Label-free Platform Research Articles

Label-free GaN HEMT-based biosensing platform for interferon-γ detection

Intracranial injury such as traumatic brain injury is caused by sudden injury to the brain from external mechanical force causing health loss and disability worldwide. The work reports the design and development of a GaN HEMT-based biosensor and system for the detection of IFN-γ for non-invasive detection of TBI. The developed platform can detect and differentiate IFN-γ with a peak sensitivity of 109.08 μA/pg/ml, high specificity, and good reproducibility. The platform offers good linearity with an LOD and LOQ of 6.82 fg/ml and 20.68 fg/ml respectively. The antibody-antigen binding has been confirmed with electrical and FTIR measurement techniques. A comparative analysis of system-level detection with on-chip measurement for validating the proposed readout interface shows a good match and thus confirms the system's suitability for the detection of IFN-γ in clinically relevant concentration ranges. The system level and on-chip measurement show a similar sensitivity of 21.59 μA/pg/ml and 19.05 μA/pg/ml respectively. The proposed platform offers a highly stable biofunctionalization protocol with high specificity and selectivity. Thus, the platform has a good potential for point-of-care system development suitable for on-field and clinical applications.

Label-free and amplification-free viral RNA quantification from primate biofluids using a trapping-assisted optofluidic nanopore platform

Viral outbreaks can cause widespread disruption, creating the need for diagnostic tools that provide high performance and sample versatility at the point of use with moderate complexity. Current gold standards such as PCR and rapid antigen tests fall short in one or more of these aspects. Here, we report a label-free and amplification-free nanopore sensor platform that overcomes these challenges via direct detection and quantification of viral RNA in clinical samples from a variety of biological fluids. The assay uses an optofluidic chip that combines optical waveguides with a fluidic channel and integrates a solid-state nanopore for sensing of individual biomolecules upon translocation through the pore. High specificity and low limit of detection are ensured by capturing RNA targets on microbeads and collecting them by optical trapping at the nanopore location where targets are released and rapidly detected. We use this device for longitudinal studies of the viral load progression for Zika and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections in marmoset and baboon animal models, respectively. The up to million-fold trapping-based target concentration enhancement enables amplification-free RNA quantification across the clinically relevant concentration range down to the assay limit of RT-qPCR as well as cases in which PCR failed. The assay operates across all relevant biofluids, including semen, urine, and whole blood for Zika and nasopharyngeal and throat swab, rectal swab, and bronchoalveolar lavage for SARS-CoV-2. The versatility, performance, simplicity, and potential for full microfluidic integration of the amplification-free nanopore assay points toward a unique approach to molecular diagnostics for nucleic acids, proteins, and other targets.

Dual-functional Au-porous anodic alumina (PAA) sensors for enrichment and label-free detection of airborne virus with surface-enhanced Raman scattering

The development of a rapid and sensitive method for the enrichment and direct detection of airborne viruses has become urgently needed to prevent their spread. We have developed a dual-functional, label-free platform for the enrichment and optical identification of airborne viruses. This platform allows for the on-site enrichment and identification of airborne viruses through a virus enrichment component combined with surface-enhanced Raman scattering (SERS). In this work, we created an Au-porous anodic alumina (PAA) composite film, by ion sputtering Au nanoparticles (Au NPs) on a porous structure. The Au-PAA serves as a dual-functional sensor: it combines ultrafiltration through the vertical nanopores in the PAA for virus enrichment and constitutes a plasmonic substrate due to the surface plasmon near-field enhancements within the nanochannel structure. This sensor demonstrates an extraordinary enrichment efficiency (about 98 %) of obtained bioaerosols and enables simultaneous, sensitive detection at the single-virus level. Finite-difference time-domain (FDTD) simulations evidenced the electric field intensity and charge distribution of the Au-PAA. This Au-PAA composite film offers a powerful system for on-site, label-free viral particle enrichment and SERS detection. Contaminated air containing viruses can be collected in a few minutes and analyzed immediately by our platform, which is particularly beneficial for timely monitoring of viruses in the air of large public spaces. Additionally, this platform can be applied to evaluate the indoor air quality.

