On the Behavior of Nanoparticles beyond the Nanopore Interface.

Recent advances in solid-state and biological nanopore sensors have produced a deluge of analytical techniques for in situ characterization of bio-nano colloidal dispersions; however, the transport forces governing particle movement into and out of the nanopore are not yet fully understood. Herein, we study the motion of particles outside the smaller opening of an elastomeric size-tunable nanopore and relate this motion to existing transport forces known to act on particles within the pore. Subsequently, we develop a combined optoelectronic approach which allows the comparison of both resistive pulse sensing and single particle tracking-based techniques for particle size characterization and, intriguingly, measurements of the ensemble particle motion induced by a combination of particle electrophoresis as well as pressure-driven and electroosmotic flows through the sensor nanopore. We find evidence suggesting that although bulk fluid flow from the pore tends to drive particle motion, in certain circumstances, electrophoretically driven motion can dominate bulk fluid flow-driven motion even at large distances from the pore opening. By permitting direct observation of the behavior of fluids at the nanopore interface, this approach enables a greater understanding of the transport forces acting on particles as they migrate toward and move through nanopore sensors-with implications for future particle characterization systems and for nanopore methods in general.

Isothermal Point Mutation Detection: Toward a First-Pass Screening Strategy for Multidrug-Resistant Tuberculosis.

Point mutations in DNA are useful biomarkers that can provide critical classification of disease for accurate diagnosis and to inform clinical decisions. Conventional approaches to detect point mutations are usually based on technologies such as real-time polymerase chain reaction (PCR) or DNA sequencing, which are typically slow and require expensive lab-based equipment. While rapid isothermal strategies such as recombinase polymerase amplification (RPA) have been proposed, they tend to suffer from poor specificity in discriminating point mutations. Herein, we describe a novel strategy that enabled exquisite point mutation discrimination with isothermal DNA amplification, using mismatched primers in conjunction with a two-round enrichment process. As a proof of concept, the method was applied to the rapid and specific identification of drug-resistant Mycobacterium tuberculosis using RPA under specific conditions. The assay requires just picogram levels of genomic DNA input, is sensitive and specific enough to detect 10% point mutation loading, and can discriminate between closely related mutant variants within 30 min. The assay was subsequently adapted onto a low-cost 3D-printed isothermal device with real-time analysis capabilities to demonstrate a potential point-of-care application. Finally, the generic applicability of the strategy was shown by detecting three other clinically important cancer-associated point mutations. We believe that our assay shows potential in a broad range of healthcare screening processes for detecting and categorizing disease phenotypes at the point of care, thus reducing unnecessary therapy and cost in these contexts.

Next-Generation Molecular Discovery: From Bottom-Up In Vivo and In Vitro Approaches to In Silico Top-Down Approaches for Therapeutics Neogenesis.

Protein and drug engineering comprises a major part of the medical and research industries, and yet approaches to discovering and understanding therapeutic molecular interactions in biological systems rely on trial and error. The general approach to molecular discovery involves screening large libraries of compounds, proteins, or antibodies, or in vivo antibody generation, which could be considered "bottom-up" approaches to therapeutic discovery. In these bottom-up approaches, a minimal amount is known about the therapeutics at the start of the process, but through meticulous and exhaustive laboratory work, the molecule is characterised in detail. In contrast, the advent of "big data" and access to extensive online databases and machine learning technologies offers promising new avenues to understanding molecular interactions. Artificial intelligence (AI) now has the potential to predict protein structure at an unprecedented accuracy using only the genetic sequence. This predictive approach to characterising molecular structure-when accompanied by high-quality experimental data for model training-has the capacity to invert the process of molecular discovery and characterisation. The process has potential to be transformed into a top-down approach, where new molecules can be designed directly based on the structure of a target and the desired function, rather than performing screening of large libraries of molecular variants. This paper will provide a brief evaluation of bottom-up approaches to discovering and characterising biological molecules and will discuss recent advances towards developing top-down approaches and the prospects of this.

Digital Decoding of Single Extracellular Vesicle Phenotype Differentiates Early Malignant and Benign Lung Lesions.

