Quantitative Proteomics Reveals Potential Crosstalk between a Small

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Quantitative proteomics reveals potential crosstalk between a small RNA CoaR and a two-component regulator Slr1037 in Synechocystis sp. PCC6803 Tao Sun, Lei Chen, and Weiwen Zhang J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00243 • Publication Date (Web): 05 Jul 2017 Downloaded from http://pubs.acs.org on July 5, 2017

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Journal of Proteome Research is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

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Quantitative proteomics reveals potential crosstalk between a small RNA CoaR and a two-component regulator Slr1037 in Synechocystis sp. PCC6803

Tao Sun1,2,3, Lei Chen1,2,3,*, Weiwen Zhang1,2,3,4

1

Laboratory of Synthetic Microbiology, School of Chemical Engineering & Technology,

Tianjin University, Tianjin 300072, P.R. China;

2

Key Laboratory of Systems

Bioengineering (Ministry of Education), Tianjin University, Tianjin, 300072, P.R. China; 3

SynBio Research Platform, Collaborative Innovation Center of Chemical Science and

Engineering, Tianjin, 300072, P.R. China; 4 Center for Biosafety Research and Strategy, Tianjin University, Tianjin, P.R. China. * To whom all correspondence should be addressed:

Prof. Dr. Lei Chen Laboratory of Synthetic Microbiology School of Chemical Engineering & Technology Tianjin University, Tianjin 300072, P. R. China Tel : 0086-22-2740-6394 Email: [email protected]

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ABSTRACT

Bacterial small RNAs (sRNAs) and two-component systems (TCSs) were two vital regulatory mechanisms employed by microorganisms to respond to environmental changes and stresses. As a promising “autotrophic cell factory”, photosynthetic cyanobacteria have attracted a lot of concentrations these years. Though most studies focused on studying the roles of sRNAs or TCS regulators in stress response in photosynthetic cyanobacteria, limited work has elucidated their potential crosstalk. Our previous work has identified a negative sRNA regulator CoaR and a positive response regulator Slr1037 both related with 1-butanol stress regulation in Synechocystis sp. PCC6803. In this work, the potential crosstalk between CoaR and Slr1307 (i.e., the coregulated genes mediated by CoaR and Slr1037) were identified and validated through quantitative proteomics and quantitative real time PCR (qRT-PCR), respectively. The results showed that the sensitive phenotype to 1-butanol of Δslr1037 could be rescued by suppressing coaR in Δslr1037, probably due to that some target genes of Slr1037 could be re-activated by repression of CoaR. 28 co-regulated proteins mediated by CoaR and Slr1037 were found through quantitative proteomics and 10 of the annotated proteins were validated via qRT-PCR. This study proved the existence of crosstalk between sRNAs and response regulators and provided new insights for the coregulation of biofuel resistance in cyanobacteria.

Keywords: Synechocystis, crosstalk, small RNA, response regulator

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INTRODUCTION

Bacterial small RNAs (sRNAs) and two-component systems (TCSs) were two important regulatory mechanisms allowing microorganisms to sense and respond to environmental changes and stress conditions.1-2 Bacterial sRNAs including trans-acting and cis-acting sRNAs, are a kind of non-coding molecules with a typical length of about 50-300 nt.1 Commonly, trans-encoded sRNAs transcribe from the intergenic regions and function by base pairing with target transcripts through limited and imperfect complementarity, resulting in altered translation or stability3 while cis-encoded sRNAs transcribing from the complementary strand of the known open reading frames (ORFs), could regulate the expression of their target genes via perfect base paring.1 For TCSs, each of them contains a histidine kinase (Hik) serving as a sensor to perceive a specific environmental stimulus and a corresponding response regulator (RR) to regulate the expression level of target genes.4 Besides the participation in biological processes such as sRNAs in bacterial virulence, quorum sensing1 and TCSs in membrane porin regulation5 and cell communications,6 recent studies have found the crucial roles of sRNAs and TCSs in bacterial stress responses like temperature stress, nutrient stress, oxidative stress and pH stress.7 Intriguingly, though most studies focused on the individual roles of a single sRNA or TCS regulator in stress response, recent work has identified the broadly defined crosstalk among sRNAs, TCSs or even between the sRNAs and mRNAs/proteins.8-10 In Escherichia coli, a 207 nt sRNA GlmZ could activate the expression a glucosamine-

