# MICROBIAL STRESS: FROM SENSING TO INTRACELLULAR AND POPULATION RESPONSES

EDITED BY : Daniela De Biase, John P. Morrissey and Conor P. O'Byrne PUBLISHED IN : Frontiers in Microbiology

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ISSN 1664-8714 ISBN 978-2-88966-024-7 DOI 10.3389/978-2-88966-024-7

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# MICROBIAL STRESS: FROM SENSING TO INTRACELLULAR AND POPULATION RESPONSES

Topic Editors:

Daniela De Biase, Sapienza University of Rome, Italy John P. Morrissey, University College Cork, Ireland Conor P. O'Byrne, National University of Ireland Galway, Ireland

Citation: De Biase, D., Morrissey, J. P., O'Byrne, C. P., eds. (2020). Microbial Stress: From Sensing to Intracellular and Population Responses. Lausanne: Frontiers Media SA. doi: 10.3389/978-2-88966-024-7

# Table of Contents

*06 Editorial: Microbial Stress: From Sensing to Intracellular and Population Responses*

Daniela De Biase, John P. Morrissey and Conor P. O'Byrne

Srinivasan Vijay, Hoang T. Hai, Do D. A. Thu, Errin Johnson, Anna Pielach, Nguyen H. Phu, Guy E. Thwaites and Nguyen T. T. Thuong

*52 Genetic and Physiological Adaptations of Marine Bacterium* Pseudomonas stutzeri *273 to Mercury Stress*

Rikuan Zheng, Shimei Wu, Ning Ma and Chaomin Sun

Yinka M. Somorin, Tara Vollmerhausen, Nicholas Waters, Leighton Pritchard, Florence Abram, Fiona Brennan and Conor O'Byrne

Ashley Smith, Agnieszka Kaczmar, Rosemary A. Bamford, Christopher Smith, Simona Frustaci, Andrea Kovacs-Simon, Paul O'Neill, Karen Moore, Konrad Paszkiewicz, Richard W. Titball and Stefano Pagliara

Erhao Zhang, Yueqing Cao and Yuxian Xia

Isidro Álvarez-Escribano, Agustín Vioque and Alicia M. Muro-Pastor

*177 Sodium Acetate Responses in* Saccharomyces cerevisiae *and the Ubiquitin Ligase Rsp5*

Akaraphol Watcharawipas, Daisuke Watanabe and Hiroshi Takagi

Geneviève Lorieux, Laurent Jourdren, Stéphane Le Crom, Gaëlle Lelandais, Eduardo Corel and Frédéric Devaux

*239 Investigation of the Role That NADH Peroxidase Plays in Oxidative Stress Survival in Group B* Streptococcus

Michelle L. Korir, Rebecca A. Flaherty, Lisa M. Rogers, Jennifer A. Gaddy, David M. Aronoff and Shannon D. Manning

Francesca M. L. Bushell, Peter D. Tonner, Sara Jabbari, Amy K. Schmid and Peter A. Lund

Hana Raschmanová, Iwo Zamora, Martina Borčinová, Patrick Meier, Astrid Weninger, Dominik Mächler, Anton Glieder, Karel Melzoch, Zdeněk Knejzlík and Karin Kovar

# Editorial: Microbial Stress: From Sensing to Intracellular and Population Responses

Daniela De Biase1 \*, John P. Morrissey 2 and Conor P. O'Byrne3

1 Department of Medico-Surgical Sciences and Biotechnologies, Laboratory Affiliated to the Istituto Pasteur Italia – Fondazione Cenci Bolognetti, Sapienza University of Rome, Latina, Italy, 2 School of Microbiology, Centre for Synthetic Biology and Biotechnology, Environmental Research Institute, APC Microbiome Institute, University College Cork, Cork, Ireland, 3 Microbiology, School of Natural Sciences, College of Science, National University of Ireland, Galway, Ireland

Keywords: acid stress, second messengers, transcriptional regulation, cyanobacteria, pathogens, organic acids, oxidative stress, biotechnology

#### **Editorial on the Research Topic**

#### **Microbial Stress: From Sensing to Intracellular and Population Responses**

#### Edited by:

Jörg Stülke, University of Göttingen, Germany

#### Reviewed by:

Thomas Schweder, University of Greifswald, Germany Matthew Cabeen, Oklahoma State University, United States

#### \*Correspondence:

Daniela De Biase<EMAIL_ADDRESS>
#### Specialty section:

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

> Received: 03 June 2020 Accepted: 25 June 2020 Published: 31 July 2020

#### Citation:

De Biase D, Morrissey JP and O'Byrne CP (2020) Editorial: Microbial Stress: From Sensing to Intracellular and Population Responses. Front. Microbiol. 11:1667. doi: 10.3389/fmicb.2020.01667 We initially devised this Research Topic (RT) as a valuable initiative to collect high-quality scientific articles from the participants of the 4th European Federation of Biotechnology (EFB) Microbial Stress meeting held in Kinsale, Ireland, April 2018. The scope of the RT is based on the scientific content of that "Microbial Stress: from Systems to Molecules and back" meeting. Indeed, over 40% of the articles eventually accepted for publication were contributed by meeting participants, but notably the remaining 60% was contributed by authors that work in this field. The collection of 22 original research and 2 review articles, contributed by 163 authors collectively, deal with the many different aspects of the microbial responses to biotic and abiotic stresses, relevant to many fields: from host-pathogen interactions to biotechnology, from bioremediation to food processing, from molecular and single-cell to population studies. The RT showcases the rapid developments of the microbial stress research on a range of microorganisms and stress conditions, and confirms that understanding microbial physiology under stress can be a trigger for the development of new methodologies as well as helping to integrate the knowledge from many different microbiological fields of research.

The retrospective analysis of the articles contributed to this RT allowed them to be assigned to one of four main sub-topics: (i) impact of weak organic acids and low pH on micro-organisms, from clinical to biotechnological contexts; (ii) adaptive responses in microbial pathogens to abiotic/environmental stress; (iii) oxidative and metal stress, from clinical to bioremediation contexts, and (iv) regulation of transcription and translation under stress, from epigenetic aspects to the role of second messengers and sRNAs.

### WEAK ORGANIC ACIDS AND LOW pH STRESS

An area of intensive research deals with the microbial responses to acids (inorganic or organic) because these are common encounters that can affect or even be a threat to microbial growth, with implications in many area of clinical and applied microbiology research.

Using a bioinformatic analysis, Pennacchietti et al. showed that the glutamine-dependent acid resistance (AR2\_Q) system in enteric bacteria is often associated with the glutamate-dependent AR system, the most potent AR system reported to date (De Biase and Pennacchietti, 2012). In addition, they developed a simple to perform, fast, and sensitive colorimetric assay which allowed the detection of the acid glutaminase, a key enzyme in AR2Q. The assay can find useful application in high-throughput phenotypic screens.

The use of weak organic acids was covered by three studies. Bushell et al. described a comprehensive characterization of the growth response of Pseudomonas aeruginosa to several organic acids over a range of pH values, with the long-term goal of using them in the treatment of topical infections caused by this pathogen. In their study, they found that the effects on the organic acids on growth could be best modeled with a nonparametric Gaussian process regression (rather than a parametric logistic approach), a finding that will undoubtedly help with modeling the growth behavior of other pathogens. Another study by Lourenço et al. provides insight into the effect of pH 4.0 and acetic acid or lactic acid on the efficacy of different azoles employed to treat vaginal candidiasis caused by two pathogenic fungi Candida albicans and Candida glabrata. In particular, acetic acid was shown to improve significantly the efficacy of all azoles tested, even on strains that were azole resistant. Thus, both studies point to an important role of these acids to treat infections or improve the efficacy of current therapeutic treatments.

A further article on yeast by Watcharawipas et al. reviewed the Saccharomyces cerevisiae response to sodium acetate. Sodium and acetic acid independently cause stress and activate appropriate responses in yeast but this article addressed the combined response to both. This illustrated the involvement of wellstudied stress response mechanisms such as the Rim101 and Hog1 pathways, as well as a role for the ubiquitin ligase Rsp5. Rim101 is a transcriptional activator, mainly studied for its role in adaptation to alkaline stress, whereas Hog1 is a protein kinase that is a key mediator of the response to osmotic shock. It is still unknown how the different pathways interact to deliver an integrated response to combined stressors with different modes of action.

A link between acid stress and osmotic stress was studied by Chakraborty and Kenney who investigated the role of OmpR in Salmonella enterica serovar Typhimurium and Escherichia coli strain MG1655. The authors demonstrated that the acid stress regulon is rather different in the number of affected genes between the two microorganisms, whereas the number of genes affected under osmotic stress is similar. Notably, in both microorganisms, OmpR repressed gltA, coding for citrate synthase, which otherwise negatively affected cell growth during stress. Moreover, OmpR binding affinity for DNA increased at acidic pH. Control of intracellular enzyme activities in response to acid frequently occurs via conformational changes (Gut et al., 2006) and these mechanisms contribute significantly to the physiological response of the cell to acid stress, even when changes at the expression level are not detected.

#### MICROBIAL PATHOGENS ADAPTIVE RESPONSES TO STRESS

Using a label-free relative quantitative proteomics approach, Zai et al. performed a detailed study aimed at dissecting the responses of Brucella abortus to different stresses singly and when applied all together, the most likely situation encountered by this intracellular facultative microorganism when infecting the host. Overall the results using the multi-stress condition suggested that B. abortus by decreasing the oxidation of nutrients and amino acid use, reducing the secondary metabolite biosynthesis, enhancing iron acquisition and two-component systems better adapted to the intracellular environment. The importance of stress adaptation in the human food-borne pathogen Listeria monocytogenes is highlighted in a broad review by Bucur et al. The regulatory mechanisms that underpin thermal adaptation, acid resistance, osmoregulation, and other food processing/preservation stresses were all comprehensively reviewed. The adaptability of this pathogen makes it a significant challenge for food producers, and remains a significant public health risk.

Some pathogens, such as Yersinia ruckeri, have optimal growth at 28◦C, but cause outbreaks in the fish host at 18◦C. To gain insights into the genes preferentially expressed at lower temperature and which could play a role in virulence, Mendez et al. used Mini-Tn5-lux-lac Km2 transposon to generate a library of 14,724 Y. ruckeri transconjugants, out of which 168 clones displayed β-galactosidase activity higher at 18◦C than at 28◦C. The acrR and osmY genes were analyzed in further detail by in vivo and ex vivo analysis of their promoters activation in different fish tissue during the colonization process via bioluminescence. The latter represents an interesting approach to significantly reduce the number of fish used in this kind of experiments. Another in vivo model, Galleria mellonella larvae, was used by Lee et al. to demonstrate that YfdX deficiency enhanced S. enterica serovar Typhi virulence while decreasing its susceptibility to penicillin G and carbenicillin. Through a combination of structural analyses (SEC-MALS, SAXS, crystallography) and mutagenesis studies the authors demonstrated that the tetrameric enzyme undergoes dissociation into dimers when the pH is increased from 5.5 to 8.0. Unlike the monomer, the oligomers were responsible for YfdX effectiveness in vivo, though the authors do not known if at different level/extent.

Metarizhium acridum alcohol dehydrogenase (MaADH1) expression and deletion effects on the growth and sporulation of this entomopathogenic fungi were investigated by Zhang et al. M. acridum belongs to a group of promising agents for biological control of pest insects such as locust and grasshopper in Africa, Asia and Australia. The authors showed that MaADH1 supports fungal growth and sporulation very likely because the enzyme detoxifies from acetaldehyde, in particular under hypoxic conditions.

A detailed analysis (hourly) of the transcriptome profile during the E. coli growth cycle in LB medium by Smith et al. revealed that the KEGG pathways "Ribosome" and "Microbial metabolism in diverse environments" were the most overrepresented in the different phases of growth (lag, exponential and stationary) when pH and nutrient availability change. Moreover, by using the persister phenotype as a proxy for changes in populations-wide heterogeneity, persisters were shown to increase during growth and the response of persisters formation to antibiotics was not only growth phase-dependent, but also affected by the composition of the medium containing the antibiotic. Thus, medium composition is an important consideration when screening for antibiotics against persisters.

### OXIDATIVE AND METAL STRESS

An interesting observation was made by Vijay et al. about the ultrastructure of Mycobacterium tuberculosis from sputum and from clinical isolates exposed to oxidative stress, antibiotic isoniazid or iron deprivation in vitro. Using Transmission Electron Microscopy, the authors demonstrated a significant reduction in thickness of the triple-layered cell envelope and the accumulation of intracytoplasmic lipid inclusions in all isolates exposed to the above stresses, but not in the M. tuberculosis H37Rv reference laboratory strain. The cellular adaptations in clinical isolates may well represent a signature of dormancy and antibiotic tolerance, making them possible targets for antibiotic treatment.

Oxidative stress is also encountered by pathogenic Group B Streptococcus in macrophages when they colonize the human female host. Korir et al. investigated the role of a putative NADH peroxidase Npx in protecting against phagosome-associated oxidative stress. They showed that a mutant lacking the corresponding gene (npx) was compromised for H2O2 survival and growth in human macrophages.

In yeast, oxidative stress is an issue both in pathogenic and biotechnological settings. For biotechnology, it is of interest to find ways to improve oxidative stress resistance and two papers addressed this. First, Vázquez et al. showed the protective effects of melatonin in different yeasts used in the beverage industry. This molecule is naturally produced by yeasts and knowledge of its protective effect open up possibilities to generate overproducing strains with enhanced stress tolerance. Liu et al. took a completely different approach that focused on creating a glutathione-dependent disulfide oxidoreductase gene (GRX1) with a noisy promoter. This also led to increased resistance to oxidative stress and highlights some interesting points around stochasticity and population structure: for example, whether natural variability is a positive or negative feature when engineering strains for biotechnology. This idea that yeast cultures display population heterogeneity is the focus of a separate study on the biotechnological yeast Pichia pastoris by Raschmanová et al. The authors used single cell approaches to identify four sub-populations that varied in the unfolded protein response and other cellular parameters. Understanding and controlling this has important implications for efficient production of recombinant proteins.

