Quantitative Proteomics Reveals Membrane Protein-Mediated

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Quantitative Proteomics Reveals Membrane Protein-Mediated Hypersaline Sensitivity and Adaptation in Halophilic Nocardiopsis xinjiangensis Yao Zhang, Yanchang Li, Yongguang Zhang, Zhiqiang Wang, Mingzhi Zhao, Na Su, Tao Zhang, Lingsheng Chen, Wei Wei, Jing Luo, Yanxia Zhou, Yongru Xu, Ping Xu, Wenjun Li, and Yong Tao J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.5b00526 • Publication Date (Web): 09 Nov 2015 Downloaded from http://pubs.acs.org on November 12, 2015

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Journal of Proteome Research

Quantitative

Proteomics

Reveals

Membrane

Protein-Mediated

Hypersaline

Sensitivity and Adaptation in Halophilic Nocardiopsis xinjiangensis

Yao Zhang1,2,5†, Yanchang Li3†, Yongguang Zhang4, Zhiqiang Wang3,6, Mingzhi Zhao3, Na Su3, Tao Zhang3, Lingsheng Chen3,7, Wei Wei3, Jing Luo3,4,5, Yanxia Zhou3,10, Yongru Xu3,7, Ping Xu3,6,8*, Wenjun Li2,4, 9*, and Yong Tao1,5*

1

Institute of Microbiology, Chinese Academy of Science, Beijing 100101, China

2

State Key Laboratory of Biocontrol and Guangdong Key Laboratory of Plant Resources, College of

Ecology and Evolution, Sun Yat-Sen University, Guangzhou, 510275, China 3

State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Engineering

Research Center for Protein Drugs, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 102206, China 4

Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and

Geography, Chinese Academy of Sciences, Ürűmqi, 830011, China 5

Graduate University of the Chinese Academy of Sciences, Beijing 100049, China

6

Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of

Education, and Wuhan University School of Pharmaceutical Sciences, Wuhan, 430071, P. R. China 7

State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi

University, Nanning 530005, P. R. China 8

Anhui Medical University, Hefei 230032, Anhui, P. R. China

9

Key Laboratory of Microbial Diversity in Southwest China, Ministry of Education, Yunnan Institute of

Microbiology, Yunnan University, Kunming 650091, Yunnan, China 10

Hebei Province Key Lab of Research and Application on Microbial Diversity, College of Life

Sciences, Hebei University, Baoding 071002, Hebei, China †

These authors contributed equally to this work.

*Corresponding authors: Yong Tao, Tel: +86-010-64807419; Fax: +86-010-64807419; E-mail: [email protected] Wenjun Li, Tel/Fax: +86-20-84111727; E-mail: [email protected] Ping Xu, Tel/Fax: +86-10-80705066; E-mail: [email protected] 1

ACS Paragon Plus Environment


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ABBREVIATIONS iTRAQ, isobaric tags for relative and absolute quantification; 2D LC-MS/MS, twodimensional liquid chromatography tandem mass spectrometry; RP-LC, reverse phase liquid chromatography; MIT, maximum ion injection time; PSMs, peptide spectrum matches; SD, standard deviation; FDR, false discovery rate; SDS, sodium dodecyl sulfate; DTT, DL-dithiothreitol; ACN, acetonitrile; TEAB, tetraethylammonium bicarbonate; HCD, higher energy collision induced dissociation; ABC, ATP-binding cassette; BS-12, dodecyl dimethyl betaine; PCD, programmed cell death

ABSTRACT The genus Nocardiopsis is one of the most dominant Actinobacteria that survives in hypersaline environments. However, the adaptation mechanisms for halophilism are still unclear. Here, we performed iTRAQ-based quantitative proteomics to investigate the functions of the membrane proteome after salt stress. A total of 683 membrane proteins were identified and quantified, of which 126 membrane proteins displayed salt-induced changes in abundance. Intriguingly, bioinformatics analyses indicated that these differential proteins showed two expression patterns, which were further validated by phenotypic changes and functional differences. The majority of ABC transporters, secondary active transporters, cell motility proteins, and signal transduction kinases were up-regulated with increasing salt concentration, whereas cell differentiation, small molecular transporter (ions and amino acids), and secondary metabolism proteins were significantly up-regulated at optimum salinity, but down-regulated or unchanged at higher 2


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salinity. The small molecule transporters and cell differentiation-related proteins acted as sensing proteins that played a more important biological role at optimum salinity. However, the ABC transporters for compatible solutes, Na+-dependent transporters, and cell motility proteins acted as adaptive proteins that actively counteracted higher salinity stress. Overall, regulation of membrane proteins may provide a major protection strategy against hyperosmotic stress. Keywords: Membrane proteins, iTRAQ, Actinobacteria, halophilic mechanism, sensitivity, adaptation INTRODUCTION Soil salinization is an important worldwide environmental problem, especially in semi-arid and arid regions1, where it impacts soil health2, agricultural production3-5, environmental wellbeing4, 6, and economic welfare. Xinjiang is a typical high saline environment in China where a number of halophilic and halotolerant microorganisms are found, including many representative Archaea, Bacteria and Actinobacteria7-12. In their natural habitat, microorganisms have to cope with various salinity stresses. A central question is how these microorganisms differ in their expression of genes and proteins, and whether membrane proteins play a key role in adapting to saline stress. These questions are important for understanding halophilic Actinobacteria biology, and support the theory of convergent evolution under extreme hypersaline stress. The halophilic response mechanisms of representative microbes from high saline areas have been the focus of study since their discovery, especially the study of Archaea13,

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and Bacteria15-19, using phenotypic,

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chemical, and metabolic approaches. Archaea and Bacteria show different adaptations to osmolarity in regards to their initial response to saline shock, and subsequent signal transduction and regulation20. Recently, genome sequencing and transcriptome profiling studies on high saline adaptive strategies in filamentous Fungi suggested that long-term adaptation to salinity requires cellular and metabolic responses21. Because Fungi have a similar morphology, these results also provide clues to the halophilic and halotolerant adaptive mechanisms in Actinobacteria. The genus Nocardiopsis is known as the most abundant halophilic group among the Actinobacteria in hypersaline environments22-24. Approximately two thirds of the Nocardiopsis species are halophilic and halotolerant Actinobacteria25-29. The large-scale sequencing of 16 Nocardiopsis species in 2013 provided an opportunity to better understand these microorganisms based on genetic information30. In general, microorganisms adopt two principal strategies to balance and regulate their saline environments. The first is a compatible solutes strategy involving uptake or synthesis31, and the other is a salt-in strategy using the accumulation of K+ and Cl- ions in extremely halophilic Halobacteria (Archaea) and halophilic anaerobic Haloanaerobiales (Bacteria)32. However, the definitive survival strategies of halophilic Actinobacteria (Gram-positive, high G+C content) remain unclear. Membrane proteins play significant roles in cellular processes, including cell signal transduction, ion and metabolite transport, and photosynthesis33. Membrane proteomics could provide a global and dynamic way to better understand the relevant molecular events 4


