Rapid differentiation of xylazine metabolites using SLIM IM-MS.

Xylazine represents an increased threat to the recreational drug market. In this study, we present a rapid strategy for identifying xylazine and differentiating its common isomeric metabolites using Structures for Lossless Ion Manipulations (SLIM) ion mobility coupled to high-resolution/tandem mass spectrometry (IM-HRMS/MS). Chemical derivatization using dansyl chloride also assisted with separations and led to identification of resolvable reaction product atropisomers.

Development of an Analytical Method for Unsaturated Disaccharides from Heparan Sulfate Using Dansylhydrazine Derivatization and High-Performance Liquid Chromatography with Fluorescence Detection.

Glycosaminoglycans (GAGs), such as heparan sulfate (HS), play essential roles in living organisms. Understanding the functionality of HS and its involvement in disease progression necessitates the sensitive and quantitative detection of HS-derived unsaturated disaccharides. Conventionally, fluorescence derivatization precedes the HPLC analysis of these disaccharides. However, the presence of excess unreacted derivatization reagents can inhibit rapid and sensitive analysis in chromatographic determinations. In this study, we describe analytical methods that use dansylhydrazine as a derivatization agent for the detection and determination of HS-derived unsaturated disaccharides using HPLC. In addition, we have developed a straightforward method for removing excess unreacted reagent using a MonoSpin NH2 column. This method may be employed to remove excess pre-labeling reagents, thereby facilitating the analysis of HS-derived unsaturated disaccharides with satisfactory reproducibility.

Detection and quantification of biogenic amines in cephalopod using dansyl chloride pre-column derivatization-HPLC and their production.

The accurate detection of biogenic amines (BAs) is an important means of ensuring the quality and safety of cephalopod seafood products. In this study, the pre-column derivatization of high-performance liquid chromatography (HPLC) was optimized using dansyl chloride (Dns-Cl) to detect BAs in octopus, cuttlefish, and squid. The reasons for the formation of BAs were investigated by assessing their decarboxylase activity and the rates of decomposition. The findings demonstrated that using Dns-Cl to optimize pre-column derivatization enabled the separation of nine different BAs. The detection limits ranged from 0.07 to 0.25 mg/L, and the results exhibited a high level of linearity (R2 ≥ 0.997). The decarboxylase activity and biodegradation rate positively correlated with the formation of BAs at temperatures below 0°C. Notably, the decarboxylase activity of octopus, cuttlefish, and squid exhibited a significant increase with prolonged storage time, and formyltransferase and carbamate kinase may be the key decarboxylase in cephalopod products. These findings serve as a valuable reference for further investigations into the mechanisms behind BAs production and the development of control technologies for BAs in cephalopod products. This study has successfully demonstrated the effectiveness of the Dns-Cl pre-column derivatization-HPLC method in accurately and efficiently detecting BAs in octopus, cuttlefish, and squid. Moreover, it highlights the influence of decarboxylase content and biodegradation rate on the formation of BAs. Importantly, this method can serve as a reference for detecting BAs in various seafood products.

Unraveling the potential of segment scan mass spectral acquisition for chemical isotope labeling LC-MS-based metabolome analysis: Performance assessment across different types of biological samples.

