Plasmonic nanoshells enhanced laser desorption/ionization mass spectrometry for detection of serum metabolites

High-Throughput Metabolic Pattern Screening Strategy for Early Colorectal and Gastric Cancers Based on Covalent Organic Frameworks-Assisted Laser Desorption/Ionization Mass Spectrometry

Precise early diagnosis and staging are conducive to improving the prognosis of colorectal cancer (CRC) and gastric cancer (GC) patients. However, due to intrusive inspections and limited sensitivity, the prevailing diagnostic methods impede precisely large-scale screening. In this work, we reported a high-throughput serum metabolic patterns (SMP) screening strategy based on covalent organic frameworks-assisted laser desorption/ionization mass spectrometry (hf-COFsLDI-MS) for early diagnosis and staging of CRC and GC. Notably, 473 high-quality SMP were extracted without any tedious sample pretreatment and coupled with multiple machine learning algorithms; the area under the curve (AUC) value is 0.938 with 96.9% sensitivity for early CRC diagnosis, and the AUC value is 0.974 with 100% sensitivity for early GC diagnosis. Besides, the discrimination of CRC and GC is accomplished with an AUC value of 0.966 for the validation set. Also, the screened-out features were identified by MS/MS experiments, and 8 metabolites were identified as the biomarkers for CRC and GC. Finally, the corresponding disordered metabolic pathways were revealed, and the staging of CRC and GC was completed. This work provides an alternative high-throughput screening strategy for CRC and GC and highlights the potential of metabolic molecular diagnosis in clinical applications.

Plasmonic Alloys Enhanced Metabolic Fingerprints for the Diagnosis of COPD and Exacerbations

Accurate diagnosis of chronic obstructive pulmonary disease (COPD) and exacerbations by metabolic biomarkers enables individualized treatment. Advanced metabolic detection platforms rely on designed materials. Here, we design mesoporous PdPt alloys to characterize metabolic fingerprints for diagnosing COPD and exacerbations. As a result, the optimized PdPt alloys enable the acquisition of metabolic fingerprints within seconds, requiring only 0.5 μL of native plasma by laser desorption/ionization mass spectrometry owing to the enhanced electric field, photothermal conversion, and photocurrent response. Machine learning decodes metabolic profiles acquired from 431 individuals, achieving a precise diagnosis of COPD with an area under the curve (AUC) of 0.904 and an accurate distinction between stable COPD and acute exacerbations of COPD (AECOPD) with an AUC of 0.951. Notably, eight metabolic biomarkers identified accurately discriminate AECOPD from stable COPD while providing valuable information on disease progress. Our platform will offer an advanced nanoplatform for the management of COPD, complementing standard clinical techniques.

Plasmonic Fluorescence Enhancement in Diagnostics for Clinical Tests at Point-of-Care: A Review of Recent Technologies

Fluorescence-based biosensors have widely been used in the life-sciences and biomedical applications due to their low limit of detection and a diverse selection of fluorophores that enable simultaneous measurements of multiple biomarkers. Recent research effort has been made to implement fluorescent biosensors into the exploding field of point-of-care testing (POCT), which uses cost-effective strategies for rapid and affordable diagnostic testing. However, fluorescence-based assays often suffer from their feeble signal at low analyte concentrations, which often requires sophisticated, costly, and bulky instrumentation to maintain high detection sensitivity. Metal- and metal oxide-based nanostructures offer a simple solution to increase the output signal from fluorescent biosensors due to the generation of high field enhancements close to a metal or metal oxide surface, which has been shown to improve the excitation rate, quantum yield, photostability, and radiation pattern of fluorophores. This article provides an overview of existing biosensors that employ various strategies for fluorescence enhancement via nanostructures and have demonstrated the potential for use as POCT. Biosensors using nanostructures such as planar substrates, freestanding nanoparticles, and metal-dielectric-metal nanocavities are discussed with an emphasis placed on technologies that have shown promise towards POCT applications without the need for centralized laboratories.

