Super-SILAC allows classification of diffuse large B-cell lymphoma subtypes by their protein expression profiles

Fkbp5 gene deletion: Circadian rhythm profile and brain proteomics in aged mice

FKBP51, also known as FK506-binding protein 51, is a molecular chaperone and scaffolding protein with significant roles in regulating hormone signaling and responding to stress. Genetic variants in FKBP5, which encodes FKBP51, have been implicated in a growing number of neuropsychiatric disorders, which has spurred efforts to target FKBP51 therapeutically. However, the molecular mechanisms and sub-anatomical regions influenced by FKBP51 in these disorders are not fully understood. In this study, we aimed to examine the impact of Fkbp5 ablation using circadian phenotyping and molecular analyses. Our findings revealed that the lack of FKBP51 did not significantly alter circadian rhythms, as detected by wheel-running activity, but did offer protection against stress-mediated disruptions in rhythmicity in a sex-dependent manner. Protein changes in Fkbp5 KO mice, as measured by histology and proteomics, revealed alterations in a brain region- and sex-dependent manner. Notably, regardless of sex, aged Fkbp5 KOs showed elevated MYCBP2, FBXO45, and SPRYD3 levels, which are associated with neuronal-cell adhesion and synaptic integrity. Additionally, pathways such as serotonin receptor signaling and S100 family signaling were differentially regulated in Fkbp5 KO mice. Weighted protein correlation network analysis identified protein networks linked with synaptic transmission and neuroinflammation. The information generated by this work can be used to better understand the molecular changes in the brain during aging and in the absence of Fkbp5, which has implications for the continued development of FKBP51-focused therapeutics for stress-related disorders.

Artificial Intelligence-Driven Precision Medicine: Multi-Omics and Spatial Multi-Omics Approaches in Diffuse Large B-Cell Lymphoma (DLBCL)

In this comprehensive review, we delve into the transformative role of artificial intelligence (AI) in refining the application of multi-omics and spatial multi-omics within the realm of diffuse large B-cell lymphoma (DLBCL) research. We scrutinized the current landscape of multi-omics and spatial multi-omics technologies, accentuating their combined potential with AI to provide unparalleled insights into the molecular intricacies and spatial heterogeneity inherent to DLBCL. Despite current progress, we acknowledge the hurdles that impede the full utilization of these technologies, such as the integration and sophisticated analysis of complex datasets, the necessity for standardized protocols, the reproducibility of findings, and the interpretation of their biological significance. We proceeded to pinpoint crucial research voids and advocated for a trajectory that incorporates the development of advanced AI-driven data integration and analytical frameworks. The evolution of these technologies is crucial for enhancing resolution and depth in multi-omics studies. We also emphasized the importance of amassing extensive, meticulously annotated multi-omics datasets and fostering translational research efforts to connect laboratory discoveries with clinical applications seamlessly. Our review concluded that the synergistic integration of multi-omics, spatial multi-omics, and AI holds immense promise for propelling precision medicine forward in DLBCL. By surmounting the present challenges and steering towards the outlined futuristic pathways, we can harness these potent investigative tools to decipher the molecular and spatial conundrums of DLBCL. This will pave the way for refined diagnostic precision, nuanced risk stratification, and individualized therapeutic regimens, ushering in a new era of patient-centric oncology care.

Cellular resiliency and survival of Neuro-2a cells under extreme stress

Stressors such as hypoxia, hypothermia, and acute toxicity often result in widespread cell death. This study investigated the outcomes of Neuro-2a (N2a; mouse neuroblastoma) cells following a cryogenic storage failure that exposed them to a combination of these stressors over a period of approximately 24-30 hours. Remarkably, a small fraction of the cells survived the event, underwent a period of dormancy, and eventually recovered to a healthy state. To understand the underlying resilience mechanisms, we created a model to replicate the dewar failure event and examined changes in phenotype, transcriptomics, proteomics, and mitochondrial activity of the surviving cells during recovery. We found that the surviving cells initially displayed a stressed morphology with irregular membranes and a clustered apperance. They showed an increased expression of proteins related to DNA repair and chromatin modification pathways as well as heightened mitochondrial function shortly after the stress event. As recovery progressed, the stress-responsive pathways, mitochondrial activity, and growth rates normalized toward that of healthy controls, indicating a return to a stable baseline state. These findings suggest that an initial robust energetic state supports key stress-responsive and repair pathways at the early stages of recovery, facilitating cell survival and resiliency after extreme stress. This work provides valuable insights into cellular resilience mechanisms with potential implications for improving cell preservation and recovery in biomedical applications and developing therapeutic strategies for conditions involving cell damage and stress.

Combining Data Independent Acquisition With Spike-In SILAC (DIA-SiS) Improves Proteome Coverage and Quantification

Data-independent acquisition (DIA) is increasingly preferred over data-dependent acquisition due to its higher throughput and fewer missing values. Whereas data-dependent acquisition often uses stable isotope labeling to improve quantification, DIA mostly relies on label-free approaches. Efforts to integrate DIA with isotope labeling include chemical methods like mass differential tags for relative and absolute quantification and dimethyl labeling, which, while effective, complicate sample preparation. Stable isotope labeling by amino acids in cell culture (SILAC) achieves high labeling efficiency through the metabolic incorporation of heavy labels into proteins in vivo. However, the need for metabolic incorporation limits the direct use in clinical scenarios and certain high-throughput experiments. Spike-in SILAC (SiS) methods use an externally generated heavy sample as an internal reference, enabling SILAC-based quantification even for samples that cannot be directly labeled. Here, we combine DIA-SiS, leveraging the robust quantification of SILAC without the complexities associated with chemical labeling. We developed DIA-SiS and rigorously assessed its performance with mixed-species benchmark samples on bulk and single cell-like amount level. We demonstrate that DIA-SiS substantially improves proteome coverage and quantification compared to label-free approaches and reduces incorrectly quantified proteins. Additionally, DIA-SiS proves effective in analyzing proteins in low-input formalin-fixed paraffin-embedded tissue sections. DIA-SiS combines the precision of stable isotope-based quantification with the simplicity of label-free sample preparation, facilitating simple, accurate, and comprehensive proteome profiling.

Progression of monoclonal gammopathy of undetermined significance to multiple myeloma is associated with enhanced translational quality control and overall loss of surface antigens

BACKGROUND

Despite significant advancements in treatment strategies, multiple myeloma remains incurable. Additionally, there is a distinct lack of reliable biomarkers that can guide initial treatment decisions and help determine suitable replacement or adjuvant therapies when relapse ensues due to acquired drug resistance.

METHODS

To define specific proteins and pathways involved in the progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM), we have applied super-SILAC quantitative proteomic analysis to CD138 + plasma cells from 9 individuals with MGUS and 37 with MM.

RESULTS

Unsupervised hierarchical clustering defined three groups: MGUS, MM, and MM with an MGUS-like proteome profile (ML) that may represent a group that has recently transformed to MM. Statistical analysis identified 866 differentially expressed proteins between MM and MGUS, and 189 between MM and ML, 177 of which were common between MGUS and ML. Progression from MGUS to MM is accompanied by upregulated EIF2 signaling, DNA repair, and proteins involved in translational quality control, whereas integrin- and actin cytoskeletal signaling and cell surface markers are downregulated.

CONCLUSION

Compared to the premalignant plasma cells in MGUS, malignant MM cells apparently have mobilized several pathways that collectively contribute to ensure translational fidelity and to avoid proteotoxic stress, especially in the ER. The overall reduced expression of immunoglobulins and surface antigens contribute to this and may additionally mediate evasion from recognition by the immune apparatus. Our analyses identified a range of novel biomarkers with potential prognostic and therapeutic value, which will undergo further evaluation to determine their clinical significance.

DeKinomics pulse-chases kinase functions in living cells

Cellular context is crucial for understanding the complex and dynamic kinase functions in health and disease. Systematic dissection of kinase-mediated cellular processes requires rapid and precise stimulation ('pulse') of a kinase of interest, as well as global and in-depth characterization ('chase') of the perturbed proteome under living conditions. Here we developed an optogenetic 'pulse-chase' strategy, termed decaging kinase coupled proteomics (DeKinomics), for proteome-wide profiling of kinase-driven phosphorylation at second-timescale in living cells. We took advantage of the 'gain-of-function' feature of DeKinomics to identify direct kinase substrates and further portrayed the global phosphorylation of understudied receptor tyrosine kinases under native cellular settings. DeKinomics offered a general activation-based strategy to study kinase functions with high specificity and temporal resolution under living conditions.

