Environmental factors driving the development of type 1 diabetes (T1D) are still largely unknown. Both animal and human studies have shown an association between altered fecal microbiota composition, ...impaired production of short-chain fatty acids (SCFA) and T1D onset. However, observational evidence on SCFA and fecal and oral microbiota in adults with longstanding T1D vs healthy controls (HC) is lacking.
We included 53 T1D patients without complications or medication and 50 HC matched for age, sex and BMI. Oral and fecal microbiota, fecal and plasma SCFA levels, markers of intestinal inflammation (fecal IgA and calprotectin) and markers of low-grade systemic inflammation were measured.
Oral microbiota were markedly different in T1D (eg abundance of Streptococci) compared to HC. Fecal analysis showed decreased butyrate producing species in T1D and less butyryl-CoA transferase genes. Also, plasma levels of acetate and propionate were lower in T1D, with similar fecal SCFA. Finally, fecal strains Christensenella and Subdoligranulum correlated with glycemic control, inflammatory parameters and SCFA.
We conclude that T1D patients harbor a different amount of intestinal SCFA (butyrate) producers and different plasma acetate and propionate levels. Future research should disentangle cause and effect and whether supplementation of SCFA-producing bacteria or SCFA alone can have disease-modifying effects in T1D.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Introduction
Batch effects in large untargeted metabolomics experiments are almost unavoidable, especially when sensitive detection techniques like mass spectrometry (MS) are employed. In order to ...obtain peak intensities that are comparable across all batches, corrections need to be performed. Since non-detects, i.e., signals with an intensity too low to be detected with certainty, are common in metabolomics studies, the batch correction methods need to take these into account.
Objectives
This paper aims to compare several batch correction methods, and investigates the effect of different strategies for handling non-detects.
Methods
Batch correction methods usually consist of regression models, possibly also accounting for trends within batches. To fit these models quality control samples (QCs), injected at regular intervals, can be used. Also study samples can be used, provided that the injection order is properly randomized. Normalization methods, not using information on batch labels or injection order, can correct for batch effects as well. Introducing two easy-to-use quality criteria, we assess the merits of these batch correction strategies using three large LC–MS and GC–MS data sets of samples from
Arabidopsis thaliana
.
Results
The three data sets have very different characteristics, leading to clearly distinct behaviour of the batch correction strategies studied. Explicit inclusion of information on batch and injection order in general leads to very good corrections; when enough QCs are available, also general normalization approaches perform well. Several approaches are shown to be able to handle non-detects—replacing them with very small numbers such as zero seems the worst of the approaches considered.
Conclusion
The use of quality control samples for batch correction leads to good results when enough QCs are available. If an experiment is properly set up, batch correction using the study samples usually leads to a similar high-quality correction, but has the advantage that more metabolites are corrected. The strategy for handling non-detects is important: choosing small values like zero can lead to suboptimal batch corrections.
Alterations in intestinal microbiota are associated with obesity and insulin resistance. We studied the effects of infusing intestinal microbiota from lean donors to male recipients with metabolic ...syndrome on the recipients' microbiota composition and glucose metabolism. Subjects were assigned randomly to groups that were given small intestinal infusions of allogenic or autologous microbiota. Six weeks after infusion of microbiota from lean donors, insulin sensitivity of recipients increased (median rate of glucose disappearance changed from 26.2 to 45.3 μmol/kg/min; P < .05) along with levels of butyrate-producing intestinal microbiota. Intestinal microbiota might be developed as therapeutic agents to increase insulin sensitivity in humans; www.trialregister.nl ; registered at the Dutch Trial Register (NTR1776).
Untargeted metabolomics aims to gather information on as many metabolites as possible in biological systems by taking into account all information present in the data sets. Here we describe a ...detailed protocol for large-scale untargeted metabolomics of plant tissues, based on reversed phase liquid chromatography coupled to high-resolution mass spectrometry (LC-QTOF MS) of aqueous methanol extracts. Dedicated software, MetAlign, is used for automated baseline correction and alignment of all extracted mass peaks across all samples, producing detailed information on the relative abundance of thousands of mass signals representing hundreds of metabolites. Subsequent statistics and bioinformatics tools can be used to provide a detailed view on the differences and similarities between (groups of) samples or to link metabolomics data to other systems biology information, genetic markers and/or specific quality parameters. The complete procedure from metabolite extraction to assembly of a data matrix with aligned mass signal intensities takes about 6 days for 50 samples.
Blood-brain barrier (BBB) dysfunction is a major hallmark of many neurological diseases, including multiple sclerosis (MS). Using a genomics approach, we defined a microRNA signature that is ...diminished at the BBB of MS patients. In particular, miR-125a-5p is a key regulator of brain endothelial tightness and immune cell efflux. Our findings suggest that repair of a disturbed BBB through microRNAs may represent a novel avenue for effective treatment of MS.
