Research Event

Event participants

Dr Hafez Ghanem, Vice President for Africa, World Bank
Chair: Elizabeth Donnelly, Deputy Director, Africa Programme, Chatham House

1 May 2020

Research Event

Event participants

7 May 2020 , Volume 96, Number 3

Fatty acid transport protein 2 (FATP2) is highly expressed in the liver, small intestine, and kidney, where it functions in both the transport of exogenous long-chain fatty acids and the activation of very-long-chain fatty acids. Here, using a murine model, we investigated the phenotypic impacts of deleting FATP2, followed by a transcriptomic analysis using unbiased RNA-Seq to identify concomitant changes in the liver transcriptome. WT and FATP2-null (Fatp2−/−) mice (5 weeks) were maintained on a standard chow diet for 6 weeks. The Fatp2−/− mice had reduced weight gain, lowered serum triglyceride, and increased serum cholesterol levels and attenuated dietary fatty acid absorption. Transcriptomic analysis of the liver revealed 258 differentially expressed genes in male Fatp2−/− mice and a total of 91 in female Fatp2−/− mice. These genes mapped to the following gene ontology categories: fatty acid degradation, peroxisome biogenesis, fatty acid synthesis, and retinol and arachidonic acid metabolism. Targeted RT-quantitative PCR verified the altered expression of selected genes. Of note, most of the genes with increased expression were known to be regulated by peroxisome proliferator–activated receptor α (PPARα), suggesting that FATP2 activity is linked to a PPARα-specific proximal ligand. Targeted metabolomic experiments in the Fatp2−/− liver revealed increases of total C16:0, C16:1, and C18:1 fatty acids; increases in lipoxin A4 and prostaglandin J2; and a decrease in 20-hydroxyeicosatetraenoic acid. We conclude that the expression of FATP2 in the liver broadly affects the metabolic landscape through PPARα, indicating that FATP2 provides an important role in liver lipid metabolism through its transport or activation activities.

The molecular mechanisms underlying exceptional radioresistance in pancreatic cancer remain elusive. In the present study, we established a stable radioresistant pancreatic cancer cell line MIA PaCa-2-R by exposing the parental MIA PaCa-2 cells to fractionated ionizing radiation (IR). Systematic proteomics and bioinformatics analysis of protein expression in MIA PaCa-2 and MIA PaCa-2-R cells revealed that several growth factor-/cytokine-mediated pathways, including the OSM/STAT3, PI3K/AKT, and MAPK/ERK pathways, were activated in the radioresistant cells, leading to inhibition of apoptosis and increased epithelial-mesenchymal plasticity. In addition, the radioresistant cells exhibited enhanced capabilities of DNA repair and antioxidant defense compared with the parental cells. We focused functional analysis on one of the most up-regulated proteins in the radioresistant cells, ecto-5'-nucleotidase (CD73), which is a cell surface protein that is overexpressed in different types of cancer. Ectopic overexpression of CD73 in the parental cells resulted in radioresistance and conferred resistance to IR-induced apoptosis. Knockdown of CD73 re-sensitized the radioresistant cells to IR and IR-induced apoptosis. The effect of CD73 on radioresistance and apoptosis is independent of the enzymatic activity of CD73. Further studies demonstrate that CD73 up-regulation promotes Ser-136 phosphorylation of the proapoptotic protein BAD and is required for maintaining the radioresistant cells in a mesenchymal state. Our findings suggest that expression alterations in the IR-selected pancreatic cancer cells result in hyperactivation of the growth factor/cytokine signaling that promotes epithelial-mesenchymal plasticity and enhancement of DNA repair. Our results also suggest that CD73, potentially a novel downstream factor of the enhanced growth factor/cytokine signaling, confers acquired radioresistance by inactivating proapoptotic protein BAD via phosphorylation of BAD at Ser-136 and by maintaining the radioresistant pancreatic cancer cells in a mesenchymal state.

