High Temperature, Differentiation, and Endoplasmic Reticulum Stress Decrease but Epigenetic and Antioxidative Agents Increase Aspergillus Ribosomal Protein Gene Expression

Short Communication

Austin J Proteomics Bioinform & Genomics. 2014;1(1): 6.

High Temperature, Differentiation, and Endoplasmic Reticulum Stress Decrease but Epigenetic and Antioxidative Agents Increase Aspergillus Ribosomal Protein Gene Expression

Chang P-K1*, Wang B2, He Z-M3, Yu J4 and Pan L2

1Southern Regional Research Center, Agricultural Research Service, U. S. Department of Agriculture, USA

2School of Bioscience and Bioengineering, South China University of Technology, China

3MOE Key Laboratory of Aquatic Product Safety, School of Life Sciences, Sun Yat-Sen University, China

4Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture, USA

*Corresponding author: Chang P-K, Southern Regional Research Center, Agricultural Research Service, U. S. Department of Agriculture, 1100 Robert E. Lee Boulevard, New Orleans, Louisiana 70124, USA

Received: September 10, 2014; Accepted: October 17, 2014; Published: October 20, 2014

Abstract

Genome-wide gene expression assays using next-generation sequencing techniques have allowed the identification of transcriptomes in many species. Transcript abundance of ribosomal protein (RP) genes can serve as a proxy for the capacity of general transcription and synthesis of cellular proteins that provide molecular functions. We analyzed and compared numbers and expression levels of RP genes of four RNA-Seq datasets. These included studies on effects of temperature, developmental stages, and epigenetic and antioxidative agents on A. flavus, and culture type and endoplasmic reticulum (ER) stress on A. oryzae RP gene expression. Under normal growth conditions, regardless of medium composition, about 55 to 65% of total Aspergillus RP genes were highly expressed (defined as among the top 2% of the total genes). Stress factors such as high temperature and hyperoxidant state (differentiation) decreased RP gene expression levels and, to a much lesser extent, the expressed RP gene populations. In contrast, factors that relieve oxidative stress increased the expression levels. ER stress greatly decreased the expression level of individual RP genes, but barely changed the population. Transcriptiomic studies can provide new insights into how abiotic and biotic factors affect RP gene expression.

Keywords: Transcriptome; Ribosomal protein; Endoplasmic reticulum stress; Aspergillus; Oxidative stress

Abbreviations

RP: Ribosomal protein; ER: Endoplasmic Reticulum; rRNA: Ribosomal RNA; PDA: Potato Dextrose Agar; PDB: Potato Dextrose Broth; 5AC: 5-azacytidine; GA: Gallic Acid; CD: Czapek-Dox Medium; DTT: Dithiothreitol; GEO: Gene Expression Omnibus; SRA: Sequence Read Archive; CNT: Control; RPKM: Reads per Kilobase Exon Model Per Million Mapped Reads; FPKM: Fragments Per Kilobase of Transcript Per Million Mapped Reads; ROS: Reactive Oxygen Species; CNT: Control; T: Temperature; Myc: Mycelia; Scl: Sclerotia; SC: Solid-state Culture; LC: Liquid-state Culture

Introduction

Ribosomes, the translation machinery, are ribonucleoprotein particles that catalyze all cellular protein synthesis using transfer RNAs and elongation factors. Bacterial ribosomes like those of Echerichia coli have served as a basis for elucidating mechanisms of protein synthesis. For E. coli, two-dimensional gel electrophoresis has been used to separate the 21 proteins in the 30 small subunit and the 34 proteins in the 50S large subunit [1]. In contrast to the bacterial counterparts, eukaryotic ribosomes including those of fungi are more complex and much larger. They are fundamentally different in many ways and contain additional ribosomal RNA (rRNA) called expansion segment and many other ribosomal proteins [2]. Fungal ribosomes are 80S ribosomes, which consist of two subunits of 40S and 60S. The small 40S subunit contains an 18S rRNA while the large 60S subunit contains a 26S rRNA. Both subunits as inferred from their eukaryotic counterparts likely contain a total of about 80 ribosomal proteins [3]. Ribosome biogenesis requires that rRNAs and ribosomal proteins in precise stoichiometric balance. The expression of ribosomal protein (RP) genes is coordinately regulated to ensure that equimolar amounts of RP are available for ribosome assembly [4].

