bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validating Antibodies for Quantitative Western Blot Measurements with Microwestern Array
Authors: Koch Rick J. , Barrette Anne Marie , Stern Alan D. , Hu Bin , Azeloglu Evren U. , Iyengar Ravi , Birtwistle Marc R. 
Published: November 2017

ABSTRACTWestern blotting is often considered a semi-quantitative or even qualitative assay for assessing changes in protein or protein post-translational modification levels. Fluorescence-based measurement enables acquisition of quantitative data in principal, but requires determining the linear range of detection for each antibody—a labor-intensive task. Here, we describe the use of a high-throughput western blotting technique called microwestern array to more rapidly evaluate suitable conditions for quantitative western blotting with particular antibodies. We can evaluate up to 192 antibody/dilution/replicate combinations on a single standard size gel with a seven-point, two-fold lysate dilution series (~100-fold range). Pilot experiments demonstrate a surprisingly high proportion of investigated antibodies (17/22) are suitable for quantitative use, and that lack of validity might often be a consequence of lysate composition rather than antibody quality. Linear range for all validated antibodies is at least 8-fold, and in some cases nearly two orders of magnitude. That range could be greater as the presented tests did not find a limit for many antibodies. We find that phospho-specific and total antibodies do not have discernable trend differences in linear range or limit of detection, but total antibodies generally required higher working concentrations, suggesting phospho-specific antibodies may be generally higher affinity. Importantly, we demonstrate that results from microwestern analyses scale to normal “macro” western for a subset of antibodies. These data indicate that with initial validation, many antibodies can be readily used quantitatively in a reproducible manner. Antibody validation data and standard operating procedures are available online (www.birtwistlelab.com/protocols and www.dtoxs.org).
TKSA-MC: A Web Server for rational mutation through the optimization of protein charge interactions
Authors: Contessoto Vinícius G. , de Oliveira Vinícius M. , Fernandes Bruno R. , Slade Gabriel G. , Leite Vitor B. P. 
Published: November 2017

AbstractThe TKSAMC is a web server which calculates protein charge-charge interactions via the Tanford-Kirkwood Surface Accessibility model with the Monte Carlo method for sampling different protein protonation states. The optimization of charge-charge interactions via directed mutations has successfully enhanced the thermal stability of different proteins and could be a key to protein engineering improvement. The server presents the electrostatic free energy contribution of each polar-charged residue to protein native state stability. The server also indicates which residues contribute to destabilizing the protein native state with positive energy and the side chain exposed to solvent. This residue is a candidate for mutation to increase protein thermostability as a function of the chosen pH condition. The web server is freely available at UNESP (São Paulo State University - DF/IBILCE): http://tksamc.df.ibilce.unesp.br.
Estimating the effects of variation in viremia on mosquito susceptibility, infectiousness, andR0of Zika inAedes aegypti
Authors: Tesla Blanka , Demakovsky Leah R. , Packiam Hannah S. , Mordecai Erin A. , Rodríguez Américo D. , Bonds Matthew H. , Brindley Melinda A. , Murdock Courtney C. 
Published: November 2017

AbstractZika virus (ZIKV) is an arbovirus primarily transmitted byAedesmosquitoes. Like most viral infections, ZIKV viremia varies over several orders of magnitude, with unknown consequences for transmission. To determine the effect of viral concentration on ZIKV transmission risk, we exposed field-derivedAe. aegyptimosquitoes to four doses (103, 104, 105, 106PFU/mL) representative of potential variation in the field. We demonstrate that increasing ZIKV dose in the blood-meal significantly increases the probability of mosquitoes becoming infected and infectious, as well as the rate at which virus spreads to the saliva, but found no effect on dissemination efficiency or mosquito mortality. We also demonstrate that determining infection using RT-qPCR approaches rather than plaque assays potentially over-estimates key pathogen parameters, including the time at which mosquitoes become infectious and viral burden. Finally, using these data to parameterize anR0model, we demonstrate that variation in viremia substantially affects transmission risk.
Integrating co-expression networks with GWAS to prioritize causal genes in maize
Authors: Schaefer Robert J. , Michno Jean-Michel , Jeffers Joseph , Hoekenga Owen , Dilkes Brian , Baxter Ivan , Myers Chad L. 
Published: November 2017

