dataesr/scientific-paragraphs-categorization huggingface dataset:
xylostella larval midgut based on shotgun HPLC-ESI-MS/MS data by means of a multialgorithm pipeline. A total of 876,341 tandem mass spectra were searched against the predicted P. xylostella protein sequences and a whole-genome six-frame translation database. Based on a data set comprising 2694 novel genome search specific peptides, we discovered 439 novel protein-coding genes and corrected 128 existing gene models. To get the most accurate data to seed further insect genome annotation, more than half of the novel protein-coding genes, i. e. 235 over 439, were further validated after RT-PCR amplification and sequencing of the corresponding transcripts. Furthermore, we validated 53 novel alternative splicings. Finally, a total of 6764 proteins were identified, resulting in one of the most comprehensive proteogenomic study of a nonmodel animal.
Some studies in Lepidoptera midgut reported involvement of lipases, proteases, and carbohydrases in digestion, as well as cytochrome P450, glutathione-s-transferases (GST), and carboxylesterases in xenobiotic metabolism  (45). For explaining Bt-resistance, receptors in the midgut of the target pest were investigated. Omics approaches started to be applied to study the physiological and toxicological changes at a global scale in the midgut. ESTs and cDNA microarray technology were used to study immune-inducible genes in P. xylostella  (39). More recently, Xie et al. (46)  provided more insights into P. xylostella EST database to understand the molecular mechanism of insecticide resistance, using an Illumina-based transcriptome profiling technique. cDNA libraries were used to develop genomic approaches to enrich mRNAs and identify key players from the surrounding cells, but they failed to identify proteins secreted into the lumen and their temporal dynamics.
Liu et al. (47)  identified the midgut protein profile of sixth instar larvae of Spodoptera litura by HPLC-ESI-MS/MS. In the larval midgut of Bombyx mori 1100 proteins were detected using a 2-DE/MS approach (48). The 2-DE/MS/MS de novo peptide sequencing technology was used to detect major proteins in the midgut lumen of the cotton bollworm Helicoverpa armigera  (44). The draft sequence of the P. xylostella genome was released recently  (49)  and provided the conditions to uncover the molecular function of the larval midgut in P. xylostella. In the present study, we have carried out an in-depth proteomic analysis of midgut proteins of P. xylostella using shotgun nanoLC-MS/MS. The mass spectrometry-derived data were analyzed by a multialgorithm pipeline using a six-frame translation of genome sequences in addition to searches of a protein database of P.
The electrospray voltage applied was 1. 5 kV. Automatic gain control (AGC) was used to prevent overfilling of the ion trap; 1 ϫ 10 4 ions were accumulated in the ion trap for generation of HCD spectra. For MS scans, the m/z scan range was 350 to 2000 Da. Database Searches for Peptide and Protein Identification-Raw data files were processed to generate peak list files by Xcalibur. 2. 1. 0 (ReAdW. exe). The filtering parameters used were: (1) allowed precursor mass range was 500 -5000 Da; (2) precursor charge state was allowed from 1 to 5; (3) minimum number of peaks in a spectrum was chosen to be 5; (4) signal to noise ratio was set as 3; and (5) for precursors with unrecognized charge state, default charge states of 2 and 3 were allowed. The protein sequences database generated from several sources were used for spectral searching.
Protein sequences from the diamondback moth genome annotations (DBM-DB. v1. 0) were downloaded from the genome database (http://iae. fafu. edu. cn/ DBM/index. php), which were used to construct a protein database (PDB). A six-frame translation of diamondback moth genome, named Genome Database (GDB), was generated based on the DBM-DB. v1. 0 genome sequence by EMBOSS:6. 2. 0. A threshold of no less than 30 putative amino acids (a. a. ) was chosen to discard small open reading frames (from stop codon to stop codon) to minimize the database size. Based on the genome database, an exon skipping database (ASDB) was constructed. The variant peptides generated were appended to the genome translation databases as separate entries. Three different search engines, Mascot (version 2. 3. 02), omssa (version 2.
