PubMed

Chin J Integr Med. 2023 May 24. doi: 10.1007/s11655-023-3552-0. Online ahead of print.ABSTRACTOBJECTIVE: To clarify the potential mechanism of Banxia Xiexin Decoction (BXD) on colorectal cancer (CRC) from the perspective of metabolomics.METHODS: Forty male C57BL/6 mice were randomly divided into normal control (NC), azoxymethane/dextran sulfate sodium (AOM/DSS) model, low-dose BXD (L-BXD), high-dose BXD (H-BXD) and mesalamine (MS) groups according to a random number table, 8 mice in each group. Colorectal cancer model was induced by AOM/DSS. BXD was administered daily at doses of 3.915 (L-BXD) and 15.66 g/kg (H-BXD) by gavage for consecutive 21 days, and 100 mg/kg MS was used as positive control. Following the entire modeling cycle, colon length of mice was measured and quantity of colorectal tumors were counted. The spleen and thymus index were determined by calculating the spleen/thymus weight to body weight. Inflammatory cytokine and changes of serum metabolites were analyzed by enzyme-linked immunosorbent assay kits and ultra performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UPLC-Q/TOF-MS), respectively.RESULTS: Notably, BXD supplementation protected against weight loss, mitigated tumor formation, and diminished histologic damage in mice treated with AOM/DSS (P<0.05 or P<0.01). Moreover, BXD suppressed expression of serum inflammatory enzymes, and improved the spleen and thymus index (P<0.05). Compared with the normal group, 102 kinds of differential metabolites were screened in the AOM/DSS group, including 48 potential biomarkers, involving 18 main metabolic pathways. Totally 18 potential biomarkers related to CRC were identified, and the anti-CRC mechanism of BXD was closely related to D-glutamine and D-glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, nitrogen metabolism and so on.CONCLUSION: BXD exerts partial protective effects on AOM/DSS-induced CRC by reducing inflammation, protecting organism immunity ability, and regulating amino acid metabolism.PMID:37222828 | DOI:10.1007/s11655-023-3552-0

J Neurochem. 2023 May 24. doi: 10.1111/jnc.15845. Online ahead of print.ABSTRACTWhite matter hyperintensities (WMH) are the most compelling risk factors of stroke, dementia, and early mortality. We aimed to investigate the associations between WMH and circulating metabolites. We studied up to 8190 individuals from the UK Biobank, who have both measurements of 249 plasma metabolites and WMH volume. Linear regression models were applied in pooled samples, and age-stratified and sex-stratified subsamples to estimate the associations between WMH and metabolomic measures. We conducted three analytic models. In the basic model, we identified 45 metabolomic measures associated with WMH after multiple testing correction (p < 0.0022), 15 of which remained significant in additional adjustments, but no metabolites passed the full adjustment in pooled samples. The 15 WMH-related metabolites were subfractions of various sizes of high-density lipoprotein (HDL), fatty acids, and glycoprotein acetyls. Among them, one fatty acid metabolite and 12 HDL-related traits showed significant negative associations with WMH. Higher glycoprotein acetyls were associated with large WMH. Strong age and sex specificities were observed indicating distinct metabolomic features accompany WMH in different samples. More metabolites were identified in males and adults under 50 years old. Circulating metabolites showed remarkably widespread associations with WMH. Population specificities may shed light on the different pertinent implications of WMH.PMID:37222503 | DOI:10.1111/jnc.15845

