ProteomicsDB

Development of hetero-triaryls as a new chemotype for subtype-selective and potent Sirt5 inhibition

In contrast to other sirtuins (NAD⁺-dependent class III lysine deacylases), inhibition of Sirt5 is poorly investigated, yet. Our present work is based on the recently identified Sirt5 inhibitor balsalazide, an approved drug with negligible bioavailability after oral administration. After gaining first insights into its structure-activity relationship in previous work, we were able to now develop heteroaryl-triaryls as a novel chemotype of drug-like, potent and subtype-selective Sirt5 inhibitors. The unfavourable azo group of the lead structure was modified in a systematic and comprehensive manner, leading us to a few open-chained and, most importantly, five-membered heteroaromatic substitutes (isoxazole CG_209, triazole CG_220, pyrazole CG_232) with very encouraging in vitro activities (IC₅₀ on Sirt5 in the low micromolar range, <10 μM). These advanced inhibitors were free of cytotoxicity and showed favourable pharmacokinetic properties, as confirmed by permeability into mitochondria using live cell imaging experiments. Furthermore, results from calculations of the relative free binding affinities of the analogues compared to balsalazide as reference compound agreed well with the trends for inhibitory activities obtained in the in vitro experiments. Therefore, this method can be used to predict the affinity of closely related future potential Sirt5 inhibitors. Encouraged by our findings, we employed chemoproteomic selectivity profiling to confirm Sirt5 as main target of balsalazide and one of its improved analogues. An immobilised balsalazide-analogue specifically pulled down Sirt5 from whole cell lysates and competition experiments identified glutaryl-CoA dehydrogenase (GCDH) and nucleotide diphosphate kinase (NME4) as potential off-targets, once again confirming the selectivity of the novel balsalazide-derived Sirt5 inhibitors. In summary, a combination of targeted chemical synthesis, biological work, and computational studies led to a new generation of tailored Sirt5 inhibitors, which represent valuable chemical tools for the investigation of the physiological role of Sirt5, but could also serve as advanced lead structures for drug candidates for systemic use.

Immune Cell Networks Uncover Candidate Biomarkers of Melanoma Immunotherapy Response

The therapeutic activation of antitumour immunity by immune checkpoint inhibitors (ICIs) is a significant advance in cancer medicine, not least due to the prospect of long-term remission. However, many patients are unresponsive to ICI therapy and may experience serious side effects; companion biomarkers are urgently needed to help inform ICI prescribing decisions. We present the IMMUNETS networks of gene coregulation in five key immune cell types and their application to interrogate control of nivolumab response in advanced melanoma cohorts. The results evidence a role for each of the IMMUNETS cell types in ICI response and in driving tumour clearance with independent cohorts from TCGA. As expected, ‘immune hot’ status, including T cell proliferation, correlates with response to first-line ICI therapy. Genes regulated in NK, dendritic, and B cells are the most prominent discriminators of nivolumab response in patients that had previously progressed on another ICI. Multivariate analysis controlling for tumour stage and age highlights CIITA and IKZF3 as candidate prognostic biomarkers. IMMUNETS provide a resource for network biology, enabling context-specific analysis of immune components in orthogonal datasets. Overall, our results illuminate the relationship between the tumour microenvironment and clinical trajectories, with potential implications for precision medicine.

Disrupting the HDAC6-ubiquitin interaction impairs infection by influenza and Zika virus and cellular stress pathways

The deacetylase HDAC6 has tandem catalytic domains and a zinc finger domain (ZnF) binding ubiquitin (Ub). While the catalytic domain has an antiviral effect, the ZnF facilitates influenza A virus (IAV) infection and cellular stress responses. By recruiting Ub via the ZnF, HDAC6 promotes the formation of aggresomes and stress granules (SGs), dynamic structures associated with pathologies such as neurodegeneration. IAV subverts the aggresome/HDAC6 pathway to facilitate capsid uncoating during early infection. To target this pathway, we generate designed ankyrin repeat proteins (DARPins) binding the ZnF; one of these prevents interaction with Ub in vitro and in cells. Crystallographic analysis shows that it blocks the ZnF pocket where Ub engages. Conditional expression of this DARPin reversibly impairs infection by IAV and Zika virus; moreover, SGs and aggresomes are downregulated. These results validate the HDAC6 ZnF as an attractive target for drug discovery.

•

A small synthetic protein (DARPin) blocks interaction between HDAC6 and ubiquitin

•

This DARPin impairs infection by influenza and Zika virus at the uncoating step

•

Both viruses contain ubiquitin associated with their capsid

•

The DARPin also impacts the formation of aggresomes and stress granules

PA1 participates in the maintenance of blood-testis barrier integrity via cooperation with JUN in the Sertoli cells of mice

Background

The blood–testis barrier (BTB) is essential to the microenvironment of spermatogenesis, and Sertoli cells provide the cellular basis for BTB construction. Numerous nuclear transcription factors have been identified to be vital for the proper functioning of Sertoli cells. PA1 has been reported to play important roles during diverse biological processes, yet its potential function in male reproduction is still unknown.

Results

Here, we show that PA1 was highly expressed in human and mouse testis and predominantly localized in the nuclei of Sertoli cells. Sertoli cell-specific Pa1 knockout resulted in an azoospermia-like phenotype in mice. The knockout of this gene led to multiple defects in spermatogenesis, such as the disorganization of the cytoskeleton during basal and apical ectoplasmic specialization and the disruption of the BTB. Further transcriptomic analysis, together with Cut-Tag results of PA1 in Sertoli cells, revealed that PA1 could affect the expression of a subset of genes that are essential for the normal function of Sertoli cells, including those genes associated with actin organization and cellular junctions such as Connexin43 (Cx43). We further demonstrated that the expression of Cx43 depended on the interaction between JUN, one of the AP-1 complex transcription factors, and PA1.

Conclusion

Overall, our findings reveal that PA1 is essential for the maintenance of BTB integrity in Sertoli cells and regulates BTB construction-related gene expression via transcription factors. Thus, this newly discovered mechanism in Sertoli cells provides a potential diagnostic or even therapeutic target for some individuals with azoospermia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00773-y.

Integrating protein copy numbers with interaction networks to quantify stoichiometry in clathrin-mediated endocytosis

Proteins that drive processes like clathrin-mediated endocytosis (CME) are expressed at copy numbers within a cell and across cell types varying from hundreds (e.g. auxilin) to millions (e.g. clathrin). These variations contain important information about function, but without integration with the interaction network, they cannot capture how supply and demand for each protein depends on binding to shared and distinct partners. Here we construct the interface-resolved network of 82 proteins involved in CME and establish a metric, a stoichiometric balance ratio (SBR), that quantifies whether each protein in the network has an abundance that is sub- or super-stoichiometric dependent on the global competition for binding. We find that highly abundant proteins (like clathrin) are super-stoichiometric, but that not all super-stoichiometric proteins are highly abundant, across three cell populations (HeLa, fibroblast, and neuronal synaptosomes). Most strikingly, within all cells there is significant competition to bind shared sites on clathrin and the central AP-2 adaptor by other adaptor proteins, resulting in most being in excess supply. Our network and systematic analysis, including response to perturbations of network components, show how competition for shared binding sites results in functionally similar proteins having widely varying stoichiometries, due to variations in both abundance and their unique network of binding partners.

