Transcriptome analysis reveals a stress response of Shewanella oneidensis deprived of background levels of ionizing radiation

Hugo Castillo; Xiaoping Li; Faye Schilkey; Geoffrey B. Smith

doi:10.1371/journal.pone.0196472

Abstract

Natural ionizing background radiation has exerted a constant pressure on organisms since the first forms of life appeared on Earth, so that cells have developed molecular mechanisms to avoid or repair damages caused directly by radiation or indirectly by radiation-induced reactive oxygen species (ROS). In the present study, we investigated the transcriptional effect of depriving Shewanella oneidensis cultures of background levels of radiation by growing the cells in a mine 655 m underground, thus reducing the dose rate from 72.1 to 0.9 nGy h^-1 from control to treatment, respectively. RNASeq transcriptome analysis showed the differential expression of 4.6 and 7.6% of the S. oneidensis genome during early- and late-exponential phases of growth, respectively. The greatest change observed in the treatment was the downregulation of ribosomal proteins (21% of all annotated ribosomal protein genes during early- and 14% during late-exponential) and tRNA genes (14% of all annotated tRNA genes in early-exponential), indicating a marked decrease in protein translation. Other significant changes were the upregulation of membrane transporters, implying an increase in the traffic of substrates across the cell membrane, as well as the up and downregulation of genes related to respiration, which could be interpreted as a response to insufficient oxidants in the cells. In other reports, there is evidence in multiple species that some ROS not just lead to oxidative stress, but act as signaling molecules to control cellular metabolism at the transcriptional level. Consistent with these reports, several genes involved in the metabolism of carbon and biosynthesis of amino acids were also regulated, lending support to the idea of a wide metabolic response. Our results indicate that S. oneidensis is sensitive to the withdrawal of background levels of ionizing radiation and suggest that a transcriptional response is required to maintain homeostasis and retain normal growth.

Citation: Castillo H, Li X, Schilkey F, Smith GB (2018) Transcriptome analysis reveals a stress response of Shewanella oneidensis deprived of background levels of ionizing radiation. PLoS ONE 13(5): e0196472. https://doi.org/10.1371/journal.pone.0196472

Editor: Y-h. Taguchi, Chuo University, JAPAN

Received: November 28, 2017; Accepted: April 13, 2018; Published: May 16, 2018

Copyright: © 2018 Castillo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Gene expression data is contained within the paper and its Supporting Information files. The RNA libraries sequences are available from the NCBI SRA repository under the accession number PRJNA396034.

Funding: This work was supported by Department of Energy Office of Environmental Management, award #DE-EM0002423. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Natural ionizing radiation is a constant, pervasive environmental factor that plays a role in the biology of all organisms on Earth. Commonly referred to as “background radiation”, it is a collective term to describe cosmic, terrestrial, and internal sources of different forms of energy and electrically charged particles [1]. Also, background radiation varies widely geographically mainly due to the radioisotopes content of soil, rocks, and altitude [2]. As a result, all forms of radiation have different abilities to interact with matter, transferring energy and potentially causing the disruption of chemical bonds in a variety of molecules. In cells, the release of energy by an alpha or beta particle, or by a gamma ray results in the conformational change of biomolecules such as nucleic acids, lipids, and proteins, either by direct ionization events or through the formation of free radicals, also known as reactive oxygen species (ROS) [2, 3]. However, ever since their appearance on Earth approximately 3.5 billion years ago [4], cells have developed sensing and defense mechanisms in response to the insult of radiation, such as the production of antioxidants, the expression of ROS (Reactive oxygen species)-scavenging enzymes, and DNA repair systems [5]. In the light of these adaptive responses, it is fair to question if after millions of years of selective pressure by ionizing radiation, some of its products (ROS) have come to play an essential role in the biology of organisms. If so, the absence of background levels of radiation would elicit a specific stress response. In support of this hypothesis, there is growing evidence that some ROS, such as hydrogen peroxide and superoxide ions, act as regulatory components of biological processes such as growth, ROS homeostasis, antioxidant gene regulation, and DNA repair, among others [6–9]. Exposing cells to below-background doses of radiation might result in what can be construed as a stress response in different species, such as the inhibition of normal growth rate in Paramecium tetraurelia and Synechococcus lividus [10]; the decreased protection to radiomimetic agents in Saccharomyces cerevisiae [11]; a higher sensitivity to gamma rays and apoptosis in Cricetulus griseus V79 cells [12]; the lower cell density in Mus musculus L5178Y cells [13]; the regulation in the activity of stress-related enzymes in Cricetulus griseus V79 cells [14]; and the regulation of DNA repair and oxidative stress genes in Shewanella oneidensis and Deinococcus radiodurans [15–17]. Thus, the growing body of knowledge suggests that regardless of differences in cellular complexity and physiology, organisms exert a stress response to this peculiar radiation deprivation treatment. We report here the first transcriptome of an organism responding to the absence of natural levels of radiation and document this response in the bacterium S. oneidensis. Although our treatment simulates an artificial condition non-existent in any biologically-relevant place on Earth, it provides valuable data that suggest a role for ionizing radiation on the development of present-day bacteria.

Shewanella oneidensis is a facultative anaerobe, a Gram-negative bacterium, estimated to be 10 and 143 times more sensitive to ionizing radiation than E. coli and D. radiodurans, respectively [18]. Transcriptome analysis upon acute exposure to ionizing radiation [19], UVABC rays [20], and solar radiation [21] show the induction of systems aimed to combat oxidative stress, to protect the cells from protein damage, and to secrete radiation damage byproducts through multidrug and heavy metal efflux pumps, among others. Our transcriptome analysis of the removal of background levels of radiation from S. oneidensis shows a growth phase-dependent gene regulation response to this unusual environmental cue. During early exponential growth, a significant number of ribosomal proteins and tRNA-coding genes are downregulated in the below-background dosage group; while the late-exponential phase is characterized mainly by the upregulation of genes related to membrane transport, oxidative phosphorylation, and biosynthesis of amino acids, as well as the downregulation of genes involved in protein folding. These patterns of regulation indicate that S. oneidensis reacts to the absence of background levels of ionizing radiation in a way that resembles a response to different types of environmental stress, suggesting that cells have not only adapted to thrive in the presence of environmental radiation but have also developed a certain degree of “dependence” on it to maintain homeostasis.

Materials and methods

LBRE (Low Background Radiation Experiment) laboratory, radiation treatments and dosimetry

The LBRE (Low Background Radiation Experiment) laboratory is located at a depth of 655 m at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, NM, within the Salado formation (Fig 1A). Protection from cosmic rays and related particles by the rock overburden and the very low abundance of uranium-238, thorium-232, and pottasium-40 radioisotopes in halite, the most abundant mineral at this depth [22], naturally lowered background radiation by a factor of four [16]. Additionally, the incubators used for the LBRE experiments were further shielded by a 15 cm thick low-activity steel vault built from fallout-free pre-World War II materials. For the control incubator, we aimed for a gamma dose rate of 100 nGy h^-1 based on the U.S. Nuclear Regulatory Commission (NRC) estimate of natural background exposure being 347 nGy h^-1 [23], and a UK study reporting the proportion of natural background radiation that came from gamma exposure as 94.7 nGy h^-1 [24]. In order to simulate this dose rate, the inside surfaces of the control incubator were lined with 11.5 kg of KCl (equivalent to 185 kBq of potassium-40) uniformly distributed in plastic containers (Fig 1A and 1C). Radiation dosimetry using a NaI detector and Monte-Carlo N-Particle (MCNP) analysis estimated the dose rate to be 0.16 and 71.3 nGy h^-1 in the treatment and control incubators, respectively (for more details, see [16]). Radon concentration inside the vault was measured with a SafetySiren™ Pro Series 3 detector at 15.6 ± 4 Bq m³, in agreement with measurements made by the EXO (http://www-project.slac.stanford.edu/exo), a particle physics experiment also hosted at WIPP (Andrea Pocar, personal communication). Using a range of values from 7 to 31 Bq m³ as input for MCNP estimates in our 5.2 × 10⁴ cm³ incubators, radon concentration ranged from 1 to 4 pGy h^-1. This contribution was included in our estimated total dose rate of 0.16 nGy h^-1 (excluding sources in the growth media) in the treatment incubator, as previously reported [17]. Considering the potassium-40 in the 1.5 mL of growth medium used (0.5 nGy h^-1 per mL) this gives a dose rate of 0.91 and 72.05 nGy h^-1 in the treatment and control, respectively. For more details, see [16].

Download:

Fig 1. Shielding from background radiation at the LBRE laboratory at the Waste Isolation Pilot Plant.

(A) The LBRE laboratory, (hosted by the Waste Isolation Pilot Plant (WIPP), a nuclear waste repository near Carlsbad, NM.), is located in the middle of the 600 m-thick Salado formation. (B) Laboratories underground at WIPP are conex shipping containers modified to accommodate office and laboratory equipment. The LBRE steel vault used in this study is under the orange fire blanket (arrow) to provide insulation from the high temperature in the drift. Inside the vault there are two incubators, one of which has 11.5 kg of KCl as a source of ~185 kBq of potassium-40 to ‘add-back” natural levels of radiation and act as our experimental control. Potassium is also present in the media in both incubators adding a dose rate of about 0.5 nGy mL^-1 h^-1 to both the treatment and control. (D) Sampling (Geoffrey Smith) from the plus KCl control incubator (70 nGy h^-1) inside the vault made from pre-World War II steel.

https://doi.org/10.1371/journal.pone.0196472.g001

Bacterial growth conditions

For each of three biological replicates, seed cultures of S. oneidensis MR-1 (ATCC 700550) were grown at the WIPP surface laboratory from a single colony in 2 mL of pH 7.0 TGY broth (5 g tryptone, 3 g yeast extract, and 1 g glucose, per L) under constant agitation (150 rpm) during 72 hours. An aliquot of 20 μL of this culture was used to inoculate 2 mL of broth to start an overnight culture under the same culturing conditions. The overnight culture was then transported at room temperature to the underground laboratory and diluted to approximately 3×10⁷ cells per mL to initiate the experiment. Initially, 1.5 mL of cell suspension were transferred into the top row of the 24-well plate and grown in the below-background (treatment) and background (control) incubators at 200 rpm during 24 hours at 30°C. After this initial growth period, a sample pooled from the first 4 wells was then diluted 1:50 and 1.5 mL aliquots were transferred to the second row of the plate to re-initiate their growth under their respective conditions.