Urine proteome profile of firefighters with exposure to emergency fire-induced smoke: A pilot study to identify potential carcinogenic effects

Firefighters are frequently exposed to a variety of chemicals formed from smoke, which pose a risk for numerous diseases, including cancer. Comparative urine proteome profiling could significantly improve our understanding of the early detection of potential cancer biomarkers. In this study, for the first time, we conducted a comparative protein profile analysis of 20 urine samples collected from ten real-life firefighters prior to and following emergency fire-induced smoke. Using a label-free quantitative proteomics platform, we identified and quantified 1325 unique protein groups, of which 45 proteins showed differential expressions in abundance in response to fire-smoke exposure (post) compared to the control (pre). Pathway analysis showed proteins associated with epithelium development (e.g., RHCG, HEG1, ADAMTSL2) and Alzheimer's disease (SORL1) were significantly increased in response to smoke exposure samples. A protein-protein-network study showed a possible link between these differentially abundant proteins and the known cancer gene (TP53). Moreover, a cross-comparison analysis revealed that seven proteins—ALDH1A1, APCS, POMC, COL2A1, RDX, DDAH2, and SDC4 overlapped with the previously published urine cancer proteome datasets, suggesting a potential cancer risk. Our findings demonstrated that the discovery proteomic platform is a promising analytical technique for identifying potential non-invasive biomarkers associated with fire-smoke exposure in firefighters that may be related to cancer.

Abstract 7097: Integrated proteomics and metabolomics reveals new insight into the synergistic interaction of valproic acid plus simvastatin in prostate cancer xenograft model associated with down-modulation of YAP and TAZ signaling

Abstract Background: Despite advancements in therapeutic approaches, including taxane-based chemotherapy and androgen receptor targeting agents, metastatic castration-resistant prostate cancer (mCRPC) remains an incurable disease, underlying the need of novel strategies that can target the complexities of this disease and bypass the development of drug-resistance mechanisms. We previously demonstrated the synergistic antitumor interaction of the antiepileptic with histone deacetylase inhibitory activity valproic acid (VPA), and the lipid-lowering drug simvastatin (SIM). This combination sensitizes mCRPC cells to docetaxel treatment and revert docetaxel-resistance, both in vitro and in vivo models, by targeting cancer stem cells compartment via mevalonate pathway/YAP axis modulation. Methods: Proteomic and metabolomic/lipidomic analysis on tumor samples were performed by LC-MS/MS-based shotgun proteomics and by 1H-NMR approach, respectively. Progenesis QI for proteomics v. 4.2 was used as label-free quantification platform. Functional annotation analysis were performed by using the DAVID v6.8 (Database for Annotation, Visualization and Integrated Discovery); g:Profiler WikiPathways databases; Reactome version 66; Ingenuity Pathway Analysis software. Partial least squares-discriminant analysis (PLS-DA) and Loading plot were performed by Metabo Analyst v5.0 tool. Results: Tumor samples derived from 22Rv1 mCRPC cells xenografted mice, treated or not with VPA/SIM combination were characterized by a combined proteomic and metabolomic/lipidomic approach. In deep bioinformatics analysis confirmed a specific impact of VPA/SIM on Hippo pathway, with a clear down regulation of YAP and its targets (CTGF, CycD1 ANKH1) in treated vs untreated tumors, functionally related with modulation of cancer-related extracellular matrix remodelling and metabolic reprogramming. Treatment also downregulated TEAD transcription factor mediating YAP-induced expression, along with the upregulation of 14-3-3, responsible for YAP cytoplasmic retention and degradation, paralleled by the up-regulation of YAP up-stream negative regulators such as LATS1 and AMPK. VPA/SIM also modulated intermediates of TCA, urea cycles and glycolysis and decreased cholesterol and fatty acids. Conclusion: In summary, this study provides further insights into the molecular mechanism of the VPA/SIM antitumor effect suggesting the potential of repurposing these two generic and safe drugs in combination with standard antitumor therapies also in other tumors besides mCRCP. Citation Format: Federica Iannelli, Rita Lombardi, Susan Costantini, Maria Serena Roca, Laura Addi, Francesca Bruzzese, Elena Di Gennaro, Alfredo Budillon, Biagio Pucci. Integrated proteomics and metabolomics reveals new insight into the synergistic interaction of valproic acid plus simvastatin in prostate cancer xenograft model associated with down-modulation of YAP and TAZ signaling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7097.

