Andreas Walter

Catherine Chapuis

Sébastien Huet
email: sebastien.huet@univ-rennes1.fr

Jan Ellenberg
email: jan.ellenberg@embl.de

Crowded chromatin is not sufficient for heterochromatin formation and not required for its maintenance

Keywords: Macromolecular crowding, chromatin, cell nucleus, fluorescence microscopy, osmotic perturbations, nuclear organelles

In contrast to cytoplasmic organelles, which are usually separated from the rest of the cell by phospholipid membranes, nuclear compartments are readily accessible to diffusing proteins and must rely on different mechanisms to maintain their integrity. Specific interactions between scaffolding proteins are known to have important roles for the formation and maintenance of nuclear structures. General physical mechanisms such as molecular crowding, phase separation or colloidal behavior have also been suggested, but their physiological significance remains uncertain. For macromolecular crowding, a role in the maintenance of nucleoli and promyelocytic leukemia (PML) nuclear bodies has been shown. Here, we tested whether a modulation of the compaction state of chromatin, which directly influences the local crowding state, has an impact on the formation and maintenance of densely packed heterochromatin. By osmotic perturbations, we could modify the packing state of chromatin in a controlled manner and show that chromatin compaction, which is associated with increased crowding conditions, is not, per se, sufficient to initiate the formation of new bona fide heterochromatin structures nor is it necessary to maintain already established heterochromatin domains. In consequence, if an increase in crowding induced by chromatin compaction maybe an early step in heterochromatin formation, specific protein-protein interactions are nevertheless required to make heterochromatin long lasting and independent of the crowding state.

INTRODUCTION

During interphase, chromatin can be categorized into two different structural and functional states in the nucleus of eukaryotic cells. Heterochromatin remains highly compact during the entire interphase; it is characterized by a low density of genes and is mainly transcriptionally silent [START_REF] Maison | HP1 and the dynamics of heterochromatin maintenance[END_REF]. In contrast, euchromatin corresponds to less compact and transcriptionally active chromatin. Several reports suggest that the high compaction levels observed in heterochromatin arise from a denser packing of the chromatin fiber [START_REF] Dillon | Heterochromatin structure and function[END_REF]. The establishment of this specific chromatin architecture in heterochromatin is assumed to be mediated by post-transcriptional modifications of the histone tails which serve as binding sites for heterochromatin scaffolding proteins, which in turn favor additional histone modifications [START_REF] Maison | HP1 and the dynamics of heterochromatin maintenance[END_REF]. The function of the high compaction of heterochromatin remains however unclear. The widespread assumption that this dense packing represses transcription by preventing access of RNA polymerase 2 has been challenged by the finding that heterochromatin is permeable to inert probes as large as RNA polymerase [START_REF] Verschure | Condensed chromatin domains in the mammalian nucleus are accessible to large macromolecules[END_REF][START_REF] Bancaud | Molecular crowding affects diffusion and binding of nuclear proteins in heterochromatin and reveals the fractal organization of chromatin[END_REF]. As an alternative function, we recently proposed that the dense fractal architecture of heterochromatin may regulate how rather than if transcriptional regulators bind chromatin [START_REF] Bancaud | Molecular crowding affects diffusion and binding of nuclear proteins in heterochromatin and reveals the fractal organization of chromatin[END_REF]. In addition to such potential functions in gene expression regulation, we and others have proposed that the macromolecular crowding resulting from the dense packing in heterochromatin plays a role in the biogenesis and maintenance of these nuclear domains [START_REF] Rippe | Dynamic organization of the cell nucleus[END_REF][START_REF] Bancaud | Molecular crowding affects diffusion and binding of nuclear proteins in heterochromatin and reveals the fractal organization of chromatin[END_REF].

Heterochromatin, like many nuclear compartments, is stable for hours when observed microscopically, but at the same time highly dynamic at the molecular level [START_REF] Snaar | Mutational analysis of fibrillarin and its mobility in living human cells[END_REF][START_REF] Cheutin | Maintenance of stable heterochromatin domains by dynamic HP1 binding[END_REF]. To reconcile these two apparently contradictory characteristics, recent reports have proposed that such nuclear compartments are formed by self-organization mechanisms involving dynamic interactions between their constituent proteins [START_REF] Dundr | Biogenesis of nuclear bodies[END_REF]. In addition, the self-organization processes could be strongly influenced by the local chromatin architecture [START_REF] Rusche | Assembling heterochromatin in the appropriate places: A boost is needed[END_REF][START_REF] Keating | Aqueous phase separation as a possible route to compartmentalization of biological molecules[END_REF]. In heterochromatin, the high compaction makes these regions more crowded at the molecular level causing a significant fraction of the volume to be inaccessible for other molecules. In agreement with theoretical and in-vitro studies (Zhou et al., 2008;[START_REF] Cho | Crowding effects on the formation and maintenance of nuclear bodies: insights from molecular-dynamics simulations of simple spherical model particles[END_REF], we could recently show that this excluded volume effect has two main consequences for the dynamics of macromolecules in heterochromatin: i) their diffusion is slowed down and ii) their binding reactions are shifted towards the bound state [START_REF] Bancaud | Molecular crowding affects diffusion and binding of nuclear proteins in heterochromatin and reveals the fractal organization of chromatin[END_REF]. These results led us to propose that enhanced macromolecular crowding could locally promote the binding of heterochromatin modifying and scaffolding proteins which in turn would cause more compaction. Such a positive feedback loop could be important to form or maintain heterochromatin foci. To be able to test this hypothesis, we now established an assay that allows predictable and reversible manipulation of the compaction state of chromatin in living cells. This allowed us to show that an enhancement of the molecular crowding associated with local chromatin compaction is not sufficient to create stable heterochromatin regions de novo that contain new scaffolding proteins. In addition, we found that the binding of heterochromatin scaffolding proteins is maintained even after decompaction of these domains, showing that a dense and crowded chromatin compaction state is not necessary for heterochromatin maintenance. Based on these findings we propose a model in which crowding induced by chromatin compaction may facilitate heterochromatin biogenesis but where it requires specific protein-protein interactions to establish stable heterochromatin that then becomes independent of the crowding state.

MATERIAL AND METHODS

Fluorescent protein constructs

The plasmid constructs coding for the core histone H2B fused to enhanced GFP (EGFP), mCherry or the photoactivatable GFP (PA-GFP), as well as the one coding for the monomeric EGFP (mEGFP), were described previously [START_REF] Snapp | Formation of stacked ER cisternae by low affinity protein interactions[END_REF][START_REF] Beaudouin | Dissecting the contribution of diffusion and interactions to the mobility of nuclear proteins[END_REF][START_REF] Mora-Bermúdez | Maximal chromosome compaction occurs by axial shortening in anaphase and depends on Aurora kinase[END_REF][START_REF] Neumann | Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes[END_REF]. The coding sequence of pmCherry was used to generate the fluorescent tandem trimer mCherry-3. The HP1β and Suv39H1 genes were tagged with EGFP within a bacterial artificial chromosome (BAC).

Cell culture and osmotic shocks

NIH-3T3 cells were routinely cultured in Dulbecco's modified Eagle's medium (4.5 g/L glucose) supplemented with 10% fetal bovine serum, 2 mM glutamine, 100 µg/ml penicillin, 100 U/ml streptomycin and 1 mM sodium pyruvate in 5% CO 2 at 37°C. For the acquisitions on imaging setups, cells were plated on LabTekII-chambered coverglasses (Nunc, Roskilde, Denmark) and the growing medium was replaced by a CO 2 -independent medium without phenol red (Invitrogen, Carlsbad, USA) supplemented with 20% fetal bovine serum, 2 mM glutamine, 100 µg/ml penicillin and 100 U/ml streptomycin. For the hypertonic shocks, this isotonic medium was replaced by imaging medium supplemented with 160 mM sucrose. For the hypotonic shocks, the imaging medium was diluted with distilled water until reaching a ratio of 35:65 v/v between imaging medium and water. The compositions of the hypertonic and hypotonic media were chosen to induce a rapid change of the chromatin compaction level without significantly precluding the cell viability after the osmotic shock. All the living cell experiments were performed at 37°C.

Cell transfection and stable cell lines

Transient transfections were performed using Fugene 6 (Roche, Basel, Switzerland), 24 h after plating. The cells were imaged 24-48 h after transfection. To establish NIH-3T3 cell lines expressing stably H2B-mCherry and HP1β-EGFP or Suv39H1-EGFP, wild-type cells were transfected with the cDNA or BAC constructs using Fugene 6 and Effectene (Qiagen, Hilden, Germany), respectively. Colonies of stable transformants were picked after two weeks of antibiotic selection.

