Single-cell analysis tools for drug discovery and development

Circulating Tumor Cells as a Tool for Assessing Tumor Heterogeneity

Tumor heterogeneity is the major cause of failure in cancer prognosis and prediction. Accurately detecting heterogeneity for the development of biomarkers and the detection of the clones resistant to therapy is one of the main goals of contemporary medicine. Metastases belong to the natural history of cancer. The present review gives an overview on the origin of tumor heterogeneity. Recent progress has made it possible to isolate and characterize circulating tumor cells (CTCs), which are the drivers of the disease between the primary sites and metastatic foci. The most recent methods for characterizing CTCs are summarized and we discuss the power of CTC profiling for analyzing tumor heterogeneity in early and advanced diseases.

Single-Cell Protein Secretion Detection and Profiling

Secreted proteins play important roles in mediating various biological processes such as cell-cell communication, differentiation, migration, and homeostasis at the population or tissue level. Here, we review bioanalytical technologies and devices for detecting protein secretions from single cells. We begin by discussing conventional approaches followed by detailing the latest advances in microengineered systems for detecting single-cell protein secretions with an emphasis on multiplex measurement. These platforms include droplet microfluidics, micro-/nanowell-based assays, and microchamber-based assays, among which the advantages and limitations are compared. Microscale systems also enable the tracking of protein secretion dynamics in single cells, further empowering the study of the cell-cell communication network. Looking forward, we discuss the remaining challenges and future opportunities that will transform basic research of cellular secretion functions at the systems level and the clinical applications for immune monitoring and cancer treatment.

Single-Cell Receptor Quantification of an In Vitro Coculture Angiogenesis Model Reveals VEGFR, NRP1, Tie2, and PDGFR Regulation and Endothelial Heterogeneity

Angiogenesis, the formation of new blood vessels from pre-existing ones, is essential for both normal development and numerous pathologies. Systems biology has offered a unique approach to study angiogenesis by profiling tyrosine kinase receptors (RTKs) that regulate angiogenic processes and computationally modeling RTK signaling pathways. Historically, this systems biology approach has been applied on ex vivo angiogenesis assays, however, these assays are difficult to quantify and limited in their potential of temporal analysis. In this study, we adopted a simple two-dimensional angiogenesis assay comprised of human umbilical vein endothelial cells (HUVECs) and human dermal fibroblasts (HDFs) and examined temporal dynamics of a panel of six RTKs and cell heterogeneity up to 17 days. We observed ~2700 VEGFR1 (vascular endothelial growth factor receptor 1) per cell on 24-h-old cocultured HDF plasma membranes, which do not express VEGFR when cultured alone. We observed 4000–8100 VEGFR2 per cell on cocultured HUVEC plasma membranes throughout endothelial tube formation. We showed steady increase of platelet-derived growth factor receptors (PDGFRs) on cocultured HDF plasma membranes, and more interestingly, 1900–2900 PDGFRβ per plasma membrane were found on HUVECs within the first six hours of coculturing. These quantitative findings will offer us insights into molecular regulation during angiogenesis and help assess in vitro tube formation models and their physiological relevance.

Tools for Bioimaging Pancreatic β Cells in Diabetes

When diabetes is diagnosed, the majority of insulin-secreting pancreatic β cells are already dysfunctional or destroyed. This β cell dysfunction/destruction usually takes place over many years, making timely detection and clinical intervention difficult. For this reason, there is immense interest in developing tools to bioimage β cell mass and/or function noninvasively to facilitate early diagnosis of diabetes as well as to assist the development of novel antidiabetic therapies. Recent years have brought significant progress in β cell imaging that is now inching towards clinical applicability. We explore here the need to bioimage human β cells noninvasively in various types of diabetes, and we discuss current and emerging tools for bioimaging β cells. Further developments in this field are expected to facilitate β cell imaging in diabetes.

Application of single-cell sequencing in human cancer

Precision medicine is emerging as a cornerstone of future cancer care with the objective of providing targeted therapies based on the molecular phenotype of each individual patient. Traditional bulk-level molecular phenotyping of tumours leads to significant information loss, as the molecular profile represents an average phenotype over large numbers of cells, while cancer is a disease with inherent intra-tumour heterogeneity at the cellular level caused by several factors, including clonal evolution, tissue hierarchies, rare cells and dynamic cell states. Single-cell sequencing provides means to characterize heterogeneity in a large population of cells and opens up opportunity to determine key molecular properties that influence clinical outcomes, including prognosis and probability of treatment response. Single-cell sequencing methods are now reliable enough to be used in many research laboratories, and we are starting to see applications of these technologies for characterization of human primary cancer cells. In this review, we provide an overview of studies that have applied single-cell sequencing to characterize human cancers at the single-cell level, and we discuss some of the current challenges in the field.

Recent advances in single-cell analysis by mass spectrometry

Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail.

Advancing single-cell proteomics and metabolomics with microfluidic technologies

Recent advances in single-cell analysis have unraveled substantial heterogeneity among seemingly identical cells at genomic and transcriptomic levels. These discoveries have urged scientists to develop new tools that are capable of investigating single cells from a broader set of "omics". Proteomics and metabolomics, for instance, are of particular interest as they are closely correlated with a dynamic picture of cellular behaviors and phenotypic identities. The development of such tools requires highly efficient isolation and processing of a large number of individual cells, where techniques such as microfluidics are extremely useful. Here, we review the recent advances in single-cell proteomics and metabolomics, with a focus on microfluidics-based platforms. We highlight a vast array of emerging microfluidic formats for single-cell isolation and manipulation, and how the state-of-the-art analytical tools are coupled with such platforms for proteomic and metabolomic profiling.