Hepatology. 2023 May 25. doi: 10.1097/HEP.0000000000000474. Online ahead of print.ABSTRACTThere is great interest in identifying microbiome features as reliable noninvasive diagnostic and/or prognostic biomarkers for non-cirrhotic NASH fibrosis. Several cross-sectional studies have reported gut microbiome features associated with advanced NASH fibrosis and cirrhosis, where the most prominent features are associated with cirrhosis. However, no large, prospectively collected data exist establishing microbiome features that discern non-cirrhotic NASH fibrosis, integrate the fecal metabolome as disease biomarkers, and are unconfounded by BMI and age. Results from shotgun metagenomic sequencing performed on fecal samples prospectively collected from 279 US patients with biopsy-proven NASH (F1-F3 fibrosis) enrolled in the REGENERATE I303 study were compared to those from three healthy control cohorts and integrated with the absolute quantification of fecal bile acids. Microbiota beta-diversity was different, and BMI- and age-adjusted logistic regression identified 12 NASH-associated species. Random forest prediction models resulted in an AUC of 0.75 to 0.81 in a receiver operator characteristic analysis. Additionally, specific fecal bile acids were significantly lower in NASH and correlated with plasma C4 levels. Microbial gene abundance analysis revealed 127 genes increased in controls, many involving protein synthesis, whereas 362 genes were increased in NASH many involving bacterial environmental responses (FDR < 0.01). Finally, we provide evidence that fecal bile acid levels may be a better discriminator of non-cirrhotic NASH versus health than either plasma bile acids or gut microbiome features. These results may have value as a set of baseline characteristics of non-cirrhotic NASH against which therapeutic interventions to prevent cirrhosis can be compared and microbiome-based diagnostic biomarkers identified.PMID:37222264 | DOI:10.1097/HEP.0000000000000474

CNS Neurosci Ther. 2023 May 24. doi: 10.1111/cns.14253. Online ahead of print.ABSTRACTAIMS: This metabolomic study aimed to evaluate the role of N-acetylneuraminic acid (Neu5Ac) in the neurological deficits of normal pressure hydrocephalus (NPH) and its potential therapeutic effect.METHODS: We analyzed the metabolic profiles of NPH using cerebrospinal fluid with multivariate and univariate statistical analyses in a set of 42 NPH patients and 38 controls. We further correlated the levels of differential metabolites with severity-related clinical parameters, including the normal pressure hydrocephalus grading scale (NPHGS). We then established kaolin-induced hydrocephalus in mice and treated them using N-acetylmannosamine (ManNAc), a precursor of Neu5Ac. We examined brain Neu5Ac, astrocyte polarization, demyelination, and neurobehavioral outcomes to explore its therapeutic effect.RESULTS: Three metabolites were significantly altered in NPH patients. Only decreased Neu5Ac levels were correlated with NPHGS scores. Decreased brain Neu5Ac levels have been observed in hydrocephalic mice. Increasing brain Neu5Ac by ManNAc suppressed the activation of astrocytes and promoted their transition from A1 to A2 polarization. ManNAc also attenuated the periventricular white matter demyelination and improved neurobehavioral outcomes in hydrocephalic mice.CONCLUSION: Increasing brain Neu5Ac improved the neurological outcomes associated with the regulation of astrocyte polarization and the suppression of demyelination in hydrocephalic mice, which may be a potential therapeutic strategy for NPH.PMID:37222223 | DOI:10.1111/cns.14253

J Periodontal Res. 2023 May 23. doi: 10.1111/jre.13140. Online ahead of print.ABSTRACTBACKGROUND/AIMS: Hyperglycemia in diabetes is closely associated with periodontal disease progression. This study aimed to investigate the effect of hyperglycemia on the barrier function of gingival epithelial cells as a cause of hyperglycemia-exacerbated periodontitis in diabetes mellitus.METHODS: The abnormal expression of adhesion molecules in gingival epithelium in diabetes was compared between db/db and control mice. To study the effects of hyperglycemia on interepithelial cell permeability, the mRNA and protein expressions of adhesion molecules were investigated using a human gingival epithelial cell line (epi 4 cells) in the presence of either 5.5 mM glucose (NG) or 30 mM glucose (HG). Immunocytochemical and histological analyses were performed. We also studied HG-related intracellular signaling to assess abnormal adhesion molecule expression in the cultured epi 4 cells.RESULTS: The results of the proteomic analysis implied the abnormal regulation of cell-cell adhesion, and mRNA and protein expression assessments revealed the significant downregulation of Claudin1 expression in the gingival tissues of db/db mice (p < .05 vs control). Similarly, the mRNA and protein expressions of adhesion molecules were lower in epi 4 cells cultured under HG conditions than in those cultured under NG conditions (p < .05). Three-dimensional culture and transmission electron microscopy revealed reduced thickness of the epithelial cell layers with no flattened apical cells and heterogeneously arranged intercellular spaces among adjacent epi 4 cells under the HG. These results were consistent with the increased permeability of epi 4 cells under the HG relative to that of cells under the NG. This abnormal expression of intercellular adhesion molecules under the HG was related to the increased expression of receptors for advanced glycation end products (AGEs) and oxidative stress relative to that seen under the NG, along with stimulation of ERK1/2 phosphorylation in epi 4 cells.CONCLUSIONS: High glucose-induced impairment of intercellular adhesion molecule expression in gingival epithelial cells was related to the intercellular permeability of gingival cells, representing a possible link to hyperglycemia-related AGE signaling, oxidative stress, and ERK1/2 activation.PMID:37221815 | DOI:10.1111/jre.13140

