Integrative Molecular Phenotyping
INTEGRATIVE MOLECULAR
PHENOTYPING
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY

PubMed

Metabolomic profiling for dyslipidemia in pediatric patients with sickle cell disease, on behalf of the IHCC consortium

11 hours 42 min ago
Metabolomics. 2022 Dec 2;18(12):101. doi: 10.1007/s11306-022-01954-z.NO ABSTRACTPMID:36459297 | DOI:10.1007/s11306-022-01954-z

The impact of the secondary infections in ICU patients affected by COVID-19 during three different phases of the SARS-CoV-2 pandemic

11 hours 42 min ago
Clin Exp Med. 2022 Dec 2. doi: 10.1007/s10238-022-00959-1. Online ahead of print.NO ABSTRACTPMID:36459278 | DOI:10.1007/s10238-022-00959-1

Diagnostic serum biomarkers associated with ankylosing spondylitis

11 hours 42 min ago
Clin Exp Med. 2022 Dec 2. doi: 10.1007/s10238-022-00958-2. Online ahead of print.NO ABSTRACTPMID:36459277 | DOI:10.1007/s10238-022-00958-2

PPI-induced changes in plasma metabolite levels influence total hip bone mineral density in a UK cohort

11 hours 42 min ago
J Bone Miner Res. 2022 Dec 2. doi: 10.1002/jbmr.4754. Online ahead of print.NO ABSTRACTPMID:36458982 | DOI:10.1002/jbmr.4754

NMR methods for the analysis of mixtures

11 hours 42 min ago
Chem Commun (Camb). 2022 Dec 2. doi: 10.1039/d2cc05053f. Online ahead of print.NO ABSTRACTPMID:36458684 | DOI:10.1039/d2cc05053f

Viral metagenomics combined with metabolomics reveals the role of gut viruses in mouse model of depression

11 hours 42 min ago
Front Microbiol. 2022 Nov 15;13:1046894. doi: 10.3389/fmicb.2022.1046894. eCollection 2022.ABSTRACTDepression is a heterogeneous mental disorder that has been linked to disturbances in the gut microbiome. As an essential part of the gut microbiome, gut virome may play critical roles in disease progression and development. However, the relationship between the effect of gut virome on neurotransmitter metabolism and depression is unknown. We evaluated the alterations of gut virome and neurotransmitters in chronic restraint stress (CRS)-induced mouse model of depression based on viral metagenomics and LC-MS/MS metabolomics analyses. The results reveal that the gut virome profile of CRS group differed significantly from CON group. Microviridae was the most abundant differential viral family in both groups, followed by Podoviridae, while Siphoviridae was only enriched in CRS group of the top 100 differential viruses. The differential viruses that predicted to Enterobacteriaceae phage, Gammaproteobacteria phage and Campylobacteraceae phage were enriched in CRS group. Furthermore, 12 differential neurotransmitters primarily involved in the tryptophan metabolism pathway were altered in depressive-like mice. Besides, tryptamine and 5-methoxytryptamine hydrochloride were strongly associated with differential viruses belonging to Podoviridae and Microviridae. Our findings provide new insight into understanding the potential role of the gut virome and metabolites in depression.PMID:36458183 | PMC:PMC9706091 | DOI:10.3389/fmicb.2022.1046894

Discovery and validation of acetyl-L-carnitine in serum for diagnosis of major depressive disorder and remission status through metabolomic approach

11 hours 42 min ago
Front Psychiatry. 2022 Nov 15;13:1002828. doi: 10.3389/fpsyt.2022.1002828. eCollection 2022.ABSTRACTMajor depressive disorder (MDD) is one of the most common psychiatric disorders that accompany psychophysiological and mood changes. However, the pathophysiology-based disease mechanism of MDD is not yet fully understood, and diagnosis is also conducted through interviews with clinicians and patients. Diagnosis and treatment of MDD are limited due to the absence of biomarkers underlying the pathophysiological mechanisms of MDD. Although various attempts have been made to discover metabolite biomarkers for the diagnosis and treatment response of MDD, problems with sample size and consistency of results have limited clinical application. In addition, it was reported that future biomarker studies must consider exposure to antidepressants, which is the main cause of heterogeneity in depression subgroups. Therefore, the purpose of this study is to discover and validate biomarkers for the diagnosis of depression in consideration of exposure to drug treatment including antidepressants that contribute to the heterogeneity of the MDD subgroup. In the biomarker discovery and validation set, the disease group consisted of a mixture of patients exposed and unexposed to drug treatment including antidepressants for the treatment of MDD. The serum metabolites that differed between the MDD patients and the control group were profiled using mass spectrometry. The validation set including the remission group was used to verify the effectiveness as a biomarker for the diagnosis of depression and determination of remission status. The presence of different metabolites between the two groups was confirmed through serum metabolite profiling between the MDD patient group and the control group. Finally, Acetylcarnitine was selected as a biomarker. In validation, acetylcarnitine was significantly decreased in MDD and was distinguished from remission status. This study confirmed that the discovered acetylcarnitine has potential as a biomarker for diagnosing depression and determining remission status, regardless of exposure to drug treatment including antidepressants.PMID:36458116 | PMC:PMC9707625 | DOI:10.3389/fpsyt.2022.1002828

