This database is the product of a multi-year, comprehensive evaluation and expansion of the world's most widely used mass spectral reference library.

Data here contain and describe an open-source structured query language (SQLite) portable database containing high resolution mass spectrometry data (MS1 and MS2) for per- and polyfluorinated alykl substances (PFAS) and associated metadata regarding their measurement techniques, quality assurance metrics, and the samples from which they were produced. These data are stored in a format adhering to the Database Infrastructure for Mass Spectrometry (DIMSpec) project. That project produces and uses databases like this one, providing a complete toolkit for non-targeted analysis. See more information about the full DIMSpec code base - as well as these data for demonstration purposes - at GitHub (https://github.com/usnistgov/dimspec) or view the full User Guide for DIMSpec (https://pages.nist.gov/dimspec/docs). Files of most interest contained here include the database file itself (dimspec_nist_pfas.sqlite) as well as an entity relationship diagram (ERD.png) and data dictionary (DIMSpec for PFAS_1.0.1.20230615_data_dictionary.json) to elucidate the database structure and assist in interpretation and use.

This repository contains a database of high-resolution electron ionization (EI) mass spectra recorded under gas chromatography - mass spectrometry (GC-MS) conditions. The vast majority of publicly available GC-MS data sets are obtained using low-resolution mass spectrometry. Few exceptions are the works E.J. Price, 2021, and V.Castro, 2022. At the same time, gas chromatography-high-resolution mass spectrometry (GC-HRMS) is used quite often in studies.This database aimed to create a GC-HRMS data set covering the diverse classes of volatile compounds (trimethylsilyl- derivatives are not included!), using a wide m/z range (starting from m/z = 40). Mass spectra were recorded using an Orbitrap Exploris GC mass detector (Thermo Fisher Scientific, USA). The mass determination error is no more than 0.0006 Da, and the mass spectral resolution value is 30000. All mass spectra were checked manually; the .zip archives contain information on peak annotations. The data.xlsx file contains a list of compounds and spectra IDs. Peaks with intensity less than 1/999 of the most intense were discarded.The data set includes:130 mass spectra of pure compounds recorded using GC-MS of 10-molecule batches or GC-MS of individual compound solutions.61 mass spectra of compounds included in the 8270 MegaMix standard compound mixture.45 mass spectra of volatile compounds included in lavender essential oil.38 mass spectra of volatile compounds included in mint essential oil.33 mass spectra of volatile compounds included in lemon essential oil.22 mass spectra of volatile compounds included in coffee.These groups of spectra are designated as Pure samples, 8270 MegaMix Standard, Lavender (essential oil), Mint (essential oil), Lemon (essential oil), and Coffee, respectively in the data.xlsx file and in the "Comments" tag in the MSP files. Please note which spectrum was obtained in what way. Identification of compounds in essential oils and coffee is quite reliable, but it was still performed without using standard samples.For convenience, in some cases (for essential oils), SMILES are provided using symbols denoting stereoisomers, but we cannot be sure that we really know which stereoisomer we are considering: often, both the retention indices and mass spectra are very close.Detailed information on the experimental conditions under which the spectra were obtained, on the equipment, and data processing is contained in the info.pdf file. The quality_assessment.xlsx file contains data obtained during quality control of the mass spectra (see the info.pdf file for additional information).Each file named all_spectra contains all spectra (both those obtained using the sample collection and those obtained from essential oil and coffee samples) in different file formats. Most likely, you need the all_spectra.msp file (NIST-compatible), it contains all the data. The plant_volatiles.msp file contains all mass spectra obtained from essential oils and coffee. The names of the remaining files are self-explanatory. If you need annotations of all peaks or more file formats, then look at the .zip archives. JCAMP (.jdx) files are in the .zip archives.Processing (interpretation) of mass spectra was done using our software:https://github.com/mtshn/gchrmsexplain versions 0.0.2 and 0.0.3.The settings used are given in the info.pdf file; however, these settings are the default for the corresponding versions.Levels of explanation of each peak in the mass spectrum:Level 1 - the molecular formula is selected, but some isotopic peaks are not found at allLevel 2 - isotopic peaks merge with other peaks. For example, the 13C peak of some ion X is superimposed (taking into account the resolution) on the main peak X + H. At not very high resolutions, such peaks may not be resolved. This also includes cases of "incorrect" isotopic peak intensity, differing from the theoretically calculated one.Level 3 - all main isotopic peaks are observed correctly, up to the accuracy of mass determination.The minimum number of bonds that must be broken to obtain such a fragment is indicated without taking into account the loss of hydrogens, as well as without some other "trivial" bond breaks: the loss of a halogen atom, a methyl group, NO-loss from a nitro-group. Details are given in the documentation of the software used to process the mass spectra: https://github.com/mtshn/gchrmsexplain.In files containing abbreviated interpretations of mass spectra (e.g., in CSV_annotated folders in .zip archives), notations like 3-1 are used. The first number denotes the interpretation level (see above), and the second denotes the number of (non-trivial) bond breaks required to obtain such a molecular formula.

