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Daniel Figeys

Publications and source records attributed to Daniel Figeys.

At least 19 recordsLinked to original sources
PubMed2026

Integrating multi-omics technologies to decipher microbiome functions.

Multi-omics approaches have revolutionized our understanding of microbial communities by enabling simultaneous interrogation of genomic, transcriptomic, proteomic, and metabolomic data. The systematic integration and analysis of these deep datasets help decipher the functional roles of microbiomes, providing critical insights into microbial activities, interactions, and dynamics across diverse environments. Biological complexity makes multi-omics analysis of a single, isolated organism demanding but highly informative, yet this complexity increases further when samples comprise hundreds to thousands of individual species. As microbiome research continues to expand into clinical, environmental, and engineered systems, standardized workflows, benchmarked datasets, and community-driven initiatives are essential to ensure reproducibility, standardization and interpretability. Establishing and disseminating best practices for experimental design, data processing, and integrative analyses will be critical for maximizing comparability and scientific rigor across studies. This perspective highlights recent advances in multi-omics microbiome research, outlines key obstacles in data integration and metadata harmonization, and proposes a collaborative roadmap for scalable, FAIR-compliant multi-omics investigations and potentially disruptive Artificial Intelligence (AI) advances comparable to those of AlphaFold in the field of microbiome science.

Multiomics↗
PubMed2026

The need for standardization and improved open (meta)data practices in metaproteomics.

Metaproteomics enables functional insight into microbial communities by identifying and quantifying proteins in complex samples. Yet, heterogeneous analytical workflows and the lack of standardization across experimental and bioinformatics stages hinder reproducibility and comparability, limiting integration with other omics data. We here present a community-developed reporting checklist tailored to the specific needs of metaproteomics. We also outline current efforts to enable structured and interoperable metadata capture, drawing on standards from proteomics and microbiome research wherever possible. By promoting transparent reporting and advancing metadata practices, our recommendations aim to align metaproteomics more closely with FAIR principles and support reproducible and interoperable research practices. Video Abstract.

Proteomics↗
PubMed2024

Retinal Proteome Profiling of Inherited Retinal Degeneration Across Three Different Mouse Models Suggests Common Drug Targets in Retinitis Pigmentosa.

Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing, and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical largescale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6βRd10 (rd10) and RhoP23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65-/- mouse model of Leber's congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The large-scale profiling of the retinal proteome, coupled with in vivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data is curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.

Animals↗
PubMed2007

Multiplexed proteomic reactor for the processing of proteomic samples.

We report the development of a 96-well plate proteomic reactor for gel-free processing of minute amounts of complex proteomic samples. The device performs multiplexed trapping, enrichment, and biochemical processing of proteins, resulting in concentrated peptide solutions ready for mass spectrometric analysis. Individual wells on the reactor can process up to 2 microg of protein. We also report the coupling of the plate proteomic reactor with protein fractionation using size-exclusion chromatography for large-scale identification of proteins. To illustrate the potential of this approach, we separated 400 microg of MCF7 cell lysate using size-exclusion chromatography and processed 35 protein fractions on the reactor plate. Using stringent criteria when searching the data, a total of 875 unique proteins were identified. More relaxed searching conditions associated with a 1% false positive rate led to the identification of 2683 unique proteins, meaning that one protein was identified per 3-10 ng of total protein lysate loaded on the reactor plate.

Biomarkers, Tumor↗
PubMed2007

Biomarker assay translation from discovery to clinical studies in cancer drug development: quantification of emerging protein biomarkers.