Comparing Urinary Glycoproteins among Three Urogenital Cancers and Identifying Prostate Cancer-Specific Glycoproteins

Prostate cancer, bladder cancer, and renal cancers are major urogenital cancers. Of which, prostate cancer is the most commonly diagnosed and second leading cause of cancer death for men in the United States. For urogenital cancers, urine is considered as proximate body fluid to the tumor site for developing non-invasiveness tests. However, the specific molecular signatures from different urogenital cancers are needed to relate changes in urine to various cancer detections. Herein, we utilized a previously published C4-Tip and C18/MAX-Tip workflow for enrichment of glycopeptides from urine samples and evaluated urinary glycopeptides for its cancer specificity. We analyzed 66 urine samples from bladder cancer (n = 27), prostate cancer (n = 4), clear cell renal cell carcinoma (ccRCC, n = 3), and benign plastic hyperplasia (BPH, n = 32) and then compared them with a previous publication that reported glycopeptides associated with aggressive prostate cancer (Gleason score ≥ 8). We further demonstrated the cancer specificity of the glycopeptides associated with aggressive prostate cancer. In this study, a total of 33 glycopeptides were identified to be specifically differentially expressed in prostate cancer compared to other urogenital cancer types as well as BPH urines. By cross-comparison with our previous urinary glycoproteomic dataset for aggressive prostate cancer, we reported a total of four glycopeptides from glycoproteins DSC2, MGAM, PIK3IP1, and CD55, commonly identified to be prostate cancer-specific. Together, these results deepen our understanding of the urinary glycoproteins associated with urogenital cancer types and expand our knowledge of the cancer specificity of urinary glycoproteins among urogenital cancer progression.

Beta-cell specific Insr deletion promotes insulin hypersecretion and improves glucose tolerance prior to global insulin resistance

Insulin receptor (Insr) protein is present at higher levels in pancreatic β-cells than in most other tissues, but the consequences of β-cell insulin resistance remain enigmatic. Here, we use an Ins1cre knock-in allele to delete Insr specifically in β-cells of both female and male mice. We compare experimental mice to Ins1cre-containing littermate controls at multiple ages and on multiple diets. RNA-seq of purified recombined β-cells reveals transcriptomic consequences of Insr loss, which differ between female and male mice. Action potential and calcium oscillation frequencies are increased in Insr knockout β-cells from female, but not male mice, whereas only male βInsrKO islets have reduced ATP-coupled oxygen consumption rate and reduced expression of genes involved in ATP synthesis. Female βInsrKO and βInsrHET mice exhibit elevated insulin release in ex vivo perifusion experiments, during hyperglycemic clamps, and following i.p. glucose challenge. Deletion of Insr does not alter β-cell area up to 9 months of age, nor does it impair hyperglycemia-induced proliferation. Based on our data, we adapt a mathematical model to include β-cell insulin resistance, which predicts that β-cell Insr knockout improves glucose tolerance depending on the degree of whole-body insulin resistance. Indeed, glucose tolerance is significantly improved in female βInsrKO and βInsrHET mice compared to controls at 9, 21 and 39 weeks, and also in insulin-sensitive 4-week old males. We observe no improved glucose tolerance in older male mice or in high fat diet-fed mice, corroborating the prediction that global insulin resistance obscures the effects of β-cell specific insulin resistance. The propensity for hyperinsulinemia is associated with mildly reduced fasting glucose and increased body weight. We further validate our main in vivo findings using an Ins1-CreERT transgenic line and find that male mice have improved glucose tolerance 4 weeks after tamoxifen-mediated Insr deletion. Collectively, our data show that β-cell insulin resistance in the form of reduced β-cell Insr contributes to hyperinsulinemia in the context of glucose stimulation, thereby improving glucose homeostasis in otherwise insulin sensitive sex, dietary and age contexts.

Genome-wide CRISPR-Cas9 screen identifies rationally designed combination therapies for CRLF2-rearranged Ph-like ALL

Acute lymphoblastic leukemia (ALL) harboring the IgH-CRLF2 rearrangement (IgH-CRLF2-r) exhibits poor clinical outcomes and is the most common subtype of Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL). While multiple chemotherapeutic regimens, including ruxolitinib monotherapy and/or its combination with chemotherapy, are being tested, their efficacy is reportedly limited. To identify molecules/pathways relevant for IgH-CRLF2-r ALL pathogenesis, we performed genome-wide CRISPR-Cas9 dropout screens in the presence or absence of ruxolitinib using 2 IgH-CRLF2-r ALL lines that differ in RAS mutational status. To do so, we employed a baboon envelope pseudotyped lentiviral vector system, which enabled, for the first time, highly efficient transduction of human B cells. While single-guide RNAs (sgRNAs) targeting CRLF2, IL7RA, or JAK1/2 significantly affected cell fitness in both lines, those targeting STAT5A, STAT5B, or STAT3 did not, suggesting that STAT signaling is largely dispensable for IgH-CRLF2-r ALL cell survival. We show that regulators of RAS signaling are critical for cell fitness and ruxolitinib sensitivity and that CRKL depletion enhances ruxolitinib sensitivity in RAS wild-type (WT) cells. Gilteritinib, a pan-tyrosine kinase inhibitor that blocks CRKL phosphorylation, effectively killed RAS WT IgH-CRLF2-r ALL cells in vitro and in vivo, either alone or combined with ruxolitinib. We further show that combining gilteritinib with trametinib, a MEK1/2 inhibitor, is an effective means to target IgH-CRLF2-r ALL cells regardless of RAS mutational status. Our study delineates molecules/pathways relevant for CRLF2-r ALL pathogenesis and could suggest rationally designed combination therapies appropriate for disease subtypes.

Systems neuroimmunology: a review of multiomics methodologies to characterize neuroimmunological interactions in spinal and cranial diseases

Neuroimmunology plays a critical role in our understanding of the pathophysiological processes that underlie a variety of diseases treated by neurosurgeons, including degenerative disc disease (DDD), glioblastoma (GBM), aneurysmal subarachnoid hemorrhage (aSAH), and others. Compared with traditional methods in neuroimmunology, which study one pathway or gene at a time, emerging multiomics methodologies allow for holistic interrogation of multiple immune-signaling pathways to test hypotheses and the effects of therapeutics at a systems level. In this review, the authors summarize key concepts for gathering and analyzing multiomics data so that neurosurgeons can contribute to the emerging field of systems neuroimmunology. Additionally, they describe 3 use cases, based on original research published by their group and others, that utilize transcriptomic, metabolomic, and proteomic analyses to study immune-signaling pathways in DDD, aSAH, and GBM. Through these use cases, techniques for performing machine learning and network-based analyses to generate new clinical insights from multiomics data are shared. The authors hope that neurosurgeons might use this review as a summary of common tools and principles in systems immunology to better engage in creating the immunotherapies of tomorrow.

Origin of diverse phosphorylation patterns in the ERBB system

Intercellular signals induce various cellular responses, including growth, proliferation, and differentiation, via the dynamic processes of signal transduction pathways. For cell fate decisions, ligand-binding induces the phosphorylation of ERBB receptors, which in turn activate downstream molecules. The ERBB family includes four subtypes, which diverged through two gene duplications from a common ancestor. Differences in the expression patterns of the subtypes have been reported between different organs in the human body. However, how these different expression properties influence the diverse phosphorylation levels of ERBB proteins is not well understood. Here we study the origin of the phosphorylation responses by experimental and mathematical analyses. The experimental measurements clarified that the phosphorylation levels heavily depend on the ERBB expression profiles. We developed a mathematical model consisting of the four subtypes as monomers, homodimers, and heterodimers and estimated the rate constants governing the phosphorylation responses from the experimental data. To understand the origin of the diversity, we analyzed the effects of the expression levels and reaction rates of the ERBB subtypes on the diversity. The difference in phosphorylation rates between ERBB subtypes showed a much greater contribution to the diversity than did the dimerization rates. This result implies that divergent evolution in phosphorylation reactions rather than in dimerization reactions after whole genome duplications was essential for increasing the diversity of the phosphorylation responses.