M2 macrophages suppress inflammation in numerous disorders, including tumour formation, infection and obesity. However, the exact role of M2 macrophages in the context of several other diseases is ...still largely undefined. We here show that human M2 macrophages promote inflammation instead of suppressing inflammation on simultaneous exposure to complexed IgG (c-IgG) and TLR ligands, as occurs in the context of diseases such as rheumatoid arthritis (RA). c-IgG-TLR ligand co-stimulation of M2 macrophages selectively amplifies production of pro-inflammatory cytokines TNF-α, IL-1β and IL-6 and promotes Th17 responses, which all play a critical role in RA pathology. Induction of pro-inflammatory cytokines on c-IgG co-stimulation mainly depends on Fc gamma receptor IIa (FcγRIIa), which selectively amplifies cytokine gene transcription and induces caspase-1 activation. These data indicate that FcγR-TLR cross-talk may be targeted for treatment to attenuate inflammation in RA, by restoring the anti-inflammatory function of M2 macrophages.
We profiled 162 lines of Arabidopsis for variation in transcript, protein and metabolite abundance using mRNA microarrays, two-dimensional polyacrylamide gel electrophoresis, gas chromatography ...time-of-flight mass spectrometry, liquid chromatography quadrupole time-of-flight mass spectrometry, and proton nuclear magnetic resonance. We added all publicly available phenotypic data from the same lines and mapped quantitative trait loci (QTL) for 40,580 molecular and 139 phenotypic traits. We found six QTL hot spots with major, system-wide effects, suggesting there are six breakpoints in a system otherwise buffered against many of the 500,000 SNPs.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Identifying the sources of natural variation underlying metabolic differences between plants will enable a better understanding of plant metabolism and provide insights into the regulatory networks ...that govern plant growth and morphology. So far, however, the contribution of epigenetic variation to metabolic diversity has been largely ignored. In the present study, we utilized a panel of
epigenetic recombinant inbred lines (epiRILs) to assess the impact of epigenetic variation on the metabolic composition. Thirty epigenetic QTL (QTL
) were detected, which partly overlap with QTL
linked to growth and morphology. In an effort to identify causal candidate genes in the QTL
regions and their putative
-targets, we performed in silico small RNA and qPCR analyses. Differentially expressed genes were further studied by phenotypic and metabolic analyses of knockout mutants. Three genes were detected that recapitulated the detected QTL
effects, providing evidence for epigenetic regulation in
and in
These results indicate that epigenetic mechanisms impact metabolic diversity, possibly via small RNAs, and thus aid in further disentangling the complex epigenotype-phenotype map.
The genetics of plant metabolism Hall, Robert D; Keurentjes, Joost J B; de Vos, C H Ric ...
Nature genetics,
07/2006, Letnik:
38, Številka:
7
Journal Article
Recenzirano
Odprti dostop
Variation for metabolite composition and content is often observed in plants. However, it is poorly understood to what extent this variation has a genetic basis. Here, we describe the genetic ...analysis of natural variation in the metabolite composition in Arabidopsis thaliana. Instead of focusing on specific metabolites, we have applied empirical untargeted metabolomics using liquid chromatography-time of flight mass spectrometry (LC-QTOF MS). This uncovered many qualitative and quantitative differences in metabolite accumulation between A. thaliana accessions. Only 13.4% of the mass peaks were detected in all 14 accessions analyzed. Quantitative trait locus (QTL) analysis of more than 2,000 mass peaks, detected in a recombinant inbred line (RIL) population derived from the two most divergent accessions, enabled the identification of QTLs for about 75% of the mass signals. More than one-third of the signals were not detected in either parent, indicating the large potential for modification of metabolic composition through classical breeding.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
MicroRNAs are negative regulators of gene expression that play a key role in cell‐type specific differentiation and modulation of cell function and have been proposed to be involved in ...neovascularization. Previously, using an extensive cloning and sequencing approach, we identified miR‐126 to be specifically and highly expressed in human endothelial cells (EC). Here, we demonstrate EC‐specific expression of miR‐126 in capillaries and the larger vessels in vivo. We therefore explored the potential role of miR‐126 in arteriogenesis and angiogenesis. Using miR‐reporter constructs, we show that miR‐126 is functionally active in EC in vitro and that it could be specifically repressed using antagomirs specifically targeting miR‐126. To study the consequences of miR‐126 silencing on vascular regeneration, mice were injected with a single dose of antagomir‐126 or a control ‘scramblemir’ and exposed to ischemia of the left hindlimb by ligation of the femoral artery. Although miR‐126 was effectively silenced in mice treated with a single, high dose (HD) of antagomir‐126, laser Doppler perfusion imaging did not show effects on blood flow recovery. In contrast, quantification of the capillary density in the gastrocnemius muscle revealed that mice treated with a HD of antagomir‐126 had a markedly reduced angiogenic response. Aortic explant cultures of the mice confirmed the role of miR‐126 in angiogenesis. Our data demonstrate a facilitary function for miR‐126 in ischemia‐induced angiogenesis and show the efficacy and specificity of antagomir‐induced silencing of EC‐specific microRNAs in vivo.
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