I Phapale

Régis Chernyavsky

D Lavigne

A Fay

V Tarasov

J Kovalev

S Fuchser

Charles Nikolenko

Pineau

Andrew Palmer

Prasad Phapale

Ilya Chernyavsky

Regis Lavigne

Dominik Fay

Artem Tarasov

Vitaly Kovalev

Jens Fuchser

Sergey Nikolenko

Charles Pineau

Michael Becker

Theodore Alexandrov
email: theodore.alexandrov@embl.de

FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry

FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry

mass-resolution (HR) MS that discriminates metabolites differing by a few mDa promises to achieve unprecedented reliability of metabolite annotation. However, no bioinformatics exists for automated metabolite annotation in HR imaging MS. This has restricted this powerful technique mainly to targeted imaging of a few metabolites only [START_REF] Spengler | Mass spectrometry imaging of biomolecular information[END_REF] . Existing approaches either need visual examination or are based on the exact mass filtering known to produce false positives even for ultra-HR MS [START_REF] Kind | Metabolomic database annotations via query of elemental compositions: mass accuracy is insufficient even at less than 1 ppm[END_REF] . This gap can be explained by the field novelty and high requirements to the algorithms which should be robust to strong pixel-to-pixel noise and efficient enough to mine 10-100 gigabyte datasets.

An additional obstacle is the lack of a metabolomics-compatible approach for estimating False Discovery Rate (FDR) [START_REF] Benjamini | Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing[END_REF][START_REF] Storey | A direct approach to false discovery rates[END_REF] . FDR is defined as the ratio of false positives in a set of annotations. FDR is a cornerstone of quantifying quality of annotations in genomics, transcriptomics, and proteomics [START_REF] Käll | Assigning significance to peptides identified by tandem mass spectrometry using decoy databases[END_REF] . The proteomics target-decoy FDR-estimation is not directly applicable in metabolomics where there is no equivalent of a decoy database of implausible peptide sequences. An FDR-estimate in metabolomics was proposed earlier [START_REF] Matsuda | Assessment of metabolome annotation quality: a method for evaluating the false discovery rate of elemental composition searches[END_REF] but is limited to phytochemical metabolites, has not found widespread use and cannot be applied to imaging MS as it does not allow incorporating spatial information. An alternative approach to estimate FDR is to use a phantom sample with controlled molecular content but it is inherently complex and narrowed to a specific protocol.

We have addressed this double challenge and developed a comprehensive bioinformatics framework for FDR-controlled metabolite annotation for HR imaging MS. Our open-source framework (https://github.com/alexandrovteam/pySM) is based on the following principles: database-driven annotation by screening for metabolites with known sum formulas, an original Metabolite-Signal Match (MSM) score combining spectral and spatial measures, a novel target-decoy FDR-estimation approach with a decoy set generated by using implausible adducts.

Our framework takes as input: 1) an HR imaging MS dataset in the imzML format, 2) a database of metabolite sum formulas in a CSV format (e.g., HMDB [START_REF] Wishart | HMDB 3.0--The Human Metabolome Database in 2013[END_REF] ), 3) an adduct of interest (e.g., +H, +Na, +K). For a specified FDR level (e.g., 0.1), the framework provides metabolite annotations: metabolites from the database detected as present in the sample. The framework cannot resolve isomeric metabolites; the provided putative molecular annotations are on the level of sum formulas [START_REF] Sumner | Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI)[END_REF] .

Our novel MSM score quantifies the likelihood of the presence of a metabolite with a given sum formula in the sample (Figure 1; Supplementary Note 1, Figure S2). For an ion (sum formula plus ion adduct, e.g., +H), we generate its isotopic pattern accounting for the instrument resolving power with isotopic fine structure if resolvable. Then, we sample from the imaging MS dataset an ion signal, namely, the ion images for all isotopic peaks with predicted intensity greater than 0.01% of the principal peak (Supplementary Note 1, Figure S1). MSM is computed by multiplying the following measures. (1) Measure of spatial chaos quantifies spatial informativeness within the image of the principal peak [START_REF] Alexandrov | Testing for presence of known and unknown molecules in imaging mass spectrometry[END_REF] . We introduce an improved measure of spatial chaos (Algorithm OM1) which outperforms earlier proposed measures [START_REF] Alexandrov | Testing for presence of known and unknown molecules in imaging mass spectrometry[END_REF][START_REF] Wijetunge | EXIMS: an improved data analysis pipeline based on a new peak picking method for EXploring Imaging Mass Spectrometry data[END_REF] in both speed and accuracy (Supplementary Note 1). ( 2) Spectral isotope measure quantifies spectral similarity between a theoretical isotopic pattern and relative sampled isotopic intensities. (3) Spatial isotope measure quantifies spatial co-localization between isotopic ion images. The MSM score of 1 indicates the maximal likelihood of the signal to correspond to the ion.

Our novel FDR-estimate helps select an MSM cutoff so that the ions with MSM scores above the cutoff will confidently correspond to metabolites from the sample (Figure 1; Supplementary Note 1, Figure S2). According to the target-decoy approach [START_REF] Käll | Assigning significance to peptides identified by tandem mass spectrometry using decoy databases[END_REF] , we propose to construct a decoy set as follows. We define a target set as ions from a metabolite database with a given ion adduct (e.g., +H). We define the decoy set as ions for the same sum formulas but with the following implausible adducts. For each sum formula, we randomly select an implausible adduct from the CIAAW 2009 list of the elements (e.g., +B, +Db, +Ag) excluding plausible adducts. MSM scores are calculated for target and decoy ions. For any MSM cutoff, FDR is estimated as the ratio between the numbers of decoy false positives (the decoy ions with MSM scores above the cutoff, FP D ) and target positives (the target ions with MSM scores above the cutoff). Here, we approximate the number of target false positives (FP T ) by FP D assuming the target and decoy sets to be similar. The sampling of implausible adducts is repeated, averaging the resulting FDR-estimate. FDR-controlled metabolite annotation is performed by specifying the desired value of FDR (e.g., 0.1) and choosing the smallest MSM cutoff providing the desired FDR (Figure 1; Supplementary Note 1, Figure S2). FDR-controlling provides annotations of a given confidence independently on the MSM cutoff, dataset, MS settings and operator, and can be used for comparative and inter-lab studies.

We evaluated the proposed FDR-estimation (Supplementary Note 1). First, we studied the similarity between the decoy and target ions required to fulfill FP D ≈FP T . Relative intensities of isotopic patterns for target and decoy ions were found to be similar (Figure 2a) despite the decoy ions have higher relative intensities for heavier isotopic peaks due to more complex isotopic patterns. The target and decoy ions were also found to be similar in the m/z-and mass defect-space (Figure 2b), with a positive offset in m/z for decoy adducts which typically have heavier elements. Second, we compared the estimated and true FDR for a simulated dataset with a known ground truth (Figure 2c; Supplementary Note 1). Although there is some difference in the low-values region, estimated FDR follows the true FDR overall. Finally, negative control experiments using each of the implausible adducts as a target one showed that FDR values for implausible adducts are characteristically higher (Figure 2d; Supplementary Note 1).

We showcased our framework on HR imaging MS datasets from two (a1 and a2) female adult wild-type mice (Supplementary Note 1). The brains were extracted, snap-frozen, and sectioned using a cryostat. Five coronal sections were collected from each brain: 3 serial sections (s1-s3) at the Bregma 1.42 mm, s4 at -1.46 mm and s5 at -3.88 mm. The sections were imaged using a 7T MALDI-FTICR mass spectrometer solariX XR (Bruker Daltonics) in the positive mode with 50 µm raster size. The datasets were of 20-35 gigabytes in size each. FDR-controlled annotation was performed with the desired level of FDR=0.1 for metabolites from HMDB with +H, +Na, +K adducts, and m/z-tolerance of 2.5 ppm (Figure 2e-i). Venn diagrams of annotated metabolites (Figure 2e) show a high reproducibility between sections from the same animal (especially between the serial sections from a2 where 51 of 73 sum formulas were annotated in all three sections), and between the animals (only two sum formulas were annotated in the animal a1 only). The numbers of detected adducts were similar (Figure 1f). Exemplary molecular images of annotations illustrate a high reproducibility between technical replicates and animals (Figure 1g). Phospholipids were detected mostly (PCs, PEs, SMs, PAs; Supplementary Note 1, Table S5 and Figure S10) that is typical for MALDI imaging MS of brain tissue using the HCCA matrix [START_REF] Gode | Lipid imaging by mass spectrometry --a review[END_REF] . From overall 103 annotations, 16 representative ones were validated with LC-MS/MS by either using authentic standards or assigning fragment structures to MS/MS data (Supplementary Note 3).

