Frauke Beilstein

Matthieu Lemasson

Véronique Pène

Dominique Rainteau

Sylvie Demignot
email: sylvie.demignot@crc.jussieu.fr

Arielle R Rosenberg
email: arielle.rosenberg@parisdescartes.fr

Lysophosphatidylcholine acyltransferase 1 is downregulated by hepatitis C virus: impact on production of lipo-viro-particles

Keywords: hepatitis C virus morphogenesis, HCV-related steatosis, lipo-viro-particle, primary human hepatocyte, very low density lipoprotein bovine serum albumin, ffu, focus-forming units, HCV, hepatitis C virus, LD, lipid droplet, LPCAT, lysophosphatidylcholine acyltransferase, LVP, lipo-viro-particle, PHH, primary human hepatocytes, PL, phospholipid

Objective Hepatitis C virus (HCV) is intimately linked with the liver lipid metabolism, devoted to the efflux of triacylglycerols stored in lipid droplets (LDs) in the form of triacylglycerol-rich very-low-density lipoproteins (VLDL): (i) the most infectious HCV particles are those of lowest density due to association with triacylglycerol-rich lipoproteins;

(ii) HCV-infected patients frequently develop hepatic steatosis (increased triacylglycerol storage). The recent identification of lysophosphatidylcholine acyltransferase 1 (LPCAT1) as an LD phospholipid-remodelling enzyme prompted us to investigate its role in liver lipid metabolism and HCV infectious cycle.

Design Huh-7.5.1 cells and primary human hepatocytes (PHH) were infected with JFH1-HCV. LPCAT1 depletion was achieved by RNA interference. Cells were monitored for LPCAT1 expression, lipid metabolism and HCV production and infectivity. The density of viral particles was assessed by isopycnic ultracentrifugation.

Results

Upon HCV infection, both Huh-7.5.1 cells and PHH had decreased levels of LPCAT1 transcript and protein, consistent with transcriptional downregulation. LPCAT1 depletion in either naïve or infected Huh-7.5.1 cells resulted in altered lipid metabolism characterized by LD remodelling, increased triacylglycerol storage and increased secretion of VLDL. In infected Huh-7.5.1 cells or PHH, LPCAT1 depletion increased production of the viral particles of lowest density and highest infectivity.

Conclusion

We have identified LPCAT1 as a modulator of liver lipid metabolism downregulated by HCV, which appears as a viral strategy to increase the triacylglycerol content and hence infectivity of viral particles. Targeting this metabolic pathway may represent an attractive therapeutic approach to reduce both the viral titre and hepatic steatosis.

SIGNIFICANCE OF THIS STUDY

What is already known on this subject?

-The most infectious HCV particles circulate as hybrid lipo-viro-particles (LVPs) consisting of viral and very-low-density lipoprotein (VLDL) components.

-The human hepatocyte is both the cell specialized in the biogenesis of VLDLs and the primary replication site of HCV, but whether the VLDL pathway is usurped for LVP morphogenesis is still a matter of debate.

-Besides the existence of LVPs another clinical feature that links HCV infection with the host lipid metabolism is the high prevalence of liver steatosis, but whether these facts are related is unknown.

What are the new findings?

-Lysophosphatidylcholine acyltransferase 1 (LPCAT1) is identified as a modulator of the liver lipid homeostasis downregulated by HCV.

-LPCAT1 depletion increases LVP production, supporting the idea that HCV indeed hijacks the hepatocellular lipid metabolism for the benefit of highly infectious LVP morphogenesis.

-LPCAT1 depletion also increases VLDL secretion, suggesting that at least some of the mechanisms of LVP morphogenesis and VLDL biogenesis are shared.

-LPCAT1 depletion also causes steatosis, illustrating a possible link between LVP morphogenesis and liver steatosis.

How might it impact on clinical practice in the foreseeable future?

-Our findings designate the LPCAT1-regulated lipid metabolism pathway as an attractive host target for antiviral therapy in most difficult-to-treat patients.

-Compared to other lipid-modulating antiviral approaches expected to aggravate liver steatosis, targeting the LPCAT1-regulated pathway would reduce liver steatosis besides reducing HCV infectious titre.

INTRODUCTION

The hepatitis C virus (HCV) is a leading cause of chronic liver disease worldwide. Unique to this human hepatotropic virus is its tight link with the host lipid metabolism. [1][2][3] Clinical evidence in chronically infected patients has long recognized the high prevalence of liver steatosis, defined as an accumulation of lipids, essentially accounted for by triacylglycerols (TAGs), in cytosolic lipid droplets (LDs) of hepatocytes. Moreover, HCV particles are heterogeneous in the circulating blood of patients and the most infectious viral particles are those of exceptionally low buoyant density due to their association with apolipoprotein (Apo) B-containing TAG-rich lipoproteins in original structures referred to as lipo-viro-particles (LVPs). 4 5 As hepatocytes are specialized in the assembly and secretion of the ApoBcontaining TAG-rich lipoproteins known as very-low-density lipoproteins (VLDLs), a working hypothesis is that LVPs are formed originally within infected cells, the hepatocellular lipid metabolism being hijacked by HCV for the benefit of their morphogenesis. [6][7][8] LDs consist of a core of TAGs and cholesterol esters surrounded by a monolayer of phospholipids (PLs) and cholesterol. 9 Importantly, TAGs stored in cytosolic LDs of hepatocytes provide most of the TAGs present in VLDLs through a mechanism of hydrolysisreesterification. 10 11 Many proteins interact with the LD surface, as shown by proteomic characterization of LDs isolated from hepatic cells. [START_REF] Fujimoto | Identification of major proteins in the lipid dropletenriched fraction isolated from the human hepatocyte cell line HuH7[END_REF] [START_REF] Mashek | Hepatic lipid droplet biology: Getting to the root of fatty liver[END_REF] The LD proteome includes structural proteins, perilipins, and proteins that control several cellular pathways including lipid metabolism (e.g., lipases, acyltransferases), membrane trafficking, signalling, etc. 14 15 The interaction of these proteins with the LD surface can be modulated through mechanisms, probably of multiple causes, that are only just starting to be clarified. 16 17 Because of the large variety of PLs conferring different physicochemical properties to the LD surface, the nature of PLs is a factor that can modulate the strength of protein association. 18 19 The most abundant PL of the LD surface is phosphatidylcholine. [START_REF] Penno | Phospholipids and lipid droplets[END_REF] The lysophosphatidylcholine acyltransferase (LPCAT) family consists of PL-remodelling enzymes [START_REF] Hishikawa | Diversity and function of membrane glycerophospholipids generated by the remodeling pathway in mammalian cells[END_REF] , among which LPCAT1 and LPCAT2 localise partially to the LD surface where they can synthesize phosphatidylcholine. [START_REF] Moessinger | Human lysophosphatidylcholine acyltransferases 1 and 2 are located in lipid droplets where they catalyze the formation of phosphatidylcholine[END_REF] Moreover, LPCAT1 and LPCAT3, both expressed in hepatocytes, were recently reported to influence lipoprotein secretion from these cells. 23 24 These considerations prompted us to examine the hypothesis of a potential hijacking of LPCAT-mediated metabolism by HCV. Indeed, LPCAT1 is shown here to be downregulated by HCV. LPCAT1 depletion, in turn, was found to increase the virus infectivity.

MATERIALS AND METHODS

Cell culture, infection and gene silencing

Huh-7.5.1 cells and primary human hepatocytes (PHH) were inoculated with JFH1-HCV at a multiplicity of infection of 0.2 and 2 focus-forming units (ffu)/cell, respectively, as described previously. 25 26 Further details for infection and for transfection with HCV subgenomic replicon or core-encoding plasmid are given in the supplementary material. ShRNA-and siRNA-mediated gene silencing was used to achieve LPCAT1 depletion in Huh-7.5.1 cells and PHH, respectively (see supplementary material).

Gene expression and virological analyses

For details of quantitative reverse-transcription real-time polymerase chain reaction (RT-qPCR), western blotting, confocal microscopy, Apo quantification, and virological analyses, [START_REF] Podevin | Production of infectious hepatitis C virus in primary cultures of human adult hepatocytes[END_REF][START_REF] Pene | Sequential processing of hepatitis C virus core protein by host cell signal peptidase and signal peptide peptidase: a reassessment[END_REF][START_REF] Carriere | A novel, sensitive, and specific RT-PCR technique for quantitation of hepatitis C virus replication[END_REF] see the supplementary material. All analyses were done at day 3 post-inoculation except for the quantification of negative-strand HCV RNA, which was done at day 1 post-inoculation. Indeed, at later time points multiple rounds of infection are expected to cause a bias in the assessment of viral genome replication per se if production of viral particles is affected.

