Microtubule-associated protein MAP1LC3C regulates lysosomal exocytosis and induces zinc reprogramming in renal cancer cells.

Microtubule-associated protein 1 light chain 3 gamma (MAP1LC3C or LC3C) is a member of the microtubule-associated family of proteins that are essential in the formation of autophagosomes and lysosomal degradation of cargo. LC3C has tumor-suppressing activity, and its expression is dependent on kidney cancer tumor suppressors, such as von Hippel-Lindau protein and folliculin. Recently, we demonstrated that LC3C autophagy is regulated by noncanonical upstream regulatory complexes and targets for degradation postdivision midbody rings associated with cancer cell stemness. Here, we show that loss of LC3C leads to peripheral positioning of the lysosomes and lysosomal exocytosis (LE). This process is independent of the autophagic activity of LC3C. Analysis of isogenic cells with low and high LE shows substantial transcriptomic reprogramming with altered expression of zinc (Zn)-related genes and activity of polycomb repressor complex 2, accompanied by a robust decrease in intracellular Zn. In addition, metabolomic analysis revealed alterations in amino acid steady-state levels. Cells with augmented LE show increased tumor initiation properties and form aggressive tumors in xenograft models. Immunocytochemistry identified high levels of lysosomal-associated membrane protein 1 on the plasma membrane of cancer cells in human clear cell renal cell carcinoma and reduced levels of Zn, suggesting that LE occurs in clear cell renal cell carcinoma, potentially contributing to the loss of Zn. These data indicate that the reprogramming of lysosomal localization and Zn metabolism with implication for epigenetic remodeling in a subpopulation of tumor-propagating cancer cells is an important aspect of tumor-suppressing activity of LC3C.

Illuminating the dark kinome: utilizing multiplex peptide activity arrays to functionally annotate understudied kinases.

Protein kinases are critical components of a myriad biological processes and strongly associated with various diseases. While kinase research has been a point of focus in biomedical research for several decades, a large portion of the kinome is still considered understudied or "dark," because prior research is targeted towards a subset of kinases with well-established roles in cellular processes. We present an empirical and in-silico hybrid workflow to extend the functional knowledge of understudied kinases. Utilizing multiplex peptide activity arrays and robust in-silico analyses, we extended the functional knowledge of five dark tyrosine kinases (AATK, EPHA6, INSRR, LTK, TNK1) and explored their roles in schizophrenia, Alzheimer's dementia (AD), and major depressive disorder (MDD). Using this hybrid approach, we identified 195 novel kinase-substrate interactions with variable degrees of affinity and linked extended functional networks for these kinases to biological processes that are impaired in psychiatric and neurological disorders. Biochemical assays and mass spectrometry were used to confirm a putative substrate of EPHA6, an understudied dark tyrosine kinase. We examined the EPHA6 network and knowledgebase in schizophrenia using reporter peptides identified and validated from the multi-plex array with high affinity for phosphorylation by EPHA6. Identification and confirmation of putative substrates for understudied kinases provides a wealth of actionable information for the development of new drug treatments as well as exploration of the pathophysiology of disease states using signaling network approaches.

Transcriptional profile of pyramidal neurons in chronic schizophrenia reveals lamina-specific dysfunction of neuronal immunity.

