A Mesoporous Gold Sensor Unveils Phospho PD-L1 in Extracellular Vesicles as a Proxy for PD-L1 Expression in Lung Cancer Tissue.

Immune checkpoint inhibitors (ICIs) targeting programmed cell death ligand 1 (PD-L1), or its receptor, PD-1 have improved survival in patients with non-small-cell lung cancer (NSCLC). Assessment of PD-L1 expression requires tissue biopsy or fine needle aspiration that are currently used to identify patients most likely to respond to single agent anti-PD-1/PD-L1 therapy. However, obtaining sufficient tissue to generate a PD-L1 tissue proportion score (TPS) ≥ 50% using immunohistochemistry remains a challenge that potentially may be overcome by liquid biopsies. This study utilized a mesoporous gold sensor (MGS) assay to examine the phosphorylation status of PD-L1 in plasma extracellular vesicles (EV pPD-L1) and PD-L1 levels in plasma from NSCLC patient samples and their association with tumor PD-L1 TPS. The 3-dimensional mesoporous network of the electrodes provides a large surface area, high signal-to-noise ratio, and a superior electro-conductive framework, thereby significantly improving the detection sensitivity of PD-L1 nanosensing. Test (n = 20) (Pearson's r = 0.99) and validation (n = 45) (Pearson's r = 0.99) cohorts show that EV pPD-L1 status correlates linearly with the tumor PD-L1 TPS assessed by immunohistochemistry irrespective of the tumor stage, with 64% of patients overall showing detectable EV pPD-L1 levels in plasma. In contrast to the EV pPD-L1 results, plasma PD-L1 levels did not correlate with the tumor PD-L1 TPS score or EV pPD-L1 levels. These data demonstrate that EV pPD-L1 levels may be used to select patients for appropriate PD-1 and PD-L1 ICI therapy regimens in early, locally advanced, and advanced NSCLC and should be tested further in randomized controlled trials. Most importantly, the assay used has a less than 24h turnaround time, facilitating adoption of the test into the routine diagnostic evaluation of patients prior to therapy.

Molecular Stratification and Treatment Monitoring of Lung Cancer Using a Small Extracellular Vesicle-Activated Nanocavity Architecture.

Development of molecular diagnostics for lung cancer stratification and monitoring is crucial for the rational planning and timely adjustment of treatments to improve clinical outcomes. In this regard, we propose a nanocavity architecture to sensitively profile the protein signature on small extracellular vesicles (sEVs) to enable accurate, noninvasive staging and treatment monitoring of lung cancer. The nanocavity architecture is formed by molecular recognition through the binding of sEVs with the nanobox-based core-shell surface-enhanced Raman scattering (SERS) barcodes and mirrorlike, asymmetric gold microelectrodes. By imposing an alternating current on the gold microelectrodes, a nanofluidic shear force was stimulated that supported the binding of sEVs and the efficient assembly of the nanoboxes. The binding of sEVs further induced a nanocavity between the nanobox and the gold microelectrode that significantly amplified the electromagnetic field to enable the simultaneous enhancement of Raman signals from four SERS barcodes and generate patient-specific molecular sEV signatures. Importantly, evaluated on a cohort of clinical samples (n = 76) on the nanocavity architecture, the acquired patient-specific sEV molecular signatures achieved accurate identification, stratification, and treatment monitoring of lung cancer patients, highlighting its potential for transition to clinical utility.

LowTempGAL: a highly responsive low temperature-inducible GAL system in Saccharomyces cerevisiae.

Temperature is an important control factor for biologics biomanufacturing in precision fermentation. Here, we explored a highly responsive low temperature-inducible genetic system (LowTempGAL) in the model yeast Saccharomyces cerevisiae. Two temperature biosensors, a heat-inducible degron and a heat-inducible protein aggregation domain, were used to regulate the GAL activator Gal4p, rendering the leaky LowTempGAL systems. Boolean-type induction was achieved by implementing a second-layer control through low-temperature-mediated repression on GAL repressor gene GAL80, but suffered delayed response to low-temperature triggers and a weak response at 30°C. Application potentials were validated for protein and small molecule production. Proteomics analysis suggested that residual Gal80p and Gal4p insufficiency caused suboptimal induction. 'Turbo' mechanisms were engineered through incorporating a basal Gal4p expression and a galactose-independent Gal80p-supressing Gal3p mutant (Gal3Cp). Varying Gal3Cp configurations, we deployed the LowTempGAL systems capable for a rapid stringent high-level induction upon the shift from a high temperature (37-33°C) to a low temperature (≤30°C). Overall, we present a synthetic biology procedure that leverages 'leaky' biosensors to deploy highly responsive Boolean-type genetic circuits. The key lies in optimisation of the intricate layout of the multi-factor system. The LowTempGAL systems may be applicable in non-conventional yeast platforms for precision biomanufacturing.