Lipid analyses

The TAG mass was quantified using the PAP150TG kit (BioMérieux) as described in the supplementary material. For analysis of lipid secretion capacity, cells were incubated for the last 24 h of culture with oleic acid (0.6 mM) in complex with bovine serum albumin (oleic acid/BSA) containing 1 μCi/ml [1-14 C] oleic acid, then lipids were extracted from cells and media and fractionated by thin layer chromatography followed by quantification of radioactivity as described previously [START_REF] Chateau | Lipid micelles stimulate the secretion of triglyceride-enriched apolipoprotein B48-containing lipoproteins by Caco-2 cells[END_REF] and in the supplementary material.

Statistical analyses

Results were expressed as the mean ± standard error of the mean (SEM) of at least three independent experiments. Statistical significance was evaluated using Student's t test for unpaired two-sided data (* for p <0.05, ** for p <0.01 and *** for p <0.001) after a Shapiro-Wilk test was done to confirm that all data follow a normal distribution.

RESULTS

LPCAT1 is downregulated by HCV

As a starting point we investigated whether HCV infection affects the expression of any member of the LPCAT family in Huh-7.5.1 cells (supplementary figure S1). Only LPCAT1 showed significantly reduced mRNA amounts upon JFH1-HCV inoculation (0.47 ± 0.05), correlating with reduced LPCAT1 protein amounts as assessed by western blot analysis (0.61 ± 0.09) (figure 1A). Most importantly, confocal microscopy analysis confirmed that at the single-cell level, those cells that were actually infected upon HCV inoculation showed a clear decrease in LPCAT1 signal intensity compared to non-infected cells (figure 1B). We concluded that HCV infection induces downregulation of LPCAT1 expression occurring at least partly at the transcriptional level.

As approaches to unravelling mechanisms of HCV-induced downregulation of LPCAT1, we transfected Huh-7.5.1 cells with either a subgenomic JFH1-HCV replicon or a plasmid encoding JFH1-HCV core protein (figure 2). LPCAT1 expression was unchanged in cells harbouring the subgenomic replicon, suggesting that the downregulation observed upon HCV infection involves neither the virus non-structural proteins nor the viral genome replication step (figure 2A-B). By contrast, cells transfected with core-encoding plasmid had significantly reduced LPCAT1 mRNA amounts at the population level (figure 2C), and most strikingly at the single-cell level those cells that actually expressed HCV core protein had reduced LPCAT1 protein signal intensity (figure 2D). Thus, the sole expression of core protein was sufficient to recapitulate HCV infection-induced downregulation of LPCAT1.

LPCAT1 depletion increases production of HCV particles with high infectivity and low density

Next we wanted to determine whether LPCAT1 downregulation has an impact on HCV infectious cycle. To address this question, we used a lentiviral vector encoding shRNA against LPCAT1 (shLPCAT1). In Huh-7.5.1 cells, this indeed resulted in a strong decrease of LPCAT1 protein and mRNA amounts (0.34 ± 0.1 for both) compared to control cells treated with lentivirus encoding shRNA against luciferase (shLuc) (supplementary figure S2A-B). This depletion was specific to LPCAT1, as the mRNA amount of LPCAT3, the main LPCAT in hepatocytes, [START_REF] Zhao | Identification and characterization of a major liver lysophosphatidylcholine acyltransferase[END_REF] remained unchanged (supplementary figure S2C). An even stronger decrease of LPCAT1 protein and mRNA amounts was observed in shLPCAT1-transduced Huh-7.5.1 cells that were inoculated with HCV (0.17 ± 0.07 and 0.20 ± 0.04, respectively), suggesting an additive effect of HCV infection and shLPCAT1 on LPCAT1 depletion (supplementary figure S2D-E). We also verified that shLPCAT1 transduction had no cytotoxic effect (supplementary figure S3A).

To examine the impact of LPCAT1 depletion on HCV infectious cycle, we first used an infectivity assay to evaluate the production of infectious virus in the culture supernatant. The infectivity titre was significantly increased in LPCAT1-depleted Huh-7.5.1 cells (5.84 ± 2.08) (figure 3A). However, this effect could not be attributed to increased replication of viral genome because upon LPCAT1 depletion the amount of negative-strand HCV RNA was modified neither in these HCV-infected cells (figure 3A) nor in cells harbouring a subgenomic HCV replicon (supplementary figure S4). These results pointed to viral morphogenesis as the step of HCV infectious cycle affected by LPCAT1 depletion.

Nevertheless, LPCAT1 depletion had only a slight, not significant tendency to increase the viral load, which reflects the production of physical viral particles irrespective of their infectivity. Accordingly, the specific infectivity (ratio of infectivity titre to viral load) was significantly increased in LPCAT1-depleted cells (3.83 ± 1.69). To exclude putative off-target effects of shLPCAT1, we transfected shLPCAT1-transduced Huh-7.5.1 cells with expression plasmids carrying wild-type or an shLPCAT1-resistant version of LPCAT1 gene (supplementary figure S5A), which led to increasing restoration of LPCAT1 protein expression (supplementary figure S5B). This indeed restrained the shLPCAT1-induced gain in both infectivity titre and specific infectivity in a dose-dependent manner (supplementary figure S5C), with a good linear inverse relationship between LPCAT1 protein amount and HCV infectivity titre (supplementary figure S5D). Collectively, the data suggested that LPCAT1 depletion favours the morphogenesis of highly infectious virus.

Finally, because HCV infectivity is inversely correlated with the buoyant density of viral particles, 25 30 we subjected culture supernatants from HCV-infected Huh-7.5.1 cells depleted or not for LPCAT1 to isopycnic ultracentrifugation through iodixanol gradients (see a representative experiment in figure 3B-E). As previously reported for HCV grown in Huh-7 cell line, 25 30 the majority of viral RNA peaked between 1.09 and 1.14 g/ml (figure 3B).

However, LPCAT1 depletion led to a shift of HCV RNA towards fractions of lower buoyant density: the percentage of total viral load present below 1.08 g/ml was 22.60 ± 1.65% for LPCAT1-depleted cells as compared to 12.59 ± 1.99% for control cells. The excess of highly infectious particles produced upon LPCAT1 depletion was also found in these fractions of lower density (figure 3C). We concluded that LPCAT1 depletion increases the production of HCV particles of high specific infectivity coinciding with low buoyant density.

LPCAT1 depletion leads to LD remodelling, increased TAG storage and increased secretion of TAG-rich lipoproteins

The lower buoyant density of HCV produced upon LPCAT1 depletion was consistent with a TAG enrichment of viral particles, prompting us to examine the impact of LPCAT1 depletion on the hepatocellular lipid metabolism. Confocal microscopy of Huh-7.5.1 cells labelled with BODIPY 493/503 did not show any gross modification of the intracellular LD distribution upon LPCAT1 depletion (figure 4A). However, the mean number of LDs was significantly reduced in LPCAT1-depleted cells compared to control cells (153.20 ± 37.89 and 352.12 ± 78.14 LDs/cell, respectively) (figure 4B). Furthermore, measurement of LD size showed a shift of the LD diameter distribution towards larger LDs upon LPCAT1 depletion (figure 4C).

Besides these modifications that might reflect fusion of small LDs into larger ones, the net intracellular TAG amount was increased in the steady state in LPCAT1-depleted cells (1.72 ± 0.07) (figure 4D). Because hepatic cells produce TAG-rich lipoproteins, this increased intracellular TAG content could result from inhibition of their secretion. Unexpectedly, however, the amount of ApoB, the constitutive apolipoprotein of TAG-rich lipoproteins, was increased in the culture supernatant of LPCAT1-depleted compared to control cells (423.28 ± 84.19 and 175.77 ± 34.35 μg/dl, respectively) (figure 4E), indicating the secretion of a greater number of lipoprotein particles. An impaired capacity to enrich lipoproteins with TAGs could also lead to an increased intracellular TAG content. To test this hypothesis, Huh-7.5.1 cells were challenged with oleic acid containing [1-14 C] oleic acid as a tracer then radiolabelled PLs and TAGs were quantified in cells and media (figure 5). The intracellular amounts of newly synthesized PLs and TAGs were similar in LPCAT1-depleted and control cells, indicating similar uptake and lipid synthesis capacity. However, the secretion of newly synthesized TAGs was significantly, albeit slightly increased in LPCAT1-depleted cells (1.24 ± 0.15 fold) while PL secretion was not modified. This indicates that LPCAT1-depleted cells have a slightly higher TAG secretion capacity compared to control. We concluded that LPCAT1 depletion in Huh-7.5.1 cells results in an altered lipid metabolism characterized by LD remodelling, increased intracellular TAG content, increased ApoB-containing lipoprotein secretion and increased TAG secretion capacity.