Growth measurement and sampling

The growth dynamics of the cultures was followed by measuring optical density at 630 nm on an ELX800 microplate reader (Biotek, Winooski, VT, USA) at 5, 8, 13, 17, and 24 hours. In parallel, 300 μL of culture from duplicate wells were transferred into 600 μL of RNAprotect solution (QIAGEN, Valencia, CA, USA) for RNA stabilization and storage, processed according to the manufacturer’s instructions, and stored at -20°C.

RNA extraction, libraries preparation and sequencing

Total RNA was extracted from RNA-protected samples using the RNAeasy QIAGEN kit (QIAGEN, Valencia, CA, USA) following the enzymatic lysis and proteinase K digestion protocol, as instructed by the manufacturer’s instructions and including an additional treatment with DNAse I (QIAGEN, Valencia, CA, USA) to remove traces of genomic DNA. Total RNA concentration was measured using the RNA Qubit assay (Invitrogen, Burlington, ON, Canada) and RNA integrity was evaluated using the Bioanalyzer RNA pico Assay (Agilent Technologies, Santa Clara, CA, USA) following the manufacturer’s protocol. Depletion of the rRNA was performed using the RiboZero kit (Bacteria) and the rRNA-depleted samples were purified using the RNAClean XP kit (Beckam Coulter, Beverly, MA, USA). Libraries were constructed using the ScriptSeq Complete kit for bacteria from (Epicentre, Madison, WI, USA). In brief, rRNA-depleted RNA fragmentation and the addition of the cDNA synthesis primer were performed by incubation in the fragmentation buffer at 85°C for 5 minutes, followed by the synthesis of the cDNA and the 3’-terminal tagging of the cDNA. Prior to PCR amplification, the cDNA was purified using the Agencourt AMPure XP system (Beckman Coulter, Beverly, MA, USA). The second strand cDNA was generated by adding the Illumina adapters as the forward primer and a ScriptSeq index primer as the reverse primer to allow multiplexing during sequencing. The resulting RNASeq libraries were purified using the AMPure XP system (Beckman Coulter, Beverly, MA, USA), quantified with the DNA Qubit assay, and their quality evaluated using the Bioanalyzer High Sensitivity DNA assay (Agilent Technologies, Santa Clara, CA, USA) to confirm the adequate distribution of fragments length. Fifty bp single reads were generated using the Illumina HiSeq 2000 platform at the National Center for Genome Research in Santa Fe, NM.

Bioinformatic analysis

The reads were mapped against the S. oneidensis reference genome (NC_004347 and NC_004349) using EDGE-pro v1.3.1 (Estimated degree of gene expression in prokaryotic genomes) software [25]. In brief, the FASTA (*.fna), protein table (*.ptt), and rRNA/tRNA genes coordinates (*.rnt) files corresponding to the chromosome (NC_004347) and megaplasmid (NC_004349) units of S. oneidensis were concatenated prior to the alignment. The alignment on EDGE-pro was run using the default parameters. The differential gene expression analysis was performed with edgeR (version 1) using as input the count table generated by EDGE-pro. Only genes with a fold change ≥ 2 and an FDR-value ≤ 0.10 were considered significant for the purpose of this study. The reads from both 5 and 13 h libraries were deposited in the NCBI SRA depository under the accession number PRJNA396034. The significantly up- and down-regulated genes were analyzed for gene ontology (GO) term enrichment (p value ≤ 0.05), separately, using GOToolBox (http://genome.crg.es/GOToolBox/), and the significantly enriched terms further explored on the REVIGO web application [26] to identify and visualize relationships among the GO terms.

RT-qPCR

The validity of the differential expression was tested using RT-qPCR for direct comparison with RNASeq. Prior to RT-PCR, cDNA was synthesized with the iScript™ Reverse Transcription Supermix for RT-qPCR (BioRad, Hercules, CA, USA) using total RNA as template and a reaction incubation program of priming at 25°C for 5 min, reverse transcription at 46°C for 20 min, and RT inactivation at 95°C for 1 min. The qPCR reactions (10 uL) were performed in triplicate using the SsoAdvanced Universal SYBR Green Supermix (BioRad, Hercules, CA, USA), 0.5 μM of each primer (Table 1), and 1 ng of cDNA as template. The PCR program was as follows: Polymerase activation and DNA denaturation step of 30 s at 98°C, followed by 40 cycles of denaturation at 98°C for 15 s and primer annealing/extension at 60°C for 30 s. After amplification, a melting curve analysis of 60 cycles from 65 to 95°C at a rate of 0.5°C per cycle was included to assess the specificity of the amplification. The relative expression of the target genes was calculated using gyrA and gyrB as reference genes and using the efficiency-corrected model [27]. For each comparison, 9 to 12 C_t values from three biological replicates were used for all calculations.

Download:

Table 1. Primers used for the validation of the transcriptome analysis on early and late-exponential S. oneidensis cultures.

https://doi.org/10.1371/journal.pone.0196472.t001

Results and discussion

In the present study we evaluated the response of S. oneidensis to the deprivation of background radiation during early- and late-exponential growth phases. Liquid cultures of S. oneidensis did not show significant differences in optical density between the two treatments over the course of the experiment, as previously reported [17]. However, because it has been previously observed that cell density as an endpoint to measure the effect of our treatment lacks the resolution needed to detect such a subtle change in environmental growth conditions, we performed RNASeq-based transcriptome analysis to explore the genome-wide response in our experiment. For this purpose, a total of 12 Illumina libraries (6 early- and 6 late-exponential) were sequenced as 50 bp reads. Principal components analysis identified one of the late-exponential control libraries as an outlier (S1 Fig). When we examined the kinetics of the growth of one of the cultures that were used in this PCA data point, it was found that the culture in question had prematurely entered stationary phase, and so from these two analyses, it was decided to exclude this library from downstream processing (S1 Fig).

On average, the libraries had between 14,735,800 and 16,791,556 million reads, of which 83.96 to 95.5% were uniquely mapped to the S. oneidensis reference genome (NC004347, NC004349; Table 2). Only genes with a p-adj≤ 0.1 and a log₂ ratio ≥ 2 were deemed significant and used for posterior analyses (S1 Table and Table 3). Using background and below-background libraries as control and treatment, respectively, we identified a total of 194 and 320 regulated genes as a result of shielding cells from background radiation during early and late stationary phase, respectively. These numbers represent the 4.6% and 7.6% of the total genes in the S. oneidensis genome, within the range of other studies with the same species that report regulations of 1.5% [28], 14% [21], and 21% [29] under different types of stress. The number of downregulated genes decreased from 120 during early- to 105 during late-stationary, whereas the number of upregulated genes increased from 74 during early- to 215 during late-stationary (Fig 2). The validity of our transcriptome analysis is shown by the significant correlation (R² = 0.93) of a subset of genes amplified with RT-qPCR and compared to the expression levels obtained with RNASeq (Fig 3).

Download:

Fig 2. Gene regulation summary.

Only genes with an FDR value ≤ 0.1 and a log₂ differential expression ≥ 2 were considered significantly regulated.

https://doi.org/10.1371/journal.pone.0196472.g002

Download:

Fig 3. Transcriptome qPCR validation.

Correlation of RNASeq and qPCR relative expression of selected genes for early (A) and late-exponential (B) transcriptomes used for transcriptome validation. Relative expression with qPCR was normalized with gyrA and gyrB as reference genes using the amplification efficiency-corrected model by Pfaffl et al. [27].

https://doi.org/10.1371/journal.pone.0196472.g003

Download:

Table 2. RNA libraries’ statistics.

https://doi.org/10.1371/journal.pone.0196472.t002

Download:

Table 3. Selected differentially expressed genes during early and late-exponential phases of S. oneidensis cultures.

Only genes with an FDR value ≤ 0.1 and a log₂ differential expression ≥ 2 are shown.

https://doi.org/10.1371/journal.pone.0196472.t003

Gene ontology (GO) term enrichment analysis

GO term enrichment was performed to group the differentially regulated genes according to their function. In the radiation-shielded treatment, both growth phases were characterized by the dominant downregulation of the processes: translation (GO:0006412), protein metabolism (GO:0019538), and gene expression (GO:0010467). Similarly, the GO terms nitrogen metabolic process (GO:0006807) and transport (GO:0006810) were upregulated during both phases; SOS response (GO:0009432) was upregulated during early-exponential and both cellular glucan metabolic process (GO:0006073) and energy reserve metabolic process (GO:0006112) during late-exponential phase (Fig 4). Metabolically, the terms structural constituent of the ribosome (GO:0003735) and structural molecule activity (GO:0005198) were significantly downregulated in both phases (Fig 5). Comparatively, the terms active transmembrane transporter activity (GO:0022804) and transporter activity (GO:0005215) were upregulated during both phases, while ATPase activity (GO:0016887) was upregulated during early-exponential and electron carrier activity (GO:0009055) and antioxidant activity (GO:0016209) were upregulated during late-exponential (Fig 5).

Download:

Fig 4. Biological process GO terms enrichment analysis in response to below-background radiation in S. oneidensis.

GO terms redundancy in down and upregulated genes was reduced and summarized using REVIGO [26]. Scatterplots show the non-redundant, down and upregulated GO terms enriched during early (A, B) and late (C, D) exponential phases. Only GO terms with a log10 p value ≤ -1.5 are labeled and the bubble size indicates the frequency of the GO term.

https://doi.org/10.1371/journal.pone.0196472.g004

Download:

Fig 5. Metabolic function GO terms enrichment analysis in response to below-background radiation in S. oneidensis.

GO terms redundancy in down and upregulated genes was reduced and summarized using REVIGO [26]. Scatterplots show the non-redundant, down and upregulated GO terms enriched during early (A, B) and late (C, D) exponential phases. Only GO terms with a log10 p value ≤ -1.7 are labeled and the bubble size indicates the frequency of the GO term.

https://doi.org/10.1371/journal.pone.0196472.g005

Ribosomal proteins, tRNAs and translation factors

The expression pattern in our experiments shows that the deprivation of background levels of radiation caused a marked downregulation of a significant number of ribosomal protein-coding genes during both early- (21% of all annotated ribosomal proteins) and late-exponential (14%) phase cultures (Fig 6A). These data suggest that an important initial response to radiation deprivation is to slow protein synthesis by reducing the number of translationally active ribosomes. Ribosomal proteins play a wide variety of roles in ribosomes, and so a decrease in their expression levels has the potential to disrupt optimal translational activity as well. For example, proteins L15 (rplO), L16 (rplP) and L20 (rplT) contribute to the stability of the ribosomes [30]); S1 (rpsA) participates in the peptide chain elongation [31]; S3 (rpsC) and S5 (rpsE) assist unwinding the mRNA secondary structure as it enters the A site [32]; L1 (rplA) releases the deacylated tRNA from the E site allowing the re-occupation of the A site [33]; L7/L12 (rplL) are in involved in the binding of the elongation factor by activating its GTPase activity [34] and L11 (rplK) senses the presence of uncharged tRNA’s in the A-site, triggering the stringent response [35], among others.