Confocal imaging, fluorescence recovery after photobleaching or photoactivation

Confocal imaging and photoactivation experiments were performed on a Zeiss LSM 510 or a LSM 510 Meta (Carl Zeiss, Jena, Germany). Fluorescence recovery after photobleaching was performed on a TCS SP5 AOBS (acousto-optic beam splitter) confocal microscope (Leica Microsystems, Wetzlar, Germany). The cells were imaged using an oil immersion Plan-Apochromat 63x objective lens (N.A. 1.4). EGFP was excited with a 488-nm laser and mCherry with a 543-nm or 561-nm laser. The PA-GFP was photoactivated with a 405-nm laser. The pinhole was set to one Airy unit for all channels. The dichroics and emission filters were chosen to optimize the collection of the emitted fluorescence in the different channels.

Immuno-fluorescence

NIH-3T3 cells expressing EGFP-H2B were fixed using 4%-paraformaldehyde and permeabilized with 0.2% Triton X-100 at room temperature or fixed with methanol at -20°C. Cells were stained using primary antibodies recognizing the trimethylation of histone H3 at lysine 9 (Abcam, Cambridge, USA), the trimethylation of histone H3 at lysine 4 (Merck Millipore, Darmstadt, Germany) or the serine 2 phosphorylation of the C-terminal domain of the RNA polymerase II (Abcam, Cambridge, USA). The secondary antibodies were labeled with Cyanine 3 (GE Healthcare, Chalfont St. Giles, UK) or Alexa Fluor 555 (Life Technologies, Carlsbad, USA).

DNA labeling with fluorescent nucleotides

NIH-3T3 cells were synchronized at the G1/S phase transition by a double 2mM thymidine block. The two blocks lasted 18h and 16h, separated by an incubation time of 8h in normal medium after the first release. After the second thymidine release, the cell layer, bathed with growing medium containing 10 µM of Cy3-dUTP (Jena-Bioscience, Jena, Germany), was scraped using a silicon stick to allow nucleotide loading [START_REF] Schermelleh | Two-color fluorescence labeling of early and mid-to-late replicating chromatin in living cells[END_REF] and integration to the DNA during replication. To label specifically early, mid and late replicating DNA, the nucleotide labeling was performed immediately, 2h or 5h after thymidine release, respectively.

Fluorescence correlation spectroscopy

Fluorescence Correlation Spectroscopy (FCS) experiments were performed on a TCS SP2 AOBS confocal microscope (Leica Microsystems) using a water immersion Plan-Apochromat 63x objective lens (N.A. 1.2). The mEGFP was excited with a 488-nm laser. FCS raw data were acquired using an avalanche photodiode (Perkin-Elmer Optoelectronics, Fremont, USA) after a spectral filtering of the fluorescence light with a bandpass filter (BP500-550, Omega Optical, Brattleboro, USA). Each FCS acquisition was lasting at least 30 s to reduce the noise on the autocorrelation curves. When probing the diffusion of mEGFP in the nucleus of cells co-expressing mEGFP and H2B-mCherry, the accuracy in the position of the probed area could be verified a-posteriori by the local bleaching of the H2B-mCherry pattern visible at the site of the FCS acquisition. To estimate the residence time of mEGFP in the focal volume, the autocorrelation curves were fitted with a one-specie model assuming anomalous diffusion and neglecting the contribution of the photophysics of the mEGFP.

Automatic segmentation of the chromatin patterns

Confocal images of nuclei expressing EGFP-H2B or H2B-mCherry were smoothed using a moving average filter and segmented by Otsu thresholding to distinguish chromatin from the background and the nucleoli [START_REF] Otsu | Threshold selection method from gray-level histograms[END_REF]. The distributions of pixel intensities in the chromatin regions were fitted with a double Gaussian (fig. S1) and the intensity threshold between compacted and non-compacted chromatin was calculated as the mean of the central values for the two Gaussian. Due to the overlap between the two pixel intensity distributions, the compacted chromatin mask included small isolated structures within the non-compacted regions. These isolated structures were removed by applying an opening morphological filter with a circular kernel of radius 4 pixels to the compacted chromatin mask. The relative amount of compacted chromatin was thus obtained by dividing the number of pixels corresponding to compacted chromatin by the sum of all the chromatin pixels. For the cells bathed with isotonic medium, the non-compacted chromatin areas were identified as euchromatin and the compacted ones as heterochromatin. In nuclei subjected to hypertonic shocks, an additional opening filter with a circular kernel of radius 7 pixels was applied to the compacted chromatin areas to remove the fine network of compacted structures, attributed to newly compacted euchromatin, while preserving round heterochromatin area. Thus, three different segmentation masks were defined: (i) non-compacted euchromatin, (ii) heterochromatin and (iii) newly compacted euchromatin, this latter mask being obtained by subtracting the mask corresponding to compacted chromatin area with the heterochromatin mask.

Boxplots and statistical significance

On the displayed boxplots, the boxes have lines at the lower quartile, median, and upper quartile values. The whiskers extend from the boxes out to the most extreme data value within one interquartile range. The crosses represent the outliers, which are out of the range defined by the whiskers. To test for statistical significance, p-values were calculated using two-sided paired or unpaired t-tests. The unpaired t-tests were performed assuming unequal variances for the two samples.

RESULTS

Osmotic perturbations can acutely manipulate the compaction state of chromatin

In order to study the role of molecular crowding in the formation and maintenance of heterochromatin, we first established an assay allowing the manipulation of the compaction state of chromatin by subjecting cells to osmotic stress. We imaged by confocal microscopy NIH-3T3 mouse embryonic fibroblast cells expressing the core histone 2B (H2B) fused to EGFP and used the fluorescence intensities as a reporter of the local chromatin compaction level. By fitting the pixel intensity distributions derived from these images with a double Gaussian, we could automatically segment the bright regions and estimate the proportion of compacted chromatin within the nucleus (fig. S1). For cells bathed with isotonic medium, this assay allowed segmenting the prominent fluorescent spots corresponding to heterochromatin clustered in chromocenters (fig. 1A) but it probably does not have the resolution to distinguish between constitutive and facultative heterochromatin. We also observed that the relative amount of compacted chromatin remained stable during interphase, in agreement with the visual inspection of the image sequences.

Subjecting NIH-3T3 cells to hypertonic shocks by incubating them with isotonic medium supplemented with 160 mM sucrose led to chromatin hyper-compaction evidenced by the appearance of multiple bright dense structures on the EGFP-H2B patterns (fig. 1B). The segmentation and quantification of these images showed that hypertonic shocks induced a rapid increase of the relative amount of compacted chromatin in the treated nuclei. The chromatin compaction upon hypertonic shock was associated with a decrease of the nuclear volume by nearly 30 % (fig. S2A). Following the initial hyper-compaction, chromatin slowly decompacted as cells adapted to the hypertonic medium within approximately one hour. Similar results were obtained when incubating cells with isotonic medium supplemented with 120 mM NaCl (data not shown).

Furthermore, we investigated whether some chromatin regions could be more prone to compaction upon hypertonic shock than others. Early, mid and late replicating DNA were labeled with fluorescent nucleotides and the relative chromatin compaction level, assessed by the Hoechst signal, was measured at the nucleotide integration sites in cells bathed with isotonic or hypertonic medium (Fig S2B). The dense heterochromatic chromocenters were excluded from this analysis. Our results suggest that the early replicating DNA shows a greater tendency to compact upon hypertonic shock than the mid or late replicating DNA.

Incubating cells with hypotonic medium (isotonic medium diluted with water, 35:65 v/v) led to a rapid smoothing of the EGFP-H2B patterns visible on the images of the fluorescent nuclei (fig. 1C). This was due to decompaction of chromatin and not release of H2B from DNA as tested by photoactivation of H2B tagged with photoactivatable GFP, which remained immobilized in hypotonic conditions (fig. S2C). Heterochromatin foci were almost completely decompacted under hypotonic conditions, indistinguishable in compaction from the rest of the chromatin. This was confirmed by the automatic estimation of the relative amount of compacted chromatin, which showed a dramatic and rapid drop upon addition of the hypotonic medium (fig. 1C). This chromatin decompaction was associated with an increase of the nuclear volume by about 40 % (fig. S2A). Following the rapid decompaction of the chromatin, cells progressively adapted to the hypotonic medium over several hours following the shock, and reestablished a significant amount of compacted chromatin.

