dataesr/scientific-paragraphs-categorization huggingface dataset:
A total of 457 OTUs were identified in midguts among all treatment conditions combined (clustered OTU sequences, Supplementary File S1). In all, 279 (61%) of these OTUs were annotated in the SILVA rRNA taxonomic database and were provisionally named on that basis (annotated raw OTU matrix, Supplementary Table  S2 ). OTU counts were normalized (normalized OTU matrix, Supplementary Table  S3 ) and analyzed to detect differentially abundant taxa found in two different comparisons: (i) mosquitoes depleted for APL1 versus controls with APL1, both without antibiotic treatment (OTU significance, Supplementary Table  S4 ); and (ii) mosquitoes treated with antibiotics versus controls without antibiotics, both with APL1 depleted (OTU significance, Supplementary Table  S5 ). Examination of the data by Principal Coordinates Analysis (PCoA) indicated that overall OTU abundance distributions were not significantly different in the mosquitoes depleted for APL1 as compared to controls (Figure  1A , p = 0.
significant OTU3_Klebsiella and displays a tendency in the same direction for APL1-depleted and antibiotic treated mosquitoes, it is a taxon of potential interest and it is hereafter analyzed jointly with OTU3_Klebsiella. Nevertheless, inclusion of OTU281_Cedecea should be regarded as provisional, and further studies will be necessary to determine the actual level of OTU281_Cedecea sensitivity to APL1 activity. All but one (OTU382_Serratia) of the eight major OTUs were significantly antibiotic sensitive under APL1-silenced conditions (Figure  3D  and Supplementary Table  S5 ). Notably,   S4 ). Positive values indicate increased absolute abundance of the family in APL1 depleted samples and negative values indicate decreased abundance after APL1 depletion. (B) Fold-change of absolute abundance of bacterial families after antibiotic treatment (ATB+) as compared to no antibiotics (ATB-), all mosquitoes depleted for APL1 (data in Supplementary Table  S5 ).
Negative values indicate decreased absolute abundance of the family after antibiotic treatment. (C) Fold-change of absolute abundance of the eight major OTUs after APL1 depletion by treatment with specific double-stranded RNA (dsAPL1) as compared to controls (dsGFP), all mosquitoes without antibiotics (data in Supplementary Table  S4 ). Positive values indicate increased absolute abundance of the OTU in APL1 depleted samples and negative values indicate decreased abundance after APL1 depletion. (D) Fold-change of absolute abundance of the 8 major OTUs after antibiotic treatment (ATB+) as compared to no antibiotics (ATB-), all mosquitoes depleted for APL1 (data in Supplementary Table  S5 ). Negative values indicate decreased absolute abundance of the OTU after antibiotic treatment. Adjusted significance levels, *p-value < 0.
Shotgun Sequencing and Fine Phylogenetic Placement of OTUs Associated With APL1 To refine the phylogenetic placement of OTU3_Klebsiella and OTU281_Cedecea, we performed shotgun metagenomics on DNA from midguts of APL1-depleted A. stephensi mosquitoes. APL1-depleted samples were sequenced because they harbor the highest abundance of the relevant APL1-modulated OTUs (Figures  2, 3 ). Of 462 million total paired-end 150 bp reads, mosquito reads were removed. From the non-mosquito fraction, the reads for the Cedecea and Klebsiella clades were binned and taxonomically identified by searching against a database of reference genomes using Centrifuge  (Kim et al. , 2016). The Cedecea and Klebsiella fractions included ∼3. 2 million reads each, ∼1% of the total sequence generated, which allowed estimation of the species composition and abundance of Cedecea and Klebsiella taxa (Supplementary Figure  S6 ).
The midgut Cedecea fraction was dominated at the species level by C. neteri (76% of the Cedecea midgut shotgun sequences) and Cedecea NFIX57 (23%), whereas the Klebsiella fraction contained three species with similar abundance profiles, K. michiganensis (38% of Klebsiella midgut shotgun sequences), K. oxytoca (34%), and K. sp. LTGPAF-6F (23%). We combined three lines of evidence to infer the most likely taxonomic identities of the OTUs in the Enterobacteriaceae sensitive to the presence of APL1 by aligning (i) the original 16S V4 Illumina amplicons, (ii) the sequences of the qPCR extended amplicons, and (iii) complete 16S rRNA gene sequences from the GenBank assemblies of the above Cedecea and Klebsiella species identified in the midgut shotgun dataset. The qPCR primers external to the OTU281_Cedecea 16S V4 Illumina amplicon display 100% identity to 16S genes corresponding to 5/5 available C.
