PubMed

Front Mol Biosci. 2023 Jan 11;9:1049402. doi: 10.3389/fmolb.2022.1049402. eCollection 2022.ABSTRACTCancer-derived small extracellular vesicles (sEVs) are multifunctional particles with a lipid bilayer structure that are involved in cancer progression, such as malignant proliferation, distant metastasis, and cancer immunity evasion. The separation protocol used to isolate sEVs is an important process and thus, several have been developed, including ultracentrifugation (UC), size exclusion chromatography (SEC), and affinity purification using antibodies against sEV surface antigens. However, the effects of different separation methods on sEV components have not been adequately examined. Here, we developed a semi-automated system for collecting sEVs by combining SEC and preparative high-performance liquid chromatography and applied it to metabolome analysis. The developed SEC system could recover sEVs more efficiently and non-destructively than UC, suggesting that it is an appropriate recovery method for metabolic analysis and reflects biological conditions. Furthermore, using the developed SEC system, we performed metabolome analysis of sEVs from isocitrate dehydrogenase 1 (IDH)-mutated human colon HCT116 cells, which produce the oncogenic metabolite, 2-hydroxyglutaric acid (2-HG). IDH1-mutated HCT116 cells released significantly more sEVs than wild-type (WT) cells. The metabolomic profiles of IDH1 mutant and WT cells showed distinct differences between the cells and their sEVs. Notably, in IDH mutant cells, large amounts of 2-HG were detected not only in cells, but also in sEVs. These results indicate that the SEC system we developed has wide potential applications in sEVs research.PMID:36710884 | PMC:PMC9873957 | DOI:10.3389/fmolb.2022.1049402

J Proteome Res. 2023 Jan 30. doi: 10.1021/acs.jproteome.2c00488. Online ahead of print.ABSTRACTThe risk stratification of acute myocardial infarction (AMI) patients is of prime importance for clinical management and prognosis assessment. Thus, we propose an ensemble machine learning analysis procedure named ADASYN-RFECV-MDA-DNN (ARMD) to address sample-unbalanced problems and enable stratification and prediction of AMI outcomes. The ARMD analysis procedure was applied to the NMR data of sera from 534 AMI-related subjects in four categories with an extremely imbalanced sample proportion. Firstly, the adaptive synthetic sampling (ADASYN) algorithm was used to address the issue of the original sample imbalance. Secondly, the recursive feature elimination with cross-validation (RFECV) processing and random forest mean decrease accuracy (RF-MDA) algorithm was performed to identify the differential metabolites corresponding to each AMI outcome. Finally, the deep neural network (DNN) was employed to classify and predict AMI events, and its performance was evaluated by comparing the four traditional machine learning methods. Compared with the other four machine learning models, DNN presented consistent superiority in almost all of the model parameters including precision, f1-score, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and classification accuracy, highlighting the potential of deep learning in classification and stratification of clinical diseases. The ARMD analysis procedure was a practical analysis tool for supervised classification and regression modeling of clinical diseases.PMID:36710647 | DOI:10.1021/acs.jproteome.2c00488

J Sci Food Agric. 2023 Jan 29. doi: 10.1002/jsfa.12474. Online ahead of print.ABSTRACTBACKGROUND: The objectives of this study were to investigate the effects of taurine on rumen fermentation, rumen bacterial community and metabolomics, nitrogen metabolism and plasma biochemical parameters in beef steers. Six castrated Simmental steers (liveweight with 402 ± 34 kg) and three levels of taurine, i.e. 0, 20, 40 g d-1 were assigned in a replicated 3 × 3 Latin square design. Each experimental period included 15 days for adaptation and 5 days for sampling.RESULTS: Supplementing taurine did not affect the ruminal pH and concentrations of ammonia nitrogen and volatile fatty acids (P > 0.10), but linearly increased the ruminal concentrations of taurine (P < 0.001) and microbial crude protein (P = 0.041). Supplementing taurine linearly increased the neutral detergent fiber digestibility (P = 0.018), and tended to linearly increase dry matter (P = 0.095), tended to increase the fecal nitrogen (P = 0.065), and increased the urinary taurine excretion (P < 0.001). Supplementing taurine quadratically increased the plasma concentration of triglycerides (P = 0.017), tended to linearly decrease growth hormone (P = 0.074), but did not affect other plasma parameters (P > 0.10). Supplementing taurine modified the rumen bacterial community and increased the ruminal concentration of taurine metabolite 2-hydroxyethoxy sulfonic acid (P < 0.001).CONCLUSION: It was concluded that taurine improved ruminal microbial crude protein synthesis and increased fiber digestibility and through modifying rumen bacterial community. It is necessary to clarify the ruminal hydrolysis of taurine in steers. This article is protected by copyright. All rights reserved.PMID:36710505 | DOI:10.1002/jsfa.12474

