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. 2020 May 15;15(5):e0233013. doi: 10.1371/journal.pone.0233013

Xylella fastidiosa subsp. pauca and olive produced lipids moderate the switch adhesive versus non-adhesive state and viceversa

Valeria Scala 1,*, Nicoletta Pucci 1, Manuel Salustri 2, Vanessa Modesti 1, Alessia L’Aurora 1, Marco Scortichini 3, Marco Zaccaria 4, Babak Momeni 4, Massimo Reverberi 2,*, Stefania Loreti 1
Editor: Chih-Horng Kuo5
PMCID: PMC7228078  PMID: 32413086

Abstract

Global trade and climate change are re-shaping the distribution map of pandemic pathogens. One major emerging concern is Xylella fastidiosa, a tropical bacterium recently introduced into Europe from America. In last decades, X. fastidiosa was detected in several European countries. X. fastidiosa is an insect vector-transmitted bacterial plant pathogen associated with severe diseases in a wide range of hosts. X. fastidiosa through a tight coordination of the adherent biofilm and the planktonic states, invades the host systemically. The planktonic phase is correlated to low cell density and vessel colonization. Increase in cell density triggers a quorum sensing system based on mixture of cis 2-enoic fatty acids—diffusible signalling factors (DSF) that promote stickiness and biofilm. The lipidome profile of Olea europaea L. (cv. Ogliarola salentina) samples, collected in groves located in infected zones and uninfected zones was performed. The untargeted analysis of the lipid profiles of Olive Quick Decline Syndrome (OQDS) positive (+) and negative (-) plants showed a clustering of OQDS+ plants apart from OQDS-. The targeted lipids profile of plants OQDS+ and OQDS- identified a shortlist of 10 lipids that increase their amount in OQDS+ and X. fastidiosa positive olive trees. These lipid entities, provided to X. fastidiosa subsp. pauca pure culture, impact on the dual phase, e.g. planktonic ↔ biofilm. This study provides novel insights on OQDS lipid hallmarks and on molecules that might modulate biofilm phase in X. fastidiosa subsp. pauca.

Introduction

Xylella fastidiosa (Xf) is one of the top 10 plant pathogenic bacteria [1] and is the cause of an environmental emergency within the European Union (EU). Xf has infected a broad host range [2] of plant species; symptoms vary depending on the combination of the host plant and Xf strain [3]. At present, X. fastidiosa subsp. pauca, associated to the OQDS, and three other subspecies, fastidiosa, multiplex, and sandyi have been identified in Europe [47]. Xf subsp. pauca was initially introduced from America into Southern Italy and recovered in olive trees [8,9]. This pathogen is associated to the OQDS which has caused losses up to €390 M of the national olive oil production, in the last three years in Italy [10].

Xf is an obligated vector-transmitted pathogen and a xylem-limited bacterium. Inter-host transmission is mediated by xylem sap-feeding insects. The biology of invasion has been described in the grapevine [11]. From the point of entry in grapevine, Xf moves along the xylem, attaches to its walls and, through a tight coordination of the adherent biofilm and the planktonic states, invades the host systemically [12,13]. The planktonic phase is correlated to low cell density and vessel colonization [14]. The colonization during the exploratory phase (planktonic) is correlated to low cell density and symptoms progression in grapevine. Increase in cell density triggers a quorum sensing system based on cis 2-enoic fatty acids—DSF that promote stickiness and biofilm formation [15]. Xylem vessels are occluded by the combined effect of bacterial biofilm and plant defences such as tyloses and formation of amorphous gels coating xylem vessel walls, causing characteristic symptoms such as leaf scorch [11,16]. DSF can modulate gene-expression in Xf [17,18]. DSF-mediated quorum sensing determines a) degradation of the pit membranes to enable cross-vessel diffusion; b) twitching motility of Xf cells; c) adhesion to the xylem surface and biofilm formation. The earlier stage of infection in Pierce disease, consists of evasion by the pathogen of the plant innate immune response and colonization of its vessels, de facto limiting opportunities for reacquisition by the feeding insect vectors [19]. At this stage, Xf is not detected by the plant as a biotic stress, but rather as an abiotic stress (drought and dehydration) [20]. At later stages, the biofilm-based phenotype, consisting of a high density of Xf cells, facilitates reacquisition by the vector and dissemination into other hosts. Only at this point, the plant recognizes the pathogen and mounts an immune response ineffective at preventing Xf colonization and symptoms [21,22]. DSF act as coordinators of this dual activity of Xf, allowing the switch from the early stage (planktonic endophytic lifestyle) into the later one (sessile insect-acquisition stage) [11,23]. Lipids appear to be central in this pathogen interplay between the two phenotypes. In Pseudomonas aeruginosa, other lipids, namely the oxylipins, act as hormones for controlling the switch among the different stages of bacterial lifestyle: planktonic, twitching, and biofilm. In P. aeruginosa, the oleic acid-derived oxylipins control the virulence in the host and function as autoinducers of a novel quorum sensing system mediating cell-to-cell communication in bacteria [24,25].

To provide a broader view of the lipids emerging in OQDS symptomatic trees infected by Xf, we analyzed the lipidomic profile of samples of 60-y.o. Olea europaea L. cv. Ogliarola salentina symptomatic and symptomless for the OQDS. The profile of 437 lipid compounds was assayed: 186 were found to be differentially accumulated in OQDS positive individuals of which 90 were further characterized and quantified by MS/MS spectrometry. Among these, we identified ten compounds, more abundant in Xf+ and OQDS+, that are novel hallmarks of Xf symptoms and infection of olive trees. Importantly, we found that these lipids modulate Xf lifestyle under in vitro conditions.