neteri genome assemblies in Genbank (100%), and 1/1 (100%) Cedecea NFIX57 genome assemblies (Supplementary Figure  S7 ). Thus, the qPCR assay for OTU281_Cedecea should accurately amplify and measure both of these Cedecea species identified in A. stephensi midgut by the shotgun sequence data. The former species was the more abundant of the two in the shotgun sequence.
sp. LTGPAF-6F (Supplementary Figures  S8-S10 ). The components of Klebsiella targeted by the qPCR assay appear less well defined taxonomically, or may display greater diversity, than the Cedecea group. These three lines of evidence (original 16S V4 Illumina amplicon OTUs, qPCR extended amplicons, and shotgun sequence species) intersect to confirm the microbiome differential abundance and qPCR results, and coherently support the identities of these two OTUs in the differential analysis. The data support an interpretation of each of the two OTUs as closely related taxonomic swarms rather than single taxonomic entities. Metagenomic shotgun assembly was able to narrow the taxonomic space occupied by each OTU, but existing phylogenetic databases are incomplete for these taxa. Finer scale resolution and incrimination of specific taxa will require additional complete genome assemblies to identify the taxa comprising the Cedecea and Klebsiella oligotypes.
neteri and Cedecea NFIX57 as candidates for OTU281_Cedecea, and K. michiganensis, K. oxytoca, and K. sp. LTGPAF-6F as candidates for OTU3_Klebsiella. These taxa are poorly represented in genome databases. The finest level of resolution developed here for the two OTUs, which is the diagnostic oligotype qPCR assays, likely still detect closely related taxonomic swarms rather than single taxonomic entities. Complete genome assemblies will be needed to resolve the OTUs to single taxa, in order to characterize cultured taxa for controlled studies. There are likely to be interactions between microbiome taxa in the consortium. This may be the case for the taxa OTU3_Klebsiella and OTU281_Cedecea, based on the observation that biological replicates 1 and 2 carry one or the other OTU, and only replicate 3 carries both of these major OTUs of the Enterobacteriaceae (Figure  5 ).
Bacterial Microbiome-Wide Differential Abundance Analysis Read filtering by sequence quality, sequence clustering to generate OTUs, and taxonomic annotation were performed using VSEARCH  (Rognes et al. , 2016)  as implemented in the SHAMAN workflow (http://shaman. pasteur. fr, Quereda et al. , 2016). A 97% sequence identity threshold was used for sequence clustering, yielding 457 OTUs across all samples (clustered OTU sequences, Supplementary File S1), of which 279 were annotated in the SILVA rRNA taxonomic database release 128  (Quast et al. , 2013) , and were provisionally named on that basis. The annotated raw OTU count matrix is presented in Supplementary Table  S2. All subsequent analysis was performed with DESeq2 (v1. 4. 5)  (Love et al. , 2014)  as implemented in SHAMAN. Of 4,072,977 total OTU raw counts across all samples, only 25,347 (0.
6% of total OTU raw counts) map to the 178 OTUs that were not annotated in the SILVA database. Most of the unannotated OTUs were removed by the DESeq2 default "independent filtering" function, which removes OTUs with counts too low to generate reliable significant differences between conditions  (Bourgon et al. , 2010). The raw OTU count values were normalized across all samples using the default method in DESeq2 (median of ratios method, the estimateSizeFactors function). Size factors of total OTU count numbers were in the range 0. 5-2. 5. The normalized OTU count matrix is presented in Supplementary Table  S3. The relationship between estimated dispersion and normalized mean count values was evaluated by visual inspection as recommended, which indicated that local regression generated a better fit than parametric regression (Supplementary Figure  S11 ).
Sequence list: Cedecea rRNA gene sequences indicated with GenBank record identifier; sequence of qPCR extended amplicons indicated as OTU3_Klebsiella qPCR amplicon and OTU281_Cedecea qPCR amplicon; sequence of V4 Illumina amplicons indicated as OTU3_Klebsiella V4 amplicon and OTU281_Cedecea V4 amplicon; sequence of qPCR primers (Supplementary Table  S6 ) indicated as Primer OTU281_Cedecea_F and Primer OTU281_Cedecea_R.
