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Expression of the Alzheimer's disease associated polypeptide Aβ42 and the human polypeptide hormon islet amyloid polypeptide (hIAPP) and the prohormone precursor (hproIAPP) in neurons of Drosophila melanogaster leads to the formation of protein aggregates in the fat body tissue surrounding the brain. We determined the structure of these membrane-encircled protein aggregates using transmission electron microscopy (TEM) and observed the dissolution of protein aggregates after starvation. Electron tomography (ET) as an extension of transmission electron microscopy revealed that these aggregates were comprised of granular subunits having a diameter of 20 nm aligned into highly ordered structures in all three dimensions. The three dimensional (3D) lattice of hIAPP granules were constructed of two unit cells, a body centered tetragonal (BCT) and a triclinic unit cell. A 5-fold twinned structure was observed consisting of the cyclic twinning of the BCT and triclinic unit cells. The interaction between the two nearest hIAPP granules in both unit cells is not only governed by the van der Waals forces and the dipole-dipole interaction but potentially also by filament-like structures that can connect the nearest neighbors. Hence, our 3D structural analysis provides novel insight into the aggregation process of hIAPP in the fat body tissue of Drosophila melanogaster. [ABSTRACT FROM AUTHOR]

MicroRNAs are conserved, endogenous small RNAs with critical post-transcriptional regulatory functions throughout eukaryota, including prominent roles in development and disease. Despite much effort, microRNA annotations still contain errors and are incomplete due especially to challenges related to identifying valid miRs that have small numbers of reads, to properly locating hairpin precursors and to balancing precision and recall. Here, we present miRWoods, which solves these challenges using a duplex-focused precursor detection method and stacked random forests with specialized layers to detect mature and precursor microRNAs, and has been tuned to optimize the harmonic mean of precision and recall. We trained and tuned our discovery pipeline on data sets from the well-annotated human genome, and evaluated its performance on data from mouse. Compared to existing approaches, miRWoods better identifies precursor spans, and can balance sensitivity and specificity for an overall greater prediction accuracy, recalling an average of 10% more annotated microRNAs, and correctly predicts substantially more microRNAs with only one read. We apply this method to the under-annotated genomes of Felis catus (domestic cat) and Bos taurus (cow). We identified hundreds of novel microRNAs in small RNA sequencing data sets from muscle and skin from cat, from 10 tissues from cow and also from human and mouse cells. Our novel predictions include a microRNA in an intron of tyrosine kinase 2 (TYK2) that is present in both cat and cow, as well as a family of mirtrons with two instances in the human genome. Our predictions support a more expanded miR-2284 family in the bovine genome, a larger mir-548 family in the human genome, and a larger let-7 family in the feline genome. [ABSTRACT FROM AUTHOR]

We recently introduced a MαCD-based method to efficiently replace virtually the entire population of plasma membrane outer leaflet phospholipids and sphingolipids of cultured mammalian cells with exogenous lipids (Li et al, (2016) Proc. Natl. Acad. Sci USA 113:14025–14030). Here, we show if the lipid-to- MαCD ratio is too high or low, cells can round up and develop membrane leakiness. We found that this cell damage can be reversed/prevented if cells are allowed to recover from the exchange step by incubation in complete growth medium. After exchange and transfer to complete growth medium cell growth was similar to that of untreated cells. In some cases, cell damage was also prevented by carrying out exchange at close to room temperature (rather than at 37°C). Exchange with lipids that do (sphingomyelin) or do not (unsaturated phosphatidylcholine) support a high level of membrane order in lipid vesicles had the analogous effect on plasma membrane order, confirming exogenous lipid localization in the plasma membrane. Importantly, changes in lipid composition and plasma membrane properties after exchange and recovery persisted for several hours. Thus, it should be possible to use lipid exchange to investigate the effect of plasma membrane lipid composition upon several aspects of membrane structure and function. [ABSTRACT FROM AUTHOR]

Calreticulin (CRT) is a high-capacity Ca2+ protein whose expression is up-regulated during cellular transformation and is associated with disease progression in multiple types of malignancies. At the same time, CRT has been characterized as an important stress-response protein capable of inducing immunogenic cell death (ICD) when translocated to the cell surface. It remains unclear why CRT expression is preserved by malignant cells during the course of transformation despite its immunogenic properties. In this study, we identify a novel, critical function of CRT as a cell survival factor in multiple types of human solid-tissue malignancies. CRT knockdown activates p53, which mediates cell-death response independent of executioner caspase activity and accompanied full-length poly ADP ribose polymerase (PARP) cleavage. Mechanistically, we show that down-regulation of CRT results in mitochondrial Ca2+ overload and induction of mitochondria permeability transition pore (mPTP)-dependent cell death, which can be significantly rescued by the mPTP inhibitor, Cyclosporin A (CsA). The clinical importance of CRT expression was revealed in the analysis of the large cohort of cancer patients (N = 2,058) to demonstrate that high levels of CRT inversely correlates with patient survival. Our study identifies intracellular CRT as an important therapeutic target for tumors whose survival relies on its expression. [ABSTRACT FROM AUTHOR]

We hypothesized that postnatal development of the vagina is impacted by early nutritional environment. Our objective was to determine if lipid profiles of vaginal swabs were different between postnatal gilts suckled by sow or fed milk replacer the first 48 h after birth, with or without a lard-based fat supplement. Gilts (>1.3 kg) were selected at birth across 8 litters and assigned to one of four treatments: 1) suckled by sow (S, n = 8); 2) suckled by sow plus administration of a fat supplement (SF, n = 5); 3) bottle-fed solely milk replacer (B, n = 8); or 4) bottle-fed solely milk replacer plus administration of a fat supplement (BF, n = 7). At 48 h postnatal, vaginal swabs of gilts were taken with a cytology brush, and lipids were extracted for analysis using multiple reaction monitoring (MRM)-profiling. Lipids extracted from serum collected at 48 h from gilts, milk collected at 24 h from sows, and milk replacer were also analyzed with MRM-profiling. Receiver operating characteristic curve analysis found 18 lipids recovered from vaginal swabs that highly distinguished between S and B gilts [area-under-the-curve (AUC) > 0.9], including phosphatidylethanolamine with 34 carbons and four unsaturations in the fatty acyl residues [PE (34:4)]. Twelve lipids from vaginal swabs highly correlated (r > 0.6; p < 0.01) with nutrition source. Lipids with greater abundance in milk replacer drove association. For example, mean intensity of PE (34:4) was 149-fold higher in milk replacer than colostrum. Consequently, PE (34:4) was found to have 1.6- and 2.12-fold higher levels in serum and vaginal swab samples (p < 0.001), respectively, of B gilts as compared to S gilts. Findings support that vaginal swabs can be used to noninvasively study effects of perinatal nutrition on tissue composition. [ABSTRACT FROM AUTHOR]

3′ downstream inhibitory stem plays a crucial role in locking rpoS mRNA 5' untranslated region in a self-inhibitory state. Here, we used optical tweezers to study the unfolding/refolding of rpoS inhibitory stem in the absence and presence of Mg2+. We found adding Mg2+ decreased the free energy of the RNA junction without re-arranging its secondary structure, through confirming that this RNA formed a canonical RNA three-way junction. We suspected increased free energy might change the relative orientation of different stems of rpoS and confirmed this by small angle X-ray scattering. Such changed conformation may improve Hfq-bridged annealing between sRNA and rpoS RNA inhibitory stem. We established a convenient route to analyze the changes of RNA conformation and folding dynamics by combining optical tweezers with X-ray scattering methods. This route can be easily applied in the studies of other RNA structure and ligand-RNA. [ABSTRACT FROM AUTHOR]

