Distinct Responses of Mycobacterium smegmatis to Exposure to Low and High Levels of Hydrogen Peroxide

Abstract

Hydrogen peroxide (H₂O₂) is a natural oxidant produced by aerobic organisms and gives rise to oxidative damage, including DNA mutations, protein inactivation and lipid damage. The genus Mycobacterium utilizes redox sensors and H₂O₂ scavenging enzymes for the detoxification of H₂O₂. To date, the precise response to oxidative stress has not been fully elucidated. Here, we compared the effects of different levels of H₂O₂ on transcription in M. smegmatis using RNA-sequencing. A 0.2 mM H₂O₂ treatment had little effect on the growth and viability of M. smegmatis whereas 7 mM H₂O₂ was lethal. Analysis of global transcription showed that 0.2 mM H₂O₂ induced relatively few changes in gene expression, whereas a large proportion of the mycobacterial genome was found to be differentially expressed after treatment with 7 mM H₂O₂. Genes differentially expressed following treatment with 0.2 mM H₂O₂ included those coding for proteins involved in glycolysis-gluconeogenesis and fatty acid metabolism pathways, and expression of most genes encoding ribosomal proteins was lower following treatment with 7 mM H₂O₂. Our analysis shows that M. smegmatis utilizes the sigma factor MSMEG_5214 in response to 0.2 mM H₂O₂, and the RpoE1 sigma factors MSMEG_0573 and MSMEG_0574 in response to 7 mM H₂O₂. In addition, different transcriptional regulators responded to different levels of H₂O₂: MSMEG_1919 was induced by 0.2 mM H₂O₂, while high-level induction of DevR occurred in response to 7 mM H₂O₂. We detected the induction of different detoxifying enzymes, including genes encoding KatG, AhpD, TrxB and Trx, at different levels of H₂O₂ and the detoxifying enzymes were expressed at different levels of H₂O₂. In conclusion, our study reveals the changes in transcription that are induced in response to different levels of H₂O₂ in M. smegmatis.

Introduction

The genus Mycobacterium includes pathogens, such as Mycobacterium tuberculosis and non-pathogenic microorganisms, such as Mycobacterium smegmatis. Mycobacteria are able to respond to and survive under different stresses [1]. Hydrogen peroxide (H₂O₂) is a natural stressor that is produced by aerobic organisms and leads to oxidative damage, such as DNA mutations, protein inactivation and lipid damage [2]. In addition, when M. tuberculosis, the pathogen which causes human tuberculosis (TB), infects a host, the production of H₂O₂ is an important innate defense mechanism against infection. As a successful pathogen, M. tuberculosis has evolved redox sensors and H₂O₂ scavenging enzymes for the detoxification of H₂O₂ damage [3,4], but the precise response to H₂O₂ has not been fully elucidated. A number of studies have shown that M. tuberculosis contains several regulators that respond to H₂O₂ and several enzymes that detoxify H₂O₂ damage [5–7]. A recent study has reported different transcriptional profiles in M. tuberculosis in response to different H₂O₂ concentrations [7]. However, the transcriptional response of M. smegmatis to different concentrations of H₂O₂ has yet to be explored. A greater understanding of the differences between pathogenic M. tuberculosis and nonpathogenic M. smegmatis in their response to H₂O₂ will help us to understand the pathogenesis of M. tuberculosis.

Transcriptional regulation in response to H₂O₂ in the Mycobacteria is complex compared to that in Bacillus or Escherichia coli. M. tuberculosis has 13 sigma factors, and M. smegmatis has 28 sigma factors [8,9], of which SigE, SigH, SigL and SigF play important roles in oxidative stress [3]. As classical transcriptional regulators such as OxyR, FNR and FixL are absent in M. tuberculosis, alternative transcriptional regulators have been suggested to be involved in oxidative stress, including FurA [10], IdeR [11], CarD [12], and the WhiB proteins [3]. In addition to transcriptional regulators involved in the response to H₂O₂, the signal transduction network including two-component systems, one-component systems, and serine/threonine kinases, is also involved in relaying and orchestrating the response to H₂O_2. M. tuberculosis encodes 11 serine/threonine kinases (STKs), of which PknB, PknF, and PknG have been shown to be involved in the oxidative stress response [13–15]. Park et al. showed that PknB phosphorylates both SigH and its anti-sigma factor RshA and causes its release from the complex of SigH and RshA. The phosphorylated SigH then regulates the response to oxidative stress [14]. Similar to PknB, PknD was shown to phosphorylate anti-anti-sigma factor Rv0516c and then to activate Rv0516c, which changes the expression of the SigF regulon [13]. Moreover, M. tuberculosis produces many enzymes that scavenge H₂O₂. Mycobacterial KatG is a multifunctional heme-dependent catalase-peroxidase-peroxynitritase [16] and efficiently protects Mycobacterium from reactive oxygen species damage [17]. KatG is the target of the first-line drug isoniazid (INH) and is responsible for the conversion of the prodrug INH into active INH [18]. Clinical strains with decreasing KatG activity showed higher levels of AhpC [19], suggesting that AhpC contributes to defense against oxidative stress. The metabolic enzyme complex with Lpd, SucB, AhpC, and AhpD, is also involved in antioxidant defense [20]. Thiol-dependent peroxidase Tpx is an antioxidant protein against oxidative stress [21]. Voskuil et al. recently investigated whole genome expression in response to different levels of oxidative stress and showed that many genes related to oxidative stress are induced concurrently with the dormancy regulon at high concentrations of H₂O₂ [7].

