- Research article
- Open Access
PacC and pH–dependent transcriptome of the mycotrophic fungus Trichoderma virens
© Trushina et al.; licensee BioMed Central Ltd. 2013
- Received: 20 October 2012
- Accepted: 23 February 2013
- Published: 28 February 2013
In fungi, environmental pH is an important signal for development, and successful host colonization depends on homeostasis. Surprisingly, little is known regarding the role of pH in fungal-fungal interactions. Species of Trichoderma grow as soil saprobes but many are primarily mycotrophic, using other fungi as hosts. Therefore, Trichoderma spp. are studied for their potential in biocontrol of plant diseases. Particularly in alkaline soil, pH is a critical limiting factor for these biofungicides, whose optimal growth pH is 4–6. Gaining an understanding of pH adaptability is an important step in broadening the activity spectrum of these economically important fungi.
We studied the pH-responsive transcription factor PacC by gene knockout and by introduction of a constitutively active allele (pacC c ). ΔpacC mutants exhibited reduced growth at alkaline pH, while pacC c strains grew poorly at acidic pH. In plate confrontation assays ΔpacC mutants showed decreased ability to compete with the plant pathogens Rhizoctonia solani and Sclerotium rolfsii. The pacC c strain exhibited an overgrowth of R. solani that was comparable to the wild type, but was unable to overgrow S. rolfsii. To identify genes whose expression is dependent on pH and pacC, we designed oligonucleotide microarrays from the transcript models of the T. virens genome, and compared the transcriptomes of wild type and mutant cultures exposed to high or low pH. Transcript levels from several functional classes were dependent on pacC, on pH, or on both. Furthermore, the expression of a set of pacC-dependent genes was increased in the constitutively-active pacC c strain, and was pH-independent in some, but not all cases.
PacC is important for biocontrol-related antagonism of other fungi by T. virens. As much as 5% of the transcriptome is pH-dependent, and of these genes, some 25% depend on pacC. Secondary metabolite biosynthesis and ion transport are among the relevant gene classes. We suggest that ΔpacC mutants may have lost their full biocontrol potential due to their inability to adapt to alkaline pH, to perceive ambient pH, or both. The results raise the novel possibility of genetically manipulating Trichoderma in order to improve adaptability and biocontrol at alkaline pH.
- Cell Wall Integrity
- Secondary Metabolite Biosynthesis
- Cell Wall Integrity Pathway
- Hygromycin Resistance Cassette
- Confrontation Assay
Fungi, whether they are saprophytes or pathogens, are able to detect and adapt to a wide range of environmental pH values. The ability of fungal cells to maintain homeostasis is exemplified in their capacity to grow in both acid and alkaline pH conditions. Furthermore, pH levels often serve as crucial external cues, providing information about the local environment. It is known that fungi respond to ambient pH levels via activation of a dedicated transcription factor, PacC [1–5]. This response is initiated by a signaling cascade which begins with a cell surface sensor, PalH, a protein with seven transmembrane helices. PalH probes the extracellular pH level. PalF, an arrestin-like protein which interacts with PalH, is ubiquitinated in response to alkaline pH . The cascade leads to the activation of PacC by proteolytic cleavage and, finally, to transcriptional regulation [3, 7–10].
