# REGULATORY POTENTIAL OF POST-TRANSLATIONAL MODIFICATIONS IN BACTERIA

EDITED BY: Ivan Mijakovic, Christophe Grangeasse and Jörg Stülke PUBLISHED IN: Frontiers in Microbiology

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ISSN 1664-8714 ISBN 978-2-88919-610-4 DOI 10.3389/978-2-88919-610-4

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## **REGULATORY POTENTIAL OF POST-TRANSLATIONAL MODIFICATIONS IN BACTERIA**

Topic Editors:

**Ivan Mijakovic,** Chalmers University of Technology, Sweden **Christophe Grangeasse,** Bases Moléculaires et Structurales des Systèmes Infectieux, UMR5086, CNRS, University of Lyon, Lyon, France **Jörg Stülke,** University of Göttingen, Germany

Post-translational modifications (PTMs) are widely employed by all living organisms to control the enzymatic activity, localization or stability of proteins on a much shorter time scale than the transcriptional control. In eukarya, global analyses consistently reveal that proteins are very extensively phosphorylated, acetylated and ubiquitylated. Glycosylation and methylation are also very common, and myriad other PTMs, most with a proven regulatory potential, are being discovered continuously. The emergent picture is that PTM sites on a single protein are not independent; modification of one residue often affects (positively or negatively) modification of other sites on the same protein. The best example of this complex behavior is the histone "bar-code" with very extensive cross-talk between phosphorylation, acetylation and methylation sites.

Traditionally it was believed that large networks of PTMs exist only in complex eukaryal cells, which exploit them for coordination and fine-tuning of various cellular functions. PTMs have also been detected in bacteria, but the early examples focused on a few important regulatory events, based mainly on protein phosphorylation. The global importance (and abundance) of PTMs in bacterial physiology was systematically underestimated. In recent years, global studies have reported large datasets of phosphorylated, acetylated and glycosylated proteins in bacteria. Other modifications of bacterial proteins have been recently described: pupylation, methylation, sirtuin acetylation, lipidation, carboxylation and bacillithiolation. As the landscape of PTMs in bacterial cells is rapidly expanding, primarily due to advances of detection methods in mass spectrometry, our research field is adapting to comprehend the potential impact of these modifications on the cellular physiology. The field of protein phosphorylation, especially of the Ser/Thr/Tyr type, has been profoundly transformed. We have become aware that bacterial kinases phosphorylate many protein substrates and thus constitute regulatory nodes with potential for signal integration. They also engage in cross-talk and eukaryal-like mutual activation cascades. The regulatory potential of protein acetylation and glycosylation in bacteria is also rapidly emerging, and the cross-talk between acetylation and phosphorylation has been documented.

This topic deals with the complexity of the PTM landscape in bacteria, and focus in particular on the physiological roles that PTMs play and methods to study them. The topic is associated to the 1st International Conference on Post-Translational Modifications in Bacteria (September 9-10, 2014, Göttingen, Germany).

**Citation:** Mijakovic, I., Grangeasse, C., Stülke, J., eds. (2015). Regulatory Potential of Post-Translational Modifications in Bacteria. Lausanne: Frontiers Media. doi: 10.3389/978-2-88919-610-4

# Table of Contents

Kehilwe C. Nakedi, Andrew J. M. Nel, Shaun Garnett, Jonathan M. Blackburn and Nelson C. Soares

*20 Phosphoproteome of the cyanobacterium* **Synechocystis** *sp. PCC 6803 and its dynamics during nitrogen starvation*

Philipp Spät, Boris Maˇcek and Karl Forchhammer

Boumediene Soufi, Karsten Krug, Andreas Harst and Boris Macek

*76 Post-translational modifications are key players of the* **Legionella pneumophila**  *infection strategy*

Céline Michard and Patricia Doublet

Liang Zhou, Auke J. van Heel and Oscar P. Kuipers

Laura M. van Staalduinen and Zongchao Jia

*133 Interaction between extracellular matrix molecules and microbial pathogens: evidence for the missing link in autoimmunity with rheumatoid arthritis as a disease model*

Nidhi Sofat, Robin Wait, Saralili D. Robertson, Deborah L. Baines and Emma H. Baker

*139 Factors that mediate and prevent degradation of the inactive and unstable GudB protein in* **Bacillus subtilis**

Lorena Stannek, Katrin Gunka, Rachel A. Care, Ulf Gerth and Fabian M. Commichau

Martha V. Radchenko, Jeremy Thornton and Mike Merrick

Lei Shi, Nathalie Pigeonneau, Vaishnavi Ravikumar, Paula Dobrinic, Boris Macek, Damjan Franjevic, Marie-Francoise Noirot-Gros and Ivan Mijakovic

*195 Production of a recombinant vaccine candidate against* **Burkholderia pseudomallei** *exploiting the bacterial* **N***-glycosylation machinery*

Fatima Garcia-Quintanilla, Jeremy A. Iwashkiw, Nancy L. Price, Chad Stratilo and Mario F. Feldman

## Regulatory potential of post-translational modifications in bacteria

#### Christophe Grangeasse1 , Jörg Stülke2 and Ivan Mijakovic3 \*

1 Bases Moléculaires et Structurales des Systèmes Infectieux, UMR 5086, Centre National de la Recherche Scientifique, University of Lyon, Lyon, France, 2 Department of General Microbiology, Institute for Microbiology and Genetics, University of Göttingen, Göttingen, Germany, 3 Systems and Synthetic Biology Division, Department of Biology and Biological Engineering, Chalmers University of Technology, Göteborg, Sweden

#### Keywords: phosphorylation, S-thiolation, dehydration, hydroxylation, N-glycosylation, protein kinases, antimicrobial peptides, proteomics

Bacteria are often viewed as simple organisms, with very basic and robust cellular regulation, optimized for rapid growth. While they certainly fit that description, bacteria also possess an amazing capacity for adaptation, and diversity of survival strategies, including variations of cell morphology, size, mode of growth and developmental behavior. Post-translational modifications (PTMs) of proteins contribute significantly to bacterial adaptability and cell cycle control. Research on PTMs in bacteria started with the assumption that they lack many features regularly found in more complex organisms. However, ongoing investigation keeps revealing new types of PTMs of bacterial proteins. This research topic gathers a number of articles discussing the advanced methods for systematic study of bacterial PTMs, approaches to utilize PTMs for biotechnological purposes, and revealing new cellular functions controlled by PTMs.

#### Edited by:

Thomas E. Hanson, University of Delaware, USA

#### Reviewed by:

Jerry Eichler, Ben Gurion University of the Negev, Israel

\*Correspondence: Ivan Mijakovic<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology

> Received: 25 April 2015 Accepted: 06 May 2015 Published: 28 May 2015

#### Citation:

Grangeasse C, Stülke J and Mijakovic I (2015) Regulatory potential of post-translational modifications in bacteria. Front. Microbiol. 6:500. doi: 10.3389/fmicb.2015.00500

Most bacterial PTMs are dynamic and reversible. This allows the cell to exploit them as regulatory devices. It also means that the full understanding of the cellular roles of different PTMs necessitates global, quantitative and time-resolved studies. One seminal paper in this topic reports a novel proteomics approach for such quantitative studies: the Intensity Based Absolute Quantitation (iBAQ). Using this approach, the authors have quantified the expression and the occupancy of various PTM sites in the proteome of Escherichia coli (Soufi et al., 2015). The authors report remarkable differences in expression and occupancy of PTMs sites under different growth conditions. The dataset comprised 2300 proteins, which is close to 90% of the expressed proteome. This is an important landmark, since proteomics in general has not yet attained the same level of coverage that global transcriptome studies can achieve.

Among different bacterial PTMs, protein phosphorylation is the most extensively studied one, and in this topic it features prominently. Several papers present global studies of protein phosphorylation in bacteria (Spät et al., 2015), including important bacterial pathogens (Fortuin et al., 2015; Nakedi et al., 2015). The focus on pathogens is understandable, since protein phosphorylation, and several other PTMs, are heavily involved in different infection strategies displayed by bacterial pathogens (Michard and Doublet, 2015). In addition to phosphoproteome studies, interactomics is also featured as a useful approach to chart the phosphorylationbased regulatory networks. It enables researchers to trace the connections among protein kinases, phosphatases, and their substrates (Shi et al., 2014a). This approach for reconstructing phosphorylation networks highlights the capacity of bacterial proteins kinases from different families to interact with, and phosphorylate, each other (Shi et al., 2014b). Protein-tyrosine kinases, and their various roles in bacterial physiology were in the focus of several review and opinion articles in this topic (Barák, 2014; Gerwig and Stülke, 2014; Mijakovic and Deutscher, 2015).

Other topic contributions highlight the broad spectrum of PTMs involved in key cellular processes. In particular, novel modifications are discussed: redox regulation via reversible Sthiolation (Loi et al., 2015), post-translational hydroxylation (van Staalduinen and Jia, 2015) and the role of citrullination for the interaction between bacteria and human mucosal surfaces (Sofat et al., 2015). Several experimental papers report studies on post-translationally modified antimicrobial peptides known as lantibiotics. These are ribosomally synthesized peptides which can efficiently inhibit the growth of Gram-positive bacteria. A study by Zhou et al. (2015) described an engineering strategy to make the lantibiotics more effective in inhibiting several important bacterial pathogens. In another study, Khusainov et al. (2015) describe the active site of the nisin dehydratase. This enzyme, essential for the production of the lantibiotic nisin, converts serines, and threonines, to dehydroalanine and dehydrobutyrine residues, respectively. Interestingly, bacterial PTM systems, such as the N-glycosylation machinery, are also being exploited and engineered to facilitate the production of recombinant vaccines (Garcia-Quintanilla et al., 2014). Another focal point of the topic are the PTMs targeting the PII proteins,

#### References

which are the key signal transduction proteins involved in the control of nitrogen metabolism in bacteria and archaea (Radchenko et al., 2014; Merrick, 2015). Finally, Stannek et al. (2015) contributed a study on a regulatory mechanism involving arginine phosphorylation and regulated proteolysis.

In conclusion, the contributions in this topic reflect the diversity of bacterial PTMs. Several studies highlight one important emergent feature of PTM systems: their capacity to interact with each other, creating an additional level of complexity in the cellular regulation. This is one of the key features of bacterial PTM systems and a challenge which future studies will have to address.

#### Acknowledgments

This topic was organized to accompany the First International Conference on Post-translational Modifications in Bacteria, held in Göttingen (Germany), 9-10 September 2014. We would like to take this opportunity to thank all the conference participants, and especially those who contributed their work to this topic.

tyrosine protein kinases on key regulatory residues. Front. Microbiol. 5:495. doi: 10.3389/fmicb.2014.00495

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Grangeasse, Stülke and Mijakovic. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

## Comparative Ser/Thr/Tyr phosphoproteomics between two mycobacterial species: the fast growing *Mycobacterium smegmatis* and the slow growing *Mycobacterium bovis* BCG

#### *Edited by:*

*Ivan Mijakovic, Chalmers University of Technology, Sweden*

#### *Reviewed by:*

*Chung-Dar Lu, Georgia State University, USA Gustavo Antonio De Souza, University of Oslo, Norway*

#### *\*Correspondence:*

*Jonathan M. Blackburn and Nelson C. Soares, Applied and Chemical Proteomics Group, Division of Medical Biochemistry and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Anzio, Observatory, Cape Town 7925, South Africa<EMAIL_ADDRESS><EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology*

> *Received: 30 November 2014 Accepted: 10 March 2015 Published: 08 April 2015*

#### *Citation:*

*Nakedi KC, Nel AJM, Garnett S, Blackburn JM and Soares NC (2015) Comparative Ser/Thr/Tyr phosphoproteomics between two mycobacterial species: the fast growing Mycobacterium smegmatis and the slow growing Mycobacterium bovis BCG. Front. Microbiol. 6:237. doi: 10.3389/fmicb.2015.00237* Kehilwe C. Nakedi, Andrew J. M. Nel, Shaun Garnett, Jonathan M. Blackburn\* and Nelson C. Soares \*

*Blackburn Lab, Applied Proteomics and Chemical Biology Group, Division of Medical Biochemistry, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa*

Ser/Thr/Tyr protein phosphorylation plays a critical role in regulating mycobacterial growth and development. Understanding the mechanistic link between protein phosphorylation signaling network and mycobacterial growth rate requires a global view of the phosphorylation events taking place at a given time under defined conditions. In the present study we employed a phosphopeptide enrichment and high throughput mass spectrometry-based strategy to investigate and qualitatively compare the phosphoproteome of two mycobacterial model organisms: the fast growing *Mycobacterium smegmatis* and the slow growing *Mycobacterium bovis* BCG. Cells were harvested during exponential phase and our analysis detected a total of 185 phospho-sites in *M. smegmatis*, of which 106 were confidently localized [localization probability (LP) = 0.75; PEP = 0.01]. By contrast, in *M. bovis* BCG the phosphoproteome comprised 442 phospho-sites, of which 289 were confidently localized. The percentage distribution of Ser/Thr/Tyr phosphorylation was 39.47, 57.02, and 3.51% for *M. smegmatis* and 35, 61.6, and 3.1% for *M. bovis* BCG. Moreover, our study identified a number of conserved Ser/Thr phosphorylated sites and conserved Tyr phosphorylated sites across different mycobacterial species. Overall a qualitative comparison of the fast and slow growing mycobacteria suggests that the phosphoproteome of *M. smegmatis* is a simpler version of that of *M. bovis* BCG. In particular, *M. bovis* BCG exponential cells exhibited a much more complex and sophisticated protein phosphorylation network regulating important cellular cycle events such as cell wall biosynthesis, elongation, cell division including immediately response to stress. The differences in the two phosphoproteomes are discussed in light of different mycobacterial growth rates.