High Accuracy of Clinical Verification of Electrohydrodynamic-Driven Nanobox-on-Mirror Platform for Molecular Identification of Respiratory Viruses.

The molecular detection of multiple respiratory viruses provides evidence for the rational use of drugs and effective health management. Herein, we developed and tested the clinical performance of an electrohydrodynamic-driven nanobox-on-mirror platform (E-NoM) for the parallel, accurate, and sensitive detection of four respiratory viral antigens. The E-NoM platform uses gold-silver alloy nanoboxes as the core material with the deposition of a silver layer as a shell on the core surfaces to amplify and enable a reproducible Raman signal readout that facilitates accurate detection. Additionally, the E-NoM platform employs gold microelectrode arrays as the mirror with electrohydrodynamics to manipulate the fluid flow and enhance molecular interactions for an improved biosensing response. The presence of viral antigens binds the nanobox-based core-shell nanostructure on the gold microelectrode and creates the nanocavity with extremely strong "hot spots" to benefit sensitive analysis. Significantly, in a large clinical cohort with 227 patients, the designed E-NoM platform demonstrates the capability of screening respiratory infection with achieved clinical specificity, sensitivity, and accuracy of 100.0, 96.48, and 96.91%, respectively. It is anticipated that the E-NoM platform can find a position in clinical usage for respiratory disease diagnosis.

Analysis of secreted small extracellular vesicles from activated human microglial cell lines reveals distinct pro- and anti-inflammatory proteomic profiles.

Microglia are a specialized population of innate immune cells located in the central nervous system. In response to physiological and pathological changes in their microenvironment, microglia can polarize into pro-inflammatory or anti-inflammatory phenotypes. A dysregulation in the pro-/anti-inflammatory balance is associated with many pathophysiological changes in the brain and nervous system. Therefore, the balance between microglia pro-/anti-inflammatory polarization can be a potential biomarker for the various brain pathologies. A non-invasive method of detecting microglia polarization in patients would have promising clinical applications. Here, we perform proteomic analysis of small extracellular vesicles (sEVs) derived from microglia cells to identify sEVs biomarkers indicative of pro-inflammatory and anti-inflammatory phenotypic changes. sEVs were isolated from microglia cell lines under different inflammatory conditions and analyzed by proteomics by liquid chromatography with mass spectrometry. Our findings provide the potential roles of sEVs that could be related to the pathogenesis of various brain diseases.

A mesoporous gold biosensor to investigate immune checkpoint protein heterogeneity in single lung cancer cells.

Immune checkpoint proteins (ICPs) play a major role in a patient's immune response against cancer. Tumour cells usually express those proteins to communicate with immune cells as a process of escaping the anti-cancer immune response. Detecting the major functional immune checkpoint proteins present on cancer cells (such as circulating tumor cells or CTCs) and examining the heterogeneity in their expression at the single-cell level could play a crucial role in both cancer diagnosis and the monitoring of therapy. In this study, we develop a mesoporous gold biosensor to precisely assess ICP heterogeneity in individual cancer cells within a lung cancer model. The platform utilizes a nanostructured mesoporous gold surface to capture CTCs and a Surface Enhanced Raman Scattering (SERS) readout to identify and monitor the expression of key ICP proteins (PD-L1, B7H4, CD276, CD80) in lung cancer cells. The homogeneous and abundant pores in mesoporous 3D gold nanostructures enable increased antibody loading on-chip and an enhanced SERS signal, which are key to our single cell capture, and accurate analysis of ICPs in cancer cells with high sensitivity. Our lung cancer cell line model data showed that our method can detect single cells and analyse the expression of four lung cancer associated ICPs on individual cell surfaces during treatment. To show the potential of our mesoporous gold biosensor in analysing clinical samples, we tested 9 longitudinal Peripheral Blood Mononuclear Cells (PBMC) samples from lung cancer patient before and after therapy. Our mesoporous biosensor successfully captured single CTCs and found that the expression of ICPs in CTCs is highly heterogeneous in both pre-treatment and treated PBMC samples isolated from lung cancer patient blood. We suggest that our findings will help clinicians in selecting the most appropriate therapy for patients.