ProteomicsDB: toward a FAIR open-source resource for life-science research

ProteomicsDB (https://www.ProteomicsDB.org) is a multi-omics and multi-organism resource for life science research. In this update, we present our efforts to continuously develop and expand ProteomicsDB. The major focus over the last two years was improving the findability, accessibility, interoperability and reusability (FAIR) of the data as well as its implementation. For this purpose, we release a new application programming interface (API) that provides systematic access to essentially all data in ProteomicsDB. Second, we release a new open-source user interface (UI) and show the advantages the scientific community gains from such software. With the new interface, two new visualizations of protein primary, secondary and tertiary structure as well an updated spectrum viewer were added. Furthermore, we integrated ProteomicsDB with our deep-neural-network Prosit that can predict the fragmentation characteristics and retention time of peptides. The result is an automatic processing pipeline that can be used to reevaluate database search engine results stored in ProteomicsDB. In addition, we extended the data content with experiments investigating different human biology as well as a newly supported organism.

Quantitative Detection of Protein Splice Variants by Selected Reaction Monitoring (SRM) Mass Spectrometry

Molecular diversification of the cellular proteome through alternative splicing has emerged as an important biological principle. However, the lack of tools to specifically detect and quantify proteoforms (Smith et al., Nat Methods 10:186-187, 2013) is a major impediment to functional studies. Recently, biological mass spectrometry (MS) has undergone impressive advances (Mann, Nat Rev Mol Cell Biol 17:678, 2016), including the generation of a highly diverse set of biological applications (Aebersold and Mann, Nature 537:347-355, 2016), and has demonstrated to be an essential tool to address many biological questions (Savitski et al., Science 346:1255784, 2014; Rinner et al., Nat Methods 5:315-318, 2008). In particular, targeted LC-MS, with its high selectivity and specificity, is ideally suited for the precise and sensitive quantification of specific proteins and their proteoforms (Picotti and Aebersold, Nat Methods 9:555-566, 2012). We describe in detail the application of this workflow applied to dissect the molecular diversity of the synaptic adhesion proteins and their splicing-derived proteoforms (Schreiner et al., Elife 4:e07794, 2015).

Arginase 2 and Polyamines in Human Pancreatic Beta Cells: Possible Role in the Pathogenesis of Type 2 Diabetes

Arginase 2 (ARG2) is a manganese metalloenzyme involved in several tissue specific processes, from physiology to pathophysiology. It is variably expressed in extra-hepatic tissues and is located in the mitochondria. In human pancreatic beta cells, ARG2 is downregulated in type 2 diabetes. The enzyme regulates the synthesis of polyamines, that are involved in pancreas development and regulation of beta cell function. Here, we discuss several features of ARG2 and polyamines, which can be relevant to the pathophysiology of type 2 diabetes.

An Introduction to Advanced Targeted Acquisition Methods

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

Specific Deletion of the FHA Domain Containing SLMAP3 Isoform in Postnatal Myocardium Has No Impact on Structure or Function

Sarcolemmal membrane-associated proteins (SLMAPs) belong to the superfamily of tail-anchored membrane proteins known to regulate diverse biological processes, including protein trafficking and signal transduction. Mutations in SLMAP have been linked to Brugada and defective sodium channel Nav1.5 shuttling. The SLMAP gene is alternatively spliced to generate numerous isoforms, broadly defined as SLMAP1 (~35 kDa), SLMAP2 (~45 kDa) and SLMAP3 (~80–95 kDa), which are highly expressed in the myocardium. The SLMAP3 isoform exhibits ubiquitous expression carrying an FHA domain and is believed to negatively regulate Hippo signaling to dictate cell growth/death and differentiation. Using the αMHC-MerCreMer-flox system to target the SLMAP gene, we specifically deleted the SLMAP3 isoform in postnatal mouse hearts without any changes in the expression of SLMAP1/SLMAP2 isoforms. The in vivo analysis of mice with SLMAP3 cardiac deficiency revealed no significant changes to heart structure or function in young or aged mice without or with isoproterenol-induced stress. SLMAP3-deficient hearts revealed no obvious differences in cardiac size, function or hypertrophic response. Further, the molecular analysis indicated that SLMAP3 loss had a minor impact on sodium channel (Nav1.5) expression without affecting cardiac electrophysiology in postnatal myocardium. Surprisingly, the loss of SLMAP3 did not impact Hippo signaling in postnatal myocardium. We conclude that the FHA domain-containing SLMAP3 isoform has no impact on Hippo signaling or sodium channels in postnatal myocardium, which is able to function and respond normally to stress in its absence. Whether SLMAP1/SMAP2 isoforms can compensate for the loss of SLMAP3 in the affairs of the postnatal heart remains to be determined.

Structure, Function, and Pharmacology of Glutamate Receptor Ion Channels

Many physiologic effects of l-glutamate, the major excitatory neurotransmitter in the mammalian central nervous system, are mediated via signaling by ionotropic glutamate receptors (iGluRs). These ligand-gated ion channels are critical to brain function and are centrally implicated in numerous psychiatric and neurologic disorders. There are different classes of iGluRs with a variety of receptor subtypes in each class that play distinct roles in neuronal functions. The diversity in iGluR subtypes, with their unique functional properties and physiologic roles, has motivated a large number of studies. Our understanding of receptor subtypes has advanced considerably since the first iGluR subunit gene was cloned in 1989, and the research focus has expanded to encompass facets of biology that have been recently discovered and to exploit experimental paradigms made possible by technological advances. Here, we review insights from more than 3 decades of iGluR studies with an emphasis on the progress that has occurred in the past decade. We cover structure, function, pharmacology, roles in neurophysiology, and therapeutic implications for all classes of receptors assembled from the subunits encoded by the 18 ionotropic glutamate receptor genes. SIGNIFICANCE STATEMENT: Glutamate receptors play important roles in virtually all aspects of brain function and are either involved in mediating some clinical features of neurological disease or represent a therapeutic target for treatment. Therefore, understanding the structure, function, and pharmacology of this class of receptors will advance our understanding of many aspects of brain function at molecular, cellular, and system levels and provide new opportunities to treat patients.

Neuronal pentraxins as biomarkers of synaptic activity: from physiological functions to pathological changes in neurodegeneration

The diagnosis of neurodegenerative disorders is often challenging due to the lack of diagnostic tools, comorbidities and shared pathological manifestations. Synaptic dysfunction is an early pathological event in many neurodegenerative disorders, but the underpinning mechanisms are still poorly characterised. Reliable quantification of synaptic damage is crucial to understand the pathophysiology of neurodegeneration, to track disease status and to obtain prognostic information. Neuronal pentraxins (NPTXs) are extracellular scaffolding proteins emerging as potential biomarkers of synaptic dysfunction in neurodegeneration. They are a family of proteins involved in homeostatic synaptic plasticity by recruiting post-synaptic receptors into synapses. Recent research investigates the dynamic changes of NPTXs in the cerebrospinal fluid (CSF) as an expression of synaptic damage, possibly related to cognitive impairment. In this review, we summarise the available data on NPTXs structure and expression patterns as well as on their contribution in synaptic function and plasticity and other less well-characterised roles. Moreover, we propose a mechanism for their involvement in synaptic damage and neurodegeneration and assess their potential as CSF biomarkers for neurodegenerative diseases.

