Mass-spectrometric multi-omics linked to function – State-of-the-art investigations of mitochondria in systems medicine

Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases

Thyroid diseases, including functional and neoplastic diseases, bring a huge burden to people's health. Therefore, a timely and accurate diagnosis is necessary. Mass spectrometry (MS) based multi-omics has become an effective strategy to reveal the complex biological mechanisms of thyroid diseases. The exponential growth of biomedical data has promoted the applications of machine learning (ML) techniques to address new challenges in biology and clinical research. In this review, we presented the detailed review of applications of ML for MS-based multi-omics in thyroid disease. It is primarily divided into two sections. In the first section, MS-based multi-omics, primarily proteomics and metabolomics, and their applications in clinical diseases are briefly discussed. In the second section, several commonly used unsupervised learning and supervised algorithms, such as principal component analysis, hierarchical clustering, random forest, and support vector machines are addressed, and the integration of ML techniques with MS-based multi-omics data and its application in thyroid disease diagnosis is explored.

Omics-based approaches for the systematic profiling of mitochondrial biology

Mitochondria are essential for cellular functions such as metabolism and apoptosis. They dynamically adapt to the changing environmental demands by adjusting their protein, nucleic acid, metabolite, and lipid contents. In addition, the mitochondrial components are modulated on different levels in response to changes, including abundance, activity, and interaction. A wide range of omics-based approaches has been developed to be able to explore mitochondrial adaptation and how mitochondrial function is compromised in disease contexts. Here, we provide an overview of the omics methods that allow us to systematically investigate the different aspects of mitochondrial biology. In addition, we show examples of how these methods have provided new biological insights. The emerging use of these toolboxes provides a more comprehensive understanding of the processes underlying mitochondrial function.

The inhibition effects of chlorogenic acid on the formation of colored oxidation products of (-)-epigallocatechin gallate under enzymatic oxidation

Untargeted Liquid chromatography tandem mass spectrometry (LC-MS) based metabolomics in combination with UV-visible and colorimeter was applied in identifying critical colored enzymatically oxidized products of (-)-epigallocatechin gallate (EGCG). Pearson correlation coefficient analysis between marker compounds and a* value was conducted, and then a series of colored oxidation products were targeted and subsequently identified by diode array detection and mass fragmentation ions. The quinone of oolongtheanin 3-O'-gallate degraded product with quasi-molecular mass ion at m/z 711 was identified as a critical colored oxidation product of single EGCG. To explore the effect of chlorogenic acid on the formation of colored EGCG enzymatic oxidation products, the variation of oxidation products on the oolongtheanin pathway was semi-quantitatively determined. The result showed chlorogenic acid significantly inhibited the formation of colored oxidation products, thus lightened the color of EGCG oxidation mixture. The addition of chlorogenic acid influences the process of tea polyphenols' enzymatic oxidation.

Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis

Lipidomics is the comprehensive analysis of lipids in a given biological system. This investigation is often limited by the low amount and high complexity of biological samples, therefore highly sensitive lipidomics methods are required. Nanoflow-LC/MS offers extremely high sensitivity; however, it is challenging as a more demanding maintenance is often needed compared to conventional microflow-LC approaches. Here, we developed a sensitive and reproducible lipidomics LC method, termed Opti-nQL, which can be applied to any biological system. Opti-nQL has been validated with cellular lipid extracts of human and mouse origin and with different lipid extraction methods. Among the resulting 4000 detected features, 700 and even more unique lipid molecular species have been identified covering 16 lipid sub-classes, while 400 lipids were uniquely structure defined by MS/MS. These results were obtained by analyzing an amount of lipids extract equivalent to 40 ng of proteins, being highly suitable for low abundant samples. MS analysis showed that theOpti-nQL method increases the number of identified lipids, which is evidenced by injecting 20 times less material than in microflow based chromatography, being more reproducible and accurate thus enhancing robustness of lipidomics analysis.

