Carbon-Based Nanoparticles and Their Surface-Modified Counterparts as MALDI Matrices

Application and mechanism of Co3O4/Co(OH)2 heterojunctions as matrices for small molecules detection by MALDI-TOF MS

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has emerged as a superior technique for detecting small molecules, owing to the strategic utilization of inorganic nanomaterial matrices. Despite the impressive capabilities of various novel matrices, the underlying interaction mechanisms between inorganic matrices and analytes remain largely unexplored. In this study, we synthesized Co3O4 nanocubes, Co(OH)2 nanosheets, Co3O4/Co(OH)2 heterojunctions, and Co3O4+Co(OH)2 composites via a facile one-pot method. Amino acids were selected as model analytes for performance evaluation. Notably, the Co3O4/Co(OH)2 heterojunctions significantly enhanced signal intensity and lowered detection limits to the parts-per-billion (ppb) level, outperforming Co3O4 nanocubes, Co(OH)2 nanosheets, and Co3O4+Co(OH)2 composites. The detection results for environmental pollutants, especially in solutions containing real samples, highlight the outstanding performance of the heterojunction material as a matrix. Further characterization indicates that the formation of the heterojunction enhances nanoparticle dispersion and promotes the separation of photogenerated electron-hole pairs. Consequently, more photogenerated charge carriers can be transferred to the target analytes, facilitating their charging ability and ultimately enhancing signal intensity in MALDI-TOF MS. These results clearly demonstrate that the enhanced photocatalytic performance directly drives the improvement of MALDI-TOF MS performance, excluding interference from other factors. Thus, this study successfully combines photocatalytic mechanisms with MALDI-TOF MS mechanisms, providing new insights into the enhancement of MALDI-TOF MS performance. Additionally, it offers a new detection method for environmental pollutants.

Hollow Mesoporous Carbon Nanospheres/Ni Hybrids Aid in Metabolic Encoding for COVID-19 Recovery Assessment in Mothers and Fetuses

Metabolite analysis of body fluids is an advanced method for disease diagnosis and status assessment. Laser desorption/ionization-mass spectrometry (LDI-MS) has been widely employed for metabolic analysis due to the fast detection speed and simple sample pretreatment. Here, we designed and synthesized hollow mesoporous carbon nanospheres anchored with Ni (HMCSs/Ni) to simultaneously enhance the ionization and thermal desorption processes of the LDI process owing to their hollow and mesoporous structure, large surface area, and abundant Ni-N bonds. Based on HMCSs/Ni, we built an LDI-MS platform that can be used for metabolic information extraction and achieved the rapid detection (about seconds per sample) of metabolic fingerprints in trace serum samples (∼0.1 μL) without complicated preprocessing procedures. Then, we conducted serum metabolic screening in a cohort of COVID-19-recovered pregnant women. The optimized machine learning model could distinguish recovered pregnant women from uninfected pregnant women based on metabolic features with an AUC value of 0.901. In addition, the model indicates that maternal COVID-19 infection does not significantly affect the metabolic fingerprints of the fetuses. Overall, our work shows the prospect of HMCSs/Ni-assisted LDI-MS in disease recovery assessment and metabolite analysis.

From Nanozymes to Multi-Purpose Nanomaterials: The Potential of Metal-Organic Frameworks for Proteomics Applications

Metal-organic frameworks (MOFs) have the potential to revolutionize the biotechnological and medical landscapes due to their easily tunable crystalline porous structure. Herein, the study presents MOFs' potential impact on proteomics, unveiling the diverse roles MOFs can play to boost it. Although MOFs are excellent catalysts in other scientific disciplines, their role as catalysts in proteomics applications remains largely underexplored, despite protein cleavage being of crucial importance in proteomics protocols. Additionally, the study discusses evolving MOF materials that are tailored for proteomics, showcasing their structural diversity and functional advantages compared to other types of materials used for similar applications. MOFs can be developed to seamlessly integrate into proteomics workflows due to their tunable features, contributing to protein separation, peptide enrichment, and ionization for mass spectrometry. This review is meant as a guide to help bridge the gap between material scientists, engineers, and MOF chemists and on the other side researchers in biology or bioinformatics working in proteomics.

A homogeneous binary matrix assisted laser desorption/ionization time-of-flight mass spectrometry assay for determination of artificial sweeteners in beverages

Artificial sweeteners have been widely used as additives in various beverages. Due to the safety risks associated with artificial sweeteners, it is essential to develop a simple, rapid, and high-throughput method for the analysis of artificial sweeteners. Here, we report a homogeneous binary matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) assay for the simultaneous analysis of sweeteners including aspartame (ASP), neotame (NEO), and advantame (ADV) with a simple dilution step. The combination of nanodiamonds with 2,5-dihydroxybenzoic acid effectively improved the signal response of sweeteners, decreased the background noise, and improved the "spot-to-spot" repeatability. After the optimization, the method exhibits low limits of detection (ASP: 20 nΜ; NEO: 10 nΜ; ADV: 5 nΜ), good linearity (r > 0.995), satisfactory accuracy (96.2-103.0%), and lower RSDs (1.5-5.8%). Finally, the target sweeteners in 17 soft beverages were successfully determined with this method, showing the potential for the routine analysis of artificial sweeteners.

