Sensitive Quantitative Proteomics of Human Hematopoietic Stem and Progenitor Cells by Data-independent Acquisition Mass Spectrometry

Droplet-based proteomics reveals CD36 as a marker for progenitors in mammary basal epithelium

Deep proteomic profiling of rare cell populations has been constrained by sample input requirements. Here, we present DROPPS (droplet-based one-pot preparation for proteomic samples), an accessible low-input platform that generates high-fidelity proteomic profiles of 100-2,500 cells. By applying DROPPS within the mammary epithelium, we elucidated the connection between mitochondrial activity and clonogenicity, identifying CD36 as a marker of progenitor capacity in the basal cell compartment. We anticipate that DROPPS will accelerate biology-driven proteomic research for a multitude of rare cell populations.

SMYD3: a new regulator of adipocyte precursor proliferation at the early steps of differentiation

BACKGROUND

In obesity, adipose tissue undergoes a remodeling process characterized by increased adipocyte size (hypertrophia) and number (hyperplasia). The ability to tip the balance toward the hyperplastic growth, with recruitment of new fat cells through adipogenesis, seems to be critical for a healthy adipose tissue expansion, as opposed to a hypertrophic growth that is accompanied by the development of inflammation and metabolic dysfunction. However, the molecular mechanisms underlying the fine-tuned regulation of adipose tissue expansion are far from being understood.

METHODS

We analyzed by mass spectrometry-based proteomics visceral white adipose tissue (vWAT) samples collected from C57BL6 mice fed with a HFD for 8 weeks. A subset of these mice, called low inflammation (Low-INFL), showed reduced adipose tissue inflammation, as opposed to those developing the expected inflammatory response (Hi-INFL). We identified the discriminants between Low-INFL and Hi-INFL vWAT samples and explored their function in Adipose-Derived human Mesenchymal Stem Cells (AD-hMSCs) differentiated to adipocytes.

RESULTS

vWAT proteomics allowed us to quantify 6051 proteins. Among the candidates that most differentiate Low-INFL from Hi-INFL vWAT, we found proteins involved in adipocyte function, including adiponectin and hormone sensitive lipase, suggesting that adipocyte differentiation is enhanced in Low-INFL, as compared to Hi-INFL. The chromatin modifier SET and MYND Domain Containing 3 (SMYD3), whose function in adipose tissue was so far unknown, was another top-scored hit. SMYD3 expression was significantly higher in Low-INFL vWAT, as confirmed by western blot analysis. Using AD-hMSCs in culture, we found that SMYD3 mRNA and protein levels decrease rapidly during the adipocyte differentiation. Moreover, SMYD3 knock-down before adipocyte differentiation resulted in reduced H3K4me3 and decreased cell proliferation, thus limiting the number of cells available for adipogenesis.

CONCLUSIONS

Our study describes an important role of SMYD3 as a newly discovered regulator of adipocyte precursor proliferation during the early steps of adipogenesis.

Serum proteomics identifies novel diagnostic biomarkers for asthma in preschool children

Background

Asthma is characterized by airway hyperresponsiveness, reversible airway obstruction, and chronic airway inflammation. It is the most common chronic disease in childhood. However, the diagnosis of childhood asthma remains challenging, and there is an urgent need to develop new diagnostic methods.

Methods

To identify biomarkers of asthma in children, we adopted the Orbitrap-based data-independent acquisition (DIA) mass spectrometry proteomics method to analyze the serum proteomic signatures of children with acute asthma and convalescent children.

Results

We identified 747 proteins in 46 serum samples and 50 differentially expressed proteins (DEPs) that distinguished between asthmatic and healthy children. Next, functional enrichment analysis of the DEPs was conducted, it was indicated that the DEPs were significantly enriched in immune-related and function terms and pathways. Furthermore, we performed statistical analysis and identified MMP14, ABHD12B, PCYOX1, LTBP1, CFHR4, APOA1, IGHG4, ANG and IGFALS proteins as the diagnostic biomarker candidates. Ultimately, a promising asthma diagnostic model for preschool children based on IGFALS was built and evaluated. The area under the curve (AUC) of the IGFALS model was 0.959.

Conclusions

In this study, the DIA proteome strategy was used and the largest number of proteins of asthmatic children serum proteomics was identified. The proteomics results showed that the DEPs play the central role of the inflammation-immune mechanism in asthma pathogenesis, suggesting that these proteins may be used in asthma diagnosis, prognosis, or therapy, and suggested biomarkers for asthma of preschool children. In conclusion, our results provide insight into the pathophysiology of asthma. We believe that the diagnostic model will facilitate clinical decision-making regarding asthma in preschool children.

Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape

The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.

Seeking the interspecies crosswalk for filamentous microbe effectors

Both pathogenic and symbiotic microorganisms modulate the immune response and physiology of their host to establish a suitable niche. Key players in mediating colonization outcome are microbial effector proteins that act either inside (cytoplasmic) or outside (apoplastic) the plant cells and modify the abundance or activity of host macromolecules. We compile novel insights into the much-disputed processes of effector secretion and translocation of filamentous organisms, namely fungi and oomycetes. We report how recent studies that focus on unconventional secretion and effector structure challenge the long-standing image of effectors as conventionally secreted proteins that are translocated with the aid of primary amino acid sequence motifs. Furthermore, we emphasize the potential of diverse, unbiased, state-of-the-art proteomics approaches in the holistic characterization of fungal and oomycete effectomes.

