Investigation of signaling molecules and metabolites found in crustacean hemolymph via in vivo microdialysis using a multifaceted mass spectrometric platform

Recent advances in mass spectrometry analysis of neuropeptides

Due to their involvement in numerous biochemical pathways, neuropeptides have been the focus of many recent research studies. Unfortunately, classic analytical methods, such as western blots and enzyme-linked immunosorbent assays, are extremely limited in terms of global investigations, leading researchers to search for more advanced techniques capable of probing the entire neuropeptidome of an organism. With recent technological advances, mass spectrometry (MS) has provided methodology to gain global knowledge of a neuropeptidome on a spatial, temporal, and quantitative level. This review will cover key considerations for the analysis of neuropeptides by MS, including sample preparation strategies, instrumental advances for identification, structural characterization, and imaging; insightful functional studies; and newly developed absolute and relative quantitation strategies. While many discoveries have been made with MS, the methodology is still in its infancy. Many of the current challenges and areas that need development will also be highlighted in this review.

Developing mass spectrometry for the quantitative analysis of neuropeptides

INTRODUCTION

Neuropeptides are signaling molecules originating in the neuroendocrine system that can act as neurotransmitters and hormones in many biochemical processes. Their exact function is difficult to characterize, however, due to dependence on concentration, post-translational modifications, and the presence of other comodulating neuropeptides. Mass spectrometry enables sensitive, accurate, and global peptidomic analyses that can profile neuropeptide expression changes to understand their roles in many biological problems, such as neurodegenerative disorders and metabolic function.

AREAS COVERED

We provide a brief overview of the fundamentals of neuropeptidomic research, limitations of existing methods, and recent progress in the field. This review is focused on developments in mass spectrometry and encompasses labeling strategies, post-translational modification analysis, mass spectrometry imaging, and integrated multi-omic workflows, with discussion emphasizing quantitative advancements.

EXPERT OPINION

Neuropeptidomics is critical for future clinical research with impacts in biomarker discovery, receptor identification, and drug design. While advancements are being made to improve sensitivity and accuracy, there is still room for improvement. Better quantitative strategies are required for clinical analyses, and these methods also need to be amenable to mass spectrometry imaging, post-translational modification analysis, and multi-omics to facilitate understanding and future treatment of many diseases.

Clinical Insights into Mitochondrial Neurodevelopmental and Neurodegenerative Disorders: Their Biosignatures from Mass Spectrometry-Based Metabolomics

Mitochondria are dynamic multitask organelles that function as hubs for many metabolic pathways. They produce most ATP via the oxidative phosphorylation pathway, a critical pathway that the brain relies on its energy need associated with its numerous functions, such as synaptic homeostasis and plasticity. Therefore, mitochondrial dysfunction is a prevalent pathological hallmark of many neurodevelopmental and neurodegenerative disorders resulting in altered neurometabolic coupling. With the advent of mass spectrometry (MS) technology, MS-based metabolomics provides an emerging mechanistic understanding of their global and dynamic metabolic signatures. In this review, we discuss the pathogenetic causes of mitochondrial metabolic disorders and the recent MS-based metabolomic advances on their metabolomic remodeling. We conclude by exploring the MS-based metabolomic functional insights into their biosignatures to improve diagnostic platforms, stratify patients, and design novel targeted therapeutic strategies.

Dual modulatory effects on feedback from a proprioceptor in the crustacean stomatogastric nervous system

Neuromodulatory actions that change the properties of proprioceptors or the muscle movements to which they respond necessarily affect the feedback provided to the central network. Here we further characterize the responses of the gastropyloric receptor 1 (GPR1) and gastropyloric receptor 2 (GPR2) neurons in the stomatogastric nervous system of the crab Cancer borealis to movements and contractions of muscles, and we report how neuromodulation modifies those responses. We observed that the GPR1 response to contractions of the gastric mill 4 muscle (gm4) was absent, or nearly so, when the neuron was quiescent but robust when it was spontaneously active. We also found that the effects of four neuromodulatory substances (GABA, serotonin, proctolin, and TNRNFLRFamide) on the GPR1 response to muscle stretch were similar to those previously reported for GPR2. Finally, we showed that an excitatory action on gm4 due to proctolin combined with an inhibitory action on GPR2 due to GABA can allow for larger muscle contractions without increased proprioceptive feedback.NEW & NOTEWORTHY We report that the combination of GABA and the peptide proctolin increases contraction of a stomatogastric muscle while decreasing the corresponding response of the proprioceptor that reports on it. These results suggest a general mechanism by which muscle movements can be modified while sensory feedback is conserved, one that may be particularly well suited for providing flexibility to central pattern generator networks.