BMC Bioinformatics. 2023 May 23;24(1):214. doi: 10.1186/s12859-023-05342-9.ABSTRACTBACKGROUND: A variety of high-throughput analyses, such as transcriptome, proteome, and metabolome analysis, have been developed, producing unprecedented amounts of omics data. These studies generate large gene lists, of which the biological significance shall be deeply understood. However, manually interpreting these lists is difficult, especially for non-bioinformatics-savvy scientists.RESULTS: We developed an R package and a corresponding web server-Genekitr, to assist biologists in exploring large gene sets. Genekitr comprises four modules: gene information retrieval, ID (identifier) conversion, enrichment analysis and publication-ready plotting. Currently, the information retrieval module can retrieve information on up to 23 attributes for genes of 317 organisms. The ID conversion module assists in ID-mapping of genes, probes, proteins, and aliases. The enrichment analysis module organizes 315 gene set libraries in different biological contexts by over-representation analysis and gene set enrichment analysis. The plotting module performs customizable and high-quality illustrations that can be used directly in presentations or publications.CONCLUSIONS: This web server tool will make bioinformatics more accessible to scientists who might not have programming expertise, allowing them to perform bioinformatics tasks without coding.PMID:37221491 | DOI:10.1186/s12859-023-05342-9

BMC Plant Biol. 2023 May 24;23(1):273. doi: 10.1186/s12870-023-04280-1.NO ABSTRACTPMID:37221477 | DOI:10.1186/s12870-023-04280-1

Harmful Algae. 2023 Jun;125:102430. doi: 10.1016/j.hal.2023.102430. Epub 2023 Mar 25.ABSTRACTFreshwater cyanobacteria are known worldwide for their potential to produce toxins. However, these organisms are also found in marine, terrestrial and extreme environments and produce unique compounds, other than toxins. Nevertheless, their effects on biological systems are still barely known. This work tested extracts of different cyanobacterial strains against zebrafish (Danio rerio) larvae and analyzed their metabolomic profiles using liquid chromatography combined with mass spectrometry. Strains Desertifilum tharense, Anagnostidinema amphibium, and Nostoc sp. promoted morphological abnormalities such as pericardial edema, edema in the digestive system region, curvature of the tail and spine in zebrafish larvae in vivo. In contrast, Microcystis aeruginosa and Chlorogloeopsis sp. did not promote such changes. Metabolomics revealed unique compounds belonging to the classes of terpenoids, peptides, and linear lipopeptides/microginins in the nontoxic strains. The toxic strains were shown to contain unique compounds belonging to the classes of cyclic peptides, amino acids and other peptides, anabaenopeptins, lipopeptides, terpenoids, and alkaloids and derivatives. Other unknown compounds were also detected, highlighting the rich structural diversity of secondary metabolites produced by cyanobacteria. The effects of cyanobacterial metabolites on living organisms, mainly those related to potential human and ecotoxicological risks, are still poorly known. This work highlights the diverse, complex, and unique metabolomic profiles of cyanobacteria and the biotechnological potential and associated risks of exposure to their metabolites.PMID:37220983 | DOI:10.1016/j.hal.2023.102430