Keywords: mycobacteria, phosphoproteome, protein phosphorylation, cell division, growth rate

### Introduction

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB), a major health concern worldwide. The current incidence of tuberculosis disease in South Africa is more than 900 cases per 100,000 people per year. Moreover, the World Health Organisation have estimated that roughly one third of the world's population is latently infected with M. tuberculosis. The majority of latently infected individuals will remain asymptomatic throughout their lives, with the risk of developing active TB disease from a latent infection being ∼10% per lifetime; in HIV positive individuals though, this risk increases to 10% per year (WHO, 2014). This latent infected population is thus a substantial reservoir of potential new TB cases and is therefore a significant public health concern. The ability of mycobacteria to adapt to, and overcome, hostile environmental conditions in order to survive within host cells depends on a fine-tuned and orchestrated series of events (e.g., response to stress; metabolic remodeling; changes in growth rate) that will ultimately define the success of establishing and maintaining long term infection (McKinney et al., 2000; Marrero et al., 2010). M. tuberculosis infection is often described by two distinct phases: an active phase, in which the microorganism is thought to be growing at or close to its maximum rate; and latent infection, in which the bacilli are thought to persist in a viable but perhaps more dormant-like state with lower or non-existent growth rate. Current thinking suggests that there is most likely a continuum of states between latent TB infection (LTBI), subclinical TB and active TB disease, but to date no M. tuberculosis bacilli have been observed in LTBI individuals, so the exact physiological state of M. tuberculosis during a latent infection remains unknown.

Alongside the increasing number of new TB infections there is another matter of great concern, which is the emergence and spread of multi- and extensively drug resistant M. tuberculosis strains. Here unique growth related mechanisms of mycobacteria which facilitate adaptation to different adverse microenvironments are thought to play an important role in the mechanisms of drug tolerance and acquired resistance that are observed during infection (Corper and Cohn, 1933; Wayne and Hayes, 1996). For instance, a recent study showed that diverse growth-limiting stresses trigger a common signal transduction pathway in M. tuberculosis that induces triglyceride synthesis, which is associated with slowing down of growth and reduced antibiotic efficacy (Baek et al., 2011). Therefore, further investigation of the signaling pathways which regulate mycobacterial growth rate might reveal important information regarding the capacity of M. tuberculosis to adapt to its environment and in particular how this relates to drug tolerance and to the ability to establish infection.

In M. tuberculosis, Ser/Thr phosphorylation is essential for growth and environmental adaptation (as reviewed by Kieser and Rubin, 2014). For instance, the Ser/Thr protein kinases (STPKs) PknA and PknB are essential for growth of M. tuberculosis in culture, indicating that phosphorylation plays a pivotal role in the survival of this bacterium (Sassetti et al., 2003; Kang et al., 2005; Fernandez et al., 2006; Molle and Kremer, 2010; Kusebauch et al., 2014). These STPKs are encoded by an operon which regulates genes involved in cell shape determination, cell wall synthesis, and cell division (Deol et al., 2005; Kang et al., 2005; Kusebauch et al., 2014). In addition to PknA and PknB, another group of STPKs comprised of PknG, PknL, and PknF appear to be involved in different aspects of M. tuberculosis growth regulation (Cowley et al., 2004; Deol et al., 2005; Canova et al., 2008). In support of the likely important role played by STPKs in M. tuberculosis, a mass spectrometry-based phosphoproteomic study identified more than 500 Ser/Thr phosphorylation sites on 300 proteins in M. tuberculosis (Prisic et al., 2010) and, more recently, a complementary study detected a number of Tyr phosphorylated proteins in M. tuberculosis (Kusebauch et al., 2014). Notably though, the physiological significance of these findings remains largely unexplored.

In the past years, the use of mycobacterial models such as M. smegmatis and M. bovis BCG have significantly contributed to our current understanding of M. tuberculosis biology and environmental adaptation (as reviewed by Shiloh and Champion, 2010). M. bovis BCG is an attenuated bovine tuberculosis bacillus by a serial passage in the laboratory (Calmette et al., 1921). This mycobacterium is a particular convenient model in part due to it is slow growth rate similar to that observed in M. tuberculosis. On other hand M smegmatis is a fast growing mycobacterial species (with a doubling time of approximately 4 h) that has been widely used to investigate different aspects of mycobacterial physiology (Barry, 2001; Reyrat and Kahn, 2001; Danilchanka et al., 2008). As part of a concerted program to associate protein phosphorylation in mycobacteria with subsequent macromolecular events which determine growth rate and eventual environmental adaption, we have carried out a phosphopeptide enrichment and high throughput mass spectrometry-based study to investigate and compare the phosphoproteome of two model mycobacterial organisms—the fast growing M. smegmatis and the slow growing M. bovis BCG—our goal being to begin to elucidate the phosphorylation events and subsequent signal transduction pathways coordinating differential mycobacterial growth rates, which may in due course lead to important insights into M. tuberculosis physiology during active and latent infection—including aspects of slow growth associated drug resistance.

### Materials and Methods

#### Bacterial Strains

Wild type strains of M. smegmatis mc2 155 and M. bovis BCG Pasteur strain 1173P2 were grown in 7H9 Middlebrook (BD, Maryland, USA) broth supplemented with 0.05% Tween 80, OADC (Becton Dickinson) and 0.2% glycerol (v/v). Cells were grown at 37◦C with continuous agitation (120 rpm).

#### Protein Extraction

Cells were harvested during the exponential phase (OD600 ∼1.2 and 0.6 for M. smegmatis and M. bovis BCG, respectively) by centrifugation at 4000 g for 15 min at 4◦C, washed twice with Phosphate Buffered Saline pH (7.5) (PBS). Cells were snap frozen in liquid nitrogen and stored at -80◦C until needed. Frozen pellets were suspended in 800µl lysis buffer [500 mM Tris-HCl, 0.1% (w/v) SDS, 0.15% sodium deoxycolate, 1× protease inhibitor cocktail, 1× phosphatase inhibitor cocktail (Roche, Mannheim Germany) and 50µg/ml lysozyme (Repaske, 1956)]. Cells were disrupted by sonication at maximum power for six cycles of 30 s, with 1 min cooling on ice between cycles. Cellular debris was removed by centrifugation at 4000 g for 5 min and the lysate filtered through 20µm pore size low-protein binding filters (Merck, NJ, USA). Proteins were precipitated using the chloroform-methanol precipitation method as previously described (Wessel and Flügge, 1984). The pellet was resuspended in urea buffer (6 M urea, 2 M thiourea and 10 mM Tris-HCl, pH 8). Protein concentration was determined using a modified Bradford assay as described by Ramagli (1999).

#### In-Solution Trypsin Digestion

Five milligram of total protein was reduced with 1 mM DTT for 1 h with agitation and then alkylated with 5.5 mM IAA for 1 h in the dark. Proteins were pre-digested with Lysyl Endopeptidase LysC (Waco, Neuss, Germany) at room temperature for 3 h and diluted 4× with HPLC grade water before adding sequencing grade modified trypsin (Promega, Madison, USA) (1:100 w/w). Proteolysis was carried out at room temperature for 14 h with agitation at 30 rpm. Proteolysis was quenched by addition of trifluoroacetic acid (TFA) (Sigma Aldrich, St Louis, USA).

#### Phosphopeptide Enrichment with TiO2 Chromatography

Acetonitrile (ACN) (Sigma Aldrich, St Louis, USA) at a final concentration of 30% was added to the tryptic peptides and the pH was adjusted to 2. Ten milligram of Titasphere TiO2 beads (MZ Analysentechnik, Mainz, Germany) in loading buffer [30 mg/ml 2,5 dihydrobenzoic acid (Sigma Aldrich, St Louis, USA), 80% ACN] were added to the sample and incubated at room temperature with rotation for 1 h. The beads were pelleted and the decanted supernatant was further incubated with a fresh batch of 5 mg of beads for 30 min. This step was repeated one further time, giving three fractions of enriched phosphoproteins bound to beads in total. Phosphopeptides bound to the beads were washed vigorously with shaking for 10 min in 1 ml of wash buffer 1 (30% acetonitrile, 3% trifluoroacetic acid) followed by an additional 10 min of vigorous wash with wash buffer 2 (80% acetonitrile, 0.1% trifluoroacetic acid). Phosphopeptides were loaded onto C8 stage tip, washed with wash buffer 2 and then eluted with 3 × 50 µl Elution buffer [40% Mass-spec grade NH4OH (aq, 25% NH3; Sigma-Aldrich, St Louis, USA), 60% acetonitrile (pH 10.5 or higher)]. Solvent was removed in a speed drying vacuum at room temperature and peptides were resuspended in 20µl Solvent A (2% ACN, 0.1% formic acid).

#### LC/MS/MS Analysis

Liquid chromatography separation was carried out using a precolumn (100µm ID × 20 mm) connected to an analytical column (75µm × 500 mm) packed with C18 Luna 5µ 100 Å beads (phenomenex 04A-5452). The columns were connected to an Easy n-LC II system (Proxeon). 5µl of resuspended phosphopeptides were loaded onto the column with starting mobile phase of 2% ACN, 0.1% formic acid. Peptides were eluted with the following gradient 5% ACN to 35% ACN for 120 min the up to 80% ACN over 5 min staying at 80% ACN for 10 min, this was followed by a column wash of 7 to 80% gradient for 30 min, and a column equilibration at 2% ACN for 2 min. The flow rate was held at 300 nL/min.

Mass spectra were acquired on an Orbitrap Q Exactive mass spectrometer in a data-dependent manner, with automatic switching between MS and MS/MS scans using a "Top-10" method. MS spectra were acquired at a resolution of 70,000 with a target value of 3 × 106 ions or a maximum injection time of 250 ms. Peptide fragmentation was performed via higher-energy collision dissociation (HCD) with the energy set at 25 NCE. Intensity threshold for ions selection was set at 1.7e4 with charge exclusion of z = 1 and z > 5. The MS/MS spectra were acquired at a resolution of 17,500, with a target value of 2 × 105 ions or a maximum injection time of 120 ms. The scan range was limited to 300 to 1750 m/z and the isolation window at 4.0 m/z.

#### Data Processing

Maxquant software package version <IP_ADDRESS> with integrated Andromeda search engine was used to analyse the raw MS spectra acquired. M. smegmatis (taxonomy 246196) and M. bovis BCG Pasteur (taxonomy 410289) databases obtained from Uniprot were used as the target-decoy databases for the Andromeda search. LysC and Trypsin were defined as proteases and two missed cleavages were allowed. Phosphorylation on serine, threonine, and tyrosine residues, oxidation of methionines and Nterminal acetylation were specified as variable modifications. Carbamidomethylation on cysteines was defined as a fixed modification. We allowed a FTMS MS/MS match tolerance of 20 ppm. False discovery rate was set at 1% for identification of peptides and proteins without re-quantifying. Stringent filtering criteria were employed to validate phospho sites. Phosphopeptides were considered as high confidence phosphorylation events and taken for further analysis only if they had a localization probability of >0.75, had a posterior error probability (PEP) score of <0.001. We further manually validated the phospho sites on the Maxquant viewer for good b- and y- ion series coverage.

#### Bioinformatics

Predicted Gene Ontology (GO) cellular functions of identified phosphoproteins with high confidence from two mycobacterium strains were obtained from The Database for Annotation, Visualization and Integrated Discovery (DAVID, v6.7) and were grouped into functional categories. To compare the identified phosphoproteomes of these two mycobacterial species, we identified homologs of the M. smegmatis phosphorylated proteins in M. bovis BCG using the University of Cape Town's Computational Biology online bioinformatics tool found at http://galaxy-fen.uct.ac.za/root. For identification of tyrosinephosphorylation site motifs, we used the Motif-X algorithm (Schwartz, 2005). We defined a sequence window of +/- 10 amino acids on each side of the tyrosine site and generated the sequence logo by Phosphosite logo generator using the algorithm PSP production (Cell signaling Technology). We aligned genomic sequences of both strains using the online tool, obtained from http://www.ebi.ac.uk/Tools/msa/clustalw2/ and respective fasta files were obtained from Uniprot.

### Results and Discussion

There is increasing evidence indicating that protein phosphorylation plays an essential role during mycobacterial cell division and environmental adaptation. Understanding the mechanistic connection between such regulatory signaling networks and mycobacterial growth rate requires a global view of the phosphorylation events taking place at a given time under defined conditions. Here, we have carried out a comparative phosphoproteomic analysis of two mycobacterial strains one fast growing (M. smegmatis), the other slow growing (M. bovis BCG). Our analysis included three rounds of TiO2 chromatography to enrich phosphorylated peptides (see **Supplementary Figure S1**), followed by subsequent analysis of phosphorylation-events using liquid chromatography coupled with state-of-the-art high resolution tandem mass spectrometry (LC/MS/MS) (**Supplementary Figure S2a** and **S2b**), in order to compare the phosphoproteomes of these two model mycobacterium species during exponential growth.