Fungal pathogens of animals and plants need to sense and respond to local pH. In addition, several fungal pathogens of plants were shown to raise or lower the local pH during the establishment of the disease. It is also known that pH signals program gene expression in the pathogen [11–18]. For instance, Colletotrichum gloeosporioides attacks unripe avocado fruits, but these remain resistant to the fungus until the fruits ripen. During the ripening process, the pH of the avocado pericarp increases from pH 5.2 to pH 6.3, and following this increase in pH, the decay symptoms become evident. Furthermore, the pathogen itself contributes to alkalinization. Thus, the host pH can affect the progress of disease via the production of virulence factors . There are several other examples which indicate the importance and relevance of PacC to this process: first, the pacC ortholog of Colletotrichum acutatum is essential for virulence on citrus, at the penetration stage . Second, in the vascular wilt pathogen Fusarium oxysporum, constitutive-active pacC strains were found to be less virulent than wild type strains on the tomato host . In contrast, pacC null mutants of the foliar pathogen Sclerotinia sclerotiorum were less virulent than wild type on Arabidopsis and tomato . This contrasting regulation suggests that in different species, PacC may play different roles in determining virulence. Another interesting example is Candida albicans, a commensal that can become pathogenic in susceptible hosts. This organism colonizes the oral-pharyngeal, gastrointestinal, and urogenital tracts as a commensal. Following this colonization, C. albicans can become a pathogen, infecting these tissues. It may then enter the bloodstream and disseminate to almost any tissue in the body. The C. albicans sites of action are characterised by a diversity in pH levels, e.g., acidic pH levels in the gastrointestinal and vaginal tracts, and neutral-to-alkaline levels in the oral-pharyngeal tract and in the bloodstream. Thus, a successful response to extracellular pH is critical for virulence . Trichophyton rubrum, a dermatophyte, responds to the pH level of human skin by expressing enzymes that have acid pH optima . PacC has been shown to serve as a virulence factor for Aspergillus nidulans in a mouse model: null mutants showed reduced virulence, while a constitutively active pacC allele conferred hypervirulence . The insect pathogen Metarhizium anisopliae uses pH as a signal to produce specific enzymes whose pH optima correspond to the ambient pH levels . A wide variety of genes and activities are controlled by PacC, including xylanases , permeases , siderophores , antibiotic and toxin production , and involvement in pathogenic processes [4, 21, 24].
Fungi can also attack other fungi (either by direct mycoparasitism or, to give a more inclusive definition, mycotrophy ). Prominent examples of this are found among soil fungi of the genus Trichoderma, which are being applied worldwide as biocontrol agents against soil-borne and foliar plant diseases . The biocontrol fungus antagonizes host fungi in a variety of ways: mycoparasitism, antibiotic production, induction of systemic resistance in the plant, competition for nutrients and space, modification of the local environment, and degradation of pathogen germination stimulants which are released by seeds. Trichoderma also increases the plant’s tolerance to stress by promoting growth and vigor [32–34]. Moreno-Mateos et al. have shown that several Trichoderma harzianum genes which are thought to be involved in the antagonism of host fungi (chitinase, protease, glucose permease, and the cell wall protein qid74) are regulated by pH. In T. harzianum, PacC promotes the expression of chitinase and qid74, and represses protease and glucose permease. PacC also negatively regulates the production of inhibitory metabolites. Contrary to what might have been expected in view of the increased production of inhibitors, however, mycoparasitism is decreased in the null mutant . In several Trichoderma species, conidiation depends on pH; the mode of regulation varies from one species or isolate to another . Conidiation has previously been correlated with intracellular acidification , providing an explanation as to why the pH must be low in order for conidiation to occur on buffered media . In this study, we examined an isolate of Trichoderma virens which is an aggressive mycoparasite on the sclerotia of S. rolfsii and on the hyphae and sclerotia of Rhizoctonia solani. The genome sequence of this species has recently been made available [39, 40], thus allowing a first complete analysis of pH- and PacC-regulation in a mycotroph at the level of the transcriptome.
Construction of loss- and gain-of-function mutants in the pH-sensitive regulator pacC
T. virens pacC gene
Having initiated this study before the T. virens genome project, we used sequences from other filamentous ascomycetes to identify a T. virens ortholog of pacC. Degenerate primers for nested amplification (Additional file 1) were designed from the amino acid sequences of the regions most conserved in several pacC orthologs (Aspergillus nidulans, Aspergillus oryzae and Fusarium oxysporum). A product of ~400 bp was obtained and cloned, and four additional primers were designed for PCR-based genome walking. We obtained a genomic clone including ~2 kb of upstream and downstream sequences, sufficient for the design of gene replacement constructs. The gene contains a 2094 bp ORF with three predicted introns. The predicted protein product has a molecular mass of 67 kDa and contains 617 amino acid residues. When this sequence was compared to GenBank-deposited sequences from several organisms, the best BLAST similarity scores were obtained with the PacC proteins of the Ascomycete fungi Fusarium oxysporum, Acremonium chrysogenum and Gibberella moniliformis (62%, 64% and 67% similarity, respectively). Like Trichoderma virens, all of these species belong to the class Sordariomycetes. The consensus binding site for PacC identified from Aspergillus nidulans, GCCARG, is found 9 times within the 1 kb upstream of the predicted translation start of T. virens pacC. The strong, pH-independent expression of the truncated, active, pacC c allele that we constructed suggests that PacC indeed regulates the expression of the gene that encodes it (see below). The sequence of the T. virens IMI 304061 pacC gene (this study, and genomic re-sequencing data, R. Normand, T. Katz-Ezov, N.T. and B.A.H., unpubl.) exhibits 24 SNPs relative to the corresponding gene model in T. virens Gv29.8 (the published reference strain ). These SNPs result in six predicted differences in protein sequence, four encoding amino acids with strongly similar properties to those of the sequence predicted from the reference genome, and two with weakly similar properties (Additional file 2). Thus, there are variations between two Trichoderma virens isolates in the amino acid sequence encoded by this well-conserved gene. It is unclear whether these SNPs have any functional significance.