A Fluorescence-Activated Single-Droplet Dispenser for High Accuracy Single-Droplet and Single-Cell Sorting and Dispensing

The ability to sort and dispense droplets accurately is essential to droplet-based single-cell analysis. Here, we describe a fluorescence-activated single-droplet dispenser (FASD) that is analogous to a conventional fluorescence-activated cell sorter, but sorts droplets containing single cells within an oil emulsion. The FASD system uses cytometric detection and electrohydrodynamic actuation-based single-droplet manipulation, allowing droplet isolation and dispensing with high efficiency and accuracy. The system is compatible with multiwell plates and can be integrated with existing microfluidic devices and large-scale screening systems. By enabling sorting based on single-cell reactions such as PCR, this platform will help expand the basis of cell sorting from mainly protein biomarkers to nucleic acid sequences and secreted biomolecules.

Multiplexed, Sequential Secretion Analysis of the Same Single Cells Reveals Distinct Effector Response Dynamics Dependent on the Initial Basal State

The effector response of immune cells dictated by an array of secreted proteins is a highly dynamic process, requiring sequential measurement of all relevant proteins from single cells. Herein, a microchip-based, 10-plexed, sequential secretion assay on the same single cells and at the scale of ≈5000 single cells measured simultaneously over 4 time points are shown. It is applied to investigating the time course of single human macrophage response to toll-like receptor 4 (TLR4) ligand lipopolysaccharide (LPS) and reveals four distinct activation modes for different proteins in single cells. Protein secretion dynamics classifies the cells into two major activation states dependent on the basal state of each cell. Single-cell RNA sequencing performed on the same samples at the matched time points further demonstrates the existence of two major activation states at the transcriptional level, which are enriched for translation versus inflammatory programs, respectively. These results show a cell-intrinsic heterogeneous response in a phenotypically homogeneous cell population. This work demonstrates the longitudinal tracking of protein secretion signature in thousands of single cells at multiple time points, providing dynamic information to better understand how individual immune cells react to pathogenic challenges over time and how they together constitute a population response.

Quantitative Phase Imaging Flow Cytometry for Ultra-Large-Scale Single-Cell Biophysical Phenotyping

Cellular biophysical properties are the effective label-free phenotypes indicative of differences in cell types, states, and functions. However, current biophysical phenotyping methods largely lack the throughput and specificity required in the majority of cell-based assays that involve large-scale single-cell characterization for inquiring the inherently complex heterogeneity in many biological systems. Further confounded by the lack of reported robust reproducibility and quality control, widespread adoption of single-cell biophysical phenotyping in mainstream cytometry remains elusive. To address this challenge, here we present a label-free imaging flow cytometer built upon a recently developed ultrafast quantitative phase imaging (QPI) technique, coined multi-ATOM, that enables label-free single-cell QPI, from which a multitude of subcellularly resolvable biophysical phenotypes can be parametrized, at an experimentally recorded throughput of >10,000 cells/s-a capability that is otherwise inaccessible in current QPI. With the aim to translate multi-ATOM into mainstream cytometry, we report robust system calibration and validation (from image acquisition to phenotyping reproducibility) and thus demonstrate its ability to establish high-dimensional single-cell biophysical phenotypic profiles at ultra-large-scale (>1,000,000 cells). Such a combination of throughput and content offers sufficiently high label-free statistical power to classify multiple human leukemic cell types at high accuracy (~92-97%). This system could substantiate the significance of high-throughput QPI flow cytometry in enabling next frontier in large-scale image-derived single-cell analysis applied in biological discovery and cost-effective clinical diagnostics. © 2019 International Society for Advancement of Cytometry.

Analysis of Single-Cell RNA-seq Data by Clustering Approaches

Background:

The recently developed single-cell RNA sequencing (scRNA-seq) has attracted a great amount of attention due to its capability to interrogate expression of individual cells, which is superior to traditional bulk cell sequencing that can only measure mean gene expression of a population of cells. scRNA-seq has been successfully applied in finding new cell subtypes. New computational challenges exist in the analysis of scRNA-seq data.

Objective:

We provide an overview of the features of different similarity calculation and clustering methods, in order to facilitate users to select methods that are suitable for their scRNA-seq. We would also like to show that feature selection methods are important to improve clustering performance.

Results:

We first described similarity measurement methods, followed by reviewing some new clustering methods, as well as their algorithmic details. This analysis revealed several new questions, including how to automatically estimate the number of clustering categories, how to discover novel subpopulation, and how to search for new marker genes by using feature selection methods.

Conclusion:

Without prior knowledge about the number of cell types, clustering or semisupervised learning methods are important tools for exploratory analysis of scRNA-seq data.</P>

Multiplexed profiling of single-cell extracellular vesicles secretion

Extracellular vesicles (EVs) are important intercellular mediators regulating health and diseases. Conventional methods for EV surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EV secretion. Herein, by using spatially patterned antibody barcodes, we realized multiplexed profiling of single-cell EV secretion from more than 1,000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to a deep understanding of previously undifferentiated single-cell heterogeneity underlying EV secretion. Notably, we observed that the decrement of certain EV phenotypes (e.g., CD63+EV) was associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EV secretion and cytokines secretion simultaneously from the same single cells to investigate the multidimensional spectrum of cellular communications, from which we resolved tiered functional subgroups with distinct secretion profiles by visualized clustering and principal component analysis. In particular, we found that different cell subgroups dominated EV secretion and cytokine secretion. The technology introduced here enables a comprehensive evaluation of EV secretion heterogeneity at single-cell level, which may become an indispensable tool to complement current single-cell analysis and EV research.