BMB Rep. 2023 May 24:5912. Online ahead of print.ABSTRACTThis study investigates the relationship between cancer cachexia and the gut microbiota, focusing on the influence of cancer on microbial composition. Lewis lung cancer cell allografts were used to induce cachexia in mice, and body and muscle weight changes were monitored. Fecal samples were collected for targeted metabolomic analysis for short chain fatty acids and microbiome analysis. The cachexia group exhibited lower alpha diversity and distinct beta diversity in gut microbiota compared to the control group. Differential abundance analysis revealed higher Bifidobacterium and Romboutsia, but lower Streptococcus abundance in the cachexia group. Additionally, lower proportions of acetate and butyrate were observed in the cachexia group. The study observed that a significant impact of cancer cachexia on gut microbiota and their generated metabolites, indicating the host-to-gut microbiota axis.PMID:37220909

aBIOTECH. 2023 Jan 11;4(1):47-56. doi: 10.1007/s42994-022-00091-4. eCollection 2023 Mar.ABSTRACTPlants are the most important sources of food for humans, as well as supplying many ingredients that are of great importance for human health. Developing an understanding of the functional components of plant metabolism has attracted considerable attention. The rapid development of liquid chromatography and gas chromatography, coupled with mass spectrometry, has allowed the detection and characterization of many thousands of metabolites of plant origin. Nowadays, elucidating the detailed biosynthesis and degradation pathways of these metabolites represents a major bottleneck in our understanding. Recently, the decreased cost of genome and transcriptome sequencing rendered it possible to identify the genes involving in metabolic pathways. Here, we review the recent research which integrates metabolomic with different omics methods, to comprehensively identify structural and regulatory genes of the primary and secondary metabolic pathways. Finally, we discuss other novel methods that can accelerate the process of identification of metabolic pathways and, ultimately, identify metabolite function(s).PMID:37220537 | PMC:PMC10199974 | DOI:10.1007/s42994-022-00091-4

PeerJ. 2023 May 18;11:e15302. doi: 10.7717/peerj.15302. eCollection 2023.ABSTRACTBACKGROUND: Malignant mesothelioma (MM) is a cancer caused mainly by asbestos exposure, and is aggressive and incurable. This study aimed to identify differential metabolites and metabolic pathways involved in the pathogenesis and diagnosis of malignant mesothelioma.METHODS: By using gas chromatography-mass spectrometry (GC-MS), this study examined the plasma metabolic profile of human malignant mesothelioma. We performed univariate and multivariate analyses and pathway analyses to identify differential metabolites, enriched metabolism pathways, and potential metabolic targets. The area under the receiver-operating curve (AUC) criterion was used to identify possible plasma biomarkers.RESULTS: Using samples from MM (n = 19) and healthy control (n = 22) participants, 20 metabolites were annotated. Seven metabolic pathways were disrupted, involving alanine, aspartate, and glutamate metabolism; glyoxylate and dicarboxylate metabolism; arginine and proline metabolism; butanoate and histidine metabolism; beta-alanine metabolism; and pentose phosphate metabolic pathway. The AUC was used to identify potential plasma biomarkers. Using a threshold of AUC = 0.9, five metabolites were identified, including xanthurenic acid, (s)-3,4-hydroxybutyric acid, D-arabinose, gluconic acid, and beta-d-glucopyranuronic acid.CONCLUSIONS: To the best of our knowledge, this is the first report of a plasma metabolomics analysis using GC-MS analyses of Asian MM patients. Our identification of these metabolic abnormalities is critical for identifying plasma biomarkers in patients with MM. However, additional research using a larger population is needed to validate our findings.PMID:37220527 | PMC:PMC10200095 | DOI:10.7717/peerj.15302

Plant Physiol. 2023 May 23:kiad298. doi: 10.1093/plphys/kiad298. Online ahead of print.ABSTRACTAcclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis thaliana) were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome × environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.PMID:37220420 | DOI:10.1093/plphys/kiad298