While the pathophysiology of schizophrenia has been extensively investigated using homogenized postmortem brain samples, few studies have examined changes in brain samples with techniques that may attribute perturbations to specific cell types. To fill this gap, we performed microarray assays on mRNA isolated from anterior cingulate cortex (ACC) superficial and deep pyramidal neurons from 12 schizophrenia and 12 control subjects using laser-capture microdissection. Among all the annotated genes, we identified 134 significantly increased and 130 decreased genes in superficial pyramidal neurons, while 93 significantly increased and 101 decreased genes were found in deep pyramidal neurons, in schizophrenia compared to control subjects. In these differentially expressed genes, we detected lamina-specific changes of 55 and 31 genes in superficial and deep neurons in schizophrenia, respectively. Gene set enrichment analysis (GSEA) was applied to the entire pre-ranked differential expression gene lists to gain a complete pathway analysis throughout all annotated genes. Our analysis revealed overrepresented groups of gene sets in schizophrenia, particularly in immunity and synapse-related pathways, suggesting the disruption of these pathways plays an important role in schizophrenia. We also detected other pathways previously demonstrated in schizophrenia pathophysiology, including cytokine and chemotaxis, postsynaptic signaling, and glutamatergic synapses. In addition, we observed several novel pathways, including ubiquitin-independent protein catabolic process. Considering the effects of antipsychotic treatment on gene expression, we applied a novel bioinformatics approach to compare our differential expression gene profiles with 51 antipsychotic treatment datasets, demonstrating that our results were not influenced by antipsychotic treatment. Taken together, we found pyramidal neuron-specific changes in neuronal immunity, synaptic dysfunction, and olfactory dysregulation in schizophrenia, providing new insights for the cell-subtype specific pathophysiology of chronic schizophrenia.

Differential genetic associations and expression of PAPST1/SLC35B2 in bipolar disorder and schizophrenia.

Lithium's inhibitory effect on enzymes involved in sulfation process, such as inhibition of 3'(2')-phosphoadenosine 5'-phosphate (PAP) phosphatase, is a possible mechanism of its therapeutic effect for bipolar disorder (BD). 3'-Phosphoadenosine 5'-phosphosulfate (PAPS) is translocated from cytosol to Golgi lumen by PAPS transporter 1 (PAPST1/SLC35B2), where it acts as a sulfa donor. Since SLC35B2 was previously recognized as a molecule that facilitates the release of D-serine, a co-agonist of N-methyl-D-aspartate type glutamate receptor, altered function of SLC35B2 might be associated with the pathophysiology of BD and schizophrenia (SCZ). We performed genetic association analyses of the SLC35B2 gene using Japanese cohorts with 366 BD cases and 370 controls and 2012 SCZ cases and 2170 controls. We then investigated expression of SLC35B2 mRNA in postmortem brains by QPCR using a Caucasian cohort with 33 BD and 34 SCZ cases and 34 controls and by in situ hybridization using a Caucasian cohort with 37 SCZ and 29 controls. We found significant associations between three SNPs (rs575034, rs1875324, and rs3832441) and BD, and significantly reduced SLC35B2 mRNA expression in postmortem dorsolateral prefrontal cortex (DLPFC) of BD. Moreover, we observed normalized SLC35B2 mRNA expression in BD subgroups who were medicated with lithium. While there was a significant association of SLC35B2 with SCZ (SNP rs2233437), its expression was not changed in SCZ. These findings indicate that SLC35B2 might be differentially involved in the pathophysiology of BD and SCZ by influencing the sulfation process and/or glutamate system in the central nervous system.

piNET: a versatile web platform for downstream analysis and visualization of proteomics data.

Rapid progress in proteomics and large-scale profiling of biological systems at the protein level necessitates the continued development of efficient computational tools for the analysis and interpretation of proteomics data. Here, we present the piNET server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with the LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. The primary input for the server consists of a set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values. Several interconnected workflows can be used to generate: (i) interactive graphs and tables providing comprehensive annotation and mapping between peptides and proteins with PTM sites; (ii) high resolution and interactive visualization for enzyme-substrate networks, including kinases and their phospho-peptide targets; (iii) mapping and visualization of LINCS signature connectivity for chemical inhibitors or genetic knockdown of enzymes upstream of their target PTM sites. piNET has been built using a modular Spring-Boot JAVA platform as a fast, versatile and easy to use tool. The Apache Lucene indexing is used for fast mapping of peptides into UniProt entries for the human, mouse and other commonly used model organism proteomes. PTM-centric network analyses combine PhosphoSitePlus, iPTMnet and SIGNOR databases of validated enzyme-substrate relationships, for kinase networks augmented by DeepPhos predictions and sequence-based mapping of PhosphoSitePlus consensus motifs. Concordant LINCS signatures are mapped using iLINCS. For each workflow, a RESTful API counterpart can be used to generate the results programmatically in the json format. The server is available at http://pinet-server.org, and it is free and open to all users without login requirement.

