Simon Haziza
email: simon.haziza@ens-cachan.fr

Nitin Mohan

Yann Loe-Mie

Aude-Marie Lepagnol-Bestel

Sophie Massou

Marie-Pierre Adam

Xuan Loc Le

Julia Viard

Christine Plancon

Rachel Daudin

Pascale Koebel

Emilie Dorard

Christiane Rose

Feng-Jen Hsieh

Chih- Che Wu

Brigitte Potier

Yann Herault

Carlo Sala

Aiden Corvin

Bernadette Allinquant

Huan-Cheng Chang

François Treussart
email: francois.treussart@ens-cachan.fr

Michel Simonneau
email: michel.simonneau@inserm.fr

Fluorescent nanodiamond tracking reveals intraneuronal transport abnormalities induced by brain-disease-related genetic risk factors

Brain diseases such as autism and Alzheimer's disease (each inflicting >1% of the world population) involves a large network of genes displaying subtle changes in their expression 1 Abnormalities in intraneuronal transport have been linked to genetic risk factors found in patients 2,3 , suggesting the relevance of measuring this key biological process. However, current techniques are not sensitive enough to detect minor abnormalities. Here, we report a sensitive method to measure changes in intraneuronal transport induced by brain disease-related genetic risk factors using fluorescent nanodiamonds (fNDs). We show that the high brightness, photostability and absence of cytotoxicity 4 allow fNDs to be tracked inside the branches of dissociated neurons with 12 nm spatial and 50 ms time resolutions. As proof-of-principle, we applied the fND-tracking assay on two transgenic mouse lines that mimic the slight changes in protein concentration (~30%) found in brains of patients. In both cases, we show that the fND assay is sufficiently sensitive to detect these changes.

A polygenic architecture of brain diseases as diverse as autism spectrum disorders, schizophrenia and late-onset Alzheimer's disease is emerging, with the discovery of interplay between hundreds of genetic variants and subtle changes in gene expression, later referred as genetic risk factors 1 . The modelling of human brain diseases to understand the function of related genes usually relies on the establishment of transgenic mouse mimicking the effects of genetic changes 5 . As intraneuronal transport abnormalities have long been recognized to be linked to neuropsychiatric and neurodegenerative diseases 2,3 , we decided to mimic in vivo the changes induced by brain disease-related genetic variants and subsequently quantify their impact on the intraneuronal transport using primary cultures of mouse hippocampal neurons.

Previous attempts to quantify intraneuronal transport have been based on cargo labelling with genetic constructs of chimeric fluorescent proteins 6 . Limitations of this strategy are low transfection yield, uncontrolled protein overproduction, photobleaching of the reporters, and substantial cytotoxicity. Fluorescent semiconductor nanocrystals (quantum dots, QDs) have been widely used to probe a variety of cellular events 7 , owing to their high photoluminescence yield and good photostability. However, attempts to use QDs to study intraneuronal transport have been limited to the specific model of long axons of dorsal root neurons cultured in microfluidic devices 8 . Moreover, QDs blinking impedes high spatiotemporal resolution tracking and therefore biases transport parameter measurements as we show in this letter. Considering these intrinsic limitations, there is a need for developing new generic approaches able to screen the functional impact of brain disease-related genetic modifications.

Here, we developed a quantitative assay based on tracking of fluorescent diamond nanocrystals (fluorescent NanoDiamond, fND) in mouse hippocampal neurons (Fig. 1, Supplementary Videos 1 and 2). We used 30 nm-sized fNDs (see Methods and Supplementary Fig. 1a), whose fluorescence stems from nitrogen-vacancy colour centres created within the nanocrystals and acting as perfectly photostable and non-blinking emitters in the far-red spectral domain 9 (Supplementary Fig. 1b). Such remarkable properties have been already exploited in bio-applications requiring long-term tracking 10 . Moreover, fNDs have been reported to show a notably low cellular toxicity in primary neurons 11 . Fig. 1a shows the different steps of the fND-tracking assay, from neuron dissociation to video acquisition. To introduce fND into neurons, we used the endocytosis mechanism 12 .

We subsequently tracked fND-containing cargoes by pseudo-Total Internal Reflection Fluorescence (pseudo-TIRF) video microscopy at 20 Hz frame rate, and then made a thorough quantitative analysis of their motion. Pseudo-TIRF microscopy excites only the region of interest, a few micrometres in depth above the culture glass substrate (Supplementary Fig. 1c), leading to a high signal-to-background ratio (SBR). We determined the localization precision of the setup for different SBR, using fNDs immobilized on a glass coverslip (see Methods), and achieved a localisation precision smaller than 30 nm for SBR>3 (Fig. 1c). For the quantification of intraneuronal transport parameters, trajectories with more than 30% of constitutive points having a SBR<3 were excluded. Using such a filter, we obtained a mean localization precision of 12 nm over all trajectories (Inset of Fig. 1c, n=460 trajectories from 11 experiments). Fig. 1d displays a white-light illumination image of a main neuronal branch and its smaller branches, merged with one frame of Supplementary Video 1 showing fNDs at different locations (red spots), two of which moving in the same branch (Fig. 1e). Fig. 1f shows the kymograph of these two fNDs, highlighting the "stop-and-go" behaviour characteristic of organelle transport in neurons 13 . In order to characterize the fNDcontaining cargoes, we first simultaneously acquired LysoTracker-tagged lysosomes and fND using two-colour imaging (see Methods). We found a dynamical colocalisation of fNDcontaining cargoes and lysosomes in less than 5% of moving fNDs (Supplementary Video 3 and Supplementary Fig. 2b). We next studied by immunofluorescence, on fixed neurons, the colocalisation between fND-containing cargoes and markers of early endosomes (EEA1 and Rab5), of recycling endosomes (Rab7), of late endosomes (Rab11) and of post-Golgi endosomes (TGN38) 14 . We observed that fNDs can colocalize with each type of compartments (Supplementary Fig. 2). Together, our results indicate that fNDcontaining cargoes are endosomes in a vast majority of the cases.

In order to quantify the motion of fND-containing endosomes, we first obtained the fND trajectories from the videos and identified the "stop" and "go" phases (Supplementary Fig. 3 and Fig. 1g) from which we inferred six intraneuronal transport readouts: velocity (in µm/s), run length (in µm), processivity (in seconds), pausing time (in seconds), pausing frequency (events per minute) and the diffusion coefficient (in µm 2 /s). Velocity of fND-containing endosome was calculated as the length of the displacement vector over time from the first to the last point of a "go" phase, whereas the curvilinear distance and time separating these two points corresponded to run length and processivity, respectively. The diffusion coefficient D was calculated during the "go" phase, by fitting the mean-square displacement (MSD) to the quadratic equation MSD

(Δt)= v 2 Δt 2 +4D Δt,
where v is the velocity. According to the Stokes-Einstein law, D is inversely proportional to the intracellular viscosity. During a "stop" phase, the pausing time was defined as the duration from the first to the last point, the pausing frequency was the number of "stop" phases per minute. Mean values and other statistical properties of these parameters are provided in Supplementary Table 1. Apart from the quantitative readouts, the fNDtracking assay can also provide a superresolution mapping of microtubule bundles in freely developing neuronal branches. For example, the two trajectories of Fig. 1g are separated by ≈100 nm, suggesting that the two fND-containing endosomes travel along two adjacent microtubules inside the same branch. Supplementary Fig. 4 and Supplementary Video 4 show another region in which four trajectories of endosomes can be seen in the same neuronal branch, no more than ≈400 nm apart. Moreover, adjacent trajectories are separated by a distance of about 40-160 nm, which is consistent with reported values 8,15 .

Intraneuronal transport occurs in both anterograde (i.e. from the soma to the distal part) and retrograde directions (from distal part to soma). In order to unambiguously measure the transport parameters associated to each direction, we cultured hippocampal neurons in a microfluidic two-chamber device to ensure the directed growth of axons (see Methods, Fig. 2 and Supplementary Video 5). We observed that transport parameters are identical for anterograde and retrograde direction (Fig. 2c, p>0.05, 3 microfluidic chambers and 3 cultures, n=22 and n=51 trajectories for anterograde and retrograde direction respectively), as already reported for primary culture of hippocampal neurons 6 .

For this reason, we applied the assay to all freely-developing branches of neurons. This approach contributed to get a high throughput in transport parameters measurements (Fig. 1b). Finally, we checked that these readouts remained constant during the 45-minute recordings for each culture well (Supplementary Fig. 5), and that there were no significant differences between the readout values for two independent experiments (Supplementary Fig. 6).

Next, as a comparison to a reference label for nanoscale tracking, we tested quantum dots with similar charge, size and fluorescence spectrum than fNDs (see Methods). We observed that QDs are less efficiently internalized (Supplementary Table 2) and that all the moving QDs display ON-OFF fluorescence blinking, indicating that there is only a single QD per cargo (see Supplementary Video 6). This ON-OFF random blinking impacts the trajectory reconstruction and leads to biased transport parameters (Supplementary Fig. 7). As a consequence, the transport parameters inferred from the QD-tracking assay were not identical for technical duplicates, contrary to fNDs (Supplementary Fig. 8 and Supplementary Table 2 for a comparison of QD and fND in term of tracking performance).

Altogether, these results demonstrate that perfect photostability of fND is the key for a reliable transport measurement.

We then checked the sensitivity of the fND-tracking assay using a pharmacological drug impacting the microtubule-based intraneuronal transport, at nanomolar concentrations. This transport is dependent on the microtubule cytoskeleton integrity, and microtubule can be depolymerized by extracellular application of nocodazole. Here, we used 2 nM and 5 nM nocodazole concentration during the course of the 1 h-experiment, whereas this drug is standardly applied at micromolar concentrations for several hours [START_REF] Courty | Tracking Individual Kinesin Motors in Living Cells Using Single Quantum-Dot Imaging[END_REF] . As shown in Fig. 3a (4 embryos, n=39, 33 and 40 trajectories for 0 nM, 2 nM and 5 nM respectively), we observed (i) a decrease in velocity (p=3.8×10 -4 and p=1.4×10 -7 for 2 nM and 5 nM respectively), in run length (p=3.4×10 -4 , p=5.3×10 -6 ) and in processivity (p = 4.5×10 -3 , p=9.8×10 -5 ), and (ii) an increase in pausing time (p=0.003, p=6.4×10 -5 ). Conversely, we observed a decrease in pausing frequency only for 5 nM (p=0.016) and the diffusion coefficients were not significantly affected (Supplementary Fig. 9). The increase in pausing time and decrease in run length and processivity are consistent with motors unable to overcome the interruptions caused by microtubule depolymerisation. The constancy of the diffusion coefficient indicates that the viscosity is not affected inside neuronal branches. Altogether, intraneuronal transport parameters vary in a drug dosage-dependent manner and change as expected for microtubule depolymerisation.

