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Transcriptomic analysis of Aspergillus niger strains reveals the mechanism underlying high citric acid productivity

Bioresources and Bioprocessing20185:21

https://doi.org/10.1186/s40643-018-0208-6

Received: 5 January 2018

Accepted: 8 May 2018

Published: 15 May 2018

Abstract

Background

Aspergillus niger is a highly important industrial microorganism because of its amazing capacity to produce citric acid (CA). To explore the metabolic mechanism and physiological phenotype associated with high CA productivity, the transcriptomes of high CA-producing A. niger YX-1217 and degenerative strain YX-1217G were investigated using A. niger ATCC1015 as a control.

Results

These strains showed distinct transcriptional differences in CA production. By contrast, the genes encoding glycoside hydrolases, aspartyl endoproteases, and carboxypeptidases were unusually upregulated in CA-producing strain YX-1217, which involved the carbohydrate hydrolysis and polypeptide degradation pathways, and should be related to its powerful capacity to utilize cornmeal fluidified liquid as raw material for the production of CA. In central metabolism of YX-1217, gene 9.735.1, which encodes glyceraldehyde 3-phosphate dehydrogenase, and two transcriptionally outstanding genes, 6000119 (An15g01920) and 3.2152.1 (An08g10920) that encode citrate synthase, were upregulated, thereby ensuring CA accumulation. In addition, a relatively strong electron transport chain, a regeneration system for NAD+/NADP+, and an efficient resistance mechanism may have contributed to the high CA production rate of YX-1217.

Conclusions

These comparisons have shed light on the mechanism underlying high CA yield in A. niger YX-1217 as well as provide insights into the development of novel strains that produce other organic acids.
Graphical Abstract image

Keywords

Transcriptome Aspergillus niger Citric acidMetabolism

Background

Aspergillus niger is a ubiquitous fungus with powerful metabolic capabilities for the hydrolysis of carbohydrates and the production of organic acids and proteins. It has therefore been widely used as an industrial workhorse to commercially produce organic acids such as citric acid (CA) and gluconic acid, as well as industrial proteins such as enzymes and active proteins (Krijgsheld et al. 2013; Andersen et al. 2008). Along with advances in metabolic engineering and synthetic biology, A. niger has been highly studied to be developed as a more versatile cell factory platform.

As an important food additive and bulk chemical, CA has a long and successful production history by fermentation. Global CA production is more than 1.5 million tons per year, of which 99% comes from the fermentation of A. niger. The biochemical mechanism underlying the accumulation of CA in A. niger has recently been a research topic of great interest. In 2006, the US Department of Energy Joint Genomics Institute (JGI) completed the genome sequence of CA-producing A. niger ATCC 1015. Soon thereafter, as a powerful industrial enzyme producer, the genome of A. niger CBS513.88 was also sequenced and analyzed by DSM Food Specialties in 2007 (Pel et al. 2007). Currently, the genomes of at least four A. niger strains have been sequenced. Some metabolic network models of A. niger in genome scales have been established based on these sequences and used in the elucidation of the mechanism underlying CA production (Sun et al. 2007). The identified genes involved in CA metabolism and transport provide excellent opportunities to study and understand the mechanism of high CA production. The genome comparison of A. niger ATCC 1015 and CBS 513.88 has revealed genetic differences, particularly in relation to electron transport, carbohydrate transport, and organic acid transport, which in turn can shed light on the metabolic complexity relating to CA production (Andersen et al. 2011). Although extensive genomic studies have been conducted with A. niger, investigations relating to metabolic differences associated with variations in CA productivity among A. niger strains are still limited.

Recently, transcriptomics and proteomics studies on A. niger have revealed some distinct metabolic profiles at specific physiological statuses, such as the dormancy and germination stages of conidia (van Leeuwen et al. 2013). The RNA profile of dormant conidia is largely related to genes involved in fermentation, gluconeogenesis, and the glyoxylate cycle, whereas the profile at germination stage of conidia is associated with genes that are related to the metabolism of internal storage compounds (Novodvorska et al. 2013). Both researches clearly illustrate that transcriptional changes directly reflect the metabolic and physiological status of cells, and the observed major changes indicate cellular responses to alterations in the environment. The hydrolase secretory capacity of A. niger was also investigated by comparing transcriptomes in response to different carbon sources such as xylose or maltose, which revealed the transcriptional regulation profile of the secretory pathways and reflected a general modulation mechanism on the secretion capacity of extracellular hydrolases in A. niger (Jørgensen et al. 2009). Subsequently, proteomic analysis demonstrated that different carbon sources result in the production of specific extracellular enzymes such as glucoamylase A in response to d-maltose, and β-xylosidase in response to d-xylose (de Oliveira et al. 2011). These two studies have improved our understanding of the secretion capacity of A. niger. In addition, a more comprehensive study has analyzed the response of A. niger to carbon starvation in terms of changes in the physiological processes, morphological features, and genome-wide transcription (Nitsche et al. 2012). Although the metabolic properties of A. niger at different physiological statuses have been extensively studied using transcriptomics or proteomics approaches, to our best knowledge, no investigation has examined the metabolic mechanism underlying high CA productivity in A. niger. As the production of CA in the industry using A. niger is of significant economic value, understanding the complex mechanism underlying its production using omics approaches is essential.

China is the largest producer of CA, having more than 70% of the worldwide market share, the competitiveness of which benefits from the robust strains used in China with powerful CA productivity (> 150.0 g/L) from low-cost raw materials such as cornmeal, cassava, sweet potato, and other starch-rich crops. A. niger ATCC 1015 is a wild-type strain used in the first patented process for CA production nearly 90 years ago, which usually utilizes monosaccharides or disaccharides as raw materials and can only produce 10–20 g/L CA in 150 h at 30 °C. Obviously, the strains derived from A. niger ATCC 1015 or similar strains are hard to compete with the strains used in China in terms of productivity and production cost.

Aspergillus niger YX-1217 is a typical CA-producing strain used in the industry in China. Compared to A. niger ATCC 1015, it uses cornmeal as a raw material, producing 180–200 g/L CA in 55 h at 38–39 °C. Unfortunately, A. niger YX-1217 is not a genetically stable strain and is prone to spontaneous degeneration of CA production. To maintain its high CA-yielding phenotype, the strain must be regularly rejuvenated; otherwise, it would be degenerated to a low CA-producing strain (designated as YX-1217G) with an approximately 70% decrease in the CA production capacity compared to strain YX-1217.

To explore the metabolic profile and physiological phenotype associated with high CA yield, the transcriptomes of A. niger YX-1217 and YX-1217G were compared and analyzed in this study, and the transcriptome of A. niger ATCC1015 was used as a control. A comprehensive analysis of significant differences involved in CA production among these three strains identified events that were responsible for high CA yield in A. niger YX-1217, as well as provided novel insights into the development of strains that yield higher levels of CA or other organic acids.

Methods

Strains and growth conditions

Aspergillus niger YX-1217, YX-1217G, and ATCC 1015 were used in this study. For spore isolation, strains were grown for 7 days at 35 °C on sweet potato powder medium, and conidia were harvested and washed with a sterile detergent solution containing 0.05% (w/v) Tween-80 and 0.9% (w/v) NaCl. To this end, the colony surface was gently rubbed with a sterile T-spatula, and the conidial suspension was filtered through sterile glass wool and maintained at 4 °C until further analysis.

Sweet potato powder medium

Approximately, 250 g sweet potato powder was added to 1 L of water, stirred after adding 10 mL of high-temperature α-amylase, and liquefied for 40 min at 90 °C and then measured by Brix. When the sugar content was adjusted to 6 Brix, the liquid was supplemented with 2% agar and 0.08% (w/v) of (NH4)2SO4.

Cornmeal seed medium

Approximately, 250 g cornmeal was added to 1 L of water, stirring after continuously adding high-temperature α-amylase, and liquefied at 105 °C. Until the result of the iodine indicator test had no blue color, 20% (w/v) of cornmeal fluidified liquid was obtained. The liquid was filtered through two layers of gauze and used as seed medium.

Cornmeal fermentation medium

The filtered and unfiltered cornmeal fluidified liquid was mixed at a volume ratio of 6:1. The mixed liquid was then used as fermentation medium.

An aliquot of 3 × 108 conidia was added to 50 mL of the seed medium in a 250 mL Erlenmeyer flask. The cultures were shaken at 300 rpm and 35 °C for 33 h and then the seed liquid was inoculated into the fermentation medium at a concentration of 5% (v/v). Under the same conditions, the fermentation broth was cultured for 60 h. Each treatment was performed in triplicate.

Measure of CA and oxalic acid (OA) concentrations

CA and OA concentrations were determined using a high-performance liquid chromatography (HPLC) instrument equipped with a refractive index detector (RID), Aminex HPX-87H column (7.8 × 300 mm, Bio-Rad, California, USA) were used for CA and OA analysis. The eluent used for analysis was 0.01 N sulfuric acid solution. HPLC analyses were conducted under the following conditions: pump flow, 0.6 mL/min; column temperature, 40 °C; sample amount, 20 mL; and integration method, peak area. The concentrations were automatically calculated by Gilson Unipoint software.

Measurement of reducing sugar concentration and biomass

Reducing sugar concentrations were measured using an HPLC Dionex P 680 system with the following components: column type: Waters Xbridge Amide 3.5 μm 4.6 mm × 250 mm; detector: Shodex RI-101; injection volume: 20 μL; column temperature: 35 °C; flow rate: 0.8 mL/min; mobile phase: (acetonitrile:water ratio, 80:20).

To determine biomass production, wet fungal biomass that was collected after 60 h of growth was placed in a pre-weighed beaker and dried at 105 °C to a constant weight. Biomass levels are expressed as grams of cell weight per milliliter of fermentation broth. All values represent the mean of three independent determinations where the experiments were performed in triplicate.

RNA extraction

Conidia (108/mL) were germinated in the seed media for 10 h at 35 °C. The pellets were cultured in the fermentation media for 40 h at 35 °C. Germinating conidia and pellets were centrifuged at 6000 rpm for 20 min and then immediately frozen in liquid nitrogen and stored at − 80 °C for RNA extraction.

For Illumina sequencing, total RNA was extracted from germinating conidia (10 h) and pellets (40 h) using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. To maximize target coverage, equal amounts of total RNA (10 µg) from three independent RNA extractions were pooled for RNA-Seq library construction at each time point. The concentration and quality of RNA for each sample were determined by UV spectrometry (Agilent Technologies, Santa Clara, CA, US). Quality checks and subsequent RNA-Seq experiments were performed at the Next Generation Sequencing Facility (Shanghai Biotechnology Corporation, China).