Ribosomal proteins are synthesized preferentially in cells growing actively. Increasing evidence indicates that individual ribosomal proteins and changes in amounts can modulate a wide array of activities that are associated with cell growth and death [5,6]. In the post-genomics era, RNA-Seq has been developed as the standard approach for profiling transcriptomes [7]. Research using this technique has generated vast amounts of data and analyses of sequence reads have revolutionized current views on the complexity of transcriptome and on the context of gene expression regulation [8]. Transcriptomic studies on fungi have been mostly focused on characterizing all transcript species [9], determining cellular protein genes differentially expressed [10], and elucidating pathogenicity or virulence [11,12]. In a recent analysis of the human transcriptome, the molar ratio of transcripts among 80%-90% of the RP genes, with little tissue specificity, was found to vary less than three-fold [13]. Up to now, no systematic analyses on the expression levels of the entire population of RP genes in fungi have been attempted.

In this short communication, using limitedly available transcriptomic datasets we collectively determine the overall expression profiles of RP genes in Aspergillus flavus and the closely related Aspergillus oryzae under common growth conditions. We evaluated how temperature, developmental stages, and epigenetic and antioxidative agents affected the RP gene expression of A. flavus as well as how culturing types and endoplasmic reticulum (ER) stress affected the RP gene expression of A. oryzae. The analyses showed that the portion of RP genes normally expressed at high levels was fairly constant, in the range of 55 to 65%. Abiotic and biotic stress factors and relief of the factors were related to changes in the overall RP gene expression. The information provides a possible means to use culturing practices in combination with transcriptomic analyses to control general transcription, thus cellular activities in fungi.

Materials and Methods

Fungal strains and culturing conditions

Two Aspergillus flavus strains, NRRL3357 and CA43, the latter differs from the former in that it produces sparse conidia but abundant small sclerotia (S strain), and one Aspergillus oryzae strain, RIB40, were used. Fungal cultures were routinely maintained on potato dextrose agar (PDA) plates. For the experiment examining temperature effects, cultures of NRRL3357 were harvested after they were growth at 30C and 37C in liquid glucose minimal salts (GMS) media for 24 h [14]. For production of mycelia and sclerotia, cultures of CA43 were grown on PDA plates, each overlaid with a layer of cellophane, and incubated at 30C in the dark. The mycelia were collected after 48 h and sclerotia after 7 days [15]. For the experiments studying chemical effects cultures of NRRL3357 grown in potato dextrose broth (PDB) containing 1 mM 5-azacytidine (5AC, treatment 1), 1% (w/v) gallic acid (GA, treatment 2) or none (control) were prepared [16]. These cultures were incubated at 30C in the dark for 72 h. For experiments investigating the effect of culture type RIB40 was grown on solid or in liquid glucose-based Czapek-Dox (CD) medium for 40 h. For ER stress treatment the resulting solid culture along with the cellophane was transferred to a stack of 2-cm thick filter paper soaked in 20 ml CD supplemented with 20 mM dithiothreitol (DTT) and the liquid culture used also was supplemented with 20 mM DDT [9].

Preparation of total RNA and isolation of mRNA

Mycelia or sclerotia collected were ground to a fine powder in liquid nitrogen. Total RNA was extracted using TRIzol® Reagent (Invitrogen, USA), RNAiso™ Plus (TaKaRa, Japan) or the hot acid phenol method. All total RNA samples were treated with RNase-free DNase I. The integrity and concentration of the resulting total RNA were determined by an Agilent Technologies 2100 Bioanalyzer. All samples had a RNA integrity number value greater than six. Poly (A) RNAs were isolated from total RNA samples using magnetic oligo(dT) beads.