We show that Cohen’s Kappa and Matthews Correlation Coefficient (MCC), both extended and contrasted measures of performance in multi-class classification, are correlated in most situations, albeit can differ in others. Indeed, although in the symmetric case both match, we consider different unbalanced situations in which Kappa exhibits an undesired behaviour, i.e. a worse classifier gets higher Kappa score, differing qualitatively from that of MCC. The debate about the incoherence in the behaviour of Kappa revolves around the convenience, or not, of using a relative metric, which makes the interpretation of its values difficult. We extend these concerns by showing that its pitfalls can go even further. Through experimentation, we present a novel approach to this topic. We carry on a comprehensive study that identifies an scenario in which the contradictory behaviour among MCC and Kappa emerges. Specifically, we find out that when there is a decrease to zero of the entropy of the elements out of the diagonal of the confusion matrix associated to a classifier, the discrepancy between Kappa and MCC rise, pointing to an anomalous performance of the former. We believe that this finding disables Kappa to be used in general as a performance measure to compare classifiers. [ABSTRACT FROM AUTHOR]

Biological network figures are ubiquitous in the biology and medical literature. On the one hand, a good network figure can quickly provide information about the nature and degree of interactions between items and enable inferences about the reason for those interactions. On the other hand, good network figures are difficult to create. In this paper, we outline 10 simple rules for creating biological network figures for communication, from choosing layouts, to applying color or other channels to show attributes, to the use of layering and separation. These rules are accompanied by illustrative examples. We also provide a concise set of references and additional resources for each rule. [ABSTRACT FROM AUTHOR]

HIV-1 replicates via a low-fidelity polymerase with a high mutation rate; strong conservation of individual nucleotides is highly indicative of the presence of critical structural or functional properties. Identifying such conservation can reveal novel insights into viral behaviour. We analysed 3651 publicly available sequences for the presence of nucleic acid conservation beyond that required by amino acid constraints, using a novel scale-free method that identifies regions of outlying score together with a codon scoring algorithm. Sequences with outlying score were further analysed using an algorithm for producing local RNA folds whilst accounting for alignment properties. 11 different conserved regions were identified, some corresponding to well-known cis-acting functions of the HIV-1 genome but also others whose conservation has not previously been noted. We identify rational causes for many of these, including cis functions, possible additional reading frame usage, a plausible mechanism by which the central polypurine tract primes second-strand DNA synthesis and a conformational stabilising function of a region at the 5′ end of env. [ABSTRACT FROM AUTHOR]

Aggregation of the prion protein has strong implications in the human prion disease. Sup35p is a yeast prion, and has been used as a model protein to study the disease mechanism. We have studied the pattern of Sup35p aggregation inside live yeast cells under stress, by using confocal microscopy, fluorescence activated cell sorting and western blotting. Heat shock proteins are a family of proteins that are produced by yeast cells in response to exposure to stressful conditions. Many of the proteins behave as chaperones to combat stress-induced protein misfolding and aggregation. In spite of this, yeast also produce small molecules called osmolytes during stress. In our work, we tried to find the reason as to why yeast produce osmolytes and showed that the osmolytes are paramount to ameliorate the long-term effects of lethal stress in Saccharomyces cerevisiae, either in the presence or absence of Hsp104p. [ABSTRACT FROM AUTHOR]

Activins regulate numerous processes including inflammation and are synthesized as precursors consisting of a long N-terminal pro-region and a mature protein. Genomic human databases currently list three activin A (Act A) variants termed X1, X2 and X3. The X3 variant is the shortest, lacks N-terminal segments present in X1 and X2, and has been the focus of most past literature. Here, we asked whether these variants are expressed by human cells and tissues and what structural features are contained within their pro-regions. Human monocytic-like cells THP1 and U937 expressed X1 and X2 variants after exposure to phorbol ester or granulocyte-macrophage colony-stimulating factor, while X2 transcripts were present in placenta. Expression vectors encoding full length X2 or X3 variants resulted in production and secretion of biologically active Act A from cultured cells. Previous studies reported a putative HS-binding domain (HBD) in the X3 pro-region. Here, we identified a novel HBD with consensus HS-binding motifs near the N-terminal end of X1 and X2 pro-regions. Peptides encompassing this new domain interacted with substrate-bound HS with nanomolar affinity, while peptides from putative X3 HBD did not. In good agreement, full length X2 pro-region interacted with heparin-agarose, while the X3 pro-region did not. In sum, our study reveals that Act A variants are expressed by inflammatory cells and placenta and yield biological activity. The high affinity HBD in X1 and X2 pro-region and its absence in X3 could greatly influence overall Act A distribution, availability and activity in physiological and pathological circumstances. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant insights. Approximately 10% of the mutations are located in “patches” which are defined as the set of residues spatially in close proximity that are mutated across multiple patients. Grouping mutations as 3D patches reduces the heterogeneity across patients. There are multiple patches that are relatively small in oncogenes, whereas there are a small number of very large patches in tumor suppressors. Additionally, different patches in the same protein are often located at different domains that can mediate different functions. We stratified the patients into five groups based on their potentially affected pathways, revealed from the patient-specific subnetworks. These subnetworks were constructed by integrating mutation profiles of the patients with the interactome data. Network-guided clustering showed significant association between each group and patient survival (P-value = 0.0408). Also, each group carries a set of signature 3D mutation patches that affect predominant pathways. We integrated drug sensitivity data of GBM cell lines with the mutation patches and the patient groups to analyze the therapeutic outcome of these patches. We found that Pazopanib might be effective in Group 3 by targeting CSF1R. Additionally, inhibiting ATM that is a mediator of PTEN phosphorylation may be ineffective in Group 2. We believe that from mutations to networks and eventually to clinical and therapeutic data, this study provides a novel perspective in the network-guided precision medicine. [ABSTRACT FROM AUTHOR]

Lipocalins represent the most important protein family of the mammalian respiratory allergens. Four of the seven named dog allergens are lipocalins: Can f 1, Can f 2, Can f 4, and Can f 6. We present the structure of Can f 6 along with data on the biophysical and biological activity of this protein in comparison with other animal lipocalins. The Can f 6 structure displays the classic lipocalin calyx-shaped ligand binding cavity within a central β-barrel similar to other lipocalins. Despite low sequence identity between the different dog lipocalin proteins, there is a high degree of structural similarity. On the other hand, Can f 6 has a similar primary sequence to cat, horse, mouse lipocalins as well as a structure that may underlie their cross reactivity. Interestingly, the entrance to the ligand binding pocket is capped by a His instead of the usually seen Tyr that may help select its natural ligand binding partner. Our highly pure recombinant Can f 6 is able to bind to human IgE (hIgE) demonstrating biological antigenicity. [ABSTRACT FROM AUTHOR]

The voltage-gated potassium channel KCNQ1 (KV7.1) assembles with the KCNE1 accessory protein to generate the slow delayed rectifier current, IKS, which is critical for membrane repolarization as part of the cardiac action potential. Loss-of-function (LOF) mutations in KCNQ1 are the most common cause of congenital long QT syndrome (LQTS), type 1 LQTS, an inherited genetic predisposition to cardiac arrhythmia and sudden cardiac death. A detailed structural understanding of KCNQ1 is needed to elucidate the molecular basis for KCNQ1 LOF in disease and to enable structure-guided design of new anti-arrhythmic drugs. In this work, advanced structural models of human KCNQ1 in the resting/closed and activated/open states were developed by Rosetta homology modeling guided by newly available experimentally-based templates: X. leavis KCNQ1 and various resting voltage sensor structures. Using molecular dynamics (MD) simulations, the capacity of the models to describe experimentally established channel properties including state-dependent voltage sensor gating charge interactions and pore conformations, PIP2 binding sites, and voltage sensor–pore domain interactions were validated. Rosetta energy calculations were applied to assess the utility of each model in interpreting mutation-evoked KCNQ1 dysfunction by predicting the change in protein thermodynamic stability for 50 experimentally characterized KCNQ1 variants with mutations located in the voltage-sensing domain. Energetic destabilization was successfully predicted for folding-defective KCNQ1 LOF mutants whereas wild type-like mutants exhibited no significant energetic frustrations, which supports growing evidence that mutation-induced protein destabilization is an especially common cause of KCNQ1 dysfunction. The new KCNQ1 Rosetta models provide helpful tools in the study of the structural basis for KCNQ1 function and can be used to generate hypotheses to explain KCNQ1 dysfunction. [ABSTRACT FROM AUTHOR]