An efficient Pt@MXene platform for the analysis of small-molecule natural products

Small-molecule (m/z<500) natural products have rich biological activity and significant application value thus need to be effectively detected. Surface-assisted laser desorption/ionization mass spectrometry (SALDI MS) has become a powerful detection tool for small-molecule analysis. However, more efficient substrates need to be developed to improve the efficiency of SALDI MS. Thus, platinum nanoparticle-decorated Ti₃C₂ MXene (Pt@MXene) was synthesized in this study as an ideal substrate for SALDI MS in positive ion mode and exhibited excellent performance for the high-throughput detection of small molecules. Compared with using MXene, GO, and CHCA matrix, a stronger signal peak intensity and wider molecular coverage was obtained using Pt@MXene in the detection of small-molecule natural products, with a lower background, excellent salt and protein tolerance, good repeatability, and high detection sensitivity. The Pt@MXene substrate was also successfully used to quantify target molecules in medicinal plants. The proposed method has potentially wide application.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

Nuclear Receptor NR1D1 Regulates Abdominal Aortic Aneurysm Development by Targeting the Mitochondrial Tricarboxylic Acid Cycle Enzyme Aconitase-2

BACKGROUND

Metabolic disorder increases the risk of abdominal aortic aneurysm (AAA). NRs (nuclear receptors) have been increasingly recognized as important regulators of cell metabolism. However, the role of NRs in AAA development remains largely unknown.

METHODS

We analyzed the expression profile of the NR superfamily in AAA tissues and identified NR1D1 (NR subfamily 1 group D member 1) as the most highly upregulated NR in AAA tissues. To examine the role of NR1D1 in AAA formation, we used vascular smooth muscle cell (VSMC)-specific, endothelial cell-specific, and myeloid cell-specific conditional Nr1d1 knockout mice in both AngII (angiotensin II)- and CaPO₄-induced AAA models.

RESULTS

Nr1d1 gene expression exhibited the highest fold change among all 49 NRs in AAA tissues, and NR1D1 protein was upregulated in both human and murine VSMCs from AAA tissues. The knockout of Nr1d1 in VSMCs but not endothelial cells and myeloid cells inhibited AAA formation in both AngII- and CaPO₄-induced AAA models. Mechanistic studies identified ACO2 (aconitase-2), a key enzyme of the mitochondrial tricarboxylic acid cycle, as a direct target trans-repressed by NR1D1 that mediated the regulatory effects of NR1D1 on mitochondrial metabolism. NR1D1 deficiency restored the ACO2 dysregulation and mitochondrial dysfunction at the early stage of AngII infusion before AAA formation. Supplementation with αKG (α-ketoglutarate, a downstream metabolite of ACO2) was beneficial in preventing and treating AAA in mice in a manner that required NR1D1 in VSMCs.

CONCLUSIONS

Our data define a previously unrecognized role of nuclear receptor NR1D1 in AAA pathogenesis and an undescribed NR1D1-ACO2 axis involved in regulating mitochondrial metabolism in VSMCs. It is important that our findings suggest αKG supplementation as an effective therapeutic approach for AAA treatment.

Nanomaterials-assisted metabolic analysis toward in vitro diagnostics

In vitro diagnostics (IVD) has played an indispensable role in healthcare system by providing necessary information to indicate disease condition and guide therapeutic decision. Metabolic analysis can be the primary choice to facilitate the IVD since it characterizes the downstream metabolites and offers real-time feedback of the human body. Nanomaterials with well-designed composition and nanostructure have been developed for the construction of high-performance detection platforms toward metabolic analysis. Herein, we summarize the recent progress of nanomaterials-assisted metabolic analysis and the related applications in IVD. We first introduce the important role that nanomaterials play in metabolic analysis when coupled with different detection platforms, including electrochemical sensors, optical spectrometry, and mass spectrometry. We further highlight the nanomaterials-assisted metabolic analysis toward IVD applications, from the perspectives of both the targeted biomarker quantitation and untargeted fingerprint extraction. This review provides fundamental insights into the function of nanomaterials in metabolic analysis, thus facilitating the design of next-generation diagnostic devices in clinical practice.