Gene expression and copy number profiling of follicular lymphoma biopsies from patients treated with first-line rituximab without chemotherapy

The Nordic Lymphoma Study Group has performed two randomized clinical trials with chemotherapy-free first-line treatment (rituximab +/- interferon) in follicular lymphoma (FL), with 73% of patients alive and 38% without any need of chemotherapy after 10.6 years median follow-up. In order to identify predictive markers, that may also serve as therapeutic targets, gene expression- and copy number profiles were obtained from 97 FL patients using whole genome microarrays. Copy number alterations (CNAs) were identified, e.g. by GISTIC. Cox Lasso Regression and Lasso logistic regression were used to determine molecular features predictive of time to next therapy (TTNT). A few molecular changes were associated with TTNT (e.g. increased expression of INPP5B, gains in 12q23/q24), but were not significant after adjusting for multiple testing. Our findings suggest that there are no strong determinants of patient outcome with respect to GE data and CNAs in FL patients treated with a chemotherapy-free regimen (i.e. rituximab +/- interferon).

Deregulated expression of the 14q32 miRNA cluster in clear cell renal cancer cells

Clear cell renal cell carcinomas (ccRCC) are characterized by arm-wide chromosomal alterations. Loss at 14q is associated with disease aggressiveness in ccRCC, which responds poorly to chemotherapeutics. The 14q locus contains one of the largest miRNA clusters in the human genome; however, little is known about the contribution of these miRNAs to ccRCC pathogenesis. In this regard, we investigated the expression pattern of selected miRNAs at the 14q32 locus in TCGA kidney tumors and in ccRCC cell lines. We demonstrated that the miRNA cluster is downregulated in ccRCC (and cell lines) as well as in papillary kidney tumors relative to normal kidney tissues (and primary renal proximal tubule epithelial (RPTEC) cells). We demonstrated that agents modulating expression of DNMT1 (e.g., 5-Aza-deoxycytidine) could modulate 14q32 miRNA expression in ccRCC cell lines. Lysophosphatidic acid (LPA, a lysophospholipid mediator elevated in ccRCC) not only increased labile iron content but also modulated expression of a 14q32 miRNA. Through an overexpression approach targeting a subset of 14q32 miRNAs (specifically at subcluster A: miR-431-5p, miR-432-5p, miR-127-3p, and miR-433-3p) in 769-P cells, we uncovered changes in cellular viability and claudin-1, a tight junction marker. A global proteomic approach was implemented using these miRNA overexpressing cell lines which uncovered ATXN2 as a highly downregulated target. Collectively, these findings support a contribution of miRNAs at 14q32 in ccRCC pathogenesis.

Meta-Analysis of MS-Based Proteomics Studies Indicates Interferon Regulatory Factor 4 and Nucleobindin1 as Potential Prognostic and Drug Resistance Biomarkers in Diffuse Large B Cell Lymphoma

The prognosis of diffuse large B cell lymphoma (DLBCL) is inaccurately predicted using clinical features and immunohistochemistry (IHC) algorithms. Nomination of a panel of molecules as the target for therapy and predicting prognosis in DLBCL is challenging because of the divergences in the results of molecular studies. Mass spectrometry (MS)-based proteomics in the clinic represents an analytical tool with the potential to improve DLBCL diagnosis and prognosis. Previous proteomics studies using MS-based proteomics identified a wide range of proteins. To achieve a consensus, we reviewed MS-based proteomics studies and extracted the most consistently significantly dysregulated proteins. These proteins were then further explored by analyzing data from other omics fields. Among all significantly regulated proteins, interferon regulatory factor 4 (IRF4) was identified as a potential target by proteomics, genomics, and IHC. Moreover, annexinA5 (ANXA5) and nucleobindin1 (NUCB1) were two of the most up-regulated proteins identified in MS studies. Functional enrichment analysis identified the light zone reactions of the germinal center (LZ-GC) together with cytoskeleton locomotion functions as enriched based on consistent, significantly dysregulated proteins. In this study, we suggest IRF4 and NUCB1 proteins as potential biomarkers that deserve further investigation in the field of DLBCL sub-classification and prognosis.

Radiation-Induced Intestinal Normal Tissue Toxicity: Implications for Altered Proteome Profile

Radiation-induced toxicity to healthy/normal intestinal tissues, especially during radiotherapy, limits the radiation dose necessary to effectively eradicate tumors of the abdomen and pelvis. Although the pathogenesis of intestinal radiation toxicity is highly complex, understanding post-irradiation alterations in protein profiles can provide crucial insights that make radiotherapy safer and more efficient and allow for increasing the radiation dose during cancer treatment. Recent preclinical and clinical studies have advanced our current understanding of the molecular changes associated with radiation-induced intestinal damage by assessing changes in protein expression with mass spectrometry-based approaches and 2-dimensional difference gel electrophoresis. Studies by various groups have demonstrated that proteins that are involved in the inflammatory response, the apoptotic pathway, reactive oxygen species scavenging, and cell proliferation can be targeted to develop effective radiation countermeasures. Moreover, altered protein profiles serve as a crucial biomarkers for intestinal radiation damage. In this review, we present alterations in protein signatures following intestinal radiation damage as detected by proteomics approaches in preclinical and clinical models with the aim of providing a better understanding of how to accomplish intestinal protection against radiation damage.

Proteomic examination of Cornus officinalis stimulated 1.1B4 human pancreatic cells reveals activation of autophagy and Keap1/Nrf2 pathway

Type 1 diabetes (T1D) is an autoimmune disease initiated by genetic predisposition and environmental influences culminating in the immunologically mediated destruction of pancreatic β-cells with eventual loss of insulin production. Although T1D can be accurately predicted via autoantibodies, therapies are lacking that can intercede autoimmunity and protect pancreatic β-cells. There are no approved interventional modalities established for this purpose. One such potential source for clinical agents of this use is from the frequently utilized Cornus officinalis (CO) in the field of ethnopharmacology. Studies by our lab and others have demonstrated that CO has robust proliferative, metabolic, and cytokine protective effects on pancreatic β-cells. To identify the molecular mechanism of the biological effects of CO, we performed a proteomic and phosphoproteomic analysis examining the cellular networks impacted by CO application on the 1.1B4 pancreatic β-cell line. Our label-free mass spectrometry approach has demonstrated significant increased phosphorylation of the selective autophagy receptor of p62 (Sequestosome-1/SQSTM1/p62) and predicted activation of the antioxidant Kelch-like ECH-associated protein 1 (Keap1)/Nuclear factor-erythroid factor 2-related factor 2 (Nrf2) pathway. Further validation by immunoblotting and immunofluorescence revealed markers of autophagy such as increased LC3-II and decreased total p62 along with nuclear localization of Nrf2. Both autophagy and the Keap1/Nrf2 pathways have been shown to be impaired in human and animal models of T1D and may serve as an excellent potential therapeutic target stimulated by CO.

Changes of Protein Expression after CRISPR/Cas9 Knockout of miRNA-142 in Cell Lines Derived from Diffuse Large B-Cell Lymphoma

Simple Summary

The gene of the human tumor suppressive microRNA-142 (miR-142) carries mutations in about 20% of cases of diffuse large B-cell lymphoma (DLBCL). Because microRNAs post-transcriptionally regulate the protein expression of their cognate messenger RNA (mRNAs) targets, we determined the effect of miR-142 knockout on protein expression in two cell lines derived from DLBCL. We found a significant up-regulation of 52 proteins but also a down-regulation of 41 proteins upon miR-142 deletion. Knockout of a miRNA may be used to identify novel targets, and seed-sequence mutants of a miRNA unable to bind to their targets can be used to confirm potential novel targets. With this approach, we identify AKT1S1, CCNB1, LIMA1 and TFRC as novel targets of miR-142. As miR-142 is highly present in the miRNA processing RISC complexes, the deletion of this miRNA might result in its replacement by other miRNAs, thus introducing an additional layer of complexity regarding gene regulation.