In all kingdoms of life, is used to encode hereditary information. Propagation of the genetic material between generations requires timely and accurate duplication of DNA by prior to cell division to ensure each daughter cell receives the full complement of . DNA synthesis of daughter strands starts at discrete sites, termed replication origins, and proceeds in a bidirectional manner until all genomic DNA is replicated. Despite the fundamental nature of these events, organisms have evolved surprisingly divergent strategies that control replication onset. Here, we discuss commonalities and differences in replication origin organization and recognition in the three domains of life. [ABSTRACT FROM AUTHOR]

T cells use their T-cell receptors (TCRs) to scan other cells for antigenic peptides presented by MHC molecules (pMHC). If a TCR encounters a pMHC, it can trigger a signalling pathway that could lead to the activation of the T cell and the initiation of an immune response. It is currently not clear how the binding of pMHC to the TCR initiates signalling within the T cell. One hypothesis is that conformational changes in the TCR lead to further downstream signalling. Here we investigate four different TCRs in their free state as well as in their pMHC bound state using large scale molecular simulations totalling 26 000 ns. We find that the dynamical features within TCRs differ significantly between unbound TCR and TCR/pMHC simulations. However, apart from expected results such as reduced solvent accessibility and flexibility of the interface residues, these features are not conserved among different TCR types. The presence of a pMHC alone is not sufficient to cause cross-TCR-conserved dynamical features within a TCR. Our results argue against models of TCR triggering involving conserved allosteric conformational changes. [ABSTRACT FROM AUTHOR]

The current study highlights, for the first time, cloning, overexpression and purification of the novel interferon epsilon (IFNƐ), from the Arabian camel Camelus dromedaries. The study then assesses the cytotoxicity of IFNε against two human breast cancer cell lines MDA-MB-231 and MCF-7. Full-length cDNA encoding interferon epsilon (IFNε) was isolated and cloned from the liver of the Arabian camel, C. dromedarius using reverse transcription-polymerase chain reaction. The sequence analysis of the camel IFNε cDNA showed a 582-bp open reading frame encoding a protein of 193 amino acids with an estimated molecular weight of 21.230 kDa. A BLAST search analysis revealed that the C. dromedarius IFNε shared high sequence identity with the IFN genes of other species, such as Camelus ferus, Vicugna pacos, and Homo sapiens. Expression of the camel IFNε cDNA in Escherichia coli gave a fusion protein band of 24.97 kDa after induction with either isopropyl β-D-1-thiogalactopyranoside or lactose for 5 h. Recombinant IFNε protein was overexpressed in the form of inclusion bodies that were easily solubilized and refolded using SDS and KCl. The solubilized inclusion bodies were purified to apparent homogeneity using nickel affinity chromatography. We examined the effect of IFNε on two breast cancer cell lines MDA-MB-231 and MCF-7. In both cell lines, IFNε inhibited cell survival in a dose dependent manner as observed by MTT assay, morphological changes and apoptosis assay. Caspase-3 expression level was found to be increased in MDA-MB-231 treated cells as compared to untreated cells. [ABSTRACT FROM AUTHOR]

LncRNA Prostate cancer non-coding RNA (PRNCR1) is downregulated in many types of cancer. The current case-control study was performed on 144 patients with colorectal cancer and 130 matching controls. Genotyping was performed using TaqMan assays for four Single Nucleotide Polymorphisms (SNPs) in PRNCR1. RNAsnp Web Server was used to detect variations in the secondary structure for each SNP. The genotyping analysis for SNP rs1456315 showed increased association with colorectal cancer with the homozygous CC variant allele (OR: 2.09; χ2 = 4.95; CI: 1.08–4.02; p = 0.02), the minor allele frequency, and additive genotype, respectively (OR: 1.55; χ2 = 6.24; CI: 1.09–2.19; p = 0.01) & (OR: 1.64; χ2 = 4.04; CI: 1.01–2.67; p = 0.04). A risk association was also observed among younger age patients (≤57) and in female patients as well as in patients with tumors of the colon. For the other SNPs tested (rs16901946, rs13252298, rs1016343), no significant association was observed. The secondary structure of the rs1456315 mutant is different from that of the wild-type. Our findings suggest that the upregulation of PRNCR1 and its variants is associated with increased risk of colorectal cancer in Saudi patients, indicating that PRNCR1 might be a unique and valuable signature for predicting the risk of colorectal cancer in a Saudi population. [ABSTRACT FROM AUTHOR]

In protein tertiary structure prediction, model quality assessment programs (MQAPs) are often used to select the final structural models from a pool of candidate models generated by multiple templates and prediction methods. The 3-dimensional convolutional neural network (3DCNN) is an expansion of the 2DCNN and has been applied in several fields, including object recognition. The 3DCNN is also used for MQA tasks, but the performance is low due to several technical limitations related to protein tertiary structures, such as orientation alignment. We proposed a novel single-model MQA method based on local structure quality evaluation using a deep neural network containing 3DCNN layers. The proposed method first assesses the quality of local structures for each residue and then evaluates the quality of whole structures by integrating estimated local qualities. We analyzed the model using the CASP11, CASP12, and 3D-Robot datasets and compared the performance of the model with that of the previous 3DCNN method based on whole protein structures. The proposed method showed a significant improvement compared to the previous 3DCNN method for multiple evaluation measures. We also compared the proposed method to other state-of-the-art methods. Our method showed better performance than the previous 3DCNN-based method and comparable accuracy as the current best single-model methods; particularly, in CASP11 stage2, our method showed a Pearson coefficient of 0.486, which was better than those of the best single-model methods (0.366–0.405). A standalone version of the proposed method and data files are available at . [ABSTRACT FROM AUTHOR]

The ribosome moves between distinct structural states and is organized into multiple functional domains. Here, we examined hundreds of occurrences of pairwise through-space communication between nucleotides in the ribosome small subunit RNA using RNA interaction groups analyzed by mutational profiling (RING-MaP) single-molecule correlated chemical probing in bacterial cells. RING-MaP revealed four structural communities in the small subunit RNA, each distinct from the organization defined by the RNA secondary structure. The head domain contains 2 structural communities: the outer-head contains the pivot for head swiveling, and an inner-head community is structurally integrated with helix 44 and spans the entire ribosome intersubunit interface. In-cell binding by the antibiotic spectinomycin (Spc) barely perturbs its local binding pocket as revealed by the per-nucleotide chemical probing signal. In contrast, Spc binding overstabilizes long-range RNA–RNA contacts that extend 95 Å across the ribosome that connect the pivot for head swiveling with the axis of intersubunit rotation. The two major motions of the small subunit—head swiveling and intersubunit rotation—are thus coordinated via long-range RNA structural communication, which is specifically modulated by Spc. Single-molecule correlated chemical probing reveals trans-domain structural communication and rationalizes the profound functional effects of binding by a low–molecular-mass antibiotic to the megadalton ribosome. [ABSTRACT FROM AUTHOR]