Many candidate biomarkers emerging from genomics and proteomics research have the potential to serve as predictive indexes for guiding the development of safer and more efficacious drugs. Research and development of biomarker discovery, selection, and clinical qualification, however, is still a relatively new field for the pharmaceutical industry. Advances in technology provide a plethora of analytical tools to discover and analyze mechanism-and-disease-specific biomarkers for drug development. In the discovery phase, differential proteomic analysis using mass spectrometry enables the identification of candidate biomarkers that are associated with a specific mechanism relevant to disease progression and affected by drug treatment. Reliable bioanalytical methods are then developed and implemented to select promising biomarkers for further studies in animals and humans. Quantitative analytical methods capable of generating reliable data constitute a solid basis for statistical assessment of the predictive utility of biomarkers. Biomarker method validation is diverse and for purposes that are very different from those of drug bioanalysis or diagnostic use. Besides being flexible, it should sufficiently demonstrate the method's ability to meet the study intent and the attendant regulatory requirements. Several papers have been published outlining specific requirements for successful biomarker method development and validation using a "Fit-for-Purpose" approach. Many of the challenges faced during biomarker discovery as well as during technology and process translation are discussed in this chapter, including preanalytical planning, assay development, and preclinical and clinical validation. Specific references to protein biomarkers for cancer drug development are also discussed.

Animals↗
PubMed2007

The proteomic reactor facilitates the analysis of affinity-purified proteins by mass spectrometry: application for identifying ubiquitinated proteins in human cells.

Mass spectrometry (MS) coupled to affinity purification is a powerful approach for identifying protein-protein interactions and for mapping post-translational modifications. Prior to MS analysis, affinity-purified proteins are typically separated by gel electrophoresis, visualized with a protein stain, excised, and subjected to in-gel digestion. An inherent limitation of this series of steps is the loss of protein sample that occurs during gel processing. Although methods employing in-solution digestion have been reported, they generally suffer from poor reaction kinetics. In the present study, we demonstrate an application of a microfluidic processing device, termed the Proteomic Reactor, for enzymatic digestion of affinity-purified proteins for liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Use of the Proteomic Reactor enabled the identification of numerous ubiquitinated proteins in a human cell line expressing reduced amounts of the ubiquitin-dependent chaperone, valosin-containing protein (VCP). The Proteomic Reactor is a novel technology that facilitates the analysis of affinity-purified proteins and has the potential to aid future biological studies.

Adenosine Triphosphatases↗
PubMed2006

Mapping protein-protein interactions by mass spectrometry.

Mass spectrometry is currently at the forefront of technologies for mapping protein-protein interactions, as it is a highly sensitive technique that enables the rapid identification of proteins from a variety of biological samples. When used in combination with affinity purification and/or chemical cross-linking, whole or targeted protein interaction networks can be elucidated. Several methods have recently been introduced that display increased specificity and a reduced occurrence of false-positives. In the future, information gained from human protein interaction studies could lead to the discovery of novel pathway associations and therapeutic targets.

Animals↗
PubMed2006

Proteomics technology in systems biology.

It has now become apparent that a full understanding of a biological process (e.g. a disease state) is only possible if all biomolecular interactions are taken into account. Systems biology works towards understanding the intricacies of cellular life through the collaborative efforts of biologists, chemists, mathematicians and computer scientists and recently, a number of laboratories around the world have embarked upon such research agendas. The fields of genomics and proteomics are foundational in systems biology studies and a great deal of research is currently being conducted in each worldwide. Moreover, many technological advances (particularly in mass spectrometry) have led to a dramatic rise in the number of proteomic studies over the past two decades. This short review summarizes a selection of technological innovations in proteomics that contribute to systems biology studies.

Chromatography, Affinity↗
PubMed2006

The proteomic reactor: a microfluidic device for processing minute amounts of protein prior to mass spectrometry analysis.

Gel-free proteomics has emerged as a complement to conventional gel-based proteomics. Gel-free approaches focus on peptide or protein fractionation, but they do not address the efficiency of protein processing. We report the development of a microfluidic proteomic reactor that greatly simplifies the processing of complex proteomic samples by combining multiple proteomic steps. Rapid extraction and enrichment of proteins from complex proteomic samples or directly from cells are readily performed on the reactor. Furthermore, chemical and enzymatic treatments of proteins are performed in 50 nL effective volume, which results in an increased number of generated peptides. The products are compatible with mass spectrometry. We demonstrated that the proteomic reactor is at least 10 times more sensitive than current gel-free methodologies with one protein identified per 440 pg of protein lysate injected on the reactor. Furthermore, as little as 300 cells can be directly introduced on the proteomic reactor and analyzed by mass spectrometry.

