Léa Le Gléau

Christine Rouault

Céline Osinski

Edi Prifti

Antoine Hédi

Jean Soula

Pauline Debédat

Chloé Busieau

Karine Amouyal

Fabrizio Clément

Andreelli

Hédi Antoine Soula

Jean Debédat

Pauline Busieau

Chloé Amouyal

Karine Clément

Fabrizio Andreelli

Dr Agnès Ribeiro
email: agnes.ribeiro@sorbonne-universite.fr

Patricia Serradas
email: patricia.serradas_pacheco@sorbonne-universite.fr

Prof Patricia

Intestinal alteration of α-gustducin and sweet taste signaling pathway in metabolic diseases is partly rescued after weight loss and diabetes remission Running Head: Intestinal α-gustducin in metabolic diseases

Keywords: Intestinal endocrine cells, α-gustducin, obesity, type 2 diabetes, microbiota New control diet, EEC: enteroendocrine cell, EGA: entero-gastro anastomosis, FMT: fecal microbiota transfer

Intestinal alteration of α-gustducin and sweet taste signaling pathway in metabolic diseases is partly rescued after weight loss and diabetes remission Running Head:

Intestinal α-gustducin in metabolic diseases

INTRODUCTION

Glucagon Like-Peptide-1 (GLP-1) is an incretin hormone secreted from specialized Lenteroendocrine cells (EECs) which enhances glucose-dependent insulin secretion by twofold in the postprandial state. The mechanisms by which EEC link glucose detection to GLP-1 secretion is still debated but they involve both sugar transporters and sweet taste receptor [START_REF] Paternoster | Dissecting the Physiology and Pathophysiology of Glucagon-Like Peptide-1[END_REF]. This heterodimeric T1R2-T1R3 receptor encoded by TAS1R2 and TAS1R3 is coupled to the taste G-protein gustducin composed of α, β and γ subunits encoded respectively by GNAT3, GNB3 and GNG13 genes [START_REF] Ren | Sweet taste signaling functions as a hypothalamic glucose sensor[END_REF]. Several lines of evidence support that T1R2-T1R3 and α-gustducin are required for glucose-stimulated GLP-1 secretion. Indeed, these three proteins are present in human and rodent L-cells of the small intestine [START_REF] Jang | Gut-expressed gustducin and taste receptors regulate secretion of glucagon-like peptide-1[END_REF][START_REF] Rozengurt | Colocalization of the α-subunit of gustducin with PYY and GLP-1 in L cells of human colon[END_REF][START_REF] Steinert | The functional involvement of gut-expressed sweet taste receptors in glucose-stimulated secretion of glucagon-like peptide-1 (GLP-1) and peptide YY (PYY)[END_REF]. Furthermore, GLP-1 secretion can be elicited from mouse intestinal explants, and/or mouse (GLUTag) and human (NCI-H716) EEC lines by sweet taste receptor agonists -sucrose, glucose, fructose and sucralose [START_REF] Geraedts | Transformation of postingestive glucose responses after deletion of sweet taste receptor subunits or gastric bypass surgery[END_REF][START_REF] Jang | Gut-expressed gustducin and taste receptors regulate secretion of glucagon-like peptide-1[END_REF][START_REF] Margolskee | T1R3 and gustducin in gut sense sugars to regulate expression of Na+-glucose cotransporter 1[END_REF]. Moreover, glucose-stimulated GLP-1 secretion is nearly or fully abolished in α-gustducin -/-, TAS1R2 -/-and TAS1R3 -/-mice [START_REF] Geraedts | Transformation of postingestive glucose responses after deletion of sweet taste receptor subunits or gastric bypass surgery[END_REF][START_REF] Jang | Gut-expressed gustducin and taste receptors regulate secretion of glucagon-like peptide-1[END_REF][START_REF] Kokrashvili | T1r3 and α-Gustducin in Gut Regulate Secretion of Glucagon-like Peptide-1[END_REF]. This is also the case, when sweet taste receptor are inhibited or silenced using RNA of αgustducin on GLUTag and NCI-H716 cells [START_REF] Jang | Gut-expressed gustducin and taste receptors regulate secretion of glucagon-like peptide-1[END_REF][START_REF] Margolskee | T1R3 and gustducin in gut sense sugars to regulate expression of Na+-glucose cotransporter 1[END_REF]. Finally, the sweet taste receptor inhibitor, lactisole, reduces circulating levels of GLP-1 and PYY after intragastric or intraduodenal administration of glucose in humans [START_REF] Gerspach | The role of the gut sweet taste receptor in regulating GLP-1, PYY, and CCK release in humans[END_REF][START_REF] Steinert | The functional involvement of gut-expressed sweet taste receptors in glucose-stimulated secretion of glucagon-like peptide-1 (GLP-1) and peptide YY (PYY)[END_REF]. In EECs, the detection of carbohydrates and sweeteners by the sweet taste receptor and the activation of α-gustducin stimulate phospholipase C β2 (PLCβ2), produce inositol-trisphosphate (IP3), and increase intracellular calcium concentration leading to GLP-1 release. Sodium (TRPM5 and SCN2A) and calcium (CACNA1A) channels are also involved in this signaling pathway [START_REF] Depoortere | Taste receptors of the gut: emerging roles in health and disease[END_REF].

The incretin effect seems to be impaired in individuals with type 2 diabetes (T2D) owing to the combined effects of reduced GLP-1 secretion and impaired GIP action [START_REF] Meier | Incretins and the development of type 2 diabetes[END_REF][START_REF] Nauck | Reduced incretin effect in Type 2 (non-insulin-dependent) diabetes[END_REF]. Gastric bypass surgery is an effective tool in reducing body weight in individuals with severe obesity [START_REF] Mingrone | Metabolic surgery versus conventional medical therapy in patients with type 2 diabetes: 10-year follow-up of an open-label, single-centre, randomised controlled trial[END_REF] and results in the improvement or even complete remission of T2D [START_REF] Debédat | Long-term Relapse of Type 2 Diabetes After Roux-en-Y Gastric Bypass: Prediction and Clinical Relevance[END_REF]. The rise of postprandial GLP-1 secretion after Roux-en-Y gastric bypass (RYGB) may contribute to this improvement [START_REF] Borg | Progressive rise in gut hormone levels after Roux-en-Y gastric bypass suggests gut adaptation and explains altered satiety[END_REF][START_REF] Harvey | Hormone Changes Affecting Energy Homeostasis after Metabolic Surgery[END_REF][START_REF] Madsbad | GLP-1 as a Mediator in the Remission of Type 2 Diabetes After Gastric Bypass and Sleeve Gastrectomy Surgery[END_REF][START_REF] Peterli | Metabolic and Hormonal Changes After Laparoscopic Roux-en-Y Gastric Bypass and Sleeve Gastrectomy: a Randomized, Prospective Trial[END_REF][START_REF] Young | GLP-1 receptor agonists and basal insulin in type 2 diabetes[END_REF]. After RYGB the rapid delivery of undigested nutrients to the lower small intestine may affect the regulation of taste receptors and/or glucose transporters on EECs, resulting in an enhanced release of GLP-1 [START_REF] Amouyal | A surrogate of Roux-en-Y gastric bypass (the enterogastro anastomosis surgery) regulates multiple beta-cell pathways during resolution of diabetes in ob/ob mice[END_REF][START_REF] Larraufie | Important Role of the GLP-1 Axis for Glucose Homeostasis after Bariatric Surgery[END_REF]45) although a recent study demonstrated that lengthening of the intestinal bypass in RYGB does not affect GLP-1 secretion [START_REF] Miras | The Effect of Standard Versus Longer Intestinal Bypass on GLP-1 Regulation and Glucose Metabolism in Patients With Type 2 Diabetes Undergoing Roux-en-Y Gastric Bypass: The Long-Limb Study[END_REF]. Therefore, the mechanisms driving the alteration of enterohormone secretion in obesity and after RYGB might not be restricted to GLP-1 incretin effects alone [START_REF] Madsbad | GLP-1 as a Mediator in the Remission of Type 2 Diabetes After Gastric Bypass and Sleeve Gastrectomy Surgery[END_REF]. Gut microbiota, participates in environmental cues that affect EEC and is altered in metabolic diseases [START_REF] Pascale | Microbiota and metabolic diseases[END_REF]. RYGB improves microbiota dysbiosis, although most patients remain with low microbial gene richness despite major metabolic improvement and weight loss [START_REF] Prifti | Major microbiota dysbiosis in severe obesity: fate after bariatric surgery[END_REF].

We have previously shown a positive association between jejunal GLP-1 cell density and fatconsumption in individuals with severe obesity [START_REF] Aranias | Lipid-rich diet enhances L-cell density in obese subjects and in mice through improved L-cell differentiation[END_REF]. Moreover, we showed that T2D is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF].

Our hypothesis is that the sweet taste transduction pathway and the taste gustducin Gprotein are altered in metabolic diseases contributing to a defective sugar detection, inappropriate plasma enterohormone concentrations and reduced incretin effect.

Taking advantage of an RNA sequencing previously performed in human EECs, we examined the relationship between obesity and T2D and the GNAT3 expression in these cells. We studied the expression of Gnat3 and other genes involved in sweet taste transduction pathway during the onset of metabolic diseases in mouse models fed for 1 to 12 weeks, either on control, high-fat (HFD) or high-fat and high-fructose (HFD-HF) diets as well as in metabolic improvement induced by an entero-gastro anastomosis (EGA) mouse model [START_REF] Troy | Intestinal Gluconeogenesis Is a Key Factor for Early Metabolic Changes after Gastric Bypass but Not after Gastric Lap-Band in Mice[END_REF]. Furthermore, to investigate the role of gut microbiota on α-gustducin expression, we performed fecal microbiota transfer.

MATERIAL AND METHODS: Human study

This study is ancillary to a previously published studies [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF] that included subjects with severe obesity involved in a bariatric surgery program (RYGB) carried out at the Pitié-Salpétrière University Hospital, Nutrition and visceral Surgery Departments (Paris, France).

Obese subjects were stratified according to their metabolic status, and two groups were constituted: obese subjects without T2D (Ob, n= 14) and obese subjects with T2D (ObD, n= 13) receiving antidiabetic treatments or yet untreated [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF]. Results related to EEC preparation, RNA-sequencing and its subsequent analysis have been already published [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF].

The RNA-Seq gene expression data and raw fastq files are available on the GEO repository (www.ncbi.nlm.nih.gov/geo/) under accession number GSE132831.