Predicting RNA-binding protein (RBP) specificity is important for understanding gene expression regulation and RNA-mediated enzymatic processes. It is widely believed that RBP binding specificity is determined by both the sequence and structural contexts of RNAs. Existing approaches, including traditional machine learning algorithms and more recently, deep learning models, have been extensively applied to integrate RNA sequence and its predicted or experimental RNA structural probabilities for improving the accuracy of RBP binding prediction. Such models were trained mostly on the large-scale in vitro datasets, such as the RNAcompete dataset. However, in RNAcompete, most synthetic RNAs are unstructured, which makes machine learning methods not effectively extract RBP-binding structural preferences. Furthermore, RNA structure may be variable or multi-modal according to both theoretical and experimental evidence. In this work, we propose ThermoNet, a thermodynamic prediction model by integrating a new sequence-embedding convolutional neural network model over a thermodynamic ensemble of RNA secondary structures. First, the sequence-embedding convolutional neural network generalizes the existing k-mer based methods by jointly learning convolutional filters and k-mer embeddings to represent RNA sequence contexts. Second, the thermodynamic average of deep-learning predictions is able to explore structural variability and improves the prediction, especially for the structured RNAs. Extensive experiments demonstrate that our method significantly outperforms existing approaches, including RCK, DeepBind and several other recent state-of-the-art methods for predictions on both in vitro and in vivo data. The implementation of ThermoNet is available at . [ABSTRACT FROM AUTHOR]

Sigma factors are key proteins that mediate the recruitment of RNA polymerase to the promoter regions of genes, for the initiation of bacterial transcription. Multiple sigma factors in a bacterium selectively recognize their cognate promoter sequences, thereby inducing the expression of their own regulons. In this paper, we report the crystal structure of the σ4 domain of Bacillus subtilis SigW bound to the -35 promoter element. Purine-specific hydrogen bonds of the -35 promoter element with the recognition helix α9 of the σ4 domain occurs at three nucleotides of the consensus sequence (G-35, A-34, and G’-31 in G-35A-34A-33A-32C-31C-30T-29). The hydrogen bonds of the backbone with the α7 and α8 of the σ4 domain occurs at G’-30. These results elucidate the structural basis of the selective recognition of the promoter by SigW. In addition, comparison of SigW structures complexed with the -35 promoter element or with anti-sigma RsiW reveals that DNA recognition and anti-sigma factor binding of SigW are mutually exclusive. [ABSTRACT FROM AUTHOR]

Plant NLRs are modular immune receptors that trigger rapid cell death in response to attempted infection by pathogens. A highly conserved ucleotide-inding domain shared with PAF-1, various -proteins and ED-4 (NB-ARC domain) is proposed to act as a molecular switch, cycling between ADP (repressed) and ATP (active) bound forms. Studies of plant NLR NB-ARC domains have revealed functional similarities to mammalian homologues, and provided insight into potential mechanisms of regulation. However, further advances have been limited by difficulties in obtaining sufficient yields of protein suitable for structural and biochemical techniques. From protein expression screens in Escherichia coli and Sf9 insect cells, we defined suitable conditions to produce the NB-ARC domain from the tomato NLR NRC1. Biophysical analyses of this domain showed it is a folded, soluble protein. Structural studies revealed the NRC1 NB-ARC domain had co-purified with ADP, and confirmed predicted structural similarities between plant NLR NB-ARC domains and their mammalian homologues. [ABSTRACT FROM AUTHOR]

Electric fields can be a powerful tool to interact with enzymes or proteins, with an intriguing perspective to allow protein manipulation. Recently, researchers have focused the interest on intracellular enzyme modifications triggered by the application of nanosecond pulsed electric fields. These findings were also supported by theoretical predictions from molecular dynamics simulations focussing on significant variations in protein secondary structures. In this work, a theoretical study utilizing molecular dynamics simulations is proposed to explore effects of electric fields of high intensity and very short nanosecond duration applied to the superoxide dismutase (Cu/Zn-SOD or SOD-1), an important enzyme involved in the cellular antioxidant defence mechanism. The effects of 100-nanosecond pulsed electric fields, with intensities ranging from 108 to 7x108 V/m, on a single SOD1 enzyme are presented. We demonstrated that the lowest intensity of 108 V/m, although not inducing structural changes, can produce electrostatic modifications on the reaction centre of the enzyme, as apparent from the dipolar response and the electric field distribution of the protein active site. Electric pulses above 5x108 V/m produced a fast transition between the folded and a partially denatured state, as inferred by the secondary structures analysis. Finally, for the highest field intensity used (7x108 V/m), a not reversible transition toward an unfolded state was observed. [ABSTRACT FROM AUTHOR]

Membrane-protein design is an exciting and increasingly successful research area which has led to landmarks including the design of stable and accurate membrane-integral proteins based on coiled-coil motifs. Design of topologically more complex proteins, such as most receptors, channels, and transporters, however, demands an energy function that balances contributions from intra-protein contacts and protein-membrane interactions. Recent advances in water-soluble all-atom energy functions have increased the accuracy in structure-prediction benchmarks. The plasma membrane, however, imposes different physical constraints on protein solvation. To understand these constraints, we recently developed a high-throughput experimental screen, called dsTβL, and inferred apparent insertion energies for each amino acid at dozens of positions across the bacterial plasma membrane. Here, we express these profiles as lipophilicity energy terms in Rosetta and demonstrate that the new energy function outperforms previous ones in modelling and design benchmarks. Rosetta ab initio simulations starting from an extended chain recapitulate two-thirds of the experimentally determined structures of membrane-spanning homo-oligomers with <2.5Å root-mean-square deviation within the top-predicted five models (available online: ). Furthermore, in two sequence-design benchmarks, the energy function improves discrimination of stabilizing point mutations and recapitulates natural membrane-protein sequences of known structure, thereby recommending this new energy function for membrane-protein modelling and design. [ABSTRACT FROM AUTHOR]

Soil food webs are important drivers for key ecological functions in terrestrial systems such as carbon and nutrient cycling. However, soil food web models generally lack quantitative data, mainly due to the shortage in high-throughput methods to describe energy flows. In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. A premise for the application of such models to soil systems is to acquire the fatty acid pattern of a broad range of resources and to reveal potential overlap in their signatures. We present a comprehensive comparison of lipid pattern across widespread taxa of plants (leaves and roots, n = 48), algae (n = 59), fungi (n = 60), and bacteria (n = 62) as basal food web resources. Lipid profiles from microorganisms and algae were assessed from laboratory cultures, whereas plant tissue was derived from an arable field. A lipid library was constructed and multivariate data analyses (hierarchical clustering, nMDS) was used to assess the extent of separation in lipid pattern by species or resource type. The performance of the lipid library was tested by leave-one-prey-out (LOPO) analysis, giving the distinctiveness of the resource (prey) groups. Fungi and plant leaves were correctly assigned based on their lipid pattern with more than 98%, while plant roots and bacteria achieved 88 and 85%, respectively. However, algae were only correctly classified by 60%, pointing to a bias in the herbivore food chain. Fatty acids most important for separation of algae and plant leaves were of the omega 3 type, i.e. 16:3ω3 and 18:3ω3. In plant roots 18:1ω9 was most important, whereas bacteria were distinguished predominantly by methyl-branched fatty acids. Overall, the lipid pattern of major soil food web resources are sufficiently differentiated to allow for qualitative (biomarker) analyses as well as quantitative modelling, yet with precaution in the case of algae. [ABSTRACT FROM AUTHOR]

Recently much effort has been invested in using convolutional neural network (CNN) models trained on 3D structural images of protein-ligand complexes to distinguish binding from non-binding ligands for virtual screening. However, the dearth of reliable protein-ligand x-ray structures and binding affinity data has required the use of constructed datasets for the training and evaluation of CNN molecular recognition models. Here, we outline various sources of bias in one such widely-used dataset, the Directory of Useful Decoys: Enhanced (DUD-E). We have constructed and performed tests to investigate whether CNN models developed using DUD-E are properly learning the underlying physics of molecular recognition, as intended, or are instead learning biases inherent in the dataset itself. We find that superior enrichment efficiency in CNN models can be attributed to the analogue and decoy bias hidden in the DUD-E dataset rather than successful generalization of the pattern of protein-ligand interactions. Comparing additional deep learning models trained on PDBbind datasets, we found that their enrichment performances using DUD-E are not superior to the performance of the docking program AutoDock Vina. Together, these results suggest that biases that could be present in constructed datasets should be thoroughly evaluated before applying them to machine learning based methodology development. [ABSTRACT FROM AUTHOR]

