What this is
- This research investigates the roles of AtfA and AtfB in the stress response of Aspergillus nidulans.
- Using , the study compares gene expression in various mutant strains under different stress conditions.
- Findings reveal that AtfA primarily regulates stress-responsive genes, while AtfB's role is more limited.
Essence
- AtfA is the main regulator of stress response genes in Aspergillus nidulans, while AtfB plays a supporting role. Gene expression analysis shows that AtfA-dependent genes are enriched in carbohydrate metabolism and stress response pathways.
Key takeaways
- AtfA regulates 329 genes in untreated mycelial samples, while AtfB regulates only 96 genes. Most AtfB-dependent genes also show AtfA-dependence, indicating AtfA's dominant role.
- In conidial samples, AtfA and AtfB are more important regulators compared to mycelial samples, with 485 upregulated and 1070 downregulated genes identified in conidia under stress.
- Gene set enrichment analysis reveals that AtfA-dependent genes are significantly involved in carbohydrate metabolism and secondary metabolite production, highlighting its critical role in stress adaptation.
Caveats
- The study primarily focuses on specific gene sets, which may not encompass the full range of regulatory interactions in Aspergillus nidulans. Further research is required to explore the complexities of these interactions.
- The findings are based on specific culturing conditions and may not be generalizable across all environmental stress scenarios faced by the organism.
Definitions
- bZIP transcription factors: A family of proteins that regulate gene expression through binding to specific DNA sequences, crucial for stress responses and development in fungi.
- RNA sequencing: A method used to analyze the quantity and sequences of RNA in a sample, allowing for the assessment of gene expression levels.
AI simplified
1. Introduction
Basic domain leucine zipper-type (bZIP) transcription factors are members of a complex regulatory network, playing a crucial role in the maintenance and differentiation of cells as well as the coordination of stress responses in eukaryotes [1].
In filamentous fungi, the bZIP transcription factor AtfA, orthologous to Atf1 of Schizosaccharomyces pombe and Atf2 in mammals, orchestrates several processes, including development and secondary metabolite production of vegetative hyphae as well as stress tolerance of both vegetative hyphae and conidiospores in A. nidulans [2], Claviceps purpurea [3], Neurospora crassa [4], Magnaporthe oryzae [5], Botrytis cinerea [6], Fusarium graminearum [7], Fusarium oxysporum [8] and Fusarium verticillioides [9]. Moreover, AtfA is involved in the virulence of the human pathogenic fungi, e.g., Aspergillus fumigatus [10,11] and plant pathogenic fungi [3,5,6,7].
In Aspergillus nidulans, deletion of atfA resulted in oxidative, osmotic and fungicide stress sensitivity of the cultures [12,13,14,15]. The viability of the conidiospores also decreased under heat stress, in the presence of H2O2, and during storage at 4 °C in the ΔatfA mutant [12,13,14,15]. Microarray analysis of the ΔatfA mutant elucidated several stress-responsive genes likely to be regulated by AtfA, including mitotic cell cycle, nitrate reduction, tricarboxylic acid cycle, endoplasmic reticulum-related as well as FeS cluster assembly genes and elements of the two-component signal transduction system (phkB, phkA, tcsB, nikA, hk-8-1, hk-8-2, hk-8-3, hk-8-4) [16,17,18]. The global transcriptional effects of the atfA gene deletion were stress-type-specific and manifested mainly under menadione stress [16,17,18]. In contrast to the ΔatfA strain, the ΔatfB mutant was not sensitive to the tested oxidative stress generating agents, namely menadione sodium bisulfite (MSB), t-butyl-hydroperoxide or diamide; however, it was sensitive to NaCl stress [19].
In Aspergillus oryzae, conidia of the ΔatfA mutant were more sensitive to oxidative stress than those of the ΔatfB [20,21]. Some genes involved in the oxidative stress defense, e.g., putative catalase, thioredoxin and glutathione metabolic genes, were repressed in the ΔatfA mutant according to the microarray analysis, which confirms the observed stress-sensitive phenotype of the ΔatfA mutant [21]. In A. oryzae, atfA is involved in conidial storage stability [21]. Therefore, conidia of the ΔatfA showed lower germination rate compared to the control [21]. Most likely, atfA controls glutamate biosynthesis, which is necessary for germination of conidiospores [21]. atfB expression was significant in the late phase of culture growth and coincided with the initiation of conidiation in A. oryzae [21]. Furthermore, AtfB-regulated genes, such as catA (encoding a catalase) or a putative trehalose-6-phosphate synthase gene are most likely associated with conidial development and conidial stress tolerance [21].
bZIP transcription factors can form homodimers with themselves and heterodimers with other bZIPs and interact physically with stress-signaling proteins as well [22]. For example, in Schizosaccharomyces pombe, Atf1 and Pcr1 bZIPs form heterodimers and activate the majority of stress genes [23,24,25]. Evaluation of microarray data confirmed, however, that some stress genes are regulated by Atf1 independently of Pcr1 under osmotic stress (elicited with 0.4 M KCl) [24]. Moreover, Atf1 physically interacts with Cid2 poly(A) polymerase to regulate further genes [26].
In this study, we performed RNAseq-based transcriptome analysis in ΔatfA, ΔatfB, ΔatfAΔatfB and control strains from MSB-treated and untreated surface cultures in vegetative and conidial development stages in order to understand more deeply the regulatory functions of AtfA and AtfB. We focused on the possible interactions between AtfA and AtfB during the evaluation process.