Fluorescence imaging-based methods for single-cell protein analysis

The quantity and activity of proteins in many biological systems exhibit prominent heterogeneities. Single-cell analytical methods can resolve subpopulations and dissect their unique signatures from heterogeneous samples, enabling a clarifying view of the biological process. Over the last 5 years, technologies for single-cell protein analysis have significantly advanced. In this article, we highlight a branch of those technology developments involving fluorescence-based approaches, with a focus on the methods that increase the ability to multiplex and enable dynamic measurements. We also analyze the limitations of these techniques and discuss current challenges in the field, with the hope that more transformative platforms can soon emerge.

Laser capture microdissection-targeted mass spectrometry: a method for multiplexed protein quantification within individual layers of the cerebral cortex

The mammalian neocortex is organized into layers distinguished by the size, packing density, and connectivity of their constituent neurons. Many neuropsychiatric illnesses are complex trait disorders with etiologic factors converging on neuronal protein networks. Cortical pathology of neuropsychiatric diseases, such as schizophrenia, is often restricted to, or more pronounced in, certain cortical layers, suggesting that genetic vulnerabilities manifest with laminar specificity. Thus, the ability to investigate cortical layer-specific protein levels in human postmortem brain is highly desirable. Here, we developed and validated a laser capture microdissection-mass spectrometry (LCM-MS) approach to quantify over 200 proteins in cortical layers 3 and 5 of two cohorts of human subjects as well as a monkey model of postmortem interval. LCM-MS was readily implementable and reliably identified protein patterns that differed between cortical layers 3 and 5. Our findings suggest that LCM-MS facilitates the precise quantification of proteins within individual cortical layers from human postmortem brain tissue, providing a powerful tool in the study of neuropsychiatric disease.

Single-Cell Screening of Tamoxifen Abundance and Effect Using Mass Spectrometry and Raman-Spectroscopy

Monitoring drug uptake, its metabolism, and response on the single-cell level is invaluable for sustaining drug discovery efforts. In this study, we show the possibility of accessing the information about the aforementioned processes at the single-cell level by monitoring the anticancer drug tamoxifen using live single-cell mass spectrometry (LSC-MS) and Raman spectroscopy. First, we explored whether Raman spectroscopy could be used as a label-free and nondestructive screening technique to identify and predict the drug response at the single-cell level. Then, a subset of the screened cells was isolated and analyzed by LSC-MS to measure tamoxifen and its metabolite, 4-Hydroxytamoxifen (4-OHT) in a highly selective, sensitive, and semiquantitative manner. Our results show the Raman spectral signature changed in response to tamoxifen treatment which allowed us to identify and predict the drug response. Tamoxifen and 4-OHT abundances quantified by LSC-MS suggested some heterogeneity among single-cells. A similar phenomenon was observed in the ratio of metabolized to unmetabolized tamoxifen across single-cells. Moreover, a correlation was found between tamoxifen and its metabolite, suggesting that the drug was up taken and metabolized by the cell. Finally, we found some potential correlations between Raman spectral intensities and tamoxifen abundance, or its metabolism, suggesting a possible relationship between the two signals. This study demonstrates for the first time the potential of using Raman spectroscopy and LSC-MS to investigate pharmacokinetics at the single-cell level.

Pushing the limits of detection for proteins secreted from single cells using quantum dots

Single cell analysis methods are increasingly being utilized to investigate how individual cells process information and respond to diverse stimuli. Soluble proteins play a critical role in controlling cell populations and tissues, but directly monitoring secretion is technically challenging. Microfabricated well arrays have been developed to assess secretion at the single cell level, but these systems are limited by low detection sensitivity. Semiconductor quantum dots (QD) exhibit remarkably bright and photostable luminescence signal, but to date they have not been evaluated in single cell secretion studies using microfabricated well arrays. Here, we used QDs in a sandwich immunoassay to detect secretion of the soluble cytokine tumor necrosis factor-α (TNF-α) from single cells. To enhance detection sensitivity, we employed two different strategies. First, we used a unique single QD imaging approach, which provided a detection threshold (180 attomolar) that was >100-fold lower than previously reported results using QDs. We also amplified QD binding to each captured TNF-α molecule using the bioorthogonal cycloaddition reaction between trans-cyclooctene and tetrazine, which further lowered detection threshold to 60 attomolar. This is 6 orders of magnitude more sensitive than organic fluorophores that have been used for single cell secretion studies, and far surpasses single molecule resolution within sub-picoliter microwells that are used to assess single cell secretion. Finally, single cell secretion studies were performed using phorbol 12-myristate 13-acetate (PMA) differentiated and lipopolysaccharide (LPS) activated U-937 cells. TNF-α secretion was detected from 3-fold more single cells using the QD-based method in comparison to rhodamine, which was accomplished by extending sensitivity into the range of ∼2 to 10 000 molecules captured per microwell. In future work, we will apply this technique to assess immune cell secretion dynamics under diverse stimuli and disease settings. We will also incorporate multiplexing capabilities to evaluate the secretome at the resolution of single molecules.

Engineering and Design of Chimeric Antigen Receptors

T cells engineered with chimeric antigen receptors (CARs) have emerged as a potent new class of therapeutics for cancer, based on their remarkable potency in blood cancers. Since the first clinical reports of their efficacy emerged 7 years ago, investigators have focused on the mechanisms and properties that make CARs effective or toxic, and their effects on T cell biology. Novel CAR designs coupled with improvements in gene transfer technology, incorporating advances in gene editing, have the potential to increase access to engineered cell therapies, as well as improve their potency in solid tumors.