Accurate identification of malignant lung lesions is a prerequisite for rational clinical management to reduce morbidity and mortality of lung cancer. However, classification of lung nodules into malignant and benign cases is difficult as they show similar features in computer tomography and sometimes positron emission tomography imaging, making invasive tissue biopsies necessary. To address the challenges in evaluating indeterminate nodules, the authors investigate the molecular profiles of small extracellular vesicles (sEVs) in differentiating malignant and benign lung nodules via a liquid biopsy-based approach. Aiming to characterize phenotypes between malignant and benign groups, they develop a single-molecule-resolution-digital-sEV-counting-detection (DECODE) chip that interrogates three lung-cancer-associated sEV biomarkers and a generic sEV biomarker to create sEV molecular profiles. DECODE capturessEVs on a nanostructured pillar chip, confines individual sEVs, and profiles sEV biomarker expression through surface-enhanced Raman scattering barcodes. The author utilize DECODE to generate a digitally acquired sEV molecular profiles in a cohort of 33 people, including patients with malignant and benign lung nodules, and healthy individuals. Significantly, DECODE reveals sEV-specific molecular profiles that allow the separation of malignant from benign (area under the curve, AUC = 0.85), which is promising for non-invasive characterisation of lung nodules found in lung cancer screening and warrants further clinincal validaiton with larger cohorts.

In Situ Single Cell Proteomics Reveals Circulating Tumor Cell Heterogeneity during Treatment.

Cancer is a dynamic disease with heterogenic molecular signatures and constantly evolves during the course of the disease. Single cell proteomic analysis could offer a suitable pathway to monitor cancer cell heterogeneity and deliver critical information for the diagnosis, recurrence, and drug-resistant mechanisms in cancer. Current standard techniques for proteomic analysis such as ELISA, mass spectrometry, and Western blots are time-consuming, expensive, and often require fluorescence labeling that fails to provide accurate information about the multiple protein expression changes at the single cell level. Herein, we report a surface-enhanced Raman spectroscopy-based simple microfluidic device that enables the screening of single circulating tumor cells (CTC) in a dynamic state to precisely understand the heterogeneous expression of multiple protein biomarkers in response to therapy. It further enables identifying intercellular heterogeneous expression of CTC surface proteins which would be highly informative to identify the cancer cells surviving treatment and potentially responsible for drug resistance. Using a bead and cell line-based model system, we successfully detect single bead and single cell spectra when flowed through the device. Using SK-MEL-28 melanoma cells, we demonstrate that our system is capable of monitoring heterogeneous expressions of multiple surface protein markers (MCSP, MCAM, and LNGFR) before and during drug treatment. Integrating a label-free electrochemical system with the device, we also monitor the expression of an intracellular protein (here, BRAFV600E) under drug treatment. Finally, we perform a longitudinal study with 15 samples from five different melanoma patients who underwent therapy. We find that the average expression of receptor proteins in a patient fails to determine the therapy response particularly when the disease progresses. However, single CTC analysis with our device shows a high level of intercellular heterogeneity in the receptor expression profiles of patient-derived CTCs and identifies heterogeneity within CTCs. More importantly, we find that a fraction of CTCs still shows a high expression of these receptor proteins during and after therapy, indicating the presence of resistant CTCs which may evolve after a certain time and progress the disease. We believe this automated assay will have high clinical importance in disease diagnosis and monitoring treatment and will significantly advance the understanding of cancer heterogeneity on the single cell level.

Characterizing the Heterogeneity of Small Extracellular Vesicle Populations in Multiple Cancer Types via an Ultrasensitive Chip.