Animals and diets

Six-and 3-week-old C57BL/6j male mice were obtained from Janvier Labs (France). For the EGA surgical procedure, 7-week-old C57BL/6j male mice were obtained from Charles River Laboratories (France). Mice were housed in groups and maintained on a 12-hour light-dark cycle with ad libitum access to water and diet: chow diet (CD: 5% Kcal fat -reference A03-10, Safe-Diets) or high fat diet (60% Kcal fat -D12492, Research Diets) with (HFD-HF) or without (HFD) 30% fructose (Sigma) in drinking water. Food and bedding were irradiated at 10 kGy. Experimental procedures agreed with the French ethical guidelines for animal studies and were approved by the Regional Animal Care and Use Ethic Committee Charles Darwin C2EA -05, agreement number (#17401).

EGA surgical procedure

The EGA surgical procedure was performed as previously described [START_REF] Troy | Intestinal Gluconeogenesis Is a Key Factor for Early Metabolic Changes after Gastric Bypass but Not after Gastric Lap-Band in Mice[END_REF]. In brief, HFD mice undergoing surgery were fasted for 6 h and anaesthetized with 2% isoflurane (Abbott) and air/oxygen. Analgesia was delivered intraperitoneally 30 min before surgery (Buprenorphine, 0.03 mg/kg, Axience SAS) and at the end of the procedure (Ketoprofen, Merial, 1%, diluted 1/100, 200 µL per mouse). Antibioprophylaxy was delivered sub-cutaneous at beginning of the surgery (ceftriaxone 100 mg/kg, Hospira,). The procedure consisted of a pyloric sphincter ligature, followed by an entero-gastric anastomosis connecting the distal jejunum to the stomach, excluding the duodenum and the proximal jejunum from the alimentary tract.

Sham-operated mice (simple laparotomy) underwent the same duration of anaesthesia as EGA-operated mice. In both groups, the laparotomy was repaired in two layers. All mice were maintained on a standardized post-operative protocol to monitor pain, body weight and hydration, subcutaneous injection of saline serum and additional analgesia was given as necessary. The mice had access to water and high fat diet right after surgery. Experimental procedures were agreed with the French ethical guidelines for animal studies and approved by the Regional Animal Care and Use Ethic Committee Charles Darwin C2EA -05, agreement number (#2762).

Fecal microbiota transfer

Mice undergoing 12 weeks of CD and HFD-HF diets were used as fecal microbiota donors.

In the morning, feces from the donor mice were collected in sterile containers and immediately diluted in sterile, anoxic Ringer buffer containing 1 g/L L-cysteine as a reducing agent. An aliquot of inoculum was snap frozen in liquid nitrogen and stored at -80•C for subsequent bacterial composition analysis.

Colonization was achieved by intragastric gavage with 200 µL of inoculum once per day for 3 consecutive days as described previously [START_REF] Roy | Comparative Evaluation of Microbiota Engraftment Following Fecal Microbiota Transfer in Mice Models: Age, Kinetic and Microbial Status Matter[END_REF]. 3-week old mice received by gavage with inoculum of CD microbiota (MRCD) or HFD-HF microbiota (MRHFD-HF) and were kept on HFD-HF diet. Gloves were changed between the handling of each group, and all instruments and working area were disinfected with hydrogen peroxide 3% vol/vol.

Microbiome composition analysis

Feces from donor mice after 12 weeks of diet, as well as those from recipient mice 3 and 12 weeks after microbiota transfer and the inoculum solution were frozen in liquid nitrogen and stored at -80°C upon usage.

Detailed pipeline information was previously described in [START_REF] Lu | Oxford Nanopore MinION Sequencing and Genome Assembly[END_REF] with modifications described in [START_REF] Alili | Exploring Quantitative Metagenomics Studies using Oxford Nanopore Sequencing: A Computational and Experimental Protocol[END_REF]. Briefly, fecal DNA was extracted using the PureLink™ Microbiome DNA Purification Kit (Invitrogen) according to the manufacturer's instructions. Bacterial DNA from these samples was sequenced using the minION nanopore DNA sequencing from Oxford Nanopore Technologies (ONT). DNA libraries were prepared using the Ligation Sequencing Kit 109 (SQK-LSK 109, ONT), with multiplexing (EXP-NBD104, ONT), so that up to 12 samples could be sequenced at the same time on the same R9 flow-cell. After sequencing, raw fast5 read files generated by the MinKNOW™ software (ONT) were base called and demultiplexed using Guppy (version 2.1.3). Taxonomic binning was performed as follow: sequences were then mapped on an 8,000 reference genomes database using Centrifuge and the assignment was further quality-checked using Minimap2. From this step, species-level abundance tables were built and integrated with taxonomic information and sample metadata in phyloseq objects for subsequent analyses with phyloseq R package. Samples were rarified to 35,000 reads per sample before quantitative analyses. All analyses on abundance data were performed after rarefaction and exclusion of rare taxa (detected in less than 20% of the samples). Relative abundances values were calculated for each sample by dividing the rarefied abundances by the sum of the abundances.

Body composition

Mouse body composition was measured in vigil mice using the Bruker Minispec mq10 NMR (Bruker Optics) after 3 and 12 weeks of diet, 3 and 12 weeks after microbiota transfer, 1 week before the EGA surgery and at day 28 after the EGA surgery. Animals were placed in a clear plastic cylinder (50 mm in diameter) lowered into the device for the duration of the scan (<2 min).

Plasma parameter measurements

Blood was withdrawn from the tail vein using EDTA as the anticoagulant. Blood glucose levels were evaluated using a glucometer (Accuchek performa ® , Roche). Plasma triglycerides were measured using Triglycerides FS kit from Diasys (Diagnostic Systems).

Plasma insulin was determined by Elisa (Alpco, Eurobio). For active GLP-1 determination, blood was collected into EDTA coated Microvettes (SARSTEDT) preloaded with Dipeptidyl peptidase-4 inhibitor (Merck, Millipore). Blood was immediately centrifuged at 4 °C to separate the plasma from the whole blood and stored at -20°C until analysis. Plasma insulin, glucagon, C-peptide, PYY, active GLP-1, GIP and Leptin concentrations were assessed by MILLIPLEX assays (MMHE-44 K Milliplex, EMD Millipore).

Glucose and insulin tolerance tests

All experiments were performed on conscious mice. A glucose tolerance test (2g/kg body weight) was performed on mice fasted overnight for 14-16 h (diet and microbiota transfer experiments) or fasted for 6 hours (EGA experiment). For the insulin tolerance test, animals fasted for 6 hours were injected intraperitoneally with 0.5 or 1 unit of insulin/kg body weight (Novorapid ® , Novo-Nordisk). For both tests, blood glucose was measured at the tail vein with an AccuCheck Performa glucometer (Roche Diagnostics) at indicated times.

Intestinal tissue collection

Human epithelial cells from obese patient jejunum were collected as described in our previous study [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF]. Mice undergoing CD, HFD or HFD-HF were euthanized by cervical dislocation, the jejunum was dissected and the mucosa was scrapped to collect epithelial cells before FACS procedure.

EGA-operated and sham-operated mice were anesthetized and decapitated 4 weeks after surgery. Duodenum, proximal and distal jejunum and ileum were frozen in liquid nitrogen and stored at -80°C. Total RNA was extracted using Rneasy mini kit (Qiagen).

Mice undergoing fecal microbiota transfer (FMT) were euthanized by cervical dislocation.

The jejunum was turned over and cut before dissociating the epithelium in a cell recovery solution (corning). Total RNA was extracted using Tri-reagent ® (Molecular Research Center.

Inc.).

FACS for enriched-EEC preparation in mouse

We adapted to mice the FACS method for enriched-EEC preparation in humans described in [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF]. Epithelial cells were scrapped and rinsed in FACS buffer (PBS, 3% FCS, 2 mM EDTA), blocked with Fc Receptor Binding Inhibitor Antibody (eBioscience) and stained with the following antibodies: CD45-BV421 (Bio Legend), CD326-APC (Biolegend) and CD24-FITC (Biolegend). Dead cells were excluded with propidium iodure (eBiosciences). During sorting experiments, cells were placed in FACS buffer with RNAse inhibitor (Life Technologies).

CD24 marker was used to select enteroendocrine, Paneth and stem differentiated cells, CD45 to get rid of B lymphocytes that also expressed CD24 and CD326-APC to select epithelial cells. CD45-negative, CD326 positive, CD24-positive EEC enriched cell fraction was on a jet-in-air flow cytometer, the MoFlo Astrios with Summit software (Beckman Coulter).

Gene expression analysis

In CD45+, CD24-and CD24+ sorted mouse cells, gene expression was measured using QuantiGene TM Plex assay kit (QGP-150-M20021104, ThermoFisher). HPRT, PPIB, PGK1 and RPS18 were used for normalization [START_REF] Verbist | Analyzing magnetic bead QuantiGene® Plex 2.0 gene expression data in high throughput mode using QGprofiler[END_REF]. Relative quantification was determined by the median fluorescent intensity.

Otherwise, reverse transcription using M-MLV reverse transcriptase (Promega) and quantitative PCR with SybrGreen were performed. Gene expression was normalized with RPLP0 expression in mice and cyclophilin expression in humans to obtain relative quantification using the 2 -ΔΔCt method. All primers are presented in Table 1.

Statistical analysis

We used GraphPad Prism and R softwares for all statistical analysis. For human data, details of all analyses and tests are described in Osinski & al [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF]. Briefly, to assess differential expression on semi-quantitative techniques such as RNAseq data, EdgeR (Biocomputing) package was used using negative binomial test. P-values were adjusted using the false discovery rate (FDR) method with a threshold of 0.001. Only genes with count per million (cpm) over 100 for at least 2 individuals were considered. Statistical differences in mice were demonstrated with one-way or two-way ANOVA or t-tests as described in each figure legend after the outliers have been removed with ROUT method (Q=1%) and the sample distribution normality checked with D'Agostino & Pearson omnibus or Shapiro-Wilk tests. For intestinal microbiota analyses, statistics on principal coordinates were computed by permanova with 1000 permutations using adonis function (VEGAN R package) and statistics on cliff-delta were calculated with Wilcoxon-Mann-Whitney analysis using EFFSIZE R package. p<0.05 was considered as statistically significance.

RESULTS

Severe obesity and T2D are associated with reduced sweet taste transduction pathway gene expression in human EEC.