Construction of cDNA library and transcriptome data analysis

The cDNA library was sequenced using the Illumina HiSeq 2000 with a paired-end 2 × 100-nt multiplex with two separate technical replicates. Clean reads were obtained by removing raw reads that contained the adaptor, unknown, or low-quality sequences. Clean reads were mapped to the genome sequence assembly of A. niger strain ATCC 1015. Full sequences and annotations are available from the Joint Genome Institute (JGI) Genome Portal (http://genome.jgi-psf.org/Aspni5). To ensure the most comprehensive gene model possible, clean reads were also mapped to the genome sequence assembly of A. niger CBS 513.88 genome from NCBI. The appendix file linking the CBS 513.88 annotation to ATCC 1015 annotation is presented in Additional file 1: Table S1. LifeScope provided all read alignment positions of each paired-end reads mapped against the complete genome sequence and exon spanning junctions. The read alignment results were recorded in BAM format for further downstream analysis. Read counts per gene were determined from primary read alignments with a mapping quality of ≥ 20 (MAPQ20). These counts were then used to calculate normalized expression values of fragments per kilobase of exon model per million mapped reads (FPKM) for each gene, as well as an input for determining significantly differentially expressed genes. BAM files were used as input, opting to ignore or include strand specificity in the calculations. Data were visualized using Integrative Genomic Viewer (IGV). Differentially expressed genes were screened using a false discovery rate (FDR) of ≤ 0.05, an absolute value of the log2 ratio of ≥ 1, and an FPKM ≥ 50 in strain YX-1217 at stage 10 h or stage 40 h as threshold. In addition, the genes that have small differences but have a decisive impact on CA production were included in the analysis.

To predict the cellular and metabolic functions associated with the observed changes in transcript levels, differentially expressed genes selected were categorized according to predicted protein function using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.genome.jp/kegg/).

Real-time quantitative RT-PCR (qRT-PCR) analysis

To validate our RNA-Seq results, the transcript expression of eight genes related to the CA metabolism was verified by qRT-PCR and reverse transcribed into cDNA by PrimeScriptH RT reagent kit with gDNA Eraser (Takara, Japan). qRT-PCR was performed using a Bio-Rad CFX-96 Real-Time PCR System (Bio-Rad, California, USA) with a final volume of 20 μL containing 2 μL of cDNA template, 10 μL of 26SYBR premix ExTaq™ (Takara, Japan), 1 μL of each forward and reverse primer (10 mM) (Additional file 2: Table S2), and 6 μL of RNase-free water. Gene transcription was analyzed using SYBR green assays as previously described (Steiger et al. 2009).

Results and discussion

Performances of A. niger YX-1217, YX-1217G, and ATCC1015

After several subcultures, some of the strains that germinated from the conidia of A. niger YX-1217 spontaneously degenerated into low CA-yielding strains. These degenerate strains exhibited no significant differences in growth and could maintain genetic stability in further multiple subcultures. Therefore, a degenerate strain YX-1217G was randomly selected for comparison with strain YX-1217 to explore genomic variations between high and low CA-yielding strains.

The variations in growth phenotypes and production performances between A. niger YX-1217 and YX-1217G were first investigated by using A. niger strain ATCC1015 as a control. These strains were all cultivated in the same conditions using cornmeal fermentation broth as medium and culturing at 35 °C for 60 h. After 60 h of fermentation, biomass, reducing sugars, and CA and OA concentrations of the three A. niger strains were measured (Table 1). The CA concentration of the three strains consistently increased with fermentation time (Fig. 1).
Table 1

Comparison of biomass, residual reducing sugars, citric acid, and oxalic acid concentration among the three strains at 60 h

Strains

Initial reducing sugars (g/L)

Biomass (g/L)

Citric acid concentration (g/L)

Oxalic acid concentration (g/L)

Residual reducing sugars (g/L)

A. niger YX-1217 (S1)

175.2 ± 2.5

132.4 ± 4.5C

180.0 ± 0.1A

0.89 ± 0.06C

3.5 ± 0.5C

A. niger YX-1217G (S2)

175.2 ± 2.5

157.5 ± 5.2B

65.0 ± 0.1B

5.78 ± 0.54A

43.8 ± 1.0B

ATCC 1015 (S3)

175.2 ± 2.5

192.5 ± 4.4A

20.0 ± 0.05C

1.83 ± 0.22B

86.0 ± 1.2A

Fermentations were performed in biological triplicate for each strain. Values are presented as the average ± standard deviation. For significance analysis, each column was listed as a level, and different uppercase letters represent extremely significant differences (p < 0.01)

Figure 1
Fig. 1

Results of citric acid fermentation by the three A. niger strains. The curves indicate that the citric acid concentration of A. niger YX-1217, YX-1217G, and ATCC 1015 increased consistently with the fermentation time

Apparently, strain YX-1217 is a robust CA-producing strain that could reach the highest CA titer of 180.0 g/L at 60 h with 3.0 g/L/h productivity, whereas the degenerate strain YX-1217G could only reach 65 g/L and 1.1 g/L/h productivity, indicating an almost 70% decrease in CA production capacity compared to strain YX-1217. Strain YX-1217 produced approximately 120 g/L CA more than YX-1217G, while producing approximately 15.1 g/L less biomass. For strain YX-1217G, the more the biomass, the less was the CA yield, which signified that part of the attenuated metabolism of CA production had shifted to the growth of A. niger. In addition, strain YX-1217 could only produce 0.89 g/L OA at 60 h, whereas strain YX-1217G had a yield of 5.78 g/L OA, which indicated that the degeneration involved not only CA metabolism but also that of other organic acids.

As A. niger YX-1217G is a degenerated strain of A. niger YX-1217 in terms of CA production, the close correlation between the two strains makes them good comparison objects to analysis some of the high yield mechanisms of CA by comparative omics. Considering that A. niger ATCC 1015 is a typical CA-producing strain and often employed as a representative research model for CA overproduction (Pel et al. 2007; Andersen et al. 2011), this strain is also selected as an available reference to analyze the distinctive feature of A. niger YX-1217 relating to the yield of CA. Experimental results show that all of the three strains can employ diverse carbohydrate-containing materials to produce CA, including cornmeal fluidified liquid. By contrast, the CA production capacity of strain ATCC1015 was significantly lower than that of strains YX-1217 and YX-1217G in the condition of 35 °C and 60 h, which reached only 20.0 g/L and 0.33 g/L/h CA productivity. As CA production of the strain ATCC 1015 was evaluated by glucose, it was tested in a glucose-based minimal medium, which only achieved 0.10 ± 0.12 g/L CA (Andersen et al. 2011). Briefly, the productivities among these strains are significantly different, and thus are good samples to explore the mechanism underlying high CA yield in A. niger by a comparative omics approach.

Transcriptional profiling

To directly demonstrate metabolic variations among these strains, transcriptomics analysis was utilized in mRNA expression profiling in relation to high CA yield. Cultures at the two different stages of each strain were selected and used in transcriptomics analysis. One stage was conidial germination, which was sampled from the seed medium cultured for 10 h, as the conidial germination of these A. niger strains was observed to flourish at 10 h, and it was reported that the majority of transcriptomic changes occur early during the germination phase (Novodvorska et al. 2013). Furthermore, at this stage, the nutrient content and pH of the medium do not undergo significant changes. More importantly, this stage involves the initial production of CA once germs emerge on the conidia, which was subsequently followed by the fast CA-producing period, signifying that CA metabolism has entered the active phase. It is thus the appropriate and reliable time point to compare metabolic differences at the initial stage of CA production among these strains. The other stage was the high CA yield phase, which involves culturing in fermentation medium for 40 h (Fig. 1). At this stage, these strains are all at their peak phase of CA production and exhibit significant differences in CA titer, intracellular metabolic activities, CA tolerance, and other aspects closely related to high CA yield capacity. Because the nutrients in the medium have not been depleted during metabolism among the three strains, the differential data at this stage may be usable in profiling CA yield in A. niger YX-1217.

Global transcriptional profiles of the three samples at two different phases were established using RNA-Seq. The number of clean reads and mapping ratio are presented in the supplemental material (Additional file 3: Table S3), and the mapping ratios were all more than 90%, which suggests that sequencing was sufficient. The comparison of strain YX-1217 to strain ATCC 1015 (designated as S1/S3) indicated 1020 upregulated genes (Additional file 4: Table S4) and 1084 downregulated genes (Additional file 5: Table S5) during the conidial germination stage (10 h) and 1058 (Additional file 6: Table S6) upregulated genes and 3024 downregulated genes (Additional file 7: Table S7) at the high citric acid yield stage. The comparison of strain YX-1217 with strain YX-1217G (designated as S1/S2) showed 506 upregulated genes (Additional file 8: Table S8) and 356 downregulated genes (Additional file 9: Table S9) during conidial germination and 1206 upregulated genes (Additional file 10: Table S10) and 1963 downregulated genes (Additional file 11: Table S11) during high CA yield. The global gene expression profiles (scatter plots) of various samples are shown in Fig. 2.
Figure 2
Fig. 2

Scatter plots of gene expression levels across different samples. a The transcriptional differences between A. niger YX-1217 and ATCC 1015 (S1/S3) at the stage of 10 h; b the transcriptional differences between A. niger YX-1217 and ATCC 1015 (S1/S3) at the stage of 40 h; c the transcriptional differences between A. niger YX-1217 and A. niger YX-1217G (S1/S2) at the stage of 10 h; d the transcriptional differences between A. niger YX-1217 and A. niger YX-1217G (S1/S2) at the stage of 40 h

Significantly greater transcriptional differences between A. niger YX-1217 and ATCC 1015 compared to that between A. niger YX-1217 and YX-1217G at the same stage were observed, and there were abundant genes that were more than tenfold up- or downregulated in the former stage than in the latter stage, which could be ascribed to their genetic relationship or their strain intrinsic physiological differences. This detailed analysis would provide an authentic view of the mechanism underlying high CA production.

Functional annotation of differentially expressed genes

Differentially expressed genes were functionally annotated to KEGG pathways to explore metabolic variations among different strains. The major KEGG pathways identified were associated with global metabolism, particularly CA biosynthesis that is related to starch and sucrose metabolism, glycolysis, TCA cycle, and fatty acid metabolism (Figs. 3 and 4).
Figure 3
Fig. 3

Comparative transcriptomic data at the stage of 10 h clustered by KEGG categories. a Comparative transcriptomic data of strain YX-1217 versus ATCC 1015 (S1/S3) at the stage of conidia germination (10 h culture of conidia in seed medium) clustered by KEGG categories; b Comparative transcriptomic data of strain YX-1217 versus YX-1217G (S1/S2) at the stage of conidia germination (10 h culture of conidia in seed medium) clustered by KEGG categories

Figure 4
Fig. 4

Comparative transcriptomic data at 40 h clustered by KEGG categories. a Comparative transcriptomic data of strain YX-1217 versus ATCC 1015 (S1/S3) at the peak stage of CA production (40 h culture of CA fermentation) clustered by KEGG categories. b Comparative transcriptomic data of strain YX-1217 versus YX-1217G (S1/S2) at the peak stage of CA production (40 h culture of CA fermentation) clustered by KEGG categories

Transcript abundance was higher in strain YX-1217 than in ATCC 1015 and YX-1217G during conidia germination, and in most of the categories the genes in strain YX-1217 were upregulated, except for those belonging to the categories of ribosomes, RNA transport, and amino acid biosynthesis, signifying that protein expression is not active in strain YX-1217 compared to strains ATCC1015 and YX-1217G. At the peak stage of CA production, most of the genes that are closely related to CA biosynthesis such as those of TCA cycle, starch and sucrose metabolism, glycolysis, and pyruvate metabolism were downregulated in strain YX-1217G compared to the other two strains. Notably, most of the ribosome-associating genes were upregulated in S1/S3 and S1/S2 at the peak stage of CA production (40 h), indicating that protein expression is higher in strain YX-1217 than the other strains at this stage.