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occurring on the plasma membrane in cells coping with the challenge of environmental osmotic stress. In this study, we optimized a method for isolating membrane proteins and performed different predictive methods to achieve higher coverage of the membrane proteome. We used isobaric tags for relative and absolute quantification (iTRAQ) to quantitatively and simultaneously compare a series of membrane proteome samples from Nocardiopsis xinjiangensis prepared in differing saline concentrations (6, 10, and 17.5% NaCl). We found that small molecule transporters and cell differentiation-related proteins acted as sensing proteins. These proteins may play a more important biological role at optimum salinity, while ABC transporters for compatible solutes, Na+-dependent transporters, and cell motility proteins may act as adaptive proteins to counteract high salinity stress.

MATERIALS AND METHODS Strain and Culture Conditions N. xinjiangensis YIM 90004T was used in this study. YIM 90004T was cultured in GYM medium (0.4% glucose, 0.4% yeast extract, 1% malt extract, 0.2% CaCO3, 10% NaCl, and 1.2% agar) for rapid differentiation and abundant spores, as described previously34. To investigate the salt tolerance of YIM 90004T, 1 × 106 viable spores were inoculated and grown on an agar plate containing 25 mL of GYM and 0-20% NaCl (w/v) at 30 °C, based on salt tolerance of moderate halophilic organisms. Three different growth conditions based on NaCl content were evaluated: 6%, 10%, and 17.5% (w/v) NaCl, which 5



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represented the minimum, optimum and maximum NaCl concentrations for growth, respectively. Using the above three NaCl concentrations (6%, 10%, and 17.5%) in GYM medium, liquid cultures were directly inoculated with spores (1 × 106 viable spores) in a 250 mL flask. The cultures were incubated at 30 °C in a shaker at 200 rpm, and growth was monitored by OD600 and cell dry weight measurements. Sampling and Fractionation of YIM 90004T Cells under Different NaCl Concentrations Two independent cultures were processed (biological replicates) under identical conditions as described. Cells were harvested at the mid-exponential phase (Figure1B). Pellets were quickly washed with lysis buffer A (0.25 M sucrose, 5 mM Tris, 1 mM EGTA, 1 mM sodium orthovanadate, and 2 mM sodium fluoride) as described previously, with some modifications35. The cell pellet was suspended in buffer A and disrupted by a Soniprep sonicator (Scientz, Ningbo, Zhejiang, China) for two cycles of 10 s each (26.6 kHz, 30 W), on ice. The remaining debris was eliminated by centrifugation (10,000 × g) at 4 °C for 10 min. Membranes and other cytosolic fractions were obtained by ultracentrifugation (120, 000 × g) at 4 °C for 80 min in an ultracentrifuge (Beckman, Pasadena, CA, USA) as previously described36. The membrane preparation was resuspended in 1 mL of 0.1 M Na2CO3 and incubated at 4 °C for 1 h with a vertical mixing apparatus (Scientz). Finally, membrane proteins were recovered again by ultracentrifugation (120, 000 × g) at 4 °C for 80 min. 6


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Membrane Protein Separation and Gel-assisted Digestion Membrane proteins were suspended in buffer B (4% sodium dodecyl sulfate (SDS), 50 mM Tris, 20 mM DTT, pH 8.0). To eliminate the potential errors resulted from the complex ingredients in the lysis buffer by regular BCA assay, the amount of these proteins were quantified based on the gel-assisted method as described previously37 and the image was analyzed by using Scion Image (4.0.3.2) software (National Institutes of Health, Bethesda, MD, USA). Briefly, the samples were run shortly on a SDS-PAGE (0.3cm), Coomassie blue G-250 stained to quantify the amount of proteins based on dye absorbance signal. The same amount of membrane protein (100 μg) from each total sample was reduced with 5 mM of DTT, alkylated with 20 mM of iodoacetamide , pre-cleaned with SDS-PAGE (10%, 0.7 cm), and digested in-gel with trypsin (10 ng/μL) at 37 ℃ for 12 hours as described previously38. iTRAQ Labeling The resulting tryptic peptides were labeled with iTRAQ reagents (4-plex system) according to the manufacturer’s instructions (AB Sciex, Foster City, CA, USA). The 114 and 115 iTRAQ tags were used for the 6% samples (6%_1 and 6%_2), and the 116 and 117 tags were used for the 10% and 17.5% samples, respectively. Briefly, peptides were dissolved in a 0.1 M tetraethylammonium bicarbonate (TEAB, pH 8.5) solution before the labeling reagent was added. After 2 h of incubation, the reaction was quenched by adding an equal volume of water. Differentially labeled peptides were mixed and dried with a vacuum dryer (LABCONCO CentriVap, Kansas City, MO, USA). 7