Download:

Fig 6.

Overview of the downregulation of S. oneidensis (A) ribosomal proteins during early- and late-exponential, and (B) tRNA genes during early-exponential phases. Adapted from the KEGG ribosomal proteins pathway, panel A shows the downregulation of each ribosomal protein in either early (upper left corner), late-exponential (upper right corner) or both phases.

https://doi.org/10.1371/journal.pone.0196472.g006

As ribosomes account for up to 40% of the Escherichia coli cell’s dry weight [36] and protein synthesis accounts for up to 50% of the cellular energy [37], ribosome synthesis and protein translation are two critical processes that are tightly regulated to meet the protein synthesis rate required under specific growth conditions [38]. The downregulation of ribosomal proteins in Shewanella has been associated with numerous stressors: Acidic stress [39], heat shock [40], exposure to a magnetic field [28], and chromate stress [29]. Ribosomal protein downregulation has been reported as well in other microbial genera in response to stress: in Campylobacter jejuni under elevated growth temperature [41]; in Streptococcus pneumoniae treated with antimicrobial peptides [42]; in Staphylococcus aureus under acid shock [43], in Corynebacterium glutamicum under suboptimal oxygen conditions [44], and in Saccharomyces cerevisiae exposed to the alkylating agent methyl methanesulfonate [45].

Other components of the translational machinery that were downregulated are genes coding for tRNAs. During early log phase, thirty seven tRNA genes were downregulated, none were upregulated. These genes are involved in the synthesis of twelve types of aminoacyl-tRNAs, with all (3 of 3 for Ile) or most (3 of 4 for Tyr, 4 of 5 for Ala, 5 of 6 for Glu) of the isotypes downregulated (Fig 6B). It has been reported that the tRNA-gene copy number determines the number of tRNAs involved in translation [46] and, interestingly, both conditions of oxidative stress and stringent response in E. coli elicit a similar downregulation of these genes [47, 48]. Additionally, fis, a growth phase-dependent regulator involved in the regulation of tRNA levels [49, 50] was also downregulated, as previously observed in S. oneidensis under acid/alkaline conditions [39].

Our experiment also revealed the regulation of other translation-related genes during both early- and late-exponential phases (Table 3). During early-exponential, we observed the upregulation of yaeJ, a peptidyl-tRNA hydrolyzing factor known to relieve stalled ribosomes [51, 52], and the downregulation of efp, a translation elongation factor responsible for the formation of the peptide bond between the first and second amino acids during translation. Later on during late-exponential phase, the reduced expression of tufA (elongation factor Tu), raiA (ribosome-associated inhibitor A), yfiA (ribosome-associated cold-shock response protein) and rluD (23S rRNA pseudouridine synthase) suggest an important reduction in ribosomal stability as a result of a lower concentration of EF-Tu to bind the aminoacyl-tRNAs to the ribosome [53, 54], a weaker stabilization of the 70S ribosome against dissociation [55], and the decreased rigidity of the 23S rRNA as a consequence of the lower expression of pseudouridine [56]. The consistent downregulation of ribosomal proteins and tRNAs, as well as the effects involving protein synthesis, all indicate a “pause” in translation, and we interpret this as a response which allows for a remobilization of amino acid and protein resources in order to re-establish homeostasis in response to the stress of reduced radiation. Similarly, the molecular chaperones groES, groEL, and dnaK were downregulated during late-exponential phase, adding to our hypothesis that reduced background radiation lowers the immediate need for active proteins. Although this downregulation opposes the “traditional” response of cells under stress, it has been previously observed in S. oneidensis [39] and in E. coli [57] under acidic stress and heat shock under microgravity conditions, respectively.

Amino acids biosynthesis and metabolism

Our transcriptome analysis showed the early-exponential upregulation of genes involved in the flux of several amino acids, such as the biosynthesis of arginine (argA, amino acid acetyltransferase; argB, acetylglutamate kinase; argH, argininosuccinate lyase), histidine (hisG, phosphoribosyltransferase), lysine (lysC, lysine-sensitive aspartokinase III), phenylalanine, tyrosine, and tryptophan (aroF, phosphor-s-dehydro-deoxyheptonate aldolase tyr-sensitive) and the metabolism of cysteine and methionine (metE, B12-independent 5-methyltetrahydropteroyltriglutamate-homocysteine methyltransferase), alanine, asparagine, and glutamate (asnB, asparagine synthase glutamine-hydrolyzing), glycine, serine, and threonine (garK, glycerate kinase), glycine, serine, threonine, cysteine, and methionine (lysC, lysine-sensitive aspartokinase III), and histidine (hisG, ATP phosphorybosiltransferase). Also, the downregulation of the leucine-responsive regulatory protein (lrp) and the transcriptional repressor of branched chain amino acid degradation (liuR) suggest the modulation of the metabolism of one-carbon compounds, amino acids, and sugars, and the assimilation of nitrogen [58] and a lower branched chain amino acids catabolism [59], respectively. Hence, another tactic taken by Shewanella, probably related to the above-mentioned remobilization of proteins, is the adjustment of the biosynthesis and degradation of numerous amino acids.

Membrane transport and cell to cell communication

Multi-drug resistance (MDR) pumps, essential for antibiotic resistance within a clinical context, also have natural roles in detoxification processes and in the maintenance of cellular homeostasis [60–62]. Notably, we identified the upregulation of ABC and other transporters-related genes that increased from 17 during early- to 30 during late-exponential phase (Table 3). Although most of these genes are involved in the efflux of macrolides and drugs (SO1918, emrD, rmrB, SO4527, SO3691, macC, SO3694, SO3692, SO1917), some are related to the uptake of Fe (nicT, SO2523), alpha ketoglutarate (SO0455), potassium (ktrA, ktrB), vitamin B12 (btuC), putrescine (potI), amino acids (SO0056), molybdate (modB), and hemin (hmuC). Similar induction of efflux pump genes has been observed in S. oneidensis under acidic [39] and chromate [29] stresses, and in response to UVA [20] and in S. algae under salt stress [63].

The passive movement of hydrophilic molecules through porins exerts a major control of the uptake nutrients, and potentially, signaling molecules. It has been reported that the cAMP-activated global transcriptional regulator CRP positively regulates the expression of the ompA gene, that codes for the structural component of porins in E. coli [64] and for ompW and omp35 in S. oneidensis [65]. In our experiment, both crp and ompA genes were downregulated during late-exponential phase, along with ompW, whose product participates in the uptake of cations in Caulobacter crescentus [66], supporting our hypothesis that cell signaling is diminished upon deprivation of background levels of radiation.

Respiration

Shewanella oneidensis is a facultative anaerobic bacterium capable of using a wide variety of terminal electron acceptors; its genome encodes 44 c-type cytochromes [67], and most of them function as terminal reductases [68]. The number of respiration-related processes that were regulated in our experiments increased from 16 during early- to 41 during the late-exponential phase, indicating a shift in the potential use of terminal electron acceptors as the cultures approached stationary phase in the radiation-deprived condition. At the beginning of growth, the upregulation of genes involved in oxidative phosphorylation (ctaG, SO3058, coxA) indicates an increase in electron-transporting activity and the hydrolysis of ATP (SO3885), along with the downregulation of subunits for the synthesis of a cytochrome c-oxidase (ccoQ), an ATPase (atpC), a periplasmic monoheme cytochrome C (scyA), and a succinate dehydrogenase (sdhB) responsible for the reduction of ubiquinone to ubiquinol. Towards the end of exponential growth, the upregulation of coxA is maintained, accompanied by the downregulation of two subunits for the cbb3-type cytochrome c-oxidase (ccoQ, ccoP), one subunit of the cytochrome bd complex (cydA), and three components of the cytochrome c maturation (Ccm) system (ccmC, ccmD, ccmE), responsible for the catalytic activity of cytochromes [69].

Our analysis also revealed the upregulation of a significant number of genes related to the use of nitrate, sulfate, TMAO, and thiosulfate as terminal electron acceptors (Fig 7). For instance, the two subunits of the nitrate reductase system (napA, napB) were upregulated throughout the experiment, suggesting the reduction of nitrate [61]. Probably related to this is the downregulation of cymA, which codes for a protein that transfers electrons to NapA, inhibiting the process of nitrate respiration [70]. During late-exponential additional respiratory systems were upregulated; for example, the reduction of trimethylamine oxide (torC, torF), sulfite (sirA, sirE, sirF, sirG, sirC, sirD, sirI, nosY, nosL), thiosulfate (SO0714, SO0717, SO4142), Cr(IV)/U(IV) (SO4483), and Fe/Mn oxides (SO2931). In contrast, all the components of the Mtr pathway (mtrA, mtrB, mtrC, omcA) were downregulated, suggesting a diminished ability to use membrane extension nanowire connections to use iron oxides as electron acceptors [71].

Download:

Fig 7. Overview of electron transport proteins genes regulated in S. oneidensis during late-exponential phase.

https://doi.org/10.1371/journal.pone.0196472.g007

We suggest that this significant investment by Shewanella in increasing respiratory options and electron transport branches may be an effort on the part of the cells to compensate for the lower availability of oxidant species under the below-background radiation condition. Reactive oxygen species such as hydrogen peroxide have been shown to perform important roles in cell-cell communication [3] and gene regulation [6]. Without natural background levels of radiation, it is likely that less of these oxidants would be produced and the cell may compensate for this by increasing the generation of endogenous oxidants through alternative membrane electron transport processes.

Chaperones and folding catalysts

Molecular chaperones, chaperonins, and heat shock proteins assist in the folding newlyformed proteins, re-folding denatured proteins into their active conformation, and prevent unfolded proteins from aggregating into non-functional states [72]. In our study, the genes coding for the major chaperone/chaperonin systems (groES, groEL, dnaJ, dnaK) and other protein folding catalysts (clpB, htpG, secB and ibpA) were downregulated during late-exponential phase. Such unusual pattern of downregulation of these genes has been previously observed in S. oneidensis under acidic stress [39].

