Open Access

Elucidating how the saprophytic fungus Aspergillus nidulans uses the plant polyester suberin as carbon source

  • Isabel Martins1,
  • Diego O Hartmann1,
  • Paula C Alves1,
  • Celso Martins1, 2,
  • Helga Garcia1,
  • Céline C Leclercq3,
  • Rui Ferreira1,
  • Ji He4, 6,
  • Jenny Renaut3,
  • Jörg D Becker5 and
  • Cristina Silva Pereira1, 2Email author
BMC Genomics201415:613

DOI: 10.1186/1471-2164-15-613

Received: 18 March 2014

Accepted: 16 July 2014

Published: 21 July 2014

Abstract

Background

Lipid polymers in plant cell walls, such as cutin and suberin, build recalcitrant hydrophobic protective barriers. Their degradation is of foremost importance for both plant pathogenic and saprophytic fungi. Regardless of numerous reports on fungal degradation of emulsified fatty acids or cutin, and on fungi–plant interactions, the pathways involved in the degradation and utilisation of suberin remain largely overlooked. As a structural component of the plant cell wall, suberin isolation, in general, uses harsh depolymerisation methods that destroy its macromolecular structure. We recently overcame this limitation isolating suberin macromolecules in a near-native state.

Results

Suberin macromolecules were used here to analyse the pathways involved in suberin degradation and utilisation by Aspergillus nidulans. Whole-genome profiling data revealed the complex degrading enzymatic machinery used by this saprophytic fungus. Initial suberin modification involved ester hydrolysis and ω-hydroxy fatty acid oxidation that released long chain fatty acids. These fatty acids were processed through peroxisomal β-oxidation, leading to up-regulation of genes encoding the major enzymes of these pathways (e.g. faaB and aoxA). The obtained transcriptome data was further complemented by secretome, microscopic and spectroscopic analyses.

Conclusions

Data support that during fungal growth on suberin, cutinase 1 and some lipases (e.g. AN8046) acted as the major suberin degrading enzymes (regulated by FarA and possibly by some unknown regulatory elements). Suberin also induced the onset of sexual development and the boost of secondary metabolism.

Keywords

Aspergillus nidulans β-oxidation Cutinase Long chain fatty acids Suberin Whole-genome profiling

Background

Plant lipid polymers, particularly cutin and suberin, are the third most abundant of the plant polymers [1], yet the least understood since the underlying polyester structure remains partially unresolved. High recalcitrance is an inherent property of their molecular structure and hallmark monomers are often identified in soils [2, 3]. Filamentous fungi are key recyclers and compose nearly 75% of the soil microbial biomass [4] but their role in the turnover (biodegradation) of plant polyesters remains largely overlooked [5]. Suberin is a structural component of the secondary cell walls in specialised tissues, namely in the phellem of tree barks and subterranean organs [5, 6] and in the endodermis of roots [7]. Cutin, together with waxes (viz. cuticle), covers the cell walls in the epidermis of aerial tissues [8, 9]. Biosynthesis of either suberin or cutin is developmentally regulated and triggered as response to infection or wounding, among other challenges [813]. These lipid hydrophobic barriers constrain apoplastic water and solute translocation, physically strengthen the cell wall and, might also play roles in plant–pathogen interactions [14, 15].

In general, both suberin and cutin contain fatty acids (FAs), ω-hydroxy FAs and glycerol but suberin also contains high levels of α,ω-dicarboxylic acids, ferulic acid and fatty alcohols and its saturated aliphatics have longer chain lengths than in cutin (>C20 and C16-18, respectively) (Figure 1a) [5, 10]. These composing monomers are linked essentially through acylglycerol or linear aliphatic ester bonds, building a three-dimensional network [16, 17]. Fungal degradation of plant polyesters has been reported to involve the activity of carboxylesterases, namely cutinases [1820]. Despite high complexity and redundancy, it is well established that FAs can be used by filamentous fungi via β-oxidation leading to the production of acetyl-CoA [21, 22]. Downstream pathways, such as the glyoxylate and the tricarboxylic acid cycles and gluconeogenesis, enable the fungus to use FAs as sole carbon and energy sources.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-15-613/MediaObjects/12864_2014_Article_6294_Fig1_HTML.jpg
Figure 1

Schematic view of suberin (a), showing the linear aliphatic ester bonds and the acylglycerol ester bonds (continuous and dashed circles, respectively) and the ATR-FTIR spectra of isolated suberin (a), namely untreated (b) and recovered at the first (c) and the last (d) time points of incubation with Aspergillus nidulans . Major peaks, which can be almost exclusively assigned to suberin, are at 2921 cm-1 (1), 2851 cm-1 (2) and 1737 cm-1 (3). The remaining peaks are simultaneously assigned to the fungal cell wall and either to suberin [1158 cm-1 (7) and 1635 cm-1 (4)], lignin [1511 cm-1 (5) and 1424 cm-1 (6)] or to polysaccharides and lignin [1034 cm-1 (8)].

In plants, suberin is ingrained between a primary and a tertiary cell wall and cross-linked to the other cell wall polymers, hence its extraction usually destroys its chemical skeleton [5]. This is still a major obstacle [5] and has restrained most biodegradation studies to the use of cutin films [2325] and/or mixtures of nearly non-esterified suberin or cutin samples [2628]. However, near-native suberin can be efficiently extracted from cork (outer bark of Quercus suber L.) through selective hydrolysis of acylglycerol ester bonds but leaving most linear aliphatic ester bonds intact [2932] (Figure 1). In the present contribution we demonstrate that suberin macromolecules could be used as sole carbon source by Aspergillus nidulans. During fungal growth, synergetic action of cutinases, lipases and long chain fatty alcohol modifying enzymes released suberin long chain fatty acids (LCFAs) that were metabolised via peroxisomal β-oxidation. Other major alterations included the onset of sexual development and the boost of secondary metabolism.

Methods

Chemicals

If not otherwise stated chemicals were of the highest analytical grade and purchased from Sigma Aldrich (USA). Suberin was extracted from cork using cholinium hexanoate as previous described [30], afterwards freeze dried and kept at -20°C until used. The same process was used to recover the residual suberin upon fungal incubation. All suberin samples were analysed using attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) as previously described [30, 32]. The selected ATR-FTIR spectra should be regarded as representative (ten replicates).

Culture conditions

Fungal cultures with a density of A. nidulans (FGSC A4) conidia of 105per mL (5 mL six-well plates, minimal media [33] containing 1% w/v glucose) were grown for two days (27°C, dark, 90 rpm) for the establishment of a mycelia mat against the bottom of the wells (control). Afterwards, old media were replaced by minimal media containing 0.1% w/v of suberin as sole carbon source, and cultures were grown, in the same conditions, for additional two, four, six or fifteen days. At each time point mycelia and the corresponding media filtrate were recovered and preserved at -80°C [33]. Additional control cultures were prepared containing 0.1% w/v of C16 glyceryl tripalmitate or C8 octyl octanoate (contain acylglycerol ester and linear ester bonds, respectively) instead of suberin. Controls were processed as described above.

Microscopic analyses

Scanning Electron Microscopy (SEM) analysis of lyophilised fungal mycelia were performed using an analytical field emission gun scanning electron microscope (FEG-SEM: JEOL 7001 F with Oxford light elements EDS detector) operated at 5-10 kV. After the LIVE/DEAD assay [34] (evaluates culture viability) and the safranin staining (detects the extracellular matrix typical of fungal biofilm [35]), mycelia were evaluated using a DM5500 B microscope (Leica) under fluorescent (49 DAPI and N21 filter sets) or white light, respectively. 10x and 63x magnification objectives were used, respectively and images were captured with a DFC420 C camera (Leica). In all tests the selected micrographs should be regarded as representative.

Secretome analyses

Extracellular protein was recovered from the culture filtrates using denaturing precipitation conditions [33]. 25 μg of protein (bovine serum albumin equivalents accordingly to the Bradford protocol) were loaded in a precast gel (Criterion™ XT precast 1D gel 4-12% Bis-Tris) and allow to migrate for 1 cm. The gel was stained with Instant Blue (Gentaur BVBA), sliced into 5 bands; (each cut into 1-2 mm cubes), first reduced, alkylated and de-stained, then digested by trypsin (Promega). The peptides were first desalted and finally fractionated by reverse phase separation in an Ultimate 3000 NanoLC System coupled to a LTQ-OrbiTrap Elite MS that was operated in data-dependent mode, automatically switching between MS and MS2, using XCalibur software. Data was processed in Mascot using Proteome Discoverer by searching against the SwissProt Fungi (released on January 21st, 2013) and NCBI databases. Protein identification was done using a set of pre-defined filters and a minimum confidence of 95%. Full details in Additional file 1. Glycerol in the culture media filtrates (40 times concentrated, duplicates) was analysed by chromatography as reported before [36]. Quantification detection limits were 0.01 g · L-1. The additional control cultures (see above) were also analysed.

RNA isolation and cRNA preparation

Total RNA was isolated from fungal mycelia (grounded to powder using mortar and pestle in liquid nitrogen) using the RNeasy Plant Mini Kit (QIAGEN) and further purified by ethanol precipitation [37]. Quantification and purity of RNA were determined on a NanoDrop 1000 Spectrophotometer (Thermo Scientific) and RNA integrity analysed using an Agilent 2100 Bioanalyser with a RNA 6000 Nano Assay (Agilent Technologies). Fragmented and biotinylated cRNA was obtained by following GeneChip 3’ IVT Express Kit protocols. Briefly, 100 ng of total RNA were used for the synthesis of cDNA, which was further in vitro transcribed into labelled cRNA. After purification and fragmentation, the size distribution of the cRNA and fragmented cRNA were assessed in an Agilent 2100 Bioanalyzer with a RNA 6000 Nano Assay.

Microarray processing

The custom array FungiANC (Affymetrix) contains a total of 20,012 transcripts from the genetic information of A. nidulans and Neurospora crassa available at the Broad Institute database (http://www.broadinstitute.org) and is based on a Perfect Match-only (PM) design with 11 micron feature size. Each transcript is represented by 11 probes (25-mer each). See full details in Additional file 2. The array processing was performed accordingly to Affymetrix GeneChip protocols (biological triplicates). A total of 200 μl of the hybridisation mixture containing 10 μg of fragmented cRNA was hybridised on arrays for 16 hours at 45°C. Standard post hybridisation washes and double-stain protocols (FS450_0001) were used on an Affymetrix GeneChip Fluidics Station 450, in conjunction with the GeneChip Hybridisation Wash and Stain Kit (Affymetrix). Arrays were scanned on an Affymetrix GeneChip Scanner 3000 7G. Array quality parameters were analysed by Expression Console Software (Affymetrix) for Robust Multiarray Averaging summarised data and confirmed to be in the recommended range. The data discussed in this publication have been deposited in NCBI’s Gene Expression Omnibus [38] and are accessible through GEO Series accession number GSE54427 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE54427).

Microarray data analysis

DNA-Chip Analyzer (dChip) 2010 (http://www.dchip.org) was used applying a probeset mask file considering only the A. nidulans probes (9675 transcripts). The normalised CEL intensities of the 12 arrays (Invariant Set Normalisation Method [39, 40]), were used to obtain model-based gene expression indices based on a Perfect Match-only model [39, 40]. dChip Log2 expression data were imported into R v2.13.0. Differentially expressed genes (analysis was carried out with Bioconductor LIMMA package, http://www.bioconductor.org), included only the probe sets with adjusted p-value ≤0.01 and fold-change (FC) ≥2. See full details in Additional file 1.