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Two-Dimensional Liquid Chromatography Tandem Mass Spectrometry (2D LCMS/MS) The pooled iTRAQ labeled samples were separated by the first dimensional high pH reverse phase (RP) HPLC system (Rigol, L-3120, Beijing, China) as described previously39. The peptide mixtures were loaded onto a Durashell C18 -column (150 Å, 5 μm, 4.6 × 250 mm). Briefly, the solvent gradient of buffer A (98% ddH2O and 2% ACN, pH 10, adjusted by ammonium hydroxide), and buffer B (2% ddH2O and 98% ACN, pH 10) was as follows: 3%-5% B, 10 minutes; 5%-18% B, 35 minutes; 18%-34% B, 22 minutes; 34%-95% B, 6 minutes; 95% B, 5 minutes; and 95%-3% B, 2 minutes. The LC flow rate was set at 0.7 mL/minute and monitored at 214 nm. The column oven was set at 45 °C. The eluent was collected every 2 minutes, and finally separated into 40 fractions as indicated. Each fraction was dried and suspended with loading buffer containing 0.1% FA and 1% ACN before LCMS analysis. The second dimension analysis was applied with low-pH RP chromatography separation coupled with tandem mass spectrometry (LC-MS/MS) using an LTQ-Orbitrap Velos mass spectrometer (Thermo Electron, San Jose, CA, USA). The instrument was interfaced to an ultra-performance liquid chromatography (UPLC) system (nanoAcquity, Waters, Milford, MA, USA). The labeled peptide mixtures were loaded onto a 75 μm i.d. × 15 cm fusedsilica capillary column (Beijing SpectraPeaks, Beijing, China) packed with C18 resins (100 Å; 3μm; Michrom Bioresources, InC., Auburn, CA ) with a flow rate of 0.3 μL/min applied, and eluted with a linear gradient of 5-7% B for 6min, 7-13% B for 34 min, 23-35% B for 8


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18 min, and 35-80% B for 7 min (Buffer A: 0.1% FA and 2% ACN; Buffer B: 0.1% FA and 100% ACN). The MS parameters were as following. Eluted peptides were ionized under high voltage (1.5 kV) and analyzed using an Orbitrap mass spectrometer (Thermo Scientific) in a survey scan (400-1800 m/z). The MS1 precursors were detected in the centroid mode, and the resolution was set at 30,000 at m/z 400 with accumulation of automatic gain control (AGC) target reaching up to 1 × 106 under the limitation of 150 ms maximum ion injection time (MIT). The ten most intense ions were selected for further fragmentation in the data-dependent mode via higher energy collision induced dissociation (HCD) with 40% collision energy. The MS2 fractions were detected in the Orbitrap using the profile mode with the lowest recorded mass fixed at 100 m/z, and at a resolution of 7,500 at m/z 400, in order to detect the reporter ions (114, 115, 116 and 117 tags). The isolation window was operated at 3.0 m/z and AGC was set as 50,000 accumulated in the linear ion trap. The dynamic exclusion was set as 40 seconds for avoiding the redundancy detections. LC-MS/MS Data Processing, Protein Identification, and Quantification The acquired raw files were then submitted to the MaxQuant40 search engine (version 1.5.3.28) against a composite target/decoy database to estimate false discovery rate. The cut off of max 25% precursor interference for peptide spectrum matches (PSMs) was used in the quantification. The target proteins include proteins encoded by N. xinjiangensis YIM 90004T (http://www.ncbi.nlm.nih.gov/genome/proteins/16736?genome_assembly_id=176980&gi 9



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=484023021, RefSeq NZ_ANBE00000000.1), along with 245 common contaminant protein sequences (http://www.maxquant.org/contaminants.zip). The search parameters were as follows: precursor ion spectra were searched with a first search tolerance of 20 ppm and main search tolerance of 6 ppm in the MS mode, and the MS2 ions with 20 ppm in the HCD mode. Full-tryptic restriction and up to two missed cleavages were allowed. Peptide matches were filtered by a minimal length of six amino acids. Carbamidomethylated cysteine (+57.0215 Da), and iTRAQ modified N-terminal residue, and iTRAQ modified lysine (+144.1021 Da) were set as fixed modifications, while oxidation (+15.9949 Da) of methionine was set as a variable modification. The peptides and proteins were filtered to a false discovery rate (FDR) of lower than 1%，estimated using the target-decoy search strategy. Protein quantification was based on the reporter intensity generated from MaxQuant results, and only unique and razor peptides of the identified proteins were selected for reporter ion quantification. The concentration ratios of proteins were calculated based on the fold change of the intensity score at higher vs. lower NaCl concentration. The significantly different proteins were derived by on in-house script, using the ‘significance B’ theory approach with Benjamini-Hochberg FDR < 5%40. Biological variability was calculated by the intensity ratio of the 6% NaCl sample labeled with two iTRAQ reagents (114 and 115 tags) based on their R-squared value and the standard deviation (SD). Membrane Protein Prediction and Quantification Six membrane protein prediction methods were tested. Among them, TOPCONS-single41, 10


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PHOBIUS42, TMHMM43, and SCAMPI44 were mainly used for α-helical membrane protein structures, and BOMP45 and PRED-TMBB46 are mainly used for β-barrel membrane proteins. Proteins were affirmed as theoretical membrane proteins of N. xinjiangensis YIM 90004T by at least two prediction tools. The identified and quantified theoretical membrane proteins were retained for further bioinformatics analyses. Downstream Bioinformatics Analyses for Quantified Membrane Proteins For proteins identified in biological replicates, iTRAQ ratios were considered to be significantly changed if their average was greater or lower than 1.3-fold. We discarded proteins without good reproducibility between replicates (6%_1, 6%_2) before confirmation of significantly changed proteins under different saline conditions. The intensity ratios of replicates were maintained within 1.2-fold. For the remaining membrane proteins among the three samples, those with iTRAQ ratios < 1.3-fold (p-values1.3-fold (p-values 0.1 g/L (Figure 6C). Mycelium growth was also inhibited after adding BS-12 during the mid-logarithmic growth phase (Figure 6D). For further determining the most effective BS12 concentration, varied gradients ranging from 0.02 to 0.5 g/L were tested. The results showed that the optimum role concentration was 0.05 g/L, which was appropriate for either spore germination or bacterium development (Figure 6C-E). To better understand the inhibitory effect at different salinities, 0.05 g/L BS-12 was added in liquid medium supplemented with low, medium, and high concentrations of NaCl at mid-logarithmic growth (Figure 6F). The three samples responded differently to the differing levels of salinity. The striking difference in the inhibitory effects was evaluated by the growthmaintenance time and the slight growth variation after adding BS-12. Compared with other conditions, cells cultured at high NaCl were the first to respond and no longer grew after 20


