Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis.

Genetic screens are powerful tools for identifying genes responsible for diverse phenotypes. Here we describe a genome-wide CRISPR/Cas9-mediated loss-of-function screen in tumor growth and metastasis. We mutagenized a non-metastatic mouse cancer cell line using a genome-scale library with 67,405 single-guide RNAs (sgRNAs). The mutant cell pool rapidly generates metastases when transplanted into immunocompromised mice. Enriched sgRNAs in lung metastases and late-stage primary tumors were found to target a small set of genes, suggesting that specific loss-of-function mutations drive tumor growth and metastasis. Individual sgRNAs and a small pool of 624 sgRNAs targeting the top-scoring genes from the primary screen dramatically accelerate metastasis. In all of these experiments, the effect of mutations on primary tumor growth positively correlates with the development of metastases. Our study demonstrates Cas9-based screening as a robust method to systematically assay gene phenotypes in cancer evolution in vivo.

Development of Integrated Systems for On-Site Infection Detection.

The modern healthcare system faces an unrelenting threat from microorganisms, as evidenced by global outbreaks of new viral diseases, emerging antimicrobial resistance, and the rising incidence of healthcare-associated infections (HAIs). An effective response to these threats requires rapid and accurate diagnostic tests that can identify causative pathogens at the point of care (POC). Such tests could eliminate diagnostic uncertainties, facilitating patient triaging, minimizing the empiric use of antimicrobial drugs, and enabling targeted treatments. Current standard methods, however, often fail to meet the needs of rapid diagnosis in POC settings. Culture-based assays entail long processing times and require specialized laboratory infrastructure; nucleic acid (NA) tests are often limited to centralized hospitals due to assay complexity and high costs. Here we discuss two new POC tests developed in our groups to enable the rapid diagnosis of infection. The first is nanoPCR that takes advantages of core-shell magnetoplasmonic nanoparticles (MPNs): (i) Au shell significantly accelerates thermocycling via volumetric, plasmonic light-to-heat conversion and (ii) a magnetic core enables sensitive in situ fluorescent detection via magnetic clearing. By adopting a Ferris wheel module, the system expedites multisamples in parallel with a minimal setup. When applied to COVID-19 diagnosis, nanoPCR detected SARS-CoV-2 RNA down to 3.2 copy/µL within 17 min. In particular, nanoPCR diagnostics accurately identified COVID-19 cases in clinical samples (n = 150), validating its clinical applicability. The second is a polarization anisotropy diagnostic (PAD) system that exploits the principle of fluorescence polarization (FP) as a detection modality. Fluorescent probes were designed to alter their molecular weight upon recognizing target NAs. This event modulates the probes' tumbling rate (Brownian motion), which leads to changes in FP. The approach is robust against environmental noise and benefits from the ratiometric nature of the signal readout. We applied PAD to detect clinically relevant HAI bacteria (Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Staphylococcus aureus). The PAD assay demonstrated detection sensitivity down to the single bacterium level and determined both drug resistance and virulence status. In summary, these new tests have the potential to become powerful tools for rapid diagnosis in the infectious disease space. They do not require highly skilled personnel or labor-intensive analyses, and the assays are quick and cost-effective. These attributes will make nanoPCR and PAD well-aligned with a POC workflow to aid physicians to initiate prompt and informed patient treatment.

Precise Nanosizing with High Dynamic Range Holography.

Optical sensing is one of the key enablers of modern diagnostics. Especially label-free imaging modalities hold great promise as they eliminate labeling procedures prior to analysis. However, scattering signals of nanometric particles scale with their volume square. This unfavorable scaling makes it extremely difficult to quantitatively characterize intrinsically heterogeneous clinical samples, such as extracellular vesicles, as their signal variation easily exceeds the dynamic range of currently available cameras. Here, we introduce off-axis k-space holography that circumvents this limitation. By imaging the back-focal plane of our microscope, we project the scattering signal of all particles onto all camera pixels, thus dramatically boosting the achievable dynamic range to up to 110 dB. We validate our platform by detecting and quantitatively sizing metallic and dielectric particles over a 200 × 200 µm field of view and demonstrate that independently performed signal calibrations allow correctly sizing particles made from different materials. Finally, we present quantitative size distributions of extracellular vesicle samples.