The RNA-sequencing transcriptome of jejunal sorted EEC from severely obese patients with (ObD) or without T2D (Ob) has been reported in Osinski & al (30). Here, we analyzed the gene expression of sweet taste transduction pathway, namely TAS1R3, GNAT3, PLCB2, ITPR3, SCN2A, TRPM5, CACNA1A, SLC2A2 and SLC2A5 (Fig. 1A). We showed that GNAT3 gene expression was decreased 3-fold (fdr≤0.0001) in ObD patients compared to Ob patients whereas ITPR3 was increased 2-fold (fdr≤0.0001) (Fig. 1A). Furthermore, we showed a strong correlation between GNAT3 gene expression analysis by RNA-sequencing and by RT-qPCR in Ob and ObD patients (Fig. 1B), confirming the down-regulation of GNAT3 by T2D in obesity. This prompted us to explore the regulation of sweet taste transduction pathway genes in animal models with metabolic degradation and after metabolic improvement.

High-fat high-fructose diet induces more severe metabolic deterioration compared to high-fat diet.

To induce different severity of metabolic disorders, mice were fed either with control (CD), high-fat (HFD) or high-fat and high-fructose (HFD-HF) diets for 1 to 12 weeks. Both HFD and HFD-HF prompted a similar weight gain (Fig. 2A) compared to CD. Body composition analyses showed an increased lean mass after 12 weeks regardless of the diets (Fig. 2B).

As expected, increased fat mass was exacerbated after HFD and HFD-HF compared to CD from 3 weeks of diets (Fig. 2C) whereas plasma triglycerides were increased after 3 and 12 weeks of HFD (Fig. 2D). Glucose homeostasis was then analyzed. The area under the curve (AUC) of glycaemia during oral glucose tolerance test (OGTT) revealed glucose intolerance as early as 3 weeks of HFD and HFD-HF diets and the glucose intolerance was accentuated after 12 weeks of HFD-HF (Fig. 2E to G). After 12 weeks of diets, fasted glycaemia was significantly higher in HFD and in HFD-HF than in CD mice (Fig. 2H). Mice fed 12 weeks with HFD-HF displayed higher basal insulin level (Fig. 2I), insulin resistance in accordance with elevated HOMA-IR (Fig. 2J) and deteriorated insulin tolerance test (Fig. 2K andL). Together, these results showed that metabolic phenotype of HFD fed mice is characterized by obesity, glucose intolerance and basal hyperglycemia. HFD-HF fed mice displayed a more severe metabolic deterioration. Indeed, HFD-HF fed mice also displayed basal hyperinsulinemia and insulin resistance.

The expression of sweet taste transduction genes is altered in sorted EEC from mice with metabolic deterioration

EEC are rare and scattered along the crypt-villus axis. Therefore, to enable the study of sweet taste pathway gene expression in EEC, a mouse epithelial cell preparation, enriched in EEC, was adapted from our previous work in humans [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF] (Fig. 3A). Since the mucosa is more difficult to separate from the muscle tissue in mice, we added the CD326 marker to select the epithelial cells [START_REF] Kawasaki | Characterization of anoikisresistant cells in mouse colonic epithelium[END_REF]. CD24 was initially used in mice to separate stem cells that weakly express CD24 from Paneth cells and EEC that strongly express this antigenic marker [START_REF] Wong | Lrig1 controls intestinal stem-cell homeostasis by negative regulation of ErbB signalling[END_REF]. As shown in Figure 3, B to E, our cell sorting strategy in mice was validated. Indeed, gene expression of EEC specific markers, namely ChgA, Gip, Pyy and Pcsk1 and specific markers of Paneth cells and stem cells, Lyz and Lgr5 respectively, were specifically expressed in the CD24+ cell fraction (Fig. 3F andG). The ApoA4 gene expression, an enterocyte marker, was significantly higher in the CD24-cell fraction than in the CD24+ cell fraction (Fig. 3H). However, an ApoA4 gene expression in the CD24+ cell fraction showed either a contamination or an unexpected gene expression. More strikingly, the Gnat3 gene expression was specific of CD24+ cell fraction, indicating that α-gustducin subunit, encoded by this gene, is specific of EEC (Fig. 3I).

We examined the expression of sweet taste transduction pathway genes (Fig. 4A), namely: the sweet taste receptor (Tas1r2 and Tas1r3), the α gustducin subunit (Gnat3), the inositol trisphosphate receptor (Itpr3), the phospholipase C β2 (Plcb2), the calcium voltage-gated channel subunit alpha 1a (Cacna1a), the sodium voltage-gated channel alpha subunit 2 (Scn2A) and the transient receptor potential cation channel subfamily M member 5 (Trpm5).

We also analyzed Slc2a2 and Slc2a5 gene expression, which encode respectively for GLUT2 and GLUT5, two sugar transporters (Fig. 4B). The expression of Tas1r2 and Tas1r3 were not detectable. We noticed that Gnat3 expression in EEC was decreased after 3 weeks of HFD and HFD-HF as well as after 12 weeks of HFD (Fig. 4A, top). Moreover, we observed a decrease in Itpr3 and Trpm5 gene expression in EEC after 12 weeks of HFD (Fig. 4A, bottom) and an increased Slc2a5 gene expression after 3 weeks of HFD-HF (Fig. 4B, top).

Gnat3 gene expression seems to be highly responsive to high fat diets resulting in a marked reduction in expression levels in EEC. Interestingly, at 3 weeks of HFD and HFD-HF diets, Gnat3 (p=0.014), Plcb2 (p=0.019) and Trpm5 (p=0.019) gene expression was negatively correlated with body weight of mice (data not shown). We concluded that expression of genes involved in sweet taste transduction pathway in EEC was altered by obesity, glucose intolerance, and basal hyperglycemia.

The α-gustducin gene expression is partly rescued by surgery-induced hyperglycemia remission in mice

To evaluate if the altered sweet taste transduction pathway gene expression within EEC could be corrected after weight loss and diabetes remission, we used EGA surgery in mice (a surrogate of the RYGB in humans), as described before [START_REF] Amouyal | A surrogate of Roux-en-Y gastric bypass (the enterogastro anastomosis surgery) regulates multiple beta-cell pathways during resolution of diabetes in ob/ob mice[END_REF][START_REF] Troy | Intestinal Gluconeogenesis Is a Key Factor for Early Metabolic Changes after Gastric Bypass but Not after Gastric Lap-Band in Mice[END_REF]. EGA surgery forms a loop that excludes the duodenum and proximal jejunum from alimentary tract. After surgery, the food contained in the stomach is then discharged directly into the distal jejunum which becomes the first segment in contact with the nutrients (Fig. 5A). EGA surgery was performed in obese mice fed 8 weeks on HFD. After surgery, the HFD was maintained for additional 4 weeks in sham-(control mice) and EGA-operated mice and metabolic parameters and gene expression were evaluated. In agreement with previous experiments [START_REF] Troy | Intestinal Gluconeogenesis Is a Key Factor for Early Metabolic Changes after Gastric Bypass but Not after Gastric Lap-Band in Mice[END_REF] in sham-operated mice, body weight recovered 30 days after surgery whereas a longterm decreased body weight was observed in EGA-operated mice during the follow-up (Fig. 5B). Body composition analyses confirmed a stable lean mass in both sham-operated and EGA-operated mice whereas fat mass decreased in EGA-operated mice after surgery (Fig. 5C andD) as well as plasma leptin level (Table 2). The AUC of glycemia during an OGTT were significantly lower in EGA-operated than in sham-operated mice as well as fasted basal glycemia (Fig. 5 E to H). The improvement of glucose tolerance in EGA-operated mice resulted from a decrease in insulin (Fig. 5I) and C-peptide secretions (Table 2). Glucagon levels were similarly reduced during OGTT in all groups during glucose challenge (Table 2).

Insulin sensitivity was improved in EGA-operated mice since plasma insulin levels and HOMA-IR were decreased (Fig. 5I to K). Thus, gut anatomy modifications performed with EGA surgery allowed to induce body weight loss, and improvement of basal glycemia, glucose tolerance, insulin secretion and insulin sensitivity. The gut anatomy modifications were concomitant with an increased glucose-induced GLP-1 secretion and elevated basal PYY level (Fig. 5 L and M). In contrast, glucose-induced GIP secretion was decreased in EGA-operated compared to sham-operated mice (Fig. 5N).

Gnat3 expression was determined in duodenum, proximal and distal jejuna, and ileum in sham-and EGA-operated mice. Gnat3 expression in sham-operated increased in distal jejunum and ileum compared to duodenum segment (Fig. 6A). In EGA-operated, Gnat3 expression increased in proximal jejunum compared to duodenum segment (Fig. 6A).

We therefore compared the intestinal segments which are the first to receive the alimentary bolus, i.e. the duodenum of sham with the distal jejunum of EGA-operated (Fig. 6B). After metabolic improvement, Gnat3 expression was increased 3-fold in the distal jejunum of EGAoperated mice compared to the duodenum of sham-operated mice (Fig. 6B). Concerning the second intestinal segment receiving alimentary bolus, i.e. proximal jejunum of sham-and ileum of EGA-operated mice no statistical difference was observed (Fig. 6C). These results show that the EGA surgery in mice restores Gnat3 expression in the new first alimentary tract of the gut which subsequently could contribute to improve the glucose-induced GLP-1 secretion.

A diet-induced dysbiotic intestinal microbiota does not directly modify the intestinal

Gnat3 expression

In order to determine if changes in the expression of sweet taste α G protein in the gut are dependent of microbiota composition, we performed fecal microbiota transfer (FMT) from donor mice fed 12 weeks with HFD-HF diet or CD to young recipient mice at weaning and then fed for additional 3 or 12 weeks with a HFD-HF (Fig. 7A). We chose to transfer the fecal microbiota at weaning period when the gut microbiota is not well established in recipient mice, to facilitate the transferred microbiota implantation [START_REF] Roy | Comparative Evaluation of Microbiota Engraftment Following Fecal Microbiota Transfer in Mice Models: Age, Kinetic and Microbial Status Matter[END_REF]. The fecal microbiota and the inoculum of donor mice either fed CD or fed HFD-HF were sequenced and analyzed.

Principal coordinate analysis based on Bray-Curtis β-diversity matrix revealed that, the overall bacterial composition of microbiota and inoculum of HFD-HF mice were significantly different from microbiota and inoculum of CD mice (Fig. 7B). In the CD recipient mice (MRCD) and HFD-HF recipient mice (MRHFD-HF) gut microbiota compositions were also significantly different both 3 and 12 weeks after the FMT, despite an overlap at 3 weeks, indicating overall different gut microbiota profiles which increased throughout the follow-up (Fig. 7C).