Quantitative real-time PCR analysis (qRT-PCR)

Based on the sequences of A. nidulans genes (Aspergillus Genome Database, http://www.aspergillusgenome.org/), all oligonucleotide pairs were designed using the GeneFisher2 web tool (http://bibiserv.techfak.uni-bielefeld.de/genefisher2) and produced by Thermo Fisher Scientific (see Additional file 1 for the list of the oligonucleotides used in this study). The qRT-PCR analysis was performed in a CFX96 Thermal Cycler (Bio-Rad), using the SsoFast EvaGreen Supermix (Bio-Rad), 250 nM of each oligonucleotide and the cDNA template equivalent to 1 ng of total RNA, at a final volume of 10 μl per well, in three technical and three biological replicates. The PCR conditions were: enzyme activation at 95°C for 30 s; 40 cycles of denaturation at 95°C for 10 s and annealing/extension at 59°C for 15 s; and melting curve obtained from 65°C to 95°C, consisting of 0.5°C increments for 5 s. Data analyses were performed using the CFX Manager software (Bio-Rad). The expression of each gene was taken as the relative expression in pair-wise comparisons of consecutive time points. The expression of all target genes was normalised by the expression of the 60S ribosomal protein L33-A gene, AN2980, selected as internal control due to its constant levels in all time points.

Functional annotation

Annotations for all the genes represented on the FungiANC genome array were obtained from the Broad Institute database (http://www.broadinstitute.org) and the Aspergillus Genome Database (AspGD, http://www.aspgd.org). See full details in Additional file 2. The differentially expressed genes for each biological condition were classified using the FungiFun web annotation tool [41] and the Functional Catalogue (FunCat). The significant hits (p-value ≤0.05) were defined using the identities present on the chip as the background.

Results & discussion

Aspergillus nidulanstranscriptome on suberin - enrichment analysis

Pair-wise comparisons were used to identify differentially expressed genes (adjusted p-value < 0.01 and |FC| > 2) between the control (grown on glucose) and during growth on suberin for two, four or six days (hereafter defined as first, mid and last time points, respectively) Additional file 2. Within the differentially expressed genes (4198 constituting nearly half of the transcripts in the microarray), 32% (1357 genes) can be specifically associated with the switch of the substrate (control vs first time point) and were enriched in functional categories associated with the metabolism of alkanes, alkenes, alkanals and alkanols (MIPS 01.20.05.03) and the oxidation of fatty acids (MIPS 2.25), as well as cellular sensing and response to external stimulus (MIPS 33.11) and cell type differentiation (MIPS 43), among others (Figure 2b, Additional file 3). Pair-wise comparison of consecutive time points, henceforward systematically used, showed that among the enriched functional categories at the mid time point some were associated with increased nutrient starvation response (MIPS 32.01.11) and alterations in fatty acid metabolism (MIPS 01.06.05), along with major alterations in cell cycle (MIPS 10) and cell fate (MIPS 40) Additional file 3. In addition, those enriched at the last time point revealed e.g. an increased stress response (MIPS 32.01) and development of ascospores (MIPS 43.01.03.09). In particular, the degradation/modification of exogenous ester compounds (MIPS 32.10.09) can be associated with cleavage of ester bonds in suberin. The intensity of the major peak assigned to ester bonds (1737 cm-1 which can be exclusively assigned to the C = O stretch of ester groups) in the ATR-FTIR spectra of suberin decreased significantly after fungal incubation (Figure 1b).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-15-613/MediaObjects/12864_2014_Article_6294_Fig2_HTML.jpg
Figure 2

Number of differentially expressed genes during Aspergillus nidulans growth on suberin in pair-wise comparisons of consecutive times (a), discriminating the up- (↑) and the down- (↓) regulated genes, and Venn diagram highlighting the number of genes that were responsive only at the first time point on suberin when compared with the control (b).

Autolysis and primary metabolism

Autolysis occurred after switching from glucose to suberin media. Major up-regulation of pepJ (AN7962, Table 1) and up-regulation of prtA (AN5558) resulted in accumulation of the encoded proteins in the secretome (Table 2). Both proteases play a role in the degradation of empty hyphae during starvation [42, 43]. Out of the 25 protein species identified in the secretome, ten are involved in cell wall remodelling events typical of autolysis and show, in general, high consistency with the transcriptome data (Table 2). Several other cell wall remodelling genes related with autolysis were up-regulated along cultivation: AN9042, mutA (AN7349), AN7613, AN2690 and AN8392, chiB (AN4871) [44, 45], engA (AN0472) [46] and nagA (AN1502) [44] (Table 1 and Additional file 2). Glucuronan lyase A gene (AN0012) has been reported to be up-regulated in A. nidulans during starvation [47] but here its expression level at the first time point was exceedingly higher (Table 1). The encoded protein specifically breaks β-1,4-glucuronans, which are rarely found in the cell walls of Aspergilli[48] and absent in those of cork [6]. Hence, the functional role of AN0012 remains largely unclear. Few genes related with apoptosis (AN7500 and AN5712) [49, 50] or autophagy (AN2876 and AN5174) [51] were responsive along the incubation, suggesting that they played only a minor role during the fungus growth on suberin Additional file 2. As typically reported in A. nidulans after imposition of severe carbon starvation conditions, several putative major facilitator superfamily (MFS) transporter genes (AN9232, AN8084, AN6778, AN8502) [47, 52] underwent major up-regulation (Table 1). The last two genes belong to uncharacterised secondary metabolite clusters [53], thus probably coding for specific transmembrane transporters. Some other MFS genes (AN5860, mstE and AN4180) and one auxin efflux carrier superfamily gene (AN8018) were amongst those showing major down-regulation (Table 1). mstE is induced in the presence of several repressing carbon sources and is dependent on the function of CreA (AN6195) [54]. Up-regulation of creA, the carbon catabolite repressor A [55], at the first time point (Table 3) might be explained by a self-repression mechanism [56, 57]. Gluconeogenesis activation might have occurred as suggested by the up-regulation of the pathway transcription activator (acuM, AN6293) and of phosphoenolpyruvate carboxykinase gene (acuF, AN1918) which, together with the fructose 1,6-bisphosphatase gene (acuG, AN5604, not differentially expressed in the suberin media), regulate this pathway [58] (Table 4, Additional file 2). The 4-aminobutyrate (GABA) shunt is inactive during gluconeogenesis [59], likely coordinated with major down-regulation of putative glutamate decarboxylase gene (AN7278) at the first time point (Table 1). Major up-regulation of the fermentation transcription activator alcR (AN8978, Table 1) at the last time point occurred but the aldehyde dehydrogenase gene (AN0554) [60] was not differentially expressed Additional file 2.
Table 1

List of the differentially expressed genes showing the highest fold changes (FCs) in pair-wise comparison of consecutive time points during Aspergillus nidulans growth on suberin

First time point of suberin incubation (between the control and second day of incubation on suberin)

Mid time point of suberin incubation (between the second and fourth days of incubation on suberin)

Last time point of suberin incubation (between the fourth and sixth days of incubation on suberin)

FC

Gene #

Description

FC

Gene #

Description

FC

Gene #

Description

Up-regulated

358.7

AN6000

Asperthecin polyketide synthase (aptA)

31.8

AN7369

GMC oxidoreductase

23.5

AN9230

Monooxygenase associated with secondary metabolism

305.8

AN5309

Putative cutinase 1 (cut1)

22.0

AN10030

Putative alkaline serine protease

9.6

AN6778

MFS transporter

278.8

AN7962

Metalloproteinase (pepJ)

22.7

AN9224

Monooxygenase

8.6

AN10026

Oxidoreductase

252.5

AN9042

Mutanase

21.7

AN9493

Putative acetyltransferase (ngn12)

7.0

AN11202

Putative DMATS-type aromatic prenyltransferase

107.4

AN0012

Glucuronan lyase A

20.1

AN9227

Dioxygenase associated with secondary metabolism

6.6

AN8392

Melibiase subfamily

91.6

AN7812

Putative sterigmatocystin biosynthesis protein (stcN)

19.4

AN5348

Fatty acyl-CoA reductase

6.6

AN8106

Dioxygenase associated with secondary metabolism

90.1

AN7349

Mutanase (mutA)

18.7

AN7613

Putative chitinase

6.4

AN8473

RNA polimerase II transcription factor

58.5

AN2623

Acyl-CoA:6-aminopenicillanic-acid-acyltransferase (aatA)

5.8

AN8978

Regulatory protein (alcR)

46.7

AN11013

Probable sterigmatocystin biosynthesis P450 monooxygenase (stcL)

16.4

AN2690

Putative β-1,3-glucanase

5.5

AN8084

MFS transporter

35.0

AN3931

Meiotic expression up-regulated protein 14 (pilB)

5.0

AN8520

protein required for terrequinone A biosynthesis (tdiE)

33.4

AN6835

NADPH-cytochrome P450 reductase

16.2

AN9232

MFS transporter

5.0

AN3369

Zn2-Cys6 transcription factor (clrB)

32.8

AN7811

Putative sterigmatocystin biosynthesis protein (stcO)

16.6

AN9234

Oxidoreductase associated with secondary metabolism

4.9

AN6747

C2H2 type zinc finger transcription factor

33 < FC < 87

Predicted proteins and poorly characterised genes

17 < FC < 147

Predicted proteins and poorly characterised genes

4 < FC < 8

Predicted proteins and poorly characterised genes

AN1532, AN8995, AN6476, AN9301, AN7235, AN2330, AN4825, AN2913, AN0461, AN8656, AN1666, AN0488, AN1952

AN6020, AN4970, AN7958, AN7957, AN5292, AN5319, AN8037, AN1155, AN2400, AN2710, AN7655, AN8162, AN9235, AN11163, AN1946

AN7419, AN7092, AN2779, AN3881, AN7091, AN7395, AN8955, AN2658, AN2859, AN1719, AN2376, AN5422

Down-regulated

-39.5

AN0399

Nitrate transporter (nrtB)

-18.6

AN7824

Probable sterigmatocystin biosynthesis P450 monooxygenase (stcB)

-13.1

AN2583

Glyceraldehyde 3-phosphate dehydrogenase

-35.9

AN1008

Nitrate transporter (crnA)

-18.1

AN8356

Alcohol dehydrogenase

-9.8

AN1666

Nucleolar GTP-binding protein 2

-35.4

AN1006

Nitrate reductase (niaD)

-14.1

AN7804

Putative sterigmatocystin biosynthesis monooxygenase (stcW)

-8.6

AN2861

Putative F-box protein

-26.1

AN7539

Hydrophobin

-12.6

AN7818

Probable sterigmatocystin biosynthesis P450 monooxygenase (stcF)

-6.3

AN5228

NADH:flavin oxidoreductase/NADH oxidase

-24.4

AN7392

Choline transporter Hnm1

-11.8

AN7807

Putative sterigmatocystin biosynthesis protein (stcT)

