The insulin-responsive 12-transmembrane transporter GLUT4 changes conformation between an inward-open state and an outward-open state to actively facilitate cellular glucose uptake. Because of the difficulties of generating conformational mAbs against complex and highly conserved membrane proteins, no reliable tools exist to measure GLUT4 at the cell surface, follow its trafficking, or detect the conformational state of the protein. Here we report the isolation and characterization of conformational mAbs that recognize the extracellular and intracellular domains of GLUT4, including mAbs that are specific for the inward-open and outward-open states of GLUT4. mAbs against GLUT4 were generated using virus-like particles to present this complex membrane protein in its native conformation and using a divergent host species (chicken) for immunization to overcome immune tolerance. As a result, the isolated mAbs recognize conformational epitopes on native GLUT4 in cells, with apparent affinities as high as 1 pM and with specificity for GLUT4 across the human membrane proteome. Epitope mapping using shotgun mutagenesis alanine scanning across the 509 amino acids of GLUT4 identified the binding epitopes for mAbs specific for the states of GLUT4 and allowed the comprehensive identification of the residues that functionally control the GLUT4 inward-open and outward-open states. The mAbs identified here will be valuable molecular tools for monitoring GLUT4 structure, function, and trafficking, for differentiating GLUT4 conformational states, and for the development of novel therapeutics for the treatment of diabetes.

Single-chain formats of TNF-related apoptosis inducing ligand (scTRAIL) can serve as effector components of tumour-associated antigen-targeted as well as non-targeted fusion proteins, being characterized by high tumour cell-specific induction of apoptosis through death receptor activation. We studied the suitability of immunoglobulin G as a scaffold for oligovalent and bispecific TRAIL fusion proteins. Thus, we developed novel targeted hexa- and dodecavalent IgG-scTRAIL molecules by fusing scTRAIL to the C-terminus of either light (LC-scTRAIL) or heavy immunoglobulin chain (HC-scTRAIL), or to both ends (LC/HC-scTRAIL) of the anti-EGFR IgG antibody hu225. The binding specificity to EGFR and death receptors was retained in all IgG-scTRAIL formats and translated into high antigen-specific bioactivity on EGFR-positive Colo205, HCT116 and WM1366 tumour cell lines, with or without sensitization to apoptosis by bortezomib. In vivo, therapeutic potential was assessed for one of the targeted variants, HC-scTRAIL, compared to the non-targeted Fc-scTRAIL. Both molecules showed a significant reduction of tumour volume and synergism with a Smac mimetic in a Colo205 xenograft tumour model. The IgG-scTRAIL format allows directing a defined, highly bioactive form of TRAIL to a wide variety of tumour antigens, enabling customized solutions for a patient-specific targeted cancer therapy with a reduced risk of side effects.

The proteolysis-assisted protein quality control system guards the proteome from potentially detrimental aberrant proteins. How miscellaneous defective proteins are specifically eliminated and which molecular characteristics direct them for removal are fundamental questions. We reveal a mechanism, DesCEND (destruction via C-end degrons), by which CRL2 ubiquitin ligase uses interchangeable substrate receptors to recognize the unusual C termini of abnormal proteins (i.e., C-end degrons). C-end degrons are mostly less than ten residues in length and comprise a few indispensable residues along with some rather degenerate ones. The C-terminal end position is essential for C-end degron function. Truncated selenoproteins generated by translation errors and the USP1 N-terminal fragment from post-translational cleavage are eliminated by DesCEND. DesCEND also targets full-length proteins with naturally occurring C-end degrons. The C-end degron in DesCEND echoes the N-end degron in the N-end rule pathway, highlighting the dominance of protein "ends" as indicators for protein elimination.

SugarQb (www.imba.oeaw.ac.at/sugarqb) is a freely available collection of computational tools for the automated identification of intact glycopeptides from high-resolution HCD MS/MS datasets in the Proteome Discoverer environment. We report the migration of SugarQb to the latest and free version of Proteome Discoverer 2.1, and apply it to the analysis of PNGase F-resistant N-glycopeptides from mouse embryonic stem cells. The analysis of intact glycopeptides highlights unexpected technical limitations to PNGase F-dependent glycoproteomic workflows at the proteome level, and warrants a critical reinterpretation of seminal datasets in the context of N-glycosylation-site prediction.