1. 1), and xtandem (version 2009. 10. 01. 1) were used to analyze the data. The parameters for database search were as follow: peptide mass tolerance 20 ppm; fragment mass tolerance 0. 6 Da; fixed modifications "Carbamidomethyl (C)"; variable modifications "Gln-Ͼpyro-Glu (N-term Q), Oxidation (M), Deamidated (NQ)"; and one misscleavage allowed. The results were filtered at 1% FDR at peptide level and each protein identified with at least one unique peptide. Because six different types of searches were performed with the same data set (genome and protein database searches using Mascot, omssa, and xtandem), peptide sequences assigned to a single spectrum in each search were compared. Spectra that were assigned different sequences in different searches were omitted from further analysis. Protein identification list was generated by grouping proteins based on shared peptides.
Proteins that have at least one unique peptide were selected from the group. From a group where no protein could be distinctly selected above others, that is, all proteins had equal evidence, it was represented by only one in the final list marked with an asterisk and remaining equivalent protein IDs were reported in parentheses. Peptide Mapping and Analysis with Genome Annotation-The full list of spectral matched peptides was established as mentioned here above with a FDR cut-off of 1%. The combination of database/ peptide and database/genome coordinate tables were used to map these peptides back to its genomic location(s), considering the split peptides because of spanning splice junctions. Genome coordinates of all the peptides were found out using blast program. Genome search specific peptides (GSSPs) were identified by excluding those peptides that mapped to known proteins from translated genome database search results.
GSSPs were categorized into three parts, including mapping to intergenic region, partially overlapping annotated genes, and completely mapping to annotated genes. Novel genes and gene model modifications thus obtained based on gene prediction software and those peptide evidences were checked based on the conservation across P. xylostella using protein blast. MS/MS spectra used for proposing novel ORFs or changes in gene structure were manually validated. RNA-Seq data downloaded from diamondback moth genome database (http://iae. fafu. edu. cn/DBM/ index. php) were also used to validate the novel genes. RT-PCR Validation-Total RNA was isolated from DBM1Ac-S P. xylostella midgut samples. The resulting double-stranded cDNA fragments were used as templates for PCR amplification. PCR reaction was performed using Premix Ex Taq polymerase (TAKARA, Beijing, China), 30 to 50 ng of cDNA, and 200 nM each primer pair.
PCR products were analyzed by agarose gel electrophoresis to determine the presence or absence of the product fragments. Their size was determined using a 100-bp DNA ladder (TIANGEN, Beijing, China). Actin was chosen as a positive control, and isolated RNA as a template was used as negative control to ensure that there was no genomic DNA contamination. Once the bands were observed at the expected sizes, they were excised and purified using DNA Gel Extraction kit (TSINGKE, Beijing, China). The purified PCR products were subjected to automated DNA sequencing using ABI BigDye 3730xl DNA Analyzer Terminator, Version 3. 1 (Applied Biosystems, Beijing, China). Functional Description of Midgut Protein Genes-Gene Ontology annotation databases (http://www. geneontology. org) were used to predict the most probable gene functions  (56).
The functional categories of genes were classified based on the categories reported previously  (57). The Gene Ontology terms (http://www. geneontology. org) were assigned by Blast2GO (http://www. blast2go. org). The Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www. kegg. jp/ or http://www. genome. jp/kegg/) was used to annotate molecular networks (pathways). Data Repository-The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (58) via the PRIDE partner repository with the data set identifiers PXD003564, PXD003565, PXD003566, PXD003567, and PXD003568 (http://www. ebi. ac. uk/pride/archive/projects).
Overview of MS/MS Data for Multialgorithmic Proteogenomic Analysis- The goal of this study was to carry out in-depth proteomic profiling to map the proteome of larval midgut of P. xylostella at a global scale using a proteogenomic approach. Fig. 1  shows the specific developed workflow. First, protein extracts from the midgut of P. xylostella larvae were resolved by SDS-PAGE. The gel was cut into 10 (preliminary experiment) or 20 (four biological replicates) pieces, equal in size each. The five biological replicates were processed leading to a total of 90 peptide fractions, which were analyzed by nanoLC-MS/MS. The resulting MS/MS data were searched using iPeak search algorithm against three databases, i. e. an annotation protein database (PDB), a six-frame translated protein database (GDB), and an alternative splicing database (ASDB), as well as a contaminant database from http://maxquant.