Label-Free Single Microparticles and Cell Aggregates Sorting in Continuous Cell-Based Manufacturing.

There is a paradigm shift in biomanufacturing toward continuous bioprocessing but cell-based manufacturing using adherent and suspension cultures, including microcarriers, hydrogel microparticles, and 3D cell aggregates, remains challenging due to the lack of efficient in-line bioprocess monitoring and cell harvesting tools. Herein, a novel label-free microfluidic platform for high throughput (≈50 particles/sec) impedance bioanalysis of biomass, cell viability, and stem cell differentiation at single particle resolution is reported. The device is integrated with a real-time piezo-actuated particle sorter based on user-defined multi-frequency impedance signatures. Biomass profiling of Cytodex-3 microcarriers seeded with adipose-derived mesenchymal stem cells (ADSCs) is first performed to sort well-seeded or confluent microcarriers for downstream culture or harvesting, respectively. Next, impedance-based isolation of microcarriers with osteogenic differentiated ADSCs is demonstrated, which is validated with a twofold increase of calcium content in sorted ADSCs. Impedance profiling of heterogenous ADSCs-encapsulated hydrogel (alginate) microparticles and 3D ADSC aggregate mixtures is also performed to sort particles with high biomass and cell viability to improve cell quality. Overall, the scalable microfluidic platform technology enables in-line sample processing from bioreactors directly and automated analysis of cell quality attributes to maximize cell yield and improve the control of cell quality in continuous cell-based manufacturing.

Development of label-free triboelectric nanosensors as screening platforms for anti-tumor drugs

This study introduces a general label-free drug screening platform with potential to support high-throughput drug screening for any protein target. Its innovation lies in quantifying the affinity of molecule-molecule interactions via voltage output variation, which achieves unprecedented selectivity and sensitivity. It combines computational analysis complemented by experimental substantiation with a solid-liquid triboelectric nanosensor. Owing to its high binding affinity, FKBP-rapamycin is used as a model system to demonstrate the platform's sensitivity. Subsequently, the research is extended to study drug interactions with an oncogenic protein ATG4B. The findings unveil the binding of S130 and Tioconazole to ATG4B, a critical cysteine protease involved in autophagy, while revealing that Dexamethasone does not bind ATG4B. This binding exerts a specific inhibitory effect on autophagic flux and triggers cancer cell apoptosis. The results support the previously verified inhibitory effects of these drugs and the effectiveness of a newly developed self-powered drug screening platform, leveraging the principles of solid-liquid contact electrification. This approach adeptly confronts enduring challenges in traditional drug development methods where biochemical assays need to be designed for each individual protein target or only time-consuming and concentration-demanding molecular interaction measurements were made available.

Bio-Interface Analysis and Detection of Aβ using GaN HEMT-based Biosensor

Early detection, prognosis, and diagnosis of devastating neurological disorders such as TBI and AD are crucial for developing treatment strategies, efficient patient outcomes, and management in biomedical fields. The work reports the design, development, suitability analysis, and validation of a label-free GaN HEMT-based biosensing platform for the non-invasive detection of FDA-approved biomarker Aβ in saliva sample concentration ranges. The biofunctionalization assay has been validated with both electrical and FTIR spectroscopy-based measurements. A comparative analysis with ELISA assay shows good agreement with ∼2.0% measurement errors demonstrating platform stability and accuracy for Aβ detection. The platform offers a peak sensitivity of 27.20 μA/pg ml−1, 19.10 μA pg−1 ml−1, and 1.48 μA/pg ml−1 for detection in saliva, serum, and CSF concentration ranges with high specificity, excellent repeatability, and reproducibility of the results. The platform offers a sensitivity of 2.40 μA/pg ml−1, 15.40 μA pg−1 ml−1, and 27.20 μA/pg ml−1 for Sbias of 1.0 V, 3.3 V, and 5.0 V respectively. The key biosensor features include fast detection with a response time of 5–10 s and a low sample volume requirement of ∼1–2 μl. The platform comparison with ELISA shows a similar and acceptable linearity trend. A novel equation has been established for ELISA and developed platform-based detection for possible detection accuracy and validation useful for correlating the sensor response with ELISA test results and vice-versa for any target Aβ concentrations. To the best of our knowledge, this is the first time reporting of Aβ detection using a GaN HEMT-based biosensing platform.