Serum Metabolic Fingerprints on Bowl-Shaped Submicroreactor Chip for Chemotherapy Monitoring

Chemotherapy is a primary cancer treatment strategy, the monitoring of which is critical to enhancing the survival rate and quality of life of cancer patients. However, current chemotherapy monitoring mainly relies on imaging tools with inefficient sensitivity and radiation invasiveness. Herein, we develop the bowl-shaped submicroreactor chip of Au-loaded 3-aminophenol formaldehyde resin (denoted as APF-bowl&Au) with a specifically designed structure and Au loading content. The obtained APF-bowl&Au, used as the matrix of laser desorption/ionization mass spectrometry (LDI MS), possesses an enhanced localized electromagnetic field for strengthened small metabolite detection. The APF-bowl&Au enables the extraction of serum metabolic fingerprints (SMFs), and machine learning of the SMFs achieves chemotherapy monitoring of ovarian cancer with area-under-the-curve (AUC) of 0.81-0.98. Furthermore, a serum metabolic biomarker panel is preliminarily identified, exhibiting gradual changes as the chemotherapy cycles proceed. This work provides insights into the development of nanochips and contributes to a universal detection platform for chemotherapy monitoring.

Multiplexed nanomaterial-assisted laser desorption/ionization for pan-cancer diagnosis and classification

As cancer is increasingly considered a metabolic disorder, it is postulated that serum metabolite profiling can be a viable approach for detecting the presence of cancer. By multiplexing mass spectrometry fingerprints from two independent nanostructured matrixes through machine learning for highly sensitive detection and high throughput analysis, we report a laser desorption/ionization (LDI) mass spectrometry-based liquid biopsy for pan-cancer screening and classification. The Multiplexed Nanomaterial-Assisted LDI for Cancer Identification (MNALCI) is applied in 1,183 individuals that include 233 healthy controls and 950 patients with liver, lung, pancreatic, colorectal, gastric, thyroid cancers from two independent cohorts. MNALCI demonstrates 93% sensitivity at 91% specificity for distinguishing cancers from healthy controls in the internal validation cohort, and 84% sensitivity at 84% specificity in the external validation cohort, with up to eight metabolite biomarkers identified. In addition, across those six different cancers, the overall accuracy for identifying the tumor tissue of origin is 92% in the internal validation cohort and 85% in the external validation cohort. The excellent accuracy and minimum sample consumption make the high throughput assay a promising solution for non-invasive cancer diagnosis.

As cancer is increasingly considered a metabolic disorder, it is postulated that serum metabolite profiling can be a viable approach for detecting the presence of cancer. Here, the authors report a machine learning model using mass spectrometry-based liquid biopsy data for pan-cancer screening and classification.

Utilizing AgNPt-SALDI to Classify Edible Oils by Multivariate Statistics of Triacylglycerol Profile

Edible oils are valuable sources of nutrients, and their classification is necessary to ensure high quality, which is essential to food safety. This study reports the establishment of a rapid and straightforward SALDI-TOF MS platform used to detect triacylglycerol (TAG) in various edible oils. Silver nanoplates (AgNPts) were used to optimize the SALDI samples for high sensitivity and reproducibility of TAG signals. TAG fingerprints were combined with multivariate statistics to identify the critical features of edible oil discrimination. Eleven various edible oils were discriminated using principal component analysis (PCA). The results suggested the creation of a robust platform that can examine food adulteration and food fraud, potentially ensuring high-quality foods and agricultural products.

Engineering of nanomaterials for mass spectrometry analysis of biomolecules

Mass spectrometry (MS) based analysis has received intense attention in diverse biological fields. However, direct MS interrogation of target biomolecules in complex biological samples is still challenging, due to the extremely low abundance and poor ionization potency of target biological species. Innovations in nanomaterials create new auxiliary tools for deep and comprehensive MS characterization of biomolecules. More recently, growing research interest has been directed to the compositional and structural engineering of nanomaterials for enriching target biomolecules prior to MS analysis, enhancing the ionization efficiency in MS detection and designing biosensing nanoprobes in sensitive MS readout. In this review, we mainly focus on the recent advances in the engineering of nanomaterials towards their applications in sample pre-treatment, desorption/ionization matrices and ion signal amplification for MS profiling of biomolecules. This review will provide a toolbox of nanomaterials for researchers devoted to developing analytical methods and practical applications in the biological MS field.

Material-assisted mass spectrometric analysis of low molecular weight compounds for biomedical applications

Low molecular weight compounds play an important role in encoding the current physiological state of an individual. Laser desorption/ionization mass spectrometry (LDI MS) offers high sensitivity with low cost for molecular detection, but it is not able to cover small molecules due to the drawbacks of the conventional matrix. Advanced materials are better alternatives, showing little background interference and high LDI efficiency. Herein, we first classify the current materials with a summary of compositions and structures. Matrix preparation protocols are then reviewed, to enhance the selectivity and reproducibility of MS data better. Finally, we highlight the biomedical applications of material-assisted LDI MS, at the tissue, bio-fluid, and cellular levels. We foresee that the advanced materials will bring far-reaching implications in LDI MS towards real-case applications, especially in clinical settings.