org/contaminants. zip with 247 sequences of common contaminants. PDB was used to confirm the gene models annotated in the DBM genome. It comprises all protein sequences from the published version of the genome annotations (DBM-DB. v1. 0). GDB was used to find new gene models. It was generated from a six-frame translation of the entire genome (DBM-DB. v1. 0). ASDB is an exon skipping database from DBM genome exons that was used to find alternative splicings. For the DBM genome database (DBM-DB), many redundant genomic regions were characterized as "n" to further assemble the DBM genome with less scaffolds. These genomic sequences were removed in the DBM genome version 2. Because the gene sets were not updated in the new genome version  (59) , the DBM genome database version 1 was used to establish the protein sequence databases described here above.
The sizes of the three databases are indicated in Table  I. The iPeak program was developed to automate spectral searches, statistical integration of PSMs and downstream analysis. It is configured with two open source peptide identification algorithms namely OMSSA, X!Tandem and the commercial software Mascot. These algorithms differ in their basic scoring. For instance, OMSSA uses a Poisson distribution for separating significant matches from random hits (60) whereas X!Tandem uses a hyper-geometric model  (61). Mascot calculates protein ratios using only ratios from the spectra that are distinct for each protein and excluding the shared peptides of protein isoforms. Although there are rescoring algorithms to improve database search results  (62, 63) , a diverse set of algorithms provide an increased sensitivity for peptide identifications than any single algorithm.
iPeak incorporates a reversed protein decoy database strategy to calculate FDR. A total of 876,341 MS/MS spectra were acquired in this study, out of which 300,078 were assigned to peptide spectrum matches (PSMs) with a 1% false discovery rate (FDR) threshold. The complete list of PSM identified in our study along with scores assessed by the three identification algorithms, charge, m/z value, post-translational modifications and genomic coordinates in the DBM genome database is provided in supplemental Data file S1. Fig. 2A  depicts all the peptides  (16, 151)  identified in this study mapped to their FIG. 1. Overview of the proteogenomic strategy used in this study. Proteins from the brush border membrane vesicles (BBMV) were extracted from the larval midgut of a susceptible Plutella xylostella strain DBM1Ac-S (two biological replicates) and from a Cry1Ac-resistant strain of P.
xylostella near-isogenic to the susceptible DBM1Ac-S strain NIL-R (two biological replicates). In a preliminary experiment, a biological replicate was obtained after mixed the midguts from the two strains. The resulting five samples of purified BBMV proteins were resolved by SDS-PAGE. A representative SDS-PAGE is shown with lane 1 and lane 2 corresponding to BBMV proteins from DBM1Ac-S strain and NIL-R strain, respectively, and lane M showing the molecular weight markers indicated in kDa. The gel was cut into 10 (preliminary experiment) or 20 (four biological replicates) pieces, equal in size each, as shown. After proteolysis, the resulting peptide fractions were analyzed by nanoLC-MS/MS. Then, MS/MS data were searched using iPeak search algorithm against three databases, i. e. an annotation protein database (PDB), a six-frame translated protein database (GDB), and an alternative splicing database (ASDB).
The decision tree for validating genes, identifying novel genes, or refining gene structure is shown. genomic loci. The distribution of peptides (Fig. 2B ) and proteins (Fig. 2C ) identified from the various MS/MS search algorithms applied is also shown. Among this peptide pool, we identified a total of 2694 genome search specific peptides (GSSPs) that could not be mapped to PDB but only to the six-frame translated GDP. These peptides mapped to 58,301 loci on the genome, which were considered for further proteogenomic analysis. Proteins Identified in P. xylostella Larval Midgut-A total of 6764 proteins were identified in the larval midgut of P. xylostella by the shotgun ESI MS and proteogenomic analysis against DBM-DB. v1. 0 genome database. The list of identified proteins with the corresponding peptide coverage is available in supplemental Data file S2.
