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PubMed2026

ProtPen Combines Sequence- and Structure-based Approaches to Facilitate Protein Function Predictions on a Proteome-wide Scale.

Proteins of unknown function represent a significant gap in our understanding of biological processes, encompassing large portions of the proteomes of many organisms, especially prokaryotes. Addressing this gap is critical to understanding the biology and pathogenicity of such organisms. We introduce ProtPen, an open-source pipeline that facilitates protein function prediction by combining eggNOG-mapper for sequence-based annotation with Foldseek for rapid structural similarity searches using AlphaFold-predicted protein structures. Annotation results from both tools are merged and enriched with UniProt metadata to produce a comprehensive output suitable for downstream analysis. The pipeline requires only a FASTA input file with UniProt identifiers, and is designed to analyze data sets on the scale of whole proteomes. Benchmarking on a curated data set of well-characterized Pseudomonas aeruginosa proteins demonstrated an annotation accuracy of >90%, and highlighted the complementarity of sequence- and structure-based methods. Further evaluation of ProtPen included its application to biologically relevant data sets, comprising proteins of unknown function that exhibited significant differential abundances in a proteomics data set of P. aeruginosa, and uncharacterized glycoproteins from Haloferax volcanii. ProtPen is readily extensible to incorporate additional protein function prediction tools. In summary, this pipeline facilitates the systemwide annotation of proteins of unknown function from proteomic data sets and whole proteomes.

Pseudomonas aeruginosa↗
PubMed2026

A human lysosomal storage disorder toolkit for decoding proteome landscapes in cortical-like and dopaminergic-like induced neurons.

Lysosomes maintain cellular homeostasis by degrading proteins delivered via endocytosis and autophagy and by recycling building blocks for organelle biogenesis. Lysosomal storage disorders (LSDs) comprise a group of diseases affecting diverse lysosomal functions. To facilitate molecular phenotyping across diverse LSD gene classes, we are developing a library of human embryonic stem cells engineered to lack individual LSD genes as a resource for the field. Here, we report our initial stem cell toolkit lacking one of 23 LSD genes, including the majority of genes associated with sphingolipidoses and neuronal ceroid lipofuscinoses, and its use in the generation of a proteomic resource for induced cortical-like and midbrain dopaminergic-like neurons. In-depth abundance and correlation profiling across organelles and suborganelle components revealed potential vulnerabilities that reflect distinct patterns of proteome alterations across both genotypes and neuronal cell types. We characterize alterations in the mitochondrial proteome associated with GBA1 and ASAH1 deficiency and identify synaptic and mitochondrial defects in ASAH1-/- induced neurons that correlate with defects in neuronal firing rates. Moreover, we developed an informatic pipeline for proteome-wide identification of individual protein-protein interactions and protein complexes that may be disrupted as a result of LSD gene deficiency. Finally, we visualized structural alterations of ASAH1-deficient endolysosomes in situ using cryoelectron tomography, revealing swollen organelles that were largely devoid of dense internal membranes characteristic of wild-type cells, but containing numerous intralumenal vesicle compartments. This toolkit and associated proteomic landscapes provide a resource for defining molecular signatures associated with LSD gene dysfunction and organelle vulnerability.

Humans↗
PubMed2026

Implications of proteome allocation constraints for understanding interbacterial antagonism.

Bacteria live in dense communities where competition influences the composition and, therefore, the function of these communities. Beyond competing for resources, bacteria engage in antagonism by deploying a range of molecular weapon systems to inhibit and kill other bacteria. Investing in antagonism is expected to incur a fitness trade-off, but the nature of this trade-off at the level of molecular physiology remains underexplained. Applying recent advances about the physiological constraints faced by bacterial cells may help us better understand existing studies and design new investigations into interbacterial antagonism. Bacterial cells face two important constraints: a finite amount of protein and a maximum translation speed for ribosomes. As a result, the only way for a cell to grow faster is to allocate more of its finite proteome to synthesizing ribosomes. A cell choosing to attack competitors must therefore allocate some of its limited proteome budget to antagonistic proteins instead of other functions. Conversely, being attacked and resisting the effects of such attacks also require an investment of proteomic resources. The extent to which proteome allocation constraints influence bacterial physiology is not fully understood; consequently, how these constraints influence interbacterial antagonism has not been investigated. Here, I will discuss how proteome allocation constraints can re-contextualize our existing understanding of the costs of both deploying and resisting attacks and how investigation of these constraints may further our understanding of interbacterial antagonism.