Optimizing linear ion trap data independent acquisition towards single cell proteomics

A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

Blood proteome of acute intracranial hemorrhage in infant victims of abusive head trauma

Abusive head trauma (AHT) is a leading cause of mortality and morbidity in infants. While the reported incidence is close to 40 cases per 100'000 births/year, misdiagnoses are commonly observed in cases with atypical, subacute, or chronic presentation. Currently, standard clinical evaluation of inflicted intracranial hemorrhagic injury (ICH) in infants urgently requires a screening test able to identify infants who need additional investigations. Blood biomarkers characteristic of AHT may assist in detecting these infants, improving prognosis through early medical care. To date, the application of innovative omics technologies in retrospective studies of AHT in infants is rare, due also to the blood serum and cerebrospinal fluid of AHT cases being scarce and not systematically accessible. Here, we explored the circulating blood proteomes of infants with severe AHT and their atraumatic controls. We discovered 165 circulating serum proteins that display differential changes in AHT cases compared with atraumatic controls. The peripheral blood proteomes of pediatric AHT commonly reflect: (i) potentially secreted proteome from injured brain, and (ii) proteome dysregulated in the system's circulation by successive biological events following acute ICH. This study opens up a novel opportunity for research efforts in clinical screening of AHT cases.

Proteomics to study cancer immunity and improve treatment

Cancer survival and progression depend on the ability of tumor cells to avoid immune recognition. Advances in the understanding of cancer immunity and tumor immune escape mechanisms enabled the development of immunotherapeutic approaches. In patients with otherwise incurable metastatic cancers, immunotherapy resulted in unprecedented response rates with the potential for durable complete responses. However, primary and acquired resistance mechanisms limit the efficacy of immunotherapy. Further therapeutic advances require a deeper understanding of the interplay between immune cells and tumors. Most high-throughput studies within the past decade focused on an omics characterization at DNA and RNA level. However, proteins are the molecular effectors of genomic information; therefore, the study of proteins provides deeper understanding of cellular functions. Recent advances in mass spectrometry (MS)-based proteomics at a system-wide scale may allow translational and clinical discoveries by enabling the analysis of understudied post-translational modifications, subcellular protein localization, cell signaling, and protein-protein interactions. In this review, we discuss the potential contribution of MS-based proteomics to preclinical and clinical research findings in the context of tumor immunity and cancer immunotherapies.

PLAG1 dampens protein synthesis to promote human hematopoietic stem cell self-renewal

Hematopoietic stem cell (HSC) dormancy is understood as supportive of HSC function and its long-term integrity. Although regulation of stress responses incurred as a result of HSC activation is recognized as important in maintaining stem cell function, little is understood of the preventive machinery present in human HSCs that may serve to resist their activation and promote HSC self-renewal. We demonstrate that the transcription factor PLAG1 is essential for long-term HSC function and, when overexpressed, endows a 15.6-fold enhancement in the frequency of functional HSCs in stimulatory conditions. Genome-wide measures of chromatin occupancy and PLAG1-directed gene expression changes combined with functional measures reveal that PLAG1 dampens protein synthesis, restrains cell growth and division, and enhances survival, with the primitive cell advantages it imparts being attenuated by addition of the potent translation activator, c-MYC. We find PLAG1 capitalizes on multiple regulatory factors to ensure protective diminished protein synthesis including 4EBP1 and translation-targeting miR-127 and does so independently of stress response signaling. Overall, our study identifies PLAG1 as an enforcer of human HSC dormancy and self-renewal through its highly context-specific regulation of protein biosynthesis and classifies PLAG1 among a rare set of bona fide regulators of messenger RNA translation in these cells. Our findings showcase the importance of regulated translation control underlying human HSC physiology, its dysregulation under activating demands, and the potential if its targeting for therapeutic benefit.

Characterization of naked mole-rat hematopoiesis reveals unique stem and progenitor cell patterns and neotenic traits

Naked mole rats (NMRs) are the longest-lived rodents yet their stem cell characteristics remain enigmatic. Here, we comprehensively mapped the NMR hematopoietic landscape and identified unique features likely contributing to longevity. Adult NMRs form red blood cells in spleen and marrow, which comprise a myeloid bias toward granulopoiesis together with decreased B-lymphopoiesis. Remarkably, youthful blood and marrow single-cell transcriptomes and cell compositions are largely maintained until at least middle age. Similar to primates, the primitive stem and progenitor cell (HSPC) compartment is marked by CD34 and THY1. Stem cell polarity is seen for Tubulin but not CDC42, and is not lost until 12 years of age. HSPC respiration rates are as low as in purified human stem cells, in concert with a strong expression signature for fatty acid metabolism. The pool of quiescent stem cells is higher than in mice, and the cell cycle of hematopoietic cells is prolonged. By characterizing the NMR hematopoietic landscape, we identified resilience phenotypes such as an increased quiescent HSPC compartment, absence of age-related decline, and neotenic traits likely geared toward longevity.