We demonstrated the potential of using FDR curves in two examples. First, we showed that MSM outperforms the individual measures (Figure 2h; Supplementary Note 1, Figure S8). The exact mass filtering performs significantly worse, achieving the lowest FDR=0.25 for 10 annotations (vs. FDR=0 for the same number of annotations when using MSM). Second, we demonstrated that the number of FDR-controlled annotations decreases with the decreasing mass resolving power (Figure 2i; Supplementary Note 1, Figure S9). For this, we artificially reduced mass resolving power by using different m/z-tolerances when sampling m/z-signals: 1, 2.5 (default), 5, 30, 100, 1000, and 5000 ppm. This indicates that a high mass accuracy and resolution are essential for confident metabolite annotation.

Our framework is directly applicable to other types of HR imaging MS with FTICR or Orbitrap analyzers (MALDI-, DESI-, SIMS-, IR-MALDESI-, etc.; with proper adducts to be selected for each source) and other types of samples (plant tissue, cell culture, agar plate, etc.) for which a proper metabolite database can be selected.

Accession Codes

MTBLS313: imaging mass spectrometry data from mouse and rat brain samples, MTBLS317: simulated imaging mass spectrometry data and MTBLS378: LC-MS/MS data from mouse brain samples. Dorrestein (UCSD) and Peter Maass (University of Bremen) for providing a stimulating environment as well as for discussions on mass spectrometry and image analysis during the years of this work. S5 for breakdown about the annotations), f) overlaps between adducts of the annotations, g) examples of molecular ion images for annotations validated using LC-MS/MS (cf. Supplementary Note 2, Figures S11 andS12; Supplementary Note 3), as well as FDR curves illustrating h) superiority of MSM as compared to individual measures for a2s3, +K (see Supplementary Note 1, Figure S8 for other datasets and adducts), and g) decrease of number of annotations when simulating lower mass resolution/accuracy for a1s3, +K (cf. Supplementary Note 1, Figure S9).

Tables N/A

Online Methods

Imaging mass spectrometry 1.1 Imaging mass spectrometry data from mouse brain samples

Samples

Two female adult wild-type C57 mice (a1, a2) were obtained from Inserm U1085 -Irset Research Institute (University of Rennes1, France). Animals were age 60 days and were reared under ad-lib conditions. Care and handling of all animals complied with EU directive 2010/63/EU on the protection of animals used for scientific purposes. The whole brain was excised from each animal immediately post-mortem and are loosely wrapped rapidly in an aluminum foil to preserve their morphology and snap-frozen in liquid nitrogen. Frozen tissues were stored at -80 °C until use to avoid degradation.

Sample preparation

For each animal, five coronal 12 µm-thick brain sections were collected on a cryomicrotome CM3050S (Leica, Wetzlar, Germany) as follows. Three consecutive sections were acquired at the Bregma distance of 1.42 mm (sections s1, s2, s3) and two further sections were acquired at the Bregma distances of -1.46 and -3.88 mm (datasets s4 and s5). The sections were thaw-mounted onto indium tin oxide (ITO) coated glass slides (Bruker Daltonics, Bremen, Germany) and immediately desiccated. Alpha-Cyano-4-hydroxycinnamic acid (HCCA) MALDI-matrix was applied using the ImagePrep matrix deposition device (Bruker Daltonics). The method for matrix deposition was set as described: after an initialization step consisting in between 10-15 cycles with a spray power at 15%, an incubation time of 15 s and a drying time of 65 s, 3 cycles were performed under sensor control with a final voltage difference at 0.07 V, a spray power at 25%, an incubation time of 30 s and a drying time under sensor control at 20% and a safe dry of 10 s; then 6 cycles were performed under sensor control with a final voltage difference at 0.07 V, a spray power at 25%, an incubation time of 30 s and a drying time under sensor control at 20% and a safe dry of 15 s; 9 cycles were performed under sensor control with a final voltage difference at 0.2 V, a spray power at 15%, an incubation time of 30 s and a drying time under sensor control at 20% and a safe dry of 50 s; finally 20 cycles were performed under sensor control with a final voltage difference at 0.6 V (+/-0.5 V), a spray power at 25%, an incubation time of 30 s and a drying time under sensor control at 40% and a safe dry of 30 s.

Imaging mass spectrometry

For MALDI-MS measurements the prepared slides were mounted into a slide adapter (Bruker Daltonics) and loaded into the dual source of a 7T FTICR mass spectrometer solariX XR (Bruker Daltonics) equipped with a Paracell, at the resolving power R=130000 at m/z 400. The x-y raster width was set to 50µm using smartbeam II laser optics with the laser focus setting 'small' (20-30 µm). For a pixel, a spectrum was accumulated from 10 laser shots. The laser was running at 1000 Hz and the ions were accumulated externally (hexapole) before being transferred into the ICR cell for a single scan. For animal a1, each spectrum was internally calibrated by one-point correction using a known phospholipid with the ion C 42 H 82 NO 8 P+K + , at the m/z 798.540963. For animal a2, every spectrum was internally calibrated by several point correction using: matrix cluster of HCCA

Signal processing

Centroid data was exported into the imzML format by using the SCiLS Lab software, version 2016a (SCiLS, Bremen, Germany). Ion images were generated with the tolerance ±2.5 ppm. A hot-spot removal was performed for each image independently by setting the value of 1% highest-intensity pixels to the value of the 99'th percentile followed by an edgepreserving denoising using a median 3x3-window filter.

Data availability

The imaging mass spectrometry data is publicly available at the MetaboLights repository under the accession numbers MTBLS313.

Simulated imaging mass spectrometry data

An imaging MS dataset was simulated that contained 300 sum formulas from the HMDB metabolite database, version 2.5, and 300 randomly generated formulas not contained in HMDB. To each sum formula, either +H, +Na, or +K adduct was randomly assigned. Random sum formulas were generated such that the probability distributions of the number of CHNOPS atoms, the C-H ratio, and the C-O ratio are the same as all formulas from HMDB. Isotope patterns were generated for each formula at a resolving power of R=140000 at m/z 400. Each isotope pattern was multiplied by a random intensity in the range [0.2-1.0]. The patterns were assigned to one of two partially overlapping square regions: one with sum formulas from HMDB, the other with sum formulas not from HMDB. Additionally 700 peaks at randomly selected m/z-values were added independently to each spectrum so that a spectrum inside one of the squares would have 3500 ± 127 peaks. The resulted line spectra were then convolved with a Gaussian function with the sigma equal to 0.015.

Data availability

The simulated imaging mass spectrometry data is publicly available at the MetaboLights repository under the accession numbers MTBLS317.

Metabolite-Signal Match score

Individual measures used in the Metabolite-Signal Match (MSM) score were defined based on the ion images generated from each peak within the isotope pattern for a particular sum formula and adduct. Isotope envelopes were predicted for an ion (sum formula plus adduct) at the mass resolution of the dataset and peak centroids were detected.