BACKGROUND: Chemical isotope labeling (CIL) LC-MS is a powerful tool for metabolome analysis with high metabolomic coverage and quantification accuracy. In CIL LC-MS, the overall metabolite detection efficiency using Orbitrap MS can be further improved by employing a segment scan method where the full m/z range is divided into multiple segments for spectral acquisition with a significant increase in the in-spectrum dynamic range. Considering the metabolic complexity in different types of biological samples (e.g., feces, urine, serum/plasma, cell/tissue extracts, saliva, etc.), we report the development and evaluation of the segment scan method for metabolome analysis of different sample types. RESULTS: It was found that sample complexity significantly influenced the performance of the segment scan method. In metabolically complex samples such as feces and urine, the method yielded a substantial increase (up to 94 %) in detected peak pairs or metabolites, compared to conventional full scan. Conversely, less complex samples like saliva exhibited more modest gains (approximately 25 %). Based on the observations, a 120-m/z segment scan method was determined as a routine approach for CIL LC-Orbitrap-MS-based metabolomics with good compatibility with different types of biological samples. For this method, a further investigation on relative quantification accuracy was done. The peak area ratios of 12C-/13-labeled metabolites were slightly reduced with 72%-84 % of peak pairs falling within the ±25 % range of the anticipated peak ratio of 1.0 among different samples, as opposed to 81%-90 % in the full scan, which was attributed to the inclusion of more low-abundance peak pairs within the narrow MS segments. However, the overall peak ratio measurement precision was not significantly affected by the segment scan. SIGNIFICANCE AND NOVELTY: The segment scan method was found to be useful for CIL LC-Orbitrap-MS-based metabolome analysis of different types of samples with significant improvement in metabolite detectability (25-94 % increase), compared to the conventional full scan method.

Sensitive poliovirus detection using nested PCR and nanopore sequencing: a prospective validation study.

Timely detection of outbreaks is needed for poliovirus eradication, but gold standard detection in the Democratic Republic of the Congo takes 30 days (median). Direct molecular detection and nanopore sequencing (DDNS) of poliovirus in stool samples is a promising fast method. Here we report prospective testing of stool samples from suspected polio cases, and their contacts, in the Democratic Republic of the Congo between 10 August 2021 and 4 February 2022. DDNS detected polioviruses in 62/2,339 (2.7%) of samples, while gold standard combination of cell culture, quantitative PCR and Sanger sequencing detected polioviruses in 51/2,339 (2.2%) of the same samples. DDNS provided case confirmation in 7 days (median) in routine surveillance conditions. DDNS enabled confirmation of three serotype 2 circulating vaccine-derived poliovirus outbreaks 23 days (mean) earlier (range 6-30 days) than the gold standard method. The mean sequence similarity between sequences obtained by the two methods was 99.98%. Our data confirm the feasibility of implementing DDNS in a national poliovirus laboratory.

Determination of binding characteristics as a measure for effective albumin using different methods.

BACKGROUND & AIMS: Transport functions of albumin are of clinical and pharmacological interest and are determined by albumin's properties like posttranslational modifications or bound ligands. Both are affected in pathological conditions and in therapeutic grade albumin solutions. The term effective albumin concentration was introduced as a measure of functionally intact albumin. Our aim was to evaluate the impact of ligands and modifications with different approaches as a measure of effective albumin. APPROACH & RESULTS: We used a spin labelled fatty acid and dansylsarcosine to characterize binding properties of albumin i) prepared from plasma of patients and healthy control donors, ii) measured directly out of plasma, iii) research grade albumin, iv) in vitro modified albumin, and v) therapeutic infusion solutions before and after removal of stabilizers. Bilirubin is the main determinant for binding function in patients' albumin. In in vitro prepared albumin bound fatty acids correlated with impaired binding. Human nonmercaptalbumin1, not human nonmercaptalbumin2, showed reduced binding properties. Binding and transport function of therapeutic albumin was severely impaired and restored by filtration. Glycation of research grade albumin had no effect on the binding of dansylsarcosine and only a minor effect on fatty acid binding. CONCLUSIONS: Our results suggest that effective albumin -in terms of binding properties- is primarily determined by bound ligands and only to a minor extent by posttranslational modifications. Characterizing albumin directly from plasma better reflects the physiological situation whereas in the case of therapeutic grade albumin stabilizers should be removed to make its binding properties accessible.

A chemical derivatization-based pseudotargeted LC-MS/MS method for high coverage determination of dipeptides.