The Opportunity of Proteomics to Advance the Understanding of Intra- and Extracellular Regulation of Malignant Hematopoiesis

Fetal and adult hematopoiesis are regulated by largely distinct sets of cell-intrinsic gene regulatory networks as well as extracellular cues in their respective microenvironment. These ontogeny-specific programs drive hematopoietic stem and progenitor cells (HSPCs) in fetus and adult to divergent susceptibility to initiation and progression of hematological malignancies, such as leukemia. Elucidating how leukemogenic hits disturb the intra- and extracellular programs in HSPCs along ontogeny will provide a better understanding of the causes for age-associated differences in malignant hematopoiesis and facilitate the improvement of strategies for prevention and treatment of pediatric and adult acute leukemia. Here, we review current knowledge of the intrinsic and extrinsic programs regulating normal and malignant hematopoiesis, with a particular focus on the differences between infant and adult acute leukemia. We discuss the recent advances in mass spectrometry-based proteomics and its opportunity for resolving the interplay of cell-intrinsic and niche-associated factors in regulating malignant hematopoiesis.

Stress vulnerability shapes disruption of motor cortical neuroplasticity

Chronic stress is a major cause of neuropsychiatric conditions such as depression. Stress vulnerability varies individually in mice and humans, measured by behavioral changes. In contrast to affective symptoms, motor retardation as a consequence of stress is not well understood. We repeatedly imaged dendritic spines of the motor cortex in Thy1-GFP M mice before and after chronic social defeat stress. Susceptible and resilient phenotypes were discriminated by symptom load and their motor learning abilities were assessed by a gross and fine motor task. Stress phenotypes presented individual short- and long-term changes in the hypothalamic-pituitary-adrenal axis as well as distinct patterns of altered motor learning. Importantly, stress was generally accompanied by a marked reduction of spine density in the motor cortex and spine dynamics depended on the stress phenotype. We found astrogliosis and altered microglia morphology along with increased microglia-neuron interaction in the motor cortex of susceptible mice. In cerebrospinal fluid, proteomic fingerprints link the behavioral changes and structural alterations in the brain to neurodegenerative disorders and dysregulated synaptic homeostasis. Our work emphasizes the importance of synaptic integrity and the risk of neurodegeneration within depression as a threat to brain health.

Calibr improves spectral library search for spectrum-centric analysis of data independent acquisition proteomics

Identifying peptides and proteins from mass spectrometry (MS) data, spectral library searching has emerged as a complementary approach to the conventional database searching. However, for the spectrum-centric analysis of data-independent acquisition (DIA) data, spectral library searching has not been widely exploited because existing spectral library search tools are mainly designed and optimized for the analysis of data-dependent acquisition (DDA) data. We present Calibr, a spectral library search tool for spectrum-centric DIA data analysis. Calibr optimizes spectrum preprocessing for pseudo MS2 spectra, generating an 8.11% increase in spectrum–spectrum match (SSM) number and a 7.49% increase in peptide number over the traditional preprocessing approach. When searching against the DDA-based spectral library, Calibr improves SSM number by 17.6–26.65% and peptide number by 18.45–37.31% over two state-of-the-art tools on three different data sets. Searching against the public spectral library from MassIVE, Calibr improves state-of-the-art tools in SSM and peptide numbers by more than 31.49% and 25.24%, respectively, for two data sets. Our analyses indicate higher sensitivity of Calibr results from the use of various spectral similarity measures and statistical scores, coupled with machine learning-based statistical validation for FDR control. Calibr executable files including a graphical user-interface application are available at https://ms.iis.sinica.edu.tw/COmics/Software_CalibrWizard.html and https://sourceforge.net/projects/comics-calibr.

Proteomic identification of proliferation and progression markers in human polycythemia vera stem and progenitor cells

Polycythemia vera (PV) is a stem cell disorder characterized by hyperproliferation of the myeloid lineages and the presence of an activating JAK2 mutation. To elucidate mechanisms controlling PV stem and progenitor cell biology, we applied a recently developed highly sensitive data-independent acquisition mass spectrometry workflow to purified hematopoietic stem and progenitor cell (HSPC) subpopulations of patients with chronic and progressed PV. We integrated proteomic data with genomic, transcriptomic, flow cytometry and in vitro colony formation data. Comparative analyses revealed added information gained by proteomic compared with transcriptomic data in 30% of proteins with changed expression in PV patients. Upregulated biological pathways in hematopoietic stem and multipotent progenitor cells (HSC/MPPs) of PV included MTOR, STAT and interferon signaling. We further identified a prominent reduction of clusterin (CLU) protein expression and a corresponding activation of NFĸB signaling in HSC/MPPs of untreated PV patients compared with controls. Reversing the reduction of CLU and inhibiting NFĸB signaling decreased proliferation and differentiation of PV HSC/MPPs in vitro. Upon progression of PV, we identified upregulation of LGALS9 and SOCS2 protein expression in HSC/MPPs. Treatment of patients with hydroxyurea normalized the expression of CLU and NFĸB2, but not of LGALS9 and SOCS2. These findings expand the current understanding of the molecular pathophysiology underlying PV and provide new potential targets (CLU and NFĸB) for antiproliferative therapy in PV patients.

