Nathalie Sturm

Morgane Roger-Margueritat

Fabien Pierrel

Philippe Lehours

Muriel Genevay

Bertrand Huard
email: bertrand.huard@univ-grenoble-alpes.fr

Spatial heterogeneity for APRIL production by eosinophils in the small intestine

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

Introduction

Eosinophils are best known for their effector functions in immunity against some helminthic parasites 1 . However, most circulating mature eosinophils produced by the bone marrow extravasate in tissues to become resident 2 . There, they may play diverse functions. One tissue well characterized for the presence of resident eosinophils is the lamina propria of the lower intestine [START_REF] Gurtner | Intestinal eosinophils, homeostasis and response to bacterial intrusion[END_REF] . This eosinophil colonization is an early process in life starting before birth and any colonization of the lower intestine by commensal bacteria [START_REF] Mishra | Fundamental signals that regulate eosinophil homing to the gastrointestinal tract[END_REF][START_REF] Jiménez-Saiz | Microbial Regulation of Enteric Eosinophils and Its Impact on Tissue Remodeling and Th2 Immunity[END_REF] . There, resident eosinophils fulfill several homeostatic functions, including maintenance of the mucus layer and interaction with the enteric nervous system. In the lower intestine, eosinophils also have immune functions with a role in the homeostasis of IgA + PC mostly achieved by provision of survival signals to IgA + PC [START_REF] Chu | Eosinophils promote generation and maintenance of immunoglobulin-A-expressing plasma cells and contribute to gut immune homeostasis[END_REF] .

A proliferation inducing ligand (APRIL), a member from the TNF superfamily (TNFSF13), is a key factor positively regulating PC homeostasis [START_REF] Baert | The number 13 of the family: a proliferation inducing ligand[END_REF] . The APRIL protein is first produced as a transmembrane protein, and early cleaved in the Golgi apparatus during its secretory path by furin proteases [START_REF] López-Fraga | Biologically active APRIL is secreted following intracellular processing in the Golgi apparatus by furin convertase[END_REF] . Myeloid cells constitute the main cellular sources of APRIL with a constitutive production, which may be further upregulated by inflammatory signals sensed by Toll-like receptors [START_REF] Manfroi | CXCL-8/IL8 Produced by Diffuse Large B-cell Lymphomas Recruits Neutrophils Expressing a Proliferation-Inducing Ligand APRIL[END_REF][START_REF] Hardenberg | Specific TLR ligands regulate APRIL secretion by dendritic cells in a PKR-dependent manner[END_REF] . We and others previously reported APRIL-production by eosinophils [START_REF] Chu | Eosinophils promote generation and maintenance of immunoglobulin-A-expressing plasma cells and contribute to gut immune homeostasis[END_REF][START_REF] Chu | Eosinophils are required for the maintenance of plasma cells in the bone marrow[END_REF][START_REF] Blosse | APRIL-producing eosinophils are involved in gastric MALT lymphomagenesis induced by Helicobacter sp infection[END_REF] , but the regulation of APRIL production by eosinophils is still poorly characterized. Here, we studied APRIL expression by eosinophils in the gut of adult mice and humans.

Material and methods

Human experimentation

Approval for research on human samples were obtained from the Ethics committee of the Geneva university hospital. Human intestinal samples were obtained from patients with Merkel cell carcinoma outside tumor lesions between 2003 and 2010 after patients' informed consent according to the declaration of Helsinki. The presence of vili with Brunner glands identified the duodenum. The presence of vili without Brunner glands but Peyer's patches identified the ileum. The right colon was identified by the absence of vili.

Bacterial cultures

Escherichia Coli (E. Coli) was grown in standard Luria Broth medium. Bifidobacterium bifidum was grown anaerobically at 37°C in a Hungate tube with degassed Yeast Casitone Fatty Acids, medium 26 supplemented with antifoam 0.05% (Sigma). Cultures were harvested, washed in PBS and resuspended in Krebs-Ringer glucose (KRG) buffer to the desired concentrations after density measurement at 600 nm.

Cell purification and activation

Peripheral blood eosinophils were purified from buffy coats of healthy adult donors. After centrifugation on a Ficoll gradient (Pharmacia) and hypotonic lysis, eosinophils were purified from the granulocyte fraction by FACS-sorting the CD16 -SSC high population with a FACS-Aria (Becton-Dickinson). The purity of the eosinophils was routinely >95%. Human blood neutrophils were purified as previously described [START_REF] Manfroi | CXCL-8/IL8 Produced by Diffuse Large B-cell Lymphomas Recruits Neutrophils Expressing a Proliferation-Inducing Ligand APRIL[END_REF] . Viability assessed by trypan blue exclusion was above 80%. 10 5 Eosinophils resuspended in KRG were incubated in microwell plates with bacteria at a ratio of 1/1. Human IL-5, GMCSF and IL-3 used at 25 ng/ml were from Peprotech.

Cultures were harvested after 18h of incubation at 37°C for mRNA analyses. Production of reactive oxygen species were determined as previously described [START_REF] Manfroi | CXCL-8/IL8 Produced by Diffuse Large B-cell Lymphomas Recruits Neutrophils Expressing a Proliferation-Inducing Ligand APRIL[END_REF] . Mouse lamina propria and purified eosinophils were prepared as previously described [START_REF] Chu | Eosinophils promote generation and maintenance of immunoglobulin-A-expressing plasma cells and contribute to gut immune homeostasis[END_REF] . Purity of eosinophils was above 90%.

Mouse experimentation

All animal care and procedure were approved by Geneva veterinary office and the French national AFiS veterinary office. C57Bl/6 WT and germ-free mice were obtained from Charles River. WT C57Bl/6 mice were maintained in our animal facility at least 6 weeks before use.

APRIL -/-mice on a C57Bl/6 background were previously described [START_REF] Huard | APRIL secreted by neutrophils binds to heparan sulfate proteoglycans to create plasma cell niches in human mucosa[END_REF] . Antibiotics treatment consisted in the addition of 333 mg/l of tylosin tartrate (Sigma) in the drinking water for 2 consecutive days. Intestinal samples were collected 1 week after treatment. Duodenum samples originated from the area right distal to the stomach. Ileum samples originated for the small intestine harboring Peyer's patches. Right colons were analyzed only.

RT-PCR

Total RNAs were prepared using Trizol (Thermo Fisher Scientific), treated with RQ1 DNAse (Promega), and reverse transcribed with Superscript II and oligo-dT12-18 (Thermo Fisher). The intron spanning for human and mouse APRIL have been described elsewhere [START_REF] Matthes | Production of the plasmacell survival factor a proliferation-inducing ligand (APRIL) peaks in myeloid precursor cells from human bone marrow[END_REF] . Denaturation was performed at 94°C, annealing at 55°C, and extension at 72°C, 1 minute each. Forty cycles were applied. Amplified PCR products were visualized on agarose gels and ethidium bromide staining. Quantitative RT-PCR was done with a light cycler System (Roche Diagnostics) and the Quantitect SYBR Green PCR kit solution (Qiagen). Expression levels were normalized to human 18S rRNA and to mouse actin Amplification was done in duplicates and experiments were performed twice

Immunohistochemistry

Formalin-fixed paraffin-embedded intestine sections of 3µm were stained with Stalk-1 (rabbit polyclonal) detecting APRIL-producing cells and Aprily-2, -6, -8 detecting secreted APRIL as previously described [START_REF] Schwaller | Neutrophil-derived APRIL concentrated in tumor lesions by proteoglycans correlates with human B-cell lymphoma aggressiveness[END_REF] . Eosinophil staining was performed with a mouse anti-major basic protein antibody (clone BM13, Thermofisher) after a citrate-based antigen retrieval. In the human system, IgA + CD138 + PC were stained with a goat anti-human IgA (Vector laboratories) and the anti-human CD138 (clone Mi15, Agilent) after citrate-based antigen retrieval. In the mouse system, a rabbit anti-mouse IgA (Thermofisher) and anti-mouse CD138 (Life technologies) were used after citrate-based antigen retrieval. Fluorochrome-conjugated secondary antibodies were from Life technologies. DAPI (Thermofisher) was used for nucleus staining. Stainings were visualized as previously described [START_REF] Manfroi | CXCL-8/IL8 Produced by Diffuse Large B-cell Lymphomas Recruits Neutrophils Expressing a Proliferation-Inducing Ligand APRIL[END_REF] .

Flow cytometry

Surface and total cell staining was performed as previously described [START_REF] Schwaller | Neutrophil-derived APRIL concentrated in tumor lesions by proteoglycans correlates with human B-cell lymphoma aggressiveness[END_REF] . All fluorescentconjugated primary antibodies were from Becton-Dickinson. Fluorescence was measured with a FACSCanto and analyzed with the CellQuest software (Becton-Dickinson).

Statistical analysis

Statistical analysis was performed using GraphPad Prism software. D'Agostino and Pearson test (normality), Anova and t-tests were performed. Significant differences were defined as p < 0.05.

Results and discussion

1-Spatial heterogeneity for APRIL-production in eosinophils from the lower intestine.