The relative abundance of bacteria genus showed the presence of Akkermansia and Bacteroides in MRCD at 3 and 12 weeks after transfer (Fig. 7D, lanes 3 and 4) but not in MRHFD-HF (Fig. 7D, lanes 7 and 8). Concerning bacteria species, CD inoculum was characterized by a high abundance of Bacteroides cellulosilyticus and Faecalibaculum rodentium while HFD-HF inoculum was characterized by a high abundance of Lactococcus lactis and Streptococcus thermophilus (Fig. 7E). Cliff's δ estimates (CDe) revealed that the MRCD microbiota at both 3 and 12 weeks after transfer was characterized by a major enrichment in Akkermansia muciniphila (CDe>0.47), whereas 8 species were highly represented in MRHFD-HF at 12 weeks after transfer (Cde<0.47) (Fig. 7F). We noticed a high abundance of Lactococcus lactis (Fig. 7E andF) that could be mainly due to a contamination in high-fat diet [START_REF] Bisanz | Meta-Analysis Reveals Reproducible Gut Microbiome Alterations in Response to a High-Fat Diet[END_REF]. Furthermore, 12 weeks after FMT, Faecalibaculum rodentium, characteristic of the CD inoculum, and Streptococcus thermophilus, characteristic of the HFD-HF inoculum, were found both in a high abundance in MRCD and in MRHFD-HF, respectively (Fig. 7F). We therefore conclude that the fecal microbiota transfer was only partial since the MRCD and MRHFD-HF microbiota are not strictly identic to the respective inoculum.

Despite differences in species abundance between MRCD microbiota and MRHFD-HF microbiota, we did not observe differences in body weight gain between MRCD mice and MRHFD-HF mice (Fig. 8A). As expected, the fat mass and lean mass of MRCD mice and MRHFD-HF mice increased between 3 and 12 weeks under HFD-HF but no difference between MRCD mice and MRHFD-HF mice was observed (Fig. 8B andC). The glucose tolerance measured by the AUC of the OGTT showed that the MRHFD-HF mice presented a statistically significant increased glucose tolerance between 3 and 12 weeks after FMT whereas the MRCD mice did not (Fig. 8D), despite a similar increase in basal glycaemia between 3 and 12 weeks (Fig. 8E). The gene expression of Gnat3 in the jejunal epithelial cells in MRCD and MRHFD-HF mice was similar between 3 and 12 weeks after FMT (Fig. 8F). However, we observed a tendency to decrease in Gnat3 gene expression at 3 and 12 weeks after FMT when we compared MRCD mice and HFD-HF mice. These results showed that FMT from HFD-HF mice with metabolic disorders (obesity, glucose intolerance and insulin-resistance) did not directly impact the sweet taste G protein expression in recipient mice.

DISCUSSION

In this study we demonstrate that EEC expression of the sweet taste α-gustducin is reduced in severely obese individuals with T2D. In mice diet-induced obesity, glucose intolerance and basal hyperglycemia, the expression of Gnat3, Itpr3 and Trpm5 involved in sweet taste transduction pathway were decreased in sorted EEC. Interestingly, the weight loss and the improved glucose homeostasis after EGA in mice led to the restoration of Gnat3 expression in the new alimentary tract and improved glucose-induced GLP-1 secretion. However, metabolic disorders-induced dysbiotic microbiota did not modify the sweet taste α-gustducin gene expression in mouse intestine. Our data support a role for the sweet taste transduction pathway in mediating GLP-1 secretion in improving glucose homeostasis in mice and this pathway may have therapeutic implications to treat metabolic disease.

EEC are rare, scattered in the intestinal epithelium and difficult to isolate. Recently, the surface marker CD24 was successfully used to enrich EEC from jejunum of obese patients [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF]. Here, we adapted to mice the EEC sorting method previously described in human [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF].

Pcsk1 expression indicated that GLP-1 EECs were present in the CD326+/CD24+ cell fraction. Indeed, Pcsk1 codes the PC1/3 pro-hormone convertase that cleaves the proglucagon into GLP-1 specifically in intestine. Although we could not exclude having selected a type of EEC, our previous study showed that enriched human EEC fraction displayed no less than 12 enterohormones [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF]. More strikingly, we showed here that Gnat3 gene expression is specifically expressed in the EEC cell fraction. The sweet taste transduction pathway was first described at the level of taste buds in the tongue [START_REF] Nelson | Mammalian Sweet Taste Receptors[END_REF][START_REF] Roper | Taste buds as peripheral chemosensory processors[END_REF].

Nevertheless, the existence of this signaling pathway in the EEC was now recognized [START_REF] Margolskee | T1R3 and gustducin in gut sense sugars to regulate expression of Na+-glucose cotransporter 1[END_REF]. Indeed, α-gustducin, as well as the β and γ subunits of the gustducin G protein, T1R2-T1R3, PLCβ2, and TRPM5 were expressed in EEC [START_REF] Jang | Gut-expressed gustducin and taste receptors regulate secretion of glucagon-like peptide-1[END_REF]. In addition, expression of T1R2, T1R3 and α-gustducin has been described in the murine EEC line STC-1 but not in the enterocyte absorptive cell lines CaCo2-TC7, IEC-6 or FHs74Int [START_REF] Dyer | Expression of sweet taste receptors of the T1R family in the intestinal tract and enteroendocrine cells[END_REF].

Sweet taste thresholds are modified by multiple factors including genetics. Interestingly, polymorphisms of TAS1R3 and GNAT3 genes were associated with taste disorder [START_REF] Bae | Polymorphisms of TAS1R3 and GNAT3 Genes Are Associated with Patients with Taste Disorder[END_REF]. Mice lacking α-gustducin, T1R2 or T1R3 displayed a defective glucose-induced GLP-1 secretion [START_REF] Geraedts | Transformation of postingestive glucose responses after deletion of sweet taste receptor subunits or gastric bypass surgery[END_REF][START_REF] Jang | Gut-expressed gustducin and taste receptors regulate secretion of glucagon-like peptide-1[END_REF][START_REF] Kokrashvili | T1r3 and α-Gustducin in Gut Regulate Secretion of Glucagon-like Peptide-1[END_REF]. Interestingly, it has been demonstrated that the gene expression of Tas1r2 and Tas1r3 was decreased in the duodenum of diet-induced obesity in mice or in genetically obese Ob/Ob mice. Moreover, Trpm5 gene expression was also decreased in diet-induced obese mice [START_REF] Herrera Moro Chao | Impact of obesity on taste receptor expression in extra-oral tissues: emphasis on hypothalamus and brainstem[END_REF]. Recently, Smith et al, suggested that sweet taste receptor has evolved to modulate glucose absorption via the regulation of its transport and to prevent the development of exacerbated hyperglycemia due to the ingestion of high levels of sugars [START_REF] Smith | T1R2 receptor-mediated glucose sensing in the upper intestine potentiates glucose absorption through activation of local regulatory pathways[END_REF].

Here we analyzed the gene expression of the sweet taste transduction pathway in metabolic diseases in human EEC. We showed that T2D decreased expression of GNAT3 and increased expression of ITPR3 in EEC in obese individuals. These results highlighted an altered gene expression involved in the intestinal sweet taste signaling pathway in individuals with metabolic diseases for several years. Our mouse models exposed to either HFD or HFD-HF diets allowed us to analyze the sweet taste transduction pathway during the metabolic disorder onset with severity degrees. In EEC the impaired Gnat3 expression occurred in the early stages of obesity as early as 3 weeks of HFD or HFD-HF diet, whereas decreased Trpm5 and Itrpr3 expression occurred after 12 weeks of diets. We concluded that in EEC the sweet taste transduction pathway, at least at the level of gene expression, was altered by obesity, glucose intolerance, and basal hyperglycemia. This gene expression alteration was aggravated with the metabolic disorder duration. However, additional basal hyperinsulinemia and insulin resistance contributing to a more severe metabolic phenotype did not aggravate the alteration of the sweet taste transduction pathway. Moreover, the down-regulation of Gnat3 was similar regardless the high-fat diet, with or without fructose. It has been previously described an alteration of the sweet taste transduction pathway in duodenum of high-fat diet-induced obese mice or of genetically Ob/Ob mice [START_REF] Herrera Moro Chao | Impact of obesity on taste receptor expression in extra-oral tissues: emphasis on hypothalamus and brainstem[END_REF]. Together, those results suggested that obesity impairs the sweet taste transduction pathway, at least at gene expression level.

We previously showed that obesity itself did not impact the GLP-1+, CCK+, GIP+ and PYY+ cell density in obese patients when compared to non-obese patients [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF]. But rather T2D was associated to a decreased GLP-1+ cell density and an impaired lineage in human obesity [START_REF] Osinski | Type 2 diabetes is associated with impaired jejunal enteroendocrine GLP-1 cell lineage in human obesity[END_REF]. Thus, in our mouse models of diet-induced obesity and insulin resistance, we could hypothesize that the EEC density was not decreased and did not contribute to Gnat3 down-regulation, although without excluding it.

Bariatric surgery is associated with metabolic improvement, a rapid remission of T2D and a restoration of gut hormone release, particularly of GLP-1 [START_REF] Jirapinyo | A Meta-Analysis of GLP-1 After Roux-En-Y Gastric Bypass: Impact of Surgical Technique and Measurement Strategy[END_REF][START_REF] Sjöström | Review of the key results from the Swedish Obese Subjects (SOS) trial -a prospective controlled intervention study of bariatric surgery[END_REF]. In mice, EGA results in weight loss, improved glucose tolerance and increased GLP-1 secretion in response to glucose [START_REF] Troy | Intestinal Gluconeogenesis Is a Key Factor for Early Metabolic Changes after Gastric Bypass but Not after Gastric Lap-Band in Mice[END_REF]. Here, we reported an over-expression of Gnat3 in the most proximal segments of the intestine after EGA surgery. In this context, we compared the Gnat3 expression in the duodenum of sham-operated mice to the distal jejunum of EGA-operated mice and the proximal jejunum of sham-operated to the ileum of EGA-operated mice because these segments were the first in contact with the flow of nutrients after surgical intestinal remodeling. The increased expression of Gnat3 in the lower small intestine could contribute to the improving of GLP-1 secretion in response to glucose.

Metabolic diseases leading to dysbiosis of the intestinal microbiota [START_REF] Pascale | Microbiota and metabolic diseases[END_REF], we hypothesized that dysbiotic microbiota from diet-induced obese mice would cause intestinal alteration of gene expression involved in sweet taste pathway. Our results showed that the HFD-HF FMT to recipient mice kept on HFD-HF diet (MRHFD-HF) did not impact the weight gain and the basal glycaemia compared to the CD FMT (MRCD). However, we observed a higher aggravation of glucose intolerance in MRHFD-HF mice than in MRCD. This could be due to the presence of Akkermansia muciniphila in MRCD mice which is absent in MRHFD-HF mice. Indeed, Akkermansia municiphila is usually associated with a healthy metabolic status [START_REF] Dao | Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology[END_REF]. However, the FMT induced only a trending decrease in Gnat3 gene expression in MRHFD-HF mice. However, it could not be ruled out that the microbiota of the host fed HFD-HF masked the effect of HFD-HF FMT on Gnat3 intestinal expression. Thus, we could not conclude if intestinal microbiota impacted or not the sweet taste transduction pathway.

