Biology subjects

Stejskal, K.

Publications and source records attributed to Stejskal, K..

13 recordsLinked to original sources

bioRxiv2026

The SPARK complex forms the molecular basis of vertebrate fertilization

Fertilization requires gamete recognition and membrane fusion, yet the molecular basis of this process in vertebrates remains unknown. Here we identify SPARK (sperm protein assembly and receptor-binding key), a conserved multi-protein complex that integrates all known sperm fertilization factors, including TMEM81-IZUMO1-SPACA6 and DCST1/2, together with two newly identified components, TMDD1 and FAM187A. SPARK subunits are mutually dependent for stability in mature sperm, and disruption of any single component causes male sterility in zebrafish and mice. Incubating zebrafish sperm with soluble egg receptor Bouncer partially rescues fertilization of Bouncer-deficient eggs in a SPARK-dependent manner, consistent with egg receptor binding priming the complex for fusion. Thus, we propose SPARK as a con-served molecular machine that couples gamete recognition to membrane fusion.

developmental biology↗

bioRxiv2025

Hierarchical assembly and functional resilience of the mammalian RNA exosome

Most eukaryotic proteins assemble into multisubunit complexes that coordinate essential cellular functions, yet the principles governing their assembly and proteostatic control remain largely undefined. Here, we systematically dissect the cellular assembly and functional organization of the RNA exosome, an essential ribonucleolytic complex, using an inducible dual-guide CRISPR/Cas9 system in mouse embryonic stem cells. We reveal a sequential assembly pathway where Exosc2, Exosc4, and Exosc7 initiate complex formation, facilitating the incorporation of barrel and cap subunits in a defined hierarchy. Unlike other structural subunits, the terminally incorporated cap subunit Exosc1 is dispensable for cell viability, revealing a modular, functionally resilient architecture. We demonstrate that orphan subunits are selectively degraded via the ubiquitin-proteasome system, enforcing stringent quality control over RNA exosome biogenesis. These findings establish a framework for decoding the assembly logic of essential macromolecular machines and uncover previously unrecognized plasticity in the composition and function of the RNA exosome.

molecular biology↗

bioRxiv2024

Breaking Barriers in Crosslinking Mass Spectrometry: Enhanced Throughput and Sensitivity with the Orbitrap Astral Mass Analyzer

The advancement of crosslinking mass spectrometry (CLMS) has significantly enhanced the ability to study protein-protein interactions and complex biological systems. This study evaluates the performance of the Orbitrap Astral and Eclipse mass spectrometers in CLMS workflows, focusing on the identification of low-abundance crosslinked peptides. The comparison employed consistent liquid chromatography setups and experimental conditions, using Cas9 crosslinked with PhoX and DSSO as quality control samples. Results demonstrated that the Astral analyzer outperformed the Eclipse, achieving over 40% more unique residue pairs (URP) due to its superior sensitivity and dynamic range, attributed to its multi-reflection time-of-flight analyzer and nearly lossless ion transmission. Additionally, the study revealed that single higher-energy collisional dissociation (HCD) fragmentation methods significantly outperformed stepped HCD methods on the Astral, while the Eclipse maintained similar performance across both approaches. Gradient optimization experiments further highlighted the impact of separation times on crosslink identifications, with longer gradients yielding higher identification rates. Collectively, this work underscores the importance of instrumentation choice, fragmentation strategies, and method optimization in maximizing CLMS performance for protein interaction studies.

biochemistry↗

bioRxiv2024

Urinary multi-omics reveal non-invasive diagnostic biomarkers in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the kidney malignancy with the highest incidence and mortality rates. Despite the high patient burden, there are no biomarkers for rapid diagnosis and public health surveillance. Urine would be an ideal source of ccRCC biomarkers due to the low invasiveness, easy accessibility, and the kidneys intrinsic role in filtering urine. In the present work, by combining proteomics, lipidomics and metabolomics, we detected urogenital metabolic dysregulation in ccRCC patients with increased lipid metabolism, altered mitochondrial respiration signatures and increased urinary lipid content. Importantly, we identify three early-stage diagnostic biomarkers for ccRCC in urine samples: Serum amyloid A1 (SAA1), Haptoglobin (HP) and Lipocalin 15 (LCN15). We further implemented a parallel reaction monitoring mass spectrometry protocol for rapid and sensitive detection of SAA1, HP and LCN15 and combined all three proteins into a diagnostic UrineScore. In our discovery cohort, this score had a performance accuracy of 96% in receiver operating characteristic curve (ROC) analysis for classification of ccRCC versus control cases. Our data identifies tractable and highly efficacious urinary biomarkers for ccRCC diagnosis and serve as a first step towards the development of more rapid and accessible urinary diagnostic platforms.