We assessed in the human lower intestine APRIL-production with the Stalk-1 antibody recognizing the stalk fragment left in producing cells after APRIL processing. Notably, we found no APRIL-producing cells in the duodenum region, while ileum and right colon contained numerous cells (figure 1A, upper panel). The highest was the right colon. High magnification of a stained cell revealed an eosinophil morphology with a characteristic bilobated nucleus (figure 1A, upper panel, inserts). We confirmed eosinophil identification for these APRIL-producing cells by a costaining with the major-basic protein, a protein specifically contained in eosinophil granules. These cells were never present in Peyer's patches, the site of T-cell dependent production of IgA + PC in the gut (figure sup1A) [START_REF] Hirota | Plasticity of Th17 cells in Peyer's patches is responsible for the induction of T cell-dependent IgA responses[END_REF] . Occasionally, they infiltrated the epithelium (figure sup1B). Eosinophil infiltration of a mucosal epithelium is at the bases of several pathologies, but also occurs in healthy small intestines [START_REF] Yantiss | Eosinophils in the GI tract: how many is too many and what do they mean?[END_REF] . Eosinophils are known to preferentially infiltrate the lower intestine with an increase in distal zones [START_REF] Matsushita | The number and distribution of eosinophils in the adult human gastrointestinal tract: a study and comparison of racial and environmental factors[END_REF] . Our eosinophil quantification based on MBP staining were similar with an infiltration of 20 cells +/-6 per mm 2 in the duodenum, 22 +/-8 in the ileum and 43 +/-4 in the right colon. APRIL and MBP costaining showed that all eosinophils infiltrating the duodenum did not produce APRIL. In the ileum, APRIL-negative eosinophils were reduced down to 9% +/-6, and all eosinophils produced APRIL in the right colon. We also tested secreted APRIL reactivity with the Aprily-2 antibody. Duodenum was negative, while a faint reactivity was detected in the extracellular space of the duodenum close to APRIL-producing cells (Figure 1C). Some eosinophils were also positive intracellularly for secreted APRIL, and PC could occasionally be detected with surface bound secreted APRIL (inserts in figure 1C). Similar reactivities were obtained with Aprily-6 and -8 antibodies also detecting secreted APRIL. The latter constituted an evidence of APRIL secretion in the lower intestine and an on-target activity. IgA + cells were obviously numerous in the lower human intestine, adjacent to APRIL producing cells (figure 1C, upper panel). Among these cells, we quantified IgA + CD138 + PCs with two-color immunofluorescence (figure 1C, bottom left panel). We excluded from the quantification the few IgA + CD138 -cells present (arrow in figure 1C, bottom left panel) likely being memory B cells present in the lamina propria as reported by others [START_REF] Lindner | Diversification of memory B cells drives the continuous adaptation of secretory antibodies to gut microbiota[END_REF] . Despite the heterogeneity in APRIL expression between duodenum and ileum, we did not observe a significant difference in the density of IgA + CD138 + PCs at these locations (Figure 1C, bottom right panel).

We next assessed APRIL expression in mouse gut at the mRNA level, since the Stalk-1 antibody did not cross-react with mouse APRIL. RT-PCR confirmed the human data with an almost undetectable amplicon in the mouse duodenum, while the lamina propria from ileum and right colon were positive (figure 2A, left panel). Analysis of purified eosinophils from these lamina propria gave identical results with negativity and positivity for duodenal and ileal/colonic cells, respectively (figure 2A, right panel). IgA + cells were also numerous in the mouse lower intestine (figure 2B, upper panel). We also quantified the number of IgA + CD138 + PCs among these cells (figure 2B, bottom left panel). Again, we found no quantitative differences in duodenum, ileum and right colon (figure 2B, bottom right panel). However, we found significantly lower numbers for these cells specifically in the ileum and right colon when we performed our analysis in APRIL -/-mice. Taken together, our results showed that the human and mouse small intestine harbor a similar expression pattern for APRIL production with an absence of expression in the duodenum. The absence of APRIL expression in the duodenum was confirmed in the mouse study by the lack of IgA + PC number variation in APRIL -/-mice.

2-APRIL production in eosinophils is induced by bacterial stimulation

We next assessed the regulation of APRIL expression in order to understand the heterogeneity described above. We used human blood eosinophils. Intracellular staining with the Stalk-1 antibody did not detect the APRIL protein in these cells, while blood neutrophils were positive as previously described (figure 3A, left panel) [START_REF] Matthes | Production of the plasmacell survival factor a proliferation-inducing ligand (APRIL) peaks in myeloid precursor cells from human bone marrow[END_REF] . We obtained a similar result at the mRNA level (figure 3A, right panel). Eosinophils may be activated by cytokines [START_REF] Dougan | GM-CSF, IL-3, and IL-5 Family of Cytokines: Regulators of Inflammation[END_REF] . The common IL-5, GM-CSF and IL-3 did not induce APRIL mRNA in human blood eosinophils, while they were potent inducer of an oxidative burst in these cells (figure 3B). Bacterial products may also activate eosinophils [START_REF] Svensson | Human eosinophils selectively recognize and become activated by bacteria belonging to different taxonomic groups[END_REF] . Coculture of eosinophils with E. Coli potently induced APRIL mRNA in these cells. We also detected intracellular APRIL in E. Coli-activated eosinophils (figure 3C). In this experiment, Bifidobacterium bifidum was also able to induce intracellular APRIL.

In vivo, Gut eosinophils are exposed to products from commensal bacteria. We observed that detection of APRIL mRNA by RT-PCR in the lamina propria of ileum and right colon vanished in germ-free mice (figure 4A). Furthermore, modulation of the commensal bacterial load post antibiotics treatment significantly reduced APRIL gene transcription in ileum and right colon in the lamina propria (figure 4B). We observed a similar reduction in mRNA with purified eosinophils. Taken together, these show that bacterial products from the commensal bacteria induce production of APRIL by eosinophils from the lower intestine. The phenotype observed in mice genetically deficient for APRIL was impairment of IgA switching [START_REF] Castigli | Impaired IgA class switching in APRILdeficient mice[END_REF] . Several groups confirmed this role with recombinant APRIL, and showed that it is a T-cell independent process [START_REF] He | Intestinal bacteria trigger T cell-independent immunoglobulin A(2) class switching by inducing epithelial-cell secretion of the cytokine APRIL[END_REF][START_REF] Tezuka | Regulation of IgA production by naturally occurring TNF/iNOS-producing dendritic cells[END_REF][START_REF] Tezuka | Prominent role for plasmacytoid dendritic cells in mucosal T cell-independent IgA induction[END_REF][START_REF] Hardenberg | Thymus-independent class switch recombination is affected by APRIL[END_REF] . A role for APRIL has also been observed in T-cell dependent humoral responses [START_REF] Castigli | Transmembrane activator and calcium modulator and cyclophilin ligand interactor enhances CD40-driven plasma cell differentiation[END_REF][START_REF] Zhang | Plasma cell output from germinal centers is regulated by signals from Tfh and stromal cells[END_REF] . The APRIL receptor involved in this switch process is the transmembrane activator and CAML interactor [START_REF] Castigli | TACI and BAFF-R mediate isotype switching in B cells[END_REF][START_REF] Sakurai | TACI regulates IgA production by APRIL in collaboration with HSPG[END_REF] . Beside a role in IgA switching, APRIL also has a role later on during B-cell differentiation at the level of PC survival. This second role has been identified in the bone marrow and mucosa [START_REF] Huard | APRIL secreted by neutrophils binds to heparan sulfate proteoglycans to create plasma cell niches in human mucosa[END_REF][START_REF] Matthes | Production of the plasmacell survival factor a proliferation-inducing ligand (APRIL) peaks in myeloid precursor cells from human bone marrow[END_REF][START_REF] Belnoue | APRIL is critical for plasmablast survival in the bone marrow and poorly expressed by early-life bone marrow stromal cells[END_REF] . Identification of the first patient deficient in APRIL largely confirmed all these preclinical studies 32 . Our present study shows that eosinophils and their production of APRIL are important for IgA + PC homeostasis. This is highly consistent with a report from Chu et al. showing that mice deficient for eosinophils harbored reduction in gut IgA + PCs 6 . However, Beller et al. recently reported that microbiota but not eosinophils is required for IgA production [START_REF] Beller | Specific microbiota enhances intestinal IgA levels by inducing TGF-β in T follicular helper cells of Peyer's patches in mice[END_REF] . In the latter study, IgA class switching occurred due to the production of transforming growth factor b upon bacteria colonization of the gut. One should note that quantification of IgA + PC was performed quite shortly after microbiota transfer (21 days), so that the study likely focused on PC generation rather than on long-term survival as Chu et al. did. Regarding the cellular source of APRIL in the human gut, we did not find evidences for APRIL production in epithelial cells from the lower intestine and right colon. This is contradicting a report from He et al. [START_REF] He | Intestinal bacteria trigger T cell-independent immunoglobulin A(2) class switching by inducing epithelial-cell secretion of the cytokine APRIL[END_REF] , despite the fact that the Stalk-1 antibody used here identified epithelial cells producing APRIL from several mucosa [START_REF] Huard | APRIL secreted by neutrophils binds to heparan sulfate proteoglycans to create plasma cell niches in human mucosa[END_REF][START_REF] Sturm | Polarized Secretion of APRIL by the Tonsil Epithelium Upon Toll-Like Receptor Stimulation[END_REF] . The discrepancy might be due to different zones studied from the gut. We studied the right colon, while He et al. did not precise the region of the human colon they analyzed. Regarding eosinophils, we further found that their APRIL production is heterogeneous along the lower intestine. Such heterogeneity is due to the fact that APRIL production by eosinophils is not constitutive as shown by the negativity of blood eosinophils, but inducible depending on the tissue the cells extravasate in, at least for the gut. We observed that E. Coli and bifidobacterium bifidum, facultative and strictly, respectively, anaerobic strains well present in the lower intestine, induced APRIL production in blood eosinophils. Hence, the spatial heterogeneity observed may be explained by either the different bacteria composition along the lower intestine or the higher bacterial density within the ileum that contains over three Log10 more cells than the duodenum [START_REF] Vaga | Compositional and functional differences of the mucosal microbiota along the intestine of healthy individuals[END_REF][START_REF] Booijink | Microbial communities in the human small intestine: coupling diversity to metagenomics[END_REF] . This observation is consistent with the fact that gut eosinophils change their phenotype once extravasated in the gut as compared to their circulating blood counterpart [START_REF] Xenakis | Resident intestinal eosinophils constitutively express antigen presentation markers and include two phenotypically distinct subsets of eosinophils[END_REF] .

