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Transcriptional and biochemical analyses of Planomicrobium strain AX6 from Qinghai-Tibetan Plateau, China, reveal hydrogen peroxide scavenging potential

BMC Microbiology volume 22, Article number: 265 (2022) Cite this article

Abstract

Background

The bacterial mechanisms responsible for hydrogen peroxide (H2O2) scavenging have been well-reported, yet little is known about how bacteria isolated from cold-environments respond to H2O2 stress. Therefore, we investigated the transcriptional profiling of the Planomicrobium strain AX6 strain isolated from the cold-desert ecosystem in the Qaidam Basin, Qinghai-Tibet Plateau, China, in response to H2O2 stress aiming to uncover the molecular mechanisms associated with H2O2 scavenging potential.

Methods

We investigated the H2O2-scavenging potential of the bacterial Planomicrobium strain AX6 isolated from the cold-desert ecosystem in the Qaidam Basin, Qinghai-Tibet Plateau, China. Furthermore, we used high-throughput RNA-sequencing to unravel the molecular aspects associated with the H2O2 scavenging potential of the Planomicrobium strain AX6 isolate.

Results

In total, 3,427 differentially expressed genes (DEGs) were identified in Planomicrobium strain AX6 isolate in response to 4 h of H2O2 (1.5 mM) exposure. Besides, Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses revealed the down- and/or up-regulated pathways following H2O2 treatment. Our study not only identified the H2O2 scavenging capability of the strain nevertheless also a range of mechanisms to cope with the toxic effect of H2O2 through genes involved in oxidative stress response. Compared to control, several genes coding for antioxidant proteins, including glutathione peroxidase (GSH-Px), Coproporphyrinogen III oxidase, and superoxide dismutase (SOD), were relatively up-regulated in Planomicrobium strain AX6, when exposed to H2O2.

Conclusions

Overall, the results suggest that the up-regulated genes responsible for antioxidant defense pathways serve as essential regulatory mechanisms for removing H2O2 in Planomicrobium strain AX6. The DEGs identified here could provide a competitive advantage for the existence of Planomicrobium strain AX6 in H2O2-polluted environments.

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Background

One of the critical challenges for living organisms is to overcome the oxidative stress caused by reactive oxygen species (ROS), including hydrogen peroxide (H2O2), hydroxyl radicals (˙OH), and superoxide anions (O2˙¯), that cause damage to virtually all macromolecules of the cell [1, 2]. For instance, the higher concentration of ROS could damage cellular proteins [3], lipids [4], and DNA [5], leading to several growth and metabolic defects, thereby causing cell death. To counteract these lethal effects, living organisms have developed different mechanisms at the genetic, molecular, and biochemical levels [1, 6]. For instance, when bacteria were exposed to the mM levels of H2O2, they produced catalase (CAT) to scavenge H2O2, while mutants with impaired CAT activity lost their H2O2 scavenging capability [7]. Furthermore, bacteria are equipped with enzymatic antioxidant defense systems to cope with higher or lower concentrations of H2O2 [8, 9]. To avoid the lethal effects of H2O2, effective natural antioxidants seem a vital target to be discovered. Therefore, identifying new bacterial taxa that could produce potent antioxidants for removing H2O2 remained the main aim of this study.

Since specific bacteria have preferred several vital ecological processes and sustaining life for decades [10]; therefore, understanding the bacterial ecosystem is gaining special attention. However, a major portion of these microbes and their ecological functions in desert ecosystems are yet to be explored. Coping with oxidative stress by activating antioxidant defense systems is among the vital functions of microbes [1, 11, 12]. The Qaidam Basin of the Qinghai-Tibet Plateau is a cold hyper-arid desert at an altitude of more than 4,500 m [13]. Diverse bacterial communities dominate these high-elevation cold-desert ecosystems, frequently subjected to stressful conditions like low atmospheric oxygen content, excessive ultraviolet (UV) radiation, low air temperatures, and low nutrient availability [13,14,15]. These extreme environmental conditions serve as a potential source of the genomic pool and are considered suitable regions for antioxidant-producing bacteria.

To cope with H2O2 stress, bacteria use multifaceted defense mechanisms by producing antioxidant enzymes, including superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and CAT [7, 16,17,18]. Among bacteria, Escherichia coli was the first identified model of enzyme regulator, and various defense-related genes have been activated for H2O2 scavenging, thereby providing the best protective system against oxidative stress [2, 19, 20]. On the other hand, the Gram-positive bacterial strain Deinococcus radiodurans utilizes enzymatic antioxidants to sense oxidative stress and scavenge ROS [21, 22]. The H2O2 stress could cause significant damage and inactivate the functions of DNA, lipids, and proteins, leading to several metabolic deficiencies and mutations [2, 8, 23]. Previously, it was reported that the process of H2O2-mediated degradation of cellular machinery was more complex. Over the last decade, researchers have recognized enzymatic defense mechanisms in bacteria that can scavenge H2O2 in vitro, while in vivo research displays a weaker response to H2O2 [2, 8, 24]. The lack of knowledge about cellular resistance against H2O2 and the resultant products of cellular metabolism hinders to development advance cellular approaches for combating toxic effects. Hence, a better understanding of the molecular events that respond to H2O2 toxicity might improve bacterial adaptation and optimization [7, 16].

In the last decade, rapid advancements in next-generation sequencing techniques and bioinformatics have made the cost of sequencing reasonable. For instance, high-throughput RNA-sequencing (RNA-Seq) has been broadly used to analyze transcriptional changes across the whole genome [25, 26]. In various bacterial species for which genomic information is absent, transcriptional profiling seems a powerful technique for studying the H2O2 adaptation mechanism and other biological characteristics [7, 8, 27]. In different species of bacteria, several H2O2-induced genes have been recognized, and the expression patterns and the function of specific H2O2-induced genes have been studied [28,29,30]. This suggests that the biochemical and physiological responses are governed by a network of DEGs that controls complex molecular mechanisms in bacteria to adapt against H2O2 stress.

The genus Planomicrobium was originally described by Yoon et al. [31]. There were six valid speciesin the genus Planomicrobiumuntil recently: Planomicrobium psychrophilum, P. chinense [32], P. koreense, P. mcmeekinii, P. okeanokoites [31], and P. alkanoclasticum [32, 33]. The known characteristics of the genus Planomicrobium are that the species are Gram-positive to Gram-variable, aerobic, yellow-to orange-pigmented, and non-spore-forming, respectively. Planomicrobium species contained DNA G and C in the range 35–47 mol% [34]. In this study, the Planomicrobium-AX6 strain was isolated from the cold-desert soil in the Qaidam Basin, Qinghai-Tibetan Plateau, China which elucidated a strong antioxidant activity. The H2O2 scavenging mechanisms of Planomicrobium are rarely explored. Therefore, in this study, we carried out the transcriptional profiling of the Planomicrobium strain AX6 intending to unravel the molecular aspects associated with H2O2 scavenging potential in cold-desert ecosystems. As per our knowledge, this is the first study that presents the transcriptional analyses of any strain belonging to Planomicrobium in response to H2O2 stress.

Materials and Methods

Preparation and molecular identification of bacterial strain

The bacterial Planomicrobium strain AX6 was isolated from the desert sand soils (0–10 cm) in the Qaidam Basin, Qinghai-Tibet Plateau, China (37.088°N, 95.427421°E). The medium used for isolation was composed of (g/L): yeast extract, 5; peptone,10; sodium acetate, 1; ammonium nitrate, 0.2; sodium citrate, 0.5 and agar, 15; having a pH of 7.5, and incubated for 96 h at 20 °C, and further preserved in glycerol (20%, v/v) at -80 °C [35] for further processing. Readers are referred to Ting et al. [36] with regard to detailed molecular identification of this bacterial strain.