2. Materials and Methods
2.1. Strains and Culture Condition
A. nidulans strains (control, ΔatfA, ΔatfB, ΔatfAΔatfB) [19] were maintained on Barratt’s nitrate minimal medium (NMM) [27], and NMM agar plates were incubated at 37 °C for 6 d [14]. Conidia harvested from these 6-day-old plates were used in all further experiments.
For RNA sequencing, freshly grown conidiospores (105 suspended in 5 μL aliquots of PBS–0.1% Tween 20) were spread on NMM plates with or without 0.04 MSB (menadione sodium bisufite), and surface cultures were incubated at 37 °C. Mycelia were collected before the formation of conidiophores, while conidia were washed from the surface culture with PBS–0.1% Tween 20 and separated from the vegetative tissue with centrifugation and filtering through Miracloth.
2.2. RNA Sequencing
Total RNA were isolated from the menadione sodium bisulfite (MSB, a superoxide generating agent)-treated and untreated cultures of the THS30.3 (control), ΔatfA, ΔatfB, ΔatfAΔatfB strains. Samples were taken from 20–33 hour-old (mycelial samples) and from 3-day-old (conidial samples) surface cultures of the strains. Total RNA was isolated according to Chomczynski, 1993 [28]. RNA sequencing, from library preparation to generation of fastq.gz files, was carried out at the Genomic Medicine and Bioinformatic Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary. Libraries were prepared with the TruSeq RNA Sample preparation kit (Illumina) according to the manufacturer’s protocol. Conidial and mycelial samples were sequenced (single-read 75 bp sequencing on an Illumina HiScan SQ instrument; Illumina, San Diego, CA, USA) separately, but each library pool belonging to the same cell type was sequenced in one lane of a sequencing flow cell. Depending on the sample type, 14–39 million reads per sample (mycelial samples) and 10–28 million reads per sample (conidial samples) were obtained. The FastQC package (http://www.bioinformatics.babraham.ac.uk/projects/fastqc↗, accessed on 25 January 2023) was used for quality control. Reads were aligned to the genome of A. nidulans FGSC A4 with hisat2 (version 2.1.0) [29]. The successfully aligned reads varied between 77–96% (mycelial samples) and 78–94% (conidial samples). DESeq2 (version 1.24.0) [30] was used to determine differentially expressed genes. Since conidial samples originated in two separate experiments, the batch effect was taken into consideration during the identification of differentially expressed genes in this case. RPKM values (reads per kilo base per million mapped reads) were also calculated with the edgeR package (“rpkm” function) [31] and used to visualize transcription activities of selected genes.
2.3. Evaluation of the Transcriptome Data
Transcriptomes were characterized with three types of features: Strain (control, ΔatfA, ΔatfB, ΔatfAΔatfB), treatment (untreated, MSB-treated) and cell type (mycelium, conidium). Since mycelial and conidial cultures were studied separately (e.g., the age of the studied cultures and the efficiency of RNA isolation were different), mycelial and conidial transcriptomes were not compared. We compared only transcriptomes (A vs. B) differing only in either strain or treatment. log2FC was calculated using the DESeq2 software, using B as reference. Differentially expressed genes were considered “upregulated” if log2FC > 1, “downregulated” if log2FC < −1 and “regulated” if |log2FC| > 1. “MSB stress-responsive” genes refer to genes “regulated” in an AMSB treated vs. B untreated comparison for any strain. The “atfA gene-deletion-responsive” genes are genes “regulated” in either the AΔatfA vs. Bcontrol or AΔatfAΔatfB vs. BΔatfB comparisons. The “atfB gene-deletion-responsive” genes were defined similarly. The atfA atfB gene-deletion-responsive genes were defined as genes “regulated” in the AΔatfAΔatfB vs. Bcontrol comparison.
We applied the following assumptions and simplifications during the evaluation of the data:
The following gene sets were constructed for mycelial and conidial transcriptomes:
Set0: MSB stress-responsive downregulated genes of the control strain
Set0+: MSB stress-responsive upregulated genes of the control strain
The following gene sets, containing downregulated genes, were also constructed for untreated and MSB-treated, mycelial and conidial transcriptomes.
