Inflammation occurs as an immediate protective response of the immune system to a harmful stimulus, whether locally confined or systemic. In contrast, a persisting, i.e., chronic, inflammatory state, ...even at a low-grade, is a well-known risk factor in the development of common diseases like diabetes or atherosclerosis. In clinical practice, laboratory markers like high-sensitivity C-reactive protein (hsCRP), white blood cell count (WBC), and fibrinogen, are used to reveal inflammatory processes. In order to gain a deeper insight regarding inflammation-related changes in metabolism, the present study assessed the metabolic patterns associated with alterations in inflammatory markers.
Based on mass spectrometry and nuclear magnetic resonance spectroscopy we determined a comprehensive panel of 613 plasma and 587 urine metabolites among 925 apparently healthy individuals. Associations between inflammatory markers, namely hsCRP, WBC, and fibrinogen, and metabolite levels were tested by linear regression analyses controlling for common confounders. Additionally, we tested for a discriminative signature of an advanced inflammatory state using random forest analysis.
HsCRP, WBC, and fibrinogen were significantly associated with 71, 20, and 19 plasma and 22, 3, and 16 urine metabolites, respectively. Identified metabolites were related to the bradykinin system, involved in oxidative stress (e.g., glutamine or pipecolate) or linked to the urea cycle (e.g., ornithine or citrulline). In particular, urine 3'-sialyllactose was found as a novel metabolite related to inflammation. Prediction of an advanced inflammatory state based solely on 10 metabolites was well feasible (median AUC: 0.83).
Comprehensive metabolic profiling confirmed the far-reaching impact of inflammatory processes on human metabolism. The identified metabolites included not only those already described as immune-modulatory but also completely novel patterns. Moreover, the observed alterations provide molecular links to inflammation-associated diseases like diabetes or cardiovascular disorders.
Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which ...contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways.
We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed.
We identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism.
Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.
Abstract
Comparative analyses determined the relationship between the structure of bisphenol A (BPA) as well as of seven bisphenol analogues (bisphenol B (BPB), bisphenol C (BPC), bisphenol E (BPE), ...bisphenol F (BPF), bisphenol Z (BPZ), bisphenol AP (BPAP), bisphenol PH (BPPH)) and their biotransformability by the biphenyl-degrading bacterium
Cupriavidus basilensis
SBUG 290
.
All bisphenols were substrates for bacterial transformation with conversion rates ranging from 6 to 98% within 216 h and 36 different metabolites were characterized. Transformation by biphenyl-grown cells comprised four different pathways: (a) formation of
ortho-
hydroxylated bisphenols, hydroxylating either one or both phenols of the compounds; (b) ring fission; (c) transamination followed by acetylation or dimerization; and (d) oxidation of ring substituents, such as methyl groups and aromatic ring systems, present on the 3-position. However, the microbial attack of bisphenols by
C. basilensis
was limited to the phenol rings and its substituents, while substituents on the carbon bridge connecting the rings were not oxidized. All bisphenol analogues with modifications at the carbon bridge could be oxidized up to ring cleavage, while substituents at the 3-position of the phenol ring other than hydroxyl groups did not allow this reaction. Replacing one methyl group at the carbon bridge of BPA by a hydrophobic aromatic or alicyclic ring system inhibited both dimerization and transamination followed by acetylation. While most of the bisphenol analogues exhibited estrogenic activity, four biotransformation products tested were not estrogenically active.
In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine ...metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. Notably, AD individuals displayed diminished formate microbial secretion in these models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.
Comparative analyses determined the relationship between the structure of bisphenol A (BPA) as well as of seven bisphenol analogues (bisphenol B (BPB), bisphenol C (BPC), bisphenol E (BPE), bisphenol ...F (BPF), bisphenol Z (BPZ), bisphenol AP (BPAP), bisphenol PH (BPPH)) and their biotransformability by the biphenyl-degrading bacterium
Cupriavidus basilensis
SBUG 290
.
All bisphenols were substrates for bacterial transformation with conversion rates ranging from 6 to 98% within 216 h and 36 different metabolites were characterized. Transformation by biphenyl-grown cells comprised four different pathways: (a) formation of
ortho-
hydroxylated bisphenols, hydroxylating either one or both phenols of the compounds; (b) ring fission; (c) transamination followed by acetylation or dimerization; and (d) oxidation of ring substituents, such as methyl groups and aromatic ring systems, present on the 3-position. However, the microbial attack of bisphenols by
C. basilensis
was limited to the phenol rings and its substituents, while substituents on the carbon bridge connecting the rings were not oxidized. All bisphenol analogues with modifications at the carbon bridge could be oxidized up to ring cleavage, while substituents at the 3-position of the phenol ring other than hydroxyl groups did not allow this reaction. Replacing one methyl group at the carbon bridge of BPA by a hydrophobic aromatic or alicyclic ring system inhibited both dimerization and transamination followed by acetylation. While most of the bisphenol analogues exhibited estrogenic activity, four biotransformation products tested were not estrogenically active.
