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Deforce, D.

Publications and source records attributed to Deforce, D..

At least 19 recordsLinked to original sources

Recombinase polymerase amplification: characterization and mitigation of undescribed multimeric artefacts

Recombinase polymerase amplification (RPA) enables rapid nucleic acid testing in low-resource environments, but poorly characterized byproducts can compromise assay specificity and cause false-positive results. Here, we amplified the thirteen original CODIS core loci and Amelogenin to characterize recurrent RPA artefacts and establish conditions that reduce their formation. First, RPA products were analyzed for two reference samples by Oxford Nanopore Technologies sequencing. This revealed two distinct classes of multimeric products: primer multimers and amplicon multimers, consisting of repeated primer or amplicon sequences, respectively. Individual artefacts contained up to 281 primer copies or 22 amplicon copies, demonstrating the extensive range of these products. Next, we performed an optimization study to evaluate the effects of reaction temperature and reagent concentrations at two representative loci, D3S1358 and D5S818. Among the conditions tested, temperature had the most pronounced effect. Reducing the temperature from 42{degrees}C to 34{degrees}C increased the relative target amplicon fraction from 15% to 83% for D3S1358 and from 84% to 98% for D5S818, while maintaining or increasing absolute target concentration. Lower primer concentrations and higher T4 UvsX concentrations also reduced multimer formation, although lower primer concentrations reduced target yield and caused allelic dropout. Finally, amplification at 34{degrees}C was evaluated across all fourteen loci by sequencing. Relative to 42{degrees}C, the target read fraction increased by more than 5 percentage points for 7/14 loci in one reference sample and 9/14 loci in the other, with the largest improvements at multimer-prone loci. These findings identify multimers as an important class of RPA artefacts and establish reaction temperature and T4 UvsX concentration as promising conditions to improve RPA specificity.

biochemistry↗

Palaeoproteomic deconvolution of physical and genetic collagen mixtures

Species identification in palaeoproteomics relies on genome-derived protein sequences which are often poor-quality, and lacks tools to cope with multi-species samples. Here, we address both challenges through the analysis of physical and genetic mixtures. Species that are absent from our database are considered a genetic mixture, i.e. a patchwork of peptides from closely related species. Inversely, various overlapping peptide stretches allow us to resolve complex physical mixtures. This is benchmarked by analysing physical mixtures of modern bone fragments, including genetic mixtures. We illustrate the impact of our approach via a rapid and high-throughput analysis of >2500 bone fragments, revealing the Eemian-era faunal environment around Scladina Cave, including the first Palaeoloxodon antiquus identified at this site. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/732552v1_ufig1.gif" ALT="Figure 1"> View larger version (67K): org.highwire.dtl.DTLVardef@a33296org.highwire.dtl.DTLVardef@4e4b85org.highwire.dtl.DTLVardef@402290org.highwire.dtl.DTLVardef@9d35b6_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

Focus on the edges: a biomolecular network of histone PTMs, metabolites and proteins unveils functional entanglement in AML

The cell phenotype is not a direct manifestation of the genotype but rather a product of cellular history and the environmental context. However, individual biomolecules cannot change independently and show coordinated behavior. To study this in acute myeloid leukemia (AML), we built a unique multi-omics biomolecular network made from proteins, metabolites and histone posttranslational modifications (hPTMs) sequentially extracted from each cell pellet. Edges between the nodes are measured directly using 400 LC-MSMS runs that cover 18 AML cell lines. We provide a novel conceptual framework to illustrate the different classes of functional entanglement between and within omics layers and present the data in three interactive data browsers to allow full community access. To help navigate the network, we approach it from the perspective of two biomolecular targets, i.e. CD34 and the epigenetic mark Histone H3 lysine 27 trimethylation (H3K27me3). Now, this easily accessible biomolecular network serves as a starting point for building and testing hypotheses and streamlining drug development, in the process positioning biomolecular associations center stage in understanding phenotypic complexity.

cancer biology↗

LFQ Benchmark Dataset - Generation Beta: Assessing Modern Proteomics Instruments and Acquisition Workflows with High-Throughput LC Gradients

