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Expert Review of Proteomics Jun 2021Fibroblasts maintain tissue and organ homeostasis through output of extracellular matrix that affects nearby cell signaling within the stroma. Altered fibroblast... (Review)
Review
INTRODUCTION
Fibroblasts maintain tissue and organ homeostasis through output of extracellular matrix that affects nearby cell signaling within the stroma. Altered fibroblast signaling contributes to many disease states and extracellular matrix secreted by fibroblasts has been used to stratify patient by outcome, recurrence, and therapeutic resistance. Recent advances in imaging mass spectrometry allow access to single cell fibroblasts and their ECM niche within clinically relevant tissue samples.
AREAS COVERED
We review biological and technical challenges as well as new solutions to proteomic access of fibroblast expression within the complex tissue microenvironment. Review topics cover conventional proteomic methods for single fibroblast analysis and current approaches to accessing single fibroblast proteomes by imaging mass spectrometry approaches. Strategies to target and evaluate the single cell stroma proteome on the basis of cell signaling are presented.
EXPERT OPINION
The promise of defining proteomic signatures from fibroblasts and their extracellular matrix niches is the discovery of new disease markers and the ability to refine therapeutic treatments. Several imaging mass spectrometry approaches exist to define the fibroblast in the setting of pathological changes from clinically acquired samples. Continued technology advances are needed to access and understand the stromal proteome and apply testing to the clinic.
Topics: Extracellular Matrix; Fibroblasts; Humans; Mass Spectrometry; Proteome; Proteomics
PubMed: 34129411
DOI: 10.1080/14789450.2021.1941893 -
Current Opinion in Chemical Biology Dec 2022Tracking proteins' biophysical characteristics on a proteome-wide scale can provide valuable information on their functions and interactions. Thermal proteome profiling... (Review)
Review
Tracking proteins' biophysical characteristics on a proteome-wide scale can provide valuable information on their functions and interactions. Thermal proteome profiling (TPP) is a multiplexed quantitative proteomics approach that measures changes in protein thermal stability-a key biophysical property-across different cellular states. Developed in 2014, as a target-deconvolution assay for drugs and other small molecules, TPP has since evolved to a system-level biochemical omics technique providing insights into context-dependent changes in protein states. In this review, we summarise key advances in the experimental and data analysis pipeline that have aided this transformation and discuss the recent developments and applications of TPP.
Topics: Proteome; Proteomics; Protein Processing, Post-Translational; Protein Stability; Protein Binding
PubMed: 36368297
DOI: 10.1016/j.cbpa.2022.102225 -
Genomics, Proteomics & Bioinformatics Oct 2021In the past decade, relative proteomic quantification using isobaric labeling technology has developed into a key tool for comparing the expression of proteins in... (Review)
Review
In the past decade, relative proteomic quantification using isobaric labeling technology has developed into a key tool for comparing the expression of proteins in biological samples. Although its multiplexing capacity and flexibility make this a valuable technology for addressing various biological questions, its quantitative accuracy and precision still pose significant challenges to the reliability of its quantification results. Here, we give a detailed overview of the different kinds of isobaric mass tags and the advantages and disadvantages of the isobaric labeling method. We also discuss which precautions should be taken at each step of the isobaric labeling workflow, to obtain reliable quantification results in large-scale quantitative proteomics experiments. In the last section, we discuss the broad applications of the isobaric labeling technology in biological and clinical studies, with an emphasis on thermal proteome profiling and proteogenomics.
Topics: Proteome; Proteomics; Reproducibility of Results; Tandem Mass Spectrometry
PubMed: 35007772
DOI: 10.1016/j.gpb.2021.08.012 -
Biochimica Et Biophysica Acta. Proteins... Jul 2021Single-cell analysis came to change the way we look at cell populations. RNA sequencing of single cells allowed us to appreciate the diversity of cell types in the human... (Review)
Review
Single-cell analysis came to change the way we look at cell populations. RNA sequencing of single cells allowed us to appreciate the diversity of cell types in the human brain in an unprecedented manner and its power to reveal cell-type specific changes in cell populations has just begun to be explored. In this context, looking at the proteome of single cells promises to bring functional information and contribute to completing the picture. The potential of single cell proteome, in developing a better understanding of the intricate connections between the very diverse cell populations in the brain, is huge. Whereas early approaches to address single-cell proteome have identified hundreds of proteins, today, techniques combining isobaric labelling and LC-MS can lead to the identification of thousands of proteins. In this review, we describe methods which have been used to identify and quantify proteins from single cells and propose that the application of isobaric labeling and label-free quantitative proteomics approach for single-cell analysis is ready to provide useful information for the neurobiology field.
Topics: Animals; Chromatography, Liquid; Humans; Neurobiology; Proteome; Proteomics; Single-Cell Analysis; Tandem Mass Spectrometry
PubMed: 33845200
DOI: 10.1016/j.bbapap.2021.140658 -
Expert Review of Proteomics 2022Schistosomes are long-lived blood dwelling helminth parasites using intricate mechanisms to invade, mature, and reproduce inside their vertebrate hosts, whilst...
INTRODUCTION
Schistosomes are long-lived blood dwelling helminth parasites using intricate mechanisms to invade, mature, and reproduce inside their vertebrate hosts, whilst simultaneously deploying immune evasion strategies. Their multi-tissue organization and solid body plan presents particular problems for the definition of sub-proteomes.
