CD39+ regulatory T cells in intrahepatic cholangiocarcinoma using single-cell CyTOF

Intrahepatic cholangiocarcinoma (iCCA) is an aggressive liver malignancy with limited treatment options and a dismal prognosis. The tumor immune microenvironment (TIME) is crucial for iCCA progression, yet its comprehensive characterization remains incomplete. This study utilized mass cytometry by time of flight (CyTOF) to comprehensively analyze immune cell populations in fresh iCCA tumor samples and adjacent peritumor liver tissues. Notably, NK cell percentages significantly decreased in iCCA lesions compared to peritumor liver tissues. Conversely, an enrichment of immunosuppressive CD39+Foxp3+CD4+ regulatory T cells (CD39+T-regs) and exhausted-like CD8+T cells (with pronounced CD39 and PD-1 expression) within TIME was identified and confirmed by multiplex immunofluorescence staining in an independent patient cohort (n = 140). Crucially, tumor-infiltrating CD39+T-regs and CD39+PD-1+CD8+T cells emerged as independent prognostic indicators associated with an unfavorable prognosis in iCCA. These findings unveil the intricate immune landscape within iCCA, offering valuable insights for disease management and novel cancer immunotherapies.

In situ monitoring of cytoplasmic dopamine levels by noble metals decorated carbon fiber tips

Dopamine (DA), a catecholamine neurotransmitter, is crucial in brain signal transmission. Monitoring cytoplasmic DA levels can reflect changes in metabolic factors and provide valuable information for researching the mechanisms involved in neurodegenerative diseases. However, the in-situ detection of intracellular DA is constrained by its low contents in small-sized single cells. In this work, we report that noble metal (Au, Pt)-modified carbon fiber micro-nanoelectrodes are capable of real-time detection of DA in single cells with excellent sensitivity, selectivity, and anti-contamination capabilities. Notably, noble metals can be modified on the electrode surface through electrochemical deposition to enhance the conductivity of the electrode and the oxidation current of DA by 50 %. The nanosensors can work stably and continuously in rat adrenal pheochromocytoma cells (PC12) to monitor changes in DA levels upon K+ stimulation. The functionalized carbon fibers based nanosensors will provide excellent prospects for DA analysis in the brains of living animals.

The high molecular diversity in Noctiluca scintillans is dominated by intra-genomic variations revealed by single cell high-throughput sequencing of 18S rDNA V4

The application of high-throughput sequencing (HTS) technologies has revolutionized research on phytoplankton biodiversity by generating an unprecedented amount of molecular data in marine ecosystem surveys. However, high-level of molecular diversity uncovered in HTS-based metabarcoding analyses may lead to overinterpretation of phytoplankton diversity due to excessive intra-genomic variations (IGVs). The aims in this study are to explore the nature of phytoplankton molecular diversity and to test the hypothesis. We carried out single-cell metabarcoding analysis of 18S rDNA V4 sequences obtained in single Noctiluca scintillans cells isolated from various sites in coastal waters of China. Results showed that each single N. scintillans cell harbored a high level of IGVs with about 100 amplicon sequence variants (ASVs). The large numbers of non-dominant ASVs identified in N. scintillans cells, which might correspond to the larger numbers of ASVs annotated as N. scintillans and showed similar temporal dynamics in metabarcoding analyses, could inflate the inter-species diversity or intra-species genetic diversity. In addition, there were large numbers of additional ASVs that were not annotated as N. scintillans. These non-N. scintillans ASVs might represent diverse preys for N. scintillans, consistent with previous reports that N. scintillans may act as chance predator of a broad-spectrum preys. This single-cell study has unambiguously demonstrated that the existence of high levels of IGVs in N. scintillans and most likely many other phytoplankton species, demonstrating that the majority of the molecular diversity revealed in metabarcoding analysis, which were generally interpreted as the sum of inter-species diversity and intra-species diversity, actually included high levels of IGVs and should be interpreted with caution.

Identification of prognostic coagulation-related signatures in clear cell renal cell carcinoma through integrated multi-omics analysis and machine learning

Clear cell renal cell carcinoma is a threat to public health with high morbidity and mortality. Clinical evidence has shown that cancer-associated thrombosis poses significant challenges to treatments, including drug resistance and difficulties in surgical decision-making in ccRCC. However, the coagulation pathway, one of the core mechanisms of cancer-associated thrombosis, recently found closely related to the tumor microenvironment and immune-related pathway, is rarely researched in ccRCC. Therefore, we integrated bulk RNA-seq data, DNA mutation and methylation data, single-cell data, and proteomic data to perform a comprehensive analysis of coagulation-related genes in ccRCC. First, we demonstrated the importance of the coagulation-related gene set by consensus clustering. Based on machine learning, we identified 5 coagulation signature genes and verified their clinical value in TCGA, ICGC, and E-MTAB-1980 databases. It's also demonstrated that the specific expression patterns of coagulation signature genes driven by CNV and methylation were closely correlated with pathways including apoptosis, immune infiltration, angiogenesis, and the construction of extracellular matrix. Moreover, we identified two types of tumor cells in single-cell data by machine learning, and the coagulation signature genes were differentially expressed in two types of tumor cells. Besides, the signature genes were proven to influence immune cells especially the differentiation of T cells. And their protein level was also validated.

Species-dependent uptake of gadolinium in Chlamydomonas reinhardtii algae

Single cell-inductively coupled plasma-mass spectrometry (sc-ICP-MS) was used in this study as a valuable tool to assess the species-dependent uptake of metallopharmaceuticals into algal cells. Chlamydomonas reinhardtii algae were incubated for 24 h with four Gadolinium-based contrast agents (GBCAs) and GdCl3. A species dependency towards the uptake of the tested Gd species was observed. Using single cell-ICP-MS, a Gd signal corresponding to single cell events was detected for GdCl3 and the linear GBCAs Omniscan® (Gadodiamide, Gd-DTPA-BMA) and Magnevist® (Gadodiamide, Gd-DTPA). For the macrocyclic complexes Dotarem® (Gadoteric acid, Gd-DOTA) and Gadovist® (Gadobutrol, Gd-BT-DO3A), no such Gd signal was visible. Total Gd analysis via ICP-MS confirmed the presence of Gd in the cells only after incubation with GdCl3 and the linear GBCAs, while only small amounts of Gd were detected for the incubations with macrocyclic GBCAs. Furthermore, the results showed that more Gd is bound to cell structures or macromolecules, while smaller amounts are present in the lysate. Using hydrophilic interaction liquid chromatography (HILIC)-ICP-MS, the soluble Gd species in the lysate were analyzed to determine if the initial Gd complexes were still intact. Surprisingly, no intact GBCAs were detected in the lysates of any incubation solution, possibly due to a change in Gd speciation. Further research is needed to assess which Gd species are present in the lysate, while "free" Gd ions or adducts with cell constituents are the most likely explanation. This study highlights the need for species-dependent investigation of elements in aquatic organisms. Moreover, the uptake of linear GBCAs and their species alteration raises the question of a potential accumulation of Gd in the food chain.

Gene transcription regulation by ER at the single cell and allele level

In this short review we discuss the current view of how the estrogen receptor (ER), a pivotal member of the nuclear receptor superfamily of transcription factors, regulates gene transcription at the single cell and allele level, focusing on in vitro cell line models. We discuss central topics and new trends in molecular biology including phenotypic heterogeneity, single cell sequencing, nuclear phase separated condensates, single cell imaging, and image analysis methods, with particular focus on the methodologies and results that have been reported in the last few years using microscopy-based techniques. These observations augment the results from biochemical assays that lead to a much more complex and dynamic view of how ER, and arguably most transcription factors, act to regulate gene transcription.