Construction of cDNA libraries and sequencing

Samples of poly (A) RNA (0.2-1.0 μg) were used for cDNA library construction following the Illumina protocol (https://www.illumina. com). The routine procedures involved fragmentation of mRNA into smaller pieces (200-500 bp), first strand cDNA synthesis, second strand cDNA synthesis, end repair, ligation of adapters, purification of ligated products, and PCR amplification to enrich cDNA templates. All cDNA libraries were sequenced using the Illumina Genome Analyzer II or the HiSeq2000.

Sequence reads deposition into databases, and mapping

Raw sequence data were processed and filtered using the Illumina pipeline (https://www.illumina.com) to generate fastq files. Raw sequence data of the temperature effect on A. flavus NRRL3357 were deposited in the NCBI's Gene Expression Omnibus (GEO; https://www. ncbi.nlm.nih.gov/geo/) under the accession number of GSE30031. Data of mycelia and sclerotia of A. flavus CA43 transcriptome were deposited in Sequence Read Archive (SRA; https://www.ncbi.nlm. nih.gov/sra/) under the accession number of SRP018670. Data of the effect of 5-azacytidine or gallic acid on A. flavus NRRL3357 were deposited in GEO under the accession number of GSE40202. Data of the effect of endoplasmic reticulum stress on A. oryzae RIB40 grown on solid and in liquid media were deposited in GEO under the accession number of GSE18851. Good sequence reads were mapped to the reference genome of NRRL3357 or RIB40 using CLC Genomic Workbench (https://www.clcbio.com), Cufflinks [17] (https://cufflinks. cbcb.umd.edu/), or SOAP [18]. All reads were mapped to coding sequences. The expression values for every gene in the RPKM (Reads Per Kilobase exon model per Million mapped reads) unit or, in the experiments of 5AC and GA treatment, as its equivalent of FPKM (Fragments Per Kilobase of transcript per Million mapped reads) [19] were calculated. These determinations are normalized values, which allows for cross-sample comparisons in an experiment.

Results and Discussion

Despite having similar genome sizes of about 37 Mb, A. flavus and A. oryzae are predicted to have 13,485 and 12,074 protein-coding genes, respectively [20,21]. To define highly expressed genes in all experiments, we first sorted the normalized expression values and then arbitrarily set the top 2% as the cutoff criterion. The glycerol- 3-phosphate dehydrogenase gene, highly expressed in eukaryotic microorganisms and its promoter used by many researchers to overexpress genes of interest [22], also was in this range. The determination of the total number of RP genes (in parentheses) expressed in cultures grown under commonly used conditions from all experiments revealed the following: (i) A. flavus at 30C in GMS for 24h (46), at 30C in PDB for 72h (45), and at 30C on PDA for 48h (50) and (ii) A. oryzae at 30C for 40 h on solid CD (45) or liquid CD (44) (Figures 1A and 1B). Assuming that Aspergillus like other eukaryotes has 80 RP genes, the results showed that about 55 to 65% of RP genes were highly expressed under normal culturing conditions. We further dissected the top 2% into two tiers, that is, top 1% and 1-2% to determine any difference in the RP gene expression pattern. Regardless of medium type 40 to 60% of the highly expressed RP genes of A. flavus were in the top 1%. Although in liquid medium the RP gene expression pattern of A. oryzae was similar to that of A. flavus, on solid medium all highly expressed RP genes of A. oryzae were in the top 1%. Exposing cultures to air such as on plates did not significantly affect the overall highly expressed RP gene number but substantially increased the number in the top1% as seen from A. flavus Myc vs. T30 and CNT (Figure 1A), and in particular A. oryzae S(CNT) vs. L(CNT) (Figure 1B). Although A. flavus and A. oryzae are phylogenetically closely related, they are classified as separate species because of food safety and economic concerns [23]. The analysis showed that 60% more top 1% RP genes were in A. oryzae than in A. flavus when both were grown on solid medium, that is, S(CNT) vs. Myc. Taken together, these results suggest that A. oryzae on solid medium has a higher capacity for making cellular proteins than in liquid medium [24]. Thousands-of-years domestication of its nonaflatoxigenic A. flavus ancestor by solid-state fermentation and selection for strains as solid-state cultures that grow fast and produce high activities of amylases and proteases to degrade macromolecules in rice, wheat bran, and soybean [25] may in part have shaped the distinct pattern of RP gene expression in current A. oryzae.