Multi-omics reveals clinically relevant proliferative drive associated with mTOR-MYC-OXPHOS activity in chronic lymphocytic leukemia

Chronic Lymphocytic Leukemia (CLL) has a complex pattern of driver mutations and much of its clinical diversity remains unexplained. We devised a method for simultaneous subgroup discovery across multiple data types and applied it to genomic, transcriptomic, DNA methylation and ex-vivo drug response data from 217 Chronic Lymphocytic Leukemia (CLL) cases. We uncovered a biological axis of heterogeneity strongly associated with clinical behavior and orthogonal to the known biomarkers. We validated its presence and clinical relevance in four independent cohorts (n=547 patients). We find that this axis captures the proliferative drive (PD) of CLL cells, as it associates with lymphocyte doubling rate, global hypomethylation, accumulation of driver aberrations and response to pro-proliferative stimuli. CLL-PD was linked to the activation of mTOR-MYC-oxidative phosphorylation (OXPHOS) through transcriptomic, proteomic and single cell resolution analysis. CLL-PD is a key determinant of disease outcome in CLL. Our multi-table integration approach may be applicable to other tumors whose inter-individual differences are currently unexplained.

Tumor Extracellular Vesicles Regulate Macrophage-Driven Metastasis through CCL5

Simple Summary

About 10–20 percent of patients with breast cancer are diagnosed with triple-negative breast cancer (TNBC). These tumors are named for their lack of expression of estrogen receptor (ER), progesterone receptor (PR), and amplification of human epidermal growth factor receptor 2 (HER2). These genes are targeted by therapies in other breast cancer patients. However, most TNBC patients recur within 5 years. Understanding how and why these tumors metastasize will help clinicians better treat these underserved cancer patients. TNBC tumors are highly infiltrated by tumor-associated macrophages (TAMs) that promote tumorigenesis and metastasis. Our study elucidates how the tumor co-opts macrophages recruited to the tumor through extracellular vesicles (EVs), further increasing tumor metastasis. Expression of tumor CCL5 regulates EV secretion and cargo that further alters macrophage phenotype to drive tumor metastasis. Together, our data suggest a more extensive role of EVs in the biology of tumor metastasis as well as their potential use as biomarkers.

Abstract

Purpose: To understand how tumor cells alter macrophage biology once they are recruited to triple-negative breast cancer (TNBC) tumors by CCL5. Method: Mouse bone marrow derived macrophage (BMDMs) were isolated and treated with recombinant CCL5 protein alone, with tumor cell conditioned media, or with tumor extracellular vesicles (EVs). Media from these tumor EV-educated macrophages (TEMs) was then used to determine how these macrophages affect TNBC invasion. To understand the mechanism, we assayed the cytokine secretion from these macrophages to determine how they impact tumor cell invasion. Tumor CCL5 expression was varied in tumors to determine its role in regulating macrophage biology through EVs. Results: Tumor EVs are a necessary component for programming naïve macrophages toward a pro-metastatic phenotype. CCL5 expression in the tumor cells regulates both EV biogenesis/secretion/cargo and macrophage EV-education toward a pro-metastatic phenotype. Analysis of the tumor EV-educated macrophages (TEMs) showed secretion of a variety of factors including CXCL1, CTLA-4, IFNG, OPN, HGF, TGFB, and CCL19 capable of remodeling the surrounding tumor stroma and immune infiltrate. Injection of tumor cells with macrophages educated by metastatic tumor cell EVs into mice increased tumor metastasis to the lung. Conclusion: These results demonstrate that tumor-derived EVs are key mediators of macrophage education and likely play a more complex role in modulating tumor therapeutic response by regulating the tumor immune infiltrate.

The Protein Landscape of Chronic Lymphocytic Leukemia (CLL)

Many functional consequences of mutations on tumor phenotypes in chronic lymphocytic leukemia (CLL) are unknown. This may be in part due to a scarcity of information on the proteome of CLL. We profiled the proteome of 117 CLL patient samples with data-independent acquisition mass spectrometry (DIA-MS) and integrated the results with genomic, transcriptomic, ex vivo drug response and clinical outcome data. We found trisomy 12, IGHV mutational status, mutated SF3B1, trisomy 19, del(17)(p13), del(11)(q22.3), mutated DDX3X, and MED12 to influence protein expression (FDR < 5%). Trisomy 12 and IGHV status were the major determinants of protein expression variation in CLL as shown by principal component analysis (1055 and 542 differentially expressed proteins, FDR=5%). Gene set enrichment analyses of CLL with trisomy 12 implicated BCR/PI3K/AKT signaling as a tumor driver. These findings were supported by analyses of protein abundance buffering and protein complex formation, which identified limited protein abundance buffering and an upregulated protein complex involved in BCR, AKT, MAPK and PI3K signaling in trisomy 12 CLL. A survey of proteins associated with trisomy 12/IGHV-independent drug response linked STAT2 protein expression with response to kinase inhibitors including BTK and MEK inhibitors. STAT2 was upregulated in U-CLL, trisomy 12 CLL and required for chemokine/cytokine signaling (interferon response). This study highlights the importance of protein abundance data as a non-redundant layer of information in tumor biology, and provides a protein expression reference map for CLL.

