PubMed

Appl Environ Microbiol. 2025 Feb 24:e0201724. doi: 10.1128/aem.02017-24. Online ahead of print.ABSTRACTAmino acid metabolism in archaea in many cases differs from those reported in bacteria and eukaryotes. The hyperthermophilic archaeon Thermococcus kodakarensis possesses an incomplete tricarboxylic cycle, and the biosynthesis pathway of aspartate is unknown. Here, four Class I aminotransferases in T. kodakarensis encoded by TK0186, TK0548, TK1094, and TK2268 were examined to identify the enzyme(s) responsible for the conversion of oxaloacetate to aspartate. Among the four proteins, the TK2268 protein (TK2268p) was the only protein to recognize oxaloacetate as the amino acceptor. With oxaloacetate, TK2268p only recognized glutamate as the amino donor. The protein also catalyzed the reverse reaction, the transamination between aspartate and 2-oxoglutarate. Substrate inhibition was observed in the presence of high concentrations of oxaloacetate or 2-oxoglutarate. Aminotransferase activity between oxaloacetate and glutamate was observed in cell extracts of the T. kodakarensis host strain KU216. Among the individual gene disruption strains of the four aminotransferases, a significant decrease in activity was only observed in the ΔTK2268 strain. T. kodakarensis KU216 does not display growth in synthetic amino acid medium when aspartate/asparagine are absent. Growth was restored upon the addition of both oxaloacetate and glutamate. Although this restoration in growth was maintained in ΔTK0186, ΔTK0548, and ΔTK1094, growth was not observed in the ΔTK2268 strain. Our results suggest that TK2268p is the predominant aminotransferase responsible for the conversion of oxaloacetate to aspartate. The growth experiments and tracer-based metabolomics using 13C3-pyruvate indicated that pyruvate is a precursor of aspartate and that this conversion is dependent on TK2268p.IMPORTANCE: Based on genome sequence, the hyperthermophilic archaeon Thermococcus kodakarensis possesses an incomplete tricarboxylic cycle, raising questions on how this organism carries out the biosynthesis of aspartate and glutamate. The results of this study clarify two main points related to aspartate biosynthesis. We show that aspartate can be produced from oxaloacetate and identify TK2268p as the aminotransferase responsible for this reaction. The other point demonstrated in this study is that pyruvate can act as the precursor for oxaloacetate synthesis. Together with previous results, we can propose some of the roles of the individual aminotransferases in T. kodakarensis. TK0548p and TK0186p are involved in amino acid catabolism, with the latter along with TK1094p involved in the conversion of glyoxylate to glycine. TK2268p is responsible for the biosynthesis of aspartate from oxaloacetate.PMID:39992121 | DOI:10.1128/aem.02017-24

mSystems. 2025 Feb 24:e0084424. doi: 10.1128/msystems.00844-24. Online ahead of print.ABSTRACTNatural products are a critical source of novel chemotypes for drug discovery. However, the implementation of natural product extract libraries in high throughput screening is hampered by natural product structural redundancy and potential for bioactive re-discovery. This challenge and large library sizes drastically increase the time and cost during initial high throughput screens. To address these limitations, we developed a method that leverages liquid chromatography-tandem mass spectrometry spectral similarity to dramatically reduce natural product library size, with minimal bioactive loss, and applied this to a collection of fungal extracts. Importantly, this method also afforded increased bioassay hit rates against microbial targets, with broad applicability across assays and natural product sources. Thus, this method offers a broadly applicable strategy for accelerated and cost-effective natural product drug discovery.IMPORTANCE: Natural product libraries are large collections of extracts derived from fungi, plants, bacteria, or any other natural sources. These libraries play an important role in the initial phases of drug discovery, providing the basis for bioassays against a target of interest. However, these collections often comprise thousands of extracts with sometimes overlapping chemical structures, which can result in a bottleneck in both time and costs for the initial phases of drug discovery. Here, we have developed a method that uses mass spectrometry to dramatically reduce the size of these libraries, with minimal tradeoffs and improved success rates in bioassays. Ultimately, this will speed up the process of bioactive candidate identification and isolation, and drug development overall.PMID:39992101 | DOI:10.1128/msystems.00844-24

Front Cell Infect Microbiol. 2025 Feb 5;15:1541881. doi: 10.3389/fcimb.2025.1541881. eCollection 2025.NO ABSTRACTPMID:39991711 | PMC:PMC11843044 | DOI:10.3389/fcimb.2025.1541881

