Absolute protein quantification allows differentiation of cell-specific metabolic routes and functions

Ibaqpy: A scalable Python package for baseline quantification in proteomics leveraging SDRF metadata

Intensity-based absolute quantification (iBAQ) is essential in proteomics as it allows for the assessment of a protein's absolute abundance in various samples or conditions. However, the computation of these values for increasingly large-scale and high-throughput experiments, such as those using DIA, TMT, or LFQ workflows, poses significant challenges in scalability and reproducibility. Here, we present ibaqpy (https://github.com/bigbio/ibaqpy), a Python package designed to compute iBAQ values efficiently for experiments of any scale. Ibaqpy leverages the Sample and Data Relationship Format (SDRF) metadata standard to incorporate experimental metadata into the quantification workflow. This allows for automatic normalization and batch correction while accounting for key aspects of the experimental design, such as technical and biological replicates, fractionation strategies, and sample conditions. Designed for large-scale proteomics datasets, ibaqpy can also recompute iBAQ values for existing experiments when an SDRF is available. We showcased ibaqpy's capabilities by reanalyzing 17 public proteomics datasets from ProteomeXchange, covering HeLa cell lines with 4921 samples and 5766 MS runs, quantifying a total of 11,014 proteins. In our reanalysis, ibaqpy is a key component in automating reproducible quantification, reducing manual effort and making quantitative proteomics more accessible while supporting FAIR principles for data reuse. SIGNIFICANCE: Proteomics studies often rely on intensity-based absolute quantification (iBAQ) to assess protein abundance across various biological conditions. Despite its widespread use, computing iBAQ values at scale remains challenging due to the increasing complexity and volume of proteomics experiments. Existing tools frequently lack metadata integration, limiting their ability to handle experimental design intricacies such as replicates, fractions, and batch effects. Our work introduces ibaqpy, a scalable Python package that leverages the Sample and Data Relationship Format (SDRF) to compute iBAQ values efficiently while incorporating critical experimental metadata. By enabling automated normalization and batch correction, ibaqpy ensures reproducible and comparable quantification across large-scale datasets. We validated the utility of ibaqpy through the reanalysis of 17 public HeLa datasets, comprising over 200 million peptide features and quantifying 11,000 proteins across thousands of samples. This comprehensive reanalysis highlights the robustness and scalability of ibaqpy, making it an essential tool for researchers conducting large-scale proteomics experiments. Moreover, by promoting FAIR principles for data reuse and interoperability, ibaqpy offers a transformative approach to baseline protein quantification, supporting reproducible research and data integration within the proteomics community.

An optimized proteomics-based approach to estimate blood contamination and cellular heterogeneity of frozen placental tissue

INTRODUCTION

Archived human placental tissue specimens are vital for studying placenta pathophysiology and toxicology. Proteomics analysis of placental tissue provides mechanistic and translational information, but the highly perfused and heterogenous nature of the placenta creates confounding technical variability. In this study, we developed an optimized proteomics-based approach to address the technical variability of proteomics data by normalizing blood contamination and cellular heterogeneity of archived placenta samples.

METHODS

Placenta samples (n = 99) were homogenized, digested using trypsin, and analyzed by liquid chromatography mass-spectrometry. Label-free quantification (LFQ) intensities of the proteins were analyzed for their correlation with blood (albumin) and placenta (aromatase) markers. Proteins that positively correlated with albumin and negatively correlated with aromatase or vice versa were considered blood and placental proteins, respectively. Next, the cellular heterogeneity of individual placenta samples was evaluated by quantifying specific cellular markers of cytotrophoblasts, syncytiotrophoblasts, extravillous trophoblasts, fibroblasts, Hofbauer cells, and decidual cells.

RESULTS

We found that placental proteins were contaminated by 41 to 85% blood proteins. Analysis of cellular markers confirmed syncytiotrophoblasts as the major cell type in placenta (i.e., 41 ± 9% of all cell types). Two samples showed distinct cell compositions with higher levels of the extravillous trophoblasts and decidual cells.