Most recent studies further indicated that they do so by responding to the gut microenvironment including the microbiota [START_REF] Diny | The aryl hydrocarbon receptor contributes to tissue adaptation of intestinal eosinophils in mice[END_REF][START_REF] Ignacio | Small intestinal resident eosinophils maintain gut homeostasis following microbial colonization[END_REF] . The absence of APRIL in the duodenum is puzzling if one considers that duodenum IgA + PC may persist for decades [START_REF] Landsverk | Antibody-secreting plasma cells persist for[END_REF] . Neverthelles, one should note that duodenum constitutes a second organ known to sustain PC survival in which APRIL is absent in addition to inflamed salivary glands from Sjögren syndrome 41 . Further studies are warranted to identify the PC survival factor(s) substituting to APRIL. decades in human intestine. J Exp Med. 2017;214:309-317. 41.

Lombardi T, Moll S, Youinou P, et al. Absence of up-regulation for a proliferationinducing ligand in Sjogren's sialadenitis lesions. Rheumatology. 2011;50:1211-5.

MuIgA

The picture shows a section of human small intestine costained for CD138 and Ig staining is also shown (right panel). Arrows mark IgA + CD138 -cells.

The picture shows a section of mouse small intestine costained for CD138 and IgA staining is also shown (right panel). Arrows mark IgA + CD138 -cells.

Figure 4

Germ-free mice

Figure 1 :

 1 Figure 1: site-specific production of APRIL by eosinophils from the lower intestine.

Figure 2 :

 2 Figure 2: site-specific dependency on APRIL for mouse IgA + plasma-cell homeostasis.

Figure 3 :

 3 Figure 3: bacterial products induce APRIL production by human blood eosinophils.

Figure 4 :

 4 Figure 4: microbiota-dependent regulation of APRIL-production by mouse eosinophils

  Figure 1

  Figure 2

  Figure 3

Figure 1sup :

 1sup Figure 1sup: localization of APRIL-producing eosinophils in the intestine A) Stained eosinophils are located outside the Peyer's patches present in the ileum. B) B) A stained eosinophil has infiltrated the epithelium in the right colon. Scale bars are shown. Inserts are high magnifications of arrowed stained cells.

Acknowledgments

This work was supported by the Finovi foundation (BH) and by the French society for Hepatology (AFEF) (NS).

Authors


Dennis Larsen

Michel Ferreira

Sébastien Tilloy

Eric Monflier

Sophie R Beeren

Unnatural cyclodextrins can be accessed from enzyme-mediated dynamic combinatorial libraries

Enzyme-mediated dynamic combinatorial libraries use natural building blocks, such as amino acids or carbohydrates, to make dynamic systems of interconverting bio-oligomers. Here, we show that dynamic systems of cyclodextrins (CDs) enabled by a native cyclodextrin glucanotransferase (CGTase) can incorporate unnatural glucopyranose-derived building blocks. Thus, starting dynamic combinatorial libraries from CDs with a single 6-modified glucopyranose results in a dynamic mixture of CDs containing several modified glucopyranoses. The relative concentrations of modified ,  or -CDs in these dynamic systems can be controlled by the addition of templates, thus providing a novel way to access desired modified CDs.

Introduction

Enzyme-mediated dynamic combinatorial chemistry uses enzymes as catalysts to make dynamic combinatorial libraries (DCLs) of interconverting oligomers. [1][2][3][4][5][6][7][8][9][10] Due to the natural origins of the enzymes, the building blocks for these oligomers are natural biomonomers, such as amino acids [1][2][3][4] or carbohydrates. [5][6][7][8][9][10] Such dynamic systems have enabled the development of peptide-based nanomaterials from proteasecatalysed systems [2][3] and the exploration of light-controlled dynamic systems of cyclodextrins (CDs), where the relative ratios of ,  and -CD can be controlled by an external light source. [9][10] Although enzymes are often considered highly specific catalysts, many enzymes also exhibit some form of catalytic or substrate promiscuity. 11 Recent decades have seen an increase in the exploitation of enzyme promiscuity, including the use of the inherent promiscuity of native enzymes, as well as the engineering of enzymes to be able to perform reactions otherwise not seen in Nature. [12][13] We reasoned this promiscuity could be exploited to make DCLs containing both natural and synthetically modified biomonomers.

Native CDs consist of 6, 7 or 8 D-glucopyranose units (,  or -CD, respectively) joined by -1,4-glycosidic linkages to form a macrocycle with a truncated cone-like structure and a hydrophobic internal cavity. 14 CDs form host-guest complexes with hydrophobic guests in water, which has been widely exploited in supramolecular chemistry and catalysis, [14][START_REF] Komiyama | Cyclodextrins and Their Complexes: Chemistry, Analytical Methods, Applications[END_REF][START_REF] Bai | [END_REF] as well as in the pharmaceutical, food and cosmetics industries. 17 Modified CDs, including mixtures of CDs, can sometimes be more efficient than a single native CD for these encapsulation applications. For example, Febreze® is composed from a mixture of various cyclodextrins that is particularly efficient at eliminating odours. 18 Mixtures of modified CDs can encapsulate and solubilise pharmaceutically active substances, 19 and have been employed to resolve enantiomers. 20 In aqueous biphasic organometallic catalysis, synergistic effects have been observed by using mixtures of CDs as mass transfer agents. 21 The production of modified cyclodextrins for specific application remains a challenge although complex synthetic procedures have recently emerged. 22 Straightforward synthetic approaches could lead to breakthroughs in this field.

glucanotransferase (CGTase) is employed in the enzymatic synthesis of CDs from starch. CGTase catalyses the reversible inter-and intramolecular transglycosylation of -1,4-glucans, to give linear and cyclic (cyclodextrin) products, as well as slow background hydrolysis. 5 Several reports have exposed the inherent promiscuity of this class of enzymes, but the investigation of CGTase-catalysed synthesis of modified CDs has received only a little attention. [23][24] We have previously shown that CGTase-catalysed DCLs of the natural (unmodified) CDs can be generated by exposing an -1,4-glucan starting material to CGTase at room temperature. A dynamic mixture of interconverting CDs forms in a kinetically trapped subsystem that operate under pseudo-thermodynamic control, such that the distribution of -, -and -CDs formed reflects their relative intrinsic stabilities and any external stabilising influences (e.g. interactions with added templates). 5- 8 In this report, we exploit the promiscuity of a commercial CGTase to produce DCLs of modified CDs. We show that these systems of interconverting (modified) CDs also operate under pseudo-thermodynamic control, and we demonstrate that templates can be used to control which modified CDs are preferentially produced (Figure 1a).

Results and discussion

We envisioned that CDs with minor modifications, both in terms of the size and chemical traits of the modification, would be most likely to be accepted as substrates by CGTase. Therefore, we set out to synthesize mono-6-deoxy--CD (m6d--CD, Figure 1b) and mono-6-deoxy--CD (m6d--CD). These two new modified CDs were obtained starting from mono-6-tosylcyclodextrins, which were subsequently reacted with sodium borohydride in anhydrous DMSO using an adapted procedure [25][26] to give the desired compounds (ESI Section S1).

m6d--CD was found to be quite water-soluble (at least up to 25 mg/mL), but m6d--CD did not dissolve in purely aqueous sodium phosphate buffer (pH 7.5) (less than 1 mg/mL). Organic co-solvents have previously been shown to reduce, but not eliminate the activity of CGTase. 6 Reaction conditions involving a number of co-solvents were tested, and the use of 10% DMF by volume in 40 mM sodium phosphate buffer (pH 7.5) at room temperature gave the best results with regards to CD solubility and enzyme activity (ESI Section S2). When m6d--CD (5 mg/mL) was treated with CGTase under these conditions, a dynamic mixture of -, -and -CDs each containing up to three 6-deoxyglucopyranose units was formed (Figure 1b). The reaction was monitored by matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-MS) wherein the different CDs were observed as the [M+Na] + ions. Since MALDI-MS does not distinguish positional isomers, we will refer to CDs with one, two and three deoxyglucopyranose units non-specifically as mono, bis and tris-6-deoxy-CDs (m6d-CDs, b6d-CDs and t6d-CDs), respectively.

To demonstrate that this mixture of modified CDs was dynamic, and that the system of CDs was operating under pseudo-thermodynamic control, two DCLs containing identical combinations of building blocks were prepared from two different starting points and monitored to see if they would converge on the same composition (Figure 2). The first DCL were prepared from m6d--CD (3.0 mg/mL) and -CD (2.0 mg/mL), and the second was prepared from m6d--CD (3.5 mg/mL) and -CD (1.5 mg/mL). In both cases, the ratio of glucopyranose to 6-deoxyglucopyranose units present was 9:1, and, therefore, when exposed to CGTase, the DCLs should eventually reach identical compositions at pseudothermodynamic equilibrium.

The evolution of each DCL was monitored using a combination of MALDI-MS and high-performance liquid chromatography with evaporative light-scattering detection (HPLC-ELS). The identities of the peaks in the HPLC chromatograms was determined by MALDI analysis of collected fractions. We found that when the DCL compositions were analysed directly using MALDI-MS, the mass intensities correlated well with the concentrations determined by HPLC, at least for the narrow range of masses (ca. 950 -1400 m/z) where the [M+Na] + ions for CDs were observed (ESI Section S5). Both HPLC-ELS and MALDI-MS were, therefore, deemed suitable for relative quantification of the components in these modified-CD mixtures.

It was found that the two DCLs converged on identical compositions within approximately 1 day (ESI Section 3.1). Figure 2a shows the identical HPLC chromatograms obtained after 30 hours of reaction Figure 2b shows how the concentrations of the different CDs in the two mixtures changed over time as they move towards the same product distribution. As a further proof of the dynamic nature of the system, mixing together a pre-formed library started from with a pre-formed library started from m6d--CD (after 8 hours initial reaction) resulted in identical composition to a DCL started directly from a 1:1 mixture of m6d--CD and m6d--CD (ESI Section 3.2).