Materials and methods

Study site and sampling procedures

Sampling was carried out in the Apulia region, in October 2017, on 120 individuals of Olea europaea L. cv. Ogliarola salentina (60 years old), 60 showing OQDS symptoms (+) and 60 OQDS symptomless (-). The OQDS+ individuals were collected in an olive grove in Copertino in the infected area of the Lecce province (40°16'5.56" N 18°03'15.48" E); the OQDS- individuals were sampled in Grottaglie, Taranto province (40°32'12.98" N 17°26'14.03" E) in an area regarded by the phytosanitary service of the Apulia region as still unaffected by the pathogen. Trees were identified as symptomatic or symptomless following the criteria previously reported [26]. Mature shoots from each OQDS+ tree was collected from sections of the canopy on branches that showed desiccation and dieback. The samples consisted of “1- or 2-year-old twigs (ca.0.5 cm in diameter) from which cuttings of 15–20 cm were prepared from the portions close but yet unaffected by the withering and desiccation phenomena” [26]. Xylem tissue was then recovered, after removing the bark, and processed. The same procedure was performed for each OQDS- tree. The obtained 120 samples were separately lyophilized. 12 pools of equal weight (1g) were generated from the lyophilized samples, namely:6 pools (each representing 10 individuals) from OQDS+ and 6 from OQDS-. For a comprehensive lipidomic analysis, the pools included the overall analytical complexity of our samples [27,28]. OQDS+ and OQDS- samples were molecularly assayed via real-time PCR in technical triplicates [3,29] to verify the presence of Xf and thereon defined as Xf+ and Xf- samples (S1 Fig).

Lipids analysis

Xylem tissue (1,0 gr) was recovered and lipids extraction and analysis were performed as previously reported [30]. Xf+ and Xf- samples were assayed with the internal reference standards tricosanoic acid, glyceryl tripalmitate d31, and 9-HODEd4. The analysis was carried out at a final concentration of 2μM. The samples were analysed by untargeted lipid analysis conducted with a G6220A TOF-MS, (Agilent Technologies, USA) operating in negative and positive ion scan mode as previously described [30]. A sub-group of lipid classes was analysed (fragmentation analysis) by LC-MS/MS (Triple Quadrupole; 6420 Agilent Technologies, USA) as reported [30]; multiple reaction monitoring (MRM) methods were adopted to analyse the most abundant lipid entities (S1 Table). MRM data were processed using the Mass Hunter Quantitative software (B.07.00 version, Agilent Technologies, USA). The mass spectrometry analyses were performed three times, each time in technical triplicate (n = 9). PCA and significance-fold change analysis (Volcano plot) for untargeted LC-TOF/MS results were performed trough Agilent Mass Analyzer software. Significance tests (T-Student Test, p<0.05) and plots of MRM and SIM results were performed trough R software.

Quantification of biofilm formation

An in vitro test was made to assess the effect of free fatty acids, diacylglycerides, and oxylipins on biofilm formation of Xylella fastidiosa subsp. pauca strain De Donno (CFBP 8402). Xf subsp. pauca biofilm formation was evaluated as previously described [31] with some modifications. Briefly, a pure culture of the bacteria was grown for 7 days on PD2 plates, scraped and resuspended in PBS. 10μL of cell suspension (A600 = 0.5 OD) was inoculated in a sterile glass tube containing 1mL of PD2. The free fatty acids (FFA) (Sigma-Aldrich, USA) or diacylglycerides (1,3-Dilinoleoyl-rac-glycerol; 1,3-Diolein) (Sigma-Aldrich, USA) or oxylipins [Cayman chemicals, USA or 7,10 DiHOME and the mix (7,10 DiHOME; 10-HOME) kindly provided by Dr. Eriel Martínez and Javier Campos-Gómez (Southern Research Center, AL, USA] were added to the medium at desired concentrations when required as reported [24]. After 11 days of incubation (28°C; 100 rpm), the total number of cells—planktonic growth (cells in suspension) and biofilm growth (cells adhered to the substrate) was estimated. The lipid compounds were divided into two groups: those dissolved in EtOH (with EtOH) and those dissolved in water (no EtOH). Spectrophotometric absorption of Xf subsp. pauca cultures was used to measure growth (600 nm) and biofilm formation (595 nm). For compounds dissolved in EtOH, references with a corresponding concentration of EtOH but without the compound were used as background. Impact on growth / impact on biofilm are defined as the amount of growth/biofilm formation minus the background, normalized to the growth/biofilm formation in a medium in the absence of added EtOH or lipids. A positive impact indicates values more than no-lipid controls (i.e. improved growth or biofilming), whereas a negative impact indicates values less than no-lipid control (i.e. inhibited growth or biofilming). EtOH at similar molarity to lipids was additionally used as a point of reference of how Xf subsp. pauca growth and biofilms were affected. The experiments were performed in biological triplicate for each treatment and carried out three times (total repetitions per treatment n = 9). Multiple comparison with Kruskal-Wallis test (p value< 0.05) and Fisher's LSD post-hoc test, with Bonferroni correction, were run on R software to individuate significant (p<0.05) groupings within the different treatments.

Results

Infected trees exhibit a lipid profile that is distinct from healthy trees

A lipidomic untargeted analysis was performed to establish if lipids are differentially accumulated in OQDS symptomatic versus symptomless samples. OQDS + and OQDS- samples resulted respectively infected and non-infected with Xf when assessed by real-time PCR. Volcano plot of LC-ToF untargeted analyses on negative-ion scans identified 437 compounds, 186 of which significantly modified (Fold Change >2.0; p <0.05), with 173 upregulated and 13 downregulated (Fig 1). PCA highlighted two primary components (X-axis: 60.48%; Y-axis: 12.05%) that separated the Xf+ and Xf- clusters (Fig 2). Volcano plot analysis on positive-ion scans provided a few significantly modified compounds (S2 Fig).

