Rachid Jellali
email: rachid.jellali@utc.fr

Stéphane Poulain

Myriam Lereau Bernier

Françoise Gilard

Yannick Y Tauran

Sachi Kato

Mathieu Danoy

Bertrand David Segard

Taketomo Kido

Atsushi Miyajima

Stephane Poulain

Myriam Lereau Bernier

Bertrand David Segard

Charles Plessy

Yasuyuki Sakai

Eric Leclerc
email: eleclerc@iis.u-tokyo.ac.jp

Integration of metabolomic and transcriptomic profiling to compare two protocols of differentiation of human induced pluripotent stem cells into hepatocytes

Keywords: metabolomic, nanoCAGE, hepatocyte-like cells, induced pluripotent stem cells

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Introduction

The maturation of induced pluripotent stem cells (iPSC) into hepatocytes is one of the technological challenges for producing adult cells with functions comparable to primary tissues. Several protocols are proposed in the literature to derive iPSC (and more generally stem cells, including embryonic) into hepatocytelike cells. It is thus possible to generate liver-like tissue with albumin-secreting cells and positive CYP450 tissue [START_REF] Cai | Directed differentiation of human embryonic stem cells into functional hepatic cells[END_REF][START_REF] Hay | Highly efficient differentiation of hESCs to functional hepatic endoderm requires ActivinA and Wnt3a signaling[END_REF][START_REF] Touboul | Generation of functional hepatocytes from human embryonic stem cells under chemically defined conditions that recapitulate liver development[END_REF][START_REF] Si-Tayeb | Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells[END_REF][START_REF] Kido | CPM is a useful cell surface marker to isolate expandable bi-potential liver progenitor cells derived from human iPS cells[END_REF][START_REF] Koui | An in vitro human liver model by iPSC-derived parenchymal and nonparenchymal cells[END_REF]. However, even if CYP450 activities have been achieved, the CYP450 functionality is still limited when compared to in vivo levels [START_REF] Holmgren | Long-term chronic toxicity testing using human pluripotent stem cell-derived hepatocytes[END_REF][START_REF] Kondo | An efficient method for differentiation of human induced pluripotent stem cells into hepatocyte-like cells retaining drug metabolizing activity[END_REF][START_REF] Negoro | Modeling of drug-mediated CYP3A4 induction by using human iPS cell-derived enterocyte-like cells[END_REF]. In addition, iPSC displayed genomic instability and wide variability in the results depending of the choice of cell lines and differentiation protocols [START_REF] Godoy | Gene networks and transcription factor motifs defining the differentiation of stem cells into hepatocyte-like cells[END_REF]. Furthermore, the choice of certain basic and fundamental culture parameters, such as the initial cell density for differentiation and the sequence of growth factors, are still unclear [START_REF] Hannan | Production of hepatocyte-like cells from human pluripotent stem cells[END_REF][START_REF] Bernier | Profiling of derived-hepatocyte progenitors from induced pluripotent stem cells using nanoCAGE promoter analysis[END_REF].

In this context, several genomic, proteomic and metabolomic profiles were generated to understand the behavior of iPSC and hepatocyte-like cells when compared either to human primary cells or various iPSC lines [START_REF] Godoy | Gene networks and transcription factor motifs defining the differentiation of stem cells into hepatocyte-like cells[END_REF][START_REF] Lin | Bioinformatics analysis to screen key genes implicated in the differentiation of induced pluripotent stem cells to hepatocytes[END_REF][START_REF] Wruck | Human pluripotent stem cell derived HLC transcriptome data enables molecular dissection of hepatogenesis[END_REF][START_REF] Kiamehr | Lipidomic profiling of patient-specific iPSC-derived hepatocytelike cells[END_REF][START_REF] Bhute | Advances in applications of metabolomics in pluripotent stem cell research[END_REF][START_REF] Mallanna | Mapping the cell-surface N-glycoproteome of human hepatocytes reveals markers for selecting a homogeneous population of iPSC-derived hepatocytes[END_REF]. In order to contribute to the knowledge of hepatic maturation, we proposed a first protocol consisting of a step-by-step differentiation process from definitive endoderm, to hepatic specification, followed by a hepatic progenitor step and finally reaching hepatic-like cells (based on Si Tayeb et al., protocol [START_REF] Si-Tayeb | Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells[END_REF]). The step-by-step transcriptomic and gene promoter analysis illustrated the passage from the epithelialmesenchymal transition (EMT) state to the mesenchymal-epithelial transition (MET) state throughout differentiation (Tauran et al., submitted). It also extracted specific networks involving complex sequences on extracellular matrix reorganization, BMP signaling, and EGF signaling with hepatic development markers (Tauran et al., submitted). These findings were consistent with other analyses, showing the importance of FGF2, BMP2, CDK1, HNF4A and EGF [START_REF] Lin | Bioinformatics analysis to screen key genes implicated in the differentiation of induced pluripotent stem cells to hepatocytes[END_REF]. In parallel, using a metabolomic dataset we demonstrated that IPS cells, from their definitive endoderm status to their final hepatocyte-like cells, followed a switch from glycolytic to oxidative phosphorylation respiration. Furthermore, we found a switch in the lipid metabolism, leading to high glycerol levels and low palmitoleic, azelaic, elaidic and lauric acids in hepatocyte-like cells when compared to definitive endoderm cells. We also monitored the kinetic signature of urea and nitrogen metabolism (Jellali et al., submitted).

In order to reduce the cost of hepatocyte-like cell production, it is important to find economically sustainable cell differentiation protocols. In this context, we investigated a second protocol in which we tried to reduce the quantity of growth factor during the differentiation sequence [START_REF] Bernier | Profiling of derived-hepatocyte progenitors from induced pluripotent stem cells using nanoCAGE promoter analysis[END_REF]. Growth factors such as activine A, OSM, HGFand BMP4 were reduced by 40%. As the protocol inspired from Si Tayeb work [START_REF] Si-Tayeb | Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells[END_REF], this protocol led to albumin secreting cells and to immunostaining positive CYP3A4 tissue. Furthermore, both protocols led to activation of HNF1A and HNF1B promoters and to specific modulation of WT1, MTF1, HCFC1, and PGCα1 regulation. However, higher functionality and expression of hepatic genes were found in second protocol (although primary hepatocytes levels were not yet achieved). The comparison also revealed a modulation of targets involved in glucose homeostasis and lipid pathways [START_REF] Bernier | Profiling of derived-hepatocyte progenitors from induced pluripotent stem cells using nanoCAGE promoter analysis[END_REF].

In the present paper, in order to refine and extend those analyses, we propose integrating and comparing the metabolomic and transcriptomic profiles of both protocols. The aim is to confirm the potential of each protocol but also to understand the key events involved in the production process of hepatocyte-like cells.

Material and methods

hiPSC differentiation

TkDN-4M human iPS cells were obtained from the stem cell bank of the Institute of Medical Science of the University of Tokyo [START_REF] Yamashita | Billion-scale production of hepatocyte-like cells from human induced pluripotent stem cells[END_REF]. Cells were cultivated on standard tissue culture polystyrene (TCPS) dishes following two protocols: protocol 1 (P1) previously published by Si Tayeb et al., [START_REF] Si-Tayeb | Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells[END_REF] and protocol 2 (P2) derived from the literature [START_REF] Kido | CPM is a useful cell surface marker to isolate expandable bi-potential liver progenitor cells derived from human iPS cells[END_REF]. The two protocols differ in the frequency of culture medium renewal, which was reduced in protocol 2 to decrease the amount of growth factors needed for the differentiation of hiPS cells into hepatocytes. The protocol 1 and 2 sequences are presented in Fig. 1. The details of the protocol are given in our previous work and in supplementary file 1 [START_REF] Bernier | Profiling of derived-hepatocyte progenitors from induced pluripotent stem cells using nanoCAGE promoter analysis[END_REF].

Metabolomic analysis

Metabolomic analysis was performed with culture medium collected at the end of each step using gas chromatography (Agilent 7890B) coupled with mass spectrometry (Agilent 5977A, GC-MS). The column was an Rxi-5SilMS from Restek (30 m with 10 m Integra-Guard column -ref 13623-127). Sample preparation and metabolite extraction were performed according to our previous work [START_REF] Jellali | Metabolomics-on-a-chip approach to study hepatotoxicity of DDT, permethrin and their mixtures[END_REF][START_REF] Jellali | Effects of DDT and permethrin on rat hepatocytes cultivated in microfluidic biochips: Metabolomics and gene expression study[END_REF]. All steps in the GC-MS analyses were carried out as described in Fiehn et al., [START_REF] Fiehn | Metabolite profiling in Arabidopsis[END_REF][START_REF] Fiehn | Quality control for plant metabolomics: reporting MSI-compliant studies[END_REF]. The metabolomic multivariate data analysis was performed using

XLSTAT.2016 software (Addinsoft) and MetaboAnalyst [START_REF] Xia | MetaboAnalyst 2.0-a comprehensive server for metabolomic data analysis[END_REF][START_REF] Chong | MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis[END_REF]. Supervised Partial Least Squares-Discriminant Analysis (PLS-DA) was carried out in order to discover significant variations between the groups. Discriminating metabolites were identified using the Variable Importance for the Projection (VIP) scores. Univariate statistics was performed with Student's t-test, and a P value of less than 0.01 was considered statistically significant. Metabolites with significant changes in the groups (P value < 0.01 and VIP > 1) were selected as biomarkers. Pathway analysis of potential biomarkers was performed using MetaboAnalyst [START_REF] Xia | MetaboAnalyst 2.0-a comprehensive server for metabolomic data analysis[END_REF][START_REF] Chong | MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis[END_REF].