H2O2 scavenging potential

Escherichia coli JM109 (strain number C1310) purchased from Solarbio Company has a low tolerance to oxidizing substances [37] and thus was used as a negative control. While Deinococcus radiodurans (strain number 1.3828) purchased from China Micro Ordinary Microbiology Center (CGMCC) was used as a positive control. This bacterial isolate thrives in desert ecosystems due to ultra-high radiation resistance and antioxidant capabilities [37, 38]. The details pertaining to the respective bacterial strains are shown in supplementary material Table S1. All these bacterial isolates were exposed to two different H2O2 concentrations (1.5 and 3 mM) for 4 h.

The effect of H2O2 on Planomicrobium strain AX6 growth was studied as follows: 100 μL inoculum of Planomicrobium strain AX6 in their exponential growth stage (OD600 = 0.6) was inoculated in 50 mL Luria Broth (LB) medium containing 0, 0.5, 1.0, 1.5, 2.0, and 2.5 mM H2O2 and incubated at 28 °C for 103 h at the speed of 200 rpm/min. The bacterial cell concentration was estimated using the absorbance of a spectrophotometer (600 nm). All these experiments were done in triplicates.

ROS scavenging potential assay

The scavenging ability of three different ROS agents by Planomicrobium strain AX6 was evaluated. For this purpose, the bacterial inoculums were mixed with phosphate buffer solution (PBS) and further suspended with 2,2-diphenyl-1-picrylhdrazyl (DPPH)•ethanol according to the method used by Lee et al. [39], and DPPH scavenging was estimated. Moreover, the bacterial inoculum was mixed with Tris–HCl buffer, and the method used by Wang et al. [40] was adopted for studying the O2¯ scavenging potential of the strain. For determining the hydroxyl radical (˙OH) scavenging potential, the bacterial inoculum was mixed with sodium phosphate buffer according to the method and estimation used by Das and Goyal. [41]. The experiments mentioned above were repeated three times, and mean results were reported in this study.

Estimation of SOD, CAT, and GSH-Px

For enzymatic analyses, the SOD was extracted using the pyrogallol auto-oxidation method [42]. Furthermore, CAT content assay was determined by spectrophotometry, hydrogen oxide absorbance change value to characterize, the procedure was modified from Nakayama et al. [43]. The activity of GSH-Px was studied by using the colorimetric method with the help of Leagene kit (Beijing Leagene Biotech Co., Ltd., China).

RNA-sequencing

The extraction of total RNA from 0 and 1.5 mM H2O2 concentrations was performed using the TRIzol® Reagent RNA Purification Kit for bacteria (Invitrogen) according to the manufacturer’s instructions. A Nanodrop 2000 spectrophotometer evaluated the integrity and the quality of the extracted total RNA. All RNA samples were DNAse treated using the Ribo-Zero Magnetic kit to eliminate every contaminating genomic rRNA. The experiments were performed in triplicate for each stress treatment. RNA sequencing was done on the Illumina HiSeq4000 according to the manufacturer’s protocol (Illumina Inc., Majorbio, China). Briefly, the quality and the integrity of the total RNA were evaluated using the Agilent 2100 Bioanalyzer. RNA with an RNA Integrity Number (RIN) of 7.0 or higher was used for sequencing library preparation and processing. Sequencing libraries were adjusted using the TruSeq Stranded Specific mRNA Library sample Prep Kit as per the manufacturer’s guidelines (Illumina). Cluster generation was done according to the manufacturer’s references for onboard clustering (HiSeq 4000 PE Cluster Kit, Illumina). Next, sequencing (2 × 150 bp) was performed using Illumina Hiseq 300 platform.

Bioinformatics analysis

The quality of FASTQ files was evaluated using FASTQC v. 0.11.8 [44]. Generally, the default parameters were used to align the reads to the Planomicrobium strain AX6 genomes to assess contamination and further aligned to the bacterial genomes assembly using Bowtie2(http://www.bowtie-bio.sourceforge.net/bowtie2/manual). The transcript abundances were processed using RSeQC-2.6.3 (http://rseqc.sourceforge.net/), having strand-specific read counting. Data were normalized, and the DEGs were quantified using the edgeR (http://www.bioconductor.org/packages/2.12/bioc/html/edgeR.html) by applying criteria of having corrected P-value or FDR < 0.05 and fold change log2FC ≤—1 or ≥ 1 [45,46,47]. Differential gene enrichment analyses for Gene Ontology (GO) (https://github.com/tanghaibao/GOatools) and Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways (http://www.genome.jp/kegg/) were performed using Goatools and KOBAS function [48, 49], respectively, and the statistical method used was Fisher’s exact test. The dominant metabolic pathways were analyzed through KEGG enrichment analysis having FDR < 0.05 [50]. The fitting growth curves of Planomicrobium strain AX6 were drawn with R-package (plyr, ggplot2) v 3.6. The Principal Component Analysis (PCA) was analyzed to find outliers and discriminate sample clusters with high similarities. The scatter plot represents genes' expression level (FPKM value) in the control and treatment samples [47]. The heatmap was generated to find genes with significant differences by clustering their expression patterns using hcluster (complete algorithm). All analyses were carried out via R-Vagan v. 6.3.

Results

Identification and growth adaptation attributes of Planomicrobium strain AX6 against H2O2 stress

Planomicrobium strain AX6 was identified at the molecular level by Ting et al. [36] using 16 s rRNA sequencing. More than 80% of the Planomicrobium strain AX6 showed resistance to 0.02—1.0 mM H2O2, and there was no significant variation in the survival rate. Though, after 1.5 mM H2O2, it reduced to 56% and showed a substantial change in survival rate, then to 45% and 27% on 2.0 mM and 3.0 mM, respectively (Fig. S1A). Planomicrobium strain AX6 growth was decreased (cultural density at OD600) after 103 h in 2.0 and 2.5 mM H2O2 treatment (Fig. S1B). We selected a concentration of 1.5 mM H2O2 for further study. As shown in Figure S1B, the growth rate was significantly inhibited by 1.5 mM of H2O2 between 10 and 49 h of treatment, demonstrating that Planomicrobium strain AX6 is directly involved in H2O2 scavenging.

Bacterial comparison for H2O2 scavenging ability

The DPPH free radical scavenging rate is usually used to determine the antioxidant capacity. Therefore, the scavenging rates of DPPH, ˙OH, and O2˙¯ were measured to characterize the antioxidant characteristics of Planomicrobium strain AX6 (Table S1). In addition, Planomicrobium strain AX6 to remove H2O2 with different concentrations (0, 1.5, and 3 mM) was verified. The DPPH, O2˙¯, and ˙OH scavenging potentials of Planomicrobium strain AX6 were significantly higher (16.6, 18.3, and 36.4%) than the negative control (5.0, 9.5, and 6.1%) (P < 0.05) while lower than the positive control (20.7, 21.8, 53.0%) when treated with 1.5 mM of H2O2 (Table S1). These results confirmed the antioxidant potential of Planomicrobium strain AX6.