Next we examined the impact of LPCAT1 depletion on the hepatocellular lipid metabolism in the context of HCV infection. For all characteristics studied, similar effects were observed in LPCAT1-depleted Huh-7.5.1 cells irrespective of whether they were infected or not. Indeed, in infected Huh-7.5.1 cells LPCAT1 depletion led to a reduction in the mean number of LDs accompanied by a shift of the LD diameter distribution towards larger LDs (figure 6A-C), and increased both the intracellular amount of TAGs and the amount of secreted ApoB (figure 6D-E). Upon isopycnic iodixanol gradient ultracentrifugation of culture supernatant of these cells, ApoB peaked at a higher buoyant density than the very low density (<1.006 g/ml) expected for VLDLs (figure 6F), consistent with the reported inability of the Huh-7 cell line to secrete genuine VLDLs. [START_REF] Podevin | Production of infectious hepatitis C virus in primary cultures of human adult hepatocytes[END_REF] Nevertheless, ApoB and ApoE, another important component of VLDLs, were both found in fractions with a density below 1.08 g/ml (figure 6F-G), i.e., in the density range of the excess of highly infectious HCV particles produced upon LPCAT1 depletion (figure 3D-E). Taken together, the results suggest that LPCAT1 depletion increases the secretion of TAG-rich lipoproteins and HCV particles associated with TAG-rich lipoproteins.

Validation of data in physiologically relevant PHH

Huh-7 sublines provide a most convenient and efficient HCV culture system, yet differ significantly from normal, quiescent, highly differentiated human adult hepatocytes and especially do not fully reproduce VLDL biogenesis. [START_REF] Podevin | Production of infectious hepatitis C virus in primary cultures of human adult hepatocytes[END_REF] In order to validate the data in a pathophysiologically relevant model, we used our HCV culture system in PHH, which produce genuine VLDLs and HCV particles whose properties mimic those of infectious HCV produced in vivo. [START_REF] Podevin | Production of infectious hepatitis C virus in primary cultures of human adult hepatocytes[END_REF] We first sought to determine whether HCV infection downregulates LPCAT1 expression in PHH as is the case in Huh-7.5.1 cells. Because PHH are primary cells, the infectivity titres reached upon JFH1-HCV inoculation were generally lower than those obtained in Huh-7.5.1 cells and varied from one donor of hepatocytes to another. When viral titres were below 5.10 4 ffu/ml, LPCAT1 mRNA amounts did not appear to be modified in PHH inoculated with HCV compared to naïve PHH (figure 7A). When higher titres were reached, however, a reduction of LPCAT1 mRNA amounts was observed, and a strong linear inverse relationship was found between LPCAT1 expression levels and HCV infectivity titres (figure 7B), consistent with the occurrence of HCV-induced transcriptional downregulation of LPCAT1 in PHH.

Next we investigated the impact of LPCAT1 depletion on HCV infectious cycle in PHH. For this, PHH were transfected with siRNA against LPCAT1 (siLPCAT1) versus GFP (siGFP), then inoculated with HCV. A significant decrease in LPCAT1 protein amount was observed in PHH transfected with siLPCAT1 compared to control (0.37 ± 0.05) (supplementary figure S2F), in the absence of cytotoxic effect (supplementary figure S3B). LPCAT1 depletion in PHH had no impact on HCV genome replication but increased the infectivity titre by almost 1 log (9.27 ± 5.60) (figure 7C), indicating an effect on virus morphogenesis. However, the viral load was not significantly modified, therefore the specific infectivity of viral particles produced was increased in LPCAT1-depleted PHH (7.87 ± 5.14). Upon isopycnic iodixanol gradient ultracentrifugation, the proportion of viral RNA-containing particles with a buoyant density below 1.08 g/ml was greater for HCV grown in PHH than for HCV grown in Huh-7.5.1 cells (compare siGFP in figure 7D with shLuc in figure 3B), as previously reported. [START_REF] Podevin | Production of infectious hepatitis C virus in primary cultures of human adult hepatocytes[END_REF] Nevertheless, a further shift of HCV RNA towards low buoyant density fractions was observed upon LPCAT1 depletion in PHH: the percentage of total viral load present below 1.09 g/ml was 47.01 ± 0.73% for LPCAT1-depleted cells as compared to 35.91 ± 0.68% for control cells (figure 7D). These low-density fractions contained the excess of highly infectious particles produced upon LPCAT1 depletion (figure 7E), also coinciding with an excess of ApoB (figure 7F). Thus, in PHH as in Huh-7.5.1 cells but even more strikingly, LPCAT1 depletion appeared to favour the morphogenesis of HCV particles of high specific infectivity correlating with low buoyant density.

DISCUSSION

The human hepatocyte is both the cell type specialized in the biogenesis of VLDLs, which permit export of TAGs into the circulation, and the primary replication site of HCV, which circulates in the form of TAG-rich LVPs. Using two cell-culture-based models of human hepatocytes, we have here identified LPCAT1 as a host cell factor downregulated upon HCV infection. Depletion of this PL-remodelling enzyme was further found to affect TAG metabolism, leading to increased intracellular TAG content and eventually increased capacity of TAG secretion in the form of ApoB-containing lipoproteins. In infected hepatocytes this also resulted in increased production of HCV particles of lowest buoyant density, i.e., enriched in TAGs, which are those of highest infectivity. Thus, LPCAT1 downregulation by HCV appears as an original viral strategy to increase the virus specific infectivity. These data support the idea that HCV hijacks the hepatocellular lipid metabolism, which is devoted in particular to the efflux of TAGs in the form of VLDLs, for the benefit of LVP morphogenesis.

High-throughput profiling studies in the Huh-7/JFH1 model have suggested that HCV regulates the expression of host genes involved in a variety of hepatocellular processes, including liver lipid metabolism, at the transcriptional, translational and post-translational levels. [START_REF] Blackham | Gene expression profiling indicates the roles of host oxidative stress, apoptosis, lipid metabolism, and intracellular transport genes in the replication of hepatitis C virus[END_REF][START_REF] Colman | Genome-wide analysis of host mRNA translation during hepatitis C virus infection[END_REF][START_REF] Diamond | Temporal proteome and lipidome profiles reveal hepatitis C virus-associated reprogramming of hepatocellular metabolism and bioenergetics[END_REF][START_REF] Liu | Systematic identification of microRNA and messenger RNA profiles in hepatitis C virus-infected human hepatoma cells[END_REF] Our study reveals a decrease in the amounts of both LPCAT1 mRNA and protein in JFH1-infected Huh-7.5.1 cells, consistent with HCV-induced downregulation of LPCAT1 expression occurring at least partly at the transcriptional level. The PHH model is less suitable for such studies owing to lower levels of HCV infection and to the notorious autofluorescence of these cells that precludes in situ immunofluorescence analysis. [START_REF] Podevin | Production of infectious hepatitis C virus in primary cultures of human adult hepatocytes[END_REF] Our finding of a strong linear correlation between HCV infectivity titre and LPCAT1 mRNA amount is all the more striking in view of these limitations, supporting the occurrence of transcriptional downregulation of LPCAT1 by HCV in a patho-physiologically relevant model. Whereas LPCAT1 expression was unchanged in cells replicating an HCV subgenomic replicon, the sole expression of HCV core protein recapitulated the downregulation of LPCAT1 upon HCV infection. Although we cannot exclude an additional contribution of other HCV components, the virus core protein thus appears to play a major role in LPCAT1 downregulation. In fact this is not surprising, as this multifunctional protein has been reported to regulate the expression of many host genes aside from its role as a structural component of the virion. 35 36 Furthermore, expression of HCV core protein alone is sufficient to alter the LD-associated proteome in various cell models. 37 38 Interestingly, HCV-induced changes in LD composition may involve different molecular mechanisms, including displacing of LD-associated proteins owing to the own localisation of HCV core protein to LDs, as reported for adipose differentiation-related protein, [START_REF] Boulant | Hepatitis C virus core protein induces lipid droplet redistribution in a microtubule-and dynein-dependent manner[END_REF] and direct or indirect regulation of gene expression, as suggested here for LPCAT1.