Axonal defects and intracellular transport impairments have been identified in the early stages of Alzheimer's disease both in humans and in mouse models [START_REF] Stokin | Axonopathy and transport deficits early in the pathogenesis of Alzheimer's disease[END_REF][START_REF] Encalada | Biophysical Challenges to Axonal Transport: Motor-Cargo Deficiencies and Neurodegeneration[END_REF] . Amyloid-β (Aβ) peptide derived from the amyloid precursor protein together with TAU microtubuleassociated protein, a key pathogenic factor in Alzheimer's disease [START_REF] Querfurth | Alzheimer's disease[END_REF] , have been found to contribute to these transport deficits [START_REF] Vossel | Tau Reduction Prevents A -Induced Defects in Axonal Transport[END_REF] . As a validation of the ability of fND-tracking assay to record abnormal intraneuronal transport, we tested Aβ1-42 oligomers on intracellular endosome transport in cultured mouse hippocampal neurons. Here, we used Aβ1-42 concentrations of 0.5 µM and 1 µM (mixture of monomer, trimer and tetramer, see Fig. 3b, 1 culture, 2 glass coverslips, n=127, 149 and 137 trajectories for 0 µM, 0.5 µM and 1 µM respectively) for 24 h under physiological conditions. As shown in Fig. 3c, we observed (i) an increase in pausing time (p=0.0014 and p=0.002 for 0.5 µM and 1 µM respectively), and (ii) a decrease of velocity (p=0.86, p=0.015), run length (p=0.66, p=0.0003) and processivity (p=0.22, p=0.0004). Note that the pausing frequency is decreased at concentration as low as 0.5 µM (p=0.017) (Supplementary Fig. 10). The increase in pausing time and decrease in run length and processivity are consistent with previous reports on impairment of intraneuronal transport by Aβ1-42 17 . Moreover, transport parameters vary in a Aβ1-42 dosage-dependent manner at submicromolar concentrations.

The fND-tracking assay could therefore be used to screen drugs capable of rescuing the damaged intraneuronal transport found in AD.

Next we evaluated if the fND-tracking assay is sensitive enough to reveal the impact, on the intraneuronal transport, of slight protein concentration changes (≈30%) found in brain of patients [START_REF] Maussion | Convergent evidence identifying MAP/microtubule affinityregulating kinase 1 (MARK1) as a susceptibility gene for autism[END_REF][START_REF] Lepagnol-Bestel | SLC25A12 expression is associated with neurite outgrowth and is upregulated in the prefrontal cortex of autistic subjects[END_REF] . We first assessed the sensitivity of the methodology to test the change in concentration of proteins directly bound to microtubule, such as TAU or MAP2.

These molecules compete with molecular motors for MT binding sites, therefore acting as roadblocks [START_REF] Lakadamyali | Navigating the cell: how motors overcome roadblocks and traffic jams to efficiently transport cargo[END_REF] . Genetic risk factors regulating the attachment/detachment of MAPs, such as the protein kinase coded by MARK1 gene, have long been associated to Alzheimer's disease [START_REF] Mandelkow | MARK/PAR1 kinase is a regulator of microtubule-dependent transport in axons[END_REF] and Autism Spectrum Disorders [START_REF] Maussion | Convergent evidence identifying MAP/microtubule affinityregulating kinase 1 (MARK1) as a susceptibility gene for autism[END_REF] . We generated two Mark1 transgenic mouse lines (Fig. 4a), leading to three distinct Mark1 overexpression levels, namely line 38 (L38 het , heterozygotes), line 8 (L8 het , heterozygotes) and line 8 (L8 hom , homozygotes). We first measured the protein levels of Mark1 in WT, L38 het and L8 het animals (Fig. 4b, Supplementary Fig. 11a; n=10, 9 and 9 mice for WT, L38 het and L8 het respectively). L38 het and WT were not statistically different (8±4%, p=0.85), in contrast to L8 het which displayed 32±6% increase (p=0.011). In comparison, most common mouse models usually have larger modifications in protein content but suffer from artificial phenotypes.

We decided to test if this slight ≈30% increase is sufficient to induce changes in intraneuronal transport parameters, taking advantage of four different genotypes: WT, L38 het , L8 het and L8 hom (Fig. 4c). The Mark1 gene overexpression in L8 hom was measured by RT-QPCR to be twice that in L8 het (42±5% for L8 het , p=0.0013 and 87±15% for L8 hom , p=0.0010; n=4, 4 and 3 cultures for WT, L8 het and L8 hom respectively). This measurement was done on the same primary cultures as the ones used for the fND-tracking assay, right after trajectories acquisitions.

Quantification of the intraneuronal transport dynamics revealed significant variations for L8 het and L8 hom , but not for L38 het in which no changes were observed in any of the readouts (Fig. 4c, Supplementary Fig. 11b; n=420 trajectories/10 cultures, n=62/4, n=145/4, and n=85/3 for WT, L38 het , L8 het and L8 hom respectively). The latter is consistent with the absence of Mark1 overexpression for this transgenic line, therefore acting as an internal control. In L8 het and L8 hom , the monotonous increase in Mark1 gene overexpression levels was accompanied by a corresponding increase in velocity (p = 0.03, p = 0.006 for L8 het , L8 hom respectively), in run length (p = 0.029, p = 0.022 for L8 het , L8 hom respectively) and in processivity (p=0.037 for L8 hom respectively). We also observed a decrease in pausing frequency for L8 het (p=0.044, Supplementary Fig. 11b). Altogether, intraneuronal transport parameters vary in a gene dosage-dependent manner and they change as expected for Mark1-mediated regulation of the microtubule track hindrance (Fig. 4d) [START_REF] Mandelkow | MARK/PAR1 kinase is a regulator of microtubule-dependent transport in axons[END_REF] . We therefore demonstrated the sensitivity of our assay to detect microtubule roadblock impairments linked to brain diseases, for protein concentration changes as small as ≈30%.

Finally, we evaluated if the fND-tracking assay is sensitive enough to detect the effect of concentration change of one protein that do not belong to microtubule complexes but is indirectly involved in the intraneuronal transport via energy supplies. We focused on the psychiatric risk factor SLC25A12 that is required for the mitochondrial integrity and found associated with different types of Autism Spectrum Disorders and with Schizophrenia [START_REF] Fromer | De novo mutations in schizophrenia implicate synaptic networks[END_REF] . We generated one Slc25a12 transgenic mouse line (L2 het ) mimicking the slight overexpression of this gene as found in brain tissues of Autism Spectrum Disorders patients [START_REF] Lepagnol-Bestel | SLC25A12 expression is associated with neurite outgrowth and is upregulated in the prefrontal cortex of autistic subjects[END_REF][START_REF] Palmieri | Altered calcium homeostasis in autism-spectrum disorders: evidence from biochemical and genetic studies of the mitochondrial aspartate/glutamate carrier AGC1[END_REF] (Fig. 5a). We measured Slc25a12 protein levels in WT and L2 het and found a significant increase in L2 het (32±7%, p=0.043; n=5 mice) (Fig. 5b, Supplementary Fig. 12).

The quantification of the intraneuronal transport dynamic revealed significant variations with a decrease in run length (p=0.022) and processivity (p=0.012) (Fig. 5c; n=420 trajectories/10 cultures and n=105/3 for WT and L2 het respectively). This result demonstrates the sensitivity of the tracking assay to detect indirect intraneuronal transport perturbations, for protein concentration changes as small as ≈30%.

In this Letter, we have reported a hitherto unexplored approach to measure the changes of intraneuronal transport parameters induced by brain disease-related genetic risk factors. Our methodology relies on fluorescent nanodiamond tracking inside freely developing branches of living neurons. We showed that the high brightness, perfect photostability and absence of cytotoxicity of fNDs make it possible to perform a high throughput and high content intracellular transport measurement based on trajectory analysis. In Supplementary Table 3 and Supplementary Text 1, we compared our fNDtracking assay to other reported methodologies used for assessing intraneuronal transport. These published techniques, based on tracking of endosomes labelled with QDs 8 , lipophilic dyes [START_REF] Nakamura | Quantitative analysis of intraneuronal transport in human iPS neurons[END_REF] or chimeric fluorescent proteins 6 , yielded a smaller number of readouts (velocity and processivity) and showed smaller spatio-temporal resolution.

Moreover, we proved that unstable emission of QDs leads to unreliable measurements (Suppl. Fig. 8). The fND tracking assay has some limitations too, in particular (i) no particular cargo labelling, while chimeric fluorescent proteins can specifically tag the compartments of interest, and (ii) low two-photon absorption cross-section, preventing tracking in thick structures or in vivo by multiphoton microscopy. However, the fND nanoparticle-based tracking assay can be extended to non-linear nanolabels [START_REF] Mayer | Single KTP nanocrystals as second-harmonic generation biolabels in cortical neurons[END_REF] .

As a proof-of-principle demonstration of fND-tracking assay unique possibilities, we established transgenic animals mimicking the changes of protein concentrations (≈30%) found in brain of patients. The fND-tracking assay was sensitive enough to detect modifications of the intraneuronal transport parameters in the transgenic neurons. To the best of our knowledge, this is the first direct measurement of the functional impact of brain disease-related genetic risk factors using a nanoparticle-based methodology.

In a near future, with the swift development of the CRISPR/Cas9 genome editing technology [START_REF] Doudna | The new frontier of genome engineering with CRISPR-Cas9[END_REF] , it is possible to model multiple brain disease-related genetic risk factors in transgenic animals. Our fND tracking methodology is adapted to understand how these multiple genetic variants interact with each other to impair the intraneuronal transport. Furthermore, powerful methodologies to dissect the molecular basis of complex brain diseases are emerging such as 3D-human neuron cultures derived from induced pluripotent stem cells obtained from patients [START_REF] Choi | A three-dimensional human neural cell culture model of Alzheimer's disease[END_REF][START_REF] Paşca | Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture[END_REF] . In the long run, this method can be instrumental to develop an unbiased diagnosis of neuropsychiatric and neurodegenerative diseases, with potential applications in translational nanomedicine. . The two colours in each trajectory correspond to "go" phases (in green for fND #1 and yellow for fND #2) and "stop" phases (in blue for fND #1 and red for fND #2), as identified by our trajectory analysis algorithm (see Methods); bottom: two-state ("stop" and "go") representation of the same trajectories over time: fND #1 moved faster than fND# 2 (scale bar: 1 s).