Dipeptides (DPs) have attracted more and more attention in many research fields due to their important biological functions and promising roles as disease biomarkers. However, the determination of DPs in biological samples is very challenging owing to the limited availability of commercial standards, high structure diversity, distinct physical and chemical characteristics, wide concentration range, and the extensive existence of isomers. In this study, a pseudotargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method coupled with chemical derivatization for the simultaneous analysis of 400 DPs and their constructing amino acids (AAs) in biospecimens is established. Dansyl chloride (Dns-Cl) chemical derivatization was introduced to provide characteristic MS fragments for annotation and improve the chromatographic separation of DP isomers. A retention time (RT) prediction model was constructed using 83 standards (63 DPs and 20 AAs) based on their quantitative structural retention relationship (QSRR) after the Dns-Cl labeling, which largely facilitated the annotation of the DPs without standards. Finally, we applied this method to investigate the profile change of DPs in a cisplatin-induced acute kidney injury (AKI) rat model. The established workflow provides a platform to profile DPs and expand our understanding of these little-studied metabolites.

Intensity-dependent mass search for improving metabolite database matches in chemical isotope labeling LC-QTOF-MS-based metabolomics.

Liquid chromatography mass spectrometry (LC-MS) has been increasingly used for metabolome analysis. One of the critical steps in the LC-MS metabolome analysis workflow is related to metabolite identification. Among the measured parameters, peak mass is commonly used to search against a database for potential metabolite matches. Higher accuracy mass measurement allows the use of a narrower mass tolerance window for mass search. While various types of mass analyzers can routinely measure a peak mass with an error of less than a few ppm, mass measurement accuracy is not uniform for peaks with different intensities, particularly for quadrupole time-of-flight (QTOF) MS. Herein we present a simple and convenient method to determine the relation between peak intensity and mass error in LC-QTOF-MS-based metabolome analysis, followed by intensity-dependent mass search (IDMS) of a database for metabolite matches. This method is based on running a series of sodium formate mass calibrants, as part of the standard operating procedure (SOP) in LC-MS data acquisition, and then curve-fitting the measured mass errors and peak intensities. We show that, in two different quadrupole time-of-flight (QTOF) mass analyzers, mass accuracy is generally reduced as peak intensity decreases, which is independent of m/z values in the range commonly used for metabolite detection (e.g., m/z < 1000). We demonstrate the improvement in metabolite matches using IDMS in the analyses of dansyl labeled standards and human urine samples. We have implemented the IDMS method in the freely available MCID database at www.mycompoundid.org, which is composed of 8021 known human endogenous metabolites and their predicted metabolic products (375,809 compounds from one metabolic reaction and 10,583,901 compounds from two reactions).

Machine learning liquid chromatography retention time prediction model augments the dansylation strategy for metabolite analysis of urine samples.

Herein, a standalone software equipped with a graphic user interface (GUI) is developed to predict liquid chromatography mass spectrometry (LC-MS) retention times (RTs) of dansylated metabolites. Dansylation metabolomics strategy developed by Li et al. narrows down a vast chemical space of metabolites into the metabolites containing amines and phenolic hydroxyls. Combined with differential isotope labeling, e.g., 12C-reagent labeled individual samples spiked with a 13C-reagent labeled reference or pooled sample, LC-MS analysis of the dansylated samples enables accurate relative quantification of all labeled metabolites. Herein, the LC-RTs for dansylated metabolites are predicted using an artificial neural network (ANN) machine-learning model. For the ANN modeling, 315 dansylated urine metabolites obtained from the DnsID database are used. The ANN LC-RT prediction model was reliable, with a mean absolute deviation of 0.74 min for the 30 min LC run. In the RT model, a deviation of more than 2 min was observed in only 3.2% of the total 315 metabolites, while a deviation of 1.5 min or more was observed in 11% of the metabolites. Furthermore, it was found that the LC-RT prediction was also reliable even for metabolites containing both amine and phenolic functional groups that can undergo dansylation on either one of the two functional groups, resulting in the generation of two isomeric forms. This RT-prediction model is embedded into a user-friendly GUI and can be used for identifying nontargeted dansylated metabolites with unknown RTs, along with accurate mass measurements. Furthermore, it is demonstrated that the developed software can help identify metabolites from a urine sample of an anonymous healthy pregnant woman.