cancer biology↗

bioRxiv2024

A multi-year longitudinal harmonization of quality controls in mass spectrometry proteomics core facilities

Quality control procedures play a pivotal role in ensuring the reliability and consistency of data generated in mass spectrometry-based proteomics laboratories. However, the lack of standardized quality control practices across laboratories poses challenges for data comparability and reproducibility. In response, we conducted a harmonization study within proteomics laboratories of the Core for Life alliance with the aim to establish a common quality control framework, which facilitates comprehensive quality assessment and identification of potential sources of performance drift. Through collaborative efforts, we developed a consensus quality control standard for longitudinal assessment and we adopted a common processing software. We generated a 4-year longitudinal dataset from multiple instruments and laboratories, which enabled us to assess intra- and inter-laboratory variability, to identify causes of performance drift, and to establish community reference values for several quality control parameters. Our study enhances data comparability and reliability and fosters a culture of collaboration and continuous improvement within the proteomics community to ensure the integrity of proteomics data.

biochemistry↗

bioRxiv2024

Metabolic enzymes moonlight as selective autophagy receptors to protect plants against viral-induced cellular damage

AbstractRNA viruses co-opt the host endomembrane system and organelles to build replication complexes for infection. How the host responds to these membrane perturbations is poorly understood. Here, we explore the autophagic response of Arabidopsis thaliana to three viruses that hijack different cellular compartments. Autophagy is significantly induced within systemically infected tissues, its disruption rendering plants highly sensitive to infection. Contrary to being an antiviral defense mechanism as previously suggested, quantitative analyses of the viral loads established autophagy as a tolerance pathway. Further analysis of one of these viruses, the Turnip Crinkle Virus (TCV) that hijack mitochondria, showed that despite perturbing mitochondrial integrity, TCV does not trigger a typical mitophagy response. Instead, TCV and Turnip yellow mosaic virus (TYMV) infection activates a distinct selective autophagy mechanism, where oligomeric metabolic enzymes moonlight as selective autophagy receptors and degrade key executors of defense and cell death such as EDS1. Altogether, our study reveals an autophagy-regulated metabolic rheostat that gauges cellular integrity during viral infection and degrades cell death executors to avoid catastrophic amplification of immune signaling.

plant biology↗

bioRxiv2023

A conserved fertilization complex of Izumo1, Spaca6, and Tmem81 mediates sperm-egg interaction in vertebrates

Fertilization, the fusion of sperm and egg, is essential for sexual reproduction. While several proteins have been demonstrated to be essential for the binding and fusion of gametes in vertebrates, the molecular mechanisms driving this key process are poorly understood. Here, we performed a protein interaction screen using AlphaFold-Multimer to uncover protein-protein interactions in fertilization. This screen resulted in the prediction of a trimeric complex composed of the essential fertilization factors Izumo1 and Spaca6, and Tmem81, a protein previously not implicated in fertilization. We show that Tmem81 is a conserved, testis-expressed transmembrane protein that is evolutionarily related to Izumo1 and Spaca6 and is essential for male fertility in fish and mice. Consistent with trimer formation in vivo, zebrafish izumo1-/-, spaca6-/-, and tmem81-/- mutants exhibit the same sperm-egg binding defect and show co-depletion of all three proteins in sperm. Moreover, we provide experimental evidence that Izumo1, Spaca6, and Tmem81 interact in zebrafish sperm. Strikingly, the Izumo1-Spaca6 interaction is predicted to form a cleft that serves as a binding site for Bouncer, the only identified egg protein essential for fertilization in zebrafish. Together, these results provide compelling evidence for a conserved sperm factor complex in vertebrates that forms a specific interface for the sperm-egg interaction required for successful fertilization.