Figure 1 :Numbers of RP genes highly expressed under various growth conditions. (A) A. flavus at different growth temperatures, at mycelia growth and sclerotial differentiation stages, and treated with epigenetic modulator 5AC and antioxidant GA. (B) A. oryzae on solid or in liquid medium without or under the endoplasmic reticulum (ER) stress condition caused by the treatment with DTT.






Figure 1 : Numbers of RP genes highly expressed under various growth conditions. (A) A. flavus at different growth temperatures, at mycelia growth and sclerotial differentiation stages, and treated with epigenetic modulator 5AC and antioxidant GA. (B) A. oryzae on solid or in liquid medium without or under the endoplasmic reticulum (ER) stress condition caused by the treatment with DTT.

The transcriptomic data obtained from different growth temperature, developmental stages and under (relief of) stress conditions allow us to assess how these factors affect the expression of RP genes. The number of RP genes highly expressed at 37C compared to that at 30C decreased about 20% (Figure 1A), but the expression level decreased greater than 40% (Table 1). High temperature is known to represses general transcription and translation. Adaptation to elevated growth temperatures involves coordination of stress responses and signaling pathways. Cells subjected to temperature elevation (40C) have been shown to induce either a partial or the full ER stress pathway [26]. Reduced translation in Saccharomyces cerevisiae also has been implicated to protect the yeast from ER stress [27]. Notably, the RP genes missing in the aforementioned 20% decrease at 37C were all those highly expressed at 30C, which included genes for L14, L23, L27e, L32, L35, S10a, S19, S22, S25 and S26. At 37C the decreased expression levels varied from 43 to 84%. Only the expression of the new RP gene for L4 was elevated at 37C; the increase was greater than two-fold (Figure 2; also see Table S1 for RP gene populations). Changes in numbers and levels of the expressed RP genes in turn can affect translation capacity of the fungus including the synthesis of hundreds of cellular proteins involved in ribosome biogenesis [28], which further decreases general transcription and translation.

Figure 2 :RP genes highly expressed at designated conditions relative to their own RP populations and common in the respective control sets. The control sets are T30 for T37, Myc for Scl, CNT for 5AC and GA, and S(CNT) for L(CNT) and S(ER). See Tables S1 and S2 for the total numbers of highly expressed RP genes at these specific growth conditions. See Figure 1 for the total numbers of highly expression RP genes for the control sets. For example, all RP genes expressed in the control set were also expressed in the 5AC and GA sets, but the common genes represent 87% and 85% of those in the population of 5AC and GA, respectively.






Figure 2 : RP genes highly expressed at designated conditions relative to their own RP populations and common in the respective control sets. The control sets are T30 for T37, Myc for Scl, CNT for 5AC and GA, and S(CNT) for L(CNT) and S(ER). See Tables S1 and S2 for the total numbers of highly expressed RP genes at these specific growth conditions. See Figure 1 for the total numbers of highly expression RP genes for the control sets. For example, all RP genes expressed in the control set were also expressed in the 5AC and GA sets, but the common genes represent 87% and 85% of those in the population of 5AC and GA, respectively.

Table 1: Relative ratios of highly expressed RP genes in A. flavus and A. oryzae transcriptomes from various culture conditions.