Aberrantly high mTORC1 signaling is a known driver of many cancers and human disorders, yet pharmacological inhibition of mTORC1 rarely confers durable clinical responses. To explore alternative therapeutic strategies, herein we conducted a proteomics survey to identify cell surface proteins upregulated by mTORC1. A comparison of the surfaceome from Tsc1^–/– versus Tsc1^+/+ mouse embryonic fibroblasts revealed 59 proteins predicted to be significantly overexpressed in Tsc1^–/– cells. Further validation of the data in multiple mouse and human cell lines showed that mTORC1 signaling most dramatically induced the expression of the proteases neprilysin (NEP/CD10) and aminopeptidase N (APN/CD13). Functional studies showed that constitutive mTORC1 signaling sensitized cells to genetic ablation of NEP and APN, as well as the biochemical inhibition of APN. In summary, these data show that mTORC1 signaling plays a significant role in the constitution of the surfaceome, which in turn may present novel therapeutic strategies.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with very limited therapeutic options. We have recently shown that the combined inhibition of EGFR and ROCK in TNBC cells results in cell death, however, the underlying mechanisms remain unclear. To investigate this, here we applied a mass spectrometry-based proteomic approach to identify proteins altered on single and combination treatments. Our proteomic data revealed autophagy as the major molecular mechanism implicated in the cells' response to combinatorial treatment. We here show that EGFR inhibition by gefitinib treatment alone induces autophagy, a cellular recycling process that acts as a cytoprotective response for TNBC cells. However, combined inhibition of EGFR and ROCK leads to autophagy blockade and accumulation of autophagic vacuoles. Our data show impaired autophagosome clearance as a likely cause of antitumor activity. We propose that the inhibition of the autophagic flux on combinatorial treatment is attributed to the major cytoskeletal changes induced on ROCK inhibition, given the essential role the cytoskeleton plays throughout the various steps of the autophagy process.

Mycobacterial Ser/Thr protein kinases (STPKs) play a critical role in signal transduction pathways that ultimately determine mycobacterial growth and metabolic adaptation. Identification of key physiological substrates of these protein kinases is, therefore, crucial to better understand how Ser/Thr phosphorylation contributes to mycobacterial environmental adaptation, including response to stress, cell division, and host-pathogen interactions. Various substrate detection methods have been employed with limited success, with direct targets of STPKs remaining elusive. Recently developed mass spectrometry (MS)-based phosphoproteomic approaches have expanded the list of potential STPK substrate identifications, yet further investigation is required to define the most functionally significant phosphosites and their physiological importance. Prior to the application of MS workflows, for instance, GarA was the only known and validated physiological substrate for protein kinase G (PknG) from pathogenic mycobacteria. A subsequent list of at least 28 candidate PknG substrates has since been reported with the use of MS-based analyses. Herein, we integrate and critically review MS-generated datasets available on novel STPK substrates and report new functional and subcellular localization enrichment analyses on novel candidate protein kinase A (PknA), protein kinase B (PknB) and PknG substrates to deduce the possible physiological roles of these kinases. In addition, we assess substrate specificity patterns across different mycobacterial STPKs by analyzing reported sets of phosphopeptides, in order to determine whether novel motifs or consensus regions exist for mycobacterial Ser/Thr phosphorylation sites. This review focuses on MS-based techniques employed for STPK substrate identification in mycobacteria, while highlighting the advantages and challenges of the various applications.

Glycosylation is a common modification of proteins and critical for a wide range of biological processes. Differences in protein glycosylation between sexes have already been observed in humans, nematodes and trematodes, and have recently also been reported in the rice pest insect Nilaparvata lugens. Although protein N-glycosylation in insects is nowadays of high interest because of its potential for exploitation in pest control strategies, the functionality of differential N-glycosylation between sexes is yet unknown. In this study, therefore, the occurrence and role of sex-related protein N-glycosylation in insects were examined. A comprehensive investigation of the N-glycosylation sites from the adult stages of N. lugens was conducted, allowing a qualitative and quantitative comparison between sexes at the glycopeptide level. N-glycopeptide enrichment via lectin capturing using the high mannose/paucimannose-binding lectin Concanavalin A, or the Rhizoctonia solani agglutinin which interacts with complex N-glycans, resulted in the identification of over 1300 N-glycosylation sites derived from over 600 glycoproteins. Comparison of these N-glycopeptides revealed striking differences in protein N-glycosylation between sexes. Male- and female-specific N-glycosylation sites were identified, and some of these sex-specific N-glycosylation sites were shown to be derived from proteins with a putative role in insect reproduction. In addition, differential glycan composition between males and females was observed for proteins shared across sexes. Both lectin blotting experiments as well as transcript expression analyses with complete insects and insect tissues confirmed the observed differences in N-glycosylation of proteins between sexes. In conclusion, this study provides further evidence for protein N-glycosylation to be sex-related in insects. Furthermore, original data on N-glycosylation sites of N. lugens adults are presented, providing novel insights into planthopper's biology and information for future biological pest control strategies.

