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Htrms converter

Manufactured by Biognosys
Sourced in Switzerland

The HTRMS converter is a specialized piece of laboratory equipment developed by Biognosys. Its core function is to convert high-resolution time-of-flight mass spectrometry (HTRMS) data into usable information for analysis and research purposes.

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12 protocols using htrms converter

1

Comprehensive Protein Quantification Using SpectroNaut

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SpectroNaut 18 (Biognosys) was used for all data analysis using the directDIA+ workflow and a human Uniprot library utilizing all default parameters for data calibration and analysis. All files were first converted to HTRMS using the appropriately named “HTRMS Converter” software from Biognosys prior to analysis. Output data was visualized in GraphPad Prizm 10.0.1.
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2

Generation of a Comprehensive HCC Proteome Library

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The library was generated with MaxQuant (version 1.5.1.2)90 (link) using the default settings except that the mass tolerance of the instrument was set to 10 ppm and the minimal ratio count for quantification was set to 1. The Uniprot SwissProt database (17 August 2015) including the iRT fusion peptide was used for the searches. All library measurements were pooled into one MaxQuant analysis to generate one general HCC library. The raw SWATH MS runs of the individual biopsies were converted using the HTRMS converter (Biognosys). The converted SWATH runs were analyzed with Spectronaut X (Version 12.0.20491.20.29183) (Biognosys) using the default settings and searched against our in-house generated general HCC library.
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3

DIA Data Analysis with Spectronaut

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Prior analysis of the DIA data, the raw files were converted into htrms files using the htrms converter (Biognosys). MS1 and MS2 data were centroided during conversion. The other parameters were set to default. The htrms files were analyzed with Spectronaut 13 (version: 13.5.190812, Biognosys) using the previously generated hybrid library and default settings42 (link). The results were filtered by a 1% FDR on precursor and protein level (Q value < 0.01).
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4

DIA Proteomic Workflow for Microbial Identification

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Raw MS data was demultiplexed and converted to *.htrms format using HTRMS converter (Biognosys) and processed in Spectronaut 15.5 (Biognosys). A spectral library was built using Direct‐DIA searches of all individual files. Searches used a Swissprot database with homo sapiens taxonomy (downloaded on 10/16/20) and appended with a concatemer containing single amino acid variant peptides, as well as porcine trypsin. Protein sequences from Streptococcus mitis, Gamella haemolysans, and Granulicatella adiacens were also downloaded from Uniprot and appended to generate a combined database with 25,944 entries. Search settings included N‐terminal semi‐tryptic specificity, up to 2 missed cleavages, fixed carbamidomethyl(Cys) and variable acetyl(protein‐N‐terminus) and oxidation(Met) modifications.
For DIA analysis, default extraction, calibration, identification, and protein inference settings were used. iRT profiling was utilized to quantify precursors that did meet a q‐value cut‐off of <0.01 in a particular run. Protein quantification was performed at MS2 level using the MaxLFQ algorithm,20, 21q‐value percentile 0.2 settings (all precursors that passed a q‐value in at least 20% of runs were included) with run‐wise imputing, and local normalization22 using precursors that met a q‐value in all runs (q‐value complete).
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5

Generating Islet Proteome Spectral Library

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To generate the islet proteome spectral library RAW data from fractionated pooled strain samples were processed using MaxQuant (v1.6.7.0) (Cox and Mann, 2008 (link)) using default settings, including enabling of LFQ, with minor changes: “match between runs” was enabled with a time window of 0.7 min to transfer identifications between adjacent fractions. Database searching was performed using the Andromeda search engine integrated into the MaxQuant environment, with searches performed against the mouse UniProt database (June 2019 release), concatenated with known contaminants and reversed sequences of all entries. Protein, peptide and site FDR thresholds in MaxQuant were each set to a maximum of 1%.
Prior to library-based analysis of the DIA data, RAW files were converted into htrms files using the htrms converter (Biognosys) with parameters set to default. The htrms files were analyzed with Spectronaut (version: 13.10.191212, Biognosys) using the MaxQuant-generated spectral libraries and default settings.
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6

