bluuebunny/crossref_metadata_2025_split huggingface dataset:
The E3 ubiquitin ligase RNF115 regulates phagosome maturation and host response to bacterial infection
Authors: Bilkei-Gorzo Orsolya , Heunis Tiaan , Marín-Rubio José Luis , Cianfanelli Francesca Romana , Raymond Benjamin Bernard Armando , Inns Joseph , Fabrikova Daniela , Peltier Julien , Oakley Fiona , Schmid Ralf , Härtlova Anetta , Trost Matthias 
Published: July 2021

SummaryPhagocytosis is a key process in innate immunity and homeostasis. After uptake, newly formed phagosomes mature by acquisition of endo-lysosomal enzymes. Macrophage activation by interferon-gamma (IFN-γ) increases microbicidal activity, but delays phagosomal maturation by an unknown mechanism. Using quantitative proteomics, we show that phagosomal proteins harbour high levels of typical and atypical ubiquitin chain types. Moreover, phagosomal ubiquitylation of vesicle trafficking proteins is substantially enhanced upon IFN-γ activation of macrophages, suggesting a role in regulating phagosomal functions. We identified the E3 ubiquitin ligase RNF115, which is enriched on phagosomes of IFN-γ activated macrophages, as an important regulator of phagosomal maturation. Loss of RNF115 protein or ligase activity enhanced phagosomal maturation and increased cytokine responses to bacterial infection, suggesting that both innate immune signalling from the phagosome and phagolysosomal trafficking are controlled through ubiquitylation. RNF115 knock-out mice show less tissue damage in response toS. aureusinfection, indicating a role of RNF115 in inflammatory responsesin vivo. In conclusion, RNF115 and phagosomal ubiquitylation are important regulators of innate immune functions during bacterial infections.
Mathematically and biologically consistent framework for presence-absence pairwise indices
Authors: Šizling Arnošt L. , Keil Petr , Tjørve Even , Tjørve Kathleen M.C. , Žárský Jakub D. , Storch David 
Published: July 2021

AbstractA large number of indices for presence-absence data that compare two assemblages have been proposed or reinvented. Interpretation of these indices varies across the literature, despite efforts for clarification and unification. Most effort has focused on the mathematics behind the indices, their relationships with diversity, and with each other. At the same time, the following issues have been largely overlooked: (i) requirement that a small re-arrangement of assemblages should only cause a small change in an index, (ii) inferences from the indices about diversity patterns, (iii) inter-dependence of indices based on their information value, (iv) overlap of the ecological phenomena that the indices aim to capture, and (v) incomparability of measures of different phenomena. Neglecting these issues has resulted in the invention or reinvention of indices without increasing their information value, although this value is crucial for correct interpretation of the indices. We offer a framework for pairwise diversity indices that accounts for these issues. We differentiate between statistical and information dependence of indices and show mathematical links between all indices, even those that have not yet been developed. Using linear algebra, we show (1) which set of indices carries complete information on assemblage arrangement, (2) how to calculate any index from two presence-absence indices, which can be used to standardize and compare different indices across the literature, and (3) what can be inferred about diversity phenomena from different informationally independent indices. It is impossible to purify an index of a single biodiversity phenomenon from the effects of other phenomena, because these phenomena inevitably constrain each other. Consequently, many recently proposed indices do not measure the phenomena that they were intended to measure. In contrast, a proper inference can be made by combining classical indices from different, information independent families.
SvAnna: efficient and accurate pathogenicity prediction for coding and regulatory structural variants in long-read genome sequencing
Authors: Danis Daniel , Jacobsen Julius O.B. , Balachandran Parithi , Zhu Qihui , Yilmaz Feyza , Reese Justin , Haimel Matthias , Lyon Gholson J. , Helbig Ingo , Mungall Christopher J , Beck Christine , Lee Charles , Smedley Damian , Robinson Peter N 
Published: July 2021