Chronic hyperglycemia is known to disrupt the proteolytic milieu, initiating compensatory and maladaptive pathways in the diabetic kidney. Such changes in intrarenal proteolysis are captured by the urinary peptidome. To elucidate the early kidney response to chronic hyperglycemia, we conducted a peptidomic investigation into urines from otherwise healthy youths with type 1 diabetes and their non-diabetic peers using unbiased and targeted mass spectrometry-based techniques. This cross-sectional study included two separate cohorts for the discovery (n = 30) and internal validation (n = 30) of differential peptide excretion. Peptide bioactivity was predicted using PeptideRanker and subsequently verified in vitro. Proteasix and the Nephroseq database were used to identify putative proteases responsible for peptide generation and examine their expression in diabetic nephropathy. A total of 6550 urinary peptides were identified in the discovery analysis. We further examined the subset of 162 peptides, which were quantified across all thirty samples. Of the 15 differentially excreted peptides (p < 0.05), seven derived from a C-terminal region (⁵⁸⁹SGSVIDQSRVLNLGPITRK⁶⁰⁷) of uromodulin, a kidney-specific protein. Increased excretion of five uromodulin peptides was replicated in the validation cohort using parallel reaction monitoring (p < 0.05). One of the validated peptides (SGSVIDQSRVLNLGPI) activated NFB and AP-1 signaling, stimulated cytokine release, and enhanced neutrophil migration in vitro. In silico analyses highlighted several potential proteases such as hepsin, meprin A, and cathepsin B to be responsible for generating these peptides. In summary, we identified a urinary signature of uromodulin peptides associated with early type 1 diabetes before clinical manifestations of kidney disease and discovered novel bioactivity of uromodulin peptides in vitro. Our present findings lay the groundwork for future studies to validate peptide excretion in larger and broader populations, to investigate the role of bioactive uromodulin peptides in high glucose conditions, and to examine proteases that cleave uromodulin.

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

The prediction of metastatic properties from molecular analyses still poses a major challenge. Here we aimed at the classification of metastasis-related cell properties by proteome profiling making use of cutaneous and brain-metastasizing variants from single melanomas sharing the same genetic ancestry. Previous experiments demonstrated that cultured cells derived from these xenografted variants maintain a stable phenotype associated with a differential metastatic behavior: The brain metastasizing variants produce more spontaneous micro-metastases than the corresponding cutaneous variants. Four corresponding pairs of cutaneous and metastatic cells were obtained from four individual patients, resulting in eight cell-lines presently investigated. Label free proteome profiling revealed significant differences between corresponding pairs of cutaneous and cerebellar metastases from the same patient. Indeed, each brain metastasizing variant expressed several apparently metastasis-associated proteomic alterations as compared with the corresponding cutaneous variant. Among the differentially expressed proteins we identified cell adhesion molecules, immune regulators, epithelial to mesenchymal transition markers, stem cell markers, redox regulators and cytokines. Similar results were observed regarding eicosanoids, considered relevant for metastasis, such as PGE2 and 12-HETE. Multiparametric morphological analysis of cells also revealed no characteristic alterations associated with the cutaneous and brain metastasis variants. However, no correct classification regarding metastatic potential was yet possible with the present data. We thus concluded that molecular profiling is able to classify cells according to known functional categories but is not yet able to predict relevant cell properties emerging from networks consisting of many interconnected molecules. The presently observed broad diversity of molecular patterns, irrespective of restricting to one tumor type and two main classes of metastasis, highlights the important need to develop meta-analysis strategies to predict cell properties from molecular profiling data. Such base knowledge will greatly support future individualized precision medicine approaches.