Mercury is a potent antimicrobial but resistance mechanisms have evolved in many microbial species. The mercury resistance gene cluster (mer) of the mercury resistant marine bacterium Pseudomonas stutzeri was characterized by Zheng et al. The cluster encodes transcriptional regulators (MerR and MerD), the structural genes required for the transport (MerP and MerT) and reductive detoxification of Hg2+ to Hg0 (MerA) as well as MerF. The latter, which has homologs in several other pathogenic bacterial species, was shown by the authors to influence motility and biofilm formation and contribute to mercury resistance.

#### REGULATION OF TRANSCRIPTION UNDER STRESS

Dostálová et al. investigated the σ D regulon of Corynebacterium glutamicum. The σ D factor of RNAP, which belongs to a group of extracytoplasmic σ factors, was recently found to be involved in envelope stress response, synthesis of mycomembrane and formation of cell wall (Toyoda and Inui, 2018). The authors showed that σ D increased the expression of 29 genes organized in 23 operons. Eleven promoter regions (encompassing 50 nucleotides) could be aligned and a consensus sequence derived. Using a combination of in vitro and in silico methods they provided evidence for overlapping functions of different sigma factors which should play a significant role in fine tuning of gene expression and coping with complex environmental stresses.

An interesting study on the global and specific changes in the m5C methylome was presented in the cyanobacterium Synechocystis sp. PCC 6803 by Hu et al. The authors demonstrated that 72 h of nitrogen starvation had no effect on the proportion of global m5C, rather on its distribution. In other words, nitrogen deficiency led to decrease of methylated sites, but the level of methylation of the m5C sites increased to an extent that balanced the decrease in the total methylated sites. The epigenetic pattern was partly inherited and still detectable after 12 generations, thus pointing to the methylome as a way to detect the stress history of a specific microorganism. Notably, no correlation was identified between level of methylation and increase/decrease of gene expression. Nitrogen stress was also investigated in the cyanobacterium Nostoc sp. PCC7120 by Álvarez-Escribano et al., though at the transcriptional and posttranscriptional level. The authors performed a detailed molecular study and demonstrated that a feed-forward loop is taking place involving the sRNA NsrR1 and the transcriptional regulator NtcA, which activated the gene nblA, encoding a protein adaptor for phycobilisome degradation under nitrogen deficiency. The authors showed that NtcA directly represses NsrR1, which in turn, when expressed, was responsible for repressing nblA expression by direct binding to its mRNA 5′ -UTR thereby interfering with the translation start, possibly causing nlbA mRNA destabilization.

The iron starvation response is important for virulence in pathogenic yeasts, so Benchouaia et al. used a transcriptomic and bioinformatic approach to study this in the human pathogen C. glabrata. By focusing on genes that responded differently to iron stress in C. glabrata and other yeasts, they identified novel genes required for surviving iron starvation in C. glabrata. The REGULOUT bioinformatic tool described in this paper is likely to be applicable also for other comparative transcriptomics studies.

The importance of cyclic dinucleotides in stress signaling and in modulating adaptive gene expression was reflected in three different papers and three distinct bacteria. While c-diAMP has been implicated as a second messenger in cell wall homeostasis in response to osmotic stress in several bacterial species its role in the physiology of cyanobacteria had not been investigated. Agostoni et al. showed that c-di-AMP levels were modulated differently in two cyanobacterial species in response to osmotic stress (by salt or sorbitol), suggesting a role in osmotic stress adaptation in the genus Synechocystis. In E. coli, c-di-GMP is well-known to influence biofilm formation as a result of its role in regulating the production of surface structures called curli. Somorin et al. reported that some soil persistent strains of E. coli have lost curli production because of mutations that negatively affect c-di-GMP pools. These strains had a reduced capacity to produce biofilm, suggesting that there may be niches in the soil occupied by E. coli that do not require biofilm formation. The links between c-di-GMP and biofilm formation in the opportunistic human pathogen P. aeruginosa were investigated by Strempel et al. In this case, hypochlorite stimulated biofilm formation by inducing expression of a c-di-GMP synthase. Given

#### REFERENCES

that HClO is a common disinfectant, the potential to modulate the very complex intracellular c-di-GMP signaling network in a serious pathogenic bacterium highlighted the need to further explore and better understand such finely balanced systems.

### AUTHOR CONTRIBUTIONS

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

#### ACKNOWLEDGMENTS

This topic was organized to accompany the 4th EFB Meeting Microbial Stress: from Systems to Molecules and Back, held in Kinsale (Ireland), 23-25 April 2018. We would like to take this opportunity to thank all the conference participants, and especially those who contributed their work to this topic.

Corynebacterium glutamicum. Mol. Microbiol. 107, 312–329. doi: 10.111 1/mmi.13883

**Conflict of Interest:** 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 © 2020 De Biase, Morrissey and O'Byrne. 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) and the copyright owner(s) 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.

# The Oxidative Stress Agent Hypochlorite Stimulates c-di-GMP Synthesis and Biofilm Formation in Pseudomonas aeruginosa

Nikola Strempel1 , Michael Nusser1 , Anke Neidig1 , Gerald Brenner-Weiss1† and Joerg Overhage1,2 \* †

1 Institute of Functional Interfaces, Karlsruhe Institute of Technology, Karlsruhe, Germany, 2 Department of Health Sciences, Carleton University, Ottawa, ON, Canada

The opportunistic human pathogen Pseudomonas aeruginosa is able to survive under a variety of often harmful environmental conditions due to a multitude of intrinsic and adaptive resistance mechanisms, including biofilm formation as one important survival strategy. Here, we investigated the adaptation of P. aeruginosa PAO1 to hypochlorite (HClO), a phagocyte-derived host defense compound and frequently used disinfectant. In static biofilm assays, we observed a significant enhancement in initial cell attachment in the presence of sublethal HClO concentrations. Subsequent LC-MS analyses revealed a strong increase in cyclic-di-GMP (c-di-GMP) levels suggesting a key role of this second messenger in HClO-induced biofilm development. Using DNA microarrays, we identified a 26-fold upregulation of ORF PA3177 coding for a putative diguanylate cyclase (DGC), which catalyzes the synthesis of the second messenger c-di-GMP – an important regulator of bacterial motility, sessility and persistence. This DGC PA3177 was further characterized in more detail demonstrating its impact on P. aeruginosa motility and biofilm formation. In addition, cell culture assays attested a role for PA3177 in the response of P. aeruginosa to human phagocytes. Using a subset of different mutants, we were able to show that both Pel and Psl exopolysaccharides are effectors in the PA3177-dependent c-di-GMP network.

Keywords: Pseudomonas aeruginosa, bacterial stress response, biofilm formation, c-di-GMP, oxidative stress, pathogen

#### INTRODUCTION

Pseudomonas aeruginosa is a widespread Gram-negative water and soil bacterium, which is in addition one of the most important opportunistic human pathogens causing severe infections in immunocompromised persons (Hancock and Speert, 2000; Stover et al., 2000). Moreover, P. aeruginosa is the leading cause of chronic pneumonia in patients suffering from cystic fibrosis (CF) (Rajan and Saiman, 2002). The high pathogenicity of P. aeruginosa is linked to its intrinsic resistance to several commonly used antibiotics, the ability to rapidly adapt to varying environmental conditions and the expression of a large arsenal of virulence factors, which facilitate bacterial invasion and the establishment of persistent infections in host organisms (Breidenstein et al., 2011).

#### Edited by:

John P. Morrissey, University College Cork, Ireland

#### Reviewed by:

Jerry Reen, University College Cork, Ireland Giordano Rampioni, Università degli Studi Roma Tre, Italy

#### \*Correspondence:

Joerg Overhage<EMAIL_ADDRESS>†These authors are joint senior authors.

#### Specialty section:

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

> Received: 18 September 2017 Accepted: 08 November 2017 Published: 22 November 2017

#### Citation:

Strempel N, Nusser M, Neidig A, Brenner-Weiss G and Overhage J (2017) The Oxidative Stress Agent Hypochlorite Stimulates c-di-GMP Synthesis and Biofilm Formation in Pseudomonas aeruginosa. Front. Microbiol. 8:2311. doi: 10.3389/fmicb.2017.02311

Under environmental stress conditions, P. aeruginosa is able to form robust biofilms in which surface-associated bacteria are embedded in a self-produced matrix (extrapolymeric substances; EPS) (Costerton et al., 1994; Hall-Stoodley et al., 2004). This switch from a free-swimming motile to a sessile biofilm lifestyle starts with the attachment of bacterial cells to a surface (Hall-Stoodley et al., 2004) and is regulated by a complex regulatory network of different signaling pathways and is associated with overall changes in gene expression leading to an enhanced matrix production and to a loss of motility-related factors (Whiteley et al., 2001; Dötsch et al., 2012). Among others, nucleotide second messengers such as cyclic di-GMP (c-di-GMP), cell-density dependent quorum sensing, sigma factors and two-component regulatory systems play an important role in biofilm formation (Mikkelsen et al., 2011; Fazli et al., 2014). Living within such a biofilm provides bacteria protection against a variety of different stressors like toxic substances, antibiotics or the host immune system and is therefore considered as an adaptive resistance mechanism (Hall-Stoodley et al., 2004; Breidenstein et al., 2011).

During acute and chronic infections, bacteria are confronted with a variety of host defense mechanisms designed to kill and eliminate invading pathogens from the host organism. These mechanisms include the secretion of compounds with direct antimicrobial or immunomodulatory activities or the incorporation and subsequent clearance of bacteria by phagocytic cells (Williams et al., 2010; Gellatly and Hancock, 2013). With respect to P. aeruginosa lung infections, main actors in the fight against this pathogen are epithelial cells and immune cells belonging to the innate immune system, such as phagocytic neutrophils or activated alveolar macrophages (Gellatly and Hancock, 2013; Lovewell et al., 2014). One major killing agent of mammalian phagocytes and, at the same time a frequently used disinfectant, is the potent oxidant hypochlorite (HClO) (Hawkins and Davies, 1998). HClO is generated from hydrogen peroxide (H2O2) and chloride ions (Cl−) in a chemical reaction which is catalyzed by the enzyme myeloperoxidase (MPO) and reacts with a large number of biomolecules, including proteins, lipids and DNA and thus rapidly induces bacterial cell death (Albrich et al., 1981; Rosen et al., 1990; Klebanoff, 2005; Gray et al., 2013a).

While several studies investigated the bacterial stress responses to the less reactive oxidant H2O2 (Palma et al., 2004; Chang et al., 2005; Salunkhe et al., 2005; Choi et al., 2007; Small et al., 2007a; Heo et al., 2010; Lan et al., 2010; Goldova et al., 2011; Hare et al., 2011; Romsang et al., 2013; Deng et al., 2014) information on the immediate response of P. aeruginosa to HClO as a component of the human first line of defense, its intracellular sensing and its implication on the adaptation of P. aeruginosa to a hostile environment still remains elusive. Earlier studies have shown that HClO influences energy, iron and polyphosphate metabolism in P. aeruginosa (Small et al., 2007a,b; Groitl et al., 2017), however, the impact of HClO on P. aeruginosa biofilm initiation and development has not been investigated so far.

In the present study, we show that sublethal HClO concentrations strongly induce early steps of biofilm formation in P. aeruginosa PAO1 by increasing intracellular levels of the second messenger c-di-GMP. Further analyses identified the diguanylate cyclase (DGC) PA3177 as part of the HClO-induced stress response and we demonstrate its involvement in motility, biofilm formation and interaction of P. aeruginosa with THP-1 macrophages.

## MATERIALS AND METHODS

### Organisms, Plasmids, Primers, and Growth Conditions

A list of bacterial strains and plasmids used in this study is provided in **Table 1**. P. aeruginosa PAO1 was either grown in complex Luria Bertani (LB) Miller broth (Carl Roth, Karlsruhe, Germany) or in BM2 minimal medium [62 mM potassium phosphate buffer, pH 7.0, 7 mM (NH4)2SO2, 2 mM MgSO4, 10 µM FeSO4, 0.4% (w/v) Glucose] at 37◦C and 170 rpm. In BM2-swarm medium, 7 mM (NH4)2SO4 was substituted for 0.5% (w/v) casamino acids. Escherichia coli strains DH5α and BL21(DE3) were cultivated in LB medium at 37◦C. For overexpression experiments, the arabinose-inducible expression vector pJN105 and the IPTG-inducible vector pET23a were used. Antibiotics ampicillin (100 µg/ml) and gentamicin (10 µg/ml for E. coli; 30 µg/ml for P. aeruginosa) were added for plasmid selection and/or maintenance.

Hypochlorite was added in the form of aqueous sodium hypochlorite (NaClO) or calcium hypochlorite [Ca(ClO)2] solutions as mentioned within the text. For effects caused by both, NaClO and Ca(ClO)2 treatment, the general term HClO was used within the manuscript.

Free chlorine concentrations of HClO solutions (VWR, Darmstadt, Germany) were determined prior to each assay using DPD Free Chlorine Powder Pillows (VWR, Darmstadt, Germany) according to the manufacturer's instructions.

The sequences of DNA primers (Eurofins MWG Operon, Germany) used in these studies are shown in Supplementary Tables S1 and S2.

#### Construction of Recombinant P. aeruginosa and E. coli Strains

Cloning procedures were performed with E. coli strain DH5α, proof-reading Platinum R pfx DNA polymerase and restriction enzymes from Thermo Fisher Scientific (St. Leon-Rot, Germany) according to standard protocols provided by the manufacturers. Primer sequences for subsequent cloning experiments are shown in Supplementary Table S1.