From the ΔatfA vs. control, ΔatfB vs. control and ΔatfAΔatfB vs. control comparions (Figure S1A):
Set1: ΔatfA vs. control (atfA gene-deletion-responsive downregulated genes)
Set2: ΔatfB vs. control (atfB gene-deletion-responsive downregulated genes)
Set3: ΔatfAΔatfB vs control (atfA atfB double gene-deletion-responsive downregulated genes; this set contains the putative AtfA-dependent and AtfB-dependent genes)
Set4 = Set1\(Set2∪Set3)
Set5 = Set2\(Set1∪Set3)
Set6 = Set3\(Set1∪Set2) (putative A/B genes)
Set7 = (Set1∩Set2)\Set3
Set8 = (Set1∩Set3)\Set2 (putative AA and A-B genes)
Set9 = (Set2∩Set3)\Set1 (putative BB and A-B genes)
Set10 = Set1∩Set2∩Set3 (putative AB and A-B genes)
From the ΔatfAΔatfB vs. ΔatfB, ΔatfAΔatfB vs. ΔatfA and ΔatfAΔatfB vs. control comparisons (Figure S1B):
Set11: ΔatfA ΔatfB vs. ΔatfB (atfA gene-deletion-responsive downregulated genes)
Set12: ΔatfAΔatfB vs. ΔatfA (atfB gene-deletion-responsive downregulated genes)
Set13 = Set3
Set14 = Set11\(Set12∪Set13)
Set15 = Set12\(Set11∪Set13)
Set16 = Set13\(Set11∪Set12) (putative AB genes)
Set17 = (Set11∩Set12)\Set13
Set18 = (Set11∩Set13)\Set12 (putative AA and A-B genes)
Set19 = (Set12∩Set13)\Set11 (putative BB and A-B genes)
Set20 = Set11∩Set12∩Set13 (putative A/B and A-B genes)
The AA, AB, A/B and A-B genes were regarded as the intersection of the appropriate gene sets defined above:
Set21 = Set8∩Set18 (AA genes)
Set22 = Set9∩Set19 (BB genes)
Set23 = Set10∩Set16 (AB genes)
Set24 = Set20∩Set6 (A/B genes)
Set25 = (Set10∩Set20)∪(Set8∩Set20)∪(Set9∩Set20)∪(Set18∩Set10)∪(Set19∩Set10) (A-B genes; the union of the A-B1-5 gene sets, respectively)
AtfA-dependent and AtfB-dependent genes were regarded as the union of the appropriate gene sets defined above:
Set26 = Set21∪Set23∪Set24∪Set25 (AtfA-dependent genes)
Set27 = Set22∪Set23∪Set24∪Set25 (AtfB-dependent genes)
The gene sets containing the corresponding upregulated genes were marked from Set1+ to Set27+.
Note, AtfA-dependent genes (similarly to the AtfB-dependent genes) were determined from two comparisons of the four strains (ΔatfA vs. control and ΔatfA-ΔatfB vs. ΔatfB as well as ΔatfB vs. control and ΔatfA-ΔatfB vs. ΔatfA) to reduce the number of misidentified genes. These comparisons were carried out under two culturing conditions (untreated and MSB-treated cultures) in two types of cells (mycelium and conidium). This way we obtained four AtfA-dependent and four AtfB-dependent gene sets. Since AtfA- or AtfB-dependence can depend on the culturing conditions and the cell types, these gene sets were studied separately.
AtfA- and AtfB-dependent gene sets were characterized by gene set enrichment analyses. For it, “Functional Catalogue” (FunCat), “Gene Ontology” (GO) and “Kyoto Encyclopedia of Genes and Genomes pathway” (KEGG pathway) terms were used with the FungiFun2 package (https://elbe.hki-jena.de/fungifun/fungifun.php↗, accessed on 25 January 2023) applying default settings. Only hits with a corrected p-value < 0.05 were regarded as significantly enriched in the studied gene set.
The enrichment of the following gene groups in the AtfA- and AtfB-dependent gene sets were also tested by the Fisher’s exact test with the “fisher.test” function of R project (www.R-project.org/↗, accessed on 25 January 2023):
“Lactose utilization” genes. This gene group contains the Leloir and oxido-reductive pathways of galactose utilization [32] as well as known and putative β-galactosidase and lactose permease genes according to Fekete et al. 2012, 2016 [33,34] and Gila et al. 2022 [35].
“Antioxidant enzyme” genes. Genes of known, or putative superoxide dismutases, catalases, peroxidases, and the glutathione/glutaredoxin/thioredoxin redox system according to Gila et al. 2021 [36].
“Glycolysis” genes, “Oxidative pentose-phosphate shunt” genes, “Ribose metabolism” genes and “TCA cycle” genes. Genes described by Flipphi et al. 2009 [37].
“Carbohydrate-active enzyme” (CAZyme) genes. Genes collected from the Carbohydrate-active Enzymes Database (http://www.cazy.org↗, accessed on 25 January 2023).
Phosphorelay response regulator activity, iron-sulfur cluster assembly, “Respiration”, and “Transcription factor” genes. These groups were constructed based on the related GO terms and their child terms [35,36].
“Secondary metabolism cluster” genes. Manually or experimentally determined secondary metabolite cluster genes collected by Inglis et al. 2013 [38] and gene set enrichment analysis was carried out with the clusters separately.
3. Results
3.1. Deletion of atfA Downregulates atfB
Mycelial and conidial transcriptomes from four strains (control, ΔatfA, ΔatfB, ΔatfA ΔatfB) at two different culturing conditions (untreated, MSB-treated) were determined. Changes in either feature (strain, treatment) had substantial effects on the transcriptomes (Figure S2). Genes responsive for gene deletions (in untreated and MSB-treated cultures), for MSB treatment (in the control strain) or that showed AtfA- and/or AtfB-dependence were identified in both mycelial and conidial samples (Table 1, Table 2 and Table S1).
MSB treatment and deletion of the atfB gene did not upregulate or downregulate the atfA gene in atfA+ strains (Figure 1). In contrast, the presence of MSB (in the case of mycelial samples) and the deletion of atfA (in both mycelial and conidial samples) downregulated the atfB gene (Figure 1). This means that AtfA can affect the transcription of AtfB-dependent genes via atfB transcription; therefore, some of the genes putatively regulated by both AtfA and AtfB may be genes that were regulated directly only by AtfB. These genes can potentially occur in any gene sets but especially in those where the effect of atfB deletion was stronger than or equal with that of the atfA gene deletion: AB (Set23), A-B1 and A-B5 (Set25) gene sets (Table 1 and Table 2). Importantly, no genes belonging to the A-B5 (Set25) gene set were identified (Table 1 and Table 2).
