Molecular omics最新文献

Maren Runchang pill (MRRCP) is a Chinese patent medicine used to treat constipation in clinics. It has multi-component and multi-target characteristics, and there is an urgent need to screen markers to ensure its quality. The aim of this study was to screen quality markers of MRRCP based on a “differential compounds-bioactivity” strategy using machine learning and network pharmacology to ensure the effectiveness and stability of MRRCP. In this study, UPLC-Q-TOF-MS/MS was used to identify chemical compounds in MRRCP and machine learning algorithms were applied to screen differential compounds. The quality markers were further screened by network pharmacology. Meanwhile, molecular docking was used to verify the screening results of machine learning and network pharmacology. A total of 28 constituents in MRRCP were identified, and four differential compounds were screened by machine learning algorithms. Subsequently, a total of two quality markers (rutin and rubiadin) in MRRCP. Additionally, the molecular docking results showed that quality markers could spontaneously bind to core targets. This study provides a reference for improving the quality evaluation method of MRRCP to ensure its quality. More importantly, it provided a new approach to screen quality markers in Chinese patent medicines.

Citrus is a crucial crop with a significant economic impact globally. However, postharvest decay caused by fungal pathogens poses a considerable threat, leading to substantial financial losses. Penicillium digitatum, Penicillium italicum, Geotrichum citri-aurantii and Phyllosticta citricarpa are the main fungal pathogens, causing green mold, blue mold, sour rot and citrus black spot diseases, respectively. The use of chemical fungicides as a control strategy in citrus raises concerns about food and environmental safety. Therefore, understanding the molecular basis of host–pathogen interactions is essential to find safer alternatives. This review highlights the potential of the metabolomics approach in the search for bioactive compounds involved in the pathogen–citrus interaction, and how the integration of metabolomics and genomics contributes to the understanding of secondary metabolites associated with fungal virulence and the fungal infection mechanisms. Our goal is to provide a pipeline combining metabolomics and genomics that can effectively guide researchers to perform studies aiming to contribute to the understanding of the fundamental chemical and biochemical aspects of pathogen–host interactions, in order to effectively develop new alternatives for fungal diseases in citrus cultivation. We intend to inspire the scientific community to question unexplored biological systems, and to employ diverse analytical approaches and metabolomics techniques to address outstanding questions about the non-studied pathosystems from a chemical biology perspective.

Nanoflow liquid chromatography-mass spectrometry is key to enabling in-depth proteome profiling of trace samples, including single cells, but these separations can lack robustness due to the use of narrow-bore columns that are susceptible to clogging. In the case of single-cell proteomics, offline cleanup steps are generally omitted to avoid losses to additional surfaces, and online solid-phase extraction/trap columns frequently provide the only opportunity to remove salts and insoluble debris before the sample is introduced to the analytical column. Trap columns are traditionally short, packed columns used to load and concentrate analytes at flow rates greater than those employed in analytical columns, and since these first encounter the uncleaned sample mixture, trap columns are also susceptible to clogging. We hypothesized that clogging could be avoided by using large-bore porous layer open tubular trap columns (PLOTrap). The low back pressure ensured that the PLOTraps could also serve as the sample loop, thus allowing sample cleanup and injection with a single 6-port valve. We found that PLOTraps could effectively remove debris to avoid column clogging. We also evaluated multiple stationary phases and PLOTrap diameters to optimize performance in terms of peak widths and sample loading capacities. Optimized PLOTraps were compared to conventional packed trap columns operated in forward and backflush modes, and were found to have similar chromatographic performance of backflushed traps while providing improved debris removal for robust analysis of trace samples.

Plants should be probably thought of as the most formidable chemical laboratory that can be exploited for the production of an incredible number of molecules with remarkable structural and chemical diversity that cannot be matched by any synthetic libraries of small molecules. The bryophytes chemistry has been neglected for too long, but in the last ten years, this scenery is changing, with several studies being made using extracts from bryophytes, aimed at the characterization of interesting metabolites, with their metabolome screened. The main objective of this study was to analyze the metabolome of Brittonodoxa subpinnata, a native Brazilian moss species, which occurs in the two Brazilian hotspots. GC-MS and LC-MS² were performed. All extracts were analyzed using the molecular networking approach. The four extracts of B. subpinnata (polar, non-polar, soluble, and insoluble) resulted in 928 features detected within the established parameters. 189 (20.4%) compounds were annotated, with sugars, fatty acids, flavonoids, and biflavonoids as the major constituents. Sucrose was the sugar with the highest quantity; palmitic acid the major fatty acid but with great presence of very long-chain fatty acids rarely found in higher plants, glycosylated flavonoids were the major flavonoids, and biflavonoids majorly composed by units of flavones and flavanones, exclusively found in the cell wall. Despite the high percentage, this work leaves a significant gap for future works using other structure elucidation techniques, such as NMR.