In this study we considered all phosphorylation-events that were detected in any of the biological replicates, and only confidently localized phospho-sites (p-sites) (**Figure 1**), were considered for qualitative comparative analysis and further discussion. In the two M. bovis BCG replicates, we detected a total of 442 p-sites of which 289 were confidently localized (Localization probability (LP) = 0.75; PEP = 0.01) and 169/289 had a LP = 0.99 (**Supplementary Table S1A** and **Figure S2c**). We identified 88,822 MS/MS spectra corresponding to 7784 non-redundant peptide sequences (**Supplementary Figure S2d**) and 1765 protein groups (402 were identified by a single peptide) (**Supplementary Table S1A**). The estimated false discovery rate (FDR) was 0.32 at the peptide level, 0.30 at the modification level, and 1.03 at the protein level. Our initial analysis of two biological replicates of M. smegmatis revealed considerable differences in the number of identified p-sites between the two Mycobacterial species, 77 p-sites for M. smegmatis (**Supplementary Figure S2e**) compared to 289 for M. bovis BCG. To verify that these differences observed were biological, we further analyzed three additional biological replicates for M. smegmatis (**Supplementary Table S1B**). Phosphoproteomic analysis of five biological replicates of M. smegmatis protein extracts resulted in identification of 180, 396 MS/MS spectra, corresponding to 16, 185 non-redundant peptide sequences (**Supplementary Figure S2f**) and 2, 462 protein groups (464 were identified by a single peptide) (**Supplementary Table S1B**). The estimated false discovery rate (FDR) was 0.22 at the peptide level, 0.21 at the modification level, and 0.98 at the protein group level. We detected a total of 185 phospho-sites in M. smegmatis, of

which 106 were confidently localized (LP = 0.75; PEP = 0.01) and 64/106 had a LP = 0.99 (**Supplementary Table S1B**). In detail, for M. bovis BCG, we detected 289 p-sites on 203 phoshoproteins: 35.3% on serine (pSer), 61.6% on threonine (pThr) and 3.1% tyrosine (pTyr). For M. smegmatis we detected 106 p-sites on 76 phosphoproteins: 39.47% on serine (pSer), 57.02% on threonine (pThr) and 3.51% on tyrosine (pTyr). Both phosphoproteomes were biased toward Thr compared with Ser (57–61%; 41–35%), which agrees with previous reports on M. tuberculosis H37Rv (Prisic et al., 2010). Importantly, the percentage of Tyr phosphorylation in M. bovis BCG was closer to that reported in M. tuberculosis (Kusebauch et al., 2014). Although it had previously been suggested that Tyr phosphorylation was non-existent within mycobacterial species, it was recently confirmed that Tyr phosphorylation does in fact occur on a number of diverse M. tuberculosis proteins (Kusebauch et al., 2014). Here, we have confidently identified nine Tyr p-sites in eight proteins in M. bovis BCG (**Table 1**, **Figure 1B** and **Supplementary Table S1A**) and four in M. smegmatis, supporting earlier suggestions that phosphorylation on Tyr residues occur in different mycobacterial species (Kusebauch et al., 2014).

The differences between the compared phosphoproteomes compelled us to investigate whether some of these dissimilarities could be explained by genomic events rather than posttranslational control. The multiple sequence alignment of 130 selected M. bovis BCG phosphoproteins with their respective M. smegmatis orthologs (**Supplementary S3A**) revealed that from 197 M. bovis BCG Ser/Thr/Tyr phosphorylated sites: 12 are conserved across the two mycobacterial species and were found to be phosphorylated in both species, while 94 conserved Ser/Thr/Tyr residues were found to be phosphorylated in M. bovis BCG only. Furthermore, whereas 91 M. bovis BCG phosphorylated residues were aligned with a different non-phosphorylated M. smegmatis residue, 72 of these were aligned with a non-phosphorylated amino acid (**Supplementary S3A**) and 19 were aligned with different nonphosphorylated Ser/Thr/Tyr residue. Conversely, the multiple sequence alignment of 64 M. smegmatis phosphoproteins with their respective M. bovis BCG orthologs showed that besides the 12 conserved Ser/Thr/Tyr residues phosphorylated in both species, 31 conserved residues were found to be phosphorylated in M. smegmatis only. In this case, while 43 M. smegmatis phosphorylated residues were aligned with a different non-phosphorylated M. bovis BCG amino-acid, 36 of these were aligned with a non-phosphorylated amino acid residue (**Supplementary S3B**) and seven were aligned with different non-phosphorylated Ser/Thr/Tyr residue (**Supplementary S3B**). These results point out that some of differences observed between the two phosphoproteomes can be explained by the absence of the corresponding amino acid residue, indicating that during exponential growth phase these two mycobacterial species present an inherently different sub-set of Ser/Thr/Tyr kinase substrates. Additionally, there are some interesting examples in which orthologous proteins were phosphorylated at different psites. This suggests that kinase specificities for a substrate could be intimately related with the actual site of phosphorylation. Finally, it is notable that occasions the Ser/Thr/Tyr residue was aligned with different Ser/Thr/Tyr residue (in most cases S for T and vice versa) in some punctual situation the respective residue was phosphorylated (e.g., PknB) but for the majority of the cases these were aligned with non-phosphorylated Ser/Thr/Tyr residue. This intriguing observation leaves open the possibility that Ser/Thr exchange could be a result of an evolutionary processes/environmental adaptation, in which the replacement for the respective residue would probably favor site phosphorylation and therefore the gain of an additional mechanism of protein

\**Tyr phosphorylated sites that were previously identified in M. tuberculosis H37Rv (Kusebauch et al., 2014).*

*ˆ Tyr phosphorylated sites in M. smegmatis.*

*aUniprot protein accession number.*

*bPhosphorylated Tyr (Y) and respective Localization probability.*

functional regulation. Although speculative, it would be interesting to explore further in which conditions these sub set of Ser/Thr/Tyr sites are phosphoryalated.

Finally, the number of phosphoproteins/sites identified in M. smegmatis is comparable to those reported in other soil bacteria, e.g., E. coli (Macek et al., 2008; Soares et al., 2013), Bacillus subtilis (Shi et al., 2014) and Pseudomonas putida (Ravichandran et al., 2009), as well as in some pathogenic bacteria such as Pseudomonas aeruginosa (Ravichandran et al., 2009), Streptococcus pneumonia (Sun et al., 2009), Helicobacter pylori (Ge and Shan, 2011), and Klebsiella pneumonia (Lin et al., 2009). Whereas, the number of phosphorylated Ser/Thr/Tyr detected in M. bovis BCG phosphoproteome is comparable to that described in M. tuberculosis H37Rv (Prisic et al., 2010). It is of particular interest that the M. bovis BCG phosphoproteome shows a number of phosphoproteins/sites that are orthologous to those reported in M. tuberculosis H37Rv (Prisic et al., 2010) but also a number that are not conserved. Recently a comparison between the Ser/Thr/Tyr phosphoproteomes of Acinetobacter baumannii reference strain (ATCC17978) and a highly invasive, multidrug resistant clone (AbH12O-A2) demonstrated that, during stationary phase, the multidrug isolate showed twice as many phosphorylation-events as the reference strain (Soares et al., 2014). In contrast to reports on Pseudomonas species (Ravichandran et al., 2009), our current study supports the notion that bacteria within the same genus/species may utilize differing numbers of phosphoproteins.

#### Phosphoproteomic Analysis Reveals Conserved Ser/Thr/Tyr Phosphorylated Sites Across Mycobacterial Species

#### Conserved Ser/Thr Phosphorylated Sites

Macek et al. (2008) reported evidence of a possible high degree of conservation within potential bacterial phospho-sites although, as noted by those authors, the conservation of residues does not mean that they are phosphorylated in all species. In fact, as the number of bacterial phosphoproteomic studies increases, it is becoming clearer that the degree of conserved phosphosites among bacterial species is rather limited and certainly lower than reported within eukaryotic phosphoproteomes (e.g., Freschi et al., 2014). Here, a comparison between the M. smegmatis, M. bovis BCG, and M. tuberculosis H37Rv (Prisic et al., 2010; Kusebauch et al., 2014) phosphoproteomes revealed that these three mycobacterial species share a number of conserved phosphorylated sites (**Table 2**). Interestingly, we found that M. bovis BCG and M. tuberculosis H37Rv phosphoproteomes share at least 32 Ser/Thr conserved phospho-sites on 27 proteins, of which three were conserved in all three species (**Table 2**). As pointed out by Freschi et al. (2014), phosphorylation sites that are phosphorylated in different species are more likely to be functional and this conservation criterion could be used to prioritize phosphorylation events for additional characterization.

In the present study we have focused in particular on the STPKs PknB and PknA that have known or predicted functions in cell wall generation and growth in M. smegmatis, M. bovis BCG, and M. tuberculosis (Gee et al., 2012; Kusebauch et al., 2014). We found PknB to be phosphorylated in Thr173 in all three species and in Thr171 in M. smegmatis and M. bovis BCG (**Table 2**). Previous in vitro assays demonstrated that both Thr173 and Thr171 are conserved auto-phosphorylated residues that lie in the activation loop of PknB (Boitel et al., 2003). Additionally, a M. tuberculosis double mutant Thr171/Thr173 was 300-fold less active than respective wild-type PnkB, suggesting a combined effect of both Thr171 and Thr173 residues on kinase activity. Subsequent studies confirmed that the mutation of these residues had a strong effect not only on PknB kinase activity but also in the process of activation loop-mediated recruitment of its substrates (Villarino et al., 2005). Here we have provided evidence that Thr173 and Thr171

#### TABLE 2 | Summary of the phosphorylated sites found in more than one Mycobacterial species.

\* *Ser/Thr phosphorylated sites that were previously identified in M. tuberculosis H37Rv (Prisic et al., 2010).*

*aUniprot protein accession number.*

*bSer/Thr residue found phosphorylated in the indicated Mycobacterial species.*

−*, Not detected.*

phosphorylation both occur in vivo during the exponential phase, at which PknB is most abundant and is thought be at its maximum activity. Thus, our data reinforces a previous hypothesis suggesting that in vivo this enzyme is regulated through an autophosphorylation mechanism involving the phosphorylation state of both Thr173 and Thr171.

Another proposed mechanism of PknB regulation relates to the maintenance of an inactive state via the interaction of the juxtamembrane region with the kinase domain. In this model, the auto-phosphorylation of specific residues in the juxtamembrane sequences releases the inhibition by making the sequence available for further interactions with domains of target proteins (Wybenga-Groot et al., 2001). However, previously it was not clear whether Thr294 and/or Thr309 were the target residues involved so it is notable that our data clearly demonstrate that PknB of M.bovis BCG is in fact phosphorylated on Thr309.

Our analyses indicate that PknA is phosphorylated in at least one conserved residue, Ser309/Ser310 (see **Table 2**). Intriguingly, in this study M. bovis BCG PknA was found to be phosphorylated on seven different residues (three Ser and four Thr, respectively), all located in the juxtamembrane region. Unlike PknB, in PknA the juxtamembrane region, encompassing residue 269– 338 is indispensable not only for auto-phosphorylation of PknA but also for its substrate phosphorylation ability (Thakur et al., 2008). STPks exhibit a wide variety of mechanisms for their regulation. Taking into account the degree of phosphorylation verified here in the juxtamembrane region of M. bovis BCG PknA compared to that observed in M. smegmatis PknA, it is tempting to speculate that this level of phosphorylation of the juxtamembrane region could be in fact limiting the access of PknA to its substrates and this way controlling the action of the enzyme. Importantly, as noted by Chawla et al. (2014), whilst the structure and mode of activation of PknB and PknA have been well established in vitro, the structure-function relationships of the various domains have yet to be investigated in the context of mycobacterial growth (Chawla et al., 2014). Here through a MS based phosphoproteomic approach we have established (at the phospho-site level) the phosphorylation state of different domains for both PknA and PknB in vivo during growth at exponential phase.

#### Conserved Tyr Phosphorylated Sites

In our study we have identified nine Tyr p-sites (see **Table 1**), of which four were also found to be phosphorylated in M. tuberculosis (Kusebauch et al., 2014): FHA-domain-containing protein (Tyr215 and Tyr232), 60 kDa chaperonin 1 (Tyr358) and conserved membrane protein mmpS3 (Tyr70) (**Figure 1B**). FHA-domain-containing protein is a substrate of numerous STPKs, including PknB. Phosphorylation of FHA by PnkB has implication in cell wall synthesis with a possible involvement in mycobacterial virulence (Gupta et al., 2009). Likewise both 60 kDa Chaperonin and conserved membrane protein mmpS3 have been implicated in mycobacterial virulence (Wells et al., 2013). Based on our data, we searched for possible conservation of these peptides across other bacterial species. A sequence motif derived from 60 kDa Chaperonin Tyr358 (RQEIEN**SDSDYDREKL**QERLA) using Seq2Logo revealed an overrepresentation of Tyr358 (**Figure 2**). A conserved Tyr360 residue on apparently conserved peptide (**SDSDYDREKL**) was found in three Gram negative pathogenic species, specifically Shigella spp., Klebsiella spp., and Salmonella spp., suggesting that this conserved Tyr phosphorylation site warrants further investigation for possible roles in bacterial pathogenesis.

#### Phosphoprotein Functional Enrichment

Gene ontology (GO) terms revealed that in both M. bovis BCG and M. smegmatis, the phosphorproteins/phosphosites were functionally enriched in nine distinct groups, (e.g., ATP binding, translation, kinase activity, cell division, see **Figure 2**). Of interest, a great deal of phosphorylated proteins in M. bovis BCG was clustered into the Transmembrane group (**Figure 2**). This included a considerable number of multiple phosphorylated proteins and some phosphorylated in internal as well as external regions, like BCG\_3967, it is a probable trans-membrane protein and we found it to be phosphorylated four times, at position 10, which like on the flagellin domain and position 801 and 801, the kinase domain. This suggests that there are transmembrane proteins with a potential role in signal transduction. Additionally, it was visible that M bovis BCG phosphoproteome comprised a notable group of phosphoproteins involved in cell division, possible implications of this is discussed below.