Diagnosis and Biomarker Screening of Endometrial Cancer Enabled by a Versatile Exosome Metabolic Fingerprint Platform

Exosomes have emerged as a revolutionary tool for liquid biopsy (LB), as they carry specific cargo from cells. Profiling the metabolites of exosomes is crucial for cancer diagnosis and biomarker discovery. Herein, we propose a versatile platform for exosomal metabolite assay of endometrial cancer (EC). The platform is based on a nanostructured composite material comprising gold nanoparticle-coated magnetic COF with aptamer modification (Fe3O4@COF@Au-Apt). The unique design and novel synthesis strategy of Fe3O4@COF@Au-Apt provide the material with a large specific surface area, enabling the efficient and specific isolation of exosomes. The exosomes captured Fe3O4@COF@Au-Apt can be directly used as the laser desorption/ionization mass spectrometry (LDI-MS) matrix for rapid exosomal metabolic patterns. By integrating these functionalities into a single platform, the analytical process is simplified, eliminating the need for additional elution steps and minimizing potential sample loss, resulting in large-scale exosomal metabolic fingerprints. Combining with machine learning algorithms on the metabolic patterns, accurate discrimination between endometrial patients (EGs) and benign controls (CGs) was achieved, and the area under the receiver operating characteristic curve of the blind test cohort was 0.924. Confusion matrix analysis of important metabolic fingerprint features further demonstrates the high accuracy of the proposed approach toward EC diagnosis, with an overall accuracy of 94.1%. Moreover, four metabolites, namely, hydroxychalcone, l-acetylcarnitine, elaidic acid, and glutathione, have been identified as potential biomarkers of EC. These results highlight the great value of the integrated exosome metabolic fingerprint platform in facilitating low-cost and high-throughput characterization of exosomal metabolites for cancer diagnosis and biomarker discovery.

Optimization of glycopeptide enrichment techniques for the identification of clinical biomarkers

INTRODUCTION

The identification and characterization of glycopeptides through LC-MS/MS and advanced enrichment techniques are crucial for advancing clinical glycoproteomics, significantly impacting the discovery of disease biomarkers and therapeutic targets. Despite progress in enrichment methods like Lectin Affinity Chromatography (LAC), Hydrophilic Interaction Liquid Chromatography (HILIC), and Electrostatic Repulsion Hydrophilic Interaction Chromatography (ERLIC), issues with specificity, efficiency, and scalability remain, impeding thorough analysis of complex glycosylation patterns crucial for disease understanding.

AREAS COVERED

This review explores the current challenges and innovative solutions in glycopeptide enrichment and mass spectrometry analysis, highlighting the importance of novel materials and computational advances for improving sensitivity and specificity. It outlines the potential future directions of these technologies in clinical glycoproteomics, emphasizing their transformative impact on medical diagnostics and therapeutic strategies.

EXPERT OPINION

The application of innovative materials such as Metal-Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), functional nanomaterials, and online enrichment shows promise in addressing challenges associated with glycoproteomics analysis by providing more selective and robust enrichment platforms. Moreover, the integration of artificial intelligence and machine learning is revolutionizing glycoproteomics by enhancing the processing and interpretation of extensive data from LC-MS/MS, boosting biomarker discovery, and improving predictive accuracy, thus supporting personalized medicine.

Graphite Sheet-Assisted Laser Desorption Ionization-Mass Spectrometry for Small Organic Compound Analysis

Carbon-based nanopowders have been used as ionization materials for laser desorption ionization-mass spectrometry (LDI-MS) and are very efficient at detection in low m/z regions. In this study, we aimed to develop a new sheet-type graphite material that possessed a randomly grooved nanostructured surface consisting of developed sp2-conjugated atomic carbon to facilitate the desorption/ionization of small compounds in LDI-MS. The graphite sheet exhibited higher UV absorption and provided higher ionization efficiency and survival yield in the LDI-MS detection of a thermometer ion, 4-chloro-benzopyridinium, than those of highly oriented graphite plates. These properties demonstrate that the present graphite sheet is suited for use as an LDI-MS material. Graphite sheet-assisted LDI-MS successfully detected various substances, including amino acids, peptides, and polyethylene glycol polymers, with higher ion intensities and less noise than those associated with conventional organic matrix-assisted LDI-MS (MALDI-MS). Furthermore, graphite sheet-assisted LDI-MS analysis provided more peaks (252 peaks) derived from soy sauce than those obtained by MALDI-MS (36 peaks) and required fewer preparation processes (dilution and air-dried) compared with previously established graphite carbon black-assisted LDI-MS (171 peaks) in the positive mode. This study demonstrates that graphite sheet-assisted LDI-MS has the potential for small organic compound analyses in the biomedical and food science fields.