Next, we investigated the addition of templates to alter the composition of these DCLs of modified CDs. To that end, we started a set of DCLs by exposing m6d--CD (5 mg/mL) to CGTase in the presence of different templates (5 mM) under conditions as described above, and we monitored the evolution of the DCLs using a combination of HPLC-ELS and MALDI-MS (Figure 3). Sodium dodecyl sulfate (1), adamantane carboxylic acid (2) and sodium tetraphenylborate (3) were employed as templates, as they have been shown to favour the formation of ,  and -CD, respectively, in dynamic libraries of unmodified CDs. 6 Templates 1, 2 and 3 were found to favour the formation of both modified and unmodified -CDs, -CDs and -CDs, respectively, compared to an untemplated library. The equilibrium compositions were reached within 24 -36 hours for the reference DCL and the DCLs templated with 1 and 2, while the DCL templated with 3 took 3 -4 days to reach equilibrium (Figure 3b). Slow production of -CD, also in presence of 3, has been observed in previously reported libraries of unmodified CDs using the same enzyme. 5 The templates chosen here were not designed to be able to distinguish between modified and unmodified CDs and the preferential amplification of CDs with a defined number of 6-deoxyglucopyranose units was not observed. Figure 3a shows how the relative distributions of -CDs, -CDs and -CDs evolved over time to give stable distributions, while Figure 3b shows the relative distributions of the different modified CDs once equilibrium was reached. Interestingly, the proportion of 6-deoxyglucopyranose units found in CDs was found to increase with longer reaction times, while the proportion of 6-deoxyglucopyranose units amongst the linear products decreased. This tendency was judged to result from a slower rate of hydrolysis of modified CDs compared to natural CDs, meaning that the modified CDs remained kinetically trapped in the CD subsystem for longer, rather than from a selective or stronger interactions between the templates and the modified CDs (ESI Section 6)

Finally, we investigated whether CGTase can accept CDs with other modifications at the 6-position as substrates. Commercially available mono-6-azido-6-deoxy-glucopyranose (m6N3--CD) and mono-6-deoxy-6-iodo-glucopyranose (m6I--CD) were tested as substrates. It was found that exposing these modified -CDs to CGTase also resulted in complex dynamic mixtures of -, -and -CDs with 0, 1 or 2 modified glucopyranose units. These DCLs also responded to the presence of templates 1, 2, 3 in a similar manner to the DCLs formed from 6-deoxy-CDs (Figures 4a,b and S25-S26 in the ESI). In the MALDI-MS analysis of these DCLs, the relative peak intensities for the modified CDs compared to the unmodified CDs were smaller when compared with the DCLs of 6-deoxy-CDs (compare Figures 4a,b to Figure 1b). Also, t6I-CDs and t6N3-CDs were not observed at all. This indicates that glucopyranose units with larger substituents are less easily incorporated into CDs compared with 6-deoxy-glucopyranose units. Meanwhile, it was possible to form a DCL by combining a 1:1 (w/w) mixture of m6d--CD and m6I--CD (total concentration 5 mg/mL) in the presence of CGTase. This resulted in a dynamic mixture that included CDs containing both 6-deoxy-and 6-deoxy-6-iodoglucopyranoses in the same macrocycle (Figure 4c). This library also adapted to the addition of templates 1 -3 (Figure S27, ESI), which shows that dynamic systems of modified CDs can be used to obtain CDs with several different modifications.

Conclusion

We have shown it is possible to generate enzyme-mediated dynamic combinatorial libraries of modified (unnatural) CDs. Using two novel CDs, m6d--CD and m6d--CD, we have demonstrated how kinetically-trapped dynamic systems of modified CDs operate under pseudo-thermodynamic control, wherein the CD distribution reflects their relative stabilities and can be manipulated via with a template. DCLs formed from m6N3--CD and m6I--CD highlight the promiscuity of CGTase. Future work will consider the design of templates that can select not only the CD size, but also the number, position and functionality of the modified glucopyranose units. Nevertheless, this work represents an important first step towards the templated dynamic enzymatic synthesis of selectively modified CDs.

Fig. 1

 1 Fig. 1 Enzyme-mediated dynamic combinatorial libraries of modified CDs. (a) Dynamic libraries of CDs with modifications (R) on C-6 can be produced by treating a CD containing a single modified D-glucopyranose unit with CGTase. Addition of templates shifts the equilibrium to produce more of the desired size of modified CDs. (b) Treatment of m6d--CD with CGTase results in a DCL containing , , and -CDs with several 6-deoxyglucose units (MALDI-MS, pH 7.5, 10 % by vol. DMF, after 30 h at 22 °C).

Fig. 2

 2 Fig. 2 Proof of pseudo-thermodynamic equilibrium. (a) The starting concentrations of two libraries started from different starting materials, but with the same overall building block concentration (5.0 mg/mL) and composition (9:1 G to 6d-G) and chromatograms (HPLC-ELS) obtained after the libraries had converged (30 hours). (b) Relative intensities of all observed CDs (MALDI-MS) in the same two libraries. The total CD concentration (as evaluated by HPLC-ELS) is illustrated with a grey dashed line (% by weight out of all -1,4-glucans). Reaction conditions as in Figure 1b.

Fig. 3

 3 Fig. 3 Templated dynamic libraries of 6d-G-containing CDs. (a) Relative intensities (MALDI-MS) of CDs (grouped into ,  and -CDs) observed over time in libraries started from m6d--CD in presence of templates 1, 2 or 3. The total CD concentration (as quantified by HPLC-ELS) is illustrated with a grey dashed line (% by weight out of all -glucans). (b) CD distribution observed at pseudo-equilibrium (in % according to rel. int., MALDI-MS). Reaction conditions as in Fig. 1b.

Fig. 4

 4 Fig. 4 Dynamic mixtures of different mono-6-modified CDs. Spectra (MALDI-MS) of mixtures obtained when starting libraries from (a) m6N3--CD in absence or presence of 1; or (b) m6I--CD in the absence or presence of 2; or (c) a 1:1 (w/w) combination of m6d--CD and m6I--CD in the absence or presence of 3. Amplified species are highlighted in templated libraries and the number of 6d-G units is noted above each peak in the mixed library. Conditions as in Fig. 1b.

Conflicts of interest

There are no conflicts to declare.

Notes and references


Louise Denis
email: louise.denis@sorbonne-universite.fr

Sylvain Bodard

Vincent Hingot

Arthur Chavignon

Jacques Battaglia

Gilles Renault

Franck Lager

Abderrahmane Aissani

Olivier Hélénon

Jean-Michel Correas

Olivier Couture

Sensing Ultrasound Localization Microscopy for the visualization of glomeruli in living rats and humans

Keywords: sensing Ultrasound Localization Microscopy, super resolution, glomeruli, human kidney, rat kidney, in vivo Research

Background

Estimation of glomerular function is necessary to diagnose kidney diseases. However, the study of glomeruli in the clinic is currently done indirectly through urine and blood tests. A recent imaging technique called Ultrasound Localization Microscopy (ULM) has appeared. It is based on the ability to record continuous movements of individual microbubbles in the bloodstream. Although ULM improved the resolution of vascular imaging up to tenfold, the imaging of the smallest vessels had yet to be reported.

Methods

We acquired ultrasound sequences from living humans and rats and then applied filters to divide the data set into slow-moving and fast-moving microbubbles. We performed a double tracking to highlight and characterize populations of microbubbles with singular behaviors. We decided to call this technique "sensing ULM" (sULM). We used post-mortem micro-CT for side-by-side confirmation in rats.

Findings

In this study, we report the observation of microbubbles flowing in the glomeruli in living humans and rats. We present a set of analysis tools to extract quantitative information from individual microbubbles, such as remanence time or normalized distance.

Interpretation

As glomeruli play a key role in kidney function, it would be possible that their observation yields a deeper understanding of the kidney. It could also be a tool to diagnose kidney diseases in patients. More generally, it will bring imaging capabilities closer to the functional units of organs, which is a key to understand most diseases, such as cancer, diabetes, or kidney failures.

Introduction

Medical imaging modalities provide an invaluable window at the organ scale deep in the human body.

Meanwhile, within thin slices of biopsies or shallow depths, optical microscopy reveals cellular morphology and mechanism. Both are necessary for clinical diagnosis and fundamental studies, but the information they provide remains incomplete. Indeed, the functional units of many organs reside at an intermediate scale, tens of micrometers in size, within multicellular units too small to be observed with medical imaging and too deep for microscopy to visualize non-invasively.

To observe such a mesoscale, we previously introduced Ultrasound Localization Microscopy (ULM) [START_REF] Errico | Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging[END_REF][START_REF] Couture | Ultrasound Localization Microscopy and Super-Resolution: A State of the Art[END_REF][START_REF] Christensen-Jeffries | Superresolution Ultrasound Imaging[END_REF] , which is an acoustic super-resolution technique that can map the microcirculation with unprecedented resolution at the scale of the organ of a living animal [START_REF] Tang | Kalman Filter-Based Microbubble Tracking for Robust Super-Resolution Ultrasound Microvessel Imaging[END_REF][START_REF] Chavignon | 3D Transcranial Ultrasound Localization Microscopy in the Rat Brain With a Multiplexed Matrix Probe[END_REF][START_REF] Lowerison | Ultrasound localization microscopy of renal tumor xenografts in the chicken embryo is correlated to hypoxia[END_REF][START_REF] Taghavi | Automatic Classification of Arterial and Venous Flow in Super-resolution Ultrasound Images of Rat Kidneys[END_REF][START_REF] Heiles | Ultrafast 3D Ultrasound Localization Microscopy Using a 32x32 Matrix Array[END_REF][START_REF] Hingot | Subwavelength motion-correction for ultrafast ultrasound localization microscopy[END_REF] . It relies on the tracking [START_REF] Tinevez | TrackMate: An open and extensible platform for single-particle tracking[END_REF] of isolated clinical contrast agents, namely microbubbles, traveling within the blood vessels. Since then, it has been investigated in humans [START_REF] Opacic | Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization[END_REF][START_REF] Huang | Short Acquisition Time Super-Resolution Ultrasound Microvessel Imaging via Microbubble Separation[END_REF][START_REF] Demené | Transcranial ultrafast ultrasound localization microscopy of brain vasculature in patients[END_REF] . Although it provides a rich microvascular mapping, it still remains blind to the functional units of organs. This is because very slow microbubbles within capillary beds are difficult to distinguish [START_REF] Desailly | Contrast enhanced ultrasound by real-time spatiotemporal filtering of ultrafast images[END_REF] .