Pooled CRISPR screening of high-content cellular phenotypes using ghost cytometry

Recent advancements in image-based pooled CRISPR screening have facilitated the mapping of diverse genotype-phenotype associations within mammalian cells. However, the rapid enrichment of cells based on morphological information continues to pose a challenge, constraining the capacity for large-scale gene perturbation screening across diverse high-content cellular phenotypes. In this study, we demonstrate the applicability of multimodal ghost cytometry-based cell sorting, including both fluorescent and label-free high-content phenotypes, for rapid pooled CRISPR screening within vast cell populations. Using the high-content cell sorter operating in fluorescence mode, we successfully executed kinase-specific CRISPR screening targeting genes influencing the nuclear translocation of RelA. Furthermore, using the multiparametric, label-free mode, we performed large-scale screening to identify genes involved in macrophage polarization. Notably, the label-free platform can enrich target phenotypes without requiring invasive staining, preserving untouched cells for downstream assays and expanding the potential for screening cellular phenotypes even when suitable markers are absent.

Label-free colorimetric detection platform based on catalytic hairpin self-assembly and G-quadruplex/hemin DNAzyme for comprehensive biomarker profiling

The expression level of human apurinic/apyrimidinic endonuclease 1 (APE1) is closely associated with the onset of various diseases, establishing it as a crucial clinical biomarker and a target in anti-cancer efforts. This study accomplished colorimetric and visual detection of APE1 by harnessing its endonuclease activity through catalytic hairpin self-assembly (CHA) and G-quadruplex/hemin DNAzyme. Optimization of the freedom degrees of the G-rich sequence significantly improved the detection performance of the strategy by influencing DNAzyme formation. Additionally, we replaced the signal reporting system with a molecular beacon to develop a fluorescence detection strategy, which served as an extension of the signal amplification system for validation and signal readout. The fluorescent probe method achieved a detection limit of 3.37 × 10−4 U/mL, while the colorimetric method yielded a detection limit of 6.5 × 10−3 U/mL, with a linear range spanning from 0.01 to 0.25 U/mL. Subsequently, the colorimetric approach effectively assessed APE1 activity in biological samples and facilitated the screening of APE1 activity inhibitors. Furthermore, this CHA/G-quadruplex/hemin DNAzyme strategy was adapted for the colorimetric detection of adenosine, showcasing its broad applicability across various biomarkers. The developed colorimetric analytical strategy represents a pivotal biosensing platform for diagnosing and treating diseases.

Aptamer Renaissance for Neurochemical Biosensing.

Unraveling the complexities of brain function, which is crucial for advancing human health, remains a grand challenge. This endeavor demands precise monitoring of small molecules such as neurotransmitters, the chemical messengers in the brain. In this Perspective, we explore the potential of aptamers, selective synthetic bioreceptors integrated into electronic affinity platforms to address limitations in neurochemical biosensing. We emphasize the importance of characterizing aptamer thermodynamics and target binding to realize functional biosensors in biological systems. We focus on two label-free affinity platforms spanning the micro- to nanoscale: field-effect transistors and nanopores. Integration of well-characterized structure-switching aptamers overcame nonspecific binding, a challenge that has hindered the translation of biosensors from the lab to the clinic. In a transformative era driven by neuroscience breakthroughs, technological innovations, and multidisciplinary collaborations, an aptamer renaissance holds the potential to bridge technological gaps and reshape the landscape of diagnostics and neuroscience.

Machine learning-assisted image label-free smartphone platform for rapid segmentation and robust multi-urinalysis.