Artificial intelligence applied to omics data in liver diseases: Enhancing clinical predictions

11 hours 42 min ago
Front Artif Intell. 2022 Nov 15;5:1050439. doi: 10.3389/frai.2022.1050439. eCollection 2022.ABSTRACTRapid development of biotechnology has led to the generation of vast amounts of multi-omics data, necessitating the advancement of bioinformatics and artificial intelligence to enable computational modeling to diagnose and predict clinical outcome. Both conventional machine learning and new deep learning algorithms screen existing data unbiasedly to uncover patterns and create models that can be valuable in informing clinical decisions. We summarized published literature on the use of AI models trained on omics datasets, with and without clinical data, to diagnose, risk-stratify, and predict survivability of patients with non-malignant liver diseases. A total of 20 different models were tested in selected studies. Generally, the addition of omics data to regular clinical parameters or individual biomarkers improved the AI model performance. For instance, using NAFLD fibrosis score to distinguish F0-F2 from F3-F4 fibrotic stages, the area under the curve (AUC) was 0.87. When integrating metabolomic data by a GMLVQ model, the AUC drastically improved to 0.99. The use of RF on multi-omics and clinical data in another study to predict progression of NAFLD to NASH resulted in an AUC of 0.84, compared to 0.82 when using clinical data only. A comparison of RF, SVM and kNN models on genomics data to classify immune tolerant phase in chronic hepatitis B resulted in AUC of 0.8793-0.8838 compared to 0.6759-0.7276 when using various serum biomarkers. Overall, the integration of omics was shown to improve prediction performance compared to models built only on clinical parameters, indicating a potential use for personalized medicine in clinical setting.PMID:36458100 | PMC:PMC9705954 | DOI:10.3389/frai.2022.1050439

Modeling interaction networks between host, diet, and bacteria predicts obesogenesis in a mouse model

11 hours 42 min ago
Front Mol Biosci. 2022 Nov 15;9:1059094. doi: 10.3389/fmolb.2022.1059094. eCollection 2022.ABSTRACTHost-microbiome interactions are known to have substantial effects on human health, but the diversity of the human microbiome makes it difficult to definitively attribute specific microbiome features to a host phenotype. One approach to overcoming this challenge is to use animal models of host-microbiome interaction, but it must be determined that relevant aspects of host-microbiome interactions are reflected in the animal model. One such experimental validation is an experiment by Ridura et al. In that experiment, transplanting a microbiome from a human into a mouse also conferred the human donor's obesity phenotype. We have aggregated a collection of previously published host-microbiome mouse-model experiments and combined it with thousands of sequenced and annotated bacterial genomes and metametabolomic pathways. Three computational models were generated, each model reflecting an aspect of host-microbiome interactions: 1) Predict the change in microbiome community structure in response to host diet using a community interaction network, 2) Predict metagenomic data from microbiome community structure, and 3) Predict host obesogenesis from modeled microbiome metagenomic data. These computationally validated models were combined into an integrated model of host-microbiome-diet interactions and used to replicate the Ridura experiment in silico. The results of the computational models indicate that network-based models are significantly more predictive than similar but non-network-based models. Network-based models also provide additional insight into the molecular mechanisms of host-microbiome interaction by highlighting metabolites and metabolic pathways proposed to be associated with microbiome-based obesogenesis. While the models generated in this study are likely too specific to the animal models and experimental conditions used to train our models to be of general utility in a broader understanding of obesogenesis, the approach detailed here is expected to be a powerful tool of investigating multiple types of host-microbiome interactions.PMID:36458093 | PMC:PMC9705962 | DOI:10.3389/fmolb.2022.1059094