The mycobiomes and bacteriomes of sputum, saliva, and home dust.

Respiratory microbiome is an understudied area of research compared to other microbiomes of the human body. The respiratory tract is exposed to an array of environmental pollutants, including microbes. Yet, we know very little about the relationship between environmental and respiratory microbiome. The primary aim of our study was to compare the mycobiomes and bacteriomes between three sample types from the same participants, including home dust, saliva, and sputum. Samples were collected from 40 adolescents in a longitudinal cohort. We analyzed the samples using 16s bacterial rDNA and ITS fungal rDNA gene sequencing, as well as quantitative PCR with universal fungal and bacterial primers. Results showed that home dust had the greatest alpha diversity between the three sample types for both bacteria and fungi. Dust had the highest total fungal load and the lowest total bacterial load. Sputum had greater bacterial diversity than saliva, but saliva had greater fungal diversity than sputum. The distribution of major bacterial phyla differed between all sample types. However, the distribution of major fungal classes differed only between sputum and saliva. Future research should examine the biological significance of the taxa found in each sample type based on microbial ecology and associations with health effects.

Structural Adaptations of Norovirus GII.17/13/21 Lineage through Two Distinct Evolutionary Paths.

Human noroviruses (huNoVs), which cause epidemic acute gastroenteritis, recognize histo-blood group antigens (HBGAs) as host attachment factors affecting host susceptibility. HuNoVs are genetically diverse, containing at least 31 genotypes in the two major genogroups (genogroup I [GI] and GII). Three GII genotypes, GII genotype 17 (GII.17), GII.13, and GII.21, form a unique genetic lineage, in which the GII.17 genotype retains the conventional GII HBGA binding site (HBS), while the GII.13/21 genotypes acquire a completely new HBS. To understand the molecular bases behind these evolutionary changes, we solved the crystal structures of the HBGA binding protruding domains of (i) an early GII.17 variant (the 1978 variant) that does not bind or binds weakly to HBGAs, (ii) the new GII.17 variant (the 2014/15 variant) that binds A/B/H antigens strongly via an optimized GII HBS, and (iii) a GII.13 variant (the 2010 variant) that binds the Lewis a (Lea) antigen via the new HBS. These serial, high-resolution structural data enable a comprehensive structural comparison to understand the evolutionary changes of the GII.17/13/21 lineage, including the emergence of the new HBS of the GII.13/21 sublineage and the possible HBS optimization of the recent GII.17 variant for an enhanced HBGA binding ability. Our study elucidates the structural adaptations of the GII.17/13/21 lineage through distinct evolutionary paths, which may allow a theory explaining huNoV adaptations and evolutions to be put forward.IMPORTANCE Our understanding of the molecular bases behind the interplays between human noroviruses and their host glycan ligands, as well as their evolutionary changes over time with alterations in their host ligand binding capability and host susceptibility, remains limited. By solving the crystal structures of the glycan ligand binding protruding (P) domains with or without glycan ligands of three representative noroviruses of the GII.17/13/21 genetic lineage, we elucidated the molecular bases of the human norovirus-glycan interactions of this special genetic lineage. We present solid evidence on how noroviruses of this genetic lineage evolved via different evolutionary paths to (i) optimize their glycan binding site for higher glycan binding function and (ii) acquire a completely new glycan binding site for new ligands. Our data shed light on the mechanism of the structural adaptations of human noroviruses through different evolutionary paths, facilitating our understanding of human norovirus adaptations, evolutions, and epidemiology.

Data Portal for the Library of Integrated Network-based Cellular Signatures (LINCS) program: integrated access to diverse large-scale cellular perturbation response data.