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10 min. Cells cultured at medium and low NaCl concentrations responded later and stopped growing after 20 min and 30 min, respectively. These findings were consistent with what was found in our proteomic study of the expression patterns of the betaine transporter proteins. These experimental results implied that the analog BS-12 analog was likely transported along with betaine, or prevented betaine transport into the cell during adaptation to high-salt environments. In addition, the glycine betaine ABC transporterconserved motif showed that the permease exhibited osmosensory and osmoregulatory properties inherent to their polypeptide chains. Together, these findings suggest that ABC transporters might play two roles during salt stress. Na+-Dependent Transporters Respond to and Regulate Salt Shock by Balancing the Intra-to-Extracellular Transport Other identified regulatory proteins included the ‘secondary active transporters’ group, including symporters (Na+-dependent), antiporters (Na+: H+, and Ca2+/Na+: H+), and uniporters (potassium and aminobenzoyl-glutamate). Among these sodium dependent transporters, the Na+: H+ antiporter, a major determining factor for intracellular pH and also maintains cellular volume49, was significantly up-regulated at either optimum or high salinity levels. To verify whether the cytosol tends to become progressively acidified and whether protons are extruded from the cells, liquid media cultured cells were detected. While liquid culture commenced, the pH of the media decreased at all three NaCl concentrations (Figure 6G). When entering the logarithmic phase, the pH of the media was reduced and remained approximately the same after the growth reached a plateau. At 21



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optimum salinity, pH variations were less than at low and high salinity. Mycelium growth was maximal at 10% NaCl, and morphology and reproductive structures were welldeveloped in contrast to that observed with other salt conditions (Figure S-3& Figure 7B). Cells were well-differentiated under higher pH variation at optimum saline stress conditions, which indicated that more H+ were extruded from the cells and Na+ was taken from the extracellular media. The extracellular pH variations of the cells were further confirmed using our proteomic techniques. This result showed that the Na+: H+ antiporter behaved similarly to the A group expression model (always up-regulated with increasing salt concentration). Some other transporters showed different expression patterns and were only significantly up-regulated at optimum salinity. Previous studies indicated that, in response to a changing environment, many biosensors proteins undergo molecular conformational shifts between an “off” and an “on” state, to detect the biochemistry of cellular environments and extracellular water levels50. This model of transport was proposed by Jardetzky51 and Shi YG52. In counteractive optimum-saline environments, these proteins might play greater roles compared with those utilized in hyper-saline environments. Phenotypic Validation of Cell Differentiation-Related and Motility-Related Proteins under Salt Stress The differentiation-related proteins and cell motility-related proteins were clustered in an evolutionary tree consistent with their biological functions (Figure 7A). The cell division and cell wall protein patterns were significantly up-regulated at optimum salinity and 22


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down-regulated or not significantly up-regulated at high salinity (Figure S-3). For the clusters of ABC transporters, six proteins were related to cell differentiation and cell wall synthesis and showed similar regulatory patterns; they were up-regulated at optimum salinity and down-regulated or not significantly up-regulated at high salinity. Examples of these proteins included the spore cortex-lytic enzyme, which has an inactive form in the spore stage and becomes active during germination, as well as the cell wall synthesisrelated proteins. Interestingly, one of the cell wall synthesis-related proteins, transpeptidase, plays a role in cell elongation and is down-regulated at high salt, indicating that the cell may not maintain a normal growth rate. In the central metabolism cluster, compared with at low NaCl concentration, all ribosomal proteins were up-regulated at optimal and high NaCl concentrations and were down-regulated at a high salt level. Because membrane proteins are synthesized at the ribosome like other proteins53, these results suggest that the expression ratio of cell differentiation-related proteins might relate to the reproductive structures of N. xinjiangensis YIM 90004T. We wished to determine if the changes in cell differentiation-related protein expression leads to YIM 90004T phenotype differences. Therefore, to answer this question and explore the biological role of differentiation-related and ribosome proteins, salinity resistance phenotypes were detected. The vegetative hyphae, aerial hyphae, and spore chains were observed by scanning electron microscopy. Cell differentiation has some relationship with the salt concentration (Figure 7B). For N. xinjiangensis YIM 90004T, the optimum salinity was 10%, at which cells were well-differentiated. The vegetative hyphae were long, slim, 23



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well-developed and fragmented; aerial hyphae were completely differentiated into spore chains, and the spores were rod-shaped and smooth-surfaced (Figure 7B middle panel). The differentiation of cells cultured in 6% NaCl was poorer and slower, with only partial aerial hyphae differentiated into spore chains and with no evidence of well-developed spores (Figure 7B top panel). Fewer aerial hyphae and more malformed spores were observed under high salinity (Figure 7B down panel). These phenotypic results strongly suggest that cell differentiation was well stimulated at optimum salinity, but was somewhat inhibited at either higher or lower salinity. However, proteins involved in cell motility (i.e., pilus proteins) and cell envelope biogenesis proteins expressed different patterns, but were always up-regulated with an increasing NaCl concentration. These results are consistent with the up-regulation of cell synthesis proteins in Corynebacterium glutamicum during salt stress54. Pilus proteins respond when exposed to environments with drastic variations in salt concentrations. To maintain normal growth in typical conditions, the pilus is motile and likely to up-take nutrients from the media. Their motility is, to some extent, differentiated under different NaCl concentrations. In our studies, the rate of mycelium extensibility was increased with an increasing concentration of NaCl (Figure 7C). These findings indicate that at higher salinities, the cell might require more metabolic substrate up-take for their normal growth, and more ions exchange for intra-to-extracellular balance. Our study demonstrated that membrane proteins are essential for response to or regulation of higher saline shock, which highlights the hypersaline adaptation in Actinobacteria. 24


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To investigate how membrane proteins play a role during salt stress, the expression of different functional clusters was analyzed through bioinformatics data and validation experiments. As shown in Figure 5, the regulatory family cluster of proteins may have a more important role in balancing osmotic stress. Interestingly, ours is the first study reporting that two typical protein groups with different functions work together to overcome cellular adversity. Moreover, these findings indicate that membrane proteins help mediate hypersaline sensitivity and adaptation in halophilic Actinobacteria. DISCUSSION In this study, we analyzed the survival strategy of halophilic Actinobacteria based on quantitative membrane proteomic technology. Experimental initiatives to perform proteomics research in Nocardiopsis and other non-model Actinobacteria have been hampered because of the lack of genetic information and effective membrane protein extraction techniques. For a complete study of the membrane proteome, enrichment of membrane proteins is the best and most important strategy55. However, even after enrichment, only a low percentage of the identified proteins are membrane proteins. To comprehensively identify the changes in membrane proteins levels in hypersaline environments, the iTRAQ labeling approach was used. To increase the membrane extraction efficiency, membrane proteins were extracted by ultracentrifugation in a vacuum, boiling in a high concentration SDS loading buffer, and separation on SDS-PAGE for 0.7 cm. Furthermore, different membrane protein prediction platforms were adopted, and conserved motifs were utilized for correct predictions. The data analysis from labeled 25



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peptides yielded 683 membrane proteins (45.5 % of all predicted), including α-helical and β-barrel proteins. To our knowledge, this is one of the largest membrane protein datasets identified by iTRAQ-labeling technology in Actinobacteria56,

57.