Clinical features and metabolic reprogramming of atherosclerotic lesions in patients with chronic thromboembolic pulmonary hypertension

11 hours 42 min ago
Front Cardiovasc Med. 2022 Nov 15;9:1023282. doi: 10.3389/fcvm.2022.1023282. eCollection 2022.ABSTRACTBACKGROUND: Chronic thromboembolic pulmonary hypertension (CTEPH) patients may present with atherosclerotic lesions in their pulmonary arteries, but their clinical characteristics remain unclear. The metabolic pathways associated with the atherosclerotic lesions may explain their occurrence and have implications for interventions, but they have not been investigated.METHODS: We collected pulmonary endarterectomy (PEA) samples of CTEPH patients from December 2016 to August 2021. Following a detailed pathological examination of the PEA specimen, the patients were divided into those with and without lesions, and age- and sex matching were performed subsequently using propensity score matching (n = 25 each). Metabolomic profiling was used to investigate the metabolites of the proximal lesions in the PEA specimens.RESULTS: In our study population, 27.2% of all PEA specimens were found to contain atherosclerotic lesions. CTEPH patients with atherosclerotic lesions were more likely to have a history of symptomatic embolism and had a longer timespan between embolism and surgery, whereas the classic risk factors of systemic and coronary circulation could not distinguish CTEPH patients with or without atherosclerotic lesions. Metabolomic profiling revealed that the formation of atherosclerotic lesions in CTEPH was closely related to altered glycine, serine, and threonine metabolic axes, possibly involved in cellular senescence, energy metabolism, and a proinflammatory microenvironment.CONCLUSION: The occurrence of atherosclerotic lesions in the pulmonary arteries of CTEPH was associated with symptomatic thromboembolic history and prolonged disease duration. The results revealed a new link between atherosclerotic lesions and aberrant amino acid metabolism in the context of CTEPH for the first time. This study has characterized the clinical and metabolic profiles of this distinct group of CTEPH patients, providing new insights into disease pathogenesis and potential interventions.PMID:36457807 | PMC:PMC9705335 | DOI:10.3389/fcvm.2022.1023282

Diagnosis and control of cryptosporidiosis in farm animals

11 hours 42 min ago
J Parasit Dis. 2022 Dec;46(4):1133-1146. doi: 10.1007/s12639-022-01513-2. Epub 2022 Jul 4.ABSTRACTCryptosporidium is a pathogenic protozoan parasite infecting the gastrointestinal epithelium of human and animal hosts. In farm animals, cryptosporidiosis causes significant economic losses including deaths in newborn animals, retarded growth, increased labor involved and high cost of drugs. The detection of Cryptosporidium oocysts in fecal samples is traditionally dependent on examination of stained slides by light microscope or by advanced microscopical tools such as: electron microscopy and phase contrast microscopy. Immunological diagnosis using either antibody or antigen detection could offer high sensitivity and specificity. Examples for these tests are Enzyme Linked Immunosorbent Assay (ELISA), Immunochromatographic tests, Immunochromatographic lateral flow (ICLF), Immunofluorescence assays (IFA) and Flow cytometry coupled with cell sorting. Molecular methods could differentiate species and genotypes of Cryptosporidium and help in studying the epidemiological features of this parasite with rapid, simple and sensitive procedures. Nanotechnology-based platforms could improve the sensitivity and specificity of other detection methods like: ELISA, ICLF, IFA and polymerase chain reaction. As the available prophylactic and therapeutic drugs or natural products treatments are insufficient and no approved vaccines are available, the best approach to control this parasite is by following firm hygienic measures. Many vaccine attempts were performed using hyperimmune colostrum, live or attenuated vaccines, recombinant and Deoxyribonucleic acid vaccines. Also, Clustered Regularly Interspaced Short Palindromic Repeats/Cas9 technology could help in Cryptosporidium genome editing to improve drug and vaccine discovery. Another approach that could be useful for assigning drug targets is metabolomics. Probiotics were also used successfully in the treatment of acute diarrhea and they proved a limiting effect on cryptosporidiosis in animal models. In addition, nanotherapy-based approaches could provide a good strategy for improving the potency of any type of drugs against Cryptosporidium and give good anti-cryptosporidial effects. In conclusion, accurate diagnosis using advanced techniques is the key to the control and prevention of cryptosporidiosis.PMID:36457776 | PMC:PMC9606155 | DOI:10.1007/s12639-022-01513-2