Modifying chromatin compaction level changes the crowding state

To test how the modulation of chromatin compaction levels by osmotic stress affects the local crowding state of the nucleus, we measured the exclusion and diffusion slow down of inert tracers in compact or non-compact chromatin identified by fluorescently labeled H2B. In isotonic conditions, a tandem trimer of mCherry (mCherry-3) was evenly distributed in euchromatin and largely excluded from heterochromatin (Fig. 2A, upper row). Upon hypertonic shocks, we observed a partial exclusion of mCherry-3 from the newly compacted euchromatin regions (fig. 2A, blue arrowheads). Automatic segmentation of the H2B patterns (see methods) allowed us to quantitatively compare the exclusion of the diffusive tracer mCherry-3 from euchromatin newly compacted by hypertonic treatment with exclusion from heterochromatin in isotonic conditions (fig. 2B). mCherry-3 was excluded from newly compacted euchromatin to a similar extent as from heterochromatin in isotonic conditions (fig. 2B), demonstrating that nuclear areas with dense chromatin induced by hypertonic conditions are indeed more crowded. Next, the diffusion of mEGFP was quantified in nuclear areas with different degrees of chromatin compaction using fluorescence correlation spectroscopy (FCS). In isotonic conditions and in agreement with our previous findings [START_REF] Bancaud | Molecular crowding affects diffusion and binding of nuclear proteins in heterochromatin and reveals the fractal organization of chromatin[END_REF], a slowing down of the diffusion of mEGFP by a factor of ~2 was measured in heterochromatin as compared to euchromatin (fig. 2C). In nuclei subjected to hypertonic shocks, the mobility of mEGFP within the newly compacted chromatin regions was similar to heterochromatin in isotonic conditions (fig. 2C). Thus the crowding conditions encountered in the hypertonically compacted euchromatin are similar to those of isotonic heterochromatin.

To test if crowding is indeed reduced in heterochromatin foci decompacted by hypotonic conditions, we quantified the exclusion of mCherry-3 in these regions before and after the perturbation in cells co-expressing mCherry-3 and EGFP-H2B. To allow identifying the position of heterochromatin foci after the shock, the nuclei were also labeled with Hoechst. Indeed, while the EGFP-H2B spots disappeared upon chromatin decompaction induced by hypotonic shocks, the heterochromatin foci were still visible on the Hoechst channel due to the preferential binding of this dye to the AT-enriched heterochromatin DNA regions [START_REF] Petit | Assessment of fluorochromes for cellular structure and function studies by flow cytometry[END_REF]. Using this assay, we found that the decompaction of heterochromatin by hypotonic shock led to loss of the volume exclusion of mCherry-3 within these regions (fig. 3), suggesting that hypotonically decompacted heterochromatin has a similarly low level of molecular crowding as euchromatin.

Newly compacted euchromatin lacks heterochromatin marks

Constitutive heterochromatin is characterized by specific post-transcriptional histone modifications, including histone 3 lysine 9 tri-methylation (H3K9me3) [START_REF] Maison | HP1 and the dynamics of heterochromatin maintenance[END_REF]. Two proteins play a key role in the dynamic maintenance of this histone mark: the methyltransferase Suv39H1, which methylates the H3K9 and the chromatin-binding protein HP1, which recognizes the methylated H3K9 and is presumed to function in stabilizing and spreading the heterochromatic region [START_REF] Maison | HP1 and the dynamics of heterochromatin maintenance[END_REF]. Both HP1 and Suv39H1 bind dynamically to chromatin all over the nucleus, but with a higher affinity for heterochromatin [START_REF] Cheutin | Maintenance of stable heterochromatin domains by dynamic HP1 binding[END_REF][START_REF] Krouwels | A glue for heterochromatin maintenance: stable SUV39H1 binding to heterochromatin is reinforced by the SET domain[END_REF]. Having shown that hypertonically compacted euchromatin is indistinguishable in molecular crowding from heterochromatin, we now wanted to test whether this local increase of crowding would be sufficient to promote the accumulation of HP1 and Suv39H1, and thus lead to the formation of new stable heterochromatin regions.

NIH-3T3 cells co-expressing H2B-mCherry and the isoform β of HP1 (HP1β) or Suv39H1 fused to EGFP were subjected to hypertonic conditions and assayed at least five minutes after the perturbation by confocal microscopy. Despite the marked compaction of euchromatin as visualized in the H2B channel, the distribution of HP1β was only slightly affected by the hypertonic shock (fig. 4A) and only a moderate clustering of Suv39H1 could be observed within the newly compacted euchromatin areas. To test if HP1β or Suv39H1 bound to the newly compacted euchromatin are above the levels expected from their low level binding to uncompacted euchromatin, we measured the fluorescence intensity increase of HP1β and Suv39H1 after the hypertonic perturbation relative to H2B (fig. 4B) in regions of interest containing newly compacted euchromatin (fig. S3A). As a control we used cells co-expressing H2B-mCherry and EGFP-H2B, which showed the same increase in both channels. The fluorescence gains for both HP1β and Suv39H1 were significantly lower than for H2B, suggesting that the binding of these proteins to compacted euchromatin was partially impaired (fig. 4B). Thus, none of the two scaffolding heterochromatin proteins that we tested showed an enhanced binding in newly compacted euchromatin.

To exclude that the hypertonic perturbation immobilized HP1β and Suv39H1 and thereby prevented their relocation and binding to newly compacted chromatin regions, we measured the dynamics of both proteins by Fluorescence Recovery After Photobleaching (FRAP) (fig. S4). Although the kinetics of HP1 recovery was slowed down, both HP1β and Suv39H1 almost completely re-equilibrated over the entire nucleus within a few minutes after FRAP in hypertonic conditions, which excludes that they are not available for binding to newly compacted chromatin.

To investigate if the activity of Suv39H1 was enhanced by the local compaction of euchromatin, we tested if hypertonic perturbations led to an increase of H3K9 methylation. Cells expressing EGFP-H2B were subjected to hypertonic perturbation, fixed after 15 and 45 min and stained against H3K9 tri-methylation (H3K9me3). While the strong methylation signal in heterochromatin foci was not affected, we could see no obvious increase of H3K9me3 in newly compacted euchromatin induced by the hypertonic perturbation (fig. 4C). Thus neither localization nor activity of Suv39H1 appeared to be enhanced in newly compacted euchromatin.

In order to further characterize the transcriptional state of euchromatin compacted by hypertonic shocks, the localizations of additional histone marks were analyzed. Up to 45 min after the shocks, no specific accumulation of H3K27 tri-methylation, which is associated with facultative heterochromatin [START_REF] Trojer | Facultative heterochromatin: is there a distinctive molecular signature?[END_REF], could be detected in these regions (fig. S5). In addition, the H3K4 tri-methylation, a classical mark for active chromatin [START_REF] Schübeler | The histone modification pattern of active genes revealed through genome-wide chromatin analysis of a higher eukaryote[END_REF], and the elongating RNA polymerase II (phosphorylated on the serine 2 of the Cterminal domain [START_REF] Heidemann | Dynamic phosphorylation patterns of RNA polymerase II CTD during transcription[END_REF]) were both partially excluded from newly compacted euchromatin (fig. S5). This exclusion was already visible 5 min after the hypertonic shock and remained stable during the 45 min following the shock.

Heterochromatin scaffolding proteins and histone marks are stable after decompaction

Even though increased molecular crowding was not sufficient for the formation of new bona fide heterochromatin foci, it could be necessary for the maintenance of already established heterochromatin regions. To test this hypothesis, we first analyzed the impact of chromatin decompaction on the binding of Suv39H1 and HP1β in heterochromatin. When cells expressing Suv39H1-EGFP or HP1β-EGFP together with H2B-mCherry were subjected to hypotonic perturbations, both HP1β and Suv39H1 remained accumulated in heterochromatin even after complete decompaction of the foci (fig. 5A). To quantify if Suv39H1 or HP1β were lost from heterochromatin upon chromatin decompaction, we measured the fluorescence intensity of HP1β and Suv39H1 after the hypotonic perturbation relative to H2B in regions encompassing the heterochromatin foci before and after the perturbation based on segmentation of HP1β and Suv39H1 (fig. S3B). While the total intensity of H2B was expected to be conserved after heterochromatin decompaction, the fluorescence intensity of Suv39H1 or HP1β proteins should decrease after hypotonic perturbation if maintenance of their binding relies on high molecular crowding in heterochromatin. As a control we again used cells co-expressing H2B-mCherry and EGFP-H2B in which heterochromatin decompaction was incomplete to allow its segmentation based on the core histone signal only. As expected, there was no significant change in both channels (fig. 5B). For HP1β, the intensity within heterochromatin did not change significantly upon hypotonic shock while for Suv39H1 we even observed an increase of the intensity within the decompacted heterochromatin. Thus, maintaining the binding of HP1β and Suv39H1 to heterochromatin does not require compact heterochromatin.