The Library of Integrated Network-based Cellular Signatures (LINCS) program is a national consortium funded by the NIH to generate a diverse and extensive reference library of cell-based perturbation-response signatures, along with novel data analytics tools to improve our understanding of human diseases at the systems level. In contrast to other large-scale data generation efforts, LINCS Data and Signature Generation Centers (DSGCs) employ a wide range of assay technologies cataloging diverse cellular responses. Integration of, and unified access to LINCS data has therefore been particularly challenging. The Big Data to Knowledge (BD2K) LINCS Data Coordination and Integration Center (DCIC) has developed data standards specifications, data processing pipelines, and a suite of end-user software tools to integrate and annotate LINCS-generated data, to make LINCS signatures searchable and usable for different types of users. Here, we describe the LINCS Data Portal (LDP) (http://lincsportal.ccs.miami.edu/), a unified web interface to access datasets generated by the LINCS DSGCs, and its underlying database, LINCS Data Registry (LDR). LINCS data served on the LDP contains extensive metadata and curated annotations. We highlight the features of the LDP user interface that is designed to enable search, browsing, exploration, download and analysis of LINCS data and related curated content.

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data.

BACKGROUND: Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions. RESULTS: uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust . CONCLUSION: uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.

Increased susceptibility of estrogen-induced bladder outlet obstruction in a novel mouse model.

Disorders of the prostate and lower urinary tract are common in elderly men. We investigated the role of metallothionein-1 (MT1) in prostate carcinogenesis by generating a prostate-specific, MT1-expressing mouse. Unexpectedly, genomic analyses revealed that a 12.1-kb genomic region harboring several conserved noncoding elements was unintentionally deleted, upstream of the transgene integration site in the mouse, which we named it 12.1ΔMT1. Male 12.1ΔMT1 mice chronically treated with testosterone (T) plus 17ß-estradiol (E2) to induce prostate cancer exhibited no evidence of precancerous or cancerous lesions. Instead, most of them exhibited a bladder outlet obstruction (BOO) phenotype not observed in treated wild-type (WT) mice. Thus, we hypothesized that 12.1ΔMT1 is a novel model for studying the hormonal requirement for BOO induction. Adult male 12.1ΔMT1 and WT mice were treated with T, E2, bisphenol A (BPA), T+E2, or T+BPA for up to 6 months. Histologic and immunohistochemical analysis of the prostate, bladder, and urethra were performed. No significant prostate pathologies were observed in WT or 12.1ΔMT1 mice treated with any of the hormone regimens. As expected, prostatic regression occurred in all E2-treated animals (WT and 12.1ΔMT1). Of great interest, despite a small prostate, 100% of E2-treated 12.1ΔMT1 mice, but only 40% of E2-treated WT mice, developed severe BOO (P<0.01). In contrast, T+E2 treatment was less effective than E2 treatment in inducing severe BOO in 12.1ΔMT1 mice (68%, P<0.05) and was completely ineffective in WT animals. Similarly, T, BPA, and T+BPA treatments did not induce BOO in either WT or 12.1ΔMT1 mice. The BOO pathology includes a thinner detrusor wall, narrowing of bladder neck and urethral lumen, and basal cell hyperplasia in the bladder body and urethra. These findings indicate that 12.1ΔMT1 mice exhibit enhanced susceptibility to E2-induced BOO that is independent of prostate enlargement but that is attenuated by the conjoint treatment with T.

Association of Streptomyces community composition determined by PCR-denaturing gradient gel electrophoresis with indoor mold status.

Both Streptomyces species and mold species have previously been isolated from moisture-damaged building materials; however, an association between these two groups of microorganisms in indoor environments is not clear. In this study, we used a culture-independent method, PCR-denaturing gradient gel electrophoresis (PCR-DGGE), to investigate the composition of the Streptomyces community in house dust. Twenty-three dust samples each from two sets of homes categorized as high-mold and low-mold based on mold-specific quantitative PCR analysis were used in the study. Taxonomic identification of prominent bands was performed by cloning and sequencing. Associations between DGGE amplicon band intensities and home mold status were assessed using univariate analyses as well as multivariate recursive partitioning (decision trees) to test the predictive value of combinations of bands intensities. In the final classification tree, a combination of two bands was significantly associated with mold status of the home (p = 0.001). The sequence corresponding to one of the bands in the final decision tree matched a group of Streptomyces species that included Streptomyces coelicolor and Streptomyces sampsonii, both of which have been isolated from moisture-damaged buildings previously. The closest match for the majority of sequences corresponding to a second band consisted of a group of Streptomyces species that included Streptomyces hygroscopicus, an important producer of antibiotics and immunosuppressors. Taken together, the study showed that DGGE can be a useful tool for identifying bacterial species that may be more prevalent in mold-damaged buildings.