Abstract

Background: As microRNA-142 (miR-142) is the only human microRNA gene where mutations have consistently been found in about 20% of all cases of diffuse large B-cell lymphoma (DLBCL), we wanted to determine the impact of miR-142 inactivation on protein expression of DLBCL cell lines. Methods: miR-142 was deleted by CRISPR/Cas9 knockout in cell lines from DLBCL. Results: By proteome analyses, miR-142 knockout resulted in a consistent up-regulation of 52 but also down-regulation of 41 proteins in GC-DLBCL lines BJAB and SUDHL4. Various mitochondrial ribosomal proteins were up-regulated in line with their pro-tumorigenic properties, while proteins necessary for MHC-I presentation were down-regulated in accordance with the finding that miR-142 knockout mice have a defective immune response. CFL2, CLIC4, STAU1, and TWF1 are known targets of miR-142, and we could additionally confirm AKT1S1, CCNB1, LIMA1, and TFRC as new targets of miR-142-3p or -5p. Conclusions: Seed-sequence mutants of miR-142 confirmed potential targets and novel targets of miRNAs can be identified in miRNA knockout cell lines. Due to the complex contribution of miRNAs within cellular regulatory networks, in particular when miRNAs highly present in RISC complexes are replaced by other miRNAs, primary effects on gene expression may be covered by secondary layers of regulation.

Erythropoietin-driven dynamic proteome adaptations during erythropoiesis prevent iron overload in the developing embryo

Erythropoietin (Epo) ensures survival and proliferation of colony-forming unit erythroid (CFU-E) progenitor cells and their differentiation to hemoglobin-containing mature erythrocytes. A lack of Epo-induced responses causes embryonic lethality, but mechanisms regulating the dynamic communication of cellular alterations to the organismal level remain unresolved. By time-resolved transcriptomics and proteomics, we show that Epo induces in CFU-E cells a gradual transition from proliferation signature proteins to proteins indicative for differentiation, including heme-synthesis enzymes. In the absence of the Epo receptor (EpoR) in embryos, we observe a lack of hemoglobin in CFU-E cells and massive iron overload of the fetal liver pointing to a miscommunication between liver and placenta. A reduction of iron-sulfur cluster-containing proteins involved in oxidative phosphorylation in these embryos leads to a metabolic shift toward glycolysis. This link connecting erythropoiesis with the regulation of iron homeostasis and metabolic reprogramming suggests that balancing these interactions is crucial for protection from iron intoxication and for survival.

The Patent Ductus Arteriosus in Extremely Preterm Neonates Is More than a Hemodynamic Challenge: New Molecular Insights

Complications to preterm birth are numerous, including the presence of a patent ductus arteriosus (PDA). The biological understanding of the PDA is sparse and treatment remains controversial. Herein, we speculate whether the PDA is more than a cardiovascular imbalance, and may be a marker in response to immature core molecular and physiological processes driven by biological systems, such as inflammation. To achieve a new biological understanding of the PDA, we performed echocardiography and collected plasma samples on day 3 of life in 53 consecutively born neonates with a gestational age at birth below 28 completed weeks. The proteome of these samples was analyzed by mass spectrometry (nanoLC-MS/MS) and immunoassay of 17 cytokines and chemokines. We found differences in 21 proteins and 8 cytokines between neonates with a large PDA (>1.5 mm) compared to neonates without a PDA. Amongst others, we found increased levels of angiotensinogen, periostin, pro-inflammatory associations, including interleukin (IL)-1β and IL-8, and anti-inflammatory associations, including IL-1RA and IL-10. Levels of complement factors C8 and carboxypeptidases were decreased. Our findings associate the PDA with the renin-angiotensin-aldosterone system and immune- and complement systems, indicating that PDA goes beyond the persistence of a fetal circulatory connection of the great vessels.

Urine Proteomics Reveals Sex-Specific Response to Total Pancreatectomy With Islet Autotransplantation

OBJECTIVES

Total pancreatectomy with islet autotransplantation (TPIAT) is a surgical option for refractory chronic pancreatitis-related pain. Despite the known clinical implications of TPIAT, the molecular effects remain poorly investigated. We performed the first hypothesis-generating study of the urinary proteome before and after TPIAT.

METHODS

Twenty-two patients eligible for TPIAT were prospectively enrolled. Urine samples were collected the week before and 12 to 18 months after TPIAT. The urine samples were prepared for bottom-up label-free quantitative proteomics using the "MStern" protocol.

RESULTS

Using 17 paired samples, we identified 2477 urinary proteins, of which 301 were significantly changed post-TPIAT versus pre-TPIAT. Our quantitative analysis revealed that the molecular response to TPIAT was highly sex-specific, with pronounced sex differences pre-TPIAT but minimal differences afterward. Comparing post-TPIAT versus pre-TPIAT, we found changes in cell-cell adhesion, intracellular vacuoles, and immune response proteins. After surgery, immunoglobulins, complement proteins, and cathepsins were increased, findings that may reflect glomerular damage. Finally, we identified both known and novel markers for immunoglobulin A nephropathy after 1 patient developed the disease 2 years after TPIAT.

CONCLUSIONS

We found distinct changes in the urinary proteomic profile after TPIAT and the response to TPIAT is highly sex-specific.

Hemojuvelin deficiency promotes liver mitochondrial dysfunction and predisposes mice to hepatocellular carcinoma

Hemojuvelin (HJV) enhances signaling to the iron hormone hepcidin and its deficiency causes iron overload, a risk factor for hepatocellular carcinoma (HCC). We utilized Hjv^−/− mice to dissect mechanisms for hepatocarcinogenesis. We show that suboptimal treatment with diethylnitrosamine (DEN) triggers HCC only in Hjv^−/− but not wt mice. Liver proteomics data were obtained by mass spectrometry. Hierarchical clustering analysis revealed that Hjv deficiency and DEN elicit similar liver proteomic responses, including induction of mitochondrial proteins. Dietary iron overload of wt mice does not recapitulate the liver proteomic phenotype of Hjv^−/− animals, which is only partially corrected by iron depletion. Consistent with these data, primary Hjv^−/− hepatocytes exhibit mitochondrial hyperactivity, while aged Hjv^−/− mice develop spontaneous HCC. Moreover, low expression of HJV or hepcidin (HAMP) mRNAs predicts poor prognosis in HCC patients. We conclude that Hjv has a hepatoprotective function and its deficiency in mice promotes mitochondrial dysfunction and hepatocarcinogenesis.

Hemojuvelin (HJV), a BMP co-receptor promoting hepcidin expression in the liver, has a hepatoprotective function and its deficiency in mice triggers mitochondrial dysfunction and hepatocarcinogenesis.

Proteomic Landscape of Extracellular Vesicles for Diffuse Large B-Cell Lymphoma Subtyping

The role of extracellular vesicles (EVs) proteome in diffuse large B-cell lymphoma (DLBCL) pathology, subclassification, and patient screening is unexplored. We analyzed by state-of-the-art mass spectrometry the whole cell and secreted extracellular vesicles (EVs) proteomes of different molecular subtypes of DLBCL, germinal center B cell (GCB subtype), and activated B cell (ABC subtype). After quality control assessment, we compared whole-cell and secreted EVs proteomes of the two cell-of-origin (COO) categories, GCB and ABC subtypes, resulting in 288/1115 significantly differential expressed proteins from the whole-cell proteome and 228/608 proteins from EVs (adjust p-value < 0.05/p-value < 0.05). In our preclinical model system, we demonstrated that the EV proteome and the whole-cell proteome possess the capacity to separate cell lines into ABC and GCB subtypes. KEGG functional analysis and GO enrichment analysis for cellular component, molecular function, and biological process of differential expressed proteins (DEP) between ABC and GCB EVs showed a significant enrichment of pathways involved in immune response function. Other enriched functional categories for DEPs constitute cellular signaling and intracellular trafficking such as B-cell receptor (BCR), Fc_gamma R-mediated phagocytosis, ErbB signaling, and endocytosis. Our results suggest EVs can be explored as a tool for patient diagnosis, follow-up, and disease monitoring. Finally, this study proposes novel drug targets based on highly expressed proteins, for which antitumor drugs are available suggesting potential combinatorial therapies for aggressive forms of DLBCL. Data are available via ProteomeXchange with identifier PXD028267.

Proteomic-Based Analysis of Hypoxia- and Physioxia-Responsive Proteins and Pathways in Diffuse Large B-Cell Lymphoma

Hypoxia is a common feature in most tumors, including hematological malignancies. There is a lack of studies on hypoxia- and physioxia-induced global proteome changes in lymphoma. Here, we sought to explore how the proteome of diffuse large B-cell lymphoma (DLBCL) changes when cells are exposed to acute hypoxic stress (1% of O₂) and physioxia (5% of O₂) for a long-time. A total of 8239 proteins were identified by LC–MS/MS, of which 718, 513, and 486 had significant changes, in abundance, in the Ri-1, U2904, and U2932 cell lines, respectively. We observed that changes in B-NHL proteome profiles induced by hypoxia and physioxia were quantitatively similar in each cell line; however, differentially abundant proteins (DAPs) were specific to a certain cell line. A significant downregulation of several ribosome proteins indicated a translational inhibition of new ribosome protein synthesis in hypoxia, what was confirmed in a pathway enrichment analysis. In addition, downregulated proteins highlighted the altered cell cycle, metabolism, and interferon signaling. As expected, the enrichment of upregulated proteins revealed terms related to metabolism, HIF1 signaling, and response to oxidative stress. In accordance to our results, physioxia induced weaker changes in the protein abundance when compared to those induced by hypoxia. Our data provide new evidence for understanding mechanisms by which DLBCL cells respond to a variable oxygen level. Furthermore, this study reveals multiple hypoxia-responsive proteins showing an altered abundance in hypoxic and physioxic DLBCL. It remains to be investigated whether changes in the proteomes of DLBCL under normoxia and physioxia have functional consequences on lymphoma development and progression.