  

    
A.    flavus 

    
T30

    
T37

    
Mycelia

    
Sclerotia

    
CNT

    
5AC

    
GA

  

  

    
 

    
1.00

    
0.57a

    
1.00

    
0.45

    
1.00

    
1.55

    
1.86

  

  

    
 

    
 

    
 

    
 

    
 

    
 

    
 

    
 

  

  

    
A.    oryzae 

    
Solid

      
(CNT)

    
Solid

      
(ER)

    
Liquid

      
(CNT)b

    
Liquid

      
(ER)c

    
 

    
 

    
 

  

  

    
 

    
1.00

    
0.30

    
1.00

    
0.03

    
 

    
 

    
 

  









Table 1:  Relative ratios of highly expressed RP genes in A. flavus and A. oryzae transcriptomes from various culture conditions.

Vegetative growth and sclerotial formation represent distinct stages in the life cycle of S-stain Aspergillus flavus. Cell differentiation in eukaryotic microorganisms is a response to oxidative stress [29]. The hyperoxidant state is a state that the production of reactive oxygen species (ROS) exceeds the cell's capacity to neutralize these damaging molecules. Fungal mycelia in early growth stages maintain minimal ROS levels. Increasing levels of ROS at later developmental stages are a major determinant for sclerotial biogenesis, which acts as a defense mechanism against oxidative stress [30]. ER stress and oxidative stress are closely linked events; activation of the unfolded protein response, an intracellular signaling pathway, on exposure to oxidative stress serves as a mechanism to preserve cell function and survival [31]. The number of highly expressed RP genes in sclerotia compared to that in mycelia decreased about 36% (Figure 1A), which included genes for L1, L5, L7A, L8, L13, L14, L15, L16a, L26, L27a, L28, L34, L37, S3, S4, S5, S9 and S24 (Table S1). The overall expression level decreased 55% (Table 1), which corresponded to a decreased expression in the respective genes from 27 to 52% (data not shown). These results suggest that oxidative stress is able to cause ER stress and manifests its effect in the RP gene expression. The number of RP genes expressed in sclerotia was decreased but no new RP genes compared to those in mycelia were expressed (Figure 2). Alternatively, sclerotia being in a resting state and metabolic inactive likely have decreased general transcription and translation. Whether this resting state has bearing on ER stress is unknown.

Table S1 :RP gene expression in A. flavus under various growth conditions






Table S1 : RP gene expression in A. flavus under various growth conditions

Table S1 :B. Mycelia and sclerotia






Table S1 : B. Mycelia and sclerotia

Table S1:C. Treatments with 5-azacytidine (5AC) and gallic acid (GA)






Table S1: C. Treatments with 5-azacytidine (5AC) and gallic acid (GA)

The epigenetic modifier, 5-azacytidine (5AC) is a DNA methylation inhibitor; it can turn on expression of silent genes [32]. 5AC induces in fungi on solid media a "fluffy" phenotype that simulates a prolonged vegetative state [33]. A. flavus treated with 5AC even in PDB would correspond to a low ROS status as in an early growth stage. Likewise, the treatment with the antioxidant, gallic acid (GA), can lower the intracellular ROS level. Compared to the control A. flavus treated by 5AC or GA increased the total number of highly expressed RP genes. Also, the increase in the expression level for 5AC was 55% and GA 86% (Table 1). A further comparison of the top 1% showed that the increase for 5AC was 98% and GA 136% as evidenced by a nearly a two-fold increase in the number of RP genes from 18 to 30 and 35, respectively (Figure 1A). In addition to having all common RP genes expressed in the control set, both 5AC and GA treatments induced a few new highly expressed RP genes. Interestingly, all seven new highly expressed RP genes for L13, L17, L18ae, L38, S6, S7e and S10a in the 5AC set were identical to seven of the eight genes newly included in the highly expressed RP genes in the GA set (Table S1). The increase in the expression of these RP genes, except the one for L38 in the GA treated sample, was in general less than two-fold (data not shown). This finding of nearly identical RP genes in the 5AC and GA sets suggests that changes in intracellular redox status, such as a decreased in oxidative stress, do not greatly influence the relative expression ratios among most RP genes, but instead elevate the expression levels of individual gene comparably. The broad increase in the RP gene levels likely raise the ranking of some of the RP genes to the arbitrarily set top 2% range.