Distributions of the preference for hydrophilic proteins conform to the law of normal distribution, in agreement with some previous proteomics reports  (64). Confirmation of Annotated Protein-Coding Genes in Genome-The DBM-DB. v1. 0 release of the P. xylostella automatic genome annotation contains 18,071 predicted proteincoding models. Based on the proteome of the larval midgut studied here, a total of 2156 peptides were mapped to 1896 gene models annotated in DBM-DB. v1. 0. These supporting peptides provide evidence for translation of the existing gene models. Many protein records in the DBM-DB database are derived from high throughput cDNA experiments or computational gene predictions. Identification of peptides from these proteins serve as confirmation that the locus in question is, in fact, a protein-coding gene.
Refining of Current Gene Models by GSSPs-To revise the annotated gene models, we used the Blastn program to find ORFs in the genomic regions where the set of 2694 GSSPs were mapped. Some intragenic loci were considered to be evidence for gene extension beyond the borders of the existing annotated frame, which suggested that the annotated gene model is incorrect. A total of 355 GSSPs clustered into existing genes that extended the existing exon. It is difficult to determine whether a novel exon is a refinement of an existing gene model or an additional instance of a novel gene model. Choosing an appropriate distance for clustering is the key to better distinguish between these two cases, which is complicated in eukaryotic organisms as exons from a single gene can be separated by large distances.
supplemental Table S2 compiles these results. Of those, 39 instances of refined genes were supported by at least two GSSPs. To provide additional support to our gene refinements, we checked the conservation of these genes based on EST and RNA-Seq experimental data available from P. xylotella using the blat algorithm. For 14 gene fixed events, EST/cDNA sequence were found to support the refined cases. We also used blast and genewise to identify homologs of the predicted amino acid sequence in the animal subset of the National Center for Biotechnology Information nonredundant database (version 2013, August 26th). For 103 proteins, homology protein evidence was found and supported the identification for reliable refined gene models. For 33 genes, homology protein or EST/cDNA evidence were found to support the refined cases with single GSSP, i.
Normally, evidence for alternative splicing comes from mRNA sequencing projects, which may include prespliced or contaminating sequences. Mass spectrometry data can confirm the presence of specific isoforms in a sample at the protein level. In this study, MS/MS data were searched against the database of exon-exon junction spanning tryptic peptides of hypothetical splice variants generated using all possible forward combinations of exons in a gene. Using our deep proteogenomic sampling we were able to identify a total of 53 events of novel alternative splicing. Their complete list is reported in supplemental Table  S3. It is worth to mention that the splice variant described in Fig. 4  is also seen in other Lepidoptera species, which contained two new alternative protein isoforms. The MS/MS spectrum of the peptide QRI-IESYVEK, resulting from splicing together of exons 2 and 54 of the Px013984 gene, has been previously described for the Danaus plexippus dynein heavy chain.
v1. 0 annotation. All the identified peptides were found matching with blat queries to the cDNA/EST database of P. xylotella. To analyze the function and establish whether homologs exist, we took into consideration the surrounding nucleotide sequence and searched against the animal protein sequences in NCBInr. The refined cases that were identified by single GSSP with only one significant PSMs without homology protein or EST/cDNA evidence were considered to be unreliable cases, thus, they were removed from the results. Of the remaining novel genes, 75 have EST and similarities support, in addition to experimental peptides; and 356 genes are supported by the peptides and similarities only. A subset of 200 genes have at least two GSSPs supported. After filtering, the full list of 439 novel protein-coding genes is available in supplemental Table  S4  with details of the supporting peptide evidence and genome coordinates.
Furthermore, the total of 348 instances for novel protein-coding genes were validated by RNA-Seq data downloaded from the diamondback moth genome database (http:// iae. fafu. edu. cn/DBM/index. php). As we mapped these novel genes to DBM-DB V 2. 0, there were 326 cases that failed to map to the scaffold of the new DBM genome database, which supported our worthy choice that the DBM-DB V 1. 0 should be used for the proteogenomic analysis. For example, we identified pieces of evidence with 16 GSSPs to support a novel protein-coding gene (scaffold_8_5_683226_ 684035). Although scaffold_8_5_ 683226_684035 was not previously functionally annotated in P. xylostella genome, we believe this protein and the novel on scaffold 8 of DBM-DB, are NADH dehydrogenase [ubiquinone] iron-sulfur protein based on their similarity to the protein encoded by Gene ID: 512937168 in B.