Proteome↗
PubMed1997

Proteome research: complementarity and limitations with respect to the RNA and DNA worlds.

A methodological overview of proteome analysis is provided along with details of efforts to achieve high-throughput screening (HTS) of protein samples derived from two-dimensional electrophoresis gels. For both previously sequenced organisms and those lacking significant DNA sequence information, mass spectrometry has a key role to play in achieving HTS. Prototype robotics designed to conduct appropriate chemistries and deliver 700-1000 protein (genes) per day to batteries of mass spectrometers or liquid chromatography (LC)-based analyses are well advanced, as are efforts to produce high density gridded arrays containing > 1000 proteins on a single matrix assisted laser desorption ionisation/time-of-flight (MALDI-TOF) sample stage. High sensitivity HTS of proteins is proposed by employing principally mass spectrometry in an hierarchical manner: (i) MALDI-TOF-mass spectrometry (MS) on at least 1000 proteins per day; (ii) electrospray ionisation (ESI)/MS/MS for analysis of peptides with respect to predicted fragmentation patterns or by sequence tagging; and (iii) ESI/MS/MS for peptide sequencing. Genomic sequences when complemented with information derived from hybridisation assays and proteome analysis may herald in a new era of holistic cellular biology. The current preoccupation with the absolute quantity of gene-product (RNA and/or protein) should move backstage with respect to more molecularly relevant parameters, such as: molecular half-life; synthesis rate; functional competence (presence or absence of mutations); reaction kinetics; the influence of individual gene-products on biochemical flux; the influence of the environment, cell-cycle, stress and disease on gene-products; and the collective roles of multigenic and epigenetic phenomena governing cellular processes. Proteome analysis is demonstrated as being capable of proceeding independently of DNA sequence information and aiding in genomic annotation. Its ability to confirm the existence of gene-products predicted from DNA sequence is a major contribution to genomic science. The workings of software engines necessary to achieve large-scale proteome analysis are outlined, along with trends towards miniaturisation, analyte concentration and protein detection independent of staining technologies. A challenge for proteome analysis into the future will be to reduce its dependence on two-dimensional (2-D) gel electrophoresis as the preferred method of separating complex mixtures of cellular proteins. Nonetheless, proteome analysis already represents a means of efficiently complementing differential display, high density expression arrays, expressed sequence tags, direct or subtractive hybridisation, chromosomal linkage studies and nucleic acid sequencing as a problem solving tool in molecular biology.

Animals↗
PubMed2006

Proteomic trajectory mapping of biological transformation: Application to developmental mouse retina.

In this report we introduce a new concept "proteomic trajectory mapping" for the investigation of a complex phenomenon underlying biological transformation and transition. We define proteomic trajectory to be the kinetic trace of protein expression and present a successful proteomic trajectory mapping of complex molecular events underlying postnatal development of mouse retina. Cluster analysis of the trajectory data using a two-state model identified four proteomic trajectory types: two distinct trajectory types accounting for the decline or the rise of protein molecules actively expressed in the juvenile stage (J-type) or in the adult stage (A-type), a class of transient trajectories that mediate the transformation from the juvenile to the adult stage (T-type), and the steady trajectories throughout the entire process of transformation (C-type). The dominance of particular protein categories expressed in each trajectory characterizes the stage of retinal development. Proteomic trajectory mapping will be a powerful tool to study the systematic changes of protein expression caused by physiological, genetic, or pathological agents and the reverse of such changes to the norm by a treatment. The proteomic trajectory mapping is applicable to any biological transformation and, therefore, will be a powerful tool in biomedical sciences.