Nanocomposite-Based Matrices in Laser Desorption/Ionization Mass Spectrometry for Small-Molecule Analysis

The efficient detection of small molecules is of significance for environmental monitoring, pharmacology, metabolomics, and lipidomics. The laser desorption/ionization mass spectrometry (LDI MS) platform enables high sensitivity, accuracy, resolution, and throughput in molecular analysis, but its analytical capability with respect to small molecules is limited due to inherent drawbacks arising from conventional organic matrices. The selection of an appropriate matrix is thus a precondition for small molecule detection by LDI MS. To date, various inorganic matrices have been developed, with a growing interest in composite materials displaying synergetic effects. This Minireview highlights the development of nanocomposites as LDI matrices driven by numerous innovations in material science, and their emerging use in small-molecule analysis.

Sustainable Carbon Materials toward Emerging Applications

It is desirable for a sustainable society that the production and utilization of renewable materials are net-zero in terms of carbon emissions. Carbon materials with emerging applications in CO₂ utilization, renewable energy storage and conversion, and biomedicine have attracted much attention both academically and industrially. However, the preparation process of some new carbon materials suffers from energy consumption and environmental pollution issues. Therefore, the development of low-cost, scalable, industrially and economically attractive, sustainable carbon material preparation methods are required. In this regard, the use of biomass and its derivatives as a precursor of carbon materials is a major feature of sustainability. Recent advances in the synthetic strategy of sustainable carbon materials and their emerging applications are summarized in this short review. Emphasis is made on the discussion of the original intentions and various sustainable strategies for producing sustainable carbon materials. This review provides basic insights and significant guidelines for the further design of sustainable carbon materials and their emerging applications in catalysis and the biomedical field.

Plasmonic Alloys Reveal a Distinct Metabolic Phenotype of Early Gastric Cancer

Gastric cancer (GC) is a multifactorial process, accompanied by alterations in metabolic pathways. Non-invasive metabolic profiling facilitates GC diagnosis at early stage leading to an improved prognostic outcome. Herein, mesoporous PdPtAu alloys are designed to characterize the metabolic profiles in human blood. The elemental composition is optimized with heterogeneous surface plasmonic resonance, offering preferred charge transfer for photoinduced desorption/ionization and enhanced photothermal conversion for thermally driven desorption. The surface structure of PdPtAu is further tuned with controlled mesopores, accommodating metabolites only, rather than large interfering compounds. Consequently, the optimized PdPtAu alloy yields direct metabolic fingerprints by laser desorption/ionization mass spectrometry in seconds, consuming 500 nL of native plasma. A distinct metabolic phenotype is revealed for early GC by sparse learning, resulting in precise GC diagnosis with an area under the curve of 0.942. It is envisioned that the plasmonic alloy will open up a new era of minimally invasive blood analysis to improve the surveillance of cancer patients in the clinical setting.

High throughput analysis and quantitation of α-dicarbonyls in biofluid by plasmonic nanoshells enhanced laser desorption/ionization mass spectrometry

Advanced analytical platforms are required for accurate detection and quantification of small molecular substances exhibiting certain toxicity. Small molecules detection in complex biological fluids are challenged by the complexity of the samples and the low throughput of the existing methods. In the present study, to detect a batch of samples (50) in 1 h, the plasmonic nanoshell enhanced matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS) was tested. The limit of quantification (LOQ) was determined as 0.01 μg/mL (for α-dicarbonyl compounds) by vortex-assisted liquid-liquid microextraction (VALLME). The developed method can be adopted to study the high-throughput metabolomics and employed for clinical precision diagnosis with MALDI-TOF MS.