S6  | Sequence of primers. Sequence of the primers (5 -3 ) used for the synthesis of double-stranded RNA for gene silencing (name preceded by "T7"), and for verification of silencing efficiency by quantitative RT-PCR (name preceded by "Ast"). Sequences preceded by "16S" used for quantitative PCR of total 16S rRNA abundance in mosquito midgut DNA. Sequences preceded by "OTU" used for quantitative PCR of qPCR extended amplicons for each indicated OTU. Sequences preceded by "Meta" used for amplification of the V4 hypervariable region of the 16S rRNA gene, with the bacterial 16S rRNA gene-specific portion indicated in bold. FILE S1 | FASTA-format database file of 457 clustered OTU sequences from Anopheles stephensi midgut. The V4 hypervariable region of the 16S ribosomal RNA (rRNA) gene was amplified and sequenced from DNA of A.
Positive values indicate increased absolute abundance of the family in APL1 depleted samples and negative values indicate decreased abundance after APL1 depletion. (B) Fold-change of absolute abundance of bacterial families after antibiotic treatment (ATB+) as compared to no antibiotics (ATB-), all mosquitoes depleted for APL1 (data in Supplementary TableS5). Negative values indicate decreased absolute abundance of the family after antibiotic treatment. (C) Fold-change of absolute abundance of the eight major OTUs after APL1 depletion by treatment with specific double-stranded RNA (dsAPL1) as compared to controls (dsGFP), all mosquitoes without antibiotics (data in Supplementary TableS4). Positive values indicate increased absolute abundance of the OTU in APL1 depleted samples and negative values indicate decreased abundance after APL1 depletion.
(D) Fold-change of absolute abundance of the 8 major OTUs after antibiotic treatment (ATB+) as compared to no antibiotics (ATB-), all mosquitoes depleted for APL1 (data in Supplementary TableS5). Negative values indicate decreased absolute abundance of the OTU after antibiotic treatment. Adjusted significance levels, *p-value < 0. 05, **p-value < 0. 01, and ***p-value < 0. 001. All values for fold-change, log2 fold-change and p-value for APL1 depletion and antibiotic treatment are in Supplementary TablesS4, S5, respectively.
FUNDING This study was received by the financial support to KV from the  European Commission ,  Horizon 2020 Infrastructures # 731060 Infravec2 ;  European Research Council, Support for Frontier Research, Advanced  Grant # 323173  AnoPath;  Agence Nationale de la Recherche , # ANR-19-CE35-0004  ArboVec;  National Institutes of Health ,  NIAID  # AI145999 ; and  French Laboratoire d'Excellence  " Integrative Biology of Emerging Infectious Diseases " # ANR-10-LABX-62-IBEID  and to MR from the  National Institutes of Health ,  NIAID  # AI121587.
The two Enterobacteriaceae taxa, OTU3_Klebsiella and OTU281_Cedecea, are sensitive to antibiotics (Figure3D). The condition that produces significant host mortality in A. stephensi(Mitri et al. , 2019)is illustrated by the midgut on the right. Control midgut APL1 depleted midgut FIGURE 4 | (Chan and Tan, 2017)icons were clustered in a reference 16S rRNA gene phylogenetic tree of 2807 full-length 16S rRNA gene sequences from complete prokaryotic genomes in the GenBank database (Supplementary FigureS3, OTUs are indicated in the tree by blue highlight and arrows). OTU281_Cedecea groups with Cedecea, in a basal position of the Enterobacteriaceae clade comprised of the taxa Escherichia/Shigella, Salmonella, Enterobacter and Klebsiella. Concordant with this placement, the OTU281_Cedecea 16S V4 Illumina amplicon displays 100% nucleotide identity with 16S rRNA gene sequences from the complete prokaryotic genomes of Cedecea lapagei, Cedecea neteri and Cedecea davisae.
Basic information (locality, senior collector name and number) is provided for collections of the previously published taxa, whereas comprehensive collection data and a distribution map are given for the new species, with the exceptions of D. antakaranae Capuron ex G. E. Schatz & Lowry, sp. nov. and D. sennenii G. E. Schatz & Lowry, sp. nov. , which can form large enough trees to be potentially exploited as a source of ebony, and for which geo-coordinates and detailed locality information have therefore been withheld. Specimen records are available for all members of the group in the Catalogue of the Plants of Madagascar (Madagascar Catalogue 2020) and the Sonnerat database  (Sonnerat 2020). Post-facto georeferencing of historical specimens is indicated by square brackets.
Acknowledgements We thank  Alain Jouy  for the excellent illustrations,  Fano Rajaonary  for preparing the map, and  Eric Lowry  for assistance with preparing the figures. Helpful comments on an earlier version of the manuscript were provided by  T. Deroin  and  B. Wallnöfer , whom we gratefully acknowledge. We thank the Curators of the following herbaria for providing access to their collections: G, K, P, TAN, TEF, US, W. We are grateful to the  Government of Madagascar (Ministère de l'Environnement, de l'Écologie et des Forêts)  for providing the necessary authorization for conducting field work, and the  Parc botanique et zoologique de Tsimbazaza  for assistance with exporting duplicate specimens. This work was facilitated by two grants generously provided by the Fondation Franklinia, one for our work on Diospyros and another in support of the conservation and sustainable management of Madagascar's precious woods.