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6-phosphate (GlcN6P) synthesizing enzyme GlmS while GlmZ itself could also be inactivated by an adaptor protein RapZ during a specific endonucleolytic cleavage event.11 Notably, when intracellular GlcN6P was limit, another sRNA GlmY would have a crosstalk with GlmZ by competitively binding with RapZ to activate the accumulation of GlmZ12. In another study, Zhang et al. (2001) proved the synergistic crosstalk among three transcriptional regulators (TRs) YRR1, Pdr1 and Pdr3 in Saccharomyces cerevisiae. YRR1, Pdr1 and Pdr3 could co-regulate a drug resistancerelated gene YOR1.8 On the contrary, Bielecki et al. (2015) investigated the antagonistic crosstalk between two RRs PhoB and TctD in Pseudomonas aeruginosa, finding that the two RRs had same target genes but regulated them in the opposite direction.10 Further, crosstalk between sRNAs and proteins like ABC transporters were discovered recently in Salmonella enterica, in which an ABC transporter generated a stable fragment to base-pair with a sRNA GcvB to trigger its degradation by RNase E, thus to alleviate the repression of other amino acid-related transport and metabolic genes mediated by GcvB.13 On the other hand, it remains interesting and worth investigating whether crosstalk existed between sRNAs and RRs. Photosynthetic cyanobacteria are a large group of gram-negative prokaryotes which are able to utilize CO2 and sunlight directly for growth. In recent years they have been proposed as “autotrophic cell factories” for biofuels production.14 In model cyanobacteria like Synechocystis sp. PCC6803 (hereafter Synechocystis), multiple sRNAs have been identified and characterized,15 including IsrR functioning as a negative regulator of the CP43 homolog IsiA, As1_flv4 as a negative regulator involved 4



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in inorganic carbon shifts, PsbA2R and PsbA3R as positive regulators to stabilize target mRNAs as well as PsrR1 controlling photosynthetic functions.15 Recently NsiR4 was found involved in nitrogen assimilation control and PmgR1 was related with photomixotrophic growth as well as the regulation of glycogen accumulation.16-17 For TCSs of Synechocystis, more than 90 genes were believed to encode a Hik or RR protein.14 Among them, several proteins have been functionally characterized and proved to be related with various biological processes as well as abiotic stress,7, 18 while the potential crosstalk between these two regulation systems have never been investigated. In our previous work, several proteins including two RRs (i.e., Slr1037 and Sll0039) and four TRs (i.e., Sll0794, Sll1392, Sll1712 and Slr1860) were identified respectively related to 1-butanol and ethanol tolerance in Synechocystis using functional genomics approach19-22. Recently, our work found a novel sRNA CoaR could also regulate the tolerance of Synechocystis to 1-butanol23. As Slr1037 has also been proved related with 1-butanol tolerance thus it was worth investigating whether crosstalk (i.e., co-regulated proteins) existed between CoaR and Slr1037 under 1butanol stress. In this work, coaR was suppressed by overexpressing its antisense fragment in Δslr1037 named as Δslr1037-CoaR(-), resulting in a rescued phenotype to 1-butanol stress. By investigating the proteomic differences among wild type Synechocystis (WT), Δslr1037 and Δslr1037-CoaR(-) using quantitative isobaric tags for relative and absolute quantification (iTRAQ) liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic analysis, the co-regulated proteins regulated by 5


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CoaR and Slr1037 were identified and then validated using qRT-PCR, revealing the potential crosstalk between them. This study proved the existence of crosstalk between sRNAs and RRs and provided new insights for the co-regulation of biofuel resistance in cyanobacteria.

EXPERIMENTAL PROCEDURES

Bacterial growth conditions

For Synechocystis, WT, mutants and the constructed strains were grown on BG-11 agar plate or in medium (pH 7.5) under a light intensity of approximately 50 μmol photons m-2 s-1 in an illuminating incubator or shaking incubator at 130 rpm at 30 oC.24 Medium for different mutants and constructed strains in this study were supplemented with appropriate antibiotic(s) when necessary (i.e., 10 μg/mL chloramphenicol or/and 10 μg/mL kanamycin). For E. coli, DH 5α were grown on LB agar plate or in LB medium with appropriate antibiotic(s) to maintain plasmids (i.e., 100 μg/mL ampicillin, 50 μg/mL kanamycin) at 37 oC using incubator or shaking incubator at 200 rpm, respectively.