Development of Chemical Isotope Labeling Liquid Chromatography Orbitrap Mass Spectrometry for Comprehensive Analysis of Dipeptides.

Dipeptides have recently attracted considerable attention due to their newly found biological functions and potential biomarkers of diseases. Global analysis of dipeptides (400 common dipeptides in total number) in samples of complex matrices would enable functional studies of dipeptides and biomarker discovery. In this work, we report a method for high-coverage detection and accurate relative quantification of dipeptides. This method is based on differential chemical isotope labeling (CIL) of dipeptides with dansylation and liquid chromatography Orbitrap tandem mass spectrometry (LC-Orbitrap-MS). An optimized LC gradient ensured the separation of dansyl-dipeptides, including positional isomers (e.g., leucine- and isoleucine-containing dipeptides). MS/MS collision energy in Orbitrap MS was optimized to provide characteristic fragment ion information to sequence dansyl-dipeptides. Using the optimized conditions, a CIL standard library consisting of retention time, MS, and MS/MS information of a whole set of 400 dansyl-dipeptides was constructed to facilitate rapid dipeptide identification. For qualitative analysis of dipeptides in real samples, IsoMS data processing software's parameters were tuned to improve the coverage of dipeptide annotation. Data-dependent acquisition was also carried out to improve the reliability of dipeptide identification. As examples of applications, we successfully identified a total of 321 dipeptides in rice wines and 105 dipeptides in human serum samples. For quantitative analysis, we demonstrated that the intensity ratios of the peak pairs from 96% of the dansyl-dipeptides detectable in a 1:1 mixture of 12C- and 13C-labeled rice wine samples were within ±20% of an expected value of 1.0. More than 90% of dipeptides were detected with a relative standard deviation of less than 10%, showing good performance of relative quantification.

Screening for Bisphenol Chemicals: A Strategy Based on Dansyl Chloride Derivatizatio n Coupled with In-Source Fragmentation by High-Resolution Mass Spectrometry.

Bisphenol chemicals (BPs) represent a complexity of halogenated and nonhalogenated substances sharing a common structure of two phenol functionalities, some of which exhibit ubiquitous environmental distributions and endocrine-disrupting activities. However, environmental monitoring of complex BP-like chemicals has faced analytical challenges arising from the lack of commercially available reference standards and efficient screening strategies. In the present study, we developed a strategy based on dansyl chloride (DnsCl) derivatization in combination with in-source fragmentation (D-ISF) during high-resolution mass spectrometry analysis to screen for bisphenol chemicals in complex environmental samples. The strategy contains three steps, including DnsCl derivatization to enhance the detection sensitivity by one to more than four orders of magnitude, in-source fragmentation to produce characteristic loss of 234.0589, 63.9619, and 298.0208 Da for the identification of DnsCl-derivatized compounds, and data processing and annotation. The D-ISF strategy was further validated and then applied to identify BPs in six types of particular matters as representative environmental samples, including settled dust from an electronic waste dismantling site, homes, offices, and vehicles, and airborne particles from indoor and outdoor environments. A total of six halogenated and fourteen nonhalogenated BPs were identified in the particles, including several chemicals that had rarely or never been identified in environmental samples. Our strategy offers a powerful tool for the environmental monitoring of bisphenol chemicals and assessment of human exposure risks.

Multi-sample dual-decoder graph autoencoder.

Self-supervised learning has shown superior performance on graph-related tasks in recent years. The most advanced methods are based on contrast learning, which severely limited by structured data augmentation techniques and complex training methods. Generative self-supervised learning, especially graph autoencoders (GAEs), can prevent the above dependence and has been demonstrated as an effective approach. In addition, most previous works only reconstruct the graph topological structure or node features. Few works consider both and combine them together to obtain their complementary information. To overcome these problems, we propose a generative self-supervised graph representation learning methodology named Multi-View Dual-decoder Graph Autoencoder (MDGA). Specifically, we first design a multi-sample graph learning strategy which benefits the generalization of the dual-decoder graph autoencoder. Moreover, the proposed model reconstructs the graph topological structure with a traditional GAE and extracts node attributes by masked feature reconstruction. Experimental results on five public benchmark datasets demonstrate that MDGA outperforms state-of-the-art methods in both node classification and link prediction tasks.