Recent advances in liquid chromatography-mass spectrometry (LC-MS) have accelerated the adoption of high-throughput workflows that deliver deep proteome coverage using minimal sample amounts. This trend is largely driven by clinical and single-cell proteomics, where sensitivity and reproducibility are essential. Here, we extend our previous benchmark dataset (PXD028735) using next-generation LC-MS platforms optimized for rapid proteome analysis. We generated an extensive DDA/DIA dataset using a human-yeast-E. coli hybrid proteome. The proteome sample was distributed across multiple laboratories together with standardized analytical protocols specifying two short LC gradients (5 and 15 min) and low sample input amounts. This dataset includes data acquired on four different platforms, and features new scanning quadrupole-based implementations, extending coverage across different instruments and acquisition strategies. Our comprehensive evaluation highlights how technological advances and reduced LC gradients may affect proteome depth, quantitative precision, and cross-instrument consistency. The release of this benchmark dataset via ProteomeXchange (PXD070049 and PXD071205), allows for the acceleration of cross-platform algorithm development, enhance data mining strategies, and supports standardization of short-gradient, high-throughput LC-MS-based proteomics.

bioinformatics↗

Mechanistically Interpretable Toxicity Prediction Through Multimodal Integration of Structure and Transcriptomics

Advances in computational toxicology increasingly emphasize the need for models that deliver both scalable predictive performance and mechanistic insights. Nevertheless, most approaches fall short of capturing the underlying mechanisms that drive toxicity. Herein, we describe a scalable multimodal modeling framework that integrates chemical fingerprints with high-throughput transcriptomic dose-response profiles across three human cell lines to predict activity for 41 curated Tox21 assay endpoints. Using gradient-boosted decision trees and nested compound-aware cross-validation, 13 assays achieved robust performance (mean AUPRC > 0.75), spanning nuclear receptor signaling, stress-response pathways, and xenobiotic metabolism. SHAP-based feature attribution analysis showed that predictions depend on both structural motifs and transcriptional programs, in a manner consistent with established mechanistic relationships between chemical structure, nuclear receptor biology, and adaptive cellular responses. These findings illustrate how structure-HTTr dose-response signature integration enables models that are accurate and mechanistically grounded, shifting computational toxicology toward transparent and biologically informed chemical risk evaluation.

bioinformatics↗

Palaeoproteomics reveals bovine carcass processing with 6,000-year-old flint tools

Lithic tools are the most abundant cultural artefacts found at prehistoric archaeological sites. Through their study, we can understand essential activities such as hunting, processing of animal carcasses and plant materials, and working of resources such as ochre and bone, as well as broader technological and cultural practices. For the first time, proteomics was applied alongside use-wear and optical microscopy residue analyses, enabling the identification of bovine, plant, and human proteins on faceted tools from the Mesolithic-Neolithic site of Bazel-Sluis, Belgium. This retrieval of identifiable protein from an area with poor organic preservation demonstrates wide-reaching potential for archaeological research, opening a new avenue of investigation into prehistoric lifeways and adding to the growing corpus of evidence accessible through palaeoproteomics. A workflow for future analyses is suggested, based on our integrated sampling strategy requiring no additional tool manipulations.

paleontology↗

Profiling histone post-translational modifications to identify signatures of epigenetic drug response in T-cell acute lymphoblastic leukemia

Epigenetic modifications are dynamic and reversible, making them attractive targets for therapeutic intervention in cancer. Although several epigenetic drugs (epidrugs) have been clinically approved, their application in T-cell acute lymphoblastic leukemia (T-ALL) remains limited, and predictive biomarkers of response are lacking. Here, we present a mass spectrometry (MS)-based pharmacoepigenetic approach to profile histone post-translational modifications (hPTMs) to identify signatures associated with epidrug sensitivity in T-ALL. Baseline hPTM landscapes were previously established by our group for 21 T-ALL cell lines using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we treated these cell lines with a panel of nine epidrugs including anthracyclines, histone deacetylase inhibitors, and DNA methyltransferase inhibitors. Correlation of cell viability data with hPTM levels revealed distinct hPTM signatures linked to sensitivity for each drug class. These signatures were subsequently evaluated in T-ALL patient-derived xenograft (PDX) models. However, we our analysis revealed substantial discepancies in hPTM sensitivity signatures compared to those observed in vitro. Co-variation network analysis highlighted divergence in hPTM-hPTM correlation between the two models, underscoring limitations of cell lines for modeling dynamic epigenetic regulation in vivo. Our findings establish a framework for MS-based hPTM profiling in T-ALL and emphasize the importance of model selection in developing predictive epigenetic biomarkers. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/673463v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1b15092org.highwire.dtl.DTLVardef@20bed5org.highwire.dtl.DTLVardef@1d0a687org.highwire.dtl.DTLVardef@1652999_HPS_FORMAT_FIGEXP M_FIG C_FIG Global hPTM profiling of 21 T-ALL cell lines was performed using LC-MS/MS, as previously published by Provez et al. In parallel, the 21 cell lines were treated with a dilution series of nine epidrugs, categorized into three distinct classes, to determine their IC50 values. Finally, Spearman correlation analysis was performed to assess the relationship between hPTM levels and drug sensitivity. Figure created with Biorender.com.