Metadata-centric, auto-curating repository designed for storage and querying of mass spectral records. It contains metabolite mass spectra, metadata and associated compounds.

NIST peptide libraries are comprehensive, annotated mass spectral reference collections from various organisms and proteins useful for the rapid matching and identification of acquired MS/MS spectra. Spectra were produced by tandem mass spectrometers using liquid chromatographic separations followed by electrospray ionization. Unlike the NIST small molecule electron ionization library which contains one spectrum per molecular structure, there are several different modes of fragmentation (ion trap and ?beam-type? collision cells are currently the most commonly used fragmentation devices) that result in spectra with different, energy dependent, patterns. These result in multiple spectral libraries, distinguished by ionization mode, each of which may contain several spectra per peptide. Different libraries have also been assembled for iTRAQ-4 derivatized peptides and for phosphorylated peptides. Separating libraries by animal species reduces search time, although investigators may elect to include several species in their searches.

The NIST DART-MS Forensics Database is an evaluated collection of in-source collisionally-induced dissociation (is-CID) mass spectra of compounds of interest to the forensics community (e.g. seized drugs, cutting agents, etc.). The is-CID mass spectra were collected using Direct Analysis in Real-Time (DART) Mass Spectrometry (MS), either by NIST scientists or by contributing agencies noted per compound. The database is provided as a general-purpose structure data file (.SDF). For users on Windows operating systems, the .SDF format library can be converted to NIST MS Search format using Lib2NIST and then explored using NIST MS Search v2.4 for general mass spectral analysis. These software tools can be downloaded at https://chemdata.nist.gov. The database is now (09-28-2021) also provided in R data format (.RDS) for use with the R programming language. This database, also commonly referred to as a library, is one in a series of high-quality mass spectral libraries/databases produced by NIST (see NIST SRD 1a, https://dx.doi.org/10.18434/T4H594).

The data for MSnLib are divided into several Zenodo records due to size constraints.

raw positive: 10966404raw negative: 10967081mzml positive and negative: 10966280spectral libraries: 11163380

This record includes the automatically generated spectral libraries (MSnLib) within mzmine, acquired using a flow injection method on an Orbitrap ID-X instrument, for all compound libraries. There are multiple files for each compound library containing MS2 only or MSn in two data formats (.mgf or .json) for both polarities.

MS2 contains next to all MS2 spectra all pseudo MS2 spectra (a full MSn tree merged into one spectrum per compound ion). MSn contains all individual MSn stages additionally. The first number for each file highlights the library building date.