Application of graphite carbon black assisted-laser desorption ionization-mass spectrometry for soy sauce product discrimination

In a previous study, we developed a novel analytical method to directly and simultaneously detect taste- and odor-active compounds using graphite carbon black (GCB)-assisted laser desorption ionization mass spectrometry (LDI-MS). In this study, we aimed to evaluate food quality using a variety of soy sauces using the method to discriminate each product. Graphite carbon black-laser desorption ionization-mass spectrometry allowed the provision of hundreds of MS peaks derived from soy sauces in both positive and negative modes without any tedious sample pretreatments. Principal component analysis using the obtained MS peaks clearly distinguished three soy sauce products based on the manufacturing countries (Japan, China, and India). Moreover, this method identified distinct MS peaks for discrimination, which significantly correlated with their quantitative amounts in the products. Thus, GCB-LDI-MS analysis was established as a simple and rapid technique for food analysis, illustrating the chemical patterns of food products.

2-Hydroxy-5-nitro-3-(trifluoromethyl)pyridine as a Novel Matrix for Enhanced MALDI Imaging of Tissue Metabolites

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which is a label-free imaging technique, determines the spatial distribution and relative abundance of versatile endogenous metabolites in tissues. Meanwhile, matrix selection is generally regarded as a pivotal step in MALDI tissue imaging. This study presents the first report of a novel MALDI matrix, 2-hydroxy-5-nitro-3-(trifluoromethyl)pyridine (HNTP), for the in situ detection and imaging of endogenous metabolites in rat liver and brain tissues by MALDI-MS in positive-ion mode. The HNTP matrix exhibits excellent characteristics, including strong ultraviolet absorption, μm-scale matrix crystals, high chemical stability, low background ion interference, and high metabolite ionization efficiency. Notably, the HNTP matrix also shows superior detection capabilities, successfully showing 185 detectable metabolites in rat liver tissue sections. This outperforms the commonly used matrices of 2,5-dihydroxybenzoic acid and 2-mercaptobenzothiazole, which detect 145 and 120 metabolites from the rat liver, respectively. Furthermore, a total of 152 metabolites are effectively detected and imaged in rat brain tissue using the HNTP matrix, and the spatial distribution of these compounds clearly shows the heterogeneity of the rat brain. The results demonstrate that HNTP is a new and powerful positive-ion mode matrix to enhance the analysis of metabolites in biological tissues by MALDI-MSI.

Assessment of MALDI matrices for the detection and visualization of phosphatidylinositols and phosphoinositides in mouse kidneys through matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI)

Phosphatidylinositols and their phosphorylated derivatives, known as phosphoinositides, are crucial in cellular processes, with their abnormalities linked to various diseases. Thus, identifying and measuring phosphoinositide levels in tissues are crucial for understanding their contributions to cellular processes and disease development. One powerful technique for mapping the spatial distribution of molecules in biological samples is matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). This technique allows for the simultaneous detection and analysis of multiple lipid classes in situ, making it invaluable for unbiased lipidomic studies. However, detecting phosphoinositides with MALDI-MSI is challenging due to their relatively low abundance in tissues and complex matrix effects. Addressing this, our study focused on optimizing matrix selection and thickness for better detection of phosphatidylinositols and their phosphorylated forms in mouse kidney tissues. Various matrices were assessed, including 9AA, DAN, CMBT, and DHA, adjusting their coating to improve ionization efficiency. Our results demonstrate that DAN, DHA, and CMBT matrices produced high-intensity chemical images of phosphatidylinositol distributions within kidney sections. These matrices, particularly DAN, DHA, and CMBT, allowed the identification of even low-abundance phosphoinositides, through tentative identifications. Notably, DAN and DHA served as optimal candidates due to their prominent detection and ability to map a majority of phosphatidylinositol species, while CMBT showed potential detection capability for phosphatidylinositol triphosphate compounds. These findings not only provide valuable insights for future research on the involvement of phosphoinositides in kidney pathophysiology, but also propose the use of the identified optimal matrices, particularly DAN and DHA, as the preferred choices for enhanced detection and mapping of these lipid species in future studies.