#### Phosphorylation Events Observed in Proteins that Regulate Mechanisms of Growth and Cell Division

Both PknA and PknB are encoded by genes (pknA and pknB, respectively) located on the same operon as protein phosphatase PstP, RodA (implicated in cell shape control) and PbpA (implicated in peptidoglycan synthesis) (Cole et al., 1998). This locus includes also two FHA (forkhead-associated) domaincontaining proteins and in mycobacteria is found near the origin of replication. In M. bovis BCG, all proteins referred to above

chaperonin revelead an overrepresentation of Tyr358. Seq2Logo analysis indicate that a conserved Tyr358−360 is found in additional three pathogenic species, specifically *Shigella* spp., *Klebsiella* spp., and *Salmonella* ssp.

(except PbpA) were found phosphorylated at a total of 15 p-sites: PknA (7); PknB (3); RodA (1); PstP (1) and FHA domain containing protein (3) (see **Supplementary Table S1A**). In M. smegmatis, however, only a few proteins were found phosphorylated at a total of 5 p-sites: PknA (2); PknB (2) FHA domain containing protein (1) (see **Supplementary Table S1B**). These observations suggest that the slow growth of M. bovis BCG preserves this central set of cell division proteins under a tight regulatory network in which key elements are intimately inter-related by an important series of functional (de)phosphorylation events. For example, PknA and PknB are regulated by PstP-mediated phosphorylation (Boitel et al., 2003; Chopra et al., 2003); additionally, recently it has been shown that both PknA and PknB phosphorylate PstP (Sajid et al., 2011). As discussed above, our results showed that both M. smegmatis and M. bovis BCG PknB has conserved phosphorylation on Thr171 and Thr173—both of which sites are known to be substrates for PstP—thus suggesting that in both cases PstP is at least partially inactive. This would make sense considering that during exponential phase PknA and PknB are likely to be at their peak of activity. PstP has been reported to be phosphorylated by PknB on Thr173, Thr141, Thr290, and Thr137 in its cytosolic domain and on Thr174 by PknA (Sajid et al., 2011). Curiously phosphorylated PstP has been reported to be more active than its unphosphorylated form (Sajid et al., 2011). Here, our results indicate that PstP of M. bovis BCG is phosphorylated in vivo on the high confidence p-site, Ser155 (see **Supplementary Table S1A**). Interestingly, PstP contains three metal-binding centers in its structure (Pullen et al., 2004), sharing the fold and two-metal center of human PP2Cα whilst having a third Mn2+ in a site created by a large shift in a flap domain next to the active site; this Mn2+ occurs at the position of Ser160 so it is plausible that phosphorylation of Ser155 may directly interfere with PstP activity, thus accounting for our deduction here of reduced PstP activity during exponential phase growth.

Overall, M. bovis BCG has 3 times more STPks and nearly 4 times respective p-sites compared to M. smegmatis. Apart from PknA and PknB, the M. bovis BCG phosphoproteome is comprised of PknG (Thr95), PknH (Thr174), PknE (Ser304 and Ser326) PknF (Thr287). Some of these enzymes have previously been directly implicated in mycobacterial growth [e.g., PknG (Fiuza et al., 2008), PknH (Zheng et al., 2007), PknE and PknF (Gupta et al., 2014)] and it is therefore conceivable that some of the proteins comprising the M. bovis BCG phosphoproteome are in fact substrate of some of these phosphorylated protein kinases (vide infra). It is worth noting that our study has also identified several Two Component sensory signal transduction proteins as phosphoproteins (e.g., Two component sensory transduction protein regX3 (Thr151 and Thr153), Two component sensor histidine kinase ppr (Ser446), Two component transcriptional regulatory pprA (Ser20). These results are reminiscient of those previously described in B. subtilis (Jers et al., 2011) and suggest that in M bovis BCG there may be cross talk between Ser/Thr/Tyr phosphorylation and Two component systems, which would add extra complexity to the overall protein phosphorylation signal transduction pathways regulating exponential growth of M. bovis BCG cells.

#### Phosphorylation Events Observed in Proteins that Regulates Mechanisms of Cell Elongation and Division

In mycobacteria, cell elongation is regulated by a macrocomplex that regulates peptidoglycan remodeling during growth by means of hydrolytic and synthetic roles (as reviewed by (Kieser and Rubin, 2014)). Our data indicate that in M. bovis BCG, three important proteins of the macromolecular elongation complex are phosphorylated during exponential growth, namely Wag31 (Ser245), CwsA (Thr77) and a putative hydrolase (BCG\_0021 involved in peptidoglycan catabolic process) (Thr43). In mycobacteria, Wag31 is phosphorylated by PknA and is essential for correct polar localization and biosynthesis (Jani et al., 2010; Lee et al., 2014); in addition, Wag31 is stabilized by the cell wall protein CwsA. Wag31 is thought to be phosphorylated during exponential phase and remains non- or lowlyphosphorylated during stationary phase (Kang et al., 2005; Park et al., 2008). Interestingly, Wag31, CwsA and the putative peptidoglycan hydrolase were not found amongst the M. smegmatis phosphorylated proteins in the present study. Whilst we cannot rule out that our assay did not isolate phosphorylated M. smegmatis Wag31, it is perhaps more likely that in the fast growing M. smegmatis the elongation complex is regulated by alternative non-phosphorylated mechanism.

Another macromolecular complex, named divisome, is responsible for mycobacterial cell division. Assembly and disassembly of this complex is regulated by protein phosphorylation (Kieser and Rubin, 2014). According to the our data, in M. bovis BCG there are five divisome proteins which are phosphorylated, including cell division FtsQ (Thr24), FtsW-like protein (Thr29), CwsA (Thr77) as well as other additional phosphorylated cell division proteins such as RodA (Thr463), cell division transmembrane protein FtsK (Thr325; Thr642) and FtsY (Thr72), strongly suggesting that divisome assembly and indeed cell division in M. bovis BCG is subject to a high level of phosphorylation.

Of interest, in our analysis we have detected Hup, a conserved histidine-like protein, phosphorylated on three different p-sites (Thr45, Thr65, and Ser90). In Mycobacterium sp., the homolog of HU (Mhpl) is implicated in bacterial adaptation to stress response conditions, possible inhibition of cellular metabolism and reduction of bacterial growth rate through nucleoid reorganization (Lee et al., 1998; Matsumoto et al., 1999; Katsube et al., 2007). Apparently, is expressed in exponentially growing cells of M. tuberculosis H37Ra and it is shown to be maximally expressed during stationary phase, while Hup kinases (PknE, PknF, and PknB) were found to be constitutively expressed during exponential phase (Gupta et al., 2014). It has been suggested that the phosphorylation of HupB during the exponential phase by the referred kinases would limit the interaction with DNA (Gupta et al., 2014). In our M. bovis BCG data we have identified all the intervenient proteins involved in the described posttranslational regulation mechanism, including the phosphorylation of phosphosite Hup Thr65. It is therefore appropriate to assume that the same mechanism takes place in M. bovis BCG cells during exponential growth, and although under limited action it remains possible that the rate of unphosphorylated HupB would have

April 2015 | Volume 6 | Article 237

an impact on the overall growth rate. In contrast, we did not find any evidence to indicate that similar mechanisms operate in M. smegmatis cells during exponential growth.

#### Stress Related Proteins

In rich broth during exponential phase, bacteria experience nearly optimal conditions of growth where there is excess nutrients and little accumulation of by products, in addition to scarce competition between bacterial cells. Surprisingly, under these conditions we observed an unexpected number of chaperones and stress related proteins in the M. bovis BCG phosphoproteome: For instance hyperosmotic and heat shock related proteins such as the chaperon protein DnaJ (Thr120) chaperon protein DnaK (Ser558) and GrpE (Ser12 and Thr2), multiply phosphorylated 60 kDa chaperonin, 10 kDa chaperonin, and Copper-sensing transcriptional repressor CsoR (Thr93). On the other hand none of these stress related proteins were found in the M. smegmatis phosphoproteome, which suggests that even under optimal environmental conditions, slow growing mycobacteria such as M. bovis BCG maintain a preventive basal level of stressrelated proteins that may act as frontline defense barrier to ensure adequate and prompt response to any sudden change in local environmental conditions. In this scenario protein phosphorylation would keep most of these proteins in an inactive state, whereby dephosphorylation could then immediately recruit these proteins when environmental conditions become unfavorable. A convenient and versatile regulatory mechanism such as this could in fact be a determinant for the survival and persistence of some bacteria.

### Conclusion and Prespectives

This study clearly demonstrated that there are major differences between a fast growing and a slow growing mycobacterial phosphoproteome. The M. smegmatis phosphoproteome observed here is in many aspects similar to those reported in other soil-dwelling bacterial models and can be viewed as a minimalist phosphoproteome compared to that of M. bovis BCG. This latter organism presents a much more complex and sophisticated protein phosphorylation network, regulating important cellular cycle events such as cell wall biosynthesis, elongation, and cell division, as well as apparently being involved in regulating response to stress, which over all would allow a quick cellular

### References

response to abrupt environmental changes. However, this regulatory advantage might be associated with a cost, reflected by reduced metabolic fitness and slower growth rate.

This study demonstrates M. bovis BCG is a good model to study aspects of mycobacterial phospho-dependent signal transduction pathways, including those involved in persistence and slow growth, including that associated with drug resistance. By contrast, the substantial differences reported here in the phosphoproteomes of M. smegmatis and M. bovis BCG suggest that exponentially growing M. smegmatis cells in vitro are of limited relevance when modeling phosphorylation networks and phospho-regulation events likely to occur in M. tuberculosis at the site of disease during an infection.

#### Acknowledgments

We thank the National Research Foundation (NRF) for their financial support of this research and for a PhD bursary to KCN. NCS and JMB thank the NRF for the South African Research Incentive Funding for Rated Researchers and the Research Chair grants respectively. SG thanks the CSIR for a PhD bursary.

### Supplementary Material

The Supplementary Material for this article can be found online at: http://www.frontiersin.org/journal/10.3389/fmicb. 2015.00237/abstract

#### Supplementary Figure S1 | Phosphoproteomic workflow diagram.

Mycobacterial strains were harvested at exponential phase, lysed. In-solution digestion was then carried out TiO2 phosphor enrichment and data acquisition with LC/MS/MS.

Supplementary Figure S2 | (a–f). Total Ion Chromatograms (TIC) and MS summary peptide/phosphopeptides identified in each experiment.

Supplementary S3A | Multiple sequence alignment of *M.bovis* BCG phosphoproteins with their respective *M. smegmatis.*

Supplementary S3B | Multiple sequence alignment of *M. smegmatis* phosphoproteins with their respective *M.bovis* BCG.

Supplementary Table S1A | Spreadsheet of all the identified protein groups, phosphopeptides and phosphoproteins from *M. bovis* BCG.

Supplementary Table S1B | Spreadsheet of all the identified protein groups, phosphopeptides and phosphoproteins from *M. smegmatis.*

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Nakedi, Nel, Garnett, Blackburn and Soares. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

## Phosphoproteome of the cyanobacterium Synechocystis sp. PCC 6803 and its dynamics during nitrogen starvation

#### Philipp Spät 1 , Boris Macek ˇ 2 \* and Karl Forchhammer 1 \*

1 Department of Organismic Interactions, Interfaculty Institute for Microbiology and Infection Medicine, Eberhard-Karls-University Tübingen, Tübingen, Germany, 2 Interfaculty Institute for Cell Biology, Proteome Center Tuebingen, Eberhard-Karls-University Tübingen, Tübingen, Germany

#### Edited by:

Ivan Mijakovic, Chalmers University of Technology, Sweden

#### Reviewed by:

Jason Warren Cooley, University of Missouri, USA Carsten Jers, Technical University of Denmark, Denmark

#### \*Correspondence:

Boris Macek, ˇ Interfaculty Institute for Cell Biology, Proteome Center Tuebingen, University of Tuebingen, Auf der Morgenstelle 15, D-72076 Tuebingen, Germany<EMAIL_ADDRESS>Karl Forchhammer, Department of Organismic Interactions, Eberhard-Karls-Universität Tübingen, Auf der Morgenstelle 28, D-72076 Tübingen, Germany<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology

> Received: 02 December 2014 Accepted: 13 March 2015 Published: 31 March 2015

#### Citation:

Spät P, Macek B and Forchhammer K ˇ (2015) Phosphoproteome of the cyanobacterium Synechocystis sp. PCC 6803 and its dynamics during nitrogen starvation. Front. Microbiol. 6:248. doi: 10.3389/fmicb.2015.00248 Cyanobacteria have shaped the earth's biosphere as the first oxygenic photoautotrophs and still play an important role in many ecosystems. The ability to adapt to changing environmental conditions is an essential characteristic in order to ensure survival. To this end, numerous studies have shown that bacteria use protein post-translational modifications such as Ser/Thr/Tyr phosphorylation in cell signaling, adaptation, and regulation. Nevertheless, our knowledge of cyanobacterial phosphoproteomes and their dynamic response to environmental stimuli is relatively limited. In this study, we applied gel-free methods and high accuracy mass spectrometry toward the detection of Ser/Thr/Tyr phosphorylation events in the model cyanobacterium Synechocystis sp. PCC 6803. We could identify over 300 phosphorylation events in cultures grown on nitrate as exclusive nitrogen source. Chemical dimethylation labeling was applied to investigate proteome and phosphoproteome dynamics during nitrogen starvation. Our dataset describes the most comprehensive (phospho)proteome of Synechocystis to date, identifying 2382 proteins and 183 phosphorylation events and quantifying 2111 proteins and 148 phosphorylation events during nitrogen starvation. Global protein phosphorylation levels were increased in response to nitrogen depletion after 24 h. Among the proteins with increased phosphorylation, the PII signaling protein showed the highest fold-change, serving as positive control. Other proteins with increased phosphorylation levels comprised functions in photosynthesis and in carbon and nitrogen metabolism. This study reveals dynamics of Synechocystis phosphoproteome in response to environmental stimuli and suggests an important role of protein Ser/Thr/Tyr phosphorylation in fundamental mechanisms of homeostatic control in cyanobacteria.