Transcriptional profile of theandgenes. (,): Expression ofin MSB treated and untreated cultures of the wild type and the Δstrain. (,): Expression ofin MSB treated and untreated cultures of the wild type and the Δstrain. Mean ± SD RPKM values calculated from three biological replicates of mycelial (,) and conidial (,) samples are presented. a—downregulated gene relative to the untreated control cultures, b—downregulated gene relative to the MSB treated control cultures. atfA atfB atfA atfB atfB atfA A B C D A C B D
| Gene Set | Mycelium from Untreated Cultures | Mycelium from MSB-Treated Cultures | Overlap between MSB-Treated and Untreated Cultures |
|---|---|---|---|
| Responsive togene deletion (Set1 and Set1)atfA+ | 326 upregulated genes865 downregulated genes | 255 upregulated genes583 downregulated genes | 85 upregulated genes336 downregulated genes |
| Responsive togene deletion (Set2 and Set2)atfB+ | 213 upregulated genes159 downregulated genes | 201 upregulated genes77 downregulated genes | 71 upregulated genes12 downregulated genes |
| Responsive todouble-gene deletion (Set3 and Set3)atfA atfB+ | 200 upregulated genes457 downregulated genes | 131 upregulated genes296 downregulated genes | 45 upregulated genes142 downregulated genes |
| AtfA-dependent genes(Set26)a | 329 genes(236 AA, 16 AB, 40 A/B, 1 A-B1, 3 A-B2 and 33 A-B4 genes)(10 upregulated and 218downregulated MSB stress-responsive genes)b | 240 genes(232 AA, 2 AB, 4 A/B and 2 A-B3 genes)(17 upregulated and 143downregulated MSB stress-responsive genes)b | 110 genes |
| AtfB-dependent genes (Set27) | 96 genes(3 BB, 16 AB, 40 A/B, 1 A-B1, 3 A-B2 and 33 A-B4 genes)(2 upregulated and 68downregulated MSB stress-responsive genes)b | 9 genes(1 BB, 2 AB, 4 A/B and 2 A-B3 genes)(1 upregulated and 3 downregulated MSB stress-responsive genes) | 3 genes |
| Gene Seta | Conidium from Untreated Cultures | Conidium from MSB-Treated Cultures | Overlap between MSB-Treated and Untreated Cultures |
|---|---|---|---|
| Responsive togene deletion (Set1 and Set1)atfA+ | 1875 upregulated genes (82; 25%)2116 downregulated genes (326; 38%)c | 1386 upregulated genes (57; 22%)1480 downregulated genes (167; 29%) | 902 upregulated genes1274 downregulated genes |
| Responsive togene deletion (Set2 and Set2)atfB+ | 117 upregulated genes (5; 2%)396 downregulated genes (36; 23%) | 74 upregulated genes (7; 3%)161 downregulated genes (1; 1%) | 30 upregulated genes108 downregulated genes |
| Responsive todouble-gene deletion (Set3 and Set3)atfA atfB+ | 1604 upregulated genes (32; 16%)2018 downregulated genes (248; 54%) | 1553 upregulated genes (27; 21%)1547 downregulated genes (125; 42%) | 848 upregulated genes1374 downregulated genes |
| AtfA-dependent genes (Set26) | 1496 genes (185; 56%)(1079 AA, 80 AB, 84 A/B, 13 A-B1, 75 A-B2, 4 A-B3 and 161 A-B4 genes)(6 upregulated and 319downregulated MSB stress-responsive genes)b | 1143 genes (105; 44%)(989 AA, 41 AB, 8 A/B, 2 A-B1, 12 A-B2 and 91 A-B4 genes)(21 upregulated and 154downregulated MSB stress-responsive genes)b | 1043 genes |
| AtfB-dependent genes (Set27) | 439 genes (26; 27%)(22 BB, 80 AB, 84 A/B, 13 A-B1, 75 A-B2, 4 A-B3 and 161 A-B4 genes)(1 upregulated and 178downregulated MSB stress-responsive genes)b | 155 genes (1; 11%)(1 BB, 41 AB, 8 A/B, 2 A-B1, 12 A-B2 and 91 A-B4 genes)(5 upregulated and 22 downregulated MSB stress-responsive genes) | 114 genes |
3.2. Most of the AtfB-Dependent Genes Show AtfA-Dependence in Mycelia of Untreated Cultures
Many more atfA gene-deletion-responsive genes were found in untreated mycelial samples than atfB gene-deletion-responsive genes (Table 1). The difference between the ΔatfA and the ΔatfB strains was more obvious in the case of the downregulated genes than with the upregulated ones (Table 1). Altogether, 329 AtfA- and 96 AtfB-dependent genes were identified in these cultures, and most of the AtfB-dependent genes showed AtfA-dependence as well (Table 1). The high number of AtfA-dependent genes relative to the number of AtfB-dependent genes concurs well with atfA gene deletion having stronger transcriptomical (Figure S2, Table 1) and physiological [19] consequences than atfB gene deletion.