Phytochem Rev. 2025;24(1):13-26. doi: 10.1007/s11101-023-09863-2. Epub 2023 Mar 30.ABSTRACTThe evolution of several hallmark traits of land plants is underpinned by phytochemical innovations. The specialized metabolism of plants can appear like a teeming chaos that has yielded an ungraspable array of chemodiversity. Yet, this diversity is the result of evolutionary processes including neutral evolution, drift, and selection that have shaped the metabolomic networks. Deciphering the evolutionary history of the specialized metabolome in the context of plant terrestrialization has only just begun. Studies on phytochemistry of model organisms and crop plants enabled the sketch of a blueprint for the biochemical landscape of land plants and a good idea on the diversity that can be explored. Evolutionary metabolomics has in the past been successfully used to identify traits that were critical for domestication of angiosperms or to unravel key innovations in land plants. Owing to recent advances in the study of non-model land plants and their close streptophyte algal relatives we can now begin to appreciate the variation of metabolic networks across the green lineage-and understand convergent solutions to similar environmental challenges and effects that plant terrestrialization had on these networks. Here, we highlight the significant progress made with regard to identifying metabolomic diversity by adding non-model organisms to the equation. We discuss the role of neutral evolution in the context of metabolomic diversity and the effects that environmental challenges had on the lineage-specific specialized metabolism from an evolutionary point of view.PMID:39991433 | PMC:PMC11842411 | DOI:10.1007/s11101-023-09863-2

Heliyon. 2025 Jan 13;11(3):e41927. doi: 10.1016/j.heliyon.2025.e41927. eCollection 2025 Feb 15.ABSTRACTOBJECTS: Our aim was to identify changes in the metabolome in dilated cardiomyopathy (DCM) as well as to construct a metabolic diagnostic model for DCM.METHODS: We utilized non-targeted metabolomics with a cross-sectional cohort of age- and sex-matched DCM patients and controls. Metabolomics data were analyzed using orthogonal partial least squares-discriminant analysis (OPLS-DA) and pathway analysis. It was validated in combination with transcriptome sequencing data from public databases. Machine learning models were used for the diagnosis of DCM.RESULTS: Using multiple analytical techniques, 130 metabolite alterations were identified in DCM compared to healthy controls. Perturbations in glycerophospholipid metabolism (GPL) were identified and validated as a characteristic metabolic pathway in DCM. Through the least absolute shrinkage and selection operator (LASSO), we identified the 7 most important GPL metabolites, including LysoPA (16:0/0:0), LysoPA (18:1(9Z)/0:0), PC (20:3(8Z,11Z,14Z)/20:1(11Z)), PC (20:0/14:0), LysoPC (16:0), PS(15:0/18:0), and PE(16:0/20:4 (5Z,8Z,11Z,14Z)). The machine learning models based on the seven metabolites all had good accuracy in distinguishing DCM [All area under the curve (AUC) > 0.900], and the artificial neural network (ANN) model performed the most consistently (AUC: 0.919 ± 0.075).CONCLUSIONS: This study demonstrates that GPL metabolism may play a contributing role in the pathophysiological mechanisms of DCM. The 7-GPL metabolite model may help for early diagnosis of DCM.PMID:39991223 | PMC:PMC11847283 | DOI:10.1016/j.heliyon.2025.e41927

Front Immunol. 2025 Feb 7;16:1479550. doi: 10.3389/fimmu.2025.1479550. eCollection 2025.ABSTRACTBACKGROUND: To construct a prediction model consisting of metabolites and proteins in peripheral blood plasma to predict whether patients with unresectable stage III and IV non-small cell lung cancer can benefit from immunotherapy before it is administered.METHODS: Peripheral blood plasma was collected from unresectable stage III and IV non-small cell lung cancer patients who were negative for driver mutations before receiving immunotherapy. Then we classified samples according to the follow-up results after two courses of immunotherapy and non-targeted metabolomics and proteomics analyses were performed to select different metabolites and proteins. Finally, potential biomarkers were picked out by applying machine learning methods including random forest and stepwise regression and prediction models were constructed by logistic regression.RESULTS: The presence of metabolites and proteins in peripheral blood plasma was causally associated with both non-small cell lung cancer and PD-L1/PD-1 expression levels. A total of 2 differential metabolites including 5-sulfooxymethylfurfural and Anthranilic acid and 2 differential proteins including Immunoglobulin heavy variable 1-45 and Microfibril-associated glycoprotein 4 were selected as reliable biomarkers. The area under the curve (AUC) of the prediction model built on clinical risks was merely 0.659. The AUC of metabolomics prediction model was 0.977 and the AUC of proteomics was 0.875 while the AUC of the integrative-omics prediction model was 0.955.CONCLUSIONS: Metabolic and protein biomarkers in peripheral blood both have high efficacy and reliability in the prediction of immunotherapy sensitivity in unresectable stage III and IV non-small cell lung cancer, but validation in larger population-based cohorts is still needed.PMID:39991162 | PMC:PMC11842339 | DOI:10.3389/fimmu.2025.1479550