To exclude that the hypotonic perturbation immobilized HP1β and Suv39H1 in heterochromatin and thereby prevented their unbinding after decompaction, we measured the dynamics of both proteins by FRAP (fig. S4). While the dynamics of Suv39H1 remained unchanged compared to isotonic conditions, the redistribution of HP1β was even accelerated after hypotonic treatment. Thus, both proteins remained mobile after the hypotonic perturbation and kept shuttling between euchromatin and heterochromatin within timescales of a few minutes, which excludes that they are unable to dissociate from heterochromatin.

Finally, we also analyzed whether the high chromatin compaction state of heterochromatin was required for the maintenance of the H3K9 tri-methylation. Cells expressing EGFP-H2B were subjected to hypotonic perturbation and fixed and stained against H3K9me3 after 15, 45 or 180 min respectively. The strong methylation signal of heterochromatin foci was unaffected for up to three hours after the hypotonic perturbation (fig. 5C), indicating that chromatin decompaction did not affect the maintenance of this classical heterochromatin histone mark.

DISCUSSION

Reversible manipulation of the chromatin compaction state by osmotic stress

In agreement with previous reports [START_REF] Brasch | Effects of low salt concentration on structural organization and template activity of chromatin in chicken erythrocyte nuclei[END_REF][START_REF] Richter | Experimental evidence for the influence of molecular crowding on nuclear architecture[END_REF], we observed that hyper-or hypotonic perturbations led to a dramatic, but reversible, chromatin hyper-or decompaction, respectively (fig. 1). Previous studies have suggested that both the cation concentration [START_REF] Martin | Chromatin condensation modulates access and binding of nuclear proteins[END_REF] and the intracellular crowding [START_REF] Cunha | Polymer-mediated compaction and internal dynamics of isolated Escherichia coli nucleoids[END_REF][START_REF] Iborra | Can visco-elastic phase separation, macromolecular crowding and colloidal physics explain nuclear organisation?[END_REF][START_REF] Richter | Experimental evidence for the influence of molecular crowding on nuclear architecture[END_REF] can affect the chromatin compaction state. The abrupt changes of the nuclear volume observed upon osmotic stress (fig S2 .) are likely to have a strong impact on the nuclear crowding level, which could in turn cause chromatin hyper-or decompaction. However, the nuclear double membrane is pierced with nuclear pores that only restrict diffusional equilibration above ~40 kDa [START_REF] Keminer | Permeability of single nuclear pores[END_REF]. Since this membrane does not insulate the nucleus entirely from the cytoplasm concerning the solute concentration, the changes in intracellular ion concentrations associated with the osmotic shocks could also contribute to the modification of the chromatin compaction state [START_REF] Delpire | Effects of osmotic shocks on the ultrastructure of different tissues and cell types[END_REF][START_REF] Martin | Chromatin condensation modulates access and binding of nuclear proteins[END_REF]. In this context, our observation that the early replicating chromatin is more prone to compaction upon hypertonic treatment than mid or late replicating regions (fig. S2) suggest that the sensitivity of the chromatin structure to the local crowding and ionic conditions may be different from one chromatin region to the other. Importantly, osmotic shocks modify chromatin compaction acutely within seconds and act independent of histone marks such as the heterochromatin specific H3K9 tri-methylation. This is in contrast to alternative pharmacological approaches inhibiting histone deacetylases (e.g. sodium butyrate, trichostatin A), that lead to chromatin decompaction, but require several hours of incubation and change histone marks [START_REF] Görisch | Histone acetylation increases chromatin accessibility[END_REF].

Modifying the chromatin compaction state by osmotic stress influences the local level of crowding in the nucleus

By characterizing the exclusion and diffusion slow-down of fluorescent tracers within nuclei subjected to osmotic stress, we could show that the local crowding is strongly influenced by the chromatin compaction level. Indeed, the euchromatin areas that got compacted upon hypertonic shocks were characterized by enhanced crowding conditions as compared to the surrounding euchromatin (fig. 2), thus mimicking the differences observed between heterochromatin and euchromatin in isotonic medium. We also found that the strong crowding conditions characterizing isotonic heterochromatin could be abolished by decompacting these regions with hypotonic shocks (fig. 3). Together with previous reports [START_REF] Martin | Chromatin condensation modulates access and binding of nuclear proteins[END_REF], these results suggest that chromatin, which is thought to occupy ~50 % of the nuclear volume [START_REF] Rouquette | Revealing the high-resolution three-dimensional network of chromatin and interchromatin space: a novel electron-microscopic approach to reconstructing nuclear architecture[END_REF], is the main crowding agent within the nucleus. Thus, modifying the level of chromatin compaction has a direct impact on the local crowding in the nucleus. Our observations also show that, because of this ability to locally affect the nuclear crowding, osmotic perturbations could be a useful tool to understand the role of molecular crowding in nuclear processes.

Chromatin hyper-compaction associated with local enhancement of molecular crowding is not sufficient for the de novo formation of stable heterochromatin

De novo formation of nuclear compartments occurs in response to external triggers [START_REF] Lavau | The acute promyelocytic leukaemia-associated PML gene is induced by interferon[END_REF][START_REF] Sleeman | snRNP protein expression enhances the formation of Cajal bodies containing p80-coilin and SMN[END_REF] and after cell division concomitant with nuclear assembly [START_REF] Dundr | Biogenesis of nuclear bodies[END_REF]. It is generally assumed that the establishment of new nuclear compartments involves self-organization processes [START_REF] Rajendra | Genetic analysis of nuclear bodies: from nondeterministic chaos to deterministic order[END_REF]. Following an initial nucleation event, whose exact nature remains elusive, the subsequent binding of diffusing scaffolding proteins and dynamic binding partners is thought to induce the expansion of the compartment till it reaches a steady-state size. In addition to the molecular players participating in these assembly steps, molecular crowding facilitates the formation of different nuclear compartments [START_REF] Hancock | A role for macromolecular crowding effects in the assembly and function of compartments in the nucleus[END_REF][START_REF] Iborra | Can visco-elastic phase separation, macromolecular crowding and colloidal physics explain nuclear organisation?[END_REF][START_REF] Rippe | Dynamic organization of the cell nucleus[END_REF]. It is however unclear if crowding is involved at the nucleation step and/or during the growing phase. In this report, we show that the local compaction of chromatin, which is associated with an enhancement of the molecular crowding, does not, per se, constitute a nucleation event initiating the formation of new heterochromatin foci, as no accumulation of HP1β, Suv39H1 or heterochromatin-specific histone marks could be observed in hypertonically compacted euchromatin (fig. 3). Moreover cells returned to a normal eu-and heterochromatin balance within an hour after hypertonic perturbation (fig. 1). Cells can experience modifications of their osmotic environment in response to different events. For example, articular cartilage tissues react to mechanical forces by exuding water, leading to an increase of osmotic pressure experienced by the cells of these tissues [START_REF] Finan | The effects of osmotic stress on the structure and function of the cell nucleus[END_REF]. The resistance to initiate heterochromatin from hypertonically compacted euchromatin regions could be important to avoid the spontaneous silencing of genes if cells encounter a change in their environment. Nevertheless, we also observed an exclusion of several marks of actively transcribing chromatin from the newly compacted regions (fig. S5). Thus, it is possible that a more prolonged hypertonically induced compaction would be required to start de novo heterochromatinization, which was not possible to achieve experimentally due to the adaptation of cells to hypertonic conditions within one hour. In addition, our data does not exclude that the increased molecular crowding induced by chromatin compaction could play a facilitating role during the growth phase of heterochromatin, by locally promoting the binding of additional heterochromatin scaffolding proteins.

A dense and crowded chromatin packing is not required for the maintenance of heterochromatin

The specific architecture of the chromatin fiber in heterochromatin allows a very tight packing of the genetic material in these areas [START_REF] Dillon | Heterochromatin structure and function[END_REF]. If this compact structure also has functional consequences remains an actively debated question. Our results, that HP1β, Suv39H1 and heterochromatin-specific histone marks remained accumulated within heterochromatin despite the decompaction of the foci for up to three hours after hypotonic perturbation, suggest that dense heterochromatin packing and high molecular crowding, are not required to maintain the molecular identity of heterochromatin foci. This is further supported by the fact that chromatin re-compacts in very similar patterns, during the recovery phase following the hypotonic shocks (fig. 1C), exhibiting a "structural memory". In the case of constitutive heterochromatin, this memory may involve stable platforms composed of proteins that bind very tightly to chromatin such as Suv420H or Ki-67 [START_REF] Hemmerich | Dynamic as well as stable protein interactions contribute to genome function and maintenance[END_REF].