Dynamic tyrosine phosphorylation is fundamental to a myriad of cellular processes. However, the inherently low abundance of tyrosine phosphorylation in the proteome and the inefficient enrichment of phosphotyrosine(pTyr)-containing peptides has led to poor pTyr peptide identification and quantitation, critically hindering researchers' ability to elucidate signaling pathways regulated by tyrosine phosphorylation in systems where cellular material is limited. The most popular approaches to wide-scale characterization of the tyrosine phosphoproteome use pTyr enrichment with pan-specific, anti-pTyr antibodies from a large amount of starting material. Methods that decrease the amount of starting material and increase the characterization depth of the tyrosine phosphoproteome while maintaining quantitative accuracy and precision would enable the discovery of tyrosine phosphorylation networks in rarer cell populations. To achieve these goals, the BOOST (Broad-spectrum Optimization Of Selective Triggering) method leveraging the multiplexing capability of tandem mass tags (TMT) and the use of pervanadate (PV) boost channels (cells treated with the broad-spectrum tyrosine phosphatase inhibitor PV) selectively increased the relative abundance of pTyr-containing peptides. After PV boost channels facilitated selective fragmentation of pTyr-containing peptides, TMT reporter ions delivered accurate quantitation of each peptide for the experimental samples while the quantitation from PV boost channels was ignored. This method yielded up to 6.3-fold boost in pTyr quantification depth of statistically significant data derived from contrived ratios, compared with TMT without PV boost channels or intensity-based label-free (LF) quantitation while maintaining quantitative accuracy and precision, allowing quantitation of over 2300 unique pTyr peptides from only 1 mg of T cell receptor-stimulated Jurkat T cells. The BOOST strategy can potentially be applied in analyses of other post-translational modifications where treatments that broadly elevate the levels of those modifications across the proteome are available.

We present a technological advancement for the estimation of the affinities of Protein-Protein Interactions (PPIs) in living cells. A novel set of vectors is introduced that enables a quantitative yeast two-hybrid system based on fluorescent fusion proteins. The vectors allow simultaneous quantification of the reaction partners (Bait and Prey) and the reporter at the single-cell level by flow cytometry. We validate the applicability of this system on a small but diverse set of PPIs (eleven protein families from six organisms) with different affinities; the dissociation constants range from 117 pm to 17 μm. After only two hours of reaction, expression of the reporter can be detected even for the weakest PPI. Through a simple gating analysis, it is possible to select only cells with identical expression levels of the reaction partners. As a result of this standardization of expression levels, the mean reporter levels directly reflect the affinities of the studied PPIs. With a set of PPIs with known affinities, it is straightforward to construct an affinity ladder that permits rapid classification of PPIs with thus far unknown affinities. Conventional software can be used for this analysis. To permit automated analysis, we provide a graphical user interface for the Python-based FlowCytometryTools package.

Anal squamous cell carcinoma is a rare tumor. Chemo-radiotherapy yields a 50% 3-year relapse-free survival rate in advanced anal cancer, so improved predictive markers and therapeutic options are needed. High-throughput proteomics and whole-exome sequencing were performed in 46 paraffin samples from anal squamous cell carcinoma patients. Hierarchical clustering was used to establish groups de novo. Then, probabilistic graphical models were used to study the differences between groups of patients at the biological process level. A molecular classification into two groups of patients was established, one group with increased expression of proteins related to adhesion, T lymphocytes and glycolysis; and the other group with increased expression of proteins related to translation and ribosomes. The functional analysis by the probabilistic graphical model showed that these two groups presented differences in metabolism, mitochondria, translation, splicing and adhesion processes. Additionally, these groups showed different frequencies of genetic variants in some genes, such as ATM, SLFN11 and DST. Finally, genetic and proteomic characteristics of these groups suggested the use of some possible targeted therapies, such as PARP inhibitors or immunotherapy.

An experimental and computational approach for identification of protein-protein interactions by ex vivo chemical crosslinking and mass spectrometry (CLMS) has been developed that takes advantage of the specific characteristics of cyanurbiotindipropionylsuccinimide (CBDPS), an affinity-tagged isotopically coded mass spectrometry (MS)-cleavable crosslinking reagent. Utilizing this reagent in combination with a crosslinker-specific data-dependent acquisition strategy based on MS2 scans, and a software pipeline designed for integrating crosslinker-specific mass spectral information led to demonstrated improvements in the application of the CLMS technique, in terms of the detection, acquisition, and identification of crosslinker-modified peptides. This approach was evaluated on intact yeast mitochondria, and the results showed that hundreds of unique protein-protein interactions could be identified on an organelle proteome-wide scale. Both known and previously unknown protein-protein interactions were identified. These interactions were assessed based on their known sub-compartmental localizations. Additionally, the identified crosslinking distance constraints are in good agreement with existing structural models of protein complexes involved in the mitochondrial electron transport chain.

The cell cycle is a highly conserved process involving the coordinated separation of a single cell into two daughter cells. To relate transcriptional regulation across the cell cycle with oscillatory changes in protein abundance and activity, we carried out a proteome- and phospho-proteome-wide mass spectrometry profiling. We compared protein dynamics with gene transcription, revealing many transcriptionally regulated G2 mRNAs that only produce a protein shift after mitosis. Integration of CRISPR/Cas9 survivability studies further highlighted proteins essential for cell viability. Analyzing the dynamics of phosphorylation events and protein solubility dynamics over the cell cycle, we characterize predicted phospho-peptide motif distributions and predict cell cycle-dependent translocating proteins, as exemplified by the S-adenosylmethionine synthase MAT2A. Our study implicates this enzyme in translocating to the nucleus after the G1/S-checkpoint, which enables epigenetic histone methylation maintenance during DNA replication. Taken together, this data set provides a unique integrated resource with novel insights on cell cycle dynamics.