Interpreting and visualizing pathway analyses using embedding representations with PAVER.

Omics studies use large-scale high-throughput data to explain changes underlying different traits or conditions. However, omics analysis often results in long lists of pathways that are difficult to interpret. Therefore, it is of interest to describe a tool named PAVER (Pathway Analysis Visualization with Embedding Representations) for large scale genomic analysis. PAVER curates similar pathways into groups, identifies the pathway most representative of each group, and provides publication-ready intuitive visualizations. PAVER clusters pathways defined by their vector embedding representations and then identifies the term most cosine similar to its respective cluster's average embedding. PAVER can integrate multiple pathway analyses, highlight relevant biological insights, and work with any pathway database.

Accelerating drug discovery and repurposing by combining transcriptional signature connectivity with docking.

We present an in silico approach for drug discovery, dubbed connectivity enhanced structure activity relationship (ceSAR). Building on the landmark LINCS library of transcriptional signatures of drug-like molecules and gene knockdowns, ceSAR combines cheminformatic techniques with signature concordance analysis to connect small molecules and their targets and further assess their biophysical compatibility using molecular docking. Candidate compounds are first ranked in a target structure-independent manner, using chemical similarity to LINCS analogs that exhibit transcriptomic concordance with a target gene knockdown. Top candidates are subsequently rescored using docking simulations and machine learning-based consensus of the two approaches. Using extensive benchmarking, we show that ceSAR greatly reduces false-positive rates, while cutting run times by multiple orders of magnitude and further democratizing drug discovery pipelines. We further demonstrate the utility of ceSAR by identifying and experimentally validating inhibitors of BCL2A1, an important antiapoptotic target in melanoma and preterm birth-associated inflammation.

Coordinated Targeting of S6K1/2 and AXL Disrupts Pyrimidine Biosynthesis in PTEN-Deficient Glioblastoma.

Intrinsic resistance to targeted therapeutics in PTEN-deficient glioblastoma (GBM) is mediated by redundant signaling networks that sustain critical metabolic functions. Here, we demonstrate that coordinated inhibition of the ribosomal protein S6 kinase 1 (S6K1) and the receptor tyrosine kinase AXL using LY-2584702 and BMS-777607 can overcome network redundancy to reduce GBM tumor growth. This combination of S6K1 and AXL inhibition suppressed glucose flux to pyrimidine biosynthesis. Genetic inactivation studies to map the signaling network indicated that both S6K1 and S6K2 transmit growth signals in PTEN-deficient GBM. Kinome-wide ATP binding analysis in inhibitor-treated cells revealed that LY-2584702 directly inhibited S6K1, and substrate phosphorylation studies showed that BMS-777607 inactivation of upstream AXL collaborated to reduce S6K2-mediated signal transduction. Thus, combination targeting of S6K1 and AXL provides a kinase-directed therapeutic approach that circumvents signal transduction redundancy to interrupt metabolic function and reduce growth of PTEN-deficient GBM. SIGNIFICANCE: Therapy for glioblastoma would be advanced by incorporating molecularly targeted kinase-directed agents, similar to standard of care strategies in other tumor types. Here, we identify a kinase targeting approach to inhibit the metabolism and growth of glioblastoma.

Copper drives remodeling of metabolic state and progression of clear cell renal cell carcinoma.