For overexpression in P. aeruginosa, ORF PA3177 was amplified from PAO1 genomic DNA using a XbaI restriction site flanked forward primer and a SacI site flanked reverse primer and the fragment was cloned into the arabinose-inducible broad host range vector pJN105 (Newman and Fuqua, 1999), resulting in pJN3177.

For overexpression in E. coli BL21 (DE3), ORF PA3177 was amplified from PAO1 genomic DNA using a BamHI restriction site flanked forward primer and a XhoI site flanked reverse primer followed by in-frame insertion into pET-23a(+) (Novagen, Merck, Darmstadt, Germany). The resulting plasmid pET3177 and the vector control pET23a were then transferred

#### TABLE 1 | Plasmids and bacterial strains used in this study.

fmicb-08-02311 November 20, 2017 Time: 13:6 # 3

TcR, tetracycline resistance; GmR, gentamicin resistance; AmpR, ampicillin resistance.

into E. coli strain BL21 (DE3) by heat shock transformation (Hanahan, 1983). E. coli was chosen for the heterologous expression of PA3177 due to its fast growth to high cell densities and the availability of highly efficient and tightly regulated gene expression systems.

#### Susceptibility Tests in Microtiter Plates

Minimal inhibitory concentrations (MIC) of different antimicrobials for planktonic P. aeruginosa cells were assayed by a standard broth microdilution method in BM2 medium as described previously (Wiegand et al., 2008). Additionally, growth of P. aeruginosa PAO1 during 24 h in the presence of different NaClO concentrations was monitored using a microplate reader (TECAN, Männerdorf, Switzerland) under shaking conditions at 37◦C.

#### Attachment Assay in Microtiter Plates

Attachment assays in 96-well polystyrene microtiter plates (Nunc, Thermo Fisher Scientific, St. Leon-Rot, Germany) were performed as previously described (Overhage et al., 2008) with the following minor modifications. P. aeruginosa PAO1 overnight cultures were washed and resuspended in BM2 medium, diluted to an optical density (OD600) of 0.2 and transferred to microtiter plates. In case of antimicrobial treatment, respective agents were added at indicated sub-MIC concentrations. Attachment of P. aeruginosa overexpression strains PAO1-pJN105, PAO1-pJN3177 or PAO1-pJN2133, was evaluated in BM2 medium supplemented with 0.1% (w/v) L-arabinose (Sigma–Aldrich, Seelze, Germany) to induce recombinant gene expression. Microtiter plates were incubated for 2 h at 37◦C without shaking followed by the quantification of biofilm biomass by crystal violet staining as previously described (Merritt et al., 2005). Experiments were performed at least in triplicate with multiple wells per condition. Statistical significance was verified by the non-parametric Mann–Whitney test.

#### Attachment on Microscope Slides and Fluorescence Microscopy

Attachment to a surface or interface is the initial step in the formation of biofilms. Attachment of P. aeruginosa PAO1 on glass microscope slides in the presence or the absence of NaClO (2 µg/ml) was analyzed as described previously (Bernard et al., 2009). The starting OD600 was 0.2 and

the slides were incubated for 2 h at 37◦C without shaking. Following fixation with 3% (v/v) formaldehyde, the attached bacteria were stained with the DNA intercalating fluorescent dye SYTO9 (Life Technologies, Darmstadt, Germany) according to the manufacturer's instructions. Fluorescence microscopy was carried out using an Axioplan 2 imaging system (Carl Zeiss, Oberkochem, Germany) with appropriate filter sets at 100 x magnification. Experiments were performed in duplicate and repeated three times. For biomass quantification, the surface coverage of four different squares with a side length of 200 µm was calculated for each slide using ImageJ software. All data were statistically analyzed by the non-parametric Mann–Whitney test.

#### Nucleotide Extraction and c-di-GMP Quantification by LC-MS

Intracellular c-di-GMP levels in P. aeruginosa PAO1 and in E. coli BL21 were quantified using a liquid chromatography coupled tandem mass spectrometry (LC-MS) method described by Spangler et al. (2010). P. aeruginosa PAO1 overnight cultures were washed and resuspended in BM2 medium. The OD600 was adjusted to 1.0 in order to increase the cell mass required for the subsequent extraction procedure, and the cells were incubated in small petri dishes with sublethal concentrations of NaClO (8 µg/ml, due to increased starting cell numbers) or without NaClO for 1 h at 37◦C. In case of experiments with PA3177-overexpressing E. coli strain BL21-pET3177 and vector control BL21-pET23a, bacterial overnight cultures were diluted 1:100 in LB containing ampicillin (100 µg/ml) and grown until mid-log phase at 37◦C under shaking conditions. IPTG was added at a final concentration of 0.4 mM and bacteria were incubated for 5 h at 37◦C and 170 rpm. Harvesting and nucleotide extractions were performed as described previously (Spangler et al., 2010; Strehmel et al., 2015) using 200 ng cXMP (Biolog, Bremen, Germany) as an internal standard. Extractions were performed in triplicate and assays were repeated at least with two independent bacterial cultures. Total protein contents of the samples were determined by the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific, St. Leon-Rot, Germany) according to the manufacturer's instructions. LC-MS measurements were performed as described by Strehmel et al. (2015). Concentrations of c-di-GMP were normalized against total protein contents of respective cultures. Statistical significance was analyzed by the non-parametric Mann–Whitney test.

#### Gene Expression Analyses

For microarray analysis, overnight cultures of P. aeruginosa PAO1 were washed and resuspended in BM2 medium. After dilution to an OD600 of 0.2, 10 ml of the suspensions was transferred to a small petri dish (5 cm diameter; Sarstedt, Nuembrecht, Germany) and NaClO was added at a final concentration of 2 µg/ml. Untreated samples served as negative controls. Bacteria were incubated for 1 h at 37◦C, mimicking growth during static attachment assays in 96-well microtiter plates in order to increase the cell mass required for subsequent RNA extractions and microarray analysis. RNA extraction, cDNA synthesis and processing was performed as described previously (Strempel et al., 2013). Samples from three independent experiments per condition each with a minimum of two technical replicates were pooled to detect significantly up- or downregulated genes. Each sample was hybridized to two microarray Affymetrix Pae\_G1a GeneChips (n = 4). Only genes which were more than 3-fold dysregulated in NaClO-treated bacteria were included in further analyses (Student t-test p-value ≤ 0.05). Complete microarray data is deposited in the ArrayExpress database under accession number E-MTAB-2876. These results were verified using qRT-PCR as described in the following on three additional, independent experiments.

For quantitative realtime-PCR (qRT-PCR), P. aeruginosa PAO1 overnight cultures were washed and diluted with BM2 medium to an OD600 of 0.2 followed by incubation with NaClO, Ca(ClO)2, NH2Cl, paraquat and H2O2 at indicated concentrations for 1 h at 37◦C. For each condition, three independent experiments each with a minimum of two technical replicates were conducted. Untreated bacteria served as negative controls. RNA isolation, cDNA synthesis and subsequent qRT-PCR experiments were carried out as described previously (Strempel et al., 2013). Obtained Ct values were normalized to expression of housekeeping genes rpoD and fabD as described elsewhere (Schmidberger et al., 2013).

#### Motility Assays

Motility assays were performed as described elsewhere (Strehmel et al., 2015). Overnight cultures of strains PAO1-pJN3177 and PAO1-pJN105 were diluted 1:50 in LB medium containing 30 µg/ml gentamicin and 0.1% (w/v) arabinose and incubated for 5 h at 37◦C and 170 rpm prior to inoculation of agar plates. LB or BM2 agar plates were also supplemented with 0.1% (w/v) arabinose and 30 µg/ml gentamicin. Assays were performed in triplicate and mean values of five plates per experiment were calculated. Statistical significance of the obtained results was examined by the non-parametric Mann–Whitney test.

#### Phagocytosis Assays with Human THP-1 Macrophages

Gene expression in phagocytized bacteria was analyzed using qRT-PCR following interaction with THP-1 human macrophagelike cells and P. aeruginosa PAO1. THP-1 cells (German Collection of Microorganisms and Cell Cultures – DSMZ, Braunschweig, Germany) were routinely cultured in complete RPMI-1640medium containing 10% (v/v) heat-inactivated FBS and 2 mM L-glutamine (Sigma–Aldrich, Hamburg, Germany) at 37◦C and 5% CO2. To start the experiment, cells were seeded out in 6-well microtiter plates at a density of 5 × 106 cells per well. Differentiation into adherent macrophage-like cells was stimulated by the addition of 5 ng/ml PMA (Sigma–Aldrich, Hamburg, Germany) for 48 h as described previously (Park et al., 2007). P. aeruginosa PAO1 overnight cultures grown in BM2 were washed twice in complete RPMI medium and added to the THP-1 macrophages at a multiplicity of infection of 100. Interaction assays were carried out for 1h at 37◦C. THP-1 cells without bacteria and P. aeruginosa incubated without THP-1 macrophages served as controls. After phagocytosis, supernatants

which contained residual planktonic bacteria were removed from the wells. After a washing step with PBS, complete RPMI medium supplemented with the antibiotic gentamicin at a final concentration of 400 µg/ml was added to the THP-1 monolayer and remaining extracellular bacteria were killed during a 30 min incubation step at 37◦C as described previously (Neidig et al., 2013). Subsequently, the THP-1 cells were rinsed with complete RPMI medium and incubated with a 1:1 (v/v) mixture of RNAprotect Bacteria Reagent and complete RPMI medium for 5 min. During this incubation step, adherent THP-1 cells detached from the bottom of the 6-well plate and could be easily harvested by centrifugation (10 min, 5,000 × g, RT). All control samples were also treated with a 1:1 (v/v) mixture of RNAprotect Bacteria Reagent and complete RPMI medium prior to RNA isolation. Supernatants were discarded and cell pellets were stored at −80◦C until needed. Total RNA was extracted using the RNeasy Mini Kit in combination with QIAshredder columns (Qiagen, Hilden, Germany) according to the manufacturer's protocol for total RNA isolation from animal cells. The obtained RNA was directly used for cDNA synthesis and subsequent qRT-PCR.

In vitro phagocytosis of PAO1 cultures by THP-1 was performed as described previously (Yeung et al., 2014) using midlog bacterial cells and THP-1 at an MOI of 10. Three independent experiments with triplicates in each experiment were performed for each bacterial strain.

### RESULTS

#### HClO Induces Biofilm Formation in P. aeruginosa PAO1

In order to determine appropriate NaClO concentrations for subsequent assays, the susceptibility of P. aeruginosa PAO1 toward NaClO was analyzed by MIC determination in BM2 minimal medium resulting in MIC values of 4 µg/ml free chlorine. This value was confirmed by monitoring bacterial growth during 24 h in the presence of different concentrations of NaClO (Supplementary Figure S1). Thus, for subsequent experiments sublethal concentrations of 2 µg/ml free chlorine were chosen.

Since adhesion of bacterial cells to a surface is among the first steps in the development of biofilms (Hall-Stoodley et al., 2004), we performed static attachment assays in 96-well microtiter plates to show a significant 2.8-fold increase in initial adhesion of P. aeruginosa PAO1 during 2 h exposure to 2 µg/ml NaClO (**Figure 1A**). Additional tests indicated a dosedependent induction of attachment starting at concentrations as low as 0.5 µg/ml NaClO (**Figure 1B**). To verify these findings, P. aeruginosa attachment was also evaluated on glass microscope slides using fluorescence microscopy to show a similar 2.6-fold increase in the amount of attached bacteria in the presence of NaClO (**Figure 1C**).

In order to investigate whether this enhanced attachment was part of the general response to oxidative stress in P. aeruginosa, bacterial adhesion was monitored under different oxidative stress conditions. Evaluated substances included H2O2, calcium hypochlorite [Ca(ClO)2], paraquat and monochloramine (NH2Cl), a downstream reaction product of HClO. In each case, half of the determined MIC was used for the experiment [H2O2: 50 µg/ml, Ca(ClO)2: 2 µg/ml, Paraquat: 1 µg/ml]. NH2Cl and NaClO were applied at a molecular ratio of 1:1. Thus, final concentrations of NH2Cl were equivalent to concentrations resulting from the reaction of 2 µg/ml NaClO with amines. In addition to NaClO, the strongest induction of attachment was found in response to Ca(ClO)2 (+4.2-fold) and NH2Cl (+1.9 fold). For H2O2, there was still a slight increase in attachment detectable (+1.5-fold), whereas cells incubated with paraquat did not show any difference in biomass compared to untreated controls (**Figure 1D**) indicating that attachment is not induced by oxidative stress in general.

### The Second Messenger c-di-GMP Is Involved in the NaClO-Induced Biofilm Formation

Pseudomonas aeruginosa biofilm development is a complex adaptation which is regulated by a multitude of different signaling pathways including the second messenger c-di-GMP (Kalia et al., 2013; Fazli et al., 2014). In order to evaluate the involvement of c-di-GMP in the observed NaClO phenotype, intracellular c-di-GMP levels were quantified using LC-MS to show a significant increase in c-di-GMP levels by 8.7-fold in bacteria treated with NaClO (**Figure 2A**). With respect to absolute c-di-GMP levels, average concentrations of 201 pmol and 25 pmol c-di-GMP per mg protein in NaClO-treated and control cultures, respectively, were measured.