In conclusion, our data highlighted: 1/ the sweet taste transduction pathway in EECs plays an important role for glucose homeostasis, at least at gene expression level; 2/ metabolic disorders led to altered gene expression of sweet taste signaling pathway in intestine contributing to impaired GLP-1 secretion; 3/ after surgical intestinal modifications increased expression of α-gustducin contributed to metabolic improvement.

We speculated that targeting the sweet taste transduction pathway in intestine, and in particular sweet taste receptors, could ameliorate the endogenous secretion of GLP-1 in individuals with obesity and T2D. Note that the all species that are statistically different between MRCD and MRHFD-HF mice present a large magnitude effect (Cliff-delta ≥ 0.474).

Fig. 1 .Fig. 2 .Fig. 3 .Fig. 4 .Fig. 5 .Fig. 6 .Fig. 7 .

 1234567 Fig. 1. Sweet taste gene expression in human EEC from obese patients with or without T2D. A: Expression of genes involved in sweet taste transduction and glucose transporters in EEC from jejunum of obese individuals with (ObD, n=13) or without type 2 diabetes (Ob, n=14): TAS1R3, GNAT3, PLCB2, ITPR3, SCN2A, TRPM5 and CACNA1A, which code for taste receptor type 1 member 3, α-gustducin subunit, phospholipase C β2, inositol trisphosphate receptor, sodium voltage-gated channel alpha subunit 2, transient receptor potential cation channel subfamily member 5, calcium voltage-gated channel subunit alpha 1A respectively, and SLC2A2 and SLC2A5 which code for GLUT2 and GLUT5, respectively. Data are presented as means ± SEM. B: Correlation of GNAT3 expression by RT-qPCR and RNAseq in human EEC of Ob (n=11) and ObD (n=11) subjects. Statistical significance was calculated with (A) unpaired t-test and (B) simple linear regression test (Pearson). *: p <0.05, **: p <0.01 and ****: p<0.0001

Fig. 8 .*

 8 Fig. 8. Metabolic parameters and intestinal α-Gustducin expression in mice after FMT. A: Body weight is measured weekly for each group of male mice during 12 weeks after FMT in MRCD mice (n= 20) and in MRHFD-HF mice (n=20). B: The lean mass and C: The fat mass of mice determined by nuclear magnetic resonance 3 and 12 weeks after the FMT. MRCD (n=6 and n=5, respectively) and MRHFD-HF (n=6 and n=7, respectively). D: Area under the curve (AUC) during OGTT 3 and 12 weeks after FMT. E: Fasting glycemia before OGTT. OGTT was performed after fasting overnight with 2g/kg of glucose on 5 MRCD mice and 5 MRHFD-HF mice at 3 weeks and 5 MRCD and 5 MRHFD-HF at 12 weeks. F: Gnat3 gene expression measured in epithelial jejunum of MRCD (n= 4 at 3 and 12 weeks after the FMT) and MRHFD-HF (n=4 at 3 weeks and n= 5 at 12 weeks after the FMT). Data are presented as means ± SEM. Statistical significance was calculated with one-way ANOVA and post-hoc Tukey's multiple comparisons tests. ** : p< 0.01 ; *** : p < 0.001 and ****: p<0.0001

Table 1 .

 1 RT-qPCR primer sequences

		Gene	Forward primer	Reverse primer
	Murine	Rplp0	AATCAGCCAGAAGGTCCAAA	CGCAAATGCAGATGGATC
	primers	Gnat3	AATCAGCCAGAAGGTCCAAA	TTTCCCAGATTCACCTGCTC
	Human	Cyclophillin	GCCTTAGCTACAGGAGAGAA	TTTCCTCCTGTGCCATCTC
	primers	GNAT3	AGCGAGATGCAAGAACCGTA CATTCTTATGGATGATCTTCATTTGT

Table 2 .

 2 Plasma hormone concentrations during OGTT in sham-and EGA-operated mice.

	[pg/mL]	Time (min)	0	15	30	60
		sham	1 763 ± 203	3 382 ± 436 ***	2 282 ± 276	1 459 ± 151
	C-peptide	EGA	669 ± 74 #	1 969 ± 285 * ##	721 ± 90 ###	565 ± 94 #
		sham	26 ± 4	37 ± 6	30 ± 4	22 ± 4
	Glucagon	EGA	38 ± 4 #	39 ± 3	44 ± 9	42 ± 5 #
		sham	17 870 ± 8 791 16 129 ± 5 614 13 258 ± 2 979 11 856 ± 3 064
	Leptin	EGA	757 ± 229 #	786 ± 359 #	1069 ± 405 #	705 ± 238

#

EGA surgery was performed in obese mice fed 8 weeks on HFD. After surgery, the HFD was maintained for an additional 4 weeks in sham-operated (control mice) and EGA-operated mice. OGTT was performed at 0, 15, 30 and 60 minutes after glucose gavage in sham (n= 14) and EGA (n=13) mice. Statistical differences were calculated with a two way ANOVA and Post hoc Tukey's multiple comparisons tests. *: p<0.05, **: p<0.01 compared to 0 min for each group. # : p<0.05, ## : p<0.01, ### : p<0.001 in EGA-operated mice compared to shamoperated mice at the same time point.

Acknowledgements. The authors thank F. Deknuydt for EEC sorting (CytoICANplatform, ICAN) and A. Lacombe for EGA surgery procedure (PreClinICAN platform, ICAN).

Fundings. This work was supported by INSERM, Sorbonne University, MSDAvenir, LLG and JD received a doctoral fellowship from Sorbonne University. This work was supported by the Fondation pour la Recherche Médicale, grant number FDT202001010875 to LLG.


Rafik Drissi

Ronan Gaugne

Théophane Nicolas

Valérie Gouranton

Immersive Volumetric Point Cloud Manipulation for Cultural Heritage

Keywords: CCS Concepts, Human-centered computing → Virtual reality, • Applied computing → Archaeology, 2. Related works

In this paper, we present a framework for an immersive and interactive 3D manipulation of volumetric point clouds in virtual reality. The framework was designed to meet the needs of cultural heritage experts such as archaeologists or curators for use on cultural heritage artifacts. We propose a display infrastructure associated with a set of tools that allows users from the cultural heritage domain to interact directly with the point clouds within their study process. The resulting framework allows an immersive navigation, interaction and real time segmentation.

The availability and access to ct-scans enabled the role of the CT scanner to expand into the field of cultural heritage. Indeed, this technology provides internal viewing of the material that helps to identify the internal content and to optimize the preparation of the excavation [SERPS10], [NGT * 18]. But this kind of image use remains still in a limited proportion due to the difficulties of exploiting the obtained digital data.

In order to propose a volume rendering of DICOM data, the use of point cloud data has been researched and used in a variety of fields. Chougule and al [CMA13] explored three dimensional point cloud generations from ct scan images for bio-cad modeling, the resulting point cloud data was plotted on an Imageware thus presenting very basic visualisation and no interaction features. However, an important increase of projects relying on point clouds for the encoding of data uses output from LIDAR scanning or photogrammetry techniques has pulled the development of tools to handle this kind of data in 3D environments for various application contexts such as geology [PMM * For such cases, some Cultural Heritage specialists have access to two dimensional, non immersive standard tools derived from the uses in the medical field for harnessing the potential of their medical imaging data. However these tools are not designed for ease of use and oftentimes require require an amount of skill that cultural heritage specialists lack, particularly when it comes to segmentation operations.

The discrete nature of the three dimensional grid structure of DICOM (Digital imaging file format) data has oriented our research towards the use of point clouds as the main representation of the volume data. It is a representation that is supported by numerous, readily available third party softwares.

In this paper, we design and implement a framework that provides a dedicated solution to cultural heritage professionals to exploit their CT-scan data by themselves, through intuitive and easy to use real time interactive and immersive 3d visualisation and segmentation tools, we illustrate these features with three cultural heritage use cases.

Multi-target Selection Technique for Dense Virtual Environments, thus working on volumetric point clouds but focusing on providing a hybrid workflow combining mid-air and tablet interactions, and the advantages of the hybrid selection technique.

Maloca and al [MdCHH18] presented a Virtual Reality Volume

Rendering of Original Optical Coherence Tomography Point-Cloud Data Enhanced With Real-Time Ray Casting, that allowed the user to import DICOM files into the VR program, interact with a light source and operate cross sections on the 3d representation but did not allow for segmentation of the 3d data or simultaneous manipulation of multiple DICOM files.

In summary, the previous works illustrate the interest of representing and manipulating volume data through point clouds, in virtual reality, in various domains. However, existing works are lacking in the integration of the medical imaging files as the input data, in the simultaneous and independent manipulation of point clouds from multiple sources, in the focus on Cultural heritage use and in the real time segmentation and extraction of point clouds.

Framework Design

Main features

Our collaboration with the archaeologists and curators involved in this project has resulted in the selection of a number of features that the user must be able to conduct, which are : The user can vary the viewpoints size and investigate the 3dimensional space, 1:1 scale for a realistic analysis, miniature for an overview and magnified to analyse morphological details, holes, empty spaces and hidden parts within the object (Figure 3).

The user can integrate and simultaneously study multiple point clouds for direct comparison [RAK19], especially in heterogeneous material such as in a complex manufactured machine, (Figure 4), or in a block excavation of an incineration (Figure 2) The user's interactions are optimised in favor of enhanced intuitiveness and ease of use by non computer scientists. It is possible to grab and manipulate point clouds ergonomically, to handle an object in any direction, internally and at any scale, thus providing relevant support for scientific study.

Technical environment

The converter from DICOM medical imaging files to point clouds was implemented using the Python programming language, with The initial segmentation step allowed for the isolation of the bones, and the outer linen layers. The three point clouds generated from this first step were respectively constituted of 1 111 249, 1 451 332 and 7 567 975 points.

Focusing on the bones and making use of the scale features of the tool make possible a visualisation of the bones at different scales and allow the user to experience "walking" inside of a bone cavity (Fig. 3) and studying it at high detail.

Furthermore, the tool was used for real time extraction of specific bones for standalone analysis. The Figure 6 shows the extraction of the bone of a cat's paw from the cat's mummy, by moving the selection sphere (the white ball) Once segmented, the generated point cloud of the bone is easy to manipulate and visualise away from the neighbouring elements and layers initially occluding it, allowing for the observation of the key elements for identification of the bone, the age, the origin ...