CAGE analysis

NanoCAGE libraries were generated and sequenced as previously described by Poulain et al. [START_REF] Poulain | NanoCAGE: A Method for the Analysis of Coding and Noncoding 5′-Capped Transcriptomes[END_REF] using pseudo-random primers to reduce the amount of sequencing reads mapping to ribosomal DNA [START_REF] Arnaud | Targeted reduction of highly abundant transcripts using pseudo-random primers[END_REF]. Total RNA extractions, library preparation steps and sequencing were performed as detailed in Lereau-Bernier et al. [START_REF] Bernier | Profiling of derived-hepatocyte progenitors from induced pluripotent stem cells using nanoCAGE promoter analysis[END_REF].

NanoCAGE sequencing data were processed for CAGEscan analysis as detailed in Lereau-Bernier et al. [START_REF] Bernier | Profiling of derived-hepatocyte progenitors from induced pluripotent stem cells using nanoCAGE promoter analysis[END_REF]. Custom R scripts using the CAGEr package were used to produce expression tables that were uploaded on the iDEP server (http://ge-lab.org:3838/idep/) for differential gene expression and pathway analysis [START_REF] Haberle | CAGEr: Precise TSS data retrieval and high-resolution promoterome mining for integrative analyses[END_REF][START_REF] Ge | iDEP : An integrated web application for differential expression and pathway analysis[END_REF]. Datasets were deposited at Zenodo (FASTQ files DOI:

10.5281/zenodo.1014009 and MOIRAI output DOI: 10.5281/zenodo.1017276).

RT-qPCR

RT-qPCR experiments were performed as previously described [START_REF] Bernier | Profiling of derived-hepatocyte progenitors from induced pluripotent stem cells using nanoCAGE promoter analysis[END_REF]. The primer sequences used in this study are shown in Table S1 (supplementary file 1).

ACTB (β-Actin) was used as the reference gene and undifferentiated hiPS cells as the reference sample for the normalization of gene expression data.

Albumin measurements

Albumin production was quantified by ELISA sandwich assays using anti-Human Albumin IgG (Bethyl, Japan, capture antibody) and anti-Human Albumin IgG coupled with peroxidase (Bethyl, Japan, detection antibody) [START_REF] Bernier | Profiling of derived-hepatocyte progenitors from induced pluripotent stem cells using nanoCAGE promoter analysis[END_REF]. After peroxidase revelation by H 2 O 2 /OPD mixture, the plate was read at 490 nm using an iMark Microplate reader (Bio-Rad).

CYP3A4 immunostaining

CYP3A4 immunostaining was performed as described by Danoy et al., [START_REF] Danoy | Optimized protocol for the hepatic differentiation of induced pluripotent stem cells in a fluidic microenvironment[END_REF]. The primary and secondary antibodies used were anti-cytochrome P450 3A4/CYP3A4 antibody (rabbit, ab135813, abcam) and anti-rabbit Alexa Fluor 647 (goat, ab150129, abcam), respectively. Observations were made with an Olympus IX-81 confocal laser-scanning microscope.

Results

Cell differentiation into hepatocyte-like cells

The differentiation into hepatocyte-like cells was confirmed in both protocols.

The morphologies at the end of the differentiation are shown in Fig. 2A. The hepatic phenotype was illustrated by the presence of albumin in the culture at the end of differentiation (Fig. 2D). The immunostaining revealed the presence of a CYP3A4

positive subpopulation in both protocols (Fig. 2B). Interestingly, we found higher numbers of cells positive to CYP3A4 in protocol 2 than in protocol 1 (Fig. 2B).

To determine whether iPSC-derived hepatocytes in both protocols displayed the mature characteristics of a hepatic lineage, we measured the gene expression of OCT3/4 (pluripotency marker) and various hepatic markers (ALB, AFP, FOXA2, CYP3A4 and HNF4A) by means of RTqPCR analysis. As shown in Fig. 2C, mRNA levels measured for the ALB, AFP, CYP3A4, FOXA2 and HNF4A genes in both protocols were significantly higher in the iPSC-derived hepatocytes than in undifferentiated iPSC. Furthermore, these genes were more highly expressed in protocol 2 (when compared with protocol 1). The expression of OCT3/4 was clearly downregulated at the end of differentiation in protocols 1 and 2 (Fig. 2C). This overall set of data confirmed the success of the differentiation into a hepatocyte-like cell lineage.

Metabolomics analysis

Multivariate metabolomics contribute to extracting common metabolite signatures at each differentiation step

The metabolomic treatment led to the identification of 105 metabolites in the culture medium (supplementary file 2). As the culture media were not the same in the different steps, especially in step 4, we performed a normalization for each compound (using the level of each compound in the basal culture media, the basal media being the control media without cell exposure). The PLS-DA analysis applied to the overall dataset led to several separate steps in different clusters, as shown in Fig. 3A. We found a clear separation between the steps 1 in each protocol, indicating distinct metabolic profiles. In addition, both steps 4 were clustered in the same area of the PLDS-DA, but still separately. These results were confirmed by PLS-DA performed with samples from step 1 and step 4 only (Fig. 3B). However, the clusters of steps 2 and 3, for both protocols, were almost superimposed.

The heatmap of the top 25 metabolites in this analysis is provided in Fig. 3C.

In step 1, we found common signatures in both protocols, including high levels of glyceric, palmitoleic and aspartic acids, spermidine, and O-phosphocolamine when compared to basal culture medium. In parallel, the specificity of each protocol was illustrated in protocol 1 by high levels of 3 phosphoglyceric and malic acids, and by high levels of glucose and galacturonic acid in protocol 2.

The heatmap also contributed to extracting common patterns characterizing steps 2 to 4 in protocols 1 and 2.

Step 2 was characterized by high levels of ketoisocaproic, citric and gluconic acids, histidine and O-phosphocolamine.

Concerning step 3, we observed high levels of histidine, ketoisocaproic acid, glucose and galacturonic acid. Finally, both steps 4 were characterized by high levels of uracil, urea, glycerol, putrescine, glutamine, phosphoric, oxalic, pyroglutamic and threonic acids.

This general analysis demonstrated that both protocols led globally to the similar metabolic profiles after the end of step 2. In order to characterize the difference in the kinetics of each protocol more specifically, and to refine the difference in the differentiation process more particularly, we then ran a step-by-step differential analysis.

Differential analysis of step 1

PLS-DA analysis contributed to clearly distinguishing the two protocols in step 1 of differentiation, as shown in Fig. 4A. More particularly, the differential analysis contributed to extracting 56 metabolites differentially expressed between the two protocols in step 1, with a P value of less than 0.01 (Fig. 4B and supplementary file 3). The heatmap of the 25 most significant metabolites at the end of step 1 is shown in Fig. 4C. The levels of carbohydrates such as glucose, fructose and galacturonic acid appeared higher in the second protocol. The first protocol exhibited high levels of Krebs cycle intermediates (fumaric, citric, succinic and malic acids) and glycolysisrelated compounds such as 3 phosphoglycreic acid, lactic acid and gluconic acid.

Extended to the top 50 metabolites, we found higher levels of hexanoic, palmitoleic, caprylic and pyroglutamic acids in protocol 2 (supplementary file 3). Table S2 (supplementary file 1) also summarizes the fold change in 56 significant metabolites, in comparison with the initial basal media (for both protocols).

The metabolite set enrichment using MetabolAnalyst with those 56 compounds (P value < 0.01) revealed that the Warburg effect, urea cycle, gluconeogenesis, glutamate metabolism and ammonia recycling were the top 5 modulated pathways. Of the top 10 pathways, we also found glycine-serine metabolism and the glycose alanine cycle (Fig. S1, supplementary file 1).