The role of CD71+ erythroid cells in the regulation of the immune response

Complex regulation of the immune response is necessary to support effective defense of an organism against hostile invaders and to maintain tolerance to harmless microorganisms and autoantigens. Recent studies revealed previously unappreciated roles of CD71⁺ erythroid cells (CECs) in regulation of the immune response. CECs physiologically reside in the bone marrow where erythropoiesis takes place. Under stress conditions, CECs are enriched in some organs outside of the bone marrow as a result of extramedullary erythropoiesis. However, the role of CECs goes well beyond the production of erythrocytes. In neonates, increased numbers of CECs contribute to their vulnerability to infectious diseases. On the other side, neonatal CECs suppress activation of immune cells in response to abrupt colonization with commensal microorganisms after delivery. CECs are also enriched in the peripheral blood of pregnant women as well as in the placenta and are responsible for the regulation of feto-maternal tolerance. In patients with cancer, anemia leads to increased frequency of CECs in the peripheral blood contributing to diminished antiviral and antibacterial immunity, as well as to accelerated cancer progression. Moreover, recent studies revealed the role of CECs in HIV and SARS-CoV-2 infections. CECs use a full arsenal of mechanisms to regulate immune response. These cells suppress proinflammatory responses of myeloid cells and T-cell proliferation by the depletion of ʟ-arginine by arginase. Moreover, CECs produce reactive oxygen species to decrease T-cell proliferation. CECs also secrete cytokines, including transforming growth factor β (TGF-β), which promotes T-cell differentiation into regulatory T-cells. Here, we comprehensively describe the role of CECs in orchestrating immune response and indicate some therapeutic approaches that might be used to regulate their effector functions in the treatment of human conditions.

A Universal and High-Throughput Proteomics Sample Preparation Platform

Major advances have been made to improve the sensitivity of mass analyzers, spectral quality, and speed of data processing enabling more comprehensive proteome discovery and quantitation. While focus has recently begun shifting toward robust proteomics sample preparation efforts, a high-throughput proteomics sample preparation is still lacking. We report the development of a highly automated universal 384-well plate sample preparation platform with high reproducibility and adaptability for extraction of proteins from cells within a culture plate. Digestion efficiency was excellent in comparison to a commercial digest peptide standard with minimal sample loss while improving sample preparation throughput by 20- to 40-fold (the entire process from plated cells to clean peptides is complete in ∼300 min). Analysis of six human cell types, including two primary cell samples, identified and quantified ∼4,000 proteins for each sample in a single high-performance liquid chromatography (HPLC)-tandem mass spectrometry injection with only 100-10K cells, thus demonstrating universality of the platform. The selected protein was further quantified using a developed HPLC-multiple reaction monitoring method for HeLa digests with two heavy labeled internal standard peptides spiked in. Excellent linearity was achieved across different cell numbers indicating a potential for target protein quantitation in clinical research.

PIGNON: a protein-protein interaction-guided functional enrichment analysis for quantitative proteomics

Background

Quantitative proteomics studies are often used to detect proteins that are differentially expressed across different experimental conditions. Functional enrichment analyses are then typically used to detect annotations, such as biological processes that are significantly enriched among such differentially expressed proteins to provide insights into the molecular impacts of the studied conditions. While common, this analytical pipeline often heavily relies on arbitrary thresholds of significance. However, a functional annotation may be dysregulated in a given experimental condition, while none, or very few of its proteins may be individually considered to be significantly differentially expressed. Such an annotation would therefore be missed by standard approaches.

Results

Herein, we propose a novel graph theory-based method, PIGNON, for the detection of differentially expressed functional annotations in different conditions. PIGNON does not assess the statistical significance of the differential expression of individual proteins, but rather maps protein differential expression levels onto a protein–protein interaction network and measures the clustering of proteins from a given functional annotation within the network. This process allows the detection of functional annotations for which the proteins are differentially expressed and grouped in the network. A Monte-Carlo sampling approach is used to assess the clustering significance of proteins in an expression-weighted network. When applied to a quantitative proteomics analysis of different molecular subtypes of breast cancer, PIGNON detects Gene Ontology terms that are both significantly clustered in a protein–protein interaction network and differentially expressed across different breast cancer subtypes. PIGNON identified functional annotations that are dysregulated and clustered within the network between the HER2+, triple negative and hormone receptor positive subtypes. We show that PIGNON’s results are complementary to those of state-of-the-art functional enrichment analyses and that it highlights functional annotations missed by standard approaches. Furthermore, PIGNON detects functional annotations that have been previously associated with specific breast cancer subtypes.

Conclusion

PIGNON provides an alternative to functional enrichment analyses and a more comprehensive characterization of quantitative datasets. Hence, it contributes to yielding a better understanding of dysregulated functions and processes in biological samples under different experimental conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04042-6.

Differential expression of hydroxyurea transporters in normal and polycythemia vera hematopoietic stem and progenitor cell subpopulations

Polycythemia vera (PV) is a myeloproliferative neoplasm marked by hyperproliferation of the myeloid lineages and the presence of an activating JAK2 mutation. Hydroxyurea (HU) is a standard treatment for high-risk patients with PV. Because disease-driving mechanisms are thought to arise in PV stem cells, effective treatments should target primarily the stem cell compartment. We tested for the antiproliferative effect of patient treatment with HU in fluorescence-activated cell sorting-isolated hematopoietic stem/multipotent progenitor cells (HSC/MPPs) and more committed erythroid progenitors (common myeloid/megakaryocyte-erythrocyte progenitors [CMP/MEPs]) in PV using RNA-sequencing and gene set enrichment analysis. HU treatment led to significant downregulation of gene sets associated with cell proliferation in PV HSCs/MPPs, but not in PV CMP/MEPs. To explore the mechanism underlying this finding, we assessed for expression of solute carrier membrane transporters, which mediate transmembrane movement of drugs such as HU into target cells. The active HU uptake transporter OCTN1 was upregulated in HSC/MPPs compared with CMP/MEPs of untreated patients with PV, and the HU diffusion facilitator urea transporter B (UTB) was downregulated in HSC/MPPs compared with CMP/MEPs in all patient and control groups tested. These findings indicate a higher accumulation of HU within PV HSC/MPPs compared with PV CMP/MEPs and provide an explanation for the differential effects of HU in HSC/MPPs and CMP/MEPs of patients with PV. In general, the findings highlight the importance of transporter expression in linking therapeutics with human disease.