7 Compound Libraries:

Short Name: Full name, Provider (Catalog number), total compounds (not all detected during library building)

MCEBIO: Bioactive Compound Library, MedChemExpress (HY-L001), 10,315 compounds

MCESAF: 5k Scaffold Library, MedChemExpress, (HY-L902), 4998 compounds

NIHNP: NIH NPAC ACONN collection of NP, NIH/NCATS, 3988 compounds

OTAVAPEP: Alpha-helix Peptiomimetic Library, OTAVAchemicals (a-helix-Peptido), 1298 compounds

ENAMDISC: Discovery Diversity Set -10, Enamine (DDS-10), 10,240 compounds

ENAMMOL: Carboxylic Acid Fragment Library + Random, Enamine and Molport, 4378 compounds

MCEDRUG: FDA-Approved Drug Library, MedChemExpress (HY-L022), 2610 compounds

Information regarding the SPECTYPE

no SPECTYPE or SINGLE_BEST_SCAN: Best spectrum for each precursor and energy (highest TIC)

'SAME_ENERGY' = Additionally, if a spectrum was acquired multiple times for a precursor with the same energy, they are merged into one spectrum only with the same energy (max. signal height used for each fragment signal).

'ALL_ENERGIES' = merged spectrum of all used energies (in our case 3 for each precursor, using the merged (same energy) if available).

'ALL_MSN_TO_PSEUDO_MS2' = mzmine merges all MSn into one pseudo MS2.

V5 fixed USIs

A mass spectral database for organic compounds. The spectra included in the database are: electron impact Mass spectrum (EI-MS), Fourier transform infrared spectrum (FT-IR), 1H nuclear magnetic resonance (NMR) spectrum, 13C NMR spectrum, laser Raman spectrum, and electron spin resonance (ESR) spectrum.

mini-Ni is a small database of electron ionization mass spectra and retention indices for nitrogen-containing compounds, mainly aromatic heterocycles.Gas chromatography-mass spectrometry (GC-MS) is a very important method of chemical analysis. Identification is performed using a library search of the mass spectrum in a mass spectral database, and retention index information is also used. Nitrogen-containing small molecules with a high content of nitrogen (Ni means i nitrogen atoms), such as derivatives of triazoles, pyrazoles, imidazoles, diazines, etc., including those containing -CN and -NH2 groups, are an important class of analytes, including priority pollutants. Unfortunately, such compounds are insufficiently represented in the available GC-MS databases, and the databases also contain erroneous entries. This database partially fills this gap.All data (and further notes) are provided in an XLSX file. The other three files also contain mass spectra and retention indices, in formats suitable for import into NIST MS Search and other software. To import the SDF file into NIST MS Search, use the Lib2NIST utility.Electron ionization mass spectra and retention indices (5%-phenylpolydimethylsiloxane and polyethylene glycol) for 104 molecules are provided. For 72 molecules, retention indices are given for three different heating rates (temperature programming mode). The following chromatographic conditions were used for these molecules:Non-polar stationary phase:Column: 5%-phenyl-methylpolysiloxane, HP-5MS, 30m х 0.25mm х 0.50µm, Agilent; starting temperature 40 °C; helium flow rate 0.84 mL/min;Polar stationary phase:Column: polyethylene glycol, HP-INNOWax, 30m х 0.25mm х 0.25µm, Agilent; starting temperature 40 °C; helium flow rate 1.01 mL/min;The analyte solution in methanol (up to 10 analytes in one batch, concentration of each ~0.1 mg/mL) was injected using split injection mode (0.5 μL, 1:20). In some cases, the concentration was increased until high-quality mass spectra of sufficient intensity were obtained.Some of the retention index data was taken from the following source: Karnaeva A. E., Sholokhova A. Y. Validation of the identification reliability of known and assumed UDMH transformation products using gas chromatographic retention indices and machine learning //Chemosphere. – 2024. – V. 362. – P. 142679. https://doi.org/10.26434/chemrxiv-2024-mfbd6 (CC BY 4.0 license)All mass spectra were recorded using a Shimadzu GCMS-TQ8040 (quadrupole mass analyzer, 70 eV electron ionization mode). All mass spectra and retention indices were obtained using pure standards.