Differential analysis of steps 2 and 3

PLS-DA treatments performed with step 2 and step 3 samples contributed to distinguishing protocol 1 from protocol 2 for each step (Fig. 5A andD). However, only a few metabolites were differentially expressed in step 2 when compared to the step 1 situation. In fact, only 8 compounds with a P value of less than 0.01 were extracted (Fig. 5B andC). Nevertheless, we found 23 metabolites modulated between both protocols, with a P value of less than 0.05 (volcano plot in Fig. 5B and supplementary file 3). The variations in these metabolites (fold change) in comparison with basal culture media are presented in Table S2 (supplementary file 1). The metabolite enrichment pathway in MetaboAnalyst (using 23 metabolites with a P value < 0.05) highlighted the glycerol phosphate shuttle, beta oxidation of fatty acids, vitamin B6 metabolism and glutathione metabolism (Fig. S2, supplementary file 1).

Similarly, in step 3, we found only five metabolites differentially expressed between both protocols, with a P value of less than 0.01 (13 metabolites with a P value of less than 0.05; Fig. 5E andF). Using these 13 metabolites for pathway analysis with MetaboAnalyst software, we found that the pathways modulated significantly were related to propanoate metabolism, glycerol phosphate shuttle, beta oxidation of fatty acids and linoleic acid metabolism (Fig. S3, supplementary file 1).

Differential analysis of step 4

The two protocols were distinguished in step 4 as two distinct clusters were formed to group each protocol (PLS-DA score plot in Fig. 5G). However, step 4 was still characterized by a low number of metabolites significantly modulated between protocols 1 and 2 (12 metabolites with a P value of less than 0.01; Fig. 5H and supplementary file 3). It included fatty acids and lipids such as caprylic acid, palmitoleic acid, and carbohydrates such as fructose, glucose and galacturonic acid.

All these metabolites were higher in protocol 2 (Fig. 5I). We also found higher levels of pyroglutamic acid in protocol 2, whereas urea was higher in protocol 1. The top 20 metabolites (with a P value of less than 0.05) are presented in the heatmap in Fig. S4 (supplementary file 1). Of them, we monitored higher levels of azelaic acid, Ophosphocolamine and cholesterol in protocol 2, and higher levels of uracil and aspartic acid in the first protocol. The metabolite set enrichment with these 20 top molecules revealed the modulation of glutathione metabolism, the transfer of acetyl groups into mitochondria and nitrogen metabolism (urea cycle, ammonia recycling, arginine-proline metabolism), as shown in Fig. S5 (supplementary file 1).

Transcriptomic characterization

In order to complete the metabolomic profiling, we integrated genomics analysis of the cells. We focused particularly on steps 1 and 4 of differentiation as a starting and end point, respectively. For step 1, a selection of target genes was analyzed by RTqPCR at the end of the step in both protocols. As shown in Fig. 6A, RTqPCR confirmed higher levels of glycolytic genes in protocol 1 at the end of step 1

for PFKM, PGAM, ENO1, G6PD and LDHA genes. The levels of IDH2 (TCA) were also higher in protocol 1. ACLY (lipogenesis) and HIF1A (hypoxia) mRNA levels remained similar in both protocols.

Concerning step 4, we used transcriptomics data obtained from nanoCAGE sequencing of the cells at the end of the differentiation protocol (step 4). For that purpose, we firstly post processed the transcriptomic data with a false discovery rate (FDR) of 0.1 and a fold change of 1.1 using iDEP software (version 8.1). This led to the extraction of 270 genes differentially modulated between both protocols (Fig. 6B and Fig. S6 in supplementary file 1). The full list of differentially expressed genes is provided in supplementary file 4.

The pathway analysis, run with an FDR of 0.2, using the KEGG database, extracted the glycolysis/gluconeogenesis, the metabolism of various carbohydrates (fructose, mannose, galactose), ferroptosis (iron metabolism), HIF signaling and arginine-proline metabolism among the top modulated pathways (Fig. 6C). The full figures and modulated genes are given in supplementary file 5. The GO molecular function also illustrated phospholipid-and steroid-related pathways, and cellular remodeling and modulations (via integrin binding, cadherin binding and cell adhesion binding activities; Fig. S7 in supplementary file 1). A selective list of lipid genes (APOA2, HMGCR, HMGCS1, ACLY, SCD, SQLE) and carbohydrate genes (ENO1, PGK1, GAPDH, GPI, HK2, LDHA, PKM, ALDOA) are presented in Table 1. All these genes were downregulated in protocol 2 when compared with protocol 1. We also included the mRNA ratio of HIF obtained by RTqPCR, which was found to be upregulated by 4.5 times in protocol 2.

Using the STRING protein database clustering tool, with the Kmeans method applied to the 270 genes, we extracted 8 typical interconnected networks with 106 genes (Fig. S8 in supplementary file 1). Those networks were related to ECM and tissue remodeling (via genes such as LUM, COL1A1, COL4A5, COL14A1, COL3A1, ACTB, CTNNA3 and VIL1), the glycolytic pathway (via genes such as ENO1, PGK1, GAPDH, GPI, HK2, LDHA, PKM and ALDOA), lipid-and steroid-related metabolisms (via genes such as APOA2, HMGCR, HMGCS1, ACLY, SCD and SQLE), some transporters (SLC1A3, SLC16A1, SLC2A3 and VDAC2), and ribosomal, RNA and DNA processing (RPL3, RPS3, EIF5 and EEF2). Furthermore, specific liver progenitor markers were extracted (ALB, NR3C2, TF, CK19 and RBP4). In those networks, the important nodes appeared to be the genes ACLY, APOA2, HSP90AA1, EEF2, RPL3, RPS3, GADPH and TPI1 linking the subnetworks. We also found the presence of chaperone protein-related genes, such as CCT2, and calciumdependent genes (CALU, CADM1 and RYR2).

Metabolomic and transcriptomic integration of step 4 data

The 270 genes and the top 20 metabolites from step 4 were integrated into metaboanalyst software. The list of enriched pathways and the corresponding genes and metabolites are given in supplementary files 6 and 7. The integration principally identified glycolysis and gluconeogenesis as the main enriched pathway (9 hits). Of the others, we also found the metabolism of nitrogen (5 hits) and gluthatione metabolism (5 hits). The network explorer option connected 7 metabolites (glycine, glutamic acid, aspartic acid, Palmitoleic acid, citric acid, 4 hydroxybenzoic acid and N-acethyl-L aspartic acid) and 10 genes (ANPEP, EEF2, CACNA2D1, GRID2, MITF, PAICS, FDPS, SND1, ACLY, FST). The network map is provided in Fig. S9 in supplementary file 1.

Discussion

In the present work, we investigated metabolomic and transcriptomic signatures of hiPS cells during their differentiation using two culture protocols. The first protocol is the conventional protocol adapted from Si-Tayeb et al. [START_REF] Si-Tayeb | Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells[END_REF]. In protocol 2, the quantity of growth factors used was reduced by 40% (when compared to the first protocol). Our aim was to confirm the potential of each protocol to generate hepatocyte-like cells, and to obtain a better understanding of the key events involved in hiPSC differentiation. The hepatic phenotype was confirmed at the end of differentiation in both protocols by albumin and urea production, and positive immunostaining for CYP3A4. We also demonstrated that hepatocyte-like cells derived through these two protocols express markers of hepatocytes such as ALB, AFP, CYP3A4, FOXA2 and HNF4A. Further studies would be required to confirm those results on other iPSC sources.

During protocol 1, the culture medium sequence was changed every day. We expected an adequate supply of nutrients to the tissue, such as glucose or fatty acids as potential sources of energy. In non-differentiated iPSC, the respiration patterns were reported as leading to glycolytic respiration (in contrast to oxidative phosphorylation respiration in mature and differentiated tissue) [START_REF] Shyh-Chang | Stem cell metabolism in tissue development and aging[END_REF]. When comparing the two protocols, metabolomic profiling revealed significant and very complex modulation of the cell signature at the end of step 1. More particularly, the two protocols differed in terms of the high levels of lipids such as palmitoleic, caprylic and hexanoic acids in protocol 2, revealing lower consumption of fatty acids. However, the ACLY gene (lipogenesis process) was not significantly modulated between the two protocols. Furthermore, glucose levels were higher in protocol 2 and lactate levels higher in protocol 1 at the end of step 1. These tendencies illustrated intense energy demand in protocol 1 and probable higher fatty acid beta oxidation and glycolysis. This was consistent with the activation of the TCA cycle in protocol 1 as demonstrated by high levels of typical intermediates such as succinic, malic, fumaric and citric acids. At the mRNA levels, these results were accompanied by higher mRNA levels of glycolytic and TCA genes in protocol 1. In protocol 2, the medium was not changed every day leading to the creation of a potential glucose shortage.

Consistently, it has been reported in the literature that starvation results in lower levels of glycolytic genes [START_REF] Pérez | Effect of starvation on gene expression of regulatory enzymes of glycolysis/gluconeogenesis in genetically obese (fa/fa) Zucker rats[END_REF]. In addition, in the present study, this downregulation was independent of the HIF mRNA levels in step 1, which remained closed to each other for both protocols (HIF being involved in glycolysis and lipid regulation) [START_REF] Goda | Hypoxia-inducible factors and their roles in energy metabolism[END_REF][START_REF] Bensaad | Fatty acid uptake and lipid storage induced by HIF-1α contribute to cell growth and survival after hypoxia-reoxygenation[END_REF].

