BACKGROUND: Atmospheric particulate matter (PM) exposure-induced neuroinflammation is critical in mediating nervous system impairment. However, effective intervention is yet to be developed.
RESULTS: In this study, we examine the effect of β-nicotinamide mononucleotide (NMN) supplementation on nervous system damage upon PM exposure and the mechanism of spatial regulation of lipid metabolism. 120 C57BL/6 male mice were exposed to real ambient PM for 11 days (subacute) or 16 weeks (sub-chronic). NMN supplementation boosted the level of nicotinamide adenine dinucleotide (NAD+) in the mouse brain by 2.04 times. This augmentation effectively reduced neuroinflammation, as evidenced by a marked decrease in activated microglia levels across various brain regions, ranging from 29.29 to 85.96%. Whole brain lipidomics analysis revealed that NMN intervention resulted in an less increased levels of ceramide (Cer) and lysophospholipid in the brain following subacute PM exposure, and reversed triglyceride (TG) and glycerophospholipids (GP) following sub-chronic PM exposure, which conferred mice with anti-neuroinflammation response, improved immune function, and enhanced membrane stability. In addition, we demonstrated that the hippocampus and hypothalamus might be the most sensitive brain regions in response to PM exposure and NMN supplementation. Particularly, the alteration of TG (60:10, 56:2, 60:7), diacylglycerol (DG, 42:6), and lysophosphatidylcholine (LPC, 18:3) are the most profound, which correlated with the changes in functional annotation and perturbation of pathways including oxidative stress, inflammation, and membrane instability unveiled by spatial transcriptomic analysis.
CONCLUSIONS: This study demonstrates that NMN intervention effectively reduces neuroinflammation in the hippocampus and hypothalamus after PM exposure by modulating spatial lipid metabolism. Strategies targeting the improvement of lipid homeostasis may provide significant protection against brain injury associated with air pollutant exposure.

BACKGROUND: Patient-derived organoids (PDOs) are multi-cellular cultures with specific three-dimensional (3D) structures. Tumor organoids (TOs) offer a personalized perspective for assessing treatment response. However, the presence of normal organoid (NO) residuals poses a potential threat to their utility for personalized medicine. There is a crucial need for an effective platform capable of distinguishing between TO and NO in cancer organoid cultures.
RESULTS: We introduced a whole-mount (WM) preparation protocol for in-situ visualization of the lipidomic distribution of organoids. To assess the efficacy of this method, nine breast cancer organoids (BCOs) and six normal breast organoids (NBOs) were analyzed. Poly-l-lysine (PLL) coated slides, equipped with 12 well chambers, were utilized as a carrier for the high-throughput analysis of PDOs. Optimizing the fixation time to 30 min, preserved the integrity of organoids and the fidelity of lipid compounds. The PDOs derived from the same organoid lines exhibited similar lipidomic profiles. BCOs and NBOs were obviously distinguished based on their lipidomic signatures detected by WM autofocusing (AF) scanning microprobe matrix-assisted laser desorption/ionization (SMALDI) mass spectrometry imaging (MSI).
CONCLUSIONS: A whole-mount (WM) preparation protocol was developed to visualize lipidomic distributions of the organoids\' surface. Using poly-l-lysine coated slides for high-throughput analysis, the method preserved organoid integrity and distinguished breast cancer organoids (BCOs) from normal breast organoids (NBOs) based on their unique lipidomic profiles using autofocusing scanning microprobe matrix-assisted laser desorption/ionization (SMALDI) mass spectrometry imaging.

Quality control and system suitability testing are vital protocols implemented to ensure the repeatability and reproducibility of data in mass spectrometry investigations. However, mass spectrometry imaging (MSI) analyses present added complexity since both chemical and spatial information are measured. Herein, we employ various machine learning algorithms and a novel quality control mixture to classify the working conditions of an MSI platform. Each algorithm was evaluated in terms of its performance on unseen data, validated with negative control data sets to rule out confounding variables or chance agreement, and utilized to determine the necessary sample size to achieve a high level of accurate classifications. In this work, a robust machine learning workflow was established where models could accurately classify the instrument condition as clean or compromised based on data metrics extracted from the analyzed quality control sample. This work highlights the power of machine learning to recognize complex patterns in MSI data and use those relationships to perform a system suitability test for MSI platforms.