Measure of spatial chaos

The measure of spatial chaos (Algorithm OM1) quantifies whether the principal ion image is informative (structured) or non-informative (noise). This approach was previously proposed by us for image-based peak picking [START_REF] Alexandrov | Testing for presence of known and unknown molecules in imaging mass spectrometry[END_REF] but here we developed an improved measure based on the concept of level sets earlier applied for image segmentation [START_REF] Vese | A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model[END_REF] . For an ion image, its range of intensities is split into a number of levels. For each level, a level set is calculated as an 0-or-1-valued indicator set having 1-values for pixels with intensities above the level. Then, the number of closed 1-valued objects (connected areas of 1-valued pixels) in the produced level set is computed. Images with structure tend to exhibit a small number of objects that simply shrink in size as the threshold increases whilst images with a noisy distribution produce a great number of objects as the pixels above the threshold level are randomly spatially distributed (see Figure S3a). The algorithm was inspired by a concept of computational topology called persistent homology [START_REF] Edelsbrunner | Persistent homology-a survey[END_REF] . The proposed measure of spatial chaos returns a value between zero and one which is high for spatially-structured images and low for noisy images. uses the label function from scipy 25 with 4-connectivity and returns the number of disconnected objects in an image.

Input

The computational complexity of the level-sets algorithm is

where is the number of pixels. The parameters controls the smoothness of the curve seen in Figure S3b and above a certain granularity the value of stabilises to a constant for a particular image. A value of was found to be sufficient to provide stable results for both the test images from 2 and random noise (data not shown).

Spatial isotope measure

The spatial isotope measure quantifies the spatial similarity between the ion images of isotopic peaks, composing a signal for a sum formula. It is calculated as a weighted average linear correlation between the ion image from the most intense isotope peak (

) and all others ( ) where is the number of theoretically predicted isotope peak centroids for a particular sum formula and adduct with an intensity greater than 1% of the principal (largest) peak. Each image is weighted by the relative abundance of the theoretical isotope peak height . Negative values are set to zero so the spatial isotope measure returns a value between zero and one; the higher values imply a better match.

Equation OM1. Spatial isotope measure quantifying the spatial similarity of each isotope peak to the principal peak where returns Pearson's correlation coefficient and where

is a vector of intensities from ion image of the 'th isotope peak.

Spectral isotope measure

The spectral isotope measure quantifies the spectral similarity between a predicted isotope pattern and measured spatial intensities. It is calculated as the average difference between normalised predicted isotope ratios and normalised measured intensities, reported so that larger values imply a better match.

Equation OM2. Spectral isotope measure quantifying the spectral similarity between a predicted isotope pattern and the measured intensities of a signal.

In Equation 2, is a vector containing the mean image intensity from the ion images for the pixels in with non-zero intensity values and , where . This can be considered as projecting both theoretical and empirical isotope patterns onto a sphere and then calculating one minus the average coordinate difference.

Metabolite-Signal Match score

The Metabolite-Signal Match (MSM) score quantifies the similarity between the theoretical signal of a sum formula and its measured counterpart, with the higher value corresponding to higher similarity. It is calculated according to Equation OM3, as a product of the individual measures: measure of spatial chaos, spatial isotope measure and spectral isotope measure). This puts an equal weighting on all measures whilst penalizing any annotation that gets low value for any of the measures.

Equation OM3. Metabolite-Signal Match (MSM) score quantifying similarity between a theoretical signal of a sum formula and its counterpart sampled from the dataset.

Section OM3. False Discovery Rate-controlled metabolite annotation

Molecular annotation

First, we consider all unique sum formulas from a metabolite database of interest. We used the Human Metabolome Database (HMDB), v. 2.5, considering only 7708 carbon-containing sum formulas [START_REF] Wishart | HMDB 3.0--The Human Metabolome Database in 2013[END_REF] . Then, we select a list of potential ion adducts. The adducts +H, +Na and +K were used as the adducts commonly detected during tissue MALDI imaging MS in the positive mode 27 . Then, we perform molecular annotation of an imaging MS dataset for each ion (combination of a sum formula and an adduct) independently as described in Algorithm OM2. Note that in this algorithm the MSM threshold needs to be specified; for the updated algorithm selecting the MSM threshold in an FDR-controlled way, please see Algorithm OM3.

Input

Calculation of the False Discovery Rate

To calculate the False Discovery Rate among the molecular annotations provided using Algorithm OM2 with an MSM threshold , we developed a target-decoy approach similar to (Elias and Gygi 2007) 28 . The innovative part of his development is in applying the targetdecoy approach in the spatial metabolomics context by defining a decoy set appropriate for metabolomics.

A target set was defined as a set of molecular ions for the sum formulas from a metabolite database (e.g. HMBD), with a given ion adduct type (e.g. +H, +Na, +K). A decoy search was defined as a set of implausible ions for the same sum formulas but with implausible ion adduct types. For each sum formula, an implausible elemental adduct is randomly chosen from the CIAAW 2009 list of isotopic compositions of the elements [START_REF] Berglund | Isotopic compositions of the elements 2009 (IUPAC Technical Report)[END_REF] excluding the plausible adducts, namely from He, Li, Be, B, C, N, O, F, Ne, Mg, Al, Si, P, S, Cl, Ar, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, As, Se, Br, Kr, Rb, Sr, Y, Zr, Nb, Mo, Ru, Rh, Pd, Ag, Cd, In, Sn, Sb, Te, I, Xe, Cs, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Ir, Th, Pt, Pu, Os, Yb, Lu, Bi, Pb, Re, Tl, Tm, U, W, Au, Er, Hf, Hg, Ta. Once the target and decoy sets are defined, the MSM scores are calculated for all target and decoy ions.

The MSM cutoff (

) is a key parameter of the molecular annotation. Setting the MSM cutoff changes the number of molecular annotations made. For any MSM cutoff, we define positives as the ions with MSM scores above the cutoff and negatives as the ions with MSM scores below the cutoff. We define as positive hits from the decoy. Since any decoy ion is constructed to be implausible, all decoy ions detected as positive are false positives. Then, we estimate FDR with FDR' according to Equation OM4.

Equation OM4. Definition of FDR and the proposed estimate of FDR (FDR'). FP, TP are False Positive and respectively True Positive,

and are the numbers of annotations from the target and decoy sets for the MSM cutoff .

Similar to the approach of FDR calculation in genome-wide studies proposed by (Storey & Tibshirani, 2003) [START_REF] Storey | Statistical significance for genomewide studies[END_REF] and picked up later in proteomics, Equation OM4 proposes an approximation of the true FDR defined as . This approach relies on having a high similarity between false-positives in the target set and the decoy set. The decoy set must be the same size as the target set and share the same statistical distributions as used by the measures used in the annotation. If these assumptions are satisfied then the number of false positives from the decoy ( ) approximates the number of false positives from the target ( ) while the denominator ( ) is equal between FDR and FDR'.

As the decoy generation is a randomized process, with one decoy search formed by a sampling of implausible adducts from all possible implausible adducts, FDR calculation is a repeated sampling process. We propose to repeat it (20 times for the presented results) and calculate the median of the observed FDR values. We favored median over mean for its general robustness to outliers and for providing integer values that can be translated into the numbers of annotations.

FDR-controlled molecular annotation

The term FDR-controlled molecular annotation means that parameters of molecular annotation are optimized so that the set of provided annotations has a desired level of FDR. This is the most widely used approach in proteomics for choosing parameters of molecular identification [START_REF] Choi | Significance analysis of spectral count data in label-free shotgun proteomics[END_REF] . We employed this approach to develop in Algorithm OM3 for selecting a key parameter of the molecular annotation, the MSM cutoff . This was performed similarly to (Zhang et al., 2012) [START_REF] Zhang | De Novo Sequencing Assisted Database Search for Sensitive and Accurate Peptide Identification[END_REF] by simultaneously sorting the MSM values for the target and decoy ions, decreasing the MSM cutoff thus one-by-one increasing the number of target ions annotated, recalculating the FDR after every new ion is annotated, and selecting the maximal number of annotations that provide FDR below the desired value (see Figure 1 in the main text). This process is repeated 20 times with the decoy adducts every time randomly sampled from the set of all considered implausible adducts and an observed recorded. After repetitions, the final MSM cutoff value is set at the median of the observed values. The final set of molecular annotations is a set of target ions with the MSM scores above the median cutoff value.