Animals↗
PubMed2002

Analysis of signaling pathways using functional proteomics.

Advances in analytical methods for protein analysis by mass spectrometry provide new tools for global analysis of the expressed protein profile of cells (referred to as proteomics). Currently, available methodology samples only part of the proteome. This is sufficient for analysis of signal transduction, because signaling pathways contain enzymes, which modify high-abundance proteins other than those of the pathway. Thus, modulation of the signaling through a pathway will produce a "footprint" in the proteome that is characteristic of a specific cell phenotype. Comparison of different samples to identify these differences in posttranslational modification or protein expression is referred to as functional proteomics. This review surveys the methods in widest use in functional proteomics, as well as a few promising new ones. Although proteomic analyses were first conducted 26 years ago, a renewed interest is fueled by several recent advances. Most important are the availability of public genome and protein databases and the development of high-sensitivity, easy-to-use mass spectrometers and database search engines capable of exploiting these databases. Other important advances include improved two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), computer programs for analysis of the 2D-PAGE gel images, protocols for proteolytic digestion of proteins in excised gel pieces, and low-flow chromatography methods. Despite the limitations of these methods, they can distinguish subtle changes in the phenotype of cells, providing the basis for future studies in regulation of the phenotype.

Animals↗
PubMed1998

Proteome in perspective.

This review describes briefly proteome science. It explains why proteome science or proteomics emerged only recently and why a shift from genomics to proteomics is occurring. This review further illustrates that proteomics can unravel new domains in nature's complexity. Finally, it demonstrates that proteomics is offering new tools for the study of complex biological or medical problems.

Genome, Human↗
PubMed2002

Proteomic analysis of secreted muscle components: search for factors involved in neuromuscular synapse formation.

Denervated but not innervated skeletal muscles secrete polypeptides that are involved in neuromuscular synapse formation. With the aim of identifying such components, metabolically labeled polypeptides in extracts from denervated and innervated muscles were submitted to two-dimensional gel electrophoresis, and the abundance of individual molecular species was compared. Consistent differences between the proteomic maps from the two sources of muscles were seen. Likewise, proteomic maps of polypeptides from organ culture media conditioned by chronically denervated muscles and by control muscles revealed consistent differences, but the abundance of material within individual spots from conditioned media was not sufficient for analysis by mass spectrometry. Since it was not possible to match the patterns from muscle extracts and from conditioned media, it has been established that extract of Sol8 muscle cells was a satisfactory source of material for analysis. From 1,200 spots identified on the proteomic map from Sol8 cells by image analysis, some 140 have been defined by mass spectrometric analysis. In order to identify the components that are shared by secreted molecules from denervated muscles and Sol8 cells, a mixture of extracts from the two sources was co-electrophoresed and a shared proteomic pattern was established by visualization of metabolically labeled spots from the conditioned medium and of silver stained spots from the Sol8 cells. More than 100 spots sharing x/y coordinate localization could be seen on the pattern. Of these, fourteen were among those identified by mass spectrometry. It is concluded that co-electrophoresis of radioactively labeled polypeptides from conditioned media with extracts from Sol8 cells can be used to mark in the proteome of Sol8 cells those polypeptides that are secreted at low abundance by adult muscles. Their higher abundance in Sol8 cells opens the possibility for further scrutiny of spots by mass spectrometry or by microsequencing.

Animals↗
PubMed2026

Proteomics-Driven Strategies for Proximity-Inducing Drug Discovery.