Cagniard siren case

The third material, the Cagniard siren, was composed of several independently scanned objects : the socle, the mechanism and two whistles. All the parts were pre-segmented into two density thresholds, (i) the metal using density threshold from 2000 to 20 000, and (ii) the wood using density threshold from -300 to 200. clouds generated are laid out in a 3d scene to reproduce the real setting of the siren. This use case highlights the interest of the cross section tool to visualize the assembly of the different elements before making selections and isolating the point clouds (Fig. 1). Contrasting point cloud colors also allows to easily identify the different components (Fig. 4).

The conversion step resulted in the generation of 6 different point clouds whose sizes are presented in table 1. The different point

We additionally used the framework's positional criteria at point cloud generation to generate a point cloud of the mechanism and a cross section point cloud revealing the internal gears.

The framework allows to visualise the composition of the studied object, to determine the nature of the components (metal, wood) and to identify the way these components were assembled during manufacture (internal screws and tubes). It is also possible to observe the usage of different types of wood and surface engravings.

Framework Evaluation

In order to assess our framework, we conducted a study in which we compared the model manipulation and manual segmentation features to existing software used by professionals who manipulate ct-scan data.

tkinter for the visual interface and VTK for the manipulation of the DICOM data.

As for the VR tool we use Unity version 2018.3 and rely on the point cloud importer "Pcx" (https://github.com/keijiro/ Pcx) as a base. Tests are conducted on a VR Ready Desktop with the following characteristics : i7-9700k processor, 32GB DDR4-2400 Ram, Nvidia GTX 1080 GPU, and an Oculus Rift CV1 with touch controllers. This tool relies on the VR plugin for Unity MiddleVR (https: //www.middlevr.com/) as a middle-ware to manage the multiple VR visualisation hardware. It has been tested on common Hardware from Oculus Rift and HTC Vive head mounted displays, as well as the large CAVE-like facility visible in Figure 3, constituted of 4 screens, one floor of 10m x 3m, two lateral screens of 3m x 3m, and a main vertical screen of 10m x 3m, with more than 45M pixels displayed by 14 WQXGA laser projectors, driven by 7 PC, with the characteristics: 2 Intel Xeon E5-2623v4 2.6 2133 4C Processors, 32GB DDR4-2400 Ram, 2 NVIDIA Quadro P6000 24GB GPU.

Experimental result

We applied our framework to three different use cases, (i) an Iron Age cremation urn recently discovered by archaeologists [GNP * 19], (ii) an Ancient Egyptian cat mummy from the collection of the Archaeological department of a Fine Arts Museum [GPN * 18], and (iii) a 19th century acoustic measuring instrument from the scientific collection of a University. All these objects were scanned using the same CT scan in the context of an interdisciplinar research project in the Digital Cultural Heritage domain.

Cremation urn case

The cremation urn (Fig. 5) contains sediment, bones fragments, and three bracelets. The data was pre-segmented into three density thresholds, (i) the metal parts using density threshold from 3500 to 10 000, (ii) the bones and metal corrosion layer using density threshold from 1800 to 2500, and (iii) the ceramic and sediments using density threshold from 500 to 1500.

The three point clouds generated from this first step were respectively constituted of 29 550, 350 850 and 7 368 665 points. The framework allows to easily visualise and separate a block excavation containing multiple materials (ceramic, sediment, bone, and iron oxide). We were thus able to independently manipulate the point cloud of the metallic objects as shown in Figure 5-c. From this last point cloud, it was straightforward to perform the segmentation of the point cloud in the virtual reality environment to extract one of the rings as shown in Figure 5-d.

Mummy cat case

The cat mummy CT scan data also received a pre-segmentation into three density thresholds, (i) the bones using density threshold from 1600 to 10 000, (ii) the dense wrappings using density threshold from 50 to 200, and (iii) the outer wrappings using density threshold from -50 to 10. We organised an experimentation session at an Archaeology Institute which provided us with 7 archaeology professors who volunteered for testing with no prior experience with the tested software and tested for metrics of Task Completion Time, as well as Mean Distance and Standard Deviation between segmented models and a reference model. By conducting One-Way ANOVA tests supported by Shapiro-Wilk Normality Tests in the three measured variables as well as Normal Q-Q plots, we determined that use of our framework provided significant enhancements to speed and accuracy of the manual segmentation in these test conditions. This encourages us to evaluate our framework further with a more important test population.

Discussion

The VR environment used in our framework offers a better perception of volumes during manual segmentation. The natural movement makes positioning and orientation of the user's point of view as well as the selection tool faster and more precise.

The informal discussions with the archaeologists involved in the project and the evaluations highlight the ease of use of the tools of our framework, even for uninformed computer scientists. The ergonomics of the environment facilitate its use in the context of manipulation and introspection of objects in real time. The possibility of inserting several point clouds offers the possibility of comparing several objects simultaneously. The use of different colors for the point clouds also allow to instantly identify the different components of the archaeological material under study. Among the perceived limitations, the main one is related to the nature of the point clouds which can pose a problem to characterize the empty spaces (the cavities or the interstices) of small size, or the objects whose limits are diffuse.

Conclusions

We presented a framework with a set of tools to manipulate volumetric point clouds in a highly immersive and interactive virtual reality environment, in a cultural heritage context. The tools were developed and used on different contexts and use cases. The framework offers an application for generation of the point clouds from the DICOM files, and an immersive VR application whose main functionalities are a segmentation tool that allows to extract any collection of points for independent manipulation, a scaling tool that allows for free roaming inside the point cloud and the ability to treat volume data from multiple sources in parallel for direct comparisons.

Further developments are underway to adapt the framework to a broader range of contexts. For example, the support of simultaneous multiple users which will enable collaboration, as it allows archaeologists to share their respective expertise and to develop relevant hypotheses as demonstrated in [FK10].

A video of presentation of the work is available here: https: //youtu.be/nftIpWPsURI.

  17], [KBK08], and cultural heritage [KKBM18]. These kinds of projects are only getting interested in data of surface representations and not that of volumetric data as explored here. Such projects can be found in the 2014 IEEE 3DUI contest in the theme of 3D annotation task of point-could data sets, [CMBF14], [BNB14], [VC14], [KSM * 14]. Gaugne and al. [GPBG19] presented a framework for an immersive and interactive 3D manipulation of large point clouds, which was limited to surface representations and to cross-sections segmentation options. Montano-Murillo and al [MNK * 20] explored a Hybrid 3D/2D 1. Introduction Computed tomography scanning is an important source of volume data, and in a Cultural Heritage context, is used as a non destructive means of studying archaeological artefacts [JPK * 06,RCD * 15]. It becomes possible to assess the degradation of the artefacts, and serves as a guide in the restoration process for the implementation of a suitable protocol and the deployment of preservation means before any destructive micro-excavation operation.

Figure 1 :

 1 Figure 1: Interactive cross-section: the cutting plan in blue is positioned interactively on an object and the resulting cross section is displayed on the back wall

Figure 2 :

 2 Figure 2: Color selection.

Figure 3 :

 3 Figure 3: The user navigates inside the magnified point cloud, here in the cavity of a feline long bone.

Figure 4 :

 4 Figure 4: Visualisation of the different point clouds of a complex machine.

Figure 5 :

 5 Figure 5: Left to Right : a) Cremation Urn; b) Volume Rendering; c) Point cloud in VR; d) Segmented bracelet point cloud (yellow)

Figure 6 :

 6 Figure 6: From left to right : Manual segmentation of the mummy's bone point cloud and extracted paw bone point cloud

Table 1 :

 1 Point clouds sizes.

		metal density wood density
	Socle	1 154 391	1 476 255
	Mechanism	4 725 453	NP
	Small whistle	NP	724 185
	Medium whistle	5 422	1 967 199

Acknowledgements

This work was partially funded by the ANR-16-FRQSC-0004 IN-TROSPECT project.


Lucie Laval

Karine Praud

Sébastien Leclercq

Axel Cloeckaert

Marie-Cécile Ploy

Olivier Barraud

Benoît Doublet

Genome-based insights into the resistome and associated-mobilome of extended-spectrum cephalosporins resistant Morganellaceae spp

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Material and methods

Results

Conclusions

The Morganellaceae family contains bacteria present in water, soil or in the intestinal tract of humans and animals. Proteus mirabilis and Morganella morganii are opportunistic pathogens responsible for various infections ranging from minor to life-threatening issues (urinary tract infections to septicemia). The apparent emergence of multidrug-resistant (MDR) Morganellaceae strains harbouring mobile genetic elements with extended-spectrum-β-lactamase (ESBL), AmpC cephalosporinase and/or metallo-β-lactamase (MBL) resistance genes is a serious threat to public health. Since the last decade, several MDR Integrative Conjugative or Mobilizable Elements (ICE or IME) belonging to the SXT or SGI1 families have been described to spread extended-spectrum cephalosporins (ESC) resistance in clinical Morganellaceae strains of diverse origins.

✓ In contrast to Enterobacteriaceae spp., ESBL/AmpC/MBL resistance genes were not mainly located on conjugative plasmids in Morganellaceae spp. ✓ Conjugative IncA/C plasmids and the IncA/C-related ICEs belonging to the SXT and SGI1 families play an important role in the spread of ESBL and AmpC resistance genes in the Morganellaceae family. ✓ Further WGS analyses are ongoing to confirm the localization of ESBL/AmpC/MBL resistance genes and to fully characterize the different MDR mobile genetic elements implicated in the spread of ESC resistance.

 Here, we characterized the resistome and mobilome of ESC-resistant Morganellaceae strains from various sources through phenotypic and genomic approaches.

✗ 83 Morganellaceae strains based on the criteria of ESC resistance were isolated from humans and animals in France, Bulgaria and Taiwan between 1996 and 2017. ✗ After PCR screening of major ESBL/AmpC resistance genes and MDR mobile genetic elements, 66 Morganellaceae strains were whole-genome sequenced on IonProton™ platform at the Limoges Genomic Research Facility. ✗ WGS analysis was performed to determine the phylogenetic diversity using bowtie2/PhyML/iTOL tree (microbial core genome alignment & SNP detection). The ResFinder and PlasmidFinder tools available at the Center for Genomic Epidemiology were used for identification of acquired resistance genes and plasmid replicon typing, respectively.

✓ Phenotypic antimicrobial resistance

✗ Nearly all ESBL/Ampc/MBL-producing Morganellaceae strains showed multidrug resistance phenotype (47/52 strains resistant to > 3 antibiotic classes).