In this study, we compared the effects of different H₂O₂ levels on transcription in M. smegmatis using RNA-sequencing. We show that low levels (0.2 mM) of H₂O₂ have little effect on the growth and viability of M. smegmatis whereas high levels (7 mM) of H₂O₂ are bactericidal. Relatively few changes in gene expression were observed on exposure to 0.2 mM H₂O₂ while a large munber of differentially expressed genes were induced after treatment with 7 mM H₂O₂. Some differentially expressed genes involved in the glycolysis-gluconeogenesis and fatty acid metabolic pathways were induced by 0.2 mM H₂O₂, and the expression of genes encoding ribosomal proteins was lower after treatment with 7 mM H₂O_2. Our analysis also identified differences in the sigma factors, transcriptional regulators, and detoxifying enzymes that are expressed in response to treatment with 0.2 mM and 7 mM H₂O₂.

Materials and Methods

Bacterial strains and culture conditions

Liquid cultures of the M. smegmatis mc²155 strain were grown in Middlebrook 7H9 medium (Becton Dickinson) supplemented with 0.2% (v/v) glycerol (Beijing Modern Eastern Finechemical), 0.05% Tween 80 (v/v) (Sigma) and 10% ADS (albumin, dextrose, and saline). Middlebrook 7H10 medium (Becton Dickinson) supplemented with 10% ADS and 0.2% (v/v) glycerol was used as the solid medium for M. smegmatis growth.

Response of the M. smegmatis mc²155 strain to H₂O₂ stress

Log phase cultures (OD₆₀₀ of 0.8–1.0) of M. smegmatis mc²155 were diluted 1:100 into 7H9 media and cultured for approximately 12 hours until the OD₆₀₀ reached 0.3. Re-inoculated cells were then treated with the indicated concentrations of H₂O₂ (0, 0.2 and 7 mM) for periods of 30 min or 3 h, and surviving cells were grown on 7H10 media. Cells were collected after 30 min of 0.2 mM or 7 mM H₂O₂ treatment, and total RNA was isolated from each sample and compared by RNA-sequencing to RNA from untreated cells that were prepared simultaneously.

RNA isolation for RNA-sequencing

Fifty milliliters of bacterial culture (OD₆₀₀ of ~ 0.3) was collected and total RNA was isolated using FastPrep Purification kits (MP Bio) according to the manufacturer’s instructions. Construction and sequencing of the cDNA libraries of the various mycobacterial strains was performed by BGI-Shenzhen (China). Briefly, total RNA from treated mc²155 strains was treated using a Ribominus Transcriptome Isolation Kit (Thermo Fisher Scientific) to remove rRNA contaminations. NEXTflex RNA Fragmentation Buffer (Bioo Scientific) was added to separate the mRNA into short fragments. Using these short fragments as templates, random hexamer-primers were used to synthesize the first strand of cDNA. The second strand of cDNA was synthesized using buffer, dNTPs, RNase H and DNA polymerase I. The short fragments were purified with a QIAQuick PCR extraction kit (QIAGEN) and resolved with EB buffer for end reparation and addition of poly(A). The short fragments were subsequently connected with sequencing adaptors. For amplification by PCR, we selected suitable fragments as templates, based on results of agarose gel electrophoresis. The library was then sequenced using Illumina HiSeq 2000. Clean reads were mapped to the reference genome and the gene sequences using SOAP2 [22]. The RNA-sequencing dataset obtained has been submitted to ArrayExpress under the accession number E-MTAB-3594.

RNA-sequencing data analysis

The raw data were filtered to 1) remove reads with adaptors, 2) remove reads with more than 10% of unknown nucleotides, 3) remove low quality reads (in which more than half of the base quality scores were less than 5). The resulting cleaned paired-end reads were mapped to the M. smegmatis mc²155 reference genome (NC 008596.1) using SOAP2. Mismatches of no more than 5 bases were allowed in the alignment. We performed statistical analysis in read alignments on the genome and genes for each sample. Randomness of the mRNA/cDNA fragmentation was evaluated using the reads distribution of reference genes.

Gene expression was calculated according to the RPKM method (reads per kilobase of exon model per million mapped reads) [23], and eliminated the biases influence of different gene length and sequencing difference using the TPM method [24]. We calculated the ratio of each gene between samples and identified genes differentially expressed between two samples using "the significance of digital gene expression profiles" [25] based on the criteria FDR ≤ 0.001 and a fold change larger than 4. STRING (9.1) [26] was used to analyze the interactions of differentially expressed genes and functional and pathway enrichment analysis. A p-value less than 0.05 was used as a threshold to indicate significant enrichment.