AbstractStructural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to limitations of existing technology. Recent technological advances such as long-read sequencing (LRS) enable more comprehensive detection of SVs, but approaches for clinical prioritization of candidate SVs are needed. Existing computational approaches do not specifically target LRS data, thereby missing a substantial proportion of candidate SVs, and do not provide a unified computational model for assessing all types of SVs. Structural Variant Annotation and Analysis (SvAnna) assesses all classes of SV and their intersection with transcripts and regulatory sequences in the context of topologically associating domains, relating predicted effects on gene function with clinical phenotype data. We show with a collection of 182 published case reports with pathogenic SVs that SvAnna places over 90% of pathogenic SVs in the top ten ranks. The interpretable prioritizations provided by SvAnna will facilitate the widespread adoption of LRS in diagnostic genomics.
PyLipID: A Python package for analysis of protein-lipid interactions from MD simulations
Authors: Song Wanling , Corey Robin A. , Ansell T. Bertie , Cassidy C. Keith , Horrell Michael R. , Duncan Anna L. , Stansfeld Phillip J. , Sansom Mark S.P. 
Published: July 2021

ABSTRACTLipids play important modulatory and structural roles for membrane proteins. Molecular dynamics simulations are frequently used to provide insights into the nature of these proteinlipid interactions. Systematic comparative analysis requires tools that provide algorithms for objective assessment of such interactions. We introduce PyLipID, a python package for the identification and characterization of specific lipid interactions and binding sites on membrane proteins from molecular dynamics simulations. PyLipID uses a community analysis approach for binding site detection, calculating lipid residence times for both the individual protein residues and the detected binding sites. To assist structural analysis, PyLipID produces representative bound lipid poses from simulation data, using a density-based scoring function. To estimate residue contacts robustly, PyLipID uses a dual-cutoff scheme to differentiate between lipid conformational rearrangements whilst bound from full dissociation events. In addition to the characterization of protein-lipid interactions, PyLipID is applicable to analysis of the interactions of membrane proteins with other ligands. By combining automated analysis, efficient algorithms, and open-source distribution, PyLipID facilitates the systematic analysis of lipid interactions from large simulation datasets of multiple species of membrane proteins.ToC Graphic
Poly(acrylamide-co-N,N’-methylene bisacrylamide) monoliths for high peak capacity hydrophilic interaction chromatography high-resolution mass spectrometry of intact proteins at low trifluoroacetic acid content
Authors: Passamonti Marta , de Roos Chiem , Schoenmakers Peter J. , Gargano Andrea F.G. 
Published: July 2021

ABSTRACTIn this study, we optimized a polymerization mixture to synthesize polyacrylamide-co-N,N’-methylene bisacrylamide monolithic stationary phases for hydrophilic-interaction chromatography (HILIC) of intact proteins. Thermal polymerization was performed, and the effects of varying the amount of crosslinker and the porogen composition on the separation performance of the resulting columns were studied.The homogeneity of the structure and the different porosities were examined through scanning electron microscopy. Further characterization of the monolithic structure revealed a permeable (Kf between 2.5 × 10−15 and 1.40 × 10−13 m2) and polar stationary phase suitable for HILIC. The HILIC separation performance of the different columns was assessed using gradient separation of a sample containing four intact proteins, with the best performing stationary phase exhibiting a peak capacity of 51 in a gradient of 25 min.Polyacrylamide-based materials were compared with a silica-based particulate amide phase (2.7 μm core-shell particles). The monolith has no residual silanol sites and, therefore, fewer sites for ion-exchange interactions with proteins. Thus, it required lower concentrations of ion-pair reagent in HILIC of intact proteins. When using 0.1% of trifluoroacetic acid (TFA) the peak capacities of the two columns were similar (31 and 36 for the monolithic and packed column, respectively). However, when decreasing the concentration of TFA to 0.005%, the monolithic column maintained its separation performance and selectivity (peak capacity 26), whereas the packed column showed greatly reduced performance (peak capacity 7), lower selectivity, and inability to elute all four reference proteins. Finally, using a mobile phase containing 0.1% formic acid and 0.005% TFA the HILIC separation on the monolithic column was successfully hyphenated with high-resolution mass spectrometry. Detection sensitivity for protein and glycoproteins was increased and the amount of adducts formed was decreased in comparison with separations performed at 0.1% TFA.
Phenotype switching of the mutation rate as a strategy for crossing fitness valleys
Authors: Lobinska Gabriela , Pilpel Yitzhak , Ram Yoav 
Published: July 2021