Most glycoproteins and biological protein samples undergo both O- and N-glycosylation, making characterization of their structures very complicated and time-consuming. Nevertheless, to fully understand the biological functions of glycosylation, both the glycosylation forms need to be analyzed. Herein we report a versatile, convenient one-pot method in which O- and N-glycans are simultaneously released from glycoproteins and chromogenically labeled in situ and thus available for further characterization. In this procedure, glycoproteins are incubated with 1-phenyl-3-methyl-5-pyrazolone (PMP) in aqueous ammonium hydroxide, making O-glycans released from protein backbones by β-elimination and N-glycans liberated by alkaline hydrolysis. The released glycans are promptly derivatized with PMP in situ by Knoevenagel condensation and Michael addition, with peeling degradation almost completely prevented. The recovered mixture of O- and N-glycans as bis-PMP derivatives features strong ultraviolet (UV) absorbing ability and hydrophobicity, allowing for high-resolution chromatographic separation and high-sensitivity spectrometric detection. Using this technique, O- and N-glycans were simultaneously prepared from some model glycoproteins and complex biological samples, without significant peeling, desialylation, deacetylation, desulfation or other side-reactions, and then comprehensively analyzed by online HILIC-UV-ESI-MS/MS and RP-HPLC-UV-ESI-MS/MS, with which some novel O- and N-glycan structures were first found. This method provides a simple, versatile strategy for high-throughput glycomics analysis.

Bioorthogonal tools enable cell-type-specific proteomics, a prerequisite to understanding biological processes in multicellular organisms. Here we report two engineered aminoacyl-tRNA synthetases for mammalian bioorthogonal labeling: a tyrosyl ( ScTyrY43G) and a phenylalanyl ( MmPheT413G) tRNA synthetase that incorporate azide-bearing noncanonical amino acids specifically into the nascent proteomes of host cells. Azide-labeled proteins are chemoselectively tagged via azide-alkyne cycloadditions with fluorophores for imaging or affinity resins for mass spectrometric characterization. Both mutant synthetases label human, hamster, and mouse cell line proteins and selectively activate their azido-bearing amino acids over 10-fold above the canonical. ScTyrY43G and MmPheT413G label overlapping but distinct proteomes in human cell lines, with broader proteome coverage upon their coexpression. In mice, ScTyrY43G and MmPheT413G label the melanoma tumor proteome and plasma secretome. This work furnishes new tools for mammalian residue-specific bioorthogonal chemistry, and enables more robust and comprehensive cell-type-specific proteomics in live mammals.

Mass-spectrometry-based proteomics has become the standard approach for identifying and quantifying proteins. A vital step consists of analyzing experimentally generated mass spectra to identify the underlying peptide sequences for later mapping to the originating proteins. We here present the latest developments in SearchGUI, a common open-source interface for the most frequently used freely available proteomics search and de novo engines that has evolved into a central component in numerous bioinformatics workflows.

PURPOSE: In Trinidad and Tobago (TT), prostate cancer (CaP) is the most commonly diagnosed malignancy and the leading cause of cancer deaths among men. TT currently has one of the highest CaP mortality rates in the world. METHODS: 6,064 incident and 3,704 mortality cases of CaP occurring in TT from January 1995 to 31 December 2009 reported to the Dr. Elizabeth Quamina Cancer population-based cancer registry for TT, were analyzed to examine CaP survival, incidence, and mortality rates and trends by ancestry and geography. RESULTS: The age-standardized CaP incidence and mortality rates (per 100,000) based on the 1960 world-standardized in 2009 were 64.2 and 47.1 per 100,000. The mortality rate in TT increased between 1995 (37.9 per 100,000) and 2009 (79.4 per 100,000), while the rate in the US decreased from 37.3 per 100,000 to 22.1 per 100,000 over the same period. Fewer African ancestry patients received treatment relative to those of Indian and mixed ancestry (45.7%, 60.3%, and 60.9%, respectively). CONCLUSIONS: Notwithstanding the limitations surrounding data quality, our findings highlight the increasing burden of CaP in TT and the need for improved surveillance and standard of care. Our findings highlight the need for optimized models to project cancer rates in developing countries like TT. This study also provides the rationale for targeted screening and optimized treatment for CaP to ameliorate the rates we report.