Here, we present a "sensing ULM" method using the microbubble as a sensor of its immediate environment (sULM). Such accuracy allows to classify particular microbubble motion patterns corresponding to expected microscopic structures. Thanks to filtering methods adapted to the movement of the microbubble, we can track the entirety of its dynamics, including its slowest movements. By applying sULM to the kidneys of humans and rats, we aim to observe the organ functional units, i.e. the glomeruli. This component of the nephron is a bundle of capillaries situated between two resistance vessels that provide its filtration force [START_REF] Chmielewski | Renal anatomy and overview of nephron function[END_REF] . The glomerulus is impacted by several chronic diseases such as hypertension, diabetes, autoimmune diseases, and cancer that can lead to its destruction and the loss of its filtration functions [START_REF] Kanzaki | Human nephron number, hypertension, and renal pathology[END_REF][START_REF] Tonneijck | Glomerular Hyperfiltration in Diabetes: Mechanisms, Clinical Significance, and Treatment[END_REF][START_REF] Segelmark | Autoimmune kidney diseases[END_REF][START_REF] Kim | Glomerular Hyperfiltration and Cancer: A Nationwide Population-Based Study[END_REF] . Imaging of glomeruli is needed for the exploration, diagnosis, and understanding of these pathologies. The problem is that the human glomeruli diameter is approximately 200 microns [START_REF] Samuel | Applicability of the glomerular size distribution coefficient in assessing human glomerular volume: the Weibel and Gomez method revisited[END_REF] , which is well below the resolution limit of most medical imaging techniques. Clinical imaging techniques cannot provide the observation of individual glomeruli [START_REF] Kassirer | Clinical Evaluation of Kidney Function -Glomerular Function[END_REF][START_REF] Rahn | How to assess glomerular function and damage in humans[END_REF][START_REF] Inker | New Creatinine-and Cystatin C-Based Equations to Estimate GFR without Race[END_REF] . Currently, in the clinic, the glomerulus function is only assessed indirectly either by blood or urine tests that provide access to the global glomerular filtration rate.

In this study, we report the direct observation of individual glomerular structures in the kidney using sULM in humans with a setup available widely in hospitals. We first studied the behavior of microbubbles in glomeruli, on rat kidneys. We then compared sULM to micro-CT considered as a gold standard for glomeruli observation 24-

Methods

Animals ethics

All animal experiments were performed in accordance with the ARRIVE guidelines and approved by the local ethics committee (ethics committee on animal experimentation n°034, Department of Regulated Research Practices Animals Used for Scientific Purposes Unit -AfiS, reference number APAFIS #33913-2021082311153607) between January and May 2022. The number of animals in our study was kept to the necessary minimum. Experiments were performed on 15 Wistar male rats (Janvier Labs, Charles River, Envigo) aged between 8 and 12 weeks. 8 rats were planned to set up the study, in particular on questions of perfusion of the micro-CT. The 7 others were planned to optimize the implementation of the sULM technique. Animals arrived in the laboratory (Institut Cochin, INSERM U1016) 12 hours before the beginning of the experiments.

When rats underwent micro-CT examination, they succumbed during contrast injection still under isoflurane anesthesia, i.e. induction at 4 %, maintenance at 2•5% in air. Four rats were used to optimize micro-CT injection.

The remaining 11 rats were used to perform sULM. Of these 11, six were scanned by micro-CT. The other five died during the micro-CT injection procedure.

Contrast ultrasound data acquisitions on rats

30 minutes before the start of the ultrasound data acquisition, 330μl/100g of buprenorphine was injected to prevent pain. The rat was then placed in the isoflurane induction cage. Once asleep, we placed it in the supine position on a thermostatically controlled warming tray under isoflurane anesthesia (Fig 1 . a). An ophthalmic gel was applied to its eyes to avoid their drying. The temperature of the rat was controlled via a rectal probe and maintained between 35 and 37°C. The animal was shaved and then depilated on the abdomen, opposite the left kidney. The absence of a pinch reflex was verified before the placement of a 25G caudal venous catheter. The left kidney was externalized thanks to a short abdominal wall incision of less than one centimeter. The kidney was then stabilized with two needles on a thin plastic plate and explored by the direct contact of the ultrasound probe, assured by an ultrasound gel.

Ultrasound acquisitions were performed with an ultrasound scanner (Vantage 256, Verasonics, Kirkland) and a linear ultrasound probe L22-14v at a frequency of 15MHz (Verasonics, bandwidth [14-22] MHz, pitch 0•10mm).

The probe was positioned longitudinally to the kidney with a real-time B-mode display (Fig 1 . b). A microbubbles infusion (Sonovue®, Bracco, Milan, Italy, 8μL of sulfur hexafluoride/mL) of 13 μl/min that lasted two to three minutes was then performed (Supplementary Table 1).

Ultrasound acquisitions were acquired at a frame rate of 500 Hz, a pulse repetition frequency of 12,000Hz, a pixel size of 50µm, and a voltage of 8V. A total of [60-90] blocks were saved, each consisting of 800 images resulting from a compound of 3 angles. The data were then beamformed using a conventional delay-and-sum algorithm.

We removed blocks containing the bolus starts and movements too large to perform the post-processing (see data sharing statement).

Power Doppler performed with the same acquisition and a high threshold SVD is presented in Figure 1c (parameters in Supplementary Table 1).

Micro Computed Tomography (micro-CT) data acquisitions on rats

Once the ultrasound acquisitions were completed, the rat was kept under isoflurane anesthesia to proceed with the injection of the micro-CT contrast agent. This contrast agent is a mixture of barium sulfate (Micropaque 100g, Guerbet, France), PBS (Phosphate Buffer Saline, Cochin INSERM U1016), and gelatin. Gelatin was dissolved at 90°C, then mixed with Micropaque at 40°C to obtain a homogeneous solution, and then stored at a temperature of 4°C [START_REF] Blery | Vascular imaging with contrast agent in hard and soft tissues using microcomputed-tomography[END_REF] . After opening the thorax, a catheter was placed in the left ventricle of the heart, and the right atrium was sectioned to let the liquid flow out, after passing by all the organs. We then injected 25µL of heparin to avoid blood clotting, i.e. vial of 25,000 units by 5,000 units/mL. Then, a 200mL contrast agent heated in a water bath at 42°C was injected at a flow rate of 750mL/h to ensure perfusion of the vasculature. The death of the animal occurred under anesthesia due to this step of injection of the micro-CT contrast medium.

The kidney was kept for 48h in a petri dish in 4% of PFA to fix the perfusion until it was scanned with a highresolution micro-CT Skyscan 1172 (Bruker, URP2496) with a 5µm voxel size.

Micro-CT and sULM registration

We performed manually the registration between sULM and micro-CT based on the similarity of large vessels (Supplementary Fig. 1). This step was done with the Amira software (ThermoFisher, 2019.4). We averaged 32 micro-CT slices to obtain a 160µm thickness, i.e. the probe elevation resolution. We had a 1,024 by 1,024 matrix of 15µm pixel elements as the output of the Amira registration which we then analyzed in MATLAB.

Perfusion index in micro-CT and noise reduction

To compare micro-CT perfusion in rats, we defined a perfusion metric as the sum of pixels with a value greater than an arbitrary threshold of 0•5 divided by the total number of pixels within the cortex, with the micro-CT matrix normalized by its maximum. In the Supplementary Table 2, we could see that on 3 rats over 6, perfusion was above 5%, which means that the vessels were less contrasted then in the 3 other rats (Supplementary Fig. 2).

To reduce these differences in contrast between the vessels, we subtracted noise from micro-CT slices before summing them, i.e. subtraction of the lowest 10% of values within the kidney. This 10% threshold was arbitrarily chosen.

Human ethics

The Ethics Committee of the French Society of Radiology approved this study (CERF, reference number CRM-2203-240). All human acquisitions were performed by following the SRQR guidelines. Informed consent has been obtained from all patients.

Male and female kidney transplanted patients were included from February to August 2020, at Necker Hospital (APHP, France). These subjects were present due to their clinical routine ultrasound examination and no supplementary experimentation was made. Contrast-Enhanced Ultrasound Sequence (CEUS) was performed on patients to search for hypo-vascular areas and necrosis. To obtain the best quality images, the patients were lying in a supine position and breathing slowly during the acquisition. 14 patients were included in this study, and the results of five of them are presented here (three females/two males). The exclusion of the others was mainly due to respiratory motion.

Contrast ultrasound data acquisitions on humans

Data acquisitions on humans were acquired with CEUS embedded in the clinical ultrasound scanner Applio i800 (Canon MS, Nasu, Japan) and a convex abdominal probe i8cX1 (3MHz, Canon, bandwidth [1•8-6•2] MHz), with an injection of a bolus of 1•2mL of contrast agent (Sonovue®, Bracco, Milan, Italy, 8μL of sulfur hexafluoride/mL). CEUS had the advantage to enhance the signal of the microbubbles and allow a better visualization of their behavior. The mechanical index was reduced to 0•07 during the acquisition process to reduce the destruction of the microbubbles and exploit their nonlinear properties. The frame rate was different for each patient due to imaging depth differences, i.e. between 14 and 64Hz. Data acquisition duration, which corresponds to a video clip screenshot of the clinical ultrasound scanner, varied from one to three minutes (Supplementary Table 3). Clips were then divided into blocks of 200 frames each to proceed to sULM. All data were anonymized and stored on an external USB disk to be post-processed in our laboratory.

sULM post-processing

The codes that allowed the reconstruction of vascular mapping by sULM are available in the following GitHub repository: https://github.com/EngineerJB/akebia. A standalone application named Akebia -usable without a MATLAB license -is available in the same repository.