Recent development of nanoparticle-assisted metabolites analysis with mass spectrometry

Metabolomics systematically studies the changes of metabolites in biological systems in the temporal or spatial dimensions. It is a challenging task for comprehensive analysis of metabolomics because of diverse physicochemical properties and wide concentration distribution of metabolites. Used as enrichment sorbents, chemoselective probes, chromatographic stationary phases, MS ionization matrix, nanomaterials play excellent roles in improving the selectivity, separation performance, detection sensitivity and identification efficiency of metabolites when mass spectrometry is employed as the detection technique. This review summarized the recent development of nanoparticle-assisted metabolites analysis in terms of assisting the pretreatment of biological samples, improving the separation performance and enhancing the MALDI-MS detection.

Zirconia Hybrid Nanoshells for Nutrient and Toxin Detection

Monitoring milk quality is of fundamental importance in food industry, because of the nutritional value and resulting position of milk in daily diet. The detection of small nutrients and toxins in milk is challenging, considering high sample complexity and low analyte abundance. In addition, the slow analysis and tedious sample preparation hinder the large-scale application of conventional detection techniques. Herein, zirconia hybrid nanoshells are constructed to enhance the performance of laser desorption/ionization mass spectrometry (LDI MS). Zirconia nanoshells with the optimized structures and compositions are used as matrices in LDI MS and achieve direct analysis of small molecules from 5 nL of native milk in ≈1 min, without any purification or separation. Accurate quantitation of small nutrient is achieved by introducing isotope into the zirconia nanoshell-assisted LDI MS as the internal standard, offering good consistency to biochemical analysis (BCA) with R²  = 0.94. Further, trace toxin is enriched and identified with limit-of-detection (LOD) down to 4 pm, outperforming the current analytical methods. This work sheds light on the personalized design of material-based tool for real-case bioanalysis and opens up new opportunities for the simple, fast, and cost-effective detection of various small molecules in a broad field.

A Biomimetic Plasmonic Nanoreactor for Reliable Metabolite Detection

Reliable monitoring of metabolites in biofluids is critical for diagnosis, treatment, and long-term management of various diseases. Although widely used, existing enzymatic metabolite assays face challenges in clinical practice primarily due to the susceptibility of enzyme activity to external conditions and the low sensitivity of sensing strategies. Inspired by the micro/nanoscale confined catalytic environment in living cells, the coencapsulation of oxidoreductase and metal nanoparticles within the nanopores of macroporous silica foams to fabricate all-in-one bio-nanoreactors is reported herein for use in surface-enhanced Raman scattering (SERS)-based metabolic assays. The enhancement of catalytical activity and stability of enzyme against high temperatures, long-time storage or proteolytic agents are demonstrated. The nanoreactors recognize and catalyze oxidation of the metabolite, and provide ratiometric SERS response in the presence of the enzymatic by-product H2O2, enabling sensitive metabolite quantification in a "sample in and answer out" manner. The nanoreactor makes any oxidoreductase-responsible metabolite a candidate for quantitative SERS sensing, as shown for glucose and lactate. Glucose levels of patients with bacterial infection are accurately analyzed with only 20 µL of cerebrospinal fluids, indicating the potential application of the nanoreactor in vitro clinical testing.

Plasmonic tweezers for optical manipulation and biomedical applications

This comprehensive minireview highlights the recent research on the subtypes, optical manipulation, and biomedical applications of plasmonic tweezers.

Urine Metabolic Fingerprints Encode Subtypes of Kidney Diseases

Metabolic fingerprints of biofluids encode diverse diseases and particularly urine detection offers complete non-invasiveness for diagnostics of the future. Present urine detection affords unsatisfactory performance and requires advanced materials to extract molecular information, due to the limited biomarkers and high sample complexity. Herein, we report plasmonic polymer@Ag for laser desorption/ionization mass spectrometry (LDI-MS) and sparse-learning-based metabolic diagnosis of kidney diseases. Using only 1 μL of urine without enrichment or purification, polymer@Ag afforded urine metabolic fingerprints (UMFs) by LDI-MS in seconds. Analysis by sparse learning discriminated lupus nephritis from various other non-lupus nephropathies and controls. We combined UMFs with urine protein levels (UPLs) and constructed a new diagnostic model to characterize subtypes of kidney diseases. Our work guides urine-based diagnosis and leads to new personalized analytical tools for other diseases.

Label-Free Detection of Transferrin Receptor by a Designed Ligand-Protein Sensor

Advanced detection of biomarkers in biofluids plays an important role in disease diagnosis and prognosis. Current techniques with pre-labelling suffer from high cost and complicated operation, etc. Herein, we designed a label-free electrochemical biosensor for rapid detection of transferrin receptor with desirable linear range, sensitivity, specificity, reproducibility, and stability for practical applications.