Nowadays, although

many used prediction tools are well-established and applied on multiple prokaryotes, it is still rare to successfully predict outer membrane proteins for Actinobacteria. The differentially expressed membrane proteins were particularly enriched in the regulatory cluster groups, including primary and secondary active transporters, and signal transduction- and cell differentiation-related proteins, of which 52.2% belonged to the transporter group of proteins, that selectively permeate nutrients and metabolites58. Among these transporters, the ABC family was the largest group. This group belongs to the primary active transporters group, and these proteins work against a concentration gradient by the hydrolysis of ATP59. In this study, we found that ABC transporters that take part in a variety of essential biological processes, including nutrient uptake, metabolic substrate export, defense, and repair processes, changed in response to salinity. This information is consistent with the four main functions of ABC transporters in Bacteria60, 61. The glycine betaine analog BS-12 validation experiments showed that cells cultured at high salinity were more sensitive to and could import more BS-12 when taking up the osmotic protectant betaine from the growth environment. The betaine concentration increased with increasing NaCl in extremely halophilic Actinopolyspora62. These results suggest that cells may require more compatible solutes to balance intracellular and extracellular osmotic shock. The amino acid transporters, had a different protein expression profile, and were only 26


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highly expressed at optimum salinity. Evidence strongly indicates that ABC uptake systems are bidirectional in Bacteria63. Thus, ABC uptake systems could accumulate some extracellular amino acids or other substrates and may quickly reach balanced concentrations in the cell, where the efflux rate would equal the rate of uptake. Therefore, proteins related to amino acid and other ion transporters have a similar expression pattern. In addition, the glycine betaine regulatory ratio compared with other compatible solutes has not been fully clarified by solute concentration testing or by gene expression studies30. In this study, we performed a comprehensive protein profiling of osmotic protection transport and regulatory protein ratios at high, middle, and low salinities. In our membrane protein studies, secondary active transporters were mainly sodium related carriers, which transport Krebs cycle intermediates64 and amino acids, and exchange extracellular Na+ and intracellular H+49, thus coupling the downhill movement of sodium. These proteins were highly up-regulated with increasing salt concentration. In this group of proteins, the majority of secondary active transporters were Na+-dependent transporters, which are used for the exchange of other ions (amino acids, K+, H+, and others) for Na+. Our results may explain how the cell accomplishes ion and small molecule exchange, and how the related protein expression ratio changes contribute to this cellular balance. This has not been fully clarified in Archaea, Eukarya, and other Bacteria. Cell division-related and cell wall proteins changed markedly; they were significantly upregulated at optimum salinity and down-regulated or not clearly up-regulated at high salinity (Table 1). Cell envelope-related protein up-regulation was also observed in 27



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Corynebacterium glutamicum transcripts and protein levels after short-term salt shock54. The N. xinjiangensis microscopic phenotype results showed that hyphae, spore chains, and spores were well-developed under optimum-salt conditions compared with high-salt or low-salt conditions. Interestingly, all ribosomal proteins had a similar expression ratio as the cell division-related proteins. These results indicate that halophilic Actinobacteria maintain normal growth, depending on the proper concentration of salt, for nutrient absorption and osmotic balancing, and can remodel their cell structure, and adopt other strategies during higher salt shock conditions. Detailed biological analyses of Actinobacteria differentiation have demonstrated that this species has a complex developmental cycle, including programmed cell death (PCD) 65, 66. Signal transduction kinases such as serine/threonine and histidine protein kinases are directly involved in the regulation of the apoptotic67 and survival processes68. In our study, more histidine kinases were down-regulated at medium salinity, and only two kinases were up-regulated at high salinity (Figure 5D); thus, these enzymes serve as basic stimulusresponse coupling proteins for sensing and responding to changes in different environmental conditions69. Previous studies have shown that serine/threonine protein kinases are directly or indirectly related to the apoptotic process via the regulation of the cell cycle70, 71. Histidine protein kinases help the organisms to sense and respond to changes in different environmental conditions69. These findings suggest that protein kinases might take part in signal sensing and transduction processes during PCD, thus providing a complex two-component system in atypical environments. This information offers new 28


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insights into the PCD mechanisms of halophilic Actinobacteria.

CONCLUSIONS Considering the results presented here, we have proposed a model for the sensing and regulation of hyper-saline environments via membrane proteins (Figure 8). To our knowledge, this is the first study on the halophilic adaptation of Actinobacteria by quantitative profiling, using membrane proteomics. Our results suggest that multiple biological processes may be involved in adaptation to salinity, including substrate transport, cell differentiation, signal sensing and transduction, and repair/defense protein expression (Figure 8A). YIM 90004T Na+-dependent halophiles and Na+-related membrane proteins may facilitate amino acid and ion exchange, and maintained pH balance. ABC transporters may participate in nutrient uptake, metabolic byproduct export, and defense and repair processes. Kinases are known to participate in signal sensing and transduction processes and in the control of cell differentiation. In agreement with the phenotypic differences, membrane proteins showed different expression patterns under saline shock. At optimum salinity, cell differentiation-related proteins, small molecular transporters, and other proteins could regulate and adapt to some salt stress, although they may not play a major role during higher salinity. However, compatible solute ABC transporters, Na+-dependent transporters (antiporters, symporters, and others), cell motility proteins, and energy-related proteins could begin to function at high salinity (Figure 8B). In summary, our study highlights a pivotal role for membrane 29



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proteins in halophilic Actinobacteria adaptation to salinity, and may suggest a new theoretical framework for the development of halophilic molecular technology.