Several classical sULM steps have been applied to each block to obtain a density map. These are very similar in humans and rats so both will be described in this same section.

The first step consisted of a bandpass temporal (for humans) or spatiotemporal singular value decomposition filter (for rats). Frequency cutoff varied from 0•5 to 8•5Hz in the first case and was fixed at 40/800 eigenvalues for the second one. Data were filtered a second time in rats with a low-threshold SVD cumulated to a bandpass filter respectively to highlight slower microbubbles and to remove surrounding tissue (Supplementary Table 1). This way, our datasets were split into two parts: high-speed microbubbles flow with the first filter and slower microbubbles with CEUS for humans and with low-threshold SVD for rats. Previous studies showed that ULM performed better with a split dataset [START_REF] Huang | Short Acquisition Time Super-Resolution Ultrasound Microvessel Imaging via Microbubble Separation[END_REF] .

The second step consisted in the localization of the center of the microbubbles. In humans, this was done with a 2D Gaussian filter and targeting of the regional maximums. In rats, we applied the radial symmetry method to localize the microbubbles' center [START_REF] Heiles | Open Platform for Ultrasound Localization Microscopy: performance assessment of localization algorithms[END_REF] . Thus, we obtained the positions of the microbubbles in lateral and axial dimensions in pixels unit initially fixed by the acquisition itself, i.e. a pixel size between 70 and 150µm in humans, and 50µm in rats. At this step, we also had the temporal information which is the number of the frame where the microbubble appeared.

The third step consisted in applying the Hungarian algorithm method [START_REF] Kuhn | The Hungarian method for the assignment problem[END_REF] with the simple tracker Toolbox [START_REF] Tinevez | TrackMate: An open and extensible platform for single-particle tracking[END_REF] . We paired frame-to-frame microbubbles with specific constraints to track them. In our case, low-speed and fastspeed tracking parameters were summarized in Supplementary Tables 1 and3.

We repeated all the precedent steps in each block of our two datasets. Thus, we accumulated all microbubble tracks of all acquisitions twice. In this way, we reconstructed the sULM composite density map. Slow flow speed track accumulation on one side and fast flow speed track accumulation on the other side.

With an interpolation step performed just before track accumulation, the final rats' sULM density maps had a pixel size of 20µm. For humans, clips were already interpolated in the clinical ultrasound scanner, so we kept the same pixel size as the original acquisitions.

All data were processed and analyzed with MATLAB.

Manual segmentation and track classification

Kidney regions were manually delimited on sULM maps in three parts, i.e. cortex, medulla, and major vesselsincluding renal, interlobar, arcuate vessels, and finer structures such as afferent and efferent arterioles.

To study the behavior of microbubbles in each region, the tracks were then labeled. If one of their points belonged to the masks, then they were marked as belonging to that area. The segmentation of these three regions was performed similarly in rats and humans.

Glomerular mask creation

A glomeruli-specific mask was then created by considering the normalized distance value of the cortex tracks (see metrics calculation section). These normalized distance values were projected onto the same reconstruction grid used to create the sULM density maps. We then arbitrarily selected pixels whose normalized distance was greater than the 90th percentile of all pixel values by smoothing the image with a Gaussian filter. By drawing a circle of the order of the glomerulus radius from these pixels -i.e. 100µm in humans [START_REF] Samuel | Applicability of the glomerular size distribution coefficient in assessing human glomerular volume: the Weibel and Gomez method revisited[END_REF] , and 50µm in rats [START_REF] Baldelomar | Measuring rat kidney glomerular number and size in vivo with MRI[END_REF] -we thus determined a glomerular mask. We applied the same procedure of track conservation as before. If at least one of its points belonged to the glomerular mask, we labeled the track as belonging to glomeruli.

Metrics calculation

The normalized distance metric was defined as the cumulative distance of a track, divided by the distance separating its first point p1 to its last one pn [START_REF] Shelton | Quantification of microvascular tortuosity during tumor evolution using acoustic angiography[END_REF] .

𝑁𝑜𝑟𝑚𝑎𝑙𝑖𝑧𝑒𝑑 𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = ∑ ||𝑝 𝑥 -𝑝 𝑥+1 || 𝑛-1 𝑥=1 ||𝑝 1 -𝑝 𝑛 ||
The remanence time metric has been established as the period (in seconds) during which a microbubble was tracked inside a circle of glomerular size, -i.e. radius of 100µm in humans [START_REF] Samuel | Applicability of the glomerular size distribution coefficient in assessing human glomerular volume: the Weibel and Gomez method revisited[END_REF] , and 50µm in rats [START_REF] Baldelomar | Measuring rat kidney glomerular number and size in vivo with MRI[END_REF] . The center is defined as the median point of the list of points constituting the track.

The dispersity corresponded to the number of times that a track went in the same direction with a tolerance of more or less 20° -taking rounded localization of each track -divided by the number of points constituting the track (Supplementary Fig. 3).

Glomeruli count and perfused distribution width (PDW) calculation

The glomeruli count on the micro-CT was performed with the imregionalmax function of MATLAB in the cortex region on which we applied a Gaussian filter. We arbitrarily chose to keep the pixels with an intensity higher than the 90th percentile of the whole area. The glomeruli count on the sULM has been detailed in the section "Glomerular Mask Creation". We proceeded with manual segmentation of the renal capsule to perform a count of glomeruli based on their distance from it (Supplementary Fig. 1).

We chose to represent the spatial distribution of glomeruli by the histogram of 20 bins for sULM. We used "auto" as a bin method in Matlab. This method worked in several steps. First, the Scotts rule was used to determine the width of the bins. Then bin picker function adjusted the bin width depending on its order of magnitude and the total number of bins and positions of the left and right most histogram edges were then computed. Finally, the remaining bin edges were distributed uniformly between leftEdge and rightEdge at bandwidth intervals (Mathworks Website).

To compare sULM and micro-CT, we chose to represent the spatial distribution of glomeruli by the histogram of 20 bins for micro-CT and we fixed the constraint of the same bin width for both imaging methods. The statistical Kolmogorov-Smirnov test was done on these bins to compare the spatial distribution of sULM and micro-CT (Table 1).

On the micro-CT, the glomeruli perfused distribution width (PDW) was determined by calculating the full width at half maximum (FWHM) of the "global" glomerulus intensity profile (Supplementary Fig. 4). This intensity profile was calculated by summing all rows and columns from all glomeruli in a region of 20 pixels around its center, i.e., a 600-micrometers edge. Noisy glomeruli were removed from the calculation by selecting only those glomeruli that existed in four successive rotation of 90° of the same glomeruli. The intensity profile was then fitted by a Gaussian and interpolated, i.e. 600 points between -300 and 300 micrometers, before calculating the FWHM.

To estimate the glomeruli PDW on sULM, we took all slow tracks, i.e. tracked with slow sULM parameters, centered in zero belonging to the glomerular mask. We then took the FWHM of the "global" glomerulus density profile (Supplementary Fig. 4). This global density profile was calculated by summing all rows and columns from all glomeruli projected four times in the four directions -i.e. 90° rotation -in an interpolated grid of one µm for rats, and of 50µm for humans. The density profile was interpolated before calculating the FWHM, i.e. 600 points between -300 and 300µm for rats and 3000 points between -1500 and 1500µm for humans.

Statistical analysis

Statistical analyses were performed to evaluate the metrics between the different regions of the kidney using an Two-sided Kolmogorov-Smirnov nonparametric statistical tests [START_REF] Lehmann | Nonparametrics: statistical methods based on ranks[END_REF] were also performed on the spatial distributions of glomeruli as a function of their distance from the renal capsule on sULM and micro-CT images with GraphPad Prism 9 software.

Role of funders

The funders had no role in the study design, data collection, data analysis, interpretation, or report writing. All of these steps were carried out by contributors described later. Olivier Couture is responsible for the decision to submit the manuscript.

Micro-CT confirms that these spinning microbubbles detected in sULM correspond to glomeruli

Figure 2a and Figure 2b show the sULM and the micro-CT of rat seven in the same longitudinal plane.

Additional rats are shown in Supplementary Figure 2.

Figure 2c shows the glomeruli count using a high normalized distance value in the sULM and Figure 2d presents the glomeruli count using the selection of local high-intensity regional maxima on the micro-CT. Both imaging techniques appeared to show glomeruli in the same location.

In Figure 2e, we can see that the glomeruli spatial distributions from the kidney capsule were similar between the glomeruli detected by micro-CT, and the glomeruli observed by sULM in rat number seven (Figure 2f).

Statistical analyses showed that these distributions came from the same continuous distribution in all rats (Supplementary Figure 6). Thus, the glomeruli were located at the same site.

Glomeruli's PDW for sULM and micro-CT appeared to be in the same order of magnitude (Fig 2 . f) meaning that we observed the same phenomena with both modalities. Indeed, in all rats, PDW is 77±6 µm for sULM and 49±18µm for micro-CT (Table 3). rat seven (Methods). See Table 1 for more details on statistical analysis (two-sample Kolmogorov-Smirnov test).

(f) Glomeruli PDW calculation with a density as a function of distance to the center of glomeruli (for sULM in blue, in 11 rats), and intensity as a function of the distance from the center pixel (micro-CT in red, in six rats).

Dashed lines indicate standard deviation.

Glomeruli can also be observed in humans by sULM

Patient one's sULM composite density map presented the same glomerular shapes as rats in the cortex area (Fig. 3a). Another patient with the same cortical glomerular behavior is shown in Supplementary Figure 7.