Diabetes and Heart Failure: Multi-Omics Approaches

Diabetes and heart failure, as important global issues, cause substantial expenses to countries and medical systems because of the morbidity and mortality rates. Most people with diabetes suffer from type 2 diabetes, which has an amplifying effect on the prevalence and severity of many health problems such as stroke, neuropathy, retinopathy, kidney injuries, and cardiovascular disease. Type 2 diabetes is one of the cornerstones of heart failure, another health epidemic, with 44% prevalence. Therefore, finding and targeting specific molecular and cellular pathways involved in the pathophysiology of each disease, either in diagnosis or treatment, will be beneficial. For diabetic cardiomyopathy, there are several mechanisms through which clinical heart failure is developed; oxidative stress with mediation of reactive oxygen species (ROS), reduced myocardial perfusion due to endothelial dysfunction, autonomic dysfunction, and metabolic changes, such as impaired glucose levels caused by insulin resistance, are the four main mechanisms. In the field of oxidative stress, advanced glycation end products (AGEs), protein kinase C (PKC), and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) are the key mediators that new omics-driven methods can target. Besides, diabetes can affect myocardial function by impairing calcium (Ca) homeostasis, the mechanism in which reduced protein phosphatase 1 (PP1), sarcoplasmic/endoplasmic reticulum Ca2+ ATPase 2a (SERCA2a), and phosphorylated SERCA2a expressions are the main effectors. This article reviewed the recent omics-driven discoveries in the diagnosis and treatment of type 2 diabetes and heart failure with focus on the common molecular mechanisms.

Development of an in vitro coculture device for the investigation of host-microbe interactions via integrative multiomics approaches

The commensal gut bacterium Akkermansia muciniphila is well known as a promising probiotic candidate that improves host health and prevents diseases. However, the biological interaction of A. muciniphila with human gut epithelial cells has rarely been explored for use in biotherapeutics. Here, we developed an in vitro device that simulates the gut epithelium to elucidate the biological effects of living A. muciniphila via multiomics analysis: the Mimetic Intestinal Host-Microbe Interaction Coculture System (MIMICS). We demonstrated that both human intestinal epithelial cells (Caco-2) and the anaerobic bacterium A. muciniphila can remain viable for 12 h after coculture in the MIMICS. The transcriptomic and proteomic changes (cell-cell junctions, immune responses, and mucin secretion) in gut epithelial cells treated with A. muciniphila closely correspond with those reported in previous in vivo studies. In addition, our proteomic and metabolomic results revealed that A. muciniphila activates glucose and lipid metabolism in gut epithelial cells, leading to an increase in ATP production. This study suggests that A. muciniphila improves metabolism for ATP production in gut epithelial cells and that the MIMICS may be an effective general tool for evaluating the effects of anaerobic bacteria on gut epithelial cells.

From Transcriptomics to Treatment in Inherited Optic Neuropathies

Inherited optic neuropathies, including Leber Hereditary Optic Neuropathy (LHON) and Dominant Optic Atrophy (DOA), are monogenetic diseases with a final common pathway of mitochondrial dysfunction leading to retinal ganglion cell (RGC) death and ultimately loss of vision. They are, therefore, excellent models with which to investigate this ubiquitous disease process-implicated in both common polygenetic ocular diseases (e.g., Glaucoma) and late-onset central nervous system neurodegenerative diseases (e.g., Parkinson disease). In recent years, cellular and animal models of LHON and DOA have matured in parallel with techniques (such as RNA-seq) to determine and analyze the transcriptomes of affected cells. This confluence leaves us at a particularly exciting time with the potential for the identification of novel pathogenic players and therapeutic targets. Here, we present a discussion of the importance of inherited optic neuropathies and how transcriptomic techniques can be exploited in the development of novel mutation-independent, neuroprotective therapies.