AbstractMutation rate plays an important role in adaptive evolution due to its effect on the rate of appearance of both beneficial and deleterious mutations and is therefore subject to second-order selection. The mutation rate varies between and within species and populations, increases under some stresses, and can be modified by mutator and anti-mutator alleles. It may also vary among genetically identical individuals: empirical evidence from bacteria suggests that the mutation rate can be affected by translation errors and expression noise in various proteins. Importantly, this non-genetic variation may be heritable via a transgenerational epigenetic mode of inheritance, giving rise to mutator phenotype switching that is independent from mutator alleles. Here we investigate mathematically how the rate of adaptive evolution on rugged, complex fitness landscapes is affected by the rate of mutation rate phenotype switching. Motivated by recent experimental results of mutation rate variation, we model an asexual population with two mutation rate phenotypes, non-mutator and mutator. An offspring may switch from its parental phenotype to the other phenotype. Thus, the mutation rate can be interpreted as a genetically inherited trait when the switching rate is low, as an epigenetically inherited trait when the switching rate is intermediate, or as a randomly determined trait when the switching rate is high. We find that intermediate switching rates maximize the rate of adaptation on rugged fitness landscapes. This is because an intermediate switching rate can maintain within the same individuals both a mutator phenotype and pre-existing mutations, a combination that facilitates the crossing of fitness valleys. Further, intermediate switching rates allow the population to quickly revert to a low mutation rate after adaptation is achieved, avoiding the accumulation of deleterious mutations linked to mutator alleles. Our results rationalize recently observed noise in the expression of proteins that affect the mutation rate and suggest that non-genetic inheritance of this phenotype may facilitate evolutionary adaptive processes.
Modeling Allelic Diversity of Multi-parent Mapping Populations Affects Detection of Quantitative Trait Loci
Authors: Odell Sarah G. , Hudson Asher I. , Praud Sébastien , Dubreuil Pierre , Tixier Marie-Helene , Ross-Ibarra Jeffrey , Runcie Daniel E. 
Published: July 2021

ABSTRACTThe search for quantitative trait loci (QTL) that explain complex traits such as yield and flowering time has been ongoing in all crops. Methods such as bi-parental QTL mapping and genome-wide association studies (GWAS) each have their own advantages and limitations. Multi-parent advanced generation intercross (MAGIC) populations contain more recombination events and genetic diversity than bi-parental mapping populations and reduce the confounding effect of population structure that is an issue in association mapping populations. Here we discuss the results of using a MAGIC population of doubled haploid (DH) maize lines created from 16 diverse founders to perform QTL mapping. We compare three models that assume bi-allelic, founder, and ancestral haplotype allelic states for QTL. The three methods have different power to detect QTL for a variety of agronomic traits. Although the founder approach finds the most QTL, there are also QTL unique to each method, suggesting that each model has advantages for traits with different genetic architectures. A closer look at a well-characterized flowering time QTL, qDTA8, which containsvgt1, suggests a potential epistatic interaction and highlights the strengths and weaknesses of each method. Overall, our results reinforce the importance of considering different approaches to analyzing genotypic datasets, and show the limitations of binary SNP data for identifying multi-allelic QTL.9
Comparing the appetitive learning performance of six European honeybee subspecies in a common apiary
Authors: Scheiner R , Lim K , Meixner MD , Gabel MS 
Published: July 2021