Metabolomics. 2023 Jan 30;19(2):8. doi: 10.1007/s11306-023-01972-5.ABSTRACTINTRODUCTION: Globally, one of the major causes of cancer related deaths in women is breast cancer. Although metabolic pattern is altered in cancer patients, robust metabolic biomarkers with a potential to improve the screening and disease monitoring are lacking. A complete metabolome profiling of breast cancer patients may lead to the identification of diagnostic/prognostic markers and potential targets.OBJECTIVES: The aim of this study was to analyze the metabolic profile in the serum from 43 breast cancer patients and 13 healthy individuals.MATERIALS & METHODS: We used 1H NMR spectroscopy for the identification and quantification of metabolites. q-RT-PCR was used to examine the relative expression of lncRNAs.RESULTS: Metabolites such as amino acids, lipids, membrane metabolites, lipoproteins, and energy metabolites were observed in the serum from both patients and healthy individuals. Using unsupervised PCA, supervised PLS-DA, supervised OPLS-DA, and random forest classification, we observed that more than 25 metabolites were altered in the breast cancer patients. Metabolites with AUC value > 0.9 were selected for further analysis that revealed significant elevation of lactate, LPR and glycerol, while the level of glucose, succinate, and isobutyrate was reduced in breast cancer patients in comparison to healthy control. The level of these metabolites (except LPR) was altered in advanced-stage breast cancer patients in comparison to early-stage breast cancer patients. The altered metabolites were also associated with over 25 signaling pathways related to metabolism. Further, lncRNAs such as H19, MEG3 and GAS5 were dysregulated in the breast tumor tissue in comparison to normal adjacent tissue.CONCLUSION: The study provides insights into metabolic alteration in breast cancer patients. It also provides an avenue to examine the association of lncRNAs with metabolic patterns in patients.PMID:36710275 | DOI:10.1007/s11306-023-01972-5

Trends Endocrinol Metab. 2023 Jan 27:S1043-2760(23)00016-4. doi: 10.1016/j.tem.2023.01.005. Online ahead of print.ABSTRACTEvidence shows that herbal medicine (HM) could be beneficial for the treatment of various diseases. However, complexities present in HM due to the unclear bioactive compounds, mechanisms of action, undetermined targets for therapy, and nonspecific features for metabolism, are currently an obstacle for the progression of novel drug discovery. Metabolomics could be a potential tool to overcome these issues and for the understanding of HM from a small-molecule metabolism level. The chinmedomics-based metabolomics method assesses the overall metabolism of organisms with a holistic view and shows great potential for understanding metabolic pathways, evaluating curative effects, clarifying mechanisms, discovering active ingredients, and precision medicine. This review focuses on the efficacy evaluation, active ingredient discovery, and target exploration of HM based on metabolomics and chinmedomics.PMID:36710216 | DOI:10.1016/j.tem.2023.01.005

Methods Cell Biol. 2023;174:65-73. doi: 10.1016/bs.mcb.2021.12.029. Epub 2022 Jan 17.ABSTRACTThe reinstatement of cancer immunosurveillance during cancer therapy is the sole means of achieving long term success with durable disease control and sometimes even cure. Induction of immunogenic cell death (ICD) by pharmacological or physical interventions such as anthracycline-based chemotherapy or ionizing irradiation, respectively, is a potent strategy for triggering immunological memory in immunocompetent mice. Thus, mice that were cured from syngeneic transplanted cancers were able to reject the same tumor cells several weeks after the eradication of the initial tumor, contrasting with the fact that antigenically distinct cells readily formed tumors. Here, we show how to harness sequential injections of antigenically identical or distinct cancer cells in immunocompetent animals to evaluate the generation of immunological memory.PMID:36710052 | DOI:10.1016/bs.mcb.2021.12.029