In hepatic cells, an increased intracellular TAG content can result from increased fatty acid uptake, increased TAG synthesis, decreased fatty acid oxidation and/or decreased TAG-rich lipoprotein secretion. The latter mechanism cannot account for the increased intracellular TAG amount observed in LPCAT1-depleted cells because the secretion of newly synthesized TAGs was slightly increased in these cells. Another mechanism is suggested by the localisation of LPCAT1 to LDs. Like HCV core protein, [START_REF] Boulant | Hepatitis C virus core protein induces lipid droplet redistribution in a microtubule-and dynein-dependent manner[END_REF] LPCAT1 may displace LDassociated proteins involved in lipid metabolism by its mere presence at the LD surface. [START_REF] Kory | Protein Crowding Is a Determinant of Lipid Droplet Protein Composition[END_REF] Furthermore, LPCAT1 is a PL-remodelling enzyme that catalyses the acylation of lysophosphatidylcholine into phosphatidylcholine, 21 41 the reverse reaction being performed by phospholipases A2 that may also be present at the LD surface. [START_REF] Penno | Phospholipids and lipid droplets[END_REF] Lysophosphatidylcholine and phosphatidylcholine have a different shape, and the alteration of the surface lipid composition may lead to changes in LD stability (e.g., LD fusion, LD interaction with membranes) and in protein binding. [START_REF] Thiam | The biophysics and cell biology of lipid droplets[END_REF] Theoretically, LPCAT1 depletion should lead to an increased amount of lysophosphatidylcholine at the LD surface, a situation that does not favour LD fusion. [START_REF] Thiam | The biophysics and cell biology of lipid droplets[END_REF] In fact, we observed fewer LDs of larger size, which may reflect LD fusion, in agreement with Moessinger et al. 22 23 Nevertheless, the modification of the PL monolayer composition induced by LPCAT1 depletion probably initiates a reaction cascade that leads to impairment of protein interactions with the LD surface and further, possibly, with other organelles such as endoplasmic reticulum or mitochondria. Indeed, the trafficking of LD-associated proteins, including key enzymes of TAG metabolism, can be strongly modulated and the various mechanisms are only beginning to be understood as exemplified by recent reports. 16 42 43 Besides the association of HCV particles with TAG-rich lipoproteins, another clinical feature that links HCV infection with the host lipid metabolism is the high prevalence of liver steatosis, which is partly attributable to a direct viral effect. 1 44 LPCAT1 depletion was shown here to cause both an increase in the net intracellular TAG content, i.e., steatosis, and an increase in the production of HCV particles associated with TAG-rich lipoproteins, thus illustrating a possible link between liver steatosis and LVP morphogenesis. However, HCV infection is not sufficient to induce steatosis in cell culture [START_REF] Gottwein | Robust hepatitis C genotype 3a cell culture releasing adapted intergenotypic 3a/2a (S52/JFH1) viruses[END_REF] Upon LPCAT1 depletion in Huh-7.5.1 cells we observed an increased intracellular TAG content, an increased ApoB secretion and a slight but significant increase in the capacity of secretion of newly synthesized TAGs, whereas a recent study reported no alteration of the total amount of lipids and a decreased secretion of both ApoB and lipids in LPCAT1-depleted Huh-7 cells. [START_REF] Moessinger | Two different pathways of phosphatidylcholine synthesis, the Kennedy Pathway and the Lands Cycle, differentially regulate cellular triacylglycerol storage[END_REF] This apparent discrepancy may be partly due to the different Huh-7 sublines but is more likely explained by the different experimental conditions used. Since ApoB is stabilized by lipids or otherwise degraded, [START_REF] Davidson | Apolipoprotein B: mRNA editing, lipoprotein assembly, and presecretory degradation[END_REF] we cultured Huh-7.5.1 cells in medium supplemented with foetal calf serum, which contains lipids, and provided them with a physiological concentration of oleic acid (0.6 mM) to assess the TAG secretion capacity. By contrast, Moessinger et al. [START_REF] Moessinger | Two different pathways of phosphatidylcholine synthesis, the Kennedy Pathway and the Lands Cycle, differentially regulate cellular triacylglycerol storage[END_REF] cultured Huh-7 cells in serum-free medium for 3 days before lipid and ApoB analysis, and incubated them with only trace amounts of radiolabelled fatty acids for TAG secretion analysis. Under these conditions, the paucity of lipids available may have precluded TAG synthesis, hence ApoB stabilisation by lipidation and eventually lipoprotein formation.

LVPs found both in the liver and in the circulating blood of HCV-infected patients contain ApoB, the non-exchangeable Apo essential for VLDL scaffolding, and exchangeable Apos including ApoE. 4 5 48 The presence of ApoB and ApoE in the density range of the excess of HCV particles produced upon LPCAT1 depletion is compatible with their physical association but does not provide direct evidence for this hypothesis. Whereas a large body of evidence has underlined the essential role of ApoE both in production and infectivity of HCV, the literature contains conflicting reports as to whether ApoB is incorporated into HCV particles produced from Huh-7 cells and is necessary for production of infectious virus. [START_REF] Boyer | The association of hepatitis C virus glycoproteins with apolipoproteins E and B early in assembly is conserved in lipoviral particles[END_REF][START_REF] Chang | Human apolipoprotein e is required for infectivity and production of hepatitis C virus in cell culture[END_REF][START_REF] Owen | Apolipoprotein E on hepatitis C virion facilitates infection through interaction with low-density lipoprotein receptor[END_REF][START_REF] Hishiki | Infectivity of hepatitis C virus is influenced by association with apolipoprotein E isoforms[END_REF][START_REF] Lefevre | Syndecan 4 is involved in mediating HCV entry through interaction with lipoviral particle-associated apolipoprotein E[END_REF][START_REF] Catanese | Ultrastructural analysis of hepatitis C virus particles[END_REF][START_REF] Gastaminza | Cellular determinants of hepatitis C virus assembly, maturation, degradation, and secretion[END_REF][START_REF] Huang | Hepatitis C virus production by human hepatocytes dependent on assembly and secretion of very low-density lipoproteins[END_REF][START_REF] Jiang | Apolipoprotein E but not B is required for the formation of infectious hepatitis C virus particles[END_REF][START_REF] Merz | Biochemical and morphological properties of hepatitis C virus particles and determination of their lipidome[END_REF] One possible source of discrepancies between published data may be the intrinsic inability of Huh-7 cell line to fully lipidate ApoB and hence secrete genuine VLDLs. [START_REF] Podevin | Production of infectious hepatitis C virus in primary cultures of human adult hepatocytes[END_REF] Our HCV culture system in PHH provides a more relevant model for readdressing these issues, yet the lower viral titres make it even more difficult to purify and characterize hybrid LVPs present within a large excess of non-viral lipoproteins. 6 8 25 Nevertheless, our identification of LPCAT1 depletion as a single mechanism that increases both VLDL and LVP secretion suggests that HCV usurps at least some of the mechanisms of VLDL biogenesis for LVP morphogenesis, even if ApoB per se is not incorporated into HCV particles.

HCV is a leading cause of chronic liver disease ranging from steatosis to cirrhosis and hepatocellular carcinoma. Treatment against HCV has entered a new era with the recent development of directly acting antivirals, yet these drugs have a prohibitive price, are intrinsically at risk for selection of resistant variants and may not cure a small proportion of hard-to-treat patients among whom those infected with genotype 3, the HCV genotype most clearly associated with virally induced steatosis. 44 59 By contrast, host-targeting agents with anti-HCV activity are expected to confer a high barrier to drug resistance and a pan-genotypic coverage, and therefore may appear as a useful complement to virus-targeting agents in most difficult-to-treat patients. [START_REF] Baugh | Host-targeting agents in the treatment of hepatitis C: a beginning and an end?[END_REF] The intimate link of HCV with the host lipid metabolism designates lipid-modulating agents as putative antivirals. 3 61 Depending on their mechanism of action, however, a potential side effect of drugs in this therapeutic class may be to aggravate hepatic steatosis. With this in mind, targeting the LPCAT1-regulated lipid metabolism pathway in the opposite direction to that usurped by HCV may represent an attractive therapeutic approach because it is expected to reduce not only the viral titre but also hepatic steatosis.

  and a variety of mechanisms have been suggested to account for HCV-induced steatosis, including inhibition of with liver steatosis in HCV-infected patients.1-3 7 44 46 Thus, HCV-induced steatosis may only partially be accounted for by LPCAT1 downregulation. Furthermore, it remains uncertain whether steatosis per se has a role in LVP morphogenesis. The occurrence of liver steatosis in HCV-infected patients may simply represent the net result of the sum of perturbations of the host lipid metabolism that HCV induces primarily for the benefit of viral replication and LVP production added to nonviral steatogenic mechanisms of metabolic origin that can coexist to varying degrees in the same individual.