Anal Chem. 2023 May 23. doi: 10.1021/acs.analchem.2c05371. Online ahead of print.ABSTRACTIn recent years, feces has surfaced as the matrix of choice for investigating the gut microbiome-health axis because of its non-invasive sampling and the unique reflection it offers of an individual's lifestyle. In cohort studies where the number of samples required is large, but availability is scarce, a clear need exists for high-throughput analyses. Such analyses should combine a wide physicochemical range of molecules with a minimal amount of sample and resources and downstream data processing workflows that are as automated and time efficient as possible. We present a dual fecal extraction and ultra high performance liquid chromatography-high resolution-quadrupole-orbitrap-mass spectrometry (UHPLC-HR-Q-Orbitrap-MS)-based workflow that enables widely targeted and untargeted metabolome and lipidome analysis. A total of 836 in-house standards were analyzed, of which 360 metabolites and 132 lipids were consequently detected in feces. Their targeted profiling was validated successfully with respect to repeatability (78% CV < 20%), reproducibility (82% CV < 20%), and linearity (81% R2 > 0.9), while also enabling holistic untargeted fingerprinting (15,319 features, CV < 30%). To automate targeted processing, we optimized an R-based targeted peak extraction (TaPEx) algorithm relying on a database comprising retention time and mass-to-charge ratio (360 metabolites and 132 lipids), with batch-specific quality control curation. The latter was benchmarked toward vendor-specific targeted and untargeted software and our isotopologue parameter optimization/XCMS-based untargeted pipeline in LifeLines Deep cohort samples (n = 97). TaPEx clearly outperformed the untargeted approaches (81.3 vs 56.7-66.0% compounds detected). Finally, our novel dual fecal metabolomics-lipidomics-TaPEx method was successfully applied to Flemish Gut Flora Project cohort (n = 292) samples, leading to a sample-to-result time reduction of 60%.PMID:37220321 | DOI:10.1021/acs.analchem.2c05371

J Clin Endocrinol Metab. 2023 May 23:dgad288. doi: 10.1210/clinem/dgad288. Online ahead of print.ABSTRACTAIMS: To examine whether nonobese (BMI<30 kg/m2) and obese (BMI≥30 kg/m2) women with gestational diabetes mellitus (GDM) and obese non-GDM women differ in metabolomic profiles from nonobese non-GDM controls.METHODS: Levels of 66 metabolic measures were assessed in early (median 13, IQR 12.4-13.7 gestation weeks), and across early, mid (20, 19.3-23.0) and late (28, 27.0-35.0) -pregnancy blood samples in 755 pregnant women of the PREDO and RADIEL studies. The independent replication cohort comprised 490 pregnant women.RESULTS: Nonobese and obese GDM, and obese non-GDM women differed similarly from the controls across early, mid, and late pregnancy in 13 measures, including VLDL-related measures, and fatty acids. In 6 measures, including fatty acid ratios, glycolysis-related measures, valine and 3-hydroxybutyrate, the differences between obese GDM women and controls were more pronounced than the differences between nonobese GDM or obese non-GDM women and controls. In 16 measures, including HDL-related measures, fatty acid ratios, amino acids and inflammation, differences between obese GDM or obese non-GDM women and controls were more pronounced than the differences between nonobese GDM women and controls. Most differences were evident in early pregnancy, and in the replication cohort were more often in the same direction than would be expected by chance alone.CONCLUSIONS: Differences between nonobese and obese GDM, or obese non-GDM women and controls in metabolomic profiles may allow detection of high-risk women for timely targeted preventive interventions.PMID:37220084 | DOI:10.1210/clinem/dgad288

J Proteome Res. 2023 May 23. doi: 10.1021/acs.jproteome.3c00226. Online ahead of print.ABSTRACTOvarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It may present little or no symptoms at the early stages and typically unspecific symptoms at later stages. High-grade serous ovarian cancer (HGSC) is the subtype responsible for most ovarian cancer deaths. However, very little is known about the metabolic course of this disease, particularly in its early stages. In this longitudinal study, we examined the temporal course of serum lipidome changes using a robust HGSC mouse model and machine learning data analysis. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages featured more diverse lipid alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations underscored unique perturbations in cell membrane stability, proliferation, and survival during cancer development and progression, offering potential targets for early detection and prognosis of human ovarian cancer.PMID:37220064 | DOI:10.1021/acs.jproteome.3c00226