-11.5

AN7815

Fatty acid synthase subunit α

-5.6

AN4180

MFS transporter

-11.4

AN5860

MFS monosaccharide transporter (mstE)

-24.1

AN2859

Dihydrodipicolinate synthetase

-11.2

AN7825

Putative sterigmatocystin biosynthesis polyketide synthase (stcA)

-5.6

AN10619

Glutamate decarboxylase

-11.2

AN4135

Stearoyl-CoA desaturase (sdeB)

-23.9

AN4131

Na+/H+ antiporter

-11.1

AN7814

Fatty acid synthase subunit β

-5.5

AN7169

Flavohemoprotein (fhbA)

-23.8

AN7278

Glutamate decarboxylase

-10.8

AN7806

Versicolorin reductase

-21.7

AN4119

MFS multidrug transporter

-10.6

AN3763

Siderochrome-iron transporter

-5.5

AN3264

MFS multidrug transporter

-19.0

AN3776

MFS transporter

-10.0

AN7811

Putative sterigmatocystin biosynthesis protein (stcO)

-61 < FC < -18

Predicted proteins and poorly characterised genes

-28 < FC < -10

Predicted protein and poorly characterised genes

-16 < FC < -5

Predicted protein and poorly characterised genes

AN2595, AN7214, AN5305, AN8081, AN6946, AN4108, AN7378, AN9220, AN6128, AN8981, AN3333, AN6930, AN4128, AN6932, AN8670

AN7397, AN3251, AN8544, AN6661, AN7817, AN8314, AN2722, AN0169, AN7812, AN7809, AN7915, AN11013

AN2571, AN9310, AN7949, AN5489, AN0421, AN0461, AN9102, AN9378, AN7960, AN3305, AN0728, AN0247, AN0288, AN8974, AN0838, AN8544, AN3314

Table 2

List of the extracellular protein species identified in the secretome of Aspergillus nidulans at the last time point of growth on suberin

Gene number

Description

MW [kDa]

calc. pI

SignalPa

SwissProt

NCBI

Microarray data*

Total peptides

Cov (%)

Total peptides

Cov (%)

Firstc

Midc

Lastc

Plant Polymer Degrading Enzymes

AN5309

Cutinase (Cut1)

22.4

7.3

Y

3

12.21

2

9.09

305.8

-3

1.5

AN8046

Triacylglycerol lipase

31.3

4.6

Y

-b

-b

7

47.28

10.4

-1.6

2.7

AN3613

β-1,4-xylanase (XlnA)

24.1

6.3

Y

4

36

4

36

6.5

-2.2

-1.1

AN7401

β-1,4-endoxylanase (XlnE)

37.7

5.5

Y

-b

-b

3

11.83

-1.3

-1.4

1

AN1818

β-1,4-xylanase C (XlnC)

35.4

5.2

Y

5

20.49

-b

-b

1.2

-1.2

-1.3

AN8477

β -1,4-xylosidase

60.3

5.4

N

-b

-b

4

9.71

1.6

1.1

1.1

AN2828

β-glucosidase L (BglL)

77.8

4.8

Y

14

21.71

12

22.52

-1.2

-1.3

2.4

Fungal Development

AN0472

β-1,3-endoglucanase A (EngA)

97.8

5.7

Y

-b

-b

6

8.49

5.8

1.1

1.2

AN7950

β-1,3-endoglucosidase (EglC)

46.7

4.6

Y

10

28.39

10

28.39

-d

-d

-d

AN4825

β-1,3-glucosidase

96.5

5.5

Y

-b

-b

11

17

42.5

1.1

1.2

AN2395

β-glucuronidase

68.5

4.8

Y

-b

-b

14

28.06

7.4

-1.4

1.2

AN4871

Chitinase B (ChiB)

44.2

5.6

Y

-b

-b

34

80.65

12.7

1.4

1.1

AN2017

α-glucosidase (AgdA)

109.6

5.2

Y

-b

-b

6

8.17

-1.5

-1.9

2.3

AN8445

Aminopeptidase Y

53.7

6.8

Y

-b

-b

6

19.68

1.8

-1.5

1.6

AN2366

Serine protease

25.4

4.4

Y

-b

-b

3

17.27

-d

-d

-d

AN5558

Alkaline serine protease (PrtA)

42.2

5.3

Y

8

32.75

7

32.75

5.4

1.3

1.1

AN7962

Metalloproteinase (PepJ)

37.4

5.1

N

6

18.36

6

18.36

278.8

1.8

1.2

AN4245

Ceramidase

80

5

Y

-b

-b

7

14.8

1.6

1.5

1.8

AN9339

Catalase B (CatB)

79.1

5.1

Y

23

35.6

20

34.54

-2.4

1.8

1

Miscellaneous

AN3351

Uncharacterised

63.2

5.1

Y

-b

-b

5

12.91

1.6

-1.4

-1.1

AN3246

Uncharacterised

22.3

6.4

N

-b

-b

4

29.8

2

-1.3

2

AN6273

Allergenic Asp F13

16.3

4.8

Y

-b

-b

3

32.91

-1

-1.5

-1.4

AN5879

Phosphatidylglycerol/phosphatidylinositol transfer protein

18.3

5

Y

9

53.25

9

53.25

1

1

-1

AN8979

Alcohol dehydrogenase I (AlcA)

36.9

6

N

5

25.57

5

25.57

-15.1

-8.8

1

AN8043

Uncharacterised

16.9

4.8

N

-b

-b

3

26.42

-4

-2

-1

aSignalP was used to predict secretion signals [67, 68] and bnot found in the database search. Corresponding microarray data are shown for comparison. *Values highlighted in bold have |FC| > 2 and p-value < 0.01 in the microarray data; cFold changes (FCs) in pair-wise comparison of consecutive time points; dnot represented in the chip.

Table 3

q RT-PCR analysis of a selected set of genes coding putative lipid hydrolysing enzymes or major regulatory proteins

Carbon source

Gene

Encoded protein

qRT-PCR

Microarray*

   

Firstd

Midd

Lastd

Firstd

Midd

Lastd

Suberin

AN6195

CreA

8.3

-2.3

-1.9

4.3

-1.4

-1.6

AN1052

VeA

2.5

-1.0

-1.0

2.6

-1.3

1.0

AN7050

FarA

2.3

-1.7

1.3

2.8

-1.7

1.3

AN5309

Cut1

119.9

-3.1

1.8

305.8

-3.0

1.5

AN7541

Cut2

-1.5

-1.0

1.5

-1.3

-1.1

1.1

AN7180

Cutinase

1.2

1.1

1.9

1.3

-1.2

-1.1

AN5267

FaeC

3.2

-2.1

1.7

3.0

-2.4

1.1

AN2697

Putative lipasea

-1.8

1.4

1.8

1.6

-1.7

-1.1

AN5777

Putative lipase

2.9

1.0

1.7

2.9

-1.2

1.6

AN8046

Putative lipase

4.1

-1.1

2.3

10.4

-1.6

2.7

AN8900

Putative lipaseb

-1.8

1.7

1.5

1.6

1.6

-1.1

AN4748

Uncharacterised proteinc

31.8

-1.8

-3.8

24.6

-1.7

-4.5

Glyceryl tripalmitate

AN5309

Cut1

1.4

36.4

-7.8

   

AN7541

Cut2

2.7

-3.8

-1.3

   

AN7050

FarA

3.7

-1.7

-1.7

   

AN8046

Putative lipase

8.2

2.3

-19.4

   

Octyl octanoate

AN5309

Cut1

3.3

14.0

-1.6

   

AN7541

Cut2

4.1

-1.2

-3.0

   

AN7050

FarA

2.7

-1.3

-1.4

   
 

AN8046

Putative lipase

2.8

5.8

-11.7

   

Values represent the relative expression of selected genes in pair-wise comparisons of consecutive time points. The expression of each gene was normalised by the expression of the 60S ribosomal protein L33-A gene (AN2980).

* Values highlighted in bold have |FC| > 2 and p-value < 0.01 in the microarray data; acontains feruloyl esterase and tannase domains, high homology with feruloyl esterase B in N. crassa; borthologue of A. niger An09g02270, which encodes a triacylglycerol lipase; corthologue of S. cerevisiae NOP6, which is necessary for rRNA-binding protein required for 40S ribosomal subunit biogenesis.dFold changes (FCs) in pair-wise comparison of consecutive time points. Corresponding microarray data are shown for comparison.

Table 4

List of Aspergillus nidulans differentially expressed genes (pair-wise comparison of consecutive time points), putatively involved in suberin degradation

Gene number

Description (gene name)

Microarray data*

Sub-cellular locationa

Number of predicted binding sites for farA

Firstd

Midd

Lastd

Lipid Hydrolysis & Transport

Cutinases

 

AN5309

Cutinase 1 (cut 1)

305.8

-3.0

1.5

Extracellular

4b, 4c

AN7180

Cutinase

1.3

-1.2

-1.1

Extracellular

2b, 2c

AN7541

Cutinase (cut2)

-1.3

-1.1

1.1

Extracellular

3b, 3c

AN10346

Cutinase

1.5

-1.4

-1.3

Extracellular

2b

Other extracellular esterases

    

AN1799

Triacylglycerol lipase

22.3

-1.9

1.6

Extracellular

1b

AN2602

Lipase/esterase

16.9

-2.0

-3.3

Extracellular

0b

AN8046

Putative triacylglycerol lipase

10.4

-1.6

2.7

Extracellular

0b

AN6773

Putative triacylglycerol lipase

5.1

13.1

-1.4

Extracellular

1b

AN4573

Hydrolase (ester bonds)

3.5

2.2

3.2

Extracellular

0b

AN5777

Triacylglycerol lipase

2.9

1.2

1.6

Extracellular

0b

AN6464

Hydrolase (ester bonds)

2.3

-1.5

1.0

Extracellular

1b

AN7158

Hydrolase (ester bonds)

-2.2

-1.1

-1.1

Extracellular

0b

AN5321

Triacylglycerol lipase

-1.5

2.8

1.1

Extracellular

2b

AN1433

Triacylglycerol lipase

-6.1

-1.9

1.8

Extracellular

1b

AN3037

Carboxylesterase

-7.2

1.3

2.4

Extracellular

1b

AN1792

Hydrolase (ester bonds)

-15.9

-1.4

2.3

Extracellular

1b

Transporters

    

AN6581

ABC drug exporter (atrF)

12.0

-1.3

-4.1

Membrane

1b

AN8813

ABC transporter

8.6

-2.2

1.2

Membrane

2b

AN2300

ABC multidrug transporter (atrD)

5.1

-1.1

-1.7

Membrane

0b

AN6369

ABC transporter

4.8

-1.6

-1.2

Membrane

0b

AN0771

ABC transporter

4.7

-1.3

-1.9

Membrane

0b

AN8892

ABC multidrug transporter

3.6

-3.5

-1.3

Membrane

1b

AN8489

ABC multidrug transporter

2.1

-1.3

1.2

Membrane

0b

Other genes

AN0623

Long chain fatty alcohol oxidase

1.7

13.7

-1.2

Unknown

2b

AN6795

Putative hydrophobic surface binding protein A

9.2

-2.5

1.1

Extracellular

1b

Fatty Acids β-Oxidation

Transport to the peroxisome/mitochondria

     

AN6279

Carnitine acetyltransferase (acuJ)