Conclusion

The present study shows the first genome-wide bacterial response, of any organism, to the extremely low levels of background and below-background radiation. In agreement with our previous work [17], the growth of S. oneidensis was not inhibited by radiation shielding. However, the regulation of different gene families, most remarkably those involved in protein translation activity, suggests that S. oneidensis cells “sensed” a change in their physical environment and responded to it by regulating their translation rate. We have also previously observed the upregulation of genes associated with oxidative stress response and DNA damage repair that suggest a stress response [16, 17]. This time, unconstrained by the limitations of targeting specific genes, we identified the regulation of a wider variety of genes involved in different metabolic processes, suggesting that exposure to some minimum amount of ionizing radiation might be required by S. oneidensis to retain homeostasis. Our hypothesis is in apparent contradiction to recently published modeling studies that suggest the improbability that the dose rates for our study could exert any effect on our cells to significantly alter their physiology [73, 74]. However, the paradigm shift we present is that the genome-wide gene regulation response in our model is precisely due to a lower intracellular radiolysis products concentration because of a reduced hit rate by radiation tracks. As we mentioned before, some ROS are catalysts for transcriptional regulation [7], therefore background-shielded cells might experience a slower transcription rate compared to their counterpart grown in the presence of background radiation. Our data suggests a decreased ability of cells to exchange substrates across the membrane, including diffusible components that might act as signaling factors. Comparatively, the bystander effect explains a population-wide effect even when only a fraction of the cells has been hit by a radiation track, precisely due to the transmission of chemical signals [75]. Interestingly, a small number of genes (twenty) regulated upon deprivation of background levels of radiation coincided with those regulated in our model when challenged with acute doses of either UV, solar (SR) or ionizing radiation (IR). For instance, katB expression was also induced by 558 J m^-2 [21] and 40 Gy [19] of solar and ionizing radiation, respectively, and umuC and umuD were also upregulated by IR and 25, 568 and 3.3 J m^-2 of UVABC [20]. The expression of these genes under such disparate conditions supports our proposal of below background radiation as a source of stress for Shewanella cells. In comparison, we have observed D. radiodurans growth inhibition while it only upregulated two of the five genes regulated in S. oneidensis which could be interpreted as its inability to perceive the lack of radiation as an important environmental cue [17]. Consistent with this proposal, there was a genome-wide transcriptome level response in Shewanella but the transcriptome response of Deinococcus appears much diminished (Castillo et al., in preparation), lending credence to the proposed connection between the inability to detect stress and the inability to take measures to preserve homeostasis.

Since the removal of normal levels of background radiation causes stress in bacteria (this and previous reports, [16, 17]), protozoa [10, 13], yeast [11], and mammalian cells [12–14], natural levels of radiation have, evidently, an important fitness role in biology. The identity of such a fitness role of low-level radiation and the associated mechanisms, however, are still largely unknown and will be an important research component in understanding the biological effects of low-dose radiation.

Supporting information

S1 Fig. Principal components analysis (PCA) showing RNA libraries distribution.

Control and treatment libraries refer to S. oneidensis cultures grown at background and below-background doses of radiation, respectively.

https://doi.org/10.1371/journal.pone.0196472.s001

(TIF)

S1 Table. Regulated genes in S. oneidensis grown deprived from background radiation.

Only genes with a FDR < 0.1 and log₂ >1 or <-1 are shown.

https://doi.org/10.1371/journal.pone.0196472.s002

(DOCX)

Acknowledgments

The authors would like to particularly acknowledge Dr. James Conca, Senior Scientist at UFA Ventures, Inc., for his vision and pioneering work in helping lead the establishment of the low radiation biology project at WIPP. Additionally, we acknowledge the help in calculating the internal dose rate contribution from K-40 in the media from Drs. Antonella Tabocchini and Giuseppi Esposito (Istituto Superiore di Sanita, Rome Italy).