pacC deletion mutants
To determine the function of pacC, deletion mutants (ΔpacC) were obtained by homologous integration resulting from double-crossover integration events. To this end, T. virens protoplasts were transformed with linearized plasmid DNA, using the polyethylene glycol-Ca++ method. Of about 100 transformants screened by PCR amplification with primers specific for homologous integration, we obtained two, ΔpacC1 and ΔpacC2, in which the pacC gene was replaced by the hygromycin resistance cassette. Transformants were purified by single-spore isolation, and homologous recombination was confirmed by PCR. The primer pairs, expected sizes, and PCR products obtained are provided in Additional file 3.
Construction of constitutively active pacC mutants
Constitutively active mutants (pacC c ), are expected to bypass the need for the ambient pH signal, resulting in a phenotype that mimics growth under alkaline conditions [3, 42–45]. Based on the known characterization of the proteolytic cascade activating A. nidulans PacC, we predicted that the truncation allele in T. virens that we designed (see below), would lead to a gain-of-function behavior, i.e. as a bona fide pacC c allele. Indeed, transcriptional data, including data on the pacC gene itself, provide strong support for this assumption. To this end, we constructed a pacC c line using the split-marker method (; Additional file 4). To construct the pacC c allele we designed a construct in which the C-terminal part of pacC (encoding amino acids 504–617, which are removed in processing upon activation in the cell) was replaced by the hygromycin resistance cassette. The construct also included flanking regions upstream and downstream of the gene, of ~1.1 kb each, to allow for double-crossover recombination. The transformants were isolated, purified, and confirmed by PCR amplification (Additional file 3).
Comparison of loss and gain-of function mutants to wt
Genome-wide study of PacC function
The phenotypes of the loss- and gain-of-function mutants in pacC that were studied here point to central roles for PacC in mycoparasitism. The PacC and pH-dependent transcriptomes provide insights into a variety of processes controlled by pH signaling, and into the mechanisms underlying pH homeostasis. To date, the transcriptomic consequences of pH signaling have only been studied in a relatively small number of fungal species [2, 14, 48, 49]. The diversity of signal processing among fungal species suggests that a conserved regulatory factor can have different targets in different biological models. Thus, we reasoned that the Trichoderma virens transcriptome could provide insights into the role of pH signaling in fungal-fungal interactions. To this end, T. virens cultures were exposed to a one-hour alkaline or acidic pH step by transferring them to medium titrated to pH 8.4 or pH 4 (see Methods), and subsequently harvested.