This study presents a groundbreaking approach for the early detection of chronic kidney disease (CKD) and other urological disorders through an image-label-free, multi-dipstick identification method, eliminating the need for complex machinery, label libraries, or preset coordinates. Our research successfully identified reaction pads on 187 multi-dipsticks, each with 11 pads, leveraging machine learning algorithms trained on human urine data. This technique aims to surpass traditional colourimetric methods and concentration-colour curve fitting, offering more robust and precise community screening and home monitoring capabilities. The developed algorithms enhance the generalizability of machine learning models by extracting primary colours and correcting urine colours on each reaction pad. This method's cost-effectiveness and portability are significant, as it requires no additional equipment beyond a standard smartphone. The system's performance rivals professional medical equipment without auxiliary lighting or flash under regular indoor light conditions, effectively managing false positives and negatives across various categories with remarkable accuracy. In a controlled experimental setting, we found that random forest algorithms, based on a Bagging strategy and applied in the HSV colour space, showed optimal results in smartphone-assisted urinalysis. This study also introduces a novel urine colour correction method, significantly improving machine learning model performance. Additionally, ISO parameters were identified as crucial factors influencing the accuracy of smartphone-based urinalysis in the absence of additional lighting or optical configurations, highlighting the potential of this technology in low-resource settings.

Utilizing solid-state nanopore sensing for high-efficiency and precise targeted localization in antiviral drug development.

The efficient identification and validation of drug targets are paramount in drug discovery and development. Excessive costs, intricate procedures, and laborious sample handling frequently encumber contemporary methodologies. In this study, we introduce an innovative approach for the expeditious screening of drug targets utilizing solid-state nanopores. These nanopores provide a label-free, ultra-sensitive, and high-resolution platform for the real-time detection of biomolecular interactions. By observing the changes in relative ion currents over time after mixing different peptides with small molecule drugs, and supplementing this with noise analysis, we can pinpoint specific regions of drug action, thereby enhancing both the speed and cost-efficiency of drug development. This research offers novel insights into drug discovery, expands current perspectives, and lays the groundwork for formulating effective therapeutic strategies across a spectrum of diseases.

A novel label-free capillary electrophoresis LED-induced fluorescence platform based on catalytic hairpin assembly for sensitive detection of multiple circulating tumor DNA.

Circulating tumor DNA (ctDNA) is a highly promising biomarker for the early diagnosis and treatment of gastric cancer (GC). However, there is still a lack of effective and practical ctDNA detection methods. In this work, a simple and economical capillary non-gel sieving electrophoresis-LED induced fluorescence detection (NGCE-LEDIF) platform coupled with catalytic hairpin assembly (CHA) as the signal amplification strategy is proposed for quantitative detection of PIK3CA E542K and TP53 (two types of ctDNA associated with GC). We have reasonably designed two pairs of programmable oligonucleotide hairpin probes for PIK3CA E542K and TP53. Using a one-pot reaction, the presence of ctDNA triggers the cyclic amplification of CHA, forming numerous thermodynamically stable H1/H2 double-strands. The H1/H2 double-stranded DNA catalyzed by PIK3CA E542K and TP53 can be easily separated by NGCE due to their different lengths, enabling simultaneous detection of both ctDNAs. Under optimal experimental conditions, the detection limits of this strategy for detecting GC-related biomarkers PIK3CA E542K and TP53 are 20.35 pM and 19.61 pM, respectively, and can achieve 730-fold signal amplification. This strategy has a good recovery in the serum matrix. The results of this study show that this strategy has significant advantages such as high selectivity, a simple process, no special instruments and equipment, no need for fluorescence modification of hairpin probes in advance, high automation, low cost, and minimal sample consumption. This provides a powerful method for the detection of trace cancer biomarkers in the serum matrix with good application prospects.

Ag nanoisland functionalized hollow carbon nanofibers as a non-invasive, label-free SERS salivary biosensor platform for salivary nitrite detection for pre-diagnosis of oral cancer.