AbstractThe Western honeybee (Apis melliferaL.) is one of the most widespread insects with numerous subspecies in its native range. In how far adaptation to local habitats has affected the cognitive skills of the different subspecies is an intriguing question which we investigate in this study. Naturally mated queens of the following five subspecies from different parts of Europe were transferred to Southern Germany:A. m. iberiensisfrom Portugal,A. m. melliferafrom Belgium,A. m. macedonicafrom Greece,A.m. ligusticafrom Italy andA. m. ruttnerifrom Malta. We also included the local subspeciesA.m. carnicain our study. New colonies were built up in a common apiary where the respective queens were introduced. Worker offspring from the different subspecies was compared in classical olfactory learning performance using the proboscis extension response. Prior to conditioning we measured individual sucrose responsiveness to investigate whether possible differences in learning performances were due to a differential responsiveness to the sugar water reward. Most subspecies did not differ in their appetitive learning performance. However, foragers of the Iberian honeybee,A. m. iberiensis, performed significantly more poorly, despite having a similar sucrose responsiveness. We discuss possible causes for the low cognitive performance of the Iberian honeybees, which may have been shaped by adaptation to local habitat.Summary statementThis study is the first to compare the associative learning performance of six honeybee subspecies from different European regions in a common apiary.
Prolonged partner separation erodes nucleus accumbens transcriptional signatures of pair bonding in male prairie voles
Authors: Sadino Julie M. , Bradeen Xander G. , Kelly Conor J. , Brusman Liza E. , Walker Deena M. , Donaldson Zoe R. 
Published: July 2021

AbstractThe loss of a spouse is often cited as the most traumatic event in a person’s life. However, for most people, the severity of grief and its maladaptive effects subside over time via an understudied adaptive process. Like humans, socially monogamous prairie voles (Microtus ochrogaster) form opposite-sex pair bonds, and upon partner separation, show stress phenotypes that diminish over time. We test the hypothesis that extended partner separation diminishes pair bond-associated behaviors and causes pair bond transcriptional signatures to erode. Pairs were cohoused for 2 weeks and then either remained paired or were separated for 48hrs or 4wks before collecting fresh nucleus accumbens tissue for RNAseq. In a separate cohort, we assessed partner preference and selective aggression at these time points, finding that these behaviors persist despite prolonged separation in both same-sex and opposite-sex paired voles. Opposite-sex pair bonding led to changes in accumbal transcription that were stably maintained while animals remained paired but eroded following prolonged partner separation. Eroded genes are associated with gliogenesis and myelination, suggesting a previously undescribed role for glia in pair bonding and loss. Further, we pioneered neuron-specific translating ribosomal affinity purification in voles. Neuronally-enriched transcriptional changes revealed dopaminergic-, mitochondrial-, and steroid hormone signaling-associated gene clusters sensitive to acute pair bond disruption and loss adaptation. Our results suggest that partner separation erodes transcriptomic signatures of pair bonding despite core behavioral features of the bond remaining intact, revealing potential molecular processes priming a vole to be able to form a new bond.
Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling
Authors: Islam Mohammad Mazharul , Goertzen Andrea , Singh Pankaj K. , Saha Rajib 
Published: July 2021

AbstractPancreatic ductal adenocarcinoma (PDAC) is a major research focus due to its poor therapy response and dismal prognosis. PDAC cells adapt their metabolism efficiently to the environment to which they are exposed, often relying on diverse fuel sources depending on availability. Since traditional experimental techniques appear exhaustive in the search for a viable therapeutic strategy against PDAC, in this study, a highly curated and omics-informed genome-scale metabolic model of PDAC was reconstructed using patient-specific transcriptomic data. From the analysis of the model-predicted metabolic changes, several new metabolic functions were explored as potential therapeutic targets against PDAC in addition to the already known metabolic hallmarks of pancreatic cancer. Significant downregulation in the peroxisomal fatty acid beta oxidation pathway reactions, flux modulation in the carnitine shuttle system, and upregulation in the reactive oxygen species detoxification pathway reactions were observed. These unique metabolic traits of PDAC were then correlated with potential drug combinations that can be repurposed for targeting genes with poor prognosis in PDAC. Overall, these studies provide a better understanding of the metabolic vulnerabilities in PDAC and will lead to novel effective therapeutic strategies.Author summaryPancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, with late diagnosis, early metastasis, insufficient therapy response, and very low survival rates. Due to these challenges associated with the diagnosis and treatment of PDAC, it has been a research area of interest. With the goal of understanding the metabolic reprogramming in proliferating PDAC cells, we reconstructed healthy and PDAC models by incorporating patient transcriptomic data into a genome-scale global human metabolic model. Comparing the metabolic flux space for the reactions in the two context-specific models, we identified significantly divergent pathways in PDAC. These results allowed us to further investigate growth-limiting genes in PDAC and identify potential drug combinations that can be repositioned for treatment of PDAC.
Predicting stable binding modes from simulated dimers of the D76N mutant ofβ2-microglobulin
Authors: Oliveira Nuno F. B. , Rodrigues Filipe E. P. , Vitorino João N. M. , Loureiro Rui J. S. , Faísca Patrícia F. N. , Machuqueiro Miguel 
Published: July 2021