In recent years, proximity-inducing drugs have emerged as a novel therapeutic modality that induces or stabilizes protein-protein interactions, especially by recruiting effector proteins to specific target proteins, thereby achieving functions beyond traditional inhibitors. The potential of proximity-inducing drugs extends beyond targeted protein degradation (TPD), as studies have demonstrated their ability to regulate biological processes such as signal transduction, gene transcription, chromatin regulation, and protein trafficking by modulating protein interaction networks. Rational discovery of proximity-inducing drugs requires clarifying their effects on protein-protein interactions, determining drug selectivity, and developing suitable ligands for drug construction. Proteomics has become a central technology in drug discovery, enabling global identification of the direct drug targets and systematic characterization of proteome-wide downstream responses. This provides a more refined map of drug mechanisms. In parallel, advances in machine learning applied to proteomic data, together with the expansion of proteome-wide ligandability maps, are further accelerating the discovery and optimization of proximity-inducing drugs. This review summarizes recent advances of proximity-inducing drugs, with a particular emphasis on how proteomics facilitates target space expansion, drug efficacy optimization, and ligandability discovery, alongside the emerging contributions of machine learning. Collectively, these insights aim to support the rational development of next-generation proximity-inducing drugs.

Drug Discovery↗
PubMed2006

Capillary separations enabling tissue proteomics-based biomarker discovery.

Development of the capability to enable large-scale proteome studies, analogous to comprehensive gene expression analysis, will clearly have far-reaching impacts on protein biomarker investigations of human diseases such as cancer through interrogation of the archived fresh frozen and formalin-fixed and paraffin-embedded tissue collections. This review therefore focuses on the most recent advances in microdissection techniques and proteome platforms for procuring homogeneous subpopulations of tumor cells or structures and performing comprehensive analysis of protein profiles within tissue specimens, respectively. Developments in capillary separations capable of providing extremely high resolving power and selective analyte enrichment are particularly highlighted for their roles within the broader context of a state-of-the-art integrated tissue proteome effort. The capabilities of CIEF-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. These proteome technological advances combined with recently developed tissue microdissection techniques provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.

Biomarkers↗
PubMedDate not supplied

Application of proteomics technologies in the investigation of the brain.

Approximately 30-50% of the genes in mammals are expressed in the nervous system. A differential expression of genes in distinct patterns is necessary for the generation of the large variety of neuronal phenotypes. Proteomic analysis of brain compartments may be useful to understand the complexity, to investigate disorders of the central nervous system, and to search for corresponding early markers. Up to now, proteomics has mainly studied the identity and levels of the abundant human, rat, and mouse brain proteins as well as changes of their levels and the modifications that result from various neurological disorders, like Alzheimer's disease and Down's syndrome in humans and in animal models of those diseases. The proteins, for which altered levels in these disorders have been observed, exert mainly neurotransmission, guidance, and signal-transduction functions, or are involved in detoxification, metabolism, and conformational changes. Some of those proteins may be potential drug targets. Further improvement of proteomics technologies to increase sensitivity and efficiency of detection of certain protein classes is necessary for a more detailed analysis of the brain proteome. In this review, a description of the proteomics technologies applied in the investigation of the brain, the major findings that resulted from their application, and the potential and limitations of the current technologies are discussed.

Animals↗
PubMedDate not supplied

Proteome analysis in the study of lymphoma cells.

This review provides an overview on recent studies in the field of proteome analysis of lymphoma cells, and highlights the potentials of such studies for a better knowledge of drug effects at the molecular level. After giving general information on the field of proteome analysis of lymphoma cells, some characteristics of the strategies used during this analysis are pointed out, such as cell extraction strategies and affinity captures. Therefore, the issue of proteome analysis of lymphoma cells content will be covered with respect to those protein extracts that can be prepared in saline solutions, such as cytoplasm proteins, or that are associated with the cell membranes. The question of which kinds of information have been retrieved from lymphoma-cell proteomics is discussed on the basis of several examples-lymphoma cell-mapping studies and constitution of protein databases, and comparative proteome analysis studies of the modifications that result from a drug treatment.

Animals↗
PubMed2003

ProteomeWeb: a web-based interface for the display and interrogation of proteomes.