To concretely distinguish the specific genes and possible mechanism contributing to high CA productivity, the genes belonging to the above categories at the two stages were further examined individually in the following sections using the selection criterion of FPKM ≥ 50 in strain YX-1217 at the stage of 10 or 40 h, log2ratio ≥ 1, and FDR ≤ 0.05.

Regulation of carbohydrate hydrolysis among different A. niger strains

Utilization of a wide range of carbohydrates as carbon sources is an important feature of A. niger. In industry, cornmeal is often used as an inexpensive carbon source for the fermentation of A. niger, and strain YX-1217 is the typical CA-producing strain that can convert high Brix starch to CA. In the present study, transcriptional variations in hydrolases between strains YX-1217 and ATCC1015 and YX-1217G were first analyzed (Table 2).
Table 2

Expression of genes involved in carbohydrate hydrolytic pathway

Gene ID (1015)

Gene ID (513.88)

Predicted function (homolog and organism)a

FPKM-10 h

FPKM-40 h

Fold changeb

S1

S3

S2

S1

S3

S2

S1/S3 (10 h)

S1/S2 (10 h)

S1/S3 (40 h)

S1/S2 (40 h)

220039

An04g09890

agsA, GH13, alpha-amylase, alpha-1,3 glucan synthases

85.31

3.70

69.89

18.92

84.01

41.45

4.52

− 2.15

− 1.13

20924

An02g13240

agdC, GH13, alpha-amylase, (A. parasiticus glcA)

94.33

6.81

34.64

9.80

27.69

25.98

3.79

1.44

− 1

− 1,79

4000142

No

amyA, GH13, alpha-amylase, catalytic region

314.72

7.81

364.47

10,173.90

196.30

8128

5.33

5.69

6.225.1

An15g07800

agtC, GH 13, alpha-amylase, catalytic region

18.68

0.88

2.99

4.99

43.02

0.24

4.40

2.64

 

4.37

80803

An14g04190

gbeA, glycoside hydrolase GH 13, 1,4-alpha-glucan-branching enzyme

80.46

10.18

19.34

15.07

58.91

53.08

2.98

2.05

− 1.96

− 1.81

140568

An03g06560

Glycoside hydrolase GH15, glucan-1,4-alpha-glucosidase with starch-binding domain

2003.34

36.57

1922.03

7633.04

293.32

8669.53

5.77

4.7

1.137.1

An01g10930

agdC, glycoside hydrolase, GH31, alpha/beta-glucosidase

325.56

65.10

122.57

99.21

41.37

405.03

2.32

1.41

1.26

− 2.03

170127

An04g06920

agdA, glycoside hydrolase, GH 31, alpha-glucosidase

2116.14

213.84

860.88

1651.11

241.73

1790.41

3.30

1.29

2.77

180456

An16g06800

Glycoside hydrolase, GH 5, endoglucanase A

505.16

93.65

557.327

104.11

77.28

449.4

2.43

− 2.11

190032

An03g00940

Glycoside hydrolase, GH 10, endo-1,4-beta-xylanase F1

1100.38

0.45

1.12

108.75

1.64

18.16

11.24

9.96

6.05

2.58

11115

An01g00780

xynB, glycoside hydrolase, GH 11, endo-1,4-beta-xylanase

218.08

13.44

5.87

191.03

0.45

29.15

4.02

5.22

8.74

2.71

80523

An14g02760

eglA, glycoside hydrolase GH 12, endoglucanase A

460.75

1.92

10.67

85.96

4.34

375.94

7.9

5.43

4.3

− 2.12

10876

An01g03340

Glycoside hydrolase GH 12, xyloglucanase

25.10

7.61

52.69

255.83

6.47

47.62

1.72

− 1.05

5.3

2.42

6000593

An15g07760

Glycoside hydrolase, GH 26, mannan endo-1,4-beta-mannosidase E

316.29

62.32

63.14

11.45

1.10

9.46

2.34

2.32

3.37

22004

An02g11150

aglB, glycoside hydrolase, GH 27, alpha-galactosidase B

59.76

6.19

41.36

618.92

1.10

248.35

3.27

9.14

1.32

20338

An02g04900

Glycoside hydrolase, GH 28, endopolygalacturonase C

698.14

21.98

362.65

458.52

16.00

307.35

4.99

4.84

90046

An12g08280

inuE, glycoside hydrolase, GH 32, inulinase

224.97

14.74

52.39

8.03

0.50

3.50

3.93

2.1

4.01

1.19

17000028

An04g06990

Glycoside hydrolase, GH 47,1, 2-alpha-mannosidase

62.66

14.20

92.03

47.61

125.33

99.55

2.14

− 1.40

30627

An08g05230

Glycoside hydrolase, GH 61, endoglucanase-4

468.30

6.76

19.19

13.28

8.30

30.59

6.11

4.61

− 1.20

6.376.1

An15g04900

Glycoside hydrolase, GH 61, endo-beta-1,4-glucanase D

130.324

6.08

1.30

0.59

1.07

2.03

4.42

6.65

− 1.79

190140

An03g00960

axhA, Glycoside hydrolase, GH 62, alpha-l-arabinofuranosidase

648.17

1.98

3.37

563.18

1.59

66.70

8.36

7.59

8.47

3.08

210054

No

Chitinase

1761.52

48.82

494.28

513.94

728.75

1145.75

5.17

1.83

− 1.15

10199

An01g12440

Chitin-binding, domain 3

367.96

15.93

29.17

333.84

7.89

39.68

4.52

3.65

5.4

3.07

140158

An03g04190

Chitinase

213.33

20.54

283.81

347.27

212.54

617.82

3.37

13.203.1

An04g04670

cfcC, GH18, Chitinase

150.49

18.23

56.79

96.25

162.39

119.70

3.04

1.4

10106

An01g12450

bxgA, chitinase

245.54

37.36

83.58

465.89

7.44

205.65

2.72

1.55

5.97

1.18

80155

An14g01840

Chitinase

494.65

192.43

679.08

3093.6

1858.9

2445.76

1.36

“–” denotes genes with no differences at transcriptional level, fold change ≤ 1. Some of the genes have small differences, but have a decisive impact on CA production. We also used fold change as an indicator

“No” denotes that sequence was not mapped to the genome sequence assembly of A. niger strain CBS 513.88

a Description of gene or closest homolog (BLASTP)

b Fold change of differentially expressed (FDR < 0.05, FPKM ≥ 50 in A. niger YX-1217 at time 10 h or time 40 h) genes based on a comparison of transcription levels at YX-1217/ATCC 1015 (designated as S1/S3) (10 h), YX-1217/YX-1217G (designated as S1/S2) (10 h), YX-1217/ATCC 1015 (designated as S1/S3) (40 h), and YX-1217/YX-1217G (designated as S1/S2) (40 h), respectively

The degradation of starch is performed by a variety of enzymes, which are divided over three glycoside hydrolase (GH) families based on their sequence similarity http://www.cazy.org), including GH13, GH15, and GH31 (Adav et al. 2010; Yuan et al. 2008). To date, several A. niger genes involved in extracellular starch hydrolytic enzymes have been characterized. GH13, a large family containing various hydrolyzing and transglycosylating enzymes, can mostly act on α-(1,4) or α-(1,6)-glycosidic bonds. GH31 releases glucose from the non-reducing end of starch. Here, the expression levels of genes agsA (An04g09890), agdC (An02g13240), amyA, agtC (An15g07800), and gbeA (An14g04190) encoding α-amylases (GH13 family), and genes agdC (An01g10930) and agdA (An04g06920) encoding α-glucosidase (family GH31) were all abundant and upregulated in YX-1217, whereas these genes were downregulated in ATCC 1015 at the two stages. However, previous reports have shown that the transcript levels of genes glaA (An03g06550) and agdA (An04g06920) in A. niger N402 did not significantly differ from days 2 to 8 (Jørgensen et al. 2010). In addition, the two genes displayed higher transcript levels among all genes on maltose-limited chemostat culture compared to xylose-limited chemostat culture (Jørgensen et al. 2009). GH15 possesses a starch-binding domain (SBD), which is a discrete C-terminal region that binds to starch and facilitates hydrolysis (Yuan et al. 2008). Gene 140568 (An03g06560), which encodes glucan-1,4-alpha-glucosidase with the SBD, was upregulated by fivefold in S1/S3, but the expression level of the gene was mostly unaffected in S1/S2.

In addition, genes encoding other families of enzymes, GH5, GH10, GH11, GH 12, GH26, GH27, GH28, GH47, GH61, and GH62 were significantly upregulated in S1/S3 and S1/S2, particularly 190032 (An03g00940), 11115 (An01g00780, xynB), and 190140 (An03g00960, axhA) at the two stages. However, there were exceptions; gene 90046 (An12g08280), which encodes β-fructofuranosidase, gene 30627 (An08g05230) encoding endoglucanase-4, and gene 6.376.1 (An15g04900) encoding endo-beta-1,4-glucanase D, were expressed at low levels in the three strains at the stage of 40 h. Gene An12g08280 has been also reported to be upregulated by 11-fold at day 2/day 0 and was rapidly downregulated at day 8/day 0 (Jørgensen et al. 2010), which was in agreement with our transcriptional results.

Aspergillus niger conidia possess a relatively thick-layered cell wall that is shed during germination (van Leeuwen et al. 2013). Six genes involved in chitin degradation were determined to be upregulated at the initial stage of germination in YX-1217.

In all, compared to ATCC 1015 and YX-1217G, YX-1217 showed a more powerful hydrolase system for carbohydrate utilization, which may be one of the essential reasons contributing to the rapid utilization of cornmeal starch to achieve high CA titer.