Methods

Fluorescent nanodiamond production.

The nanodiamonds were radiation-damaged with a high-energy (3 MeV) proton beam, as detailed in Su et al. [START_REF] Su | Creation of high density ensembles of nitrogen-vacancy centers in nitrogen-rich type Ib nanodiamonds[END_REF] A thin diamond film (thickness<50 µm) was prepared by depositing ≈5 mg of nanodiamond powder on a silicon wafer (1×1 cm 2 size) and subsequently subjected to the ion irradiation at a dose of ≈2×10 16 H + .cm -2 . Afterwards, the radiationdamaged nanodiamonds were annealed at 800°C for 2 h to form fNDs. To remove graphitic carbon atoms on the surface, the freshly prepared fNDs were oxidized in air at 490°C for 2 h and microwave-cleaned in concentrated H2SO4-HNO3 (3:1, v/v) at 100°C for 3 h. The average number of nitrogen vacancy colour centres per fND is 15.

Pseudo-TIRF Microscopy setup and video acquisition

TIRF illumination was implemented on a two-stages inverted microscope (Eclipse Ti-E, Nikon, Japan), equipped with 100x magnification and 1.49 numerical aperture immersion oil objective (CFI Apo TIRF 100X Oil, Nikon, Japan). The excitation beam from a continuous-wave diode-pumped solid-state laser emitting at the wavelength of 561 nm with a maximum power of 100 mW (SLIM-561-100, Oxxius S.A., France) was expanded 16x and then focused on the back focal plane of the microscope objective, off the propagation axis to ensure partial internal reflection at the culture dish glass -medium interface. This configuration results in wide-field illumination of a volume confined to ≈2 µm above this interface and to an in-plane disc of ≈40 µm diameter, ensuring a larger signal-to-background ratio than in epifluorescence configuration. The maximum laser intensity was 20 kW/cm 2 in the sample plane. We used filters adapted to the spectral characteristics of nitrogen vacancy colour centres in diamond: a dichroic beamsplitter with a steep edge at 561 nm and a 97% flat transmission above this wavelength (zt561rdc, Chroma Corp., USA) and a band-pass filter centred on 697 nm wavelength with a fullwidth at half maximum (FWHM) of 75 nm (HC 697/75, Semrock, USA), on the detection channel. White-light illumination observations were done with the differential interference contrast mode of the microscope without changing the microscope objective. The whole microscope was enclosed in a cage incubator (Okolab, Italy) allowing to maintain a temperature of 37°C, 5% partial CO2 pressure and 100% hygrometry, necessary for live neuron imaging. Images and videos were recorded with a cooled electron multiplied CCD array detector (iXon-DU885, Andor Technology, Ireland), having a pixel size in the sample plane of 80 nm.

Video processing, trajectory extraction and analysis.

We recorded videos of total duration of 120 s, at a time resolution of 50 ms/frame with Nikon NIS software in the proprietary ND2 format (Fig. 1a). A filtering pretreatment was done with Fiji software (version 1.46j; NIH, USA), which consists in subtracting to each frame the median intensity of the whole stack in order to remove static fluorescent spots.

For each dynamic fND-containing endosome, we reconstructed the full trajectory using the Spot Detector plugin of ICY image analysis software (GPLv3 open source) developed by the Quantitative Image Analysis team at Institut Pasteur (Paris, France) [START_REF] Chenouard | Multiple hypothesis tracking for cluttered biological image sequences[END_REF] . Using the Track Manager plugin, we exported a text file containing the spot (X,Y) coordinates and the signal amplitude and background (based on a 2D-gaussian fitting of fluorescence spots), and we processed these data with a home-made program written for Igor Pro software (WaveMetrics Inc., USA). Detection of "stop" and "go" phases relies on two main steps, namely a coarse "stop" phase detection based on the confinement ratio function, and a refine "go" detection based on three different sequential filters as detailed in Supplementary Fig. 3. Transport readouts for each trajectory are then computed and the program finally makes a statistical report for the entire run set corresponding to one experiment, namely one LabTek well. The IgorPro program is available upon request.

Localization precision.

We calibrated the localization precision of our set-up by tracking the position of more than 100 fNDs immobilized on a glass coverslip and imaged over 100 frames. We then analysed the video with the same tracking software parameters as for the intraneuronal trajectories. Movies were background-subtracted using Fiji plugin with a rolling ball of 20 pixels, in order to mimic the effect of a median subtraction. For each fND, the localization precision was measured as the standard deviation of the center positions of the fluorescent spot over time. We then plotted all localization precisions with respect to the signal-to-background ratio (SBR) associated to each fND (Fig. 1c). SBR was determined as the ratio of the maximum fluorescence intensity of the fND (amplitude minus residual background) over the residual background intensity. Therefore, trajectories containing more than 30% of points having a SBR smaller than 3 were not considered, so that according to the calibration, we achieved a localization precision better than 30 nm.

Primary hippocampal neuron cultures.

For wild type neuron cultures, hippocampi from E18.5 OF1 mouse embryos were isolated in a dissecting medium (HBSS-Hepes) and hippocampus from at least four embryos were pooled together. Hippocampal neurons were then enzymatically dissociated (0.25% trypsin), mechanically triturated and plated on LabTek II (Nunc, USA) dishes (2x10 5 cells per well) coated with poly-DL-ornithin (Sigma-Aldrich, USA), in DMEM (Invitrogen, USA) supplemented with 10% foetal bovin serum (FBS), 0.1% GlutaMAX (Invitrogen) and 1% PenStrep (Invitrogen). Two hours after plating, DMEM was replaced by Neurobasal phenol-free medium (Invitrogen) supplemented with 0.1% GlutaMAX (Invitrogen), 2% B27 (Invitrogen) and 1% PenStrep (Invitrogen). Cultures from C57Bl6 transgenic mouse were conducted separately for each embryo and genotyping was performed elsewhere. Cultures in microfluidic devices (RD450 from Xona Microfluidics, USA) were performed on coated 22 mm coverslip, plated with 5.10 6 cells/chambers. Neurons were grown until DIV 17/18.

fNDs internalization in hippocampal neuron cultures.

We conducted fNDs internalization in neurons at DIV15/16. The maintaining medium was set aside and replaced by 0.5 ml of Neurobasal phenol-free medium (Invitrogen) to which we added 5 µl of ≈30 nm-sized fND stock solution, reaching a final concentration of 5 µg/ml. After 10 min incubation, the medium was replaced by the old maintaining medium and neurons were placed 20 min in the incubator before starting the video acquisition. The same internalization procedure was applied to QD (ref. Q21361MP from ThermoFisher, USA) but with 1:10 5 dilution of the stock solution i.e. 0.1 nM final.

fND-containing cargos staining and colocalisation analysis.

For lysosomes labelling, live neurons were stained using LysoTracker Green DND-26 (ref. L7526, ThermoFisher) applied at 100 nM concentration at least 1 h prior to acquisition. We only considered internalized fNDs, i.e. having either a directed motion or a static colocalisation with a lysosome (Supplementary Fig. 2b). For endosomes immunostaining, neurons were fixed with 4% PFA for 20 min at room temperature. EEA1, Rab5, Rab11, Rab7 and TGN38 were labelled overnight at 4°C ). The DualView contains another green/red dichroic filter followed on each channel by a bandpass filter (Ref. D535/40M for green emitters and ET-BandPass-700-75 for fND, both from Chroma Technology, USA). The excitation laser powers were adjusted for each channel so that dynamic range was identical at given camera settings (EMgain=60, preamp gain=3.8, and digitalization speed 35 MHz). The slight shift between both channels was measured using 100 nm TetraSpeck fluorescent beads (Ref. T7279, ThermoFisher). For colocalisation study of fixed cultured, z-stack (7 planes with 0.25 µm step, total of 1.75 µm displacement) were recorded for each field of view and maximum intensity projections were carried out. As for video microscopy, we used ICY Spot Detector 33 plugin to extract spot coordinates (in pixels), spot maximum intensity (in counts) and spot size (surface in pixels#). Then, a custom program was written with IGOR Pro to count colocalised spots between each half of the image within 1.5 pixels uncertainty (equivalent to one standard deviation) in x and y directions. To filter out non-specific labelling, we only considered spots composed of 15 pixels (≈350 nm in diameter, compatible with the convolution of the microscope point spread function and 100 nm sized endosomes) and being at least three times brighter than the dimmer spot (values empirically determined). Moreover, as fNDs are located inside endosomes, we rejected colocalisation candidates having a fNDs spot size larger than the labelled-endosome one. This led to colocalisations statistics in the z-stack volume, but in this volume, only fNDs that were moving at the time of fixation would have been considered for transport parameters measurement. From transport quantification videos, we estimated to 9.0 ± 0.6 % this fraction of fNDs moving. However, all videos have been recorded at a single focused plane that only displays part of all fNDs spots detected in the whole z-stack volume. Considering that fNDs are homogeneously distributed in the sample volume, the single-plane detectable fraction corresponds to the ratio of the depth of field (nλ/NA²=0.42 µm, for n=1.33) over the 1.75 µm z-stack thickness, which yields 24%. Therefore, assuming that one detects moving fNDs with the same yield in a single focused plane than in the z-stack volume (but out-of-focused), we infer a fraction of possibly moving fNDs in the analysed z-stack volume to be only 24%×9%=2.2%. We applied this correction factor of 2.2% to z-stack raw colocalisation data to obtain the proportion (≈10-40%) of each type of moving fND-cargoes displayed in Supplementary Fig. 2c.

Microtubule destabilizing-drug experiment.

Nocodazole powder were purchased from Sigma-Aldrich (St Louis, MO, USA) and resuspended in dimethylsulfoxide (DMSO). Nocodazole was added to the cultures after fND protocol internalization and the DMSO volume added to each well was adjusted to be 0.5% of the total medium volume per well.