Kaleidoscopic fluorescent arrays for machine-learning-based point-of-care chemical sensing.

Multiplexed analysis allows simultaneous measurements of multiple targets, improving the detection sensitivity and accuracy. However, highly multiplexed analysis has been challenging for point-of-care (POC) sensing, which requires a simple, portable, robust, and affordable detection system. In this work, we developed paper-based POC sensing arrays consisting of kaleidoscopic fluorescent compounds. Using an indolizine structure as a fluorescent core skeleton, named Kaleidolizine (KIz), a library of 75 different fluorescent KIz derivatives were designed and synthesized. These KIz derivatives are simultaneously excited by a single ultraviolet (UV) light source and emit diverse fluorescence colors and intensities. For multiplexed POC sensing system, fluorescent compounds array on cellulose paper was prepared and the pattern of fluorescence changes of KIz on array were specific to target chemicals adsorbed on that paper. Furthermore, we developed a machine-learning algorithm for automated, rapid analysis of color and intensity changes of individual sensing arrays. We showed that the paper sensor arrays could differentiate 35 different volatile organic compounds using a smartphone-based handheld detection system. Powered by the custom-developed machine-learning algorithm, we achieved the detection accuracy of 97% in the VOC detection. The highly multiplexed paper sensor could have favorable applications for monitoring a broad-range of environmental toxins, heavy metals, explosives, pathogens.

Intra-Cardiac Release of Extracellular Vesicles Shapes Inflammation Following Myocardial Infarction.

RATIONALE: A rapid and massive influx of inflammatory cells occurs into ischemic area after myocardial infarction (MI), resulting in local release of cytokines and growth factors. Yet, the mechanisms regulating their production are not fully explored. The release of extracellular vesicles (EVs) in the interstitial space curbs important biological functions, including inflammation, and influences the development of cardiovascular diseases. To date, there is no evidence for in situ release of cardiac EVs after MI. OBJECTIVE: The present study tested the hypothesis that local EV generation in the infarcted heart coordinates cardiac inflammation after MI. METHODS AND RESULTS: Coronary artery ligation in mice transiently increases EV levels in the left ventricle when compared with sham animals. EVs from infarcted hearts were characterized as large vesicles (252±18 nm) expressing cardiomyocyte and endothelial markers and small EVs (118±4 nm) harboring exosomal markers, such as CD (cluster of differentiation) 63 and CD9. Cardiac large EVs generated after MI, but not small EVs or sham EVs, increased the release of IL (interleukin)-6, CCL (chemokine ligand) 2, and CCL7 from fluorescence-activated cell-sorted Ly6C+ cardiac monocytes. EVs of similar diameter were also isolated from fragments of interventricular septum obtained from patients undergoing aortic valve replacement, thus supporting the clinical relevance of our findings in mice. CONCLUSIONS: The present study demonstrates that acute MI transiently increases the generation of cardiac EVs characterized as both exosomes and microvesicles, originating mainly from cardiomyocytes and endothelial cells. EVs accumulating in the ischemic myocardium are rapidly taken up by infiltrating monocytes and regulate local inflammatory responses.

New Technologies for Analysis of Extracellular Vesicles.

Extracellular vesicles (EVs) are diverse, nanoscale membrane vesicles actively released by cells. Similar-sized vesicles can be further classified (e.g., exosomes, microvesicles) based on their biogenesis, size, and biophysical properties. Although initially thought to be cellular debris, and thus under-appreciated, EVs are now increasingly recognized as important vehicles of intercellular communication and circulating biomarkers for disease diagnoses and prognosis. Despite their clinical potential, the lack of sensitive preparatory and analytical technologies for EVs poses a barrier to clinical translation. New analytical platforms including molecular ones are thus actively being developed to address these challenges. Recent advances in the field are expected to have far-reaching impact in both basic and translational studies. This article aims to present a comprehensive and critical overview of emerging analytical technologies for EV detection and their clinical applications.

Digital diffraction analysis enables low-cost molecular diagnostics on a smartphone.