Methods Enzymol. 2023;680:381-419. doi: 10.1016/bs.mie.2022.07.029. Epub 2022 Sep 6.ABSTRACTTerpenes are the primary determinants of cannabis flower aroma, and ongoing research tests their potential for impacting the overall experience. Frustratingly, despite the importance of terpenes in cannabis physiology and commercial uses, literature reports vary widely regarding the major constituents of volatile blends and the concentrations of individual terpenes. In this article, we provide detailed descriptions of complementary approaches that will allow researchers to determine the identity and quantity of cannabis terpenes unequivocally and reliably. These standard operating procedures will guide decisions about which method to employ to address specific analytical goals. We are including two application examples to illustrate the utility of different approaches for tackling the analysis of terpenes in cannabis flower samples.PMID:36710020 | DOI:10.1016/bs.mie.2022.07.029

Methods Enzymol. 2023;680:353-380. doi: 10.1016/bs.mie.2022.07.028. Epub 2022 Sep 14.ABSTRACTThe cannabis (Cannabis sativa L.) genome is highly heterozygous and, to retain genetic identity, clonal propagation of cultivars is very common. Establishing controlled environments, often involving multiple locations throughout a single grow, is critical for reliably generating materials to be used in research and production. In this article, we break down different periods of the grow cycle, such as cloning, hardening (optional), vegetative growth, flowering growth, and harvest, into individual steps. We are including images and videos for an in-depth coverage of methodological details. We are providing a list of equipment, supplies, reagents, and other resources to help with planning a grow experiment. Finally, we are discussing considerations for different aspects of controlled environments, including lighting, fertilizer regimes, and integrated pest management. With this article, it is our goal to empower researchers to reliably generate disease-free cannabis material suitable for genetic and biochemical studies that require full control of environmental factors.PMID:36710019 | DOI:10.1016/bs.mie.2022.07.028

Methods Enzymol. 2023;680:325-350. doi: 10.1016/bs.mie.2022.08.015. Epub 2022 Sep 13.ABSTRACTNon-targeted metabolome approaches aim to detect metabolite markers related to stress, disease, developmental or genetic perturbation. In the later context, it is also a powerful means for functional gene annotation. A prerequisite for non-targeted metabolome analyses are methods for comprehensive metabolite extraction. We present three extraction protocols for a highly efficient extraction of metabolites from plant material with a very broad metabolite coverage. The presented metabolite fingerprinting workflow is based on liquid chromatography high resolution accurate mass spectrometry (LC-HRAM-MS), which provides suitable separation of the complex sample matrix for the analysis of compounds of different polarity by positive and negative electrospray ionization and mass spectrometry. The resulting data sets are then analyzed with the software suite MarVis and the web-based interface MetaboAnalyst. MarVis offers a straightforward workflow for statistical analysis, data merging as well as visualization of multivariate data, while MetaboAnalyst is used in our hands as complementary software for statistics, correlation networks and figure generation. Finally, MarVis provides access to species-specific metabolite and pathway data bases like KEGG and BioCyc and to custom data bases tailored by the user to connect the identified markers or features with metabolites. In addition, identified marker candidates can be interactively visualized and inspected in metabolic pathway maps by KEGG pathways for a more detailed functional annotation and confirmed by mass spectrometry fragmentation experiments or coelution with authentic standards. Together this workflow is a valuable toolbox to identify novel metabolites, metabolic steps or regulatory principles and pathways.PMID:36710017 | DOI:10.1016/bs.mie.2022.08.015

Methods Enzymol. 2023;680:303-323. doi: 10.1016/bs.mie.2022.08.005. Epub 2022 Sep 29.ABSTRACTOver the past decade, the number of fully sequenced genomes has increased at an awe-inspiring pace. Similarly, the quality and scope of tools for the prediction of both protein structure and function has seen vast improvements. However, to pinpoint the exact function of a protein, for instance the exact reaction catalyzed by an enzyme, experimental evidence is crucial. At the same time, this step is the main bottleneck when generating a conclusive model for the function of an enzyme and to interpret its function in a physiological context. Hence, a comprehensive experimental strategy for functional annotation of enzymes that is as efficient as possible is required. Ex vivo metabolomics is a powerful non-targeted approach that overcomes several of the challenges inherent to in vitro characterization of enzymes with unknown functions. By incubating the recombinant enzyme of interest in a quasi-native metabolite extract from its tissue of origin under specific environmental and developmental conditions, the complete native substrate range can be tested in a single assay. This unlocks compounds that are commercially unavailable or otherwise difficult to procure. Coupled with non-targeted metabolomics analysis, ex vivo has the capability to test for and identify even unexpected substrates and assign the respective products of the enzymatic reaction.PMID:36710016 | DOI:10.1016/bs.mie.2022.08.005