Regulation of polypeptide degradation among different A. niger strains

In addition to carbohydrates, cornmeal is also rich in proteins and peptides. The genome of A. niger encodes 198 proteases that are involved in proteolytic degradation, including nine secreted aspartyl endoproteases, ten serine carboxypeptidases, and nine dipeptidyl and tripeptidyl aminopeptidases (Pel et al. 2007). Overall, 14 peptidases were differentially expressed at the transcriptional level during CA production (Table 3), of which four aspartic peptidases, five serine carboxypeptidases, one cysteine peptidase, and one arginase were more abundant in YX-1217. These all were upregulated in S1/S3 and slightly upregulated in S1/S2 at the two stages, including gene 80863 (An14g04710, pepA). The transcript levels of gene 80863 has been reported to peak at day 2 and showed a sharp reduction on day 8 (Jørgensen et al. 2010), which agrees with our results. In addition, previous reports have shown that aspartyl endoproteases and carboxypeptidases are mostly active at low pH (Pel et al. 2007). Because of the acidifying properties (about pH 2.5) of A. niger YX-1217, four aspartic peptidases and five serine carboxypeptidases were all more abundant and upregulated in YX-1217.
Table 3

Expression of genes involved in polypeptides degradation

Gene ID (1015)

Gene ID (513.88)

Predicted function (homolog and organism)a

FPKM-10 h

FPKM-40 h

Fold changeb

S1

S3

S2

S1

S3

S2

S1/S3 (10 h)

S1/S2 (10 h)

S1/S3 (40 h)

S1/S2 (40 h)

80863

An14g04710

pepA, peptidase aspartic, active site

2540.17

3.11

3437.07

34,270.0

49.03

10205

9.67

9.44

1.74

12707

An01g00370

Peptidase aspartic, active site (AP1) (A. phoenicis, apnS)

1855.35

265.64

549.84

1602.29

42.57

742.46

2.80

1.75

5.23

1.11

5000659

An07g00950

Peptidase aspartic, active site

424.65

7.66

154.19

548.92

17.21

148.96

5.79

1.46

4.99

1.88

61129

An15g06280

peptidase aspartic, active site

210.08

26.26

37.04

605.44

97.34

112.93

3.00

2.50

2.64

2.42

11004

An09g06460

Peptidase, eukaryotic cysteine peptidase active site

388.70

1.60

484.87

200.71

31.84

42.39

7.92

− 1.21

2.65

2.24

2000089

An02g04690

cpdA, Serine carboxypeptidases F (lysosomal cathepsin A)

182.61

5.86

423.40

2358.41

51.97

1327.78

4.96

5.50

30096

An06g00310

Peptidase S8, serine carboxypeptidases S1 (lysosomal cathepsin A)

96.75

3.44

142.95

161.62

87.04

63.09

4.81

1.36

90133

An12g05960

Peptidase S28, extracellular serine carboxypeptidase

204.37

27.80

180.01

238.87

20.48

120.63

2.88

3.54

 

30678

An08g04490

Peptidase S28, serine peptidase

214.22

40.93

166.05

2417.0

21.60

923.24

2.39

6.81

1.39

30666

An08g04640

Peptidase S8 and S53, serine peptidase

107.55

3.15

166.05

349.08

6.92

220.11

5.09

5.65

1000155

An01g11340

Peptidase M24, methionine aminopeptidase MAP

87.46

3.44

145.30

72.97

3.02

28.31

4.66

4.59

1.37

8000249

An14g05960

Arginase family protein (E. coli, speB)

156.44

0

3.61

5.97

0.00001

0.12

c

5.43

19.18

5.60

30486

An06g01880

Peptidase M20, beta-ureidopropionase

293.47

4.54

37.29

44.86

38.18

22.38

6.01

2.98

1.00

40364

An11g01970

Peptidase C15, pyroglutamyl peptidase I

100.04

15.68

57.07

266.533

77.46

94.93

2.67

1.78

1.49

60486

An15g01980

Aminotransferase, class I and II

125.68

15.02

20.95

24.15

14.33

18.70

3.06

2.58

20000064

An04g08630

Aminotransferase, class IV

68.03

2.52

69.61

265.13

7.80

71.43

4.76

5.09

1.89

“–” denotes genes with no differences in transcriptional levels, fold change ≤ 1. Some of the genes have small differences, but have a decisive impact on CA production. We also used fold change as an indicator

“No” denotes that the sequence was not mapped to the genome sequence assembly of A. niger strain CBS 513.88

a Description of gene or closest homolog (BLASTP)

b Fold change of differentially expressed (FDR < 0.05, FPKM ≥ 50 in A. niger YX-1217 at time 10 or time 40) genes based on a comparison of transcription levels at YX-1217/ATCC 1015 (designated as S1/S3) (10 h), YX-1217/YX-1217G (designated as S1/S2) (10 h), YX-1217/ATCC 1015 (designated as S1/S3) (40 h), and YX-1217/YX-1217G (designated as S1/S2) (40 h), respectively

c The FPKM of ATCC 1015 is zero

Proteins and polypeptides in the medium were degraded into various amino acids by peptidases, including serine and aspartic acid, which are transported via amino acid transporters for the uptake by cells (Table 5). The significant upregulation of genes encoding the amino acid trasporters demonstrated that a greater amount of amino acids were produced in the culture of strain YX-1217 compared to YX-1217G and ATCC 1015 due to the more powerful capacity of polypeptide degradation. Obviously, the peptidase expression profile of YX-1217 during the high acid production ensured the efficient utilization of amino acids from protein hydrolysis, which may also be one of attributes of strain YX-1217 to adapt to the high production of CA.

Regulation of central metabolism of CA production among different A. niger strains

CA is a product of cell central metabolism, which includes various pathways such as glycolysis, TCA cycle, fatty acid metabolism, and glyoxylic acid metabolism. The observed transcriptional variations on central metabolism of CA production in S1/S3 and S1/S2 are presented in Table 4.
Table 4

Expression of genes involved in central metabolism processes

Gene ID (1015)

Gene ID (513.88)

Predicted function (homolog and organism)a

FPKM-10 h

FPKM-40 h

Fold changeb

S1

S3

S2

S1

S3

S2

S1/S3 (10 h)

S1/S2 (10 h)

S1/S3 (40 h)

S1/S2 (40 h)

Glycolysis

 15000076

An13g00950

alcB, alcohol dehydrogenase, class V

52.65

11.95

14.25

22.79

8.00

12.23

2.13

1.88

1.51

 50661

No

Aldehyde dehydrogenase

406.67

10.58

34.53

101.40

23.60

25.76

5.26

3.55

2.10

1.97

 160032

An10g00850

Aldehyde dehydrogenase (NAD+)

154.32

1.60

6.90

7.62

3.29

8.48

6.58

4.48

1.21

 9.735.1

No

Glyceraldehyde 3-phosphate dehydrogenase

673.82

0.32

1455.29

404.21

0.00001

421.74

11.05

− 1.11

25.26

 90161

An12g08610

glkA, Glucokinase

228.90

99.06

151.49

158.72

89.83

119.21

1.21

 70571

An16g02990

Phosphoglycerate mutase

182.92

426.80

143.55

48.55

204.61

119.11

− 1.22

− 2.08

− 1.29

 100101

An18g01670

pfkA, 6-phosphofructokinase

141.71

396.31

126.75

18.73

117.42

83.83

− 1.48

− 2.65

− 2.16

 50068

An07g08990

 pkiA, pyruvate kinase

1339.84

713.44

791.51

111.70

301.28

309.77

− 1.43

− 1.47

TCA cycle

 3.2152.1

An08g10920

citB, citrate synthase

79.42

0.07

349.09

0.34

0.16

1.10

10.06

− 2.13

1.06

 6000119

An15g01920

mscA, methylcitrate synthase

286.25

20.60

47.61

43.11

34.60

49.59

3.79

2.58

 130482

An04g02090

pycA, Pyruvate carboxylase

176.18

242.37

174.54

42.81

49.14

33.15

1

1.44

 20251

An02g12770

Succinate dehydrogenase SDH1

499.46

384.63

166.11

53.31

297.99

201.71

1.58

− 2.48

− 1.91

 40489

An11g02550

Phosphoenolpyruvate carboxykinase (A. nidulans, acuF)

71.15

98.07

18.84

71.19

313.94

113.38

1.91

− 2.14

 30306

An06g00990

Fumarate reductase FRDS

199.86

270.39

99.20

38.69

307.69

145.62

1.01

− 2.99

− 1.9

 50562

An07g02160

mdh1, malate dehydrogenase

1452.29

1178.52

1336.53

1725.86

810.04

764.45

1.09

1.17

 101221

An18g06760

Isocitrate dehydrogenase, gamma subunit

1198.24

711.97

1113.35

2581.7

700.18

808.43

2.03

1.82

 110571

An09g03870

Aconitase

202.23

332.86

80.18

8.67

33.42

41.12

− 1.94

− 2.24

 40119

An11g00510

aclB, ATP-citrate lyase

950.20

459.53

554.44

46.72

181.23

63.03

1.05

− 1.96

 40123

An11g00530

aclA, ATP-citrate lyase

980.48

473.78

682.24

110.4

211.46

81.49

1.05

Fatty acid metabolism

 7000050

An16g04830

Acyl-CoA synthetase

90.11

4.06

43.06

33.90

2.32

11.33

4.47

1.06

3.86

 170132

An04g05720

3-ketoacyl-CoA thiolase

95.82

62.70

40.55

684.04

62.88

149.85

1.24

3.44

2.19

 13000035

An04g04330

afeA, acyl-CoA synthetase

196.82

0.31

113.28

10.26

1.27

2.41

9.31

3.01

2.81

Glyoxylic acid metabolism

 11071

An01g09270

acuB, isocitrate lyase

29.32

9.50

1.90

133.18

63.90

116.37

1.62

3.94

1.05

 160030

An10g00820

oahA, isocitrate lyase/oxaloacetate acetylhydrolase

623.51

0.26

65.54

5.66

10.70

6.91

9.97

3.25

 6000115

An15g01860

acuE, malate synthase

26.01

175.50

11.42

95.47

127.09

85.78

− 2.75

1.18

“–” denotes genes with no differences at transcriptional level, fold change ≤ 1. Some of the genes have small differences, but have a decisive impact on CA production. We also used fold change as an indicator

“No” denotes that sequence was not mapped to the genome sequence assembly of A. niger strain CBS 513.88

a Description of gene or closest homolog (BLASTP)

b Fold change of differentially expressed (FDR < 0.05, FPKM ≥ 50 in A. niger YX-1217 at time 10 or time 40) genes based on a comparison of transcription levels at YX-1217/ATCC 1015 (designated as S1/S3) (10 h), YX-1217/YX-1217G (designated as S1/S2) (10 h), YX-1217/ATCC 1015 (designated as S1/S3) (40 h), and YX-1217/YX-1217G (designated as S1/S2) (40 h), respectively

CA is formed mainly via cytosolic glycolysis and the subsequent mitochondrial TCA cycle. In the present study, the expression levels of genes involved in glycolysis were mostly unaffected, except for gene 9.735.1. This gene, which is predicted to be a glyceraldehyde-3-phosphate dehydrogenase (GAPDH), was upregulated nearly 11- and 25-fold in S1/S3 at the two stages. Besides its established metabolic function, GAPDH has recently been implicated in various non-metabolic processes, including transcription activation, initiation of apoptosis, and ER to Golgi vesicle shuttling, or axoplasmic transport (Tarze et al. 2007). The outstanding difference of GAPDH among strain ATCC 1015 YX-1217G and YX-1217 indicated that it should be one of the key enzymes in central metabolism, closely regulating the production of CA. The expression level of gene 100101 (An18g01670), which encodes 6-phosphofructokinase (6-Pfk), was downregulated in YX-1217 at the stage of 40 h. Because an increase in CA production results in feedback inhibition of 6-Pfk, a reduction in 6-Pfk activity may lead to an improvement in CA production (Ruijter et al. 1997).