The macrophage-derived protein PTMA induces filamentation of the human fungal pathogen Candida albicans

Evasion of killing by immune cells is crucial for fungal survival in the host. For the human fungal pathogen Candida albicans, internalization by macrophages induces a transition from yeast to filaments that promotes macrophage death and fungal escape. Nutrient deprivation, alkaline pH, and oxidative stress have been implicated as triggers of intraphagosomal filamentation; however, the impact of other host-derived factors remained unknown. Here, we show that lysates prepared from macrophage-like cell lines and primary macrophages robustly induce C. albicans filamentation. Enzymatic treatment of lysate implicates a phosphorylated protein, and bioactivity-guided fractionation coupled to mass spectrometry identifies the immunomodulatory phosphoprotein PTMA as a candidate trigger of C. albicans filamentation. Immunoneutralization of PTMA within lysate abolishes its activity, strongly supporting PTMA as a filament-inducing component of macrophage lysate. Adding to the known repertoire of physical factors, this work implicates a host protein in the induction of C. albicans filamentation within immune cells.

The human fungal pathogen Candida albicans filaments within host macrophages, enabling its escape. Case et al. demonstrate that lysates prepared from macrophage-like cell lines and primary macrophages induce C. albicans filamentation and implicate the immunomodulatory protein prothymosin alpha (PTMA) as a trigger of filamentation produced by host immune cells.

Precise Quantitation of PTEN by Immuno-MRM: A Tool To Resolve the Breast Cancer Biomarker Controversy

The tumor suppressor PTEN is the main negative regulator of PI3K/AKT/mTOR signaling and is commonly found downregulated in breast cancer (BC). Conflicting data from conventional immunoassays such as immunohistochemistry (IHC) has sparked controversy about PTEN's role as a prognostic and predictive biomarker in BC, which can be largely attributed to the lack of specificity, sensitivity, and interlaboratory standardization. Here, we present a fully standardized, highly sensitive, robust microflow immuno-MRM (iMRM) assay that enables precise quantitation of PTEN concentrations in cells and fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tissues, down to 0.1 fmol/10 μg of extracted protein, with high interday and intraday precision (CV 6.3%). PTEN protein levels in BC PDX samples that were determined by iMRM correlate well with semiquantitative IHC and WB data. iMRM, however, allowed the precise quantitation of PTEN-even in samples that were deemed to be PTEN negative by IHC or western blot (WB)-while requiring substantially less tumor tissue than WB. This is particularly relevant because the extent of PTEN downregulation in tumors has been shown to correlate with severity. Our standardized and robust workflow includes an 11 min microflow LC-MRM analysis on a triple-quadrupole MS and thus provides a much needed tool for the study of PTEN as a potential biomarker for BC.

CLEC12A and CD33 coexpression as a preferential target for pediatric AML combinatorial immunotherapy

Emerging immunotherapies such as chimeric antigen receptor T cells have advanced the treatment of acute lymphoblastic leukemia. In contrast, long-term control of acute myeloid leukemia (AML) cannot be achieved by single lineage-specific targeting while sparing benign hematopoiesis. In addition, heterogeneity of AML warrants combinatorial targeting, and several suitable immunotargets (HAVCR2/CD33 and HAVCR2/CLEC12A) have been identified in adult AML. However, clinical and biologic characteristics of AML differ between children and the elderly. Here, we analyzed 36 bone marrow (BM) samples of pediatric AML patients and 13 age-matched healthy donors using whole RNA sequencing of sorted CD45dim and CD34+CD38-CD45dim BM populations and flow cytometry for surface expression of putative target antigens. Pediatric AML clusters apart from healthy myeloid BM precursors in principal-component analysis. Known immunotargets of adult AML, such as IL3RA, were not overexpressed in pediatric AML compared with healthy precursors by RNA sequencing. CD33 and CLEC12A were the most upregulated immunotargets on the RNA level and showed the highest surface expression on AML detected by flow cytometry. KMT2A-mutated infant AML clusters separately by RNA sequencing and overexpresses FLT3, and hence, CD33/FLT3 cotargeting is an additional specific option for this subgroup. CLEC12A and CD33/CLEC12Adouble-positive expression was absent in CD34+CD38-CD45RA-CD90+ hematopoietic stem cells (HSCs) and nonhematopoietic tissue, while CD33 and FLT3 are expressed on HSCs. In summary, we show that expression of immunotargets in pediatric AML differs from known expression profiles in adult AML. We identify CLEC12A and CD33 as preferential generic combinatorial immunotargets in pediatric AML and CD33 and FLT3 as immunotargets specific for KMT2A-mutated infant AML.

Trips-Viz: an environment for the analysis of public and user-generated ribosome profiling data

Trips-Viz (https://trips.ucc.ie/) is an interactive platform for the analysis and visualization of ribosome profiling (Ribo-Seq) and shotgun RNA sequencing (RNA-seq) data. This includes publicly available and user generated data, hence Trips-Viz can be classified as a database and as a server. As a database it provides access to many processed Ribo-Seq and RNA-seq data aligned to reference transcriptomes which has been expanded considerably since its inception. Here, we focus on the server functionality of Trips-viz which also has been greatly improved. Trips-viz now enables visualisation of proteomics data from a large number of processed mass spectrometry datasets. It can be used to support translation inferred from Ribo-Seq data. Users are now able to upload a custom reference transcriptome as well as data types other than Ribo-Seq/RNA-Seq. Incorporating custom data has been streamlined with RiboGalaxy (https://ribogalaxy.ucc.ie/) integration. The other new functionality is the rapid detection of translated open reading frames (ORFs) through a simple easy to use interface. The analysis of differential expression has been also improved via integration of DESeq2 and Anota2seq in addition to a number of other improvements of existing Trips-viz features.

Plasma Proteomics of Renal Function: A Transethnic Meta-Analysis and Mendelian Randomization Study

BACKGROUND

Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed.

METHODS

A cross-sectional study of 993 plasma proteins among 2882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified transethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR.

RESULTS

In total, 57 plasma proteins were associated with eGFR, including one novel protein. Of these, 23 were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR.

CONCLUSIONS

In a discovery-replication setting, we identified 57 proteins transethnically associated with eGFR. The revealed causal relationships are an important stepping stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.

The tweety Gene Family: From Embryo to Disease

The tweety genes encode gated chloride channels that are found in animals, plants, and even simple eukaryotes, signifying their deep evolutionary origin. In vertebrates, the tweety gene family is highly conserved and consists of three members—ttyh1, ttyh2, and ttyh3—that are important for the regulation of cell volume. While research has elucidated potential physiological functions of ttyh1 in neural stem cell maintenance, proliferation, and filopodia formation during neural development, the roles of ttyh2 and ttyh3 are less characterized, though their expression patterns during embryonic and fetal development suggest potential roles in the development of a wide range of tissues including a role in the immune system in response to pathogen-associated molecules. Additionally, members of the tweety gene family have been implicated in various pathologies including cancers, particularly pediatric brain tumors, and neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. Here, we review the current state of research using information from published articles and open-source databases on the tweety gene family with regard to its structure, evolution, expression during development and adulthood, biochemical and cellular functions, and role in human disease. We also identify promising areas for further research to advance our understanding of this important, yet still understudied, family of genes.