A marked difference was observed for RP genes expressed by A. oryzae solid- (SC) and liquid-state (LC) cultures. The overall expression level based on the total transcript count of the highly expressed RP genes in SC was about 2.7-fold that of in LC (Table S2). Studies have shown that expression levels of many protein folding related genes are higher in SC than in LC [9, 34]. Elevated amounts of folding proteins can lead to higher production of stable cellular and ribosomal proteins, which may further increase general transcription. Heterogeneity of ribosome structure resulting from variations in ribosomal protein composition is of physiological significance in eukaryotes [35]. Different sets of ribosomal protein genes in yeast have been shown to be associated with various phenotypes such as life span, budding, and drug resistance [27]. RP genes in normal adult human tissues, including brain, lever, muscle, retina, uterus and ovary are also differentially expressed [36]. We found that, for the same experiment, medium composition not the medium type had a major role in determining the expressed RP gene populations. For example, 94% (42/45) of the highly expressed RP genes in LC were common genes expressed in SC, and 98% (44/45) of the RP genes expressed in SC were expressed in SC under the ER stress condition despite a 2 to 3-fold decrease in each expression level (Figure 2 and Table S2). The latter finding also showed that ER stress specifically exerts it effect mainly on individual RP gene expression levels but does not affect the highly expressed RP gene population. This is in striking difference from what were found from the effects of temperature, developmental stages, and treatments by 5AC and GA. Changes in their RP populations apparently were caused by other complex factors if ER stress played a role. It is unclear what the underlying mechanisms are for the general decrease of RP gene expression in LC. Genes differentially expressed in response to oxygen levels are divided into two groups: aerobic genes expressed under normoxic conditions, and hypoxic genes expressed when oxygen is low or absent. Both are regulated by signaling pathways at the level of transcription [37,38]. The analysis showed that lower oxygen tension also was able to decrease the RP gene expression significantly (Table S2). In addition, a striking synergistic effect between hypoxia and ER stress in decreasing the RP gene expression was found (Figure 1B and Table 2).

Table S2 :Culture state and endoplasmic reticulum (ER) stress on RP gene expression in A. oryzae






Table S2 : Culture state and endoplasmic reticulum (ER) stress on RP gene expression in A. oryzae

Table S2 :






Table S2 :

Conclusion

Slightly more than half of the total RP genes of A. flavus and A. oryzae are highly expressed under normal growth conditions. This proportion in general is not affected by medium type or composition. The RP gene population and the expression level are decreased by abiotic and biotic stress factors such as elevated growth temperature, differentiation, and hypoxia but elevated by relief of stress factors. ER stress does not the change the RP gene population but mainly decreases the expression level of individual genes. Transcriptomic analyses improve our understanding of how RP gene expression profiles in fungi are shaped by their living environments.

Acknowledgements

We thank Brian Mack of Southern Regional Research Center for his support in analyzing A. flavus CA43 RNA-Seq data.

Supporting Information

Table S1: Ribosomal protein gene expression in A. flavus under various growth conditions.

Table S2: Culture state and endoplasmic reticulum stress on ribosomal protein gene expression in A. oryzae.