3.0

-1.6

-1.3

Peroxisome/mitochondria

2b, 2c

AN5356

Carnitine/acyl-carnitine carrier (acuH)

2.0

-2.6

-1.0

Mitochondria

1b, 1c

AN0257

Peroxisomal ATP carrier protein (antA)

4.2

-1.4

-1.2

Peroxisome

3b, 3c

β-oxidation cycle

     

AN5646

Acetyl-CoA acyltransferase

4.6

-1.7

-1.5

Peroxisome

1b, 1c

AN5698

Acetyl-CoA acyltransferase

-1.2

-2.2

1.3

Mitochondria

0b

AN1699

Acyl-CoA dehydrogenase

8.9

-1.1

-1.6

Peroxisome

3b, 3c

AN7320

Acyl-CoA dehydrogenase

2.4

-2.1

1.4

Peroxisome

1b

AN9162

Acyl-CoA dehydrogenase

-2.0

-1.1

1.4

Mitochondria

0b

AN6761

Acyl-CoA dehydrogenase

-2.8

1.4

1.2

Mitochondria

0b

AN2762

Acyl-CoA dehydrogenase

-2.2

-1.5

1.7

Mitochondria

1b

AN12335

Acyl-CoA dehydrogenase (acdA)

-2.7

1.6

1.2

Peroxisome

1b, 1c

AN0824

Acyl-CoA dehydrogenase (scdA)

2.1

-1.4

1.1

Mitochondria

3b, 3c

AN8280

Acyl-CoA synthetase (faaB)

7.9

-2.6

-1.4

Peroxisome

2b, 2c

AN5192

Acyl-CoA synthetase (fatA)

3.0

-2.8

1.1

Peroxisome

2b

AN4397

Acyl-CoA synthetase (fatD)

1.2

-2.3

-1.6

Peroxisome

1b

AN10512

β-ketoacyl-CoA thiolase (mthA)

1.9

-2.2

-1.8

Mitochondria

1b

AN6752

Long chain fatty acyl-CoA oxidase (aoxA)

5.7

-1.4

-1.4

Peroxisome

3b, 3c

AN2999

NADP-isocitrate dehydrogenase (idpA)

3.5

-1.5

-1.4

Peroxisome/mitochondria

1b

AN4688

Isovaleryl-CoA dehydrogenase (ivdA)

1.1

-1.5

3.0

Mitochondria

0b

Gluconeogenesis

AN6293

Transcription activator (acuM)

2.1

-1.6

1.6

Cytosol

2b

AN1918

Phosphoenolpyruvate carboxykinase (acuF)

6.8

-3.8

-1.2

Cytosol

1b

AN5604

Fructose 1,6-bisphosphatase (acuG)

1.9

-1.8

1.0

Cytosol

2b

Glyoxylate cycle

AN5634

Isocitrate lyase (acuD)

2.9

-2.2

-1.7

Peroxisome

1b,1c

AN6653

Malate synthase (acuE)

-1.2

1.2

-1.2

Peroxisome

2b,2c

Regulatory genes

AN7050

Zn2-Cys6 transcription factor (farA)

2.8

-1.7

1.3

Nucleus

0b

AN1425

Zn2-Cys6 transcription factor (farB)

4.2

-1.8

1.0

Nucleus

1b

AN1303

Zn2-Cys6 transcription factor (scfA)

-2.0

-2.8

-1.1

Nucleus

0b

AN0689

Zn2-Cys6 transcription factor (facB)

5.4

-2.4

-1.4

Nucleus

0b

*values highlighted in bold have |FC| > 2 and p-value < 0.01 in the microarray data; a) Sub-cellular location was attained using Pedant Database (http://pedant.gsf.de). bthe number of predicted binding sites for farA was manually searched according to the conserved sequence 5’-CCTCGG or its reverse complement sequence (5’-CCGAGG) within 1 Kb of the upstream region of the start codon of listed genes; cnumber of predicted binding sites as previous reported [22]. dFold changes (FCs) in pair-wise comparison of consecutive time points.

The transcriptional regulation of the assimilatory nitrate system in A. nidulans differs in high availability or limiting glucose conditions [61]. AreA is the major nitrogen regulatory protein, however, under glucose limiting conditions, the nitrogen status-sensing regulator AreB controls the expression of the nitrate catabolic genes [61, 62]. Major down-regulation of nitrate reductase niaD (AN1006) and of nitrate transporters (AN1008, AN0399) (Table 1) was consistent with the down-regulation of nitrite reductase niiA (AN1007) and the up-regulation of areB (AN6221) Additional file 2. At the last time point, the inducible nitric oxide-detoxifying flavohaemoglobin gene (AN7169, fhbA) showed major down-regulation (Table 1). This gene is co-regulated with niaD and niiA, yet its expression is AreA-independent [63, 64].

Development and secondary metabolism

During growth on suberin the mycelia mat surrounded the water-insoluble substrate, disrupting the fungal biofilm formed in the control, i.e. loss of hyphae alignment and disruption of the extracellular polysaccharide matrix (Figure 3). The expression levels of some A. nidulans orthologs of A. fumigatus genes coding in important pathways of biofilm formation were consistent with the loss of biofilm morphology [65], including major down-regulation of hydrophobin gene (AN7539) (Table 1).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-15-613/MediaObjects/12864_2014_Article_6294_Fig3_HTML.jpg
Figure 3

Microscopic analysis of Aspergillus nidulans mycelia in controls (top panels) or on suberin (bottom panels) at the first time point, showing the red safranin stain (scale bar: 137 μm) (a), the hyphal morphology (detected by SEM, scale bar: 10 μm) (b), and the total (c) and the dead (d) hyphae, shown in blue (calcofluor white stain) and red (propidium iodide stain) (scale bar: 1000 μm). Only the controls showed the typical features of fungal biofilms, namely the extracellular matrix stained with safranin and the hyphal alignment. Total and dead hyphae were alike in controls and on suberin.

Sexual development in A. nidulans was induced during growth on suberin, similar to that observed before on FAs [22]: Hülle cells and few ascospores were detected at the first and last time points, respectively; whereas cleistothecia and numerous ascospores were observed only after fifteen days of cultivation (Figure 4). The breach of cleistothecia might explain the few ascospores detected at the last time point. In agreement, mutA (mutanase associated with the use of glucose reserves during the formation of Hülle cells [66]) and AN10030 (alkaline serine protease involved in the biosynthesis of the ascopore cell wall [67, 68]) underwent major up-regulation at first and mid time points, respectively. In addition, MAT1 (AN2755) and MAT2 (AN4734) genes, which encode the transcription factors considered the master switchers of sexual development in A. nidulans[69, 70], were up-regulated at the first time point Additional file 2. The expression profile of the vast majority of genes associated with sexual development in A. nidulans, including steA (AN2290), was consistent with the onset of sexual development [71]. The few exceptions included genes signalling response to nitrogen/carbon limitation [61], namely down- and up-regulation of sexual development activators (csnB, AN4783 and noxA, AN5457) and repressors (silG, AN0709; cpcA, AN3675 and rosA, AN5170), respectively Additional file 2.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-15-613/MediaObjects/12864_2014_Article_6294_Fig4_HTML.jpg
Figure 4

SEM images of Aspergillus nidulans during growth on suberin. Hülle cells were detected at the first time point (a, b), few ascospores were detected at the last time point (c, d), and numerous ascospores (f) and cleistothecia (e) were detected after fifteen days. Untreated suberin (control) is also shown (g, h). Scale bar: 10 μm.

The expression of genes regulating fungal growth and development is known to be coordinated with those coding in the biosynthesis of asperthecin, penicillin and sterigmatocystin [72]. Moreover, exogenous addition of mannans to the growth media (oligosaccharides that might be released during autolysis) increases penicillin production in Penicillium sp. [73]. In fact, genes in asperthecin (AN6000, aptA), penicillin (AN2623) and sterigmatocystin (AN7812, AN11013 and AN7811) clusters were amongst those more profoundly affected at the first time point (Table 1). Analyses of the expression levels of the other in-cluster genes confirmed these findings, e.g. up-regulation of genes in sterigmatocystin cluster included the aflR regulator (AN7820) [74], the polyketide synthase (AN7825) and the fatty acid synthase genes (AN7814 and AN7815) Additional file 2. At the mid time point, sterigmatocystin biosynthesis probably decreased, since genes encoding the synthase (AN7825) and some auxiliary enzymes (AN7804, AN7806, AN7811, AN7818 and AN7824) become major down-regulated (Table 1). Suberin also induced major alterations in numerous genes coding in uncharacterised clusters (AN9234, AN9227, AN9230, AN11202, AN8106 and AN8520). Overall, 65 secondary metabolite gene clusters, out of the 71 estimated by now in this fungus [53], were responsive but only in a few clusters the synthase gene was largely affected. Supplementation of the growth media with suberoylanilide hydroxamic acid induced several secondary metabolite synthases in A. niger[75] and potato suberin augmented the diversity of the secondary metabolites biosynthesised by Streptomyces sp. [76].

Twelve genes involved in the control of development and carbon metabolism, as well as in suberin degradation, were selected to validate the microarray data by qRT-PCR (Table 3). The tested genes included four genes which putatively encode lipid hydrolysing enzymes (AN7541, AN7180, AN2697 and AN8900) that showed FC ≤ 2 in the microarray. All the analysed genes, with the exception of AN2697, showed a profile of expression along the cultivation similar to that of the microarray data.

Degradation of suberin: lipid hydrolysis

Several genes encoding polyester hydrolysing enzymes were induced during the fungus growth on suberin (Table 4). Data made apparent that Cut1 played the major role in suberin initial degradation: the encoding gene (AN5309) was extensively up-regulated (Table 1) and the enzyme was present in the secretome (Table 2). Cut1 hydrolyses aliphatic polyesters [77] and potato suberin [18, 19, 26]. FarA and FarB are major transcription activators of genes involved in FAs utilisation [22]. Deletion of farA (AN7050) eliminates induction of a number of genes by both small chain fatty acids (SCFAs) and LCFAs, while deletion of farB (AN1425) eliminates SCFAs induction [22]. As expected, farA and farB were both up-regulated at the first time point (Table 4). The down-regulation of scfA on suberin (Table 4, AN1303, which encodes a similar transcription factor and its deletion leads to farB deleted mutant phenotype [22]) might be explained by its repression under nitrogen limiting conditions [64]. With the exception of cut1, the expression levels of the other three cutinase genes were kept at basal levels (AN10346) or underwent minor alterations (cut2 - AN7541 and AN7180) (Tables 3 and 4). FarA regulation of A. nidulans cutinase genes might be similar to that reported in Fusarium solani[26]. In the pathogenic fungus, cut1 is strongly induced by cutin monomers under the regulation of CTF1α - which has 70% similarity with FarA and the same binding motif, CCTCGG - but cut2 and cut3 are expressed at basal levels. Similar regulation was noticed in media containing octyl octanoate or glyceryl tripalmitate as sole carbon sources (Table 3). In the suberin media major up-regulation of cut1 occurred at an earlier time point probably because it contains ca. 4 wt% of soluble “cutin-like” monomers [30, 78]. Glycerol could not be detected in the suberin culture filtrates likely because 80-90% of the acylglycerol bonds in suberin were hydrolysed during its extraction (Figure 1a) [31]. In agreement, glycerol catabolic genes [79], namely glycerol kinase (AN5589, glcA) and FAD-dependent glycerol 3-phosphate dehydrogenase (AN1396) were not differentially expressed. When glyceryl tripalmitate was used as sole carbon source, glycerol was detected, namely 0.063 ± 0.003 and 0.0201 ± 0.0018 gL-1 at the first and the last time point, respectively.