A mass spectral database that assists in identifying compunds in life sciences, matabolomics, pharmaceutical research, toxicology, forensic investigations, environemnta analysis, food control, and industry.

(Version 20230306, btmsp files modified May 31, 2023)

Version 4.1 (20230306) of the RKI MALDI-ToF mass spectra database represents the third update of the original database (version 20161027, https://doi.org/10.5281/zenodo.163517). The RKI Database v.4.1 now contains a total of 11055 MALDI-ToF mass spectra from 1599 microbial strains of highly pathogenic (i.e. biosafety level 3, BSL-3) bacteria such as Bacillus anthracis, Brucella melitensis, Yersinia pestis, Burkholderia mallei / pseudomallei and Francisella tularensis as well as a selection of spectra of their close and distant relatives. The database can be used as a reference for the diagnosis of BSL-3 bacteria using proprietary and free software packages for MALDI-ToF MS-based microbial identification. The spectral data are provided as a zip archive (zenodo db 230306.zip) containing the original mass spectra in their native data format (Bruker Daltonics). Please refer to the pdf file (230306-ZENODO-Metadata.pdf) for information on cultivation conditions, sample preparation and details of the spectra acquisition. Please do not try to print this document (>1600 pages!).

Version 20230306 of the RKI database contains for the first time files in the btmsp format (e.g. 2023-May-23-Bacillus-RKI-Database-568.btmsp and others). These files were generated using the MALDI Biotyper software (Bruker Daltonics) and contain a total of 1599 main spectra (msp) from the BSL-3 database in the proprietary data format of the MALDI Biotyper software. *.btmsp files can be imported and used for identification with this software solution. Please refer to the manufacturer's manual for details on importing btmsp files. Note that the btmsp file available in database version 4 is broken and cannot be imported.

The pkf files (230306_ZENODO_30Peaks_0.75.pkf, 230306_ZENODO_45Peaks_0.75.pkf) represent two versions of the MS peak list data in a Matlab compatible format. The latter data can be imported into MicrobeMS, a free Matlab-based software solution developed at the RKI. MicrobeMS can be used for the identification of microorganisms by MALDI-ToF MS and is available at https://wiki-ms.microbe-ms.com.

The RKI mass spectrometry database is updated regularly.

The author would like to thank the following individuals for providing microbial strains and species or mass spectra thereof. Without their help, this work would not have been possible.

• Wolfgang Beyer - University of Hohenheim, Faculty of Agricultural Sciences, Stuttgart, Germany
• Guido Werner - Robert Koch-Institute, Nosocomial Pathogens and Antibiotic Resistances (FG13), Wernigerode, Germany
• Alejandra Bosch - CINDEFI, CONICET-CCT La Plata, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina
• Michal Drevinek - National Institute for Nuclear, Biological and Chemical Protection, Milin, Czech Republic
• Roland Grunow, Daniela Jacob, Silke Klee, Susann Dupke and Holger Scholz - Robert Koch-Institute, Highly Pathogenic Microorganisms (ZBS2), Berlin, Germany
• Jörg Rau - Chemisches und Veterinäruntersuchungsamt Stuttgart, Fellbach, Germany
• Jens Jacob - Robert Koch-Institute, Hospital Hygiene, Infection Prevention and Control (FG14), Berlin, Germany
• Martin Mielke - Robert Koch-Institute, Department 1 - Infectious Diseases, Berlin, Germany
• Monika Ehling-Schulz - Functional Microbiology, Institute of Microbiology, University of Veterinary Medicine, Vienna, Austria
• Armand Paauw - Department of Medical Microbiology, CBRN protection, Universitair Medisch Centrum Utrecht, TNO, Rijswijk, The Netherlands
• Herbert Tomaso – Friedrich-Löffler-Institut (FLI), Federal Research Institute for Animal Health, Jena, Germany
• Gabriel Karner - Karner Düngerproduktion GmbH, Research & Development, Neulengbach, Austria
• Rainer Borriss - Institute of Marine Biotechnology e.V. (IMaB), Greifswald, Germany
• Le Thi Thanh Tam - Division of Plant Pathology and Phyto-Immunology, Plant Protection Research Institute, Hanoi, Socialist Republic of Vietnam
• Xuewen Gao - College of Plant Protection, Nanjing Agricultural University, Key Laboratory of Integrated Management of Crop Diseases and Pests, Nanjing, People’s Republic of China