Janus particles: design, preparation, and biomedical applications

Janus particles with an anisotropic structure have emerged as a focus of intensive research due to their diverse composition and surface chemistry, which show excellent performance in various fields, especially in biomedical applications. In this review, we briefly introduce the structures, composition, and properties of Janus particles, followed by a summary of their biomedical applications. Then we review several design strategies including morphology, particle size, composition, and surface modification, that will affect the performance of Janus particles. Subsequently, we explore the synthetic methodologies of Janus particles, with an emphasis on the most prevalent synthetic method (surface nucleation and seeded growth). Following this, we highlight Janus particles in biomedical applications, especially in drug delivery, bio-imaging, and bio-sensing. Finally, we will consider the current challenges the materials face with perspectives in the future directions.

Design of Hierarchical Beads for Efficient Label-Free Cell Capture

Defined hierarchical materials promise cell analysis and call for application-driven design in practical use. The further issue is to develop advanced materials and devices for efficient label-free cell capture with minimum instrumentation. Herein, the design of hierarchical beads is reported for efficient label-free cell capture. Silica nanoparticles (size of ≈15 nm) are coated onto silica spheres (size of ≈200 nm) to achieve nanoscale surface roughness, and then the rough silica spheres are combined with microbeads (≈150-1000 µm in diameter) to assemble hierarchical structures. These hierarchical beads are built via electrostatic interaction, covalent bonding, and nanoparticle adherence. Further, after functionalization by hyaluronic acid (HA), the hierarchical beads display desirable surface hydrophilicity, biocompatibility, and chemical/structural stability. Due to the controlled surface topology and chemistry, HA-functionalized hierarchical beads afford high cell capture efficiency up to 98.7% in a facile label-free manner. This work guides the development of label-free cell capture techniques and contributes to the construction of smart interfaces in bio-systems.

Plasmonic-Enhanced Oxygen Reduction Reaction of Silver/Graphene Electrocatalysts

Oxygen reduction reaction (ORR) is of paramount importance in polymer electrolyte membrane fuel cells due to its sluggish kinetics. In this work, a plasmon-induced hot electrons enhancement method is introduced to enhance ORR property of the silver (Ag)-based electrocatalysts. Three types of Ag nanostructures with differently localized surface plasmon resonances have been used as electrocatalysts. The thermal effect of plasmonic-enhanced ORR can be minimized in our work by using graphene as the support of Ag nanoparticles. By tuning the resonance positions and laser power, the enhancement of ORR properties of Ag catalysts has been optimized. Among these catalysts, Ag nanotriangles after excitation show the highest mass activity and reach 0.086 mA/μg_Ag at 0.8 V, which is almost 17 times that of a commercial Pt/C catalyst after the price is accounted. Our results demonstrate that the hot electrons generated from surface plasmon resonance can be utilized for electrochemical reaction, and tuning the resonance positions by light is a promising and viable approach to boost electrochemical reactions.

Design of plasmonic nanomaterials for diagnostic spectrometry

Molecular diagnostics relies on the efficient extraction of biomarker information from the given bio-systems. Plasmonic nanomaterials with tailored structural parameters are promising for the development of biomarker assays due to enrichment effect and signal enhancement. Herein, we overview the recent progress on the development of plasmonic nanomaterials for diagnostic spectrometry, encompassing the interface, mechanism, and application of these materials. For interface, we summarized the types of plasmonic nanomaterials used as interfaces between different materials and light. For mechanism, we descirbe the key parameters (e.g., hot carriers and heat) that characterize the plasmonic effect of materials. For application, we highlighted recent advances in matrix assisted laser desorption/ionization mass spectrometry (MALDI MS) and surface enhanced Raman spectroscopy (SERS) toward precision in in vitro and in vivo diagnostics. We foresee the upcoming era of precision diagnostics by nano-assisted spectrometry methods in both academy and industry, which will require the interest and effort of scientists with diverse backgrounds.