Only Cut1 and AN8046, putative lipid hydrolysing enzymes, could be detected in the secretome (Table 2). Gene expression data corroborate the hypothesis that farA regulates cut1 and AN8046 during A. nidulans utilisation of suberin (Table 4), as well as octyl octanoate or glyceryl tripalmitate (Table 3) as sole carbon sources. The farA ortholog gene of A. oryzae regulates not only cutL (cutinase gene) but also the putative lipid hydrolysing enzyme genes mdlB (ortholog of AN8046) and tglA (70% homology with AN10346) [80]. It also regulates hsbA (ortholog of AN6795) that encodes hydrophobic surface binding protein probably involved in the recruitment of CutL to the FAs surface. AN6795 was also stimulated by suberin (Table 4). In addition, during Fusarium oxysporum growth on wheat oil, the transcription factor ctf1 regulates both cut1 and lip1[81], which is amongst the lipase genes more strongly induced [82] (n.b. Lip1 shows high homology to AN8046 protein).

Several other putative lipase genes, namely AN2602, AN6464, AN5777, AN4573, AN1799, AN6773, in addition to AN2697 and AN8900 (FC < 2, Table 3) were also stimulated by suberin (Table 4). Their regulation was variable, except AN4573 (increased along the incubation) and AN6773 (increased at first and mid time points). The latter, as well as AN1799 and AN5321, have been associated with unresolved secondary metabolite gene clusters in A. nidulans[53] and likely are not involved in suberin degradation.

Eleven genes encoding ABC transporters carrying transmembrane domains were up-regulated at the first time point. ABC transporters are generally assumed to be involved in multidrug resistance, yet more recent studies have shown their physiological significance e.g. in oxidative stress response, pathogenicity and excretion of siderophore peptide breakdown products [83]. A role in penicillin secretion was proposed for the A. nidulans AtrD transporter, which belongs to the subfamily ABC-C [84]. atrD (AN2300) up-regulation at the first time point agrees with major up-regulation of penicillin synthase gene (Table 1). Up-regulation of numerous ABC-G transporter genes (AN6581, AN8813, AN6369, AN0771, AN8892 and AN8489) might imply a possible involvement in the transmembrane transport of suberin hydrolysed monomers. The function of this subfamily of transporters remains largely unknown with putative roles in e.g. excretion of hydrophobic and/or lipid molecules [85]. In addition, suberin possibly stimulated the formation of eisosomes playing a role in the endocytosis of lipid cargos [86], as suggested by the major up-regulation of pilB (AN3931) (Table 1).

Hydrolysed suberin LC fatty alcohols (Figure 1a) need further modification before entering FAs β-oxidation pathways. ω-Hydroxy fatty acid oxidation was probably mediated by NADPH-cytochrome P450 reductase fusion enzyme (AN6835), as well as by LC fatty alcohol oxidase (AN0623). Both encoding genes were up-regulated during growth on suberin (Tables 1 and 4). The first enzyme might catalyse the oxidation of the LC fatty alcohols to carboxylic acids and of mid-chain saturation functionalities to vic-diols [87, 88]. LC fatty alcohol oxidases have been shown to catalyse the oxidation of ω-hydroxy fatty alcohols in Candida cloacae[89] and the encoding genes display usually a peroxisomal targeting sequence, notwithstanding their cellular localisation in A. nidulans remains unknown. Due to different substrate specificities and/or cellular compartmentalisation, possibly AN6835 and AN0623 enzymes have acted sequentially during A. nidulans growth on suberin. The hypothesis that LC fatty alcohols undergo modification by LC fatty alcohol oxidase in the peroxisome merits further analysis.

Degradation of suberin: β-oxidation

Current understanding of FAs utilisation in A. nidulans indicates significant complexity and redundancy in β-oxidation pathways [21, 22, 90]. FAs are activated by FA-CoA synthetases to their acyl-CoA derivates, which are processed by FA-CoA oxidases or dehydrogenases. Each round of β-oxidation produces a chain-shortened fatty-acyl-CoA (which undergoes further rounds) and an acetyl-CoA, which is channelled into the tricarboxylic acid or glyoxylate cycles. In addition, β-oxidation substrates are actively transported across the mitochondria and/or the peroxisome membrane by carnitine shuttles, ADP/ATP carriers or ABC transporter proteins. Suberin stimulated two peroxisomal FA-CoA synthetase genes, namely faaB (AN8280) and fatA (AN5192) (Table 4) but none of the well characterised mitochondrial ones (e.g. facA (AN5626) and pcsA (AN5833), Additional file 2). It seems that hydrolysed suberin monomers were essentially processed via peroxisomal β-oxidation pathways (Table 4) and that, as previously suggested, FaaB is the major peroxisomal FA-CoA synthetase, while the remaining ones (FatA-D (AN5192, AN5877, AN6649, AN4397), FaaA (AN6114) and AN4659) display high functional redundancy [91]. Activation of peroxisomal β-oxidation agrees with the up-regulation of antA, a peroxisomal ATP carrier (AN0257) and of acuJ, a mitochondrial/peroxisomal carnitine acetyltransferase (AN6279) (Table 4). Uncharacterised transporters for the peroxisomal translocation of activated LCFAs have been suggested [22]; justifying the basal expression levels of pxa1 and pxa2 (AN10078 and AN1014, ABC transporter proteins).

Suberin stimulated the expression of aoxA (AN6752) but not aoxB (AN6765), both encoding peroxisomal fatty-acyl-CoA oxidases (Table 4) but AoxA plays the major role during growth on LCFAs [92]. Deletion of aoxA leads to growth impairment on LCFAs but not on SCFAs or very long chain fatty acids (VLCFAs) [21]. aoxA stimulation is consistent with the observation that suberin hydrolysis releases three times more LCFAs than VLCFAs [30, 78]. Only three peroxisomal fatty-acyl-CoA dehydrogenase genes (out of seven) were responsive at the first time point, namely acdA (AN12335), AN1699 and AN7320 genes (Table 4). Deletion of either acdA or AN7320 has not led to any growth impairment on FAs, suggesting that the encoded enzymes display high redundancy [92]. Botrytis cinerea BC1G_13535 gene, which displays 78% of homology with AN1699, was amongst the highest up-regulated genes coding in FAs β-oxidation during Lactuca sativa infection [93]. The hypothesis that this fatty-acyl-CoA dehydrogenase plays a major role in A. nidulans degradation of plant FAs calls for its functional characterisation.

LCFAs β-oxidation is shuttled between the peroxisomes and the mitochondria, typically when the produced chain-shortened fatty-acyl-CoA is a butyryl-CoA (C4) [92]. At the first time point, most mitochondrial fatty-acyl-CoA dehydrogenase genes were down-regulated (AN2762, AN6761 and AN9162), except scdA (AN0824) [22] that was up-regulated. The remaining mitochondrial β-oxidation genes, in general, decreased at the mid and/or last time points, including the well characterised mthA, a β-ketoacyl-CoA thiolase gene (AN10512), as well as acuH, a mitochondrial carnitine/acyl-carnitine carrier (AN5356) (Table 4). The only exception was ivdA, an isovaleryl-CoA dehydrogenase gene (AN4688) that was up-regulated, together with mccB (AN4687), at the last time point (Table 4). This might imply that the fungus started using leucine as a catabolic source; both genes are clustered with mccA (AN4690) in the leucine catabolic pathway [94].

The glyoxylate bypass is absolutely required for growth on carbon sources that produce acetyl-CoA and is dependent on isocitrate lyase (AcuD) and malate synthase (AcuE) activities. Transcription of acuD (AN5634) and acuE (AN6653) is regulated by FA and acetate induction via the FacB activator, but facB (AN0689) mutations do not prevent growth on FAs [22]. Up-regulation of farA and farB (FA-induced) and of facB (acetate-induced) led to up-regulation of acuD but not of acuE (Table 4). Previous studies have demonstrated that the imposition of several stresses might lead to both fluctuating mRNA and irregular protein expression levels in A. nidulans[95].

Degradation of phenolic suberin

Release of ferulic acid during fungal growth on potato suberin has been suggested to involve the activity of feruloyl esterases (Fae) [5], notwithstanding a direct proof is still lacking. Ferulic acid release probably justifies the up-regulation of faeC (AN5267) (Table 3). Ferulic acid degradation might involve the activity of 2,3-dihydroxybenzoate carboxylyase [96], of which the encoding gene dhbD (AN6723) was up-regulated at the first time point (Additional file 2). Several downstream products have been reported in different fungal strains, however the associated enzymes remain largely unknown [96]. Nevertheless, final degradation of the formed aromatics might involve the homogentisate, benzoate or the salicylate pathways [97], and several genes coding in these pathways were found to be up-regulated (e.g. AN10950, hmgA (AN1897), hpdA (AN1899), maiA (AN1895), Additional file 2) in the suberin media.

Degradation of other cell wall constituents

Several polysaccharides degrading enzymes were identified in the A. nidulans secretome on suberin at the last time point (Table 2, Additional file 4), in general, agreeing with the transcriptome data (Additional file 2). They included the β-glucosidase BglL (AN2828) and the xylanase XlnA (AN3613), of which the encoding genes were found up-regulated at the last and the first time points, respectively. The other β-glucosidase genes were up-regulated at the first (bglM, AN7396) and mid time points (eglB (AN5214) and AN3046) and could not be detected in the secretome. xlnR (AN7610), which encodes the xylanolytic/cellulolytic transcriptional activator, was up-regulated at the last time point (consistent with creA decrease [98]), notwithstanding the up-regulation of the xlnA and xlnB (AN9365) at the earlier time points. The additional polysaccharide degrading enzymes detected in the secretome were not consistent with the transcriptome data (Table 2), including XlnC (AN1818) and XlnE (AN7401). Probably the up-regulation of their corresponding genes occurred at an intermediate time point. The poor correlation between transcriptomic and proteomic data has been previously reported [95, 99], often related to mechanisms associated with mRNA turnover and/or efficiency of translation [100] or to transcription on demand of certain mRNA pools [101], among other reasons, including experimental noise [102]. Protein species grouped in the miscellaneous category (six, of which half have a predicted intracellular localisation) might be associated with cell lysis, as highlighted by the presence of alcohol dehydrogenase I (alcA, AN8979) (Table 2).