The analysis of proteomes, i.e., the proteins expressed by biological organisms under a given set of conditions at a given time, requires separating complex protein mixtures into discrete protein components, measuring their relative abundances, and identifying the individual protein components. Many types of data are generated during the course of proteome analysis, including graphic images of the protein profiles, flat files containing numeric data, spreadsheets for assimilating numeric data, and relational database tables for integrating data from multiple experiments. As part of a project to describe the proteomes of microbes of interest to the U.S. Department of Energy, a World-Wide Web-based interface has been developed for the display of protein profiles generated by two-dimensional gel electrophoresis. The web interface is capable of obtaining protein identifications on the fly, interrogating the quantitative data in the context of available genome sequence information, and relating the proteome data to existing metabolic pathway databases. Analysis of protein expression profiles is expedited, providing the capability to efficiently determine the gene locations for proteins modulated in abundance in response to different growth conditions and to locate the positions of the proteins within specific metabolic pathways. The proteome of the archaeon Methanococcus jannaschii, a microbe for which the complete genome sequence is available, is used to demonstrate the capabilities of this evolving web interface (http://proteomeweb.anl.gov).

Amino Acid Sequence↗
PubMed2003

Between-gel reproducibility of the human cerebrospinal fluid proteome.

This manuscript describes the between-gel reproducibility of the two-dimensional gel electrophoresis analysis of the human lumbar cerebrospinal fluid (CSF) proteome. This reproducibility study is a necessary component for our long-term research program that uses comparative proteomics to analyze lumbar CSF samples in a study of human idiopathic low back pain. A Protein-Plus Dodeca Cell electrophoresis apparatus and PDQuest software were used to measure the level of between-gel reproducibility of the CSF proteome. One pooled CSF sample was used to evaluate the level of within-sample, between-gel reproducibility, and a set of seven different CSF samples (CSF-1 to 7) was used to test the level of within-group and between-group variability. Differentially expressed proteins (six CSF samples versus the designated control, CSF-3) were characterized with mass spectrometry. The number of spots found in the pooled CSF sample was 490 +/- 30 (n = 10 gels); the percentage of protein spots found in those 10 gels was 92 +/- 6%, with a coefficient of variation of 6%; and a positive coefficient of correlation (r = 0.82) was found. In order to test the proof-of-principle, that set of seven CSF samples served as a test of our ability to perform reproducibility comparative proteomics, and to detect differentially expressed proteins within that set of test samples. One sample (CSF-3) served as the control for the other six to locate the differentially expressed proteins. A comparison of fifteen differentially expressed proteins found in that set of test CSF samples correlated with pathology. Matrix-assisted laser desorption/ionization-time-of-flight and electrospray ionization quadrupole ion trap mass spectrometry were used to characterize thirteen of those fifteen differentially expressed proteins. These results (reproducibility, protein characterization, set of test samples, and proof-of-principle) suggest that the analysis of human CSF two-dimensional gels can achieve a high level of within-sample and between-sample reproducibility, and that PDQuest software can measure the relative protein abundance in the human CSF proteome.

Adult↗
PubMed2004

A proteomic view of cell physiology of Bacillus licheniformis.

The still ongoing sequencing of Bacillus licheniformis at the Göttingen Sequencing Laboratory provides the basis for proteome studies of the bacterium. By using two-dimensional (2-D) electrophoresis and protein identification by mass spectrometry, we were able to create master gels for B. licheniformis cells grown either in minimal medium or in complex medium containing about 300 and 180 entries, respectively. With the DECODON Delta 2D software we identified the most abundant protein spots on the gels, which were shown to perform mainly basic metabolic functions in the cell such as translation, amino acid metabolism, glycolysis, and tricarboxylic acid (TCA) cycle. Based on the master gels, we were able to study the regulation of metabolic pathways such as glycolysis and TCA cycle. In cells grown in the presence of glucose a significant increase of the amount of some glycolytic enzymes (TpiA, GapA, Pgk, Pgm, Eno, Pyk) and of the pyruvate dehydrogenase (PdhA-D) was found. At the same time, there is a strong repression of almost all TCA cycle enzymes and of the ATP synthase. Glucose also stimulates the acetate kinase (AckA) and the phosphotransacetylase (Pta) which are known to be involved in the overflow metabolism in B. subtilis. Furthermore, we began developing proteomic signatures for growth of B. licheniformis in complex medium. For this purpose, we compared the proteome pattern of exponentially growing cells with that of cells in different stages during stationary phase. The most obvious proteomic signature indicates that cells during stationary phase are subjected to a severe oxidative stress and a resulting protein stress. Furthermore, the level of many vegetative proteins is strongly reduced when the growth is arrested after entry into stationary phase. The data indicate that proteomics can be a valuable tool to describe the physiological state of B. licheniformis cell populations, e.g., of cells growing in a bioreactor.

