A novel biomimetic nanoplasmonic sensor for rapid and accurate evaluation of checkpoint inhibitor immunotherapy.

Immune checkpoint inhibitors (ICIs) emerged as promising immunotherapies for cancer treatment, harnessing the patient's immune system to fight and eliminate tumor cells. However, despite their potential and proven efficacies, checkpoint inhibitors still face important challenges such as the tumor heterogeneity and resistance mechanisms, and the complex in vitro testing, which limits their widespread applicability and implementation to treat cancer. To address these challenges, we propose a novel analytical technique utilizing biomimetic label-free nanoplasmonic biosensors for rapid and reliable screening and evaluation of checkpoint inhibitors. We have designed and fabricated a low-density nanostructured plasmonic sensor based on gold nanodisks that enables the direct formation of a functional supported lipid bilayer, which acts as an artificial cell membrane for tumor ligand immobilization. With this biomimetic scaffold, our biosensing approach provides real-time, highly sensitive analysis of immune checkpoint pathways and direct assessment of the blocking effects of monoclonal antibodies in less than 20 min/test. We demonstrate the accuracy of our biomimetic sensor for the study of the programmed cell death protein 1 (PD1) checkpoint pathway, achieving a limit of detection of 6.7 ng/mL for direct PD1/PD-L1 interaction monitoring. Besides, we have performed dose-response inhibition curves for an anti-PD1 monoclonal antibody, obtaining a half maximal inhibitory concentration (IC50) of 0.43 nM, within the same range than those obtained with conventional techniques. Our biomimetic sensor platform combines the potential of plasmonic technologies for rapid label-free analysis with the reliability of cell-based assay in terms of ligand mobility. The biosensor is integrated in a compact user-friendly device for the straightforward implementation in biomedical and pharmaceutical laboratories.

A highly sensitive nanopore platform for measuring RNase A activity.

Ribonuclease A (RNase A) plays significant roles in several physiological and pathological conditions and can be used as a valuable diagnostic biomarker for human diseases such as myocardial infarction and cancer. Hence, it is of great importance to develop a rapid and cost-effective method for the highly sensitive detection of RNase A. The significance of RNase A assay is further enhanced by the growing attention from the biotechnology and pharmaceutical industries to develop RNA-based vaccines and drugs in large part as a result of the successful development of mRNA vaccines in the COVID-19 pandemic. Herein, we report a label-free method for the detection of RNase A by monitoring its proteolytic cleavage of an RNA substrate in a nanopore. The method is ultra-sensitive with the limit of detection reaching as low as 30 fg per milliliter. Furthermore, sensor selectivity and the effects of temperature, incubation time, metal ion, salt concentration on sensor sensitivity were also investigated.

Validation of a plasmonic-based serology biosensor for veterinary diagnosis of COVID-19 in domestic animals.

The coronavirus disease 2019 (COVID-19) pandemic recently demonstrated the devastating impact on public health, economy, and social development of zoonotic infectious diseases, whereby viruses jump from animals to infect humans. Due to this potential of viruses to cross the species barrier, the surveillance of infectious pathogens circulation in domestic and close-to-human animals is indispensable, as they could be potential reservoirs. Optical biosensors, mainly those based on Surface Plasmon Resonance (SPR), have widely demonstrated its ability for providing direct, label-free, and quantitative bioanalysis with excellent sensitivity and reliability. This biosensor technology can provide a powerful tool to the veterinary field, potentially being helpful for the monitoring of the infection spread. We have implemented a multi-target COVID-19 serology plasmonic biosensor for the rapid testing and screening of common European domestic animals. The multi-target serological biosensor assay enables the detection of total SARS-CoV-2 antibodies (IgG + IgM) generated towards both S and N viral antigens. The analysis is performed in less than 15 min with a low-volume serum sample (<20 µL, 1:10 dilution), reaching a limit of detection of 49.6 ng mL-1. A complete validation has been carried out with hamster, dog, and cat sera samples (N = 75, including 37 COVID-19-positive and 38 negative samples). The biosensor exhibits an excellent diagnostic sensitivity (100 %) and good specificity (71.4 %) for future application in veterinary settings. Furthermore, the biosensor technology is integrated into a compact, portable, and user-friendly device, well-suited for point-of-care testing. This study positions our plasmonic biosensor as an alternative and reliable diagnostic tool for COVID-19 serology in animal samples, expanding the applicability of plasmonic technologies for decentralized analysis in veterinary healthcare and animal research.