Normal plasmalogen levels are maintained in tissues from mice with hepatocyte-specific deletion in peroxin 5.

On the basis of findings that cultured rat hepatocytes secrete lipoprotein with a high plasmalogen content and the occurrence of this lipid in human serum, it has been suggested that hepatocytes play a role in the supply of plasmalogens to tissues. We tested this hypothesis in a mouse with a hepatocyte-specific defect in peroxisomes, an organelle essentially required for plasmalogen biosynthesis. We analyzed plasmalogens in lipid extracts of forebrain, liver and five further tissues and in plasma by reaction with dansylhydrazine in hydrochloric acid, which cleaves the vinyl ether of plasmalogens and forms a fluorescent dansylhydrazone, which we quantified by reversed phase high performance liquid chromatography. Reaction with dansylhydrazine in acetic acid was used to quantify free aldehydes as a control. Our results show normal levels of plasmalogens in plasma and in all tissues examined, including forebrain and the liver, irrespective of the inactivation of hepatic peroxisomes. None of the selected ether lipids analyzed by mass spectrometry in plasma and liver was decreased in the mice deficient in liver peroxisomes. In contrast, we found three plasmenylcholine species which were even significantly increased in the livers of these animals. Quantification of mRNA expression of plasmalogen biosynthetic enzymes revealed particularly low expression of fatty acyl-CoA reductase, the key regulatory enzyme of plasmalogen biosynthesis, in liver, with and without hepatic peroxisome deficiency. Our results do not support the suggested role of hepatocytes in supplying plasmalogens to tissues.

Instrument-type effects on chemical isotope labeling LC-MS metabolome analysis: Quadrupole time-of-flight MS vs. Orbitrap MS.

Chemical isotope labeling (CIL) LC-MS is a powerful tool for metabolome analysis with markedly improved metabolomic coverage and quantification accuracy over the conventional LC-MS technique. In addition, with differential isotope labeling, each labeled metabolite is detected as a peak pair in the mass spectra, offering the possibility of differentiating true metabolite peaks from the singlet noise or background peaks. In this study, we examined the effects of instrument type on the detectability of true metabolites with a focus on the comparison of quadrupole time-of-flight (QTOF) and Orbitrap mass spectrometers. Using the same ultra-high-performance liquid chromatography setup and optimized running conditions for QTOF and Orbitrap, we compared the total number of peak pairs detected and identified from the two instruments using human urine and serum as the test samples. Many common peak pairs were detected from the two instruments; however, there were a significant number of unique peak pairs detected in each type of instrument. By combining the datasets obtained using QTOF and Orbitrap, the total number of peak pairs detected could be significantly increased. We also examined the effect of mass resolving power on peak pair detection in Orbitrap (60,000 vs. 120,000 resolution). The observed differences in peak pair detectability were much less than those of QTOF vs. Orbitrap. However, the type of peak pairs detected using different resolutions could be somewhat different, offering the possibility of increasing the overall number of peak pairs by combining the two datasets obtained at two different resolutions. The results from this study clearly indicate that instrument type can have a profound effect on metabolite detection in CIL LC-MS. Therefore, comparison of metabolome data generated using different instruments needs to be carefully done. Moreover, future research (e.g., hardware modifications) is warranted to minimize the differences in order to generate more reproducible metabolome data from different types of instruments.

Rapid and Economical Chemoselective Metabolomics Using Boronate Ester Formation on a Monolithic Substrate.