AbstractBackgroundGenome wide association studies (GWAS) have identified thousands of loci linked to hundreds of traits in many different species. However, because linkage equilibrium implicates a broad region surrounding each identified locus, the causal genes often remain unknown. This problem is especially pronounced in non-human, non-model species where functional annotations are sparse and there is frequently little information available for prioritizing candidate genes.ResultsTo address this issue, we developed a computational approach called Camoco (Co-Analysis of Molecular Components) that systematically integrates loci identified by GWAS with gene co-expression networks to prioritize putative causal genes. We applied Camoco to prioritize candidate genes from a large-scale GWAS examining the accumulation of 17 different elements in maize seeds. Camoco identified statistically significant subnetworks for the majority of traits examined, producing a prioritized list of high-confidence causal genes for several agronomically important maize traits. Two candidate genes identified by our approach were validated through analysis of mutant phenotypes. Strikingly, we observed a strong dependence in the performance of our approach on the type of co-expression network used: expression variation across genetically diverse individuals in a relevant tissue context (in our case, maize roots) outperformed other alternatives.ConclusionsOur study demonstrates that co-expression networks can provide a powerful basis for prioritizing candidate causal genes from GWAS loci, but suggests that the success of such strategies can highly depend on the gene expression data context. Both the Camoco software and the lessons on integrating GWAS data with co-expression networks generalize to species beyond maize.
CapsidMesh: atomic-detail structured mesh representation of icosahedral viral capsids and the study of their mechanical properties
Authors: Alonzo-Velázquez José Luis , Botello-Rionda Salvador , Herrera-Guzmán Rafael , Carrillo-Tripp Mauricio 
Published: November 2017

AbstractViruses are the most abundant pathogens affecting all forms of life. A major component of a virus is a protein shell, known as the viral capsid, that encapsulates the genomic material. The fundamental functions of the capsid are to protect and transport the viral genome, and recognize the host cell. Descriptions of this macromolecular complex have been proposed at different scales of approximation. Here, we introduce a methodology to generate a structured volumetric mesh of icosahedral viral capsids (CapsidMesh) based on the atomic positions of their constituents. Material properties of the capsid proteins can be set on every mesh element individually. Hence, we have control over all levels of protein structure (atoms, amino acids, subunits, oligomers,capsid). The CapsidMesh models are suitable for numerical simulations and analysis of a physical process using a third-party package. In particular, we used our methodology to generate a CapsidMesh of several capsids previously characterized by Atomic Force Microscopy experiments, and then simulated the mechanical nanoindentation through the Finite Element Method. By fitting to the experimental linear elastic response, we estimated the elastic modulus and mechanical stresses produced on the capsids. Our results show that the atomic detail of the CapsidMesh is sufficient to reproduce anisotropic properties of the particle.
Flex ddG: Rosetta ensemble-based estimation of changes in protein-protein binding affinity upon mutation
Authors: Barlow Kyle A. , Conchúir Shane O , Thompson Samuel , Suresh Pooja , Lucas James E. , Heinonen Markus , Kortemme Tanja 
Published: November 2017

AbstractComputationally modeling changes in binding free energies upon mutation (interface ΔΔG) allows large-scale prediction and perturbation of protein-protein interactions. Additionally, methods that consider and sample relevant conformational plasticity should be able to achieve higher prediction accuracy over methods that do not. To test this hypothesis, we developed a method within the Rosetta macromolecular modeling suite (flex ddG) that samples conformational diversity using “backrub” to generate an ensemble of models, then applying torsion minimization, side chain repacking and averaging across this ensemble to estimate interface ΔΔGvalues. We tested our method on a curated benchmark set of 1240 mutants, and found the method outperformed existing methods that sampled conformational space to a lesser degree. We observed considerable improvements with flex ddG over existing methods on the subset of small side chain to large side chain mutations, as well as for multiple simultaneous non-alanine mutations, stabilizing mutations, and mutations in antibody-antigen interfaces. Finally, we applied a generalized additive model (GAM) approach to the Rosetta energy function; the resulting non-linear reweighting model improved agreement with experimentally determined interface DDG values, but also highlights the necessity of future energy function improvements.
Deleterious variation mimics signatures of genomic incompatibility and adaptive introgression
Authors: Kim Bernard Y. , Huber Christian D. , Lohmueller Kirk E. 
Published: November 2017