Input

LC-MS/MS validation of annotations 5.1 Samples

Mouse brain sample

One female adult wild-type C57 mouse age 10 weeks was obtained from the European Molecular Biology Laboratory animal resource (EMBL-LAR, Heidelberg, Germany). The animal was reared under ad-lib conditions within the specific pathogen free facility. Care and handling of the animal complied with EU directive 2010/63/EU on the protection of animals used for scientific purposes. The whole brain was excised from each animal immediately post-mortem and rapidly cryo-frozen in CO 2 cooled isopentane. Tissue was stored at -80 °C until use.

Authentic lipid standards and chemicals

All lipid standards used for validation of annotations were purchased from Sigma Chemicals (Sigma-Aldrich Co., St. Louis, MO) and Avanti Polar Lipids (Alabaster, LA, USA). The LC-MS grade buffers and other reagents were purchased from Sigma Chemical. All mass spectrometry grade solvents and MiliQ grade water was used throughout the analysis.

Sample preparation

20 mg of brain tissue was extracted using Bligh and Dyer extraction method [START_REF] Bligh | A rapid method of total lipid extraction and purification[END_REF] . The dried extract was reconstituted with 100 µL of methanol and isopropanol (1:1) and 10µL of this sample solution was injected LC-MS system for each run. Lipid standards were prepared in same solvent with concentration of 100 ng/mL each.

LC-MS/MS methods

The separation of lipids was carried out on Agilent 1260 liquid chromatography (LC) system with Ascentis® Express C 18 column (100 x 2.1 mm; 2.7uM) and detected with high resolution mass spectrometry (Q Exactive Plus MS, Thermo Scientific).

Three LC-MS/MS methods were used: Positive: ESI positive mode using 'buffer 1'. Negative 1: ESI negative mode method using 'buffer 1'. Negative 2: ESI negative mode method used 'buffer 2'. LC was run with flow rate of 0.25 ml/min with solvent A consisted of acetonitrile-water (6:4) and solvent B of isopropyl alcohol-acetonitrile (9:1), which are buffered with either 10 mM ammonium formate and 0.1% formic acid (buffer 1) or 10 mM ammonium acetate (buffer 2). MS parameters (Tune ,Thermo Scientific) were set as: spray voltage of 4 kV, sheath gas 30 and auxiliary gas 10 units, S-Lens 65 eV, capillary temperature 280 o C and vaporisation temperature of auxiliary gas was 280 o C.

LC-MS/MS validation strategy

LC-MS/MS validation of lipid annotations was performed differently for annotations when lipid standards are available and for other annotations. When lipid standards were available, LC-MS/MS information in particular the LC retention time (RT), MS and MS/MS (MS2) was used to compare the data from a standard with the data from a sample (both acquired using exactly the same LC-MS method and precursor selection range). First, extracted ion chromatograms (XICs) were evaluated for all possible adducts to confirm the presence of the ion of the sum formula obtained from imaging data. As for the tolerance value for XICs: for data with standards we used the 5 ppm; for data with no standards we selected the best fitting tolerance value from 2, 3, and 5 ppm. We considered possible adducts for each metabolite (+H, +Na, +NH4 for the 'Positive' method; -H, +FA-H for the 'Negative' methods, FA stands for the formic acid) and selected the best matching adduct as follows. The precursor delta m/z was calculated for the sample both in MS1 and MS/MS data. The matching MS/MS spectrum was searched within the elution profile and manually interpreted for fragments corresponding to head-group and fatty acid side chains. Only precursor and fragments with accuracy <6 ppm were considered for structural interpretation to identify possible lipid species. The lipid class was confirmed by the presence of head-group fragment or its neutral loss (e.g. MS/MS fragment with m/z 184.0735 corresponds to the phosphocholine head-group). Since lipids from the classes of phosphatidylcholines (PC) and sphingomyelins (SM) have the same head-group (m/z 184.0735), given a sum formula, we searched in HMDB and SwissLipids to rule out a possibility of the sum formula to correspond to a lipid from another class other than annotated by our framework. Further to confirm the fatty acid side chains, the 'Negative' LC-MS methods were used (e.g. fatty acid fragments for phosphocholines were obtained after fragmentation of formate ion precursors using the 'Negative' LC-MS method). The collision energy was selected as best representing the precursor and the expected fragments. When standards were available, the RT, precursor m/z and MS/MS fragments corresponding to head-groups and fatty acid chains from the sample were matched with spectra from the corresponding standard. When standards were not available the fragments were manually interpreted. Finally, structural annotation of the matching peaks in the MS/MS spectra was performed with the help of the HighChem MassFrontier software (Thermo Scientific). The MS, MS/MS and RT (for standards) data is presented in Supplementary Note 3 and summarized in Table S5.

Figures

  Figures

Figure 1 .

 1 Figure 1. The proposed framework for metabolite annotation for HR imaging MS;

Figure 2 .

 2 Figure 2. Evaluation of the proposed framework: a) intensities of highest four peaks in the

  [C 20 H 14 N 2 O 6 +H + , m/z 379.092462] if present and known phospholipids present in the mouse brain [C 40 H 80 NO 8 P+H + , m/z 734.569432] and [C 42 H 82 NO 8 P+K + , m/z 798.540963]. Data was acquired for the mass range 100 < m/z < 1200 followed by a single zero filling and a sinapodization. Online feature reduction was performed in the ftmsControl software, version 2.1.0 (Bruker Daltonics) to return only the peak centroids and intensities.

:

  Real-valued image , number of levels

	6.
	7.
	8. return
	Algorithm OM1. The level-sets based algorithm for calculating the measure of spatial
	chaos of an ion image.	is a hole-filling operation to 'fill in' isolated missing pixels that
	can happen in HR imaging MS (and to avoid overestimating the number of objects). It
	consists of a sequence of morphological operation:	with
	structuring elements	24 .
	Output: measure of spatial chaos
	Algorithm:
	// scale image intensity range to [0 1]
	1.
	// main part
	2. For n in	:
	// threshold image at a current level
	3.
	4.
	// fill single-pixel holes
	5.
	// count separate objects with 4-connectivity

:

  Metabolite sum formula, adduct, charge, resolving power of the spectra, imaging MS dataset, MSM threshold

	Output: Decision whether the ion	is present in the dataset
	Algorithm:
	// Predict isotopic patterns
	1. Predict the isotope envelope* for	at the resolving
	power
	2. Detect centroids of the isotope envelope*, exact m/z's and relative intensities (	)
	// Generate and score signals from the dataset
	3. For	in	:
	4.	Generate an ion image	for the i'th isotopic peak at m/z
	5. Calculate	from	and	from	and	according to Algorithm
	1,
	Equation OM1, and Equation OM2, respectively
	6. Calculate the	score according to Equation OM3
	// Annotate the data
	7. If		:
	8.	the ion				is annotated as being present in the dataset
	Algorithm OM2. MSM-based molecular annotation determining whether a metabolite ion
	is present in an imaging MS dataset.

:

  Metabolite database, resolving power of the mass spectrometer used, imaging MS dataset, ion charge, target adduct, decoy adducts, desired FDR level FDR-controlled molecular annotation that screens for metabolite ions present in an imaging MS dataset, with the desired FDR level.