CA is an important intermediate in the TCA cycle. Citrate synthase (Cs), which is a pace-making enzyme in the first step, catalyzes the condensation of oxaloacetate and acetyl-CoA to form CA, which is the most important enzyme in CA production. Two genes, namely, 6000119 (An15g01920, mscA) and 3.2152.1 (An08g10920, citB), which encode Cs, were observed at the two stages and were upregulated in S1/S3 at the stage of 10 h, whereas these were downregulated in S1/S2 at the stage of 10 h and showed no transcriptional differences at the stage of 40 h. Three genes encoding Cs in A. niger CBS 513.88 (An01g09940, An08g10920, and An09g06680) have been previously identified and mapped (Pel et al. 2007). A. niger ATCC 1015, which shares six Cs isoenzymes (202801, 48684, 126525, 176409, 35756, and 46236), including methylcitrate synthase, may contribute to the high citrate production efficiency of A. niger (Sun et al. 2007). However, it was previously reported that overexpression of Cs did not increase the rate of Cs production, which suggested that Cs minimally contributes to flux control in the CA biosynthetic pathway in a non-commercial strain (Ruijter et al. 2000). But, Ghulam et al. (2014) reported that CA production by overexpression of a mutant CS was significantly enhanced from 19.4 to 64.20 mg/mL. Accordingly, the Cs activity in the fermentation broth of strain YX-1217 was assessed as described (Ruijter et al. 2000), which indicated that Cs activity was higher (289U) at the stage of 10 h, whereas it decreased (83U) at the stage of 40 h. These findings coincided with the results of transcriptome analysis and indicated that, although Cs is one of the key enzymes for CA production, the upregulated expression of Cs is not a sufficient and necessary condition for the high yield of CA.

The expression of the other key enzymes in TCA cycle, such as two succinate dehydrogenases [encoded by genes 20259 (An02g12770) and 5000505 (An07g03170), respectively], malate dehydrogenase [encoded by gene 50562 (An07g02160)], isocitrate dehydrogenase [encoded by gene 101221 (An18g06760)], and aconitase [encoded by gene 110571 (An09g03870)] showed no transcriptional differences among the three strains at the two stages. Nevertheless, their expression levels as indicated by FPKM value were high during CA formation. ATP-citrate lyase is the key enzyme to catalyze the decomposition of CA to oxaloacetate (OAA) and acetyl coenzyme A, and there are two homologs in these A. niger strains, encoded by gene 40119 (An11g00510) and 40123 (An11g00530), respectively. Both of these enzymes maintain stable transcriptional levels and were even slightly upregulated at the stage of 10 h for strain YX-1217. These data illustrated that the TCA cycle still maintained basic activity in these A. niger strains, which should be an important prerequisite for these A. niger strains to maintain growth and survive in the living environment of high CA titers.

Glyoxylic acid cycle is the variation of TCA cycle, which forms an alternative pathway where isocitrate is converted into malate without the production of NADH by the consecutive catalysis of isocitrate lyase and malate synthase. The transcripts of two homologous encoding isocitrate lyase contain two homologous genes 11071 (An01g09270, acuB) and 160030 (An10g00820, oahA), which are highly abundant in YX-1217; however, the transcript of gene (An15g01860, acuE) encoding malate synthase was not obviously different in these strains.

Under the conditions of adequate oxygen, fatty acids are decomposed into acetyl-CoA and completely oxidized into CO2 and H2O, which consequently releases a large amount of energy. Acyl-CoA synthetase plays a major role in this process by activating long-chain fatty acids with more than 12 carbons, which encodes genes 7000050 (An16g04830) and 13000035 (An04g04330) and shows higher transcriptional level in YX-1217 than in ATCC 1015 at the two stages. The data indicated that strain YX-1217 has more powerful catabolic capacity for fatty acid than ATCC 1015, which can supply a greater amount of acetyl-CoA and energy for the growth and survival of YX-1217 to yield a greater amount of CA.

In short, the central metabolism among the three strains displayed no substantial differences, while the better central metabolism was an important premise for strain YX-1217 to overproduce CA.

Regulation of transporter mechanisms of CA production among different A. niger strains

Elucidating transporter mechanisms for CA production is crucial. The transcriptional variations in transporter mechanisms among the three A. niger strains are presented in Table 5. In this study, 25 transporters were differentially expressed at the transcriptional level, which include seven synaptic vesicle transporter SVOP and related transporters (major facilitator superfamily), four amino acid transporters, three peptide transporters, and seven ion transporters that were upregulated in YX-1217 at the two stages.
Table 5

Expression of genes involved in transporter mechanisms

Gene ID (1015)

Gene ID (513.88)

Predicted function (homolog and organism)a

FPKM-10 h

FPKM-40 h

Fold changeb

S1

S3

S2

S1

S3

S2

S1/S3 (10 h)

S1/S2 (10 h)

S1/S3 (40 h)

S1/S2 (40 h)

2.412.1

An02g08970

Synaptic vesicle transporter SVOP and related transporters (major facilitator superfamily)

185.2

2.21

94.74

21.26

4.17

5.31

6.38

2.44

2.00

3000074

An08g10970

Synaptic vesicle transporter SVOP and related transporters

160.28

0.71

917.73

6.31

9.60

11.21

7.80

− 2.51

160123

An17g01710

Synaptic vesicle transporter SVOP and related transporters

103.76

2.77

49.29

930.44

2.51

122.66

5.22

1.07

8.53

2.92

5000334

An07g05880

Synaptic vesicle transporter SVOP and related transporters

107.56

4.57

49.04

70.54

8.35

23.06

4.55

1.13

3.07

1.61

5.1708.1

No

Synaptic vesicle transporter SVOP and related transporters

24.18

2.10

58.59

323.21

43.80

63.16

3.52

− 1.27

2.88

2.35

160129

An10g00690

Permease of the major facilitator superfamily

118.95

0.44

26.12

13.04

6.55

0.91

8.07

2.18

3.83

9000464

An12g03550

Permease of the major facilitator superfamily

80.14

1.01

28.94

53.88

13.55

1.50

6.29

1.46

1.99

5.16

31842

An08g03200

Ammonia permease

658.74

11.45

452.98

874.63

583.09

67.70

5.84

3.69

8.781.1

An14g02390

Ammonia permease

95.62

5.25

9.21

6.99

7.80

5.15

4.18

3.37

150043

No

Amino acid transporters

313.46

3.98

494.76

1872.15

1170.98

219.82

6.30

3.09

18.284.1

An16g07900

Amino acid transporters

91.62

2.61

2.59

60.14

8.98

12.63

5.13

5.14

2.74

2.25

11.172.1

An09g02550

Amino acid transporters

85.21

1.01

3.44

178.80

4.02

13.43

6.39

4.63

5.47

3.73

19000022

An03g01590

Amino acid transporters

77.90

0.49

6.71

79.07

7.25

1.22

7.32

3.53

3.44

6.01

51440

An07g01950

Xanthine/uracil transporters (A. nidulans, uapC)

103.74

21.22

60.84

245.16

194.55

16.35

2.28

3.90

31302

An08g06240

Uridine permease/thiamine transporter/allantoin transport

60.46

4.80

28.19

269.89

72.22

3.70

3.65

1.10

1.90

6.18

110148

No

Tetrapeptide transporter, OPT1/isp4

1213.89

6.69

1523.02

1328.97

230.62

666.57

6.18

2.52

18.109.1

An16g06770

Monocarboxylate transporter

45.49

6.18

11.67

106.08

12.00

24.68

2.87

1.95

3.14

2.10

111102

An09g00660

Oligopeptide transporter OPT superfamily

20.89

0.33

96.18

570.88

25.23

123.98

6.00

− 2.20

4.49

2.20

21.45.1

An12g10320

Fe2+/Zn2+ regulated transporter

111.77

5.31

126.14

2585.52

606.42

499.30

4.39

2.09

2.37

10845

An01g03790

Na+: solute symporter

74.05

3.14

53.95

51.89

51.48

2.18

4.56

4.57

1001002

An01g01950

Mg2+ transporter protein, CorA-like

42.43

0.98

12.76

461.93

187.17

408.91

5.44

1.73

1.30

9000143

An12g07730

Ctr Cu2+ transporter

79.63

16.88

94.62

518.01

27.41

58.48

2.23

4.24

3.14

22.68.1

An04g09850

git1, Inorganic phosphate transporter

16.87

1.25

20.28

100.07

22.88

14.74

3.75

2.12

2.76

240077

An19g00340

Ca2+/H+ antiporter VCX1 and related proteins

50.22

0.86

15.81

615.05

81.96

175.32

5.77

1.58

2.98

1.89

240035

An19g00330

Ca2+/H+ antiporter VCX1 and related proteins

29.77

2.50

15.81

204.99

28.69

92.59

3.57

2.83

1.15

“–” denotes genes with no differences at transcriptional level, fold change ≤ 1. Some of the genes have small differences, but have a decisive impact on CA production. We also used fold change as an indicator

“No” denotes that sequence was not mapped to the genome sequence assembly of A. niger strain CBS 513.88

a Description of gene or closest homolog (BLASTP)

b Fold change of differentially expressed (FDR < 0.05, FPKM ≥ 50 in A. niger YX-1217 at time 10 or time 40) genes based on a comparison of transcription levels at YX-1217/ATCC 1015 (designated as S1/S3) (10 h), YX-1217/YX-1217G (designated as S1/S2) (10 h), YX-1217/ATCC 1015 (designated as S1/S3) (40 h), and YX-1217/YX-1217G (designated as S1/S2) (40 h), respectively

The transport functions of synaptic vesicles may be more complex than currently envisioned, which are related to eukaryotic and bacterial phosphate, sugar, and organic acid transporters (Janz et al. 1998). Seven synaptic vesicle trafficking proteins were upregulated in S1/S3 and S1/S2. In strain YX-1217, abundant synaptic vesicles could accelerate the absorption and utilization of materials such as sugar that were prepared for the production of CA. In addition, synaptic vesicle trafficking associated with neuronal development, macromolecules, small molecules, and ion transport is regulated by a voltage-dependent Ca2+ channel (Augustine et al. 1987; Zhang et al. 2013). Vesicle initiation and subsequent membrane fusion both require an increase in Ca2+ concentration in the cytoplasm. The cytosolic Ca2+ levels are determined by two opposite fluxes, namely, Ca2+ influx via channels and Ca2+ efflux via active transporters (Waditee et al. 2004). Furthermore, changes in intracellular Ca2+ distribution affect ion homeostasis. Genes involved in various ion transport proteins for Na+, K+, Fe2+, Ca2+, Mg2+, Zn2+, and Cu2+ were differentially expressed in the three strains. Two important genes, namely, 240077 (An19g00340) and 240035 (An19g00330), which encode a Ca2+/H+ antiporter of Vcx1 and related proteins, showed significantly higher transcriptional levels in S1/S3, whereas these were slightly upregulated in S1/S2. The results showed that these genes were associated with maintaining a low cytosolic-free Ca2+ concentrations by catalyzing pH gradient-energized vacuolar Ca2+ accumulation in A. oryzae RIB40.