AbstractWhile it is appreciated that population size changes can impact patterns of deleterious variation in natural populations, less attention has been paid to how population admixture affects the dynamics of deleterious variation. Here we use population genetic simulations to examine how admixture impacts deleterious variation under a variety of demographic scenarios, dominance coefficients, and recombination rates. Our results show that gene flow between populations can temporarily reduce the genetic load of smaller populations, especially if deleterious mutations are recessive. Additionally, when fitness effects of new mutations are recessive, between-population differences in the sites at which deleterious variants exist creates heterosis in hybrid individuals. This can lead to an increase in introgressed ancestry, particularly when recombination rates are low. Under certain scenarios, introgressed ancestry can increase from an initial frequency of 5% to 30-75% and fix at many loci, even in the absence of beneficial mutations. Further, deleterious variation and admixture can generate correlations between the frequency of introgressed ancestry and recombination rate or exon density, even in the absence of other types of selection. The direction of these correlations is determined by the specific demography and whether mutations are additive or recessive. Therefore, it is essential that null models include both demography and deleterious variation before invoking reproductive incompatibilities or adaptive introgression to explain unusual patterns of genetic variation.
Identification and characterisation of the cryptic Golgi Apparatus in Naegleria gruberi
Authors: Herman Emily K. , Yiangou Lyto , Cantoni Diego M. , Miller Christopher N. , Marciano-Cabral Francine , Anthonyrajah Erin , Dacks Joel B. , Tsaousis Anastasios D. 
Published: November 2017

AbstractAlthough the Golgi apparatus has a conserved morphology of flattened stacked cisternae in the vast majority of eukaryotes, the organelle has lost the stacked organization in several eukaryotic lineages raising the question of what range of morphologies is possible for the Golgi. In order to understand this range of organellar diversity, it is necessary to characterise the Golgi in many different lineages. Here we identify the Golgi apparatus in Naegleria, the first description of an unstacked Golgi organelle in a non-parasitic eukaryote, other than fungi. We provide a comprehensive list of Golgi-associated membrane trafficking genes encoded in two separate species of Naegleria and transcriptomic support to show that nearly all are expressed in mouse-passaged N. fowleri cells. We then study distribution of the Golgi marker NgCOPB by fluorescence, identifying membranous structures that can be disrupted by Brefeldin A treatment consistent with Golgi localisation. Confocal and immuno-electron microscopy revealed that NgCOPB is localized to membranous structures consistent with tubules. Our data not only identify the Golgi organelle for the first time in this major eukaryotic lineage, but also provide the rare example of a tubular form of the organelle representing an important sampling point for the comparative understanding of Golgi organellar diversity.
Transcription activator-coactivator specificity is mediated by a large and dynamic fuzzy protein-protein complex
Authors: Tuttle Lisa M. , Pacheco Derek , Warfield Linda , Luo Jie , Ranish Jeff , Hahn Steven , Klevit Rachel E. 
Published: November 2017

SUMMARYTranscription activation domains (ADs) are inherently disordered proteins that often target multiple coactivator complexes, but the specificity of these interactions is not understood. Efficient activation by yeast Gcn4 requires tandem Gcn4 ADs and four activator-binding domains (ABDs) on its target, the Mediator subunit Med15. Multiple ABDs are a common feature of coactivator complexes. We find that the large Gcn4-Med15 complex is heterogeneous, containing nearly all possible AD-ABD interactions. This complex forms using a dynamic fuzzy protein-protein interface where ADs use hydrophobic residues to bind hydrophobic surfaces of the ABDs in multiple orientations. This combinatorial mechanism allows individual interactions of low affinity and specificity to generate a biologically functional, specific, and higher affinity complex despite lacking a defined protein-protein interface. This binding strategy is likely representative of many activators that target multiple coactivators and allows great flexibility in combinations of activators that synergize to regulate genes with variable coactivator requirements.
Biologically plausible mechanisms underlying motor response correction during reward-based decision-making
Authors: Lee Jung Hoon 
Published: November 2017