Keywords: cyanobacteria, Synechocystis sp. PCC 6803, nitrogen starvation, phosphoproteome, peptide dimethylation labeling, LTQ-Orbitrap

### Introduction

Cyanobacteria constitute one of the most widely distributed groups of prokaryotes in the biosphere, where they inhabit almost all illuminated environments. They are oxygenic photoautotrophs, employing photosynthetic machinery that resembles that of plants, due to the endosymbiotic origin

of chloroplasts. The substrate diversity of cyanobacteria is limited since photoautotrophs only need H2O as an electron donor, CO2 as a carbon source, and inorganic salts such as nitrogen, phosphorous, sulfur, and iron to fulfill their anabolic needs. Among these, the highest demand is for nitrogen, whose cellular abundance amounts to a carbon to nitrogen ratio of 5:1.

Cyanobacteria encounter many environmental fluctuations, such as changing light conditions, nutrient availability and the ambient physico–chemical properties (osmolarity, temperature etc.). During evolution, these microbes have developed sophisticated regulator systems to adapt cellular processes and maintain metabolic homeostasis in response to these challenges. Nitrogen starvation induces in non-diazotrophic cyanobacteria a highly dynamic response, which can be classified in three phases. Their temporal occurrence depends on many environmental and intrinsic conditions (Schwarz and Forchhammer, 2005). In response to nitrogen depletion, an acclimation process is initiated that is known as chlorosis (Allen and Smith, 1969). Chlorosis is characterized by a rapid degradation of the phycobilisome antenna and a cell cycle arrest after completion of a final cell division (Allen and Smith, 1969; Collier and Grossman, 1992). This initial phase (phase I) is followed by a subsequent gradual and consecutive decrease in photosystem (PS) II and PSI activities (phase II), down-tuning of metabolic activities and proteolytic degradation of cellular proteins. Only after 10–15 days, cells have reached a final resting state, where they are completely bleached (phase III) and can survive for prolonged periods (Görl et al., 1998). **Figure 1** indicates the metabolic changes in the cell in the phase II chlorosis stage, which starts after 24 h of nitrogen starvation.

Among the short-term acclimation processes, protein phosphorylation plays a prominent role (Biggins and Bruce, 1987; Stock et al., 1989; Hagemann et al., 1993). In bacteria, the twocomponent sensory transduction pathways have been historically known as the hallmark of bacterial signal transduction, involving protein histidine kinases and response regulators phosphorylated on aspartate residues. These are universally distributed and have been systematically investigated in several cyanobacterial strains (Ashby and Houmard, 2006). Among these, the 47 histidine kinases and 45 response regulators in the unicellular strain Synechocystis sp. PCC 6803 substrain Kazusa (hereafter designated as Synechocystis) has received the most thorough investigations (Murata and Suzuki, 2006).

Phosphorylation on serine, threonine and tyrosine residues (Ser/Thr/Tyr), referred to as S/T/Y phosphorylation or O-phosphorylation, was initially thought to occur exclusively in eukaryotic signal transduction. However, primarily due to advances in mass spectrometry proteomics technologies, it is now clear that this type of modification frequently occurs in bacteria serving an important role in prokaryotic signal transduction (Macek and Mijakovic, 2011). Most bacterial Ser/Thr kinases resemble those classified in eukaryotes and are termed as Hanks-like kinases, whereas, most bacterial tyrosine (BY) kinases are unique to prokaryotes (Mijakovic and Macek, 2012; Soufi et al., 2012). Genome sequencing revealed that Hanks-like Ser/Thr kinases, BY-kinases, and protein phosphatases are

globally distributed in the bacterial domain (Pereira et al., 2011). Bacterial S/T/Y phosphorylation is widely involved in signal transduction in response to environmental stimuli and regulates many physiological processes in a bacterial cell (Petranovic et al., 2007; Mijakovic and Macek, 2012).

A survey of the genome of Synechocystis revealed the presence of 11 Ser/Thr kinases, one Tyr kinase and seven protein phosphatases (Zhang et al., 2005). Pioneering work in the late 1980s and in the 1990s, employing in vivo and in vitro labeling experiments using [γ 32P] phosphate shed the first light on the occurrence of protein phosphorylation events in cyanobacteria (reviewed by Mann, 1994). Protein phosphorylation was shown to be dynamic and to respond to a variety of environmental stimuli, such as changing illumination, nutrient supply, or osmolarity (Sanders et al., 1989; Hagemann et al., 1993).

One of the first discovered and most intensively studied phosphoproteins in cyanobacteria is the signal transduction protein PII (Forchhammer and Tandeau De Marsac, 1994); reviewed in Forchhammer (2004, 2008). The PII signaling protein, a homotrimer of 12.4 kDa, is phosphorylated at the tip of a large, surface exposed loop (termed T-loop) in response to the cellular nitrogen supply. The effector molecule 2-oxoglutarate (2- OG) whose abundance reflects the cellular state of nitrogen assimilation (Muro-Pastor et al., 2001), binds to PII and elicits its phosphorylation on T-loop residue Ser49 (Forchhammer and Tandeau De Marsac, 1995). In its phosphorylated state, PII is not able to bind to and activate the key enzyme of the ornithine/arginine biosynthesis pathway, N-acetyl-L-glutamate kinase (NAGK) (Heinrich et al., 2004). Shifting nitrogen-starved cells back to nitrogen-sufficient conditions, the cellular 2-OG level drops, leading to dephosphorylation of PII (Irmler and Forchhammer, 2001) with a concomitant activation of NAGK (Maheswaran et al., 2006), thereby feeding nitrogen into the arginine pool.

In addition to PII, the functions of only a few other phosphoproteins have been identified in Synechocystis, such as the phosphorylation of phycobiliproteins and phycobilisome linker proteins (Harrison et al., 1991; Piven et al., 2005), or the oscillating phosphorylation of the circadian clock protein KaiC (Nishiwaki et al., 2004). Except these specific investigations focusing on particular phosphoproteins, Mikkat et al. recently published a snapshot of the phosphoproteome of Synechocystis based on 2D gel electrophoresis, where the authors identified about 30 phosphoproteins, of which the modified residue could be localized in eight cases. Among these, most previously identified phosphoproteins were included (Mikkat et al., 2014). However, the physiological function of most phosphorylation events remains still unclear.

In the recent years, the analysis of global phosphoproteomes has made dramatic progress due to the development of gel-free workflows and biochemical phosphopeptide enrichment strategies such as titanium dioxide (TiO2) chromatography coupled to high accuracy mass spectrometry. The development of chemical stable isotope labeling by dimethylation of tryptic peptides enables the application of a cost efficient and reliable quantification strategy also to autotrophic organisms, without the need of profound genetic manipulation of amino acid metabolic pathways (Boersema et al., 2009). Despite these advantages, the dimethylation approach was never applied in global phosphoproteomic studies in a prokaryotic organism.

The first global study of a cyanobacterial phosphoproteome using gel-free methods was performed in a qualitative manner in the marine unicellular cyanobacterium Synechococcus sp. PCC 7002, which resulted in the identification of 410 phosphorylation sites on 245 phosphoproteins (Yang et al., 2013). One general drawback in global studies in cyanobacterial organisms is the high percentage of integral membrane and membraneassociated proteins. Particularly, such membrane proteins are often involved in protein phosphorylation based signal transduction and represent a high potential for phosphorylation (Jers et al., 2008). Therefore, efficient extraction of cytosolic as well as of membrane proteins is essential in order to attain deep phosphoproteome coverage. So far, about 900 known or predicted membrane (associated) proteins have been identified in Synechocystis by previous large-scale studies (24.5% of 3672 protein coding genes list on Cyanobase). However, 52.7% of the total protein coding genes was thus far not identified on the proteome level, indicating a need for improvement in protein extraction methods, particularly with respect to hydrophobic (membrane)proteins (Wang et al., 2009).

In the present work, we applied state of the art mass spectrometric analysis to define the phosphoproteome of Synechocystis. To ensure an efficient extraction of cytosolic as well as of membrane (phospho)proteins, we compared three common, in gel-free approaches frequently used extraction methods in a qualitative experiment. Here, in total 301 phosphorylation events could be identified, of which 262 could be localized to a specific Ser, Thr, or Tyr residue. This dataset represents the so far most comprehensive qualitative phosphoproteome dataset of Synechocystis. It encouraged us to investigate phosphoproteome dynamics in response to nitrogen starvation in a quantitative manner employing for the first time in a bacterial system the method of chemical dimethylation labeling. Extracts from Synechocystis cultures grown in the presence of nitrate or ammonia and cultures subjected to nitrogen starvation were dimethyl labeled. Thereby, we could identify altogether 2382 proteins and 183 phosphorylation events. Of those, the dynamics of 2111 proteins and 148 phosphorylation events from two independent experiments could be quantified. The PII signaling protein, which served as a positive control to validate the experiments, showed the highest increase in phosphorylation level upon nitrogen starvation. Other proteins with increased phosphorylation levels comprised functions in photosynthesis and in carbon and nitrogen metabolism, suggesting an important role of protein S/T/Y phosphorylation in such a fundamental acclimation response.

#### Material and Methods

#### Cell Culture and Harvest

Wild-type Synechocystis sp. PCC 6803 substrain Kazusa was grown photoautotrophically at a constant photon flux density of 40µmol photons m−2 s −1 in 5 mM NaHCO3 and 20 mM Spät et al. Synechocystis sp. PCC 6803 phosphoproteome

HEPES supplemented BG11 medium (Rippka, 1988), with either 17.6 mM sodium nitrate (NaNO3) or 5 mM ammonium chloride (NH4Cl) as exclusive nitrogen source, at 26◦C. A stationary culture of Synechocystis in BG11 nitrate medium served as a stock for the final inoculation of experimental 500 mL batch cultures in the qualitative experiments. For the quantitative experiment 1, precultures were grown from the stock in fresh nitrate or ammonia medium to optical density (OD)750 = 0.6–0.8 and were directly used as inoculum for the experimental 500 mL batch cultures. In experiment 2, the pre-cultures were repeatedly cultivated to OD750 = 0.6–0.8 and after five cycles used as inoculum for the experimental 500 mL batch cultures. All experimental cultures were inoculated to an initial OD750 = 0.2 and grown to OD750 = 0.6 with ambient air bubbling and magnetic stirring. Cultures were harvested by addition of 100 g ice for rapid cooling and centrifugation at 7477 × g for 10 min. The supernatant was removed and cell pellets were resuspended in 50 mL ice cold nitrogen-free BG11 medium and centrifuged again. Cell pellets were quickfrozen in liquid nitrogen. For nitrogen starvation conditions, nitrate grown cells (at OD750 = 0.6) were shifted to nitrogenfree BG11 medium by centrifugation with 3500 × g for 8 min at room temperature (RT). The supernatant was decanted, the cell pellet was gently overlaid with nitrogen-free BG11 medium, swiveled and decanted again and finally, the cell pellet was resuspended in the same volume as before centrifugation. Cells were kept for 24 h under previous incubation conditions and harvested as described.

#### Protein Extraction, In-solution Digestion, and Peptide Dimethylation Labeling

Protein extraction method A: Filter Aided Sample Preparation was performed as described previously (Wisniewski et al., 2009) with the following exceptions: In brief, a frozen cell pellet from a nitrate grown culture was resuspended in 2 mL lysis buffer, containing 4% (w/v) sodium dodecyl sulfate (SDS) and 100 mM dithiothreitol (DTT) in 100 mM Tris/HCl, pH 7.5, and each 5 mM of the following phosphatase inhibitors: glycerol-2 phosphate; sodium fluoride (both Sigma-Aldrich) and sodium orthovanadate (Alfa Aesar). The sample was incubated for 10 min at 95◦C in a water bath and subsequently sonified on ice for 30 s with a Branson Sonifier 250/Microtip 5 at output control 4 and 40% duty cycle for DNA comminution. The lysate was centrifuged at 13,000 × g for 5 min and the supernatant was transferred onto an Amicon Ultra-15 3 kDa Centrifugal Filter Unit. The lysate was mixed with 5 mL urea buffer (6 M urea/2 M thiourea in 100 mM Tris/HCl; pH 7.5) and centrifuged with 3345 × g for 10 min at RT. This step was repeated once for washing. Alkylation of reduced cysteine disulfide bonds was performed by washing the filter unit with 5 mL urea buffer containing 50 mM iodoacetamide (IAA) and centrifugation for 15 min as before, followed by incubation with 2 mL IAA-urea buffer for 20 min in the dark. The filter was washed for three times with each 2 mL urea buffer and 50 mM NH4HCO3 buffer, subsequently. For protein digestion, 50µg trypsin (MS grade; Thermo Scientific) in 500µL NH4HCO3 buffer, pH 8.0, were added onto the filter and incubated overnight (o.n.) at 37◦C. Peptides were collected in a fresh tube by centrifugation as before for 10 min and additional with 500µL NH4HCO3 buffer.