Fig 1. Volcano plot analysis of 437 compounds on negative ion scan, in Xf+ and Xf- samples.

Fig 1

The x-axis shows the fold change to indicate the variation in abundance of compounds present in Xf+ compared to Xf- samples. The compounds on the right side were more abundant, whereas those on the left side were less abundant in Xf+ condition. Entities that satisfied the fold change and the P-value cut-off of 2.0 and 0.05, respectively, are marked in red.

Fig 2. Principal component analysis.

Fig 2

Score plot of data generated by HPLC-ESI/TOF-MS analysis of Xf+ (red square) and Xf- (blue square) samples. The results of the analysis referred to three separate experiments performed in triplicates.

Among the 186 differentially accumulated, 90 compounds were selected and analysed by a targeted MRM or SIM on the basis of the highest FC and in light of previous results [30] (S1 and S2 Tables). The chemometric analysis highlighted that ten compounds discriminated Xf+ from Xf- samples and were significantly more abundant in Xf+ samples. Namely: oleic/linoleic/linolenic acid-deriving oxylipins (9-hydroxyoctadecenoic acid - 9HODE; 9-hydroperoxyoctatrienoic acid - 9HOTrE; 13-hydroxyoctadecenoic acid - 13HODE; 13-hydroperoxyoctatrienoic acid - 13HOTrE; 13-oxo-octadecenoic acid - 13oxoODE; 10-hydroxyoctadecenoic acid -10HODE; 10-hydroperoxyoctamonoenoic acid - 10HpOME); unsaturated fatty acids (oleic acid—C18:1; linoleic acid—C18:2); and diacylglycerol [DAG36:4 (18:1/18:3)] (Fig 3 and S3 Table).

Fig 3. Boxplots of statistically significant compounds analyzed by MRM or SIM.

Fig 3

Comparisons between naturally non-infected (Xf negative) and naturally infected (Xf positive) plant samples are displayed on X-axis. The Y-axis shows the normalized relative abundance. Horizontal line in each boxplot indicates the median and black dots represent the outlier samples.

Lipids moderate Xf biofilm formation

In order to determine the effect of the compounds showed in Fig 3 on Xf ability to form biofilm, we proceeded to an in vitro test as reported in [24]. In vitro test of biofilm formation indicated that the 7,10-dihydroxyoctamonoenoic acid (7,10-diHOME), the mix 7.10 diHOME and 10-hydroxyoctamonoenoic acid (10-HOME), C18:1 and C18:2 and their diacylglycerols (DAG 36:2 and 36:4), at the concentration of 0.0025 mg mL-1, stimulated planktonic growth (Fig 4A); at the same concentrations, 9-HODE induced biofilm formation, whereas 7,10-diHOME and the mix of 7,10 diHOME and 10-HOME strongly inhibited it (Fig 4B). Free fatty acids (linoleic acid, oleic acid) and diacylglycerides (1,3-Dilinoleoyl-rac-glycerol; 1,3-Dioleyl-rac-glycerol), tested at different concentrations, stimulated planktonic growth and did not affect biofilm formation (S3 and S4 Figs). LOX-derived oxylipins, namely 9HODE, 13HODE, 13OXODE and 9HOTRE promoted biofilm whilst the JA-related 13-HOTRE did not significantly affect it (S5 Fig). The DOX-derived oxylipins, 7,10-DiHOME and 10-HOME, produced by the pathogen (as suggested in [30]), strongly inhibited biofilm formation (S4 Fig). LOX-oxylipins did not show an effect on bacterial growth (S6 Fig), except for the DOX-oxylipins mixture of 7,10-DiHOME and 10-HOME (S3 Fig).

Fig 4.

Fig 4

Boxplots of effects caused by lipid compounds on planktonic growth (A) and biofilm formation (B). Selected compounds (FFA, DAG and oxylipins) are the ones with the most relevant effect, measured as OD fold-change, considering 0.0025mg mL-1 concentration versus control. The Y-axis displays the optical density (OD). The X-axis displays the compounds (Statistical significance assessed trough Kruskal Wallis test, p-value <0.05). Horizontal line in each boxplot indicates the median and black dots represent the outlier samples.

Discussion

In the host plant, Xf colonizes the xylem vessels and elicits their occlusion [11,23,32]. Xf maintains a lifestyle that switches bidirectionally from adhesive to non-adhesive cells phenotype and vice versa [14]. Lipids are crucial signals that can modulate the pathogen virulence and play important roles during the infection process [15,33]. Among lipids, oxylipins can modulate biofilm formation and virulence in the Gram-negative pathogen P. aeruginosa [25]. Most information on the biology of Xf is mostly referred to one of its subspecies, i.e. fastidiosa, in the context of Pierce’s disease and, regarding lipids involvement, to DSF [21]. Recently, we showed that during the infection of the model organism Nicotiana tabacum by Xf subsp. pauca, several lipids were differently accumulated in infected versus healthy plants; DSF-like compounds apart, oxylipins emerged as hallmarks of pathogenic invasion of host tissues [30]. In olive trees, reports are available on the molecular basis of Xf subsp. pauca invasion [26,32]. More recently, Cardinale and colleagues [34] demonstrated that Xf subsp. pauca forms biofilm in xylem vessels of OQDS+ trees (cultivar “Ogliarola di Lecce”), pinpointing the role of bacterial aggregates in vessel occlusions in naturally infected olive trees. Notwithstanding the importance of lipids in Xf lifestyle, no report employs a lipidomic approach to differentiate OQDS+ from OQDS- trees.