Differential Proteomic Analysis of Plasma

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All DIA files were extracted from home generated plasma library containing 73 466 precursors, 55 433 modified peptides and 5190 proteins using Spectronaut X (Biognosys). Raw MS data files were converted to HTRMS files with HTRMS converter (Biognosys). HTRMS files were imported to Spectronaut with default parameters with the decoy generation set to “mutated.” Cutoff of fold change > 1.3 or <0.3785 and Q < 0.05 (FDR‐corrected P value for t test) was set for differentially expressed proteins. Correlation and ROC analysis were carried out using R software version 3.5.3.
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7

Spectronaut Proteomics Data Analysis

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DIA raw data was converted to Spectronaut’s HTRMS file format using the HTRMS converter (version 18.5, Biognosys, Switzerland) with default settings. Then peptide and protein identification and quantification was performed with Spectronaut (version 18.5.231110, Biognosys), followed by statistical analysis in R Statistical Software (version 4.3.2, R Core Team 2023). Details are described in the section “Quantification and Statistical Analysis” below. Results of the statistical analysis were visualized in a Volcano plot in R using the EnhancedVolcano package (version 1.20.0).
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8

Spectral Library Creation and Protein Quantification

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A total of 61 MS runs (14 DDA and 47 DIA) of the meniscal samples were converted to HTRMS format using HTRMS Converter (Biognosys AG, Switzerland) in order to decrease data analysis search time. A spectral library was created in Spectronaut X™ Pulsar (version 12.0.20491.15, Biognosys AG) using all DIA and DDA runs. Default settings (BGS factory settings) were used with additional modifications: cysteine carbamidomethylation as a fixed modification, and deamination, pyro-glutamic acid (N-term Glu to pyroglutamic acid), methionine oxidation, hydroxyproline and acetylation as variable modifications. The human protein database (20190416_UP152602_n20415) was used as the background proteome. A subsequent protein search was conducted in Spectronaut™ Pulsar using the recently created spectral library and the same human database as background proteome. Default settings were used for the search. Precursor quantitation was performed at MS2 level, and area under the curve was used as quantitation type. The top three peptides (proteotypic) for each protein were averaged to calculate protein abundance15 (link).
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9

Quantitative Proteomic Analysis of Meniscal Samples

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The 30 DIA raw files of the meniscal samples were converted to HTRMS format using HTRMS Converter (Biognosys AG, Switzerland) in order to decrease data analysis search time. A subsequent protein search was conducted in Spectronaut Pulsar (Biognosys AG, Switzerland) with the human protein database (150612_UP5640_n20200) as background proteome, using a library-free workflow, DirectDIA. Default settings were used for the search, with the following modifications: cysteine carbamidomethylation as a fixed modification, and deamination, pyro-glutamic acid (N-terminal Glu to pyroglutamic acid), methionine oxidation, and hydroxyproline as variable modifications. Precursor quantitation was performed at the MS2 level, and the area under the curve was used as a quantitation type. The top three peptides (proteotypic) for each protein were averaged to calculate protein abundance.12 (link)
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10

DIA-based Peptide Quantification Protocol

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The peptides were analyzed by LC–MS operating in data-independent acquisition (DIA) mode. The LC was operated as above, except a different gradient elution was used. The concentration of mobile phase B was increased from 2 to 50% over 60 min, increased to 99% over 6 min, held at 99% for 3 min, and decreased to 2% over 2 min.
The MS was the same instrument as above but operated in DIA mode. Mass spectra were acquired using a collision energy of 35%, resolution of 30 000, maximum inject time of 54 ms, and automatic gain control target of 5 × 104. Staggered isolation windows of 12 Da in the range of 400 to 1000 m/z were used.
Data were analyzed with Spectronaut 15 using the directDIA workflow and default settings. Peak area intensities were exported from Spectronaut. Quantitative and statistical analysis was performed, and processing protein peak areas were determined by the Spectronaut software. Prior to library-based analysis of the DIA data, the DIA raw files were converted into htrms files using the htrms converter (Biognosys). MS1 and MS2 data were centroided during conversion, and the other parameters were set to default. The htrms files were analyzed with Spectronaut (version: 15, Biognosys) via directDIA. Precursor and protein identifications were filtered to 1% false discovery rate.
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