In order to test whether these increased c-di-GMP levels were an important factor for the NaClO-triggered initiation of biofilm formation, additional assays were performed with strain P. aeruginosa PAO1-pJN2133, which overexpresses the phosphodiesterase (PDE) PA2133 in the presence of 0.1% (w/v) arabinose leading to an enhanced and continuous c-di-GMP degradation and subsequently low intracellular c-di-GMP levels within the cell. Crystal violet staining after 2 h revealed a significant 1.4-fold increase in adhered biomass of PAO1-pJN105 in the presence of NaClO compared to the untreated control. In contrast, attachment was not affected in NaClO-treated cells of PAO1-pJN2133 in comparison to untreated bacteria (**Figure 2B**) suggesting an important role for c-di-GMP in NaClO-induced biofilm formation of P. aeruginosa.

## Expression of the Putative DGC PA3177 Is Induced by HClO

Intracellular c-di-GMP levels are regulated by the activity of DGCs which catalyze c-di-GMP synthesis from two GTP molecules and c-di-GMP-degrading PDEs. DGCs are characterized by a conserved GGDEF domain, whereas PDEs harbor either an EAL or a HD-GYP motif (Hengge, 2009; Kalia et al., 2013). To investigate which DGCs or PDEs are responsible for the increase in c-di-GMP upon NaClO treatment, global gene expression analyses using DNA microarrays were performed and gene expression levels in response to NaClO (2 µg/ml, 1 h) were compared to those of untreated PAO1 cells. Out of the 33

FIGURE 1 | Attachment of P. aeruginosa PAO1 in the presence of different oxidants. Attachment of P. aeruginosa PAO1 during 2 h incubation in the presence of sublethal NaClO concentrations (A–C) or half-MIC concentrations of oxidants NaClO (2 µg/ml), Ca(ClO)2 (2 µg/ml), NH2Cl (equivalent to 2 µg/ml NaClO), H2O2 (50 µg/ml) and paraquat (1 µg/ml) (D). (A,B,D) Attachment was assayed in 96-well microtiter plates by crystal violet staining and subsequent measurement of A595. Obtained values for treated samples were normalized against A595 of untreated controls (=relative biomass). Experiments were performed at least in triplicate, each with multiple wells per condition (n ≥ 18). (C) P. aeruginosa PAO1 was incubated with sub-MIC concentrations of NaClO (2 µg/ml) in BM2 for 2 h in 50 ml reaction tubes containing glass microscope slides. Adhered bacteria were stained with the DNA-intercalating dye SYTO9 prior to visualization by fluorescence microscopy at 100× magnification (scale bar: 100 µm). Average surface coverages from 36 pictures per condition were calculated using ImageJ. Experiments were performed in triplicate. For all experiments, statistical significance was evaluated by the Mann-Whitney test (∗∗∗p ≤ 0.001, n.s., not significant). Boxes include median (thick horizontal line), 25th and 75th percentiles. Dots indicate extreme values considered as outliers.

FIGURE 2 | Implication of c-di-GMP in the response of P. aeruginosa PAO1 to NaClO. (A) P. aeruginosa PAO1 was incubated with NaClO (8 µg/ml, OD600 = 1.0, BM2) for 1h followed by nucleotide extraction and quantification of intracellular c-di-GMP by LC-MS. Levels of c-di-GMP were normalized to the total protein content of the respective sample and compared to c-di-GMP levels in untreated controls (n = 6). The chromatogram shows c-di-GMP peaks of one representative measurement. (B) Attachment of P. aeruginosa in response to NaClO during overexpression of the c-di-GMP-degrading PDE PA2133 was evaluated by crystal violet staining. PAO1-pJN2133 and the vector control strain PAO1-pJN105 were incubated in 96-well microtiter plates either in the presence or in the absence of NaClO (2 µg/ml) for 2 h at 37◦C followed by the quantification of biofilm biomass. BM2 was supplemented with 0.1% (w/v) arabinose to induce recombinant gene expression. Experiments were repeated four times, each with six wells per strain and condition (n = 24). Absorbance at 595nm (A595) was determined and obtained values for NaClO-treated samples were normalized against the A595 of respective untreated controls (=relative biomass). Statistical significance was evaluated by the Mann–Whitney test (∗∗∗p ≤ 0.001, ∗∗p ≤ 0.01, n.s., not significant). Boxes include median (thick horizontal line), 25th and 75th percentiles. Dots indicate extreme values considered as outliers.

genes which possess a DGC consensus sequence in P. aeruginosa (Kulasakara et al., 2006; Winsor et al., 2011), only ORF PA3177 showed statistically significant changes in gene expression levels and an upregulation by 26.2-fold in response to NaClO. Genes coding for PDEs were not affected by the oxidant (ArrayExpress E-MTAB-2876). The increase in PA3177 gene expression in response to NaClO was confirmed by qRT-PCR (**Table 2**). In addition, qRT-PCR experiments with the oxidants H2O2, paraquat, Ca(ClO)2 and NH2Cl indicated that the induction of PA3177 was not part of the general response of P. aeruginosa to oxidative stress. A strong increase in PA3177 expression was only found upon treatment with Ca(ClO)2, NH2Cl and NaClO. In contrast, in response to paraquat, PA3177 levels were only slightly enhanced and H2O2 did not affect PA3177 gene expression at all (**Table 2**).

#### Characterization of the DGC PA3177

According to the Pseudomonas Genome Database (Winsor et al., 2011), the gene product of ORF PA3177 is a hypothetical cytoplasmic protein with a predicted molecular weight of 34.4 kDa containing a GGDEF domain (here: GGEEF). However, previous studies failed to confirm a c-di-GMP-generating enzyme activity of the PA3177 homologue in P. aeruginosa PA14 and did not show a consistent impact of PA3177 on biofilm formation (Kulasakara et al., 2006; Merritt et al., 2010).

To investigate the DGC activity of P. aeruginosa PAO1 PA3177, the enzyme was heterologously expressed for 5 h in E. coli BL21-pET3177 to obtain a high protein concentration, which was confirmed by SDS-PAGE and MALDI-ToF mass spectrometry analysis. Nucleotides were extracted from BL21-pET3177 and subsequent quantification of intracellular c-di-GMP levels by LC-MS revealed a 26.1-fold increase in c-di-GMP synthesis upon overexpression of PA3177 compared to BL21-pET23a (**Figure 3A**), which confirmed its DGC activity.

To further characterize this DGC, the PA3177 overexpressing strain PAO1-pJN3177 was constructed in which PA3177 expression was under the control of an arabinose-inducible

aP. aeruginosa PAO1 was incubated with different oxidants at indicated half-MIC concentrations in BM2 minimal medium for 1 h at 37◦C followed by RNA isolation and qRT-PCR. bFree chlorine concentrations are shown in µg/ml as determined by the respective test kit. Since free chlorine is defined as a mixture of HClO, ClO− and Cl2 and therefore possesses a variable molecular mass, corresponding millimolar concentrations were not calculated. cMean averages and standard deviations of three independent experiments, each analyzed at least in duplicate (n ≥ 6). Ct values were normalized against expression of housekeeping genes rpoD and fabD and relative PA3177 expression in treated cells compared to untreated controls was calculated.

promoter. After 2 h of PA3177 expression, cultures of PAO1 pJN3177 showed a 2.4-fold enhancement in biofilm biomass in 96-well microtiter plates in comparison to vector control PAO1-pJN105 or uninduced PAO1-pJNPA3177 cultures (**Figure 3B**).

Since motility is also strongly regulated by c-di-GMP (Hengge, 2009), the main motility types of P. aeruginosa – swimming in aqueous environments, twitching on solid surfaces and swarming on semisolid surfaces – were evaluated during PA3177 overexpression. To this aim, overnight cultures of P. aeruginosa PAO1-pJN3177 and control strain PAO1-pJN105 were diluted 1:50 in LB broth supplemented with 0.1% (w/v) arabinose and grown for 5 h at 37◦C. Of note, at this time point PAO1-pJN3177 formed already clearly visible cell aggregates in the flask indicating DGC activity (**Figure 3C**). In agreement with other studies which identified several DGCs as negative regulators of P. aeruginosa motility (Aldridge et al., 2003; Merritt et al., 2007), a 61% decrease in swimming ability was observed upon induction of PA3177 expression. Similar results were obtained for twitching motility after 72 h at 37◦C (18% decrease) and swarming motility after 21 h at 37◦C (99% decrease) in response to PA3177 overexpression (**Figure 3D**).

### Role of Pel and Psl exopolysaccharides

Several DGCs have been shown to induce attachment and biofilm formation by influencing flagella movement or stimulating extracellular matrix production (Klebensberger et al., 2009; Boehm et al., 2010; Malone et al., 2010; Petrova et al., 2014). To investigate in which way PA3177 modulates biofilm formation, plasmid pJN3177was transferred to a set of different Pseudomonas aeruginosa PAO1 mutants and attachment of respective strains was quantified after PA3177 induction. In addition to a flgK mutant with a defect in flagellum synthesis, mutants with defects in the Pel or Psl exopolysaccharide biosynthesis clusters were tested, since Pel and Psl have been identified to be important components for attachment and early biofilm formation in P. aeruginosa PAO1 (Evans and Linker, 1973; Friedman and Kolter, 2004; Jackson et al., 2004; Overhage et al., 2005). As shown in **Figure 4A**, a disrupted pslA gene or a simultaneous knock-out of Pel and Psl in the double mutant PAO1-1pelF1pslA-pJN3177 completely abolished the biofilminducing effect of PA3177. Furthermore, the single mutant PAO1-pelF-pJN3177 showed only a marginal 1.1-fold increase in attachment when PA3177 was overexpressed. In contrast, in the absence of flgK, overexpression of PA3177 in strain PAO1-flgK-pJN3177 led to a 2.1-fold increase in attachment which was comparable to PAO1-pJN3177 cells (**Figure 4A**). In addition, we analyzed gene expression of pelA and pslA in PAO1-pJN3177and PAO1-pJN105 using qRT-PCR. Since the microarray data did not reveal any upregulation in gene expression after 1 h of incubation and to ensure appropriate expression levels of PA3177 in PAO1-pJN3177, we determined pelA and pslA gene expression after 4 h of PA3177 expression. In comparison to the vector control strain PAO1-pJN105, we obtained an enhanced expression of pelA and pslA by 2.6 ± 0.8 and 7.9 ± 1.0-fold, respectively, after 4 h of PA3177 overexpression.

Next, we investigated whether Pel and Psl were implicated in the enhanced biofilm initiation in response to NaClO, i.e., under conditions in which the expression of PA3177 was naturally induced in PAO1 wildtype cells. To this aim, attachment of the deletion mutants PAO1-1pelF, PAO1-1pslA and of the double mutant PAO1-1pelF1pslA was analyzed in the presence of 2 µg/ml NaClO. Similar to PA3177 overexpression, NaClO treatment led to a significantly lower induction of attachment in the respective mutant strains in comparison to PAO1 wildtype (**Figure 4B**). Thus, the results demonstrate that both Pel and Psl polysaccharides are involved in the NaClO- and PA3177 dependent stimulation of biofilm formation in P. aeruginosa PAO1.

### Identification of Alternative NaClO-Responsive DGCs

A P. aeruginosa PA3177 knock-out mutant (PAO1-PA3177) of the Pseudomonas aeruginosa PAO1 mini-Tn5 lux transposon mutant library (Lewenza et al., 2005) was used in the following experiments. The correct insertion of the transposon cassette was confirmed by colony PCR. Susceptibility tests revealed equal MIC values of 4 µg/ml NaClO for PAO1-PA3177 and PAO1 wildtype. Phenotypical characterization of the PAO1-PA3177 mutant showed no changes in swimming, swarming or twitching motility as well as the ability to form biofilms compared to PAO1 wildtype (data not shown). Furthermore, subsequent attachment assays in the presence of NaClO demonstrated that a knock-out of PA3177 does not completely impede the biofilminducing effect of NaClO, since attachment of the mutant was still significantly enhanced compared to the untreated control (**Figure 5A**). However, this increase in attachment by 2.2-fold was significantly lower than the 2.6-fold increase of PAO1 wildtype.

The P. aeruginosa PAO1 genome encodes for at least 33 proteins with the GGDEF consensus sequence of DGCs (Kulasakara et al., 2006).  Most of these

FIGURE 4 | Attachment assays with PAO1 mutants. (A) Attachment of P. aeruginosa PAO1 wildtype (WT) or PAO1 mutant strains during overexpression of PA3177 was evaluated by crystal violet staining. Bacteria were incubated in 96-well microtiter plates for 2 h at 37◦C prior to biomass quantification. For recombinant gene expression, L was supplemented with 0.1% (w/v) arabinose (+). Cultures without arabinose (−) served as negative controls. (B) Attachment of P. aeruginosa PAO1 WT or PAO1 deletion mutants during NaClO treatment (2 µg/ml in BM2, 2 h) was evaluated by crystal violet staining. All experiments were carried out in triplicate, each with six wells per strain and condition (n = 18). Statistical significance was evaluated by the Mann–Whitney test (∗∗∗p ≤ 0.001, ∗∗p ≤ 0.01, n.s., not significant). Boxes include median (thick horizontal line), 25th and 75th percentiles. Dots indicate extreme values considered as outliers.

biomass). Statistical significance was evaluated by the Mann–Whitney test (∗∗∗p ≤ 0.001, n ≥ 12). Boxes include median (thick horizontal line), 25th and 75th percentiles. Dots indicate extreme values considered as outliers. (B) P. aeruginosa mutant strain PAO1-PA3177 was treated with 2 µg/ml NaClO and relative gene expression levels of genes encoding DGCs in comparison to untreated control cultures were analyzed by qRT-PCR. The figure shows mean averages and standard deviations calculated from three experiments, each analyzed in duplicate (n = 6). Ct values were normalized against the expression of housekeeping genes rpoD and fabD. The red line corresponds to a relative gene expression level of 1, which means no change in gene expression. Blue bars indicate relative gene expression values ≥ 3.

hybrid proteins possess either a DGC or a PDE activity, whereas a dual DGC-PDE function has been confirmed for only few enzymes (e.g., PA4601) so far (Phippen et al., 2014). In contrast, the hybrid enzymes PA2567 and PA5017 have been identified as functional PDEs (Rao et al., 2009; Roy et al., 2012). So far, an actual DGC activity has been proposed for at least eleven putative DGCs of P. aeruginosa (Kulasakara et al., 2006; Merritt et al., 2007; Klebensberger et al., 2009; Petrova et al., 2014). Therefore, we hypothesized that in case of a PA3177 knock-out, alternative DGCs may adopt functions of PA3177 with respect to NaClO induced biofilm formation.