In osteoarthritis (OA), impairment of cartilage regeneration can be related to a defective chondrogenic differentiation of mesenchymal stromal cells (MSCs). Therefore, understanding the proteomic- and metabolomic-associated molecular events during the chondrogenesis of MSCs could provide alternative targets for therapeutic intervention. Here, a SILAC-based proteomic analysis identified 43 proteins related with metabolic pathways whose abundance was significantly altered during the chondrogenesis of OA human bone marrow MSCs (hBMSCs). Then, the level and distribution of metabolites was analyzed in these cells and healthy controls by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), leading to the recognition of characteristic metabolomic profiles at the early stages of differentiation. Finally, integrative pathway analysis showed that UDP-glucuronic acid synthesis and amino sugar metabolism were downregulated in OA hBMSCs during chondrogenesis compared with healthy cells. Alterations in these metabolic pathways may disturb the production of hyaluronic acid (HA) and other relevant cartilage extracellular matrix (ECM) components. This work provides a novel integrative insight into the molecular alterations of osteoarthritic MSCs and potential therapeutic targets for OA drug development through the enhancement of chondrogenesis.

Systemic infection and proliferation of intracellular pathogens require the biogenesis of a growth-stimulating compartment. The gastrointestinal pathogen Salmonella enterica commonly forms highly dynamic and extensive tubular membrane compartments built from Salmonella-modified membranes (SMMs) in diverse host cells. Although the general mechanism involved in the formation of replication-permissive compartments of S. enterica is well researched, much less is known regarding specific adaptations to different host cell types. Using an affinity-based proteome approach, we explored the composition of SMMs in murine macrophages. The systematic characterization provides a broader landscape of host players to the maturation of Salmonella-containing compartments and reveals core host elements targeted by Salmonella in macrophages as well as epithelial cells. However, we also identified subtle host specific adaptations. Some of these observations, such as the differential involvement of the COPII system, Rab GTPases 2A, 8B, 11 and ER transport proteins Sec61 and Sec22B may explain cell line-dependent variations in the pathophysiology of Salmonella infections. In summary, our system-wide approach demonstrates a hitherto underappreciated impact of the host cell type in the formation of intracellular compartments by Salmonella.

Acute myeloid leukemia (AML) is a clonal disorder arising from hematopoietic myeloid progenitors. Aberrantly activated tyrosine kinases (TK) are involved in leukemogenesis and are associated with poor treatment outcome. Kinase inhibitor (KI) treatment has shown promise in improving patient outcome in AML. However, inhibitor selection for patients is suboptimal.

In a preclinical effort to address KI selection, we analyzed a panel of 16 AML cell lines using phosphotyrosine (pY) enrichment-based, label-free phosphoproteomics. The Integrative Inferred Kinase Activity (INKA) algorithm was used to identify hyperphosphorylated, active kinases as candidates for KI treatment, and efficacy of selected KIs was tested.

Heterogeneous signaling was observed with between 241 and 2764 phosphopeptides detected per cell line. Of 4853 identified phosphopeptides with 4229 phosphosites, 4459 phosphopeptides (4430 pY) were linked to 3605 class I sites (3525 pY). INKA analysis in single cell lines successfully pinpointed driver kinases (PDGFRA, JAK2, KIT and FLT3) corresponding with activating mutations present in these cell lines. Furthermore, potential receptor tyrosine kinase (RTK) drivers, undetected by standard molecular analyses, were identified in four cell lines (FGFR1 in KG-1 and KG-1a, PDGFRA in Kasumi-3, and FLT3 in MM6). These cell lines proved highly sensitive to specific KIs. Six AML cell lines without a clear RTK driver showed evidence of MAPK1/3 activation, indicative of the presence of activating upstream RAS mutations. Importantly, FLT3 phosphorylation was demonstrated in two clinical AML samples with a FLT3 internal tandem duplication (ITD) mutation.