Comparing metagenomic samples is crucial for understanding microbial communities. For different groups of microbial communities, such as human gut metagenomic samples from patients with a certain disease and healthy controls, identifying group-specific sequences offers essential information for potential biomarker discovery. A sequence that is present, or rich, in one group, but absent, or scarce, in another group is considered "group-specific" in our study. Our main purpose is to discover group-specific sequence regions between control and case groups as disease-associated markers. We developed a long k-mer (k ≥ 30 bps)-based computational pipeline to detect group-specific sequences at strain resolution free from reference sequences, sequence alignments, and metagenome-wide de novo assembly. We called our method MetaGO: Group-specific oligonucleotide analysis for metagenomic samples. An open-source pipeline on Apache Spark was developed with parallel computing. We applied MetaGO to one simulated and three real metagenomic datasets to evaluate the discriminative capability of identified group-specific markers. In the simulated dataset, 99.11% of group-specific logical 40-mers covered 98.89% disease-specific regions from the disease-associated strain. In addition, 97.90% of group-specific numerical 40-mers covered 99.61 and 96.39% of differentially abundant genome and regions between two groups, respectively. For a large-scale metagenomic liver cirrhosis (LC)-associated dataset, we identified 37,647 group-specific 40-mer features. Any one of the features can predict disease status of the training samples with the average of sensitivity and specificity higher than 0.8. The random forests classification using the top 10 group-specific features yielded a higher AUC (from ∼0.8 to ∼0.9) than that of previous studies. All group-specific 40-mers were present in LC patients, but not healthy controls. All the assembled 11 LC-specific sequences can be mapped to two strains of Veillonella parvula: UTDB1-3 and DSM2008. The experiments on the other two real datasets related to Inflammatory Bowel Disease and Type 2 Diabetes in Women consistently demonstrated that MetaGO achieved better prediction accuracy with fewer features compared to previous studies. The experiments showed that MetaGO is a powerful tool for identifying group-specific k-mers, which would be clinically applicable for disease prediction. MetaGO is available at https://github.com/VVsmileyx/MetaGO.

Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks.Summary: We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding.

Rising evidence has shown the development of resistance to vascular endothelial growth factor receptor (VEGFR) inhibitors in the practices of cancer therapy. It is reported that the efficacy of axitinib (AX), a VEGFR inhibitor, is limited in the treatment of breast cancer as a single agent or in combination with other chemotherapeutic drugs due to the probability of rising population of cancer stem-like cells (CSCs) caused by AX. The present study evaluated the effect of dopamine (DA) improving AX's efficacy on MCF-7/ADR breast cancer in vitro and in vivo, and developed a pharmacokinetic-pharmacodynamic (PK-PD) model describing the in vivo experimental data and characterizing the interaction of effect between AX and DA. The results showed that AX up-regulated the expression of breast CSC (BCSC) markers (CD44+/CD24-/low) in vivo, and DA significantly synergized the inhibitory effect on tumor growth by deducting the BCSC frequency. The PK-PD model quantitatively confirmed the synergistic interaction with the parameter estimate of interaction factor ψ 2.43. The dose regimen was optimized as 60 mg/kg AX i.g. b.i.d. combined with 50 mg/kg DA i.p. q3d in the simulation study on the basis of the PK-PD model. The model where DA synergistically enhances the effect of AX in an all-or-none manner provides a possible solution in modeling the agents like DA. Moreover, the outcome of AX and DA combination therapy in MCF-7/ADR breast cancer provided further insight of co-administering DA in the treatment of the possible CSC-causing AX-resisting breast cancer. And this combination therapy has the prospect of clinical translation.