Preparation of oligomeric Aβ1-42 peptides.

1 mg of synthetic Aβ1-42 (Bachem AG, Switzerland) was dissolved in 500 µL trifluoroacetic acid (Sigma Aldrich) and sonicated during 10 min. After evaporation under nitrogen, the preparation was processed according to Klein et al [START_REF] Klein | Aβ toxicity in Alzheimer's disease: globular oligomers (ADDLs) as new vaccine and drug targets[END_REF] . The pattern of oligomers was checked by Western blot (see Fig. 3b), with the following gel composition: 10-20% Tris-Tricine, 5 µL Aβ1-42 preparation at 100 µM concentration, and Anti-Human sAPP alpha (clone 2B3) Mouse IgG MoAb antibody (IBL/Tecan AG, Switzerland).

Mark1 and Slc25a12 transgenic mice constructs. We used a 3,200 bp mouse CamKIIα and a regulatory sequence of 711 bp intron and polyA SV40 in a pGL3-basic vector. The pGL3-modified vector was realized in two steps: (i) the regulating sequence "intron+polyA SV40" (711 bp) was amplified by PCR from pCDNA1.1 vector with the following primers: forward 5'-TATATCTAGACCCGGGTGGACAAACTACCTACAGAG (XbaI site underlined) and reverse 5'-TATAGGATCCGCGGCCGCAGAAATATGGCGTTGATACC (BamHI site underlined); (ii) the specific promoter "mouse minimal promoter CamKIIα" (3,200 bp) was amplified by PCR from mouse brain cDNA with the following primers: forward 5'-TATAGCTAGCGAGATTCTTCCAGCTAGTTC-3' (NheI site underlined) and reverse 5'-TATAAAGCTTCCGTGCTCCTGAGTGCAAAC-3' (HindIII site underlined). The XbaI/BamHI and then the NheI/HindIII digestion products of the amplicon were inserted into the two multiple cloning site of the pGL3 basic vector. E. coli DH5α cells were cotransformed with these constructs. The coding regions of the mouse Mark1 gene (2,386 bp) and mouse Slc25a12 gene (2,034 bp) were amplified by PCR (sequences of primers and probes are available on request. The two HindIII/SmaI digestion products of the amplicons were inserted into the multiple cloning site of the pGL3 modified vector. E. coli DH5α cells were co-transformed with this shuttle construct. Transgenes were injected in C57/Bl6 fertilized eggs for random integration into the mouse genome (CNRS SEAT/TAAM UPS 44, Villejuif, France).

Mark1 and Slc25a12

DNA extraction & genotyping. Tissue from mouse hippocampus embryo was digested overnight at 55°C in the digesting buffer: Tris HCl pH=8 (50 mM), EDTA pH=8 (100 mM), NaCl (60 mM), SDS (1% w/v), complemented with 15 µl of proteinase K (Qiagen N.V., Netherlands). Inactivation was done at 99°C for 10 min and 3 µl of 1% (w/v) RNaseA (Thermo Fisher Scientific, USA) was added prior to incubation at 37°C for 90 min. DNA was then extracted in 300 µl of Phenol/Chloroform, and after 5 min centrifugation at 13200 rpm, aqueous phase was diluted elsewhere with 10% of sodium acetate (3 M concentration). Then, 800 µl of cold ethanol were added before freezing the solution at -80°C for 30 min, followed by 30 min of 13200 rpm centrifugation at 4°C. Supernatant was removed and the pellet was rinsed at least once with ethanol 70%. The pellet was finally dried at room temperature and resuspended in sterile water. PCR was then performed using primers for Mark1 and Slc25a12 as follow: UPCamKIIα GACTAAGTTGTTCGCATCC; DW_Mark1: TGACGTAATGGAGTTTCTACAC; DW_Slc25a12: TTTCAAATGTCACCTCTCCA. Each PCR amplification was prepared by mixing 0.5 U Hifi taq DNA polymerase (Life Technologies, USA) 1 μL of 10x Buffer, 2 mM MgSO4, each deoxynucleoside triphosphate at a concentration of 0.2 mM, 1 µM of each of the corresponding primer, and 50 ng of genomic DNA A final volume of 10 μL was achieved using water. A negative control using all reagents except template DNA was also included.

Reactions were carried out in a Mastercyler® pro S thermocycler (Eppendorf, Germany) using the following cycling conditions: 2 min at 95°C followed by 28 of 95°C for 15 sec, 58°C (for Mark1) or 56°C (for Slc25a12) for 30 s, and 72°C for 30 s. A final extension step at 72°C for 7 min was performed after the cycles. After this step, samples were kept at 4°C until being electrophoresed in 1.5% agarose 1xTBE gels. For visualization of electrophoresed PCR products, gels were stained with 1xSYBR® Safe DNA Gel Stain (Life Technologies) and digital images were captured in a InGenius 3 (Syngene, UK).

Mark1 RNA extraction and RT-qPCR. Primary neuronal cells were collected in Trizol® (Life Technologies) for RNA extraction as described by the manufacturer. Reverse transcription (RT) was carried out at 50°C for 30 min in a 20 μl RT mixture containing 1 μg total RNA in Maxima First Strand Synthesis kit (Thermo Fisher Scientific) as described by the manufacturer. The cDNAs generated were amplified by real-time PCR, using probes (obtained from Merck Serono, Germany) labeled at their 5' ends with a fluorogenic reporter dye (FAM) and at their 3' ends with a quencher dye (TAMRA). Sequences of primers and probes are available on request. PCR assays had a final reaction volume of 20 μl, and contained 2 U of Taq polymerase (Applied Biosystems, USA), 10 μM primers and fluorogenic probe. PCR was carried out over 40 cycles of 95°C for 15 s, 60°C for 1 min and 50°C for 1 min. We used the DNA Engine Opticon 2 sequence detection system (Bio-rad, USA), with the Opticon Monitor software for data analysis. For each group, the cDNAs synthesized from total RNA were serially diluted to cover the 0.19 ng to 50 ng range for specific mRNAs and 0.98 pg to 250 pg range for 18S rRNAs. These serial dilutions were used to construct standard curves for 18S and for each gene of interest and to calculate the amounts of RNA. Each qPCR signal was normalized with respect to 18S and expressed in arbitrary units.

Mark1 and Slc25a12 proteins extraction and Western Blot.

Hippocampus were dissected from P15 Mark1 and Slc25a12 transgenic mice and proteins were extracted in 100 µl of lysis buffer: Tris HCl pH7.4 (20 mM), NaCl (100 mM), NP40 (1% v/v) and protease phosphatase inhibitor dose (Thermo Fisher Scientific). After milling and restoring for 30 min on ice, centrifugation was performed at 13200 rpm at 4°C for 10 min. Supernatant was then removed and kept at -80°C until Western Blots were performed. Protein electrophoresis migration was performed in 4 staining. Secondary HRP-conjugated antibodies were used in corresponding species and enzyme reaction was activated using Clarity Western ECL Substrate (GE Healthcare, USA), and imaged with ChemiDoc XRS (Bio-Rad). Slc25a12 and Mark1 quantification normalized to Actin were performed using images acquired at the best dynamic range (very few saturated pixels).

Statistical analysis.

Comparison between two data sets was performed with the statistical analysis tools integrated in Igor Pro (WaveMetrics, USA). The pipeline analysis first applies a Kolmogorov-Smirnoff rank test of the null hypothesis "data follow a Gaussian (normal) distribution". In most cases, normality hypothesis was rejected and thus a Mann-Whitney-Wilcoxon comparison two-tailed test was performed. When the normality hypothesis could not be rejected, two-sample two-tailed t-test was performed, after evaluating the null hypothesis of equal variance. Data collection for nocodazole and transgenic mouse experiments were performed blind to the conditions of the experiments. No statistical methods were used to predetermine sample sizes, but our sample sizes are similar to those generally employed in the field [START_REF] Vossel | Tau Reduction Prevents A -Induced Defects in Axonal Transport[END_REF] . Stars are referred to the following significance level: * for p<0.05; ** for p<0.01; *** for p<0.001.

FiguresFigure 1 |

 1 Figures

Figure 2 |Figure 3 |Figure 4 |

 234 Figure 2 | Transport parameter quantification for anterograde and retrograde motions in axons of neurons grown in microfluidic chamber. a, DIC image of axons emerging from one microfluidic channel. Scale Bar: 5 µm. b, Colour-coded kymograph showing anterograde (green) and retrograde (red) motions. Scale bars: time (horizontal) 5 s, space (vertical) 10 µm. c, Quantification of the transport readouts. No significant (ns) differences between both directions of motion were observed (Wilcoxon and Mann-Whitney two-tailed test p>0.05). Data are displayed as mean values ± s.e.m. Figures written inside the bars represent the total number of trajectories from n=3 microfluidic chambers from n=3 cultures.

Figure 5 |

 5 Figure 5 | Sensitivity of the fND-tracking assay to slight overexpression of autismrelated Slc25a12. a, Schematic representation of the Slc25a12 transgene used to create transgenic mouse line L2. b, Quantification of Slc25a12 expression in L2 het showing an increase of 32±7% (p=0.043) in Slc25a12 protein level as measured by Western Blot. c, Effects of Slc25a12 overexpression on velocity, run length and processivity intraneuronal transport parameters. Velocity and run length are decreased when Slc25a12 is slightly overexpressed. All data are presented as mean ± s.e.m. (calculated from the total number of samples in (b) or of independent cultures in (c)). Figures written inside the bars represent the number of mouse hippocampus in (b) or the number of trajectories/number of independent cultures in (c), with one experimental run associated to one culture of one embryo. Statistical significance: one star (*) indicates p value smaller than 0.05 (Wilcoxon and Mann-Whitney two-tailed test).

  Fluorescence acquisitions were performed in two colours with the same electron multiplied CCD array detector array as for videomicroscopy, with a DualView DV2 system placed in front of the detector (Photometrics, USA). The DualView splits the image vertically in two parts: on one half of the sensor surface green light emitted by LysoTracker and AlexaFluor 488 is detected, and red light from fNDs is recorded on the other half (Supplementary Video 3). Fluorophores are excited with solid-states lasers: Sapphire 488 (Coherent, USA) at 488 nm wavelength for LysoTracker and AlexaFluor 488, and SLIM 561 (Oxxius S.A., France) at 561 nm wavelength for fNDs. The two laser beams are combined with a dual-band dichroic filter (Ref. Di01-R488/561, from Semrock, USA

	using Cell Signaling (USA)
	ref. C45B10, C8B1 and D4F5, and Santa Cruz (USA) Ref. sc-271608, sc-271624
	respectively as primary antibodies. Secondary antibodies tagged with AlexaFluor 488 dye
	(Ref. 111-545-144 and 715-547-003, from Jackson ImmunoResearch Inc., USA) were then
	applied for 1 h at room temperature.