We explored for the first time the lipidomic profile of olive trees naturally infected by Xylella fastidiosa. Lipids play a key role in plant disease. In this work, we check by untargeted analysis all the lipids that change under the pathogen pressure; moreover, PCA of the lipid entities allowed to differentiate the infected trees from the uninfected ones. Since the OQDS- samples clustered differently from OQDS+ samples, we suggest that the differential formation of lipid entities can be modulated by the presence of Xf producing OQDS symptoms. Lipids are essential constituents of the cells involved in different biological functions; this study could pave the way for developing a diagnostic tool targeted on the lipids that differentiate the infected plants by non-infected ones. In this regard, the Volcano plot analysis of the extracted entities from olive trees affected by OQDS, highlighted that 186 lipids compounds were specifically formed in symptomatic samples. More intriguingly, 10 compounds emerged as statistically able to discriminate Xf+ from Xf- olive trees. Considering that this part of the study gathers data straight from natural infection processes, we suggest these specific lipids as hallmarks of Xf infection of olive trees and propose to extend this type of approach to other hosts affected by this fastidious bacterial pathogen.

In olive trees, OQDS symptoms are closely related to xylem vessel occlusions caused by biofilm formation from Xf [34]. Lipid metabolism has a strong impact on plant-host interaction and, despite the proceedings in plant pathology, many important questions remain unanswered about the functional diversity of lipids and the mechanisms bacterial cells employ to coordinate their response to lipids modulation. In this study, we investigated how lipids differently accumulated in OQDS+ samples affected the lifestyle of X. fastidiosa subsp. pauca. To identify their role in Xf biofilming [18,25], we tested in vitro the oleic acid-derived 7,10-diHOME alone as well as in conjunction with 10-HOME (DOX-oxylipins); the free fatty acids C18:1 and C18:2 and their diacylglycerols (DAG 36:2 and 36:4); the LOX-derived 9-oxylipins (9HODE, 9-OXODE, 9-HOTRE) and 13-oxylipins (13-HODE, 13OXODE and 13-HOTRE).

Our working hypothesis on the effects of these compounds on Xf biofilming stemmed from the available information on their biological role and was inspired by Roper and colleagues’ intuition: “the bacteria induce an autoimmune-like syndrome” [14]. More specifically, the oleic acid is among the modulators of quorum sensing in Xf [15]; in other bacterial pathogens its ratio with the linoleic acid could promote virulence [33], whilst DAG associated compounds (e.g. DAG 36:2) lead to establish an appropriate defence response by inducing defence-signalling molecules [33]. As reported elsewhere, oleic acid-derived DOX-oxylipins are instrumental in moderating the lifestyle of another opportunistic pathogen: P. aeruginosa [24]. Concerning LOX-derived products, in animal systems, 9-oxylipins (e.g. 9-HODE) may display a pro-inflammatory effect, whereas 13-oxylipins (e.g. 13-HODE) has an anti-inflammatory one [35]. Some authors suggested using 13- to 9-oxylipins ratio as a marker of the inflammatory status in murine models [36]. 9- and 13-oxylipins play a similar, apparently antagonistic role in fungal–plant interaction [37]. Our results show that 18:1 DOX-oxylipins (e.g. 7,10-diHOME) hold back biofilm formation, while LOX-derived 9-oxylipins (e.g. 9-HODE) stimulate biofilm formation. Regarding a possible antagonistic role for 9- and 13-oxylipins, we noticed a similar antagonistic effect in biofilming (i.e. 9- and 13-HOTRE).

Our hypothesis provides the following scenario: plants produce oxylipins in response to several stresses, including which pathogenic insult [38]. Oxylipins, other than functioning as plant defence signals [39], may display an effect toward pathogens in modulating their lifestyle, or a biocidal one [40, 41]. Notably, LOX-derived products could interact with the membranes of pathogens altering their organization and disturbing cell growth [42]. Further studies are needed to clarify how Xf can adapt to oxylipins-modulated plant stress response and exploit it to trigger its biofilming.

We highlight for the first time the different accumulation of FFA, oxylipins and DAG in OQDS+ and Xf+ olive trees and we suggest their role in the modulation of Xf subsp. pauca biofilming. We encourage researchers to investigate oxylipins as new targets for the development of treatments for OQDS in line with the Roper team suggestion: “design therapeutics that target the dispersal state or encourage adhesion to lock the bacterial population into its self-limited state permanently” [14].

A more straightforward outcome of our results leads to exploit lipids as markers for developing diagnostic methods based on both destructive strategies, such as molecular tests (lipids related genes) and/or MS spectrometry analysis, and on non-destructive tests such as volatilome of Volatile Organic Compounds (VOCs) derived lipids, as recently suggested [43,44].

Supporting information

S1 Fig. Summary of OQDS and Xf real-time PCR screen results.

A) Amplification curves of real-time PCR of OQDS- samples and B) of OQDS+ samples following the protocol published by Harper and colleague [29].

(DOCX)

S2 Fig. Volcano plot analysis of 524 compounds on positive ion scan, in Xf+ and Xf- samples.

The x-axis shows the fold change to indicate the variation in abundance of compounds present in Xf+ compared to Xf-. The compounds on the right side were more abundant, whereas those on the left side were less abundant in Xf+ condition. Entities that satisfied the fold change and the P-value cut-off of 1.5 and 0.05, respectively, are marked in red.

(DOCX)

S3 Fig. Impact on growth development at different concentrations of individually added lipids (DAG 36:2, DAG 36:4, oleic and linoleic acids, 7,10-DiHOME and 7,10-DiHOME and 10-HOME mix) to in vitro cultures of Xylella fastidiosa.

Impact is expressed as OD600 fold-change compared to the control, the effect of the corresponding amounts of ethanol employed to dissolve the compounds has been subtracted. Concentrations are expressed in molarity. The effect of ethanol at equivalent and higher molarities is plotted as a reference. Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

(DOCX)

S4 Fig. Impact on biofilm production at different concentrations of individually added LOX-oxylipins to in vitro cultures of Xylella fastidiosa subsp. pauca strain De Donno (CFBP 8402).