Protein extraction method B: SDS buffer protein extraction and acetone/methanol precipitation: Proteins from frozen cell pellets were extracted with 2 mL lysis buffer (see method A, without DTT), supplemented with 10 mM ethylenediaminetetraacetic acid (EDTA). Cell lysates were sonified on ice as described in method A and subsequently reduced with a final concentration of 10 mM DTT for 1 h at RT under agitation at 650 rpm on a shaker. Alkylation was performed with a final concentration of 5.5 mM IAA for 1 h at RT under agitation in the dark, followed by centrifugation at 13,000 × g for 5 min. Proteins in the supernatant were precipitated by mixing with eight volumes ice cold acetone and one volume ice cold methanol, followed by incubation at −20◦C o.n. The precipitate was washed five times with 5 mL ice cold 80% (v/v) acetone in water and centrifugation at 1000 × g. The protein pellets were air dried and dissolved in urea buffer.

Protein extraction method C: Protein extraction with Y-PER (Yeast Protein Extraction Reagent; Thermo Scientific) and acetone/methanol precipitation: A frozen cell pellet was resuspended in 2 mL Y-PER, supplemented with 50µg/mL lysozyme (from chicken egg, Sigma-Aldrich), c0mplete protease inhibitors (Roche) and phosphatase inhibitors, as described in method A. The suspension was incubated at 37◦C for 20 min under agitation at 650 rpm. Cell lysates were sonified on ice and centrifuged as described before. Proteins in the supernatant were acetone/methanol precipitated, washed and dissolved in urea buffer as described in method B. Reduction and alkylation of cysteines was subsequently performed as described in method B.

Protein concentration of samples derived from methods B and C were measured by Bradford assay (Bio-Rad) and subsequently pre-digested with endoproteinase Lys-C (Waco) for 3 h and digested further o.n. with trypsin (MS grade; Thermo Scientific) at RT. The protease/protein ratio was for both enzymes 1:100 (w/w). The resulting peptide mixtures from methods A, B, and C were acidified to pH 2.5 with trifluoroacetic acid (TFA) and desalted by solid phase extraction on Sep-Pak C18 columns (Waters) according to the manufacturer's instructions.

For the quantitative experiments, samples were extracted with method B, in-solution digested and on-column (SepPak C18) dimethylation labeled as described previously (Boersema et al., 2009). In brief, 5 mL of the respective labeling solutions with CH2O (Sigma-Aldrich) and NaBH3CN (Fluka) for light-, CD2O (Sigma-Aldrich) and NaBH3CN for medium-heavy and 13CD2O (Sigma-Aldrich) and NaBD3CN (Sigma-Aldrich) for heavy labeling were flushed with 15 min contact time through the column. Labeled peptides were washed with 5 mL HPLC Solvent A (0.5% acetic acid) on the column and eluted with HPLC Solvent B (80% acetonitrile in 0.5% acetic acid). For validation of labeling efficiency and correct mixing of the labeled peptides, two times 5µg of each labeled sample (based on Bradford measurements) were used for separate measurements or mixed 1:1:1 and subjected after purification by C18 stage tips (Ishihama et al., 2006) to pilot LC-MS/MS measurements. Based on the obtained label ratios, correction factors were applied for correct mixing of samples. The labeling efficiencies were in all cases ≥94%.

#### Sample Preparation

Sample fractionation for the qualitative proteome experiments was performed on the peptide level by strong anion exchange chromatography (SAX). For quantitative proteome analysis, isoelectric focusing (OffGel fractionation strategy) was performed: For SAX, 100µg peptides were loaded onto in-house packed SAX column (Empore™) and subsequently eluted stepwise in five pH fractions with 20 mM of acetic-, phosphoric- and boric acid at pH 3, 4, 5, 6 and 8, (pH adjusted with sodium hydroxide), respectively. Each fraction was subsequently purified by C18 stage tips. For OffGel fractionation, 100µg of the labeled peptide mixture was separated on a linear 13 cm pH 3–10 IEF strip (GE Healthcare) and focused on a OffGel Fractionator 3100 (Aglient), according to the manufacturer's protocol, with 20 kVh at maximum 50µA. Peptides focused in 12 fractions were separately purified by C18 stage tips.

Phosphopeptide enrichment for qualitative analyses was performed from the digested samples of protein extraction methods A, B and C by TiO2 chromatography (Soares et al., 2013), with the following exceptions: Obtained peptide solutions from solid phase extraction (pH 2.5) were directly incubated with each 5 mg TiO2 spheres (10µm; MZ Analysetechnik), pre-incubated with 2,5-dihydrobenzoic acid (final concentration 30 mg/mL) for five consecutive rounds of 30 min. TiO2 spheres were washed and eluted as described previously and purified by C18 stage tips. The sample volume was reduced by vacuum centrifugation at RT and subjected to nano-LC-MS/MS analysis.

For the quantitative study, labeled phosphopeptides were enriched by TiO2 chromatography from each 15 mg peptide mixture. For TiO2 chromatography, a modified protocol was applied: peptides were eluted from SepPak columns with 80% acetonitrile in 6% TFA and enriched for eight consecutive rounds with each 5 mg TiO2 spheres (5µm Sachtopore NP) for 10 min. TiO2 spheres were washed twice with each 1 mL 80% acetonitrile in 6% TFA for 1 min at 1000 rpm and loaded onto C8 (Empore™) stage tips. The spheres were washed once with 200µL HPLC Solvent B and phosphopeptides were eluted with 30µL 5% ammonium hydroxide solution in 60% acetonitrile, pH 11, for 30 min at 4◦C into 30µL 20% TFA in a fresh tube. Eluates were purified by C18 stage tips. The sample volume was reduced by vacuum centrifugation at RT and subjected to nano-LC-MS/MS analysis.

#### Mass Spectrometry

For nanoLC-MS/MS analyses of proteome and phosphoproteome samples, peptides were loaded onto an in-house packed 15 cm reverse-phase C18 (3µm; Dr. Maisch) nanoHPLC column on an EasyLC nano-HPLC (Proxeon Biosystems). Separation was performed by 90 min (for OffGel-separated samples) or 130 min (for TiO2-enriched samples) segmented linear gradients with 5–90% HPLC solvent B. Eluted peptides were directly ionized and measured on a LTQ Orbitrap XL (qualitative study), or LTQ Orbitrap Elite mass spectrometer (quantitative study). Mass spectrometers were operated in the positive ion mode.

The LTQ Orbitrap XL had the following acquisition cycle: one initial full (MS) scan in the Orbitrap mass analyzer was acquired at resolution 60,000 and scan range of m/z 300–2000, followed by collision induced dissociation (CID) of the 5 (phosphoenrichment) or 15 (proteome) most intense multiply charged ions in the linear ion trap mass analyzer (LTQ). For phosphoproteome analysis, multi stage activation (MSA) in all MS/MS events with neutral losses of phosphoric acid on singly (−97.97 Th), doubly (−48.99 Th) or triply (−33.66 Th) charged precursor ions, was activated.

The LTQ Orbitrap Elite was conducting higher energy collision dissociation (HCD) of the 20 most intense multiply charged ions at the same scan range at resolution 120,000.

Dynamic exclusion of sequenced precursor ions for 90 s and the lock mass option (Olsen et al., 2005) for real time recalibration were enabled on both instruments.

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http:// proteomecentral.proteomexchange.org) via the PRIDE partner repository (Vizcaíno et al., 2013) with the dataset identifier PXD001831.

#### Data Processing and Validation

All raw MS spectra were processed with MaxQuant software suite (version <IP_ADDRESS>) (Cox et al., 2009) and default settings. Identified peaks were searched against the target-decoy databases of Synechocystis sp. PCC 6803 from Cyanobase (http://genome. microbedb.jp/cyanobase) and Uniprot (http://www.uniprot.org), containing 3672 and 3507 protein sequences and 245 common contaminants, with the following database search criteria: Trypsin was defined as cleaving enzyme and up to two missed cleavages were allowed. Carbamido-methylation of cysteines was set as a fixed and methionine oxidation, protein N-termini acetylation and S/T/Y phosphorylation were set as variable modifications. Light-, medium-heavy- and heavy- dimethylation labeling on peptide N-termini and lysine residues was defined for samples from the quantitative experiments. The initial mass tolerance of precursor ions was limited to 6 ppm and 0.5 ppm for fragment ions. False discovery rates (FDRs) of peptides and proteins were set to 1%, respectively. Quantification of dimethylation labeled peptides required at least two ratio counts. Peptides were only allowed with a posterior error probability (PEP) <1% at the peptide- and <5% at the phosphopeptide level. Phosphopeptide MS/MS spectra were further manually filtered and validated with stringent acceptance criteria: Phosphorylation site localization with ≥ 75% localization probability was manually validated as well as comprehensive coverage of b- and y-ion series for CID and HCD spectra as well as a low noise to signal ratio (Supplementary MS Spectra). To exclude quantitation bias of phosphopeptide ratios due to fluctuations of corresponding proteins, phosphopeptide ratios were normalized by division with corresponding protein ratios. Significance analysis of regulated phosphorylation events was performed with Perseus software (version <IP_ADDRESS>), normalized phosphopeptide ratios were log2 transformed and plotted against the respective log10 transformed phosphopeptide intensities. Significantly regulated phosphorylation events were identified by significance A analysis with a p-value of 0.05.

#### Immunoblot Analysis

Proteins from 2 mL cell culture aliquots were extracted in 50 mM Tris/HCl, 5 mM EDTA buffer, pH 7.4, with a RiboLyser, conducting five cycles with a speed of 6.5 m s−1 for 15 s at 4◦C. Protein concentration was measured by Bradford assay and 50µg or 15µg total protein content was separated either by SDS- or by non-denaturing clear native polyacrylamide gel electrophoresis (PAGE), respectively. Pre-cast Tris-glycine 4–20% gradient SDS polyacrylamide gels (NuSep) or 4–16% gradient native polyacrylamide gels (Serva) were used according to the manufacturer's protocols. Protein transfer was performed on a semi-dry blotting system (peqlab) onto polyvinylidene fluoride (BioTrace™ PVDF, Pall Corporation) membranes. Membranes were blocked o.n. in TBS and 1% Tween20 at 4◦C. Polyclonal primary antibodies against the PII protein (serum, produced in rabbit) or the AtpB protein (Abcam 65378, produced in rabbit) were incubated for 2 h at RT in a 1:5000 dilution in TBS-T after washing of the membrane with TBS-T buffer. Membranes were washed again and peroxidase coupled secondary antibody (Sigma A6154) was added in a 1:2000 dilution for 1 h at RT. Proteins were visualized by Lumi-Light Plus detection reagent (Roche).

#### Results

As an initial step to systematically approach the global phosphoproteome of Synechocystis PCC 6803, we first performed a conventional qualitative gel-free phosphoproteome analysis, based on TiO2 enrichment of phosphopeptides from a tryptic digest of the crude protein extract, followed by mass spectrometry (MS) analysis. In order to achieve the most comprehensive coverage of the phosphoproteome, we compared three common sample preparation workflows for MS identification of phosphorylation events as well as for total proteome analysis (see below). Based on the obtained results, we applied the most successful protein extraction strategy for a quantitative study to analyze phosphoproteome dynamics in response to nitrogen starvation.

#### The Qualitative (Phospho)Proteome of Synechocystis under Growth on Nitrate

Cells were harvested from a nitrate-grown Synechocystis culture at mid exponential growth phase (OD750 = 0.6) and split into three equal parts that were subjected to the following workflows: (A) Filter Aided Sample Preparation (FASP), (B) protein extraction as in the FASP protocol in combination with acetone/methanol protein precipitation, and (C) extraction with Y-PER in combination with acetone/methanol protein precipitation (hereafter designated as methods A, B and C, respectively; for details see Materials and Methods). For total proteome analyses, one portion of the sample was fractionated into five fractions by strong anion exchange chromatography. The remaining sample was used for five consecutive rounds of phosphopeptide enrichment by TiO2 chromatography. All samples were analyzed by nanoLC-MS/MS on an LTQ Orbitrap XL mass spectrometer.

On the proteome level, 2055 proteins were identified in the combined analysis of all three tested sample preparation workflows, including proteins detected in the proteome measurements and (unmodified) proteins detected from the TiO2 chromatography. Method A recovered 1835 proteins, method B 2014 proteins and method C 1983 proteins in total (Supplementary Table 1). At the phosphoproteome level, 301 phosphorylation events were identified with high confidence after manual validation of phosphopeptide MS/MS spectra, of which 262 non-redundant phosphorylation events, corresponding to 242 non-redundant phosphopeptides and 188 phosphoproteins, could be located on a specific S/T/Y residue. Additionally, 39 non-redundant phosphorylation events could be located on specific peptides and are referred to as unlocalized. Method A, B or C recovered, respectively, 21, 235, or 67 non-redundant phosphorylation events in total (Supplementary Table 2; Supplementary Information 1).

We concluded that all three methods had a similar performance on the protein level; however, striking differences in the performance were observed on the phosphoproteome level, with method B obviously being the method of choice. These results clearly demonstrate the importance of a potent and suited protein extraction protocol for the analysis of the phosphoproteome in organisms with a high content of membranous compartments such as cyanobacteria. As evidenced here, the overall number of identified proteins did not automatically lead to high numbers of identified phosphorylation events. Since phosphorylation events have in many cases a low occupancy in prokaryotic organisms (Soares et al., 2013), the quantity of specific extracted (phospho)proteins may be crucial, however this issue only can be analyzed in a quantitative experiment.