Nuclear compartments can be separated into two broad categories, those associated with specific chromatin regions, such as nucleoli and heterochromatin foci, or those that do not contain chromatin, including for example PML bodies or paraspeckles. While the first category can use chromatin as a structural platform for their dynamic steady state maintenance, the second type of compartments can only rely on the transient interactions between diffusing scaffolding proteins to preserve their integrity. Molecular crowding has been shown to be involved in the maintenance of organelles from both groups, nucleoli and PML bodies [START_REF] Hancock | A role for macromolecular crowding effects in the assembly and function of compartments in the nucleus[END_REF]. Here, our data suggest that heterochromatin foci, which similar to nucleoli are associated with specific chromatin domains, do not require a dense and crowded chromatin packing for their maintenance, suggesting that the physical mechanisms underlying the dynamic maintenance of nuclear compartments may be different from one compartment to the other. Zhou, H.-X., Rivas, G., Minton, A.P., 2008. Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences. Annu Rev Biophys 37, 375-397. The image on the left is the result of the segmentation for the raw images displayed in (A). Based on this segmentation, the concentrations of mCherry-3 in heterochromatin and compacted euchromatin, were estimated relative to non-compacted euchromatin. The boxplot shows the result of this quantification performed on 13 cells imaged successively in isotonic and hypertonic conditions. The green and blue boxes correspond to the relative concentrations of mCherry-3 in isotonic heterochromatin and hypertonically compacted euchromatin, respectively. Unpaired t-tests were used to test for statistical significance. (C) The diffusion of mEGFP was characterized by FCS at different locations in the nucleus of cells coexpressing H2B-mCherry and mEGFP. Shown on the left are the normalized autocorrelation curves at different nuclear locations for a typical cell. The raw data (dots) were fitted (plain and dotted lines) to estimate the characteristic residence times of mEGFP in the focal volume. The boxplot displays the residence times estimated for 10 cells before and after hypertonic shocks. The red, green and blue boxes correspond to the residence times measured in isotonic euchromatin, heterochromatin and in hypertonically compacted euchromatin. Shown p-values were calculated by unpaired t-tests.

Figure 3: Enhanced crowding in heterochromatin is lost upon decompaction of the heterochromatin foci by hypotonic shocks. (A) Living 3T3 cells co-expressing EGFP-H2B and mCherry-3 and labeled with Hoechst were imaged successively by confocal microscopy before and after hypotonic shocks to visualize the exclusion of mCherry-3 from heterochromatin. Insets are pseudocolored, 1.5-fold magnified views of the heterochromatin focus indicated by the red square. Bar = 4 μm. (B) Shown are the concentration ratios for mCherry-3 between heterochromatin and euchromatin measured in 8 cells imaged successively before and after hypotonic shocks. For each cell, the mCherry-3 concentrations were measured within three manually chosen euchromatic and heterochromatic areas, delineated based on the Hoechst patterns. Statistical significance was estimated by a paired t-test. For each nucleus, three heterochromatin foci were delineated manually before and after the shocks on the images in the HP1β or Suv39H1 channels. The fluorescence intensities in the hypotonic conditions were measured at least 5 minutes after the shocks. As a control, the intensity variations upon hypotonic shocks of EGFP-H2B and H2B-mCherry within heterochromatin foci were estimated in 8 nuclei co-expressing the two constructs. Displayed p-values were calculated by paired t-tests. (C) Confocal images of 3T3 cells expressing EGFP-H2B, fixed at different times after hypotonic shocks, as indicated above the images, and stained with an antibody against the histone 3 trimethylated at lysine 9 (H3K9me3). Bar = 4 μm.

Figure 1 :

 1 Figure1: Effect of osmotic stress on the chromatin compaction state in living cells. Living 3T3 cells expressing EGFP-H2B were imaged by confocal microscopy for several hours to study the consequences of osmotic stress on the chromatin compaction state. The chromatin pattern was imaged for cells bathed in isotonic (A), hypertonic (B) and hypotonic (C) media. Bar = 4 μm. Time is indicated in h:min. The raw images of the EGFP-H2B patterns were segmented automatically to distinguish compacted chromatin regions from the rest of the chromatin. The result of the segmentation is shown below the raw image sequences with green regions corresponding to compacted chromatin areas. The graphs on the right display the variations of the amount of compacted chromatin relative to the first time point, that were derived from the segmentation procedure. The purple dots correspond to the proportions of compacted chromatin calculated for the images shown on the left. The green curves were obtained by interpolating the data points after having smoothed them using a median filter. The black arrows indicate the time of the osmotic shock.

Figure 2 :

 2 Figure2: Crowding conditions in hypertonically compacted euchromatin are similar to those encountered in isotonic heterochromatin. (A) Living 3T3 cells co-expressing EGFP-H2B and mCherry-3 were imaged by confocal microscopy to visualize the exclusion of mCherry-3 from dense chromatin areas. The EGFP-H2B and mCherry-3 patterns were imaged before and after hypertonic shocks. Bar = 4 μm. The fluorescence intensity profiles shown on the right for EGFP-H2B and mCherry-3 were measured along the green or red dotted lines, respectively, and normalized against the mean intensity along the profile. The orange arrowhead corresponds to a heterochromatin focus and the blue arrowheads indicate two hypertonically compacted euchromatin regions. (B) The image on the left is the result of the segmentation for the raw images displayed in (A). Based on this segmentation, the concentrations of mCherry-3 in heterochromatin and compacted euchromatin, were estimated relative to non-compacted euchromatin. The boxplot shows the result of this quantification performed on 13 cells imaged successively in isotonic and hypertonic conditions. The green and blue boxes correspond to the relative concentrations of mCherry-3 in isotonic heterochromatin and hypertonically compacted euchromatin, respectively. Unpaired t-tests were used to test for statistical significance. (C) The diffusion of mEGFP was characterized by FCS at different locations in the nucleus of cells coexpressing H2B-mCherry and mEGFP. Shown on the left are the normalized autocorrelation curves at different nuclear locations for a typical cell. The raw data (dots) were fitted (plain and dotted lines) to estimate the characteristic residence times of mEGFP in the focal volume. The boxplot displays the residence times estimated for 10 cells before and after hypertonic shocks. The red, green and blue boxes correspond to the residence times measured in isotonic euchromatin, heterochromatin and in hypertonically compacted euchromatin. Shown p-values were calculated by unpaired t-tests.

Figure 4 :

 4 Figure 4: The local compaction of euchromatin by hypertonic shocks is not sufficient to initiate the formation of new heterochromatin areas. (A) Confocal images of living 3T3 cells expressing HP1β-EGFP or Suv39H1-EGFP together with H2B-mCherry and bathed with isotonic or hypertonic media. Insets are pseudocolored, 1.5fold magnified views of the euchromatin areas indicated by the red squares. Bar = 4 μm. (B) Shown are the relative variations upon hypertonic shocks of the integrated fluorescence intensities for H2B, HP1β and Suv39H1 within hypertonically compacted euchromatin (12 cells co-expressing HP1β-EGFP and H2B-mCherry and 11 cells co-expressing Suv39H1-EGFP and H2B-mCherry, 3 ROIs per nucleus).The regions where we measured the fluorescence intensities were defined manually based on the H2B patterns after the shocks. The fluorescence intensities in the hypertonic conditions were measured at least 5 minutes after the shock. As a control, the intensity variations upon hypertonic shocks of EGFP-H2B and H2B-mCherry within hypertonically compacted euchromatin were estimated in 8 nuclei co-expressing the two constructs. p-values were calculated by paired t-tests. (C) Confocal images of 3T3 cells expressing EGFP-H2B, fixed at different times after hypertonic shocks, as indicated above the images, and stained with an antibody against the histone 3 trimethylated at lysine 9 (H3K9me3). Insets are pseudocolored, 1.5-fold magnified views of the regions indicated by the red squares. Bar = 4 μm.

Figure 5 :

 5 Figure5: Dense chromatin packing is not necessary for the maintenance of heterochromatin. (A) Confocal images of living 3T3 cells expressing HP1β-EGFP or Suv39H1-EGFP together with H2B-mCherry and bathed with isotonic or hypotonic media. Insets are pseudocolored, 1.5-fold magnified views of the heterochromatin foci indicated by the red squares. Bar = 4 μm. (B) Shown are the relative variations upon hypotonic shocks of the integrated fluorescence intensities for H2B, HP1β and Suv39H1 within heterochromatin (13 cells for both HP1β-EGFP / H2B-mCherry and Suv39H1-EGFP / H2B-mCherry co-expressions). For each nucleus, three heterochromatin foci were delineated manually before and after the shocks on the images in the HP1β or Suv39H1 channels. The fluorescence intensities in the hypotonic conditions were measured at least 5 minutes after the shocks. As a control, the intensity variations upon hypotonic shocks of EGFP-H2B and H2B-mCherry within heterochromatin foci were estimated in 8 nuclei co-expressing the two constructs. Displayed p-values were calculated by paired t-tests. (C) Confocal images of 3T3 cells expressing EGFP-H2B, fixed at different times after hypotonic shocks, as indicated above the images, and stained with an antibody against the histone 3 trimethylated at lysine 9 (H3K9me3). Bar = 4 μm.