Clubroot is a destructive root disease of canola (Brassica napus L.) caused by Plasmodiophora brassicae Woronin. Despite extensive research into the molecular responses of B. napus to P. brassicae, there is limited information on proteome- and metabolome-level changes in response to the pathogen, especially during the initial stages of infection. In this study, we have investigated the proteome- and metabolome- level changes in the roots of clubroot-resistant (CR) and -susceptible (CS) doubled-haploid (DH) B. napus lines, in response to P. brassicae pathotype 3H at 1-, 4-, and 7-days post-inoculation (DPI). Root proteomes were analyzed using nanoflow liquid chromatography coupled with tandem mass spectrometry (nano LC-MS/MS). Comparisons of pathogen-inoculated and uninoculated root proteomes revealed 2515 and 1556 differentially abundant proteins at one or more time points (1-, 4-, and 7-DPI) in the CR and CS genotypes, respectively. Several proteins related to primary metabolites (e.g., amino acids, fatty acids, and lipids), secondary metabolites (e.g., glucosinolates), and cell wall reinforcement-related proteins [e.g., laccase, peroxidases, and plant invertase/pectin methylesterase inhibitors (PInv/PMEI)] were identified. Eleven nucleotides and nucleoside-related metabolites, and eight fatty acids and sphingolipid-related metabolites were identified in the metabolomics study. To our knowledge, this is the first report of root proteome-level changes and associated alterations in metabolites during the early stages of P. brassicae infection in B. napus.

The present study deals with the metabolomic status of Ulva cells undergoing phase transition (vegetative, determination and differentiation) when exposed to different abiotic conditions. The objective was to study whether metabolite changes occurring during the phase transition reveal any commonality among differential abiotic conditions. The phase transition was followed through microscopic observations and ¹H NMR characterization at 0 h, 24 h, and 48 h after the incubation of the thallus under abiotic conditions, such as different salinities (20–35 psu), temperatures (20–35 °C), photoperiods (18 : 6, 12 : 12, and 6 : 18 D/N), light intensities (220, 350, and 500 μmol photons m⁻² s⁻¹), nitrate (0.05–0.2 g L⁻¹) and phosphate (0.05–0.2 g L⁻¹) concentrations. Microscopic analysis revealed the role of all abiotic conditions except variable salinity and phosphate concentration in phase transition. NMR analysis revealed that glucose increased in the determination phase [7.58 to 9.62 normalized intensity (AU)] and differentiation phase (5.85 to 6.41 AU) from 20 °C to 25 °C temperature. Coniferyl aldehyde increased in vegetative (5.79 to 6.83 AU) and differentiation (6.66 to 7.40 AU) phases from 20 °C to 30 °C temperature. The highest average (22.97) was found in photoperiod (average range = 0–122.91) and the highest SD (24.73) in salinity (SD range = 1.86–57.04) in region 9 (creatinine and cysteine) of the differentiation phase. A total of 30 metabolites were identified under the categories of sugars, amino acids, and aromatic compounds. The present study will aid in understanding the mechanisms underlying cell differentiation during reproduction. The result may serve as an important reference point for future studies, besides helping in controlling seedling preparation for commercial farming as well as the management of rapid green tide formation.

