Molecular omics最新文献

Several software packages are available for the analysis of proteomic LC-MS/MS data, including commercial (e.g. Mascot/Progenesis LC-MS) and open access software (e.g. MaxQuant). In this study, Progenesis and MaxQuant were used to analyse the same data set from human liver microsomes (n = 23). Comparison focussed on the total number of peptides and proteins identified by the two packages. For the peptides exclusively identified by each software package, distribution of peptide length, hydrophobicity, molecular weight, isoelectric point and score were compared. Using standard cut-off peptide scores, we found an average of only 65% overlap in detected peptides, with surprisingly little consistency in the characteristics of peptides exclusively detected by each package. Generally, MaxQuant detected more peptides than Progenesis, and the additional peptides were longer and had relatively lower scores. Progenesis-specific peptides tended to be more hydrophilic and basic relative to peptides detected only by MaxQuant. At the protein level, we focussed on drug-metabolising enzymes (DMEs) and transporters, by comparing the number of unique peptides detected by the two packages for these specific proteins of interest, and their abundance. The abundance of DMEs and SLC transporters showed good correlation between the two software tools, but ABC showed less consistency. In conclusion, in order to maximise the use of MS datasets, we recommend processing with more than one software package. Together, Progenesis and MaxQuant provided excellent coverage, with a core of common peptides identified in a very robust way.

The modification patterns of N6-methyladenosine (m6A) regulators and interacting genes are deeply involved in tumors. However, the effect of m6A modification patterns on human proteomics remains largely unknown. We evaluated the molecular characteristics and clinical relevance of m6A modification proteomics patterns among 1013 pan-cancer samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). More than half of the m6A proteins were expressed at higher levels in tumor tissues and presented oncogenic characteristics. Furthermore, we performed multi-omics analyses integrating with transcriptomics data of m6A regulators and interactive coding and non-coding RNAs and developed a m6A multi-omics signature to identify potential m6A modification target proteins across global proteomics. It was significantly associated with overall survival in nine cancer types, tumor mutation burden (P = 0.01), and immune checkpoints including PD-L1 (P = 4.9 × 10⁻⁸) and PD-1 (P < 0.01). We identified 51 novel proteins associated with the multi-omics signature (P_FDR < 0.05). These proteins were functional through pathway enrichment analyses. The protein with the highest hit frequency was CHORDC1, which was significantly up-regulated in tumor tissues in nine cancer types. Its higher abundance was significantly associated with a poorer prognosis in seven cancer types. The identified m6A target proteins might provide infomation for the study of molecular mechanism of cancer.

Type 1 diabetes (T1D) has been reported to cause systematic metabolic disorders, but metabolic changes in different intestinal segments of T1D remain unclear. In this study, we analyzed metabolic profiles in the jejunum, ileum, cecum and colon of streptozocin-induced T1D and age-matched control (CON) mice by an LC-MS-based metabolomics method. The results show that segment-specific metabolic disorders occurred in the gut of T1D mice. In the jejunum, we found that T1D mainly led to disordered amino acid metabolism and most amino acids were significantly lower relative to CON mice. Moreover, fatty acid metabolism was disrupted mainly in the ileum, cecum and colon of T1D mice, such as arachidonic acid, alpha-linolenic acid and linoleic acid metabolism. Thus, our study reveals spatial metabolic heterogeneity in the gut of T1D mice and provides a metabolic view on diabetes-associated intestinal diseases.

Physical inactivity affects multiple organ systems, including the musculoskeletal system, which upsets the delicate balance of several secretory factors leading to metabolic derailment. This reduces contractile recruitment of the skeletal muscle with dampening of its oxidative capacity resulting in impaired intramuscular lipid metabolism and substrate utilization. We hypothesized that this altered phenotype would also have an indispensable effect on circulatory cytokines and the level of metabolic intermediates. In this study, comparison between sedentary (SED) and exercised (EXER) animal models showed that organismal metabolic parameters (body mass, oxygen utilization and glucose tolerance) are altered based on physical activity. Our data suggest that cytokines linked to glycemic excursions (insulin, c-peptide, glucagon) and their passive regulators (leptin, BDNF, active ghrelin, and GIP) exhibit changes in the SED group. Furthermore, some of the proinflammatory cytokines and myokines were upregulated in SED. Interestingly, serum metabolite analysis showed that the levels of glucogenic amino acids (alanine, glycine, tryptophan, proline and valine), nitrogenous amino acids (ornithine, asparagine, and glutamine) and myogenic metabolites (taurine, creatine) were altered due to the level of physical activity. A pyrimidine nucleoside (uridine), lipid metabolite (glycerol) and ketone bodies (acetoacetate and acetate) were found to be altered in SED. A Spearman rank correlation study between SED and CTRL showed that cytokines build a deformed network with metabolites in SED, indicating significant modifications in amino acids, phosphatidylinositol phosphate and glycerophospholipid metabolic pathways. Overall, long-term physical inactivity reorganizes the profile of proinflammatory cytokines, glucose sensing hormones, and protein and glycerophospholipid metabolism, which might be the initial factors of metabolic diseases due to SED.

Correction for ‘Generation of β-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids’ by Lisa Morisseau et al., Mol. Omics, 2023, https://doi.org/10.1039/d3mo00050h.