  -20% Mini-PROTEAN Tetra TGX gels (Bio-Rad, USA) in a TGS buffer (Tris, 5 mM; Glycine, 192 mM; 0.1% SDS, pH 8.3) with 40 µg of protein lysate after denaturation for 10 min at 95°C. Nitrocellulose membranes (Trans-Blot Turbo, Bio-Rad) were used for protein transfer. Membrane was then blocked in TBS 1X Tween 0.1%, 5% non-fat milk for 1 hour at RT under shaking. Primary antibody Mark1 (ref. 3319S, Cell Signaling, USA) and Slc25a12 (ref. ab107436, Abcam, UK) were incubated overnight at 4°C either in 5% BSA and in 5% milk respectively. Normalization was performed using Actin (ref A3854, Sigma Aldrich, USA)

Acknowledgments

We thank Paul Tchénio for his comments on the manuscript, Alain Lombard for his contribution to data processing, Joanna Lipecka for her help with western blotting. This work was supported by a public grant overseen by the French National research Agency (ANR) as part of the « Investissement d'Avenir » program IDEX Paris-Saclay ANR-11-IDEX-0003-02 (S.H.); the ANR and the Ministry of Science and Technology (Taiwan) through grant ANR-2010-INTB-1002 (M.S., F.T., H.C.C., C.C.W.); the ANR through the Eranet Euronanomed project 2011-ERNA-006 (F.T., M.S., C.S., A.C.); the Fondation Jérôme Lejeune (M.S.), the European Union FP7-Health "AgedBrainSysBio" grant (M.S.); grant n°12018592 from Region Ile-de-France (F.T.); CNRS "Programme interdisciplinaire" (F.T., M.S.) and Triangle de la Physique contract no. 2012-038T (F.T., M.S.).

Authors contributions

SH, FT and MS conceived and designed the experiments; SH, NM, YLM, AMLB, MPA, SM, XLL, JV, CP, ED, CR and RD performed the experiments; SH, NM, SM, MPA and XLL analyzed the data; PK, FJH, CCW, BP, YH, CS, AC, BA and HCC contributed to materials/analysis tools; SH, FT and MS wrote the paper.

Additional information

Supplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to F.T. or M.S.

Competing financial interests

The authors declare no competing financial interests.

Supplementary Information

"Fluorescent nanodiamond tracking reveals intraneuronal transport abnormalities induced by brain disease-related genetic risk factors"

Simon HAZIZA, Nitin MOHAN, Yann LOE-MIE, Aude-Marie LEPAGNOL-BESTEL, Sophie MASSOU, Marie-Pierre ADAM, Xuan Loc LE, Julia VIARD, Christine PLANCON, Rachel DAUDIN, Pascale KOEBEL, Emilie DORARD, Christiane ROSE, Feng-Jen HSIEH, Chih-Che WU, Brigitte POTIER, Yann HERAULT, Carlo SALA, Aiden CORVIN, Bernadette ALLINQUANT, Huan-Cheng CHANG, François TREUSSART and Michel SIMONNEAU

Supplementary

Supplementary Video 1 | Video from which Fig. 1d-e snapshots were extracted. The white frame delimits the neuronal branch in which the endosomes containing fND #1 or fND #2 (same as in Fig. 1f

Supplementary Tables

Supplementary Table 1 | Statistical analysis of intraneuronal transport parameters. All trafficking parameters were extracted from n=460 trajectories acquired from n=11 C57Bl6 mouse embryos. The range and interquartile range correspond to the 0-100% and 25-75% percentiles, respectively. Supplementary Table 2 | Comparison between fND-tracking assay and QD-tracking assay, in terms of the nanolabel physical properties, and of the tracking-assay performance index (localization precision, fraction of moving labels, number of trajectories per field of view and number of missed points in trajectory reconstruction). For the localization precision, fNDs and Qdots were deposited on a coverslip and tracked over 100 frames to measure the standard deviation of (X;Y) coordinates over time. Because of QDots blinking, we considered the maximum of emission signal to measure the SBR for each particle. Altogether, the table shows that QDs and fNDs have similar physical properties but that the performance indices of fNDs are all more favorable than the ones of QDs. All tracking data have been acquired at the same excitation wavelength (561 nm) and the same laser power for both nanolabels.

Supplementary Table 3 | Comparison of the fND-tracking assay with published methodologies used to monitor the intraneuronal transport, regarding ease-of-use, spatio-temporal resolution, toxicity and potential in vivo applications.

In particular, we compared our approach with the one using QDs, first reported in Cui et al 1 , and the one of Nakamura et. al. 2 using lipophilic dye CM-DiI. We also included the fluorescent protein category as it is a well-established and versatile molecular cell biology Footnote citations refer to the list of references provided in Supplementary Text 1.

Red and green colors indicate pros and cons properties of each technique. Orange color codes

for what we consider as a moderate drawback in the context of intraneuronal transport measurement.

Supplementary Text 1 | List of references cited in Supplementary Table 3 3. Supplementary Figures

Supplementary Figure 1 The "control" bar corresponds to colocalizations of fNDs with non-specific secondary antibodies Alexa488 (no primary antibody). Data displayed have been corrected (multiplicative factor) to take into account the fraction (2.2%) of moving fNDs only (see Methods). Note that the sum of all contributions is ≈110%. However, as EEA1 is an effector of Rab5, it is always associated to this marker, and its contribution has to be excluded from the total, which in turn is Supplementary Figure 3 | Detection of the "stop-and-go" motion phases. a-b, Coarse detection of "go" phases. a, The confinement ratio function Rconf is calculated for each trajectory point, using a forward sliding window of four consecutive points, as the relative distance drel between extreme positions i=1 and i=4 over the absolute distance Σdi (i=1,…,4). Rconf is used to discriminate between static ("stop") and directed ("go") phases of motion, where Rconf ≈ 1 corresponds to an endosome in a directed motion "go" state, and Rconf ≈ 0 corresponds to the "stop" state. b, Graphic representation of Rconf function applied to trajectory #2 (Fig. 1), revealing the presence of these two phases, with a histogram for Rconf distribution on the right. In the trajectory analysis algorithm, a "go" or "stop" state is assigned to each trajectory point as a function of its Rconf value relative to a cutoff fixed at Rconf cutoff =0.9 (horizontal dashed black line). Green and blue stars referred to short GO and STOP phase respectively. c, Kymograph of trajectory#1 and #2 showing green and blue arrow heads pointing out the same position as stars in (b). These events are usually missing when kymograph is used to infer velocity, run length and pausing time, leading to erroneous measurements. (d-f) Refined detection of "stop" phases. d, If two consecutive "go" state positions (depicted in green) are separated by a distance too small to be determined with precision (below the resolution of this method), the first is considered to be a "stop". Scale bar: 100 nm. e, If the angle between two consecutive segments of motion is larger than 70 degrees, the point separating the two segments is considered to correspond to a "stop". Scale bar: 50 nm. f, If a point within a "stop" region but is identified as a "go", it is considered to be a positive false and is reassigned as a "stop". Supplementary Figure 7 (caption in the next page) Supplementary Figure 7 | Failure of QDs to provide reliable transport parameters. a, Distributions of missed points (absence of nanoparticle signal either due to defocus and due to blinking in the case of QDs) per trajectory in tracking analysis of QDs (grey) and fNDs (black) labeled cargoes. For QDs, the missed-point fraction is mostly homogeneously distributed in a broad range (0-35%) while it is peaked around zero for fNDs. The histogram in inset shows the average fraction of missed detections for a given dataset. The trajectories from the three QD datasets were selected based on a maximum fraction of missed points/trajectory accepted (low-pass filtering with 10, 20 and 35% cutoffs). Vertical figures in the bars correspond to: # of experiments/# of filtered trajectories. To get a larger number of filtered trajectories from QDs analysis than from fNDs at 10% cutoff, the QDs missed-points/trajectory cutoff has to be set at 20%. Note that for similar size of datasets, 3 experiments need to be conducted for QDs against only 2 for fNDs, due to a lower internalization efficiency of QDs, as summarized in Suppl. Table 2. Moreover, the fNDs 10% cutoff corresponds to an average of only ≈1% missed points/trajectory (cargoes going out of focus), while the 20% cutoff for QDs is associated to ≈8% missed points/trajectory due to blinking. When performing the transport parameter calculation from the filtered trajectories, we observed that space-dependent parameters (velocity, run length and diffusion coefficient) increased with increasing missed-point fraction cutoff, and differed from values inferred from fND-tracking (considered as ground truths). This can be interpreted as the direct consequence of ICY Spot Tracker algorithm which infers missed points (QD dark period) and creates aberration. Bottom: p-values from Wilcoxon U-test. fND/QDs mm% corresponds to the comparison of fND to QD data for different missed-point fractions (mm=10-35%). b, Left: Portion of a QD trajectory (purple lines) as determined with ICY Spot Tracker. The red circles indicate QDs spots as detected by ICY Spot Detector plugin in a single frame. In the left part of the trajectory, where the QD has long dark periods, the tracking algorithm is not able to connect spots from the moving QD together and therefore create aberrant segments. In the opposite, the right portion in yellow brackets shows full connectivity. Right: despite the continuity, a significant fraction of the trajectories is made of inferred segments (in yellow; white numbers are in pixel unit). These aberrant segments are only one time-frame long (50 ms) and can be as large as 14 pixels (i.e. ≈1.1 µm), which correspond to an aberrant velocity of 22 µm/s. c, Comparison of scattered plot of run length vs processivity for fNDs (left) and QDs (right). Black lines indicate extremal cargoes velocities (1 µm/s and 5 µm/s lower and upper bounds respectively) as reported in the literature (e.g. D. Zala et al., Cell 152, 479 (2013)) and consistent with fNDs measurements. The QD scattered plot shows a significant fraction of velocities larger than the upper bound, especially at short processivities (as displayed in the zoom of panel d). Therefore, the more we increase the fraction of missed point per trajectory (from 10 % to 35 %), the more we increase the proportion of such aberrant spatial displacements. This will thus affect upward the values of the run length, the velocity and the diffusion coefficient, as observed in a. Altogether, these results demonstrate that QDs cannot be used to measure the intraneuronal transport parameters as it will lead to biologically irrelevant values. and diffusion coefficient displayed no (or very little) significant differences for the Mark1transgenic lines L38 het , L8 het and L8 hom (p=0.684, p= 0.787, p=0.164, respectively, for L38 het ; p=0.413, p=0.044, p=0.337, respectively, for L8 het ; p=0.252, p=0.252, p=0.187, respectively, for L8 hom ). Supplementary Figure 12 | Quantification of the overexpression of Slc25a12 in the hippocampus in transgenic lines and additional intraneuronal transport parameters. a, Western blotting was performed on hippocampal tissue dissected from P15 mice from the Slc25a12-transgenic line L2 het , with comparison to WT mice. WB was carried out with an antibody against Slc25A12 (top) and an antibody against actin (bottom) (n=5 P15 mice both WT and TG). b, Pausing time, pausing frequency and diffusion coefficient displayed no significant differences for the Slc25a12-transgenic lines L2 het (p=0.092, p=0.252, p=0.873, respectively). ***