Genes selected for initial studies of pH regulation in T. virens
Transcription factor PacC
T. virens, this study
L-ornithine N5-monooxygenase SidA (2.5E-124)
ATPase, P-type (0)
Acid phosphatase (6.50E-95)
Glucose permease (0)
Aspartyl protease (0)
High affinity sugar/H+ symporter (0)
Validation of microarray results by qPCR
Genes selected from microarray data for validation by qPCR
regulation of pH - Na/H exchanger
CVNH domain-containing protein
predicted small secreted cysteine-rich protein
pH-response regulator protein palC
Fe2+/Zn2+ regulated transporter
Transcription factor PacC
peptidylprolyl isomerase A [PPIA] - normalization gene
ribosomal protein L5 [RPL5] - normalization gene
Tubulin - normalization gene
Actin - normalization gene
Classification of regulated transcripts
Secondary metabolite biosynthesis is finely tuned, and there is previous evidence for its regulation by ambient pH [45, 50, 51]. One of the proteins included in the PacC-dependent, down-regulated secondary metabolite-related gene class is a non-ribosomal peptide synthase, protein ID 37142. The gene coding for this protein, named tex15, is related to ChNPS4 of Cochliobolus heterostrophus, which has a role in conidial surface hydrophobicity . The Alternaria brassicicola ortholog of this gene is important for the development and integrity of conidia . Inspection of the T. virens genomic region near tex15 revealed a cytochrome P450 (protein ID 13148), which was also significantly down-regulated (Additional file 7). Additional members of this putative ChNPS4-like cluster were not significantly down-regulated (data not shown). Members of secondary metabolite biosynthetic clusters are known to be PacC-regulated in other fungi as well . It would be rather surprising if all of secondary metabolism were to be downregulated at alkaline pH in Trichoderma. Two genes related to siderophore biosynthesis and import are indeed upregulated at alkaline pH in T. virens (Figure 3) and in other fungi as well (see Table 1). The SidA gene, ID 33825, is located near a predicted NRPS gene: ID 85582, Tex10 . Tex10 is the ortholog of C. heterostrophus NPS2, and is responsible for the biosynthesis of the intracellular siderophore . However, although Tex10 is clustered with SidA, it is not coregulated with it. The siderophore transporter ID 43838 shown in Figure 3 is clustered in the genome with ID 44273, a predicted NRPS gene showing 41% identity with ChNPS6 of C. heterostrophus. The transcript corresponding to ID 44273 is co-regulated with the siderophore transporter ID 43838 (Figure 3). We note that there is no functional information for the gene corresponding to protein ID 44273. The most closely related NRPS to ChNPS6 in T. virens is a different gene, which corresponds to protein ID 57567 , and unfortunately is not represented in the microarray probe set. T. reesei also has two paralogous NPS6-like genes .
Eight clearly-annotated genes encoding ion transporters were in the alkaline-upregulated, PacC dependent group (Additional file 8). These are of interest because of the importance of maintaining ion homeostasis, which is also tightly linked to pH homeostasis. The P-type ATPase Ena1 of Fusarium oxysporum (ortholog of T. virens ID 67662), for example, is known to be required for growth at alkaline pH and high salt . ENA1 was one of the first targets of Rim101 (PacC) to be studied in Saccharomyces cereviseae. Protein ID 89677 is annotated as a ZIP zinc transporter. These zinc transporters have been studied in fungal pathogens: for example, zrfA–C of A. fumigatus are regulated by pH and by available Zn levels . Zrt1 of Candida albicans is important for virulence, possibly via the maintenance of cell wall integrity.
To test whether ena1 is involved in the pacC related phenotypes, we proceeded to construct a knockout mutant, Δena1, in which this gene was replaced by the hygromycin B resistance cassette, using the split-marker procedure  as described above for pacC. Growth on acidic and alkaline pH and colony morphology of Δena1 were normal. Likewise, Δena1 performed similarly to wt in confrontation assays with R. solani, and with S. rolfsii (Additional file 9). It is not surprising that the deletion of a single gene did not account for the effect of a global regulator like PacC. Thus, we reason that either there may be redundant P-Type ATPase genes, or that a loss of a combination of factors may be required to account for the ΔpacC phenotype.
Additional pH regulated genes with functional annotation
Regulation in T. virens
Species and regulation
upregulated at alkaline pH
GPR1/FUN34/yaaH ammonia exporter
upregulated at alkaline pH in Colletotrichum
upregulated at alkaline pH
glucose-repressible protein (GRG1)
upregulated at alkaline pH in Colletotrichum
upregulated at alkaline pH, PacC dependent
DFG5, a cell-wall glycoprotein involved in tolerance to alkaline pH
downregulated at alkaline pH
like NAD+ epimerase/dehydratase family, EPME
alkaline pH downregulated in Colletotrichum
downregulated at alkaline pH (2.5 downregulation trend, though below the level of significance for our cut-off criteria)
high affinity glucose transporter
alkaline pH downregulated in Colletotrichum
Secondary metabolite biosynthesis genes whose expression is not necessary at high pH could be expected to be downregulated. This would occur if interaction with particular soil microorganisms did not pose a threat (or if the soil microorganisms targeted by a particular metabolite were not available as hosts for the mycoparasite) in an alkaline environment. In contrast, siderophores are necessary for Fe uptake, which becomes increasingly difficult at higher pH. The export of ammonia increases pH. The increase in the level of the transcript for an ammonia transporter (Table 3) suggests that ammonia export is upregulated with increasing pH. This would indicate a quorum-sensing like feedback mechanism, in which local alkalinization is self-reinforcing. In this respect, it would be interesting to compare a foliar pathogen (C. gloeosporioides) with a rhizosphere resident (T. virens).