The transcription levels of four amino acid transporters were elevated in the three strains. Gene 18.284.1 (An16g07900) is similar to a choline transporter Hnm1 in A. fumigatus Af293, which is associated with nitrogen uptake. Gene 11.172.1 (An09g02550) is similar to a putative GABA permease GabA, which was upregulated in S1/S3 and S1/S2 at the two stages. Genes involved in other small molecule transport (ammonium, xanthine, uracil, thiamine, urea, and peptides) exhibited high levels of mRNA expression in the three strains (Table 5).

The significant upregulation of the transporters showed the more powerful transporter capacity of materials in strain YX-1217 compared to YX-1217G and ATCC1015, which enables YX-1217 to quickly and sufficiently transport substances (macromolecules, small molecules, and ions) into, out of, or within a cell. It may also be one of the attributes of strain YX-1217 to adapt to the high production of CA.

Regulation of energy metabolism, transcription factor regulation, and resistance among different A. niger strains

The maintenance of energy balance is critical for high CA fermentation. Increased transcript levels were detected in YX-1217 such as genes 21.34.1 (An12g09940), 9.1179.1 (An05g00300), and 40169 (An11g04370) encoding cytochrome 5; gene 3.1942.1 (An08g06550) encoding ubiquinol cytochrome c reductase; and gene 4.1469.1 encoding cytochrome c heme-binding proteins (Table 6). Most of their FPKM values were highly expressed in the three strains at the two stages, and mRNA expression was upregulated at the stage of 40 h compared to 10 h. This result showed that a large amount of energy was produced by the respiratory chain to maintain the energy balance and supply energy for CA production during the high CA production period in YX-1217. Novodvorska et al. (2013) detected increased transcript levels for genes encoding putative subunits of the respiratory chain mainly during the first hour of germination such as cytochrome b (An11g04370), which would supply energy for spore germination. Moreover, the present study detected important genes such as 2000458 (An02g06550), 5000079 (An07g08760), 6000073 (An15g00690), and 2.1052.1 (An02g09730), encoding relatives of NADH/NADPH oxidase, which catalyze the regeneration of NAD+/NADP+. These genes were upregulated in YX-1217 at the stage of 40 h. To maintain the balance of intracellular redox state and energy metabolism, the superfluous reducing power NADH must be converted to its oxidation state NAD+ in time by a regeneration system for NAD+/NADP+, otherwise the metabolism of glucose to CA will be arrested. In a successful CA-producing strain, a powerful regeneration system for NAD+/NADP+ is needed to convert the mass production of NADH/NADPH along with the CA overproduction.
Table 6

Expression of genes involved in energy metabolism, transcription factor regulation, and resistance mechanism

Gene ID (1015)

Gene ID (513.88)

Predicted function (homolog and organism)a

FPKM-10 h

FPKM-40 h

Fold changeb

S1

S3

S2

S1

S3

S2

S1/S3 (10 h)

S1/S2 (10 h)

S1/S3 (40 h)

S1/S2 (40 h)

Energy metabolism

 9.1179.1

An05g00300

Cytochrome b5 (Musca domestica, cytb5)

43.10

208.68

41.02

1503.85

162.33

333.18

− 2.27

3.21

2.17

 40169

An11g04370

Cytochrome b5

1411.35

658.03

895.69

5202.49

565.65

883.43

1.10

3.20

2.55

 21.34.1

An12g09940

Cytochrome b5

69.63

3.12

4.94

1.49

0.33

 

4.47

3.81

2.17

 3.1942.1

An08g06550

Ubiquinol cytochrome c reductase, subunit QCR8

944.78

1718.06

1690.58

6710.39

755.36

1955.17

3.15

1.77

 4.1469.1

No

Cytochrome c heme-binding site

34.15

9.48

30.55

185.57

28.69

80.69

1.84

2.69

1.20

 2000458

An02g06550

Ferric reductase, NADH/NADPH oxidase and related proteins

109.62

6.85

5.55

4.73

4.43

2.40

3.99

4.30

 6000073

An15g00690

NADH:ubiquinone oxidoreductase, NDUFA6/B14 subunit

336.69

335.46

351.26

1782.8

206.93

367.27

3.10

2.27

 2.1052.1

An02g09730

NADH:ubiquinone oxidoreductase, NDUFB7/B18 subunit

588.21

870.88

791.99

3764.33

578.95

671.06

2.70

2.49

Transcription factor

 1.2786.1

An01g13950

Upstream transcription factor 2/L-myc-2 protein

92.02

0

21.14

543.05

39.25

183.80

c

2.12

3.79

1.56

 80804

An14g04200

rghB, transcription initiation factor TFIID, subunit BDF1 and related bromodomain proteins, rhamnogalacturonase B

101.42

3.72

19.40

46.80

6.79

2.75

4.76

2.38

2.78

 

 5.1343.1

An07g07370

Transcription factor, Myb superfamily

46.57

4.25

31.47

134.79

71.56

1.04

3.45

 8.1025.1

An14g00780

Putative translation initiation inhibitor UK114/IBM1

98.99

26.99

80.59

1084.41

129.09

105.30

1.87

3.07

3.36

 800003

An18g04840

Translation elongation factor EF-1 alpha/Tu

630.05

1919.49

2031.67

1059.85

0.00001

0.00001

-1.60

-1.68

26.65

26.65

 12000021

An12g00240

Putative translation initiation inhibitor UK114/IBM1

664.05

638.32

624.75

2105.6

187.81

208.68

3.48

2.04

 1000929

An01g02900

Translation initiation factor 5A (S. cerevisiae, anbA)

1299.2

2868.77

1426.52

3715.03

808.85

1219.28

2.19

1.61

 2000159

An02g07890

pacC, pH-response transcription factor

91.52

55.30

39.50

29.38

89.03

32.46

1.21

− 1.60

Resistance mechanism

 20494

An02g02750

Catalase

59.61

35.89

8.12

68.79

9.45

19.16

2.87

2.86

1.84

 10568

An01g01550

Catalase (A. fumigates, cat1)

257.06

106.96

4.78

0.33

56.87

5.29

1.26

5.74

− 7.42

− 3.99

 1.973.1

An01g12530

Manganese superoxide dismutase

1308.37

30.85

3758.22

116.36

9.46

1.82

5.40

− 1.52

3.62

5.97

 10.1058.1

An18g00260

Cytochrome P450 CYP3/CYP5/CYP6/CYP9 subfamilies (A. parasiticus, avnA)

69.73

2.98

75.30

126.19

9.63

20.70

4.54

3.71

2.60

 11000284

An09g03210

Cytochrome P450 CYP2 subfamily

92.33

21.67

17.98

175.49

3.08

22.36

2.09

2.36

5.83

2.97

 130837

An04g00480

Basic-leucine zipper (bZIP) transcription factor

119.36

42.05

114.03

223.53

644.36

74.15

1.50

− 1.53

1.59

 4000214

An11g05340

FAD-dependent oxidoreductase

534.85

43.75

408.23

37.98

20.96

39.89

3.61

 160248

An17g00010

Copper amine oxidase (H. polymorpha AMO)

2319.99

1.33

4.91

4.92

2.37

2.71

10.77

8.88

1.05

 150032

An13g00710

Copper amine oxidase AO-1

944.56

7.30

16.52

133.7

37.95

78.39

7.30

5.83

1.81

 110401

An09g01550

ao-1, copper amine oxidase

713.37

0.95

9.10

222.50

23.89

22.92

9.55

6.29

3.21

3.27

 19000158

An03g00730

Hypothetical copper amine oxidase with signal peptide motif

255.57

13.09

25.24

116.39

32.08

36.72

4.28

3.34

1.85

1.66

 50349

An07g08720

Glycosyl transferase, family 20, trehalose-6-phosphate synthase

115.01

19.63

14.41

11.60

69.86

71.36

2.55

2.99

− 2.58

− 2.62

 80430

An14g02180

tpsB, trehalose-6-phosphate synthase component TPS1 and related subunits

41.24

23.10

6.07

7.16

24.02

19.63

2.76

− 1.74

− 1.45

“–” denotes genes with no differences at transcriptional level, fold change ≤ 1. Some of the genes have small differences, but have a decisive impact on CA production. We also used fold change as an indicator

“No” denotes that sequence was not mapped to the genome sequence assembly of A. niger strain CBS 513.88

a Description of gene or closest homolog (BLASTP)

b Fold change of differentially expressed (FDR < 0.05, FPKM ≥ 50 in A. niger YX-1217 at time 10 or time 40) genes based on a comparison of transcription levels at YX-1217/ATCC 1015 (designated as S1/S3) (10 h), YX-1217/YX-1217G (designated as S1/S2) (10 h), YX-1217/ATCC 1015 (designated as S1/S3) (40 h), and YX-1217/YX-1217G (designated as S1/S2) (40 h), respectively

c The FPKM of ATCC 1015 is zero

Genes encoding proteins that are involved in transcription and translation were upregulated in YX-1217. Gene 800003 (An18g04840), encoding translational elongation factor EF-1 alpha, was upregulated by at least 26-fold. It was associated with the binding reaction of aminoacyl-tRNA (AA-tRNA) to ribosomes, which laid a good foundation for rapid synthesis of a series of enzymes involved in CA production. Genes of transcription factors involved in pH regulation in YX-1217 are presented in Table 6. Gene 2000159 (An02g07890) is the pH-responsive regulator PacC of Aspergillus, which has been implicated in the regulation of genes encoding transporter proteins such as GABA (γ-amino n-butyrate) permease and phosphate permease (Peñalva et al. 2002). CA production in A. niger begins at pH 3.0 and is optimal just below pH 2.0 (Haq et al. 2005). Some reports on the sensitivity of hypoxia in filamentous fungi to intracellular pH refer to the reduced activity of plasma membrane H+ ATPase, which is involved in the maintenance of intracellular proton concentrations by extrusion of protons from the cytoplasm at the expense of ATP (Andersen et al. 2009). Therefore, acid concentration affects the internal pH of cells.