Public repository of mass spectral data which allows users to search similar spectra on a peak-to-peak basis, on a neutral loss-to-neutral loss basis, or by the m/z value and molecular formula, search chemical compounds by substructures, and keyword search chemical compounds

A library containing spectra upwards of 200,000 chemical compounds. Spectra include metabolites, peptides, contaminants, and lipids. All spectra and chemical structures are examined by professionals.

The NIST Chemistry WebBook provides users with easy access to chemical and physical property data for chemical species through the internet. The data provided in the site are from collections maintained by the NIST Standard Reference Data Program and outside contributors. Data in the WebBook system are organized by chemical species. The WebBook system allows users to search for chemical species by various means. Once the desired species has been identified, the system will display data for the species. Data include thermochemical properties of species and reactions, thermophysical properties of species, and optical, electronic and mass spectra.

Text data of Fig. 2. ESI mass spectrum of transferrin. (A) QTOF mass spectrum. (B) Q mass spectrum.

The mass spectral data (.txt or csv files) can be seen by the MSSJ’s viewing software, which is available at https://ms.wdc-jp.com/wp-content/uploads/Spectrum-Viewer.zip.

Publication Salla et al., 2013. Anal Chim Acta 794, 55, DOI: 10.1016/j.aca.2013.07.014. A mass spectrometry library for shrimp identification was developed with the goal of developing mass spectrometry methods for identifying contaminated seafood using mass spectrometry fingerprinting. Matrix-assisted laser desorption ionization (MALDI) time of flight mass spectrometry was used to identify shrimp at the species level using commercial mass spectral fingerprint matching software (Bruker Biotyper). In the first step, a mass spectrum reference database was constructed from the analysis of six commercially important shrimp species: L. setiferus, F. azticus, S. brevirostris, P. robustus, P. dispar and P. platyceros. In the second step, the reference database was tested using 74 unknown shrimp samples from these six species. Specimens were collected by extractive fishing in the Gulf of Mexico, North Pacific Coast, and North Atlantic Coast and shipped to our location on ice or, for Louisiana shrimp, obtained locally. Correct identification was achieved for 72 of the 74 samples (97%): 72 samples were identified at the species level and 2 samples were identified at the genus level using the manufacturer’s log score specifications. Samples of 1 g of shrimp skeletal muscle were obtained by dissecting a shrimp and then homogenizing at room temperature in 2 mL of nanopure water using a mortar and pestle. The homogenate was then centrifuged at 13,000 rpm for 20 min. The supernatant was removed and further purified using desalting pipette tips. A 4 µl volume of the desalted sample was directly pipetted into 4 µl of 30 mg/ml 2, 5-dihydroxy benzoic acid matrix solution in 1:1 (v/v) ethanol/0.1 % TFA. A 1 µl aliquot of the analyte/matrix mixed solution was spotted onto a stainless steel MALDI target and allowed to dry at room temperature. MALDI-TOF MS measurements were performed on a commercial instrument in positive ion reflectron mode with an accelerating voltage of 25 kV and analyzed in the mass range of 1,000 – 5,000 Da. A minimum of 500 laser shots per sample was used to generate each mass spectrum. MALDI BioTyper 2.0 software (Bruker) was used for the mass spectra fingerprinting [46]. Unknown spectra are identified by comparing their individual peak lists to the mass spectrum database and a matching score based on identified masses and their intensity is used for ranking of the results. The MALDI fingerprinting method for the identification of shrimp species was found to be reproducible and accurate with rapid analysis. Data was collected between October 2011 and May 2012 in the Department of Chemistry at Louisiana State University in Baton Rouge.

