Biology subjects

Bekker-Jensen, D.

Publications and source records attributed to Bekker-Jensen, D..

3 recordsLinked to original sources

bioRxiv2026

Pairing Data Independent Acquisition and High-Resolution Full Scan for Fast Urinary Tract Infection Diagnosis

BackgroundRapid and accurate identification of urinary tract infection (UTI) pathogens is critical for effective treatment and combating antimicrobial resistance. Conventional culture-based diagnostics are slow, and standard tandem mass spectrometry workflows are resource-intensive. MethodsWe present a proof-of-concept workflow that integrates high-resolution data-independent acquisition (DIA) MS/MS on the Thermo Scientific Orbitrap Astral with MS1-only spectra from the Orbitrap Exploris 480. DIA data establish a reference panel of pathogen-specific peptides, which are then identified in MS1 spectra from urine samples. Machine learning models trained on these matched MS1 features were used to classify eight common uropathogens and non-infected controls across synthetic inoculations, pure cultures, and clinical patient samples. Model development employed a one-vs-all Random Forest (Ranger) framework with nested cross-validation for feature selection and hyperparameter tuning, followed by evaluation on an independent held-out external patient cohort. ResultsThe approach accurately distinguished bacterial species in both controlled inoculated samples and clinical patient samples. Using repeated nested cross-validation, the model achieved a mean Matthews Correlation Coefficient (MCC) of 0.88, indicating robust classification performance across resampled training partitions. Performance generalized to an independent patient cohort, achieving an MCC of 0.822, confirming the models ability to maintain predictive accuracy under external validation. ConclusionsThis proof-of-concept demonstrates that pairing DIA-derived peptide panels with MS1-only data acquired on a cost-effective instrument suitable for routine analysis, enables rapid, culture-free identification of UTI pathogens. The method provides a scalable, high-throughput platform suitable for clinical applications and establishes a foundation for broader biomarker discovery and potential quantitative workflows. Key Points- DIA-derived peptide panels enable pathogen detection using MS1-only measurements. - Machine learning classifies eight common uropathogens covering 84% of infections. - MS1-only workflows enable culture-free pathogen identification of 300 samples/day.

bioinformatics↗

bioRxiv2023

High-throughput and scalable single cell proteomics identifies over 5000 proteins per cell

The emergence of mass spectrometry (MS)-based single-cell proteomics (SCP) promise to revolutionize the study of cellular biology and biomedicine by providing an unparalleled view of the proteome in individual cells. Despite its groundbreaking potential, SCP is nascent and faces challenges including limited sequence depth, throughput, and reproducibility, which have constrained its broader utility. This study introduces key methodological advances, which considerably improve the sensitivity, coverage and dependability of protein identification from single cells. We developed an almost lossless SCP workflow encompassing sample preparation to MS analysis, doubling the number of identified proteins from roughly 2000 to over 5000 in individual HeLa cells. A comprehensive evaluation of analytical software tools, alongside strict false discovery rate (FDR) controls solidified the reliability of our results. These enhancements also facilitated the direct detection of post-translational modifications (PTMs) in single cells, negating the need for enrichment and thereby simplifying the analytical process. Although throughput in MS remains a challenge, our study demonstrates the feasibility of processing up to 80 label-free SCP samples per day. Moreover, an optimized tissue dissociation buffer enabled effective single cell disaggregation of drug-treated cancer cell spheroids, refining the overall proteomic analysis. Our workflow sets a new benchmark in SCP for sensitivity and throughput, with broad applications ranging from the study of cellular development to disease progression and the identification of cell type-specific markers and therapeutic targets.

systems biology↗

bioRxiv2018

Alternative translation initiation generates a functionally distinct isoform of the stress-activated kinase MK2

Shaping of the proteome by alternative translation is an important mechanism of post-transcriptional gene regulation. It can lead to the expression of multiple protein isoforms originating from the same mRNA. Here we show that a novel, abundant and long isoform of the stress/p38MAPK-activated kinase MK2, a key regulator of transcription, migration, death signaling and post-transcriptional gene regulation, is constitutively translated from an alternative CUG translation initiation start site located in the 5'UTR of its mRNA. GC-rich sequences and putative G-quadruplex structures influence the usage of that codon as a translation initiation start site and the RNA helicase eIF4A1 is needed to ensure alternative isoform translation. We recapitulated the usage of the alternative start codon and determined the molecular properties of the short and a long MK2 isoforms. Phenotypically, only the short isoform phosphorylated Hsp27, supported migration and stress-induced immediate early gene (IEG) expression. Interaction profiling by quantitative mass-spectrometry revealed short isoform-specific binding partners that were associated with migration. In contrast, the long isoform contains additional putative phosphorylation sites in its unique N-terminus. In sum, our data reveal a longer and previously non-described isoform of MK2 with distinct physiological properties originating from alternative translation.

molecular biology↗