Bacillus↗
PubMed2004

Proteomic investigation of natural variation between Arabidopsis ecotypes.

Two-dimensional (2-D) gel electrophoresis and peptide mass fingerprinting were used to investigate the natural variation in the proteome among 8 Arabidopsis thaliana ecotypes, of which 3 were previously shown to display atypical responses to environmental stress. Comparison of 2-D maps demonstrated that only one-quarter of spots was shared by all accessions. On the other hand, only 15% of the 25 majors spots accounting for half the total protein amount could be classified as major spots in all ecotypes. Identification of these major spots demonstrated large differences between the major functions detected. Accordingly, the proteomes appeared to reveal important variations in terms of function between ecotypes. Hierarchical clustering of proteomes according to either the amount of all anonymous spots, that of the 25 major spots or the functions of these major spots identified the same classes of ecotypes, and grouped the three atypical ecotypes. It is proposed that proteome comparison has the capacity to evidence differences in the physiological status of ecotypes. Results are discussed with respect to the possibility to infer such differences from limited comparisons of major proteins. It is concluded that classical proteomics could constitute a powerful tool to mine the biodiversity between ecotypes of a single plant species.

Arabidopsis↗
PubMed2004

Presentation of differentially regulated proteins within a web-accessible proteome database system of microorganisms.

Web-accessible proteome databases represent indispensable tools for quantitative and comparative proteomics research. The majority of two-dimensional gel electrophoresis (2-DE) databases contains clickable 2-DE gel images and descriptive textual information such as protein name, Mr/pI values, methods of identification, cellular localization and other information on proteins. Although a great part of the work in comparative proteomics consists of the analysis of 2-DE gels using image analysis approaches, most proteome databases lack the ability to present protein abundance data and their alterations within experiments via the web. Now, differentially regulated proteins detected in microbial experiments by quantitative gel image analysis are presented in a web-accessible relational database DIFF (Differentially Regulated Proteins). The DIFF database is a part of the proteome database system for microbial research available at http://www.mpiib-berlin.mpg.de/2D-PAGE.

Bacterial Proteins↗
PubMed2005

Proteomic profiling of facial development in chick embryos.

Craniofacial disorders are associated with one-third of human birth defects but the underlying molecular and cellular causes remain poorly understood. Proteomics seems well-placed to benefit this medically important area but the scarcity of embryonic tissues poses a major challenge. In this study, we applied a microsample proteomics strategy to investigate the first branchial arch, an embryonic structure crucial for facial development, and found that proteome analysis is both practicable and informative despite the scarcity of tissue. Exploiting the embryonic chick as a tractable source of accurately staged tissue, we developed a sequential extraction procedure to interface with one-dimensional polyacrylamide gel electrophoresis (1-D PAGE) and 2-D PAGE. In 2-D gels, about 8% of the visible proteome changed between embryonic days 3 and 5, and the identities determined for 21 proteins accorded with the rapid growth during this period. These results led to the first molecular identification of chicken alpha-fetoprotein, and an unusual localisation of vimentin to endoderm. With over 470 protein spots accessible, this comparative proteomics approach has good prospects for providing new markers, functional hypotheses and genes to target in functional tests. A broader value of extending these approaches to facial development in other species and to other areas in embryology can be anticipated.

Albumins↗