Impact is expressed as OD595 fold-change compared to the control. Concentrations are expressed in molarity. The effect of ethanol at equivalent and higher molarities is plotted as a reference. Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

(DOCX)

S5 Fig. Impact on biofilm production at different concentrations of individually added lipids (DAG 36:2, DAG 36:4, oleic and linoleic acid, 7,10-DiHOME and 7,10-DiHOME and 10-HOME mix) to in vitro cultures of Xylella fastidiosa subsp. pauca strain De Donno (CFBP 8402).

Impact is expressed as OD595 fold-change compared to the control, the effect of the corresponding amounts of ethanol employed to dissolve the compounds has been subtracted. Concentrations are expressed in molarity. The effect of ethanol at equivalent and higher molarities is plotted as a reference. Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

(DOCX)

S6 Fig. Impact on growth development at different concentrations of individually added LOX-oxylipins to in vitro cultures of Xylella fastidiosa.

Impact is expressed as OD600 fold-change compared to the control, the effect of the corresponding amounts of ethanol employed to dissolve the compounds has been subtracted. Concentrations are expressed in molarity. The effect of ethanol at equivalent and higher molarities is plotted as a reference. Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

(DOCX)

S1 Table. Analysed lipid entities and relative parameters for Multiple Reaction Monitoring (MRM) experiments and Single Ion Monitoring (SIM).

A) MRM analysis method for oxylipins; B) MRM method for phospholipids, glycerolipids, ornitholipids, bactophenols; C) SIM method for free fatty acids.

(DOCX)

S2 Table. Compound identification from LC-TOF untargeted analysis.

Each row provides the compound putative identification and values explaining differences between Xf-positive and Xf-negative samples, i.e.: p-value, corrected p-value, Fold Change of Xf-positive versus Xf-negative, abundance difference of Xf-positive versus Xf-negative in raw and log2 form. Compounds highlighted in yellow were fragmented and characterized through product ion experiments.

(DOCX)

S3 Table. Normalized peak areas of SIM and MRM analyzed lipid entities.

Compounds’ peak areas were divided by their internal standard’s peak area and then by the maximum value of internal standard peak area. For each compound the fold-change of Xf+ samples versus Xf- samples was calculated, as such the p-value from Student T-test. Compounds with a p-value <0.05 are represented on the upper part of the volcano plot, above the red line corresponding to -log10(0.05).

(DOCX)

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The study was funded by MIPAAFT, Project Oli.Di.X.I.It (“OLIvicoltura e Difesa da Xylella fastidiosa e da Insetti vettori in Italia”), D.M. 23773 del 6/09/2017, Project SALVAOLIVI (“Salvaguardia e valorizzazione del patrimonio olivicolo italiano con azioni di ricerca nel settore della difesa fitosanitaria”), D.M. 33437 del 21-12-201 and by Regione Puglia agreement: “Strategie di controllo integrato per il contenimento di Xylella fastidiosa in oliveti pugliesi ed analisi epidemiologiche del complesso del disseccamento rapido dell’olivo (CoDiRO). B.M. and M.Z. were supported by a start-up fund from Boston College and by an Award in Biomedical Excellence from the Smith Family Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Chih-Horng Kuo

24 Feb 2020

PONE-D-19-35039

Xylella fastidiosa and plant produced lipids control the switch adhesive versus non-adhesive state and viceversa

PLOS ONE

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Reviewer #2: Partly

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Reviewer #1: This study determined the lipidomic profile of Xf-infected versus uninfected Olea europaea (symptomatic versus symptomless for Olive Quick Decline Syndrome OQDS). The authors selected ten lipidic compounds differentially detected in the Xf-plants and study their effect on Xf biofilm formation and growth in vitro. They show that some of these compounds have an effect (positive or negative) on biofilm formation in vitro. This work is important since it provide initial evidence of the existence of a Xf-plant host cross-talk mediated by lipid molecules. However, the main limitation of this work is that it lacks studies in vivo, which would have greatly support the cross-talk hypothesis. For example, some experiment co-inoculating olive leaves with Xf and the lipidic compound to measure the effect on symptoms and biofilm in vivo. Fluorescent Xf can be used to observe biofilm in vivo into the xyleme vessels.

At the end on the Introduction the authors state: “Importantly, we found that these lipids can be part of a novel Xf quorum sensing control system during its pathogenic relationship with the host”. Although this claim might be correct for some of the lipid molecules studied, it is weakly supported by the experimental evidence presented in the manuscript. The consensus definition of bacterial quorum sensing (QS) involves self-produced extracellular chemical signals, which can accumulate in a local environment to levels that are required to activate transcription of specific effector genes. The authors neither present experimental evidence showing that the lipidic compounds accumulate in a cell density dependent fashion, nor they show that this molecules function as signals to induce a specific subset of effector genes. The evidence provided to this respect is indirect and tangential. In addition, some of the molecules are produced by the plant, which cannot fulfill the definition of QS.

This reviewer thinks that for the paper to be accepted either, 1) the authors should provide more evidence (preferentially in vivo) of the bacterial-host cross-talk and of the QS nature of some of the lipid molecules produced by Xf, or 2) the authors should refocus the manuscript by making more emphasis in the importance of lipidomic determination of Xf-infected vs uninfected olive plants and by unbolding the claims regarding the QS and cross-talk hypotheses. The QS and cross-talk hypotheses should be stated more cautiously and hypothetical. The value of the differential lipidome can be exploited in the discussion as a way to diagnose Xf in olive crops perhaps.

Minor issues:

• Olive Quick Decline Syndrome (OQDS) should be defined the first time mentioned in the abstract.