Large-Scale Proteomic Analysis of Follicular Lymphoma Reveals Extensive Remodeling of Cell Adhesion Pathway and Identifies Hub Proteins Related to the Lymphomagenesis

Simple Summary

Follicular lymphoma represents the major subtype of indolent B-cell non-Hodgkin lymphomas, ranging from about 20 to 30% of all B-NHLs cases in western countries. Yet, the global proteome profile of follicular lymphoma remains largely undocumented; thus, we aimed to employ for the first time a comprehensive proteomic analysis to outline its molecular landscape. A total of 15 lymphoma fine-needle aspiration biopsy samples and 14 controls were evaluated by label-free quantitative proteomics. Among the 7673 proteins identified in our dataset, 1186 proteins were differentially expressed between lymphoma and control samples. Importantly, dysregulated proteins were enriched in biological processes such as B-cell receptor signaling pathway, cellular adhesion molecules pathway, or membrane trafficking. Additionally, we identified several novel hub proteins related to lymphomagenesis. To summarize, we have determined the molecular characteristics of follicular lymphoma and discovered proteins which may hold potential for biomarkers or therapeutic targets.

Abstract

Follicular lymphoma (FL) represents the major subtype of indolent B-cell non-Hodgkin lymphomas (B-NHLs) and results from the malignant transformation of mature B-cells in lymphoid organs. Although gene expression and genomic studies have identified multiple disease driving gene aberrations, only a few proteomic studies focused on the protein level. The present work aimed to examine the proteomic profiles of follicular lymphoma vs. normal B-cells obtained by fine-needle aspiration biopsy (FNAB) to gain deep insight into the most perturbed pathway of FL. The cells of interest were purified by magnetic-activated cell sorting (MACS). High-throughput proteomic profiling was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allowed to identify of 6724 proteins in at least 75% of each group of samples. The ‘Total Protein Approach’ (TPA) was applied to the absolute quantification of proteins in this study. We identified 1186 differentially abundant proteins (DAPs) between FL and control samples, causing an extensive remodeling of several molecular pathways, including the B-cell receptor signaling pathway, cellular adhesion molecules, and PPAR pathway. Additionally, the construction of protein–protein interactions networks (PPINs) and identification of hub proteins allowed us to indicate the key player proteins for FL pathology. Finally, ICAM1, CD9, and CD79B protein expression was validated in an independent cohort by flow cytometry (FCM), and the results were consistent with the mass spectrometry (MS) data.

Kinome Profiling of Primary Endometrial Tumors Using Multiplexed Inhibitor Beads and Mass Spectrometry Identifies SRPK1 as Candidate Therapeutic Target

Endometrial carcinoma (EC) is the most common gynecologic malignancy in the United States, with limited effective targeted therapies. Endometrial tumors exhibit frequent alterations in protein kinases, yet only a small fraction of the kinome has been therapeutically explored. To identify kinase therapeutic avenues for EC, we profiled the kinome of endometrial tumors and normal endometrial tissues using Multiplexed Inhibitor Beads and Mass Spectrometry (MIB-MS). Our proteomics analysis identified a network of kinases overexpressed in tumors, including Serine/Arginine-Rich Splicing Factor Kinase 1 (SRPK1). Immunohistochemical (IHC) analysis of endometrial tumors confirmed MIB-MS findings and showed SRPK1 protein levels were highly expressed in endometrioid and uterine serous cancer (USC) histological subtypes. Moreover, querying large-scale genomics studies of EC tumors revealed high expression of SRPK1 correlated with poor survival. Loss-of-function studies targeting SRPK1 in an established USC cell line demonstrated SRPK1 was integral for RNA splicing, as well as cell cycle progression and survival under nutrient deficient conditions. Profiling of USC cells identified a compensatory response to SRPK1 inhibition that involved EGFR and the up-regulation of IGF1R and downstream AKT signaling. Co-targeting SRPK1 and EGFR or IGF1R synergistically enhanced growth inhibition in serous and endometrioid cell lines, representing a promising combination therapy for EC.

Predictive Signatures of 19 Antibiotic-Induced Escherichia coli Proteomes

Identifying the mode of action (MOA) of antibacterial compounds is the fundamental basis for the development of new antibiotics, and the challenge increases with the emerging secondary and indirect effect from antibiotic stress. Although various omics-based system biology approaches are currently available, enhanced throughput, accuracy, and comprehensiveness are still desirable to better define antibiotic MOA. Using label-free quantitative proteomics, we present here a comprehensive reference map of proteomic signatures of Escherichia coli under challenge of 19 individual antibiotics. Applying several machine learning techniques, we derived a panel of 14 proteins that can be used to classify the antibiotics into different MOAs with nearly 100% accuracy. These proteins tend to mediate diverse bacterial cellular and metabolic processes. Transcriptomic level profiling correlates well with protein expression changes in discriminating different antibiotics. The reported expression signatures will aid future studies in identifying MOA of unknown compounds and facilitate the discovery of novel antibiotics.

Protein profile of well-differentiated versus un-differentiated human bronchial/tracheal epithelial cells

Un-differentiated (UD) and well-differentiated (WD) normal human primary bronchial/tracheal epithelial cells are important respiratory cell models. Mature, WD cells which can be derived by culturing UD cells at an air-liquid interface represent a good surrogate for in vivo human airway epithelium. The overall protein profile of WD cells is poorly understood; therefore, the current study evaluated the proteomic characteristics of WD and UD cells using label-free LC-MS/MS and LC-PRM/MS. A total of 3,579 proteins were identified in WD and UD cells. Of these, 198 proteins were identified as differentially expressed, with 121 proteins upregulated and 77 proteins downregulated in WD cells compared with UD cells. Differentially expressed proteins were mostly enriched in categories related to epithelial structure formation, cell cycle, and immunity. Fifteen KEGG pathways and protein interaction networks were enriched and identified. The current study provides a global protein profile of WD cells, and contributes to understanding the function of human airway epithelium.

Bayesian networks established functional differences between breast cancer subtypes

Breast cancer is a heterogeneous disease. In clinical practice, tumors are classified as hormonal receptor positive, Her2 positive and triple negative tumors. In previous works, our group defined a new hormonal receptor positive subgroup, the TN-like subtype, which had a prognosis and a molecular profile more similar to triple negative tumors. In this study, proteomics and Bayesian networks were used to characterize protein relationships in 96 breast tumor samples. Components obtained by these methods had a clear functional structure. The analysis of these components suggested differences in processes such as mitochondrial function or extracellular matrix between breast cancer subtypes, including our new defined subtype TN-like. In addition, one of the components, mainly related with extracellular matrix processes, had prognostic value in this cohort. Functional approaches allow to build hypotheses about regulatory mechanisms and to establish new relationships among proteins in the breast cancer context.

Deep proteome profiling reveals novel pathways associated with pro-inflammatory and alcohol-induced microglial activation phenotypes

Microglia, the resident immune cells of the brain, can exhibit a broad range of activation phenotypes, many of which have been implicated in several diseases and disorders of the central nervous system including those related to alcohol abuse. Given the complexity of global-scale molecular changes that define microglial activation, accurate phenotypic classification in the context of alcohol exposure is still lacking. We employed an optimized method for deep, quantitative proteome profiling of primary microglia in order to characterize their response to acute exposure to alcohol (ethanol) as well as the pro-inflammatory driver and TLR4 agonist, LPS. From this analysis, 5,062 total proteins were identified where 4,857 and 4,928 of those proteins were quantifiable by label-free quantitation in ethanol and LPS treatment groups, respectively. This study highlights the subtle, yet significant proteomic changes that occur in ethanol-treated microglia, which do not align with the robust pro-inflammatory phenotype induced by TLR4 activation. Specifically, our results indicate inhibition of several upstream regulators associated with inflammation, opposing effects on pathways such as phagocytosis upon comparison to TLR4-mediated pro-inflammatory phenotype, and a potential metabolic shift associated with increased expression of proteins related to OXPHOS and lipid homeostasis. Data are available via ProteomeXchange with identifier PXD14466. SIGNIFICANCE: Alcohol abuse has a significant impact on the central nervous system, which includes the pathophysiological mechanisms resulting from glial cell activation. Microglia, in particular, are the resident immune cells of the brain and exhibit a broad range of activation phenotypes. The molecular changes that drive microglial activation phenotype are complex and have yet to be fully characterized in the context of alcohol exposure. Our study highlights the first and most comprehensive characterization of alcohol-induced proteomic changes in primary microglia to date and has shed light on novel immune-related and metabolic pathways that are altered due to alcohol exposure. The results from this study provide an important foundation for future work aimed to understand the complexity of alcohol-induced microglial activation in vivo and other translational models of acute and chronic alcohol exposure.