cancer biology↗

A laser capture microdissection-based method for high-sensitivity transcriptomics from archived FFPE tissue slides with single-cell resolution using LCM-FFPEseq

Understanding gene expression within its spatial context is essential for unravelling biological processes. Laser Capture Microdissection (LCM) has emerged as a transformative technology, enabling targeted isolation of individual cells or regions from tissue sections while preserving spatial context. However, its application to formalin-fixed, paraffin-embedded (FFPE) tissues has been limited by RNA degradation, leaving the vast repository of clinical FFPE samples underutilized. To address this, we introduce LCM-FFPEseq, a novel method combining LCM with the advanced Smart-seq3xpress protocol and FFPE-specific adaptations for spatial transcriptomics of FFPE sections. Unlike traditional protocols requiring thousands of cells to generate high-quality libraries, LCM-FFPEseq achieves high sensitivity, reproducibility, and transcript coverage. With as few as 30 FFPE-embedded K562 cells and Sertoli cells, we detected over 14,000 protein-coding genes per sample, with no substantial gains when a higher number of cells were isolated. Even individual LCM-isolated cells yielded an average of 7,353 or 6,490 protein-coding genes per K562 or Sertoli single cell, respectively. To demonstrate its clinical utility, we applied LCM-FFPEseq to archived testicular FFPE samples from transgender females receiving gender-affirming hormone therapy. Transcriptomic profiling of isolated seminiferous tubules revealed tubular hyalinization to be associated with greater upregulation of extracellular matrix remodelling and inflammatory pathways, alongside stronger downregulation of spermatogenesis-associated pathways. These findings suggest that testicular fibrosis and/or tubular hyalinization may contribute to germ cell loss following inappropriate hormonal exposure. By enabling high-resolution transcriptomics in archived FFPE samples, LCM-FFPEseq unlocks new possibilities for investigating rare cell types, spatial heterogeneity, and therapy-induced tissue remodelling in vast FFPE repositories.

genomics↗

Recombinase Polymerase Amplification of Forensic Short Tandem Repeat Loci

Short tandem repeats (STRs) are highly polymorphic repetitive DNA sequences extensively used in forensic science for identification of individuals. STR genotyping is usually performed by capillary electrophoresis (CE) or next-generation sequencing (NGS) in centralized laboratories. However, there is an increasing need for a low cost, portable and rapid STR genotyping method. Multiple methods for miniaturization have been explored, all relying on polymerase chain reaction (PCR) for generating amplicons. PCR requires precise thermal cycling, which complicates the design of the STR genotyping microfluidic device. Recombinase Polymerase Amplification (RPA) is an isothermal DNA amplification method that operates between 37{degrees}C and 42{degrees}C and completes within 40 minutes. This, along with the robustness of reagents and reduced stutter rate compared to PCR makes RPA a suitable candidate for implementation in an STR genotyping microfluidics device as well as a part of the established STR genotyping work flows. In this proof-of-concept study, we evaluate RPA assay for amplification of forensically relevant STR loci. Thirteen core STR loci of the Combined DNA Index System (CODIS) were amplified using RPA in both singleplex and multiplex formats. The amplicons were then analyzed using three different methods: CE, Illumina and Oxford Nanopore Technologies (ONT). A subset of 5 loci was used for CE analysis. CE, Illumina and ONT sequencing of singleplex RPA each resulted in complete and correct STR profiles across all samples. Sensitivity assessment demonstrated that complete and correct genotypes were achieved with DNA inputs of 62 pg and above for all but locus D8S1179. Attempts at multiplex RPA amplification resulted in incomplete or incorrect STR profiles. This outcome highlights a challenge in adapting RPA for simultaneous amplification of multiple STR loci, which is a standard requirement in forensic DNA profiling.