Confinement-enhanced microalgal individuals biosensing for digital atrazine assay

Microalgal sensors are widely recognized for their high sensitivity, accessibility, and low cost. However, the current dilemma of motion-induced spatial phase changes and concentration-related multiple scattering interferes with induced test instability and limited sensitivity, which has hindered their practical applications. Here, a differentiated strategy, named confinement-enhanced microalgal biosensing (C-EMB), is developed and proposed to pave the way. The in-situ printed microgel trap is designed to confine Chlamydomonas reinhardtii individuals, stabilizing their spatial phase. The microgel trap arrays are introduced to eliminate the multiple scattering of microalgae, breaking the existing effective concentration in traditional microalgal sensing and enabling sensitive assays. The integration with lab-on-a-chip technology and a developed digital imaging algorithm empower portable and automated detection. With this system, a microalgae analyzer is developed for atrazine detection, featuring a linear range of 0.04-100 μg/L. We assess the system's performance through practical atrazine assays on commercial food, using a double-blind test against a standard instrument. Our results demonstrate the good accuracy and test stability of this system with the mean bias atrazine detection in corn and sugarcane juice samples (SD) were 1.661 μg/L (3.122 μg/L) and 3.144 μg/L (4.125 μg/L), respectively. This method provides a new paradigm of microalgal sensors and should advance the further applications of microalgal sensors in commercial and practical settings.

Phenotype predictions of two-person mixture using single cell analysis

Over a decade after the publication of the first forensic DNA phenotyping (FDP) studies, DNA-based appearance predictions are now becoming a reality in routine crime scene investigations. The significant number of publications dedicated to the subject of FDP clearly demonstrates a sustained interest and a strong need for further method development. However, the implementation of FDP in routine work still encounters obstacles, and one of these challenges is making phenotype predictions from DNA mixtures. In this study, we examined single-cell sequencing as a potential tool to enable reliable phenotyping of contributors within mixtures. Two mock mixtures, each containing two contributors with similar and different physical appearances, were analyzed using two different workflows. In the first workflow, the mixtures were sequenced using the Ion AmpliSeq™ PhenoTrivium Panel, which includes 41 HIrisPlex-S (HPS) markers. Subsequently, the genotypes were analyzed using the HPS Deconvolution Tool to predict the phenotypes of both contributors. The second workflow involved the introduction of single-cell separation and collection using the DEPArray™ PLUS System. Two different PhenoTrivium amplification protocols were tested, and the phenotype predictions from single cells were compared with the results obtained using the HPS Tool. Our results suggest that the approach presented here allows for the obtainment of nearly complete HIrisPlex-S profiles with accurate genotypes and reliable phenotype predictions from single cells. This method proves successful in deconvoluting mixtures submitted to forensic DNA phenotyping.

Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learning

Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.

Evaluation of Cd2+ stress on Synechocystis sp. PCC6803 based on single-cell elemental accumulation and algal toxicological response

With the development of single cell analysis techniques, the concept of precision toxicology has been proposed in recent years. Due to the heterogeneity of cells, we need to perform toxicological assessments on individual cells. Microalgae, one kind of important primary producers, play as a major pathway by which heavy metals enter the food chain and thus accumulate/transfer to higher trophic levels. Herein, the biosorption of Cd (Ex-Cd) and bioaccumulation of Cd (In-Cd) for Synechocystis sp. PCC 6803 were investigated by online 3D droplet microfluidic device combined with inductively coupled plasma mass spectrometry detection. Meanwhile, the algal toxicological responses of the algae cell to Cd²⁺ exposure under different concentration (50, 100, and 150 μg L ^- 1) and time (15 min, 24, 48 and 96 h) were studied. Combining single-cell analysis with toxicological indicators, the toxicity mechanism of Cd²⁺to algal was discussed. The single cell analysis results revealed heterogeneity in cellular uptake of Cd²⁺. The proportion of Cd-containing cells and Cd content in single algal cells all reached the maximum at 24 h. The uptake of Cd²⁺ occurred within 15 min under all tested exposure concentrations and a large part of Cd²⁺ were adsorbed on the algal cells surface. The Pearson correlation analysis showed that cell density, chlorophyll a and carotenoids were significantly negatively correlated with Cd accumulation, whereas ROS level and SOD activity were significantly positively correlated with Cd accumulation. It suggested that Cd²⁺accumulated intracellular would show toxic effects on the algal cells and oxidative stress is the main mechanism of Cd toxicity to algal cells. This work promotes our understanding of the toxicological responses of microalgae under Cd stress at single cells level.

Linking antigen specific T-cell dynamics in a microfluidic chip to single cell transcription patterns

A new non-invasive screening profile has been realized that can aid in determining T-cell activation state at single-cell level. Production of activated T-cells with good specificity and stable proliferation is greatly beneficial for advancing adoptive immunotherapy as innate immunological cells are not effective in recognizing and eliminating cancer as expected. The screening method is realized by relating intracellular Ca²⁺ intensity and motility of T-cells interacting with APC (Antigen Presenting Cells) in a microfluidic chip. The system is tested using APC pulsed with OVA_257-264 peptide and its modified affinities (N4, Q4, T4 and V4), and the T-cells from OT-1 mice. In addition, single cell RNA sequencing reveals the activation states of the cells and the clusters from the derived profiles can be indicative of the T-cell activation state. The presented system here can be versatile for a comprehensive application to proceed with T-cell-based immunotherapy and screen the antigen-specific T-cells with excellent efficiency and high proliferation.

Nanokit coupled electrospray ionization mass spectrometry for analysis of angiotensin converting enzyme 2 activity in single living cell

Angiotensin-converting enzyme 2 (ACE2) is not only an enzyme but also a functional receptor on cell membrane for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, the activity of ACE2 in single living cell is firstly determined using a nanokit coupled electrospray ionization mass spectrometry (nanokit-ESI-MS). Upon the insertion of a micro-capillary into the living hACE2-CHO cell and the electrochemical sorting of the cytosol, the target ACE2 enzyme hydrolyses angiotensin II inside the capillary to generate angiotensin 1-7. After the electrospray of the mixture at the tip of the capillary, the product is differentiated from the substrate in molecular weight to achieve the detection of ACE2 activity in single cells. The further measurement illustrates that the inflammatory state of cells does not lead to the significant change of ACE2 catalytic activity, which elucidates the relationship between intracellular ACE2 activity and inflammation at single cell level. The established strategy will provide a specific analytical method for further studying the role of ACE2 in the process of virus infection, and extend the application of nanokit based single cell analysis.