Quantitative Proteomic Analysis Reveals Antiviral and Anti-inflammatory Effects of Puerarin in Piglets Infected With Porcine Epidemic Diarrhea Virus

Porcine epidemic diarrhea virus (PEDV) has caused enormous economic losses to the swine industry worldwide in recent years. Puerarin (PR), a major isoflavonoid isolated from the Chinese herb Gegen, possesses many pharmacological activities, including anti-inflammatory, and anti-viral activities. This study was conducted with both PEDV-infected African green monkey kidney cells (Vero) and neonatal pigs to determine the effect of PR on PEDV infection and to elucidate the underlying mechanisms by using proteomic analyses. Twenty-four piglets fed a milk replacer were randomly allocated into one of three groups (Control, PEDV, and PEDV + PR). After a 5-day period of adaption, piglets (n = 8/group) in the PEDV + PR were orally administered with PR (0.5 mg/kg body weight) between days 5 and 9, whereas piglets in the other two groups received the same volume of liquid milk replacer. On day 9, piglets were orally administered with either sterile saline or PEDV (Yunnan province strain) at 10^4.5 TCID₅₀ (50% tissue culture infectious dose) per pig. On day 12 of the trial, jugular vein blood and intestinal samples were collected. In addition, Vero cells were assigned randomly into three groups (Control, PEDV, PEDV + PR). Cells in the PEDV and PEDV + PR groups were infected with PEDV at a multiplicity of infection of 0.01, while cells in the control group were treated with the same volume of sterile saline. One hour later, cells in the Control and PEDV groups were cultured in serum-free DMEM, while cells in the PEDV + PR group were supplemented with PR. After 36 h of culture, cells were harvested. PR attenuated the reductions in cell proliferation in vitro and growth performance in PEDV-infected piglets, and inhibited PEDV replication and the expression of several cytokines (including IL-8) both in vitro and in vivo. Proteomic analyses identified that the abundances of 29 proteins in the ileum were altered by PEDV infection and restored to the control level by PR. Pathway analyses revealed that PR restored the expression of several interferon-stimulated genes and selectively upregulated the expression of guanylate-binding proteins. Western blot analyses showed that PR supplementation inhibited the PEDV-induced NF-κB activation. Collectively, these results indicate that PR could exert antiviral and anti-inflammatory effects in piglets infected with PEDV and have the potential to be an effective antiviral feed additive.

Functional proteomics interrogation of the kinome identifies MRCKA as a therapeutic target in high-grade serous ovarian carcinoma

High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological cancer with few effective, targeted therapies. HGSOC tumors exhibit genomic instability with frequent alterations in the protein kinome; however, only a small fraction of the kinome has been therapeutically targeted in HGSOC. Using multiplexed inhibitor beads and mass spectrometry, we mapped the kinome landscape of HGSOC tumors from patients and patient-derived xenograft models. The data revealed a prevalent signature consisting of established HGSOC driver kinases, as well as several kinases previously unexplored in HGSOC. Loss-of-function analysis of these kinases in HGSOC cells indicated MRCKA (also known as CDC42BPA) as a putative therapeutic target. Characterization of the effects of MRCKA knockdown in established HGSOC cell lines demonstrated that MRCKA was integral to signaling that regulated the cell cycle checkpoint, focal adhesion, and actin remodeling, as well as cell migration, proliferation, and survival. Moreover, inhibition of MRCKA using the small-molecule BDP9066 decreased cell proliferation and spheroid formation and induced apoptosis in HGSOC cells, suggesting that MRCKA may be a promising therapeutic target for the treatment of HGSOC.

Drug screening approach combines epigenetic sensitization with immunochemotherapy in cancer

BACKGROUND

The epigenome plays a key role in cancer heterogeneity and drug resistance. Hence, a number of epigenetic inhibitors have been developed and tested in cancers. The major focus of most studies so far has been on the cytotoxic effect of these compounds, and only few have investigated the ability to revert the resistant phenotype in cancer cells. Hence, there is a need for a systematic methodology to unravel the mechanisms behind epigenetic sensitization.

RESULTS

We have developed a high-throughput protocol to screen non-simultaneous drug combinations, and used it to investigate the reprogramming potential of epigenetic inhibitors. We demonstrated the effectiveness of our protocol by screening 60 epigenetic compounds on diffuse large B-cell lymphoma (DLBCL) cells. We identified several histone deacetylase (HDAC) and histone methyltransferase (HMT) inhibitors that acted synergistically with doxorubicin and rituximab. These two classes of epigenetic inhibitors achieved sensitization by disrupting DNA repair, cell cycle, and apoptotic signaling. The data used to perform these analyses are easily browsable through our Results Explorer. Additionally, we showed that these inhibitors achieve sensitization at lower doses than those required to induce cytotoxicity.

CONCLUSIONS

Our drug screening approach provides a systematic framework to test non-simultaneous drug combinations. This methodology identified HDAC and HMT inhibitors as successful sensitizing compounds in treatment-resistant DLBCL. Further investigation into the mechanisms behind successful epigenetic sensitization highlighted DNA repair, cell cycle, and apoptosis as the most dysregulated pathways. Altogether, our method adds supporting evidence in the use of epigenetic inhibitors as sensitizing agents in clinical settings.

Noncompetitive binding of PpiD and YidC to the SecYEG translocon expands the global view on the SecYEG interactome in Escherichia coli

The SecYEG translocon constitutes the major protein transport channel in bacteria and transfers an enormous variety of different secretory and inner-membrane proteins. The minimal core of the SecYEG translocon consists of three inner-membrane proteins, SecY, SecE, and SecG, which, together with appropriate targeting factors, are sufficient for protein transport in vitro However, in vivo the SecYEG translocon has been shown to associate with multiple partner proteins, likely allowing the SecYEG translocon to process its diverse substrates. To obtain a global view on SecYEG plasticity in Escherichia coli, here we performed a quantitative interaction proteomic analysis, which identified several known SecYEG-interacting proteins, verified the interaction of SecYEG with quality-control proteins, and revealed several previously unknown putative SecYEG-interacting proteins. Surprisingly, we found that the chaperone complex PpiD/YfgM is the most prominent interaction partner of SecYEG. Detailed analyses of the PpiD-SecY interaction by site-directed cross-linking revealed that PpiD and the established SecY partner protein YidC use almost completely-overlapping binding sites on SecY. Both PpiD and YidC contacted the lateral gate, the plug domain, and the periplasmic cavity of SecY. However, quantitative MS and cross-linking analyses revealed that despite having almost identical binding sites, their binding to SecY is noncompetitive. This observation suggests that the SecYEG translocon forms different substrate-independent subassemblies in which SecYEG either associates with YidC or with the PpiD/YfgM complex. In summary, the results of this study indicate that the PpiD/YfgM chaperone complex is a primary interaction partner of the SecYEG translocon.

MS1 ion current-based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts

The rapidly-advancing field of pharmaceutical and clinical research calls for systematic, molecular-level characterization of complex biological systems. To this end, quantitative proteomics represents a powerful tool but an optimal solution for reliable large-cohort proteomics analysis, as frequently involved in pharmaceutical/clinical investigations, is urgently needed. Large-cohort analysis remains challenging owing to the deteriorating quantitative quality and snowballing missing data and false-positive discovery of altered proteins when sample size increases. MS1 ion current-based methods, which have become an important class of label-free quantification techniques during the past decade, show considerable potential to achieve reproducible protein measurements in large cohorts with high quantitative accuracy/precision. Nonetheless, in order to fully unleash this potential, several critical prerequisites should be met. Here we provide an overview of the rationale of MS1-based strategies and then important considerations for experimental and data processing techniques, with the emphasis on (i) efficient and reproducible sample preparation and LC separation; (ii) sensitive, selective and high-resolution MS detection; iii)accurate chromatographic alignment; (iv) sensitive and selective generation of quantitative features; and (v) optimal post-feature-generation data quality control. Prominent technical developments in these aspects are discussed. Finally, we reviewed applications of MS1-based strategy in disease mechanism studies, biomarker discovery, and pharmaceutical investigations.