Proteomic/transcriptomic analysis of erythropoiesis

PURPOSE OF REVIEW

Erythropoiesis is a hierarchical process by which hematopoietic stem cells give rise to red blood cells through gradual cell fate restriction and maturation. Deciphering this process requires the establishment of dynamic gene regulatory networks (GRNs) that predict the response of hematopoietic cells to signals from the environment. Although GRNs have historically been derived from transcriptomic data, recent proteomic studies have revealed a major role for posttranscriptional mechanisms in regulating gene expression during erythropoiesis. These new findings highlight the need to integrate proteomic data into GRNs for a refined understanding of erythropoiesis.

RECENT FINDINGS

Here, we review recent proteomic studies that have furthered our understanding of erythropoiesis with a focus on quantitative mass spectrometry approaches to measure the abundance of transcription factors and cofactors during differentiation. Furthermore, we highlight challenges that remain in integrating transcriptomic, proteomic, and other omics data into a predictive model of erythropoiesis, and discuss the future prospect of single-cell proteomics.

SUMMARY

Recent proteomic studies have considerably expanded our knowledge of erythropoiesis beyond the traditional transcriptomic-centric perspective. These findings have both opened up new avenues of research to increase our understanding of erythroid differentiation, while at the same time presenting new challenges in integrating multiple layers of information into a comprehensive gene regulatory model.

Ultra-High-Resolution IonStar Strategy Enhancing Accuracy and Precision of MS1-Based Proteomics and an Extensive Comparison with State-of-the-Art SWATH-MS in Large-Cohort Quantification

Quantitative proteomics in large cohorts is highly valuable for clinical/pharmaceutical investigations but often suffers from severely compromised reliability, accuracy, and reproducibility. Here, we describe an ultra-high-resolution IonStar method achieving reproducible protein measurement in large cohorts while minimizing the ratio compression problem, by taking advantage of the exceptional selectivity of ultra-high-resolution (UHR)-MS1 detection (240k_FWHM@m/z = 200). Using mixed-proteome benchmark sets reflecting large-cohort analysis with technical or biological replicates (N = 56), we comprehensively compared the quantitative performances of UHR-IonStar vs a state-of-the-art SWATH-MS method, each with their own optimal analytical platforms. We confirmed a cutting-edge micro-liquid chromatography (LC)/Triple-TOF with Spectronaut outperforms nano-LC/Orbitrap for SWATH-MS, which was then meticulously developed/optimized to maximize sensitivity, reproducibility, and proteome coverage. While the two methods with distinct principles (i.e., MS1- vs MS2-based) showed similar depth-of-analysis (∼6700-7000 missing-data-free proteins quantified, 1% protein-false discovery rate (FDR) for entire set, 2 unique peptides/protein) and good accuracy/precision in quantifying high-abundance proteins, UHR-IonStar achieved substantially superior quantitative accuracy, precision, and reproducibility for lower-abundance proteins (a category that includes most regulatory proteins), as well as much-improved sensitivity/selectivity for discovering significantly altered proteins. Furthermore, compared to SWATH-MS, UHR-IonStar showed markedly higher accuracy for a single analysis of each sample across a large set, which is an inadequately investigated albeit critical parameter for large-cohort analysis. Finally, we compared UHR-IonStar vs SWATH-MS in measuring the time courses of altered proteins in paclitaxel-treated cells (N = 36), where dysregulated biological pathways have been very well established. UHR-IonStar discovered substantially more well-recognized biological processes/pathways induced by paclitaxel. Additionally, UHR-IonStar showed markedly superior ability than SWATH-MS in accurately depicting the time courses of well known to be paclitaxel-induced biomarkers. In summary, UHR-IonStar represents a reliable, robust, and cost-effective solution for large-cohort proteomic quantification with excellent accuracy and precision.

Sca1+ Progenitor Cells (Ex vivo) Exhibits Differential Proteomic Signatures From the Culture Adapted Sca1+ Cells (In vitro), Both Isolated From Murine Skeletal Muscle Tissue

Stem cell antigen-1 (Sca-1) is a glycosyl-phosphatidylinositol-anchored membrane protein that is expressed in a sub-population of muscle stem and progenitor cell types. Reportedly, Sca-1 regulates the myogenic property of myoblasts and Sca-1^-/- mice exhibited defective muscle regeneration. Although the role of Sca-1 in muscle development and maintenance is well-acknowledged, molecular composition of muscle derived Sca-1⁺ cells is not characterized. Here, we applied a high-resolution mass spectrometry-based workflow to characterize the proteomic landscape of mouse hindlimb skeletal muscle derived Sca-1⁺ cells. Furthermore, we characterized the impact of the cellular microenvironments on the proteomes of Sca-1⁺ cells. The proteome component of freshly isolated Sca-1⁺ cells (ex vivo) was compared with that of Sca-1⁺ cells expanded in cell culture (in vitro). The analysis revealed significant differences in the protein abundances in the two conditions reflective of their functional variations. The identified proteins were enriched in various biological pathways. Notably, we identified proteins related to myotube differentiation, myotube cell development and myoblast fusion. We also identified a panel of cell surface marker proteins that can be leveraged in future to enrich Sca-1⁺ cells using combinatorial strategies. Comparative analysis implicated the activation of various pathways leading to increased protein synthesis under in vitro condition. We report here the most comprehensive proteome map of Sca-1⁺ cells that provides insights into the molecular networks operative in Sca-1⁺ cells. Importantly, through our work we generated the proteomic blueprint of protein abundances significantly altered in Sca-1⁺ cells under ex vivo and in vitro conditions. The curated data can also be visualized at https://yenepoya.res.in/database/Sca-1-Proteomics .