Conclusions

Previous studies on A. nidulans colonisation of cork revealed that suberin remained unaltered [103] probably because the outermost lignin-enriched cell wall layers hampered its degradation. Here we have shown that A. nidulans was able to utilise suberin macromolecules as sole carbon source (Figure 1b) and that the fungus also underwent sexual development (Figure 4) and boosted secondary metabolism (Table 1). We propose the suberin degradation and utilisation pathway in A. nidulans, as depicted schematically in Figure 5. Amongst the up-regulated genes encoding lipid hydrolysing enzymes only two were detected in the secretome, namely Cut1 and AN8046 (Tables 2, 3 and 4). In particular, out of the four cutinase genes, only cut1 expression pattern was correlated to that of farA, similar to that described in plant pathogenic fungi [22, 81]. ω-Hydroxy fatty acid oxidation reactions (mediated by either NADPH-cytochrome P450 reductase or LC fatty alcohol oxidase, Tables 1 and 4), are likely involved in the modification of suberin LC fatty alcohols, even if their cellular compartmentalisation remains uncertain. The hydrolysed suberin monomers were essentially composed of LCFAs, hence activated to their corresponding acyl-CoA derivatives probably by FaaB; the major peroxisomal fatty acyl-CoA synthetase in this fungus [92]. Despite high functional redundancy of additional peroxisomal FA-CoA synthetase genes, fatA showed the highest up-regulation on suberin. Up-regulation of aoxA also occurred, agreeing with the idea that the encoded fatty-acyl-CoA oxidase plays a major role during growth on LCFAs [21]. In addition, among the peroxisomal fatty-acyl-CoA dehydrogenase genes up-regulated here, AN1699 underwent the highest up-regulation (Table 4), similar to that reported for its B. cinerea ortholog during plant infection [93]. The core binding sequence for FarA, typically overrepresented in the promoter region of genes required for growth on FAs, is not present in all related genes up-regulated during A. nidulans growth on suberin (Table 3). Some unknown regulatory elements are certainly yet to be discovered, further emphasised by the down-regulation of some lipid hydrolysing genes carrying the FarA recognition site.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-15-613/MediaObjects/12864_2014_Article_6294_Fig5_HTML.jpg
Figure 5

Schematic view of putative suberin degradation and utilisation pathways in Aspergillus nidulans . For sake of clarity, some steps and intermediates are omitted and only the proteins of which the encoding genes were up-regulated in the first and the mid time points are represented. Uncertainties in the cellular compartmentalisation or activity of the enzyme are indicated by question marks.

Availability of supporting data

The data sets supporting the results of this article are included within the article (and its additional files).

Authors’ information

This research constitutes an important milestone of C. Silva Pereira’s team (established in 2008) that is addressing a major scientific question: How fungi perceive and interact with the environment? What makes our research approach distinctive is the merging of fundamental biology research with chemical expertise. Such multidisciplinary environment has inspired the development of a new extraction method for suberin - a structural component of the plant cell wall. Elucidating how fungi utilise and degrade plant polyesters strongly impacts on our understanding of plant-fungi interactions and nutrients cycling. Complementary to this research, we have reported that the plant polyester can be reconstituted as a material that combines bactericidal and antibiofouling properties. We are particularly interested in further elucidating plant polyesters physiological roles and to promote the clinical use of plant polyester based materials.

Abbreviations

FC: 

Fold change

FAs: 

Fatty acids

SCFAs: 

Small chain fatty acids

LCFAs: 

Long chain fatty acids

VLCFAs: 

Very long chain fatty acids

ATR-FTIR: 

Attenuated total reflectance Fourier transform infrared spectroscopy

SEM: 

Scanning electron microscopy

qRT-PCR: 

Quantitative real-time PCR analysis

MIPS: 

Munich Information Center for Protein Sequences.

Declarations

Acknowledgements

The work was partially supported by a grant from Iceland, Liechtenstein and Norway through the EEA financial mechanism (Project PT015), and FCT through the grants PEst-OE/EQB/LA0004/2013, PTDC/QUI-QUI/120982/2010 and PTDC/AAC-CLI/119100/2010.

IM, DOH, PCA and RF are grateful to Fundação para a Ciência e a Tecnologia (FCT), Portugal, for the fellowships SFRH/BD/38378/2007, SFRH/BD/66396/2009, SFRH/BD/66030/2009, SFRH/BD/48286/2008, respectively and HG to Fundação Calouste Gulbenkian, Portugal for the fellowship 21-95587-B. We are thankful to Dr. Tiago Martins (ITQB), who read and critically commented the final manuscript.

Authors’ Affiliations

(1)
Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa
(2)
Instituto de Biologia Experimental e Tecnológica (iBET)
(3)
Proteomics Platform, Centre de Recherche Public - Gabriel Lippmann
(4)
Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS
(5)
Instituto Gulbenkian de Ciência
(6)
previously, the Scientific Computing department, Samuel Roberts Noble Foundation