Estimation of SOD, CAT, and GSH-Px

As illustrated in Fig. 1A, upon 1.5 and 3 mM of H2O2 treatment, GSH-Px activity was significantly higher than the control (0 mM H2O2) (P < 0.05). With the increase in H2O2 levels, the SOD and CAT activity of Planomicrobium strain AX6 decreased significantly (Fig. 1B and C). This suggests that SOD is likely to be responsible for the conversion of O2˙¯ into H2O2, where the oxidation environment dominated by H2O2 inhibits the process of SOD [51], which as a result, might decrease the SOD activity.

Fig. 1
figure 1

Antioxidant enzyme activity of Planomicrobium-AX6 exposed to H2O2 treatments. A glutathione peroxidase (GSH-Px), B superoxide dismutase (SOD), and (C) catalase (CAT) production rate when exposed to H2O2 (0, 1.5, and 3 mM) for 4 h. Where asterisks indicate significant differences. ***P < 0.001; **P < 0.01; *P < 0.05

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Transcriptional profiling of the Planomicrobium strain AX6 in response to H2O2 stress

To gain insights into genes and key metabolic pathways responsible for H2O2 regulation by Planomicrobium strain AX6, their transcriptional profiling was conducted in response to H2O2 stress. The Illumina/Truseq™ RNA platform generated two libraries of bacterial included (AX6) and control (CK) groups comprising 22,260,393 and 23,723,531 raw reads, respectively (Table S2). The length of a single read was 200 bp. After removing the short reads, contaminated reads, and adaptor sequences from Planomicrobium strain AX6 and CK group libraries, a total of clean reads comprising 21,936,575 and 23,271,179, having Q20 values 98.89 and 98.75%, respectively, and Q30 values were 96.59 and 96.17%, respectively. Moreover, the GC content values were 44.03 and 45.66%, while 98.90 and 98.62% of transcripts have been mapped, respectively (Table S2). Furthermore, 770,388 transcripts were composed of high-quality reads using Glimmer 3.02 software. The average length was 832 bp. Scaffold N50 and N90 values were 55, 491, 2, and 59,610.

Gene expression pattern and correlation between control and H2O>2 stress

According to RSEM software, the log2FPKM distribution between the control and H2O2 suggested the highly expressed genes under stress conditions compared to the control (Fig. 2A, B), which exhibited a pattern consistent with the main biological replicates that meet the expectations of the experimental design. The statistical results of each sample's correlation are shown in Fig. 2B. The columns correspond to the FPKM ≥ 0.01 of each gene, and the rows correspond to the six samples. Similarly, the scores matrix delivered sample scores for gene expression patterns, labeling the profiling of gene expression distribution between control and stress treatment. The biological triplicate samples of each group were clustered together. The control and stress treatment groups were plotted distinctly along the PC1 direction (Fig. 2C).

Fig. 2
figure 2

Density curve, hierarchical cluster heatmap, and Principal component analysis (PCA) of Planomicrobium-AX6 transcriptome data, exposed to hydrogen peroxide for 4 h under H2O2 (1.5 mM). A Density curve. The probability density distribution of the expression of all genes was log.2FPKM, the peak of the density curve represents the region where the gene expression of the entire sample is most concentrated. Each color in the figure represents a sample, and the sum of all probabilities is 1. B Hierarchical cluster heatmap. The correlation analysis between samples, the closer the correlation coefficient is to 1, the higher the similarity between samples. According to the quantitative results of FPKM, I calculated the correlation between all the samples. C Principal component analysis (PCA). The PCA demonstrates of expressed genes (FPKM ≥ 0.01) a clear separation (Axis 1) of AX6 vs.CK treatment. CK designate RNA sample replicates obtained from Planomicrobium-AX6 without H2O2 (1.5 mM) for 4 h, whereas AX6 is RNA sample replicates obtained from Planomicrobium-AX6 with H2O2 (1.5 mM) for 4 h. CK1-3 control; AX1-3 treatments, n = 3

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Identification of DEGs in Planomicrobium strain AX6 exposed to H2O2

To find the variation in transcriptional profiling of Planomicrobium strain AX6 exposed to H2O2, the gene expression changes of both control and stress treatments were compared. In this study,

statistical comparisons employed (P-value) indicating significant differences between Planomicrobium strain AX6 and CK control, the DEGs were regarding the two criteria, the average fold change was ≤ 2 having P-value > 0.01 and FDR ≤ 0.001 (For instance of AX6 vs. CK, Fig. 3A and B). A total of 3,427 significant DEGs were identified. Among them, the number of up-regulated transcripts (2833) was higher compared to down-regulated (594) at the 4 h under H2O2 (P > 0.05) (Table 1; Fig. 3A and B), there was rich variation in response to H2O2. We found that the expressions differed for analyzed genes, with significant differences between control and stress treatment. For transcriptional profiling of Planomicrobium strain AX6 in response to H2O2 stress, the transcription profiles of 6 samples were analyzed using a clustering algorithm and tree view (Fig. 3C). They exhibited different profiles at the time points of the pairing between the two groups and each group had a different sample-specific profile. Commonly, similar transcription patterns were identified across control (CK1, CK2, CK3), while the up-regulated genes were reported in stress treatment (AX6-1, AX6-2, AX6-3), respectively. The samples of CK3 and AX6-3 shared similar transcription patterns (Fig. 3C). In addition to this, 976 stress-responsive DEGs were found that were further divided into 10 sub-clusters. The average profile for each group in each sub-cluster and the existent profile variances between the Planomicrobium strain AX6 and the control group are shown in Fig. 3D. For instance, in sub-clusters 1, 2, and 4 to 7, the gene expression level under stress was up-regulated, while it was down-regulated in CK. In sub-cluster 8, the gene expression was down-regulated upon stress, whereas it was up-regulated in CK. Similarly, in sub-cluster 9, the gene expression was down-regulated in AX6-1 and up-regulated in AX6-2 and AX6-3, remaining stable from CK1 to CK3, respectively. Finally, in sub-cluster 10, the gene expression in AX6-2 was comparable with the control (Fig. 3D).

Fig. 3
figure 3

Heatmap, scatter, and volcano plot of DEGs of Planomicrobium-AX6 transcriptome data, exposed to hydrogen peroxide for 4 h under H2O2 (1.5 mM). A Scatter plot. The horizontal and vertical coordinates have logarithmic values, indicate the expression levels (FPKM value) of genes in the AX6 and CK. B Volcano plot. Each colored point in the volcano plot represents a single gene. Plotted along the x-axis is the log2 fold change of each gene. The y-axis represents the negative logarithm of the corresponding P-value of that gene. C Heatmap. The scale bar shows the z-score for a differentially expressed gene. The color represents the amount of gene expression in the group of samples (log.10 FPKM), referring to the color key at the upper left. D Line plot. The sub-cluster of the heatmap represents a gene, and the blue line represents the average expression of all genes in the sub-cluster. CK designate RNA sample replicates obtained from Planomicrobium-AX6 without H2O2 (1.5 mM) for 4 h, whereas AX6 is RNA sample replicates obtained from Planomicrobium-AX6 with H2O2 (1.5 mM) for 4 h. CK1-3 control; AX1-3 treatments, n = 3

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Table 1 The number of DEGs in AX6 when exposed to H2O2 (1.5 mM) for 4 h
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Functional annotation

The functions of all the DEGs recognized in this work were classified by GO assignments (http://www.geneontology.org/). A total of 3,427 DEGs were annotated into 2,345 functional groups in the two categories in the three basic ontologies as cellular component, molecular function, and biological process. The study covered 39 functional groups comprising 11 for cellular components and molecular function and 17 for biological processes. Metabolic process and catalytic activity were the two largest groups, and the smallest group were extracellular region part, nucleoid, and biological adhesion, with only one GO enrichment predicted for each group (Fig. 4).

