Systemic Lactate Acts as a Metabolic Buffer in Humans and Prevents Nutrient Overflow in the Postprandial Phase.

On an organismal level, metabolism needs to react in a well-orchestrated manner to metabolic challenges such as nutrient uptake. Key metabolic hubs in human blood are pyruvate and lactate, both of which are constantly interconverted by very fast exchange fluxes. The quantitative contribution of different food sources to these metabolite pools remains unclear. Here, we applied in vivo stable isotope labeling to determine postprandial metabolic fluxes in response to two carbohydrate sources of different complexity. Depending on the ingested carbohydrate source, glucose or wheat flour, the net direction of the lactate dehydrogenase, and the alanine amino transferase fluxes were adjusted in a way to ensure sufficient availability, while, at the same time, preventing an overflow in the respective metabolite pools. The systemic lactate pool acts as a metabolic buffer which is fueled in the early- and depleted in the late-postprandial phase and thus plays a key role for systemic metabolic homeostasis.

PRODORIC: state-of-the-art database of prokaryotic gene regulation.

PRODORIC is worldwide one of the largest collections of prokaryotic transcription factor binding sites from multiple bacterial sources with corresponding interpretation and visualization tools. With the introduction of PRODORIC2 in 2017, the transition to a modern web interface and maintainable backend was started. With this latest PRODORIC release the database backend is now fully API-based and provides programmatical access to the complete PRODORIC data. The visualization tools Genome Browser and ProdoNet from the original PRODORIC have been reintroduced and were integrated into the PRODORIC website. Missing input and output options from the original Virtual Footprint were added again for position weight matrix pattern-based searches. The whole PRODORIC dataset was reannotated. Every transcription factor binding site was re-evaluated to increase the overall database quality. During this process, additional parameters, like bound effectors, regulation type and different types of experimental evidence have been added for every transcription factor. Additionally, 109 new transcription factors and 6 new organisms have been added. PRODORIC is publicly available at https://www.prodoric.de.

MIAMI--a tool for non-targeted detection of metabolic flux changes for mode of action identification.

SUMMARY: Mass isotopolome analysis for mode of action identification (MIAMI) combines the strengths of targeted and non-targeted approaches to detect metabolic flux changes in gas chromatography/mass spectrometry datasets. Based on stable isotope labeling experiments, MIAMI determines a mass isotopomer distribution-based (MID) similarity network and incorporates the data into metabolic reference networks. By identifying MID variations of all labeled compounds between different conditions, targets of metabolic changes can be detected. AVAILABILITY AND IMPLEMENTATION: We implemented the data processing in C++17 with Qt5 back-end using MetaboliteDetector and NTFD libraries. The data visualization is implemented as web application. Executable binaries and visualization are freely available for Linux operating systems, the source code is licensed under General Public License version 3.

Non-Targeted Mass Isotopolome Analysis Using Stable Isotope Patterns to Identify Metabolic Changes.

Gas chromatography coupled with mass spectrometry can provide an extensive overview of the metabolic state of a biological system. Analysis of raw mass spectrometry data requires powerful data processing software to generate interpretable results. Here we describe a data processing workflow to generate metabolite levels, mass isotopomer distribution, similarity and variability analysis of metabolites in a nontargeted manner, using stable isotope labeling. Using our data analysis software, no bioinformatic or programming background is needed to generate results from raw mass spectrometry data.

Postprandial Metabolic Effects of Fiber Mixes Revealed by in vivo Stable Isotope Labeling in Humans.

Food supplementation with a fiber mix of guar gum and chickpea flour represents a promising approach to reduce the risk of type 2 diabetes mellitus (T2DM) by attenuating postprandial glycemia. To investigate the effects on postprandial metabolic fluxes of glucose-derived metabolites in response to this fiber mix, a randomized, cross-over study was designed. Twelve healthy, male subjects consumed three different flatbreads either supplemented with 2% guar gum or 4% guar gum and 15% chickpea flour or without supplementation (control). The flatbreads were enriched with ~2% of 13C-labeled wheat flour. Blood was collected at 16 intervals over a period of 360 min after bread intake and plasma samples were analyzed by GC-MS based metabolite profiling combined with stable isotope-assisted metabolomics. Although metabolite levels of the downstream metabolites of glucose, specifically lactate and alanine, were not altered in response to the fiber mix, supplementation of 4% guar gum was shown to significantly delay and reduce the exogenous formation of these metabolites. Metabolic modeling and computation of appearance rates revealed that the effects induced by the fiber mix were strongest for glucose and attenuated downstream of glucose. Further investigations to explore the potential of fiber mix supplementation to counteract the development of metabolic diseases are warranted.