Defining the relationship between cellular and extracellular vesicle (EV) content in breast cancer via an integrative multi-omic analysis.

Much recent research has been dedicated to exploring the utility of extracellular vesicles (EVs) as circulating disease biomarkers. Underpinning this work is the assumption that the molecular cargo of EVs directly reflects the originating cell. Few attempts have been made, however, to empirically validate this on the -omic level. To this end, we have performed an integrative multi-omic analysis of a panel of breast cancer cell lines and corresponding EVs. Whole transcriptome analysis validated that the cellular transcriptome remained stable when cultured cells are transitioned to low serum or serum-free medium for EV collection. Transcriptomic profiling of the isolated EVs indicated a positive correlation between transcript levels in cells and EVs, including disease-associated transcripts. Analysis of the EV proteome verified that HER2 protein is present in EVs, however neither the estrogen (ER) nor progesterone (PR) receptor proteins are detected regardless of cellular expression. Using multivariate analysis, we derived an EV protein signature to infer cellular patterns of ER and HER2 expression, though the ER protein could not be directly detected. Integrative analyses affirmed that the EV proteome and transcriptome captured key phenotypic hallmarks of the originating cells, supporting the potential of EVs for non-invasive monitoring of breast cancers.

Integration of Yeast Episomal/Integrative Plasmid Causes Genotypic and Phenotypic Diversity and Improved Sesquiterpene Production in Metabolically Engineered Saccharomyces cerevisiae.

The variability in phenotypic outcomes among biological replicates in engineered microbial factories presents a captivating mystery. Establishing the association between phenotypic variability and genetic drivers is important to solve this intricate puzzle. We applied a previously developed auxin-inducible depletion of hexokinase 2 as a metabolic engineering strategy for improved nerolidol production in Saccharomyces cerevisiae, and biological replicates exhibit a dichotomy in nerolidol production of either 3.5 or 2.5 g L-1 nerolidol. Harnessing Oxford Nanopore's long-read genomic sequencing, we reveal a potential genetic cause─the chromosome integration of a 2µ sequence-based yeast episomal plasmid, encoding the expression cassettes for nerolidol synthetic enzymes. This finding was reinforced through chromosome integration revalidation, engineering nerolidol and valencene production strains, and generating a diverse pool of yeast clones, each uniquely fingerprinted by gene copy numbers, plasmid integrations, other genomic rearrangements, protein expression levels, growth rate, and target product productivities. Τhe best clone in two strains produced 3.5 g L-1 nerolidol and ∼0.96 g L-1 valencene. Comparable genotypic and phenotypic variations were also generated through the integration of a yeast integrative plasmid lacking 2µ sequences. Our work shows that multiple factors, including plasmid integration status, subchromosomal location, gene copy number, sesquiterpene synthase expression level, and genome rearrangement, together play a complicated determinant role on the productivities of sesquiterpene product. Integration of yeast episomal/integrative plasmids may be used as a versatile method for increasing the diversity and optimizing the efficiency of yeast cell factories, thereby uncovering metabolic control mechanisms.

Correction: Plasma extracellular vesicle phenotyping for the differentiation of early-stage lung cancer and benign lung diseases.

Correction for 'Plasma extracellular vesicle phenotyping for the differentiation of early-stage lung cancer and benign lung diseases' by Liwen Yuan et al., Nanoscale Horiz., 2023, 8, 746-758, https://doi.org/10.1039/d2nh00570k.

Nanophotonic immunoarray with electrochemically roughened surfaces for handheld detection of secreted PD-L1 to predict immuno-oncology efficacy.

The analysis of secreted protein biomarkers can be a useful non-invasive method of predicting or monitoring cancer therapeutic response. The increased level of soluble programmed cell death protein ligand 1 (sPD-L1) is a promising predictive biomarker for selecting patients who are likely to respond to immune checkpoint immunotherapy. The current established immunoassay for secreted protein analysis is enzyme-linked immunosorbent assay (ELISA). Yet, ELISA is generally still liable to limited detection sensitivity and restricted to bulky chromogenic readout equipment. Herein, we present a designed nanophotonic immunoarray sensor which achieved sPD-L1 analysis at high-throughput, enhanced detection sensitivity and portability. The key benefits of our nanophotonic immunoarray sensor are (i) high-throughput surface-enhanced Raman scattering (SERS) analysis of multiple samples on a singular platform; (ii) improved sPD-L1 detection sensitivity at 1 pg mL-1 (by two orders of magnitude as compared to ELISA) via electrochemically roughened gold sensor surfaces; (iii) fit for handheld SERS detection with miniaturized equipment footprint. We evaluated the analytical performance of the nanophotonic immunoarray sensor and successfully demonstrated quantitative sPD-L1 detection in a cohort of contrived human plasma samples.