Ther Hypothermia Temp Manag. 2023 May 23. doi: 10.1089/ther.2022.0065. Online ahead of print.ABSTRACTTargeted temperature management (TTM) may moderate the injury from out-of-hospital cardiac arrest. Slowing the metabolism has been a suggested effect. Nevertheless, studies have found higher lactate levels in patients cooled to 33°C compared with 36°C even days from TTM cessation. Larger studies have not been performed on the TTM's effect on the metabolome. Accordingly, to explore the effect of TTM, we used ultra-performance liquid-mass spectrometry in a substudy of 146 patients randomized in the TTM trial to either 33°C or 36°C for 24 hours and quantified 60 circulating metabolites at the time of hospital arrival (T0) and 48 hours later (T48). From T0 to T48, profound changes to the metabolome were observed: tricarboxylic acid (TCA) cycle metabolites, amino acids, uric acid, and carnitine species all decreased. TTM significantly modified these changes in nine metabolites (Benjamini-Hochberg corrected false discovery rate <0.05): branched amino acids valine and leucine levels dropped more in the 33°C arm (change [95% confidence interval]: -60.9 μM [-70.8 to -50.9] vs. -36.0 μM [-45.8 to -26.3] and -35.5 μM [-43.1 to -27.8] vs. -21.2 μM [-28.7 to -13.6], respectively), whereas the TCA metabolites including malic acid and 2-oxoglutaric acid remained higher for the first 48 hours (-7.7 μM [-9.7 to -5.7] vs. -10.4 μM [-12.4 to -8.4] and -3 μM [-4.3 to -1.7] vs. -3.7 μM [-5 to -2.3]). Prostaglandin E2 only dropped in the TTM 36°C group. The results show that TTM affects the metabolism hours after normothermia have been reached. Clinical Trial Number: NCT01020916.PMID:37219970 | DOI:10.1089/ther.2022.0065

Arthritis Rheumatol. 2023 May 23. doi: 10.1002/art.42616. Online ahead of print.ABSTRACTOBJECTIVE: We aimed to decipher the gut microbiome (GM) and serum metabolic characteristic of individuals at high risk for rheumatoid arthritis (RA) and to investigate the causative effect of GM on the mucosal immune system and its involvement in the pathogenesis of arthritis.DESIGN: Fecal samples were collected from 38 healthy individuals (HCs) and 53 high-risk RA individuals with anti-citrullinated protein antibody (ACPA)-positivity (PreRA), 12 of 53 PreRA developed RA within 5 years of follow-up. The differences in intestinal microbial composition between the HC and PreRA individuals or among PreRA subgroups were identified by 16S rRNA sequencing. The serum metabolite profile and its correlation with GM were also explored. Moreover, antibiotic-pretreated mice received GM from the HC or PreRA groups were then evaluated for intestinal permeability, inflammatory cytokines and immune cell populations. Collagen-induced arthritis (CIA) was also applied to test the effect of fecal microbiota transplantation (FMT) from PreRA individuals on arthritis severity in mice.RESULTS: Stool microbial diversity was lower in PreRA individuals than in HCs. The bacterial community structure and function significantly differed between HC and PreRA individuals. Although there were to some extent differences in the bacterial abundance among the PreRA subgroups, no robust functional differences were observed. The metabolites in the serum of the PreRA group were dramatically different from those in the HC group, with KEGG pathway enrichment of amino acid and lipid metabolism. Moreover, intestinal bacteria from the PreRA group increased intestinal permeability in FMT mice and ZO-1 expression in the small intestine and Caco-2 cells. Moreover, Th17 cells in the mesenteric lymph nodes and Peyer's patches were also increased in mice receiving PreRA feces compared to HC. The changes in intestinal permeability and Th17-cell activation prior to arthritis induction enhanced CIA severity in PreRA-FMT mice compared with HC-FMT mice.CONCLUSION: Gut microbial dysbiosis and metabolome alterations already occur in individuals at high risk for RA. FMT from preclinical individuals triggers intestinal barrier dysfunction and changes mucosal immunity, further contributing to arthritis development.PMID:37219936 | DOI:10.1002/art.42616