To test this idea, PAO1-PA3177 was incubated in the presence of sub-MIC concentrations of NaClO and expression of all putative DGCs was analyzed by qRT-PCR in order to detect changes in gene expression compared to untreated controls. Indeed, NaClO treatment induced the expression of

additional six alternative DGCs in the PAO1-PA3177 knockout mutant by more than three-fold (**Figure 5B**). The strongest upregulation was found for PA2072 (9.8 ± 0.5-fold) and PA1107 (8.7 ± 0.4-fold), followed by PA0847 (6.4 ± 0.2-fold), PA3258 (5.8 ± 0.3-fold), PA0575 (5.7 ± 0.4-fold) and PA0290 (3.6 ± 0.1 fold). Of note, none of the mentioned DGCs were identified differentially regulated in above described microarray analysis of NaClO-treated PAO1 (ArrayExpressE-MTAB-2876). Additional qRT-PCR experiments on different cultures confirmed these results for PA0290, PA0575, PA0847, PA3258. Interestingly, an upregulation of PA1107 (5.5 ± 0.2-fold) and PA2072 (5.4 ± 0.2 fold) was observed in addition to PA3177 (13.7 ± 0.9-fold) in NaClO-treated PAO1 wildtype cells, however, the induction of these two DGCs in PAO1 WT was considerably lower than in the mutant strain PAO1-PA3177. Overall, these results suggest that in addition to PA3177 additional DGCs exhibit an increase in gene expression in response to NaClO in the PAO1 wildtype and the PAO1-PA3177 mutant strain, indicating that a knock-out of PA3177 can be counterbalanced by one or more additional DGC activities within the c-di-GMP network of PAO1.

#### PA3177 Expression Is Induced in Contact with Phagocytes

HClO is generated in human immune cells during phagocytosis in a chemical reaction of H2O2 and Cl− which is catalyzed by the MPO enzyme (Klebanoff, 2005; Groitl et al., 2017). Since HClO was able to activate PA3177 gene expression in vitro, in the next step, PA3177 expression was examined in P. aeruginosa PAO1 ingested by phagocytic cells in order to identify a role of PA3177 during host–pathogen interactions. Phagocytosis experiments were carried out with human THP-1 macrophage-like cells and P. aeruginosa PAO1 at a multiplicity of infection of 100. MPO expression in THP-1 macrophages had been previously confirmed by Hachiya et al. (2000). Phagocytic uptake of bacteria by THP-1 macrophages was confirmed by fluorescence microscopy using a P. aeruginosa strain which constitutively expressed the green fluorescent protein GFP. As a result, expression of PA3177 was upregulated by 9.5 ± 0.4 fold in phagocytized bacteria compared to PAO1 cells grown without any contact to THP-1 macrophages. However, when we investigated virulence of PAO1-PA3177 and PAO1 wildtype during phagocytosis using THP-1 cells and an MOI of 10, we did not observe any statistically significant changes in survival rates after 2 h of incubation (Supplementary Figure S2).

#### DISCUSSION

The second messenger c-di-GMP acts as a key regulator of motility and biofilm formation in many bacteria. Although much effort has been put into the elucidation of P. aeruginosa c-di-GMP signaling during the last decade, there is still a need for further investigation in order to obtain a complete view of cellular c-di-GMP actions and their implication in P. aeruginosa stress response and host-pathogen interactions (Hengge, 2009; Römling et al., 2013). For example, only a few environmental stimuli which influence the synthesis or degradation of c-di-GMP have been identified so far (Hoffman et al., 2005; Klebensberger et al., 2009; Malone et al., 2012; Li et al., 2013; Luo et al., 2015), and knowledge about detailed c-di-GMP effector pathways and connections to other stress-responsive networks is still incomplete (Hengge, 2009; Römling et al., 2013).

In this study, we demonstrate that the phagocytic killing agent and strong disinfectant HClO acts as an activator of c-di-GMP synthesis and subsequent attachment and biofilm formation in P. aeruginosa. The hyperattachment phenotype is prevented by overexpression of the c-di-GMP-degrading PDE PA2133 enabling a constant degradation of c-di-GMP in the respective strain P. aeruginosa PAO1-pJN2133 (Hickman et al., 2005) during NaClO incubation, which highlights the role of the second messenger in this adaptation process. Further results suggest an involvement of the DGC PA3177 whose expression was strongly stimulated by the HClO-releasing agents NaClO and Ca(ClO)2 and NH2Cl, which is an abundant secondary reaction product of HClO and nitrogen-containing organic compounds. In contrast, transcriptional levels were not altered or only marginally enhanced in response to the oxidants H2O2 and paraquat.

Several studies present evidence for the ability of bacteria to increase biofilm formation in response to sublethal concentrations of otherwise highly toxic agents such as antibiotics, detergents and biocides (Bagge et al., 2004; Hoffman et al., 2005; Linares et al., 2006; Klebensberger et al., 2009; Shemesh et al., 2010; Damron et al., 2011; Kaplan, 2011; Malone et al., 2012). However, a regulatory impact on c-di-GMP metabolism in P. aeruginosa has only been described for some agents including tobramycin and SDS and both toxic agents promote a sessile mode of growth of P. aeruginosa when applied at sublethal concentrations (Hoffman et al., 2005; Klebensberger et al., 2009). So far, the only studies in which sublethal doses of NaClO are linked to an enhanced bacterial biofilm formation deals with E. coli (Capita et al., 2014) and Staphylococcus aureus MRSA (Buzon-Duran et al., 2017). The authors propose that an increase in cell surface hydrophobicity caused by NaClO is responsible for the observed induction of biofilm formation in E. coli. However, a potential implication of c-di-GMP in the observed phenotype was not suggested in the respective study(Capita et al., 2014).

Our results indicate that the DGC PA3177 is specifically induced by HClO but not by oxidative stress in general. With respect to the tested agents, both HClO and NH2Cl as well as H2O2 are able to directly generate oxidative damage of cellular macromolecules and additionally promote the synthesis of further highly reactive oxygen species, e.g., hydroxyl radicals (·OH) and singlet oxygen (1O2) which in turn intensifies the oxidative cell injury (Fang, 2004; Klebanoff, 2005). Similar mechanisms have been reported for the herbicide paraquat whose oxidative potential is predominantly caused by a massive production of superoxide anion radicals (·O2) upon cell contact (Cocheme and Murphy, 2008; Hare et al., 2011). ·O2 stimulates the generation of reactive nitrogen species or is converted into the less reactive H2O2 by superoxide dismutase (Fang, 2004; Flannagan et al., 2009). A crucial difference between the tested oxidants is the rate at which they promote the reversible pathway.

fmicb-08-02311 November 20, 2017 Time: 13:6 # 11

oxidation of methionine residues in proteins to methionine sulfoxides (Met-SO) (Drazic and Winter, 2014). In general, all tested oxidants are able to induce Met-SO formation; however, the reaction occurs considerably faster in case of HClO compared to the less reactive H2O2 (Pattison and Davies, 2001; Peskin and Winterbourn, 2001; Drazic and Winter, 2014). Met-SO generation by chloramines appears at medium rates depending on the chloramine type (Peskin and Winterbourn, 2001). Besides methionine oxidation, the oxidative modification of cysteine residues in proteins represents a second predominant reaction of HClO with cellular components (Pattison and Davies, 2001; Gray et al., 2013a). Pattison and Davies (2001) demonstrated that at molecular ratios ≤ 4:1 of HClO and proteins, 98% of applied HClO is consumed by methionine and cysteine oxidation. In addition to the lower reactivity of H2O2, P. aeruginosa possesses highly efficient H2O2 removal strategies such as glutathione peroxidases and catalases (Elkins et al., 1999; Lan et al., 2010) – a fact which might also contribute to the lack of Met-SO generation or cysteine oxidation by H2O2 in contrast to HClO in vivo (Romsang et al., 2013). An implication of both types of protein modification in HClO signaling in bacteria has been shown for B. Subtilis (Palm et al., 2012) and E. coli (Gebendorfer et al., 2012; Drazic et al., 2013; Gray et al., 2013b), but not for P. aeruginosa so far. To finally answer the question whether Met-SO generation represents a key factor in the described PA3177-mediated hyperattachment phenotype of P. aeruginosa in response to HClO and to identify potential modified residues in regulatory proteins, further analyses such as global mass spectrometry approaches as described by Rosen et al. (2009) would be required.

Using a PA3177 overexpression strain of P. aeruginosa PAO1, we were able to demonstrate a strong stimulating impact of PA3177 on self-aggregation, attachment and biofilm initiation whereas motility was strongly inhibited by the DGC. Similar cellular functions have been reported for the P. aeruginosa DGCs such as SiaD (PA0169), RoeA (PA1107) and YfiN (PA1120) (Klebensberger et al., 2009; Malone et al., 2010; Merritt et al., 2010). As a common feature, the expression of exopolysaccharide synthesis genes was affected by all mentioned DGCs (Klebensberger et al., 2009; Malone et al., 2010; Merritt et al., 2010). In general, changes in matrix production often play a role in the enhanced bacterial biofilm formation in response to most previously mentioned antimicrobials (Bagge et al., 2004; Hoffman et al., 2005; Linares et al., 2006; Klebensberger et al., 2009; Shemesh et al., 2010; Damron et al., 2011; Kaplan, 2011; Malone et al., 2012). In B. subtilis, for example, stimulation of biofilm formation by ClO2 is associated with an enhanced matrix production mediated by the histidine kinase KinC (Shemesh et al., 2010). A similar induction of pellicle formation was also observed in P. aeruginosa PA14, but underlying mechanisms have not been further investigated in the respective study (Shemesh et al., 2010).

In P. aeruginosa biofilms, the main structural components are the polysaccharides alginate, Pel and Psl (Evans and Linker, 1973; Friedman and Kolter, 2004; Jackson et al., 2004). In contrast to alginate, which is primarily produced by mucoid strains at a later stage of biofilm development, Pel and Psl are already involved in early steps of biofilm formation like cell adhesion of P. aeruginosa non-mucoid variants, such as PAO1 (Wozniak et al., 2003; Overhage et al., 2005; Colvin et al., 2012; Cooley et al., 2013). In addition, flagella are important for initial cell surface attachment and biofilm formation (O'Toole and Kolter, 1998). Both flagella and exopolysaccharides are controlled by a complex regulatory network including c-di-GMP in P. aeruginosa (Ha and O'Toole, 2015). Using a subset of recombinant strains with mutations in genes related to flagella function (flgK) and exopolysaccharide synthesis (pelF, pslA), we were able to demonstrate a role of the Pel and Psl exopolysaccharides in the PA3177-mediated biofilm phenotype of P. aeruginosa PAO1, since in NaClO-treated P. aeruginosa deletion mutants the increase of attachment in the presence of NaClO was strongly inhibited when pel and/or psl genes were disrupted. Moreover, no increase in biofilm formation in response to a PA3177 overexpression was observed in the respective pel and psl deletion mutants.

Since PA3177 expression was also induced by contact with human macrophages, and given the fact that infected CF lungs bear an unusual high phagocytic burden and thus severely increased levels of HClO-generating MPO enzyme (Van Der Vliet et al., 2000; Downey et al., 2009), we can imagine an implication of this DGC in the development of persistent P. aeruginosa strains during chronic infections. Moreover, the applied HClO concentrations of 2 µg/ml are considered as physiologically

relevant, since it has been demonstrated previously that 5 ×106 stimulated neutrophils are able to generate 88 ± 24 nmol HClO (which corresponds to 4–5 µg HClO) within 2 h (Kalyanaraman and Sohnle, 1985) and the numbers of invading neutrophils have been estimated by approximately 1 ×104 /ml during airway inflammations (Thomson et al., 2010). However, we were not able to identify a role of PA3177 in virulence and survival using THP-1 cells, since the knock-out PAO1-PA3177 mutant strain showed no differences compared to wildtype cells.

Previously, it has been shown that a PA3177 mutation in P. aeruginosa strain PA14 results in altered biofilm formation, however, the authors state that these results were not consistent (Merritt et al., 2010). Furthermore, Kulasakara et al. (2006) were able to show that a PA3177 knock-out in strain PA14 did not alter virulence or biofilm phenotypes.

The observation that in addition to PA3177 gene expression of other DGCs is induced in the presence of NaClO, in particular in the PA3177 knock-out mutant, emphasizes the importance of biofilm formation as an adaptation process for P. aeruginosa in response to HClO stress. Further studies have to be done to clarify if one or more DGC activities are involved in counterbalancing a PA3177 knock-out. These additional effects, the potential involvement of PA3177 in pathogenesis of P. aeruginosa as well as the regulatory cascade involved in the regulation of PA3177 gene expression will be investigated in more detail in the future.

Concluding, within this work we were able to identify the host defense compound and strong disinfectant HClO as a new environmental stimulus for c-di-GMP synthesis and biofilm formation in P. aeruginosa (**Figure 6**). The finding that expression of the HClO-responsive DGC PA3177 is also induced upon contact of P. aeruginosa cells with human macrophages highlights its potential role during host–pathogen interactions.

#### REFERENCES

### AUTHOR CONTRIBUTIONS

JO and GB-W conceived the experiments. NS and AN performed susceptibility tests, biofilm, motility and phagocytosis experiments and plasmid constructions. MN performed c-di-GMP quantification by LC-MS. NS, GB-W, and JO wrote the manuscript. All authors contributed to the final version of the manuscript, and all authors approved the final manuscript.