ASSOCIATED CONTENT Supporting information The supporting information is available free of charge on the ACS Publications website via http://pubs.acs.org/. Figure S-1, the cell differential characteristics of YIM 90004T under different saline conditions (6%, 10%, and 17.5%) when reaching mid-log phase, respectively, including A and B two biological replicates. Figure S-2, two typical protein expression patterns of four major regulatory proteins. Figure S-3, two major expression patterns of cell cycle-related proteins. Proteins related to cell differentiation and cell wall synthesis had similar regulatory patterns, which were up-regulated at optimum salinity and down-regulated or not significantly up-regulated at high salinity (PDF). Table S-1, the quantitative information of total quantified proteins. Table S-2, prediction, identification, and quantification of YIM 90004T membrane proteins. Table S-3, the quantitative information of total membrane proteins. Table S-4, two typical expression pattern information was obviously showed in 126 differential membrane proteins (XLSX).

Acknowledgements This work was supported by grants from the National Basic Research Program of China (973 Program) (No. 2011CB910600), the National High-Tech Research and Development 30


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Program of China (SS2012AA020502, 2011AA02A114 & 2014AA020900), the National Natural Science Foundation of China (No.31270054, 31070673, 31170780, 31400698), the National Megaprojects for Key Infectious Diseases (2013zx10003002), the Key Projects in the National Science & Technology Pillar Program (2012BAF14B00), and the International Collaboration Program (2013DFA31980 and 2014DFB30020). W-J Li was also supported by the Hundred Talents Program of the Chinese Academy of Sciences and Guangdong Province Higher Vocational Colleges & Schools Pearl River Scholar Funded Scheme (2014).

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Tables Table 1．Five regulatory proteins of 126 differentially expressed membrane proteins dually-regulated under different saline conditions Protein

Function

10%/6%

17.5%/10%

17.5%/6%

WP_017608406.1

Cold-shock protein

3.19

0.29

0.94

WP_017608740.1

Histidine kinase

0.40

5.97

2.38

WP_017609226.1

Antimicrobial peptidase

4.53

0.32

1.44

WP_017610181.1

50S ribosomal protein L30

2.83

0.30

0.85

WP_017611485.1

Fusaric acid resistance protein

0.71

4.66

3.30

Table 2．Summary of quantitative data: regulatory proteins Function

Proteins

Description

10%/6%

17.5%/10%

17.5%/6%

ABC transporters

WP_017610121.1

Amino acid ABC transporter permease

2.69

4.72

12.67

WP_017609094.1

Branched-chain amino acid transport permease

2.80

2.71

7.59

WP_017610489.1

Sugar ABC transporter permease

2.22

5.10

11.33

WP_017607765.1

Arabinose efflux permease

3.49

3.11

10.88

WP_017607391.1

ABC transporter permease

2.25

4.83

10.86

WP_017611149.1

ABC transporters

3.56

2.96

10.52

WP_017608985.1

Transporter

2.51

2.37

5.95

WP_017608794.1

Choline-glycine betaine transporter

1.74

6.21

10.79

WP_017608296.1

Oligosaccharyl transferase

2.43

3.07

7.44

WP_017608724.1

Choline-glycine betaine transporter

2.13

4.80

10.21

WP_017608739.1

ABC-type antimicrobial peptide transport permea se

1.43

7.73

11.06

WP_017610576.1

Threonine/homoserine efflux transporter

1.91

4.27

8.16

WP_017608377.1

Lysine-arginine-ornithine-binding periplasmic protein

4.12

1.74

7.18

WP_017607390.1

ABC transporter permease

1.74

5.62

9.78

WP_017607397.1

Phosphate ABC transporter permease

2.85

2.56

7.31

WP_017607978.1

Branched-chain amino acid ABC transporter permease

1.45

4.40

6.36

WP_017608738.1

Heme ABC exporter

0.94

4.68

4.40

WP_017610871.1

Multiple sugar transporter permease

3.20

1.35

4.32

WP_017611168.1

Molybdate ABC transporter permease

0.46

2.75

1.28

WP_017610420.1

Sirohydrochlorin cobalt chelatase

0.67

1.39

0.93

WP_017607349.1

Iron ABC transporter substrate-binding protein

0.96

0.68

0.65

WP_017607311.1

Na+/melibiose symporter and related transporter

1.98

4.36

8.64

WP_017607738.1

Sodium:dicarboxylate symporter

2.62

2.61

6.84

WP_017611288.1

Sodium:alanine symporter

2.11

3.30

6.96

WP_017608786.1

Na+/H+ antiporter

2.48

5.53

13.71

WP_017607620.1

Na+/H+ antiporters

0.66

1.24

0.81

WP_017608940.1

Calcium/sodium:proton antiporter

0.56

0.33

0.19

WP_017611012.1

Ammonia channel protein

3.63

3.26

11.86

WP_017609477.1

Putative p-aminobenzoyl-glutamate transporter

1.95

4.24

8.25

WP_017608332.1

Phosphotransferase

1.65

3.99

6.59

Symporters

Antiporters

Other transporters

36


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Cell differentiation/Cell cycle