	Algorithm OM3.
				, number
	of decoy samplings
	Output: A set of molecular annotations (ions from the metabolite database detected as
	present in the dataset)
	Algorithm:
	// Predict and score all metabolite signals
	1. For	in	:
	2.
	3.	Calculate	according to Algorithm
	4.			, where decoy adduct is
		randomly chosen from the list of decoy adducts
	5.	Calculate	according to Algorithm OM2.(1-3)
		// Calculate the MSM cutoff corresponding to the desired FDR level
	6. Form a combined vector of	values
		// Find the maximal number of annotations providing FDR below
	7. Sort in descending order.
	8.
	9. While	:
	10.
	11.
	12.	Calculate	according to Equation OM4
	13.
	14.
	15. Repeat steps 1-11 according to the number of decoy samplings,
	16.
		// Perform the MSM-based molecular annotation with the calculated cutoff
	17. For	in	:
		a. If		then add	into the list of molecular
		annotations

Acknowledgements

We thank Olga Vitek (Northeastern University), Alexander Makarov (ThermoFisher Scientific) and Mikhail Savitski (EMBL) for discussions on FDR and Dmitry Feichtner-Kozlov (University of Bremen) for discussions on computational topology. We acknowledge funding from the European Union's Horizon2020 and FP7 programmes under the grant agreements No. 634402 (AP, RL, AT, VK, SN, CP, TA), 305259 (IC, RL, CP), and from the Russian Government Program of Competitive Growth of Kazan Federal University (SN). We thank EMBL Core Facilities for instrumentation for LC-MS/MS analysis. TA thanks Pieter

Data Availability Statement

The data is publicly available at the MetaboLights repository under the following accession numbers: MTBLS313: imaging mass spectrometry data from mouse and rat brain samples, MTBLS378: LC-MS/MS data from mouse brain samples, and MTBLS317: simulated imaging mass spectrometry data.

Code availability

The reference implementation of the developed framework is freely available at https://github.com/alexandrovteam/pySM as open source under the permissive license Apache 2.0.

Code availability

The reference implementation of the developed framework is freely available at https://github.com/alexandrovteam/pySM as open source under the permissive license Apache 2.0. Data was acquired in full scan mode in mass range of 150-900 m/z (resolving power R=70000) and data dependent tandem mass spectra (MS/MS) were obtained for all precursors from an inclusion list (resolving power R=35000). Tandem mass spectra (MS/MS) were acquired using higher energy collisional dissociation (HCD) with normalized collision energies of 10, 20 and 30 units at the mass. The inclusion list was composed of all annotations provided from imaging MS analysis and detected in all three serial sections (s1, s2, s3 at the Bregma 1.42) for either of two animals. We considered adducts relevant for LC-MS (+H, +NH4, +Na for the Positive method; -H, -H+HCOOH for the Negative methods).

Data availability

The LC-MS/MS data from mouse brain samples is publicly available at the MetaboLights repository under the accession numbers MTBLS378.

Author Contributions

AP and TA conceived the study, AP, IC, DF, AT, VK implemented the algorithms, RL, JF, CP, MB provided imaging data, AP and TA analyzed imaging data, PP collected LC-MS/MS data, PP and TA performed LC-MS/MS validation, AP and TA wrote manuscript, with feedback from all other coauthors, TA coordinated the project.

Competing Financial Interest Statements

Theodore Alexandrov is the scientific director and a shareholder of SCiLS GmbH, a company providing software for imaging mass spectrometry. During the work presented in the paper, Michael Becker was an employee of Bruker Daltonik GmbH, a company providing instrumentation and software for imaging mass spectrometry.


Keywords:

BISON

Abstract. Remains of Bison (Eobison)


Laurence Husson
email: laurence.husson@univ-provence.fr

、 必須向外謀生的「推力」進行分析之外

, 我們也不能

忽略出於政治因素才產生的移民制度 , 特別是在上述三個亞洲島嶼國家

Is a Unique Culture of Labour Migration Emerging in the Island Nations of Asia?

Keywords: female migrant workers, Indonesia, Philippines, Sri Lanka

In the space of three decades, three countries, the Philippines, Indonesia and Sri Lanka have become the main exporters of labor on a worldwide scale.

Are island nations, such as the two archipelagos of the Philippines, Indonesia and the island of Sri Lanka, predisposed to the current large exodus of female migrant workers? Another record shared by these three countries: the very high percentage of women making up these migrant workers. This paper will analyze the principal factors of geography, population and the international labour market that explain this massive exportation of female migrant workers together with the state policies that are actively encouraging female migration.

Beyond the determining geographical factor and the need to leave an overpopulated land to earn a living, we should indeed take into consideration the presence of a political will that contributed to the formation of a system of migration which is possibly particular to the island nations of Asia.

TJSEAS 113

The emergence of a globalised labour market has encouraged the free movement of people. Instead of weakening the links between the place of origin and the place of living and working, migratory movements reinforce connections. Real networks are created that organize the way people relocate. These networks also contribute to maintaining the collective identity links beyond national borders. Considered from the identity point of view, labour-based migrations illustrate the delicate connection between local and global contexts and show how individuals practice their dual relationship between their country of origin and the country where they find employment.

Migrations due to work, voluntary or forced, supervised or spontaneous, have a long tradition in Asia. After the abolition of slavery in the late 1800s, European colonial powers introduced the labor contracts that led to the extensive Chinese and Indian diasporas.

The vast continent of Asia comprises 60% of the world's population and two-thirds of the world's workforce. This labour market is expected to remain a very mobile zone for a long time [START_REF] Hugo | The Demographic Underpinnings of Current and Future International Migration in Asia[END_REF]. The two archipelagos of Indonesia and the Philippines are at the crossroads of the trade routes between China and India. It appears that this geographic region, made of archipelagos, peninsulas and straits is an eastern equivalent of the "Mediterranean sea" that encourages mobility and flows in all kinds of exchanges.

In the space of three decades, the Philippines, Indonesia and Sri Lanka, have become the world's leading exporters of labour. Another feature that these two archipelagos and one island nation share is the record high percentage of women TJSEAS 114 making up these migrant workers. These two striking facts have been the catalyst for this paper in which we will analyze the principal factors that explain this massive exportation of female migrant workers.

Hania [START_REF] Zlotnik | The Global Dimensions of Female Migration[END_REF] estimates that women represent 47% of migrants in Asia.

However, in Sri Lanka, the Philippines and Indonesia, the proportion is higher than 70%. Are the islands of Asia predisposed to such a large exodus? Why are so many women leaving for foreign countries?

Beyond the determining geographical factors and the need to leave overpopulated islands to earn a living, state policies have played a determining role in the gender pattern of migration and have contributed to the formation of a system of labour migration which is possibly unique to Asia. The Philippines and Indonesia form the primary focus of this paper. The consideration of Sri Lankan worker migration is used as a comparison.

A Significant Recent Development

The rise of Asian migrations has followed global trends in migration. In 1965 the world accounted for 75 million international migrants. Twenty years later it was 105 million, and in 2000 it was 175 million. From the 1980s, the growth rate of the world population declined to 1.7% per year while international migration rose considerably to 2.59% per year (IOM 2003).

It was not until 1973, at the time of the extreme petroleum price escalations, that the large scale immigration of workers to the Gulf States began, firstly from Southern Asia and then from South-East Asia. The oil-rich states of the Arabian Peninsula 2000,2004).

The Gulf War (1990War ( -1991) ) as well as the Asian financial crisis of 1997 provoked a massive return, albeit temporary, of migrant workers. Since then migrant flows have resumed. Maruja Asis noticed that "unlike male migration, the demand for female migration is more constant and resilient during economic swings. The 1977 1997 crisis in Asia was instructive in this regard. While the demand for migrant workers in the construction and manufacturing sectors declined, no such change was observed for domestic workers" [START_REF] Asis | When Men and Women Migrate: Comparing Gendered Migration in Asia[END_REF]).

However, available statistical figures seem to be contradictory and are therefore difficult to analyze with confidence. For example, [START_REF] Stalker | Workers without Frontiers -The Impact of Globalization on International Migration[END_REF] stated that in 1997 there were up to 6.5 million Asian migrant workers in Japan, South Korea, Malaysia, Singapore, Thailand, Hong Kong and Taiwan. While, [START_REF] Huguet | International Migration and Development: Opportunities and Challenges for Poverty Reduction[END_REF] estimated that at the end of 2000 approximately 5.5 million foreign workers were living in a host East and Southeast Asian country. The misleading implication from comparing these two estimates is that the number of Asian migrants has decreased during those three years.