A highly selective, label-free, surface-enhanced Raman spectroscopy (SERS) based sensor platform employing hollow carbon nanofibers functionalized with silver nanoparticles (Ag@HCNFs) has been developed to monitor anomalous concentrations of potential biomarkers, such as salivary nitrite facilitating pre-diagnosis of oral cancer. Co-axial electrospinning was used for the fabrication of the nanofibrous Ag@HCNFs followed by thermal treatment of PAN/PVP core-shell nanofibers and chemical reduction of silver nanoislands. The developed plasmonic Ag@HCNFs was structurally and morphologically characterized using X-Ray diffraction, Raman spectroscopy, scanning electron microscopy, and transmission electron microscopy, which clearly demonstrated the successful anchoring of silver nanoparticles on hollow carbon nanofibers. The properties of Ag@HCNFs showed significant SERS enhancement of the order of 107 with a detection limit of 10-11 M with R6G, demonstrating its efficacy to investigate real-time salivary samples, particularly towards the detection of salivary nitrite within the clinically relevant range (50 μM-300 μM) towards the pre-diagnosis of oral cancer. The proposed SERS-based salivary platform has the potential to be used as a low-cost, non-invasive pre-diagnostic tool for early diagnosis and mass screening of oral cancer.

AuNPs-BP-MWCNTs-COOH-based electrochemical immunosensor for the determination of deoxynivalenol in wheat flour.

Deoxynivalenol (DON) has drawn considerable attention for its obvious pathogenicity and wide use in agro-products, which cause a potential threat to human health. In this work, an electrochemical immunosensor is developed for the highly sensitive and selective detection of DON in wheat flour using AuNPs-BP-MWCNTs-COOH and antibodies. The AuNPs-BP-MWCNTs-COOH nanocomposite was prepared via an in situ reduction reaction and ultrasonic-assisted liquid-phase exfoliation. The nanocomposite exhibits a larger surface area, decent stability, excellent electron transfer capability, good protein binding capability and prominent specificity. The plentiful carboxyl group on the nanocomposite can bind to the amino group of the antibody, and AuNPs have an affinity for the sulfhydryl group of the antibody, which makes it feasible for the nanocomposite to load the antibody. The peak currents are plotted against the logarithm of DON concentration from 0.002 to 80 ng mL-1 with a limit of detection (LOD) of 0.5 pg mL-1. This approach establishes an effective label-free immunosensor platform for the detection of DON with high sensitivity and selectivity in various food and agricultural products.

Carboxyl-functionalized two-dimensional MXene-Au nanocomposites were prepared as SERS substrates for the detection of melamine in dairy products.

In the present study, we address the limitations of conventional surface-enhanced Raman scattering (SERS) techniques for sensitive and stable detection of melamine in food products, especially dairy. To overcome these challenges, we developed a novel SERS-active substrate by incorporating gold nanoparticles (AuNPs) onto carboxyl-functionalized two-dimensional (2D) MXene material doped with nitrides, specifically Au-Ti2N-COOH. Our strategy leverages the unique physicochemical properties of MXene, a class of atomically thin, 2D transition metal carbides/nitrides, with tunable surface functionalities. By modifying the MXene surface with AuNPs and introducing carboxyl groups (-COOH), we successfully enhanced the interaction between the substrate and melamine molecules. The carboxyl groups form hydrogen bonds with the amino groups on the melamine's triazine ring, facilitating the adsorption of melamine molecules within the 'hotspot' regions responsible for SERS signal amplification. A series of characterization methods were used to confirm the successful synthesis of Au-Ti2N-COOH composites.Using Au-Ti2N-COOH as the SERS substrate, we detected melamine in spiked dairy product samples with significantly enhanced sensitivity and stability compared to nitride-doped MXene alone. The detection limit in liquid milk stands at 3.7008 μg kg-1, with spike recovery rates ranging from 99.84% to 107.55% and an approximate RSD of 5%. This work demonstrates the effectiveness of our approach in designing a label-free, rapid, and robust SERS platform for the accurate quantitation of melamine contamination in food, thereby mitigating health risks associated with melamine adulteration.

Activated silver nanoparticle-based platform for specific capture of Porphyromonas gingivalis in human saliva