Utilization of the Proteome Data Deposited in SRMAtlas for Validating the Existence of the Human Missing Proteins in GPM

The Human Proteome Project (HPP) has made great efforts to clarify the existing evidence of human proteins since 2012. However, according to the recent release of neXtProt (2019-1), approximately 10% of all human genes still have inadequate or no experimental evidence of their translation at the protein level. They were categorized as missing proteins (PE2-PE4). To further the goal of HPP, we developed a two-step bioinformatic strategy addressing the utilization of the SRMAtlas synthetic peptides corresponding to the missing proteins as an exclusive reference in order to explore their natural counterparts within GPM. In the first step, we searched the GPM for the non-nested SRMAtlas peptides corresponding to the missing proteins, taking under consideration only those detected via ≥2 non-nested unitypic/proteotypic peptides "Stranded peptides" with length ≥9 amino acids in the same proteomic study. As a result, 51 missing proteins were newly detected in 35 different proteomic studies. In the second step, we validated these newly detected missing proteins based on matching the spectra of their synthetic and natural peptides in SRMAtlas and GPM, respectively. The results showed that 23 of the missing proteins with ≥2 non-nested peptides were validated by careful spectral matching.

A super-SILAC based proteomics analysis of diffuse large B-cell lymphoma-NOS patient samples to identify new proteins that discriminate GCB and non-GCB lymphomas

Diffuse large B-cell lymphoma—not otherwise specified (DLBCL-NOS) is a large and heterogeneous subgroup of non-Hodgkin lymphoma. DLBCL can be subdivided into germinal centre B-cell like (GCB) and activated B-cell like (ABC or non-GCB) using a gene-expression based or an immunohistochemical approach. In this study we aimed to identify additional proteins that are differentially expressed between GCB and non-GCB DLBCL. A reference super-SILAC mix, including proteins of eight B-cell lymphoma cell lines, was mixed with proteins isolated from seven non-GCB DLBCL and five GCB DLBCL patient tissue samples to quantify protein levels. Protein identification and quantification was performed by LC-MS. We identified a total of 4289 proteins, with a four-fold significant difference in expression between non-GCB and GCB DLBCL for 37 proteins. Four proteins were selected for validation in the same cases and replication in an independent cohort of 47 DLBCL patients by immunohistochemistry. In the validation cohort, we observed a non-significant trend towards the same differential expression pattern as observed in the proteomics. The replication study showed significant and consistent differences for two of the proteins: expression of glomulin (GLMN) was higher in GCB DLBCL, while expression of ribosomal protein L23 (RPL23) was higher in non-GCB DLBCL. These proteins are functionally linked to important pathways involving MYC, p53 and angiogenesis. In summary, we showed increased expression of RPL23 and decreased expression of GLMN in non-GCB compared to GCB DLBCL on purified primary DLBCL patient samples and replicated these results in an independent patient cohort.

The liver proteome in a mouse model for Ascaris suum resistance and susceptibility: evidence for an altered innate immune response

Background

Ascariasis is a neglected tropical disease that affects 800 million people worldwide. Whereas most people only experience light worm burden, some people experience heavy worm burdens even after several rounds of chemotherapy, a phenomenon known as predisposition. Such heavy infections are associated with more severe symptoms and increased chronic morbidity.

Methods

In order to investigate potential mechanisms that may explain the observed predisposition, we infected mice with the porcine ascarid Ascaris suum using an established mouse model with two different mouse strains, where the C57BL/6J strain is more susceptible to infection and therefore a model for heavy infection and the CBA/Ca strain is more resistant and thus a model for light infection. At day 7 post-infection we investigated the liver proteome, using shotgun mass spectrometry, of both infected and control mice of each strain.

Results

We identified intrinsic differences, between the two mouse strains, in both oxidative phosphorylation proteins and proteins involved in retinol metabolism. Additionally, we found differences between the two mouse strains in activation of the complement system, where the CBA/Ca strain has higher protein abundances for lectin pathway proteins and the C57BL/6J strain has higher protein abundances for complement inhibiting proteins. The CBA/Ca strain had a higher abundance of proteins involved in the activation of the complement cascade via the lectin pathway. In contrast, the C57BL/6J strain demonstrated a higher abundance of proteins involved in arresting the complement pathway.

Conclusions

We observed clear differences between the two mouse strains both intrinsically and under infection.

Electronic supplementary material

The online version of this article (10.1186/s13071-019-3655-9) contains supplementary material, which is available to authorized users.

Phenotypic Characterization of Diffuse Large B-Cell Lymphoma Cells and Prognostic Impact

Multiparameter flow cytometry (MFC) is a fast and cost-effective technique to evaluate the expression of many lymphoid markers in mature B-cell neoplasms, including diffuse large B cell lymphoma (DLBCL), which is the most frequent non-Hodgkin lymphoma. In this study, we first characterized by MFC the expression of 27 lymphoid markers in 16 DLBCL-derived cell lines to establish a robust algorithm for their authentication. Then, using the expression profile in DLBCL samples of the genes encoding B lymphoid markers that are routinely investigated by MFC, we built a gene expression-based risk score, based on the expression level of BCL2, BCL6, CD11c, and LAIR1, to predict the outcome of patients with DLBCL. This risk score allowed splitting patients in four risk groups, and was an independent predictor factor of overall survival when compared with the previously published prognostic factors. Lastly, to investigate the potential correlation between BCL2, BCL6, CD11c, and LAIR1 protein level and resistance to treatment, we investigated the response of the 16 DLBCL cell lines to cyclophosphamide, etoposide, doxorubicin, and gemcitabine. We found a correlation between BCL6 overexpression and resistance to etoposide. These results show the interest of MFC for the routine characterization of DLBCL cells and tumors samples for research and diagnostic/prognostic purposes.

High-throughput mass spectrometry and bioinformatics analysis of breast cancer proteomic data

Data present here describe a comparative proteomic analysis among the malignant [primary breast tumor (PT) and axillary metastatic lymph nodes (LN)], and the non-tumor [contralateral (NCT) and adjacent (ANT)] breast tissues. Protein identification and quantification were performed through label-free mass spectrometry using a nano-liquid chromatography coupled to an electrospray ionization-mass spectrometry (nLC-ESI-MS/MS). The mass spectrometry proteomic data have been deposited to the ProteomeXchange Consortium via PRIDE partner repository with the dataset identifier PXD012431. A total of 462 differentially expressed proteins was identified among these tissues and was analyzed in six groups' comparisons (named NCTxANT, PTxNCT, PTxANT, LNxNCT, LNxANT and PTxLN). Proteins at 1.5 log2 fold change were submitted to the Ingenuity^® Pathway Analysis (IPA) software version 2.3 (QIAGEN Inc.) to identify biological pathways, disease and function annotation, and interaction networks related to cancer biology. The detailed data present here provides information about the proteome alterations and their role on breast tumorigenesis. This information can lead to novel biological insights on cancer research. For further interpretation of these data, please see our research article 'Quantitative label-free mass spectrometry using contralateral and adjacent breast tissues reveal differentially expressed proteins and their predicted impacts on pathways and cellular functions in breast cancer' [2].

Quantitative Proteomics of Presynaptic Mitochondria Reveal an Overexpression and Biological Relevance of Neuronal MitoNEET in Postnatal Brain Development

Although it has been recognized that energy metabolism and mitochondrial structure and functional activity in the immature brain differs from that of the adult, few studies have examined mitochondria specifically at the neuronal synapse during postnatal brain development. In this study, we examined the presynaptic mitochondrial proteome in mice at postnatal day 7 and 42, a period that involves the formation and maturation of synapses. Application of two independent quantitative proteomics approaches - SWATH-MS and super-SILAC - revealed a total of 40 proteins as significantly differentially expressed in the presynaptic mitochondria. In addition to elevated levels of proteins known to be involved in ATP metabolic processes, our results identified increased levels of mitoNEET (Cisd1), an iron-sulfur containing protein that regulates mitochondrial bioenergetics. We found that mitoNEET overexpression plays a cell-type specific role in ATP synthesis and in neuronal cells promotes ATP generation. The elevated ATP levels in SH-SY5Y neuroblastoma cells were associated with increased mitochondrial membrane potential and a fragmented mitochondrial network, further supporting a role for mitoNEET as a key regulator of mitochondrial function.