DISCUSSION

In summary, the optimized proteomics-based approach to estimate blood contamination and cellular heterogeneity of placental tissues has the potential to address technical variability in placenta proteomics analysis, which can be extended to other highly perfused and heterogenous tissues.

The Curious Case of the HepG2 Cell Line: 40 Years of Expertise

Liver cancer is the third leading cause of cancer death worldwide. Representing such a dramatic impact on our lives, liver cancer is a significant public health concern. Sustainable and reliable methods for preventing and treating liver cancer require fundamental research on its molecular mechanisms. Cell lines are treated as in vitro equivalents of tumor tissues, making them a must-have for basic research on the nature of cancer. According to recent discoveries, certified cell lines retain most genetic properties of the original tumor and mimic its microenvironment. On the other hand, modern technologies allowing the deepest level of detail in omics landscapes have shown significant differences even between samples of the same cell line due to cross- and mycoplasma infection. This and other observations suggest that, in some cases, cell cultures are not suitable as cancer models, with limited predictive value for the effectiveness of new treatments. HepG2 is a popular hepatic cell line. It is used in a wide range of studies, from the oncogenesis to the cytotoxicity of substances on the liver. In this regard, we set out to collect up-to-date information on the HepG2 cell line to assess whether the level of heterogeneity of the cell line allows in vitro biomedical studies as a model with guaranteed production and quality.

The Curious Case of the HepG2 Cell Line: 40 Years of Expertise

Liver cancer is the third leading cause of cancer death worldwide. Representing such a dramatic impact on our lives, liver cancer is a significant public health concern. Sustainable and reliable methods for preventing and treating liver cancer require fundamental research on its molecular mechanisms. Cell lines are treated as in vitro equivalents of tumor tissues, making them a must-have for basic research on the nature of cancer. According to recent discoveries, certified cell lines retain most genetic properties of the original tumor and mimic its microenvironment. On the other hand, modern technologies allowing the deepest level of detail in omics landscapes have shown significant differences even between samples of the same cell line due to cross- and mycoplasma infection. This and other observations suggest that, in some cases, cell cultures are not suitable as cancer models, with limited predictive value for the effectiveness of new treatments. HepG2 is a popular hepatic cell line. It is used in a wide range of studies, from the oncogenesis to the cytotoxicity of substances on the liver. In this regard, we set out to collect up-to-date information on the HepG2 cell line to assess whether the level of heterogeneity of the cell line allows in vitro biomedical studies as a model with guaranteed production and quality.

The Curious Case of the HepG2 Cell Line: 40 Years of Expertise

Liver cancer is the third leading cause of cancer death worldwide. Representing such a dramatic impact on our lives, liver cancer is a significant public health concern. Sustainable and reliable methods for preventing and treating liver cancer require fundamental research on its molecular mechanisms. Cell lines are treated as in vitro equivalents of tumor tissues, making them a must-have for basic research on the nature of cancer. According to recent discoveries, certified cell lines retain most genetic properties of the original tumor and mimic its microenvironment. On the other hand, modern technologies allowing the deepest level of detail in omics landscapes have shown significant differences even between samples of the same cell line due to cross- and mycoplasma infection. This and other observations suggest that, in some cases, cell cultures are not suitable as cancer models, with limited predictive value for the effectiveness of new treatments. HepG2 is a popular hepatic cell line. It is used in a wide range of studies, from the oncogenesis to the cytotoxicity of substances on the liver. In this regard, we set out to collect up-to-date information on the HepG2 cell line to assess whether the level of heterogeneity of the cell line allows in vitro biomedical studies as a model with guaranteed production and quality.