A zoom in the cortex area confirmed the presence of arterioles with spinning microbubbles at the middle of their path, i.e. the glomeruli (Fig. 3b). Examples of glomeruli tracks are shown in yellow and red respectively in Figure 3c and 3d (Supplementary Videos 5-7).

The glomeruli count in sULM with the study of their PDW and of their spatial distribution from kidney capsules are presented in all patients in Supplementary Figure 8. We could observe that glomeruli PDW in humans were around 381±107µm (Table 4), which is bigger but in the same order of magnitude as the literature [START_REF] Samuel | Applicability of the glomerular size distribution coefficient in assessing human glomerular volume: the Weibel and Gomez method revisited[END_REF] .

Manual segmentation of kidney areas is shown in Figure 3e, and the glomerular mask is presented in Supplementary Figure 7c. In the same way as in rats, glomeruli tracks remained slower (Fig. 3f), more stagnant (Fig. 3g), and less dispersed than the medullary region and the main vessels (Fig. 3h). The tracks inside the glomeruli therefore had a similar specific behavior in humans and in rats. Statistical analyses are detailed in Table 5.

Discussion

In this study, we implemented a form of ULM which exploits the kinetic of individual microbubbles -including those flowing in the glomeruli -in order to map the renal microarchitecture of vessels. By classifying their behavior based on known anatomical features, we sought in this case the precise complexion of glomeruli microcirculation, including arterioles and capillaries. Spinning microbubbles were followed in the cortex and tracks analysis confirmed that these microbubbles are slower, more stagnant, and less dispersed than in the other kidney regions. The spatial distribution of glomeruli measured by sULM and by micro-CT belonged statistically to the same continuous distribution in six rats. Moreover, the glomeruli PDW measured by micro-CT and sULM was in the same order of magnitude with both techniques in all rats. Thanks to two these results and the fact that the micro-CT is considered to be the ex-vivo gold standard to observe microcirculation including inside glomeruli, we could conclude that glomeruli were observable by sULM.

These results allowed us to observe a part of individual glomeruli in living human grafts with a clinical imaging device, which was not possible with current imaging techniques [START_REF] Kassirer | Clinical Evaluation of Kidney Function -Glomerular Function[END_REF][START_REF] Rahn | How to assess glomerular function and damage in humans[END_REF][START_REF] Inker | New Creatinine-and Cystatin C-Based Equations to Estimate GFR without Race[END_REF] . We were not only able to observe a category of slow-moving microbubbles, but we showed how to reduce the gap between anatomical and functional imaging. This was done because we could image the very structures responsible for the function of the organ. By using sULM maps and the information given by the microbubble itself, we managed to image functional microvascular units. These kinds of observations will be essential to study many organs and diseases such as diabetes or cancer.

Still, this study has some limitations. The use of CEUS from a clinical ultrasound scanner has a frame rate between 14 and 64Hz, which implies bias in the estimation of the velocities for large vessels. The maximum velocity found in human sULM is 4cm/sec, whereas it is normally 100cm/sec [START_REF] Pellerito | Introduction to vascular ultrasonography[END_REF][START_REF] Al-Katib | Radiologic Assessment of Native Renal Vasculature: A Multimodality Review[END_REF] . Besides, glomeruli PDW measured by sULM are larger than the diameters found in the literature for humans 20,35, and thinner for rats [START_REF] Baldelomar | Measuring rat kidney glomerular number and size in vivo with MRI[END_REF] .

This is mainly because we did not measure the same information. With micro-CT and sULM, we measured the interval vascular system, i.e. the FWHM of the glomerular imaging task, whereas in the literature they measured the cellular content. Additional confirmation of the glomeruli distribution and size could later be obtained on immunostained histological sections.

For humans, the spatial resolution of CEUS, i.e. between 70 and 150µm, the localization error of 43±4µm -that increases with depth due to divergent ultrasound beam -and the presence of efferent and afferent arterioles in the same track as glomeruli leaded us to a rough PDW estimation with sULM (Supplementary Fig. 8, Supplementary Video 5 and 6). For rats, micro-CT perfusion was not always complete because of the complex injection procedure (Supplementary Table 2). Besides, fixation of the organ by PFA before scanning sometimes distorted the kidney, including vascular structures. Thus, the comparison between a living organ in sULM and a fixed organ in micro-CT is limited. Registrations of both techniques were done manually which also implies a bias. These points may explain the difference in PDW between sULM and micro-CT.

The observation of glomeruli in this study is only partial compared to results found in the literature [START_REF] Xie | Micro-CT imaging and structural analysis of glomeruli in a model of Adriamycin-induced nephropathy[END_REF][START_REF] Hlushchuk | Cutting-edge microangio-CT: new dimensions in vascular imaging and kidney morphometry[END_REF][START_REF] Baldelomar | Measuring rat kidney glomerular number and size in vivo with MRI[END_REF][START_REF] Bonvalet | Number of glomeruli in normal and hypertrophied kidneys of mice and guinea-pigs[END_REF][START_REF] Cullen-Mcewen | Nephron Number, Renal Function, and Arterial Pressure in Aged GDNF Heterozygous Mice[END_REF][START_REF] Geraci | Combining new tools to assess renal function and morphology: a holistic approach to study the effects of aging and a congenital nephron deficit[END_REF][START_REF] Klingberg | Fully Automated Evaluation of Total Glomerular Number and Capillary Tuft Size in Nephritic Kidneys Using Lightsheet Microscopy[END_REF][START_REF] Murawski | The relationship between nephron number, kidney size and body weight in two inbred mouse strains[END_REF][START_REF] Perrien | Novel methods for microCT-based analyses of vasculature in the renal cortex reveal a loss of perfusable arterioles and glomeruli in eNOS-/-mice[END_REF] (Supplementary Table 4). On the one hand, this is due to a lack of acquisition time with the right concentration of microbubbles 42 (Supplementary Fig. 9). On the other hand, this is due to 2D sULM that limits the field of view to a unique imaging slice.

The 2D sULM also has the disadvantage of creating false out-of-plane tracks. These false tracks are mostly present in the medullary region because these regions were positioned transversely to the imaging plane used for rats. Supplementary Fig. 10 shows these out-of-plane tracks inside the medulla in 4 rats. In humans, these out-ofplane tracks were less present because the clinician knew how to position the probe in the plane of the medullary vessels. These artefactual tracks could explain why the medulla tracks and the glomeruli tracks behave similarly in rats. Besides, medullary region is composed of capillaries within the vasa-recta and the juxtamedullary glomeruli, which can also explain the similarity between metrics in the medulla an in the glomeruli.

As another limitation, we can also mention the computational time which was multiplied by two due to the double tracking we performed to highlight the behavior of slow and fast microbubbles. These two regimes of microbubble behavior could not be followed in the same way, i.e. with the same tracking parameters. Indeed, if we had imposed the same tracking parameters for slow microbubbles as for fast microbubbles, i.e. high linking distances and short tracking time, then we would have risked matching microbubbles that did not belong to the same track or missing some microbubbles -because the parameters were not adapted to what we saw in the filtered acquisition that enhanced slow microbubbles. In the example of glomeruli, this could generate a deficit in their number.

In addition, movements were limited in this study because we had to externalize kidney in rats and because we had to include patients with shallower renal allografts (Supplementary Fig. 11). A future clinical trial to verify the feasibility of sULM on native human kidneys is hence needed.

In the future, 3D sULM [START_REF] Chavignon | 3D Transcranial Ultrasound Localization Microscopy in the Rat Brain With a Multiplexed Matrix Probe[END_REF][START_REF] Heiles | Ultrafast 3D Ultrasound Localization Microscopy Using a 32x32 Matrix Array[END_REF][START_REF] Jensen | Three-Dimensional Super-Resolution Imaging Using a Row-Column Array[END_REF][START_REF] Harput | 3-D Super-Resolution Ultrasound Imaging With a 2-D Sparse Array[END_REF] will also be needed to reduce and compensate for movements and to resolve the transverse direction, as encountered in the medullary region of rat acquisitions. Further studies will be necessary to analyze the behavior of microbubbles in more detail in the healthy and diseased glomeruli. Another study will be done to demonstrate the predictive diagnostic character based on glomerular sULM imaging. Furthermore, we believe that sULM might be a way to explore the vascular and functional status of various organs, not just kidneys. This approach could thus allow us to establish a diagnosis according to the individual behavior of each microbubble. This would eventually link macroscopic imaging and metabolism analyses.

  unpaired two-sided parametric student's t-test with a 95% confidence level assuming a Gaussian distribution on GraphPad Prism 9 software. The significance of the scoring was explained by the following P values: ns = P > 0•05, * = P ≤ 0•05, ** = P ≤ 0•01, *** = P ≤ 0•001, **** = P ≤ 0•0001.

Figure 1 .

 1 Figure 1. Glomerular structures were observed in the rat kidney cortex by sULM. (a) Experimental setup. (b) The imaging plane is the yellow one. (c) Power Doppler of the rat 14. (d) sULM density map in rat 14 with superimposed slow-tracking (pink) and fast-tracking (green). (e) Zoom in the cortex area. (f) Zoom of yellow glomerular behavior highlighted in e. (g) Masks of the three regions in rat kidney: cortex (yellow), main vessels (blue), and medulla (red). 500 first slow and 500 first fast tracks encoded with speed are presented upon background masks. (h) Mean normalized speed of all tracks in 11 rats compared by region. The significance of the scoring is explained by the following P values: ns = P > 0•05, * = P ≤ 0•05, ** = P ≤ 0•01, *** = P ≤ 0•001, **** = P ≤ 0•0001 (unpaired student's t-tests with a 95% confidence level). The center line corresponds to the median, box limits to upper and lower quartiles, whiskers to 1•5x interquartile range and no outliers have been considered. (i) Mean remanence time of all tracks in 11 rats compared by region. Same statistical tests. (j) Mean dispersity of all tracks in 11 rats compared by region. Same statistical tests.

Figure 2 .