References

1. McLaughlin JP (2015) Some characteristics and effects of natural radiation. Radiat Prot Dosimetry 167: 2–7. pmid:25904693
- View Article
- PubMed/NCBI
- Google Scholar
2. Thorne MC (2003) Background radiation: natural and man-made. J Radiol Prot 23: 29–42. pmid:12729417
- View Article
- PubMed/NCBI
- Google Scholar
3. Riley PA (1994) Free radicals in biology: Oxidative stress and the effects of ionizing radiation. Int J Radiat Biol 65: 27–33. pmid:7905906
- View Article
- PubMed/NCBI
- Google Scholar
4. Forman HJ, Maiorino M, Ursini F (2010) Signaling functions of reactive oxygen species. Biochemistry 49: 835–842. pmid:20050630
- View Article
- PubMed/NCBI
- Google Scholar
5. Djokic t Van Kranendonk MJ, Campbell KA, Walter MR, Ward CR (2017) Earliest signs of life on land preserved in ca. 3.5 Ga hot springs deposit. Nat Commun 9(8):15263.
- View Article
- Google Scholar
6. Imlay JA (2013) The molecular mechanisms and physiological consequences of oxidative stress: lessons from a model bacterium. Nat Rev Microbiol 11: 443–454. pmid:23712352
- View Article
- PubMed/NCBI
- Google Scholar
7. D’Autreaux B and Toledano MB (2007) ROS as signaling molecules: mechanisms that generate specificity in ROS homeostasis. Nat Rev 8:813–824.
- View Article
- Google Scholar
8. Murphy MP, Holmgren A, Larsson NG, Halliwell B, Chang KJ, Kalyanaraman B, et al. (2011) Unravelling the biological roles of reactive oxygen species. Cell Metab 13: 361–366. pmid:21459321
- View Article
- PubMed/NCBI
- Google Scholar
9. Ray PD, Huang BW, Tsuji Y (2012) Reactive oxygen species (ROS) homeostasis and redox regulation in cellular signaling. Cell Signal 24: 981–990. pmid:22286106
- View Article
- PubMed/NCBI
- Google Scholar
10. Planel H, Soleilhavoup JP, Tizador R, Richoilley G, Conter A, Croute F, et al. (1987) Influence on cell proliferation of background radiation or exposure to very low, chronic γ radiation Health Phys. 52: 571–578. pmid:3106264
- View Article
- PubMed/NCBI
- Google Scholar
11. Satta L, Augusti-Tocco G, Ceccarelli R, Esposito A, Fiore M, Paggi P, et al. (1995) Low environmental radiation background impairs biological defense of the yeast Saccharomyces cerevisiae to chemical radiomimetic agents. Mutat Res 347: 129–133. pmid:7565903
- View Article
- PubMed/NCBI
- Google Scholar
12. Satta L, Antonelli F, Belli M, Sapora O, Simone G, Sorrentino E, et al. (2002) Influence of a low background radiation environment on biochemical and biological responses in V79 cells. Radiat Environ Biophys 41: 217–224. pmid:12373331
- View Article
- PubMed/NCBI
- Google Scholar
13. Kawanishi M, Okuyama K, Shiraishi K, Matsuda Y, Taniguchi R, Shiomi N, et al. (2012) Growth retardation of paramecium and mouse cells by shielding them from background radiation. J Radiat Res 53: 404–410. pmid:22739010
- View Article
- PubMed/NCBI
- Google Scholar
14. Fratini E, Carbone C, Capece D, Esposito G, Simone G, Tabocchini MA, et al. (2015) Low-radiation environment affects the development of protection mechanisms in V79 cells. Radiat Environ Biophys 54: 183–194. pmid:25636513
- View Article
- PubMed/NCBI
- Google Scholar
15. Smith GB, Grof Y, Navarrette A, Guilmette RA (2011) Exploring biological effects of low level radiation from the other side of background. Health Phys 100: 263–265. pmid:21595063
- View Article
- PubMed/NCBI
- Google Scholar
16. Castillo H, Schoderbek D, Dulal S, Escobar G, Wood J, Nelson R, Smith G (2015) Stress induction in the bacteria Shewanella oneidensis and Deinococcus radiodurans in response to below-background radiation. Int J Radiat Biol 91: 749–756. pmid:26073528
- View Article
- PubMed/NCBI
- Google Scholar
17. Castillo H, Smith G (2017) Below background ionizing radiation as an environmental cue for bacteria. Front Microbiol 8: 1–7.
- View Article
- Google Scholar
18. Ghosal D, Omelchenko MV, Gaidamakova EK, Matrosova VY,Vasilenko A, Venkateswaran A, Zhai M, Kostandarithes HM,Brim H, Makarova KS, et al. (2005) How radiation kills cells: Survival of Deinococcus radiodurans and Shewanella oneidensis under oxidative stress. FEMS Microbiol Rev 29: 361–375. pmid:15808748
- View Article
- PubMed/NCBI
- Google Scholar
19. Qiu X, Daly MJ, Vasilenko A, Omelchenko MV, Gaidamakova EK, Wu J, et al.(2006) Transcriptome analysis applied to survival of Shewanella oneidensis MR-1 exposed to ionizing radiation. J Bacteriol 188: 1199–1204. pmid:16428429
- View Article
- PubMed/NCBI
- Google Scholar
20. Qiu X, Sundin GW, Wu L, Zhou J, and Tiedje JM (2005) Comparative analysis of differentially expressed genes in Shewanella oneidensis MR-1 following exposure to UVC, UVB and UVA radiation. J Bacteriol 187: 3556–3564. pmid:15866945
- View Article
- PubMed/NCBI
- Google Scholar
21. Qiu X, Tiedje JM, Sundin GW (2005) Genome-wide examination of the natural solar radiation response in Shewanella oneidensis MR-1. Photochem Photobiol 81: 1559–1568. pmid:16022560
- View Article
- PubMed/NCBI
- Google Scholar
22. Esch E- I, Bowles TJ, Hime A, Pichlmaier A, Reifarth R, Wollnik H (2005) The cosmic ray muon flux at WIPP. Nucl Instrum Methods Phys A 538: 516–252
- View Article
- Google Scholar
23. National Council on Radiation Protection report No. 93: Radiation exposure of the population of the United States (1987). Bethesda, Md: National Council on Radiation Protection and Measurements.
24. Kendall GM, Little MP, Wakeford R, Bunch KJ, Miles JCH, Vincent TJ, et al. (2014) A record-based case-control study of natural background radiation and the incidence of childhood leukaemia and other cancers in Great Britain during 1980–2006. Leukemia 27(1): 3–9.
- View Article
- Google Scholar
25. Magoc T., Wood D., and Salzberg SL (2011) EDGE-pro: Estimated degree of gene expression in prokaryotic genomes. Evol Bioinform online 9: 127–136.
- View Article
- Google Scholar
26. Supek F, Bošnjak M, Škunca N, Šmuc T (2011) REVIGO summarizes and visualized long lists of gene ontology terms. PLoS ONE 6(7): e21800. pmid:21789182
- View Article
- PubMed/NCBI
- Google Scholar
27. Pfaffl MW, Horgan GW, Dempfle L (2002) Relative expression software tool REST for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res 30: 1–10.
- View Article
- Google Scholar
28. Gao W, Liu Y, Zhou J, Pan H (2005) Effects of a strong magnetic field on bacterium Shewanella oneidensis: An assessment by using whole genome microarray. Bioelectromagnetics 26: 558–563. pmid:16037957
- View Article
- PubMed/NCBI
- Google Scholar
29. Brown SD, Thompson MR, VerBerkmoes NC, Chourey K, Shah M, Zhou J, et al. (2006). Molecular dynamics of the Shewanella oneidensis response to chromate stress. Mol cell Proteomics 5: 1054–1071. pmid:16524964
- View Article
- PubMed/NCBI
- Google Scholar
30. Nierhaus KH (1991) The assembly of prokaryotic ribosomes. Biochimie 73(6): 739–755. pmid:1764520
- View Article
- PubMed/NCBI
- Google Scholar
31. Sorensen MA, Fricke J, Pedersen S (1998) Ribosomal protein S1 is required for translation of most, if not all, natural mRNAs in Escherichia coli in vivo. J Mole Biol 280: 561–569.
- View Article
- Google Scholar
32. Takyar S, Hickerson RP, Noller HF (2005) mRNA helicase activity of the ribosome. Cell 120: 49–58. pmid:15652481
- View Article
- PubMed/NCBI
- Google Scholar
33. Agrawal RK, Penczek P, Grassuci RA, Frank J (1998) Visualization of tRNA movements on the Escherichia coli 70S ribosome during the elongation cycle. J Cell Biol 150: 447–460.
- View Article
- Google Scholar
34. Hamel E, Koka M, Nakamoto T (1972) Requirement of an Escherichia coli 50 S ribosomal protein component for effective interaction of the ribosome with T and G factors and with guanosine triphosphate. J Biol Chem 217: 805–814
- View Article
- Google Scholar
35. Wendrich TM, Blaha G, Wilson DN, Marahiel MA, Nierhaus KH (2002) Dissection of the mechanism for the stringent factor RelA. Mol Cell 10: 779–788. pmid:12419222
- View Article
- PubMed/NCBI
- Google Scholar
36. Nomura M, Gourse R, Baughman G (1984) Regulation of the synthesis of ribosomes and ribosomal components. Ann rev Biochem 53: 75–117. pmid:6206783
- View Article
- PubMed/NCBI
- Google Scholar
37. Russell JB, Cook GM (1995) Energetics of bacterial growth: Balance of anabolic and catabolic reactions. Microbiol Rev 59: 48–62. pmid:7708012
- View Article
- PubMed/NCBI
- Google Scholar
38. Bosdriesz E, Molennar D, Teusink B, Bruggeman FJ (2015) How fast-growing bacteria robustly tune their ribosome concentration to approximate growth-rate maximization. FEBS J 282: 2029–2044. pmid:25754869
- View Article
- PubMed/NCBI
- Google Scholar
39. Leaphart AB, Thompson DK, Huang K, Alm E, Wan XF, Arkin A, et al. (2006) Transcriptome profiling of Shewanella oneidensis gene expression following exposure to acidic and alkaline pH. J Bacteriol 188: 1633–1642. pmid:16452448
- View Article
- PubMed/NCBI
- Google Scholar
40. Gao H, Wang Y, Liu X, Yan T, Wu L, Alm E, Arkin A, Thompson DK, Zhou J (2004) Global transcriptome analysis of the heat shock response of Shewanella oneidensis. J Bacteriol 186: 7796–7803. pmid:15516594
- View Article
- PubMed/NCBI
- Google Scholar
41. Stintzi A (2003) Gene expression profile of Campylobacter jejuni in response to growth at temperature variation. J Bacteriol 185: 2009–2016. pmid:12618466
- View Article
- PubMed/NCBI
- Google Scholar
42. Le CF, Gudimella R, Razali R, Manikamm R, Sekaran SD (2016) Transcriptome analysis of Streptococcus pneumoniae treated with the designed antimicrobial peptides, DM3. Sci Rep 6:26828. pmid:27225022
- View Article
- PubMed/NCBI
- Google Scholar
43. Bore E, Langsrud S, Langsrud O, Rode TM, Holck A (2007) Acid-shock responses in Staphylococcus aureus investigated by global gene expression analysis. Microbiol 153: 2289–2303.
- View Article
- Google Scholar
44. Sun Y, Guo W, Wang F, Peng F, Yang Y, Dai X, Liu X, Bai Z (2016) Transcriptome and multivariate data analysis of Corynebacterium glutamicum under different dissolved oxygen conditions in bioreactors. PLoS One 11(12): e0167156. pmid:27907077
- View Article
- PubMed/NCBI
- Google Scholar
45. Jelinsky SA, Samson LD (1999) Global response of Saccharomyces cerevisiae to an alkylating agent. Proc Natl Acad Sci USA 96: 1486–1491. pmid:9990050
- View Article
- PubMed/NCBI
- Google Scholar
46. Gorgoni B, Ciandrini L, McFarland MR, Romano MC, Stansfield I (2016) Identification of the mRNA targets of tRNA-specific regulation using genome-wide simulation of translation. Nucleic Acids Res 44: 9231–9244. pmid:27407108
- View Article
- PubMed/NCBI
- Google Scholar
47. Zhong J, Xiao C, Gu W, Sun X, He A-Y, Zhang G (2015) Transfer RNAs mediate the rapid adaptation of Escherichia coli to oxidative stress. PLoS Genet 11(6): e1005302. pmid:26090660
- View Article
- PubMed/NCBI
- Google Scholar
48. Durfee T, Hansen A- M, Zhi H, Blattner FR, Jin DJ (2008) Transcription profiling of the stringent response in Escherichia coli. J Bacteriol 190: 1084–1096. pmid:18039766
- View Article
- PubMed/NCBI
- Google Scholar
49. Nilsson L, Verbeek H, Vijgenboom E, van Drunen C, Vanet A, Bosh L (1991) FIS-dependent trans activation of stable RNA operons of Escherichia coli under various growth conditions. J Bacteriol 174: 921–929,
- View Article
- Google Scholar
50. Nilsson L, Emilsson V (1994) Factor for inversion stimulation-dependent growth rate regulation of individual tRNA species in Escherichia coli. J Biol Chem 269: 9460–9465. pmid:7511587
- View Article
- PubMed/NCBI
- Google Scholar
51. Handa Y, Inaho N, Nameki N. YaeJ is a novel ribosome-associated protein in Escherichia coli that can hydrolyze peptidyl-tRNA on stalled ribosomes (2010) Nucleic Acid Res 39: 1739–1748. pmid:21051357
- View Article
- PubMed/NCBI
- Google Scholar
52. Chadani Y, Ito K, Kutsukake K, Abo T (2012) Arfa recruits release factor 2 to rescue stalled ribosomes by peptidyl-tRNA hydrolysis in Escherichia coli. Mol Microbiol 86(1): 37–50. pmid:22857598
- View Article
- PubMed/NCBI
- Google Scholar
53. Van der Meide PH, Vijgenboom E, Talens A, Bosh L (1983) The Role of EF-Tu in the expression of tufA and tufB genes. Eur J Biochem 130: 397–407. pmid:6337847
- View Article
- PubMed/NCBI
- Google Scholar
54. Aoki H, Xu J, Emili A, Chosay JG, Golshani A, Ganoza MC. Interactions of elongation factor EF-P with the Escherichia coli ribosome. FEBS J. 2008;275:671–681 pmid:18201202
- View Article
- PubMed/NCBI
- Google Scholar
55. Agafonov DE, Kold VA, Spirin AS (2001) Ribosome-associated protein that inhibits translation at the aminoacyl-tRNA binding state. EMBO Rep. 2: 399–402. pmid:11375931
- View Article
- PubMed/NCBI
- Google Scholar
56. Cabello-Villegas J, Nikonowickz EP (2005) Solution structure of Ψ₃₂-modified anticodon stem-loop of Escherichia coli tRNA^Phe. Nucleic Acids Res 33: 6961–6971. pmid:16377777
- View Article
- PubMed/NCBI
- Google Scholar
57. Kim HW, Rhee MS. (2016) Influence of low-shear modeled microgravity on heat resistance, membrane fatty acid composition, and heat stress-related gene expression in Escherichia coli O157:H7 ATCC 35150, ATCC 43889, ATCC 43890, and ATCC 43895. Appl Environ Microbiol 82: 2893–2901. pmid:26944847
- View Article
- PubMed/NCBI
- Google Scholar
58. Newman EB, Lin R (1995) Leucine-responsive regulatory protein: A global regulator of gene expression in E. coli. Annu Rev Microbiol 49: 747–775. pmid:8561478
- View Article
- PubMed/NCBI
- Google Scholar
59. Kasakov AE, Rodionov DA, Alm E, Arkin AP, Dubchak I, Gelfand MS (2009) Comparative genomics of regulation of fatty acid and branched-chain amino acid utilization in proteobacteria. J Bacteriol 191: 52–64. pmid:18820024
- View Article
- PubMed/NCBI
- Google Scholar
60. Ahmed M, Lyass L, Markham PN, Taylo SrS, Vazquez-Laslop N, Neufakh AA (1995) Two highly similar multidrug transporters of Bacillus subtilis whose expression is differentially regulated. J Bacteriol 177: 3904–3910. pmid:7608059
- View Article
- PubMed/NCBI
- Google Scholar
61. Lewinson O, Bibi E (2001) Evidence of simultaneous binding of dissimilar substrates by the Escherichia coli multidrug transporter MdfA. Biochemistry 40(42): 12612–12618. pmid:11601985
- View Article
- PubMed/NCBI
- Google Scholar
62. Lee SJ, Gralla JD (2004) Osmo-regulation of bacterial transcription via poised RNA polymerase. Mol Cell 14: 153–162. pmid:15099515
- View Article
- PubMed/NCBI
- Google Scholar
63. Fu X, Wang D, Yin X, Du P, Kan B (2014) Time course transcriptome changes in Shewanella algae in response to salt stress. PLoS ONE 9(5): e96001. pmid:24789066
- View Article
- PubMed/NCBI
- Google Scholar
64. Gibert I, Barbe J (1990) Cyclic AMP stimulates transcription of the structural gene of the outer-membrane protein OmpA of Escherichia coli. FEMS Microbiol Lett. 68(3): 307–311.
- View Article
- Google Scholar
65. Novichkov PS, Kazakov AE, Ravcheev DA, Leyn SA, Kovaleva GY, Kazanoc MD, et al. (2013) RegPrecise 3.0 –A resource for genome-scale exploration of transcriptional regulation in bacteria. BMC Genomics 14: 745. pmid:24175918
- View Article
- PubMed/NCBI
- Google Scholar
66. Benz R, Jones MD, Younas F, Maier E, Modi N, Mentele R, et al. (2015) OmpW of Caulobacter crescentus functions as an outer membrane channel for cations. PLoS ONE 10(11):e0143227.
- View Article
- Google Scholar
67. Heidelberg JF, Paulsen IT, Nelson KE, Gaidos Ej, Nelson WC, et al. (2002) Genome sequence of the dissimilatory metal ion-reducing bacterium Shewanella oneidensis. Nat Biotechnol 20: 1118–1123. pmid:12368813
- View Article
- PubMed/NCBI
- Google Scholar
68. Jin M, Jiang Y, Sun L, Yin J, Fu H, et al. (2013) Unique organizational and functional features of the cytochrome c maturation system in Shewanella oneidensis. PLoS ONE 8(9): e75610. pmid:24040415
- View Article
- PubMed/NCBI
- Google Scholar
69. Gao H, Barua S, Liang Y, Wu L, Dong Y, et al. (2010) Impacts of Shewanella oneidensis c-type cytochromes on aerobic and anaerobic respiration. Microb Biotechnol 3(4): 455–466. pmid:21255343
- View Article
- PubMed/NCBI
- Google Scholar
70. Marritt SJ, Lowe TG, Bye J, McMillan GG, Shi L, Fredrickson J, et al. (2012) A functional description of CymA, an electron-transfer hub supporting anaerobic respiratory flexibility in Shewanella. Biochem J 444: 465–474. pmid:22458729
- View Article
- PubMed/NCBI
- Google Scholar
71. Pirbadian S., Barchinger SE, Leung KM, Byun HS, Jangir Y, Bouchenni RA, Reed SB, Romine MF, Saffarini DA, Shi L, Gorby YA, Golbeck JH, EL-Nagar MY (2014) Shewanella oneidensis MR-1 nanowires are outer membrane and periplasmic extensions of the extracellular electron transport components. Proc Natl Acad Sci USA 111: 12883–12888. pmid:25143589
- View Article
- PubMed/NCBI
- Google Scholar
72. Hartl FU (1996) Molecular chaperones in celular protein folding. Nature 381: 571–580. pmid:8637592
- View Article
- PubMed/NCBI
- Google Scholar
73. Smith JT, Willey NJ, Hancock JT (2012) Low dose ionizing radiation produces too few reactive oxygen species to directly affect antioxidant concentrations in cells. Biol Lett 8: 594–597. pmid:22496076
- View Article
- PubMed/NCBI
- Google Scholar
74. Lampe N, Biron DG, Brown JMC, Incerti S, Marin P, Maigne L, et al. (2016) Simulating the impact of the natural radiation background on bacterial systems: Implications for very low radiation biological experiments. PLoS ONE 11(11):e0166364. pmid:27851794
- View Article
- PubMed/NCBI
- Google Scholar
75. Azzam EI, de Toledo SM, Little JB (2001) Direct evidence for the participation of gap junction-mediated intercellular communication in the transmission of damage signals from α-particle irradiated to nonirradiated cells. Proc Natl Acad Sci U S A 98(2): 473–478 pmid:11149936
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. McLaughlin JP (2015) Some characteristics and effects of natural radiation. Radiat Prot Dosimetry 167: 2–7. pmid:25904693
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Thorne MC (2003) Background radiation: natural and man-made. J Radiol Prot 23: 29–42. pmid:12729417
View Article
PubMed/NCBI
Google Scholar