Figure 1 HCV

 1 Figure 1 HCV infection downregulates LPCAT1 in Huh-7.5.1 cells. Cells were inoculated

Figure 2

 2 Figure 2 Mechanism of HCV-induced downregulation of LPCAT1. Huh-7.5.1 cells were

Figure 3 LPCAT1

 3 Figure 3 LPCAT1 depletion in Huh-7.5.1 cells increases production of HCV particles

Figure 4 LPCAT1

 4 Figure 4 LPCAT1 depletion in Huh-7.5.1 cells alters lipid metabolism. Cells were

Figure 5 LPCAT1

 5 Figure 5 LPCAT1 depletion in Huh-7.5.1 cells increases TAG secretion capacity. Cells

Figure 6 LPCAT1

 6 Figure 6 LPCAT1 depletion in HCV-infected Huh-7.5.1 cells alters lipid metabolism.

Figure 7 HCVF

 7 Figure 7 HCV infection downregulates LPCAT1 in PHH and LPCAT1 depletion in

ACKNOWLEDGEMENTS

We thank J. McLauchlan for the R308 antibody, R. Everett for silencing plasmids, F.V.

Chisari for the Huh-7.5.1 cells and Cochin Imaging Facility for help with image analysis.

Funding FB was the recipient of postdoctoral fellowships from ANRS (France REcherche Nord&sud Sida-hiv Hépatites) and EPHE. ML and VP were the recipients of doctoral or postdoctoral fellowships from ANRS, respectively. This work was supported by ANRS, Université Paris Descartes and Inserm.

Confocal microscopy was performed using the CICC facilities of UMR_S 1138.

FOOTNOTES

FB and ML or SD and ARR contributed equally to this work.

Contributors FB, ML, SD and ARR conceived and designed the study. FB, ML, VP and DR performed the experiments. FB, ML, VP, SD and ARR analysed and interpreted the data. FB, ML, SD and ARR drafted or wrote the manuscript. SD and ARR obtained funding. All authors approved the final version for submission.

Competing interests None.

SUPPLEMENTARY MATERIAL TO:

Lysophosphatidylcholine acyltransferase 1 is downregulated by hepatitis C virus: impact on production of lipo-viro-particles Frauke Beilstein 1,2, † , Matthieu Lemasson 3, † , Véronique Pène 3 , Dominique Rainteau 4 , Sylvie Demignot 1,2, ‡ , Arielle R. Rosenberg 3,5, ‡ † or ‡ These authors contributed equally to this work. 1 Sorbonne Universités, UPMC Univ. Paris 06, Inserm, Université Paris Descartes, Sorbonne Paris Cité, UMR_S 1138, Centre de recherche des Cordeliers, F-75006, Paris, France; 2 EPHE, Ecole Pratique des Hautes Etudes, PSL Research University, Laboratoire de Pharmacologie Cellulaire et Moléculaire, F-75006, Paris, France; 3 Université Paris Descartes, EA 4474 « Hepatitis C Virology», F-75014, Paris, France; 4 UPMC Univ. Paris 06, ERL INSERM U 1157/UMR 7203, F-75012, Paris, France; 5 AP-HP, Groupe Hospitalier Cochin, Service de Virologie, F-75014, Paris, France

SUPPLEMENTARY MATERIALS AND METHODS

Antibodies

The antibodies against LPCAT1 (HPA022268) and actin (A3853) were obtained from Sigma-Aldrich (St. Louis, MO, USA), the anti-ApoE antibody (AB947) was from Millipore (Darmstadt, Germany), and the monoclonal antibodies against HCV core protein (C7-50) and NS3 protein (AB65407) used for confocal microscopy were from Abcam (Cambridge, UK).

The anti-HCV core protein antibody (R308) used for western blots was generously provided by J. McLauchlan 1 and the monoclonal antibody against human ApoB (1D1) was from the Heart Institute of the University of Ottawa (Canada). Secondary antibodies were appropriate Alexa Fluor 568-and 633-conjugated antibodies and horseradish peroxidase (HRP)conjugated IgGs (GE Healthcare, Chalfont St. Giles, UK).

Cell culture

HEK 293T cells were grown at 37°C in Dulbecco's modified Eagle medium (DMEM, Life technologies, Carlsbad, CA, USA) supplemented with 10% heat-inactivated foetal calf serum (FCS, GE Healthcare). Huh-7.5.1 cells 2 (a kind gift from F.V. Chisari, the Scripps Research Institute, La Jolla, CA, USA) were grown in DMEM supplemented with 10 mM hydroxyethyl piperazineethanesulfonic acid (HEPES) buffer (pH 7.3), 1% non-essential amino acids, 2 mM L-glutamine, 100 μg/ml streptomycin, 100 U/ml penicillin (all Life technologies) and 10% heat-inactivated FCS, at 37°C in a humidified 5% CO 2 atmosphere.

PHH freshly isolated from HCV-seronegative adult patients were purchased from Biopredic (Rennes, France) and maintained in primary culture as described previously. 3 Briefly, PHH were resuspended in complete medium consisting of Leibovitz's L-15 medium (Invitrogen, Cergy Pontoise, France) supplemented with 26 mM NaHCO 3 , 100 μg/ml streptomycin, 100 U/ml penicillin, 100 IU/l insulin (Novo Nordisk, Bagsvaerd, Denmark) and 10% heatinactivated FCS, and seeded onto 6-well plates pre-coated with calf skin type I collagen (Sigma-Aldrich) at a density of 1.6 x 10 5 viable cells/cm 2 . The medium was replaced 16 h later with fresh complete medium supplemented with 1 μM hydrocortisone hemisuccinate (SERB, Paris, France), and cells were left in this medium until HCV inoculation or siRNA transfection. The cultures were maintained in complete medium at 37°C in a humidified 5% CO 2 atmosphere.

HCV infection

A high-titre stock of JFH1-HCV 4 was produced as described previously. 3 Huh-7.5.1 cells and PHH were inoculated at a multiplicity of infection of 0.2 and 2 ffu per cell, respectively. The culture medium was replaced with the inoculum diluted in the smallest volume of fresh medium sufficient for covering the cells. The inoculum was removed after a 4-h incubation at 37°C. Cells were washed three times with phosphate-buffered saline (PBS) and maintained in culture for the indicated times post-inoculation.

Subgenomic replicon transfection

The HCV subgenomic R-Luc/JFH-1-replicon (SGR) was provided by Taka Kato (NIID, Tokyo, Japan). 5 The plasmid was linearized at the XbaI site, purified by phenol-chloroformisoamyl alcohol extraction and used as template for in vitro transcription by T7 RNA polymerase with the RiboMAX TM large scale RNA production system (Promega), according to the manufacturer's instructions. The resulting RNA were purified by use of TRIzol RNA isolation reagent (Life Technologies), and their quality and quantity were evaluated by electrophoresis and NanoDrop spectrophotometry (Thermo Scientific). Huh-7.5.1 cells in mid-log phase were detached with trypsin, and resuspended at 10 7 cells/ml in Opti-MEM R (Invitrogen). Then 400 μl of this suspension were mixed with 10 μg of in vitro transcribed RNA in an electroporation cuvette (0.4-cm gap), and pulsed once at 0.28 kV, 975 μF, in a Gene PulserR II electroporator (Bio-Rad, Marne La Coquette, France). Immediately after electroporation, cells were plated at a density of 5.10 4 cells/cm 2 and maintained in culture for the indicated times post-electroporation.

Plasmid cloning and transfection

The pUC/JFH-1 plasmid was provided by Takaji Wakita (NIID, Tokyo, Japan). 4 HCV core sequence was amplified from pUC/JFH-1 plasmid using the following primers: All plasmid transfections were performed using Lipofectamine 2000 transfection reagent (Life Technologies), according to the manufacturer's instructions.