Quantitative PCR of selected genes

Log phase cultures (OD₆₀₀ = 0.8–1.0) of all the tested strains were diluted 1:100 in 7H9 media. The strains were cultured until the OD₆₀₀ reached 0.3 and then divided into control and treatment groups. In the treatment group, the cells were treated with 0.2 or 7 mM H₂O₂ for 30 min and then collected by centrifugation at 12,000 x g. Bacterial pellets were resuspended in TRIzol (Invitrogen, USA), and RNA was purified according to the manufacturer’s instructions. cDNA was synthesized using the SuperScript III First-Strand Synthesis System (Invitrogen, USA). Quantitative real-time PCR (qRT-PCR) was performed in a Bio-Rad iCycler using a 2x SYBR real-time PCR pre-mix (Takara Biotechnology Inc., Japan). The following cycling program was used: 95°C for 1.5 min followed by 40 cycles of 95°C for 10 s, 60°C for 15 s, and 72°C for 15 s, followed by 72°C for 6 min. The M. smegmatis rpoD gene encoding the RNA polymerase sigma factor SigA was selected as a reference gene for normalizing gene expression. The 2^-ΔΔCT method was used [27] to evaluate relative gene expression in the different strains and/or different treatments. All primers used are listed in S1 Table.

Statistical analysis

All statistical analyses were performed using GraphPad Prism 5.0c. Significant differences in the data were determined using t-tests.

Results and Discussion

Effects of H₂O₂ on growth and viability

Hydrogen peroxide (H₂O₂) is a natural oxidant produced by aerobic organisms and can lead to oxidative damage, such as DNA mutations, protein inactivation and drug resistance [2]. In addition, increasing levels of toxic H₂O₂ in the infected host is an important defensive mechanism against invading pathogens. Resistance to H₂O₂ might increase bacterial survival in mycobacterial-infected macrophages. A previous study from our lab showed that increased resistance to H₂O₂ in a mutant strain of M. smegmatis could lead to higher survival in infected macrophages [28]. M. tuberculosis can persist in macrophages for decades, partly because it possesses many regulators that respond to H₂O₂ and many enzymes that detoxify H₂O₂ [3,7]. A recent study analyzed genome-wide changes in gene expression in response to different levels of oxidative and nitrosative stresses in M. tuberculosis [7]. Responses to oxidative and nitrosative stresses were compared and their results revealed a common genetic response used by M. tuberculosis in response to these stresses. This study demonstrated that analyzing global transcription levels can help us understand the molecular mechanisms underlying the response of bacteria to H₂O₂. Here, we examined the global transcriptional response of M. smegmatis to different levels of H₂O₂ using RNA-sequencing.

Bacteria are most sensitive to environmental stresses at the early logarithmic phase [29]. We therefore chose to treat the M. smegmatis strain mc²155 with H₂O₂ when bacteria reached the early logarithmic phase of growth (optical density, OD₆₀₀ of ~ 0.3). We have previously reported that, under experimental conditions in our laboratory, the MIC to H₂O₂ in M. smegmatis is 0.039 mM [28] and that of M. tuberculosis is 1mM. The ratio of the MIC to H₂O₂ of M. smegmatis to M. tuberculosis is ~26. In order to compare the response of M. smegmatis and M. tuberculosis to H₂O₂, we used concentrations of H₂O₂ comparable to those used in Voskuil et al [7]. Here we used an H₂O₂ concentration of 7mM for M. smegmatis to correspond to the 200 mM H₂O₂ treatment used by Voskuil et al. in M. tuberculosis. Similarly, the 0.2 mM H₂O₂ treatment used here corresponded to the ~ 5 mM H₂O₂ treatment used by Voskuil et al in M. tuberculosis. When the M. smegmatis mc²155 strain reached the early logarithmic phase, bacterial cultures were exposed to two different H₂O₂ concentrations, namely 0.2 mM or 7 mM for either 30 min or 3 h, and cultures were then collected and spotted onto 7H10 media. As shown in Fig 1, no growth differences were detected between the bacteria treated with 0.2 mM for 30 min or 3 h and untreated control bacteria, indicating that exposure to 0.2 mM H₂O₂ had little effect on bacterial growth and viability. In contrast, when cultures were treated with 7 mM H₂O₂, we observed that exposure to 7 mM H₂O₂ resulted in a significant decrease in cell survival (Fig 1), indicating that 7 mM H₂O₂ has a bactericidal effect in M. smegmatis. Moreover, the genes induced in response to H₂O₂ (5–10 mM) in the Voskuil study were also found to be induced in M. tuberculosis during infection of activated macrophages[30], indicating that a level of 5–10 mM H₂O₂ is similar to that experienced by bacteria within infected macrophage. Here, the response of 7 mM of H₂O₂ used to examine the M. smegmatis response might suggest the response of bacteria within infected macrophage.

Fig 1. The effect of H₂O₂ stress on the survival of M. smegmatis.

The panel represents serial dilutions (1:10) of mc²155 cultures treated with 0.2 mM or 7 mM H₂O₂ for either 30 min or 3 hour. Three microliters of diluted M. smegmatis cultures were spotted onto solid 7H10 medium. Images shown are representative of at least 3 experiments.

The following experiments were performed to compare the transcriptional response of M. smegmatis exposed to 0.2 mM H₂O₂ or 7 mM H₂O₂ for 30 min when bacterial growth had reached an OD₆₀₀ of 0.3.

Expression profiles of M. smegmatis in response to different levels of H₂O₂

Transcriptional reprogramming is a critical step in bacterial responses to various stress factors to ensure their survival. We therefore examined changes in mRNA expression following treatment with H₂O₂ using RNA-sequencing. mRNA samples from of M. smegmatis mc²155 with or without H₂O₂ treatment were prepared as described in the “Materials and Methods”.