[6] View Article

[7] PubMed/NCBI

[8] Google Scholar

[ref3] 3. Riley PA (1994) Free radicals in biology: Oxidative stress and the effects of ionizing radiation. Int J Radiat Biol 65: 27–33. pmid:7905906
View Article
PubMed/NCBI
Google Scholar

[10] View Article

[11] PubMed/NCBI

[12] Google Scholar

[ref4] 4. Forman HJ, Maiorino M, Ursini F (2010) Signaling functions of reactive oxygen species. Biochemistry 49: 835–842. pmid:20050630
View Article
PubMed/NCBI
Google Scholar

[14] View Article

[15] PubMed/NCBI

[16] Google Scholar

[ref5] 5. Djokic t Van Kranendonk MJ, Campbell KA, Walter MR, Ward CR (2017) Earliest signs of life on land preserved in ca. 3.5 Ga hot springs deposit. Nat Commun 9(8):15263.
View Article
Google Scholar

[18] View Article

[19] Google Scholar

[ref6] 6. Imlay JA (2013) The molecular mechanisms and physiological consequences of oxidative stress: lessons from a model bacterium. Nat Rev Microbiol 11: 443–454. pmid:23712352
View Article
PubMed/NCBI
Google Scholar

[21] View Article

[22] PubMed/NCBI

[23] Google Scholar

[ref7] 7. D’Autreaux B and Toledano MB (2007) ROS as signaling molecules: mechanisms that generate specificity in ROS homeostasis. Nat Rev 8:813–824.
View Article
Google Scholar

[25] View Article

[26] Google Scholar

[ref8] 8. Murphy MP, Holmgren A, Larsson NG, Halliwell B, Chang KJ, Kalyanaraman B, et al. (2011) Unravelling the biological roles of reactive oxygen species. Cell Metab 13: 361–366. pmid:21459321
View Article
PubMed/NCBI
Google Scholar

[28] View Article

[29] PubMed/NCBI

[30] Google Scholar

[ref9] 9. Ray PD, Huang BW, Tsuji Y (2012) Reactive oxygen species (ROS) homeostasis and redox regulation in cellular signaling. Cell Signal 24: 981–990. pmid:22286106
View Article
PubMed/NCBI
Google Scholar

[32] View Article

[33] PubMed/NCBI

[34] Google Scholar

[ref10] 10. Planel H, Soleilhavoup JP, Tizador R, Richoilley G, Conter A, Croute F, et al. (1987) Influence on cell proliferation of background radiation or exposure to very low, chronic γ radiation Health Phys. 52: 571–578. pmid:3106264
View Article
PubMed/NCBI
Google Scholar

[36] View Article

[37] PubMed/NCBI

[38] Google Scholar

[ref11] 11. Satta L, Augusti-Tocco G, Ceccarelli R, Esposito A, Fiore M, Paggi P, et al. (1995) Low environmental radiation background impairs biological defense of the yeast Saccharomyces cerevisiae to chemical radiomimetic agents. Mutat Res 347: 129–133. pmid:7565903
View Article
PubMed/NCBI
Google Scholar

[40] View Article

[41] PubMed/NCBI

[42] Google Scholar

[ref12] 12. Satta L, Antonelli F, Belli M, Sapora O, Simone G, Sorrentino E, et al. (2002) Influence of a low background radiation environment on biochemical and biological responses in V79 cells. Radiat Environ Biophys 41: 217–224. pmid:12373331
View Article
PubMed/NCBI
Google Scholar

[44] View Article

[45] PubMed/NCBI

[46] Google Scholar

[ref13] 13. Kawanishi M, Okuyama K, Shiraishi K, Matsuda Y, Taniguchi R, Shiomi N, et al. (2012) Growth retardation of paramecium and mouse cells by shielding them from background radiation. J Radiat Res 53: 404–410. pmid:22739010
View Article
PubMed/NCBI
Google Scholar

[48] View Article

[49] PubMed/NCBI

[50] Google Scholar

[ref14] 14. Fratini E, Carbone C, Capece D, Esposito G, Simone G, Tabocchini MA, et al. (2015) Low-radiation environment affects the development of protection mechanisms in V79 cells. Radiat Environ Biophys 54: 183–194. pmid:25636513
View Article
PubMed/NCBI
Google Scholar

[52] View Article

[53] PubMed/NCBI

[54] Google Scholar

[ref15] 15. Smith GB, Grof Y, Navarrette A, Guilmette RA (2011) Exploring biological effects of low level radiation from the other side of background. Health Phys 100: 263–265. pmid:21595063
View Article
PubMed/NCBI
Google Scholar

[56] View Article

[57] PubMed/NCBI

[58] Google Scholar

[ref16] 16. Castillo H, Schoderbek D, Dulal S, Escobar G, Wood J, Nelson R, Smith G (2015) Stress induction in the bacteria Shewanella oneidensis and Deinococcus radiodurans in response to below-background radiation. Int J Radiat Biol 91: 749–756. pmid:26073528
View Article
PubMed/NCBI
Google Scholar

[60] View Article

[61] PubMed/NCBI

[62] Google Scholar

[ref17] 17. Castillo H, Smith G (2017) Below background ionizing radiation as an environmental cue for bacteria. Front Microbiol 8: 1–7.
View Article
Google Scholar

[64] View Article

[65] Google Scholar

[ref18] 18. Ghosal D, Omelchenko MV, Gaidamakova EK, Matrosova VY,Vasilenko A, Venkateswaran A, Zhai M, Kostandarithes HM,Brim H, Makarova KS, et al. (2005) How radiation kills cells: Survival of Deinococcus radiodurans and Shewanella oneidensis under oxidative stress. FEMS Microbiol Rev 29: 361–375. pmid:15808748
View Article
PubMed/NCBI
Google Scholar

[67] View Article

[68] PubMed/NCBI

[69] Google Scholar

[ref19] 19. Qiu X, Daly MJ, Vasilenko A, Omelchenko MV, Gaidamakova EK, Wu J, et al.(2006) Transcriptome analysis applied to survival of Shewanella oneidensis MR-1 exposed to ionizing radiation. J Bacteriol 188: 1199–1204. pmid:16428429
View Article
PubMed/NCBI
Google Scholar

[71] View Article

[72] PubMed/NCBI

[73] Google Scholar

[ref20] 20. Qiu X, Sundin GW, Wu L, Zhou J, and Tiedje JM (2005) Comparative analysis of differentially expressed genes in Shewanella oneidensis MR-1 following exposure to UVC, UVB and UVA radiation. J Bacteriol 187: 3556–3564. pmid:15866945
View Article
PubMed/NCBI
Google Scholar

[75] View Article

[76] PubMed/NCBI

[77] Google Scholar

[ref21] 21. Qiu X, Tiedje JM, Sundin GW (2005) Genome-wide examination of the natural solar radiation response in Shewanella oneidensis MR-1. Photochem Photobiol 81: 1559–1568. pmid:16022560
View Article
PubMed/NCBI
Google Scholar

[79] View Article

[80] PubMed/NCBI

[81] Google Scholar

[ref22] 22. Esch E- I, Bowles TJ, Hime A, Pichlmaier A, Reifarth R, Wollnik H (2005) The cosmic ray muon flux at WIPP. Nucl Instrum Methods Phys A 538: 516–252
View Article
Google Scholar

[83] View Article

[84] Google Scholar

[ref23] 23. National Council on Radiation Protection report No. 93: Radiation exposure of the population of the United States (1987). Bethesda, Md: National Council on Radiation Protection and Measurements.