ACKNOWLEDGMENTS

We thank Marc Tramier and Wanqing Xiang for critical reading of the manuscript. We are grateful to the members of the Advanced Light Microscopy Facility at the European Molecular Biology Laboratory, and of the Microscopy Rennes Imaging Center for technical assistance with the microscopes. S.H. was supported by a fellowship from the European Molecular Biology Organization. S.H. and C.C. were supported by grants from the Agence National de la Recherche (JCJC-SVSE2-2011, ChromaTranscript project) and from the European Union (FP7-PEOPLE-2011-CIG, ChromaTranscript project)


Charles Crespy
email: charles.crespy@insa-lyon.fr

Philippe Duvauchelle
email: phillipe.duvauchelle@insa-lyon.fr

Valerie Kaftandjian

Ferréol Soulez

Energy Dispersive X Ray Diffraction to identify Explosive Substances : spectra analysis procedure optimization

Keywords: Explosives detection, X-ray diffraction, non destructive testing

come

Introduction

Energy dispersive X-ray diffraction (EDXRD) has been successfully used for many years to provide information about the crystalline structure of samples. In this technique, a sample is probed by a polychromatic X-ray beam. Photon-matter interactions occur along the incident X-ray beam, in particular, the coherent scattering. The measurement is performed at a fixed scattering angle (θ) with an energy resolved detector. The spectrum thus obtained is material specific since it is linked to the atomic planar spacing (d) and to the radiation wavelength (λ) according to Bragg law: 2dsin θ = nλ (where n is an integer).

Nowadays, EDXRD is a well established technique developed for a large number of inspection applications (see [Harding'90] and [Luggar '99]). The spectrum analysis procedure is chosen over the major requirements of the application (fast acquisition, accuracy...). Historically, the procedure to recognize an unknown substance from its diffraction spectrum has been developed by Hanawalt in 1936 (see [Langford'96]). It is based on comparison between the main peaks location of the sample spectrum and referenced ones in a paper library. Some particular spectra analysis procedures have been introduced for specific applications. In [Luggar'99b], oil and water ratios are measured in bulk liquid. The analysis spectra procedure consists in performing ratio of the scattering into two energy windows, which provides results with a relative error of 0.6%. [Ballirano '08] reports the first application of EDXRD to the simultaneous structural and compositional characterization of papers. The procedure consists in analyzing the shape of the relevant peak of the crystalline form of cellulose. In [Farquharson '97], authors show that multivariate analysis (MVA) can be a useful technique to estimate components concentration in bones from EDXRD spectra. Principal components are estimated, then calibration bone phantoms are constructed to train the MVA model. The results obtained with measured spectra highlight the influence of exposure time on the accuracy which can reach 3%. For all these studies, the analysis is based on the assumption that the spectrum under testing contains known materials.

In the case of luggages inspection, materials number and type are unknown. They can be divided into illicit materials (like drugs, explosives) and common ones (such as sugar, toothpaste...). The identification of illicit materials from their diffraction spectra is usually based on a comparison with a library. One can distinguish different cases : either the library contains only illicit materials spectra, or a complete set of illicit and common materials.

In [Cook'07], X-ray diffraction is proposed as a suitable method to identify illicit drugs in parcels.

To this end, spectra of several drugs and possible cutting agents have been used to train a MVA software to identify drug in samples. The technique provides quantitative data of a desired variable (like drug content). In order to reduce the false alarm rate, a database containing the measured spectra of several thousand materials likely found in parcels has to be used. A specific software has been developed to predict EDXRD experimental spectra from powder diffraction profiles [Cook '09]. The interest is that powder diffraction files are high energy resolution, and thus, the software allows to model different experimental conditions (see [Pani'09]). However, the database must contain a huge number of materials. In [Cook'09b], authors show that MVA predictions based on simulated data are close to MVA predictions based on measured data.

Concerning explosive devices detection inside packages, EDXRD has been examined over the last decade as a suitable tool. In order to reduce the time measurement and to increase the spectral resolution, an experimental device geometry has been established to optimize explosive detection by Luggar and al. (see [Luggar'96] and [Luggar'97]). In [Luggar '98], MVA is performed to detect the presence of explosives. His study demonstrates how MVA may be applied to reduce acquisition time which constitutes one of the main requirement for explosive detection. The limit of this study is the low number of substances used to calibrate the model which leads to a high false alarm rate. In [Malden'00] EDXRD combined with an angular dispersion is examined. It seems to be an efficient way to improve robustness but requires a more complex experimental device.

Harding studied the detection of crystalline explosives (see [Harding'99] and [Harding'04]). The data processing takes place in two stages. At first, Wiener filtering is performed to reduce noise in spectra recorded with a low acquisition time, then similarity measure between sample spectra and all library entries is calculated. The author does not disclose the false alarm rate related to this method. In [Harding '06] and [Harding'07] the author focuses on amorphous explosive detection.

The main conclusions of the Harding's studies are summed up in [Harding '09].

The present survey concerning substance identification with EDXRD highlights that different kinds of analysis procedures could be implemented successfully. In the present study, a database containing measured EXDRD spectra of several explosives and common materials has been constructed. To construct the database, two kinds of detector, characterized by their spectral resolution, are used. In a second time, different classical analysis procedures are implemented, the robustness and the limit of each methods are examined. Finally we propose a spectra analysis sequence to discriminate explosive substances. The paper is organized as follow: the first section deals with the experimental procedure used to build the library, then the recorded spectra are commented in the second section. Finally the robustness of different analysis procedures are tested in the third section.

2.EDXRD technique

Experimental arrangement

Schematic representation of experimental device is shown in figure 1. X-ray radiations from a 100 kV tungsten anode X-ray tube operating at 280 µA irradiate the sample. The X-ray source has a 10 µm focal spot. The scattered photons are detected with detector orientated at 4.28° from the incident beam. Two types of detectors are used to acquire spectra in this work: CdZnTe or High purity Germanium (Ge). The main difference between both detectors is that Ge detector has to be cooled by cryogenic system (it cannot be used in a mobile detection system,) while CdZnTe detector is a room temperature detector. This point leads to a better spectral resolution when Ge detector is used.

CdZnTe detector has a FWHM (full width half middle) of 2 keV at 60 keV (see [Verger'07]), while Ge detector has a FWHM of 0.4 keV at 60 keV Another difference between spectra acquired with CdZnTe and Ge is the difference between spectral range of both detectors. It can be noticed that the measuring range of Ge detector is from 15 to 100 keV while the measuring range of CdZnTe detector is from 30 to 100 keV. The CdZnTe detector cut the spectra around 30 keV, this limit is not due to the crystal but just an electronic threshold. In the case of luggage inspection, this threshold is out consequence because low energy photons are strongly attenuated thus information under 40 keV is not really useful.

Collimation system allows the direct localization of a scatter volume within the sample. The collimator located after the source is a slit of 0.2 mm width and 8 cm length. The collimator located in front of the detector is a slit of 0.1 mm width and 8 cm length. The scatter angle is a critical parameter which affects the energy resolution, the peaks intensity. It is chosen close to 4° as a good compromise between angular resolution and main peaks location of explosive substances.

Scattering angle is estimated accurately thanks to graphite spectrum measurement performed with Ge detector. The uncertainty of the scatter angle is +or-0.05°. Finally, the exposure time is set at 600s, for each spectra spectra to have a good counting statistic.

EDXRD Spectra

In EDXRD, the spectra acquired depends not only on the sample but also on the experimental set up. An example of an EDXRD acquired with Ge detector spectrum is presented in figure 2.

Figure 2

On figure 2, it can be noted that the spectra is composed of a baseline and peaks. The baseline is caused by the amorphous part of the sample, the incoherent scattered radiation and the spectral shape of X-ray beam. In our configuration, the number of photons whose energy is upper than 90 keV is too low to provide suitable information in this range of energy. Thus the useful range of energy is from 20 kev to 90 keV. The spectral shape of the X-Ray source bias the intensity of the diffraction peaks too: its influence can be removed by normalization to the transmitted spectrum if required.

