Article pubs.acs.org/JAFC
Untargeted Metabolic Profiling of Winery-Derived Biomass Waste Degradation by Penicillium chrysogenum Avinash V. Karpe,*,†,§ David J. Beale,§ Nainesh B. Godhani,‡ Paul D. Morrison,⊗ Ian H. Harding,† and Enzo A. Palombo† †
Department of Chemistry and Biotechnology, Swinburne University of Technology, P.O. Box 218, Hawthorn, Victoria 3122, Australia § Land and Water, Commonwealth Scientific and Industrial Research Organization (CSIRO), P.O. Box 2583, Dutton Park, Queensland 4001, Australia ‡ Department of Mechanical and Product Design Engineering, Swinburne University of Technology, P.O. Box 218, Hawthorn, Victoria 3122, Australia ⊗ Australian Centre for Research on Separation Science, School of Applied Sciences, RMIT University, P.O. Box 2547, Melbourne, Victoria 3000, Australia S Supporting Information *
ABSTRACT: Winery-derived biomass waste was degraded by Penicillium chrysogenum under solid state fermentation over 8 days in a 2H2O-supplemented medium. Multivariate statistical analysis of the gas chromatography−mass spectrometry (GC-MS) data resulted in the identification of 94 significant metabolites, within 28 different metabolic pathways. The majority of biomass sugars were utilized by day 4 to yield products such as sugars, fatty acids, isoprenoids, and amino acids. The fungus was observed to metabolize xylose to xylitol, an intermediate of ethanol production. However, enzyme inhibition and autolysis were observed from day 6, indicating 5 days as the optimal time for fermentation. P. chrysogenum displayed metabolism of pentoses (to alcohols) and degraded tannins and lignins, properties that are lacking in other biomass-degrading ascomycetes. Rapid fermentation (3−5 days) may not only increase the pentose metabolizing efficiency but also increase the yield of medicinally important metabolites, such as syringate. KEYWORDS: winery biomass, solid-state fermentation, metabolomics, GC-MS, multivariate statistics
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limited.9 Although a few researchers mention the biomass degradation properties of this fungus,5 none have presented data on the metabolic behavior of P. chrysogenum during biomass degradation. As such, the purpose of the current study was to investigate metabolic flux during the degradation of winery-derived biomass waste by P. chrysogenum. The study utilized 2H flux due to its rapid incorporation in fungal metabolism as compared to13C. The flux experiment herein was designed to differentiate the metabolites derived from the substrate and those generated by the fungus. This process also aided in differentiating and quantifying significant metabolites generated by the fungus at different intervals. The overall goal of this research was to gauge the performance of P. chrysogenum during biomass degradation on the basis of its metabolic behavior. This monitoring is likely to provide the pathway information required to improve the generation of specific products (such as ethanol for biofuels) and/or generate numerous products in significant quantities (secondary metabolites of lignin/tannin origin, such as benzoates and gallates) in a single bioconversion process setup.
INTRODUCTION Penicillium chrysogenum has been used as an established organism for the manufacture of penicillin, one of the most widely used antibiotics in the world. However, this fungus is a highly versatile eukaryote. Apart from penicillin production, it is known to degrade several types of lignocellulosic wastes.1−3 Similar to other ascomycetes, such as Trichoderma spp. and Aspergillus spp., it produces enzymes including cellulases and hemicellulases that degrade agricultural biomass. In addition, unlike Trichoderma spp. and Aspergillus spp., Penicillium spp. have an inherent ability to degrade small-chain lignin components. In particular, P. chrysogenum has been observed to degrade the lignin component of various sources including wheat straw, pine lignocellulose,2 and grape biomass wastes from wineries.1,4 However, due to their lower enzyme production compared to other ascomycetes, Penicillium spp. are not widely used in the bioprocess industry. Nonetheless, as we have observed previously, Penicillium spp. (especially P. chrysogenum) produced comparable levels of winery biomass degradation with respect to A. niger and its cellulose and β-glucosidase activities are considerably higher than those of T. harzianum.1 Besides this, it also degrades lignins, a property found to be absent in the other species.1,4 The metabolic profiling of this fungus has been reported from numerous groups for the purpose of enhancing penicillin production through metabolic engineering.5−8 However, the study of its metabolic behavior during biomass degradation is © XXXX American Chemical Society
