Data-independent acquisition (DIA) in liquid chromatography tandem mass spectrometry (LC-MS/MS) provides more comprehensive untargeted acquisition of molecular data. Here we provide an open-source software pipeline, MS-DIAL, to demonstrate how DIA improves simultaneous identification and quantification of small molecules by mass spectral deconvolution. For reversed phase LC-MS/MS, our program with an enriched LipidBlast library identified total 1,023 lipid compounds from nine algal strains to highlight their chemotaxonomic relationships.

Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.

Currently, most hydrogel sensors require an isolation layer to prevent the current from damaging the skin. However, the mismatch of the mechanical property between the isolation layer and the hydrogel sensor may affect the accuracy of the sensing. Herein, a bilayer hydrogel sensor consisted of a nonconductive layer and a conductive layer, which were prepared through twice freeze–thawing methods. The nonconductive layer which could directly come in contact with the skin was composed of polyvinyl alcohol (PVA) and glycerin (GL), and the conductive layer for conducting current and perceiving strain was composed of PVA, GL, and polyaniline (PAni). Unlike ions, PAni was difficult to diffuse in the hydrogels, which had two layers and exhibited significant difference in conductivity. When the voltage was applied, the bilayer hydrogel could protect the skin from irritation and injury. More importantly, the mechanical property of the two layers was close, enabling the bilayer hydrogel to detect strain effectively. Compared with a single-layer hydrogel sensor, the response and recovery time of the bilayer hydrogel were reduced by 14.8 and 8%, and the accuracy was improved by 32.1%. This unique strategy provides novel inspiration for the development of fast responsive and skin-protective hydrogel strain sensors.

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Systematic analysis and interpretation of the large number of tandem mass spectra (MS/MS) obtained in metabolomics experiments is a bottleneck in discovery-driven research. MS/MS mass spectral libraries are small compared to all known small molecule structures and are often not freely available. MS2Analyzer was therefore developed to enable user-defined searches of thousands of spectra for mass spectral features such as neutral losses, m/z differences, and product and precursor ions from MS/MS spectra in MSP/MGF files. The software is freely available at . As the reference query set, 147 literature-reported neutral losses and their corresponding substructures were collected. This set was tested for accuracy of linking neutral loss analysis to substructure annotations using 19 329 accurate mass tandem mass spectra of structurally known compounds from the NIST11 MS/MS library. Validation studies showed that 92.1 ± 6.4% of 13 typical neutral losses such as acetylations, cysteine conjugates, or glycosylations are correct annotating the associated substructures, while the absence of mass spectra features does not necessarily imply the absence of such substructures. Use of this tool has been successfully demonstrated for complex lipids in microalgae.