Regarding to the peaks, two kinds of peaks must be distinguished. Some are caused by the characteristic X-ray lines of the X ray tube tungsten target, others are diffraction peaks. Diffraction peaks are the part of the information which is used to identify the sample. The diffraction peaks width are linked to the angular dispersion due to the collimation system and the spectral resolution of the detector. Assuming that diffraction peaks are Gaussian type it can be written:

FWHM T = (FWHM D 2 + FWHM C 2 ) 0.5 (1)
Where FWHM T is the total diffraction peak FWHM, FWHMc is the contribution of the collimation system and FWHM D is the contribution of the detector. While FWHM D is known, FWHM C can be estimated experimentally by comparing the width of the diffraction peaks with the width of the fluorescence peaks or numerically by using a Monte Carlo simulation code.

The FWHM T is experimentally estimated: using a CdZnTe detector the FWHM of a diffraction peak is close to 2.4 keV, while it's close to 0.95 keV for Ge detector. These values are of the same order of magnitude than the numerical prediction. In our case it can be noticed that when CdZnTe detector is used, the detector resolution is the predominant parameter in overall spectral resolution. In the case of the Ge detector, the angular resolution due to the collimation system, is the predominant parameter.

Concerning the noise it can be reduced by rising the exposure time. In the case of an automated system the exposure time has to be as smaller as possible. As it has been advocated by Harding, the Wiener filter is a suitable tool for noise reduction in EDXRD spectra. The influence of the Wiener filter on Ge and CdZnTe detectors spectra is shown on figure 3.

Figure 3

In the following all spectra presented have been filtered.

Database diffraction spectra

Explosives spectra

The spectra of five explosive substances have been recorded: TNT (100% Tolite), Semtex (91 % RDX), Formex (87% PETN), PLA NP (89% PETN) and HCG (98% RDX). The acquisition time is set to 600 seconds. As an illustration, the filtered spectra of PLA NP and Formex recorded with Ge and CdZnTe detectors are shown in figure 4.

Figure 4

The spectra obtained with the Ge detector show a serie of well resolved peaks. The spectra acquired with the CdZnTe detector show a series of broader peaks which does not allow to resolve very close peaks. Figure 4 shows the influence of the CdZnTe hardware cut at 40 keV. Formex and PLA NP are characterized by the same explosive substance (PETN), this results in two peaks in common around 45 keV which can be seen in Ge spectra.

Common material spectra

In order to evaluate the robustness of the method, spectra of eleven common materials likely to be found in packages have been recorded: NaCl, graphite, PVC, toothpaste, sugar, cotton, soap, aluminum, nickel, copper and coffee. Filtered spectra of PVC and NaCl recorded with Ge and CdZnTe detectors are shown in figure 5. Unlike explosive spectra, it can be noticed that most of common materials from our library do not show well resolved peaks, but an amorphous trend with broad peaks.

Figure 5

Uncertainty estimation on peaks location

Since peaks location of a spectra is a capital information about the sample, the uncertainty on the major peak location is estimated. Ten spectra of the same sample successively recorded under similar conditions are compared. The standard deviation on peak location (s) is estimated and used to calculate the uncertainty (2s). This procedure is repeated with three samples (NaCl, Graphite and Aluminum), for the both detectors, with and without Wiener filtering. The results are shown in figure 6.

Figure 6

It can be concluded that Wiener filtering is not only a means to remove noise, but also an efficient tool to reduce the uncertainty on peaks location since it allows to reduce significantly the uncertainty with both detectors. After filtering, the uncertainty on peak location for Ge detector is less close to 0.2 keV instead of 1.6 keV for CdZnTe detector. Thus, it is expected to obtain a lower false alarm rate when Ge detector is used.

Spectra analysis procedure

Cristallinity criterion

It can be useful to define a cristallinity criterion to distinguish amorphous materials from crystalline ones. The chosen method is based on the cristallinity degree estimation as performed with angular dispersive X ray diffraction (see [Cheetham'98]). A smooth curve which connects peak base is estimated using mathematical morphology opening technique (see figure 7).

Figure 7

The area above the smooth curve corresponds to the crystalline part while the area under the smooth curve corresponds to the amorphous part. The crystallinity criterion is then estimated as the ratio of upper spectrum area to total diffraction spectrum area. This criterion corresponds to the crystallinity degree used in Angular dispersive X ray diffraction. In the EDXRD case even if the source spectrum shape plays an important role we decide to use the same criterion. The quantitative results of our samples are shown on figure 8. Choosing a crystallinity criterion threshold around 0.2 allows to eliminate a large part of common materials (4 common materials have a cristallinity criterion higher than 0.2) Thus, this crystallinity criterion estimation can be used as a first discriminative step.

Figure 8

Similarity criterion

As a second step, it has been chosen to identify explosives by calculating a similarity criterion i.e. the cross correlation coefficient.

Acquisition time influence

In order to estimate the robustness of the technique, the influence of acquisition time is investigated.

For many substances, six spectra of a same material are acquired with different acquisition times (60s, 300s, 420s, 600s, 720s and 900s). Then, the cross correlation coefficient is calculated between the spectrum acquired in 900s and the five others. The threshold in terms of cross correlation coefficient is fixed at 0.97, i.e. if the cross correlation coefficient between two spectra is higher than 0.97, the spectra are considered identical. The results for Semtex spectra with and without filtering are shown on figure 9.

Figure 9

This example is typical of all investigated cases. The results show that after filtering, spectra acquired with different acquisition time are equivalent. Thus, Wiener filter is a suitable tool to reduce acquisition time. The results are the same whatever the detector used.

Substance identification

To test the method robustness, a library containing the filtered spectra of each materials is constructed. For a given and unknown material, the cross correlation coefficient is calculated and compared to each library's spectrum in an identification goal. It can be noted that the whole spectrum (amorphous and crystalline part) is used for cross correlation analysis. The results are shown in Table 1.

Table 1

Using the Ge detector allows to identify a material whatever its crystallinity criterion. Using the CdZnTe detector, the low spectral resolution leads to a partial loss of information. Indeed, although there is no real false alarm case, confusion between some amorphous materials can be noted. For instance, toothpaste can not be distinguished from PVC, nor cotton from coffee. The confusion between TNT and Formex is the only confusion between two substances whose cristallinity criterion is upper than 0.2. Thus, it can be thought that some crystalline common materials could also lead to false alarm.

Multivariate Calibration

Detailed description of multivariate calibration procedure can be found in [Cook '07] or [Farquharson'97]. The MVA consists in creating a model in order to link experimental data (X) to quantitative information concerning the sample (Y). As a first step, a linear regression model of the form Y=BX is estimated. To this end, a set of calibration spectra is used to train the model. The second step consists in using the model to identify an unknown spectrum. In our case, the experimental X data are the measured spectra. While, in general, Y data corresponds to composition of the sample (see [Cook'07] [Luggar '98]). Thus X is a N dimension vector (N corresponds to the number of channels), Y is a M dimension vector (M corresponds to the number of substances searched for). In practice, it's impossible to perform a well conditioned regression in these conditions, thus X variables is reduced to a short number of principal components (PCs). Authors show that MVA is a very powerful tool when the spectra of the substances to identify have been used to train the model. Thus, for an unknown package, a database containing several thousands spectra would be required. In our application the presence of explosive is examined, thus Y is not the sample composition but a threat factor whose value varies from 0 to 1 (0: no explosive in the sample, 1: explosive in the sample). This kind of model is an efficient way to search for a characteristic in explosive spectra which could accurately discriminate them from common materials spectra. The model is trained with a set of 84 measured spectra (spectra of the 16 materials acquired with the 5 acquisition time), the number of PCs is 9. The threshold for detecting the presence of an explosive is fixed to 0.5. Results of the model are shown in figure 10.

Figure 10

It can be concluded that this model leads to one mistake whatever the detector used. In order to check the robustness, the model is tested with spectra from materials which have not been used to train the model. For instance, the model results for water spectra is a false alarm (Y(H2O)=0.8).

These findings allow to conclude that it's difficult to identify explosives spectra with a linear model.

Thereby, this kind of model is not suitable to discriminate explosive spectra from common materials. The only way to reduce the false alarm rate should be to train the regression model with a complete library containing every common materials spectra which is impossible.

Major peaks location analysis

Another technique inspired from Hanawalt procedure consists in using the major peaks location in order to identify a substance. To perform that a Levenberg-Marquardt minimization algorithm is used to find the sum of Gaussian functions which fit best the spectrum (see figure 11). It's to note that the amorphous part of the spectrum is subtracted before performing the extraction peak procedure.

Figure 11

The standard deviation of the Gaussian function is linked to the detector spectral resolution and the collimation characteristics (see §2.2). According to Bragg's law, it must be noted that the standard deviation of the Gaussian function is not constant but increases with energy. In first approximation, this point is neglected in the peaks extraction procedure. If a peak corresponds to a characteristic line of the X ray tungsten, it is not taken into account during the analysis.