Methods Enzymol. 2023;680:247-273. doi: 10.1016/bs.mie.2022.08.029. Epub 2022 Sep 24.ABSTRACTPlants are expert chemists producing millions of metabolites, only a fraction of which are known to date. Plant metabolomics explores the rationale for highly diverse metabolites evolved and synthesized by plants. Over two-thirds of modern medicines are somehow inspired and/or derived from plants, making the identification of phytochemicals a means of discovering new medicines to challenge existing and emerging diseases. This chapter introduces our established liquid chromatography-tandem mass spectrometry-based untargeted metabolomics approach centered around discovering specialized metabolites (so-called secondary metabolites) across broad lineages of nonmodel plant species. Detecting hundreds to thousands of metabolite peaks, including assigning chemical identity, makes metabolomics data generation and analysis a very complex process. Various mass spectrometry techniques are currently being developed to approach the comprehensive metabolome. Among them, untargeted metabolomics can provide new biological insights by simultaneously and unbiasedly measuring and analyzing all detected metabolites. We have provided a hands-on modular account for untargeted plant metabolomics, from preparing plant biological samples to data analysis and processing using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The methods described here offer a foundation and expert opinion on plant metabolome analysis.PMID:36710013 | DOI:10.1016/bs.mie.2022.08.029

Biochem Pharmacol. 2023 Jan 26:115433. doi: 10.1016/j.bcp.2023.115433. Online ahead of print.ABSTRACTInherited metabolic disorders (IMDs) are genetic disorders that cause a disruption of a specific metabolic pathway leading to biochemical, clinical and pathophysiological sequelae. While the metabolite abnormalities in body fluids and tissues can usually be defined by directed or broad-spectrum metabolomic analysis, the pathophysiology of these changes is often not obvious. Mounting evidence has revealed that secondary mitochondrial dysfunction, mainly oxidative phosphorylation impairment and elevated reactive oxygen species, plays a pivotal role in many disorders. Peroxisomal proliferator-activated receptors (PPARs) consist of a group of nuclear hormone receptors (PPARα, PPARβ/δ, and PPARγ) that regulate multiple cellular functions and processes, including response to oxidative stress, inflammation, lipid metabolism, and mitochondrial bioenergetics and biogenesis. In this context, the activation of PPARs has been shown to stimulate oxidative phosphorylation and reduce reactive species levels. Thus, pharmacological treatment with PPAR activators, such as fibrates, has gained much attention in the last 15 years. This review summarizes preclinical (animal models and patient-derived cells) and clinical data on the effect of PPARs in IMDs.PMID:36709926 | DOI:10.1016/j.bcp.2023.115433

Phytomedicine. 2023 Jan 13;111:154674. doi: 10.1016/j.phymed.2023.154674. Online ahead of print.ABSTRACTBACKGROUND: Panax notoginseng (PN) was an edible Chinese herbal medicine. PN's current quality control standard cannot precisely match the traditional grading experience.PURPOSE: In this study, under the guidance of the traditional grading experience, the combined metabolomics and biological effect evaluation were used to reveal the distinct chemical quality of PN.METHODS: The quality of PN was evaluated by traditional experience and characterized by the electronic tongue. A zebrafish myocardial ischemia model was developed to verify the grading experience. The untargeted metabolomics method was used to identify and validate the grading markers of PN.RESULTS: The taste was the critical indicator for classifying the quality. Based on the experience sensory scores (ranged from 47.0 to 87.8), PNs could be divided into two grades. The experience scores were significantly associated with umami and richness of the electronic tongue(p<0.01). Besides, superior PN showed substantially stronger anti-myocardial ischemia activity(p<0.001). Thirty-nine differential components were found using UHPLC-LTQ-Orbitrap MS, of which 22 were identified. A new kind of grading quality markers alkynols in PN-associated efficacy was identified, which revealed stronger anti-myocardial ischemia activities than saponin.CONCLUSION: This study evaluated PN through untargeted metabolomics and anti-myocardial ischemia evaluation of zebrafish and proposed the critical role of alkynols in PN's quality classification.PMID:36709617 | DOI:10.1016/j.phymed.2023.154674