developmental biology↗

bioRxiv2023

Mast cell-derived BH4 is a critical mediator of postoperative pain

Postoperative pain affects most patients after major surgery and can transition to chronic pain. Here, we discovered that postoperative pain hypersensitivity correlated with markedly increased local levels of the metabolite BH4. Gene transcription and reporter mouse analyses after skin injury identified neutrophils, macrophages and mast cells as primary postoperative sources of GTP cyclohydrolase-1 (Gch1) expression, the rate-limiting enzyme in BH4 production. While specific Gch1 deficiency in neutrophils or macrophages had no effect, mice deficient in mast cells or mast cell-specific Gch1 showed drastically decreased postoperative pain after surgery. Skin injury induced the nociceptive neuropeptide substance P, which directly triggers the release of BH4-dependent serotonin in mouse and human mast cells. Substance P receptor blockade substantially ameliorated postoperative pain. Our findings underline the unique position of mast cells at the neuro-immune interface and highlight substance P-driven mast cell BH4 production as promising therapeutic targets for the treatment of postoperative pain.

immunology↗

bioRxiv2022

Wide Window Acquisition and AI-based data analysis to reach deep proteome coverage for a wide sample range, including single cell proteomic inputs

A comprehensive proteome map is essential to elucidate molecular pathways and protein functions. Although great improvements in sample preparation, instrumentation and data analysis already yielded impressive results, current studies suffer from a limited proteomic depth and dynamic range therefore lacking low abundant or highly hydrophobic proteins. Here, we combine and benchmark advanced micro pillar array columns ({micro}PAC) operated at nanoflow with Wide Window Acquisition (WWA) and the AI-based CHIMERYS search engine for data analysis to maximize chromatographic separation power, sensitivity and proteome coverage. Our data shows that {micro}PAC columns clearly outperform classical packed bed columns boosting peptide IDs by up to 140%. Already at classical narrow isolation widths CHIMERYS boosted ID rates by a factor of 2.6 compared to the conventional search engine MS Amanda 2.0. By combining CHIMERYS with WWA, even a 4.6-fold increase in ID rates could be achieved. Using our optimized workflow, we were further able to identify more than 10,000 proteins from a single 2 h gradient shotgun analysis. We further investigated the applicability of WWA for single cell inputs and found that the choice of the optimal isolation window width depends on sample input and complexity. Using a short 5.5 cm column and very high flow rates during loading and column equilibration we improved sample throughput to [~]100 samples per day while maintaining high protein ID numbers. We believe that this is especially important for the single cell field where throughput is one of the most limiting factors. Finally, we applied our optimized workflow on immunoprecipitations of Smarca5/SNF2H and found 32 additional interaction partners compared to the original workflow utilizing a packed bed column. These additional interaction partners include previously described interaction partners of Smarca5 like Baz2b as well as undescribed interactors including Arid1a, which is also involved in chromatin remodeling and has been described as key player in neurodevelopmental and malignant disorders.

biochemistry↗

bioRxiv2021

Analysis of 8000 proteins and reduced carry over significantly increase the throughput of single-shot proteomics

In the field of LC-MS based proteomics, increases in sampling depth and proteome coverage have mainly been accomplished by rapid advances in mass spectrometer technology. The comprehensiveness and quality of data that can be generated do however also depend on the performance provided by nano liquid chromatography (nanoLC) separations. Proper selection of reversed-phase separation columns can be important to provide the MS instrument with peptides at the highest possible concentration and separated at the highest possible resolution. In the current contribution, we evaluate the use of prototype generation 2 PAC nanoLC columns which use C18 functionalized superficially porous micro pillars as a stationary phase. When comparing to traditionally used fully porous silica stationary phases, more precursors could be characterized when performing single shot data-dependent LC-MS/MS analyses of a human cell line tryptic digest. Up to 30% more protein groups and 60% more unique peptides were identified for short gradients (10 min) and limited sample amounts (10-100 ng of cell lysate digest). With LC-MS gradient times of 10, 60, 120 and 180 min, we respectively identified 2252, 6513, 7382 and 8174 protein groups with 25, 500, 1000 and 2000 ng of sample loaded on column. Reduction of sample carry over to the next run (up to 2 to 3%) and decreased levels of methionine oxidation (up to 3-fold) were identified as additional figures of merit. When analyzing a disuccinimidyl dibutyric urea (DSBU) crosslinked synthetic library, 29 to 59 more unique crosslinked peptides could be identified at a experimentally validated false discovery rate (FDR) of 1-2%.

biochemistry↗

bioRxiv2021

Quantitative accuracy and precision in multiplexed single-cell proteomics.