Glioblastoma, the most malignant brain cancer, contains self-renewing, stem-like cells that sustain tumor growth and therapeutic resistance. Identifying genes promoting stem-like cell differentiation might unveil targets for novel treatments. To detect them, here we apply SWIM - a software able to unveil genes (named switch genes) involved in drastic changes of cell phenotype - to public datasets of gene expression profiles from human glioblastoma cells. By analyzing matched pairs of stem-like and differentiated glioblastoma cells, SWIM identified 336 switch genes, potentially involved in the transition from stem-like to differentiated state. A subset of them was significantly related to focal adhesion and extracellular matrix and strongly down-regulated in stem-like cells, suggesting that they may promote differentiation and restrain tumor growth. Their expression in differentiated cells strongly correlated with the down-regulation of transcription factors like OLIG2, POU3F2, SALL2, SOX2, capable of reprogramming differentiated glioblastoma cells into stem-like cells. These findings were corroborated by the analysis of expression profiles from glioblastoma stem-like cell lines, the corresponding primary tumors, and conventional glioma cell lines. Switch genes represent a distinguishing feature of stem-like cells and we are persuaded that they may reveal novel potential therapeutic targets worthy of further investigation.

In this study, we aimed to identify differentially accumulated proteins (DAPs) involved in PEG mock osmotic stress, cadmium (Cd2+) stress, and their combined stress responses in Brachypodium distachyon seedling roots. The results showed that combined PEG and Cd2+ stresses had more significant effects on Brachypodium seedling root growth, physiological traits, and ultrastructures when compared with each individual stress. Totally, 106 DAPs were identified that are responsive to individual and combined stresses in roots. These DAPs were mainly involved in energy metabolism, detoxification and stress defense and protein metabolism. Principal component analysis revealed that DAPs from Cd2+ and combined stress treatments were grouped closer than those from osmotic stress treatment, indicating that Cd2+ and combined stresses had more severe influences on the root proteome than osmotic stress alone. Protein-protein interaction analyses highlighted a 14-3-3 centered sub-network that synergistically responded to osmotic and Cd2+ stresses and their combined stresses. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis of 14 key DAP genes revealed that most genes showed consistency between transcriptional and translational expression patterns. A putative pathway of proteome metabolic changes in Brachypodium seedling roots under different stresses was proposed, which revealed a complicated synergetic responsive network of plant roots to adverse environments.

This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to "prune" the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF "N-specificity" index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs-CRF4, SNZ, CDF1, HHO5/6, and PHL1-validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15NO3- uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal "transcriptional logic" for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine.

Several regulators of SUMOylation have been previously linked to senescence but most targets of this modification in senescent cells remain unidentified. Using a two-step purification of a modified SUMO3, we profiled the SUMO proteome of senescent cells in a site-specific manner. We identified 25 SUMO sites on 23 proteins that were significantly regulated during senescence. Of note, most of these proteins were PML nuclear body (PML-NB) associated, which correlates with the increased number and size of PML-NBs observed in senescent cells. Interestingly, the sole SUMO E2 enzyme, UBC9, was more SUMOylated during senescence on its Lys-49. Functional studies of a UBC9 mutant at Lys-49 showed a decreased association to PML-NBs and the loss of UBC9's ability to delay senescence. We thus propose both pro- and anti-senescence functions of protein SUMOylation.

Type 1 T helper (Th1) cells play a critical role in host defense against intracellular pathogens and in autoimmune diseases by producing a key inflammatory cytokine interferon (IFN)-γ; some Th1 cells can also be antiinflammatory through producing IL-10. However, the molecular switch for regulating the differentiation of inflammatory and antiinflammatory Th1 cells is still elusive. Here, we show that Bhlhe40-deficient CD4 Th1 cells produced less IFN-γ but substantially more IL-10 than wild-type Th1 cells both in vitro and in vivo. Bhlhe40-mediated IFN-γ production was independent of transcription factor T-bet regulation. Mice with conditional deletion of Bhlhe40 in T cells succumbed to Toxoplasma gondii infection, and blockade of IL-10 signaling during infection rescued these mice from death. Thus, our results demonstrate that transcription factor Bhlhe40 is a molecular switch for determining the fate of inflammatory and antiinflammatory Th1 cells.