References

  1. Heredia A, Matas A, Dominguez E: Investigating plant lipid biopolymers. Biochem Educ. 2000, 28 (1): 50-51.PubMedGoogle Scholar
  2. Winkler A, Haumaier L, Zech W: Insoluble alkyl carbon components in soils derive mainly from cutin and suberin. Org Geochem. 2005, 36 (4): 519-529.Google Scholar
  3. Hamer U, Rumpel C, Dignac MF: Cutin and suberin biomarkers as tracers for the turnover of shoot and root derived organic matter along a chronosequence of Ecuadorian pasture soils. Eur J Soil Sci. 2012, 63 (6): 808-819.Google Scholar
  4. Harms H, Schlosser D, Wick LY: Untapped potential: exploiting fungi in bioremediation of hazardous chemicals. Nat Rev Microbiol. 2011, 9 (3): 177-192.PubMedGoogle Scholar
  5. Kolattukudy PE, Scheper T, Babel W, Steinbüchel A: Polyesters in higher plants. Biopolyesters. 2001, 71: 1-49.Google Scholar
  6. Pereira H: Cork: Biology, Production and Uses. 2007, Amsterdam: ElsevierGoogle Scholar
  7. van Fleet DS: Histochemistry and function of the endodermis. Bot Rev. 1961, 27 (2): 165-220.Google Scholar
  8. Yeats TH, Rose JKC: The formation and function of plant cuticles. Plant Physiol. 2013, 163 (1): 5-20.PubMed CentralPubMedGoogle Scholar
  9. Schreiber L: Transport barriers made of cutin, suberin and associated waxes. Trends Plant Sci. 2010, 15 (10): 546-553.PubMedGoogle Scholar
  10. Pollard M, Beisson F, Li YH, Ohlrogge JB: Building lipid barriers: biosynthesis of cutin and suberin. Trends Plant Sci. 2008, 13 (5): 236-246.PubMedGoogle Scholar
  11. Javelle M, Vernoud V, Rogowsky PM, Ingram GC: Epidermis: the formation and functions of a fundamental plant tissue. New Phytol. 2011, 189 (1): 17-39.PubMedGoogle Scholar
  12. Kolattukudy PE: Biopolyester membranes of plants: cutin and suberin. Science. 1980, 208 (4447): 990-1000.PubMedGoogle Scholar
  13. Lulai EC, Corsini DL: Differential deposition of suberin phenolic and aliphatic domains and their roles in resistance to infection during potato tuber (Solanum tuberosum L.) wound-healing. Physiol Mol Plant Pathol. 1998, 53 (4): 209-222.Google Scholar
  14. Ranathunge K, Schreiber L, Franke R: Suberin research in the genomics era: new interest for an old polymer. Plant Sci. 2011, 180 (3): 399-413.PubMedGoogle Scholar
  15. Garcia H, Ferreira R, Martins C, Sousa AF, Freire CSR, Silvestre AJD, Kunz W, Rebelo LPN, Silva Pereira C: Ex situ reconstitution of the plant biopolyester suberin as a film. Biomacromolecules. 2014, 15 (5): 1806-1813.PubMedGoogle Scholar
  16. Graça J, Schreiber L, Rodrigues J, Pereira H: Glycerol and glyceryl esters of ω-hydroxyacids in cutins. Phytochemistry. 2002, 61 (2): 205-215.PubMedGoogle Scholar
  17. Graça J, Lamosa P: Linear and branched poly(ω-hydroxyacid) esters in plant cutins. J Agr Food Chem. 2010, 58 (17): 9666-9674.Google Scholar
  18. Fernando G, Zimmermann W, Kolattukudy PE: Suberin-grown Fusarium solani f. sp pisi generates a cutinase-like esterase which depolymerizes the aliphatic components of suberin. Physiol Mol Plant Pathol. 1984, 24 (2): 143-155.Google Scholar
  19. Kontkanen H, Westerholm-Parvinen A, Saloheimo M, Bailey M, Rättö M, Mattila I, Mohsina M, Kalkkinen N, Nakari-Setälä T, Buchert J: Novel Coprinopsis cinerea polyesterase that hydrolyzes cutin and suberin. Appl Environ Microb. 2009, 75 (7): 2148-2157.Google Scholar
  20. Garcia Lepe R, Nuero OM, Reyes F, Santamaria F: Lipases in autolysed cultures of filamentous fungi. Lett Appl Microbiol. 1997, 25 (2): 127-130.PubMedGoogle Scholar
  21. Maggio-Hall LA, Keller NP: Mitochondrial β-oxidation in Aspergillus nidulans. Mol Microbiol. 2004, 54 (5): 1173-1185.PubMedGoogle Scholar
  22. Hynes MJ, Murray SL, Duncan A, Khew GS, Davis MA: Regulatory genes controlling fatty acid catabolism and peroxisomal functions in the filamentous fungus Aspergillus nidulans. Eukaryot Cell. 2006, 5 (5): 794-805.PubMed CentralPubMedGoogle Scholar
  23. Purdy R, Kolattukudy P: Hydrolysis of plant cuticle by plant pathogens. Properties of cutinase I, cutinase II, and a nonspecific esterase isolated from Fusarium solani pisi. Biochemistry. 1975, 14 (13): 2832-2840.PubMedGoogle Scholar
  24. Fan C-Y, Köller W: Diversity of cutinases from plant pathogenic fungi: diferential and sequential expression of cutinolytic esterases by Alternaria brassicicola. FEMS Microbiol Lett. 1998, 158 (1): 33-38.Google Scholar
  25. Bonnen AM, Hammerschmidt R: Cutinolytic enzymes from Colletotrichum lagenarium. Physiol Mol Plant Pathol. 1989, 35 (6): 463-474.Google Scholar
  26. Li D, Sirakova T, Rogers L, Ettinger WF, Kolattukudy PE: Regulation of constitutively expressed and induced cutinase genes by different zinc finger transcription factors in Fusarium solani f. sp. pisi (Nectria haematococca). J Biol Chem. 2002, 277: 7905-7912.PubMedGoogle Scholar
  27. Castro-Ochoa D, Peña-Montes C, González-Canto A, Alva-Gasca A, Esquivel-Bautista R, Navarro-Ocaña A, Farrés A: ANCUT2, an extracellular cutinase from Aspergillus nidulans induced by olive oil. Appl Biochem Biotechnol. 2012, 166: 1275-1290.PubMedGoogle Scholar
  28. Yang S, Xu H, Yan Q, Liu Y, Zhou P, Jiang Z: A low molecular mass cutinase of Thielavia terrestris efficiently hydrolyzes poly(esters). J Ind Microbiol Biotechnol. 2013, 40: 217-226.PubMedGoogle Scholar
  29. Garcia H, Ferreira R, Petkovic M, Ferguson JL, Leitão MC, Gunaratne HQ, Seddon K, Rebelo L, Silva Pereira C: Dissolution of cork biopolymers in biocompatible ionic liquids. Green Chem. 2010, 12: 367-369.Google Scholar
  30. Ferreira R, Garcia H, Sousa AF, Freire CSR, Silvestre AJD, Rebelo LPN, Silva Pereira C: Isolation of suberin from birch outer bark and cork using ionic liquids: a new source of macromonomers. Ind Crop Prod. 2013, 44: 520-527.Google Scholar
  31. Ferreira R, Garcia H, Sousa AF, Guerreiro M, Duarte FJS, Freire CSR, Calhorda MJ, Silvestre AJD, Rebelo LPN, Silva Pereira C: Unravelling the dual role of cholinium hexanoate ionic liquid as solvent and catalyst in suberin depolymerization. RSC Adv. 2014, 4 (1): 2993-3002.Google Scholar
  32. Ferreira R, Garcia H, Sousa AF, Petkovic M, Lamosa P, Freire CSR, Silvestre AJD, Rebelo LPN, Silva Pereira C: Suberin isolation from cork using ionic liquids: characterisation of ensuing products. New J Chem. 2012, 36 (10): 2014-2024.Google Scholar
  33. Carvalho MB, Martins I, Medeiros J, Tavares S, Planchon S, Renaut J, Nuñez O, Gallart-Ayala H, Galceran MT, Hursthouse A, Silva Pereira C: The response of Mucor plumbeus to pentachlorophenol: a toxicoproteomics study. J Proteomics. 2013, 78: 159-171.PubMedGoogle Scholar
  34. Petkovic M, Hartmann DO, Adamová G, Seddon KR, Rebelo LPN, Silva Pereira C: Unravelling the mechanism of toxicity of alkyltributylphosphonium chlorides in Aspergillus nidulans conidia. New J Chem. 2012, 36 (1): 56-63.Google Scholar
  35. Seidler M, Salvenmoser S, Müller FM: In vitro effects of micafungin against Candida biofilms on polystyrene and central venous catheter sections. Int J Antimicrob Agents. 2006, 28 (6): 568-573.PubMedGoogle Scholar
  36. Carvalho MB, Martins I, Leitão MC, Garcia H, Rodrigues C, Romão VS, McLellan I, Hursthouse A, Silva Pereira C: Screening pentachlorophenol degradation ability by environmental fungal strains belonging to the phyla Ascomycota and Zygomycota. J Ind Microbiol Biotechnol. 2009, 36 (10): 1249-1256.PubMedGoogle Scholar
  37. Hartmann DO, Silva Pereira C: A molecular analysis of the toxicity of alkyltributylphosphonium chlorides in Aspergillus nidulans. New J Chem. 2013, 37 (5): 1569-1577.Google Scholar
  38. Edgar R, Domrachev M, Lash AE: Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002, 30 (1): 207-210.PubMed CentralPubMedGoogle Scholar
  39. Li C, Wong WH: Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc Natl Acad Sci U S A. 2001, 98 (1): 31-36.PubMed CentralPubMedGoogle Scholar
  40. Li C, Wong WH: Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application. Genome Biol. 2001, 2 (8): 1-11.Google Scholar
  41. Priebe S, Linde J, Albrecht D, Guthke R, Brakhage AA: FungiFun: a web-based application for functional categorization of fungal genes and proteins. Fungal Genet Biol. 2011, 48 (4): 353-358.PubMedGoogle Scholar
  42. Emri T, Szilágyi M, László K, M-Hamvas M, Pócsi I: PepJ is a new extracellular proteinase of Aspergillus nidulans. Folia Microbiol. 2009, 54 (2): 105-109.Google Scholar
  43. Szilágyi M, Kwon NJ, Bakti F, M-Hamvas M, Jámbrik K, Park H, Pócsi I, Yu JH, Emri T: Extracellular proteinase formation in carbon starving Aspergillus nidulans cultures - physiological function and regulation. J Basic Microbiol. 2011, 51 (6): 625-634.PubMedGoogle Scholar
  44. Pusztahelyi T, Molnár Z, Emri T, Klement É, Miskei M, Kerékgyártó J, Balla J, Pócsi I: Comparative studies of differential expression of chitinolytic enzymes encoded by chiA, chiB, chiC and nagA genes in Aspergillus nidulans. Folia Microbiol. 2006, 51 (6): 547-554.Google Scholar
  45. Shin KS, Kwon NJ, Kim YH, Park HS, Kwon GS, Yu JH: Differential roles of the ChiB chitinase in autolysis and cell death of Aspergillus nidulans. Eukaryot Cell. 2009, 8 (5): 738-746.PubMed CentralPubMedGoogle Scholar
  46. Szilágyi M, Kwon NJ, Dorogi C, Pócsi I, Yu JH, Emri T: The extracellular β-1,3-endoglucanase EngA is involved in autolysis of Aspergillus nidulans. J Appl Microbiol. 2010, 109 (5): 1498-1508.PubMedGoogle Scholar
  47. Szilágyi M, Miskei M, Karányi Z, Lenkey B, Pócsi I, Emri T: Transcriptome changes initiated by carbon starvation in Aspergillus nidulans. Microbiol (UK). 2013, 159: 176-190.Google Scholar
  48. Muzzarelli RAA, Miliani M, Cartolari M, Tarsi R, Tosi G, Muzzarelli C: Polyuronans obtained by regiospecific oxidation of polysaccharides from Aspergillus niger, Trichoderma reesei and Saprolegnia sp. Carbohyd Polym. 2000, 43 (1): 55-61.Google Scholar
  49. Tsiatsiani L, Van Breusegem F, Gallois P, Zavialov A, Lam E, Bozhkov PV: Metacaspases. Cell Death Differ. 2011, 18 (8): 1279-1288.PubMed CentralPubMedGoogle Scholar
  50. Uren AG, O’Rourke K, Aravind L, Pisabarro MT, Seshagiri S, Koonin EV, Dixit VM: Identification of paracaspases and metacaspases: two ancient families of caspase-like proteins, one of which plays a key role in MALT lymphoma. Mol Cell. 2000, 6 (4): 961-967.PubMedGoogle Scholar
  51. Savoldi M, Malavazi I, Soriani FM, Capellaro JL, Kitamoto K, da Silva Ferreira ME, Goldman MHS, Goldman GH: Farnesol induces the transcriptional accumulation of the Aspergillus nidulans Apoptosis Inducing Factor (AIF) like mitochondrial oxidoreductase. Mol Microbiol. 2008, 70 (1): 44-59.PubMedGoogle Scholar
  52. Ren Q, Chen K, Paulsen IT: TransportDB: a comprehensive database resource for cytoplasmic membrane transport systems and outer membrane channels. Nucleic Acids Res. 2007, 35: D274-D279.PubMed CentralPubMedGoogle Scholar
  53. Inglis DO, Binkley J, Skrzypek MS, Arnaud MB, Cerqueira GC, Shah P, Wymore F, Wortman JR, Sherlock G: Comprehensive annotation of secondary metabolite biosynthetic genes and gene clusters of Aspergillus nidulans, A. fumigatus, A. niger and A. oryzae. BMC Microbiol. 2013, 13: 91-PubMed CentralPubMedGoogle Scholar
  54. Forment JV, Flipphi M, Ramón D, Ventura L, MacCabe AP: Identification of the mstE gene encoding a glucose inducible, low affinity glucose transporter in Aspergillus nidulans. J Biol Chem. 2006, 281 (13): 8339-8346.PubMedGoogle Scholar
  55. Dowzer CEA, Kelly JM: Analysis of the CreA gene, a regulator of carbon catabolite repression in Aspergillus nidulans. Mol Cell Biol. 1991, 11 (11): 5701-5709.PubMed CentralPubMedGoogle Scholar
  56. David H, Krogh AM, Roca C, Akesson M, Nielsen J: CreA influences the metabolic fluxes of Aspergillus nidulans during growth on glucose and xylose. Microbiol (UK). 2005, 151: 2209-2221.Google Scholar