RNA-sequencing mapping statistics showed that approximately 96% of the sequencing reads could be mapped to the M. smegmatis reference genome (NC_008596.1) (Table 1). The percentage of unique mapped reads for untreated mc²155, mc²155 treated with 0.2 mM H₂O₂ and mc²155 treated with 7 mM H₂O₂ were 92.34%, 98.28% and 98.17%, respectively and the number of reads mapped was 6089174, 6390446 and 6548357, respectively.

Table 1. RNA-sequencing mapping statistics.

Sample name	mc2155		mc2155 / 0.2 mM		mc2155/ 7 mM
	Reads number	Percentage	Reads number	Percentage	Reads number	Percentage
Total reads	6594442	100.00%	6502552	100.00%	6670090	100.00%
Total base pairs	593499780	100.00%	585229680	100.00%	600308100	100.00%
Total Mapped Reads	6089174	92.34%	6390446	98.28%	6548357	98.17%
Perfect match	4382586	66.46%	5499445	84.57%	5525430	82.84%
≤ 5bp mismatch	1706588	25.88%	891001	13.70%	1022927	15.34%
Unique match	5818976	88.24%	6065452	93.28%	6171788	92.53%
Multi-position match	270198	4.10%	324994	5.00%	376569	5.65%
Total unmapped reads	505268	7.66%	112106	1.72%	121733	1.83%

Fully annotated data are presented in S2–S4 Tables. Genes were considered to be significantly differentially expressed if their changes in expression were > 4-fold greater compared to the non-treated wild type mc²155 strain, with a false discovery rate (FDR) corrected P-value of < 0.01. To confirm the results obtained from the RNA-sequencing analysis (Fig 2B), several induced genes were examined by quantitative RT-PCR (qRT-PCR). In three independent experiments, total RNA was isolated from M. smegmatis exposed to 0.2 mM or 7 mM H₂O₂ for 30 min and relative levels of expression were analyzed by qRT-PCR. Results were consistent with those obtained from RNA-sequencing results, confirming the validity of our approach. For example, msmeg_0574 exhibited a 21.17 ± 1.11-fold enhancement when induced by 7 mM H₂O₂, but little enhancement (1.61 ± 0.31-fold) when induced by 0.2 mM H₂O₂ (Fig 2A), consistent with RNA-sequencing results (Fig 2B). In addition, msmeg_3242 exhibited a 3116.9 ± 182.8-fold enhancement when induced by 7 mM H₂O₂ and a 7.43 ± 0.11-fold enhancement when induced by 0.2 mM H₂O₂ (Fig 2A)_. The relative expression levels of the genes we chose to test under 0.2 mM and 7 mM H₂O₂ were also consistent with RNA-sequencing results (Fig 2). In summary, these results support the fidelity of the RNA-sequencing results for the analysis below.

Fig 2. Quantitative RT-PCR validation of RNA-sequencing results.

(A) Quantitative RT-PCR analysis of the mRNA expression of genes differentially expressed after treatment with different levels of H₂O₂. M. smegmatis cultures were treated with 2 mM or 7 mM H₂O₂ for 30 min before extraction of RNA for qRT-PCR. The data represent 3 independent experiments. (B) Fold changes of selected genes differentially expressed genes after treatment with 0.2 mM and 7 mM H₂O₂ obtained by the RNA-sequencing.

