scholarly journals Salivary bacterial signatures in depression-obesity comorbidity are associated with neurotransmitters and neuroactive dipeptides

2021 ◽  
Author(s):  
Suzi Hong ◽  
Gajender Aleti ◽  
Jordan N. Kohn ◽  
Emily A. Troyer ◽  
Kelly Weldon ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Depressive Symptomatology ◽  
Aromatic Amino Acids ◽  
Oral Microbiome ◽  
Mass Spectrometry Analysis ◽  
Metabolomics Data ◽  
16S Sequencing ◽  
Spectrometry Analysis ◽  
Oral Microbes ◽  
Host Microbe Interactions

Abstract BackgroundDepression and obesity, both of which are highly prevalent and inflammation underlies, often co-occur. Microbiome perturbations are implicated in obesity-inflammation-depression interrelationships, but how microbiome alterations contribute to underlying pathologic processes remains unclear. Metabolomic investigations to uncover microbial neuroactive metabolites may offer mechanistic insights into host-microbe interactions. MethodsUsing 16S sequencing and untargeted mass spectrometry of saliva, and blood monocyte inflammation regulation assays, we determined key microbes, metabolites and host inflammation in association with depressive symptomatology, obesity, and depressive symptomatology-obesity comorbidity. ResultsGram-negative bacteria with inflammation potential were enriched relative to Gram-positive bacteria in comorbid obesity-depression, supporting the inflammation-oral microbiome link in obesity-depression interrelationships. Oral microbiome was highly predictive of depressive symptomatology-obesity co-occurrences than obesity and depressive symptomatology independently, suggesting specific microbial signatures associated with obesity-depression co-occurrences. Mass spectrometry analysis revealed significant changes in levels of signaling molecules of microbiota, microbial or dietary derived signaling peptides and aromatic amino acids among host phenotypes. Furthermore, integration of the microbiome and metabolomics data revealed that key oral microbes, many previously shown to have neuroactive potential, co-occurred with potential neuropeptides and biosynthetic precursors of the neurotransmitters dopamine, epinephrine and serotonin. ConclusionsTogether, our findings offer novel insights into oral microbial-brain connection and potential neuroactive metabolites involved.

scholarly journals Salivary bacterial signatures in depression-obesity comorbidity are associated with neurotransmitters and neuroactive dipeptides

2021 ◽  
Author(s):  
Gajender Aleti ◽  
Jordan N Kohn ◽  
Emily A Troyer ◽  
Kelly Weldon ◽  
Shi Huang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Depressive Symptomatology ◽  
Aromatic Amino Acids ◽  
Oral Microbiome ◽  
Mass Spectrometry Analysis ◽  
Metabolomics Data ◽  
16S Sequencing ◽  
Spectrometry Analysis ◽  
Oral Microbes ◽  
Host Microbe Interactions

Depression and obesity, both of which are highly prevalent and inflammation underlies, often co-occur. Microbiome perturbations are implicated in obesity-inflammation-depression interrelationships, but how microbiome alterations contribute to underlying pathologic processes remains unclear. Metabolomic investigations to uncover microbial neuroactive metabolites may offer mechanistic insights into host-microbe interactions. Using 16S sequencing and untargeted mass spectrometry of saliva, and blood monocyte inflammation regulation assays, we determined key microbes, metabolites and host inflammation in association with depressive symptomatology, obesity, and depressive symptomatology-obesity comorbidity. Gram-negative bacteria with inflammation potential were enriched relative to Gram-positive bacteria in comorbid obesity-depression, supporting the inflammation-oral microbiome link in obesity-depression interrelationships. Oral microbiome was highly predictive of depressive symptomatology-obesity co-occurrences than obesity and depressive symptomatology independently, suggesting specific microbial signatures associated with obesity-depression co-occurrences. Mass spectrometry analysis revealed significant changes in levels of signaling molecules of microbiota, microbial or dietary derived signaling peptides and aromatic amino acids among host phenotypes. Furthermore, integration of the microbiome and metabolomics data revealed that key oral microbes, many previously shown to have neuroactive potential, co-occurred with potential neuropeptides and biosynthetic precursors of the neurotransmitters dopamine, epinephrine and serotonin. Together, our findings offer novel insights into oral microbial-brain connection and potential neuroactive metabolites involved.

scholarly journals MStractor: R Workflow Package for Enhancing Metabolomics Data Pre-Processing and Visualization