genomics↗

On the edge of extinction: Delayed plant genetic response to forest edge dynamics

Understanding genetic responses to forest dynamics is essential for predicting the long-term viability of understory plant populations and for developing effective conservation strategies. This study investigates genetic extinction debt and colonization credit in Circaea lutetiana, a clonal forest understory species, across its European range. Using pooled genotype-by-sequencing data from 40 forest edge and core populations, we examined to what extent population size, latitude and historical changes in forest configuration predict genetic diversity. Our findings reveal that the historical forest configuration profoundly shapes present-day genetic diversity. Long-established forest edge populations exhibit significantly reduced allelic richness (-9%) compared to core populations, indicating the partial pay-off of a genetic extinction debt. In contrast, populations from recently established forest edges maintain comparable allelic richness to core populations, suggesting delayed population genetic responses to land use changes. Finally, populations established in areas that were afforested during the past 250 years exhibit lower genetic diversity than historical forest core populations, indicating a delay in genetic recovery and thus a potential genetic colonization credit. Our results highlight that C. lutetiana populations are not at equilibrium with the current forest configuration, underscoring the role of lagged genetic responses across very long time scales. Connectivity and population size further moderate genetic diversity, with smaller, isolated populations particularly vulnerable to genetic erosion. Given the limited research on delayed evolution in forest understory species, our results improve the understanding of extinction risk dynamics and underscore the need for history-informed restoration efforts.

ecology↗

Development of a General Purpose Targeted LC-MS Method for Accurate Quantification of the SARS-CoV-2 Spike Protein Expression

The COVID-19 pandemic has catalyzed interest in immuno-multiple reaction monitoring (immuno-MRM) methods, with the detection of peptides unique to the nucleocapsid protein in nasopharyngeal swabs. While current applications predominantly focus on disease biomarkers, the pandemic has unveiled new opportunities, namely for the quantification of antigen expression following mRNA vaccination. Here, we present an optimized immuno-MRM method for quantifying SARS-CoV-2 spike protein fusion peptide, SFIEDLLFNK, for several practical applications. The method is versatile, applicable to multiple biological matrices, including plasma, and can be extended to nasopharyngeal swabs. It also offers a high-precision tool for assessing protein expression following plasmid and mRNA transfection. Moreover, in parallel to enabling accurate antigen quantification, the flow-through can be used to determine the proteome profile of the infected cells, providing insights into the intracellular immune response. This dual capability supports the rapid optimization of mRNA vaccines, thereby driving advancements in vaccine development strategies.

immunology↗

ClassiCOL: LC-MS/MS analysis for ancient species Classification via Collagen peptide ambiguation

LC-MS/MS extends on the MALDI-TOF ZooMS approach by providing fragmentation spectra for each peptide. However, ancient bone samples generate sparse datasets containing only a few collagen proteins, rendering target-decoy strategies unusable and increasing uncertainty in peptide annotation. ClassiCOL embraces and even extends this ambiguity using a novel isoBLAST approach. The exhaustive set of potential peptide candidates created in this way is then used to retain or reject different potential paths at each taxonomic branching point down to the taxonomic level attainable with the sample information, always allowing for potential mixtures in the process. As an end point, all considered ambiguity is graphically represented with a clear prioritization of the species in the sample. Using public as well as in-house data, we demonstrate the performance of this universal postprocessing approach on different instruments and explore the possibility of identifying genetic as well as sample mixtures. Diet reconstruction from 40,000 year old cave hyena coprolites illustrates the exciting potential of this approach. TeaserClassiCOL is a postprocessing tool that allows for more accurate species classification from LC-MS/MS measurements of collagen.

bioinformatics↗

Mass Spectrometry-based Profiling of Single-cell Histone Post-translational Modifications to Dissect Chromatin Heterogeneity