Received: July 16, 2015 Revised: November 25, 2015 Accepted: November 27, 2015
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DOI: 10.1021/acs.jafc.5b04834 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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used. The GC-MS system was fitted with a 30 m HP-5MS column, 250 μm i.d., and 0.25 μm film thickness. All injections were performed in splitless mode with 1.0 μL volume; the oven was held at an initial temperature of 70 °C for 2.0 min before increasing to 325 °C at 7.5 °C min−1. The transfer line was held at 280 °C. Total ion chromatogram (TIC) mass spectra were acquired from m/z 45 to 550, at an acquisition frequency of 4 spectra s−1. The solvent delay time of 7.5 min ensured that the source filament was not saturated and damaged. Data acquisition and spectral analysis were performed using MassHunter. Qualitative identification of the compounds was performed according to the Metabolomics Standard Initiative (MSI) Chemical Analysis Workgroup using standard GC-MS reference metabolite libraries (NIST 11, Fiehn and Golm) and with the use of Kovats retention indices based on a reference n-alkane standard (C8−C40 Alkanes Calibration Standard, Sigma-Aldrich, Castle Hill, NSW, Australia). For peak integration, a five-point detection filtering (default settings) was set with a start threshold of 0.2 and a stop threshold of 0.0 for 10 scans per sample. Furthermore, the samples were reapplied to a Waters GCT Premier Accurate mass spectrometer (Waters, Rydalmere, NSW, Australia) chromatograph operated using the same conditions as the GC-MS system. The time-of-flight mass spectrometer was used for metabolite confirmation, with data acquisition and processing performed using MassLynx (Waters). Chemometrics and Statistical Analysis. Chemometric and statistical analyses was undertaken using SIMCA 13 (Umetrics AG, Umeå, Sweden) and MetaboAnalyst 2.0.13 All of the samples were processed in triplicate for statistical analyses purposes. The cutoff level for significant peaks was kept at a signal-to-noise (S/N) ratio of at least 50 and a p value ≤0.05. The data obtained during metabolite mass spectral analysis were transferred to Microsoft Excel. The nonderivatized values and other noise background peak data were manually filtered out. The unsupervised data thus generated were then normalized with respect to the internal standard, adonitol (RSD = 9.3%). The normalization process yielded FC values, where a unit of magnitude referred to a concentration of 10 mg L−1 (i.e., 1 FC = 10 mg L−1). The unsupervised data thus generated were then analyzed by principal component analysis (PCA). PCA yielded orthogonal scores of sample and metabolite variables, which were plotted on a twodimensional score plot with 95% confidence level, as represented by Hotelling’s T2 tolerance eclipse. The data quality of the PCA model was assessed by the linearity (R2X) and predictability (Q2), which were observed at 84.4 and 68.9%, respectively. This two-dimensional scatter plot displays the variables with respect to each other and controls (Figure S1). The repeatability and reliability of the normalized data were assessed by the measure of distance of observation (DModX). The DModX chart represents normalized observational distance between variable set and X modal plane and is proportional to the variable’s residual standard deviation (RSD). Dcrit (critical value of DModX), derived from the F distribution, calculates the size of the observational area under analysis. Values that are twice that of the Dcrit values are generally considered as moderate outliers. The Dcrit value calculated by PCA in the current experiment was determined to be 1.237 (Figure S2). To accommodate within-group comparisons and account for moderate outliers, partial least square-discriminant analysis (PLS-DA) was employed.14 PLS-DA is used to analyze large data sets and has the ability to assess linear/polynomial correlations between variable matrices by lowering the dimensions of the predictive model, enabling easy discrimination between samples and the metabolite features that cause the discrimination (Figures S3 and S4).15 MetaboAnalyst 2.0 was used to further differentiate and classify the most significant metabolites in D2O- and non-D2O-based media. MetaboAnalyst 2.0 employs preprocessing data filtering and normalization before its application to differential expression analyses and twogroup or multigroup analyses.13 The filtered sample data were applied to univariate differential analyses methods of t test, analysis of variance.16 On the basis of a volcano plot model generated from these tests, the total number of differentially expressed metabolites in D2O was reduced to 94 (Table 1; Table S1).