Fig. 4
figure 4

Gene ontology (GO) classification of DEGs for Planomicrobium-AX6 between the H2O2 (1.5 mM) for 4 h and the control samples without H2O2 (1.5 mM) for 4 h. The red bars represent up-regulated genes, the blue bars represent down-regulated genes. The lower axes represents the number of genes annotated to a GO term, and the upper axes represents the ratio of the number of genes annotated to a GO term to the total number of all GO-annotated genes

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Clusters of Orthologous Groups (COG) assignments were also used to estimate and classify possible functions of the DEGs. Based on sequence homology, DEGs could be characterized into 21 COG groups. Metabolism group and amino acid transport with 173 COG were the most prominent groups, followed by an unknown function (161), general function prediction only (143), ribosomal structure, translation, and biogenesis (136), and metabolism group and inorganic ion transport (123) (Fig. S2). The chromatin structure and dynamics groups were the smallest, with only one COG.

ntioxidant genes regulation in Planomicrobium strain AX6 exposed to H2O2

The DEGs reported in Planomicrobium strain AX6 in response to H2O2 were ascribed to many genes encoding antioxidant enzymes. In addition, KEGG pathways enrichment analysis of the identified DEGs recognized many metabolic pathways that seemed to be potentially affected by the addition of H2O2 to Planomicrobium strain AX6. For instance, our results indicated that the defensive line against H2O2 in Planomicrobium strain AX6 comprises GSH-Px, Coproporphyrinogen III oxidase, SOD, and CAT (Table 2). The gene encoding GSH-Px (Gpx, orf03455_E1.11.1.9) was up-regulated by 10.15-fold in response to H2O2, while the GSH-Px gene (orf02189_ E1.11.1.9) was down-regulated 1.21-fold (Table 2). Genome sequence analysis showed two Gpx genes present in Planomicrobium strain AX6. The Gpx systems are the leading and highly studied enzymatic system that eliminates H2O2 in different bacteria. The Coproporphyrinogen III oxidase genes (orf00260_ hemN, hemZ, orf03367_ hemL, and orf00170_ hemL) were up-regulated by 5.31-, 2.34-, and 1.19-fold in H2O2 treatment samples (Table 2). The SOD gene (orf00300_ SOD2) was down-regulated by 1.34-fold, and other SOD genes (orf03456_guaB and orf03437_cysK) were up-regulated by 1.02- and 1.17-fold in H2O2, respectively. SOD catalyzes the dis-mutation of superoxide into H2O2 and O2, and therefore orf03456 and orf03437 might be vital antioxidant defenders in Planomicrobium strain AX6 when the cell is exposed to free radicals. Furthermore, to cope with the H2O2 stress, the gene encoding CAT (orf02500_ katE, CAT, catB, srpA, orf03059_ K07217, and orf01958_ katE, CAT, catB, srpA) were down-regulated by 1.21-, 1.26-, and 1.24-fold in H2O2 (Table 2). These results indicate that the capacity of oxidative stress defense in Planomicrobium strain AX6 with strongly decreased CAT activity was due to a decrease in the expression level of CAT genes, confirmed by CAT enzymes activity (Fig. 1). A future experiment should be conducted to determine which mechanisms Planomicrobium strain AX6 utilizes to down-regulate the CAT gene expression level.

Table 2 Bacterial antioxidant genes differently expressed when exposed to hydrogen peroxide for 4 h under H2O2 concentration (1.5 mM)
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In addition, changes in gene expression levels analysis and DEGs between Planomicrobium strain AX6 and CK were primarily related to coenzyme transport and metabolism. Consequently, the DEGs involved in these functions were further described in detail (Table S3). Most of the genes were involved in thiamine metabolism, including the iron cysteine desulfurase, thiamine biosynthesis protein ThiI, hypothetical protein, and alkaline phosphatase up-regulated by the addition of H2O2. The genes related to cysteine desulfurase (iscS, NFS1) might be providing sulfur, which is later combined during in vivo Fe-S cluster synthesis, were observed to be up-regulated in H2O2 treatment (Table S3). Thiamine biosynthesis protein-encoding genes (such as thiI and thiE) were also up-regulated by adding H2O2.

Besides, three genes encoding alkaline phosphatase (E3.1.3.1, phoA, phoB) were up-regulated. In addition, the environmental bacterial regulatory genes were down-regulated in H2O2 treatment. Moreover, genes responsible for oxidative stress adaptation were detected in the amino acids biosynthesis, mismatch repair, bacterial chemotaxis, fatty acid, cysteine and methionine metabolism, pentose phosphate pathway, and two-component system substitutions that might have allowed for effective functionality (Table S3).

Discussion

The potential scavenging ability of H2O2 toxicity in the Planomicrobium strain AX6 recovered from desert soil in the Qaidam Basin, Qinghai-Tibetan Plateau, China, was carried out here by studying its growth and transcriptional profiling in response to H2O2 stress. This area is characterized by low temperature, oxygen level, and high radiation [13, 52], which directly cause light-induced damage to organisms, and forms an environment with high oxidation intensity [53]. In the higher H2O2 concentration, Planomicrobium strain AX6 showed a high survival rate coupled with a strong oxidative stress response. Previous studies have shown that different bacterial strains isolated from cold environments can adapt to the desert oxidative stress environment [12, 54,55,56,57,58,59]. In addition, Planomicrobium strain AX6 showed potential DPPH, O2˙, and OH, scavenging ability (Table S1), where the bacteria generate basal levels of ROS-scavenging enzymes to avoid the accumulation of endogenous H2O2 and O2∙− [60]. The mechanism mainly comprises SOD that catalyzes the dismutation of O2∙− to H2O2 and CAT that convert H2O2 to O2 and H2O [61, 62].

Furthermore, we studied the mechanisms that might play an essential role in the resistance of Planomicrobium strain AX6 against H2O2 stress using RNA sequencing. Based on RNA-seq profiling, a substantial number of genes (3,508) was reported to be distinctly expressed in the Planomicrobium strain AX6, signifying an extreme variation in the transcriptional profile of bacterial strain (Table 1) upon exposure to H2O2 stress. The genes are expressed differentially to elaborate on the resistant mechanism and the metabolic pathways that provide the energy needed to cope with oxidative stress. Therefore, it is reasonable to assume that might cause the weak resistance response produced against the bacterial strain or basis nutrients to be easily accessible to the bacteria to accomplish their metabolic pathways.

Transcriptional dynamics were examined in the CK and H2O2 stress-treated Planomicrobium strain AX6 strain (Fig. 2). The differences between the H2O2 stress treatment and CK responses were also revealed in the PCA of the transcriptional data (Fig. 2), which separated the H2O2 stress treatment and CK samples. Toxic levels of H2O2 can reach up to millimolar due to the oxidative stress caused in the host immune cells [7]. To prevent the toxicity of H2O2, the bacteria produce several scavenging enzymes to maintain intracellular H2O2 levels at the nanomolar [61]. The accumulation of high concentrations of H2O2 might cause serious damage to many cellular organelles by amending proteins and DNA. However, several genes encode antioxidant proteins/enzymes that detoxify H2O2 or repair the oxidative damage caused by oxidative stress. Furthermore, these antioxidant proteins/enzymes are vital in regulating the antioxidant defense system's expression, including the thioredoxin and catalase systems, against H2O2 and at extreme pressure with MgCl2 supplementation [63,64,65]. However, it is currently unclear what bacterial-specific genes respond to and which antioxidant enzymes regulated genes contribute to H2O2 toxicity. These are exciting concerns for future research exploring the relations between H2O2 stress and CAT defense mechanisms of cold-desert isolated bacteria.