✗ 3 human clinical P. mirabilis strains isolated in Bulgaria were extensively-drug resistant showing only susceptibility to aztreonam. ✓ ESBL/AmpC/MBL resistance genes (Table 1) ✗ The CTX-M ESBLs were predominant with a large diversity of variants: bla CTX-M-15 , bla CTX-M-3 , bla CTX-M-14 , bla CTX-M-2 , bla CTX-M-24 , bla CTX-M-1 , bla CTX-M-11 ✗ Six P. mirabilis strains harboured simultaneously up to 3 ESBL/AmpC/MBL resistance genes.

✓ Phylogeny, MDR mobile genetic elements and horizontal gene transfer

✗ The phylogenetic analysis revealed a great diversity among P. mirabilis strains except few clusters (Fig. 1) ✗ Surprisingly, Only 20 out of 66 Morganellaceae strains harboured conjugative elements carrying ESBL/AmpC/MBL resistance genes, mainly conjugative IncA/C plasmids or SXT-related elements. ✗ Moreover, 31 Morganellaceae strains contained a MDR SXT or SGI1 integrative elements; few strains carrying elements of both families.

✗ The cephalosporinase AmpC gene bla CMY-2 was carried by conjugative IncA/C plasmids or ICEs related to ICEPmiJpn1 (Fig. 1 & 3).

✗ All ESBL resistance genes bla VEB-6 were carried by the MDR integrative mobilizable element SGI1-V in epidemiologically-unrelated but clusterized P. mirabilis strains of animal and human origins (Fig. 1 & 2).

P-010

We thanks Denys Brand and Nathalie Winter from the Féri (Fédération de Recherche en Infectiologie Région Centre Val-de-Loire) to have supported Lucie Laval by a Master fellowship.

Fig. 1 .

 1 Fig. 1. Maximum-likelihood tree of P. mirabilis strains.

Fig. 2 .

 2 Fig. 2. Schematic view of SGI1-V.

Fig. 3 .

 3 Fig. 3. Schematic view of SXT ICEs (SXT, R391, ICEPmiJpn1, and ICEPmiChn1).

Table 1 .

 1 ESBL/AmpC/MBL resistance genes in Morganellaceae spp.

Acknowledgments


Katharina Märker

Sabine Hediger

Gaël De Paëpe

Efficient 2D double-quantum solid-state NMR spectroscopy with large spectral widths

double-quantum single-quantum correlation spectra with arbitrary spectral widths can be recorded with SR26 and related supercycled recoupling sequences when applying Supercycle-Timing-Compensation (STiC) phase shifts. This concept widely extends the applicability of supercycled sequences, most importantly for obtaining long-range distance constraints for structure determination with solid-state NMR.

Solid-state nuclear magnetic resonance (ssNMR) is a powerful spectroscopic technique which can provide unique structural information at atomic resolution for a wide variety of samples, ranging from biological macromolecules to inorganic materials. Valuable structural information can be obtained from dipolar recoupling experiments, 1,2 because they reintroduce a coupling which is inversely proportional to the cube of the distance between the spins involved. Hence, such experiments give direct insight into spatial proximities and even allow internuclear distance measurements. For homonuclear recoupling experiments, double-quantum (DQ) recoupling schemes are very useful because signals from uncoupled spins can be suppressed by an appropriate phase cycle ("DQ filter"). 3,4 This is essential when such contributions dominate the spectrum and conceal the desired signals from coupled spin pairs, as it is for instance the case when correlating nuclei with low natural isotopic abundance (NA), such as 13 C (1.1 % NA) or 29 Si (4.7 % NA). 5,6 The feasibility of such experiments, which often suffer from very low sensitivity, has greatly increased in recent years, owing to the substantial sensitivity enhancements achievable with magic-angle spinning dynamic nuclear polarization (MAS-DNP). 7,8 Efficient excitation and reconversion of DQ coherences is fundamental for a successful implementation of DQ recoupling experiments. High DQ-filtered efficiencies (~73 %) can in theory be achieved using so-called γ-encoded recoupling sequences, 9 for example POST-C7, 10 SPC-5, 11 R14, 12 and CMRR. 13 However, experimental imperfections and interfering interactions like chemical shift anisotropy (CSA) often lead to dramatically reduced efficiencies in practice, in particular over long recoupling times, which impairs the detection of long-distance correlations. 14 Compensation for such deleterious influences can be achieved by supercycling where the same sequence is repeated with cyclic radio-frequency (rf) phase shifts and/or permutations. 15,[START_REF] Edén | eMagRes[END_REF] Even though this often leads to a loss of the γ-encoding property and associated reduced theoretical maximum efficiency of ~52 %, the increased robustness of supercycled sequences means that they frequently outperform γ-encoded sequences experimentally. [START_REF] Edén | eMagRes[END_REF] While supercycled pulse schemes are thus well suited for challenging recoupling experiments, a major drawback exists with regard to the acquisition of two-dimensional (2D) homonuclear DQ-SQ correlation spectra, one of the most important applications of DQ recoupling. When employing nonγ-encoded DQ recoupling sequences and hence most supercycled ones, the indirect evolution time (𝑡 1 ) has to be rotor-synchronized in order to record clean spectra. This means that the maximum spectral width in the indirect (𝐹 1 ) dimension is limited to the MAS frequency, which is often insufficient for nuclei with a broad chemical shift range. This limitation becomes even more severe at high magnetic fields, since the chemical shift dispersion in Hz is proportional to the magnetic field. For instance, a typical 13 C chemical shift range of 160 ppm requires a DQ chemical shift range of up to 320 ppm. This translates into a 𝐹 1 spectral width, and hence a required MAS frequency, of ~32 kHz at 9.4 T, or ~64 kHz at 18.8 T. Such high spinning frequencies are however incompatible with most DQ excitation schemes and/or the available probe hardware. An insufficient 𝐹 1 spectral width results in signal folding in the DQ dimension whereas non-rotor-synchronized 𝑡 1 evolution gives rise to reconversion rotor-encoded DQ spinning sidebands, [START_REF] Geen | [END_REF]18 in either way leading to difficulties in interpreting these more complex spectra. Note that this limitation can be circumvented for γ-encoded sequences by applying appropriate phase shifts to the DQ reconversion pulses (vide infra), allowing the choice of a 𝑡 1 increment of arbitrary length. [19][20][21][22] In this communication, we show that 2D DQ-SQ spectra with large 𝐹 1 spectral widths can be recorded with non-γ-encoded supercycled DQ recoupling sequences if they are derived from γ-encoded sequences. The method is based on Supercycle-Timing-Compensation (STiC) phase shifts. It eliminates one of the biggest drawbacks of supercycling, enabling 2D correlations in samples with a wide chemical shift range without limitations regarding the size of the DQ dimension. This is of particular relevance for the recoupling of nuclei with large CSA and/or small dipolar couplings, where well-compensated sequences are required. It also recently enabled us to complete the resonance assignment of a 2'-deoxyguanosine derivative (170 ppm 13 C chemical shift range) through the use of a 13 C- 13 C correlation spectrum 23 recorded with the SR26 recoupling sequence. 24 In the following, we will describe the concept and derivation of the STiC phase shifts. It will be demonstrated on the SR26 pulse scheme, one of the most robust homonuclear DQ recoupling sequences to date. 24,15 The SR26 sequence is a supercycled sequence constructed from the symmetry-based R26 4 11 pulse scheme. 12,22,24 It consists of the R26 4 11 sequence (𝑆 0 ), a π-shifted cycle in which all rf phases are shifted by 180° (𝑆 𝜋 ), a phase-inverted cycle in which the signs of all rf phases are inverted (𝑆 ), and a π-shifted phaseinverted cycle which combines both operations (𝑆 ). 24 The full sequence (𝑆 0 𝑆 𝑆 𝑆 𝜋 , Fig. 1b) spans 16 rotor periods (𝜏 𝑟 ) and requires an rf nutation frequency of 6.5 times the MAS frequency. Its high robustness has for instance enabled the acquisition of 29 Si- 29 Si DQ build-up curves of zeolite and silicate samples at NA, which were sensitive to Si-Si distances of up to 8 Å 25 and played an important role in structure elucidation of these systems. [26][27][28] Fig. 1. (a) Pulse sequence for the acquisition of a 2D DQ-SQ correlation spectrum with SR26 used as dipolar recoupling sequence, with X being, e.g., 13 C, 15 N or 29 Si. (b) Construction scheme of SR26. 24 The sequence consists of four 𝑆 elements based on the R26 4 11 sequence. Overall rf phase shifts are indicated by subscripts, phase inversion by 𝑆 ′ and gray boxes. The construction of one R-element is given in the bottom boxes, with flip angles and phases (subscript) in degrees. STiC phase shifts 𝜙 (highlighted in red) have to be applied to the DQ reconversion rf pulses in order to allow the use of a 𝑡 1 increment of arbitrary length.

A standard 2D DQ-SQ correlation experiment consists of a DQ excitation block, followed by 𝑡 1 evolution and a DQ reconversion block, usually of the same length as the DQ excitation (Fig. 1a). When a rotor-synchronized DQ recoupling sequence is used, the position of the rotor should be the same at the starting point of DQ excitation (𝑡 𝑒𝑥𝑐 0 ) and of DQ reconversion (𝑡 𝑟𝑒𝑐 0 ) to avoid modulation of the recoupled signal by sample rotation. [START_REF] Geen | [END_REF]18 This means that the 𝑡 1 evolution interval has to be an integer multiple of a rotor period, restricting the maximum 𝐹 1 spectral width to the spinning frequency. For γ-encoded sequences, this restriction can be circumvented by removing the dependence of the recoupled Hamiltonian on 𝑡 𝑟𝑒𝑐 0 . This is accomplished by shifting the phases of all DQ reconversion rf pulses 𝜙 𝑟𝑒𝑐 according to the phase-time relationship 21,22 𝜙 𝑟𝑒𝑐 = 𝜙 𝑒𝑥𝑐 + 𝑚 𝜇 𝜔 𝑟 (𝑡 𝑒𝑥𝑐 0 + 𝑡 1 )

where 𝑚 and 𝜇 are quantum numbers of the symmetry-allowed first-order terms, and 𝜔 𝑟 is the angular spinning frequency. The applicability of this relationship requires that 𝜇 ≠ 0, and that 𝑚/𝜇 is the same for all symmetry-allowed terms, which is only the case for γ-encoded sequences. For detailed accounts of symmetry-based recoupling sequences and derivation of the relationships presented here, please refer to the literature 22 and the ESI.