MATERIALS AND METHODS
Grape Waste and Fungi. Post-fermentation grape waste of Vitis vinifera var. Shiraz was obtained from the Australian Wine Research Institute (AWRI), Glen Osmond, SA, Australia. P. chrysogenum (ATCC 10577) was obtained from Agpath Laboratories, Vervale, VIC, Australia. The fungus was first cultured in yeast mannitol broth at 30 °C for 48 h, and about 1 × 107 spores/mL was used for the biodegradation studies. The grape biomass waste was oven-dried at 70 °C for 96 h and ground using a domestic blender (model HR2094; Philips Electronics Australia, North Ryde, NSW, Australia). The temperature was selected to prevent any negative impacts on thermolabile metabolites.10,11 The dried, ground substrate was further oven-dried for 96 h at 70 °C to ensure sterility of the sample. The general composition of this biomass (g/100 g dry mass) consisted of proteins (2.22 ± 0.01), sugars (1.92 ± 0.18), lignins (35.96 ± 0.13), cellulose−hemicellulose complex (57.84 ± 0.13), and ash (2.81 ± 0.01), as determined previously.4 Degradation Process. For all degradation experiments, American Association of Textile Chemists and Colorists (AATCC) mineral salts iron medium, consisting of NH4NO3 (3.0 g/L), KH2PO4 (2.5 g/L), K2HPO4 (2.0 g/L) MgSO4·7H2O (0.2 g/L), and FeSO4·7H2O (0.1 g/ L), was used with crushed−dried grape waste (0.5:1 w/v) as the sole carbon source. The pH of this medium was adjusted to 5.6 with 1 M H2SO4 (98% AR, Thermo-Fisher Australia, Scoresby, VIC, Australia). The substrate to medium ratio was maintained at 1:1, thereby resulting in a solid state fermentation (SSF). The efficiency of biomass degradation was measured by chemical analysis of increased sugar levels, lignin mineralization, and overall activities of cellulase, βglucosidase, and xylanase enzymes according to the methods described previously.1 The metabolic flux experiment was performed using two sets of growth media. The first set consisted of 30% 2H2O (SigmaAldrich, Sydney, NSW, Australia), henceforth referred to as “deuterated water” or D2O. The second set served as the control with 1H-deionized water, henceforth referred to as “control”. The cultures were incubated at 30 °C for 8 days with shaking at 200 rpm in an incubator shaker (model OM15; Ratek Instruments Pty Ltd., Boronia, VIC, Australia). To prevent any weight loss and gas exchange, parafilm was used to seal the culture flasks. Samples were collected every 24 h and were denoted D0−D8 (D0 = 0 h; D8 = 192 h). Sample triplicates were used for biochemical analysis. After harvesting, a fraction of fungal degraded samples was freeze-dried (model Cryodos-50; Telstar Industrial, S.L., Terrassa, Spain) for the purpose of silyl derivatization of metabolites. The remaining samples were snap-frozen using liquid nitrogen to cease any enzymatic/biochemical activities and were immediately stored at −80 °C. Sample Preparation for Silyl Derivatization. P. chrysogenum degraded samples were derivatized prior to analyses (by gas chromatography−mass spectrometry (GC-MS)) as previously reported.4 Briefly, a 1.0 mL aliquot of methanol (LC grade, ScharLab, Sentemanat, Spain) was added to 40.0 ± 2.5 mg of freeze-dried sample, then vortexed briefly before centrifugation at 572.5g for 15 min at 4 °C. Adonitol (20.0 μg/mL HPLC grade, Sigma-Aldrich, Castle Hill, NSW, Australia) was added as an internal standard. A 50.0 μL aliquot of the supernatant was then transferred to a fresh tube and dried in a centrifugal evaporator at 210g and 40 °C (model RVC 2-18; Martin Christ Gefriertrocknungsanlagen GmbH, Osterode, Germany). These samples were stored at −80 °C until further use. Silyl Derivatization. A 40.0 μL aliquot of methoxyamine HCl (20 mg/mL in pyridine) followed by an aliquot of 70 μL of N,Obis(trimethylsilyl)trifluoroacetamide (BSTFA) in 1% trimethylchlorosilane (TMCS) was added to the dried samples. Samples were then briefly vortexed before being transferred to GC-MS vials. These were then derivatized in a Multiwave 3000 microwave (PerkinElmer Inc., Melbourne, VIC, Australia) for 3 min at 120 °C and 600 W before transfer to the GC-MS setup for analysis.9 Single-Quadrupole and Time-of-Flight Gas Chromatography−Mass Spectrometry (GC-MS). Single-quadrupole GC-MS was performed as previously reported.12 Briefly, an Agilent 6890B gas chromatograph (GC) oven coupled with a 5973A mass spectrometer (MS) detector (Agilent Technologies, Mulgrave, VIC, Australia) was B