Upon exposure to 0.2 mM H₂O_2, there were 303 up-regulated genes and 331 down-regulated genes. Genes differentially expressed in the mc²155 strain on treatment with 0.2 mM H₂O₂ were significantly enriched for several GO biological processes, including response to stress (p = 1.44 x 10⁻¹⁰), DNA repair (p = 2.87 x 10⁻⁵), and ergothioneine biosynthesis (p = 1.18 x 10⁻²) when compared to the untreated mc²155 strain (Fig 3A). In GO molecular function categories, we found that genes differentially expressed after treatment with 0.2 mM H₂O₂ were significantly enriched for nuclease activity (p = 2.49 x10^-4), helicase activity (p = 4.55 x 10⁻²), and sulfur compound transmembrane transporter activity (p = 4.55 x 10⁻²) when compared to the untreated mc²155 strain (Fig 3A). As H₂O₂ causes DNA damage, genes involved in DNA repair (listed in Table 2) were induced upon exposure to 0.2 mM H₂O₂. Induction of RecA, AlkA, and DNA helicase by H₂O₂ was also found in the M. tuberculosis study [7]. M. tuberculosis RecA is involved in nucleotide excision, recombination and the SOS response [31]. In M. smegmatis, RecA is induced by DNA damage and is a key regulator element of the SOS response [32]. In M. tuberculosis, dnaE2, which encodes an error–prone DNA polymerase, was shown to increase its expression in response to DNA damaging agents, suggesting that its role is involved in damage tolerance [33,34]. mRNA levels of M. smegmatis dnaE2 and recA were increased 46-fold and 12-fold, respectively, by 0.2 mM H₂O₂, and 5-fold and 7.8-fold, respectively, by 7 mM H₂O₂ (Table 2). The response profiles with high inductions of DNA repair genes in M. smegmatis by both low (0.2 mM) and high (7 mM) levels of H₂O₂ were strikingly different to those in M. tuberculosis which showed high induction from mild levels of H₂O₂ and no change in induction with bactericidal H₂O₂ levels [7]_. Future work should compare and investigate differences between M. smegmatis and M. tuberculosis in DNA-damage-mediated death caused by H₂O₂ in order to provide greater insights into the pathogenicity of M. tuberculosis. The STRING database was used to establish protein interaction networks of physical and functional interactions among the differentially expressed genes identified (Fig 3B). Interestingly, using the KEGG-User Data Mapping [35] (Fig 4B), seven genes involved in fatty acid metabolism (RM018 and RM020) were found and formed an interconnected cluster (Table 2 and Fig 4A). In addition, nine genes involved in glycolysis/gluconeogenesis (msm00010) were found in a partially interconnected cluster (Table 2). Transcription of these genes was induced, suggesting that these differentially expressed genes are involved in the central carbon metabolism (CCM) switch and providing supporting evidence for a previous suggestion that the CCM of M. tuberculosis plays important roles in growth and pathogenicity [36,37]. An extensive transcriptional switch in M. tuberculosis CCM genes during host infection has been reported, indicating that there is a quick change in the metabolic pathway in response to various stresses [38]. The gene pdhB involved in glycolysis/gluconeogenesis was repressed 9.7-fold by 0.2 mM H₂O₂, and pdhA was repressed 11-fold. PdhA and PdhB are constituents of the mycobacterial pyruvate dehydrogenase complex which connects glycolysis and the tricarboxylic acid (TCA) cycle [39]. In contrast to cells treated with 7 mM H₂O₂, changes induced in pdhA and pdhB in the 0.2 mM treatment were weak (Table 2). Similarly, the seven differentially expressed genes induced by 0.2 mM were involved in fatty acid metabolism and decreased by 4 to 6-fold (Table 2), whereas a decrease induction did not appear after the 7 mM H₂O₂ treatment. Together, these results suggest that the metabolic switch of glycolysis/gluconeogenesis and fatty acid metabolism was specific to induction by 0.2 mM H₂O₂.

Fig 3. Overview of the differential expression profiles in response to 0.2 mM H₂O₂ in M. smegmatis.

(A) Enrichment analysis. The differently colored bars indicate the gene number for the enrichment of the annotations. (B) Interaction network of the differentially expressed genes of M. smegmatis induced by 0.2 mM H₂O₂ using STRING (9.1) at confidence scores ≥ 0.4. The network is enriched among the 634 differentially expressed genes and 111 interactions were observed (p value = 0).

Table 2. Fold changes of genes differentially expressed after treatment with 0.2 mM and 7 mM H₂O₂ (treated vs untreated).