References

  1. Kaltschmidt E, Wittmann HG. Ribosomal proteins. XII. Number of proteins in small and large ribosomal subunits of Escherichia coli as determined by two-dimensional gel electrophoresis. Proc Natl Acad Sci U S A. 1970; 67: 1276-1282.
  2. Wilson DN, Doudna Cate JH. The structure and function of the eukaryotic ribosome. Cold Spring Harb Perspect Biol. 2012; 4.
  3. Ban N, Beckmann R, Cate JH, Dinman JD, Dragon F, et al. A new system for naming ribosomal proteins. Curr Opin Struct Biol. 2014; 24: 165-169.
  4. Popescu SC, Tumer NE. Silencing of ribosomal protein L3 genes in N. tabacum reveals coordinate expression and significant alterations in plant growth, development and ribosome biogenesis. Plant J. 2004; 39: 29-44.
  5. Naora H, Naora H. Involvement of ribosomal proteins in regulating cell growth and apoptosis: translational modulation or recruitment for extraribosomal activity? Immunol Cell Biol. 1999; 77: 197-205.
  6. Tushinski RJ, Warner JR. Ribosomal proteins are synthesized preferentially in cells commencing growth. J Cell Physiol. 1982; 112: 128-135.
  7. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009; 10: 57-63.
  8. Gibcus JH, Dekker J. The context of gene expression regulation. F1000 Biol Rep. 2012; 4: 8.
  9. Wang B, Guo G, Wang C, Lin Y, Wang X, et al. Survey of the transcriptome of Aspergillus oryzae via massively parallel mRNA sequencing. Nucleic Acids Res. 2010; 38: 5075-5087.
  10. Novodvorska M, Hayer K, Pullan ST, Wilson R, Blythe MJ. et al. Trancriptional landscape of Aspergillus niger at breaking of conidial dormancy revealed by RNA-sequencing. BMC Genomics. 2013; 14: 246.
  11. Ke X, Yin Z, Song N, Dai Q, Voegele RT, et al. Transcriptome profiling to identify genes involved in pathogenicity of Valsa mali on apple tree. Fungal Genet Biol. 2014; 68: 31-38.
  12. Krajaejun T, Lerksuthirat T, Garg G, Lowhnoo T, Yingyong W, et al. Transcriptome analysis reveals pathogenicity and evolutionary history of the pathogenic oomycete Pythium insidiosum. Fungal Biol. 2014; 118: 640-653.
  13. Gupta V, Warner JR. Ribosome-omics of the human ribosome. RNA. 2014; 20: 1004-1013.
  14. Yu J, Fedorova ND, Montalbano BG, Bhatnagar D, Cleveland TE, et al. Tight control of mycotoxin biosynthesis gene expression in Aspergillus flavus by temperature as revealed by RNA-Seq. FEMS Microbiol Lett. 2011; 322: 145-149.
  15. Wu X, Zhou B, Yin C, Guo Y, Lin Y, et al. Characterization of natural antisense transcript, sclerotia development and secondary metabolism by strand-specific RNA sequencing of Aspergillus flavus. PLoS One. 2014; 9: e97814.
  16. Lin JQ, Zhao XX, Zhi QQ, Zhao M, He ZM. Transcriptomic profiling of Aspergillus flavus in response to 5-azacytidine. Fungal Genet Biol. 2013; 56: 78-86.
  17. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010; 28: 511-515.
  18. Li R, Li Y, Kristiansen K, Wang J. SOAP: short oligonucleotide alignment program. Bioinformatics. 2008; 24: 713-714.
  19. Mortazav A, Williams BA, McCue K, Schaeffer L, Word B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature Methods. 2008; 7: 621-628.
  20. Payne GA, Nierman WC, Wortman JR, Pritchard BL, Brown D, et al. Whole genome comparison of Aspergillus flavus and A. oryzae. Medical. 2006; 44 Suppl: 9-11.