Comparative Proteome-wide Characterization of Three Different Tissues of High-Protein Mutant and Wild Type Unravels Protein Accumulation Mechanisms in Rice Seeds.

Improving the proteins and amino acid contents of rice seeds is one of the prime objectives of plant breeders. We recently developed an EMS mutant/high-protein mutant (HPM) of rice that exhibits 14.8% of the total protein content as compared to its parent Dharial (wild-type), which shows only 9.3% protein content in their mature seeds. However, the mechanisms underlying the higher protein accumulation in these HPM seeds remain largely elusive. Here, we utilized high-throughput proteomics to examine the differences in the proteome profiles of the embryo, endosperm, and bran tissues of Dharial and HPM seeds. Utilizing a label-free quantitative proteomic and subsequent functional analyses of the identified proteins revealed that nitrogen compound biosynthesis, intracellular transport, protein/amino acid synthesis, and photosynthesis-related proteins were specifically enriched in the endosperm and bran of the high-protein mutant seed. Our data have uncovered proteome-wide changes highlighting various functions of metabolic pathways associated with protein accumulation in rice seeds.

Substantial dimerized G-quadruplex signal units engineered by cutting-mediated exponential rolling circle amplification for ultrasensitive and label-free detection of exosomes.

Sensitive and accurate determination of tumor-derived exosomes from complicated biofluids is an important prerequisite for early tumor diagnosis through exosome-based liquid biopsy. Herein, a label-free fluorescence immunoassay protocol for ultrasensitive detection of exosomes was developed by engineering substantial dimerized guanine-quadruplex (Dimer-G4) signal units via in situ cutting-mediated exponential rolling circle amplification (CM-ERCA). First, exosomes were captured and enriched via immunomagnetic separation. Then, molecular recognition was built by the formation of antibody-aptamer sandwich immunocomplex through the specific binding of the designed aptamer-primers with the targeted exosomes. The accuracy of exosome detection was significantly improved by the specific recognition of two typical exosomal protein markers simultaneously. Eventually, in situ CM-ERCA was triggered by a perfect match between the multifunctional circular DNA template and the aptamer-primer on exosomal surface. Amplicons of CM-ERCA loaded with Dimer-G4 were exponentially accumulated during continuous cyclic amplification, dramatically lighting up the thioflavin T (ThT) and generating substantial Dimer-G4 signal units. As a result, ultrasensitive detection of exosomes with the detection limit down to 2.4 × 102 particles/mL was achieved due to the fluorescence enhancement of substantial Dimer-G4 signal units, which is ahead of most of available fluorescence-based methods reported currently. In addition, the intense fluorescence emission and favorable anti-interference of the proposed immunoassay supports identification of exosomes direct in human serums, overcoming the limitations of conventional G4/ThT in serum analysis and revealing its potential for exosome-based liquid biopsy.

Selectable encapsulated cell quantity in droplets via label-free electrical screening and impedance-activated sorting.

Single-cell encapsulation in droplets has become a powerful tool in immunotherapy, medicine discovery, and single-cell analysis, thanks to its capability for cell confinement in picoliter volumes. However, the purity and throughput of single-cell droplets are limited by random encapsulation process, which resuts in a majority of empty and multi-cells droplets. Herein we introduce the first label-free selectable cell quantity encapsulation in droplets sorting system to overcome this problem. The system utilizes a simple and reliable electrical impedance based screening (98.9% of accuracy) integrated with biocompatible acoustic sorting to select single-cell droplets, achieving 90.3% of efficiency and up to 200 â€‹Hz of throughput, by removing multi-cells (∼60% of rejection) and empty droplets (∼90% of rejection). We demonstrate the use of the droplet sorting to improve the throughput of single-cell encapsulation by ∼9-fold compared to the conventional random encapsulation process.