Fungi rely on resistance to scavenge reactive oxygen species (ROS) that can cause cell damage by oxidizing cell components such as DNA, proteins, and lipids and can also compromise cell functions (Devasagayam et al. 2004; Kroneck and Torres 2015; Fountain et al. 2016). Catalase, superoxidase, and oxidoreductases can protect cells by opposing oxidative stress during growth and development. The transcript levels of these genes that are involved in resistance were relatively high in the three strains and were significantly upregulated in YX-1217 at the two stages. Gene 1.973.1 (An01g12530), involved in manganese and iron superoxide dismutase, showed higher expression in S1/S3 at the stage of 10 h, as well as in S1/S3 and S1/S2 at the stage of 40 h. Antioxidant defense systems to scavenge ROS can decrease cell damage and retard cell aging. A previous report has indicated that the knockout of five catalase family genes (catA, catB, catC, catD, and catP) can lead to a significant decrease in anti-oxidative capability, UV-B resistance, and virulence in B. bassiana (Wang et al. 2013). The overexpression of a cytosolic manganese-cored SOD (Bbsod2) in B. bassiana leads to significantly enhanced anti-oxidative capability and UV-B resistance. Knocking out three superoxide dismutase genes (sod1, sod4, and sod5) in B. bassiana could lead to significant decreases in anti-oxidative capability (Xie et al. 2010a, b). The expression of bZIP transcription factors such as atf21 and atfA has been shown to regulate aflatoxin production in response to oxidative stress in vitro during early stages of fungal growth (Fountain et al. 2016). The overexpression of five bZip transcription factors (RsmA, Napa, ZipA, ZipB, and ZipC) in A. nidulans results in the significant improvement of resistance to ROS (Yin et al. 2013). To obtain a CA production strain with a higher yield, it is essential to investigate genes that are involved in resistance mechanism.

Taken together, the findings of the present study indicate that a highly efficient electron transport chain, a regeneration system for NAD+/NADP+, the highly upregulated expression of key genes involved in transcription and translation protein, and an effective resistance mechanism apparently contribute to high CA production in A. niger YX-1217.

Transcription regulation of genes involving CA production among three different A. niger strains

To elucidate the mechanism underlying CA yield, the central metabolic pathways were first assessed in terms of their direct correlation to CA production (Figs. 5 and 6).
Figure 5
Fig. 5

Transcription level regulation of genes involving CA production in three different A. niger at 10 h. Upregulated, downregulated, and no differentially expressed genes involving CA production are highlighted in red, green, and gray color, respectively. Comparative transcriptomic differences of strain YX-1217 versus ATCC 1015 (S1/S3) and strain YX-1217 versus YX-1217G (S1/S2) at 10 h are exhibited, respectively, in squares. PFK 6-phosphofructokinase, GADPH glyceraldehyde-3-phosphate dehydrogenase, PYC pyruvate carboxylase, ACS acetyl-coA synthetase, ADH alcohol dehydrogenase, CS citrate synthase, ICL isocitrate lyase, SDH succinate dehydrogenase, ACL ATP-citrate lyase, NOX NADH/NADPH oxidase

Figure 6
Fig. 6

Transcription level regulation of genes involving CA production in three different A. niger at 40 h. Upregulated, downregulated, and no differentially expressed genes involving CA production are highlighted in red, green, and gray, respectively. Comparative transcriptomic differences of strain YX-1217 versus ATCC 1015 (S1/S3) and strain YX-1217 versus YX-1217G (S1/S2) at 40 h are exhibited, respectively, in squares. PFK 6-phosphofructokinase, GADPH glyceraldehyde-3-phosphate dehydrogenase, PGAM phosphoglycerate mutase, PK pyruvate kinase, ACS acetyl-coA synthetase, ADH alcohol dehydrogenase, ACO aconitase, IDH isocitrate dehydrogenase, SDH succinate dehydrogenase, ACL ATP-citrate lyase, NOX NADH/NADPH oxidase

The results indicate that the transcriptional levels of most of the key genes contributing to CA yield are significantly higher in A. niger YX-1217 than in strain YX-1217G and ATCC 1015 during conidia germination. The genes encoding the GH family for carbohydrate hydrolysis and the genes encoding proteins/peptides degeneration were upregulated in A. niger YX-1217 during conidial germination. It should be related to its powerful capacity to utilize cornmeal fluidified liquid as raw material for the production of CA.

Gene 9.735.1, encoding GAPDH that catalyzes the conversion of glyceraldehyde 3-phosphate to d-glycerate 1,3-bisphosphate, was upregulated by nearly 11- and 25-fold in S1/S3, whereas there was no differential expression in S1/S2. In TCA metabolism, the significantly upregulated expression of some key genes such as 6000119 (An15g01920) and 3.2152.1 (An08g10920), which encode Cs, a crucial enzyme in CA production that catalyzes the condensation reaction of acetyl coenzyme A and oxaloacetate to form CA, was upregulated in S1/S3. In terms of lipid metabolism, the transcript of genes 7000050 (An16g04830) and 13000035 (An04g04330), which encode Acyl-CoA synthetase that convert fatty acid molecules into acyl-coenzyme A for their subsequent oxidation, was highly abundant in S1/S3 at the two stages. Furthermore, some important genes, 2000458 (An02g06550), 5000079 (An07g08760), 6000073 (An15g00690), and 2.1052.1 (An02g09730) that encode relatives of NADH/NADPH oxidase catalyze the regeneration of NAD+/NADP+. In the present study, these genes were upregulated in YX-1217.

Interestingly, some genes associated with CA production have no obvious differences or have low transcriptional expression in the three strains at the stage of 40 h. Filamentous fungi utilize a feedback mechanism termed repression under secretion stress (RESS), which selectively downregulates the transcription of genes encoding extracellular enzymes upon ER stress and thus helps to reduce the ER load (Fan et al. 2015). RESS represses the transcription of secretory protein genes under ER stress conditions in T. reesei, A. niger, and A. nidulans (Wang et al. 2010). In A. niger, RESS leads to the selective transcriptional downregulation of the glucoamylase gene (Alsheikh et al. 2004). Transcriptome profiling of N. crassa has revealed that the expression of most lignocellulase genes are significantly induced at early time points (16 h), but rapidly declines thereafter, implying that RESS exists in N. crassa and might be a limiting step of lignocellulase synthesis (Wang et al. 2010), which agrees with our findings. At the peak time of the CA production, RESS could result in the downregulation of the key genes involved in CA production.

Experimental validation of gene expression level by qRT-PCR

To verify the expression level of the genes identified by RNA-Seq, eight genes highly related to the CA production were selected and qRT-PCR was performed. The majority of these candidates exhibited upregulated expression in S1/S3 and S1/S2 at the stage of 10 h, and only a minority of genes exhibited downregulated expression in S1/S3 and S1/S2 at the stage of 40 h (Table 7). The results coincide with the findings of RNA-Seq and qRT-PCR analyses, thus indicating that our results were effective and reliable.
Table 7

Gene expression verification by qRT-PCR

Gene ID

Predicted function (homolog and organism)

RNA-Seq

qRT-PCR

S1/S3 (10 h)

S1/S2 (10 h)

S1/S3 (40 h)

S1/S2 (40 h)

S1/S3 (10 h)

S1/S2 (10 h)

S1/S3 (40 h)

S1/S2 (40 h)

190032

GH 10, endo-1,4-beta-xylanase F1

11.24

9.96

6.05

2.58

10.69

8.42

5.50

1.93

80523

eglA, GH 12, endoglucanase A

7.9

5.43

4.3

− 2.12

6.3

4.21

4.1

− 1.1

190140

axhA, GH 62, alpha-l-arabinofuranosidase

8.36

7.59

8.47

3.08

7.41

6.38

6.54

2.01

6000119

mscA, methylcitrate synthase

3.79

2.58

0.31

0.20

3.45

2.45

0.20

0.10

12707

Peptidase aspartic, active site (AP1) (A. phoenicis, apnS)

2.80

1.75

5.23

1.11

2.11

1.54

4.37

1.00

7000050

Acyl-CoA synthetase

4.47

1.06

3.86

0.45

3.98

1.01

3.55

0.22

160123

Synaptic vesicle transporter SVOP and related transporters

5.22

1.07

8.53

2.92

6.45

0.67

9.36

2.44

11.172.1

Amino acid transporters

6.39

4.63

5.47

3.73

7.65

5.00

6.57

2.84

All data were ratio log2

Genes based on a comparison of transcription levels at YX-1217/ATCC 1015 (designated as S1/S3) (10 h), YX-1217/YX-1217G (designated as S1/S2) (10 h), YX-1217/ATCC 1015 (designated as S1/S3) (40 h), and YX-1217/YX-1217G (designated as S1/S2) (40 h), respectively

Conclusions

In this study, to explore the metabolic mechanism and physiological phenotype associated with high CA productivity, the transcriptomes of high CA-producing A. niger YX-1217 and degenerative YX-1217G were investigated and compared using A. niger ATCC1015 as a control. The results revealed the striking transcriptional differences in CA production among the three A. niger strains. In the carbohydrate hydrolysis and polypeptide degradation pathway, many key genes were upregulated in YX-1217, which showed a more powerful hydrolase system for carbohydrate utilization. It may be one of the essential reasons contributing to the rapidly utilization of cornmeal starch to achieve high CA titer. In central metabolism, the three strains displayed no substantial differences, while the better central metabolism was an important premise for strain YX-1217 to overproduce CA. A total of 25 protein transporters were differentially expressed in YX-1217, which could accelerate the absorption and utilization of materials such as sugar that were prepared for the production of CA. In addition, a relatively strong electron transport chain, a regeneration system for NAD+/NADP+, and an efficient resistance mechanism may have contributed to the high CA production rate of A. niger YX-1217. These results will undoubtedly help us to comprehensively understand the character of A. niger and pave the way for further research on fungi.

Abbreviations

A. niger

Aspergillus niger

A. nidulans

Aspergillus nidulans

T. reesei

Trichoderma reesei

CA: 

citric acid

OA: 

oxalic acid

FPKM: 

fragments per kilobase of exon model per million mapped reads

FDR: 

false discovery rate

KEGG: 

The Kyoto Encyclopedia of Genes and Genomes database

qRT-PCR: 

real-time quantitative RT-PCR

S1: 

A. niger YX-1217

S2: 

A. niger YX-1217G

S3: 

ATCC 1015

SBD: 

starch-binding domain

OAA: 

oxaloacetate

AcCoA: 

acetyl coenzyme A

GH: 

glycoside hydrolase

PFK: 

6-phosphofructokinase

GADPH: 

glyceraldehyde-3-phosphate dehydrogenase

PYC: 

pyruvate carboxylase

PGAM: 

phosphoglycerate mutase

PK: 

pyruvate kinase

ACS: 

acetyl-coA synthetase

ADH: 

alcohol dehydrogenase

ACO: 

aconitase

IDH: 

isocitrate dehydrogenase

CS: 

citrate synthase

ICL: 

isocitrate lyase

SDH: 

succinate dehydrogenase

ACL: 

ATP-citrate lyase

NOX: 

NADH/NADPH

RESS: 

oxidase repression under secretion stress

Declarations

Authors’ contributions

HX and FQW designed the experiments. QYM supplied A. niger YX-1217 and YX-1217G. HX performed the experiments and analyzed the data. FQW and DZW provided reagents and materials. HX wrote the manuscript. FQW revised the manuscript. All authors read and approved the final manuscript.