Systems biology approaches to study lipidomes in health and disease

Lipids have many important biological roles, such as energy storage sources, structural components of plasma membranes and as intermediates in metabolic and signaling pathways. Lipid metabolism is under tight homeostatic control, exhibiting spatial and dynamic complexity at multiple levels. Consequently, lipid-related disturbances play important roles in the pathogenesis of most of the common diseases. Lipidomics, defined as the study of lipidomes in biological systems, has emerged as a rapidly-growing field. Due to the chemical and functional diversity of lipids, the application of a systems biology approach is essential if one is to address lipid functionality at different physiological levels. In parallel with analytical advances to measure lipids in biological matrices, the field of computational lipidomics has been rapidly advancing, enabling modeling of lipidomes in their pathway, spatial and dynamic contexts. This review focuses on recent progress in systems biology approaches to study lipids in health and disease, with specific emphasis on methodological advances and biomedical applications.

Applications of mass spectrometry imaging in virus research

Mass spectrometry imaging (MSI) is a label-free molecular imaging technique allowing an untargeted detection of a broad range of biomolecules and xenobiotics. MSI enables imaging of the spatial distribution of proteins, peptides, lipids and metabolites from a wide range of samples. To date, this technique is commonly applied to tissue sections in cancer diagnostics and biomarker development, but also molecular histology in general. Advances in the methodology and bioinformatics improved the resolution of MS images below the single cell level and increased the flexibility of the workflow. However, MSI-based research in virology is just starting to gain momentum and its full potential has not been exploited yet. In this review, we discuss the main applications of MSI in virology. We review important aspects of matrix-assisted laser desorption/ionization (MALDI) MSI, the most widely used MSI technique in virology. In addition, we summarize relevant literature on MSI studies that aim to unravel virus-host interactions and virus pathogenesis, to elucidate antiviral drug kinetics and to improve current viral disease diagnostics. Collectively, these studies strongly improve our general understanding of virus-induced changes in the proteome, metabolome and metabolite distribution in host tissues of humans, animals and plants upon infection. Furthermore, latest MSI research provided important insights into the drug distribution and distribution kinetics, especially in antiretroviral research. Finally, MSI-based investigations of oncogenic viruses greatly increased our knowledge on tumor mass signatures and facilitated the identification of cancer biomarkers.

Antioxidant activity and absorption of cyanidin-3-O-glucoside liposomes in GES-1 cells in vitro

The use of anthocyanins are limited by their chemical properties. Recent evidence suggests Cyanidin-3-O-glucoside (C3 G) liposomes via the ethanol injection method exhibit improved stability. In the current study, the characterization and cell absorption of C3 G liposomes were explored via transmission electron microscopy and flow cytometry. The internalization of the C3 G liposomes across the gastric epithelial cell monolayer (GES-1 cells) were investigated. Results showed that the particle size and encapsulation efficiency were 234 ± 9.35 nm and 75.0% ± 0.001, respectively. The total antioxidant capacity (T-AOC) and malondialdehyde (MDA) content were used to evaluate the antioxidant activity of C3 G liposomes. The C3 G liposomes can obviously increased T-AOC and decreased the MDA content.Collectively, C3 G liposomes protected human GES-1 cells from gastric mucosal injury induced by H₂O₂ by activating the related antioxidant pathway. Our research could provide a new effective treatment strategy for the absorption of stomach drugs.Abbreviations: C3G: Cyanidin-3-O-glucoside; LP: Liposome; GES-1 cells: Human gastric epithelial cell lines; FBS: Fetal Bovine Serum; PBS: Phosphate-buffered saline; PC: Phosphatidylcholine; CH: Cholesterol; MDA: Malondialdehyde; TEM: Transmission electron microscope; FCM: Flow cytometry; FITC: Fluorescein isothiocyanate; DAPI: 4', 6-diamidino-2phenylidole; FT-IR: Fourier Transform infrared spectroscopy; PFA: Paraformaldehyde.