Tumor Immune Evasion Induced by Dysregulation of Erythroid Progenitor Cells Development

Cancer cells harness normal cells to facilitate tumor growth and metastasis. Within this complex network of interactions, the establishment and maintenance of immune evasion mechanisms are crucial for cancer progression. The escape from the immune surveillance results from multiple independent mechanisms. Recent studies revealed that besides well-described myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs) or regulatory T-cells (Tregs), erythroid progenitor cells (EPCs) play an important role in the regulation of immune response and tumor progression. EPCs are immature erythroid cells that differentiate into oxygen-transporting red blood cells. They expand in the extramedullary sites, including the spleen, as well as infiltrate tumors. EPCs in cancer produce reactive oxygen species (ROS), transforming growth factor β (TGF-β), interleukin-10 (IL-10) and express programmed death-ligand 1 (PD-L1) and potently suppress T-cells. Thus, EPCs regulate antitumor, antiviral, and antimicrobial immunity, leading to immune suppression. Moreover, EPCs promote tumor growth by the secretion of growth factors, including artemin. The expansion of EPCs in cancer is an effect of the dysregulation of erythropoiesis, leading to the differentiation arrest and enrichment of early-stage EPCs. Therefore, anemia treatment, targeting ineffective erythropoiesis, and the promotion of EPC differentiation are promising strategies to reduce cancer-induced immunosuppression and the tumor-promoting effects of EPCs.

Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post‐translational turnover, we devised a strategy combining pulse stable isotope‐labeled amino acids in cells (pSILAC), data‐independent acquisition mass spectrometry (DIA‐MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome‐wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.

Use of data-independent acquisition mass spectrometry for comparative proteomics analyses of sera from pregnant women with intrahepatic cholestasis of pregnancy

We used data-independent acquisition (DIA) proteomics technology followed by ELISAs and automated biochemical analyses to identify and validate protein expression levels in Intrahepatic Cholestasis of Pregnancy (ICP) and healthy pregnant controls. We employed bioinformatics to identify metabolic processes associated with differentially expressed proteins.The expression levels of two proteins (S100-A9 and the L-lactate dehydrogenase A chain) were significantly higher in ICP patients than in controls; the areas under the receiver operating characteristic (ROC) curves (AUCs) were 0.774 and 0.828, respectively. The expression levels of two other proteins (apolipoprotein A-I and cholinesterase) were significantly lower in patients, with values of 0.900 and 0.842, respectively. Multiple logistic regression showed that a combination of the levels of the four proteins optimized the AUC (0.962), thus more reliably diagnosing ICP. The levels of all four proteins were positively associated with that of total bile acids. Bioinformatics analyses indicated that the four proteins principally affected neutrophil activation involved in the immune response, cell adhesion, lipoprotein metabolism, and the PPAR signaling pathway. SIGNIFICANCE: This preliminary work improves our understanding of changes in serum levels of protein in pregnant women with ICP. The four proteins may serve as novel noninvasive biomarkers for ICP.

Integrative proteomics reveals principles of dynamic phosphosignaling networks in human erythropoiesis

Human erythropoiesis is an exquisitely controlled multistep developmental process, and its dysregulation leads to numerous human diseases. Transcriptome and epigenome studies provided insights into system-wide regulation, but we currently lack a global mechanistic view on the dynamics of proteome and post-translational regulation coordinating erythroid maturation. We established a mass spectrometry (MS)-based proteomics workflow to quantify and dynamically track 7,400 proteins and 27,000 phosphorylation sites of five distinct maturation stages of in vitro reconstituted erythropoiesis of CD34+ HSPCs. Our data reveal developmental regulation through drastic proteome remodeling across stages of erythroid maturation encompassing most protein classes. This includes various orchestrated changes in solute carriers indicating adjustments to altered metabolic requirements. To define the distinct proteome of each maturation stage, we developed a computational deconvolution approach which revealed stage-specific marker proteins. The dynamic phosphoproteomes combined with a kinome-targeted CRISPR/Cas9 screen uncovered coordinated networks of erythropoietic kinases and pinpointed downregulation of c-Kit/MAPK signaling axis as key driver of maturation. Our system-wide view establishes the functional dynamic of complex phosphosignaling networks and regulation through proteome remodeling in erythropoiesis.