AbstractOur propensity to acclimate to new surroundings and choose a goal-directed behavior for a maximal reward (i.e., optimal outcome) is natural, for it affects our survival. A line of studies suggested that anterior cingulate cortex (ACC) could be a potential hub for adaptive behaviors. For instance, an experimental study noted ACC’s contribution to selecting motor responses for maximal rewards; it found 1) that ACC neurons were selectively activated when the reward was reduced and 2) that suppression of ACC activity impaired monkeys’ ability to change motor responses to obtain the maximal reward. To probe ACC functions in adaptive behaviors, we sought biologically-plausible mechanisms to account for the experimental findings mentioned above by utilizing a computational model. Our simulation results raise the possibility that ACC can correct behavioral responses by reading out and updating the motor plans (guiding future motor responses) stored in prefrontal cortex (PFC).
Time intervals in sequence sampling, not data modifications, have a major impact on estimates of HIV escape rates
Authors: Ganusov Vitaly V. 
Published: November 2017

AbstractThe ability of HIV to avoid recognition by humoral and cellular immunity (viral escape) is well documented but the strength of the immune response needed to cause such a viral escape remains poorly quantified. Several previous studies observed a more rapid escape of HIV from CD8 T cell responses in the acute phase of infection as compared to the chronic infection. With the help of simple mathematical models the rate of HIV escape was estimated and results were interpreted to suggest that CD8 T cell responses causing escape in acute HIV infection may be more efficient at killing virus-infected cells than responses that cause escape in chronic infection, or alternatively, early escapes occur in epitopes mutations in which there is minimal fitness cost to the virus. These conclusions, however, were challenged on several grounds, including linkage and interference of multiple escape mutations due to a low population size and because of potential issues associated with modifying the data to estimate escape rates. Here we use a parametric resampling method which does not require data modification to show that previous results on the decline of the viral escape rate with time since infection remain unchanged. However, using this method we also show that estimates of the escape rate are highly sensitive to the time interval between measurements with longer intervals biasing estimates of the escape rate downwards. Our results thus suggest that data modifications for early and late escapes were not the primary reason for the observed decline in the escape rate with time since infection. However, longer sampling periods for escapes in chronic infection strongly influence estimates of the escape rate. More frequent sampling of viral sequences in the chronic infection may improve our understanding of factors influencing the rate of HIV escape from CD8 T cell responses.
Wx: a neural network-based feature selection algorithm for next-generation sequencing data
Authors: Park Sungsoo , Shin Bonggun , Choi Yoonjung , Kang Kilsoo , Kang Keunsoo 
Published: November 2017

AbstractMotivationNext-generation sequencing (NGS), which allows the simultaneous sequencing of billions of DNA fragments simultaneously, has revolutionized how we study genomics and molecular biology by generating genome-wide molecular maps of molecules of interest. For example, an NGS-based transcriptomic assay called RNA-seq can be used to estimate the abundance of approximately 190,000 transcripts together. As the cost of next-generation sequencing sharply declines, researchers in many fields have been conducting research using NGS. The amount of information produced by NGS has made it difficult for researchers to choose the optimal set of target genes (or genomic loci).ResultsWe have sought to resolve this issue by developing a neural network-based feature (gene) selection algorithm called Wx. The Wx algorithm ranks genes based on the discriminative index (DI) score that represents the classification power for distinguishing given groups. With a gene list ranked by DI score, researchers can institutively select the optimal set of genes from the highest-ranking ones. We applied the Wx algorithm to a TCGA pan-cancer gene-expression cohort to identify an optimal set of gene-expression biomarker (universal gene-expression biomarkers) candidates that can distinguish cancer samples from normal samples for 12 different types of cancer. The 14 gene-expression biomarker candidates identified by Wx were comparable to or outperformed previously reported universal gene expression biomarkers, highlighting the usefulness of the Wx algorithm for next-generation sequencing data. Thus, we anticipate that the Wx algorithm can complement current state-of-the-art analytical applications for the identification of biomarker candidates as an alternative method.Availabilityhttps://github.com/deargen/DearWXContactkangk1204@dankook.ac.krSupplementary informationSupplementary data are available at online.
Denaturants Alter the Flux through Multiple Pathways in the Folding of PDZ Domain
Authors: Liu Zhenxing , Thirumalai D. 
Published: November 2017