Research progress on nanomaterial-based matrices for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis

Matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a novel soft ionization bio-mass spectrometry technology emerging in the 1980s, which can realize rapid detection of non-volatile, highly polar, and thermally unstable macromolecules. However, the analysis of small molecular compounds has been a major problem for MALDI-TOF MS all the time. In the MALDI analysis process based on traditional matrices, large numbers of interference peaks in the low molecular weight area and "sweet spots" phenomenon are produced, so the detection method needs to be further optimized. The promotion of matrix means the improvement of MALDI performance. In recent years, many new nanomaterial-based matrices have been successfully applied to the analysis of small molecular compounds, which makes MALDI applicable to a wider range of detection and useful in more fields such as pharmacy and environmental science. In this paper, the newly developed MALDI matrix categories in recent years are reviewed initially. Meanwhile, the potential applications, advantages and disadvantages of various matrices are analyzed. Finally, the future development prospects of nanomaterial-based matrices are also prospected.

Doped nanomaterial facilitates 3D printing target plate for rapid detection of alkaloids in laser desorption/ionization mass spectrometry

This work aims to rapidly detect toxic alkaloids in traditional Chinese medicines (TCM) using laser desorption ionization mass spectrometry (LDI-MS). We systematically investigated twelve nanomaterials (NMs) as matrices and found that MoS2 and defect-rich-WO3 (D-WO3) were the best NMs for alkaloid detection. MoS2 and D-WO3 can be used directly as matrices dipped onto conventional ground steel target plates. Additionally, they can be conveniently fabricated as three-dimensional (3D) NM plates, where the MoS2 or D-WO3 NM is doped into resin and formed using a 3D printing process. We obtained good quantification of alkaloids using a chemothermal compound as an internal standard and detected related alkaloids in TCM extracts, Fuzi (Aconiti Lateralis Radix Praeparata), Caowu (Aconiti Kusnezoffii Radix), Chuanwu (Aconiti Radix), and Houpo (Magnoliae Officinalis Cortex). The work enabled the advantageous "dip and measure" method, demonstrating a simple and fast LDI-MS approach that achieves clean backgrounds for alkaloid detection. The 3D NM plates also facilitated mass spectrometry imaging of alkaloids in TCMs. This method has potential practical applications in medicine and food safety. Doped nanomaterial facilitates 3D printing target plate for rapid detection of alkaloids in laser desorption/ionization mass spectrometry.

Boron nitride quantum dots-enhanced laser desorption/ionization mass spectrometry analysis and imaging of bisphenol A

Bisphenol A (BPA) displays harmful effects on the human health, including potent endocrine activity and potential impact on the development of cancer. Analysis BPA residues in water and plastic products attracted considerable attention in the past decades. However, dominantly used conventional analysis techniques are unable to directly and non-destructively identify the correct species of BPA in plastic products. Hence, this study demonstrates the effective utilisation of boron nitride quantum dots (BNQDs) as an inorganic matrix in matrix-assisted laser desorption/ionization mass spectrometry analysis and imaging (MALDI-MS & MSI) for BPA. The presence of abundant hydroxyl and amino groups on the BNQDs' surface is favourable for the formation of hydrogen bonds with BPA, and increases their ionization and chemoselectivity. Intriguingly, the BNQDs matrix offers a distinct signal for phenolic hazardous molecules featuring different hydroxyl groups. The method was applied to detect BPA at nanomolar level in environmental water, and also allowed non-destructive and in situ mapping of BPA in plastics and pacifiers. This research provides a novel strategy for adapting nanomaterials as inorganic matrices for analysis of small molecular pollutants in environmentally relevant samples using MALDI-MS & MSI.

Au@BN-enhanced laser desorption/ionization mass spectrometry and imaging for determination of fipronil and its metabolites in food and biological samples

Gold nanoparticles (AuNPs) represent an attractive inorganic matrix for laser desorption/ionization mass spectrometry (LDI-MS) detection of low-molecular-weight analytes; however, their direct use is hindered by severe aggregation. To limit AuNPs aggregation, hexagonal boron nitride nanosheets (h-BNNs) were employed as supports to improve their desorption/ionization efficiency. Thus, Au@BN was synthesized and systematically characterized. It showed low background noise and high sensitivity for LDI-MS of fipronil and its metabolites. Au@BN-assisted LDI-MS was validated using complex samples including blueberry juice, green tea beverage, and fish muscle, achieving low detection limits (0.05-0.20 µg·L^-1 for liquid media, 0.82-1.25 ng·g^-1 for fish muscle), wide linear ranges (0.2-100 µg·L^-1 for liquid media, 3.00-1000 ng·g^-1 for fish muscle), high reproducibility (7.55%-13.7%), and satisfactory recoveries (82.62%-109.1%). Furthermore, spatial distributions of analytes in strawberries and zebrafish were successfully imaged. This strategy allows for the quantitative analysis of other small molecules in complex substrates.