Copper (Cu) is an essential trace element required for mitochondrial respiration. Late-stage clear cell renal cell carcinoma (ccRCC) accumulates Cu and allocates it to mitochondrial cytochrome c oxidase. We show that Cu drives coordinated metabolic remodeling of bioenergy, biosynthesis and redox homeostasis, promoting tumor growth and progression of ccRCC. Specifically, Cu induces TCA cycle-dependent oxidation of glucose and its utilization for glutathione biosynthesis to protect against H 2 O 2 generated during mitochondrial respiration, therefore coordinating bioenergy production with redox protection. scRNA-seq determined that ccRCC progression involves increased expression of subunits of respiratory complexes, genes in glutathione and Cu metabolism, and NRF2 targets, alongside a decrease in HIF activity, a hallmark of ccRCC. Spatial transcriptomics identified that proliferating cancer cells are embedded in clusters of cells with oxidative metabolism supporting effects of metabolic states on ccRCC progression. Our work establishes novel vulnerabilities with potential for therapeutic interventions in ccRCC. Accumulation of copper is associated with progression and relapse of ccRCC and drives tumor growth.Cu accumulation and allocation to cytochrome c oxidase (CuCOX) remodels metabolism coupling energy production and nucleotide biosynthesis with maintenance of redox homeostasis.Cu induces oxidative phosphorylation via alterations in the mitochondrial proteome and lipidome necessary for the formation of the respiratory supercomplexes. Cu stimulates glutathione biosynthesis and glutathione derived specifically from glucose is necessary for survival of Cu Hi cells. Biosynthesis of glucose-derived glutathione requires activity of glutamyl pyruvate transaminase 2, entry of glucose-derived pyruvate to mitochondria via alanine, and the glutamate exporter, SLC25A22. Glutathione derived from glucose maintains redox homeostasis in Cu-treated cells, reducing Cu-H 2 O 2 Fenton-like reaction mediated cell death. Progression of human ccRCC is associated with gene expression signature characterized by induction of ETC/OxPhos/GSH/Cu-related genes and decrease in HIF/glycolytic genes in subpopulations of cancer cells. Enhanced, concordant expression of genes related to ETC/OxPhos, GSH, and Cu characterizes metabolically active subpopulations of ccRCC cells in regions adjacent to proliferative subpopulations of ccRCC cells, implicating oxidative metabolism in supporting tumor growth.

Canonical Bcl-2 motifs of the Na+/K+ pump revealed by the BH3 mimetic chelerythrine: early signal transducers of apoptosis?

BACKGROUND/AIMS: Chelerythrine [CET], a protein kinase C [PKC] inhibitor, is a prop-apoptotic BH3-mimetic binding to BH1-like motifs of Bcl-2 proteins. CET action was examined on PKC phosphorylation-dependent membrane transporters (Na+/K+ pump/ATPase [NKP, NKA], Na+-K+-2Cl+ [NKCC] and K+-Cl- [KCC] cotransporters, and channel-supported K+ loss) in human lens epithelial cells [LECs]. METHODS: K+ loss and K+ uptake, using Rb+ as congener, were measured by atomic absorption/emission spectrophotometry with NKP and NKCC inhibitors, and Cl- replacement by NO3ˉ to determine KCC. 3H-Ouabain binding was performed on a pig renal NKA in the presence and absence of CET. Bcl-2 protein and NKA sequences were aligned and motifs identified and mapped using PROSITE in conjunction with BLAST alignments and analysis of conservation and structural similarity based on prediction of secondary and crystal structures. RESULTS: CET inhibited NKP and NKCC by >90% (IC50 values ~35 and ~15 µM, respectively) without significant KCC activity change, and stimulated K+ loss by ~35% at 10-30 µM. Neither ATP levels nor phosphorylation of the NKA α1 subunit changed. 3H-ouabain was displaced from pig renal NKA only at 100 fold higher CET concentrations than the ligand. Sequence alignments of NKA with BH1- and BH3-like motifs containing pro-survival Bcl-2 and BclXl proteins showed more than one BH1-like motif within NKA for interaction with CET or with BH3 motifs. One NKA BH1-like motif (ARAAEILARDGPN) was also found in all P-type ATPases. Also, NKA possessed a second motif similar to that near the BH3 region of Bcl-2. CONCLUSION: Findings support the hypothesis that CET inhibits NKP by binding to BH1-like motifs and disrupting the α1 subunit catalytic activity through conformational changes. By interacting with Bcl-2 proteins through their complementary BH1- or BH3-like-motifs, NKP proteins may be sensors of normal and pathological cell functions, becoming important yet unrecognized signal transducers in the initial phases of apoptosis. CET action on NKCC1 and K+ channels may involve PKC-regulated mechanisms; however, limited sequence homologies to BH1-like motifs cannot exclude direct effects.