RGS14 Regulation of Post-Synaptic Signaling and Spine Plasticity in Brain

The regulator of G-protein signaling 14 (RGS14) is a multifunctional signaling protein that regulates post synaptic plasticity in neurons. RGS14 is expressed in the brain regions essential for learning, memory, emotion, and stimulus-induced behaviors, including the basal ganglia, limbic system, and cortex. Behaviorally, RGS14 regulates spatial and object memory, female-specific responses to cued fear conditioning, and environmental- and psychostimulant-induced locomotion. At the cellular level, RGS14 acts as a scaffolding protein that integrates G protein, Ras/ERK, and calcium/calmodulin signaling pathways essential for spine plasticity and cell signaling, allowing RGS14 to naturally suppress long-term potentiation (LTP) and structural plasticity in hippocampal area CA2 pyramidal cells. Recent proteomics findings indicate that RGS14 also engages the actomyosin system in the brain, perhaps to impact spine morphogenesis. Of note, RGS14 is also a nucleocytoplasmic shuttling protein, where its role in the nucleus remains uncertain. Balanced nuclear import/export and dendritic spine localization are likely essential for RGS14 neuronal functions as a regulator of synaptic plasticity. Supporting this idea, human genetic variants disrupting RGS14 localization also disrupt RGS14’s effects on plasticity. This review will focus on the known and unexplored roles of RGS14 in cell signaling, physiology, disease and behavior.

A Probe for NLRP3 Inflammasome Inhibitor MCC950 Identifies Carbonic Anhydrase 2 as a Novel Target

Inhibition of inflammasome and pyroptotic pathways are promising strategies for clinical treatment of autoimmune and inflammatory disorders. MCC950, a potent inhibitor of the NLR-family inflammasome pyrin domain-containing 3 (NLRP3) protein, has shown encouraging results in animal models for a range of conditions; however, until now, no off-targets have been identified. Herein, we report the design, synthesis, and application of a novel photoaffinity alkyne-tagged probe for MCC950 (IMP2070) which shows direct engagement with NLRP3 and inhibition of inflammasome activation in macrophages. Affinity-based chemical proteomics in live macrophages identified several potential off-targets, including carbonic anhydrase 2 (CA2) as a specific target of IMP2070, and independent cellular thermal proteomic profiling revealed stabilization of CA2 by MCC950. MCC950 displayed noncompetitive inhibition of CA2 activity, confirming carbonic anhydrase as an off-target class for this compound. These data highlight potential biological mechanisms through which MCC950 and derivatives may exhibit off-target effects in preclinical or clinical studies.

Whole genome sequencing identifies allelic ratio distortion in sperm involving genes related to spermatogenesis in a swine model

Transmission Ratio Distortion (TRD), the uneven transmission of an allele from a parent to its offspring, can be caused by allelic differences affecting gametogenesis, fertilization or embryogenesis. However, TRD remains vaguely studied at a genomic scale. We sequenced the diploid and haploid genomes of three boars from leukocytes and spermatozoa at 50x to shed light into the genetic basis of spermatogenesis-caused Allelic Ratio Distortion (ARD). We first developed a Binomial model to identify ARD by simultaneously analysing all three males. This led to the identification of 55 ARD SNPs, most of which were animal-specific. We then evaluated ARD individually within each pig by a Fisher’s exact test and identified two shared genes (TOP3A and UNC5B) and four shared genomic regions harbouring distinct ARD SNPs in the three boars. The shared genomic regions contained candidate genes with functions related to spermatogenesis including AK7, ARID4B, BDKRB2, GSK3B, NID1, NSMCE1, PALB2, VRK1 and ZC3H13. Using the Fisher’s test, we also identified 378 genes containing variants with protein damaging potential in at least one boar, a high proportion of which, including FAM120B, TDRD15, JAM2 or AOX4 among others, are associated to spermatogenesis. Overall, our results show that sperm is subjected to ARD with variants associated to a wide variety of genes involved in different stages of spermatogenesis.

Evaluation and Refinement of Sample Preparation Methods for Extracellular Matrix Proteome Coverage

The extracellular matrix is a key component of tissues, yet it is underrepresented in proteomic datasets. Identification and evaluation of proteins in the extracellular matrix (ECM) has proved challenging due to the insolubility of many ECM proteins in traditional protein extraction buffers. Here we separate the decellularization and ECM extraction steps of several prominent methods for evaluation under real-world conditions. The results are used to optimize a two-fraction ECM extraction method. Approximately one dozen additional parameters are tested, and recommendations for analysis based on overall ECM coverage or specific ECM classes are given. Compared with a standard in-solution digest, the optimized method yielded a fourfold improvement in unique ECM peptide identifications.

Deficits in Prenatal Serine Biosynthesis Underlie the Mitochondrial Dysfunction Associated with the Autism-Linked FMR1 Gene

Fifty-five to two hundred CGG repeats (called a premutation, or PM) in the 5′-UTR of the FMR1 gene are generally unstable, often expanding to a full mutation (>200) in one generation through maternal inheritance, leading to fragile X syndrome, a condition associated with autism and other intellectual disabilities. To uncover the early mechanisms of pathogenesis, we performed metabolomics and proteomics on amniotic fluids from PM carriers, pregnant with male fetuses, who had undergone amniocentesis for fragile X prenatal diagnosis. The prenatal metabolic footprint identified mitochondrial deficits, which were further validated by using internal and external cohorts. Deficits in the anaplerosis of the Krebs cycle were noted at the level of serine biosynthesis, which was confirmed by rescuing the mitochondrial dysfunction in the carriers’ umbilical cord fibroblasts using alpha-ketoglutarate precursors. Maternal administration of serine and its precursors has the potential to decrease the risk of developing energy shortages associated with mitochondrial dysfunction and linked comorbidities.

IGF1R and Src inhibition induce synergistic cytotoxicity in HNSCC through inhibition of FAK

Head and neck cancer is the sixth most common cancer worldwide with a 5-year survival of only 65%. Targeting compensatory signaling pathways may improve therapeutic responses and combat resistance. Utilizing reverse phase protein arrays (RPPA) to assess the proteome and explore mechanisms of synergistic growth inhibition in HNSCC cell lines treated with IGF1R and Src inhibitors, BMS754807 and dasatinib, respectively, we identified focal adhesion signaling as a critical node. Focal Adhesion Kinase (FAK) and Paxillin phosphorylation were decreased as early as 15 min after treatment, and treatment with a FAK inhibitor, PF-562,271, was sufficient to decrease viability in vitro. Treatment of 3D spheroids demonstrated robust cytotoxicity suggesting that the combination of BMS754807 and dasatinib is effective in multiple experimental models. Furthermore, treatment with BMS754807 and dasatinib significantly decreased cell motility, migration, and invasion in multiple HNSCC cell lines. Most strikingly, treatment with BMS754807 and dasatinib, or a FAK inhibitor alone, significantly increased cleaved-PARP in human ex-vivo HNSCC patient tissues demonstrating a potential clinical utility for targeting FAK or the combined targeting of the IGF1R with Src. This ex-vivo result further confirms FAK as a vital signaling node of this combinatorial treatment and demonstrates therapeutic potential for targeting FAK in HNSCC patients.

Computational Biology and Machine Learning Approaches to Understand Mechanistic Microbiome-Host Interactions

The microbiome, by virtue of its interactions with the host, is implicated in various host functions including its influence on nutrition and homeostasis. Many chronic diseases such as diabetes, cancer, inflammatory bowel diseases are characterized by a disruption of microbial communities in at least one biological niche/organ system. Various molecular mechanisms between microbial and host components such as proteins, RNAs, metabolites have recently been identified, thus filling many gaps in our understanding of how the microbiome modulates host processes. Concurrently, high-throughput technologies have enabled the profiling of heterogeneous datasets capturing community level changes in the microbiome as well as the host responses. However, due to limitations in parallel sampling and analytical procedures, big gaps still exist in terms of how the microbiome mechanistically influences host functions at a system and community level. In the past decade, computational biology and machine learning methodologies have been developed with the aim of filling the existing gaps. Due to the agnostic nature of the tools, they have been applied in diverse disease contexts to analyze and infer the interactions between the microbiome and host molecular components. Some of these approaches allow the identification and analysis of affected downstream host processes. Most of the tools statistically or mechanistically integrate different types of -omic and meta -omic datasets followed by functional/biological interpretation. In this review, we provide an overview of the landscape of computational approaches for investigating mechanistic interactions between individual microbes/microbiome and the host and the opportunities for basic and clinical research. These could include but are not limited to the development of activity- and mechanism-based biomarkers, uncovering mechanisms for therapeutic interventions and generating integrated signatures to stratify patients.