In this study, the CAT enzymes coding genes such as (katE, CAT, catB, srpA, K07217, katE, CAT, catB, srpA) were slightly down-regulated, signifying that CAT might not play a key role in the scavenging of H2O2. So we were also surprised to find that relatively down-regulation of these genes had no seeming effect on H2O2 resistance in Planomicrobium strain AX6, despite the circumstance that CAT expression genes were invoked more strongly by CK treatment than by H2O2 [66, 67] (Fig. 1; Table 2). This might be due to the redundant nature of bacterial resistance mechanisms [7] or could be predictable since O2 is produced in its reaction [65]. Another possibility is that increased production of SOD likely to combine with CAT, resulting in a decreased ability of cells to remove H2O2 [51, 68]. Glutathione is a vital antioxidant, and GSH-Px catalyzes the reaction of glutathione and an extensive range of oxides [69,70,71]. The genes Gpx, orf03455_E1.11.1.9 were up-regulated while orf02189_ E1.11.1.9 was down-regulated (Table 2). We investigated that Planomicrobium strain AX6 has the complete KEGG pathway of glutathione metabolism and encodes as many as 2 copies of GSH-Px genes (Table 2), which shows that glutathione likely plays a key role in avoiding cellular substrates from O2 inactivation. In addition, coproporphyrinogen III oxidase and SOD can also protect the bacterial cells against H2O2 stress [72, 73]. Planomicrobium strain AX6 contains 4 genes (hemN, hemZ, hemL1,2) which were slightly up-regulated and thought to be involved in the coproporphyrinogen III oxidase system and 3 SOD genes in which 2 were up-regulated (guaB and cysK) whose products may also assist Planomicrobium strain AX6 in relieving H2O2 stress, while SOD2 gene was relatively down-regulated.

We next focused on the expression patterns of thiamine metabolism-related genes, which might regulate the enzymatic activity of bacteria [29, 63]. The genes that were up-regulated include iscS, NFS1 (Cysteine desulfurase), E2.7.6.2, THI80, thiM, thiD (hypothetical protein), and thiE (thiamin-phosphate pyrophosphorylase), and the down-regulated genes of the environmental bacterial metabolism were glxK, E2.3.3.9, aceB, glcB, kdgK, glk, E5.1.3.3, galM, and hemL, under Planomicrobium strain AX6 compared to CK condition. In addition, numerous genes associated with cysteine were up-regulated (Table S3). Cysteine plays a key role in iron transport, as a high level of cysteine is a crucial component for the biosynthesis of siderophores in iron transport [63, 74]. Cysteine is mainly derived from the conversion of other amino acids to directly acquire extracellular cysteine in the bacterial cell [75]. The expression of genes in E. coli is mostly controlled by S-adenosylmethionine concentrations and intracellular cysteine [76,77,78,79], signifying that methionine synthesis, cysteine, and transport genes are up-regulated by H2O2 in Planomicrobium strain AX6. The up-regulated genes encode permease, SAM-dependent methyltransferase, 5'-methylthioadenosine/S-adenosylhomocysteine nucleosidase, and aspartate kinase. Furthermore, chemotaxis plays a crucial role and the genes that were up-regulated include fliNY, fliN, fliM (Hypothetical protein), motB (Flagellar motor protein MotB), and motA (Flagellar motor protein MotA), under Planomicrobium strain AX6 compared to CK condition. However, it is not clear whether the up-regulation of these genes could protect cells against H2O2 stress. An overview of Planomicrobium strain AX6, when exposed to H2O2 concentration (1.5 mM) for 4 h, including antioxidant genes that avoid cell damage, was summarized in Table 2.

Overall, the findings of this study provide a clue to the biological roles and mechanism of the Planomicrobium strain AX6 in H2O2 scavenging. The above-mentioned antioxidant systems proposed that the bacterial strain could protect proteins from the toxicity produced during H2O2 stress. In addition to the above-annotated genes, numerous genes with unknown functions exist in the function of Planomicrobium strain AX6. In this study, several genes coding for antioxidant proteins, including glutathione peroxidase (GSH-Px), Coproporphyrinogen III oxidase, and superoxide dismutase (SOD), were induced in Planomicrobium strain AX6 in response to H2O2 when compared with the control. Taken as a whole, the findings propose that the induced transcripts responsible for antioxidant defense pathways serve as important regulatory mechanisms for scavenging H2O2 in Planomicrobium strain AX6. The DEGs presented in this study could provide a competitive advantage for the survival of Planomicrobium strain AX6 in H2O2-polluted environments.

Conclusion

In this study, Planomicrobium strain AX6 has been studied for its remarkable H2O2 scavenging potential. Based on RNA-seq data, it is evident that Planomicrobium strain AX6 could potentially lead to severe variations in the numerous metabolic pathways involved in generating an antioxidant defense system in response to H2O2 stress, consequently reducing the toxicity of the H2O2 stress. We found many slightly up-regulated DEGs encode proteins involved in antioxidant defense like GSH-Px, Coproporphyrinogen III oxidase, SOD, and other H2O2 scavenging-related metabolisms. To our surprise, in this study, CAT was relatively down-regulated, signifying that CAT might not play a key role in the scavenging of H2O2 in Planomicrobium strain AX6. Collectively, the data have provided several pathways and candidate genes for future functional genomics work. This study opens new research doors to explore bacterial H2O2 scavenging mechanisms and further expands our knowledge of the cold-desert bacteria coping mechanism under extreme environmental stresses.

Availability of data and materials

Raw sequence data from this study have been submitted to the NCBI sequence read archive under the BioProject accession [PRJNA807914] and are available at the following link: https://www.ncbi.nlm.nih.gov/sra/ PRJNA807914.

References

  1. Winterbourn CC, Kettle AJ, Hampton MB. Reactive Oxygen Species and Neutrophil Function. Annu Rev Biochem. 2016;85:765–92.

    Article  PubMed  CAS  Google Scholar 

  2. Imlay JA. The molecular mechanisms and physiological consequences of oxidative stress: lessons from a model bacterium. Nat Rev Microbiol. 2013;11(7):443–54.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Park S, Imlay JA. High levels of intracellular cysteine promote oxidative DNA damage by driving the fenton reaction. J Bacteriol. 2003;185(6):1942–50.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Kong S, Davison AJ. The Role of Interactions between 02, HzOz, *OH, e- and 0; in Free Radical Damage to Biological systems. Arch Biochem Biophys. 1980;204(1):18–29.

    Article  PubMed  CAS  Google Scholar 

  5. keyer K, Imlay JA. Superoxide accelerates DNA damage by elevating free-iron levels. Proc Natl Acad Sci USA. 1996;93:13635–40.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Faulkner MJ, Helmann JD. Peroxide stress elicits adaptive changes in bacterial metal ion homeostasis. Antioxid Redox Signal. 2011;15(1):175–89.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Mishra S, Imlay JA. An anaerobic bacterium, Bacteroides thetaiotaomicron, uses a consortium of enzymes to scavenge hydrogen peroxide. Mol Microbiol. 2013;90(6):1356–71.

