A critical look at how spectral denoising affects compound identification and molecular network reliability.
A study found that applying a standard 5% intensity cutoff was often too aggressive, resulting in the loss of nearly 50% of the ions explained by SIRIUS.
N. Dalla Valle et al. Anal. Chem. (2025) doi: 10.1021/acs.analchem.5c02109
⬇️ Downloadable Libraries: You can now download our integrated spectral library with curated spectra from GNPS, MassBank and MsnLib.
⬆️ Transformation Product Database Export: We now offer the export of the entire transformation product database generated with BioTransformer during your custom database import, as users love the simplicity of generating transformation products within SIRIUS.
The largest gathering for laboratory technology and analysis is just days away, and we are geeting ready to meeting you in Munich! See SIRIUS 6 in action—from automated LC-MS/MS preprocessing to de novo structure generation of unknowns.
Offshore produced water discharges introduce over 240 billion liters of complex chemical mixtures into the marine environment annually. In a case study using produced water from North Sea offshore oil platforms, researchers demonstrated that traditional monitoring significantly underestimates the persistence of discharged chemicals. They introduce a novel analytical framework using advanced non-target analysis and computational workflows, including SIRIUS to highlight a significant “hidden burden” of persistent pollutants.
M. T. Møller et al. Environ. Sci. Technol. (2025) doi: 10.1021/acs.est.5c08802
Stop by our booth to see SIRIUS in action. Whether you are tackling drug discovery, E&L detection, PFAS analysis, or natural product dereplication, our latest machine learning models are designed to accelerate your structure elucidation workflows.
The maturation of the gut microbiome during the first six months of life is a foundational process, playing a key role in metabolic programming and training of the immune system, but these patterns remain critically underexplored in populations from low- and middle-income countries. To address this gap, an observational, longitudinal study profiled the developing gut microbiome and metabolome in Bangladesh using a multi-omics approach. Systematic classification and metabolite annotation was achieved using SIRIUS. The overall aim was to understand how maternal and environmental factors—specifically delivery mode, maternal milk composition, and household water treatment—shape this foundational postnatal development.
Read the full blog post.
K. E. Kvitne et al. Cell Host Microbe (2025) doi: 10.1016/j.chom.2025.11.002
In pharmacology, one of the most significant challenges is the variability in how patients respond to the same drug. While factors like genetics and lifestyle are known to play a role, emerging research points to a hidden player: the human gut microbiota. This vast community of trillions of microbes is an active participant in our health, influencing everything from nutrient absorption to the efficacy of our medications. Using advanced computational tools like SIRIUS to analyze mass spectrometry data, researchers investigated how gut microbiota alter the chemical structure of GPCR drugs.
Q. Wu et al. Nat. Chem. (2025) doi: 10.1038/s41557-025-01789-w
SIRIUS plays a significant role in prioritization strategies for non-target screening in environmental samples. Its primary function is to generate molecular fingerprints from MS/MS data, which are then used for compound identification or toxicity prediction.
A. Torres-Agullo et al. J. Chromatogr. A (2025) doi: 10.1016/j.chroma.2025.465944
Although direct structural information may not always be available, specific structural details, such as the presence of function groups, can be obtained from MS/MS spectra using SIRIUS. These molecular fingerprints serve as crucial inputs for other predictive models, such as toxicity predictions, even when the exact identity of a compound is unknown.
A. Canchola et al. Environ. Int. (2025) doi: 10.1016/j.envint.2025.109404
In a biodiverse ecosystem, it’s often assumed that plants have safety in numbers—that a mix of species will confuse pests and dilute disease pressure, allowing individual plants to save energy on defences and focus on growth. But is this ecological truism always the case? A recent study from the long-running Jena Experiment uses untargeted metabolomics and SIRIUS for feature annotation and compound class prediction. They found that for many plants in a diverse community it is less about relaxing their defences and more about adapting to intense competition for light and nutrients.
L. Bassi et al. New Phytol. (2025) doi: 10.1111/nph.20434