mori (e value 3E-155). Fig. 5  shows the characteristics of this novel case including the GSSPs used for its identification, the closest homolog in NCBI nr, XP_004933701. 1 (e value 3E-155), and the EST/cDNA evidence. Validation of Novel Genes Using RT-PCR and cDNA Sequencing-As described above, our MS/MS data identified 439 novel protein-coding genes in the midgut of P. xylostella. We performed an additional level of validation by performing RT-PCR on selected examples of novel genes. Of all the novel protein-coding genes, 246 (56% of 439) have been confirmed by RT-PCR. A table listing the novel protein-coding genes supported by RT-PCR data including primers and production size is available in supplemental Table  S4. Fig. 6  shows an example of a novel gene supported by its RT-PCR sequence.
xylostella using a multialgorithmic pipeline to gain molecular understanding of this animal. Using identified GSSPs, we discovered novel protein-coding genes and corrected wrongly annotated gene models. Furthermore, novel alternative splicings were identified and validated. The DBM draft sequence was only recently published and annotation efforts are still in the early stages. The MS/MS data analyzed in this study largely support the DBM annotations. In-depth analysis identified proteins putatively involved in insecticide resistance. The presence, at high levels, of numerous enzymes of the glycolysis pathway, as well as absorption and transport of fatty acids and lipids, indicate that active metabolic processes of carbohydrates and lipids occurred in the larval midgut of P. xylostella. However, as the first tissuespecific proteogenomics analysis of P.
xylostella, we have provided examples showing the unique role proteogenomics can play in building the most accurate and descriptive structural annotation. Clearly, our results show that there is a need for continued improvements to existing gene models, annotation of missing genes, and corrections to the genome sequence itself to provide P. xylostella researchers with the most accurate representation of the DBM genome, transcriptome, and proteome upon which their research relies, and to a wider extent to all those interested in Arthropods as these proteogenomics data can be used to better annotate new genome sequences of this yet molecularly poorly characterized group of animals, especially within the i5k framework. This study provides the fundamental basis for future elucidation of the molecular mechanism involved in insecticide resistance.
This last one is amplified by a Preamplifier from Langer (PA 303), before the measurements by the Picoscope 3405A (USB oscilloscope). The bandwidth of the measurement setup is limited by the Picoscope with an upper frequency of 100MHz. The traces obtained are composed of p = 3700 points, with a 1GS/s sampling rate. We remind that 100MHz is a cutoff frequency marking an attenuation of the relevant signal, not its total removal. One has to remark that the required equipment comes at a very low cost, under 2000 excluding the computer. The computation heavy step is the profiling phase. The program is written with the language (Bezanzon et al. , ), which is particularly efficient for computing-intensive tasks. Considering the large size of the covariance matrices, the computation requires a lot of memory.
The results show that some methods, such as linear and piecewise constant interpolations should definitely be avoided, particularly when the resulting signal is differentiated, which is necessary to estimate speed, an important feature in postural control. Other methods, such as averaging on sliding windows or SWARII, perform significantly better on synthetic dataset, and produce results more similar to the laboratory-grade AMTI force plate (AFP) during experiments. Those methods should be preferred when resampling data collected from a WBB.
1). This problem is magnified when differentiating the signal, which is necessary to compute the speed of the CoP. Since this indicator is one of the main quantifiers of postural control (see, e. g. ,  [13] ), the use of a correct resampling method is of paramount importance. In this study, we discuss the non-uniform sampling limitation of the WBB. We then present and study several resampling approaches used in the Posturography literature to derive a uniformly sampled signal. Additionally, we introduce a new resampling method, SWARII, specifically designed with the WBB in mind, for which we provide an open source implementation. We compare those different methods by applying them to three different datasets: (1) a synthetic dataset, whose parameters were chosen to highlight the shortcoming of the most commomly used resampling approaches; (2) a WBB dataset obtained by recording immobile objects; and (3) a comparison dataset, where 10 subjects have been recorded using both the WBB and the AMTI force platform.