According to the type of possible interactions between the regulatory effects of AtfA and AtfB, genes that showed both AtfA- and AtfB-dependence were grouped into three sets: AB, A/B, and A-B (Figure 2, Table 1). The most interesting group was the AB set. The transcriptional pattern of the related genes (Figure 2, Table S2) suggests that both AtfA and AtfB were needed for their normal (“wild type”) activity. Besides the genes regulated by AtfA via regulation of the atfB gene, it is possible that some of these genes were regulated by an AtfA-AtfB heterodimer. The majority of the genes under both AtfA and AtfB regulations belonged to the A/B or A-B gene sets (Table 1 and Table S2), suggesting that the missing transcription factor was completely (A/B) or at least partially (A-B) substituted with the other transcription factor. In the case of the most A-B genes, atfA gene deletion had a stronger consequence than that of atfB (A-B2 and A-B4 genes) (Figure 2, Table S2).
Transcriptional pattern of selected genes potentially regulated by both AtfA and AtfB. (,): AN5994 and AN2583 (AB genes; Set 23), (,): AN5984 and AN7321 (A/B genes; Set24), (,): AN4299 and AN0759 (A-B1 genes; Set25), (,): AN1814 and AN10368 (A-B2 genes; Set25, (,): AN9320 and AN10995 (A-B3 genes; Set25), (,): AN6856 and AN2638 (A-B4 genes; Set25) (see also). Mean ± SD of the three biological replicates from mycelial (,,,,,) and conidial (,,,,,) samples of untreated (–,–) and MSB-treated () cultures are presented. A B C D E F G H I J K L A C E G I K B D F H J L A D F L E Figure S2
3.3. AtfB Regulates Only Few Genes in Mycelia of MSB-Treated Cultures
The transcription of fewer genes was affected by atfA and/or atfB gene deletions on MSB than in untreated cultures (Table 1). Only a few AtfB-dependent genes (10 genes) were found in this case, and most of these genes were AtfA-dependent too (Table 1). This concurs well with the observation that atfB was downregulated by MSB stress in the control strain (Figure 1). Not surprisingly, the ΔatfB mutant was as sensitive to MSB stress as the control strain [19].
The overlaps between the MSB-treated and untreated cultures in the cases of the gene-deletion-responsive gene sets and the AtfA-dependent gene sets were relatively small (Table 1), supporting the view that AtfA regulates (directly or indirectly) different genes in mycelia under different culturing conditions [16,17,18]. Surprisingly, the AtfA-dependent gene set of MSB-treated cultures, similarly to the AtfA and AtfB-dependent gene sets of untreated cultures, was enriched in MSB stress-responsive downregulated genes (Table 1), i.e., many genes that were downregulated by the presence of MSB showed further downregulation in the absence of AtfA. This behavior suggests that one of the main functions of AtfA in cultures that have adapted to the presence of MSB is not to keep high the transcriptional activity of genes upregulated by the stress treatment but to prevent the excessive downregulation of genes downregulated under this stress. Of course, this does not exclude that several genes are upregulated by AtfA during the early stress response of MSB stress.
3.4. AtfB, Similarly to AtfA, Increases Importance in Conidia
The transcriptional activity of both atfA and atfB was much higher in conidia than in mycelial samples (Figure 1). Not surprisingly, huge numbers of atfA and/or atfB gene-deletion-responsive and AtfA- and/or AtfB-dependent (Table 2) genes were recorded in conidial samples, demonstrating that AtfA and AtfB are more important regulators of the physiology of (germinating) conidia than of the vegetative mycelia. MSB treatment did not reduce the abundance of atfB transcript in conidia (Figure 1); however, the number of AtfB-dependent genes decreased more radically in the presence of MSB than did AtfA-dependent genes (Table 2).
Again, most of the AtfB-dependent genes showed AtfA-dependence as well (Table 2 and Table S2). Among the genes showing both AtfA- and AtfB-dependence, the AB, A/B, A-B2 and A-B4 genes were the most abundant (Table 2 and Table S2). Accordingly, AtfB regulates only few genes independently of AtfA (BB genes, Table 2 and Table S1). Some genes are regulated together with AtfA (AB genes, Table 2), and in the case of the most AtfB-dependent genes AtfA can replace the missing AtfB (A/B, A-B2, A-B4 genes, Table 2 and Table S2).
MSB treatment substantially modified the transcriptome of both conidia and mycelia: 485 and 786 upregulated and 1070 and 912 downregulated MSB stress-responsive genes were found in conidial and mycelial samples, respectively. The effect of MSB treatment on the conidial transcriptome suggests that stresses affecting the physiology of mycelia also affect the transcriptome of conidia produced by the stress-treated mycelia. Interestingly, these changes modified only slightly the regulatory role of AtfA and AtfB in conidia: The overlaps between the AtfA- (AtfB-) dependent genes of conidia from untreated and MSB-treated cultures were large, in contrast to those in mycelial samples (Table 1 and Table 2). It can be understandable if we assume that the transcriptional changes of mycelia reflect how vegetative cells adapted to the presence of MSB, while the transcriptional changes in conidia show how the “experiences” of mycelia are implemented into the germination strategies of conidia. In other words, conidia do not have to adapt to all consequences of long-term MSB treatment; they have to prepare only for the increased possibility of MSB stress during their germination.
Gene sets identified with conidial samples showed surprisingly low overlap with the appropriate mycelial gene sets (Table 2). Even in the case of the AtfA-dependent genes, the overlap was only around 50% (Table 2). This huge difference between mycelial and conidial samples suggests that AtfA and AtfB had different functions and that atfA and atfB gene deletions had different consequences in mycelia and in conidia.