The widespread distribution of smartphones, with their integrated sensors and communication capabilities, makes them an ideal platform for point-of-care (POC) diagnosis, especially in resource-limited settings. Molecular diagnostics, however, have been difficult to implement in smartphones. We herein report a diffraction-based approach that enables molecular and cellular diagnostics. The D3 (digital diffraction diagnosis) system uses microbeads to generate unique diffraction patterns which can be acquired by smartphones and processed by a remote server. We applied the D3 platform to screen for precancerous or cancerous cells in cervical specimens and to detect human papillomavirus (HPV) DNA. The D3 assay generated readouts within 45 min and showed excellent agreement with gold-standard pathology or HPV testing, respectively. This approach could have favorable global health applications where medical access is limited or when pathology bottlenecks challenge prompt diagnostic readouts.

Facile Coating Strategy to Functionalize Inorganic Nanoparticles for Biosensing.

The use of inorganic nanoparticles (NPs) for biosensing requires that they exhibit high colloidal stability under various physiological conditions. Here, we report on a general approach to render hydrophobic NPs into hydrophilic ones that are ready for bioconjugation. The method uses peglyated polymers conjugated with multiple dopamines, which results in multidentate coordination. As proof-of-concept, we applied the coating to stabilize ferrite and lanthanide NPs synthesized by thermal decomposition. Both polymer-coated NPs showed excellent water solubility and were stable at high salt concentrations under physiological conditions. We used these NPs as molecular-sensing agents to detect exosomes and bacterial nucleic acids.

Point of care assessment of melanoma tumor signaling and metastatic burden from µNMR analysis of tumor fine needle aspirates and peripheral blood.

This study evaluates µNMR technology for molecular profiling of tumor fine needle aspirates and peripheral blood of melanoma patients. In vitro assessment of melanocyte (MART-1, HMB45) and MAP kinase signaling (pERK, pS6K) molecule expression was performed in human cell lines, while clinical validation was performed in an IRB-approved study of melanoma patients undergoing biopsy and blood sampling. Tumor FNA and blood specimens were compared with BRAF genetic analysis and cross-sectional imaging. µNMR in vitro analysis showed increased expression of melanocyte markers in melanoma cells as well as increased expression of phosphorylated MAP kinase targets in BRAF-mutant melanoma cells. Melanoma patient FNA samples showed increased pERK and pS6K levels in BRAF mutant compared with BRAF WT melanomas, with µNMR blood circulating tumor cell level increased with higher metastatic burden visible on imaging. These results indicate that µNMR technology provides minimally invasive point-of-care evaluation of tumor signaling and metastatic burden in melanoma patients.

Exploring alternative ovarian cancer biomarkers using innovative nanotechnology strategies.

Our increased understanding of ovarian cancer's blueprints (mediated by DNA and RNA) and behavior (mediated by proteins) points to wide differences across patients that cannot be depicted by histology alone. Conventional diagnosis usually entails an adequate tissue biopsy, which limits serial testing. There is thus a motivation to shift towards easier to obtain clinical samples (e.g., ascites or blood). In response, investigators are increasingly leveraging alternative circulating biomarkers in blood or proximal fluids and harnessing novel profiling platforms to help explore treatment-related effects on such biomarkers in serial fashion. In this review, we discuss how new nanotechnologies we developed intersect with alternative ovarian cancer biomarkers for improved understanding of metastases and therapeutic response.

Ascites analysis by a microfluidic chip allows tumor-cell profiling.

Ascites tumor cells (ATCs) represent a potentially valuable source of cells for monitoring treatment of ovarian cancer as it would obviate the need for more invasive surgical biopsies. The ability to perform longitudinal testing of ascites in a point-of-care setting could significantly impact clinical trials, drug development, and clinical care. Here, we developed a microfluidic chip platform to enrich ATCs from highly heterogeneous peritoneal fluid and then perform molecular analyses on these cells. We evaluated 85 putative ovarian cancer protein markers and found that nearly two-thirds were either nonspecific for malignant disease or had low abundance. Using four of the most promising markers, we prospectively studied 47 patients (33 ovarian cancer and 14 control). We show that a marker set (ATCdx) can sensitively and specifically map ATC numbers and, through its reliable enrichment, facilitate additional treatment-response measurements related to proliferation, protein translation, or pathway inhibition.