Mol Genet Metab. 2022 Dec 26;138(2):106983. doi: 10.1016/j.ymgme.2022.106983. Online ahead of print.ABSTRACTGM2-Gangliosidosis are a group of inherited lysosomal storage pathologies characterized by a large accumulation of GM2 ganglioside in the lysosome. They are caused by mutation in HEXA or HEXB causing reduced or absent activity of a lysosomal β-hexosaminidase A, or mutation in GM2A causing defect in GM2 activator protein (GM2AP), an essential protein for the activity of the enzyme. Biochemical diagnosis relies on the measurement of β-hexosaminidases A and B activities, which is able to detect lysosomal enzyme deficiency but fails to identify defects in GM2AP. We developed a rapid, specific and sensitive liquid chromatography-mass spectrometry-based method to measure simultaneously GM1, GM2, GM3 and GD3 molecular species. Gangliosides were analysed in plasma from 19 patients with GM2-Gangliosidosis: Tay-Sachs (n = 9), Sandhoff (n = 9) and AB variant of GM2-Gangliosidosis (n = 1) and compared to 20 age-matched controls. Among patients, 12 have a late adult-juvenile-onset and 7 have an infantile early-onset of the disease. Plasma GM2 molecular species were increased in all GM2-Gangliosidosis patients (19/19), including the patient with GM2A mutation, compared to control individuals and compared to patients with different other lysosomal storage diseases. GM234:1 and GM234:1/GM334:1 ratio discriminated patients from controls with 100% sensitivity and specificity. GM234:1 and GM234:1/GM334:1 were higher in patients with early-onset compared to those with late-onset of the disease, suggesting a relationship with severity. Longitudinal analysis in one adult with Tay-Sachs disease over 9 years showed a positive correlation of GM234:1 and GM234:1/GM334:1 ratio with age at sampling. We propose that plasma GM2 34:1 and its ratio to GM3 34:1 could be sensitive and specific biochemical diagnostic biomarkers for GM2-Gangliosidosis including AB variant and could be useful as a first line diagnostic test and potential biomarkers for monitoring upcoming therapeutic efficacy.PMID:36709536 | DOI:10.1016/j.ymgme.2022.106983

J Steroid Biochem Mol Biol. 2023 Jan 25:106250. doi: 10.1016/j.jsbmb.2023.106250. Online ahead of print.ABSTRACTVitamin D is a steroid hormone precursor that was initially recognized for its important roles in calcium-phosphate homeostasis and bone health. However, the resent prevalence of vitamin D deficiency has highlighted its non-skeletal function, such as its important role in regulating endogenous metabolism. The aim of the present study was to examine the roles of vitamin D supplementation or deficiency on metabolic phenotypes in both male and female mice by using targeted metabolomics analysis. Six weeks old C57BL/6 mice of different sexes were fed with standard chow diet (1000 IU/kg vitamin D3 contained), vitamin D deficient diet (0 IU/kg vitamin D3 contained), or vitamin D enriched diet (10000 IU/kg vitamin D3 contained) for a total of 14 weeks. Liver pathological analysis showed that vitamin D deficiency caused significant fat deposition in both male and female mice. While vitamin D supplementation was found to improve the accumulation of fat in the liver tissue. Metabolomics analysis indicated that metabolic perturbation related to vitamin D regulation in male mice mainly involved in tricarboxylic acid cycle, fatty acylcarnitine and fatty acid metabolism, sugar metabolism, glutathione metabolism, steroid hormone and pyrimidine metabolism. Based on the criteria of VIP>1 in OPLS-DA analysis and P<0.05 in hypothesis test, a total of 62 metabolites and 78 metabolites were found to be significantly changed in VD-deficiency group and VD-supplement group compared with the control group, respectively. While for female mice, the metabolites disturbance mainly involved in fatty acylcarnitine and fatty acid metabolism, TCA, sugar metabolism, folate cycle, methionine cycle, and purine metabolism. A total of 38 and 57 metabolites were found to be significantly changed (VIP>1 and P<0.05) in VD-deficiency group and VD-supplement group compared with the control group, respectively. Energy metabolism was the most relevant metabolic pathway for vitamin D regulation in both male and female mice. Sex-specific changes of fatty acyl carnitines and dehydroepiandrosterone were observed in the vitamin D supplementation groups. However, most of the energy metabolism related compounds exhibited the same trend in vitamin D supplementation groups of different sexes. Pearson's correlation analysis indicated that vitamin D was significantly correlated (P<0.05) with the levels of D-fructose 6-phosphate, D-glucose 1-phosphate, D-glucose 6-phosphate, DL-pyroglutamic acid, 2-oxoglutarate, L-glutamic acid, and fumarate, which were all involved in the sugar metabolism pathway. The results achieved in this study demonstrated that vitamin D significantly regulated the metabolism of lipid and sugar, and the regulation showed a certain sex specificity.PMID:36708934 | DOI:10.1016/j.jsbmb.2023.106250