#### FUNDING

We gratefully acknowledge financial support by the BioInterfaces in Technology and Medicine (BIFTM) program of the Karlsruhe Institute of Technology (KIT) in the Helmholtz Association and start-up funds by Carleton University.

#### ACKNOWLEDGMENTS

We thank Bernd Rehm and Bob Hancock for kindly providing bacterial strains, Caroline Harwood for kindly providing plasmids used in this study, Robert Geffers for the microarray analysis, Boris Kühl for mass spectrometry measurements, Marie Eckstein and Linda Guedemann for technical assistance. We acknowledge support by Deutsche Forschungsgemeinschaft and Open Access Publishing Fund of Karlsruhe Institute of Technology.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb. 2017.02311/full#supplementary-material

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an MHYT domain-coupled phosphodiesterase. J. Bacteriol. 195, 3531–3542. doi: 10.1128/JB.01156-12

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polysaccharide matrix of PA14 and PAO1 Pseudomonas aeruginosa biofilms. Proc. Natl. Acad. Sci. U.S.A. 100, 7907–7912. doi: 10.1073/pnas.1231792100

Yeung, A. T. Y., Janot, L., Pena, O. M., Neidig, A., Kukavica-Ibrulj, I., Hilchie, A., et al. (2014). Requirement of the Pseudomonas aeruginosa CbrA sensor kinase for full virulence in a murine acute lung infection model. Infect. Immun. 82, 1256–1267. doi: 10.1128/IAI.01527-13

**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.

The reviewer JR and handling Editor declared their shared affiliation.

Copyright © 2017 Strempel, Nusser, Neidig, Brenner-Weiss and Overhage. 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.

# Relative Quantitative Proteomic Analysis of *Brucella abortus* Reveals Metabolic Adaptation to Multiple Environmental Stresses

Xiaodong Zai, Qiaoling Yang, Ying Yin, Ruihua Li, Mengying Qian, Taoran Zhao, Yaohui Li, Jun Zhang, Ling Fu, Junjie Xu\* and Wei Chen\*

Laboratory of Vaccine and Antibody Engineering, Beijing Institute of Biotechnology, Beijing, China

#### *Edited by:*

Daniela De Biase, Sapienza Università di Roma, Italy

#### *Reviewed by:*

Jayaseelan Murugaiyan, Freie Universität Berlin, Germany Eustache Paramithiotis, Caprion, Canada Carlos Rossetti, Instituto Nacional de Tecnología Agropecuaria (INTA), Argentina

*\*Correspondence:*

Junjie Xu<EMAIL_ADDRESS>Wei Chen<EMAIL_ADDRESS>
#### *Specialty section:*

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

> *Received:* 29 August 2017 *Accepted:* 15 November 2017 *Published:* 29 November 2017

#### *Citation:*

Zai X, Yang Q, Yin Y, Li R, Qian M, Zhao T, Li Y, Zhang J, Fu L, Xu J and Chen W (2017) Relative Quantitative Proteomic Analysis of Brucella abortus Reveals Metabolic Adaptation to Multiple Environmental Stresses. Front. Microbiol. 8:2347. doi: 10.3389/fmicb.2017.02347 Brucella spp. are facultative intracellular pathogens that cause chronic brucellosis in humans and animals. The virulence of Brucella primarily depends on its successful survival and replication in host cells. During invasion of the host tissue, Brucella is simultaneously subjected to a variety of harsh conditions, including nutrient limitation, low pH, antimicrobial defenses, and extreme levels of reactive oxygen species (ROS) via the host immune response. This suggests that Brucella may be able to regulate its metabolic adaptation in response to the distinct stresses encountered during its intracellular infection of the host. An investigation into the differential proteome expression patterns of Brucella grown under the relevant stress conditions may contribute toward a better understanding of its pathogenesis and adaptive response. Here, we utilized a mass spectrometry-based label-free relative quantitative proteomics approach to investigate and compare global proteomic changes in B. abortus in response to eight different stress treatments. The 3 h short-term in vitro single-stress and multi-stress conditions mimicked the in vivo conditions of B. abortus under intracellular infection, with survival rates ranging from 3.17 to 73.17%. The proteomic analysis identified and quantified a total of 2,272 proteins and 74% of the theoretical proteome, thereby providing wide coverage of the B. abortus proteome. By including eight distinct growth conditions and comparing these with a control condition, we identified a total of 1,221 differentially expressed proteins (DEPs) that were significantly changed under the stress treatments. Pathway analysis revealed that most of the proteins were involved in oxidative phosphorylation, ABC transporters, two-component systems, biosynthesis of secondary metabolites, the citrate cycle, thiamine metabolism, and nitrogen metabolism; constituting major response mechanisms toward the reconstruction of cellular homeostasis and metabolic balance under stress. In conclusion, our results provide a better understanding of the global metabolic adaptations of B. abortus associated with distinct environmental stresses. The identification of proteins necessary for stress resistance is crucial toward elucidating the infectious process in order to control brucellosis, and may facilitate the discovery of novel therapeutic targets and effective vaccines.

Keywords: *Brucella abortus*, proteomic, label-free, environmental stress, differentially expressed protein, metabolic pathway

#### INTRODUCTION

Brucella (Brucellaceae) are gram-negative, facultative intracellular pathogens that cause brucellosis, which results in abortion and infertility in the natural host (Akpinar, 2016). Brucellosis is a major global zoonosis that infects approximately 500,000 people annually (Hasanjani Roushan and Ebrahimpour, 2015). Brucella abortus, B. melitensis, and B. suis are most pathogenic toward humans and have been listed as high priority biological agents (Doganay and Doganay, 2013). However, the pathogenic mechanisms of Brucella are currently not well understood. During invasion of the host tissue, the bacteria multiply inside phagocytic cells and eventually establish persistent infection and replication within the host (Ahmed et al., 2016). It appears that Brucella species do not depend on single discrete virulence factors such as cytolysins, capsules, exotoxins, secreted proteases, fimbriae, or phage-encoded toxins for their pathogenicity (He, 2012). Rather, their pathogenicity mainly depends on their capacity to survive and proliferate within host cells (Byndloss and Tsolis, 2016). During the invasion of host tissue, these bacteria are subjected to several severe stresses, including nutrient limitation, low pH, antimicrobial defenses, and extreme levels of reactive oxygen species (ROS) from the immune response of the host (Roop et al., 2009; Barbier et al., 2011; Olsen and Palmer, 2014). The pathogen may therefore be able to withstand the variety of stresses encountered during its intracellular infection (Lamontagne et al., 2009).

In recent years, proteomics has become an indispensable tool used to investigate the metabolic adaptation mechanisms of various organisms to multiple environmental stresses (Cash, 2011; Van Oudenhove and Devreese, 2013; Greco and Cristea, 2017). The assessment of differential proteome expression patterns of a pathogen under stress may contribute to a better understanding of pathogen adaptation and pathogenesis. Distinct environmental conditions can be simulated by in vitro models, in which bacterial cultures are exposed to different in vivo-mimicking conditions experienced in the cellular environment of the host. The metabolic adaptation of Brucella to specific stresses such as nutrient starvation, acidity, high temperature, or peroxide has been explored in previous studies (Teixeira-Gomes et al., 2000; Al-Dahouk et al., 2008, 2009, 2013). However, earlier proteomic approaches employed twodimensional electrophoresis (2-D), and are therefore limited in their detection of alkaline and low-abundance proteins. Lamontagne et al. (2009) used an LC-MS approach to investigate and compare global proteomic changes in B. abortus at different times after infection in vivo, which provided insight into mechanisms utilized by Brucella to survive and proliferate within host cells. During the invasion of host tissue, Brucella is simultaneously subjected to a variety of harsh environments (Roop et al., 2009); however, previous proteomic studies failed to test a range of potential environmental stresses that the bacteria could be exposed to within the host.

In this study, we utilized a label-free relative quantitative proteomics approach to investigate and compare global proteomic changes in B. abortus in response to a variety of typical environmental stresses. A total of 2,272 proteins were identified and quantified, with significant changes observed in 1,221 under the multiple stress conditions tested. The differentially expressed proteins (DEPs) identified that were significantly changed under the stress treatments may provide novel insights into the global metabolic adaptations of B. abortus to multiple stresses. The identification of proteins necessary for stress resistance is crucial to elucidate the infection process and may facilitate the discovery of novel therapeutic targets and effective vaccines.

#### MATERIALS AND METHODS

#### *Brucella* Strains and Experimental Design

The B. abortus 104-M strain was obtained from the Lanzhou Institute of Biological Products in China (Yu et al., 2015). The cells were subjected to a control treatment [grown on tryptic soy broth (TSB), condition #1] and eight different stress treatments as previously described, with some modifications (Teixeira-Gomes et al., 2000; Al-Dahouk et al., 2008, 2009, 2013; Lamontagne et al., 2010). These included: (i) seven singlestress conditions: #2 serum stress [addition of 10% serum (obtained from healthy volunteers after informed consent; stored at −20◦C)]; #3 nutrient starvation stress (grown in Sauton's glycerol medium); #4 physical/chemical stress [grown in an acidic, high-temperature, hyperhaline, and high osmotic pressure condition (pH 4.5, 45◦C, NaCl 1 mol/L final concentration, sorbitol 1 mol/L final concentration)]; #5 peroxide/nitric oxide stress (addition of 50 mM H2O2 and 5 mM DETA-NO, final concentrations); #6 oxygen deficiency stress (incubation sealed); #7 iron-limited stress [addition of 50µM final concentration of the Fe2+-chelator 2,2′ -dipyridyl (DIP; Sigma-Aldrich, Shanghai, China)]; #8 antibacterial stress (addition of polymyxin B to 100µg/mL final concentration); and (ii) a multi-stress condition, consisting of a combination of conditions #2 to #8 (#9, see **Table 1** for details).

The cells were first cultured in TSB with continuous shaking (200 rpm) at 37◦C for approximately 24 h until mid-log phase (OD600nm = 1.0). The cells were harvested by concentrating the solution, and were then resuspended in the eight different growth conditions listed above and incubated for 3 h in a shaking incubator. Cultures were then serially diluted and plated on tryptic soy agar to determine their viability post-challenge. The survival percentage of the 3 h post-stress challenge was calculated by dividing the number of colony-forming units obtained from each stress treatment to that obtained from the control treatment, multiplied by 100. The survival experiments were performed at least three times for each treatment. All experiments involving live B. abortus 104-M were conducted in BSL-2 labs in line with health and safety guidelines.

**Abbreviations:** 2-D, two-dimensional electrophoresis; CAMPs, cationic antimicrobial peptides; DEP, differentially expressed protein; LC-MS/MS, liquid chromatography coupled to tandem mass spectrometry; LTQ, Linear trap quadrupole; FDR, False discovery rate; COG, Clusters of orthologous groups; KEGG, Kyoto Encyclopedia of Genes and Genomes; STRING, Search Tool for the Retrieval of Interacting Genes/Proteins; LFQ, label-free quantitation; PCoA, principal coordinate analysis.

### Protein Sample Preparation and Proteolytic Digestion

The protein samples were prepared as described previously (Zai et al., 2017). Briefly, cells cultured in each condition were harvested by centrifugation (7,000 × g for 15 min), and then washed three times with phosphate-buffered saline (PBS). The bacterial cells were resuspended in lysis buffer and disrupted by ultrasonication (25% amplitude, 15 min at 0◦C). The resultant suspension was centrifuged (40,000 × g for 30 min) and the protein concentrations in the collected supernatants were measured using a BCA (bicinchoninic acid) protein assay kit (Thermo Fisher Scientific, Waltham, USA). The cell protein extracts were reduced in 1 mM dithiothreitol (25◦C for 1 h) and then alkylated in 5.5 mM iodoacetamide (25◦C for 1 h, in the dark). Sequencing-grade trypsin (Promega) was added to a final ratio of 1:50 (V:V) and the proteins were digested in solution overnight at 37◦C.

### Liquid Chromatography Coupled to Tandem Mass Spectrometry (LC-MS/MS)

All experiments were performed on an LTQ Q-Exactive HF mass spectrometer (Thermo Scientific, USA) coupled online with a nano-HPLC (Ultimate 3000, Thermo Scientific) (Scheltema et al., 2014). The peptides were loaded onto a trap column (C18, 3µm particles, 100µm × 2 cm) and separated on EASY-Spray columns (C18, 1.9µm particles, 15µm × 12 cm) with trapping at a flow rate of 600 nL/min (Kentache et al., 2017). The mobile phase A was 0.1% formic acid in water and the mobile phase B was 0.1% formic acid in acetonitrile. The peptides were eluted using a gradient (6–95% mobile phase B) during a 195-min LC run and then sprayed directly into the MS instrument.

The mass spectrometer was operated using the datadependent top-15 method with automatic switching between MS and MS/MS scans (Kalayou et al., 2016). Full MS scans were acquired at a resolution of 120,000, with an automatic gain control target value of 3 × 106 ions or maximum injection time of 80 ms within the scan range 300–1,400 m/z. Peptide fragmentation was performed by higher energy collision dissociation (HCD) with the normalized collision energy set to 27 (Tutturen et al., 2014). The 15 highest-intensity ions were then selected for the collision-induced fragmentation at a resolution R = 15,000, an automatic gain control target value of 5 × 104 ions, or maximum fragment accumulation time of 45 ms. After the fragmentation event, dynamic exclusion of precursor ion masses for 12 s was used to avoid the repeated fragmentation of peaks. We excluded precursor ions with single, unassigned, or ≥ seven charge states from the fragmentation selection.

