Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or “suspects,” were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

Despite being information rich, the vast majority of untargeted mass spectrometry data are underutilized; most analytes are not used for downstream interpretation or reanalysis after publication. The inability to dive into these rich raw mass spectrometry datasets is due to the limited flexibility and scalability of existing software tools. Here we introduce a new language, the Mass Spectrometry Query Language (MassQL), and an accompanying software ecosystem that addresses these issues by enabling the community to directly query mass spectrometry data with an expressive set of user-defined mass spectrometry patterns. Illustrated by real-world examples, MassQL provides a data-driven definition of chemical diversity by enabling the reanalysis of all public untargeted metabolomics data, empowering scientists across many disciplines to make new discoveries. MassQL has been widely implemented in multiple open-source and commercial mass spectrometry analysis tools, which enhances the ability, interoperability and reproducibility of mining of mass spectrometry data for the research community.

Novel multiple emitting amphiphilic conjugated polythiophene‐coated CdTe quantum dots for picogram level determination of the 2,4,6‐trinitrophenol (TNP) explosive are developed. Four biocompatible sensors, cationic polythiophene nanohybrids (CPTQDs), nonionic polythiophene nanohybrids (NPTQDs), anionic polythiophene nanohybrids (APTQDs), and thiophene copolymer nanohybrids (TCPQDs), are designed using an in situ polymerization method, which shows highly enhanced fluorescence intensity and quantum yield (up to 78%). All sensors are investigated for nitroexplosive detection to provide a remarkable fluorescence quenching for TNP and the quenching efficiency reached 96% in the case of TCPQDs. The fluorescence of the sensors are quenched by TNP through inner filter effect, electrostatic, π−π, and hydrogen bonding interactions. Under optimal conditions, the detection limits of CPTQDs, NPTQDs, APTQDs, and TCPQDs are 2.56, 7.23, 4.12, and 0.56 × 10⁻⁹ m, respectively, within 60 s. More importantly, portable, cost effective, and simple to use paper strips and chitosan film are successfully applied to visually detect as little as 2.29 pg of TNP. The possibility of utilizing a smartphone with a color‐scanning APP in the determination of TNP is also established. Moreover, the practical application of the developed sensors for TNP detection in tap and river water samples is described with satisfactory recoveries of 98.02−107.50%.

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of public MS/MS spectra. Annotations were propagated based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

Actinomycetes have been a cornerstone species for the discovery of bioactive natural products with applications in pharmacotherapy and biotechnology. To expand the experimental evidence of their biosynthetic potential, we collected liquid-chromatography mass spectrometry untargeted metabolomics data on 948 microbial strains, mostly from Actinomycetes . This resulted in nearly two million MS/MS spectra, with an annotation rate of 13.3% corresponding to 2352 annotated molecules. Despite the efforts to link biosynthetic gene clusters to known molecules, most remain uncharacterized. This highlights the need for metabolomic data to bridge the gap between genomic potential and metabolite production. Although many unannotated spectra might correspond to different ion forms of the same molecule, the large amount of unknown molecules present in these datasets indicates that a significant number of natural products remain to be discovered, even within one of the most thoroughly studied sets of organisms. We provide a large metabolomics dataset as a public resource for data mining of microbial molecules and highlight its value by demonstrating the detection of edapochelins, recently discovered non-ribosomal peptides.

Over the past several decades, large efforts have been made to diagnose and overcome prostate cancer. Among all screening methods, the measurement of prostate-specific antigen (PSA) threshold has been stood out and contributed to diagnose prostate cancer (PCa) in a large number of men. Nevertheless, the early detection of prostate carcinoma and its focal imaging is remaining crucial to diminish the elevated number of PCa-related deaths. Because of the multifocal behavior of PCa development, a whole gland ablation has been practiced during previous years. Furthermore, there is an evidence of the likelihood of high-risk PCa that proves once again the importance of early diagnosis and accurate staging of the disease. So far, numerous advanced spectroscopic methods with different approaches have been reported as the alternative tools to conventional techniques of PCa diagnosis and imaging. In this review, we introduce innovative emerging techniques utilizing spectroscopic methods such as photoluminescence, surface-enhanced Raman spectroscopy, and surface plasmon resonance to measure the ultralow level of PSA. In addition, we review novel and alternative approaches of diagnosis such as imaging methods through photoluminescence, magnetic resonance imaging, and positron emission tomography.