To answer the question of how brain pathology affects reasoning about negative emotional content, we administered a disjunctive logical reasoning task involving arguments with neutral content (e.g. Either there are tigers or women in NYC, but not both; There are no tigers in NYC; There are women in NYC) and emotionally laden content (e.g. Either there are pedophiles or politicians in Texas, but not both; There are politicians in Texas; There are no pedophiles in Texas) to 92 neurological patients with focal lesions to various parts of the brain. A Voxel Lesion Symptom Mapping (VLSM) analysis identified 16 patients, all with lesions to the orbital polar prefrontal cortex (BA 10 & 11), as being selectively impaired in the emotional reasoning condition. Another 17 patients, all with lesions to the parietal cortex, were identified as being impaired in the neutral content condition. The reasoning scores of these two patient groups, along with 23 matched normal controls, underwent additional analysis to explore the effect of belief bias. This analysis revealed that the differences identified above were largely driven by trials where there was an incongruency between the believability of the conclusion and the validity of the argument (i.e. valid argument /false conclusion or invalid argument /true conclusion). Patients with lesions to polar orbital prefrontal cortex underperformed in incongruent emotional content trials and over performed in incongruent neutral content trials (compared to both normal controls and patients with parietal lobe lesions). Patients with lesions to parietal lobes underperformed normal controls (at a trend level) in neutral trials where there was a congruency between the believability of the conclusion and the validity of the argument (i.e. valid argument/true conclusion or invalid argument/false conclusion). We conclude that lesions to the polar orbital prefrontal cortex (i) prevent these patients from enjoying any emotionally induced cognitive boost, and (ii) block the belief bias processing route in the neutral condition. Lesions to parietal lobes result in a generalized impairment in logical reasoning with neutral content.

The chromokinesin Kif4A controls proper chromosome condensation, congression/alignment, and cytokinesis to ensure faithful genetic inheritance. Here, we report that Cdk phosphorylation of human Kif4A at T1161 licenses Kif4A chromosomal localization, which, in turn, controls Kif4A early mitotic function. Phosphorylated Kif4A (Kif4AWT) or Cdk phospho-mimetic Kif4A mutant (Kif4ATE) associated with chromosomes and condensin I (non-SMC subunit CAP-G and core subunit SMC2) to regulate chromosome condensation, spindle morphology, and chromosome congression/alignment in early mitosis. In contrast, Cdk non-phosphorylatable Kif4A mutant (Kif4ATA) could neither localize on chromosomes nor associate with CAP-G and SMC2. Furthermore, Kif4ATA could not rescue defective chromosome condensation, spindle morphology, or chromosome congression/alignment in cells depleted of endogenous Kif4A, which activated a mitotic checkpoint and delayed early mitotic progression. However, targeting Kif4ATA to chromosomes by fusion of Kif4ATA with Histone H1 resulted in restoration of chromosome and spindle functions of Kif4A, similar to Kif4AWT and Kif4ATE, in cells depleted of endogenous Kif4A. Thus, our results demonstrate that Cdk phosphorylation-licensed chromosomal localization of Kif4A plays a critical role in regulating early mitotic functions of Kif4A that are important for early mitotic progression.

Motivation: The rapid advancement of single cell technologies has shed new light on the complex mechanisms of cellular heterogeneity. Identification of intercellular transcriptomic heterogeneity is one of the most critical tasks in single-cell RNA-sequencing studies. Results: We propose a new cell similarity measure based on cell-pair differentiability correlation, which is derived from gene differential pattern among all cell pairs. Through plugging into the framework of hierarchical clustering with this new measure, we further develop a variance analysis based clustering algorithm 'Corr' that can determine cluster number automatically and identify cell types accurately. The robustness and superiority of the proposed algorithm are compared with representative algorithms: SNN-Cliq and several other state-of-the-art clustering methods, on many benchmark or real scRNA-Seq datasets in terms of both internal criteria (clustering number and accuracy) and external criteria (purity, adjusted rand index, F1-measure). Moreover, differentiability vector with our new measure provides a new means in identifying potential biomarkers from cancer related single cell data sets even with strong noise. Prognosis analyses from independent datasets of cancers confirmed the effectiveness of our 'Corr' method. Implementation and Availability: The source code (Matlab) is available at http://sysbio.sibcb.ac.cn/cb/chenlab/soft/Corr-SourceCodes.zip. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