Diverse roles of the <em>CIPK</em> gene family in transcription regulation and various biotic and abiotic stresses: A literature review and bibliometric study

11 hours 42 min ago
Front Genet. 2022 Nov 15;13:1041078. doi: 10.3389/fgene.2022.1041078. eCollection 2022.ABSTRACTCIPKs are a subclass of serine/threonine (Ser/Thr) protein kinases. CBLs are ubiquitous Ca2+ sensors that interact with CIPK with the aid of secondary Ca2+ messengers for regulation of growth and development and response to stresses faced by plants. The divergent roles of the CIPK-CBL interaction in plants include responding to environmental stresses (salt, cold, drought, pH, ABA signaling, and ion toxicity), ion homeostasis (K+, NH4 +, NO3 -, and microelement homeostasis), biotic stress, and plant development. Each member of this gene family produces distinct proteins that help plants adapt to diverse stresses or stimuli by interacting with calcium ion signals. CIPK consists of two structural domains-an N-terminal domain and a C-terminal domain-connected by a junction domain. The N-terminal domain, the site of phosphorylation, is also called the activation domain and kinase domain. The C-terminal, also known as the regulatory domain of CIPK, further comprises NAF/FISL and PPI. CBL comprises four EF domains and conserved PFPF motifs and is the site of binding with the NAF/FISL domain of CIPK to form a CBL-CIPK complex. In addition, we also performed a bibliometric analysis of the CIPK gene family of data extracted from the WoSCC. A total of 95 documents were retrieved, which had been published by 47 sources. The production over time was zigzagged. The top key terms were gene, CIPK, abiotic stress, and gene expression. Beijing Forestry University was the top affiliation, while The Plant Cell was the top source. The genomics and metabolomics of this gene family require more study.PMID:36457742 | PMC:PMC9705351 | DOI:10.3389/fgene.2022.1041078

Biomarkers of AIT: Models of prediction of efficacy

11 hours 42 min ago
Allergol Select. 2022 Nov 21;6:267-275. doi: 10.5414/ALX02333E. eCollection 2022.ABSTRACTAllergic rhinitis is an IgE-mediated inflammation that remains a clinical challenge, affecting 40% of the UK population with a wide range of severity from nasal discomfort to life-threatening anaphylaxis. It can be managed by pharmacotherapeutics and in selected patients by allergen immunotherapy (AIT), which provides long-term clinical efficacy, especially during peak allergy season. However, there are no definitive biomarkers for AIT efficacy. Here, we aim to summarize the key adaptive, innate, humoral, and metabolic advances in biomarker identification in response to AIT. Mechanisms of efficacy consist of an immune deviation towards TH1-secreting IFN-γ, as well as an induction of IL10+ cTFR and TREG have been observed. TH2 cells undergo exhaustion after AIT due to chronic allergen exposure and correlates with the exhaustion markers PD-1, CTLA-4, TIGIT, and LAG3. IL10+ DCREG expressing C1Q and STAB are induced. KLRG1+ IL10+ ILC2 were shown to be induced in AIT in correlation with efficacy. BREG cells secreting IL-10, IL-35, and TGF-β are induced. Blocking antibodies IgG, IgA, and IgG4 are increased during AIT; whereas inflammatory metabolites, such as eicosanoids, are reduced. There are multiple promising biomarkers for AIT currently being evaluated. A panomic approach is essential to better understand cellular, molecular mechanisms and their correlation with clinical outcomes. Identification of predictive biomarkers of AIT efficacy will hugely impact current practice allowing physicians to select eligible patients that are likely to respond to treatment as well as improve patients' compliance to complete the course of treatment.PMID:36457722 | PMC:PMC9707369 | DOI:10.5414/ALX02333E

Cotton straw biochar and compound <em>Bacillus</em> biofertilizer reduce Cd stress on cotton root growth by regulating root exudates and antioxidant enzymes system