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Journal of Agricultural and Food Chemistry Table 1. Top 20 Significant Metabolites Analyzed by GC-MS Profilinga sample 2,3-dimethylsuccinic acid D-ribulose N-acetyl-D-glucosamine oleic acid, trimethylsilyl ester butanal, 2,3,4-tris[(trimethylsilyl)oxy]-3-[[(trimethylsilyl)oxy] methyl]-, O-methyloxime, (S)dodecanoic acid, n- (1TMS) 3,5-diiodo-L-tyrosine glycerol-3-phosphate, DL- (4TMS) mannose, 6-deoxy-2,3,4,5-tetrakis-O-(trimethylsilyl)-, Luridine-5′-diphosphogalactose disodium salt ethyl oleate D-(+)-melibiose monohydrate D-xylopyranose, 1,2,3,4-tetrakis-O-(trimethylsilyl)ribitol, D- (5TMS) D-glucuronic acid, 2,3,4,5-tetrakis-O-(trimethylsilyl)-, trimethylsilyl ester glutaric acid, 2-hydroxy- (3TMS) sorbopyranose, 1,2,3,4,5-pentakis-O-(trimethylsilyl)-, Larabinoic acid, 2,3,5-tris-O-(trimethylsilyl)-, γ-lactone, Lbenzoic acid erythritol (4TMS)
Kovats index
KEGG name
KEGG ID
fold change
p value
1701.972 1472.212/1184.853 1702.041 2225.456 1649.574
succinyl-CoA D-ribulose N-acetyl-D-glucosamine (9Z)-octadecanoic acid D-erythrose
C00091 C00309 C00140 C00712 C01796
6.255 6.255 6.255 3.9425 2.963
0.000768 0.000768 0.000768 0.00676 0.009683
1649.717 2424.825 1754.952 1686.424 1409.93 2164.847 2748.831 1621.056 1713.261 2412.129 1553.943 1808.785/2274.986 1628.232 1244.733 1680.215
dodecanoate 3,5-diiodo-L-tyrosine sn-glycerol 3-phosphate L-rhamnose UDP-D-galactose ethyl oleate melibiose D-xylose D-ribitol D-glucuronate 2-oxoglutarate L-sorbose L-arabinoate benzoate erythritol
C02679 C01060 C00093 C00507 C00052 D04090 C05402 C00181 C00474 C00191 C00026 C00247 C00545 C00180 C00503
2.956 2.9471 2.9436 2.8706 2.8227 2.7904 2.5419 2.5262 2.5064 2.4483 2.3018 2.2887 2.1836 2.164 2.0797
0.009758 7.63e−05 0.000658 6.32e−07 1.52e−05 0.01185 8.65e−05 1.11e−06 0.00227 0.000416 0.05978 0.008467 0.005197 9.67e−05 0.00275
a Only the metabolites with fold change values ≥2.0 and p value ≤0.05 are considered. A further detailed table comprising all statistically significant metabolites can be found as Table S1 in the Supplementary materials.
The identified metabolites were then crossed-checked against the KEGG database of metabolic pathways (http://www.kegg.jp/kegg/ pathway.html). The data obtained were then applied to MATLAB 2014a statistical software using Covariance-Inverse (COVAIN) script.17
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RESULTS AND DISCUSSION P. chrysogenum was observed to effectively degrade grape biomass over the duration of a week. During this time, reducing sugars increased from 1.8 ± 0.02 to 16 ± 0.01 kg/m3. Similarly, about 2.2% of lignin mineralization was observed during the SSF process. Cellulase, β-glucosidase, and xylanase activities were observed at 31 ± 0.26, 106.3 ± 0.41, and 936.8 ± 9.94 U/mL, respectively.1,4 The overall activities were either comparable to or higher than those of other ascomycetes used in previous experiments.1,9 Metabolic Flux Analysis of P. chrysogenum during Winery Biomass Degradation. Mass spectrometry indicated ca. 640 peaks across all samples in growth media supplemented with H2O and 30% D2O. Further data obtained from PLS-DA, Metaboanalyst 2.0, and COVAIN were applied as a correlation between the different metabolites in a time series analysis. The PLS-DA was able to yield a better model predictability for all follow-up analyses, with linearity values of R2X = 79.7% and R2Y = 99.6% and a predictability level of Q2 = 93.1%. The resultant volcano plot obtained from a further analysis of PLS-DA data was able to differentiate 94 D2O-labeled metabolites carrying isotopic signatures from the non-isotope-labeled metabolites (Figure 1). A correlation of these metabolites was considered for all pathways under current experimental considerations. On the basis of previous papers, glycolysis leading to the tricarboxylic acid (TCA) cycle was considered as the basic skeletal/central pathway with respect to any other upstream or downstream metabolic pathways.6,8 The data relating to all metabolites were manually fed into MATLAB 2014a software script at glucose, glycerate-3-phosphate, acetyl-coenzyme A (acetyl-CoA), and fumarate junctions, where an increase or decrease in other
Figure 1. Volcano plot displaying the differentially expressed metabolites in deuterated and nondeuterated media of P. chrysogenum. The significant metabolites expressed in deuterated medium (yellow circles) were taken into consideration for further metabolic flux analyses.
