Extracting Biological Insight from Untargeted Lipidomics Data

Ultra-High-Performance Liquid Chromatography-Orbitrap-MS-Based Untargeted Lipidomics Reveal Lipid Characteristics of a Clinical Strain of Mycoplasma bovis from Holstein Cow

Mycoplasma bovis is a global concern for the cattle industry owing to its high rates of infection and resulting morbidity, but there are no reports on the lipid composition and metabolic pathways. This study examined the lipidomics of M. bovis to better investigate the biological characteristics of clinical isolates of M. bovis. The M. bovis strains NX114 and PG45, cultivated to log-phase, underwent untargeted lipidomics via ultra-high-performance liquid chromatography-mass spectrometry for differential analysis. Over 65 lipid types and 1476 lipid molecules were identified. We found that glycerophospholipids and sphingolipids constitute the predominant lipid components of M. bovis, with significant constituents of its cell membrane comprising ceramides, phosphatidylglycerols, sphingomyelins, triacylglycerols, hexosylceramides, ether-linked oxidized phosphatidylcholines, and oxidized phosphatidylglycerols. Secondly, 562 differentially expressed lipid molecules were identified, including 17 lipid subclasses (15 up-regulated and 2 down-regulated) with significant differences in relative content. These findings indicate that distinct M. bovis isolates contain structurally varied lipid molecules, with sphingomyelin, phosphatidylinositol, cardiolipin, and phosphatidylcholine being characteristic lipids. The glycerophospholipid metabolism pathway was identified as a key pathway regulating lipid metabolism in M. bovis by KEGG pathway enrichment analysis. The results indicated alterations in the lipid metabolism of M. bovis, offering insights into its pathogenic mechanisms.

Multi-Omics Approaches in Colorectal Cancer Screening and Diagnosis, Recent Updates and Future Perspectives

Colorectal cancer (CRC) is common Cancer as well as the third leading cause of mortality around the world; its exact molecular mechanism remains elusive. Although CRC risk is significantly correlated with genetic factors, the pathophysiology of CRC is also influenced by external and internal exposures and their interactions with genetic factors. The field of CRC research has recently benefited from significant advances through Omics technologies for screening biomarkers, including genes, transcripts, proteins, metabolites, microbiome, and lipidome unbiasedly. A promising application of omics technologies could enable new biomarkers to be found for the screening and diagnosis of CRC. Single-omics technologies cannot fully understand the molecular mechanisms of CRC. Therefore, this review article aims to summarize the multi-omics studies of Colorectal cancer, including genomics, transcriptomics, proteomics, microbiomics, metabolomics, and lipidomics that may shed new light on the discovery of novel biomarkers. It can contribute to identifying and validating new CRC biomarkers and better understanding colorectal carcinogenesis. Discovering biomarkers through multi-omics technologies could be difficult but valuable for disease genotyping and phenotyping. That can provide a better knowledge of CRC prognosis, diagnosis, and treatments.

Omics technologies in allergy and asthma research: An EAACI position paper

Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force "Omics technologies in allergic research" broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients' stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Lipidomics: An excellent tool for chronic disease detection

It has been known as almost all the cells consists a lipid molecule which has a considerable impact in various biological processes. Lipids have been investigated with a potential role for the formation of cellular membrane and thereby maintaining the structural integrity. Omics has placed as a combined technologies utilized for an exploaration of mechanistic actions in several kinds of molecules that make up the cells of an organism. Lipidomics has been recognized as a newly emerged branch of omics technology. This technology has the captivating factors to classify and characterize almost all the cellular lipids with the help of various analytical techniques and computational biological plateform. In lipidomics studies, structural display of several lipid biomarkers could also be analyzed and considered for actual disease diagnosis procedures. This could also replace certain traditional diagnostics method at all over the globe. Our review focuses how important this lipidomics particularly in disease diagnosis and also covers various analytical techniques and computational methods or bioinformatics tools in for the diagnosis of disease. In addtion, we also pinponted the possible role of lipids in several kinds of cellular disorders including cancer, neurodegenerative diseases, cardiovascular diseases, diabetes and obesity in human population. .