Combined Numerical and Experimental Investigation of Localized Electroporation-Based Cell Transfection and Sampling

Localized electroporation has evolved as an effective technology for the delivery of foreign molecules into cells while preserving their viability. Consequently, this technique has potential applications in sampling the contents of live cells and the temporal assessment of cellular states at the single-cell level. Although there have been numerous experimental reports on localized electroporation-based delivery, a lack of a mechanistic understanding of the process hinders its implementation in sampling. In this work, we develop a multiphysics model that predicts the transport of molecules into and out of the cell during localized electroporation. Based on the model predictions, we optimize experimental parameters such as buffer conditions, electric field strength, cell confluency, and density of nanochannels in the substrate for successful delivery and sampling via localized electroporation. We also identify that cell membrane tension plays a crucial role in enhancing both the amount and the uniformity of molecular transport, particularly for macromolecules. We qualitatively validate the model predictions on a localized electroporation platform by delivering large molecules (bovine serum albumin and mCherry-encoding plasmid) and by sampling an exogeneous protein (tdTomato) in an engineered cell line.

Coupled Single-Cell CRISPR Screening and Epigenomic Profiling Reveals Causal Gene Regulatory Networks

Here, we present Perturb-ATAC, a method that combines multiplexed CRISPR interference or knockout with genome-wide chromatin accessibility profiling in single cells based on the simultaneous detection of CRISPR guide RNAs and open chromatin sites by assay of transposase-accessible chromatin with sequencing (ATAC-seq). We applied Perturb-ATAC to transcription factors (TFs), chromatin-modifying factors, and noncoding RNAs (ncRNAs) in ∼4,300 single cells, encompassing more than 63 genotype-phenotype relationships. Perturb-ATAC in human B lymphocytes uncovered regulators of chromatin accessibility, TF occupancy, and nucleosome positioning and identified a hierarchy of TFs that govern B cell state, variation, and disease-associated cis-regulatory elements. Perturb-ATAC in primary human epidermal cells revealed three sequential modules of cis-elements that specify keratinocyte fate. Combinatorial deletion of all pairs of these TFs uncovered their epistatic relationships and highlighted genomic co-localization as a basis for synergistic interactions. Thus, Perturb-ATAC is a powerful strategy to dissect gene regulatory networks in development and disease.

Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis

In the proteomic and genomic era, lung cancer researchers are increasingly under challenge with traditional protein analyzing tools. High output, multiplexed analytical procedures are in demand for disclosing the post-translational modification, molecular interactions and signaling pathways of proteins precisely, specifically, dynamically and systematically, as well as for identifying novel proteins and their functions. This could be better realized by single-cell proteomic methods than conventional proteomic methods. Using single-cell proteomic tools including flow cytometry, mass cytometry, microfluidics and chip technologies, chemical cytometry, single-cell western blotting, the quantity and functions of proteins are analyzed simultaneously. Aside from deciphering disease mechanisms, single-cell proteomic techniques facilitate the identification and screening of biomarkers, molecular targets and promising compounds as well. This review summarized single-cell proteomic tools and their use in lung cancer.

Profiling Single Cancer Cells with Volatolomics Approach

Single-cell analysis is a rapidly evolving to characterize molecular information at the individual cell level. Here, we present a new approach with the potential to overcome several key challenges facing the currently available techniques. The approach is based on the identification of volatile organic compounds (VOCs), viz. organic compounds having relatively high vapor pressure, emitted to the cell's headspace. This concept is demonstrated using lung cancer cells with various p53 genetic status and normal lung cells. The VOCs were analyzed by gas chromatography combined with mass spectrometry. Among hundreds of detected compounds, 18 VOCs showed significant changes in their concentration levels in tumor cells versus control. The composition of these VOCs was found to depend, also, on the sub-molecular structure of the p53 genetic status. Analyzing the VOCs offers a complementary way of querying the molecular mechanisms of cancer as well as of developing new generation(s) of biomedical approaches for personalized screening and diagnosis.

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Measurement of VOCs was achieved at the single-cell level

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Genetic changes influence the emitted volatiles of single and bulk cancer cells

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Single-cell VOC analysis measures population heterogeneity in initial stage of tumors

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Volatolomics research can promote non-invasive, simple, and cost-effective diagnostics

Evaluating nanomedicine with microfluidics

Nanomedicines are engineered nanoscale structures that have an extensive range of application in the diagnosis and therapy of many diseases. Despite the rapid progress in and tremendous potential of nanomedicines, their clinical translational process is still slow, owing to the difficulty in understanding, evaluating, and predicting their behavior in complex living organisms. Microfluidic techniques offer a promising way to resolve these challenges. Carefully designed microfluidic chips enable in vivo microenvironment simulation and high-throughput analysis, thus providing robust platforms for nanomedicine evaluation. Here, we summarize the recent developments and achievements in microfluidic methods for nanomedicine evaluation, categorized into four sections based on their target systems: single cell, multicellular system, organ, and organism levels. Finally, we provide our perspectives on the challenges and future directions of microfluidics-based nanomedicine evaluation.

Effective Soil Extraction Method for Cultivating Previously Uncultured Soil Bacteria

Here, a new medium, named intensive soil extract medium (ISEM), based on new soil extract (NSE) using 80% methanol, was used to efficiently isolate previously uncultured bacteria and new taxonomic candidates, which accounted for 49% and 55% of the total isolates examined (n = 258), respectively. The new isolates were affiliated with seven phyla (Proteobacteria, Acidobacteria, Firmicutes, Actinobacteria, Verrucomicrobia, Planctomycetes, and Bacteroidetes). The result of chemical analysis showed that NSE included more diverse components of low-molecular-weight organic substances than two conventional soil extracts made using distilled water. Cultivation of previously uncultured bacteria is expected to extend knowledge through the discovery of new phenotypic, physiological, and functional properties and even roles of unknown genes.IMPORTANCE Both metagenomics and single-cell sequencing can detect unknown genes from uncultured microbial strains in environments, and either method may find the significant potential metabolites and roles of these strains. However, such gene/genome-based techniques do not allow detailed investigations that are possible with cultures. To solve this problem, various approaches for cultivation of uncultured bacteria have been developed, but there are still difficulties in maintaining pure cultures by subculture.