Gene silencing

The use of lentiviral vectors expressing small hairpin RNA (shRNA) was described previously. 6 Briefly, HEK 293T cells were co-transfected with three plasmids: pVSV-G, pCMVDR8.91 (provided by D. Trono [http://ww1.tronolab.com/]) and the shRNA-encoding plasmid based on pLKO.1puro (the 19-nucleotide sequences used for silencing LPCAT1 and luciferase were GGAAGATCACATTCGCTGA and GTGCGTTGCTAGTACCAAC, respectively). The culture supernatant containing recombinant lentivirus was harvested 3 days post-transfection and used to transduce Huh-7.5.1 cells in the presence of hexadimethrine bromide (5 μg/ml polybrene, Sigma-Aldrich). After overnight incubation, the cells were placed in selective medium containing 2 μg/ml puromycin (Sigma-Aldrich) for 1 day, then culture supernatant was changed for fresh selective medium and cells were cultured in this medium 1 additional day. Finally, culture supernatant was replaced by complete medium and the next day cells were inoculated or not with HCV.

Three days post-seeding, PHH were transfected with 20 nM siRNA (Eurogentec) using RiboCellin (BioCellChallenge) according to the manufacturer's instructions. The siRNA sequences were GGACCUGCCUAAUUACCUUtt and GAACGGCAUCAAGGUGAACtt for LPCAT1 and GFP, respectively. After 3 days, cells were washed with PBS then inoculated with HCV.

RT-qPCR

Total RNA was isolated from cells using TRI Reagent (Molecular Research Center, Cincinnati, OH, USA), according to the manufacturer's protocol. Reverse transcription was performed with 1 μg of total RNA in a total volume of 20 μl. PCR reactions were performed in quadruplicate using a Light-cycler instrument (Roche, Basel, Switzerland). For each reaction, a 1:400 final dilution of the reverse transcription product was used with 0.4 μM (final concentration) of each primer in SYBR Green I master mixture (Roche). PCR conditions were one step of denaturation (8 min at 95 °C) followed by 45 cycles (each cycle consisting of 10 s at 95 °C, 10 s at 60 °C and 10 s at 72 °C). Expression of LPCAT1, LPCAT3 or LPCAT4 transcripts was normalised to that of human ribosomal protein L19 transcript. The following oligonucleotide primers were used (for each couple, the forward primer is listed first and the reverse primer second): L19 (AAGATCGATCGCCACATGTAT / TGCGTGCTTCCTTGGTCTTAG), LPCAT1 (CGATGTCCTCCATCGTGA / GGCCGTATATACTGGATCAGAGTT), LPCAT3 (ACCAGGAAAGATACCAAACAGC / GGTAGAAAAGGCCCAGACTCA) and LPCAT4 (CCCTTCGTGCATGAGTTACA / ATAAAGGCCAGAAGCACTCG).

Western blotting

Proteins were resolved on 10% (5% for ApoB) sodium dodecyl sulphate-polyacrylamide gels and transferred to nitrocellulose membrane (Hybond ECL, GE Healthcare). Blots were blocked for 30 min with 5% skimmed milk in TBS-Tween consisting of 20 mM Tris-HCl (pH 7.6), 137 mM NaCl and 0.1% Tween 20, then probed with primary antibodies diluted in TBS-Tween containing 1% skimmed milk followed by appropriate peroxidase-conjugated secondary antibodies. Actin was used as a loading control. Blots were developed by enhanced chemiluminescence using ECL reagent (GE Healthcare). Bands were visualised using the Image Reader LAS-4000 (Fujifilm, Tokyo, Japan) and quantified using ImageJ software.

Confocal microscopy

Cells on glass coverslips were fixed with 4% paraformaldehyde for 10 min at room temperature and, after two washes with PBS, permeabilized with 0.03% saponin in PBS for 30 min. After incubation with antibodies against LPCAT1 and HCV core protein (C7-50) or HCV NS3 protein for 1 h at room temperature, the coverslips were washed three times with

ApoB and ApoE quantification

ApoB and ApoE levels in filtered culture supernatants or iodixanol gradient fractions were quantified by using the total human ApoB or ApoE ELISA assay from ALerCHEK (Springvale, MA, USA), respectively, according to the manufacturer's instructions.

Virological analyses

Intracellular amounts of negative-strand HCV RNA were quantified by a RT-qPCR technique described previously. 7 HCV RNA amounts in filtered cell culture supernatants or in iodixanol gradient fractions were quantified by the Abbott RealTime HCV viral load assay and expressed as international units (IU)/ml; infectivity titres were assessed by focus-formation assay and expressed as ffu/ml. 3 8 Specific infectivity values were calculated as follows: 10 3 x infectivity titre (ffu)/HCV RNA level (IU). The buoyant densities of viral particles were determined by isopycnic iodixanol gradient ultracentrifugation, as previously described. 3

Lipid analyses

Quantification of the TAG mass was done on dried lipids extracted from cells with chloroform/methanol (2:1, v/v) using the PAP150TG kit (BioMérieux) according to the manufacturer's instructions with the following modifications: 0.5 ml of the buffer provided with the kit was added to the dried lipids and tubes were sonicated for 10 s in a water bath sonicator; then 0.5 ml of the 2-fold concentrated kit reagent was added and absorbance was measured after a 1-h incubation at 37°C.

The analysis of lipid secretion capacity was performed as described previously. 9 Briefly [1-

14 C] oleic acid (Perkin Elmer Life Sciences, Waltham, MA, USA) (1 μCi per ml of final medium to prepare) was added to non-radioactive oleic acid (6 µl from a 100 mM stock solution in chloroform/methanol 2:1 (v/v) per ml of final medium to prepare) before drying under a stream of nitrogen, followed by incubation with FCS (0.1 ml per ml of final medium to prepare) for 1 h at 37 °C to obtain oleic acid in complex with BSA. The mixture was adjusted to 1 ml with culture medium without serum and supplied to the cells for the last 24 h of culture. Lipids were extracted from cells and media and fractionated by thin layer chromatography (TLC). The radioactive bands of the TLC plates were excised and the radioactivity was quantified by liquid-scintillation counting to evaluate the incorporation of [1-14 C] oleic acid into lipids. For normalisation, protein concentration of cell lysates was measured using the BC Assay (Interchim, Montluçon, France), according to the manufacturer's instructions.

Cytotoxicity assay

To assess the potential cytotoxicity of LPCAT1 silencing, the activity of lactate dehydrogenase released into culture supernatants was measured in triplicate using the CytoTox 96 Non-Radioactive Cytotoxicity Assay (Promega, Madison, WI, USA), according the recommendations of the manufacturer.

Supplementary Figures


Marwan Ghanem

Olivier Fourmaux
email: olivier.fourmaux@upmc.fr

Fabien Tarissan

Takumi Miyoshi

Takumi

P2PTV Multi-channel Peers Analysis

come

I. INTRODUCTION

After being the support of the data and voice convergence, the Internet has become one of the main video providers (live TV or video on demand). Those multimedia services were previously confined to the video broadcasting infrastructures (terrestrial, satellite or hybrid fibre/coax). The transmission of broadcasting quality TV streams in High Definition (or soon in Ultra High Definition 4K/8K) requires the use of huge amount of communications networks resources. The development of dedicated technologies to distribute these contents is either local and limited to a residential operator (IPTV), or global but complex and expensive (CDN).

The alternative to these limited or expensive technologies could be partly or completely based on P2P. In this context, peers communicate via virtual mesh networks (overlays) that connect them. The dynamic topology of these overlays depends on many parameters: location of resources, network status, internal mechanisms of peers, as well as the distributed content and the behaviour of the peers directly involved as consumers of content.

In the case of TV streams, specific constraints require significant adaptation of P2P (specifically related to realtime aspects). A new application class realizes this kind of service: P2PTV. For these applications, the content consists of audio/video streams to distribute in real-time to a large number of receivers. The large number of streams and their intrinsic real-time characteristics generate timing constraints which are difficult to guarantee in the considered dynamic environment. Strict compliance with these constraints impacts directly on the peer's quality of experience and thus on his behaviour, which in turn impacts the overlay.

P2PTV applications broadcast hundreds of channels, each carrying a live audio/video content to thousands of peers. Each channel corresponds to an overlay integrating peers wishing to receive its contents, and these peers can switch channels at any time (usually depending on the contents) adding an extra dynamic factor. This is this last dynamical aspect we intend to address in the present paper. Although several works have been proposed to measure and analyse the activity on P2PTV infrastructure, tracking the presence of peers active on different channels remains challenging. Here we show that we can rely on noninvasive measurement techniques such as Wireshark to track peers switching from one channel to another. To do so, we rely on 2 datasets obtained by measurements campaigns that coordinate several points of measure on a well known P2PTV infrastructure; we show that although the views obtained by such a measurement approach are partial, they are sufficient to detect multi-channel peers and highlight particularities in their behaviour, thus leading the way to a more in-depth investigations on the subject.