Clin Cosmet Investig Dermatol. 2025 Feb 17;18:383-392. doi: 10.2147/CCID.S494185. eCollection 2025.ABSTRACTBACKGROUND: Metabolic disorders have been hypothesized to be associated with female-pattern hair loss. However, ambiguity persists regarding the causality and directionality of the relationship between blood metabolites and female hair loss patterns.METHODS: To evaluate the causal relationship between 1400 blood metabolites and female pattern hair loss, we conducted a bidirectional Mendelian randomization analysis using publicly available summary data from genome-wide association studies. The primary analyses employed the inverse variance weighted method supplemented by the weighted median, MR-Egger, and weighted mode approaches. To control for multiple testing, the false discovery rate method was applied to adjust P values. The leave-one-out method was employed for the sensitivity analysis. Heterogeneity was evaluated using Cochran's Q value, whereas horizontal pleiotropy was assessed using MR-Egger intercept and MR-PRESSO. Additionally, metabolic pathway analysis was performed for the metabolites that demonstrated significant correlations. We further performed colocalization analysis to delve into the underlying causality.RESULTS: After rigorous selection, 23 metabolites and 4 metabolic ratios were associated with female-pattern hair loss. There were no noticeable outliers, horizontal pleiotropy, or heterogeneity. Metabolic pathway analysis identified one significant pathway: fructose/mannose metabolism (P < 0.05). In the reverse analysis, dimethylglycine was identified as overlapping with the forward analysis results, thereby removing it from the final analysis.CONCLUSION: Through integration of genomic and metabolomic data, we identified blood metabolites that may be associated with the development of female pattern hair loss. Our findings provide novel insights into the pathogenic mechanisms of this condition. These findings have significant implications for early diagnosis, preventive measures, and treatment.PMID:39991105 | PMC:PMC11844202 | DOI:10.2147/CCID.S494185

EPMA J. 2025 Jan 31;16(1):165-182. doi: 10.1007/s13167-025-00396-6. eCollection 2025 Mar.ABSTRACTOBJECTIVE: Metabolomics measurements of eccrine sweat may provide novel and relevant biomedical information to support predictive, preventive and personalised medicine (3PM). However, only limited data is available regarding metabolic alterations accompanying chemotherapy of breast cancer patients related to residual cancer burden (RCB) or therapy response. Here, we have applied Metabo-Tip, a non-invasive metabolomics assay based on the analysis of eccrine sweat from the fingertips, to investigate the feasibility of such an approach, especially with respect to drug monitoring, assessing lifestyle parameters and stratification of breast cancer patients.METHODS: Eccrine sweat samples were collected from breast cancer patients (n = 9) during the first cycle of neoadjuvant chemotherapy at four time points in this proof-of-concept study at a Tertiary University Hospital. Metabolites in eccrine sweat were analysed using mass spectrometry. Blood plasma samples from the same timepoints were also collected and analysed using a validated targeted metabolomics kit, in addition to proteomics and fatty acids/oxylipin analysis.RESULTS: A total of 247 exogenous small molecules and endogenous metabolites were identified in eccrine sweat of the breast cancer patients. Cyclophosphamide and ondansetron were successfully detected and monitored in eccrine sweat of individual patients and accurately reflected the administration schedule. The non-essential amino acids asparagine, serine and proline, as well as ornithine were significantly regulated in eccrine sweat and blood plasma over the therapy cycle. However, their distinct time-dependent profiles indicated compartment-specific distributions. Indeed, the metabolite composition of eccrine sweat seems to largely resemble the composition of the interstitial fluid. Plasma proteins and fatty acids/oxylipins were not affected by the first treatment cycle. Individual smoking habit was revealed by the simultaneous detection of nicotine and its primary metabolite cotinine in eccrine sweat. Stratification according to RCB revealed pronounced differences in the metabolic composition of eccrine sweat in these patients at baseline, e.g., essential amino acids, possibly due to the systemic contribution of breast cancer and its impact on metabolic turnover.CONCLUSION: Mass spectrometry-based analysis of metabolites from eccrine sweat of breast cancer patients successfully qualified lifestyle parameters for risk assessment and allowed us to monitor drug treatment and systemic response to therapy. Moreover, eccrine sweat revealed a potentially predictive metabolic pattern stratifying patients by the extent of the metabolic activity of breast cancer tissue at baseline. Eccrine sweat is derived from the otherwise hardly accessible interstitial fluid and, thus, opens up a new dimension for biomonitoring of breast cancer in secondary and tertiary care. The simple sample collection without the need for trained personnel could also enable decentralised long-term biomonitoring to assess stable disease or disease progression. Eccrine sweat analysis may indeed significantly advance 3PM for the benefit of breast cancer patients.SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-025-00396-6.PMID:39991101 | PMC:PMC11842658 | DOI:10.1007/s13167-025-00396-6