M K Co

Light and Transmission Electron

Microscopies (LM and TEM) hold potential in bioimaging owing to the advantages of fast imaging of multiple cells with LM and ultrastructure resolution offered by TEM. Integrated or Correlated LM and TEM are the current approaches to combine the advantages of both techniques. Here we propose an alternative in which the electron beam of a scanning TEM (STEM) is used to excite concomitantly the luminescence of nanoparticle labels (a process known as cathodoluminescence, CL), and image the cell ultrastructure. This CL-STEM imaging allows obtaining luminescence spectra and imaging ultrastructure simultaneously. We present a proof of principle experiment, showing the potential of this technique in image cytometry of cell vesicular components. To label the vesicles we used fluorescent diamond nanocrystals (nanodiamonds, NDs) of size ≈150 nm coated with different cationic polymers, known to trigger different internalization pathways. Each polymer was associated to a type of ND with different emission spectrum. With CL-STEM, for each individual vesicle, we were able to measure (i) their size with nanometric resolution, (ii) their content in different ND labels, and realize intracellular components cytometry. Contrary to the recently reported organelle flow cytometry technique that requires cell sonication, CL-STEMbased image cytometry preserves the cell integrity and provides a much higher resolution in size. Although this novel approach is still limited by a low throughput, the automatization of data acquisition and image analysis, combined with improved intracellular targeting, should facilitate applications in cell biology at the subcellular level.

Simultaneous cathodoluminescence and electron microscopy cytometry of cellular vesicles labeled with fluorescent nanodiamonds

Sounderya Nagarajan, † Catherine Pioche-Durieu, ‡ Luiz H. G. Tizei, † Chia-Yi Fang, § Jean-Remi Bertrand, || Eric Le Cam, ‡ Huan-Cheng Chang, § Francois Treussart,* ,⊥ and Mathieu Kociak* , † Cell imaging techniques have been constantly evolving. Fluorescence microscopy is most widely used, owing to the possibility to label cell compartments with high specificity by immunofluorescence or by the expression of fluorescent proteins. In the last decades fluorescence-based super-resolution microscopies have opened new perspectives in structural imaging [1][2][3] . This is particularly true in studying cellular dynamics and a striking example is the monitoring of endocytotic pits and actin filaments formation imaged at a resolution of 84 nm by structured illumination microscopy 4 . However, there still exist complexities in sample preparation, choice of fluorophores and difficulties in imaging the cellular morphology at sub-organelle resolution, despite these recent progresses.

On the contrary, electron microscopy (EM) easily reaches this spatial resolution when conducting structural investigations. Techniques where fluorescence and EM imaging can be correlated on the same sample, usually coined Correlative Light and Electron Microscopy (CLEM), have shown great success in recent years and are becoming standard 5 . Moreover, with the recent development of genetically encoded tags providing both EM and LM contrasts 6 and complementing advantageously immunochemical nanogold labeling 7 , the gap between EM and LM is about to be bridged. These methods utilizing both electron and light microscopies are implemented either independently or in correlative or integrated manners 8 . In conventional CLEM, samples are transferred between the light and the electron microscopes. This approach requires locating the same region of interest with fiducial markers 9 , which is not straightforward as there are non-linear distortions of the images due to various scanning systems. Integrated light and electron microscopy tries to get around these issues by using a fluorescence detection set up fitted on an electron microscope 9 , but it requires a light source aligned with the electron beam to excite the emitters.

An interesting alternative is to use electrons not only for structural imaging, but also to take advantage of the luminescence of some materials when they are probed with an accelerated electron beam, an effect known as cathodoluminescence (CL) 10 . This implies that the CL emission from the sample can be collected while it is imaged by an electron microscope without the need to move it from EM to LM setup. This approach has been used via the combination of CL and secondary electron scanning EM (SEM) for simultaneous luminescence and structural imaging of fluorescent rare-earthdoped yttrium or gadolinium oxide (Y2O3 or Gd2O3) particles after their uptake in cells 11,12 and europium-zinc-codoped Y2O3 nanoparticles of size down to 30 nm 13 . Although SEM combined with CL (SEM-CL) provides a sub-cellular resolution 11 , it is not sufficient for determining cell ultrastructure. On the other hand, Scanning Transmission Electron Microscopy (STEM) offers such an ultrastructural resolution, and it is thus appealing to extend SEM-CL to STEM-CL so as to get both ultrastructure and luminescence information in parallel. Indeed we demonstrated recently that STEM-CL is sensitive enough to address single nanoparticles, such as individual ≈20 nm sized core/shell quantum dots 14 or ≈100 nm sized nanodiamonds (NDs) with embedded defect centers 10,15 . In our CL-STEM configuration, the light collected is spectrally analyzed at each beam position, yielding one CL spectrum per pixel, and the matrix of CL spectrum is called a hyperspectral image.

NDs are actually remarkable STEM-CL labels owing to the large quantum yield and low electrobleaching of the embedded luminescent defects. Moreover, we have used cationic polymercoated NDs to deliver gene to Ewing sarcoma cells in culture 16 and have shown, in this context, that the internalization pathways and therefore the corresponding vesicular compartment labeled by the fluorescent ND (size ≈50 nm), depends on the cationic molecules used 17 In this Letter, we report a novel ultrastructural image cytometry method to investigate quantitatively the cellular uptake of nanoparticles. Our approach relies on the combination of STEM-CL imaging with fluorescent NDs having different spectral signatures for each type of cationic coating. We applied our method to some quantitative characterization of the compartments containing ND uptaken by human Ewing sarcoma cells A673 in culture. We studied single (ND-PEI or ND-PAH alone) and double labeling (both types of cationic ND put together) situations. Four hours after their cellular uptake, all NDs localized inside vesicles and were not found free in the cytoplasm. From ultrastructure images, we inferred the size of individual ND-containing vesicles, and used the ultrastructure-correlated CL emission to count the number of fluorescent NDs inside each vesicle.

These counts are equivalent to luminescence intensities in conventional cytometry. For each vesicle we get a set of data made of its size, the number and the type (PEI, PAH or mixed PEI/PAH coating) of cationic NDs it contains. These data allowed us to build plots offering a synthetic view of all the information at the vesicle scale. Being based on ultrastructural imaging our novel cytometry is a method that could be further developed by extracting information, beyond the vesicle size.

Results and Discussion

We have used NDs with diameters ≈150 nm (see Supporting Information) containing nominally either Nitrogen Vacancy (NV) color centers (further referred as Type 1 NDs), having a red CL emission 15 or Nitrogen Vacancy Nitrogen color centers (H3) with a green CL emission 15 (further referred as Type 2 NDs). Type 1 NDs are made from synthetic precursors while the Type 2 NDs are made from natural diamond, which implies a better control of nitrogen impurity in Type 1 NDs than in Type 2 NDs. We observed that Type 1 NDs were pure red emitters while Type 2 ND sample was composed of a mixture of either green or red emitting NDs. We measured the content of pure green emitting NDs in Type 2 sample and found it to be 57±2 % (Supporting Information Figure S1), with the rest (43%) being composed of NDs with a pure red emission. We also observed that ND in both samples had crystals that did not show any luminescence. We measured the fraction of fluorescent NDs to be 67±5% for Type 1 and 62±3% for Type 2.

Type 1 NDs were coated with PAH, (ND-PAH) and Type 2 NDs with PEI (ND-PEI). We incubated these cationic polymer-coated NDs with A673 cells, either separately or in conjunction (see Methods). The polymer coated NDs were spontaneously taken up by cells, and we then analyzed their intracellular distribution by STEM and CL-hyperspectral imaging. STEM enables imaging at the scale of a whole cell (Figure 1A) down to the ultrastructure (Figure 1B), in either a Bright Field (BF) mode with contrasts similar to that of conventional TEM, or High Angle Annular Dark Field (HAADF) with roughly speaking an inversed contrast. In both modes, subcellular compartments like mitochondria, lysosomes, endosomes and nuclear membranes, and at the same time NDs, are observed with a high contrast. NDs appear as black or white features in either BF or HAADF mode respectively. Figure 1C displays the detection system: the two images are obtained by scanning an electron beam (acceleration voltage ≈ 60 kV) onto the sample, and collecting the BF and the HAADF signal at each scan position.

At the same time, a CL spectrum, showing clear NV or H3 signatures (Figure 1D) is collected at each scan position. The NV signature presents a well-known form, consisting in a Zero Phonon Line (ZPL) centered on 575 nm wavelength (corresponding to the neutral form 18 NV 0 followed by a convoluted series of peaks corresponding to phonon replica). Various analyses can be performed on this set of data (later called a spectrum image, Spim). The most straightforward method is to integrate the intensity in a given wavelength range (Figure 1D) for every pixel of the Spim and map this intensity to each point of the scan, producing colored images. This colored image can be related, pixel-by-pixel, to the morphological images (either BF or HAADF). As shown in Figure 1E, it is possible to correlate the emission properties of the fluorescent NDs and the samples ultrastructure (the vesicles) with nanometer resolution. However, while the green color unambiguously identifies a ND-PEI, a red emission might be attributed to a PAH or a PEI coated ND, due to non purity of Type 2 sample.