Transcriptional regulators

Other regulatory proteins

Kinases

Actinomycete specific


WP_017610924.1

Potassium transporter

1.23

4.30

5.30

WP_017607367.1

Carboxylate transporter

3.00

0.99

2.97

WP_017610873.1

Carbohydrate Uptake Transporter

4.08

0.49

1.98

WP_017609980.1

Phosphoenolpyruvate-protein kinase

0.91

0.55

0.50

WP_017610021.1

Carbonic anhydrase

1.22

0.34

0.42

WP_017609556.1

Flagellum synthase

2.08

5.02

10.44

WP_017607498.1

Flagellar basal body-associated protein FliL

4.05

2.09

8.47

WP_017609351.1

Spore cortex-lytic enzyme SleB

8.49

0.53

4.50

WP_017608347.1

Transpeptidase

2.97

1.28

3.81

WP_017609736.1

Cell wall-associated hydrolases

3.19

0.58

1.85

WP_017609560.1

Flp pilus assembly protein TadC

0.45

2.86

1.30

WP_017609398.1

Transglycosylase

3.03

0.51

1.56

WP_017611398.1

Small-conductance mechanosensitive channel

0.73

1.55

1.14

WP_017607428.1

Glycosyltransferase

1.19

1.47

1.76

WP_017607464.1

Flagellar outer arm dynein protein

1.16

0.43

0.50

WP_017608842.1

SMP-30/Gluconolaconase/LRE-like

0.72

0.44

0.32

WP_017608334.1

Glutamine--fructose-6-phosphate

0.87

0.42

0.36

WP_017607203.1

Transcriptional regulator

0.90

0.59

0.53

WP_017609767.1

Transcriptional attenuator

3.06

0.53

1.61

WP_017611364.1

Transcriptional regulator

3.57

0.48

1.71

WP_017609396.1

Single-stranded DNA-binding protein

2.69

0.67

1.79

WP_017608406.1

Cold-shock protein

3.19

0.29

0.94

WP_017609375.1

DNA-binding protein, YbaB/EbfC

1.31

0.49

0.64

WP_017610265.1

Dynein regulation protein LC8

1.08

0.43

0.46

WP_017609279.1

Nitrobindin heme-binding protein

1.05

0.34

0.35

WP_017608063.1

Base-induced periplasmic protein YceI

2.14

0.36

0.77

WP_017611303.1

Serine/threonine protein kinase

1.79

4.37

7.81

WP_017609659.1

Histidine kinase-like ATPases

1.44

4.24

6.10

WP_017607858.1

Serine/threonine protein kinase

1.17

3.51

4.11

WP_017608740.1

Histidine kinase

0.40

5.97

2.38

WP_017609752.1

Phage-shock protein

2.87

0.63

1.82

WP_017610977.1

signal peptide protein

3.38

0.57

1.91

WP_017610141.1

Histidine kinase

0.72

1.18

0.85

WP_017609357.1

Histidine kinase

0.75

0.93

0.70

WP_017611405.1

Phosphoglycerate kinase

2.10

0.31

0.64

WP_017610243.1

Histidine kinase

0.41

1.42

0.58

WP_017609273.1

SseC

1.00

0.45

0.44

37



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Page 38 of 53

Table 3．Summary of quantitative data: central metabolism proteins Function

Proteins

Description

10%/6%

17.5%/10%

17.5%/6%

Krebs cycle and energy metabolism

WP_017607807.1 WP_017609843.1 WP_017609848.1 WP_017609743.1 WP_017610547.1 WP_017609277.1 WP_017609978.1 WP_017609953.1 WP_017607907.1 WP_017607684.1 WP_017611282.1 WP_017609758.1 WP_017609870.1 WP_017609029.1 WP_017610165.1 WP_017610304.1 WP_017610164.1

Synthesis of Cytochrome c Oxidase NADH:ubiquinone oxidoreductase subunit N NADH:ubiquinone oxidoreductase subunit H Cytochrome C oxidase subunit II FAD-dependent oxidoreductases Alcohol dehydrogenase Fructose-1-phosphate kinase, fructose-6-phosphate Glycerate kinase FAD-dependent oxidoreductases Dipeptidase Glutamine amidotransferase Leucyl aminopeptidase Lysophospholipase L1 and related esterases Aldolase Acyltransferases Glycerol-3-phosphate dehydrogenase Phosphatidylglycerophosphate synthase

2.32 1.35 1.68 2.17 0.67 1.76 1.25 0.59 0.85 2.99 1.68 2.40 2.20 2.33 4.47 1.29 0.48

5.59 5.81 4.76 2.61 0.94 0.33 0.45 0.87 0.50 3.42 2.71 0.33 0.30 0.49 0.64 1.66 1.01

12.97 7.86 8.00 5.66 0.63 0.57 0.57 0.52 0.43 10.24 4.54 0.78 0.66 1.15 2.87 2.13 0.48

WP_017609861.1 WP_017611443.1 WP_017610867.1 WP_017610090.1 WP_017610192.1 WP_017610183.1

ResB protein Stomatin/prohibitin protease 30S ribosomal protein S20 50S ribosomal protein L27 50S ribosomal protein L22 50S ribosomal protein L18

1.26 1.86 3.36 3.72 2.51 2.29

3.92 3.84 0.90 0.61 0.69 0.61

4.93 7.16 3.04 2.28 1.72 1.40

WP_017610180.1 WP_017610181.1 WP_017610580.1 WP_017609198.1 WP_017610809.1 WP_017611070.1

50S ribosomal protein L15 50S ribosomal protein L30 Peptidase Antimicrobial peptidase SdpC Beta-lactamase class D Beta-lactamase

2.58 2.83 0.38 2.48 1.16 2.70

0.56 0.30 2.03 4.41 4.36 1.46

1.44 0.85 0.77 10.93 5.08 3.95

WP_017607840.1 WP_017611485.1 WP_017607382.1 WP_017611299.1 WP_017609226.1 WP_017607066.1 WP_017607483.1 WP_017607665.1 WP_017609679.1

Beta-lactamase TEM Fusaric acid resistance protein-like FUSC_2 L,D-transpeptidases-like Cell wall-active antibiotics response protein Antimicrobial peptidase SdpC Virulence and protective immunity protein Ribonucleotide-diphosphate reductase subunit beta Tn3 transposase Holliday junction resolvase

3.67 0.71 3.00 2.17 4.53 1.02 0.93 1.79 0.58

1.35 4.66 0.59 3.01 0.32 0.38 0.44 2.51 0.44

4.95 3.30 1.76 6.52 1.44 0.39 0.42 4.50 0.26

Nitrogen and amino acid metabolism

Glycolysis Lipid metabolism

Translation, protein folding, RNA/protein processing

Secondary metabolism synthesis

Nucleotide transport and metabolism DNA replication, recombination and

38


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Table 4．Summary of quantitative data: unknown function Function

Proteins

Description

10%/6%

17.5%/10%

17.5%/6%

Unknown

WP_017609107.1 WP_017608991.1

Membrane protein

2.18

5.02

10.92

Hypothetical protein

2.71

3.52

9.54

WP_017610992.1


2.38

3.70

8.82

WP_017608093.1


1.85

3.21

5.95

WP_017574925.1

Integral membrane proteins

3.06

2.53

7.73

WP_017609269.1


2.74

2.80

7.68

WP_017608113.1


2.75

2.34

6.42

WP_017609129.1


1.40

4.23

5.92

WP_017611340.1


4.89

0.95

4.65

WP_017607945.1


3.81

1.25

4.74

WP_017578042.1

MULTISPECIES: hypothetical protein

3.33

1.36

4.53

WP_017610034.1


2.90

0.73

2.12

WP_017609799.1


1.49

1.09

1.62

WP_017611013.1


2.79

0.62

1.74

WP_017609079.1


0.72

2.06

1.48

WP_017607724.1


2.43

0.35

0.84

WP_017609214.1


2.36

0.32

0.76

WP_017607796.1


0.21

2.10

0.44

WP_017609749.1


0.95

0.53

0.50

WP_017608543.1


0.94

0.36

0.34

WP_017609359.1


0.28

0.74

0.21

39



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Figure Legends: Figure 1. Morphological characteristics of salt tolerance and growth curves of N. xinjiangensis under different NaCl concentrations. (A) Strain YIM 90004T, grown on agar media containing varied NaCl concentrations. (B) The growth curve of the strain grown in liquid media determined at OD600. (C) The growth curve of the strain grown in liquid media by cell dry weight measurement.

