dataesr/scientific-paragraphs-categorization huggingface dataset:
6b ). These five genes can be further categorized into two groups based on their genomic context. Two genes, Xi_rhs-1 and Xi_rhs-2 encode an N-terminal PAAR motif (PF05488), though Xi_rhs-2 is annotated as a truncated ORF, missing its C-terminal-encoding domain. The other three (Xi_rhs-3 through rhs-5) lack the PAAR domain but are encoded next to small open reading frames with a PAAR-like domain, DUF4150/PF13665. Furthermore, the Xi_rhs-1 and Xi_rhs-2 are encoded downstream of a DUF1795-containing protein and putative vgrG gene, both of which were necessary for Rhs protein translocation in Serratia marcescens  [69]. The other three rhs genes are also encoded downstream of putative vgrG genes. The genomic contexts of these three rhs genes are distinct from those of rhs-1 and rhs-2 in that these gene clusters also encode DUF2169 and DUF4150 domain-containing proteins, which in Agrobacterium tumefaciens are demonstrated accessory proteins required for secretion of their cognate T6SS toxin  [67].
The highly variable C-terminal domains (CTDs) of Rhs proteins contain the toxic effector activity. An analysis of the CTDs of X. innexi Rhs-family proteins (except Xi_rhs-2 which lacks a CTD) revealed no recognizable CTD function in rhs-3, -4, and -5. In contrast rhs-1 contains PF14437, a MafB19 deaminase domain  [70]. This domain occurs in the CTDs of several classes of polymorphic toxins, including the recently recognized Neisseria MafB toxins, and the Rhs protein putative toxin E1IMF  [70]. While our data demonstrate that in several insect hosts, X. innexi displays attenuated virulence relative to other Xenorhabdus spp. it remains an associate of S. scapterisci nematodes (Fig. 1 , Table  2 ), and successfully reproduces within crickets, where it may encounter competing microbes (Additional file 8).
Identification of the Xlt-encoding NRPS/PKS hybrid gene cluster X. innexi secretes a small lipopeptide named Xlt with toxicity toward mosquitoes  [28, 29]. Previous structural data suggested that Xlt is a cyclic lipopeptide composed of six amino acids and two fatty acids  [28]  and we hypothesized that it may be synthesized by a hybrid NRPS/PKS cluster  [72]. Based on this hypothesis, we predicted that the locus would encode six A-and two AT-domains respectively. Among the three identified hybrid genes in X. innexi genome, only one gene cluster, XIS1_460105 to _460116 (present in the center of a single contig) has two AT-domains and six A-domains that correspond to the number of fatty acids and amino acids identified in Xlt  [28]. The candidate gene cluster encodes 12 ORFs with predicted NRPS or PKS functions based on BLASTp analysis (Table  7 ).
szentirmaii and S. plymuthica respectively (the sequences of X. budapestensis fcl were not available). BLASTp analysis indicated that the predicted function of each gene in Xlt biosynthesis gene cluster is very similar to both Fcl and Zmn coding genes (Table  8 ). We noted two differences in coding content, both on the flanking edges of the X. innexi cluster, relative to X. szentirmaii: the first gene in the X. szentirmaii locus (fclA, predicted to encode a NUDIX hydrolase) is absent in the Xlt-encoding cluster (Tables  7  and 8 )  [74]. Instead, the flanking genes are predicted to encode a TonB homolog and a cardiolipin synthase. Also, X. szentirmaii has cluster genes fclM and fclN, predicted to encode ABC transporters, immediately downstream of the last condensation domain gene  [74]. In contrast, in X.
The presence of certain amino acid residues of Xlt, including histidine and 2,3-diaminobutyric acid (DAB), could not be explained by the in silico analysis conducted in this study. However, the structural analysis of fabclavine, which is produced by a homologous gene cluster from X. szentirmaii and X. budapestensis, showed a replacement of phenylalanine by histidine as well as the presence of 2,3-diaminobutyric acid in its peptide moiety. The structure of fabclavines, which corresponds to the preliminary structural data of Xlt, provided further support that the selected gene cluster should produce Xlt. Based on our prediction, we next tested if mutation of the gene cluster from XIS1_460105 to _460116 would disrupt mosquitocidal toxin activity in X. innexi.