Biomimetic nanoplasmonic sensor for rapid evaluation of neutralizing SARS-CoV-2 monoclonal antibodies as antiviral therapy.

Monoclonal antibody (mAb) therapy is one of the most promising immunotherapies that have shown the potential to prevent or neutralize the effects of COVID-19 in patients at very early stages, with a few formulations recently approved by the European and American medicine agencies. However, a main bottleneck for their general implementation resides in the time-consuming, laborious, and highly-specialized techniques employed for the manufacturing and assessing of these therapies, excessively increasing their prices and delaying their administration to the patients. We propose a biomimetic nanoplasmonic biosensor as a novel analytical technique for the screening and evaluation of COVID-19 mAb therapies in a simpler, faster, and reliable manner. By creating an artificial cell membrane on the plasmonic sensor surface, our label-free sensing approach enables real-time monitoring of virus-cell interactions as well as direct analysis of antibody blocking effects in only 15 min assay time. We have achieved detection limits in the 102 TCID50/mL range for the study of SARS-CoV-2 viruses, which allows to perform neutralization assays by only employing a low-volume sample with common viral loads. We have demonstrated the accuracy of the biosensor for the evaluation of two different neutralizing antibodies targeting both Delta and Omicron variants of SARS-CoV-2, with half maximal inhibitory concentrations (IC50) determined in the ng/mL range. Our user-friendly and reliable technology could be employed in biomedical and pharmaceutical laboratories to accelerate, cheapen, and simplify the development of effective immunotherapies for COVID-19 and other serious infectious diseases or cancer.

StatsPro: Systematic integration and evaluation of statistical approaches for detecting differential expression in label-free quantitative proteomics.

Quantitative label-free mass spectrometry (MS) is an increasingly powerful technology for profiling thousands of proteins from complex biological samples. One of the primary goals of analyses performed on such proteomics data is to detect differentially expressed proteins (DEPs) under different experimental conditions. Many statistical methods have been developed and assessed for DEP detection in various proteomics studies. However, it remains a challenge for many proteomics scientists to choose an appropriate statistical procedure. Therefore, in this study, we organized 12 common testing algorithms and 6 P-value combination methods and further provided Cohen's d effect size for every protein and three evaluation criteria to help proteomics scientists investigate their influence on DEP detection in a systematic manner. To promote the widespread use of these methods, we developed a user-friendly web tool, StatsPro, and presented two case studies involving label-free quantitative proteomics data obtained using data-dependent acquisition and data-independent acquisition to illustrate its practicability. This tool is freely available in our GitHub repository (https://github.com/YanglabWCH/StatsPro/). SIGNIFICANCE: One of the primary goals of analyses performed on liquid chromatography-mass spectrometry (LC-MS) based proteomics data is to detect differentially expressed proteins (DEPs) under different experimental conditions. Despite of many research efforts have been proposed to detect DEPs, to date, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics scientists to choose an appropriate statistical procedure. Herein, we present a new tool, StatsPro, to enable implementation and evaluation of different statistical methods for proteomics scientists. This tool has two significant advances compared to existing software: a) It integrates up to 18 common statistical approaches (12 statistical tests and 6 P-value combination strategies) and performs Cohen's d effect size systematically for users, moreover, it provides a web-based interface and can be quite conveniently operated by users, even those with less profound computational background. b) It supports three performance evaluation criteria (e.g. number of DEPs, correlation coefficient between P-values and effect sizes, Area under the ROC curve) for users to review the final statistical results, which may guide the method selection for DEPs detection.

Effect of resveratrol on the biofilm formation and physiological properties of avian pathogenic Escherichia coli.