Fufang Danshen (FFDS or Compound Danshen) consists of three Chinese herbs Danshen (Salviae miltiorrhizae radix et rhizome), Sanqi (Notoginseng radix et rhizome) and Tianranbingpian (Borneolum, or D-borneol), which has been show to significantly improve the function of the nervous system and brain metabolism. In this study we explored the possible mechanisms underlying the therapeutic effects of the combination of the effective components of FFDS (Tan IIA, NG-R1 and Borneol) in the treatment of Alzheimer's disease (AD) based on network pharmacology. We firstly constructed AD-related FFDS component protein interaction networks, and revealed that macrophage migration inhibitory factor (MIF) might regulate neuronal apoptosis through Bad in the progression of AD. Then we investigated the apoptosis-inducing effects of MIF and the impact of the effective components of FFDS in human neuroblastoma SH-SY5Y cells. We observed the characteristics of a "Pendular state" of MIF, where MIF (8 ng/mL) increased the ratio of p-Bad/Bad by activating Akt and the IKKα/β signaling pathway to assure cell survival, whereas MIF (50 ng/mL) up-regulated the expression of Bad to trigger apoptosis of SH-SY5Y cells. MIF displayed neurotoxicity similar to Aβ1-42, which was associated with the MIF-induced increased expression of Bad. Application of the FFDS composite solution significantly decreased the expression levels of Bad, suppressed MIF-induced apoptosis in SH-SY5Y cells. In a D-galactose- and AlCl3-induced AD mouse model, administration of the FFDS composite solution significantly improved the learning and memory, as well as neuronal morphology, and decreased the serum levels of INF-γ. Therefore, the FFDS composite solution exerts neuroprotective effects through down-regulating the level of Bad stimulated by MIF.

The rat cardiomyoblast cell line H9C2 has emerged as a valuable tool for studying cardiac development, mechanisms of disease and toxicology. We present here a rigorous proteomic analysis that monitored the changes in protein expression during differentiation of H9C2 cells into cardiomyocyte-like cells over time. Quantitative mass spectrometry followed by gene ontology (GO) enrichment analysis revealed that early changes in H9C2 differentiation are related to protein pathways of cardiac muscle morphogenesis and sphingolipid synthesis. These changes in the proteome were followed later in the differentiation time-course by alterations in the expression of proteins involved in cation transport and beta-oxidation. Studying the temporal profile of the H9C2 proteome during differentiation in further detail revealed eight clusters of co-regulated proteins that can be associated with early, late, continuous and transient up- and downregulation. Subsequent reactome pathway analysis based on these eight clusters further corroborated and detailed the results of the GO analysis. Specifically, this analysis confirmed that proteins related to pathways in muscle contraction are upregulated early and transiently, and proteins relevant to extracellular matrix organization are downregulated early. In contrast, upregulation of proteins related to cardiac metabolism occurs at later time points. Finally, independent validation of the proteomics results by immunoblotting confirmed hereto unknown regulators of cardiac structure and ionic metabolism. Our results are consistent with a 'function follows form' model of differentiation, whereby early and transient alterations of structural proteins enable subsequent changes that are relevant to the characteristic physiology of cardiomyocytes.

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because they are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.