Long considered active only in the germline, the PIWI/piRNA pathway is now known to play a significant role in somatic cells, especially neurons. In this study, piRNAs were profiled in the human retina and retinal pigment epithelium (RPE). Furthermore, RNA immunoprecipitation with HIWI2 (PIWIL4) in ARPE19 cells yielded 261 piRNAs, and the expression of selective piRNAs in donor eyes was assessed by qRT-PCR. Intriguingly, computational analysis revealed complete and partial seed sequence similarity between piR-hsa-26131 and the sensory organ specific miR-183/96/182 cluster. Furthermore, the expression of retina-enriched piR-hsa-26131 was positively correlated with miR-182 in HIWI2-silenced Y79 cells. In addition, the lnc-ZNF169 sequence matched with two miRNAs of the let-7 family, and piRNAs, piR-hsa-11361 and piR-hsa-11360, which could modulate the regulatory network of retinal differentiation. Interestingly, we annotated four enriched motifs among the piRNAs and found that the piRNAs containing CACAATG and CTCATCAKYG motifs were snoRNA-derived piRNAs, which are significantly associated with developmental functions. However, piRNAs consisting of ACCACTANACCAC and AKCACGYTCSC motifs were mainly tRNA-derived fragments linked to stress response and sensory perception. Additionally, co-expression network analysis revealed cell cycle control, intracellular transport and stress response as the important biological functions regulated by piRNAs in the retina. Moreover, loss of piRNAs in HIWI2 knockdown ARPE19 confirmed altered expression of targets implicated in intracellular transport, circadian clock, and retinal degeneration. Moreover, piRNAs were dysregulated under oxidative stress conditions, indicating their potential role in retinal pathology. Therefore, we postulate that piRNAs, miRNAs, and lncRNAs might have a functional interplay during retinal development and functions to regulate retinal homeostasis.

Heart failure is a complex syndrome characterized by progressive circulatory dysfunction, manifesting clinically as pulmonary and systemic venous congestion, alongside inadequate tissue perfusion. The early identification of HF, particularly at the mild and moderate stages (stages B and C), presents a clinical challenge due to the overlap of signs, symptoms, and natriuretic peptide levels with other cardiorespiratory pathologies. Nonetheless, early detection coupled with timely pharmacological intervention is imperative for enhancing patient outcomes. Advances in high-throughput omics technologies have enabled researchers to analyze patient-derived biofluids and tissues, discovering biomarkers that are sensitive and specific for HF diagnosis. Due to the diversity of HF etiology, it is insufficient to study the diagnostic data of early HF using a single omics technology. This study reviewed the latest progress in genomics, transcriptomics, proteomics, and metabolomics for the identification of HF biomarkers, offering novel insights into the early clinical diagnosis of HF. However, the validity of biomarkers depends on the disease status, intervention time, genetic diversity and comorbidities of the subjects. Moreover, biomarkers lack generalizability in different clinical settings. Hence, it is imperative to conduct multi-center, large-scale and standardized clinical trials to enhance the diagnostic accuracy and utility of HF biomarkers.

Areca nut (Areca catechu L.) is commonly consumed as a chewing food in the Asian region. However, the investigations into the components of areca nut are limited. In this study, we have developed an approach that combines mass spectrometry with feature-based molecular network to explore the chemical characteristics of the areca nut. In comparison to the conventional method, this technique demonstrates a superior capability in annotating unknown compounds present in areca nut. We annotated a total of 52 compounds, including one potential previously unreported alkaloid, one carbohydrate, and one phenol and confirmed the presence of 7 of them by comparing with commercial standards. The validated method was used to evaluate chemical features of areca nut at different growth stages, annotating 25 compounds as potential biomarkers for distinguishing areca nut growth stages. Therefore, this approach offers a rapid and accurate method for the component analysis of areca nut.

The outer membrane vesicles (OMVs) secreted by some Gram-negative bacteria contain RNA cargo, which can be introduced into target cells, affecting their cellular processes. To test whether the antimicrobial OMVs secreted by predatory myxobacteria might contain cargo RNA with a role in prey killing, we purified OMVs and cells from four different strains of Myxococcus spp. for RNA-seq transcriptome sequencing. Myxobacterial OMVs contained distinct sets of RNA molecules. The abundance of major cellular transcripts correlated strongly with their abundance in OMVs, suggesting non-specific packaging into OMVs. However, many major cellular transcripts were absent entirely from OMVs and some transcripts were found exclusively in OMVs, suggesting OMV RNA cargo loading is not simply a consequence of sampling the cellular transcriptome. Despite considerable variation in OMV RNA cargo between biological replicates, a small number of transcripts were found consistently in replicate OMV preparations. These ‘core’ OMV transcripts were often found in the OMVs from multiple strains, and sometimes enriched relative to their abundance in cellular transcriptomes. In addition to providing the first transcriptomes for myxobacterial OMVs, and the first cellular transcriptomes for three strains of Myxococcus spp., we highlight five transcripts for further study. These transcripts are ‘core’ for at least two of the three strains of M. xanthus studied, and encode two alkyl hydroperoxidase proteins (AhpC and AhpD), two ribosome-associated inhibitors (RaiA-like) and a DO-family protease. It will be interesting to test whether the transcripts serve a biological function within OMVs, potentially being transported into prey cells for translation into toxic proteins.