EPMA J. 2025 Jan 16;16(1):217-238. doi: 10.1007/s13167-024-00395-z. eCollection 2025 Mar.ABSTRACTRespiratory syncytial viral (RSV) infection is a leading persisting pulmonary disease-causing agent. It causes loss of lives especially among infants, old ages, and adults immunocompromised individuals. This viral pathogen infects children more especially those under the age of 2 and may lead to death. It causes 3 million hospitalizations and up to 60,000 deaths annually for under the age of 5. The most vulnerable are immunocompromised individuals and asthmatic children with suboptimal antiviral defenses. It is associated with bronchiolitis, pneumonia, and bronchopneumonia. Despite all the current interventions and clinical trials, the only available therapeutic strategies for this viral infection are palliative care. Therefore, it is imperative to understand the pathogenicity of RSV and the corresponding host immune response to depict a sort of a targeted intervention. With the increasingly cutting-edge methods in harnessing the pathogenicity of this viral infection, high throughput systems including omics technological advances are at the spotlight. For instance, the associated genes with RSV complications for the host, the set of microbiome identified as operational taxonomic unit, the upregulated or downregulated metabolites, the protein subtypes, and the small molecules can help explain the viral microenvironment. Moreover, these big data will lead to RSV patients' stratification through individualized patient profiles that will bring in targeted prevention and treatment algorithms tailored to individualized patients' profiles. Through this, the virus and host interactions based on the pathogenicity of infection will provide a strong ground for depicting the prevention, prediction, and personalized medicine (3PM) for RSV. The 3PM approach brought cutting edge functional medicine to the healthcare givers, thus conferring targeted prevention and precision medicine while observing personalized treatment as well as preventive regularities. The viral replication mechanisms against the host defense mechanisms are crucial for the development of safe and effective therapy. Integrative personal omics profiles, whose analysis is based on the combined proteomics, transcriptomics, genomics, proteoformics, metabolomics, and autoantibody profiles, are very robust for predicting the risk of RSV infection. The targeted prevention will emerge from the patient stratification when the diagnosis is accurately predicted. In addition, the personalized medical services will give an effective prognostic assessment for RSV complications.PMID:39991100 | PMC:PMC11842696 | DOI:10.1007/s13167-024-00395-z

Drug Des Devel Ther. 2025 Feb 19;19:1215-1229. doi: 10.2147/DDDT.S484561. eCollection 2025.ABSTRACTBACKGROUND AND OBJECTIVE: Lung cancer stands as the leading cause of cancer-related fatalities worldwide. While chemotherapy remains a crucial treatment option for managing lung cancer in both early-stage and advanced cases, it is accompanied by significant drawbacks, including severe side effects and the development of chemoresistance. Overcoming chemoresistance represents a considerable challenge in lung cancer treatment. Amlodipine cytotoxicity was previously demonstrated and could make lung cancer cells more susceptible to chemotherapies. This research aims to examine the metabolomics changes that may occur due to amlodipine's anticancer effects on non-small cell lung cancer (NSCLC) cells.METHODS: Amlodipine's effects on A549 and H1299 NSCLC were evaluated using a colorimetric MTT assay, a scratch wound-healing assay and Matrigel invasion chambers to measure cell viability, cell migration and cell invasion. Ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS) was used for the untargeted metabolomics investigation.RESULTS: Our study revealed that amlodipine significantly reduced proliferation of cancer cells in a dose-dependent fashion with IC50 values of 23 and 25.66 µM in A549 and H1299 cells, respectively. Furthermore, amlodipine reduced the invasiveness and migration of cancer cells. Metabolomics analysis revealed distinct metabolites to be significantly dysregulated (Citramalic acid, L-Proline, dGMP, L-Glutamic acid, Niacinamide, and L-Acetylcarnitine) in amlodipine-treated cells.CONCLUSION: The present study illustrates the anticancer effects of amlodipine on lung cancer proliferation, migration, and invasion in vitro and enhance our understanding of how amlodipine exerts its anticancer potential by casting light on these mechanisms.PMID:39991087 | PMC:PMC11847429 | DOI:10.2147/DDDT.S484561