Position is given in momentum transfer (x=sin(θ/2)/λ) which is a convenient way to express results independently on the diffraction angle .The two main peaks location from Ge spectra of each sample are plotted in figure 12.

Figure 12

It can be noted that the spectra of the explosive substances have the main peak located between 1 nm -1 and 1.4 nm -1 (respectively 30 keV and 50 keV when θ=4.28°). Sugar, soap and graphite also show this characteristic. Using two main peaks allows to reduce the false alarm rate: materials which have the two main peaks located between 1 nm -1 and 1.6 nm -1 (respectively 30 keV and 55 keV when θ=4.28°) are explosives only.

Regarding now CdZnTe spectra, the explosive main peaks are located between 1.2 nm -1 and 1.6 nm - 1 (respectively 40 keV and 52 keV when θ=4.28°). Some spectra of common materials (soap, sugar, graphite) have the same characteristics.

Figure 13

The example of graphite is an interesting case. It's known that theoretically the graphite spectrum has just one peak. When a measured peak is broader than the previsions, peaks extraction procedure can lead to the detection of two very close peaks. On figure 3 it can be noted that the main peak of graphite has a non Gaussian shape (asymmetric shape). This asymmetry is related to the height of the collimator which increases the angular aperture with angles above the nominal angle. Moreover, since the graphite peak is located at high energy, it can be though that this point is linked to the variation of standard deviation of Gaussian fit with energy.

To sum up, it can be noted that the couple defined by the two main peaks location is material specific whatever the detector used. Moreover all explosives spectra of our library have their main peak located between 1 and 1.6 nm -1 . Concerning Ge acquisition, a second peak in this range of energy can be detected. In the future it 's important to check that this observation is valid for every crystalline explosive substances. However, it's possible that others common materials can have these characteristics, probably crystalline organic materials such as drugs.

Influence of attenuation on explosive detection

The aim of this section is to examine if the detection procedure presented above is still valid in the context of our application (when the explosive is in a package). The main problem concerns photon attenuation which depends on their energies and then can significantly modify the diffraction spectrum. Thus, this section focuses on the possibility to identify an explosive spectrum which is modified by a attenuation. The part of the transmitted signal integrated along the wave length can be measured using a scintillator.

An experimental procedure has been implemented. It consists in measuring the spectra of an explosive without attenuation, then the experience is repeated when the material is in a package. For example, Figure 14, we can see the presence of explosives (Semtex) into a package containing paper, books and cotton.

Figure 14

Six packages containing materials more or less absorbent (cotton, pound, copper …) are used. Each package is characterized by the percentage of attenuation it causes. The most mitigating package absorbs 89% of the total transmitted signal while the least absorbs 15% of the signal. The figure 15 show the influence of attenuation on Semtex spectrum when the transmitted signal is close to 65 %.

Figure 15

We observe on figure 15 the difficulty to recognize attenuated from original spectrum. This is due to the fact that attenuation is not spectrally homogeneous, the high energy signal is less attenuated than the signal at low energy. Fortunately, the peaks location is not modified by the attenuation.

However, it had be found experimentally that when the transmitted signal is below 30%, the peaks located below 50 keV are no longer detectable. Since the characteristic peaks of explosives are between 30 and 50 keV, it is considered that explosive detection is not possible if the transmitted signal is less than 30%.

To quantify the influence of attenuation on the cross correlation coefficient identification procedure the cross correlation coefficient is calculated between the spectrum unattenuated and the attenuated one. The results are presented in Figure 16.

Figure 16

Note that when the transmitted signal is below 65%, it's no longer possible to recognize the spectrum of Semtex using the correlation coefficient. Since attenuation can damage the spectra shape of a sample, the thresholds of all detection procedures have to be redefined as a function of attenuation.

Spectra analysis sequence

Taking into account the conclusions of the section 4, an algorithm dedicated to automatic detection has been implemented. The principle is illustrated in figure 17. The two entries of the algorithm is sample spectra and the integrated attenuation.

Figure 17

First, the integrated attenuation is used to define the detection reliability. This parameter influence the detection thresholds of the detection procedure. If the transmitted signal is less than 30% of the initial signal, it is considered that the identification is not possible.

If the detection reliability is sufficient, the sample spectrum is analyzed. The sample spectrum is first filtered, then the crystallinity criterion is calculated. If the spectrum of the sample is of crystalline type (crystallinity criterion >0.2), the cross correlation coefficient is used to compare the sample spectra with the explosive spectra of our library. Finally, in case of non detection, peaks location of the sample are compared with those of explosives taking into account the uncertainty.

It's to note that the whole spectrum (amorphous and crystalline part) is used in cross correlation analysis, while only the crystalline part is used for peak location analysis. In case of using CdZnTe spectra, only the two main peaks are used for identification while when Ge detector is used it's possible to compare a larger number of peaks in order to reduce the false alarm rate. This step is important to detect explosive substance in inhomogeneous voxel. The three step detection procedure allow to increase the robustness. Moreover, the graphic user interface (GUI) allows a direct visual comparison between sample spectra and those of the library. To illustrate, Figure 18 shows a screen-shot of the graphic user interface.

Figure 18

Conclusion

In this study, explosive detection using EDXRD has been investigated using a library containing five explosives and eleven common materials. As a first step it was chosen to study crystalline explosives. Thus a crystallinity criterion calculation is proposed in order to discriminate them from common materials. This step allow to discriminate easily many common materials from explosive ones. To perform a more accurate discrimination three classical spectra analysis procedures have been implemented: similarity criterion calculation, MVA and main peaks location. It has been shown that the use of MVA requires to build a complete library containing not only explosives spectra but also every common materials spectra. That's why this technique is considered as not suitable for package inspection. On another hand, explosive spectra show some discriminant characteristics in term of peaks location and cross correlation coefficient. Whatever the analysis procedure, the Ge spectra are more suitable for discrimination than CdZnTe. Thus CdZnTe detector can be applied as a complementary technique in a portable system in order to reduce the false alarm rate.

Following this study, the library will be completed with other explosive spectra, and the detection technique will be tested with more crystalline common materials in order to estimate accurately the false alarm rate. Moreover, to improve the discrimination rate with CdZnTe detector it's envisaged to decrease the scattering angle at 3° and redefine the collimation system.

  Figures caption: figure 1: schematic representation of the experimental setup figure 2: Example of a diffraction spectrum acquired with Ge detector figure 3: visualization of Wiener filter influence on measured spectra with CdZnTe (a) and with Ge (b) figure 4: examples of explosive spectra measured with a Ge detector (left) and a CdZnTe detector (right) figure 5: examples of common materials spectra measured with a Ge detector and a CdZnTe detector figure 6: peak location uncertainty figure 7: estimation of amorphous area (gray zone) with morphological opening of the global spectrum (on the left for the PLA NP and on the right for PVC) figure 8: cristallinity criterion of our samples figure 9: cross correlation coefficient as a function of exposure time for Semtex and the 2 studied detectors figure 10: MVA results for CdZnTe and Ge spectra figure 11: examples of peaks extraction in TNT spectra acquired with CdZnTe detector (a) and Ge detector (b) figure 12: two main peaks location of Ge spectra θ=4.28°f igure 13: two main peaks location of CdZnTe spectra θ=4.28°f igure14: visualization of a package containing an explosive substance figure 15: visualization of the influence of attenuation on Semtex spectrum acquired with Ge detector when the transmitted signal is close to 65% figure 16: influence of the attenuation on the substance identification with cross correlation coefficient figure 17: detection algorithm principle figure 18: illustration of the interface of the detection algorithm

Table caption :Table 1 :

 caption1 substance identification using cross correlation coefficient

	Table:
	Material Tested	Germanium detector	CdZnTe detector
	Aluminum	Aluminum	Aluminum
	Coffee	Coffee	Coffee
			Cotton
	Copper	Copper	Copper
	Toothpaste	Toothpaste	Toothpaste
			PVC
	Graphite	Graphite	Graphite
	NaCl	NaCl	NaCl
	Nickel	Nickel	Nickel
	PVC	PVC	PVC
			Toothpaste
	Sugar	Sugar	Sugar
	Soap	Soap	Soap
	Cotton	Cotton	Cotton
			Coffee
	Semtex	Semtex	Semtex
	Formex	Formex	Formex
			TNT
	PLA NP	PLA NP	PLA NP
	HCG	HCG	HCG
	TNT	TNT	TNT
			Formex

Table 1 :

 1 substance identification using cross correlation coefficient

Acknowledgements

This work was conducted in the frame of the SPIDERS project, supported by the French National research agency. Specifically, we wish to thank the CEA LETI for having lent the CdZnTe detector and ETBS for having supplied the explosive substances.