Selective Roles of Vertebrate PCF11 in Premature and Full-Length Transcript Termination

The pervasive nature of RNA polymerase II (Pol II) transcription requires efficient termination. A key player in this process is the cleavage and polyadenylation (CPA) factor PCF11, which directly binds to the Pol II C-terminal domain and dismantles elongating Pol II from DNA in vitro. We demonstrate that PCF11-mediated termination is essential for vertebrate development. A range of genomic analyses, including mNET-seq, 3′ mRNA-seq, chromatin RNA-seq, and ChIP-seq, reveals that PCF11 enhances transcription termination and stimulates early polyadenylation genome-wide. PCF11 binds preferentially between closely spaced genes, where it prevents transcriptional interference and consequent gene downregulation. Notably, PCF11 is sub-stoichiometric to the CPA complex. Low levels of PCF11 are maintained by an auto-regulatory mechanism involving premature termination of its own transcript and are important for normal development. Both in human cell culture and during zebrafish development, PCF11 selectively attenuates the expression of other transcriptional regulators by premature CPA and termination.

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Human PCF11 enhances transcription termination and 3′ end processing, genome-wide

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PCF11 is substoichiometric to CPA complex due to autoregulation of its transcription

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PCF11 stimulates expression of closely spaced genes but attenuates other genes

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PCF11-mediated functions are conserved in vertebrates and essential in development

A conformational switch regulates the ubiquitin ligase HUWE1

The human ubiquitin ligase HUWE1 has key roles in tumorigenesis, yet it is unkown how its activity is regulated. We present the crystal structure of a C-terminal part of HUWE1, including the catalytic domain, and reveal an asymmetric auto-inhibited dimer. We show that HUWE1 dimerizes in solution and self-associates in cells, and that both occurs through the crystallographic dimer interface. We demonstrate that HUWE1 is inhibited in cells and that it can be activated by disruption of the dimer interface. We identify a conserved segment in HUWE1 that counteracts dimer formation by associating with the dimerization region intramolecularly. Our studies reveal, intriguingly, that the tumor suppressor p14ARF binds to this segment and may thus shift the conformational equilibrium of HUWE1 toward the inactive state. We propose a model, in which the activity of HUWE1 underlies conformational control in response to physiological cues-a mechanism that may be exploited for cancer therapy.

Label-Free Quantitative Analysis of Mitochondrial Proteomes Using the Multienzyme Digestion-Filter Aided Sample Preparation (MED-FASP) and "Total Protein Approach"

Determination of proteome composition and measuring of changes in protein titers provide important information with a substantial value for studying mitochondria.This chapter describes a workflow for the quantitative analysis of mitochondrial proteome with a focus on sample preparation and quantitative analysis of the data. The workflow involves the multienzyme digestion-filter aided sample preparation (MED-FASP) protocol enabling efficient extraction of proteins and high rate of protein-to-peptide conversion. Consecutive protein digestion with Lys C and trypsin enables generation of peptide fractions with minimal overlap, largely increases the number of identified proteins, and extends their sequence coverage. Abundances of proteins identified by multiple peptides can be assessed by the "Total Protein Approach."

Combined Quantification of the Global Proteome, Phosphoproteome, and Proteolytic Cleavage to Characterize Altered Platelet Functions in the Human Scott Syndrome