Spatial Metabolomics of the Human Kidney using MALDI Trapped Ion Mobility Imaging Mass Spectrometry

Low molecular weight metabolites are essential for defining the molecular phenotypes of cells. However, spatial metabolomics tools often lack the sensitivity, specify, and spatial resolution to provide comprehensive descriptions of these species in tissue. MALDI imaging mass spectrometry (IMS) of low molecular weight ions is particularly challenging as MALDI matrix clusters are often nominally isobaric with multiple metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Additional difficulties surrounding low weight metabolite visualization include high resolution imaging, while maintaining sufficient ion numbers for broad and representative analysis of the tissue chemical complement. Here, we use MALDI timsTOF IMS to image low molecular weight metabolites at higher spatial resolution than most metabolite MALDI IMS experiments (20 μm) while maintaining broad coverage within the human kidney. We demonstrate that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different distributions within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for spatial metabolomics experiments. Through this improved sensitivity, we have found >40 low molecular weight metabolites in human kidney tissue, such as argininic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. Future work will involve further exploring metabolomic profiles of human kidneys as a function of age, sex, and race.

Capillary electrophoresis coupled to MALDI mass spectrometry imaging with large volume sample stacking injection for improved coverage of C. borealis neuropeptidome

Neuropeptides are important signaling molecules responsible for a wide range of functions within the nervous and neuroendocrine system. However, they are difficult to study due to numerous challenges, most notably their large degree of variability and low abundance in vivo. As a result, effective separation methods with sensitive detection capabilities are necessary for profiling neuropeptides in tissue samples, particularly those of simplified model organisms such as crustaceans. In order to address these challenges, this study utilized a capillary electrophoresis (CE)-matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) platform, building upon our previous design for improved neuropeptidomic coverage. The capillary was coated with polyethylenimine (PEI) to reduce peptide adsorption and reverse the electroosmotic flow, and large volume sample stacking (LVSS) was used to load and pre-concentrate 1 μL of sample. The method demonstrated good reproducibility, with lower than 5% relative standard deviation for standards, and a limit of detection of approximately 100 pM for an allatostatin III peptide standard. The method was tested on brain and sinus gland (SG) tissue extracts and enabled detection of over 200 neuropeptides per run. When comparing the number detected in brain extracts in a direct spot, 60-second fractions, and 30-second fractions, the continuous trace collection afforded by the CE-MALDI-MSI platform yielded the largest number of detected neuropeptides. The method was compared to conventional LC-ESI-MS, and though the number of neuropeptides detected by LC-ESI-MS was slightly larger, the two methods were highly complementary, indicating the potential for the CE-MALDI-MSI method to uncover previously undetected neuropeptides in the crustacean nervous system. These results indicate the potential of CE-MALDI-MSI for routine use in neuropeptide research.

Comprehensive urinary metabolomic characterization of a genetically induced mouse model of prostatic inflammation

Dysfunction of the lower urinary tract commonly afflicts the middle-aged and aging male population. The etiology of lower urinary tract symptoms (LUTS) is multifactorial. Benign prostate hyperplasia, fibrosis, smooth muscle contractility, and inflammation likely contribute. Here we aim to characterize the urinary metabolomic profile associated with prostatic inflammation, which could inform future personalized diagnosis or treatment, as well as mechanistic research. Quantitative urinary metabolomics was conducted to examine molecular changes following induction of inflammation via conditional Interleukin-1β expression in prostate epithelia using a novel transgenic mouse strain. To advance method development for urinary metabolomics, we also compared different urine normalization methods and found that normalizing urine samples based on osmolality prior to LC-MS most completely separated urinary metabolite profiles of mice with and without prostate inflammation via principal component analysis. Global metabolomics was combined with advanced machine learning feature selection and classification for data analysis. Key dysregulated metabolites and pathways were identified and were relevant to prostatic inflammation, some of which overlapped with our previous study of human LUTS patients. A binary classification model was established via the support vector machine algorithm to accurately differentiate control and inflammation groups, with an area-under-the-curve value of the receiver operating characteristic of 0.81, sensitivity of 0.974 and specificity of 0.995, respectively. This study generated molecular profiles of non-bacterial prostatic inflammation, which could assist future efforts to stratify LUTS patients and develop new therapies.

Coupling of CE-MS for protein and peptide analysis

The review is focused on the latest developments in the analysis of proteins and peptides by capillary electrophoresis techniques coupled to mass spectrometry. First, the methodology and instrumentation are overviewed. In this section, recent progress in capillary electrophoresis with mass spectrometry interfaces and capillary electrophoresis with matrix-assisted laser desorption/ionization is mentioned, as well as separation tasks. The second part is devoted to applications-mainly bottom-up and top-down proteomics. It is obvious that capillary electrophoresis with mass spectrometry methods are well suited for peptide and protein analysis (proteomic research) and it is described how these techniques are complementary and not competitive with the often used liquid chromatography with mass spectrometry methods.

