Mass Spectrometry Measurements of Neuropeptides: From Identification to Quantitation.

Neuropeptides (NPs), a unique class of neuronal signaling molecules, participate in a variety of physiological processes and diseases. Quantitative measurements of NPs provide valuable information regarding how these molecules are differentially regulated in a multitude of neurological, metabolic, and mental disorders. Mass spectrometry (MS) has evolved to become a powerful technique for measuring trace levels of NPs in complex biological tissues and individual cells using both targeted and exploratory approaches. There are inherent challenges to measuring NPs, including their wide endogenous concentration range, transport and postmortem degradation, complex sample matrices, and statistical processing of MS data required for accurate NP quantitation. This review highlights techniques developed to address these challenges and presents an overview of quantitative MS-based measurement approaches for NPs, including the incorporation of separation methods for high-throughput analysis, MS imaging for spatial measurements, and methods for NP quantitation in single neurons.

Droplet Microfluidics with MALDI-MS Detection: The Effects of Oil Phases in GABA Analysis.

Microfluidic and mass spectrometry (MS) methods are widely used to sample and probe the chemical composition of biological systems to elucidate chemical correlates of their healthy and disease states. Though matrix-assisted laser desorption/ionization-mass spectrometry (MALDI)-MS has been hyphenated to droplet microfluidics for offline analyses, the effects of parameters related to droplet generation, such as the type of oil phase used, have been understudied. To characterize these effects, five different oil phases were tested in droplet microfluidics for producing samples for MALDI-MS analysis. Picoliter to nanoliter aqueous droplets containing 0.1 to 100 mM γ-aminobutyric acid (GABA) and inorganic salts were generated inside a polydimethylsiloxane microfluidic chip and deposited onto a conductive glass slide. Optical microscopy, Raman spectroscopy, and MALDI-mass spectrometry imaging (MSI) of the droplet samples and surrounding areas revealed patterns of solvent and oil evaporation and analyte deposition. Optical microscopy detected the presence of salt crystals in 50-100 µm diameter dried droplets, and Raman and MSI were used to correlate GABA signals to the visible droplet footprints. MALDI-MS analyses revealed that droplets prepared in the presence of octanol oil led to the poorest detectability of GABA, whereas the oil phases containing FC-40 provided the best detectability; GABA signal was localized to the footprint of 65 pL droplets with a limit of detection of 23 amol. The effect of the surfactant perfluorooctanol on analyte detection was also investigated.

An Assessment of the Stability of the Canine Oral Microbiota After Probiotic Administration in Healthy Dogs Over Time.

The administration of an oral probiotic has been demonstrated to impact oral microbial diversity in humans but has not been examined in canines. The objective of this study was to test the hypothesis that oral probiotic administration would impact the oral microbiota of canines compared to control. Working canines in training (n = 13) were assigned to Test or Control groups and acclimated to one of three commercially available study diets utilizing common protein sources (Purina Pro Plan Savor lamb, Purina Pro Plan Sport chicken, Purina Pro Plan Focus salmon) for a minimum of 30 days prior to initiation of the study. Following acclimation, dogs in the Test group began a daily regimen of oral probiotic (Fortiflora® Purina, St. Louis, MO) top-dressed on their midday feeding. Control dogs received their midday feeding with no probiotic. All dogs were sampled once weekly via oral pediatric swabs across the 7-week study. Next generation sequencing (Illumina, MiSeq) was utilized to develop microbial profiles specific to treatment, diet, and time. Bacterial composition was dominated by eight phyla (Proteobacteria 43.8%, Bacteroidetes 22.5%, Firmicutes 18.9%, Actinobacteria 6.1%, Fusobacteria 3.6%, Gracilibacteria 2.1%, SR1 Absconditabacteria 1.5%, and Saccharibacteria 1.3%) representing more than 99% of the relative abundance of the microbial composition. Probiotic administration failed to impact relative abundance at any taxonomic level (P > 0.05). Similarly, no effect on the oral microbiota was measured for diet (P > 0.05). Comparison using a Jaccard Index demonstrate a consistent microbial profile over the 7-week study with no impact evidenced by study week (P = 0.19). The data also revealed a profile of ubiquitous taxa that were present across all dogs and all samples regardless of breed, sex, diet, treatment or other factors. These genera include Actinomyces, Corynebacterium, Capnocytophaga, Flavobacterium, Gemella, Abiotrophia, Streptococcus, and Frederiksenia. These data demonstrate the stability of canine oral microbiota over time.

Single-Cell Classification Using Mass Spectrometry through Interpretable Machine Learning.

The brain consists of organized ensembles of cells that exhibit distinct morphologies, cellular connectivity, and dynamic biochemistries that control the executive functions of an organism. However, the relationships between chemical heterogeneity, cell function, and phenotype are not always understood. Recent advancements in matrix-assisted laser desorption/ionization mass spectrometry have enabled the high-throughput, multiplexed chemical analysis of single cells, capable of resolving hundreds of molecules in each mass spectrum. We developed a machine learning workflow to classify single cells according to their mass spectra based on cell groups of interest (GOI), e.g., neurons vs astrocytes. Three data sets from various cell groups were acquired on three different mass spectrometer platforms representing thousands of individual cell spectra that were collected and used to validate the single cell classification workflow. The trained models achieved >80% classification accuracy and were subjected to the recently developed instance-based model interpretation framework, SHapley Additive exPlanations (SHAP), which locally assigns feature importance for each single-cell spectrum. SHAP values were used for both local and global interpretations of our data sets, preserving the chemical heterogeneity uncovered by the single-cell analysis while offering the ability to perform supervised analysis. The top contributing mass features to each of the GOI were ranked and selected using mean absolute SHAP values, highlighting the features that are specific to the defined GOI. Our approach provides insight into discriminating the chemical profiles of the single cells through interpretable machine learning, facilitating downstream analysis and validation.

Suspected Anaphylactic Reaction to Ketamine in 3 Yucatan Swine (Sus scrofa).

This case series describes the clinical courses of 3 juvenile Yucatan miniature swine (Sus scrofa) that experienced a suspected anaphylactic reaction to ketamine hydrochloride during premedication for protocol-related surgery. All 3 swine rapidly developed diffuse erythema shortly after injection with ketamine-containing drug combinations. Clinical signs ranged from tachycardia and erythema alone to tachycardia and erythema followed by respiratory and cardiac arrest. Ketamine was considered the most likely cause of these reactions because it was the only agent in the premedication sedation combination that was used in all 3 swine. Subsequent intradermal skin testing confirmed this suspicion. With supportive care measures and standard medical interventions for anaphylaxis, all 3 animals recovered well and went on to be successful experimental subjects when an alternative anesthetic regimen that did not contain ketamine was used. To our knowledge, this report is the first description of a suspected adverse ketamine reaction of this type in swine despite the widespread use of the drug in this species. Ketamine anaphylaxis is rare in people, but the few cases described presented with symptoms similar to the clinical signs seen in the pigs in this report. In addition to highlighting a potential adverse drug reaction to ketamine in swine, this case series demonstrates the value of emergency preparedness for even the most routine of procedures.