PRODORIC2: the bacterial gene regulation database in 2018.

Bacteria adapt to changes in their environment via differential gene expression mediated by DNA binding transcriptional regulators. The PRODORIC2 database hosts one of the largest collections of DNA binding sites for prokaryotic transcription factors. It is the result of the thoroughly redesigned PRODORIC database. PRODORIC2 is more intuitive and user-friendly. Besides significant technical improvements, the new update offers more than 1000 new transcription factor binding sites and 110 new position weight matrices for genome-wide pattern searches with the Virtual Footprint tool. Moreover, binding sites deduced from high-throughput experiments were included. Data for 6 new bacterial species including bacteria of the Rhodobacteraceae family were added. Finally, a comprehensive collection of sigma- and transcription factor data for the nosocomial pathogen Clostridium difficile is now part of the database. PRODORIC2 is publicly available at http://www.prodoric2.de.

BrEPS 2.0: Optimization of sequence pattern prediction for enzyme annotation.

The prediction of gene functions is crucial for a large number of different life science areas. Faster high throughput sequencing techniques generate more and larger datasets. The manual annotation by classical wet-lab experiments is not suitable for these large amounts of data. We showed earlier that the automatic sequence pattern-based BrEPS protocol, based on manually curated sequences, can be used for the prediction of enzymatic functions of genes. The growing sequence databases provide the opportunity for more reliable patterns, but are also a challenge for the implementation of automatic protocols. We reimplemented and optimized the BrEPS pattern generation to be applicable for larger datasets in an acceptable timescale. Primary improvement of the new BrEPS protocol is the enhanced data selection step. Manually curated annotations from Swiss-Prot are used as reliable source for function prediction of enzymes observed on protein level. The pool of sequences is extended by highly similar sequences from TrEMBL and SwissProt. This allows us to restrict the selection of Swiss-Prot entries, without losing the diversity of sequences needed to generate significant patterns. Additionally, a supporting pattern type was introduced by extending the patterns at semi-conserved positions with highly similar amino acids. Extended patterns have an increased complexity, increasing the chance to match more sequences, without losing the essential structural information of the pattern. To enhance the usability of the database, we introduced enzyme function prediction based on consensus EC numbers and IUBMB enzyme nomenclature. BrEPS is part of the Braunschweig Enzyme Database (BRENDA) and is available on a completely redesigned website and as download. The database can be downloaded and used with the BrEPScmd command line tool for large scale sequence analysis. The BrEPS website and downloads for the database creation tool, command line tool and database are freely accessible at http://breps.tu-bs.de.

The molybdenum cofactor biosynthesis complex interacts with actin filaments via molybdenum insertase Cnx1 as anchor protein in Arabidopsis thaliana.

The pterin based molybdenum cofactor (Moco) plays an essential role in almost all organisms. Its biosynthesis is catalysed by six enzymes in a conserved four step reaction pathway. The last three steps are located in the cytoplasm, where a multimeric protein complex is formed to protect the intermediates from degradation. Bimolecular fluorescence complementation was used to test for cytoskeleton association of the Moco biosynthesis enzymes with actin filaments and microtubules using known cytoskeleton associated proteins, thus permitting non-invasive in vivo studies. Coding sequences of binding proteins were cloned via the GATEWAY system. No Moco biosynthesis enzyme showed any interaction with microtubules. However, alone the two domain protein Cnx1 exhibited interaction with actin filaments mediated by both domains with the Cnx1G domain displaying a stronger interaction. Cnx6 showed actin association only if unlabelled Cnx1 was co-expressed in comparable amounts. So Cnx1 is likely to be the anchor protein for the whole biosynthesis complex on actin filaments. A stabilization of the whole Moco biosynthesis complex on the cytoskeleton might be crucial. In addition a micro-compartmentation might either allow a localisation near the mitochondrial ATM3 exporter providing the first Moco intermediate or near one of the three molybdate transporters enabling efficient molybdate incorporation.