Metabolites ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 492
Author(s):  
Luca Nicolotti ◽  
Jeremy Hack ◽  
Markus Herderich ◽  
Natoiya Lloyd
Keyword(s):  
Mass Spectrometry ◽  
Data Processing ◽  
Programming Languages ◽  
Detailed Comparison ◽  
Mass Spectrometry Data ◽  
Mass Spectrometry Analysis ◽  
Molecular Feature ◽  
Metabolomics Data ◽  
Spectrometry Analysis ◽  
Mass Spectrometry Technology

Untargeted metabolomics experiments for characterizing complex biological samples, conducted with chromatography/mass spectrometry technology, generate large datasets containing very complex and highly variable information. Many data-processing options are available, however, both commercial and open-source solutions for data processing have limitations, such as vendor platform exclusivity and/or requiring familiarity with diverse programming languages. Data processing of untargeted metabolite data is a particular problem for laboratories that specialize in non-routine mass spectrometry analysis of diverse sample types across humans, animals, plants, fungi, and microorganisms. Here, we present MStractor, an R workflow package developed to streamline and enhance pre-processing of metabolomics mass spectrometry data and visualization. MStractor combines functions for molecular feature extraction with user-friendly dedicated GUIs for chromatographic and mass spectromerty (MS) parameter input, graphical quality-control outputs, and descriptive statistics. MStractor performance was evaluated through a detailed comparison with XCMS Online. The MStractor package is freely available on GitHub at the MetabolomicsSA repository.

scholarly journals Effect of Ocular Hypertension on D-β-Aspartic Acid-Containing Proteins in the Retinas of Rats

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Takashi Kanamoto ◽  
Takashi Tachibana ◽  
Yasushi Kitaoka ◽  
Toshio Hisatomi ◽  
Yasuhiro Ikeda ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ocular Hypertension ◽  
Aspartic Acid ◽  
Atp Synthase ◽  
Wistar Rats ◽  
Protein Band ◽  
Mass Spectrometry Analysis ◽  
Liquid Chromatography Mass Spectrometry ◽  
Spectrometry Analysis ◽  
Sds Page

Purpose. To investigate the effect of ocular hypertension-induced isomerization of aspartic acid in retinal proteins. Methods. Adult Wistar rats with ocular hypertension were used as an experimental model. D-β-aspartic acid-containing proteins were isolated by SDS-PAGE and western blot with an anti-D-β-aspartic acid antibody and identified by liquid chromatography-mass spectrometry analysis. The concentration of ATP was measured by ELISA. Results. D-β-aspartic acid was expressed in a protein band at around 44.5 kDa at much higher quantities in the retinas of rats with ocular hypertension than in those of normotensive rats. The 44.5 kDa protein band was mainly composed of α-enolase, S-arrestin, and ATP synthase subunits α and β, in both the ocular hypertensive and normotensive retinas. Moreover, increasing intraocular pressure was correlated with increasing ATP concentrations in the retinas of rats. Conclusion. Ocular hypertension affected the expression of proteins containing D-β-aspartic acid, including ATP synthase subunits, and up-regulation of ATP in the retinas of rats.

scholarly journals N-Terminomics Strategies for Protease Substrates Profiling

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4699
Author(s):  
Mubashir Mintoo ◽  
Amritangshu Chakravarty ◽  
Ronak Tilvawala
Keyword(s):  
Mass Spectrometry ◽  
Protease Activity ◽  
Viral Infections ◽  
Mass Spectrometry Analysis ◽  
Post Translational Modification ◽  
Spectrometry Analysis ◽  
Physiological Conditions ◽  
Inflammatory Conditions ◽  
Biological Mixtures

Proteases play a central role in various biochemical pathways catalyzing and regulating key biological events. Proteases catalyze an irreversible post-translational modification called proteolysis by hydrolyzing peptide bonds in proteins. Given the destructive potential of proteolysis, protease activity is tightly regulated. Dysregulation of protease activity has been reported in numerous disease conditions, including cancers, neurodegenerative diseases, inflammatory conditions, cardiovascular diseases, and viral infections. The proteolytic profile of a cell, tissue, or organ is governed by protease activation, activity, and substrate specificity. Thus, identifying protease substrates and proteolytic events under physiological conditions can provide crucial information about how the change in protease regulation can alter the cellular proteolytic landscape. In recent years, mass spectrometry-based techniques called N-terminomics have become instrumental in identifying protease substrates from complex biological mixtures. N-terminomics employs the labeling and enrichment of native and neo-N-termini peptides, generated upon proteolysis followed by mass spectrometry analysis allowing protease substrate profiling directly from biological samples. In this review, we provide a brief overview of N-terminomics techniques, focusing on their strengths, weaknesses, limitations, and providing specific examples where they were successfully employed to identify protease substrates in vivo and under physiological conditions. In addition, we explore the current trends in the protease field and the potential for future developments.

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