The Scott syndrome is a very rare and likely underdiagnosed bleeding disorder associated with mutations in the gene encoding anoctamin-6. Platelets from Scott patients are impaired in various Ca²⁺-dependent responses, including phosphatidylserine exposure, integrin closure, intracellular protein cleavage, and cytoskeleton-dependent morphological changes. Given the central role of anoctamin-6 in the platelet procoagulant response, we used quantitative proteomics to understand the underlying molecular mechanisms and the complex phenotypic changes in Scott platelets compared with control platelets. Therefore, we applied an iTRAQ-based multi-pronged strategy to quantify changes in (1) the global proteome, (2) the phosphoproteome, and (3) proteolytic events between resting and stimulated Scott and control platelets. Our data indicate a limited number of proteins with decreased (70) or increased (64) expression in Scott platelets, among those we confirmed the absence of anoctamin-6 and the strong up-regulation of aquaporin-1 by parallel reaction monitoring. The quantification of 1566 phosphopeptides revealed major differences between Scott and control platelets after stimulation with thrombin/convulxin or ionomycin. In Scott platelets, phosphorylation levels of proteins regulating cytoskeletal or signaling events were increased. Finally, we quantified 1596 N-terminal peptides in activated Scott and control platelets, 180 of which we identified as calpain-regulated, whereas a distinct set of 23 neo-N termini was caspase-regulated. In Scott platelets, calpain-induced cleavage of cytoskeleton-linked and signaling proteins was downregulated, in accordance with an increased phosphorylation state. Thus, multipronged proteomic profiling of Scott platelets provides detailed insight into their protection against detrimental Ca²⁺-dependent changes that are normally associated with phosphatidylserine exposure.

Proteomics Unveils Fibroblast-Cardiomyocyte Lactate Shuttle and Hexokinase Paradox in Mouse Muscles

Quantitative mapping, given in biochemically interpretable units such as mol per mg of total protein, of tissue-specific proteomes is prerequisite for the analysis of any process in cells. We applied label- and standard-free proteomics to characterize three types of striated muscles: white, red, and cardiac muscle. The analysis presented here uncovers several unexpected and novel features of striated muscles. In addition to differences in protein expression levels, the three muscle types substantially differ in their patterns of basic metabolic pathways and isoforms of regulatory proteins. Importantly, some of the conclusions drawn on the basis of our results, such as the potential existence of a "fibroblast-cardiomyocyte lactate shuttle" and the "hexokinase paradox" point to the necessity of reinterpretation of some basic aspects of striated muscle metabolism. The data presented here constitute a powerful database and a resource for future studies of muscle physiology and for the design of pharmaceutics for the treatment of muscular disorders.

A Proteomics Approach to the Protein Normalization Problem: Selection of Unvarying Proteins for MS-Based Proteomics and Western Blotting

Proteomics and other protein-based analysis methods such as Western blotting all face the challenge of discriminating changes in the levels of proteins of interest from inadvertent changes in the amount loaded for analysis. Mass-spectrometry-based proteomics can now estimate the relative and absolute amounts of thousands of proteins across diverse biological systems. We reasoned that this new technology could prove useful for selection of very stably expressed proteins that could serve as better loading controls than those traditionally employed. Large-scale proteomic analyses of SDS lysates of cultured cells and tissues revealed deglycase DJ-1 as the protein with the lowest variability in abundance among different cell types in human, mouse, and amphibian cells. The protein constitutes 0.069 ± 0.017% of total cellular protein and occurs at a specific concentration of 34.6 ± 8.7 pmol/mg of total protein. Since DJ-1 is ubiquitous and therefore easily detectable with several peptides, it can be helpful in normalization of proteomic data sets. In addition, DJ-1 appears to be an advantageous loading control for Western blot that is superior to those used commonly used, allowing comparisons between tissues and cells originating from evolutionarily distant vertebrate species. Notably, this is not possible by the detection and quantitation of housekeeping proteins, which are often used in the Western blot technique. The approach introduced here can be applied to select the most appropriate loading controls for MS-based proteomics or Western blotting in any biological system.

Insulin/IGF1-PI3K-dependent nucleolar localization of a glycolytic enzyme--phosphoglycerate mutase 2, is necessary for proper structure of nucleolus and RNA synthesis

Phosphoglycerate mutase (PGAM), a conserved, glycolytic enzyme has been found in nucleoli of cancer cells. Here, we present evidence that accumulation of PGAM in the nucleolus is a universal phenomenon concerning not only neoplastically transformed but also non-malignant cells. Nucleolar localization of the enzyme is dependent on the presence of the PGAM2 (muscle) subunit and is regulated by insulin/IGF-1–PI3K signaling pathway as well as drugs influencing ribosomal biogenesis. We document that PGAM interacts with several 40S and 60S ribosomal proteins and that silencing of PGAM2 expression results in disturbance of nucleolar structure, inhibition of RNA synthesis and decrease of the mitotic index of squamous cell carcinoma cells. We conclude that presence of PGAM in the nucleolus is a prerequisite for synthesis and initial assembly of new pre-ribosome subunits.