A Microfluidic SERS Assay to Characterize the Phenotypic Heterogeneity in Cancer-Derived Small Extracellular Vesicles.

Small extracellular vesicles (sEVs) are nanoscopic bioparticles that transport biomolecular cargoes between cells. sEVs have been implicated in many pathological processes such as cancer, rendering them as promising targets for therapeutics and diagnostics. Characterizing phenotypic differences in sEV biomolecular cargos could support understanding their roles in cancer. However, this is difficult due to similar physical properties of sEVs and requirement for highly sensitive analysis. Our method describes the preparation and operation of a microfluidic immunoassay with surface-enhanced Raman scattering (SERS) readouts, termed sEV subpopulation characterization platform (ESCP). ESCP applies an alternating current induced electrohydrodynamic flow to enhance collisions of sEVs with the antibody-functionalized sensor surface. Captured sEVs are labeled with plasmonic nanoparticles to facilitate multiplexed and highly sensitive phenotypic characterization of sEVs by SERS. ESCP is demonstrated for characterizing the expression of three tetraspanins (CD9, CD63, CD81) and four cancer-associated biomarkers (MCSP, MCAM, ErbB3, LNGFR) in sEVs derived from cancer cell lines and plasma samples.

A universal reagent for detection of emerging diseases using bioengineered multifunctional yeast nanofragments.

Accurate and early detection of biomarkers provides the molecular evidence for disease management, allowing prompt actions and timely treatments to save lives. Multivalent biomolecular interactions between the probe and biomarker as well as controlled probe orientation on material surfaces are keys for highly sensitive detection. Here we report the bioengineering of programmable and multifunctional nanoprobes, which can provide rapid, specific and highly sensitive detection of emerging diseases in a range of widely used diagnostic systems. These nanoprobes composed of nanosized cell wall fragments, termed as synthetic bionanofragments (SynBioNFs), are generated by the fragmentation of genetically programmed yeast cells. SynBioNFs display multiple copies of biomolecules for high-affinity target binding and molecular handles for the precisely orientated attachment on surfaces used in diagnostic platforms. SynBioNFs are demonstrated for the capture and detection of SARS-CoV-2 virions using multiple diagnostic platforms, including surface-enhanced Raman scattering, fluorescence, electrochemical and colorimetric-based lateral flow systems with sensitivity comparable with the gold-standard reverse-transcription quantitative polymerase chain reaction.

Liquid Biopsy Snapshots of Key Phosphoproteomic Pathways in Lung Cancer Patients for Diagnosis and Therapy Monitoring.

Phosphorylation is a post-translational modification in proteins that changes protein conformation and activity for regulating signal transduction pathways. This mechanism is frequently impaired in lung cancer, resulting in permanently active constitutive phosphorylation to initiate tumor growth and/or reactivate pathways in response to therapy. We developed a multiplexed phosphoprotein analyzer chip (MPAC) that enables rapid (detection time: 5 min) and sensitive (LOD: 2 pg/µL) detection of protein phosphorylation and presents phosphoproteomic profiling of major phosphorylation pathways in lung cancer. We monitored phosphorylated receptors and downstream proteins involved in mitogen-activated protein kinase (MAPK) and PI3K/AKT/mTOR pathways in lung cancer cell line models and patient-derived extracellular vesicles (EV). Using kinase inhibitor drugs in cell line models, we found that the drug can inhibit the phosphorylation and/or activation of the kinase pathway. We then generated a phosphorylation heatmap by EV phosphoproteomic profiling of plasma samples isolated from 36 lung cancer patients and 8 noncancer individuals. The heatmap showed a clear difference between the noncancer and cancer samples and identify the specific proteins that are activated in the cancer samples. Our data also showed that MPAC could monitor immunotherapy responses by assessment of the phosphorylation states of the proteins, particularly for PD-L1. Finally, with a longitudinal study, we found that the phosphorylation levels of the proteins were indicative of a positive response to therapy. We believe that this study will lead to personalized treatment by providing a better understanding of the active and resistant pathways and will provide a tool for selecting combined and targeted therapies for precision medicine.