3.5. AtfA Affects Carbohydrate Metabolism and Light Dependent Processes
Gene set enrichment analyses were carried out with four AtfA- and four AtfB-dependent gene sets (identified in untreated mycelial and conidial samples as well as in MSB-treated mycelial and conidial samples) (Table 3, Table 4, Tables S3 and S4).
The AtfA-dependent gene sets were enriched with carbohydrate metabolism genes. Among them, AtfA-dependence of glycolytic genes in the case of the conidial samples is the most notable (Table S3). Phosphorelay response regulator genes were enriched in all AtfA-dependent gene sets but the untreated mycelial samples (Table 4 and Table S4), while enrichment of iron-sulfur cluster assembly genes was characteristic for the AtfA-dependent genes of conidial samples (Table 4 and Table S4). Interestingly, antioxidant enzyme genes were enriched only in the AtfA-dependent gene set of conidial samples from untreated cultures (Table 4 and Table S4). Enrichment of TCA cycle and respiration genes was characteristic for the AtfA-dependent gene set of conidial samples from MSB-treated cultures. Most of the above-mentioned genes were regulated only by AtfA (AA genes) (Table S4). Certain secondary metabolite cluster genes also showed AtfA-dependent regulation (Table 4 and Table S4). Among them, the Emericellamide cluster is notable since, depending on the treatment, four or five genes out of the five cluster genes were AtfA-dependent, including the easB gene (AN2547) encoding the polyketide synthase (Figure S3, Table S3). Interestingly, in untreated cultures, these genes showed both AtfA- and AtfB-dependence (A/B genes), while in MSB-treated cultures, where atfB was downregulated (Figure 1), they were only AtfA-dependent (AA genes).
Altogether 87 genes showed AtfA-dependence in all the four AtfA-dependent gene sets. Most of them encode proteins with unknown functions (Table 5). The genes with known or predicted function includes the catA catalase, six genes involved in carbohydrate metabolism as well as the hk-8-1 and hk2 putative histidine-containing phosphotransfer protein genes and 10 genes involved in light sensing and light response (Tables S1 and S4).
Only 23 AtfB-dependent genes were found that never showed AtfA-dependence (Table S1). Out of them, the following four genes are notable: AN8953 (agdB), putative α-glucosidase and AN3402 (amyB), putative α-amylase genes; AN7619 (calA), involved in early conidial germination; and AN2099, putatively encoding alternative oxidase.
| Culture | AtfA-Dependent Genes (Set26) | AtfB-Dependent Genes (Set27) |
|---|---|---|
| Mycelium(untreated) | C-compound and carbohydrate metabolism; galactose metabolic process | |
| Mycelium(MSB-treated) | Amine/polyamine transport | |
| Conidium(untreated) | C-compound and carbohydrate metabolism; C-compound and carbohydrate transport; glycolysis and gluconeogenesis; pentose phosphate pathway; fructose and mannose metabolism; pyruvate metabolism; glyoxylate and dicarboxylate metabolism; homeostasis of phosphate; proton-driven antiporter; sodium-driven symporter;biosynthesis of secondary metabolites;cellular sensing and response to external stimulus; oxidative stress response | C-compound and carbohydrate metabolism; C-compound and carbohydrate transport; glycolysis and gluconeogenesis; starch and sucrose metabolism; valine, leucine and isoleucine degradation;biosynthesis of secondary metabolites; |
| Conidium(MSB-treated) | C-compound and carbohydrate metabolism; glycolysis and gluconeogenesis; pentose phosphate pathway; fructose and mannose metabolism; glyoxylate and dicarboxylate metabolism; TCA cycle;homeostasis of phosphate;biosynthesis of secondary metabolites;cellular sensing and response to external stimulus;peroxisome |
| Culture | AtfA-Dependent Genes (Set26) | AtfB-Dependent Genes (Set27) |
|---|---|---|
| Mycelium(untreated) | Secondary metabolism: No PKS/NRPS backbone cluster 1, Microperfuranone cluster, AN2924 cluster; AN9005 cluster; AN10297 cluster; Emericellamide cluster | Secondary metabolism: AN2924 cluster; AN10297 cluster; Emericellamide (eas) cluster |
| Mycelium(MSB-treated) | CAZyme genesPhosphorelay response regulator genesSecondary metabolism: Aspercryptin cluster, AN2924 cluster; AN10297 cluster; Emericellamide (eas) cluster | |
| Conidium(untreated) | Glycolysis; Pentose-phosphate shunt; Leloir pathwayAntioxidative enzyme genes; iron-sulfur cluster assemblyPhosphorelay response regulator genesSecondary metabolism: AN9005 cluster; AN1594 cluster; AN10297 cluster; AN1242 cluster | Transcription factorsSecondary metabolism: AN9005 cluster; AN10297 cluster |
| Conidium(MSB-treated) | Glycolysis; pentose-phosphate shunt; Leloir pathway; TCA cycle; respirationIron-sulfur cluster assemblyPhosphorelay response regulator genesSecondary metabolism: AN1594 cluster; AN10297 cluster; AN1242 cluster |
| Gene ID | Gene Name | Description | AtfA/AtfB-Dependence in | |||
|---|---|---|---|---|---|---|
| Mycelium (Untreated) | Mycelium (MSB-Treated) | Conidium (Untreated) | Conidium (MSB-Treated) | |||
| Light dependent regulation | ||||||
| AN0387 | cryA | senses UVA and blue light | AA | AA | AA | AA |