Many studies about classification and the functional annotation of intrinsically disordered proteins (IDPs) are based on either the occurrence of long disordered regions or the fraction of disordered residues in the sequence. Taking into account both criteria we separate the human proteome, taken as a case study, into three variants of proteins: i) ordered proteins (ORDPs), ii) structured proteins with intrinsically disordered regions (IDPRs), and iii) intrinsically disordered proteins (IDPs). The focus of this work is on the different functional roles of IDPs and IDPRs, which up until now have been generally considered as a whole. Previous studies assigned a large set of functional roles to the general category of IDPs. We show here that IDPs and IDPRs have non-overlapping functional spectra, play different roles in human diseases, and deserve to be treated as distinct categories of proteins. IDPs enrich only a few classes, functions, and processes: nucleic acid binding proteins, chromatin binding proteins, transcription factors, and developmental processes. In contrast, IDPRs are spread over several functional protein classes and GO annotations which they partly share with ORDPs. As regards to diseases, we observe that IDPs enrich only cancer-related proteins, at variance with previous results reporting that IDPs are widespread also in cardiovascular and neurodegenerative pathologies. Overall, the operational separation of IDPRs from IDPs is relevant towards correct estimates of the occurrence of intrinsically disordered proteins in genome-wide studies and in the understanding of the functional spectra associated to different flavors of protein disorder. [ABSTRACT FROM AUTHOR]

Leishmaniasis caused by obligate intracellular parasites of genus Leishmania is one of the most neglected tropical diseases threatening 350 million people worldwide. Protein kinases have drawn much attention as potential drug targets due to their important role in various cellular processes. In Leishmania sp. mitogen-activated protein kinase 4 is essential for the parasite survival because of its involvement in various regulatory, apoptotic and developmental pathways. The current study reveals the identification of natural inhibitors of L. donovani mitogen-activated protein kinase-4 (LdMPK4). We have performed in silico docking of 110 natural inhibitors of Leishmania parasite that have been reported earlier and identified two compounds Genistein (GEN) and Chrysin (CHY). The homology model of LdMPK4 was developed, followed by binding affinity studies, and pharmacokinetic properties of the inhibitors were calculated by maintaining ATP as a standard molecule. The modelled structure was deposited in the protein model database with PMDB ID: PM0080988. Molecular dynamic simulation of the enzyme-inhibitor complex along with the free energy calculations over 50 ns showed that GEN and CHY are more stable in their binding. These two molecules, GEN and CHY, can be considered as lead molecules for targeting LdMPK4 enzyme and could emerge as potential LdMPK4 inhibitors. [ABSTRACT FROM AUTHOR]

Notophthalmus viridescens (Red-spotted Newt) possess amazing capabilities to regenerate their organs and other tissues. Previously, using a de novo assembly of the newt transcriptome combined with proteomic validation, our group identified a novel family of five protein members expressed in adult tissues during regeneration in Notophthalmus viridescens. The presence of a putative signal peptide suggests that all these proteins are secretory in nature. Here we employed iterative threading assembly refinement (I-TASSER) server to generate three-dimensional structure of these novel Newt proteins and predicted their function. Our data suggests that these proteins could act as ion transporters, and be involved in redox reaction(s). Due to absence of transgenic approaches in N. viridescens, and conservation of genetic machinery across species, we generated transgenic Drosophila melanogaster to misexpress these genes. Expression of 2775 transcripts were compared between these five newly identified Newt genes. We found that genes involved in the developmental process, cell cycle, apoptosis, and immune response are among those that are highly enriched. To validate the RNA Seq. data, expression of six highly regulated genes were verified using real time Quantitative Polymerase Chain Reaction (RT-qPCR). These graded gene expression patterns provide insight into the function of novel protein family identified in Newt, and layout a map for future studies in the field. [ABSTRACT FROM AUTHOR]

In the last decades, huge efforts have been made in the bioinformatics community to develop machine learning-based methods for the prediction of structural features of proteins in the hope of answering fundamental questions about the way proteins function and their involvement in several illnesses. The recent advent of Deep Learning has renewed the interest in neural networks, with dozens of methods being developed taking advantage of these new architectures. However, most methods are still heavily based pre-processing of the input data, as well as extraction and integration of multiple hand-picked, and manually designed features. Multiple Sequence Alignments (MSA) are the most common source of information in de novo prediction methods. Deep Networks that automatically refine the MSA and extract useful features from it would be immensely powerful. In this work, we propose a new paradigm for the prediction of protein structural features called rawMSA. The core idea behind rawMSA is borrowed from the field of natural language processing to map amino acid sequences into an adaptively learned continuous space. This allows the whole MSA to be input into a Deep Network, thus rendering pre-calculated features such as sequence profiles and other features calculated from MSA obsolete. We showcased the rawMSA methodology on three different prediction problems: secondary structure, relative solvent accessibility and inter-residue contact maps. We have rigorously trained and benchmarked rawMSA on a large set of proteins and have determined that it outperforms classical methods based on position-specific scoring matrices (PSSM) when predicting secondary structure and solvent accessibility, while performing on par with methods using more pre-calculated features in the inter-residue contact map prediction category in CASP12 and CASP13. Clearly demonstrating that rawMSA represents a promising development that can pave the way for improved methods using rawMSA instead of sequence profiles to represent evolutionary information in the coming years. Availability: datasets, dataset generation code, evaluation code and models are available at: . [ABSTRACT FROM AUTHOR]

The Acinetobacter baumannii BlsA photoreceptor has an N-terminal (NT) BLUF domain and a C-terminal (CT) amino acid sequence with no significant homology to characterized bacterial proteins. In this study, we tested the biological role of specific residues located in these BlsA regions. Site-directed mutagenesis, surface motility assays at 24°C and protein overexpression showed that residues Y7, Q51 and W92 are essential for not only light-regulated motility, but also BlsA’s solubility when overexpressed in a heterologous host. In contrast, residues A29 and F32, the latter representing a difference when compared with other BLUF-containing photoreceptors, do not play a major role in BlsA’s biological functions. Analysis of the CT region showed that the deletion of the last five BlsA residues has no significant effect on the protein’s light-sensing and motility regulatory functions, but the deletion of the last 14 residues as well as K144E and K145E substitutions significantly alter light-regulated motility responses. In contrast to the NT mutants, these CT derivatives were overexpressed and purified to homogeneity to demonstrate that although these mutations do not significantly affect flavin binding and photocycling, they do affect BlsA’s photodynamic properties. Notably, these mutations map within a potential fifth α-helical component that could play a role in predicted interactions between regulatory partners and BlsA, which could function as a monomer according to gel filtration data. All these observations indicate that although BlsA shares common structural and functional properties with unrelated photoreceptors, it also exhibits unique features that make it a distinct BLUF photoreceptor. [ABSTRACT FROM AUTHOR]

The coding space of protein sequences is shaped by evolutionary constraints set by requirements of function and stability. We show that the coding space of a given protein family—the total number of sequences in that family—can be estimated using models of maximum entropy trained on multiple sequence alignments of naturally occuring amino acid sequences. We analyzed and calculated the size of three abundant repeat proteins families, whose members are large proteins made of many repetitions of conserved portions of ∼30 amino acids. While amino acid conservation at each position of the alignment explains most of the reduction of diversity relative to completely random sequences, we found that correlations between amino acid usage at different positions significantly impact that diversity. We quantified the impact of different types of correlations, functional and evolutionary, on sequence diversity. Analysis of the detailed structure of the coding space of the families revealed a rugged landscape, with many local energy minima of varying sizes with a hierarchical structure, reminiscent of fustrated energy landscapes of spin glass in physics. This clustered structure indicates a multiplicity of subtypes within each family, and suggests new strategies for protein design. [ABSTRACT FROM AUTHOR]