A Multiplexed SERS Microassay for Accurate Detection of SARS-CoV-2 and Variants of Concern.

Severe acute respiratory syndrome coronavirus 2 variants play an important role in predicting patient outcome during postinfection, and with growing fears of COVID-19 reservoirs in domestic and wild animals, it is necessary to adapt detection systems for variant detection. However, variant-specific detection remains challenging. Surface-enhanced Raman scattering is a sensitive and multiplexing technique that allows the simultaneous detection of multiple targets for accurate identification. Here we propose the development of a multiplex SERS microassay to detect both the spike and nucleocapsid structural proteins of SARS-CoV-2. The designed SERS microassay integrates gold-silver hollow nanobox barcodes and electrohydrodynamically induced nanomixing which in combination enables highly specific and sensitive detection of SARS-CoV-2 and the S-protein epitopes to delineate between ancestral prevariant strains with the newer variants of concern, Delta and Omicron. The microassay allows detection from as low as 20 virus/µL and 50 pg/mL RBD protein and can clearly identify the virus among infected versus healthy nasopharyngeal swabs, with the potential to identify between variants. The detection of both S- and N-proteins of SARS-CoV-2 and the differentiation of variants on the SERS microassay can aid the early detection of COVID-19 to reduce transmission rates and lead into adequate treatments for those severely affected by the virus.

Plasma extracellular vesicle phenotyping for the differentiation of early-stage lung cancer and benign lung diseases.

The development of a minimally invasive technique for early-stage lung cancer detection is crucial to reducing mortality. Phenotyping of tumor-associated extracellular vesicles (EVs) has the potential for early-stage lung cancer detection, yet remains challenging due to the lack of sensitive, integrated techniques that can accurately detect rare tumor-associated EV populations in blood. Here, we integrated gold core-silver shell nanoparticles and nanoscopic mixing in a microfluidic assay for sensitive phenotypic analysis of EVs directly in plasma without EV pre-isolation. The assay enabled multiplex detection of lung cancer-associated markers PTX3 and THBS1 and canonical EV marker CD63 by surface-enhanced Raman spectroscopy, providing a squared correlation coefficient of 0.97 in the range of 103-107 EVs mL-1 and a limit of detection of 19 EVs mL-1. Significantly, our machine learning-based nanostrategy provided 92.3% sensitivity and 100% specificity in differentiating early-stage lung cancer from benign lung diseases, superior to the CT scan-based lung cancer diagnosis (92.3% sensitivity and 71.4% specificity). Overall, our integrated nanostrategy achieved an AUC value of 0.978 in differentiating between early-stage lung cancer patients (n = 28) and controls consisting of patients with benign lung diseases (n = 23) and healthy controls (n = 26), which showed remarkable diagnostic performance and great clinical potential for detecting the early occurrence of lung cancer.

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.

Tetraplex Immunophenotyping of Cell Surface Proteomes via Synthesized Plasmonic Nanotags and Portable Raman Spectroscopy.

Multiplex immunophenotyping of cell surface proteomes is useful for cell characterization as well as providing valuable information on a patient's physiological or pathological state. Current methods for multiplex immunophenotyping of cell surface proteomes still have associated technical pitfalls in terms of limited multiplexing capability, challenging result interpretation, and large equipment footprint limited to use in a laboratory setting. Herein, we presented a portable surface-enhanced Raman spectroscopy (SERS) assay for multiplex cell surface immunophenotyping. We synthesized and functionalized customizable SERS nanotags for cell labeling and subsequent signal measurement using a portable Raman spectrometer. We extensively evaluated and validated the analytical assay performance of the portable SERS immunophenotyping assay in two different cellular models (red blood cells and breast cancer cells). In terms of analytical specificity, the cell surface immunophenotyping of both red blood cells and breast cancer cells correlated well with flow cytometry. The portable SERS immunophenotyping assay also has comparable analytical repeatability to flow cytometry, with coefficient of variation values of 21.89-23.33% and 6.88-17.32% for detecting red blood cells and breast cancer cells, respectively. The analytical detection limits were 77 cells/mL for red blood cells and 1-17 cells/mL for breast cancer cells. As an alternative to flow cytometry, the portable SERS immunophenotyping assay demonstrated excellent analytical assay performance and possessed advantages such as quick sample-to-result turnaround time, multiplexing capability, and small equipment footprint.