Avian pathogenic Escherichia coli (APEC) is widely distributed, causing great economic losses to the poultry industry. The formation of APEC biofilms causes chronic, persistent, and repeated infections in the clinic, making treatment difficult. Resveratrol is a natural product, which has good health benefits including antimicrobial, anti-inflammatory, and cardiovascular activities. Resveratrol shows efficient inhibition of bacterial biofilm formation. However, a comprehensive understanding of the proteomic properties of APEC treated resveratrol is still lacking. In this study, APEC cells treated by resveratrol were investigated using a label-free differential proteomic method. Several proteins, including those related to a two-component system and chemotaxis, were found to be implicated in APEC biofilm formation. In addition, the physiological properties were significantly changed in terms of purine, pyruvate, and glyoxylate and dicarboxylate metabolism in APEC. Data are available via ProteomeXchange with the identifier PXD025706. We speculated that pyruvate dehydrogenase might be a potential target to inhibit Escherichia coli biofilm formation. Overall, our results indicated that resveratrol inhibits APEC biofilm formation by regulating the levels of proteins in two-component systems, especially chemotaxis proteins. The results showed that resveratrol had a potential application in inhibiting the biofilm formation of APEC. SIGNIFICANCE: This study elucidated the mechanism of resveratrol inhibiting biofilm formation of avian pathogenic Escherichia coli (APEC) based on a label-free differential proteomics. It was indicated that resveratrol inhibits APEC biofilm formation by regulating the levels of proteins in two component systems, especially chemotaxis proteins. Meanwhile, we speculated that pyruvate dehydrogenase might be a potential target to inhibit Escherichia coli biofilm formation. It shows that resveratrol has a potential application prospect in inhibiting the biofilm formation of APEC.

Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response.

Three-quarters of compounds that enter clinical trials fail to make it to market due to safety or efficacy concerns. This statistic strongly suggests a need for better screening methods that result in improved translatability of compounds during the preclinical testing period. Patient-derived organoids have been touted as a promising 3D preclinical model system to impact the drug discovery pipeline, particularly in oncology. However, assessing drug efficacy in such models poses its own set of challenges, and traditional cell viability readouts fail to leverage some of the advantages that the organoid systems provide. Consequently, phenotypically evaluating complex 3D cell culture models remains difficult due to intra- and inter-patient organoid size differences, cellular heterogeneities, and temporal response dynamics. Here, we present an image-based high-content assay that provides object level information on 3D patient-derived tumor organoids without the need for vital dyes. Leveraging computer vision, we segment and define organoids as independent regions of interest and obtain morphometric and textural information per organoid. By acquiring brightfield images at different timepoints in a robust, non-destructive manner, we can track the dynamic response of individual organoids to various drugs. Furthermore, to simplify the analysis of the resulting large, complex data files, we developed a web-based data visualization tool, the Organoizer, that is available for public use. Our work demonstrates the feasibility and utility of using imaging, computer vision and machine learning to determine the vital status of individual patient-derived organoids without relying upon vital dyes, thus taking advantage of the characteristics offered by this preclinical model system.

HologLev: A Hybrid Magnetic Levitation Platform Integrated with Lensless Holographic Microscopy for Density-Based Cell Analysis.

In clinical practice, a variety of diagnostic applications require the identification of target cells. Density has been used as a physical marker to distinguish cell populations since metabolic activities could alter the cell densities. Magnetic levitation offers great promise for separating cells at the single cell level within heterogeneous populations with respect to cell densities. Traditional magnetic levitation platforms need bulky and precise optical microscopes to visualize levitated cells. Moreover, the evaluation process of cell densities is cumbersome, which also requires trained personnel for operation. In this work, we introduce a device (HologLev) as a fusion of the magnetic levitation principle and lensless digital inline holographic microscopy (LDIHM). LDIHM provides ease of use by getting rid of bulky and expensive optics. By placing an imaging sensor just beneath the microcapillary channel without any lenses, recorded holograms are processed for determining cell densities through a fully automated digital image processing scheme. The device costs less than $100 and has a compact design that can fit into a pocket. We perform viability tests on the device by levitating three different cell lines (MDA-MB-231, U937, D1 ORL UVA) and comparing them against their dead correspondents. We also tested the differentiation of mouse osteoblastic (7F2) cells by monitoring characteristic variations in their density. Last, the response of MDA-MB-231 cancer cells to a chemotherapy drug was demonstrated in our platform. HologLev provides cost-effective, label-free, fully automated cell analysis in a compact design that could be highly desirable for laboratory and point-of-care testing applications.