Whereas, a more careful consideration of these estimates suggests that the collection and analyses of migration statistics in this part of the world are not yet sufficiently reliable due to movement complexities. What may be discerned is that the global circulation of information, capital, ideas and labor and wider access to air travel has increased mobility and overcome the problem of large geographical distances. During this time, the main destination for female Asian migrants shifted from the Middle East TJSEAS 117 to the other Asian countries whose booming economies needed additional migrant workers to fill labor shortages.

A Growing Feminization

Since the 1980s, the massive participation of women in the international labour market has been a phenomenon without precedent in the history of human migrations.

While most researchers agree that global restructuring increasingly forces a larger number of women in developing countries to participate in the international labour market, Nana [START_REF] Oishi | Women in Motion. Globalization, State Policies and Labor Migration in Asia[END_REF] demonstrated the need to investigate the differential impacts of globalization, state policies, individual autonomy and social factors.

In the past migration flows, women have been the wives, mothers, daughters or sisters of male migrants. In contrast, since the 1990s women, with or without work contracts, have become active participants in the international labour market, and not just to join or accompany a male migrant. Since this period, these female migrants have became fully integrated into the host country's job market. This phenomenon is referred as "the feminization of migration".

In addition to the feminisation of migration, the other significant change has been a new level of awareness on the part of migration scholars and policy-makers as to the significance of female migration, the role of gender in shaping migratory processes and, most importantly, the increasingly important role of women as remittance senders (Instraw 2007). The trend seems now to be irreversible. The inclusion of the gender perspective in the analysis of migration has illuminated the new geographic mobility of women. The development in recent years of feminists studies has allowed female migrations to be understood as a different social phenomenon to the mobility TJSEAS 118 of men. Applying a gender lens to migration patterns can help identify ways to enhance the positive aspects of migration and to reduce the negative ones.

In 1990, the United Nations estimated that the total number of migrants living outside their native countries at 57 million, that is to say, 48% on the global scale.

According to an estimate by the ILO (International Labour Organisation) in 1996, at least 1.5 million female Asian workers were employed outside their country of origin.

Each year, almost 800,000 Asian women leave their own country for an employment under contract in the UAE (United Arab Emirates), Singapore, Hong Kong, Taiwan, Korea or Malaysia, where they will reside for a minimum of two years [START_REF] Lim | International Labor Migration of Asian Women: Distinctive Characteristics and Policy Concerns[END_REF]. The migrations of female workers henceforth, constitute the majority of the migrant work-flow under contract. Indeed, the Philippines and Indonesia export the largest number of migrant workers in Southeast Asia and are also the world's top exporters of female workers. The females of these two archipelagos are far more numerous than their male counterparts-as women represent 60% to 70% of workers sent abroad by these two countries. Sri Lanka created an office for foreign employment (SLBFE) with the express objective to promote and develop their export of workers, and especially female workers. . The number of Sri Lankan women leaving under contract to work abroad, in particular to Saudi Arabia, United Arab Emirates and Kuwait, grew from 9,000 in 1988 to 42,000 in 199442,000 in and to 115,000 in 199642,000 in (UNO 2003)). Even though Sri Lanka started sending its domestic assistants to the Gulf States later than Bangladesh, Pakistan or India, it remains the only country to continue doing so. The proportion is one male migrant to three female migrants, of which more than 60% work as domestics almost exclusively in one of the seven member states of the Gulf Cooperation Council. Besides the numerical importance of these flows and their visibility, another feature of these Asian female migrations is their disproportionate concentration in a very limited number of jobs.

It seems that female labor is mainly related to medical care, private domestic services and commercial sexual services. The categories of typical female employment returns to the stereotype roles of women as maids, waitresses, prostitutes and nurses [START_REF] Chin | Service and Servitude: Foreign Female Domestic Workers and the Mlaysian Modernity Project[END_REF][START_REF] Parrenas | Servants of Globalization: Women, Migration and Domestic Work[END_REF]). In the eyes of employers, Asian women are traditionally perceived to be discrete, subservient, docile, gentle, ready to please and serve, particularly suited to these subordinate employments as carers, nurses, domestic servants and as sex workers. The female migrants are forced into a limited number of trades due to a clear segregation of the sexes in the international labor market. They are concentrated in the service sector, domestic house-work, and a large number of entertainment trades that are a thinly disguised form of prostitution.

We will now compare the female migrations of Indonesia and the Philippines and consider the initiatives introduced in the Phillipines and Sri Lanka to protect vulnerable female migrant workers who emigrate to the Arabian Peninsula and Eastern Asia.

With 7.8 million migrant workers, the Philippines is an example of how to improve and defend the rights of migrant workers. Indonesia, has the largest total number of migrant workers and the majority of these are women who are recruited as maids. Indonesia has tried to protect them by providing training and by fighting against the non-official recruitment agencies. Repeated press articles on the vulnerability of foreign workers, where migrant workers and locals are rarely treated on an equal footing means that the states concerned can no longer remain insensitive to this problem.

We will use the following abbreviations: TKW (tenaga kerja wanita) in Indonesia to designate the female migrants workers and OFW (Overseas Filipino Workers) for the Philippines.

Over representation of female Asian migrants in the international labor market

The reasons for the strong participation of Asian women in the international labor flow are numerous and different in order: psychological, religious, economic, and political. In general, the offer of employment for female workers was as a result of supply and demand. These women were able to leave their families at short notice and for a set time in order to earn income at a time when the demand for male workers had diminished in the Gulf States. They profited from a demand for female workers.

This was even easier as the jobs for women generally did not need a diploma or qualifications and appeared very attractive due to the big differences in wages and salaries between the countries of departure and the countries of arrival.

In South East Asia, women have a certain level of freedom of movement and autonomy in decision making, and are used to working away from home. In several ethnic groups in Indonesia, women have traditionally had a significant role in the generation of household income, through productive work both within and outside the household (Williams 1990: 50). In 2005 the ILO (2006: 13) stated that up to 53% of women in Indonesia participate in the work force compared to 87.1% of men.

TJSEAS 122

Whereas in the Philippines, the proportions were 56.7% for women and 70.7% for men. In the families that need supplementary income, the women know how to cope with bringing money home, this would oviously favor emigration. However, many Islamic countries, including Pakistan and Bangladesh, have forbidden sending female workers overseas, as it was considered that young women travelling without a male escort outside their homes was against the teachings of the Koran. India has also put a brake on the export of female workers following too many denunciations by the national press.

To explain this massive feminine participation of women in migrational work, it is tempting to invoke traditional Asian values and the notion of family responsibility.

Family responsibility is a foundational concept and is not a question of filial devotion.

The sending of a woman abroad to earn money is related to the idea that she will remain committed to her family and that she will willingly sacrifice her own wellbeing and send all her savings home. A man in the same position, may be more inclined to play, drink and spend his savings. Overall, men remit more than women because they earn more, though women tend to remit a larger proportion of their earnings. This study carried out in Thailand confirms that despite their salaries being lower than men, the female migrants who work abroad to help their families managed to save more and sent most of their savings to their families [START_REF] Osaki | Economic Interactions of Migrants and their Households of Origin: Are Women More Reliable Supporters?[END_REF]. Women, especially if they are mothers, do not leave home easily and conversely the families certainly preferred to see the men go abroad rather than the women. In general, an extended family always found it more difficult to replace a mother than a father. She would often carry out a great number of tasks and is hard to replace, especially when it concerns the needs of very young children and elderly parents. But there is little TJSEAS 123 choice when the only employment offered is for females. The woman, whether she is a mother, daughter or sister, accepts temporary emigration and the family left behind will have to deal with her staying abroad.

Another possible factor, that needs to be verified with specific studies, is the incidence of bad conjugal relationships preceding female emigration. The researchers Gunatillake and Perera (Gunatillake and Perera 1995: 131) showed that in Sri Lanka, female worker migration is often a form of disguised divorce, in a society where divorce is still negatively perceived. The divorce is then not officially announced, but the emigration of the wife marks her economic independence and their physical separation as a couple. In Indonesia, while married women constitute the largest proportion of migrants, divorced women, single mothers and widows are over represented. It is clear that the departure is a solution to survive, a way of forgetting or escaping a situation of failure.