The neural pathways of Caenorhabditis elegans play a crucial role in regulating host immunity and inflammation during pathogenic infections. To understand the major neuro-immune signaling pathways, this study aimed to identify the key regulatory proteins in the host C. elegans during C. sakazakii infection. We used high-throughput label-free quantitative proteomics and identified 69 differentially expressed proteins. KEGG analysis revealed that C. sakazakii elicited host immune signaling cascades primarily including mTOR signaling, axon regeneration, metabolic pathways (let-363 and acox-1.4), calcium signaling (mlck-1), and longevity regulating pathways (ddl-2), respectively. The abrogation in functional loss of mTOR-associated players deciphered that C. sakazakii infection negatively regulated the lifespan of mutant worms (akt-1, let-363 and dlk-1), including physiological aberrations, such as reduced pharyngeal pumping and egg production. Additionally, the candidate pathway proteins were validated by transcriptional profiling of their corresponding genes. Furthermore, immunoblotting showed the downregulation of mTORC2/SGK-1 during the later hours of pathogen exposure. Overall, our findings profoundly provide an understanding of the specificity of proteome imbalance in affecting neuro-immune regulations during C. sakazakii infection.

Since the identification of four different pancreatic β-cell subtypes and bi-hormomal cells playing a role in the diabetes pathogenesis, the search for in vitro models that mimics such cells heterogeneity became a key priority in experimental and clinical diabetology. We investigated the potential of human induced pluripotent stem cells to lead to the development of the different β-cells subtypes in honeycomb microwell-based 3D spheroids. The glucose-stimulated insulin secretion confirmed the spheroids functionality. Then, we performed a single cell RNA sequencing of the spheroids. Using a knowledge-based analysis with a stringency on the pancreatic markers, we extracted the β-cells INS+/UCN3+ subtype (11%; β1-like cells), the INS+/ST8SIA1+/CD9− subtype (3%, β3-like cells) and INS+/CD9+/ST8SIA1-subtype (1%; β2-like cells) consistently with literature findings. We did not detect the INS+/ST8SIA1+/CD9+ cells (β4-like cells). Then, we also identified four bi-hormonal cells subpopulations including δ-like cells (INS+/SST+, 6%), γ-like cells (INS+/PPY+, 3%), α-like-cells (INS+/GCG+, 6%) and ε-like-cells (INS+/GHRL+, 2%). Using data-driven clustering, we extracted four progenitors’ subpopulations (with the lower level of INS gene) that included one population highly expressing inhibin genes (INHBA+/INHBB+), one population highly expressing KCNJ3+/TPH1+, one population expressing hepatocyte-like lineage markers (HNF1A+/AFP+), and one population expressing stem-like cell pancreatic progenitor markers (SOX2+/NEUROG3+). Furthermore, among the cycling population we found a large number of REST+ cells and CD9+ cells (CD9+/SPARC+/REST+). Our data confirm that our differentiation leads to large β-cell heterogeneity, which can be used for investigating β-cells plasticity under physiological and pathophysiological conditions.

Cancer is one of the deadliest diseases in humans and dogs. Nevertheless, most tumor types spread faster in canines, and early cancer detection methods are necessary to enhance animal survival. Here, cerumen (earwax) was tested as a source of potential biomarkers for cancer evaluation in dogs. Earwax samples from dogs were collected from tumor-bearing and clinically healthy dogs, followed by Headspace/Gas Chromatography-Mass Spectrometry (HS/GC-MS) analyses and multivariate statistical workflow. An evolutionary-based multivariate algorithm selected 18 out of 128 volatile metabolites as a potential cancer biomarker panel in dogs. The candidate biomarkers showed a full discrimination pattern between tumor-bearing dogs and cancer-free canines with high accuracy in the test dataset: an accuracy of 95.0% (75.1–99.9), and sensitivity and specificity of 100.0% and 92.9%, respectively. In summary, this work raises a new perspective on cancer diagnosis in dogs, being carried out painlessly and non-invasive, facilitating sample collection and periodic application in a veterinary routine.

Lactic acid is a versatile, multi-functional organic monomer in various industries, creating worldwide demand. High titer lactic acid production was achieved by novel Bacillus amyloliquefaciens J2V2AA through sugarcane molasses fermentation up to 178 mg mL⁻¹. A metabolomics approach such as combined GC-MS and LC-MS was applied to elucidate the involvement of key metabolites in lactic acid production. The results revealed the participation of 58 known intra-cellular metabolites at various pathways in lactic acid production. Twenty-eight highly up-regulated and down-regulated metabolites were analyzed, and a schematic diagram of a possible lactic acid production pathway was proposed. The produced lactic acid was analyzed through FTIR, UV-Spectrum, and HPLC analysis.

Dietary methionine restriction is associated with a reduction in tumor growth in preclinical studies and an increase in lifespan in animal models. The mechanism by which methionine restriction inhibits tumor growth while sparing normal cells is incompletely understood. We do know that normal cells can utilize methionine or homocysteine interchangeably (methionine independence) while most cancer cells are strictly dependent on methionine availability. Here, we compared a typical methionine dependent and a rare methionine independent melanoma cell line. We show that replacing methionine, a methyl donor, with its precursor homocysteine generally induced hypomethylation in gene promoters. This decrease was similar in methionine dependent and methionine independent cells. There was only a low level of pathway enrichment, suggesting that the hypomethylation is generalized rather than gene specific. Whole proteome and transcriptome were also analyzed. This analysis revealed that contrarily to the effect on methylation, the replacement of methionine with homocysteine had a much greater effect on the transcriptome and proteome of methionine dependent cells than methionine independent cells. Interestingly, methionine adenosyltransferase 2A (MAT2A), responsible for the synthesis of S-adenosylmethionine from methionine, was equally strongly upregulated in both cell lines. This suggests that the absence of methionine is equally detected but triggers different outcomes in methionine dependent versus independent cells. Our analysis reveals the importance of cell cycle control, DNA damage repair, translation, nutrient sensing, oxidative stress and immune functions in the cellular response to methionine stress in melanoma.