Predicted PacC binding sites
Groups of genes with expression patterns that have not been studied previously
ΔpacC pH8> ΔpacC pH4
ΔpacC pH8> ΔpacC pH4
ΔpacC pH8> ΔpacC pH4
ΔpacC pH8> ΔpacC pH4
Trichoderma spp. are widely used as biofungicides. Even though approximately 60% of all registered biofungicides are Trichoderma-based, the market size of biopesticides is only a small fraction of the total pesticide market, which is largely dominated by chemicals [31, 60]. Bioefficacy of Trichoderma, like any other biocontrol agent, is bound to be strongly influenced by environmental factors. One of the major limitations of applying Trichoderma in agricultural settings is its inability to operate in alkaline conditions, since the pH optima for Trichoderma growth, development, and activities is in the range of 4–6 . In this respect, an understanding of the pH signaling pathways might be instrumental in improving the bioefficacy of Trichoderma spp. Thus, this study was carried out with the goal of elucidating the role of the pH-responsive transcription factor PacC and the gene regulation network mediated by this transcription factor in the commercially used biofungicide T. virens. The phenotypes of loss- and gain-of-function pacC mutants studied here reveal the importance of this signaling pathway in development, and in the mycoparasitic interaction of T. virens with two important fungal pathogens, R. solani and S. rolfsii. The present study also indicates that pH regulation does not depend entirely on PacC, since we found a number of up- and downregulated genes whose dependence on pH was similar in the ΔpacC mutant and wild type (despite the fact that steady-state growth of the mutant is very slow at pH 8). This result points to the possible existence of a pH-sensing mechanism other than the PacC pathway, by which normal regulation takes place during the one-hour alkaline pH step, despite its adverse effect on the growth rate. It will be interesting to identify such alternative pathways. The pathway for transduction of pH signals in A. nidulans has been described as “mechanistically dissimilar to all other known eukaryotic signal transduction pathways” . This makes it an attractive target for antifungals, as has been proposed, for similar reasons, for the two-component signaling pathways of bacteria . In biocontrol, however, growth of the (mycoparasite) pathogen is beneficial, so the reasoning usually applied to host-pathogen interactions would need to be reversed. Strains could be selected for growth at different ambient soil pH or for growth in the rhizosphere of different crop plants. Detection of ambient pH through PacC and other mechanisms, and the resulting ability to maintain pH homeostasis, are likely general requirements for a mycoparasite to attack the host, explaining the loss of biocontrol ability in T. harzianum pacC mutants . Genetic manipulation of the global pH-dependent regulator PacC or some of its downstream target genes may be relevant for optimization of biocontrol strains according to the local environment, crop plant, and fungal host.
Our genome-wide analysis of PacC and pH regulation identified some genes that are well-known targets of regulation by pH, for example pacC itself and ena1. We also found a large number of novel genes that are promising candidates for construction of loss-of-function mutants. Several hypotheses can be proposed to explain why pH (both PacC dependent and independent) regulation is important for mycoparasitism: pH homeostasis in the face of host-mediated changes in ambient pH, a signal provided by the host, and programming of expression of hydrolytic enzymes to be expressed near the pH optima for their activity. The results, while compatible with all these mechanisms, also indicate a more complex picture. For example, several genes encoding enzymes predicted to have acid pH optima are expressed at alkaline pH. Thus, an initial alkaline pH signal may anticipate varying pH during the fungal-fungal interaction. Measurement of local pH at the microscopic level, in real time during the interaction, could provide further insight. We anticipate that gene knockout and overexpression of candidate genes identified here will be helpful in improving the pH adaptability of the most popular biofungicides, i.e., Trichoderma spp.