[ref24] 24. Kendall GM, Little MP, Wakeford R, Bunch KJ, Miles JCH, Vincent TJ, et al. (2014) A record-based case-control study of natural background radiation and the incidence of childhood leukaemia and other cancers in Great Britain during 1980–2006. Leukemia 27(1): 3–9.
View Article
Google Scholar

[87] View Article

[88] Google Scholar

[ref25] 25. Magoc T., Wood D., and Salzberg SL (2011) EDGE-pro: Estimated degree of gene expression in prokaryotic genomes. Evol Bioinform online 9: 127–136.
View Article
Google Scholar

[90] View Article

[91] Google Scholar

[ref26] 26. Supek F, Bošnjak M, Škunca N, Šmuc T (2011) REVIGO summarizes and visualized long lists of gene ontology terms. PLoS ONE 6(7): e21800. pmid:21789182
View Article
PubMed/NCBI
Google Scholar

[93] View Article

[94] PubMed/NCBI

[95] Google Scholar

[ref27] 27. Pfaffl MW, Horgan GW, Dempfle L (2002) Relative expression software tool REST for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res 30: 1–10.
View Article
Google Scholar

[97] View Article

[98] Google Scholar

[ref28] 28. Gao W, Liu Y, Zhou J, Pan H (2005) Effects of a strong magnetic field on bacterium Shewanella oneidensis: An assessment by using whole genome microarray. Bioelectromagnetics 26: 558–563. pmid:16037957
View Article
PubMed/NCBI
Google Scholar

[100] View Article

[101] PubMed/NCBI

[102] Google Scholar

[ref29] 29. Brown SD, Thompson MR, VerBerkmoes NC, Chourey K, Shah M, Zhou J, et al. (2006). Molecular dynamics of the Shewanella oneidensis response to chromate stress. Mol cell Proteomics 5: 1054–1071. pmid:16524964
View Article
PubMed/NCBI
Google Scholar

[104] View Article

[105] PubMed/NCBI

[106] Google Scholar

[ref30] 30. Nierhaus KH (1991) The assembly of prokaryotic ribosomes. Biochimie 73(6): 739–755. pmid:1764520
View Article
PubMed/NCBI
Google Scholar

[108] View Article

[109] PubMed/NCBI

[110] Google Scholar

[ref31] 31. Sorensen MA, Fricke J, Pedersen S (1998) Ribosomal protein S1 is required for translation of most, if not all, natural mRNAs in Escherichia coli in vivo. J Mole Biol 280: 561–569.
View Article
Google Scholar

[112] View Article

[113] Google Scholar

[ref32] 32. Takyar S, Hickerson RP, Noller HF (2005) mRNA helicase activity of the ribosome. Cell 120: 49–58. pmid:15652481
View Article
PubMed/NCBI
Google Scholar

[115] View Article

[116] PubMed/NCBI

[117] Google Scholar

[ref33] 33. Agrawal RK, Penczek P, Grassuci RA, Frank J (1998) Visualization of tRNA movements on the Escherichia coli 70S ribosome during the elongation cycle. J Cell Biol 150: 447–460.
View Article
Google Scholar

[119] View Article

[120] Google Scholar

[ref34] 34. Hamel E, Koka M, Nakamoto T (1972) Requirement of an Escherichia coli 50 S ribosomal protein component for effective interaction of the ribosome with T and G factors and with guanosine triphosphate. J Biol Chem 217: 805–814
View Article
Google Scholar

[122] View Article

[123] Google Scholar

[ref35] 35. Wendrich TM, Blaha G, Wilson DN, Marahiel MA, Nierhaus KH (2002) Dissection of the mechanism for the stringent factor RelA. Mol Cell 10: 779–788. pmid:12419222
View Article
PubMed/NCBI
Google Scholar

[125] View Article

[126] PubMed/NCBI

[127] Google Scholar

[ref36] 36. Nomura M, Gourse R, Baughman G (1984) Regulation of the synthesis of ribosomes and ribosomal components. Ann rev Biochem 53: 75–117. pmid:6206783
View Article
PubMed/NCBI
Google Scholar

[129] View Article

[130] PubMed/NCBI

[131] Google Scholar

[ref37] 37. Russell JB, Cook GM (1995) Energetics of bacterial growth: Balance of anabolic and catabolic reactions. Microbiol Rev 59: 48–62. pmid:7708012
View Article
PubMed/NCBI
Google Scholar

[133] View Article

[134] PubMed/NCBI

[135] Google Scholar

[ref38] 38. Bosdriesz E, Molennar D, Teusink B, Bruggeman FJ (2015) How fast-growing bacteria robustly tune their ribosome concentration to approximate growth-rate maximization. FEBS J 282: 2029–2044. pmid:25754869
View Article
PubMed/NCBI
Google Scholar

[137] View Article

[138] PubMed/NCBI

[139] Google Scholar

[ref39] 39. Leaphart AB, Thompson DK, Huang K, Alm E, Wan XF, Arkin A, et al. (2006) Transcriptome profiling of Shewanella oneidensis gene expression following exposure to acidic and alkaline pH. J Bacteriol 188: 1633–1642. pmid:16452448
View Article
PubMed/NCBI
Google Scholar

[141] View Article

[142] PubMed/NCBI

[143] Google Scholar

[ref40] 40. Gao H, Wang Y, Liu X, Yan T, Wu L, Alm E, Arkin A, Thompson DK, Zhou J (2004) Global transcriptome analysis of the heat shock response of Shewanella oneidensis. J Bacteriol 186: 7796–7803. pmid:15516594
View Article
PubMed/NCBI
Google Scholar

[145] View Article

[146] PubMed/NCBI

[147] Google Scholar

[ref41] 41. Stintzi A (2003) Gene expression profile of Campylobacter jejuni in response to growth at temperature variation. J Bacteriol 185: 2009–2016. pmid:12618466
View Article
PubMed/NCBI
Google Scholar

[149] View Article

[150] PubMed/NCBI

[151] Google Scholar

[ref42] 42. Le CF, Gudimella R, Razali R, Manikamm R, Sekaran SD (2016) Transcriptome analysis of Streptococcus pneumoniae treated with the designed antimicrobial peptides, DM3. Sci Rep 6:26828. pmid:27225022
View Article
PubMed/NCBI
Google Scholar

[153] View Article

[154] PubMed/NCBI

[155] Google Scholar

[ref43] 43. Bore E, Langsrud S, Langsrud O, Rode TM, Holck A (2007) Acid-shock responses in Staphylococcus aureus investigated by global gene expression analysis. Microbiol 153: 2289–2303.
View Article
Google Scholar

[157] View Article

[158] Google Scholar

[ref44] 44. Sun Y, Guo W, Wang F, Peng F, Yang Y, Dai X, Liu X, Bai Z (2016) Transcriptome and multivariate data analysis of Corynebacterium glutamicum under different dissolved oxygen conditions in bioreactors. PLoS One 11(12): e0167156. pmid:27907077
View Article
PubMed/NCBI
Google Scholar

[160] View Article

[161] PubMed/NCBI

[162] Google Scholar

[ref45] 45. Jelinsky SA, Samson LD (1999) Global response of Saccharomyces cerevisiae to an alkylating agent. Proc Natl Acad Sci USA 96: 1486–1491. pmid:9990050
View Article
PubMed/NCBI
Google Scholar

[164] View Article

[165] PubMed/NCBI

[166] Google Scholar

[ref46] 46. Gorgoni B, Ciandrini L, McFarland MR, Romano MC, Stansfield I (2016) Identification of the mRNA targets of tRNA-specific regulation using genome-wide simulation of translation. Nucleic Acids Res 44: 9231–9244. pmid:27407108
View Article
PubMed/NCBI
Google Scholar

[168] View Article

[169] PubMed/NCBI

[170] Google Scholar

[ref47] 47. Zhong J, Xiao C, Gu W, Sun X, He A-Y, Zhang G (2015) Transfer RNAs mediate the rapid adaptation of Escherichia coli to oxidative stress. PLoS Genet 11(6): e1005302. pmid:26090660
View Article
PubMed/NCBI
Google Scholar

[172] View Article

[173] PubMed/NCBI

[174] Google Scholar

[ref48] 48. Durfee T, Hansen A- M, Zhi H, Blattner FR, Jin DJ (2008) Transcription profiling of the stringent response in Escherichia coli. J Bacteriol 190: 1084–1096. pmid:18039766
View Article
PubMed/NCBI
Google Scholar

[176] View Article

[177] PubMed/NCBI

[178] Google Scholar

[ref49] 49. Nilsson L, Verbeek H, Vijgenboom E, van Drunen C, Vanet A, Bosh L (1991) FIS-dependent trans activation of stable RNA operons of Escherichia coli under various growth conditions. J Bacteriol 174: 921–929,
View Article
Google Scholar

[180] View Article

[181] Google Scholar

[ref50] 50. Nilsson L, Emilsson V (1994) Factor for inversion stimulation-dependent growth rate regulation of individual tRNA species in Escherichia coli. J Biol Chem 269: 9460–9465. pmid:7511587
View Article
PubMed/NCBI
Google Scholar