Single-cell proteomics workflows have considerably improved in sensitivity and reproducibility to characterize yet unknown biological phenomena. With the emergence of multiplexed single-cell proteomics, studies increasingly present single-cell measurements in conjunction with an abundant congruent carrier to improve precursor selection and enhance identifications. While these extreme carrier spikes are often >100-times more abundant than the investigated samples, undoubtedly the total ion current increases, but quantitative accuracy possibly is affected. We here focus on narrowly titrated carrier spikes (i.e., <20x) and assess their elimination for comparable sensitivity at superior accuracy. We find that subtle changes in the carrier ratio can severely impact measurement variability and describe alternative multiplexing strategies to evaluate data quality. Lastly, we demonstrate elevated replicate overlap while preserving acquisition throughput at improved quantitative accuracy with DIA-TMT and discuss optimized experimental designs for multiplexed proteomics of trace samples. This comprehensive benchmarking gives an overview of currently available techniques and guides conceptualizing the optimal single-cell proteomics experiment.

biochemistry↗

bioRxiv2021

Ultra-sensitive nanoLC-MS using second generation micro pillar array LC technology with Orbitrap Exploris 480 and FAIMS PRO to enable single cell proteomics

In the light of the ongoing single-cell revolution, scientific disciplines are combining forces to retrieve as much relevant data as possible from trace amounts of biological material. For single cell proteomics, this implies optimizing the entire workflow from initial cell isolation down to sample preparation, liquid chromatography (LC) separation, mass spectrometer (MS) data acquisition and data analysis. To demonstrate the potential for single cell and limited sample proteomics, we report on a series of benchmarking experiments where we combine LC separation on a new generation of micro pillar array columns with state-of-the-art Orbitrap MS/MS detection and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS). This dedicated limited sample column has a reduced cross section and micro pillar dimensions that have been further downscaled (inter pillar distance and pillar diameter by a factor of 2), resulting in improved chromatography at reduced void times. A dilution series of a HeLa tryptic digest (5-0.05 ng/L) was used to explore the sensitivity that can be achieved. Comparative processing of the MS/MS data with Sequest HT, MS Amanda, Mascot and SpectroMine pointed out the benefits of using Sequest HT together with INFERYS when analyzing sample amounts below 1 ng. 2855 protein groups were identified from just 1 ng of HeLa tryptic digest hereby increasing detection sensitivity as compared to a previous contribution by a factor well above 10. By successfully identifying 1486 protein groups from as little as 250 pg of HeLa tryptic digest, we demonstrate outstanding sensitivity with great promise for use in limited sample proteomics workflows.

cell biology↗

bioRxiv2021

Comparative proteome signatures of ultra-low input samples by TMT multiplexed Data-Independent Acquisition

Single cell transcriptomics has revolutionized our understanding of basic biology and disease. Since transcript levels often do not correlate with protein expression, it is crucial to complement transcriptomics approaches with proteome analyses at single cell resolution. Despite continuous technological improvements in sensitivity, mass spectrometry-based single cell proteomics ultimately faces the challenge of reproducibly comparing the protein expression profiles of thousands of individual cells. Here, we combine two hitherto opposing analytical strategies, DIA and Tandem-Mass-Tag (TMT)-multiplexing, to generate highly reproducible, quantitative proteome signatures from ultra-low input samples. While conventional, data-dependent shotgun proteomics (DDA) of ultra-low input samples critically suffers from the accumulation of missing values with increasing sample-cohort size, data-independent acquisition (DIA) strategies do usually not take full advantage of isotope-encoded sample multiplexing. We developed a novel, identification-independent proteomics data-analysis pipeline that allows to quantitatively compare DIA-TMT proteome signatures across hundreds of samples independent of their biological origin, and to identify cell types and single protein knockouts. We validate our approach using integrative data analysis of different human cell lines and standard database searches for knockouts of defined proteins. These data establish a novel and reproducible approach to markedly expand the numbers of proteins one detects from ultra-low input samples, such as single cells.

biochemistry↗