Raman Trapping Microscopy for Non-invasive Analysis of Biological Samples.

Raman microscopy is an emerging tool in biomedicine. It provides label-free and non-invasive analysis of biological cells. Due to its high biochemical specificity, Raman spectroscopy can be used to acquire spectral fingerprints that allow characterizing cells types and states. Here, we present a methodological approach for implementing Raman microscopy in skin cell measurements. Raman spectra can clearly identify keratinocytes, fibroblasts, and melanocytes cells that are involved in the production of autologous skin grafts. Consequently, Raman microscopy is a promising tool that can be used to analyze single cells and to test the quality of therapeutic cell products.

CRISPR-dCas9 powered impedimetric biosensor for label-free detection of circulating tumor DNAs.

Label-free biosensors which can be integrated into lab-on-a-chip platforms have the advantage of using small volumes for rapid and inexpensive measurements contrary to label-based technologies which are often more costly and time-consuming. In this study, graphene oxide screen printed electrodes (GPHOXE) were modified by deactivated Cas9 (dCas9) proteins and synthetic guide RNA (sgRNA) as the biorecognition receptor for label-free detection of circulating tumor DNAs (ctDNA). This was achieved by detection of a tumor related mutation (PIK3CA exon 9 mutation) via sequence-specific recognition followed by electrochemical impedance spectroscopy (EIS) analysis. The biosensor showed high specificity as there was no impedance signal for other ctDNA sequences, even the single nucleotide mismatch. dCas9-sgRNA modified biosensor demonstrated linear detection limits between 2 and 20 nM for 120 bp ctDNA's in 40 s. The calibration curve showed good linearity, LOD was calculated as 0.65 nM and LOQ was calculated as 1.92 nM. Selectivity and repeatability studies were carried out in real blood samples and the recovery was higher than 96%. In conclusion, dCas9-sgRNA was effectively immobilized and optimized on GPHOXE as the selective biorecognition receptor of this ultrafast impedimetric biosensor. The CRISPR-dCas9 powered impedimetric system showed good selectivity, high repeatability and good recovery properties. This is the first literature to report the use of CRISPR/Cas technology as a label-free tool that can be used in an impedimetric system for detection of ctDNA's.

XPO1 is a critical player for bortezomib resistance in multiple myeloma: A quantitative proteomic approach.

Among the blood cancers, 13% mortality is caused by Multiple myeloma (MM) type of hematological malignancy. In spite of therapeutic advances in chemotherapy treatment, still MM remains an incurable disease is mainly due to emergence of chemoresistance. At present time, FDA approved bortezomib is the first line drug for MM treatment. However, like other chemotherapy, MM patients are acquiring resistance against bortezomib. The present study aims to identify and validate bortezomib resistant protein targets in MM using iTRAQ and label free quantitative proteomic approaches. 112 differentially expressed proteins were commonly found in both approaches with similar differential expression pattern. Exportin-1 (XPO1) protein was selected for further validation as its significant high expression was observed in both iTRAQ and label free analysis. Bioinformatic analysis of these common differentially expressed proteins showed a clear cluster of proteins such as SMC1A, RCC2, CSE1, NUP88, NUP50, TPR, HSPA14, DYNLL1, RAD21 and RANBP2 being associated with XPO1. Functional studies like cell count assay, flow cytometry assay and soft agar assay proved that XPO1 knock down in RPMI 8226R cell line results in re-sensitization to bortezomib drug. The mass spectrometry data are available via ProteomeXchange with identifier PXD013859. BIOLOGICAL SIGNIFICANCE: Multiple myeloma (MM) is a type of hematological malignancy which constitutes about 13% of all blood cell related malignancies. Chemoresistance is one of the major obstacles for the successful treatment for MM. Bortezomib is a first proteasome inhibitor drug, widely used in MM treatment. The present study aims to identify and validate bortezomib resistant protein targets in MM. Here, we identified 112 candidate proteins to be associated with bortezomib resistance using global quantitative proteomic analysis. Among these candidate proteins, we show that XPO1 plays crucial role in emerging bortezomib resistance using functional studies like cell count assay, flow cytometry assay and soft agar assay. XPO1 could be a potential therapeutic target for MM and development of inhibitors of XPO1 might help to cure MM.