Exp Gerontol. 2023 Jan 25:112108. doi: 10.1016/j.exger.2023.112108. Online ahead of print.ABSTRACTWe characterized long-term changes in cardiac structure and function in a high-fat diet/streptozotocin mouse model of aging and type 2 diabetes mellitus (T2D) and examined how the intersection of both conditions alters plasma metabolomics. We also evaluated the possible roles played by oxidative stress, arginase activity and pro-inflammatory cytokines. C57BL/6 male mice (13-month-old) were used. Control animals (n = 13) were fed regular chow for 10 months (aged group). T2D animals (n = 25) were provided a single injection of streptozotocin and fed a high fat diet for 10 months. In select endpoints, young animals were used for comparison. To monitor changes in left ventricular (LV) structure and function, echocardiography was used. At the terminal study (23 months), blood was collected and hearts processed for biochemical or histological analysis. Echo yielded diminished diastolic function with aging and T2D. LV fractional shortening and ejection fraction decreased with T2D by 16 months peaking at 23 months. Western blots noted increases in fibronectin and type I collagen with aging/T2D and greater levels with T2D in α-smooth muscle actin. Increases in plasma and/or myocardial protein carbonyls, arginase activity and pro-inflammatory cytokines occurred with aging and T2D. Untargeted metabolomics and cheminformatics revealed differences in the plasma metabolome of T2D vs. aged mice while select classes of lipid metabolites linked to insulin resistance, were dysregulated. We thus, document changes in LV structure and function with aging that in select endpoints, are accentuated with T2D and link them to increases in OS, arginase activity and pro-inflammatory cytokines.PMID:36708752 | DOI:10.1016/j.exger.2023.112108

Curr HIV/AIDS Rep. 2023 Jan 28. doi: 10.1007/s11904-023-00648-y. Online ahead of print.ABSTRACTPURPOSE OF REVIEW: To synthesize recent evidence relating the gut microbiome and microbial metabolites to cardiovascular disease (CVD) in people living with HIV (PLWH).RECENT FINDINGS: A few cross-sectional studies have reported on the gut microbiome and cardiovascular outcomes in the context of HIV, with no consistent patterns emerging. The largest such study found that gut Fusobacterium was associated with carotid artery plaque. More studies have evaluated microbial metabolite trimethylamine N-oxide with CVD risk in PLWH, but results were inconsistent, with recent prospective analyses showing null effects. Studies of other microbial metabolites are scarce. Microbial translocation biomarkers (e.g., lipopolysaccharide binding protein) have been related to incident CVD in PLWH. Microbial translocation may increase CVD risk in PLWH, but there is insufficient and/or inconsistent evidence regarding specific microbial species and microbial metabolites associated with cardiovascular outcomes in PLWH. Further research is needed in large prospective studies integrating the gut microbiome, microbial translocation, and microbial metabolites with cardiovascular outcomes in PLWH.PMID:36708497 | DOI:10.1007/s11904-023-00648-y