Lipolysis is reported to be one source of carbohydrates in a starvation state [START_REF] Berg | Section 30.3 Food intake and starvation induce metabolic changes[END_REF]. As a result, we expected lower lipid levels in protocol 2, which was not the case in step 1. Furthermore, high levels of fructose are said to induce lipogenesis and only limited amounts of lipids can be used to generate glucose [START_REF] Softic | Role of dietary fructose and hepatic de novo lipogenesis in fatty liver disease[END_REF][START_REF] Abd El-Haleim | Effects of combined PPAR-γ and PPAR-α agonist therapy on fructose induced NASH in rats: Modulation of gene expression[END_REF],. These results may reflect the behavior observed in protocol 2, in which high lipid levels were correlated with high levels of fructose. A second alternative source of glucose during starvation is amino acids (amino acids are usually extracted from protein degradation in muscle). As we observed higher levels of amino acids in protocol 2, including isoleucine, cystine, serine, lysine, tyrosine and tryptophan, additional analysis is required if we are to identify whether or not protocol 2 led to reduced amino acid consumption or to amino acid production as a result of protein degradation for generating glucose.

After step 1, the metabolomic profiles were very similar in steps 2 and 3 for both protocols. Nevertheless, small differences appeared when considering P values of less than 0.05. In step 2, it was mainly fatty acid, glycerol and lipid metabolisms that were highlighted due to lower levels of heptadecanoic acid and moderately higher levels of glycerol-1 phosphate, cholesterol, phosphoric, capric and caprylic acids in protocol 2 (fold change of 0.62, 1.13, 1.16, 1.06, 1.06 and 1.16 respectively).

This tendency was also observed in step 3, in which we observed higher lipid levels (linoleic, lauric and elaidic acids) in the culture medium of protocol 2. In parallel, for both steps, we detected high levels of kynurenine and low levels of tryptophan.

Interestingly, L-kynurenine is said to decrease cell membrane fluidity (in liver cells) and to reduce linoleic acid incorporation into phospholipids [START_REF] Rudzite | The influence of kynurenine and its metabolites on lipid metabolism[END_REF]. It led in parallel to an increase in cholesterol levels, which appeared consistent with our findings [START_REF] Rudzite | The influence of kynurenine and its metabolites on lipid metabolism[END_REF]. A slight difference in vitamin B6 metabolism was finally extracted in step 2 (higher levels of pyridoxine in protocol 2). Vitamin B6 deficiency is linked to an altered fatty acid profile and impaired fatty acid synthesis, which may also be the illustration of overall complex crosstalk in the fatty acid metabolism in steps 2 and 3 [START_REF] Zhao | Vitamin B-6 restriction impairs fatty acid synthesis in cultured human hepatoma (HepG2) cells[END_REF].

A difference in both protocols was detected concerning lipid and fatty acid levels in step 4. The high levels of palmitoleic, caprylic and azelaic acids in protocol 2 revealed a difference in the lipolysis/lipogenesis processes (and consistently with their kinetics from steps 1 to 3) when compared to protocol 1. These high levels of lipids were correlated with high levels of fructose and glucose in protocol 2 (as in step 1). In addition, the transcriptomic analysis confirmed modulation at the gene level of lipid and steroid metabolisms (in protocol 2, downregulation of APOA2, HMGCR, HMGCS1, ACLY, SCD, SQLE), glycolysis and carbohydrate metabolism (in protocol 2, downregulation of ENO1, PGK1, GAPDH, GPI, HK2, LDHA, PKM, ALDOA, as in step 1) and modulation of HIF levels (upregulation of HIF by RTqPCR in protocol 2).

A potential underlying mechanism and transcription factor could thus be the hypoxia and HIF-related signaling, given that several upstream and downstream targets were modulated in our study. mRNA levels of HIF1A in step 4 confirmed significant upregulation of HIF1A in protocol 2. Under hypoxia, HIF1A induced glycolysis and also increased glucose uptake [START_REF] Goda | Hypoxia-inducible factors and their roles in energy metabolism[END_REF]. In parallel, it is said to induce fatty acid uptake and lipid storage, but HIF-1 also inhibits de novo fatty acid synthesis in the liver [START_REF] Goda | Hypoxia-inducible factors and their roles in energy metabolism[END_REF][START_REF] Bensaad | Fatty acid uptake and lipid storage induced by HIF-1α contribute to cell growth and survival after hypoxia-reoxygenation[END_REF]. HIF, as a pivotal lipid glucose compound in energy metabolism, is also reported, mainly by triggering a switch from mitochondrial oxidative phosphorylation to anaerobic glycolysis in hypoxic conditions [START_REF] Goda | Hypoxia-inducible factors and their roles in energy metabolism[END_REF]. In our study, we found higher levels of glucose and lipids in the culture medium of protocol 2. In addition, the glycolytic genes were not upregulated. As a result, it seems that we did not face a HIF signaling governing process in step 4 of protocol 2. The process in step 4 appeared similar to step 1, in which fructose-and starvation-like dependent control seemed to govern the phenomena. However, as the metabolomic signature was closer in step 4 between both protocols (8 metabolites with a P value of 0.01 compared to 65 in step 1), it also appeared that the predominance of this phenomenon could be attenuated when compared to the situation in step 1. Although we can postulate that liver-like cells start to play their role in metabolism homeostasis, additional analysis is needed to clarify the status of the situation in protocol 2.

Finally, step 4 was characterized by a common signature, illustrating liver differentiation, as shown by the level of urea in both protocols when compared to step 1. Although urea and glutamine were produced in both protocols in step 4, the urea, glutamic acid and aspartic acid levels were higher in protocol 1. At the transcriptomic level, it was related to moderate upregulation, in protocol 1, of typical urea cycle genes such as ARG1, ARG2, GOT1, GOT2 and OAT.

We also observed high levels of pyroglutamic acid for both protocols, illustrating greater oxidative phosphorylation in step 4 when compared to step 1. This process is consistent with other iPSC differentiation reports presenting a switch from ATP production via glycolysis in the pluripotent stem stage, to mitochondrial oxidative phosphorylation (OXPHOS) respiration, which leads to an increase in reactive oxygen species (ROS) levels (ROS are produced by OXPHOS) [START_REF] Shyh-Chang | Stem cell metabolism in tissue development and aging[END_REF][START_REF] Dahan | Metabolism in pluripotency: Both driver and passenger?[END_REF].

Pyroglutamic acid production illustrates the activation of glutathione metabolism in order to detoxify the ROS produced by OXPHOS. Glutathione metabolism activation was also illustrated by the consumption of the main glutathione precursors in step 4

of both protocols (glycine, cysteine and glutamic acid; fold change between 0.4 and 0.9 when compared to basal culture media) [START_REF] Zhao | Vitamin B-6 restriction impairs fatty acid synthesis in cultured human hepatoma (HepG2) cells[END_REF].

The results presented in this work demonstrate that the reduction of growth factors by 40% (protocol 2) efficiently generate hepatocyte-like cells similar to those generated by the classical protocol (protocol 1). Integration of metabolomic and transcriptomic data highlighted several key metabolic pathways during differentiation process and contributed to identify the effect of frequency of the culture medium renewal and growth factors reduction on iPSC metabolism. However, additional analysis such as the repetition of those protocols of differentiation on other iPSC sources, evaluation of the protocol stability and their key events, cell sorting to quantify the population heterogeneity, proteomic characterisation, and benchmark with both fetal and primary hepatocyte cultures, are required (i) to clarify the real benefit of our protocols (ii) to understand the metabolic effects observed. In addition, precise hepatocyte quantification would be required to normalise the hepatocytes productions/consumptions regarding the overall tissue. Nevertheless, we believe that those results provide knowledge on the behavior of iPSC during hepatic differentiation.

Conclusion

We compared the metabolomic and transcriptomic signatures of human induced pluripotent stem cells during their differentiation into hepatocyte-like cells.

Two differentiation protocols were tested. By reducing the frequency of culture medium change in one protocol, we managed to produce hepatocyte-like cells producing albumin and urea. The metabolomic signature demonstrated a major difference at the start of differentiation, leading to 65 differentially-expressed metabolites. The difference became weaker once the differentiation reached hepatic specification. At the end of both protocols, only 8 metabolites remained differentiallyexpressed (including fructose, palmitoleic and caprylic acid). During the process as a whole, the reduction in culture medium change led to a metabolic signature with high levels of fructose and lipids in the culture medium. This was accompanied by downregulation of glycolytic genes. The present study clearly reveals the potential of our new protocol to generate hepatocyte like-cells from hiPSC, with a reduced cost.

Our analysis could also contribute to a better understanding of differentiation and suggest novel targets to improve iPSC maturation into functional hepatocytes.