Text data of Fig. 6. ESI-QTOF mass spectrum of various CDG-II types. A (control) B (MAN1B1) C (ATP6AP2) D (B4GALT1)

The mass spectral data (.txt or csv files) can be seen by the MSSJ’s viewing software, which is available at https://ms.wdc-jp.com/wp-content/uploads/Spectrum-Viewer.zip.

FragHub v1.2.4

Repository v8

INPUT_FILES downloaded in .mgf, .msp, .json or .csv)

https://systemsomicslab.github.io/compms/msdial/main.html#MS

https://github.com/MassBank/MassBank-data/releases/tag/2024.11

https://mona.fiehnlab.ucdavis.edu/downloads

https://external.gnps2.org/gnpslibrary

https://www.metaboanalyst.ca/docs/Databases.xhtml

https://zenodo.org/records/8287341

https://zenodo.org/records/13911806

OUTPUT_FILES available in .csv, .json or .msp

Integration results:

===================== PARAMETERS =====================

normalize_intensity: ON

remove_peak_above_precursormz: ON

check_minimum_peak_requiered: ON

n_peaks: 3.0

reduce_peak_list: ON

max_peaks: 500.0

remove_spectrum_under_entropy_score: OFF

entropy_score_value: 0.5

keep_mz_in_range: ON

from_mz: 50.0

to_mz: 2000.0

check_minimum_of_high_peaks_requiered: ON

intensity_percent: 5

no_peaks: 2

reset_updates: NO

======================= FILTERED OUT =======================

No peaks list: 0

No smiles, no inchi, no inchikey: 123401

No precursor mz: 9898

No or bad adduct: 4315818

Low entropy score: 0

Minimum peaks not required: 159243

All peaks above precursor mz: 3502

No peaks in mz range: 1006

Minimum high peaks not required: 93163

================== SPECTRUM NUMBER ==================

POS LC Exp: 1056998

NEG LC Exp: 389093

POS LC InSilico: 233623

NEG LC InSilico: 228443

POS GC Exp: 46

NEG GC Exp: 0

POS GC InSilico: 1

NEG GC InSilico: 0

Total: 1908204

================= UNIQUE INCHIKEYS ==================

POS LC Exp: 138374

NEG LC Exp: 80992

POS LC InSilico: 109085

NEG LC InSilico: 105233

POS GC Exp: 43

NEG GC Exp: 0

POS GC InSilico: 1

NEG GC InSilico: 0

TOTAL Unique InChIKeys: 304124

Golm Metabolome Database (GMD) provides public access to custom mass spectral libraries, metabolite profiling experiments as well as additional information and tools. Analytes are subjected to a gas chromatograph coupled to a mass spectrometer, which records the mass spectrum and the retention time linked to an analyte. This collection references GC-MS spectra.

Agilent 1260 Infinity nHPLC stack and Thermo Orbitrap Velos Pro hybrid mass spectrometer were used for analysis of 8-µl samples with a C-18 column (75 μm x 15 cm; 300 Å; 5 μm; Phenomenex). All data were acquired in collision-induced dissociation mode. The phase A was 0.1% FA in ddH2O and phase B was 0.1% formic acid (FA) in 15% ddH2O/85% acetonitrile). The mobile phase gradient was: 10 min at 2% phase B, 90 min at 5-40% phase B, 5 min at 70% phase B and 10 min at 0% phase B. The MS detection included a full scan (m/z 300 -1200) with resolution at 60k and data-dependent MS2 scans on the top abundant ions (15 ions). The MS data files were converted to MzXML using ReAdW (v. 3.5.1). MzXML2 Search was used to create a Mascot generic format file. Data were analyzed using the SEQUEST engine and searches were performed using the Uniref100 database. The peptide ID lists were then further analyzed by Scaffold viewer. The mass spectrometry peptide identifications were filtered by Scaffold. In short, protein probabilities were set to ≥0.99 with false discovery rate