Re-routing of Sugar Catabolism Provides a Better Insight Into Fungal Flexibility in Using Plant Biomass-Derived Monomers as Substrates

The filamentous ascomycete Aspergillus niger has received increasing interest as a cell factory, being able to efficiently degrade plant cell wall polysaccharides as well as having an extensive metabolism to convert the released monosaccharides into value added compounds. The pentoses D-xylose and L-arabinose are the most abundant monosaccharides in plant biomass after the hexose D-glucose, being major constituents of xylan, pectin and xyloglucan. In this study, the influence of selected pentose catabolic pathway (PCP) deletion strains on growth on plant biomass and re-routing of sugar catabolism was addressed to gain a better understanding of the flexibility of this fungus in using plant biomass-derived monomers. The transcriptome, metabolome and proteome response of three PCP mutant strains, Delta larA Delta xyrA Delta xyrB, Delta ladA Delta xdhA Delta sdhA and Delta xkiA, grown on wheat bran (WB) and sugar beet pulp (SBP), was evaluated. Our results showed that despite the absolute impact of these PCP mutations on pure pentose sugars, they are not as critical for growth of A. niger on more complex biomass substrates, such as WB and SBP. However, significant phenotypic variation was observed between the two biomass substrates, but also between the different PCP mutants. This shows that the high sugar heterogeneity of these substrates in combination with the high complexity and adaptability of the fungal sugar metabolism allow for activation of alternative strategies to support growth.Peer reviewe

The Sugar Metabolic Model of Aspergillus niger Can Only Be Reliably Transferred to Fungi of Its Phylum

Fungi play a critical role in the global carbon cycle by degrading plant polysaccharides to small sugars and metabolizing them as carbon and energy sources. We mapped the well-established sugar metabolic network of Aspergillus niger to five taxonomically distant species (Aspergillus nidulans, Penicillium subrubescens, Trichoderma reesei, Phanerochaete chrysosporium and Dichomitus squalens) using an orthology-based approach. The diversity of sugar metabolism correlates well with the taxonomic distance of the fungi. The pathways are highly conserved between the three studied Eurotiomycetes (A. niger, A. nidulans, P. subrubescens). A higher level of diversity was observed between the T. reesei and A. niger, and even more so for the two Basidiomycetes. These results were confirmed by integrative analysis of transcriptome, proteome and metabolome, as well as growth profiles of the fungi growing on the corresponding sugars. In conclusion, the establishment of sugar pathway models in different fungi revealed the diversity of fungal sugar conversion and provided a valuable resource for the community, which would facilitate rational metabolic engineering of these fungi as microbial cell factories

Ambient mass spectrometry in metabolomics

Since the introduction of desorption electrospray ionization (DESI) mass spectrometry (MS), ambient MS methods have seen increased use in a variety of fields from health to food science. Increasing its popularity in metabolomics, ambient MS offers limited sample preparation, rapid and direct analysis of liquids, solids, and gases, in situ and in vivo analysis, and imaging. The metabolome consists of a constantly changing collection of small (<1.5 kDa) molecules. These include endogenous molecules that are part of primary metabolism pathways, secondary metabolites with specific functions such as signaling, chemicals incorporated in the diet or resulting from environmental exposures, and metabolites associated with the microbiome. Characterization of the responsive changes of this molecule cohort is the principal goal of any metabolomics study. With adjustments to experimental parameters, metabolites with a range of chemical and physical properties can be selectively desorbed and ionized and subsequently analyzed with increased speed and sensitivity. This review covers the broad applications of a variety of ambient MS techniques in four primary fields in which metabolomics is commonly employed.Fil: Clendinen, Chaevien S.. Georgia Institute of Techology; Estados UnidosFil: Monge, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias ; ArgentinaFil: Fernández, Facundo M.. Georgia Institute of Techology; Estados Unido

¹³C NMR Metabolomics: INADEQUATE Network Analysis

The many advantages of ¹³C NMR are often overshadowed by its intrinsically low sensitivity. Given that carbon makes up the backbone of most biologically relevant molecules, ¹³C NMR offers a straightforward measurement of these compounds. Two-dimensional ¹³C–¹³C correlation experiments like INADEQUATE (incredible natural abundance double quantum transfer experiment) are ideal for the structural elucidation of natural products and have great but untapped potential for metabolomics analysis. We demonstrate a new and semiautomated approach called INETA (INADEQUATE network analysis) for the untargeted analysis of INADEQUATE data sets using an <i>in silico</i> INADEQUATE database. We demonstrate this approach using isotopically labeled <i>Caenorhabditis elegans</i> mixtures

An Overview of Methods using 13C for Improved Compound Identification in Metabolomics and Natural Products

Compound identification is a major bottleneck in metabolomics studies. In nuclear magnetic resonance (NMR) investigations, resonance overlap often hinders unambiguous database matching or de novo compound identification. In liquid chromatography-mass spectrometry (LC-MS), discriminating between biological signals and background artifacts and reliable determination of molecular formulae are not always straightforward. We have designed and implemented several NMR and LC-MS approaches that utilize 13C, either enriched or at natural abundance, in metabolomics applications. For LC-MS applications, we describe a technique called isotopic ratio outlier analysis (IROA), which utilizes samples that are isotopically labeled with 5% (test) and 95% (control) 13C. This labeling strategy leads to characteristic isotopic patterns that allow the differentiation of biological signals from artifacts and yield the exact number of carbons, significantly reducing possible molecular formulae. The relative abundance between the test and control samples for every IROA feature can be determined simply by integrating the peaks that arise from the 5% and 95% channels. For NMR applications, we describe two 13C-based approaches. For samples at natural abundance, we have developed a workflow to obtain 13C-13C and 13C-1H statistical correlations using 1D 13C and 1H NMR spectra. For samples that can be isotopically labeled, we describe another NMR approach to obtain direct 13C-13C spectroscopic correlations. These methods both provide extensive information about the carbon framework of compounds in the mixture for either database matching or de novo compound identification. We also discuss strategies in which 13C NMR can be used to identify unknown compounds from IROA experiments. By combining technologies with the same samples, we can identify important biomarkers and corresponding metabolites of interest