Fortunately, the exact spectral shape can be used to disentangle both cases. Figure 2 shows that for known samples of ND-PEI and ND-PAH their CL spectra significantly differ in the ratio of ZPL to the phonon side band and in the phonon sideband shape too. These differences are visible only after PEI and PAH coating of the NDs and can be used for segregating red emitting NDs in ND-PAH and ND-PEI. To do so, we took advantage of the large redundancy of the data in spectral-imaging to analyze the data through multivariate analysis (see Supporting Information). We obtained 60% identification efficiency for ND-PAH and 100% for ND-PEI.The influence of the polycation coating on the CL spectra shape maybe related to band bending effect induced by electrophilic surface functionalization, as reported for hydrogenated diamond surface 19,20 . Band bending results in a decrease of occupancy of NV in the vicinity of ND surface, depending on the electron affinity of the coating. Band bending effect on the phonon lines is however not documented in the literature and requires more detailed studies, out of scope of the present paper. From now on, we will thus only mention the type of coatings, as deduced from spectral analysis, without referring anymore to the type of embedded defect centers.

We then investigated the distribution of ND-PEI and ND-PAH inside the cells in different incubation conditions: when the cells are incubated (i) with ND-PAH alone, (ii) with ND-PEI alone at the same nominal concentration as ND-PAH, and (iii) when the cells are co-incubated with both ND-PAH and ND-PEI simultaneously, each of them at the same concentration as in (i) and (ii), so that in condition (iii) there is twice more NDs than in (i) and (ii). NDs were always found inside vesicular compartments and never free in the cytoplasm. From bright field and dark field images, we inferred the size of the vesicles, given as an equivalent diameter calculated as the geometric mean of the major and minor axis of its best approximant ellipse, and from the CL spectra we categorized the vesicle labeling depending on the type of coating of the NDs it contains. The number of NDs per vesicle varied between 1 and 11. We could then build cytometry plots displaying either counts of ND-PEI or ND-PAH per vesicle versus its size in the case of a single type of labeling (Figure 3A), or ND-PEI versus ND-PAH counts (Figure 3B) in the case of the two types of labeling. These plots are similar to the ones of image cytometry plots built from fluorescence microscopy data. The (discrete) number of fluorescent NDs of each kind is reminiscent to, but more precise than, the (continuous) luminescent intensity at a given wavelength in conventional cytometry plots. In Figure 3B the occurrence of a vesicle encompassing a given (ND-PAH, ND-PEI) count is represented by the color of the marker.

Figure 3B thus gives a rapid, comprehensive and synthetic view of the data set.

In this particular proof of principle where we used two different labels (Figure 3B), several straightforward observations can be drawn. First, the pure vesicles (single type of label) are overrepresented compared to mixed vesicles (labeled with two types of cationic NDs). Indeed, over the 88 investigated vesicles, 31 are filled only with PEI and 23 only with PAH. The fact that most of the internalization seems to occur with only PEI or only PAH coating is consistent with differential internalization pathways of ND-PAH and ND-PEI that we have shown in previous work 17 , although here the NDs are larger (150 nm instead of 50 nm). Indeed, we had observed that PAH-coated particles are mainly internalized by clathrin mediated endocytosis while PEI-coated ones are able to trigger an additional pathway, the macropinocytosis. Second, the content of mixed vesicles distributes evenly in the (number of PEI, number of PAH) space. Third, the vesicles containing a small quantity of fluorescent NDs are over-represented (about 65% with a number smaller or equal to 3 fluorescent NDs). A STEM image of a typical vesicle of this category is shown on top of Figure 3C and3D, sparsely filled with NDs. It corresponds in this case to an endosome. Fourth, the general tendency is of course an increase of the diameter as the number of embedded NDs increases, as expected from simple steric consideration. However, the dispersion in vesicles sizes is very large for the same or similar (PEI, PAH) counts. An example of a large vesicle containing densely packed NDs is shown at the bottom of STEM images Figure 3C and 3D. This vesicle is most likely a macropinosome, considering its size, elongated form, and not well-defined delimiting membrane. Here, ultrastructure images are invaluable to identify the vesicle filling.

Recently a new fluorescence microscopy based technique was introduced to quantify the macropinocytotic index of cancer cells. It relies on labeling macropinosomes through internalization of fluorescently labeled high molecular weight dextran molecules 21 . This approach provides a better selectivity than previous fluorescence microscopy image-based techniques. Our method could be applied to the measurement of such macropinocytotic index with yet the additional advantages of combining both luminescent microscopy (with some selectivity brought by the polymer coating) and ultrastructural morphology identifications.

Let us point out that the minimal vesicle size of ≈300 nm that we observed is of the order of the optical diffraction limit, and can therefore be resolved by conventional fluorescence microscopy.

Moreover, fluorescent NDs are known to be ideal labels for STED super-resolution microscopy 22 because they can sustain the high power of the stimulated emission laser without any degradation, with a resistance even larger than the one to the electron beam of CL-STEM. Conventional or STED microscopies could be used to realize a fluorescence image-based cytometry of internalization vesicles. However, from Figure 1, Figure 2 and Figure 3 one can see that the ND labels usually do not fill the whole vesicle, so that its size and morphology cannot be extracted from NDs fluorescence in a reliable manner, while it can be inferred from a STEM scan with nanometer precision. Therefore, despite a simpler implementation of image cytometry based solely on fluorescence microscopies, such an approach does not offer a precise quantification of the vesicle size, neither of its detailed morphology including the inner composition.

Conclusion

We have demonstrated the potential of CL-STEM for combined luminescence and cell ultrastructure imaging, and have applied this technique to multicolor image cytometry of vesicles.

Thanks to the diversity of emission spectra of CL-nanoprobes 23 , CL-STEM should have a higher specificity than gold nanobeads of different sizes conventionally used in EM immunocytochemistry when probes are multiplexed. Though this is an advantage, the materials currently available have a few drawbacks. As in our case, a simple straightforward bicolor imaging was complicated by the presence of red emitters in the batch of green emitters. This is an issue related to purification of samples and with efforts in this direction, pure emitters are not far away. As a proof of principle application we have considered vesicular localization of two types of fluorescent nanodiamonds of with distinct CL spectral signatures after internalization. The high resolution of STEM allows acquiring images of the cellular ultrastructure both in BF and HAADF contrasts from which we can infer various information, and in particular the cross-sectional size of vesicles. By overlapping pixel-by-pixel, the STEM images with the CL emissions of internalized NDs, we could classify the vesicles depending on the ND spectral labeling. The different cationic polymer coatings (PEI or PAH) of the NDs could be used in the future in order to direct each type of ND in different vesicles. Indeed, as demonstrated in a previous study 17 , that NDs-PAH are found only in clathrin-related endosomes, and therefore should label these type of endosome in CL red color. On the contrary, NDs-PEI were found in both clathrinmediated endosomes and in macropinosomes. In order to improve the specificity of functionalized ND and direct them in macropinosomes, PEI could be replaced by dextran 21 . More generally, using antibody-functionalized ND 24 combined with microinjection, it should be possible to label other intracellular organelles like mitochondria and then proceed with a detailed CL-STEM cytometry in relationship with the problem of interest (e.g. study of local temperature fluctuations measured with ND-based thermometer 25 ). Also, other types of CL nanolabels, such as II-VI luminescent semiconductor nanocristals (quantum dots) could be used, as they also have been demonstrated to be efficient cathodoluminescent emitters 13 . Finally, with the emergence of commercial STEM-CL instruments, image acquisition and analysis automation improving the statistics, we foresee that CL-STEM novel image cytometry technique will find numerous applications in subcellular level cell biology. This plot displays also vesicles containing a single type of polymer coated ND (counts equal to 0 along the other coating axis). In the co-loaded case, we investigated 5 cells in which we detected 296 CL-emitting NDs that were distributed among 88 vesicles. The diameter of the circular markers is proportional to the vesicle size (refer to the scale bar). Different vesicles with the same number of ND-PAH and ND-PEI but different diameters appear as concentric circles. The occurrence (i.e. the number of vesicles encompassing the same number of NDs whatever its coating is) is given by the color. (C) HAADF and (D) BF STEM image showing, in the same field of view, two vesicles with different morphology and ND density: a small and round one containing a few NDs (on top), and a larger one, elongated with much more NDs inside.

Methods

Fluorescent ND preparation.

Both types of NDs were radiation-damaged with a high-energy (3 MeV) proton beam, as detailed in Su et al. 26 . Briefly, a thin diamond film (thickness<50 µm) was prepared by depositing ≈5 mg of ND powder on a silicon wafer (1x1 cm 2 size) and subsequently subjected to the ion irradiation at a dose of ≈2x10 16 H + .cm -2 . Afterwards, the radiation-damaged NDs were annealed at 800°C for 2 h to form fluorescent NDs. To remove graphitic carbon atoms on the surface, the freshly prepared fluorescent NDs were oxidized in air at 490°C for 2 h and microwave-cleaned in concentrated H2SO4-HNO3 (3:1, v/v) at 100°C for 3 h.

Cell lines.

A673 Human Ewing Sarcoma cell lines were used as the model system. These cells were cultured in DMEM with 10% FBS and 1% PS. Once the cells reached 70% confluence they were trypsinized and seeded on cover slips placed in 6 well plate. About 10 5 cells were plated and allowed to adhere overnight. These cells were then incubated with ND-PEI and ND-PAH (100 µL each in 500 µL of medium) for 4 hours. Control cells were treated with only ND-PEI or ND-PAH for 4 hours. The coloaded cells and the control cells were rinsed in 1X Phosphate Buffered Saline (PBS) to remove nanoparticles in excess. Cells were fixed using 2% glutaraldehyde in 0,1M cacodylate buffer, pH 7.4 for 1h at room temperature and then post-fixed for 1 hour at room temperature with 1% osmium tetroxide and 1% potassium ferrocyanide in cacodylate buffer. They were dehydrated and finally embedded in epoxy resin. The monolayer was sectioned to 200-300 nm thin section on an ultramicrotome. The sections were exposed to chloroform vapors to stretch them and reduce wrinkles. They were then loaded on carbon/collodion coated copper finder grids. For experiments of Figure 1, the whole procedure was the same except for an additional final step of Uranyl Acetate staining used to increase the image contrast.