Women can also be "trapped" into migration. Low wages, financial difficulties, irresponsible spending, spousal infidelity, estrangement from children, and many others personal factors at home, may compel women to stay in, or return to the same country, or find another labor contract elswhere.

It is necessary to add that working abroad has become more commonplace and less harrowing as the cost of transport and overseas communications via phone, Internet, MSN, Skype have been considerably reduced. With quicker and cheaper exchanges, the effective distances have been shortened and the social-emotional separation from family has became more acceptable by the women. For example, in certain Javanese villages, the migration of women is so frequent, so usual, that they have become normal, and as one might say, they constitute a standard.

An additional religious factor is often proposed by Indonesians wanting to work in the Arabian Peninsula, especially in Saudi Arabia as it allows them to make the pilgrimage to Mecca at a reduced cost. It has been attested by researchers that Sri Lankan Muslim female workers were able to gain respectability and self-esteem by working in the Arabian peninsula, acquiring material assets, adopting Arab customs in fashion, cooking, interior decoration, and obtaining religious education for them and their relatives (Thangarajah 2003: 144). As pertinent as they are, these reasons alone cannot explain these growing flows.

It is also necessary to take into account the actions of governments in order to augment foreign-exchange revenues and private organizations that promote the export of female labour, and who apply pressure on family and social networks. Authorised Asian female migration would never have known such growth without an initial worker migration industry and the setting up of labour market channels and networks.

The Multiple Channels And Networks

Migrant workers have become commercial objects that constitute a valuable resource. In Asia, the recruitment of foreign workers has become a lucrative activity.

The agencies, whether public or private, legal or illegal cover the financial cost of migration, in order to maximise the profits on each departing candidate. Manolo In the Philippines, there are approximately 2,876 Foreign Employment Agencies, amongst which, 1400 are regarded as reliable (POEA 2004). Because of the competition, these agencies tend to specialize in particular destinations or types of employment.

In Indonesia, 412 employment/placement agencies were listed in 2000 (Cohen 2000). Sri Lanka had 524 licensed recruitment agencies by the end 2002 (plus many more illegal operators) which placed 204,000 workers abroad in that year [START_REF] Abella | Social Issues in the Management of Labour Migration in Asia and the Pacific[END_REF]. These numbers clearly show the commercial and profitable character of worker migrations. A large number of temporary work migrations are thus orchestrated by these paid recruiter agencies. The OIT (International Work Organization 1997) points out "their intervention in 80% of all movements of the Asian work-force to the Arab States, one of the biggest migrant flows in the world". In the same press release, the OIT added "In Indonesia and in the Philippines, the private agencies dominate the organization of migrant workers, placing 60% to 80% of migrants". [START_REF] Kassim | Labour Market Developments and Migration Movements and Policy in Malaysia[END_REF] has pointed out that both the heavy burden of the formal bureaucratic procedure and the high financial costs involved may induce Indonesian migrant workers to look for irregular recruitment channels in order to get a job in Malaysia.

TJSEAS 127

The Journey Of The Migrant Through Legal Or Illegal

Channels

For example, an Indonesian who wants to work in Malaysia has three possible choices. One is to contact a legal placement agency (PJTKI, Perusahaan Jasa Tenega Kerja Indonesia, Office for the Indonesian workers) situated in town and endure a long and costly administrative procedure due to civil servants demanding bribes.

The second way is to go to a local intermediary/recruiter (called locally calo, boss, taikong, mandor or patron/sponsor), who is often a notably rich and respected man, having performed the hadj (pilgrimage to Mecca), and who will serve as intermediary between the candidate and an official agency based in Jakarta. His performance is equally costly but it has the advantage of reassuring the candidate, as the calo is a well-known person.

In the embarcation ports to foreign countries, situated mostly in Sumatra (for example Medan, Tanjung, Pinang, Dumai, Batam, Tanjung Balai, and Pekanbaru) the migrant candidates may go to a third kind of intermediary, unscrupulous ferrymen who try to transport them to Malaysia on the first available boat. In the Indonesian archipelago, generally the official legal procedure is badly perceived and does not prove to be more secure, less expensive or any more effective than the private recruitment agencies. Corruption exists at every stage in the migratory cycle.

Despite these factors, these intermediaries do enable the low-qualified and less well-informed women to go through the procedures to find foreign work. The beneficial services provided by these intermediaries is that they can connect the employee and employer, give training and find board and lodging, supervise their work contracts, organize the trip, lend them money, and organize the return journeys of the migrant.

The negative costs is that these agencies have a tendency to claim excessively high and unjustified fees, commissions and gratuities that force the applicants into debt.

This debt can bring about a relationship of dependence and abuse between the female migrant worker and her recruiter agency. Such abuses are more obvious in the case where the female migrant worker is involved in illegal or Mafia networks.

Outside of these channels of recruitment, the migrant workers forge their own networks through which information circulates, allowing them sometimes to meet the supply and demand. The combination of formal agencies and informal networks end up creating a chain migration.

The Indonesians prove to be more exposed than Philippine workers to extortion and abuse before their departure. This system, along with the tariffs applied by the agents and their high rates of interest mean that the female Indonesians are often in debt for several months of their pay. In 2003, the Indonesian Ministry of Work and Emigration recognized that 80% of the problems, such as falsification of documents and the various extortions undergone by the migrants, take place before departure [START_REF] Dursin | Would be migrants chafe against ban on unskilled labor[END_REF].

The period immediately before departure and immediately upon their return are the critical moments when Indonesian and Sri Lankan female migrants are most at risk of being robbed.

Every day, almost 800 migrants pass through Terminal 3 in Jakarta's airport, while in Sri Lanka around 300 women a day return to their home country. These female migrant groups, who return loaded with packets, presents and money, are targeted by civil servants, servicemen, policemen, porters, and bus-drivers who seek to take their money.

The Philippines And Sri-Lanka Provide Two Female Labour-Export Models For Indonesia?

Massive labor-exporting countries like the Philippines, Indonesia and Sri-Lanka To benefit from the Filipino example, Indonesia should:

-increase the level of general education of its population;

-"clean up" its recruiter system; -train the migrant candidates better, particularly in language;

-diversify the countries of destination.

Following the example of the NGOs that advocate for Filipino women migrants workers, Indonesian NGO's could similarly pressure the Indonesian government to help the migrant labor-force through better national and international coordination, information networking to provide accurate information on all aspects of migration, TJSEAS 131 and more strict regulations for the recruitment industry to help prevent abuses and malpractices.

Towards An Industry And A Culture Of Migration In

Asia

As we have seen, the global trend towards the feminization of migratory flows in Asia and the demand for female migrant workers is likely to increase. This phenomenon is more accentuated in Asia, where the proportion of women in the total number of migrant workers approaches 70%. Even though we cannot speak of a migratory system peculiar to the island nations of Asia, the migratory flows of these three countries present common characteristics which are unique.

In three decades, Indonesia, the Philippines and Sri Lanka constitute the majority of emigration workers in the world.

These nations have put in place policies favoring the emigration of workers to reduce the poverty and unemployment and to increase the foreign currency remittance by migrant workers.

These two archipelagos and the island nation of Sri Lanka share high unemployment rates and chronic under-employment. The respective rates of unemployment in Indonesia and the Philippines remain high at 9.9% and 10.1%, under-employment is considerable. While there remains a large inequality in the wages between men and women, women will continue to comprise the majority of poor workers. .

TJSEAS 132

These countries, via their recruitment agencies, filled an opportune labour-market niche that was vacant by others. The agencies could satisfy the growing demand for domestic personnel, nannies and home nurses. These female employment positions had the advantage for South East Asian migrant women of not requiring any particular qualifications.

Encouraged by the State, in Indonesia, the Philippines, and Sri Lanka, a culture of migration has emerged with the establishment of a solid "migration industry" with a network of agents and intermediaries. Advisors, recruiters, travel agents, trainers, started to work together at all stages of the migration process to find as much labor as possible for the greatest number of foreign employers. The Philippines enjoys a great deal of experience in this field.