Mutant strains construction

E. coli DH5α strain was used for vectors construction and enrichment. Primers used in this study were listed in Table S1. All the strains and plasmids used in this study were 6



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listed in Table 1. In our previous work, the TCS gene slr1037 in WT was deleted by replacing with a chloramphenicol resistance cassette (Δslr1037);19 the coaR was suppressed by overexpressing the antisense fragment of coaR in WT (CoaR(-)).23 In this work, slr1037 and the antisense fragment of coaR was amplified from genome of Synechocystis and introduced with XbaI and BamHI restriction sites. Then two fragments were respectively ligated to a broad host replicating vector pJA2 with kanamycin resistance cassette (kindly provided by Prof. Paul Hudson of KTH Royal Institute of Technology of Sweden), generating pJA2-CoaR(-) and pJA2-Slr1037.25-26 Both Δslr1037 and WT were transformed with pJA2-Slr1037, leading to a complementation strain Δslr1037-Slr1037 and an overexpression strain WT-Slr1037. pJA2-CoaR(-) was introduced into Δslr1037 to make Δslr1037-CoaR(-). The transformation was performed by electroporation (~10 ng plasmid DNA) using GenePulser XcellTM (Bio-Rad, CA, USA) and grown photoautotrophically on agar plate adding 10 μg/mL kanamycin (and 10 μg/mL chloramphenicol when necessary), All the transformants were validated by colony PCR. Table 1. Strains and plasmids used in this study. Genotype

References

E. coli strains DH 5α

F– endA1 glnV44 thi-1 recA1 relA1 gyrA96 deoR nupG purB20 –

φ80d lacZΔM15 Δ(lacZYA-argF) U169, hsdR17(rK mK ), λ +

Stratagene

–

Synechocystis strains WT CoaR(-)

Wild-type Synechocystis sp. PCC6803 pJA2::PpsbA2-reverse complementary sequence of CoaR, Km

ATCC27184 R

[23]

in WT WT-Slr1037

pJA2::PpsbA2-slr1037, KmR in WT

this study

Δslr1037

slr1037::CmR

[19]

Δslr1037-pJA1037

pJA2::PpsbA2-slr1037, Km in Δslr1037 R

7


this study

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Δslr1037-CoaR(-)

pJA2::PpsbA2-reverse complementary sequence of CoaR, KmR

this study

in Δslr1037 plasmids pJA2

[25,26]

Reverse transcriptional PCR (RT-PCR)

Total RNA extraction of Δslr1037-CoaR(-) and Δslr1037 were achieved through a Direct-zol™ RNA MiniPrep Kit (Zymo, CA, USA). Approximately 10 mg of cell pellets were frozen by liquid nitrogen immediately after centrifugation and then following the manufacturer’s protocol. cDNAs were synthesized using specific reverse primer of CoaR named RT-CoaR-R (Table S1) and SuperScript® VILO™ cDNA Synthesis Kit following manufacturer’s protocol (Invitrogen, Carlsbad, CA). Then 1 μL cDNA was used as template for RT-PCR using primer RT-CoaR-F and RT-CoaR-R.23

Growth patterns

Cell density was measured on an ELx808 Absorbance Microplate Reader (BioTek, VT, USA) at OD630. For growth and 1-butanol treatment, 5 mL fresh cells at OD630 of 0.04 were collected by centrifugation and were then inoculated into 25 mL of BG11 liquid medium in a 100 mL flask. Culture samples were taken and measured at OD630 every 12 h.23 For biofuels treatment, 0.20% (v/v) 1-butanol were added at beginning of the cultivation. Growth experiments were repeated at least three times to confirm the growth patterns.

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Quantitative proteomics

For quantitative proteomics analysis, samples composed of the WT, Δslr1037 and Δslr1037-CoaR(-) were harvested after cultivation for 48 h under 0.20 % (v/v) 1butanol stress, each with two biological replicates. Protein preparation and digestion, iTRAQ labeling, LC-MS/MS proteomic analysis and proteomic data analysis were the same as before.27 Briefly, cell samples for proteomics analysis were collected by centrifugation at 8000 x g for 10 min at 4 oC then immediately frozen in liquid nitrogen. Then the quantitative proteomics were performed as follows: i). Protein extraction, concentration measurement, SDS-PAGE and protein digestion. For SDS-PAGE, 30 μg protein from each sample was mix briefly in equivalent loading buffer at 95 oC in heat block for 5 minutes. The concentration of gel was 12% and the electrophoresis was taken for 2 hours on 120 V. When electrophoresis was completed, the gel was dyed by dyeing buffer for 2hours and destained by destain buffer for 30 m (using for quality control; data not shown). For protein digestion, Digest the protein with Trypsin Gold with the ratio of protein: trypsin=20:1 at 37 oC for 4 h (the digestion process was performed one more for 8 h unceasingly). ii). The iTRAQ labeling. After trypsin digestion, the peptides were dried by vacuum centrifugation. The samples were dissolved with 0.5 M triethylamine borane. Then the iTRAQ labeling of peptide samples were performed using iTRAQ Reagent 8-plex Kit (Applied Biosystems, CA, USA) according to the manufacturer's protocol and the peptides were labeled with respective isobaric tags for 2 h’s incubation (8-plex-113 for WT-1, 8-plex-114 for WT2, 8-plex-115 for Δslr1037-1, 8-plex-116 for Δslr1037-2, 8-plex-119 for Δslr10379