  57. Strauss J, Horvath HK, Abdallah BM, Kindermann J, Mach RL, Kubicek CP: The function of CreA, the carbon catabolite repressor of Aspergillus nidulans, is regulated at the transcriptional and post-transcriptional level. Mol Microbiol. 1999, 32 (1): 169-178.PubMedGoogle Scholar
  58. Hynes MJ, Szewczyk E, Murray SL, Suzuki Y, Davis MA, Lewis HMS: Transcriptional control of gluconeogenesis in Aspergillus nidulans. Genetics. 2007, 176 (1): 139-150.PubMed CentralPubMedGoogle Scholar
  59. Meijer S, Panagiotou G, Olsson L, Nielsen J: Physiological characterization of xylose metabolism in Aspergillus niger under oxygen-limited conditions. Biotechnol Bioeng. 2007, 98 (2): 462-475.PubMedGoogle Scholar
  60. Felenbok B, Sequeval D, Mathieu M, Sibley S, Gwynne DI, Davies RW: The ethanol regulon in Aspergillus nidulans - characterization and sequence of the positive regulatory gene alcR. Gene. 1988, 73 (2): 385-396.PubMedGoogle Scholar
  61. Macios M, Caddick MX, Weglenski P, Scazzocchio C, Dzikowska A: The GATA factors AREA and AREB together with the co-repressor NMRA, negatively regulate arginine catabolism in Aspergillus nidulans in response to nitrogen and carbon source. Fungal Genet Biol. 2012, 49 (3): 189-198.PubMedGoogle Scholar
  62. Wong KH, Hynes MJ, Davis MA: Recent advances in nitrogen regulation: a comparison between Saccharomyces cerevisiae and filamentous fungi. Eukaryot Cell. 2008, 7 (6): 917-925.PubMed CentralPubMedGoogle Scholar
  63. Berger H, Basheer A, Böck S, Reyes-Dominguez Y, Dalik T, Altmann F, Strauss J: Dissecting individual steps of nitrogen transcription factor cooperation in the Aspergillus nidulans nitrate cluster. Mol Microbiol. 2008, 69 (6): 1385-1398.PubMedGoogle Scholar
  64. Schinko T, Berger H, Lee W, Gallmetzer A, Pirker K, Pachlinger R, Buchner I, Reichenauer T, Güldener U, Strauss J: Transcriptome analysis of nitrate assimilation in Aspergillus nidulans reveals connections to nitric oxide metabolism. Mol Microbiol. 2010, 78 (3): 720-738.PubMed CentralPubMedGoogle Scholar
  65. Muszkieta L, Beauvais A, Pähtz V, Gibbons JG, Anton Leberre V, Beau R, Shibuya K, Rokas A, Francois JM, Kniemeyer O, Brakhage AA, Latge JP: Investigation of Aspergillus fumigatus biofilm formation by various “omics” approaches. Front Microbiol. 2013, 4: 13-PubMed CentralPubMedGoogle Scholar
  66. Wei HJ, Scherer M, Singh A, Liese R, Fischer R: Aspergillus nidulans α-1,3 glucanase (mutanase), mutA, is expressed during sexual development and mobilizes mutan. Fungal Genet Biol. 2001, 34 (3): 217-227.PubMedGoogle Scholar
  67. Arnaud M, Chibucos M, Costanzo M, Crabtree J, Inglis D, Lotia A, Orvis J, Shah P, Skrzypek M, Binkley G, Miyasato SR, Wortman JR, Sherlock G: The Aspergillus Genome Database, a curated comparative genomics resource for gene, protein and sequence information for the Aspergillus research community. Nucleic Acids Res. 2010, 38 (Database issue): D420-427.PubMed CentralPubMedGoogle Scholar
  68. Apweiler R, Martin MJ, O’Donovan C, Magrane M, Alam-Faruque Y, Alpi E, Antunes R, Arganiska J, Casanova EB, Bely B, Apweiler R, Martin MJ, O’Donovan C, Magrane M, Alam-Faruque Y, Alpi E, Antunes R, Arganiska J, Casanova EB, Bely B, Bingley M, Bonilla C, Britto R, Bursteinas B, Chan WM, Chavali G, Cibrian-Uhalte E, Da Silva A, De Giorgi M, Dimmer E, et al: Update on activities at the Universal Protein Resource (UniProt) in 2013. Nucleic Acids Res. 2013, 41 (D1): D43-D47.Google Scholar
  69. Dyer PS, O’Gorman CM: Sexual development and cryptic sexuality in fungi: insights from Aspergillus species. FEMS Microbiol Rev. 2012, 36 (1): 165-192.PubMedGoogle Scholar
  70. Krijgsheld P, Bleichrodt R, van Veluw GJ, Wang F, Müller WH, Dijksterhuis J, Wosten HAB: Development in Aspergillus. Stud Mycol. 2013, 74 (1): 1-29.PubMed CentralPubMedGoogle Scholar
  71. Paoletti M, Seymour FA, Alcocer MJC, Kaur N, Caivo AM, Archer DB, Dyer PS: Mating type and the genetic basis of self-fertility in the model fungus Aspergillus nidulans. Curr Biol. 2007, 17 (16): 1384-1389.PubMedGoogle Scholar
  72. Bayram O, Braus GH: Coordination of secondary metabolism and development in fungi: the velvet family of regulatory proteins. FEMS Microbiol Rev. 2012, 36 (1): 1-24.PubMedGoogle Scholar
  73. Ariyo B, Tamerler C, Bucke C, Keshavarz T: Enhanced penicillin production by oligosaccharides from batch cultures of Penicillium chrysogenum in stirred-tank reactors. FEMS Microbiol Lett. 1998, 166 (1): 165-170.PubMedGoogle Scholar
  74. Yin W-B, Amaike S, Wohlbach DJ, Gasch AP, Chiang Y-M, Wang CCC, Bok JW, Rohlfs M, Keller NP: An Aspergillus nidulans bZIP response pathway hardwired for defensive secondary metabolism operates through aflR. Mol Microbiol. 2012, 83 (5): 1024-1034.PubMed CentralPubMedGoogle Scholar
  75. Fisch KM, Gillaspy AF, Gipson M, Henrikson JC, Hoover AR, Jackson L, Najar FZ, Waegele H, Cichewicz RH: Chemical induction of silent biosynthetic pathway transcription in Aspergillus niger. J Ind Microbiol Biotechnol. 2009, 36 (9): 1199-1213.PubMedGoogle Scholar
  76. Lerat S, Forest M, Lauzier A, Grondin G, Lacelle S, Beaulieu C: Potato suberin induces differentiation and secondary metabolism in the genus Streptomyces. Microbes Environ. 2012, 27 (1): 36-42.PubMed CentralPubMedGoogle Scholar
  77. Baker PJ, Poultney C, Liu Z, Gross R, Montclare JK: Identification and comparison of cutinases for synthetic polyester degradation. Appl Microbiol Biotechnol. 2012, 93 (1): 229-240.PubMedGoogle Scholar
  78. Gandini A, Pascoal Neto C, Silvestre AJD: Suberin: a promising renewable resource for novel macromolecular materials. Prog Polym Sci. 2006, 31 (10): 878-892.Google Scholar
  79. Salazar M, Vongsangnak W, Panagiotou G, Andersen MR, Nielsen J: Uncovering transcriptional regulation of glycerol metabolism in Aspergilli through genome-wide gene expression data analysis. Mol Genet Genomics. 2009, 282 (6): 571-586.PubMedGoogle Scholar
  80. Garrido SM, Kitamoto N, Watanabe A, Shintani T, Gomi K: Functional analysis of FarA transcription factor in the regulation of the genes encoding lipolytic enzymes and hydrophobic surface binding protein for the degradation of biodegradable plastics in Aspergillus oryzae. J Biosci Bioeng. 2012, 113 (5): 549-555.PubMedGoogle Scholar
  81. Rocha ALM, Di Pietro A, Ruiz-Roldan C, Roncero MIG: Ctf1, a transcriptional activator of cutinase and lipase genes in Fusarium oxysporum is dispensable for virulence. Mol Plant Pathol. 2008, 9 (3): 293-304.PubMedGoogle Scholar
  82. Bravo-Ruiz G, Ruiz-Roldan C, Roncero MIG: Lipolytic System of the Tomato Pathogen Fusarium oxysporum f. sp. lycopersici. Mol Plant Microbe In. 2013, 26 (9): 1054-1067.Google Scholar
  83. Kovalchuk A, Driessen AJM: Phylogenetic analysis of fungal ABC transporters. BMC Genomics. 2010, 11 (1): 177-PubMed CentralPubMedGoogle Scholar
  84. Andrade AC, Van Nistelrooy JGM, Peery RB, Skatrud PL, De Waard MA: The role of ABC transporters from Aspergillus nidulans in protection against cytotoxic agents and in antibiotic production. Mol Gen Genet. 2000, 263 (6): 966-977.PubMedGoogle Scholar
  85. Holyoak CD, Bracey D, Piper PW, Kuchler K, Coote PJ: The Saccharomyces cerevisiae weak acid inducible ABC transporter Pdr12 transports fluorescein and preservative anions from the cytosol by an energy dependent mechanism. J Bacteriol. 1999, 181 (15): 4644-4652.PubMed CentralPubMedGoogle Scholar
  86. Vangelatos I, Roumelioti K, Gournas C, Suarez T, Scazzocchio C, Sophianopoulou V: Eisosome organization in the filamentous ascomycete Aspergillus nidulans. Eukaryot Cell. 2010, 9 (10): 1441-1454.PubMed CentralPubMedGoogle Scholar
  87. Kelly DE, Kraševec N, Mullins J, Nelson DR: The CYPome (cytochrome P450 complement) of Aspergillus nidulans. Fungal Genet Biol. 2009, 46: S53-S61.PubMedGoogle Scholar
  88. Kitazume T, Takaya N, Nakayama N, Shoun H: Fusarium oxysporum fatty-acid subterminal hydroxylase (CYP505) is a membrane-bound eukaryotic counterpart of Bacillus megaterium cytochrome P450BM3. J Biol Chem. 2000, 275 (50): 39734-39740.PubMedGoogle Scholar
  89. Vanhanen S, West M, Kroon JTM, Lindner N, Casey J, Cheng Q, Elborough KM, Slabas AR: A consensus sequence for long-chain fatty-acid alcohol oxidases from Candida identifies a family of genes involved in lipid omega-oxidation in yeast with homologues in plants and bacteria. J Biol Chem. 2000, 275 (6): 4445-4452.PubMedGoogle Scholar
  90. Hynes MJ, Murray SL, Khew GS, Davis MA: Genetic analysis of the role of peroxisomes in the utilization of acetate and fatty acids in Aspergillus nidulans. Genetics. 2008, 178 (3): 1355-1369.PubMed CentralPubMedGoogle Scholar
  91. Reiser K, Davis MA, Hynes MJ: Aspergillus nidulans contains six possible fatty acyl-CoA synthetases with FaaB being the major synthetase for fatty acid degradation. Arch Microbiol. 2010, 192 (5): 373-382.PubMedGoogle Scholar
  92. Reiser K, Davis MA, Hynes MJ: AoxA is a major peroxisomal long chain fatty acyl-CoA oxidase required for beta-oxidation in A. nidulans. Curr Genet. 2010, 56 (2): 139-150.PubMedGoogle Scholar
  93. De Cremer K, Mathys J, Vos C, Froenicke L, Michelmore RW, Cammue BPA, De Coninck B: RNAseq-based transcriptome analysis of Lactuca sativa infected by the fungal necrotroph Botrytis cinerea. Plant Cell Environ. 2013, 36 (11): 1992-2007.PubMedGoogle Scholar
  94. Maggio-Hall LA, Lyne P, Wolff JA, Keller NP: A single acyl-CoA dehydrogenase is required for catabolism of isoleucine, valine and short-chain fatty acids in Aspergillus nidulans. Fungal Genet Biol. 2008, 45 (3): 180-189.PubMed CentralPubMedGoogle Scholar
  95. Pusztahelyi T, Klement É, Szajli E, Klem J, Miskei M, Karányi Z, Emri T, Kóvacs S, Orosz G, Kóvacs KL, Medzihradszky KF, Prade RA, Pócsi I: Comparison of transcriptional and translational changes caused by long-term menadione exposure in Aspergillus nidulans. Fungal Genet Biol. 2011, 48 (2): 92-103.PubMedGoogle Scholar
  96. Mathew S, Abraham TE: Bioconversions of ferulic acid, an hydroxycinnamic acid. Crit Rev Microbiol. 2006, 32 (3): 115-125.PubMedGoogle Scholar
  97. Caspi R, Altman T, Dreher K, Fulcher CA, Subhraveti P, Keseler IM, Kothari A, Krummenacker M, Latendresse M, Mueller LA, Ong Q, Paley S, Pujar A, Shearer AG, Travers M, Weerasinghe D, Zhang PF, Karp PD: The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res. 2012, 40 (D1): D742-D753.PubMed CentralPubMedGoogle Scholar
  98. Tamayo EN, Villanueva A, Hasper AA, de Graaff LH, Ramón D, Orejas M: CreA mediates repression of the regulatory gene xlnR which controls the production of xylanolytic enzymes in Aspergillus nidulans. Fungal Genet Biol. 2008, 45 (6): 984-993.PubMedGoogle Scholar
  99. Gygi SP, Rist B, Gerber SA, Turecek F, Gelb MH, Aebersold R: Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat Biotechnol. 1999, 17 (10): 994-999.PubMedGoogle Scholar
  100. Hinnebusch AG: Translational regulation of GCN4 and the general amino acid control of yeast. Annu Rev Microbiol. 2005, 59: 407-450.PubMedGoogle Scholar
  101. Beyer A, Hollunder J, Nasheuer HP, Wilhelm T: Post-transcriptional expression regulation in the yeast Saccharomyces cerevisiae on a genomic scale. Mol Cell Proteomics. 2004, 3 (11): 1083-1092.PubMedGoogle Scholar
  102. Laloo B, Simon D, Veilla V, Lauzel D, Guyonnet-Duperat V, Moreau-Gaudry F, Sagliocco F, Grosset C: Analysis of post-transcriptional regulations by a functional, integrated, and quantitative method. Mol Cell Proteomics. 2009, 8 (8): 1777-1788.PubMed CentralPubMedGoogle Scholar
  103. Martins I, Garcia H, Varela A, Núñez O, Planchon S, Galceran MT, Renaut J, Rebelo LPN, Silva Pereira C: Investigating Aspergillus nidulans secretome during colonisation of cork cell walls. J Proteomics. 2014, 26 (98): 175-188.Google Scholar

Copyright

© Martins et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.