TRAM is a conserved domain among RNA modification proteins that are widely distributed in various organisms. In Archaea, TRAM occurs frequently as a standalone protein with in vitro RNA chaperone activity; however, its biological significance and functional mechanism remain unknown. This work demonstrated that TRAM0076 is an abundant standalone TRAM protein in the genetically tractable methanoarcheaon Methanococcus maripaludis. Deletion of MMP0076, the gene encoding TRAM0076, markedly reduced the growth and altered transcription of 55% of the genome. Substitution mutations of Phe39, Phe42, Phe63, Phe65 and Arg35 in the recombinant TRAM0076 decreased the in vitro duplex RNA unfolding activity. These mutations also prevented complementation of the growth defect of the MMP0076 deletion mutant, indicating that the duplex RNA unfolding activity was essential for its physiological function. A genome-wide mapping of transcription start sites identified many 5′ untranslated regions (5′UTRs) of 20–60 nt which could be potential targets of a RNA chaperone. TRAM0076 unfolded three representative 5′UTR structures in vitro and facilitated the in vivo expression of a mCherry reporter system fused to the 5′UTRs, thus behaving like a transcription anti-terminator. Flag-tagged-TRAM0076 co-immunoprecipitated a large number of cellular RNAs, suggesting that TRAM0076 plays multiple roles in addition to unfolding incorrect RNA structures. This work demonstrates that the conserved archaeal RNA chaperone TRAM globally affects gene expression and may represent a transcriptional element in ancient life of the RNA world. [ABSTRACT FROM AUTHOR]

Nowadays CHK2 mutation is studied frequently in hereditary breast and ovarian cancer patients in addition to BRCA1/BRCA2. CHK2 is a tumor suppressor gene that encodes a serine/threonine kinase, also involved in pathways such as DNA repair, cell cycle regulation and apoptosis in response to DNA damage. CHK2 is a well-studied moderate penetrance gene that correlates with third high risk susceptibility gene with an increased risk for breast cancer. Hence before planning large population study, it is better to scrutinize putative functional SNPs of CHK2 using different computational tools. In this study, we have used various computational approaches to identify nsSNPs which are deleterious to the structure and/or function of CHK2 protein that might be causing this disease. Computational analysis was performed by different in silico tools including SIFT, Align GVGD, SNAP-2, PROVEAN, Poly-Phen-2, PANTHER, PhD-SNP, MUpro, iPTREE-STAB, Consurf, InterPro, NCBI Conserved Domain Search tool, ModPred, SPARKS-X, RAMPAGE, Verify-3D, FT Site, COACH and PyMol. Out of 78 nsSNP of human CHK2 gene, seven nsSNPs were predicted functionally most significant SNPs. Among these seven nsSNP, p.Arg160Gly, p.Gly210Arg and p.Ser415Phe are highly conserved residues with conservation score of 9 and three nsSNP were predicted to be involved in post translational modification. The p.Arg160Gly and p.Gly210Arg may interfere in phosphopeptide binding site on FHA conserved domain. The p.Ser415Phe may interfere in formation of activation loop of protein-kinase domain and might interfere in interactions of CHK2 with ligand. The study concludes that mutation of serine to phenylalanine at position 415 is a major mutation in native CHK2 protein which might contribute to its malfunction, ultimately causing disease. This is the first comprehensive study, where CHK2 gene variants are analyzed using in silico tools hence it will be of great help while considering large scale studies and also in developing precision medicines related to these polymorphisms in the era of personalized medicine. [ABSTRACT FROM AUTHOR]

Following the treads of our previous works on the unveiling of bioactive peptides encrypted in plant proteins from diverse species, the present manuscript reports the occurrence of four proof-of-concept intragenic antimicrobial peptides in human proteins, named Hs IAPs. These IAPs were prospected using the software Kamal, synthesized by solid phase chemistry, and had their interactions with model phospholipid vesicles investigated by differential scanning calorimetry and circular dichroism. Their antimicrobial activity against bacteria, yeasts and filamentous fungi was determined, along with their cytotoxicity towards erythrocytes. Our data demonstrates that Hs IAPs are capable to bind model membranes while attaining α-helical structure, and to inhibit the growth of microorganisms at concentrations as low as 1μM. Hs02, a novel sixteen residue long internal peptide () derived from the unconventional myosin 1h protein, was further investigated in its capacity to inhibit lipopolysaccharide-induced release of TNF-α in murine macrophages. Hs02 presented potent anti-inflammatory activity, inhibiting the release of TNF-α in LPS-primed cells at the lowest assayed concentration, 0.1 μM. A three-dimensional solution structure of Hs02 bound to DPC micelles was determined by Nuclear Magnetic Resonance. Our work exemplifies how the human genome can be mined for molecules with biotechnological potential in human health and demonstrates that IAPs are actual alternatives to antimicrobial peptides as pharmaceutical agents or in their many other putative applications. [ABSTRACT FROM AUTHOR]

Among the cancer susceptibility genes, TP53 is one of the crucial genes involved in cell cycle regulations and, therefore, it greatly affects breast cancer initiation and progression. In addition, WRAP53—a natural antisense transcript—regulates TP53 transcription and, as a protein, modulates the normal cell cycle, which results in breast cancer susceptibility. In this study, we aimed to analyze a haplotype comprising four SNPs, including rs1042522, rs17878362, rs2287499, and rs2287498, which are located at 5′ regions of the TP53 and WRAP53 genes, in 118 patients and 110 healthy controls of the Iranian-Azeri population. In silico studies were conducted using the SIFT, Polyphen2, Fanthmm, RNAsnp, and SNP&GO online servers. Linkage disequilibrium (LD) and D′ for each combination of the markers were calculated via the Haploview program. Our results showed that the GA1CC haplotype was the most frequent in the studied population. Additionally, no significant LD between any pairwise haplotypes was observed. The GA1CC and CA2GC haplotypes were significantly associated with breast cancer susceptibility. Moreover, the in silico analysis revealed the negative effects of rs2287499 and rs1042522 on WRAP53 and P53, respectively. In conclusion, the CA1GC haplotype was strongly identified as a breast cancer risk factor, and the GA1CC haplotype was assumed to be a protective factor against breast cancer risk. Hence, these markers may potentially be used as molecular prognostic and predictive biomarkers for breast cancer. [ABSTRACT FROM AUTHOR]

In this study, we evaluated the modulation effect of long-chain Acyl-CoA synthetase during early embryo development. Bovine embryos were cultured in four groups: positive modulation (ACS+) with GW3965 hydrochloride, negative modulation (ACS-) with Triacsin C, association of both modulators (ACS±), and control. Embryo development rates were not altered (P>0.05) by treatments. Embryonic cytoplasmic lipid content increased in ACS+ but reduced in ACS- compared to the control (P < 0.05), whereas the membrane phospholipids profile was not altered by treatments. The total number of blastomeres did not differ (P > 0.05) between groups; however, an increased apoptotic cells percentage was found in ACS- compared to control. Twenty-four hours after warming, ACS+ and control grade I embryos presented the best hatching rates, whereas the ACS+ group equaled the hatching rates between their embryos of grades I, II and III 48 hours after warming. The relative abundance of transcripts for genes associated with lipid metabolism (ACSL3, ACSL6, ACAT1, SCD, and AUH), heatshock (HSP90AA1 and HSF1), oxidative stress (GPX4), and angiogenesis (VEGF), among other important genes for embryo development were affected by at least one of the treatments. The treatments were effective in modulating the level of transcripts for ACSL3 and the cytoplasmic lipid content. The ACS- was not effective in increasing embryonic cryosurvival, whereas ACS+ restored survival rates after vitrification of embryos with low quality, making them equivalent to embryos of excellent quality. [ABSTRACT FROM AUTHOR]