Nanostar Clustering Improves the Sensitivity of Plasmonic Assays.

Star-shaped Au nanoparticles (Au nanostars, AuNS) have been developed to improve the plasmonic sensitivity, but their application has largely been limited to single-particle probes. We herein describe a AuNS clustering assay based on nanoscale self-assembly of multiple AuNS and which further increases detection sensitivity. We show that each cluster contains multiple nanogaps to concentrate electric fields, thereby amplifying the signal via plasmon coupling. Numerical simulation indicated that AuNS clusters assume up to 460-fold higher field density than Au nanosphere clusters of similar mass. The results were validated in model assays of protein biomarker detection. The AuNS clustering assay showed higher sensitivity than Au nanosphere. Minimizing the size of affinity ligand was found important to tightly confine electric fields and improve the sensitivity. The resulting assay is simple and fast and can be readily applied to point-of-care molecular detection schemes.

Fluorescence Polarization Based Nucleic Acid Testing for Rapid and Cost-Effective Diagnosis of Infectious Disease.

A new nucleic acid detection method was developed for a rapid and cost-effective diagnosis of infectious disease. This approach relies on the three unique elements: 1) detection probes that regulate DNA polymerase activity in response to the complementary target DNA; 2) universal reporters conjugated with a single fluorophore; and 3) fluorescence polarization (FP) detection. As a proof-of-concept, the assay was used to detect and sub-type Salmonella bacteria with sensitivities down to a single bacterium in less than three hours.

Molecular characterization of scant lung tumor cells using iron-oxide nanoparticles and micro-nuclear magnetic resonance.

Advances in nanotechnology and microfluidics are enabling the analysis of small amounts of human cells. We tested whether recently developed micro-nuclear magnetic resonance (µNMR) technology could be leveraged for diagnosing pulmonary malignancy using fine needle aspirate (FNA) of primary lesions and/or peripheral blood samples. We enrolled a cohort of 35 patients referred for CT biopsy of primary pulmonary nodules, liver or adrenal masses and concurrently obtained FNA and peripheral blood samples. FNA sampling yielded sufficient material for µNMR analysis in 91% of cases and had a sensitivity and specificity of 91.6% and 100% respectively. Interestingly, among blood samples with positive circulating tumor cells (CTC), µNMR analysis of each patient's peripheral blood led to similar diagnosis (malignant vs benign) and differential diagnosis (lung malignancy subtype) in 100% and 90% (18/20) of samples, respectively. µNMR appears to be a valuable, non-invasive adjunct in the diagnosis of lung cancer. FROM THE CLINICAL EDITOR: The authors of this study established that recently developed micro-nuclear magnetic resonance (µNMR) technology can be leveraged for diagnosing pulmonary malignancy using fine needle aspirate (FNA) of primary lesions and/or peripheral blood samples derived from 35 patients, suggesting practical clinical applicability of this technique.

Phase-driven progress in nanophotonic biosensing.

In the continuous pursuit of enhancing the sensitivity of nanophotonic biosensors by leveraging phase phenomena, a recent development involved the engineering of an atomically thin Ge2Sb2Te5 layer on a silver nanofilm to generate large Goos-Hänchen-shifts associated with phase singularities. The resulting detection limit reached ~7 × 10-7 RIU.

Deep learning pipeline for automated cell profiling from cyclic imaging.

Cyclic fluorescence microscopy enables multiple targets to be detected simultaneously. This, in turn, has deepened our understanding of tissue composition, cell-to-cell interactions, and cell signaling. Unfortunately, analysis of these datasets can be time-prohibitive due to the sheer volume of data. In this paper, we present CycloNET, a computational pipeline tailored for analyzing raw fluorescent images obtained through cyclic immunofluorescence. The automated pipeline pre-processes raw image files, quickly corrects for translation errors between imaging cycles, and leverages a pre-trained neural network to segment individual cells and generate single-cell molecular profiles. We applied CycloNET to a dataset of 22 human samples from head and neck squamous cell carcinoma patients and trained a neural network to segment immune cells. CycloNET efficiently processed a large-scale dataset (17 fields of view per cycle and 13 staining cycles per specimen) in 10 min, delivering insights at the single-cell resolution and facilitating the identification of rare immune cell clusters. We expect that this rapid pipeline will serve as a powerful tool to understand complex biological systems at the cellular level, with the potential to facilitate breakthroughs in areas such as developmental biology, disease pathology, and personalized medicine.