The resulting PCR products were purified and loaded onto the Illumina MiSeq cartridge according to the manufacturer instructions. The quality of the run was checked internally using PhiX, and then each pairend sequences were assigned to its sample with the help of the previously integrated index. Each pair-end sequences were assembled using Flash software  (Magoc & Salzberg, 2011)  using at least a 10 bp-overlap between the forward and reverse sequences, allowing 10% of mismatch. All the sequences are publically available on NCBI under the BioProject PRJNA531076. They were processed with the DADA2 pipeline  (Callahan et al. , 2016)  with the following parameters: trim 17 bp from each fragment to remove the primers, filter out the sequences below 390 bp after merging R1 and R2 or sequences with undetermined bases, remove the chimera using the consensus method.
| RE SULTS The internal standard is an artificial DNA sequence that contains specific ATCG pattern that sets it apart from every sequence of 16S E extraction = Q retrieved Std Q added Std = Std_measured_qPCR(copies) × 100 × 100 10 8 OTU_1(copies per weight) = Counts_OTU_1_in_sample_1 total_number_reads_in_sample_1 × Q Step 13 total 16S (copies) × E extraction Sample_Weight rRNA gene entered in Genbank. The DNA sequence is added to the sample before the DNA extraction so its recovery can quantify the extraction yield. We can then calculate the absolute numbers of 16S rRNA genes in the sample after lysis from the qPCR measurement targeting the 16S rRNA genes and this extraction yield. Here, we first verify the linearity of the signal across the range of detection. Second, an experiment using E.
Several authors have proposed to add cells as internal standards before the DNA extraction, but we believe that adding a synthetic DNA offers more control than adding cells, whose exact number of 16S rRNA genes per cell is difficult to control. Indeed, growing E. coli cells can harbor up to 38 copies per cell, instead of the seven copies per genome due to multiple replication forks  (Bremer & Dennis, 2008). Adding starved cells is more accurate (Figures  A7  and A8 ; Table  A3 ) but it should also be noted that databases associating genera and a 16S rRNA gene copy number are based on genome sequencing rather than actual measurements of growing cells. Therefore, any database would associate seven copies per E. coli cell  (Vandamme & Coenye, 2003)  even if that number might not hold in growing E.
ACK N OWLED G EM ENTS This work was performed in collaboration with the GeT core facility, Toulouse, France (http://get. genot oul. fr) and was supported by France Génomique National infrastructure, funded as part of "Investissement d'avenir" program managed by Agence Nationale pour la Recherche (contract ANR-10-INBS-09). We also thank Mathilde Hazon-Le Sciellour and David Renaudeau for providing the pig sample.
DATA AVA I L A B I L I T Y S TAT E M E N T All sequences are available in NCBI GenBank under Bioproject PRJNA531076: https://www. ncbi. nlm. nih. gov/bioproject/531076. Supplemental information (such as the dada2 OTU table) can be found at https://doi. org/10. 15454/YWMMH4.
(2018) workflows samples Synthetic • 16S sequenc- • Relative abundance of • Initial density/ex- • 20%-80% devoted Tkacz et al. DNA internal ing of the V4 reads traction efficiency to measure the DNA (2018) standard region to obtain number internal standard of OTU per mg • Dose of internal stand- (optionally con- ard difficult to calibrate verted to cells per • Can only be used with mg via database) 515F/806R • Assumes 100% lysis in the first step of the DNA extraction • Sequencing • Relative abundance of • Initial density/ex- • Assumes 100% lysis This study • qPCR reads traction efficiency in the first step of the • 16S rRNA copies per mg to obtain number DNA extraction of OTU per mg Abbreviations: OUT, operational taxonomic unit; qPCR, quantitative PCR.
We here collect the most significant scientific results, identify limitations, and summarize the lessons learned from exploring the rich Piton de la Fournaise SAR data archive over the past ~20 years. For instance, the technique has delivered first evidence of the previously long suspected mobility of the volcano's unsupported eastern flank, and it is especially useful for detecting displacements related to eruptions that occur far away from the central cone, where Global Navigation Satellite System (GNSS) stations are sparse. However, superimposed deformation processes, dense vegetation along the volcano's lower eastern flank, and turbulent atmospheric phase contributions make Piton de la Fournaise a challenging target for applying InSAR. Multitemporal InSAR approaches that have the potential to overcome some of these limitations suffer from frequent eruptions that cause the replacement of scatterers.