Gene Name	Gene Product	log2 Ratio (0.2mM/mc2155)	P-value	FDR	log2 Ratio (7mM/mc2155)	P-value	FDR
DNA repair
msmeg_2839	transcriptional accessory protein	-1.7523338	2.02E-243	5.7E-242	-1.6975845	9.0323E-80	5.4177E-79
alkA	methylated-DNA—protein-cysteine methyltransferase	-2.106759	8.54E-09	2.73E-08	-1.1090648	0.00020253	0.00030498
msmeg_1383	endonuclease IV	-2.8849149	0	0	-0.4418784	0	0
msmeg_1756	endonuclease VIII and DNA N-glycosylase with an AP lyase activity	3.01822392	2.08E-105	3.04E-104	2.96577039	9.82E-104	7.22E-103
dnaE2	error-prone DNA polymerase	5.52502439	0	0	2.44964676	1.32E-277	2.48E-276
lig	ATP-dependent DNA ligase	2.37386688	1.03E-184	2.21E-183	1.60677746	5.66E-69	3E-68
ligA	NAD-dependent DNA ligase LigA	2.32734432	0	0	2.47575753	0	0
recA	recombinase A	3.59091497	0	0	2.96402929	0	0
uvrB	excinuclease ABC subunit B	3.25788081	0	0	4.50884994	0	0
lexA	LexA repressor	3.10981267	0	0	1.01678782	4.81E-103	3.51E-102
radA	DNA repair protein RadA	2.82617738	0	0	1.71244303	0	0
dinP	DNA polymerase IV	4.26301055	1.85E-174	3.84E-173	4.18732816	2.79E-169	3.17E-168
msmeg_1622	putative DNA repair polymerase	4.79317887	8.44E-277	2.71E-275	-0.1339395	0.658812	0.69126208
recD	exodeoxyribonuclease V, alpha subunit	3.50057135	3.24E-216	8.07E-215	2.03125644	2.04E-46	8.42E-46
msmeg_1756	endonuclease VIII and DNA N-glycosylase with an AP lyase activity	3.01822392	2.08E-105	3.04E-104	2.96577039	9.82E-104	7.22E-103
helicase	ATP-dependent DNA helicase	4.16679804	0	0	4.74283172	0	0
tag	DNA-3-methyladenine glycosylase I	2.81384991	2.09E-184	4.47E-183	2.86173411	2.34E-201	3.15E-200
Glycolysis/gluconeogenesis
msmeg_1543	eptc-inducible aldehyde dehydrogenase	-2.6859775	8.91E-139	4.21E-148	-1.2892582	5.64E-56	2.60E-55
msmeg_1762	piperideine-6-carboxylic acid dehydrogenase	2.93235592	2.30E-149	4.21E-148	-1.6876011	2.28E-12	4.83E-12
pfkB	6-phosphofructokinase isozyme 2	-5.7653785	3.88E-196	8.90E-195	-2.8501465	6.61E-126	5.73E-125
pdhB	pyruvate dehydrogenase E1 component subunit beta	-3.2722769	3.01E-30	1.92E-29	0.71595693	5.59E-07	9.61E-07
pdhA	pyruvate dehydrogenase E1 component, alpha subunit	-3.4705711	1.84E-89	2.39E-88	-0.3895867	0.00010596	0.00016157
adhB	alcohol dehydrogenase B	-4.0478653	2.97E-105	4.33E-104	-2.1612025	4.92E-60	2.38E-59
msmeg_6616	S-(hydroxymethyl)glutathione dehydrogenase	-2.956082	0.00E+00	0.00E+00	-1.1422205	1.36E-159	1.45E-158
msmeg_6687	aldehyde dehydrogenase, thermostable	-3.706221	1.64E-29	1.03E-28	-1.5049935	9.36E-12	1.94E-11
msmeg_6834	alcohol dehydrogenase	-2.7848309	2.21E-05	5.51E-05	0.08733237	0.840712	0.85579383
fadA	acetyl-CoA acetyltransferase	-2.7273404	0.00E+00	0.00E+00	0.33348045	5.36E-35	1.86E-34
fadB	putative 3-hydroxyacyl-CoA dehydrogenase	-2.6949142	0.00E+00	0.00E+00	1.39743214	0	0
msmeg_5199	putative acyl-CoA dehydrogenase	-2.6174798	7.78E-91	1.02E-89	-0.4351779	5.88E-07	1.01E-06
msmeg_4832	acyl-CoA dehydrogenase	-2.2726247	1.84E-34	1.30E-33	-1.4448556	2.45E-20	6.42E-20
msmeg_4833	putative acyl-CoA dehydrogenase	-2.176661	8.50E-49	7.39E-48	-2.3488919	3.50E-57	1.65E-56
echA4	enoyl-CoA hydratase	-2.5812975	1.27E-32	8.59E-32	-0.1876747	0.1805012	0.20801109
fadE13	putative acyl-CoA dehydrogenase	-2.4369076	3.84E-11	1.38E-10	-0.1310912	0.579156	0.6139111
Sigma factors
sigG	RNA polymerase factor sigma-70	2.93398738	0	0	3.88123043	0	0
msmeg_0573	putative ECG sigma factor RpoE1	1.38509413	0.0569946	0.08901435	7.09387521	1.35E-209	1.91E-208
msmeg_0574	putative ECG sigma factor RpoE1	0.18840222	0.422278	0.5067336	4.08443636	3.1E-276	5.78E-275
msmeg_1348	RNA polymerase ECF-subfamily protein sigma factor	-0.0465176	0.804554	0.84797939	-2.3586787	1E-17	2.48E-17
sigL	RNA polymerase sigma factor SigL	0.52825986	0.00083713	0.00176811	-2.2355973	4.27E-20	1.12E-19
msmeg_1970	sigma factor	-1.6126499	4.2715E-20	1.1152E-19	-4.1999183	4.27E-20	1.12E-19
mysB	RNA polymerase sigma factor SigB	-0.4921846	4.74E-104	6.85E-103	2.50111799	0	0
msmeg_3008	putative sigma 54 type regulator	-1.8964762	1.61E-11	5.87E-11	-2.0197975	3.44E-13	7.46E-13
msmeg_5214	RNA polymerase sigma-70 factor	4.65312922	2.09E-184	4.47E-183	2.81376729	1.63E-13	3.59E-13
msmeg_5444	RNA polymerase sigma-70 factor protein	0.03717083	0.894318	0.91679688	-2.0919913	9.72E-09	1.8E-08
Transcriptional Regulators
devR	two-component system response regulator	1.01514452	0.00136283	0.00280756	6.64431111	0	0
furA (msmeg_6383)	transcription regulator FurA	2.0393827	1.57E-38	1.19E-37	4.16725591	0	0
phoP	DNA-binding response regulator PhoP	2.90191537	4.67E-220	1.19E-218	-0.5325639	0.00089158	0.00128064
msmeg_4517	TetR-type transcriptional regulator of sulfur metabolism	3.21516913	0.00000169	0.00000457	4.13040109	7.31E-14	1.62E-13
msmeg_4925	transcriptional regulator	0.69321643	0.00330216	0.00644626	2.93688979	1.02E-78	6.03E-78
msmeg_1919	Transcription factor WhiB	2.52297686	0	0	1.07820136	2.53E-126	2.21E-125
msmeg_4025	transcriptional regulator, LysR family protein	1.30263197	0.00055968	0.00120459	5.38130323	1.6E-210	2.28E-209
msmeg_6253	fur family protein transcriptional regulator	1.24070422	0.0469844	0.07479434	3.90800867	1.22E-25	3.59E-25
Detoxification enzymes
trxB	thioredoxin-disulfide reductase	-0.0780198	0.1478068	0.20755437	2.71109242	0	0
trx	thioredoxin	0.12205973	0.0602136	0.09347541	3.84889994	0	0
msmeg_6884	NADP oxidoreductase	0.87052096	0.1166366	0.1680318	4.68101209	4.52E-68	2.38E-67
KatG	catalase/peroxidase HPI	3.82587233	0	0	4.95397834	0	0
msmeg_4890	alkylhydroperoxidase	3.42735043	6.73E-19	3.21E-18	4.22476909	0.0465926	0.05777446
msmeg_3448	two-component system sensor kinase	0.55015338	0.1588256	0.22100457	5.07235098	4.09E-202	5.55E-201
ahpD	alkylhydroperoxidase AhpD core	-2.3697934	0.0210456	0.03618406	3.85029317	4.71E-31	1.53E-30
msmeg_3708	catalase	2.47422002	5.45E-56	5.11E-55	-3.0001305	5.73E-15	1.31E-14