Investigation of toxic effect of mercury on Microcystis aeruginosa: Correlation between intracellular mercury content at single cells level and algae physiological responses

Single-cell studies can help to understand individual differences and obtain atypical cellular characteristics in view of cellular heterogeneity. Herein, the accumulation of mercury (Hg) in single algae cells was studied by droplet chip-time resolved inductively coupled plasma mass spectrometry analytical system, and the relation of Hg accumulation to the physiological responses of algae cell was explored. When low concentrations of Hg²⁺ (5-20 μg/L) were used in the exposure experiment, the content of Hg in single cells increased in first 2 h, then decreased with further increase of exposure time to 96 h, probably due to the growth dilution effect of the algae. When exposed to 30 μg/L Hg²⁺, the uptake of Hg by individual cells increased over time, which was associated with increased cell membrane permeability. The exposure to Hg²⁺ (5-30 μg/L) inhibited the growth of algae in a concentration-dependent manner and serious growth inhibition occurred under the exposure concentration of 30 μg/L. While the exposure concentration was lower than 20 μg/L, algal cells exhibited a recover tendency due to the self-protection mechanism of algal cells. Bivariate results showed that intracellular Hg accumulation was significantly negatively correlated with cells growth in terms of OD₆₈₀, photosynthetic pigments, F_v/F_m and PI_abs. On the contrast, reactive oxygen species content, superoxide dismutase activity, and cell membrane permeability were significantly positively correlated with the accumulation of intracellular Hg. These results are helpful to further understand the toxic effect of Hg on algae.

High-Efficiency Single-Cell Electrical Impedance Spectroscopy

Single-cell impedance measurement is label free and noninvasive in characterizing the electrical properties of single cells. At present, though widely used for impedance measurement, electrical impedance flow cytometry (IFC) and electrical impedance spectroscopy (EIS) are used alone for most microfluidic chips. Here, we describe high-efficiency single-cell electrical impedance spectroscopy, which combines in one chip the IFC and EIS techniques for high-efficiency single-cell electrical property measurement. We envision that the strategy of combining IFC and EIS provides a new thought in the efforts to enhance the efficiency of electrical property measurement for single cells.

Resolving Crosstalk Between Signaling Pathways Using Mathematical Modeling and Time-Resolved Single Cell Data

Crosstalk between signaling pathways can modulate the cellular response to stimuli and is therefore an important part of signal transduction. For a comprehensive understanding of cellular responses, identifying points of interaction between the underlying molecular networks is essential. Here, we present an approach that allows the systematic prediction of such interactions by perturbing one pathway and quantifying the concomitant alterations in the response of a second pathway. As the observed alterations contain information about the crosstalk, we use an ordinary differential equation-based model to extract this information by linking altered dynamics to individual processes. Consequently, we can predict the interaction points between two pathways. As an example, we employed our approach to investigate the crosstalk between the NF-κB and p53 signaling pathway. We monitored the response of p53 to genotoxic stress using time-resolved single cell data and perturbed NF-κB signaling by inhibiting the kinase IKK2. Employing a subpopulation-based modeling approach enabled us to identify multiple interaction points that are simultaneously affected by perturbation of NF-κB signaling. Hence, our approach can be used to analyze crosstalk between two signaling pathways in a systematic manner.

Computational modeling implicates protein scaffolding in p38 regulation of Akt

Cells process environmental cues by activating intracellular signaling pathways with numerous interconnections and opportunities for cross-regulation. We employed a systems biology approach to investigate intersections of kinase p38, a context-dependent tumor suppressor or promoter, with Akt and ERK, two kinases known to promote cell survival, proliferation, and drug resistance in cancer. Using live, single cell microscopy, multiplexed fluorescent reporters of p38, Akt, and ERK activities, and a custom automated image-processing pipeline, we detected marked heterogeneity of signaling outputs in breast cancer cells stimulated with chemokine CXCL12 or epidermal growth factor (EGF). Basal activity of p38 correlated inversely with amplitude of Akt and ERK activation in response to either ligand. Remarkably, small molecule inhibitors of p38 immediately decreased basal activities of Akt and ERK but increased the proportion of cells with high amplitude ligand-induced activation of Akt signaling. To identify mechanisms underlying cross-talk of p38 with Akt signaling, we developed a computational model incorporating subcellular compartmentalization of signaling molecules by scaffold proteins. Dynamics of this model revealed that subcellular scaffolding of Akt accounted for observed regulation by p38. The model also predicted that differences in the amount of scaffold protein in a subcellular compartment captured the observed single cell heterogeneity in signaling. Finally, our model predicted that reduction in kinase signaling can be accomplished by both scaffolding and direct kinase inhibition. However, scaffolding inhibition can potentiate future kinase activity by redistribution of pathway components, potentially amplifying oncogenic signaling. These studies reveal how computational modeling can decipher mechanisms of cross-talk between the p38 and Akt signaling pathways and point to scaffold proteins as central regulators of signaling dynamics and amplitude.

Label-free tumor cell screening based on IDO1-mediated tryptophan metabolism at single cell level

Indoleamine 2,3-dioxygenase 1 (IDO1) plays a critical role in inflammatory and immunometabolism programming through catalyzing the oxidation of tryptophan (Trp) into downstream N-formylkynurenine. IDO1 is typically up-regulated in malignant tumors, making it a potential biomarker for cancer diagnosis. Here we show an effective strategy for tumor cell detection by integrating IDO1 activity assay with single cell-encapsulated droplets on a microfluidic platform for high-throughput bioanalysis. Mixed cells, as well as other cofactors, are encapsulated in individual droplets, which act as dynamic microreactors for IDO1-catalyzed oxidation of Trp. After pico-injection of a biosensing ensemble consisting of the macrocycle cucurbit [8]uril (Q8) and a fluorescent guest, rapid and robust screening of tumor cells by fluorescence signal is achieved in a few minutes reporting to Trp depletion, expanding the scope of conventional antibody-based detection of protein biomarkers. The results represent the first example of quantifying IDO1 enzymatic activity at the single cell level with a high-throughput performance, therefore promising warning signs and early diagnosis of tumor cells.

An ultrasensitive bunge bedstraw herb type DNA machine for absolute quantification of mRNA in single cell

Messenger ribonucleic acids (mRNAs) comprise a class of small nucleic acids carrying genetic information, which exhibit very important role in medical research and diagnosis. If only the mean mRNA expression levels of the mRNA population are considered in medical research, important information linking mRNA expression and cellular function may be lost. Single-cell analysis provides valuable insights into studying its heterogeneity, signaling, and stochastic gene expression. In this study, a "bunge bedstraw herb"-type DNA machine based on DNAzyme catalyzing coupled clamping hybrid chain reaction (c-HCR) is presented. In the DNA machine, a bunge bedstraw herb-type DNA structure was first formed by hybridizing a core junction scaffold cruciform probe to a hairpin probe that can trigger the c-HCR via a target molecule in four directions. This approach can reduce the detection limit of mRNA to 5 × 10^-15 M. Absolute quantification of survivin mRNA in individual cells was achieved using the DNA machine on a microfluidic chip electrophoresis platform. The reported method represents an unprecedented single-cell analysis platform for single-cell biology studies.

Rolling circle amplification of begomoviral DNA from a single nucleus isolated by laser dissection microscopy

Laser dissection microscopy (LDM) is a method for isolating organelles, a specific cell or cells/tissue of interest from microscopic regions with the help of a laser. Here we describe a LDM-based isolation of begomovirus infected Nicotiana benthamiana epidermal cells and nuclei, in combination with a fast method to prepare non-fixed leaf epidermal samples for LDM. The bipartite Abutilon mosaic virus (AbMV) was used in which the coat protein gene of DNA A was deleted and replaced by the open reading frame (ORF) coding for the green fluorescent protein (GFP, accession: U87624), agro-infiltrated together with DNA B, to visualize infected cells. GFP expressing epidermal cells or nuclei were isolated by LDM with the MMi Cellcut system and viral circular DNA was amplified by rolling circle amplification (RCA). Subsequently, the RCA product was incubated with the restriction enzymes BamHI and PstI and restriction fragments were separated on an agarose gel to prove presence of the viral genome. It was shown that even a single-isolated nucleus harbored enough material to produce a sufficient restriction fragment pattern to identify a begomovirus infected cell/nucleus.