Single-cell proteomics confidently quantifies cellular heterogeneity, yet precise quantification of post-translational modifications, such as those deposited on histone proteins, has remained elusive. Here, we developed a robust mass spectrometry-based method for the unbiased analysis of single-cell histone post-translational modifications (schPTM). schPTM identifies both single and combinatorial histone post-translational modifications (68 peptidoforms in total), which includes nearly all frequently studied histone post-translational modifications with comparable reproducibility to traditional bulk experiments. As a proof of concept, we treated cells with sodium butyrate, a histone deacetylase inhibitor, and demonstrated that our method can i) distinguish between treated and non-treated cells, ii) identify sub-populations of cells with heterogeneous response to the treatment, and iii) reveal differential co-regulation of histone post-translational modifications in the context of drug treatment. The schPTM method enables comprehensive investigation of chromatin heterogeneity at single-cell resolution and provides further understanding of the histone code.

molecular biology↗

Non-random polymorphisms near transposable elements facilitate evolution across the genome of Arabidopsis thaliana

Evolution is a key characteristic of all life on earth, and is achieved mainly through mutation and recombination. To facilitate evolutionary rates in the absence of recombination, increased mutagenesis could provide essential opportunities for evolution. Here, we harness the genomes of 973 wild accessions of Arabidopsis thaliana, a self-fertilizing species characterized by reduced recombination rates, to study the role of transposable elements (TEs) as mutagenic drivers of non-random genetic variation. We found that multiple TE superfamilies accumulate large numbers of genetic variants in gene-rich regions of the genome. Moreover, TEs were enriched in genes underpinning key molecular processes, including fertilization and mRNA cis-splicing, suggesting that TEs generate genetic variation that is fundamental to organismal functioning and reproduction. An excess of common genetic variants (maf>0.4) flanking TEs, despite the extreme degree of self-fertilization, further corroborates the notion that TEs can generate substantial evolutionary potential in the absence of outcrossing. Nevertheless, while other studies point to TE mobilization as a strategy to facilitate adaptive evolution, we find that only a fraction (4.8%) of TE families was linked to genetic variants involved in climate adaptation to a significantly larger extent than background genomic variation, possibly because the high mutation rates near TEs dilute adaptive signals. Overall, all TE superfamilies but one (Gypsy) were significantly associated with evolutionary processes through their association with genes, functional molecular processes, flanking common variants and/or climate adaptation. We conclude that non-random mutations flanking TEs provide substantial evolutionary potential in a self-fertilizing species.

evolutionary biology↗

Genome-wide methylome stability and parental effects in the worldwide distributed Lombardy poplar

BackgroundDespite the increasing number of epigenomic studies in plants, little is known about the forces that shape the methylome in long-lived woody perennials. The Lombardy poplar offers an ideal opportunity to investigate the impact of the individual environmental history of trees on the methylome. ResultsWe present the results of three interconnected experiments on Lombardy poplar. In the first experiment, we investigated methylome variability during a growing season and across vegetatively reproduced generations. We found that ramets collected over Europe and raised in common conditions have stable methylomes in symmetrical CG-contexts. In contrast, seasonal dynamics occurred in methylation patterns in CHH-context. In the second experiment, we investigated whether methylome patterns of plants grown in a non-parental environment correlate with the parental climate. We did not observe a biological relevant pattern that significantly correlates with the parental climate. Finally, we investigated whether the parental environment has persistent carry-over effects on the vegetative offsprings phenotype. We combined new bud set observations of three consecutive growing seasons with former published bud set data. Using a linear mixed effects analysis, we found a statistically significant but weak short-term, parental carry-over effect on the timing of bud set. However, this effect was negligible compared to the direct effects of the offspring environment. ConclusionsGenome-wide cytosine methylation patterns in symmetrical CG-context are stable in Lombardy poplar and appear to be mainly the result of random processes. In this widespread poplar clone, methylation patterns in CG-context can be used as bio-markers to infer a common ancestor and thus to investigate the recent environmental history of a specific Lombardy poplar. The Lombardy poplar shows high phenotypic plasticity in a novel environment which enabled this clonal tree to adapt and survive all over the temperate regions of the world.

genomics↗

An interactive mass spectrometry atlas of histone posttranslational modifications in T-cell acute leukemia