Fig 4. Connected network of the enriched differentially expressed genes following exposure to 0.2 mM H₂O₂.

(A) Connected network of enriched differentially expressed genes involved in fatty acid metabolism (RM018 and RM020). (B) Partial fatty acid metabolism in M. smegmatis. Genes expressed differentially after 0.2 mM H₂O₂ treatment assigned to RM018 and RM020 are marked in red.

Compared to the down-regulation of 331 genes under the 0.2 mM H₂O₂ treatment, 1671 genes were down-regulated under the 7 mM H₂O₂ treatment and 343 genes were up-regulated. In contrast to the small proportion of genes in the genome that responded to the 0.2 mM H₂O₂ treatment (663 differentially-expressed genes, ~10% of the genes in the M. smegmatis genome), 2002 genes were induced in response to 7 mM H₂O₂, representing 29.3% of the genes in the M. smegmatis genome. In contrast to the interaction networks obtained among genes which showed differential expression at the mRNA level in response to the 0.2mM H₂O₂ treatment, we did not find enrichment in specific metabolic pathways among genes that were differentially expressed in response to the 7 mM H₂O₂ treatment. This might be due to the fact that the 7 mM H₂O₂ treatment had more global effects on transcription, which were not limited to specific metabolic pathways. We also conducted an analysis of GO biological processes and identified enrichment in processes including gene expression (p = 2.47 x 10⁻¹), macromolecule biosynthetic processes (p = 2.47 x 10⁻¹) and regulation of gene expression (p = 2.84 x 10⁻¹) (S1 Fig). Ribosome biogenesis was also enriched, though the P-value was 5.48 x 10⁻¹, slightly higher than the cutoff value (P < 0.5). Oxidative stress results in the rapid inhibition of protein synthesis as well as in the reprogramming of gene expression, resulting in growth reduction as an adaption to oxidative stress [40].

Responses of specific genes to exposure to low and high levels of H₂O₂

Mycobacterium utilizes diverse antioxidant systems to combat H₂O₂ stress, including sigma factors, transcriptional regulators, STKs and detoxifying enzymes. To further clarify the responses to different levels of H₂O₂ stress, we compared the biological categories involved in oxidative stress. In M. tuberculosis, sigma factors (such as SigE, SigH, SigL and SigF) are important for initiating the H₂O₂ detoxification pathway [7], and so we examined the response of sigma factors to different levels of H₂O₂ in M. smegmatis. We did not find any differences in the expression of sigF in the 0, 0.2 mM, and 7 mM H₂O₂ treatments. SigF was first described as a stationary-phase stress response sigma factor in M. tuberculosis [41], and we have previously shown that SigF is involved in the oxidative stress response in mycobacteria [41,42]. Lack of SigF induction here may have been due to the fact that SigF is a stationary-phase stress response sigma factor and does not function at the early logarithmic phase, which was used in this study. It will be interesting to compare the global transcriptional response to H₂O₂ at different growth phases. While Voskuil et al. conducted studies showing that M. tuberculosis SigH is highly induced upon exposure to high levels of H₂O₂ [7], here, M. smegmatis SigH was moderately induced at both low and high stresses (data not shown). The gene msmeg_0573, which encodes the ECF sigma factor RpoE1, was the most highly induced sigma factor, exhibiting a 136-fold increase in expression following the 7 mM H₂O₂ treatment. No change in its expression was observed following the 0.2 mM H₂O₂ treatment. Its paralog, msmeg_0574, which encodes the ECF sigma factor RpoE1, was also specifically induced (~17-fold) by 7 mM H₂O₂. These results showed that both MSMEG_0573 and MSMEG_0574 are specifically induced by 7 mM H₂O₂. In contrast, msmeg_5214, which encodes the RNA polymerase sigma-70 factor, was specifically up-regulated in 0.2 mM H₂O₂ (Table 2). Together, these data indicate that distinct sigma factor genes respond to different levels of H₂O₂. In addition to sigma factors, transcriptional regulators also have important roles in the regulation of the oxidative stress response. As M. tuberculosis does not have a functional OxyR, the transcription regulators FurA, IdeR, CarD and WhiB play important roles in the oxidative stress response. FurA was induced 4-fold at 0.2 mM H₂O₂ and 18-fold at 7 mM H₂O₂. Furthermore, no significant changes were found in IdeR and CarD expression levels at either 0.2 mM or 7 mM H₂O_2. The M. smegmatis genome contains six whiB genes, and only MSMEG_1919 was induced by 0.2 mM H₂O₂ (Table 2). DevR has previously been shown to be highly induced in M. tuberculosis only when exposed to high concentrations of H₂O₂ [7]. Consistent with this report, our results showed that in M. smegmatis, devR expression was mildly increased by 0.2 mM and strongly increased (100-fold) after treatment with 7 mM H₂O₂ treatment (Table 2). We next compared the transcription responses of genes coding for serine/threonine-protein kinases (SPTKs) to H₂O₂ exposure. Of the STPKs, we found that following 7 mM H₂O₂ treatment, only pknK was up-regulated. M. tuberculosis PknK has been shown to regulate the slow growth of mycobacteria in response to various stresses and during persistence in infected mice [43]. Just as PknK is involved in the oxidative stress response pathway in M. tuberculosis, PknK plays an important role in M. smegmatis in regulating the response to high levels of H₂O₂. The functions of PknK and its involvement in the response to H₂O₂ require further exploration.