Our data show the potential of pY-phosphoproteomics and INKA analysis to provide insight in AML TK signaling and identify hyperactive kinases as potential targets for treatment in AML cell lines. These results warrant future investigation of clinical samples to further our understanding of TK phosphorylation in relation to clinical response in the individual patient.

The redox-based modifications of cysteine residues in proteins regulate their function in many biological processes. The gas molecule H₂S has been shown to persulfidate redox sensitive cysteine residues resulting in an H₂S-modified proteome known as the sulfhydrome. Tandem Mass Tags (TMT) multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent in detecting cysteine modifications. Here we developed a TMT-based proteomics approach for selectively trapping and tagging cysteine persulfides in the cellular proteomes. We revealed the natural protein sulfhydrome of two human cell lines, and identified insulin as a novel substrate in pancreatic beta cells. Moreover, we showed that under oxidative stress conditions, increased H₂S can target enzymes involved in energy metabolism by switching specific cysteine modifications to persulfides. Specifically, we discovered a Redox Thiol Switch, from protein S-glutathioinylation to S-persulfidation (RTS^GS). We propose that the RTS^GS from S-glutathioinylation to S-persulfidation is a potential mechanism to fine tune cellular energy metabolism in response to different levels of oxidative stress.

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100x) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

The respiratory epithelium comprises polarized cells at the interface between the environment and airway tissues. Polarized apical and basolateral protein secretions are a feature of airway epithelium homeostasis. Human respiratory syncytial virus (hRSV) is a major human pathogen that primarily targets the respiratory epithelium. However, the consequences of hRSV infection on epithelium secretome polarity and content remain poorly understood. To investigate the hRSV-associated apical and basolateral secretomes, a proteomics approach was combined with an ex vivo pediatric human airway epithelial (HAE) model of hRSV infection (data are available via ProteomeXchange and can be accessed at https://www.ebi.ac.uk/pride/ with identifier PXD013661). Following infection, a skewing of apical/basolateral abundance ratios was identified for several individual proteins. Novel modulators of neutrophil and lymphocyte activation (CXCL6, CSF3, SECTM1 or CXCL16), and antiviral proteins (BST2 or CEACAM1) were detected in infected, but not in uninfected cultures. Importantly, CXCL6, CXCL16, CSF3 were also detected in nasopharyngeal aspirates (NPA) from hRSV-infected infants but not healthy controls. Furthermore, the antiviral activity of CEACAM1 against RSV was confirmed in vitro using BEAS-2B cells. hRSV infection disrupted the polarity of the pediatric respiratory epithelial secretome and was associated with immune modulating proteins (CXCL6, CXCL16, CSF3) never linked with this virus before. In addition, the antiviral activity of CEACAM1 against hRSV had also never been previously characterized. This study, therefore, provides novel insights into RSV pathogenesis and endogenous antiviral responses in pediatric airway epithelium.

Autoimmune thyroid diseases (AITD) are the most common group of autoimmune diseases, associated with lymphocyte infiltration and the production of thyroid autoantibodies, like thyroid peroxidase antibodies (TPOAb), in the thyroid gland. Immunoglobulins and cell-surface receptors are glycoproteins with distinctive glycosylation patterns that play a structural role in maintaining and modulating their functions. We investigated associations of total circulating IgG and peripheral blood mononuclear cells glycosylation with AITD and the influence of genetic background in a case-control study with several independent cohorts and over 3,000 individuals in total. The study revealed an inverse association of IgG core fucosylation with TPOAb and AITD, as well as decreased peripheral blood mononuclear cells antennary α1,2 fucosylation in AITD, but no shared genetic variance between AITD and glycosylation. These data suggest that the decreased level of IgG core fucosylation is a risk factor for AITD that promotes antibody-dependent cell-mediated cytotoxicity previously associated with TPOAb levels.

Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.

Neoantimycins are anticancer compounds of 15-membered ring antimycin-type depsipeptides. They are biosynthesized by a hybrid multimodular protein complex of nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS), typically from the starting precursor 3-formamidosalicylate. Examining fermentation extracts of Streptomyces conglobatus, here we discovered four new neoantimycin analogs, unantimycins B–E, in which 3-formamidosalicylates are replaced by an unusual 3-hydroxybenzoate (3-HBA) moiety. Unantimycins B–E exhibited levels of anticancer activities similar to those of the chemotherapeutic drug cisplatin in human lung cancer, colorectal cancer, and melanoma cells. Notably, they mostly displayed no significant toxicity toward noncancerous cells, unlike the serious toxicities generally reported for antimycin-type natural products. Using site-directed mutagenesis and heterologous expression, we found that unantimycin productions are correlated with the activity of a chorismatase homolog, the nat-hyg5 gene, from a type I PKS gene cluster. Biochemical analysis confirmed that the catalytic activity of Nat-hyg5 generates 3-HBA from chorismate. Finally, we achieved selective production of unantimycins B and C by engineering a chassis host. On the basis of these findings, we propose that unantimycin biosynthesis is directed by the neoantimycin-producing NRPS–PKS complex and initiated with the starter unit of 3-HBA. The elucidation of the biosynthetic unantimycin pathway reported here paves the way to improve the yield of these compounds for evaluation in oncotherapeutic applications.