Although chemoselective labeling strategies show great potential in in-depth description of metabolomics, the associated time and expense limit applications in high-throughput and routine analysis. We report a fast and effective chemoselective labeling strategy based on multifunctionalized monolithic probes. A rapid pH-responsive boronate ester reaction was employed to immobilize and release probe molecules from substrate in 5 min. The mesoporous surface and hierarchically porous channels of the substrate allowed for accelerated labeling reactions. Moreover, the discernible boron beacons allowed for recognition of labeled metabolites with no need for expensive isotopic encoding. This new strategy has been successfully used for submetabolome analysis of yeast cells, serum, and faeces samples, with improved sensitivity for short chain fatty acids up to 1 600 times compared with non-labeled liquid chromatography-mass spectrometry (LC-MS) methods.

Segment Scan Mass Spectral Acquisition for Increasing the Metabolite Detectability in Chemical Isotope Labeling Liquid Chromatography-Mass Spectrometry Metabolome Analysis.

We report a segmented spectrum scan method using Orbitrap MS in chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) for improving the metabolite detection efficiency. In this method, the full m/z range is divided into multiple segments with the scanning of each segment to produce multiple narrow-range spectra during the LC data acquisition. These segmented spectra are separately processed to extract the peak pair information with each peak pair arising from a differentially labeled metabolite in the analysis of a mixture of 13C and 12C reagent-labeled samples. The sublists of peak pairs are merged to form the final peak pair list from the LC-MS run. Various experimental conditions, including automatic gain control (AGC) values, mass resolutions, segment m/z widths, number of segments, and total data acquisition time in the LC run, were examined to arrive at an optimal setting in the segment scan for increasing the number of detectable metabolites while maintaining the same analysis time as in the full scan. The optimal method used a segment width of 120 m/z with 60k resolution for a 16 min CIL LC-MS run. Using dansyl-labeled human urine samples as an example, we demonstrated that this method could detect 5867 peak pairs or metabolites (not features), compared to 3765 peak pairs detectable in a full scan, representing a 56% gain. Out of 5867 peak pairs, 5575 (95.0%) could be identified or mass-matched. The relative quantification accuracy was slightly reduced (81% peak pairs were within ±25% of the expected peak ratio of 1.0 in full, compared to 87% in the full scan) due to the inclusion of more low-abundance peak pairs in the segment scan. The peak ratio measurement precision was not significantly affected by the segment scan. We also showed the increase of the peak pair number detectable from 3843 in the full scan to 7273 (89% gain) using the Orbitrap operated at 120k resolution with a 60 m/z segment width when multiple repeat sample injections were used. Thus, segment scan Orbitrap MS is an enabling method for detecting coeluting metabolites in CIL LC-MS for increasing the metabolomic coverage.

A new two-dimensional cadmium(II) coordination polymer based on Cd6(CHADC)6 clusters (H2CHADC is cyclohexane-1,2-dicarboxylic acid): synthesis, structure and properties.

The highly effective recognition and detection of metal ions and anions in water has attracted much attention with respect to environmental safety. Herein, a novel Cd-based coordination polymer, poly[[4,4'-bis(2-methylimidazol-1-yl)biphenyl]bis(cyclohexane-1,2-dicarboxylato)dicadmium(II)], [Cd2(C8H10O4)2(C20H18N4)]n or [Cd(CHADC)(4,4'-BMIBP)0.5]n, (I), has been synthesized employing cis-cyclohexane-1,2-dicarboxylic acid (H2CHADC) and 4,4'-bis(2-methyl-1H-imidazol-1-yl)biphenyl (4,4'-BMIBP). Single-crystal X-ray analysis reveals that (I) presents a 6-connected hxl two-dimensional layer based on Cd6(CHADC)6 clusters with the point symbol (36·46·53). Furthermore, (I) has been characterized by elemental analysis, IR spectroscopy, thermogravimetric analysis and fluorescence spectroscopy, and exhibits good stability and excellent photoluminescence properties. Coordination polymer (I) was chosen as a fluorescent probe to sense different target analytes and shows an obvious selective recognition response to Fe3+ cations and Cr2O72-/CrO42- anions through luminescence-quenching effects in aqueous solution. The sensing mechanism was investigated and showed that the detection mechanism was resonance energy transfer between (I) and the Fe3+, Cr2O72- and CrO42- ions.