11 hours 42 min ago
Front Plant Sci. 2022 Nov 15;13:1051935. doi: 10.3389/fpls.2022.1051935. eCollection 2022.ABSTRACTINTRODUCTION: Cotton straw biochar (biochar) and compound Bacillus biofertilizer (biofertilizer) have attracted wide attentions in the remediation of heavy metal-contaminated soils in recent years. However, few studies have explored the metabolomics of lateral roots of Cd-stressed cotton to determine the mechanism of biochar and biofertilizer alleviating Cd stress.METHODS: In this pot experiment, biochar and biofertilizer were applied to the soils with different Cd contamination levels (1, 2, and 4 mg kg-1). Then, the responses of cotton root morphology, vitality, Cd content, and antioxidant enzyme activities were analyzed, and the mechanism of biochar and biofertilizer alleviating Cd stress was determined by metabolomic analysis.RESULTS: The results showed that exogenous Cd addition decreased the SOD and POD activities in cotton taproot and lateral root. Besides, with the increase of soil Cd content, the maximum Cd content in taproot (0.0250 mg kg-1) and lateral root (0.0288 mg kg-1) increased by 89.11% and 33.95%, respectively compared with those in the control (p< 0.05). After the application of biochar and biofertilizer, the SOD and POD activities in cotton taproot and lateral root increased. The Cd content of cotton taproot in biochar and biofertilizer treatments decreased by 16.36% and 19.73%, respectively, and that of lateral root decreased by 13.99% and 16.68%, respectively. The metabolomic analysis results showed that the application of biochar and biofertilizer could improve the resistance of cotton root to Cd stress through regulating the pathways of ABC transporters and phenylalanine metabolism.DISCUSSION: Therefore, the application of biochar and biofertilizer could improve cotton resistance to Cd stress by increasing antioxidant enzyme activities, regulating root metabolites (phenols and amino acids), and reducing Cd content, thus promoting cotton root growth.PMID:36457531 | PMC:PMC9705756 | DOI:10.3389/fpls.2022.1051935

Metabolome and transcriptome integration reveals insights into the process of delayed petal abscission in rose by STS

11 hours 42 min ago
Front Plant Sci. 2022 Nov 15;13:1045270. doi: 10.3389/fpls.2022.1045270. eCollection 2022.ABSTRACTThe abscission of plant organs plays an important role in ensuring the normal life activities. Rose is one of the most important ornamental plants, and its premature abscission of petal has seriously affected the quality and commercial value. Silver Thiosulfate (STS) is an ethylene inhibitor, which is often used preservative to delay the senescence of fresh cut flowers. To understand the regulatory mechanism of petal abscission in rose by STS, integrative analysis of the metabolome and transcriptome profiles was performed in abscission zone (AZ) tissues of rose under different treatments (MOCK, STS, ETH, STS+ETH). The results showed that STS significantly delayed the petal abscission in phenotype and reduced the activity of two enzymes (pectinase and cellulase) associated with cell wall degradation in physiological level. STS affected the contents of five metabolites (shikonin, jasmonic acid, gluconolactone, stachyose and D-Erythrose 4-phosphate), and involved changes in the expression of 39 differentially expressed genes (DEGs) associated with these five metabolites. Five DEGs (LOC112192149, LOC112196726, LOC112189737, LOC112188495, and LOC112188936) were probably directly associated with the biosynthesis of shikonin, jasmonic acid, and D-Erythrose 4-phosphate. Meanwhile, the effect of STS on the abscission process significantly involved in the pentose phosphate pathway and amino acid biosynthesis pathway. In addition, STS had a greater effect on the transcription factors, phytohormone related DEGs represented by auxin and ethylene, DEGs related to disease resistance and amino acid, etc. Above all, STS negatively influences petal abscission of rose, these results maybe provide a reference for subsequent studies on petal abscission of rose by STS.PMID:36457520 | PMC:PMC9706100 | DOI:10.3389/fpls.2022.1045270

Characterizing microbiota and metabolomics analysis to identify candidate biomarkers in lung cancer