Acknowledgements

The authors thank the Shan Dong Weifang Ensign Industry Co., Ltd. (Weifang, China) for donating the industrial strains of A. niger YX-1217 and A. niger YX-1217G.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

All data generated and analyzed during this study were included in the manuscript in the form of graphs and tables. The authors will provide any missing data on request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

The National Special Fund for State Key Laboratory of Bioreactor Engineering supported this study.

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Authors’ Affiliations

(1)
State Key Lab of Bioreactor Engineering, Newworld Institute of Biotechnology, East China University of Science and Technology, Shanghai, China
(2)
Weifang Ensign Industry Co., Ltd., Weifang, China
(3)
Life Science College, Henan Agricultural University, Zhengzhou, China

References

  1. Adav SS, Li AA, Manavalan A, Punt P, Sze SK (2010) Quantitative iTRAQ secretome analysis of Aspergillus niger reveals novel hydrolytic enzymes. J Proteome Res 9:3932–3940View ArticleGoogle Scholar
  2. Alsheikh H, Watson AJ, Lacey GA, Punt PJ, MacKenzie DJ, Jeenes DJ, Pakula T, Penttilä M, Alcocer MJC, Archer DB (2004) Endoplasmic reticulum stress leads to the selective transcriptional downregulation of the glucoamylase gene in Aspergillus niger. Mol Microbiol 53:1731–1742View ArticleGoogle Scholar
  3. Andersen MR, Nielsen ML, J Nielsen (2008) Metabolic model integration of the bibliome, genome, metabolome and reactome of Aspergillus niger. Mol Syst Biol 4:178View ArticleGoogle Scholar
  4. Andersen MR, Lehmann L, Nielsen J (2009) Systemic analysis of the response of Aspergillus niger to ambient pH. Genome Biol 10:R47View ArticleGoogle Scholar
  5. Andersen MR, Salazar MP, Schaap PJ et al (2011) Comparative genomics of citric-acid-producing Aspergillus niger ATCC 1015 versus enzyme-producing CBS 513.88. Genome Res 21:885–897View ArticleGoogle Scholar
  6. Augustine GJ, Charlton MP, Smith SJ (1987) Calcium action in synaptic transmitter release. Annu Rev Neurosci 10:633–693View ArticleGoogle Scholar
  7. de Oliveira JM, van Passel MW, Schaap PJ, de Graaff LH (2011) Proteomic analysis of the secretory response of Aspergillus niger to d-maltose and d-xylose. PLoS ONE 6:e20865View ArticleGoogle Scholar
  8. Devasagayam T, Tilak JC, Boloor KK, Sane KS, Ghaskadbi SS, Lele RD (2004) Free radicals and antioxidants in human health: current status and future prospects. JAPI 52:794–804Google Scholar
  9. Fan FY, Ma GL, Li JG, Liu Q, Benz JP, Tian CG, Ma YH (2015) Genome-wide analysis of the endoplasmic reticulum stress response during lignocellulase production in Neurospora crassa. Biotechnol Biofuels 8:1–17View ArticleGoogle Scholar
  10. Fountain JC, Bajaj P, Pandey M, Nayak SN, Yang L, Kumar V, Jayale AS, Citikineni A, Zhang W, Scully BT, Lee RD, Kemerait RC, Varshney RK, Guo B (2016) Oxidative stress and carbon metabolism influence aspergillus flavus transcriptome composition and secondary metabolite production. Sci Rep 6:38747View ArticleGoogle Scholar
  11. Ghulam M, Aisha T, Muhammad A, Mehboob-Ur R, Amer J (2014) Comparative sequence analysis of citrate synthase and 18s ribosomal DNA from a wild and mutant strains of Aspergillus niger with various fungi. Bioinformation 10:1–7View ArticleGoogle Scholar
  12. Haq I-UL, Ali S, Qadeer MA (2005) Influence of dissolved oxygen concentration on intracellular pH for regulation of Aspergillus niger growth rate during citric acid fermentation in a stirred tank bioreactor. Int J Biol Sci 1(1):34–41Google Scholar
  13. Janz R, Hofmann K, Südhof TC (1998) Svop, an evolutionarily conserved synaptic vesicle protein, suggests novel transport functions of synaptic vesicles. J Neurosci 18:9269–9281View ArticleGoogle Scholar
  14. Jørgensen TR, Goosen T, van den Hondel C, Lversen JJL (2009) Transcriptomic comparison of Aspergillus niger growing on two different sugars reveals coordinated regulation of the secretory pathway. BMC Genomics 10:44View ArticleGoogle Scholar
  15. Jørgensen TR, Nitsche BM, Lamers GE, Arentshorst M, Ca VDH, Ram AF (2010) Transcriptomic insights into the physiology of Aspergillus niger approaching a specific growth rate of zero. Appl Environ Microbiol 76:5344–5355View ArticleGoogle Scholar
  16. Krijgsheld P, Bleichrodt R, vanVeluw GJ, Wang F, Müller WH, Dijksterhuis J, Wösten HAB (2013) Development in Aspergillus. Stud Mycol 74:1–29View ArticleGoogle Scholar
  17. Kroneck PMH, Torres MES (2015) Sustaining life on planet earth: metalloenzymes mastering dioxygen and other chewy gases. Metal ions in life sciences, vol 15, pp 1–12Google Scholar
  18. Nitsche BM, Jørgensen TR, Akeroyd M, Meyer V, Ram AFJ (2012) The carbon starvation response of Aspergillus niger during submerged cultivation. BMC Genomics 13:318View ArticleGoogle Scholar
  19. Novodvorska M, Hayer K, Pullan ST, Wilson R, Blythe MJ, Stam H, Stratford M, Archer DB (2013) Trancriptional landscape of Aspergillus niger at breaking of conidial dormancy revealed by RNA-sequencing. BMC Genomics 14:1–18View ArticleGoogle Scholar
  20. Pel HJ, de Winde JH, Archer DB et al (2007) Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88. Nat Biotechnol 25:221–231View ArticleGoogle Scholar
  21. Peñalva MA, Arst HN Jr (2002) Regulation of gene expression by ambient pH in filamentous fungi and yeasts. Microbiol Mol Biol Rev 66:426–446View ArticleGoogle Scholar
  22. Ruijter GJ, Panneman H, Visser J (1997) Overexpression of phosphofructokinase and pyruvate kinase in citric acid-producing Aspergillus niger. Biochem Biophys Acta 1334:317–326View ArticleGoogle Scholar
  23. Ruijter GJG, Panneman H, Xu DB, Visser J (2000) Properties of Aspergillus niger citrate synthase and effects of cita overexpression on citric acid production. FEMS Microbiol Lett 184:35–40View ArticleGoogle Scholar
  24. Steiger MG, Mach RL, Mach-Aigner AR (2009) An accurate normalization strategy for RT-qPCR in Hypocrea jecorina (Trichoderma reesei). J Biotechnol 145:30–37View ArticleGoogle Scholar
  25. Sun JB, Lu X, Rinas U, Zeng AP (2007) Metabolic peculiarities of Aspergillus niger disclosed by comparative metabolic genomics. Genome Biol 8:R182View ArticleGoogle Scholar
  26. Tarze A, Deniaud A, Bras ML, Maillier E, Molle D, Larochette N, Zamzami N, Jan G, Kroemer G, Brenner C (2007) GAPDH, a novel regulator of the pro-apoptotic mitochondrial membrane permeabilization. Oncogene 26:2606–2620View ArticleGoogle Scholar
  27. van Leeuwen MRV, Krijgsheld P, Bleichrodt R, Menke H, Stam H, Stark J, Wösten HAB, Dijksterhuis J (2013) Germination of conidia of Aspergillus niger, is accompanied by major changes in RNA profiles. Stud Mycol 74:59–70View ArticleGoogle Scholar
  28. Waditee R, Hossain GS, Tanaka Y, Nakamura T, Shikata M, Takano J, Takabe T, Takabe T (2004) Isolation and functional characterization of Ca2+/H+ antiporters from cyanobacteria. J Biol Chem 279:4330–4338View ArticleGoogle Scholar
  29. Wang B, Guo GW, Wang C, Lin Y, Wang XN, Zhao MM, GuoY He MH, Zhang Y, Pan L (2010) Survey of the transcriptome of Aspergillus oryzae via massively parallel mRNA sequencing. Nuleic Acids Res 38:5075–5087View ArticleGoogle Scholar
  30. Wang ZL, Zhang LB, Ying SH, Feng MG (2013) Catalases play differentiated roles in the adaptation of a fungal entomopathogen to environmental stresses. Environ Microbiol 15:409–418View ArticleGoogle Scholar
  31. Xie XQ, Wang J, Huang BF, Ying SH, Feng MG (2010a) A new manganese superoxide dismutase identified from Beauveria bassiana enhances virulence and stress tolerance when overexpressed in the fungal pathogen. Appl Microbiol Biotechnol 86:1543–1553View ArticleGoogle Scholar
  32. Xie XQ, Ying SH, Feng MG (2010b) Characterization of a new Cu/Zn-superoxide dismutase from Beauveria bassiana and two site-directed mutations crucial to its antioxidation activity without chaperon. Enzyme Microbiol Technol 46:217–222View ArticleGoogle Scholar
  33. Yin WB, Reinke AW, Szilágyi M, Emri T, Chiang YM, Keating AE, Pócsi I, Wang CCC, Keller NP (2013) bZIP transcription factors affecting secondary metabolism, sexual development and stress responses in Aspergillus nidulans. Microbiol 159:77–88View ArticleGoogle Scholar
  34. Yuan XL, Kaaij RMVD, Cees AMJJ, van den Hondel Punt PJ, van der Marc JEC, Maarel Dijkhuizen L, Ram AFJ (2008) Aspergillus niger, genome-wide analysis reveals a large number of novel alpha-glucan acting enzymes with unexpected expression profiles. Mol Genet Genomics 279:545–561View ArticleGoogle Scholar
  35. Zhang R, Zhao M, Ji HJ, Yuan YH, Chen NH (2013) Study on the dynamic changes in synaptic vesicle-associated protein and axonal transport protein combined with LPS neuroinflammation model. ISRN Neurol 2:496079Google Scholar

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