Comparative Evaluation of MS-based Metabolomics Software and Its Application to Preclinical Alzheimer's Disease

Mass spectrometry-based metabolomics has undergone significant progresses in the past decade, with a variety of software packages being developed for data analysis. However, systematic comparison of different metabolomics software tools has rarely been conducted. In this study, several representative software packages were comparatively evaluated throughout the entire pipeline of metabolomics data analysis, including data processing, statistical analysis, feature selection, metabolite identification, pathway analysis, and classification model construction. LC-MS-based metabolomics was applied to preclinical Alzheimer's disease (AD) using a small cohort of human cerebrospinal fluid (CSF) samples (N = 30). All three software packages, XCMS Online, SIEVE, and Compound Discoverer, provided consistent and reproducible data processing results. A hybrid method combining statistical test and support vector machine feature selection was employed to screen key metabolites, achieving a complementary selection of candidate biomarkers from three software packages. Machine learning classification using candidate biomarkers generated highly accurate and predictive models to classify patients into preclinical AD or control category. Overall, our study demonstrated a systematic evaluation of different MS-based metabolomics software packages for the entire data analysis pipeline which was applied to the candidate biomarker discovery of preclinical AD.

Profiling of small molecule metabolites and neurotransmitters in crustacean hemolymph and neuronal tissues using reversed-phase LC-MS/MS

Crustaceans have been long used as model animals for neuromodulation studies because of their well-defined neural circuitry. The identification of small molecule metabolites and signaling molecules in circulating fluids and neuronal tissues presents unique challenges due to their diverse structures, biological functions, and wide range of concentrations. LC combined with high resolution MS/MS is one of the most powerful tools to uncover endogenous small molecules. Here we explored several sample preparation techniques (solid-phase extraction and denaturing) and MS data acquisition strategies (data-dependent acquisition and targeted MS2-based acquisition) that provided complementary coverage and improved overall identification rate in C18 LC-MS/MS experiment. By MS/MS spectral matching with mzCloud database and those generated from standard compounds, a total of 129 small molecule metabolites and neurotransmitters were identified from crustacean hemolymph and neuronal tissues. These confidently identified small molecules covered predominant biosynthetic pathways for major neurotransmitters, validating the effectiveness of the high-throughput RPLC-MS/MS approach in studying the metabolism of neurotransmitters.

Pharmacokinetic and Pharmacodynamics of Self-Assembled Cubic Liquid Crystalline Nanoparticle Gel After Transdermal Administration

BACKGROUND The aim of this study was to assess the pharmacokinetics after transdermal administration by a novel skin microdialysis technology in rats. The guinea pig model was established by investigating the pharmacodynamics. MATERIAL AND METHODS Three different agents were given after hair removal, and the samples were extracted by microdialysis and detected by HPLC. Subcutaneous/plasma concentration-time curves of the 3 different agents were analyzed and the pharmacokinetic parameters were calculated. The SS-04B UV light therapy instrument was used in the modeling. Changes in melanin index and histopathology were observed with HE staining. RESULTS The increment and decrement results showed that the concentration had no significant effect on drug recovery both in vivo and in vitro. After the paeonol cubic liquid crystalline nanoparticles gel (PAE-LCNPs) was administered, the maximum peak time (tmax) of paeonol skin concentration appeared at 2.42±0.20 h, the maximum skin concentration Cmax was (926±105) ng/ml, and the area under the curve AUC0-8 was (8056±954) ng/h/ml. The tmax was shortened much more than in the other groups, and the performance of PAE-LCNPs targeting was good. Pharmacodynamic results showed that PAE-LCNPs can reduce melanocytes and reduce the melanin index, proving its utility in the treatment of melanin deposition. CONCLUSIONS The skin microdialysis study indicated PAE-LCNPs have good transdermal permeability and efficacy. Pharmacological experiments based on the study found that the topical pigmentation model of guinea pigs showed a better therapeutic effect.

Neuropeptide modulation of pattern-generating systems in crustaceans: comparative studies and approaches

Central pattern generators are subject to modulation by peptides, allowing for flexibility in patterned output. Current techniques used to characterize peptides include mass spectrometry and transcriptomics. In recent years, hundreds of neuropeptides have been sequenced from crustaceans; mass spectrometry has been used to identify peptides and to determine their levels and locations, setting the stage for comparative studies investigating the physiological roles of peptides. Such studies suggest that there is some evolutionary conservation of function, but also divergence of function even within a species. With current baseline data, it should be possible to begin using comparative approaches to ask fundamental questions about why peptides are encoded the way that they are and how this affects nervous system function.