Evaluation and optimization of PolyJet 3D-printed materials for cell culture studies

Use of 3D printing for microfluidics is a rapidly growing area, with applications involving cell culture in these devices also becoming of interest. 3D printing can be used to create custom-designed devices that have complex features and integrate different material types in one device; however, there are fewer studies studying the ability to culture cells on the various substrates that are available. This work describes the effect of PolyJet 3D-printing technology on cell culture of two cell lines, bovine pulmonary artery endothelial cells (BPAECs) and Madin-Darby Canine Kidney (MDCK) cells, on two different types of printed materials (VeroClear or MED610). It was found that untreated devices, when used for studies of 1 day or more, led to unsuccessful culture. A variety of device treatment methodologies were investigated, with the most success coming from the use of sodium hydroxide/sodium metasilicate solution. Devices treated with this cleaning step resulted in culture of BPAECs and MDCK cells that were more similar to what is obtained in traditional culture flasks (in terms of cell morphology, viability, and cell density). LC-MS/MS analysis (via Orbitrap MS) was used to determine potential leachates from untreated devices. Finally, the use of a fiber scaffold in the devices was utilized to further evaluate the treatment methodology and to also demonstrate the ability to perform 3D culture in such devices. This study will be of use for researchers wanting to utilize these or other cell types in PolyJet-based 3D-printed devices.

Advances in droplet microfluidics for SERS and Raman analysis

Raman spectroscopy can realize qualitative and quantitative characterization, and surface-enhanced Raman spectroscopy (SERS) can further enhance its detection sensitivity. In combination with droplet microfluidics, some significant but insurmountable limitations of SERS and Raman spectroscopy can be overcome to some extent, thus improving their detection capability and extending their application. During the past decade, these systems have constantly developed and demonstrated a great potential in more applications, but there is no new review systematically summarizing the droplet microfluidics-based Raman and SERS analysis system since the first related review was published in 2011. Thus, there is a great need for a new review to summarize the advances. In this review, we focus on droplet microfluidics-based Raman and SERS analysis, and summarize two mainstream research directions on this topic up to now. The one is SERS or Raman detection in the moving droplet microreactors, including analysis of molecules, single cells and chemical reaction processes. The other one is SERS active microparticle fabrication via microfluidic droplet templates covering polymer matrix and photonic crystal microparticles. We also comment on the advantages, disadvantage and correlation resolution of droplet microfluidics for SERS or Raman. Finally, we summarize these systems and illustrate our perspectives for future research directions in this field.

An ultrasensitive multivariate signal amplification strategy based on microchip platform tailored for simultaneous quantification of multiple microRNAs in single cell

MicroRNAs (miRNAs) play a very important regulatory role in life activities. Abnormal expression levels of miRNAs in cells are associated with various diseases, especially human cancer. Nevertheless, accurate detection of the copy numbers of various miRNA molecules in single cell is still a great challenge. In this study, an intracellular multivariate signal amplification strategy based on microchip platform was proposed, and an ultrasensitive single-cell analysis method was established for simultaneous quantification of absolute copy numbers of multiple miRNAs in a single cell. Using miRNA-21 and miRNA-141 as the analytical models of miRNAs, the detection limits of 1.0 and 2.0 fM were obtained. Based on the developed method, an analysis of 600 randomly acquired different types of cells was performed. The distribution of absolute copy numbers of miRNA-21 and miRNA-141 in six types of cells was obtained. It was found that the number of copies of miRNA-21 and miRNA-141 in different types of cancer cells showed different expression characteristics. The study results can help us more accurately understand cell-to-cell heterogeneity and the relationship between different miRNAs and different types of cancer at the single cell level.

Breast cancer circulating tumor cells with mesenchymal features-an unreachable target?

Circulating tumor cells (CTCs) mediate dissemination of solid tumors and can be an early sign of disease progression. Moreover, they show a great potential in terms of non-invasive, longitudinal monitoring of cancer patients. CTCs have been extensively studied in breast cancer (BC) and were shown to present a significant phenotypic plasticity connected with initiation of epithelial-mesenchymal transition (EMT). Apart from conferring malignant properties, EMT affects CTCs recovery rate, making a significant portion of CTCs from patients’ samples undetected. Wider application of methods and markers designed to isolate and identify mesenchymal CTCs is required to expand our knowledge about the clinical impact of mesenchymal CTCs. Therefore, here we provide a comprehensive review of clinical significance of mesenchymal CTCs in BC together with statistical analysis of previously published data, in which we assessed the suitability of a number of methods/markers used for isolation of CTCs with different EMT phenotypes, both in in vitro spike-in tests with BC cell lines, as well as clinical samples. Results of spiked-in cell lines indicate that, in general, methods not based on epithelial enrichment only, capture mesenchymal CTCs much more efficiently that CellSearch^® (golden standard in CTCs detection), but at the same time are not much inferior to Cell Search^®, though large variation in recovery rates of added cells among the methods is observed. In clinical samples, where additional CTCs detection markers are needed, positive epithelial-based CTCs enrichment was the most efficient in isolating CTCs with mesenchymal features from non-metastatic BC patients. From the marker side, PI3K and VIM were contributing the most to detection of CTCs with mesenchymal features (in comparison to SNAIL) in non-metastatic and metastatic BC patients, respectively. However, additional data are needed for more robust identification of markers for efficient detection of CTCs with mesenchymal features.

Microfluidics for single cell analysis

Cells have several internal molecules that are present in low amounts and any fluctuation in its number drives a change in cell behavior. These molecules present inside the cells are continuously fluctuating, thus producing noises in the intrinsic environment and thereby directly affecting the cellular behavior. Single-cell analysis using microfluidics is an important tool for monitoring cell behavior by analyzing internal molecules. Several gene circuits have been designed for this purpose that are labeled with fluorescence encoding genes for monitoring cell dynamics and behavior. We discuss herewith designed and fabricated microfluidics devices that are used for trapping and tracking cells under controlled environmental conditions. This chapter highlights microfluidics chip for monitoring cells to promote their basic understanding.

Simultaneous Quantification of Single-Cell Proteomes and Transcriptomes in Integrated Fluidic Circuits

Understanding the principles of gene regulation at single-cell resolution would require measurement and integration of multiple methods such as DNA mutation profiling, open chromatin profiling, RNA expression, protein quantification, and DNA methylation. Recent developments in single-cell multi-omic technologies have enabled integration of these modes in various combinations.With the advent of RNA expression and protein sequencing assay (REAP-seq), researchers can simultaneously analyze protein and gene expression within the same cell. In REAP-seq , cells are labeled with antibodies conjugated to unique DNA sequences. A barcode of 8 nucleotides can allow up to 65,536 unique barcodes for multiplex analysis of proteins, circumventing the limitations of fluorescence (~17 targets). Here, we describe the implementation of REAP-seq assay in the Fluidigm^® C1™ mRNA Seq HT (high-throughput) v2 system.