Metabolomics and Natural-Products Strategies to Study Chemical Ecology in Nematodes

Synopsis This review provides an overview of two complementary approaches to identify biologically active compounds for studies in chemical ecology. The first is activity-guided fractionation and the second is metabolomics, particularly focusing on a new liquid chromatography-mass spectrometry-based method called isotopic ratio outlier analysis. To illustrate examples using these approaches, we review recent experiments using Caenorhabditis elegans and related freeliving nematodes

Preoperative Metabolic Signatures of Prostate Cancer Recurrence Following Radical Prostatectomy

Technological advances in mass spectrometry 14 (MS), liquid chromatography (LC) separations, nuclear 15 magnetic resonance (NMR) spectroscopy, and big data 16 analytics have made possible studying metabolism at an 17 “omics” or systems level. Here, we applied a multiplatform 18 (NMR + LC−MS) metabolomics approach to the study of 19 preoperative metabolic alterations associated with prostate 20 cancer recurrence. Thus far, predicting which patients will 21 recur even after radical prostatectomy has not been possible. 22 Correlation analysis on metabolite abundances detected on 23 serum samples collected prior to surgery from prostate cancer 24 patients (n = 40 remission vs n = 40 recurrence) showed 25 significant alterations in a number of pathways, including 26 amino acid metabolism, purine and pyrimidine synthesis, tricarboxylic acid cycle, tryptophan catabolism, glucose, and lactate. 27 Lipidomics experiments indicated higher lipid abundances on recurrent patients for a number of classes that included 28 triglycerides, lysophosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, diglycerides, acyl carnitines, and 29 ceramides. Machine learning approaches led to the selection of a 20-metabolite panel from a single preoperative blood sample 30 that enabled prediction of recurrence with 92.6% accuracy, 94.4% sensitivity, and 91.9% specificity under cross-validation 31 conditions.Fil: Clendinen, Chaevien S.. Georgia Institute of Techology; Estados UnidosFil: Gaul, David A.. Georgia Institute of Techology; Estados UnidosFil: Monge, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Arnold, Rebecca S.. University of Emory; Estados UnidosFil: Edison, Arthur Scott. University of Georgia; Estados UnidosFil: Petros, John A.. Atlanta Va Medical Center; Estados Unidos. University of Emory; Estados UnidosFil: Fernández, Facundo M.. Georgia Institute of Techology; Estados Unido

Light-Dependence of Formate (C1) and Acetate (C2) Transport and Oxidation in Poplar Trees.

Although apparent light inhibition of leaf day respiration is a widespread reported phenomenon, the mechanisms involved, including utilization of alternate respiratory pathways and substrates and light inhibition of TCA cycle enzymes are under active investigation. Recently, acetate fermentation was highlighted as a key drought survival strategy mediated through protein acetylation and jasmonate signaling. Here, we evaluate the light-dependence of acetate transport and assimilation in Populus trichocarpa trees using the dynamic xylem solution injection (DXSI) method developed here for continuous studies of C1 and C2 organic acid transport and light-dependent metabolism. Over 7 days, 1.0 L of [13C]formate and [13C2]acetate solutions were delivered to the stem base of 2-year old potted poplar trees, while continuous diurnal observations were made in the canopy of CO2, H2O, and isoprene gas exchange together with δ13CO2. Stem base injection of 10 mM [13C2]acetate induced an overall pattern of canopy branch headspace 13CO2 enrichment (δ13CO2 +27‱) with a diurnal structure in δ13CO2 reaching a mid-day minimum followed by a maximum shortly after darkening where δ13CO2 values rapidly increased up to +12‱. In contrast, 50 mM injections of [13C]formate were required to reach similar δ13CO2 enrichment levels in the canopy with δ13CO2 following diurnal patterns of transpiration. Illuminated leaves of detached poplar branches pretreated with 10 mM [13C2]acetate showed lower δ13CO2 (+20‱) compared to leaves treated with 10 mM [13C]formate (+320‱), the opposite pattern observed at the whole plant scale. Following dark/light cycles at the leaf-scale, rapid, strong, and reversible enhancements in headspace δ13CO2 by up to +60‱ were observed in [13C2]acetate-treated leaves which showed enhanced dihydrojasmonic acid and TCA cycle intermediate concentrations. The results are consistent with acetate in the transpiration stream as an effective activator of the jasmonate signaling pathway and respiratory substrate. The shorter lifetime of formate relative to acetate in the transpiration stream suggests rapid formate oxidation to CO2 during transport to the canopy. In contrast, acetate is efficiently transported to the canopy where an increased allocation towards mitochondrial dark respiration occurs at night. The results highlight the potential for an effective integration of acetate into glyoxylate and TCA cycles and the light-inhibition of citrate synthase as a potential regulatory mechanism controlling the diurnal allocation of acetate between anabolic and catabolic processes