metabolites was considered with respect to these metabolites. The pathways merging at the glycolysis junction point of glyceraldehyde-3-phosphate were mapped manually with respect to glycerate-3-phosphate, the immediate next metabolite. Similarly, pathways merging at the pyruvate junction were mapped manually with acetyl-CoA. Overall, including glycolysisTCA, 23 distinct (and 36 individual) pathways with respect to glycolysis and TCA were taken into account on the basis of biosynthesis or degradation of metabolites during the 8 day fermentation. Figure 2 represents a general layout of all metabolic pathways involved in the biomass degradation process, whereas Table 1 and Table S1 present the metabolite information. Glucose/Glucose-1-phosphate Junction. Glucose is one of the most important molecules in many metabolic pathways. It marks the initial metabolite of glycolysis and TCA cycle pathways; these pathways are required for energy production C
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Figure 2. Metabolic pathway of P. chrysogenum during SSF-based degradation of winery biomass waste over 8 days. Detailed information about the metabolites is provided for individual pathways in the Supporting Information, Section 2.
Figure 3. Metabolism of (A) major saccharides and (B) chitin biosynthesis intermediates by P. chrysogenum during winery biomass waste degradation of Shiraz grapes over 8 days (p ≤ 0.05).
It was observed that metabolic pathways of seven different sugars and sugar alcohols were directly linked to glucose (Figure 2). These metabolites consisted primarily of galactose, melibiose, L-sorbose, maltose, and psicose along with trehalose and sorbitol in lower concentrations. Contrary to a previous paper,18 in which L-sorbose was observed to be a minor metabolite output (near lower levels of detection), in this study it was observed to be in considerable concentrations in Shiraz grape biomass. A considerable amount of this sugar was utilized by P. chrysogenum. The initial concentration of 632.6 mg/L detected on D0 rapidly dropped to 16.1 mg/L by D4. This was inversely proportional to the glucose concentration, indicating that a considerable amount
from storage molecules in all organisms. The initial glucose concentration prior to degradation (D0) was 4.7 mg/L in the substrate. This was expected because winery biomass waste contains very low amounts of this sugar. Due to fungal degradation, however, the concentration increased to 85.1 mg/ L by day 5 (D5) and then decreased again to 1.3 mg/L by day 7 (D7). The latter decrease indicates utilization of the sugar by the fungus and indicates its role as an intermediate of many metabolic pathways. However, an increase to 28.7 mg/L by day 8 (D8) suggests accumulation of glucose due to the probable onset of cellulase enzyme inhibition from D7 onward (Figure S5). D
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samples. Melanins are one of the numerous polyketides produced by filamentous fungi. Their production is induced by polyketide synthases (PKS enzymes), which, in turn, are regulated by PKS genes. The number of these genes varies according to species, and they occur in high concentrations (23 copies) in Penicillium spp.28 Although melanins have been observed from disease-causing fungi, such as Penicillium marneffei,28 the pigments have also been observed during penicillin production by P. chrysogenum due to derepression of melanin synthesis genes.7 The current experiments showed that the concentrations of melatonin and 3,5-diiodo-L-tyrosine increased during the initial periods (D0−D3) of fungal growth. Melatonin deposition increased from 6.1 mg/L on D0 to 9.8 mg/ L on D3, whereas 3,5-diiodo-L-tyrosine increased from 2.1 to 5.7 mg/L during the same time. However, during the later phases, these concentrations dropped rapidly to 3.7 and 0.6 mg/L on D8 for melatonin and 3,5-diiodo-L-tyrosine, respectively (Figure S6). This drop in the melatonin levels can be attributed to the late autolysis observed in P. chrysogenum cultures, as indicated by the decrease in chitin biosynthesis intermediates (Figure 3B). The observed results were found to be in agreement with the previously reported metabolic flux of A. niger.29 Glycerate-3-phosphate Junction. Glycerate-3-phosphate, or 3-phosphogleceric acid, is the downstream metabolite of glyceraldehyde-3-phosphate in the glycolysis pathway. During the current experiments, it was observed that at least six pathways converged at the glycerate-3-phosphate junction either directly or via glyceraldehyde-3-phosphate (not detected as a statistically significant metabolite during P. chrysogenum flux). These consisted of pentose phosphate pathways, lecithin metabolism via serine biosynthesis, terpenoids metabolism, deoxy sugar metabolism, glycerol biosynthesis, and pectin metabolism. Glyceraldehyde-3-phosphate is generated during glycolysis by type I and type III D-glycerate kinases in the cell cytoplasm, as has been reported for Saccharomyces spp. (yeast) and Nostoc spp. (bacteria).30 In our experiments, owing to hemicellulose degradation by P. chrysogenum, numerous monosaccharides such as D-ribulose, erythrose, and xylose accumulated during the earlier phase of degradation, especially during the first 3 days of SSF. These accumulated sugars underwent fungis-mediated metabolism to generate glycerate-3-phosphate. Due to this, glycerate-3-phosphate increased from an