Acknowledgments

The project received a grant from JSPS Kakenhi 16F16715, the JSPS-CNRS post-doctoral fellowship program of Myriam Lerreau Bernier, P16715, the UTC foundation in support of Dr Jellali, and iLite ANR-16-RHUS-0005. Bertrand-David Segard was supported by the CNRS, Stephane Poulain by the JSPS Grant-in-aid for Scientific Research (S) 16H06328 and Charles Plessy by a grant from RIKEN CLST (DGT) from the MEXT, Japan.

Conflict of interest

The authors declare no conflict of interests


Béatrice ; Roche
email: beatrice.roche@unibas.ch

L A Gaëtan

Mislin

Isabelle J Schalk

Identification of the fatty acid coenzyme-A ligase FadD1 as an interacting partner of FptX in the Pseudomonas aeruginosa pyochelin pathway

Keywords: Pseudomonas aeruginosa, pyochelin siderophore, iron uptake, coenzyme-A ligase, membrane complex Pseudomonas aeruginosa, pyochelin siderophore, iron uptake, coenzyme-A ligase, membrane complex

Pseudomonas aeruginosa is one of the most important nosocomial bacteria emerging as a highly multidrug-resistant pathogen. P. aeruginosa produces two siderophores including pyochelin to fulfill its need for iron during infections. We know that both outer and inner membrane proteins FptA and FptX are involved in the ferri-pyochelin uptake, but this process requires increasing molecular and biochemical knowledge. Here, using bacterial two-hybrid and copurification assays we identified the fatty acid coenzyme-A ligase FadD1 as a novel interacting partner of the inner membrane transporter FptX, and found that FadD1 may play a role in pyochelin production. We managed to purify the FadD1-FptX inner membrane complex and obtained low-resolution 3D models, opening the way for future high-resolution structures.

Introduction

Pseudomonas aeruginosa is a major human pathogen naturally resistant to many antibiotics due to the low permeability of its envelope. The situation is particularly critical as P. aeruginosa belongs to the World Health Organization list of antibiotic-resistant priority pathogen [1]. The success of bacteria to colonize the host relies mostly on their ability to obtain adequate supplies of the nutrients that are essential for growth and virulence. To circumvent the low bioavailability of iron in the host during infections, P. aeruginosa produces the two siderophores pyoverdine (PVD) and pyochelin (PCH) [2][3][4]. Siderophores are small iron chelating compounds produced by bacteria under iron limitation conditions [5]. Previous studies have shown an upregulation of the PCH pathway in clinical isolates from cystic fibrosis patients [6][START_REF] Rossi | High-resolution in situ transcriptomics of Pseudomonas aeruginosa unveils genotype independent patho-phenotypes in cystic fibrosis lungs[END_REF] and reported a potential role of PCH in the inflammatory response [8].

PCH is synthesized by non-ribosomal peptide synthetases in the bacterial cytoplasm and then secreted into the extracellular medium by an unknown mechanism [START_REF] Reimmann | Dihydroaeruginoic acid synthetase and pyochelin synthetase, products of the pchEF genes, are induced by extracellular pyochelin in Pseudomonas aeruginosa[END_REF]. Once in the bacterial environment, PCH chelates ferric iron leading to the formation of ferri-PCH complexes. Only two proteins involved in the ferri-PCH uptake have been described so far: the specific TonB-dependent outer membrane transporter FptA [START_REF] Ankenbauer | Cloning of the outer membrane high-affinity Fe(III)-pyochelin receptor of Pseudomonas aeruginosa[END_REF][START_REF] Cobessi | Crystal structure at high resolution of ferric-pyochelin and its membrane receptor FptA from Pseudomonas aeruginosa[END_REF][START_REF] Mislin | Binding properties of pyochelin and structurally related molecules to FptA of Pseudomonas aeruginosa[END_REF], and the inner membrane protein FptX [13-15]. Much attention has been paid to structural studies of FptA, and X-ray structure of FptA bound to ferri-PCH provided valuable information for the design of PCH- antibiotic conjugates [START_REF] Noël | Synthesis and biological properties of conjugates between fluoroquinolones and a N3''-functionalized pyochelin[END_REF][START_REF] Paulen | Synthesis of conjugates between oxazolidinone antibiotics and a pyochelin analogue[END_REF]. In the context of antibiotic resistance, conjugation of antibiotics with siderophore is a promising drug delivery strategy exploiting iron uptake systems as gates to carry out antibiotics into the bacteria [START_REF] Ghosh | Targeted Antibiotic Delivery: Selective Siderophore Conjugation with Daptomycin Confers Potent Activity against Multidrug Resistant Acinetobacter baumannii Both in Vitro and in Vivo[END_REF][START_REF] Liu | A Synthetic Dual Drug Sideromycin Induces Gram-Negative Bacteria To Commit Suicide with a Gram-Positive Antibiotic[END_REF]. Such Trojan horse strategy can provide increased penetration of drugs previously unable to cross the cell wall of bacteria [4]. But we currently lack biochemical/structural data on the inner membrane transporter FptX predicted to have 12 transmembrane segments.

Here, we explored potential new actors involved in the ferri-PCH uptake pathway by using a genome-wide screening approach. We identified the fatty acid coenzyme-A ligase FadD1 as a new and previously undescribed interacting partner of FptX, forming an inner membrane complex. Deletion of fadD1 led to a decrease in PCH production, suggesting a role of FadD1 in biosynthesis and/or secretion of this siderophore.

Materials and methods

Chemicals and growth media.

X-Gal (5-bromo-4-chloro-3-indoyl--D-galactopyranoside) and IPTG (Isopropyl--D thiogalactoside) were purchased from Euromedex. ONPG (2-Nitrophenyl--D galactopyranoside) and sodium oleate were obtained from Sigma-Aldrich. Detergent n-Dodecyl--D-maltopyranoside (DDM) was purchased from Anatrace. LB (Lennox) and LB agar medium were both purchased from Difco and were used as nutriment- rich medium in all experiments. Bacteria were routinely grown at 30°C in LB broth (Difco) or in iron- restricted medium (CAA) as previously described [15]. Media were supplemented as necessary with ampicillin (Ap; 100 -1 ), kanamycin (Kan; 50 -1 ), gentamicin (Gm; 30 -1), chloramphenicol (Cm; 50 -1 ), IPTG (0.5 mM). The strains used in this study are listed in Table S1.

Plasmids construction.

All DNA amplifications for cloning were performed with Phusion High-Fidelity DNA polymerase (ThermoFisher Scientific) using genomic DNA of PAO1 strain as template. Restriction enzymes and T4 DNA ligase were purchased from ThermoFisher Scientific. All enzymes were used in accordance with the manufacturer's instructions. Oligonucleotides are listed in Table S2. Escherichia coli strain Top10 was used as the host strain for all plasmids. Absence of mutations was checked by DNA sequencing (GATC).

Expression plasmids. Plasmid p33-fptX(His 6 ) was constructed by PCR amplification of the coding region of fptX by using the primer pairs 970/969. The PCR product was then digested with EcoRI and HindIII enzymes and ligated into the EcoRI/HindIII linearized pBAD33 vector. Plasmid p24-fadD1(StrepII) was constructed by PCR amplification of the coding region of fadD1 by using the primer pairs 1157/1158. The PCR product was then digested with NcoI and HindIII enzymes and ligated into the NcoI/HindIII linearized pBAD24 vector.

Two-hybrid plasmids. DNA fragments encoding proteins of interest were fused to the two fragments T25 and T18 of Bordetella pertussis adenylate cyclase carried on the pKT25, pKNT25, pUT18C and pUT18 vectors. The DNA regions encoding fptX and fadD1 were amplified by PCR by using primer pairs 951/952 and 1037/1038, respectively. PCR products were then digested with XbaI and KpnI enzymes and ligated into the XbaI/KpnI linearized pKT25, pKNT25, pUT18C and pUT18 vectors.

Bacterial two-hybrid screen.

Four independent two-hybrid libraries (pUT18CPAO1Lib, pUT18PAO1Lib, pUT18+1PAO1Lib and pUT18+2PAO1Lib) of PAO1 genome were tested independently. The pKNT25-fptX vector was used as the bait and the two-hybrid screen was performed as described in Houot et al., 2012 [20].

Bacterial two-hybrid assay.

The adenylate cyclase-based bacterial two-hybrid technique was used as previously published [START_REF] Battesti | The bacterial two-hybrid system based on adenylate cyclase reconstitution in Escherichia coli[END_REF].

Western blot analysis.

Proteins were applied to SDS-PAGE acrylamide gels and transferred onto nitrocellulose membranes.

FptX(His 6 ) and FadD1(StrepII) proteins were immunodetected with the anti-His (1:3,000 ; GeneTex) and the StrepMAB (1:1,000 ; IBA) antibodies, respectively. Immunoblots were developed by using horseradish peroxidase-conjugated goat anti-rabbit and anti-mouse antibodies (1:10,000 ; GE Healthcare), followed by chemiluminescence detection.