Heterogeneity and coexistence of oncogenic mechanisms involved in HCV-associated B-cell lymphomas

The association of HCV-infection with B-lymphomas is supported by the regression of most indolent/low-grade lymphomas following anti-viral therapy. Studies on direct and indirect oncogenic mechanisms have elucidated the pathogenesis of HCV-associated B-lymphoma subtypes. These include B-lymphocyte proliferation and sustained clonal expansion by HCV-envelope protein stimulation of B-cell receptors, and prolonged HCV-infected B-cell growth by overexpression of an anti-apoptotic BCL-2 oncogene caused by the increased frequency of t(14;18) chromosomal translocations in follicular lymphomas. HCV has been implicated in lymphomagenesis by a "hit-and-run" mechanism, inducing enhanced mutation rate in immunoglobulins and anti-oncogenes favoring immune escape, due to permanent genetic damage by double-strand DNA-breaks. More direct oncogenic mechanisms have been identified in cytokines and chemokines in relation to NS3 and Core expression, particularly in diffuse large B-cell lymphoma. By reviewing genetic alterations and disrupted signaling pathways, we intend to highlight how mutually non-contrasting mechanisms cooperate with environmental factors toward progression of HCV-lymphoma.

Dysregulated expressions of PTEN, NF-κB, WWP2, p53 and c-Myc in different subtypes of B cell lymphoma and reactive follicular hyperplasia

This study aimed to investigate the value of PTEN, NF-κB, WWP2, p53 and c-Myc expressions in distinguishing B cell lymphomas from reactive follicular hyperplasia (RFH), and their abilities to discriminate different B cell lymphoma subtypes. Lymphoma tissue samples were obtained from 30 follicular lymphoma (FL) patients, 30 germinal center B-cell like (GCB) diffuse large B cell lymphoma (DLBCL) patients, 30 non-GCB DLBCL patients and 30 Burkitt's lymphoma (BL) patients. And hyperplasia tissue samples were obtained from and 30 RFH patients. Immunohistochemistry was used to quantify the expressions of PTEN, NF-κB, WWP2, P53 and c-Myc. PTEN expression was elevated in GCB DLBCL and BL compared with RFH, and in GCB DLBCL, non-GCB DLBCL and BL than that in FL; WWP2 expression was higher in FL, GCB DLBCL, non-GCB DLBCL and BL compared with RFH; p53 expression increased in non-GCB DLBCL compared with RFH, and in BL compared with RFH, FL or GCB DLBCL; c-Myc expression was higher in GCB DLBCL, non-GCB DLBCL and BL compared with RFH; c-Myc expression was elevated in GCB DLBCL, non-GCB DLBCL and BL compared with FL. Additionally, PTEN negatively correlated with p53 expression in FL and CGB DLBCL, whereas NF-κB negatively correlated with WWP2 in GCB DLBCL, but positively associated with PTEN in RFH and c-Myc in BL. PTEN, WWP2, p53 and c-Myc expressions might be served as biomarkers for identification of B cell lymphomas from RFH as well as distinguishing different B cell lymphoma subtypes.

Multi-omics dataset to decipher the complexity of drug resistance in diffuse large B-cell lymphoma

The prognosis of patients with relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) remains unsatisfactory and, despite major advances in genomic studies, the biological mechanisms underlying chemoresistance are still poorly understood. We conducted for the first time a large-scale differential multi-omics investigation on DLBCL patient’s samples in order to identify new biomarkers that could early identify patients at risk of R/R disease and to identify new targets that could determine chemorefractoriness. We compared a well-characterized cohort of R/R versus chemosensitive DLBCL patients by combining label-free quantitative proteomics and targeted RNA sequencing performed on the same tissues samples. The cross-section of both data levels allowed extracting a sub-list of 22 transcripts/proteins pairs whose expression levels significantly differed between the two groups of patients. In particular, we identified significant targets related to tumor metabolism (Hexokinase 3), microenvironment (IDO1, CXCL13), cancer cells proliferation, migration and invasion (S100 proteins) or BCR signaling pathway (CD79B). Overall, this study revealed several extremely promising biomarker candidates related to DLBCL chemorefractoriness and highlighted some new potential therapeutic drug targets. The complete datasets have been made publically available and should constitute a valuable resource for the future research.

Epstein-Barr Virus Infection of Cell Lines Derived from Diffuse Large B-Cell Lymphomas Alters MicroRNA Loading of the Ago2 Complex

Diffuse large B-cell lymphoma (DLBCL) is an aggressive lymphoid tumor which is occasionally Epstein-Barr virus (EBV) positive and is further subtyped as activated B-cell DLBCL (ABC-DLBCL) and germinal center B-cell DLBCL (GCB-DLBCL), which has implications for prognosis and treatment. We performed Ago2 RNA immunoprecipitation followed by high-throughput RNA sequencing (Ago2-RIP-seq) to capture functionally active microRNAs (miRNAs) in EBV-negative ABC-DLBCL and GCB-DLBCL cell lines and their EBV-infected counterparts. In parallel, total miRNA profiles of these cells were determined to capture the cellular miRNA profile for comparison with the functionally active profile. Selected miRNAs with differential abundances were validated using real-time quantitative PCR (RT-qPCR) and Northern blotting. We found 6 miRNAs with differential abundances (2 upregulated and 4 downregulated miRNAs) between EBV-negative and -positive ABC-DLBCL cells and 12 miRNAs with differential abundances (3 upregulated and 9 downregulated miRNAs) between EBV-negative and -positive GCB-DLBCL cells. Eight and twelve miRNAs were confirmed using RT-qPCR in ABC-DLBCL and GCB-DLBCL cells, respectively. Selected miRNAs were analyzed in additional type I/II versus type III EBV latency DLBCL cell lines. Furthermore, upregulation of miR-221-3p and downregulation of let7c-5p in ABC-DLBCL cells and upregulation of miR-363-3p and downregulation of miR-423-5p in GCB-DLBCL cells were verified using RIP-Northern blotting. Our comprehensive sequence analysis of the DLBCL miRNA profiles identified sets of deregulated miRNAs by Ago2-RIP-seq. Our Ago2-IP-seq miRNA profile could be considered an important data set for the detection of deregulated functionally active miRNAs in DLBCLs and could possibly lead to the identification of miRNAs as biomarkers for the classification of DLBCLs or even as targets for personalized targeted treatment.IMPORTANCE Diffuse large B-cell lymphoma (DLBCL) is a highly aggressive tumor of lymphoid origin which is occasionally Epstein-Barr virus (EBV) positive. MicroRNAs are found in most multicellular organisms and even in viruses such as EBV. They regulate the synthesis of proteins by binding to their cognate mRNA. MicroRNAs are tethered to their target mRNAs by "Argonaute" proteins. Here we compared the overall miRNA content of the Ago2 complex by differential loading to the overall content of miRNAs in two DLBCL cell lines and their EBV-converted counterparts. In all cell lines, the Ago2 load was different from the overall expression of miRNAs. In addition, the loading of the Ago2 complex was changed upon infection with EBV. This indicates that the virus not only changes the overall content of miRNAs but also influences the expression of proteins by affecting the Ago complexes.

Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Quantitative Proteomics

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful approach for high-throughput quantitative proteomics. SILAC allows highly accurate protein quantitation through metabolic encoding of whole cell proteomes using stable isotope labeled amino acids. Since its introduction in 2002, SILAC has become increasingly popular. In this chapter we review the methodology and application of SILAC, with an emphasis on three research areas: dynamics of posttranslational modifications, protein-protein interactions, and protein turnover.

Deep proteome of human nNOS/NOS1-positive versus MOCK SH-SY5Y neuroblastoma cells under full nutrition, serum free starvation and rapamycin treatment

Upregulations of neuronal nitric oxide synthase (nNOS/NOS1) in the mouse brain upon aging suggest a role in age-associated changes of protein homeostasis. We generated a cell model, in which constitutive expression of nNOS in SH-SY5Y cells at a level comparable to mouse brain replicates the aging phenotype i.e. slowing of cell proliferation, cell enlargement and expression of senescence markers. nNOS+ and MOCK cells were exposed to proteostasis stress by treatment with rapamycin or serum-free starvation. The proteomes were analyzed per SILAC or label-free using hybrid liquid chromatography/mass spectrometry (LC/MS). Full scan MS-data were acquired using Xcalibur, and raw mass spectra were analyzed using the proteomics software MaxQuant. The human reference proteome from uniprot was used as template to identify peptides and proteins and quantify protein expression. The DiB data file contains essential MaxQuant output tables and includes peptide and protein identification, accession numbers, protein and gene names, sequence coverage and quantification values of each sample. Differences in protein expression in MOCK versus nNOS+ SH-SY5Y cells and interpretation of results are presented in Valek et al. (2018). Raw mass spectra and MaxQuant output files have been deposited to the ProteomeXchange Consortium (Vizcaino et al., 2014) via the PRIDE partner repository with the dataset identifier PRIDE: PXD010538.