AbstractAlthough we understand many aspects of how small proteins (number of residues less than about hundred) fold, it is a major challenge to understand how large proteins self-assemble. To partially overcome this challenge, we performed simulations using the Self-Organized Polymer model with Side Chains (SOP-SC) in guanidinium chloride (GdmCl), using the Molecular Transfer Model (MTM), to describe the folding of the 110-residue PDZ3 domain. The simulations reproduce the folding thermodynamics accurately including the melting temperature (Tm), the stability of the folded state with respect to the unfolded state. We show that the calculated dependence of lnkobs(kobsis the relaxation rate) has the characteristic Chevron shape. The slopes of the Chevron plots are in good agreement with experiments. We show that PDZ3 folds by four major pathways populating two metastable intermediates, in accord with the kinetic partitioning mechanism. The structure of one of the intermediates, populated after polypeptide chain collapse, is structurally similar to an equilibrium intermediate. Surprisingly, the connectivities between the intermediates and hence, the fluxes through the pathways depend on the concentration of GdmCl. The results are used to predict possible outcomes for unfolding of PDZ domain subject to mechanical forces. Our study demonstrates that, irrespective of the size or topology, simulations based on MTM and SOP-SC offer a framework for describing the folding of proteins, mimicking precisely the conditions used in experiments.
Patient‐level Factors and the Quality of Care Delivered in Pediatric Emergency Departments
Authors: Marcin James P. , Romano Patrick S. , Dayal Parul , Dharmar Madan , Chamberlain James M. , Dudley Nanette , Macias Charles G. , Nigrovic Lise E. , Powell Elizabeth C. , Rogers Alexander J. , Sonnett Meridith , Tzimenatos Leah , Alpern Elizabeth R. , Andrews‐Dickert Rebecca , Borgialli Dominic A. , Sidney Erika , Charles Casper T. , Michael Dean J. , Kuppermann Nathan ,   for the Pediatric Emergency Care Applied Research Network
Published: November 2017

AbstractObjectiveQuality of care delivered to adult patients in the emergency department (ED) is often associated with demographic and clinical factors such as a patient's race/ethnicity and insurance status. We sought to determine whether the quality of care delivered to children in the ED was associated with a variety of patient‐level factors.MethodsThis was a retrospective, observational cohort study. Pediatric patients (<18 years) who received care between January 2011 and December 2011 at one of 12 EDs participating in the Pediatric Emergency Care Applied Research Network (PECARN) were included. We analyzed demographic factors (including age, sex, and payment source) and clinical factors (including triage, chief complaint, and severity of illness). We measured quality of care using a previously validated implicit review instrument using chart review with a summary score that ranged from 5 to 35. We examined associations between demographic and clinical factors and quality of care using a hierarchical multivariable linear regression model with hospital site as a random effect.ResultsIn the multivariable model, among the 620 ED encounters reviewed, we did not find any association between patient age, sex, race/ethnicity, and payment source and the quality of care delivered. However, we did find that some chief complaint categories were significantly associated with lower than average quality of care, including fever (–0.65 points in quality, 95% confidence interval [CI] = –1.24 to –0.06) and upper respiratory symptoms (–0.68 points in quality, 95% CI = –1.30 to –0.07).ConclusionWe found that quality of ED care delivered to children among a cohort of 12 EDs participating in the PECARN was high and did not differ by patient age, sex, race/ethnicity, and payment source, but did vary by the presenting chief complaint.