Animals↗
PubMed2006

N-glycosylation analysis using the StrOligo algorithm.

N-glycosylation of proteins is the predominant glycosylation in mammals and confers specific conformations, localization, and functions to proteins. High-throughput proteomics techniques have focused on the identification of proteins through amino acid sequence determination, with little attention paid to their post-translational modification, in particular, glycosylation. High-throughput mass spectrometric data often contain information about glycosylation, but this is systematically discarded by proteomic search engines. We have developed an algorithm, StrOligo (for STRucture of OLIGOsaccharides), capable of automated analysis of oligosaccharide composition and possible structures by mass spectrometry. The algorithm analyzes tandem mass spectrometry (MS/MS) data in an automated three-step process and provides possible structures and a discrimination score. In the first step, the algorithm constructs a relationship tree of the monosaccharide moiety losses observed in the MS/MS spectrum. In the second step, the algorithm uses the tree to propose possible compositions and structures from combinations of adduct and fragment ions as well as a discrimination score, which reflects the fit with the experimental results. Finally, an interface is available to visualize the proposed structures and their scores. As well, the MS/MS spectrum is displayed with relevant peaks labeled for the proposed structure with the highest discrimination score, using a modified nomenclature.

Algorithms↗
PubMed2004

Combining different 'omics' technologies to map and validate protein-protein interactions in humans.

The mapping of protein-protein interactions is key to understanding biological processes. Many technologies have been reported to map interactions and these have been systematically applied in yeast. To date, the number of reported yeast protein interactions that have been truly validated by at least one other approach is low. The mapping of human protein interaction networks is even more complicated. Thus, it is unreasonable to try to map the human interactome; instead, interaction mapping in human cell lines should be focused along the lines of diseases or changes that can be associated with specific cells. In this paper, an approach for combining different 'omics' technologies to achieve efficient mapping and validation of protein interactions in human cell lines is presented.

Cell Line↗
PubMed2003

HysTag--a novel proteomic quantification tool applied to differential display analysis of membrane proteins from distinct areas of mouse brain.

A novel isotopically labeled cysteine-tagging and complexity-reducing reagent, called HysTag, has been synthesized and used for quantitative proteomics of proteins from enriched plasma membrane preparations from mouse fore- and hindbrain. The reagent is a 10-mer derivatized peptide, H(2)N-(His)(6)-Ala-Arg-Ala-Cys(2-thiopyridyl disulfide)-CO(2)H, which consists of four functional elements: i) an affinity ligand (His(6)-tag), ii) a tryptic cleavage site (-Arg-Ala-), iii) Ala-9 residue that contains four (d(4)) or no (d(0)) deuterium atoms, and iv) a thiol-reactive group (2-thiopyridyl disulfide). For differential analysis cysteine residues in the compared samples are modified using either (d(4)) or (d(0)) reagent. The HysTag peptide is preserved in Lys-C digestion of proteins and allows charge-based selection of cysteine-containing peptides, whereas subsequent tryptic digestion reduces the labeling group to a di-peptide, which does not hinder effective fragmentation. Furthermore, we found that tagged peptides containing Ala-d(4) co-elute with their d(0)-labeled counterparts. To demonstrate effectiveness of the reagent, a differential analysis of mouse forebrain versus hindbrain plasma membranes was performed. Enriched plasma membrane fractions were partially denatured, reduced, and reacted with the reagent. Digestion with endoproteinase Lys-C was carried out on nonsolubilized membranes. The membranes were sedimented by ultra centrifugation, and the tagged peptides were isolated by Ni(2+) affinity or cation-exchange chromatography. Finally, the tagged peptides were cleaved with trypsin to release the histidine tag (residues 1-8 of the reagent) followed by liquid chromatography tandem mass spectroscopy for relative protein quantification and identification. A total of 355 unique proteins were identified, among which 281 could be quantified. Among a large majority of proteins with ratios close to one, a few proteins with significant quantitative changes were retrieved. The HysTag offers advantages compared with the isotope-coded affinity tag reagent, because the HysTag reagent is easy to synthesize, economical due to use of deuterium instead of (13)C isotope label, and allows robust purification and flexibility through the affinity tag, which can be extended to different peptide functionalities.