Proteomic analysis of young and old mouse hematopoietic stem cells and their progenitors reveals post-transcriptional regulation in stem cells

The balance of hematopoietic stem cell (HSC) self-renewal and differentiation is critical for a healthy blood supply; imbalances underlie hematological diseases. The importance of HSCs and their progenitors have led to their extensive characterization at genomic and transcriptomic levels. However, the proteomics of hematopoiesis remains incompletely understood. Here we report a proteomics resource from mass spectrometry of mouse young adult and old adult mouse HSCs, multipotent progenitors and oligopotent progenitors; 12 cell types in total. We validated differential protein levels, including confirmation that Dnmt3a protein levels are undetected in young adult mouse HSCs until forced into cycle. Additionally, through integrating proteomics and RNA-sequencing datasets, we identified a subset of genes with apparent post-transcriptional repression in young adult mouse HSCs. In summary, we report proteomic coverage of young and old mouse HSCs and progenitors, with broader implications for understanding mechanisms for stem cell maintenance, niche interactions and fate determination.

Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications

Research into the basic biology of human health and disease, as well as translational human research and clinical applications, all benefit from the growing accessibility and versatility of mass spectrometry (MS)-based proteomics. Although once limited in throughput and sensitivity, proteomic studies have quickly grown in scope and scale over the last decade due to significant advances in instrumentation, computational approaches, and bio-sample preparation. Here, we review these latest developments in MS and highlight how these techniques are used to study the mechanisms, diagnosis, and treatment of human diseases. We first describe recent groundbreaking technological advancements for MS-based proteomics, including novel data acquisition techniques and protein quantification approaches. Next, we describe innovations that enable the unprecedented depth of coverage in protein signaling and spatiotemporal protein distributions, including studies of post-translational modifications, protein turnover, and single-cell proteomics. Finally, we explore new workflows to investigate protein complexes and structures, and we present new approaches for protein-protein interaction studies and intact protein or top-down MS. While these approaches are only recently incipient, we anticipate that their use in biomedical MS proteomics research will offer actionable discoveries for the improvement of human health.

Comparison of different variant sequence types coupled with decoy generation methods used in concatenated target-decoy database searches for proteogenomic research

Concatenated target-decoy database searches are commonly used in proteogenomic research for variant peptide identification. Currently, protein-based and peptide-based sequence databases are applied to store variant sequences for database searches. The protein-based database records a full-length wild-type protein sequence but using the given variant events to replace the original amino acids, whereas the peptide-based database retains only the in silico digested peptides containing the variants. However, the performance of applying various decoy generation methods on the peptide-based variant sequence database is still unclear, compared to the protein-based database. In this paper, we conduct a thorough comparison on target-decoy databases constructed by the above two types of databases coupled with various decoy generation methods for proteogenomic analyses. The results show that for the protein-based variant sequence database, using the reverse or the pseudo reverse method achieves similar performance for variant peptide identification. Furthermore, for the peptide-based database, the pseudo reverse method is more suitable than the widely used reverse method, as shown by identifying 6% more variant PSMs in a HEK293 cell line data set. SIGNIFICANCE: In our survey of publications on proteogenomic studies, 57% of the studies adopt the peptide-based variant sequence database coupled with the reverse method for decoy generation to construct a target-decoy database for searches. However, our results show that when using the peptide-based variant sequence database, it is better to adopt the pseudo reverse method for generating decoy sequences, to avoid leading to fewer variant peptides being identified.

The Implementation of Mass Spectrometry-Based Proteomics Workflows in Clinical Routines of Acute Myeloid Leukemia: Applicability and Perspectives

With the current reproducibility of proteome preparation workflows along with the speed and sensitivity of the mass spectrometers, the transition of the mass spectrometry (MS)-based proteomics technology from biomarker discovery to clinical implementation is under appraisal in the biomedicine community. Therefore, this technology might be implemented soon to detect well-known biomarkers in cancers and other diseases. Acute myeloid leukemia (AML) is an aggressive heterogeneous malignancy that requires intensive treatment to cure the patient. Leukemia relapse is still a major challenge even for patients who have favorable genetic abnormalities. MS-based proteomics could be of great help to both describe the proteome changes of individual patients and identify biomarkers that might encourage specific treatments or clinical strategies. Herein, we will review the advances and availability of the MS-based proteomics strategies that could already be used in clinical proteomics. However, the heterogeneity of complex diseases as AML requires consensus to recognize AML biomarkers and to establish MS-based workflows that allow their unbiased identification and quantification. Although our literature review appears promising towards the utilization of MS-based proteomics in clinical AML in a near future, major efforts are required to validate AML biomarkers and agree on clinically approved workflows.

Addressing Cellular Heterogeneity in Cancer through Precision Proteomics

Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.

Absolute Quantification of Transcription Factors Reveals Principles of Gene Regulation in Erythropoiesis

Dynamic cellular processes such as differentiation are driven by changes in the abundances of transcription factors (TFs). However, despite years of studies, our knowledge about the protein copy number of TFs in the nucleus is limited. Here, by determining the absolute abundances of 103 TFs and co-factors during the course of human erythropoiesis, we provide a dynamic and quantitative scale for TFs in the nucleus. Furthermore, we establish the first gene regulatory network of cell fate commitment that integrates temporal protein stoichiometry data with mRNA measurements. The model revealed quantitative imbalances in TFs' cross-antagonistic relationships that underlie lineage determination. Finally, we made the surprising discovery that, in the nucleus, co-repressors are dramatically more abundant than co-activators at the protein level, but not at the RNA level, with profound implications for understanding transcriptional regulation. These analyses provide a unique quantitative framework to understand transcriptional regulation of cell differentiation in a dynamic context.