Universal Spectrum Explorer: A Standalone (Web-)Application for Cross-Resource Spectrum Comparison

Here, we present the Universal Spectrum Explorer (USE), a web-based tool based on IPSA for cross-resource (peptide) spectrum visualization and comparison (https://www.proteomicsdb.org/use/). Mass spectra under investigation can be either provided manually by the user (table format) or automatically retrieved from online repositories supporting access to spectral data via the universal spectrum identifier (USI), or requested from other resources and services implementing a newly designed REST interface. As a proof of principle, we implemented such an interface in ProteomicsDB thereby allowing the retrieval of spectra acquired within the ProteomeTools project or real-time prediction of tandem mass spectra from the deep learning framework Prosit. Annotated mirror spectrum plots can be exported from the USE as editable scalable high-quality vector graphics. The USE was designed and implemented with minimal external dependencies allowing local usage and integration into other web sites (https://github.com/kusterlab/universal_spectrum_explorer).

Glucagon-like peptide-1 (GLP-1) receptor agonists and their cardiovascular benefits-The role of the GLP-1 receptor

Cardiovascular outcome trials revealed cardiovascular benefits for type 2 diabetes mellitus patients when treated with long‐acting glucagon‐like peptide‐1 (GLP‐1) receptor agonists. In the last decade, major advances were made characterising the physiological effects of GLP‐1 and its action on numerous targets including brain, liver, kidney, heart and blood vessels. However, the effects of GLP‐1 and receptor agonists, and the GLP‐1 receptor on the cardiovascular system have not been fully elucidated. We compare results from cardiovascular outcome trials of GLP‐1 receptor agonists and review pleiotropic clinical and preclinical data concerning cardiovascular protection beyond glycaemic control. We address current knowledge on GLP‐1 and receptor agonist actions on the heart, vasculature, inflammatory cells and platelets, and discuss evidence for GLP‐1 receptor‐dependent versus independent effects secondary of GLP‐1 metabolites. We conclude that the favourable cardiovascular profile of GLP‐1 receptor agonists might expand their therapeutic use for treating cardiovascular disease even in non‐diabetic populations.

CIDer: A Statistical Framework for Interpreting Differences in CID and HCD Fragmentation

Library searching is a powerful technique for detecting peptides using either data independent or data dependent acquisition. While both large-scale spectrum library curators and deep learning prediction approaches have focused on beam-type CID fragmentation (HCD), resonance CID fragmentation remains a popular technique. Here we demonstrate an approach to model the differences between HCD and CID spectra, and present a software tool, CIDer, for converting libraries between the two fragmentation methods. We demonstrate that just using a combination of simple linear models and basic principles of peptide fragmentation, we can explain up to 43% of the variation between ions fragmented by HCD and CID across an array of collision energy settings. We further show that in some circumstances, searching converted CID libraries can detect more peptides than searching existing CID libraries or libraries of machine learning predictions from FASTA databases. These results suggest that leveraging information in existing libraries by converting between HCD and CID libraries may be an effective interim solution while large-scale CID libraries are being developed.

Prioritizing Pain-Associated Targets with Machine Learning

While hundreds of genes have been associated with pain, much of the molecular mechanisms of pain remain unknown. As a result, current analgesics are limited to few clinically validated targets. Here, we trained a machine learning (ML) ensemble model to predict new targets for 17 categories of pain. The model utilizes features from transcriptomics, proteomics, and gene ontology to prioritize targets for modulating pain. We focused on identifying novel G-protein-coupled receptors (GPCRs), ion channels, and protein kinases because these proteins represent the most successful drug target families. The performance of the model to predict novel pain targets is 0.839 on average based on AUROC, while the predictions for arthritis had the highest accuracy (AUROC = 0.929). The model predicts hundreds of novel targets for pain; for example, GPR132 and GPR109B are highly ranked GPCRs for rheumatoid arthritis. Overall, gene-pain association predictions cluster into three groups that are enriched for cytokine, calcium, and GABA-related cell signaling pathways. These predictions can serve as a foundation for future experimental exploration to advance the development of safer and more effective analgesics.

Fully Automated Sample Processing and Analysis Workflow for Low-Input Proteome Profiling

Recent advances in sample preparation and analysis have enabled direct profiling of protein expression in single mammalian cells and other trace samples. Several techniques to prepare and analyze low-input samples employ custom fluidics for nanoliter sample processing and manual sample injection onto a specialized separation column. While being effective, these highly specialized systems require significant expertise to fabricate and operate, which has greatly limited implementation in most proteomic laboratories. Here, we report a fully automated platform termed autoPOTS (automated preparation in one pot for trace samples) that uses only commercially available instrumentation for sample processing and analysis. An unmodified, low-cost commercial robotic pipetting platform was utilized for one-pot sample preparation. We used low-volume 384-well plates and periodically added water or buffer to the microwells to compensate for limited evaporation during sample incubation. Prepared samples were analyzed directly from the well plate with a commercial autosampler that was modified with a 10-port valve for compatibility with 30 μm i.d. nanoLC columns. We used autoPOTS to analyze 1-500 HeLa cells and observed only a moderate reduction in peptide coverage for 150 cells and a 24% reduction in coverage for single cells compared to our previously developed nanoPOTS platform. To evaluate clinical feasibility, we identified an average of 1095 protein groups from ∼130 sorted B or T lymphocytes. We anticipate that the straightforward implementation of autoPOTS will make it an attractive option for low-input and single-cell proteomics in many laboratories.

The TIM22 complex mediates the import of sideroflexins and is required for efficient mitochondrial one-carbon metabolism

Acylglycerol kinase (AGK) is a mitochondrial lipid kinase that contributes to protein biogenesis as a subunit of the TIM22 complex at the inner mitochondrial membrane. Mutations in AGK cause Sengers syndrome, an autosomal recessive condition characterized by congenital cataracts, hypertrophic cardiomyopathy, skeletal myopathy, and lactic acidosis. We mapped the proteomic changes in Sengers patient fibroblasts and AGK^KO cell lines to understand the effects of AGK dysfunction on mitochondria. This uncovered down-regulation of a number of proteins at the inner mitochondrial membrane, including many SLC25 carrier family proteins, which are predicted substrates of the complex. We also observed down-regulation of SFXN proteins, which contain five transmembrane domains, and show that they represent a novel class of TIM22 complex substrate. Perturbed biogenesis of SFXN proteins in cells lacking AGK reduces the proliferative capabilities of these cells in the absence of exogenous serine, suggesting that dysregulation of one-carbon metabolism is a molecular feature in the biology of Sengers syndrome.