11 hours 42 min ago
Front Oncol. 2022 Nov 15;12:1058436. doi: 10.3389/fonc.2022.1058436. eCollection 2022.ABSTRACTBACKGROUND: Lung cancer is the leading malignant disease and cause of cancer-related death worldwide. Most patients with lung cancer had insignificant early symptoms so that most of them were diagnosed at an advanced stage. In addition to factors such as smoking, pollution, lung microbiome and its metabolites play vital roles in the development of lung cancer. However, the interaction between lung microbiota and carcinogenesis is lack of systematically characterized and controversial. Therefore, the purpose of this study was to excavate the features of the lung microbiota and metabolites in patients and verify potential biomarkers for lung cancer diagnosis.METHODS: Lung tissue flushing solutions and bronchoalveolar lavage fluid samples came from patients with lung cancer and non-lung cancer. The composition and variations of the microbiota and metabolites in samples were explored using muti-omics technologies including 16S rRNA amplicon sequencing, metagenomics and metabolomics.RESULTS: The metabolomics analysis indicated that 40 different metabolites, such as 9,10-DHOME, sphingosine, and cysteinyl-valine, were statistically significant between two groups (VIP > 1 and P < 0.05). These metabolites were significantly enriched into 11 signal pathways including sphingolipid, autophagy and apoptosis signaling pathway (P < 0.05). The analysis of lung microbiota showed that significant changes reflected the decrease of microbial diversity, changes of distribution of microbial taxa, and variability of the correlation networks of lung microbiota in lung cancer patients. In particular, we found that oral commensal microbiota and multiple probiotics might be connected with the occurrence and progression of lung cancer. Moreover, our study found 3 metabolites and 9 species with significantly differences, which might be regarded as the potential clinical diagnostic markers associated with lung cancer.CONCLUSIONS: Lung microbiota and metabolites might play important roles in the pathogenesis of lung cancer, and the altered metabolites and microbiota might have the potential to be clinical diagnostic markers and therapeutic targets associated with lung cancer.PMID:36457513 | PMC:PMC9705781 | DOI:10.3389/fonc.2022.1058436

Untargeted metabolomics of pulmonary tuberculosis patient serum reveals potential prognostic markers of both latent infection and outcome

11 hours 42 min ago
Front Public Health. 2022 Nov 15;10:962510. doi: 10.3389/fpubh.2022.962510. eCollection 2022.ABSTRACTCurrently, there are no particularly effective biomarkers to distinguish between latent tuberculosis infection (LTBI) and active pulmonary tuberculosis (PTB) and evaluate the outcome of TB treatment. In this study, we have characterized the changes in the serum metabolic profiles caused by Mycobacterium tuberculosis (Mtb) infection and standard anti-TB treatment with isoniazid-rifampin-pyrazinamide-ethambutol (HRZE) using GC-MS and LC-MS/MS. Seven metabolites, including 3-oxopalmitic acid, akeboside ste, sulfolithocholic acid, 2-decylfuran (4,8,8-trimethyldecahydro-1,4-methanoazulen-9-yl)methanol, d-(+)-camphor, and 2-methylaminoadenosine, were identified to have significantly higher levels in LTBI and untreated PTB patients (T0) than those in uninfected healthy controls (Un). Among them, akeboside Ste and sulfolithocholic acid were significantly decreased in PTB patients with 2-month HRZE (T2) and cured PTB patients with 2-month HRZE followed by 4-month isoniazid-rifampin (HR) (T6). Receiver operator characteristic curve analysis revealed that the combined diagnostic model showed excellent performance for distinguishing LT from T0 and Un. By analyzing the biochemical and disease-related pathways, we observed that the differential metabolites in the serum of LTBI or TB patients, compared to healthy controls, were mainly involved in glutathione metabolism, ascorbate and aldarate metabolism, and porphyrin and chlorophyll metabolism. The metabolites with significant differences between the T0 group and the T6 group were mainly enriched in niacin and nicotinamide metabolism. Our study provided more detailed experimental data for developing laboratory standards for evaluating LTBI and cured PTB.PMID:36457328 | PMC:PMC9705731 | DOI:10.3389/fpubh.2022.962510

Isotope tracing reveals distinct substrate preference in murine melanoma subtypes with differing anti-tumor immunity