Fungal strains and culture conditions
T. virens[38, 64] is deposited as IMI 304061. Local isolates of R. solani and S. rolfsii were kindly provided by Dr. Ada Viterbo, Faculty of Agriculture, Hebrew University of Jerusalem, Rehovot. Wild type T. virens and R. solani were grown on potato dextrose agar (PDA; Difco) at room temperature unless otherwise indicated. Complete medium (PDYC) contained 24 g/l potato dextrose broth, 2 g/l yeast extract and 1.2 g casein hydrolysate (all from Difco). For long-term storage, a dense conidial suspension in PDYC, 20% glycerol was stored at −70°C. For hygromycin B selection, PDA was prepared with 100 μg/ml hygromycin B (Calbiochem). For phenotype assays on different pH-buffered media, the following buffers were used: for pH 4 and 5 - potassium hydrogen phthalate (Sigma-Aldrich), for pH 6 - KH2PO4, for pH 7, 8 and 9 -Trizma base (Sigma-Aldrich). For visualization of pH changes, Phenol Red (Riedel-de Haën) was added to the plates (final concentration 0.01%). The growth rate of the mutants relative to the wild type was determined by placing a 5-mm-diameter mycelial disk of the fungus in the centre of a PDA plate and measuring the colony diameter at the indicated times. For confrontation assays, T. virens was co-inoculated with host fungi by placing 5-mm-diameter mycelial discs at the opposite sides of PDA Petri dishes. Overgrowth of the host by the different T. virens strains is evident from the production of green conidia and the disappearance of the normal morphology of the host colony. For pH step treatments, shake cultures in PDB (initial pH 4.5) were grown for 3 days, and reached pH 5.2-5.9. The mycelia were collected by filtration and transferred to fresh medium titrated to either pH 8.4 or pH 4. Measured immediately (within minutes) after the addition of mycelium, the pH was 7.7-7.9. At the end of harvesting, the pH was 6.7-6.9. In the acidic direction, there was only a slight upward shift (less than 0.1 unit) upon addition of mycelium, and at most by 0.4 units after the experiment.
Total RNA was isolated from mycelia ground in liquid nitrogen with Tri-reagent (Molecular Research Center, Cincinnati, OH) according to the manufacturer’s protocol. Alternatively, mycelia were lysed by homogenization together with Tri-reagent in a Mini-bead Beater (Biospec Products, Bartlesville, Oklahoma), using 0.2 g of 0.5 mm-diameter zirconia/silica beads (BioSpec Products). RNA yield was evaluated using a NanoDrop ND-1000 spectrophotometer (NanoDrop, Wilmington, DE). Samples for microarray analysis were further evaluated using the Agilent 2100 Bioanalyzer and RNA 6000 Nano kit (Agilent, Santa Clara, CA) according to the manufacturer’s instructions. Samples with electropherograms exhibiting sharp 18S and 28S rRNA peaks and showing no evidence of degradation were retained.
Real time qPCR
For cDNA synthesis, 2 μg of RNA were used for reverse transcription with random primers following the protocol supplied with the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Abundance of transcripts was measured by real-time qRT-PCR reactions performed in an Applied Biosystems 7000 cycler; approximately 15 ng of cDNA were used as template. The 15 μl reaction volume included 7.5 μl of 2XABsolute SYBR Green ROX MIX (ABgene, Surrey, U.K.) and 75 nM final concentration of specific primers for the gene of interest. Assays were run in duplicate or triplicate, using the following protocol: initial activation at 95°C for 10 min; 40 cycles of 95°C for 15 s, 60°C for 60 s, followed by a gradual increase in temperature from 60°C to 95°C during the dissociation stage. Tables 1 and 2 detail the genes validated by qPCR and assay conditions. The transcript abundance was calculated using the ABI software DataAssist. Prior to quantitative analysis, a standard curve was constructed using serial dilutions of RT product and the efficiency of each primer set was determined using the equation [(10(−1/slope)-1)·100]. Efficiencies near 100% were required to include the qPCR assay in array validation. For balancing the amount of cDNA, the following were tested for stable expression across all experimental treatments using DataAssist software (ABI): tubulin (protein ID 88010), peptidylprolyl isomerase A (PPIA, protein ID 43392), actin (protein ID 91925) and ribosomal protein L5 (RPL5, protein ID 77851). Tubulin, PPIA and L5 were chosen as “housekeeping” genes.