ACS Meas Sci Au. 2024 Dec 27;5(1):109-119. doi: 10.1021/acsmeasuresciau.4c00077. eCollection 2025 Feb 19.ABSTRACTDirect-infusion mass spectrometry (DI-MS) and mass spectrometry imaging (MSI) are powerful techniques for lipidomics research. However, annotating isomeric and isobaric lipids with these methods is challenging due to the absence of chromatographic separation. Recently, cyclic ion mobility mass spectrometry (cIM-MS) has been proposed to overcome this limitation. However, fluctuations in room conditions can affect ion mobility multipass arrival times, potentially reducing annotation confidence. In this study, we developed a multipass arrival time correction method that proved effective across various dates, room temperatures, ion mobility settings, and laboratories using mixtures of reference standards. We observed slight variations in the linear correction lines between lipid and nonlipid molecules, underscoring the importance of choosing appropriate reference molecules. Based on these results, we demonstrated that an accurate multipass arrival time database can be constructed from corrected t 0 and t p for interlaboratory use and can effectively identify isomeric lipids in MSI using only a single measurement. This approach significantly simplifies the identification process compared to determining multipass collision cross-section, which requires multiple measurements that are both sample- and time-intensive for MSI. Additionally, we validated our multipass drift time correction method in shotgun lipidomics analyses of human and mouse serum samples and observed no matrix effect for the analysis. Despite variations in dates, room temperatures, instruments, and ion mobility settings, our approach reduced the mean drift time differences from over 2% to below 0.2%.PMID:39991034 | PMC:PMC11843504 | DOI:10.1021/acsmeasuresciau.4c00077

Kidney Int Rep. 2024 Nov 22;10(2):522-534. doi: 10.1016/j.ekir.2024.11.022. eCollection 2025 Feb.ABSTRACTINTRODUCTION: A US Food and Drug Administration-approved new bromodomain (BRD) and extraterminal (BET) bromine domain antagonist called apabetalone, which targets BRD4, has been shown to increase prebeta-1 high-density lipoprotein (HDL) particles, enhance apolipoprotein A-I in both humans and animals, and restore angiogenesis in experimental diabetes. Its action is not however fully known mechanistically. The objective of our research was to investigate the impact of apabetalone on renal damage linked to diabetic kidney disease (DKD).METHODS: This research employed both pharmacological and genetic methods to examine the impact of apabetalone on db/db (BKS. Cg-leprdb/leprdb) mice and human tubular epithelial cells (HK-2).RESULTS: Here, significant reductions in blood creatinine, urea nitrogen, and urinary albumin-to-creatinine ratio (UACR) levels, serum triglycerides (TGs) and serum total cholesterol (TC), as well as ectopic lipid droplet formation in renal tissue, were seen in the db/db mice following apabetalone therapy. Analysis of the gut microbiota revealed changes in its composition. Significantly, the proportion of Firmicutes to Bacteroidetes decreased, as well as Deferribacterota, indicating a positive influence on lipid metabolism. Untargeted metabolomic analysis indicated that the ABC transporter signaling pathway, implicated in cholesterol metabolism, was enriched. Moreover, peroxisome proliferator-activated receptor gamma (PPARγ)/liver X receptor (LXR)/adenosine triphosphate-binding cassette transporter A1 (ABCA1) protein, and mRNA level, as well as fibrosis-related marker proteins, fibronectin and collagen I were all improved by apabetalone.CONCLUSION: Therefore, we suggest that apabetalone showed significant antihyperlipidemic and antifibrotic effects, closely associated with alterations in the gut microbiota and cholesterol metabolism. The results of this investigation provide fresh perspectives on the processes that underlie apabetalone's effects in db/db mice.PMID:39990894 | PMC:PMC11843129 | DOI:10.1016/j.ekir.2024.11.022

Kidney Int Rep. 2024 Nov 23;10(2):535-548. doi: 10.1016/j.ekir.2024.11.024. eCollection 2025 Feb.ABSTRACTINTRODUCTION: Fabry disease (FD) results from pathogenic GLA variants, leading to a deficiency in lysosomal α-galactosidase A (α-Gal A) and accumulation of the sphingolipid globotriaosylceramide (Gb3). This leads to severe renal and cardiovascular complications, primarily affecting kidney podocytes. As a multisystemic disorder, FD initiates at the cellular level; however, the mechanism(s) underlying Gb3-induced cell dysfunction remain largely unknown. This study aimed to identify potential drivers of FD and explore the underlying cell pathology in induced pluripotent stem cell (iPSC)-derived podocytes from patients with FD.METHODS: iPSCs were derived from patients with FD with GLA c.851T>C or GLA c.1193_1196del variants and compared with controls or CRISPR-Cas9-corrected cell lines. iPSCs were differentiated into podocytes; and α-Gal A activity, Gb3 accumulation, and cell morphology were assessed. Label-free mass spectrometry identified the top, differentially expressed proteins which were validated by using western blot.RESULTS: Podocytes derived from patients with FD exhibited expression of podocyte-specific markers and morphological features of FD. Reduced α-Gal A activity was observed in FD iPSC-derived podocytes along with the accumulation of Gb3. Proteomic profiling revealed distinct proteomic signatures between control and iPSC-derived podocytes from a patient with FD, with apparent variations among FD lines, highlighting GLA variant-specific proteomic alterations. Notably, the ferroptosis-associated protein, arachidonate 15-lipoxygenase (ALOX15), was the most upregulated protein in FD podocytes and ferroptosis was the most enriched pathway. Western blot analysis confirmed the upregulation of ALOX15 in FD podocytes, with validation of other markers implicating ferroptosis in FD pathology.CONCLUSION: These findings underscore the heterogeneity of FD and, for the first time, implicate ferroptosis as a potential common pathway driving its pathology.PMID:39990892 | PMC:PMC11843119 | DOI:10.1016/j.ekir.2024.11.024