 2 Figure 2. Capillary bundles observed in the sULM density map correspond to the glomeruli on micro-CT. (a) sULM density map in rat number seven. (b) Micro-CT in the same rat and same plane. (c) Zoom of sULM normalized distance (ND) map in rat seven (Methods). Red circles indicate glomerular count. 10,000 first slow and 5,000 first fast tracks encoded with ND are presented here. (d) Zoom of micro-CT in the same rat. Red circles indicate glomerular count. (e) Glomeruli count as a function of kidney capsule distance in micro-CT and sULM in

Figure 3 .

 3 Figure 3. Glomeruli can be observed in the cortex of human kidneys by sULM. (a) sULM density map in patient one with superimposed slow-tracking (pink) and fast-tracking (green). (b) Zoom in the cortex area. (c) Zoom of yellow track highlighted in b. (d) Zoom of red track highlighted in b. (e) Masks of the three regions: cortex (yellow), main vessels (blue), and medullary region (red). 500 first slow and 500 first fast tracks encoded with speed are presented upon background masks. (f) Mean normalized speed of all tracks in five patients compared by region. The significance of the scoring is explained by the following P values: ns = P > 0•05, * = P ≤ 0•05, ** = P ≤ 0•01, *** = P ≤ 0•001, **** = P ≤ 0•0001 (unpaired student's t-tests with a 95% confidence level). The center line corresponds to the median, box limits to upper and lower quartiles, whiskers to 1•5x interquartile range and no outliers have been considered. (g) Mean remanence time of all tracks in five patients compared by region. Same statistical tests. (h) Mean dispersity of all tracks in five patients compared by region. Same statistical tests.

ContributorsS

  .B., O.H., J.M.C., and V.H. contributed to the conception the human study. S.B. and V.H. contributed to the acquisition of the humans' sULM data. G.R., F.L., and O.C. contributed to the conception of the rats' study. A.A., L.D., S.B., F.L., G.R., and O.C. contributed to the acquisition of the rats' sULM data. A.A., L.D., S.B., F.L., G.R., and O.C. contributed to the acquisition of the micro-CT data. L.D., V.H., A.C. contributed to sULM and micro-CT post-processing. L.D., S.B., V.H., A.C., J.M.C., O.H., and O.C. contributed to the analysis and interpretation of the data. L.D., J.B., and O.C. contributed to the development of the Akebia software and the formatting of the codes. L.D., S.B., V.H., A.C., and O.C. contributed to drafting the manuscript. L.D., S.B., V.H., A.C., G.R., O.H., J.M.C, and O.C. contributed to revising the manuscript. L.D. and O.C. have direct access to the presented data. L.D. and O.C. have verified all the presented data. All authors have read and approved the final version of the manuscript.

Figure 1 .

 1 Figure Legends

Figure 2 .

 2 Figure 2. Capillary bundles observed in the sULM density map correspond to the glomeruli on micro-CT. (a) sULM density map in rat number seven. (b) Micro-CT in the same rat and same plane. (c) Zoom of sULM normalized distance (ND) map in rat seven (Methods). Red circles indicate glomerular count. 10,000 first slow and 5,000 first fast tracks encoded with ND are presented here. (d) Zoom of micro-CT in the same rat. Red circles indicate glomerular count. (e) Glomeruli count as a function of kidney capsule distance in micro-CT andsULM in rat seven (Methods). See Table1for more details on statistical analysis (two-sample Kolmogorov-Smirnov test). (f) Glomeruli PDW calculation with a density as a function of distance to the center of glomeruli (for sULM in blue, in 11 rats), and intensity as a function of the distance from the center pixel (micro-CT in red, in six rats). Dashed lines indicate standard deviation.

Figure 3 .

 3 Figure 3. Glomeruli can be observed in the cortex of human kidneys by sULM. (a) sULM density map in patient one with superimposed slow-tracking (pink) and fast-tracking (green). (b) Zoom in the cortex area. (c) Zoom of yellow track highlighted in b. (d) Zoom of red track highlighted in b. (e) Masks of the three regions: cortex (yellow), main vessels (blue), and medullary region (red). 500 first slow and 500 first fast tracks encoded with speed are presented upon background masks. (f) Mean normalized speed of all tracks in five patients compared by region. The significance of the scoring is explained by the following P values: ns = P > 0•05, * = P ≤ 0•05, ** = P ≤ 0•01, *** = P ≤ 0•001, **** = P ≤ 0•0001 (unpaired student's t-tests with a 95% confidence level). The center line corresponds to the median, box limits to upper and lower quartiles, whiskers to 1•5x interquartile range and no outliers have been considered. (g) Mean remanence time of all tracks in five patients compared by region. Same statistical tests. (h) Mean dispersity of all tracks in five patients compared by region. Same statistical tests.

Table 1 . A detailed comparison between glomeruli spatial distribution in micro-CT and in sULM 32

 1

	Declaration of Interest

O.C. and V.H., hold patents in the field of ultrasound localization microscopy (EP4011299A1). O.C. and V.H. are founders and shareholders of the ResolveStroke startup. O.C. has received several grants: ERC Consolidator grant agreement no 772786-Resolve Stroke, ERC POC (2022-2023), Maturation SATT Lutech for Tables

Table 2 . A detailed comparison between main vessels, medulla, and glomeruli in rats 581

 2

	Test statistic	Metric	Region	Confidence	Size (n)	Degrees of	P-value
			compared	intervals		freedom
			Main vessels	-0•14 to -0•07	11		<0•001
			and medulla
		Normalized	Main vessels	-0•13 to -0•06	11		<0•0001
		Speed	and glomeruli
			Medulla and	-0•02 to 0•04	11		0•39
			glomeruli
			Main vessels	0•02 to	11		<0•001
			and medulla	0•04
	Two-sided	Remanence	Main vessels	0•02 to	11		<0•001
	student t-test		and glomeruli	0•03
			Medulla and	-0•02 to 0•00	11		0•12
			glomeruli
			Main vessels	-0•09 to -0•04	11		<0•001
			and medulla
			Main vessels	-0•09 to -0•04	11		<0•001
		Dispersity	and glomeruli
			Medulla and	-0•01 to 0•02	11		0•80
			glomeruli
	582

Table 4 . Glomeruli PDW estimation by sULM in patients 585

 4

	Patient n°	sULM (µm)
	1	389
	2	236
	3	203
	4	462
	13	372
	Mean ± std	332 ± 109
	586

Table 5 . A detailed comparison between main vessels, medulla, and glomeruli in humans

 5

. Finally, we demonstrated that the observation of glomeruli by sULM is also possible on human transplanted kidneys. We provide materials, such as post-processing codes, to reproduce these experiments in hospitals equipped with conventional ultrasound scanners.

Acknowledgments

We thank the "Plateforme d'Imagerie du Vivant" (Université de Paris), and specifically Lotfi Slimani for the micro-CT acquisitions with the Skyscan 1172 Bruker. This study was funded by the European Research Council under the European Union Horizon H2020 program (ERC Consolidator grant agreement No 772786-ResolveStroke).

Funding

This study was funded by the European Research Council under the European Union Horizon H2020 program (ERC Consolidator grant agreement No 772786-ResolveStroke).

Data Sharing Statement

ZENODO repository is accessible: https://zenodo.org/record/6811910#.ZA8Mkh-ZPic (DOI 10.5281/zenodo.6811910). All 60 blocks of rat 14 have been made available. To get the same image as in the article only blocks 10 to 20 and 27 to 32 have to be loaded (see README). This is due to the presence of motions on the last 28 blocks, and too many microbubbles at the beginning of the bolus (Methods). Patients' imaging data are not available due to ethical, medical, and legislative considerations toward personal information.

The GitHub repository is accessible with scripts and functions used to perform sULM. Matlab 2021a is needed to run the programs: https://github.com/EngineerJB/akebia. Moreover, a standalone application named Akebia, i.e. usable without a MATLAB license, is available in the same repository.

Results

sULM highlighted spinning microbubbles in the rat kidney

Thanks to the double-filtering and the double-tracking explained above, we could obtain a composite sULM density map with slow tracks highlighted in pink and fast ones in green (Fig. 1d). The microvasculature reconstructed by sULM was much more resolved than with the Power Doppler of the same acquisition (Fig 1 . c).

In the sULM map, we could observe particular microbubble behavior in the cortex: microbubble tracks that entering and then exiting an area where they were spinning at velocities corresponding to the capillary flow. A zoom on the cortex in Fig. 1e confirmed the presence of these slow bundles of capillaries, i.e. the glomeruli. As an example, an independent microbubble was followed along this pathway leading to a glomerular shape in Fig. 1e and Fig. 1f. Other microbubbles within the cortex appeared to rise, then swirled before leaving again (Supplementary Videos 1-4, Supplementary Fig. 5). Such microbubble behavior has only been observed along the intermediate vessels of the cortex.

Segmentation of the different regions of the kidney, namely the medulla, main vessels, and cortex, are presented in Figure 1g. Glomerular mask constructed by including high normalized distance tracks is shown in Supplementary Fig. 5e. Metrics to highlight glomeruli, including normalized speeds -i.e. distance traveled by the track divided by the maximum speed in each area; remanence time -i.e. time duration of the track within a radius of 50µm from the track center; and dispersity -i.e. number of times that a track goes in the same direction divided by the number of points constituting the track; are displayed respectively in Fig. 1h, Fig. 1i and Fig. 1j.

Tracks in the glomerular mask seemed specific to this area. They are slower, more stagnant, and less dispersed compared to tracks in the medullary region and in the main vessels. Statistical analyses showed that these differences were always significant from the main vessels to the glomeruli and from the main vessels to the medullary region, but these metrics were not significantly different between the medulla and the glomeruli (Table 2). 584

Supplementary Materials

This paper contains supplementary material available online.

Correspondence and requests for materials should be addressed to:

Louise Denis: louise.denis@sorbonne-universite.fr Olivier Couture: olivier.couture@sorbonne-universite.fr