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CoaR(-)-1 and 8-plex-121 for Δslr1037-CoaR(-)-2). After that, the iTRAQ labeled peptides were fractionated using LC-20AB HPLC Pump system SCX chromatography (Shimadzu, Kyoto, Japan). The iTRAQ labeled peptide mixtures were reconstituted with 4 mL buffer A (25 mM NaH2PO4 in 25% ACN, pH 2.7) and loaded onto a 4.6×250 mm Ultremex SCX column containing 5-μm particles (Phenomenex, CA, USA). The peptides were eluted at a flow rate of 1 mL/min with a gradient of buffer A for 10 min, 5-60% buffer B (25 mM NaH2PO4, 1 M KCl in 25% ACN, pH 2.7) for 27 min, 60-100% buffer B for 1 min. The system was then maintained at 100% buffer B for 1 min before equilibrating with buffer A for 10 min prior to the next injection. iii). LC-ESI-MS/MS analysis based on Q EXACTIVE. Each fraction was re-suspended in buffer A (5% acetonitrile, 0.1% formic acid) and centrifuged at 20000 x g for 10 min, the final concentration of peptide was about 0.5 μg/μL on average. 10 μL supernatant was loaded on a LC-20AD nanoHPLC (Shimadzu, Kyoto, Japan) by the auto-sampler onto a 2 cm C18 trap column (inner diameter 200 μm, Waters, MA, USA). Then, the peptides were eluted onto a 10 cm analytical C18 column (inner diameter 75 μm, 5-μm resin, 300 Å, Waters, MA, USA) packed in-house. The samples were loaded at 8 μL/min for 4 min, then the 35 min gradient was run at 300 nL/min starting from 2 to 35% buffer B (95% acetonitrile, 0.1% formic acid), followed by 5 min linear gradient to 60%, then, followed by 2 min linear gradient to 80%, and maintenance at 80% buffer B for 4 min, and finally return to 5% in 1 min. The peptides were then subjected to nanoelectrospray ionization followed by tandem mass spectrometry (MS/MS) in an Q EXACTIVE (Thermo Fisher Scientific, CA, USA) coupled online to the HPLC. Intact peptides were 10



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detected in the Orbitrap at a resolution of 70000. The MS was operated with a RP of greater than or equal to 30 000 FWHM for TOF MS scans. For IDA, survey scans were acquired in 250 ms and as many as 30 product ion scans were collected if exceeding a threshold of 120 counts per second (counts/s) and with a 2+ to 5+ charge-state. Peptides were selected for MS/MS using high-energy collision dissociation operating mode with a normalized collision energy setting of 27.0; ion fragments were detected in the Orbitrap at a resolution of 17500. A data-dependent procedure that alternated between one MS scan followed by 15 MS/MS scans was applied for the 15 most abundant precursor ions above a threshold ion count of 20000 in the MS survey scan with a following Dynamic Exclusion duration of 15 s. The electrospray voltage applied was 1.6 kV. Automatic gain control (AGC) was used to optimize the spectra generated by the orbitrap. The AGC target for full MS was 3e6 and 1e5 for MS2. For MS scans, the m/z scan range was 350 to 2000 Da. For MS2 scans, the m/z scan range was 100-1800. iv). Bioinformatics pipeline. Raw data files acquired from the Orbitrap were converted into MGF files using Proteome Discoverer 1.2 (PD 1.2; Thermo Fisher Scientific, CA, USA) and the MGF file were searched. Proteins identification were performed by using Mascot search engine (Matrix Science, London, UK; version 2.3.02) (Parameters: Enzyme-Trypsin; Fragment Mass Tolerance-0.05 Da; Mass Values-Monoisotopic; Variable modifications-Oxidation (M), iTRAQ8plex (Y); Peptide Mass Tolerance-20 ppm; Fixed modifications-Carbamidomethyl (C), iTRAQ8plex (N-term), iTRAQ8plex (K); Database-I-mhHDQ003 (3827 sequences)). For an MS/MS Ions Search, each query represents a complete MS/MS spectrum, and is delimited by a pair of statements. 11


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For protein identification, a mass tolerance of 20 Da(ppm) was permitted for intact peptide masses and 0.05 Da for fragmented ions, with allowance for one missed cleavages in the trypsin digests and FDR

Quantitative Proteomics Reveals Potential Crosstalk between a Small

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