Flow Cytometry-Based Single Cell Analyses of Bacterial Adaptation to Intracellular Environments

Since decades, flow cytometry (FC) is a powerful technique to perform single cell analyses with high accuracy and throughput. Moreover, FC is the method of choice to study bacterial cell heterogeneity and complements single-cell imaging techniques. The complex experimental approaches for FC sample preparation and the subsequent FC adjustment and gating strategy demand careful considerations to be successful when analyzing complex microbial populations, especially when liberated populations of intracellular bacterial pathogens, or bacterial pathogens inside intact host cells are analyzed. Here, we provide a set of experimental protocols for FC sample preparation of (1) in vitro cultured bacterial cells, (2) liberated intracellular bacteria from host cells, or (3) preparation of intact infected phagocytic or epithelial cells commonly used as host cells in infection biology. Since sample preparation, cytometer adjustment, and gating strategy are essential for experimental success, we aim to provide our expertise to support application of FC by other researchers.

Molecularly assembled graphdiyne with atomic sites for ultrafast and real-time detection of nitric oxide in cell assays

Nitric oxide as a signal molecule participates in a variety of physiological and pathological processes but its real-time detection in cell assays still faces challenging because of the trace amount, short half-life and easy conversion to other substances. We report here a rational design by assembling highly π-conjugated and small capacitive gaphdiyne (GDY) with a coordination complex of hemin (HEM) into a molecularly assembled material of GDY/HEM to achieve ultrafast and real-time monitoring of nitric oxide in cell assays. GDY comprising alkynyl C atoms can hybridize with the HEM to enable strong π-π interaction and atomic dispersion of iron sites while avoiding the formation of catalytically inactive dimer for the HEM. These characteristics make the GDY/HEM an excellent sensing material towards nitric oxide, which has an ultrafast response time of 0.95 s, a low detection limit of 7 nM and long linear range up to 151.38 μΜ. The GDY/HEM realizes real-time monitoring nitric oxide released from cancer and normal cells, demonstrating its capability for cell analysis.

Intravital imaging and single cell transcriptomic analysis for engraftment of mesenchymal stem cells in an animal model of interstitial cystitis/bladder pain syndrome

Mesenchymal stem cell (MSC) therapy is a promising treatment for various intractable disorders including interstitial cystitis/bladder pain syndrome (IC/BPS). However, an analysis of fundamental characteristics driving in vivo behaviors of transplanted cells has not been performed, causing debates about rational use and efficacy of MSC therapy. Here, we implemented two-photon intravital imaging and single cell transcriptome analysis to evaluate the in vivo behaviors of engrafted multipotent MSCs (M-MSCs) derived from human embryonic stem cells (hESCs) in an acute IC/BPS animal model. Two-photon imaging analysis was performed to visualize the dynamic association between engrafted M-MSCs and bladder vasculature within live animals until 28 days after transplantation, demonstrating the progressive integration of transplanted M-MSCs into a perivascular-like structure. Single cell transcriptome analysis was performed in highly purified engrafted cells after a dual MACS-FACS sorting procedure and revealed expression changes in various pathways relating to pericyte cell adhesion and cellular stress. Particularly, FOS and cyclin dependent kinase-1 (CDK1) played a key role in modulating the migration, engraftment, and anti-inflammatory functions of M-MSCs, which determined their in vivo therapeutic potency. Collectively, this approach provides an overview of engrafted M-MSC behavior in vivo, which will advance our understanding of MSC therapeutic applications, efficacy, and safety.

Investigation of the robustness of Cupriavidus necator engineered strains during fed-batch cultures

It is of major interest to ensure stable and performant microbial bioprocesses, therefore maintaining high strain robustness is one of the major future challenges in industrial microbiology. Strain robustness can be defined as the persistence of genotypic and/or phenotypic traits in a system. In this work, robustness of an engineered strain is defined as plasmid expression stability, cultivability, membrane integrity and macroscopic cell behavior and was assessed in response to implementations of sugar feeding strategies (pulses and continuous) and two plasmid stabilization systems (kanamycin resistance and Post-Segregational Killing hok/sok). Fed-batch bioreactor cultures, relevant mode to reach high cell densities and higher cell generation number, were implemented to investigate the robustness of C. necator engineered strains. Host cells bore a recombinant plasmid encoding for a plasmid expression level monitoring system, based on eGFP fluorescence quantified by flow cytometry. We first showed that well-controlled continuous feeding in comparison to a pulse-based feeding allowed a better carbon use for protein synthesis (avoiding organic acid excretion), a lower heterogeneity of the plasmid expression and a lower cell permeabilization. Moreover, the plasmid stabilization system Post-Segregational Killing hok/sok, an autonomous system independent on external addition of compounds, showed the best ability to maintain plasmid expression level stability insuring a greater population homogeneity in the culture. Therefore, in the case of engineered C. necator, the PSK system hok/sok appears to be a relevant and an efficient alternative to antibiotic resistance system for selection pressure, especially, in the case of bioprocess development for economic and environmental reasons.

Measurement methods of single cell drug response

In the last decades, a wide multitude of research activity has been focused on the development of new drugs, and devoted to overcome the challenges of high cost and low efficiency in drug evaluation. The measurement of drug response at the single cell level is a quicker, more direct and more accurate way to reflect drug efficacy, which can shorten the drug development period and reduce research costs. Therefore, the single cell drug response (SCDR) measurement technology has aroused extensive attention from researchers, and has become a hot topic in the fields of drug research and cell biology. Recent years have seen the emergence of various SCDR measurement technologies that feature different working principles and different levels of measurement performance. To better examine, compare and summarize the characteristics and functions of these technologies, we select signal-to-noise ratio, throughput, content, invasion, and device complexity as the criteria to evaluate them from the drug efficacy perspective. This review aims to highlight sixteen kinds of SCDR measurement technologies, including patch-clamp technique, live-cell interferometry, capillary electrophoresis, secondary ion mass spectrometry, and more, and report widespread representative examples of SCDR measurement the recent approaches for over the past forty years. Based on their reaction principles, these technologies are classified into four categories: electrical, optical, electrochemical, and mass spectrometry, and a detailed comparison is made between them. After in-depth understanding of these technologies, it is expected to improve or integrate these technologies to propose better SCDR measurement strategies, and explore methods in new drug development and screening, as well as disease diagnosis and treatment.

Molecular allergology approach to allergic asthma

Allergic asthma is a frequently encountered and well described asthma phenotype. However, its precise mechanisms are less known. The tools for targeted selection of patients for an optimal response to intervention (prevention or treatment) are also lacking. Here we explore the potential of the molecular allergology approach to achieve a better understanding of allergic asthma mechanisms, a precise diagnosis and an optimal management of these patients.

Single-cell transcriptomic profiling reveals distinct mechanical responses between normal and diseased tendon progenitor cells

Regenerative medicine approaches utilizing stem cells offer a promising strategy to address tendinopathy, a class of common tendon disorders associated with pain and impaired function. Tendon progenitor cells (TPCs) are important in healing and maintaining tendon tissues. Here we provide a comprehensive single cell transcriptomic profiling of TPCs from three normal and three clinically classified tendinopathy samples in response to mechanical stimuli. Analysis reveals seven distinct TPC subpopulations including subsets that are responsive to the mechanical stress, highly clonogenic, and specialized in cytokine or growth factor expression. The single cell transcriptomic profiling of TPCs and their subsets serves as a foundation for further investigation into the pathology and molecular hallmarks of tendinopathy in mechanical stimulation conditions.