The remainder of the paper is organised as follow: we start by presenting existing works related to the analysis of P2PTV applications (Section II) before presenting the dataset used in the present paper (Section III). Then we turn to the study of the information contained in the dataset in order to analyse the behaviour of multi-channel peers. We start by exploiting the dataset by aggregating all the information (Section IV) before refining our analysis using narrowed views provided by sliding time windows (Section V). Then we show that comparing the two datasets gives insight on how diffusio through P2PTV has evolved (Section VI). Finally we conclude the paper by presenting the perspectives opened by the present study (Section VII).

II. RELATED WORKS

Several studies and experiments have been done to analyse P2PTV applications [START_REF] Takumi | A case study of large scale p2p video multicast[END_REF], [START_REF] Alessandria | P2p-tv systems under adverse network conditions: A measurement study[END_REF], [START_REF] Spoto | Analysis of pplive through active and passive measurements[END_REF], [START_REF] Valenti | Accurate, fine-grained classification of p2p-tv applications by simply counting packets[END_REF], [START_REF] Tang | Topology dynamics in a p2ptv network[END_REF], [START_REF] Rossi | Black-box analysis of internet p2p applications[END_REF], [START_REF] Bermolen | Abacus: Accurate behavioral classification of p2p-tv traffic[END_REF]. Rossi et al.

proposed a framework for comparing P2P applications [START_REF] Rossi | Black-box analysis of internet p2p applications[END_REF] in which they define a set of observable features related to the protocols used by the applications. They highlighted the main similarities and differences between several P2P applications. In particular, they provided the key elements that open the way to passive analyses one can use when the applications are proprietary and no internal access is provided. Spoto et al. presented an investigation of PPLive using both active and passive measurements [START_REF] Spoto | Analysis of pplive through active and passive measurements[END_REF]. Using a crawler, they were able to classify the traffic into three classes as well as to show that only 15% of peers could be considered as active peers, revealing the potentials and limits of PPLive active measurement strategies.

Other works have been done on a more quantitative perspective [START_REF] Hei | A measurement study of a large-scale p2p iptv system[END_REF], [START_REF] Jia | Characterizing ppstream across internet[END_REF], [START_REF] Hoßfeld | A qualitative measurement survey of popular internet-based iptv systems[END_REF], [START_REF] Wu | Queuing network models for multi-channel p2p live streaming systems[END_REF]. Hei et al. proposed for instance a large scale measurement study of P2PTV, using a PPLive dedicated crawler [START_REF] Hei | A measurement study of a large-scale p2p iptv system[END_REF]. By collecting a huge amount of data in different scenario, they have shown that P2P IPTV peers have the same behaviour as the one of TV peers. They also demonstrated the existence of a small set of super-peers that highly contribute to the video uploading. Similarly, using a crawler, Jia et al. tried to characterize PPStream [START_REF] Jia | Characterizing ppstream across internet[END_REF]. They were able to find certain characteristics such as geographical clustering, arrival/departure patterns and playback quality.

Magharei et al. proposed a study on the structure of networks that most P2PTV applications used. They examine key issues with such structures and how bottlenecks can appear [START_REF] Magharei | Understanding mesh-based peer-to-peer streaming[END_REF].

By passively studying the traffic in P2PTV infrastructures, Silverston et al. were able to compare different applications pointing out their similarities and differences [START_REF] Silverston | Traffic analysis of peer-to-peer iptv communities[END_REF]. Looking more deeply into the traffic, they discovered that signalling traffic tends to have a large inter-packet time while video traffic tends to have a smaller one. They also looked into peer behaviour, revealing that the vast majority of peers tend to receive data more than they send, pointing out potential reciprocity issues.

There are also few studies more specific to the peer behaviour and the multi-channel observations [START_REF] Cha | Watching television over an ip network[END_REF], [START_REF] Mendes | P2p-tv service and user characterization[END_REF], [START_REF] Wang | Network impact of p2p-tv zapping[END_REF], [START_REF] Mizutani | Traffic Analysis in Concurrent Multi-Channel Viewing on P2PTV[END_REF]. Wang et al. analysed the traffic that is characteristic to peers switching from one channel to another [START_REF] Wang | Network impact of p2p-tv zapping[END_REF]. Using the most popular P2PTV applications such as PPLive or SOPCast, they monitored a channel for a given period and then suddenly changed to another one. They revealed that switching has a huge impact on the network efficiency as it increases the overload and adds a significant overhead. Finally, Mitzutani et al. were able to detect video servers as well as to find new characteristics of PPTV by monitoring multi-channel PPTV traffic [START_REF] Mizutani | Traffic Analysis in Concurrent Multi-Channel Viewing on P2PTV[END_REF].

III. DATASET

In this section, we present the datasets that were used during this work. It consists in two distinct measurement campaigns conducted on PPTV at a different time. The key aspect of those campaigns is that they coordinated traffic measurements from different points of measure. Concretely, the measurements For capturing and monitoring traffic, Wireshark [START_REF]Wireshark[END_REF], a well-known packet sniffer, was running on every measurement PC during the campaigns. Therefore we have the totality of the traffic that has been sent and received by our machines.

The first dataset was extracted from a 14 hour long traffic measured on December 2013 using 12 points of measure, while the second was extracted from a 7 day long traffic measured on July 2015 using 10 points of measure. We shall refer to those datasets later on as 2013 and 2015 respectively.

Table I presents the global properties of both datasets. We can particularly notice the huge amount of data exchanged (193 GB and 601 GB for 2013 and 2015 respectively). It is also worth noticing that, although 2015 dataset is way longer (12 times longer than 2013 dataset), it exhibits a less dense traffic than expected (the total payload size is for instance only 5 times higher), which is partly due to the lower number of channels.

As mentioned in many previous works [START_REF] Hei | Iptv over p2p streaming networks: the mesh-pull approach[END_REF], traffic generated by such applications can be shared out into two categories. Control (or signalling) traffic which could be either a heart beat signal, a peer's list exchange or buffer maps in form of a bit vector, representing the data a peer has available or missing from its video buffer. The second kind of traffic is data (or video) traffic which is transferred in the form of data chunks. Most P2PTV applications were initially designed as a P2P mesh-based architecture [START_REF] Magharei | Understanding mesh-based peer-to-peer streaming[END_REF] including PPlive and PP-Stream [START_REF] Jia | Characterizing ppstream across internet[END_REF]. Nowadays, most applications use hybrid P2P infrastructures with super-peers to guarantee that the viewers receive a better quality. Each transmitted channel by a P2PTV application would have its own P2P mesh-based network, which contains two types of peers. The first are the superpeers that are servers, are active the whole time and appear in more than one P2P mesh in the same slot of time with the goal of maintaining the infrastructure of such systems. The second type is the regular peers that might appear in more than one channel due to switching behaviours [START_REF] Wang | Network impact of p2p-tv zapping[END_REF]. In this section, we exploit all the information contained in the collected data in order to detect multi-channel peers. We start by presenting global properties of the dataset (IV-A) that complete those provided in Section III. Then we focus on the topics of this paper, namely the presence of multi-channel peers (Section IV-B). Note that in the rest of the section, if not mentioned otherwise, we will present the results on the 2015 dataset as it is the more recent and the larger one.

A. Tracking exchanges of video content

As mentioned in Section III, since we monitored the entire traffic using Wireshark, it is necessary to distinguish exchanges depicting the activity of a peer watching a TV program from the traffic dedicated to controlling the P2P infrastructure. To do so, it is reasonable to assume that a peer actively watching a TV program will trigger exchanges of video content, thus leading to a stream of packets with a significant size.

Figure 1 shows the inverse cumulative distribution of the payload size (plain circles). One can clearly observe two regions. The first region involves packets smaller than 1000 bytes (68%) while a second region involves packets larger than 1000 bytes (32%). Obviously, the first one is related to control traffic while the second one can be categorized as video exchanges. In order to simplify the analysis, we will further make the assumption that any packet whose size is less than 1000 bytes is not a video content. Furthermore, a peer involved in at least one traffic containing a video will now be referred to as an active peer.

In order to get a better image of the peers behaviour, we also display on Figure 1 the inverse cumulative distribution of the maximal payload size a peer has exchanged (cross dots). In other words, a (x, y) dot in this plot indicates that y% of the peers have exchanged packets with x bytes at most. This plot reveals that only 25% of the peers are actively involved in video traffic

B. Presence multi-channel peers

Turning now to the analysis of multi-channel peers, we start by studying the proportion of peers identified in several channels. It is worth remembering that the dataset consists of partial and independent measurements of the 10 channels (Section III). Thus, it is absolutely not guaranteed to detect such a behaviour.