    Article  PubMed  CAS  Google Scholar 

  8. Tong H, Dong Y, Wang X, Hu Q, Yang F, Yi M, Deng H, Dong X. Redox-Regulated adaptation of Streptococcus oligofermentans to hydrogen peroxide stress. mSystems. 2020;5(2):e00006-00020.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Henningham A, Dohrmann S, Nizet V, Cole JN. Mechanisms of group A Streptococcus resistance to reactive oxygen species. FEMS Microbiol Rev. 2015;39(4):488–508.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Horner-Devine MC, Carney KM, Bohannan BJ. An ecological perspective on bacterial biodiversity. Proc Biol sci. 2004;271(1535):113–22.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bérdy J. Bioactive microbial metabolites. J Antibiot. 2005;58(1):1–26.

    Article  Google Scholar 

  12. Sajjad W, Din G, Rafiq M, Iqbal A, Khan S, Zada S, Ali B, Kang S. Pigment production by cold-adapted bacteria and fungi: colorful tale of cryosphere with wide range applications. Extremophiles. 2020;24(4):447–73.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Zhang W, Bahadur A, Zhang G, Zhang B, Wu X, Chen T, Liu G. Diverse bacterial communities From Qaidam Basin of the Qinghai-Tibet Plateau: insights into variations in bacterial diversity across different regions. Front Microbiol. 2020;11.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Bahadur A, Zhang W, Sajjad W, Nasir F, Zhang G, Liu G, Chen T. Bacterial diversity patterns of desert dunes in the northeastern Qinghai-Tibet Plateau. China Arch Microbiol. 2021;203(6):2809–23.

    Article  PubMed  CAS  Google Scholar 

  15. Zhang H, Yohe T, Huang L, Entwistle S, Wu P, Yang Z, Busk PK, Xu Y, Yin Y. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2018;46(W1):W95–101.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Cabiscol E, Tamarit J, Ros J. Oxidative stress in bacteria and protein damage by reactive oxygen species. Int Microbiol. 2000;3:3–8.

    PubMed  CAS  Google Scholar 

  17. Maruyama A, Kumagai Y, Morikawa K, Taguchi K, Hayashi H, Ohta T. Oxidative-stress-inducible qorA encodes an NADPH-dependent quinone oxidoreductase catalysing a one-electron reduction in Staphylococcus aureus. Microbiol (Reading). 2003;149(Pt 2):389–98.

    Article  CAS  Google Scholar 

  18. Zhang B, Yang R, Zhang G, Liu Y, Zhang D, Zhang W, Chen T, Liu G. Characteristics of Planococcus antioxidans sp. nov., an antioxidant-producing strain isolated from the desert soil in the Qinghai-Tibetan Plateau. Microbiologyopen. 2020;9(6):1183–96.

    Article  PubMed  CAS  Google Scholar 

  19. Weber H, Engelmann S, Becher D, Hecker M. Oxidative stress triggers thiol oxidation in the glyceraldehyde-3-phosphate dehydrogenase of Staphylococcus aureus. Mol Microbiol. 2004;52(1):133–40.

    Article  PubMed  CAS  Google Scholar 

  20. Zheng M, Aslund F, Storz G. Activation of the OxyR transcription factor by reversible disulfide bond formation. Sci. 1998;279(13):1718–21.

    Article  CAS  Google Scholar 

  21. Luan H, Meng N, Fu J, Chen X, Xu X, Feng Q, Jiang H, Dai J, Yuan X, Lu Y, et al. Genome-wide transcriptome and antioxidant analyses on gamma-irradiated phases of deinococcus radiodurans R1. PLoS ONE. 2014;9(1): e85649.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Slade D, Radman M. Oxidative stress resistance in Deinococcus radiodurans. Microbiol Mol Biol Rev. 2011;75(1):133–91.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Jang S, Imlay JA. Micromolar intracellular hydrogen peroxide disrupts metabolism by damaging iron-sulfur enzymes. J Biol Chem. 2007;282(2):929–37.

    Article  PubMed  CAS  Google Scholar 

  24. Grifantini R, Toukoki C, Colaprico A, Gryllos I. Peroxide stimulon and role of PerR in group a streptococcus. J Bacteriol. 2011;193(23):6539–51.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Ozsolak F, Milos PM. RNA sequencing: advances, challenges and opportunities. Nat Rev Genet. 2011;12(2):87–98.

    Article  PubMed  CAS  Google Scholar 

  26. Raz T, Kapranov P, Lipson D, Letovsky S, Milos PM, Thompson JF. Protocol dependence of sequencing-based gene expression measurements. PLoS ONE. 2011;6(5): e19287.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Georgiou CD, Sun HJ, McKay CP, Grintzalis K, Papapostolou I, Zisimopoulos D, Panagiotidis K, Zhang G, Koutsopoulou E, Christidis GE, et al. Evidence for photochemical production of reactive oxygen species in desert soils. Nat Commun. 2015;6:7100.

    Article  PubMed  CAS  Google Scholar 

  28. Cassier-Chauvat C, Chauvat F. Genomics of the resistance to metal and oxidative stresses in cyanobacteria. JohnWiley & Sons: Inc Published; 2016.

    Book  Google Scholar 

  29. Lisher JP, Tsui HCT, Ramos-Montañez S, Hentchel KL, Martin JE, Trinidad JC, Winkler ME, Giedroc DP. Biological and chemical adaptation to endogenous hydrogen peroxide production in Streptococcus pneumoniae D39. mSphere. 2017;16:00291.

    Google Scholar 

  30. Imlay JA. Where in the world do bacteria experience oxidative stress? Environ Microbiol. 2019;21(2):521–30.

    Article  PubMed  CAS  Google Scholar 

  31. Yoon JH, Kang SS, Lee KC, Lee ES, Kho YH, Kanf KE, Park YH. Planomicrobium koreense gen. nov., sp. nov., a bacterium isolated from the Korean traditional fermented seafood jeotgal, and transfer of Planococcus okeanokoites (Nakagawa et al 1996) and Planococcus mcmeekinii (Junge et al. 1998) to the genus Planomicrobium. Int J Syst Evol Microbiol. 2001;51:1511–20.

    Article  PubMed  CAS  Google Scholar 

  32. Dai X, Wang YN, Wang BJ, Liu SJ, Zhou YG. Planomicrobium chinense sp. nov., isolated from coastal sediment, and transfer of Planococcus psychrophilus and Planococcus alkanoclasticus to Planomicrobium as Planomicrobium psychrophilum comb nov and Planomicrobium alkanoclasticum comb. nov. Int J Syst Evol Microbiol. 2005;55:699–702.

    Article  PubMed  CAS  Google Scholar 

  33. Engelhardt MA, Daly K, Swannell RPJ, Head IM. Isolation and characterization of a novel hydrocarbon-degrading, Gram-positive bacterium, isolated from intertidal sediment, and description of Planococcus alkanoclasticus sp. nov. J Appl Microbiol. 2001;90:237–47.

    Article  PubMed  CAS  Google Scholar 

  34. Zhang DC, Liu HC, Xin YH, YU Y, Zhou PJ, Zhou YG. Planomicrobium glaciei sp. nov., a psychrotolerant bacterium isolated from a glacier. Int J Syst Evol Microbiol. 2009;59:1387–90.

    Article  PubMed  CAS  Google Scholar 

  35. Wang W, Wang L, Shao Z. Diversity and abundance of Oil-Degrading bacteria and alkane hydroxylase (alkB) genes in the subtropical seawater of Xiamen Island. Microb Ecol. 2010;60:429–39.

    Article  PubMed  Google Scholar 

  36. Ting L, Wei Z, Ming-Hui W, Guang-Xiu L, Tuo C, Shi-Weng L. Physiological and biochemical characteristics of two antioxidant bacteria in desert soil. Microbiol China (Chinese). 2020;47(2):379–89. https://wswxtb.ijournals.cn/wswxtben/article/abstract/tb20020379?st=article_issue.