Dinoflagellates from the Symbiodiniaceae family and corals have an ecologically important endosymbiotic relationship. Scleractinian corals cannot survive for long periods without their symbionts. These algae, also known as zooxanthellae, on the other hand, thrives outside the coral cells. The free-living populations of zooxanthellae are essential for the resilience of the coral to environmental stressors such as temperature anomalies and ocean acidification. Yet, little is known about how ocean acidification may affect the free-living zooxanthellae. In this study we aimed to test morphological, physiological and biochemical responses of zooxanthellae from the Symbiodinium genus isolated from the coral Mussismilia braziliensis, endemic to the Brazilian coast, to acidification led by increased atmospheric CO2. We tested whether photosynthetic yield, cell ultrastructure, cell density and lipid profile would change after up to 16 days of exposure to pH 7.5 in an atmospheric pCO2 of 1633 μatm. Photosynthetic yield and cell density were negatively affected and chloroplasts showed vesiculated thylakoids, indicating morphological damage. Moreover, Symbiodinium fatty acid profile drastically changed in acidified condition, showing lower polyunsaturated fatty acids and higher saturated fatty acids contents, when compared to the control, non-acidified condition. These results show that seawater acidification as an only stressor causes significant changes in the physiology, biochemistry and ultrastructure of free-living Symbiodinium. [ABSTRACT FROM AUTHOR]

Intra-chain domain interactions are known to play a significant role in the function and stability of multidomain proteins. These interactions are mediated through a physical interaction at domain-domain interfaces (DDIs). With a motivation to understand evolution of interfaces, we have investigated similarities among DDIs. Even though interfaces of protein-protein interactions (PPIs) have been previously studied by structurally aligning interfaces, similar analyses have not yet been performed on DDIs of either multidomain proteins or PPIs. For studying the structural landscape of DDIs, we have used iAlign to structurally align intra-chain domain interfaces of domains. The interface alignment of spatially constrained domains (due to inter-domain linkers) showed that ~88% of these could identify a structural matching interface having similar C-alpha geometry and contact pattern despite that aligned domain pairs are not structurally related. Moreover, the mean interface similarity score (IS-score) is 0.307, which is higher compared to the average random IS-score (0.207) suggesting domain interfaces are not random. The structural space of DDIs is highly connected as ~84% of all possible directed edges among interfaces are found to have at most path length of 8 when 0.26 is IS-score threshold. At this threshold, ~83% of interfaces form the largest strongly connected component. Thus, suggesting that structural space of intra-chain domain interfaces is degenerate and highly connected, as has been found in PPI interfaces. Interestingly, searching for structural neighbors of inter-chain interfaces among intra-chain interfaces showed that ~86% could find a statistically significant match to intra-chain interface with a mean IS-score of 0.311. This implies that domain interfaces are degenerate whether formed within a protein or between proteins. The interface degeneracy is most likely due to limited possible ways of packing secondary structures. In principle, interface similarities can be exploited to accurately model domain interfaces in structure prediction of multidomain proteins. [ABSTRACT FROM AUTHOR]

Lipid species patterns are conserved within cells to maintain physicochemical properties of membranes and cellular functions. We present the lipidome, including sterols, glycerolipids (GLs), glycerophospholipids (GPLs), and sphingolipids (SLs), of primary ex vivo differentiated (I) white, (II) brite, and (III) brown adipocytes derived from primary preadipocytes isolated from (I) epididymal white, (II) inguinal white, and (III) intrascapular brown adipose tissue. Quantitative lipidomics revealed significantly decreased fractions of phosphatidylcholine (PC) and phosphatidylethanolamine (PE), with longer (C > 36) and more polyunsaturated species, as well as lower levels of cardiolipin (CL) in white than in brite and brown adipocytes. Together, the brite and brown lipidome was comparable and indicates differences in membrane lipid packing density compared with white adipocytes. Changes in ceramide species profile could be related to the degree of browning. Beta-adrenergic stimulation of brown adipocytes led to generation of saturated lyso-PC (LPC) increasing uncoupling protein (UCP) 1-mediated leak respiration. Application of stable isotope labeling showed that LPC formation was balanced by an increased de novo synthesis of PC. [ABSTRACT FROM AUTHOR]

The length of cilia is controlled by a poorly understood mechanism that involves members of the conserved RCK kinase group, and among them, the LF4/MOK kinases. The multiciliated protist model, Tetrahymena, carries two types of cilia (oral and locomotory) and the length of the locomotory cilia is dependent on their position with the cell. In Tetrahymena, loss of an LF4/MOK ortholog, LF4A, lengthened the locomotory cilia, but also reduced their number. Without LF4A, cilia assembled faster and showed signs of increased intraflagellar transport (IFT). Consistently, overproduced LF4A shortened cilia and downregulated IFT. GFP-tagged LF4A, expressed in the native locus and imaged by total internal reflection microscopy, was enriched at the basal bodies and distributed along the shafts of cilia. Within cilia, most LF4A-GFP particles were immobile and a few either diffused or moved by IFT. We suggest that the distribution of LF4/MOK along the cilium delivers a uniform dose of inhibition to IFT trains that travel from the base to the tip. In a longer cilium, the IFT machinery may experience a higher cumulative dose of inhibition by LF4/MOK. Thus, LF4/MOK activity could be a readout of cilium length that helps to balance the rate of IFT-driven assembly with the rate of disassembly at steady state. We used a forward genetic screen to identify a CDK-related kinase, CDKR1, whose loss-of-function suppressed the shortening of cilia caused by overexpression of LF4A, by reducing its kinase activity. Loss of CDKR1 alone lengthened both the locomotory and oral cilia. CDKR1 resembles other known ciliary CDK-related kinases: LF2 of Chlamydomonas, mammalian CCRK and DYF-18 of C. elegans, in lacking the cyclin-binding motif and acting upstream of RCKs. The new genetic tools we developed here for Tetrahymena have potential for further dissection of the principles of cilia length regulation in multiciliated cells. [ABSTRACT FROM AUTHOR]

Curcuma is a traditional ingredient of some Eastern cuisines, and the spice is heralded for its antitumoral and antiparasitic properties. In this report, we examine the effect of the curcuminoides which include curcumin, demethoxycurcumin (DMC) and bis-demethoxycurcumin (BDMC), as well as curcumin degradation products on thioredoxin glutathione reductase from Taenia crassiceps cysticerci Results revealed that both DMC and BDMC were inhibitors of TGR activity in the micromolar concentration range. By contrast, the inhibitory ability of curcumin was a time-dependent process. Kinetic and spectroscopical evidence suggests that an intermediary compound of curcumin oxidation, probably spiroepoxide, is responsible. Preincubation of curcumin in the presence of NADPH, but not glutathione disulfide (GSSG), resulted in the loss of its inhibitory ability, suggesting a reductive stabilizing effect. Similarly, preincubation of curcumin with sulfhydryl compounds fully protected the enzyme from inhibition. Degradation products were tested for their inhibitory potential, and 4-vinylguaiacol was the best inhibitor (IC50 = 12.9 μM), followed by feruloylmethane (IC50 = 122 μM), vanillin (IC50 = 127 μM), and ferulic aldehyde (IC50 = 180 μM). The acid derivatives ferulic acid (IC50 = 465 μM) and vanillic acid (IC50 = 657 μM) were poor inhibitors. On the other hand, results from docking analysis revealed a common binding site on the enzyme for all the compounds, albeit interacting with different amino acid residues. Dissociation constants obtained from the docking were in accord with the inhibitory efficiency of the curcumin degradation products. [ABSTRACT FROM AUTHOR]