Mass synaptometry: High-dimensional multi parametric assay for single synapses

BACKGROUND

Synaptic alterations, especially presynaptic changes, are cardinal features of neurodegenerative diseases and strongly correlate with cognitive decline.

NEW METHOD

We report "Mass Synaptometry" for the high-dimensional analysis of individual human synaptosomes, enriched nerve terminals from brain. This method was adapted from cytometry by time-of-flight mass spectrometry (CyTOF), which is commonly used for single-cell analysis of immune and blood cells.

RESULT

Here we overcome challenges for single synapse analysis by optimizing synaptosome preparations, generating a 'SynTOF panel,' recalibrating acquisition settings, and applying computational analyses. Through the analysis of 390,000 individual synaptosomes, we also provide proof-of principle validation by characterizing changes in synaptic diversity in Lewy Body Disease (LBD), Alzheimer's disease and normal brain.

COMPARISON WITH EXISTING METHOD(S)

Current imaging methods to study synapses in humans are capable of analyzing a limited number of synapses, and conventional flow cytometric techniques are typically restricted to fewer than 6 parameters. Our method allows for the simultaneous detection of 34 parameters from tens of thousands of individual synapses.

CONCLUSION

We applied Mass Synaptometry to analyze 34 parameters simultaneously on more than 390,000 synaptosomes from 13 human brain samples. This new approach revealed regional and disease-specific changes in synaptic phenotypes, including validation of this method with the expected changes in the molecular composition of striatal dopaminergic synapses in Lewy body disease and Alzheimer's disease. Mass synaptometry enables highly parallel molecular profiling of individual synaptic terminals.

Nano-plasmonics and electronics co-integration in CMOS enabling a pill-sized multiplexed fluorescence microarray system

The ultra-miniaturization of massively multiplexed fluorescence-based bio-molecular sensing systems for proteins and nucleic acids into a chip-scale form, small enough to fit inside a pill (∼ 0.1cm3), can revolutionize sensing modalities in-vitro and in-vivo. Prior miniaturization techniques have been limited to focusing on traditional optical components (multiple filter sets, lenses, photo-detectors, etc.) arranged in new packaging systems. Here, we report a method that eliminates all external optics and miniaturizes an entire multiplexed fluorescence system into a 2 × 1 mm2 chip through co-integration for the first time of massively scalable nano-plasmonic multi-functional optical elements and electronic processing circuitry realized in an industry standard complementary-metal-oxide semiconductor (CMOS) foundry process with absolutely 'no change' in fabrication or processing. The implemented nano-waveguide based filters operating in the visible and near-IR realized with the embedded sub-wavelength multi-layer copper-based electronic interconnects inside the chip show for the first time a sub-wavelength surface plasmon polariton mode inside CMOS. This is the principle behind the angle-insensitive nature of the filtering that operates in the presence of uncollimated and scattering environments, enabling the first optics-free 96-sensor CMOS fluorescence sensing system. The chip demonstrates the surface sensitivity of zeptomoles of quantum dot-based labels, and volume sensitivities of ∼ 100 fM for nucleic acids and ∼ 5 pM for proteins that are comparable to, if not better, than commercial fluorescence readers. The ability to integrate multi-functional nano-optical structures in a commercial CMOS process, along with all the complex electronics, can have a transformative impact and enable a new class of miniaturized and scalable chip-sized optical sensors.

Current Trends of Microfluidic Single-Cell Technologies

The investigation of human disease mechanisms is difficult due to the heterogeneity in gene expression and the physiological state of cells in a given population. In comparison to bulk cell measurements, single-cell measurement technologies can provide a better understanding of the interactions among molecules, organelles, cells, and the microenvironment, which can aid in the development of therapeutics and diagnostic tools. In recent years, single-cell technologies have become increasingly robust and accessible, although limitations exist. In this review, we describe the recent advances in single-cell technologies and their applications in single-cell manipulation, diagnosis, and therapeutics development.

A Chemical Approach for Profiling Intracellular AKT Signaling Dynamics from Single Cells

We present here a novel chemical method to continuously analyze intracellular AKT signaling activities at single-cell resolution, without genetic manipulations. A pair of cyclic peptide-based fluorescent probes were developed to recognize the phosphorylated Ser474 site and a distal epitope on AKT. A Förster resonance energy transfer signal is generated upon concurrent binding of the two probes onto the same AKT protein, which is contingent upon the Ser474 phosphorylation. Intracellular delivery of the probes enabled dynamic measurements of the AKT signaling activities. We further implemented this detection strategy on a microwell single-cell platform, and interrogated the AKT signaling dynamics in a human glioblastoma cell line. We resolved unique features of the single-cell signaling dynamics following different perturbations. Our study provided the first example of monitoring the temporal evolution of cellular signaling heterogeneities and unveiled biological information that was inaccessible to other methods.