Amino Acid Sequence↗
PubMed2003

Novel approaches to map protein interactions.

Although we now have the sequence of the human genome at hand, we face the challenge of assigning function to the identified genes. Genes usually ascribe their function through proteins, and the role of proteins is to interact with other molecules. Therefore, if we could map the interactions of proteins we would be able to understand protein function. The challenge of mapping protein interactions is vast and many novel approaches have recently been developed for this task using molecular biology, mass spectrometry and chemiproteomic techniques.

Carbohydrate Metabolism↗
PubMed2003

On-line strong cation exchange micro-HPLC-ESI-MS/MS for protein identification and process optimization.

We have developed an on-line strong cation exchange (SCX)-ESI-MS/MS platform for the rapid identification of proteins contained in mixtures. This platform consists of a SCX precolumn followed by a nanoflow SCX column on-line with an electrospray ion trap mass spectrometer. We also used this platform to study the dynamics of peptide separation/extraction by SCX, in particular to understand the parameters affecting the performance of SCX in multidimensional chromatography. For example, we have demonstrated that the buffer typically used for tryptic digestion of protein mixtures can have a detrimental effect on the chromatographic behaviour of peptides during SCX separations, thereby affecting certain peptide quantitation approaches that rely on reproducible peptide fractionation. We have also demonstrated that band broadening results when a step (discontinuous) gradient approach is used to displace peptides from the SCX precolumn, reducing the separation power of SCX in multidimensional chromatography. In contrast, excellent chromatographic peak shapes are observed when a defined (continuous) gradient is used. Finally, using a tryptic digest of a protein extract derived from human K562 cells, we observed that larger molecular weight peptides are identified using this on-line SCX approach compared to the more conventional reverse phase (RP) LC/MS approach. Both methods used in tandem complement each other and can lead to a greater number of peptide identifications from a given sample.

Cations↗
PubMed2002

Death-associated protein 4 binds MST1 and augments MST1-induced apoptosis.

The protein kinase MST1 is proapoptotic when overexpressed in an active form, however, its physiologic regulation and cellular targets are unknown. An overexpressed inactive MST1 mutant associates in COS-7 cells with an endogenous 761-amino acid polypeptide known as "death-associated protein 4" (DAP4). The DAPs are a functionally heterogeneous array of polypeptides previously isolated by Kimchi and colleagues (Kimchi, A. (1998) Biochim. Biophys. Acta 1377, F13-F33 in a screen for elements involved in the interferon gamma-induced apoptosis of HeLa cells. DAP4, which is encoded by a member of a vertebrate-only gene family, contains no identifiable domains, but is identical over its amino-terminal 488 amino acids to p52(rIPK), a putative modulator of protein kinase R. DAP4 is a widely expressed, constitutively nuclear polypeptide that homodimerizes through its amino terminus and binds MST1 through its carboxyl-terminal segment. MST1 is predominantly cytoplasmic, but cycles continuously through the nucleus, as evidenced by its rapid accumulation in the nucleus after addition of the Crm1 inhibitor, leptomycin B. Overexpression of DAP4 does not cause apoptosis, however, coexpression of DAP4 with a submaximal amount of MST1 enhances MST1-induced apoptosis in a dose-dependent fashion. DAP4 is not significantly phosphorylated by MST1 nor does it alter MST1 kinase activity in vivo or in vitro. MST1-induced apoptosis is suppressed by a dominant interfering mutant of p53. MST1 is unable to directly phosphorylate p53, however, DAP4 binds endogenous and recombinant p53. DAP4 may promote MST1-induced apoptosis by enabling colocalization of MST with p53.

Adaptor Proteins, Signal Transducing↗