Novel lateral flow assay to detect H2O2 by utilizing self-biotinylation of G-quadruplex.

We herein describe a novel lateral flow assay (LFA) to detect H2O2 by utilizing self-biotinylation of G-quadruplex (G4). In this strategy, the G4 strand promotes the self-biotinylation of G4 itself in the presence of H2O2, which is then allowed to bind to the FAM-labeled complementary detector probe. The resulting biotin-labeled G4/FAM-detector probe complex is captured on the test line, producing a red-colored band during lateral flow readout. Based on this unique approach, we achieved the naked-eye detection of target H2O2 at concentrations as low as 1 µM, with reliable quantification down to 0.388 µM. This method also demonstrated exceptional specificity in distinguishing H2O2 from other non-target molecules. We further verified its versatile applicability by reliably identifying another biomolecule, choline, by coupling with choline oxidase, which generates H2O2 during oxidation. This novel LFA strategy holds great promise as a powerful point-of-care testing (POCT) platform for detecting a large spectrum of target biomolecules by employing their corresponding oxidases.

CRISPR/Cas13a-assisted amplification-free miRNA biosensor via dark-field imaging and magnetic gold nanoparticles.

MicroRNAs (miRNAs) are short (about 18-24 nucleotides) non-coding RNAs and have emerged as potential biomarkers for various diseases, including cancers. Due to their short lengths, the specificity often becomes an issue in conventional amplification-based methods. Next-generation sequencing techniques could be an alternative, but the long analysis time and expensive costs make them less suitable for routine clinical diagnosis. Therefore, it is essential to develop a rapid, selective, and accurate miRNA detection assay using a simple, affordable system. In this work, we report a CRISPR/Cas13a-based miRNA biosensing using point-of-care dark-field (DF) imaging. We utilized magnetic-gold nanoparticle (MGNPs) complexes as signal probes, which consist of 200 nm-sized magnetic beads and 60 nm-sized gold nanoparticles (AuNPs) linked by DNA hybridization. Once the CRISPR/Cas13a system recognized the target miRNAs (miR-21-5p), the activated Cas13a cleaved the bridge linker containing RNA sequences, releasing 60 nm-AuNPs detected and quantified by a portable DF imaging system. The combination of CRISPR/Cas13a, MGNPs, and DF imaging demonstrated amplification-free detection of miR-21-5p within 30 min at a detection limit of 500 attomoles (25 pM) and with single-base specificity. The CRISPR/Cas13a-assisted MGNP-DF assay achieved rapid, selective, and accurate detection of miRNAs with simple equipment, thus providing a potential application for cancer diagnosis.

Rigorous Comparison of Extracellular Vesicle Processing to Enhance Downstream Analysis for Glioblastoma Characterization.

Extracellular vesicles (EVs) are highly sought after as a source of biomarkers for disease detection and monitoring. Tumor EV isolation, processing, and evaluation from biofluids is convoluted by EV heterogeneity and biological contaminants and is limited by technical processing efficacy. This study rigorously compares common bulk EV isolation workflows (size exclusion chromatography, SEC; membrane affinity, MA) alongside downstream RNA extraction protocols to investigate molecular analyte recovery. EV integrity and recovery is evaluated using a variety of technologies to quantify total intact EVs, total and surface proteins, and RNA purity and recovery. A comprehensive evaluation of each analyte is performed, with a specific emphasis on maintaining user (n = 2), biological (n = 3), and technical replicates (n≥3) under in vitro conditions. Subsequent study of tumor EV spike-in into healthy donor plasma samples is performed to further validate biofluid-derived EV purity and isolation for clinical application. Results show that EV surface integrity is considerably preserved in eluates from SEC-derived EVs, but RNA recovery and purity, as well as bulk protein isolation, is significantly improved in MA-isolated EVs. This study concludes that EV isolation and RNA extraction pipelines govern recovered analyte integrity, necessitating careful selection of processing modality to enhance recovery of the analyte of interest.