A disorder-related variant (E420K) of a PP2A-regulatory subunit (PPP2R5D) causes constitutively active AKT-mTOR signaling and uncoordinated cell growth

Functional genomic approaches have facilitated the discovery of rare genetic disorders and improved efforts to decipher their underlying etiology. PPP2R5D-related disorder is an early childhood onset condition characterized by intellectual disability, hypotonia, autism-spectrum disorder, macrocephaly, and dysmorphic features. The disorder is caused by de novo single nucleotide changes in PPP2R5D, which generate heterozygous dominant missense variants. PPP2R5D is known to encode a B'-type (B'56δ) regulatory subunit of a PP2A-serine/threonine phosphatase. To help elucidate the molecular mechanisms altered in PPP2R5D-related disorder, we used a CRISPR-single-base editor to generate HEK-293 cells in which a single transition (c.1258G>A) was introduced into one allele, precisely recapitulating a clinically relevant E420K variant. Unbiased quantitative proteomic and phosphoproteomic analyses of endogenously expressed proteins revealed heterozygous-dominant changes in kinase/phosphatase signaling. These data combined with orthogonal validation studies revealed a previously unrecognized interaction of PPP2R5D with AKT in human cells, leading to constitutively active AKT-mTOR signaling, increased cell size, and uncoordinated cellular growth in E420K-variant cells. Rapamycin reduced cell size and dose-dependently reduced RPS6 phosphorylation in E420K-variant cells, suggesting that inhibition of mTOR1 can suppress both the observed RPS6 hyperphosphorylation and increased cell size. Together, our findings provide a deeper understanding of PPP2R5D and insight into how the E420K-variant alters signaling networks influenced by PPP2R5D. Our comprehensive approach, which combines precise genome editing, isobaric tandem mass tag labeling of peptides generated from endogenously expressed proteins, and concurrent liquid chromatography-mass spectrometry (LC-MS³), also provides a roadmap that can be used to rapidly explore the etiologies of additional genetic disorders.

Electron transfer flavoprotein and its role in mitochondrial energy metabolism in health and disease

Electron transfer flavoprotein (ETF) is an enzyme with orthologs from bacteria to humans. Human ETF is nuclear encoded by two separate genes, ETFA and ETFB, respectively. After translation, the two subunits are imported to the mitochondrial matrix space and assemble into a heterodimer containing one FAD and one AMP as cofactors. ETF functions as a hub taking up electrons from at least 14 flavoenzymes, feeding them into the respiratory chain. This represents a major source of reducing power for the electron transport chain from fatty acid oxidation and amino acid degradation. Transfer of electrons from the donor enzymes to ETF occurs by direct transfer between the enzyme bound flavins, a process that is tightly regulated by the polypeptide chain and by protein:protein interactions. ETF, in turn relays electrons to the iron sulfur cluster of the inner membrane protein ETF:QO, from where they travel via the FAD in ETF:QO to ubiquinone, entering the respiratory chain at the level of complex III. ETF recognizes its dehydrogenase partners via a recognition loop that anchors the protein on its partner followed by dynamic movements of the ETF flavin domain that bring redox cofactors in close proximity, thus promoting electron transfer. Genetic mutations in the ETFA or ETFB genes cause the Mendelian disorder multiple acyl-CoA dehydrogenase deficiency (MADD; OMIM #231680). We here review the knowledge on human ETF and investigations of the effects of disease-associated missense mutations in this protein that have promoted the understanding of the essential role that ETF plays in cellular metabolism and human disease.

Mitochondrial Fission Protein 1: Emerging Roles in Organellar Form and Function in Health and Disease

Mitochondrial fission protein 1 (Fis1) was identified in yeast as being essential for mitochondrial division or fission and subsequently determined to mediate human mitochondrial and peroxisomal fission. Yet, its exact functions in humans, especially in regard to mitochondrial fission, remains an enigma as genetic deletion of Fis1 elongates mitochondria in some cell types, but not others. Fis1 has also been identified as an important component of apoptotic and mitophagic pathways suggesting the protein may have multiple, essential roles. This review presents current perspectives on the emerging functions of Fis1 and their implications in human health and diseases, with an emphasis on Fis1's role in both endocrine and neurological disorders.

ERICH3: vesicular association and antidepressant treatment response

Selective serotonin reuptake inhibitors (SSRIs) are standard of care for major depressive disorder (MDD) pharmacotherapy, but only approximately half of these patients remit on SSRI therapy. Our previous genome-wide association study identified a single-nucleotide polymorphism (SNP) signal across the glutamate-rich 3 (ERICH3) gene that was nearly genome-wide significantly associated with plasma serotonin (5-HT) concentrations, which were themselves associated with SSRI response for MDD patients enrolled in the Mayo Clinic PGRN-AMPS SSRI trial. In this study, we performed a meta-analysis which demonstrated that those SNPs were significantly associated with SSRI treatment outcomes in four independent MDD trials. However, the function of ERICH3 and molecular mechanism(s) by which it might be associated with plasma 5-HT concentrations and SSRI clinical response remained unclear. Therefore, we characterized the human ERICH3 gene functionally and identified ERICH3 mRNA transcripts and protein isoforms that are highly expressed in central nervous system cells. Coimmunoprecipitation identified a series of ERICH3 interacting proteins including clathrin heavy chain which are known to play a role in vesicular function. Immunofluorescence showed ERICH3 colocalization with 5-HT in vesicle-like structures, and ERICH3 knock-out dramatically decreased 5-HT staining in SK-N-SH cells as well as 5-HT concentrations in the culture media and cell lysates without changing the expression of 5-HT synthesizing or metabolizing enzymes. Finally, immunofluorescence also showed ERICH3 colocalization with dopamine in human iPSC-derived neurons. These results suggest that ERICH3 may play a significant role in vesicular function in serotonergic and other neuronal cell types, which might help explain its association with antidepressant treatment response.

Single-Cell Transcriptional Analyses Identify Lineage-Specific Epithelial Responses to Inflammation and Metaplastic Development in the Gastric Corpus

BACKGROUND & AIMS

Chronic atrophic gastritis can lead to gastric metaplasia and increase risk of gastric adenocarcinoma. Metaplasia is a precancerous lesion associated with an increased risk for carcinogenesis, but the mechanism(s) by which inflammation induces metaplasia are poorly understood. We investigated transcriptional programs in mucous neck cells and chief cells as they progress to metaplasia mice with chronic gastritis.

METHODS

We analyzed previously generated single-cell RNA-sequencing (scRNA-seq) data of gastric corpus epithelium to define transcriptomes of individual epithelial cells from healthy BALB/c mice (controls) and TxA23 mice, which have chronically inflamed stomachs with metaplasia. Chronic gastritis was induced in B6 mice by Helicobacter pylori infection. Gastric tissues from mice and human patients were analyzed by immunofluorescence to verify findings at the protein level. Pseudotime trajectory analysis of scRNA-seq data was used to predict differentiation of normal gastric epithelium to metaplastic epithelium in chronically inflamed stomachs.

RESULTS

Analyses of gastric epithelial transcriptomes revealed that gastrokine 3 (Gkn3) mRNA is a specific marker of mouse gastric corpus metaplasia (spasmolytic polypeptide expressing metaplasia, SPEM). Gkn3 mRNA was undetectable in healthy gastric corpus; its expression in chronically inflamed stomachs (from TxA23 mice and mice with Helicobacter pylori infection) identified more metaplastic cells throughout the corpus than previously recognized. Staining of healthy and diseased human gastric tissue samples paralleled these results. Although mucous neck cells and chief cells from healthy stomachs each had distinct transcriptomes, in chronically inflamed stomachs, these cells had distinct transcription patterns that converged upon a pre-metaplastic pattern, which lacked the metaplasia-associated transcripts. Finally, pseudotime trajectory analysis confirmed the convergence of mucous neck cells and chief cells into a pre-metaplastic phenotype that ultimately progressed to metaplasia.

CONCLUSIONS

In analyses of tissues from chronically inflamed stomachs of mice and humans, we expanded the definition of gastric metaplasia to include Gkn3 mRNA and GKN3-positive cells in the corpus, allowing a more accurate assessment of SPEM. Under conditions of chronic inflammation, chief cells and mucous neck cells are plastic and converge into a pre-metaplastic cell type that progresses to metaplasia.