Systems Pharmacology: Defining the Interactions of Drug Combinations

The majority of diseases are associated with alterations in multiple molecular pathways and complex interactions at the cellular and organ levels. Single-target monotherapies therefore have intrinsic limitations with respect to their maximum therapeutic benefits. The potential of combination drug therapies has received interest for the treatment of many diseases and is well established in some areas, such as oncology. Combination drug treatments may allow us to identify synergistic drug effects, reduce adverse drug reactions, and address variability in disease characteristics between patients. Identification of combination therapies remains challenging. We discuss current state-of-the-art systems pharmacology approaches to enable rational identification of combination therapies. These approaches, which include characterization of mechanisms of disease and drug action at a systems level, can enable understanding of drug interactions at the molecular, cellular, physiological, and organismal levels. Such multiscale understanding can enable precision medicine by promoting the rational development of combination therapy at the level of individual patients for many diseases.

Simultaneous Assay of Oxygen-Dependent Cytotoxicity and Genotoxicity of Anticancer Drugs on an Integrated Microchip

Oxygen deprivation is a common feature in a variety of cancer tissues and associated with tumor progression, acquisition of antiapoptotic potential, and clinical therapeutic resistance. Thus, great interest has been aroused to develop new platforms or approaches of activity assays to impact on the hypoxic microenvironment and oxygen-dependent drug responses to improve the productivity of new drug discovery. In this study, an integrated microsystem is established to combine the cytotoxic and genotoxic tests together for continuous multiple measurements under mimicking hypoxic tumor microenvironment. We fabricated a double-layer chip device by combining a single-cell-arrayed agarose layer with a microfluidics-based oxygen gradient-generating layer using a PDMS membrane. Using tirapazamine (TPZ) and blemycin (BLM) as model anticancer drugs, we demonstrated its application and performance in single cell loading, cell cultivation, and subsequent drug treatment as well as in situ analysis of oxygen-dependent cytotoxicity and genotoxicity of anticancer drugs. The results demonstrated the opposite oxygen-dependent toxicity of TPZ and BLM, which also indicated that the formation of DNA breaks is related with cell apoptosis. Compared with the traditional assays, this device takes advantage of microfluidic phenomena to generate various oxygen concentrations while exhibiting the combinatorial diversities achieved by the single cell microarray, offering a powerful tool to study single cell behaviors and responses under different oxygen conditions with desired high-content and high-throughput capabilities.

Microfluidic and Paper-Based Devices for Disease Detection and Diagnostic Research

Recent developments in microfluidic devices, nanoparticle chemistry, fluorescent microscopy, and biochemical techniques such as genetic identification and antibody capture have provided easier and more sensitive platforms for detecting and diagnosing diseases as well as providing new fundamental insight into disease progression. These advancements have led to the development of new technology and assays capable of easy and early detection of pathogenicity as well as the enhancement of the drug discovery and development pipeline. While some studies have focused on treatment, many of these technologies have found initial success in laboratories as a precursor for clinical applications. This review highlights the current and future progress of microfluidic techniques geared toward the timely and inexpensive diagnosis of disease including technologies aimed at high-throughput single cell analysis for drug development. It also summarizes novel microfluidic approaches to characterize fundamental cellular behavior and heterogeneity.

Experimental Considerations for Single-Cell RNA Sequencing Approaches

Single-cell transcriptomic technologies have emerged as powerful tools to explore cellular heterogeneity at the resolution of individual cells. Previous scientific knowledge in cell biology is largely limited to data generated by bulk profiling methods, which only provide averaged read-outs that generally mask cellular heterogeneity. This averaged approach is particularly problematic when the biological effect of interest is limited to only a subpopulation of cells such as stem/progenitor cells within a given tissue, or immune cell subsets infiltrating a tumor. Great advances in single-cell RNA sequencing (scRNAseq) enabled scientists to overcome this limitation and allow for in depth interrogation of previously unexplored rare cell types. Due to the high sensitivity of scRNAseq, adequate attention must be put into experimental setup and execution. Careful handling and processing of cells for scRNAseq is critical to preserve the native expression profile that will ensure meaningful analysis and conclusions. Here, we delineate the individual steps of a typical single-cell analysis workflow from tissue procurement, cell preparation, to platform selection and data analysis, and we discuss critical challenges in each of these steps, which will serve as a helpful guide to navigate the complex field of single-cell sequencing.

Highly Multiplexed Single-Cell Protein Profiling with Large-Scale Convertible DNA-Antibody Barcoded Arrays

Highly multiplexed detection of proteins secreted by single cells is always challenging. Herein, a multiplexed in situ tagging technique based on single-stranded DNA encoded microbead arrays and multicolor successive imaging for assaying single-cell secreted proteins with high throughput and high sensitivity is presented. This technology is demonstrated to be capable of increasing the multiplexity exponentially. Upon integration with polydimethylsiloxane microwells, this platform is applied to detect ten immune effector proteins from differentiated single macrophages stimulated with lipopolysaccharide. Significant heterogeneity is observed when the derived human primary macrophages are analyzed. This versatile technology is expected to open new opportunities in systems biology, immune regulation studies, signaling analysis, and molecular diagnostics.

Paving the way to single-molecule protein sequencing

Proteins are major building blocks of life. The protein content of a cell and an organism provides key information for the understanding of biological processes and disease. Despite the importance of protein analysis, only a handful of techniques are available to determine protein sequences, and these methods face limitations, for example, requiring a sizable amount of sample. Single-molecule techniques would revolutionize proteomics research, providing ultimate sensitivity for the detection of low-abundance proteins and the realization of single-cell proteomics. In recent years, novel single-molecule protein sequencing schemes that use fluorescence, tunnelling currents and nanopores have been proposed. Here, we present a review of these approaches, together with the first experimental efforts towards their realization. We discuss their advantages and drawbacks, and present our perspective on the development of single-molecule protein sequencing techniques.