The selection rules for R𝑁 𝑛 𝜈 sequences can be applied to determine which terms are symmetry-allowed by the SR26 sequence. 12 To first order, the 𝑆 0 and 𝑆 𝜋 elements allow dipoledipole terms with quantum numbers {𝑙, 𝑚, 𝜆, 𝜇} = {2, ±1,2, ∓2}, whereas the related phase-inverted elements 𝑆 0 ′ and 𝑆 𝜋 ′ allow {2, ±1,2, ±2} terms. Since the ratio 𝑚/𝜇 is not the same for all 𝑆 elements, the SR26 sequence is not γ-encoded. However, each separate 𝑆 element is still γ-encoded, having 𝑚/𝜇 ratios of -½ (𝑆 0 , 𝑆 𝜋 ) or +½ (𝑆 0 ′ , 𝑆 𝜋 ′ ), respectively. As described above, this property can be used to remove the 𝑡 𝑟𝑒𝑐 0dependence of the average Hamiltonians created by the different R26 cycles. Assuming 𝑡 𝑒𝑥𝑐 0 = 0, the following overall phase shifts Δ𝜙 have to be applied to the DQ reconversion pulses of the respective 𝑆 elements, in addition to the phase shifts for DQ coherence selection:

Δ𝜙(𝑆 0 ) = Δ𝜙(𝑆 𝜋 ) = 𝜙 𝑟𝑒𝑐 (𝑆 0 ) -𝜙 𝑒𝑥𝑐 (𝑆 0 ) = -1 2 ⁄ 𝜔 𝑟 𝑡 1 Δ𝜙(𝑆 0 ′ ) = Δ𝜙(𝑆 𝜋 ′ ) = 𝜙 𝑟𝑒𝑐 (𝑆 0 ′ ) -𝜙 𝑒𝑥𝑐 (𝑆 0 ′ ) = + 1 2 ⁄ 𝜔 𝑟 𝑡 1
This makes all four separate average Hamiltonians independent of 𝑡 𝑟𝑒𝑐 0 , and hence also their sum, which is the effective Hamiltonian of the SR26 sequence. Consequently, arbitrary 𝑡 1 increments can be used in a DQ-SQ correlation experiment with SR26, and any desired 𝐹 1 spectral width can be achieved, when these Supercycle-Timing-Compensation (STiC) phase shifts are applied (also highlighted in Fig. 1b). The concept of these phase shifts can be transferred to similar supercycles of other sequences, as long as their separate cycles are γ-encoded. Fig. 2a demonstrates the successful application of STiC phase shifts in a 13 C-13 C DQ-SQ correlation experiment of a DNPenhanced frozen solution of U-13 C, 15 N-labeled L-histidine. The spectrum was taken at a spinning frequency of 7.8 kHz, employing the SR26 pulse sequence as given in Fig. 1. A 𝑡 1 increment of 33.3 μs, which is much shorter than a rotor period (τr = 128.2 µs), was used to achieve an 𝐹 1 spectral width of 30 kHz. The spectrum is dominated by cross peaks between directly bonded carbons, located in 𝐹 1 at the sum of the chemical shifts of the respective correlated spins, and allows to establish carbon-carbon connectivities (green solid lines). In addition, peaks originating from relayed polarization transfer over two bonds can be observed (green diamonds), which is typical for dipolar recoupling experiments with longer mixing times in uniformly 13 C-labeled samples. 20 Direct polarization transfers over two bonds are only observed for correlations involving the isolated Cϵ with either Cγ or Cδ (green dotted lines). For comparison, a spectrum taken with identical parameters, but without STiC phase shifts (Δ𝜙 = 0), is shown in Fig. 2b.

Here, cross peaks are of lower intensity and do not appear at the expected DQ frequency, but rather at more than one DQ frequency for the same 13 C- 13 C pair. The analysis of such a spectrum is practically impossible. Due to its high robustness, the SR26 sequence is particularly well suited to the observation and measurement of long distances (>3 Å), and thus the extraction of important structural information. Such polarization transfer over long distances is greatly facilitated in samples with nuclei at low NA or with sparse isotopic labeling since the relevant spin pairs occur mostly isolated and dipolar truncation is greatly reduced. 25,[30][31][32] This case is exemplified in Fig. 3 which shows a DNP-enhanced 13 C-13 C DQ-SQ spectrum of the antibiotic ampicillin at its NA.

The spectrum was recorded at a MAS frequency of 6 kHz, employing the SR26 sequence as shown in Fig. 1. The large 𝐹 1 spectral width of 26.2 kHz was achieved by using a non-rotorsynchronized 𝑡 1 increment of 38.2 µs (𝜏 𝑟 = 166.7 µs). Three repetitions of the full SR26 cycle were used for DQ excitation and reconversion each, resulting in a total recoupling time of 16 ms. All expected correlations corresponding to one (~1.5 Å) and two (~2.5 Å) bond distances are present in the spectrum (yellow and orange dashed lines, respectively), but more importantly, numerous correlations over longer distances can be observed (red and blue solid lines). Comparison to the crystal structure 33 shows that they range from 3.1 Å to ~4.3 Å, as also summarized in the ESI. Notably, not only intramolecular contacts are detected (red), but also several intermolecular ones (blue), which provide information on the crystal packing of the substance. Many of these correlations involve carbonyl and/or aromatic carbons which is remarkable due to their large CSAs and demonstrates the good performance of the SR26 sequence. 3 Å, see also ESI). 33 Only the shortest distance contribution is marked for each pair of cross peaks. Black dashed lines indicate the maximum 𝐹 1 spectral width feasible with rotor-synchronized 𝑡 1 evolution at the MAS frequency and magnetic field (9.4 T) used here. A 13 C-CPMAS spectrum is displayed above for illustrational purposes, with resonance assignment taken from ref. 34 . Asterisks denote spinning sidebands and signals from glycerol. The most intense aromaticaromatic correlation peaks occur at the position of the (𝜔 𝐷𝑄 + 𝜔 𝑟 )/2𝜋 spinning sideband in the indirect dimension, caused by insufficient averaging of their large CSA at 6 kHz MAS frequency. Correlations involving the methyl groups cannot be detected, which is often the case at measurement temperatures of ~105 K. 35 In both examples presented here, the maximum 𝐹 1 spectral width that would have been attainable with rotor-synchronized 𝑡 1 evolution is marked by black horizontal dashed lines (Fig. 2a and3). It is obvious that a spectrum with such a small spectral width and hence folding of many cross peaks would be extremely difficult to interpret, even for the simple case of histidine. Furthermore, the spectra shown here were recorded at a relatively low magnetic field of 9.4 T. The available 𝐹 1 spectral width with rotor-synchronized 𝑡 1 evolution would be even smaller at higher magnetic fields.

In summary, we have presented a method for recording 2D DQ-SQ correlation spectra with arbitrary 𝐹 1 spectral widths when employing the supercycled symmetry sequence SR26. It is based on applying STiC phase shifts to the DQ reconversion pulses in order to compensate for non-rotor-synchronized 𝑡 1 evolution, extending the concept known for γ-encoded sequences. Consequently, all correlation peaks of samples with a large chemical shift range can be obtained without signal folding in the indirect dimension, but also experimental time can be saved when an 𝐹 1 spectral width smaller than the MAS frequency is sufficient. The recoupling performance of SR26 remains unchanged, meaning that all benefits of this well-compensated sequence can be exploited, as for example for the recoupling of nuclei with large CSA, and for the detection of long distance correlations for structural studies. This will be particularly useful for MAS-DNP applications involving the acquisition of 2D correlation spectra of dilute spins, as demonstrated here by a long-range 13

Fig. 2 .

 2 Fig.2. DNP-enhanced13 C-13 C DQ-SQ correlation spectra of a solution of U-13 C,15 N-Lhistidine in 60/30/10 (v/v/v) D8-glycerol/D2O/H2O, containing 10 mM AMUPol.29 The pulse sequence shown in Fig.1was used with (a) and without (b) STiC phase shifts. Spectra were acquired at 7.8 kHz MAS frequency (𝜏 𝑟 = 128.2 µs), using a 𝑡 1 dwell time of 33.3 µs (30 kHz 𝐹 1 spectral width) and a total recoupling time of 4.1 ms (see ESI for experimental details). Identical processing has been applied to both spectra, and the same contour levels are shown. Solid and dotted green lines in (a) illustrate direct one and two bond connections, respectively, and green diamonds indicate peaks originating from relayed transfers. Black horizontal dashed lines indicate the maximum 𝐹 1 spectral width feasible with rotor-synchronized 𝑡 1 evolution at the MAS frequency and magnetic field (9.4 T) used here.13 C-CPMAS spectra are displayed above for illustrational purposes. Asterisks denote spinning sidebands and glycerol signals.

Fig. 3 .

 3 Fig.3. DNP-enhanced13 C-13 C DQ-SQ correlation spectrum of NA ampicillin anhydrate, employing the SR26 sequence for dipolar recoupling as displayed in Fig.1. The spectrum was recorded at 6 kHz MAS frequency with a total recoupling time of 16 ms (see ESI for experimental details). Yellow and orange dashed lines denote correlations corresponding to one and two bonds, respectively. Solid lines indicate longer intra-(red) and intermolecular (blue) correlations (3.1 -~4.3 Å, see also ESI).33 Only the shortest distance contribution is marked for each pair of cross peaks. Black dashed lines indicate the maximum 𝐹 1 spectral width feasible with rotor-synchronized 𝑡 1 evolution at the MAS frequency and magnetic field (9.4 T) used here. A 13 C-CPMAS spectrum is displayed above for illustrational purposes, with resonance assignment taken from ref.34 . Asterisks denote spinning sidebands and signals from glycerol. The most intense aromaticaromatic correlation peaks occur at the position of the (𝜔 𝐷𝑄 + 𝜔 𝑟 )/2𝜋 spinning sideband in the indirect dimension, caused by insufficient averaging of their large CSA at 6 kHz MAS frequency. Correlations involving the methyl groups cannot be detected, which is often the case at measurement temperatures of ~105 K.35

  C-13 C correlation spectrum of NA ampicillin. The general principle of applying different 𝑡 1 -dependent phase shifts to each element of a supercycle is applicable to any conventional supercycle of a γ-encoded sequence, solving one of the major problems associated with supercycle construction. This work was supported by the French National Research Agency (ANR-12-BS08-0016-01, ANR-11-LABX-0003-01 and RTB) and the European Research Council (ERC-CoG-2015, No. 682895). We are grateful to Daniel Lee and Nghia Tuan Duong for initial discussions about SR26, and to Sachin R. Chaudhari for preparation of the ampicillin sample. There are no conflicts of interest to declare.