  21. Machida M, Asai K, Sano M, Tanaka T, Kumagai T, et al. Genome sequencing and analysis of Aspergillus oryzae. Nature. 2005; 438: 1157-1161.
  22. Punya J, Tachaleat A, Wattanachaisaereekul S, Haritakun R, Boonlarppradab C, et al. Functional expression of a foreign gene in Aspergillus oryzae producing new pyrone compounds. Fungal Genet Biol. 2013; 50: 55-62.
  23. Chang PK, Ehrlich KC. What does genetic diversity of Aspergillus flavus tell us about Aspergillus oryzae? Int J Food Microbiol. 2010; 138: 189-199.
  24. Akao T, Gomi K, Goto K, Okazaki N, Akita O. Subtractive cloning of cDNA from Aspergillus oryzae differentially regulated between solid-state culture and liquid (submerged) culture. Curr Genet. 2002; 41: 275-281.
  25. Machida M, Yamada O, Gomi K. Genomics of Aspergillus oryzae: learning from the history of koji mold and exploration of its future. DNA Res. 2008; 15: 173-183.
  26. Xu X, Gupta S, Hu W, McGrath BC, Cavener DR. Hyperthermia induces the ER stress pathway. PLoS One. 2011; 6: e23740.
  27. Steffen KK, McCormick MA, Pham KM, MacKay VL, Delaney JR, et al. Ribosome deficiency protects against ER stress in Saccharomyces cerevisiae. Genetics. 2012; 191: 107-118.
  28. Ebersberger I, Simm S, Leisegang MS, Schmitzberger P, Mirus O, et al. The evolution of the ribosome biogenesis pathway from a yeast perspective. Nucleic Acids Res. 2013; 42: 1509-1523.
  29. Aguirre J, Rios-Momberg M, Hewitt D, Hansberg W. Reactive oxygen species and development in microbial eukaryotes. Trends Microbiol. 2005; 13: 111-118.
  30. Georgiou CD, Patsoukis N, Papapostolou I, Zervoudakis G. Sclerotial metamorphosis in filamentous fungi is induced by oxidative stress. Integ Compa Biol. 2006; 46: 691-712.
  31. Malhotra JD, Kaufman RJ. Endoplasmic reticulum stress and oxidative stress: a vicious cycle or a double-edged sword? Antioxid Redox Signal. 2007; 9: 2277-2293.
  32. Zutz C, Gacek A, Sulyok M, Wagner M, Strauss J, et al. Small chemical chromatin effectors alter secondary metabolite production in Aspergillus clavatus. Toxins (Basel). 2013; 5: 1723-1741.
  33. Tamame M, Antequera F, Santos E. Developmental characterization and chromosomal mapping of the 5-azacytidine-sensitive fluF locus of Aspergillus nidulans. Mol Cell Biol. 1988; 8: 3043-3050.
  34. Ye L, Pan L. A comparison of the unfolded protein response in solid-state with submerged cultures of Aspergillus oryzae. Biosci Biotechnol Biochem. 2008; 72: 2998-3001.
  35. Sugihara Y, Honda H, Iida T, Morinaga T, Hino S, et al. Proteomic analysis of rodent ribosomes revealed heterogeneity including ribosomal proteins L10-like, L22-like 1, and L39-like. J Proteome Res. 2010; 9: 1351-1366.
  36. Bortoluzzi S, d'Alessi F, Romualdi C, Danieli GA. Differential expression of genes coding for ribosomal proteins in different human tissues. Bioinformatics. 2001; 17: 1152-1157.
  37. Poyton RO, Castello PR, Ball KA, Woo DK, Pan N. Mitochondria and hypoxic signaling: a new view. Ann N Y Acad Sci. 2009; 1177: 48-56.
  38. Butler G. Hypoxia and gene expression in eukaryotic microbes. Annu Rev Microbiol. 2013; 67: 291-312.

Citation: Chang P-K, Wang B, He Z-M, Yu J and Pan L. High Temperature, Differentiation, and Endoplasmic Reticulum Stress Decrease but Epigenetic and Antioxidative Agents Increase Aspergillus Ribosomal Protein Gene Expression. Austin J Proteomics Bioinform & Genomics. 2014;1(1): 6. ISSN : 2471-0423