Serum proteome analysis is severely hampered by the extreme dynamic range of protein concentrations, but tools for the specific depletion of highly abundant serum proteins lack for most farm and ...companion animals. A well‐established alternative strategy to reduce the dynamic range of plasma protein concentrations, treatment with combinatorial peptide ligand libraries (CPLL), is generally applicable but requires large amounts of sample. Therefore, additional depletion/enrichment protocols for plasma and serum samples from animals are desirable. In this respect, we have tested a protein precipitate that formed after withdrawal of salt from human, bovine, or porcine serum at pH 4.2. The bovine sample was composed of over 300 proteins making it a potential source for biomarker discovery. Precipitation was highly reproducible and the concentrations of albumin and other highly abundant serum proteins were strongly reduced. In comparison to the CPLL treatment, precipitation did not introduce any selection bias based on hydrophathy or pI. However, the composition of both preparations was partially complementary. Salt withdrawal at pH 4.2 is suggested as additional depletion/enrichment strategy for serum samples. Also, we point out that the removal of precipitates from serum samples under the described conditions bears the risk of losing a valuable protein fraction.
White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. ...There are no large-scale studies testing associations between WMH and circulating metabolites.
We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted
values (
)<0.05 were considered significant.
In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH (
<0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men (
=1.40×10
) and in both the pooled sample (
=1.66×10
) and statin-untreated (
=1.65×10
) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate (
=0.047).
Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.
Exaggerated hepatic triglyceride accumulation (i.e., hepatic steatosis) represents a strong risk factor for type 2 diabetes mellitus and cardiovascular disease. Despite the clear association of ...hepatic steatosis with impaired insulin signaling, the precise molecular mechanisms involved are still under debate. We combined data from several metabolomics techniques to gain a comprehensive picture of molecular alterations related to the presence of hepatic steatosis in a diabetes-free sample (N = 769) of the population-based Study of Health in Pomerania.
Liver fat content (LFC) was assessed using MRI. Metabolome measurements of plasma and urine samples were done by mass spectrometry and nuclear magnetic resonance spectroscopy. Linear regression analyses were used to detect significant associations with either LFC or markers of hepatic damage. Possible mediations through insulin resistance, hypertriglyceridemia, and inflammation were tested. A predictive molecular signature of hepatic steatosis was established using regularized logistic regression.
The LFC-associated atherogenic lipid profile, tightly connected to shifts in the phospholipid content, and a prediabetic amino acid cluster were mediated by insulin resistance. Molecular surrogates of oxidative stress and multiple associations with urine metabolites (e.g., indicating altered cortisol metabolism or phase II detoxification products) were unaffected in mediation analyses. Incorporation of urine metabolites slightly improved classification of hepatic steatosis.
Comprehensive metabolic profiling allowed us to reveal molecular patterns accompanying hepatic steatosis independent of the known hallmarks. Novel biomarkers from urine (e.g., cortisol glucuronide) are worthwhile for follow-up in patients suffering from more severe liver impairment compared with our merely healthy population-based sample.
Membrane envelopment and budding of negative strand RNA viruses (NSVs) is mainly driven by viral matrix proteins (M). In addition, several M proteins are also known to be involved in host cell ...manipulation. Knowledge about the cellular targets and detailed molecular mechanisms, however, is poor for many M proteins. For instance, Nipah Virus (NiV) M protein trafficking through the nucleus is essential for virus release, but nuclear targets of NiV M remain unknown. To identify cellular interactors of henipavirus M proteins, tagged Hendra Virus (HeV) M proteins were expressed and M-containing protein complexes were isolated and analysed. Presence of acidic leucine-rich nuclear phosphoprotein 32 family member B (ANP32B) in the complex suggested that this protein represents a direct or indirect interactor of the viral matrix protein. Over-expression of ANP32B led to specific nuclear accumulation of HeV M, providing a functional link between ANP32B and M protein. ANP32B-dependent nuclear accumulation was observed after plasmid-driven expression of HeV and NiV matrix proteins and also in NiV infected cells. The latter indicated that an interaction of henipavirus M protein with ANP32B also occurs in the context of virus replication. From these data we conclude that ANP32B is a nuclear target of henipavirus M that may contribute to virus replication. Potential effects of ANP32B on HeV nuclear shuttling and host cell manipulation by HeV M affecting ANP32B functions in host cell survival and gene expression regulation are discussed.
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