Gene replacement: ΔpacC
A fragment of the pacC gene was cloned by amplification with degenerate primers, as described in the Results. We used a PCR-based genome walking method (Universal Genome Walker kit, Clontech) to clone the unknown (prior to assembly of the T. virens sequence at the Joint Genome Institute) genomic DNA sequences adjacent to our known sequence. Genomic libraries were prepared and amplifications were done according to the manufacturer’s instructions. The deletion construct was made by replacement of the coding region with the selection marker gene for hygromycin resistance, hygromycin phosphotransferase (hph) under the control of the Aspergillus nidulans TrpC promoter and TrpC transcription termination signals (Additional file 11). 1.5 kb upstream and 1 kb downstream flanking sequences of the pacC gene were amplified with the following primer pairs: (5′ flank s and 5′ flank as primers) and (3′ flank s and 3′ flank as primers) respectively (Additional file 12), by PCR using BIO-X-ACT high fidelity enzyme (Bioline). The resulting 1.5 kb upstream PCR fragment was cloned into pUC57 (Fermentas), and the resulting plasmid digested with Acc65I and EcoRI. The 1 kb downstream PCR fragment was digested with NotI and EcoRI. The Hph cassette was excised from pUC-ATPH  with Acc65I and NotI. For pacC replacement, pUC57 plasmid containing the upstream fragment was ligated in one step using T4 DNA ligase (NEB) to the downstream flank and Hph cassette fragment (Additional file 11). Transformation to HIT DH5α (UBI) competent cells was performed according to the manufacturer’s protocol. Plasmid DNA was isolated from bacterial cultures using the Qiagen Plasmid Mini Kit. Linear DNA for transformation was prepared by cleavage of the plasmid with EcoRI (New England Biolabs).
Split-marker method: pacC c
The pacC c mutant was constructed using the split-marker method [46, 66]. A linear DNA construct was made by overlapping PCR reactions. The construct, upon integration into the genome, inserts the hygromycin selectable marker flanked from one side by the truncated pacC gene (constitutively active) ended with an inserted TAA stop codon, and 3′ UTR  (Additional file 4). Reactions with primer pairs 1 and 2 (Additional file 13) were carried out using T. virens genomic DNA as template. Reactions with pairs 3 and 4 were carried out using pBlueScript-Hyg (derived from pUCATPH ) plasmid DNA as template. The product obtained with primer pair 3 or pair 4 is part of the gene (hph) encoding hygromycin phosphotransferase. The second round of PCR joins the 5′ flank (truncated pacC gene) or 3′ flank with the partial hph coding sequences amplified in the first round, by annealing of the complementary sequence present in the reverse primer of pair 1 or the forward primer of pair 2, respectively. To construct the 5′ side of the final sequence, the products of pairs 1, 3 were used as template for amplification with primers FP1 and NLC37; for the second half, the products of pairs 2 and 4 were used as template for amplification with primers NLC38 and RP2. The two final products were integrated into the T. virens genome by double-crossover recombination, resulting in reconstruction of the complete hygromycin resistance cassette and replacement of the 3′ coding region of pacC. Fungal protoplasts were prepared as described below; transformants were selected for hygromycin resistance, and tested for homologous integration by amplification with primer pairs 5 and 6 (Additional file 13) and others (Additional file 3).
Transformation was performed essentially as described by , optimized for T. virens. The protoplasts were released from germinating conidia by 2 to 2.5 h of digestion at 30°C with gentle shaking (70 rpm, rotary shaker) in an enzyme mixture which consisted of 0.2 g of β-D-glucanase (InterSpex, San Mateo, CA - we note that InterSpex products are no longer available; replacements are currently being tested and calibrated), 0.4 g of Driselase (InterSpex), and approximately 2 mg of chitinase (Sigma, catalog number C6137). The mixture was stirred for 5 min at room temperature in 70 ml of 0.7 M NaCl, centrifuged for 10 min at 8,000 rpm (Sorvall SS34 rotor), and sterile filtered (0.22-μm-pore-size filter). Protoplasts were counted, and mycelial fragments were removed by filtering through three layers of sterile gauze followed by one layer of Nytex 50 monofilament nylon mesh. Protoplasts were washed in STC (sorbitol, 1.2 M; Tris pH 7.5, 10 mM; CaCl2, 50 mM). About 108 protoplasts were taken for transformation with 20 μg of plasmid DNA or linearized fragments for double-crossover integration. Selection was on 200 μg/ml of hygromycin B in PDA. Single spore isolates were obtained from transformants that formed conidia.