#### Quantification of the Synechocystis (Phospho)Proteome

The qualitative phosphoproteome analysis of the nitrate-grown Synechocystis sp. PCC 6803 cells showed a high abundance of protein S/T/Y phosphorylation; therefore, we were interested in the dynamic response of the (phospho)proteome in response to nitrogen starvation. Since autotrophically growing cyanobacteria are not suitable for metabolic stable isotope labeling, we used a protocol in which samples are labeled after protein digestion, using stable isotope dimethylation of peptides on N-termini and lysine side chains (Boersema et al., 2009). The experimental setup allowed us to analyze and compare three different metabolic conditions: (1) cells exponentially growing on nitrate; (2) cells exponentially growing on ammonia; (3) cells from nitrogen-free medium (nitrogen starvation for 24 h after growth on nitrate). We utilized this approach to perform a global quantitative phosphoproteome study including two experiments with slightly different cultivation settings. In the first experiment, cells from a stationary culture were diluted into fresh medium, grown to an optical density of 0.6 and then used as an inoculum for the final experimental culture. In the second experiment, the cells were pre-adapted to their respective nitrogen source by five cultivation cycles, from where the final experimental culture was started. The exact cultivation conditions for both experiments are described in the Materials and Methods section. The comparison between nitrate and ammonium-grown cells was not further addressed in this study.

Proteins were extracted from cell pellets by "method B" as described in Materials and Methods, precipitated by acetonemethanol mixture and subjected to in-solution digestion by trypsin. Obtained peptide solutions were loaded onto C18 reverse phase columns and subsequently chemically labeled by dimethylation. Different isotopoloques of formaldehyde and cyanoborohydride were used: Samples from nitrate grown cultures were light labeled with CH2O and NaBH3CN, samples from ammonia grown cultures were medium-heavy labeled with CD2O and NaBH3CN and samples from nitrogen starved cells were heavy labeled with 13CD2O and NaBD3CN. Labeling efficiency was in all cases 94% or greater (Supplementary Information 2). Labeled samples from nitrate (NO− 3 ; light), ammonium (NH+ 4 ; medium-heavy), and nitrogen starved (-N; heavy) cells were then mixed in a ratio of 1:1:1 based on the underlying protein amounts. Correct mixing of labeled peptides was validated by a dedicated MS measurement. The mixed sample was used for proteome and phosphoproteome analyses. For proteome analysis, isoelectric focusing (IEF) of the peptide mixtures was performed (OffGel strategy) and phosphopeptide enrichment was conducted by TiO2 chromatography in two technical replicates. All samples were analyzed by nanoLC-MS/MS on an LTQ Orbitrap Elite mass spectrometer. The experimental workflow is shown in Supplementary Information 3. To exclude quantification bias of phosphorylation events induced by possible alterations in the abundance of the corresponding proteins, measured phosphopeptide ratios were normalized by the respective unmodified protein ratios from the proteome measurements.

#### Technical Reproducibility of the Experiments

To estimate the technical reproducibility of the phosphoproteome, we analyzed the correlation of phosphorylation event ratios, determined by phosphopeptide enrichments, between the two technical replicates of each experiment. To this end, we calculated Pearson correlation coefficients of 65 and 67 shared quantified phosphorylation events between technical replicates for experiments 1 and 2, respectively. The calculated Pearson correlation coefficients of unnormalized phosphorylation events were 0.905 for –N/NO− 3 ratios and 0.937 for –N/NH+ 4 ratios for the first experiment and 0.948 for –N/NO− 3 ratios and 0.913 for –N/NH+ 4 ratios for the second experiment, revealing a good technical reproducibility and high overlap of phosphorylation events. Correlation plots from technical replicates of phosphopeptide ratios are shown in the supplement (Supplementary Information 4). When comparing the correlation between experiments 1 and 2 in the final dataset, differences on the proteome level as well as on the phosphoproteome level could be observed, which might be accounted to the different preculture treatments. On the proteome level, the calculated Pearson correlation coefficients were 0.758 for –N/NO− 3 protein ratios and 0.867 for –N/NH+ 4 protein ratios between experiments 1 and 2. On the phosphoproteome level, the Pearson correlation coefficient were 0.687 for 87 shared –N/NO− 3 phosphorylation event ratios and 0.638 for 89 shared –N/NH+ 4 phosphorylation event ratios between experiments 1 and 2 (Supplementary Information 5).

#### Protein Phosphorylation Dynamics in Response to Nitrogen Starvation

The combined dataset including proteome and phosphoproteome measurements from all experiments led to the overall identification of 232,924 MS/MS spectra, covering 16,774 nonredundant peptides from 2382 proteins. The estimated false discovery rate (FDR) was 0.18% at the peptide level and 1.04% at the protein level. Of the identified 2382 proteins, 2111 proteins fulfilled the requirement of having at least two quantification events (ratio counts) in at least one of both experiments and were considered as quantified.

Wang and coworkers cataloged the so far identified Synechocystis sp. PCC 6803 proteome by combining previously published proteome studies. Thereby, they reported a total of 1738 experimentally identified proteins, which amounts to 47.3% of the possible 3672 protein coding genes listed on Cyanobase (Wang et al., 2009). By comparison, the present quantitative gelfree proteome analysis identified 64.9% of the theoretical Synechocystis proteome (2382 of 3672 proteins), with a quantification rate of 57.5% of the total proteome (2111 of 3672). These numbers are presumably close to the completeness of the expressed proteome under the actual experimental conditions, since of the previously identified 1738 proteins, 90.0% (1565) were also identified in the present study. Of the 1935 previously unidentified proteins, 44.3% (857) were identified and 32.0% (620) were even quantified in our combined dataset. In a global transcriptome study, analyzing ten different growth and stress conditions, Kopf and coworkers could recently identify a total of 3101 expressed genes in Synechocystis. Under nitrogen starvation and nitrate growth conditions, approximately 75% of these expressed genes were present (approx. 2300) (Kopf et al., 2014). These results match very closely to the number of identified proteins in our MS based analysis (2382).

On the phosphoproteome level, manual inspection of phosphopeptide MS/MS spectra identified in both experiments 183 S/T/Y phosphorylation events with high confidence. Of these, 148 phosphorylation events, corresponding to 86 phosphoproteins, fulfilled the following two criteria: quantification of the phosphorylation event with at least two ratio counts in at least one experiment and normalization by the corresponding protein ratio of the respective experiment. Of these 148 phosphorylation events, 105 were quantified in experiment 1 and 130 in experiment 2, with an overlap of 87 phosphorylation events between both experiments. All detected proteins and phosphopeptides (including unlocalized and localized phosphorylation events) from the quantitative study are shown in the supplement (Supplementary Tables 3, 4).

As a test case for our quantitative mass spectrometry acquired (phospho)proteome data, we analyzed the expression profile of the nitrogen regulatory signal protein PII by immunoblot analysis on the protein level by SDS-polyacrylamide gel electrophoresis (PAGE) and on the phosphorylation level by non-denaturing PAGE (Forchhammer and Tandeau De Marsac, 1994). Under nitrogen-limiting conditions, the PII signal protein accumulates, associated with enhanced phosphorylation of residue Ser49 at the apex of the surface exposed T-loop (Forchhammer, 2004). Under nitrogen-depleted conditions, all three subunits of the homotrimeric PII protein are phosphorylated (Forchhammer and Tandeau De Marsac, 1994). In the present experiments, PII protein levels were similar between nitrate or ammonium grown cells but increased under nitrogen starvation (**Figure 2**). This is in accordance with transcription analysis of the glnB gene (encoding the PII protein), showing up-regulation under nitrogen starvation (Fadi Aldehni et al., 2003; Aguirre Von Wobeser et al., 2011). The result of the analysis of the PII phosphorylation state by non-denaturing PAGE from both experiments is shown below in the figure. As expected, the Ser49 phosphorylation strongly increased under nitrogen starvation, with the phosphorylated PII trimer isoforms becoming the most prominent bands. The unphosphorylated PII protein is in contrast the most intense band in nitrate and ammonia grown conditions. Overall, MS based quantification of the PII signaling protein with respect to protein abundance as well as on the phosphorylation level, as indicated in the figure, is in good agreement with the immunoblot results, implying that the quantitative MS analysis is valid.

To analyze the response of the Synechocystis phosphoproteome to nitrogen starvation, we classified the quantified –N/NO− 3 and –N/NH+ 4 phosphorylation event ratios into up- or down-regulated and static patterns, separately for both experiments (**Figure 3**). Functional assignment of phosphoproteins, comprising all proteins with one or more quantified phosphorylation events in our dataset (proteins with multiple phosphorylation events were only listed once), could be retrieved from InterPro database. InterPro protein terms were obtained for 81 of the 86 phosphoproteins. For classification of phosphorylation event ratios, we defined an arbitrary threshold of a twofold change; phosphorylation events with a ratio below 0.5 were classified as down-regulated; phosphorylation events with ratios above 2.0 were classified as up-regulated; phosphorylation events with a ratio between 0.5 and 2.0 were classified as static. Interestingly, a difference in the percentage of regulated or static phosphorylation events was observed between both experiments in response to nitrogen starvation (for –N/NO− 3 and –N/NH+ 4 ratios). In experiment 1, characterized by a short pre-adaptation to the respective nitrogen sources, the majority of phosphorylation events revealed a static pattern, whereas, in experiment 2, characterized by a long pre-adaptation, the majority revealed up-regulation. In both experiments, downregulated phosphorylation events revealed the lowest occurrence. The occurrence and frequency of InterPro terms was analyzed in the three classes (down-regulated, static or up-regulated) between –N/NO− 3 and –N/NH+ 4 ratios for each experiment (see **Figure 3**), to reveal whether the phosphorylation pattern correlates with potential protein functions. Whereas, for downregulated phosphoproteins this analysis did not reveal any results, globin-like proteins (e.g., phycobilisome) revealed in all cases static phosphorylation patterns. In addition, phosphorylation on anti-sigma antagonist proteins was in principal static in the first, but up-regulated in the second experiment. With the exception of the –N/NH+ 4 ratios in experiment 1, phosphorylation on adenylyl/guanylyl cyclase proteins was in principal up-regulated. In experiment 2, following proteins showed additionally up-regulated phosphorylation dynamics: proteins of photosystem I (PSI) and RuBisCO, as well as P-loop NTPase and N-regulatory PII and PII-like proteins. However, in experiment 1, these phosphoprotein classes did not fulfill the requirement of having at least two up-regulated evidences. The respective classified proteins are indicated in Supplementary Information 6.

This classification provides a comprehensive overview about general protein functions, which are frequently regulated under

#### FIGURE 2 | Immunoblot validation of PII protein and phosphorylation dynamics. The change in protein abundance (SDS PAGE) and phosphorylation (Clear native PAGE) of the N-regulatory PII protein between nitrate- (NO− 3 ) or ammonia-grown (NH+ 4 ) and 24h h nitrogen starved cells (-N24h ) from both experiments is shown on the left panel. P 0 II represents the

unphosphorylated trimeric complex and P 1–3 II represent PII trimers with one, two and three phosphorylated subunits. The AtpB protein serves as loading control for SDS and Clear native PAGE. Corresponding MS acquired protein and phosphorylation event ratios in log2 scale, relative to the NO− 3 are shown on the right panel.

nitrogen starvation by S/T/Y phosphorylation in Synechocystis. In order to obtain a more detailed insight about specific phosphorylation events with strong dynamics, and their abundance under the studied conditions, we plotted the quantified phosphorylation event –N/NO− 3 and –N/NH+ 4 ratios against the respective phosphopeptide intensities, separately for each experiment (**Figure 4**). Based on the overall distribution of the specific phosphorylation events, significantly regulated events (both, localized and unlocalized on the detected peptide) were identified by significance analysis, (p-value = 0.05; for details see Materials and Methods). Phosphorylation events revealing significant up- or down-regulation are depicted in the scatter plots as stars (in red), and the respective phosphoprotein and modification site (or phosphopeptide span in case of unlocalized phosphorylation events) is indicated. All significant phosphorylation events (between N/NO− 3 and –N/NH+ 4 ratios) from both experiments are listed in **Table 1**.

As expected from previous studies, PII (Ssl0707) Ser49 phosphorylation exhibited the highest level of increase in phosphorylation and intensity throughout all experiments in response to nitrogen starvation. Interestingly, two Ser/Thr protein kinases with contrary phosphorylation dynamics were identified: The Ser/Thr protein kinase C (Slr0599) revealed multiple significantly down-regulated phosphorylation events in experiment 1 and for one of them in experiment 2. Four out of five events could be localized on a specific Thr residues (on positions 291, 297, 312, and 319), and one event could be quantified on the phosphopeptide 324VYTQEFTGYTETQEGSPLMK343 . In contrast, the putative Ser/Thr protein kinase F (Slr1225) revealed one significantly up-regulated phosphorylation event, which was quantified on the phosphopeptide 324APPGATV STPQGTNTQIQPTPASSASPLTAPK355 for –N/NO− 3 ratios in experiment 1.

Other significantly down-regulated phosphorylation events were detected in experiment 1 on Ser144 of the largeconductance mechanosensitive channel (Slr0875) and on the phosphopeptides 28TDVGPITTPNPQK40 and 187LVAAG VILPLSERSASR203 of the hypothetical proteins Slr0483 and Sll0505, respectively. The phosphopeptide 100LQSELSTL EQELAQQDSSPTGPGEEQKSSR129, Ser4 and Ser49 of the hypothetical proteins Slr1686 and Sll0822 and the phycocyanin beta subunit (Sll1577), respectively, revealed down-regulated phosphorylation events in experiment 2. Interestingly, down-regulated phosphorylation on Ser65 of

the 2,3-bisphosphoglycerate-independent phosphoglycerate mutase (Slr1945) was detected in both experiments for only –N/NH+ 4 ratios. Among other proteins with significantly up-regulated phosphorylation events in our study, Ser64 phosphorylation of the unknown protein Sll0981 was detected in experiment 1, whereas, phosphorylations on Thr4 of the hypothetical protein Slr0397 and Thr349 and Thr361 of the hypothetical protein Sll0103 were detected in both experiments. Remarkably, the sodium-dependent bicarbonate transporter SbtA (Slr1512) revealed in our study down-regulation of Thr189 phosphorylation in experiment 1, whereas, the neighboring gene product, the PII-like membrane-associated protein SbtB (Slr1513), revealed significant up-regulation on Thr53 in experiment 2 in response to nitrogen starvation. For a complete

#### TABLE 1 | List of significantly regulated phosphorylation events.

overview of the detected phosphorylation events revealing significant regulation in response to nitrogen starvation, see **Table 1**.