| AN5056 | induced by light | A-B | AA | AA | AA | |
| AN9285 | ccgA | induced by light | AA | AA | AA | A-B |
| AN4299 | induced by light | A-B | AA | AA | AA | |
| AN8638 | cetJ | induced by light | AA | AA | AA | AA |
| AN0045 | induced by light | A-B | AA | AA | AA | |
| AN0693 | induced by light | AA | AA | AA | AA | |
| AN5004 | induced by light | A-B | AA | A-B | AA | |
| AN8339 | induced by light | AA | AA | AA | AA | |
| AN8641 | induced by light | A-B | AA | A-B | AA | |
| Carbohydrate metabolism | ||||||
| AN8138 | aglC | α-galactosidase | A-B | AA | A-B | AA |
| AN2835 | predicted D-arabinono-1,4-lactone oxidase activity | AA | AA | A-B | AA | |
| AN8639 | putative α,α-trehalose-phosphate synthase | AA | AA | A-B | A-B | |
| AN10060 | putative α-amylase | AA | AA | AA | AA | |
| AN3200 | putative β-glucuronidase | AA | AA | AA | AA | |
| AN9180 | putative transketolase | AA | AA | AA | AA | |
| Other | ||||||
| AN2470 | cellular response to nitrosative stress | AA | AA | AA | AA | |
| AN8637 | catA | conidia-specific catalase | AA | AA | AA | AA |
| AN2581 | hk-8-1 | putative histidine-containing phosphotransfer protein | AA | AA | AA | AA |
| AN7945 | hk2 | putative histidine-containing phosphotransfer protein | AA | AA | AA | AA |
| AN9005 | putative polyketide synthase | AA | AA | AB | AB | |
4. Discussion
bZIP-type transcription factors are important regulators of developmental processes, stress responses and secondary metabolite production in filamentous fungi [19,39,40,41,42]. They can act as homodimers, and they can also regulate processes forming heterodimers with other bZIP-type transcription factors or physically interact with other signaling proteins [22]. In A. fumigatus, AtfA physically interacts with other three bZIP transcription factors, namely AtfB, AtfC and AtfD, as well as with the MAPK SakA to coordinate stress responses [11]. According to the stress sensitivity assays, the ΔatfAΔatfB double-gene deletion mutant was as sensitive to the oxidative stress generating menadione sodium bisulfite or to the cell wall stress-generating agents calcofluor white (CFW) and CongoRed as the corresponding single mutants in A. fumigatus [11]. In A. parasiticus, AtfB and AP-1 bZIPs form functionally active heterodimers and regulate aflatoxin production and oxidative stress responses [39]. In the case of A. nidulans, Lara-Rojas et al. 2011 [2] suggested possible physical interaction between AtfA and AtfB. Here we studied genome-wide transcriptional changes in mycelia and conidia of ΔatfA, ΔatfB, ΔatfAΔatfB gene-deletion mutants and the control strain in the presence and absence of MSB to collect data on the possible interactions between AtfA and AtfB.
The high transcriptional activity of atfA (Figure 1) and the genome-wide transcriptional as well as phenotypic consequences of atfA gene deletion (Table 1 and Table 2; [15,19]) suggest the importance of AtfA-dependent regulations in both mycelia and conidia. The data also support the view that AtfA was a more important regulator in conidia than in vegetative mycelia (Figure 1, Table 1 and Table 2). This concurs well with the observations of Hagiwara et al. 2008 [12] and Balázs et al. 2010 [14] that AtfA protects conidia under different temperatures as well as against oxidative stress. AtfA plays a paramount role in the regulation of conidium-specific genes in other Aspergillus species as well. In a comprehensive study, more than 50% of the conidia-associated genes (CAGs) proved to be atfA-dependent in A. fumigatus, A. oryzae and A. niger [43].
Many genes regulated (directly or indirectly) by AtfA have been identified so far in Aspergillus species. These genes–among others–encode antioxidant proteins, heat shock proteins, phosphorelay response regulators, iron-sulfur cluster assembly proteins, enzymes involved in trehalose and glycogen formation, utilization of different carbohydrates or secondary metabolite synthesis as well as light response of conidia [11,16,17,18,21,43,44,45,46,47]. Our data support the role of AtfA in the transcription of antioxidant enzyme and phosphorelay response regulator genes, trehalose and glycogen metabolism genes, glucose utilization genes as well as secondary metabolite cluster genes (Table 3, Table 4 and Table S4). The cytoplasmic phytochrome FphA (acting as red-light sensor) activates AtfA via the high-osmolarity glycerol (HOG) MAPK pathway in A. nidulans [46,47]. Not surprisingly, several light-dependent genes were identified as AtfA-dependent in our study (Table 5 and Table S1). Among them, cryA encoding a putative UV-A/blue light sensor (cryptochrome) [48] is particularly interesting. Yu et al. 2016 [46] found that the blue-light-dependent activation of the HOG pathway depends on FphA only, but not on the blue-light sensor LreA-LreB complex. One explanation of this observation is that another blue-light receptor (e.g., CryA) is involved in this process and its activity is somehow regulated by FphA [46]. The AtfA-dependent transcription of cryA (Table 5 and Table S1) also supports the view that there is interaction between the blue- and red-light dependent signaling pathways.