SAR Data and SAR Data Archives The most important SAR data archive for Piton de la Fournaise volcano is the OI2 scientific database that has been developed in order to support both the semi-operational InSAR monitoring of Piton de la Fournaise volcano and the scientific exploitation of long InSAR time series. The OI2 SAR data archive holds 1835 SAR scenes acquired since September 2000 by 8 different SAR satellite systems or constellations (and a total of 13 different satellites) as of 31 December 2019 (Figure  3  and Table  1 ). In addition, InSAR products such as interferograms and coherence maps dating back to May 2003 are also kept within the OI2 database. All data stored within OI2 are available through a dedicated web interface named CASOAR  [24]. The data have been immensely valuable to image and study 52 of the 58 eruptions that occurred since 9 March 1998 (Figure  3 ).
While access to most of the raw data has to be restricted due to the data policies of the responsible space agencies, derived data products are downloadable in geotiff format by registered users. A mirror archive of OI2 has been developed locally at OVPF, ensuring on-site processing and analysis as well as OI2 data and product backup. Even though SAR scenes cannot be distributed through CASOAR, the online platform provides an almost complete listing of all SAR data acquired at Piton de la Fournaise volcano since 2003 (Figure  3  and Table  1 ). A number of SAR images that were acquired before the development of OI2 are not centrally stored and are, therefore, harder to access for the community. While comprehensiveness is anticipated, not all SAR data acquired since 2003 at Piton de la Fournaise volcano are yet included within the OI2 database.
For example, CNES routinely acquired ENVISAT ASAR swath 4 data on both ascending and descending tracks that are not stored within OI2. Also, several Radarsat-1 images may exist that are not maintained within the central archive OI2, and certainly more CSK and ALOS2 images exist than the ones OI2 is holding. Moreover, the German Aerospace Center (DLR) is operating the TanDEM-X satellite (TDX) as a TSX add-on for the collection of digital elevation measurements and the generation of a global digital elevation model (DEM). For this purpose, bistatic SAR data are being acquired in a way that one satellite is transmitting the electromagnetic signal while both TSX and TDX satellites are receiving the echoes simultaneously. Over Piton de la Fournaise volcano, a total of 211 such Co-SSC scenes were acquired before the end of the year 2019, which are listed in Table  1  (but not included in Figure  3 ).
However, not all of them are stored in OI2. Most of the data maintained within the OI2 archive were obtained through data proposals in response to the Space Agencies' announcements of opportunity (AOs). Because data contingents offered through these AOs are usually limited to a certain number of images or to a specific time window, the temporal density of acquisitions often remains below the capacities of the satellite systems. Another source of SAR data are the open archives of the space agencies. For example, archive data acquired by "old generation" (i. e. , out of order) satellites, such as ESA's ENVISAT, and JAXA's ALOS-1 SAR systems, are now freely available through these space agencies. For the restricted archives, like RADARSAT, CSK, and TSX, data can be purchased, even if no AOs are open for proposal submissions.
On the other hand, the SAR instruments on board the satellites are likely to stay on standby mode during the entire Indian Ocean flyover when no acquisitions are explicitly requested. Therefore, not many background acquisitions are being acquired over La Réunion Island. As for many other isolated volcanic ocean islands, no ERS1 or ERS2 data have been acquired as the satellites were not equipped with large onboard storage capacities and because any real time data downlink station was too far from the island at the time. Likewise, no ENVISAT ASAR swath 1 data have ever been acquired at Piton de la Fournaise since those had unfavorable viewing geometries. Especially the new generation SAR satellite systems (Figure  3b ) deliver high-resolution and high-quality data with acquisition designs that are optimized for InSAR applications.
Discussion and Conclusion: Lessons Learned and Future Perspectives For Piton de la Fournaise volcano, a well-developed and coherent SAR database exists that contains satellite acquisitions dating back to early September 2000 (Section 2). Surface deformation measurements derived from these data using InSAR and MT-InSAR techniques complement an elaborated ground deformation monitoring network operated by OVPF-IPGP (Figures  2  and 3 ). The InSAR techniques have proven to be very well suited to measure the spatial extent and magnitude of the full variety of characteristic surface displacement phenomena associated with the high level of activity of Piton de la Fournaise volcano (Section 3). In particular, SAR data are playing a fundamental role in the detection and quantification of movement of the volcano's eastern flank.