AREAS COVERED
Here, we focus on the two host-parasite interfaces of the adult worm accessible to the immune system, namely the tegument and the alimentary tract, but also on the secretions of the infective cercaria, the migrating schistosomulum and the mature egg. In parallel, we introduce the concepts of "leakyome' and 'disintegrome' to emphasize the importance of interpreting data in the context of schistosome biology so that misleading conclusions about the distinct proteome compositions are avoided. Lastly, we highlight the possible clinical implications of the reviewed proteomic findings for pathogenesis, vaccine design and diagnostics.
EXPERT OPINION
Proteomics has provided considerable insights into the biology of schistosomes, most importantly for rational selection of novel vaccine candidates that might confer protective immunity, but also into the pathogenesis of schistosomiasis. However, given the increasing sensitivity of mass spectrometric instrumentation, we stress the need for care in data interpretation since schistosomes do not deviate from the fundamental rules of eukaryotic cell biology.
Topics: Animals; Proteomics; Helminth Proteins; Schistosoma; Schistosomiasis; Vaccines; Proteome
PubMed: 36331139
DOI: 10.1080/14789450.2022.2142565 -
Proteomics Aug 2022For a long time, targeted and discovery proteomics covered different corners of the detection spectrum, with targeted proteomics focused on small target sets. This... (Review)
Review
For a long time, targeted and discovery proteomics covered different corners of the detection spectrum, with targeted proteomics focused on small target sets. This changed with the recent advances in highly multiplexed analysis. While discovery proteomics still pushes higher numbers of identified and quantified proteins, the advances in targeted proteomics rose to cover large parts of less complex proteomes or proteomes with low protein detection counts due to dynamic range restrictions, like the blood proteome. These new developments will impact, especially on the field of biomarker discovery and the possibility of using targeted proteomics for diagnostic purposes.
Topics: Mass Spectrometry; Proteome; Proteomics
PubMed: 35816345
DOI: 10.1002/pmic.202100330 -
Platelets Dec 2023Multi-omics approaches are being used increasingly to study physiological and pathophysiologic processes. Proteomics specifically focuses on the study of proteins as...
Multi-omics approaches are being used increasingly to study physiological and pathophysiologic processes. Proteomics specifically focuses on the study of proteins as functional elements and key contributors to, and markers of the phenotype, as well as targets for diagnostic and therapeutic approaches. Depending on the condition, the plasma proteome can mirror the platelet proteome, and hence play an important role in elucidating both physiologic and pathologic processes. In fact, both plasma and platelet protein signatures have been shown to be important in the setting of thrombosis-prone disease states such as atherosclerosis and cancer. Plasma and platelet proteomes are increasingly being studied as a part of a single entity, as is the case with patient-centric sample collection approaches such as capillary blood. Future studies should cut across the plasma and platelet proteome silos, taking advantage of the vast knowledge available when they are considered as part of the same studies, rather than studied as distinct entities.
Topics: Blood Platelets; Proteome; Phenotype; Plasma; Proteomics
PubMed: 36894508
DOI: 10.1080/09537104.2023.2186707 -
Bioinformatics (Oxford, England) Oct 2022The comprehensive analysis of the proteome and its modulation by post-translational modification (PTM) is increasingly used in biological and biomedical studies. As a...
SUMMARY
The comprehensive analysis of the proteome and its modulation by post-translational modification (PTM) is increasingly used in biological and biomedical studies. As a result, proteomics data analysis is ever more carried out by scientists with limited expertise in this type of data. While excellent software solutions for comprehensive and rigorous analysis of quantitative proteomic data exist, most are complex and not well suited for non-proteomics scientists. Integrative analysis of multi-level proteomics data on protein and diverse PTMs, like phosphorylation or proteolytic processing, remains particularly challenging and inaccessible to most biologists. To fill this void, we developed SQuAPP, an R-Shiny web-based analysis pipeline for the quantitative analysis of proteomic data. SQuAPP uses a streamlined workflow model to guide expert and novice users through quality control, data pre-processing, statistical analysis and visualization steps. Processing the protein, peptide and PTM datasets in parallel and their quantitative integration enable rapid identification of protein-level-independent modulation of protein modifications and intuitive interpretation of dynamic dependencies between different protein modifications.
AVAILABILITY AND IMPLEMENTATION
SQuAPP is available at http://squapp.langelab.org/. The source code and local setup instructions can be accessed from https://github.com/LangeLab/SQuAPP.
Topics: Proteomics; Proteome; Protein Processing, Post-Translational; Software; Phosphorylation
PubMed: 36102800
DOI: 10.1093/bioinformatics/btac628 -
Nucleic Acids Research Jan 2022Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric...
Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point-the pH at which a particular molecule carries no net electrical charge-is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides' isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org.
Topics: Amino Acid Sequence; Computational Biology; Databases, Protein; Electrophoresis, Gel, Two-Dimensional; Isoelectric Point; Molecular Weight; Peptides; Proteome; Proteomics
PubMed: 34718696
DOI: 10.1093/nar/gkab944 -
Briefings in Bioinformatics Jan 2021Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers... (Review)
Review
Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.
Topics: Biomarkers; Body Fluids; Humans; Proteome; Proteomics
PubMed: 32020158
DOI: 10.1093/bib/bbz160