Phosphoproteomic quantitation and causal analysis reveal pathways in GPVI/ITAM-mediated platelet activation programs

Platelets engage cues of pending vascular injury through coordinated adhesion, secretion, and aggregation responses. These rapid, progressive changes in platelet form and function are orchestrated downstream of specific receptors on the platelet surface and through intracellular signaling mechanisms that remain systematically undefined. This study brings together cell physiological and phosphoproteomics methods to profile signaling mechanisms downstream of the immunotyrosine activation motif (ITAM) platelet collagen receptor GPVI. Peptide tandem mass tag (TMT) labeling, sample multiplexing, synchronous precursor selection (SPS), and triple stage tandem mass spectrometry (MS3) detected >3000 significant (false discovery rate < 0.05) phosphorylation events on >1300 proteins over conditions initiating and progressing GPVI-mediated platelet activation. With literature-guided causal inference tools, >300 site-specific signaling relations were mapped from phosphoproteomics data among key and emerging GPVI effectors (ie, FcRγ, Syk, PLCγ2, PKCδ, DAPP1). Through signaling validation studies and functional screening, other less-characterized targets were also considered within the context of GPVI/ITAM pathways, including Ras/MAPK axis proteins (ie, KSR1, SOS1, STAT1, Hsp27). Highly regulated GPVI/ITAM targets out of context of curated knowledge were also illuminated, including a system of >40 Rab GTPases and associated regulatory proteins, where GPVI-mediated Rab7 S72 phosphorylation and endolysosomal maturation were blocked by TAK1 inhibition. In addition to serving as a model for generating and testing hypotheses from omics datasets, this study puts forth a means to identify hemostatic effectors, biomarkers, and therapeutic targets relevant to thrombosis, vascular inflammation, and other platelet-associated disease states.

Radiosensitization by Kinase Inhibition Revealed by Phosphoproteomic Analysis of Pancreatic Cancer Cells

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers and known for its extensive genetic heterogeneity, high therapeutic resistance, and strong variation in intrinsic radiosensitivity. To understand the molecular mechanisms underlying radioresistance, we screened the phenotypic response of 38 PDAC cell lines to ionizing radiation. Subsequent phosphoproteomic analysis of two representative sensitive and resistant lines led to the reproducible identification of 7,800 proteins and 13,000 phosphorylation sites (p-sites). Approximately 700 p-sites on 400 proteins showed abundance changes after radiation in all cell lines regardless of their phenotypic sensitivity. Apart from recapitulating known radiation response phosphorylation markers such as on proteins involved in DNA damage repair, the analysis uncovered many novel members of a radiation-responsive signaling network that was apparent only at the level of protein phosphorylation. These regulated p-sites were enriched in potential ATM substrates and in vitro kinase assays corroborated 10 of these. Comparing the proteomes and phosphoproteomes of radiosensitive and -resistant cells pointed to additional tractable radioresistance mechanisms involving apoptotic proteins. For instance, elevated NADPH quinine oxidoreductase 1 (NQO1) expression in radioresistant cells may aid in clearing harmful reactive oxygen species. Resistant cells also showed elevated phosphorylation levels of proteins involved in cytoskeleton organization including actin dynamics and focal adhesion kinase (FAK) activity and one resistant cell line showed a strong migration phenotype. Pharmacological inhibition of the kinases FAK by Defactinib and of CHEK1 by Rabusertib showed a statistically significant sensitization to radiation in radioresistant PDAC cells. Together, the presented data map a comprehensive molecular network of radiation-induced signaling, improves the understanding of radioresistance and provides avenues for developing radiotherapeutic strategies.

Kinase inhibitor data set for systematic analysis of representative kinases across the human kinome

A large set of multi-kinase inhibitors with high-confidence activity data was assembled and used to generate network representations revealing kinase relationships based upon shared inhibitors [1]. Compounds and activity annotations were originally selected from public repositories and organized in an in-house database from which the data set was extracted and curated. The new data set comprises more than 36,000 inhibitors with multiple activity annotations for a total of 420 human kinases (providing 81% coverage of the human kinome), representing a total of ∼127,000 kinase-inhibitor interactions. Use of the data is not limited to the network application reported in [1]. It can also be used, for example, for different types of compound promiscuity analysis or machine learning (such a multi-task modeling). In addition, the data set provides a large resource for complementing kinase drug discovery projects with external compound information.

The E3 Ubiquitin Ligase Mind Bomb 1 Controls Adenovirus Genome Release at the Nuclear Pore Complex

Adenoviruses (AdVs) cause respiratory, ocular, and gastrointestinal tract infection and inflammation in immunocompetent people and life-threatening disease upon immunosuppression. AdV vectors are widely used in gene therapy and vaccination. Incoming particles attach to nuclear pore complexes (NPCs) of post-mitotic cells, then rupture and deliver viral DNA (vDNA) to the nucleus or misdeliver to the cytosol. Our genome-wide RNAi screen in AdV-infected cells identified the RING-type E3 ubiquitin ligase Mind bomb 1 (Mib1) as a proviral host factor for AdV infection. Mib1 is implicated in Notch-Delta signaling, ciliary biogenesis, and RNA innate immunity. Mib1 depletion arrested incoming AdVs at NPCs. Induced expression of full-length but not ligase-defective Mib1 in knockout cells triggered vDNA uncoating from NPC-tethered virions, nuclear import, misdelivery of vDNA, and vDNA expression. Mib1 is an essential host factor for AdV uncoating in human cells, and it provides a new concept for licensing virion DNA delivery through the NPC.

CAR T Cell Therapy for Pediatric Brain Tumors

Chimeric Antigen Receptor (CAR) T cell therapy has recently begun to be used for solid tumors such as glioblastoma multiforme. Many children with pediatric malignant brain tumors develop extensive long-term morbidity of intensive multimodal curative treatment. Others with certain diagnoses and relapsed disease continue to have limited therapies and a dismal prognosis. Novel treatments such as CAR T cells could potentially improve outcomes and ameliorate the toxicity of current treatment. In this review, we discuss the potential of using CAR therapy for pediatric brain tumors. The emerging insights on the molecular subtypes and tumor microenvironment of these tumors provide avenues to devise strategies for CAR T cell therapy. Unique characteristics of these brain tumors, such as location and associated morbid treatment induced neuro-inflammation, are novel challenges not commonly encountered in adult brain tumors. Despite these considerations, CAR T cell therapy has the potential to be integrated into treatment schema for aggressive pediatric malignant brain tumors in the future.

Proteome activity landscapes of tumor cell lines determine drug responses

Integrated analysis of genomes, transcriptomes, proteomes and drug responses of cancer cell lines (CCLs) is an emerging approach to uncover molecular mechanisms of drug action. We extend this paradigm to measuring proteome activity landscapes by acquiring and integrating quantitative data for 10,000 proteins and 55,000 phosphorylation sites (p-sites) from 125 CCLs. These data are used to contextualize proteins and p-sites and predict drug sensitivity. For example, we find that Progesterone Receptor (PGR) phosphorylation is associated with sensitivity to drugs modulating estrogen signaling such as Raloxifene. We also demonstrate that Adenylate kinase isoenzyme 1 (AK1) inactivates antimetabolites like Cytarabine. Consequently, high AK1 levels correlate with poor survival of Cytarabine-treated acute myeloid leukemia patients, qualifying AK1 as a patient stratification marker and possibly as a drug target. We provide an interactive web application termed ATLANTiC (http://atlantic.proteomics.wzw.tum.de), which enables the community to explore the thousands of novel functional associations generated by this work.

The protein expression profile of ACE2 in human tissues

The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across > 150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye, and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitute an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.