Detection and Inhibition of Bacteria on a Dual-Functional Silver Platform

Detection and inhibition of bacteria are universally required in clinics and daily life for health care. Developing a dual-functional material is challenging and in demand, engaging advanced applications for both defined bioanalysis and targeted biotoxicity. Herein, magnetic silver nanoshells are designed as a multifunctional platform for the detection and inhibition of bacteria. The optimized magnetic silver nanoshells enable direct laser desorption/ionization mass spectrometry based metabolic analysis of bacteria (≈10 µL^-1 ), in complex biofluids. The serum infection process (0-10 h) is monitored by statistics toward clinical classification. Moreover, magnetic silver nanoshells facilitate surface adhesion on bacteria due to nanoscale surface roughness and thus display long-term antibacterial effects. Bacteria metabolism is studied with metabolic biomarkers (e.g., malate and lysine) identified during inhibition, showing cell membrane destruction and dysfunctional protein synthesis mechanisms. This work not only guides the design of material-based approaches for bioanalysis and biotoxicity, but contributes to bacteria-related diagnosis by using specific metabolic biomarkers for sensitive detection and new insights by monitoring metabolomic change of bacteria for antibacterial applications.

A Plasmonic Mass Spectrometry Approach for Detection of Small Nutrients and Toxins

Nutriology relies on advanced analytical tools to study the molecular compositions of food and provide key information on sample quality/safety. Small nutrients detection is challenging due to the high diversity and broad dynamic range of molecules in food samples, and a further issue is to track low abundance toxins. Herein, we developed a novel plasmonic matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxins in complex biological emulsion samples. Silver nanoshells (SiO₂@Ag) with optimized structures were used as matrices and achieved direct analysis of ~ 6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, which is superior to the conventional biochemical method currently in use. The developed approach contributes to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real-case bio-analysis.

Nanoparticle-Assisted Metabolomics

Understanding and harnessing the interactions between nanoparticles and biological molecules is at the forefront of applications of nanotechnology to modern biology. Metabolomics has emerged as a prominent player in systems biology as a complement to genomics, transcriptomics and proteomics. Its focus is the systematic study of metabolite identities and concentration changes in living systems. Despite significant progress over the recent past, important challenges in metabolomics remain, such as the deconvolution of the spectra of complex mixtures with strong overlaps, the sensitive detection of metabolites at low abundance, unambiguous identification of known metabolites, structure determination of unknown metabolites and standardized sample preparation for quantitative comparisons. Recent research has demonstrated that some of these challenges can be substantially alleviated with the help of nanoscience. Nanoparticles in particular have found applications in various areas of bioanalytical chemistry and metabolomics. Their chemical surface properties and increased surface-to-volume ratio endows them with a broad range of binding affinities to biomacromolecules and metabolites. The specific interactions of nanoparticles with metabolites or biomacromolecules help, for example, simplify metabolomics spectra, improve the ionization efficiency for mass spectrometry or reveal relationships between spectral signals that belong to the same molecule. Lessons learned from nanoparticle-assisted metabolomics may also benefit other emerging areas, such as nanotoxicity and nanopharmaceutics.

Plasmonic Janus hybrids for the detection of small metabolites

Janus hybrids with amphiphilic structures were used for the sensitive detection of small metabolites.

Plasmonic silver nanoshells for drug and metabolite detection

In-vitro metabolite and drug detection rely on designed materials-based analytical platforms, which are universally used in biomedical research and clinical practice. However, metabolic analysis in bio-samples needs tedious sample preparation, due to the sample complexity and low molecular abundance. A further challenge is to construct diagnostic tools. Herein, we developed a platform using silver nanoshells. We synthesized SiO2@Ag with tunable shell structures by multi-cycled silver mirror reactions. Optimized nanoshells achieved direct laser desorption/ionization mass spectrometry in 0.5 μL of bio-fluids. We applied these nanoshells for disease diagnosis and therapeutic evaluation. We identified patients with postoperative brain infection through daily monitoring and glucose quantitation in cerebrospinal fluid. We measured drug distribution in blood and cerebrospinal fluid systems and validated the function of blood-brain/cerebrospinal fluid-barriers for pharmacokinetics. Our work sheds light on the design of materials for advanced metabolic analysis and precision diagnostics.Preparation of samples for diagnosis can affect the detection of biomarkers and metabolites. Here, the authors use a silver nanoparticle plasmonics approach for the detection of biomarkers in patients as well as investigate the distribution of drugs in serum and cerebral spinal fluid.