Figure 2 presents the distribution of the peers over the 10 channels. For each channel, we show the number of all peers detected (left bar in blue) and the number of active peers (right bar in green) as defined above. In addition, we show for each of these quantities the fraction of the peers that are also detected in at least one other channel (bottom part of the bars with hatched lines). We will therefore refer to those peers as multichannel peers (or multi peers for short).

The chart shows that the majority of the peers are concentrated in three channels. More importantly, it answers the first question raised in this paper which confirms that the measurement approach on which we rely on enables us to detect peers that appear in several channels. It turns out that 8% of the peers are multi-channel peers. Moreover, one can notice that this statement still stands even if we focus only on peers that exchange video contents, although the ratio then drops to 0.8% of the total number of peers. However, the ratio of multi-channel peers actively watching a TV program still involve 3% of the active peers, thus revealing that a non negligible fraction of peers exchanging video content are involved in several channels. Note that this percentage could be overestimated if distinct active peers are recorded with a single identifier, which would be the case if they are behind a NAT. Although we did not investigate deeply this question in a systematic manner, we manually looked in detail the most susceptible peers of the dataset. Our preliminary results show that this is not the case and that those IPs detected on several channels depict a unique peer.

V. EXPLOITING SLIDING TIME WINDOWS

The results presented in the previous section are interesting as they highlight the presence of multi-channel peers but aggregating all the information contained in the dataset prevents further refinement regarding the real behaviour of the peers. In particular, it does not allow to distinguish a peer that switches between different channels (referred to further as a switching peer) from a peer that stops watching TV programs and starts watching another one way later on. To overcome this issue we propose in the present section to rely on the view provided by sliding time windows. More precisely, we sliced the whole dataset into non-overlapping windows of similar size and studied whether it enables an indepth analyses of multi-channel peers. As one can expect, the size of the window becomes a key parameter in this approach. Since we focus on tracking the presence of switching peers, the size has to be short enough to discard peers that disconnect but it also has to be long enough to be able to detect the presence of the peers in several channels. Therefore we decided to use a 1 minute size window.

In the following sections, we will investigate how this approach enables us to distinguish between different types of peers (Section V-A) and different types of super-peers (Section V-B).

A. Different peer behaviour

By relying on short-time windows, we are now able to detect peers present simultaneously on different channels. In particular, we can determine the number of peers present in different channels for each slot of 1 minute. Besides, when such a peer is detected, one can track how many channels it is involved in.

Figure 3 presents the inverse cumulative distribution of the average number of channels on which a peer is simultaneously present; for all the peers (plain circles) and for active peers (cross dots). In both cases, there is a large amount of peers involved in 1 channel only, then the value decreases smoothly between 1 and 2. However, when it comes to values higher than 2, active peers (cross dots) are no longer present. While in case of all peers (plain circles), a few peers are close to 4 or 5 channels in average. Finally, it is remarkable that some peers appear in almost all the channel (especially when computing the average value) when using such a short-time window. This indicates an unusual behaviour and it is reasonable to consider such peers as super-peers, i.e. usually servers active the whole time whose purpose is to maintain the efficiency of the infrastructure (see Section III).

B. Different super-peers behaviour

The detection of video injectors raises the question of the role of super-peers present on several channels in the infrastructure. In particular, do they all participate actively to the diffusion of video content or do they also regulate and control the traffic over the P2P infrastructure?

In order to have a better understanding of this question, we compare in Figure 4 the average number of channels in which a peer is simultaneously present to the maximal size of a payload it sent/received. Each dot standing for a different peer, one clearly finds the super-peers detected previously but we can now refine their role: obviously, most of them only support control traffic since all the packets they exchange have a very low size. Thus, these super-peers are present only for administration and surveillance purposes, while the video injectors are clearly present in the top left part of the figure mixed with regular users.

VI. EXTENDING THE ANALYSES

In order to strengthen the results presented so far, we present in this section different analyses that allow to sustain our former claims. In particular, we show that the size of the time window has little impact on the former conclusions (Section VI-A). We also compare the results obtained on the 2015 dataset to the ones obtained on the 2013 dataset (Section VI-B). This allows to give insights on how diffusion through P2PTV has evolved.

A. Impact of the size of the window

All the results presented in Section V are strongly related to our choice of using a 1 minute time window. Although we claim that this choice is reasonable regarding our main objective (tracking multi-channel peer), one might wonder whether another value would have altered our conclusions. We therefore present in Figure 5 a figure similar to Figure 3 but for different time windows (1, 5, 10, 30 and 60 minutes). The figure shows that the main effect of increasing the size of the time window is to increase the number multi-channel peers. This is completely expected since more times gives more opportunity to switch between channels. But if the size of the window impacts quantitatively the results, the overall observations remain qualitatively valid. In particular, all curves present a sharp breach around the value of 2 and another one after 3. It is worth noticing that increasing the size of the time window also reveals that some super-peers cover all of the ten channels. Thus, this confirms our assumption that they do not correspond to regular peers.

B. Comparisons of the datasets

We turn now to the comparison between the two datasets. Using the same exact method explained in Section V-A), Figure 6 presents the inverse cumulative distribution of the average number of channels on which a peer is simultaneously present. Unlike Figure 3, the breach between values 2 and 4 is more prominent. More interesting is that we can see that super-peers are also present on the active peer curve (cross dot). Thus, we can deduce that between 2013 and 2015 the roles of super-peers have changed. In 2013, a super-peer could have been responsible for injecting video contents as well as administrating the infrastructure. In contrast, in 2015 each of these two roles seems to be taken in charge by a specific super-peer.

Finally, Figure 7 compares the average number of channels to the maximal payload size it has sent/received. We compare the figure with the one obtained on the 2015 dataset. Like in dataset 2015, the majority of super peers involved in several channels support only control traffic. However, in the 2013 dataset several super peers also support video traffic, which is in sharp contrast with what can be observed in the 2015 dataset. This is another indication of the important modification that took place between the two measurement campaigns.

VII. CONCLUSION

In this paper, we used two datasets obtained by two measurement campaigns relying on respectively 10 and 12 points of measure associated to 10 and 12 channels on a P2PTV system. We investigated how much information we can retrieve on multi-channel peers and showed that although the obtained view is partial, such a non-invasive measurement approach yet enables to detect peers present in several channels. Indeed, we were able to detect that respectively 8% and 16% of the total number of peers were present on more than one channels during the measurement campaign. This number drops to 2% and 3% if we restrain to active peers, i.e. peers involved in video content traffic. In addition, conducting an analysis based on sliding time windows led to precisely track peers switching from one channel to another one as well as to identify superpeers and to qualify their role in the infrastructure.

These results are interesting to characterize the behaviour of peers and extrapolate the behaviour of users. This is important for content providers to adapt the video supply, and for network operators to optimize their infrastructure.

These results also allow to envision promising lines of research. Since the measurement approach is light and does not require to have privilege access to the application itself or its infrastructure, we intend to conduct several measurement campaign targeting both different P2PTV systems and different measurement points to detect more characteristics related to the applications or to the users behaviour.

Figure 1 .

 1 Figure 1. Inverse CDF of payload size and maximal payload size/peer

Figure 2 .

 2 Figure 2. Distribution of the peers over the channels.

Figure 3 .

 3 Figure 3. Inverse CDF of the average multi-channel presence.

Figure 4 .Figure 5 .

 45 Figure 4. Average multi-channel presence v.s. maximal payload size

Figure 6 .

 6 Figure 6. Inverse CDF of the average multi-channel presence (2013 dataset).

Figure 7 .

 7 Figure 7. Average multi-channel presence v.s. maximal payload (2013 dataset).

  conducted on several PCs each running the application on a different channel thus, from the application's point of view, they acted as a regular peer. Every PC had an Internet connection provided by FLET'S HIKARI NEXT, 100 Mbps optical access service via Plata HIKARI Mate as an ISP in Japan.

	Table I
	PROPERTIES OF THE DATASET
	Property	2013	2015
	Duration	14 hours	7 days
	Number of channels	12	10
	Number of peers	100 809	289 710
	Maximum number of peers per channel	21 518	96 258
	Average payload size	504 B	408 B
	Total payload size	193 GB	601 GB

were

ACKNOWLEDGEMENTS

This study was partly supported by JSPS KAKENHI Grant Number 26420370. The datasets were captured by Koki Mizutani (Dataset 2013) and Naoki Takeuchi (Dataset 2015).