Assembling the Community-Scale Discoverable Human Proteome

The increasing throughput and sharing of proteomics mass spectrometry data have now yielded over one-third of a million public mass spectrometry runs. However, these discoveries are not continuously aggregated in an open and error-controlled manner, which limits their utility. To facilitate the reusability of these data, we built the MassIVE Knowledge Base (MassIVE-KB), a community-wide, continuously updating knowledge base that aggregates proteomics mass spectrometry discoveries into an open reusable format with full provenance information for community scrutiny. Reusing >31 TB of public human data stored in a mass spectrometry interactive virtual environment (MassIVE), the MassIVE-KB contains >2.1 million precursors from 19,610 proteins (48% larger than before; 97% of the total) and doubles proteome coverage to 6 million amino acids (54% of the proteome) with strict library-scale false discovery controls, thereby providing evidence for 430 proteins for which sufficient protein-level evidence was previously missing. Furthermore, MassIVE-KB can inform experimental design, helps identify and quantify new data, and provides tools for community construction of specialized spectral libraries.

Wang et al. introduce MassIVE-KB, a program designed to distill the entire community’s mass spectrometry data into reusable spectral library resources. As a result, the statistically-significant discovery of a peptide or protein in a single researcher’s data will thus be made available to the whole community to support its identification (in shotgun experiments) or quantitative detection (in targeted experiments) in all future analyses.

SILAC-based quantitative proteomic analysis of the livers of spontaneous obese and diabetic rhesus monkeys

Type 2 diabetes mellitus (T2DM) is a severe metabolic disorder that affects more than 10% of the population worldwide. Obesity is a major cause of insulin resistance and contributes to the development of T2DM. Liver is an essential metabolic organ that plays crucial roles in the pathogenesis of obesity and diabetes. However, the underlying mechanisms of liver in the transition of obesity to diabetes are not fully understood. The nonhuman primate rhesus monkey is an appropriate animal for research of human diseases. Here, we first screened and selected three individuals of spontaneously diabetic rhesus monkeys. Interestingly, the diabetic monkeys were obese with a high body mass index at the beginning, but gradually lost their body weight during one year of observation. Furthermore, we performed stable isotope labeling with amino acids in cell culture-based quantitative proteomics to identify proteins and signaling pathways with altered expression in the liver of obese and diabetic monkeys. In total, 3,509 proteins were identified and quantified, of which 185 proteins displayed an altered expression level. Gene ontology analysis revealed that the expression of proteins involved in fatty acids β-oxidation and galactose metabolism was increased in obese monkeys; while proteins involved in oxidative phosphorylation and branched chain amino acid (BCAA) degradation were upregulated in diabetic monkeys. In addition, we observed mild apoptosis in the liver of diabetic monkeys, suggesting liver injury at the late onset of diabetes. Taken together, our liver proteomics may reveal a distinct metabolic transition from fatty acids β-oxidation in obese monkey to BCAA degradation in diabetic monkeys.

Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Genomic characterization has begun to redefine diagnostic classifications of cancers. However, it remains a challenge to infer disease phenotypes from genomic alterations alone. To help realize the promise of genomics, we have performed a quantitative proteomics investigation using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and 41 tissue samples spanning the 4 genomically based subgroups of medulloblastoma and control cerebellum. We have identified and quantitated thousands of proteins across these groups and find that we are able to recapitulate the genomic subgroups based upon subgroup restricted and differentially abundant proteins while also identifying subgroup specific protein isoforms. Integrating our proteomic measurements with genomic data, we calculate a poor correlation between mRNA and protein abundance. Using EPIC 850 k methylation array data on the same tissues, we also investigate the influence of copy number alterations and DNA methylation on the proteome in an attempt to characterize the impact of these genetic features on the proteome. Reciprocally, we are able to use the proteome to identify which genomic alterations result in altered protein abundance and thus are most likely to impact biology. Finally, we are able to assemble protein-based pathways yielding potential avenues for clinical intervention. From these, we validate the EIF4F cap-dependent translation pathway as a novel druggable pathway in medulloblastoma. Thus, quantitative proteomics complements genomic platforms to yield a more complete understanding of functional tumor biology and identify novel therapeutic targets for medulloblastoma.

Molecular signatures that can be transferred across different omics platforms

Motivation

Molecular signatures for treatment recommendations are well researched. Still it is challenging to apply them to data generated by different protocols or technical platforms.

Results

We analyzed paired data for the same tumors (Burkitt lymphoma, diffuse large B-cell lymphoma) and features that had been generated by different experimental protocols and analytical platforms including the nanoString nCounter and Affymetrix Gene Chip transcriptomics as well as the SWATH and SRM proteomics platforms. A statistical model that assumes independent sample and feature effects accounted for 69–94% of technical variability. We analyzed how variability is propagated through linear signatures possibly affecting predictions and treatment recommendations. Linear signatures with feature weights adding to zero were substantially more robust than unbalanced signatures. They yielded consistent predictions across data from different platforms, both for transcriptomics and proteomics data. Similarly stable were their predictions across data from fresh frozen and matching formalin-fixed paraffin-embedded human tumor tissue.

Availability and Implementation

The R-package ‘zeroSum’ can be downloaded at https://github.com/rehbergT/zeroSum. Complete data and R codes necessary to reproduce all our results can be received from the authors upon request.

Characterization of the Small Intestinal Lesion in Celiac Disease by Label-Free Quantitative Mass Spectrometry

Global characterization of tissue proteomes from small amounts of biopsy material has become feasible because of advances in mass spectrometry and bioinformatics tools. In celiac disease (CD), dietary gluten induces an immune response that is accompanied by pronounced remodeling of the small intestine. Removal of gluten from the diet abrogates the immune response, and the tissue architecture normalizes. In this study, differences in global protein expression of small intestinal biopsy specimens from CD patients were quantified by analyzing formalin-fixed, paraffin-embedded material using liquid chromatography-mass spectrometry and label-free protein quantitation. Protein expression was compared in biopsy specimens collected from the same patients before and after 1-year treatment with gluten-free diet (n = 10) or before and after 3-day gluten provocation (n = 4). Differential expression of proteins in particular from mature enterocytes, neutrophils, and plasma cells could distinguish untreated from treated CD mucosa, and Ig variable region IGHV5-51 expression was found to serve as a CD-specific marker of ongoing immune activation. In patients who had undergone gluten challenge, coordinated up-regulation of wound response proteins, including the CD autoantigen transglutaminase 2, was observed. Our study provides a global and unbiased assessment of antigen-driven changes in protein expression in the celiac intestinal mucosa.

Proteomic analysis and bioluminescent reporter gene assays to investigate effects of simulated microgravity on Caco-2 cells

Microgravity is one of the most important features in spaceflight. Previous evidence from in-vitro studies has shown that significant changes occur under simulated microgravity. For this reason, human colon adenocarcinoma Caco-2 cells were selected as cell model of intestinal epithelial barrier and their response to altered gravity conditions was investigated, especially on the protein level. In this study, we combined label-free shotgun proteomics and bioluminescent reporter gene assays to identify key proteins and pathways involved in the response of Caco-2 cells under reference and microgravity conditions. A two-dimensional clinostat was modified with 3D-printed adaptors to hold conventional T25 culture flasks. The comparative proteome analysis led to identify 38 and 26 proteins differently regulated by simulated microgravity after 48 and 72 h, respectively. Substantial fractions of these proteins are involved in regulation, cellular and metabolic processes and localization. Bioluminescent reporter gene assays were carried out to investigate microgavity-induced alterations on the transcriptional regulation of key targets, such as NF-kB pathway and CYP27A1. While no significant difference was found in the basal transcription, a lower NF-kB basal activation in simulated microgravity conditions was reported, corroborating the hypothesis of reduced immunity in microgravity conditions.

Data integration and predictive modeling methods for multi-omics datasets

We provide an overview of opportunities and challenges in multi-omics predictive analytics with particular emphasis on data integration and machine learning methods.