initial concentration of 160.9 to 252.5 mg/L during the first 3 days (Figure S7). However, owing to the biosynthesis of downstream molecules such as serine and glycerol, this concentration depleted considerably to 12.9 mg/L by D8. The only sugar showing late accumulation during the fermentation was D-ribulose. The initial concentration of this pentose sugar was 4.5 mg/L on D0, which increased to 6 mg/L and then to 40 mg/L by D8, possibly showing the onset of xylanase inhibition. Ribulose and ribulose-5-phosphate are two of the most important metabolites of the pentose phosphate pathway. It is known that CO2 is assimilated in the metabolic pathways, especially in the TCA or Calvin cycle, via ribulose and ribulose-5-phosphate. This CO2 fixation or acquisition is catalyzed by ribulose biphosphate carboxylase (RuBisCO). This pathway is common in plants, algae, and photosynthetic bacteria. Additionally, RuBisCO-like enzymes catalyze a reversal of the TCA pathway, causing the generation of ribulose and ribulose-1-phosphate in sulfur bacteria such as Chlorobium limicola and Thiocapsa roseopersicina.31 In non-photosynthetic organisms such as fungi, ribulose is one of the intermediates in the reduction of pentose sugar alcohols such as arabitol32 or from
of sorbose was converted to glucose via a rapid sorbitol reduction process, as observed from constantly low sorbitol levels throughout the experimental period (Figure S5). The probability of a rapid sorbitol conversion can be inferred from previous observations that indicated the presence of very low concentrations or complete absence of sorbitol in grapes in contrast to other fruit sources such as pear or pineapple.19 Melibiose, which was earlier reported as a trace sugar in grape berries,20 is a disaccharide made up of an α(1−6) linkage between glucose and galactose. Contrary to previous reports of the low concentration of melibiose20,21 and at a relative concentration level of 3.99 against glucose (840.73),22 the current experimental observations showed the presence of about 80 mg/L of melibiose, which increased to 101.3 mg/L from D0 to D5 and later dropped to 6.7 mg/L by D7, thus indicating considerable metabolism, directly proportional to glucose metabolism (Figure 3A). N-Acetylglucosamine (NAG) is one of the other major metabolites synthesized during fungal growth on a substrate; it is an essential component of the fungal cell wall. It was observed that the NAG content of P. chrysogenum degraded biomass initially increased from 4.51 mg/L on D0 to 111.4 mg/L on D5. However, it then decreased rapidly to 39.9 mg/L by D8 (Figure 3). Although unexpected, this depletion in NAG levels was likely due to autophagy by P. chrysogenum. Autophagy is not uncommon in filamentous fungi, especially during the carbon depletion period of their growth. It is utilized by these fungi to recycle the nutrient resources for their survival. In the case of P. chrysogenum, autolysis has been generally linked with proteolysis activity of fungus after 3 days of substrate degradation. The NAG content of the fungal cell wall can be also used as a growth indicator, especially where the carbon source is water-insoluble, such as cellulose or related biomass. The obtained results were observed to be in line with the previously observed glucosamine ranges of 111−170 and 320 mg/g and fungal dry weight of Cunninghamella elegans and Trametes hirsute.23,24 However, the quantification of P. chrysogenum with respect to the increase in glucosamine remains to be validated. A recent paper indicated no significant impact of mycelium age with respect to glucosamine content. This may be attributed to the ascomycete origin of Penicillium spp., which do not require a fruiting body for sporulation, unlike basidiomycetes, therefore yielding a mix of spores and hypae in growth medium.25 These conflicts make it necessary to employ a more reliable method to quantify fungal growth in water-insoluble growth media. Protease activities possibly dropped sharply after D5. This drop coinciding with ammonia release probably marked the onset of autophagy.26 Chitinases are the other group of enzymes responsible for the onset of autophagy in P. chrysogenum. Although the enzymes are produced by P. chrysogenum using chitin synthase enzymes, their activity increases considerably toward the carbon starvation period, that is, from the fourth day of incubation.27 These enzyme activities have been shown to decrease the hypal concentration in tested samples, indicating P. chrysogenum autolysis, primarily after the fifth day of incubation. Our results were found to be in agreement with previous work and showed considerable depletion of NAG after D5. Similarly, N-acetylmannosamine, one of the intermediates of chitin biosynthesis, also displayed an overall depletion from 3.4 to 0.25 mg/L during P. chrysogenum-mediated biomass degradation. P. chrysogenum was observed to generate melanin products via tryptophan metabolism. One end product, melatonin, and an intermediate, 3,5-diiodo-L-tyrosine, were detected in culture E
DOI: 10.1021/acs.jafc.5b04834 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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Figure 4. Metabolism of (A) xylitol biosynthesis intermediates, (B) propanol biosynthesis intermediates, and (C) pectin intermediates by P. chrysogenum during winery biomass waste degradation of Shiraz grapes over 8 days (p ≤ 0.05).