Identifying small extracellular vesicle (sEV) subpopulations based on their different molecular signatures could potentially reveal the functional roles in physiology and pathology. However, it is a challenge to achieve this aim due to the nano-sized dimensions of sEVs, low quantities of biological cargo each sEV carries, and our incomplete knowledge of identifying features capable of separating heterogeneous sEV subpopulations. Here, a sensitive, multiplexed, and nano-mixing-enhanced sEV subpopulation characterization platform (ESCP) is proposed to precisely determine the sEV phenotypic heterogeneity and understand the role of sEV heterogeneity in cancer progression and metastasis. The ESCP utilizes spatially patterned anti-tetraspanin-functionalized micro-arrays for sEV subpopulation sorting and nanobarcode-based surface-enhanced Raman spectroscopy for multiplexed read-outs. An ESCP has been used for investigating sEV phenotypic heterogeneity in terms of canonical sEV tetraspanin molecules and cancer-associated protein biomarkers in both cancer cell line models and cancer patient samples. Our data explicitly demonstrate the selective enrichment of tetraspanins and cancer-associated protein biomarkers, in particular sEV subpopulations. Therefore, it is believed that the ESCP could enable the evaluation and broader application of sEV subpopulations as potential diagnostic disease biomarkers.

Two-Photon Nanolithography of Tailored Hollow three-dimensional Microdevices for Biosystems.

Functional three-dimensional (3D) microstructures incorporating accessible interiors have emerged as a versatile platform for biosystem applications. By configuring their 3D geometric features, these biosystem microdevices can accurately evaluate and control targeted bioenvironments. However, classical fabrication techniques based on photolithography-etching processes cannot precisely and programmably control the geometric of the entire hollow 3D microstructures. Here, we proposed the use of a two-photon polymerization (TPP)-based technique for the precise, straightforward, and customizable preparation of hollow 3D microstructure devices with small opening(s). Factors governing the formation of hollow 3D biosystem microdevices, including material composition, laser input, and (post-) development treatment, have been systematically investigated and a set of optimized conditions are presented as a starting point for the development of novel hollow biosystem microdevices. To evaluate the broad applicability of this approach, a series of tailored hollow 3D microdevices with small opening(s), including a micropore, microneedle, microelectrode, microvalve, and micromachine, were successfully prepared using our direct laser writing-TPP technique. To further validate the feasibility of these biosystem microdevices in practical implementations, we demonstrated the use of hollow 3D micropore devices for the robust resistive-pulse analysis of nanoparticles.

Maskless 3D Ablation of Precise Microhole Structures in Plastics Using Femtosecond Laser Pulses.

Femtosecond laser ablation is a robust tool for the fabrication of microhole structures. This technique has several advantages compared to other microfabrication strategies for reliably preparing microhole structures of high quality and low cost. However, few studies have explored the use of femtosecond laser ablation in plastic materials because of the lack of controllability over the fabrication process in plastics. In particular, the depth profile of microhole structures prepared by conventional laser ablation techniques in plastics cannot be precisely and reproducibly controlled. In this paper, a novel three-dimensional femtosecond laser ablation technique was developed for the rapid fabrication of precise microhole structures in multiple plastics in air. Using a three-step fabrication scheme, microholes demonstrated extremely clean and sharp geometric features. This new technique also enables the precise creation of arbitrary-shaped microwell structures in plastic substrates through a rapid single-step ablation process, without the need for any masks. As a proof of concept for practical applications, precise microhole structures prepared by this novel femtosecond laser ablation technique were exploited for robust resistive-pulse sensing of microparticles.

Simultaneous size and ζ-potential measurements of individual nanoparticles in dispersion using size-tunable pore sensors.

The prospect of characterizing individual nanoparticles, molecules, or DNA base pairs has generated considerable interest in resistive pulse sensing. In addition to size and concentration analysis, this technique also has the capacity to measure the charge density of objects in situations where electrophoretic forces dominate their motion. Here we present a methodology to simultaneously extract, via appropriate theoretical models, the size and ζ-potential of objects from the resistive pulse signal they generate. The methodology was demonstrated using a size-tunable elastic pore sensor to measure a complex "bimodal" suspension composed of two particle sets with different size and charge. Elastically tuning the size of the pore sensor, by stretching the elastic pore membrane, enables a larger sample size range to be analyzed, improves measurement sensitivity, and fine-tunes the forces acting on objects. This methodology represents a new approach for investigating and understanding the fundamental behavior of nanoscale dispersions.