[183] View Article

[184] PubMed/NCBI

[185] Google Scholar

[ref51] 51. Handa Y, Inaho N, Nameki N. YaeJ is a novel ribosome-associated protein in Escherichia coli that can hydrolyze peptidyl-tRNA on stalled ribosomes (2010) Nucleic Acid Res 39: 1739–1748. pmid:21051357
View Article
PubMed/NCBI
Google Scholar

[187] View Article

[188] PubMed/NCBI

[189] Google Scholar

[ref52] 52. Chadani Y, Ito K, Kutsukake K, Abo T (2012) Arfa recruits release factor 2 to rescue stalled ribosomes by peptidyl-tRNA hydrolysis in Escherichia coli. Mol Microbiol 86(1): 37–50. pmid:22857598
View Article
PubMed/NCBI
Google Scholar

[191] View Article

[192] PubMed/NCBI

[193] Google Scholar

[ref53] 53. Van der Meide PH, Vijgenboom E, Talens A, Bosh L (1983) The Role of EF-Tu in the expression of tufA and tufB genes. Eur J Biochem 130: 397–407. pmid:6337847
View Article
PubMed/NCBI
Google Scholar

[195] View Article

[196] PubMed/NCBI

[197] Google Scholar

[ref54] 54. Aoki H, Xu J, Emili A, Chosay JG, Golshani A, Ganoza MC. Interactions of elongation factor EF-P with the Escherichia coli ribosome. FEBS J. 2008;275:671–681 pmid:18201202
View Article
PubMed/NCBI
Google Scholar

[199] View Article

[200] PubMed/NCBI

[201] Google Scholar

[ref55] 55. Agafonov DE, Kold VA, Spirin AS (2001) Ribosome-associated protein that inhibits translation at the aminoacyl-tRNA binding state. EMBO Rep. 2: 399–402. pmid:11375931
View Article
PubMed/NCBI
Google Scholar

[203] View Article

[204] PubMed/NCBI

[205] Google Scholar

[ref56] 56. Cabello-Villegas J, Nikonowickz EP (2005) Solution structure of Ψ₃₂-modified anticodon stem-loop of Escherichia coli tRNA^Phe. Nucleic Acids Res 33: 6961–6971. pmid:16377777
View Article
PubMed/NCBI
Google Scholar

[207] View Article

[208] PubMed/NCBI

[209] Google Scholar

[ref57] 57. Kim HW, Rhee MS. (2016) Influence of low-shear modeled microgravity on heat resistance, membrane fatty acid composition, and heat stress-related gene expression in Escherichia coli O157:H7 ATCC 35150, ATCC 43889, ATCC 43890, and ATCC 43895. Appl Environ Microbiol 82: 2893–2901. pmid:26944847
View Article
PubMed/NCBI
Google Scholar

[211] View Article

[212] PubMed/NCBI

[213] Google Scholar

[ref58] 58. Newman EB, Lin R (1995) Leucine-responsive regulatory protein: A global regulator of gene expression in E. coli. Annu Rev Microbiol 49: 747–775. pmid:8561478
View Article
PubMed/NCBI
Google Scholar

[215] View Article

[216] PubMed/NCBI

[217] Google Scholar

[ref59] 59. Kasakov AE, Rodionov DA, Alm E, Arkin AP, Dubchak I, Gelfand MS (2009) Comparative genomics of regulation of fatty acid and branched-chain amino acid utilization in proteobacteria. J Bacteriol 191: 52–64. pmid:18820024
View Article
PubMed/NCBI
Google Scholar

[219] View Article

[220] PubMed/NCBI

[221] Google Scholar

[ref60] 60. Ahmed M, Lyass L, Markham PN, Taylo SrS, Vazquez-Laslop N, Neufakh AA (1995) Two highly similar multidrug transporters of Bacillus subtilis whose expression is differentially regulated. J Bacteriol 177: 3904–3910. pmid:7608059
View Article
PubMed/NCBI
Google Scholar

[223] View Article

[224] PubMed/NCBI

[225] Google Scholar

[ref61] 61. Lewinson O, Bibi E (2001) Evidence of simultaneous binding of dissimilar substrates by the Escherichia coli multidrug transporter MdfA. Biochemistry 40(42): 12612–12618. pmid:11601985
View Article
PubMed/NCBI
Google Scholar

[227] View Article

[228] PubMed/NCBI

[229] Google Scholar

[ref62] 62. Lee SJ, Gralla JD (2004) Osmo-regulation of bacterial transcription via poised RNA polymerase. Mol Cell 14: 153–162. pmid:15099515
View Article
PubMed/NCBI
Google Scholar

[231] View Article

[232] PubMed/NCBI

[233] Google Scholar

[ref63] 63. Fu X, Wang D, Yin X, Du P, Kan B (2014) Time course transcriptome changes in Shewanella algae in response to salt stress. PLoS ONE 9(5): e96001. pmid:24789066
View Article
PubMed/NCBI
Google Scholar

[235] View Article

[236] PubMed/NCBI

[237] Google Scholar

[ref64] 64. Gibert I, Barbe J (1990) Cyclic AMP stimulates transcription of the structural gene of the outer-membrane protein OmpA of Escherichia coli. FEMS Microbiol Lett. 68(3): 307–311.
View Article
Google Scholar

[239] View Article

[240] Google Scholar

[ref65] 65. Novichkov PS, Kazakov AE, Ravcheev DA, Leyn SA, Kovaleva GY, Kazanoc MD, et al. (2013) RegPrecise 3.0 –A resource for genome-scale exploration of transcriptional regulation in bacteria. BMC Genomics 14: 745. pmid:24175918
View Article
PubMed/NCBI
Google Scholar

[242] View Article

[243] PubMed/NCBI

[244] Google Scholar

[ref66] 66. Benz R, Jones MD, Younas F, Maier E, Modi N, Mentele R, et al. (2015) OmpW of Caulobacter crescentus functions as an outer membrane channel for cations. PLoS ONE 10(11):e0143227.
View Article
Google Scholar

[246] View Article

[247] Google Scholar

[ref67] 67. Heidelberg JF, Paulsen IT, Nelson KE, Gaidos Ej, Nelson WC, et al. (2002) Genome sequence of the dissimilatory metal ion-reducing bacterium Shewanella oneidensis. Nat Biotechnol 20: 1118–1123. pmid:12368813
View Article
PubMed/NCBI
Google Scholar

[249] View Article

[250] PubMed/NCBI

[251] Google Scholar

[ref68] 68. Jin M, Jiang Y, Sun L, Yin J, Fu H, et al. (2013) Unique organizational and functional features of the cytochrome c maturation system in Shewanella oneidensis. PLoS ONE 8(9): e75610. pmid:24040415
View Article
PubMed/NCBI
Google Scholar

[253] View Article

[254] PubMed/NCBI

[255] Google Scholar

[ref69] 69. Gao H, Barua S, Liang Y, Wu L, Dong Y, et al. (2010) Impacts of Shewanella oneidensis c-type cytochromes on aerobic and anaerobic respiration. Microb Biotechnol 3(4): 455–466. pmid:21255343
View Article
PubMed/NCBI
Google Scholar

[257] View Article

[258] PubMed/NCBI

[259] Google Scholar

[ref70] 70. Marritt SJ, Lowe TG, Bye J, McMillan GG, Shi L, Fredrickson J, et al. (2012) A functional description of CymA, an electron-transfer hub supporting anaerobic respiratory flexibility in Shewanella. Biochem J 444: 465–474. pmid:22458729
View Article
PubMed/NCBI
Google Scholar

[261] View Article

[262] PubMed/NCBI

[263] Google Scholar

[ref71] 71. Pirbadian S., Barchinger SE, Leung KM, Byun HS, Jangir Y, Bouchenni RA, Reed SB, Romine MF, Saffarini DA, Shi L, Gorby YA, Golbeck JH, EL-Nagar MY (2014) Shewanella oneidensis MR-1 nanowires are outer membrane and periplasmic extensions of the extracellular electron transport components. Proc Natl Acad Sci USA 111: 12883–12888. pmid:25143589
View Article
PubMed/NCBI
Google Scholar

[265] View Article

[266] PubMed/NCBI

[267] Google Scholar

[ref72] 72. Hartl FU (1996) Molecular chaperones in celular protein folding. Nature 381: 571–580. pmid:8637592
View Article
PubMed/NCBI
Google Scholar

[269] View Article

[270] PubMed/NCBI

[271] Google Scholar

[ref73] 73. Smith JT, Willey NJ, Hancock JT (2012) Low dose ionizing radiation produces too few reactive oxygen species to directly affect antioxidant concentrations in cells. Biol Lett 8: 594–597. pmid:22496076
View Article
PubMed/NCBI
Google Scholar

[273] View Article

[274] PubMed/NCBI

[275] Google Scholar

[ref74] 74. Lampe N, Biron DG, Brown JMC, Incerti S, Marin P, Maigne L, et al. (2016) Simulating the impact of the natural radiation background on bacterial systems: Implications for very low radiation biological experiments. PLoS ONE 11(11):e0166364. pmid:27851794
View Article
PubMed/NCBI
Google Scholar

[277] View Article

[278] PubMed/NCBI

[279] Google Scholar

[ref75] 75. Azzam EI, de Toledo SM, Little JB (2001) Direct evidence for the participation of gap junction-mediated intercellular communication in the transmission of damage signals from α-particle irradiated to nonirradiated cells. Proc Natl Acad Sci U S A 98(2): 473–478 pmid:11149936
View Article
PubMed/NCBI
Google Scholar

[281] View Article

[282] PubMed/NCBI

[283] Google Scholar

Figures

Abstract

Introduction

Materials and methods

LBRE (Low Background Radiation Experiment) laboratory, radiation treatments and dosimetry

Bacterial growth conditions

Growth measurement and sampling

RNA extraction, libraries preparation and sequencing

Bioinformatic analysis

RT-qPCR

Results and discussion

Gene ontology (GO) term enrichment analysis

Ribosomal proteins, tRNAs and translation factors

Amino acids biosynthesis and metabolism

Membrane transport and cell to cell communication

Respiration

Chaperones and folding catalysts

Conclusion

Supporting information

S1 Fig. Principal components analysis (PCA) showing RNA libraries distribution.

S1 Table. Regulated genes in S. oneidensis grown deprived from background radiation.

Acknowledgments

References