### Protein Identification and Label-Free Quantification

Protein identification was performed by submitting raw data files to Proteome Discoverer software (Thermo Scientific, USA, v. 1.2). The MS/MS searches were performed using the SEQUEST (v. 28) algorithm against a database constructed from the UniProt entries for B. abortus 104-M (taxonomy: 1210454), which contained 3,072 protein sequences. The search parameters included specific digestion with trypsin with up to two missed cleavages allowed; carbamidomethylation (C) on cysteine was set as a fixed modification; and oxidation (M) on methylene and acetyl (protein-N term) on asparagine & glutamine were applied as variable modifications. The initial allowed mass deviation of the precursor ion was set to 15 ppm, and the allowed value for the fragment mass was set to 0.02 Da. Protein identifications that contained at least two identified peptides were accepted with a false discovery rate (FDR) less than 1.0% (Zai et al., 2017).

For protein quantification, a label-free experiment was performed as previously described (Pettersen et al., 2016; Schmidt et al., 2016). Briefly, raw data were imported into Proteome Discover 1.4 following the MS analysis. Protein abundance of was calculated on the basis of label-free quantitation intensity [LFQ]. For comparison, the protein abundance in the control group was set as a reference and the protein abundance in the other eight stress groups were aligned. Proteins identified in at least two out of nine groups were considered for label-free quantification. Those proteins exhibiting fold change >1.5 (P-value ≤0.05) between the treatment and the control were deemed up-regulated or down-regulated respectively. The MS proteomics data have been deposited in the ProteomeXchange Consortium via the jPOSTrepo (Japan ProteOme STandard Repository) with the data set identifier PXD007548 (Vizcaino et al., 2014; Okuda et al., 2017).

#### Bioinformatics Analyses

The calculation of protein molecular masses, pI, and peptide grand average of hydropathicity (GRAVY) values were carried out using the ProtParam tool from the ExPASy toolbox (Gasteiger et al., 2003). Protein transmembrane helices were predicted using TMHMM 2.0 (Krogh et al., 2001). The protein functions were assigned by the Clusters of Orthologous Groups (COG) database (Galperin et al., 2015). The pathways of proteins were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Kanehisa et al., 2017). Possible interactions between identified proteins were tested using the STRING tool (Search Tool for the Retrieval of Interacting Genes/Proteins) (Szklarczyk et al., 2017). Heatmaps of the proteins were generated using the versatile matrix visualization and analysis software Morpheus, available from the Broad Institute.

### Experimental Design and Statistical Rationale

The proteomes of bacteria grown under the nine groups were investigated. For each condition, two biological replicates and two technical replicates were sampled, resulting in a total of four samples per condition for LC-MS/MS. Protein identifications should contain at least two identified peptides with a FDR less than 1.0%. Significant label-free changes in proteins were determined using the statistical analysis-based variance (ANOVA) test, which was performed on the protein LFQ values. Additionally, principal coordinate analysis (PCoA) was used to visualize the correlations among the nine groups. The Pearson's r correlation coefficient between the nine groups was also visualized by means of a correlation matrix. The expression patterns of the proteins grown under the nine conditions were presented in a heatmap with hierarchical clustering performed using a Euclidean distance metric and the average linkage method (Pettersen et al., 2016).

## RESULTS

### Experimental Design

Brucella spp. are facultative intracellular bacteria. During the invasion of host tissue, Brucella are subjected to various harsh environmental conditions including nutrient limitation, low pH, antimicrobial defenses, and extreme levels of ROS (Roop et al., 2009; Barbier et al., 2011; Olsen and Palmer, 2014). Correspondingly, Brucella is well-equipped from both a physiological and metabolic perspective to adopt to environmental stresses (Roop et al., 2009). Analysis of the differential proteome expression patterns of Brucella under stress should improve our understanding regarding its adaptation and pathogenesis. Thus, we chose a multiple-environmentalstress strategy to reveal the global metabolic adaptations of B. abortus to intravacuolar environmental conditions. These conditions included: (i) a control condition (growth on TSB, condition #1); (ii) seven single-stress conditions: (conditions #2–8) and (iii) a multi-stress condition (#9, see **Table 1** for details). The multi-stress condition constituted a combination of each single-stress condition, and may more realistically simulate the conditions experienced by Brucella during infection of the host. We investigated the survival rate and differential protein expression of B. abortus in the single-stress and multi-stress conditions compared with the control condition (**Figure 1**). The survival rates of B. abortus under the different stress conditions ranged from 3.17 to 73.17%. Nutrient starvation, physical/chemical starvation, peroxide/NO starvation, and anaerobic starvation resulted in low survival rates (**Table 1**). The multi-stress condition resulted in the lowest survival rates, and may constitute a more accurate reflection of the in vivo conditions of B. abortus under intracellular infection.

### Coverage of the *B. abortus* Proteome

The goal of this study was to achieve substantial coverage of the B. abortus proteome under in vitro stress conditions. Accordingly, we applied a proteomics approach on whole cell lysates prepared from B. abortus grown in the nine groups described above. LC-MS/MS analysis of the resulting peptide mixtures generated 1.1 million spectra. The acquired raw MS data files were then analyzed and the spectral files matched to 27,076 unique peptides with an FDR of 1.0%. We mapped the unique peptides to the B. abortus 104-M UniProt database (3,072 protein sequences), and only proteins that were identified by at least two unique peptides were confirmed (Zai et al., 2017). A total of 2,289 proteins were identified by two repeats, which represents approximately 74.5% coverage of the predicted proteome (**Figure 2A**). Proteins identified in at least two out of nine groups (2,272) were considered for label-free quantification (**Figure 2B**). The distribution of the identified proteins with respect to pI, molecular weight, hydrophobicity, and transmembrane regions was consistent with the annotated proteins (Figure S1). Among the 2,289 identified proteins, 1,570 were annotated in the COG database. Almost all of the pivotal categories for Brucella were identified, suggesting good coverage and representation of the genomic content of B. abortus by the proteome. Table S1 lists all identified proteins with their accession numbers and calculated score.

### Quantification Analysis of Proteins under Environmental Stress

We used high-resolution MS to quantitatively describe the protein profiles of B. abortus under stress conditions, and compared them with the expressed proteome in the control. Protein quantification allowed the characterization of proteins that were differentially expressed across the nine groups. Here, we obtained LFQ intensities for 2,272 quantified proteins. Their quantitative levels covered a 5-log10 dynamic range. The density plot of the log2 ratio between the stress group and control group closely matched a normal distribution, which indicated that the experimental procedure was performed without systematic bias toward the different samples. PCoA analysis indicated good homogeneity of the biological replicates and was able to discriminate nine distinct protein populations (**Figure 3A**). The Pearson's correlation coefficient r varied between 0.95 and 0.99, indicating that there were differences in the protein levels between the different stress conditions (**Figure 3B**).

We next explored differences between the protein profiles of B. abortus under the various stress conditions. Hierarchical

FIGURE 1 | Experimental design of the quantitative proteomics of Brucella abortus under environmental stress. A label-free relative quantitative proteomics approach was utilized to investigate and compare the global proteomic changes of B. abortus in response to a variety of distinct stresses including a control condition, seven single-stress conditions, and a multi-stress condition. Protein samples were prepared and proteolytic-digested using trypsin enzymes. Peptides were analyzed on a Q-Exactive HF MS coupled online with a nano-HPLC. The identified proteins were quantified using a label-free approach and further functionally analyzed using the COG and KEGG databases.

clustering was performed based on the LFQ intensities of the 2,272 proteins quantified in this study, and indicated distinguishable protein expression profiles between the nine different groups (**Figure 3C**). For each growth condition, a range of 1,967–2,109 proteins per group were identified (**Table 2**). About 87.6% of the detected proteins were common to all groups. Several of the identified proteins demonstrated a significant difference in abundance in stress compared to the control condition. The study identified DEPs in each stress condition whose quantitative levels varied by more than 1.5 fold from the respective LFQ intensity means in the control, i.e., 213, 413, 311, 451, 314, 357, 401, and 306 proteins in the eight stress conditions, respectively (Figure S2). Table S2 lists all the DEPs along with their accession numbers and LFQ intensities for each condition.

### Metabolic Pathway Analysis of DEPs under Each Environmental Stress Condition

To understand the functional classification and metabolic pathways that were involved in the environmental stress response, the DEPs in each stress condition were functionally analyzed. All of the enriched KEGG pathways of B. abortus in response to each stress treatment are listed in **Table 3**. The results

FIGURE 2 | Coverage of the B. abortus proteome by high-resolution mass spectrometry. (A) Venn plot of protein identification overlaps among two independent biological experiments. The number of proteins identified in the B. abortus proteome were 2,289, with 2,235 and 2,239 in the respective experiments. (B) The number of proteins identified in at least two out of nine groups and considered for label-free quantification was 2,272. The coverage of proteins identified and proteins quantitated in this study was 74.5 and 74%, respectively.

suggested that the metabolic adaptations of B. abortus to each environmental stress condition varied.

Brucella can persist for several weeks in the blood of an intraperitoneally-infected host (Vitry et al., 2014). Considering the role that serum stimulation has in intraperitoneally-infected

hosts of Brucella, serum stress was chosen as single-stress condition #2. In this treatment, we discovered 125 and 88 up-regulated and down-regulated proteins, respectively, compared with the control. As shown in Figure S3A, the main enriched KEGG pathways for regulated proteins included biosynthesis of siderophore group non-ribosomal peptides, ABC transporters, synthesis and degradation of ketone bodies, thiamine metabolism, and two-component system. This suggests that Brucella may enhance its iron acquisition through the regulation of ABC transporters and biosynthesis of siderophores

conditions was compared to the control condition.

in order to adapt to the serum stress. During the invasion of host tissue, a major hurdle in the infection of a host cell by Brucella is the lack of nutrients within the phagosome (Essenberg et al., 2002; Hanna et al., 2013; Barbier et al., 2017). Considering the role that nutrient starvation has in the intracellular replication of Brucella, nutrient stress was set as single-stress condition #3. Of the DEPs detected under this condition, 139 and 274 proteins were respectively up-regulated or down-regulated compared with the control. The primary enriched KEGG pathways for regulated proteins included two-component system, glycerophospholipid metabolism, ABC transporters, nitrogen metabolism, and porphyrin and chlorophyll metabolism (Figure S3B). This implies that Brucella may decrease its energy usage and secondary metabolite biosynthesis through the regulation of glycerophospholipid metabolism, nitrogen metabolism, and porphyrin and chlorophyll metabolism in response to nutrient starvation stress.

One major mechanism of Brucella pathogenesis is the capacity to survive in the acidic, high-temperature, hyperhaline, and high osmotic pressure environment inside macrophages (Detilleux et al., 1991; Liu et al., 2015). Given that physical/chemical stimulation influences the intracellular replication of Brucella, physical/chemical stress was set as single-stress condition #4.  ABC transporters, thiamine metabolism, biosynthesis of siderophore group nonribosomal peptides, glycerophospholipid metabolism, and two-component system constituted the main enriched KEGG pathways (Figure S3C). Brucella may therefore decrease its energy usage and secondary metabolite biosynthesis through the regulation of

aProteins unique to the stress condition.

bProteins unique to the control.

cThe common proteins identified in both the control and stress conditions.

dThe up-regulated proteins under stress conditions.

eThe down-regulated proteins under stress conditions.

glycerophospholipid metabolism and thiamine metabolism in order to the physical/chemical stress.

The exogenous production of ROS such as O2− and H2O2 by the host immune system has also been shown to be important for the survival of Brucella (Jimenez De Bagues et al., 2007). Nitric oxide produced by the macrophages were also crucial for phagocytes to control the intracellular replication of Brucella (Roop et al., 2009; Ronneau et al., 2016). Peroxide/nitric oxide stress was therefore set as single-stress condition #5. Of the DEPs detected in this treatment, 235 and 216 proteins were up-regulated or down-regulated respectively compared with the control. The main enriched KEGG pathways for regulated proteins included nitrogen metabolism, ABC transporters, biosynthesis of siderophore group nonribosomal peptides, thiamine metabolism, and two-component system (Figure S3D). The result suggests that Brucella may decrease its amino acid usage and secondary metabolite biosynthesis through the regulation of nitrogen metabolism and thiamine metabolism, meanwhile enhancing its iron acquisition through regulation of the two-component system and biosynthesis of siderophores in response to peroxide/NO stress.

The presence of oxygen has positive effects on the levels of proteins that are functional in aerobic respiration and purine metabolism, while low access to oxygen results in the induction of enzymes of mixed-acid fermentation and gluconate metabolism (James et al., 1995). Considering the role that oxygen deficiency plays in the intracellular replication of Brucella, oxygen deficiency stress was set as single-stress condition #6. In this treatment we discovered that 165 and 149 proteins were up-regulated or down-regulated respectively compared with the control. The main enriched KEGG pathways for the regulated proteins were two-component system, flagellar assembly, glycerophospholipid metabolism, quorum sensing, and ABC transporters (Figure S3E). Thus, Brucella may decrease its energy usage and virulence through the regulation of glycerophospholipid metabolism, two-component system, flagellar assembly and quorum sensing to manage oxygen deficiency stress.

Iron is an essential element for Brucella and is pivotal in hostpathogen interactions (Eskra et al., 2012; Roop, 2012). In the host, free iron levels are extremely low, resulting in iron limitation being a crucial stress (Braun, 2001). Iron-limitation stress was thus set as single-stress condition #7. We found that 169 and 188 proteins were respectively up-regulated or down-regulated in the iron-limited stress condition compared with the control. As indicated in Figure S3F, the main enriched KEGG pathways included oxidative phosphorylation, two-component system, biosynthesis of siderophore group nonribosomal peptides, nitrogen metabolism, and citrate cycle (TCA cycle). This result suggests that Brucella may decrease its energy usage through the regulation of oxidative phosphorylation, nitrogen metabolism and the TCA cycle, while enhancing its iron acquisition through the regulation of siderophore biosynthesis to adapt to the stress resulting from limited iron.