innexi genome lacks many of the canonical virulence determinants encoded by its sister species may indicate that specialization in crickets has led to an erosion of virulence coding potential. However, the specificity of S. scapterisci for colonization by X. innexi, and our identification of several loci predicted (e. g. T6SS/Rhs) or confirmed (e. g. xlt) to be necessary for production of secreted factors indicate that X. innexi remains an actively transmitted and biologically active symbiont. Relative to the well-characterized entomopathogenic nematode symbiont X. nematophila, X. innexi is attenuated for virulence and reproduction in the lepidopteran hosts G. mellonella and M. sexta, as well as the dipteran D. melanogaster. Unpublished data suggests X. innexi is also avirulent towards honeybees (Apis mellifera) and Colorado potato beetles (Leptinotarsa decemlineata)  [29].
doucetiae is virulent in both S. littoralis and G. mellonella, even though it does not produce Tc toxins  [7]. Ogier et al. [7]  suggested that the absence of Tc toxins encoded in genomes of members of this clade (C I )  [84]  is due to loss of an ancestral component  [7]. In the X. innexi genome we did not find evidence of fragments or pseudogenized copies of Tc-encoding genes, as are present in the X. bovienii CS03 genome  [4]. As such, we propose that the apparent lack of these genes in the genome of X. innexi, a member of clade C IV indicates a loss event, separate from that proposed to have occurred in clade C I. Interestingly, in the draft genome of another strain of the C IV clade (X. cabanillasii, accession number: GCA_000531755), Tc loci are incomplete, which supports the idea that recent deletions for Tc-encoding genes have occurred in this clade (unpublished data, S.
DNA extraction, genome sequencing and annotation The X. innexi genomic DNA was isolated using a standard protocol  [110]  and submitted for Roche (454) pyrosequencing and assembly at the University of Wisconsin Biotechnology Center. The assembled genome sequence was annotated using the Magnifying Genomes server (MaGe) from MicroScope Microbial Genome Annotation and Analysis Platform. Sequences are available through accession numbers: FTLG01000001-FTLG01000246. Identification of putative toxin genes in X. nematophila and X. innexi The X. nematophila ATCC19061 genome was used as a reference to identify the various toxin gene families that we evaluated  [104]. We determined the presence or absence of genes encoding putative toxins in X. innexi in three ways: using X. nematophila sequences as BLAST queries (E ≤ 0.
0) software package, which implements probabilistic profile hidden Markov models. We set our threshold E-value criterion at 10 -6 , to reduce the probability of false-positive matches. For MaGe analyses we used loci present in the completely sequenced genome of the virulent strain X. nematophila (ATCC 19061) and identified those with homologs in the genomes of the virulent strains X. bovienii SS-2004 and X. doucetiae FRM16  [6, 7] , but without homologs in the X. innexi HGB1681 genome. The following homology constraints were used: bidirectional best hit, minimal alignment coverage of 0. 8, and amino acid sequence identity of 30%. Identification and analysis of Tps genes in X. innexi TpsA proteins sequences were aligned using the CLUS-TAL W program implemented in SEAVIEW  [112] , and alignments were cleaned using Gblocks  [113].
Additional in silico analyses were conducted to further test this prediction. Protein sequences of each ORF in the cluster were examined through protein BLAST to predict the putative function, and then analyzed through the conserved domain search to identify PKS, NRPS and non-PKS/NRPS domains. Protein sequences of A-domains in NRPS modules were analyzed through NRPSpredictor2  [115]  and AT-domains identified in PKS modules were analyzed using I-TASSER server  [116].
Percent mortality of late 3rd instar Ae. aegypti larvae after treatment with dilutions of culture supernatants of WT X. innexi, ΔXIS1_460109 and ΔXIS1_460115. Half-fold serial dilutions of cellfree supernatants from cultures of (a) wild type X. innexi, b the XIS1_460115::kan mutant (ΔXIS1_460115), or (c) the XIS1_460109:: kan mutant (ΔXIS1_460109) were bioassayed with 20 larvae per concentration. Mortality was recorded at 48 h. Each data point indicates a single experiment (n = 3 experiments). No mortality was observed after larvae incubation in 0. 25 dilution or lower of ΔXIS1_460109 and ΔXIS1_460115 supernatants but over 70% mortality was observed in the lowest test concentration of WT X. innexi supernatants.