SERS Multiplex Profiling of Melanoma Circulating Tumor Cells for Predicting the Response to Immune Checkpoint Blockade Therapy.

Immune checkpoint blockade (ICB) therapy has achieved remarkable success in many cancers including melanoma. However, ICB therapy benefits only a small proportion of patients and produces severe side effects for some patients. Thus, there is an urgent need to identify patients who are more likely to respond to ICB therapy to improve outcomes and minimize side effects. To predict ICB therapy responses, we design a surface-enhanced Raman scattering (SERS) assay for multiplex profiling of circulating tumor cells (CTCs) under basal and interferon-γ (IFN-γ) stimulation. Through simultaneous ensemble and single-cell measurements of CTCs, the SERS assay can reveal tumor heterogeneity and offer a comprehensive CTC phenotype for decision-making. Anisotropic gold-silver alloy nanoboxes are utilized as SERS plasmonic substrates for improved signal readouts of CTC surface biomarkers. By generating a unique CTC signature with four surface biomarkers, the developed assay enables the differentiation of CTCs from three different patient-derived melanoma cell lines. Significantly, in a cohort of 14 melanoma patients who received programmed cell death-1 blockade therapy, the changes of CTC signature induced by IFN-γ stimulation to CTCs show the potential to predict responders. We expect that the SERS assay can help select patients for receiving ICB therapy in other cancers.

Detection of Dengue Virus 2 with Single Infected Mosquito Resolution Using Yeast Affinity Bionanofragments and Plasmonic SERS Nanoboxes.

Dengue disease is an emerging global threat triggered by dengue virus (DENV) transmission, primarily by the mosquito Aedes aegypti. The accurate surveillance and sensitive detection of DENV in mosquito populations are critical for the protection of human populations worldwide that are in the habitat of these mosquito species. There are four DENV serotypes with DENV2 reported to cause the most severe complications. There are limited ultrasensitive methods to early detect DENV2 mosquito infection and prevent human infection. Herein, we report an innovative nanobased immunoassay platform for early, specific, and ultrasensitive detection of DENV2-secreted nonstructural 1 (NS1) protein biomarker in single infected mosquitoes with the limit of detection of 500 fg of recombinant DENV2 NS1. The high sensitivity and DENV2 serotype specificity of the platform are the result of using nanomixing, plasmonic SERS nanoboxes, and yeast affinity bionanofragments displaying single-chain variable fragments (nanoyeast scFvs). Nanoyeast scFvs used for high affinity capture of DENV2 NS1 provided an innovative and cost-efficient alternative to monoclonal antibodies and differentiated DENV2 NS1 from other DENV serotypes and Zika virus NS1. The platform used electrohydrodynamically driven nanomixing to enhance NS1 capture by the nanoyeast scFvs while reducing nonspecific interactions. High sensitivity detection of captured DENV2 NS1 was achieved using NS1-specific surface-enhanced Raman scattering (SERS) nanotags. These nanotechnologies provide a significant innovation for early DENV2 detection in single infected mosquitoes, improving the accurate surveillance of mosquito habitats and preventing infection and severe disease arising from DENV2 transmission.

Modelling clinical DNA fragmentation in the development of universal PCR-based assays for bisulfite-converted, formalin-fixed and cell-free DNA sample analysis.

In fragmented DNA, PCR-based methods quantify the number of intact regions at a specific amplicon length. However, the relationship between the population of DNA fragments within a sample and the likelihood they will amplify has not been fully described. To address this, we have derived a mathematical equation that relates the distribution profile of a stochastically fragmented DNA sample to the probability that a DNA fragment within that sample can be amplified by any PCR assay of arbitrary length. Two panels of multiplex PCR assays for quantifying fragmented DNA were then developed: a four-plex panel that can be applied to any human DNA sample and used to estimate the percentage of regions that are intact at any length; and a two-plex panel optimized for quantifying circulating cell-free DNA (cfDNA). For these assays, regions of the human genome least affected by copy number aberration were identified and selected; within these copy-neutral regions, each PCR assay was designed to amplify both genomic and bisulfite-converted DNA; and all assays were validated for use in both conventional qPCR and droplet-digital PCR. Finally, using the cfDNA-optimized assays we find evidence of universally conserved nucleosome positioning among individuals.