The electrode potential determines the yield coefficients of early-stage Geobacter sulfurreducens biofilm anodes

Geobacter sulfurreducens is the model for electroactive microorganisms (EAM). EAM can use solid state terminal electron acceptors (TEA) including anodes via extracellular electron transfer (EET). Yield coefficients relate the produced cell number or biomass to the oxidized substrate or the reduced TEA. These data are not yet sufficiently available for EAM growing at anodes. Thus, this study provides information about kinetics as well as yield coefficients of early-stage G. sulfurreducens biofilms using anodes as TEA at the potentials of -200 mV, 0 mV and +200 mV (vs. Ag/AgCl sat. KCl). The selected microorganism was therefore cultivated in single and double chamber batch reactors on graphite or AuPd anodes. Interestingly, whereas the lag time and maximum current density within 12 days of growth differed, the anode potential does not influence the coulombic efficiency and the formal potential of the EET, which remains constant for all the experiments at ~ -300 to -350 mV. We demonstrated for the first time that the anode potential has a strong influence on single cell yield coefficients which ranged from 2.69 × 10¹² cells mol_e-^-1 at -200 mV and 1.48 × 10¹² cells mol_e-^-1 at 0 mV to 2.58 × 10¹¹ cells mol_e-^-1 at +200 mV in single chamber reactors and from 1.15 × 10¹² cells mol_e-^-1 at -200 mV to 8.98× 10¹¹ cells mol_e-^-1 at 0 mV in double chamber reactors. This data can be useful for optimization and scaling-up of primary microbial electrochemical technologies.

Droplet Microfluidics with Reagent Micromixing for Investigating Intrinsic Platelet Functionality

Introduction

Precision mapping of the functional structure of platelet populations holds great promise for the identification of hyper-reactive subtypes that are likely to be disease drivers, having value in prognostics and as therapeutic targets. However, the ability to measure the intrinsic functional capacity of individual platelets is confounded by potent paracrine cross-talk, resulting in phenotypic remodeling of the entire platelet population, and in doing so obscuring the identity of hyper-reactive platelets.

Methods

To address this we have developed a droplet microfluidics strategy for single platelet confinement to exclude paracrine signaling. Consideration of the Poisson distribution was used for high throughput single platelet encapsulation and the preparation of minimal platelet collectives serving as digital models for understanding the role of hyper-reactive platelets coordinating system-level behavior by paracrine signaling. Platelets are retrieved from the droplets for phenotyping using standard flow cytometry. In addition, we have incorporated a staggered herringbone micromixing element for accurate agonist and antibody dispensing in droplets.

Results

The methodology was used for characterizing sensitivity distributions from healthy blood donors in response to convulxin (agonist of the GPVI receptor, the major platelet receptor for collagen). P-selectin exposure and α _IIb β ₃ integrin activation were used as analytical end-points to demonstrate the existence of hyper-reactive platelets that direct 20-fold gains in system level sensitivity.

Conclusions

The analytical workflow represents an enabling tool for the accurate classification of platelet subtypes and description of their underlying biology.

Supplementary information

The online version of this article (10.1007/s12195-020-00665-6) contains supplementary material, which is available to authorized users.

Rapid single cell evaluation of human disease and disorder targets using REVEAL: SingleCell™

BACKGROUND

Single-cell (sc) sequencing performs unbiased profiling of individual cells and enables evaluation of less prevalent cellular populations, often missed using bulk sequencing. However, the scale and the complexity of the sc datasets poses a great challenge in its utility and this problem is further exacerbated when working with larger datasets typically generated by consortium efforts. As the scale of single cell datasets continues to increase exponentially, there is an unmet technological need to develop database platforms that can evaluate key biological hypotheses by querying extensive single-cell datasets. Large single-cell datasets like Human Cell Atlas and COVID-19 cell atlas (collection of annotated sc datasets from various human organs) are excellent resources for profiling target genes involved in human diseases and disorders ranging from oncology, auto-immunity, as well as infectious diseases like COVID-19 caused by SARS-CoV-2 virus. SARS-CoV-2 infections have led to a worldwide pandemic with massive loss of lives, infections exceeding 7 million cases. The virus uses ACE2 and TMPRSS2 as key viral entry associated proteins expressed in human cells for infections. Evaluating the expression profile of key genes in large single-cell datasets can facilitate testing for diagnostics, therapeutics, and vaccine targets, as the world struggles to cope with the on-going spread of COVID-19 infections.

MAIN BODY

In this manuscript we describe REVEAL: SingleCell, which enables storage, retrieval, and rapid query of single-cell datasets inclusive of millions of cells. The array native database described here enables selecting and analyzing cells across multiple studies. Cells can be selected using individual metadata tags, more complex hierarchical ontology filtering, and gene expression threshold ranges, including co-expression of multiple genes. The tags on selected cells can be further evaluated for testing biological hypotheses. One such example includes identifying the most prevalent cell type annotation tag on returned cells. We used REVEAL: SingleCell to evaluate the expression of key SARS-CoV-2 entry associated genes, and queried the current database (2.2 Million cells, 32 projects) to obtain the results in < 60 s. We highlighted cells expressing COVID-19 associated genes are expressed on multiple tissue types, thus in part explains the multi-organ involvement in infected patients observed worldwide during the on-going COVID-19 pandemic.

CONCLUSION

In this paper, we introduce the REVEAL: SingleCell database that addresses immediate needs for SARS-CoV-2 research and has the potential to be used more broadly for many precision medicine applications. We used the REVEAL: SingleCell database as a reference to ask questions relevant to drug development and precision medicine regarding cell type and co-expression for genes that encode proteins necessary for SARS-CoV-2 to enter and reproduce in cells.

Flash-comet assay

In the present paper, we present a substantially revised protocol of the widely used SCGE assay performed under alkaline conditions. In our updated version of the comet assay, which we call the Flash-comet, LiOH is used instead of NaOH during the unwinding and electrophoresis. This allows a higher voltage during the electrophoresis (5 V/cm instead of 0.7 V/cm), making it possible to reduce the unwinding time from 20 to 40 to 2.5 min, and the electrophoresis time from 10 to 20 to 1 min. Still, the Flash-comet was found to detect DNA strand breaks and alkali-labile sites with a higher degree of sensitivity than the conventional protocol in cells that had been exposed to H₂O₂ or ionizing radiation. In order to prevent alkaline hydrolysis of DNA, the wash and lysis solutions have been modified in the Flash-comet protocol.•

By using an alkaline LiOH-based medium, the Flash-comet allows for much shorter times for both unwinding and electrophoresis than the conventional comet assay without compromising the sensitivity.

•

The reduced run-times of the unwinding and electrophoresis steps in the Flash-comet should also reduce the risk of laboratory-induced alkaline hydrolysis of DNA when evaluating the potential DNA-damaging effects of different types of xenobiotics.

Advances in Proximity Ligation in situ Hybridization (PLISH)

Understanding tissues in the context of development, maintenance and disease requires determining the molecular profiles of individual cells within their native in vivo spatial context. We developed a Proximity Ligation in situ Hybridization technology (PLISH) that enables quantitative measurement of single cell gene expression in intact tissues, which we have now updated. By recording spatial information for every profiled cell, PLISH enables retrospective mapping of distinct cell classes and inference of their in vivo interactions. PLISH has high sensitivity, specificity and signal to noise ratio. It is also rapid, scalable, and does not require expertise in molecular biology so it can be easily adopted by basic and clinical researchers.