1.Challenges, strategies and new technologies in the field of biotransformation were presented and discussed at the 5th European Biotransformation Workshop, which was held on March 14, 2024 on the Novartis Campus in Basel, Switzerland.2. In this meeting report we summarise the presentations and discussions from this workshop.3. The topics covered are listed below:Advances in understanding drug induced liver injury (DILI) risks of carboxylic acids and targeted covalent inhibitorsBiotransformation of oligonucleotide-based therapeutics including automated software tools for metabolite identificationRecent advances in metabolite synthesisQualification and validation of a new compact Low Energy Accelerator Mass Spectrometry (LEA) system for metabolite profiling.

Mass spectrometry imaging (MSI) provides information about the spatial localization of molecules in complex samples with high sensitivity and molecular selectivity. Although point-wise data acquisition, in which mass spectra are acquired at predefined points in a grid pattern, is common in MSI, several MSI techniques use line-wise data acquisition. In line-wise mode, the imaged surface is continuously sampled along consecutive parallel lines and MSI data are acquired as a collection of line scans across the sample. Furthermore, aside from the standard imaging mode in which full mass spectra are acquired, other acquisition modes have been developed to enhance molecular specificity, enable separation of isobaric and isomeric species, and improve sensitivity to facilitate the imaging of low abundance species. These methods, including MS/MS-MSI in both MS2 and MS3 modes, multiple-reaction monitoring (MRM)-MSI, and ion mobility spectrometry (IMS)-MSI have all demonstrated their capabilities, but their broader implementation is limited by the existing MSI analysis software. Here, we present MSIGen, an open-source Python package for the visualization of MSI experiments performed in line-wise acquisition mode containing MS1, MS2, MRM, and IMS data, which is available at https://github.com/LabLaskin/MSIGen. The package supports multiple vendor-specific and open-source data formats and contains tools for targeted extraction of ion images, normalization, and exportation as images, arrays, or publication-style images. MSIGen offers multiple interfaces, allowing for accessibility and easy integration with other workflows. Considering its support for a wide variety of MSI imaging modes and vendor formats, MSIGen is a valuable tool for the visualization and analysis of MSI data.

The presence and localization of plant metabolites are indicative of physiological processes, e.g., under biotic and abiotic stress conditions. Further, the chemical composition of plant parts is related to their quality as food or for medicinal applications. Mass spectrometry imaging (MSI) has become a popular analytical technique for exploring and visualizing the spatial distribution of plant molecules within a tissue. This review provides a summary of mass spectrometry methods used for mapping and identifying metabolites in plant tissues. We present the benefits and the disadvantages of both vacuum and ambient ionization methods, considering direct and indirect approaches. Finally, we discuss the current limitations in annotating and identifying molecules and perspectives for future investigations.

UNASSIGNED: Taxus species contain the anticancer alkaloid paclitaxel, as well as other taxanes similar in structure and potentially in effect to paclitaxel. Tissue-specific distribution patterns and seasonal variations of taxanes in some Taxus species have been reported; however, it is still under-presented for the taxanes in Taxus cuspidata.
UNASSIGNED: The radial distributions of eight taxanes in the transverse surface of freeze-fixed T. cuspidata stems from the late summer and the spring seasons were investigated by cryo-time-of-flight secondary ion mass spectrometry and scanning electron microscopy (cryo-TOF-SIMS/SEM) visualization and liquid chromatography-mass spectrometry (LC-MS) quantitative analysis. By optical microscopic observation, seasonal differences in the amounts and distribution patterns of target taxanes were further characterized in specific tissues.
UNASSIGNED: The overall amount of taxanes was higher in the late summer than in the spring. Also, taxanes\' radial distribution was generally found at higher concentration in the phloem, the cambium and lower level in the periderm, the latest-forming xylem, with different taxanes showing several patterns with distinction between seasons, which were considered related to seasonal plant physiological behaviors. In addition, the distribution of baccatin III (BAC) was investigated at the cellular level, which was regarded in specific cells suggesting its transport in the radial and axial directions in the T. cuspidata stem. Characterizing the microscopic distribution of taxanes in the T. cuspidata stem is expected to play a role in the further study of their biosynthesis and in planta behaviors.