    Google Scholar 

  37. Paulino-Lima IG, Azua-Bustos A, Vicuna R, Gonzalez-Silva C, Salas L, Teixeira L, Rosado A, Leitao AA, Lage C. Isolation of UVC-tolerant bacteria from the hyperarid Atacama desert. Chile Microb Ecol. 2013;65(2):325–35.

    Article  PubMed  CAS  Google Scholar 

  38. Lim S, Jung JH, Blanchard L, de Groot A. Conservation and diversity of radiation and oxidative stress resistance mechanisms in Deinococcus species. FEMS Microbiol Rev. 2019;43(1):19–52.

    Article  PubMed  CAS  Google Scholar 

  39. Lee B-J, Kim J-S, Kang YM, Lim J-H, Kim Y-M, Lee M-S, Jeong M-H, Ahn C-B, Je J-Y. Antioxidant activity and γ-aminobutyric acid (GABA) content in sea tangle fermented by Lactobacillus brevis BJ20 isolated from traditional fermented foods. Food Chem. 2010;122(1):271–6.

    Article  CAS  Google Scholar 

  40. Wang YC, Yu RC, Chou CC. Antioxidative activities of soymilk fermented with lactic acid bacteria and bifidobacteria. Food Microbiol. 2006;23(2):128–35.

    Article  PubMed  Google Scholar 

  41. Das D, Goyal A. Antioxidant activity and γ-aminobutyric acid (GABA) producing ability of probiotic Lactobacillus plantarum DM5 isolated from Marcha of Sikkim. LWT - Food Sci Technol. 2015;61(1):263–8.

    Article  CAS  Google Scholar 

  42. Chen LL, Zhang W, Wang ZX, Xin J. Determination of superoxide dismutase activityin methanobactin-copper complexes by pyrogallol autoxidation. J Food Saf Qual. 2017;8(9):3438–44 (in Chinese).

    Google Scholar 

  43. Nakayama M, Nakajima-Kambe T, Katayama H, Higuchi K, Kawasaki Y, Fuji R. High catalase production by Rhizobium radiobacter strain 2–1. J Biosci Bioeng. 2008;106(6):554–8.

    Article  PubMed  CAS  Google Scholar 

  44. Cock PJ, Fields CJ, Goto N, Heuer ML, Rice PM. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res. 2010;38(6):1767–71.

    Article  PubMed  CAS  Google Scholar 

  45. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat biotechnol. 2010;28(5):511–5.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat biotechnol. 2013;31(1):46–53.

    Article  PubMed  CAS  Google Scholar 

  47. Reiner A, Yekutieli D, Benjamini Y. Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics. 2003;19(3):368–75.

    Article  PubMed  CAS  Google Scholar 

  48. Lu J, Peatman E, Tang H, Lewis J, Liu Z. Profiling of gene duplication patterns of sequenced teleost genomes: evidence for rapid lineage-specific genome expansion mediated by recent tandem duplications. BMC Genom. 2012;13:246.

    Article  CAS  Google Scholar 

  49. Aickin M, Gensler H. Adjusting for multiple testing when reporting research results: The Bonferroni vs Holm Methods. Am J Public Health. 1996;86(5):728.

    Article  Google Scholar 

  50. Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol. 2005;4:Article17.

    Article  PubMed  Google Scholar 

  51. MacMillan-Crow LA, Crow JP. Does more MnSOD mean more hydrogen peroxide? Anti-Cancer Agents Med Chem. 2011;11(2):178–80.

    Article  CAS  Google Scholar 

  52. Chen Y, Zhang G, Chen Z, Yang X, Chen B, Ma Y, Xie H, Luo Q, Yang J, Ye T, Yu D, Wang J, Tang H, Chen Z, Shi P. A warming climate may reduce health risks of hypoxia on the Qinghai-Tibet Plateau. Sci Bulletin. 2022;67:341–4.

    Article  Google Scholar 

  53. Mckay CP, Friedmann EI, Gómez-silva B, Cáceres-Villanueva L, Andersen DT, Landheim R. Temperature and moisture conditions for life in the extreme arid region of the Atacama desert: four years of observations including the El Niño of 1997–1998. Astrobiology. 2003;3(2):393–406.

    Article  PubMed  CAS  Google Scholar 

  54. Nimse SB, Pal D. Free radicals, natural antioxidants, and their reaction mechanisms. RSC Adv. 2015;5(35):27986–8006.

    Article  CAS  Google Scholar 

  55. Akbari E, Beheshti-Maal K, Nayeri H. Production and optimization of alkaline lipase by a novel psychrotolerant and halotolerant strain Planomicrobium okeanokoites ABN-IAUF-2 isolated from Persian Gulf. Int J Med Res Health Sci. 2016;5(4):139–48.

    Google Scholar 

  56. Luo X, Zhang J, Li D, Xin Y, Xin D, Fan L. Planomicrobium soli sp. nov., isolated from soil. Int J Syst Evol Microbiol. 2014;64(Pt 8):2700–5.

    Article  PubMed  CAS  Google Scholar 

  57. Zhang DC, Liu HC, Xin YH, Yu Y, Zhou PJ, Zhou YG. Planomicrobium glaciei sp. nov., a psychrotolerant bacterium isolated from a glacier. Int J Syst Evol Microbiol. 2009;59(Pt 6):1387–90.

    Article  PubMed  CAS  Google Scholar 

  58. Ramezani M, Nikou MM, Pourmohyadini M, Sproer C, Schumann P, Harirchi S, Aryaefar M, Fazeli SAS, Amoozegar MA, Ventosa A. Planomicrobium iranicum sp. nov., a novel slightly halophilic bacterium isolated from a hypersaline wetland. Int J Syst Evol Microbiol. 2019;69(5):1433–7.

    Article  PubMed  CAS  Google Scholar 

  59. Sarafin Y, Donio MB, Velmurugan S, Michaelbabu M, Citarasu T. Kocuria marina BS-15 a biosurfactant producing halophilic bacteria isolated from solar salt works in India. Saudi J Biol Sci. 2014;21(6):511–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Seaver LC, Imlay JA. Alkyl hydroperoxide reductase is the primary scavenger of endogenous hydrogen peroxide in Escherichia coli. J Bacteriol. 2001;183(24):7173–81.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Gonzalez-Flecha B, Demple B. Metabolic sources of hydrogen peroxide in aerobically growing Escherichia coli. J Biol Chem. 1995;270(9):13681–7.

    Article  PubMed  CAS  Google Scholar 

  62. Franco B, Padilla-Vaca F, Vargas-Maya NI, Herrera-Gutierrez LJ, Mora-Garduno JD, Tafoya-Ramirez MD, Paramo-Perez I, Anaya-Velazquez F, Mendoza-Macias CL. Development of an oxidative stress sensor in live bacteria using the optimized HyPer2 protein. Antonie Van Leeuwenhoek. 2019;112(2):167–77.

    Article  PubMed  CAS  Google Scholar 

  63. Wang H, Zhang Y, Bartlett DH, Xiao X. Transcriptomic analysis reveals common adaptation mechanisms under different stresses for moderately Piezophilic bacteria. Microb Ecol. 2021;81(3):617–29.