Another common characteristic of these three labor exporters resides in the creation of formal and informal migrant networks and channels by which to disseminate important information for future migrant workers. Maruja M. B. Asis (2005: 36) suggests that the nunerical growth in the domestic personnel in various countries, of Philippine origin, partly reflects the "multiplying effect" of the informal migrant information network resulting in parents and friends going to the same destination and working in the same niche markets.

This suggests the possibility of a direct job appointment without having to go through the employment agencies. Moreover, the conditions for migrant workers

Abella ( 2005 )

 2005 has emphasized the role played by private fee-charging job brokers in organizing labour migration in those countries. According to him, "recruitment and placement have been left largely in the hands of TJSEAS 125 commercially-motivated recruitment agencies because few labour-importing states in the region have shown any interest in organizing labour migration on the strength of bilateral labour agreements. As a consequence, over the years, the organization of migration has emerged as a big business in both countries of origin and of employment".Nevertheless, the governments of exporting workforce countries play a major role. Sending migrants workers abroad is a solution to national unemployment, a way to avoid social unrest, and a means to gain foreign-exchange reserves. As early as 1974, the Philippine government, recognized the importance of labour migration to the national economy by establishing the Philippine Overseas Employment Administration in order to promote labour export. Sri Lankan and Indonesian authorities have followed this example.Female labor migration is a demand-driven, rather than a supply driven, phenomenon. To respond to demand patterns in the host countries, labor-exporting countries have to promote both male and female overseas contract workers and to face increased competition for a good position in the labor export market. To achieve this goal, they have created within their Ministries of Labor, offices or agencies to increase the number of foreign employment with an aim to promote, control and organize the recruiter and exportation of workers: AKAN in Indonesia, the Philippine Government Agency for Overseas Employment, (POEA) in the Philippines, and the Sri Lanka Bureau/Office for Foreign Employment (SLBFE) in Sri Lanka.The AKAN Indonesian Office of Foreign Employment was created in 1984 under the supervision of the Ministry of Labor. A year later, in 1985, the SLBFE TJSEAS 126 adopted the same objectives. The government objectives were to reduce national unemployment and to increase the savings of migrants. The transfer of funds from migrant workers made up 8.2% of PNB in the Philippines or more than $7 billion, 6.3% in Sri Lanka[START_REF] Cesap | Fifth Asian and Pacific Population Conference: Report and Plan of Action on Population and Poverty[END_REF], and 4.7% in Indonesia. The three million Indonesians who work abroad bring in approximately $1 billion (ILO 2006b).

  are confronted with the dilemma between promotion of female labour emigration and the protection of their national workers abroad. The Philippines, has substantial experience in labour export. The government, conscious to protect their "new heroes" (Bagong Bayani in Tagalog) who allow the country to prosper, create two distinct institutions. The POEA whose mission was to promote the export of the work-force and the Overseas Workers Welfare Administration (OWWA) which was established to defend and protect the rights of migrants. In the same spirit, the archipelago established an official charter, the Migrant Workers and Overseas Filipinos Act, voted in, in June 1995, so that the migrants are aware of their rights and their duties to be respected. The government enacted this charter to slow down the exportation of the less qualified workers who were the most vulnerable. Filipino NGO's, civil society and the Catholic Church have had a long history of activism, campaigns and debates to improve the life, conditions and rights of migrants workers.TJSEAS 130The civil society is better organised organized in the Philippines. They list more than a hundred NGOs who are very active in the fight to protect migrant workers. In comparison, Indonesia accounts for only 15 NGOs and a similar number in Sri Lanka.Cassettes, training modules, self-defense courses, handbooks and information booklets emanating from Filipino NGOs inform the migrants of the dangers in looking for employment abroad. Very rapidly, the Sri Lankan NGOs are following their example with pre-departure orientation and training programs. One of the major problems is the lack of clear, precise and reliable information explaining each stage in the migration process. This information is often not provided to Indonesian workers resulting in frequent misdirections, errors and fraud with their damaging consequences. In general, female Filipino migrants with better education and training and a good command of the English language have less problems in communication than Indonesian migrants.

  could progressively improve. The International Convention on the International Protection of the Rights of Migrant Workers and their families provides a normative framework to the transnational labor migrations. It has been ratified by 34 countries, TJSEAS 133 including the Philippines and Sri Lanka, and came into effect in 2003. These three countries were pulled between the desire to increase the export of their work-force and their duty to protect them. By sending so many female workers abroad, in conditions that, in one way, could put them in danger, they highlighted the global question of Human Rights within the general framework of migrations and work legislation.This positive outcome puts into perspective some of the criticisms that is sometimes addressed to them, that by exporting their own work-force in such great numbers, they would not create local jobs and thereby would avoid the internal problem of unemployment. Perhaps the years to come will show that the returning migrants can fulfill the role of providing local employment thanks to their remittances, their ideas and new skills.

Table 1 Estimated numbers of Asian (origin) workers in the Middle East

 1

	Nationality	Year	Number
	Filipinos	2003	1,471,849
	Indonesians	2000	425,000 *
	Sri Lankans	2003	900,000
	* for Saudi Arabia only
	Source: Hugo (2005: 10).

sought Asian workers for construction and general laboring because they were thought to be more docile and cheaper.

Rising from 1 to 5 million between 1975 and 1990, the number of migrant workers rose to almost 10 million in 2000 in Saudi Arabia, the United Arab Emirates (UAE) and Kuwait. The table 1 above illustrates the attraction that the Gulf States continue to exert on Asian labourers.

After 1980, the South-East Asian work migrations became more diversified. The Gulf States continued to absorb a large number of mostly South-East Asian laborers and notably women (Philippinos, Sri Lankans and Indonesians) to meet the increased demand for house-workers (maids and domestics) and the growth in service jobs.

By the middle of the 1980s, inter-Asian mobility rapidly developed. Japan, Taiwan, South Korea, Malaysia, Singapore, Hong Kong and Brunei became preferred migrant worker destinations. During this period, migrant flows became more complex as numerous countries became simultaneous importers and exporters of labor (cf.

Table 2 Estimated number of annual departures

 2

	Country of origin Year Annual departures Estimated	Destinations
				number of
				illegals migrants
	Indonesia	2002	480,393	+ 50,000	Malaysia, UAE
	Philippines	2002	265,000	+ 25,000	Asia, OCDE, UAE
	Sri Lanka	2003	192,000	+ 16,000	UAE, Singapore
	Source : ILO (2006).

Table 3 Proportion of Female Labor Migrants

 3

	Origin	Year	Number of migrants under contract	Percentage of women
	Philippines	2003	651,938	72.5 %
	Indonesia	2003	293,674	72.8 %
	Sri Lanka	2003	203,710	65.3 %

Source:

Hugo (2005: 18)

.

Table 4 Female Migration in Asia -proportion of female in percent regarding the total number of migrants

 4

	Regions	1960	1970	1980	1990	2000
	South Asia	46.3%	46.9%	45.9%	44.4%	44.4%
	East and SE Asia	46.1%	47.6%	47%	48.5%	50.1%
	West part of Asia	45.2%	46.6%	47.2%	47.9%	48.3%

Source:

Jolly and Narayanaswany (2003: 7)

.

Keiko

Yamanaka and Nicola Piper (2005: 9)

have calculated the number of women as a percentage of total migrant workers in the Asian labour-importing countries for the early 2000s (Singapore: 43,8% ; Malaysia: 20,5% ; Thailand: 43%; Hong Kong SAR: 95%; Taiwan: 56%; Korea: 35.1%).

One must emphasize that these statistics apply only to official work migrants who are legally permitted to work abroad. They do not take into account people who leave their own country to study, travel, or to get married who subsequently work in the visited country. Illegant entrants or people who work without a work permit. It is probable, therefore, that the number of migrant workers would be much higher if we include those who migrate clandestinely. It is estimated that at least a third of all labor migration in Asia is unauthorized.

TJSEAS 120