Development of a rapid and sensitive LC-MS/MS assay for the quantification of commonly abused drugs in Asia in a micro-segment of a single hair using microwave-assisted extraction and dansyl chloride derivatization.

A high-throughput method using microwave-assisted extraction, chemical derivatization and liquid chromatography-electrospray tandem mass spectrometry (LC-ESI-MS/MS) was developed for the simultaneous analysis of illicit drugs and their metabolites, including amphetamine (AMP), methamphetamine (MA), methylenedioxy- amphetamine (MDA), methylenedioxy-methamphetamine (MDMA), morphine (MOR), 6-acetylmorphine (6-AM), ketamine (K), and norketamine (NK) in a micro-segment of a single hair (0.4 mm). In order to elevate the throughput and sensitivities of selected compounds, 3 min microwave-assisted extraction and 10 min derivatization with dansyl chloride (DC) were employed. After derivatization, all compounds except ketamine and norketamine were derivatized and enhanced the sensitivities significantly. Derivatives showed intense fragment ions and low background noise on DC-MOR, DC-6-AM, and four DC-amphetamine-type stimulants. The total sample preparation and analysis time was 50 min. The calibration range was from LOQ to 5000 pg/mg, the coefficient of determination was better than 0.997. Intra-assay precision and accuracy were generally less than 15%. Limits of detection ranged from 15 to 50 pg/mg, limits of quantitation ranged between 45 and 125 pg/mg. The matrix effect was better than 90%. The method was successfully applied to the analysis of actual hair samples collected from multi-drug abusers. This advanced method showed practicality in hair analysis and was suitable for the extremely insufficient sample.

Development of a Simple Dansyl-Based PH Fluorescent Probe in Acidic Medium and Its Application in Cell Imaging.

A simple pH fluorescent probe based on dansyl derivative (Bu-Dns) was synthesized via one-step reaction between dansyl chloride and 4-bromobutan-1-amine hydrobromide. The obtained probe showed good selectivity and sensitivity toward H+ in acidic medium over two pH units (~4-2). At pH > 4, Bu-Dns solution emitted yellow fluorescent light, which became gradually weaker with decreasing pH value. At pH below 2, complete fluorescence quenching occurred. The pH response of Bu-Dns was ascribed to the protonation of dimethylamine group. The lack of influence of metal ion on pH response increases the prevalence of Bu-Dns in the potential detection of pH variation in acidic aqueous media. More importantly, it can sense the intracellular pH change in acidic range.

Development of a method for dansylation of metabolites using organic solvent-compatible buffer systems for amine/phenol submetabolome analysis.

Metabolomics, which serves as a readout of biological processes and diseases monitoring, is an informative research area for disease biomarker discovery and systems biology studies. In particular, reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) has become a powerful and popular tool for metabolomics analysis, enabling the detection of most metabolites. Very polar and ionic metabolites, however, are less easily detected because of their poor retention in RP columns. Dansylation of metabolites simplifies the sub-metabolome analysis by reducing its complexity and increasing both hydrophobicity and ionization ability. However, the various metabolite concentrations in clinical samples have a wide dynamic range with highly individual variation in total metabolite amount, such as in saliva. The bicarbonate buffer typically used in dansylation labeling reactions induces solvent stratification, resulting in poor reproducibility, selective sample loss and an increase in false-determined metabolite peaks. In this study, we optimized the dansylation protocol for samples with wide concentration range of metabolites, utilizing diisopropylethylamine (DIPEA) or tri-ethylamine (TEA) in place of bicarbonate buffer, and presented the results of a systemic investigation of the influences of individual processes involved on the overall performance of the protocol. In addition to achieving high reproducibility, substitution of DIPEA or TEA buffer resulted in similar labeling efficiency of most metabolites and more efficient labeling of some metabolites with a higher pKa. With this improvement, compounds that are only present in samples in trace amounts can be detected, and more comprehensive metabolomics profiles can be acquired for biomarker discovery or pathway analysis, making it possible to analyze clinical samples with limited amounts of metabolites.