Recovery of single source DNA profiles from mixtures by direct single cell subsampling and simplified micromanipulation

Deconvolution of forensic DNA mixtures into their individual component DNA (geno)types is of great investigative value, though often complex and difficult. Two-person mixtures comprising a major and minor contributor are often easily interpreted although, when the DNA ratio of the two individuals is approximately equal (~1:1), deconvolution and interpretation becomes much more difficult. To address this issue, a physical separation of individual-, two- or three- cell subsamples prior to autosomal STR analysis was performed using a simplified micromanipulation technique paired with a decreased reaction volume and increased cycle number PCR. Using this method, single and multiple buccal epithelial cells were collected from a 1:1 two-person mixture (i.e. from individual 'A' and 'B') and directly amplified, omitting standard DNA extraction and purification steps. Single cell subsamples resulted in partial single-source profiles for both contributors while, in accordance with expectations of a quasi-binomial sampling schema, two- and three-cell subsamples resulted in single source informative partial profiles of individual A and individual B as well as complete consensus profiles, and equally mixed 1:1 (2-cell subsamples) and 2:1 (3-cell subsamples) admixed profiles of individual A and B.This proof-of-concept approach shows promise in permitting the DNA deconvolution of mixed samples where the individual contributors are present in similar amounts that would otherwise be difficult to interpret, resulting in an increase in evidentiary value. The subsampling approach can be readily investigated for DNA casework applications without additional investment in costly, new equipment, requiring only a stereo microscope and a tungsten needle.

Low-dose DNA demethylating therapy induces reprogramming of diverse cancer-related pathways at the single-cell level

BACKGROUND

Epigenetic reprogramming using DNA demethylating drugs is a promising approach for cancer therapy, but its efficacy is highly dependent on the dosing regimen. Low-dose treatment for a prolonged period shows a remarkable therapeutic efficacy, despite its small demethylating effect. Here, we aimed to explore the mechanisms of how such low-dose treatment shows this remarkable efficacy by focusing on epigenetic reprograming at the single-cell level.

METHODS

Expression profiles in HCT116 cells treated with decitabine (DAC) were analyzed by single-cell RNA-sequencing (scRNA-seq). Functional consequences and DNA demethylation at the single-cell level were analyzed using cloned HCT116 cells after DAC treatment.

RESULTS

scRNA-seq revealed that DAC-treated cells had highly diverse expression profiles at the single-cell level, and tumor-suppressor genes, endogenous retroviruses, and interferon-stimulated genes were upregulated in random fractions of cells. DNA methylation analysis of cloned HCT116 cells revealed that, while only partial reduction of DNA methylation levels was observed in bulk cells, complete demethylation of specific cancer-related genes, such as cell cycle regulation, WNT pathway, p53 pathway, and TGF-β pathway, was observed, depending upon clones. Functionally, a clone with complete demethylation of CDKN2A (p16) had a larger fraction of cells with tetraploid than parental cells, indicating induction of cellular senescence due to normalization of cell cycle regulation.

CONCLUSIONS

Epigenetic reprogramming of specific cancer-related pathways at the single-cell level is likely to underlie the remarkable efficacy of low-dose DNA demethylating therapy.

Mouse single oocyte imaging by MALDI-TOF MS for lipidomics

Reproductive cells are a very special kind of material for the analysis. Depending on the species, their dimensions allow for the application of mass spectrometry imaging-based techniques to receive a reasonable data for interpretation of their condition without any additional sample preparation steps, except for typical sample preparation characteristic for IMS protocols. A comparison between lipid profiles of oocytes could answer the question of the overall quality of the cells in the function of time or conditions of storage. Even tiny differences in the lipid profiles, but still detectable by bioinformatic analysis, could be crucial for the estimation of the conditions of the cells in various stages of development or aging. In our study, MALDI-TOF/TOF MSI was used to analyze and visualize the single oocytes. We deposited the cells on the transparent indium-tin-oxide (ITO) glass and marked their positions, which allowed for the fast localization of the cells and precise laser targeting in the ion source. We also optimized the usage of different MALDI matrices and different approaches. The proposed way of measurement allows analyzing quite a significant quantity of oocytes in a reasonably short time. During the analysis, the lipid composition of the single cell was successfully estimated in a conventional usage of the MALDI ion source, and the localization of lipids was confirmed by imaging mass spectrometry (IMS) analysis. The observed quantity of the lipids allowed for the application of the LIFT™ technique to obtain MS/MS spectra sufficient for lipids' unambiguous identification. We hope that our idea of the oocyte analysis will help to elucidate chemical changes that accompany different processes in which oocytes are involved. There could be such fascinating phenomena as the oocyte maturation, changes in the lipid components during their storage, and much more.

ShapeMetrics: A userfriendly pipeline for 3D cell segmentation and spatial tissue analysis

The demand for single-cell level data is constantly increasing within life sciences. In order to meet this demand, robust cell segmentation methods that can tackle challenging in vivo tissues with complex morphology are required. However, currently available cell segmentation and volumetric analysis methods perform poorly on 3D images. Here, we generated ShapeMetrics, a MATLAB-based script that segments cells in 3D and, by performing unbiased clustering using a heatmap, separates the cells into subgroups according to their volumetric and morphological differences. The cells can be accurately segregated according to different biologically meaningful features such as cell ellipticity, longest axis, cell elongation, or the ratio between cell volume and surface area. Our machine learning based script enables dissection of a large amount of novel data from microscope images in addition to the traditional information based on fluorescent biomarkers. Furthermore, the cells in different subgroups can be spatially mapped back to their original locations in the tissue image to help elucidate their roles in their respective morphological contexts. In order to facilitate the transition from bulk analysis to single-cell level accuracy, we emphasize the user-friendliness of our method by providing detailed step-by-step instructions through the pipeline hence aiming to reach users with less experience in computational biology.

Using toponomics to characterize phenotypic diversity in alveolar macrophages from male mice treated with exogenous SP-A1

Background

We used the Toponome Imaging System (TIS) to identify “patterns of marker expression”, referred to here as combinatorial molecular phenotypes (CMPs) in alveolar macrophages (AM) in response to the innate immune molecule, SP-A1.

Methods

We compared 114 AM from male SP-A deficient mice. One group (n = 3) was treated with exogenous human surfactant protein A1 (hSP-A1) and the other with vehicle (n = 3). AM obtained by bronchoalveolar lavage were plated onto slides and analyzed using TIS to study the AM toponome, the spatial network of proteins within intact cells. With TIS, each slide is sequentially immunostained with multiple FITC-conjugated antibodies. Images are analyzed pixel-by-pixel identifying all of the proteins within each pixel, which are then designated as CMPs. CMPs represent organized protein clusters postulated to contribute to specific functions.

Results

1) We compared identical CMPs in KO and SP-A1 cells and found them to differ significantly (p = 0.0007). Similarities between pairs of markers in the two populations also differed significantly (p < 0.0001). 2) Focusing on the 20 most abundant CMPs for each cell, we developed a method to generate CMP “signatures” that characterized various groups of cells. Phenotypes were defined as cells exhibiting similar signatures of CMPs. i) AM were extremely diverse and each group contained cells with multiple phenotypes. ii) Among the 114 AM analyzed, no two cells were identical. iii) However, CMP signatures could distinguish among cell subpopulations within and between groups. iv) Some cell populations were enriched with SP-A1 treatment, some were more common without SP-A1, and some seemed not to be influenced by the presence of SP-A1. v) We also found that AM were more diverse in mice treated with SP-A1 compared to those treated with vehicle.

Conclusions

AM diversity is far more extensive than originally thought. The increased diversity of SP-A1-treated mice points to the possibility that SP-A1 enhances or activates several pathways in the AM to better prepare it for its innate immune functions and other functions shown previously to be affected by SP-A treatment. Future studies may identify key protein(s) responsible for CMP integrity and consequently for a given function, and target it for therapeutic purposes.