• The figures can be improved by enlarging some difficult to read fonts.

• In the discussion avoid to repeat information already provided in the Introduction and Results sections.

Reviewer #2: Comments to author are attached.

The study showed streamlined methods in lipid profiling of Xf infected plants from the field, which provides insights into the disease in the field. However, the basis for doing bacterial growth assays was not well elaborated and it was unclear why certain assays and conditions were used. Parameters and findings from the lipidomic analysis were not well interpreted. I suggest the authors address these points through data analysis and assessment of bacterial infection/burden/biofilm formation in the Xf+ samples before resubmission.

**********

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Reviewer #2: Yes: Mengyao Niu

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Attachment

Submitted filename: 021020 PLOSE ONE ms review comments MN NPK.docx

PLoS One. 2020 May 15;15(5):e0233013. doi: 10.1371/journal.pone.0233013.r002

Author response to Decision Letter 0


30 Mar 2020

Answer to Editor

Dear,

We have inserted and corrected all the information and suggestions proposed by the reviewers. Specifically, concerning suggestion proposed by reviewer#1 due to lab closure for covid-19 restrictions we were not able to perform the in planta experiments suggested and we choose to reformulate completely our paper following his/her suggestion as second option. Regarding the reviewer#2 we answered all his/her criticisms/suggestions and inserted novel supplementary material. We removed the sentence regarding the not shown data as suggested by your editorial office.

Answer to Reviewer #1: This study determined the lipidomic profile of Xf-infected versus uninfected Olea europaea (symptomatic versus symptomless for Olive Quick Decline Syndrome OQDS). The authors selected ten lipidic compounds differentially detected in the Xf-plants and study their effect on Xf biofilm formation and growth in vitro. They show that some of these compounds have an effect (positive or negative) on biofilm formation in vitro. This work is important since it provide initial evidence of the existence of a Xf-plant host cross-talk mediated by lipid molecules. However, the main limitation of this work is that it lacks studies in vivo, which would have greatly support the cross-talk hypothesis. For example, some experiment co-inoculating olive leaves with Xf and the lipidic compound to measure the effect on symptoms and biofilm in vivo. Fluorescent Xf can be used to observe biofilm in vivo into the xyleme vessels.

At the end on the Introduction the authors state: “Importantly, we found that these lipids can be part of a novel Xf quorum sensing control system during its pathogenic relationship with the host”. Although this claim might be correct for some of the lipid molecules studied, it is weakly supported by the experimental evidence presented in the manuscript. The consensus definition of bacterial quorum sensing (QS) involves self-produced extracellular chemical signals, which can accumulate in a local environment to levels that are required to activate transcription of specific effector genes. The authors neither present experimental evidence showing that the lipidic compounds accumulate in a cell density dependent fashion, nor they show that this molecules function as signals to induce a specific subset of effector genes. The evidence provided to this respect is indirect and tangential. In addition, some of the molecules are produced by the plant, which cannot fulfill the definition of QS.

This reviewer thinks that for the paper to be accepted either, 1) the authors should provide more evidence (preferentially in vivo) of the bacterial-host cross-talk and of the QS nature of some of the lipid molecules produced by Xf, or 2) the authors should refocus the manuscript by making more emphasis in the importance of lipidomic determination of Xf-infected vs uninfected olive plants and by unbolding the claims regarding the QS and cross-talk hypotheses. The QS and cross-talk hypotheses should be stated more cautiously and hypothetical. The value of the differential lipidome can be exploited in the discussion as a way to diagnose Xf in olive crops perhaps.

Thank you for your kind suggestion. Since we are currently working on a set of mutant strains showing defective for oxylipin-forming enzymes, we accept your suggestions and will include another set of data in a following paper still underway. We agree with you that, at this stage, we cannot fully support the hypothesis proposed, so we we eliminated or “unboldened” it in the revised version of this paper.

Minor issues:

• Olive Quick Decline Syndrome (OQDS) should be defined the first time mentioned in the abstract.

Thanks for your suggestion. We have defined OQDS in the abstract

• The figures can be improved by enlarging some difficult to read fonts.

The font of the boxplot figures have been enlarged.

• In the discussion avoid to repeat information already provided in the Introduction and Results sections.

The discussion has been completely revised avoiding repetitions from the introduction and results.

Answer to Reviewer#2

Summary: In the current submitted manuscript, the authors described their work in profiling the lipids of Xylella fastidiosa, both from infected olive trees and the uninfected counterparts. Furthermore, they identified free fatty acids derivatives that are differentially represented in these two groups, and some of those inhibit or stimulate the growth of X. fastidiosa.

Comments:

Dear reviewer,

replies to your comments are shown in italics

Line 96. It was unclear which part of the plant was collected and how.

The description of how samples collection was performed is now added to the manuscript at L72-77

Line 101. Can authors elaborate further what they mean by “six pools from OQDS+ and six from OQDS-“? Does it mean that 10 samples from each group were pooled together? How many samples (or pools) then were subjected to the lipidomic analysis? 10 samples (derived from 10 different olive tresses) were pooled together and 12 samples were analysed.

Lipidomic analysis was performed on 12 pools for a total of 120 plants (60 infected and 60 non-infected); each pool was made putting together samples harvested from 10 plants. The sentence has been modified accordingly at L78-80

Line 156. Are most of the symptomless samples free of Xf, and are the OQDS+ samples mostly infected by Xf? Please provide a summary of OQDS and Xf PCR screen results.

The real time PCR results are reported in this answer and, now, in S1 Figure. The figure S1A shows the results of OQDS- samples, the figure S1B the results of OQDS+.

A)

A) B)

Samples were amplified following the protocol published by Harper and colleague [29].

Line 159. The authors described two principle components in Figure 2-do both PC’s differentiate the Xf+ and Xf- samples? Please clarify.