11 hours 42 min ago
Cancer Metab. 2022 Dec 1;10(1):21. doi: 10.1186/s40170-022-00296-7.ABSTRACTBACKGROUND: Research about tumor "metabolic flexibility"-the ability of cells to toggle between preferred nutrients depending on the metabolic context-has largely focused on obesity-associated cancers. However, increasing evidence for a key role for nutrient competition in the tumor microenvironment, as well as for substrate regulation of immune function, suggests that substrate metabolism deserves reconsideration in immunogenic tumors that are not strongly associated with obesity.METHODS: We compare two murine models: immunologically cold YUMM1.7 and immunologically-hot YUMMER1.7. We utilize stable isotope and radioisotope tracer-based metabolic flux studies as well as gas and liquid chromatography-based metabolomics analyses to comprehensively probe substrate preference in YUMM1.7 and YUMMER1.7 cells, with a subset of studies on the impact of available metabolites across a panel of five additional melanoma cell lines. We analyze bulk RNA-seq data and identify increased expression of amino acid and glucose metabolism genes in YUMMER1.7. Finally, we analyze melanoma patient RNA-seq data to identify potential prognostic predictors rooted in metabolism.RESULTS: We demonstrate using stable isotope tracer-based metabolic flux studies as well as gas and liquid chromatography-based metabolomics that immunologically-hot melanoma utilizes more glutamine than immunologically-cold melanoma in vivo and in vitro. Analyses of human melanoma RNA-seq data demonstrate that glutamine transporter and other anaplerotic gene expression positively correlates with lymphocyte infiltration and function.CONCLUSIONS: Here, we highlight the importance of understanding metabolism in non-obesity-associated cancers, such as melanoma. This work advances the understanding of the correlation between metabolism and immunogenicity in the tumor microenvironment and provides evidence supporting metabolic gene expression as potential prognostic factors of melanoma progression and may inform investigations of adjunctive metabolic therapy in melanoma.TRIAL REGISTRATION: Deidentified data from The Cancer Genome Atlas were analyzed.PMID:36457136 | DOI:10.1186/s40170-022-00296-7

The untargeted urine volatilome for biomedical applications: methodology and volatilome database

11 hours 42 min ago
Biol Proced Online. 2022 Dec 1;24(1):20. doi: 10.1186/s12575-022-00184-w.ABSTRACTChemically diverse in compounds, urine can give us an insight into metabolic breakdown products from foods, drinks, drugs, environmental contaminants, endogenous waste metabolites, and bacterial by-products. Hundreds of them are volatile compounds; however, their composition has never been provided in detail, nor has the methodology used for urine volatilome untargeted analysis. Here, we summarize key elements for the untargeted analysis of urine volatilome from a comprehensive compilation of literature, including the latest reports published. Current achievements and limitations on each process step are discussed and compared. 34 studies were found retrieving all information from the urine treatment to the final results obtained. In this report, we provide the first specific urine volatilome database, consisting of 841 compounds from 80 different chemical classes.PMID:36456991 | DOI:10.1186/s12575-022-00184-w

Marked gut microbiota dysbiosis and increased imidazole propionate are associated with a NASH Göttingen Minipig model

Thu, 01/12/2022 - 12:00
BMC Microbiol. 2022 Dec 1;22(1):287. doi: 10.1186/s12866-022-02704-w.ABSTRACTBACKGROUND: Gut microbiota dysbiosis is associated with the development of non-alcoholic steatohepatitis (NASH) through modulation of gut barrier, inflammation, lipid metabolism, bile acid signaling and short-chain fatty acid production. The aim of this study was to describe the impact of a choline-deficient amino acid defined high fat diet (CDAHFD) on the gut microbiota in a male Göttingen Minipig model and on selected pathways implicated in the development of NASH.RESULTS: Eight weeks of CDAHFD resulted in a significantly altered colon microbiota mainly driven by the bacterial families Lachnospiraceae and Enterobacteriaceae, being decreased and increased in relative abundance, respectively. Metabolomics analysis revealed that CDAHFD decreased colon content of short-chain fatty acid and increased colonic pH. In addition, serum levels of the microbially produced metabolite imidazole propionate were significantly elevated as a consequence of CDAHFD feeding. Hepatic gene expression analysis showed upregulation of mechanistic target of rapamycin (mTOR) and Ras Homolog, MTORC1 binding in addition to downregulation of insulin receptor substrate 1, insulin receptor substrate 2 and the glucagon receptor in CDAHFD fed minipigs. Further, the consequences of CDAHFD feeding were associated with increased levels of circulating cholesterol, bile acids, and glucagon but not total amino acids.CONCLUSIONS: Our results indicate imidazole propionate as a new potentially relevant factor in relation to NASH and discuss the possible implication of gut microbiota dysbiosis in the development of NASH. In addition, the study emphasizes the need for considering the gut microbiota and its products when developing translational animal models for NASH.PMID:36456963 | DOI:10.1186/s12866-022-02704-w

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