BMC Plant Biol. 2023 Jan 28;23(1):59. doi: 10.1186/s12870-023-04074-5.ABSTRACTBACKGROUND: Massive parallel sequencing technologies have enabled the elucidation of plant phylogenetic relationships from chloroplast genomes at a high pace. These include members of the family Rhamnaceae. The current Rhamnaceae phylogenetic tree is from 13 out of 24 Rhamnaceae chloroplast genomes, and only one chloroplast genome of the genus Ventilago is available. Hence, the phylogenetic relationships in Rhamnaceae remain incomplete, and more representative species are needed.RESULTS: The complete chloroplast genome of Ventilago harmandiana Pierre was outlined using a hybrid assembly of long- and short-read technologies. The accuracy and validity of the final genome were confirmed with PCR amplifications and investigation of coverage depth. Sanger sequencing was used to correct for differences in lengths and nucleotide bases between inverted repeats because of the homopolymers. The phylogenetic trees reconstructed using prevalent methods for phylogenetic inference were topologically similar. The clustering based on codon usage was congruent with the molecular phylogenetic tree. The groups of genera in each tribe were in accordance with tribal classification based on molecular markers. We resolved the phylogenetic relationships among six Hovenia species, three Rhamnus species, and two Ventilago species. Our reconstructed tree provides the most complete and reliable low-level taxonomy to date for the family Rhamnaceae. Similar to other higher plants, the RNA editing mostly resulted in converting serine to leucine. Besides, most genes were subjected to purifying selection. Annotation anomalies, including indel calling errors, unaligned open reading frames of the same gene, inconsistent prediction of intergenic regions, and misannotated genes, were identified in the published chloroplast genomes used in this study. These could be a result of the usual imperfections in computational tools, and/or existing errors in reference genomes. Importantly, these are points of concern with regards to utilizing published chloroplast genomes for comparative genomic analysis.CONCLUSIONS: In summary, we successfully demonstrated the use of comprehensive genomic data, including DNA and amino acid sequences, to build a reliable and high-resolution phylogenetic tree for the family Rhamnaceae. Additionally, our study indicates that the revision of genome annotation before comparative genomic analyses is necessary to prevent the propagation of errors and complications in downstream analysis and interpretation.PMID:36707785 | DOI:10.1186/s12870-023-04074-5

Sci Rep. 2023 Jan 27;13(1):1552. doi: 10.1038/s41598-023-27726-w.ABSTRACTHemp seed bran (HB) is an industrial food byproduct that is generally discarded. Knowledge on the functional capabilities of HB is limited and it is not known the impact of HB on human colon microbiota, where vegetable fibers are metabolized. In this work, we investigated in depth the prebiotic potential of HB and HB protein extract hydrolyzed by alcalase (HBPA) in comparison to fructooligosaccharides (FOS) after human distal colonic fermentation using MICODE (multi-unit in vitro colon gut model). During the 24 h of fermentation, metabolomics (SPME GC/MS) and microbiomics (MiSeq and qPCR) analyses were performed. The results indicated that HBPA on a colonic fermentation had a higher prebiotic index than HB (p < 0.05), and slightly lower to that of FOS (p > 0.05). This feature was described and explained as HBPA colonic fermentation produces beneficial organic fatty acids (e.g. Pentanoic and Hexanoic acids); reduces detrimental phenol derivates (e.g. p-Cresol); produces bioactives VOCs (e.g. Acetophenone or 4-Terpineol); increases beneficial bacteria (e.g. 1.76 fold and 2.07 fold more of Bifidobacterium bifidum and Bacteroides fragilis, respectively) and limits opportunistic bacteria (e.g. 3.04 fold and 2.07 fold less of Bilophila wadsworthia and Desulfovibrio, respectively). Our study evidenced the prebiotic role of HB and HBPA, and within the principles of OneHealth it valorizes a byproduct from the queen plant of sustainable crops as a food supplement.PMID:36707683 | DOI:10.1038/s41598-023-27726-w

Sci Rep. 2023 Jan 27;13(1):1526. doi: 10.1038/s41598-023-27903-x.ABSTRACTDelta age is a biomarker of brain aging that captures differences between the chronological age and the predicted biological brain age. Using multimodal data of brain MRI, genomics, and blood-based biomarkers and metabolomics in UK Biobank, this study investigates an explainable and causal basis of high delta age. A visual saliency map of brain regions showed that lower volumes in the fornix and the lower part of the thalamus are key predictors of high delta age. Genome-wide association analysis of the delta age using the SNP array data identified associated variants in gene regions such as KLF3-AS1 and STX1. GWAS was also performed on the volumes in the fornix and the lower part of the thalamus, showing a high genetic correlation with delta age, indicating that they share a genetic basis. Mendelian randomization (MR) for all metabolomic biomarkers and blood-related phenotypes showed that immune-related phenotypes have a causal impact on increasing delta age. Our analysis revealed regions in the brain that are susceptible to the aging process and provided evidence of the causal and genetic connections between immune responses and brain aging.PMID:36707530 | DOI:10.1038/s41598-023-27903-x