Raman spectroscopy for the diagnosis of unlabeled and unstained histopathological tissue specimens.

AIM: To investigate the possibility of diagnosing gastric cancer from an unstained pathological tissue using Raman spectroscopy, and to compare the findings to those obtained with conventional histopathology. METHODS: We produced two consecutive tissue specimens from areas with and without cancer lesions in the surgically resected stomach of a patient with gastric cancer. One of the two tissue specimens was stained with hematoxylin and eosin and used as a reference for laser irradiation positioning by the spectroscopic method. The other specimen was left unstained and used for Raman spectroscopy analysis. RESULTS: A significant Raman scattering spectrum could be obtained at all measurement points. Raman scattering spectrum intensities of 725 cm-1 and 782 cm-1, are associated with the nucleotides adenine and cytosine, respectively. The Raman scattering spectrum intensity ratios of 782 cm-1/620 cm-1, 782 cm-1/756 cm-1, 782 cm-1/1250 cm-1, and 782 ​​cm-1/1263 cm-1 in the gastric adenocarcinoma tissue were significantly higher than those in the normal stomach tissue. CONCLUSION: The results of this preliminary experiment suggest the feasibility of our spectroscopic method as a diagnostic tool for gastric cancer using unstained pathological specimens.

In vivo cytological and chemical analysis of Casparian strips using stimulated Raman scattering microscopy.

The Casparian strip, a barrier to the apoplastic movement of solutes from the cortex to the stele, is essential for the exclusion of salts, selective nutrient uptake, and many other processes. To date, extensive studies have focused on the physiological functions of endodermal Casparian strips. However, the chemical deposition nature of Casparian strips, as well as its relevance with respect to diffusion barrier functions, remains to be further elucidated. Here, we revealed three developmental stages of Casparian strips in maize primary roots using a traditional fluorescent staining method. Apoplastic permeability tests demonstrated that the barrier function of Casparian strips is largely related to their developmental stage and the pattern of lignin and suberin deposits. Fourier transform infrared (FTIR) analysis showed that the Casparian strips from the roots exhibited significant absorption bands characteristic of lignin and suberin, implying that the Casparian strips in maize primary roots consist largely of lignin and suberin. Furthermore, we developed a new method for label-free, in vivo structural, and biochemical analysis of Casparian strips based on stimulated Raman scattering (SRS) microscopy. Using SRS microscopy, we found that lignin and suberin accumulate simultaneously during the Casparian strip formation process. Based on these results, we propose a potential application of SRS for the chemical composition analysis of plant Casparian strips in situ.

Characterizing rapid, activity-linked conformational transitions in proteins via sub-second hydrogen deuterium exchange mass spectrometry.

This review outlines the application of time-resolved electrospray ionization mass spectrometry (TRESI-MS) and hydrogen-deuterium exchange (HDX) to study rapid, activity-linked conformational transitions in proteins. The method is implemented on a microfluidic chip which incorporates all sample-handling steps required for a 'bottom-up' HDX workflow: a capillary mixer for sub-second HDX labeling, a static mixer for HDX quenching, a microreactor for rapid protein digestion, and on-chip electrospray. By combining short HDX labeling pulses with rapid digestion, this approach provides a detailed characterization of the structural transitions that occur during protein folding, ligand binding, post-translational modification and catalytic turnover in enzymes. This broad spectrum of applications in areas largely inaccessible to conventional techniques means that microfluidics-enabled TRESI-MS/HDX is a unique and powerful approach for investigating the dynamic basis of protein function.