The PC1 distinguish Xf+ from Xf-. PC2 is more related to the type of lipids present as highlighted in the corresponding loading plot. From this, we can suggest that specific type of lipids are hallmarks of infection (e.g. oxylipins), some others are probably more related to specificities in lipid composition of the different pools.

Line 162. Please elaborate the reasons for selecting the 90 compounds for further analysis. What previous results specifically were the authors referring to? Please also provide a table with fold change and p-values listed for these 90 compounds.

The select compounds emerged from the previous dataset published in Scala et al., 2018 doi https://doi.org/10.3389/fmicb.2018.01839 [30], and from selecting compounds on the upper right and left box within the volcano plot of Figure 1 straight from mass profiler professional output. Then, on these 90 compounds we performed product ion fragmentation to confirm the ToF analysis. On those positively identified (~80%) we performed MRM and SIM analysis to quantify them. Within this dataset (Table S2), only 25 were revealed within our samples (both Xf- and Xf+) and consequently quantified by MRM (now shown in Table S3). 10 out of 25 resulted significantly different between Xf+ and Xf- samples (T Test and volcano plot in Table S3) and were used for building up the boxplots of Figure 3.

Fig 1. Statistical corrections be taken into account for multivariant analysis. A more stringent cut-off should be applied.

We worked on default settings of the mass profiler version (Cut-offs were 2 fold-change and 0,05 p-value) working downstream, but knowing that this analysis could be more stringent we chose almost half of the emerged compounds from the volcano plot and specifically those presenting the highest FC and corrected P value.

Line 165. In Fig 3 the authors showed 10 lipids that are differentially abundant between the Xf+ and Xf- samples. It was unclear why these 10 lipids were chosen, so please elaborate further. Are they the most different ones? Did these show the biggest fold change?

Among the set of 90 targets, twe chose the most different between the Xf+ and Xf- samples. The 10 compounds are the statistically significant ones (T-test, p-value<0,05; Table S3) among targeted analysis tested compounds (listed in MRM table in Material and Methods), as also stated above at answer at lane 162 question.

Line 182, Fig 3. The authors said “The Y-axis shows the normalized relative abundance” though it is not clear how the normalization was done, and the axes appeared arbitrary. Please elaborate how these numbers were calculated.

Target compounds’ peak areas were divided by their internal standard’s peak area and then by the maximum value of internal standard peak area

Line 188. Even though other studies have shown SEMs of Xylella fastidiosa infecting other plants and forming biofilm (Newman et al., 2004), it was not confirmed that they do the same in the host being studied here. Can the authors confirm with a subset of Xf+ samples that biofilm was indeed formed? This will provide basis for linking lipid profiles with planktonic/biofilm growth.

Unfortunately, we cannot confirm the biofilm formation in Xf+ olive samples, but we are supported by Cardinale et al 2018 [34] who demonstrated that Xf form biofilm into symptomatic olive trees cultivar (“Ogliarola di Lecce”). The cultivar used in this study was the same we employed. Cardinale et al 2018 evaluated the role of bacterial aggregates in vessel occlusions and quantified the level of infection and vessel occlusion in both petioles and branches of naturally infected and non-infected olive trees. The authors demonstrated that symptomatic petioles showed colonization by X. fastidiosa, and the vessels appeared completely occluded by a biofilm containing bacterial cells and extracellular matrix. Thus, Cardinale and colleagues point out the primary role of the pathogen in olive vessel occlusions and underline the bacteria role in causing vessel occlusion in leaves. The paper is now cited in ref section [34].

Line 192. It was not shown that 7,10-diHOME were different between the Xf+ and Xf- samples, so why was this tested? Why was a mixture of 7,10-diHOME and 10-HOME tested?

The oleic-derived oxylipins present in figure 3 is the 10-HpOME that is a relatively unstable product and thus difficult to provide in vitro. Following the study of Martinez et al. 2016 [24], 10-HpOME is readily converted to 7,10-diHOME and 10-HOME. These products are commercially unavailable, and we asked the Martinez group to provide them and they kindly send us these oxylipins. Unfortunately, 10-HOME is in mixture with 7,10-diHOME and the 7,10-diHOME was pure. We inserted them in the in vitro tests since they are, as indicated in Martinez et al 2016 and 2018 [24, 25], part of the oleic acid oxylipin pathway and a quorum-sensing molecule in Pseudomonas aeruginosa; furthermore, in Scala et al. 2018 [30] we found 7,10-diHOME in Xf, thus in this manuscript we aim at verifying if this compound could act in Xf similarly to P. aeruginosa.

Minor point here: 9-HODE induced biofilm formation was shown in Fig 5, not Fig 4.

Concerning Fig. 5, we suppose it is due to the consequent numeration generated by the PloS submitting system. Thus, the boxplots are reported in the second page of the figure 4.

Line196. Can authors provide statistical support for the effect of these compounds shown in Fig S2?

Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

Decision:

The study showed streamlined methods in lipid profiling of Xf infected plants from the field, which provides insights into the disease in the field. However, the basis for doing bacterial growth assays was not well elaborated and it was unclear why certain assays and conditions were used. Parameters and findings from the lipidomic analysis were not well interpreted. I suggest the authors address these points through data analysis and assessment of bacterial infection/burden/biofilm formation in the Xf+ samples before resubmission.

- The basis for bacteria growth assays was elaborated in relation to the results of Martinez et al., 2016 [24] whereas the growing conditions were chosen in relation to the information reported in Scala et al 2018 [30]. In relation to this issue, more information were now added in the text.

- The interpretation of parameters and finding of lipidomic analysis were explained in the replies to reviewer comments (see above). Therefore, the interpretation of lipidomic results was conduct following the available literature on X. fastidiosa and on laboratory experience in lipidomics in plant disease and by closely following the outputs of mass profiler professional provide by Agilent technologies.