Herbal medicines (HMs) have long played a pivotal role in preventing and treating various human diseases and have been studied widely. However, the complexities present in HM metabolites and their unclear mechanisms of action have posed significant challenges in the modernization of traditional Chinese medicine (TCM). Over the past two decades, mass spectrometry imaging (MSI) has garnered increasing attention as a robust analytical technique that enables the simultaneous execution of qualitative, quantitative, and localization analyses without complex sample pretreatment. With advances in technical solutions, MSI has been extensively applied in the field of HMs. MSI, a label-free ion imaging technique can comprehensively map the spatial distribution of HM metabolites in plant native tissues, thereby facilitating the effective quality control of HMs. Furthermore, the spatial dimension information of small molecule endogenous metabolites within animal tissues provided by MSI can also serve as a supplement to uncover pharmacological and toxicological mechanisms of HMs. In the review, we provide an overview of the three most common MSI techniques. In addition, representative applications in HM are highlighted. Finally, we discuss the current challenges and propose several potential solutions. We hope that the summary of recent findings will contribute to the application of MSI in exploring metabolites and mechanisms of action of HMs.

Emodin is an important anthraquinone compound with good anti-inflammatory activity in Chinese traditional medicine rhubarb. Detailed spatial distribution information in bio-tissues plays an important role in revealing the pharmacodynamics, toxicology and chemical mechanism of emodin. Herein, the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging (MALDI-TOF-MSI) analytical method was established to obtain information on the spatial and temporal changes of emodin in multiple mouse tissue sections (heart, liver, spleen, lung, kidney, and brain) after intraperitoneal injection of emodin in mice. The measurements were accomplished in the negative ion mode in the range of m/z 250-285 Da with a spatial resolution on 40 µm. It was found that emodin was predominantly distributed in the arteriolar vascular region of the heart, the capsule region of the spleen, and the cortex of the kidney. Moreover, the MALDI-TOF-MSI result implied that emodin might be distributed in the brain. These more detailed spatial distribution information provides the significant reference for investigating the action mechanism of emodin, which cannot be obtained from conventional LC-MS analysis. The distribution trend of emodin in the results of MALDI-TOF-MSI analysis agreed with the ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) results well, demonstrating the complementarity and reliability of the established MALDI-TOF-MSI method. Our work provided a label-free molecular imaging method to investigate the precise spatial distribution of emodin in various organs, which prove great potential in studying the effective substances and mechanism of rhubarb.

Many bacteria co-exist and produce antibiotics, yet we know little about how they cope and occupy the same niche. The purpose of the present study was to determine if and how two potent antibiotic-producing marine bacteria influence the secondary metabolome of each other. We established an agar- and broth-based system allowing co-existence of a Phaeobacter species and Pseudoalteromonas piscicida that, respectively, produce tropodithietic acid (TDA) and bromoalterochromides (BACs). Co-culturing of Phaeobacter sp. strain A36a-5a on Marine Agar with P. piscicida strain B39bio caused a reduction of TDA production in the Phaeobacter colony. We constructed a transcriptional gene reporter fusion in the tdaC gene in the TDA biosynthetic pathway in Phaeobacter and demonstrated that the reduction of TDA by P. piscicida was due to the suppression of the TDA biosynthesis. A stable liquid co-cultivation system was developed, and the expression of tdaC in Phaeobacter was reduced eightfold lower (per cell) in the co-culture compared to the monoculture. Mass spectrometry imaging of co-cultured colonies revealed a reduction of TDA and indicated that BACs diffused into the Phaeobacter colony. BACs were purified from Pseudoalteromonas; however, when added as pure compounds or a mixture they did not influence TDA production. In co-culture, the metabolome was dominated by Pseudoalteromonas features indicating that production of other Phaeobacter compounds besides TDA was reduced. In conclusion, co-existence of two antibiotic-producing bacteria may be allowed by one causing reduction in the antagonistic potential of the other. The reduction (here of TDA) was not caused by degradation but by a yet uncharacterized mechanism allowing Pseudoalteromonas to reduce expression of the TDA biosynthetic pathway.IMPORTANCEThe drug potential of antimicrobial secondary metabolites has been the main driver of research into these compounds. However, in recent years, their natural role in microbial systems and microbiomes has become important to determine the assembly and development of microbiomes. Herein, we demonstrate that two potent antibiotic-producing bacteria can co-exist, and one mechanism allowing the co-existence is the specific reduction of antibiotic production in one bacterium by the other. Understanding the molecular mechanisms in complex interactions provides insights for applied uses, such as when developing TDA-producing bacteria for use as biocontrol in aquaculture.