Previous studies have shown that sphingosine kinase interacting protein (SKIP) inhibits sphingosine kinase (SK) function in fibroblasts. SK phosphorylates sphingosine producing the potent signaling molecule sphingosine-1-phosphate (S1P). SKIP gene (SPHKAP) expression is silenced by hypermethylation of its promoter in acute myeloid leukemia (AML). However, why SKIP activity is silenced in primary AML cells is unclear. Here, we investigated the consequences of SKIP down-regulation in AML primary cells and the effects of SKIP re-expression in leukemic cell lines. Using targeted ultra-HPLC-tandem MS (UPLC-MS/MS), we measured sphingolipids (including S1P and ceramides) in AML and control cells. Primary AML cells had significantly lower SK activity and intracellular S1P concentrations than control cells, and SKIP-transfected leukemia cell lines exhibited increased SK activity. These findings show that SKIP re-expression enhances SK activity in leukemia cells. Furthermore, other bioactive sphingolipids such as ceramide were also down-regulated in primary AML cells. Of note, SKIP re-expression in leukemia cells increased ceramide levels 2-fold, inactivated the key signaling protein extracellular signal-regulated kinase, and increased apoptosis following serum deprivation or chemotherapy. These results indicate that SKIP down-regulation in AML reduces SK activity and ceramide levels, an effect that ultimately inhibits apoptosis in leukemia cells. The findings of our study contrast with previous results indicating that SKIP inhibits SK function in fibroblasts and therefore challenge the notion that SKIP always inhibits SK activity.

Coenzyme Q (Qn) is a vital lipid component of the electron transport chain that functions in cellular energy metabolism and as a membrane antioxidant. In the yeast Saccharomyces cerevisiae, coq1–coq9 deletion mutants are respiratory-incompetent, sensitive to lipid peroxidation stress, and unable to synthesize Q6. The yeast coq10 deletion mutant is also respiratory-deficient and sensitive to lipid peroxidation, yet it continues to produce Q6 at an impaired rate. Thus, Coq10 is required for the function of Q6 in respiration and as an antioxidant and is believed to chaperone Q6 from its site of synthesis to the respiratory complexes. In several fungi, Coq10 is encoded as a fusion polypeptide with Coq11, a recently identified protein of unknown function required for efficient Q6 biosynthesis. Because “fused” proteins are often involved in similar biochemical pathways, here we examined the putative functional relationship between Coq10 and Coq11 in yeast. We used plate growth and Seahorse assays and LC-MS/MS analysis to show that COQ11 deletion rescues respiratory deficiency, sensitivity to lipid peroxidation, and decreased Q6 biosynthesis of the coq10Δ mutant. Additionally, immunoblotting indicated that yeast coq11Δ mutants accumulate increased amounts of certain Coq polypeptides and display a stabilized CoQ synthome. These effects suggest that Coq11 modulates Q6 biosynthesis and that its absence increases mitochondrial Q6 content in the coq10Δcoq11Δ double mutant. This augmented mitochondrial Q6 content counteracts the respiratory deficiency and lipid peroxidation sensitivity phenotypes of the coq10Δ mutant. This study further clarifies the intricate connection between Q6 biosynthesis, trafficking, and function in mitochondrial metabolism.