Antimicrobial peptides can limit the colonization of bacterial during infection in the innate defense, and therefore it is likely that Brucella encounters antimicrobial peptides within host microenvironments during infection (Martinez De Tejada et al., 1995). These peptides may be involved in environmental signaling that triggers changes in bacterial gene expression. Considering the role that antimicrobial peptide stimulation has in the intracellular replication of Brucella, antibacterial stress was set as single-stress condition #8. Of the DEPs in this treatment, 146 and 255 proteins were up-regulated or downregulated respectively in comparison with the control. The main enriched KEGG pathways included two-component system, nitrogen metabolism, oxidative phosphorylation, biosynthesis of siderophore group nonribosomal peptides, and base excision repair (Figure S3G). This suggests that Brucella may decrease its energy usage through the regulation of oxidative phosphorylation and nitrogen metabolism, while enhancing its antimicrobial peptide resistance through regulation of the two-component system and base excision repair in response to antibacterial stress.

During the invasion of host tissue, Brucella experiences several stresses simultaneously, including nutrient limitation,

(Continued)

#### TABLE 3 | Continued

low pH, antimicrobial defenses, and extreme ROS levels from the host immune response. Thus, the combination of stress conditions 2 to 8 was set as the multi-stress condition #9 that may better simulate the environments that Brucella may occur during host infection. We discovered that 116 and 190 proteins were respectively up-regulated or downregulated in the multi-stress condition compared with the control. The primary enriched KEGG pathways included twocomponent system, nitrogen metabolism, thiamine metabolism, biosynthesis of siderophore group nonribosomal peptides, and ABC transporters (Figure S3H). Brucella may decrease its energy usage and secondary metabolite biosynthesis via the regulation of nitrogen metabolism and thiamine metabolism, while enhancing its iron acquisition and antimicrobial peptide resistance by regulating the two-component system and siderophore biosynthesis in order to cope with multiple stresses.

Compared with the single-stress condition, the enriched pathways of B. abortus in response to multi-stress conditions were more extensive and covered the primary enriched pathways of each single-stress condition. For example, the two-component system pathway enriched in the multi-stress condition was also enriched in all eight of the single-stress conditions, indicating its significance in the metabolic adaptation to multiple environmental stresses. The nitrogen metabolism pathway was enriched in the multi-stress condition and also in numerous single-stress conditions, including nutrient starvation stress, physical/chemical stress, peroxide/nitric oxide stress, ironlimited stress, and antibacterial stress. The DEPs included in this enriched pathway were similar in their regulatory patterns in both the single-stress and multi-stress treatments. The results suggested that the metabolic adaptations of B. abortus to multiple stresses constitute the synthesis of each environmental stress condition, and that the multiple stress treatment may better simulate the metabolic adaptations of Brucella during host infection.

#### Metabolic Pathway Analysis of DEPs under Various Stress Conditions

The functional analysis above indicated that B. abortus exhibited different metabolic adaptations to each environmental stress condition. To better understand the primary metabolic adaptations of B. abortus to various stress conditions, we summed all the DEPs in each stress condition, resulting in a total of 1,221 proteins that were differentially expressed in at least one stress condition compared with the control. The protein functions of all 1,221 DEPs in the eight stress conditions were assigned by the COG database. We identified 20 different COG phylogenetic protein groups (**Figure 4**), with the highest represented subsets in category E (amino acid transport and metabolism, 104 proteins), category K (transcription, 93 proteins), category C (energy production and conversion, 90 proteins), category P (inorganic ion transport and metabolism, 87 proteins), and category G (carbohydrate transport and metabolism, 63 proteins). Furthermore, 114 proteins were assigned only a putative function (category R), while 127 proteins remained without an allocated biological role (category S). The COG functional analysis suggested that energy usage-related categories (E, C, and G) and the iron acquisition-related category (P) were involved in the main metabolic adaptations of B. abortus to various stress conditions.

A putative protein-protein interaction network was then constructed from all high-confidence B. abortus protein interaction pairs that were matched with the 1,221 DEPs using the STRING tool (Szklarczyk et al., 2015). The KEGG pathway analysis showed a significant enrichment of DEPs (P-value ≤ 0.05). All 1,221 DEPs in the eight stress conditions were primarily enriched in oxidative phosphorylation, ABC transporters, twocomponent systems, biosynthesis of secondary metabolites, porphyrin and chlorophyll metabolism, glycerol phospholipid metabolism, the TCA cycle, thiamine metabolism, nitrogen metabolism, or were associated with carbon metabolism (**Figure 5**). The KEGG pathway analysis suggested that the

was accomplished using the clusters of COGs. Letters displayed on the pie chart represent individual COGs with the numbers of proteins listed in brackets afterwards.

energy usage-related pathways and regulatory mechanism pathways constituted the primary pathways involved in the metabolic adaptation of B. abortus to various stress conditions. Table S3 lists the DEPs that were related to the main metabolic changes of B. abortus in response to stress treatments.

### Main Metabolic Changes in Response to Environmental Stress

Oxidative phosphorylation is the process in which ATP is formed through using enzymes to oxidize nutrients (Dimroth et al., 2000). TCA cycle is a series of chemical reactions that produces ATP through the oxidation of acetyl-CoA. In this study, several proteins involved in oxidative phosphorylation and the TCA cycle, such as those associated with the NADH dehydrogenase (NDH) family, succinate dehydrogenase (SDH), and cytochrome c oxidase CcO, were abundantly downregulated in response to both the single-stress and multiple-stress treatments (**Figures 6A,C**). A major hurdle in the infection of a host cell by Brucella is the lack of nutrients within the phagosome (Barbier et al., 2017). These results suggest that immediately after phagocytosis, Brucella reduces energy metabolism via the TCA cycle as the available extracellular nutrients decrease.

Two-component systems are adapted to respond to a wide variety of stress, including nutrients, quorum signals, antibiotics, temperature, pH, and so forth (Mascher et al., 2006). In this study, several proteins involved in two component systemcontrolled metabolic pathways, such as chromosomal replication initiator protein dnaA and nitrate reductase Nar, were decreased in abundance. Two-component system sensor histidine kinase PhoR/GlnL, hybrid sensor histidine kinase/response regulator ChvG, and transcriptional regulator RegB were up-regulated in response to several single-stress and multiple environmental stresses (**Figure 6B**). During the invasion of host tissue, Brucella must survive under several severe stresses through generating a suitable adaptive response to various signals (Viadas et al., 2010). Here, we found that the two-component system proteins were regulated in response to stress, which is essential for the persistence of Brucella within stressed environments in the host organism.

Cationic antimicrobial peptides (CAMPs) are crucial for the host defense against invasive bacterial infection (Alegado and Tan, 2008). The resistance of pathogenic bacteria toward antimicrobial peptides may also account for their virulence. In this study, several proteins involved in CAMPs resistance, such as the serine peptidase DegP and Hemolysin D (NL70\_15120), were increased in abundance in our study. Transporter TolC and N-acetylmuramoyl-L-alanine amidase (NL70\_04450) were down-regulated in response to several single environmental stresses, especially antibacterial stress (**Figure 6E**). These results indicated that the adopted mechanism of Brucella to resist host antimicrobials is important for persistent infection.

Siderophores are an important group of structurally diverse natural products that chelate iron and are important in the acquisition of the essential trace element iron by most microorganisms (Miethke and Marahiel, 2007). In the host, free iron levels are extremely low as the metal is largely bound to proteins. To overcome iron limitation, some bacteria and fungi produce siderophores. In this study, several proteins involved in the biosynthesis of siderophore group nonribosomal peptides, such as enterobactin biosynthetic enzymes EntA/B/E/F, were found to be up-regulated particularly in response to serum stress and iron-limitation stress (**Figure 6F**). These results indicated that Brucella has evolved strategies to overcome iron limitation and to compete with the iron sequestration immune mechanisms of the host.

We also observed specific variations in the amounts of multiple proteins involved in nitrogen metabolism, thiamine metabolism, and purine metabolism. In this study, nitrate reductase (Nar), nitrite reductase (NirK), and thiamine pyrophosphokinase (ThiN/E/G), which play essential roles in amino acid metabolism, and several enzymes participating in glycine, serine, and threonine metabolism, were relatively significantly differentially expressed in the different conditions (**Figure 6D**). Serine peptidase HtrA and heat shock protein

Hsp20 were observed to increase considerably under both the single-stress and multiple-stress treatments. The Cu-Zu superoxide dismutase SodC was found to increase during oxidative stress and multiple-stress treatments, but remained unchanged under the physical/chemical stress conditions of heat shock or acidic pH. Other proteins such as exopolyphosphatase (NL70\_13665), ribonuclease H (RnhA), single-stranded DNA exonuclease (RecJ), and urea amidohydrolase (UreA/B/C) were also reduced in at least one of the stress conditions in our study.

## DISCUSSION

The virulence of Brucella strains mainly depends on their capacity to survive and proliferate within host cells (Kohler et al., 2002). During the invasion of host tissue, Brucella is able to withstand the environmental stresses encountered and establish and maintain persistent intracellular residence (Roop et al., 2009). However, the mechanisms used by Brucella in intracellular infection are not fully understood. The aim of this work was to elucidate the regulatory processes of Brucella that enable survival under extreme stress by mirroring the possible living conditions of the bacteria in the host environment.

Multiple approaches have been used to investigate the proteomes of bacterial pathogens (Schmidt and Volker, 2011; Semanjski and Macek, 2016). Since bacteria are much smaller than mammalian host cells, the detection of bacterial proteins is difficult due to interference from the large excess of host proteins present. As a result of these challenges, the majority of bacterial proteomic datasets are still obtained from in vitro experiments (Cash, 2011). The main advantage of in vitro systems is the ability to implement a simple experimental design in a controlled manner using defined media and conditions. Although the in vivo approach in cultured cell lines reflects the conditions in infected hosts more closely than in vitro cultures, and reveals pathogenesis-related determinants present throughout the course of infection, it only partially describes the actual infection state due to the artificial conditions of the cell culture. Thus, in vitro approaches significantly contribute toward our understanding of the physiology of pathogenic bacteria and assist in identifying novel virulence factors that may represent potential biomarkers or drug targets. However, previous in vitro studies did not test the range of possible environment stresses that Brucella may be exposed to within the host. During the invasion of host tissue, Brucella is simultaneously subjected to a variety of harsh environments. Distinct environmental conditions can be simulated in in vitro models in which bacterial cultures are exposed to different in vivo-mimicking conditions similar to the cellular environment of the host. We therefore chose a multiple-environmental-stress strategy in order to reveal the global metabolic adaptations of B. abortus to intravacuolar environmental conditions.

We used a label-free proteomics approach to quantitatively elucidate the protein profiles of B. abortus under conditions of stress, and compared them with the expressed proteome in the control sample. The in vitro single-stress and multistress conditions simulated the in vivo conditions of B. abortus

stress condition. The red and blue colors reflect high and low fold changes, respectively.

under intracellular infection, with survival rates ranging from 3.17 to 73.17%. The results suggested that all of the singlestress conditions constituted harsh environments for B. abortus. The multi-stress condition resulted in the lowest survival rates, and may constitute a more accurate reflection of the in vivo conditions of B. abortus under intracellular infection. During the invasion of host tissue, Brucella is subjected to a harsh environment that results in the vast majority of the cells being killed within the macrophages (Di-Russo Case and Samuel, 2016). The in vitro stress treatments utilized in this study correspond well with the in vivo conditions of Brucella under intracellular infection.

The proteomic analysis identified and quantified a total of 2,272 proteins and 74% of the theoretical proteome, which has provided wide coverage of the B. abortus proteome. By replicating eight typical stress environments in vitro, we were able to investigate the influence of various stresses on the detected proteomes. The results indicated that there were different metabolic adaptations to different environmental stresses. The COG functional analysis of the 1,221 DEPs showed that energy usage-related categories (E, C, and G) and the iron acquisition-related category (P) were involved in the main metabolic adaptations of B. abortus to various stress conditions. While the KEGG pathway analyses revealed that the majority of pathways were involved in oxidative phosphorylation, ABC transporters, two-component systems, biosynthesis of secondary metabolites, the citrate cycle, thiamine metabolism, and nitrogen metabolism; all representing major response mechanisms involved in the maintenance of cellular homeostasis and metabolic balance under stress. The multi-stress treatment was a combination of each single-stress, and may better reflect the metabolic response of Brucella under intracellular infection. Most of the regulated proteins in the multi-stress treatment were associated with oxidative phosphorylation, the citrate cycle, nitrogen metabolism, and biosynthesis of secondary metabolites, suggesting that Brucella may decrease the oxidation of nutrients, amino acid use and reduce secondary metabolite biosynthesis in order to adapt to the intracellular environment.

Teixeira-Gomes et al. (2000) studied the differences in protein synthesis patterns in B. melitensis 16M in response to heat, oxidative, and acidic pH stresses using a 2-D approach. The 19 resulting DEPs suggested that B. melitensis invoked an adaptive response to stress conditions. Al-Dahouk et al. characterized the proteome of B. suis at the late stage of in vitro infection, oxygen deficiency and long-term nutrient starvation using a 2- D approach, respectively (Al-Dahouk et al., 2008, 2009, 2013). The resulting 168, 37, and 30 DEPs indicated the regulatory mechanisms that reducing processes participating in energy, protein, and nucleic acid metabolism. Lamontagne et al. (2009) characterized the proteome of B. abortus strain 2308 and attenuated strain 19 that were infected into macrophages. The comparative analysis suggested that the B. abortus initially reduced the majority of biosynthesis and altered its respiration, but these adaptations were reversed later in the infection process.