Oncol Lett. 2025 Feb 11;29(4):178. doi: 10.3892/ol.2025.14924. eCollection 2025 Apr.ABSTRACTIdentifying the mechanism by which lipid metabolism regulates cancer may offer a novel approach for therapeutic intervention. It has previously been identified that a lipid metabolism-related factor, namely fatty acid hydroxylase domain containing 2 (FAXDC2), is downregulated in various types of cancer, and inhibits the proliferation and migration of liver cancer cells through a mechanism associated with ERK. The liver is important for lipid metabolism, and FAXDC2 is involved in the synthesis of cholesterol and sphingomyelin. However, the functional mechanism by which FAXDC2 influences liver cancer cells through metabolic processes and ERK signaling remains unclear. Therefore, the present study induced the overexpression of FAXDC2 in HepG2 liver cancer cells and performed a metabolomics analysis. This identified guanosine diphosphate (GDP) as a significantly altered metabolite. Using AlphaFold3, a robust interaction was predicted between FAXDC2 and GDP, which lead to the hypothesis that GDP may mediate the inhibitory effects of FAXDC2 on liver cancer cells by directly modulating the functional properties of the cells, thereby influencing their behavior and progression. Cell Counting Kit-8 assays were used to study the impact of elevated GDP concentrations on HepG2 cell growth. The results revealed a gradual reduction in the viability of HepG2 cells as the GDP concentration increased. In addition, western blotting showed that GDP treatment was accompanied by a significant downregulation of cyclin dependent kinase 4 and cyclin D1 expression levels, and Transwell experiments revealed that GDP treatment significantly decreased the invasion of HepG2 cells. Treatment with GDP also significantly inhibited the expression of ERK. In summary, the present study is the first to indicate that GDP is a metabolic small molecule with inhibitory activity in cancer cells, which has previously been overlooked in tumor metabolic reprogramming. The study findings offer new insights and strategies for the diagnosis and treatment of liver cancer, and potentially other types of cancer.PMID:39990806 | PMC:PMC11843412 | DOI:10.3892/ol.2025.14924

Front Plant Sci. 2025 Feb 7;16:1530324. doi: 10.3389/fpls.2025.1530324. eCollection 2025.ABSTRACTINTRODUCTION: Specific microorganisms and metabolites in soil play key roles in regulating organismal behavior. Currently, the effects of different preceding crops on the rhizosphere soil quality of flue-cured tobacco remain unclear.METHODS: Four treatments were compared in the study: fallow + tobacco (CK), maize + tobacco (T1), rapeseed + tobacco (T2), and wheat + tobacco (T3).RESULTS AND DISCUSSION: Results showed that preceding crops significantly enhanced soil nutrient levels and improved tobacco growth by altering rhizosphere metabolites and microbial community structure. Previous cultivation of maize and rapeseed significantly promoted tobacco growth, rapeseed and wheat cultivation enhanced the diversity of soil bacterial communities, and notably decreased the abundance of urea-degrading bacteria. In contrast, the preceding crop of maize reduced plant pathogenic fungi and promoted positive microbial interactions. Metabolomics analysis showed that different preceding crops altered lipids, organic acids, flavonoids, alkaloids, and terpenoids, enhancing secondary metabolite synthesis pathways in soil. Preceding crops regulated rhizosphere metabolites which potentially participated in soil carbon and nitrogen cycling, balancing soil nutrients, and improving tobacco yield. Overall, the three preceding crops altered the composition and function of metabolites and microbial community structures in rhizosphere soil, thereby increased soil nutrient concentration. Both maize and rapeseed cultivation significantly boosted tobacco growth and biomass. These findings offer new insights into the potential interactions between rhizosphere metabolites and microbial communities and strategies of comprehensively regulating tobacco growth.PMID:39990714 | PMC:PMC11842363 | DOI:10.3389/fpls.2025.1530324