Figure 2. The flow chart for the proteomic profiling. (A) Overview of iTRAQ methodology for multiplexed comparative analysis. (B) 10% SDS-PAGE separation and excision of N. xinjiangensis membrane proteins under different NaCl concentrations.

Figure 3. Analysis of identification and quantification of proteins using LC-MS/MS and iTRAQ. (A) Labelled peptides analyzed by LC-MS/MS. (B) The majority of the peptides labeled with the four tags at a ratio of 1:1:1:1. (C) Some representative peptide ratios showed significant variations at different salt concentrations. (D) Detailed information of reproducibility of two replicates. The square of the Pearson correlation coefficient was 0.9993. (E) Good correlation between the 114 and 115 tags was shown with the standard deviation 40


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(SD) of 0.1. (F) Differential expression of proteins under different salinities showed in the distributions of the ratios of log2 (6%/10%), log2 (6%/17.5%) and log2 (10%/17.5%).

Figure 4. Comparison of identification, quantification and expression abundance between total proteins and membrane proteins. (A) The venn diagram showing the overlap of proteins quantified from the total identified proteins. The number of proteins quantified in all three samples analyzed according to the criteria described in the “Experimental Procedures "is indicated. (B) The venn diagram of α-helical membrane proteins as predicted by TOPCONS-single, PHOBIUS, TMHMM, and SCAMPI methods. (C) The venn diagram showing overlap of predicted and quantified membrane proteins based on α-helical and β-barrel structures. (D) A scatter plot displays the iTRAQ expression ratios of total quantified proteins across ion intensities. (E) The determination of significantly altered quantified membrane proteins. A scatter plot displays the iTRAQ expression ratios of membrane proteins across ion intensities.

Figure 5. The iTRAQ ratios for membrane proteins grouped into different functional groups and two typical protein expression patterns shown in regulated clusters. (A) iTRAQ ratio values for membrane proteins quantified from the 6%, 10%, and 17.5% 41



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samples grouped into regulatory proteins (ABC transporters, symporters, antiporters, other transporters, cell cycle-related, transcriptional regulators, and kinases). (B) iTRAQ ratio values for membrane proteins quantified from the 6%, 10%, and 17.5% samples grouped into central metabolism proteins clusters (Krebs’ cycle, energy metabolism, nitrogen metabolism, amino acid metabolism, glycolysis, lipid metabolism, translation and protein folding, RNA processing, secondary metabolism, nucleotide transport and metabolism, and DNA replication and recombination). (C) Two typical protein expression profiles were predominantly observed in the majority of 126 differential proteins. (D) Differential protein groups were clustered into two typical protein expression models.

Figure 6. Sensitivity and adaptation of ABC transporters in different salt environments. (A) Neighbor-joining tree based on protein sequences showing the phylogenetic relationship of ABC transporters. Proteins involved in compatible solute transport in ABC families were clustered in the bottom group, while proteins related to ion, amino acid, and peptide transport were clustered in the top groups. (B) Proteins involved in compatible solute transport were shown to be up-regulated with increasing NaCl concentration, whereas ion transporters and amino acid transporters were only significantly up-regulated at the optimum NaCl salt concentration. Various compatible ABC transporters showed different expression patterns after salt stress. (C) The cell growth curve after adding BS-12 at 0h and during the mid-logarithmic growth 42


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phase. (D) Effects of BS-12 on bacterial mycelium. (E) Effects of BS-12 on spore germination. (F) Effects of BS-12 on cells cultured at different salinities. (G) pH variation of liquid media with developmental times at different NaCl concentrations.

Figure 7. Sensitivity and adaptation of cell differentiation related proteins in different salt environments. (A) Neighbor-joining tree based on protein sequences showing the phylogenetic relationship of cell differentiation-related protein expression. The cell differentiationrelated proteins also exhibited a conspicuous dually-regulated profile. (B) Strain YIM 90004T grown on sterilized glass cover slips in 6% (top panel), 10%, (middle panel) and 17.5% (bottom panel) solid media visualized by scanning election microscopic observation. (C) Degree of cell motility on swarm diameters. The same inoculation scale was cultured in liquid media and was added at different NaCl concentrations in solid media.

Figure 8. Proposed major strategies of membrane proteins in hypersaline environments based on quantitative proteomics studies. (A) The overall halophilic N.xinjiangensis response and adaption to hypersalinity is a well43



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organized and complex process. It includes salinity signal sensing and transmission, cell cycle reprogramming, ion and metabolite transport, and repair and defense systems. Nutrient and waste products are transported across membranes under higher salinity by primary active transporters, secondary active transporters, and some channels. ABC transporters and other membrane proteins also take part in repair and defense processes. (B) YIM 90004T show phenotypic differences, and their membrane proteins also show differences in expression levels. At optimum NaCl concentrations, the cells could maintain normal growth by reprogramming differentiation. The compatible solute ABC transporters, Na+-dependent transporters (antiporters, symporters, and others), cell motility, and energyrelated proteins played a greater role at high salinity

44


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For TOC only 87x46mm (300 x 300 DPI)



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Figure 1 176x137mm (300 x 300 DPI)


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Figure 2 171x143mm (300 x 300 DPI)



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Figure 3 234x242mm (300 x 300 DPI)


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Figure 4 234x203mm (300 x 300 DPI)



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Figure 5 229x306mm (300 x 300 DPI)


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Figure 6 172x235mm (300 x 300 DPI)



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Figure 7 160x235mm (300 x 300 DPI)


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Figure 8 173x227mm (300 x 300 DPI)


Quantitative Proteomics Reveals Membrane Protein-Mediated

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