The effect of dust storm particles on single human lung cancer cells

Exposure to dust particles during dust storms can lead to respiratory problems, diseases, and even death. The effect of dust particles at the cellular level is poorly understood. In this study, we investigated the impact that dust storm particles (Montmorillonite) have on human lung epithelial cells (A549) at the single cell level. Using live-cell imaging, we continuously followed individual cells after exposure to a wide range of concentrations of dust particles. We monitored the growth trajectory of each cell including number and timing of divisions, interaction with the dust particles, as well as time and mechanism of cell death. We found that individual cells show different cellular fates (survival or death) even in response to the same dust concentration. Cells that died interacted with dust particles for longer times, and engulfed more dust particles, compared with surviving cells. While higher dust concentrations reduced viability in a dose-dependent manner, the effect on cell death was non-monotonic, with intermediate dust concentration leading to a larger fraction of dying cells compared to lower and higher concentrations. This non-monotonic relationship was explained by our findings that high dust concentrations inhibit cell proliferation. Using cellular morphological features, supported by immunoblots and proinflammatory cytokines, we determined that apoptosis is the dominant death mechanism at low dust concentrations, while higher dust concentrations activate necrosis. Similar single cell approaches can serve as a baseline for evaluating other aerosol types that will improve our understanding of the health-related consequences of exposure to dust storms.

Single-cell alternative splicing analysis reveals dominance of single transcript variant

Alternative splicing contributes to the diversity of gene products by producing multiple transcript variants from one gene. Previous studies have revealed highly variable splicing patterns in single cells, but there is still a controversy in the understanding of the simultaneous expression of multiple transcript variants. Here we show that the dominance of a single transcript variant is a common phenomenon in single cells. We analyzed several single-cell RNA sequencing datasets and observed consistent results. Our results demonstrate that single cells tend to express one major transcript variant of a gene, and the diversity of transcript variants in cell populations mainly results from the heterogeneity of splicing pattern in single cells.

Sample Preparation and Analysis of Single Cells Using High Performance MALDI FTICR Mass Spectrometry

Imaging mass spectrometry is a powerful technology that combines the molecular measurements of mass spectrometry with the spatial information inherent to microscopy. This unique combination of capabilities is ideally suited for the analysis of metabolites and lipids from single cells. This chapter describes a methodology for the sample preparation and analysis of single cells using high performance MALDI FTICR MS. Using this approach, we are able to generate profiles of lipid and metabolite expression from single cells that characterize cellular heterogeneity. This approach also enables the detection of variations in the expression profiles of lipids and metabolites induced by chemical stimulation of the cells. These results demonstrate that MALDI IMS provides an insightful view of lipid and metabolite expression useful in the characterization of a number of biological systems at the single cell level.

Botrytis cinerea response to pulsed light: Cultivability, physiological state, ultrastructure and growth ability on strawberry fruit

Botrytis cinerea causes postharvest spoilage in important crops such as strawberry and other berries. Pulsed light (PL) treatment could be an environmentally friendly postharvest alternative to synthetic fungicides in berries. Cultivability, physiological state, ultrastructure of Botrytis cinerea suspended in peptone water and irradiated with PL (fluence = 1.2 to 47.8 J/cm²) were investigated by using conventional plate count technique, flow cytometry analysis (FCM) and transmission electron microscopy. In addition, PL effect on B. cinerea development in artificially contaminated strawberries throughout storage at (5 ± 1) °C was evaluated. PL reduced fungus' ability to form colonies on agarized culture media. Survival curve fitted with the Weibullian model evidenced a wide distribution of conidia sensitivity to PL. FCM showed that most of irradiated conidia entered in a viable non-culturable state, although a subpopulation without esterase activity and compromised membranes and a subpopulation with active esterase and intact membranes were also detected. PL attacked multiple targets in B. cinerea. Ultrastructural changes varied with the dose and within the conidia population, supporting FCM results. Damage included plasmalemma detachment from cell wall, cytoplasm collapse, and vacuolization of cytoplasm, disruption of cell wall and plasmalemma with massive loss of cytoplasm and/or disruption of organelles. In strawberries artificially contaminated with B. cinerea, a 2-day delay on the onset of the infection and a lower incidence in PL-treated strawberries (11.9 and 23.9 J/cm²) compared to control (16-20%) up to 10 days of cold storage was observed. Results indicated that PL significantly reduces B. cinerea growth in peptone water and in inoculated strawberries. However, other preservation factor(s) in combination would be needed to increase PL action for a better control of this fungus.

Phospho-protein Analysis in Adherent Cells Using Flow Cytometry

Protein phosphorylation is one of the most important post-translational modifications, which acts as a reversible on or off switch for the activity of a large number of proteins. Analyzing the phosphorylation status of different proteins can reveal the alterations in the state of the cells in response to cellular damage, cancer and pharmaceutical drugs. Techniques such as mass spectrometry, radiolabeling, 2D-gel electrophoresis and western blotting are used to quantify protein phosphorylation. These assays can quantify phosphorylation in the bulk population of cells, however, flow cytometry can couple cell surface marker expression data with phosphorylation data to understand differential signaling in a sub-population within a heterogeneous population of cells. Our protocol describes the use of flow-cytometry for rapid and single cell-based quantification of intracellular phospho-protein with the help of anti-phospho protein specific antibody.

Concentration and distribution of silica nanoparticles in colon cancer cells assessed by synchrotron based X-ray techniques

The quantitative uptake of Silica nanoparticles (SiNPs), although representing an essential prerequisite for their theranostic use, is difficult to address and it is still not utterly investigated. In this study, we tested the uptake and toxicity of two different types of luminescent core-shell silica-PEG (polyethylene glycol) nanoparticles SiNP and their carboxylate analogues on human adenocarcinoma cell line LoVo. We assessed the intracellular spatial distribution and concentration of Si element in the cell by a state-of-the-art approach merging synchrotron-based X-ray techniques (XRFM) with scanning transmission X-Ray microscopy (STXM). The concentration maps of Si obtained reflect the distribution of the SiNPs. In addition, we calculated the number of SiNPs per volume unit in each single cell, quantitating the exact amount of conveyed particles. The absence of effects on proliferation and cell death was confirmed by viability assays, morphological analysis and cytofluorimetric evaluation of ROS content. The three-dimensional analysis of intracellular uptake of both types of nanoparticles (with different surface charge) was performed by confocal fluorescence microscopy, which showed a main localization in the cytosolic region with no sign of nuclear uptake.

Glioblastoma Multiforme heterogeneity profiling with solid-state micropores

Glioblastoma multiforme (GBM) is the most common and lethal type of brain cancer. It is characterized by widespread heterogeneity at the cellular and molecular levels. The detection of this heterogeneity is valuable for accurate diagnosis. Herein, solid-state 20 μm diameter micropore made in thin suspended silicon dioxide membrane is used as cell sensor device. The device relies on a cell's mechano-physical properties as an indicator to differentiate between the subtypes of GBM. A library of GBM cell lines (U251, U87, D54 EGFRviii, and G55) was created by measuring the differences in cell's micropore translocation properties from their distinct electrical profiles. Each GBM subtype has distinct phenotype and this was delineated in their cell translocation behaviors. The library was used to distinguish cells from samples of brain tumor patients. The micropore device accurately profiled GBM patient samples for cell subtypes by comparing data with the GBM library. The micropore approach is simple, can be implemented at low cost and can be used in the clinical setups and operation theaters to detect and identify GBM subtypes from patient samples.