The M. smegmatis genome encodes several enzymes involved in the detoxification of H₂O₂ [4,8]. Our analysis showed that mRNA levels of katG were up-regulated 12-fold and 30-fold following exposure to 0.2 and 7 mM H₂O₂ respectively (Table 2). Notably, trxB (encoding thioredoxin-disulfide reductase) and trx (encoding thioredoxin) expression was induced strongly by 7 mM H₂O₂ treatment (Table 2), but not by 0.2 mM H₂O₂. Similarily, ahpD (encoding alkylhydroperoxidase) and msmeg_6884 (encoding NADP oxidoreductase) responded to 7 mM H₂O₂ but not to 0.2 mM H₂O₂. msmeg_3708 (encoding catalase) exhibited a 5-fold increase in mRNA expression only after exposure to 0.2 mM H₂O₂, indicating that it is specifically induced in response to low levels of H₂O₂ exposure. It will be interesting to investigate the distinct biological roles of enzymes that scavenge different levels of H₂O₂ in mycobacteria. Such studies will lead to greater understanding of the basic roles of these enzymes.

Conclusion

In this study, we have shown that, in M. smegmatis, different genes are induced in response to low and high levels of H₂O₂. A notable difference in the response to low-level (0.2 mM) H₂O₂ and high-level (7 mM) H₂O₂ was observed. When exposed to 0.2 mM H₂O₂, expression of approximately 10% of the genes in the M. smegmatis genome was significantly changed. In contrast, 29.3% of M. smegmatis genes were significantly changed in response to 7 mM H₂O_2. Transcriptional analysis suggested that a metabolic switch in glycolysis/gluconeogenesis and fatty acid metabolism was potentially involved in the response to the 0.2 mM H₂O₂ treatment but not to the 7 mM H₂O₂ treatment. We also observed that transcriptional levels of genes encoding ribosomes decreased when bacterial cells were treated with 7 mM H₂O₂. This result suggests that 7 mM H₂O₂ treatment affected the protein synthesis apparatus and thus reduced protein synthesis, resulting in reduced bacterial growth. The expression level of gene msmeg_5214 (encoding the RNA polymerase sigma-70 factor) was induced in response to 0.2 mM H₂O₂, and the rpoE1s (msmeg_0573 and msmeg_0574) were induced specifically in response to 7 mM H₂O₂. In addition, different regulators were observed to respond to different levels of H₂O₂. MSMEG_1919 was induced following exposure to 0.2 mM H₂O₂, while DevR was highly induced by the 7 mM H₂O₂ treatment. Our results show that pknK, a gene encoding a STPK, is involved in the 7 mM H₂O₂ treatment response and that different genes encoding detoxifying enzymes, including the genes encoding KatG, AhpD, TrxB and Trx, were expressed in response to different levels of H₂O₂. In summary, this study of global transcriptional changes that occur after exposure to different levels of H₂O₂ documents changes in transcriptional regulation in response to exposure to low and high level H₂O₂ treatments, including the use of different sigma factors, regulators, serine/threonine kinases and differences in the transcriptional levels of detoxifying enzymes used to combat H₂O₂ stress. Further study of these genes will aid our understanding of the mechanisms underlying the precise regulation and scavenging of H₂O₂.

Supporting Information

S1 Fig. Overview of differential gene expression in response to 7 mM H₂O₂ in M. smegmatis.

(JPG)

S1 Table. Oligonucleotide primers used in this study.

(DOC)

S2 Table. RNA-sequencing expression data for the control of M. smegmatis mc²155 without H₂O₂ treatment.

(XLSX)

S3 Table. RNA-sequencing expression data for the M. smegmatis mc²155 strain treated with 0.2 mM H₂O_2.

(XLSX)

S4 Table. RNA-sequencing expression data for the M. smegmatis mc²155 strain treated with 7 mM H₂O_2.

(XLSX)

Data Availability

All relevant data are within the paper and its Supporting Information files. The dataset of RNA-sequencing has been submitted to ArrayExpress under the accession number E-MTAB-3594.

Funding Statement

This work was supported by the National Basic Research Program of China (2012CB518700 and 2014CB744400) and the Key Program of the Chinese Academy of Sciences (KJZD-EW-L02).