Expression and purification of FptX.

Top10 E. coli cells were transformed with the p33-fptX(His 6 ) vector. Cells were grown at 37°C with shaking until they reached an OD 600 0. Expression and purification of the FadD1-FptX complex by two-step affinity chromatography.

Top10 E. coli cells were transformed with the p33-fptX(His 6 ) and p24-fadD1(StrepII) vectors. Cell growth, gene induction and membrane preparation were done as described for FptX. The supernatant was loaded onto a 1-mL StrepTrap HP column (GE Healthcare) equilibrated with buffer A (50 mM Tris-HCl pH 8, 50 mM NaCl, 0.1 % DDM). The FadD1-FptX complex was eluted in buffer A supplemented with 2.5 mM D-Desthiobiotin (Sigma Aldrich) into a 1-mL HisTrap HP column (GE Healthcare). The column was washed in buffer A and the FadD1-FptX complex was eluted in buffer A supplemented with 250 mM imidazole. Central fraction of the peak was then loaded onto a Superdex 200 column 10/300 GL (GE Healthcare) equilibrated with 50 mM Tris-HCl pH 8, 50 mM NaCl, 0.025 % DDM. The FadD1-FptX complex was eluted as a single peak, and the central fraction was immediately used for EM sample preparation.

EM processing of FptX, FadD1 and the FadD1-FptX complex.

Determination of FadD1-FptX complex, FptX and FadD1 proteins structure was made by negative-stain EM. 5 µL of FadD1-FptX complex (28 -1 ), FptX (23 -1 ) and FadD1 (6.25 -1 ) sample was fixed with 0.6 glutaraldehyde 1%. The sample was then spotted to 300 meshs Cu grids covered with a carbon film (Euromedex CF300-CU-050). After 60s of absorption, each sample was stained with 2% uranyl acetate. For the FadD1-FptX complex, the sample was washed with one drop of 50 mM Tris pH 8, 50 mM NaCl before staining with 2% uranyl acetate. Images were recorded automatically using the SerialEM software on a FEI Tecnai F20 microscope operating at a voltage of 200 kV and a defocus range of 500 nm, using a Gatan US1000 detector at a nominal magnification of 50,000X, yielding a pixel size of 2.12. A dose rate of 20 electrons per square angstrom per second, and an exposure time of 10s were used. For the FadD1-FptX complex, a total of 58,034 particles were selected from 3,000 independent images and extracted within boxes of 200 pixels using Relion2. For FptX, a total of 38,746 particles were selected from 1,500 independent images and extracted within boxes of 192 pixels using Relion2. For FadD1, a total of 102,978 particles were selected from 1,500 independent images and extracted within boxes of 120 pixels using Relion2. The defocus value was estimated, and the contrast transfer function was corrected using CTF estimation in Relion2. We used two rounds of reference-free 2D class averaging to clean up the selected data set. High-populated classes displaying high-resolution features were conserved during the procedure with a final data set of 30,355 particles for the FadD1-FptX complex, 33,001 particles for FptX and 61,553 particles for FadD1. An initial 3D model was generated in EMAN2. Relion2 auto-refine procedure was used to obtain a final reconstruction at 33-Å, 26-Å and 17-Å resolution for FadD1-FptX, FptX and FadD1, respectively, after masking and without symmetry constraints. Resolutions are based on the "gold standard" Fourier shell correlation (FSC) (Fig. S4). USCF Chimera was used to display three-dimensional reconstructions.

Iron uptake assays and cell fractionation.

Cells were cultured overnight in LB medium at 30°C, and afterwards at 30°C overnight in CAA medium.

Then, they were diluted in fresh CAA medium and grown at 30°C overnight. Bacteria were washed with 50 mM Tris-HCl at pH 8 and diluted to an OD 600nm of 1. The PCH-55 Fe complex was prepared as previously described [START_REF] Gasser | Catechol siderophores repress the pyochelin pathway and activate the enterobactin pathway in Pseudomonas aeruginosa: an opportunity for siderophore-antibiotic conjugates development[END_REF]. Cells were incubated 30 min with 200 nM PCH-55 Fe at 30°C. After incubation, cells were centrifuged for 8 min at 6, 700 g to obtain the supernatant as the extracellular medium, and the cell pellet which was resuspend in Tris-sucrose EDTA (Tris-HCl 0.2 M pH 8, EDTA 1 mM, sucrose 20 %).

Spheroplasts were obtained by adding 200 g.mL -1 lysozyme (Euromedex) to the suspension and incubated at 4°C for 1 h. The suspension was centrifuged for 8 min at 6,700 g at 4°C to obtain the spheroplast pellet and the periplasmic fraction (supernatant). The supernatant was ultracentrifuged (120, 000 g, 40 min, 4°C) to clarify the periplasmic fraction. Spheroplast pellet was washed with Tris-HCl 0.2 M pH 8, sucrose 20 %, and resuspend in cold water by vortexing. The suspension was then incubated with benzonase for 1 h at 37°C. The cytoplasmic fraction was isolated by ultracentrifugation (120,000 g, 40 min, 4°C). Pellet was washed twice with cold water and resuspended in Tris-HCl 0.2 M pH 8, sucrose 20 % to obtain the bacterial membranes.

Deletion mutant construction.

For the deletion of both fadD1 and fadD2 genes, PCR was used to generate a 500 bp DNA fragment upstream of fadD2 and a 500 bp DNA fragment downstream of fadD1, by using the primer pairs 1280/1281 and 1282/1151, respectively. Each PCR product was linked by overlapping PCR and products were digested with HindIII and EcoRI and cloned into the suicide vector pEXG2, yielding fadD1 fadD2.

Deletion in the chromosomal genome of P. aeruginosa was generated by transferring the suicide vector from E. coli SM10 strains into recipient strains allowing the plasmid to integrate into the chromosome, with selection for gentamicin resistance. A second crossing-over event excising the vector was selected using NaCl-free LB plates supplemented with 5 % sucrose. Deletions were confirmed by sequencing using external primers.

PCH production.

Cells were cultured overnight in LB medium at 37°C, and afterwards at 30°C overnight in iron-deficient CAA medium. They were then diluted to 0.1 OD 600nm units in fresh CAA medium and incubated at 30°C for 16 h. The extracellular medium was separated from the cells by centrifugation at 7,700 g for 15 min. The pH of the supernatant was acidified by adding 1 M citric acid and PCH was extracted with dichloromethane.

Pyochelin concentration was determined by measuring the absorbance at 320 nm ( = 4,300 L.mol -1.cm -1 ).

Results are expressed as a function of PCH produced ( M) to bacterial growth (OD 600nm ).

Significance tests

Student's t test was used for two-group comparisons using unpaired two-tailed t test. Analyses were performed using GraphPad Prism 8.

Results

Identification of FptX interacting partners. FptX is proposed as the inner membrane protein involved in ferri-PCH uptake in P. aeruginosa [START_REF] Cuív | Identification of rhtX and fptX, novel genes encoding proteins that show homology and function in the utilization of the siderophores rhizobactin 1021 by Sinorhizobium meliloti and pyochelin by Pseudomonas aeruginosa, respectively[END_REF][START_REF] Michel | Ferripyochelin uptake genes are involved in pyochelinmediated signalling in Pseudomonas aeruginosa[END_REF][15]. In order to find other proteins involved in this pathway, we looked for FptX-interacting partners by using a bacterial two-hybrid genome wide screening. The pKNT25-fptX bait plasmid was combined with the P. aeruginosa PAO1 fragment prey libraries constructed in the pUT18 vector by Houot et al., 2012 [20]. Blue colonies reflecting a protein interaction with FptX were identified, and the DNA sequence inserts contained in the pUT18 derivative vectors were further sequenced.

The prey fragments corresponded either to the 253 first amino acids of the fatty acid coenzyme-A ligase FadD1, or to the 120 first amino acids of PA1316, a putative major facilitator superfamily transporter. Only data showing that the expression of fptA, encoding for the outer membrane transporter, is drastically decreased in an fptX mutant [START_REF] Michel | PchR-box recognition by the AraC-type regulator PchR of Pseudomonas aeruginosa requires the siderophore pyochelin as an effector[END_REF]. Regarding the fadD1D2 mutant, a very similar 55 Fe repartition was observed compare to the control strain, indicating that FadD1 plays no role in iron acquisition by PCH.

We next investigated the effect of fadD1D2 mutations on PCH production. WT and the corresponding mutant strains were grown under iron-starvation conditions and PCH was extracted from growth medium and its concentration determined using its characteristic absorbance at 320 nm. A 1.4-, 2.4-, and 4.4-fold decrease in PCH concentration in the growth medium was observed for the fadD1D2, fptX and fptX fadD1D2 mutants respectively, compared to the wild type PAO1 strain (Fig. 3), suggesting a role of FadD1 in PCH production and/or secretion.