Rotavirus VP8*: phylogeny, host range, and interaction with histo-blood group antigens.

The distal portion of rotavirus (RV) VP4 spike protein (VP8*) is implicated in binding to cellular receptors, thereby facilitating viral attachment and entry. While VP8* of some animal RVs engage sialic acid, human RVs often attach to and enter cells in a sialic acid-independent manner. A recent study demonstrated that the major human RVs (P[4], P[6], and P[8]) recognize human histo-blood group antigens (HBGAs). In this study, we performed a phylogenetic analysis of RVs and showed further variations of RV interaction with HBGAs. On the basis of the VP8* sequences, RVs are grouped into five P genogroups (P[I] to P[V]), of which P[I], P[IV], and P[V] mainly infect animals, P[II] infects humans, and P[III] infects both animals and humans. The sialic acid-dependent RVs (P[1], P[2], P[3], and P[7]) form a subcluster within P[I], while all three major P genotypes of human RVs (P[4], P[6], and P[8]) are clustered in P[II]. We then characterized three human RVs (P[9], P[14], and P[25]) in P[III] and observed a new pattern of binding to the type A antigen which is distinct from that of the P[II] RVs. The binding was demonstrated by hemagglutination and saliva binding assay using recombinant VP8* and native RVs. Homology modeling and mutagenesis study showed that the locations of the carbohydrate binding interfaces are shared with the sialic acid-dependent RVs, although different amino acids are involved. The P[III] VP8* proteins also bind the A antigens of the porcine and bovine mucins, suggesting the A antigen as a possible factor for cross-species transmission of RVs. Our study suggests that HBGAs play an important role in RV infection and evolution.

Hypomorphic mutations in PRF1, MUNC13-4, and STXBP2 are associated with adult-onset familial HLH.

Familial hemophagocytic lymphohistiocytosis (HLH) is a rare primary immunodeficiency disorder characterized by defects in cell-mediated cytotoxicity that results in fever, hepatosplenomegaly, and cytopenias. Familial HLH is well recognized in children but rarely diagnosed in adults. We conducted a retrospective review of genetic and immunologic test results in patients who developed HLH in adulthood. Included in our study were 1531 patients with a clinical diagnosis of HLH; 175 patients were 18 years or older. Missense and splice-site sequence variants in PRF1, MUNC13-4, and STXBP2 were found in 25 (14%) of the adult patients. The A91V-PRF1 genotype was found in 12 of these patients (48%). The preponderance of hypomorphic mutations in familial HLH-causing genes correlates with the later-onset clinical symptoms and the more indolent course in adult patients. We conclude that late-onset familial HLH occurs more commonly than was suspected previously.

The active kinome: The modern view of how active protein kinase networks fit in biological research.

Biological regulatory networks are dynamic, intertwined, and complex systems making them challenging to study. While quantitative measurements of transcripts and proteins are key to investigate the state of a biological system, they do not inform the "active" state of regulatory networks. In consideration of that fact, "functional" proteomics assessments are needed to decipher active regulatory processes. Phosphorylation, a key post-translation modification, is a reversible regulatory mechanism that controls the functional state of proteins. Recent advancements of high-throughput protein kinase activity profiling platforms allow for a broad assessment of protein kinase networks in complex biological systems. In conjunction with sophisticated computational modeling techniques, these profiling platforms provide datasets that inform the active state of regulatory systems in disease models and highlight potential drug targets. Taken together, system-wide profiling of protein kinase activity has become a critical component of modern molecular biology research and presents a promising avenue for drug discovery.