- The bacterial infection/burden/biofilm formation in the Xf+ samples is assessed in the replies above and in the text

Attachment

Submitted filename: Rebuttal Letter.docx

Decision Letter 1

Chih-Horng Kuo

28 Apr 2020

Xylella fastidiosa subsp. pauca and olive produced lipids control the switch adhesive versus non-adhesive state and viceversa

PONE-D-19-35039R1

Dear Dr. Reverberi,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Chih-Horng Kuo, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Dear authors,

Congratulations on the nice revision. Both reviewers are satisfied with the changes and I agree with the assessment. Reviewer #2 have provided some additional comments in a separate file. I believe that these are pretty minor and could be corrected prior to production, there is no need for this manuscript to go through another round of scientific review.

Best, CH

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: (No Response)

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Reviewer #1: (No Response)

Reviewer #2: The authors addressed our questions through detailing the rationales behind the study and supplementing data and methods that were previously missing or poorly explained. This overall meets the expectation. I accept this manuscript if the authors address a few points highlighted in attached document.

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Reviewer #1: No

Reviewer #2: Yes: Mengyao Niu

Attachment

Submitted filename: 042120 PlosOne review comments.docx

Acceptance letter

Chih-Horng Kuo

4 May 2020

PONE-D-19-35039R1

Xylella fastidiosa subsp. pauca and olive produced lipids moderate the switch adhesive versus non-adhesive state and viceversa

Dear Dr. Reverberi:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Chih-Horng Kuo

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Summary of OQDS and Xf real-time PCR screen results.

    A) Amplification curves of real-time PCR of OQDS- samples and B) of OQDS+ samples following the protocol published by Harper and colleague [29].

    (DOCX)

    S2 Fig. Volcano plot analysis of 524 compounds on positive ion scan, in Xf+ and Xf- samples.

    The x-axis shows the fold change to indicate the variation in abundance of compounds present in Xf+ compared to Xf-. The compounds on the right side were more abundant, whereas those on the left side were less abundant in Xf+ condition. Entities that satisfied the fold change and the P-value cut-off of 1.5 and 0.05, respectively, are marked in red.

    (DOCX)

    S3 Fig. Impact on growth development at different concentrations of individually added lipids (DAG 36:2, DAG 36:4, oleic and linoleic acids, 7,10-DiHOME and 7,10-DiHOME and 10-HOME mix) to in vitro cultures of Xylella fastidiosa.

    Impact is expressed as OD600 fold-change compared to the control, the effect of the corresponding amounts of ethanol employed to dissolve the compounds has been subtracted. Concentrations are expressed in molarity. The effect of ethanol at equivalent and higher molarities is plotted as a reference. Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

    (DOCX)

    S4 Fig. Impact on biofilm production at different concentrations of individually added LOX-oxylipins to in vitro cultures of Xylella fastidiosa subsp. pauca strain De Donno (CFBP 8402).

    Impact is expressed as OD595 fold-change compared to the control. Concentrations are expressed in molarity. The effect of ethanol at equivalent and higher molarities is plotted as a reference. Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

    (DOCX)

    S5 Fig. Impact on biofilm production at different concentrations of individually added lipids (DAG 36:2, DAG 36:4, oleic and linoleic acid, 7,10-DiHOME and 7,10-DiHOME and 10-HOME mix) to in vitro cultures of Xylella fastidiosa subsp. pauca strain De Donno (CFBP 8402).

    Impact is expressed as OD595 fold-change compared to the control, the effect of the corresponding amounts of ethanol employed to dissolve the compounds has been subtracted. Concentrations are expressed in molarity. The effect of ethanol at equivalent and higher molarities is plotted as a reference. Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

    (DOCX)

    S6 Fig. Impact on growth development at different concentrations of individually added LOX-oxylipins to in vitro cultures of Xylella fastidiosa.

    Impact is expressed as OD600 fold-change compared to the control, the effect of the corresponding amounts of ethanol employed to dissolve the compounds has been subtracted. Concentrations are expressed in molarity. The effect of ethanol at equivalent and higher molarities is plotted as a reference. Tested compounds were evaluated through Kruskal Wallis test and classified by Fisher LSD post-hoc test with Bonferroni correction (p-value<0,05).

    (DOCX)

    S1 Table. Analysed lipid entities and relative parameters for Multiple Reaction Monitoring (MRM) experiments and Single Ion Monitoring (SIM).

    A) MRM analysis method for oxylipins; B) MRM method for phospholipids, glycerolipids, ornitholipids, bactophenols; C) SIM method for free fatty acids.

    (DOCX)

    S2 Table. Compound identification from LC-TOF untargeted analysis.

    Each row provides the compound putative identification and values explaining differences between Xf-positive and Xf-negative samples, i.e.: p-value, corrected p-value, Fold Change of Xf-positive versus Xf-negative, abundance difference of Xf-positive versus Xf-negative in raw and log2 form. Compounds highlighted in yellow were fragmented and characterized through product ion experiments.

    (DOCX)

    S3 Table. Normalized peak areas of SIM and MRM analyzed lipid entities.

    Compounds’ peak areas were divided by their internal standard’s peak area and then by the maximum value of internal standard peak area. For each compound the fold-change of Xf+ samples versus Xf- samples was calculated, as such the p-value from Student T-test. Compounds with a p-value <0.05 are represented on the upper part of the volcano plot, above the red line corresponding to -log10(0.05).

    (DOCX)

    Attachment

    Submitted filename: 021020 PLOSE ONE ms review comments MN NPK.docx

    Attachment

    Submitted filename: Rebuttal Letter.docx

    Attachment

    Submitted filename: 042120 PlosOne review comments.docx

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.


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