Stress tolerance of conidia highly depends on culturing conditions occurring during conidiogenesis [49,50,51,52]. Not surprisingly, MSB stress treatment (of mycelia) affected both the mycelial and conidial transcriptomes (Table 1 and Table 2). The regulatory role of AtfA also depended on culturing conditions: Different genes showed AtfA-dependence in MSB stress-adapted and unstressed cultures (Table 1 and Table 2). Importantly, the difference between the AtfA-dependent gene sets was more obvious in mycelial than in conidial samples (Table 1 and Table 2). It is reasonable to assume that conidia, de facto, do not have to adapt to the presence of MSB. Conidiogen cells alter the mRNA content of conidia only to prepare them for the stresses that (according to their “experiences”) most likely will occur during germination.
Transcriptional activity of atfB was low in mycelial samples; however, atfB mRNA was abundant in conidia (Figure 1), suggesting that this transcription factor may have a minor regulatory role during vegetative growth. The small transcriptomic (Table 1 and Table 2) and phenotypic [19] consequences of atfB gene deletion relative to that of atfA also support this view.
The majority of the AtfB-dependent genes were AtfA-dependent as well (Figure 2, Table 1, Table 2 and Table S2), which concurs well with results of Sakamoto et al. 2009 [21], who also found that most of the stress-responsive genes regulated by AtfB were also AtfA-dependent in A. oryzae. Some of the genes that showed dual AtfA- and AtfB-dependent regulation needed both AtfA and AtfB for their “normal” expression (AB genes on Figure 2 and in Table 1, Table 2 and Table S2). It is possible that some of them are regulated by an AtfA–AtfB heterodimer; however, without experimental justification, other possibilities cannot be ruled out. The majority of the AtfA-, AtfB-dependent genes were genes where one of the two transcription factors could completely or partially substitute the missing other transcription factor (A/B and A-B genes on Figure 2 and in Table 1, Table 2 and Table S2). Some of these genes may be regulated by both transcription factors directly, which also allows physical interaction between the two transcription factors on the promoters. Moreover, atfB itself also showed AtfA-dependence; deletion of atfA downregulated atfB in both mycelial and conidial samples irrespectively of the presence of MSB (Figure 1). Therefore, some of the genes showing both AtfA- and AtfB-dependence can be AtfB-dependent genes regulated by AtfA only indirectly via atfB transcription. The interaction between AtfA and AtfB has also been suggested by the overexpression of atfB being able to compensate for the increased MSB sensitivity of the ΔatfA mutant [19]. Moreover, sterigmatocystin production was completely inhibited by atfA gene deletion; however, it was restored in the ΔatfAΔatfB mutant [19]. Importantly, we found a few AtfB-dependent genes that did not show AtfA-dependence (Table 1, Table 2, Tables S1 and S4). Among them, calA is notable, since it contributes to the germination of conidia [53,54] which may explain why conidia of the ΔatfB strain were sensitive to high temperature [19].
Our results support the view that (1) AtfA and AtfB have some regulatory functions in mycelia; however, they are more important regulators in conidia. (2) Besides regulating antioxidant enzyme genes, phosphorelay response regulator genes, secondary metabolite cluster genes, and light-dependent genes, AtfA also control genes of carbohydrate metabolism (e.g., trehalose and glycogen metabolism genes as well as glucose utilization genes) in A. nidulans, as it was also found in A. fumigatus [11]. (3) There should be a complex genetic and possibly physical interaction between the two transcription factors where AtfA is the dominant player, and the main function of AtfB is supporting the regulatory role of AtfA. Understanding the nature of the interaction between the two transcription factors needs further investigations: e.g., determining the AtfA- and AtfB-binding sites on the promoters at genome level by combining chromatin immunoprecipitation assays with sequencing (ChIP-Seq), and justifying the AtfA–AtfB heterodimer formation using a bimolecular fluorescence complementation (BiFC) technique. Both are in progress in our laboratory.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cells12030463/s1↗, Figure S1: Identification of potentially AtfA and AtfB dependent genes; Figure S2: Principal component (PC) analysis of the transcriptomes; Figure S3: Transcriptional profile of easB encoding the polyketide synthase of the Emericellamide secondary metabolite cluster in mycelial samples; Table S1: Lists and characteristics of AtfA- and AtfB-dependent genes; Table S2: List, characteristics and RPKM values of genes that showed both AtfA- and AtfB-dependence in mycelial and conidial samples; Table S3: Results of the gene set enrichment analyses for AtfA- and AtfB-dependent genes; Table S4: Characterization of AtfA- and AtfB-dependent genes by their known or putative functions.
Author Contributions
Conceptualization I.P. and J.-H.Y.; methodology B.K., M.-K.L., T.E., K.A. and É.L., writing T.E., J.-H.Y., I.P. and É.L. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Transcriptome data sets are available with the GSE220052↗ accession number of the Gene Expression Omnibus database (GEO; http://www.ncbi.nlm.nih.gov/geo/↗, accessed on 25 January 2023).
Conflicts of Interest
The authors declare that there is no conflict of interest.
Funding Statement
Project no. TKP2021-EGA-20 (Biotechnology) has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the TKP2021-EGA funding scheme. This research was also supported by the National Research, Development and Innovation Office with the grants NKFIH K131767 and NN125671. The work at UW-Madison was supported by the UW Food Research Institute.
Footnotes
References
Associated Data
Supplementary Materials
Data Availability Statement
Transcriptome data sets are available with the GSE220052↗ accession number of the Gene Expression Omnibus database (GEO; http://www.ncbi.nlm.nih.gov/geo/↗, accessed on 25 January 2023).