Genomics and genome screening are proving central to the study of cancer. However, a good appreciation of the protein structures coded by cancer genes is also invaluable, especially for the understanding of functions, for assessing ligandability of potential targets, and for designing new drugs. To complement the wealth of information on the genetics of cancer in COSMIC, the most comprehensive database for cancer somatic mutations available, structural information obtained experimentally has been brought together recently in COSMIC-3D. Even where structural information is available for a gene in the Cancer Gene Census, a list of genes in COSMIC with substantial evidence supporting their impacts in cancer, this information is quite often for a single domain in a larger protein or for a single protomer in a multiprotein assembly. Here, we show that over 60% of the genes included in the Cancer Gene Census are predicted to possess multiple domains. Many are also multicomponent and membrane-associated molecular assemblies, with mutations recorded in COSMIC affecting such assemblies. However, only 469 of the gene products have a structure represented in the PDB, and of these only 87 structures have 90–100% coverage over the sequence and 69 have less than 10% coverage. As a first step to bridging gaps in our knowledge in the many cases where individual protein structures and domains are lacking, we discuss our attempts of protein structure modelling using our pipeline and investigating the effects of mutations using two of our in-house methods (SDM2 and mCSM) and identifying potential driver mutations. This allows us to begin to understand the effects of mutations not only on protein stability but also on protein-protein, protein-ligand and protein-nucleic acid interactions. In addition, we consider ways to combine the structural information with the wealth of mutation data available in COSMIC. We discuss the impacts of COSMIC missense mutations on protein structure in order to identify and assess the molecular consequences of cancer-driving mutations. [ABSTRACT FROM AUTHOR]

The aim of this research was to improve nutritive value of fishmeal-based feed by lactobacilli in order to achieve satisfactory nutrient availability needed to support fish development. Feed was solid-state treated at a laboratory scale with the combination of Lactobacillus paracasei subsp. paracasei BGHN14 and Lactobacillus rhamnosus BGT10 in different experimental settings, which included the variation of strain ratio, total lactobacilli concentration, percentage of moisture and duration of incubation. Short peptides, soluble proteins, phospho-, neutral and unsaturated lipids were quantified. Differences among treated and control feeds were evaluated by Student t-test, while Gaussian process regression (GPR) modeling was employed to simulate the incubation process and define the optimal treatment combination in the context of overall feed nutritional profile. Treatment duration was shown to be the critical determinant of final outcome, either as single factor or via interaction with strain ratio. Optimal nutrient balance was achieved with 12 h incubation period, 260% moisture, 75:25 and 50:50 BGHN14:BGT10 ratios and 200 mg of lactobacilli per g of dry feed. This study should serve as the basis for large-scale tests which would simulate on-farm production of both fishmeal-based and unconventional, lower cost aquafeed with added value. [ABSTRACT FROM AUTHOR]

Tauopathies are neurodegenerative diseases that affect millions of people worldwide including those with Alzheimer’s disease. While many efforts have focused on understanding the role of tau protein in neurodegeneration, there has been little done to systematically analyze and study the structures within tau’s encoding RNA and their connection to disease pathology. Knowledge of RNA structure can provide insights into disease mechanisms and how to affect protein production for therapeutic benefit. Using computational methods based on thermodynamic stability and evolutionary conservation, we identified structures throughout the tau pre-mRNA, especially at exon-intron junctions and within the 5′ and 3′ untranslated regions (UTRs). In particular, structures were identified at twenty exon-intron junctions. The 5′ UTR contains one structured region, which lies within a known internal ribosome entry site. The 3′ UTR contains eight structured regions, including one that contains a polyadenylation signal. A series of functional experiments were carried out to assess the effects of mutations associated with mis-regulation of alternative splicing of exon 10 and to identify regions of the 3′ UTR that contain cis-regulatory elements. These studies defined novel structural regions within the mRNA that affect stability and pre-mRNA splicing and may lead to new therapeutic targets for treating tau-associated diseases. [ABSTRACT FROM AUTHOR]

Being able to assess the phenotypic effects of mutations is a much required capability in precision medicine. However, most of the currently available structure-based methods actually predict stability changes caused by mutations rather than their pathogenic potential. There are also no dedicated methods to predict damaging mutations specifically in transmembrane proteins. In this study we developed and applied a machine-learning approach to discriminate between disease-associated and benign point mutations in the transmembrane regions of proteins with known 3D structure. The method, called BorodaTM (BOosted RegressiOn trees for Disease-Associated mutations in TransMembrane proteins), was trained on sequence-, structure-, and energy-derived descriptors. When compared with the state-of-the-art methods, BorodaTM is superior in classifying point mutations in transmembrane regions. Using BorodaTM we have conducted a large-scale mutation analysis in the transmembrane regions of human proteins with known 3D structures. For each protein we generated structural models for all point mutations by replacing each residue to 19 possible residue types. We classified ~1.8 millions point mutations as benign or diseased-associated and made all predictions available as a Web-server at . [ABSTRACT FROM AUTHOR]

Prions are unusual protein assemblies that propagate their conformationally-encoded information in absence of nucleic acids. The first prion identified, the scrapie isoform (PrPSc) of the cellular prion protein (PrPC), caused epidemic and epizootic episodes []. Most aggregates of other misfolding-prone proteins are amyloids, often arranged in a Parallel-In-Register-β-Sheet (PIRIBS) [] or β-solenoid conformations []. Similar folding models have also been proposed for PrPSc, although none of these have been confirmed experimentally. Recent cryo-electron microscopy (cryo-EM) and X-ray fiber-diffraction studies provided evidence that PrPSc is structured as a 4-rung β-solenoid (4RβS) [, ]. Here, we combined different experimental data and computational techniques to build the first physically-plausible, atomic resolution model of mouse PrPSc, based on the 4RβS architecture. The stability of this new PrPSc model, as assessed by Molecular Dynamics (MD) simulations, was found to be comparable to that of the prion forming domain of Het-s, a naturally-occurring β-solenoid. Importantly, the 4RβS arrangement allowed the first simulation of the sequence of events underlying PrPC conversion into PrPSc. This study provides the most updated, experimentally-driven and physically-coherent model of PrPSc, together with an unprecedented reconstruction of the mechanism underlying the self-catalytic propagation of prions. [ABSTRACT FROM AUTHOR]

Studies on the Bin-Amphiphysin-Rvs (BAR) domain have advanced a fundamental understanding of how proteins deform membrane. We previously showed that a BAR domain in tandem with a Pleckstrin Homology (PH domain) underlies the assembly of ACAP1 (Arfgap with Coil-coil, Ankryin repeat, and PH domain I) into an unusual lattice structure that also uncovers a new paradigm for how a BAR protein deforms membrane. Here, we initially pursued computation-based refinement of the ACAP1 lattice to identify its critical protein contacts. Simulation studies then revealed how ACAP1, which dimerizes into a symmetrical structure in solution, is recruited asymmetrically to the membrane through dynamic behavior. We also pursued electron microscopy (EM)-based structural studies, which shed further insight into the dynamic nature of the ACAP1 lattice assembly. As ACAP1 is an unconventional BAR protein, our findings broaden the understanding of the mechanistic spectrum by which proteins assemble into higher-ordered structures to achieve membrane deformation. [ABSTRACT FROM AUTHOR]

Type III protein-secretion machines are essential for the interactions of many pathogenic or symbiotic bacterial species with their respective eukaryotic hosts. The core component of these machines is the injectisome, a multiprotein complex that mediates the selection of substrates, their passage through the bacterial envelope, and ultimately their delivery into eukaryotic target cells. The injectisome is composed of a large cytoplasmic complex or sorting platform, a multiring base embedded in the bacterial envelope, and a needle-like filament that protrudes several nanometers from the bacterial surface and is capped at its distal end by the tip complex. A characteristic feature of these machines is that their activity is stimulated by contact with target host cells. The sensing of target cells, thought to be mediated by the distal tip of the needle filament, generates an activating signal that must be transduced to the secretion machine by the needle filament. Here, through a multidisciplinary approach, including solid-state NMR (SSNMR) and cryo electron microscopy (cryo-EM) analyses, we have identified critical residues of the needle filament protein of a Salmonella Typhimurium type III secretion system that are involved in the regulation of the activity of the secretion machine. We found that mutations in the needle filament protein result in various specific phenotypes associated with different steps in the type III secretion process. More specifically, these studies reveal an important role for a polymorphic helix of the needle filament protein and the residues that line the lumen of its central channel in the control of type III secretion. [ABSTRACT FROM AUTHOR]