chrysogenum showed the potential to generate propanol, one of the other important biofuel molecules. By D6, about 6.2 mg/L propanol was generated. However, probably due to the stationary growth phase of this fungus, this metabolite was reutilized as an energy source, thereby ultimately depleting the propanol levels to 0.6 mg/L. Similarly, sn-glycerol-3-phosphate was produced during the earlier growth phase and reached its peak value of 18 mg/L at D6, followed by a depletion to 1.1 mg/L by D8 (Figure 4B). From these results, it can be deduced that P. chrysogenum has the ability to generate propanol during lag-phase growth. However, the experiments also highlighted the desirability for extraction of propanol from the medium before the onset of the stationary phase. The study also indicates a necessity to further improve the Penicillium-mediated biomass degradation to generate higher quantities of industrially useful alcohols, such as propanol and glycerol. P. chrysogenum was observed to possess pectin degradation as well, a feature observed less prominently during A. niger metabolic flux29 observed during the similarly scaled experiment on grape biomass. It was found to degrade pectin in biomass via the inositol metabolism pathway. Galacturonate dropped from 79.6 mg/L on D3 to 3.1 mg/L on D8, and glucuronate reduced from 4.3 mg/L on D0 to 0.2 mg/L on D8 (Figure 4C). Acetyl CoA Junction. Acetyl-CoA is one of the most important cellular metabolites as it forms a link between glycolysis and the TCA cycle. Due to its presence at this critical position, a large number of pathways either merge in or merge out at the acetyl-CoA junction. In the current experiments, seven pathways merged at this junction directly, and three pathways merged (indirectly) via pyruvate. These pathways related to the metabolism of isoprenoids, fatty acids such as hexadecanoate, dodecanoate, octadecanoate, linoleate, and docosanoate, secondary metabolites, and amino acids such as leucine, isoleucine, lysine, cysteine, methionine, and lysine. Unlike glycerate-3-phosphate, the overall concentration of acetyl-CoA remained unexpectedly low during the entire SSF
pentose acid reduction of molecules such as gluconates or idonates, as observed in our studies (Figure S8). In an inversely proportional relationship to ribulose, the concentration of these acids depleted from about 6.2 mg/L on D6 to about 3.4 mg/L on D8. One of the interesting features observed during the metabolic profiling of P. chrysogenum during the SSF of winery biomass waste was the role of pentose alcohols such as arabitol and xylitol. As mentioned above, arabitol was reduced initially to ribulose, thereafter merging into glycolysis at the glycerate-3-phosphate junction. It was thus utilized as quickly as it formed, and its concentration remained relatively constant at 18−19 mg/L during the degradation period. Xylose is one of the major hemicellulosic residues. However, a large number of fungi, including yeasts, are unable to utilize this sugar. During this experiment, it was observed that xylose accumulated in the early phase of P. chrysogenum-mediated degradation due to xylanase activities for hemicellulose degradation. During this period, the xylose concentration increased >2-fold from 15.1 mg/L on D0 to 37.7 mg/L on D3. However, its concentration depleted to 1.4 mg/L by D8, displaying xylose metabolism toward either glycolysis via xylulose-5-phosphate or xylitol biosynthesis. It was also noted that during the xylose depletion period, considerable amounts of xylitol accumulated in the media. Xylitol was observed to accumulate during the later phase of fermentation, and it increased from 2.6 mg/L on D0 to 24 mg/L by D8 (Figure 4A). P. chrysogenum, therefore, was observed to possess the property of xylose conversion. This property can be applied to cogenerate biofuel molecules such as ethanol during the biodegradation of lignocellulose components. Studies utilizing S. cerevisiae-33 and Candida maltosa-based32 D-xylulokinase catalyzing activities to generate ethanol from xylose have been reported. One of the other peculiar results observed was propanol biosynthesis via the glycerol metabolism pathway. Although not generated in as high a concentration as xylitol, SSF with P. F
DOI: 10.1021/acs.jafc.5b04834 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Figure 5. Metabolism of (A) lignin and tannin degradation intermediates via benzoate degradation pathway and (B) penicillin biosynthesis intermediates via lysine degradation pathway by P. chrysogenum during winery biomass waste degradation of Shiraz grapes over 8 days (p ≤ 0.05). (C) Fatty acid biosynthesis by P. chrysogenum during winery biomass waste degradation of Shiraz grapes over 8 days (p ≤ 0.05).