Front Plant Sci. 2025 Feb 7;15:1518058. doi: 10.3389/fpls.2024.1518058. eCollection 2024.ABSTRACTINTRODUCTION: Amorphophallus albus, a perennial herb in the Araceae family, is a valuable cash crop known for its high production of konjac glucomannan and high disease resistance.METHODS: In this study, we present a high-quality, chromosome-scale genome assembly of A. albus using a combination of PacBio HiFi sequencing, DNBSEQ short-read sequencing, and Hi-C technology. To elucidate the molecular mechanisms underlying southern blight resistance, we performed an integrated analysis of transcriptomic and metabolomic profiles across three infection stages of A. albus.RESULTS AND DISCUSSION: Here, we assembled and annotated the complete genome of A. albus, providing a chromosome-level assembly with a total genome size of 5.94 Gb and a contig N50 of 5.61 Mb. The A. albus genome comprised 19,908 gene families, including 467 unique families.The slightly larger genome size of A. albus compared to A. konjac may have been affected by a recent whole-genome duplication event. Transcriptional and metabolic analyses revealed significant enrichment of differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) involved in phenylpropanoid biosynthesis, plant hormone signal transduction, phenylalanine metabolism, and the biosynthesis of phenylalanine, tyrosine, and tryptophan. These findings not only advance the understanding of genetic and evolutionary characteristics of A. albus but also provide a foundation for future research on the resistance mechanisms of konjac against southern blight disease.PMID:39990650 | PMC:PMC11842328 | DOI:10.3389/fpls.2024.1518058

bioRxiv [Preprint]. 2025 Feb 12:2025.02.11.637688. doi: 10.1101/2025.02.11.637688.ABSTRACTBACKGROUND & AIMS: Mitochondrial dysfunction has been implicated in aging and various cancer development. As highly dynamic organelles, mitochondria constantly undergo fission, mediated by dynamin-related protein 1 (DRP1, gene name Dnm1l ), and fusion, regulated by mitofusin 1 (MFN1), MFN2, and optic atrophy 1 (OPA1). However, whether and how dysregulation of mitochondria dynamics would be involved in liver pathogenesis and tumorigenesis is unknown.METHODS: Dnm1l Flox/Flox ( Dnm1l F/F ), Mfn1 F/F and Mfn2 F/F mice were crossed with albumin-Cre mice to generate liver-specific Dnm1l knockout (L- Dnm1l KO), L- Mfn1 KO, L- Mfn2 KO, L- Mfn1, Mfn2 double KO (DKO), and L- Mfn1, Mfn2, Dnm1l triple KO (TKO) mice. These mice were housed for various periods up to 18 months. Some mice also received hydrodynamic tail vein injections of a Sleeping Beauty transposon-transposase plasmid system with c-MYC and YAP . Blood and liver tissues were harvested for biochemical and histological analysis.RESULTS: L- Dnm1l KO mice had elevated serum alanine aminotransferase levels and increased hepatic fibrosis as early as two months of age. By 12 to 18 months, male L- Dnm1l KO mice developed spontaneous liver tumors, primarily hepatocellular adenomas. While female L- Dnm1l KO mice also developed liver tumors, their incidence was much lower. In contrast, neither L- Mfn1 KO nor L- Mfn2 KO mice had notable liver injury or tumorigenesis. However, a small portion of DKO mice developed tumors at 15-18 month-old. Increased DNA damage, senescence and compensatory proliferation were observed in L- Dnm1l KO mice but were less evident in L- Mfn1 KO, L- Mfn2 KO or DKO mice, indicating that mitochondrial fission is more important to maintain hepatocyte homeostasis and prevent liver tumorigenesis. Interestingly, further deletion of Mfn1 and Mfn2 in L- Dnm1l KO mice markedly abolished liver injury, fibrosis, and both spontaneous and oncogene-induced tumorigenesis. RNA sequencing and metabolomics analysis revealed significant activation of the cGAS-STING-interferon pathway and alterations in the tumor microenvironment pathways, alongside increased pyrimidine synthesis and metabolism in the livers of L- Dnm1l KO mice. Notably, the changes in gene expression and pyrimidine metabolism were considerably corrected in the TKO mice.CONCLUSIONS: Mitochondrial dynamics and stability are essential for maintaining hepatic mitochondrial homeostasis and hepatocyte functions. Loss of hepatic DRP1 promotes liver tumorigenesis by increasing pyrimidine metabolism and activating the cGAS-STING-mediated innate immune response.PMID:39990472 | PMC:PMC11844448 | DOI:10.1101/2025.02.11.637688