Biochemical and architectural analysis of FptX, FadD1 and the FadD1-FptX complex.

In contrast to the available X-ray structure of the outer membrane transporter FptA [START_REF] Cobessi | Crystal structure at high resolution of ferric-pyochelin and its membrane receptor FptA from Pseudomonas aeruginosa[END_REF], structural data are still lacking for the inner membrane transporter FptX. The determination of the 3D structure of this polytopic inner membrane protein remains very challenging because of the low expression levels of FptX even in overproducing bacterial systems. Consequently, we then investigated the architecture of FptX, FadD1 and the FadD1-FptX complex by negative-stain EM. First, the proteins were produced and purified from E. coli membranes and their functional integrity was established by assessing the binding activity to ferri-PCH for FptX and the FadD1-FptX complex, and the fatty acid coenzyme-A ligase activity for FadD1 (Fig. S2). EM data set were collected, and reference-free two-dimensional class revealed characteristic views of the FadD1-FptX complex, FptX and FadD1 (Fig. S3). The EM data set was used to reconstruct a 33-Å, 26-Å and 17-Å resolution three-dimensional (3D) model of the FadD1-FptX complex, FptX and FadD1 proteins, respectively (Fig. 4). FadD1-FptX complex is ~230 Å in height and ~150 Å in diameter. FptX is ~225 Å in height and ~120 Å in diameter, and FadD1 is ~115 Å in height and ~90 Å in diameter. The FptX EM model was then docked into the EM volume of the FadD1-FptX complex, showing that FptX occupies most of the EM envelope of the complex (Fig. 4). However, at this low resolution and according to the small volume of FadD1, the electron density may not have sufficiently distinctive features for an unambiguous placement of FadD1 in the EM volume complex.

Discussion

The data presented here give new insights in the P. aeruginosa PCH siderophore pathway. Previous studies had shown that FptA and FptX are the outer and inner membrane transporters involved in iron uptake by the siderophore PCH [START_REF] Ankenbauer | Cloning of the outer membrane high-affinity Fe(III)-pyochelin receptor of Pseudomonas aeruginosa[END_REF][START_REF] Cobessi | Crystal structure at high resolution of ferric-pyochelin and its membrane receptor FptA from Pseudomonas aeruginosa[END_REF][START_REF] Mislin | Binding properties of pyochelin and structurally related molecules to FptA of Pseudomonas aeruginosa[END_REF][START_REF] Cuív | Identification of rhtX and fptX, novel genes encoding proteins that show homology and function in the utilization of the siderophores rhizobactin 1021 by Sinorhizobium meliloti and pyochelin by Pseudomonas aeruginosa, respectively[END_REF][START_REF] Michel | Ferripyochelin uptake genes are involved in pyochelinmediated signalling in Pseudomonas aeruginosa[END_REF][15]. Both proteins also play a role in PCH production: in fptA and fptX mutants no more PCH-Fe is transported into bacteria, affecting the PCH-mediated signaling cascade, and hence PCH production [START_REF] Michel | Ferripyochelin uptake genes are involved in pyochelinmediated signalling in Pseudomonas aeruginosa[END_REF][START_REF] Michel | PchR-box recognition by the AraC-type regulator PchR of Pseudomonas aeruginosa requires the siderophore pyochelin as an effector[END_REF].

Here, the bacterial two-hybrid screen represented a powerful tool as it identified for the first time a fatty acid coenzyme-A ligase enzyme, FadD1, as an interacting partner of the inner membrane transporter FptX.

FadD1 is described as a fatty acid coenzyme-A ligase involved in fatty acid metabolism in P. aeruginosa [23]. To assess the physiological significance of the FadD1-FptX complex, we explored the impact of FadD1 on both ferri-PCH uptake and PCH production. We showed that FadD1 has no impact on iron uptake by PCH but is required for optimum PCH production. FadD1 may play a role in biosynthesis and/or secretion of PCH, but the data do not allow to discriminate between these two biological processes. Our findings suggest a potential acylation of PCH. FadD1 might load a fatty acid chain to PCH, allowing PCH to be anchored to the inner membrane during its synthesis as described previously for PVD, ferrichrome or mycobactin [START_REF] Hannauer | The ferrichrome uptake pathway in Pseudomonas aeruginosa involves an iron release mechanism with acylation of the siderophore and recycling of the modified desferrichrome[END_REF][START_REF] Hannauer | Biosynthesis of the pyoverdine siderophore of Pseudomonas aeruginosa involves precursors with a myristic or a myristoleic acid chain[END_REF][START_REF] Vergnolle | Mechanism and regulation of mycobactin fatty acyl-AMP ligase FadD33[END_REF]. For mycobactin, the fatty acid ligase FadD33 (also known as MbtM) was reported to transfer a lipophilic aliphatic chain to the -amino group of the lysine mycobatin core [START_REF] Vergnolle | Mechanism and regulation of mycobactin fatty acyl-AMP ligase FadD33[END_REF]. In the case of PVD, the biosynthesis begins with an acylation introducing a myristic or myristoleic group carried out by the first module of the PvdL non ribosomal peptide synthetase [START_REF] Hannauer | Biosynthesis of the pyoverdine siderophore of Pseudomonas aeruginosa involves precursors with a myristic or a myristoleic acid chain[END_REF]. The presence of a myristic or myristoleic acid group retains the PVD precursor at the membrane during its biosynthesis. For both PVD and mycobactin, the acylation of siderophore promotes plasma membrane localization. As FptX is involved in ferri-PCH uptake, we can also hypothesize that such acylation of PCH could occur after its uptake for its recovery/recycling, if any.

Further experiments are still necessary to identify the role of an acylation of PCH by FadD1. Moreover, currently nothing is known concerning the proteins and the molecular mechanisms involved in PCH secretion as well as in the molecular mechanism allowing iron release from PCH.

FptX was reported to be a homolog of the transporter of rhizobactin RhtX, belonging to the major facilitator superfamily (MFS) transporters [START_REF] Cuív | Identification of rhtX and fptX, novel genes encoding proteins that show homology and function in the utilization of the siderophores rhizobactin 1021 by Sinorhizobium meliloti and pyochelin by Pseudomonas aeruginosa, respectively[END_REF]. Currently, structure determination of such inner membrane proteins remains a difficult task and presents a challenge for expression and purification. Here, we established for the first time a low-resolution 3D model of FptX, its interacting partner FadD1 and of the FadD1-FptX complex by negative-stain EM. Due to the lack of information concerning the various domains of FptX and the low resolution of the EM reconstruction, it was impossible to clearly define a topology of the complex.

Altogether, these results highlight a new actor in the PCH pathway and suggest that this pathway would probably be more complex than what has been described so far. In addition, our efforts to purify and initiate low resolution EM-models pave the way for future high-resolution studies for structure-based drug design to counter antibiotic resistance, one of the biggest public health challenges of our time. instantaneous free thiol concentration via absorbance readings at 412 nm. A color change is produced upon the binding of 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB or Ellman's reagent) to the free thiol groups of CoA-SH. Progressive loss of signal at 412 nm is indicative of CoA-SH consumption. Reactions were prepared with 40 µg of purified FadD1 in a reaction buffer containing final concentrations of 150 mM Tris- HCl (pH 7.2), 10 mM MgCl2, 2 mM EDTA, 0.1 % Triton X-100, 5 mM ATP, 0.5 mM co-enzyme A and sodium oleate (0 and 200 µM). To perform the reaction, each mixture was assembled containing all components above (excluding CoASH). The reaction mixture was prewarmed at 37°C for 2 min. The reaction was initiated with the addition of CoASH (final concentration 0.5 mM) that was pre-incubated at 37°C for 2 min, quickly mixed, and incubated at 37°C during the course of the reaction. 70 µL aliquots of the reaction were taken at different intervals and mixed with 600 µL of 0.4 mM DTNB (dissolved in 0.1 M potassium phosphate at pH 8). A 412nm values were acquired after a 5-minute color development period at room temperature. Control reaction mixture lacking protein was also prepared. The previously published extinction coefficient of 13,600 M -1 .cm -1 for DTNB was used to compute specific activity [1].

Acknowledgement

Loading of the individual FptX(His 6 ) into a StrepTrap HP column. Top10 E. coli cells were transformed with the p33-fptX(His 6 ) vector. Cell growth, gene induction and membrane preparation were done as described in the "Expression and purification of FptX" section in the main Materials and Methods. The supernatant was loaded onto a 1-mL StrepTrap HP column (GE Healthcare) equilibrated with buffer A (50 mM Tris-HCl pH 8, 200 mM NaCl, 0.1 % DDM). Elution was done using buffer A containing 2.5 mM D-Desthiobiotin. The unbound fraction was then loaded onto a 1-mL HisTrap HP column (GE Healthcare) equilibrated with buffer B (50 mM Tris-HCl pH 8, 500 mM NaCl, 0.1 % n-Dodecyl--D-maltopyranoside (DDM), 20 mM imidazole). Elution was done with buffer B containing 500 mM imidazole. (A, D and G) Size-exclusion chromatography analysis of the purified FptX (A), FadD1 (D) and the FadD1- FptX complex (G) (continuous line) on a Superdex 200 10/300 GL. The dead volume is indicated as the V0.