Acid/alkaline pH conditions
For each line (wt, ΔpacC and pacC c ), spores were collected from a 4-day old culture growing on a 90 mm PDA Petri dish (for mutants, PDA amended with 100 μg/ml Hygromycin B) and 107 spores were inoculated into 100 ml potato dextrose broth (PDB; Difco) in six 250 ml Erlenmeyer flasks (three repeats for each pH). After 3 days of shaking at 170 rpm at 29°C under continuous light, the medium in each Erlenmeyer flask was replaced with fresh PDB at pH 4 or pH 8 (the pH was adjusted with HCl and NaOH, one hour before the experiment started), by filtering the mycelium onto one layer of Nytex 50 monfilament nylon mesh. The mycelium was immediately transferred into PDB at the desired pH, and the culture returned to shaking. After 1 hour, each mycelial sample was vacuum-harvested on a Buchner funnel and frozen in liquid nitrogen.
Microarrays and sample preparation
A custom microarray was designed (Genotypic, Bangalore, India) from the complete set of filtered transcript models (Trichoderma virens v1.0, JGI http://genome.jgi-psf.org/Trive1/Trive1.home.html, ) and printed as 15 K arrays (Agilent, Santa Clara, CA, USA). To 1 μg total RNA, we added RNA from a spike-in kit (Agilent). cDNA synthesis was primed with oligo dT, and the double-stranded template was used for amplification and labelling by in vitro transcription using the MessageAmpII kit from Ambion (Austin, TX, USA). Amplified RNA (aRNA) was labeled with Cy3 and hybridized onto the custom microarrays. Microarray hybridization and washing steps were performed following the Agilent protocol for single-channel arrays. The arrays were scanned at 10% laser power to avoid signal saturation. Agilent’s Feature Extraction software was used to extract the data.
Normalization of the expression data
Microarray signals were normalized to allow comparison of samples with different RNA amounts, using the spike-in data. First, the log10 microarray data were normalized so that signals for one of the spike-ins (E1A_r60_a20) with a log relative concentration of 3.83 had the same values across all samples. Next, as described previously [68, 69], the log10 expression data were normalized by linearly interpolating to concentrations using the ten spike-in measurements for each sample and subsequently normalizing to the 75th percentile signal intensity. To summarize the replicate data for each gene, the mean for the three values (three biological replicates for each treatment) was computed. The complete data set and array platforms are provided in Additional file 14.
Statistical analyses for qPCR were performed with the GraphPad Prism software version 5.00 (GraphPad Software, San Diego, California, USA, demo version). Unless otherwise indicated, the threshold level chosen for comparison of means was P<0.05 by Student’s t-test (one-tailed, non-paired, equal variance). Adjusted P values for microarray data were calculated using LIMMA implemented in R, and the cut-off was at an adjusted P value <0.05. Cluster analysis was done using Genesis, http://genome.tugraz.at/.
We are grateful to Laura D. Cohen for editing the manuscript. The microarray platform at the Department of Biology, Technion was established by Dr. Itai Yanai, to whom we are grateful for his advice, support and development of data analysis tools. We thank Dr. Michael Shmoish (Bioinformatics Knowledge Unit, Technion) for assistance with data analysis, and Samer Shalaby from the Horwitz lab for comments on the manuscript. Supported in part by a binational grant to B.A.H. and P.K.M. from the Ministries of Science of Israel and India. Design and production of T. virens oligonucleotide microarrays was funded by TIE-BARD (US-Israel Agricultural Research and Development Fund, and Texas Department of Agriculture, to B.A.H. and Dr. Charles M. Kenerley). We are grateful to the Joint Genome Institute (U.S. Department of Energy) for sequencing the T. virens genome and developing the tools for analysis of fungal genomes. N.T. was supported by a pre-doctoral fellowship from the Technion Graduate School.
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