Appl Microbiol Biotechnol. 2023 May 23. doi: 10.1007/s00253-023-12595-0. Online ahead of print.ABSTRACTCaseous lymphadenitis (CLA), an infectious disease caused by Corynebacterium pseudotuberculosis in small ruminants, is highly prevalent worldwide. Economic losses have already been associated with the disease, and little is known about the host-pathogen relationship associated with the disease. The present study aimed to perform a metabolomic study of the C. pseudotuberculosis infection in goats. Serum samples were collected from a herd of 173 goats. The animals were classified as controls (not infected), asymptomatic (seropositives but without detectable CLA clinical signs), and symptomatic (seropositive animals presenting CLA lesions), according to microbiological isolation and immunodiagnosis. The serum samples were analyzed using nuclear magnetic resonance (1H-NMR), nuclear Overhauser effect spectroscopy (NOESY), and Carr-Purcell-Meiboom-Gill (CPMG) sequences. The NMR data were analyzed using chemometrics, and principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) were performed to discover specific biomarkers responsible for discrimination between the groups. A high dissemination of the infection by C. pseudotuberculosis was observed, being 74.57% asymptomatic and 11.56% symptomatic. In the evaluation of 62 serum samples by NMR, the techniques were satisfactory in the discrimination of the groups, being also complementary and mutually confirming, demonstrating possible biomarkers for the infection by the bacterium. Twenty metabolites of interest were identified by NOESY and 29 by CPMG, such as tryptophan, polyunsaturated fatty acids, formic acid, NAD+, and 3-hydroxybutyrate, opening promising possibilities for the use of these results in new therapeutic, immunodiagnosis, and immunoprophylactic tools, as well as for studies of the immune response against C. pseudotuberculosis. KEY POINTS: • Sixty-two samples from healthy, CLA asymptomatic, and symptomatic goats were screened • Twenty metabolites of interest were identified by NOESY and 29 by CPMG • 1H-NMR NOESY and CPMG were complementary and mutually confirming.PMID:37219572 | DOI:10.1007/s00253-023-12595-0

Anal Chem. 2023 May 23. doi: 10.1021/acs.analchem.3c00222. Online ahead of print.ABSTRACTAfter decades of research, gene therapy products have reached market maturity in recent years. Recombinant adeno-associated viruses (rAAVs) are one of the most promising gene delivery vehicles and are currently under intense scientific investigation. These next-generation medicines remain very challenging when it comes to designing appropriate analytical techniques for quality control. One critical quality attribute is the integrity of ssDNA incorporated in these vectors. The genome is the active compound driving rAAV therapy and therefore requires proper assessment and quality control. Current techniques for rAAV genome characterization include next-generation sequencing, quantitative polymerase chain reaction, analytical ultracentrifugation (AUC), and capillary gel electrophoresis (CGE), yet each of them presents their limitations or lack of user-friendliness. In this work, we demonstrate for the first time the potential of ion pairing-reverse phase-liquid chromatography (IP-RP-LC) to characterize the integrity of rAAV genomes. The obtained results were supported by two orthogonal techniques, AUC and CGE. IP-RP-LC can be performed above DNA melting temperatures, avoiding the detection of secondary DNA isoforms, and does not require the use of dyes due to UV detection. We demonstrate that this technique is suitable for batch comparability, different rAAV serotypes (AAV2 and AAV8), internal vs external (inside vs outside the capsid) DNA analysis, and contaminated samples. Overall, it is exceptionally user-friendly, needs limited sample preparation, has high reproducibility, and permits fractionation for further peak characterization. All of these factors add significant value of IP-RP-LC to the analytical toolbox of rAAV genome assessment.PMID:37219094 | DOI:10.1021/acs.analchem.3c00222

Proteomes. 2023 May 3;11(2):17. doi: 10.3390/proteomes11020017.ABSTRACTBreast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.PMID:37218922 | DOI:10.3390/proteomes11020017