Organoids for Drug Discovery and Personalized Medicine

A wide variety of organs are in a dynamic state, continuously undergoing renewal as a result of constant growth and differentiation. Stem cells are required during these dynamic events for continuous tissue maintenance within the organs. In a steady state of production and loss of cells within these tissues, new cells are constantly formed by differentiation from stem cells. Today, organoids derived from either adult stem cells or pluripotent stem cells can be grown to resemble various organs. As they are similar to their original organs, organoids hold great promise for use in medical research and the development of new treatments. Furthermore, they have already been utilized in the clinic, enabling personalized medicine for inflammatory bowel disease. In this review, I provide an update on current organoid technology and summarize the application of organoids in basic research, disease modeling, drug development, personalized treatment, and regenerative medicine.

A coming era of precision diagnostics based on nano-assisted mass spectrometry

Precision diagnostics relies on omic analysis by mass spectrometry to overcome the limitation in accuracy by an individual biomarker, due to the complex nature of diseases. Recent development in nanotechnology markedly enhanced sample treatment and detection efficiency of this method. Herein, we foresee a coming era of precision diagnostics based on nano-assisted mass spectrometry. Some important progress in the field includes detection of (1) nucleic acids for genetic analysis; (2) proteins/peptides for proteomic analysis; and (3) small molecules for metabolic analysis. We anticipate that this review will be a reminder for both young and experienced researchers about the future of diagnostics and call for attention worldwide.

The Making of a PreCancer Atlas: Promises, Challenges, and Opportunities

Many cancers evolve from benign precancerous lesions and have a natural history of progression that provides a window of opportunity for intervention. The biological mechanisms underlying this evolutionary trajectory can only be truly understood through an extensive characterization of the molecular, cellular, and non-cellular properties of premalignant and malignant tumors, and must also recognize how the microenvironment (stromal cells, immune cells, and other types of cells) contributes to this evolution. We describe here the need to develop comprehensive molecular and cellular atlases for organ-specific premalignant lesions while capturing the spatial, structural, and functional changes over time that will provide a greater understanding of how premalignancy transitions to malignancy. The PreCancer Atlas (PCA) initiative, described in this Opinion, will address this need and aims to overcome the many challenges that currently plague the field. The hope is that PCAs will lead to the development of effective and timely interventions to prevent the development of invasive cancers.

Design and Application of Sensors for Chemical Cytometry

The bulk cell population response to a stimulus, be it a growth factor or a cytotoxic agent, neglects the cell-to-cell variability that can serve as a friend or as a foe in human biology. Biochemical variations among closely related cells furnish the basis for the adaptability of the immune system but also act as the root cause of resistance to chemotherapy by tumors. Consequently, the ability to probe for the presence of key biochemical variables at the single-cell level is now recognized to be of significant biological and biomedical impact. Chemical cytometry has emerged as an ultrasensitive single-cell platform with the flexibility to measure an array of cellular components, ranging from metabolite concentrations to enzyme activities. We briefly review the various chemical cytometry strategies, including recent advances in reporter design, probe and metabolite separation, and detection instrumentation. We also describe strategies for improving intracellular delivery, biochemical specificity, metabolic stability, and detection sensitivity of probes. Recent applications of these strategies to small molecules, lipids, proteins, and other analytes are discussed. Finally, we assess the current scope and limitations of chemical cytometry and discuss areas for future development to meet the needs of single-cell research.

Characterizing Glioblastoma Heterogeneity via Single-Cell Receptor Quantification

Dysregulation of tyrosine kinase receptor (RTK) signaling pathways play important roles in glioblastoma (GBM). However, therapies targeting these signaling pathways have not been successful, partially because of drug resistance. Increasing evidence suggests that tumor heterogeneity, more specifically, GBM-associated stem and endothelial cell heterogeneity, may contribute to drug resistance. In this perspective article, we introduce a high-throughput, quantitative approach to profile plasma membrane RTKs on single cells. First, we review the roles of RTKs in cancer. Then, we discuss the sources of cell heterogeneity in GBM, providing context to the key cells directing resistance to drugs. Finally, we present our provisionally patented qFlow cytometry approach, and report results of a "proof of concept" patient-derived xenograft GBM study.

Optimization of a Density Gradient Centrifugation Protocol for Isolation of Peripheral Blood Mononuclear Cells

Objective: Peripheral blood mononuclear cells (PBMC) are extremely important in the body’s immune response. Their isolation represents a major step in many immunological experiments. In this two phase study, we aimed to establish an optimum protocol for PBMC isolation by density-gradient centrifugation.

Methods: During Phase-1, we compared two commercially available PBMC isolation protocols, Stemcell Technologies (ST) and Miltenyi Biotec (MB), in terms of PBMC recovery and purity. Twelve blood samples were assigned to each protocol. Each sample was divided in three subsamples of 1ml, 2ml and 3ml in order to assess the influence of blood sample volume on isolation performance. During Phase-2, a hybrid protocol was similarly tested, processing six blood samples. Additionally, we performed a flow cytometric analysis using an Annexin-V/Propidium-Iodide viability staining protocol.

Results: Phase-1 results showed that, for all subsample volumes, ST had superior PBMC recovery (mean values: 56%, 80% and 87%, respectively) compared to MB (mean values: 39%, 54% and 43%, respectively). However, platelet removal was significantly higher for MB (mean value of 96.8%) than for ST (mean value of 75.2%). Regarding granulocyte/erythrocyte contamination, both protocols performed similarly, yielding high purity PBMC (mean values: 97.3% for ST and 95.8% for MB). During Phase-2, our hybrid protocol yielded comparable results to MB, with an average viability of 89.4% for lymphocytes and 16.9% for monocytes.