Porphyromonas gingivalis (P. gingivalis) is the leading causative pathogen for periodontitis and gingivitis. Specific and direct detection of P. gingivalis based on surface-enhanced Raman spectroscopy (SERS) is a challenge, especially in clinical samples. In this paper, we have developed a novel label-free SERS platform to successfully obtain Raman fingerprints of P. gingivalis in simulated and clinical patients. The activated silver nanoparticles was used as the substrate with the addition of reducing agent (sodium borohydride) twice and aggregating agent (Na+) to establish the "hot spot", that accumulated on the surface like the “mask” to capture bacteria. The method broke the bottleneck of poor quantification and low specificity of SERS, and achieved rapid, sensitive, quantifiable and specific determination of bacteria with lower limit, excellent repeatability and stability. Further mechanical learning was combined with effective classification of four different oral bacteria, including P. gingivalis, Enterococcus faecalis (E. faecalis), Staphylococcus aureus (S. aureus) and Streptococcus mutans (S. mutans). The technique could identify P. gingivalis not only in artificial serum, artificial saliva and mixed bacterial samples, but most importantly, enabled non-destructive detection in the saliva of patients with periodontal disease. In addition, antimicrobial experiments have confirmed environmental friendliness that no secondary infections will occur. Therefore, the unlabelled, convenient and green SERS detection tool for oral bacteria holds great potential applications in clinical early diagnosis and prediction disease progression in periodontal disease.

A novel self-assembled dual-emissive ratiometric fluorescent nanoprobe for alkaline phosphatase sensing

BackgroundAlkaline phosphatase (ALP) is widely found in various organs and tissues of the human body which could assist in the verification of the presence of various diseases through its content in the blood. In the past few years, many analytical methods for ALP activity assays have been explored. However, a simple and economical method with high sensitivity and specificity also remains great challenge. Therefore, the development of sensitive and efficient approach for ALP analysis is of great significance in biomedical studies. ResultsHerein, we constructed a highly sensitive and label-free ratiometric fluorometric biosensing platform for the determination of ALP activity, which utilizing lysozyme(Ly)-functionalized 5-methyl-2-thiouracil(MTU)-modified gold nanoclusters (MTU-Ly@Au NC) and poly-dopamine (PDA) as signal indicators. Dopamine (DA) can self-polymerizes to form PDA under alkaline conditions that can further quenched the fluorescence of MTU-Ly@Au NC at 525nm due to fluorescence resonance energy transfer (FRET) and absorption competition quenching (ACQ) effects. In this process, the PDA fluorescence intensity at 325nm was nearly unchanged. After the addition of ALP, ascorbic acid (AA) which can alleviate the self-polymerization process of DA was generated from the substrate ascorbic acid 2-phosphate (AAP), thus changing ratiometric fluorescence intensity of I525/I325. Hence, by monitoring the fluorescence ratio (I525/I325), a ratiometric fluorescence biosensing platform for ALP was established with the linear calibration in the range of 0.5–8 U L−1 and the limit of detection of 0.157 U L−1. SignificanceThis work not only synthesized a novel fluorescence probe with simple preparation and low cost for ALP which has excellent anti-interference properties and selectivity. Furthermore, this biosensing platform was successfully applied for the determination of ALP activity in human serum samples. This work provided a potential tool for biomedical diagnostics in the future.

Quartz Crystal Microbalance Platform for SARS-CoV-2 Immuno-Diagnostics

Rapid and accurate serological analysis of SARS-CoV-2 antibodies is important for assessing immune protection from vaccination or infection of individuals and for projecting virus spread within a population. The quartz crystal microbalance (QCM) is a label-free flow-based sensor platform that offers an opportunity to detect the binding of a fluid-phase ligand to an immobilized target molecule in real time. A QCM-based assay was developed for the detection of SARS-CoV-2 antibody binding and evaluated for assay reproducibility. The assay was cross-compared to the Roche electrochemiluminescence assay (ECLIA) Elecsys® Anti-SARS-CoV-2 serology test kit and YHLO’s chemiluminescence immunoassay (CLIA). The day-to-day reproducibility of the assay had a correlation of r2 = 0.99, p < 0.001. The assay linearity was r2 = 0.96, p < 0.001, for dilution in both serum and buffer. In the cross-comparison analysis of 119 human serum samples, 59 were positive in the Roche, 52 in the YHLO, and 48 in the QCM immunoassay. Despite differences in the detection method and antigen used for antibody capture, there was good coherence between the assays, 80–100% for positive and 96–100% for negative test results. In summation, the QCM-based SARS-CoV-2 IgG immunoassay showed high reproducibility and linearity, along with good coherence with the ELISA-based assays. Still, factors including antibody titer and antigen-binding affinity may differentially affect the various assays’ responses.