8 Percent mortality of late 3rd instar Ae. aegypti larvae after treatment with dilutions of culture supernatants of WT X. innexi, ΔXIS1_460109 and ΔXIS1_460115. Half-fold serial dilutions of cellfree supernatants from cultures of (a) wild type X. innexi, b the XIS1_460115::kan mutant (ΔXIS1_460115), or (c) the XIS1_460109:: kan mutant (ΔXIS1_460109) were bioassayed with 20 larvae per concentration. Mortality was recorded at 48 h. Each data point indicates a single experiment (n = 3 experiments). No mortality was observed after larvae incubation in 0. 25 dilution or lower of ΔXIS1_460109 and ΔXIS1_460115 supernatants but over 70% mortality was observed in the lowest test concentration of WT X. innexi supernatants.
a large fraction of CH 4 variability is correlated with ENSO, with higher tropical wetland CH 4 emission during La Niña periods. However, this pattern has not been verified until now by atmospheric CH 4 measurements during a La Niña. Furthermore, La Niña periods have received less attention in studies of the atmospheric CH 4 budget than El Niño, since continued warming likely favors neutral or El Niño conditions  16. The La Niño of 2011 (LN11 hereafter) was the strongest since 1980 (see Fig. 1a ) and offers the possibility to investigate the response of the atmospheric CH 4 budget to La Niña conditions. In this study, we investigate this response by combining different measurement dataset and model simulations. A brief overview of them is given in the next section.
We use the TM5-4DVAR (TM5-variational data assimilation system  27  ) in combination with GOSAT FP XCH 4 , and surface measurements from NOAA-ESRL 3 and CSIRO  28  to optimize surface CH 4 emissions. Note that the inverse model makes use of actual meteorological fields from the ECMWF ERA-interim reanalysis to account for variability in the atmospheric transport of CH 4. Earlier studies have established the link between biomass burning CH 4 emissions and ENSO  29. To exclude the influence of biomass burning, fire related CH 4 emissions from the Global Fire Emissions Database version 4s (GFED4s) inventory have been subtracted from the TM5-4DVAR emissions. The origin of an atmospheric CH 4 anomaly can be identified using CH 4 stable isotope measurements. We look at measurements of  13  C/ 12 C in CH 4 (expressed in δ-notation as δ 13 C-CH 4 ) analyzed by INSTAAR in samples from the NOAA-ESRL (ref.
Acknowledgements We acknowledge the support by the  Netherlands Organization for Scientific Research (NWO)  under project number  ALW-GO-AO/11-24. The computations were carried out on the Dutch national supercomputer Cartesius maintained by SURFSara (www. surfsara. nl). Access to the GOSAT data was granted through the third GOSAT research announcement jointly issued by JAVA,  NIES , and  MOE.
Data Availability We use Level 2 SRFP XCH4 v2. 3. 7 GOSAT XCH4 retrievals that are publicly available from ESA's Climate Change Initiative website (www. esa-ghg-cci. org/). NOAA CH4 and INSTAAR δ13C-CH4 measurements are freely available from NOAA's public ftp server (ftp://aftp. cmdl. noaa. gov/data). CSIRO CH4 measurements can be downloaded from the WDCGG (World Data Centre for Green-house Gases) website. GFED4s CH4 emissions can be downloaded from http://daac. ornl. gov. CRU TS3. 23). Precipitation and temperature data are held at British Atmospheric Data Centre, RAL, UK (http://badc. nerc. ac. uk/data/cru/). SWAMP wetlands fraction data can be downloaded from http://wetlands. jpl. nasa. gov after a short registration. CLM4. 5 and LPJ-wsl CH4 emissions and wetlands fractions can be obtained by contacting William J.
Molecular analyses The molecular analyses were made using 28 specimens of the six valid Tometes plus the new species proposed herein, from six large tributaries of the Amazon Basin in Brazil: as Jari, Negro, Tapajos, Tocantins-Araguaia, Trombetas and Xingu river basins; and also from Maroni River, a costal drainage between French Guiana and Surinam. Tissues were preserved in 95% ethanol for DNA extraction and deposited at CTGA, with vouchers deposited at GEA, IEPA, INPA and MPEG. The sequences obtained in this study are deposited in GenBank under the following accession numbers KX868671 to KX868698. Total DNA was isolated from approximately 50mg of tissue using standard phenol-chloroform extraction methods  [20]. A fragment of approximately 750 bp of the mitochondrial control region was amplified using the primers LPROF (5' AACYCCCRCCCCTAACYCCCAAAG 3') and DLOsteri R1 (3' GTAAAACGACGGCCAGTCCTGGTTTH 5').
0. 6  [22]  and edited manually. The alignment was then checked manually for insertions, deletions or stop codons for COI sequences using translated amino acids. Genetic distances (uncorrected p-distances, recommended by Collins et al. [23] ) were calculated using the Ape 3. 5 package  [24]  in R version 3. 3. 2 [25] , with the pairwise deletion option set to "true". We used a cutoff of 2. 0% for genetic distance as a threshold value adopted for the COI-based identification systems  [26]  in most Neotropical freshwater fish fauna  [27]. We further visualized the divergence of these taxa using a Neighbor Joining (NJ) tree, which is the standard method of phylogenetic inference in DNA barcoding studies  [26]. To demonstrate that the new species is divergent and diagnosable from all other nominal species of Tometes, assuming the Phylogenetic Species Concept  [28] , we used the R package SPIDER  [29]  to extract diagnostic molecular characters in the COI and control region sequences.