To date, the most effective treatment of HIV-1 is a combination antiretroviral therapy (cART), which reduces viral replication and reverses pathology. We investigated the effect of cART (RT and protease inhibitors) on the content of extracellular vesicles (EVs) released from HIV-1-infected cells. We have previously shown that EVs contain non-coding HIV-1 RNA, which can elicit responses in recipient cells. In this manuscript, we show that TAR RNA levels demonstrate little change with the addition of cART treatment in cell lines, primary macrophages, and patient biofluids. We determined possible mechanisms involved in the selective packaging of HIV-1 RNA into EVs, specifically an increase in EV-associated hnRNP A2/B1. More recent experiments have shown that several other FDA-approved drugs have the ability to alter the content of exosomes released from HIV-1-infected cells. These findings on cART-altered EV content can also be applied to general viral inhibitors (interferons) which are used to treat other chronic infections. Additionally, we describe unique mechanisms of ESCRT pathway manipulation by antivirals, specifically the targeting of VPS4. Collectively, these data imply that, despite antiretroviral therapy, EVs containing viral products are continually released and may cause neurocognitive and immunological dysfunction.

Protein Phosphatase 1 (PP1) is a serine/threonine phosphatase which has been implicated in the regulation of a number of viruses including HIV-1, Ebolavirus and Rift Valley fever virus. Catalytic subunits of PP1 (PP1α, PP1β, or PP1γ) interact with a host of regulatory subunits and target a wide variety of cellular substrates through a combination of short binding motifs, including an RVxF motif present in the majority of PP1 regulatory subunits. Targeting the RVxF interacting site on PP1 with the small molecule, 1E7-03 inhibits HIV-1, Ebolavirus, and Rift Valley fever virus replication. Here we determined the effect of PP1 on Venezuelan equine encephalitis virus (VEEV) replication. Treatment of VEEV infected cells with 1E7-03 decreased viral replication by over 2 logs (EC50=0.6 μM). 1E7-03 treatment reduced viral titers starting at 8 hours post infection. Viral replication was also decreased after treatment with PP1α-targeting siRNA. Confocal microscopy demonstrated that PP1α shuttles toward the cytosol during infection with VEEV and that PP1α colocalizes with VEEV capsid. Co-immunoprecipitation experiments confirmed VEEV capsid interacting with PP1α. Furthermore, immunoprecipitation and mass spectrometry data showed that VEEV capsid is phosphorylated and that phosphorylation is moderated by PP1α. Finally, less viral RNA is associated with capsid after treatment with 1E7-03. Coupled with data that shows 1E7-03 inhibits several alphaviruses, this study indicates that inhibition of the PP1α RVxF binding pocket is a promising therapeutic target and provides novel evidence that PP1α modulation of VEEV capsid phosphorylated influences viral replication.ImportanceVenezuelan equine encephalitis virus (VEEV) causes moderate flu-like symptoms and can lead to severe encephalitic disease and potentially death. There are no currently FDA approved therapeutics or vaccines for human use and understanding the molecular underpinning of host:virus interactions can aid in the rational design of intervention strategies. The significance of our research is in identifying the interaction between Protein Phosphatase 1 (PP1) and the viral capsid protein. This interaction is important for viral replication as inhibition of PP1 results in decrease viral replication. Inhibition of PP1 also inhibited multiple biomedically important alphaviruses, indicating PP1 may be a potential therapeutic target for alphavirus induced disease.

Transcription is a highly regulated and inherently stochastic process. The complexity of signal transduction and gene regulation makes it challenging to analyze how the dynamic activity of transcriptional regulators affects stochastic transcription. By combining a fast-acting, photo-regulatable transcription factor with nascent RNA quantification in live cells and an experimental setup for precise spatiotemporal delivery of light inputs, we constructed a platform for the real-time, single-cell interrogation of transcription in Saccharomyces cerevisiae. We show that transcriptional activation and deactivation are fast and memoryless. By analyzing the temporal activity of individual cells, we found that transcription occurs in bursts, whose duration and timing are modulated by transcription factor activity. Using our platform, we regulated transcription via light-driven feedback loops at the single-cell level. Feedback markedly reduced cell-to-cell variability and led to qualitative differences in cellular transcriptional dynamics. Our platform establishes a flexible method for studying transcriptional dynamics in single cells.