chrysogenum probably synthesized α-tocopherol chiefly via the mevalonate pathway and, surprisingly, to a minor extent by the MEP pathway, which is not a common mechanism of isoprenoid synthesis in fungi. Mevalonate levels increased to 109.8 mg/L by D3, which was directly proportional to a considerable increase in α-tocopherol levels from 0.003 to 0.03 mg/L during the same period. After D3, the drop in mevalonate levels to 67.4 mg/L by D7 resulted in depletion of α-tocopherol to 0.01 mg/L. However, α-tocopherol increased to 0.03 mg/L on D8, probably as a result of increasing MEP levels from 2.2 mg/L (D0) to 5.7 mg/L (D7) (Figure S9). Other isoprenoids were not detected in significant levels by GC-MS analysis. LC-MS-based analysis may help to detect these metabolites and resolve these discrepancies. Tannins and lignins are some of the major constituents of grape biomass and can comprise up to 35−40% of dry weight of this biomass.1,36 It has been demonstrated that P. chrysogenum has the ability to degrade minor amounts of low molecular weight lignin components such as vanilates and ferrulates.2 Additionally, Penicillium spp. are known to possess tannin-degrading enzymes, such as tannin acyl hydrolase, which catalyze the hydrolyzation of tannic acid.37 However, this property has not been widely reported in P. chrysogenum. During SSF-based degradation of Shiraz grape biomass, P. chrysogenum was observed to liberate and then degrade the syrinagate or syringic acid component of grape tannins via the benzoate degradation pathway. The initial syringate content of grape biomass was recorded at 1.03 ± 0.01 mg/L (D0). Considering that the majority of syringate ends up in grape juice used for wine production, this result is in agreement with previous observations that had reported Shiraz grapes to contain up to 3 mg/L of syringate.38 This metabolite was observed to accumulate to about 3.2 mg/L during the early phase (D3) of P. chrysogenum-mediated degradation. However, this concentration depleted to 0.6 mg/L by D8 (Figure 5A).
period (Figure 5A). This was in contrast to the levels observed in our previous study investigating A. niger metabolism, where the levels were >100 mg/L during the early phase of metabolism.29 One of the reasons for this might be the biosynthesis of amino acids, fatty acids, and isoprenoids, as explained below. One of the major biosynthetic pathways seen from the acetylCoA junction was isoprenoid biosynthesis, resulting in the formation of α-tocopherol via the mevalonate pathway. Tocopherols are the large groups of isoprenoids generally produced by plants as defense molecules in response to fungal infection. Reference 34 reported the presence of multiple expressed sequenced tags (ESTs) responsible for secondary metabolite production in citrus plants via 7-phospho-2-deoxy-3D-arabino heptanoate (DAHP). This molecule was also observed during the current experiments as an intermediate metabolite during melanin pigment synthesis (Figure S6). Another molecule acting as an α-tocopherol biosynthesis intermediate observed during the metabolic profiling was 4-(cystediene-5diphospho)-2-C-methyl-D-erythritol. It has been reported that this molecule belongs to the 4-phospho-2-C-methylerythritol (MEP) pathway and is one of the most widely used precursors for α-tocopherol biosynthesis in plant plastids and prokaryotes.35 However, in fungi and other eukaryotes, this isoprenoid is synthesized from acetyl-CoA. Isopentyl pyrophosphate (IPP) acts as an active isoprene precursor in the mevalonate pathway, which combines with dimethylallyl pyrophosphate (DMAPP) to form geranyl pyrophosphate (GPP). GPP serves as the immediate precursor to carotenoids, tocopherols, and numerous other fat-soluble vitamins.35 During our experiments, it was observed that although αtocopherol was found at levels of