AbstractThe D76N mutant of theβ2m protein is a biologically motivated model system to study protein aggregation. There is strong experimental evidence, supported by molecular simulations, that D76N populates a highly dynamic conformation (which we originally named I2) that exposes aggregation-prone patches as a result of the detachment of the two terminal regions. Here, we use Molecular Dynamics simulations to study the stability of an ensemble of dimers of I2generated via protein-protein docking. MM-PBSA calculations indicate that within the ensemble of investigated dimers the major contribution to interface stabilization at physiological pH comes from hydrophobic interactions between apolar residues. Our structural analysis also reveals that the interfacial region associated with the most stable binding modes are particularly rich in residues pertaining to both the N- and C-terminus, as well residues from the BC- and DE-loops. On the other hand, the less stable interfaces are stabilized by intermolecular interactions involving residues from the CD- and EF-loops. By focusing on the most stable binding modes, we used a simple geometric rule to propagate the corresponding dimer interfaces. We found that, in the absence of any kind of structural rearrangement occurring at an early stage of the oligomerization pathway, some interfaces drive a self-limited growth process, while others can be propagated indefinitely allowing the formation of long, polymerized chains. In particular, the interfacial region of the most stable binding mode reported here falls in the class of self-limited growth.Graphical AbstractHighlightsThe D76N mutant of proteinβ2m populates an aggregation-prone monomer (I2) with unstructured terminal regionsMolecular Dynamics simulations and MM-PBSA calculations indicate that dimers of I2are stabilized by hydrophobic interactionsThe N- and C-terminal regions, together with the BC- and DE-loops are prevalent in the most stable dimer interfaces, while the CD- and EF-loop appear in the less stable onesThe most stable dimer interface has a limited potential to oligomerize in the absence of structural rearrangement
Ing4-deficiency enhances HSC quiescence and confers resistance to inflammatory stress
Authors: Thompson Zanshé , Anderson Georgina A. , Rodriguez Melanie , Gabriel Seth , Binder Vera , Taylor Alison M. , Kathrein Katie L. 
Published: July 2021

AbstractHematopoiesis is tightly regulated by a network of transcription factors and complexes that are required for the development and maintenance of hematopoietic stem cells (HSCs). We recently identified the tumor suppressor, Ing4, as a critical regulator of HSC homeostasis. Though the Ing4 mechanism of action remains poorly characterized, it has been shown to promote stem-like cell characteristics in malignant cells. This activity is, in part, due to Ing4 mediated regulation of several major signaling pathways, including NF-κB and c-Myc. In murine hematopoiesis, Ing4 deficiency induces G0 arrest in HSCs, while simultaneously promoting gene expression signatures associated with differentiation. This results in a poised state for Ing4-deficient HSCs. Long term HSCs are unable to overcome this block, but short-term HSCs convert the poised state into regenerative capacity during hematopoietic challenges, including irradiation and transplantation. Overall, our findings suggest that Ing4 plays a crucial role in the regulation of hematopoiesis. Our model provides key tools for further identification and characterization of pathways that control quiescence and differentiation in HSCs.