Additionally, we concatenated the two genes and analyze the phylogenetic relationships among the species using a maximum-likelihood (ML) in the Ape 3. 5 package  [24] ; the nucleotide substitution model (GTR+G) was selected using Phangorn with the AICc criterion, and node support was evaluated using 1,000 bootstrap replicates. In the ML analysis we included Myloplus schomburgkii and Myloplus rubripinnis as outgroups. Sequence alignment is available at https://github. com/legalLab/datasets.
Acknowledgments This study is part of the Doctoral thesis of the first author (MCA) at the  Graduate Program on Aquatic Ecology and Fishing ,  Biological Sciences Institute, Federal University of Para. We thank  Chico Mendes Institute for Biodiversity Conservation (ICMBio)  for allowing the collection of specimens at  Mosaic of Conservation Units of Serra dos Carajas, Itacaiunas River Basin. We also thank  Wolmar Wosiacki  and  Izaura Magalhães  (MPEG), Lucia  R. Py-Daniel ,  Renildo R. de Oliveira ,  Isabel Soares  and  Douglas Bastos  (INPA),  Oswaldo T. Oyakawa  and  Michel D. Gianetti  (MZUSP),  Flavio Lima (ZUEC) ,  Cecile Gama  (IEPA), and  Patrice Pruvost ,  Zora Gabsi ,  Claude Ferrara  ( MNHN ) for making available the specimens of their museums,  Allan Jesus  (GEA) and  Nelson Balão  for help in collecting the specimens, and  Douglas Bastos  for providing the picture of holotype alive.
aegypti Aag2 cell line  (20). The presence of transcripts from ALFEs and AEFEs in Aedes mosquitoes prompted us to check whether the expression level of their transcripts was altered during DENV infections in vivo. We utilized unpublished transcriptome data sets from female A. aegypti mosquitoes that were orally infected with either of two DENV serotypes (DENV serotype 1 [DENV1] and DENV3) or that were uninfected, which were available in the Lambrechts laboratory, to examine AEFE1 transcript expression. DENV1 infection did not affect AEFE1 transcript expression at 24 and 96 h postinfection (Fig. 4A ). No  significant difference in AEFE1 expression was observed between DENV1-and DENV3infected A. aegypti mosquitoes at 18 and 24 h postinfection (Fig. 4B ). The data suggest that AEFE1 is constitutively transcribed and not affected by DENV1 and -3 infections in adult female A.
aegypti mosquitoes. Searching for new flavivirus-like elements in Aedes mosquitoes. PCR for fulllength ALFE1 DNA in the A. albopictus Vietnam strain did not result in amplification (Fig. 1B ). We then performed PCR with primer pairs targeting ALFE1 and its flanking regions and amplified bands with unexpected sizes (data not shown). Because of the heterogeneity of the PCR products, we moved on to confirm the existence of ALFE1 and to search for new ALFEs in A. albopictus. We performed whole-genome DNA sequencing of the A. albopictus Vietnam strain and the C6/36 cell line. First, we mapped reads from the A. albopictus Vietnam strain and C6/36 cell DNA libraries to the ALFE1 to ALFE3 sequences and to the sequences of their respective flanking regions (Fig. 5 ). DNA coverage showed the presence of full-length ALFE1 in the genomes of the Vietnam strain and of C6/36 cells (Fig.
5A ), despite the lack of PCR amplification. In addition, the relative coverage of the flanking regions of the ALFE1 to ALFE3 sequences was substantially higher, indicating that these elements are integrated in multicopy regions (Fig. 5A to C ). We also observed a similar trend of insertion of ALFEs in multicopy sequences when analyzing the genome sequence of the A. albopictus Foshan strain, available in the VectorBase database (data not shown). To identify new ALFEs, we performed an in silico screening based on an iterative mapping and assembly procedure using ALFE1 to ALFE3 sequences as scaffolds and the DNA library from the A. albopictus Vietnam strain as the query (details are provided in Materials and Methods). This in silico screening yielded eight contigs named ALFE4 to ALFE11 harboring partial sequences of ALFE1 to ALFE3 (Fig.