The arrow indicates the position of the fraction corresponding to FptX (A), FadD1 (D) and the FadD1-FptX complex (G). (B and H) Immunoblot analysis of the purified FptX (B) and the FadD1-FptX complex (H) using anti-His ( -His) and anti-StrepII ( -Strep) antibodies. (C and I) Binding of PCH-55 Fe to purified FptX (C) and FadD1-FptX complex (I). Purified proteins were incubated with 10, 100 or 200 nM of PCH-55 Fe complex. The non-specific retention was subtracted from the total of radioactivity monitored in the presence of the proteins. (E) SDS-PAGE of the purified FadD1 protein analyzed by Instant blue TM staining. (F) FadD1 enzymatic assay was conducted using DTNB to monitor CoA-SH consumption at 412 nm with increasing amount of sodium oleate as substrate. A loss of signal at 412 nm is indicative of FadD1 activity. The errors bars represent the standard deviation of the mean of three independent experiments. . FSC curves of FptX (A), the FadD1-FptX complex (B) and FadD1 (C) reconstruction without symmetry applied. The FSC curves were calculated in Relion using the masked reconstruction of FptX, the FadD1-FptX complex and FadD1, respectively.

  Authors acknowledge the Centre National de la Recherche Scientifique (CNRS) for general financial support. BR would like to thank Roche Pharmaceutical Research and Early Development Basel for their financial support via the Roche Postdoctoral Fellowship (RPF) Program. We acknowledge the support and the use of resources of the French Infrastructure for Integrated Structural Biology (FRISBI) ANR-10-INBS-05, "Project ID 52", and of Instruct-ERIC, "PID 2886". Specifically, we would like to thank Christine Ruhlmann and Corinne Crucifix (IGBMC, Strasbourg) for help with EM sample preparation and EM data collection, and Veronique Mallouh (IGBMC, Strasbourg) for help with data processing. We acknowledge Eric Durand (LISM, Marseille) for fruitful EM processing discussion. We acknowledge Christophe Bordi (LISM, Marseille), Laetitia Houot (LISM, Marseille) and Aurélia Battesti (LCB, Marseille) for kindly providing the PAO1 two-hybrid libraries and the two-hybrid vectors, and Laurent Loiseau (LCB, Marseille) for providing pBAD vectors. 28 Vincent F, Round A, Reynaud A, Bordi C, Filloux A & Bourne Y (2010) Distinct oligomeric forms of the Pseudomonas aeruginosa RetS sensor domain modulate accessibility to the ligand binding site. Environ Microbiol 12, 1775-1786.

Fig. 1 .Fig. 2 .

 12 Fig. 1. Interaction between FptX and FadD1. (A) Bacterial two-hybrid assay. The fadD1 and fptX genes

Fig. 3 .

 3 Fig. 3. Amount of PCH secreted by PAO1 and its corresponding mutants. Cells were grown in CAA medium

Fig. 4 .

 4 Fig. 4. Architecture of the purified proteins. 33-Å 3D reconstruction of the FadD1-FptX complex (A), 26-

Fig. S1 .

 S1 Fig. S1. Negative control by loading the individual FptX(His 6 ) onto the StrepTrap column. (A) Solubilized bacterial membranes overexpressing FptX(His 6 ) only were loaded onto a StrepTrap HP column: Unbound (U1) and elution with desthiobiotin steps are represented. (B) The unbound U1 fraction was then loaded

Fig. S2 .

 S2 Fig. S2. Purification and biochemical characterization of FptX, FadD1 and the FadD1-FptX complex.

Fig. S3 .

 S3 Fig. S3. Representative electron micrograph showing FadD1-FptX (A), FptX (D) and FadD1 (G) particles

Fig. S4

  Fig. S4. FSC curves of FptX (A), the FadD1-FptX complex (B) and FadD1 (C) reconstruction without

Table S1 .

 S1 Strains and plasmids used in this study.

	Strains		Characteristics	Reference
	Escherichia coli	ID collection
	TOP10	2	F-, mcrA (mrr-hsdRMS-mcrBC), 80lacZ, M15, lacX74, recA1,	Invitrogen
			araD139, (ara-leu)7697, galU, galK, rpsL, endA1, mup
	E. coli DHM1	281	F-, cya-, recA1, endA, gyrA96, thi-1, hsdR17, spoT1, rfbD1, cya-854	[2]
	Pseudomonas aeruginosa
	PAO1	43	Wild-type strain	[3]
		PAS218	PAO1; fptX chromosomally deleted	[4]
		PAS431	PAO1; fadD1 and fadD2 chromosomally deleted	This study
		PAS410	PAO1; fadD1, fadD2 and fptX chromosomally deleted	This study
		PAS213	PAO1; pvdF and pchA chromosomally deleted	[4]
		PAS273	PAO1; pvdF, pchA and fptX chromosomally deleted	[4]
		PAS428	PAO1; pvdF, pchA, fadD1 and fadD2 chromosomally deleted	This study
		PAS413	PAO1; pvdF, pchA, fptX, fadD1 and fadD2 chromosomally deleted	This study
	Plasmids	ID collection	Characteristics	Reference
	pKNT25	264	P15 origin, Plac, C-terminal T25 cyclase fragment, Kan R	[2]
	pUT18C	265	ColE1 origin, Plac, N-terminal T18 cyclase fragment, Ap R	[2]
	pBAD33	270	pBAD33 plasmid, Cm R	[5]
	pBAD24	271	pBAD24 plasmid, Ap R	[5]
	pUT18CPAO1lib	294	pUT18C containing PAO1 genomic library as a C-terminal T18 fusion	[6]
	pUT18PAO1lib	295	pUT18 containing PAO1 genomic library as an N-terminal T18 fusion	[6]
	pUT18+1PAO1lib	296	pUT18+1 containing PAO1 genomic library as an N-terminal T18 fusion	[6]
	pUT18+2PAO1lib	297	pUT18+2 containing PAO1 genomic library as an N-terminal T18 fusion	[6]
	pKNT25-fptX	268	pKNT25 plasmid containing fptX-cyaAT25 fusion	This study
	pUT18C-fadD1	293	pUT18C plasmid containing cyaAT18-fadD1 fusion	This study
	p33-fptX(His 6 )	272	pBAD33 plasmid expressing fptX Cter-fused to 6His tag	This study
	p24-fadD1(StrepII)	311	pBAD24 plasmid expressing fadD1 Cter-fused to StrepII tag	This study
	pEXG2 delfadD1D2	330	suicide vector for deleting fadD1 and fadD2	This study

Author contributions

BR and IS designed the experiments. BR performed the experiments. GM provided the PCH siderophore.

BR wrote the manuscript. IS helped to improve the article. All authors discussed and commented on the manuscript. Supplementary data Identification of the fatty acid coenzyme-A ligase FadD1 as an interacting partner of FptX in the

Pseudomonas aeruginosa pyochelin pathway

Béatrice Roche 1,2,3* , Gaëtan L.A. Mislin 1,2 and Isabelle J. Schalk 1,2 1. CNRS, UMR7242, ESBS, Bld Sébastien Brant, F-67412 Illkirch, France.

2. Université de Strasbourg, UMR7242, ESBS, Bld Sébastien Brant, F-67412 Illkirch, France.

3. Present address: Biozentrum, University of Basel, CH-4056 Basel, Switzerland * = correspondence should be addressed to Béatrice Roche (beatrice.roche@unibas.ch)

Materials and methods

Binding of PCH-55 Fe.

10 nM of purified FptX or the complex was incubated with various amount of PCH-55 Fe in 500 of 50 mM Hepes pH 7.5, 50 mM NaCl, 0.025 % DDM at room temperature for 2 h. The solution of PCH complexed with 55 Fe was prepared with a siderophore/iron (mol/mol) ratio of 20:1. Incubation was stopped by filtering the assay mixture over GF/B filters (Whatman, presoaked in 0.1 % polyethyleneimine to reduce the non-specific retention). The filters were then rapidly washed three times with 1 mL of 50 mM Tris pH 8 and counted for radioactivity in a scintillation mixture. The experiment was repeated in the absence of the purified protein. For each PCH-55 Fe concentration, the non-specific retention was then subtracted from the total radioactivity monitored in the presence of the protein.

Measurement of fatty acyl-CoA synthetase activity of FadD1.

The activity of purified FadD1 was assessed using Ellman's reagent to monitor the consumption of the free thiol group of Co-A due to FadD1-catalyzed acyl-CoA ligation [1]. This colorimetric assay quantifies the