    Article  PubMed  CAS  Google Scholar 

  64. Agrawal S, Jaswal K, Shiver AL, Balecha H, Patra T, Chaba R. A genome-wide screen in Escherichia coli reveals that ubiquinone is a key antioxidant for metabolism of long-chain fatty acids. J Biol Chem. 2017;292(49):20086–99.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Zhou A, He Z, Redding-Johanson AM, Mukhopadhyay A, Hemme CL, Joachimiak MP, Luo F, et al. Hydrogen peroxide-induced oxidative stress responses in Desulfovibrio vulgaris Hildenborough. Environ Microbiol. 2010;12(10):2645–57.

  66. McCord JM, Fridovich I. Superoxide dismutase. J Biol Chem. 1969;244(22):6049–55.

    Article  PubMed  CAS  Google Scholar 

  67. Kuo CF, Mashino T, Fridovich I. a, B-Dihydroxyisovalerate Dehydratase: a superoxide-sensitive enzyme. J Biol Chem. 1987;262(10):4724–7.

    Article  PubMed  CAS  Google Scholar 

  68. Mao GD, Thomas PD, Lopaschuk GD, Poznansky MJ. Superoxide dismutase (SOD)-catalase conjugates. Role of hydrogen peroxide and the Fenton reaction in SOD toxicity. J Biol Chem. 1993;268(1):416–20.

    Article  PubMed  CAS  Google Scholar 

  69. Forman HJ, Zhang H, Rinna A. Glutathione: overview of its protective roles, measurement, and biosynthesis. Mol Aspects Med. 2009;30(1–2):1–12.

    Article  PubMed  CAS  Google Scholar 

  70. Strange RC, Spiteri MA, Ramachandran S, Fryer AA. Glutathione-S-transferase family of enzymes. Mutat Res. 2001;482:21–6.

    Article  PubMed  CAS  Google Scholar 

  71. Li LH, Shih YL, Huang JY, Wu CJ, Huang YW, Huang HH, Tsai YC, Yang TC. Protection from hydrogen peroxide stress relies mainly on AhpCF and KatA2 in Stenotrophomonas maltophilia. J Biomed Sci. 2020;27(1):37.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Asad NR, Asad LMBO, de Almeida CEB, Felzenszwalb I, Cabral-Neto JB, Leitão AC. Several pathways of hydrogen peroxide action that damage the E. coli genome. Genet Mol Biol. 2004;27(2):291–303.

    Article  CAS  Google Scholar 

  73. Rong JC, Ji BW, Zheng N, Sun ZZ, Li YS, Xie BB. Genomic insights into antioxidant activities of Pyruvatibacter mobilis CGMCC 1.15125(T), a pyruvate-requiring bacterium isolated from the marine microalgae culture. Mar Genomics. 2021;55:100791.

    Article  PubMed  CAS  Google Scholar 

  74. Crosa JH, Walsh CT. Genetics and assembly line enzymology of siderophore biosynthesis in bacteria. Microbiol Mol Biol Rev. 2002;66(2):223–49.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  75. Schwartz CJ, Djaman O, Imlay JA, Kiley PJ. The cysteine desulfurase, IscS, has a major role in in vivo Fe-S cluster formation in Escherichia coli. Proc Natl Acad Sci U S A. 2000;97(16):9009–14.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Gray MJ, Wholey WY, Jakob U. Bacterial responses to reactive chlorine species. Annu Rev Microbiol. 2013;67:141–60.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. Imlay JA. Transcription factors that defend bacteria against reactive oxygen species. Annu Rev Microbiol. 2015;69:93–108.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Kredich NM. The molecular basis for positive regulation of cys promoters in Salmonella typhimurium and Escherichia coli. Mol Microbiol. 1992;6(19):2747–53.

    Article  PubMed  CAS  Google Scholar 

  79. LaMonte BL, Hughes JA. In vivo hydrolysis of S-adenosylmethionine induces the met regulon of Escherichia coli. Microbiology (Reading). 2006;152(Pt 5):1451–9.

    Article  CAS  Google Scholar 

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Acknowledgements

We are thankful to the State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China and Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province, Lanzhou 730000, China.

Funding

This study was supported by the National Key R&D Program of China (2019YFE0121100), the National Science Foundation of China (31870479), the Scientific Project of Gansu Province (18JR2TA019, 20JR5RA548), and the CAS-President’s International Fellowship Initiative (PIFI) Postdoctoral Fellowship (2021PB0072).

Author information

Author notes

  1. Ali Bahadur and Ting Li contributed equally to this work.

Authors and Affiliations

  1. State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China

    Ali Bahadur, Wasim Sajjad, Minghui Wu & Tuo Chen

  2. Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province, Lanzhou, 730000, China

    Ali Bahadur, Gaosen Zhang, Guangxiu Liu & Wei Zhang

  3. School of Ecology and Environmental Science, Yunnan University, Kunming, 650091, China

    Ting Li

  4. Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences (CAS), Changchun, 130102, Jilin Province, China

    Fahad Nasir

  5. National Institute for Genomics and Advanced Biotechnology (NIGAB), National Agriculture Research Center (NARC), Islamabad, Pakistan

    Muhammad Amir Zia

  6. Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China

    Gaosen Zhang, Guangxiu Liu & Wei Zhang

  7. Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Lanzhou, 730000, Gansu Province, China

    Wei Zhang

Authors
  1. Ali Bahadur
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  2. Ting Li
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  3. Wasim Sajjad
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  4. Fahad Nasir
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  5. Muhammad Amir Zia
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  6. Minghui Wu
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  7. Gaosen Zhang
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  8. Guangxiu Liu
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  9. Tuo Chen
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  10. Wei Zhang
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Contributions

Ali Bahadur, Ting Li, and Wasim Sajjad: Writing- Original draft preparation, Conceptualization, Methodology, and Software. Ali Bahadur, Wei Zhang and Minghui Wu: Data curation. Guangxiu Liu and Gaosen Zhang: Visualization, Investigation. Tuo Chen, Wei Zhang: Supervision, Validation: Tuo Chen, Fahad Nasir, and Muhammad Amir Zia: Writing- Reviewing and Editing. The author(s) read and approved the final manuscript.

Corresponding author

Correspondence to Wei Zhang.

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Supplementary Information

Additional file 1: Table S1.

The ability of anti-oxidantstrains to remove various oxidants: differentconcentrations of hydrogen peroxide (0, 1.5, and 3 mM of H2O2).Planomicrobium-AX6 is an antioxidantstrain isolated from the Qaidam Basin; the model strain Escherichia coli was used as a negative control; Deinococcus radiodurans was used as apositive control. Table S2. Summary of the sequencing data of strain Planomicrobium-AX6. Table S3 Selected significantly differentially expressed genes (DEGs) for strainPlanomicrobium-AX6 when exposed for 4hr to H2O2 concentration (1.5 mM). Fig. S1. Response of Planomicrobium-AX6to H2O2 treatments. A:Survival rate. On the survival response of exponentially growing Planomicrobium-AX6 exposed to H2O2treatment. B: Challenge time. Atspecific time intervals, samples were diluted and plated on agar medium tomonitor cell viability. The data are means of triplicate points. Fig. S2. Clusters of Orthologous Groups (COG)classification of the Planomicrobium-AX6were annotated and grouped into 21 specific categories.

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Bahadur, A., Li, T., Sajjad, W. et al. Transcriptional and biochemical analyses of Planomicrobium strain AX6 from Qinghai-Tibetan Plateau, China, reveal hydrogen peroxide scavenging potential. BMC Microbiol 22, 265 (2022). https://doi.org/10.1186/s12866-022-02677-w

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Keywords

BMC Microbiology

ISSN: 1471-2180

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