Heat shock factor 1 (HSF1) regulates cellular adaptation to challenges such as heat shock and oxidative and proteotoxic stresses. We have recently reported a previously unappreciated role for HSF1 in the regulation of energy metabolism in fat tissues; however, whether HSF1 is differentially expressed in adipose depots and how its levels are regulated in fat tissues remain unclear. Here, we show that HSF1 levels are higher in brown and subcutaneous fat tissues than in those in the visceral depot and that HSF1 is more abundant in differentiated, thermogenic adipocytes. Gene expression experiments indicated that HSF1 is transcriptionally regulated in fat by agents that modulate cAMP levels, by cold exposure, and by pharmacological stimulation of β-adrenergic signaling. An in silico promoter analysis helped identify a putative response element for activating transcription factor 3 (ATF3) at −258 to −250 base pairs from the HSF1 transcriptional start site, and electrophoretic mobility shift and ChIP assays confirmed ATF3 binding to this sequence. Furthermore, functional assays disclosed that ATF3 is necessary and sufficient for HSF1 regulation. Detailed gene expression analysis revealed that ATF3 is one of the most highly induced ATFs in thermogenic tissues of mice exposed to cold temperatures or treated with the β-adrenergic receptor agonist CL316,243 and that its expression is induced by modulators of cAMP levels in isolated adipocytes. To the best of our knowledge, our results show for the first time that HSF1 is transcriptionally controlled by ATF3 in response to classic stimuli that promote heat generation in thermogenic tissues.

Phosphoglycerate kinase 1 (PGK1) plays important roles in glycolysis, yet its forward reaction kinetics are unknown, and its role especially in regulating cancer cell glycolysis is unclear. Here, we developed an enzyme assay to measure the kinetic parameters of the PGK1-catalyzed forward reaction. The Km values for 1,3-bisphosphoglyceric acid (1,3-BPG, the forward reaction substrate) were 4.36 μm (yeast PGK1) and 6.86 μm (human PKG1). The Km values for 3-phosphoglycerate (3-PG, the reverse reaction substrate and a serine precursor) were 146 μm (yeast PGK1) and 186 μm (human PGK1). The Vmax of the forward reaction was about 3.5- and 5.8-fold higher than that of the reverse reaction for the human and yeast enzymes, respectively. Consistently, the intracellular steady-state concentrations of 3-PG were between 180 and 550 μm in cancer cells, providing a basis for glycolysis to shuttle 3-PG to the serine synthesis pathway. Using siRNA-mediated PGK1-specific knockdown in five cancer cell lines derived from different tissues, along with titration of PGK1 in a cell-free glycolysis system, we found that the perturbation of PGK1 had no effect or only marginal effects on the glucose consumption and lactate generation. The PGK1 knockdown increased the concentrations of fructose 1,6-bisphosphate, dihydroxyacetone phosphate, glyceraldehyde 3-phosphate, and 1,3-BPG in nearly equal proportions, controlled by the kinetic and thermodynamic states of glycolysis. We conclude that perturbation of PGK1 in cancer cells insignificantly affects the conversion of glucose to lactate in glycolysis.

Triple-negative breast cancer (TNBC) is characterized by its aggressive biology, early metastatic spread, and poor survival outcomes. TNBC lacks expression of the targetable receptors found in other breast cancer subtypes, mandating use of cytotoxic chemotherapy. However, resistance to chemotherapy is a significant problem, encountered in about two-thirds of TNBC patients, and new strategies are needed to mitigate resistance. In this issue of the Journal of Biological Chemistry, Geck et al. report that TNBC cells are highly sensitive to inhibition of the de novo polyamine synthesis pathway and that inhibition of this pathway sensitizes cells to TNBC-relevant chemotherapy, uncovering new opportunities for addressing chemoresistance.

Treatment of patients with triple-negative breast cancer (TNBC) is limited by a lack of effective molecular therapies targeting this disease. Recent studies have identified metabolic alterations in cancer cells that can be targeted to improve responses to standard-of-care chemotherapy regimens. Using MDA-MB-468 and SUM-159PT TNBC cells, along with LC-MS/MS and HPLC metabolomics profiling, we found here that exposure of TNBC cells to the cytotoxic chemotherapy drugs cisplatin and doxorubicin alter arginine and polyamine metabolites. This alteration was because of a reduction in the levels and activity of a rate-limiting polyamine biosynthetic enzyme, ornithine decarboxylase (ODC). Using gene silencing and inhibitor treatments, we determined that the reduction in ODC was mediated by its negative regulator antizyme, targeting ODC to the proteasome for degradation. Treatment with the ODC inhibitor difluoromethylornithine (DFMO) sensitized TNBC cells to chemotherapy, but this was not observed in receptor-positive breast cancer cells. Moreover, TNBC cell lines had greater sensitivity to single-agent DFMO, and ODC levels were elevated in TNBC patient samples. The alterations in polyamine metabolism in response to chemotherapy, as well as DFMO-induced preferential sensitization of TNBC cells to chemotherapy, reported here suggest that ODC may be a targetable metabolic vulnerability in TNBC.