#### Discussion

#### Sample Preparation and Dimethylation Labeling for Phosphoproteome Quantification

Numerous previous studies revealed insights with regards to the Synechocystis proteome and shed first light into the phosphoproteome. However, most of these studies were exclusively focused on specific cellular compartments such as different membrane fractions or the cytoplasm or on specific proteins. Therefore, most previous studies mapped only "snapshots" of either delimited cellular compartments or only one particular metabolic condition of the proteome or the phosphoproteome, mainly performed in a qualitative manner, based on 2D gel strategies. The present study aimed to establish a method to analyze the global dynamic changes of the Synechocystis phosphoproteome in a site specific and quantitative manner between distinct metabolic conditions. In the present study, this was exemplified using nitrate and ammonia grown cells in comparison to 24 h nitrogen starved cells.

This study led to a comprehensive detection of the entire expressed proteome, including the identification of 857 and the quantification of 620 previously not identified proteins, and thus far is the largest reported dataset of phosphorylation events in Synechocystis. The efficient extraction of phosphoproteins contributed in combination with a gel-free MS strategy to a high percentage of detections in the qualitative phosphoproteome dataset. Although similar identification numbers were detected on the proteome level, when comparing method B with the detergent buffer based method C (Y-PER), significantly more localized phosphorylation events (235 vs. 67) could be obtained exclusively with method B. This may be due to the fact that the overall extraction efficiency of hydrophobic proteins was higher with method B compared the other methods. In bacteria, phosphorylation events are predominantly present in low occupancy compared to eukaryotes. Therefore, an overall small percentage of phosphoproteins are actually phosphorylated compared to the respective unmodified protein (Soares et al., 2013). When more copies of a certain phosphoprotein with low phosphorylation occupancy are present in the sample, the chances to detect the phosphorylation event or even to localize the modified S/T/Y site are much higher. This becomes especially relevant for quantitative studies, where the corresponding phosphorylation events must be detected in all samples and stages, even if their abundances are strongly fluctuating as in the case of regulated phosphorylation events.

Subsequent to an efficient protein extraction method from the cyanobacterial samples, the quantification technique is crucial. Although many different techniques for quantitative phosphoproteome studies have been reported, SILAC has been established as a precise and robust method firstly in eukaryotic and later in prokaryotic organisms (Ong et al., 2002; Soufi et al., 2010). Previously, we could detect the phosphoproteome dynamics of the model bacterium E. coli K-12 throughout the growth in minimal medium (Soares et al., 2013). However, in autotrophic cyanobacteria species, metabolic SILAC labeling would require severe disruptions in the nitrogen metabolic pathway by knocking out key enzymes of the lysine and/or arginine amino acid synthesis pathways. We decided to bypass this drawback by application of chemical stable isotope labeling based on dimethylation of peptides on a C18 column as described earlier. As mentioned, the methodology was applied before successfully in quantitative phosphoproteome studies, but limited to the eukaryotic domain as reviewed previously (Kovanich et al., 2012).

Here, we expanded this method to the quantitative phosphoproteome analysis in prokaryotic organisms. All validation steps of the labeling methodology confirmed a high quality of the experiments. The labeling efficiency was high (≥94%). The correlation between technical replicates of the phosphoproteome revealed high reproducibility and the overlap of quantified phosphorylation events between technical replicates (see Supplementary Information 4) and experiments (see Supplementary Information 5) was high. We conclude that the dimethylation labeling strategy combined with an efficient protein extraction method is highly suitable for systematically detecting phosphoproteome dynamics in (cyano)bacteria.

#### Dynamics of Protein S/T/Y Phosphorylations Involved in Nitrogen and Carbon Metabolism and Photosynthesis under Nitrogen Starvation

In bacteria, research on protein phosphorylation on Ser/Thr and Tyr residues in the past years led to accumulating evidences revealing this modification as one of the most prominent mechanisms in signal transduction for fast cellular responses to environmental changes (Macek and Mijakovic, 2011; Soufi et al., 2012). Moreover, previous phosphoproteomic studies have revealed that a large portion of these phosphorylation events are associated with key metabolic processes in a cell, however, detailed information of the phosphorylation functions are rare. For cyanobacteria, having an autotrophic lifestyle, fast response to changing environmental conditions that affect the energy-, nitrogen-, and carbon metabolism appears to be essential. This statement agrees with the high numbers of identified and quantified phosphorylation events in our dataset that can be assigned to photosynthesis, carbon and nitrogen uptake and subsequent metabolic pathways.

Of the significantly regulated phosphoproteins, the sensory nitrogen signaling PII protein showed the strongest dynamics in response to nitrogen starvation with Ser49 phosphorylation being strongly up-regulated. This is in agreement with previous studies and emphasizes its role as a marker for nitrogen-limited conditions (Forchhammer and Tandeau De Marsac, 1994, 1995; Mikkat et al., 2014). In E. coli, it was reported, that the PII homolog protein GlnK regulates the influx of ammonia from the surrounding medium through the homotrimeric ammonium/methylammonium permease AmtB, and GlnK-AmtB interaction blocks the uptake (Van Heeswijk et al., 1996). A similar mechanism, although not yet demonstrated, could be assumed in Synechocystis between PII and the AmtB homologue Amt1 (Sll0108), with the PII Ser49 phosphorylation preventing this interaction to ensure efficient ammonia uptake under N-limited conditions. Interestingly, we identified Amt1 as a phosphoprotein, which is increasingly phosphorylated under N-limitation. This mechanism could reveal an additional and more sensitive regulative control mechanism to ensure maximum ammonia uptake. Remarkably, the PII-like membrane-associated protein SbtB (Slr1513) revealed significant increasing Thr53 phosphorylation under N-limitation, like the GlnB PII protein. Interestingly, the sbtB gene is neighboring the sodium-dependent bicarbonate transporter Slr1512 (sbtA) gene on the chromosome, which revealed in our analysis significant decreasing Thr189 phosphorylation under the same conditions. It is thus tempting to speculate that SbtB may be involved in regulation of SbtA activity, in agreement with a recent analysis of the sbtAB operon (Du et al., 2014).

Phosphorylation of proteins involved in the inorganic carbon uptake mechanism and the Calvin cycle was also observed: On the carbon dioxide concentrating mechanism (Ccm) proteins M and N (Sll1031 and Sll1032), multiple phosphorylation events were detected, of which three could be quantified and localized on Sll1031 (pSer352, pThr358, and pThr609) and one on Sll1032 (pThr121). These phosphorylation events generally showed either static or slightly increasing phosphorylation under N-depletion, with the most prominent regulation on pThr609, showing up to threefold increase for –N/NH+ 4 ratios. More pronounced, phosphorylation of the phosphoribulokinase (Sll1525) on Ser17 increased strongly upon N-starvation. In addition, two phosphorylation events were quantified on the small and large subunits of the ribulose bisphosphate carboxylase/oxygenase RuBisCO (Slr0012 and Slr0009), both showing a three- to fourfold increase in response to nitrogen starvation. Both phosphorylation events are localized on seryl-residues, Ser78 on the small and supposedly Ser323 on the large subunit. Interestingly, similar phosphorylation sites were identified in a phosphoproteome study of Arabidopsis thaliana on the respective subunits. Here, Ser71 and Ser321 were phosphorylated on the small and large subunits, respectively, besides several other phosphorylation events (Aryal et al., 2011).

Several enzymes involved in the pentose phosphate pathway and in glycolysis were detected as phosphoproteins, generally with static or increasing phosphorylation dynamics toward N-starvation, such as the fructose-bisphosphate aldolase (Sll0018) and the 6-phosphogluconate dehydrogenase (Sll0329). Interestingly, the 2,3-bisphosphoglycerate-independent phosphoglycerate mutase (Slr1945) elicited an opposite response, with the level of Ser65 phosphorylation significantly decreasing under N-depletion.

Cyanobacteria are considered as progenitors of chloroplasts, which explains why the photosynthetic apparatus is highly similar to that of green plants. However, some features are unique to cyanobacteria, such as the phycobilisome light harvesting antenna, transferring light energy to the PSII. Previously, linker proteins from the phycobilisome antenna and ferredoxin-NADPH reductase were identified as phosphoproteins in Synechocystis, and dephosphorylation was driven upon long-term exposure to high light intensities and under nitrogen limitation, initiating proteolytic cleavage and degradation (Piven et al., 2005). In our study, we detected a high abundance of phosphorylation on proteins from the photosynthesis apparatus; we detected in the qualitative dataset 60 phosphorylation events on specific S/T/Y residues from 24 proteins associated with photosynthesis (see Supplementary Table 2). During quantitative analysis, only nine phosphoproteins associated with photosynthesis could be detected. This is in agreement with the general tendency of less identified phosphorylation events in the quantitative dataset.

Among the detected proteins, the most prominent dynamics were observed for PSI, phycocyanin and allophycocyanin proteins. Surprisingly, phosphorylation events on these proteins revealed increasing levels under nitrogen starvation, in contrast to the phycobilisome antenna linker proteins, which were described to undergo dephosphorylation under nitrogen starvation. We were not able to quantify the phosphorylation events on linker proteins. On the proteome level, we detected strong decreasing levels of linker proteins Sll1579 and Sll1471, whereas, all other linker proteins (Slr1459, Slr0335, Sll1580, Slr2051, Ssr3383, and Ssl3093) revealed only slight decreasing or static levels under nitrogen starvation. This result could indicate that either the process of chlorosis has not occurred to a level that is required in order to significantly reduce the level of phycobiliproteins, or phycobiliproteins were only partially degraded and peptide fragments were still present in the cells, which were then detected by MS analysis. To solve this issue, further experiments containing earlier and later time points are required.

#### Dynamics of Serine/Threonine Kinases

In our quantitative phosphoproteome dataset, we observed an overall trend of increased phosphorylation levels during nitrogen limitation. These dynamics are visualized in **Figures 3**, **4**. Overall, there was a higher incidence of increasing than of decreasing phosphorylation in response to nitrogen limitation. This observation is more pronounced in experiment 2, characterized by longer pre-adaption in the respective nitrogen source. Interestingly, two Ser/Thr protein kinases were found among the phosphoproteins with significantly fluctuating phosphorylation dynamics. Ser/Thr protein kinase F (Slr1225) displayed in response to nitrogen starvation increasing phosphorylation of two phosphothreonines on positions 24 and 27 (2–3 fold increased), and on

#### References

an unlocalized phosphorylation event on the phosphopeptide 324APPGATVSTPQGTNTQIQPTPASSASPLTAPK355. Contrary, we identified four phosphothreonines to be significantly decreasing under the same conditions on the Ser/Thr protein kinase C (Slr0599) and one unlocalized phosphorylation event (see **Table 1**). These two Ser/Thr kinases were shown previously in vitro by radiolabeling experiments to autophosphorylate (Kamei et al., 2002). Furthermore, both kinases were suggested in combination with Ser/Thr protein kinase K to be required for a phosphorylation cascade resulting in GroES phosphorylation (Zorina et al., 2011). It is conceivable that the phosphorylation dynamics of both kinases are interconnected and could involve a protein phosphatase.

In conclusion, this study reports the first global phosphoproteome analysis of Synechocystis, with the highest discovery rate of proteins (2382) and phosphorylation events (301 under nitrogen growth conditions) described thus far. We showed quantitative dynamics of the total proteome in response to nitrogen starvation. This is not only of broad relevance for Synechocystis molecular biology, but sets the ground for a comprehensive analysis of the phosphoproteome, with quantified dynamics of 148 phosphorylation events. Using nitrogen starvation acclimation as a test case, this study reveals that protein S/T/Y phosphorylation may play an outstanding regulatory role for metabolic adaptation in the model cyanobacterium Synechocystis. This analysis paves the way for an in depth analysis of the role of protein phosphorylation in cyanobacteria, to unravel its contribution to homeostatic control.

#### Acknowledgments

BM and KF thank the SFB766 of the Deutsche Forschungsgemeinschaft for financial support. Furthermore, we would like to thank all members of the Proteome Center Tuebingen, especially Boumediene Soufi for revising the manuscript, and the Department of Organismic Interactions, especially Khaled Selim for help with immunoblots and Alexander Klotz for help in graphics preparation.

#### Supplementary Material

The Supplementary Material for this article can be found online at: http://www.frontiersin.org/journal/10.3389/fmicb. 2015.00248/abstract

Synechococcus 6301," in Progress in Photosynthesis Research, ed J. Biggins (Dordrecht: Springer), 773–776.

**Conflict of Interest Statement:** The Guest Associate Editor Ivan Mijakovic declares that, despite having coauthored an article with the author Boris Macek in 2014, the review process was handled objectively.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Spät, Maˇcek and Forchhammer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

## Redox regulation by reversible protein *S*-thiolation in bacteria

#### Vu Van Loi, Martina Rossius and Haike Antelmann\*

*Institute of Microbiology, Ernst-Moritz-Arndt-University of Greifswald, Greifswald, Germany*