bioRxiv [Preprint]. 2025 Feb 14:2025.02.13.638044. doi: 10.1101/2025.02.13.638044.ABSTRACTThe extracellular space (apoplast) of plants is an important molecular battleground during infection by many pathogens. We previously found that a plant-secreted β-galactosidase BGAL1 acts in immunity by facilitating the release of immunogenic peptides from bacterial flagellin and that Pseudomonas syringae suppresses this enzyme by producing a small molecule inhibitor called galactosyrin. Here, we elucidated the structure and biosynthesis of galactosyrin and uncovered its multifunctional roles during infection. Structural elucidation by cryo-EM and chemical synthesis revealed that galactosyrin is an iminosugar featuring a unique geminal diol attached to the pyrrolidine moiety that mimics galactose binding to the β-galactosidase active site. Galactosyrin biosynthesis branches off from purine biosynthesis and involves three enzymes of which the first is a reductase that is unique in iminosugar biosynthesis. Besides inhibiting BGAL1 to avoid detection, galactosyrin also changes the glycoproteome and metabolome of the apoplast. The manipulation of host glycobiology may be common to plant-associated bacteria that carry putative iminosugar biosynthesis clusters.PMID:39990308 | PMC:PMC11844564 | DOI:10.1101/2025.02.13.638044

Front Microbiol. 2025 Feb 7;16:1527480. doi: 10.3389/fmicb.2025.1527480. eCollection 2025.ABSTRACTINTRODUCTION: Antibiotic overuse has caused the development of bacterial resistance, which is a major threat to public health. Intracellular metabolic processes are essential for maintaining the normal physiological activities of bacteria, and an increasing body of research has demonstrated a significant association between metabolic alterations and the development of drug resistance. Numerous studies have demonstrated that the addition of adjuvants can counteract bacterial antibiotic resistance.METHOD: Cystine treatment was verified in vitro to promote the lethal effect of gentamicin on Salmonella using in vitro bactericidal counting methods. The metabolic differences in Salmonella enterica Typhimurium standard strain ATCC 14028 with or without the addition of cystine were analyzed via untargeted metabolomics. The multifunctional electronic enzyme marker was used to determine intracellular reduced glutathione/oxidized glutathione (GSH/GSSG), ferrous iron on (Fe2+), and reactive oxygen species (ROS) levels. The expression of glutathione and stress genes was determined using real-time quantitative PCR.RESULT: We confirmed that exogenous cystine increased the lethal effect of gentamicin against strain S. enterica Typhimurium (ATCC 14028) and other clinically resistant Salmonella serotypes. Exogenous cystine stimulated the metabolism of the cell and activated the glutathione pathway while altering the GSH/GSSG ratio, which placed bacteria in a state of redox imbalance with increased Fe2+ and ROS levels. Our results suggest that when bacterial redox levels are reprogrammed, bacterial susceptibility to antibiotics can also change.DISCUSSION: This study confirms that cystine enhances the antimicrobial efficacy of gentamicin against drug-resistant Salmonella. Through the application of metabolomics, the underlying metabolic mechanisms by which cystine exerts its effects on Salmonella have been elucidated, offering a novel perspective in the domain of metabolic reprogramming aimed at counteracting drug resistance. Furthermore, these findings reinforce the potential role of small-molecule metabolites as effective adjuvants to enhance antibiotic action.PMID:39990151 | PMC:PMC11843173 | DOI:10.3389/fmicb.2025.1527480

Biodes Res. 2024 Dec 5;6:0059. doi: 10.34133/bdr.0059. eCollection 2024.ABSTRACTMultiomics research is a transformative approach in the biological sciences that integrates data from genomics, transcriptomics, proteomics, metabolomics, and other omics technologies to provide a comprehensive understanding of biological systems. This review elucidates the fundamental principles of multiomics, emphasizing the necessity of data integration to uncover the complex interactions and regulatory mechanisms underlying various biological processes. We explore the latest advances in computational methodologies, including deep learning, graph neural networks (GNNs), and generative adversarial networks (GANs), which facilitate the effective synthesis and interpretation of multiomics data. Additionally, this review addresses the critical challenges in this field, such as data heterogeneity, scalability, and the need for robust, interpretable models. We highlight the potential of large language models to enhance multiomics analysis through automated feature extraction, natural language generation, and knowledge integration. Despite the important promise of multiomics, the review acknowledges the substantial computational resources required and the complexity of model tuning, underscoring the need for ongoing innovation and collaboration in the field. This comprehensive analysis aims to guide researchers in navigating the principles and challenges of multiomics research to foster advances in integrative biological analysis.PMID:39990095 | PMC:PMC11844812 | DOI:10.34133/bdr.0059