6A ). For instance, ALFE4 was composed of a portion of ALFE1 followed by full-length ALFE3. We detected different genomic sequences flanking each ALFE, suggesting that multiple versions of each ALFE are present in the genome of the A. albopictus Vietnam strain. The sequences of the nearby regions are unique to Aedes mosquitoes, as a search for homology against the sequences in the GenBank and VectorBase databases did not show homology with any known organisms. Moreover, the six-phase translation of the flanking sequences did not show any similarity with known proteins from the UniProt Knowledge database. To confirm the existence of the bioinformatically predicted ALFE4 to ALFE11, we used two different assessments: (i) the quality of the DNA mapping of the A. albopictus Vietnam strain and C6/36 cell reads to the new ALFE contigs and (ii) PCR with primer pairs specific to the new ALFE contigs.
Indeed, the currently available genome assemblies of A. albopictus and A. aegypti in the VectorBase database consist of thousands of unassembled supercontigs. There is an urgent need to assemble these fragmented reference genome sequences into end-to-end chromosome maps. It is hoped that the advent of new tools, such as long-read sequencing technologies and chromosome confirmation capture, will produce a leap forward in the study of mosquito genomes. Finally, a phylogenetic analysis of AEFE1 in A. aegypti mosquitoes from Cameroon, French Guiana, and Thailand showed that the evolutionary history of AEFE1 was similar to that of most nuclear genes. Note that we did not investigate the phylogenetic relationships of ALFEs because the current lack of population genomics studies of A. albopictus mosquitoes would have made any interpretation difficult.
Total RNA was extracted from the mosquito samples with the TRIzol reagent (Invitrogen). Following DNase I (Promega) treatment, cDNA was synthesized with Maxima H Minus reverse transcriptase and oligo(dT) primers according to the manufacturer's instructions (Thermo Fisher Scientific). PCR and nested PCR were performed with DreamTaq DNA polymerase (Thermo Fisher Scientific). The sequences of the primers are provided in Table  2. Transcriptome data analysis. Individual midgut libraries of A. aegypti mosquitoes infected with DENV1 or DENV3 were prepared from total RNA extracts from individual midguts after quality control Small RNA and genome DNA libraries. To analyze small RNA production from ALFEs and AEFEs, we used small RNA libraries of A. albopictus and A. aegypti mosquitoes infected or not infected with CHIKV that are publically available in the Sequence Read Archive under accession number SRP062828.
For genomic DNA libraries, total DNA was extracted from C6/36 cells and the A. albopictus Vietnam strain using a NucleoSpin tissue kit (Macherey-Nagel). Genomic DNA was then sheared into 200-bp fragments using a Covaris S220 device with the following parameters: peak incident power, 175; duty factor, 10; cycle burst, 200; and duration, 180 s. Genomic DNA libraries were prepared using a Kapa LTP library preparation kit Illumina Platforms (Kapa Biosystems). The library was amplified with 10 PCR cycles, and 2 ϫ 151 paired-end reads were sequenced on a NextSeq 500 sequencer. For bioinformatics analysis, the quality of the fastq files was assessed with FastQC software (www. bioinformatics. babraham. ac. uk/projects/fastqc/). Low-quality bases and adaptors were trimmed from each read by use of the Cutadapt program.
Only reads with an acceptable quality (Phred score, 20) were retained. A second set of graphics was generated by the FastQC software using the fastq files trimmed by the Cutadapt program. Reads were mapped to target sequences using the Bowtie 1 tool with the Ϫv 1 (one mismatch between the read and its target) or the Bowtie 2 tool with default options for the small RNA or DNA library, respectively. The Bowtie 1 tool (small RNA library) and the Bowtie 2 tool (DNA library) generate results in sequence alignment/map (SAM) format. All SAM files were analyzed by the SAMtools package to produce bam indexed files. Homemade R scripts with Rsamtools and Shortreads in Bioconductor software were used for analysis of the bam files. In silico screening for new EFVEs. To identify all versions of EFVEs in A.
albopictus mosquito DNA contigs, we developed an iterative bioinformatics pipeline. Each iteration is composed of 4 steps: (i) BLASTN analysis using raw reads from the DNA library as the database and an E value threshold of 1EϪ20, (ii) read extraction according to the BLASTN result, (iii) assembly of these reads using the SPAdes (v3) genome assembler, and (iv) extraction of contigs larger than 400 bases. For the first iteration, the already known ALFE sequences were used as queries. For the following iterations, the contigs selected from the previous iteration were used as queries. Due to the very large number of matches detected by BLASTN analysis after some iterations (repetitive regions from the flanking region of EFVEs), only 5 iterations were used in order to analyze the contigs obtained.