K-Means method used to identify the coating of red emitting NDs.

Principle -K-means is a clustering method that groups different data into separate clusters, based on the minimal distance between observations within a given cluster. The number of clusters is an input of the method, and thus an evaluation of the relevance of the choice of a particular number of clusters is necessary. We note that several numbers of clusters may be optimal, as sub-clustering might arise in samples. Moreover, the K-Means relying on heuristic minimizing methods, might be prone to initial condition errors, and it is therefore usually run several times with different initial conditions to avoid local minima.

In the present work, the data set is made of the CL spectra, and each cluster is centred around a centroid spectrum, from which any spectrum comprised into the given cluster is supposed to be the closest, and any spectrum comprised in any other cluster supposed to be furthest. Here, the criterion that is used to validate the optimal number of clusters in the sample pool is a maximal mean silhouette index 1 (Figure S2). The silhouette index defines how well separated the sample groups are. A high silhouette index for a given number of groups indicates that the different spectra cluster well around their centroid and are far away from the other centroids. Therefore, the optimal number of components has the maximum mean silhouette. If this optimum is reached for different number of clusters, sub-clustering is taking place. Moreover, some reports suggest a relationship between the values of the mean silhouette and the strength of the difference between samples. Values above 0.8 indicate a well defined structure, 0.5 to 0.8 presence of some structure, 0.3-0.5 weak structure and less than 0.3 might be an artefact. But these values are empirical based on observations that strongly depend on the analysed sample and cannot be used as a rule of thumb. Finally, the physical content of the output of the automatic method must be also carefully considered with respect to relevant physical parameters.

In practice, the CL spectra were analysed using the K-Means function of MATLAB statistical analysis tool box. K-Means algorithm groups the spectra in clusters for which it calculates the mean centroid spectrum representing best each cluster (see Figure S3 for an example). A minimum of 3 replicates (starting values are changed by the method in MATLAB) were run to ensure identification of a global solution by the K-means method. The number of clusters were chosen to be two, in agreement with the silhouette behaviour (Figure S2) as a function of the number of clusters, and the known physical input (i.e. the existence of two different coatings).

Applying the method of identification of the coating to blind samples -The method was first applied to cells co-incubated with ND-PAH and ND-PEI. We used K-Means to analyse CL spectra of red emitting ND only. This led to the finding of two clusters of red spectra (each presented as 2D stacks on Figure S3, left.), with their corresponding centroids represented in the centre of Figure S3. The corresponding residuals are represented on the right side, while the difference between the two centroids is shown at the bottom of Figure S3. It is clear that both centroids differ by the ratio between the phonon region and the zero-phonon line, as can be seen in Figure 2C of the main text, but here 1 Rousseeuw, P. J. J. Comput. Appl. Math. 1987, 20, 53-65. retrieved with limited prior information or assumption. We now need a criterion to assign a given centroid, and thus cluster to each type of coating. Applying the methods of polymer coating identification to reference samples -We applied K-Means to a set of data gathering CL spectra of red emitting ND from known samples, one with only ND-PEI and the other with only ND-PAH (Figure S4). The purpose of this test was to (i) verify the accuracy of K-Means to identify clusters of each type of coated NDs and (ii) assign a typical centroid to a given coating. All the ND-PEI have been correctly assigned (100% success) while ≈60 % of the ND-PAH have been correctly assigned. Moreover, the ND-PEI centroid spectrum differs from the ND-PAH one by a larger phonon contribution. As a confirmation, we have compared the centroid spectra of red emitting ND from samples containing pure ND-PEI or pure ND-PAH, and we have observed the same differences (data not shown). Such an observation allowed us to assign each of the centroids of the co-incubated cell sample in Figure S3 to a given type of ND-coating.

  : the Polyallylamine Hydrochloride (PAH) coating triggers clathrin-mediated endocytosis, whereas both clathrin-mediated endocytosis and macropinocytosis are involved in the case of Polyethylene Imine (PEI) coating, with a predominance for macropinocytosis. Such coated NDs are thus interesting labels of different internalization pathways.

Figures

  Figures

Figure 1 .

 1 Figure 1. Correlation between ultrastructure imaging and hyperspectral imaging. (A) Left: High Angle Annular Dark Field (HAADF) and Right : Bright Field (BF) images of a whole cell (N : nucleus) with visible NDs on the cell membrane marked CM. (B) Magnified images (Left: BF, Right: HAADF) of the area framed in yellow in (A). The nanodiamond (ND) as well as ultrastructure components such as vesicles (V), mitochondria (M) and nucleus membrane (NM) are clearly distinguished in the uranyl acetate stained cell samples. (C) Schematics of the detection part of the CL-STEM hyperspectral setup. PM: parabolic mirror; Spec. : optical spectrometer; CCD: Charge Coupled Device array detector. (D) Examples of H3 (boxed in green) and NV (boxed in red) spectra, extracted from the two NDs shown in E. The NV spectrum consists in a sharp line (Zero-phonon line) followed by a convoluted series of peaks (phonon lines). (E) HAADF image, and overlapped H3 (green), NV (red) and HAADF images taken on a vesicle framed in red in (A).

  Figure 1. Correlation between ultrastructure imaging and hyperspectral imaging. (A) Left: High Angle Annular Dark Field (HAADF) and Right : Bright Field (BF) images of a whole cell (N : nucleus) with visible NDs on the cell membrane marked CM. (B) Magnified images (Left: BF, Right: HAADF) of the area framed in yellow in (A). The nanodiamond (ND) as well as ultrastructure components such as vesicles (V), mitochondria (M) and nucleus membrane (NM) are clearly distinguished in the uranyl acetate stained cell samples. (C) Schematics of the detection part of the CL-STEM hyperspectral setup. PM: parabolic mirror; Spec. : optical spectrometer; CCD: Charge Coupled Device array detector. (D) Examples of H3 (boxed in green) and NV (boxed in red) spectra, extracted from the two NDs shown in E. The NV spectrum consists in a sharp line (Zero-phonon line) followed by a convoluted series of peaks (phonon lines). (E) HAADF image, and overlapped H3 (green), NV (red) and HAADF images taken on a vesicle framed in red in (A).

Figure 2 .

 2 Figure 2. Disentangling NV emission as a function of coating. (A) HAADF image showing vesicles containing NDs. (B) Green and red CL emission maps extracted from a spectral image of the same area as in (A), and superimposed to HAADF image. (C) CL emission spectra of two NV-containing NDs corresponding to the violet and orange delimited areas in (A) and (B), and normalized to their ZPL maximum intensity. The phonon regions of the spectra have clearly different amplitudes, as a signature of different coatings (see text).

Figure 3 .

 3 Figure 3. Cytometric plots of internalization vesicles labeled with polymer coated fluorescent NDs. (A) Number of ND per vesicle versus the vesicle size (equivalent diameter) in the case of single labeling (control sample) by either ND-PAH (red dots) or ND-PEI (green dots). (B) Double labeling by internalization of ND-PEI and ND-PAH simultaneously. Number of ND-PEI vs number of ND-PAH per individual vesicle. This plot displays also vesicles containing a single type of polymer coated ND (counts equal to 0 along the other coating axis). In the co-loaded case, we investigated 5 cells in which we detected 296 CL-emitting NDs that were distributed among 88 vesicles. The diameter of the circular markers is proportional to the vesicle size (refer to the scale bar). Different vesicles with the same number of ND-PAH and ND-PEI but different diameters appear as concentric circles. The occurrence (i.e. the number of vesicles encompassing the same number of NDs whatever its coating is) is given by the color. (C) HAADF and (D) BF STEM image showing, in the same field of view, two vesicles with different morphology and ND density: a small and round one containing a few NDs (on top), and a larger one, elongated with much more NDs inside.

Figure S2 -

 S2 Figure S2 -Mean Silhouette for a K-Means analysis of polycation coated NDs in the coloaded samples.

Figure S3 -

 S3 Figure S3-K-Means analysis of CL spectra of red-emitting ND in the case of cell co-incubated with ND-PAH and ND-PEI . In this representation, each spectrum is represented as a linear image. All spectra are then stacked on each other to form a two dimensional image. This representation helps to identify differences and similarities between spectra. Top row : first cluster, further attributed to ND-PAH signature. From left to right, experimental spectra, centroid and NAE: Normalized absolute error (normalized value of the difference between experimental and centroid spectra). The centroid 2D image is the repetition of the centroid spectrum. Middle row: second cluster, further attributed to ND-PEI. Bottom: N.A.E between the two centroids .

Figure S4 -

 S4 Figure S4 -K-Means analysis for the reference sample consisting of a data set made of CL spectra of naodiamonds with known coating. K-Means is able to identify the two populations of coated nanodiamonds.

Supporting Information

"Simultaneous cathodoluminescence and electron microscopy cytometry of cellular vesicles labeled with fluorescent nanodiamonds" S. Nagarajan et al.

Contamination of Type 2 ND sample by particles containing red emitting NV centers.

In green light emitting type 2 sample we have observed the presence of red light emitting nanoparticles in addition to the green emitting ones. To determine the contamination of type 2 sample, we dispersed ND on a carbon film and imaged them by CL-STEM. Figure S1 shows that type 2 sample diamond nanocrystals displaying a CL signal contain either green (H3) or red (NV) color centers but never both in the same crystal. From the analysis of CL spectral images for 8 field of view of size 15.17 µm x 15.17 µm we inferred that 57 of type 2 ND are purely green emitters. As stated in the main text, the Type 2 ND sample is unfortunately not spectrally pure and contains either red or green emitting nanoparticles. The red emitters are NV centers in type 1 and in type 2 NDs, and we did not observe significant CL spectrum differences in bare ND of both types. However, we noticed that after cationic polymer coating, the spectrum of embedded NV centers were modified differently, depending on the type of polymer used (Figure 2C of the main text). The phonon region is indeed significantly different in both types of NDs.

In order to distinguish between PAH-coated Type 1 NDs (which are all red emitters) and PEIcoated Type 2 red-emitting NDs, we have developed a method relying on multivariate analysis. Specifically, we have applied K-means analysis to the coloaded sample. This analysis has lead to the discrimination of the NDs into two clusters. These clusters could be assigned to either ND-PAH or ND-PEI by comparison with the results of the same analysis done on reference samples made up of only ND-PAH or ND-PEI with a priori knowledge of polymer coating.