The holistic nature of omics studies makes them ideally suited to generate hypotheses on health and disease. Sequencing-based genomics and mass spectrometry (MS)-based proteomics are linked through epigenetic regulation mechanisms. However, epigenomics is currently mainly focused on DNA methylation status using sequencing technologies, while studying histone posttranslational modifications (hPTMs) using MS is lagging, partly because reuse of raw data is impractical. Yet, targeting hPTMs using epidrugs is an established promising research avenue in cancer treatment. Therefore, we here present the most comprehensive MS-based preprocessed hPTM atlas to date, including 21 T-cell acute lymphoblastic leukemia (T-ALL) cell lines. We present the data in an intuitive and browsable single licensed Progenesis QIP project and provide all essential quality metrics, allowing users to assess the quality of the data, edit individual peptides, try novel annotation algorithms and export both peptide and protein data for downstream analyses, exemplified by the PeptidoformViz tool. This data resource sets the stage for generalizing MS-based histone analysis and provides the first reusable histone dataset for epidrug development.

cancer biology↗

Cas9 targeted nanopore sequencing with enhanced variant calling improves CYP2D6-CYP2D7 hybrid allele genotyping

CYP2D6 is one of the most challenging pharmacogenes to genotype due to the high similarity with its neighboring pseudogenes and the frequent occurrence of CYP2D6-CYP2D7 hybrids. Unfortunately, most current genotyping methods are therefore not able to correctly determine the complete CYP2D6-CYP2D7 sequence. Therefore, we developed a genotyping assay to generate complete allele-specific consensus sequences of complex regions by optimizing the PCR-free nanopore Cas9-targeted sequencing (nCATS) method combined with adaptive sequencing, and developing a new comprehensive long read genotyping (CoLoRGen) pipeline. The CoLoRGen pipeline first generates consensus sequences of both alleles and subsequently determines both large structural and small variants to ultimately assign the correct star-alleles. In reference samples, our genotyping assay confirms the presence of CYP2D6-CYP2D7 large structural variants, single nucleotide variants (SNVs), and small insertions and deletions (INDELs) that go undetected by most current assays. Moreover, our results provide direct evidence that the CYP2D6 genotype of the NA12878 DNA should be updated to include the CYP2D6-CYP2D7 *68 hybrid and several additional single nucleotide variants compared to existing references. Ultimately, the nCATS-CoLoRGen genotyping assay additionally allows for more accurate gene function predictions by enabling the possibility to detect and phase de novo mutations in addition to known large structural and small variants. Author SummaryDuring the last decades, the usefulness of personalized medicine has become increasingly apparent. Directly linked to that is the need for accurate genotyping assays to determine the pharmacogenetic profile of patients. Continuing research has led to the development of genotyping assays that perform quite robustly. However, complex genes remain an issue when it comes to determining the complete sequence correctly. An example of such a complex but very important pharmacogene is CYP2D6. Therefore, we developed a genotyping assay in an attempt to generate complete allele-specific consensus sequences of CYP2D6, by optimizing a targeted amplification-free long-read sequencing method and developing a new analysis pipeline. In reference samples, we showed that our genotyping assay performed accurately and confirmed the presence of variants that go undetected by most current assays. However, the implementation of this assay in practice is still hampered as the selected enrichment strategies inherently lead to a low percentage of on-target reads, resulting in low on-target sequencing depths. Further optimization and validation of the assay is thus needed, but definitely worth considering for follow-up research as we already demonstrated the added value for generating more complete genotypes, which on its turn will result in more accurate gene function predictions.

genetics↗

A comprehensive LFQ benchmark dataset on modern day acquisition strategies in proteomics

In the last decade, a revolution in liquid chromatography-mass spectrometry (LC-MS) based proteomics was unfolded with the introduction of dozens of novel instruments that incorporate additional data dimensions through innovative acquisition methodologies, in turn inspiring specialized data analysis pipelines. Simultaneously, a growing number of proteomics datasets have been made publicly available through data repositories such as ProteomeXchange, Zenodo and Skyline Panorama. However, developing algorithms to mine this data and assessing the performance on different platforms is currently hampered by the lack of a single benchmark experimental design. Therefore, we acquired a hybrid proteome mixture on different instrument platforms and in all currently available families of data acquisition. Here, we present a comprehensive Data-Dependent and Data-Independent Acquisition (DDA/DIA) dataset acquired using several of the most commonly used current day instrumental platforms. The dataset consists of over 700 LC-MS runs, including adequate replicates allowing robust statistics and covering over nearly 10 different data formats, including scanning quadrupole and ion mobility enabled acquisitions. Datasets are available via ProteomeXchange (PXD028735).

bioinformatics↗