Conclusions: ST yields higher cell recovery rates and MB excels at platelet removal, while the hybrid protocol is highly similar to MB. Both cell recovery and viability increase with blood sample volume.

Bioinformatics and Translation Elongation

Codon usage depends on mutation bias, tRNA-mediated selection, and the need for high efficiency and accuracy in translation. One codon in a synonymous codon family is often strongly over-used, especially in highly expressed genes, which often leads to a high dN/dS ratio because dS is very small. Many different codon usage indices have been proposed to measure codon usage and codon adaptation. Sense codon could be misread by release factors and stop codons misread by tRNAs, which also contribute to codon usage in rare cases. This chapter outlines the conceptual framework on codon evolution, illustrates codon-specific and gene-specific codon usage indices, and presents their applications. A new index for codon adaptation that accounts for background mutation bias (Index of Translation Elongation) is presented and contrasted with codon adaptation index (CAI) which does not consider background mutation bias. They are used to re-analyze data from a recent paper claiming that translation elongation efficiency matters little in protein production. The reanalysis disproves the claim.

Counting Proteins in Single Cells with Addressable Droplet Microarrays

Often cellular behavior and cellular responses are analyzed at the population level where the responses of many cells are pooled together as an average result masking the rich single cell behavior within a complex population. Single cell protein detection and quantification technologies have made a remarkable impact in recent years. Here we describe a practical and flexible single cell analysis platform based on addressable droplet microarrays. This study describes how the absolute copy numbers of target proteins may be measured with single cell resolution. The tumor suppressor p53 is the most commonly mutated gene in human cancer, with more than 50% of total cancer cases exhibiting a non-healthy p53 expression pattern. The protocol describes steps to create 10 nL droplets within which single human cancer cells are isolated and the copy number of p53 protein is measured with single molecule resolution to precisely determine the variability in expression. The method may be applied to any cell type including primary material to determine the absolute copy number of any target proteins of interest.

Label-Free Optofluidic Nanobiosensor Enables Real-Time Analysis of Single-Cell Cytokine Secretion

Single-cell analysis of cytokine secretion is essential to understand the heterogeneity of cellular functionalities and develop novel therapies for multiple diseases. Unraveling the dynamic secretion process at single-cell resolution reveals the real-time functional status of individual cells. Fluorescent and colorimetric-based methodologies require tedious molecular labeling that brings inevitable interferences with cell integrity and compromises the temporal resolution. An innovative label-free optofluidic nanoplasmonic biosensor is introduced for single-cell analysis in real time. The nanobiosensor incorporates a novel design of a multifunctional microfluidic system with small volume microchamber and regulation channels for reliable monitoring of cytokine secretion from individual cells for hours. Different interleukin-2 secretion profiles are detected and distinguished from single lymphoma cells. The sensor configuration combined with optical spectroscopic imaging further allows us to determine the spatial single-cell secretion fingerprints in real time. This new biosensor system is anticipated to be a powerful tool to characterize single-cell signaling for basic and clinical research.

Translating GWAS Findings to Novel Therapeutic Targets for Coronary Artery Disease

The success of genome-wide association studies (GWAS) has significantly advanced our understanding of the etiology of coronary artery disease (CAD) and opens new opportunities to reinvigorate the stalling CAD drug development. However, there exists remarkable disconnection between the CAD GWAS findings and commercialized drugs. While this could implicate major untapped translational and therapeutic potentials in CAD GWAS, it also brings forward extensive technical challenges. In this review we summarize the motivation to leverage GWAS for drug discovery, outline the critical bottlenecks in the field, and highlight several promising strategies such as functional genomics and network-based approaches to enhance the translational value of CAD GWAS findings in driving novel therapeutics

Opportunities and Challenges in Implementation of Multiparameter Single Cell Analysis Platforms for Clinical Translation

The high-content interrogation of single cells with platforms optimized for the multiparameter characterization of cells in liquid and solid biopsy samples can enable characterization of heterogeneous populations of cells ex vivo. Doing so will advance the diagnosis, prognosis, and treatment of cancer and other diseases. However, it is important to understand the unique issues in resolving heterogeneity and variability at the single cell level before navigating the validation and regulatory requirements in order for these technologies to impact patient care. Since 2013, leading experts representing industry, academia, and government have been brought together as part of the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium to foster the potential of high-content data integration for clinical translation.

Fabricating High-viscosity Droplets using Microfluidic Capillary Device with Phase-inversion Co-flow Structure

The generation of monodisperse droplets with high viscosity has always been a challenge in droplet microfluidics. Here, we demonstrate a phase-inversion co-flow device to generate uniform high-viscosity droplets in a low-viscosity fluid. The microfluidic capillary device has a common co-flow structure with its exit connecting to a wider tube. Elongated droplets of the low-viscosity fluid are first encapsulated by the high-viscosity fluid in the co-flow structure. As the elongated low-viscosity droplets flow through the exit, which is treated to be wetted by the low-viscosity fluid, phase inversion is then induced by the adhesion of the low viscosity droplets to the tip of the exit, which results in the subsequent inverse encapsulation of the high-viscosity fluid. The size of the resultant high-viscosity droplets can be adjusted by changing the flow rate ratio of the low-viscosity fluid to the high-viscosity fluid. We demonstrate several typical examples of the generation of high-viscosity droplets with a viscosity up to 11.9 Pas, such as glycerol, honey, starch, and polymer solution. The method provides a simple and straightforward approach to generate monodisperse high-viscosity droplets, which may be used in a variety of droplet-based applications, such as materials synthesis, drug delivery, cell assay, bioengineering, and food engineering.