Quantitative Evaluation of Filter Aided Sample Preparation (FASP) and Multienzyme Digestion FASP Protocols

Filter aided sample preparation (FASP) and related methods gain increasing popularity for proteomic sample preparation. Nevertheless, the originally published FASP method has been criticized by several authors, who reported low digestion performance. In this work, we re-evaluate FASP and the related multienzyme digestion (MED) FASP method. We use different types of animal tissues and cultured cells and test the performance of the method under various conditions. We analyze the protein to peptide conversion by assessing the yield of peptides, frequency of peptides with missed cleavage sites, and the reproducibility of FASP. We identify conditions allowing efficient protein processing with high peptide yields and demonstrate advantages of the two step digestion strategy over single step digestion with trypsin. In addition, we show that FASP outperforms in-solution cleavage strategies. Our results clearly demonstrate that the performance of digestion varies between different types of samples. We show that MED FASP in combination with the total protein approach provides highly reproducible protein abundance values. The presented data can be used as a guide for optimization of sample processing.

Will Quantitative Proteomics Redefine Some of the Key Concepts in Skeletal Muscle Physiology?

Molecular and cellular biology methodology is traditionally based on the reasoning called “the mechanistic explanation”. In practice, this means identifying and selecting correlations between biological processes which result from our manipulation of a biological system. In theory, a successful application of this approach requires precise knowledge about all parameters of a studied system. However, in practice, due to the systems’ complexity, this requirement is rarely, if ever, accomplished. Typically, it is limited to a quantitative or semi-quantitative measurements of selected parameters (e.g., concentrations of some metabolites), and a qualitative or semi-quantitative description of expression/post-translational modifications changes within selected proteins. A quantitative proteomics approach gives a possibility of quantitative characterization of the entire proteome of a biological system, in the context of the titer of proteins as well as their post-translational modifications. This enables not only more accurate testing of novel hypotheses but also provides tools that can be used to verify some of the most fundamental dogmas of modern biology. In this short review, we discuss some of the consequences of using quantitative proteomics to verify several key concepts in skeletal muscle physiology.

Absolute Proteome Analysis of Colorectal Mucosa, Adenoma, and Cancer Reveals Drastic Changes in Fatty Acid Metabolism and Plasma Membrane Transporters

Colorectal cancer is a leading cause of cancer-related death. It develops from normal enterocytes, through a benign adenoma stage, into the cancer and finally into the metastatic form. We previously compared the proteomes of normal colorectal enterocytes, cancer and nodal metastasis to a depth of 8100 proteins and found extensive quantitative remodeling between normal and cancer tissues but not cancer and metastasis (Wiśniewski et al. PMID 22968445). Here we utilize advances in the proteomic workflow to perform an in depth analysis of the normal tissue (N), the adenoma (A), and the cancer (C). Absolute proteomics of 10 000 proteins per patient from microdissected formalin-fixed and paraffin-embedded clinical material established a quantitative protein repository of the disease. Between N and A, 23% of all proteins changed significantly, 17.8% from A to C and 21.6% from N to C. Together with principal component analysis of the patient groups, this suggests that N, A, and C are equidistant but not on one developmental line. Our proteomics approach allowed us to assess changes in varied cell size, the composition of different subcellular components, and alterations in basic biological processes including the energy metabolism, plasma membrane transport, DNA replication, and transcription. This revealed several-fold higher concentrations of enzymes in fatty acid metabolism in C compared with N, and unexpectedly, the same held true of plasma membrane transporters.